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          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.6/302.6 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m119.8/119.8 MB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m50.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install -q torch transformers accelerate bitsandbytes\n",
        "# ! pip install -qq -U flash_attn"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install -qq -U flash_attn"
      ],
      "metadata": {
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      },
      "execution_count": 3,
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          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.5/2.5 MB\u001b[0m \u001b[31m11.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.2/43.2 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m307.2/307.2 kB\u001b[0m \u001b[31m11.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for flash_attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
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      "source": [
        "from PIL import Image\n",
        "import requests\n",
        "from transformers import AutoModelForCausalLM\n",
        "from transformers import AutoProcessor\n",
        "\n",
        "model_id = \"microsoft/Phi-3-vision-128k-instruct\"\n",
        "\n",
        "model = AutoModelForCausalLM.from_pretrained(model_id, device_map=\"cuda\", trust_remote_code=True, torch_dtype=\"auto\")\n",
        "\n",
        "processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)\n",
        "\n",
        "messages = [\n",
        "    {\"role\": \"user\", \"content\": \"<|image_1|>\\nWhat is shown in this image?\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"The chart displays the percentage of respondents who agree with various statements about their preparedness for meetings. It shows five categories: 'Having clear and pre-defined goals for meetings', 'Knowing where to find the information I need for a meeting', 'Understanding my exact role and responsibilities when I'm invited', 'Having tools to manage admin tasks like note-taking or summarization', and 'Having more focus time to sufficiently prepare for meetings'. Each category has an associated bar indicating the level of agreement, measured on a scale from 0% to 100%.\"},\n",
        "    {\"role\": \"user\", \"content\": \"Provide insightful questions to spark discussion.\"}\n",
        "]\n",
        "\n",
        "url = \"https://assets-c4akfrf5b4d3f4b7.z01.azurefd.net/assets/2024/04/BMDataViz_661fb89f3845e.png\"\n",
        "image = Image.open(requests.get(url, stream=True).raw)"
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            "text/plain": [
              "image_embedding_phi3_v.py:   0%|          | 0.00/14.1k [00:00<?, ?B/s]"
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            "A new version of the following files was downloaded from https://huggingface.co/microsoft/Phi-3-vision-128k-instruct:\n",
            "- image_embedding_phi3_v.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
            "A new version of the following files was downloaded from https://huggingface.co/microsoft/Phi-3-vision-128k-instruct:\n",
            "- image_embedding_phi3_v.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
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          "data": {
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              "model.safetensors.index.json:   0%|          | 0.00/68.9k [00:00<?, ?B/s]"
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              "model-00001-of-00002.safetensors:   0%|          | 0.00/4.94G [00:00<?, ?B/s]"
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          "data": {
            "text/plain": [
              "model-00002-of-00002.safetensors:   0%|          | 0.00/3.35G [00:00<?, ?B/s]"
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          "data": {
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              "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "image_processing_phi3_v.py:   0%|          | 0.00/11.4k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e896001627c8450db716226b61c246e0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/microsoft/Phi-3-vision-128k-instruct:\n",
            "- image_processing_phi3_v.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
            "A new version of the following files was downloaded from https://huggingface.co/microsoft/Phi-3-vision-128k-instruct:\n",
            "- processing_phi3_v.py\n",
            "- image_processing_phi3_v.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/9.40k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f6fb4552bd8240c98828b958e96ed3ce"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/1.85M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bfdfbd1115cc4b7b897180d9f23d7f9b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/670 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f170e2eba9f146feb7d12bafad6bfffa"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "UVKPq1ytXWzF",
        "outputId": "350b8433-83de-457c-f767-539074e00b40"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x750>"
            ],
            "image/png": 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lOd9jmajyu8dN2p5Ef3+/Va49e/bg1VdfxcMPP5yYHkDZ+bsMDg5qi7GF7P9WQZ1ndXV1yd/b/Q18FAoFzMzMFK2zwcFBVFRUXNb1Si4/GCuCLCbY3slig22eLDbY5gm5YIS0wDJQsazOl3KEmIsh1iSVf77n5aYdHBws6np2vnW2WNza5nOe5dSpWuXwQh2TEEIIIYQQQgi5VFn0MbCIwBc8vFAooK2tDdls9g1bOZEQQgghhBBCCCHEhRZYBIAwbe3s7ER1dbWOxdXf349CoYDm5mZrtTxCCCGEEEIIIYSQNxIKWASACCpeVVWFvr4+Hb/rfe97H2688cbLJqA6IYQQQgghhBBC3ppQwCIAREyuhoYGugoSQgghhBBCCCHkkoMxsAghhBBCCCGEEELIJQ0FLEIIIYQQQgghhBBySUMBixBCCCGEEEIIIYRc0lDAWiQ8+eST2LNnz5tdDEIIIYQQQgghhJB5wyDui4TBwUFks9k3uxiEEEIIIYQQQggh84YWWOSC09PTg9bW1je7GIQQQgghhBBCCLlMoIBFLjh9fX3o7+9/s4tBCCGEEEIIIYSQy4RF40I4NjaGVCqFVCoV257NZpFKpVBTU5O4/8DAAAqFAqqqqpBOpxPTFQoFDAwMlMxvPsc2885msygUCti0aVPRtKq8NTU1sXMulm856VW5S9XFhToeIYQQQgghhBBCFjeXrYDV09ODtrY2tLS0oKOjA/39/Uin03jooYcAANlsFm1tbZalUDqdRktLiyXKdHV1obOzE4VCQW9raGjAjh07AAAdHR3o7OzEAw88gGeffRY9PT1F8wOEhVJnZ2fs2A0NDWhubrbS/vVf/zUaGhpQU1NjlSOdTuOee+5BdXW1lT6TyWDfvn1WeZuamhLryXd+TU1NVjlUXe7cuRNdXV1WuRsbG7Ft2zZ9Xrt377bKbuZXKBTQ2dmJrq4uqwwPPPBA7DwIIYQQQgghhBBCFJetgKXo6OhAKpXCzp07tUiTzWZ1jCYlMPX396OjowOtra1a5Orr60N7ezsaGxvR2NgIQFg2+YKhP/nkk6ipqUFLSwtSqRQGBgbQ3t6O1tZW3H///drKKJPJYO/evaiurtbHzmazWkhKpVL6WIqBgQH09/dj586duqxtbW3Ys2ePLqubt5m2o6MDMzMzqKioiNVNZ2enPr+ZmRlkMhldZ2452tvbUV9fjx07dmBmZgYdHR3o6upCRUUFmpubUVNTgx07dqC7uxv9/f1a5FPWZe3t7ejp6UFzczMaGhowMzODgYGBBf2uhBBCCCGEEEIIWTxc9gJWoVBAS0uLta2jowPZbBYPPfSQto5qaGhAOp1Ga2sr+vv7UVtbqy2NbrvtNp0uyWUunU5rSyQAqK6uRqFQ0KKNEoPa29u1ZZYStdLpNGpra9Ha2orOzk40NDRYbnWDg4Oxsg4MDKCrqwuDg4PaesmXd0NDA2pra/HVr37VErCy2aw+llvuvr4+dHV1xQSs2tpaK+327dvR39+v6ymVSqGhoQF9fX362CaqXk2LMFpeEUIIIYQQQgghpBSXfRB3V4QBgN7eXtTX18fEKCWmHDlyBAC0CGS6BSaxefPm2DYl4Cgro76+PmSzWTQ2NnrjPm3evBmFQgGZTMba7iursmoaGxvTx8hmszHxCxACmRtjS4lOvnLX1tYim83qvJPOMZVKaQuyckin0xgcHGSAd0IIIYQQQgghhMyLy94Cq6qqyvpcKBS0SKRiNLnMzMwAEAJUJpNBZ2cnenp60NDQgM2bN3utsNasWRPb5go84+PjAJAYsF0JaOr4Ctf1zzye6RZZLO+KigorzpUSp5Qr5UJx8y3Gxz72MezZswetra2ora3V9UkIIYQQQgghhBBSjMtewHJR4lBtbW2ieKIEqlQqhZaWFmQyGfT09KCzsxOHDx/G3XffXbbw4opRABIFn3KFoHKPUw7btm1LXAXwQq8OqOJ+qbhc+/btQ2dnpzfQPSGEEEIIIYQQQohi0QlY6XTaig9VDvX19aivr9fB35966qmYgHXq1KnYftlsFoVCQVtWKZEmyeWulIVWMdQxkvJ2BS5VBzU1NaitrZ338RaKWm2xoaEBXV1daG9vx7PPPouPfexjb1gZCCGEEEIIIYQQ8tbiso+B5aO6uhqDg4NesaeYFZQKtq7cEE26u7tj6Ts6OgAAN954oz5uKpVCV1eX9zhdXV36GPNFCXO+cmQymdhqf+oYvvTA+VmDKXGsVB4qFtjg4OCCj0UIIYQQQgghhJDLn0UpYH3sYx9DoVBAa2sruru7MTY2hrGxMXR1dWHv3r06XUdHB7q6ujAwMICxsTH09fWhv78fNTU1Mfe6np4edHR06LRq9UG1CiAghJ1t27Yhm81i165d6Ovr0/nu3bsXAwMD1gp98yGVSqGpqQmDg4PYu3evzltZOfmCwG/evBk9PT1oa2uzzrGtrQ1dXV0LKgcQWZp1dXVhbGxMC1Sqvs06KhQKZVvCEUIIIYQQQgghZHGy6FwIAWEJtXPnTrS3t2Pfvn16uxKBzM/t7e3WvrW1tdixY0csz507d6KtrQ2dnZ16W2NjY0yQUmJNR0cHdu/erben02ns3LkT9fX1Cz6vxsZGzMzMoKOjQ69kmE6ncc899+DJJ5+MWZxt374dFRUV6OrqslZarK2txe23377gcij3wM7OTnR2dqKpqQnV1dWYmZmJ1fe2bdsYyJ0QQgghhBBCCCFFCcIwDN/sQryZDA4OolAoIJ1OewOJFwoFDA4OIpVKYc2aNTHLq46ODnR2duLBBx9EVVWVtjbypZ3vsReKWWYVG6vc9OWUu1xUXZhlyGazyGazF/xYhJDLh76+PmzatOnNLgYhbwhs72SxwTZPFhts84RcMMJFaYFlUkrgSaVS84pJVY5gtJC082G+ZZ5v+nLxnd+FFusIIYQQQgghhBBy+bMoY2ARQgghhBBCCCGEkLcOFLAIIYQQQgghhBBCyCUNBazzpKamBg0NDYzlRAghhBBCCCGEEHKRWPQxsM6X+vr681o5kBBCCCGEEEIIIYQUhxZYhBBCCCGEEEIIIeSShgIWIYQQQgghhBBCCLmkoYBFCCGEEEIIIYQQQi5pKGB5aGtrQ0dHx5tdDEIIIYQQQgghhBACClhe+vv7kc1m3+xiEEIIIYQQQgghhBBQwCKEEEIIIYQQQgghlzgUsAghhBBCCCGEEELIJc2Vb3YBLnUKhQKy2SwKhQI2bdpUNO3Y2Jh2PSyVttSxampqkEqliqYdGBhAKpVCTU1NWfmPjY0hlUrF8lXlrqqqQjqdLqt8Czk/QgghhBBCCCGEkIVwWQpY7e3t6OrqwsMPP2yJNV1dXWhvb0dLSwtqa2v19o6ODnR2duKhhx6yBJzu7m489dRTKBQKAIB0Oo0dO3ZY+wLA4OAgnnzySfT39+ttqVQKt912G5qbm0uWt1AoYN++fejv79fHAoDGxkZs27bNSpvNZtHW1mYdK51Oo7m5GW1tbdi+fTs2b95sndcDDzygy1dbW4uWlpbEvGpra7Fjx46YkNXR0YHDhw9bddHY2IjGxsaS50cIIYQQQgghhBByPlyWAlZ9fT26urrQ39+P+vp6vT2TySCVSuHIkSOWCKWEHVO0yWaz6OzsxM6dO5FOp9Hf34/29nbs3bsXDz74oBbGstksWltbUVFRgZaWFqTTaczMzODZZ59FZ2cnZmZmYiKUy8zMDAYGBtDU1IT6+nrMzMygu7sbXV1dqK6u1oIUALS2tmJmZgbNzc1oaGjQx2pvb0/M/8knn0Q6ncbOnTut82ttbQUAXW51jm1tbVrkAiJBUAlWMzMz6OjoQHt7O2pqamKCHiGEEEIIIYQQQsiF5LKMgVVdXY1UKoW+vj69LZvNor+/H9XV1ejt7dXbC4VCTOgChKilLLXS6TQaGhpw2223oVAoYHBwUKfbu3evFq9U2urqauzYsUMLaWNjY0XLW1FRgfvvvx+NjY16/6amJqRSKausPT09yGazaGpqQlNTk3Ws6urqxPyV5Vh9fb0+z46ODszMzMTOsampCf39/doqK5vNoqurC83Nzdi2bZs+5vbt25FKpdDR0VHy9yCEEEIIIYQQQgg5Hy5LASuVSsWEqv7+fu1qp+I4qe1APGaVa5EFQMeaUoJUNpvFwMCANy0A7V5nliOpvKaroxlLy3Qp7O7uRiqV8rrtFXPlc8U5QIhhdXV1sXKrtAMDAwCE2yUANDQ0xMpcV1dniXmEEEIIIYQQQgghF4PL0oUQEEJMe3s7xsbGUFVVpd0GlXVWJpPB5s2bkclktFWRiU+QqqiosD4rISvJhU7lYYpQSXR1dSGTyWBwcDAxfTabTbS0cstmUlVVFcsHECJWT0+Pdx9VBnWOX/3qV4ufACGEEEIIIYQQQshF4rIVsBoaGtDe3o7e3l40NDSgt7cXLS0t2jqrv78fmzdvxuDg4Jsew0nFmGpoaEBjYyNqampQUVGBXbt2XZD8r776au9206XQxV3ZcMeOHRekLIQQQgghhBBCCCHz5bIVsFKpFGpra7WFlfoMCOGms7NTuwCWCrKehLJsUu52Lsp6yWfNpSgUClq8ckWimZmZ2Dkp6ymX+bjyKWutioqKmGugizrHuro6y82REEIIIYQQQggh5I3isoyBpaitrcXg4CAymQzq6ur09vr6ehQKBTz77LOWsDVf0uk0amtr8cILL3iFJeWe58bXMlEilesCaMbpMs9HBaN3UbGqykGdc29vr7fc5nGVhVZnZ6c3r3LcIwkhhBBCCCGEEELOh8tawNq0aRMKhQJ6e3stV7l0Oo10Oo0XXnjhvN0Hm5ubUSgU0NraiiNHjmBsbAwDAwNob29HT08Pmpubi1pgKeuwF154AZlMBmNjY+jr68PevXtjFk+NjY1IpVLYu3cvuru7ddrW1taixyi33GNjY+jo6MDu3bt1utraWtTW1qKrqwtPPvkkBgYGrONmMpl5HZcQQgghhBBCCCFkvly2LoSAEF9SqRQKhUJMqKqvr0dXV5dlmbXQY7S0tKCtrQ0/+clP9PZUKoVt27YVXR1Q0dLSgj179mDv3r163+3bt6O9vd1Kl06nddp9+/bp7Y2Njairq8Pu3bvLdvOrra3Fzp070d7eHit3U1OTlValO3z4MA4fPmzlUcy6jBBCCCGEEEIIIeRCEIRhGL7ZhbhcUCsIKguv+dLf349UKoU1a9aUFKJUzCuVNpPJYO/evWhpaZm3VVm55S4UChgcHCy7jIQQshD6+voojpNFA9s7WWywzZPFBts8IReM8LK2wHqjqa6uPq/95yM8ucdSrnwLKUO5+5xPvDBCCCGEEEIIIYSQhXJZx8C63BgYGEBfX19se1dXF3p6etDQ0ECrKEIIIYQQQgghhFx20ALrLUShUMDu3buRTqdRU1ODiooK9Pf3I5vNora2Ftu2bXuzi0gIIYQQQgghhBBywaGA9RZi06ZN2LlzJ/r6+jA+Po6ZmRnU1dXhxhtvpGsfIYQQQgghhBBCLlsoYL3FqK+vR319/ZtdDEIuK8bGxpDNZpFKpVBTU5OYrlAoIJvNAkDRdIQQQgghhBBCLiwUsAghlwWtra3o7+8vme6nP/2pfp/JZNDe3q5FKQBIp9NoaWmJrcjZ1dWFzs5OFAqFxHTZbBatra3IZrPYtm0bGhsbz/e0CCGEEEIIIYSAQdwJIYuUnp4e7N271xKvACFC7dq1y9re09OD9vZ2AMBtt92GdDqNbDaLtrY2a9+Ojg5ks1mk02mKV4QQQgghhBByAaEFFiHksmDz5s3eWHDZbBY9PT0AgIaGBr29o6NDv29sbMTmzZuRyWTQ0dGBQqGAtrY2tLS0AACOHDkCAGhqakJjYyOam5vx+c9/3rL46unp0cdR+xFCCCGEEEIIuTBQwCKEXBaY4pTJV7/6Vf2+ubkZANDX16ctrMwVPKurq9Hd3Y1sNov+/n4UCgWkUinMzMwAiOJepVIpnadyKVSCWHNzc8z9kBBCCCGEEELI+UEXQkLIZUtPT48WqhoaGrSwND4+rtO4YpNpxaUsrCoqKgAI4QuAzjOVSiGVSqGzs1O7DjY1NV2ksyGEEEIIIYSQxQstsAghly2mm6CyvnJxY2CZboHKuurGG29Eb28vDh8+jMHBQQwMDAAQrofZbBZdXV0A6DpICCGEEEIIIRcLCliEkMuSJOsrAKirq9Pv+/v70dbWhrq6Orz66quWoGXun81m0d3djUwmg1QqhebmZjQ1NWkXRdN1cGxsDFVVVRf9HAkhhBBCCCFksUABixByWVLM+koJUCqNGYBdrTCo3iuamprQ1NSkXQXVMUzXwY6ODhw+fFjHzrrtttsSLb8IeSswNjaGbDaLmpoaK/YbIYQQQgghbzQUsAghlx2ZTMYK0u4Lqt7U1IR0Oq1FqFQqhaamJgwMDGgxy2dFpfLKZrPo7OwEIFwHOzo60NnZiXQ6jdraWvT39+vPmzdvvlinShYpfX192L17d8l0TU1NaG5uRmtrq+Uem8RPf/pTAKJ9t7W1WfuovEzMdn///fdT5CKEEEIIIRcNCliEkMuOTCaj3yetTqi+c7/ftWuXfl9dXZ24b2trKwARByudTmvR65577kF1dbWe2Pf29lLAIm85Wltbkc1mtQDc09ODzs5ObNq0SS90YIq4TU1NFK8IIYQQQshFhQIWIeSyo7e3V7/ftGlT2ftlMhkdoL22tjZxQu66DhYKBW3xpUQvNclXgeAJuZBUVVUlrnhpxn9T4unmzZutFTYV2WxWi69KzB0YGNBWiWphglQqha6uLvT19el8lIjb0NBAkZYQQgghhFx0KGARQi4r+vr6tGiUTqe97oMA0NXVhTVr1qCqqgoVFRXo6enB4cOH9feNjY3e/Uyrkx07dsRELhX/anx8HABolUIuCul02htfLWnxgiRLRLUIARDFilP9x7RArKiosL7r6urSIi7jvJG3Cuphg7pO19TUJKYB4P2ekLcSKo4hgMRYhox1SAh5K0EBixByWWFaXxWbfAwMDKC9vd37XXNzM+rr673fmVYnpkWLinu1a9cu1NXV4YUXXgBgr3hIyMWm2OIFLklil5rADA4O6om+SldVVRVzHUwSiQm50JQTyy0IAvzkJz+xtmWzWXR0dKC3t9eyim1oaMCOHTv0566uLnR2dloPQVpaWqw2PjY2ht27dyObzWLbtm2JDzsIOV/mG+vQpKenB11dXdqqXPHggw/q+J6MdUgIeStyxZtdAEIIuZCYg7ViMax8AdpTqRS2bduW6JpVzOpkx44dqKurQzab1ZZc27Zto2sVecNIEqSSSBK7ampqkE6nUSgUsHv3buzduxc9PT1Ip9Oor69HR0cHCoUCXQfJW4KxsTG0traip6enqEt3T0+Pfqhx22236RVp29rarHSdnZ3IZrOoqqqieEUuSTo6OtDW1hYTr1yUIFxbW6utdDs7Oy1Bi7EOCSGXGrTAIoRcVqiYPaVoamrCbbfdhsHBQQDF3Q0VjY2NiROWdDqNe+65B4VCAePj41izZg0HeuQN5UJYXylaWlr0k/mBgQHU1tbiYx/7GPr7+7WY5bocsr2Ti005sdze97736e1hGGprKQCor6/XC28oV0LFkSNHAIh7Q2NjI5qamnDffffh1Vdf1Wl6enr0ce67774Lf4KEGMw31qHargQntbpyfX09ZmZmMDAwoK/TjHVICHmrQgGLELJoSaVS3snQ+ebJiTx5o7lQ1lcK5TplilPKDQsQk/yZmRnLpau6uhr33HMPXQrJRcMXyy0MQ3zta1/Tn832/MILL1j9wnQXdNvpzMwMgMj13LyOFwoFhGGo239zczPbObnozDfWodlGAeD++++32qlplc5Yh4SQtyp0ISSEEELe4nR1den3pZ6SZzIZPfmpra0tOhE3BVm1+mZDQwM2bdqEPXv2oL+/H/X19aipqcHg4KB+Wk/IG4UrUpntubu7W7+//fbbi+ajJu99fX0AoPNUfeC///f/rl0Hk6xiCLnYuCKVKSz19/db1oalru1AFOsQAGMdEkLeEtACixBCCHkLk81mdayTdDpd0qowk8no90mrE7oo16lUKoXm5mY9Uaqvr8fOnTtRKBTwta99DdlsFoODg0XjzxFyoSg2mQ/DUFsHplIp5PN5bTGYSqVQV1dnWVLdeOON6O3txeHDhzE4OKj71G233YaxsTEtEtN1kLyZFBNszdhV1dXV6OjowOHDh1EoFFBdXY3Gxkb9gEPFOsxms9i9ezfS6TQymQxjHZJFAVfefGtDAYsQQgh5C2MKUuW4xJordW7atKlketd1MJ1O68m9EqpSqRSqq6vR399fNFA2IReSYpN5tV1hruZWKBTQ09ODV199FQ8++KDeP5vNoru7G5lMRou1H/7wh7WLoil4jY2NeRcDIeRiUUywBew2r4QrxeDgIPbt2wcgstJlrENyqbGQlTfb29stK3STdDqNhx56SH/mypuXBxSwCCGEkLcw8xGw+vr69ESknIULgMh1sLa2Vi9i4MZKAWyXK0IuNvOZzCsLlObmZszMzKC9vR2FQgFjY2Po7u7WE/qmpiY0NTXpuD9A1P6V66Bp1ZJKpXDbbbcxPhB5Qygm2ALxNt/c3Iza2lp0dXXp+0RnZ6du74x1SC4H5vPQrLW1VY9n0um0XvRg06ZNevzElTcvfShgEfIGocxVq6qqSt74y0lbKBT0YEUFnSWELC4KhYL1JPFtb3tb0fSm9VU51w1z1TUzAPamTZvQ2dmJw4cPY2ZmBtlsVk/66T5I3gh6e3uLxnJzP5uT7rGxMT1B6e/vj7lI+dLdd9991lP52tpa9Pf36890syIXm1KxDs0239DQoGO1mdax2Ww2Zj1oTtDdWIdqwl9fX6/d1VtbWy2rFkIuFAtZeVNtS6fTsbAIZtvmypuXDxSwCLnI+MxVa2trsWPHDu/TMzdtQ0MDtm3bZl2Eu7q60NnZiYqKCmSzWVRXV6OlpSX2lOCrX/2qPhYh5PJDufIpSolHZvpSaQuFQuKqa7W1tdi2bRu6urq0wMVrDXkjKRXLTVkJAkAQBFb7Lcf1LwxD7crS2NiINWvW6LZ+zz336BhDnZ2d6O3t5USHXFTGxsb09buqqsprbWuOAc32nkqlUFFRUdJShbEOyZvNfFfeLGdfBVfevHyggEXIRaa1tRUzMzNoaWlBOp1Gf38/2tvb0draavlVZ7NZrforMSqTyaCjowMzMzPYuXOnTtfe3o5t27ahsbFR79fV1WVdbNWTOl6ACbl82bRpE37605+WnV49dSyHVCpV9Cl7Y2MjGhsbMTg4iIqKCrqUkDeMMAxLxnJLpVI6SHUYhtaE25zIm0KXSWdnp57INDU1aeuVIAh0PkpEYNw3crEx2/v111/vTWNa1Q4ODlrfzczM6Pc+lyjGOiSXMuW4i5dy9XNX3lQuswBX3nyrQQGLkIuIWq5++/bteqDb0NCAQqGA9vZ2ZDIZ/dRWmW0/9NBD+qJZXV2NsbEx9PT0oL+/H7W1teju7kZNTY2ORZNOp9HY2GgJWNlsFl1dXbwAE0IuOnwKT95ozAl0kqt9EARoaGjQE5LHHnsMO3bsQKFQsFyxbr/99ti+puvgjh07kEqlEIah/l5NfsbHxwEw7hu5+JQT6/CGG25AKpVCoVBAJpNBV1cX6urqrIDuDQ0N3vbKWIfkUqUc6ysA2r0VEOOS22+/3UrLlTcvHyhgEXIRURdcNy6Nb/ChBCr3wrx582b09PToFWKy2WzsibE7kOjo6EBtbS0vwIQQQi47TGuUYgLqbbfdpic/g4OD2LVrl/V9Y2Nj7J5rug42NDTo+3UQBDru1a5du1BXV4cXXngBAFBXV3dBzosQH/l8vqxYh5WVlWhqakJ7ezsAsTqbeg9Auwa6MNYhuZQpZn0FRHMt1T4BMac6fPiw9lZRcOXNywMKWIRcRJQ595EjR6ybvRqIqEGIck3wxfFQg2dlyl1TU2MNZACxspgahPf09KC3txf333//BT4bQggh5M2n3FhulZWVaGlpQUdHh56gA2JC0tTUZE1sFIcPH06MgbJjxw48+eST6O3txeHDh5FKpbBt2zY+LCIXFdMd0HRh9dHY2IhUKqUtqhRJsVcZ65BcypRjfWU+/M9ms9Ycqb293bI65MqblwcUsAi5iNTW1qK5uRldXV1W7IDDhw+jublZD0LUYDzp4qhMXgGgvr4enZ2d6OjoQENDA7LZLHp7e3H33Xfri7DvqTIhhBByOTCfWG7pdBo7duzAtm3bMDg4iFQqhTVr1iQ+VVex3ZLyuueee1AoFDA+Pl40H0IuFPONddjQ0ICGhgYd6yedTieOCRnrkFzKlFp5E4jfD7LZLHbt2qVFqp6entg1nStvvrWhgEXIRea2225Dd3e3ZcbtW+q1XNLpNLZv34729nZ0dnbqJ8mbN29GW1sbACQuQUsIIYQsRlKpVGLsoIXkReGKXOpcSDc/ugySNxolHgFi7lPu9TudTqOurk5bDRZbcIArb741oYBFyEXEXVlQWVK1tbWhtbVVb5sv9fX1qK+vt7YNDAygp6cHDz30EAqFAvbu3aufviWZjhNCCCGEEELIpUQ5CxckYbrPJs19uPLmWxcKWIRcRHwrCyr/6127dqGtrW1erhDF2Lt3r45f0NbWhkKhoPNua2ub17H6+vouSJkIWShsg2QxwfZOFhts82SxwTY/P8y4hStXrvTW38DAAH7/+9/j3e9+N1atWoVTp07h5ZdftuJgLV261LvvgQMHkM1mUV1djerqavT19WmR6v/5f/4fvc/w8DAAYHR01FqNdrGwadOmN7sIMShgEXIR6enp8a4smE6ncf311+PVV18FIJYBB+wnBibZbLboKkfmE4RsNouenh488MAD+gnC9u3bsWvXLoyNjeljFeNSvFiRxUNfXx/bIFk0sL2TxQbbPFlssM3Pj0KhYC3WcfPNNye67z311FN4+eWXvd81Nzfjpptuim3v6enR+5gB2oMgQE9PD44cOYKrr74a2WwWU1NTSKfTuPXWW8/3tMgFggIWIReZmZmZxO1K6U+n00ilUrHVBQF79UEf2WwWnZ2d2rpqbGwMALBmzRqdRu07Pj5eloBFCCGEEEIIIW80pngFJMdgS6VS1kJXZvrm5uZYuBWAK29eDlDAIuQiUltbi8HBQb0kt0It82qKUg0NDejq6oqlVStwJD25aW1tRUNDg/YPV4FlC4WCfq9uBAw6SwghhBBCCLlUKXflzZqaGjz00EM65i+AoqtuAlx583Lgije7AIRczjQ3N6NQKKC1tRXd3d3o6+tDd3e3DuxurhbY2NiIVCqF1tZW9PX1YWxsDO3t7ejp6Yk9IVAocau5uVlvq6mpQTqdxuHDh6106XSaq2cQQgghhBBCLhuqq6tRW1vrDdtyPnlSvLo0CcLFGI2MkDeQTCaD9vZ2y7y1uroaH/vYx2KragwODmLPnj06bSqVQlNTExobG2P5qhUOm5qasHnzZm8+yn2xoqJiwSse+pgOT2Map61t53JnMDd9Fkuvqywrj7NDeSxZsRRXLL+qZNpzuTNACFyxonRalfe8yrF8aVl5n5s+g7nc/M6x3LTnps8AKO8cF1TXxjn+h2BlWfu9WTBWBFlMsL2TxQbbPFlssM0TcsEIKWAR8gahzFtLmbYCQH9/P1KpFNasWZPo9lcoFDAzM1M0r4tl/rrndA/2nH7B2pZ9qAdXrLgKq//mz0ruP/OrQYz/+CWs+7s7cOX64iLMudwZDP/nf8Gq/3wDKu98R8m8Jx87ijPHJnDtgx8omXZ2KIeh/++/4Lp/+HDJcgDA8H/+F1S8vwarPvWnJdNOP/UHTD31B/zH9r8oqxyjn30WVQ99AFdtXF0y/fnW9f9v5edL7vdmwoEeWUywvZPFBts8WWywzRNywQgZA4uQN4j5uO+5llk+UqlUyZhWb5TL4NRTf8CpzIgUawIAPl1cbJ8dymHixy/h2oc+UJZoNPF3v0XF+2vKEq9mfjWI3NOvYd3f3VEy7bnpMxj97LNY8zfvKasck48dxZLrKssSr2aHcjj52FFc9w8fLpkWAMa+9u+ovGtDWeKVXdelyzGfuiaEEEIIIYSQSxXGwCKELIBAa1SzQ3lMPnYU6/72DrEtDOVf44VAb7fEGjedo3spsWb1Z6SlkZvO+Ds7lI/EmnWVURkTXhM/LiKMOWmVMLb6M+/xltPcLy6MBf6yS7QwtuNPY+fknmesrmF/76LresPq6HcghBBCCCGEkLcgFLAIIQsjUK5vz8StmALYWkkYAoEj1hQRgZQgpcUatd1NZ/wd+9ovI7FGHdMpryJRGPMcZ3ZYCmMPfgBXmjGntDBn728JY0rQMw8eRILWzL8bwphpuOYRp85Nn43XtTpuAKccQVwYc+uNEEIIIYQQQt5CUMAihCyMEJh87HeovGsDKu/a4HzpKlhA/l9eQ+6AFGuKEQSYHc77hbEEIve+G3QeWiiS5VB61uxwHpNthjDmnJOLEsaWKouxxPSBIYy9x9puiWnSEm12OI+JR6Qwtr6yiLAkyj/x45eKW4wZzPz7QCSMmUkY8pAQQgghhBDyFoUCFiFkQUw+dhSnMiPSmsoURoRgE2rLo8ASja5cv1yndA2NlMgy+dhRIYzFxJogZiyVf9oQxlQ5lBujcZQgJowtj5XB/WxaMfmd76LUs8PTCcJYaIhp6jSCyGJs42p9Xr4yAB6LMac0pvGVLYxFdR1oUZFuhIQQQgghhJC3HhSwCCHzZnYoh9yB16RYExdGhHQVIJRSzOhnn0HlXRuwZH0lQr01kGmAUL4PEGDysd9JYewGb95qTyDAXEwYE9tFnqG9f4iYMBbCFXaiMuUPRMKYKq+Zv/lXCGPPWsKYKUqZYl4IKYytr8TKHX+KMCYoBbpsIu8cpn/2B6euAbss0dbIYmyNUdeqPooF8CKEEEIIIYSQSxcKWISQeZM/8Bqu+dQNWGJYMSkhKhKFIAWpo1hWvw6rdtxgyFSmxVEk4MwO55A7cFxbMdkhoey8ASGMpe7aYFkaqeOa6UIAk21HtTAWWiKQeQzxd244ir915frlVl5qP7MskTC2wcpHnKd9voWnX0Pu6eNY/TfvsY4PmdYU1WaHRYyxaz51A65cv9xrsRada4Cpx36HpdevxsodNxi/gCm80QKLEEIIIYQQ8taEAhYhZN6s2nEDUls32FKIodwoT77808eRO3Acqz5VF3n3wYg7LrcFiALCr9ohhLFQJgyNPM0450oYu2bHDTHbIlfomRvOIff0caz70RbLy1Dn7+w0+tlnUXnnBl0OM9/QOFAYRq6UK7ffEM/bSBvAjL+1BUvWL9f1p85Rf5bvJx/7HVJ3SmHMLS/s+tB1rcWrKK/QqCDaXxFCCCGEEELeilz5ZheAEPLWI4QI6xRb6M8QSGaHIrFGBWKPpZcKjLKQUmKNKcyo90rwCgDkDgixxhSkrLIZ+88N5zD6OSGMXbm+UotF5g7qfABg6rGjWFa/Fit33GCJT75gWXPDeeQOHMfaH92hz8cXJz2UYbBGP3sIqTs3YMm6SktMCpSXo7GvEMaG8R/+74/YeTqCGhAJY2t/dAeuXLc8XgluBZF5891T/4bDZ487q2vKv3Lb2WMTmPg7EX8sWH5V/DcwFcsAGP7PT2PVp/4TKm6t8f9eRvqptt/hzKvjqHroA/HO4ewzN5THyGefxXX/cJcoh3FM/dfYNv5fe7Csfp1wrU06P/m+cEBYEF770AcQVF4VL6uR79xQHie+9u/iHN9fY5fT9X0FMPUPvwMQYqVejCGhTmTfy/7Xbruu3fOU6f9jsBKPVd4NQgghhBDy1oYCFiFk3iQ5oZlzzdHPHRJWTOsq48KVSiuFnanHjuLMsQms/8pmkY+R3rTcAoRYMyXFmiXrKxEEgYwx5S/HZNtRVEphDIEtspnz3DAE8lIYW/ujLbETM8WmMBTujie0MLbcsigz81bphcXYemEhJTfGLNGMvIVAd4edF+LzeVXXqTs32G6Ghvhm7lM48Brwv3oyIUWZDk/jj+FUoig4O5TD6Feexeq/eQ9mK08B4Smv6KmY+Lvf4tyGK3DullWYKJIvAJw5NoET//0I1v3dHfjjuSlvfua2P/7NP2PF3X8CpE4B507F05tC6T8cRaFvENd9+d2YLFGO2eE8hv/2MNb/w4cxlJLnmFSWEDjxt7/EVbesEedoltuTd/7p13DyX47iun/4MHLhVNHzE9aaqq5Px+vaeT/z/CBwl//whBBCCCHkrQNdCAkhC8JnTaWErZOPvIRl9euFFZP63tzXeH/m1XHkDhxH1a4PlnVcU6wR5bALYh5nqk0IY6ocyh0wFtEqEPGmTj7yEtb96A5tMaZiXFlHCKNzVBZjsTTW50BYrRw4jpU7/lSX2Ts3d4SxJc5KiT5jlKm2yJXSh7nP3HAOJ9t6velIKWSrMdxCNSEw8ePfovKuDah4f3VCY4haXf7p11D41YBYObNYTDIp1ox99ZdigYB1lYnpVD4TP/4tlt24TghYSY1S/j376gRyT7+Gax/6gD+dw+j/8QxWfapO9I8kwUgy+djvMDucx6pP/WlymZUwNpTDxI9fwrq/vQNXVC71pzfQdX1rtd/k0SD/9GuYfOxoyTwJIYQQQsilDy2wCCEXBB336sBrKDw3gPV//2H7e8StgeaG8xi7/5dY85mbtGhUjIlHXtIB4RPLIY9z+ti4djMETJkgWh0xsr4KpWhUp0Uj8b0K927vM9V2FLPDea/o5lpLzQ7lMPHIS1j393+OpetXwJWu3Om3K4yJPIPYfkDkSrn2R3eU9AycG85j9HPPYtWOuhIpSSIJos3kY6I9XPvQB+Mmg0DkgxoKK6aJH7+E9f/tw7hi+VLEgrup9PJzTBgzzfqssoVaGLvuv33Yr3oajXN2KI8TX5PCmBKkzHyd7LUw9tFN/ryN92eOjYuYc397R+J5mfuNfvZZrPrUDdE1oEhj1nX9oCG6JbgZqrp+x2P/7+QMSSKHZ49hKjzt/a7wq0Esu341lniv2/YPffbVCZzLncGyG9ejuC0pEE6fQeG5QaTeXx25v3rzFn8LvxrE0vWVWHr96oR8o/RzQzmcOTYh+lIZ5J9+TZZjWWJ5FaeOjCJAaJxjMnPDeZw6MoLKu94B2/fVT+FXg1h6XSWWblztnJP7Pqrrd/wvtbjpyvLOk0Qcnj2OKW1Zare1qD2Y7dLflqP2sM5zFPs3nxvK41RGtYfkPM02n9z3bM4em8C56TMJ5bCPVbrv2dh9z5+nYm4ob/S95P6v8Ne1mXeUh6rrd/xZLW5awjZPyGKAAhYhZEEExkBCiStzw3mcfORFrPv7D2PJ8mUlxZoJKdZcfWvpQUfhwGuYeW4A1/19k1UGdQzz/exwHtn7f4nVn7lJD/KiY4ex/SekxdiKj/6J12jFtJE5e2zCinvl4s7tVfwtn3jlooSxa3d9yEkb30/U9UtY9/cfjq3C6EPU9TtEnCNywTiVGUXuwGtSrEn4feXmc7mzYqGCT92AK69bnigWqcH5ZJsh1ljNIX6c2eE8Jh4xhLGkckiRauLHLxlWTEa+HnEs/7QQpa/7b4YordI56WeH8xj72r9HwpinHkwmfvxbLKtfhxUf/RN/mQ3OHJuI6tosg/hgHEC8V3VdzkSPxHn89BG8ODcY2z711B8w/bM/4Lr/9mFcMWO0NU/bmR3KYfS+Z5H+Lw1YNpM0iY6Y2PtbAMDqD/4ZMFM87an/MYLsD3rEarEzxX/jc9NnMfy//3esuPtPsOI9pduaWpxj3QfvKFmO2T/mMPqNZ7G2jHIgBEYeeBZX37gOq2YSrBMNEuvaW448Ru97Bqv/5j34wJksbrqScd/mQwjguzP/JlzFHS5qe/jGs7i63mgPScE0Mc/2MJTD6OcvUt87MoLs93uw7u+Mc0wo97ncGQz/7/8yv753pMy6Hsph9OvPYu3f3YGPnjmLmyooYBGyGKALISFkQYRSYhFWSkLiGf3cIazaUWfFYgoM+cd8L8SanGVNFcj/XOaG85h45EWs/dEdCIzJeWgcxRSyJh55EZV3ysm5QeD8FyJEXgpjqz/znkR5SbkpKoux1Z+5yRKNzDyNwklXyrVY/lelB21KGKva9UFPTC9lBxb9HZUWY0vXryiSqyiTXddFXNbIvJgdzmP8v3aj6r80lGVBOPnYUVS8vwYrPvpOOdCP/xYhAIQhTh0ZEe59pqWRmcYgEsbqbDEziFxg9T5hqK2YVu3wTKCtthdoYWzd395hC2PWkpvRcSJhrEbnYUrGZt7KWnP137zH+N7fPoUw9kusNoWxJPEqDA2LsdJ9jyQR/y1m/5hH7md/iLcHwGMVCGT/6wuovGtDEQuQiKmn/oDCcwNY9SnTwjahPfwxh/Hv9qDqK2X2vTbZ9+4u1h7EsU79jxHkDryG9H/ZXDLfc1NnMfq5Z7Hio39SdjkQhMmutQazf8wl17VLCGS/25PsxkwWzMyvBi9ue4DTHhLEq3m3h/n2vV+5fc/P7FAe4/+1J37fSyj35GO/K6PvCdR9L/1VVdfJ45Vz02cw+tlnseLu8uqaEHL5QAGLEDJvQjUjDgGEAcJQuvfVrRdiTSifxIUqbWCZJum4V9/5oBBl5PdhKMWiUIo1ct/Rzx3Cqu11uHLdciN9tB+MY0y29WJ2OI+V2+uAMLDyCcNQHyMMhVn7yUdexNqHt4gV1WL5muUOtMVYxS3VVrrQKLsqn56c33uTUXNmvtFLCGP/htX33iRWEZTpzLoJIIPVhwHGH3kRy+qEMGbVr5mvzOO0UdciDWc2CyUSgoQok/2vYsK4rF5NEAJEgk1gpdeT8x03aPEXTn5KcJwdzmP8uz1I/5cGKUjJ74MACJT4Gh1PCWPLP7rJLmtoOsGKfU4dERZj1z74AU85TQKcy50xhLFK6/xcUSpEgClDGIvOMW6FGULEelNxr5QordKHRr5RbC8hjKVurdHliI5ti4HKYqxkjDFSgtC4vqrJ+TNicr7OcfcMnReUWINIKHXTGGm1MPYjGQdNfx/G058Dst9NmJx78p9qj/qefdzoOin2DTH7x7wUxjaLcwyL5z25T4nSf5J8jvIYWhj7yubEerDr+tmors3yeo5j1TUv8eeHUa+zfxTXqWt3fSBytU767c6JcZBuD7G2Zu+jhbGFtocir8k2saKrbg+e9qj73lAOuaf+EI9BmLCfvu/duK5o/wccYaxY3YWOMKbP0dP/jXO0hTFe6wlZLFDAIoTMGzGPjgbT0z9/BTPPDeAaa8IYyDR6LwDA3Ege2Qf+Xca9Wm7oKeaENZDbA0w8+iKW1a/H8o++09iOWL6AYcX0nQ/qbSqf+DGA0c8fwqod9Y41lb88U/t6hRXT9hu856XehyEwN5LDyUdfEsLY8quicod2evVu4pGXkNq6ERW31iDK2j5XdR75A8dlXd8UO7b1TpYj+8Avsebem7QQwkHeAgmVBZwQcKYe+x0ASEEqQOi2A/lXCFLiyfnav70DwfKrHGs9W2AKEU0Qrq5fr8f3gWwPZn8JAUsYM8Uk055RHWtuOI/x73aj6r9stoSxQLcLdX5ieySM/Yl1fmbOqjinj4xoYQzG8dXfaP8AoWExtkSXw7QvtEVAHRDesNaM5j6mqCbqWlmMBcuvMtKQ+WPXm7ZiMsUa869BJNY0xNNIIVZxbupMJIwVs6QIonJYYo1n4qyYHcoj93OP1YpydzLdeMPIimlZ/Vr7wJ687b5XhDAUk3PXYsxtlsYxYnUt89ETegMlSqe/0sCmfiEJgbH7/x2Vd23AVdevjuo98FRyCEz97A841TuC1Z/5M8/39u82O5S3hTGFmbfRvyxhrAQzzw0id+B4ZMUUa2dRQc5Nn41bMSX0JWW9awljSEor+55PGHP6v9o//kDIwdhFC2OmKE0IWTRQwCKELAg1BhKT81ew9uEtWOIG3AztsVMYAtnvdiO1dQOuvqUGxQiCSBhbfe97SqadG85h7IFfCismryBlc1IJY457n28cdPbYuCWMxVZgdN6Pfu4ZYTFWRjm0MGaslJjE3LAQxtY9vAVXFAmyqrIQwtgGXH1r8bom5SHEHiXWHEf6vzSIupbtXD0wNlFWTCs++s5o5UyVn/tbh8CUXDFPrZwZwJ5nm7LX3HAeuZ+9osUawE5jCaCQE4Q7jQmCp62p85k2JueB8Z1PK5gdymH8u91IS2FM1ZOVp5F35Eppr5So8zauG6czoq6vffAD8bl7aKcNp6XFmFyMgXLthWPqqT+g8PxA3A3ZM5lXYk065t6nrFCiXzEEMLnvd5FrbTFCKdYcNISxIpybVhZj73RW8AzsziEfxkzu+x0QhFi540+ddhbvKLNDOSGM/UgJY36RS5U7EsbWWdutMkmmftZn1HVStoEshxSlVV0XExVIaRwRccl/qIxbtcXaQ4DZoTwm9x3FOhkbM179tmAzdv8vhTC2cbX1nQofYO4fF8aSrmqBLYy5VpKeck38eB7CmM+V0ifmIXJrt937/P0fQSAtxuB3a3cKPzuc5MbMRk/IYoFB3AkhC0BaeuTO4MTnn8GKj77LinulCJ09Jvf1AiFKP7GGnCBIYcxdiUaJBfo4IZD9nhDGKkqINUEgBoSF5waw/v9qiuXlkiSMmZj7jz/6IipuEVYrSWkUp3rF5Hztw9FKiYlzoPxZjH5eCGNLygjaroQx0xpNHYMskFDGvfpuN9JfkVZMUq3RApMzNz752FFU3Crbg9shYItNSqxZ97dbEBhijW4XxrYwdwajnz2EFR99J5asW66/iPVBuWGqLRLG3LKG8r3aeU6J0j+6A0HlVV7B1hSxst/tQerODVhWty4SlMw6MT5Py7533d9/OMo36Qm+jDGW/spmLFm3XIt5bkdRseQn2uy6ds+LzA+9KMZQDpP7juK6v/+wdPe0K1/8JKKiQ2NyfnX9eienyKFV/ZDTT70StQfze5leWNeJ7UqsufbByGpFHTvaVxEYVkybrO3QpVHWqqG0YjqOdT+6w7I1dMsAKGHsWay4+52Ga60p29oNTsW9Wikn52Z9RVaTYp+5ISlK/yianAe+MssG7hXGyMKRVT3zq0HkDr6mBSn7omP+dqGIxfS5Z7D6MyI+X2hlpojST7YdxZLrKj1ijexDxh5zUhi7Tq3qHAuUbuwThjFhLIpRGsrUhlD61B9wKjOC//jkX3jKardoFQvR7HuQx7T6v9wnEsbeaZxTvP8DIWb+fSBatdaqN0/f08LYO3VdRwv4cHQzX6bD03j8zP8AIFzvQwDL7yq90M/sUB75A6/J2G2lb7L5p1/D0utXy3apsH9nlcepI6OYHc5h+V0bnHyDWNpz02cx/bM/oPKudyRY79r75J9+DUvWL8fVN651vvef48xzA2XEbpP9+rHfFSmHzcyvBjGXO7OAura5aUnNol1tlgIWIWTBTO7rFWKNYcWUdDuYyQyLCcLDW0vmG+bOYPTzz2DFX71Li0Zmvm7+U0WEMTft7FAeuZ+9rK2YzCEp9EAoOl65whgQWYyt/7+arO2+OpkbllYrX74lZpnj42RbxiuM+fI/pet6Sywt5/Lnx9j9/ybEmvp1CQJM9GtM/+wPoj3IlTNNIUcJPUp8mRuJhLEl6yqtdun7zSalWLPi7ndaQf996ZUwtvZHdnuw5kFS8AlzkdXK0uuW2xZOntNVwphrqRV76h86wliCBaEpjmW/263r2py3+awUp55y6tqoZ85rFkqgxRoxObeFc1W10RQhwFRbr5yc32BN5N2fIESAOUsYu8rzMxmupKFptbLGOr7vCFNPvYLC8wP4j//3R4xJfJQvjH2VBaGYnLsPByI32xAhAhkL0bRaib5XdREdbeZXA1oICYzjRpP+qPxKCFlx9zuxJGbJGK8d5Uq50rDUMqUKsgBCacX0yEuoku0h+h2CeJs22kPlnRvkN55sZXoljIlVjLUUqfMz24RqD2vMvhf6jiA+T0lhbKXse2Z+bnubHc5hsq1Xrixr5+dKwSGAsa/ZfS/K023PIaae6sOpzAj+w5Mf8chmdn3MDdt17Z5XaP21LcaK9X9SHlPhaew5/QJmh3IY+cmzYlXJ0ydQaqT4x0//Myrv2oBVp/MljzH52FHknn4N/7H9L4DTxdPODucx+s1nUPXQB3DV6dGSeWd/2IMrVlyF1avzJfOe+dUgxn/ykjzHYmKXXLX20/8dqz51AypPnyxZjsnHjuLMsQlc+//5QOlz/GMOQ9/6F1z33z6MK0udYwgMf+FfUPH+Gm9d37MMi1bAogshIWT+hEKsKTw3oAfPxlexe9/ccB4T3+tB+su3lLWk/UkljBliTdLtVE3O13wleYUgPYjLncXo5w9hxV+9y2PFFIlX6nimMFZqeKTcudZ63PtCzwcljJXz5FwJY25d+/K369o+Rw7yFk4IOUFYXxkTStUgHoAM5C/Emsm2Xqw1LClCwLJKCgEEgZycfy0SxtzjuigrplU7brDFqyAa6KsyaaH0K5utJ4PxCYXgZFuvtmJyXRBd3L4XJqQDICwIP/esdqX0T8Gi/U1hDPCLVgrlxqysVrQwqPNlu18QoYy9c6uYnJsCpu+9EmuucVZ09bW10Dc5T8gXiPreyu3mqrV2WpVeWYyt/dEdsQlwLL1HGHPLGv0NtDuXiPfoimj239khEY/t2l0f0Nfi0NlH5x1GcY581rtunRd+NYDcweNIf6Uh8fhkAcj2kJLtwW03gfEKYbr3vccS331ivxLGrt31ASyVwlhSuwyN9pCSwpiZzt3nlGwPq2W7dB/4mUKWcmtf8zfvsSznky6xU4/JvmcIpUn9dG44L+572poq+V7jE8aS8g0g3NpPZUasczTTFpdcSBKzQzmMfvZZXPOpG+QYIaEm5ebJx45i2Y3rIosgX4PUeeeRe/o1rPu7O1AOo//HM6I9bFhdMu3kY0dFe/gbT8w5B+1a+9AH4hZSofFGvleLxlSWYSE186tB5J5+zVhNORkR7/FZed9LmAsZ9afdmMtYtXaxQQGLEDJvZodzyD31Ctbu3oIrKqVYkzRyC4Hs956PxJqweNrpn72CmV8NYNX2unhaZ5+54TzGv2dbMflGV2plQ2XFtOKj74zlqdKo1+nMCHJPH8eaL2+W3xsV4O5rCGNXKncu+YpWQYwGkVNtR4EQuGZHnc7PTGcew6rr5Vcl14ncT9d13bpIsHLPkcybUzIw7jWfeU9MCHQHz+dyymol7nZqTiQA8Zuoyfk1O+KTcxc1QVhnWDEFUEJYVAo14R67/9/tuFeIrEVclMWYV5RW+8qYJ3OGK+XShIGYOaGefKwXFbdW68m5e3zzcylR2pr8587ixOcSYozp92z0CyFnijVhZDGo3sN4P/dHKdZ854NytVhjom9UfxhCrtb2W1TcWoPUVjk5l9dY8xjqJaxWosl5tOqrkbfcVwWEX33ve7B0vX0tVphlF+5cyx2LMTtf8xwn94m+p+8JYbw8YQiE56QQcucGXLVhjXV+6kDmMUwhRB3PVxcIgbk/5nHykZdQ9Z0PCPdho8z2Qg9kfoSY3CcfUmy3V82zLFHl57k/5jD981ew9uE7vL+T1Z7PCevdyjs3YOmGNbbA7ulP06rv3fsea/zhtjmERt/b9QHtTm6W100/8eOXdN8z8zP/BrrvDRj3veT+jxCYkzEIV3/mJiw1YhDG+r/cRwljKhB7Uv9HKAQI9UCoWP8n80e4vm1A5Z3vKDq2BIQrYO7p1+zg+UE8nfrNRj/7jBDGklbORPR38rGjWFa/rrxVa5Uw9rd32Pm4+crX6GefMYTSIDktgMl/EMJY4iIhVruMVlP2nqOVPsDEI7+N6tocn3vG//mnX0PuwGsiBrDvHN06X2RQwCKEzJv8weM67lUQBMkX0RCY2meINSGcFfwgb4Aij7mRPHI/V3GvZGBcTWDvAyD73Uis8d1ATaZ/Lifn2xPibxnlmhuRwthXbrEFiIQbxmSb7UppnqMlKoQhTveOIHfwGNZ8ebMlKIWmr5Pcds6JMVbqZqWEsVXbldWK6zpDFsrMcwOo2vVB+cTa/iHsVipdSm6tloMUm8hFVfynhLHVn7lJ52o+Pbf2zZ3F6OcOYfVnbrKs60LY7Uz95pNtvViyPuURpOK56yfnPyqxQIA8jnKlNFdKjJ+rnKhoi7E6b3s0t9nC2PJYGrduLIuxxFKThXDm2DjWPhw9OY9NRCF/j3PA2ANCrFkqY5y4E0zz/fTP/4BTvcNiUhxAu9Hq90YZ5obyOPnIi0KsSYr9p45xDph41LAYM8prTrjV9lPPCauVa+79s7gw4JzvuSkRg3D1ve+xRCOdt/N+al80ObduS+6EO1QWY71aCHEXSHTPdeyBX6LyTsNqxUnLK/4CCSEtOm7yLzRo3P/nhnIyJuUNMeHcWmBPbpzaJ+NefeoG/b3b1pTgM2sIY7Hje8o8+vlnhFDqWhB60k+1icm56ntAksuj4d636wPOitFO/5fvT2przXcU7f9AJIyt/pubivZ/ACKkxOcOed2YzfOkcLswtFhTjFC4900+dlSINXol1eTx/+RjRyOxRjc2//hfC2OfMscq/iuZJYytjy9U4H7WFmM7/rRIIxHHmh3OI3fgNSMeW3K+ADD62WdRedeG0iuJQjzEO9U7Ep2j+UDZiXUgBFuxKETiOS5yKGARQubNyu03aLEmLDJqmHl+wBZrdHr3JhbKIOWHrLhXxRSpqX3SxUiKNTFhzEC4972MtQ9vFXGvdFaGjYhxHqYVUxLqeMKV8nVDGAsS60QLY1++xT8Qs84x8MQYS3YSOd07gtwBUddWjrosnNacD9d85s9iK0ZFRNumfvYKTmWGxZPzIoQIMTucw8QjL6Jq1wcs11rRQ+zjCGHsRT1BKJX3zHMDWhjzDXwiQSgQLiVSGFuaJBIYmK6UWgxLEHdnDWEsqFwKHY/InAwZeVgxxoxEURjgqPzKYixJGCPnhysiKsyrUAhbrCmWFoCMe9UrHlLAFYvMcNPCCmTsAWG1ssyYnLvXevVJCGORe5917MBsO0IY0xZj8kGMsmSMnUMYCWPLHXcuWSD9NoQQu3MHj+Oaz9wUT2ukCyGsVk5IYUwLIZ5JvDqEqOu4KO3Lm8yTIMDaH90hYhAmVGAo/5ncdxSpOzfouFc6C8TnyPkDx4UF4b03WQKqL+/ZoTxGP/8MrpGrGJvt0Xf3n9p3FMvq10t38nh+ptA0N5y3YiGWGhqMfu4ZSyj1lUM/pDCEsaS0irlhZTH2QSyRKyV6+798KWtNHWMsof+ThWEF8S8yjlZWTCp4vugL9qIDism230lhLBJrVHr3F5sdysWFsViORt6mMKZIKHf+gLBisu5NvvG/HI+NfvYZrDKFMQ+hPJ5pMRaVNPB2cC2M/eiOIiJaNA5Sfe/K63zxcRMe7C8yKGARQhZA4LyibSoU6dxwHicffQnXfvtDuHL9Cp0mHkxXvCYeeTEWED5+HPGaeX5QCmO36JT2PSFKey53FqP3HYqsmKw05l8xMNJxr7bXxc7JfIWhWs7ZjHtlDunijD3wb6jcugHL6tTqXP66AAJM//xlaTFW50kbGmldV8oV+lxi52f9XmQ+XLH8qkh4CQP7BbFNuzk8vAVw00L8Vf8psabyzo24amPa2B5EkxzjGEIYG8E1996k84pesI41N5zHyUd+i6rvfFBaiwR2/rL9iuOEOPnIb1FxSw0qt26QVoFmWeyXWEr9uChHGJ2L2VfUf+F0ZDF2pVGOyArFzntq31EsWRe57ySVAWGggxCvfVgKY/r83XwR/UZkXiQJIeaERU3O3YkrYIuwIYRoNPr5Z+WKrpWxK6VrRajcuVbGrJjcMNNqtbZe22LMPA9j0hKGPoux0GPJKJiSFmOrndheRoGMcuRwUgtj8Zhz1h0wBE5qYWxjrL7sY0TC2Ooiwph7PDI/fPUWWyBg31EhlJa1aEwOU/uOYu3Dd3jcyeM7T+7rReWdG5CSk/O4W3j0V/W9VR7Xc1fkmR3OY/Rzh7BqRzQ5V6MB33x6qu0oltWv9QqlbjlmtTBmW60ktefRzz2j+16x/h9CuPieygxb1xdf/yfni7ga2w88o5ft3meMJ6zxpfh3djjvXVUy+tdcKikwhLEoLlxo7GGWR8W9Mtt8qP+xz8a0GFtSljAmXCmjhxS++Yf4N//0cSGMfcperESdm/maHTYtxuw5iN2X5Dm2/Q7L6teJVWtDc31NlT7a4rOmXyxQwCKEXADiA5Wxr/8bUls3YKl+ehdY35v7TP/8FTlBkJPzIkLL3EgOJx99EVXf/pC8GcRFNJOTjyph7J2x47rnUHhOBCE2hTG7zMa23BmcuO8QVm6vk6KRKxjZNz41OY8LUvEyR5PzrYYwhoT0Aca+LoWx+kgYU080zWOFEFZxZAEUe3Ieyvbw+Wfk5FwNUuSwQ+qaarIQhsqSYrleIMB0T3HbgwoIv06tImiUQ8xTomlxEMjYO1udFaMsBSA6zvTP/4BTmWGs/pub9LbYSu1GOU4++hKqpNVKlK8xNA2j18SjL6HilrehcmtkpaDcRdxzVBZj1xjXgMT6zqk4RzcZ14DonOx3AU73DvszIvPCncjPDeUxte8o1j28BUv1Qwqb0Hgzue8oKu98h54guLHYzM85LYzZYo0qgbmfsFo5FMW9cvK0J9KhtmLSMQhhXinjopt27/OeoX2OYw+ImHNLjeXi7RUKoymHshgT7sPJE5EAQgg5+chvce13PmhNxkxLSvM8zhwbT8yPzA9hNSrqdm4oj9zB41j78JaiU0cl7J/4/LOo3LoBS9evsH57ka+NEsaSrOssV2tDGFuyvlJ/pyfEzsVzsi1uMeYK1KqvFA68htyB41hp9A/3+LocWhir81qVx86xLbIYK9b/lYWyu3qur/+r9zPPcWyzEFTrNkUUsV38Djkp1ogg5eZ3cPYJtBXTNZ+6Qa+kCiONSq/a0sSPX5JiTeTBYAtj0fszx8Yt974QAUKZPjTOQ+VhCmPeh9A6DyFencqMGA9LAucco7qyXSmXW/eY0Di++htZjNnCWAjV5qNzyD8tRelP3aC/s8UztU0IY2ePnSz5+16uUMAihFxwpvb1SkuKupJphViTwdrdW8uKYTD2wL/FJudJktT0z5U7V+kn1rPDShj7YIJ7n32cCSmMVd65sWTeM88PIHfgWFnlUMLY6ntvLs+dS9b1yjLqem44h+x3nyuZjsyfiUdfQmpr3KUEiMQg1bxPKbHm3vfYcUWc/QJIsUYKY27sHV/ek22y78kBYeBJq7YroXTdw1sst6Wkfjj2QFwYs8pqfFZ9b7XHMsfN3yeMJRFACWOmS4k/bQgxqZl45KWieZLiRINzu7GOfv4QUls3YMn6Sus7N32AQE7Oh+UEIZQD8RB2luKDsFoR1nWuK4fddALLakWtlOgKVqaLav7Aa9piTLuzGvma5zEn3blsUdo/kQeEALF04+rERRDMss8N5WWcoy1GOvfs5MQlDDD2wL8jdec7LGEsXh/i81TbUUw8+j+8ZSSl8f2+ISKhVMS9Kr6ashJKXSumKO/A2hYJY3d40kZ5qsKMfv4ZpLZuMOJvJQ+epqQVk8/F1zxOiBBnh6d1sPTIUstv7REgwGSb6nvv8OZnfs5LYSwSr/z9HxDC2InPPWNZjMlTt0pgn+NIYh2QZNS9O3b/D1UMQhGkPFh+VUzQgbOfWr0vdeeG6KGdehljFSXWFJ4b0Kv3+a6T6v3scA5jX/tlLA6a1UOMHU1hzBSiYscIgbPHxpE7ICzGlFQUOvmZZVLCmCnQWfUSRvubFmPuWA3yQZ968CcWCVGitD0OMo8TGHkv5gcVFLAIIQvDN3JGgljjvcqbYk18tTbffloY+2Rd/Obi3Jm0MPbwVvjuYO6NLystxpZtTMfLq2488r0Wxu65yXte5jbhSmlajHnyNl5aGNu6wRpIxO68oarr41Fde+/Q4n0oXSlXlyGikfkxta/XO0GIT1VkYFyvFVOcEMWFMZf8geN6xSgzD19cn9nhvLYYW7LeF2fBRve9hEmQOQA23ftUnn4bKcHYA79EZZmi9JTqe5ZLSTydEuhOPvpSLC4cmQfaRVa9AnktPopldetkDEIltIjvQyft2T/mtNWKysdcwMJyFT0nrFZSWzbIFV0DORGy/4rtoWG1UqfLGVrljV7aYmz3Fp13tPqsOL5+mn5Oxjna+g5UbrVX51JutuJAIn3+aSGMrdz+pzo/dV4B7HLPSSHkmu11uHJdZawMkRuxmOFM7uvF0g3XxFbG07PCMHL9mZV1veZLDRepQVz+hO5MO4RYOVNdi7duMH7/KI3pPq2E0pXbRXy+mIWt0YbO/nFaCGOfvEFYMpq/v243sPte/XppQejpF6o/IdBxr9Y9vMVok4DdX0N9jBOfk8KYXk3Z3/8hxSthtVKHYv0/DEPR9+Q9YYnZ5uH0f7mvEMY2onLrxqL9HyG0xdiKj5rhJ0i5mAtYWGNdCHfPVTvq9OqW7iuQ+4WhEBFnh/MiHmysb0SflSXjxCMvYe2P7sAVlVdpUUZ9HzjlmvjxS6i8cwMqbq3RxzOPrfYLw0gYU6vnJo3/A4iHZ1oYk2EOVN5m+VU5TiphzLgWh065lcW9KYxZDw/VPk79j35exr1ab6wkmlD+ybajON076o/JuEiggEUImTfmzUgPKuCINeYND8ZfY79IrNlobfftN9MthbF7borl46YNc2e1FdOV0molcFYGCY19p/ZHwpg1eDWRn2dHDGEs4bzMbWNf/9fIakUPcs1KjJj+hSOMqTwD531oulJ+UNd1YKYzyxMAE4/+xq5rMk8C7yft5mBYUih8TV9ZrVy1cU3sCbvbJJKEMV/aueHIncsVg32LCkzu6y1LGAsQCWM+ayqRJrJimRvOeVwp491EoeNeJVitmMwZwlgpQgDZIhZjpDTqWiXcPiM3hsJBOTm3Jq6A3SrlPWEojxP3yaDU60yX70DnaTbPqf1SGLPclyKXaNNlVVut7N5i3IeMCbr5CgOM3vcMKreKJ+d2jEDDYktNxvYLi7FV6hydl3aDDYVAN7X/KNbu3mK5k5sB6nW5QyWMbZR9z83TrL8AebeunbozZfK5P+Zx4r5nseqTdSUthEgC+neyf++p/UcxO5Iz2kM8nfqdZ/8o7s2iPZir9wX6X93+wgAn9/xWtgfz3hy1ZW/fU4vGGP0iylP8mR3Kafe+Ja7Lt0wfuXMHUpRer89RLWzg9n8gwOyQcd8r0v9VPsJibKMV9sHX/1U5TmVGnIVx7L9qu1g99yjWFnFjJgtj4pGXsKx+PZZ/VK2uHR93hBBtQ4k1Vbs+EPseiAs2pttpbKjtCDxaGCsxRlDjDyGM2asp2yuDR6+JR4TFWMWtNfJ5QOjNGxDjoMJzA4njIDPfueE8xu7/d6z+jLtqbaD+t5h49CUZYyx+jma3DgCc6R8X970fJayUuEiggEUImTfufFhd9EfvO1j2hHFqf69077tZZpKcdlaJNd/5UEkXI8AUa8zYO/4DKGGsHMukMO8IYx4RysQUxsxy2E9jBUIY68Xa3Vs9B46/VzHGEuMcGcQsxsgCCGOf5qQV0yo9OS/O1L5eOTm/QeYh8nTdmABjxagEscb9rSN3rgTzeqccxVxKTM4Oq1grW2Jm7bosRsnF5HyD1fd8CCuF40KUVsGxi1wD5ob97lxJRG7Mpc+R+DGMJHR7mx2Sbg6740KpiXqiPrn/KCq3bkDK0x5UnqqdFg4el2JN8d9MPcEfve8ZKdb4LRlNQWhqf2/05NyT1tzHEsbcc3LKjhA4cd8zwmKsnHa5v1cKY5FLiZ6gGGUS5ZB9z1PXsfLLulaidIlbE0kkXnNnXhUTxmu/8yFbovFVcgjZLuv9MaGMSS4g2oMQxux26Wtrc0M5TDz6kkcYs9Opcpx89CUhjG3dYEudAXScQ7VP4eBx7d5nldWT96x8SLFquz/ulVv+ybZe/+Tcc65zI8kPhHx5m66URW4fZJ7kDxzHzHMDuOYzf6a3me1BEQCYHZrG2P1x9z4zjYkpjOmxT8KPd/bYBHIHjuPaBz8Yy8fX/ZTFWMz13DlAANtirNT1cm5YLM6x7kdbEEhhrNg+E4+8iMo734GKW2ti5XDrsXDgNcw8P4BrPnNT0f4PiPvv2AO/lCElKhd1m6eARQi5IOjJ+SfNJ5R+5kbyyB04JsSakoGvApy4T1qtbCghjMlVBMsVa6K4Vx/yxhdyiQljsaJH532qW7r3xcoRr5tz2mJsnpNzQxhLOsbcSF7HGCPng2FpIn/3ybZeW6wJk1/5A8eRe/q4ZXoemaCHhgWJEmsOicm5apfWse0n7VNtvZE7l5VvvBzaYmz3lng5ZZ6Bca4nPm+4lCSdo9w+1daLU0eGreDYSRaKs1IYi9y54mnMslh17RzXTavq+pp73xMvA1k4UqxZ8ZfvLLmiWohIrFm5w54g+NKKYOmyPZS4BoYhMLm/tAWhurWo1dqUeGXbXNnM/jGP0fsOWcKYWU6Xqf22KF2MuSHh3rfOuRZ7Jy3nhBCS2rLBE5g+/t4UxpLKSsrBrrm5oTyyX/8lVt8TnzDGBFMAE3texLK6dVhxt9+dzfzttDD27Q/Gvov9floYi9plUhsOIIWx4ZzVHkwxyiy7tlop8pDC5KTHrd3Xp4HIetd8kJCUVgSEfwZrSoyDVPqTj75o9z02+vNC/S5iFWPp3rf8KtPeMEYIIUilpHufSBfE0uuHFAdes4SxYrHbZodzGLv/37D6M+WJNScfEVZMyz2upG7Zz0hhrGrXB/V5FEO7UibGY4vOO8lizEyjmBvKY+LRF0XfW740MW+1ceLR38q6rl70DykoYBFC5o375DF/8DhyB48ZgkoI171BvWaH8xi97yBWba+X7hbFmdqfMYSxWEmsT7ND0/LJ+dbYd759TrQcisXeSSzHPhHvobgwJm47Is5RUkB4VTdRWU7ucS3Gkm9NM88PIHfwWHnlGBF1vebemz2rtZH54A60dGBcw80hibmRvLZiKrZqnhKylHvf8rs2QgtnOnlgzT6iyXmSmGmX48TnpTuX0fdc1xP1tFKL0ttLTBBC25UyFD4n0bmp2CtqYBsEGP38Ie3OVYwwNCzGHGuqWJDjMNR1ve5HW8sSg0n5qMm5b4LgNo2zcnK+TloxuTqmSRACo/cdwoq/fGd5FoT7e3Hm+HiZolEeU/uPYt3uqD2Yk3n3JCb2vIjK+bjWlmExBkh3LilALElw7zPLpCzGrtlxQ6ysbl0qYcy1GCPniWwPqa0bYpYUPnIHjmPmeeFiVCyuobAgzEXCWBkxCH19Lym9EsaqvvNBAP5+ZI7ORktYU5lM7bOFsWJlESEl4sJYfOIvmHhU1PXVWghJRrlzXZPgzkXKx7QAD3NnDSsmu116BXwp1qwyHlJEi2PY4/+5YRH3ap1070taDENx8hEV96o6seSK/IHXpHvfTdY5KUK9RyDd+4QwVo6r9YQUxlZ89J1WvnEhNowsxqQw5mIuHBKEgVwUQliMmWX0MbXvqG2tWbLklzcUsAgh88Z+epfH1H7h+hYNUqJbWfRXvKb2ZwyrlWKX4EAIYweOY+Un663tRkmicozkcaLlkDEQCz3po33U5HylRxizbyBCdMsdPFb2BGG0pZQrZVQvfmHMXy+zwzmc3PMi1u6+0zPYjNsVTO7LOO47i/2Wt3DMmhWDlGMyDprZ1v0DDyXWKPHKFoAtdUrE/zgixBrb7D2IJZ/Vca+2JgzEnPYgrZhSuu8lTW2UKK2sVoo9g5V97z5zEqQsuKJ2Hhp+s5NtQpReWdS9T1mjuS4ljuDnoF0p11XG0pOFUzAm54qkmp0bymHMmZwXYzxBGPNdrfTkXFqtFMUSxkpPVJTVihKkirWcs0M5nNzzUklXSlWOk3teMtz7irfJggwAvmp7Xckrts+VUpSd7X5h6CiVMfe+YswZ7SEwYu/4CENgYs9LqCxTGMvLvldMrAlkyWeNvnfl+uUI4O9H6mo8Ia2YVnz0nbH8XHScoyLCmEk0OS/xkAJ+YSyp7avFOdY9vNWKc0TOA9kgJtt6UXFLdXQtDs1rif0w7XRmxBJroq+UIBbqv+dyZ2Tcqxv0tTh2/zY+mlZMtmgUjYPUKpbCYuxFrP3RHQikFZMbnkEfIgyle58jjLmW3HLb9M/+IC3G3iPc/+QxRV52ubUwdu97it5vVNkmHn1RC2O+7836sEVpXtsBCliEkPMhlGLNlg24cp1cPQdBZKOu56wBEAZarIncDN1XlHZ2OCeFMWOCoG8Y6jjQ+07uyyC1ZQMqt9iBcc00scn5J+ud44q/4ialLMZyONFiWowllFuea8yVUh8/qjPTGi0KQmyU19zHCBJ7ouWQvTpXTLQK9b6qrld+st5bB2S+RL/Z2Nf/zXH39FsbAoEIzqnFGjmwC+FNe/b4uCOMucKR/Ve51gqxxleG6L0IjDuMVdvrYLcBMzCuEo2kxdjurYallpoKxfPW7n13bozl7Z5n4aBYMWrldvsaEMCuC1WO0ftUsNcV3vzMV2QxVod4OcmCCKWbw56XsK51q5icy2uUz0VVrdZWuXUDKm6piU8MTPOnMIr/sdq3YhTs96Y7lxVzLv6cBAECPTlf/ld/klwO+VKBcau+/UH9vff85DmeUKJRwupcZrmm9kkhRLr4hrF7Y1QuUdcvYm2rWK0tlifscigLIRHnKMqrlPBFkgnDUE/Oq771Qav+Y8Kg/B1GjfYQrfQH+68xRpgdycXdyZ10qu+d3PMS1rZuwRWVV9lpjDKEAMJzIU7usfteaJXdzjuKc/Qeu02q9mP2veG8jr2j2nxi/wiFm6Hb93z9P0AgJucHpChdpP+rzyr+lhYJ2NjPC3X/n/75H1B4bkAE8VerQqrv1aqPanw+lMf4d3uQ/vItcoXCwHjJB1Z6VckAJ9t6UXFLDZb/1Tv1Nn3fNyy0AwQ4dUQKY9/5INxVLUNjX4RAmJcWY9uja7Fe1VKObczVQaf2HcW56bNi/GGuymks6qHKPjecR+5nr2Ddw6rvyVwCWeYgMMoSIPvdbvGA8P1vi87RPIZRR9M/+wMKzw9g9b03GXXlpJP5zv0xj+wDv8Tqe95jrw4aLu7HFBSwCCELIxQr8yy7YR1WKQspNcf1TUZHcpF7n7Fcsj1gUTcT4MR9pjAG66Yljg9x0wlhCGP1MCcEvkGhmJz3ysm5eTMwjm8sHT21v1cKYxuL5CvKlj9kCGO+PI1zmBvO4cR9B+UTyhVRfgj0eSEMdJ1O7eu169o9vlHvs0NmXZtlMMpO5oWqtpOPKpeSt5XcJ3/wOGaeex3X3HsT4iKK/XluJIexB2xhzCcFKZQw5hOkXM4cM4Wx5HSK0ftMi7GkMov3kXtfXUJu0T5zwzlM7uvF2ofj7n2hp0R6pcQyVs7U1ppluFKSMpHXCxUTasn6ytj1w1rdNYisVnS8KWv1J2PnUFhSKLEmqPRYUpjHOhe5GFXcUmOVT783jpU7cExYrdz7HruMZjmCSCjNfiOyWgnDMLaPiXbn+it/nCOz7GdfnRDC2Lc+mJAuKouIexXF3wpUtG3IenSu33plPB2YPvpyMU9szodQtsvx73Uj/eVb7OtUiJjQA4j2ICbnfyLzCHV66y+AU5lhGffqQ3qb68KtPoe5s1F7uG55LC+3/av24LVsDQGz+82NSPe+3YYw5qQ3ifU9t+yAbnT5g8dR+JW47xXr/4Co6+zXf+mP/+k5V68o7SkvmR9zIznkfvYK1j7sWhD6xxbj3xNizbL6dZ5v7YdH0z9/BTNKGHNSmiu1BoG8J3xPCGO6zcfKEW1TwpiwYopEK5FplHcYAqekKJ3+ymaRUmlyel5hiFi5Mxj9/DNY8VfvklbEgZWXWXZAjIMQAqt21DkrZSL2eW44h9zPX8E6aa1p32tsC/0AQPb73ajcutE/5lzE7Z4CFiFkQeQPHkPu4DGs3F4vNmjxKo6I/yHEGjcgrY+pfb1YVr/eFsZ8hEoYO4a1rZ4g5Z79lHtfyVXjgmilREs0Mo5tMjeSE8JY69Yo76RyB0YQYiWMJeUdeuo6iVCsZigsxpyV8TijOS8CGG4O5cSbGs6LpdTLdHOYeCQujLnjd7XBFMZK/axzwzlkYxZjyajAuFoIKjJAUi4ltjCWTLIwFj9UaWEsQi3GsPbhrVZAeG1xQBZGUFqsMSelZ/onYu59XjdYAAgNKyZjghCYsdOMfVyxJqEwAMT9RrlzXbH8qvgKVOayf6F/cp60am3+4GtaGIsTGH9lrBWj7ykrADt9JF5M7PmNVdehMVtyy3P22ARyB49ZQog1AWO7XxBBaEzO69YnpdLvpn/+Cma6BxzRyGzLEbNDeUx837Bakbi/rZrwTu7rjYSxEr/n6d4R5A4ek0Kprw8ZE+r8Wce9z2y3cabajmJ2yN/34qJ03nDvW5rc/yX6vneLuO8l9X8gkPe9pL5HFkqYO4PRzwmxptw4aEKssQPz+5qoacUkxJpiBYG2YlpWv867uIWJEsZWeuIEAtbzDCFKf1eI0kvUipVF+pTue554jy6ntTB2i318T9pw2hXGEL9Wh1GPndzXCwCJcRYX82WeAhYhZN7MDedFLCZTrClyJT2550VUbt2Iyi0biw+sQyB/SIo1ZmyqJGFsWApjnhWjfPtN7XesmIqURficJwhjHkbvO6iXcy5Vbj059wljDrMjwpVy3e6tpUU3SIsxJYyZLOY73QUgiv/xoQQrPPulBNtEFyPjpYUx1eadJ/zme0sYq7zKchHxlSmanL+taBkCqMC4hjCWdI6QKwR9XcR7KOcc1ZPzlZ+sK1l/wqXkWGRBWOwF4Uqp6loPWo0npWz7CyP3s1eEe9+9Kj6fa1kbvWaH8sh+49+w+p6bsPS6Iq7WMh+9WttfOfE/9I8W7XPmVSHWCGHMl6fxOQxwokUJY75ymE/EgyjOkbUYg7/c+r63ewuuWL7Mk86ezFt9D4HRZM18Q4jJ+TGjrpPqWUzwtTB2z02GEFJchCDlEGJyfy8QwCPWuPUrXYx+/grWtm512oP4Ta2xThhg/PvPO8JYUlsWk/PC869b7tBWLCKn741/rxvpL90i27xqaWYbi84jcuf6E+u4gZFG/RVWK8fEfa9I/wcCvZqycO9b7klj5i/cucQDISPulaf/AwHmRnIyILxb125aMl9OesSapNo8nRlG7sBxrPnKZmu77xZ7LncGo58/ZAljxcb/k/uOxoSxpLznhnORe5/xgNAst3ksn8VYEtM/f0W6UpYR+86w1nTjXvnKfXJ/r2Wt6UP13lOZEeQOHseaL4u6jl+BFnerp4BFCJk3+UPHyl+1RrmUeFcRtBGDFEcYK4IWxspyMVLCWH3JtLMjOWS/8a9lW62oyVg5gtTZ41IY212eMHZCCmNLyhSvyhXGyPyY/vkfIrGmxKhBuzn8pT059z1YVu59VcqSIpRPoX1zDzjCmIkj1gSBRxhzymBaCEQLBBjCWBJh5EqZSnKlNEZXymJstblQQcIj27kRKYSU2/ecuqblyYXjVO8w1u6Wca+KNfoQenJecevbSvwG0qVExf+Q26Q8Y7wXzA3ntDDmX7XWLldkMfZOT1o7/VkdEN6cnCfsEwaGe1/S6rlRHpEwVuq+FxgBwEVdJ9e0cDOciLkxx/dYzBObBROKSeOaL90C/zQxqtVz02fEAgFeqxWPWKOFMX97CIx/54ZyyP38ZaPv6eIh9ssafW9ZvSuMxd8Lq5XXPa7nbv4B5oZzmPh+N9JfuaVsyxwd5ygRkf/p3mEhSkthLKn/A9JCKDEgPFv6+TLjEWuSRKNx5d7nCXNgEsC2YnLzc/c7LYXStCOM+ThnuPf5QhG4+CzGfGkDRMJY3JXST3aewtjM835hzK2POUuU9q8GaT4HXIxQwCKEzJuVn6zD8r98V8l0Z6SbQ9W3PlRWvnpyfqGFMf3kPB57x/eE8KRaOnuzf3JuDrHyB49j5vnXsfqemxOObosEY1//13gQ4gQWJIy13lkyLZk/19z7Hu3mEBtJGOQPyfZw702I2cuH9nsl1qy592arXeo4Kw5JwpgvXs9pa3LuL4Pp3jF6X3krRgG2MJYoVoQAwgCzI5EwZg0IE/abePQ3lktJMbQrpbWCJ7lQpL90q17JrBilJucmanK+bvdWuZS6wOka+k32e8+XHXNOTBBUzDk7Q1eemhvKY+wb/2ZNEIoRxTkqNjkXnJXWu9e6fc9HCIy2HLKsiItNSnzCmO/3WcwTmwUTBFj7cOlVJQOIEADltIcA0mrl4DEpjPlRv9e56TMYbUkSxuK4fa9YX50bySP3s5ex9uGtZU7ORd+7OtGVMkJYrbxeVgxCFWOs6ku36pAS3v4vOVmWMEYWyvr/syl+b/b8IGMP/BKVplijrJw9SsqU4d6n0lrWUcb7ueG8YcW0HIkKjXxvutaGznfufsq9b81XNnvHbWaA97kiwpiJCsquhbHt9kqJ5vHVduVKqVcpdeordD5ktbVmVNdRnvH8FyMUsAgh88ZcZjYJ8eT8MFbfc7MUa4pfaIVYs94Rxjz7hNJqxSuMBd6b6WjLgbjVinvHkBvUUuqrPlHvSWdvElYrv8Ha1oQBYWimDiJhrNzJ+fOv45p7bkZi3YVROca+IYUxd/ne2E178d7wzocoyHRy/c0O5zHVJhYICCrjgxSX7PeeExMEKzCuL/8gmpx7xBo3hsqsslqZtxWT6nvJ53j2uHLnKkeUDiP3vkSrlQjXYqzY4GxuJBKllQtBscDbZP4Ey5fGJynOKzY5N74zB9oIgXD6rJ6cqzgkxfLWk3PT7TR0jyGu+dpqpVVYELrXvdA8j3PmBGF9Qr7Re9X3Ym7t7kRLlkMJY3oyVuSlhbG/fKc3P3PbKVnXVd/+kPVd6NlnMU9szgtPvbvvp1R7MOMEuvdZue3sUA7j3xdizZXm5NyTVrV5qz2EznjL0x7WfPEWq5372pmwWjmIFR99Vzzsg/M3gJycA9FDiiKv2eEccj97WcS9qrzKKLedt/o8LoWxq1ScoyIvZTEmVo2Lfx9b2ZDMmyukoBJbkc+o16m2o1iyrtJeOdNFbpsdymHysd5ogYBQ3JuTfuuxB/5NjIPq19vtxVOO6Z+9gplfGTHnjO+s1T8RCWNV3/lgQpsX+Ydy1cSTj77kxJwLvOUFgJnnB6y4V/bKstExwjAUizEoV0ozPm5Cfei+pxZCQWD9JqGZ/yJu+BSwCCHzxrIQ8V7gA728d8Xmmiihe1OQ70X8D2NyrvMK4d5EtHvfPTd5Yu8YF3O5TbuU/OW77bQqWKixYpCKe1X1rQ9BrwToPUdxLidaDvqXUlfP+42b1NT+jHhy/skbvfXlDgiVMCYGAKGnDND5n9zzIlJbNgqLMc/N1kx79vh42b8z8eEfMIT5szjRchArPvpOQzRSFW8iXYyMCULys0nB3EjkUlJOQPjx73dHS6nH3FlsbGHMGt3FmB3OCwtCx2IsjjiO32LMXx5hrWlbjIXe+hP4rDWTAm+f7h0pUlaSSImx8aycnKe/dKsVPF/v7jSnk/syscm5hfFTq6DUa77oBMb1rCgY5s76rVYSyi+EsTDRtVaXPQjkilFSGFt+VbzczvuYMObv/kAATP/CEUKSyhyKup74vnQpcR/EePY5w+v8+eP5nUXcK49QaqY3/ma/ISbnV9Wtiyblzr1ZNWkV98q1Ko9Z5Moxgm4P65dHY40EtNWKuhabZVFllnmo1dqKWYzpouRF3KsVH31XLMyBbzW4qf3Gfa9I/wcMizHp1g74+7/idIbX+fMhWj3T/mFmnh9A7uCxuGWrL4/cWZy475nYw7Moy+j3C4IAU/t6sWRdJVZtv8GzmIG9GuzcSB6Tbb1ygYD4OMjdXwljV21YA9+FOND7iAeEp44MGwsEBLF6UIhFY15C1bc/hCXrKj0pbK+OiUejVUp9q8ma5yjq+jjWfClypTQX8xAbxJ9zubOYG857y7gYoIBFCJk/sZVirC8xtU+KNcqKCTAGSuaFOIxi76gBoXcmESGsmDZG7n2JVheBdue65p6bo3zMFaiMss2O5JD95r9GsVZKBNOZ2OuzGDPKrAadQRBZrXzrQ3a+rogmyyZWEayX8ZaKCBCh4VLyiboobWyfQJ5jHqP3HSh6XsSPu9RxzO20TU3OXQtCtx2FwqzdcikJjfT2McRS6gedyXk0C3YtLYQwFkbB0hNnNUE0Gdt9pzEgTO5P499/zlitLekaIM5ZxXuILMZ84ph4PzucN2LOrYgnc7CFseTyAmK1tolHf5OcGSkPt5pDYPwH3babQxH0am3FXL61SJDD+Pef1y6MVhLPddkSxpKKL/vv6d4R5A7FhTFfezs3dToSxq4rw4LQtBhLyled45AjhBQjBMZ/4AYAt8/LZPrnr2Biz0sly0v8JFlyCvc+91qczNR+OTk32oOv/YahEMYm9/dGQqkujCdjQxjT7SE0Ejv7aCsmnzBmECDA3Ehe9L0vb7bP0VOOIAiM+15p977TvSLOUaIwZhTnXO6MuO999F1lPaSY2teLwvOvlywD8WGISs4YRIk1137nQ4Z1f3z8o7ZPPCLEmso7Nzjfxe//hedeR+7AcVs0cvJUP/c5acW0+t6b9Op9btnN91P7hMXYNTvUA0KRUdS3Q72Yx+xwDpP7hDAWpQm9+QKGMLZxNZIRKtX0z/9gCWPxRQoCLaLNyRU8q779IT0Oii/coLIPcPLRFzHz3OJt8xSwCCHzJrDe2a/TvcPIHVLufe6NTpnCygt3/ixOfOEgVn2yHleukytGhW6+0edIrKmPtlvpo9LNjkxLK6Y7cUXlsuh7ZdWlhSOxPRLG3u5MOuJ5W8KYt6zR37nhHMa+cVhajBUJ/iufzGhh7CPvNM7PrnU9OT8+Iev6NrsujPMy9znRcoAB3hdIZCIuhxTqKVoYBaVe9cl64+laoL83X7PDeYz/4Hmkv6ysVozvYaYX+ej4H3/5Lpmnma/8qeU+etWaL90Kq1168g9zxmRMufg6eZtlm9qXAQDR90L7/EXe0f6zanWu3VtF3zPTwK4PIYw9j9SWDYYFoZnWLsf0z/8ghLGdN0flRJBYjrFv/CtWbq+/8A1iseHMG6ce70XMiimB2aE8cr94GWtbt3ifnAfm9TP0xP8wUrrXNSGMxSfn9j6i/84Oy8l5ybhXYp9Jy50rqgCfwHEqM+wXxjwIi7F5CCGPe4QxlZczoZ8bFnW95oulgyETP3adRtehk3tfKlusmXl+ALlDx4vG51PtSLUH8fAsYXEOg6nH48KYldjYZ3Ykj8l9mUTrXVOwCMMQY1//V69Q6i3Hz16Ou9YmMKtE6S/H+17g6dcxizGZ0qekKVdKd0VTMh/kmNx4DwDZr/8Sqa0bsFRbMfnEHfGa/vkrONU7Ii214nMD8UuLv3MjeUMYWwH7d42PqU8+qoSxjU6a+PuZ5we1xZht+RVo0UrfF/JncOI+Uxiz07gCkhLGzNVBk8b/wmIsg7UPb/WmiW4jAYIQGPu6EsbW6O2hlWdUjulfvILTR0ew/KOlYxFfrlDAIoTMmyTjiNmRHMZ/8BzSX7zVI9ZEExTFyf0ZVNzythIB4cV+kTB2m52fJ61y51r1yXpnsOQOgMT7uDCWnHZ2OG8IY+6AMH4Tm9jzm0gYs/IN7IoMxeqO/rhX8fdzI3kpjN3sCQjvlgOY2PubZIsxUgbGoMeaIOT0UupWnKyETqLEmmU3rBfpzJ/W2Ue5GGnR0ZdnEJVj4gfPRy5GyQZPQCCFsc2GxVgs76hgp3qHI2EssL9z8z6XO4MT9x3Eir96p38y5goh0mLMK6w64+TZJFdK3zlC1HXllg1IJSzGQErh/s7is3IpEWKN/zqpJufnps/gxBeSxBrZn4wfzWvFZBGljYSxYq61alIfWRDGJudWicQErZjFWEw0Gsph4gfdjsWY7/4ksC3GktMBya6UZonVX1sY87m2kNK4905pSfGLV3Cqd6isBSPUojFV3/qgE/vP/q3VQxEVB61y6wZvOhPtzmWVw59euPcdNFy+4+msvrfPFcb8/R+Q7lz7Mli3+05csXxZLI0r8sYsxoy0bhwfb8w5o8Qms8N50fe+fEtZcRZJ+UTufe7vEG9Hs8M5Idbs3lI0T/XrKSumpVqsSWb656/gVGa4LBdGYTH2orRiKr0AibYYS1jJ3GxtIu5VMVdKQwzOS4uxz7jhFkzBONo6uT+pruPMDeUwuS+Da1uL1/XlDgUsQsj8SZqc/+A5pLZuLDpBUEz/Qj29qy+ZdnbYFMZKP7G2hLEirkiAnJxbwlgy53JncOILB6TFWDkuBBmcy51xhDE/s8M5TO3PJAhjcbKyrpNWSjSxhTGyIDxGbedyZ0TcK1esSRg1ifgfCWKNgxn3quiKUbJ9a2GszBWjROwduxw+z5nZkRwmvu8RxhKIrFZK9z21lHokjCUTmsJYWX1P1PXKT9aXzJuUS4i5ITE5v/Zbt8k276qS4r2anJ/c+6JjSeEqttFnYbXiE2vMJ/+R1YotjCX9yOohRaaEMKZKFBYRxnzCbYCs5d7nF/QUtjDmSxdtmx3KJ7hSmmkjpXo+whgphS2UTu7PYG2raUmR8BuHwNg3/tWwpEi6CArrDlMYi6w9TDej6O/skBLGPmSINT6LGLFp4tHfOMKYP19hteIKY26+av9Au/etvvdmLFlficT+L/OxhbHk/q+tVvb1Og8p4v1fkf2Gshi7zlYESPnIS7hZs/mDx22xxrS6NveDEGyVFVMsWLrnWDFhLPRcreSx5pQw9vBWf3N00me/bsS9Co0kZtnl36LCmJNeC2Pf+VB0LfY9OJP7TTwi+96WDfHvYV9BVN9bbdZ1QnnUKqXqwfVivspTwCKEXBCm9meAEGWLNWKCUJ5YM/7DiyeMTfiEsYSb7+Tj5ViMCZQwJty5iqOEsRV/+a6yhbH51PV8hDGSgGc8P7nfsWJSeNqPFmu+eGvJtGFexv9QYk2JcbkljJUY0cwOG1ZMTnvwjf/Hv++PveM7jg5KXa4oPQ9hzHalLM4pUxgDSuZNihFAu2eeCzD2zX9Faot0KfG5her3kJPzEcPdU1omWi6l4vPcUE5Ozm+LXGth7oPo/Tlh2VqxuQbLP6Jca418zXIhcuda88Vb/WUw0ofTQhhbqR9SuIJFYJ3L1P5eXLH8Ko9rLexjIZDC2Csy7pVhtWK6whrHyMq6FgHhzfIaaeU2JYwJN2aVhsyXALDq+pxsD2LCuMLz+9rtaWp/L5asrYzag9NezN9wdign417dCYTSXcjrUg6rPVy1IW1/5x5DCWMZt++5/UnkoeKQVn37tsidS7exIFamk3teQsXmGlRu2RhPA/tcZ55/HbmDx2Uc0uT+jxCGMHaTEVLC0/+1W7usa+W6v6in8+ePWiVwbjiPKSkiWvdmQ1/VNR0Ck/syqNy6IbJi8ghL6pU/JIWxe26KthvHNrfNjeQx6hPGfPnDZ0FofO80jbnhvC2MeQQu04rQFcZcwcrcTwtj9ziClFFuFSZ3bkgKY9/6ULRqrafe1LaTMWvNxQsFLELIwjAursq9T0/Oky7CoSPWrHVX70PssxZrPl7vzc9Mq4WxH96JK1JXefMzyz/+g+eQ2rJRuHP50hj7a2HMDUzveVnCmHuOntfk/gwqNr9NTMZKpD1l1nWxm518Uhqra7IwnLpbiFgjnpyXFiiFS0l5QqmYIHj6nocwb1iMlW3FhNLufQiS3fsSSApK7WM+dT3nWoyR88P4nacelxNGZbmnRF13QgE7KHXJ/ENoYeyqDWuEKaApGDuTj+l/ksKYsigtct2OhLEPGe3BtpjRf8/Jvqcn54hfV41jKYuxcixbz02JvrfyE3WlJ2MhIiFET8495VX3vT/mtDAW8CHFeRE6H07uddqDwqOVzHS/LuJe3XtzlCihbaoYhKt3FrFaMfuedjGqj6d19psbkn1vd0LfC+wTyH7D6HsqP1/fhjk5v7lo/xfWVNHkPPFabOx7UvW9rRuL9n9A1rUWxvxZk4Uxet9BpLZuKBqPTT3smtrXi1OZEb+7p9suR3JaGFtaxqIYk/sySJnCWJG884eOe1xrPelDJYwdtIUxT77KitgrjCUgAsJnkvueU5axbxhxr0q0Y/FAaNg6x8VsdEgBixByXui4V18wllL3WZ8HAILAFmvM7xDfJyaMFcFrxeQbEKoJwuMZAHJyHiRMaNQEYcQQxtTS2UVuHOM/NIQxl9hk7GUZhNgph6wvExHnyKhr3znqsofxuvb9LmTezKlBinYxKv7kN2u6lMTq395XPDkfLivWinpyfu23b0uML2SiYq3MTxgrFZQ6QJg7XaZ7nyhT3JUyuf60xVjROEdR/tkkizFyXojJ+TExOfeIOZpATs6/ICbnS4sJtmoS9Hgvlqxbbsd6S5igzw3nhDvXD0sIY3K/MXdy7imvYvqfXsGpo8PJgpRVDunO9c0yROkQOPmT4rFWTGaef71sYSzMiRhjljAGJK6kR0rgiEZiwuj5HZy2P6ssKb5ZRKwB9D04inu10f7OTCo/W+2hxP17diiH0ZYDtjDm5u8KY0ooNb/zHCc2OU/o/4qxr/8rKu/caASldjD2j+57Nxft/4AQQiJXSj6kuJBM7evFsrp1ZYs1uYPHS8a9UozedwiVUhiLL5QQL8epzHCZ5ZAWYw/fWVZ7sIWxoOi1Mn+whDBmlSOHEy2HjJhzPqJjTT3ei6UbVutzdFe6Nj/PDucxLd3aiYACFiFkQajbT/abh4VYY04YfZP0EJj++e8jscaXGaBHbXZA+DJuSj5hLIFTRyNhLJRij3lsk3m79z2eAULXvc8WyNTpRsLYXVIYC6107uMVbTFWd13JcljCmJknWTihdHNoORgFz1e/kxx06zgmSijdJyfn2qVEfqfdnqIGMTuc18JYKUs8hJEwtvQdqz3fh9ax9JPznTeXzFe7lKgJgvm9Lnd0HC2MJVkQGueq4j2klQWhU39mDJdzubPSYuxdRl27eRt1vT8DhKHtzkXOm7nhMiwpFKYV09aNJZ8QR5Pz0hOEc6bVSpmr94kn5/XJiVTfG8oZcY4EiRObEBj7xmGvKO3bR1iMFRHGDGaH5jE5D8WqtT5hzA00T+bH3HAOuUPHyhZKT3zhoLOCWHLaqcd7/UKp85OF6lq890Ws/eHW0n1P5j1fq5XV9zrl8DT7uZEcTqiVEouVQ4nS0mJs5SfKE0L0fa8Mxr4uRekyAoCT8lFiTfFVJeX4fDiPEy2HsGr7DWVciwMtjPmtqG0xa3Y4j9zBY8WtmIz0J1qkxdi60gtXxIWxUF4rzRUHRb5zI3lMSUvGchYImNrfK10pXfc+M19xrqquo9UM3Wt2qD/PDuXkolR1JeI9Li4oYBFCFkQAERNKT86LEopByuOZSKyJ5aaSiou2Fsa8Vkyu1Yor1iQ8yoQb92qFfdPyDPonH5+HMJZoMWbnG2A+wpiIFaEtxj5RH8vPjtHiuFLSpeSComMQuC4lktAQpGa6B5In505bOzd9BidaDkQThCCIXi5BEFmtfKLen8ZwX5kdjk/OfXmqv0IY24irNqYR60tOufXkfGeRybkaiI3kcHLPb0S8B6vNO31QHuLknt9IYcxZHt1jMSlcSlRAeDO+SnKxSBmERlDqJCsmANq6zpicByUG2lqsKWW1Istx0me1kkDU98pw75MrJbqT82g5dZuYxZhZTKd/aGGsTCEk+023rpPrcD7CGCkfYcV0EKs+UVe2ULqsbn15i3PMVxhrOYjKLRvLLsepo8NllWN2OIcpKRotKeJGpZjcX0QYA2C20/zBY1IYe29Z5TjRcrCE1UqEdqUs4xxJ+cwNC7Fm3e47rZVU49dw0Tim9isrputL5q3aQ7IwZo9dT7QcxKrt7gri/vRT+zIeizF7PKzOYS4mjJnp3LUwQ8eVsvhAQgljZa2cOZTD1OO9Tt9LelgixnpWjDGd3+IWsihgEUIWxEz368gfOhabuMYv8zIW0xcPSKuVUk9JhFizZN1yrPxEvWPRrgKdRkeZHVHCWCTWuLciyCcsAJD91mHDiinJTEOkjQtj9vcmsyM5jP/wOVR987bYZCz0vBcB4d+O5R95t97uL02Ime7/aQljqi7cXENA17UpjIl5WIDFfsM7HwL4xBq3TgP9V1gx/cawWnHrPrD2F6u1vQ2VW66HbeUUH6wo9z4hjAVG+7YHZECAc/mzUhi72S6HFscCIw8xIBTCWF3C8aN9ZkfUk/M7k+vCaHdaGFNBiBPrxIj3YF5flHBlna94GmwHAA+dPMlCidwc6kukDDE7ZE/OY9dhO3kZViu2u0VR9z4D4c71G9u9L6koYaBXSoxEabOd2e1fWYytLmNJdy2MFbUYs88xLoz5C54sjLG9nxdywmi6GBUjf/AYcoeOxVZ09bEgYax+fcKk2AkvMFRcGHOFCG21UqZoJKxW6oukEu10bjgnrFZat2JJORYxj/eicuvGaLU2p9Tm+8idi4LthSXAaMtBpLZsEKtKGgH2Q/NeawTPP5UZkfH5QiQF8EcYCWNrd98prJjcsYo1wBeLIKS2bBDXYj0GCvT35vvIYqw++k4UWp8XwkAESx/Oi763vd7z4Nopt2ExphfFgPMyzlkIY8exdvedRl5meYzynwNOfOEQUndsiBZMUOfvnicCTO3P4FTviDhH57vFDgUsQsi8mRvO4eTe36Dqm7fJJwjyZgdAiEzmZBc4ufc3qNj8dqTuuN7argUpSYhAizXX7HyvTOF7miJeyopp9U6xQlCoUwSGGBTtP6Utxm40nq7bL7Ff6Ahjy4zv1EulF3+z3zyMyi1qch5tt89VLZ0thTHDck3dUAOZTh1ndjiPib2/QdU3G41zVJPD+DGExZgQxlQegTFQoEHKwoiLNSb2bwAoSwrXisn9vQResSYhbyHW/EaKNeZS6v59hBXT24wVo+T3MbU0cKxW3DLbxzknA8JHwlhCXVguJaa1pptnlPfssFq23hTGjMGdM7HJfvOwFMbWJJaXzJ/CweNicq4Gz+7LaEezQzmc+IIxOTcnJp7X1H45QfhEPcx2Yu8T6rz15Nyn9JvbzhnCmGsxZrYfXY6MEMYs11pHAJXbZoeiuFdLklxajXJEovRGp9zmxE2co+1K6UzsnLqOhLGb46611nmS+RFi6nHRHiI35DDxN55TlhQ/3CoezMV+M/OzIYz5FghwXloY0w8S3Fd0Q58bykd9z11NWb60EOH2vWJtGCrO0TG/W7t5H5Gv0ZaDSG3dGF+oIOEaIKxW6ov2f4TA7PC0XE3ZWRnPPQaZNxOPvohlN5hijcT9jQGcOT4uxZqt8euMrv/o/jt6nxDGot8s8LchBIZ7X32UTxAfSwByDrLnRaxtvdNuD6F9fTfPUQtjAexVDx2Exdhxu116+gYg+seocu/zWRGr+gxk33v8qCGM+coQnae47x2P7nsxwW9xX+UpYBFC5k3+mWNIbbkeS9+RRiCfcIRhoIUSJcWEITD9i9+LAeGnb9bbAZFevAm0mKSFsW80Ysna5ULMCcXNJjpO9FLCWOWW6+UNKbBvZMZnLYx9+r26FGZe5n5h7ixGv3AAq3e+V4sEoZFn4NzMJh8/YgljKr/oJhno96YrZZC6SuZrllnWkDxW9ltdqLzjeix9xxqIIWhgnZuea4VA7hcixtiqT98s6kw/rTHPczHf8hbO1P5ej1iTlDYTj3uVwNxIzhBrSmOLNcWZ/sXLpd37JJHFWNyC0IctjBVHBwAvx51LidILqWtyQVGiUTwYtLp2q0m0Mzl3Btmui2v+0HHknjmGlZ+8UQ7sdUJYQ/JAWDKKyXl93JLRvG5LSz/tzqXaQ+jkG0YXzdnhHHLPJFit6HOIhIITXzgQ9T3rOmqXGTAsxnbeFK8DKz6dYUFoulK6FrPGPpHFmMdqRabjVX4BhCIMgN0eglj7VWlHv3AQqS0bjcVrEoRYRELpqk/cKL/zPXQQzA7nDWEsoe8Z+U8+nvELY24rCEPkDx0zrFYSUHFIh/NR7B2zHG7/R9TmRd+ri8rhlll+nh1RwtidRfu/IopzZMQiivV/shBmnn+9ZDw2QFwvs1//19Jx0CQTe16MxBpFws8khDFP3KuE8dOoFROqOFP7ezE7kosvVOBhVgtjZcScg3BrT20p5loLfUwtSpfpamw9EFKY9Rcubs2WAhYhZN6ktmzEyo/XA5DjNrldj7HlHGFOWjFd+4O7Yt+reUuA6H32W11I3XF9bHJujuXVsXL/FAljSbHPA/l5Vgpj6W80Ysm65eYcxjhIVJ6Te38thLE7Nkbldo6hxqqnev6ncKX89Hv1/iYqLQCE+TM48cWncc3O92LJ2uXW+VhzGpnP1BNHsGTdCuvG64vNG4aGK6WsayvPxXyXu0Bcs/OmssSa/KFjZYs14undxRFrZodzctUanzAWxEY+l4wwtvdiCGOc3CyEa7/5IXvCaBE9GbesVqzv3Pcq/kfGsFoxL6xqRC4v+OdCKYyZLkbq4u5YCIay7z3jibViPSWQ5TAnCLFzDGIvMTlfF03OY0pFoN/ODuWlMGb0vZibb/QARwhjGyLXWuvJij2pj4SxYm0+WNQTmwUTBLjWvU6pJ13WBrGqpCWUarMOxNKePTZhCKX+NLoNKaFUCWOuqBPa++q4V1bfUy+nzaug1MpqxTq+aeki9hNxjjYmXIvN/UIdEF70veT+DwCzQ9NSGKu3Q0q4/V+VwxKlk/s/WQAhsP6nzWWs8CvFmq0bUHHL20qmzR86XrYwNjcihbF75yGM3bCurNWUzxwTwljVtz5UMi0AJ1h6EQLh7jg7nCsv9p1cObPcxRgm9iYIY2znGgpYhJB5c+VaY7lu+K+pcyM5LdbEA+PGHkILsWZtFPcqcNKaY8M5j1hj4gwJMfatLqS2CGHMGvZ4HnBPSWHsmk/fbIlhLkqg0xZjZrwpT1pACGNXG8JYrMBGuWd6ZIwxQ6DTcbad8wvzZzD6xaexeud7rYCs5vk5w2AyT4LKZdGH0POCDIy7X7idXrnWcaPy7Df1eAapLRvj7SFEbF/19C5xFUFjPzE5PyAnCB5XJ7WDKsf+DJZuWFPapSQUTwan5QIBRc9PflaTsavesSY5X+3akhHC2KeNQW/CeWph7Ju3RXXtqYuinZgUJViu2rwjvOjqFFazkVhjXmVMkUZ+DgOc+KKyWlkRz9e5QtmTc18ZTKsVJYzd6cnbOQdtMbZRxpxzz9EuSiSM3ZhQ5ugYs0M5nPjiAcdizD23UKefejwjJ+c3+utaEzjCWFI5zDon8yWovAr+dhbVbf7QcRS6zcm5p43JbbPDeYx987AOcxBvk7C2TVjCmCsE2enPHBtP6HvuPuJ1ouWA4d7nKYchCk3t78Wp3mJ9L9pPrNaWkcKY6dbu9H/5ivrexnjeTvkjYcwph9P/ycIpR7yKWTEVYW5ExCBc27q1rLwnlDC2uQxh7OAxIYy5K2d6mB3OIfsNaTHmXUXQbj/KYqwsYezV7LyEsdH7DmLVdp8w5r/vlVvXixkKWISQ+WMoI9FQ3P479fgRpO64Pj45N7ORf/OHjsmA8NGqNUnj79mRnFesMTHLNPnEEVy5drllMab+mvPaAOLGOyWFsXKGRspibGk5ViuGMGaVNYzPr+dGcpjY+2tLGLMEPXN/ABN7f43U5rcjdYe7lLqdTuVNFkJoCyRAbE5qPzmPtlt/JVOPZ4wJAmzBJbD3iaxW7kx+emfkP7XfEMZ85TU6iLIYW6nEqyINf3Y4h1FTGPOdn3GMaHJen5wpAIQi5pxwWbszys+rBos/Whjz9T1nv1NHh4sfnyyI2SHZHj5RX54FYbntAaZ7XxmutUl9r0g5bKsVf56qHCX7nrHP1BPFrFYUSghRwliRciAqhy2MFefs8fGSacj8Udbca394Z+nJeSgsSlNbN5Y3OT90DDPdHqsVXzmGcshqYawMq5W9vynd92SbP3NsXFyLy3RrH7WEseKohxRlXQNGcoYwVjrvc7kz5RSXzJOzxycukFgTZ15WTIZ7Xzmra5/ca1qMFRlMQPY9n8WYrxwjQhhbc095K2cKYWx9gjBmD3TOyr5X9U23rv0Ds7nhfMnjX65QwCKEzB8jzoY7Jw4hrKlOHR3WQcqTnjeGUNZUR7D2B3dhybrlvuf31r5Tjx9B5R3Xx8Qa37NHnzCWlN4Vxko9wDYtxpLQy/cawpg/nc2YjHtlTs6TypP7p9/j9NFhXPPp9yZqD2q7OkdygTBFo/lMzl2xpki+AHDii65LiYMhKBednFtiVmBMzu+KC1Iepp5IsBjzHMMSxkrIwbMjjsVYMYJg3nV9cs9vSqYj8yQETv7kN2WINYJ5iTVDsj1cBGHszKvjb64wJilLlDbKMfV4OcKYIH/oGCZ+8mLJdGSeyPag22WJQcLU4xnMjubKbg9aGCs1OTf6XtnCWJmT89lhKYyV6dZeljAmma8wdmKewtjJvbzOLwzHss6xKh/7+mFpxeR5MKf2ky8t1nzkXbaFteeYMfc+X1qjLHoVwfUr4k9xnX20MOazKnfynh3O4eSjHmHMkxahDAi/dSOuvqUmwaI8Opf8QeFKufqem2L5xKzKh3IY+8a/ilVr1VjPtCJ30k/seRH5Q8c8dbs4oIBFCFkwPiOJuZEc8oeO4VrDikkZdnjujzjxxadRecf1epDiS6M+K2Fs1SfqY7dEcQyxNYCMCfXEEVzrCGNJKGFMTc7dZadNCs/4hbF4mULLlTLJYszcc0pZjElXSl++CteVMmk8rbargPBkISS3B1usKb6Pdu+zJud2OvN3tCfnAeK/cqAF5dnhEsKYdZBQT879y527Zu3zfHJuTc6LmXYF0pWyuLWmOuv8wVdlXd/oSWUfQ9X1ir98d8kykyJ4Bt16cv7xev/g3ZwEqcn5D9wVoxC/0J+Tk3PXgjDhGPmDQhhLdK11ypH9lrRacd1OY5MPp+8537n7aWHsB3cm14V6nZOi9B0bI3f8IuWOr4zn1JmxTQlja1puAVkIxjXE+S2UWLP8I++KvjfTGe9Ve6j6xm3F25l8aes6nzu0k9bqe7oc/nIrV+u1P7wTV6SuirdjZ5+Te0Xfq2h4mzc/86Xducy+56aXWMKYr807x5rYI4Ux8xx9x0AkjBV7mEiKYLoB6EGnEE/Gf/C8tGJ6OyxBRaU1zPynf/GKFEqdhSuMFTDNdinc+26WgpSR1tMuImHsnfH8dLnFtjM+izF38QOjv9gLFTjuqU45tCulWh3UxHmaPzc8Lfpe61bhmuymN3cMDYsxJUo7iySY5RfWmgNYUYa74+UKBSxCyAJQQpG48Kq/c8NCrFn18RtxpQyW7u5j3QweP4JlN1yHlR+vF5uLDPqVMLb2B3f5g7Ab+4awhbEAgc5fCVPmMrpTjx8xVghS30c30sAou7CmOoJrv3+XDsSujh1bmjcUKxQmulLqMUOIAAEKhsVYYNygQye9qmvbYiwUpUwYEE49XtpijJTCL0hNyCfnSwwLqTD2r0BNEOzYO9DporSBIYzdqFOY35vH0i5G0oopcawk0/tj75jHjwZPsyN5KYzdZaWF6lewg0ZHwljxJ+chRP8Qwlidd24VlSKwhDG/6AZdHsCIMVZqhSDix50YS1Tsnapv3Jawj8E52K5vJSbQU094rFZ8aQMpjP1ECGNXVF6FoiuRnXMm58XSBh5hrMg5zg4bwpjPfdhh4ieu1UqyVWVMGDPK6LvWa2GsDKsVkoBbr4G4Fs/0GFZMRS5Wuj18uogVkzk5d4UxeUxfWWJ9T5cjjJcb8Fu2+sZZkMLYiOx7ekVFfz+ZHUmwGEvo1zFhLCGdruvu16OFChL6P2C4UiohhCwQVyQJMbW/FwDEGCG2UqTpIyGsuXNy0RjdHkLjh3J+w/EfPBeJNYkxKsW+kTBmWhB69tHC2GGkv3hrFI8tttJtVLYJuaLr8r98t0inRSgjf7mKlBJKq77lue85RTqXPxutlGhdA9y6E8eaeqLXuO8FRe9Pwo35Raz94RYEZcQYu1yhgEUIWQBisBTKi7z6O/WEEGtSVuydIEprDJwKh44h/4wxOQ+BIAhilk9BEGBOur6t+viNkWgk9zEHYLocj2ew7Ib1Iu6VPHYkXEXlUHnnnzmGtd+/C2EY6rSBtcpNdIwTX3waKcNirNiEbOqJIzithDElhHlErgABZoenMfnEEayVwlho3kAdEU3VdeUd1yN1+0YjP6PcIRDIp1qFZ0RdX/Pp9yK+fDeZH2Lwoao8Eo1WWGkCY6Ci3qsn58K6LrTyMUVhJdaICcJdUpCyB4xwjqYmCKk7Nhrj+8DIW5VbCKW2MBYYOdnnJ6yYnsaqT9RjybpKuT3Uf926mbSEMTOv0Gn6IgB4/lAUhFgdOzDKHRjnHblzuYGCozTqTCZdqxUyfwLEJhezw/mik3O3qpVYY03OE4gm541GGQL/+3PAiS85loxFgvVPPZHB7AlDGItNUKITiISxu4pPzuU2r9VKAloIMVcRVMvyWvmGxYUQZz4GOMIYL/Pnh/F7zA1NR0JpqoRQGgLjP3xOtIdy3fvc9gB423KiUJqAFsbKsEA9c1zF3lHCWGj/VQTRtdjn8u3rIpYwVoLZ4WlbGEvq//JAVt/jYh0LRAk30b30VO8IcoeOYc0Xb43SeKs3wLn8GZz4wkGs+Mt3FVm4IsrfEsb0dsB3P58dzjvCmJvGTj/+w+eR2roRy+rWO+V2x08Bpn/xMmaef10uzgFrHG29Qhn36pv/KoSx9e45xl+T+zOouOVtsu8Vr48zxyaMvmeO8+NlDnNn5eq57phz8UEBixCyAOKT6aknxIRx5cdv1NsC6+YR7Tcn3fvWfv/PjRUNAy0gmWnD0BBr7rjee2wzvRBrXjXKEei8XUFhdngao19SFmMrrLShUW6179QTGWkxdqNzbLMUYrsSxq79/p8njgWj8wZGvyQsxpZ4VucKrPK7dW3XlXXjC6Dr+trv3yWfUHKQt2BCRNZ/oRCNlt2wHsv/4t1y8BO1Ces3DyM3h6pvNAphMYzETKUTBNqMHkI0+qRhySiPG6jfGVFZJh8/Ip/e3Sj7XIAwNPqgUf65YUMYWxstEGDmp/YTwtivhXvflutlmQP9nfqsypU/9Cryh45h5cdvlNsQ1UsY7SMEWxWU+kYsWbtCHzs0ztOsx8nHj2BZ3Xqdtzpu9HtA99nZYdNaM2ngTUpiXbvF55M/+XXRybnZ3hIn54j/JLZYY1jXWUJ+9L4cYUyljty5pDDmLkJi3nNCIUqv/ES9UQ7f5EMQE8aKYFqMBW6co5iFQCRK23Ud2Ocgd4vVNdv8+SF/j3PTZzDqBs8vIZQiQMn2oB4OTD2RiSwIExHtcrz1uTKEUtEupv/p5ciKyV3G2KF43Ku4sOq1GNOp7fT6vvdN22olqQZPfOEAVn4yoa6deo/HGKNqu2CMqp0dyWHiB89JK6bSQmkk1iRdi6Pf5VTvsCOMJSOEsQOGMFacqf0ZICzd9wD4LcaKkP3Bc5EwVuLaGgljZZRDWhCmv1BeXZ983KnrRXydp4BFCDkPxI3p7PFx5J95FWu//+fGN4Fp6W29i8Sa5caTH/XXnizogPBarLHzMy005kampVjz51IIiqc330785NdaGEsqq/pceOZVQxgz09nWNiGEaBQJY5FAFxj7mOc59cQRXK2FsYQSBGL/uZG8U9d2SvN+FobAiS8pV8oVlihH5klo123+0KtygvBe9XWUzhlUzI7kkP1WV3yBgCASr8w8Jn7yayy7YT0q/yIaEJoik/n37PFx5A8dQ/objV7XWlPcCQGMfvFprPyEsGQMgdg+gbFNCWMrP15v5+vuExiulCrmXIDY4Mos+4QWxjb6W6Qh7qnFGOLXAFhW/4BcKVGdoxNXj8yX6EcMAUxq97747wDY9Tw7lLfd+zw5631MKyYt1rgPJ9TfoKgw5jI7lEP2244wFkbWgOb9Awi1MLbiI+8yrAXtd+qvFecoVlbnfRjgxJeUMGbHvotyj/KefOKIFMZudL4Lteim9ou5UpLzRtX55BMZVGx+myHWBLHfS/2Op3qHkXvmGNZ8wZ2c2w/cQgDh9Bmc+OIBLP+IabVi5mtfFaeeyADwT85D59PsUA65f3oZa3+ohFIldjoiqUQJY1c3vA3x8YnZ7gNbGCtajqCoxVjg7BMishhb8ZF3oVj/BzwWY+SCMW6KNSWYl1gzfKGFsQgtjH2pDGEsd4kIY0qUnk9dd5dX14sBCliEkPNibmQaY9/uwjWf9gcpdyePJ3/6a1x9w3VYJSejxay+lTB2rSGMFct/9EtPY8VH3m3dlHyTY2XVdfa1Ce+k2EUJY2u//+dlneOkYTEWFEkHIEEYi09owhCYHZnG6Jf+BSs/fqO3HK6dwNQTRwyLMXJemC4lI3LC+MO7LEsKV7NRbfvk3l8jdcf1coJgf++2idxBIYytchYICI0iqJLMjeQw9q0uXLPzvVjqafPKCkod4+RPfo2r664rabUSBJEwZrlzGWnc8zjxxaeFNZXhWhuf6AmmnjiCOUMYM9OYE5sQKtbKr7UwFiuLc5yTe39tL8ZAvfa8COWE/XTvMPKWe18k2Ku/6qHFuekzOPEl0R6UZWto7WML+JPaiulGnTb+EmlntTuX6Ht2XvZxgjDAyZ8qYezt9nf6wUN0jEgYe68hbsXPFQgwZwljK6w00SvU+0z85Ndycv5uIx/oskQCRoizr47Lur5NpzDTmq62QahcKW80YvCx0Z8P6ref/sXLmOkRLkbmbwrYlkZCRMxj/IfPId3yfud3CBC5i+tIlZYwFjrHDXVacaRTvUNSGHs/3D5ni7CBsBj70gGs+Mi75eI15nED4xxkOR7PACGw8hP1Om10llH/DyDc+3K/eBlrf3gXrqhcFitLAFPcC6Ur5fWxvuf2/xBA7hcv6wdCxfo/IN2YvymEMdtinSwI4wasxRq1OIeZJrTfa7FGuXuG/nQK5Vq77Ib18Xyd/bQw5ltF0FMOSxhLKod8aWFMrZTo1oXxsizGiuULRxhTizEgOf3U4xkAcBZj8JwnYInSV6SustMvUihgEULOC2XFVNHwdmu7e20NIMSame7/iWs+/d6S1965kRyy334Wqz/93vJMa6Uwtvwv7HgPvuOcPZ6VVkx3edMGzt8TUhgrFZQaUMLYeNnC2Mmf/DpRGHNRdZ20kqB5z8s7whiHdxeGAIZYY7jgJdXv1BNHdNyrUvlqYcyIvWOGxzEttQIIK6bKO65HquFteltMRJN/Rd97Hdd8OnpybpU7NCcIkTC2xCOMued6UlqMmcKYry8FKC6M+fZzramKoerafFLKsCjnSQjMDeUxISfnyqXVdKWF/Kus/cTk/O1YLi0IXdfXwNjfEsbCKK2SaITLqWgPQhg7gJWfkJatoRBwVKMJY+WIXGsRqvygv9fuqvIcdd9LXRU/L0CXBaFaKfF6XO3c96DrJHrlD70qhLFPvzc6P7cMAMIwwNxQXgpj79WutZDfudaSYRi5Ulb+xbsiUYVtfuHI32d2KIfcP7+Mtd+X12LHDRpQv0kAnAPGW3+Fyi3X46ob1tvtDDDaZBBNznteFzEIVZ6I+kgA6OPNDuV03xOxMd38AqsdTT6RQWrz2532YMhthtv3qd5h5A8dw5ovvt84tu55UUiCMMC53Fmc+KJY0VWVI6n/B6GIhQgIq5Vi/R9hgLnhvJic/+AuBKmrEvu/2mf8h7/SfS/W/8k8ie7QM8+/Hnfvc4QUNdCIuff5hCDjvWXFpAYpvt8rFA+tLGHMh7Hv+A8MYaxYORC51q50FwkxyyOrJHKlfH9yDELj8+R+11ozOX3MWtMUr5yn3uekteaKj7zLXsFzkUMBixCyYCJLiiJijbzQzo5MY0KKNUWXlJXbJ37ygrRaeXtCwggljK369HuTE8l854ZzkcXYWr8VU2j8PfnTX2OZRxjz5a+EsfQDt+t7UFzIi+5Oo196OtGayiVW18YN1xUU5kZymJR1feW6FWKAW/IIpChydKzc+1Y4Yo1vPOaKNW58EIUWSr+orFaKD5YCiMn5nA4Ib48JTWdVQLQH5d7nxt6Jxk3RQUxhLPCmjSg4rpQuZtpZaTG2eqffWtPdr5TFmFk2s67Z1i8goZicp7Zcj2V162Pupu773D/9Xk7O68Xu7uTSuBbNDYvJ+Ro5OUdgWMyFzr5SkFLCmCnmhohEILX7qaNSGPt6Y3RM8zpoHOtcTliMrfx45Fqr7wOOeAyIcpwrnBGLhBjli+LHyb+BOMepJzJCCFl+VTQRhzFfMs554ie/lpPz4gHAw1D2PSmMqYW2jFCJZCEEkQXh8r8QD618YZjM9jb9j0eAAFj58fpowTNPuwFEe8j/88v6IYXZvty8dd+7QwhjCcXVx9J9T7oYueU2P8+N5DD+w+ew5guy74VOOqefTz4u+p7Prd19f+rokBDGvvD+ov0fAML8GZz44tNY/pF348r1y4v2/wBiHAQg6nvqFYLWtgtCVLIKnl/1zdvs8YevUkPg5J7fJIs1DjPdjjBW5AY9b/c+QygtRcxizIdafTMIDGFsXcm8I/e+G6N8AM8EIIgsxloSXCmdfSYfLyKMLWIoYBFC5k8InD0mxJqqB263Z/DuS6ZXMaGWuKa1ntm/Fmv+txut7wPPPnPDOWHF9L0/l0/O/eVQMXkmfvoCKm+/HhXve7u3DHoyAsNi7K/fGy+zs69ypVz96ffhyvVR4O14/iJzy2IsqT5CVdfClbLq67fLegiiEaM54AxVXUduhmFsplfmb0wcAkz/0+9j7n1JopRy70t/4f2GWOOv/BBi4lqx+e2WS4n5vYl6cm5aMVmTAvkpRDRBWOWxYtITaGOb6numO1f0TD5+jhM/+Q2u9QhjvnNU7n1Jk3PzCAW1lLplMWaXQZV/TsYYcy3GyPkzZUzOY/HVYAunc8OR1Ypw77Mx5gbW5Fy5lJiWXe6+U44w5iOEKNDccA7jP/yVducyL686rTFB1sKYZ4Lgxr8+1TuE/DPHsKbl/dZ2u/8JhDtXJIQkXXtVWab+8QhCQxiLlcHYNjecw9Q/ZqK6LiJWkHkQBro9rHDagyvYhIB271st20NkTefJOhe1hyvX2TEIXevWEKrvBbrNaxdy+/aPMHT6nnQxSioHIKyYKu+4HlcnCGPmbuq+t8Lpe27/B+Q9QQljbtwrs/9LlDC2/CPvKtr/Q0hR+pBypfSUmW1+AYgfI/vNw0ht2YirNqwxtgdGpUY/2vQvXsapo8PlxSCUqynHhDH4Lodi4Ypksca+/8eEsSKcy0srplLCmDzfqf1HALjCWOAt9+xwDpOPZ6QwthRmvcXOMQxl3KvrnbhX/nHk9D+9bIjS5lWCai0FLELIvJkdmcbYd7qw+q/fV9aE8eT/6XfvEwTGu0DHvap64PZYSvGUzb5wj345OSaUu+/UPxpWTJ7rv5n33HAOEz/5Na79nrAYC9ToS2do7zvx01+j8vbrcfX73uadqJh5F56NXCnNc/eWY2QaY995Fqs//T5tMRb6RngSJYyt+Mh/olh1AZkbmUZeujlckbrKsLoI4+0ijCYIV/3p+ki8ROTGZL5yv/h9ZNYeRml8aeeGcxhv/VVktQKj7XhE1snHM7jacOcyv7dWCQ2lO9chYbUSIloRNFTnaewf5s5g9IvGQgVelSA6zpQREN5Ma52jfK9F6R9EkzGRPDTKHOWvYoxVqL5XSgEkZaHc+9a0vL/kcNmcnCddi00rDCWMlfPkXFutfD8ulLr3g1C5cxWxWtH7Qk7Oe/yTczOdEgnGlcWYWiCgSNuafOIIUoYwVqwZnj4ar2u3zpOEMbcOfPuScgjFtVgKpbE2YKWUY4TW51D19UZcuW55EavryGo2ZYg1vt9ICTwz3f9Ttodocm5aJFllcfqeOl5Se1NWTL6+506R50Zy2r2vnAUCxn9oi9LWuTn3CCWMlXKvB5TF2K9iwpiv7ZP5EGLq8QyWrFvutHn3Rirem2JNObfVsW8eRmrL9VgqhTEzV2UnrrZN/9PvHWHMdwUU6WeHyxfGQkALY5XGYgzxsxTb/MJY1KPMfq6EMbFQwQr9jXuO6jX5eAZXVF6FlR+vs8pgl0Vsnx2Sda0X5wiN3DmooYBFCJk3hWePGZYUxQcQ0//8+5hYYxPqQcjssBBrrvnr9xqBUJ3UxoxBizV/8Z9KljkmjMk4FuYAyMx79Mv/oifnQRDYE3gHSxhLOku5v4hzJCzGrMm54Xeg0gYQQYi1MAZ3wGbXT+GZVzHTIyzGzPImWQmR8pl6IiMmCEo0cgbOIq5NgCAI5IpRgXQpMdK5QhDkBOGfX8a1xpPzSDiy0wYI9ORcTxBMMSgIrN9aCGP/Uy+Y4I57zOPMjeQwIYWxK9evcASpILa/irWy4iOOBaGTLkCgrVbSXzfiXunJWNT/wzAUFmPSnUsHxzYEPMuiEEaMMW21YpbVEZ3JvJh84kjMislnKaLSphKsmNyrj2nFVOrnCXO2O1eUp/qd7Ry0xVjJmHPClSNvxDkyn2ubZQ4BBCGsvudeUwPnNa0txux7gu98lcXYmiIWY2aZYnWt7xfGdYkT+/kTAvlnjsWEUhWc3E079u0upO6wJ+cJ2er2YFqUuvKA+sVmh3KY/MlvUPX12+NWTO77ULhau0KpK74pTnX/T8uKyXfpVn/PGe59qhxJ/R+IVkp0+55PhpgbySH/Ty+XZb0LyAdCW6L7XlL/J/Mnd+gYrtn5XpgLRKhXaPw9lz+L0ZhY46aPRJjJxzO4ct1yrNILBJiovMVvOTecw+R+IYzBSqsWNbDb2ti3lMVYOnZcADAXCpj+xcs41TuMVTtvNs5PHdk8T7FAQCSMmYtzhHDPE4hcKVNbrpdlMBc0sAWqGdn3opWrzeUUYJQFODd9Fie+dCC2SAitsCIoYBFC5k3q9uuFex8A93mK+XduREwQrnXEmghbsBnf/SsnIHzSEB7I/fPvI7EmIV/F3EhOCmPvi7lz+YQpNyC8ncbOW8S9OoaqB+5w0vhvLifKshgT+07+4//A7Oi0IYwFzngtqvu5kRwmfhpZjJl5hZ4aIvNj1affi+UfiSwIQy3sBFrgDKEm569idcutiH4vd3orBypSrFn+kXd7BimBnIwaT++eOAIg0O59Oh95jMhSKtDCmIg5tzTK01OOIAgMd67rPGVWiM+5fxLC2IqP32gMGp085d/ZkelIGHPOMXDKL85RBgD/yLuNtu4v+2kd5+h2p6zm9IoDvYWypuX9MSsmn7jixr1yMdMKC8JotTbfr2OuEBi1ByMoNcTgP4A98Tctxuz84nmfy52OWa3Ayi+w9pn8xwxMdy7zmmquvqasAyJhbKm3TvS+jjDm1oOJKYSYFmOWbpwgfpMyCAJUfbPRag+A+1sLpv7xCK5cu1yu3mf/VoHzy80N5zAp46CVKIAljEXuXOaxzT4gHhCe+t0wVn3a786l+ggQuXxXfaPRK0q7+03s/bWw3vUszuG2rlPdryN/6FWve5+b1ox7tdSpa3FsO7C9thgzHhD6+j+v8gshwNof3mVZUZuunCrgPkLg5B4hlKbuuN4KzG/HbguAMIjEGrlwhchLfGfF6Axl3KsvHsA1O9+LK9et0MH9YRxb7ReGIu7VleuW2w+MQ/EAMSqD2Hd2OIepxzNY+4O74C54YJ5jIMuf/VYXUluux1Ub0lYaczEP9TmnXSnfq88FoXEtUOMaWY6Jvb8R15e1y3V5IReCMK0TAylKVxh1bV3OjQUTFvPQngIWIWTeRCa7vqcCYkgR5k9j9Mv/guV/8S5j4pq0TyCenIfAyv/tf4l9bz81iaxW1lpijTnJNQmEMHb79ajQFmNu3tH+0/8sn5T+9fucssYnyEIY68Jqy2IsPuFXr5M//Y0MQvxuK5/4Pspi7Ji0GDPz9Q3ZQstizJ+eE/nzQblPuG0RiMSsuZFp7d4XPaFMJlqt7d0ybxtz0HL6qBLG3o/ic1PR95Qw5loy+nadfFwKY0VXzlRtfloLY8VcStRxlDB29Q3XJaZRTBvCWPzIjhBiWIzZLiXmXmzv54O7JLnrvhkgwNyQnJx/z1xBLLD20YP7c2JybrrWxoJGaxEWmP6FeEgRBUsPnUF7ILcDc0PStfa+98fiLEb5CzE/DMPIiukv3qUnL2b8wzCM3FWVKL2m5dZYHZjlBYDQce/zxkJEtP/kE0eEMPbxeqvedL5Geu1K+b27isZ7FGfKtr8QVKwyt02ak+JT3a8j/4yYnEdtOLR+Nz3ZlQHhV3/aGCP42oPcb+oJKYx9vF7nabY58zhzQ2KBgGu/d5eVzmxHZvsb+5boe0vfscZpZ/HyTP/i9zh9dBjX/PXNRfs/wsjlO/31Rly5bkVy/5evib2/thZjSOr/CCOrFREQPrn/q35L5o9e3dJUOyXq49QTR3DqqC2Umm6wZuw3tWiMEkrhZG0JQxAhAK7e/HZU3rHRGtuot+ZCB6YVkzoeouYSLaIAaKHUXDTGPL1ApZf5TD1xRLhSmmEOPGUA5EJJj2dw7Q/uiglMMVEvEMJY5RZblNbnZ+wHSFdKQ5T2LWzgnstihAIWIWRhhEkD5OjJearh7Vhuuff59xGT82NY0/L/8uYV6n/ETUkJY0ssYcy9/yph7H8AIbDy4/8L7OMbeRuT87wUxkrHe4iEMXelRN9ZTkuLsRUegU78awp0Mu7VX79XnKN1p3LFKyGMCYux/+Q5R+OzHFyQhVNs0BBZUthija895DxiTZiQds6yYoo/sXaZfELFvXp3ybTCikkKY853MUEtL61WPhKPc+Q7zpS0GFupLbX8BFB97/e41iOM+fY1LcbMfHzi3pnj2SJHJ4kE9gfXffPc9Gmc+PLTlsu3mLwbgo4xmZ/6xwyuXLtCWhCqA9jXJ8Xs0LQIUv69u/Sqtco9TsQjDKwJ7dh3ugwrpiCWXyBnNkEYGBZjN8oyOidsiAU65tx978eVa1dYwpbrHowQmPzHjJ6cKzHPdu0VZUco+96zx7Dmvmh1Lm9MnzASQpb/xbuFi6+Fc08IRfBksgCUAKjamimSIBJrqh5odB4OGA/F1L5hgImfisl56vaNtjgDo03I3/1Uz+vIP/v/Z+/P4+QqzrNh+CokGGlGM1pHmCUvgu9FwmY1i4QwNotEEiRWPzGLnS/gPU+cOMnj2GbfwdiOE8e72UnQzvMZ0EJitICN0S4BEgYJHoQ/G6PpntHM9OkeaaTuqfePqrvqruWc7hmJvP5Z59KvNd2n69SpU111qu6rrvuut8xuyty1Wv2115DlvSjovueGOYiHO1DEWGuwQQAHXc8oxr49i38b9H9y/7aKsfGZ/R9QG6H0v7oTo784FVn93xAhmhgbNnFUev+ncyp7U+8tR3141WnbQ0cZlZ+/pVRMcIcFTsLQ++JXn1VEaYSs8c/v1cTYmBQFIZWLytHzk3UYf/sMs1usUwbhkmpEjDVf9H/H82Xv9zDFGC+kTy4B2gb56rMY8z+n4VDPtZbKwY/1/sdmDDOkNEvHykEbM3C1pu3/brl5rzmY5/M5gZUjR44hQLhPX+m+V24Ov9FqKpYm8qp1JNj1L79wV85lJF/9t/eJlzFy+jEYdflJQTpfVkvE2NivfCw9X1q9K2vF2OUfsitS3vXNIKVXayC1YowGTcrLv8edZWWc3+/tlMjy5teLEWNq0ApXb6muR3/h7Oh98bLVOhIUvr4MOfYPaWTNIS1N0ThovjmhVEyKrBnWQPyPLm0g+MRYrFykYiI1VRZxpIixXxhijPJIKzcpxmIx5/y0pBjz3bliGKj0O7tz1YPdSt3WdWTxGIBeKf3p2rp55ohAAj7ZbhSI2jgfec4xaLnoeIegEeZpJcz5yjh/E2P+eipzGYU5h79keS+KX3/WEvh0XJ/nu5Yqd65Wr+95eepzqzsT9M5RqhXl1u72ZlN2oVw8iBgbccoRmmBmJIJ0r0PP4jHaODf8mow8A3YqBeGEW2eae5RBndt67J1jSWl+f069C/W3/9Wd2PUvLyLHUCG8Niq0ganaA5E1/vdmUUyfW/rZVvRv2al2MXaILrftCwhU30vQ/ZO1mHDrTBzKY//x9kjXkCrMQbPue7Hy8tee1UoxphQdIuWl22lFKQjH/PU0He8xpf/rV+9/qL43moU5iPV/QCmUS0+8jInfmhXUQaw8XaTWpDhHKf2f+l7PT/Ln/P7CGf+lio1Z/OqzaOO7GIuYDl2h9MRmNJ3yAbtzZiQN/Xw+MVavPESMNXmutZSO86vJEy9nEmOcmCJibMLtM8z8I04aqfvu/jH1vf+biQFtSXk5iBjjO1enlX2g7Kk1pTTlFEKYa9DUvvTEZlSeeys13z925ARWjhw5hgBpn6LsEKCVFE+/Zt37sixoaNXKzOPRdHLEOPdGP4p7NZqIMa9IHLWdmhj7x49i+MSIUSzd/HvnaGLMN84ZKUQkU/+W91BZ/qajGOOrQM7plX4Ub1iKUZdHtu/1CTqExBgnuMIA4Kqu2+9nqhW/voUdUHf9q6rrHPsBbozq32fP6t+g8tybxqUkIEr5uTr2TuunlLsnj33gkJ/6WOmJzRjGjfMIQapIShWUuvTEZhtzLoUEppchxk4+wr0+XELWEKWaGHNW4v171RNCZ6fEFGKVXoaUpoDwrAz+BNiQ0v/roy4BHSmLMsaWBQrJHI3DNSntT1l+6jX0b9mJ0V+c5qTlaYyhstMa58MyXGupzfWQauWi46NmP3/G7ln9G1SWs5XzqMmky1O2ijHXxdcsD9iyS6CXEWN+E/ZR26kUY+3f9I3z4A5V37vbDQBuyhg5yxJj00zZ/PRkBNV2KjfmMV+ov8V9jvrgrkC9T4TtwSZUf4wyYicpCF0VU+QUSN0eSLUSmRY4bkllinv1xXSjmFDr0H3vtpl13NpV2SggfIvue2n9X8Ab9yJpnPLrRYoxfz0tNf4nrx0a94gYS+v/dI+lJ17WKvsc+wP++wJA6T82o/mi49GiVUzqORPugycB9D33Fio/f8vZuCJt+l/rKKtdjP+/6fFgBfufE2OxPPmxWkcZ5Z+/mUqM0XOe2lTxq8+aZ3FaedX9Ktfz/lcjMedM/7eNk8eciy3MOf1Eqr7HFWPOtMpTNhIpnaYuOxiQE1g5cuQ4YFBkjVUx1UNp7mYAsEotAp8J6ZGm1lFGWZM1De1ao1VMmaoVNiHkxFjWBk61jrKrGPPy8ldueue8jBERYizmKtL/qkuMZZVDVvpR0HWdqVrR5XFjjOUYNCSbYLOZRa0jUS4lt82Mt3mPVOn+yVqMnK5XzmMzfXbebm0gjP7iNAQzRg8DWkE49q/PbowonaOJMdqMQbjpDZGl+17pic3atbYps8wA0HnXcktK+1YNgxDC7FI6+i8/bCeBwpZBdX+lOrDuXOdmt3l9zd4nNqN5+jFoveLE9LQ5UpHGxdZ2ltE7Z7NjnKc1T+EZ52kgo4KMc0PWRPLn7lzdP1mL8beGu7XFboZiELYwYsy/X4Iixt50ds9Nexwr9a5SjDWkIJzjkdIZqO1MgrqOlkH/R4oxPwB4jkYRjx7W99ybqCx/07j3+eDttLYzMe59DZE1Ke0hplGq7UyQ6AXCRkAx5+r1PUC5te951RJjaf0fUC6qRIxRQPho/4eqUQpKrRRj8XR0PhFjo/96Wmb/B+Aqxhroezni8Nu8hI175W7OEX8KqphQmzHx2xd7u8XG0fsfm9Fy0fFRAsa47erPfT8PiTGnoF45ipoYixG2nBSTUHOEplOOYJsxuE8AnxiLKcZU25U6vTQnxVwp/Xvk8/M9W5RijG9gwNPTZxr3Jn7r4oZirf6xIiewcuTIccDQ89O1UbImBjLOw7hXCAYlWe5HIU3FFEFpTgoxFkGtI0H56dcwkRFj1ngPh99d//oLtMycHFeMeUhSFWNhnIpaRxnd/+oSY7F4PoRUxVgEPjGWY6gI20Pn3SvQPFMHxq2D5KnX0L+lA2P/+uwwZ6+tkevbhFtnNtTmu3+yBiOn61grdbCHE2OElLZGxBgZY/V2NwvcuVKIKwCo7kx0EGKXlHYuIWGu2XX38vqktD4nLSB8jsbh7BaloYzzZZnGOUdvg2QNGf69c7SC0JTB/ctP6Lx7ecNkjdqt7b3GVCvaQAj7XsQck9adqznFOOcgxZhPhEQJNU2MNVrXbt/LWP3IkQG7tb1VU1nCtu6zWCv3Wi46viGypqKJsRhR6itcqpoYa/vUhxsiCUpPbMZhx41vrO91JEj05hyx8voofG1ZXWKM8u59YpNy58roe3SvrmJsVHr/1+j+yRrmSpljKLBu4TCv2k5F1rR/62LnuBNIn70Kmqwxi3gmfZg2eeJl9L+6025cAaReQ80RNDEWU3N770kx1jzz/46WVcLmX/n5m4oY00HbTXB5SEsYUX2QYkzvIJ62UYKuUJT+wxJjfhkE3PhttffKqDz3lnJrpx/FqwelepPAAFD42rNomUl1nT0f+2NGTmDlyJFjCAinE2bl/Auhce6j1lFGzwNrMOGWFNWKh56frm2YrNmtV87H/i9O1rjOSCY4YmWvVjGFQakBBMa6VTE1sHLeUTbufaFizOZLA/iuf/kFmg0xlm18EDHW9qnTU9aLYfKodSTY9a/KlbKRus6RAl3NnGgajMGoVEwq9k6MBPKPdd69XBFj2kDgsXmcAoHcuTqMgRBvE7Y9dA+CGOv56TqjGBPO9UMoUvqtuiSBlNJsxjD2r2OqlfAag1Kt6LqmzRiyypwjAyZ4NNQja4AZ574rckSu4RjnvrFhJvPqb+29shOU2uwsxv7yHc2o7zk7Z0aMJWWMJSjN2YyJ988y6SQ7x4wO+h6JGDv0uHHm+s6qODfGuDtXyvWtoaKM8/G3zFBu7Y7RZtNROWjca5nJ3blEUJfGnUvXNVcE5BgshDVmAWUwfn2ZNRizfmPdLvu37FTPKd+wZUY0tfnSE5vRfv8s1zjnYHlQ3xt10WTPGPauAa0Ye+4tReDXa5c7yyh87Vm0/eVp4T0CAQlRemIzRpxyhPssjuRLeVeeexPt35oVTSe8Y4WvPevslJjW/6kc/a825kqZIx1+eIpah2oPo//ywzjUbBhBcdgiY7NpD6e5z6fIOG7c+751sf3ea/d8/lL4mnLvi3k7+PmX/kMrxv7yNOc7p9xSfTZzhG9xxZglrfz5mKMYo3YZQABSKGLsubfQGtnNEPDqemfZkNJOSAnPZqGyl+a87PW9g3dukxNYOXL8N6Kvrw+//e1vsW3bNvT19aWm6+zsxLZt29DVlb57FuX129/+9v0oah24T+Vah16hvL9BWfvdz6Fl5uS6q3fA0Ikx1yh2Z1U0gHT/dI0mxtJcjCxZsCdKjMWhiLGlJs5ROtS27qFiLN34IGKMjPN0Q0Udb8iVMkd96EkNtZ09mqxxV5XjkwlZ2Yvi15dhzBensvbgT1BsWwuDUqt2IsAnP+pvrSNRu9Z808raeZuwk0F1rPPuFWiZmbZyzskx5d7HV84lZMrETfe9n67F+FtnePcYvwa5UjYbIoRfWzrp43Udz5eIsTFfnGq3zq6jGssRhzT/KZTmauOcCPyIwUoIjHPE05GB2jtnE1pmamLMN2jI9tA7mlW0cT76i9PC1W+/HB1lFffqCxQYl90cM9DNTolzdd9jixS0wxvv/0IIG+fo/llZj2yFAaDzHtX3shRj1F+Tpz1XSqm+9XeCA4Dqe1YxFmxAkmNw8OqtNFcb55/6cF1bsbYzQeW5N+PtQXrvJVC8QRFjzhyBk5m8782xfc/f5c+/Ru097Xb6rYvj8T8Bx6AvzdmMlpmaGPPhPop133szTtB55ynjfJkyzlMIOundo6lrp6z2XvmOdJXn3lQx5+o8A3I0AkuR9/xkrSZrjnc2B7DPSZu28txbqDz3llnEk05ebloixtr+8sMmFqKfH8+j9AQna0TkBSfvynNveRsE6PwYAUqfiSjlm4QANHdiijRdjv5Xd+rFkvi98QVC2qhguJN3+BJSOGpNXr7Y79L33FuoLH8rJ680hv+/XYAcOQ4G9PX14fHHH8fLL7/sHL/11ltx9NFHm89dXV147LHHsH37dnNs+vTpuOqqq9Dc3GyOrVixAkuWLMHIkSPR1dWFo48+Gl/5ylecNABw0003YfLkybj++usP8B3RA17qWExLlYHAJymu3Ww+G+P8kx9m3wk9wrh/awVFjB3+gyvM9UwasHM1FDFmV+/s9zIoR6KDEB/xyFU2b/reZG9Jgu4H1mDCLRfZCWFssqTLRsRYy4zQGLNlUGl3r1HEWPv9s9wyRK4h+/bqgPAnYli7NyG0szxTjtLczTik5TC0ffL0fHJ3QGAnKd0/XYvxt14UBKUWZgJGkCr+x/Rj0KINBJeicUms3avfYXJyYaZT7uRQ/T9Q0bF3/nqaKYdP//BzSnM2aWLMdWmlc/h1aCL2gR9d4VyT58fRqd371I5Rfu4uKAD4EY9d5aXx/7qKsawA4HRet1fXaWXI0QjY77CzjMryNzHxm7O972NWaYpx7pwpDNFamrsZ/Vt3sth/3MXadbeu7SwrNdU3ZzUU96r3iU1onpnuzgUI/biUxjin+EKcuPJRfS9B8YZnMeYLU113LhG6h9M9EikdprH1KKU0irEP/PBKkyd9F1xHAp33WMVY2vVzDB59WklhFgcyqrW2s4ziDaF7XxpKc7WL0V+eDkA6/SGWt+p7s1J/X94eCjdwF6M4KI/SnM3Y8+p7OOKxq+q2G9P3vjWL7VCYfg4RY7G+599vn+577cE9xsMtFIkY43WdP+aHBD7tLv3HZlQLFYy/fab9Hnp+QOn08aqO//mBH13RUJsnYqwRd096Fqv5hztH8Z+c1Y4ExQbioNF5voIwbT4mAez7P11qTPjWrLpTaAGgaIix7PoQUIrK/i1q3MvuSSwW4rdm5Z4UGjmBlSPH+4yuri585zvfwe7du3HVVVfhtNNOw+7duwPlFKUDYMiol19+GYsXL8bu3bvxP//n/zTpFi5ciKuuugozZsww561YsQKXXnqpyW/FihUA4Bw7oJBqOOl+YC1GTp+kXUoY8yKF/mhN492r31ETsfvZKomgvMBWx6VRMY35wjQMn9hqrmf+As45xjj/5BleORGkrxWUgWCIMVsQkMRYSjtcdt2jFWPHjfcydk1/SLVyroixqzPSqeVCUoyNv+UidY+URnrX0Kf3/HQNRkyfhFGXn4xguDPlVefv4cSYuT+E5+UYNMil5DA/7pVu9hylOS9jz5adOOLRq3gy943+fWuFRMe9Uu3Bb+r8HAmlYmqZeTxTMcFVzbBZ0Z41v9HG2CwnH3rLFuTVZgwU54iIUsHy9mZbhpT+1OnutXl6jdpOpRj7wA+viHYN/3wixkzfSyOEJVB+mhFjeTM/ANAE/s4yCjcsw+i/PB3DJrYE3/sNwhrnH0YM3HhVLkZv6bhXijylZ6+/VsGJsWGOyi/eKEpzN6F/a0ck9h8/R+rd+0JiLNWgl0oxpoixyeANmY8bdK+V57YbUtrm65aBQESIWhBqcb7m9WYIiLk6zpFWreTk1f5CQgiB6nsJeh5Yi4k/8I3zyDgqgZ4H1kaI0njbJAVhu6Oa9aHOdfteegxC3h4C974UOCom58o+mabK4rhSOqUOaYXSnE2GGAvvzM2/1sGJsdb0/q/R+8QmvTMezTnzNr8/IFJq71u7UNZkjfO994Y+k5th1kYFnDSqFsoOMeanIdQYMWbi0vplYZ+7f7IWzRcdj5EN7DZMROnhmhiLllvP/2sdZXTetSIgxtJanAkI30Df2/tWlyGlY/fllEcCha97McZy5C6EOXK83yAC6pZbbsGMGTMwfvx4HH300Zg+fbqjvlq8eDG6urrwla98BZMnT8bRRx+NSy65BNOnT8fLL79sVFkvvfQS/uRP/gQzZswAAIwfPx4zZszA6tWrTV5dXV1YsWIFLrnkEowf7ysiDhTUJKV/y06M+fzZ8JUkABzyqLYz0WTNTAybyJQUJg0nkgR6HlijiTGtpIjE/iHsXvMOKivexOgvnF13FU7tlMiIMWc0UteW7Hom9s4nT7dJHFLMVYuU5mxG+zdiW2f79SPQqYmxwwwx5heeEWNPbVUuJZ+nexSRly5HgRRjMzUxFvltcgweUq/enXwERpOKSbKX95lcStq/GY//wfOFAIpfX+bEvaLvjHTfI42US8np4bV5viD3vjVhrBXWNPk1en6iNmNw4hyxvHkLqizXu3ORi68I0/P6KNygiTF/IhYpe+mJzRjerogxElJGm68kV0q9W1tslptjaJA69s5MFRjX3xnJ/0H6yKWEbVwhnGegVSiScW7if3i5+Sollxija0unTHy8qTz3Ftrvv9g57sIS/oUoMRbeH5Wjf2uHLkfMtLJ3UjWB6S+OuLWH5eids5kRIVRf9M+9j77lqq5bP8XrI+1eczQGoeJe3cAVPrZuhZ8WijSqFhMvFmLMzBWo7SwrYsy0hzCNgjTEGPU9W4b4eE7EWDxGJ78H7c4VUzEF5JUqC7n3jf5Lv1/7NSJQ60icxZK0/k+gcW/YxNbM/g/QuNehny+x/p9jsBBQKqauu5Znqpj4tKHnp2sx4pQjMOrK9B1+Kf2+/7MLlefexITbZqam5YgRY2m/cOmJzagVyo6aKg20QUD7t1T4DUofTA+kCtfQ85M1aPGIsTTyioixtF1KnXLsTNB59wqMjc2DIuh+YG2gGMuRE1g5cryv6OrqwurVqw1xlYXt27dj8uTJQbpzzjkHAIxiq6urCyNHjnTS+K6DixcvxuTJk825BxzaYKyseBMT759dPz0QIWvSUZqzyZI17JoAgqd3rcMSY8MPb61rrHY/oFRMhhiLpdfGtEOM+eXwT6n0o3CjJsYa2NrWKsYa2ymxNHezVVPVuUcTY6yBus7RKAT6NFmj3D4EHY6iVmDGeQOTlNITm9F08hEuIZWCWkei1HV85dw7hwdbLdywFM0xd66I7W22c/ZjzrH75HFIkjmb3N25MspuXEp8YiwCQ4x98WznmrHqrnWU04mxHEOGgEBp7svo37rTtHlLoviGqNAqpk1MxSS8cxgo/odD1sBLa/+aoNSfOt3LK4y7YlQrn/owi0PipuF5lOZSrJXTvTS2Hug4EWOkIubfBaSXFIYYy46HYtUzvK55CfzPtZ1l9D5Bfa/VS+uTHDkahrQGo9o0JtbWYI7ve2sXKs+9hfG3zETYtrzfWROloz+lYgAJv7145ylirOy1h3icIUuMzfLi+oRtR0IREC1GQRgrh331MWIsq/8DAtWOxBBjVI5o/6d7nPMyc6VM7/8CMHGOuHLNyT9fqBgSpF60ap55PEaefUx08YlvXlH++ZvY/dJvMOaL0+xzxl+cM4tWZXTetVyFOYhsguBvENDzE+p7JzrlkJFyqL73JibcOlOVIpIffxExxjfQiOULKDVVtVBWZHBGeekeu3+yFu3fnIVDmg/LrA9IoPunazUxNime1vwwihjbvfo3ziYhsU0bDkbkBFaOHO8jSDU1ffr0zHR9fX3o6urC5MlhEE06RgTWn/zJnwTB3bdt22aIr9WrV+OVV155/1wHoY3zG5ei7ZMfbshgLM3ZhMOOm9AwWVNZ8SYmfiOFGPMe2IUblw6KGOv3ibHUcpRdYqwOuh9Yg2ZOjGVgz5rfhMRYCmRlryXGJjZKjLU1VNc5Gke1I0EvGefclSNlAtH7xKaQrEkBEWOtn2qkfzDjvMEYJyowbmN5u26nPMPwEBFjjT0DFDHWaDlKPjFGxYiUQwUAn9xQXedoHGQgOMR57KW/K96glRQ+mRlJW5rDyBoJY4DEJvK1nWXT95zd+/xrAHanRHKtjRgF/BxaOTfEccR4I4Oh9l7CCIhRoUHjlac0R6k16R6DPmTOFai9x4kxtx6CuhmIuFL6hiFyDB4SleVvYvea32DMF8+Otx32t/Zegs57lpuxOfid+OcBpaYaccoRGHX5SVFjmFM8+97qQuW5tzDhlpnR/ISXd+GGZRhN87GMfkftstpRtrEQY21Tg2IQtn9Tufel9n+dT7chxo7PLgdYQPhPnZ7Z/wGgupPFvZrYGuSVN/ihozRHkzW+65tEEH+v1pGgR7cH0XKYibuWBiJKR5x9TN1y9C1XZA3frEUIl5i05Sij8+7latHKLJZklOMBRoxFwNV+e99Sca/G36oVY5GsnQXCry9zd2zMqI/SnM2oFcvBZgxOnjTe7FR9jzZsCtIe5G0+J7By5HgfsXnzZjQ3N2PkyJFYvHgxfvzjH+M73/kOFixY4JBQRE6lqbTGjx9v0lMMrcWLF5vdCl955RVMnz4dXV1dWLx4cUOKr/1BZfl2bTDWJ2sqy7ejsuJNtH4yJmt3UetILDHWoIppxMlHDooYc9370lG4ccmgibHRDRJj3Q+sVgHhGyLGVhtXynqr6pYYy7eVPtBItFHcKFnT3zBZk6A0ZxPa7w/JGh8Cym23ZeZkJ+5VLCVXjLVm9g9hylG4YSlGf+rDOLShvqeN80+dUTctKcYa3aW0cIMipQdX1/WfLzkGh+4H12DMF6el7iBmoI1zR0EowffXsJA6MO5y/SwmHjiWvzHOl8b7XoQQKs3djH07doV9L2Jsq8C4m9ydEhEptxZJ9c71iLFYefXfCielYwSaR9AVbtTEWKTNG/WhLldp7uagrk059d9cfzUESLXBxMT7Z0E0H+YcjxGl5N5HLkZBG2af+1YwYizt8pqYqu1M0HXP8sDFSEA4e7XQNXoe5Ioxdm3HH0/9oaDUE26bGe0T/qvw9fqLJZwYq3WUTbtM6//Q99jz0zVsQSg9X0ig54E1yrW2AfVujsHBIWtARIpLXAHQuylrFZMmjURGaA9FjCUZMaHsObUOq2ISLYd5xFmYNxFjzedMgkDWxhVKQUiKsXpQxNgKjP3rszNV5XQ940p5xYl14w+SK6VSa8bz5CRW8YZnnTFBCBEQigczcgIrR473Ebt378bIkSPxne98BytXrsTIkSPR3NyMlStX4jvf+U6gpGoE48ePx3XXXYfVq1fj5ptvxk9+8hNccsklOOecc7B48WIAwCWXXHKgb8VB88zjLWmUtuIotZJi7ia0f2O2qx6KrcxJoHfuJrTMIGIsZWVHp60sf7MxYky6xJizepdSHkWMHRESY5EJnlGtZCnG+ITwxiVomTEZhx47zr0uT6sH7NKcTeh/dSfGfH66qo7Iltm2HIklxoK4V5F7zTEojP7CNGYU++49Fsa9r2GyZlnEvS/+2/Vq11pL1qSZqbIOMRZaNsq9TxFjErG4IvYzGeeqPrIblCLGyKWk/j1aYqwRwrtchxjLzfj9wdgvnK1cSuqgoo3z0Z5x7sdtA7RLCalW6u0gRsb5ya6CMDCMuXG+PN1A8M8p3LgMrZefGFf5eYZ9ae5m7HsnQoxFQK6UjZDS6h7XuJsxpHQpKeG6MafUQ/6MHyKEwNj/9bHGiHNy72uoPaiYlAExFoEcsAHhfdWK2hHTTW/6nqfmjik0ah1KMTb2i9m7tRF6HlB9zyHGUkB9j8c5ivV/VTjmSkl1nfGoNooxXddp/T/H0ND+zVnOopUiUngKRWj1PrEZI6Yfo1VMPpHi/gj9r+5UrrW3zvTy4e/VObKy16iYyNXatnObjsCJMSnT9u5UhC9XEApHxRSf31jF2P/lpQsbqOPeF03HCbrEKMbiY4KtTyGFWhDSxJhg36URegcj8l0Ic+R4H9HV1YWuri6cdtppuPXWW83xV155BT/60Y+wePFiXH/99YPO97TTTsNpp53mHPvtb3+L1atX47777kNfXx9+/OMf43e/+x36+vowefJkXH/99Q2rsrZt25b5fc9h/e6Y4o8x+nPhxqVomTHZrt5lTDRKcxVZM+6R88JVQQ+1QhmluRtdYixloqTy3qyIsRksILyzrK3JMiFQWb7NU2qxtCZfdazWkaBw0zK0fer0+ioFfY8jTvKIMRqPnHuWqBU8dy4qc0rdUF0feuw4k0f4u6gD9X7fPwT8oZWxPGKPXvKJtB3AkJmFG5dhzBfOdlesU9oFGQgmIK3ey1qANTn9u+97exdrD5SWtQdvyyZSMRmVHw8ipd8LoQL2knvfEf/4MXY7rNDsnFqBjPPZxo3K2Yeb/wW5c2n3Pt7WedvU/bTy3Jv2Hv0689pyrVBG8YalGP2p05VaU/rltX/37dv3B9eefPwhlm/fESMB7AGAYGdWAm3Ocfj3rwzcHAJI5WrNVSv8Ox9knB/+/SvcpLExwRBjduU83E3NXouIMTLO7f2F2Pd/djk7RmVCj3sxYiyG0ly9O5engAjcSyBQ3VlC9wNr8IEfXOm6ikVQ6evDts4/vDbF8YfW5iUA8X+1gto8EG9D1B4aWqSQQPFG5t5XB7H2AMTbhIp7pdqD3/dibZkUYyMozlEGKtqdS+3UnN7/AWWcd+m+18g99vw0QoyllIfGPd730sQnvb0lbOv4w2pTPv7Q2nzhkD16Aw23UqVZSFUsZPmp17B79f9f7R6sUrDU7oBb6yhj17/8AuP+18f0/CNt4FfofWIzRhpizP9x48SYjYOWTuYMVPoZMUZuhhK0261bdolkzsuq7zESNiytfhZrYuwDP6S+FyPy7Puen66Lj3uReygv347da36DD+i+J5E+lnV1dWHb79//NjVlypT3/RqDRU5g5cjx34CrrnK3Ej711FMxefJkvPLKKwfsGj/+8Y9x6aWXYvz48XjsscfQ19eHr3zlKwCAxx57DI899pj5XA/1HlYTSglQesceiCiJFFnzgXT3Ps8YtQHh2ZDBVxGZEV00xFgdn3Ndjj2vvocjHrmaHWcDKZsNqWDpm9B+32ym1NJpHVZBQSnGjleKsWDHHDdtZfl2PemdHX7vr5QWyijcuARtnzxdlyN7thklxkw52AWkhKzs/YMcjDi2bdv2B1fGtp7fA307A6JRQbUPY5yffQws0RWZuAmBvue2W+PctDOVp9RpaGvAWkcZXfc8p43zSPwP/l4I9Px0jVYQftgjdlySSzJijIJSx9o5v05Ru3MpwtbrQ95fcu8b94/nwelLXr+DFKgVVN+beP9stiofmZwSKT1nE5pnTkbzDO7ORXm7fjbD+uUfXHvi+ENs7wAwsvMNYG83AG4Qu8+tgjbOGyVrasUy2hrYjcoY59+/Eoe0NJnrRokmSSqmyY6BkLY2HyPGeJ7cWKjtTNCp+57aPTftWaz6VtSdKwX79FbqPhESIwqklJoIOb0hkmDEwPA/yDZF+ENs8xLAoR3rgdoedky3O90majvVs3jsFwdBlE4/pqH20L9lZyoxFmvzxRuXNk6MaRWTIsZiZrkF7Vp7OCPG0pQ2gFWMxY1zF0SMkXGehVpHgq67n8NYRoxlEc1tw0b8wbUpjj/ENj+qlgAdL5lx1bQMegRpFVP5qV9HVEwcVoG0619+iZaZx6PplCOC75y/UqD8NCfG0skoARWH1CXGYte36H3iZU2MneSkk8E5Av2vvofyc+Eihe39gJRqfsSJsWGHj6rTm9RcJUZKx+6ytjNBMudltH9zNkRLkymE1L8F/10AYEyt6Q+uTf13IXchzJHjfcTRRx+N8ePHR5VP48ePR19fHwBgwoQJAJDqUtjV1YWjjz469TrcdZB2Pvz0pz+No48+GkcffTSuu+46bN++HZ2dnft7Sw2hsoJcjCLxcTyj1Lr30cScG0gStDpCh0tzN6n4Hw3FvSp7pBGHTzhZ975wcJRucimVYmzLTlUOTmRE8q51JCjNU6qV4c49pruKtcyYjJaLprB0cWmycaWM1bWn4a91lLHzy/+/6DVzNABOlJg4Eeq3KD2xSW3n/MkzkDph0+nJpaT9/lnaOBfhS9r0Kv7HZIw8e5I3gXHLAFhiTLmUpOep2mUZnfc8h7FfmKaNcwRp+KvnQR3nKLjH8LXv7V2RmHNp5/C4V2wHLdb9+W9Au5SqZ0BaXcPcY9fdzyHH4CEi7wykCFRMWQbIvrd2Rdz7UtJLgcKNSxVZE7j3haYCqVYacjvVxNjEb4SBcVWJGBkhBbofWKuJsUlwn9vheNIXdeeK32NtZxmd90ZcKVl+5nxNhDSdfARz3/H7PpVeYN//2YWue1Zk1EKOdMR/L6nnALu++4vAvU+mjOfJ069h95rfNOx2uutfXsC4f/yoQ4xFy0R9b/oxGHXFyZnlBoD+V99Tfc8Y0OkkrKz061iIp7N2Gctbj3uOe196GehZ3PtTNe4pIiQtvTre81PtSkm7tSHe/wE1D+p5YE3G9XPUhbeuBEC1h68vw6grPoRDDx8VjMX+q/TEZkDC3biCvQQ7TxFjr2HiN7VrbSQ9H/+JGBtxyhHZaSWQ/Ow15d7HYxDyv9IthyLGPhrdKdGpF8mIMX8zhkje/a++pzZjoL7nz2n4NZJ+FG9YhlGXfwjDJ46ydRUzK3RdV557M/ZLHhTICawcOd5HTJgwAV1dXYao4uDHxo8fj+bmZrNrIQfffTCGrq4uLFmyxLgiEkk1btw4k4bO3bVr19BupC7sRKvWoVxK2r8x2xrFJk1oRHc/uFapmGYcj/SJuYIJjPvJ0908PSOeJkuFm5bouFdEGsUMaAWlYjpSG+fxNCZvrRhTca/49zJyDlC4yVOMRckodV5p7mb0b3lPlSOYq7n3WSuUFTFGirE6xjzFGMsxBPi/Bfu87+0uVFa8aScpdVC4URsIjewqOVet3gVupxGoOGicGMuGUoxNxoizJ2XbHlAKwt2rf4MxDeycWSuQamWaJYNjkzCNngfWxGPOcejz9r3dNbiA8DcuRdMpRzaUNkcEzuRfmM/J01tVUGoiSiXguDhzA2Fngs57WXsw30knrYBQwbEfVO1h1OUnuvlyAlmfR8SY2a0N4fXNa0D3PV+14q+TsMWSWrGslIxOOumVSait1B9Yg3Yixpy0cMs/oNq8cimZlGqwkcFndsYzdS29lz2nqhVjoy77UPpvmiMbzjNKsPawGQAscR60dTvHqO0so/L0a4oo9Y1zPg/S7XLXv/5Cq1aONN+ZHd4oX6/vKeOc+pD0ygJtnJex619/wYgx23fsX5pXSPTOIeP8xHg681kqd67letzL6P+QMMSYE24h1v/1cbMzHi0QpvR/Tow1sotvjjic4T+FrJH+b+uBFITjvvKx4Ht/8wFZ2WvIGudZLNz0hF4ixj51erZDgtAL10+/5irGnHbswijGTj4i/NJD8hQjxnx4eQfEWBYk0DvXVYylih4l0L/lPVRWvFlnM58/buQEVo4c7yMoTtWKFe5qaFdXF373u99h+vTp5tj06dOxffv2QIVF56bJRL/zne9g+vTpmDxZERPNzc0AXIKMSDD67sAgRhwBhZuUm4NVMcXJKAAozd2IWiHxFB3xa9Q6EvQ+uIbFvUpfFQS0S8mMyWiZOSVaTn4OuffFg3S7n41i7NrYPYZkV5wY86+h3ivjfLsXED6dWVBxr473FGMxEktoxdh7rBw5BoWUn0EFxlXG+bAGCCkia0Zd3oCL0dsx1Uo6BkWMzSHFGNuMIQW1QlmT0rOsrD0D3T/V7lxnT7IHU/Kv6HgPY74wPZ7AK8dQ6roRtWaOGDyrQx/jxrl1KWHPP8mehxLY9a+/tO1Bwt25itLqY6RaMQpCf5crYxQLrWLy2oPURrDwzuWKsctPMmVzympc1oVLjBFpFCyAaBhijFy++T15aSVQmqcDgH+S71DopdVusNX3Suh5kPoer2tdj4JdZ8CS0iOZaiXHYMHapW77RNaM/cePOcdDUkVCJntRvHEpRl1+IntO8TYmnTxKczcDAnrRiufL+5E6XntPG+ffmAXRrNW7PrnErrXrX36BlpmT0XTykU7fUddg/VsCZVKtmDEh3v+JNNr1r0oxNuxwppo157ntXsU5moRRl5+U2f8BS4SMv3VmZv8HBGTZI8ZyDAkxUsiQNX/Z2G7KpCDM2kmV0Dtns+ta6y1w8fSkIBz3lY/Vvw/dHkjF5EN4zFhpjiXG6sEQY/dnuVJa1CXG2D3WVWuytEqt+QtHrXkwIiewcuR4HzF58mScdtppWLJkCVasWIHf/va32LZtG370ox9h9+7duPTSS03aGTNmoLm5Gd/5znewbds2dHZ2YuHChVi9erWJbeWDyC2ez5/8yZ9g/PjxWLlypZNu/PjxmW6IBwI9D67GiJOYcc4HLe89KSnG33xRQ3kXblJuhu4Kfjx/pVpJUlRM7rm1jkQbCJ5iLMXg7n5wjY17VQeKGNtuXUrSSAKpiZB7WZwjvxzeuVTXbdeeEU/D3hMxNvEb7+/ulH/USGsPD0TImhQQWTO6EbKmo4zOe37uqpgyMDhijBRjDfa9G5Zol5IhEGMZqHVod677Z9eZEKpJZ0+MGEuBrev6irEccagm75JRstyPgmOcC69veAbCPDLObXuwAYLdi1XfS1B55jVM/MZsqyB00nIjWblzue2BG8buuckzW7F7LXetjZcBcBVjw4yCMGXhQQqmGPP6XlAvwgQAH38zxSKKlANCHZLCLggFdS2CXd6MYuxTp2cse+RoGKTw2VnRZM3HPBW1T9So9tA7dzNGaLLGpnXzpOP9W3aisuJNjPvHj7G0IrJgIiDLe1G4SfW94YG6nZdJofTEJgC873ltV9hzah0Jys+8pnZKNG7t3n2yeYZSjDFiLCiL/WyMc61kTOv/UqpFCqeu0/q/Ru+czWg2dZ23+gOFWkcZpTmbrXtfHXTevdyLe5WOckzFlDK/qnWU0a0VhMMmjkK4O7KL3jkvozkj5hx3Qe3fMghirLLXEmONxHucsxlAg8TYzsSS0g1shKLGvcYUY3/MyIO458jxPuO6667DyJEjsXDhQnNs/Pjx+MpXvuKQUnTsRz/6Ef7lX/4FgFJMXXXVVZgxY0aQb1dXF1asWIFLLrkkILf+5m/+Bj/60Y+wevVqAMDIkSMbDuDeGHyjBaisUC5Gh3//ykziCtBKCiJrzCQFetIeXq3noTWKGLvsJPd7nl6/d8gaidQ86XjhpqUYfe3pthwZ42Np7ialGLv5ojBPuo4+n4ixw793JQ5pZqqVLGLswuMxctok9554vvo41fUHvv/xeL5solkraGPs82fX3bkqx+BgyJpbLnLbjt/uhGoPydzNysWIXEqc3TDdvHf96wtomUHGOcuMXUdAuZkkT2/VgXGvTCkpW8EnFdPn2Y5RppysseldLA0xRn0vo3+4OyV68M+VVrVi2qXXh/h7FQg1sXFcInVMx5VibC0O//4VDblS5ohDwG2iys3BKinqgQwENw5aHGSct15+UoO7tW1SxBiPcZICYyDUca0VQkAOSJcYS1lAICRPK2Ls8O9dUbfMRIyNpUWKtLEJ8Fwp43Vtfhupd8ZboV1r82f8gYMEdn33BU3WNOBiNMj2oMia80JFqf8bNtr3dJsiF6PMnRJpSKn0650zTwrK4e37AUA9iwE0uEhhjfNGnsVWMdaIO9fW6C6lOYYK1XiIrBn7xWkNbxAwfGKrjnmb/fCpdZTRO2czDv+BGpvdzQ/CB2Ln3c+heeZkQ4ylbcwBCNUe9M6ZqRsrsHJQQPjwHv1yCPTO2RwJCB+HuxlDZALPIMt7UbhxWcquteGE0rgxp3qLHDzICawcOd5nNDc34/rrr8ell16Krq6u1KDugAr6ft9992H79u1obm7GuHHjUt3+iJSK5UX5/O53v8PIkSNTrzd0SOd5XCukkDUp6H5wtSVrvGx9KLLmHRzOyZqUItUKCTrvSzHOI+l7HvIUY356rmLasUu5993H3Pv4mMT/Co8YyyoHgNI8Rox5ZfTf1wplU9eCYq3wcc67jiHGGlCt5KgDVrfGQCB3TzNP0W9YWjVJWYrWy07C8MPbrEXg7MRn35bmMgNB6i+5JUF/hFTx2J7RsnYixjIK3v3AakuMBUaSS6aZCeH3r0QQxMKzbFTcq59j7Bemu6R0vBiucR7rQ+ycfW932roOVvtlcE7hxiVqZ7y0cuRoCBJuEy0P0Tivq9yTakfXQRFjtEFAnd+XE2P1XGul3pzDV4ylobZT971GjHNpFWMj6FmcUXaq6w98L42Utr+NcqX8uUOE1Nm4NkcafLJmUO0hMc/iwbSHwRBjWe2B8q3tLNu+14CrtTLO433Pb0fU99SO0XWKwoixRtW7wCCIsUb7Xo5smDmketPz0zUYOf0YL74SG/+Nck9iz+rfMLIm+6FDxNiYL07D8ImjIgST+9kSYx9GnACyx2odCUqGGDssnbzSh7vufi5DxSSdeXX5qa1250xnIS5cQa91JOj+F60gPJzH3o2UZ4BIadqMIYvMk8aV0pLSBy95BeQuhDly/Ldh/PjxmDx5ckNk0uTJk3H00Udnxqxqbm6umxftgnjAwYgSWdkbkjUZMGRNA7GYaoWyiXt1SEzGLAH+EB8MWUMqptGfr+diJLRi7OcY8/kU9z4PgStlBpRqZXvElTI+OBVuWuIqxqgckbIMpq5zNI5aRxm7vvsCxv2D3s7ZxM5B1HLsnbsJI8/WBgL/3o9UCqtaGfuP57luS5w40scVMbYEoy7zXUriKM3dBFnZGxoIQZwRlxhTQam9+/I+7/rXX6BlxmRnd640kGJs9OenRb5160T1veWq7/krpYYwtOh5cE3DfS9HNnjN1naWUX7mNbTf9/4Z5yZYegYsMRbbSj0sx1CIsXH/cF7kW7edyXI/iuTO1YhxPkhiTNV1mmut65IWUwhFHi05Bok9a36Dyoo3MTbaHlzIcr8iSok4r4PBtofSvM1ov68xF6Oue58btIqpob7XYd37GlHmZBFjPqjvjf3HRty5rBtzI30vRzYEi/2X/Gwr9mzZiTGfPxs2qL4nw9MrG7UOtXHF+Ftm2vmoSU8vmLy7f7oGI6dPsuE3ZOSlr7lbE2Njvni2vT7PT9o5iyxrYoxvEuKUnf2FIsaGTWy1C4ROvgCfV5NiTC0QRtzaeaw8CXTdvRzNRIx53/nXSp5RrrVjPn+2lwY2b/259l6CXf/6C13XbBOEg3ihIiewcuTIMQTY2XHvvI0YOY1v55yO/q3vMbLG5hE+g/V2zjctUcHSMyeEaq3FJWuyZ+9VrWJqv292xBjzz5VWMUbEWIZ10Dgxpo3z+zQxFtxjWCvGlfLyenUtLDF2U2NxjnI0jl3fVe59apIi9aqk3ybU5IXIGmsgcOPT/Y1rBU2M/ePH9CQlIkmi64ETY357YISULpchxmLGmHcdWfGJMU995cFRjNXpe7UORYxNvD/W96gMNg/lSnk8Rp59TCRv6ZSprOvaDQgvDupJ3v6A3NOUimmJNhjbXOLc/yu5cX5GipFi/5KKaSI9i/00/DWgibEZk9F0kreVuv87S7tbW9u1Hw7z88ptVCv/8LFQvesbC3rlfMTZxzAFoQjz1e+Ncf4PH7PpUu5TJnsVMXaZdimJ1oUti6nra0938swVWEOFMO2h+4HVmHDzRcxghGcc61OkWjwbefYktctvVpsn45yI0rS0dEqi+p5aPGsLvuf5Aqo9OMY5EFyfUOtIUCK39pamMD+v7F33PGf7np+vd175Kdb3Mvq/IgmSSNyrSDl03ffO2azGPXJrj/X/HA2DYpLVdqr2MFG7vplYZaS4os/6pVRMk3HYceP1NIO+49DzoJ9tRb8mxtQQL5y8zEvaTWMm3DLT3QTBv4b+7bsfYMQY5W3K6v7drUnpMV/0Ngmh8rByGcXYF6Y5se8M4ee0ZcGIMWaDeHVGedR2llVdf2MW0urBlF0KdN673NR1dHOQgxA5gZUjR47BQw8kyTNknLPdc+DNI/QAYYzzf1CydpL4uuYqzNHeeZsUMaZX79LmbRACe7e855E1Mv2cyl4UScV0eGvE5qCSqVJZYuxMm0b6pVbnG2JMByFOLbNGQIyx67ppBSor3sTu1e8wYkywMdS+lyBXSq4Y8wfyHEODYGQNTVL4hINPKiRqhYSRNSPg1n84uaK4V2rlnH/vv+fEWCwWArVPqQ2EMnZ99xfanWuUk0+sTTiKsci1+ctRjHl1FZ0QauNckQRhHfDyu8SYl69OK3T+tYJWrXyDVCssr1yOMnRI1h4uYwpC/+GmP+9e8w4jaxCve8pCG+emPVCeXNHIUJqXoVox448wbb6i24Mhxvwy6C4C6ZHS/P4i55mA8A5JIG1+5jxhjfN/IOPcZyjc973zNnnEWKQMGv2vvhdXCOWG/H5APTM771VkzaHHjYO7oyXgLFhIRZz3b9XGeUa2gFIQ9jy4GuNvnhlXMbE2iQE1R2g+exJaZhzvtnGwdLospFoZ/YWz4+QSK7NapGDGuQSM4iZSdkWMjUrftZYTY4UyeuduVn1v1IjUuqC/nfcsd4mxlP4PAMlTW9ydEk2eeaPfH5CqLbrDb+xZzIlSpFe/EC5RmpUnoVMTY4ce53mPRM4pP82IsTp51zoS9GjF2DA/tEfkWdvDiDG/+/vTJhr3Gtk0htSaYz7f2G7KpbmblCulrut8NqOQE1g5cuQYPCRQLSSoPL2VuTkIQ6YIbpDqkW3Xd59Hy4XHOwYCJ2j41MwSY0rRYdzuPQgIVDtK2PVvmhg7vA08JS8HlY0UYy3aOBfaGHZNZ0Vj9TvEmHTmlpbo0p85MaYHJZ6ndI64ijF3Vx7J6lFBxRhbrRVjI0wqa8bb9wJEjE3GyLOP1de2Jc6neUOErKNiciCMgTDqsjAwboy4CYkx/r373sb/8FVM4UofQMb58R4x5peHiLHXnL6XhVpHYomxiSlEKWtwigg5RivG0sgrIsZ+r3YI+sfzvHtyyy2lnXyPuuykCGGbbgzlqA8ia+LGuVu3tQ5F4I+/+SJL1qRZNlI9pyxRSlmK6Dm71yjjfOzfx/qea10YxdhlJ1q3U59IY0ayIcY+1YBbe4dVjAXuXLzYQgAUEH5GhjsXK5dDjDVQjl3f/YUmxiLbxdfNIUcaSvM2YbhD1kTaMW2K0VFG77zNLDZmRs1Lgc77FDF2mG+cmzSUjUD5GUWMjf78dLhKEbhtTbtz9Ty4xroY8bRemQGg+6dEjE1mX8uQrIPte+HuueGzVT2Ll2DM56d5KuI4lHHO6jql/9MiRWnuZrQHu9bmrX1/0f3AGjRz974M7F7zjiVK66C6M7FEaYNx0DhZk4VaR6Lc+xrYJAQAOu+xirF6KD9lXSmBSJN0xj1LjDXi1t79oOdKmYE9mhgb80XV91K7x0GInMDKkSPHoDFQ6UfxpiVo0ca5MCSTmtBIKSGl0FvWCmUgAGi99kw4xqgUENrPW2h/8WpHWRNjlyifc8oXApC0dbhWdEiJ7u++gJYLJ+Owk47Q16VrUzlg8kie3sIUYzBlVX+tsSulUAYCEWMT26ynmLRpqDwCwijGWi47yRBSVFYhBWjHOCEFI8b+VC/mClZWYRkvKTBQ2WtcKYdNbDPfCXZ9XieleZtQ60jQdu0Z5r7N7yM5uZhjMKga975IUOrIhKJ3LlMQ1plwKLJmu0uMxSZMRNbcxMka93v/PJcYi8AjICrPbMXEgBiLn7Pruy9YUlqG3/NjgWIso04MMfYPkd25/HJIHQj17GPCXUrrXCdHNmodiYm9EwdbdpBA570/18b5OC9dSGwmz8RUKzQ7d9PXdpaVauWWme5OTUJ4adXLEmPMtda0Axp7lLFOLiVj//48du34M5ICwo+67EQMixoq7sKNoxhzSAF/OZ8pxlLjXvGCCI+UjiTJziFHChwVU0ZbAGCIUjc2Jl+Kc/+W5m3E8IltkcWB8Bq1nYkixmiTEL7xhy8BkaQYOx6HHTeBHdfphNtHSDEWDXMg2bVg45COv+WiCFHq36t25zrbN85jCzKcCJluv4/0f7Ug5BFjQKT/5xgKSnM2oX+LJkoZYnNFImvavzGrIUKqd+4mtMyc3BBZU1n+ZsMqplpH+f0lxuZubmijAgDoumd5w8RY0ohak8qxM9Exxi4yas2cvLLICawcOXIMGn0r3lTG+WUnW3KE5EkA+KTCGOdfPt/Z9psPjmR3D5T7Ubx5iTLOtaIjtMntCmQyzxrnQgjjTkTp6JgEUO1IUHlGEWOHNDepcjtlteUSALr/7XlNjB3JruueIwQRY1uxe/U7ijSC9ZE392hWTQSqhQS7vvsCxv79+Va1IsP86VCJiJDLTrYlZacIWFJqj67r8Tf/qa03It6oLvMBcEgoP71VkTUnMbKGKlmw99LGYhr9qdPDtN6r1lFGtyZrTADS2Dn6xzfEGI//EftNJdD/KiPGfFLJK7uskGrlJFdeH3vBI8b8OuDXASnGturNGJrc9P514CnGYvXB8ldqzXc0SeCnC9UEORrHru/+AmM+dzaGTyRla1zhBwCleZu1cX5GnbTCBKWe+I3ZmekAQKlWiBib4KaPtPvk6S3aQGBGcTRvYdy5Jtx8kafcC9NCEjGmFYQykoad5yrG3Ge8e45gxNhJTMmY/rLEWKyu/frM0TD0LpSKrGljX0TqVoow7lVGWzZkzefPRtgG3HOJGBvrxMZM61NC971WtkjhpWNttbYzMe59aX2Z59F5z8/RPON4bZyn939AqXeVO9f0zLoABFOMXZSi3nX/WmJsis03n8scEFSWv6mfxS5iev3ijcvQMmNy/Y0KpCXG4mEOECyeleZuRPs3ZscX5jz0zt2ElhmcGIvlrebGleXblYopUBCGZbHE2NkNbVRQmuO51mbk7ywIReZJfvrOe0kx5i8IEQ7uZ3xOYOXIkWPQGHH2MZqsseCbaBBqBaViGvv356t4U9K1MQXgPINL8yxZ460xKiObndu/9feorFDEmAk27A0GtFgp+/aieLNVjHmcQGAfl+ZtBAC06nv0xxhBu8BJ7Ur5zBalGNOqFb8ueLm6v/s8mj2XEp4/v2cVhPgdU9c0D3UWY/XxaiFBt65rrlrxx8mDe8gbOkaePckaCES++A0IFP9jk4rF1Fx/e+/Oe3+O5piKyYf0XWthyxJJWysk6P63X1h3Ll5O6aYFPGKMp4nkr4yxOooxOkxxry7VxjnZNCnpDTHmPV9iZVYxxrZmxDmKPBRyNIyxnz87Y+XcN863N7RxhSz3o3DzUoz93NmNxf+Yt4kRY9mwu7U1sHIueZyjtJVz2/jLRjEWcaMKypFY47xRl5Kzj2lotzbT96KulDn2C0JgzBemN6SkKM3bhP6t70XaQ4ihtYdJaJ7RqDvX4PpeuGlMnDRS7n1pfc9Nq+IcbbKKsTqgvtewamVLY3WdY5CQ0DGhRtkJpT7ukPSakGo66QOuijptYa5QRmWFJsacibBPPqr3hRuXKGLscH/DBATXKs3ZhP5X32O7CIZp6HpVE39rto2zmLIoBwn0ztmoiLEZx6emJU+TyvI3GSmdnW+toImx2IZNkfQ27pW3EQrVnaT6PHiRE1g5cuQYNIZPbMUhLU2OHRqzo7u/uwotF6aTNfwZXH7GkjUZdjYAZbju+u4LGPsP5weuHLGpWGmuinvVetnJTjo2nBrsJWLs789PzZMKLQNXSi8duwYAJPM2AgIYHSHG/HLEiDF26QDd330+qOscBw5NJ33AfjAN1G31tHNmfFdJsIakDYR5m7yV8xQIgVrBGgjKvY+vrofovPc5NF94PNu1Jh2kYooaCF7+tUIZPQ+twfhb/rSh7eK7H1itXSlPtvmldOzBGOcBMXZwz+XeFww/bnzmpBwyYpzXMT66H1yDkdOOUcZ5quGhXrtXM+PcHxS8v7K8F4Wbl2Ds584OyxF5OX0v1agh1UoZvfM2WWIs02iCinN04fE47NjxblkjUK6UnnEeGJF16tovR94XhoxAYQvvvf4dKsu3q/YQa7ve38LNS1V74GRNyjPQEGOfm57+25q+56uYkH7OgCVKnZ0SOdgxhxjL6P8AjFu7GffS+r9+b4xzWqRIy1tGiLE6z4Ecg4RASCI6v50EJJSKafmbDcYJTFC4cQnarv0wUzHRfEW6k1itehxx8hGNxd0slFFZ/ibaffc+ylO4s/DijUvRMuN45Xaa5sbNCFtXMRaHlNK2y/tn22dxNLHK3yHGYnHsTOw5Yepa9T0v44OctOLICawcOXIMGny+kTYkJPM24pCWJkfFRK5u0ktfKyQozduI9nsvicbe8a/RpWOt0K415CbolxHQxrlHjPkEEx23OyWe7xBS/n1S+tI8HZRaE2NpcykJYO/W9wwxFhuCnDliZS86fXeulPoAVF1LEVGtsLT0d6CyN3L1HHURnVdJ9r81zltmTInnYRqItAbC586uO/eW5T3aQJjOSCPeKt3CBcRYxqRHBcbd5KlW0iaRQsU5uvB4HHbsuDpptXFuVs79XhSWwxBjh4cKQrds2p2LYozlboLvDzIn5QoqKLUmazIMYiBFtZLy4K516PaQpSCkvwMw7n0OMZaC3WsjxFj0PqXaKfHmJcqV0jdUImUP+x5LGxAQCUrzNqH93gwihL0P6jq9m2KgnD/nhwy+uuVNdGodCQo3L0XbJ0+PKym8v6V5mzDipCOU4Z9BAgXEmJ+nDwkUbl4SJ0odw1j9Kc1nxBgd5/fHziH3vvZvzI4vUngTqe4H1qDlwuOdgPDB/enPlRXbXcVY2sQNgOzbGxJjsfvUf/O5zRAQa1/eeFrrKKvn1P2z62xIo95b9z42D+I7d7JzKyuUism4Q0fbu15I0Cqmtk+d7sRjEzxfaRtFae4mNBlijH/nl0MaxVj7/bMDEsy8Z9cp3LTMEmN1UJq7Ef1bd0bKwYugiD01JmzWMcbawnQ5DHICK0eOHIMGf7zbuZ0lkdTOGdsx+nPTnXNo5zyCImuUimnM56Y7aqoYYQRAB0JtNcQYAB0sPsRAoayJsUtdFRMrt70Xga57/0u592lijA93/hW4YqwelGLseePeFw7jgr1X98iJMR+cDCRXynFfTifGzD1X+tHx9/+7bnlzRGAqN7QaBSxZM/rz02F3ffTT24mYMc49BWHsN7TE2GQvbZjaEmPTY7aJcw3aIIAHIbYlD++T+h6PtSK9nsTJ4NClJN3qtsQYrQYL9r9b+uSZLaau1aGIxabfq0nvkug1c9RBZEcyjtK8TTjs2PGNPQM7yso4v7cx9z5jnNdzMRJAsnirNc5j5WXKx2CnxLS0uhzdD612VSsZ4KR0PSjF2FJLjNWBIcZ4XaeUp9ZRRtd9z9XNM0cK0kjEAaB33qY4WRMBkTWt156e3XZ0u0wlxiIozdfEWD31rmR9zyfGUspUuGmJjXOUuTggtGrlvcZcfAuaCEkjxjx0P7C6fl3r4lVWbEfvg6vr5pkjC1wZJMzLtodRcBuNawEQaaRUTJF4bF6AflKVT7xfu/c5M27+Uuf1ztmElhnUHmy7lJHxv2+FCggfxt/yWWlh4l61XauJMZOdZyXo46W5ft8Tbjr2XvW9N1MWCL30kur6eG9MiKcvzd1sQi4cjMgJrBw5cgwaZnFSjwO04x+ggqX3PLQa42/6U7Vaw9JQwHfo95BAz0Nqx6jmCyebdNEVNukSYwKUj5vWlKm8F4WbFitizBmU7HlmZ0EApXkbMEwbCKYM3jk0TtYMMWZ3SvRXU+n+ID3FmNTJ2DmSDkqmGLuGrUh5+UHXtwoAzuJembTx8ijF2KTB/NQ5DIiglaxqVeurdlgVk526+Po9RfZISWSNCkpt+hKC5gYgHv/DqOW91C4xNiqYVtk7UUd7tIqp+cLJJhvTR9nEVIKCUhMpbe/HpmDpGTE2rL2V9WldB6z0Eso4H9beitZPnpFKRtPRqlGMXWLuxr9DaepIovPen+dutfsD5+ew9WyM84Z2dSqjcPMSZZzziXmUbBKNG+dQblTlp7cy975I+zGMrQyJMb8M7PRAtRIW1pajI64gjIKIsQgpHUPdOEeszBQAvOXC4+vmm2NwoPbQULvsYGRNvfYwINE7b6Mla6IKEIuh9b0zIqRRbJFC971rY7vF+sqcUkiMpUEI0y5NOVL6P5WjMWJMESHJvE1obeB3yRGDT75Y9Dy4GiNOOrKBzTmAfW/vUgHh03bv89p1Qbv3DXM2roiXL06U+uWxpFGvno/ZvOH9tddSirHjdbzHeBpCHynGPpUSmN4bEwo3LWXjXqzebHrV93hdx9Lpe9yZoLJiO5ob2N3xjxU5gZUjR45Bw5BXPiSw676fo3nGZBx6bLhyTsap0O/LpFr5rDIQSApM/wthd9irFYgY+zMViN0jrOj6hJ6HXrLEmM6bSCC//Ls1MUZxJ+yCvXCIK0DvlGiIsXR5vZQSAgLJvI0YNrEVrdecQXcVrnxq4mCg6CrGuDEfM+y77vsvtMyYYhRjNi1sPer3yTNbNDFWf9KbIw6z46YUEFKY1e3izUpBOHxiGyAFpBTm95c6ThYRuIkmaxRRKnX7EiZPIe01qmQE3XeJzleqtIKuYV+A3jHqwsk49Fi9W5skwlinMektMUaEFOVhiCY6V69Q9jy0GuNv/lOzGQN0GcGuT/fY7RBjdnJJZaF6lERKL9+OMZ+fDgHawTNcmYQUkJW9KN5Idd1q6krVo3u/NOkdPrEVo689jVnf2AABAABJREFU87+rifwRIqRVbbuMKSm83V0ltHE+OYOssWRmZfm2TOOc5+0QYxPbooISvrZAxFgrNxBS3EqqHYmjGKPrutfQpK3k7lzjgnL690lEiFJrZkHEXSnTDD1GjDWnuTHnaByMYKnWURBK7wO1B/rNYosT9D4gxpgblJ+eE2N1N0Ewfe94FXvH3lgkZ08xllpaXY6Cb5z7ebtttDR3YwYpbfs/pHbnSiHGgrwlULhpKZovPB7D2+urunJE4K+eaVSWb8fu1b/BmC/UV5TWOhJ03vuc3r3Pc/eMzc8fXN3gIoXAvre7VHuIbRAQmUsXbloaUTHFUZq7Cft2dDVISidmgx7nHlPK0/PgGkaMpZRZv1dxr9i4l/KbAIq8KtxMirGDt83nBFaOHDkOCAQEkvnaxeiaM5QxCktACWFXHyS0imm+JmvoOJE/gDbWpXmId933czTPmIJDj03bUtairF1KiBgDz08VxhxXqhWmGEPquAEA6DUuJfUNhN1rd6Cycruzgh+6famyDFT6mWKs/qCUzCdizE42DQFgrqVQTXGlzNE4rKpHOHOL3nkb0XzhZDTPmOzokDhRSSq/yortiig1air399KHAAhUC4l1rdU7Z/r9hJILKANh+OGtdoMAaVNIJ2835pwqgzUJfHNeSqUgVMTYeGcnUUpPRKkAU4x97hxNGptbcvIUUO1SuXO5ak1Tfv2iMlGcoxavrv3fRAhXrZlNEuRIRcoEvXjzErRcOJkZCHxl2aryXOM8QkgxlxIJ2mbcEmMRu0f3AekZ55PNdWNFFgD6jGpFjU3hc9h+rnaUUbw5Zpz711CfSvM3ockQY/abyA2j5hFjIiDFWFuWEcUYK6tvzBvFmIk5l2O/oKvQLFIYV2tXnUGtWOoPPQ+Hxjl976QFUP0/uwxZ47ariA1riLHJGD6xzY4Hznn2WJpizG/7EjRH0KqVw1uDtuWjdy7ve+n9H0gjxhD0fwEixhQpPezwcD4mWO1JKLf2RtWaOVLAB3/94nHQAi+DyKtbkzUjp03iA3M4WZCWGAs25/BfUCq/znufCzcI8Ikx/ep5SPe9a+tsziGBff9HEWPjb74o9fr8c+GmpWi99CR3TEg5pzR3E6qFJF4Ofp5QhFTCF4R4g/fPHQC6H2LE2EEc1D0nsHLkyDF4OBaxGqF2r92hDcZzzFfOBIydM1DZi+LNix3j3JrnRHrZvBOKvXMNl+2GclwBwdz7Lo3k5U48AYGu+/6LKcbc7yTf9hdCb6X+HkZ/9iORccPN2xJjf4ZhE9vYnbnpqORWMRYSY/497FlLirFzTK2ZiaBTZhXnqPPmxRjz2elsR5gcg0Ws9ZTmbVSy9mvPiM3TnHnIvkKC0tyNaL/vEoegdEhb9rk0byOaZ0w2W6nHTAktEDTEWBpZw4mjWqEcxJzju2dTevpMCkJ+j2lzMUOU3neJycQa4+G8bJd2rT302PEBgebDqDU/d44zP/bLLcDcmG9ubKfEHGmQbNMopW4z7n3G1do+d8xnMj52kmrlEicfGhyUck8//aVA8ealmhhrc9zT6S93baWA8G3XnmmMElIAqvLYc6s7rdupUWmwPPn9YUCgpBVj3K1dSPsEIOUhII1x3nbtGRDmmkwZaO5VEWNm5fzwNkP8umWxnaY0fxNGnHiE575j0yqSXF2jutMqhA5im2a/4RD/UgIDAt0PqVhMI6cd69Qtb2PQbaSycjt2r/mNUtd5bYvGfzpn384End/4uTLO21shaCwwfUnnC9XeyL1PEUHSlNMY5ezcfUSM3TMbfPTgCmKrpIXaTfnCyTZGp1H8ev1DwrhztV57Rmb/F5K7fM92XcX8/q+PK2JschBSwu//UgrtzkXEWDrZlqMOIs+Lwk1LMLpBhU9p3ibUCklIIvqTIOh5sSbGDhnVFL8+G9y7H1QbBDQS+qKyghFjfl5ewWqFBJ33PZe+Y7RXLiLGRl1+UvS+OEgxNv6mi8L78sszoHYpHeUTY/55GqX5m1ArMmLsIN7AJiewcuTIMUQI879L1qhJijuJdleZex9ajeYZU1LIGndsIBXTaEPWCG8MsATOQKVfEWOfnZ6pprLuXBs0MXamkw8n0wgDhcQoxtxrh6SYJcamMONceOOeMMfKz2zRxNg5QT7+Cn3gSsnKyd9THr0P6xhjM6YE5FmOwYN+C7VrzXatYqqPzpuWoFkHxs1SigCKNCJizL+uUxbJ4rHdd2mg3ONED8EnxmL3Rn/7Vm43rrXpZVZXqBUSx7XWJ8X8c5N5G3HYcTYAODPHAmKsxokxhM8I/xpFHXQ25sacYzCwzyBIoG8lGYxn6LmzfqZpd1mzG6xQhErxliVou/YMR7ViiBpjcKu8SUnRqomx2MIDueRWdfwP6ntSl8+6prpkU/Fm1R6GTWxljSe2qCFQmr8R/VuVca7uhz9bYdq1hCbGtIvv8MNbdVruQmXdcBUBoV0pZ07RmbhpSaUswIzzT57B3HndeyMDprozMXWtFktEvIPkaABETqr3pfkbtXF+pv2tGKnDX4o4X6N2U25uguk74G3TXqP3oTVouXAyRkw7VrUd4z7N2q9Q51VWbNfzoOnm/Bi5pMpRRtc3fo4xn5+OYZoMdtoNv1ch0PPQGkWUXnsGiBxSdrHb/wGBvTt2qb533yWZ/Z/OLd5Ifa/NlDPW/6XUu7VpYiyr/0MyFfF9l6i88/Z+wGDImivimwhx7Nuxy1UxEfzfQ392iLHob2afXSExlj53rRUSS4xxL4OUicJgiLG+GDGWWo6yJcaIkCKSySe+pFVrjrr8pJQcbX0YxdiNjBg7iFcrcgIrR44cg4fnpla8eTGaZ0wxO4hlUSTJvA3o3/p7HaTchf98J7Km/V7XOE97ZPcQMTZjSrQM/Fhl5TZDjMXKzK9RLSQoeMRYFogYGx25Rx+1KDEWLwcAQ4yl1TX/XH5mC/q3/B5jNDF28A51BxZKxbRYGYwNxFlI5m1EE6lW4P4O/PcisiaNGIv9fsWbFtsdoyLg11PE2O8dYsynXgk1UozdewlzKXGhuAD1TWneRrTMmILmGZOjedq/QrlzrdiO1mvOyJzzUjlIrenfY6yPl1hdE1eRU7b7BwmrauMKQuuRrQ1XIlkG1MS8RbvWGkUGy9N9Fuv24Kn8VN5uOWodnKxx3QyjhO0Ctz3wvHk5pFR5U98ToIUOWDdffh9SuVI2a9VK1sNVQrl8EzHGSTCn/+vr7evgxnmruWbMfVcOAKX5G21dmxvLW/1QoUgZraRYsR3jb/xT2xaQvphQvHkJRl9zunF/NWlleE4yfyNqnYnZTZl+31ibqHUk6Hl4tWqXZJwL548pt4BaIFTE2CQnja/2BbRqZc07Tjw2wdLy9LVCgq57NTHG4pAG/V8TUj0PrTZ9zy+r0zoFsG9HlyHGWFZB/6e/Tt/z7inHUCHUJkLGvS+7RmuFMjrv/XlExRR/9jgqplSoa6qA8Nsx/qY/Zfmll6dw01JPMeaWQbJjccVYvMy1QhndD65B+zcucYmxFHQ/qPqeIsbcccOHVWtmEWNSj3tldH7jOc+NGQf1cz4nsHLkyDF4SPtK5m1Qk5Sr7e59XP7OX7VCgsrK7Wi/51KbD+JplYGwGM0XTjEGgvTTwhoThhi7+gw7AfPS0gTPxgC6FMParSJGePnbvDei+UKtGPMtbu/VRyulnz0nXh8M1Y7EKsbaI8a5dMuU0E6JvK69ctBxTozxyWWOoYOqsDRvA1pmKDcH4Sfw6pnIGkMamXbrKjsAq2LKIsa4/pCIsdZrGyFK48QYtXtumAkIo2KicsSmSdSuSDFG8dj8LgLYuXCV973IPUr+RmrFGIsxZvIyxp5VONi6PtP5KfKmP1ToumXG+bCJrU7MNMA1jAFtnBcSQ0iZ+o/E56MNAnzXWj9vOqnnodWmPcTAk1Pcq7ZPnuG0nVhbHuhIUNS7tQXEmHd/Ut9j08lHmJhzWTDE2D2276WZZFICnVwx5qfzCk/EWIwkyDF01DoSdN33c9fVGvwZySCB3ocVWdNy2cn8sPOXsO9tpWIaf8OfhoStfk9dhfpem+57Jm+vTRJK8zaiVrR9L400onlQz4Oq7xEx5owDHknW89AaNM9QxnlW/we0amXNOxjDNyqI9H8B5Vrbde/Po4sUMQ6l96HVaDrxCGchxr+/HIOFirtZeWYraw9h6+E/x67vPo9mpmKy34U/miXGwh1d/dTVQhmd9ylibNjho4IU7ifBiLGTzbEwlTrTEmMXsfvz/9qzrGJsVLSs/JngE2O0uGd3XragzTna7/WJMVsWqf8KCevGfPYkk2u0QAcRcgIrR44cQ0bfKkXWKBc8ZC4K1IqKrGm75sxwlxIPQggk8zeoWCvXnJGeVhM2VY8YkzJSBjPSCBRvXoyWGVMMaeQQTfwUCSTzI4qxCFEBEGm0Ae33hO5cwblSGR+GGPO+sy4j6m+fVoyNcdwMXUKD7tmoVogYM6RJvNw5GoOAQDJ3I/a93YXWa86wbhZe26F65vHYTGwR/R2PdUPpyb2vZcZkFQ8l8qLzHGLMy89/ccXY8MPbInnCIVlL8zYEgVCtiwpYuYVDjAlhj/vXoB09izctRvOMySoeW0p5qU0n87Ur5TVeINRIPe7rKLG6HhWWIccQoOq25+HVGHGyNc5991D+qOWqFZ0DU4B4RoVUixSjPePcScPOT+Yr49zfVdI31AGmWuGKMYSmjdT/dT+0Gi0zJqOFkdJp6laXlA4NO0fJyHcpPTxCSHnpk/kbMeLk0Dg357ETOTGWMZzmGCwkqbknY0SKi5FD1qzcjt1r32Gbc6Sj2pGg677/MsRY7PfiC3A9mhgbxYgxno6P/4YYY32PXjFyp3izMs7T1O2cmErmbUSto2Ri36W1X4Ap5zURktr/dd5Zde33bU6M+Wnytj9ESLWJUPGmJWi59CQ9fjpfm/9pXC3N2wQAGE2xEMHbonDmr9VC2RBjh7Q0BfNbIe05UgLd331eq5iOdQohpf9eIHl6S6AYo9iD9Gyn99UOS4wNP7yNZW03eLKxCNVO5pYYo94m2P1ZhdVehxhzKs6Z00gJyAG1GcPoa07H8MNH2WSmAbPWLKUhxki9y+//YEZOYOXIkWPQkJCoFcsozfPIGjYoAe7jVcX/mKJUK5ppSVO/Vla8gcrK7Wi95sx4AoZaMUHnLYvRds0Z0RVKAl2zNG89Rpx0JFqvrr9y7hNj9VC8hSnG2DVjUCvncVdKH0ZNFSHG+KSQ3pZ8Ysz7PsfgISWw9+1OVFaSrJ0mOrZS6femQ8WbFmPUZXpCqGOZxNuEQDJPEWOqPdi4Z7H0qu8p977hE9tS2xlNmnoefMkoxqSUTnrbF9XfPuPOdWa8vUh73r6Okialz3BcSqhO/HIl81WcIyIg0sotpQqyqoixxvpe581LLDEG93fJMVQIY5yP/ly6cU41XesoO6oVX2XoRBZkxnnLZSc7aWNrD447lzGm7PfSO0Epxs4IFR2R8hMx5pNGflkkXHcupdRi/d+7htBGUItWraQRCXTU9L1rzgzqzMeA2RlvumOM5dh/8PaQVv90tErt4Z5Lgh1+hX+2pPif6WQNb8ucGEtTwFL7U33vvxzFGC+n30d6tIqpJUKM+TDE2M1/Gv3e71NFo1ppc773I4tyYozGhLT+D7ghJRxiLFKGHI1DQqA0dxNGTjsGrZqsoVhj0BtWSPMX2LP1PVSWb8fYL58PInZ4eieGYd9eFG9cooKU07NYWCKIYrzauLSbIAEbC5GuS/lJu7t5tSNBZbFWjDWPsOUAK4t+LyDQ/W/Pm5hzduFO5emSUmrDJqMYY0wwkVs0n4NUi3hdRIxRm5duTEOwa/U+vMaQ0pLVr81T5SukUMTYCutK6WwEdZA3+pzAypEjx5BQvPkZh6yJgZ6vRsVEkxS22uGjViinkjUxlObFyZqgLFIaFVPrNe7ENEoSFIgYO7OxuFfzN6DppCMdQirNiFbE2DZDjKVNkgnFWxaj5cIpZnDMJsbSY4w1cq0ccdSK1jh3fwfmFmF+b6HcHE46AqMuPQVqciSdNPw33Pt2V0CM2TwBf0pfvGkxWi872RjQFEQ3hmSedue6xgZCdUlP2xdpMwZSMcUhzHlkjDWbrdRd8OtUVmwzcY78unDPVRNC5TZzhi6HXdmN3aeJMeYQ3nk731/UfOOcrShzq1EAwIAia8g4VyoSadKZz1BtzTXOhUMEcTWgigHkEmP+QolTFqk2rhhx0hFoueykuDs7O4erVsiQMiWRCM4nYkwpKoWTl6NShFpIqBUTG+tN2jLzc6WUNsbYvZdotxn9nblZVu4BoJvqeuok2/9j95ljUNi75T1PxSSDNgPodlLei07m3mcNVZjflbelZP5GDPT1u4pSuOoMOs773iEtIzSxY41x6lOxvucb3LwtkKs1qZiITI61G1LYGmKM7eAZ9H9dHjPuXXZyZv93+t5Nf5bZ/03fu2kJ2q49nS1ShL9LjsGj/MxW7F7zjnJ943MPuNUqoebF3d99AWP//vxAQRg8XiXQO3cTRp59jFIQCtY3YJ+11P77t/4elRXbMe7vz08tAx1zFWPZ83MJtUEAALtIwaYH/nS6VrDE2CHNTUEZSCFJp3X/2/No1ooxes6D7s97fJcXb1Xjnt4xWrDr+2mr5MasY87RrtP51EYhJ7By5MgxaFQWb8UIj6xRCA3MfTu6rIopc5KhziveoogxIgn83Pmn+iomWvFT/v2cGHMnTGHBrIqJG+eM9GLH+laSK2W6msrs1lYsB4qx0EPeXke5Uh6pjSCaAMYrMogxFkF4rRyNoPzMFrTMmKJ3jFK/pyv5toSWMc4/F+4qaVcsIwaC3qlJOOkB2KmOMRBaLj3JrsTpVUx/56a9O4gY+zO2cieDspi+d7N2M+TbnXtlp7IRMebv4BnbParqEGNt0WvzHTKVakVtxuDkbRYd7XVM3zNuZWG5c9J2aNj1b8/b2DvcMuHQM2qjWrmGXFrV145xrtPXCmVLjDU3eYYu70vqmDHOp01yyiFsgzDHKiu3WcUYlcGzUIQ+zlUrxrWW8vbbjFTG+Qjqe0LYclO+wrZl35XSL6fZuU2TETEixJzn1T13pTRPCE9ZmWMIkBI9D72kjHNq86yd8TYpoHaVHHn2JIy6lFxrI2OrzmPvVkWMjfvyBcH3fjuSlb1O3Cv63if+yUDmxJiIFIGXo9qRINGu1qrvuclMn9LX63mQ9T3Kx89Xt8Lk6a027lVG/wd0QHgz7ll38qD/a9gFoZNNPrH+n2PwqDyzRauYmszsIA3d//Y8WmZMxoiTjwi+42QMwIixiLLV/1wrlLHruy9g7D+c74RbcEZzYWcvpXmMGIvky+9jrybGxn75fHM8XCRUIGJslCbGYvUhWVmSeZYY8wkov24UMbbF2YyBiDw/rZSaGGN9j7tdpl3nYEJOYOXIkWPQOOykIzH6s+RSwh/vFK5QkzWFMrq+8V9m9z4JUorEhkiJ3odfMsSYTctTWOzb0emomLIgIdHpu/dFy6DKFqqYpPmW56nusYG4VwyleRuYYiw03vn1rGKsAVfKQoJixJUyfo85BosmTSISwsmD0MZ5gp6HXkL7vZem7lpDv7aE3TlzxLRjs/OGag+WGBOZk82qYyC0Mjs4fkbvQy+pgPCXnuxdP0y/zyHGXMTK1KmJMScOWOQ8QG1UQIqxIG/ppk/bpdQv+cE+0RsqxnzuHK0gtPCVq0II9G/5vWoPN/6pk85XVgGALO/Vbqdu7B1r6EpLDgFIFjBizCuHTxjUOogYuzRw53JPVu4ZPQ+/pEnpSUFe/ue+Vduxe907GP35c6Lfc1R3sgDgsXYphEOAUQDwGBESLgjt0nX9Zypdmhtu+t3nSIMQGP25c9B0kmucx37r5Jkt2L3uHbRde3rdbGsdZez6t+c1McaVre7Ch7oYNDF2jCVrMsbsvVvfQ2Xldoz78vl0eioUMbYYLZed5LjWcrKI4gcByjiXpBgzJQn7v5QqpIQyzhUxltb/Cd3/9oLpezxfv/8DrmqFlyMWUyvH4DGaPadoXhIDkTWt19pNMTjRRGSMImvKihjTZI35TsRn3kSMUd+TPE+dhn7uhCvG6qBWSBQxphVjPG8fAkCiiTF/MwYBOM9aKa1ibKzue1lzm5hiLEbSUfpk/kbgEDi75+ZwkRNYOXLkGDQOPXY8RIvyOXcVHXCO9Tz8EpovnIIR044z5/KpOVdHmFgrLEh5fCAVjBg7Rys6bH7uS+XQ+/BLxr3PxlqRkfRcMXYZm6zF1SiAMIox11AR8IclCYlk/gbs29EZuDpJZzpgVSuuK6VwzvH/WsXYCSl1kUYc5mgEI6cdYz/I9Jos3rwYo691Y0IB4QRFrd5tQK1QwmhfuRdp+Jys4cQYjzfHT+t9aLXue8eiHvpWWGLM5JEyiw2IMXb92KlEjI265ORotvw8ToxBpk+kCUVGjFFesXLkrX5oOPTYcXCf2HZnJGgDct/OhBnnVl3nEqbMOJ+vjPNW7VrL09NVyDDtd9y53OcvbxsCQhFjt3BizL2uPVf1mdL8Dca9jz/nQwUhJ8aUSsFNxyABeMQYL6NJJqXpN5VV27B7HVdrus95PjY4cY5IvasJB6sIpXE1x1DQdNKRMHUo3DZHaqNahyZr7rlUtwcfbpya7u8pJYUyzv12I7QaT51VXrxVEWNM2cr/B3vvEmNp8yBdHskVY6c48x9qN7xN792iiDEyzimF3/+llIoYu0kRY9T3ov1ff07mbQSE1AtC6f2f5nqKCLmU7YwX9n//WI7GQS7fWU+NPWveccgaQqzOa5V+2x78nYYlX+JWfxUxJoPdlKN5c2KM9b3YDFcC6P7uC4oY04oxwb7zkXiKMeeZrctOR3xXSj9PvyazFGP+PIXUmmP/7oJIKXMQcgIrR44cg4YA2NIIMxJYIMdkvjLO264+k33H00LL1Mml5CVFGnEDgZ9n8oYlxqYea0skEb7A3Lk+w1UrfEIKU6ZaIUHXN/4TYz5zDoa1t1qDgMrK0gJA78O/Uoqxq88My8nrBELFe1i5HeNv/HO33gBbLyzvzlueQcuFUzCs3bq2OEaTuY6wxJipa+8HY3WSGzZDg6T/dN3GYuv0aLKm5ZKTvTYAh8yC1EGpSUkBv0+FeZtg6dQuvbQ81gkRYzzWiojkSW3eqFaamzLLoO5xte17Em78Bu9liDEipSNpJCtH133/ZXbOpB0N014OMcbySq2bHEOAS+gEE3Qp0PO959E8Y4o2/LPzKi+xxrmfl2uqK5Kg+3uhce6awtYAV8TYpEAxZsttTaa9W39v+h4ANibQewtLjJ3BysEfsW79JIwYCwk6lyTgirFDnG3rRfheqqD3rlrTpsub+IEHuXmbzwBkuV/FpNQxCEPCyP09kvmKrHFdrRG8l9CxMYkYM4sUbEMPb/zv1n1vhOl74ehO5U8Wk2KMFB2CpVEvuk6tkGCX7nvDPVLaLb06zomxdKi01PfGMlfKWP8HBGSlH8WbF2MUq+to/9efZWVvxvVzZEGNnZZYd+cIKgTA+Jv+1HGthbRPNDM/AtD70BqrIPTHe3Y9SGA3I8YEyyMW029AE2OmPbAGSWM/H/+TeRshhSbGpG3jPP6gJaQ8YkzXhxOr0FxMEWPNRIzF5hwsbeBKGXlY0+m1jgS7vvs8xv39+SoWIpu/OK1fxvM5mJATWDly5Ng/sAcpGbNKSbEN42/4c+e44LMkhuItz6Dt6jOdIKFpz+ZkgSXGHCM3AmWcv4T2uy+zu9Z4xr45XzBijAwEVl7/WuTONfozPM5RHNWOBF33W2LMua5fDihirOnEI9F6NVNqxYxzEBFi65qnj9XNe1+YU7e8OUII818c5cVbHLImGo+GJoTFxHGtVb+Rm56fTgpC61ISKZ8+gRNjPJ80Eqd482ITlDq13DofQ0o7GxWA9RF7bq1oibFDRjVl5g0wYqwRxZhxpfxIZjqKfVe85Zm6eeaII+05TGSNFDJjwwhmIHQkykC4x91BLPYIl1KpVlo8YswfPohsKpNxHnE7pfMItQ6uGLMurZSXc75DjNm+l9aK926xxFhaGroOESFpLt/++YoYK3nuXPH01UKC7u+9kFKCHIOBJY+Q2h5iELDtYeyXL6i7cCTLPlmTXhbA7XtZdiwZxVwx5qdnUyAAFHtH9b2s/g+o2JC7174TfQb4/alWsH1vuOey5vdrAIYYa9F1ndb/AaUY6334pZTS5shCsKGR96N33ftfaJkxBYceO16nsd8Z0kuqc8tPb0X/lt87nhTOTsfsx/aJMT9Omg8ixlouPSmaH8eete/omHPns++FIabomJSIKAip3DYtXUsSMQZpFwg5DNkEQ/4ZBWFzykYo9Bog19rJOOykI4LGzmNFAooYK2m3zoMROYGVI0eOAwYptYvR/f+p3ftazXH+l6P3EUXWBBPCSNp971iyRg0u2eUxxJhXjhiMasUjjfi9EQaKZYcY4+CBXgm9j7zUuHG+ylOtOJnDmRXWCowYayD+FtV1jsGDtmOOoRZZOc+KkaN2rZmCkWcfZ6eOQXL1jSXGpvsJ3PJJaYixsV8+v6E2r4ixI4yBkFXuvR4xpkrommX8XKMYYxPTtLxTibEIakWtWrn3Mojmw9JvTl9PxRfK2/x+g4wU/ZHiXo37uwvcSTn7K6F+x4FEkTWjLj1ZGa7SSyrthB/QxjkkWq8+w0kY23WsSsb53SwotUfeS3ZO9/eeR8uFU9RzULrf+av4nBgLyuHda63DqlaGtbc6+Tp1qOuEiJDWS0O1pl/nJsbYDX8WjklUdjpW7kfnzYtx6KRxyDEEpBiY0mkPntKZpSPlyD5qD1+OtIfIqzR/I0ZOm+Sqd/k5sEM/EWPjvnxBmNZ7T0TpqEtPVotnaen1x2TeBgBA29UeGez1fyAy7qX0f9P3/k2T0ice6Sb1+j9khBhL6f8SpBhbpTfcyTFYuLsSA/xXTuZtxLCJrWi95nQz3vuKIIp3Vu3QGyXde4mrXGSbDnB03fdfaJ4xWRNj6XMJQJE1/Vt+jzGfVYtWfpw0Am2M4yjGvDx5uQG1eBYjpd1A7+rDnrXvqL5ndkr0Fx5tHVHMOUVKp+3qbJHM14oxb5d0nje9ah1lVJZsOajbfE5g5ciRY9DIMop7vr/Kc++z8BUYxjj/XH0VkzLOFVkz/PDWzDIAGcRYBPt2dKGyKqJiSkHhlqcdYozDH1S5K2W9XaKUakW7UsaCEHuGWc9giLGVGcRYjiFAT1Qq2qXkUu7mkP47k3Heds0ZavXSuJy47cYJjMvagz/54uj+N22ca8Imqxy272WrmABNSnvEWKzMhN6HX8LIaeGE0I0pp9CvgxBzYiwGAaFcCG5+RinG2huZEBIxVn8ThBwR8OcNU/IZ9z6vPZhz+LlQgdhHTlNKipiLCodjnPt5svdCAJIRY/7KuXrDztEKQgDOZgx1Sem7WZwjnpbLQQZ0nCPd9wKlsUd2cGLMHPbSU8Djakfi1DXlHfRsjwhpZNzLkQL6LVglVzsSlBZs1O3hsDAtfdQqiV3f+K+gPaSN/2Xm3ge4am+jXodqE1VNjI2/8c+smtsvB/URTozx9pBCvvUbxdj5+l7Y96z/CwgMaMVYi9f30shY1fc0Ke1d161ANQ9yYoyl9H96TwtCh+ULFUMEXxm1JA+RNXbTGNYQOEEFqcfmxWY3Zenkrd+ZtiwMMdYWkDV+/iwe7L2XQCIM8s8hIRkxNsHkwd1veRM1xFjEBvHnK5YY+7PUuLQ8DmHPQy+xzRgoph7P0342xNiXz1f355XbbFog7YJQ69VnYLgfY+wgQk5g5ciRY9BIM4uT+RsgJRwVU7jDjUKtkKCy5FW0330ZDmkekX4tfX7391ahRZM19cgr350rC9VBq5heGjIxlqXKASKulAw+GeHEGKuDaiFBzyNxxViOwUOw2bNvMKpv4r+z3TGKjHPKJ5y0qdW7ZzDq0lOc1TvanVM6U0ShiTE4ZE1sJ09Ay9qNgZCtYgKg4hxd2EicI7tjFK2cuxNHPnUU2tVpFcZ9+YLUvsc3XUgcY8x3UIHz2RJjjZHSOeqA/XTd31tljXNj2YanCCFcFVNW9pKpmGLEWCR9aUHEOEdcqRELSp2GgXKcGOP35RjnC6xLiQ2mHgcnxg7xjXPvGnJAouf7bt+jjQedDSIEU2t6xFiO/QCpfCr96Lx1McZ8ZjqGH96WfQ5UmAMyzgH7W8XG/1qhzIixJie9+161uS5NjJE7Fy+n/z5J6XsxIq1WVETp+Bv/LN73PDVK78OrMXLaJL0ZA1L7PwDsWbsjiHsVZK/PJyIkIMZS0ifz7IJQjgMB9ZtV9aYxlqyx37lEEJE1SsWkdte2eakmoNIQubNbtwcixvxrO/OgPqUoHfPZ6SYeW7jpgCV5knkbMXxiq5kHCaesbt5qB/GNaL/3Uod4MuVl6QUEuu7jrpRZ5VYKwv6t72H0Zz8SWaQQzpnVDk6MtaVuzEP33vOwrusZUw7q+J45gZUjR44Dgv6tv0dl1TZ35RzxlRJZ6Ufx1mfQcskpysWIpQ/SSmmIsdYGyRoixlyyxl/9UOj5viXG6kERYztSiDG37I2796nz6inG+OpXY4oxW57OW59JVYzlaAyC/U9N2idrePvyiaNaoYxd31uFsQFZw6cp9m9p/gZtnJ8UlMInyPq3/t7ZSp2nd1dNSTH2jDEQ/N3UQqJUxVhINxDs+co4f5W5UtL1fUmDuueQGAtJKbpXIqXdcsQlMUSMKSKkvlIrRxrC53GyYANEy2HWOM+gShzVSoQ494PSdt3/X6lEqd8uGyXGqBy7THug2DtufvxzkkKMmaKyMU31PX/cC/MHQrVmPduDE2OUq7p+WB7rSnmZE2Msx/6jR5M1zRdOSSccjZJCG+cNLJ4p975nMOYz0xsgbCWSBRsxbGJbQ22+1lFO7Xsxo7frPtX3DjOqFXVXMZQXb0H/VhXnKKv/SynNJiExYizog0IYYixdvWthVSsXpKbJMThQDbpkTXb6ZN4G0x787xyiHXY3ZZcYc6/N0fMgI2u87/zPRIyN/tw5Ji8+83BmH6QY+2z9vgcApXkuKe2Dl50TY3VBak1d18L9ynkvoPvea7auD+YWnxNYOXLkGDSk+Q+glYzu76/C2L/zjXMZ2uYASgs2YOTUSXaXkiCRXfWIGgiRlQyAVkotMeamkXo0taoXS4ydpfMU3qhoiYhUYszY59KRxXd/fxWaL0ghxryRt7x4C3avecf498ehym0VYx8JiRCnGtWH3kd+hRFEjMUk+zkagqk2Se2hrMiauy+DaB4Bd1XSXZ0EhKNaUb+Vv4JnX5YYO9P7zqYVOg+XGGvzrovgPKsYOwV2ldF+b86XQquYtumVc8HKzVc9FQYqe5lx3hZc196v+muIsavPZGV2y0L3WC1wV8oRJi+RUjeWGDvKyzfH4OA+j41LiZk8p9dt3DiPk5MCAsmCjRieYZxzQ7lWhxjzb2FXhBgLiF1OlK6LkdIhXFdKpcwxapvIgzbbvc+9zp4tcWLMprbpB8pKIaT6Xk7YHigI/SzmBmMaYSOhSMQ0siaGnkcYMYZw0YND9b1tGbEQ3fZQvDWdGPOvkszfYPqee3/+wgMzzu+5tCHCyFWMpfd/AYHkmS1RIoSnteVQcUh5XWeRaTkagwpSvgGHHjvexiCMNQl9vFpIUFm5He33XBp878cjlFLFxmy+cAoOnTTeOc5NBWolhhj7zDlOPvTySaOeh1Yb11rfrDCxDfU99jyk+96MKSofys8j3AQE9qyx414QaN6/h7JHjPEyI3xfmq+IsdF6AxLflZz+Cqi4ejTu5cgJrBw5cuwP9AOWyJqmk44KBxpKp90urJLirPChLqGMU+3rXS2ULDHW3urkqYxblzQqzdfE2CUnR8qhhzt9Tv/Wd5Vi7O8ucEc2pzwSUir/fkOMOeVwFQSEZAFzpYwMvIZs0vdoiLHmw+LppS13DxFjUyeF3zvlEIYYG/3Zj7DZQW7QDwlUzwKKKL3FJUoFT8MnWNJzrY1NCNlntWMUtYem1PZAP7chxnRQ6qyXCYxL5fDLzD7XSMXE+55fZjbpTLRibNQlp8SvL+z7vZqUHvt3F4Rl8O7RqWtWDjPZ814U5yi4xxxDAJGDErWOwRmMZJy3XHhCXUNXrZxv8wxX/xxNsJb7USR3roltXorwHOXORcSY8NK65XdVK0RKS7hloXFEoOv+/2SulATJUtqjTgDwzHskYmxVxJVSsnf2PSnG8rhXBxb7OkooLdjADEaPlPfGfyJK66lWaGxWxBgtWsnU/qSIMep7fHGAw57b6xBjgN9++XWIlFZ9L21RRfUBqRcpyDivRxgRMTa6TgxCCYl9hRJK8zdYIiSl/xO6vvGfaPHqOldgDRFsvtK3chsqK7eHcSMlq339s9cKibNZi/+9A6Haw4iTjsDoa89Mb8J63K/5xJifnRDO+G+IMWoP3thvpr16jmCIUjaX8l3PVcy5UjDu8TmIj0y1pjeH4mpNTrAF8zGouFedt6hxb9jh1gY5mKc2OYGVI0eOQUOY/wWS+euVcX7NWexbb3IHKKO4WFZkzV3aOA9UIjohmGqFiDFKp3fhcP3JhSXGrj7Ty5dYB5u2ViTF2IVsQhgqOeh9Mn+jJsZOsXfPA5FQcEYh0P8arZxfmFIfQr8VLjEWU614L4cY09dzfxV7fkCMUZqD2Wl+P8AnQD2RIOWxapVmksKUFH5T5+8919p6SBZswCEtTao9CGRuEhBVEEYmWJRF9/dXhe5c/mRQH7M7RmUYKmzSu+t7MbVmHKUFG9y61s0+Vt/U9wwxFrvHHIMHI2tUYNz484k/i8k4t3Nx+2ziyjlLjP05C4ybThRY1coJLF9NbnnXcd253DyDc8t7tWrlHKOmotK6ZVFIFpBq5cxofpYoEIwYu8y41sbGPuHVtTPupdb1VkOMCfh1kWPwsO1Sxb06JzI2+78aVxBy1SwQ+81qgZIioz9JwYgx173PjwHk9z075+FlZfcYUTHZPKV3njTjXvOFJ2SXGS4xltX/AUWMdd6yWO9cnTYPsmVJ5itXylZPoZy3+f3Dvg6rrotvUKT+0jyjNH8jWi6cguYLp9TdoKhvxXZUVm5H6zVnmmDkaah6xBiH0NfnbtyKGDsy07VWsvlHFjHmo3jL4oAohSkDvbflIGIsqz7ULoL7odb0foeDFTmBlSNHjkGDho69r72rjPO/uzBUlgDgk4uBvn4Ub30aowxZw9O4aQEgWbAeEkDb1We56fhKhT5WKyaoLH0V7XdfrlfO/XxdKMXYCUq1EoBNTYVAecmr2L12ByuHSuMGfVSodWhi7MsX6kDs/rXtPah73IiRU4/VxFh4fQ6rGLvQyyec4Mm+GDGWXh856sPGvdJuDp+pv3tfTQfPH3/DnwerdwQ+Cen2iLGs+cmedVq18plzTL6pO/Po9tDaQBw0KeObMfhpzD0WGTHWXH+DgCgxlgKXlKaLx8mrKleMBfeYt/khwTynNFlDvwOtxrMVcKrh2k5tnN91WVTZB0DvZAZgAJYYm+TG/4gp8srPaOOc+l6kHPRMrO3UqhXqe5H8+KvnEW2cXzDFuX5M5adcSraZFfzYPSqQYuwZjPn0OYGK2JZfmGsZxdjVZ1qqJGVlXhEhG8yCEF/BFzJv80OGVMQ5GedB/XvtQqlWtllXJ5NWBG2n1pGw9tAWthkvfbJgA4a1u33PJHXaPHetvUyn4G0nLEvXN6jvTYjk6ba78uKt2jj/SGb/h2TufTf8ud2QJtb/9V8ixlp4APCUfrpnzQ7tSnlOvP/nGDI6b1EqpobisWmyptVsVCBT10aV26lS19lNENKfT8n8jWimvudfG+48hxRjrY3EhSskKN7iEmPZO0ZvxIiTjozm7cy1pFCL84wYy9qwSQ5IFG9dHKg108qSzN/gxb3ShK2Mb9JzsCAnsHLkyDEkVAsJdn1/FcbfcHH6DmLMAu99+FcYOfVYtDhkTRxknCuyJhsDFUWMNa5aWZ9pnHNY1crl2bFW9FjV/f2VGcSYC0uMNVaO7h+swti/vbAx1cr8DRFiLMf+Qe9as2ADMxDSUqp2b1Ur6S4lNNGJEWNZE0JunMeC4XLYlfNwQuhjz9odbDOG7MnRgA4Ir4ixcHcuvxzJ/A0QzU0Nt3mq60Z2ztzF3LlyHDiQwciJUiDeNmW5H8XbtHHOn1O+gQ5G1jDj3DHIvaZX7UhQWqjImnrlwADQ9U3W93SaNELYqFY+8xGwDUajiJLS3j0K9tkQY37fi5Sfxr0xuq4lN8q9OqSNUMZ8+hx3K3UJIwjOMTQkC5TB2NqAG7Ixzu++LHWRgv8WpQUbXOOcvovkT8SYCQifSpQyYuwz54Qu37F7nG/7nmnzkX4HqZ/F+h4z+50+Zogx352LvTe7CD5jx72s/g94fU8TY7mg/MAgmb8BTZ6Kyd/ghWBVTJd5aV3Q+F9kxJiU2R2KiLFQTRXmXy1kK8Z8lCLEWNwNVqBv5XZUVm6rS4wJKG+H4s3PRBVjlIa/TxZsZIox+12sJLUOTYyxuFd8Y5yDOe5bTmDlyJFjSNj1zWfRfMEJDRrnrw5StfKrTGKMo/eRX2HktMbImj3rdjAVUzbkEIgxoDFizKpW6hBjGj1EjDWkWmmcGMvROGRfP3MxqrNCCekYCOnQCsIGiTGCT4xJSHeyyeY0lhg7t26+1cA4T58cCQj0OsZ5mJavEBIxlr47l53IkWttvK7DiWz9uj54J3n7A2oPjnEeARkqPY+8lLpy7qNue5A2X1nuR+dtjfU9IKJaoSy9ZkCuHJwYyzSIpdf3UtIataavGMuAiXPkE2Mp4MSYDEgrkRv2Q0RtZ4LKym2WKM2CBIq3PlNftaIJGVJS+IpSTqxSm6922DEhcKOKkDuGGLsg0ve8ttC3apvT96KBozWqhSTjWeyWGWjkWWyROe5JBAsgVNf1Y4zlGAwUWbM9II1khE20KqYznQ0jonymVComRYxltwehXVpd9z7++0uTjo43qhgjt9M4MRaiyuKxWbd2vzxUKhkhxkSQho5VVr7hEWN2jiS8+6t1lFG89Rld17YcPE2uwMqRI0eOQaBv1baGJylWSXF5/Ywl0JVGjEVGSGOcf3oQxNjXGyPGeh75VcMqpj3r3tGxd4aqGMuQMS/YAAkEk95YfVQLzJWyAXeuHI2jpIOUN/tuDpHfbs/adzKMc3dSZpQUXuydALRinWIgcMk6rcq5BkJMMuN+3OUQYyIzbdIgKS0hPdVK2j1Kc43emGolxSAP6jo33A8YyN2zEZeS0jzt5nDNWZlpAaUWaYQYozbd8+hL6cY5g4BQqhXdHsgATpvk79tZUoqx/STGYvCJMV7KABLY9c36ak0CV4yZLBwXrbwTDAlSouub/4m2BlytAdUemk48EqOvrt/mqzsTVFalEWM8PIJ6Dnbelk6M+T9vlBhLQa0johirM/9oqUNKk/sY73v1UC1oxdhn0/ueH+eo6cQjM+/xYI8JNFT0PPwS2u+5DMMmtjEyxY8/pt73PLyakTXxNPSeFISWvBKpr2ohQfEWImv8jQpsntQiXGIsPV9SzldWbtOKMaKJ/DLblyXGYhsmuGmtYiwr9p1CrVBmirEwtIc/rXfVmiyd8qN06uNgRE5g5ciRY9AY3t6KMZ/+CCNS4nE6Bsr96LztaYz5zEfc+B8pr2ShNhCuOjM7b0nG+XpFjNXJ1xBj55/gbN/rl5feO8RY4MbhxpJQKoUXFTHWwD32EjE2+xSWZzytCkL8hhtjzF8t1a+Biqprs1tbVt45Bo2mE49024OpW+m1y7ImSv88pT1I8HgkPQ+/hJFTw9g7sd+MAsKPiW0r7ZVlgBNj/s6ZkTZviDHT92Qkf3V+lYwginNk+qiIXqfr/v9E8wW0dbbMvMfy4i3o32L7ngj6vz3fktJU10yB5rxyw2YoGPPZjzRsFJNxXpc8kUAxwzj3MRjj3O4ad5njrpLmZpEsjKlWYm1FDMI4V6quqCulLk1QjgNCjOXYbwiBtqvPrKMgVO2DVExt15yZ2r4I1Y4Enbc9k0qMBYTUgvpkDYH3vbpw+l6b+4WBq6bq36pdKeuVo5CuGIshyVKMeehbud3UdRZy4nZoGPd355s5gtTjZXSH33kbUCuUgt21ucs0jbcU5qD97ssamhf3PMwWKZy8hcmTjhlijMeFS5nrVjsYMcbKYWLYeucm8zZYYsyZmwj3XiVzpSTX2tSXOrd4i+57FPtO5yUj5U7mbXTHPX8uxudFBylyAitHjhyDxmEnHmknKXxLMKlXwYR6uPY++hJGTj3WTlIy7EgV/+MNRYxxRCYlA5V+FDkxlrbypo8bYuxqb/teGb6vEjF21+VeOeLlacSVklBe8qqrGEvJEwCqxQQ9j/7KEmMp90bofeQllxjLiK2RY/AYMe1YhFLycLWteOvTuj2w3doc/x4B9aMIE2tl9Ge1e5+UbBXZPbda9N370lb71KvXEGMnuGWQcM8Vwou9E1tNtZAV7c6lV86d3Th1+c0xIVzj3L83A71SWizbWCswWUbuVf1VxNgJOPQ4CkIs3XR5MKD9wqGT6j/TiKzJUq1wBVSyYANGBMZ5nDSqRozzNDWVkCJTtRKUg1bOdTnsd6ExX/OIsWxIlBa6cY6y3Dx8YixMy1bwM4mxHAcC6jmfBZmiYkpH4rWHWJ4Eag/1yBrqH27fy37WucRYnLQClEtTrVBWfa9Bt/YsV0q/Tft9L63/A3yh8rJovEd+jfxJPzTUb/PAvh1dqKzahvE3/rlz3NkRWM//hVBkzehrvDEh5QdK5jNizIM/Na4VGTGmN+cQsUe3vl7vI556N2P+b0hpHvvOSyuZnVC8JXvc8++x6aQjQ0+KSLmprv14j/69+bdzsCEnsHLkyLF/8AJwKAm8RHnJFvRvfVeTNUwZwUHxHgqMrGkk7pVPjIXBTczIGhBjqYSOwEDfXnTeromxBiemRrWSkiehWqQdoy63ZczALlKMpRFj0hrrihh713WljA56uUG//0gjsVQctOjKOV81039rRYq1crlDKqmfVQTndt76jEeMUVbh75ksWB/GvYq0ByGUEdTzyEsYf+PFbFU+JJfoRa61RIzZ8tryE+lkFWP6GSDT8raute5W6mnGvECyYL0lxiKkXL1g3DkahL9S7a0EK7LmBDRfMMWakN5quNTLzLRyrhQdPE/ppIdUpJFRrZig1LR9eliekul7Z6WUVRj3LIcYMyvyMnKeBAa0auWCKXElgVduY5wzFbGTN2x98l0EjQKCfe/nX1qwAc0XMJUCwBQK3m+VYz+Q0t4lTHsYxXf45c8f77eItYfoNaBi3vjtIf0llXHO2wPvR941KCh12zVnBdf1VbH7CiUUb33a9r2M/k9t3nGlTOn/pu+t3OYp58P+T52heCvrexn9P8f+IWs6Wism6Lr/P62am8FM/81niZ6Hf4WmE49EyyUnuxn5v5NgxNgNf45GECON4tN/4SrG0spA91jwiLE66H3kpbqutQSzSPEZq95Nq+9aB6vrenH1DnLkBFaOHDmGAE8RQRMOWjUrllFe8gpTMcWetnbpZte3iKyZEE/H4BJjKSBDxSHGMuILafQ+8qJLjEWuT0hVjEVA7n3OoJQqdxdIFq6PuJTEyiFtjLG7Lo8QVN45UqLwTwvqljfH4NG3imTtDcQAKibWQIhNUrymkUqMRdIaYqyBmHNSAp23acVYA2obS4z5Kskwba04hM0YDDGWDasYS+l70navWjFB8ban6+aZIwYipIgtcZ8v1jhnuykZEkXYWbqMBKWmNkOLDd6zqrSQkTXCK4ch79XxvlXkYnSW91wNn5m1Qtlz58om9ZOFTDEWKCkB657KVCt3XebdF7fwhBmfDDE2sdWm5QY93auwak3zDNAq56DrSYlaMUHvwy+l3lOODPj176lGex9VxvmoS04BY+vd9xr7dnTFA8L71wA0Mfa0JsZigaPdtpcs2IBaseS0B8HbGyOxanoepNy5RsFtj2EV9D6sibELT7D3ZurCbct9q7aH7lyR/g+oZ3Hnbcydi/KMLaxJYRVjFFcvpf8LoXaC6/7+qvBmctQBLTynpyD3PlepZX8v0zwg0LdqG3avfaexOGgeWVNPQ9f7iO57l56cmU5KYO/bnVoxdnHdcgCKKB2MmqpWKDXsWkvxHvmGTWn1TfEeG1HF9a3chtL8DXXT/bEiJ7By5MhxgKAkD9VCGcXbnkLb1Wd5BkLcULDufWd5edk86VyXGPPz9Y0LGSHG0tIK5t53bmoa+lwtlj1iLGLYsHu1irETovnx9HvWva2Mc6Nci6VTr4EKV4yRX71k6aWTnuo6x4GB2TGKxWNrbDvn9Wi+4ARrIGRgUMRYoQ4x5iGTGPNQLTDFWAOwrpSNEGMbGt6ltKrjXg2mrptOPKqhMufwwJUlnlFs3Rz0s5jWIwL1oDJmO29XCkI3MG6oWCHjXLkYnWWImrRxpFYoa5fvy6xaJPbs1nmUFui+R661BuFYQsZ569VnBfcP2P4PkDvX02i76kz7LHaMFI+AWLjBKsacvMOyWMUYG/dM3fq/kUDx1mcwrOUw5BgCBFzi0dSvehbvXvcOI87T5iCKzOy6/1k7NmekBQR6H30JI4gYy5hLmL63chvGf/1ip5zSaXO2bxVve8a2S56nCMuRLCDVylmZ/V/Nx9iz+PC29P6vXz0Pv8T6nltGP62NMRYph1cfFBD+sPw5PwRkS3nS3fvMCoQ5Ui2UjIqpkd21yb2vIbJmMMRYgSvGRmWmpd2UOTGWRaSlK8b8c9TnoRBjDc3HOhL0Prq6oRhyf6zICawcOXLsB8KHdrJwPZrPjxkI/Bw7IQxUTGxFm/+tFhJGjGWRMCp9snADDp00oY7hb/N2FWNZEOi87akUxVg44UwWbtCKMU6M+edQOXxiLF5eQu+jMdWKT7opDEYxliMGXZdsEk9BY0nF1Chp5Mb/gJevRa1RYkyfa4zzoRJjKXPZaiFB520NEmNycMSYCoT6hlWMxcrAjpm6jsWF85Ba1zn2C9VCgq5v/ifGfJq5WnO3IQ+9j/4qEvcqjn3vdLlEaZZ9JZVqxRJj2UgWrEf/rxvcra1O33NivwBq3HufSOlOQ4w15tbedOKRGFU3hlKOKFJc0qodWsV01+UNGec9j/wKzRec0Lhxvm5HYwR+R4Kubz6LMZ9tLMyBoxjz4d2nIcZuaFS1wsaEjP4PqL7XqHFuiLG7Lm/oOd/z8K903zt4jfmhwyccLfZu/T0ja9JIHXUS7aYczhHi58XIGuNq6qHK3PsONDFWWfkGdq/doYkxYcsRgSKl09z7/HOkqxgLFijcU/ft2OURY3HymtJ33vYMWq8646COhZgTWDly5BgaIjEIlMH4LtquSolDwl61QoLSQhUsPVixjvxNFmhi7PwTwjTe+75Vb6Cy8g1VjjrlrhYSdN7OiDEZz9Pc40JtnPv3mJJ3ZeUbaL/rirr1AQCdt2tibNKEuumprkdff27q9em4cqV8EeO/PitXYA0Z0qtn6ZI1PMZJysuomDhZk9Hui7c9jebzTwjjoUTONaqVq84Mv/dWuR3FmLNDoXu7vK2ZlfM6ba3veW2cN/AMUKQ0i7WS1v9hy+EQY4Op6xwHDL3vk3FeKyRKtTJI45wbQWmxRQwxdmcD7UFyYixeDoe8WrC+4Z0SlSvlINSagyal32DqmRwHBBLovH0QJOKC9a57XwYGS4z1Pqr73tTG+16qqzUvR0ETYw3G/zTGeYwY87BfxFgdDIYYy5GCYPxXc4Rd31+FsX97QWT+IYLxtjR/A0ZOOxajLjnZ+04Gafu3/l63hz/Xx4RbBnYNWdmLzlvDWIjhmK+OJfM3oNZRYvMxT7nnzRF6HnkJ7XddBtHc5NZF5KVI6SkYMe24unObvpXbsHvNO+7GOCl1UqVx7zPnMBtERtKq97bvZbtS/rEjJ7By5MhxQKDcHDRZ0wCKWsVkHtj+QgMbzJKF69H/2ruWkEoxcAEKlq6Jsfa2cHDxYBRj558Qfu997ltJxNhU94uI0VQtMmKsQbWIIcbqoFqgumbGWJrBImEVYw3EOcqRgkj9ElnTiKrNUTFxsiZ2HVFnK3XvXEuUXh4vqxtlVamYzk9RrXj9JFm43iXGVIap9zgY4zxZsMESY07/F0EfN6qVq+ob5yrWSgN1nSMbkZ95qMb5IS0j6qY3qpX9MM5jsUVUrJVBGOcRYiwNNs5RY8RY5+2DU2vue6fzgCjGcgwdmSomD657Xx28j8SYiXvVKDE2WFJ6bWPEWO0PiBjL0QB0jL6e769C8wVT0HTSkfQF0jwqyou3YPfadyKbGYXeANVigu7vr8LYL1/gurSyOGh8Z2NFjE3SZA1XwfvupBL9rzFijB13iCCNgUq/JcYO1/Mg6d8j86RYoIkxZ4dCVnY2x6oVym7cK6e8fv0IvRnDCRgx9biUuQr3WtnuuTEfvMgJrBw5cuw3akTWXNUgWeOrmIAoGQUwsiZr5ZyNC8ZAaEBppIzzdxsjjYoJSos2hLJ2Mra9gccoxhoISt236g1UVkWIsZRydN5BxFibLUMMQrh1nWPo8IL5cjeHhlfOG24PEddaWxDnkyJKn8aYz5zLgkF7MFa9cI3zYMLmXsdx5/JIsBgMMTaovseD/8bzrzpqzdjzxb2H0oINDdd1jgx45L8xGL92cfrqM1vlNsZ5e2t8lz92DScodWre6q8hxu68XK2ce3n5L+p7I6Yem7mYAXjEWOy+WN0Yd67PfCRUEEbKbvpePbUmj3P0tYvdPGP5BwHAdXlzDB7eb1Ze/CojSiPKD3asltUeInkbYmz2Kdntwe97flnhzUF0exhN87GstgOmYmpQRWzGPep7af1EalI61vci5THE2Kc/Er8+3HI4dZ1jP+CSQcmCDZASNj4fhDv/kfacaiFBZemraL+b5kE+seQSQj3fW4XmC05QcSm95ymloV2MFTG2Q89dY/nZc2rFsibGLvR2U46FJBFIFmzEyKnH6s0YYmnte0OM3XhxmJ8z/1dxaY2q3Ik5B3Yer+sYKS2CdIDapTTRi/O2rg9e5ARWjhw59hs9j7zoBedMR9/z2xRZc3UDZE2BEWNZMU5oIrZwPZo+dIQ34KXkXSRi7Arvm8h5guJeTQmN88iuV1YxNjXVUOLlKC1cj/Y7G4v3ELhSBmWw5ehb+XrDdZ0jG26rkGyS4v9mYftJFjYSnJPioNUjxqRzjV5jIEzSX9P3YTn6Vr1hDQQnv7Ds1WKJrZy3pbRjtxxWteKW0UcQ5ygjX0CT0uf7qpWU2BpEjF1d/xmQo3HUCuW4ksKrYvpolBSzU5QUNPEXRJS+YYmxNEJeGwpR1UrKczZZaIkx4efrG+c+MeakpQtYA90hxoIacNG3UhNjaWpNVrZqR8mt66ihZxElQnIMDfQ7CKC6UxvnhqyJVKzZGQ/o/sFKtz1ElKQEQ4zF2oPXhAL3Pv4bCwTl6n1MtYeW2Se7eUWK37BiTNdLEAsxpf9D1hn3WP8H1M7VZtwblaLWZOXvfcTre3m7PyDY+9q7qKzchnF/d6H7RaRuaXftFoc4T0eyYD0ANBwHzSXGstH9/ZWaGDuyblrqe41uXmOIsdj83KuXZAG5UtZXEFJdN6LWlJV+FG9vvK4PBuQEVo4cOfYLycL1qBWTBhQ+AtVigp5HXkT7XVc0QNYI9D72K+ZilLUCw1VMVI702Uy1mKDzNiLG6gVjBJIF69B04lEN3KP0FGP1Z1TWpYQTYxnG+WuNKMZkCjGWG/RDhfQmz65xHlt1VC9lILzh7hiVsdrXeTtfvfPzdokpayCcFcnLPbcauJTEymHJL2sgHOfVRFgOo1oxGxXwtH45yi4xFuSLoBzObm0ZdZfuzpW3+/2CBLp/sIIZjML5zkkqpWoP69PIGkEJAQDVnaWQGOOdzSOdHLLGyTYcHxxiDHbThWh78IkxQ2T4pJfKgxNjbn2EZa8VEvQ8pomxNGOMP1+y4hyJSN+juk4j/nI0Dv37yXI/Ou/QBmMwV4ksUixS29k7RnGKUrXaoY3ztPYg3f7V4xNjTlr3Y3nxFpcYc9Yn3HJXi4oYG/t3F0bUu2G7731EbRozavapqdenPuaOexxu/4eUGOjr1xv0UED49P4PpBBjedvfb9SKOu4VtYc6SBZssCqmOqC4V2N9YiwC2deP4q0uWZO1M6BVjDW4mzKR0o1sxjBYYmztjogrZYhaYXB1XUqp66x6+WNHTmDlyJFjyNj3Thcqq95wZe2pkIo0ajQm1MJ1qBV6WdyrDEJK797XftcVDe1G1csUYyrX9EFAbeecEhA+KEeDijENVzHGEd5rQ66UDJ23PRUhxvIlyv2DUComh6xJbzu1YoKubz2r3fsa2FXykRe1cX5q9HuO0EDInsgoYuysDFm7/ZssXO8RY/HyArzv8QlhuiHU++iLHjGWRrrBq+tsVAtpdX3wTvAOFJJF6yHBDYS4ag9QSq1k4fqM9uAqmXp+mGace4YugPKSLZqsifQ9k04TY0HsnWwZU0CMMQNbFYcRYzs4MRbPz5wrgeLt2p2rnoJQCEuMpRlB0kpNAmKMj5H5o36/YAzGqILQrdy9r/0elZVvYOzf1jfOByqMGEs1XG3+yaINXt9LhzLOX8kgxtxyB8a59PuIbaPlJYoYU+0yvf+rhcoyur7FiLG0/q//JvNjdR32fwDanYsvCMXvLcfg0XX/s6o9nNQIWaPd+xrcTbn7BysbJ2vmh2RN2s6Aihh7I1SMRTAoxZhUijGn78WKwFxaG1aMSaYYo7rOaL5ESrvxt+i0g7fd5wRWjhw5hgRlICzDmE+fG+7ex3zCyZ+999EX0XTiURg1+xRzzEIbI/q8vTs6NTE2K8jTWUXXbztv/xmLCSXsdZ2yqL+lhdrn/KqzIKVewXACPNqy0O597XdewdyohPfX5k3GuR8QXrL6IBAx1nrVVPd7/leqcxUx9rSOMRbZKRHhPQY7JcJLn2PQyIz/AcBvqz2PaLLmrGOj3/OXQ9bE8mXnO2RN2kYF7LMhxmadEi8r+7xvR6frzlWn3EbJmFUO/dfGWjnLzRdwP5u+lxVrxbvHRzPqOseQQfE/xv3thcgmPgUGKv0o3v6UVq1wolQ66eiYa5zH1ID2HNc4P4zlG1HmSsFUK8exvOPqxPKSV1OIMXaeLk61g/reR5hxnqaSFMydK02lwIixtzsdxVhQBn6OFCimBgAXOW87ZAhDlFoSMf7bUrvcZYxzf5Ei/N2MaiW2SCHcaxjj3PS9dPXpQLkfncbFKE29a48lC3Xfu6q+srVWLKu+F6hWYukler6v1JpNJx5ljsXSmb63LhbnyD9HqXe7nbpO6f85Bo1kwQYMa28L46ABwdhrNoy46/Jw9z7nvXpudn3zWUuURtPZzwExljb3gEC1I0KMZcxZHKI07f409vJxj8/dI/MQ2UfE2Knhjo2RurR970znO8FtCpoHdSS270V2SswVWDly5MgxGJDBeMEJGHHWcYyQ0uSRIZEkBKxqZfSnzwWk0LuMALTFLRE4EkrWvutbz1piDMJM7Mx0hbbdZcRYCxnnmuCiBzt9glSxVvpWvYFxX5vFyCsAQuVN0n0p1bqGIY0mtpljKk9ONKlXaZF2pbx6qq0HZ5BRRJkipMroefRFTLiTuVLqOpGm0Hayp4zzKWg+/4PmmBn3eFopUHl+G/pWvYHRn/6ozQ8CUrr3mGNwkJV+tqtkyu59gJnnKBVTgmDnzAiqFBA+GnsnzN8ha2I/J7tW3/MRFRMvC4vTUiuSaoWpmDLKrfpeRpwjVvZ972hS+usXu9+RreJdx24K0Vb3Ho1irIG6ztE4qs7KecwodhEa52npRcQ45+nhnGON81M9BWHsr2CKsZhq1i1LujtXpNFJwRRjx8XTsPPJOLd9L0YUqL+WGDvXq+t42XsffZHVdYSoyPvAkFBziNIRiP/Gto6JKLVkTQrhCEuUWsW119bZb1btKKP7h1nEmPs+WZhBjHlp+7e+y/peyr1pDFSUe5/b9+L93yHGArf2sD4MKR1Va4bX6PmBT4ylPQdyDAZ71u5I3zTGe44od8+nMeYz59SfI0iJZOF6S4wZiOj4z3cQF81NlpxJ2Zhm17ee1e0hQox5cBWE3v15rrPVDk5Kt+oypj9QrWKM7ZQYg7QKwqDvCebiTn8qjJRO8VqRB7HyMCewcuTIMWj0Pf+GIms+MdVZAwPgfdZxrzRZc0hzkyFdzFgj7RgmIExg3CZNjBEnRd9LTWQBQEUb56OvP1d/p8glOw4Ic7xK7lyfPhfD29tYehgCTpry2JXzUbNPNd8LnTdfQwSAve90amLsYmfwpPLatCoPMs6H6wkhX3nhKyoSyoWgVkzQqncoNIQcnafLRPfYqxVjornJ3D8vT46hobz0Vbt6l1WNNElZFYv/EWKgr9+61jbidhpTMaXAKMZixJgpr82gx5DSx6oDGXFFDDH2mQbd+76pSelgE4Qwfe+jL6LpQ0cxd670vPft6Gy4rnMMDuZZ/KGjMleUIREa5xnpqx2JMs7/9sK4cs87J1m4XvW9WRkr5/pliLEvXZieVn8eoDhHs0+15UCYjv4mCz1iLK0+wFbO72xArTkA9PxwhSWlI4Quz9up67T7yzF4SImubz3rtoeU3xdg7YErnQfTHhA5x2sPTR86yr1u5LzyYq89xNqC/qz6no6947d5ICh7siDS91LasUNK13leDOgFodS6jpTDqetY3eUYEnoe/RXGf/3i0N0zMv73PvISRk49Vm/YRJUeJzP3rNuByspt6RtXmHmvMComRYwpssYSOuGPmyzUirGruUrSy1vDIcbqudb6xBjYbUbu0yoIyb0vvSFWi75ijOUXucfQjTlSzwdx7LecwMqRI8egMXximyJrEJJX9JfecyWFhBV8CLiPegFoFVMJbVdNDdap/fTVgiJrJtx5BQ5paXKGUkuIWZCKqems45yy+hBQxNiedW8rxVjk+nR/Ap5ijBnnsTmVBNDzGItzJO34E5tvVt/pRN+q101dR+bQphwCnmrFS5N1zznqY9iEVrWrJJA5oVGqlRXaOG9sZ56R01JirXiTk/7X3tVkzayU3Gz6gT6mGJs4OqMEAir2DhFjbMfKtCDExpXyCojmlB2jGGgzhiAAeARGtfKZtEmvW46uSN+zOHgndwcCI846Njv2HxnnpKS4g4jSlHrXDzlSMTWdeFTdnyhUrSB8wAtbju4frsDYv52BYYez9uAPNPqzIsYm2b7nDzLswUl9b9zfznAHAP/+AAwknnEOL61XHqMY8++R0rLBodbh1zXLz19ZyTE4CIG2q85KD0rN2sOetTtse4iJ6lh6FRDeaw/0fUTMFLSHGMmkr1XtSFBZ9mr6IoVHBKm+N4WpmCL56vflpdy9LwJeDj7upY03LP9kwXqMPKuBAODSLgiN+9sZ5nqx/p9jaGi76iwceuz48AtvnlNesgX9W9/FaIeQis22gWqhxIgxPyZl2OB69AYBihjLVtYpYowUY7GHni1TjBjLajDJwg0YHhBj8QdrrVhGacEGHfdqBEvvQx3b9U2PGIs+AEit6bsxh9dXBODB+7DPCawcOXIMGod96EhDSGWRI6XH3KDUXInL59wS0O59ryv3PoSLdhyyT00IOTEGltYnmhJNjHEVUyjCV+DEGE0II8OGOc6JMaaGdsur//Z5xJjU9eHXhYQNAD7aM85jwyknxlpYXfOpQj7H2z80X3ACRPNh3tGw1ff8kALjHl03T7N69wluIMRX5Yw719/OSCHG2K8thF05n31KtJz8Hvq3vmtjztWxfgccV0o/OHaIwL0va4WyUMcYM1B11PPDFem7tfFrHbxzvP1Cy4UnxL9gTdQEpZ59amMKwkXrAci4glAIJ28b90o/i2MPPvrLibGTjkr/zfXx8lKPGDMrK2mk9MqQlE65RrIoQkqnpO3f6hnnPL13zkBZxxhLq2vzsI+wIjkaglHAZaCmY2OO/9rFbswbIHpuz2O/UmRNbJHC+533rNsRbw8RDCREjJ0SEviRn18RY9JVMaWgWqTd2q4In8UR4paexQ4xlgJDjF19Vmb/p3JYYiwS54j/zTEkWNLIXzKG+VstlI2KyU3jM4nqRSqmQ4+dkJqnJWteRf/W3+t5cRp5pdLSpjEuMSa8lz2vxyjGPoiwzO6LiLHRhhgLiSV6yb69KN72lIqF2N7mXDNWHqsYOyuSt1s/1Q67g7h1Y47dIyL5HDzICawcOXIMAe5DUw0H7rHK0lexe93bGH39uc48I/a4VWTNMoz5kjLOY65unIgp6ZXzltmnRh/pHHtfe9dRMcXWUqhcsuISY+RmGEsPhMQYhz/81gwxdqV27/OHIeFcg4ixEZoY49f2zzXE2PXnOmliZT6YB7z3DzRJYQZCZFbNF8ssWXOFlrWnrSQqWGIsbYcg20PKi19xVs7T5/csMO7fqlgrYVq3JRt3rsAYCydkRjH2tT/PTAdwl5JTMGzi6MwyA5K579iYczlfdYCRtrrLlRS+iinjvD3rlXE+Ns04Z2y+62LkGa4RuMZ5dguwijFmnKe5q0je99KMc9umjWLsExnKNVYOZZzPSFEQuogSYzEcxKvyBxaRsVICXd9WQamtcZ6O8tJX0f/au2bRKv1SKvZOz2O/wvivz2pIvdv72K/Sd0r0mkA2Mebep9qtjYixSDm8vJOF6yGamxrcMVq7c7EFQpuvDPLe9a1nbd/Lm/X7g9iqK8OAjsWkNq7QcdC4OsubJNu4V1lhDlSb4wHhgzJFsOtbyxQxNinS97xzFDH2rpkX+9fmqOlNY0LFWDx/RzFWp11axdi5Xl2F5RjQas0xn/5IfEzg9X6QIyewcuTIMQSkWIp6IFTG+SuGrFHmZYSWkmrOouI9WFm7hIyvako1Idyz7m2M+oRWU3lJIV3SqPuHKzH2SzMwXMdZoBhXpjTSrsmUFllizJQj5fb3vvZ7hxijspj7Yvc3YIixqRg2oTWoN8GuJcCIsU8oV0oedwvSJbsMMeYYY356/VkCu364PH5POerDTDoEa3Sqpo2bw5dmuN+zDQcoDxWUmhkIUgQNWW0AoI4lC9dDSqnIGs5OUr66nakNAkooL3vFKgglIHQ5rF1B5ZPo+eFyNJ8/BYd96ChzPcoLrAyQ0ijGWvUKvmTlpTLTsWqhhO4frMLYL83QLiUCZgMBVn4V50JoUvpYjJp1qlMON626CNX12C/NUOebC8P0DzpnoNKPrm/9537+8DkU3Cc4kTWhgRCmV26nL2L81wZhnDdC1sASY6rvZcP2vVPDOCROmTVhy4mxOjCk9B1XNLSVuktKZ1tBgyXGeh99sW66HBE4zSH8TZJF67U7eQO/Aykp7rg8JQWXMkrs+vYyNJ8/JW6ce8td5SWvov/XDRBjuhyOYiyAe5+9j6YRY6HRTH0vHgvRLTO5tY/59EcQ7pwZIlk4iLouJOj5wYq66XJkwJ9b6Ffvo7/CyLMm2d21pZeewXHv8wVa3nm0QYBRMUnE89evZEGEGIudA0aUcmLMLy/73PVNRoyl1AOd4xBjKWU1tlCHHvc4Ke2XgZ1PpHTz+SfE07Bje9btQN/zb+BgRU5g5ciRY2gIBjF1QPbtRdcdT6Fl1imKrAHZlzIwSAFtIEhoskY43ylFuRr9BARqxQTlpa9gwh0qILxJpy/vC2t7frSCGef2uCqLdMiCiibGgnJEXrWijrXypZkYNqHNKXNssEkWrseIqZPUTommfGz3RZZ3PxFjX51lymb+mveq7LRa48S9iqZXr2TRelTf6fR/yRwNwgTklzQrU7+h2s6ZKSkk1HfmTB38X+92qYhSTdZQnhAwrj9SE6xCoP/XvzeqFbvZANMd6mMCArKyF523P41Rs05VhC2VETSPVHmr5iNQWkTbOU815bT0Lm2YQNL9BGWtGDukeYSTNyfphL4HirVy2IlH2b4PeHWjrlNe8ir2rNuBtqummuMmL6oToT5Xi1oxpklpweuC14k+T60Gj9rfn/4gB7dAmJvDoizjnNIDkEKtnF9wQjzWir4GNRGjWrn+o5FyuHpbYyB87WLPKI67WXDViuRlNOlsQzWqFU2MSS8vfp9mp8TZp2QY5/Zclxjz9bru/Zo4R3WIMRqGe364EofUI9ByxKGfTzFQe3B3lYzDKCmu/0iKooO3NU2MtY9OVe+CtdZqR6mBvmdP2/XtZY0rxpbEFGNh/wcYKZ2qGKP7UPfa68Q58uGOl2FdUz6+3l4YteZhDbgv5hgckoXrddwr/TukBQ2XMBs2td91ef1NMaA3CbngBJes4WA/tSFKGyFsC4lSjHEVUwpxBUSIsQxxk1UQXp5eFwxm3JvkjXvuUAOAj3uRHaO98tO4d+gx9fv0HytyAitHjhxDhrNjnn7Alhau02TNqdFz+HN476/fRd/zr2MsGQhMek6GMB0bqOxB5x1PYVQk3oPv/SGlcjMkYoyu67vpESwxdmVq7B1+r5YYS3PnsqgsfRV71r+N1r9w3Qxj299aYiwtzpEe04VVB4zUdS3qDKZ7f/179D1vibEcgwep4fgMR0AbCOefgMM+dJQ33xDsvTq3vHQL9qzbgVZD1rjfc+6Ux71SZI01IWLzGlIQjpp9qjNHs9tR2/PJtXbsl1QQYn/3S36XA30qztGoWac4se+I7nLMFKnKIaVkrrVu2+R1Uy0mRjEGFnPObG6geWYiYblak/PKYO/JkLdBiEMX3xyNQNjKZBXNjfNDAgOBKQ4Ncb5OGQifYGSN9F9qz1RSrUy444owDcAe8gAGbN8bTqoVlh9XGkLCqla0gSC8/PmihlWtWONcEcC8LoQhbxUxNincrY3VA51LxvnYL12oCWUZlJnS250ST1EuvqasKm/pXYeIsdYGlFo50iFZnQJAtaPstgf2e8ZerpLC9gnptQVIYLchaz4StBv/4SbLe9F5x9O27/H0/Bz9ssTY1Hha9r5aoNg7V7hl8Po/vbfuXOMz+z+pdxUx9lEnD7//q3KUInXt/DBOnyXFWCoRkiMbKXPHajFBZdUbaL/rCnswwz2087an0Hz+CY25Q2tiLFVdJ/R/ul326N21G90Yp/n8KSlEqYu+57dFFITp9dF5+1PWlbKOq7Zxpbw6Mv/wTq2v1nTPHQwp/ceKnMDKkSPHkKAMVwmukKosU2RN2yemOuliUGTNSqViao+snJNBofMoGRXTqUFaxyUQITFG33GXQHNMB4Qfpd25BCPNOOhIQsb5J+obxTUyzu+4EsNa6u/W1k3G+YdiAcCtUkdKaeraEHQZg2kjxFiOOkip3tIiNUkhssaQTCI8rVZMkCxc52wQEFyGnaBW77SC0CuKT2IlpCDUxJhgafy5f5W51g5rbwvccPl6O+DGnANLE6sSQ4z97UwnL78sgN0pcdSsU7RijC26SlteyiNhxJj08ob33roxX5GrUYYKqZ43kKTi42TNsWg+XwfGlUohJzWZw5+y/XrlfPSnz2VEZKiak+DE2LmmPajv9EuC/QVKT1rjXD23hUlvDGj9vlooo7RIE2NE/Ai3DKR6xIAwxJhy57JElVNufaPlpYoYa7v+XPud4GlofBLY16FirYz72iwMax9tDDUqJ90jlaX3sRc1MXYqIGHyEYLGKXsdE2NMk9I5hgKPgIFqD513POW0B65O9V+lRes1UfpR8LYmJf2yNm21o4zeR3+lyZo2GCUuEV7U9nQfofbQfMEHTT7EMVF56bXb9L2PKBUsbB82bUefN9C3V7v3nYtD2lsZbxX2f7rHYe2j1biX0f+FENinibEJd16R2f/pNkwAcK+u/f4vIVBJVWvmaAj0UPZQLSbovI3U/Y25ezadeGTjrtar3lBEaQPl6rxdE2MNup32v5ZBjPFyFG2wdHuPIpWYShasz1aMMfSt2sZI6Wyiq1pI6qg1vXIsWo9hE0c3dI9/zMgJrBw5cgwBQpNB1hWoWiwxFdMIfZSrM9wJiyJrTtAqJv4dnHwBgWTpK4wY4+mk/t9GkCJibMyXZho3qtjwQWdYYuw0k6OAdYWi8gDSqJjGfmkmu6twMiagdinhxJjNx9Yhv4banQto/cQ0U4awXhSqhSSoa9+cF+yfreujg7xyNAgBpx1JALvXv42+Va/H45B45IvUZI2/q6RPGnGyZlh7m6Mg9K9PqBVCYox/7//iFGuFu1zwNPxarmutS5rRXzq+r0B9jzZjyAYnxvw+yutFAtij65oHAOdlcN5X3G3rs6ePObJgf3P1RLJkzUfd9ij9s2jl3Brn5tkU6UsCRNYoJUVa+yVieM/6Hegj41wnShOhUgzC0dfrvkekkdcwyGbixBi1Lb+89KoWyJXyCrekMtI+JdD9z886cY4ovqHp/4z4JsUYr2tORvNFGxX3itV13uj3C7yNJk+ScT7VaQu6GTm/TbWQoG/VG5hwxxVuu5F2PsR/ms47n0LzBao9GFKeJeAznWTRBkOMuYsOYb411h7I1ZorcX3SqPdR1fdGnu/uSOf3fwga92i3Np1HpP9L6BiEdzyNMWzcS+v/kOoe+YIQrwM6l47WipYYM4XLMUS4dZcs1GTNBR+seyaRNSGhEv4eyr1P72LcICHVdOJRQyTGstuDUoxN8UgjtijglSNOjEXusajHhDuv8HZK9CFM3qquTwi+82EUY9efk3FnBwdyAitHjhxDBJvgGBXTqc6WsnwlzkzOoFxKDmlpMvGmsoaZWqGklBQOWeMSPI57nyZrmpg7ly2v+7LufdPY3biLUpS3Cgiv4l4RMcYNen4VCeVKOXLqsZoY84gruo4+ee9rv3cUY1SGsF4EZF8/uu4M69r/SxPa0qJ1ANCQYixHFngLUWqqXqOkaDXfxQkegZ5H9cr5+SdEWzxPv8cQY9ZA8H9hc16Fdq1hBgJrx/wvwIixq6ayPF2S19xjIUFp4Tq1GUOKionfS7cmxuxmDGE9EIgYG339x1LJMwIZ5+MMEeL3KBc9WqXAY87lGDyMoa4rWMW9WqdVTGE6/l4OWKJ0OAtKLWBJG44kQoxxokiwc33jHPo48wA05wsw1cr5JxiCwF0CsWXbw0hp57sIOyaZYuwQ7eLLy23KoL9QxFhb4NLK75PGhFqB6vpKW28InzFUJ7yuczN+6OAEIaB2+K2sel1tXKHhPK+k/U1qHYndrCXiRuWT8qVFmhj7xNRom+efa4UEfatex4Q7rkyZG7gXUooxS4xJ73v+trxIG+daxeT3DU6qVjvCZ3G0/+s3vY++iBFTJ2liLL3/x8a9tP4voMe92+24J4khzjEE6Bapqy9ZuIG59/HWFiOkylbFNHG0OshZW3on1fmGrDmfiDFGFnkN1RJjZ6aU2b6nuFeOYoy7m3rnlALFWNosRDBi7HIvbdwC6LztaUWMtYcbNvHzpVS7Kff/2hJjtup0vbPzqx12B09T1wcxcgIrR44cQ4c2Gnof/SULSm2/S52kPP+6iUMSM1hN3pV+dN75FNo+cVYYFJL9pY/lResgNDFWD7VCyRgIh7Q0RSeFfHja9c9hnKPg5jQqWjHW+heWJOArlPz8WqGE7h+twJgvzQxWzvmEl2CIsYtPDb7zsfe1dwNiLMcQoRsqTaBV/I8pKogm+w7eSwBIlr6Cva+9i7brPgrjomq+F04nMMb5V2dh2ARaObd5+9fooZXz805g5ZBuOXT596zboQwEvXuOMQa89JL6HhFjeudMY3g4adUFKN5D6yemRu+NX8cQY3dciejmDl5ZiBjjde3/JnSN8pJXTV0HdZBj0JBQ9VvrSNB5pyJrfOM89gxKnlyPQydNCJQU3k8HQLWHytKX1U6qKfma9NIla2LPSEoPuMQYz8c3uiV849xTB7AuQtfqfVwRY2Scx5oa9V0yzsf4xJj3Xhnne5krZWuUGOdlLz/pujErWzGnsYYE6bbLRCt8uJIz9hsAQPLkOjSfPwUjiShFnCiVUMRY36rXnViIkaKocjjEWKvzXWwxhBRjft6x8tcKCSqrXkf7nVdwKsE5h89dODFGSGtpiSbGRjNiLNb/AavWbL/zyugihf/YJ1KaE2M5hgga8wHs29GFyqrXjbunaQAUqw82jpuUQOftP0PzBVMsmakePm4MOb0pTbJwnSJKPzHVyZPHHqTyVJnbqb9DoRPzVr8UMab6nhonBCsHpVXX6Vu1DX2r3mBx4Zg7tv6sH6KoFkqMGBut79uWl8/LpOSulHrcE4LdJ6W186CKVms61zV1Zz1L5IDte8PaW8M6OwiRE1g5cuQYGvTDs7zsFWUg/NVHHUMScA1LNSiV0PvYixj31dnu7n3+rEZ/7n3sl9o4/2Aw+6LxhvLes+5tVJ5/HaOvOzc1T0pLxNjo6891yuEb0vSZghC3/sXU4HtjpLN7LC1ahwm3fxyiuYkF2Q3vVcASY00fdHdKjJWjrImxURQQnn3nn2OIsb+ZGa/rHENGaaHr3peFKrn3aSWFH6vM+SxD1QpNfEgBwpUglWWvYu+v30XbdfGdeYTeuQ9SK8YeexHjvuoa52nhGUgxNvI8N94DLwth9zqXlKbvTQw7wSaSfVwxZsuRZQTF6tq4XrGyVAsJEk+1kmPocIhzZpz7kF5aa5yfFaTzUdXGeStTrRgix8tXwCXGstbBAU6MXZl5n1Q4ehZz4zwlqeNKWS9tLYMYk8F7gZ7HfumoVlQ9uApQwp71b6MSc2OuE3clRx1IbjDG49Lw3yXRca8cEhEp7bJDEWOKrAndqHxSKrvvUatR4MRYPdQKlhg7hG3OQWUOVJKLLDHmliFMWytqxRiLcxSrCzq3ixnnWf2fypFGjOUYGtQu32V0fetZE+bA3YlYpbLjv0DvY79C04lHofUTU8Hjo6nkjMQSwN53OgP3PttyNdlkriXQebtSMbm7KQtdUmHn3kKgtEgRY61BiBE450EIE/dqwp1X6A1IhO3HVF4AFGstWbhe970PmvJSvYDVhYDA7ue3WbWmhEkjTQp1noBWjN3xNNqumsruEaac5r3OI3lyg3alnGrysHV+cCInsHLkyDF46IdmtVhSBuPtroEQxBbRn7vJQNBbv2YZmJwYs8Z7WA5JxvnjL2LcP812J5sp5eh57JcYcdaxaD4v3b/fxlrRxvl150YLzAkI2dfPVAopuwiy2ZZDjEXKycHr+pDmpqAu/HMMMfahfGvpA4m+599wyZroujXYJCUka9LgkzV8gwRL3Ko3Kv7HOrQTWRNzcaLVTbC4V8e2R6/N47ERMTb6uo9F0/I2r4ixXznEWBZJR3GORp53gpnU6RIE1/HVmr5hJ1neMWLsIJ7bHRCQAZksXK+IUr1iLXgCj2Qn43zCHVeGxLlvIUtrnDdrBaH6TXUSj/ivkHH+ialOGWIKPke1MsHfySx8JYsUMUauHMEigimcyruy9GVMuP1K2/u9/MyxAR3nSCsIZez67Fhp4Trd9z4KUm+RSeUuWAhLjH1Vu1L6eeYYGqRStTWdeKRVlML9nc1imJSodVj3PrA0sZeQwrQHZ4c99ruRuoL3PV4Op32x/uf2vdZou3TbvO57558QlhOs7UlGjHl9z+//kJoYu536XsozgJ1P7lyt2pUyrf9LWFdKQ4Twa+cYEiQACOXu2Xz+FIw467h4Gvah7/k3VAiAT58bkIzcRVRCLVLsYsQYHY/NnARUCACHKBU2BIn/U+/b0aliznkKQj8dlcslxtwmxs8TwhKlbXqxhOdtyqLbpa8Y85uj9M5LFq03pLT0v5du2SspC0IHO3ICK0eOHEPCQEXFYqLAuEJkx7KKkTX+oEioFUlJ8XH1FRmpKZOUXf+81Kyc11NdVJa9Yg2EjMRSKtLIIcbqTJKIGBuZQYzRPfRvYIqxOqC4V2Ou/6gn1Y4jjRjLsX9Q7VIbCHqFMg414So/uQ7N558QqJh4OoJPjAHaaGZ/1RnCrJyr2Dtx0ojSAi4xZpN5ZJC2AogYU7FW0hqZPZcTY/5uoP4Utax3jGq7jty5JJs4SnAyq1YgYmw2m/RKlq97j70UYyzoe7kOa6gQUMZH3/OvY8LtVzruGNG2L+EY56SQi5GrRBoZ45wdp7+00g4wd647rtQuFIiqAQklbZyPPO8E5zkvIk2a+p5ZwSeLjs4RumUL3ffuVMb58Il6BT+SJx1LOBHC749fgd0j1TXPgxvoRt04IC0xNmlCpP/n7X6oMHGvPsEMRumOubxdUnswRGkGSovWaRejafEx3PzObt/zv5d+O4r0PSeN1xzIOLeqFR9CeT9J2j1X7eBJfS9rtldaqMa95vNOyOz/AO97ZznH/f4PWMVY6yem4pAJbWH/z0msIaO0cD1qxZJRtmap2qrFBL2Pvmg2jSHCh4PIGEAtWhExFuEvnfQVIsauZ8QYzf/1RzpeLSSOYizr55e6HNy1NrIebrB3R6dREPq8q58WSFdr+kQdkVf7ftOZulEBfZZgpLR2rfUJt4MZOYGVI0eOIaH0+IsYyVVMMt3c3bP+bfS98DpGX2fdLWITICGE2jHqzp8psmZCI6oVl6xJNbmF3rWGKcaySCABphibNCFzwgYQMfZ7jLmOZO0xVY5CtVhCz2MRxZiT1p7f+9gvMfKsYzOIEAtV1280RIzlGBxoK3W+imgnQgJ8qpJEZe3+rpXqPJ8Yc/MiubhKK0HG+QkYef4Hg7T8JeESY6Hayb1GrZi4u7Wl5q3OtcTYNLNCLp18YdJaUlorxry84JUtdOcS0XMkmDvXdR/zru/fb47BoFr0yRqLGGFa9skawWKcePDJmhiMexRTrQz3iONY3smi9dj7uu17npeuylPnUSvwvkcEhHDypXuQUhrVysjzTjDHQgNdfXaJMfe6vCxUDhXvcWqg1hSC7RinyxUQYz5yC2dIqHUoNfeEO67E8PbR5ngaUdr7+IumPQD29yXSk4OTNbF2y1HVMedaP8H7XrwMEmF7CBQg7MC+dzrR9/zraL/zSu3eLYN7NDF7EI579L0PIQQjpc/K7P80H1N974qUoPf0NLdjavP5J6DlfLtIIbNYuhwNYd87iqwZ97VZhjjJap1KXXdW4O0QI3mSRYoY8zeuiP1SarMWRYxRXFrKh59DnzkxBu87H6QYa7u+/ry4VlCKsTGftgvGWfN/TozFZjR8nmjq+qsXO3mExJSAMKT0CQ3t6nywISewcuTIMWj0vfA6+n/9O6Ok8Hcx46g5KiYWeydyhpQSpcdJxXRgyZqB8h5LjDVAGpUCYix+hwIC1SLFvbrCUZT4oCPdkVgroXuUSm1cKa/LjrUCcMXYrNR7zDE0lJe9kmow+r90rVBSxnkk9k6sFcUMhLRzkkXKxajtE+mrd6YcxZJDjMWuzSdZZuX8/A8Gafxr9D3/OiPGsie8tULJKMZiO1cR6Jghpf24V5Gy1wolhxjLceCg2sMUNJ/3wVSyn55bfc+/gYpH1rhqI2vQZ5E1lg62pkDpyXXMxUimP4u1QkoRY1cgvk8sK5ohxk6wcUgEvHNsy08WrUf/6+8qwpZ9Z41omzYgxsx14+VJgjhH9v59AsAnxkJiF+kPhRzpkBK7vrNMbxrT6hrjEYVbsmg9ap0lp80b1ax0f2tOjA0zxJj9zfzxXxFjiqwxAaaDErhEqYqFGCNT3b6369vPYsz1H8UhE1oteRVpZwAzzlOIUt5P9+4ouuNeSv9X9SNTxr2w/0tIphg7K0MZnGMoUGSN2qxFPRf1F6QGhG1V1B5aZp9qzk9T41YNMXax41bIL2HzgHb5PgvDJrSZcvjuiAQixlqvmhqU18+8RsTYHVdiWEtTqGLUDJOvGGs661jzvXEh9/J3iDEJ75lh84ZUBJ3vSmmvzWpHqv7R8zj1vbPsSMZYwoP9EZ8TWDly5Bg0DmlpwoTbP24+c/cffzDrvPMpNJ93Ag6bFI+9w5EsWod+7d4Xy4vDxr2a5a2SpK+U1iPGaGJkFWMpxBgbpQYqewL3vhDcCLLEWGw1nh8zxnmGSoGj+5+Xofm8+kGIcwwehzQ3BUH8Y69qoWRWzlOD57NjyUJtnP+FjS9ENrTw0leJGGPuXDTJi5XFGAgT2GSJ503nQpVj76/ftW6nkTR0XLXL9Zhw+5Vmsim8c/ik0FGM8brw60YyYuy6c4O80uqaNmPgdRe8cgwahx3TbsgaYf4P1Xi1AjfOedBdOO/pMxnnzVpB6KsSueKQ2gOpqSitiJSlurPEiLHRzvVj5S47xJiCCTzskUKhO5e/1s4+S75ynqVkVC8TAPwT0xxDP6aYdIkxG4Q4LFOOQUMIjJp1GlpmnYb472tfpGIa90+zUtLYc4UU6LyL2qVVU9k+BXbMJcZkJA3vU1VOjLWMiJRZwe97TWcdF/Q7/x76nn8De9a/jdHXfzSz/6t2WcKubz+L0WYelN7/AeEQY1n9HwD2vdNliLGs/p8/54eGUbNPRdOZWsXE5wh6Axh6JlaWvmrc+9yxVc8AiIiRan7eRSqmCW1W3Zcylvc8qokx2smcro9wfrNvB6mYZtkWrtObZ6Y3D1KKsVaXtOJ/9XUScqVkuylH00uXGDukucmWg8qsQbduFGNnHheSVpr9Uq7qjBjTNkgQ582flx2EyAmsHDlyDBojzjwuCEDqrIqRcb5oHZo+pIxzs+1rhjHa98IbmHDbx22etPIYM87v/Jkia46ZYAZNdW12Hdhy9P/6XYz+q496acOXMcZu/7ghIIJz2N/ex19E83knYOTHwkCo9lyVuO/515krpbB1wsrNt9jtvOspjLnuo245wMtj6yZZtA7DJlh3LvM93HT5JG9oyFJIGQigvIjif3wwuukAYCc01B6cuHBsYsInLbVigi7PpSTLTOV9j18bPG+NWiFB3wvMOI+k4WVxjXNkTqZKnBjzJmAOJFOM3a4VYzL7JkvGpeRDbjlzHBDQKnvWY0NKGNJoeAOqz2TROs84N+aPzVP/rRVKHjEWtTsMev/9ReZam42+518PFWMpqHWU0BUQECHoHhJNjLWlqlbcvJ24V4jfIz3zed/zaQ0HeT8YEqwroIVft9WOEnZ9exnGXP/Rum1eAOh5/JeOcU75xR6Hex1iLMzLKY+E0y79n9wvN+97/JoCYXOp6R2jJ9xxpYlzFAP1XSLGYgHAffQ9/7oixkwsxHj/B9SYsOvbywwxltX/cwwNLbNOiR7nirxqoYTK0ldMe3DTuWkBoOdHK5SK6cxjTV5pY3N56au6PbgLxlLKoA3XiokmSs+18dg811cOIkpHzT4NAFJdgQGgqolSRYzZdGnnmE1C/J1lHfJK72a4yBJjFC/YdVO35eek9CEtTU5eYXkO3sWKnMDKkSPHkBCoowzppD72vfAG+l54A61/MQ0IHrh6FU0frxUTz0Bg6SlDYc9LnlyHpg8dpY1zu12vO3YJQKo4C4oYuxKGNAIAGRsEBDrvUsSYUq2wFSC6R5ZeEWO/U/forXjCrB6pk2qFBMmT6zHhto/rYK9s+ujkq+oleXIdms/7oA4Iz/Pi9yBZXWtizA/4IolA88qXY3CQ6RMZQrJQEaXG7TQ2YdPHqsWSag+3fzwwiv3LCADJorXMpQTp+YMRY8bVKQ4B1fc67/wZ2j4xrSG304SCEKfkzbtrrVjSxNjHo2n9+wyIMSDVUiFXSkOOI70+cuwfBBCS8/pY7+O/RNOHjkTLxaemKgHNyjkZ51+ZBVqpdsYNnrfeva/tL0IlI53HzzfG+V9MdY6b9+w+ah2KGGsnYsy7J34OpCXGmrmCMPKS0ioIW/9iWnp9sHJ03vWUMs6ZSpITFFRuCUuMERnMSWXp5Z1jPyB1FcrwPSRQ+nerYvLdkPx2V3n+dexZv8PsKhm0dfaqMWKMFKVOmSRTd/C+N+vU1PZI5/p9j5dRyrCPm8D0RJSmtGFItZBQK5bqK5ShiJDex15UuymTO1es/9M9PqaJMa1aSev/+cxmf5BdewMVtcNvy+xTDFmTNhdScQLXQ0oEuymHV9Xz82df0WTNiCCNZGkBS4wRURrboZlAxFjbdeeyOULs4ajK0fXtZYYY8+/JL7dxpZx1CmL1R+WVUtq+99VZ5ljqI5r63ifOsm7tLK/Q1ffgfdjnBFaOHDmGhNDVwj5oq8UEyZPrFFljdu8LCRTKo0RkzcfsyrkQXr76Od33wuuaGEvfPceWo4TOu36mjCAm3XfXMu375Mm1mhjTbjMCYVpGuili7H/Er+/VjyLGPhhxKQnrprRorUOE+PnyuqmZuv4fZjfIsK7t++TJdZE6y9EIYiuCgKrdfe90ZpI1bj5A151PYdSsUyMxgBAQMaVFlhirR9JQzDlFjMU3QTDSfFhibKTeMSoLRJQq4zy7INWCDUKcVg6ehSLGjjJtPqskqu9l1zU/f9e3l2WWNUcGZNge6XjfC69rAyF7R1cA2sVoWd2dVIVma3r/XRvnLNYKfW8IXH3MMc69fGOutp13KWLsECLG2D355yRPWmJMrfZHCGZh71H1vStT2zzPn4ixEZ77jk9GWWLsDTM2pWdu3etzDB6cPDS/M39OsfaQRRhK6bYH0dzkrFnFYNqDNs4dYonlK4Tte9a9T2ft5y0p7tWyIMxB2iOck9JZ/R+wfW/8V0PFWOycrjuZYiyj/wuhSWkixtj3fv8HFDGWLMrnNkOHMHNHHoqDXFpHTD2WudYKNv8HwOaze1/7Pfqefx1jvzTDfC/ZNfjLEGOzTvUUhDxemr4ewIixaSaVfVTy9OoZWFnGiTF/vs3LIzUxdgJGnvX/Mdfzy0DlSpa+YvqeXV5w3VrpCMWc46618Q1s1PHex4kYOw0qNItbd/ZKQivG3kj5Pf/4kRNYOXLkOODoMmRN9i6CAkDy5Fo39o5GbHKjVCuMGKsDV8WUDUuMWQPBLwNNrogYa/2LdOPcLcdaphjLRrVoXSnTbEJerk6vrrN4heTJteh74eAd8PYL+seIVW+1mGDXPy/D6Os+Gu4gFvkVnZXzzEvqWCsvvIH2NBWTl78fHDt2fbOT2SJfMZbeeMwughnEGEfv4780rpRpcIIQv/A6Wv/CblufVhJSjGURY/z8ZNE6HDLqsLrlzZENAdc4rhYsUXpIS1Pqc8fE/yDVypnZLkZSusa53xD8xedqocT6Xjgm+Aa9IcZY34uTUhTn6A2M+8ps5/r+vRLRQMQYL0caKcwVY2mgM61b+xWRHQoR1FHv47/EIc15mx8KnObl1eveX7+r20N9smag3M/ag/ecivQV3h6oPXGyhsO4GN3+cZcYi5QZUG2+Xt+zynlLSnP4/R/Q7n267x0yIT4f4+c0Mu5ROfbuUAtCvitlmvik886nMGxi/XEpRzpCYtCSNenu0PYHrhVL6P7RCoz90kxvwdim400oWbROE2O8PXDSy+au+t7rGPelGSZd2NT1uX170XnHUxg1+9TImOCTWHAUY2HzcimkarFkiDHrSukTdfZ8IsbiOyW6Haq87BW7IARE5250frVQQte3lzkuhgcbcgIrR44cBxS9j/8CTR86Cm0NkDV7tXE+4bb6qhXAJcbqLPinEmMx1BxirP7KORFjWcY5IUaM+XBdKS0xVk8cPFRiLMcQEPwYtgUSWROL/+GLxfteeIOt3mVjX7FXGwjn4pAUQornrwyEo5wJYZpYvRpVjKX3qs47f4ZRs05rjLANVs7jakAJqXfO/KWJe1UPVNct532obloixtrqqVZyNASuTOpKM86Dk0QqWRNrbTwGoR9rJYaSp1rxCSNu8JrYO17fi5FS1Y6S6Xuxe/TLruIcHRUY5zFSmNSa9YgQqf/jKuJAYONl3wgxlmPwqBWUcT7mb2ZEfwcfyf9ehxFn+cZ5HHt//S76XvCIUjAFFoMixn7WWN9DxLU2Aj7/UO59H48axk5sHzQY90qHaiDjfDQjxtLKU3MWhBobE5o+dGRD87EcKeBtTcuaaoUS+hhZI7z0vutn9w8VWXPYB49ylIMBxy6B8tJXsHv9jrqxMSU0MfbDFRj7NzMNURori3FpXbgOI6nv+ffF0wPY+5oixsb+zYy4opKlJcXYqFmnKve+WLnZ32TROkjABoSP3B/dS62jhPLSV5RrrY45Z5LyD/p9jBg72JATWDly5BgChPdJKyleeB17NuzAmL/6WF3ypVosYdd3lmL0X4WqlRiIGDNqkdTSANXfDI4Y81VMWXh/iDFp8j6QxBgvR9cgFGM5UmAmEnpKJhlZ8z/c+B9GJs4mHrVCgt7HfqnUdSObLBnlTcDoeElvEDDiTL1jlARs4H/hnGN2jLruXDcfnrdGtZCg65+X6Q0CWlkZpXOPdA+GGLv4lKCszr0yxdi4f5rtzsDYe14u7lKiECkzEce8rhn4pgb0TxEhv8SE267EIRPyNr+/4M/b3n//pTUQkL5SDAB73ylqsmZ28F3wDHfImsEZ5ybPSLwSQPe9f69PjFH7IdWKcikJwa9CxFjbX9kgxGl1UmOKseHto1PLQCDF2KhZpwXX9WGJsdlZXHSOwUIC3T9WBmPTh46iQ6kwSopG5giFhBFjEXdy7zMnxrL6HQD0v/au0/diZaaYOgOVfh0LcapeIPQXSlzwuFdZ5aBFir5lyjgXjBhLm8NlLQj5qCx7peEFoRwp0D+EE1Ovrx+ddz6FltmnmhiEQZwyDSFsaIrWv5jqKge986Rk7n23X+Hs3gcJy3axVw8RY7rv+WSOWbMQ1B52OKSRQwQTqSZ432OKsQjJRZ9Liywx5hNy/l9SjEWJMe/+SK05atapbjmo7rzrEDHW9gmP/DvIkBNYOXL8AaKzsxPbtm1DV1dXapq+vj789re/xW9/+9v/xpIRpPMAllLq2Du/xIRbP64mKZEBwFklefyXaP7YB53gnGkvIsZG/9VHw/zgDpC1YoKuf9bEmGOch+dBesRYZHDmack4n3Drx1MHI05AOMSYn87LO3mSxb3KGvDAiLFbP27vMVZ2jdKT69D8MU2MHcQD3oGBnp1JS5QGxrmgHSapgarzOu/6GXPvc3ehdHfS0cZ5oeQRlCx2AguoomLeaGKsucmkMbt4mnIL2/fOI5cSyo/HZYDp13bHKL5DkAAvi905UxnnY647V7VLdu/mvbQkg3HnuvhUU7YgUIxewXeNc1Z3LD9IaTg4S4SMRm7N7x+4gUrGuY1VJuCq/Gxacu8b+zcz6xJSEqo9xIzzmIG81zHOsw1oOQjVioREadFa685V54FZNcQY3zHKrxMLHueIp+H3KLUlR6S0784VQ63guTHnz/kDBm6c14NRrdyu5kGZJJMEen683CHGslDWxnmbJo1ibYwWE2qFEnp+vCKj75HbkzT3yBVjaW0TIMWYcu/L6v+AUq103WnjHKVB6uski9ZhoNLvqGbT6rBaLKFMdd2AWjNH4yCyZlQDCsLd697WZM1MfcRf4LZQxNjPXLKGw2vSyZNaxZQSBw2w72uFRLWHO66I7pTIxblSAt0/aqzvCVii1Oxa68/RGWpFS4zRjtFZKD05eLXm2C/NhDO9Owgx/P/tAuTIcbDhsccew+rVq3HdddfhnHPOcb7r6urCY489hu3bt5tj06dPx1VXXYXm5mZzbMWKFViyZAlGjhyJrq4uHH300fjKV77ipAGAm266CZMnT8b1119/gO9C+7MLuyOGMhCm6a1t+ejCT1MjT/K/16JWLEVX5d3LCFQLveh9/JeYeP+1alBKI5j0yk3v479A83kftIFxeRqPUCNibOL917j5UFr2PqoYSzESpJTo/fdfoOmDR1lljnNfbpn2/SaFGEu5RuddP0Pzx5hijAKhREis5H8rxdjY783MjZr9hiWDasUSuv55mW4P3iSFkzYaRJSOmnUam3y5pBV93vebIts5Ux3nu/tJ6eatiLHYLoKReA9PqpXzcf80O5LOfU/E2MRvXgvRHO4Q5Jel999/iebzPoimMz3VCt0ba/cq1soOTPzmNdFy8s/WpeRj3qYQcfQ+9gvtSnlaapocDYAIQv272ZVzazA6z3puIQwAPT9egebzP4jDPnQ0vAYcXKryrDLO2795tfvsJaKXnVctlND94xUY+zcXuc/iWN5CGQgjzzrWBKVOgxACe177ne17Zkxg+fJbLPeji4gxJyC8dMcRDQoArtSJbhqfjKgVS+j9919i4v1Xa5cS9XwXgggD915V32O7teUYGojI122u/7XfKVdrvYux0w68epYVpqTQC0vO70rn6PHaGOexOYKHakHH3jEB4W37oWDWkBJSSGBAK8bOO8Hte25p1blCoLzsZexZ/7Z6FlPf41M4U26mWvmfM3Ug9pT+rw8nT67DyLOOs30vLbAXgP5fU127bu1+/weAgb5+thFKW2qeOQYPUjEd/oO/yqxWIQT2FXrR+/iLGPdPs1kcVvckPrXuecxV72Zhz3pFjPmbtcTK5BBjKfHY/E1jgJCUjnRr7BskUcqJsXrNkhaEJn7rmrr5OmrNCdk2yMGAXIGVI8d/I7q6urB69erU777zne+gq6sLX/nKV3Drrbfi0ksvxerVq/H444876RYuXIhLLrkE9913H+677z7s3r0bK1ascPKjz5deeun7dj92NyVF1rRcXGdQktKQNeP+6RJ90DNevUlQ192WGLNgaSi9VPL6mItRbIssMhAm3OoNStw4llYZU/p3phirAyLGUlfO2TXSXCmdWC7sfe/jv1TEGB94mZKHp3eIsRwHFN0/Xq6I0gbcHMrLXlYKwus+WndCUy1mB6X2zydiLOx7YZu37n2X1N01DnBJ6RicCeGTa7ViLEOlQCulpNa8rbEJYe/jvwxJ6RQYtSaPtXIQr1LuP5QyTlb2ovOun2HUxdo4J0Wfo/CT5lmU/G9tIPyPs7zl8jB/s3J+25XapUQTtpIZrUzN2PsTbZx/8ChTPksuuONJeekr2LPhbS8emy233bVVxb3q+X/Y+884u4orXRx+tiQkdUvdLalb+MNI+P5sENEzIvgaBYIRyUYiGhEcwJ7gMJ5gY/uODb7v7z/GjMcYPOPxGHuiE0mg2LKJEqDQDTYgcUEICXvutQT3fUd9Tksn9OmgPl3vh6pVtSrsffZpCQ9/dz3QOqmqdu3aVXvXeupZq+7ZhNmfdoIQ83JFov8qq4kYW6g6ma92pM43THGOPk/klSnHbQ9JhKxF+zWkIIQ+R9uNRx6z+jCLOWfVI6J5mJ2/qD9IsqbD6QeA25e0kuIDC53fiBSjQwilIHwNsz9NqhUbliJ3YATFr61TY891tfbVvnrsfeh9rM52XQG565wOSv0/r1a7tcEZo6wfi0Q9907CtFPmZY5/INGKMb45R2j8AwlG+yqSlNbEGMLjX+WpPESqlYVs/AebMqIJ1PsqKD/0C3T9f65smFYIgYPf+jlazz8Jx/y3robpqz9/CcOvvqmClNv3KDfIO+2mzIkxNy1/n0WMucca+uV/yLH3mWVeWuGkF7WRzB2jXaQRYyHUHVI6rc4UIuFgE2rNiYBIYEVE/BbR3d3tqaT4b0ReLViwAPPmzcPy5cuxaNEi7Ny5U6uyenp6MH/+fCxbJm++nZ2dWLZsmUWMFYtFbNq0CcuXL0dnZ+fRPxE2UdBkzccauTkkNlmj49II9mobCz4xRhMmbhDJ9JKs2Y05t7jEGNjkx3xX8IixUHr5kCbFmHwoZRgHakJIxNikTONcHsMmxtiD05ssU1vzQKgpyhXl0hmOMRaNmyNF5eHnAOSbpIz2lTHwyEu5yZpDRIzlIGs0MdZw7MH0B+Vi1IhIK//YDwifBk6M5UEjYoyQQBFjffmCUqcRY3Fxfrww94ryw89JJYXeSj2UTt6ftZvDpy8CGcqu8Ux/Y9VhFL62FjM/sFBvM+6Xbf4qq8mlRLkYMWGXez+sH6ig9shL6Pqf1ygFYYAs0o+fBIe+L8fe1FN+L1geZ0IHHtmJoV/+b8y8xq6HfQxpeIweqDjEmGtsh4iQdzEFoUtKmfcjr76BgWdeU8+9aMQfOQx5evCun0lF6Snz9G/m1e5LA4+8hKHn/zfarsmKSanImgOSrJnF+wMSRj5Sv5Tv7bHn1gNWvmFr7PG0/KMaH1WpWpmhxx4/N+ccBX/uuefoj+s6e+5JYiw8/gmle2jszYMNnwgceGSnaWtr/EccCYSKg9Zx81IVny/tPi9ReegXmDy3PeezmYixq+SxnBsVfSYCqT+DGON5BQQGfv4SRhQxFjwvUhuCwi1sQ+cXPpjq0srLP/TDLbnd+4af/9+oPcNdKdMhQnGv+PzfOcdm3JgnCiKBFRHxW0Jvby96e3uxcuXK4O979+7FggULPMKJ3Awp1lWxWERLS4uVxiXFuru7sWDBAs9F8ejCIWtY/I/wHydr3g3/4QiWX6C25TUMPf8faP/YubAnO+4qe4J6X8kha1xix5ks/ZhUKwu9ct3VGq0YIwPBqid/L8k3oxhLmxCaOhli7H0N2gNWW4eNMftYpSAxFmd5RwpunDcKojs2IF2MpHGeZ4OAJlbvlIEw939ebQXGTQMpxlpyEGMDP9+JwV/+Rw5SGhlEaRilH21RxnnjCeEIV4w1TJ2fGItoDkSU5ltV5koKcilJT19Z81z+/vDqG45xbuAeQwxIYmxGg50zqV9VVj9nxVpxY6bIL+WLXjn/n+Hd2tw8nBhrBDLO8wQA166Un24cYywiH+iaV1Y/l9s4Hz1QRllt1pKnPxhi7Pe831xQf5jpqsoD+XTcq6z+4KhmaexlePYBgENKZ0PUhpVac2GuxZLKw/bYy4KOe+W0dVykOEIIuZNqy3vfhdZzT1YEintTNWo+qWLabRZTVXKKwZawuS4nxiz3PhH4A1B+iI09ReTy8nh6Q4y54TcSR6kqF4X7v/UztJ53Eqb8ty47vXUc+bmqiLGOm84J1tMcSz73Dv1wq1KM8YDwfp0hWLxH7tbOPSnYOVBbz/50yk6JExSRwIqI+C2gWCyiu7sbK1aswJw5c7zfa7UaisUiFixY4P1G3xGBNX/+fC+4+549ezTx1dvbi5deeuktdR0ElHH+tTWMrPFXJTkqq5/D2MBwSlBqO+9oXwWlH21xiDGeB1b6Q99/MoMYsz9X1Upp+0fPDdSDngtEjFWUcX6us1qTRoxtVYqxhcFj8/wU58goxty62Hl9YixUF4kwMRbJqyODDIx78J4ntYFAcWmsSQ17rw0EUhCGJmwqLQXGnf3pi1LT0OvYgDEQJoUCNjvpNTF2zX+3XZAC5Y8eUCvnXEGYlh5KMXYuc6V0J3csPREh7df8d/93px51R63JdzWy1C7qfelHWzH9rEBbu3WKaAqjB8pKxZRDQSiAQ99/IjdZI2PvsP6QgXoTZE0CqRizxl4GhgPEmIzv6KfVxFheUnp1frVm/YAxzvO1dRYxFu/344EQwNDz0sWo46ZzG6Yfqw6j+LW1uQn8t5IY61fEWO6xx4jSLAKo3mc/9xqh/BApxvKQ0vmJMb0g1ICUjmgSQs6LR1590+ykqp/JCbQ7NAAIgdEDzL2Pb5QE486q3VodYozShZ/JCYZ+KVVMHR87xzom37RFH6s2gsL/s9bspgxYecz5ybyVh3+ByV3tyrWWFp1NeRDQxxntq6DykBx7ELY60hyH3ieaGDvmnXNtIorXSaWv/vwlDO/+v+j4mLq/JEk4vVC752pXSm5npbXhxEEksCIifgtYtWoVAGD58rCLDZFTae5+nZ2dmrRauHAhBgcH0d3drXcrfOmll7Bo0SJNlC1btuytcR1kqKx+ThqMly60fwjciIdffUPuUkKTlNBKBmVxibGsm7RQK+ciIGsP5BvtK6P2yE5jnIcMXPb+4Pef8ONehcgCAVQf2WkUYyl1JpNCG+cfdeIcpZAh2pWS2jqFMAEoAPhuzPn8cr+NJ/gD74ggBA4qonTqyb9nT2B0GvVKgXGf/99ou9rZtSaQrd5XwcF7nsSsT13IXGvd45vXysPPGbLG7QdOn6bd2hoaCAIQNWmMaeM8YSuSifMqnJVzp5+56rR6X0UTY9ZmDK7MRcjvNDFGY8+N7SOgJ6myrdm29bHPHxXIe/FazGS792WpDiurn0PSOi23ca5da4+ycV6hsZeDGDt8gMc5MmPPDURMMO5c6cY5tVBTxrnlSnl0ibGI/JDG+VbMucWPvRNC+SfKOD/v5IZpKfZOHmJMHAEx1kgZrHcxzunWLo1z5VrboGxNjOVU7zZDjFVo7OUgpSPyo67JmmsAGJfvJEnYY998d1D1h2PeORchzwJehlQx/V/VHzjxYqeTC8Zy7HV+YblH1pi6mGMdUmrulvNOdurh/w09/7/V2HP7pbtYnGCsNoLiXytizFJTOXnUeVQeprH3PqdM91wlIVVZ/QsWl9ZO4+btv9tta16Xib1IEQmsiIi3GN3d3di5cyduueWWo1JeZ2cnbrrpJvT29uLWW2/F97//fSxfvhyLFy9Gd3c3gHSi7GihtuVVGRj3ahb/g/4SWDf70b4yDn3/SWkgdAUIKUeBUV79HFqIGHMJJift8G65a83sTwVUK056uVK6BjMuXYjJXe0mSGqICFLGOYgYyygXiYpz9POd6LotW7VC6peD9zxhFGPsdytwuzpW9VG5Q5BeraE2diHkCr4mxtztewPXJiI/qo+8BAD2JCXFyNXxP0hBGCJpAP099YdcW6k/wo1zh1SierF6HPx+A2KMocyJMQB65VO956861sqnmHHOSD2LQ6oNo/DXa8LGubdrXILKw88aYoyXHWjvUdbWcSv1o4tDP96K6XzlXDBix7m3ecZ54P5HINVK2zWKGEu7v6r32jin3drSyhYy8HaNKwgDpK5+P6bcuc49GdNO/r1wvRUSJBhwibEU8liA3PvU2KOFGK9c4+aiF4SIlM549lnEGJHFae0XkR9CaFXbMSEXI+dv4Oc7Mbz7TbR/NMXFiH2uH6ig9GNFjHW1Bcvj1/HQT7ai5Sw19ryyEyu9HntqjuCNUX6KVane1XFI3TSBeRB350ob/xDyXkzEWNb4p8+aGKMFoZTxL9ualPOBto59/YhQ+Ou1OjYmYD/q3ce/5d6XAeH2h4x0BFqkmPLOQNwrYacdeGQnRl79v7njfxpSWs6Ls2KmlX+0lRFj2WhGrVlXixSzUkhpt06V1c8pxdh/D6az4zROPEz5r65ARMTvMvbs2YONGzdi5cqVR1URtXDhQixcuND6bv/+/ejt7cUdd9yBWq2Ge+65B2+88QZqtRoWLFiAm2+++ejVQQBdt12DSTOnISHZMPuNv5aUamXayW5wTh8DiqyZ+40bgsfkqBcqOPT9JzH7UxelBmPkqKwhA2GhLC5DM6+3c/7q1Q0nR2JgGMXb17AgxA3qQSvngWCvbp1GC4oY++o1gZ0S4dXt4A8cYqxB+oj8mDRjmiJrshvTJmvaoWb94ULVBgEQrpKCmEbOOCYOMTbd/GYVbz6QYqwZYuzYb6Rt52zqUu+raFJ6yrHOVupwZrwIEGOp52jiHPk7Z1Ja9k1tSCqEeFtHHDVMfWcXOs47TV8i6VYnvMs2eqBsG+dpoGcCGefnnexfMqcrkYGQuZOqCuAzNjCM4u1r0UZx0KzAPqrCrPzKGscYc5Ly7w4fKKG8+hc49m9usBWEofoLJ85R0BfRZKaxN9cbe06dE0nQadWKauuU4R/RLBJg2snz0HbFKQ2fmaMHyro/BOH04/67NqL13JNxTMA418mE6Q8ju9/EO/7+JlUvZ7FEBWgTQqDOxx53Jw89/yGJseln2YoxPa6d+uuxpwiptPEPGPc+bZyH2o2PPU5Kp6Sh9/W+MsoPP4djQ/NCeQLw3LYicmPmBxfmUhDWntlt+gPU0zjUdyDJq6JDjGWh8nCYrAmh3lfRrtZ5QEQpDwifNiWrPPwchl99E+/4h5ty1EMRY4GdEkMo/TibGON1IlI6dI42qThxO31UYEVEvEUoFov40Y9+hGXLlukdA99K3HPPPVixYgU6OzuxatUq1Go13HLLLfjqV7+KwcFB/PCHPzxqx2o97xQ9SckigqR7nzBkTWjZQ303Wiij+vOdOXbvkzh4z+PGnasBiBhrz9whCLoeh37AVs7ToOqtFWM67lU6hneTO9fFDdNSjLFMlxLWnpoIyTrHuFXPuNF63slsgwBXNk9IpGrF6g++vN7I2v8jsGOUS+zI70RtCIWvOcRY4PiEyupfKGLsfQjXweSx3fv4jlHhcyTX2mknz2OTrlD6RBvn7ZZrS+iVtlJ/ErM/5ezOZaU1Flr54V84bZ1WdsR4oNvV5yTZZUhw8O6f2cZ5xpyajHPLxSjlvmQZ566iNKBW1cTYuSf5FXaeU3rl/GOBlXPXllfEmHT5bmPHD9e7suYXYeM8gNE+41LiPffcZ+sYdFvL517ipIt9/ciQpBjQ9r2kfqDs94cMeERp2nM4STB6oCz7w23McA0SoPL+38/HXoPn+8AjL2Fk95ten/fncGaDHk5KB8e/apOSIsZaQqS0A2/sZdR7rKZUKzeda7d1YPxHjA95XDK5mkortZA+/688/Au0nneyTZQG7k8JDDGWS8XUV0Hhr9egjbm1Z6Hy8HM45r/Nzb0xThpp5Nc7QeGv1yr3vnRSmtdj5NU30fGxcxrepem519mAGJvod/uowIqIeIvwwx/+EMViEfv378ddd92lv6/VagCAzZs3o7e3FzfddBO6uuQN0A3OTigWi/iDP0h/yHDXwWKxiN7eXnz1q1/FvHlS9XTTTTfh9ttvR6FQ0MfKwp49ezJ/L44VMn6VhvewCkrd9dVrzE8pEzGbrOlAoxlJlorJRb1QUcTYNblcjCj2zjRvO2e/3tVHlGIsbRWWQbpSPoFZn7qogTuXbD+jGDudDhisA6AUY1t2o+u2a/w0gfSNru/bAW+3OpZFCTKYp/pCb1NmphFS1v4m3vGdmwMl2BPueoEbCO0OZ+WTLxYxFkxjXoee/7VREAIIcl3qi7GBYYcYCyHR52sRpbpc5o6bQLdTvc+4cyWt01UPDrhTqq8OKWLM2krdOleTv/rISxj65X84q/JUj0TXKwFw+PDo264/uXg71q82VnO+8SVKlTXP5gxKLTdBqIRUKykKJcs495ROtjVdVca5Vq04x+b191QrKWpAyncoFOdIhAZVYOwFCWl5DIr32JgIMc8E09bp5QLAQK32tuxTHG+3+gkAh8dGnW99OV5lzS/Qeu7JzalWvnq1KSvF6B/9zxKKt6/FrI9yssbtY2YMVlY7Yy9jMVEqxp5TY68R4yO0a61tnIclilX93MtSrcg8FjFG55hR77J67rWce7Jdb49NS1Aql7Gn8vbqUy7ebn3+AIb97pDI56YQQne/oiJrUtV1Oq8kr0ZefROzv3OhdWsSCb9+8uVwQRFjX71azYuTcH9Q9ag8/Jwhxtzu6Ny+a1t22+rdtHon8plQ+NpaSYzxwPQpw6+8+llMO+X3jFt7BkY5MUZCQfdRw1D42lq0nnsyphzXBZrDCK62Z+sWxUIRe4pvfZ868cQT3/JjNItIYEVEvEWYP39+8HuKc1Sr1dDS0oLW1lb9t3fvXi89330whGKxiI0bN+oYW4WCJJf4boeUt7+/PxeB1ehm1dk3BPS9mfKrwGhfBYd+8ARmf/oiZ2LO79rGqLDd+0KTJIOR3W86BkJ6Wrlj1OocgXGVgbD6OQAiQIy59RYq9o4kxhruEARjnIfdufwJoSHGstuj3qcUY58MBUL1611Z/RxO/OrHGtb3vxJ79ux52z0w2/9vAThU8Fae6fNogdwcbgzZwF637ycD4bi55jKFbGjIOGgju97EO/7h5oAhb+cZJWLs85fZMeeICOJ2twBKP9liE2NAyoRQGedP75YTMX5ero2XMGJMxZwL1pl9Nq6U71NHS3FNTljMua+yAOAp7SIAVP/1aZz4revwdsXbsb8DQOtv/g9Qq6TceYis4cZ5GoS8F9++Bh0fdXd0DSOdrPEhVStknKfVw3QIQ4zNtc4ndAzbnSuUxrTO6IFSgBiz0/B8xp3rlIyWkHUPu1K65RMpPYTRR1/Aibdd1aDc/zq8Hfu8AHDMr3YBh4edb831rqx+DsO738Q7/v5C+DdBG1pN9dWrU3YxtlFVxFjLeSd5aUwPUvPHEDGWUvaoUozNssaeX2fyxDMB4eleHB7/gAkILxcSssaezGOIsbkpaQ2qj+yU7lzfuTlYX456XxnH/N8RnHj9BxuW+1+Ft2Ofn3m4CvxqByw3VSHM9RZSzT3t5HxkTf1A2Z+fqzzWM111quJfS7LGJTM9t1bVL2V/uDBcD/adVox99erGpBuA8mpFSp/rkNLu/CZxxp7r3guTDkL2S72DOF+4dueI6nNl9XOyrRkpLdz2UHWq95XR0teHE6956z183o6IBFZExFuElStXBr/fs2cP7r77bh14nbBo0SJs2rQJxWLRilW1adMmAOmk0l133YVFixZhwYIFAIDW1lYAkiCj90SC0ee3DvJOfPDubt+9TwDgKzBqKYKClGsVk56nOA8FIY3zg99/wgRj1A8XweY25mlQduJepdUX4IoxvjuIcOpiVCsm7lWbU5abXK6UAkwx5s3FzFPSJsamw3uCOnlNnCOuGOOMCHTbVx/Zidozu4GvpjRHxLgwVpNKilkfOzesrnOIIWkgtIUVhE63lwaCMs4F7DgkrEzCQR1rxRgIXh51nOojihj7zs3eby6JNRpSjKWcHxFjlmttiGBSsFQrussGyCsY19q2JnYpnZG1R3xEQ4RaT7s53LI8ByGV4JAiSnPt1mapmDhJ42OsKu/FHR89F1Pmtmd0B5nfEGMh9a59jLoixt5hEWOhekhi7GCQGAuVnTBi7ObUGhNGWQDw9HM05Zd+shWY+86G5UbkgWlX2zh3SUwHAijevkYZ543JK0OMhXes5Nec+qVNjKWTO5U1zylijI89P70QZJzbBETamBrtK0sF4ccakdJq7K3OGns29HNPK2yzCHIZY0xcvqJhuREpCLiRAiLYH9JQL1RQ+NpatF8Tdu8LEVIWWZOWFkzFFKpHoIMWv+YQYxkg977Z32ExTi1Cj1ImZgdPTYyljA5NSClSmtzaU9MmqG15NeUc/Thj9f8so3D7WuBTf9Lw/H5XEWNgRUS8TbBs2TK0trbirrvuwp49e1AoFLBq1Sr09vbq2FYuiNxascI8uOfPn4/Ozk5s3rzZStfZ2aldCo8YxI2IRP3RZ4HKahX/4+qz7XRQf8L8jRbUROy2azCpdbqdDk7ZYAbCcWpL2USlATuGOh6pmDo+cq51THpYUH0hEq0Ym/P55dKFkX5DID2UauVM2imRyhXsXAnGpWT2py42aVk9eZ6xgRFDjBFJoOtp2oHea8XY1e+zy7JeZT1G+yqSGGvkZhiRH+p6lH+8hbk5hNPQe+oPHR89L5yGucuN1ZRqhRkIoWC7BBMY1zYQQnlG+4wRJI+bUm8aewFizINKS8RY+0cbx7QY7Suj9BN7h6BgfdR3pR8zIqRBzBepWtmdy9U4ogF4fxgDCso4n0Luffz+5OTR8T+oP4j0Px0QnhSECJTN6lL66Ra9ci6Qng4CGPqlVBB2fPRc/9jOcUTVKMYmWffi8LlaYy9UJvuOFGNdt17tpwmcw8G7N+rnnkgrl8bez6U7V8dHGu/OFZGCwPWtHyijcPsatF/zPr9fBv60cU79wS3b6Q+1Z3bL/pDVL52xp++XaX1TmLFn7absniONPf1MuCasmnWOVV39nFGtZIx/CEOMdXwsMPbce0BfGQVOjGWMf8DslJgnDmlECDTn5jDunpqsaYDSj7YEiFL3OBLk3pe6kMCe7aOkYrrmfdaCceLFISSi9BepxJhbj7pFjAnzmzVnMkrLwl+vyU+Mrf4Fhl99k6mI0+ERYxbcgQWUm3Bj/l1FJLAiIt4m6Ozs1G6Ad999N2699Vb09vZi5cqVWL58uZe+WCxi06ZNWL58uUdufeYzn8HOnTvxuc99Dp/73Oewd+9eXfZRQaL/YV9QUOpXmXHuPGDYfZhUTN7qXeKmlWVoA+Hqs2EIICcTTQj7DDHmPzgYKaV+0wbCO+d6v7npBx7ZoYyx84JtwN9L43yLJMbcCSESlczUvfSTZ6Rq5dLTA+Xaf0MvSON89icvlmXwsnSTyLRjtWEUb1+de6fEiPwgWXtHHrKmwMmalAkQmzhpsiZEjDnkDZE1FjGWAlELjD1/jqSPk0aMhcCNoDywxp46nnZ1dKCNc01ApFVaxRj7yRbV1h256hLhIIVYqaxJMc4DeYxq5RqrjOB8XhjViu4PIcNVva+sVsY5V7a6adkzofSTrQF3LngqRgjg0E+2NDYQ1Hlq49y9BwS6p2CKsaCC0CEKgmOP2Vkc9QNlVNY8JwOAZ9tLEWkIkU2Qam6ppDjZT+dAGue70XbN2cGyNBJy71uDtmveF342O9dajz1GSCX6+W9nrfeVVWxMR9GRMqaKX1PGOamIM4jVyurnMLzrTf+ZEMhjFiqvNvOgjP5ZcYmxjHrXntmN2pZ8z72INPCbsvnTrm96QxUE0wGSrKn3lRlZE/qTeet9FZR+xO/FJo0O9M7m3OUfb3Vca2UaszDnEmO7GTEWqoccVEYx5p5j4uSFOkc29ryy7XqM9lUctabbxuy9SFD4Giels9pPtvXIbkWMZdyHftcRXQgjIn7LOPHEE/GDH/wg+Nu8efNwxx13YO/evWhtbcWcOXNS3f5aWlpwyy23BJVZVM4bb7yBlpaWYJqjjdG+Mko/TSNr4BkJpZ8+g+lnvgut5zjxPwI35KEXfm2ClHsEl42x2jCKX1+dP9aKRYxlY7RPBUK948aGaYGAce6CnUP1URUI9e8/bqcJ+NiPFhgxluZGxdv6J88oxdjpgYQR44WUtYcmKWGQgZAn/gcZ5+GA8LD6hO4PtywPu7Q6OPTjLWq3tqzVO5l/6Je/tgkIINgnAZcYy4rHZs7RNs55uXb6eqGi4hzdmHluhP4mYq1EpCCgcCMDIZdLSZ9SrbjxP4Dg5bOIsTQIWa/R/yyl1iNBAtcFNezOFa5LZfVzGNn9JmZ/6qKGBoKlWsmxKq+JscyxJ5HZ1k69RvvKNjEWGayjhsrDqj/8Xdi9j6Pex937GvQH4ZA1gHdr47FvTH+4xkoT2glu9D/LKH6dEWMN+rEce/PQds37/PhDbtl9gThHIahzKX4tMPZSiq+sfg4ju8idKwA1/iGEfiZ03ZZPIRSRBv9eUfrxFkw7+feCO/y6T9/DvymwOULj+07ha2sYMWbD7RaV1c+h3lfGnFvMIr45vk2q1fvKKP1oK479xg25XFqzFWP2edSeec1x7wssjKtXcq21Sem09A4pHUgl2KfRVDfmiYeowIqIeBtiwYIFmDdvXmbMqtbW1obE1Lx5894a8iow+Tj47ebJmjyrZpaKKSQnd0BkTeu5jQLjKneuLa9KN8MGeKuJscrqZ8PufYGJZENijKGZto7Ij9G+ilw51xOxFFmEguVS0rDssk8aeTATJkOM5djOWRFjvnufu4QvzNhz4xwJN5/EIa0YC409ux+HFWNh8mpMbcZgiLFUuZg+x7yKsYj8sMmafPdAS7WSgaBqJQX1AyVpnKcZQc49kxvnEunjVBsIrmollMcixtrCaXg9FDGWa/fcvkogzlEIps9bRMgEXpk/mjj8mz65eHZrDkWpCLj3ZSDYH5zrRn159EATxFiS6LhXuYnSp3fLIN0IE2IEIkrTxp5d+fE+9xoQY6p+ha+tzt3WEflRe2Y3hp7/D7STuydBsBc1D6/3ldF/18/kTqp89z4R/tPE2KULMxWzgBp7T+/GnM8vt8oQIWWgUMSYS9i69VEgYkwrGTmcOtf7yij9eItxrW1wjqQYs1xr3T/W1nLsne39ps9VvSe1pmzrxqT07zoigRUREXHEOGpkjYdEEWOnHCFZ4xsWowWmGAtOgOw8FPfq/1XEWKGZto5oCGsC9CwzEJgsMDBZsYzzEAHL0gYNBHeyBoBitFVWP6sMBF62o2RS8dBsYixxyqbZoSlDu3Md12V+o2PrOgvVHirO0UfO1XWTaX0JfL2vYivGdJ15oyT6OwoIL8eeI6t3ztkQY+fa5UQ0D2cybZM12aCg1LkM1wPNqZjKLlmTioSNvXz1SCfGfGvBKMbOTk3Dy5bEWF4iJI9xLoneMDE2wa2bI0aC+oEy+u/+mXo2u7sp+yj9dEsGWWPn0aqVnP2h+PU0YsyvS+XhZ1V/SJsjsHtxgRNjHQ3LLv9ka66xlyTNjb16oQliDESMzYuLFEcDQbLmarO7doAsIpR+LFVM0896d7p3hHoE17ZIYqzjY+faaWm6wPJpYuxj52Dyse1WOdYjXeUp/YQpxjwyjPVjARz+P32oPbMbcz6/IkxGAZb6WBNjXW22F2IAkhgr+f3SHUpCbYTyky0+KR0gsgCg/BPW1hGRwIqIiDgy1La8mpusGe2rhMma1IfBs4qsabRbW9KAGBPe28YqJpNHEmNv5FeMZRFjzrkeHcWYP9GUMcbyE2MReSDJIBN752zYgfj9v1Fyc9CBcU3cAyuovypfKynOOcUmZ8DSqtfaM68GVCssvoLetEC6W+hYKzoodeLXRwVGrTz8rDQQeMw5/kp/SaICoe5mMed4m8AhmRJtnMuYc4lfLptUasXYR85TxJlLnqk6C2C0ULFjzjmbQEQ0C9NwvoqJw77/pJM1ifM+yTDOA2nBVSs5lFqp7n3hDmFUK43vxWHFWJjYsImxHORfHldKAIBIaetI2h45hN4gYPpZ72Lfh9pVkjVDv/yPjI0rTJ8bPVBG/90bmaI0+1pJYiw09siSNvf8w7/pY/0h7cZn8hS+tgYzL6XYmDy9b6WnGueB+h8+UDKqlaAbld1HiQgxxFh62maIsYjmYMiaHG6nq59Dva8SjkHIoRbPSj/egq7brkbSOi28iMfeW8RYiGTiKiY19jo+ljL2nHALkpQ+J/tezDZsslwpQ/MJ1TVp7M35fGA3zMD5Fm5fg/ar8xO29UI59nmGSGBFRESMD+qhJIPGfsh54CXBh05lzbNoPccxzt086s8QY+elPrgoz2hfySdr3BUMllermK6yFTHCO45DjLHfrN2g2DEOfnsjWs85Re6UmGo8y3prxVjoHJ0/L8aYVU/hpS/9dAumn/luv62jMT8+qHYb5WRN1iRMoUhKilBcOAuMGLv6bDZfDxs39QKNPS5rZ4SRU3ZZK8YaGOd67O12iOPEeZUYVXGOdLyHLNtZMCKEdil1i2fjabSgghBrV0qn8MQ+3yInxiKOAiThSAZj+0fP8YlGoQxduk8dqKD4dRUHjVxKKB2Rj7qfCm0gyL4mYBG6nKgUwjfO+f3M2t0Varc2pmKySFQ45TNi7GrHGPPOlynGbrtGnaN//+XnWSVi7JyTg7/zelFAeKOodFWG5r1FjFk748Wb/LjB+kO9UGH3KdNndd+j+QeRNbddg0mt02BfJ8prFgrKP5UqpulnvouVCViEv/psiLFzAn2MXWdBxNjPzNhz5lT8/AAae/Mw4wOnp88RVP+zVCsZ45/OsXg7U61kjH/d1n3KOM8Y/xBKvavdubjLWiRtjxSkdM6zm6Mha/wNptzrMFYbRpG79wVh8lj9IXOnYbmTOSnGktZpDetd/nF+FZMee2nEGEEwYiwY/9OtdqLVmk219ecCxNgERiSwIiIixgGpeijevhqt55hda4hLMRMyk6Oy5jmMvPpG0PVN5jOJRwsVZpy3+byLnrTIUL3kztVyzin2/FL4VSFirP3D6qGUJLrKhjOQ3xli7DxM7mpPrQcdo7LmORzzzrlou/p99hyQTwxVANLRQhkDj+xwYmv4D2sqR7a1IsZYPSkRn59SW5NSSzhlRYwPo4Uyil9fnb5jlAPt5pDTtba25VWjpGhwsfK5GJl6aGKsUT04MZZWNuumZiv1U0y9U+pe2/Iqas+82lhRmai2vn21UYyFwO8vTbR1RE4IvnJ+DSa1TodLosh0xkAvk2rlzHdrNZ9Nfpr8ta0q1spHz1P3RZeANflH+yrMOG+Hpx7U+eR3WrViERBcSWjya3euW68Jp3GN86+n7Rhl11ka57+QrpRXn+20BycAaCGmYpPSSFSxTt1JjeYpxty6RIwHh/fJ/jDnL5VxnvBrBadfyP5g7WRm9TebRKqsUUoKrWx1+7D5XO8jFyM29vhfwsoH7LHn9Re7z9eeUcb5R8710/E+n8j5WP+3+dhD6vgHjGJsxgdOh90f/fGk2/rzKzLHP/0Vbl9tFELB8R8xHlQf2YmhX/4HZmYqfGQ707141qcuTCFr7AtRWf0cpjckxmSe4VffRG0LUzFlkPFjA0M5iDG7HpZijJ2TjUTuYvxjPvayQXGvbLVmCFI5H1Zr+nWxSOngxjgTF5HAioiIGBcqq5/FtFPmYaaaiHkLfAxSSfGq5eZg0tHGueZmXPz6w4oYa9e/JywfnxRV19DK+dnq24TmXTov1We0UEFl7XPovO0aTJnbbhFnPJ0QAgk4MWbiPfCpmJnjJahtlcTYTGacBx+9QgbHlkTI2ZikJr2yLGG1I9Wfq1as3wMP9zoRIbdeY5NozjlGNItExyDI52Ik+0OQrHHwWyXGGqCYhxgjwnb1cxhOIaVD9WhIjLHyK3kVY2iurSOaQAIUv746n4GQMDcH6g8ZNxubGGvgUpK4xnn4+ITallcVMZbHrb2M/m+TO1fjsVe6lxFjDewHuXL+qlmkyLr5CtnWwd3aAsehnfEsJWO8uR8xRg9UpHtfmprbuRiarMmxw+/hfbI/aGIsCwIofH11touRReD/wh57GaBda7tuu8bEOQLsUyPiVLDYO2ljj+WVxvmv5dhr0B+lakW1tbtI4Yx/oEFbR9523Bjtq2DgkZ2KrHFVTP7su/T9J9B67smYdsp8liYMIsbSn81mRj3aV8ahHzyBWZ+8yNlNOZRHblTgK8a8TgxAEWNBxZjfSccGhlhA+KxNYySMYizH2DtQ0nGvzNiz25fXv2y5MbttMbFv+JHAioiIaBpkMM68Sj6UiMQhEOUkVUykpDgbk+d2OARXookaWY58KE09aR7arl7EvjdpExiyjIzzzts+pMoNPbzMa/H2h9F6zimMGLPLNFSZrIc0EBYxMizx6iLrUVIuJR/SSq2EnZM5Vyr7WbSecwpazznFajded/reEGNnq9JMHTmZl0DGWyrewYkx+3f3OkXkR/XRnXKScvWihmm5gZDHKG6OGNudnxjrO1rEWGBlMEBKZ0Ea56ccfcVYM8RYRFPQLkZ5jPP/04falvzGeW5iDJKs0cZ52u2L1CJ9zDjP41KSRYw57iu1rco4pxiEDQi6/m9vzB2D0FKMuXCOc3hfn16kiDiKEALle/O7GA08uhNDz7P+kIHRvrJPjGXAImsa2KnUH3KPvdtTxp674gVmnDe6FwuHGMsz9vIGpRaKlCZiLCVNxPhQvH01Zn5goePyDRgVn/lcefg5CAg5/9Cu08KkIaWiUu/axJitRtRupQqHvv+kJMZO/j1H8WjKpDxaMXb1+zyVo6UOhFQyHvrBE1Ixxl1a9fmx81Rz/+lnvospCM1vbvoRToxZx4d3rmMDw1KtefX7MLmrw1JPhtq9svpZ89wTlMhRMU7gfh8JrIiIiHGh69YPqV1rbJKJE0wJaDvnU9BCsZgYocLXHQSAQVJSqJUMrtICe03AVStnW0otSucSZdU1dlBqXrZ9DBlfyCXGeFlw8hXvkMb5JIcY89PKOGAju9/ETKWmss8xsdKOqh2COm/9kFKM+efF26myWhJjLeec4pXl1iOiOUxqnYY5n1sO3fqu6oE1rDQQznZW8F1CFWqSogyEq86246rxPOrzaF8FpZ88E4g5B6tMei3/dIuMOUe79wUMFIKlYrKOLyeMeo4qDCmtV87dejifDTEW2LLaOl+uGPtQrkla8evSjXlSFydsI44ORH7jfBxkTS5i7DeOcZ51AxtrkhhzFWMuuFs7xd5xVSspMCvnrnHu90+pGAsQIYH4L/UmiZCI5jB5bltu4rz6yI58/UEAh37wRG5irErEWF4F4XiJsQbQY+9zOYgxZBBjAeQmxtAEKR0nN+NC67knq/7gumyCyfYTjLz6BmpbdmP2py6G7w6tXtU9S9RGULx9jSLGuGstTB6t8pPEGCCMa60V39KeO40WKjL8huXe55YJ/XdQE2PzWb1Z2fo1MYoxvquz3mzHTl/vq+DgD57ArE9dpMOoeO3B2rKyWhFj1thjx2fk1PDuN+24V9xd2Eo/cREJrIiIiKbRcu4pmDS3PXj75DZ4Zc2zGP1NH2Yq9z62fqDvw1RGva+M0k+fQeetXMVkfndt+/JPnjHEWOD4/DMRYzOZCx4HPw9pnD/MiDG7LP08V6iueRbTTrJXzvnv/NFL7n2dt34o+Dt/LwCpGFOqFeGkd49VXfMsRna/oZRa/vHT8kfkQ+u5JznxP/xXIaRqZepJ8zDjkoUm9hn9iASCBXzWK+fKQEh4mZSHE2Nff1it3rkx5+DVq7KGGQiCju+ng7ANBNt9SYC72ELIVyLGLGNMlcWJLggWc442KkjMJM2enLrEmJoQqnh0/nkmUiF00jx9f7HINgG7/SOaRsdHzsswzs11k2TNKfkD4zajWhkXMXZGsJ4cHjGWBaHGHielM5BOjLlPD5g4RyEiJOAiXkolxiKOGEmSYzflBGPVYRS/rlQrefrDmucAIDdZM0DEWJCssRdAxkWM5TjHxmPPHlf51ZpJU8SYVK3kJ8Yimkc6gQ9rYcmQNRk7FKrvyy5Zoye3iZd2ePcbqG15FbM/ebH3m3v7HqsNM8VY412+K6s5Meb/zqHj0qaNPW6wADhIrpQnz/Mr6kCqNf8D7XncDLVi7CJ7cw40PMyEQiSwIiIimgYZszrwuWNcJgBG1SRl9udWyLQsDw9qTu+LX38YbVefbZEE2u52/qqrn0W9r4yZV51tHT+U1iXGEKgvN3jLPzXEGC+bnzN95sSYLtcpn85bunMFzlEwQo9NGCqrpWKMzlETfwGywiLGUs7NJRgimgWtSIZnEAKyPww9/2t0qJVzlzyEMA6l1sp5lyEoKb3N1STWyjl9Z5Wt65UwYmyFl4boKF5+8eur0c76Je/GXGkooIixA2XZ5x0Cih8nSRLtUtJ52zWY1DpVjQUhSTxKz97zWCu6DqzD8m5f27JLqRTOM79zso3XLPb5cYKvVMPplPJLrqQw96/EzwNYO7pOmjHNKc95D9UfzlHufU5adxdYW8XECmGEJtXNN84do8o5lhl7C825pdTdIsacOlqEtIDeKVGS0k7cK6fOuq0L8rlnk8DucUyeiCOEd40FKmufw/Qz340Zl5zu/87zCGD4VTLOL/LLdK6vJsYuXegvlui8pj9rYuyqs/nPfvnCIcbU2DO3VnecC0WMKVI6Y/xDOMRYxvgHZLgFPfZCC0JOf9buXE5bB3eBjnjLQESpJGuyQf3BigmVcp3qBUbWhAhKJ31YxRSGGXsXN0w7NsCIsTzxP9c4xFgGuFqz4U6JokFbx36uEQmsiIiIcUErfAM31NEDZfR/uxvtHznPIo1Ctn+SAOV7n8HUk+fJSQr7PjQFH93Xh9pWSYxpQsepE4dUrZztr2ToPCZTda0hxlyyxz3PUUaMTZnbLokof4FdnXdiEWMuOHGVJNIYG9xqiDG9i7Sw6wshJwAWMRYAN+gHHtsRTBPRANwIZa6YdOnqhTJKP92Crls/pOM90G9JID25GE1TZI3rdsqvWe0ZY5ybalBENTMQBXhg3POsWG88j4Ah0so/lSqm1ksX6uPzPibTKuk+kdKfX67rSxsPCHYkoUgqIsamkKIySXQqYZ1pgqpSjFGfT9jZucNqtFBRqpUPIWmdytSdtqsv1YsMvYhxgHfchLUvN87/cjk4OUtjhF80bpxP6nJIoyQx91e141tl9XMYqw1rA8Gyc4U9SiQx9hy6brVjrRBflFC5kH1TKwg1MSbMAZyHSPURxzjXN3q/jdyg1NrO5+fH0pfu3YJpp8xDqzLGXMWgYO8O/6YgibG/WK7Pw0roGIgDj8T7/LggWN8JPP+rjynjnKu5aZdC5zobJcXFATcq9lb1P02M0SIFpeHEUSLviUa1QsRYYi2GcWjjnBFj+n4s6H5tjmUpxjLGP0SKaiUw/qlND/3gCaXePd78Fhj/QrC2vupsu4s745/qUdv6KiKOBuz7m1QxHS0FoY3+uzc2TYy1X5MvDumhf8ogxjTU4sCaJomxZ/IRY6I2HrVmFjFmK9ZrW3c3LPN3FZHAioiIGBeylDzlexVZ4wTGDeUZINXKR85zfuFOdRL1giHGpgTIGrd8IsZaL0l/KJEhcJgrxqgGSargRhJjV0nSyHKbCqCyutcQYwG4LoyeYixQX4JLjBHx56lQIIMQDzwaDZtxIQFkDDLTspo0qY3IeGxX27tK2pHeTBD/qnbvW6RTeWWqtKN9FZR++owia8xW6olTF7rS5Fo7zR17Th2ABINbyZ3rPEYVkT1l0mli7NuGGNNkl5OO8hExJo0x9bswhBfVRcAde6qO2jYxdaZjFW/npLStEDPnCN3Ww7vfaOJCRxgIx3A0957RgtkxaoranMPkon/N3aey9jlMP+NdmHHpGfJbKksZrEaFKmT8D7ZyTiW5xrkQAmMDI9o41xtXKDKXR0WkulfXPIexgSHPQODnSO9HC2UMPLoDnZqUthPbdWHuXJqUNumtx0iSWKoVvg+vxReoV6nW7Eb7R8/Vrvv+Y8kQtqWfbsHhfQUvRURjCHZVEzYBSGDIGtkfplp9VmZmlKMADv2T7A9TT/o9RQ6Z8WSPjoQRY++zrj1YeiqYj73JXR26DkTU8k10gEQRY+9icY6oKKEJMfojYmzWn1xk1VenZ9DuXJeezmIQhse/gBx7ABFj6eNfQM71iAhJZkxLHf90nod+8AREdQQRRwOmlYee/3VzKqYmN42ZPLc9hayx73JcvZu0Tm1Y9sG7N6L1nDzEmAgrxlIw2peXGJPwXCkzEHSlDNQXMAtCHls9gRAJrIiIiKYhV8CkUsOYivJddY1RMTW6t9b7yigrsiZpnWZNyknFwb8jska7GCVJYCIvMbiViLHzvTRurnpfGQf/zlGMwV+FlXklMZYV74GXP/obWzEWAp/qFb/+MNquOhtTujrsMgNMGm9ro7IJLshbrpQRRwZm4gCQsd6mnyFXzt2rZBkfAEZokvK5FZahEjLS5YRQkjWTAvHYePlkIHAVk9117ZrJuFeyP0yaMc0znOG82sRY4kwv7feD2p3rPO8eEBp7/d/uRsdHz8OUuc7YgzuNlfeAaScb1Yq1Es8gwBRjf3KR93tEHnADlBu+hqyZevI8RrqaPLJPKtLoUa5aMUanMepNL6n3VXDoB49j1icvVkSpTe4CvPclqKx9FtPPfJfuD0RgJpoETXQeYyBcwuqaOH1eviNibMalp6ut1G23W34PEACqa8k4X8RWPXyVooDcSn3g0R3KtXa6+p0T06w9dVubBSGbLLSXKwYe3YmhF36N9g83jjEW4cNSyzJ3Z6MgNP2B331cQp/6g68oTazjSIKyJIkxy8XIvgsnWkGYOGPP9BxDppknSvXRHWrsLVKLAc4dns0XtGrlkxd5rrXW+FefSbXSeunpmeNfABhRpPSsP7kIWeNfLghxYqxD/xIa/wJCE2MzPrDQu54ReZA4Nza52CQXU7dgzueXY3JXmx1bkt931OfST5/B9DPehdZzTkl1ZaX0RIx1aGWr+U11ZD35JmLMdztNnDzyzybGnDT8fMGJsQ9hUotxa0+r/8FvEzE2P3hsXT6MetdTMgb+tFrzkxfZak1+rvwcFSmdZ+fq31VEAisiImJcEBDWarWAkEqKrUbFlE4vSRTvMComWYYBqVfoO07W6DqwlXZ+rHpBqVbUyrlrRAvnG1KMBbdSt+qktlJnxnnoHKn8eqGMfkaMufWw8/jEWEhBoN259tltre01lkaTWpBt3XZVupthRAMI/zonADMQmLsnmFHDLrrczvlxzPqTi/XqHXcb4oRpAunSOv3Md0vj3O/E1isRY3rXGmH6g+CfBSAUMdZ29dlmgwCnPP62QmNPB0u355kcnCjVQalZ2Tq5qg+R0tNY3Cs6f7MqL9/UGDHGi9VTadZ2nBibNLcDEc3DNsrle9s4X2TdY7jqg/KN9lW0iimZMd1KYxuiCSASHPqnx9F67imaGKOUvFzqewM09q5ZZP2m+yiNKyTMQGDuXKCxSmpAc54VNfZItcKPb2ol3xvj/GLdX9066/pVpVpzxqWna/WMbfTDOgYnQjQxp+vqk8EDj+5A51c+lGunxIg0ONcMCUr3bsH0M9S9mPVBX4EKDL3wa90f3N/ccSIG7P5gE2OMCFVGbHXtswCg1bu6LyRuXRLTH279kFYxmTHiLj8oYuycUzD15PlWHd3xnyBxxl76+BdIUC8wUnpuB1LHP0ycRf3cQ/r4B9yxlz3fjEiBcGfEsqVJxXTMcXP1d1bsEDXZEZDzoJFX37RiUrpxOmmeMVrgxJgT+49XAJK0Kf10iybGrKTa7zUBubcOvfAfatOYc01CNu8QwpwvudZKVXmbd3jez6hfTu5qV/EeBSPyeFvKufpoXxmVNc/quFfuXNDN4ynGhNN+TLHIF4QmMiKBFRERcYSQN1muYiL1EF/tc0kmImtaA2SNySthx72y/5NpeW0SFL/+ENqukqoV/9FsoxIgxnhZlpqqwIzz1ulsYhUGV4zxMkMY3Oob527d5fGENs6NYoxWUqk9hPWqY4zlkDFHpEFYJBCEivdALkYzpplrS0QUn/0IWMa5NTuC/54TYwnsclyyySbGOjxCjKvzABjjPCUIMV995Iox67zUnybFhCHGyL3Piu0GmBhxQr6vuApCVq5gdUoSSQZX1jwrSWnuUuIMQPpOE2NnxN3ajiZGtIuRce9Lw1h1GMU7HlaqlYA7tJOfjHN3J1VOShG4cT7JVe8GDmSNPSedm56Mc7cecOohQCvn0ji3FIReTpm3so4TY+kQYGPvTy62vg+9d9s6+6kXkQbXiE0g+8PIa2+g/aPnOVSOn6eulK1zPrci2Ofdflz66TO6P7i/udeQVCuzWH9wyXt6KxVjD2PGpadb/ZKnSVi26prw2AuBP/eyglITUXboB/7Yo9/d9h54bIdnnIfGP8Cee87Yi2gCgRuFEEKSNce2W2puIlLsa5HIZzO596nvqBx95RIzl5YqplNwzHHHmsMnjsJVZa0+thMjr76BDk2MGXLU6hWC4pA+gzmfX6EXjEnf5/afBEDpJ89g+lnvQus5J6fcrxOtfNSKsY+ahWvX/tB1Z8QYKefNWEu8fl9ZS4qxRXY9hHDGaYLRAyU1D8oXY+x3GZHAioiIGCcSy4A99M+Po/WcUzD9jOP1g0sapUKvgNDNmSYp7R8+X5WhpO0C0EoXIVcd630VSdZ8+DxM7mQPJb1qJG/vtBpSuvdpExBeJKq8xHnKyO9Hf9OHwa2vYvZfrlBpnJVXwcggUq1ctUitlHKSItHnQeWTcd521SJ28kzCr+thVCtdt16LpIWCEAv9O9WX2tUoxo4HREItwIiORJ+PdqVUbR2eCkY0RmK9k8E5H8bMS07XZI0bI4SjQgaCIkpDLqGEesE2ELLizQGucW4Sm8VS813IQAghSRxirKu9Yc8hYoxizlnB4BkplSTMnUtvxuCfpArRol0pZ1wiY63oxV9hCCsehsbajEF+26DmEUGwNk3g9we6/9MzgJO7EIqsOcMoKSzS0/lMAeFn/cnFtkHOCE1NllZNf5iiyBoh7DpwolUTY3xzjkB9IWzjfPKM6X46dr4YY2PvpHnpbjNUD5eUzkjL23oSd5sJ1F2wtp6h1JrxLn8EYP1+9IAkzju/8iHTd2B+t4h2ARz8djdazz0FU46bG+w7PL0mxj5ynt3fKZ3TH0o/lcQY9XlO4OtqqfTlew0xxu+TACPeVNphToy5/Qtm7CUw86AZ6rmXNf4hgPLqXgAwu9amjH899h7ZgS5OjAXGPx3TUmuyNo5oDnbXSzBMKqYP89iYxiOC1KoCJg6aJGs6QG6qxoPC7qCkYpp59ftYDRL2/DfkFHfv82+RJj2RVFLFdIpWjFlzeXZ+AlLFNLL7TbR/5Hw1lhL9m6VuFXLhunzvFk2MceKK8gqY+U7p3i2Yfua70XLOyVbahLUNVDsOqrFHC9f2Odl0+Vh1CMU7VFu7u+dOQEQCKyIiommYyU2iDMbnAAHMvGqRSaEnd4xAEpKQkm4O16pJipLHC/7QMDfmQ//8mCTGzjqelUMPVOjPSWJWzts/fL783VoiTVQ6+SW5983640skIcWf4nwyJOQD1VWt8IksX3UCEoy8th+DW1/FnM9dHmgDk04a5yPKvW8RJnXynYoSq3R6r10pr1zkTHZpFyJTG1qR4m0dJ3njgyYyhWzCCnfva4CR197A4FZ75ZwTNvwKEzFGBkII1s6Za55VY8+4MJpj2PnqaUGpAxBCkdLnnqJl7aGuQ98FV86126uN0QMliwjJ7JICjjuXAW8Heu8SYxFHCDJ+x4xxTkoK2eR85zXT4lZ/cIxLoYx9wmhfGaV/elyqVlifT5yOoRWE62z3PrdsDlcxFiqPQKqVmZcSKS2sdBY5BtkvAaRuzqHPI8kmpakbc8M+pBgz6U2bJ4nd1pzIjTgCCKNqMzu6mt/857/sDzwodZI414H1o3ofI8boZ4fE4vk4MWbHIoL1mfqDS4zxsjnZo1Urn7tcq5isejPySwhHMZYx/gFg+IVfm+dexvgXwjz3yK0dSB//QgCV1cyVko/PiHHAED2jTEE4xVFy8qc5/Vv6iewPrdbu2jZhRATPkEXW2DHT2FKIzDswjOLtD2sVU1bUzUTNiyfPbVeu1oYG42noXz32dDxYHl/NnCv9ETE25bi51vd2f5PPoYFHpWJMqjV911d+vvVCGeWfbsFspdbkZBhPR3UjN2a5YVO298dEQCSwIiIixo0EwMhr+1Hbuguz/uSShunFwDCKdzyEGZeckSsWU3UtGeeLELpb88nhaF8ZA4+9iM6vXKuN89Aknr4jYsw2xmzQjn7Vx3Zg6IVfSzVV6LzYxKpeKOPQPz2OWX9yiSKkQhlM+uq6XkOMNcDIa2+gtnUXZv/l5V493bqMqbaWirEorz9S8OkQNxhDk2b+Xb3gqFYC4JOnVLKGp1cXWfaHVzFL7Vrjxj7j7z3FWOa52sSYm5YfhyaEWS4lbn4ixkLGuQu+bb1XLovdIYR0rS39U4gYi6bNkUAAqK5TBoIVg9AmYuk9GQhdgc05eJlECFmqFbD7Kfz78oC6F2tX6wymhu7Fsxkx5taFfy7f94ylIARskpTzcEPKOJ8dIMbcY2hiLIWUdk+hstYmpV3TzdoNss8npROn3hHjA/WHlqWnBJeTCEJIskYGpT6vIYmoibGPnJfL9a1KxFjaLsbsWluKsQZIwMdeV2q9hTrGwGM7MLL7DTb2wuMfMHFI53xuRXjHaNhtScRYCwUAR3j8AyrGmCLGrOM3POOIRih+/WHZH94511FmGSTqu+qaZ2V/+Ki/WQuHACdKV3j3wFBe6g9EjIXS0P04pGIKcMAA5P2y+HWflNaLE855EjGmSelAmbxsToyltYlQ/xy8W469Y9451/4tAO7GHDqviYhIYEVERIwbcktZSdbkIUkq63qlm0MGWSMn38DwbkmMzc4gxrSLVM0nxsJrNRKSGEuYYiyd7JIGwotMxZQNTYyd1Ng4H2hAjHFIY+wxpRhzJgB8NVg1SmVt47aOaA4JErZ6d60Kzumu9dmTClu1km1UVh8zsXdCZdobFbjufUauz2On0XuuGPPjsDkr57ttYoyfPy9TQCiilLuUNDjHNYyUDpTNY0tI1cqLDjHmk3METozxcqIpf2QY0sb5+Q3TigFjnLs7ZxJoLVzAGOdpMQj5YHJVK5pUCCjxuDuXcSmxyWIOUq10fMQxEAJKSbly/gxmf24FUwewPE7ZJebOlQUBRox98hLre3/FH9qda+alp2MKI2yFU++IJqCazVIxwTdWObiKKa3Pc1B/aGVkTRqIrAnt6KqrTEpBNvZyzcfWhIkxvrs0gWLv5N3F+OC3N1iktFU+uNIEHjFm0tnjn56/NPaIGNNjPlfNIlwk6gZTXf0spp48z1fNqvdcgVrvK6O25VX5bIb5PWHp+V/x9oet/uCm42VoYkz1B542YXWixbMyJ8Z4ebDLhpB9vvXcU9Cy9BSrbOGcK4TcNIaIMcHTBdqmTsQYjb1AG/A/rRi76myvDdy/uuPG7LXbBEUksCIiIpoG3bsP/cs4yJqr08kaWtkZPVBG6Z8fx6w/viRzQmhcOXyyhk/2+PuR3aQY81fOvbrUhlH8m4cw01GMpT00KmvDxnkIdaYYSyPG+HEkMXZqpmpFupaIXG0d0RyEAMYGhoIGApFL7oRbr97x/qAnP7aughvnk1qng8d4oDweMcZ3jBLcxE3U5EZ+1oqxq+TOVYLSgNII/b6uSWlXMWbK5uaNdue65HRVtruGadpkRBNjlwBOOis2hBBqdy5SrXR47aXPme4BlisluTAIdr4R4wE3GCd1tVm/hchKMs5b3B2jGOjacOM8BMF6k6jaxjn12kT1A953yOU7jRjjdRKwDYRQXyEDmYwYTozRL+6GHwROhDTqh9wYc9ua1xnqvDURcsnpXtlRgDVOJPZujuEkXPLMVCvHdTUsvrrm2dT+4F6yeqFiG+dpdVAwxNipqWkIWcQYV7YmSCfG0sq3jHOkj395jq47F09nP00EBA7+nVoQUu5c7viPaB4CchOh2tZXDXnFf9QwC0va3ZPIGsCOCcdQWSOJMVe9a9VByHvWKCPGeJn09Kd7MP1mxt5crzwe+y1JDDHm1sMshJj8vF9O7mq33Fnt0CTmHFvPPcV67qWhptrae+45bUKu58Gxl5hzm6iIBFZERETTIAMBIsmtHmpE1gAuMWbImqzJCZE1M3OQNfVCGYcUMdZohVLAEGOtjoqJJk4cw7v3Y7AZV8q/cRVj/jkSJVH1XErC7UFuVHnaOqJ5lO59RsYgWHqqmoUngclbAojEGAgfPt/EeOPElV5FS5iBcL6Jx0YbEAgyoBP9fXXNc8pAsDcI4HWiODn1vooyzlV/sFbwWPw59f7g3yli7KT5rA6yTD4hhEgwoNz7Zl5FW7rDy0N1q/dVjFqzsx18owFeF2pDM/bOCKxMqjyqXUZ2U4yxS2A2gYBTh4jxgAxGs5W6ITLdXVIHHttpqVaywImx1FhvjGQt3WcTY75RbEjYwRd+hdpWoxhz75fWDlLVYRT/xjYQ+DkCsNRMrmLMdEvX3HZWzhtBmLZ2jbHQ/b762IvZbS38PBGNUT9QkTEplXEe6jv8tbr2WUxzjHNKaeeRiwO1ra8yBaGdxiIohdxNWY69Y3V5Jji2DZsYk7+Gd2BOfNVK4PwIghGlLeeckjn+EyQNSWmrbKUgTFOMeW3NiLG08R/RPFyyJq0lJVFoyJrWc0+V8dLU76E7zuDWVzFIxJiDxHkl9z5NjNHvSRJ8jFfXhMcerwflGaWxFyRK6fzMd5oYU/WwzlHPyUw9XGLMXmozqBfKqKq2nuKQwe7SnxCsrc8xijGa2wmE23yiIBJYERERTWPohV8psubihtOGYNyrjEwV7d7Ht1FWK2zCnmARWdP1lZW5tpR1415lwVMxZdS53mcUY1PUDoVBqPpXAnGv0iZgQ6QY++NLjNHF2sMqPkCMRRwdDG59Vcnaz7e+T4yASX4GczH6y8tzXQdtICwNr97xidXQC79CbesutVFBOqRiTI49SYzlj7WSpSCkukjFWK8Vcy5rjBz8uw2+WjMl/cDj9tijFVTAUZYIO+ZcWpyjiPHB6g9EcgLm3iPMe0nW9KLrK9faJCYnVomwHEs0UXrM/LkwpK78S2AIVYiEkTXnO8Qxr4/8G+0rSeOcxp4mXk2ddewewYixpadYRK6sj7Dqxklp+/zNudJxDDF2viJsWRtwAlu9r6qt1GdeuchrM04yQySGGPvyh2yS1mqXaNA3DSFQWduL1nNOQcs5cpFCANb15ffi2happDALCYnVz6D7sVxYksTYIkzu7JAGK09HxwFtGtMrjfMrz9ZKUzJytWpELw4o4/zL12qyTPdLOH8CKN7xsAxKPX+uU2e/HtU1vfK59+HzM8c/YMbe7L+8HJM7O9LHv/ozxNip1m/u+BeCKcY+fF76+I8YF4isyeVlwMgaIYQ1Htw7Do+F6BOljDhSn1NVTEIYN1H1yhVjjUIieIqxBqgyxZhPlKry2TyIE2Nmjm7noRoZYqwjhV42bVNdK0lpqocZ/6Y9JvJkJxJYERERTWOsNiwNhE7m6w2wiTT0BKN079PSve/i0xukZcTYH1/slWN2hJKTOU7WTOpssyeOgb/K2mcxqXU6270vPX29r4zK2l45IWxhxBjLxyeVB/9+A1qX0lbqIr0ekCvnQy/8Gm1XLgr8bhs3nBgzK2M0kRa6TnTuOsaYauvUNoloGvVCGZ1fudb7PhTwlsiaYwLxP1wMPL7DGAg56lC+lxnngOcqxD+X73s6kxgDzPwnLzEGQLvWNiLGqOw8xBiBE2MJC0qdFmCY2noaI6Unsqz+aGJsYBjtHz7fniML3r7yl3qhIsmaD5/vuTnYBrp8MQHhOVnDDsHea9faL18r72m6g9uEFJVPxJiOtULuf/z+qvIPPK7c+z58vh44/s618j2R0mbs+YQGP45FjPHjBu710jhnYy/QZrr8AUaMdXXoneCARP6v4wFNYMvmCCBqI2zTmMS2PgX0Dn2jfWVU1z6Lrq9cy/oD72dg1y4xxJi6F1tjSPVhcguqbdlliDGrz5ICwxzHIsa62jUppkl/59lfXUvGuVHN8jrzsUSqla5b2XMvMP6ThBFjXK2ZMv4BZZxrYsz+zY7paS8ITZnbYbWbO/4jmkWC1nNO8VRMoaYc/U2fJmsakUaA6Q+hMCBu+ZWAiomXzef/fBfBSV3t4OEHZNl26SFiLO3+WOOulIEzo1ijApyUNsRY2sKBgO1K6aYz5yBJKh1jzFHvagUm3+lggiISWBEREU2jZalavQPMjD9wIx2glXPHKHZ3SEoS6WJUvvcZzP4LbpwnanLkr8BYxBi/oQfKH37x1xjcugvtN7J6pFi5Y2Scc2OMJ3XyVdb25jfOC5IY6/rKyrB7nxNEgBNj1u98BQbyoa5VK1Zg+gn8dDvKmHmVv3oXmgLJ2Dsd+fuDImvSwK8zkTXcxSgYSwIsMG4jpRaUO5dDjLnH5qCxx3fnSis7RIz5U19lPDljjxy9BEvD83JizDJ6vPIjxoP2D59njGIGd9dTo1qxg1KHbj+DW3dZ/SEtVlMCtXLuEKWhMqmfSmLMjL1QTBY6XJ025/iyGnsOQUpkAv0WGnte3VVeixhrgBApbZ+b/bl0nxl7vL50fCFgxWuJaAJJgtl/ucL/3u3TAije8RBazwkb5y4qSknRdvViOkwQQqhdBNdKl+/QZi06tk9CZdvEmJueg8Ze3rAPtIuxu5uyO/6FYK6UV2ZvjENl17bukosUGeOfyqC2Pua4uZnjP97pxwMR3DQG+umb6MXU/r/rRrty9+Qu21QOR/neZ0zcK+8eTKSszDu6r88nSnUNEuf5n2hizHg72IpTfi7GvY+FOQAnmsx39T7l3veVD9mkNEvHj1NZaweED/c/oxgbTFWMmTqlEWP8d5ewm6iIBFZERETT0DF5AFhuFuyPyBppINgPLHs1XJJPB/9+PVqX8ngPfHXbuHUI4RoI7uTFkFlJIutRuvdpzPkL10Cw60Tfle/lBkISSGv+hl5UxvmN73dbyHm1iTF7Qhguu6JVCoudOvL2kOBtLYmxhF0j+/ziJO/owZ1Ly0nKLunmkAEKll684yFPteIdQ13oytpAQPgUjJKCMIUYc3vAwb/fgNZzTg0EQvWtBa0YU66UWbZyGjHm5qFJoSbGdJwjI38wcV0kshRjZmqaWJ8jmkSKdcm7hXFzyEvg28a5Joz4YaFWrJVx3pqhIJRlCOVS0njsEWFb/BtpnKeNPRLSApIYm/LOud45hoxpvXPmlzNIaVYZMs5Du7W5xzAB4c9PLVsVG3GUYRHn67iKKRv1vjIGt+5C55evZSqSlGMIoPg3sj80jNEpDDEWqoe7k2Bo7Nnp7c+clA4dm4OIsbztUbzjIVsxhvD4B4gYm9/ArT1KsMYPtvlEIOYlKejK9z4j+8OZxwfSMJdVkWBwy6sYev7X2u1ULkKbP12ukDE6+7/djXaaF7vpFOg4pZ8+rYlS7VqtzgPqM30/+puCijl3rVH5icQ7T3pPrrUyDqn9W8LbB4khxrTLd5Javtmg51pM7uzwXMK56yzFF5ak9KnBdHr+Lyb2BjWRwIqIiDgChAkRW0nREchjo6JXzhf7ZTl36HqhpMialZBETahsUy+pYjoVU4471vstsfIlGHicFGPvd8ryUS+UlHF+heVSEiLUbGLsVK8eLoZe/JVSjHFiTKa3p6UJxmojTltzktDOCwADj78YPGZEk3DmzJpEdFxKglmFQGVd+sq5i9rWXYoYO99MWPTk0gYZ55oY89ki+ZWQvamqFWNn2+cFwF3l4+59aWk4JDGWbpxzmK3Uz3fq6p8kV62kxpxj2WpbdzU8fkQA2ri0rzF90kqKDLKGl0VkTciAdoREFjGWNUlPEBp7TprEvm/S2Gu1XErCIGIsl2qlz6hWMklpXY/miJCBx7KJMY6BR+N9fjxI6wd0zWqOiinr/kcKQrc/pOUoB/qDv3SV6LIHM8Ye30nQjL1TU3cR9Ejp3YYYSxv/AIVbSCfGXKQ999zxD5ixl7aTKK9Lva+M2rZXGx4/wkdIqQoYUrO69lnU+8pa6Wzm3Gb+Ldg8qHTvM1ZszCxHgPK9T6P1nFMw/cx3e8fVeVX+wa27MPTCr201N7GdelHc1KP/7zagPSPMgRVu4d6nMfXkeak7d/Nz0K6USkHYaMdXQ4yFwz7wY5TX2KR0MEQEa+vhF36dffDfYUQCKyIiomk08kwr3fuUQ9akw5A15zdMG3Lvy6qLdO9Ld+fiWY2KaWXDegCMGJufM86RJsZsuM8yaZw/jTl/cUWqocfzlJ22znqWDr34Kww8Fg2bcUE4f7BfLQNBwEg4An/VdXz1LpzGrFDKWCudX77WizlHsUf4X2VtL1qXKgPBJTGdeg9sfUUpCM/zLQhhv7eIsc52XZ4b803HYyNi7EonzlHKOWq1ZrCN7fwH/0661k6ZP1eTcV47QtZt4LEdqD22I+2qRmTC7ejmU16yhlBd11hJQZCBcfMSY0kmMQaQMS/PoRIgxkK7ulE9sogxF9o4z7GVOqk1cxNjQSIkfLevrn0Wh/cXGpYb4SNralM/IIlzS0GYkYOMc7c/8Bx0DdP6g7/+IDLHXohsMooxN86RsNIBbOxZ6l1//BPyKsYAnxjLQv6xJ2teWdcLMTDcsNyIJiDIvW8XZv/l5bqP6E0E4M+/Q/0ybU5aYcSYddiUhTkixnj4jbT5vybGzmDEmHt6DjHWQTtGZ0C6Um7QNkga+cfr4ZLSbow3wui+Po+UDoaIUCRW8Y6HMFabuH0+ElgRERFNw3oQOEqQyrpen6xJucFLFyObrDFyZv+YvoopUB8F4953fsPzkcTYKnR8+P0Nt3QH5DlO7goQY6EHb6GMytqeVGLMzSJdKX13Lp6Q3oaIsbRnKSfGIsaJlFgbUkkxHzOv9OM9uGhKtQIyEE4Nk5nO7Ka6zhjnVvwqRaiZnWuka60mxrxYb6TiM+VbxJj80amNyTO4zSjGTFpWH1Y3HeeI4l6FlidV3ZPEca3l8fG8djduzLP/4nK/zIgcIJISHsHpEaUZf5ZqJS2dKtcja9KIY/VXXtcriTEiSvnzw+HftDvXX11r/SYgvPSJSOTYW3qKIY7h9DNWD8uVMqWuHmH7FUZKp6SFcFQr7HtNHuurlZi2vjJdtRKRgZRrl4gExW+ofuleMzev6g/1QtlfpNB5Et336gdkmAO9SJFRDwi5OYcmxlzS3rwBAAy4ca/cMtV7AWfssXqExj+5Oumxl3UPAKlWdvmLFKHzBCPGOtvT06kxQMTYjEvOQMTRw6ijYnK7uovyvdK9j3bXTlLSJjBkzRxGjAFIjbtZ/JuH0J6yWOLmSCXGAuWmEWPeMVS9aOxNOzOdGCNwYiwNXLnW/3cb0N4gpATlKd8nibE8iyW/q4gEVkRExPjAJxTqDm4MhJX2pCNBcAJS/MYqo2IKTcr5pG1tL0Ze2y/d6pzJj4mjYHzOy/c+jTl/foU/AQr8aWJsSboxRvWinRLbbzw/exImoHaMYsRYoNyE5amsZcSYW65TtjSCekxbM3i7DyKDGIvIhcQyXqlTJxjcplbOtQGNwKt877uU+C6vPF+VE2OB33leQ4xJ11o3zpz8TtVbwBjn3mSJBqupU2VdWqwV321Wx1r58kpM7myTLcd177odZT5JhJyqY84Z0sw+RyGYKyWR0lZMmQQ8mG+9UMpwY47IB2HIRqb2q657FqP7++z+wOIiJg5BSUTppM62zEMBLlEaIjPlsZIkQU2NvZlXnq3JTDikDr0PqpiEncaqBxFjVy0ybcB3ftJ9mJHSnBhzy2XfaVKax0IMpQUbe1dmqFYEAJFgtK9k2jqHIiYiA871KN37FKaePE9tGuOkcZ7TWrXy55I4T8D8jHQe+cYixvQ1sxcf+HiqrjPEmKW2YjEvtZuhVoytlK7WauwE+6gyiu1FCgTHP5JE34vbbjzPOb5PQtT7yuj/+wbGOatTRe+U6IeU4OMfMG3d+ZWVcdOao4yQiimEBGH3PvMkt/sDEWMdHz5f7SJoELqGkhibj9ZLTvd+o+NQzydibPZf5lu0ahQLkddrvMTYpNbpqeVS24RcKU0aG7UcxNhEQCSwIiIijhyKUCl+YxXarlycYhTb76vrejH1pPnZE3OFeqGMwW270PXl6/wf2WSGHn6aGCOyJmAHmZ2rGDGWox7l+57G7D8Pu/eZwuUL7RjVuvTUVANFqAnq0Iu/wuA2RoxZiZyPtWEUv7EKHTc6OyVyss2cqCHGaKU0onkk/I0xXMnt1Dc+fHLKkDWnBtLJ9zShqW1TsXc8Ysx/nxZrJe0kqto4pw0CfCKKUC9UlKx9ZUpaG5IYO9Um6BhhxXORWtPeISj9HE1bd1i/65VeRirYbR0xPiQ2aaMMBG6cU7pEJ7K3+C7+zUOYcckZOZ8JRIwpw9XbIAT6+9EDJZRJtdLVbuoZHFfKQFiaM+bcNhWUWqtn3Jum0RZkjz27DkmSoLpeGeeeQkr1ZUZE6DhHf3Wtk87Oo6rCxl4kbI8cpp0Ht72KoRd/jY4bz4d7Td089QIna9h1sPqQ6aOle5/CtJPnO8SYvYBA4+mwHntXWN/rPOpPLrZJYqz9qkWY3NnGFi/CE4DqOmmcy50S2Rhyxj+QoN5X0oqxSbRpjE6UOCREoseeTYSEFmQMKd1x4/mZ418IodtaurVnkOMRTSONrAlhlMVB81RMgcXV8k+fRus5p1oqpjQMbn1VEWPneUQYlUffj/aVcquYEtUvp5JiLLSYwc7h8G9yEmMqf5ZizE4ujFrzqvD8nO9RwN2Yk5ZpwTaZKIgEVkRExFFBZR1XUjhwJlq1bbtQ20bGeTbqBUOMBVfw9YRNfgwSY8K/ydMEqLZNKcYU0iTMgCHGjmmkYhI2MeauKvFjJIlcOS/f9zQ6/2ql/cALRnCUxFhe43xw6yuGGIs4qij+zSpG1mTDJmvSIUCqFZcYSzedKmt78vcH1zjPgDTOV2njvNFUyVKtMIQW/E0Q4nwx57La2p3z5W3riDzgJGLJMc65kQ1Yhi8SlO97RhnnZ8A2RH2CctQxzhPXaOXpLdVKR0q5Jn113bOoF8sphK39RztnmrEXSsfO8d6nHVI67Ry5e98i7zcCdykxxJg8R64wdAmA6np77E1cs+bIYO2wrPoDkTXGOE8n/Mv0bD7jeP2bq4aVlzFBbdsuDL34a/ZstsuldESMHbRUTNn9uHzfU5h68ny0Xnx6oK723+i+ghx7f3GFtfOznd7A7ZdAePzLsderjHN37LllJ2pjnKfR+eWVSrWSMv6dsTftjONhj4+IpiDsv5Hdbxiyhn3vKfsFMDYwbBYpXFdr4j5ZnMzyWtUfKNxCxh+5Wnd9ZSWSlmlevE1arJV/wKF/fgyt55wqidIG9a4+9qKvYiK1o1sPNfY6+NhzCS92vuWfKsXYxaebBeWU+pBr7ew/v9wrK3GOk4CT0lFhGwmsiIiII0ZFkTUzryTJd8j4kKgXyqiu6/XJGg0zoZExb9KMc0YCqfeDQWIsARcz83qEFGNpMvRKqmLMP88QMcbBjyGE0MSY1x6BCI6mrRc1nLDVC2VUMts6Ii/cSyFX73IEpRZy5fxokDVezxRAdW1v2MUosKJogqWv9Akpt3DBVExLTrWShHodxb2yiePw+RlizFFrOnWmcV1d14tpJ6W3Na9Ps8RYRDrc60wG43RtnKdjcNsuDL34q4bEeQLYSgodHDsd5fvl2JPEWHbdXWIsEwIBd650VNf1KmIsX1DqkjLOueGfhvK9T3nPvTQPqRApHb2pxgfebmMDwwGi1IWZrxiyJnvnTCFMmIPOL69UxFhokc28D429tB5ExFhjxRiNvfVB1UooJ7lzZY09glaMZcTd5MfgSsZG3bfC2jriaEESpYf++THM+uNLnB1+jbLOcmld24vpZ7xbKQhtUt3FyGuKGPuLyzPSKUJU7a4945IzMKmzzZvruovA1XXPAkg8ZWuSMEWgylMvqB1dv6KIUka+hub/h/75MbQuPQXTNDHGVImOS+7A4zsUKX2eVw6BjmGrNfnYC9eldB+5Up7hn9sERCSwIiIijgCJdu+TZE1gOcJBKlmjYfKV1/YEjPPESyeUK4dN1rjpEiuPIca4YkytfDoP1dq2XRgMEmNUpiHs6kUixvIbQdNyuVK6bZ1OtlF9wm0dVynHgwTQ3bq2VRrnHTecb6/WgbUurd4Vyzj49+vRfuP5ueOxaaK0QdrD+/psotSpi/ta/MYqzGQrpSKUnlYoGVHq/iacsi1izNkpMVRvrRhzY87xciH7N6lWLHm9Ux6dhybGrgwEAI9oGrzZKuMka7IC49IxbCVFNmrbdmHohV8p4zz9biaQbZyHIAPj5jPO04ixYH2EHHtvPTHG1JpRjTJuUMtV15Fx7vcHt3VHXtuP2tZdmJODKBUDw0elP4Ruaz4xlg0iSkOktFt+TZHSbTnU3FK10njs0TGaJcYGFTHGr8MEtuWPEGb+SmTN1JPmG7dTZxGY1HZE1pgQAIzYscqGRYzZIQAEzGgyr5W1fOz5Kkau+BvaLcferD++xDuuFVNTQIbf0IqxNlaOqQd349bEmD5HUlGq96yNNDGm1ZphlabMl6i2PpW51vptTa8Dj+/A0Au/YjtGJ2o3yIl7n48EVkRERNNQ6zAyULJWMfGHkisVl9/7ZE1I/m7KHrRUTPSgEFaZPlnT4aT3JevVdVy14qcRsB9KUjF2XUpsEZso82PvuKtS5jjkShkm6Ozzs9vadSGA8ypQXdcTUIxN3Ifd0QLFQev8q4CBwEkhhbdCtUL1OPid9Wi/0dk5M+USEzHWelFO4zxDQRgixlqXnppL1l5d14vRfX2NCVvhqDU72/3h78BSrURj5sih+vIoxf8g4zyrbYmsCZGIQTKzF/VCKTs+HxGUAePcIlOd955xnpIOUEGIOSntpmN1lkGpA6Q0/PEPKGLspPmYwcdeChlrEWOhNuN5xlhb853xAucXkRPqHj7w2IuSrLlqcfBacRNTG+d/dCkmpS1SMFQ4MeaW7RxnZPcbPlHqkv3U96qSGGtPG3tO/op25/IXS/iCjTv2JrXkIcbUc+/04xveA2jstd9wfrgwVv96nyTGOtRzzxv/EeNGdV0vJFnDPSnA3nMPhpIia1Zi8ozpwTR8TkpkzdST5nu/uccaeFyOvWAQfwf1QhklTYzxeTGvjym7svZZixgL1ZU4LyKlJTFmT6ysjaPgEGOeWtOtD1BdT23t7J7rpKO5/8BjL6LryyuROAHhJ3LXjwRWRETE+CBUvIclpxmDkcea0pMrudowuO0V6d53w/nQN2h3UqVWFjRZc8Vi8zAQ7CEg6M/UY+pJ8zHzisWsHklwsnR43wFlnF9nlWFPHs33xW+sQuuS09iEMEnJlxj3visWs3qG8shz1MRYZ4dJQ+fI6w9FjC05TbpzicQ7NrUdhAoAvm0X2q5k9XDbO6IpUNM1q67TxnkA7m5tpfso/kcOA+G+p5zVO6eiDESMdeQkxvq/YwyExvV42myl3gCj+yUxluVSwlH8xirMuJgFAKc+HoB2KclRj4j8oP5gkTWAMnLNfYjel+97GtPPOB4zLzlTp01TA43u68Og2x88QzrR33tkDf0lgHV/EynGOS+fva8fMGNPk9J0bMdFJEkSHefII6UDzzNNjOmdM006d/VcK8aorUNgxyjfr4ixi8+w11EEIOLNftyoF8oYePxFuUjRYvqDBWrnMeDQPz+qjPN55ne3y6v0A4/tkMTYlWqukrYroKrHoX95FLP+6JKwshX2+Kisl8RYK1cx8Xqw/MO798uxx4kxPn1j9aBNY/TYU2WFxj+E/9zLUgPq5x4tCKWNf3VMGnvTeJwjGv8R48bwayEVUxhjFlnT3lD5VlnHyZrsK2VUTPnmQT4xlo5miTGpGLs0l4LQVoxlg7d1o17LY4yFdpadyL0+ElgRERHNQwCV9T1ykhJyc3AmWfUiTVKuMz7nIYNCffaJsZS0IOP8dbTf8H574SLwUK0XSka1EjIQnDxkIATVAc7EcHR/n1KMXZd6fA5NjLn1cImxBKiu68HInv3Zba3eS2KsRxFj7d61iHbN+EFkzYyLz3R+8acR5N5nDAQ/DXcB9QyEDBiyJm0iZiTunBizgxCHQcTYtDPenZkOYC4l1sq5nydJknzGuVUPZpxb8DuwTYRM5CndUYZIcOhfHvPJGmfXV0BelYEndmjVivubC48YS6uCKqd8/9PpBoKAZXHr/tDInUuRB8W/JVK6Q33Nzs+xziprezJJaesc+0Jjzz83giGlx6HWdBp5IruWHAnGBkZ84jwDWkmRFoOQQRJjL9jq3TTrXwCH/uVR2zgPXFLqQ9Kd61fmmZDxvK8Xyij9y2OSGAvFIHQgFWPHm7GXMv6RyDhHrmIsbcphEWMpbc2PUUlbEHLGf0Rz8FVM2aimkTWBS0AB4TkxZiVjHyRZo8ZeDgI/kxhz6uIRY6mdUr5oUvrEeSkJDYgYa2tEjAnW1mrsNeq1WW7MEx2RwIqIiGgaRNbM/rMrnVUwBB8MxW88iLYrAsa5OyFLEkWMOUoKS1Gb6O/qhRJK9z+Frr+6zjyUMp4I5fslMTb99HQDgYyXGifGQrBWSkvo/846tN+QQowF6jE1Iyg1h3bn+h/X5SKfin+bQoxFHBEGLbKGd3gf5N5nq5j4xbPzlu97GtM8ssaX1gMq/oc2ztNnYUIIJGhMjHFDN03FFDKGuSvlJCsIsV8nIUSKcW6XSzvP1TzFmHEFSJx2MUTI+6WSMdgm0ZgfD6rrewAgYDAydl2h3lfCwGMvoPOvrkPSMjUlvcojECDG0q5Roo3ztlTCVqUkovQ76zHrj7JXzmU9hCLGlHGu6inc+ipoBaFHjAXI6YFhQ4x5Y89PX21CQaiJsb9KVylEc34cEALV9T02WZOBkdfeQG3bLsz6o8aqFYp7NePiMzBlriRKvV2GGQwxxvp8ykXlxFhD1UqIGNPw66ONc2tzDn/8QwjU+5hizCLGwuPJcqXMGP+ACgDegJSOd/nx4eDfr1dkzXyEduzj35Fr7UxSEAYWoLWytS9FQeiq65hyb/oZ78YMFaQ8pMKjXQKHX/yVJMb+6BJdP8GPz94LlxhzF8R5nZIE1bUOKR1Ix89x4DGm1sxIC3C15vyGZWs3ZretQ+0+AREJrIiIiKYx8tp+38Uo5WZq3Bxc1Yqf5/BvDoQnKZwkYzuAFP92FdquWCTjTjRAdX22O5c+lJAB4cv3P6UUYzncuYgYyxuEmIixBg8gbZzfkNOd6/6nVYyxxhLpiOZweN8BZSDw7b0T/z0zzml7b9t9006vjXPuWuv5fRg1lR33yk0Lq4ySJsbODJQt39OkzybGbHdWESjbrJx3sPNLgn+2YowfX1jpBCQZXFZqzSSwlbo9ZJQ71xKXCAm1S0SzGKsNNzDO5fUbY8b55K42hMlXuiZCGeeSGEvY96E89UKJqVbs+B82EogxwYzzefp7+/im7ka1kvVMEKCx1//3IWIsVPdEu3M1Q4TYz71w/x3jxFjqLr5RfzVe1AtlZ7OWEBLm3teIKJXg/UETpJ5qyJA1hhjLniQIa+yFngn2/bASIsZMadYny5UyOA+yF3LouTf1pOOs87HrIfMYUnoJssY/IHK2dTLR7flxY8pxx+p7oLcxENvpTm+UZMW9Ugg0/sHvrM907+PHIqK0/UZ/XiyVsACQ6Pl56d6nMecvrlAujMYmCKF0X4Z618HgC6/nJqXHau7Yy4ZWjHFijIN1/cZjL1zEREIksCIiIppG60VnYFqGiolA7n0daSomhnqhjIP/0EDFxO7WmcSYA7ly/opUjAVhT/eLf/ugjL+Vx51LKcYayoehjPOmiLGnHOM8vc5EjLXd8H5M7MfaW4MOUvhkrbAJtXIuYFYoNRiRpVfvlHH+P5hrLUH4eQ79y2NGQUgEkwBMjDO2Uvr4i76CMLR6J9ROiUSU0jmy9AlgygZ37zvTIZf94xzed8BXa1qx4ex8MvZdIM6RlU7mM7FWnLa2jpPYv0XkhiRKO9SnNMNYElJStXKm8zs3cOVFcVUrdqwm3okAMTDEDAReD/5q3qe6c6nf+b+2aoWI0pRzFIIZ5y4x5p5jYmKtaMLWrbM5RyvOUWoQYvscTVv7bRA7+xEgSTD7zy93dhALtLEQzDifp35JX0zw3Puc3837LLLG7UNqcWC9494XlGbI74Zfk3GvfOPcH1Pk3jezITEm+7w0zrlaMzz+fVJ6qlOmeyNP2NibH6xrXKw4MmSSNUIgSRJN1nSo8Bt8F0AJ5z61rheT53bkU5SyHcQzoYgqGntT5s8NJLL7wsDjL2Lktf2SGEtDYp4J5fuexuw/vyJlwyYbFO9xxsVnNNz1dejFXwXGnpNHdf0xj5T208ZdZiOBFRERMS40njzUC2WUFFmTK/bO/U9lqJjCZE2qex/LI1VM6xqomMykSRJjx+XfznnbLsz+syv8lasApGKsGWIsSzFmG0Hl+59SREhjYiyieQg+F3ehvh/Zo4zzP77UJ3MAa24+VpNKihkXneErGQN5tTsXdzv1CC8JYyBcZwfGZXXleTQxlqIg5B4jRIx1kILQtZudehz8zgYz9rLaT2SQ0oE6y80YHFLa5UIijhwu0ehsCKGN8yso9o6TlhGJlnFOG1e4BqkmHZVxfjojxvT1ddJC7RhFBgIrg/cJof4ZU7u1zbjoDOV2Cqf/mnIBpVrRpHRinxevi2Wcu6S0k0ckwBgzzk88zmpXm7hN7La23Mr49TB1izTWeMGvKfuOXfPK+l5M7uowBKVIzO6TTt+rHyihomJSTmqZ7vdNZ5xI4/w0TD1xfqAfs7Ei4BOlejwkdr8QiXQ7/ZfHMOsPL2WLFG7fMfWnuFetF52ZOf6BhBFjl2aOfyAxijE99tLHP0SC6jpyY15sHdNKG/GWQoYAkGRNy9JT6FukTQCGXvwVatt2BXaV9K+VRYwFCVv+Xu4gLsdePpVkmBhziSObGDvmuLnsfML9yxBj56si0u+4NjHGzzGcJxzv0Z7ciMwJ6cRAJLAiIiLGBz0BEs5km9wclIppjlq9E4BmAQStWEqYuFfM1xusTD0jT2yyhnzOnYkdv9dbxJhTT+sYwhBjeit11yhn3/mKscDEV6dPpHF+4nx762y4k0GZXgchJtWKN6G238u2Zltnh9pClVPbtgsR44C7WxSHICXFI8o4bxDrDUpJcbqrWgljWBvnl6bXgaoyOIzi3z6kDITGGxVU0uIcBaAVY0SMuQvmDg7962O2gpCltVYQBTDwREAxFqpzIkmCg/+wIUxKB4i04R2/anhuEQFk9HfAVRBOs+2ZAIgotVxKQvdkUH9w4n+46SGPV+8r2cRYqA4sT3XDs7ZiLHSfV68jZJz/sTP2uN2mvhcWMdZupw+8r25QY++KQOBtzu3BaeuWaV57ufmGX4h9flxImx8okJJCuzpxO9e5ZmMDwyh+06hWPDjpq+t7pHF+xSLzO39ldav3cWJsmt+/+L1ZAAf/QRFjobEHWPlp7Ol+6YLlqfeVUPqXRxUx1mCRAmCKMTb2AuMfAEb2BJ57gfFPc87BOLcZJ9yLZne8gcd3WGSNnc6+aGGyhnfgRH0jO3/5vqcw/Yx3yw2bQitV7P3Qi9K9L1wPuz5jtaEUYoyXzWwQixhLq0eiz5FcKe3fnAGtYBNjbr3dtiZi7ALnN79O9UIJI6/t9443URAJrIiIiHGAZuzCm3QAzDi/6AyTDlAkgDBfiQTDFJzzz65w0gUONzAUVjFRPYSQedVxKut6UO8ryQlhyBhj39ULZbl73/+4zmydzdM49dHEGLlS0o5VoQnh4y8w45yRUdYuV4kmQvq/sw7t1zP3HSqX2oUdo3yfIsYuOtOkQeK0hUx+eN8BreSJOLo49K+PSuP8xEC8B2eVmMiaPLHK6oUSSv/KDIQGqKzrxfTT352LGBvZI8ferD+8tGFaSzHGtlJPrUeQGDPtwFcsjTtXDgWhED4x5oKRYwNPvIjKutjnx4d0NopiMXnxP1L6hBUQvgEJq/vD/7guPf6HqloiEtkflrKxFyJ2FPTYSzPOrXooYiw09gLnUNmQn5TWas0/Shl7nBgbSFFr+nYhIIDKuh7Uel5tWIeI5kCLZ3P+/MrGuwcDKD/wFKaffjxalpwaLpClH9pBqpX327/zV5o6EDEWCrcQ6BOVDQ4xlnmOihjLqeY++A8bbFI6g/Qm9e4Rjz3AjH/1RsY4LTcsNyIANRf3FHkgsqZHqpisUAVMBcfIG0PWHMvKE3bZQsYrk2TNG5KsEaF6mPf1PiLGrpTzYktpaOore0TCFGOn2mW5+URik9LWYrh9bgC0a60OKRFahGZtZIgx5k7Owz+wutf7Aooxa+5o1//gd9ZP6D4fCayIiIimYYeItW/yA0+8iKEdWZMUk7deKKH0L49g1icuNa4cgPUA1WUn5FLybkWM+Q8XTtYM73kDg9uVislbHUmMkUv+/d9chRkXnxmQtVNak7+yvhdjA8PqHN162MfhxtikGdNtwsp6WMq6lB94Cq1LmWKMl+k8JKmt7UkvI8WIJAMFAJfEWMQ4kCERr6zvAQRSYpwA/MJZ/SGHgSDJmtNSA6FykHHeaLc2qoc2EHSMk3TYirHstERK5yfGHkxXjGmQoUJtHTLGaGJIfV6qVmb/+ZUN6xERQnqfL9//lFqkyHD3VCCXklz9QQcpX5wdGFdVrbx+Oya1TmOqlfS+2dTYE+Mbe0FS2mlGrdbMS0qnEWOBRR4ipduvP79huRFNQAAH/2EdWpeclhJ7x8bAE37snbS4NbRxxZw/vzJXny+psSeN83Aaem8b59mgRYqOG95vdkrMQGV9DyZ3tfs7RgdgiJC8xNj67LGn11AFI6UbE3QRKUjgLY7W+0oOWcPSwk5LxLkmayxCl81dVV6uILQIeMCrB1cQHjN/rknvqvLU+yqpmCjMQegxpvLXi2zsuXE3A+dYuvdpQ0pnpYVUfnO1ZmKlSaxzEFUz9qxYq4FyIYxaM3gPmCCIBFZERETTkPdRTsBI6PgfX7ouEBiXEzAy36F/fVTJ2vmuNS45JjHw+AuMGAvNkkz5Wtb+iQ8EgjHy1Y9EPQyIGGMGguPiRJDE2CvpK+fsOGO1IZsYswgpejHvK+t6HGIsXK42zp9gxFgGiQYAh/7tUUWMndCg3hFhhK+HCc55KcxsJJzekDVnphsqrK9pYizXynkZA49lqVbs+kjFGN8hKJ2saJYYK/3rI4wY4/CPkd+VkgcAv5R/HSxf1IaMK+WcxiRBRH4MPPEiRvakBMb1yJoSyvfnMM4VJDH2bqZaSSektHHuEvgBWG7teXaM2tAjibFcrrVpxnmg7oKpNY+UGHPrwYmxHOcYkQX72mkVUzP94X9cZ33vx8lJjHG+JC0otY3w2EsjxqRibPafBRRjAZTvM8RYo5iewbEHBB8josaN83zxP8PuXD60YuyvrstMF9EAIUXp+l60LjnNVhCmdIvBbbts19q0YwjZL73+kNHd7P6QUQ9hE6XB47N6ANAx57yx5xJqaPDcc9LWCyWU7ntKKsbUOaYOKQGUHsggpXndYRaEMtt6AiASWBEREUcFY7Uh5VJyZq4dPLSLUU45ubVbWwNIsiZ9+16OgSckMSa3c2YIPBi0O9cnPmCvSKUgSIylHGN4935JjOVSrai2vogTYw7YA9gQIY3bOiINwl5xE2QgPG0MBE5caSVcotOTgWApCJ0ySUVoE2Ow02qyVr7KXWsetLdSF24ec4zKOocYc+vAz5HF3kl07B1aAk28Y9iulElm+ZZLSVodmLzeGOfOCiU/hmor7UqZNvYicsAlw13j3CbJPQhyMQoZ536esIEggmkt4zzPjlFatXJaw7SpxnkAMs7Rg8wYC1g+DOMixlKfe/YiCymEzIJQxPhhrt24+0PDfimOAjHGpSi86ET3Bz/2DuUzsMeeuwBmLypqV8o/uzKXerd0nyKlLeM8e0HItHV4/APNE2MR+VFd34uR1/aH+yV1N717XwmV9ZI0yhfmoEcSYznUQ7XtOYgxBUmMPZgec85BlTZjuGKRr44MLMTQPCgPLMVYGtQxKut7Gu+UyOpRvp8RY9lD73cakcCKiIg4KtDbe+cwGIdfU2TNH32gYVqLGMtBGjVD1nDFmBX3KgW+aiUdxpVyScO0UrWSphjzkautSca8J39bRzQCqeXk68HvrEPrklPlJIUmQJaLKMzq3ZPKQLjhAuhYcKGdZITwiTGrXPWexZMr3/+U6g9nGYKJ/c4x9OKvMLidiDHXLdWpSm0YxW86AeETdl5ODDxDjLGg1ERCJdwgUoqxJzJIad6egqk1TzzOUTIm9mdh1JptmUrGiFxgsf1IxWQMRsHSmI96Yr5BuRhdQUoK1gcsN2fmUkLEmNsvefljNPbIpUT4eRyiVI6993uksltva+yFYns5xLBFjFljwlfwWsZ5oL34+7GqQ4w57aWJCyKleQDwuEPVEcBeKOCbxliLFMLJA9j9YcmpKdfMfA72B2exgT7X+0pOf6DyeEVM3Ssbtvtxr6z+JljZLjEmWN3N+KfPNPamEDGWMv6tsecGpXbbRsh6aGIsLcYYe1+6j8cYi/39aKFeKKO27ZWwisnyTJAXpPi3q9C65LTcIQBG9qQQY4F6VNf1mrHXAJX1Pb5iLAW1bbtQ2/aKJkqFO28DLIJOx95tSNgmqKzvwZTjjs0dc25w2658xJgwba2JsQak3u8yIoEVERExfpBx3jDulUlvq5jag5Me/irJmnebIOXu8dl3mhj7wzQXI/NdkBgLGBJ8lQSAce8TKelBsVael66UuYixR2zFWOg8FUxb82DISTBfvVA2rpRz2if0w+7IwSffUl4/eW6H3R9S3De1rJ0mKVZaN1+Cg99dr4ixY73fXNJGr5zfcIFdVqA+tktJR/DY/K+k3LlmXHRWoFz71SbGAmlYPsuV0iKlw6RUZX0vgCxSmimErADg073fI5oAEaEKRJRqA4HugRQjkGIQJomvpLAUicx4BalWHkonayzyFqh088C4sMpyyYV6oSzVAVwxFnLlUvksUjpEPLD8Zuy93y/TMeqDpLQ+NuxjCR4AnCnGrOeNIRWGdsixl0chFNEA/DqOCRS/8aBtnHuhBRJ9Lcg4DwZip7J5f7jvKds4TxI/j/qs3blIQagXKKjvmnGlVSu0aYxL/rBYofVC2Q4IH0rr1EM+9xZljn8ig/XYyxj/BPncY+5cKeMfSWKPPX4tIo4Ikqx50N8oieDc5yrrezD1pPnM3TPtGgjUCyXU8pI1kLtrty45NZ/Lt1Ix5SPGSqiqfukvGPO+Jt9X1vXmVowNbnsFg9t2qcWzxvWwibFsVDb0YOpJx6VujDPREAmsiIiI5qEnLmr1bv12dH5RKSnYipqVVn2W0tpTfRcjvvOgKlvHvbp8if4ujZCyVEw8CCLlceqhibELA1up0/xKvRpi7APhCRWb6JFKQRNjoeOzP9ohbeYV8hwFr4fzaoix6zGpZTo7Pp2oXbYkxpQ7V+KUFzFuDL34Oga3v5IrID4RpTo4ZwNU1vdgcmd7bgVhZX0POr+Ub/Xu4HdJ1n5sw+QDT7zgEGPZ9TDGeeNzNIqxlJhzDEM7Xs8Zc655tWZEIxgSsrK+l/WHxBitmjCSxnmSJKj3sf7Q1WHSubvLqu8lWfNuRtYECFV1vKEdv8LgtleYSwmlEawu8jtbMdbBygb0Dq0wda9sIJcSZ3MOyzhWZHBfmY29dBKYyAWKc2SPvXDZqaS02+5IzLb1euzx9ohoHqZttcHI+wOf2zCytF4so7Z9l+9am4T7Q/FvH0Tr0tPMNbMUs3Z6GnvS1drp50QMJfKzVq186Toz/3DLZMSXdOc61Yk5x/+gX2vbd8nn3g3vzxz/NFcxxBg/x5S2Xt+rnnuLAnWw27HeV3JI6djfjwhsjqnJGgpSrn935peQKiaPrPGIfPlCca80WeOWyYkYRZTKsRdYqKX3rGyjYuJl2unoe60Y62qHtdDgdiE1P9eKMd0eItDdEmuh0lNrBrqnTYy59bbbx7T1otTyJhoigRURETFujA0MKVn7BZg8twMQgi0k2w8OARX/o6sdMy8nFyOhf+MPPgFlIGzoUcQYqZgSk02YtICK/0HEmDJO2LzKut9T3KuZl2e79yUARl3FGIP13FUPtfIDT2liTOhETh6F4T37MdhDxJjQxxSBxFq1Eooxpia/vGytGLt8ka5exJHDKCmuyh9754x320qKFGhiLNeOUYwYyxlzrmlirKl4D65xHkCSpBNjgf7pG+fZoLaOca+OEtTNqF4oYXD7KzZRGpjAA4AYIwNB9QfHeDBpZfqKVq1cYJXjQTQiSv188l58fGDscaOCiLHXjXGeCrZI8c2UsZf476sb3LGXwK8vEWMNSGmnPSUpHRh7IqUdI3Khtv0VDG5XBmMQpn0t49wlSkOGq0WMgaXz+4Uee/peHOo3pj8Xv7kKrUtPNf3SJQdYGTT2bMLWASMJLGIsbfyr76U716kpCkL7WIPbX2HPvfTxL+tRSlkQiv39iCDkou7ovgMBt1MiSs3X9b4yqut7mYqJzfc5caM+l+97irn30dhgZTIiSSoIX7HHHi9bQHc0uVMiU4wROUv2h6PmrazvwdQT5zvEGGCHRoAmYQeJlLbOLXCeQqk1lwGCQZ4AAQAASURBVLqulI4RRPVYR6T0Imj1ZOgcVT10W3e2I1WpOcEQCayIiIhxQQAoP/C0NM4Xm9UaPY1wGJPhHb/C4PZX0HHD+71ngDv1kLF3HkT7DRdgcldHZvoEbDvnyxdrMozvosPTjxZKkhj70vVW7B1vUUM9JA59dz1aFDEWXKhhzx1pnO9D2/UXsOMmVh4iqEaVYmz2Z6/C5M52+1mqjs+/48SYS1a5OwYN7njdEGOqxDi9OzogojQzOKdCcyomRow1QdakuhgxSPe+Rsa5RC7FGDuOHnt5iLG+Q/kVY+BtnUcx5qpWIo4YijQqfpNWznMQpRt6MO2k+bmJUo8Yy6iLRYw1qodHjGXVgxGleUjpB55C69JTw6S087Aa2vE6annH3sAQinc2QUpTAPBQW8cb/rhRL5QMWZNzccAja1JAKqZ8O7qWAsRYRj02kHGeb8fK3GMPauxxYiwDVYsYa1SPEiqcGGuAyvqe9LEXMU4kOLy/D7Xtr2D2n12JIAvvvGr3Ptft1FNVSXVdvVA26jprExiw927MuY7A8e305QeeRutSTow5xBU7jhx7u8zY8+J5sXoUy8yVsgN2fVk91HGqG3qVK6W7SOHX2yalU27UpDgktSa1tW5bt00mHiKBFRER0TwSoPbkixjZsw/t11/gLE74N9VRir3zWWmcJ1Z6+70kxjZj+hnHo3XxqazExHsoCaj4Hz3SnYtTVrwW9P1YbRj931yF9uvfr0gjocvhdSISjCvG7Mdb4pVdL5Q1MWa3hfDKTgAc/O46tCyVu3P5izvmXAXIOJfEmNvGpu6JbuvK/U/LtnYmmxN8webIoFbvphx3rFQQcjbTu4CJraRw0wb+LGIsLR2rx8ie/Wi//gL/2E5aHffqs0y1klZ3wYixxadllw2HGAuUxf8MMXZBej3YnwlKvTj1+HyltLJ+uxx7aXWIGBeaM86lkiKvAW1cSrihklKPDSrWSlPE2PUN00pi7MHcRGmlSeO8fN/TuYmQ8gNP5W7rZtyYI5qAaI6saa4/lFFd16PImpxBqXOSNYNEjF3ROD4O7daWm5Re39zYqzVDjGnF2Kxc9cjb1hH5US+UcPA76+W8WPeHdJVo+f6nHddaF+a7w/sPYHD7K5j9Z1ew70MEmUSYsHVJMYnK+h7U+8op9bDrHyTGBE9n5y/f/5QixgLqXYd8q22XAeHb9FyFE2N2XSQp/VDKObI/NWcJujGzNpnIFFYksCIiIpqGNhi/eD0knWOrhRJNMMnvDVlzrKJzeHoikOT3NaWkaLv+/Sydkqc7t+sxTox1zYJ9O/fz2C4lVG9DiiX6oaBirWx/BR3XX6B+SZg9LPR5AEwxdv0FiqCjY5NLZWL9V1nfgyldHWi7fAk7rqkvL18SY9sx54vXs7aFrg+vF5DYxJig9hUIXaeI/CA3h9TgnKphhQBG+w6hqIjSSWqS4pOUBpUNDjHmgjGgo7Ry/kV3K/VwfYp/+yBalp6KY457B/wYJHbaygZGjAHw49KZ/mOR0l38HJNgdcr3M7UmO6Y5BZPJcucKNRx7T6611lbqhtUNHioiH7SSQrt8w0zIHXLQcjHqavd+19AE5XbHOBeppGNtGxt7AQKTf2dUK0vseiAJ9iFNjHFSOlS+kO4qmhjLIF/pTxMhPCZjiIwVzDi/3Lm/BAlb6UrZ+aXrVZ9PwnWIaA5CoPzAU3Z/0L/Bu2aH9/UFVEyJn173hwdNf+DlBtJbZE3WWAKLvfOl652+Jpy0EtbYs8pOvPrUtu2yx17K+Kd+qccer4dbZ3aORjGWPv5l2QHFWOzrRwWSrDkV0884ITthIhcphna8nktRWi+UJTGmPCny1GPqSfNzhQCwibHGaErJaBFj2ZD34qfMIkUDRonaupkFobaMwPQTuetHAisiIqJpyJXfCzBJufdpwxWJt6NyVSkp2li8KZ4e6r0AufcRWWPIK3uOYj73f3cdWpaepogx+3d6T3RPjamYIOw0bp5R9VCa/dmr9DnytJYGSyQWMUZ1S3Q6IqbkH1859zfjMe2RABC1IfQrYmyKUinYczZ7Naa6fjumdHWo2F6qDPa7nSeiGYzseQNzvngdJjF3z9D8OUGC6oZetC49Fa1skuKtPao4bVq1cnnGJEUdYLRQQv83H8TMK5ZgEletOC6lVDdaOW+7XAb/FXxXOSdo+mgwzpGA1V+YQdRPxBgpxlRKIYRnN0ljzFZrpp3kKLlSfjawlbpzggKk1nw3pi8+Lfh7WnD4iMYYqw0bRallUDpXUbk5tHCyBrDbng0Ui6zJMkKF7A/V9b2MrGHpXZmtULu1LT3VcmvXdU5gHUsTYzT2yH4P1Me4Ui7J7peqTkSMzbh8sX/LpbqzgNeWYsxpEx7zkYixlqVsd64Y4PCo4fC+A0bVxvuL09fqxTIO/sM6W7VCpJH1QFCqFU6MsXKsV6qDMs61epfqoo/B8owJM/ZCO5np+su5mQ5KHVoscSYkMvaOCrfA+3xwF09n7LFzt+qhoI3zrKDU6vtRUoxdvtjfoCel/Ij8kO59eUIAlLSKycSlTUf5/s2SGDv9eDSadxpi7Pwc9S3h4D+4irE0JOMjxv68SWLMijkXRmV9TxNtrRRjREpHeIgEVkRERNOYefli42Kk7AJ3NQ5CbSnLyBornZO3roxzUjGF0vDPmqxZsVh/x//4pL/OiTFWR0qTCPvzwe+uQ8uS0zBl3rH6mMKpN32uPfkCRl7bh7brLrDqoduB1b1eKKH8gCLGHDcq9xyFUO5cpx+P1iWnpbYffT/MXUqc37z6RzSNjj+81JoscbuC2zmV9dsxsmefNlSIQBUstbRzBEb7Sto4n+LEegPLRyQoEWPaQIB7Sc0kcXD7Lgz2BBRjZF8xI2S0UEb/N83KuWX3s0/0jhNjAtCGirbLWfp6oYzBnle0WpPX2bSJQf83H2RqTavaVh4Btm29UknadwDT9yOFNT60s1hMhgz3UVm/3THObWJV2/SJjC0y2JM/7lW/Uq1MCm7pzj8kmiideUV4cw5ud48W5Nib86XrFRmMzL5S2dCLlqWnYvriUzM5NwgW5+jyReae7VRbbh4npHH+zQfRdsWS8DnCrhMRY22KgLDqEcnaI0OSoPNLzDh3bkD8Y+n+zbI/nH6CTTAGoI1z7u6Zkr5eKBvjnOYIinzi91kCEWNtaepdfTyB0f19auz5rrWh+2vxm0RKt2eOf6HCLZjnXvr4R5KYoNQ5jfPqhh60hFQrzviPGB+6/p+PmQ/uzY19tlRM/HeuOlSvmqxxNmxy56+kICSyRseldccUy1O+X7paTz/9hIxOKV9q2142xFjgnPh3WjF2/fvTVZIsv0WMhe4B1DZCEuODOsZYdp0hoJ4Ji9kiRSDdBEcksCIiIo4Y3DCgaUS9WEZ1Qw/mqElKwtJZ82xBhFSP3KWEKSkSMw+yUNv2io57xevA/yjvqEuMsbK5oU2obtguY+9YBEQY9aJy72MTQrcOvO6HiBgLxFrxzvFJFhDeeYBqNY8+x7Ikxv5MEmMJ7DaOds1RgJqMuP8ZIivRZI2vICRqRxJCRK/0f9OoVoioIrdbAUMeCQhtnM+4fLHW9XH3V1PNRK+cz/nSdcootokwl0giA4GMc/6bI1oxxBiRV5AGjOm+pk3qhbJWjMnNGKhF3A4p81iKMd0e4XnhWJHa+jrdVvw/o1b01WkRTYDF4gvdRmoOUSrYv4ZIlK+jfSUU/5bfi32DnPIJAJVu495nKEm/FgJq5ZyI0kaKJJGg/5tSxTQl0zgnZYkce22qHtZCiZN2lKtWmGqW15XreLVxvvhUuGpd146sbX8l0NasHjxGZOz044Nji7vvAdkfxpRx7o4LO22C0QOHUH7gKXR+0Rjn7j2Wf1d+4Cm0LD0V005n7lza+DdPEtkfdmFoJyPGEldZTq8JRgukGDPzIPfYJpdA5f6nrHtx2vgHIImx7a9gzpeuzxz/pAIuftN2pUwb/4Bs69F9B1Q90sd/7PBHAHazsfo9+6DJmgvP9DqOcHbQ89z7eKcF9O2J7lkmHpsTED5J7M/gKqYl5jbn3jCFzFvvk/Pizi9dj0ktjBhTdbDOH1wxdkL4Bsxea9t3KVL6fP9mYU2eBEa1YuwCO+h9yo2+FGprp64UHmQid/tIYEVERBwR0iY1/d98AC1LTgtOUjwXow3bmXEeTkdTlzEixr54gyZrghCGGGtxiTFVtjsp09s5X/d+XkwQUjH2gEeMWVVgmasbtmOSIsb4MUPkUr1YsoixlGeYLv/gd9caxZj6nc15jRILwPCO11POKCIP/DkHGQjKve/yJcrdU/7GKRsBQ1JVlWql7fIl7Huw1CY2mibGvmSIMWGloXrIf+XK+WmY3DnLqoM9T5L5q6Ra8eKxkVrMvNcuJV80xnlI+UT5qhvM2ONt5b4XcIkxuyyXOJSxVqitZznH5wos+X54569yXt2INCTsHfWh0b4yyg9sRucXr3PUQ3Rt7d5W0cb58drodI15ob7V92K1OQc3Ut08dWWct2mXEt7PTJ2pP5Qf2GyNPZdIM68Ch0m18kU+9ux0dK5CSAWh3Eq9Q5cBlp6TVLZa07SX3fPNOVbX92LOF6/Tu9YaIttv98P7+xDRPFwPQPdaU3+Y9dkr0ucedI2FQP+dxsXIUOv2vZ6TNfVCSS+eubYw76f1vhLKD2zGnC9dj6R1GoBE70ZMY4jXnMbe9NNPCPxqai2gFGM7bcVYaPwDcIixdpbaH/8C0MTYjMsXe/Xg499t66zxT++HdsT7/LiQ8KtrczwCwMCTL3r9Qbd9AmscSNdaW8UkAKuj0Xw0gU2MaVJG57EXn6g/zP6zK3WogtAiNOUlFdMkZ5dvK4M698oGSYzNUKS0/ywwGC3IsefuZO5B3Usqatda6UppyhPq+Px4te27MLwzRa0p7Gsz2lfCyJ796cf/HUcksCIiIsaNUFBwAanomHrifD8gbQD1Ylmv3lH+EOgmX9TEWHvD9ESMufUITVDrBUmMdX7pBkZAAEmAYUoAVLuNce6b7za4MeYdn30ggi6kGEs71+qG7Thm/rGZbW2MoBIO/fsjqekiGoAmTMK8JzK0/MBThqwRMO6plF69CqFca4msEeZ7OO+FMK61My9fgslzOjwGjbuvCMHcuVYEdkpkEz4Is1sbudYmTj3cfP3ffBAtS06T7q/CnDuVR/WRxPF2jLy2L7xjozMA64WSVIx98XpJQPBzY+1GfxYxllJfSju4/RVU128f9yWf2CBFIP9T932RoP9O5fqmSESzeYfJT4QtGedtly8JkJ42SUkr53O0aiVhdYGXr/zAZrQsPQ0tpy9w7pF2HoGQce4Squa1zoxzioXINyixVZgJKg8Y45y+8wlhac6TOxeR0ry+9vkmSASpNU/D5K5ZrI4AJ7Kp+1fX96D84FPjvegTGtSa/BpT+/L+QNchTOAbw3XqSfPReuGZVun8PfUT6g+zP3sl3H5DY0jnE1DE2BJLyeiOC+o/lfXbFTG2BPYGNP7fWMEee6njn8pmirGs8Q8kGLQUY+njH4G2zhr/gIxzNPLaxDXmjwgOUWQRUoUSBh5/XpM1dI+hK+bGcT30r48wotQvj2PgCUOMCZ1OWHnolYjSjk98QM+LXfKKTy1oN2Uz9sLzfgiB4df2a/e+JOFbKsn5v2CfaSdzIsZMLe3xTOVXN/RglKk1vXYW5nzrakFozpeu127MoTm/PscHNqNeLAVSTAxEAisiImLcEM50AiCy5uV85FWhjP5vPiBdjBrEQkggyRoeayV9BRSOO5dflov+Ox9Qxnm79cASwn6EJFDE2Gv7giulgP3QIWJszhevZw/ecM0FJAHhKsbSMNhjtq13y+SfBSRR2H/ng2aHuYimYRE24ITKdmvlHIDn/kqv9WIJ5Qc3SwOhs4PCgnj5CBVGjKXWSzGUuj+sSB8fRPjUiyYgPLn48gxuXj/OkTmnRNj1HlW7tXHXWq8ubMAQMTa5s8P3/qJjqAKqbOxljX9AuTGv78GsP72qQcqINLimMZGDpGJqvfBM63uXsAWA0X0HlJLiSkPuwiZfNek4BvTfqQhbigvn3GATlre6frt051rByGDAuofTF3WtGLseSet07/juTZxI6WnKpYQfl5OkgHzuaeNc2G1FdaKyZRDidWi/7gJMIfd69bt1DHUOJdXW3m6Qws9DrpSzPn5pgysbEYIhadRndq3pXjz99BOs6yusvqCIUmacQyR+nCzWR3h/mMTDLbBj6z4EE/eqddmZuixeLi97VLlzzfrsleq3xCf82bkUv/kg2mjsifTxD8ixR6R01viHMKqVOV+8Holy5wqOf/WdO/bSxj+EHHvDO19P3yE4oiE4+SjUN0TWzLj4TC8+n0xnwiHQ7toANFlj0sEqO4F0aR144nmmIPRvxfx96d8kMTbtxONg6LaE/WvOo/bECxja+TpmqsUS/rvQqeT5jhZKKP3bo+j4xAfk3F/YZfP5v4BcHJh+xvGYceFZ5r4Ne79xoV6H90hibM5nr7SJqMSMKvp+bGAYxTulYmyKF4cU7Ixl3sr6HowVK7nshN9VRAIrIiJiXHAfCgIOWdPVESRq+HfVDZKsaV38nozjyPR6t7YVFAPIjetjUC+U0X/nA9oIco/L88k4JNu1Yoy7eITqPMpUK/x7s3poZyZiLM82wtUUxZhbJq0GyzhH16sYSsL63f1cbYIYiwghsaZNCeTq3KgyGOXKuWP4sM/02k8GAsnrmUHA8wGyP4w6xJhfK5mnXjQuJdTXLCOe0rNdsXh/EM6xef8fVLF3iBjj5+PmrRdKkoC4YgmmMFJat53D0LmktHd+jAis650Sr9eTxywSS7sx5xh7ESlIIWuGd74uXa1T+i+9jhbKOPhdaZxP5oStYPN4lr/84GY7/oc184d1PG2c/+mV+mcd25AZw5Sv/84H0Hb5Eq0gtM7ROYZFSjvnROdAfbl+oKyNcx3nyB3/7HOFGefCqaelyBXyuTe843Vrcw4OHmexXijh0D+Yto5oHqG+kySyP4zVhqRxTmSNs/BA/bpeKEnj/AuGrNFwx4pQxjmRNbD7gJu39sQLZuzx8pz6ymeCHfcqFK6A6gwAFUZKu+W6z6nRfWbsZY1/euXu9VnjH1Bt7Yw93gb8ePUAMRbRLGziij5XFFnTeuFZbE5J2itKJ9MOv7YPgz2voOMTH9BpXGUSzZHH1O7aMy4+Sy2embm4cMqWc1cixpZY5Zi6G/XeaKGEgSdeYApCAVcpybt26d8eRcvS0zD1xON0yUTLCadeRErPZApbOHWmOo0WSij966Po+MQH2Y7R6k+A1UN+V9lg2trE8Ay1o8DIa/vlIsWfXnFkl/3/5YgEVkRExDhgVhQTdUNOkEiyZjGL/8H1xXoiJJSBQIFxl5ggkPopmuiJixDCIsamdM1S/u9qtcPNKwwx1rLoNPOwUOkJlK+2/WVJjKlVRLe+vM7aOGcEhE4DAR7MUhJjypXScecSgWPQVuqaGOPtC7teMraGamtyK4NfX/qrbNim29qbEEbkhOk/1LSjfYcs45x+s3OZ18oDmzH1xPmWrN0ldOgzGecuMebXSkK7GTYwXIUQtoFAx005Qr1gFGNpuzDy18qDTzlxr/zjE8i11iWvLHKMGedSQbgMk6yg9z4S2G7MjZRaESlQtxHefvU+0x+S1unm+oeMY8g+7xrnrnFLabWSgsUgTCu7XijJsXf9BZbLt2toU/7yg3Lszbgweyv1BP7Yc+thFDeygfq/9YAmpd1j8/GfAMyda3Hw3Pj9YLTPGOeTWqYH+zE/Ho29aSrOUcTRwbAyGDs+/gHnFz6fUH8Dw9I4v+isdOKcXZpqt3Rvtu/F7AisP9SLjBhzYu/wq22IsZ9bYy9Uc1JN1Z58QQaldsaeO/5lPcre2Esb/0liiDGKc5Q2/gFHMabbwC+b0H+nvSAU0Ty40k5+oYjSHa/ruasmW/QcE2p+Ku/FpX97FB0f/6Dl3idYeZoEhVIxnX48WpdJ9a4sy1Epqtfh1/ZhcLsixoRZsHNVvELAIsamKAUhhIkT6C66UWgBvTDHjm0UfolePBt44nlDlLpzbl4vYUjpqQvmM7sGXj6AtfXltKM6n//bdaoXykox9sEJ3+cjgRUREdE89JPJ+MCXlXE+8/LFctKlb9RqFSNRKzekWtn+MuZ88QZJLCXOSoNQjxsh0/ff+QBmXHSmIq/A0vMJnnytdm/H4f0HMHPFEvO7UL/TA03I/HUWEJ4rYgzssrlxTqSY/p21SZIkSjH2spQxJ4mup1UfBenepxRjnbNs2bKgNjTnXO2WirG2K5awNuN1Nn8UY6xTtXU6FRKRCQG4+9mVLYPRMTycdh7UW6lf4BOp/DBCMON8mVYxueaoWbU0Y2/GhWd6a4FuvpCBEE4p4RoIbu/h8zFSjLUF1FS8voDs80SETOmcxdLZNaHzMW19PGs/4bUzAD32qK2jKX9k0Nd4YBj930ohSl3SCNLVmsga9yq5xOcoEWNf8APjhhQp7tgLgcqubSMV0wU+8ZrYPWiUG+duDMJgPQwpbY9/vy56d67PXpVaJl/06f8Wc+eCMy4S+zh87NkjLaIZuJdYGuePSOO8y1YxufduQMbGnH768fYiBez+TrlGlIuRS4zZZJT8JAaGPGIs6wpXu407lz6uS1QojBbLxjgPBKV2zzJIjAXGvwAw8MQL+rnn/s5fBWxijN9f0hRp/LkXcRSgbjKcrJk0Y7r1m0smCk7WnDgfgOlr/KZFytia6g8zr1ii8/MdwXVeGGJsliJrSFmYFnKhwogxrpZ1ibEEwIilGDO/h/qaGJRjr/Wis7zFEqvtFKobbFLaVR1bCsK+knGlbLHVu/q9MPk5MSbPfeLe5yOBFRER0TycG+dgzy4M7diL9uuUwagJmkTfZI1LSQkH/3Ed2q5bpgOQ+ivmpuwSqVaWnRWY7IMdS+1Ssv0VzNYxb+ybu7sI0n/nA5hx4ZlsssQfoz4xNlooYeYKCkLsEGksz2ihhPKDmzQxxuvpE2QJyg9uRsvi09CiXSltwopjsGeXcqVc4pXlGvNjxZImxiZZwV4jmofddtUNPV7cK2Mc22k5WZO0TvOIMBcVRtakpaQyyMWoTW8QIElKTlVSz+CqFW4gJCl9zRgIZ3nnaOc1xNicP73KI6B4fYX6rv+bDzDjnBG2sNtPQFhEiN0GPqnIFWMUWyNifHCvdaV7O6affrw2GLkx7qYd3kNuDlda6bj7N+UbGxiyyJosJJAGglDuXFRGiDwmo7i6YbvXH/Txhd2DSDE2/fQTguoTDu1KqYxzmxwzORMwV8rrL/DiyYRArpStKcY5FzdrYuxPrzRKiYhxQlhvS/9uG+ecBHIJS6li2ptyn7JLrxfLkhj7xAdzuThXFDE2IyUoNa/PyJ79GOx5GbM+8UEvrftcELUh9H/zAbRmKcYYqhsMMZY1/gEZ5mDgiedlzLmWafqY7vgnZCnG+DlSW5NrbVyWOwI4hJAYHEL/nYYo5YQRJ5cI1B/aLl+siShLWafyCmGI0s4v3YCkZZohL4XTP9UPRNYcw8aeVXVhvqP+kBVugbu1u4qxLBAxRgpCs/jBzlO9alL6E4aUTnMRFzXW1g2V875aU5aVPZf8XUYksCIiIpoHX0EoKrLmCzfIwLiwJxPuw4zImukZkxQqf7DnFQwrYsz6WfgU01ixjEP/uJYRY+HjE8zKuTHOdTrnvXYp+cxV9qQt5dnRf+cDaFuxxFvBD02yqt3kzrUkXBiDbusv3hCcbLptX2LEWJiiiMgPoS2Rw0pBKInSBFr2TcmEcSeVLiWSrJmidlOiPEYmbsqg2DvG3ZP1csFfpZy8/OBmdH7xBkwiWbtQpI6gcZKAtpwuP/gUWhazwLhgv6u6U/mD23cZ1YrgUSYSa/yTi+/B765DmzLOuQResHYjoqz0wCZFSvuxVni9ICB35yJSmspk9aFy6X3/nQ9i5gqlEFJpJ/Ac74jA76/GQFjipUicV+nmYFQrvPkFKOCtQUi1Yo5g37WG9+zTqhU3riE/BmDG3oyLzlJjL+tcpcu3jnMUKJdDurVvV+5c06xausSqAFB50BBjaedIZVBbt133fu+e7X6uF8o4RKS0jn0XO/yRgAj/sHtfmHypa+PcqJjcvsufEUTWTD1xvpfOBR97WVdWwB57nCjlcYPMrVbI2DsOMebCNs5fZoqx8PgHlDvXnXLsTbJcz/3xD/iqFV5v9xxHNTF2g27r2OPHCUehVL7/KZ8oTSFth3e8LvvDJz4g+5Pw56CaaK+Ze/GkBjuIQ8j+kLROZ4pSu0w+n61nKAjt+b/McfC7ayVRqogxv0lMr6s9KWPOzWBqqvD8PzFjjxRj9il556HH3kW2DRK6G4SIsYmOSGBFREQcEYisCcXHcWGUFMYISpu6SdWKIcbc9O6qZunBTQ2JMXrgGGJsWTgdez9aLOMgEWOOMeY+oABpqBAxJpx0brsQETLrM1chD/rvfMAY5w7cY3BijCbdcZJ3JEiAJEG9WMKh765D23UXYHJnu56663gLzFU2SRKtWtEKQitIjzIo1GeK9zDrM1cyVyIigNQUSL2ODQyxoNRyQqgVgfpCG8VftZspxhhRJazZmCyfiNLOL96gVs4TE/MHJi8dRxvnCxeYY+q6mKmmEEq1suN1RUontrsxJyQEuZSsVW3dYdKDSEI6R/m+8uBTlkuJ614c0RyIANU7RpGKiRGJ3usYUPr3n0ui9MTjPIJWFgz9WRvnK5b4aTkBKZz4H5zAF4E/gI29M+HGBbTIWAEM7/mNvBd/3KhW3PJ1narD6L/zAbReqIgxNo5CpGqIGON1Me0HrVqhuFeuK44Zr/KlrMbetIUn2MRx2upKRAPI+8kwc+9La1dNCA0Mo/hN2R8mM3douq46ncprEWO8TO8hnbD+cINWMbn9XB+Djb2pC+ZbfVEuUggrnzX2ALtsVi7FAOLGeer4p7G3YTuLc5Q+/iEgg1I7bR0a/xCKCFHEmL4HxMnN+MG6Xu3JF2SsVOVq7ZPyBjJ4/lOY/dmrvPmomxeQau7QIkWIvB3a8ToGt7+C9uve7x2Xk7AANDEWUhD6xJeM/zm5qwNt/F7splMUK1cQuptzuOULCBz6x7W2WjOlzoBNjHlhJJzyvbEXASASWBEREUcAV8WUZSZS3KvZiqxJI3Xou/4775dkDXsoJSnpQyomd1WbYCvGsl2MEgBlRYy1BIgx90Ez2POKcqVc5q14uqgrxVi7IsYawQQh9hVj7jFcYszekTBiXFAzqdK/P6KIUkbW8GTM0Bx48nnfQNBrh4n1uV4so/TvcuV8ytxZTjpFiun0QLW7F9MXSmKMfjd1sfV2tHKuFWNUUpJ46aWB8CDaVoTcTv1jVLt7jGttiNFlebmC0J4Q2u1BxzBqzQX6iH56+ZnGXhsjxqT7Q+zx40WSAGNVpaS4kO8YFWpT1R82GuOcjwUiBgzJC7VjlL1yrmP+WP0MgEhQ+vefo3UJEWPMGObp1Pugcc4JUHYM6c71qFGtUB/jRreuW4LKxu2YvpBcSthTQPD6SxXmyF6mWtGGuEusqv46wIxzz62dEwCqrTdshxgYUkGI7XtR7PfjhDDufRR7x8TpNGlkcGfZn8sPbrb7AxGYjGynaza841eKrPmgsvTNooO9AJHosSeJsXZzbP7sEHTvF6hu7AEE9DyI90XKq3fO1GPvBkyaMd2QdPwcdZ9K9HNvmtqtzYe5L7hjL238CyGs5x61tcnjnCskGUwLQqae1BaBakU0RKKI0gq5WmfMW+m7g/+4Trr3zX+HVY6bjhYpiBhz0/ohAMqKGLta7WRu19NVthIx5ioIadGW14mIsQ4WC9Gtty5bEaUzr5DzoGAalr+6YTsmdXWwmHNJ+jn2qbZ24j3yY2hbRwCHVFtPTVGMTVREAisiImJcqG16AcM79qJt5QVmdQywVwfVX71QwkFF1rgr1qH05Qc2Y+qC+Zix7Cx79Y1XQH3QQalJxaTTCpOMrehZKia+vMProFBRu7XJnRIDacy8UMXeUcRYyzRvVdVafQRQUcSYdudyJ4/ss1aMrVxmleEiUUSIRYy5Rlg4a0QOVLu3WwZCFvSOUV+8IRgYl0DTfr1yfuJxqa6p9HVt0/MY3rE3dz24gcCPGzpOpbtHEmMX5pC17+XEWLg8XfeaUYxN7uxo2A+r3b5aMy1POjGWXaeIbAgBTdbI/hAiSY3hOrJ3nzHOLXJGvdOGKwxZY6lWQuSufCVibAaL/UeGsUvEjhXLzthjBC17FsgvEmvs6fIcA57+5NgjV8owGW2R0uRK2TkreG5SqSnrVd3Y45HSvFxTF2CEXCk/wdua1SH2+/FBAAeVkuKYBcdpJa3bDyRkf5DG+TKrH7rjJEnUfeqBzZj9p1cbRSlLZ+URQGUVEWO8Pzj9R32SxBiPe8UWPtgmOUIAYwNykYJIaSMK9sc0wBVjSzLHP8DduczYC41/yueOvbTxD8g559COvR4xFsnaIwO5e1JszJDbPb9nkopp5orFlkLOUvipv9FCSRFjN1jz8NAO5XzsTZk319gJbvkqnybGrrvAm8dbpJEAxgplVBQxNmlOe3gurz8nkhhbeDxaF78HpGAM5UmQGGLsOmYLBeb/CRKp3v3WA3Ln6q4O0668zsw+qnYrYszZyZxfmYmKSGBFREQ0DWmc/xJzvnBD6goCh3YpWXiCLZcNTLJrm57H8M4U9z72gAHkao0kxoyLkVcFbewIqWIiYiyQhn8+vO+ADIT66at8I5iWRxKTvv9bypWSx9/iq0VsUlDt3o7RvpJ2m/HPz3yWcY6YYiz0wGUPzfIDm3Rb83MPP/wi8kIa5y8rgzEb2s3hwnBwTj5FF5CuTmnEmNudzVbq6cQYz2O5c/E6BvIRKT3z8qX+OQXqUfq3n9tbZ2cYEpIYO8GsnGeAjHOzGYMNfhQxOKxJ6SlO3ImII4NWEAb6gwvZHx7xtlIHfDIxASNrUhSlHHrs3Rwee9YjZWAIxTvvZ4qxABLzUt3oj7000jPP2DOFwDHO7cPzthFCPveGAqS0a8pTPUKkNM8Tb/PjgVQxTenqsEgStz/Qtahz41xmB79SVr8cU8b54tMwZf6x7Ihh1Da9YIixzBqbTUJm/enVSjXrpHEOQsRY2tjjxxuiOEcpY886To0rxjoyx3+SjHNBKDD2uAgyonlo977F74GcQ7PFVouQSTD8onHvc2HUuYosVfOgdhVuwSZp4REx1W4ae4utcvSF1f1HLg5UNmxHJ4099b0O4UCEkTqgHnvzjoUL4XSg2pOGlDahCthR2ALHaEGS0rP+9CrHk8ImvSkEQ3mVbOuWxe+BVHGa40Ik4Orc4Rd/ZYgxd5FCUHrvdCYMIoEVERHRNAZ7Xgka5/SQ4zCrd/mMoIEnnw+49zkzE/VEKf3QEGP6e5fgUahteiGdGPPqUcah72W49znH0K6Uy95r1dcL4pokdgDwDIM/SRK5Mvat+z1iLA2kWmnz2tpeJY1oHoM9u7TB2CjobqV7u2cgWKQLTBcywTk/qNLZZVvzvRpz58pwO6VRmGYghGrPSek8u/eFjPO0uDu2aiUbxqXkA6l9nh+lsmG7VilEfvboYnT/AaWkaOBqLYyBwInSEO8PAAMOWZM1miwVU1djgrKyURGlauyF+gN1UxkQPh8pTTHnZlxob6WeBpcYSxv/AIxizFkQ4vUX7Is0YozniXf7cUAAI6/tk6ry7GRq58wH9OJZiDTk16C6cbs0zvPE/yyUUNmwDXO+cIM+XlZlDv7jGrQsPg3HKGLMLZc//bliLOv8APlMqDyoFGMZfZ7KNq6U4bHHF22GXlTE2Mc/2LCvcmIsz9iLaA4je/aj7bplTnw9l0CiEADKvc9SlBqShl9L6g8ti9/jLG75ZVNA+DaPrOFaQ/lH9+L26y5gYQ4Si2zmqsJqd49y71vCSgz9QRNjmpS2lhBcBaF57k097h1eeAN3eq9JaWWD2L/b7SPbWo69SZY7eWhJY2IiElgRERFNY+aKJQElBZ+eyM+0nbOM95BtWoqalNa2amIs7QYtv5fxHgQja9LT14tlSYzdkkWMmfelf/+ZTYxlQCrGXlfufba54Rr0o4USDn1vLTpupkCo5nePuBBC7s7lqVbCkvnRNw5gsEeqVnwigUymKLcfL9quuwBTF0iDMSSVp0tfe9K49/FAztp1iUGSNT/HrI9/EJPndLCVTgY2KbT6Q+DY/L0JQiyNc0uK7+SzFGONgmMLhxgLHZ+dgoy18oLcra1lWsN609ibqgKApxHSCRKlGHsdM9KCEEccEXJvM75RuZQEdklziRutWvlCjh3EmHFOZE3WpSXX2hls56o0splUTMadKxtVRow16l4jihib9YnLrKdiqCZjXDHWFXat5SZLSDEWRrzPN40kSd3h1wWpmGiH3yBRql5JxeTtpswPrV4NMZYeG9MlxiY7xFja099TjCG7l4QUYyEIpBNj7vgHbMVYWp/n4MRYIzIvonnM/cYnATS+Y/Tf+UCqismd/Ve7t1v9IWv6z8kaV73LyySUHzSKsUbT2eGUsReqPxGlxqMjG9VuSUq3Wa61rN58HuQRY/bv1mmI7LEXp/ASkcCKiIgYJ0Lkj3mtF0so/fDn6Lj5Mmu1hsdj4OmlauUEzFj2Xqc8/71UrfwvzPr4ZUz1JQLlAmJQqphmXHimmhD6dQWbgmrF2AquYnKJH/l+rFjGwJMvMNVKaO3THMOsnL8TLoRzjlIx5gYhVmmdFbK62imRYq1wGXU4b0SzmOTuABWYRNQLrD+0TNeBnAHoWQePeXDwu2rlfIETnNMlmIQkxoZ27MWMFfY241YeVo/Sv/8cHTd/wMR6U3XQ/ZjNOEnF5BFjPJ2CFeeI9yXLGlOknSalz9TGmEegCtM21Q3KOA+51jptowOAUyBUl7hSn73gxBG5YceKQpCo1AYCi4WYsDQC0NfBMs7JQEghKAF5L3aNc/f4dKx6nyHG9O59CJDNABBy52K/8zEKYYgxHYQ4rW9C7Rj1748od652Qxbrku2yq909/thzzpHK0IoxGnuBtOZz7PTjgwheXz4WSEnRfv0yq4/DfRWKNCIlxZwOPx0dUqU3xNhp9nVl+eh4Q+7YA6sr7H4sBobN2GP1sOqu87OxR/OPjP7GSems8U/pLcVYxvgHbHcu3l6he03EkSGrCavd2zH1xPlqYS47b71YwuD2l7WCEGAz4UBmTYzlcK3VxNh1y0CqqzRYRGkDQkrAVoy5cOfSWjG28oKGXU8SY/dnEmO8jJBa00ob+zqASGBFREQcEWyyyHyX7ubg33wTrWKaESBrXHBizN4lLVQPuTuIVK24xJhfj5G9+zHY8wo6br7MOz9XHixqwyh+635ndy6exj6WJMYEI8ZCRB6dI1eMTU9NRzBbZx/H6qq4ASfvyN59wTIimoTTjyVZcz9mrljsTFLUNVNkFt9K3TIQMq5vvb+MSvd2zLnFdzGyIfO7qhVTSUaoMWNseOfe9LHHztPdMco7ut5FS2YiYmzmhe81BlPKUqUcey9rxVjw7FT55Fo748IzvXq4RDPtBBfRPHhQWfal2clMrZy7BkLAkxwCApVVT2H6whPQsug0u1yXMBDKQOh5Ge3XXuCRPla5Qo29ux5AByfGWFnuDnLaQFixxC9T2H3UNc4zCb0x4ND3JDF2zLxj7WOrcnnZFO+x7bpl0rJzZQwKSZKkK8Z4WiYFOrz/ACLGgZTrS9dNEqXSvY+7XJm4OHY+HnuH9wXvGGAqpuuW+Ra8Uz659836DFetJKau6pWOWSZijMZe4BzpzyLGeH35udJHToypeqSNf0AuUlhjL1C+If/kc6/zCzdmjn/C0M7XEXH0MdjzCga3vxxcTOVIIOcI/Xc+gJmXLzWLVmCX2rl+nBhrhHqxbBFj7u5+dCxC/533W661WXAVYy74saznXhcbeymg3ZRbA8SYiyFGjHGESq8XSxh9Y+Le5yOBFRERMT64kw4Gi6xJWS2gG7KOe9XQOJewyJq0lQhtnD+PIaZi8lbrLOO8pFQrH9S794XKJJBirPWC9FgrtEI4smefNM41MZaSQYAZ52eFd0p08uu2Xu7HGKOthN1zjDjaSJSBcAJbvXOtUUMkDpFxbsnaA7NzKOP8zvvRvjLdpYSXYRNjvmqQjA9pFJdR6d4WjL0TgibGLMUYM2aY3IRI6ZkrlkpDyiHouBFErpQdH7+MuQ/7ZDOVb6lW3BZwosSO7N2PyoObGp5bRH6QgXzwH9eilcgaL5H9KneM+o2O/5F2jQFmIHxGuRg1WHKmsTedGedJkujlfp5/eKcce23XZruUAIYYa1+5LKeb4XZM6pRjL/GObfd/Ms61SiGw85eux5jIDEJsEsqX2qbnUX7oqYb1jWgO9WI52B/kLoX+xdPufWrRKqsf60Urplqx4Gx+o4nSDOOc6mWrVlJTq3r47lx+VUxdyqs22aQ0q6P9Ss+9V9TYSx//gJkHta9chkmd7Rn1lpDnGBcqxoUUIlOSiCVUFYFP81E3BAG9FwKobtiGlsWnyf7AvrcIHvXZIsYy7AlJ2JbRf+f9DXcQp7qFiDFrIYQdxyLGQufmHIMUY6QgtHYpdOpd7e7ByJ59mLnCcTN0y4VRa/K2ds+L/1U3bMfhff+JiYpIYEVERIwDbCXRuRHTyrlH1ghfWi5dSu5H67KzvBt26K+6wZA11mqm+wcVe8dSMbE5oLUkJP+CxBgrM0nMe60YW77ES+e2y6hWjH3QdptJAnkADFCcowvOsud3gbJHXnOIMacdrC2OB4Y1MRZxJPAVdnLl/Dda1m4umK+cqxdLqKzajNl/eo3tWusp8uSfTYy5k377Txrnr6iNCmQdEicPKQnrA4PaQJD1QKBs894QY66C0G4XvUNQN49zlOjW0BAmnyHG3KDUfjuSakVuChFSMZpXIsbaVjbeuCEiC37bVjdux5S5HQHlnm+MSrJmm1RShG5knOQVRrWSZ+XcjD0e/JcMCtui0C4ln7kaU+bOCtaVn4cZe6dlpJMg45xI6fQ4hMBYbRj9d91vESGG0HXrlDAiZIn1fQj1QhmVjdvRcdMHGtY5IgSf9Afk9al2K+PcUlK45JXMM9j7CrsX+7/bz4SyUu8uwZSuWZlpAaUgnH+sp4hx6yGU4T/Y8zLmfOF69kuo78j7bP+3QnGO/PEPGNKozVqICZWd6OferM/Qbm0p419BqjWPb2rsxbnNEcK9ZQG6P6QS+CwP9QfdLzlnRYtYbF5sEWNUVmDuDTBiTI09T83IMNj7Cga3v+Kp/EI7oNcLRIwt9c+R5aXjaWKMlR2KW0qkm+tK6Zar22ks0NYZwa6q3dsxsnd/0N1xoiASWBEREUcN9WIJ5VWbMFvJ2t3br7sCUVEGwgylpMgKTji883UM9hqyhj803Lg6QhkIQRUT4D30qhvTVUxuloaKMSFPhLypXPe+YB3U+9rm5zG0c6+ph/ugY6gXSyj9yCHGMtqvsnFbICB8RHPwjct6saRUTDc2SCuh4384SorAJbZdSlLK5krG8oOb9dijX0PlAjDuXJ5izDfgtHG+krZ099uBUGcr51PcXUp12kS/58RYo7LHiiXlSnkjkpbpgRT2ORxKc6WMyAWX/KTXwZ6XlZKCE7ZhRYVUrZCSoqPBblTCIWvCpC7l1SqmW24M1tP6Ezz2zjsstSAAmNiMEvbYSyeNPeM8sDuX+1ch1Yompel55p/D0I69DilttwEnvjUxdu2yuFvbuOG2sfyusoGMc3fTGH+hol4sS+P8lhscRWm4jxpi7PetHc4MzDEGeyQxZuYqobEBVY+SIsaWWv1SwO1rph5TF8wPjD23zkIRY68o4zx9/NP7/m/dr3drs3+zxz89E+TYuzCQxj5GvVhmYy/2+aMJTtZw5XYIeYhSPmcn9z5XyZhWj5E9+63dtf35vzP2vnC9WZjzJkGmD5mx15golWPvZcxcnuHuqMiuer8hpfl8LAmNESFtEE2MmZMMHkK39eevD/4+URAJrIiIiKOGg99bY63eZXl+1DY9j5G9+yx1RFp6IsZmfSYsa3dXQMoPbbLc+yTCD8ehnQHFWAhCydrvup/tlJiWVkg5dci9L+McwzslhlH6YYAYSym7tpkpxjKuSUQO8EU8RtaEYu9Y74WJe9W2Yqn8mf2WwM5TLyhi7JYbwqIV9ZnKIePcczEKXG9tnK9c5qsHneNI49yQ0iKtLuq7ClOMuefo/uk4R6oewbLVe1EbQvFbzJWSleNWI4Fs60ldHZmkdEQ2QreKerGEqorHlu3SSkbxdrSylXM3liDHYO8uTZSm3a+p7HqxZFRMOcia6saeFAWhMur1ySZaMTbnFr5yHq5PIoBDWjH2jmAaDjn29jukdGjDDUOMzU557gH2NeJjL97njxbkdRjsednpD/I3r18IQ9bk6pfdLjHGy7aP4Y+9UJ806avd2wOKMQSNaCKlZT2yxp6tGEufByX6SNXu7YoYW5o5/k1bvxJoa7ds+UptnWfsRTQC7w+KKFWECs2xQ26w1B/anHlQmsts5cHNmHrifEVImb6QVrYkSq933LENhJ5omP4g62HS2/dX+X21e5utGPPawuQZLcix1/mFGzHZUkny9PJVCIHqhu0OMSYJWmFNciTCxFh4jJixtzTX/eV3GZHAioj4LaBWq2H//v3Ys2cParVaw/SFQgF79uxBsVhsWOb+/f8Ffv+BKJ1aSbH8nIbZ68USKhtdAyEdkhh7D1OtpE2wEtQ2M+PcrrSVTteDGeeh8ji0YuyCLBWTzDOclxiDIcaCMuYAqt3bkbROy2Wca4VQzhhjEWlIPFJF7lpzAloWvSedCFLQ/SHFnY1vpikGjYuRdinhczeH4DFBqZfav7tzJZcY42dHQYKd+qcRY3qxlB3LGnshgoshlZR2208dR7tzLQpI5p1zHeTEmFtmRH4ESFjbQIBFvrqvpKSYwRWlIXIXyjjfsM0Y5y7hyesDZpxTfwilVyADweoPAfIVAjYxxnfwdNtDoUKKsTTVLKsTubV38rFHJKxbn7EcpDR7zQwAHtEc1DVJIK+ZJmtC/dLpS9WNiqwJLVo5eeoFRoyxcRMcI2PhsZdWNo29mcuXer/p6rJ6aGIsdC92nzecGMsY/xBAredlaZyvWJp+bgpWW7shJWCnBWxirNHzJiILtjKoXiyjvGqTcu+bhZAKjis/yw9uQsvi0zD99AXBtPxvsOcVDO18He0rlwVcb+0/ImvkBgGz2LF5epO//OAmpWJywwtQ1zB1P7z/ACNKwyq/hJVNY29SaIMe9kqErYx7ZRN0aedY7d6OOV+4McWt3U5vk9LZRPPvOqb8V1cgIuJ3Hd3d3di8ebNFXC1atAgrV65Ea2urlbZYLOKHP/wh9u7dm5l206ZN2LhxI1paWlAsFjFv3jzccsstXnlf+cpXsGDBAtx8881vwZmRdSmkiqk3tEJpIAOKC+bmcGFgtzZ/BqJdSqzVCffBJz/Xi4dQ6d6Grts+3qBc+fng99aiZfF7MgLjmnykGJt7x6calu26UjaCXjl3A6EGMJyjrQlEjLWvdNs6omkEJs9+fwgggZ4QzvrM1ZjEVUwpx6AJYcui94TjKzAQMcaVWsGgwsJ253L7QzAIcbdjnLOy3NRElM697RPBU3PrRGrNYABw51hknOu2zmg/IqXT1JoRTSLLOFe/icCrpVox3kH2K8E1zoXqL7yjcQN64/bG/UF9J1Ur24xx7hJSjg2gV845URrKI4DB3pdtZY7w0yCRb0cLkhibuXyJNIIy6gwA1Z+lEGNuWmGrd6ntJrpxM26wdhZjMki57g/uNXBIfBn3ivV5Xp6Tl4hSvmgVDJumUP1ZeOyllW31S3e8Oen77woQY6G0jBibe8enMsc/1cMixtLGv3rPSems8Q84Yy8SV0cM3oTG7TT9+Unpq93bUS+UMPszVwNIm8Wre6CaF3fd9nEdlzYLNA+atvCE1LrSQBvseRnDO19H51dvbljuaLGEQ99bKxVjGSomIr0qD24yRKlzXPc+q4mxtM0YnAPw5x5XAYegx97fNJhzThBEAisi4i3Ezp07sXnzZixbtgyLFi3C4OAgdu7cie7ubhSLRdxyyy06bbFYxF133QUAmoyitIODg/j0pz+t061atQorV67EsmXLdL5NmzZhxYoVurxNm+TOW/y7PNizZ0/DNMUhUoYJqehYtQmzP60MRiHsp1hiyCsIyPgff3CC2aVET/S09Q2ykIdeYsY5zPd2+fI7rVq59kJMntMhEwkhfyew40njvF0SY16Z9vt6sYzKxm3ouvXjjnEiWLmJPndSjEliLHHOj7dkgtqmX0oi5OufYnXm58oJOqZaoXO0Kg2TXwhJjP3BCWg5+zRjFAqR6xr/V+PtVsdyraTf14ul3CSinKTcl4+sgTLO9+7D3JvtSUqIlKL+4K6cp0n3dbyHkIrJQR5SmqCJ0mvDO0a5dU8lxgIgtaZNSqeDiLGpOs4RcPjw4bddf3LxdqzfYG0QgLx+pKTI0x+Mcb7EJo3cV3X78oxzpPfhdHeuAIQxzqd0zfLiprg7R2lS+uYGBoIIGOeBNPQqIMd1y+L35Aq6axEhbn0d6LZevoQRIQIDtdrbsk9xvN3qJwCMHj6sP1c3KuP801enZ1CoF0oor3oSXbd93OrzHhGj8hliLEfsHZcoJQTYglB/yFrY0CqmjHsx5WvquYcMYiwwz3Kfe9k7NobHXqlcetv1KRdvt/odGBux+lBl1WZMXTDfeBlkkIOjbxzwSMQgeaWmtRYxllYuPRP42AuRngx1RoxNapmu5roBQlhBK8YWntCQ/BzsfRlDO19H5203pzNzqn71QhkHv7fGuFJSPRCoeyJtoakLjjMqyRDBq94fDrQ1EqBQKGJP9a3tUyeeeOJbWv54EQmsiIi3EK2trbjtttvQ2dmpv5s3bx4KhQJ6e3tRKBTQ1dUFAJrUuuOOO3R6nnbv3r1YsGABenp6MH/+fCxbJt0hOjs7sWzZMovAKhaL2LRpE5YvX24dOw/y3Kw636gDbx6QBsLd96NlkSJrRGIvTAgBCDWBSxJUN25TZM2nYT9lGKujV+/KUknx6asxec4sRuaAPQxk+YDazvkPyMWIJozs6cHyDu3cKydin79R5zcPDipT5hG1IfTfdZ8kxrpUPXidqXxFHFW7t0l3rsuWsokjIJgsmbLUi4cUMfYJ+4lLdXfeH/zeWrQseg+O+T1FjFE9eKEqbW3z86ytebMlb9sHEmHPnj1vuzq2/0cZ6DsYNhAyEHQpCSIr1kp4Qu8ZCFn1yGucw6iYQsa5JqMZKqs2ZxrnvO6Dva/kNoK0O9e1vmIsBE6M8WMec8wxb7v+xPF27O8A0LL7/wuUqxgtHLJVTA0gyRqfKPUMaBEma9LQ9Nj72XZtINjxU0SQDG6KlG5m7LmKsVQkqBfDbZ1OSoeJsRmtrW/LPkV4O/Z5AWDKzl8DwyPSYOx9WW0Q0Dhj/933Y+ZyX7UihDAkFuQYqGzclk2MMdQLZW2cp+6Sxj5XVm1qgih9OVefJ/KqqbEXIMZC4x9okpRG+tjr6OjAie96e/Upjrdjn585PADsfA2AvBcP7dwryRogSNhoMrO/hIPfWxNUc7sQirCdumC+3LApizRyyRr2fRpkv1zq3C/disMnxryTs49Dyvmu2z4eDr/B0wugsupJ5UppiDFpFtjjX0BgsIcRY4Gy+HnXiyUc4sQY+62rqwsn/t7bq0/9thBjYEVEvIVYsGBBkECih1h/f7/+jggqN/3ixYsBQMe6KhaLaGlpsdK4roPd3d1YsGCBzvuWQADVjdukgcADf1oPDsNm1QslQxrRb5yosbIk6L/7PknWzGPBOb2HmMxLxJjctQaSDHKUTnyyVHlIEWPBCWFi5bGIMcHKc+uRqB2jel9G27UX2sUK571QqpW7mSulPnaKfHjjNqUY40FW3TaXn+sFFWPs887ku8FqU0QG2EqxHRg33VWHjHM/QC/B5JUGwn0ZBoJ9zcMr56H4CcY477R2a0uHNBDeE94wgcsYYYixfAFISzmIELvsUBDiEIgYkzsl8uNHV6rxI2FkTbg/uDtHVbu34/C+/wz2S580KjdHjDXbH3peZjuqEUwdEj0+ym8RKd3IOHf6phAZxJjfj8NjTxUVb/bjhm0w+opSF+WHNmPqguP0bsruteL9/vD+/8Rgz8vK5arBvUkA/Xffx4zz7PTVn23HaKGcuksar4eOc5TzXqwVY25A+MDOcXQvdnds9EnYBGP9TY69LMVY7PLjhlQxPdkwVipdQ6lieo/n3gfA66aDvdK9r33lhQ2vUb2/jEM5iTHAKMZmXvje7J0ShVGMkbtjKA2HnI9luFKy9JIYKxs1FU/G+r0QAvU+o5zXbZ3WLsKMvemhts7aKet3HJHAioj4LwDFwyLiqVaroVgsYsGCBV5a+o4IrPnz53vB3ffs2aOJr97eXrz00ktNuw42C1q9C92woUgaQr1YciZiGeDEmDtJCTyX9Mr5528Mr2A4eYPEWAo0MbbywnACfo6FDGLM5egSoPIQV4xlgxRj7dem1INBEmP3BWKMRRwpdHDOy9jEnNyQnL5nG+ezpKqPSEr+qv6q3dvQuvg9aFn8+zYhqdMIrbLTBoIee4mTxq4HrVBOmtPuKx75McAMhMuWWPULHadeLDsqhYS1iWCf5a+aCNEuvqwazj3DGOc85kvi10lQEOJtmPP5GzB5ToeZMKr2iobNeCGUcT4/wygGqD+NKtWKb5zTBbAXB/rvug+ty/iOrukGerV7Ow7vd4mxcB5v7KV0ACJ5pGttc6qVxru1JdbYC5+jXS9JjAWee4G0zbpzReSEZzBmk0bSON+LtpUXqG9C6c1Cgq1acceFjfJDmzQxlmT5UMGoVmZ/5irvuOa9uR8b43xWxjnS+JCqlVC/5ONfnmNZESE3sj4fGP/q+9KDT+YOSm2PvdA5RowHFAKgLe8mQhupP4SfCSEVU97dtcuqPwSJMedaS/e+vWhfeSGEMKpaEdhkqt5fzq0YA+SmMVox1gBEjM36zFXecWWtbQ+TNLVmCNWfybZuW9F4c6yJhkhgRUT8F2DTpk3o7OzEvHnzABhyKs3dr7OzU5NWCxcuxODgILq7u/VuhS+99BIWLVqEYrGI7u5uLFu2rGnXwWZQL5ZQVQqffA+8bWhZ9J5cZI1FjLlw5m+ZxFiAVEslxgKwiLEcyCTGnLpUuhsQY049Kg9twuxPX5NvReqhTZj+BwtytXVEfmiXks8rFRMnpADznTIS+u+S/UEaCJTMJbEg3U5V/I8ZlzFCylIomj9tnH+e7RAkZDkmn8lf7eZjTyoFJfHjnoPcIUiOvXO847r1kca5ow7gRFeQGDtOkX9Om4nE1J8TY7ytU9oDSLQb8+TOWVY5Om+0ccaFwZ5XlHEeuE9ZpK3QxnnbymWKoOQkItR1NiSsNM5VrBVO0vKy1d/h/YoYo3goDtlpvR9jxNicjgCRaqvzDDG2xPo+dK4yztEmNfY6/LrquiTAmEB51ZNy7JFx7pLMrA8P9tBzb4lzX+Fp5aulGJvT4d9TaHxHNAmB6sZtUkmh78WCXWP7HqeVFJ93VCsUhoD3a5FIYmzRaZi2UO3Wpsty+oQwQalp50yhf0u8tFoxdi2NPQTqbjqqrRhjiw1WX5afR/dzUtpqKmv8Ux7zTGhn9aC2E1a9NDFGbZ0y/oHEHnu6z8M+RsS4UN24Xe2u/V71Tfq9Y2TvvhQVk59HbtiUc+Fa1WOMVEzBcs2F5vE/7YDwiZcWSBQxxhVjaeeYMFI6vGM0RzopzWttvjOk9Hu9dG69DjPFWNiFfGLf4yOBFRHxWwbFulq+fPm48nd2duKmm25Cb28vbr31Vnz/+9/H8uXLsXjxYnR3dwPAuMvOi8Hel5XBmI+8spQUGfgvI8YC9citGMNvhxhL3ynRrockxho/eCOaQ23T834spsR7A0DK663gnK7BzbIc3v+f4f6QMin3iLGM9MGxp4kzuy5HNPbc83PKthRjafVVn40rZYNgr6we1tgL1SMaOOMC9UsZGDex/yySkozz92D6H5Bx7hKq0J8lMfa6UpS6JKlP2B66Rxnn7pbuTrkQCcoPK+P8gvcyUpeBkRE09mZ/5hrrXGyC15Tdf/f9mHnZUqOo5MfWZKkijn/muJToeIVu20ESIQ9tUmNvllMXRloIAGNgxNjv22Wx9pvYps04IYCRvftVfJwAgZ9AX7+xgSH0f1spKbpm2dfJJUJV/E/ZH86xSSKLoFeEVKGs+0PSOt2+/gmstNbYW7jAL4/3OZEYUvraZU7/ZvUhYqy/jIP3rJHPvTmz4I0JJx8992Zc8N7M8Q+R6AWh2Z++xjluoN2FVK20WYqxQLkR48LwztdlnECbhfdQL5ZQ+uHP0XHzBwNzBJeYZ8SYRdaEr9PInn1MxeSU64B2Mg/Pz/kER9Wje5sixkKKMbvv1IuHHPe+JDUtAJR++PN0V0qeT8g5pCGl0yYlQtWjlOJKmThpJ26/j0HcIyJ+S6jVati4caMOtn4k8akWLlyIhQsXWt/t378fvb29uOOOO1Cr1XDPPffgjTfeQK1Ww4IFC3DzzTcfNVVW6wVnYWb/nAapZEDa8ZA1zRBjPEh5GoLGeca9fzzEWJ5zfDsRYxHNoe3aZZg28P+zvwzMQQZ7X8bwS3vljpVZoJVzbZyr/pA45bLPZb5rTQOMWoqx8PH5+4Zjj9Wj4dgTJn298NaT0g3PceLO8Y4Isz59NSYfrqQnUNe4+jNlIHzqGuv70PioF0ooP/Qkum79ROOt1AVQeehJY5y7YwPsszDuXHrHSscekwGIVT3U2Gsn1UoDkrP8cGDlPJRHAIffCJDSWvno17v/2/cpYqzDnKN6tXfTSlD9mSRCZn/qmkjMHm0kCWZ96moMTq6b71KUPtWN2zH9D5RqJfM6JNI45/0h1I8VxmpDdn9I6+9UD94fzCGD9eZjLyvOEYGIUqkYC56aLpuee523fjxz/AMpz73Mesix17os0NbZnEtEDnTd+nEkLdPBd7AOvZZ++HO0LDoNU094p/0bh/pY2/y8uRc7G2hoMljIDPX+Mko/+jk6brpMLQ4IOy0VrI43oMfeWfJ3r3yTzRp7gpXFO466N2ti7LKl7JmgHx7euVY3bgcAE27BPUd2rvX+EgY2PY85n1eKMe8cTT0goNt62h+c4JwjO7kJPq+JCqyIiN8CisUibr/9dvT29uKWW255SxRS99xzD1asWIHOzk6sWrUKtVoNt9xyC7761a9icHAQP/zhD4/asSa1qJUJvZrt/9WLhxRZc47vYhSYhFS7tzEXo/R0AExA+M/d6BsF7h8S2zhPS6+gVSuXLU2vgz5HZZx/7kY7rk9KPbRxfvZ7Ase282rF2GVL08tk9ei/m016A3VNbfuIXJiUI35DvSgNBL1y3gBlbpwTUvo8GQjuBgFp9Th4z+rccdBI1p5JjKl6BI3zjPTjIaWPulozulONC/I+nwFG1sziuzql3WNcsgbInIRXf7ZNBaUOqOsckHE+5/M3SmMsdHh23ydiLNU4Z9AuJdfmcykJGucpdfdcShyDnNstOsZYjt3r4m1+fMhD7NQ2/xLDL+1VrtbZqBdLKP3oZ+i4+TJ78SwFmhhLdTEyGNm7L9wfAuULRYy1NbF4VvfcudxC5Qt/7k1qnd6w85VdUjoD9Nxrv7ZxAPCI8cHMVZiiznmtdm8DANPnE5bG+asXiay50aiYdGB19aq5qQSlH/4MLYveg6kLjmNl8ldTl9rm5zG0cy9m0GZGVh3YeyGfCYYY67DLchR+cnGAK8bCaehvZO9+DPa+jI6bLjPfu+eoXsWAjDE2Y9lZiqALnKNuT/ncM20dOkeYNpzAiARWRMRbjDfeeAO33347Ojs7cdtttwUDtXd1dQGAF5ydUCwWdbysELjrYLFYRG9vLz7+8Y9j3rx5mDdvHm666Sbs3bsXhULhKJwRcjH/cpLy+2g5+zRFnLC7rbUaLX3OB5992SavCA7xUi+WnBXrxM/DUO3eGoi9EzgR4RBjHLwObIcTzzgP+aknJKfeaoixxHngUvuotBYxxs8xpeGD7lwp7VHvL4V/iDhiBEnEFKQbCP41tg2EHIFQtXGeJWuXIOM8zwYBRrWSkxjLpRiT55ubGFMwY29Ww7Qje3+Tq8yI5mDImuaI0oYqJpj+kIesCRJjGSDVir2jaxicGGtIbogUUjoFhpTOGWvlntW523p0/382TBPRPLhx3jAotQBKP1LG+QnHme9Du6TBEGMz8vRLIsY84zyMiiLGWi84AmIsANo0pk0vVGbDe+5lkdLWglDj597hNw40TBORgozuRv1BkjUKKdeN+sOMZe/F5K4Oa9HAg5D9AUDuRSubGEsdSgDY2FtwXHoiBVKMmQ16UpBkjL3QOSY09hbosRess8pLbT2Lt3UKRG0I9eLEnc9HAisi4i1EsVjEXXfdhYULF+KWW27JDNLe2tqKvXv3er/x3QfTjrFx40bcfPPNAKBJqjlzjIsf5e3v7x/3uVhwCSnAImVMINQlzu+U3+StFw6h/PCThqyRiVMPTQaCdjEKbM1MGHxWEmNtH1rmpHXKTxJNjLV96MLsetAqycZtmHrCcY0feAAOv3nAJsZECsOk6tf/7TRizD9XoxjLtxrcf/d9DdNFhJCtICSyZkaqm4PpSzr+x6dCW6kL760mxuakGAisfMtACNXDIYONamWaU56P8kObDDHmkszOefjGeWD1UN1HLNVK6Byt+iSGGLtsaZg0Zl8d3n8AlYc2hU8oYvxgxnlwe28Htc3PGyVFAzRNlDYMjGtgFGPkcpVhQR8RMebC7v+GGPtwk8RYPlK6/PDmhukimgMZ560XnJW7PwAB4zxwz/KN8+x+2ZxxzomxbDRLjFU1MdZ4t7bxEGPNLAgN9rzcMF1ECtIWPMfVHxbI/tBAIRQkxtKqVxs2xBirRzC2OcZDjP0yn3K+2bG36Xk19owtlFZn3taTcpLSwy/5NuNEQSSwIiLeQpAy6tprr22YdtGiRdi7d6+nwtq0SRpfJ554YjDfXXfdhUWLFmllV2trKwAZc4tAJBj9dsTweB2SuQppnD9LxjklJh9uR+YLMhCYm6F1EPvP2iEoWBFTvjbOP/dhFoyR/nw/jfLDUjHmr5y79WDEWCgIsSunLhzCoXtWK2JsVuAc7ffanUsrxtL/Dr/xnxh8logx4ZRl1xlIFDH2+4g4CmBkEBkIbdzNwVPtCa3yk/1BuRhl7AAFKGLshOMwY9l/N+WGyDQhTFDqT12dUg/1nVJASgPhHEYaJeF8Qrr4WjtG8TTq+PRZG+efowDg8M+TofIQDwDuH5t/N9j7vyQR8iFGhLjpE+NCcOj7qzHzg40nsRFZ8PubZ5yn9BsIbiB82FZS6H5gK2HJQAgTpXbZRIxp11qrf9nKVTn2SDHWnm5g0dh7iAelRrA/0nvLvS/Uf2HGRyIS9txrt8tzz1ewGGOalE78uvOx9/CT6PjYB1NOLqIhvHuUbO9U977AtfOM84y+ZhFjfBdB/jxg0GPvMuZGFeqfcIgxfS9OP8+gYixl8YbG3ozlgWeCk166czlESGj8q++tGGPs+9AxqK3zENgRLrKVfgfvWdOciskha9JgEWNdsxqmr2zc1jRRmocYsxRjOYlSoHliLM8iRdOKsf+1F9PPnrjz+UhgRUS8hXjjjTfQ0tKCnTt3oqenx/vjiqtly5ahtbUVd911F/bs2YNCoYBVq1aht7dXx7ZyQeTWihUr9Hfz589HZ2cnNm/ebKXr7OzMdENsCnpSZftl14tlHPp+I7LGfFd+SBnnF7w3+DsHkTUyWKnjghfwD08nxtw8acRYuB4+MZaNysObAsSYW74ixni8hxwuBH5bp9U7QfmhJ3MrxiLyo95fwsDm5w1Zo+EoDtXku/RjpVo5/UT79wAs1QpXD6as4B/6fgN3Lk3uCGacswkhc2Pl42vUI6VhFJcBPXz/t+9D22UBl5JAvasbt2GUiLFMcFJauZQkofuLQfnhTbnjHEUEoI1E+7ppA+Fjl4UJI0aUjqmV89YL3ovJc9pTiCBD7mgDIY0otZ43ykD43I2Y1OK4GFnlCmCMjT0KjGudo30cTYx9KKAYc4x+cu/r+NhlhoBInPQsT+mhJzH9DxbIseeRCCqz+o7UmrMsUlr4dYcKQvzt+zDzg+dgSg5jLCKAAIEIMOP8snOC/YXn0WQN9Qd930Uw74BSrRiyxiV0zPigoNQdH7vM/JZyDmMDAWKMp0nsMVDt3goAfhzSVMXYL53nnj/+qRwae1NPOC5z/EtSWinGgvFQHSVjkbV17PPjgHttTftWN27D5K72XCEA6sUSKhu32nGvMmARY2mSJIVxxZzLpRhLbMVYRjqgWWJsuLFak522vSDUeO6vx14O19rfVcRdCCMi3kLUajUUi0X86Ec/Cv6+YMEC3HLLLQCkG+Ett9yC733ve7j77rsBSMXUypUrsWyZHyOjWCxi06ZNWL58uUdufeYzn8H3vvc99Pb2AgBaWlr0cd5KpKuYfJCSovMrn2iY1iZrGk9SJFnzTnv1LgVGxfThhmkBoP/b9zJiLBvVjVsxWihh1ievaZi2XpQr511f+cPUIMQc42vrP2yYNiI/LOO8swNmRpIE3ieobtwKCEh3T2sXGgfKrW5g8y8NWeOVa0MaCL9vVExIKV8IbYwFx56z2029eAgHvbHHSDRNZsvPRErLeA9uHeyJmT/26PdQ3YVPSod2H1LfS1K6hNmfvNpvg4h8CJCTmQaj1Sfk5+rPthmyxj8A+LUZeX0fU5SyOvCxoo5Bu7WZsYfMy2yrVlKgjpXfQEiAMWGMc75yHqxLgtrmX6ix93Hv/E1e+R099/Ia57ytG9iEEWkI2I71wiF9Lw73B3ux4uD3yTh/Jxrde2qbf4mhl/aii9+Lg2ERBOrFMko//hk6PrbcCXMQPkb1Z5wYM88hnZ5lG9mbNfZsjA24zz2n3g7RWt24TT33QvEeWflJotpaLQi1Tk8d/wRr7MU+Pz4I/8PQS3vtjZJc6EsnIAZlf2j/0IWMsBWMuFUFJObZPLmr3V6koDKd+khibBu6vvIJGeagwTXWxNgJgf6Q2AeobVL34ls/gbSFQUpf75fPvVmfutrftdZdrIDs83rsue1gF/3/Z+9fo6Q6rnRRdAYgUTwrE+3blh/jkLTllnrbhsJtPXyuBYW2JSS5LQpJfrVtVUHv3Xa7uw3y/nXvHaOBHmf0nzuGAbffvVsUkty2bIkqZImnNlWAzhYgXVFI9mnJskTR2+q291Hlg6qsrAIy4/6ImBEzXmutTEoCVPExkszKjBUrItacETG/mDEDJobstg6Ug2lSet5tN4ZDSkwTRAIrIuJtxN///d83lf4DH/gA/P3f/z38+te/hrlz58KiRYuC2/6QlPJ5ZmE+6AEWir11UaBzISbImvr/XYH8XyQc7y3T14uSrPl//Xn41BqS99nHn4E5tyw1txh50gEHqB17CSaHfg3X/H/+PGjDI+pFQoylxt4R5bj6Q/8bzFtF4hz5Fks4DUr9Jec3X12LW38M8+++1b9SatXT29a0HWgdR0hbZ5gARCTB3cphrpyH0jI49+szAbLGFSBuGOc5K0t3+9DYU9bKeUL+mhjL5kGoiDHv1lrzb1wp1cRYuI6KlPZ6jPm8NZ8h3pq+MujPuI1ZtHXYmzIiBR5D2iRrPEYxSWvKg4+c1B1WfaRsEWO2wWp2uKZxbhSapBOftXH+JTDytQ8A4VzEWtkqDQQnFqKdtyDotHHuI6715/qIZZyTtnIGVE6Nc0mEGOU1O3tX9yJah352yqvt058kfXHY0B17mhjnXu8WLRP1t8ow+vSzYtFKxb2y9UR+5gxKP3hCygONh2rJjYSre0SPlDEtrqmPlCUx9mnTY90X51SR0ri9L6z/AGCNe7acm3VsVO1xL6z/AJx4a6Z75kRkR32kAqM//++Q+9p9+hAhWxbIn2d//gy0LfuQjktLf7eumxj6tUmU0ryNpAwa4zUobpXEWMbtfTP/Q7s5DzLy1zeoj1Sk7q2X8+LkiTESY1d94D3uj4Y9ose9/8f/8ZdWQldP6iMVGH38v0Me29pIbrU7Fzs6DI+xaTyfj1sIIyIuQ/zRH/0RfOADH0iMWTV37txUYuoDH/jA20NeATP64nO/PiNj79znJHO84WuTphdTeC6oyRq6xchOT+Y3SIwtevBLektJQgd/9ucBYoyDc13tmDxK/f7b3RUX61UvVqD8Q2mc42qNJ0/MxzDOGfjTy886zpHV1vY8T74rYiy6118crGfnbHNIQH2k4lk5D2M0RIx5ZAgNhPYH/jQ1X+G18mN35TwA7TGWMd5DU8TYU5bHWBhGjLEM5WjGWzMiCcx4GR6EDslopg3Lg50eCFmzVJI1/jzx+2TdY8b1Ya8V5tEnpnRv7m03gjuAmXmjx1h795/660U+IxGijXNf++n3sadpW4OnvLpcbluzSNm2Cm4+u9HHxXZPM3akK5MAABOnXoPasZdh4f23u2m4eS0fn4Ditn+GhfffHjg0xvw89vRRaZzfCv77E3l4qwKjTx+1dM8ui75WeIzZuuepJ7e2Uhr3dcvkH/d8eoJ1tMc9v/4DaFI6y7gXkRVUHj4KV33gD8TXXnIH++IX4Nyv/zUwNtvyUIbRxyUxhnGvEryekKxx47a6vRsSYwvvtw6N8XkQyr54oQq/kZy3IKXbE2LvatRHymIrpXOSuWfyxplq61nY1jRvq+zjh56XbZ1+au10QCSwIiIiWoPsW41Jyn9od9NYJMzo00ehbekfCS8mcLp0Ms9j+tSahC14XKZtIDFmkzWBsWbs6aNQH/HE3vGMp8KL6aCcEKZ7MZ39+TPQdksG45xTYkxMALyLUaQcihhLMs65LofttTKNF2ymDI7B6CEaKZCscYJzeoR//NDzMDlkGec+8hMs3fN57lnlGnv6WaF7KA80jZVWEWPdfxqsF36fSoxZ9zGIMR/xSu5ltDXdWhsghZshxiKyAw0EJQ8JaJooffptIkp5gu550DQpvTM7KZ3srWnC0b0EhNo69vMXD20wZiPOR3/+DOS/dn+2MAeKGPtoalptnKeXozE+CcVtP7aIsTDGnjrqeq0EILxWbGIsDOEx9jbpXhMLQhFp0CTT2FPPwsxrQkSpSSLWR85KefgzKx/PyjUw6cW0VHgxcV96/XKJsRBhy6BePKuJMWdxwH25pDT9nRvXTwy9BrXnUPfcOtEXhpTQuheunyKlnbb2t2P9rbMw+vSzllf59F6miARWRETERaHy8FMw55alwRgE+isG1QE0zm81fvORWMKt/Slo7/ZNUphpE3MOY08fhdlLfV4rzFpklyvnHmLMx0PghHD+3SsyG2P1TEGp0WPsIJgnJYbahem4Vx7j3HYEU14r999u5TK9B72LApfxP7b+GOauulF7ENIAvTgHki9F1tz9SfchWXkr4/ybX3JPjAJwrq/slMY5nhjly1v+PT5ADARaVgCn3PWiNBC+8qdmvAe7/PJ7ZZyvujGYBvM/9xrxGPORV6TcYjuXbGt6OpfnuQBYbR3KN6JpiG0Oz0Duq/eZRKn9jOVnNBCcE8Q8z8Egxjx5qc9AyBqqewHiE8BDjPnKS+poEKUh2eQgA8KnEGMkb0VK0z7ASqN0L2ScB3QwkZSOaA1cejE9dRQWbQzExrTkofSDJ2DOLUuFJ4VPLi15OPfqv4pFq4AOUXkYffwZyH3tfrcP9MjP6M8PQtvSP4I5t3zUn4ZAEWP3WcSYR+Ybsi82iLGEso89hca5LxC7eS9FjG0kixQ+PZHfKWKMxjmKMt8i9Hyw9txLQh5SCVvhYavlIQdpZEqrRGmWspe+/4QmxlKQTkoTYkzp3n0BD0ITowYpndweSvcykOPNktLTBZHAioiIaAkcdGDceZ/+JJk/mIQRduP1kTKMSwMBg1Lb6wic/F3ZKYixq9RxzjRfblxbkwaCGQsBSS6ubHMsR+Xhp6D9gT+FGde0k3kSM8gdJq8f24PE2MdVGX0cAYB2a89/7T6Zkx7s7PkVTgjn332rKoddL5r32NNHBDF2d2jbjEZ9pALVgefFhFC2NW27iNYxtueoGZwTAOzA5wgMhGpsc7DnNWic18QkxSBrksrxdPb4H8o432itnAeMG0VKX59x5RyN8yQQ43zhV7JupTyqjXPabh4R1ifjWV4rUdxbBzUYbyEGAu0ArY5qfCDBOLfy1cSYNM7tTo9+RmJs6R/BvP90k5vGkg8MjKuIUl955efGuEVKB3QU38f2HAU2py1ASjMjveMxZteRlotbpHSIRJPQpDQ5GS+uT1w0sC9WBqP9jD3yoMgaX39Dnrkixh78UljOyN9K997/B2Yaj0yMD1jGuU0skc/1twgxprZzhcsy+jghxhL0H0COe+gxlqD/ghib0EQIevAH9B8AtNfK3ZaHcpT7i0J9pAJj0sPH3VbnYuzpozDnE0szeRAqYiyDB6FJjGWYB9lEaUre2YgxASRKMxNjrzbhrYm6l1ZHbhNjEYhIYEVERLQEYTC+BAulwagdOJCKAfWOKwhzV90EM69pN8gd39xm7GkdlFqTT34KBsmavOXWLogrJKX07Kby8FPQdstSuEqunPvmkFiPcYMY06XGfOncrD5SgcojT8HCr/ypQUiZZddEFhJjc63tffSFZbNjjCHhpq/R3/DxSSjJtp4hB0edl0ukRWRHFeUhaSKGJ4gVfat3AMAtmZfeW2OUrAllLd8FMfaSNM5Jbp5T4xrjE4oYm+GZLNnyYHit8OS09aKreyHOAhiDyiOCGJudYUtJ9ZDprZkkuIIYeyphS0m0blqF3uZgGgjc+UCOUrcNBB/5aBBjlnHuARJj8z/7KQid5oTvQd3zXcO118q8/3QT2ASUnRxJ6aAxRsrWsOM9+upIvDfH9hwFNrfNNc49xTFJ6dlmXuKPcL0jEjH6+EGYvTTj9r4keSByxCFAjCXAIMaSwDMa5+QQgNIPpXH+/j8QMmuVleZdHXCNc5/+AxDd+yrRvcDiAwc0zq/XxFgCMrV1RPPgIlbqnFuWSo9r7idrsZ966iic+/W/+gl862USY+3BPPHvsackMUaJ0sCr9txLWh7sPtuWS0qM2XFpaVpSR0WU2uW10ird++aXkssMoL01le4l13Gc6p7vmUxjRAIrIiKiadRHynD2kaeg/YHPwMxFOZMk4iA+c6betRfTjcA5Aw4MONcUE8drgMF56Umx8IE/FX01Z3JSJfLiHL2jmEGMzZKrRpyLayjBxOWsDE+MWoAr1ip/BhxpIFmW+kgFxqVxzubOBq6OcmbyHnTSJ0/numUpXP2hxYCBYFVZjUGHaSLk07eqtlNtyEF95pxJYuxpWPjAn8LMa3K6vKRNgOvrNTH2cZInlhlAB6mNaAZiIiYMBJQtCnuOo7eUvMf43tnEyTVRuuCzt5O8mHWd+Iau3hmEFGNSRikYjD7xjCJKNRlMPQ11uZWBIElpe77E8D6gjfO5q27UumflScuB2/swxknS3Ivqnn1sve86YxuzF9N8ptciJonB6EqWuQChjPPP3i7lkkiBp/nROKfyYNsGCEqMpfZe3PQYc+f6jCYVBsJraCBgJ+kvRyOke/4qwujPJRFyCyVCrBrI+00E2trRP9BtPY/Ge3ROrIoy3zy4MM5f/Vdna4+vv7/g3WJk25eiv2RAtvchMWYsOJhyMXHqtWSilEBtMbpPEGMhWcfxQemex2uWg1mSerECY08dhbxFjNn6b497V33gWjNTD2q4nev+/5So/1iOTKR0RNMYe/ooXP2h/y1MlJKHUS9WxCmCdGttQqdc3PpjmPOJpWYoAitP/HvsaUKMpaBetIgxmqctlJwQY59YquYwTh3ll7VjHo+xQKfsEGM2rLZRpPTdnzT139OGhrdmaMI5jREJrIiIiKZRO/YytN0stvfhvFmTIwyYIocAxgdOSLJmBQDIPluRXOIzkyvHjZGy8GIyiDFzcx8SQkwOeLOXXg9zV91IbA9CHqkBjMH516TH2Fc+o3KiZA4j5BEfn1BeTDMX5VS9zINENDlU3XMUADjMu/tWUkdyDSG+GkVpnG/8MrA5bSpPQXaJtqD3OUuIMccmseyV6iHZ1nffKoktmjgSVxeDsaefhQXSOLf96kxCiEH16WeNlXNz7kP95RhZOf+ySikIMneGwkGsnLdhrBWSN+d0q6woz/ihE2r1zlwE50aeHEzjHI0gc1OtNoLQGBOk9E1WjrpFsCwTp16F2rGXoP2BzyjyjzmpxTealBbEmN3GtEQctLcm3cZMyULbMIrIjurA88pgpNuwUfrpc3Ri71itTp8D3WKk5UEvOtCn7HitOOUwQb1W6O+azOda5qWBkN/4Ja99YuTPpdeK1D1m/07uBCA8CHE7F83P1n8Ad0tJOG/x/ejjB4XXyic+aui/UQaPN2ZECjjAudf+VfbFzC8HJG1p24+FNzfZYoSyrGVU9JdonItFCqb6Up2/1iZBjB00yBpfGfA77TEmglKbPST1HNdE6QKie3Z++F4vauN8FiHGfPoPAFB9mpLSYf3nIGV+jxj3kvQfkUxKR1wMas+9nC0UgZQHw6MU5/EeCGJssUnW+MgjmXftuZczb+9THmMBMpPeY+zpo3DuNfQYozMkl5dSxNjGLyXqHs17zi1LvYsU3Lq49tzLkpS+Xf5GJ/BmvvViBYrbxYJQJGz9iARWRERE02i7Zaka8JJ2c9SLZRh7+qgka2Yrksk1irVxPudmHZSanshnn86H8T9wtcY3X6cTsQp6jBHXfU2KmflTYiyUJ95PbO/TxBjNy7m2NgnFbY+qrZTO71xfywBcYoyU14ZBjNHtXDx8TUR2LLj/UzDnlqUGlQqcyIOcfE+cehVqz70EC+7/FNCIZswgTIW3FG7vW0BOrUEjlxr2eE3V2M5lmininak8LlBijHrsYdmt/NE4F8YYGhPcyBONjHHbOCeWHhLMOE0UR2eLOEczFi3UdeNYV7wPB861MSZIaa7qpcui854kHmPUI0B/5h5TKCIrcl+9X3lSoLFKDXQVJ/DpZw15QFBTAclQI+7VNTn1VDWtQ7xhgWkvJnKUuk1ionxS45zeE4g84NW8NikMBKl72ouYXqHvOLaHns5lG/uMkE4c6m9pb03My5ZCpC44p7r3B8rQd4le8TfGWpl//38iedljKumYIrKDMWj/yqdhxjULDZoR3ymhVd3zrPJaod/biw8MRF9ce+5l4sVk5q3BFTGmvXd9XlpaRlH3Fn72U0pvTOJN1wR1D71WdI/q9yhWxrkkSkP6D8CE1wrRPbuWjOhIY6SiPMZmXLMwUf8BGIxZC0Ih/Y8i3xqu+X+v9wQpd9tz7ClN1tjyZbd/7djLJjGGZC3njtwjMTbv0zQebPh5KmKM6J5vSQxAjDfUYwyJI26k09cWtwpSmnoyUrKL3k95jFmLJT7yVnvwfxlmSplPrCO2tRz3wrI9fec3kcCKiIhoGtRV1u4+cbLOa8KLaeH9dxhkTWh1uaq2lNxqpPWhPlKG0aePmGRNwuyl/MPHlccYBO4PIEip8YETBjEWLAcXHmNnH5UeY1lWa/YcgTZCjCUNPZMWMUbzdiabhBibJcvBLEYPJ6DTd7i7OMyY2waKnFTebZqU4twOSp2zZzwgrtBGtQiMez3MJcY5kC2i9F0Z5/fdDugtiGn1S9wLPQgX3H87zFik5YHJ/Gk9OAflMTbv7lud7a66DiLthZGyPDHqyyovLVmM3Etcq7xW3k+IMZI/I/VQQYjvF14KwjOT1lWXmxJjMxflyHNh/s8RTWMGWXTQp7mSbdxS5mvPvQT5B78ktjd7iUS5ZbwBUJReK7M+8B5pzDBjW7S4QMjJ2NNHlNcKbg0HJT+EGAaPB6HicOjWWtRVTYy13fJRlUal46T8nClSeuH9t+t7U72TdQQuPQglMSZ0j4EisjlSwEh+M6jusY6tV1vmZZuTezTe0kaQuXVcqggn94poCTOvyZF21TKmnwODiWMvQ+25l4RXOe2fkLwi310YqUBpmzDO9VZr0l9iny2f3dieZ+HqDy1WJ1bic6VhAJDMv6B078tK/pj1rmVe6N6cW5bCDOndrkMVcJ1W1qP69LNw7tV/JWOCX/+xL64+/SzkSQBwr/7LuiIx1nbLRxP1H0Bu53ruJVhw/+2J+m97C0dkhx07lhJC+EiQrJmnSEQ/1Y9E6djTR6U8LCS/aNKTzmGRrJlLYs5R+aEYl0Sp6zHGyf+aNCpuEx5juOXbT3OJ9NWnhe4tIHXEdDaZVS+WlccYrYs95ePyP9Q9c+GaGdeo9qBtzbk3f/13ksXx7kYksCIiIpqGudprfo8drPCkuF4aCGZ6e1ialEGpF95/u5PWBq9NQmn7j2GBRYyFyonE2IJPay8mRbJZ97mAAy8hxmiZ7XqXfmR6jNn3pu+1Afe0ttDQU/cQYzQvG2NPH9FbKTFvD6PHAeBCsRLIJSIJnvA4xm8AAOUfPgFtN+u4VwjcZovEEW6tpSdGcXtmQtAoluWWkvud4L/KMx/0O+renFs0McbtWZCET/fscDrqshohxpCwNcg5XT/OCSl9t55scg6GtyReTr01vWW2UAq0NYWabL75+3BGERmgjUR8YGI7dBlK0kBA49wgVoHKNYPqXjQQRAxCZgQdN+XuwogwEPIbv6zSMMyf5Ms5KGJMeRCq+IuYLzPSV/cclV4rmgwWhD/RIs5UHbUHYbuuIwGtI5LSbbcsVWVAvTC22wODyaFfW8QYaW9LrxrjE5IYu8ONtcKpIS/KcuG3UeZbgym31GucMTE2Yz81Y5F5II0msvQCUvVpNM6XEjJY501nFhPPCbJG9JemDANgv8kUaYTE2ExSDszTeJdhDgQxpj3nqdwiXcCYWJirPfcS6Yv9+o9QxrlatPHrP0jC9tyvBTGWpP+cA1x4S7e1qqNP/+WrMT6Z8FwjQkDCCt9tL8Lzv/29JGu+LNPLOLZgEijYB+EihfZi0sQ6PVyJg/BiOv8//5ckxsxZM1f3EqiPVAhRutC4szl9EiUZe/ootN2yVHnOc5U39TAXdUBSep7lUYmEMS0zxr2a9+lbYeY1OUK0MasE4l3p3qc/aRCENvnEAReEtLem1jNzfMLyNUam73w+ElgREREXDZsQUsa5jLNgg3bb9ZEyjD5x0DQQEoDG+VxCjIXW3vC0tgX33e6QVbZtLLxWHoWF99+hvJjcMuv7+DzG3PQC1GOMrnbp8pso/0gY57M/tDiYJwK3Ui7IEux1pAKlbY+mpotIhk/aqir2jisP9vbXRlETpQlhEJReKbLm/e9x01kXVYnuOWUl5WDg6h6m9RFHIWKMlpNepoix+0xS2pc/9RhrhpTGtra9DWl168UyVB5+KjHPiGT45EIYCM9C281Loe2WpeZvzEzPGMDEcW2cG2QuuQ+mN4xzKzg2pqfT+epebZw7W9S5WW6xcv6S1j2rrEY9uDbOKVEaWkhAYsw5pdSTd71YUbo300MG23WkC0Je/Sf3mDz1azj7xH8PlDIiGe4WJ/Gt+K+07ceiL07xuKZE6by79aExrqkribFiGcb2SLJGeVG7eSKqTx+FtpuXqr44iexHLya6kEDrRfX7wltlcUAA0b2Q/mNfTIkxWm6q/wCm7iXpP6K0XbQ19W736T/Icow+fjDcCBFBqLiykqCkHsz1kQqUf/iEiP+5qB1sr2zqVco5wNnHD8q4V7eq3yjZSD0JL0hiLPfV+9X3tsc1qGuYPsl8UQ6QyFVe4MQjlnMxNp3/n/8L5ssxwfBoB7OOjZEKnH38IOQf/DLMQkKKeFya3oHi5Mw5khhz8rY8v2vUYwwXGow66u/QY0yQ0kiM6fR2+1SffhZqx15++wXkMkUksCIiIpoGV//pv7VRXDE8KWhsAwT9jGSNbSD4JpFii9EZGV+I3t+dvTVG0ED4rPfIatvlfPQJbZyHJ6Xil0lCjJl5umVvjKPHmI5z5ORLPlPj3OdFhffBOo7hVsqAWUW/L/3ocZhz81JvuohkGEax9dsEbnPwyAO+q2dWrEBx26OwQAbGBQgbHxxEUOpZH3hPMMgqtV/rI2UYP/S84cUEoAkebl1Xlh6E9KREHxi4xJhdBmoIUWLMNoLszwAAo088A22EGAvpP4BJSqv7exqQgSbG5tx2UyC3iFYxtuconPv1mUTCFoGeFIuIcU6T2M+6usc0zgG0DCvjWL4mPMZ5SI7rxYr0GFuRiTQa23sUrrKMc1/+SAabXithmWcAUNr2qNK9JP3HPiBJ9+g76t7C+/6TkzYiC/xBpgGEcX7VhxaLsdl7pX5dePP3JlljpTX64oZLjAGExwUkxhakhFtgIDwIq3uOQv7BL6sDAmzY8w9b90IIEWPOAgUX5JUgpVdYJyWGF4Sulm0NENZ/kHUU3jPpgcgjXPjIe8To48/AnJuXwuylf5R4PedikWJy6New4D739D6bsG0Uy1D+4eNqHmT3jzZ5OyqJMQy/YSz8WfdA3ct99f5AgUX+qKvFbT+G+XevUJ6tSZ721T1Hof5WxUsG2/P/erEMZx8/CIse/LKzOO8QtxYx5isHnU+i7mXR03crIoEVERHRNNTYIjteXLm5MFKB0vZHYcF9t+tjc9XqC3c+V58+CjMXtcP8u29VeeBKA3W1B07Img1fNr4PvUo/elx6rfyBHLDs/HVMBhWU+r5PGeV0XiDjHKFx7tTRLfvo4wcEMXbzUjKYM6O++DKIMWKZ0LRq5XJ8EorbHxVbKRe1A8aTsfPE77GtfQNvRPOgZI29co6gxiV+Hnv6CDEQzFmaPZFH43y+d7Jkpm4UK1DabhrnqhyeGVmaByG9T32kAuOHnodF0hgLlQXvQklp28C2P1clEbKAbGHkVhpVRw8xFgIHQkrf/NHEtBEh6MDLBilfFLF3FkmyJkQ2AggvptJ2GXvHembKs4N8p7yYPm0bxVy+6+9s3UsqB4DcznUzxt4Jg4M2EHy6R8sOILY7lrb7PcbwndZxbM9RSYSsCOaJqMu2dkhpX3k48Vp5f3hrbUTzqB17CSZP/RoW3vepoOzgc75QrCjj3CZrUKfsxbOrCFljw5C13/7eKw+2jgIIXSlu+zHMuXmpNs5pvswcRWzdw999eV8guufzWKdlZ0A9xj5q/OaUCfzEmE//AWQAcIwxtigXLEdE81BkjRV+wwZ6EJ59/KA3/AZ9BwDpqfWM2GWw7I+85C59zqh7BjHmAQeTGDPCbzAzHU7zzyYQYzaU7gWIMctUEIsld69wyCtfO1b3irb2z/V0/gxkHNInBDHmbCefRogEVkRERNOwJ0E4uQiv3rnD3sTxl6F27CVYeP8dIs+EkaMuvVbsgPAh06m6RxNjqszcN42U27n2HIFFG78SvL+6hjEVEH7W+98T3LqE+Y8PPA/nXvtXY+DFYMG0PAyY2FLyuCbGaN40LX7UxNhHvekoJk69Ktva3c4VkQ32JF5NUtBg9ExSbFSfJgYCB8c7kT69xkglSIwBuM96TBoIbdbWWp9E1AIeY04hAODCSAmK2x/VJwRZvzOrLNU9R+GqD7wnaPjTsqkA4Bu/DGknpzFgUJRtjR5jQe3jxEshZdIbkQTuGCD1kTIUt2l5oL9RUC8me4tRKG1jxE/WuOmZSdYEyuEa52eUMRYWNdEXVz26F/LCrO551vUYC+ROSekk/Uf9KG17VHmtUPiMPtxKOf/Tt6aSeRHZUX8LDcavwIy5bartvW3MhbfIHGmcuz/rU9sATGIMyPc+WauPVKD8oxAx5srE6BMHZeydWw2jWXyWgdXldxfe/F+O7tHf7byp7iXpPwftQZiFoKuP+HXPTK+voFspE4aPiCbh82LyLSzhgiqSNb5n5vOwrb9VMfqp0LNryK3WqHtJ+QKYxBiFb96iibHbU/vL+khZ6Z4/ILwJ22OMlsNuR9rWSfqP15e2a2JsOst8JLAiIiJahJx0c/EZDQTlTUVe9H80EMb2HFGBUF3nW919Mya8h9puWQptNy/1pNXlYYyJWCvHXlInmanfrOkbBy73nAsvJl0OCLyLU7Fm/od2mH/3ClJ3nc6sY1nUccOXPeUwy88BoPyjx+VpbdeK8nH3/vgZiTEzvpBOQyd4mhj7LMyIK5QtAydqdPZRfVp6UqBxTn63PQjFcc4vGUGpqZec8rSTxnlx26OKGLM969TzlZ8FMXZGxp1w87XLoQwEy4OQBh7F7xQpTbeeWvVE78bac6bXCj0Ry67DhZEylLY9KjzGsBxW3qpMXHiuXXXdYqOOHPxpaawVlWdE87Bn2lxu90SyhjwzZl3Hubm9jwaANmOtiPf6SAWK2x/VHoQ+65zIdXWPqXuOMUHkw97ep09g8+ddIrpH20DJG7mf0r1P32qmtfoKALm93mOcO9vsVR2FtyaN92joP5bDausULjgiCTZj0wAoffvHMP+uFTBj0UKjzzGMYuyLlXG+QudD5ID2g0iM5Td+GdicNvP529dyQUip7VzWOEDfGTDDOMeyUn1T1JTUvfIPfy6IMboQY+u/xCiNc6TqbrYFtg16rSwyDmNw9R/rU9z+qOEx5pSFjGtU91wKOKJZqIUEy4PQnZVrcBDycBUha3zp8bNNjKU9seK2RyVZszA1LSXGQnVDXJA7KYTH2OzUvHHco8SYfQ3eY4LqXko5hO49boSU8OWty6HberovUkQCKyIiomlY02dhMB57CfIbvwKCHDIpF25dV5KTFL/Lt00aHYVzr51RpJGbUt9Jn1rzFZI3ndqYU//qXnFCkBkXyk9iTRyTxNh9dwTTqTlvUXgpLLjvDnWsNC0HpbOQ/BPb+9w62tMARYxt/Iqqk52Gfl/+IRJj7/HkF5EV9oQC5WH+XThZ8pOeAHJ737ZHYZ6Ms8Cs56XuIa0MjP+x4NMrAFfKVWpm/n1hpKyJsRQwYF7dUzGy1DYN8a62lFCCzgPOuThKfS85ncvwINT3x/tV98ij1JUHoV8uMbZG7dhLzsTU3kbJOTfjHE1j9/qpg0lmqm0OltFMCRvGhPfQWWkg2Eax4T3IxHMcffyg8CC8+aOmoUvugUB5UAQ+1+WkRJkgMys6BqHUPeUB6zHQq3uOwtXXLXY9CGlaeT+TlGaqPkYnDyB+a5Bx75ocMch1+6oyAY1ztMJpW3M7vqgjPa0t4iJBnvPoroNw1XVoMDL9nAH0s5bpz//2d1A7Jj0p7AjlMj/OuSL8kRjTsXc4UFmm8MXeMe5BZf4tcWqtIMZmk/hRdPYj/zFmEmOYF9cpKXnkGOcB/QcwjfOZ5JRSR/9l+rOPH4CrrtPemiH9B5BEyLGXdEgJZx4UkRW2B2jl4acMskYRjZ5rxw+dcLbWcnDHZgAGjZGyRYxZaawbhLyYdFotH0iUIjHmzA2supa2P+r3GLPHBEmU1t+qGDHnyN2NS+m4x+bOdurEuS4D40L3jK2UlAy2rg15a05XRAIrIiKiadCOUwTn1MY5TWONA8BBbjG6bjHMu3tFagdcHylD7dgpyG/Q2/sMu8BKX9r+qDi+N8G1Fr9XW0qCxJj+XB8pw9jeI5Df8JVMBgI9vjepDBzQGDsFC+6/w5uWoj5SljHG3KPUfdM3FefIS4xFNA/0rquoeA9iYu5bc0SJZ3D28YMqOCcTFjtJy4280TjHE9XobwDUM09vMRJkTc5I53uN7TkCVxu6Z0u6ftWL2ji3PSp9L72VUpZDGSrCytO2lvBkFLpHjos3ykPLIUnpDV8mJ/PIluNmWiSDqbemG3EmIjvQQpdbjI6ZW0p8bcuAAW9wKH37UZh/1wpFlAYPpOBCLusjbvwPHwlQf0vq3gZhnBtpDbJXyCASY2icm56ttJ4ANfTelca5Mvw98nPhrRKU5GEMoi/m6p7iRkZNYHTXM9Jrxe6LaULRntjWhrcmGpkeUoSOezp1lPlWgc+9dhwNRiEPXLE0EuRjvSi39913e2COYC5UjO46CFdfh8a5rUfmQ0ayJvcX91tpCSHFmCLGit9+VAWlpgseZigCQeKOPX3E8BijiwxmWeS49wQhxkL6L+8zKse92Uv/KFH/Oee6re+3DufwXFYfceMcJYWgiEgA7a8kWcOBG57OSha4+aqPVGB88AXlQeioByHZOedQeeRp3Rdz8ny5W44anq6N2/uwLKSPxevr6DFGYu8aXu3kHpxzTYx13ujUCQCMeLlq3PuL+x2vevtv7IsVKW3VyS732J4jrrcmaTd6bf3/pqR0m2tgTUNEAisiIuKiUE0ia6wOVnitnErwptJAsmaetUoS6rP1lpIwWYP3ECvnghgz7suNN/W5tP1RFe8hzSyo7gl7jNmoj5RlYHpCjCUMStU9Igixr63VeMZFPbGttcdYNOMvCuS5lLahgZALJDYJlfpIRZGIHKgRahIsDTQQNnxFrVgnzVFGnzhIyJrk56uIsU/bcskco7ght/fNk8RY2jxJnRhFZN4kyHTJGpa3JlgpbMO7tE0a50Z7+EkpvY3ZLkdE62BiS8mPxBajWYQo5SQN/U4b5zcZz4sSofj5PHpSfPWzRj7eF2dQ+gdcOc950tB7ycC4ihjDNFwG9DVlqP6W2Gqd34CxVjRZbMqcKMfoE89A2y1LYfbS6733py+xcv4qLLj3dqL/njZhYkFIb+fKBfRI3w89hObfvQJMojmiVXDOoVGsQHXPs4IolfKAz4vZz45rD8LZy64nfZhfNieOUy8mexHBvK5BjXPlze2mxS2CSJTOXXWTrItOYy9EXPgtGuefdWTdXhxgIMe9u/RiSUj/xbj3LBn3wvoPIA/GocZ5Sj/g170o8y2BafLv3Gv/CrVjL0H7Vz5jJPGRg3x8AkrbH4W5nTd6t3va11T3HAVAYsy4vUmYCu/dMlQHnldEKc3KV5azjzwl5EF6jJmLXOIQIyR4xwkxRu8L1jUAGHPu5wZRKg42oDKsgYfGzHNOPXZlE9s699X7AQJErS4QE96ad7te5dNZ6iOBFRER0TxkZ6vImrtWBFcb8F3E/yBkjb2aAebAg1uM1Ol9vpfM30uMeVYxOIhAwaXtj8C8u1fALAxK7UmrVqTQOJd19K2O0BUp5TEWKjMlQiQxNgtjvuAKkKf82NbzsK0T8hUnBLnEmL1CFtE8MDAuGghJuPDb30Pt2CnI/cVng2nwcTAAKG57RBgIJEioO70SQGIsC1lTHynD2ScOJHoQ0nud3XUQ5tyyzNpa6wd6EGbx8muMlEVAeM9EjAPSCxo+YiwEn7dmxBSAi5OaxMr59Y6M2XJZs7YY0d/thQHhSfFzWHDfHc5JTT7o7Vx+3aP3Oq+8Vj5rGRo2YStW20vf1ltKOCQbBpoYyyaXo5KUZlYQYgBT/3lDk9Kzl16vjnq364aYOP6y6SGUWpqINHAAdcLv3M4bLdLIO7Vx5MEkHU2IkzOfhUUbtTyYKYm0coCKMs6vTy37+MAJRZRiXnbZEY1iGcr/+HMZ5iBd984Gxj1fLdW499XPJuo/vivdyxCj0zfuqbJEBWgekqhsFCtw9pFfwMKvfCbgzY0Qn8f2Pguzl14v5cFHkIL6fF6SNQu//Bnje5swZYxBY3wCStt/DHM7bzQWS+zr8IXE2AJClNrEKi4aXBgpw/igIMZmzGmT3olg5a+vO/voU2rc00SxfbCB+B6Jsfl33eqQv2be4LS1INHoQoZJ9I7uOgBty8y2tvOcjogEVkREREu48D9/bxiMyu3WBw5Q2v6IJGtywTR4EplB1gCE+2kOOiC8TYz5ysSF264TlNoHhltKAsa5VVcRa+URwzgPnVKIwV7ROLcXlbj1R2bjXF7obClJs8giUsGAyfgfr/pP7wOziZXXCjEQktaJfQaCYyzJP0IGQqhMyq09wVDBezmxVnxWh0R9pAxnHxfEWNJR6oizTxyEOTcvC26tpagdy06MGd6axHVfEcERLSONrKHNK4JSHzDImmDzc0LWkMC4fnMJlO4tDOgevRclxnynpNk6M7oLA+OauueD2M7lJ6UdXbSIsST950CPUteHhNhkCaIhdW9RgBiLaA0MxMmZbco4T8b5185klgfqtTLDCrfgQ3XvUQCAzETp+ODzQaLU0CkkxmTsnbQxRBFjHt2zyy5Oa/u5CnOQ1v2OPmGS0iH9B0hfEIpdfetAovTqDy0OpNBPRmzve5XE/3QXn5R3XbEMFSRrrskF58QAIOfnR2G2JGu4kZPPi+mMJMbu8Tx7c9mCj09AaRt6jOWM+ZRbT+ox5nqs26gXK5IYM3XPTckAOIPKI0/BHNLWvm3hiOqAiDE27y47MD2zk047RAIrIiKiaTSKFb16RwOQBjC66yAhaxK6XK4NBIOsSbgEiTEfaeS4Me+1tvfx8GBaf6sMVduLKQFVDzEWquv4sVPJxjm5rF6sKCNolhUQ3v0s6ngVeowF8oxoHtSLCWMQGJ5y1MONi4C0NN4D/u6Lm2AQY/bvYH5ujBBiLN/uegRaZTqLp9Z03hT23JN1oQaCHQzbdw8a78FXL/pSWynvutVfN9I2lAjxeWva7YOBUOfcvNSI1xHDolwcxDYHYjD65AG/Gp/w9FNgXkeAxNiCu02PUpU1+bv+lqt73v5Mfq8C4y79I/d3MOWipoixO9y01kud1ibHPdtT1jCKuOsxxu005Mss3poAoPSyKHVvBo21YtUzonlUDwnj3OinPH2VkAdpnH/5M+bJmbY8yL/H9krjvJMQY56+lXOQXiunhNeK/N4m5JFSUMTYyhu95UA9QoztJcY51+U0/DrkBQYxNqfNLbNVj7OPPgVzbllmkNIheaxJYmzhfXck6j+AIGwpMRZlfOrgI2tCM+P6SBmqHqI09DjU9r4QWUOAROl8i6zxXVIfKWsvJrJ4FvL4U7qXgZQ+J0nphV++JzWtIMYe8W6l9JW7KnUvaWEOr6sXTVLa7yc2fREJrIiIiKZRO/6SMhBCwWLRnVgE53zViMWkfzdRp14rxmDgvwclxhAh0ggNBEqMcWeI0UND6duPwtxVN2dza997FM7/9veZVkpFbA2XGAu14+gTB+TpXEtJ3WwLSAC3c+lyTOfhbWoxtveoDs6pORIvgl4rHt7RIcZAkrCY1rrJ2ScOJBrnythhWveocU4XQCnZe2HE1L00ohm9VubddrM3CSOzK5/XCnOXbBUwAHg24tjavhNZqynD2J4jcpuDxyjGz/I1tveo2FLSeZOMO6J/U89avs79WnutYJx/Sjzqgw4A+PhkWB5ImVCSHd3zkRCyPPW3KtpjbM5sM61tJXDdF6vTueyykHsYuoft4Gs/cMc94/Q1K18MAG57jDlpI5oH5zD50qsmWaN+s9OC2mJ09YcWe0kjeo02zldodxWLjEIIr5UnBTFmhwAgeeOCiNK9224y86R9rLxGE2P3ODpBg24zJnUPiTFfjE5L5qp7jwLnHObddWui/gMXCzGaCJkd1H/Mp6K2c3mIMR5nOhcDH1nj9G0A3rhX3naXz0MRY3e5BzbZ15nykB6k/OyjJjGG9+XkM74r3cPFEprEukeIGAvBIMbsMlv6kUSM2WMDr00KjzGie6j/WO600FnvdkQCKyIiomm03byUxHvwd6EcODRGyqaBQIYt33WjIePcsCgEJgLEmA8+jzEBZvzD4WB01wF9Soln6DUMf/QYC6ycmwFdAYrbH4G5nTd7Vmu4cRVAiAjxr7uIE4LElhKdd9q0ISIr5t93uzYYfca8BCVrHHd5lV57NwmvlZXmCZ6ByZspDzpvn1v+hbdKlu6RvD2fg14rHkwQ4zxEGIk6MMs4z3nvTYGk9FTFGBOIct8KFtx3B1x93eLkbR8AMD5IDASJkJzVixU4+6jwWplFtpTYJ6Sh/I/tPUJirXiAk3oOcP43/xrezsV0v82ACQPh2484umfniwZIdR/RvQT9F0GIBTG2KEH3aB72uOc9fU3+7Sel3ecTedwWwFjCKYI0GYPqPkHWoMwHwwUwprcYUaLUgnpeDYsYC+SJMHSPQ6IHaqNYcYkxVQC3PKh7oUUKCjTO279yj1kfcMvBxyfkPOgm5a0Z0n/ONTHmXSAk6SJag7PLwCIb8bvRJw6SWEygZcyTfuLUrzVZ4yFS6XUi5hzxYvKRQORzdY+Uh7tWhGPYys+GF1PbbCeNWCtkyrNV6d51i916yRempR5jhvYb+cutlEiMUW9N2gbWmDK2xxr3yO/mOuj0ndtEAisiIqJpzHJOw/G/it9+BObftZIEheTBa1yyJhQUUmzlML1WmCe9fp194iC03byMBGM0occb22PMdpkRdcDBpk68VkRMC9fJl0vyjYEda8VfN7yHQYQY6XxtKLZSzr9rJcxQJIHH3cf5HJEVM9twRT7cfnXLiym8PIZE6UHptXIj+c11TWLA3O1cRA5sEkl7rQSMc6scQvfKMP/ulel1LFLdm+1JYTrxKw/Cpdc79bJhk9JJk7O6h5QOEy3RumkFV73/DwAAgiQlALjGOYH9PBgwOPvoL5Rxzjn3kzUSPmLMhjIQkoxzWQesB+dcE2OG7vnLfs6Ic5TcfzbGJwQxdlfGoNT7jgKvTSZ6zaIe1EcqUN171ENKuw2YRjpG+DHrA+8hf/nb0CZrAMI60qjWoCTJmixe5TYxBoDPkiz+4SlpHt0L6ioHqDz6C2i7eVlCnCN9P6p7aV6tlJQ2vMpt/Zd/j+07qnQvSf8B/G3tyzOidRjeVAl98bnXzsD8e29PHk4ZHlxxAHJ/8Vk1D0qKkTv6xAHvIoXxbOW1ky/9OigPtizwmseD0FNgHBscojRBtOyttUG1k/Lt9dYMwPAY89XLIIen79wmElgRERFNA70rqCeJ/lG8jT6BXkx0mwO5hlx34be/Mw0EjqvyJE/1YtJAWAkz8zkjL+6kBajuPSKN8xVGHmgW0HvgwJv/Bom1guVR92Eqj9Fdkhj76PUkjUVIye/Hj50SK+f33uGUkZE8RTlonKMcWWWyyyLe1cl4Ks4RM+pJy1MfKXufaUQyuOeTjbM//gU5tQYUeWlC/K0NhFvBfEZu/heKZTj7aMg4d9OP7cPVuxut+3s8tQwvJmsZ0L7T+KQkSpO29+k6U1Ja50jrqstjktLSGPO2n4DrrekSefh9vVgJlDXiYiC2lDwCc1faxrn83XoeY3uPAHBfUGqbxA8TY/ax59pA+EWi1wqFnxizjQRx/Hp9xDbOk6036jGWpP8AzIxzpO/s5MqByxhjj6QYY+Sa8Vpqmogk+Pti04spl3CteFGyRvxiL0Tp70JkDfe45GJfrHUvmcip7jsqdQ/jCzGwFwg0UVoOktJuTVlQ95yFFc5TdM8sT8NDjHn1H/OvTSaWNSIZIS6kTk61Ts8EoPyPj4sDm96vyWD9nMz5CBJjKv6nUR5uyGi9WDGJMaf8ZgYhYgzvzbieM7jEWJhwa1RFvMdwX2zObar7jgKbMxvm373CS7jS7+ojTZDSIHRkuiISWBEREa3DRzCBXEF46VVYcO8d5u/0Gvm5PiKPc75XkDXevAn09j45KNH5oJX2wpuSGPsvn1W/MZJeJZcfkBibdU0ubMvLvxUxZgdLp2WR9kujWIHRXYQYQyCfZ43tBjGWxD9wgNrxU7qtffNAUpb6SBlK337ELW9EKvQcw+/lJ1bvABYYXkw+soaLScoATlLmkDT+/M+qlfOCky+z/ja3lPjur/OtjwgvpoVfvidwdLZ5H02M3RxsB7zmvOExZgumaRwKjzHLW9MgX82218TYSn/duC5LY6QMlR/9HCJahe/ZCSjjfNWNwTQI9CBc+BVK1tjGvHg3jfOckdY3lxdeK2DJg09PfMSYX8aQEFWk9IcKzu/2teODxy3j3EeCcFmOMlQcUtru7D1EiPLeNetFrzn32r9C6b894TZURAaY4QTwOwDxVelHPydeTElkJlfyQE/v06ECiJzJMeHso7+QxnkOXF0y5c1cpJCF8+ofU8a5qXtYeou4rcntXA4x5ubNQBC2XJHSYf0H8GylDOg/fm96jIX1H8e90ScO+H6MSIX5TCnwcI6FTvgNP6p7j8LMa9oTvGb1A6wXfcSYdX+Svvyjn0ti7NpgegQSY/bhHJRAxpxxyzcSYywpQCcIGyRxWzsxRlD30KvcJKP0OAMAals7Jcbc/l2juvco1I6/FCznux2RwIqIiGga/iFDQExSTkD+Gw+4gVCBEgECwkBYprxWkuaE44PHTWIsIb3eYrQ6HHuHfB7ddUCd1uYZYwxcePP3UDsuibE0cIDitx8mxrmZtUGscQ8xFigv1tEgxpIdaGSco2XpZY5wQTzb1HOTLzxKvf3L96ScxscUWTO38ybTg9BHBnNxuiVwMOWBlIV659VHyoIYs4lSX1lA697V1y0Op5P3qQ4c10GIA/lRolQY5/c4XpK67bAt0WvlBvOkRKfdRXq1nQtJ6QCJDlxMvovffiTKfMtAw53JdtXvtUESlNrwrGXWM0MvpidNopTkqWMQiu+VPGBgXJ8RLb9HYqydnNYmyowpmfrTJcZ8ZdZZUGKMGzJrtZGso9K9tjajjLp99LtBSmNbYVsDKQcnxBi2NXkWnN6Di9Pazj76JMy/0z52PSITuGxeTp6X/Lu67yjMvCZHyBqTLKcyVH+rQoxzBj4doX1h+R8FMTbrfdeSfszWP/EZtxjpMAfMkQute3I713/5rLlIYfTHSKSh1wr2xWH9B85g4qVXte4l6D8As7w1c4n6L+ZB0mPsLh8xZpYDx72kk90iksBBEYRGJ8pUmIM2crq2C/HsbLLGtziAz1ls73tEEmM5kt6efAtoYmyl9TsH+z71otY9kzC26yeuVbonPcYoyWQuEALxGCO65zMSwOcx5owcRrv4PMbMqbyuC7Z18nN5dyMSWBEREVMGsYLwsCfeA0lDDQRcvfN5MVlQq3cBYszG2R8/CW03L5Oxd5IxPig8xhbee4f7o2VQ14tlKP/jz4THWIYYJ8JjrGBupcSsufn5wpu/k8TY51LzBQAoBYgxH6p7j0C9GPAYi2gK3JKHyqNPwsIv3ZNphdIgawDMOY1FPJ7/zRmoHSen1viISbQxatKtvRMNBH+eeI2XGAugXizD+GFpnM8N6B65/mwo1goHZwW9OiBIafvobDtPxkQ5TCLETUfhtHVE8/C0bf2tMozuOWLKg2knGJ6uaCAYgXExrZQJLtPiIoUiSjFvz+f6iEcerP6a7r5KJEqxSLJMmpT+jJPOJqmF7j2idY+2h+e9utfSPQinrReRlH7AJaVJG+I7eq1chaR0RPOgNrF8xpOSrFmAMYC8MimN5NoElP7hEX1whSE/usPHEzire48IYuwuT+wdy96uj5RhbK/QPa8MW+m1cX6tVVYw+2MOMD5wXBjn996uy+HrW6VcGsRYSP9lepMYI2kt/QfQba221gb0P6h7Ec3BJh0lMVjdcyRM1nCTuPETpWBdp58zykPbTcv0vWl6UiaXGAMrf1DX4CIF6p4mRq28SR0NUpqb9dT6IRYpxuS4pypj9AXmteUf/RzmoO7ZCxQ0bxDzIKF7d1hlBKO8BimtvDWnJyKBFRER0TRCtu7Y3sOZDcZzrwnjvF1OUpICNpuTlHSSgBJjWQKQJnmM2UDjfHYTxNgCHzEG5vYPQYw9Lomx9DpSj7E0NOUxFuEFB/DGL1BeTJSsCYiyNs7TvSPqxYomxpKOczaM8+szycP515AYM7eUeE8zQ91beZPHGHNR3XsEAMAkIALQpPRXYEaIGMNycI/HWAKaaeuIjECD8R8egYXo2RowoLHbre6zjHM7LSEKtHH+gBl7h5IJ5FqDGAuUF4Hb2tMIfM7p9j6TKPXGi2YppLR1jSalTd3zliXLuEeJsX1a92Js69agmo3ITr1YhtFd1DgPXSQgvFZugDlonHvyBCbkafLUq1A7Logx5pNzejkSY/feATPpQTqB9I7uhfpjuTigiLFQvkRfHWLMuoZOu2qDx+Hcbwgx5slPkdLSq9xo64R2wbY2iLGIlkDPCqgXy1A7fiqBrDH/LklPZ0HWJKet7jtiEqV4b5vAB4sotT3W7fxBE2Ooe9yTBj9PvoS6R+LSMn/e2Bd7SWmL7AYOihib55sHcbPO9beE7i3a8BXjdyN/UhbqrTmdu/lIYEVERLQEm3BCsiabcV6Gsz9Gr5UcAABwp9fW8Bvn/q4bDYT2L9/j/Z3C7zFmOvbSFZ7q3iPAIavHWJkQY3YgVDEi0TpjINRsxNjxsMeYpxzNeIxF+MEAHDI06EHoEWVK1ng9KSycffRJTYylTMyp10raqUwh4xzArR9A2IvJd59zTRvnD6uV87TDdJrz1iw35a0ZEUCCwdh2U/rWBW0g3B5OhAZvbVIb5zZZ4ylHIjFmQRBjh6XuJQelTiLGfDI6PnDcJcYCpAXqXu6/fM711PKgGQ9Ce9ybxodTTRnw5LQgWYOgROngcTj32nCyzMtrLoyYxJjzzKy/lXF+87LUMSGT7uFt5AEBmeYI3OMxloB6sQKjNjFm5UdR/sefuW0dqGvmto7IBCR76iMVKH37EZiHJ6l62p8O/9W9R+DqDy0Oy4PVB9aOnXLkwTiwicAgxoIF1+XwEqWetJoo/VxwcYDWUcS9ksRYIE/E5Eu/9usepqOeh4SUnkFjANP0JP9mxr13OyKBFRER0RKUsctFkHJN1szxrrrQFY2zj/4C5niNc2Z12kwb505MD31/Oigpr5V8u5HMdfH1eIxZAwZXowzAudeGhYHwJTTOmU5rr9aMT+rtXPl2tz2AG98ZxJjP+CH5N+hWyjZr+47xWbSl4TEWjZqWYTcdGgjtTZA1akKYgureI8DmtjVJ1gjjPM3jMNVrhcDYzmXBjhMhjlI3SekkNGOca2/NrKR0dm/NiARYHKWI/5HNYDQNhFxqemUgZIhXZqycp0AQY49mJvCbJ8Y8HmPegoATayUJzS4ICWLsszAjyvxFwRhKOW9RHrKe1pZCjBGMD55IN84lxKExB5vQvYMe3fMvhDSte99+OLvuNUmMZW7riKZQ3XMY2m5eltgX4/BfO34KasdPwby7VqbmWy9qYmzWNfn0cqQRY1bewmPsgdS0ACL8hrcvJh2A8iLe63qMhcuR4q1p3cMgpVPgI8am85Q+ElgRERHNw3CtnYQi8aQAzsXSheMGK3zmq3sEWTPvzhUO2QKEFAMQAWnHB5+H/N+QIOUeQgyvUV4rNCi18c7Vy1w5Z2YadY3c31+swNkf/0Ib51hWDuYyjbxUEGPXw9yVNzm/GW3DtddK+5fuAYMUA6ZWgFUW45NQVAHA2528zM9cE2PY1r7nEtE03G0Onsm+MUlBA2Gpp/3Na/UkxTYQwtv75nuIMd+W3OYMBJMYC4GBOEULV86duFeeOmjjfIXxfagcWvfSjHPW1DbmiBTQlXPlxRQyEGgsEm2cX5XJOM/uSWHqXjpZM/rEfpi99PoEA0HLXvPEWEavFUgixlzZNz3GUjwIA0RImidmRDomjr+U2YupXixnlAfxXPzyYO49VSdnpuoeAQco/ePP5GltNlHqykSYlHYnCsI4PxjwWrFjEgnda7sI4zwEXKSIXuVTD/RiyjpHqO49CvlvPJAttMeeI4oYS1toQ92bl7EcYoFwZeYQI5QYSwpf0jwx9ojnpMRwOSgpbZeD9uFC9/YnE2PTDJHAioiIuAgwGN21XxiMK28i5A8HY0LDGADnIt7DCSRrQKdRgxlTG/F5bRKK/4CeFKHVGu1RpcmalWBPBG3UixURlPpvHgDWNluTVcy6Tn4vAsIvlcSYlR8l4YDB+OETMPnyq4I0wrQGyaXrqomxNWLgVe3GlIsxvZ8ixjpvJvdmnpckxk5QYowBWPlFNAFCmqptDurEKK5+M7adchkY9zfDsGDt7a43IL0W5HHOuw5A7j9/VnvuqRe3/tbEWNtNS53fOE0PTMdaWXuHk9a5Vp6UOO+uWz0nJTLnPooYQ6LUIZl1XesjFWGMUd2zykrvIYzzpWYA8EB5tLempxwRLYOPI1mzWnu2AlgLCLrvF8Z5u4hBCFq+nefBdfyP/DceMJ+nrw/36R6AP39ue60wSxZQT0X56iPEOJd1NAwKq+xmrBXdEL5rlHFO+wA69pF21MSYeXqus0AhoYgQKvMAqQZiRADYFxcrijQyT6z0X1bdc9T0WrH7epU/V14rC9YiWYMyT2VBhBioFyuaGFO6Z/bB9F7VfUdg1gfeY84/7MqBruP44HHTOKflteqKfbEixgL6D0CIkHutcc+WY068Vv7zZ8VcL6T/Enham9rOFUV9SpCNrNHPAsmaLAtLQh6GYX6qpxYj8dgeyLY4oIix9G3tPo8xDOVhE0jCY6x1YozWyYbZ1swohyoXWUw3t1LGOTxAJLAiIiJahtjed+43Z4RR7CFR6ESoXqzAaN8ByP3nz1leK9Y1aCDskkfKrrzZTUejTYJcOafEGAMjT8b0tWggzO282fWe4eZ1ABAgxvz1VHGv/obG3mFWvvo6RYx9aLFzXxNMeK28TIzzlFUjTYzlgukimoBs7ureIzBzUc5DlApw9PKTBOXYviOQ/5sHzEyUTOB30mvlv/1cr95Jj0VvNGYmiFJBjN3hT0PKVh8pS93zHedskayMke1cHa4nh2UsTL5MjPOQDMuJmGmc0wmhRfDK9jOIMV9ZSd7K4PybB+TJeDpN9Ea5CHDRF7fdvAzmYNwrjxEqFikYkYc7hEFgky74LOSYUPqORdZQQ1gZvFwa50e1PJB8jHcJ5bXyNw/oPBjRP+seSvfep41zNGvsvAUxNkwICN0OJnGMHmP7pe7lSFqTuMJrhMcYeq3QhQeSTo5nQW/NlPEhIgUNvcVILyRQltF8VfdI49wiEfW7lol6sQLVvUcg/zdfsU7vs3SF5D3n5mUw56YO8hvX16h3poxzMTaZ97VfRpwjulhCryNlUae1+epI9B9A5F07fgoWKVIazHrSv4ESY9cm6r8YE44K3UOZD+h/RBPgYtupS9Ywsw8HMAjKqz5UEISUTx5oHzhS9hNjKg0zZE8RY84inpWehzzGmJG/8mRE3VMeY6bdoRZbZFnUVko67hnl1p9r6DF250qPTNpjQoLHmCPHDKr7jsDVHyroeZA9dkxTRAIrIiKiJdSLZRjbd5gY58kwjPMUCGJMGuc+kM67XixbxBg4nTudeyIxNi/DFqPJl1+F2okh4jEWhkuMJUOd1kYHvADqxTKMH7aJsTBMjzGBaMRfPCZf/jXUTtgGo88DjsngnA8T49wynq3P1b1HYeaidk2M2RM28jKMc/CnoWUTurcMZr3/vfo3ZqWTeWiPsTukQW7nrf9W27n+8+csL0kf2cyU7omVc3+e+BK6d8okx5GYtsrkeK1wsxzRGaV1VPcdlca5NIqDJKX2pEDj3JQd+ZmQK9W9cuXcOK2NpCd91sSJl6B2fEjLg1fmtVxqYowYCIbxwwHlU3sxrVTfifTEUGA+3fPdX9dPEGM/I7rnKTPRQ+UxZntJ2tdx9BjbL3Qv327lBxAtnNbAgEF1/1G46roCWaQIv+rFCtROUE8KnzxIcAalf5DE2KIcqAUKKo+yFGi4nvvNsDCKtSDKN9Por4+UoSoXS3zjDV3EA2BS95ZKYiyhzMCEcW73xTaUcS48xubdtVIGpQ7rP9bxqg9c6+9f6JyFMUmEDGlSOrHcEc3g7BNkkYIQh9qTU8tb7dhLkihdAQ6xa6ExouVBEFLc6tcIuBhvrrpuMVm0IqD9MhAvpr/5ikVymQQPl7pFSWlBzHGXrJX3EaT0Ge0xZqRhxnealCZbKX1kF9bR8NZkbjpSl9qxIUmMWSeJqn7D047TBJHAioiIaBrBbQ4BCK+VdjJJCeOdIsbSjFptnH8+YyDU/W7cqwCEx9gQLMxEjE00TYxxAKet45aSi0NjhJI1udT0TQelPjGUMfbOxNTonkcc3hbdk/dJJaWtcnjbOiDCJjEWMVUQBsKQx4MQP5ukSukfcEtJ3snLNjDRk2L+nSvJT1b+0lhQAZv/JuOWEkqMJRjmAAC1Y6eIcS4RIN7qxTKUvvNoiu5R4/woIcbcNtD3kh5jqHtOMpsIocSYtaVElj0prktEGMKLaShzDCBtnOcCqQhptO+ISYw5BKV+rxel14qhezYRhJ+Z1L1lllzq9HT4V9u5gvMxStDZxJibhsqfJsbsvthHjJ2y4hz59R+JY9XW0at8SlHdewTqxTLZdup5EbJmtG+/RZSGx4Wzuw4QeQgQvPI5Cy+mIR2XFgCMhTYqD3RrrVEOf3mqe9CLaSUAY56FOX1dfaQsSOm/eYAQy77xQ7z0uOcrh0scK91LWKTEOlb3HfWQ0qDKNZ3XpSOBFRER0TTGDx+H2R/NFoMg1TinKyUh49xeIZFIJcZI+szGubym/N9+Bm03WYFQA/XM7DHGfVsp/eXFv0d3HYDZHw0EhLeAbe31GHNW9COawdi+I00G59ReTElIlAcPmiFr3nZi7JrLi5SOmFpUfvxkZoNRGOeLM8tD7cSQ5UEYgEGMZShHqnFulsNvnIfz9hvnLmrHTwndy0jYGsRYSp9R3U+3MUdMGThXns5vlzw0TYxl1b0Ptah7KXhHdC9I/pl5Z23riOZQO3EKcv/5c5DuxSbImvl3dXrkwSV5NDGWJA+asB3tOyB1L69/cwhegVFJjM3+6A2BcuvyOH1xQv+qiTHbc95fx9G+/U2Oe6ey6V5w3DPJtum8Lh0JrIiIiKbRdtMyc5sDgOXCC3KbgzTO//xzOhg0gJ+QImTNnBuXmWmYmQ44Mc7Xrvbem16vPMbWrnaDUtMVEHkvhxjz1RNX5XHl/K8fCJeD6esVMaaCELNA/oIoVPEePPVKbetIWk0Z5t254m0yEB5ujRjzwSBsk4gx5shES8RYBuP8cvLWjGgOC+69Y4qMc92Bt2ScewwEn4dRU7p3JRNjx9NJ6els2LQMxmDB2uynSp5/83fZ5GGEGucpeXNtnDele74tV3Y5yPa+rHLZMiltwNXVi9W96GE4dcjaT43u2g9Xf2hxpl0GF978PdRODEliLB2CGMsul+nEmAAlxrKE39DE2PWpaWvHT8HkS6/CwgwLhC4xllKOJoix6YpIYEVERDSNLCdyAACU/wm9mIhx7vWm0vEelFHsC2oq0yrj/M99xzm7GN21X3uMUU99TzBoxzgPGQKcC6+V70hiLGlQknlU9wWMc48fcH2kIo3zbnPfO5bdQvmffgZzbjKPUp/W/sVTjFm+E8EsgrCO8R7uXBkmbMmruvcIXH3dYpi/GuUhEA9B5l07MRQmSq1rS//wsNY9Jy030joeYwkvQ/dw5dxXP/n36K790HbTUk1KJ5DHXt0LkNLY1l5S2ndtRNO46n3v8csYQX2kIsiav37A9B6ibU7ijFT3HhHyQI1zI61+Gca59RzpCU0ol0r3QttOSdmCHmNknHF0z/YY88kXEmM3LXU9SzzjmWmch/UfF0uctg6kjV1/a7iKxI30ti0AXHjzd1A7PgS5P/9csP3pq/SdR2A+lUtr7kOvqe7zGOeB/qv+ljTO/9pDQNjX0L4YY845ZddlmfDqnn8LrEGM2WMCANgxidS4RxcIablJuUSMMTLuqSxN/Y9oHVkIldrxUzD58qsZPUorUP5vP8tO1uw6AFddl5UY+90UEmOteIwJNEWMoe41Q4y9nI0Ym86IBFZEREQLSJodi9+q+47ArPe/J5v78EhZT1IQwSVkDqXvPAxtNlkTgEOMGZNMeg+mA8L/+ecDcVxMjPYdMLdSJgADwjsTAHXqGvmqNgml7zwsjfN2WTym01lNg8TYPHsV1mlDEfA6onnYJ9QAgEWAAlT3HQ4b59ajqJ0QBoIRnBMn+tZJTfWRMpS+87BrnBsF1DcwjHNfefE7RlbO0UBIsXwFMUZ0z64f03+j7qVOCDlXxFj+r7uTt1Gh4e9rayuN+rM2kXz/iGzwnGom+uKlfvKK6gvzkDW2AW3IpUWMgSedYRQfTjbOyWfUPcM4d9KLP+ojFa17Nint8Qx2iDFfm0gY416C/uN76TuPuG0N4E3Lx6PMTxlI29ZHKlD+bz8XY/M1eW8aCvSkmLvyJr9MEnJHGed//nlXJqm+oO59lxBjQTkGkxjDU+N8oYJkWerFMpz1EWO+Uw3BWqSw24KOC1yT0vNCp9dhWsBFCmvcC+g/cAA+Huc2F4VAf6nH5geAtbX5ZY1cj/Iw+6PX+2WSvAuy5hVYSMMt2PnLl9I9utU6If/RXVL3VtwUyJOrtMpj7M8JMRYoB3BCjNHFM/saCaV7q1cG+wldR01Km8SYq//AxemR0xWRwIqIiGgBtPe1DV4OtRMvWW7tzPMuZjQi/gedpNhpzPtoA8F2mXeDLBqrd05aj1u7NBBE3Ct7hDHhEGNe4P7+CiHGcsF0iNE+9Bjr0F8GCD1xMp7cShkkFuV++doEjPx/f5RQ3ogwfKvP+plkJmvAZ5xbeVvPurrvCLTdRINS20XT37m6F8iXMWmco9dK3ntvuxyu7tll13UUutcNrv671xlESBIYa7qty//0s9R0ET4kk5nNbHO48NvfE3lIAQe1SGGQBAFoeejUXwaIWLW9jxrndlrytyBKl2UiSg1iLCEdlsPRPZXevUDp3l2dbmZW+evFCpQe+rmbLiIbbMOcYLSPGufJc4TaiZeEJ0XGOGjlf5LEmM+r3LqXQYwBgDrR0APDOA+QFLS+jsdYArweYz5w4rXi8xiz0gJgWwd0z0LtxEsw2rc/NV2ED+ZCHAWephyUBwyPIa8zvJgsQtKQN0bJmu5s2/v69kPbzcs0MWaD5F87cSpZ90iZlMfYWosYSyiHIsZ89yc3wXEv9+ef95bTvsbrrUnJNoLqviNQO3EqXNB3OSKBFRER0QLMQILuyRmH5SQlb11D38VnbZx3eNKYyzvaQFhplcFXjiRizCbgGFT3HZbGWKcnb/M+rnHuT4f5a4+x96Sm1cTYaqtOYKQT5SjDaN9+uZUy57SBDSTGIlqBnHV5kEyUulDGeUYDwdxi5MquPla6THQvKW9xjenFZE+QzLJrYsw2VNyJVb1IvFYWtYNuO89yLTDLayXZKNReKz4ixO1jSt952NwWFDElSDUQCJBENLZaJxoIBzRRysN6B6CNc6F7JFOP9ymAMBDmrrzZ9SyhkH+7RGm4HH6PsXB6Me5ljHNExz1fvch3OO7NuXFpar4RPvjmKQKZyRoAqI+UxGltjieF/56jfQc0MRYsk4Cpe5R88PXFZVf3jHzdxTNNjCUT2NpjLON2ru9YHmMJ0G1NTqQLAE/GmxfjBbUGa4ungPD4Gdt32D1EyLhWfzz3mzN+eeDgkKt8fNJPlAbkQnsxrQjLDjMXjBN1j+vyGKS0zsx7WVPj3gjVPQ8pbd0Lxz3V1gk6gro3nQ81iARWRETElEIb50heJU3iDzdxnDMaCN0ZDf/DCcSY+W4SY8kwjfOkcqDH2GFinCdNxBjZzhUyzk2yTniMLYNZ739vQhm055pJjEU0B5ckBdDyoA0EP9moJyn7LXkIe81p4xzlIcnzUcuDqXs+spR7vFbssnD1nSalu0kdbeJY52F6rSS3R+3EUILumfm6xFiyPmlirDMhXUQy3DYOb3PwX+83EPyzc+G18oplIPjSMo9x7i4I0L/Dxrl7jal7yeQugBj3BDGWd36zYQYAD+s/gE2MtVu/+xYpBBHSNo0Nm6mB6a2qvZg+D2mECgBA6buPBrxWXIKsuu+wRYwxy+AnBGVI9wJEbzIxZrqAaOMcvbmTF220x5hdRwpz3Ju78manTnZ6dzuXX/8Rpe8keAhFtAgO44ePw+TLr2qPUmbLrn6vFytw9p+fhIV/tsb/HKxHaBJjyWzm+RAx5rmHiEtryQPz9fV6kULoXifYcyR9Cc4/mhn3QsSYr9zcGvds/TdBdW/GNJb5SGBFRERMGUyyxoLlLiu8Vk5l21IChBjLcuQyEmOrfUaxWw7TOPenUy7SBjGWjOaIsQxxjqxyNH1CUMa2jsgKprY5mMc5+wxpuqXERyKaRJN/5TzkXcc827maIcZ8Rr9pIIQ9xszJrElKJxPHLintI9tMQ89PSrvpm9G9iDSYz0XH3sk7v9kvbZx3gl8/iMyPlKXXSjewOXNS8qbGuX2Uuqt/rnFO05rXJBNjbrld49xfP9M4t4kQv+ybxJirE/TaZjyEIvxg6n9inI+k9cXmy5SHkOyId1ce5G/cfw9X99zyuvLQaeXj5k1jEGrj3J8W62iOe2E9dce9pHLQtk7qX8DT1hGtw+xT6sUKjB8+YcqD8vBz38/+825ou2kpXK28nW1Z15NpQYy94iHw3edbL1agooixfKDM+h5ej7EAuas9xsj2PrJwp/JWxBjVPfv+ZlnMvjik/wJ014oY92yPOHM8E229bNrvpogEVkREROvg+iUMxlM6UGFonzdHr5WdMG/1Cn8wRit9dd9huOqD5LQ2X3qOeUuy5q+6w2mZ/lz6zk5tnPvKQD4bxFioDFjHEbmd66+63VPSPC9lnN/YkVoOZZz7ymGlVQHAV2dz3Y/IDnflPAzc7qkmhPYc0IJpICRDGOevaAMh4RlrA+HOiz/O2boPurUnEqXkGi8xFii7Q0qn1DFISkdcFJoxGI2g1F6YE3kjKHUKTGIsGXo7lx1rxTVqAFrRvRApbZWjRd0z29pfZrOt/Wki0mF2K6IdtcGYLg/oteLKg/tMUB6CXisWMARANt3zxN4JlMXrtZKAixr3EsoB8PbpXkQSTCIGDxHSW62TCEpBlHIAjxeTS1J6iTGLoKHXou5dfV3Bycu+x/jhE9JjbCW45TTThj3GbEJNQBNjN1u/uelNYixMXrttnUSMib91W9vk3/RDJLAiIiJaA/ViKokYBPm/ooFxIcE43wdtN6Z4MSEx9nyKJwXpw5UX0+qME7H9hBhLIXYyezHJfErf9RjngfGmut/jMUbTcgC6v18RY2mu2hygup/EGIvkVeuwiMILv5UG43rPiVGez8pAoCeZ+fIGYiBkIWzRa+WvuvUJQQD+dy4NhBuXweyPpJwQxMkJQV2rE8laABLvoWu16yXpucYhxnzth2395u+FtyYlpRPqWPrOw9B24zL3hKCIJsGM54Ar5wvXBuSBEvhFSx5S5EcHxr3Z/7zId8o4p7pnpaH3KX33EZi/eqW/HBYM4zxpcYATYsyne568le7ZQYjt9NwipRN0w2zrO6PMXyysdq7uO6wNRt8zINfVi2UYP3zclIdAHwVcGuc3LoOrP1hIzBfA8lpJk4eRMpT/6TFhnCd5rMs8lHG+wkOMWWU699qwf9zz1NUgxkK6R96F7lX8nvOWPCtiDNs6Ysog5OGGTETpud8IeWj/szWpaVEenBiEARi6lwKlexkDwrvEWBh6K2W2ciRupQQwZNklxsIQxNipTG09HRAJrIiIiOZhTSZK39kpDATZYXNPGkR1v7V6x8PzbU2MCbLGmyX5crR/v7G9jwOAEzxS/ieIsVPWoMR81RPE2HcfhnmrO2FmPlAOcp1BjAXKqvOumMY5JrXTyi9K390pjHPZHkl2ytj+w3DuN6dhXmgrZUR2WERp+SGPJ4VN2krZHu3fD1d9cLFrIHgenkGMOWVgTllK333Y0D3jd8tIcHTPBy7uUy+WYbRfGghpE0IOMNp/QBrnNxjf++qoVs67VoeVX0LEe3hMECFJhC0SIf0WMTa9FymnDIZxniQP8jk077UiiVKaj8fYrY+gPHi8mBg48qR0jxoIzJOee0jpQN0QihgLLdqQvB1ijP5upa8XCTHma2tLprXXyvXk9yj4LQPJmtelcf7FNS7hQtNyAD5he61IUJkg11b3HwbOwSTwMT3JF0DIvEGMWeU07sUAzv4kgRizdEoRY77FEgv1kQqc/UlG45xL4/wjAWLMugbbOrf+c/4yk+8UMZZxoTIiBaR9FVlDg6UH5EeRNV9c4+5g8FznJUoDz/nca2dM3Ut48XFJjK24OVM5FDHmW7i26ziC494DflLaehmktK331rVe3bPzlRAeY7th4Rfv0aR0ytzp3Y5IYEVERDQPMjf2GQgB+1l5UuTWf8HJznY4AmAGMRaaPyLQOHfIGs6da/Xq3QMG6cZBpNVlYcBBG+d44oe7q1/Xg3qMcSO1WT8OSIztzOwxNiaJMXraTqgs59/8HUzQrZQRU4bRfu3FZLQ7dz9OPC/ImizB8xUxJo1zjhkhcYWsJtflcIxzqxyIC//2+yAx5sgp55KwzS6X9WLJJMY8bSHqWJHEWMZAqP3CW/PqDPEeaidOwQQhQlT7RbQGKW98YhJK37UMBEziuay6nxgIAR4Fn02QGKMLD+QzGuezl1ry4JnMjx85bm6ttQttGAim7vmSU6DuzVl5szchvebCm7+H8RApbYGDIMbmrV4pAvQa+u9mLsY9y2slCv5FwzDOr7Fj77gY2zcovFYyLFKg18pCnyeFlb4xMQml7+40iLHgXIj7vVZ8NjqA67Xiy4/i7E/6hdcKEmP+6gGA1r35d630/k5FVLd1lz/wtrUI6fVamebG/FSgXqrA2L5Bc2z2tal8HOV/+pn2YgoJmYSQh1f1mBB6XnJMOPuT3ZoYS8HYfkmUrvR471p/K4+xL64x09DyYHc7MSHGPZ/HmKfsDimdkN4Z90JKrYixfjEPQo+xKOuRwIqIiGgBsvOsPY8xCO50fkYiiE6Wyg89BvO7xJGyof4Xrxvt3+cYCK4tJL45Lw2E9vWfd3ak+8YFNM5nkAmhINHEPzToOXBpIJQIIWWWk/6Nxznn/qobZi7KG/5c+lom/2eKCPFtpbQXYjHu1YK1qz27M5lRlnqxApWHfgbzu+5U++rj/O4iIRtvzPJiCu2UZaDlIf9XD8CMOW3gxB6xrtFeTNeb8sXdtLXnBVlDiTGVhkz4US7L//SYlIecUwYGoIheQdgK43yeDEKcNCc8/+bvYcIyzqms2XpS+q4gpUOn59C8x9A4TzDGEPWSIMYWESIkYRdzRBZIORrbNygNhFvcJNbf514/YxoIAVKHAUCjJgyEOSvsWCsAhguq/CyIMW54Mfn6d5T5kMeYImyZ7uvP/uRJ5cVky4xdR0qMJek/yHKUH3pMeGtaRIjvurF+HfdK6z/3ptVbKT9n5pdwglVEGoRMnP3Jk9B24zK46roCcMcd2sT4keMw8fIrwmuFzB8o1DyoJL2YvtgFszJtoxp0vJhQ5pjxjUf35G82X0B1b+6Km2GG9OhIkhqDlDZyN+HoHvEYs/Ufvzv7E7qdK6z/AFr3cKHS0P8o9i1DxGLa6Xo6+9qUi7F5Zr49fFCSTgr1YtkkxlIG5fJDPzPJGkgjSsPb+6h8CGJME6XePBlTiwboQTgnzYMQCDH2pS6ZT6DgjAkPQroglAIfMRbnNZHAioiIaBGarHkAYM5sAHAnSZoYco1zml5fJ3p99KRA41xP1vTeD3ENl2TNY4bXis+oQYpnzPJaUWk5yBy5ugsaCO3rPy/LwFT+mB+9H3pTzVqUB/Tmsg0r/L+6f1B4jN25UuWoiTOZr7y4UUTjvEcaY8y4P1j3Qq+Vto/eALbpkzIXj0jAud+cgYkTpyRZYxoq9nNu1CYVWaMnKdxIQzHmIUppajofqhcrMLbvsEHWGNdwUx7Qa6VNejGZOqfBAGBC6d6dgCSuqXtmOSqKlDZ1zzayFDF2nal7Pv3ngMTYKWhf/zlD/11PTfEuDoUIE2MRLYBr4xz7KV//it8JT4rdhieFrw9G3anKlfN5apECe00X534zDOMnhmChNM51P2wUV3xTm4DSd3cSYsxMw7AmXMj22P5B4JzDvNUrDVkzS8KUzFcPH4f8X/UAEFLaV2plnN+4DNo+cr3R+drpOWhjbAH1IFR3N+uIC0K2MYb6H9EqOIxTohTchTDauq4HIbdGZpqz6UlhyxdNB2DqHp0b4PhPpUlvMVoDMwx5ML3KsfxV5bVyi7dPpX+fe/2MWCD84ppE/ecgiZDv7lTGeZL+Yzk4R2IsrP+oe7Stbf0PXBqRAaN9+wRZoxZT5cxdtalu6YmXX4UJuZgK4JcD9XdNeO/6QgD45iCKGLPIGt8cBImxHPEYC/XDDBghxhY7uWk7QHwaP3xMEKV3rnQWKezP9aImpWfm241ETr/BufAY++gNpveuryygA8ILb02q/1HcI4EVERHRNBrSQJi3eiXMzOeBcQacMwAuBzyuBz/OmfBiGinDvNWdZJQTvzOg12iyJv/1HpjRNkemY8CFvSEmbpyr7zEgvAhKzUh6Wh5x7cSJUzDx0iuwoOtO874cQA/Y4r1eLAtibM2dMGtRXt2XWeXB+431YZyjW+T3+jft2yXKdeHN38P48SGxlVLmBYDl5LpssjzY1jPyOeveYNSVgVg1El4rnUb5aFkimkejVFFu7cJAQAPFnEbgX9X9YuV8jkXWUMMYn4Qmxr6gJlsoNc6kUOre3BU3E7KGmgbmxEYYCNoYsw0KaqzXixUY24/E2GxSR9e0YABQ+Um/IkppfXyekrUjx2HipVdgftdqv1HD9bUNixjTdeJG++E3QVLaKUdEM6gXy1A9fBwW/VUPzJgzx2l3alQw0GTNVdctdg0ZoDLEoYaeFPIUQZ9hjJ/RQGgnZA31PjH/lgbCR24gxJjO39YPNBBoYFwsqy6LvIoY5zMWtcvfXf3H17hX91z95yBkvnr4OOT+6gGYMWdOUP/xnrSt/fof+/lWMPnyK1A7cQoWSrIGwSw544CLFA8bRCm3Xpp4Z1IeQBJS3Hi+YFzD4IJ3ay0dc3TpOJC4V9cV9FxDlZ3WA6TuvapO8KRyST3QARg0JCnd/sUuY3HAp/8AOO4J4zxJ/wEAzpMA4En6zwEUMTZHjns+/Y/9fWsYP3Iczv3mDMxfu9qQKm79BSBJo/79kFv/eUWU2uM+fR/t3wezP3IDtN3U4e3LqA5M/PJVtctA39emdhmRh4dTt3zjtWP7B2Fmvp2E3zD7VrpAhguEecOb29Qnel35occMYiyk/wyIt2bXHZb+m4vjYkwQWynb139e1tE/55yuiARWRERE05h8/hTM/sgNMHfFLZ6Jg1x/5OLz+deHYfz4KXKcMyVRBBnD5JYHgxhblLPm4Ga+ANKLqVQhx/f6jWcABo2SCEq96K97jON7xa1NI5pzPDGqQwUhxvv66jrx/BBMvPwqLOi60/kNr8VXoySJsbV3Ktd9sx2YuhdjxDhfIbbvGKEhjGkcxr06Be3rPm8swpvXRLSC6uFjwmD8YEGRhZSw1ZQTg9rh4zDx0qswb/VKQNKScSQwZXpJRArjfDcs/MI9DkEpiFowyMfqvsNK99RvAIrcVaumHOC8JMba/6wLOGcOoUnl0lw5z4NDfJJrgAuiFDhIopSpF6g8TTIYjbEZKhCqzk95E8prtcfYDQBOvqA+AxdtrbxWMC96f0oQRzSFyk92yy1Ggqyh7WtMvrlYOeccxNYey4rXhLz4+4IKSt0DrG22QeDjOzV0FFnzwcVK3g3vACIjVSkP81avUDJiyAKpB8Zaaf9iF8zI57SZofRbloULs2KMbOdS+k/bReXA4Lw6MapL1Y+umzOqf1T38jlhOqr7YjvK/DkhQlavDOt/RPPgHKr7j0D7us/JU/P0QhL2xWhsAhdeK1d/5AZ1cqZeVCL9EIjnOCGJsfY/6zLlijxivKZRq0EZtxjl8+rZ0zR6MU8sUrC22cqDkAN6kjPjWuAiKPXYvsPKa0XVi7wzWWYO3NzOlaD/XI17r8A8DAAe0H/OBWErSOk1eh4U0H/gjGylxG3MHv2PaBocAMb2Si8mNRLrea6xkxP09r5Z73+vTMnoY1PvHARZc/43Z2DB2juMuarWI1By2ihWYKzPJMZoj6nlQfx/tn8fXP2R66HtpmWGLJo7E8T75MuvwsSJUzB/7WqzHE56rvriBV13EKKUgUm9aqDHGHpJcpUvbQvx78JISRFjWHfaKLosQgd1W19LLCZdXrsu0w2RwIqIiGgaV31wMcy1YhD4Vl8aJTQQyCSFQHXyMhPDOAdwDE/aXZ9/fVhMCNeZJ0ZxKx0AyGCMxIuJ5G0P0ABkex/WkaSx88bT2haR43sZCxNFIu5VB8z+iOd0LmXoCNRODIntXJIYY7SQYLY9eozNt1y1WaCOEc1h9kduEB6EErpNBdGIxih6rYjVuzmGgeI+ByaN8w64+rol1h2ZIjQR1cPHYOLlV41VRF0W4pkHTBNjUvfUSqAjmOK76r7D0hi7JYXwYUr3Fn6RGucqN+M+jXG6nSsPlMA2Y9MjKX1YbufqtMrBFNGtSOliGcaPkLYGkxAjVyZVKCKABV2rZV/MDBlT79LAn/zlq1A7LuRBP1/9Us+XM+ATk1D+nvSkyOeAMUIGI3kkv2NcELYoD/j8GSU+uZajRqkCtSPHIfd1Ig9g9sVMyhHnAJV/flKR0pRE1TqCsszElpJfvqr6AE266fxoHyBI6TUqthdXhBUh0mTe5rin24Ix0i7ynpO/0bqXpP+xo28BjMH8rtUw6/3vJX0GkV808bn2WlnQtVrJFJUXIDJfL1ZgrH8/tK/7vDxBzNIRTp8Xg9G+/UIeaMw5o1/TejX5S2mcd91J8iKLAwyUrvKJSSh9T27nyufJQpmtr1ouZ+bbSV/s13/si4Vx3qN0z6f/+J3wWhHjXpL+M2AwfkSMe+gxFtL/2Mu3hkV/3QOzFuUBiXL72arFAUMeuHwO3JA5RcIWKzC29zDkvv6Au3gGNK34Db2Yrnr/ew35xXtjes4ZjB8+DudfOyPmxWQRASy5QKJU6N7nlMzT8mD5kQw+K3Vvzk3LVR50IZGp9mAw+bIY9xaspTs69BwIFyqBA/DaJJS/94jSPaBtjPUEff0YaWu9CIdpGPlu+iISWBEREU1j1vuvlUGpNXyrMJV/Fsb5VdcVvJML2v+OHzlmBOekYFZ6RYzJ45xpPkwF5tXX2sQY/c0ulyLGrBOj7DIACGKs/D2TGAOQg57nPtX9g3IrpVlHO28u6yhOa+s22to3ZnEgxNhHbzDqZJcjojVgQFGvHCNJhdv7PCdG+VD1xt5x8wUQ7uTeo9Q9YAAw+lOpe/LEKCVbngJVZbyHUCBUCuW1Yh2l7ug/ktK4ncvSPV9ZKDFm1Ie56fnEBJQIEULTRpmfGsx6/7XG33ZbMmZuKcHtnrbHJ71utG+/IkoBzL5S9YPyi4lfvgITz2t5oA5JtM/kXHvvhuJeYf5I8lT3DwKAJMZIPkDS4D2QlM59vdt/GIMlx3TcSzMyVKyV1SsT9R9Ajgk/TT+di6n/IprF1VZ/iaB9UKNYgup+6klh9U3W+F/ZIciaWe+/1vtcqNzXjhwT27m6VjuLA2hQIxqlsibGyLY6qn80PRJjbTd2GPf3yejEy0L35hOvcp/+A4BaIFzQtRpmLcol6j+A0L2Z+ZwY9xL0n4PUPfRaadNxjmz9x88RzYEBwMz3XQvcNwEhX0w8f8qSB38MUM5Bnlq7ExasXa0OEQrNm3BebBKlVimYJuqVPPx1tyUvcnGD0b81UYoeY3btaN61I8fh/OvDRPcsUhq0rBlbKfM5Iz3npkwyxmCsH4mxDqtttd8b5jHx8qtQO6HbWu0S4X5dna6IBFZEREQLcIcj3yRFGAjCKE7qdxvFMtQOH4ec58Qo37XKQCDHOYsyMOUCr8px5JgIhOohxux8G8Q4n2UNvL7yJxFj9rW4ck6JMfo7nejhhHD+6k7vaSm+tjY8xjxlTfo+IhvQ0LWfLwLJGrXd03rRa4Jkjee+SNYgMZZmm9Kg1D4DgqJREsRYzkOM+Q4zQ48xV/dcjBPdS5I9BkT3PMa5l3QjHmO0vJR4AIgyfzFwCBX7b24Z5+Ax5sl1wjgfhoUkxknoWdVHTOMcwPS04FZ6NBDsvpjeB3V38peviK21SIx5r5D3mNCk9KxAzBcKOu4l6T+AkPmqNe4l6epZOe5dbemet9y1ycQ0EclwxnA0SCcmtBdToC+m12rjfKWRj5G3/NywthgpgiiQvzbOr1Xybd8Dgbo3v2u1+6OVr02MIXz6z4AQYxjnKKD/AFL3nj+lyhHSf871gpBq6wT9BwCAiSjzFwNn4VW2d6NUhur+w5D7eneqzAPo8BuUKA0tKtWeH3KIUl+5sBzl7wl5mJH3zIut8d/WPSdf8hk9CHNfN3XP1n8EjntXyXGP1sm+dvzwMZh8bdggpY28QY8RjWIZxvr3QW7952HWNTnvvePahEAksCIiIlpGqCM9/5thmJDGeVpny2vSk2Kl/0hZH0lAiTGaju5Tx8GgFjhK3UdMUePcDpQo12HU3zWLGKO/cesdV859xrkuuy63Jsbo0dnaDKIlO+chxtz85XW1CRj5P7YH00Ukw16kpM+hJj0I5xK55NYLv6sTsmZWgoGAQHmYR+N/OJ/EZ6p7tAw+NDweY0b9rAvROJ8vt1ElEmPSY2xRgJSm4EB0jxydHboHtjU9wpuR8tLn1CiWofS93sT7R/jhXQ0nn6mBYMuhTdxQ4zzLluayRYzR8tjXjGcwzvGaOhrnMtZKqH64Lo7G+bwVtyTqP4Awzmse3bP1H0CPe/MyeGsiEcID4579uV4sw9mf7g7kFpEFPtKIgd7eN0ca51z97o7/E1IekoxzzLsxMQGl7z+svJjsQjBgyjLmYHox+cpLobf3dSeWA/OgxJivrBSoewu6TFLa1n9VDosYSyr3WL/w1myTXitJnlaTv3wFRvv2JeQWkQW+8b/03Z3QdmOHnrsy5jxbRHX/IJz7zTCZF7tQfXHRJMbSylPdfxjabuwgXkxmOiofE8+fIltrw/kKj8oylL4nPMZQ93ykEb4MD0KVgOg/KUcW3aPzf2Pco/rPwNB/AKF7wh6anogEVkRERGvgsqPm5DPoyTNuc1BpQKelL+W1custzm80KK0wzs/AxIkhYSBYabn1d4MSY/mcla+5UiPKMQgcAObdsdJrddC98A0a58j2WpHlpa+zZEuJr8wcdLkcrxU1GHKyFx9UOZAYm7Uo59xX1VXeBNs6onX4CCG1eofbPT2THwq1euccpe7mjUQpPb3PPB0I78GU7rWvx1gryRjf73oQ6vxMKKL0i10GUazlk9Shpj3GfCSBjao8tj7NOEdSetzjrRlqx8pPdjveYhHZoI8mICS4/A29mHxbjJxuqKaN89Stb6CJsfmEGDO9mLRkNEZKeotRBqQZ51THKDFmD2E2GtZWSl+9KNSWEstjzJe3OJ3LJMbs9CqQcU1sa5/94es9OUW0Cg4AY/sHHHkwU2jZTJIH8wqZt+XFRH8Xn+X4DzLm3IlTBmEbWkzAvnjBWve0Nh+ocZ6k/8pbhHqMkXLbUygAPylNYXjmoLcm8dTy6T+A3s4V8r6MyA57/K/uPwxXfXCxQUiJAP9uP9QoVaB24pTRF/v6M0T5exYxZsFeLDn32nDQm5t+J4ixQcj9lZ8Yw35eE1KHlcdYqLxY39rzQ47uiQSm/gMQYiww7tl67nhrWtlzwqqJbcxHoO3GZYESv/sRCayIiIjmEdqIzYlx/sGCf6ZNUDsqj1K/wzJc1X5zrv6uFytw9qf9ghhLMc4ZYyYxZvyo/lME0vnXzyjjXCx0uqsp6m+6nYucnmOc5kOgVs6RGLPqiNcDAFwY0cfWs7Y2PRhyaUxae7oMj7HQI5F1VMSY1dYR2eGQk0AMBDzOGWdGHqISOEB1n5yk4HPwkI5IPNbRQPh6t0OoMrDvwbWB8L5rE/MGbnkQevPD+zBFlObWfV6eUAhOeehrFLdzoe4F68jksfVDsPALXcb3qgzSjOKQTErb+TJganVy3h2dzT7qCECjWU6elYFOPCmQKFVp1IXqnYGO/9F2U4crMyqdABrnC7ru1LFEMH/UOXmhQYzhQQU+mZR/V/cfNoxzu6z4kYG1nYvj967+42ev7mG+VtrakWMwiR5jCfoPYG4pmUk8c+jiCx1/UPems2FzsaDPmYN4bxTL2jinYy3KpPUcStI4n/W+a01Z8dyjuv+wkIc1q/Wz5QDO+A/ytDYqD9b91X3kZyUPH1+W2F8Cp6T0alUXn/4DB2jUJrVxLmMAhfQf+2LvuKfSadDtXEn6j9fa25gjmodNgHJAL6Yh4/AaXFC2E9eLZSh9txfm4wniKajuH4SrPljIFvO2KIixHF2k8OgUAokxDAPiyxsvHSMeYzZZa2ffKFZU7LtQnEVcLBZ1lMSY12OMGTowoYixO71EreHNXCyLbcxr7sjU1u9WRAIrIiLiImAOe2oFIYUkYYyJOAv7BuWpNVZAeMLG4CSqvOOn3tg7bjkYVA8/5yXGRIZm/sJrpV+elNiufrcJIxxM1HauWz8Rqp36dP71Yag9f0oY51b9baKLT0xC+fs7Ye7KWxQx5raD/psSY2mnrNWN09qSt3NFBOCZKKHBeDUG5wxOqsTzwfgfC7ructLZ5GRDelIgMcasgCi+7X1ZdA9ArJQiMYZEaegYcoMYe/+1jtzaGD9yDM6jMWbV0a5rvViCsd37JTGWM+5JP6MRM2YTY14I3Zp4+V8kMbYmRTsiwhAtp05Vk0akQ9YgbCMaAKpHnoNJ3GLk0w8izxeQrEGiFLSsUPnHyT/qHsZa4SH94wCTv3oVaieGFElgpONATkOURKnazpX350nriF4r1DgP1LNRLJmktISt/yjzZRprhbSvQVhI1I5Kj7E14a2UESnA8Z/p0wTrJeFJMX/1SjU2KwNUXkMhjPPFZl9skTrYx9VLZaidGNJeK8YCGyfPW4z/pe/1OsSYMf6TslT3DZp9cajKnOu4Vx7vXVv/AQBG+/c5cY58+o998cSJIZi/5k63vYg8q7hXnnHPp/+C/NO6lzY2Rfhhk+FI2Fb3D4rtfWSxSLUxSQtgejGFiFJ84fY+NXe1fqcLfhdkCAClex4Zo9cqYgzlwZM35l+XpHRO9sVKBmUcXftkQdQ9FQcsVEcgWyntHR2W/gPorZR5tZUSF/C4WW55zzG7racpIoEVERHRPNSxyxy0cf6qMM7X3AV6SLQ3AYn3Bp2kGMdK22nF5+r+AWIg+DYWaTTUvvoeEhiXOsPjZEh8rvQSjzGyBsMBJ2vadX78yHGY+KUgxvS4wayXLEepIrZzfbFLGmO2V5c5MavuG7SMc7du+N3518+I07m+0EVOXbSd7MXnRs0lxiJagGxaamiq+B/UKPaCi6PUd4v4HzPy7W4Kdb3IXxvny0gRNKlKjZbJXwndQwPBT2iiPExA6Xu92mMMANwNARrjB3DlvNMhdW3QmBZJwMlbeEuJux48jl4rhjHmKwsXnmuUGIsM1kXBJs5nve/abERpsSJPzuwx+jwKKqtq5ZwQpfQdSQXOOVT3C+N8YVeSzAuIuFcmMYaLFPRavJf2YuowvIDpO2Lyl69A7flTsGCNP9YKBZ8Ib6X0Gd+m1woL6j96SSpSOgr8RcAljwzjXCJElkw8fwpqz5+yvFZM4LUYlJoSY2CNAxRonM8neZuLYWSOVarAxPOnUvtihOExFigvLYcyzhMhFyp375dxjnweMWY98TRlHPdC+g8AMPGCaOv5a1ZHmW8ROM+1xVnJwzX6mSlS1wKVh7TnIALCDybGvaKy79O9ENCLybejw1iMlgvoQvc6rXKg/oMxJRrbN6BJaU97UdSLZZg4EdY9qk+MMXMrZdI8kgNUDxyG81T3EuZj73ZEAisiIqJ5WJOsRrECY7v3Qfu6L5CYN5TEMgmt0f592kAwMrbTMjj3q1fkJOXOQJ76Wj4xCaXvU+OckFE0HZmYCmKs05OfSQfhwJv/eg+wOXOsFO6Vfo8xs9xMlkUTY50AYI9hJjnWKJXlVkpBjLkDqSbcABiM76fEmK/dIrJAr84BoIEgVs16AGXMJTP1q9L7U3Kcsy+NuJ6Bjv+xYM1q9bta+CQLoABMxv8QuodEKS0Ls/If220fpR4us9jONQTz19yl7qmJCPOFHoRC9/KJ+QIwj+65JDCW325rXz9htvVjRlvHhfmLgW5rZZwbWzL9/UmjVIHS93uFgZBvB/d5CeCj0Svndt5ahtELpa6Mc02MmQsK5rWaGDOPUkc90fGFGFQPHJZeTPq4eEbujbKEMecEUYrjXkg2BTQxtjyYDg1AQYwNqXFPFs/RfwAMAK69VuwDSCKagV6UAxBzBGEwdpK+1J3TiL64AtUDYo4wM58H+/nbf7vGOe3rufEdJcaMhTVjLib+qBdLUPpeL8xTxrk77lODHj3G5jtbrd261osVqD1/SngQGvW3Ib4vKeM8T7539R/bwyTG/Povxl89H5u5KG/oQ0SrEO03tnu/6cUkQfs/xIU3fwe150/Boq/3iDTGE3Wfhy0P9sIdlWOTKE2euzZKFageQC+mvPEblRuUI+3FtMzKl4N9H9S9+XesSqib+LteLEP5+zul7uW9afRfzCDG9EJKqI5lmDgxlJmUfrcjElgREREtgXbFZWWcp8cg0FuM0lesG8UyjPbvg9y6L6jTQfzDhninxFgaqIEQGhZxHGlMuF4rPmA+2q29M7EMHLSr9iLiMZaUf2grpa8O40eOwcQvX4G5MQbQRYO2b126tfvkwfccbHkIyTAAwIVSGcYkWaM9ROi0TnyD9ocma9zjnAFMA0EFpSbGOQAYxz7j9Y1iWZDS67/gnFDom0qO9u8ztnMlwTTOQ5DGueUxlqT/AH7di2ZNiyDC05DG+aKv9yijmDkSQQnKQWKcu0+AEqs2MWafcUXlvlGqQNkwzs1czXcR4yREjNllEVtKhiRRqskkn4crB4Dy93c64x7zfBLtoYkx14zRnzmA8tbMrxektNJ/Yuxp/oEZ455JskQ0D0LWlMow8fwQ5JRxHk4LAFD+vt5i5KYLyIMk8F3PFX1No1RWujfL8KLW96cjRfXA4YDuadlAEkzr3irPIoxZnkapDGUkpRflE/UfIERK0xLr6xulCtSeHyLjnl//XWKMtkdEK8AdCQyEV9vky69Ij1LzmVLvT1xYqvQ+Bgu67vQQ+K5sjPXvt+TB7q/1+4U3fy+J0h5VNgAqNya5qbf35UlevvJQorST5O2WmwMSY4IoneGQweY1DBiMH/CT0r5ras8PwYTUPYzz6c9bEMel7+10SelpvFYRCayIiIiWgC62hsGIrk60UyWf1ekgX+8h+8E96eXf5d6fQtvHhVu74YFCXvi9Y5zbZSHvaJzn1n1BBCC17m3HlBjr3wezP3wDtH28wy0nuQfnHuM8oU1ErJVePQHwlBVAt9EYtvXtnWYa7rYLEmP5r/fAjLY2fzkiWkL1wGDQrd1u3onnhxyyxk6jiNJiGcqErLHTUZOC27oXyBtB5cEpM9d54/WKlCZbSiyRU9BbKbOR0kr3PISUjbHdJikdajsOWYmxiFZQksY5PVWS+ohQVPcPwqQyEFxQMrZRLCsDQR1hTtL58m5mS8nE80OZFhLEynmvsaUkqasMGec+nW0UBRGSDxAh9t+KCLG2c9n6j+Wg417s3i8euCWz9L1emJ+yaIWoHgiTNTaE14ogxuwh3wc0zmd4xgQE9WQ8l6B7FFT3aB1DffKYpXsh/QfQ456fvDLrq9pa6l6S/gMkE2MRzQPH/3pJLhgHFlPt8FcYBy3LydYTzw/BxC9fceYIvudbL5ah0vtTK8wBGO9A/h7r39e07tF5kNNnk0KVvtcLc1bckqkPGNs/COff/F2mctRHSjC6W7S1b65nlAfEPChpQWg6IhJYERERLWPyV6/ABBqM9mzGIo/E8d69JO6VTuakB4/XCgYS9fTdjWIZxvYPQv4ve1xCjP4tr6fEGMPZlHUNBnCsHcXYOxhrxZO//K6OxnnPF3TASbscpCxj/fvgaiTGEsqMxBi2NbPZBvtS6jEW415NHTgxGG3C1kNo1qmB4AtAaqWvHhiEto9bgVABrO2L4nuDGAvlKV/1YllvrbVjrVj3MEhpJEqtFwMzb0WMhRgu8j3VPbtt7TqouFf33BkmuglhS0npSNhOETgxGG/vVP2ikgMw+/BGsWwaCNzqsrn5SErf74W2j3eohQT6nH0HFUz+ZtiRS59soO7lUPcATHmw5E2R0nSRwio3yPIZxJgtZ9Zn1L15qzv9Y4JVdtrW6mfZZnZ7OG1N7x/l/iLAYXT3Pmj7ODHOLZmn34nYO4Ss8fTtiAY1zpP6KfmdMs6JPBjyTq43jPMEmcTrle7h4pmtdyRvPe6tStR/JGzpuJek/0r35LiXpP903KO6h9dEs755IEnIQZA18+7weba611T3D0K9WA6TNeTZNYplGN29T4bfaEvtm8Zs3YPws7WJsSQZaHiIMZXeGj8YaN2jh8aE8kfda1/3hUx9b/kHO0VbZ5ifj1ltHeVcIBJYERERLQFj7+TWfdHshAOd9+huucXINhA86RUxdg/xWsFgulb33SiZ27nS4t3YxJiKaUKWXVSsFUKM6d/CeVfQOM+ylfLoMTj3usdrxZN/vVRWMcbwyGobtPzNbKWMyAqxhaL2/JCM9yDdxt2dFgrl72nj3IDn+RleK/i7vVQtr62XPCvnVjrGmCqLMhBQ93xGvMTEC0OO7tn1RPnDLSVeYgw/k3tUD2AA8E71HbfSIBqlMowfOSZ0jxE99dQVQBtj3iDEbvKIjEB50P2lbk3b67NeKpO4VznTEPUY1E5QaikPuKiAaxZeYgxBZIPew9G9BOKoekB6rdzeqRc0SH5qzOGUlF4njHNm5Wf1B2O27tFyWm3i9VoJEG6NoqetaR2jldMauGUwWu1qyzJ6UuT/sieZoJQvSow5AbFp3szjtSJ/c07bZKK/rOz4qdEXM3v8IPo4tpt4rXjS0O8u/NvvlAdhkv7jdyVL90L6j2PCOTLuhfSfgd5KmaekNNH/2M83Dw5SHihZ43lWdNHqPCFraN/o69OAE2KM6geVZSoPAd3jnnJQYmyGJMYcmaS61y9178M3OPenC9kcQGzvQ93j4fJiOWzdC5UBSFvPW3FLuO3k9xfeFLrX3vMFtwzTHJHAioiIaAl6m8N7UtNWD4gTo7JsMVJeTCTWCoV9Ig66tc/5+PLUvJVx7imHna9hnHtWpGwirXpgEGYuSo97hXn7tnOFTnir7HC3czkxM2Txa0ePwfnXh03PnIiLBgbGnb+6E2bkc+R0JJ2GGgzV/YNw1XXZ3NqRGKNEqcgc8zWftWGcB54xnqKFuteMXOb+UhNj6vRyz33G9nuM8wAmXghvKfGVg24pcQxIC6nbd6IetIRGUW5z+MuebCvF0jjPKg8Tzw/BvNs7pdFKFxDIO7fkIQsZfCBF98g1Svdwe5/HgKdjAxrneJJoSP8d4zwFdRqU2iLdvCd/+YixQB0jsuP8v/279qRIAD4S5UmxKJd4QiuAeGbUOLfnHPT6BhJjX+8B1uZu5zLuxSUxdqM0zvHrgAxMvODfzqUz1x+RGJuf0Zt7bPe+zOPehX/TWymT9B8/U29NnTj1NhFJ4GLO6JUH7o7/dYusoad1+oDyQL2YQkB5MHTPImGpTBvEWAqqBwahXgp7jNF86yNiK2X+L6XuedSaqh9upWz7yB+nloPqnq2fxs4Krtvat41Z7UiZxogEVkRERNOYeGFITlJWgRl00EVdrpznbOPcuUZ8LqMnhQrGyIN5Vw8MwvnXh2UA0lBvLq5F47wdt/elQMV7CBgI9H64pcT2WvGVpVGqBLf30aPdEZQYY0wHe6X3FwEguTiyWhIQ+EvE1GD86HEpD2GiFCckSfE/bNSpJ0XAdZ96HyYb50ylw5Mz03VPywjGWpmlThEMG0HVA4Nw7vVh62QeP+g2w0yTTUf3wnJMiZCIqUXlsd2ZtpQAWMa5RMigb4yURKwVQpTaxjyFMhCCxJi+TzO6FyLG7CDSiDRizDCCMO6VV/dclDEIsUc/bO/j6oFQjDFmpItoEpzD6GO7M229V15MxDhPkmH0Ykoixuj4X/rBTr3tVMIY/8m9xj26F0Jd6l6IGBOZ648+YiwENM5xHpRE6HmJkAQYHmMOGPk/ohkwxqAqPZ1RHnxkImL0sX5DHpL6mnFJjKXPi10PQlWGgFgoonTFJwBP8w7BS4wloIxbvgPe7QC6XSgxlibD9WLJJMY8edL2HHvS1D3GdCD9tHtNB0QCKyIiomnMMAJHe5asJcxTa3LgElamv6w2EFZ5joe2tg4mEmPutco4V9v7wnu/0DjHU0r86XUdqwep14pLytE6ju0fCBhjmpjCQUzFObrnLvEb55K4srzSgDsn4zGjfePU7mKhJ8+0/V1DV20x8nqtZPWk8D+v2vMnhXGuyBpXvkCSmfVSKYEYs/dJmca5kEEb+ps62c4VJo41lLdmPk++DZPSk5KUdstqQnmMWUGI3XtE+W8F89fcaa2c+9vR2OZAEJpkK+Oc9JchQ8i3cu6mFfdp2Nu5UhAixrizl4PEvbq9E5L0H0Cc2Fj+vi8AeLiOJjHmT8eBK2OMnlJKU6D+R7QAxmDuHSstssbfh7heTOlkTRYvJg5ckTVa97TRao//F978HYwbupesT2VFjOU9v7qLZyYxllxHJMZmyADgYSObqaDUsz/8x4nlBSBtjcRYQP+j1DcPzrmcM+aN71zyUSyecQBjXhzqa+okBMAM7+naZv5nf9pP5IFZ838T1GNM64QPzLu1NpQWIMljzC2HIsZ6shJjOwOn52rg/N/UPaL/kbhSiARWRERE07j6gwUyAWLmi+N31JNiufyNk7QSHMmaU9I4Jx4dXP0HijjgwkAofb8X5t/RaR2bS8pjbOUYIB5jdAJEyiJXP82Vc3uqxAC4eeS1ivewKC/rws0ic90mLjHmnxxz0MfW5yUxxpy0VlsfMNua07Qca83iLK9FtH34BvAbrKZB4R6lHp6YVw8MwoV/+51DlDoyB+I4Z2WcG96JZjr8DuM9zEHdc9JpOfZ5rbiTQvF3HY1z5R1g6b91D9M4D3tTiryp7vmIcbMe6uhsrzFGUkb+qiVc9T5N9iMhbksnnhiVfFobWVUOGAiuvLEwMeZJC8AsYixkFOv+khJjzKsj4jPGWskp3TMXXmyZHt29l6ycJwsf6t4CuUgR0n8cm4QxdpcMeh/W/4jW0PZh3AYkZEo/C92ujSLdYjTH+d3GWKoXk+47VdwrJQ+YgkoF9sVuUGpM7VvoMnXPV179nQpK3fMFSNJ/RJkeVOCtn/5cPTDgkNJ+nZbjHrY1EmMB/Y9oHowxKZdmm9pEybnXT0Pt+SFY+PkuTEFzMd75xCSUv9cLc1fcYhBjIZjEGCcv+z5y0cryGEt69pWf9ju65+/ruTiwSRGlqP9uv+r0xVlOKEzcSmmW//yb/+4QY9Gr1kUksCIiIpoHT3hJkqS6X3pS3L7K/M24XvxdL1agemAA8n+5zjwRh3nIMSYmQG03LhdkDbfys8ox8QIhxmQa95QdkT8epS721ecFF6XIH1BjmODVmIpzpE7mYTIvxlTdBBjURzDO0TpdF7DKzPV1pe/vgLYbl5vlMOpntvU5u63tFSxSl4jm4Uz31fPVRKLe5rBKP0siXyq9NM7FJOWLTl7KlRy/5wxK39sB81avEtv7qKzQ+8i8lXF+u/Rk5FyXgciHIErRY2wdzMzl9X2VLJp/j+3eS3TPzI/qNHBGvFZIe4CVVr7Qa0V7B9jEmF1HSUoTvXZeshxx0bJFkHbE/odTeeboSbEcZv9HsXJuy4sjD798RXqUWvpB5U2SRoIYu0saQdSgMNMCAIzt3isMhE9+QuWF/bQtQxfe/L0kxr6oysCJTDJadw7yFMFV1mKJq//ATd1L0n/gYkxAUloY52H95wC6rT98Q6L+xz7+IkHGblwIwsUfXpuE0g96Yd4dqxRxzsCSMSKfrjxYfRm5V6NYgTHZF7O2NuPZqgUpIk+G7tn9qyGfzCDGHB2yZEed1rbmLlXHkP7TcW/urZ/Q33v0X4x7xDhP0H8sO4572AeE9B9QZyKagzE3Rzk3ZaJerMDoT/uh/QtdRl/skubivbp/AK7+yA1SHsBKj89LCPX514dFX/z5tWA/e/vFa5NQ+l4vzF3xCV0Oa55NX9UDAwAAOtQJnb9TWeGijtUjxyBHiFKaVi/+ir747GP9qi/26j95uVsp7bFDf2eS0lhHbup/7OMBIBJYERERrSDFpeHCv/0Oai8gWWNd6klfVmRNjnToYBrGEtUDA5IY60wtptjOJYmxDMF/xw4MauPcSsutck28MAS1F4Y0SRDImzFRjvIPdgiPMfskFg+q+wfE6Vy4QulrNHltvVSGiUBb220HADDy91v9N41IhDBqQbcnM/+eeH5IrN6tuctsczrHk6/6CDUQcubvmJzIyNiTaJzfYjoxeuYxBjFmF8Ijp6Xv98KcFZ8wT4yy0mAW4wfJynkSKcTFSuno7r2Qs3SPGY2iMYrE2J8s1/clL3UFJx5j1FszUI56qQzl7+9IThfREpQnBe2LfXLBdUD4/F+ugxlt8ij1hH4N5WH2f7zBkAPn1Eoe9lox7oG6VypDpfcnMB91jwFQg4IxUwfGntwrSGn7dC6SJ37WW0qI7nn0H68pUyIkpP8S1f1WWwf0n4Egpc8+thsiLgLW88LFn+qBAZj94T/WnhQBmQQAOPeb05ootfM2DGgAXpuA0vd3wNxbdV/MtFia1zFwvZh8XAKReUqMuSe/MuPvUUqUpqB25Dm5nesu8/52fRm4xFiC/gOXpPQHxbiXpP+oe2d/2pda3ggTBpmD7cvM784+1gdtNy6Hqz+4xNP2Jlk5fkR4MalFXd84rhaMK3D2p/2w8PNrYQY9SdWzMMZAyPzVH/ljty/2XHPuN+gxtpbIJCFsyTV8YgLK398hiLF83nt/tfjLRV8MAKIvTpBJMe7hVsp1MKNtDhikLYBTnlEkxv7jH+s5pxEPTH+uHTkG1QODmZ7zuxGRwIqIiGgeCS4NYgXhJ6ZxDuCcZoJQBoJNSNmTG06Oc/aRNR6Uf0CIsRRUDwzAuddPZyLGxHHOHmLM0yycA1QPBogxDxQxRuOA+ZqbYYyxHU2cxCKIsYiLhGVsUrLGCc7peXZjT+7NbCDo+B/EOPcYwwBoILi6FwLq3txP3pK6ze7CbzHWyhf98mih9P0d0jgX5Ug6zdBLhFjlweuwrb2ktAfCCFqSXuCIMGTbUxk5//ppmHhByoNtPFto1CaI10rOyReB+TtkTQIEMbZXe634yk4Jqd2W7llloPKp4xzdZSaziSwIj3uhNlG6l3I6FwMZY+wFQoQE9B+NqdL3d8BV700/HTiiOYwffQ4mf/lKptMt66UyjD4mjPNgP0XSo3FO5SE0/qNxbvTFATlTxjkSY6F+Xi7IVA8MQKM24SWljTFCEmPVo8eIx1ggb5m+IomQkO7RU9jGj1rEWAIakpSerbZ/RjQLQyyITCkvJnlarPG7hUapDONHj3nnQb7xf/RnQh6MOSkz0yOqkiidf0dnkvmhyjH6WD+0U91LKLvSvU+mn5R4/vVhmHhBEmM2rLwbSEqTBcIkVA8MAAdQuhdsby5tkKPHMp34+25FJLAiIiKmFCHj3DfoqFNrfJOUgIEwv0nj3DaCfCfjXPi334W9mDwofb85YuzCv/37xXuM2eDEa6VJYiyiFYQZHpusSYKXrAmAkjX+o9TNv0dt4zwB1DgHSOSkhYGwswVizGeMWUBvTb+XgouW2jrD6VwR6aAkIq6cz8znUjczjB80jfPw6WQMzr9+2i8PHgSJsQCa0j2bGEsxmloipTMY5xdGhO75xj1fM6LuzclwbH2ED37ZTDLOfRh9zGOcB4BkTWI/JeWvXvQY5wlwiLGQHHOA828MQ+2FIVj4BY9xDmYf3qhpYmxWplNKBwC4MM6T9B9A1HGcEmMpQGLs6o+k616EH77xefJXr4i+2EfWWGh4PAiT8q8eGADOwe2LuZu+WXk4m6B7tughKT0/wxyhUSrD2cf6kklpmvfBAZidRIyROuK45yXGrLR8IrmtpwsigRURETFlaM5A0Mb5jJRBiQFTBkJbhlW2JAPBDk45VcSYDxfeDBjnAZR/sAPmZByUmmnrpoixCD8u0pMCIIGsCSCNrKGiTOUhHAtEGwiJXiskLUBrxJiXlLYQ9FpxSiLKMvakfTpXGM3qXkR22AZCEvlZe/aYY5yHTlK6MFKCs00Y5zYxloRzTRBjfMJHjIVpuqb64pEUjzELScSY3Yx63Ls7sbwRzaFZgzFonHuAxFiWeRBAwGslgFoWYkyiXirD2Z/2taR7aR4x5183ibGQ/nPOhcfYD5pra+AsU1tHuAj1Eo1SGcZ274VczxfF9r4UjD25N3NfjMRYiCilsOUhLc6Z8GIKy4NBwjZJSldaIKXnZtG9Yrmpca96QBJj03yRIhJYERERLcDjxUS3OWTZYvQDn3HOvNeOEQMh7YhwNM4XpQxK2ij2GQh2/cTe+aaNc8NrJXng9RMhNMiJvt5rnNN9/lYTNbOVMiI7arh61zJZE5YJUx786VCGUR5yUh5CJzqhYJS9ukfTMZW2OVK6kpmUBvDpnr+eHNA4/5dMbd2wdC+a8q3DNhiaMs6LZageeS5FHnT+Z5swztFAmJ/oUUoI2wwGAnqG+A0E/7iDxnkmYqw2AeUfUmIs3RhTAcB95SXXmx5js1PLEhGAd4vRYGaDEYlSbZy74zcizWvFvj6b7mmZrzZBjIW8VnyEQe2o3s6VBhGPLYkYc/uXZkjpiReGYOEXulLTRvhhiruWtXLvT6DtxuUwS51EG8b40efg3OvDbgxCDygxlnZ6MIBYPKO6lzT/V8TY57tSiS5em2yClBaHMUBLpPSc1PTJ455Zj9RtzNMIkcCKiIhoETr4IJI189fcBTNzOfGzHaeDvHzBOcWLm9eCPK3thZPQ3v1FT+wPN9giGuczcrnEMnAgBsKnOt1yWH8rj7GvrYMZs9vc+1vlHtu9F9o+LoMQy5NEQmXBAODz77nLqhsn14l3ZZzfc5cO/gtM+EZ72hDb2qhjRGsgz6xRrKjVuxmz9QlijkzI687+rE/Iw4f/mPzOvXnX5Kk1akKIkVWtPDlwgyhVMm/lpwReyoOK9+DIoikcJlFKAqCCVU/5Kv3gIWGc27pH6yjfDd1T5eXudRygjsa5oXukDFZ9R58kusedakU0AeotoTwpMDBuwvMV2/ukgWDLpXpnSraVJwX2U0YhzPvUi2WoHT0G+a+tAzZ7tpnGkWemdO+qDxb8ect33uDmdq6ksQaYXDlH4xyNMY/+SyhiDHUvoP8AFjGWoP/AwToZL+feOKIJmH2QOEHsXzSJmCCbBlGqZJ67+co/x43YO/5xA687R7cY2TJpBKe2vJhoX0zLS16G7lkGs+ktxTQx9rV1wIy+2LqHfK+g7v1hwZNG679oa6l7vm1lVrtjW6vtXAGdi0iGChROxv/qgQGYmc+pIOU6pTv+q1OMv7YO1I8Jz0ERY++91k1oyVLt6DE49/qwPL3PR0jp7+pFQozlckEvPzUPenKvS0rbeiIx+at/gdoLJwUp7cuWfGeQ0rmc+aNHv/XW2kD/QtoUt1Lm/lLqnrHAPf0QCayIiIgWYFqFY9RgBICkwWb86HMw8Ss8St2XzFxVDnsxycGUpBdeK0syBWO88Oa/CwOhG43zAGT+yjin3jM4CWOmcVE9cAjqZVw5ZxC2oJmIc/TkXsh9LeMWAiTGPnyDzheJLqseEy8MwcSvXoEF99xt3DPiYsCgMTEBpR88JLd75sE4uoy7E5bqwUFQ2xwsg8BnnFePPicMhDlztIxzLmWRTFq4XDk3dA/AmdjI/JXuOQcmMP0u0yJRqo0xu16mTKstBD7dU0aW+IyxVoTumfU3glRwAD4x6fcY426ZAURbZ/UYi8gCbagEPSk8E//xA574H4bRDUqGtHHe5eaJaeVzbtQm3K3WCQZT9cAhYSDgqVi+vJGAwJVzNM7xvj5wLrZzfXy5OCSALjR46lA7egwmfmUb536yyyDGcrlE/QcAqB60ibHYx7cOc/5RPTAg++I2S14Y4GlqKJuVnT8xyRrMz2O41p4VffGCz9wpv7PkhjxjEZTao3v2+I8ehPutoNT0FDNLns+/gUGpu6TjLbf0VL/zWmB7n8/wt8c9o93c8lPdU6eUevQfX2cpMRaJq5YhHokeSyd/+QrUXjgp5+dEbjzjv5gH7YAF99zpkogcnGcoiLG8SdbYz1nKhzg5U+ieun9CetS9We97r1VO95ras8/B5OunYf5n7vTkZ9ahXqwYxBhpNFB9AJHN6pP7rHlQgJjm1GNsLdE7kj8pW6NmkdKAz2T6Cn8ksCIiIlqAnkhXDw5AozZJtnIwK41Go1SB8WflJGWO7VpLVnjkgKq8Vv7jH3vylZ23bZzTgddbHiaOUqdeTPR3w0gQ5dHE2CdESob3lyAflddK9xfNH4z20J/9WynBHCRVWw+axJiTJ6g61EsVGH1SeK3ELSUXD/okxw8MyknKJ/TkyjF0xbMRZM1JbZwbBI0pH3xiAso/JAaCM9EHoGRl9eAgADBrixEaCCINbouql8pK95jt1q4mTPo+lcfQQFgCVBfs+gGIOEeTihiz9Meoq5BLPxHCdDrSRtUDh3RbG3lyc9IHoNra3M4VjfmWoeQIoIzGuTrR0ep3yDMbfxbJGiqXNFN9bd0wzvMknfXcpGxq3bvFTMes8gCDc7bHmFNu/RmJUq9xbixCSJLg4CBwLnUvQf8BAOqliklKW3Wy66uIsT9cYqaz9B+AyRhj/0KIMVtPI1oBn5iA0g979eIZWSBiasFCz0GqB9E477Qych9GvViCMeW1EioAqPuZukfnKACGnnAZc+5Xr8CCz9BTa625Co4JSJR2y+1cnORrH4HGuXVaW1j/AZg0zk+apLQugHFtwxv3yq//wMScUxNjvvtHNAXZtvViCcae3Au57i+S+QedC5uyjGRN28eXk8D8/vFfEGNDwpvK21/qsmBfrIgxBc+cwtY9J2/zsyDGiO7Z832rXJWd/yyIsfdeq/JS+s+1/gPI7X2vn9akNGlbG/VS2WxrTztQjP1in16kCNZveiESWBERES2DrpxzMuGiYHKA4NJrZS56rTgEDQG3DAQvxHWMiVUSRYwpL6bAJA+I14ovILw13owffQ4mf0UDwrNAXYVxXnkYPcbygfvrzyYxFjD8JS7827/rrZTOrd32KyuPMSyHP9+IbJBTF0mU/gvM95JGZjvjqTXaOPel0+mrlBjzEK/0b6F71ECwn6/4zDlAo0aN83wgX/1d9eAAgEOMgXUdyDoK4zznI8ZA6z9ec/axXS4xZtdVttH4UUGMueXQ1wnRt4ixXN7INy0eRoQL3cUJolStnBt9H3mX39eLFRhHsqaNbnPwPWvqtbKEfO83hlD3TALfvD/+3SiVYfRnnu19xrv+rLf32X0xTSf+FsSYpXuB8UzoXtK4Z9bDHfcCOgKWt2bbHKu8Ea2DwSga53+yHEQ/o9ufW89QbDEaIludwq9GbRLKP+wli2ehtAKu7pnlFG/iGkGMDRBiLJCvJLEqD5teK3oa4V43fvQYTPzqXyQxFtZ/0RdT49xXR/PasSf3eXTPX45zv6HemiH9j8gKpv5nlheTry2JPDx7TJI1Qh6S5v/1UsWVh4R+cFR6c7d9/GPOb2Y5wK97HKxrpO5JotTQPVunyLVU95L0H0D2xQeRGEvuA/xtHX6NP3sMzr1+GuZ7dW/6IhJYERERLaHuNRBc4EKCXr37RGrernGeUI7xCSj/8CHLOA8j2Ti38i6WYfxZaZzjlpIEoHEuPMaSIbYQ/Et4K6VVDjfuFYH1t+0xFnHx4CCDcz5LjfNkVAyyJhl+YsyPrLqn8j5IjfNkOB5jCRBxjpJ1zzgpsSXdW5+4tRbzP9tEW0dkBBcGwoTaUpKMRk30xfNvX5W5Lza2lCSgPlJSBkKWrdZluXKeSfeepcRYMvzEWELeB1sZ99aml2MibdyLBk6rqD37HJxTxrlAKApAvWiTNckYU8b58tS06MUkjHMCz/iP3rumV3kYznYuIE5OVtp6qQzVgwPJHmMEymuFbucKQAQAR+M8Gah7Wds6Ih0oSk31xXiqdQZ54LxZeTjm6F4IDYcYSwbG/8yme/9i6F5SHE0x7jWhe020td7GvF5/6XgTT09EAisiIqIlNGMwmivnyagX30bjXK2cpxsIPNVAMNGscS5WzpONc8TZn+0Ke4xZQGIsy4kwEdnBa7VUsoaiFbIm/7X1mYixVnRvbkbj/Oxju5TupXkuNWOcn3e8VhLKUaO6l0tNn9bWcUdVa0BPivbQNgcLGBi3FQMhCY3aBJR/9PYYCPUREucoEzFme4yF0RQpbYx7ufS80xaE4skFLaE+gl5M69MTA0Dl4SbJmjeyGeeCGNuT2Tgfbco4f0WS0n7do5IjYu889PboXrE5YqzcBBESkR0TLwx5Fyl843+9WIbyD5uTh1nve2+T86Cpl4fqwYEmdW8v5Lr/LFsdf9E6MZaERm0CSooYy6Wmn26IBFZERETTmHjhJAAwmPepVTrQIAUJD0EHJRWck6aj6UGSNX8iDQRu/mbfq2YY58y5N3UprhfLcPZnu6D98/eaASfte8g8lMfY//MTbr5WerVy/rkuf/3I9co4/+QnwuUg5VfG+aesCYDHPlHE2FfXmycEBdovIjuqzwzC1R+W8oCyFZB9Hf9jbbjtMbSITdYE5BHfHXkI6Qc3iTFFlAbSGnGvlgjj3HuSD4n3oEjpBP0HoLqH2/vcelEoYgzbOqENg6S0fEbMt00gIh2cq9MclYFA+1Xr2aFxPv9P73Kev3EttwyEnGUgeGRJea38yXJ/OnIv5bWChoqvvFT3kBjL5dPHhIPydK5PrYIk/QdAj7EByH9VEmMhnZafkQi5asmScNo03Yv9+8WBc6g88lPTYLTlhrwUWfOpVc4zsqHkAYmxUL4Sihh773tTn6sixlD3aL7WvZAYa6e65yuLhOExlqD/YtyTxjkNjg0kHfkO50EOERIYSxxiLMr9lKF68BDkvrbeIWt843/14AC0fXy52RfbkM9j4oUhqL1wMkxeWXKpvHepXPrkGHzEmEW2kfG/XixD7YWTkP+qh5T25F3+4UNy3Ls23A9zXY5J6jEWkkNueWuG6khgjHtRvh1EAisiIqJpzMjnYeHnPAaj1RErL6ZPkvgf9EQcADDjPQyA8qQIGAb4uV4sQ/XZ5yD/1XUwY3ab+NK5hosXI8TYkkLiIANcbymZ/ynPZAnMOqiV88/dqycACUb3+MEBQYRk2lLyhibGVDk8xhgHTYR80vJasQfo6e113DJmvfdaPUlRp4LJH8lzaJTkyvkD9qk1Vlr5efTJvRYxZoF8p45zpvLA3HTArS1GvqPUrfyrzwwAAJjEmF1mNM6RGPvqeql7bhoNpoNSL1kS1n/UPTTOkwhbmbZeksTY59b6yT/OgXMe4/u2AsZg7q2fMI1zBSn7KA+2cc7MpLrvET9o4/xaM42nXxt/lhjn9Dd6KpmE8lp5gAYhBjCCoGNoEdC6l8UYm/y/CDGWoP8AHo+xBP0HLnRvZi7vyjyA0/aaGJO6x8Bph2jstAjGYO6nVmmD0ddfynQTL5w0iVIAr/wq4/xHxJMi6flwSdagPNi6RIlTbsqDUw67TBDQPV8duUWM2T8y81oV9+qBP4OZiyxCytJ/4B7jPKD/AJQYI+S4R/8jWsO821fpk4Z94zj2U9KLyVk8s1+A204PQf5r6z2n99H8xd/VgwPQ9ieEGPPII75PPC90b96nOsk9PWXnHC4US2Rbe85bVvpePTgAV/3hEpeUpp/JIQiCGFuXKL/4roix9wY8xsh1Xo8xj/5PZ0QCKyIiomlc/YeFzFt7NFmDAxe3Bkfxx7k3sm/va9jEGIA7SfIRY3fclpp3vaSN8+CWErIyhdv7zKOz/VDEmG8VkTH9AhLniBJj1r0pqlm3c03zQa9VmN4fSticdOWHPcc5I8hx1QDEOA+5tROZrhfLMPYLaSDk8yYR5GFoxigx5mNwyFdonDukNC0D/jkxYU4IU1A9eAjYnDaYd7vUvYD+A5BYK1/NFufoLD2tLUH/426q1nA17dOMNtQkemOCejHlzLSMWQY4F2RNPkDWWGgUtReTyo/kpYtjEWNJW0qQGMuynUvma5DS6kQ6gNBqwFiIGLP0H4AQY74t37QdudXWSBIE9D+uVLSGtg/fkJqmXixB9RlBGmWdBymvFSRRAbzj/8T/b8jcYuQY8vqLRskixtLK0YTu6b7Y8hgThXXKVXn4n6HtTyyvFY/+A3hI6ZRyiHHvixYx5up/nNs0DwaQTuCDeA5BLyYPyj98CNr+ZLkeExLm/9VnJDF2+6rUbqteKhPd83juWeP/OCXGUlayUPdStztyDvVSOVu8R1mu6jMDcNUHl5ikdGD+r9t6XaL+T3dEAisiIuIiQQcMPUCoWEzKtZYHBxBB1uwSxrka8ML3Gz84aHgxMa9hI97Vdq7PrbU6f7csZtyrnJWGOdcIrxXP9r5AHROJMfQWk8d1662UhdS8VRDiT/kIOtegj2gVVhvax0o/MwAzczlN1thQniDcIGtSwbk4MepP6HYuYglZc5rxZ4+ZxnnCVkBtnP9Z+AhzBeYxzsPypbdzpRydDVr30mNrCD2sPjMAM+a0wbxPrUrU/4i3AYTA8ZM11FghZA31pEi7xcQElOy4V6HJe5PEWL3o8VoJ5AsAUFbG+fu8v1MkktJE/wHQa4UQY4nlsNo6Qf8FwRDlv2V4SHD6tzLOM5JGhtcKgL9r4lzK5SHXOA9gzPZa8fbb4jtFjCm5dOcz+HejROMc5bxlpXko3bO3c1n6D2DOg7LAIKUT9D+iNfhbzn1mYbLGs2D8jPRiokRQYPx3iLGUR+nTvdD4X31mACaRGDN+c+vYQI+xr64nRKlfPwA8HmMJmHjhJEy8cNLv3U7LLfuAZg5Cmc7TnEhgRUREXAQY+JYU66UyjDkGAjMn3QTG6l0K4VJ79n/A5K/+L+uEIP/AVC9VYOwXtnGurgJzEsfIdq7/3aiP6S8vkOi1YsH0GMt56mYSZdVnDgEACxMh5Bo6IZzRNtuTzjToSz/ckVreiBD88gtAT4y6K2GiJA2EicnmAqEaxJixfOmkrZOJWBaUFTF2rZWvW8/as/8DJg3j3NZ/sxxa9ygB4W8/vZ3rYyRvH7gZawXC+g/AgE9MQmXnTwJ5RSTDZ+RqVJ85RMgaw9UCvGMCelJkMPwzbe+TZdTb++60jCR7LGGCKPV6rfjHHdM4D8svACXGKCkdLo9DSieg9uz/8BBjfuulXirB2NP7U/OMCIDbHyzj/INLUsZmgbDXSlZiLEn3BrXXiltw4zvDOFd5+/YgSaLUiHOU4rXywoseUtrvZtYwiJAcpCFxa62CngeN/nxXap4RWWD2c2NP7iHyYI+1ZtrEuFfW+F/3ykN4/u8lxsA//jdSPcbM+X+J6l6C/mM5XN3zAz3GcobupRBjmXSPwcQLQzD+fz6XWoZ3KyKBFRER0SJ8Aw1TZI1rnOOAQQcOpicpakJIBzkGdJBBYiz31fWeNHZZbGLMzs8s97gyEO723puWvV6qBLxW/K+qPJ1r7if/d09ZzXroOEdrvb/T9nSJsZRyyDhHEc3DP5UQ7eqSNa582RNCk6yx76LTG8SY5970GpcY88mwrXs5ORHz64Wte3mle74W0fepeIkx1CGzLKbXik//9fXJbe2WafTJPTBzUc5T1ojmYMqOaZz7SBrTQEDjXHgx+fph/Y4Ggu6LwZMW5bIEY0/ukcb5Issmt8ccQYyJlfOPJZRBfEZjbL5D0LltUje2cy3ytIlrBM3M5ywjyD+m1Ysl/4KQ9x5C99hs32JGRDr8cw8ATdYIQsUmf0yZbpQqlnEelncAapzfBu5zBeNaoXsvBvpid9w3jPPgeCD+RlLa9eZ2dbZeKnm2c/n1H4ARj7Ek3RPvSvfu8XmMmXVGIuSqDy6BiIuBK0vVZwagXq5IefD12xr1UhlGf7GHyIOdxhz/x1RfvJyk8Y//LjHm7yuxHCWvF5O//H7d89WTJxBjPnlmhJQOzVXccc/UvZDMl6D6zKFMJ5O/WxEJrIiIiNZAF/DIXE5tc/jYx2QaRl7g31JyD56e4x8YAQAaNTTO7yYnVzFdDsxXfq4eHCReKyRf24GFk+Oc/yIhEKqqCyHG3vtenTcH8yUx/uxzMPnGaZj/6bs97cWM9IZxjqdiAZC2w2vES8U5+uT/LutP28BsP0WMfXatt30jkiGak5lyKttYG+fvtZ4xc5559eCgNs5t/aD34JYHoZIHS95I3ooY+xghxizZxbRmYFw7P1NXONU956ACZskak0GIc2Ii5tV/nb/aSvkXKcSYLJPptRLWfwCmT8YziJCIpuCRHbXN4VO3eQwEcJ5x9ZlBGRj3Nr/jB7nOODHKHhOs8cMxEIx+1ZI5ToMQ36bz872DKEf1mUOQ/4v1pu559B/zbvuT5Vr3AvoPnAQA/9O7IEn/sRzlH+2ABZ/Bcc/Wf7ccQvfQ0ItoCdb4Xy9WBFmD8qD6JP/4P3bwEJEHf3+N36M8GIfXcOZ+luUQurfKOtHVP/5XDx4iumflSevKBVHq6J5H//E30zgHCOm/GBMIMZag/wDY1odcIsSj/6KOqHvL7YwjUsAAzL4S/waAC//271B74SS0f+WL7oWe/qf8w4dkQPi8Ne9wx39BjJX1/JzqkoV6qWISY76+koz/ihhT86Dw/N+re550Qj8qghj71CpSDp/+o1we0sRYgv6jDWJupQzoqmwrHWOMjr/TC4x7z8mOiIi4UsFSAhVGRERERERERERERERERITAGINGo3Gpi2GDz7rUJYiIiJhaRE46IiIiIiIiIiIiIiIi4t2GuIUwIiIiIiIiIiIiIiIiIiIiIuKyRiSwIiIiIiIiIiIiIiIiIiIiIiIua0QCKyIiIiIiIiIiIiIiIiIiIiLiskYksCIiIiIiIiIiIiIiIiIiIiIiLmtEAisiIiIiIiIiIiIiIiIiIiIi4rJGJLAiIiIiIiIiIiIiIiIiIiIiIi5rRAIrIiIiIiIiIiIiIiIiIiIiIuKyRiSwIiIiIiIiIiIiIiIiIiIiIiIua0QCKyIiIiIiIiIiIiIiIiIiIiLiskYksCIiIiIiIiIiIiIiIiIiIiIiLmtEAisiIiIiIiIiIiIiIiIiIiIi4rJGJLAiIiIiIiIiIiIiIiIiIiIiIi5rRAIrIiIiIiIiIiIiIiIiIiIiIuKyRiSwIiIiIiIiIiIiIiIiIiIiIiIua0QCKyIiIiIiIiIiIiIiIiIiIiLiskYksCIiIiIiIiIiIiIiIiIiIiIiLmtEAisiIiIiIiIiIiIiIiIiIiIi4rJGJLAiIiIiIiIiIiIiIiIiIiIiIi5rRAIrIiIiIiIiIiIiIiIiIiIiIuKyRiSwIiIiIiIiIiIiIiIiIiIiIiIua0QCKyIiIiIiIiIiIiIiIiIiIiLiskYksCIiIq54lMtlKJfLl7p/fYukAABhhklEQVQYDsrlMvT29sLw8PClLkrEFYrLUa5D6O/vh8HBwUtdjIgrCNOpfxwcHHT0Y7rUPULjcp2vTCWGh4eht7f3Uhcj4m1C7Ldaw+DgIGzZsgV27tx5qYtyxSMSWBEREVOGjRs3JnbMab9fzH3z+fxlNyksl8uwbt06OHz48KUuSoTExo0bob+/3/l++/btsG7dOhgaGnrHyxRCuVyGJUuWwNq1ay91UTLhwQcfjBOzKxhJ/TPnPKg7rYJzDuvXr58W/SPnHHbu3Al/93d/p77bsWMH/OEf/mEkfS8BOOewbt26YNun/X4x9121ahV87GMfm9J8LzcMDg7CunXrLnUx3tXYsmULbN++veXfW0Vvby8sWbJkSseC6YD+/n5YtWpVXOibIkQCKyIiYsqwe/fuxI457fdW0dnZCV1dXZDL5aY874h3F3bv3g2nTp0yvtu5cyds3LgRFi9eDB0dHZemYB7kcjlYs2YNrFy58lIX5V2D7du3x9XjAHbv3p1IJvl050rD4ODgZWN4dXR0wJo1a6BQKFzqokxL7Ny5E86cOdPy761izZo18I1vfGPK882C7du3X1HGc29v72Wjr5cb0vqyt6uv6+jogK6urstqrnQl4MEHH4Senh44efIk7Nix41IX54pHJLAiIiKuePT09EBfX9+lLkbEFYihoSHYuHEjbNq0CTZv3nypi+Ogt7cXNm7ceKmL8a7A8PAwbNy4MRJY0xToVXO5kHDLly+Hvr6+SGBNIzDGYPPmzZekT8f+7+0g5d4uXE76GiHQ0dER+60WMDw8HEm/KUQksCIiIi45yuUyDA0NvW3bt4aHh2FwcDBxi2G5XE5Nk3aPZuqQpc7NtMvw8PBlt4Xycsfw8DCsXbsW1qxZk0he4XNIIz6yyNlUIqt8YLneSWDZ0nTuYuQ7yz2axTv9DN9NmEpZvBjZaHU8afaeWcaUi5HPLGPS2z12Rrh4p+YrWdJMdT+VNV9sg2bLMNVt1+y8K0I8g7dznHun+i189r580+rVTP2T5h7NLoaFdok0o09TpUNX/FyHR0REREwRCoUC7+npyfx7qVTinZ2dHADUq1Ao8JMnT3LOOR8YGOAAwAcGBpy8Ojs7eWdnJ+ec882bN/NCoaB+O336NAcA3tvba+RfKBR4b2+vkY+vDJs3bzbyT8Lp06ed67u6upxyUGzbto3ncjmjXKdPn87cLqE6bt68ObW80x2FQoFv3ryZl0olXigUeEdHhzcdPn/7Wfnke2BggHd0dBjPq6OjQz3TUqnEAYBv27bNuG7jxo0cAHipVFLfnTx50pB5+7n29PTwQqHA+/r6jHJ1dHQY+WC5bDnr6+sL6hQil8vxjRs3Gt/t2LGDA4Ajp1S+Ub/tNrPz4tyvA1S+Ufd7e3tV22I7lEol1XZU5+z6U/T09Bjp7WeZ9gynAwqFAl+3bp33t0ajoXQHsXnzZs4Y4y+++CIvFAqq3ZYsWeK0m52mUCjwHTt2cMaY0z9u3brVkI0lS5YYsnHo0CHOGOOHDh3ihULByMO+Np/Pq7Laz3/VqlWqbnZ/a9/zjTfe4IwxvnXrViOtr/zFYpF3dXUZ+W3cuJH39PSoe3LO+UMPPcQZY6qtGo2GknNbvu2+vdFo8I0bNxp17erq4hs3buRLliwJPOEIRKPR8D67pN/feOMNr5zg89u6dStnjDn9EOrOunXreKPRcOQA5XlgYMDI35bBUBlw/hPSXc5b6//seQli8+bNhtz55BPHCwq7z8/lcsHy+vSVzsdOnjzpnSMljWvvNqTNUX2/28+AzktwPPfNI7u7u9Uc2zcXyNpvcc6D/Radw/tA5wT2vL5UKrU070A9oDqbNre269jZ2Zk4T/DJsj2O2mV68MEHnXx8ur927VrOudmHUPi+t8dIOgZdQWhEAisiImLKUCgUeFdXFz99+rT3ZRNYp0+f5l1dXapzPX36NO/o6DBIBZ8xbRNDIQKrUCjwrVu38lKppPLO5XLGYNXZ2WlMfLBMuVwulcDCOnV0dBjXb9261VtOLCsA8B07dhh1tstvt4tNttA6btq0iZ88efJKHITecaARjs891Gb4OyUxtm7d6hBROKnasGGDSnfy5EleKBTUxArzs+UJDXoqH9u2bTNkwUdg5XI53tHRoYwbLBdNh/LR3d2tyrVjxw41cUma6CNJZrdHLpcz6t7f328QcIVCgedyOd7d3c1LpRIvlUp806ZNzv1wAkx1s7u729BNbFeffONkGvPE9k7S15MnTyrybtu2bXxgYEDll/UZvtvRCoGFE3h8Frt27eK5XM6YgL/xxhu8UCjw5cuXK5k9dOgQ7+jocEgCJAFQNnDSvmTJEvUcDh06pO6LslEqlRQhhH1rqVQy+lkkvLq7u/nAwIAqCxJYWIc33niDd3R0KPILv0Ojm5YN02HZGo0G7+7u5vl83sgPx5QsBFahUOAbNmxQ9+ju7naMECQPqQ5t2rSJ53K5SGBlABJUW7du9c5VkLCksjkwMGD0EW+88YbxTIvFotdoRyPy9OnTQQILCSsqM4VCwUiHOkjTUWI4icCi/d+GDRuM/s83VoT6PyQf+vr6VB/vG39sAgv/xnJT3fTh9OnTql+29ZXOh+h3qGPTZR7U2dmp5ie+l2/OgfNKfHbd3d3GGB4ixejcPURg0X4Lx3R77Mcxw9dvZSWw6NiPMo12A5YJSSbfvbGMWBd77kDn1hs2bDDmHki0NTP3oLJMdQ8XIfL5vKFP3/rWtxwSi46h1C7o6+vjnGcnsHAc27Rpk7rfjh07rsQ5TiSwIiIipg50hT30SvLQ4twdHHF1wp5E0cEuRGDZ90KD2/bw8nllZSGw0JAOdf42gYUrXJs2bTLSJXmaIbZt22ZMNEJ1jEgGTnzT2htXuuzJcEdHh/Kww3S+iRc+HyR8cOUPnx96WvX09BgEbWdnp/FMfQSWr1x2OeiKKQXKUVLdUQdtWevq6jJ0oru72/gbDR4K1CVaR5+npu2lhjphp8PvceJm1ytpIob1sOue9Rm+29GqBxZtTzTQkfyhhI4tszi5xv6ReqpQFItFIx0a/HY6LE8IvjqEYJNLOPG374l1QHn0ER9476wEFk1D649yiESJXRYk4iKBlQ5s66RXkocW5oEGKP7d2dnpkE7d3d2Gt1/IA8vniUjlw5YXREg2bfgW1DhP7/9QX3DM8rWJPU+zCSz8vVn4CEEc2+x28I0172bY3ji+V5ZFWDqe+uaiOG+mC2E+Asu+lz2m49++OWtIBimwbPZ47Jur+bzJQjtE7DqH5tYh/bHbJwT72tBYwbnQF1wYwT7E59mMyEpghfqQKxCNGAMrIiJiStHZ2QkDAwPeVyjo4+DgoApWbR/7u3LlSrXnG9Hf3w+dnZ2pZenu7jb+XrZsGQCA2vONJ27Z6XK5XKZgi7t3727q9EOsA2MMent71Qv30dvBSmm79Pb2GmVHrFmzJtO9IzQ6OzuhUCjAunXrEmMYYDqKjo4O4xkMDg56A/IWCgXo6OhQsUzWrFljyPHhw4ehq6sLVq5cqZ4tgJCRtGdaKBS85aLYvXu3V0eyyEtXV5fKA0DUsbOzEzZs2GDEl8A6JJUjl8tBoVBQ12DciFwuZ+hAf38/5HI553nYuok6Wy6Xjetp/s0i6zOM8IPKGWPMeN4Aol8L6RLF4OAgDA8PQ3t7uyMbnHNDNhhj8MADDxjXr1ixAjjnsHbt2pbkYGhoSPW3Tz75pPM7Y8w5ERTrVKlUAEDrjE/PbF0Jwb5HLpeD9vZ2Q8Z99WeMZRoXIzQ2bNjgnascOnTImx7j+2zfvh0efPBBI4YMYwz+9m//FgYHB1WfUS6X4eGHH3b6MR9wfoKg+sI5hyNHjkBHR4ejR77xoBkMDg5CT0+P8z32f3TMAvDLNs7TQuMp/t6qblKcOnXK2w65XA66urqm1amFHR0dwfl2aA6L/dyWLVvgwQcfBADdf3V0dEAulzNOo+3r6/P23zbsvieXy0Eul3PGZp8uNNNv2XqCZabls//GscV3b2wne/5tyzn27ZxzY3w6ffo0ADQ/90gaK1asWKH6GixblmeQhq6uLmhvb4fbbrvtip/XzLrUBYiIiHh3oVAoZB6MhoeHYdWqVVAul9WEpFAoGANBZ2cndHZ2ws6dO6Gzs1MNRJs2bbrosg4PD1/UgFAul5u6Hid3lLBA0HyGhoZg7dq1ie2CyEqeRWjkcjkYGBiAVatWwdq1a2FgYKCldsTnGbqWTt7QGEBiqb+/H3p6emDNmjWKSMNgoa0YoXYZmpVNOy/Ute7ubujv7zeOzR4aGoJCoQDDw8PO5MvXFvQ7bI/+/n7H0MjlcsA5TywbtvmWLVuc31qpbzPPcLrjYoKRp8kFhU82CoWCk95+3qtWrYIdO3bAli1bYPny5bB8+XLYtWtXqlycPn0abrvtNqUzHR0d0N7enlypANAQnOp+meaHMnuxxsx0B2MMli9f7u1vff3QwMAA3HvvvQAg5iVooFN0dnZCe3s7HD58GDo7O2H37t1QKBQyEVh2XrYMIvE/lUiTJdr/oR77yoDXh05a6+zsNHQT/25FhoeGhjKTwe924Fgd+o1ieHgY1q1bB4ODg9DR0REkAXt6emDbtm2wadMmKJfLsHPnTu+cNWv56P0Bpr7fCskkBfbLvnvjtfb45ptTAUzd3CNprLAXRqZK5vP5PLz44ouwfv16WLVqFRQKBdi8eXOm/ulyQ/TAioiIuGRYu3Yt5HI5OH36NAwMDMCOHTuCK9f9/f3K62IqViIApsY4beYUknw+DwBiInz69GnntWHDBgAQR0cXCoXUdoloHYVCAfr6+tRJhK0gNPHxpQHQcoynv6xcuVJNQHfv3q3IrakwUkKynVXe6Ur24cOHVVmRhBscHGxp5R/rtnXrVq8ObNu2LfF6JDJ8154+fbpp8i/tGYbIl3cjli1bFlxFLpfLUKlUprQtfAYDYywoG9g/JqGnpwdOnz4Nhw4dglKpBB/72McS+2jOOaxfvx4YY3D69Gk4efIk7Nix46In9D55avbEqmbBOY9k69sElJNVq1ZBqVSCvr4+2LFjh9PfMMZg48aNsHPnTuCcq4W3qQD1wrPR6nNvZgzDMSVJtpP6B9TNgYEBGB4ehuXLl7ekE7h44kOpVJo2/XWz2Lx5MwwPDxv9nK9PRW/xwcFB6O/vz0zAXgzeqX4rSd7S5AZ/P3nypHd8apZgQoI6SZ8WL16s7o1k1sViyZIlMDAwAC+++CJ0dHQoUvNKQySwIiIiLhlwVYEOHL6OFAfP3bt3w+HDh73u7q1g2bJlhpsuIutR7+ilkhW4NWTnzp2J6YaGhhwi40ocYC53dHR0wNatW2FwcFC50jcDJJ98WxZQhuikZuXKlTA8PKyIKiR/MI+hoaEpk2269YMC3dbTgJPYLVu2KOIKQBBbOLFtZUUQCais5bCBW1EuRh/ohDHtGU6n1f7ly5ero7xtYJ/VCpG+bNkytQBB4fOyam9vd7ZytIJVq1bBoUOHoFwuG9thAMAxBIaHh41xiHPu3UKYBStWrAAAdzuJ78j3VtHZ2anIERvTafvUO4nh4WE4c+aMIf+cczh58qSTdsWKFTA8PAw7d+6Ew4cPwze+8Y2Lvj96i+EWbAq6rbtZNDOG4dYtX9/d29ub2fsew0z4dDMLsLx2ncvlstpeGOHizJkzzqKTr6/HXQ+7d++eUgIW87kU/RYuwIVkFyB9bEP5n6p+HPOz2wPHH/QGBhDzORoqwQY+0zNnzhjfJxF26KHc3t7e8nh3KREJrIiIiEsG7JRx69T27du9A0wul4OVK1fC5s2bAcC/h74VdHV1qVhIOCgNDg7C2rVrM3mWbNq0SW33w4FiaGgoSFDlcjno7u6Gbdu2wc6dO9Vq5uDgIKxbt06lKxQKylMnqV0iLh49PT2wadMm2LZtm9c1PA2bNm1Szw9lYHBwULlnU1lFUnLz5s0GUbVy5UpFHNjxb1rFhg0bYHBwELZs2WLIUZqHEwInT9u2bTMInDVr1sDQ0BAcPny4JTIjl8upmG5btmxREzJsszR0dnaqVUOc9KIOpT0/JCjQaMLn1cwzfDfjG9/4BixevBjWrVsHO3fuVMYyxkrZsGFD0x53jDHYsGEDlEolo30HBgbg29/+tpEWt69s2bIFtm/fbsjG+vXrU++1c+dOI/YQ9pm4ig0Aais26gR+h/0tgDCmWt0y09nZCYsXL4b169erspw8eVJtPZsKIFGwfft2NdaUSqVMbRTRGnIyDtn27dtheHgYSqUSfPOb3/QSMJ2dnbBy5UrYvn272qo1FfjGN74B7e3tcO+99xp6tH79+kxeR7jVCuXS7v/oPIbOg7D/Q2IDPcwAQI0rO3fuTOwnt2zZkqqbPhQKBRVnjJYXQJDUOG/D7XH09wgT2PfRua4dcxaBHtiDg4NT1p7Yb+H8F0DIAp37vl3I5XLGPI+OLVu2bMk0tqH84/gIoOcerSyAYj+xZcsWR5+2bdsG3d3dyiv5W9/6FnDODVtleHhYzYEKhQIsXrxYzfcARN/wzW9+07jn4cOHle2B9a9UKk5csSsBkcCKiIi4ZNixYwcACJfWfD4P/f393mDKAAAbN26E4eHhKQ1Sm5OxkADEagRjDNauXQvd3d2ZDLXOzk7o6+uDoaEhWLJkiVolTfIO2bZtG6xZswZ6enogn89DPp+HtWvXGgNIX18flMvlTO0ScfHAGACbN28OTuhCwFgeg4ODSgaQ+EDZoujq6oJyuWwQVSjTvpgUraKrqws2bdoEmzdvNuSor6+vqTzK5bJBVNEV3FZ1cdOmTaps+Xxe6V3Wuvf19UGhUIC1a9cCY0zpUNr1dBLLGFOEV7PP8N2KfD4Phw4dUkTS8uXLYcmSJbBt2zbYvHkzbN26taV8V61aBVu3bjX6yf/6X/8r7Nq1y0iHE/UNGzbAxo0bDdlIM3QBABqNBqxatUrJxJYtW+Bb3/qWklPGGHzjG9+AgYEBWLJkCdx7772GcYBl+/a3vw3f+ta3WqorYwwOHToEnHNVlttuuw26u7unzJOPMQYPPfQQrFixAnp6eoAxBosWLYLFixdPmQdnhIl8Pg/f+ta34OTJk7BkyRJYtGgRDA0NeUkbxhisWbMGTp06lWnbazNlwK2xKKv33XcfPPTQQ5niAOVyOdiwYQP09vY6/Z89j1m1apUxP0L09fWp+QvqGfYNuMDoQ3t7u6GbeE3aGIILMfl8XhEd2C+Xy2U1b1uyZAmUy+XEw4KmOzZt2gS5XE612bp164LkVHd3t5pvT2V77tixA1auXGnIzzvVb23cuFGN/3RsWbNmTeaFvR07dsCyZcuM8mcdn2wwxmDXrl1wzz33GPlt2bIFtm7dajwb9JYaGhoyZB49pzAvOo6tX7/eGceKxaKyPRhjcO+998KmTZuuyEU6xtMipkZERES8zWg1ns5UAlc1cIvT8uXLoaOjQ5FszV6fhrI8kQ7T+665HNolIjualYF3AlTOcDV71apVMDAwMKVk8MWULSdPDGq2zey6NXMdHuBg3/NyfIaXAln6p1aQtU9r9f5ZZCL0/KksTgXeCVlCTzLcfrlu3Tp46aWX4MUXX3xb7jfd0WqfM9VA2ero6ADOOSxatEgZ6GmYiv6vlXZ4u/prlP84T8oGKjuXCrTfwgWTU6dOebfkvh242L55qvuBZvJLK3vaOEa9Ga/geQ6PBFZERESEheHhYViyZAn09vZekSsTEREh9PT0wO7du6FUKl3qokREREwhMGj9qlWr4KGHHrrUxYl4h9DX1wf33XcfHDp06JIvSkRENAv0pENP6IiIDOBxC2FERMS0Bj2BA/ezT7fYNxHvPmCsA1xpw4DsO3funNJtLREREe88tm/frmIDAQjPtnvvvRcqlQr87d/+7aUtXMTbAozzhB4YuGXum9/8JnR0dETyKuKyh6/fWrt2LZTL5Ri7LKIpzLrUBYiIiIi4lBgaGnIC9saVoIgrHaVSSR2bjcjlcrB169YYTy0i4goG5xyGh4cdPe7s7IRDhw7FrVTvUrS3t8Pg4KAzX1m7dm30uIu4IhDqt2LssohmEbcQRkRETHtcbCyeiIjLFRgjJJfLxePFIyLeRcBxCwBiDKBphOHhYRgeHo7zlYgrErHfipgCxBhYERERERERERERERERERERERGXNWIMrIiIiIiIiIiIiIiIiIiIiIiIyxuRwIqIiIiIiIiIiIiIiIiIiIiIuKwRCayIiIiIiIiIiIiIiIiIiIiIiMsakcCKiIiIiIiIiIiIiIiIiIiIiLisEQmsiIiIdxz9/f0wODh4qYtxUbjYOvT398OWLVtUHsPDw1NSrmZQLpeht7f3ktx7KjE4OAhbtmyBnTt3AoCo11TiYtvpnZD3i32Gdhte6ZhqGYiIaAZX2hg3NDQEvb29l7oYEe8Qplo+r5T+djrJ+ZXyTC4H4Pynv79ffVcul2H79u2wZcsWNb9qtk3L5fIleQ5X2vjTCiKBFRER8Y4DB4UrGRdTh3Xr1sG6detgcHAQhoeHobe3F5YsWWIMnu8EyuUyrFu3Dg4fPvyO3ncq0d/fD6tWrVIDdrlchiVLlsDatWun7B4X205vt7zv3r0blixZAtu3b2/p+u3btxtteKVjy5YtkM/n1VHd7xRQTt4NbRjROjjnsH37dnj44YcvdVEyY/fu3bB+/fpLXYyIdwhTOSa9HWPu24Xdu3fDunXrLnUx3nZcqjHwSsSWLVvU/Gf37t3q++XLl8PmzZvVPL2VNl2+fDmsWrXqbSh1GDj+/N3f/d07et93GrMudQEiIiIiphMGBweht7cXBgYGoLOzEwDEqmBXVxd0dHRc0rJdidiyZQv09PTAjh071Hc9PT2wePHid7wsuGK3YcMGyOVy79h9V65cCV1dXbBy5cqWrt+2bZvThlcKent7oVAoKF0CAFizZg0MDQ29o88AQHvq0bJEXD7Yvn07rFmzBgqFwqUuSkTEuwa5XG7Kx1xczOvq6pqyPN+tuJzGQB+Ghobg1KlT0N3dfamL4qBcLsPmzZth06ZNsHnzZvU9etyfPn3aGC+6urqaatOurq63dS56qeaclwOiB1ZERETEOwh0RaaTjY6ODujr64uGVQsYGhpyiL+tW7fCxo0b3/Gy9Pf3w+bNm99xl/FcLgd9fX0tE6DDw8NXLOmybt06OHPmjPFd1KcIG6dPn4YHH3zwit8uHRFxOWKqx9wHH3wQTp06NWX5vZtxuY+B27dvv2y3beJczZ7/nDlzBgqFgtF+nZ2dTbfp2z0X7evrgy1btkzL7aKRwIqIiHBQLpdhaGgok6vs8PCw2rqVlt/FdLJ4nzSE9pxnrU9SvlnrkKVNmr131jZOq2PWdryS0OzK06Vsp2ae01S5/+M9WzHem+kLyuVy8B6++mQpF1431W2RNb+pvPflAp9sN9suzWAq8kbZytoPTlX/G5Lpi5HLVvqWrPXHtGlj1dv5vN9uvBN9SVq6ZsfbLLLYyvPIKu9Z5hB2Wey2bDYPO793sg+fCvme6nnc5YSLGQOmut+4mGd1uTyjVurQjE1zOdTxsgOPiIiIkCiVSryzs5MDgHoVCgV+8uRJleb06dMcAHhfX5+RtlAo8N7e3tT8Nm7cyDs7O3lnZ2diWXbs2MEBgJ8+fdq5z7Zt24y0hUKB9/T08M2bN6s0iG3btvFcLmdc39fX11SbdHV1ZarDyZMneUdHh5F28+bNRjnpb1i/gYEB9Zmm3bx5M9+4cWMwv6Q60rywbPT+hUKBb926lQOA89yuBOCz9rUNth1Ni3Jst1OpVDLy9bUTymJSO/meLaZHWbGfU1dXl3P/vr6+puUVdXJgYEB919nZyXt6epx7bty4UaXp6ekJtmGpVOIbN240rvXJH9VTbIOBgQFVpt7eXkd/T58+nVgufA5239HZ2anay1d21EcsEwXWh6bP5XJOfVCufHJg61ToOVyO+oTPjrYb6oStF0uWLOGlUok3Gg2+ceNGns/nHTltNBqOnvmwdetWJ29sxxdffNGRqUajwbu7u/mSJUuCeTDGnDGAc/Hs7HQvvviiI0ehfhTv39PTo/Q+l8txxphRZju/JUuWGGNko9HgnZ2dfN26dUbehw4dcmTKV4+0NvS1GT4Lu1/01dPOr6Ojg2/cuJEzxlLLcinwxhtvcADgmzZtMtoeZcmuz4MPPuhc73tmVKY3b96s5IU+IyqvnOtnm/T8Q/fEcciWi127djk6ktbno57YY0WWOdjmzZud+Qv2mXa/h/2y3Xf65mCtjrkUvnEdy5llfuora0dHh5M/RU9PD8/lciofe87pq+/lgKS2ouMyAgD41q1bveNxb2+v8ZzoWItodm6C81r7hSiVSry7u9t5nmljCuf++QHKfmgctr8PjQuhMvtkxzdPyuVyqt1xHmaX3R4H7P4cyxKa/2OfT39jjPHe3l7VR61atUqVmzEWHMPt/ugKQSMSWBEREQqnT5/mXV1dyhA+ffo07+joMCYAOAggAVIqlVS6XC5ndJLd3d28UCgY+XV1dfFcLpeZwOro6HCuBzCN9UKhwAuFgio7TkQwjw0bNqhy4qQvaRJFkbUOp0+f5rlcjnd3d6u8N23aZJR1YGBADYIDAwPG9/ZkA+uEZacGOK075mc/CzpRxLJ1dHSothkYGFAD4OVocKeBEn8bNmxQpAnn/sk01h/bDmWDEifYTl1dXSqvvr6+TO1En+2OHTv4wMCAav/Ozk51f1s2aDlpffCZY7ok8iREYIXkESedJ0+eDLYh6gnWo1QqKcKTlhnbsbOzU+ne6dOnjX4Cy4UT4M7OTsPwsMuFaTdt2mQ8B3pvX9ltvadAncCy0Lalxgk+Q6wPLbc9EQ09h8tRn/BZbNq0iXPOFeGI/TvW9Vvf+pbRzocOHeKMMcdQeeihhwxix4fNmzfzfD6vrn3jjTd4R0eHQU5hGpRRO1801FEOi8Ui7+7uNq5Bog1JDvx+x44diqDbtWuXIr6onNtAAgvlFPvpUqnE33jjDZ7L5fjy5cuVrL3xxhu8q6uL5/N5o8w2gYUkDOp2sVjkmzZt4owxQ2995cFxDa9DsonW3x4vaDp7vGCMqfECy4EG0OUIbLt8Pq/qcujQIfWMkEBqNBqqTZP6EiSM7DHC1ntMh4Yg5/rZYhqU6Xw+b6QpFAp8yZIlKh0lxqhcHDp0KCgXSbpFy4GyiXJI5zbY16bNX2g/bvfLnZ2dahzBORQAGPdpdcy1geN6oVBQem8TS/b8lC5Y4j1oGioLNgmB5AMlwXAuifXDseZyg28OZI+BNoGFxDznmkixx0bfON/K3KRUKvGBgQG+Zs0aJQe0HbOOyT4kPaOsBNbJkyfVvIKOCwMDA8b8B/P1EVioS319fapdduzYYcz96LwB55hJ4wASWLQ/f+ONN3h3d7fRL+CckzFmzDltAqtYLDrPk3M9tl+Osp0BkcCKiIhIhj0Q4iBgG3P9/f1qBY9zPeD5VgSbIbBC19P74+TdJqXQM8t3fZYVtWbqgESXjc7OTt7V1eXUy3cfH4Fl35cO7qVSiRcKBa/3Cp3EYdnsiUaoflcSfOX3TaZ9E601a9YYbYztZMtR1nbyTRo51yt99vcdHR2GbIQ8E3O5XOqk30dg+eTRR8TYdUuqr00Ah/Q01E/4SNgsdcQ62e3ju7etY9g3+VaLsT4ISjDb5abpfLjcCSwqa5wLz027vDj5Xbt2rfG3bcSvWbPG+M7GG2+8oYgSCnvSXCwW1SpwVq+uF1980SApQvfylSdtso4EFmPM8apCzzC7fygWizyXyynPH5vAwvaixB1+XygUHI8hG/b9sC743ChhYpfLt2pvr7hjeS93AouWG0lL+5k2Gg2ey+USvQrweSxfvlx9h4agnRd6ICbBJl1D5K5dD59u0TqkyYUNW7eamb/YxA+iUCgYHiWc6/kFzTc05treUfaYG0JWTxx7zEXvyRAoCeHr6+051pWApDHQJrDs8RjbwL5+quYmnItnYl+LY7KvP8bFtxBwnA09o6wEFv3OLgd6ENrf+eYVSeO9TWD57IRGo8E7OjqMfgEAnH4B+31ab19fY/croTHc9nS+wtCIpxBGREQ4wGNj8fQQH+wTRZYtWwYAAKdOnYKOjg44fPiwN10ul2sq2PSaNWuc67u6upy94x0dHUYsJBq7xBdAEveqHz582Pl9zZo10NXV1VQdTp06BYVCIfFezaKnp8e5b6FQUHvhMU5FLpfz3vfw4cPQ2dmpnokdfPJyCPD5TgHbjmL58uWGfGM72TG1pqKdOjs7nXw6OjqUjGKcg66uLudZFgqFluJX+fQsi+6F5B4AYO3atbBz504YHh428kL9t+HTXwA3aCqVawS2yZkzZ+D06dMwPDzc0rMYHBxU/YaNzs5OVR87YKtd7is9BoX97LG+9rMrFApKBhhjsGbNGvi7v/s7KJfLkMvlYHh4GJ588snEUytPnToFnHOoVCqGPJdKJQAAFXQ4n8/DQw89BLfddhuUSqX/f3t3s542ki5w/FX37C26L8AiOeuxnOzbIjnrBqf3ATv7GLv3ATLrE6AvwEAuwEDvj8F9ATG+AYPnAox8LsB1Fp6qloT49Jcc/3/P089MsCiVSqVS8apUJZZlSalUmkhPzy9ycXFh2tOrqysREbP0ebS9vI1pbbzneRPtg65bnU5Hvnz5Eptet9udem3Puz/Yth17/FHR+h1t8/S19P79+9B2lmWJ53nmnCeRZVmhVVYty5rZlkRF25KzszOxLGtiu2BalmXJ+vr6zDk19TnRlFLy119/Tb3fBj+7izZ/Vr04OTkR27aX6oNNayOC+V60DY7bz+bm5q3rWbB/Gp28fGtrS5rNpuzs7EipVJqa10qlIuVyWRqNRuic27YtnudJrVaLLbunLno+9Ap50RWM77tvou/JcYvH5PN5c47jzp/znxUXH/sc6WNYZv/dblc8z5soR93GB0XPieM4opRauh9iWZZ8+vRJ3r59K/1+35T5yclJaOXFp4YAFgBjNBpJJpMR3/fFcRxxXXflJWB1Gre16ATd0e30TbXf708Eu2zblrW1NRERWVtbm8inTmuZYxj8Z8niuJv5fQWKZgXoHMcJHceqK9R9LxapR4PB4NGW7dadkn6/f2cTpC567cTlZVqd1e1BtBM1rX6tev3W63XTufI8T9bX1291PNO+q49z1eDYU6bbwHnlms/npVKpSKvVkr29PTk5ORHHcWZ23HWgalrbpPctcnN+Pc+Tbrcrx8fHoW2Hw6Hs7u5Kv98X13UnAgNKKbNi1Kr1I05cWqPR6Fbtw7Rre3Nzc+p35h1/ULBM4+j7xfdez6PnrlarSaVSEZFwW6IDoLNEy3Q4HMqbN29CfaToNvqh0jy3afN1vRgMBiYf0fO6aD6CFtl+1TZdW/VBQFz/NFr2OohdqVSk2WyK53nSaDQmyqZWq4nnebFB70ajIeVyWQqFgvnfuKD6U7RKG3kffZNZfQz9+ax6koRzNIhZAXseHQyMK8d0On03GYvheZ6sra2Zh9rdblcuLi4mgmRPCQEsAMb29rbYti2np6fmRtftdqXVai2d1n2OWFjkx6bOf7lcnvlDS/8omJbGosfgOI7kcjmpVqsLbX8XUqmUiNwspTvvRhoXWHvqI0ruWtwoIJGHKadgfd3b27v3/c3Ly2g0ig38PERZjEYjKRaLUiqVQk8Ic7ncQj86o2Zdxzq9uwx+fG/0CKNutysfP36Uer0e++Q8yrIs6fV6c9tqvRpTLpeTz58/m7SVUlKpVMyoGZ3OcDiUer1u9jHtwcFds217YsSHNh6P59YhXacXpZSSP/74Y+bxL0PfL55Tuz8cDmV/f1/K5bIpe6WU7O7uLj0SSH/PsiwZDofmfPd6Pfn69avZbm1tTf7973/HphEse9u2xbKspdv84HVxenpq6sXp6WmoXnwPo0aDdnZ2RERCZd/v9yf6p4VCQQqFgjSbTalUKrK5uRn6jshNnymTyUilUpm4JvVI+nK5bP5XRL6bINay7qtvMu+ePOu+kYRz5DjO0qvJ2rYthULhQX8niNzcJ4vForRaLfn06ZM0m00pFApP+mHGD4+dAQDJoUegRG/0q9BD76MN/LJLiE/7/ryAjX4i3+l0Ft5X1MbGxsLHMO31wfukn57oV2im2djYkE6nM9FheIpLqN+naefwIV6t0a/73Ka+3hVdr+Ku02azaYbw3xcdjIiOdpn2OvO8H2lbW1ux17HITfumn+YjnmVZ8v79ezOa9ezsTD59+jTzO57niVJq7sMPpZS8efNGCoWCHB4eTvwI16Oroq/CBf3yyy+xn8e5zQ96fX3GveqqXz+eZtVX9PQIm1nHv6itrS1RSk3cL5RSD37veiij0ci8Bhu0ahnqUXi6j6SUkj///NP83bIs2dzcNK/3R78bDWCtr6/PvX/HiZsWIHo/X6b/8hT0+30pFAqh/umselsoFKRWq4nv+xNlo0dmlctlMzovynEcM7on6dfHfQYq76Nvks1mp9ZDfU9e5KGSPkfZbNacI/296PV313Vev2a5TLqu6z5av/vjx48yGo2k1WrJn3/+OfEq+VNDAAuA4bquNJtN09FqtVorda5Ebn58Oo4jOzs7poEfDAZmlNei9vf3J77vOM5CT4JKpZJ0Oh2pVCqhVwoXnStFz1u0yDGUSiXxfV+2t7fNvkajkVQqlXvrLNq2LcViUcrlstTr9dBQb/20UuTmyb/v+7KzsxMqh2kdt+dKn0NdTr7vS6fTkVqtttD39Y8Jfc0s26nc29sz50Wfp8FgIPv7+w8ywkTTr3Tt7OyYAITv+6HXyO6TvrZarZb4vi++78v+/n5seeogdXDOu6hcLieu604cz/7+vrRarSc9D8RD8TxPNjY25N27d7HzuUXpEan1ej10HqPtzufPn828V6lUSj59+hSq/85/5ojSnf5eryd//PHHRN62trbk3bt3ofOr72UiN/VEz0+k/74My7Lk8PDQBNx0fk5PT82onGlBPcuy5OPHj9Lr9ULX8mg0mntt6x88s45/UXrOmVqtZoKE4/FYDg4OVkrvKdDzxug6qI931R/8+oe8PmedTmfih/3Hjx9lbW1N3r17Z7br9Xry7t27UL8hWC+WbfPX19dDryLF1YtgH0xv1+/3TR8q6fQ8SPpcBfunIhLbP202m6a/FQxcxR2vfu0sGMTSfbbguQjOG5REi9wDb+s2fRM9v1PwXAbvyfr6WfSeHHeO9PyEen+6nQvW+1VGrc6Sz+fN9aXLX/eTpimVSqZ/fhe/E1zXNSN1RWbf12zblq2tLalUKvf+EPIhEMACYOhJedPptKRSKWk2mysPdbVtW3q9noiIZDIZsSxLMpmM5PP5pUY7lEol2dnZMU82Rf5+QjNP8DWkdDpt8jDtNZDbHIPnedJut2UwGJh9pdNp6ff799pZLJVKUiwWpVgsSiqVEsuyZHt7OzQxs+d5UiqVQnmrVCozJ2F+jnQ5NZtNcw3U6/WFy8nzPMlms1IsFsWyrKWDv7q+1mo1c5700/yHfsWt3W5LNpuVQqEglmVJKpWSWq0m1WpVisXive7bdV1TDqlUSlKplKytrcXOP6Q7hKlUKhS0jWq327K1tRU6Ht2+fW8T9d4Hy7LMK5yLlJcO+Pz6669SKBTMedze3jbz1ugf7sHJlovFoqyvr8u7d+9MUGhtbU02NzfFsiz58OHDxETplmXJ0dGR2Zc+vwcHB+a6sW1bSqWSVKtVsSxrpR8z6XRajo+PZTwem/y8evVKrq6u5Pj4eGY7v729LdVqVTqdTuj+cHZ2NvXa1gGO6PHPG/02jS6nYBv1008/iVLqTifATxLHcUJtyU8//TS1LZnHsiz58uWLKKXMOfzjjz8mzkcqlTL1RG/322+/yeHhodi2HTrf09r8efWiWq3OvS6C/Re93fb2tuzt7SU+gKXb9XQ6Ldvb2yIS7p9alhXbP724uDB9NX3PipsDS9Ovluoglv2fBXGC50LXoaRa9B54G7fpm+zt7Ylt26ZPpel78vb2duie3Gg05t5j5p2jRqMhtm2beq8n9b9L+vra2NiQ7e1tc4+bNVLN8zypVqumbuv7gJ5Xclmu60o2m5VqtSo//PDDzD6nvp9cXFwkuj4vylJKqcfOBIBk0UGXu+rkBJ+CLfpDXK8ko5uo2+RJP4nTQ6FXCQYscwyrHO9t6WPU+5y237s+t9+jYFmuUk7Buraqx6hDcW5bFnex77iVIaPb6Xnx5pXVYx7PU1er1eSPP/6Q8/Pzpb53F2Wur4d5Dz/m7Us/Jb/tuR8MBiadZdNa5dpe9PgXpUdDPHb78lAWbUsWtWgbHzxvSin56aefps6Fdp/1Iin3k2VMa9fn9WHusr15KuW1zD3wtlYtG72oQPQ7q56vRfJx1+3mNKscw13WsUXbo0ajIR8+fJDz8/On3v9RBLAAJFI0gAUAeBxKKXnx4oVkMhk5PDx87OwAT0673ZbffvtNjo+Pn/zrOwCeFqWUvHr1SjY3N7+He7jiFUIAAABM0COWPn/+LFdXVyu/vgY8F6PRKDTvlO/70uv15ODgQFzXJXgF4MHoebE+f/680AIsTwUBLAAAAEyo1+tmLrjDw8On/toBcO/W1tak3++b+XdSqZS8efNGNjc35fj4+LGzB+AZabfbYlmW1Go1+fLly3dzD+cVQgCJdFdzlQAAVjMajWQ0Gt3Z3EHAc6GvndvMvQkAt/Gd3sOZAwsAAAAAAACJxhxYAAAAAAAASDYCWAAAAAAAAEg0AlgAAAAAAABINAJYAAAAAAAASDQCWAAehO/70mw2xff9O0mrXq9LpVK5k/Sesud+/E9Jv9+XTqez0LbU8duj3LAIveKtNhqNFr5XLfLdRethNC0sb5HyX6YdxnSLlCN1Gnch2B8ajUaPnZ1H9dyPXyOABeBB+L4vOzs7MhgMbpXOaDSSzc1NKZfL0u/3b53eU1apVCSVSj3rMnhKWq2W7O/vz91O1/FarSb9fp8fACuo1+tcG5hLKSXb29vy4sUL89lwOJTd3d25151SSjKZjLx69cp81uv1Qt8dj8eSSqXk3bt3c9MqFovy008/cb3fwrTy393dFZGbcm61WnJwcPCIufw+LHI/297elnQ6/UA5wvcqk8mYPv9zDuB0Oh158eKFtFqtx87Ko/vHY2cAAJZRr9dF5OZHhm3bj5uZB9RsNsVxHPE8z3y2tbUluVzuWZXDc1Aul0Xkpo5jvmazKbZtSy6XM59xbWARlmVJNpsNtavLyGazc+tYPp8P1U2Rm/tYNpsVx3FMPnK5nPzf//0fdfaO5fN5+fXXXx87G7dSr9dlY2Nj5Xo6jR7ZUiqV7jRdLZvNytbW1r2kjeeh2WzKYDCQ4XBo2svnoN/vy8XFheTzefPZxsYG19R/EMAC8KQMBgNxHOfZdfJ3dnak2WyGPvM87847tHh8FxcX4rruY2fjydjZ2ZFyuRwKEriuK+12+/EyhSejWCyu9D3LskyweZpUKjXRbg+HQ9nf35eNjY3QD7JcLjcR6MLtxJX/U6PrS6PRuPO0O52OlMvlewtgrXptAdrFxYXYtv2sgldKKdnZ2ZFMJhMKYKXTafo1/8ErhMAzNhgMFnrFxvd9GQwGc19n0tst+9rOaDS6s1ellklrNBotNT9JXLqLHO8iedJld5fDo6fleZX9rnpuk0Qfw13U4fs+p7MCtPdRx29zDU6rZ6PR6E7L8S7r3l1eG9+juHqzyHlY9Fwtss2y5/2u8hZ1l/enVS2ShyTk83tz27ZnkTbwLtq3Rfazarr3Wad0+veZh/vqEz6kRevHqu128Pt3dT5834+9dy6yj6hF+kOL/pZZps8f11+8qzK6r37NXfVxE9/nVwCenWazqWzbViKiREQ5jqMajYYSEdXr9ULblsvl0LYioorFYmib8XisPM8LbeM4jjo9PTXbDIfDifRrtdpE2sHvBPV6vdB2eh9au92eSMvzPDUcDkPpiIhqNpsmv4VCYWo5OY6jCoWCKpfLoX32ej11enqqHMcJfR7d1+npqXJdN5Sncrk8sZ9isTg134VCYeK4dZ71OYs7vuj3arXa3P0WCgVVKBRC5Toej1Uulwttl8vlppZZ0sSdw2nnIVofo3VYqZt6HK3ri5zTQqGgcrlcqGyj4uq453lT86fTDdY7fZ1Vq9WF6nhcmnHHE+V5Xuy10Ww21XA4XOjaWKUcXdc1aUXPabC89LUR3K++NqJp3tX5e+ocx1HlctmUayaTMX+rVquhepJOp0PXxuXl5cT53N7eVkopdX19rQqFgkqn0+rbt28z09FpRcvftu2J81Qul5VlWerbt2+h+pZOp0PnfZG8BY/1+PhYWZaler3ezDp6fX2tPM8Lfffw8FBZlmX2f319bb6nt4/WWZ1muVxW6XQ6dIzn5+cT39nf3w9tc3R0FCpTy7Km3ke/d7PKX/9b10Xt8vJSua47UW/m1flZ+4/Wnbjvxp1bx3HMvVrnNVpfdnZ2TBrHx8cTbW2z2VyorILf0//p78b1p6L3kbi+guu6ofa+UCiE7mH6Hhctn2XutfqePk+73Z44xml9wnK5bMo6mN/Hosstrq8e16+e1qeN9t+j9+LgfTJ6PqLtbaPRmPtbQOc72K/Q4vrM8/oa0foZTW/e7w6lJvuAs+7hcfnX9SOujBaps9EyUmqy3xVsew4PDyeOWbdXwXuTUjdtxDJ93Gibps+BZVmh7aL1JnpfSoBrAljAM6M7EHt7e2o8Hiulbm5M+sYSDDAVi0Vl27aqVqtqPB6r8XisqtXqRKM8HA5VLpcz3x0Oh8p1XeW6bmibYPr636VSyaTdbrendhDH47Hq9XomXR1E0vmPHlOv11OO4yjHccxnSinTQdnb21Onp6czO6SO4yjbtk0e9XHZtm0CWUrd3Eht254oE9u2VT6fN/vXZRct42hajuOYTtTp6WnonPV6PXOjmxbAchzHlEXwhhosB31u2+222U7/aAze4PP5fCh/w+FQtdvtqWWWNPoc6vIYj8fmOKPBVBExdV3Xadu2TbnpwEwwiKLPafBHQ1zZlkqluZ2nYB33PG/hOh53nbmuu1Adz+fzqlarmTR1PqOB7CjP80LlGr02Go2GUurvayMY9NTlGHdtRMsxWveC18ZwODTXRj6fjy2vaABLl4vOcz6fj702onVhkfP31On2cm9vz5StUjfnxrIsUx7n5+cql8upVCqlxuOxur6+Vvl8XqXT6dh2Qv8Qt21bbW5umm3Oz8+V67omHb2tDibo7S4vL1WpVFKWZYUC8brDrq8Vpf4O5ugf+YvmLRrA0nVFH3MwD7qOLhvAUurmejg6OjLHEmzPowGsy8tL5TiO2tzcNPX68PAwFMw7Pz+PbRcIYA2VUvMDWNfX1yqXy8UGr2bV+Vn71z/4dH3TAdZgPdE/PKP1MlrHdH2Ju/9Hz32wjs5rv5W6qSf6Gur1eqrX65ljq9Vqpt+jy0Mk/CAsGsDS/w6W47QAVly7HryPKfV3exTtV8YF06La7fbEdaH7VnF9wrh27zHpsozrGwbzr+/3cX1aHYSIll/wfOj7pO5TR++L0b5qsK+g60SwPxjNd3Dfwf6CUov1NXq9nsrn8+Y4ounlcjlT3/QDY9u2Q3VQ5yefz5v+9KxyD/bbg2XheV7ot0CwL6LUTf9N1+NgPyT68EVfc8G2Rd/zdNo6MB3tB04LYAXLVj8AirYD+nxF2wv90EMLBuH1cen+XIIQwAKeG8/zYn+EBTsySoVHckzbdlZHTgcEojdanX7cD8xF8x99QuY4TuyoIN1ZCv4oXuYJm77xBXU6nYWeRurAT1z+dV6DT8/i9hE3eiRoWgArmrdoOcw6t9H64XneRMfyKYk7h+PxeCLgGPdUdzweh8pNB1SidTabzYaCKouW7TR6dFP0OOI67frcRq/b24ySixvtEpfH6LHovETzqctN09dGtP0IXtvTrg29j+i1Efe0OG67aLlE9xMMrC9yzN8T/YM6SHeQg6M+lLoJrugf2jqQs7m5GZuuDhoEAwva+fl5KDDVbreVZVkTQXIdiEqlUuYz/eQ42EnX+9LbxQWZ4vIWF8CKjnSKprVKACt4zNEfUtEAVjQtnV6xWJx4Iv+UHircp2UCWMG6Ei3jeXV+3v6j2+iAmG7z4s6t3nf0WtL1JZjmtGvu+vp64t42S1wfYhrXdUNte7DPox/aRAOn0wJY0fLR/cXow7m4ES6LBLCiD1Cj+w8G4pL4YEKPBovWj2j+p93v590/o/3w6Ha6jzSvnB3HCdW1afme1h+O1qk4etTdIunpfAfb27g+4DRx+Z9WxtHfONN+0wT7P3F9T6VugtxxgaloGzQtgBW9b19eXirbts09bFp619fXKpvNmgBW9P6ZYNdM4g48M/1+P3bi2eiqFt1uV0RECoXCxLbZbNYsaRucdFYvcTsYDOTk5EREbt6jjnt/PZfLyf7+vmQyGWk0GitPRj4ajWQ0GsUek+d5Ytu29Pv90ESIy0yUG83XxsaGiEgoPRGZmGDy7OxMHMeJnUBWv1Ouy1gpFdpOv78+Go1WmrgyOgF49BjOzs5iPxe5OY7gvAWe50m5XJadnR0plUpPciLN6HHati22bZty1vXWtu2J82XbtimPwWBg6lOQZVnmnC5TtovS8zBls9mJv+k63u12Q/tc5nrS8zVcXFwsNQdItJ7puhHNZ7AMRW7KyLZt6XQ6sXkR+fva8H0/9to4OTm5k2tDp6H3q89fXBux6vl7SqLHra+NtbW10HlQSsna2pqMRiOxLMu0E/v7+7K3txd7bhzHmfjccRxZX1+Xs7MzUUrJycnJxIqSIjfX2NbWlnz9+nWiXQzWdcuyxHEcU08WzVuUZVmxK9e5rvsgS5grpaTb7cr6+vpEezMej8116rqurK2tyf7+vlxdXU3clxBPKSWfP3+Wbrcrx8fHoTqxSJ2fR/cTNJ2+7/uytrYm3W5XXNedqIt6VcyDg4OpfadgPnO53MQ9y3Eccz8aDAZm5WYtm80u1AfS8wReXFyYeXXijr1SqUiz2ZRer7fw4iPR8tH/1tetvkfEtdfzrl89d0+tVpv4m+d5ofLR4vq5jy2ufuj7ffQ8TOvjjUaj2PvnxcVFaPu4e3Yul5toe3zfl06nI1dXV6ZfEu0vxOVb90/i+lerzLHU7XZjz5muM51OJ7QwwTKL4ug6oun/H01jbW1NRP7+jdPpdMRxnJnttb6Oon1NpZS5/63yW2heH3cwGMjFxcXEPU23N3/++af59/v376XZbCa+z08AC3hG9E1vkQZJN3xxHSj92dXVlYjcNI7b29umQ607GbNuTLZty+npqVlpw3EcKZfLS3fA9TGtr69P3c8in901HeyI6/AFO7MiNx3AadusYt7x6fOyyE29VCqJUkparZY0m00pFAqJvqndRqfTmQiq6I6AyN8TpMadL73NMmW7qFnXov482olctI7r1S1d1zU/hhf97qz8zKInUp1V7/XxxP0IcRzHdB6XNa/ejsdjEbnb8/eUTCvXedfGp0+fTDtRq9WWaieC28z60R4MNi7T/qyat7jgQty1dl+urq5mXie+74vjOPLt2zfZ3d2VQqEg5XJ5pfvoc6Mfeu3s7Ey91ufV+Vmi20Svq6urq6npRH8Yx9H9immTV+u6a8es3rZI/iuVipTLZXEcR1zXndq/0uVYKBSWajOn5SH4g3vVNnje/fKpPIi4zf1e14m4B6hx989l64TneVP7CnGf6WDorLq6jHn3iWgQ6SH6/Iu017reTTsv95XPeddEkB5UoAPTmUxGDg8PE9fnJ4AFPCO68VqkAx7cNtro6e/rTs3Ozo44jiPtdtts22w2Y0dYBDmOI71eL9QJWl9fX+oJhG5Uo0+Ugnl9iJtXlL7Jz1r6Wufr9PT0QfM469zqH/BB+kdRs9mUSqUi/X5fhsPhA+T0YegyqFarM59M27Y995zqayLuR3Zc2S6Tv2nXrf4hu6xms2menAevuYcYYZLL5RJ5bWh3ef6eMtu2xbKsudeGZVkT7cTJyYmcn5/P3cdgMJDNzU2zv2n1XD8wWbY+3CZvQUopGQ6HD1Yf19bWJJ1Oy7dv32Zul06npdfryXA4lEqlIjs7O+L7vuzt7T1IPp8ix3Hk48ePcnBwIOvr66HRGovW+dvuX49Sj1qknus8lsvlmefZcZzQsS1Cj9KvVqtSLBbN53pUT1z6ug+47L6miQtCaMusIjft81VH/D+kaflfJICv+yG9Xm/hB9bR+hbcT7fbNe1nMDiuR0rPY9u2FAoFqVarC22/SHq3KZ/7sLa2Jo7jyOnp6dRtUqmUiIi02+0HfUg2qw+p25ugQqEghUJBer2e7O7uyqtXr+T8/PxR+mLT/PDYGQDwcPTTuLjAUvSJgB7SHR1+LvL3D1zdAA8GAzO0WVtmmVznP6/a2ba99I9n/dRi2qt6vu9PvB75EDY2NuYG8HQZP/QytXq/0bL2fT+2k6oVCgWp1Wrmtc3vha5Ds45d5GaYdqfTmdmBDnb4guaV7SL5i+ss6qWaV6nj+jXXYGf+IZYRX6Qc9fEsu9z2bek2La4dWvX8PWX6af0yx14oFOTTp08T7URcu9Hv9+Xq6kp++eUXsSxLfvnlF/O0PkgpZV7RuE3Hf1reovSIraiTk5M7C2rMqv+WZcnm5qZ5TWcR6XRaGo2GbGxsPMu6ugzLsqRYLEqpVJJyuRwaNbFKnV923xsbG+bV7SD96mi0PxVl27ZsbW0tHECYJ3qdioRfJ9avP8XRIxqj5XgbruvGXqOL3J90GzHtFfXbjO56SHHHqvu58+73s+5jcaLnVtfNYB9fJDx1xjL9QNd177Sfq89vtHz0+Y2bbuG+LdJe6/N2V9ftohzHEaXURJum25tpMpmMHB0die/7D57neQhgAc/M3t6e9Pt9qVQqoVd5ok8DPc+TXC4ntVpNWq2W2bZer0utVpNSqWQ6WDoopm+49Xp9bmN3cnJi0hX5+4f4Kk/GSqWSOabg0Prt7W1xXffenqLOUiwWxfd92d7eNnkajUZmBJPITRl7nic7Ozumo6F/vEU7gnZgzqDbBo/0fsvlcihN/eQ+qF6vm46H7/vSbrfvdajzY7BtW4rFopTLZanX66E6ubOzY7bTT7ozmYwpE31OdTkuU7bL5K9UKpnRI8E6vrOzI4VCYaXrRr9KoYPU+lXg+z63+XxefN+XnZ2diXIMvoI57drY398PpWf/Z16y4BD9Ven96nZP5+025+8pS6VSUiwWpVKpTFwbu7u7ZrtgOzEej+XPP/+caCeUUvLu3TtzjvTTXcdxTBudy+VkY2MjdN7H47EcHBzI169fVxrhEaxXwbzNe0rfbDZDedjd3ZWLiwv59OnT0nkIsm1blFLy119/icj0QNbHjx9lbW1N3rx5E2qD9bkQublmo/fR0Wgk//znP2+Vx+fAsiwplUoTwZdF6/xt5PN5WV9fl93dXdMf0PX85OQkVMds25a1tTXTR9Pzzr1//156vV7onjAajWR/f3/hdjD4wEX38fRnwXZ3f39/ZvtXLpfvNIiVz+fFtu3QvVb36Ra5P+k+YbAs+v2+ma7iqbxim8lkQvmvVCqmjzFL3H1sWt9SRGR/f9/UQ90PcBzH9HmiD7SX7Svo87GzszO1P7yMarVq7ss6vWCeHqPPv7e3J7Zty/b29tT2Oq6vqc9LtG1x/jMNy108VNT7DeZFtzfRtIPnxPd9Mz/WYwwEmOmBZ40HkAB66VT9n+d5ZgWN4MpI4/HYLCmv/7Nte2KFNb28bzA9vVKhXpEjugqhXuY4mO7e3t7cvHsxqxAqdbPKTzAP8p9VQ6IrnUnMiivTODErv0WPQ4tbKaXdbk/kyfO8iRVOstnsRFnErWKk/67zNG0Vwrjji34eXJI6eF7jlsYO5s1xnCe1RHvcOZz2eVxdj65Gt+g5XaRsp/FiViFU6ua6je47uCy13veidXw8Hofqnm3bqtFoKMdxFlqFcJlrI1pPFy1HvYT1rPYneG3otmHaKoTTro3g8Q6HQ+V53srn76madt71ynfR8xBd2S3493Q6bdoJ/XfHcSbuPZlMJnZlwkXOu16FMCr4+fX1dehaFBG1ubk5kbfoKoSWZamjo6NQHU2lUqHV/lZdhfD6+jpUDvpv0VUIlbpZnSp6nWxubppr7Nu3b8q27dDfF12B7nu0zCqEml7hMrjS37w6v+j+NV2ngp+fn59P3PvT6fRE+xmtL3olMf15tH5kMpmZK0RHBa8PXb+Dx66vvWjfK6491N/T5TRtFcJpq+sFjz3ar7Rt29w35q1cp5Qy97LoPSauTzjvvD40XW5xffW4FfLi7mvj8XhuO6rvk9H7cVw/L65ORM9F9HwHxfXRo8cTJ65vrdRNnVkkvUXry6z8x9WRuD5GtM6KiHJdd6XfVXo1XN0u6M8WWa0w7vPLy8uJ+rC3t2faLE3312blLQGuLaWUEgDPjh4Srp9Ed7tdyeVyMh6PY+e8Cm47Tb/fX+jJdjBd/fTkrkb16CcfSRoltEieFiljXV53eWzRvOVyObm6upJer7dU3r4XwWO1Z0zYq8tNv5Y7a5u7rot3ne5jXjNJvjb0k89Z18ZzMu/amHaelFKyu7tr5p1atD25y3bnNmnpBTnuuu1bps7q1+Gn5T+J973vwaL3g7vax7zrYVp9ue35j6vj99GmriK6MIoeIbfoaMyneG3okUW9Xs/UD9d1V8r/rPqlV5vToYB5ffjoPXEV31P/ZZp57bXIYm3LfVyD0TT1qKzLy8vYvCW0z68IYAEQkZt5DE5OTr6rybmxnNFoJJubm3c62SbwPRiNRpLJZCSXy3FtLCkawAKAVejXAKMLj3xvggGs+xQNYOF5UUrJixcvZHNzU46Ojh47O8tQzIEFPDOtVktardbEnAmtVkvK5fKj5g0PJzr3QHB+CVavwnNWr9djrw2fld0A4N7p+Y2CcwnpOZScyMIjAOar1+uhie9Ho9Gdzev4GP7x2BkA8LCUUhMTctq2LdVq9clMbInbOz09nQhYep4njUYjqUOGgQcxGo1Cy8eL3Fwbiy5JDgBYnV6YI7q6tO6jAFjO9fW1bG9vhz5Lp9NydHT0JFbljOIVQuCZWuQdbXzf9HvuIkI9AAK4Nu5WdIUzAJhHt8N6fq6kzHF03x6qvaRdfl6+o34Nc2ABAAAAAAAg0ZgDCwAAAAAAAMlGAAsAAAAAAACJRgALAAAAAAAAiUYACwAAAAAAAIlGAAsAAABzNZtNs4rRc6RX7XpqaQcNBgNpNpv3vh88PaPR6MH29VD1HcD3hwAWAAAAZlJKyc7OjnS73cfOislLp9Mxn52cnMjBwcG97nNzc1PevHlzL2lvb2/Lixcv7v1HfbfblZ2dnXvdB56eZrMp6XRa+v3+g+xve3tb0uk0QSwASyOABQAAgCel2WzK2dmZ+fdwOAwFtO5DLpeT9+/f33m6lmVJNpuVvb09sW3bfN7v9+/9mAAREdd1JZfLieM4d5qu7/tSr9cnRndls1nJ5/Oh+g4Ai/jHY2cAAAAASDLLsqRard5b+sViMfRvpZRUKhVJp9OSy+Xubb+AyE0Aq91u33m6g8FAisWibGxshIJj0foOAItiBBYAAACW4vu+9Pv9ma8A+b4vg8FgoXmzRqPRvc6vFZe+zt9dvca06LHeldFodKfnAIuV6aKm1a9F6/qqdXbRY/B9/07mvbrLMhNZrs7qbR9y/i4Aj0wBAADgWRiPx0pEVK1WC31eLBaVZVlqPB6bz759+6Ysy1K9Xk9dX18rEVHlclkVi0UlIua/crk8sZ9qtaps2zbbpNNpNRwOzd8PDw9N2p7nhbY7PT2deQzBvGjD4VC1223z7+PjY2VZlmo0GspxHJP+5uamGo/HE/mLO4boPj3PUzs7O+azcrmsLMtS3759C+0jeKzVatUcZzQ9x3HUzs6Our6+VoVCQaXTaVM2wfLVaWrn5+ehMhMRtb+/P/cceJ5nzh3Cvn37plzXNWVlWZapT+fn57HnUH/ebDaVUn/XkUKhoMrlciitZrOpzs/Pp9YTpf6us8fHx7F1NphmXJ09OjoKnW8RUYVCIbRNoVBQjuOodrttth0Oh6rRaJj/r7eL1kH9n74+G43GxP6KxaLZV7SOBvOs8xE0HA4nvqPzGj0Gz/NUrVYL7b9QKITaLwDfpWtGYAEAADwTtm2L53kTcyvpfwcnaf/rr7/EcRzxPM981mw2RSkl4/FYhsOhFItFqVQqocmfK5WKHBwcSLValfF4LOfn57K2tiZv3rwJjdJQSsnu7q6USiVRSsm3b99EKbXSZOyO40y8aqeUks+fP0uj0RCllHz58kVOT08lk8nI169f5fT0VC4vL2OPYVE6v3ofR0dHMh6PZXd3V0RE8vm8rK2tycnJSeh7/X5fLi4uYufUymQycnx8LK7riud50uv15OjoyOzvzZs3cnV1Jaenp6KUksPDQ2k0GlKpVEwa+hyUSiUZj8dyeXkpW1tbrEAYQykl7969k3Q6LePxWJRScnx8vPJ8UJ1OR8bjsan7GxsbUiwW5c2bN6G6Hqwnwbz8/vvvsXW22+2acxlXZ//973/L3t6eOYZqtSrNZlPq9fpEHuv1urTbben1erHzUO3t7Umv1zP/NRoNsW1bSqWSuK4rIiJnZ2dSLpdD+6vVaqYtqVar5rXbWq0mvV5P8vl8bJmNRiPJZDIyGo2k1+uJUkqGw6G4rivb29sT1+ZoNJJms2m2nXWsAL4zDxwxAwAAwCPSIxf0aIXT01Nl27bKZrNmJE90xJEe9bS5uRlK6/LyUlmWZUZ0XV5exo4OCY7mUurvEVh69IqmRyzNGkkRNwIrSo9mCaavj8myrNDIl+gxTNvntBFYwZE519fXqlgsqlQqFftv/Vk+nzejqqIjsKbtT6m/yy2Yf70P/f3Ly0tl2/bEd3WadP/DoiOppv190RFYwfOo1E1dFJHQ+YirF3ddZ5VSynXd0CgsPbIqOsoxOgIryvM85bruzH0ppZRt26FRWL1eT4nIRNlFR2DN2r/rusrzvIljiG7ruq7K5XJz8wjgSbtmEncAAIBnJJvNSrFYlMFgIJ7nycnJiXieJ57nSb1ely9fvojIzQiLvb29ie8G2bYt6+vrZmRVcN6a4GgfpZRJMziia2NjI5SeHvXi+/6drFC2vr4+kf7FxUVodE30GJYVPB7LsuSf//ynScuyLPn111+lXq9Lv983256cnEi5XF5qP0op6Xa7sr6+PjEiZTwey2g0MnMCXV1dTYzusixLPM9baaTZ98xxHFlfXzfnY9oooWXSi/7bsizZ2toyn1mWNbXO3abO6rnpLi4uzFxZ0fmhbNs2o6gWUalUzMioKN/3pdPpyNXVldnfKtdRq9USz/NiR715njcxcjBuW9d1mQsLeAYIYAEAADwjjuOI4zjS7XbN64SFQkF+/fVX2d/fl9FoJMPhUHzfDwVnFqF/QMa9qhb9YS4iE0GqtbW1pfb3FHieJ2tra/Lnn3+aH+MXFxehgMairq6uxPf90OuCmuM4oYDFqq/APTeWZcnx8bFUKhUpFApSLpelUChIqVRaKb1Fy31aXV/1vFUqFSmXy+I4jriuG3u9iUxec7OMRiMpl8vSbDYn8rW/vy+1Ws28Zry2trZy0Hk0Gk1ta2zbvrMJ4gE8fQSwAAAAnplcLif9ft+sINZoNCSVSsnW1pZ0u10ZjUaytbW19A/SVCollmVJu91eapTH98yyLCkWi1Kv1+V//ud/pNvtSqFQWClQsba2Jul0Wr59+zZ1m1QqJSLCj/4lpNNpaTabUi6XpVarmdFYwSBW3GinpOj1elKpVKRarUqxWDSfn52drZymnpdqb29vYlRat9uVWq0m7XY7NPdccA69Zdi2PXX01F2NxgTwfWASdwAAgGcmm83KYDAwo7B0MEWPyBoMBlIoFJZOd2try7zqhr99/PhRfN+XVqslf/75Z+zk7fNYliWbm5syGAxmvio17RwopZjEfQ7HcaRarYrneab8dPDk4uIitG3wddnHputD8JrVr5OuSgfx4l511ekGg1ej0WjlV/hyudzUet3pdCYWaADwfBHAAgAAeGY8zxPbts3rUtrW1pYMBgPp9/srveJm27ZZIa1er5s5cfr9/sSKa8+JbduytbUllUplYmXHadbW1qTT6Zi5rURuAmF6RUcdRNCvFOoV2PRKk/V6XVqtlojczJG1yuqOz4EuPx080YEUPYJQn7t6vW7KvNfryR9//PE4GY7hOI4opUwd8H1f9vf3Vx4lputOuVw27YH+z/d983qi3t9gMJDt7e2JkVI6MK6DgdPys7e3J7ZtSyaTCdVrfQyrvs4J4PtDAAsAAOAZyuVy4vt+KFClAyuu6670iptlWfLp0yd5//69FItFSaVSkkqlZHt7W/75z3/eUc6fHsuy5P3793JxcbHQj3HLsqRUKplXBl+9eiUiN68HHh8fi1JKNjc3xbIsSaVS0u12zYT4lmXJ0dGR/PLLL1IoFMSyLPnpp59EKbXSqLrv3Xg8lmazKel0WizLklevXkk6nZZPnz6JyE15Hh4ehsr8w4cPZrGDJPA8T4rFopTLZbEsS9LptGxsbCw9h53ITeBIj7oqFAqSyWRC/+nRmcViUYrFoliWJZlMRvL5fGwAq1gsSq1WE8uyTMAryrZt6fV64jhOqF4PBgPzOQCIiFhKLwsDAAAA3BH9CpPjOGLbNvPYrEBPyq7LMEiv+qYn5Y+jR2/FfR9heuTPrLLS2yR1frdZ9eU+LFq/lllYINhuELgCEKEIYAEAAAAAACDJFK8QAgAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAAAAINEIYAEAAAAAACDRCGABAAAAAAAg0QhgAQAAAACQEEqp0H9Pzbw8R4/r9PT0vrO0kvF4LPV6XTqdzsppTCuLVc+r7/vSbDaX3t8sg8FA+v3+Svl5aASwAAAAAABIgHq9Li9fvpQff/xRfv75Zzk4OHjsLC1lMBjImzdvZgZZ3r17Fzqu3377TSqVygPkbjmvXr2Ss7MzGY1GIjI7OFSv12OP4d27d9JqtUKfnZycyO7u7kp5Go/HU7+rlJI3b96Y/C6q2+3K169fV8rPQ/vHY2cAAAAAAIDnrlKpSLPZlEajIY7jiO/7cnZ29tjZWorv+9Lv92U0GkmhUJj4e7/fl36/L67rms+Oj4/Ftu0Hy+Mi+v2+2LYth4eH5rMXL15Ir9cTx3EmtnccRwqFgpRKJfPZYDAwo7fy+bz5vNPpiO/795Lvk5OTe0k3KRiBBQAAAADAI+v3+1IsFsXzPHEcR1zXDQU+RG5G2QyHQxkOhxMjguJGCAU/0/9/PB7LeDyem6ZSSsbj8cTn0e9HOY4jtm3HvpZWq9VCwSsRkfX19YkAlt5vNJ/L5D96DNE8z/uebduhVzlHo9HU1zq3trZM8E47OTkRz/MmyqHf70sul1s4H3HHHLfNPLP2s8jfk4AAFgAAAAAAj8x1XWk2m1MDFaenp/LixQv57bff5LfffpMXL16E5o/64YcfQq+P9ft9efPmjfn3ixcvpFKpyOvXr+W3334zab569Urevn1r0hW5CZi8e/dOXr58afY1HA5FROTz58/y9u3bmcdSKBQmXqkbDodydnY2EZR78+ZN6DW7er1u8vj69WsziumHH34I/U1EpNfryc8//zy1TA4ODuTly5fy4cMH+fnnn0N5efPmjTnuly9fSrvdFpGbkXBv376Vfr8vP/74o3z48EF+/PFHERF5+fKlvHz5cuJ4bdsWz/NCI+Y6nY7s7e2ZcyEiMhqNZDAYyNbWlojcBPR0/t++fSsvX74MvbL4448/Sq1Wk9evX8vvv/8e2qdSSsrlcug70/T7/dB+gvVCp7W7uxubj0RRAAAAAADgUQ2HQ5VOp5XjOKrRaKjr6+vQ32zbVo1Gw3xWLpeVbdtqPB4rpZQSETUcDs3fe72e8jzP/NtxHOV5nhqPx2o8HqvhcKgcx1HVatVso9MqFosql8uZz4vFoklrOByqXq8Xewy9Xk85jqPG47GybTu0XT6fV9VqVTUajVC+PM9TzWZTKaVUo9FQjuOEjiN4fIVCIZT/6D7K5bLZf6/XC5VPME3HcVS5XDb/brfboW2jZaf3H0wjqlarme+Mx2MlImo8HqtCoWD21Wg0lOu6SimlTk9PlW3b6vT0VCml1PX1daicr6+vlYionZ0ds4/z83NlWZa6vr5WpVJJpdNpk6fr62tlWVZsHk9PT82xXV5eqlQqZcqtXC6H/n19fa0ymYwqFotTj/WRXDMCCwAAAACAR+Y4jpyfn0upVJLPnz+HRj3peaOC80rp+ZYGg8HC+yiVSmLbtnnFz3EcKRaL5u/6Vb5msynv3783r5Rls1kzishxHPE8b+Z+bNuWYrFoRlaNRiNptVqhV+fitFotKZfLoXmmgq8X5vN5k/9utyuu64byUiqVxPd9GY1GYtu2XF1dSafTEaWUSbPb7ZpttVwuJ47jmL+tQpeR7/vm9UHbtmVra8uUXb/fN/nV5aFfqbQsSz59+iQnJydm9JNlWfL+/fvYcvr69ascHx/HzskV5bquKKXk9PRUOp2OrK+vy8XFRejvOl+WZcnHjx8nJp9PAgJYAAAAAAAkRKFQkPPzc8nlcuZVr4uLi9hAheu6oUDEMqal6fu++L4v//rXv+TDhw/y4cMH+fz5s2QymaXS39vbMxOW1+t1KRQKc4Mto9FI1tfXp/49GMzyfT82Pdu25ezsTFzXlcPDQxMM1CsjjsfjqWV5m9fmHMcRx3FkMBhIu902wbpcLhcKbGWzWRG5eY0xmg99fMFJ3qPbKKXk4OBAPn78uFDwSkTMa4j/+te/5OzsTK6uribyHrS+vn5vE83fBqsQAgAAAACQMKVSSWq1mhlNFBdcGQwGUwM+0SBF1LQ09QinL1++zB1pNS/9bDYr9XpdOp2O9Hq9hb4zK4gUDGBN29b3fVMmhUJBCoWCNJtN2d/fF8dxJJVKxX5vNBqZ4NKqcrmcdLtdOTk5MSPb9PxY9XpdfN8Xz/NEKSWpVGoiSKTzNSswZVmW/O///q+8fft2YgRanPF4LAcHB3J+fi6O44hSamJ1SxWZtP3i4mJisv0kYAQWAAAAAACPrNPpmBXglFLSarUknU6L4ziSz+fl7OxM2u22+Xu9XpdUKmUCGK7rSr1eNyvv1Wq1mfvTaTabzdBKeyIim5ub0mq1zOfj8di8qjgajRYKRoncBJDK5bK4rrvQaKFcLieVSiVUDtMCWtlsdqJMKpWKKRPf9006euJ43/dla2tLrq6upFKpmO+12+25QRvbtueu0JfNZs1Ir2BanudJs9kMvaaXz+el1WqFjvXr16+Sy+UmVmWM2tzclC9fvsi7d+9Ck9aLSGjlxGBeg+V5cnIS+k632zX5uLy8lIODg1sH8+4DASwAAAAAAB7ZX3/9ZVa5+/nnn6XVasnR0ZGI3ARPDg8P5ffff5fXr1/Ly5cvpdvtyvHxsfl+qVSSbrcrb9++ldevX0s2mxXLsszfg/8/mObnz59Nmp8/fxYRkcPDQzk7O5OXL1/K69ev5fXr1yaQ9Pnz54kV8YKC+/E8TzKZjFmNL26b4P8vlUqyvb0tL1++lLdv38rPP/9sAmfR/DuOM1EmJycnpkxGo1EonVwuZ4JDx8fH0mq1zLH9/vvvcnR0FAqyRfdXLBblw4cPM1dgdF1XLMuaeN1ya2tLLi4uQnOAeZ4ne3t78vbtW7Py38nJiXz58mVqHoKfFQoF+fLli/z3f/93aB60ly9fyo8//ig//vij/OMf/5BUKiWfPn0yx/rhwwfxPC+U9tbWllmd8L/+679ka2srNEdYUlhqVvgQAAAAAAA8CD3/lMj018hmvWamv69fA1zUtDSnpac/uy/LHsey+Z/3vVn7WbZsHzPdIF0Ws471IfJxC4oAFgAAAAAAAJJM8QohAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEo0AFgAAAAAAABKNABYAAAAAAAASjQAWAAAAAAAAEu0fIqIeOxMAAAAAAADAFOr/AfLGsciDusADAAAAAElFTkSuQmCC\n"
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "prompt = processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
        "\n",
        "inputs = processor(prompt, [image], return_tensors=\"pt\").to(\"cuda:0\")"
      ],
      "metadata": {
        "id": "yJwhEe2fYAMF"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "prompt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 105
        },
        "id": "dGPFRsmMYFWB",
        "outputId": "a1c3cac3-1a34-4e01-a1f2-b58ed711c5c9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"<|user|>\\n<|image_1|>\\nWhat is shown in this image?<|end|>\\n<|assistant|>\\nThe chart displays the percentage of respondents who agree with various statements about their preparedness for meetings. It shows five categories: 'Having clear and pre-defined goals for meetings', 'Knowing where to find the information I need for a meeting', 'Understanding my exact role and responsibilities when I'm invited', 'Having tools to manage admin tasks like note-taking or summarization', and 'Having more focus time to sufficiently prepare for meetings'. Each category has an associated bar indicating the level of agreement, measured on a scale from 0% to 100%.<|end|>\\n<|user|>\\nProvide insightful questions to spark discussion.<|end|>\\n<|assistant|>\\n\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inputs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QnRSj4l1YGnS",
        "outputId": "0fad4fa9-0103-4c32-d38e-20793e06a671"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'input_ids': tensor([[    1, 32010, 29871,  ..., 29871,    13, 32001]], device='cuda:0'), 'attention_mask': tensor([[1, 1, 1,  ..., 1, 1, 1]], device='cuda:0'), 'pixel_values': tensor([[[[[ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
              "           [ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
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              "           ...,\n",
              "           [ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
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              "           [ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303]],\n",
              "\n",
              "          [[ 2.0749,  2.0749,  2.0749,  ...,  2.0749,  2.0749,  2.0749],\n",
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              "\n",
              "          [[ 2.1459,  2.1459,  2.1459,  ...,  2.1459,  2.1459,  2.1459],\n",
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              "\n",
              "\n",
              "         [[[ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
              "           [ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
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              "\n",
              "          [[ 2.0749,  2.0749,  2.0749,  ...,  2.0749,  2.0749,  2.0749],\n",
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              "\n",
              "          [[ 2.1459,  2.1459,  2.1459,  ...,  2.1459,  2.1459,  2.1459],\n",
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              "\n",
              "\n",
              "         [[[ 1.9303,  1.9303,  1.9303,  ...,  1.9303,  1.9303,  1.9303],\n",
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              "           [-1.2083, -1.1937, -1.1937,  ...,  1.9303,  1.9303,  1.9303],\n",
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              "           [-1.1937, -1.1937, -1.1937,  ...,  1.9303,  1.9303,  1.9303]],\n",
              "\n",
              "          [[ 2.0749,  2.0749,  2.0749,  ...,  2.0749,  2.0749,  2.0749],\n",
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              "\n",
              "          [[ 2.1459,  2.1459,  2.1459,  ...,  2.1459,  2.1459,  2.1459],\n",
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              "\n",
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              "\n",
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              "\n",
              "\n",
              "         [[[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
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              "\n",
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              "\n",
              "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
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              "\n",
              "\n",
              "         [[[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
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              "           ...,\n",
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              "\n",
              "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           ...,\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
              "\n",
              "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           ...,\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],\n",
              "           [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]]]]],\n",
              "       device='cuda:0'), 'image_sizes': tensor([[1008, 1344]], device='cuda:0')}"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "generation_args = {\n",
        "    \"max_new_tokens\": 500,\n",
        "    \"temperature\": 0.0,\n",
        "    \"do_sample\": False,\n",
        "}"
      ],
      "metadata": {
        "id": "u5Re8-cJYS5O"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "generate_ids = model.generate(**inputs, eos_token_id=processor.tokenizer.eos_token_id, **generation_args)\n",
        "\n",
        "# remove input tokens\n",
        "generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]\n",
        "response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]\n",
        "\n",
        "print(response)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "XMss0xdwYIWH",
        "outputId": "31d45327-92ff-41e5-ce23-c1c64e1c148a"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:515: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "RuntimeError",
          "evalue": "FlashAttention only supports Ampere GPUs or newer.",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-10-1c35713a1209>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgenerate_ids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meos_token_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meos_token_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mgeneration_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# remove input tokens\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mgenerate_ids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgenerate_ids\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'input_ids'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprocessor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerate_ids\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskip_special_tokens\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclean_up_tokenization_spaces\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py\u001b[0m in \u001b[0;36mdecorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    113\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mctx_factory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 115\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    116\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self, inputs, generation_config, logits_processor, stopping_criteria, prefix_allowed_tokens_fn, synced_gpus, assistant_model, streamer, negative_prompt_ids, negative_prompt_attention_mask, **kwargs)\u001b[0m\n\u001b[1;32m   1734\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1735\u001b[0m             \u001b[0;31m# 13. run sample (it degenerates to greedy search when `generation_config.do_sample=False`)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1736\u001b[0;31m             result = self._sample(\n\u001b[0m\u001b[1;32m   1737\u001b[0m                 \u001b[0minput_ids\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1738\u001b[0m                 \u001b[0mlogits_processor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprepared_logits_processor\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py\u001b[0m in \u001b[0;36m_sample\u001b[0;34m(self, input_ids, logits_processor, stopping_criteria, generation_config, synced_gpus, streamer, logits_warper, **model_kwargs)\u001b[0m\n\u001b[1;32m   2373\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2374\u001b[0m             \u001b[0;31m# forward pass to get next token\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2375\u001b[0;31m             outputs = self(\n\u001b[0m\u001b[1;32m   2376\u001b[0m                 \u001b[0;34m**\u001b[0m\u001b[0mmodel_inputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2377\u001b[0m                 \u001b[0mreturn_dict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compiled_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1531\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1532\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1533\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1534\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1539\u001b[0m                 \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_pre_hooks\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_hooks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1540\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1542\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1543\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/.cache/huggingface/modules/transformers_modules/microsoft/Phi-3-vision-128k-instruct/dbcdaaacf52c8e40cf8de6d6ffa6ff6860e5f256/modeling_phi3_v.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, pixel_values, image_sizes, labels, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m   1298\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1299\u001b[0m         \u001b[0;31m# decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1300\u001b[0;31m         outputs = self.model(\n\u001b[0m\u001b[1;32m   1301\u001b[0m             \u001b[0minput_ids\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minput_ids\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1302\u001b[0m             \u001b[0mattention_mask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mattention_mask\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compiled_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1531\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1532\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1533\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1534\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1539\u001b[0m                 \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_pre_hooks\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_hooks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1540\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1542\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1543\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/.cache/huggingface/modules/transformers_modules/microsoft/Phi-3-vision-128k-instruct/dbcdaaacf52c8e40cf8de6d6ffa6ff6860e5f256/modeling_phi3_v.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, input_ids, attention_mask, position_ids, past_key_values, inputs_embeds, pixel_values, image_sizes, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m   1174\u001b[0m                 )\n\u001b[1;32m   1175\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1176\u001b[0;31m                 layer_outputs = decoder_layer(\n\u001b[0m\u001b[1;32m   1177\u001b[0m                     \u001b[0mhidden_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1178\u001b[0m                     \u001b[0mattention_mask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mattention_mask\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compiled_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1531\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1532\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1533\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1534\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1539\u001b[0m                 \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_pre_hooks\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_hooks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1540\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1542\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1543\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/.cache/huggingface/modules/transformers_modules/microsoft/Phi-3-vision-128k-instruct/dbcdaaacf52c8e40cf8de6d6ffa6ff6860e5f256/modeling_phi3_v.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache, **kwargs)\u001b[0m\n\u001b[1;32m    872\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    873\u001b[0m         \u001b[0;31m# Self Attention\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 874\u001b[0;31m         attn_outputs, self_attn_weights, present_key_value = self.self_attn(\n\u001b[0m\u001b[1;32m    875\u001b[0m             \u001b[0mhidden_states\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhidden_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    876\u001b[0m             \u001b[0mattention_mask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mattention_mask\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compiled_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1531\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1532\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1533\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1534\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1539\u001b[0m                 \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_pre_hooks\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_hooks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1540\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1542\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1543\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/.cache/huggingface/modules/transformers_modules/microsoft/Phi-3-vision-128k-instruct/dbcdaaacf52c8e40cf8de6d6ffa6ff6860e5f256/modeling_phi3_v.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, hidden_states, attention_mask, position_ids, past_key_value, output_attentions, use_cache, **kwargs)\u001b[0m\n\u001b[1;32m    560\u001b[0m         \u001b[0mvalue_states\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue_states\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    561\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 562\u001b[0;31m         attn_output = self._flash_attention_forward(\n\u001b[0m\u001b[1;32m    563\u001b[0m             \u001b[0mquery_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    564\u001b[0m             \u001b[0mkey_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/.cache/huggingface/modules/transformers_modules/microsoft/Phi-3-vision-128k-instruct/dbcdaaacf52c8e40cf8de6d6ffa6ff6860e5f256/modeling_phi3_v.py\u001b[0m in \u001b[0;36m_flash_attention_forward\u001b[0;34m(self, query_states, key_states, value_states, attention_mask, query_length, dropout, softmax_scale, use_sliding_windows)\u001b[0m\n\u001b[1;32m    658\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    659\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0muse_sliding_windows\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 660\u001b[0;31m                 attn_output = flash_attn_func(\n\u001b[0m\u001b[1;32m    661\u001b[0m                     \u001b[0mquery_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    662\u001b[0m                     \u001b[0mkey_states\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/flash_attn/flash_attn_interface.py\u001b[0m in \u001b[0;36mflash_attn_func\u001b[0;34m(q, k, v, dropout_p, softmax_scale, causal, window_size, alibi_slopes, deterministic, return_attn_probs)\u001b[0m\n\u001b[1;32m    829\u001b[0m             \u001b[0mpattern\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnegative\u001b[0m \u001b[0mmeans\u001b[0m \u001b[0mthat\u001b[0m \u001b[0mlocation\u001b[0m \u001b[0mwas\u001b[0m \u001b[0mdropped\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnonnegative\u001b[0m \u001b[0mmeans\u001b[0m \u001b[0mit\u001b[0m \u001b[0mwas\u001b[0m \u001b[0mkept\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    830\u001b[0m     \"\"\"\n\u001b[0;32m--> 831\u001b[0;31m     return FlashAttnFunc.apply(\n\u001b[0m\u001b[1;32m    832\u001b[0m         \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    833\u001b[0m         \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m    596\u001b[0m             \u001b[0;31m# See NOTE: [functorch vjp and autograd interaction]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    597\u001b[0m             \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_functorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munwrap_dead_wrappers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 598\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    599\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    600\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_setup_ctx_defined\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/flash_attn/flash_attn_interface.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(ctx, q, k, v, dropout_p, softmax_scale, causal, window_size, alibi_slopes, deterministic, return_softmax)\u001b[0m\n\u001b[1;32m    509\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msoftmax_scale\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    510\u001b[0m             \u001b[0msoftmax_scale\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m**\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 511\u001b[0;31m         out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = _flash_attn_forward(\n\u001b[0m\u001b[1;32m    512\u001b[0m             \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    513\u001b[0m             \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/flash_attn/flash_attn_interface.py\u001b[0m in \u001b[0;36m_flash_attn_forward\u001b[0;34m(q, k, v, dropout_p, softmax_scale, causal, window_size, alibi_slopes, return_softmax)\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0mmaybe_contiguous\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontiguous\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstride\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m     \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mmaybe_contiguous\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m     out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = flash_attn_cuda.fwd(\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m         \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mRuntimeError\u001b[0m: FlashAttention only supports Ampere GPUs or newer."
          ]
        }
      ]
    }
  ]
}