{"cells":[{"cell_type":"markdown","metadata":{"id":"aR-3PCa0zt7D"},"source":["# Breast Cancer Segmentation Using Transformers\n","\n","- **Semantic segmentation** เป็นการทำนายที่ต้องการนำภาพมาและแบ่งประเภทของแต่ละพิกเซลในภาพ Semantic segmentation มีประโยชน์และถูกนำมาใช้ในหลากหลายแอพพลิเคชั่น เช่น การตัดแบ่งภาพถ่ายทางการแพทย์ และรถยนจ์ขับเคลื่อนอัจฉริยะ ยกตัวอย่างเช่น ในกรณีของรถส่งพิซซ่าอัจโนมัติ การนำ semantic segmentation มาช่วยจะสามารถไกด์ให้รถยังขับอยู่บนทางเท้าได้ ไม่ขับเข้าไปในบริเวณที่ผิดพลาดได้ (ดูตัวอย่างจาก https://huggingface.co/blog/fine-tune-segformer)\n","\n","- วิธีการเก็บข้อมูลของ Semantic segmentation ปกติ จะทำการเก็บภาพที่เราสนใจมาเป็นข้อมูลตั้งต้น จากนั้นใช้ image labeling tools เช่น [Segments.ai](https://segments.ai/) หรือ [CVAT](https://github.com/opencv/cvat) ในการเก็บข้อมูลพิกเซลชนิดต่างๆ (บางครั้งเรียก \"mask\") ในการใช้เป็น label ในการเทรน แต่ในตัวอย่างนี้เราจะใช้ชุดข้อมูลภาพถ่ายอัลตราซาวน์ (ultrasound) ของเต้านม เพื่อตรวจจับเนื้องอกหรือมะเร็งเต้านม\n","\n","- โดยการทำงานของโมเดลจะนำภาพมาทำการทำนายและสรุปว่าแต่ละ pixel ควรเป็นประเภทใด เช่น พื้นหลัง, เนื้องอก, หรือมะเร็ง โดยในกรณีนี้เราจะนำโมเดล [Segformer](https://huggingface.co/docs/transformers/model_doc/segformer) มา fine-tune สำหรับการตรวจจับบริเวณต่างๆที่อาจเป็น เนื้องอก (benign) หรือเนื้อร้าย (malignant) จากภาพถ่ายอัลตราซาวน์ โดยในที่นี้เราจะใช้โมเดลที่ขนาดเล็กที่สุดของ Segformer นั่นคือ `MiT-b0` มาทดลอง fine-tune เพื่อตัดแบ่งภาพของเรา\n","\n","- สำหรับการวัดผลของ Segmentation ส่วนมากจะใช้ Dice Score (เท่ากับ 2 x Overlapped Area / (Actual Area + Predicted Are) ) หรือ Intersection over union (IoU, เท่ากับ Overlapped Area / Union of actual area and predicted area)\n","\n","- ตัวอย่างนี้จะแบ่งเป็นการเตรียมข้อมูลที่โหลดมาได้จาก Kaggle, การนำโมเดล Segformer มา fine-tune, และจากนั้นคือการนำโมเดลไปทำนายผลจากภาพใน validation set\n","\n","\n","Reference: https://huggingface.co/blog/fine-tune-segformer"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":27589,"status":"ok","timestamp":1688479857280,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"OLoLjNG4znH5","outputId":"0cd23921-8bb1-4a03-c603-11af6bcf5e52"},"outputs":[{"name":"stdout","output_type":"stream","text":["Requirement already satisfied: kaggle in /usr/local/lib/python3.10/dist-packages (1.5.13)\n","Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.10/dist-packages (from kaggle) (1.16.0)\n","Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from kaggle) (2023.5.7)\n","Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.8.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.27.1)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from kaggle) (4.65.0)\n","Requirement already satisfied: python-slugify in /usr/local/lib/python3.10/dist-packages (from kaggle) (8.0.1)\n","Requirement already satisfied: urllib3 in /usr/local/lib/python3.10/dist-packages (from kaggle) (1.26.16)\n","Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.10/dist-packages (from python-slugify->kaggle) (1.3)\n","Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (2.0.12)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (3.4)\n","Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.30.2)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.2)\n","Requirement already satisfied: huggingface-hub<1.0,>=0.14.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.15.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.22.4)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2022.10.31)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.27.1)\n","Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.13.3)\n","Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.3.1)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.65.0)\n","Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (2023.6.0)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (4.6.3)\n","Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.16)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.5.7)\n","Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.12)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n","Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (2.13.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.22.4)\n","Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (9.0.0)\n","Requirement already satisfied: dill<0.3.7,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.6)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (1.5.3)\n","Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.27.1)\n","Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.65.0)\n","Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.2.0)\n","Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets) (0.70.14)\n","Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.8.4)\n","Requirement already satisfied: huggingface-hub<1.0.0,>=0.11.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.15.1)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (23.1)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.1.0)\n","Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (2.0.12)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.4)\n","Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.2)\n","Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.2)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.3)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.11.0->datasets) (3.12.2)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.11.0->datasets) (4.6.3)\n","Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (1.26.16)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2023.5.7)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.4)\n","Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2022.7.1)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n","Requirement already satisfied: evaluate in /usr/local/lib/python3.10/dist-packages (0.4.0)\n","Requirement already satisfied: datasets>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from evaluate) (2.13.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from evaluate) (1.22.4)\n","Requirement already satisfied: dill in /usr/local/lib/python3.10/dist-packages (from evaluate) (0.3.6)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from evaluate) (1.5.3)\n","Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from evaluate) (2.27.1)\n","Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from evaluate) (4.65.0)\n","Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from evaluate) (3.2.0)\n","Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from evaluate) (0.70.14)\n","Requirement already satisfied: fsspec[http]>=2021.05.0 in /usr/local/lib/python3.10/dist-packages (from evaluate) (2023.6.0)\n","Requirement already satisfied: huggingface-hub>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from evaluate) (0.15.1)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from evaluate) (23.1)\n","Requirement already satisfied: responses<0.19 in /usr/local/lib/python3.10/dist-packages (from evaluate) (0.18.0)\n","Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.0.0->evaluate) (9.0.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets>=2.0.0->evaluate) (3.8.4)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.0.0->evaluate) (6.0)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.7.0->evaluate) (3.12.2)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.7.0->evaluate) (4.6.3)\n","Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->evaluate) (1.26.16)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->evaluate) (2023.5.7)\n","Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->evaluate) (2.0.12)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->evaluate) (3.4)\n","Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->evaluate) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->evaluate) (2022.7.1)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (23.1.0)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (6.0.4)\n","Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (4.0.2)\n","Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (1.9.2)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (1.3.3)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets>=2.0.0->evaluate) (1.3.1)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->evaluate) (1.16.0)\n","Requirement already satisfied: transformers[torch] in /usr/local/lib/python3.10/dist-packages (4.30.2)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (3.12.2)\n","Requirement already satisfied: huggingface-hub<1.0,>=0.14.1 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (0.15.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (1.22.4)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (23.1)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (6.0)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (2022.10.31)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (2.27.1)\n","Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (0.13.3)\n","Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (0.3.1)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (4.65.0)\n","Requirement already satisfied: torch!=1.12.0,>=1.9 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (2.0.1+cu118)\n","Requirement already satisfied: accelerate>=0.20.2 in /usr/local/lib/python3.10/dist-packages (from transformers[torch]) (0.20.3)\n","Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate>=0.20.2->transformers[torch]) (5.9.5)\n","Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers[torch]) (2023.6.0)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers[torch]) (4.6.3)\n","Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch!=1.12.0,>=1.9->transformers[torch]) (1.11.1)\n","Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch!=1.12.0,>=1.9->transformers[torch]) (3.1)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch!=1.12.0,>=1.9->transformers[torch]) (3.1.2)\n","Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch!=1.12.0,>=1.9->transformers[torch]) (2.0.0)\n","Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch!=1.12.0,>=1.9->transformers[torch]) (3.25.2)\n","Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch!=1.12.0,>=1.9->transformers[torch]) (16.0.6)\n","Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (1.26.16)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (2023.5.7)\n","Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (2.0.12)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (3.4)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch!=1.12.0,>=1.9->transformers[torch]) (2.1.3)\n","Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch!=1.12.0,>=1.9->transformers[torch]) (1.3.0)\n"]}],"source":["!pip install kaggle\n","!pip install transformers\n","!pip install datasets\n","!pip install evaluate\n","!pip install transformers[torch]"]},{"cell_type":"markdown","metadata":{},"source":["## Download Data"]},{"cell_type":"code","execution_count":16,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8504,"status":"ok","timestamp":1688479865779,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"Xo9VZgwbzx8r","outputId":"e6ba057a-0070-4978-9d3e-a58bc99dbf61"},"outputs":[{"name":"stdout","output_type":"stream","text":["Downloading breast-ultrasound-images-dataset.zip to /content\n"," 92% 180M/195M [00:01<00:00, 171MB/s]\n","100% 195M/195M [00:01<00:00, 184MB/s]\n","Archive: breast-ultrasound-images-dataset.zip\n"," inflating: Dataset_BUSI_with_GT/benign/benign (1).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (1)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (10).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (10)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (100).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (100)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (100)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (101).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (101)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (102).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (102)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (103).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (103)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (104).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (104)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (105).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (105)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (106).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (106)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (107).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (107)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (108).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (108)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (109).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (109)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (11).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (11)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (110).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (110)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (111).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (111)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (112).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (112)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (113).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (113)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (114).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (114)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (115).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (115)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (116).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (116)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (117).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (117)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (118).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (118)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (119).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (119)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (12).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (12)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (120).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (120)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (121).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (121)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (122).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (122)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (123).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (123)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (124).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (124)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (125).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (125)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (126).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (126)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (127).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (127)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (128).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (128)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (129).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (129)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (13).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (13)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (130).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (130)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (131).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (131)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (132).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (132)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (133).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (133)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (134).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (134)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (135).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (135)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (136).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (136)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (137).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (137)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (138).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (138)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (139).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (139)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (14).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (14)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (140).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (140)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (141).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (141)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (142).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (142)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (143).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (143)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (144).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (144)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (145).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (145)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (146).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (146)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (147).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (147)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (148).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (148)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (149).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (149)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (15).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (15)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (150).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (150)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (151).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (151)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (152).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (152)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (153).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (153)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (154).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (154)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (155).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (155)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (156).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (156)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (157).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (157)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (158).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (158)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (159).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (159)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (16).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (16)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (160).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (160)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (161).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (161)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (162).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (162)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (163).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (163)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (163)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (164).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (164)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (165).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (165)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (166).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (166)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (167).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (167)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (168).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (168)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (169).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (169)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (17).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (17)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (170).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (170)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (171).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (171)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (172).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (172)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (173).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (173)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (173)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (174).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (174)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (175).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (175)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (176).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (176)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (177).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (177)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (178).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (178)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (179).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (179)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (18).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (18)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (180).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (180)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (181).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (181)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (181)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (182).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (182)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (183).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (183)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (184).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (184)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (185).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (185)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (186).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (186)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (187).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (187)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (188).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (188)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (189).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (189)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (19).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (19)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (190).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (190)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (191).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (191)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (192).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (192)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (193).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (193)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (194).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (194)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (195).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (195)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (195)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (195)_mask_2.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (196).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (196)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (197).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (197)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (198).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (198)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (199).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (199)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (2).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (2)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (20).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (20)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (200).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (200)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (201).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (201)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (202).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (202)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (203).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (203)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (204).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (204)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (205).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (205)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (206).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (206)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (207).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (207)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (208).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (208)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (209).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (209)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (21).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (21)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (210).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (210)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (211).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (211)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (212).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (212)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (213).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (213)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (214).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (214)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (215).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (215)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (216).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (216)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (217).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (217)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (218).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (218)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (219).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (219)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (22).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (22)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (220).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (220)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (221).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (221)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (222).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (222)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (223).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (223)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (224).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (224)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (225).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (225)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (226).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (226)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (227).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (227)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (228).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (228)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (229).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (229)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (23).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (23)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (230).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (230)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (231).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (231)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (232).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (232)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (233).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (233)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (234).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (234)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (235).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (235)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (236).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (236)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (237).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (237)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (238).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (238)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (239).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (239)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (24).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (24)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (240).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (240)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (241).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (241)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (242).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (242)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (243).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (243)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (244).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (244)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (245).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (245)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (246).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (246)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (247).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (247)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (248).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (248)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (249).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (249)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (25).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (25)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (25)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (250).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (250)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (251).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (251)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (252).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (252)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (253).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (253)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (254).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (254)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (255).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (255)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (256).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (256)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (257).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (257)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (258).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (258)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (259).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (259)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (26).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (26)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (260).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (260)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (261).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (261)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (262).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (262)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (263).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (263)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (264).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (264)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (265).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (265)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (266).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (266)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (267).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (267)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (268).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (268)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (269).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (269)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (27).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (27)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (270).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (270)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (271).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (271)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (272).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (272)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (273).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (273)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (274).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (274)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (275).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (275)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (276).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (276)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (277).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (277)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (278).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (278)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (279).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (279)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (28).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (28)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (280).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (280)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (281).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (281)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (282).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (282)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (283).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (283)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (284).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (284)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (285).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (285)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (286).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (286)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (287).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (287)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (288).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (288)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (289).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (289)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (29).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (29)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (290).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (290)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (291).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (291)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (292).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (292)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (293).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (293)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (294).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (294)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (295).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (295)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (296).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (296)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (297).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (297)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (298).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (298)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (299).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (299)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (3).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (3)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (30).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (30)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (300).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (300)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (301).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (301)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (302).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (302)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (303).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (303)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (304).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (304)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (305).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (305)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (306).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (306)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (307).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (307)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (308).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (308)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (309).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (309)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (31).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (31)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (310).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (310)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (311).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (311)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (312).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (312)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (313).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (313)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (314).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (314)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (315).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (315)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (315)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (316).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (316)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (317).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (317)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (318).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (318)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (319).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (319)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (32).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (32)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (320).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (320)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (321).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (321)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (322).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (322)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (323).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (323)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (324).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (324)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (325).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (325)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (326).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (326)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (327).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (327)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (328).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (328)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (329).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (329)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (33).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (33)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (330).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (330)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (331).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (331)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (332).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (332)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (333).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (333)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (334).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (334)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (335).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (335)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (336).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (336)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (337).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (337)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (338).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (338)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (339).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (339)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (34).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (34)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (340).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (340)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (341).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (341)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (342).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (342)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (343).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (343)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (344).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (344)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (345).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (345)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (346).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (346)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (346)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (347).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (347)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (348).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (348)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (349).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (349)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (35).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (35)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (350).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (350)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (351).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (351)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (352).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (352)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (353).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (353)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (354).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (354)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (355).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (355)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (356).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (356)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (357).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (357)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (358).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (358)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (359).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (359)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (36).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (36)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (360).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (360)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (361).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (361)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (362).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (362)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (363).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (363)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (364).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (364)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (365).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (365)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (366).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (366)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (367).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (367)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (368).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (368)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (369).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (369)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (37).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (37)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (370).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (370)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (371).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (371)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (372).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (372)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (373).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (373)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (374).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (374)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (375).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (375)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (376).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (376)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (377).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (377)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (378).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (378)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (379).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (379)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (38).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (38)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (380).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (380)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (381).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (381)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (382).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (382)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (383).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (383)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (384).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (384)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (385).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (385)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (386).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (386)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (387).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (387)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (388).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (388)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (389).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (389)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (39).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (39)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (390).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (390)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (391).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (391)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (392).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (392)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (393).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (393)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (394).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (394)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (395).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (395)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (396).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (396)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (397).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (397)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (398).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (398)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (399).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (399)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (4).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (4)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (4)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (40).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (40)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (400).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (400)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (401).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (401)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (402).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (402)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (403).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (403)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (404).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (404)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (405).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (405)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (406).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (406)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (407).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (407)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (408).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (408)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (409).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (409)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (41).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (41)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (410).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (410)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (411).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (411)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (412).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (412)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (413).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (413)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (414).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (414)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (415).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (415)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (416).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (416)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (417).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (417)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (418).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (418)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (419).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (419)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (42).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (42)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (420).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (420)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (421).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (421)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (422).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (422)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (423).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (423)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (424).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (424)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (424)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (425).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (425)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (426).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (426)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (427).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (427)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (428).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (428)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (429).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (429)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (43).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (43)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (430).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (430)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (431).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (431)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (432).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (432)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (433).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (433)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (434).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (434)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (435).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (435)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (436).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (436)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (437).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (437)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (44).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (44)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (45).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (45)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (46).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (46)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (47).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (47)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (48).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (48)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (49).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (49)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (5).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (5)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (50).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (50)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (51).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (51)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (52).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (52)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (53).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (53)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (54).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (54)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (54)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (55).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (55)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (56).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (56)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (57).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (57)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (58).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (58)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (58)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (59).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (59)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (6).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (6)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (60).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (60)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (61).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (61)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (62).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (62)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (63).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (63)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (64).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (64)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (65).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (65)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (66).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (66)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (67).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (67)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (68).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (68)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (69).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (69)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (7).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (7)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (70).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (70)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (71).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (71)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (72).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (72)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (73).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (73)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (74).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (74)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (75).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (75)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (76).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (76)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (77).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (77)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (78).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (78)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (79).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (79)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (8).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (8)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (80).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (80)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (81).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (81)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (82).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (82)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (83).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (83)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (83)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (84).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (84)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (85).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (85)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (86).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (86)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (87).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (87)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (88).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (88)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (89).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (89)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (9).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (9)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (90).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (90)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (91).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (91)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (92).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (92)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (92)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (93).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (93)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (93)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (94).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (94)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (95).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (95)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (96).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (96)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (97).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (97)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (98).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (98)_mask.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (98)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (99).png \n"," inflating: Dataset_BUSI_with_GT/benign/benign (99)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (1).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (1)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (10).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (10)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (100).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (100)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (101).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (101)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (102).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (102)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (103).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (103)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (104).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (104)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (105).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (105)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (106).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (106)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (107).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (107)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (108).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (108)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (109).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (109)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (11).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (11)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (110).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (110)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (111).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (111)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (112).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (112)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (113).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (113)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (114).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (114)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (115).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (115)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (116).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (116)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (117).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (117)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (118).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (118)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (119).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (119)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (12).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (12)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (120).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (120)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (121).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (121)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (122).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (122)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (123).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (123)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (124).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (124)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (125).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (125)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (126).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (126)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (127).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (127)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (128).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (128)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (129).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (129)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (13).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (13)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (130).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (130)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (131).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (131)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (132).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (132)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (133).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (133)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (134).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (134)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (135).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (135)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (136).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (136)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (137).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (137)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (138).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (138)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (139).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (139)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (14).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (14)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (140).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (140)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (141).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (141)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (142).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (142)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (143).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (143)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (144).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (144)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (145).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (145)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (146).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (146)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (147).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (147)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (148).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (148)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (149).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (149)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (15).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (15)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (150).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (150)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (151).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (151)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (152).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (152)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (153).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (153)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (154).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (154)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (155).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (155)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (156).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (156)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (157).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (157)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (158).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (158)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (159).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (159)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (16).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (16)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (160).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (160)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (161).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (161)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (162).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (162)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (163).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (163)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (164).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (164)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (165).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (165)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (166).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (166)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (167).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (167)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (168).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (168)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (169).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (169)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (17).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (17)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (170).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (170)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (171).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (171)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (172).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (172)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (173).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (173)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (174).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (174)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (175).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (175)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (176).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (176)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (177).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (177)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (178).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (178)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (179).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (179)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (18).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (18)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (180).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (180)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (181).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (181)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (182).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (182)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (183).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (183)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (184).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (184)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (185).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (185)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (186).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (186)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (187).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (187)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (188).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (188)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (189).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (189)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (19).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (19)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (190).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (190)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (191).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (191)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (192).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (192)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (193).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (193)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (194).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (194)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (195).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (195)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (196).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (196)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (197).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (197)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (198).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (198)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (199).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (199)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (2).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (2)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (20).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (20)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (200).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (200)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (201).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (201)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (202).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (202)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (203).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (203)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (204).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (204)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (205).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (205)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (206).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (206)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (207).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (207)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (208).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (208)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (209).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (209)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (21).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (21)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (210).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (210)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (22).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (22)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (23).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (23)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (24).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (24)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (25).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (25)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (26).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (26)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (27).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (27)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (28).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (28)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (29).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (29)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (3).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (3)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (30).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (30)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (31).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (31)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (32).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (32)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (33).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (33)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (34).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (34)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (35).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (35)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (36).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (36)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (37).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (37)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (38).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (38)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (39).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (39)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (4).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (4)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (40).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (40)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (41).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (41)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (42).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (42)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (43).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (43)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (44).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (44)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (45).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (45)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (46).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (46)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (47).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (47)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (48).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (48)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (49).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (49)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (5).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (5)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (50).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (50)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (51).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (51)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (52).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (52)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (53).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (53)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (53)_mask_1.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (54).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (54)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (55).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (55)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (56).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (56)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (57).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (57)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (58).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (58)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (59).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (59)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (6).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (6)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (60).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (60)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (61).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (61)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (62).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (62)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (63).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (63)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (64).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (64)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (65).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (65)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (66).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (66)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (67).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (67)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (68).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (68)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (69).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (69)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (7).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (7)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (70).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (70)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (71).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (71)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (72).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (72)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (73).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (73)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (74).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (74)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (75).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (75)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (76).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (76)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (77).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (77)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (78).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (78)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (79).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (79)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (8).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (8)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (80).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (80)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (81).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (81)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (82).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (82)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (83).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (83)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (84).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (84)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (85).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (85)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (86).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (86)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (87).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (87)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (88).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (88)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (89).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (89)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (9).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (9)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (90).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (90)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (91).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (91)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (92).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (92)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (93).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (93)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (94).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (94)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (95).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (95)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (96).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (96)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (97).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (97)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (98).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (98)_mask.png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (99).png \n"," inflating: Dataset_BUSI_with_GT/malignant/malignant (99)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (1).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (1)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (10).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (10)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (100).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (100)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (101).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (101)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (102).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (102)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (103).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (103)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (104).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (104)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (105).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (105)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (106).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (106)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (107).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (107)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (108).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (108)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (109).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (109)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (11).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (11)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (110).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (110)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (111).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (111)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (112).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (112)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (113).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (113)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (114).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (114)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (115).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (115)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (116).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (116)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (117).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (117)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (118).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (118)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (119).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (119)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (12).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (12)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (120).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (120)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (121).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (121)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (122).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (122)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (123).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (123)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (124).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (124)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (125).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (125)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (126).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (126)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (127).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (127)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (128).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (128)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (129).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (129)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (13).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (13)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (130).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (130)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (131).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (131)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (132).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (132)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (133).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (133)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (14).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (14)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (15).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (15)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (16).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (16)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (17).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (17)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (18).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (18)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (19).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (19)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (2).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (2)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (20).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (20)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (21).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (21)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (22).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (22)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (23).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (23)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (24).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (24)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (25).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (25)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (26).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (26)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (27).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (27)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (28).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (28)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (29).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (29)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (3).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (3)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (30).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (30)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (31).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (31)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (32).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (32)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (33).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (33)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (34).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (34)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (35).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (35)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (36).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (36)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (37).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (37)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (38).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (38)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (39).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (39)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (4).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (4)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (40).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (40)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (41).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (41)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (42).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (42)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (43).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (43)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (44).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (44)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (45).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (45)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (46).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (46)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (47).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (47)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (48).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (48)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (49).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (49)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (5).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (5)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (50).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (50)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (51).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (51)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (52).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (52)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (53).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (53)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (54).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (54)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (55).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (55)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (56).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (56)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (57).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (57)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (58).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (58)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (59).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (59)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (6).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (6)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (60).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (60)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (61).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (61)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (62).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (62)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (63).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (63)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (64).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (64)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (65).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (65)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (66).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (66)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (67).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (67)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (68).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (68)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (69).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (69)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (7).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (7)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (70).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (70)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (71).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (71)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (72).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (72)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (73).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (73)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (74).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (74)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (75).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (75)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (76).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (76)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (77).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (77)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (78).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (78)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (79).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (79)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (8).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (8)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (80).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (80)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (81).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (81)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (82).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (82)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (83).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (83)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (84).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (84)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (85).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (85)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (86).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (86)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (87).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (87)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (88).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (88)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (89).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (89)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (9).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (9)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (90).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (90)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (91).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (91)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (92).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (92)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (93).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (93)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (94).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (94)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (95).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (95)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (96).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (96)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (97).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (97)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (98).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (98)_mask.png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (99).png \n"," inflating: Dataset_BUSI_with_GT/normal/normal (99)_mask.png \n"]}],"source":["# อัพโหลด kaggle.json ที่หาได้จาก https://www.kaggle.com/settings (ไปที่หน้านี้แล้วกด \"Create New Token\" ใน section API)\n","!mkdir ~/.kaggle\n","!cp kaggle.json ~/.kaggle/\n","!chmod 600 ~/.kaggle/kaggle.json\n","!kaggle datasets download -d aryashah2k/breast-ultrasound-images-dataset\n","!unzip breast-ultrasound-images-dataset.zip"]},{"cell_type":"code","execution_count":17,"metadata":{"executionInfo":{"elapsed":36,"status":"ok","timestamp":1688479865779,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"CDgAXI4u0Hze"},"outputs":[],"source":["from transformers import SegformerForSemanticSegmentation\n","from transformers import SegformerFeatureExtractor\n","from transformers import TrainingArguments, Trainer\n","from torchvision.transforms import ColorJitter, Resize, Compose\n","\n","import torch\n","from torch import nn\n","import evaluate\n","import datasets\n","from datasets import Dataset, Features\n","import numpy as np\n","\n","import os.path as op\n","from glob import glob\n","from pathlib import Path\n","from PIL import Image\n","from tqdm.auto import tqdm\n","import os"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":35,"status":"ok","timestamp":1688479865779,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"1RSj_XlAz0Ni","outputId":"651eb360-84bc-45f7-ad30-b7595e9caefb"},"outputs":[{"name":"stdout","output_type":"stream","text":["Length of image and segmentation paths = 780\n"]}],"source":["paths = glob(\"Dataset_BUSI_with_GT/*/*\") # get all folders: normal, benign, malignant\n","im_paths = [path for path in paths if \"_mask\" not in path]\n","data_paths = []\n","\n","# สร้าง dictionary ที่รวม image path, masking path, และ class name\n","for path in im_paths:\n"," class_name = Path(path).parent.name\n"," seg_path = Path(Path(path).parent, Path(path).stem + \"_mask.png\")\n"," if op.exists(seg_path):\n"," data_paths.append({\n"," \"img\": path,\n"," \"seg\": str(seg_path),\n"," \"class\": class_name\n"," })\n","print(\"Length of image and segmentation paths = \", len(data_paths))"]},{"cell_type":"code","execution_count":19,"metadata":{"executionInfo":{"elapsed":8,"status":"ok","timestamp":1688479865780,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"qBwhByT7xwkp"},"outputs":[],"source":["# list of dictionary to dictionary of each list\n","data_paths = {\n"," \"img\": [p[\"img\"] for p in data_paths],\n"," \"seg\": [p[\"seg\"] for p in data_paths],\n"," \"class\": [p[\"class\"] for p in data_paths]\n","}\n","\n","# convert ระหว่าง id <-> lable name\n","id2label = {0:\"background\", 1: \"benign\", 2: \"malignant\"}\n","label2id = {v: k for k, v in id2label.items()}"]},{"cell_type":"code","execution_count":20,"metadata":{"executionInfo":{"elapsed":557,"status":"ok","timestamp":1688479866330,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"3AGDg9y81bIG"},"outputs":[],"source":["ds = Dataset.from_dict(data_paths, features=Features(\n"," {\"img\": datasets.Image(),\n"," \"seg\": datasets.Image(),\n"," \"class\": datasets.Value(dtype='string', id=None)}))\n","\n","# train test split\n","ds_split = ds.train_test_split(test_size=0.2)"]},{"cell_type":"code","execution_count":21,"metadata":{"executionInfo":{"elapsed":7,"status":"ok","timestamp":1688479866330,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"a-rFaY7125KY"},"outputs":[],"source":["train_ds = ds_split[\"train\"]\n","test_ds = ds_split[\"test\"]"]},{"cell_type":"code","execution_count":22,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7,"status":"ok","timestamp":1688479866331,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"JNd8ouJ61-Jq","outputId":"d65bb8bd-c522-455b-adf8-1088910f5217"},"outputs":[{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.10/dist-packages/transformers/models/segformer/feature_extraction_segformer.py:28: FutureWarning: The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use SegformerImageProcessor instead.\n"," warnings.warn(\n"]}],"source":["feature_extractor = SegformerFeatureExtractor()\n","\n","# กำหนด transformsที่ต้องการ\n","_transforms = Compose([\n"," ColorJitter(brightness=0.25, contrast=0.25, saturation=0.25, hue=0.1),\n","])"]},{"cell_type":"code","execution_count":23,"metadata":{"executionInfo":{"elapsed":5,"status":"ok","timestamp":1688479866331,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"abtxGvEzpKic"},"outputs":[],"source":["def train_transforms(example_batch):\n"," '''\n"," pipeline ในการ transfrom train data\n"," ถ้าเป็น mask ของ class benign จะให้value = 1\n"," และถ้าเป็น class malignant จะเป็น value = 2\n"," และลด channel ให้เหลือ 1 channel\n"," '''\n"," images = [_transforms(x) for x in example_batch[\"img\"]]\n"," labels = []\n"," for segim, cls in zip(example_batch[\"seg\"], example_batch[\"class\"]):\n"," segim = np.array(segim).astype(int)\n"," if cls == \"benign\":\n"," segim[segim == 1] = 1\n"," elif cls == \"malignant\":\n"," segim[segim == 1] = 2\n"," else:\n"," pass\n"," if len(segim.shape) == 3:\n"," segim = segim[:, :, 0]\n"," labels.append(segim)\n"," inputs = feature_extractor(images, labels)\n"," return inputs\n","\n","def val_transforms(example_batch):\n"," images = [x for x in example_batch[\"img\"]]\n"," labels = []\n"," for segim, cls in zip(example_batch[\"seg\"], example_batch[\"class\"]):\n"," segim = np.array(segim).astype(int)\n"," if cls == \"benign\":\n"," segim[segim == 1] = 1\n"," elif cls == \"malignant\":\n"," segim[segim == 1] = 2\n"," else:\n"," pass\n"," if len(segim.shape) == 3:\n"," segim = segim[:, :, 0]\n"," labels.append(segim)\n"," inputs = feature_extractor(images, labels)\n"," return inputs"]},{"cell_type":"markdown","metadata":{"id":"Bq84-2-gBiYi"},"source":["input function สำหรับ transfrom data"]},{"cell_type":"code","execution_count":24,"metadata":{"executionInfo":{"elapsed":4,"status":"ok","timestamp":1688479866331,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"x_c_EeDJ_6QT"},"outputs":[],"source":["train_ds.set_transform(train_transforms)\n","test_ds.set_transform(val_transforms)"]},{"cell_type":"markdown","metadata":{"id":"5iPE7u7nD84L"},"source":["function ที่ใช้ในการ evaluate"]},{"cell_type":"code","execution_count":25,"metadata":{"executionInfo":{"elapsed":5,"status":"ok","timestamp":1688479866332,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"YshZurDdpKid"},"outputs":[],"source":["num_labels = len(id2label)\n","metric = evaluate.load(\"mean_iou\")\n","\n","def compute_metrics(eval_pred):\n"," '''\n"," process สำหรับการ evaluate ผลลัพธ์ ที่ทำนายจากโมเดล\n"," '''\n"," # ไม่ต้องคิด gradient\n"," with torch.no_grad():\n"," logits, labels = eval_pred\n"," logits_tensor = torch.from_numpy(logits)\n"," logits_tensor = nn.functional.interpolate(\n"," logits_tensor,\n"," size=labels.shape[-2:],\n"," mode=\"bilinear\",\n"," align_corners=False,\n"," ).argmax(dim=1)\n","\n"," pred_labels = logits_tensor.detach().cpu().numpy()\n","\n"," # คำนวน evaluation metric\n"," metrics = metric.compute(\n"," predictions=pred_labels,\n"," references=labels,\n"," num_labels=num_labels,\n"," ignore_index=255,\n"," reduce_labels=False,\n"," )\n"," for key, value in metrics.items():\n"," if type(value) is np.ndarray:\n"," metrics[key] = value.tolist()\n"," return metrics"]},{"cell_type":"markdown","metadata":{},"source":["## Download a Pretrained Model and Train It"]},{"cell_type":"code","execution_count":26,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":654,"status":"ok","timestamp":1688479866982,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"OQambUM3WXVA","outputId":"e1dad995-c1cd-45b3-b18e-5802bec1933a"},"outputs":[{"name":"stderr","output_type":"stream","text":["Some weights of the model checkpoint at nvidia/mit-b0 were not used when initializing SegformerForSemanticSegmentation: ['classifier.weight', 'classifier.bias']\n","- This IS expected if you are initializing SegformerForSemanticSegmentation from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n","- This IS NOT expected if you are initializing SegformerForSemanticSegmentation from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n","Some weights of SegformerForSemanticSegmentation were not initialized from the model checkpoint at nvidia/mit-b0 and are newly initialized: ['decode_head.linear_fuse.weight', 'decode_head.linear_c.3.proj.bias', 'decode_head.batch_norm.weight', 'decode_head.batch_norm.num_batches_tracked', 'decode_head.batch_norm.bias', 'decode_head.linear_c.2.proj.bias', 'decode_head.linear_c.2.proj.weight', 'decode_head.classifier.weight', 'decode_head.batch_norm.running_mean', 'decode_head.linear_c.0.proj.weight', 'decode_head.linear_c.1.proj.weight', 'decode_head.linear_c.1.proj.bias', 'decode_head.linear_c.0.proj.bias', 'decode_head.linear_c.3.proj.weight', 'decode_head.batch_norm.running_var', 'decode_head.classifier.bias']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"]}],"source":["# สร้างโมเดลจาก pretrain model\n","pretrained_model_name = \"nvidia/mit-b0\"\n","model = SegformerForSemanticSegmentation.from_pretrained(\n"," pretrained_model_name,\n"," id2label=id2label,\n"," label2id=label2id\n",")"]},{"cell_type":"code","execution_count":27,"metadata":{"executionInfo":{"elapsed":5,"status":"ok","timestamp":1688479866982,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"hCBPmV5RpKid"},"outputs":[],"source":["save_path = \"segformer-breast-cancer_30ep\""]},{"cell_type":"markdown","metadata":{"id":"tcA8QXMIEeWN"},"source":["เทรน 30 epochs"]},{"cell_type":"code","execution_count":28,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":766},"executionInfo":{"elapsed":3965630,"status":"ok","timestamp":1688483832607,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"_zk3BtDIWg-U","outputId":"13e6090e-9b1c-4695-faf3-f5f0a765622d"},"outputs":[{"name":"stderr","output_type":"stream","text":["Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none).\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n"," warnings.warn(\n"]},{"data":{"text/html":["\n","
\n"," \n"," \n"," [2340/2340 1:05:53, Epoch 30/30]\n","
\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
StepTraining LossValidation LossMean IouMean AccuracyOverall AccuracyPer Category IouPer Category Accuracy
3000.1805000.2071050.5635840.6502180.945108[0.9522910214628129, 0.35597900507094016, 0.38248337122310894][0.9844119296714371, 0.4803877884345996, 0.48585527883746626]
6000.1520000.1627830.6048530.7134260.947683[0.9525706140330837, 0.4258345563794154, 0.43615323108476856][0.9791855052811275, 0.5975566139521575, 0.5635362311699621]
9000.0435000.1517410.6281680.7080190.954531[0.9580944032975929, 0.4604088037923396, 0.46600137880435566][0.9878961064559273, 0.6007323005025066, 0.5354272765687837]
12000.0781000.1468540.6484380.7438150.955529[0.9586950345597687, 0.46937472529471586, 0.5172430492953498][0.983367143662574, 0.5959896339391627, 0.652088757114403]
15000.0352000.1533060.6475110.7476190.954053[0.9565895254437337, 0.47311257865553547, 0.5128303326014411][0.9806451753285087, 0.5658362591574818, 0.6963768026680048]
18000.1004000.1579090.6584620.7331710.958309[0.9603114527087526, 0.4867013048043347, 0.5283727513095081][0.9881126634523039, 0.5895808868674706, 0.6218209122610078]
21000.0201000.1616420.6548430.7343760.957776[0.9603979053980308, 0.47884308927633784, 0.5252888038447846][0.9872288158312638, 0.5836944664667767, 0.632204579889383]

"],"text/plain":[""]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["Trainer is attempting to log a value of \"[0.9522910214628129, 0.35597900507094016, 0.38248337122310894]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9844119296714371, 0.4803877884345996, 0.48585527883746626]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9525706140330837, 0.4258345563794154, 0.43615323108476856]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9791855052811275, 0.5975566139521575, 0.5635362311699621]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9580944032975929, 0.4604088037923396, 0.46600137880435566]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9878961064559273, 0.6007323005025066, 0.5354272765687837]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9586950345597687, 0.46937472529471586, 0.5172430492953498]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.983367143662574, 0.5959896339391627, 0.652088757114403]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9565895254437337, 0.47311257865553547, 0.5128303326014411]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9806451753285087, 0.5658362591574818, 0.6963768026680048]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9603114527087526, 0.4867013048043347, 0.5283727513095081]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9881126634523039, 0.5895808868674706, 0.6218209122610078]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9603979053980308, 0.47884308927633784, 0.5252888038447846]\" of type for key \"eval/per_category_iou\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n","Trainer is attempting to log a value of \"[0.9872288158312638, 0.5836944664667767, 0.632204579889383]\" of type for key \"eval/per_category_accuracy\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n"]},{"data":{"text/plain":["['segformer-breast-cancer_30ep/preprocessor_config.json']"]},"execution_count":28,"metadata":{},"output_type":"execute_result"}],"source":["os.environ[\"WANDB_DISABLED\"] = \"true\"\n","\n","n_epochs = 30\n","\n","training_args = TrainingArguments(\n"," output_dir= save_path,\n"," learning_rate=6e-5,\n"," num_train_epochs=n_epochs,\n"," per_device_train_batch_size=8,\n"," per_device_eval_batch_size=8,\n"," save_total_limit=3,\n"," evaluation_strategy=\"steps\",\n"," save_strategy=\"steps\",\n"," save_steps=300,\n"," eval_steps=300,\n"," logging_steps=1,\n"," eval_accumulation_steps=5,\n"," remove_unused_columns=False,\n"," push_to_hub=False,\n"," load_best_model_at_end=True,\n",")\n","\n","trainer = Trainer(\n"," model=model,\n"," args=training_args,\n"," train_dataset=train_ds,\n"," eval_dataset=test_ds,\n"," compute_metrics=compute_metrics,\n",")\n","\n","trainer.train()\n","feature_extractor.save_pretrained(save_path)"]},{"cell_type":"markdown","metadata":{"id":"r-7psi1QpKid"},"source":["## Inference\n","ทดลองใช้จริง โดยการเตรียมข้อมูลจะคล้ายกับการเตรียมข้อมูลสำหรับเทรนโมเดล"]},{"cell_type":"code","execution_count":38,"metadata":{"executionInfo":{"elapsed":3,"status":"ok","timestamp":1688484812541,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"nuO0Dol04qbN"},"outputs":[],"source":["# [optional] copy preprocessor_config.json to the model path folder\n","!cp segformer-breast-cancer_30ep/preprocessor_config.json segformer-breast-cancer_30ep/checkpoint-2100/preprocessor_config.json"]},{"cell_type":"code","execution_count":30,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":586,"status":"ok","timestamp":1688483833192,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"4bAeVLU1pKid","outputId":"7bdea023-688c-4ed0-cb19-ab49dd2261a4"},"outputs":[{"name":"stdout","output_type":"stream","text":["segformer-breast-cancer_30ep\n"]},{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.10/dist-packages/transformers/models/segformer/feature_extraction_segformer.py:28: FutureWarning: The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use SegformerImageProcessor instead.\n"," warnings.warn(\n"]}],"source":["print(save_path)\n","model_path = f\"{save_path}/checkpoint-2100\"\n","image_processor = feature_extractor.from_pretrained(f\"{save_path}/preprocessor_config.json\", local_files_only=True)\n","model = SegformerForSemanticSegmentation.from_pretrained(f\"{model_path}\",id2label=id2label, label2id=label2id, local_files_only=True)"]},{"cell_type":"code","execution_count":31,"metadata":{"executionInfo":{"elapsed":2,"status":"ok","timestamp":1688483833192,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"SWFDj7bRpKie"},"outputs":[],"source":["ds = Dataset.from_dict(data_paths, features=Features(\n"," {\"img\": datasets.Image(),\n"," \"seg\": datasets.Image(),\n"," \"class\": datasets.Value(dtype='string', id=None)}))\n","ds_split = ds.train_test_split(test_size=0.2)\n","train_ds = ds_split[\"train\"]\n","test_ds = ds_split[\"test\"]"]},{"cell_type":"code","execution_count":32,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":221},"executionInfo":{"elapsed":2361,"status":"ok","timestamp":1688483835551,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"YUpFBhC3pKie","outputId":"ccefeb13-42af-4b1d-f7d6-a2e1ba0762d2"},"outputs":[{"data":{"text/plain":["(-0.5, 605.5, 604.5, -0.5)"]},"execution_count":32,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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","text/plain":["

"]},"metadata":{},"output_type":"display_data"}],"source":["from torch import nn\n","import matplotlib.pyplot as plt\n","import numpy as np\n","\n","image = test_ds[22]['img']\n","gt_seg = test_ds[22]['seg']\n","\n","inputs = feature_extractor(images=image, return_tensors=\"pt\")\n","outputs = model(**inputs)\n","logits = outputs.logits # shape (batch_size, num_labels, height/4, width/4)\n","\n","upsampled_logits = nn.functional.interpolate(\n"," logits,\n"," size=(image.size[1], image.size[0]),\n"," mode=\"bilinear\",\n"," align_corners=False,\n",")\n","pred_seg = upsampled_logits.argmax(dim=1)[0]\n","\n","plt.figure()\n","plt.subplot(1, 3, 1)\n","plt.imshow(image)\n","plt.title(\"Ultrasound Image\")\n","plt.axis(\"off\")\n","\n","plt.subplot(1, 3, 2)\n","plt.imshow(pred_seg, cmap=\"gray\")\n","plt.title(\"Prediction\")\n","plt.axis(\"off\")\n","\n","plt.subplot(1, 3, 3)\n","plt.imshow(gt_seg, cmap=\"gray\")\n","plt.title(\"Ground Truth\")\n","plt.axis(\"off\")"]},{"cell_type":"code","execution_count":33,"metadata":{"executionInfo":{"elapsed":4,"status":"ok","timestamp":1688483835551,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"4ON-WhFjpKie"},"outputs":[],"source":["image = Image.open(\"./Dataset_BUSI_with_GT/benign/benign (1).png\")\n","gt = Image.open(\"./Dataset_BUSI_with_GT/benign/benign (1)_mask.png\")"]},{"cell_type":"code","execution_count":34,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3127,"status":"ok","timestamp":1688483838675,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"Yent7lr6pKie","outputId":"dc687ad5-ac2e-4ebc-c4f8-bc8715c5378b"},"outputs":[{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.10/dist-packages/transformers/models/segformer/feature_extraction_segformer.py:28: FutureWarning: The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use SegformerImageProcessor instead.\n"," warnings.warn(\n"]},{"data":{"text/plain":["[{'score': None,\n"," 'label': 'background',\n"," 'mask': },\n"," {'score': None,\n"," 'label': 'benign',\n"," 'mask': }]"]},"execution_count":34,"metadata":{},"output_type":"execute_result"}],"source":["from transformers import pipeline\n","\n","segmenter = pipeline(\"image-segmentation\", model=model_path)\n","segmenter(image)"]},{"cell_type":"code","execution_count":35,"metadata":{"executionInfo":{"elapsed":876,"status":"ok","timestamp":1688483839540,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"3hnRp9CKpKie"},"outputs":[],"source":["encoding = feature_extractor(image, return_tensors=\"pt\")\n","pixel_values = encoding.pixel_values\n","\n","outputs = model(pixel_values=pixel_values)\n","logits = outputs.logits.cpu()\n","\n","upsampled_logits = nn.functional.interpolate(\n"," logits,\n"," size=image.size[::-1],\n"," mode=\"bilinear\",\n"," align_corners=False,\n",")\n","\n","pred_seg = upsampled_logits.argmax(dim=1)[0]"]},{"cell_type":"code","execution_count":36,"metadata":{"executionInfo":{"elapsed":3,"status":"ok","timestamp":1688483839541,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"Uy049ROIpKie"},"outputs":[],"source":["def ade_palette():\n"," \"\"\"Creates a label colormap used in ADE20K segmentation benchmark.\n"," Returns:\n"," A colormap for visualizing segmentation results.\n"," \"\"\"\n"," return np.asarray([\n"," [0, 0, 0],\n"," [120, 120, 80],\n"," [140, 140, 140],\n"," [204, 5, 255],\n"," [230, 230, 230],\n"," ])"]},{"cell_type":"code","execution_count":37,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":807},"executionInfo":{"elapsed":1718,"status":"ok","timestamp":1688483841257,"user":{"displayName":"korrawiz Chotayapa","userId":"13359737025054536148"},"user_tz":-420},"id":"pF_dHKOEpKif","outputId":"71781049-e40b-4264-e253-d9dcce5927c6"},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA6oAAAMWCAYAAAD4dHsQAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9y46lWZLdh2/3CPfIrKxbdxar0RKlBiQSIKEboKGggR5AA72lHkBPIM0ETTQWQFEim2yqWsWqrurqjHD3cP8PEstj+c/Xsr1PVgv/HrgBB+ec79sXM9tmy2xfzneunp6entYbvdEbvdEbvdEbvdEbvdEbvdEbvdE/ELr+/zcDb/RGb/RGb/RGb/RGb/RGb/RGb/RGTm8T1Td6ozd6ozd6ozd6ozd6ozd6ozf6B0VvE9U3eqM3eqM3eqM3eqM3eqM3eqM3+gdFbxPVN3qjN3qjN3qjN3qjN3qjN3qjN/oHRW8T1Td6ozd6ozd6ozd6ozd6ozd6ozf6B0VvE9U3eqM3eqM3eqM3eqM3eqM3eqM3+gdFbxPVN3qjN3qjN3qjN3qjN3qjN3qjN/oHRW8T1Td6ozd6ozd6ozd6ozd6ozd6ozf6B0VvE9U3eqM3eqM3eqM3eqM3eqM3eqM3+gdF748Lvn+/np6e1tPT01prraurq7XWer727t275+9+XWVTvffv368/+ZM/Wf/D//A/rOvr6/X4+Piirup4vevr63V1dbWur6+fP6vO4+Pjenx8XJ8/f16Pj4+xHW9PdcUfX+KH9VI7el1fv5z7iyeXy9t1PhqpXeo88ZdIdb2d1me67jpsuvR+WjvTdW+bcrW+0xhO7SSb8ToaK9aTLXkd2ubV1dV69+7dur6+fn5P/Uy6SDJ4PdpnkuHp6SmOr8vgNI2ry8bXJJf7QPNB56/ZpfeTrmms2v2p36RLtyXK2nhP1Pqgz+5wqfXXsPHSdljO/YZ90Lcnvez043IkHppdnfQ9+RnrTrbf+vd2mo0kXzuxqcmv3H6aL1PehIOTXv19KtvKN10kTD2xTW8ztd38e2ebLcZ5mwnzG6W2idtTOw2/pv6Esbvx4jglu5q+q65jdLPNJBfvTZi885FTvNzVYV29Gr/kO/E49cP4slbGWLbDXNL5Vi6jl/PFdho+pTJJH8qnmbfKHt69e/cKu+j3Kc5OtItxLU7sckTKOOUeCZPbuNF+mq0kfpzvZnvej+exPlZe1jEi6XQXB5IOU9+e00wxT7bw8PDw/P758+f19PS0/sf/8X+MvDgdT1T/yT/5J+tv//Zv169//et1f3+/Hh8fXwDX119/vW5ubtaPfvSj9eHDh3Vzc/NCQZ8+fVr39/frD3/4w7q7u1vffffdenx8XB8/flz/x//xf6xf/OIX69tvv302BDeINCC6TwPx+iqXFO9tM6D7Pa9D2gUdGgYDYOMr0efPn2MiQ/2Q30tAVf03Y6W+2E+6NgH4jjQeqb0kUwI3gmMKPCkJnIIrAYzAR3s9TT6c51Q3gXUCU2+P7Z+Ae+ojlW0JyuPj43Od5lPOu3TvwErwbf2cyLJLosQv9d78gO8taLEvr5fKTXpO8jw9Pa3r6+s65s0XUn9exoNLoyZz8rmWmKgsA6r3PY1vs1tiRPInlbsEn1h3wluPQY0/1v1jsHKHLSmJ4v1kI6ldHzfiny84e/nkE/452Yi3n3gg77yX7HCyxZR7NJ0lPpKOXMame5fB/ZnvTo5ZSWbqpukxyTPFumkMp8+7GOOfp7FMvJ7maQknacfeLj+rfKoz0YS9k15S/qN35nW79lIewRxordeLzF5/J6vfnyZJp3nhVI6Y0uwj+WfCA+YnzjdloB+k8fEcaGo/UcNgz6mIuy3fu4R2OMt+drkQ9Z9ep3Q8Uf1v/9v/dv2rf/Wv1v/+v//v62/+5m/W58+f11pfdql++tOfrp/+9KfrP/6P/+P1p3/6p+unP/3pM+MPDw/rN7/5zfrbv/3b9a/+1b9av/nNb9anT5/W4+Pj+v3vf7/+l//lf1n/9X/9X69f/vKXz6s3ench0yriWn3Hqxmvynl5v+ZlqVQvm5xg4iPxlRI18sGkjYlY4rUZA3lIAT+BPwGOdRM/1M0ko19Xf+7sep9soCVIXp7jkna7k214m767dHI9AfSUPLXANo0/dcjvSiCnJGg3Vj42fi8lR04nO0wuE5O15tME6yQX9Zba5Upxo5YcNGrBLOFFqpfe2aZ8ZAqwU6KUZHAfSz6Q5KKNtAA3BUMfE7cB9pnwkJ+54kxKbe8Sm6ZTr/Pu3bsXSUmy2ROa7IL9s0xLiJL/k//Wn7frevITTs2ffTxPMZZtXRJbko5OkyLx5zx6bNnhdtNhy0man3j9Xdyf5GNc93bIw46mRfYJI1o+Qfl2lHyS1xq+ppzHeWFescM+bRwkfGuYmMj9gv1wvPWir3nbzJlV3uXlOCqXp69Rx20S22J3iuVJvqaf5jMun8s95Ys7Sryc2qVIfTW8a4uvlKvxNo1L2mVl/V0/7Vrq1/2lLUpM7TW7b3Q8Ub25uXk+3iulPD4+rp/85Cfr22+/Xf/sn/2z9eMf/3h9+PBhXV9fr/v7+2eGbm9v109+8pP14cOH9bOf/Wz9+te/Xv/3//1/r7/6q79a33333Xp6+n4y63U8SEh4riQkBVBZTRmTAU9BnMDP+96nAKANBoEkAVxKwryuA1eSw+tMO8aJt0YEQ/LTAikBawfQAh4epSVvfsykgTv7TEfDk804f4mHJEtLTtuETW03Pfh3HZdg0HV+mk0mSsGffE/20oJPOvLDfglyPt6qK51JbpInyo3vlmAlG0g6o06bjTe9JD9NwdB5mXaLW8KWxi/ZyYkME3Y6TTicjqSlAJpwm/I3XTR/VZ+ypUQTzjf+vO2EwQ8PD8/8p2OvCQNTeynOEbeavzqPk878umNkKpt+rsLjh847+/DrxOvmX003HIsWVyacTOOdfjrEvviebICYpjbTGPnJNJVXuSnBpV38UFtgWxO1ReLUJvkij7Q3rz/5fRo3/yx/T5jidk5bTT/38bqUwTEuxTJvJ2FTw33KnXxNR23TT2ySn3IcaOeyTfaXxjn5Y3qlHUWnhoNJ57t6LOfj2xZyJ1yZYl/LZXh82G3LN93aZgp5mCa1TedO02mo1I6+p/t+r8koXj0/dR8RtQXNHR1PVCnI1dX3ScA333yzvv322/WLX/xiff311+vu7m59/Phxffr0aT09ff/b1dvb2+87e/9+/eQnP1lrrfXdd9+92Fn9+PHj+s1vfrN+9rOfbVcGWmDz7wxWDfD42fuZ9MBEwq+drBiT94mH5IwnbXj/KeAxeKTAnogrV+yfSYsDkPeTnDEFhqZntuULGV6WvDPhazomNYd23ilDI8rYghj1QntmfQbhVD/JcJJ8pLpTP1PAEXilwOpt+USVJF9Lxw1p95NO3Q5dHtpnwhmXhW1TrmTPXs6DGXn2+hOeJPlYRvy2xR/Kn9pucvLajr/U94QNDUuav50EbG+7JUwpXkw454lgS3q9X724+5ESmB1Ok58k604XJ7h46cJn06/XZ1xdq0+Qmi2IN9rFrk2Om65NOYbbwtPT66P4StymUyXOT5InjUGyN6ckd/LxpNdELV86tTHywPFm+ZN4zLKKBy0PYr+tr0nvHHsuNKQ2W+zd+Qttb5cv0t5dVt/t4yJaWuCnH7b864TaWO7GPPmv+m9l2BZzq50dp3YnG6Q9p7EVrjf/b8+NIa5OttBi78Szf052lXiabJB8N15OeCQdT1Q/ffq07u7u1ufPn5+PPfz5n//5+ou/+Iv1n/wn/8m6ublZf/d3f7f+6q/+av3rf/2v17/7d/9uffz4ca31/SrXP//n/3z9+Z//+frw4cP6kz/5k/Wzn/1s/ft//+/X58+f19/+7d+uf/Ev/sX61//6X6///r//79e33377nHwqcDjYU5ktmRCQODEwJIWn36iwfU/2WJdOTeJEPD14x1cmdqDPnSi1o3fuRqWAS4BLSbrXT4kW9btzJAbYlhy5w/qKqa6n8ZL9UL7T428sM4HKLpEQ8bhDG1cPKs5Xs0vyMe3GNVkoNyf0rEtdcaxSouhttIRC91PAaIGgJV0ehBsONLuYgJaUjo2RL5Zr9uP687KtTloNTzrxV8JQp3TMMfG9o+YXiZItpbYSXrT2Lk2qpoQq6ZN6En+O4dw5bLrgGE2LtV6vJTmTfKSWjDg5Jnk70oEfH9SOj8vh8VLJvcf4hIvKM5LOHBMSLrYdTMZb7n4SK9yGUiLHnRIvc319HR9EQ50nPVHXk0/wGn0l+XGrQ13Rtk/ao4ypnD77UXnKlBbWp/48T0i8TPEy2WDye+1oqkyLQ8kmpzjaZHSbTb7OOL3LbyjbKdY55rVYxIUrxrIT/Gk5TMKoHf6rvYRlyb6d9+Sz3q63zzyTfuyY5zzR571N5YpT/iKsJe+e79PniE/ihTkWZUh9s9zT0/cPyOW8zfXp8rRTcomOJ6rp2MG33367vvnmm3V9fb0+ffq0fve7361/+S//5frtb3+7vvvuu3V/f/9c96/+6q/Wx48f11dffbW+/vrr9dVXX62f//zn69OnT+sPf/jDenx8XHd3dy8mo0mxVJgrTpTA2geECUz7nIgD7+01wD+hVC+twiR5RZwki3yCdBJkaLztvn+nXqX3ttvkjsHPCTzSLu5u1Tz1m/qZAjgpJStMpHyXL4Ew5U+23vpjfbbZVtZbkGfi5mUdgHe8+hjplfhxHqYEtI1pAvYkr5c/8cnEU7KLNIZu68k2WK7xwHa9v0lnSY70vrO1RClhatQSwenaxMekI/LmbaVk4hKeUv9TQHWbaJPSCVvIcxunKYGk3Z1Qi59TWfHhCVEadyYyzY4cy0+OxdH/WqJ9CcYzOd7hRduN9Xe1l3bAd/GNtPOrNvbcnU/9pzhMGZP9kVJcma43nPb7fm2XlyXZUt9NhpRr0cYmP231kp1OdrmLP17G8cYXZlJ+4G1RHpY/4YnXE1+Jn9RO0lvqg3gi3Fjrpe9O9jrpsuF3GnfWZX++qONt+eTQ9d906uUvJcrAftPiWppQp3ZFE2alnfv/zyeq7969W+/fv1/v379fV1ffz+R/8YtfrB//+Mdrre+P8v72t79d/+Jf/ItXAn7+/Hn9m3/zb9avf/3r9ed//ufr6upqffXVV+tP//RP1+fPn9e//bf/9vmxxTyGwB9jN+Nz4/EXDYYOOxnBicPSqJPD7AJQClJuxCfJofpsR8dotJO8PL60S+7o0G2i1up53ylQ+Th6GV5LYLKT1ctP4z2BMu/7xCXdd/nIE0HCxyQRAdb7340bg20DYOq17cT6yqFAqB154c6YrrWx5m+BGr8MuMmOd+CbZHabYz8pmWJAn4Kfl2/A3a43O27878Y6EVfzJ5/m99NA5GWJYUw+mg1Pu1ItAZoSm2Yz1IG3lXbydnjaZEg2wh2NVi7ptfmz2mmUxt13UtP4Mylqtp7siX23hbQp0Ul9tphAG2k4kfCSWODvzGda364Llku+ys9sV/qaMC3Jv9PX5Mut7IQVJ9jg/j/Fs7RI6Dy1GOFyp9/PMR6Rt4Sn7ZX0wWvT/WRn4o92lspO9rXb9WztktJEbxe7Gn60enpmiedKOulJHaR8gH5LvtOCWfqZTNq99n/n8LJsi/ImPZzE6ZRzeP5Fcsxlju68TXFe+ksLdj4h1WkSn9vxxNFpfnDRjurj4/e/JX18fFwfPnxYf/qnf7o+fPiw1lrrV7/61frrv/7r9fT05Xep/81/89+s3//+9+t/+9/+t7XW94P413/91+vdu3fr5z//+fr5z3/+LMzV1dW6ublZt7e36/b2dkwM1FaapVMJLYmk47rCE1gkx3ND5W/oWkBLiW7rLwX5yYGdt5MyUznnm0GiHS9RPY2nHGatl0fHXA4GFI6768zb0WcGqinANlmbc3JcuEqYPosIeBxvgsO0G+evVsb78N9/JpujPMm+GPioEwc758XbSIF65wfUYZugcqx9bPgbM8refG4no+uNfk0e0+SkJQNe17GFZbkCSp3IjlJQ5WfXBceh7abonsvr/O2SykY7DHIeUlyQvH7ax+VhIpdO2Tj/1I3zmIK3+9nDw0Pkn3p0bGhHZacFGeclYV4b60YJz1xHziNjU4qvKW6RL48JSj4T1rW4kPICPwqXdNJsoLXtvuB2pmvCgsm3qZPJFi4hjlXi13nwz7v8I9Fuhzbpkfymd35OutzhieOT2khHvKdcIOmMuM2NFO/bP+94V5xKD39KcjVsSv15exwfxozUl/SX+E923HgnLiSMSRjB+ju9OD6l3IVjnk6deXnGv4ZnKQY2au0k/ohtbpcsl3Q5+aTka7hETNcrPcST9v/09PQ8Kf38+fPzgwVpP3rXsf8TuuhhSs7g9fX1urm5We/ff9/Ex48f18ePH18oJhnMx48f193d3Xp6elofPnxYX3/99Xr37t2L37icGIoLzaR0OsJzCsqpnBtlS2i8bgpMqTyJoNvknq5NQEl+Jmpgw/uNh9Ngk8Z453jkryVHDdQv0cMkA3W00wPrUsZUN4FY05XzRP5S8nAaAKcxmK63Nv275OEiSAPVRLs+yJPXu5TSmDfbpD5SW208G2ak5GM3USU1WyZfE1EP7X7qc8Kx3VizzElCwf53lLA+3UsxJ40lv6tsWozxJ503m00+/0MwKPlMkzPZR+PDE54kf6rfJm3JxqacoL1TJt1L/pV8csJZv36qq8Qb8XrnAzy5xH6ajthnKjP59SWU7OuPxWC2n9psmNzGT9e8XjsRkWJqiput7FpfFj2nE1NJLtXlNedxyqPThNz9oP3s7EQm5yHZ2vTd6zdqP3Frvj7FoPRd9ZOOWGeX0156zXXGz16+LeZM8XvCROITcd+fE8T23ObTBuIUE09x5Hii+vnz53V9fb2+/vrr9fHjxxdJ0Vpr3d3drbu7u3V19f2T7r777rv1P//P//Mrof/u7/5uffz4cX3+/Hl9+PBhffPNN+vrr79+/k1rCogkV4xm70lBUoQnAFPyQ6PmoKkuk+npd3hr9R+Ze7/kw9/5278W9Jgwnf7mpvHenKrpcNKrL0SktgigTr6an9puuqSdpLHyQL+Tm+2fJEpr5d8m0ibJv4/9FEj5zqDqdVpgmRKIRg1EW9ByHoQlLQjzARsuG2Vv9u7fExFkU1niEH13shkmETudpvFksEi8JftJ/OkeP6e2dxPdFAB3gcf7meylYZyXp27bTw2SzqYkpY1Tk424Qr1TL16fJ0N033eF00kL7/s08DPuNJnTsT2112JJ2mXTJDtR8mm17+PnfflxOurUseLp6SliauJB+JOwmf2oHK9NeJn8OPm4XpOPT22n9kRpDGiXlKG15Tw1LNvhyw4HpzyFcav5sU/8HBvYHmX1+rq2y5OSDewwROQ5YfLx5qunfXAcJ0xPcWLKWVse1Yh6bjmNv/NUmPOWTi+mhwp5n0m//j5hdcotktwtZqV+Wde/T/ImvNjlOA07aRfkU31rdzTNrZIcusYTMs7rzrdIxxNVTQjv7u7W9fX1829VvVMxlJR5fX394piDEouHh4fn2bqCTlsx8T52j333fvTubfC9AXUyPPXt/7fmPKgvHyjv5wSwqYd0vG0KnGlFY+rL9ZH06O9+vxlcC1DUr+zF33Vf13a/j3N5/Zrf889NhiZP6tvHeCL1nX67wPFtQanxwkQqBbY0/mwjjavr3mUmgDuIpv6aXIkf1mFwSLLRzlmWCU7Sb2vf66bxYFCd2kqyex/pHm2YGMYFrLSgxd+rJZ+kTJRrSlob0T6bHpLc6jslDNSV7vtRv4T17ehv0kXSR0pqE774veRnu2Qm2Xi73647j5MPsZwT+ZNtPT29fmZCwrVT29jJ5feb/ly2hMsud/o5BMeXPKkMr5Hv1kbCoBYLLtWbric+nG+nhG2p/lqv9eh41errmr/z+i5RTeMwtTvV5QJWI9dXm9zq2gmeUs+e87jtpZ9TNN0mPxa/HO9UL9nY7lgpN2aaLbfYkcjbSXnmFFvZ71rrVR6S+mO//jn9m4TL3zY6nBfmqk2mU1uc5PF+2/c03rSRtjDjsnMjMPXV/OT0/o6OJ6pPT0/PM2tPBlLA0Uqw/15HE1UPNA8PD88TVZVJwELDmZID8eSG7gDg5bydNoHhb3PccNv2toyhTR5IKWgkMHG5xBfbpX7abypc/vSZDpZenhhMvJyCkutO9dsKebOPlJjJvtJY0ZlSkE8JcErW0thO9pW+T6CSbDrJ1ewtyUqZWfZE7/6ZQfhk5TXZhNpV/RQsBaIE0Nb+KXnfV1dX9T9c9e76SzZ/wgv9g+01SkmYj+s0UfU+WE/3eC1hiLeTcIL9JDygjEmuhPNez3dTdnymNhtWNbmnWET9KbZNk//kw00PyY7Yt8cq8tbGs8ma+nCi3XLRMPU7LfKlhIt2rXJpN1ufG++TT3mZVC7pxftu4zX1yUXtRC1mJv8mr40u6fMkxuzu8Xrz/52NO96Q11Q2ydTwmXlI4nnKP5Mfsj3V97HjWHr91N4kv7fpp00Sv8kPUyxLuaLz3WLF1G6iZOfUF9tuGNdwW3VESQfckOLiVuKbc5yko0nmSSdNvoZ3UzuihE2uH73aE969DeeJcqU6l9BFv1EVE3d3d+v9+/fr8+fPz8d1b29v11dfffUMuEzuNMg/+tGP1u3t7Qsh7u/vn48D+uzdhWqJgd93HjlBTQkF6yflaSeMgKL3dIRIbZISn9RROgvuhvDp06e1Vj6el8CF40c+ErgmWf1ec8A0odM97iiyX9334+RuDw2ApDffuZwCVAIqLzf9Lsxlvb+/rzJr/HhUIukz6XwKAr5yOiV6KtOCl3/nA2C83zZOTQ7ykFbgpgSE992W9eN8H2surqSAOZHr1ftLifZp+1MQph5aOzo+6XaU+FZ/iQclVKmOl+NnXxxovp3ameycemWZXZDd6ZTlEr65fLuYkBIujlcK5E4qx2PuJ4mdr3S7bN4G5fZ3ypUWLF2m6chssoukDyZM0++VpBf1zZ93tDjjdXQt4XizFe48sU7Slfhv8ZYYojLyX45Pi7knmNUw3eXze1zg83bSuz4z4ZYeGBOmRRB+FqX8jTJNONuSZo+PLY6nU1fUbes7xYVph43ye/wSKcfRXzmSl/R58uspv5jilesv4YEvuAvvmu2keOG8t/55Yov8en3mVUknzdfYlnIL6tnzDJWb/FN9tzjpbZ3kEaJ0ki3lKQmf2g6v64R65GlV+kjSM6nF/+R3J/SDHqYkYf7whz+sH/3oR+urr75a33zzzfq7v/u7F+X+0T/6R8+O+PHjx7XWWt9888368OHDiy1lF8onqinZSDtUDH6JkuGmwEYFMkDtEqrU1qV1dny2INP6IMix7GkAS+WbDLy2ayclD22MWwCh4zpxDHbjP+mHO6uekIjvlCSk4zms04LnDsSdPIFKMuheAox0LwFVC1Jsa/p+ci/5ggfMSwBvCuLpu/fbkgbynnyf8uj65MuJ6CNMmMl/Gxt+bkFueidNQXdXdyrPxMz7oo69fOs7BcyEGyc2nviiTpJswgLvZ0pMk25Sm85LOonAyS/HK9li0inr7xKulqCk2Np0wPuOcQ3zU58uQ4o5iffp/qSLnT+0+lM5Xd/lFBw74ij1y2vejscg1U8xofFA/pMsE+5xjE7yGPcxv+b10uINZW3+fimmsf5ODtoDT4kk227x3OUgru1ie7OJnX68vVMdue53P9lz/99he8PMxnOSh7EntcVrCcNV1jdj0n1iHdvR98Zj8nVh5Q6XuFm281GXlXpj27txaXQ8USWwPTw8rL/6q79a/+F/+B+ub7/9dv3yl7984fjv379f/9V/9V+tr776an369Gn9X//X/7V+//vfrz/7sz9b33zzzfr8+fP69OnTur+/f37q79PT9ysbeipwmqj47kICcgeoFNjYnn9uClQbPG7LdhuApQRgGlgaCUH1JGiu1f//kA4+JQVJ3nQU0mkaH29HZb3cdITTaReEUr8NwPx45AT25PHqar9TnPh2x/bxTRMvBxgejU/Jnfd9qkvSjhfvjwFL912PafUzjYt/T+9edvKBHcC3ev4+/Q5vCoy7ybMHWB9XBmUudiRdTLsDksHHg0FRcnEMib3er/Pr5Ng4YetOL8lmGYR3j7UnvrEd+lvz+YYDSc9JJ423tbJvJrxOyQ55SLun5Jdj4v2wX/a3i2kpvrANL0/+xH9aAEy8Jbw8TXqmMSK/DYfcf913aQeSiWPjE4J0Msqp2eG0k5byDW8rxT7W9xdtm4sg06mZJJs/iyRRi9/ihf7NWJMwLdEu3iabTidbmgzJhlKdFifpM37aLNn7Dnd3/qsx8V1p2of6Tw8v8jFl7j6NN8l38/1ZOI2mnLxRigWpvUlnbG+tl7+VZRnXpZ8gZD8sS7xW2z6ubbGOfCQZiKtJf6l8irEiP2WU4sHJGDkdT1T5JL/Hx8f1//6//+/68Y9/vP7RP/pH68OHD+vbb79d/8V/8V+sX/3qV+tv/uZv1l/+5V+un//85+vP/uzP1n/6n/6n6/HxcX377bfr/fv36927d+uv//qv129+85vnIxHX19fr9vZ2ffjw4XlnlQ8sagbl3z0guDJTAHciiDvYCCz02fXAAWb9tfLDd7wd7cq1I8vOX/qs9rw/Bpop2fb6DFLUUUtSkiGeAMb0PYFUCn4NzBhskk51f9qN5eeUmKajUV4vJSo8UpPqeGLUAMPHqwWspjvvj8ddXNaUkKddEde1yjTAcj79/iRDA2MmFbTrVj8laYnPlOhNcu5kTAmiKB2ZJPZQR+yb+KP70zFPXVMiQn6JK0lvabzSgobXdd6oZ9pUiwH0q1Sn+QP12a5Ll3qnXph40FbacapdMtbI22knOZrM5CvJ5dT8lmV8jNt4clxSUvfu3bvnSY142sXbxOsuXjSeXTfCxJ1tMj7qPWF/woDEW/Np9kt5Eh9ez4nxyPtO/4XuGwvkIcWDxHOjKZaLj4QJHLPUXtJ1wuSWM3E8UpvNJyb7dJuY4ofH24lS3kZ+/NVio09cTzEqxaXGB4ny62dJLSYn/9mNTyt3mh+ke9O4NbtyG2bM8nryN18MI7632LKjCdOTXyR9+6KFy+O4R14Tbk100Y6qv3/+/Hn9/ve/X3/4wx/Wd999t969e7d+9KMfrX/8j//x85n7u7u79fDwsD58+LB+8pOfrHfv3q0PHz6stb53gD/84Q/rd7/73audWK2ipCTDnVr8TAbn96dVh1SfbaR++OKgNECibn1w1/p+8N3wfDct8XkiV5IzrcymhIv8snwLnq77S5MxBhHyfpJMERCYLHl7BIBJZgZL8svAnfQ4Oa7bXJPVeWsAmOy2BYi18iq5/6djGseUGHm/9I0Gjjt9qdwki/tXs7nUVwuEjWgnzW7Y584O0rWGRztek61PwVTvtOtWNtWbMKjhRbLXZIeUZbJj+k9azT/RY4s5V1evf8enyZXLslY+1u96aglAk63pw/tNOMR3LY762CVsZ//kPfkk9ZImDm1CrXtJVk5Ud7s0CRMle+LVdUH/8X59bKfFlZ0vJUp4zzH292k3qNlU8qXEO+NA8s8Uu6hbx+IJCylDkmPC6sm/Uv2JZ+ZBKa7t+GhypbGlD+4wO/X19PT6v8fZR7P3tV7vhDaMnLCe/qO2drEhkecMjZd2LbWdbD7Zw0n7J6eunPf0Yvn2fhrr20kofm7U8Crll/IPzhXk777AkU7V7WzC6Xiiend396Lz+/v79dd//dfr+vr7p/v+03/6T9c333yz/uIv/mL98pe/XJ8+fVo/+tGPXuzEqp4msf/yX/7L9atf/Wo9PX3/1zTv379k5/379y9WEFIiQ0HTZPR0gE6caQL+aVeV/BBI0ipuAhufsKaJFYPy09OXv0ahDp1nyqgkLDlKCvwJlKhP6pYBn+SPDKcuGFgaEWSSnnhfevEjIZ48pJ1Fd0jXN3U08ZrGM+lXPKVdzzQ2SQZSAijJ2uoQGBvIt3utbOIr+Sf9KoG0y6y20spler9Ejl3gbkHMryVdpuRm+g2Pt+P6crtN9pv8gfYzXefxKS/f9EqsSTs26S/A6Isp8DOR5mkglyPhvidGye6cb5dPMazhoSZtUyKT9Nd05zGBCVjCYcYY9rXWy0lcO4osIp62Okz4fQzSEcy11vPYtwe4Tf7m72m3W3kJfUkv30XlA/18Z9V9QO1ooT3FYp6caeOa6vrnNN5OPLbpPuv1T7GpXUv+QT5aXPI6TPp1P2GI5zXMY+hX3jbzmYSTuke/dt5T0s3PKQ+ddrx28TH52UlZERdmdE2La5MeGxGr2qLN1FaaVKdYRGynrG08nL/UVrKDZkfe9tXV638DSDkU5UxxhvzteGBfjPHpNKl8aYp5qR+Rt5lOEzrR/ugDwvRTO1vrBxz95aD94Q9/WP/P//P/rG+++Wb99Kc/XT//+c/X9fX1+vrrr58nGo+Pj+vjx48vnpT64cOH9aMf/Wh9/fXX6+PHj6+Y9qOwNCDulDQgT5QSAX5O5TlADLhuGGw3gYsbTgrAU6KRkg4HSOd50pXz6EErJRyJJj5SMGV/EzAKCFLAmAAhAVbiPwFkIyYETa4dTbok8KivdISHR3ESWHtbJxPVJMs0mfE+dp93lOyIPO1WL1vActueeCWIsw8Sbcd1y6QiJYypLZeRuOfEJFT15UspiHkyzolh0mm7nnQknJkCqxPl4aKb6hOTUrI2TVT9qKX3zWstMfJyLfHkkea2c+ufk6zkI9VN33nPJ2OMmYwFrV/XkeqkiQT7viQGTztVrV3yPPGS4rYvfLaJKu3N9adx4w6x622tLzaQsJuvJE/C9V0y3Xwqja3zOMUD8tDun4x38mPG1SQL86OkQ+YQxFPiZZIv8crrIh//VJ/lvV7SE2VM9b2M21Xqh/qe2kwY2XhxTOb3JIP68PeTPvwa8TXh9w+hE75SXpJia6vn34kJtCe/1nibjg17TGG+Qf9M39X/ZL8nsYnxkX6ZFtZP6HiienNz8+phQtfX1+tv//Zv1+9///v18PCwfvazn62/+Iu/WH/yJ3+yfvKTnzz/dc3T09P69//+36/vvvtuffPNN+vHP/7x+tnPfrZ+8YtfrIeHh/Xb3/52PT4+Pv/egQPhQjWASIMwJSMNjFqw9EDm/bQ2GSj9mvNMY9J1rnymY1LppX7SBJWUEt6065KCC4NJc4Ymt8vZdhjaZ99lb+2eOjsdJ5EH9xZsUh2C7kngcP5bH/wLngQ0zTZS4FfdFAAnvmm/lMFpSoaclzam5EV9p1Vx2uZJIFX7vnKY+E522fqWTn1ieJIU8Fo6nu9HblTefSn5X/LrRq437gKmsZ38t+mrXWMfvjBD/jnJEPGvUTS2tDHav9tY8iVvU9d8LPzvB/zd+0h2fuIfSffUE++JZ+K4+kyy8t3tp8VHjzdpUkVer66uXj2QhXw3DGzxmzalz5qUuh9q13P630PXm4+d/3VU4lULrDyJkGRjH8n+k1+fnApIiS3H6AQL0hilvht+c6yntigLY414lw5SWeIEF+ZULp3WaLmH1yNffi35/TRGEw5MWNH6arjr7aRcMtVp7TTeG1EGb6fFZeI7+2ynMBKfiVfiUsMa1k85z1qv/xbKiXmj5yOMO61PyqfrEyZT1oZXKR9JtjW17+VTf64n10Va8Et0PFH9n/6n/2l9/Phx/e53v1sPDw/r66+/Xv/5f/6fr1/96lfrL//yL9evf/3r9Td/8zfrV7/61fPvTB2E7+/v1+Pj43r//v366U9/un75y1+uH//4x+sf/+N/vP7dv/t36+PHj+vx8fH5YUqeFHjSoYF14EsPOUj/R0qHTg5AakE8DTjBMDn8BPb+fpLg6BqTa9Z350i8eR9+HMQTa393nboxTsksdToFt+Qcvjo6Obgfx3BQY/upD46lHubhPDQAVT8EpcS3vwi81EcK2ClQn5SjrC4zbcIDPXWn93Zcq4F+sjsCVvJZ6pvJi68KT35EGZzHdLSlJY/0Gx7/Ix5wR4e8pMUT9cGJkeskkftpk38itwVvT/cYsJ3nS/rzttKTEhNWJbzyJNR5eP/+/asYsvO1if8UfNMRwITPbhMM3mmsEk8TZjlxMXU3SSWGMpny17T4mXBhh/FeR6+EWQlL3D6aTr1NTSx5TeNDHXvOwZjgsvnx5Cnpoj9Rzxw3l9P5SMlmi7WeL3GsfYLOnGWtfuKIY0LeyD8Xx1x3HLNd7CCPiT/HAl+MSLlC0mmyyRYDUpxKcbTFjSRjio3JH5rs7T3pmuNF3mkfKqsxn/hMGJv45ykgxyqP7UkvSXc7G/M+yfdEHC/6TcIQ6rDlgO6fpMR/0+VJfNi16e2lHJDtUXdTTHX98+cUOzqeqP7lX/7l8+evv/56/eQnP1nffvvturu7W3/zN3+zPn/+vB4eHtavf/3rV3V9AK6vr9enT5/W09PTM+j7LDvtlnngSYrwM/ZSnAJTmrisNQ8qy/ngpSDhPDWwT9QMj0RDYZsnSSLBMjnTBMyTYROYmhxJ1mbULTAlMGiUxq6V0/2pX590pt0LlWHineq7Pa/1erEltS0SMEzn/D2gpASCtpt0nMDV9ZXA9STZSIFvCuhpLFK7u2vep+ver1NPk60xEWhBKulOlJJI2peunwbTlhAlve2SwoR9+kx7TrhNSrpvmDElXg0TWlLjiV7Cqgm3/B4nqmyLk7lmO+y76WSt139p5e1OMe0UI33sTuyM/Pv7lDSRL+JIijnTeHg+4AmT+yJxltf0zljt2JkWOp0P55U8t37Jp/hPdtBeCdfJp9sXsZ1xqd3nWDr/viGQ5E8nOJL/TGPMd35O/Xm/iQfvx/Xkumvy6z5j36TbxLtfT+87rGn8NfxJMZ/xv9mC19dnf6dOWT4R7dztI03aKFfLW1pfE+8pFk7t8T7jOHlqeVSyszZmyU4bX0nmhE0pB2r27npqsSphm3+nHH/vO6rO8D/7Z/9s/eIXv1jX19frP/qP/qP1F3/xF+vh4WH95je/Wf/r//q/Pg/K/f39K+YfHx/Xb3/72/W73/1u/Z//5/+51voy0Xz37t26u7tbnz59erX61xS31ssfKsuhtYOrdwfTtAKYBu3q6vXvJL08P3s9Gq3XTX22lVK2zaSFut2Ryigo+n8Scqc0BQLqgIGGBu3XyC/LN/Bujs42BHAEX+/bbUpt+lOmvf8puE/65yq83pnYc1x2iU7S5RQwfLU/2R39gPpuwT3pkzxRljTOfi8FS9dV8yNvM9mhl6W+CKITTRjhlBKTybZTG2vl3zomfyIvk88yqDa+3E7Zt2Nm84e2OMK2VU92qAUe2pXb4zSx5+6q35/+9+/x8fufnfjO2BTgRe5f8rFku96Oj03zX/aVdhVabNGiD6+35CYlSLt4yyQj8U4/OEk8VS7pviVZu/uOLe5T+rsH6YuLQ74Tn3aJJrvhhML1ksbQbZV/x0H7SLidYpVfV6zT3wL6bmMbE92fdlbls0k3HFevn3bkmIslvohvem96YPsNb5MdJr69T8/DWlxIOUOKZRwvyiU9U2/MKZzHRMln6ZsuKzdA3O5dbsfvli8wRqQyLVfgjuOUQ3p/LYZq7Hg6ovXf8o8UO/lTAtpAspXW/xTvU+xgTnP6ov7TyZNmU2u9tj3HHW+HOHl19fqBVI2OJ6r/5J/8k7XW90r76U9/um5ubtbt7e2zsLe3t+tnP/vZ+uf//J+/CFYaKDfw3/72t+vf/tt/+0JZf/Znf7b+g//gP1hfffXVC2DxwK7+U6IiRamvtdYLEKWDcheHNIGef94ZVQI754HOTj4Tfynoq71GLYC2MkkWXXOHS4DeHDslaCqXdoVp+GxzNymgffi19KfSyWmT7bFNlUt/TcH2KFuSJQHxpAeS6uk33+lofDuyJb9KT2JtyUjqn0Do8raJgL+SzO43Tc9OOz1xzMln4o9JUep/ClR+3/vwvqkflnPZ2mmKCY8Y+Om/aSedONXGKAUk7zfx6ztXkz4nWcUbd+abnnc+1qgF+bRA5vwS89I19kEdJF5SGdqwY94OU2ijSR+emE5Jz+QDLMtJvcdxTgBlZ65byk35+c7joGyHEzC3ex73TbEs6cPf6YdpvFw+xgqfeLmumRdJVn9poupE2yUlHFnry9/opTaaH6aJkbeRJmMer30cWD7JPxH1Lt7Sb5cbfqS8inE02WXD+DT51HfXaXogWItdaTFwIvqv12Ecd/7oT26nU76tdj1OpLH0+NjihfOvdnlaocVLv5cWGU7jcqrDMo3nlJPwPX1O/FCelMt4314+8dNwwPtNMUNjqDLCn51/io4nqv/0n/7TVw53e3v7/FczNzc366c//en6z/6z/+wZwPXk33fv3j3vbF5dXT3/LY07zS9/+cv1X/6X/+W6vb19MUlNAidjdmV5EFtrvVjx5iCmnawUxB0g2+5XIyZY3OHaJWqU3dsikEzJi/eRHK614f08PX2ZkDH4MAFOk5y1Xj9xMCVFDnJpDKgDvXNXJSXdfv/q6upF0PYx5rikuknXrtcULJJuW1LremqykA8PSi6D6zXJpzHzIOhBScf7OUlNyQntLIEfdcR2XS8cn+R/SRccFw9aiYgdbfwSb64/D67JVlTXk3GX0W0uyeDypiRF7ehewraURCVs9QCXcNR5SLuM3qb7p7dJO2x+MiUmE66lxY1kR82GvE3GgDZG9GnR9fX1Cz0m35/kl85Sn4lf2qrznHbMfNz9AYpqz8c1LXa5XG3cOSZ8UKO347//dJmmOJUW/vw+H7DkOJew0cfcJ6mMZeSd8nhMS7+d3Pk82/INgBb3lIP53/3xb5RS3pT6bnzJFrxNl4f8p3EiP45V/pc/E264L02xoOFxWqhtcV3vvjjn7SX7EtGeXS+Omd4eY7QecEo/cz2KN9/5Z58tJ0z5BRdhfHFQvGshhX7nC2WJkl8w31GfrvPkZ7QV2hntINm480A8aXkI853EV5Lby7VrDVPYT5OP/Dp+J17Unttk09WOVCbh/AlddPSXAKOjvbe3ty8AwkHw4eHhxdN/11rrz/7sz9Z/99/9d8/lr6+v1zfffLOenr7/n9Xr6+t1c3PzakKgtt0hPWAx4WA5lWVSyAFvyZ8HKTo4gXlqh8mjriVQT+SOS1BNZV1O7nhwhS0FiQayTg7KnMimRMb7VH3Xjffb9OG2mPhtAX8KnLSTNOFqfU2g2hZLOIauowRErqN0RE+g7EGNQZG24J+dJ29T1/WQNF+EcB4JRCnR03Xq3nWi952vJtoBoeu52YrbbFoxXys/4dV1pQTSJ8a7hIV9JBvXEb73798/42TyOX6n79H/PEngRPUEl6QTJZEuw7Tyzx064mp6qT4XBpIOiGmccDAmuN5Fbrdpgcd5YJLqbXARqdlzktnL39zcPPfbkmqOs9/3RbpLxtfHK+kvJUoTplNvTQ/UeUuuE7460Z+4UyeZ7u/vnxfmUvxKiWuiZJs+WfT/mXc5pGddS7jRFgnYf7KPHe40HGqfKWOqn3TD/hImr5X/wiPZobeVsDP5SKK2IJx8kpOmlit4PcXoNLnlsWvXbdI5vztvqpfyC+83Tfwa9jofO0yf8Id6bjqnffi4u3+qTNo1bvbN/CPV8bwo4ZSPLWMYye2b7fvYsn36SpKx5Wwpt/G+Gf+S/7Ef2lqLlynnYAw/oYsmqm5kNNC0MkvmRLe3t+v29va5rD/uXeROpnIEGe/PB0ZK8ITdB8mTbCc6VHM+H6AWIBOPIudLRpKCAHXINplsEMyTIfDYkn4TQ1k8SSUffECVeE6PgaczpuRCslD3LYC7ntJihvNFavqlbt0uk5Om8glwueKdVrCSzpLfUOftHnnzRRCVSf6S5GIZ2n/q08eNE2EPoqzf5Gl6oD6aLn5IXbYh2fQ+6erExpI9pz7ShFFPVX/37t2LBb1GblNpErjWy120lDCcTGYY/Ke2W135SgtwXrYlNUl2Buym/zQWziN14rxocsqE0+u7L6QkgWVZh77ruMtFWdeVj4N/boucSddNjslH0/jwPcWapIvUH/ncTf5Tn47NvojsOvS+06Qp9ely++Qj/WbU2/E+XTbqo/2ko8nqY+AxIcUT102bQLAMMWKKwfw8+aN/9+s+1pqwTP7h/KY+29gl3Ei+zEUNb8f7cz5dnvQ3SgnbdhjMmJs2V1I9xgfeI5ZwXJJ9+cvrTPGN5djOxL9/93deJ3ncSWXZHucm/rm1kewu8U07bXhOSrK2WNbut/Z5n+OScIT27p/bODa6+GFKDrBKkhp4uJBJAL/OAOSDw6OZa33/+7s0oOKRikt9kD9vIw2wg1C7n4BMPzInJR5ScpQAUHJqPDwApoDi/KddAd3zwKr2PTBy5TABUZIzJWPUYwO9XYJGGVMQmIg7iUw4U5LegJHgq/Z9cSA5susj8c1x4uJGAkS2zft+FGdn2+TXfTQlLqqbfuu1SyaTrDqVke5Rj5KDCeCkiySnl0kr1ym5bz6XME82nHzW/Y+4RtucaPKBJI/rTIl7wsuksykJ8Dbp29wlI48paCe8IB8tYVjryy5Ckq/VSbJOY+PHFVmXdjzx6/hLW/Zx877TkcNT+/8hlJIkb//vq58dD2nHNV2bcFZHZRkn1UeKLc2GNR63t7fPpyDk24yxasdlYd8JR3e7o01W1qGPu20xDvriCG1uN0Y7anGntc2JmOrQJ0+x/lLSWNzd3T2fnHKMSnjh/TiGTLlGW9hiec83pt9T+0tHg/3hozvdNLtqeax/Jn5zgs4FBfqCyzf91clJvpVyS/LnE1m9+zxjtyDAHM31SUxnXHae0yJE0rPbnvfVSPGw8UE5KB9tnvy4jFM+1uh4oupg5C8q0weeiS9Bnu8chM+fP7/aNUiJVXKK9HLlMpmlYaZ3N04mUKkfJmUiDmiabKtNJVPJiDwh8gclJFl2uqHhpLGd6rTgT337tcSf0zQpmeq28WPf5NvHdAruyS4cxFiurcBLxtQ+g1x76h/lm8AikfOeAiDLpu8Ed7cZ2S7tV+9JN3p3MFYAbQstKfGXfhkk6HcpODUdTzZF33T9ipj4+a5KW/mXbAkvufiWEoLJb9Vf2llLfpFW0pNNJH5YfxpD4nz6Th45mSCfxBL27+2Rkn2TJ5cx2ZGPIReJJr2l+x5bfNJADEt9J9kSRuz8f2q76ZDtpGuNdvz42Exxq8Ui4dXT09OLv7zzchwb2Y5PCrSw7O1qvJKtpfyJRJ6bzzefpV1M9ua6Tk8xbfGS9am71H4jxtZGrsupv0uv7fhT2aen7zcSPn/+/GqiutZ6hQvedtIb47vbrL+TuINJbEs/O0pYnHQ45RTJbpKtTb6b4pG35+U4QeVvb72vhJuNGHPcnjhJTfmS6/lkwpeo6dj7VD7FWH2iW/9Ov095gevzdDEs5VQJC5sdN7p4osoJYppk0aHkRC6wC+eC674MUQGDK3a+i5icgO25YflnBnTnjddkGCkhcOPc/fl3CiDJ6JxPH1wPIv6QBL2TbxJ1vgt4qY7zmNr2+ynYN/LyvpPsv31riU4CxpSsJcBOwTfJ2EA78eTffXxdD76azvYJiKndBOynwOh1CLwn5AlY01sCLPpUAl0GXP1mzFeH24TV7zuwpz5bUue6JM/On392+Tjh8+u+0Hdzc/NioYlj54GZetd9JiLJnzmhdfmurvLpBOohBSLqhryLX95z2ZIMvhvClXbHfH9POwHOt+63vxRRWyn5Jla7LnyBsCW6CR8ShviEhsRkdBqXhl87YqLS7rcyKSll3dTHjsfWl99P715W+qUe05jx9//k1bFJbZIXJv5envIwTvn4ss+UfLIN+Ul69z5SfFYbzZ4mXTPGpnFljE6U5GP/LMM+faxbu40/18HElyZLmqgKV0SeL+t7kzsl77S1nU79xRgxxfhp4uAY4+XZlo8pT5N4rtNkbLJNfufx0f2G9chfs3nymDDLdUK+uLM/xUrqN91PfsLyE9YlOVMuwP52vkV88s+08ck2T2PT8UT1w4cPrwK1MyyG9D4l+zsGXSAZIVfWPblT4kKDpmLbfZdLlIBZlHYfyPMECklnPvBuZEy8yZNkch0k/U+kftuqydTOro/JQXf0/v37FzrVavV01CP1lRJCfV7ry7EFTpYI0NNDq7y9BkZTsjElBVqASDZFfpgsJ15a4J9kaveSjU/BP11jsp38KgUlAq7KaCKixMH5TJNU56M9CTfxkYI1ZfFX+puI3WIbAwz7Tv/fKPk5gW825593/ur6cxlcRgb8FPS4sOfvbr9tcZRjI/2oD46FjnKyHy4A+th5Yu8/d/HfGFJ+lzN9nhJFjm2LWfqu/tIxzIT/XqctEHlfSaeXUIvDa72Orx6LU2Kc7CbZlrc9JX+pPm04YbHq+wKd88vx1aRFMcb9X8eB2wOV6OctudyR40x7Cq3bRqOka9oqcxfXHcc17TA6JX9qOZzyAuclYXxqg8RxbTFU47I7Nss8NT0EUbpstkne+DnJ0/CDvs2FXPcB8a/rLrso5bv+0zziI/GZC8qpvMf1h4eH5/H2WNfwwHn37wmXk1+znvPu7Zz4Ju24teUT3TSXoo+xX8ZW+mLC5LRh4+142YSNiVfyk/DshI4nqmkV25mQ8H4vBRpf4UqBgqR20yTNhWZ7aQCTYfJsdePB3/3BCEkWrtInY5dcvtvsjktjTBNVD+767EGPPFIP1H9Lur0/1Uu2MBndLnlIxNUt101LNHbUEhzXodvqyQ71af8/NDCSL8o8JWhtrP4YOZykH9qG89gmLa2vdC3tuPJx9x7QtLjVJqqTXyZ9pcCW/CMFMu4OcjLRAqz7voKFT9Z3E1Xe87ZdPsqZSNd9gsPfxtNX0sqtT0o5mW4TVeoxjVGSkbpPNpiSNcmiBColEhzjS3yGCYLHMSW76WmWadej2Vf67TP1kia0qc/E85RksMxke6zTEp4p8UrJn7eV/HxnK2lCR1ujzbq9t8kaE7+2qLBWf8I09ed8yQdlz7zmfVJ/iVr+lHId4pTnLCnG7XKCNP7+cn2nCUsa/4az7HOKE6rDpLstJnBBcrfQnRazUjxJ8cf7dhtnjGC/U9zjtdRf6tvjvrfvcdIX4FU3+UPT845SPPY23UdoGy1Xa+2lsiexIcV/14/3q/stZuq+l0tzB5bV52lRIenBeW1yic+28HZCxxNV/kE0g7YYdqP0lSMpVglA2hGbQEVtiPjXEASwRirPv0+YQFKUnsqW+PRrqW0mX2lFnkEvAYza9x1nJY/+l0HOD8GkBcGWKFCuVCbxmGQ9cWICqE8QvL8WUJ2vtPKmthlQtYMyBbsTAEr8JFtrAYxgk5J/6smfoj0lQl73FDAS3+LT5XVeUiBLADfdc3Jcoe9w5ZVBkHpmwuN8kDevy1Xxpj+3+/QQJA82zs+UCPupgpQcc6K6m6ROOEv/kzzv3r17/mmGPyQm2YQHJ9990HeOA/XH95Q8pfruu74rkMYg1eOEb62Xf1ROPDvxd5XzcdNv2x4eHtanT5/Ww8PDi9+7cYyTbiSjxsJ367hjr7Iey3zM0okF2cVJ0uvXd/HY61H3LiMTnBQHUvwhPrRY7zrxnXJip+uJWOy/mxMfzDOES1dXV+v+/r7GQMZr4hcXo11PnuOonOyo5RuUz/ueeOPY+EKhFl5S+0mnjR/mdoyFu9iYZNFYJHLcSLu+KZc6oYZda71eiGXfxC3ij6gtlqSFE/Y17Ybxe/ID5pKpXY67v+QP1JX6oR1MOTbbp07XyrlJksPbSzJ425Sp5Tj8LvzwPPRkMTE94NT54rjvfK31nzYKpjzY7dCPxxPHT+l4osoAq2spCBA804Cn3TK2x+CcEq5kaA1AkkLTvQQoV1dXL37ETaNvBkhjTXISkFKQmkDRkw0FWQWsacKZgm0ayyQXZZsSRQV/9dGOHzVKSZOvgKWVQ+c1gXeTQTrwZF//7ZuClffTgjrvp/LJLrwfJgMMOr540n6b5ICTEuw/hryt5gv03ylwe90WPFLAoIwaTx9byk09p/Z9UuNtJL4YvJ0HJkAuo9flg1kE+B6cGKBagtL0vvPBZpPOMxcMlQy7zulLPlFlgE3BL2FSSmhcTvLrCXzSOe2WOKzJhU+uPZiTT/KmdjyBl+w+af/06dP6/Pnz+vTp05iA+zi4TeklzPL/SU270zwdlGICdeSTxbaA6mPQxi7ZLNtgGSbdjoMpz6DcHFvniQ+lSi/XvfO51noxthy35Pfkp8nvNE2eKY/K+X8tuy2Q3I7T+Ds2tvsJn6inZC+ceLMOJ6jNL2gzkx5b/OX3hElTzEw2pzoeN7wfxhXJ7Pd8cUYy0K4of/Ih8qq+GvamWNF8k7r3eOBte4xO/bg+yIvu+W5sW6RIWJxiHuOocmgft1TX++LpTJVnbkBKuKvxdt2lBfYku/ObxtT7bBjk9VPsdL24Xbq/M2dl7nqygCm6+O9pEqMSzJ0mJR+JqEAap65xAtJefp/8JgNNfbtMbVeSALbrszmMBncy7GZATY9pMsL29DlN7BKvSX/+Pa2mMWAm5yA1hyKvBK009g1Id6Q6vgpN3lp/ie9dOZe9JUXN2VXGkyyfoPI3kZzQel8+NpfSZCeTzpN/tYCYKPHcAmvCFvaxC9YpEDoPHty83PX19fNkhzqnPaSJql+bVsopSzpiI3z2iTz1QR0knfmOjWR3m1K/vsPivy2afmue7In+kca50WmdhlHS/8PDw4vdWcc3ts3EXxN07Zj6zr90oetpspPGxnl1PjQ2vsvNXWVd0+RHbbNP6ibt8u903jC04bO3nezd8XnCB5fVk3nnxfXDmN/wONmR2wh3DagHb995SrHBx5i/F5zkkdxatOBDINt4pf7XWq+SUN1jjOO4sb20sJAWUbxNLtLpc9IZ++GEI43pNM4nOUPSYRpv8ut9TH2mPCLhD8u0viaeWk6SZGE55mOJB8qTePO2Unx3OTWpTJjU/DbxQ9uhHMk3vG6Sb/rMa5yoOh9r5YWkNElNOcqJbega+25yO8kG3dfSwlJaWD+h44nq7e3tc0dtV0dg70qkgKeTBdWhwMlh08ycAcD7duDzsh68dd2dNB2bYVAjLz6ZUHkaQ5LbDbQZnZN48wnNro7uteDItncPkUogoZfvSip5Sn/H0XaAffxTYEm6bE6bPrusfk9JXyMGZvbLJKut/jt53x6UvR2W527AWl+OAPtRNj6ELK20p+A32c+OmGS5/e/a8gSaY+nXXa/8jVTT2Q7YucrvwdhPVhDvkk94u16m7Qq4jPquBLj5WyL2sdb811ysO93f+Q/5Jo5PtpOSE+K0jxFlSZjVbHnSp75/+vTpeZL58ePHF5NA5yct/vhkVEd71RYfCNIWFqYEWOOpY5YtcWIb9PdpLBo2nNgG74tfLcJwh/nEL1w3k/95/y2eps9pkuNlPFeQTojzjBtJb2mSIUp88nkcOwxI4yW5WCf5B+3F+yY/U32XyXGI+khjlTCddpFwPF1zG97Z86RT/5zsTPpovkt/Y87HWO5l0oSm9cOfLnAMkn/tchPvc60vD72kTbmtkVK8TVidbJe88kUf0Wfalrd5e3u7HXeXxReO0wLyiT6neJ9+i0/e9T6NX/LJlkOxPcnpfNBGVXeKqek16SXRxRPVh4eH5xWMdi46MZECUBKu1UmzcS8jOklC/LMGhpMvB5sGhF6WA+z19b2Bcmsz6SWtyLZJ3gntEt3EBxcgpqTAdaOXH6MjIKWVd/bTAoyA2e2LY622kqO3BCLZmjuu/CGVTbsBJ5NV74e2m/QtmXxSJP3KZz1w6bds3FlNCRiDRBrfZHdT4jL5v+vd7aOB3ImfJn2nMs2Hki/7JIkBcQqqbid+xCjphe2yfJpgOE5qHNPOE222YUcaP+rG75N//uZxohZs6b++O+b3fVyaLMku13p9PNj1LF+6v7+Pv+9sCzyqq0mpH/OlXloSyoQ+jaPe0wRv0kPyX+rIsTXJfBLHpT+3Te0a+2Q91Se/+u4Y69fUBvWYsKfhRFqIT3bu454w330rLXL7hMl59P54jf2kxNwpLUglP/O+Wt5CmvK55mcphjU7VDnfUU1xIOEbsZPXmg5Y/0Qv5J861/inBf8Uz4kvKicsSIuvzmvqL9l80gd14DInnKMfrvXyGQ4ph6HdMPdoOk788eW+6PbBsWwL0ak/b8f9TnMin7BO+Jt8OWFNktPfmRd5eyzHcfJ7ycZVn/e9zOQ/Ez87e2t0PFH96quv1ufPn9f79+9fBJgTJbsA6TiM30+7Yj5RTStqaiu9uzG04OOD7dc9AfIg2kCJ1EDtNMC3a6w7tdeCxVpfVoW8H/Koa6djPAGL+vDf3TlvE/ATaNMk1cfSx5vOTH5pR74L6buA3qbASbbBYKLPu5f36/XZ3+TYzkMK9lw91ku/XfKAqaDmD5NKT/ye7Jk+shvXNC5MfBxoqae1XibrDIA+FqQE/OQpJTzu8+/fv3816XNe0vHWpAtO5PRZ9afdZU7cPJG5vr5+hdWTP7B/0k6nKYFpSUnqh9/TKq6u6YgrE/60Y0F7Ih+uMyUgLRFqmK6+XQf+bIM0Bs4jbdxtqtkv8SLtyiZK2ErdePJ4c3Oz1lovTsRwHJMM/vJdMf191P39fcRCT+jTGKsd2XvyV5/EJtmbPh17Rcw7kg9T796/ZNF37nj5fedTNuft8wgsfa1R4lfvU77iOqO9XJIbeB2OOW2QZSmr89+w078Tn1m23SePrhc+yd3b8XZ9rBl33d68L550kp7bzyYYi3lyKmF7s1vKwD74t0rE95ubm+e2+fc9jq30D/HtvKW8hpTsPk2Mm64c5zieLh/nIk9PT89/l+OLjxz/ZD+q7/8RT7zUOKT8R22QR8nOseS4EwOIP6msX08+R9mdB9a/hC76H1V14obng0Sw4g/pEyC0JMWNKx0dm5It9ZEMXIPBJNd58jpMfNyor6+vXzxYY6pPfuQU6XoLJpSP95iM+bWkZwfHyZCnz+SHcnl/ajsdX/J2kp0kgEwPavCHuxCEOHZtgr/WvLOWeE+B05NGt1t/6Ib/HQV1lSap6T0lGRwftqGg38CfevLx4X1dT+POJJPX2m7uRNNCldpzvWkiyYSqBWHq3tuXrplocMxafxwn1236HfK0Wkv+fEHB7wurOVli0EuBym232X7Dg4RjyZ6TnVJ/Ce9pi9SrLzj5Q4Va0GQAbhNVUZpgpEVL2hPrJHyfJhwchzSeUzKQxsmvpx0Y9SMbUrkks/zPbY67D+SRE0q10RJGl7sd9W8+3HROXbx79y7ymqjdT7uZTmq/5QutL45JouR3U27hGOx9+SIo5b1EN3xPZdJn9sGYt9bLhbrUj+Ty4/pccHKd+WQl/Q3X9NRs4hb79t+NJ+wUMb7KpuVXWuDhGPpL/uF5EcuxrvfN/En3eCxZsqa6Ohp8c3Pz6lkF/lRoj/tsu+HwzvbEd+K37aKqnMduLgZ6bife04YX2+TixOfPn59x5vb29hWe09e5EDnlQclv+LnJn/w9Ye9O/xPJPk/oB/+PKhOHNLNvYHYCWClJSm22hEdEI/EBmia7+s6disSj2hKpHwbdJqvKeH9TQJl01q63ZDBNVMk7wTStsPr1RtRDA50khwOvEpikG3/yWtpJ9F3CNFlNY9JoGhOudjvQCai1a8mH0kyAPPlA4nsKYrzvbXGlU/d9rBlI08pt03V7InFK2Hb2QVBNSQsnPm3s1B/xIQX4hCvsbxob6UGUfvPii3ScOJG/aYfL/wKlTfR9PF0e58Hb1fe0kJESHOmFwTYleRz3NnY+Xk6yJ2GFEsamH6cp9jB+pOB+gvUeI1KdlgQkXGiLjaSUFDecd770rn5kh/LfNoY85swFl5P46P16WX+lB+0kf0/xu40J9bbT6em1hM3sM5VNdVxHvD+Rj2nic5dznPShtqacpJU/yQlSnPA+0tj6pJNY4GWFpXrd3Ny82p30UwVOyf6Yj7SFtZ0NMN7onTGKsZm6T+S+zlfimX9X6XxR56l/6Yd1vFzzlV1sTWOa8sWm+2R/nKg6H8wFvG1d43j74gHjgOOW9+dtpsWphBdpwTPpLc07GLeZd0zxk3om3rvcJ/SD/kdVSkxO6kkWmebKvJjegabfl2AKkC1ZmHbOXNke5FLf01NSnRh03Eg5sUsrOW0HL+mIzqNrE7gnR3D52UbiQZSMmiDcVsKb3liO1z1JoiN5ee/fj6aI35YU/H2T+k27g75L5glckj0lDgmombipXa+n9tjuWl/+WoH20XhLgMYnvqocbcPLpb/V4UNqXJ8Eu5Zs+LvrIPnGlPy1IOp96ZhTssvUxonNpd0iHZXkqm7SM/vh7hZl8bHhSrImG9RPO9Ks9hznZEt8gJAv5Ey7xkwO2F8KguStJXAtSZD81JWoXWv9Oo8etzy2ThjciCv5qX+X04l8JZ9Wmzr1oYW1u7u7aHO+W5ISJcdEj+Ekt4WE92rXH8rE5IjlPTdJWDhhBnW2i9sn45hiOvlobaWyE69PT0+v4mHix3VBu0qxc+r/hxD7SP22/Cld8wcI6v/l00TL2/Y6PlFNeY7Lzjw34RpJtsudV97nos9ar0/68e+oyFs6Ou3j7DvA7pdc6EtY4X1NeuHOq99PPjnZVIqtaWKY6mhTg/jDPCtNTlPs3Nmkk8udTkJxTLhY53/3OOUTUywlriZe09jRnolDzBH93g+l44mqK8QV60FKxuwPy2mMixrI0fBSGSo7TU5bciJFK2HSqrv3z/ocyOYA08BTBueHdZwHysxgzbZbQpeSMfK+Czbc8ZCze5Lbxo1JJ/k8kcvloXP47xsUXMSbfmPtk6L2ewgn9nXidC2BX+v1kUEFkJTUTeCRdES9pnJJDtbhhKjtwvkYt6QtBbimM01m5I8q7wF0t/pHWQnmzbaSLvm9LcCdTpjT99S3yyQb4RPV3V6SLtw3bm5uXo2ly+H26Pd9okqb4g6vy8eEgf651pcJhvRHHTGoEl+9L6cJS13HuzHw/qmrXV1+T2Pjtu19sl/vM9kl+2JdJoCJWoKVFqmEnfJT6th34JN9cOKedMf4lGIodcX4nXR0Mu78nHTKOn8fCdnUPr+7Tvkuart0J3y0+Dq1k3hqn3cxKfkJ7TMdxfX8zxc+lQv4jqrbIH3bJ6Tp6d58ud06hgq3GT+Zp0nnKU62+MTJNuu3jYIWA0T0I8nUMCXhvOf+nmv7zwQ56XFqR2lTDHZem75YP8U96qrlP8SzlPOm/D3lW9NmBXMO9tHsYtINPzcdyaZb/ui6PsmXU5+XYOXxRFWGyZ0RX2134/VVn8R8o6aUKSlNk9K0e0N5np6+X/nRatbux+nki5/TaqWDWJO1BRglda7X5izeF42cQTvVnWhKEnRffft7S0TS6tQu6Oq7VvVbcuCLKP5bVgWc9PcsaqNNphggnZ8UUFpi63Yi2/NgRvtLvK3V/zIh6XIa65T8JpBOpyQmPZG3lBSkiS+Dt+vNdXYKhJSzfZ+IvpRs34NJCkqpzV0Zt+GJr9YOxzatgCbbIA5yourBVAlYW8RIAS35NTGjYYLabYtLqsMV36urlyvQu4mNiDZ/gpnJ/hNWNdzgq2HoRBzjhN+J5/TMBLa31pediLRzocSWE03/7hMJ8pTsNcnXdEZevE7SpfvrZKNTDE+xj2X+GKKdNL7SuDL+k+9kg9Sb2kp449fTWCRK96aYy4Vln0Dqmj+giJNSxXzdazGJ/DgfDWM5aVCcSrEiTXa4w9lyjYYbKddIPuxlvL2EsWl8tNgv8p9Ykby+xww++TxNziSDT47ZR1rESjlu0h/HpsVZjyPtuQ7qm5RsJ40b8ys/XZTkSO0nndMfeX+HJ8TA5q9rvf7XglauXTvFxuOJ6u9+97t1ff39E8u4K+X/oyQn0+SATsqESQYspjVYrqy0i+EBhg/KaFv/k+N7MkxHo4IdQMXHlKCeGJoT+/TEjDsPIufbj3EmIyIo8F56b2XoAA28aAtpN/WkX7eFpPO02jStwHIyyHFlsNT39BCgZGs7p2xBfwI7l7HZUNJpopSYeR3307Qz03huwVVtevBioGqg63aTxmsKzpR5d83lTquerOfBNa3Y/30Qj+mvNU9kW5D0Mu5TKuNPbJT86fexfpSYbSXcYVKbkqWESynxbWOQsJaLLXwIoOyQiZP4daxyuZh0Oi8NI71MspEpAWK7kx48lvmibOJJPLS+ySNtw69zsZax1fGbdcnbLuGi3hkbk+8zZkzxtMnf+OU92vvJ/dbP1J7bpLBRdt/GbqKT5JHY0uwr4ZDbRIqtvoPJJ+X6pNPzPv72lDF8J/t0L/l40ytjn+MHj/jrWsqR00Mh9dRt6t37SA+Y5Ji4P7YYlezQ4xr1k3Tl8VO4e39/v+7u7l78ft3xVpQ2mmhfLfdsr6QLkT8UVZR2fb1emtz6e8J52kyzzYZ5iRiHpg2g1F7ju9nAFONSTs92uAB8QscT1Y8fP75YQdcxNFEafJ+cuAO7YSq5I6g2YzwxTtVnefKaePYy7Vo6kjAZGqmBQypPY0+7tqlfBy+27fpvoJN0lIy9TeSngMtFi0kPU9KSAjH5djm5404AaSuubaKbAu/uGnXBsXLATqv9LbHa0RSMpiRMevbvrMdAs0uM3Pc9mBEjvLxPkn1ixYdjTTbdeEo25JPi9OTdhj1+1JxjzmC805Pz0wJQ4t/b43W3n5QgqIzKuY/Rr/xJrrRhrlon+6ed7eSfgq10L/69z2miqt9R+m94PXlispXwhbI2G6bsvHYJNXviWLn+EnY4Hk4PmGsPv2ox1snlbLIm/KBsKcFKsd/7nPqeeCFNvtr4SjGr9eXvO6w41XeK220MEpaxvMfP9mT/xIvHwhSD3faurl5POrk76uVaPOckdaezxLfHP/k5ddUWR/x9WpB3f00YO+UUnoP7DicXC5lT0JdOcgqOX/M11xVf/hcufHKx+vD+fIxd1xwXjglt1t/pl96ft6P2264vy056a32d5Lmnduv2ybg01Tm55tcTJrvdTv424dKOjieqf/jDH56PWGhVy49bpIdiOEkAfziDJ318yIfvrHp9Dng7PsR++e4O5EnMLrikYMdVBq6MERS8TnJ4JsP8IT+TCOcl/eh+SvB8PFxmH88E1NPkpSWmzsM0VikZbEkd+5MN+fgm4o6p9Myx8VfahWWbLJceFuT2knZqGJBSoKeuXJZGPh5sZwLck9XX06Q7BWzfleM9Bj76peQQFvnpgxaUEjnfnKDyf87Wevn3Bff399tkP/mF889xdj+UP1Mn3i7tWbwk//LvJ4G22ZV48f/1c935WCV/8B2AFtgaDjhR946XyVdcp5448TdUSqIYIzh5pf2e8Owy+mcmAo2YtDX7Yj/EIsXy9+/fv9i1UhuS8e7u7oVu6JvOgydKvMfPlDUlmSIuFHi5NM7E1USeaLmeSFNMOx1rL9/eUyKc9NCSUMrCMhMmue/4fe5q8nPiN8VPTig5WWUcXmveWTvBr0uJtsv8x+2ZsbzpvOUvtCXHJ/WV9KjJuvRDPTk+0VdSv/xMfidMcVtrscBxUouDegq9HhDofTmlRQiOE4ljQvtTfX+nnMSQ5Ef+YM+U1ye8cJ7TZJ55zqV4knBsygFSGcdEx5NEu/ts+4fS8UT17u7uxZN2+Vh6rjrsZvMe0PTdV/Fd4W11rAFF6qvx4PVoHASXaZCd55TUeH1P/F2HemegSI7KpN2Bwt9Tcq/yk/yT87C885qS5knnfo1tpx0MOr9fU3/Jprz9NH7SKcfEZfNVSy5OUAdTYsPFFcrWAr0nE15ffK+VjxOmxISThlaHOkjBJAFhAspkW/63Kcke0i6dTwqmiWoC7XSdPuhB1Z9eyiSFR9D0G2gmcF6H70zcXMeSlQtPxFbaWTvinpKrhp274Lbze+I7MUz6Su01u2nYzrZPEivXz+Pj44uHTfFY+lo5vqWJakpqiVvJD1rs4edpTJL81Llk1pNMtfDMn/SIJNunT5+eJ/PpeKHz6E92bk+IbDK4HBw7LW60MSUf8oWUyOm72+kU+50v5iPCDH2+NDG7VA8kxxrXTxoblXWc1Ljf3t6+sAPZghYzPnz48Hw94VzKV5gLpLiYvrNN4tUUq3b60nXV466fv7eTFB47mWMQG31sdJ/6SdjB34F6HnJ9fV1/J5oWkKir9N5sl5jMfNfjshZ1Fdc5afXYSv3SltZ6/Xv4xEvyVfKf4oLXTRPeFHdaXsZXi0mpf8YOfj6lKU56mUlXvHdqD0lH7OtS33U6nqgqWSODnlDxXgtKKWj7dQUkn9Cxzlr5aWNO4o3vTikZYgLroEYZU30mlL4yRv4Sz9LBrl8aNn9Lt0uASEygkixTQNfL5aUBU+42JtQrgSS1nUBr53ReZkoOXa61Xk82U3t+z2Wg3dLGfUU5AaDuUzcESPLjgN92fZMMTHYb4Ca/pvxuU09PX/7fMx0BYvB2O/c+r6+/7GryUe8cH7bN+8KedDzJ9aydh6urqxcnTDyBo12kCWT6ywPXY5swT7bubftvujiRpw/t/IOf/VrCLeqd8vnDzFJyx/FLQZb2mOoykPoiq/hNuMoFU09q3I59l9Ft22Mifd7xmr//pW0m+92NDxcm/AFyPjH98OHDK9v19sTjx48fn3dVUwLsvKpcSlbTKZ82tqn9JntLlrxuwlxvN8U1f28TLfKRYtokZ+N5oqanpI8Uo10Wn4hysipbeffu3frqq68iZpH/afHtJB5PsqZ6u3ZSHPDPbqPa4ZPttkV6/8kJsZTx3LGcccvxjxjTJprKjZWPcFHU2/IxSXpNfuDt0Ja5mOd4pd3Sh4eH9fHjxxf4xvyRi84cG+pUuk5yujzikXIm33J+2okuf0+5mF9fK5+YTH7h/YtfYj7l29FUh3qasNQ/T/2ndlreqfeEoSd0PFH99OnTi9+oejLmzszVRqcWcKdkwMvQ2Vrizzq+U+b9eGLhQTRNsF2xas8fz+/tcoLqbfkkjjpKgEc+krMnYr/q23XjTsJxSEl8CsbN+RnMvXwCpdSG6mocJ6eRXrm7uFZ/4Iy3T0qg5bq6u7urZf0aFyzUJ8c/gR3L7oKby0wZ2R4nqNNqt+8cEqApv/sIAdeDgfTivw2k3XP3kHbPQMyAnMbFJyZp1VI25AHW+eB4uP58YkhfkR55JNWvTU+kbPxSVmJw0k9rP7VNuXiUvdkXgxQ/q18mYwxqfyx5e54QuF21oOmYQ8xSO/qe7tOuXN+e7DHpSy9vo+GG95/sS+POxYu0+OR8Pj4+rtvb2xc/z3Gbch14TPV3T2D1WZOC9jdH7TPHNo2B6yFRslHPZ1Jc8NjiORDld35TbkPeUo4xyTj5lvj2WOX4pEno7e3ts23c3t6u9+/fr6+++urVRLX5PnlNvtRia6OWH6ZyCbe9DcdMt0X/PT3xnYuCLcdKsbrlcv5KvkyZKEvKCWRzbTLEesqB18o7h9R3wh7HPMcsb9d/TuEPS/LdU5FkcP36z0Aol8qmmEi5dn7VfLTdJyX89/eUayV78Pboy8m+T/g5iUVOiZ8dMUaL/4a3zD8ahkx0PFH134zqnavRa52tcCegpRI4MaFCCUiT0SUn5Aq4r/QSnAgW7khp8tcM1+VwcgekI5KS3Kl97pIpgU0LAOmdn9O4cyx2lMAiEWVMTuDfuaPIOklH1NeOB/I8JVX+ve3ONMCibAS71HbyE8qaZJ4mL35fSa2OHE3g4mPicsvXxL+SA08cXP7miymIrpX/wzXp03GFq7nOOzEh2Sv1+O7du2cd+STLccMTXOHH4+OXR/+nXYppLKmXpgMdoeJxsV3Qvrr6fmLjfDPY+HhSNyfERGsX2JNuJr24fpK/tLoJixO2Nzxpfkle0kp6+t70kcac+nSdtslp0oH7lRaq3ZdEPvZpAuC+oYnqu3fvnhd72+5VGpMkb3o1SvkJZWZ8a7bVxk7X+J78i1hPvuRj/JzKMd4JlzQh9Ump76Tq3Z9B4hNczyXSQuUUX6mzSS9JP6zrtkXytojjfnrBJ6qpXS/nfCXMSTbpvub10vgm+WkTDUuJCZzQcheP9traTfHbeUynQHRdC9DSeYujLiNjv8sjPrkIPcWu5FNJd/SVCTfYV2uXbXBzqsUa2kSTLfU34d8OTzmv4f1Wzz9P+mh1T8uvdcFEVQGFK+D6LIHT0y5FDLhp52hHDI7pQSwNVBIgccdkCnb+I/ZELZlt5RwIpjITUW8OTkx624pLc4qUaMkgk75JbfemydjA2/tuQU126f09Pb3cXeLYedLW9MExSnZxcs154jXqxuuSZ9dBS+oSKCYQnpIkt5921Guydw90yb9aUrq7z75T/fROGckLbS/tujVqEwDpjg8HcZz0lWn+5pW7Nb4iTV0kzKJdpXGgHGxXPOrBEX79UkpjIh/1hJq7gEy2UhLnunKd6HPC910yyNM23k6LeSmukVJfCT/SderihIg9DW8mnaTffntd/351dfXC7zWej4/f/xbYjxPf39+/OFbskwrnseEU+fDJR6pPvfC96X2KOVOsTnZ4wkeypYlSfJOtaJf0q6++Wl999dW6ublZ33zzzfOxXu2u+v+MOz9NNpbZEf0v+WTbeVvr5a6d530J8x3r/GgvTzEkOVJsbTEmYWGblDRcd7vwNjkO1FvCIo8/ftTf43JaVKSMXGiiLuhniUf2RbldV5RL9xSbOeE/JfqF9MX+nf+W700xNuESxz/ZC2NqwiDqK1HyJe+X7Yh84b7l6STyn3LbCT99DE7H86KHKbWAvtaXCYI/TrqVJQgzuWvCpe/t5X050QhS4tb4FsBRlokcTCZqwdflbWW9DicTft+NkgsO3gcDMPtyeej4LO+rSZRrkj85PgOQt5NWeT1Rcr69bY4PeXUnTPpzeZIdJvm93QRkU8KTxmtKcJz/ZEduG0nnShxTm6kd1kvHZ1MCQB4ZMBLRZndBhuPF8WC7aYew6Te1N9mwxlKLfy3J9Hb82CV11vTjfaZJl8ubbHutbgNJf82GW/CV7FdXL5+imHToE1q/7wsC+iyadrzUputSdcRbmzgR08nbWnlylzCbuvY4I9xR27v6LaGh/Tf/3VHCecYCye0xhqv2GquHh4f1/v375/9W9KOD3PEi/0yQXFf6nmKEf26+RFzy9iaMZr/ymylZ94UyxlLec326PGlxR7ujet3c3Kyvv/76eaLqE5kfsgDiMqfrxHLfreQmA3c2XVc+Nj5RbUfG1T8nqj5pavlKkmuKIS3WpNhwf38f44zXES/uM5Qn8ZPit7ejsul4reOK88Xj0t4f8dDHieTjmOIi23B+k+/tFsvpP8ybvC9dc78Uf2lX2SlhaMoRUixnbKZt0RemPMjvT7qlryS96MTVRFPOkz57nTTnO6GLjv5OQZKBiKCXBvV0otpW3ryMyvFa6t8pAV2S0/tk/WmAvP3GA8HFrzdZEo9p4C9NShIIJr5Yxr/veGD5JlPTh5L7CTh8TBOAp53K1H9KMMUDkxkPqLsFihSIJkrj4m0lgCQw0oYZQJi8EaB9UtGCogOeJyOnk1T2O+kl1WnBvE16nW/yQf6oqxTgvd3daQKODW2HutX4pMmVj5vI8VBj4bz45xbE0hhz/HfEZIOfuaNNXYnShI2Jud69nTamlM358Uk9d9dFLRiLr4QpU33nOcWaXb3dPfYxfT9pM8UWxn/XgxYNRZwkacKanjpMHpNvTrwS3yasZ3vJbhlfvJ77MeNE0mHTZ7ouOTix9L8ZEjZ9+PDhxS6pHp51e3v74gm+PBGQeEvfExHDuOjDiWb6nbbr3vnhRHeaqIqXdiKijcdk600HLV4lfJjaY/z2e9xtTPwRx7zNVJ+bSyrv4/X09PTqGHTTQ5I15XA/BKOkW8rXeGHZ5FvNDtiHj23q33Ev5WJ8BgXzMdd56oN21fIYfm5y0YaY3zA3mMpOfPB6wtxTWzieqCYBPRET8+l42i75cea5Au712Zbz4e01BexWUXUtzfb1+5opgUh0OhBthcH1PiVKSaeSzcdk2qVKbbSdI0/qEo9T4jmBDfvgePs1JQGpLdalDG4LXChpsp4AhlOS0+85H4lv9s36nqykozHpCGJ6AI73dWqvJI2/r2Lz2BB3Oylj2hV1WRJ4s1/SNAYsp3cF9oQrnvTxWC/lYrtOHvikIz2N1pPc9FTJlnA3P3Xfurr68pcdfLBTSiqaHI6d/kpY5ffS6nTDPL6nCYvL5RNW94m1Xj9FU7r1/w4VX56YcScmJYLED594Sd8NT6nHNCnmhMd1wAW3RMTW5DdcTFJZf/prwwyOY9pBUFmeCpC+NWn59OnT+vTp0/ruu+/Wd99993w0mDtwnuSlBSHJ0BYDyTfbIRbvcNrbdJttJ0mcUmxKOnS79SOdsjH/e6ybm5vniaqe2sunPHubE6X41yaAbksuuyaW/pA6jmfCBWIZ29T1CWd1PWESPyecS+1y/PwzMTAtWjMOej8p7uxyD89xEqW4K//xkyz0obY503SQYtOO2vin++yPPFAPpzw4HrJNj8spl6Fv6t2xgycg6NMp5tF+EtH2Uuzn2Cc9u+78WsorvS3aTCPasj/z6ISOJ6ouTGKcAvBacrKWvHmZFgzStSlpXysfd3XZpoDljjgNSJLN9ebvzZmo53R/SiqdF66CJVBIfKTdG+pNMjw97Z/KS74mHlI/aay8f2+b+nbwarrWPYF3S8qaPaZ2vf2kg+ZPu3Glnqgr3U+yMPFpMrh9Un+tvict6eEoE1D69aZnyjitZDfZaHMt+NEXhAuaoPpTM1MgS69kC57U+N/P6JkAaeEk+QrxK8lH/Xj5tiDFemlMkk7TeDUiFnrwZgBPO+aND2K4j8P19ZcH+Oiz7ic7JsYkfKY++bTsFmOcx7ZII3/mk1dTcuF8+uemR04qkv5oJ802kt8k3pJ/pt9GSnfpCaJpl8jlIr8NWxpWNpyYZGCu4LpISX/yWf51lfPlNuVPYecxXn+yr09UpROXd/LVhmXppx2+A5cm6f47Udpbw4gU5yZ8afwzVrQFNR+7yc79e8o1pkl0i/3EktN+xS/bOtWN129lE7GvlBtMtIuXjVfnL5Wb+nN+9XnSUcJn5rrEDNpZ+uubxjPlavpI5PjTfLthVcslTsd0Nw6ON17mxE7WumCimgTze4m5RC3gN+NMn6e2p51J/+xBg0HYVz84udXnCdxbYEsAmwYqtUce0mTcy8kw2Hdqn+3tktYpQOzGiU7fgnfiO/GbgoS/+30/huZPP00Om3Yjk3wcQ+rME+5mg8lemp8lX0urgF6fExG3bwIudZp0kiZCPp67lfLTZML5YmLR2k6B2n2h2SwDNfWuRND/3kEJoBJs14En1DuckNyfPn16kaC2XSnnz+3Ux4dj5uOeHv7Dcm2s2ri5Tbhf0z4mDEy+t9bLo7hpp8bbcn03e/a+tJvA37WqLcpCOVKckY79GGbzwaurq+fdXE5Sfdw1mXY79P7cntIYPT09vXgSp8vlOlU7zt+U0EyUduraX4V5P66v+/v756cD39/fv/hvVv9f15aMOc+MOWnsml95Aujl02fqp+GX8+a+62NMu/GJanr4mtsc21H5tV7/Fo127ddp97476n8vxiO59NO2Y5RsSzQtdiR9JvvnokzyNdqAMC3F3yn39XiT7MxzE95j++l7kr3VUxnPNfwadZRODSRqPJ7kjNP3FM9TnZO2JoxKPKoNLlilsUuLHGzL9Z1O5STemo2yPZfDcanhV9Ktxy/ywdyAecQkK/WSxtN5PKWLd1SnQXYmLmlzcohLjJLXUsLDBMOTt/QwDtVTu2kVMPEg/kkEaDf+ydFTMteIxjEZkrfdkogGIjtA8OscCw9eacdiopSA6HuatJGPxG8b0xQoqIvUtl4aV+qwJU1TECBNAb8FWU8CXZb0ead758MT4PRExkso2Vkqk3ii/txGPRi1QJmO5/BptHzd3t4+tzv9pjHx6EAvW0lHsdzOU9ByPXDBzT8T56YHqjBwtjFwW/bfnKVdFQZHt1XyRRnIzy6pSTuHtIOkS/+pRHrw1C7Rvrq6evEAKu586V329vDw8IIvH++k44eHh/Xp06coN8eGukrYlXxecmhnnzaf7KvxQNwn3vjvFXXddwSlz4eHh+enBmsCq6PBaifFGCZdtEHil4+3dh93cYNE7NZiRCrjduF/DyP50yKydJ8mst5v8hfpip+5uOjyeTs+UfUn8LqvUI/N9lpCPNlQsrPEd8KvZOvUr661+O+fGQd5L415im0ep9pubosnqsNFSNcD8bnFwCQjeademPd43Wn8PD9KOQ75aTrg9aT3VD6V2/Erf0w2pTLEltRmsp/ka7sY1/xCMcXLppjQ+NY1+kHawEn+N11XXd9A2NFFO6r+7pSY4PVWJt1rlAyDAbcNgJf3hMkdvCVqrDeBnjtzc4amh6QL6j2BQgM+8r2jBJoN8L3OztiaE6S+Wv0U3NhW69e/TwmVf5YTtQUB2gF5TLy3dryNVq/ZcLL31N40TkxWCZTJHyZeJoBqOjgJQBPRT/xdOyI+pt5nCsh656vJ3nThZXd+Qn2TF7fNSTceVNJENe26KBl3e/edxd0YcWLKV+PPeXMdrNWPs6XTAH5fvDNh9nFvY8fPlIG+4fKINyZ0uk5f95h1gmluw9whoT52uJ36YWx02Tw+8umyvrjLJM2vJR375Jtj5Hby9PT06q821LY/lCfpLGGk27k+c1Kla9O4TDbo330RmNh0dXX17JP6n1NN1Llw3iattD/nzxdL0/FcX2Ckbbt8nKj6u0+CJh/Te9LjFCtbHZeRfaVrHMuUjLeEPI0r461jQovflOEkj5iIfPtkW+1rEYf2kPhpsqYxSDpqeR7ruY8T/4hBP5SYv5yWn/oXr7s47G3qnWPbcJ5l27ikvIT9kgf209pKY9T0kvKDtEiV2j2hi3ZUEzUF8NpJvV2dtV6uUKREQd89wDBYPD09vUqS2EZagZqO8SUnTnSSkEz1kmMzMXAZTsdAOpt22lrCmmRiMkAHPQENd47UBsv6GDAx4BinINZsOAVR6paJnbdzIqsTHZqJW0oCWp8EVf/tY5Iz/c8cgyDHhSvpLdnRe+rbiTxPdOpLHH/XaaubEkElZ1dXV88PWPPVy/TbrRQMTo+9JB02W+WKvsvsu5a+S8bkRnr3nXE/XjmNyeRP5CPtCJGfNBlSOZez6ZQ8TDK47eo4o4+r2kq75SnBkn8oWRR/T09PLyZ6fo8TPpLjLxdbJqz2+LXWetW/6rn8Pv5r5YdAaSx4TJUTP5cn2bH7h+8I8VjvWl+ebqs+FbMeHh7W3d3dc3t8UinzAe7k+E5J2lltGJ582/tJu57pc/rtO4/+Nrtwu2cO43az1nq27bu7u2dZ3d7TbovLSj9oO0uJkgzEZMbZFBvID2Wk/IkPjgvfWyxpft94TWPjOqTsUwxLOQYXOvx3zW43Glt9dgyhDOSz8UG5T3PZ1J7nBNTLSf1L+k726jJ4HixK+YNwIrVx2jd9IcnLBWTaSrML9qnPruMUI53YT8Of5qcNRy6li3dU03UKnAycALPrJ/XXnMgHJ+2IcneMgcLbV3mCMo1jkq/xn4xrJ3NKgtL9E0CZyNshUPDlQZ4OnJIZ3vOA5Alc4qlNdnZg6X1PCxEpqfP+Wz9MFP1+2+1IbU9jT13wdZog6L4nX80ffZLCviXDSUD1Xcwkx05WBdIp2ZjIefXyPN7OMUh+7fL7zqEnBOxX+uPkUW2lJD75crIv1uPOI/lmecc08s2JjcucfIRtT/1LH+TDJ00ac5+88gmKbNeT1dT/zgZ0TTKKB+3U+cID/27J5fJ358HtRIsE+v/Q6+vrF7911tNY0xE+90FOoBpuNVxkXU4+OHFxcgxQcpx+UpAoxW19ZqLteOWxYq314inNV1dXz79h1fh8+vTpxU44+0/2yf68LP3Ydclx9gWX9DvlNOlPR/BTnYQ1bhe6zgVDXfOJquxYk9Y0UW2JJu3QqWH8ST7SsC/lPiyXxqbxtttF3cVU96e0mEHMmXCQMjjvxPaUB8h+fDGPdaccy/lPtpT02xZHWnyQzF4+9bPT+w+llkemcq4r1y39T7pyn0m5n39PNqLPO/tu/Pu4pbZZN+Gck9tPwkny4D/Z8FxpohMscDqeqHL11Ttz5ij8qeOLmFi0gJvaozG1QVCZBPpKzNzwCCKp/8nIUrKYDPNSIL/UIGhsrb820Ur9N+Bfa37gU0sWyFMCzIl8MaKtkjKQOzhP48oklHWY1DQdqj51tpOx6bmBTrLXFHR8LNKOqI8xdyJUn8lrSuzI085+k6+d2kqSrWGL2+mUKK21/83JJEsLJm6zlKdN1J3nFuSmZIk+4BOxdH+3c0J98um0rOf2ofb9d5tc1fZxZFvuh7ou/9eEhmOf+Pf+n56+/52kJj6ayPqTZ/23pYx/Tf/iSxPVd+/erc+fPz8f91xrvZikMpZ5jGrjzT5T/KLv+iTVdxV9/NNusu9yu++n5Mn70xi5Tq6uXu4McexpV86DJtZ6wNJa6/kak0i3Y+7ktISTcUtEGWRz0knbceZYJD2mCWt66Bd513ce6dWkdNpRpZ0lvNphNsfnEpxMmNviJ/tN761MGoPGh38n1k6Y6P2y/ZRPJ9kSj5yM0m683k4fPs7urw3j0+fWPu0nxTLmdy3+ntCu/CRbiici+qDI8yV/nfSh7yk38fbXyr8pbe3tiHifbM9fKXfmO2P5id1N9xMdT1QVxHfJtJM7gDN5Sqkekzldo+NObZE/gn3aBWr8tHb5nclo08PUnr/LSZo8Ox7dCZymlXqvmwJ0ChaNB/Evu2pyM9EiXy1A7SaqPt5MishnAlMmcM03mq+c6kjUHnyjPvz4LUHPA9JEDMZJxxOApaQ37Twz0CebFU3HShIW0Kep32QvrR33hZbIUmftRfIgkSaqyZ7SbiL1wvucjHqb7EPvKYD5zyamMWv2zD44gaVMbuv+37UcLx8HP27tdpoSDGJpwgqfHGjC6w+NST8LcfvnTyXE49XV9zuAnlz6g7l8YuP6bBMpn+S57za/S4tR9Bn/W5g0YVU9f4AR2+LYs0zCEj/a63+1Ivvze+r3w4cPz/rWRFUPXXL+fXLvts4JnXTqRLzgJNKfwusLDX4tTVSJH26HXtcn8BxHP/L86dOnZz3wSK/vmvIvZJhkp4Tb403L6VyvLuNJcrqLTy3WE/cSRra2aY8TNnoe12Te5QEnfHlZ7nbys+OofMPb0ctPhzScn3IE6jbFzCYTsZ/X0n320/Bk6n+Kk5MNpxMM+pww1v86y/ME5yfhcLJfb9fH9UTulrufxHfd1z3GS+Z5Sa4TSno9oR989DcNBAPoZPQ7h92B2q49OjLBjAmXD9K08sM+UpK1SyR3cqV77GcHBic8pTYdrBtfky4pZ+u78d3uTUlQk7UFGZEmQZQ56ZBtpTonts92XQb262CdEqKUfE8BceJpCrBp3NOkibtuvrM6yb+jVN552Mkx+V2618afyeWOP/pJ468FcvaTsIx+5rI4z0yi6FNed1ocSG24TpJdpLaS73gd/sY8BfOkU/qh2+uUwKSdurVeB3XJ9/T09GLxNj1MSuUm3WtsfCLli3dMXjzZ8ESG8U46mJ7kmj5PfpPsK7U9tc/P4tXl1A6zdDyNIeOQdKfj1JyoTnYi/bXYSjz2I89poupjk56UnNpPum5EvSthvr+/X58+fYoT1bTwMI27U4rpJ9g3+W96n/pOeE2/bfXbuKb7zbbdr0lNplP5yA95EREr3YecP/fR3V/GNb4TBpC/RFOuMRH7OJ2opmsp1qtsu7dWf56F+yl3xH0RapcfNFz1cWP5nd0wDlMvCaOTDUx2txsD1k+5CXf8T+mPepiSHDeBXQtKTpcwmijVZ4BPgcGTg7Ven9lObVKmpPQmTwryl8gmfpMRNt5O+5n6dOdo79Ibj6KllWXn05OFKYDsnCsBG+XwB4JMO78ndkp+rq+vXzx0hGOSdOrEwEfg8t+vcRXfeWKCPemt+U1KrqkD+pbbgSamusYdyUTen/OdgiPrJd/2Nlieekn9OU/+nmxs0g+vk7ckU5rUe5u+szTJ6vVSYOBRHa5uTklfwvw0ZuRv8i0fe000PNn3tlLb3pbup9+SutxeXvikz2kcfEKSdmnVj/9lR/rfUsdy58fvXV9fr7u7uxd2NvmPeHHefGy4gJR05nwljOVTfdNOnOu28ep+kzBGDyjjkWuefmFS6GWurq7W7e3tC1v1iZo/KMuTTP0+WOT688k0d/s5cU2LLBwr78OJ4yYZaZOyNb3f39+v+/v79d133627u7v13Xffrfv7+xdPRJ5yNPLKkzAJ1yZf5AkFXXNKCziJn+SvLR9ptMuV/LOXS7tUU18tf5xkS3pMvOizTjE4fjuWEOsdCx2LLqFLdO6Y5TmFP2tgp5N2eqjh2Elcb/U9Tq71+uFFnt/q5xn0lTRRTTymncpd7tHIx2HKAxgH2jyHC+FNX+Qh5Uj83OZhp3Q8UW2J5BRMm0GnZJ1t7xK+NDg7ZXkb4ltOz90wBpfEtw+i787RiEktWKSg0AYzTQLoCIncaFlf1IJSmhQkuVKZlDhNyW6jBF5sX+Pq5T0JnNpofeo9Aa3rZkoEEqUAmAAjyT/tCJ8GcK8zjQ3tLPU5JbondtPqURbXz26xiN9dPj6t2O87P8k/GoATc1pbnlRPmOWJ8IcPH14FUU9CPTlxuZ6eXh5Tdb4TRu5sx5+Q2mhKQP27L3BxMue/PXz//v3zoo0/SMcnIJoY6t3tMU2mkt6ddy+vo7ja7dOExIOwdPP+/fv1+Pj4/FTa9FCmNIGWPiTPlBw6vyrr/7+b5NC1lhASz9Za6+bm5vma2vMJkvNLDHBi4iddJF2LT7cFyXh/f/8c53z3mAl5wmbKnBYJkz0kvXHhou2oNh+aYo3rQDL5IqXkdXvXpFQTVO2mOt/EImJ44zldTz7T8CDlUxrD9k8C7KcdGTyJsd5Owtwks+cKLeanPpLsOyx0/bT67Z549SfRu6wp1k1tntKujST3SX7l71MZ78f7o036+6V9yNaINZSvPWDvBLsbXqf3JHvLT9gP+aVeyA/bSHK12KH3lJslbD2h44lqUoY7A5NWF4TttAEhePrgTADhPLFMSsTWer2r4DxQRg4G+VZ7LdmjDKk/tj0lUdM75SY5eDW5PfFq+qOedv0zsfSEp9kWaQdWa73eNdHnS1dz3N6S01LvJwCY2ufEwftsQJP8ZLKDBlzJrpREcBLHIJ0CLnlpsrNOktUTFBFX6RsYth1Bl0cycHKdfsdGPpPuTpINH2vf5acOXA7/faZ+v+h1fOIj8h3+tPBA3VwSOLxseoIy8SUFMekgfW5jw+BKPEkPhXF9TxNVtuvt86gvyzebVF0lvBoTJTvp96ver/Pa4orz4j7j4+Bt+HeeLGGCoWvpZwbcofQJOJ8QrTb9RE06gXKKf963ZOZENWFy0iGTzlQuYYnf891V11WKYSnu+j3GVl888/GQrHowku+c6jeqvghAPqQz2Sgp2RnbmE7weDvs33VKm2+5xVovj+YzDjMWTZTkSuPEUwnsL+mltZXwv8VP6mAnn+45tiT9eBxI+thda/023tyGm22wr12ecsrXhOutz1RX912fwjdhO3WbYl2ztdRX0mfK6VLcSLjpn9NOKuuT30SOf8KkhN9tDvFD6Acd/fUOG+g0EElAlbbLJ4Umftb6stKfgJFK8oDnA5iOrCQ+HISTcbZ65NvBJZVJCVYiH4800RQP3D3iTjKvp6Dfdm09mHpZyuZ8pIRqRy2opTJp3BPfSQfpPiklTmvlcUgrtPruiZuOpV1dvdwlYRLEgJTk9n59tT+BCP02+Qd1zHG9lNiXt+O+oQTNx4KnGFSHk8DUj/TMQO7kY9mCKHWfrqfFCD9C5IDPsb65uXk+YqhdPfoXx80nD/os/U1JkiglM003KQjRplLyRWISJf7v7u6ecf3Tp0+vbNfb5K6x86qdQeeP497wV37I3S3fWU0P0tGYKqnhxM77px0m39rZWirvMvsYkV99dtziTw4S9jMhJV4kW6P/tfKMxb6DucN/3WuJp4+TrrvcvlPKGNJ4bTqa+CQu+X/3cnLh/q2Ht/hJguYDKX4lvaT3Rm33NLVH+3LsS9jI/hnLRLs8M9GUP6ZyyecoF+VNvHFsJiym7Kd8J+ybdJTaSZ8vmVyc6oov59V1k3K3hJHMf7y9JK9eDfO9XOK52SH7Se8TtRja7CLll863Y4jaIj6lGO59u5ysl/r1vIT1dH2HH6SLJ6oJQCYis23QWjLjgzQFpWRQacKWACQFdfLYgl7jgzo44Z11+Nl5SMlgcv5keDSmKXGlXpLTUJZm+NTHqV6SDZ0GJu+vlW+LEt4nP7suWv/sty0KJH34WIlHBxzaJm0kJWA+sWNCrbp+rG8KqBOxTd5Let0lnA60jgeUIfXl/aWEugEw20n9NBzheNB30ysBvsvP3aLGo8p4sNA9TsjbOEyYkDCIizA+Vk0vExFn3O65cMBY4TThIeuTPx87T6hdVv2OUhMbrbanPjnG6oM77bzmCVobG+rYX0kH6XOLB0mXlG2Kp43fNKlqO9/pRbxM/tnin9sT8wXfIU1Pmm6xa8LlNElx/PHJu+oyMVc7/jvbtDtPfhMOXkqn9ZJtuV6Zk9F/yS/b3PE4jT+vn2BQq9MwhT7ARYYkY+OjlW1Ylmxy58+NJsyceCbfxBf/zGtpAspnn7R4cspbs6WpnSSD42qyk7RRxDZ5P9kvy6aYove0+OZPMl8rL0J7281/Jj9q8UQyMSeY2mv0R+2okkEmZwzyqZ3EdAu4uzYIjP7d22tHlCbyJF9t8Rr5SPKQ76SHndzJSJkE+XXKoT48WJ86fOK7yZ3aO9H1CZg0h56CRgJQ17nrgvacAgB5STz53zewXuKztZ8mqOSt8SQQ0xFE3y3xNt0v+NAFBhjvfwJXTpYmct1ThgSwp76W7rVyHkDZ3xR8lHhzMYKypFXPtBPjYyLy3WUeAWZ7enebbwsl1AM/Nxwg5u5sk30xNnAVVvYgHxLm8sE+U3BlDPCyCf/4nnSmOvqLGf2W1pNx1wljEWOmxyUupKRrXodteFstqdaE2vW+1pekUHrhbj3H3uMsdZRoinPpO8eD8dr9zcc4ycb2/InNXj/tlPMBSeqj5SnEg6enpxc78mmMWxvsw9s5iWtJdtoHy7R8YLqefI4+wN35xt90bdK589/ykBYv2Lb3kWjiyxcPGD+TH6VxTnwznqRcp/HnPPAz5bjEjhJ5HJpy0oSHxDv9Jr3x6f2lONBiw0RpvsLc0BdcRG13U/ymtj0f9zyv9c+2nRdef3p6enHaQtTwPPWbFs+b3TG2JnxSm9PmUKIfNFGdgpEYcXJnnJhjANdn301JZfVKR7CcFwb/ZJByEE+MJkegLibn9rbbwHu/KYlMiW4DIPXHhNa/e9vsjzymXbh0zEn3UzDnsY6Jd+qO91LymQICExzqgXaVErQUDL2/5LwpkJ7QpBcn8pSuuw6urq5iQu3+ySNkTUZ+vgR0qCvXefOxKTgmuzlJMk58yMv7okMb78YXfYm4kvw2+SETvjTJ9WOmOzt0f/FA7HKz/IRfqTxldF78muNPGo808WuY0bDV7d0nvK7r5lP+mYmpcNYxKf0liccnyeS64NEo/8wdON33/8ZMuOV9ux3RfvQ5Ha+VjC0eUC+u77RozLFoNse++dtrJ5eD1DCEfkVdiD/9BIN9Od++28ldz0+fPr04rksfbztvlKEdb3e+WD8tEKVy1Ak/6zvLTZhAn3V+vL1kt5S9EeMU9ZNiCuufxusJ71jfJ13kk220BUP6S+LfeduNJ/mdyvI92VRqr9kMx/rq6uXEjLkHxyFhMPFjrdd5IXlpbU5ELONka7J376uNUeIv5QwJtxO2OvE0xx9zSm63U5zusZ21LtvAWOvChym5UbSEJxkFV8onSkJOO5e670lAW+l1ANklsuqvOe0l/LN/fU87KP65TaRooMn5+L05gOuW7TBYMSn2z+ST36cVFvaX2mmB2+vSRhrRFttuZQP3VI76m8ZjCjRr5Qn4JMfufrI7HlFMQdbHw4NJshPqr+lhGvMJxJssE2BeAoTOT7O/hH/ky1/0n5TIJb05RvmKvF78q6KUCLYkqcl8oscJC090TR+lHolRpIQ/ky8lPdNX5QuNp0k+xhFO5Hzyyng0BX1iie/+uX243tT3NIFLE7G0Yp52A1KbXP1nOSZ1jDUcv+QL9Ln0cmqT1PSebCPtAiV/Jr/Oj09S9bq7u3v+j9OUiLfP6ieNe9MZZW+6an05pbyEOnPdkaeGb2wz8bnzP/bTiDkHxz/ZVNtVS5/buLFtv9Zsp/E9ydvGlrw2HU2xfJeDpDZ27ezk3cnDOlPcmORotkbatdmws9VrciZcShjqP0do8U3k+Vp6IvQPyZGSXlJs39mQj9uOLpqoMnDoelKsl3OGdpNETs6mcrtA47zzOCN3LCa5J2pOQvBKR7b8iJW3lRzB+2vGcInRuZ4b0KZEwes776mttfJ/1J7wmdpxurr68ih2T4CYPPn9tLK81pcjb9yFb4EyAaz7g+viEsd1ntNn9uly0Q6lC+rPfZLAlmyP1I5CrpX/KNvfk352icl0LC7xkPTd7C1hmv+t0am9pnKqz5VD9ke+HS/SSYC11vOu+NXVl10t/0uMpKdJP2t9wQNOkNvYuf/R1khT36f2QludTrqwfIoT3r5P8nzHrvFE3rye46LvnsoW/HeF4oXHSsVre/CZ+nT88mNytEO1wQSnxY8ks9tj+nsDt1vK4X37SQ5/YBHjiRYQ1B93KHkyR3VcZueLMUj3Uu7gOYTrgotGTAL19F2flHKiKv59PFveQP4TufzpXrPb5mM+bsynHGN8nE7jWpOHeJViDPmi7SYfSv1NelxrflCP+vLFrSY782C223CGcnpu4v2kvOgkr/I2Gu/TeDabSjnAVP9k13St10+WT7GNdYnFGoPmW+I/5V0tTrn/ezlvL/lmykmIB4wdu1jvbVP3Nzc3z7HHf9ZFnbU433yTsZj8+8kW1/+l8wDRD/p7Ggdwv+afGXREzUBbHzsg8P48CLPdSSns19sU0ZhSXV6bHNr1c0LJ6R0spyTDdZmclP38kKD4903kw78ncEiOm757PRLBv7V1SfBnmRYkEki27wQPBwJPvlSWx8oSP95XC8BN/mZ7O33xvSUvvD/Z8JQ87HhJtAPTnY+ncg3XOI7puic+TJh2vpmSTOfJA1rCFOeFiyMTnjOAqh9vb9Indca2qUf2+cfS5NuOrUpetDjRbDgFe29vrS8TNe5CpnpuB8l2FGtO/9+zJSi7I+UpEVH/fIru9fX1898trfXlKcTijf3pyGz6H1rHOk54yXvLWxgfueDp455k9r9H4vvj4+O6u7uLPNAnXaZkQ4lSktzuNXzRO5Pi3e57ssldzE2+lBYeEuZ7Pb+WJv8tf0i8sd60YJcmKCTK5TxPcbFRitU7u3Bq2DGNW8otaJ9sp+UPLrOPNRfQG9/peuJpqpdiGvE78T75k4hxuMkjct45Ns3XvG76zPabPqZTJ/454Tv5bDjw9PTy52P0p4n3RD/4N6pTgkFFc1IpwKZS2FZS9KScNKCTonfAlQBzomZMbHeSg3V39xO4sE/qOCUWXu+SCXRqm/2Td/LEe37/BHx4nav6J+PXgmNKhrzOSSLhZf07dyCTLN6395+SJfLgu3nTZJV1vN8UHFM914WXnfw7tevfd7t6fE9JvXhTmSmZSjaXqLU3BbjEc2qz8ZF4ko50L+28sV5b8fYEbcLGNjGexkjtu817P01P/n3iiX0kuae2k7/zfvNx542JyiSD6zEd75Y9U5a0kyXe+IAgryPduw4mLOGupSZj/iAf/taSn92ONVH1hxM9Pj6um5ubV2Ol7+LBj9Dqd7i+K+B69AmveHB+Xe6E+b5A4OPmY+e74npYiT/kiLu/zgNl1LgQd91upviS4ijbSGPddr714u5NS0wpS6MJE5sNrfX6L0mcHPsm/2t692teT+Olvk93oEgpFra4uYs5rf0kW6Mp52ztJozwtrxt5jNeX595wo59NduiHCdyU1ZideI95WRJDn5X3TaWE4/+vovPa+X8tvmml0m87OJkmmCyL8YpLmhOC4W7mC76QRNVp6QgMafV08bQzumnJMbvcWdA780hxLeCEtt3ozgBJOeh7RT4fTpFIpcvOU1KsNJqRTOMBEbeh9OUmCbnSc4y1XVZ6XSJ9xNq8iV5dmB9Qg0g0oKMB0Tn4ZJg5fXoJxxjB5OdjZzYpb83/052xntev8lIf3S5066ey3gCyDtKtpJkOw2ezrvXS/j09PT6YRot0VNyRV4dI4URaULPhJD8UKfOm/fVdvaYJHBMKRcXy1oyc+o3zddT4pQW73aUJpWpPd+xIrWEwOswdvjubTv1046oeZ0kr8Yz2QMTGd9lTcmN7M6Psz09fXmKrU9k2bd2JjX5I99JV9xR9YSJWEL9+uSMckrWtMPLiXvbPUg2kuy7JapscxdvvSxl9/Kuu3akN/HAPIy449fouwl30i5kWhTxl9qhH1KH/qIvum/4E5ppM7vxa68JqyasSbqTrMwlmh2wfsrB0nvjI/WR5G/XmHd7+62v1F7DyzTxTPaj9rixRrncTpMvqp2WjyW/Sz7i/fnYcoG44bmu0YfaAiLf6a8eX0TUrfxH/TAWTH/NdUp/1ESVipsSqfS9JR+pj0RuGDSOFmDVpn8mH80YUz9sz7+nZIyrlY28nynJoAG1hMI/N3204JZ44/cGbDvajQ3vTca9M3yC4Gkbk72wXVI6Xjl9T22cOHTjkQlXArYEQs2XE9+JTm0n8ZyuJ15aMPj7IMeknT74OfFHauPF+lPwm8qnz6K0m+mYkpLBqU8GzlYnYVr63Ox10tXkV94uiXJO8iZqiUPiJe0ATWXZviZ7nozxmHHiYUpskqxMUHivtdP4IG4ocfEdR/3VT9op1q4l/94ljU+aqPorTTpcv4rL9DVOdtPfxJzkHJMNJkr++0OwbsIS8sX2mQ+5PaUYuIuzfj/tQvlJINqoxoljeYJRDRPow83mm0zJ/snjD81d1NfJKTfy1ibtE37u7HCy47XyMw7SYhj12+xml0OmxVI+VLWdsHC+dvI1/0lxeeI51T2J7c4H5fUyDYsSLjV5JvknudZaMX9wvnwMkqyN/qj/Ud39fiEZK5n2NqcjMKkehXZlchLXDNF3Gnb16GQ0GncMgp47Ef8HkW15naaLtEpMoGyr5QQElU0TXZeXCW4DPrcP3m+G6TqdnD3ZxPQ9BSIv62Pfgnfa3UlHp3Z9teNLpzI4Tzsw38k8JQItmWL9xGfjh2X4eQrmkz4nXHF+JtnY7tPT05gYEAum1cGULJwkO35d9dIqdOLN/Y8rwc1+0s6i98/xP0mcdrpJ+kifU9/JHqdjZezPeWz3KXvj33cCk515fX8QltcXpR1KL+djq/fkv+SB9XXNZZ520fz4lu8g+gM6VI47UUl/j4/f/2XLWmt9/PjxRXz0uJT6njCIY0hyfbruvQ59Nv1vacMZ6m4Xdzy2eu6QxpDxnjIlOU+JuvQHFVKOhNsaOx5NJ59sYzeePk7Jz5udpX6dH//sC0DsNx19dvm8jvMlH3h4eHilY+ZlO7kdj1KuwOvTib2Gj5MfqS3m++SBfx01LSh4+/o8neRSmTaWxERhsk51qrzGhDhFHfHz5E/kg/pxHaW6jBktR/K2OX9wDOYOJnVIubwPn0sx9noZ8us2kPDN5XX7P6U/+uivM+CfCWYngaUFUW+fCUq7N7Wfkh+W93p+rbXHPwkn3yIGo1SGfTulBK29vK12lC7JPOnE+07BvelK9a6uXv4XnvOi5CS10/hIY5W+e10mGJPDtISBQdjvpTbdcdMxEy+XbDsFrsTDpLMWyBkA6CMnyaHbxAnwnvjzCaVA3O5Tl6dl0vinBGkKwu2a6k16c3Bv/aRJhpfj6rHKJTuddKr7vrgznRpowc7vJayiLqg/8pbwL03sk3yTrSb7ZEKSknny12zJy3ESyD6nxQbnucnUjmEmeZLu0w4uJwtr5f/ta5MKYorbVRtb11nCSY6xT56oq+T7bXKR7Di1zTEn+c46ryfaxcFdLOLnRo2n1j7rKbZ5jPMJK+MKY8wJn44P/j1N/tKOmeq4L6VTRD7WaWFpwlAv9/79lxSbmwf+PmECdZz6muIZ48gUt1Kbmhilnx64zt+9e/c8+bu6unpe4JHsLbZIh+4XzXe8HsdoymESHiXdOz9JN+mYLm2RMdHLNMxynTvWtp97eP9Jrt0CMXlyarbI+64LydX+IzrFz0voeKKalEkBGhE01E4yXPZJZ/DPk6M1nlt/SYmsrz65unR1dbVubm7W+/fvnyesyVH0noz8NGEkEE/XkuwMDJQzGWTSk1NKbFLfcqQGBExE/H4bu5RssfzOEXdOQ/25LSQ7bGDHRMSPgbv8Kdg6eBEE21j6tSlp4Zg3e9gB4GQ7ia+kt0bJbwj06Rr7SrbKxCfxncYy4Rop2WPTxZRsUL7WB2XWNZ/4pLadx5TQk4+dD7PdNl7kw5NO6kO2nybtu/dJ5vQ+yUN9TfVOsMZ9fffgnwkDeb/JxoSI+Nn+xibF0KQfT1okU/pNp2JBSmoo2yl+NaxP/KcxnRL5xNdJbsE2fDLXcKXJMu2Kn+jD/YzU+J/aY10uxvrPmzwPaPicfIZ9MB57TsEYxXH09ps/sL82CSL/KQ4nPZ/Eu7Xyk4yTTnb4T/mTbbM+deOTVbdD8uvH+d3PiNtNH8yzKIt/38Udb9sXANOOctOfU7MTjnuyD/eP1Afb9t/LU+euV54umMaYtn1qC+TT6zsvzkfCsaTPnQ+IfvBTfymMFOlb7V5+d3RHYMPdJh4f5cCu9fo/QRMYOR/sdwpAbTWWcvPR/1x1cwfhFj2TOIKE8+8vJsuuH6+fjol5XTfaNtaNPCHhuKXjNO3Y3q7vloA4GLeEJgXBBiS0qZTY0EEbcRx5jCjpxz8/Pj6+eNCDg93k5FPS5HVSQsZdG11PQSG1qf7ph0k+8uW7NYlntdeOLjU7os7pmwm02X96sQ+ndowp2V8ql4JKkzvhwMR7StCSnZPH5jONWtCkXZyQ6unY0Y6HxGvDxrXyiRDxOfma46nXcfJE13nxhF3f+VTbxDM/k2+/7jYz2aP4ZLzgg2Z4X5/T5Fb8Pz09vXoqbjqC5zGRiY505uPksSTJw5i6w8Tm/942cS8tqrBdfp4wYIpRJyQ526RA+uMEkm1McZTX/bvb2tXV1fPuNPO6NB7sJ+mn5UPcUSU1fVDuFiv0LvtlzGj4m+wxycgcLumcdvxD7SP9N6nfb5gjGadjrdLT7e3t888cNElNi9wtXifanThwDNVYuUxtjNb64g8pbk+5Ke1N9u56bHbc/MrbJb6IvzRBTfpgvkd9THjnlHZPkz37cWrydUl/pIt3VP1zAyo6koSbwInfJyf8IQ7q/E0Jrd5bEteCgBuWgq3X45Z8S3wn/Xk7O1lcJvLvgb85lPOSgIxjudMZeeIRMu/T9Ul+qA+/no6Nsc2kn3atJYINFFwPqZ1kX40mcNTnXfLT5JroFEhaEjbRrv8piCVbvKSfZpvsaxc0WgKxk4W8NFs+Idpcwg7yPo0Xk+QfEkzot8lWd7rbxZidTtPnVnbCqFMdNIxhW774o9fT08tJl+soLSARd5MNpbFnW5foxSeqriNf4efRNN1f6/VE0o+zKeFV0u87cWlBm/pO313+Se7kNxyD1MclmDfpPI0VacqTUp6V4jv5uCRGNExL+cIuVtN2mT80PGs5C/Uw2UjLBfiZfMl2/bjupJekw10ZzyU9H0rYl74nOXd2w/7T9ela0jn50HvbsLg0dzjN21TOF/IT74n8dAfxdeqXNpwWTIjjSfcpL3GenSe2ncaKG3yT3nbU/LSdbNrZyA/h5Xii2nYUnRkFHgWctHPRkqJdktTAyvlo/Ok9zfC9fQbptvKX+tAqDttogDABUjo/30A5GWnTOds5peScaeWJq49Jb1dXV8//95d20NzRtbuwA2x/QAmDW6rbQP0SSrpPY+/3prbW6k+qpp+kdybA/C2F3+OuaUsAvP5OB5NfSxdTm02uds1145SOrfquUDulQXxIgDslLP69yZr8pumX9rnz12QP6TvLtiSRPJ/0OemONk353G8a8SQB8Y586512mvA5jWfzwSa/f2bS4yvhxIqkszTRaviefE7vvrpNXneUcNzl8d+t3d7ePp+o0l/N6F0+qDqSS7useqovdwnSwlDix9/Vtv+/KWU/wRjGWZbz75NtNJqwsCWGKZ5dXV29+BvAVC8RE/JLYuEuB5twmv7n9xK1kynTWHrdp6en54WRyQd4zRdOlNvx1EXCkMar69h9wCfEtLnp5BDjrXhKpwz4nXK0v8riu/OkhSbKrXc/qfL+/fvn8s3nmo03/Jv0LJ0Q+ye75HF09uvjzbmB8+P6mZ5QTuxXXeZu3qfy3PZvIX5yx8uk/pPNcVGm6Zebbkn/afeccl+COT9oR1VM+bszxmO8fn9nOJzseH9JCVMylwL9TkkT4LQ+1lovjqSpfvutKl/sP/FHYKIzNl7b5HwKYieGlPTE781gd8DhzrazmRQAyc8EEmmsvS8mggk4fSfhNHh5Xw6uDKjSIfuc5J90ouDYduanY6RMMHYA3OT1zye4kMZnB3IEefK+1mvMSgEzyZh4THbhfHif031da/362O58udmft727N+HEpJdmF0ysdrbKthru0SZabEn9NhnakSqWPbF3f1JiS+pUPtmgy0tf59HinV+R52RLV1dfjs5RZ0qa/MmwSub1pE3utiYbZxwXLnkdjqOPYZrocGJOrJrs2SmNQSKOi19nucnWU1kfzxQLUrvOe5KF8az1mXhL7Z/mMPTNnU714lH/lMukvoiTPDJJf2l88mdNjCsNz2g/qR/viyfMGKdbHtXGPuFI0kfCjvbu2Ot25Lm6eGU8JfYnG0x20SZOk+2wTPOzCV9ZLtkvcwrKo+tpgSQtqE87z+ybp1ja+J/qtM2pyEuazLZYy/YmfNzRxb9R3SUu0/HLBqAqr/cGlu6wXF1nG4lPvz+t3E+G3fjydzdQBwMPNjQgTwImQ5n45ZGHFgyY8OgzHbL14985VgyubWVlCjKidDx4N67ky2Wb+J74S9/Jp5I0D2KJl9QPE5D2exX2vwOAlBD5ODuApsCSKCVQqUz6zoCww4dGJ/691pejhpyssq9kY5PtOu0C5g4zTvyutdGSTr+f7G+nf7a1W2XdUbLPZpust8OvXTxq/fKa15mC/EStHPXsduj8tXFJbTPxcLtO/tzqnvbr4+XHdaU7n7T67mlKqDjuDXfScUjfqWkTWiVy/p50yOQ06Zj43LA0+W+KEa6LloO4jjxBnHyd8k1l0phzXJqfnGB2i8NTDG98pj7T55Q3OR+7I7bNvzi+PkGd8CHd38VKjkuK05fE3IlHt6tpjBp2NQxtv09k3pDi3mS/E4/EhkancrJsyqn882mumTCu5XG83+6lhUAubrB/J9rGLiamuNJ0N8XZS+l4ouqPbE8D1cBpIjes6RiWK6hN8qgMX0nVNf5gOg2w6uwAxskD0CSHt+XBz6/zWCb5SUaRAo+X5Y5cc47d53Rkchozr9t02Pjw+uk3B6mN1uaOt5M2JxlUvoHxKY+u52mS1Ow92czUt+9YMyCyDRGTrMkuvS3nq/VBkE+8T32qvPxQRxP9CKJ2g/xY4NNT/hPwH0IJC9POz84H+e623/D1NID4saC0s56Oj7GfE7rEvyZ/S3aR7jV717UWo2iL6XdGO17X2idKiRqvHMeU/LQ4kXaNEgY2vD/hT+S6Ej/+QBG+OGHbyaHvk+zuI+7P3FVNJ0F2O2z8nvQ22bnjTlo0Yx/NDzz+pXyg/V6M+mnEmO7yXUIcm/TgnpRXTTGnydD0R31NtItP+uw4rmv+9yuJT7cr+jTjdsJD95OU/3p9PvRsrZcTlsnOpxNbSV+ql3a7va/JV/0zxyrZCG1+yhPaPfbtbU8nyKRfHWPWmGhjwvFKr/S/y9RjsgEv5zlMwsuE6XrxP2InXiYdenu7+lN7jc9TuujobzKAZohTIrID9DQQNGoSwYlJSRvoFhjc+BrI+DuDkLfDNp2v5JBJzp1zJhmmepP8iSawYTtMXlhnCvZeRi8eT9nxyXfqeZdo7PhpfabgRhBuevQdAE+ofPWWvCT78TYdSHlvR8nfyLd4mHbckh5TGSYYfq/Jn/rwnRz9VZR+N6d+BOBqW59TYuxBrPnRRDtcJDWfOcHYhiXkhxOqdOyn4azfa9jZ+J2I7aXEs5WdeEi8p88pkCc9NpknnaR+JzzYBfDEY5Ih4dHU5hSjG45PvPo4cJHz6urlCRRv+yQpbfyko5K0afn6TndNvmaPSceXJGOpn0vKNb/f+cGEFxO1vIi8NbtqtnRpEptk4ffJv70N+mAb0xP+PE4nPHWb8bwx+d7uXsvnWt6QZGW7O9la+61vLoAybrd+VIeLyqmPJE/KK0gTflP/abFp53PpO+c8nuvpmnIY73OyFfI8LTon/pnvTBjYxjq1zz4uxZqLHqbUjGyXlKR7NMw00WMi2X7LI+JupBsVg2Hqx5NiHhWhPHxp18YDsu/Y6FrSi8ujvnfJfwqUacez/c5qN2as034bpJdW9Fxu523XfpIp7Z4nvU36SaA86SP9rir9ZULqbxpnjg/tL9ki7fH0d97OtwObv5Kt+FilI1LJXvSbsh1PjUcflylY7HY6JdO7d+/Wzc3Niwmq/uNYepAu9ZANPaTg8fFx3d3dxeQijX1KDCZZG/+6NiUj/Nx+IpD6Sb7m91p/U3BPvE5tOR+N75ZAMqCmPnZJyCmRh5b4tv5bYu42lfDuEnnUXkvSdgmE30u6dRub6raf+RBr3a+9jrAj2bLj3C5uUu6GWQ1jErae4tkuCU5x57RdltmVb/6TPk/98H6y14bVrgt+TmNB/qefCrW47jqmXGy/yepxMtXhtYbpbbynvMEXqRn/9V3xKem77dJ7nSk/oXwn+LNrx3OXKf4k/tvCFf/W0f2Wv013HqccifkR77Os8+j4mGSaYv1aL5+CzrmD2lAuw7w0YZXLyhyv5S/+7rvBeifPp323XOaH0sVP/U3g5NTup8FO92kABCiVTb+v+2P58rL+ORmAeEq/x1F5XfMg2ICYEwMdyySv1EMK8C1xaMdMkq7SNZdNbXBVXHK78TewSA7g1/1oKmVuMrQgrXuc8CTwIWh4vWQv5GdKWgjCCTCdV39ynI6ttn5aEDgZc7Yz+UsLoMm2Xc9e/yRoNtlSkiJZ3717t25vb58nrJqs+kKSBzR/6uhar//c3e2d+tBYtkUl2s3JGJzgkeNfOlbM7x402S59N/U1+VQaz5bgsd0T2uG2f9/ZUrPFtdYLfe4WRZLttsSGtpT4TNdOyqT7jh8TTfjpbdBeUmLSZHY9Jd/1NpMdN6z1eol/L5tigGO642vzY+r2EixNfPrOSGqP9tVkUtt+BPMET0/9ZLKFqW7CzYZ/DU+mHIbXmm/sEvPUZ9oMIbaxborp9JPpeC39ZfI5lyu12/STFqabTKRdrG54Sr59ou36dgxgzuK64LF+/nxnR26T3t/V1cuNJs8Fk80+PT29+CmkE//3vtmWX9dpr/fvv0zH2o6q6krm9s8YPPbb/p/a9UJ508af5wxsz/Xj5V3m9PmEfvBTf1tHiRlXgJTNXRgaZuovOZsGrYEh+yDgtoSQ3xNQuwFyQuAA77L6gyhSn+33UUm2BGg745iCRiO2lwJQ6scT5B3IndybQCzx2saTY0lw4oTRZUrBJPE5AedpEkn9toDmunAw9N9kp/ZPeE280cZ9cucyniYKU2LmddPOMPnwhSN/cWyvrl7+TVKzY5eLE77TcU82k6j50w6XvH5qc+qbsqUV6Wbru7b/PunERqV/95PJZ3c+zH6ncUjX045kwujWdvOf9t3bb/ydJAup35R0p/i9s3WOzVov//+abZ3YWJOz+RET6EQ/xJcmou5OsJB4OOVGp3aV+jnhfYdt5IWfPWdgecp0ie5PbTiVZ5vT+NKvUoxmG2m8J54T381m/bNPANOua5LNcXI6ved8nMaadL3Z284Xkw8nm+I4pJyV7XpOwLyBeWD6SUHCP0621abyjWQ3un5zc/OCN9b3eOKbF0l/XCjwRTlunHEcTvNT/5x8Y6p7KYYeT1STw/l3DtBaX3bbWgLmg9+CKw2BidXT09PzSkQCQv89mu96JlkSJXBoAZQ7cvwvI72nBx/40QWVmVb2005lM7aU4P+xyWVLAlwPT09Pz5OBtAKVgM/1xL9H0HtaYUptpxd3rsWvf2YbPi4i8dYCVSI9fGGXQHLc6QM3NzevgFYyuM05X+1hQQSs1G8jTyjdjp1SMEn97IKVj7n7u+tsGgvHmfT7NZXhDkvDH+e9/Q/dbpxpc46XLpf3164zAJIYdJ0HHhHyEyqnMrDtk0kA+ZyS6lQ2XaPtpnFO/u5+oCPhTQfNXml7PHaXriXZd/5Hf/Kd/YRVySaInU1vbeGU5Hrmbr+3ozI6HeK5ApPD9IAY9cUHueg6kz/K5w8FcX68vyQXdxd2RL/Su2MtF7dpV0zI1S7tLMW0yYZajuW64OddLPBybVya3ptt0mYm3U++4vUTjqcY2Pra5U9N1rY757wnvJmOpHvd9PeI7uO7+Ou6SPdaOae0iyo+ks44BvoJjvPMnxcol1Qu5fmU+tmNo+dRPjkVbvgzLihbGg/vh5se/lOkhHE+Vp7XTfHc+XAeWYa69f+t1nfeS/kPcyGndPow8UH98P6OLvp7mub0YoD3vJ4bawMsMT45SePHr6XvfDkwcVAd9Bm8mCA055949GO93peOnZGPNIlwPaZFhHQEpPFIY2qAksapreCREj8NdBNfuwCReG7jyqBO2yXfAjEfm1NnY+KQ5PZyKVFg0HEg9Ymq+GVfGiMCTrIfAtOUAHiStNaKwDb5eXpnWZ+AexAgManVCqJ40Rj6tbu7u/Xw8LA+ffq07u7ungE7BdwkQ9IHKdm028SEqZKfmDjZntsnbSr5OZM2YvSJrbqv8RRFw5Zk55O97Yi42O6v9fKYbys7vZps5MMD+IQxTW6XhXpLi3SMS35d/aSEiv7bJqfJl1NCtYs3zovbHPmc7M5jaNu1ol2lMTwh+lyTn/Ke2AvtIcV68nJKlLPhgWNsshuVTXZxiS5P8oTTHCaV5ThNOHXCQ/KbVGbHm9t56y/husfR3QJgiyP0d2/faRfn6JNt3CdfJ3/+3cumiabrwncGW57BsW446aeumFv4bzTbRNXbnuxtwh3PzdyOieXpt7mpzWaPjEcppmgOwmPVKQ5Mdr+z+bXmv70jXXT0l0bfDC45S3OUpIRLgkkCEPbLWf9aLxPZlow53+3seQNtJowN0Gig6ZUmF25QkqcFoqbbxE8b26RzgUaTLemT9Zv+U90Gnq0flZn6Sm1zXK+url44LoltehK5G4MmC33JdxM1Qb29vX2xc0+9+o/iJUNKTNW+25rrIK1sO09MtNqq4+TbKZDQ/9yPnZrd39/fP7fDp/4+PT2tT58+rYeHh/Xx48fnFUWtMk6JQQv+tHHqjos67TPbmvw2YYQTVztdp7R9L+Ptph3o3cq35KVfNCzR5+Rfye/9PbXT/E58pXrUZUpMJqyijprOWr0k84QJqX7qY4ptKS7q+24s0uQ76ZPj4ePX4mPajfYEy3WcJimJTmL1pDfqoPHufsM+vA2XZ+qTY0p+/TN9OfHt/T89fXmWhnZ0Wlvp6GDKgaYx2WFeut4o6a3FEeet+XDyL8rH8ie5T+J3ItclJ6qtTcd28kaf4WLIzlbYj2h32sL916+lvCHxQT0wX28xL20u8bMv1PlE1WVjX21yyE0474Nt6LrrR+VdPmLL1dXVixyFsnOxLsUc51O54NXV1YuHSUrP6eQJyeUnBiV7Yb1d+04X/4+qM+HHa7hCm0BC5AqhE6ZAon6dJqdnQGu8OAgRVJNc3g4VzMRWMvqO3AkQJznJt3TmvDAhbQ5PPe14mZy8JUzJ+NoEj3yk8Ur3Utmm4ynhanVTMqW2TpL3JudEU7B1cL/Uprwdl8eB1O3VfdIDQrKfZmsEa5Z3YExJXAqySUb3BcqrI5xrfT9ppTw6AqN3BsOkw0m3Ln9KiiY7ZbnUR5uEeMLoPOgzcY423RIGjslafSErTYh1j/i+s9VLaRcYed314bbD4N/aSvhPPho+trElNSyZ+p/Ke5ssxzHfJRD0T8cmYiXxY/KPxB99xuPe5A/ermM2MYexgf1yzJqeaIOnCRhzkdPy3k86GaAxabjqMvnv8xJNuyrUs9eZcDvJT9rF9SRbwqwpR0lYudb8n7vTBK193+Fe4yvZJ3HX/YEP5KEu+FnldvaseK2yftS45XYpJiecTphAm+PCT6JkA4kXnySrr/YzPa/T9MQ5gsqmo77SXYutKqvNCM/zfN40nfrSeGnMiEtex3eSOVHV9YeHh+f+Gdupz5OcYsKtRn8vD1Pi5/Zi+QbODGj+vut/x8+OhxNZEq8N+HxQvE32neqRJwdPOl5K1k/IeWgBIenEed3120CJfCQeUtutjR1xnDwRmexw4nW6Po3ppYkMQVzAwb7Xev1/Y1wJT0Rdc5WMAbrJ0RIjJmQKet52srN2xHGHD64Hl93ffXLaJs1JT4mfH0oJO3gEqPWTkrzJnlOfuwSQZXbJo9chH83Hfqj+yFeS3a83Xnftsy1iR+KFdAlWpbY4Xqm9nW1y9zS10/hPZVKSluKD3h1DSAkfk469v+kkUtoV94lqk53ycQyEuzucUDs/BOenNpoPpb5Zn+MmaidV1Db1ecrrFMt5nZOq3Vh4/8lPGk25i7fj+Os5HOPUJXH9dJyYo/jn5Hv+vU1OJ300/G5lPV5LLzu9U5e7sumVeLvEBnjf8Ui6nPIJ5jPStU/2OFlNGLLWy0VRl0F1pF+fqLovMp+jDXKC3OyLeuWJOy7OMOdsLyfisl8/jcfHE9WvvvrqhZAEEg4Wjxsk4+Jxw6enlw/daQPhNDlsAjuvcwowbmQp8Pr7Wl/OtrPvKaCzH8rHo4/+Y3Lpys/UTwGtyT0Zm5f3Bwk1vlO/SdaU6KTjaAm0moMw8NHGKK+fFqA8KUi35C7pjODCepNdX11dPa9s6XjGu3fvXnxOJwc48UqTsOSXqX8GIm9jOo7UxtJ934Md9Ud/Ia+7oMIJqI7L+I5p21nxtlvfO19heVJKflwPukYcTXSCXXpvftDk4r1JtpMkbZdEpOspoWzvKXFRv0me1K5+/5hwbcJOXUsBmMnnyXju8MSJcvFoXWqfxOS8nURJsTbht48d9ZKSNFLDyzTeLYlTvGr21+w86Y9+w/G/JPFSfdpoi5XtHuvt4jfj7Vovj0oykVROxl3Epkf2s8OQhG/NL3dYJP6m91R2ajvJyZg2xXG2n/Ap2UCztZ3f+f/ZN7mdp4Yx6bNTi+tJBs8XPKdo9pHi4i628H76Tuxynd7d3dX2Xbf66zv+rnW3YEdeuVBOfqeTKtIlc0rXd9Ktv6sP3vOJsq55PGDur37TzrHrr8Wsnd+Ijieqt7e3LxhjgEkrCdPxJRmi31cdCaXrTK5ScGsTU09Ip+DtlJJyv049JN5EdA4eiZnAynWi1WNfQeaTz1jH+2/8thUS6qHxdkopiBNkk0M2nbPdBHb6zglb42cXMOh8SVesn1a/VL8lJV7fv7sfXF1dvTh+4/rzvlkv+VwKuGlsE88NfJqvuTynyYjKchym3ZEWLJOMbD/Jz7FI9SZ5GrXAkhK4lmz5uKaA7HXFL/WZ5JgwyvumTtzmWvnEU9Jhww3STvfNrhu2uU5S2y3AtgTlEqxs7U5Y5Pw2jE54Rtk8SWn/5U05PV77WKZdOPJ6aQzxtlts4/cJ56e+WJ72O/kQ22jtUw7vb4rhl5CXT+OUdObfmUhPcVDXpolI+v5D/KPlCxoLn+j4vam9dI025La8s2fquNliisfNdvXSQjV5Zd/UTSrTbMCvOU/pdIaXbaevXCZvx+VUvpuOojc883jTThfS3ohTqQ+WF896mq++pzlP0ql8yRfOE04m/+Hmi+vZdU0dUybK5nr3+YXnVyrL2Ot9tdjOPl0/p1h2PFHVf/yslX9E7YL44JHBZBB+r+3e+HcqwetMyVQKCiTvo7287I6S0aRdMOqBjxtPKxZ+tFO8uaMw2U1OTb0l3VBuTnZOiHr4+whWTH5SX/qeVtpFk8xNT+33PKybVr5IO3tc6yX40ufW6hMbH28CW/JJv8dxaUHJ6xC4Uts73bNcGl+OZeuH1+UXrovE944mUE52nur5d/WfgqQnBVOgppzNp6jP1P/OLxMmEmubfaR2mAx4HfI+0S7msG9+bv4+yXBKbSwSj9TBFHekM39PMrQjqyk++bgkXdDHU0LVJqpJrslOk+wpljcsmOzJ25yuNTtg/5e2S6LfEX93trDjxfVHSuM1JfHkWZ9T0p7k4STlRH+tLd6fJqnN5uhH3uakg+R73s+pTaZYm+SUfv0BQFMc5P3JLpu/8TonLCnmpzEQeT7TJqtTTFJbPC3x9PT0ijfn0V+c3Hp/Lc54TG7/z+66U2z2z/43MG2iyoeUtlziJBbRpty+2X47icg8pPGxw6NL47no4omqBw9/SVDfDucf3IphJZk+SLo3BUNPyBwcZKzJkHfAnvhzopHtAOdE8X6szx2LOvWJaKIEPA5iHIMJrKj7iVIyuAvYDQBVN/XPfuhI7Ffg432u9foIebJdUluMcX6dr0YtOSTv6buIPKSguQPKdvx3SgamVcKdLJT5UpAl8PliVHpMe1pFdVvh8Tb5lZ+2mPQy2TfLUX87/6OsTPp0mqIlGElX5Nt5kHxpF3YnY8LDU3siH6zbfGmynZbIeNnEF3W2C/jsJ+kv8co+yV+TOa2oMw4m3hu+74gJpWOntz3VZ+LZJqrNFk6SMa7wJ93tbJD6mnDN63KBi/wlvTeZWj9T3RR/UnvT+PPoHu04tXfql+me/8ZuGjMnT45TX7v6xNE2xtNRxNNciP3S3j1OpSPxSS8eO/RQHb0zrqgv/mWL5JtswWWcdut22Ontpdjl/LC+P7gn8aZTHcRD6tJ9M80HvB7x6fHx8fkhVG53zKX1/enpy08Up5OA5KfNedqYsL20yUBKMcP5cbkZt1Icpc6aXOyj4UWb7O7oeKKaVj1SotLOauuVjp74MeAUjJmUyjBdAS0JdF6cpkHy+umIMmkHwrsEs23fN5kmYn3uxJ0AFx1kKtecdHr3cr7qRiflNfLWEgDqLS0wsF7qx+26gXWSy3mbZHc/2PWhNpOttroTqDT5Hfjddlpy1MbHbXsay0vs+uRFfGo+S4yYKOl7Kjf1RXmaDqi/1M+ED7STVFfvLDf5f8LjhOk7nUz3yCP7572ER07N/3e4mnToNpD0OtnAJbrYxRQmDvrs/U204ze1ceqr7vM/JH5NWOj3T2LBFFNaW17PkzUukquNKfdI7Z3qgtRiyiXjnupO8bHZ4IQtOzzd8ddipiidLkrlOUbt86lfTvmdx1a22XJhb7/9zvHm5mZdX1/HY6ayJU2CNenz3chmn40P6dcnVVN+uiPxPOm5jQPzG+Zj9FHp0eORv3z309tRneS/02Kz9ENdeuz23Mt9jfi08xnytrNbluXusZchHrr8STavn+ZtHLdJzlOsuGiiOh0l9U7T6oeMgwkwVxe4MuS/wXSnYbLg7XpfvhIlasfknFzp3jZBlM6eznC3lakU0BsP5NffvR/xQ4dIoJKcOQV2l8HlpCMnflwOOmpqtzlK4pe6SQ6ZVq9aMpF0k+qeJAbkS/xMlPpz36IPun81YGqnFxKfHlA4+WhBOlHST7IzBYnJR5pMLluy8wkkW1BKeknB8ETupgfnvfXt5bXaLGyceGg+TFlc5ycJB22f9pTsOvnu1M8lQTfVaUF1anMnd8Idl4UJ2KX2MfXn/fp96pFjs/Mltpf4nvS3w1CPGV7H66WF46a75kOJ0jglWRMGthjDa+6D8smWgPK/GR1Ld7bg8k740MYoYZ/bCF9JF34tHaecbCnlA/654ekUq9d6fXIo2Vtrj/Km3GNnC+mEmu8ANyxsP/fyfvh3j3pgj/JYPjzReVCe7P+x2WIjczeOrdrxv2/zCZfKkNJmln/X7ugul0p24z7DY7H0Kf5Fj+u07Q5Kby3fSTbTYrjzebKr3Y4qu00xd6OOeS/pecr9pKumL9e1/q6GfTiPybdP42Sii/+eJgGM/6ZlrfXiyb0teXDl649sPQHyc9yelCa+pEx37HR+3B21JbFsO4F+Kp+OqUpeyr4DY8rW+PR63HlJyUaTIwHzFMzYX3K25DiNf39vwU+fXR8nhp/6djBi2dTeDqTSODp4uv2mwJF4SXL4Z9e5jxEnrdMYTWDi7U6+T2o27bY1AXNrh6craJtp8Sl9Z5JIftKYpOSCfDNYpmTEA+Au0PDe7lTHWvkhQ41/D4JTIHX5+Hkq12ymBcsTH0jtNvyinOx/h71rvX56u94nvOIkrPli4jfx3vSSsEw20o6Js8+GoSlOkqeGDUlPnh84BiTZG4ZSly3xShjT7OpkPLy/lpvseGnxMenP7afZBseb45IoxWPq3HloeHTio03OhA3Ui9tKWnDhDlbCpaQDxnAv4zlFWoD3jQ/vN9km6+p7OgLt5NfYt67L3pgTpvHTLivbv7q6epUj+0PTfML77t27F/+h6ZtGzk/Kj07s0Pk6jRvUu9/XK/0rRdN9sjXW8w0wH/spj/FxSnmN85f0k3zb63BXmOMw4QH9OcUt9csJMnEw4UrLF66url4sMlyCJRdNVCfAcsbaURIXZK3XvxXj7ulO2a7k9roUWMnraVm+N10l+VkuAQ/7oDE08GNZL39CaQzYXwumSebEn5ff6fxkTBxM1soJVwNHyuF9sg6dcZfUpQkWZUq8eH+tf4Epd5BpS62fBIbOJ3W6owRgDtytnWQ3woiks9OAmIg6WCuvkqbFESff9SQInwRb2sME4pNcbD+1lT7vdrO9fdqIPifbbzzThpn8tTa9vyn5YNlkiztqvpbKnfhESg4uwc/WlvOX4kfjpfFAeWi/nrhRr83u2dY0fo5zKfFJ+jjFz1T3hH/Hb19wnE5meNzWZ1LSX1qY5ucpL9rhIWMYv6eFlhYL/X7zg9MYN8Wm1g77aTE11U92fuKjfj/lXT6OV1evnxWyw6rU91qvn9bMNig7+XN+9NJpQ5+oatPI6yv+qi1fNFXennho8u1yQdLk75RfftnaT/qffFif06ST/pN428XJJkPyb7eLtukwtdEwkbw7nylX4aZLs2nykI5kn9LxRPX9+/exA4K4GzmNxxNOJw8AaefJjUX9c8dU5/jdAdX2BOxp0Hxg2tEetqHJUFohJPlRkdRem2S7/iZjacCfgKSBrcqm4wtptTqBegPa5GgJ4HzXNq1qpgmEtzvtvLXkvNkDeXWd+m4/ddzsehfAmeiwfwYLrzuBYfPhXZKREpIJUFO/zp/zQIygfibQnf7zssnejk8lPbSExftpK/I8auT17u/vX/iY3tn25FfJtoWNLJfkarraHZd3ub1f8pQoBXXxR39uY+Gypbbpu9Q/x3vi95TaU8DpM8kGk7xcmNnJuSP20XYDUj1+pg+k+ON1aBPUQZNvt+Ct+p6YJp/bUbNJ54GnvdIiM+XiUU6OQfOtFFPTsUruPtLOknzerk+gqD9i005P5Fe8tP9opZxNPm+rEe2rnVxqfCdf5GkKH4cUP51P1y+PTVLGKSejrpJdUBYev3Q71HjrGLF+/5p20PVdk1r+FaL7wd3dXZ2wOqXxb3GDGDJhf8oR2H/7uQDbo10QSxTrfNc25Ss8rttwnvw3XPETo44rXpf4tDsuTH7VpueWyTYTnnjOwVzO+XC9XRK/Lj76S0anRGZnUCkYeD0dYfBrU6DngDUw2cnotDtSSEpJUAImrsy29i9x5nZsiACYxq99ngwqASbbJz+s4zqa+Gvj58HAA57ry8F1kn+i5vDsd0ouk9zpeM7uREDixXU38Zp4YZupbipLe5z48/LJbghubKfZFG2mJTUtyPM+dZ7sdWpbQcRXq5msPD09rffv3z8HFf0+RveJBylQS86ETwx89AtR2x1qyZNTwjnynOokTCamU6+0g5PVZBJ1J/ldj8l3WnvOt7fdfJbjOCVevNZw2fXp5RU3J5xr8THx3Hjz8U98pzopBrg8qc7Ey1r5pzyXxPkUJ91G6COUhzxOrzRxOaF2zDf56Ql++eSFtkgMmTB+N0ZTbJBcKc/T54b73p7HUr1zIbq9ex9TvNvFlxaT9d3lY7zaYRavNdxgWxpfbow8Pj6+eJqu/3ZUO6oPDw/xvz4Tf86Tx52Jdnq/xDcSXy3+pPLteutH8hFDvVzKZRr2MR6R0uJ3yqE01u/evXuxOeJ9THGl8UU8bLpKmDTZDPmZ6Hiiqo7bbieZ9GTCjw2ojXaUzweAE4sU7FiewTsFhwT6VFoKZm2Xk3WmiScTQjcm6c0BV/067wms0ootAw55I6VE8urq6tnwKesEMJ5IJQdtn1tw9J16X+USf77DzrYccHXNd4Oc7/S5BRLqwleiqYurq6tnwE9113r9/2jpGNZarwHtJFmhXNwFI0969wBHPbRr3o7zkh6CoPc0UUqg1mz8JDlz8j5VJu3oTUBKPnxiqtMdene9e+J7f3+/Pn36tB4eHqI9eoBKfpKOtbtssiX3RZZLu/0peLfPTSe0jYadruu0+9zkTfZLPG+xQvcp8y5ZSfJyoWzC5+bTa71MAjxeJv54isLlVfK/SxySbdOeUxx0SsnVLjk5jaOsM52E8Hia5KSO/PPUDv3D61Eu3qNdU6dNt0mWk51NfmY8afInnOOpigkXkgzkr9VxzCNP9HPyr+/COdebZPB+Jt6bLprvpHZSTGIOR35aPt3izi4ucUKsmKTfmvrOnP/1jXjyiSrjwrSQ7HIlH6SO/PMOc1NO0eqkhSCNRYqvSR7pzje81K6eqpwwf9qsYE4zyeiy6uU5LuMMccwxK22GJb6aLui/KV9m2yc4fMmJl7UunKg6I3QugoRfd0pANBm/G8AErGvlH6Gn3Yy1Xh+tErCrn8Sv2mqBgvynez6ABOOrqy87MX4sx1cIOQauZ+fb5ffkJo0dx4oytDokL+c6T4HbZfY2mSxQVpdDn5WYyaHJD49vc0xaQE58iKZgQb1O9pN2wdOKmRMB8erq9c6a32PgFQ+pn9RvsoddMuD1ki6SjhPA02bEN/2HY+Pv/Oy2o3u6ln5LlPpxXjUeaYLgtqmyV1dXLx44pyRLu6yatLr8zWd5j/r3xQFOeGlrJ3afvv9QSnom0Sb45OOWALqNq23qjwtLtLNmj3rnSjflOY1bCXN294irLmNr64SIswmrkz5SPxzXhPWt7xQzKC8n9inueFstyZOePDlXGy3mJbtN405dEneTXMR1xm/GkIbzHvtaXGm2mRZUeUz4hBIu83Oyd5ab9O1j7fU8TvrnJKN01fhPcU3EiQr9kPG55R4JB0/6b9RsjA9T8qfkCvd5fDTFafcbv+f9N3Ld+LVki83v0+LRJfohP4k3jovLnTC/yU1sOI2pilGyTR8v32H1PN/tSjpy2/Zy08aZz5HSf6a6bJSZsdXrtFgy0fFEtRlrEj7VSQGfQNMAKgX8RA7GKeFMx0sa7+SxJRguJ+WmDsRDAifKN/WXeG3tuWPQ0ZoumkE2XkRTgOcigt9ryZb31VbzCBqeXPHIVrLD5rSpvlOzC09+JptmeX5O9RO1MgyUCcSTDSTbSwnQzuYnmnTc7JL1W3t+v+3OnfA4+X7ye5VXQOBvMVIiStvwkxQM5J7spMB4yUmJJFPrh22c6I3f25i2xDO1OeGV+9zUzo5PHwNvm2X88w6zSckO22627ifM2/WVxukSn5po13fD9alui81Nxyf+7LZBnhiDiJM7nhtupzonvLbYoEVqt03iBhcUJixu/jPlch7DyWuSc8pTOH5T/yTKPWFa+px4Sbka+zwdv8RT00m63vIG8nc6ts6X39euoCaqXPxLu3GeFxKrpg2QRLuxbj5LPU3tnvR5inkuGzeNuDB9EsvS+CaZkn+d2ij5SBPkpkOOK08j0mYb0e8axp3Q8UTVVxsT0zvD8YF2Q/RB4v12bCL1p3L+SsAhI3ODI2CpfQ8CXG2bwKuB0kQ0CN+JEa9PT6+ffsoEbXJ8Al4KrjRSPop6Au600kUetCLkQJmOy7ld8Jiq8+h2Qqc+OfZAuV0W7yeVd93557RLdUrS+Vr5h+ctEPLa1C93IuRf6Vily+bjMfE/3UtBl3p23vTuL7cH75Myp12BpseUDKfkOAVuHyeN/YmNO+8+DpKR8vj93TFIXWu7NySNvevWcYdjQdxPO5tt/Fzn/LwLfNO4kaeTpIltOnalnfAmA8fBY0aTOdnT5D9etx0h1Wf+Z6HqJP0Qv5N+HL9T38TE5kNOLnO6n3SV9DQtKLaJnifnKbZSj4rHrq8kq/PrfCd+HH/dVyn/1dXViyezevvJt5Nd+fhxDHafXc+S4XR8k54m7H96eqoPJktt0fedqE+VJ48nC9pJNscG+oXLyX5S+24Xek+8tvotL0hHXdV2e9iXjwl3VdvJpx3t8H9np9SVxyu+JxybeN7ZiNuXn5pKJ/SmPCK1PV2jz/D7dHo1+RUxqY2tP9zxZLPG+fPr7NPL/n929Dc9bXa36+ZM87Mfl0sA70BOJXDQkrORr6TsBJ5+fQJfJkYNLKe2GqUEgo62M34fn6QP59vLTG2KJiCY7MJ1JGf3AMygk8ClJSrJhuiIidrY7eqkz9N9t1nqnfbBvjnufE/+4PWYxCS+PUAloPb6rlfnd7LRRA3oGui1tprvOflkPOmwtU37SCDvi1h+vJuY5C8lYwnMVS/p0+8nm2F7bYKV+k59tYDCugl3k517eycJAt9TstNwI/lQikfO/xQ/mh68713d1L7zn8Yg6aJNVGlL3h5/MpDG8ATPUgxMPFKfLQ5NPu7xZK3XsfDq6uWiTsJx15XaS77DxC/Zh3ggv83+k150j/+Q8Pj4+GqBYWcPpF3M4u5Z0tfUDse8TapYh227zG3skt5oTyl2+vtJXuN4vYsjk521kyitDcpJ/ie9sW47Usr+OHaqmzC87ahOtNOz3neYwDbafW8nyTjZltffLY5MPKUFhnT8f+cnp/364rE/aZmT0jSR9s8pBvj11H+KcymOsb3EwyW6+KMnqmTUBUsBXJ+n4yzNsdrRk7ajxncOXnMWGlsawFNgSwmQkxt7u+d9nzqWr9p6Gwks9J088/oE0uqzGf9U1h9t3XSUbCR9ZvlpojoBGK/RsVp7ySYYWFKgTY6/1rzLkQIMeaR/+LikHXD6yFp5h9ixoOnS+aUuqNN03DXVT9ensaGOpx0hr+u8cKeXQTztXHhC6OPjO66UYxfUJizx8XTd8ndlafzpqxyb9Hc3a/WnFCZKON38jHrZ/aav6aLhNnWhNpIt0Kdpa+SZuNxs2ikdUU/jnGw2yU6ZWX+t17uQLZYl3zrx8ynWtc+TnSY8b5jJPt2PW4yhHF6OE1vHQVH6iU0bJ8oguRxrqPe0O+jtuc74Wd8vmUglfaT7yV/9c8LohJuuT481CRMnLEi5QsN6v//0lB/UljAvTQi4yNHeJ7xsOVMqk3QylUl6SROsZqeTjzkf/nnCiYbfUx3ayFovd6K9PmNUswfPCybMShil6/Qtt6d0+sDl2cmtdrwv1nt6ev03krTTptP0OemZ5WhHqSzlSN93WCy6aKKqDprRJkdrjDQH8OOubkRqKzk/V0wbL237OrXLNlOyc2oA/qJudm21hKMNfGorJWRMPt2ouVt0ydG0JlNyLvX1+fPnFw+O8racp6SPU1A/AcOJdkHGeU6g3cqlo/Dp5TL477AFhvxN9vS7brWn4/z39/cvnvancRdxAuTXmj6T3Dva1Wk6TUkN6zglkEw2lR5AMB2LEQ8e/J18rPUwJY3VDu8m/Ux2ySA++c4USF1faoe/55zwISUHft35Se/E+aQr9ncSqyhrC96sk2Raa36qepI/9dOuTddbP6muj51/PtGD61zEcdolIckGG06lWDYlUq0/9821+v+SpjYbX8xbmowNr1JMS//f6fjGPGeteZG76bDlS/zsfPAofOpL9yYsYy414ZL7ftJLIu8n4Uyrw7Lu0xyDk1xgur7DGbeP1objb7rv8vsJnoZBrmfG+Ykf1U/HnynTrn6r5/XT5FNyKSeayrK/k5yDdpzs0Xnxvmlb9IOka3/f+arbyxRDRc57yrudHx4H9j54spa63J2eOo1la134MKXWaSqj7wxevOfkYJhW0b1vvp8MUKIpcZpkTPpIxtgAgLzv9ONGm643OVNAddBlOzLOaSeSPKT2JnKbaOfsd8lBCxYJpFvfXp71vXxqO9EUnJ3ctgkUlLX5CH//6I8uT6/kF1dXV68mXEn2ne01Xfh7andqYxfo0/Vd8ioZfZySfpPvJf+YThA0zOPndqKk+VTyO+pmSvqSvPyc9Heid+ed91pi1OgkXrDcaXutbR/DaexSfw2HT2TexahEJ8ly4mF3b5dQtKRssjle0/dLEpVpTC7RH31rx8cldnAiD3ODFue9rMfsVG6K/RMPu7HjtZbPsR3u0F1iq+Jvop0tTXh02l/C3fZi+Sa3629HDe8ab37vFIP8+nRU9dLx8/bE3xQnPOcnTZPjHSY7H1Muy/stn3dfnE44TJRiQLKRKZ/YxcbdWEn3lIv9iHg6M9k/+3ZsTfa2i/+kH/T3NFPy6y/Ovqe2PHGn4U4B/pJB2imG95mI8tgwB2GaKCQndCfhbq9fS49Np/wpYWugdWIkBNWnp9dPI/VxTwlv49W/r7VeTR7Ia5LrRI7W3+RAqW4iJuG+msgdMgKy20p72A51lnykTVRV19tpCxBXV9/v7qmdtkqrNjgWHJd0v9Eu0dwlEClJaP1MftDGP61Q7k4X7IB50lEKTrtV7NQP5Z70uzsGvfMD9tl+Y5d8oNl7wkLpghiRArlfd2qLb1McS7KSn1RmN/aUN7XRKCVKJ7bQ2tL9lHxNq+INW9M4cEwblu98cuqr8Tnx7nbD/3lmv14vEXU/xWb2fZpcTjbO8XZbbXo9+bkOYwrb8H6ab6U6ek0+6e37Z5ZnbKK8jedEzKvS0fMkS4vhPJXm9RIpxqdY7v2R51R20onzkNps+Mw+vSxzQfadeEwTVfWlo720Z9VrvHjbThyHNi4cT+VG/veR7aeBzNmoC+cpxbqdPyZy/U/yTnGCPjnFjxOenFKecQldNFGdDI4KdsPiEZcdQLhgnABMdRrAXhK8pyDH3wTSmBs4tj6d7/Z7L9cBZSZ4Tr+T0OfEZ3J+BlH2x+uNvA06gTtPW9FL8kxBiLbX+HFqxx5ISV/Ov78mPtP9NLGl3N4XfYM+yQD7+fPn55eu67jv3d3d87HfFlQTJSB2Xkm0/WQLO6Kvs27jZwfW3n6zc8qQxmayU+LXzo6T3Ky/O77UkguV98kfxyIdRSK+kx9/n/A1JXXOTxoz+ovaScR2nd80lsmudvJxvNp4J1tQnTbOU98pFp7gJm3XbXyakE40jXFKLlmuvbx9nmLQ9aS/Fvc4/jy2ntrwug0Pvc0kp/jl77hOMKnphnwzxqb6bHsn99Q/YxVjDV+prabHJMeO50nu1l/i0dtvskx24BigNlJulvwijREfuDeN4+QPjBMtDnvb7nct/rGPxgf7ZF3nJcnT2uSEL+mKenJqPydrfNIHeNJh4pV2QTxPuH9iI5RvpzeP7b4IkMa/2YDkZ/uTnTCuX0oX76jugM+d8+rq5Y5AO0PtbfKvHny3iP3vDLnxT553dSi7Xny8d2uDhsKBItDTiNPDTPwlY0pGMAUutcUy/iTeZIg6r77WevHkwkaUKQXWBKTkizJM49WCDykF8xYUGIy8jOyU45X4bDIwEZBeGlB5wpAAyX9XoEno/f39i2v6jap+K3wSmHQ98U6dTW20tnZlW91kL6192pPKNUw59atkF8SI1s5O5qRH95VJ7w13008S9H2XOLQxTxjTcDbZdsIetn1qY6ndCa/8XpsMTv0n3+eLY5GusU/xQ1uabJufaQ8nScOkM9pSGuOG/ZLH3+kjTCR3D3eZsCCN185Gd7aYdMS+T3GEcTBdI1Yl3Bcxhkw8Tzxxo4CYdnV19Zz0tt+xOe/Jh5q97qjFxfZO2cWrPu/wzuuSiIeeH53UE5+OPYxLkyzk23U0nZJiG97n6bNJWl33IX9nefKQchDyQXvymNTkpJ7SPZZL2EobnvKHSc7ULv3S20+Ls0lvJxsNjqktDngZ59P5432vN9HuWQ6kix6mJObaajhJD2ZREjwp0QfjxNgapSSASUJz9rSanx4kkyYSnEyqXV9RfXp6ep4cEBySPjTx8eMGKutGmQyUuyHUc6JdwFBbfrxPIHiyCKF202sKpgRjvbckYgo05MPbdCfk0ztb4kIZkm0xGHmfPk5+9Fbttd8HpM/UuSaePglNk1LfbU36bwFfCcrObgi6jW/2S0py75Kd1NZkc17XbZtBJPFGHhwb2F8LDCm5dF9ba/+7nfQiRlAPXBAhJiVfIgakoO6fHV/9Pq+5b6RdXddBw04SsdPbanUahrLNZoMnO6pOLT4mjLm5uRl5S32wb9dpW6DandJJNnvq52mi6vV8vNKEglhKfsl3mmh5Ep8mwg23J3uZMKlhly96pzHjBNZ581ilNt6/f//ipyHMFVKe0HCl+XbiTe177Jra4mk54mzyL9aZTpslG/SyJPp8y1+8L/7XfNJf0iHb9Ff7WQF5T/lNilXMT9zm9WA/1k16SrbWfKTxzXLtWsNqyuu8rJWf+8C45+/8nNp0u/bxTG24f3Ls/QRT8o30WTK5P7Pe09OXE3K7uMbr1Hm6R7vXezrhktpLOr+ELn6YElfIRC15m16kBgjkgcrk5wR0KTlKwaglEg24JgBKumj32N9ar48NUVbKQwe9lLedMaUgzSODJ+PbEobUVwOs5BC87+/8nIJDAyt/T4mGiIk420k26O36xI88NaBOskuf/EspBVMeAfYEpgEv5U3BhddVJwUVL3tip162tZvqpH51jzI02008tgRmp7MTnlt/6bO3y0WxJgvryk52eKkEyus6z4k41jtsEc/iifzTh5M+Ez/JJqcyHIddvCJvDNINZ1pSwH781X7vkxKUlrSkiT7H4BIbaj/d4I4922v4yr5PcGLyrTYOKZ5zwnbqh63MVE6v9jdSk4zJXtw+/Kco1LvkbON8gmW6doKXXp9xf4q/Ip+Utp3dtV5iH/+pwvm+JI6cjLlTG5dd26w/ta3Pk2ytj6QDb2/Xb7rnfTR8am1NOYLbkj6nGJTqOXGCSdl3eCnyvv037ak/tZfyHX/tTopMuvTrXLDh0d5kHwnzp5iSfFr9nNDO1xpddPSXgYPvuyDiCTEpBfApiPgKpPOR2kyToF1QSAEy8SOeeL8NSDpq1xIyn0g0YG9G3Y57JN7SDq+/T0kancMnRcnIGWi4m5OcSgGn/WbCddX41GcfS++/leeYug0SZJqzNjtl+ymwXXpEYq18NIS7p3d3dzUhO/Fp2t6083IS3L1uC270mebDBOS0cyqek92d2NElSVYLrAn0m1+zXLP/lnR6+6rnO1Vc6b26unqFsWu93GVOgS3prMmUEiw/BTC1dULN/iZca8ke63ubXEQj78SZhDvetuvU31kv6cLxjTKRnM9kP6c/A6BMxPcUw3kCh1iS7GuyIyVmzFHSizy6DE3ull/4e6Kpb7/v7bBvxpgpf+I4NP37aTdiRrK5lhM0vEk6IV62EwkN/yhXwqd37969OjHE2JxypqurL7uYfj/pr/lJoxZ/Gi6JhxN8mvpNddMOJR+AxzoptqbvvuvXMOgkvjq1k3bJT1ubjQ/dSxjavvsCqnDB7dHbnPKTdMLUxyfhRRtzldV/sxNj9Z07/2xnsuMWc3gSYsqhJjva0fFE1ZWwOzLnjCSnZhkXUgPjR1cESAQF3wVqEwA6TUoCkgyJX/Ls39PuJ+uI2tY99ZUcnseLpr4mJ2xG5XpL/E1BeUoq2I8nFTRgHlN052pHu9LR6wYWKXloOuR12l7SX6ubjnvoHgOkX2vA2fr133mTX4GV5E5tpOSOOqDdN5mVAPh3yuF9uz8nn/XyjkVp0th07XL4tZYIn9iQXyMRK7z/5HtN3qS30yA96d316JjZjiOyPZFjkx/9m16ui8fHx1d9Nn03+1R7KekjriRcI0/+mbhM/2mJhPrk7lY7gTFhSKrHxKFhWkqKPKEhxu4Sj4mI9SJOUJO+JJP7gvSeyib+XDfcgVvr5W+JiZH6LOxSnbSg2WyQcqRdwKa39EpJeeJLvKstt9PUBut6m5StJbIpN2i6os4ajjr/qUzaHNB15Qv6mYsm5ZONJN177HJZ2Y7bpfPSMHdHKR9otMMOxp6dTzdMcfkSLk+LB61/v576nzC4yZjiO3lg3R0G+1hMcbjl5k3mideEE41PXnes9Empb5IlHEl5TNI1MSnpII2vf94t7pCOJ6r+gB0XijQZVGPaSUp69+7d80uT5LXWi994NoV7O5zx+7uXSzJ5OcpGOdJqXJO98ev8EaQneSejmu6Lby+fgqkbYCPy5bprTppkaokTg2watxbwkvwp+FEfTWc7wGy+kXhpQamNOXnw79Q3x8/fGRBcJ2vlROUE+Cc+m++4vaSgQP2k8U7JaDry5nyk487efvq+s79d/aQXXtd7qzd9Z79p/FLQZflptzjhaOIrtc+FhbXyb/uS7Mlnp7Lkp70a0VZZJwXbJDftf4oTOwxpvkTdtMVQt33HBH7f9ZX44jimUxZsbxoD+v/OZ5zS8VLueCTd+P1mw86X5xcT/74zMuEBx2it+S80yK/Isa3ZO3mhDTXsT/Hcdc62kn6m68m30ykhHr0UX75zxN1Vyuttpxwl2V6yC9pBsrFEKR62PhLuknaxK8mS5GBdjpfHa3+IZLNx9pcWr9OiyW5CM9lns/ldW9O9qQz7n3hp4z7FPZY/yVuEI1xsaH6fTmymuNf6JWbTXvj5lP6o/1ElMAkkWkBJgJqATSszNzc36927d+v29va5nCaq/vIfECeFO02ATXBdqx/90Ge+sz862gl4JT5S/2yPbaR+PAgyOJ/QlFiwPZbzBEbyeXLDpMnHNQVEf0hNCowJXNP4CyDbYsMElF5/SlommtpPAdDrpbFMSUoabw/QjWfqKrXRgrOX3wG16/1S/ZGXdtQq1RFxRz6BL/netcm2dhMA1tkFR45x44PkE3gPKNJdOjbo/aj+JWPG5FL1tfPacJJ2Tb20/psPO274dU7SpCfnx3Wma/TPtnOWYibb83ZSAubXHx4eXrXpCSMTA8fVh4eH5wdvpHi6S4Sarh1r2iIRdUlcYB8Jj1N7Ku860DvjBHe1/bh50nfqfzf5lT6SzrhjnXTomO33mSclYkKZeHj//v0Lm/X3KQa2eKL+WjxuPKb/rvX60mFatHZ9+Kk7L6efuqS8Sd+nI8htbFqcSLG0naRqbTM26p3t7/zCy6STjKkNf6Bisz3JxNOPeujnNO5qJ/VPXFhrvdgNT2OYNjUm+VwO2mgqm2JSyz9ZL/lKyn8Sb8LQpLMmW7I9yskFn5RvtHndWqvGipaDcKxpvyc2vNaFT/31jjhAEkiBMK3QJuZ1TZNTf6VVyDR4DHQNJBO4ki/WJRAxYWHClozHjw9NlBKWxmdyxgYA5KcBohwk9T8ZZOuzJRs+btRdS2BSm41awHH5qI/UP9ujjHTyKTg3OSb+2TbvSRYl++onBc/U/mRv0zi73Z+sJDtg8xr12eSdAvQUBNgv6yRdJ320JKTpp31ufuDfyUeyqV3gI1Y3mfwzJ6gNqx0rTvzReaK8XJAi/6mNhHf8zrqJ18RzSw6cd/5eh4lASgpS+84TddNiVPrsPE4Y5ztM/A3fLi7SlqgX9kUe0vHfFI8ZVz3eTjw6r2ksJmymHF6OyZxkYft+v7Xf8CldcxtvGEmdJcxsukq7V80G0/tpnGz3/R6vew7CNttE1RN76s/j446SfifdOG+u/zTpT/axw00fS+ZLpJPcbOcHqT3KxljBnD3lBV438eX9+Rj7olKzN8eSS6jlGuQr1dlthPEUYMK5iYihLfdIMnjZ6SSit+E8+YKwy+Ny6eUypzYTv5eO01oXTlSduWbwvpKVVhIaEMjQtYvKiepaLwFZP5pvgJgSgGmi6nXbMR0aA4NqCkZ09mRw6Tv513c/gr1zznQvGS4NVKucl7TLe81xXEbqha82aWZfzYnX6r/BUT2O2bS74/X8WkqInL9TSjJwMYj3xDN3MKgbtpECaPKZxJ+3t5uorvX60e5+bUp22A93310+14MDPAGVcjkgp+TPv19Kkw+dYIHbE/XMACJZdwkUder2kZKQiffdim9K8NKK924h08v65ymZYL20G5t8IvkYiT7p8YIxy/km/2nXMfmw9+N8NsxJmPb09PRiAdnjecO7lAQl/GR9xQ/5I382lBI5p4Z3u8lG0s9uh2eH+YmXliNMfTCmEXvZrz4Tv1M5v5ZsYSrX8pWpfsJtb6PtqJ/E8cSrl0t/v3F9/f0T7lvO5rut5JN9td3PFguS7XqcS/jadJFis9/b5ZyJ0r1dftuwOmGedlTl51zsdJ+ccNH90HfvmDNQNsV7L3cJJb7SwnaLkZSl7fCexirnwcc3xaGGUSl38f7TiSiVE7+OD359mts1vhK1uo0uPvrrg8AXGdgx7AlTcmYmMGrfr6VVtMRzUkxyUn52WfzYmvPS5N8NQkoAXJ6pfEp0dsEs1WnvJ7yu1ZOHFuCc/8mQCXKUh6CtsSFAtkDvRKfz762uy5KSYC+zG0vXCYl/GJ7GLrUpvvxest1ETfc7MG/fk8/5JFvliAEcR9oud8mod7cH9cOxTTZEXpuOJ0p4dgnRp+kvSTaVSxPztoNC/Xl/DGIJ47wtb4eTBvLhbRDzJp+jf57slLiuLh2PpHeXUZ/9P69TbHT7UzvpXZ+Tbbe+qR/qSt+9byWVOkLsiZHXTzEk9cdr7q9+nLDhHHGpYWnSW3q5zFNewN0B6nQ3TjvdtFfqJ2H0CV5zMqDPU5xI95lUs55jyJR3JSw90ZPIk+Ukiz6LB58cpJ8DaRLlZU9OWLhefAKVZPb6tHd+TruN3l+Kl6kv6nEq531zMqlyU46Q/Eu65SKd9J1wd9e219eYJtxXG8IZH2ce9U7j5bxx0plyZNdfiiGOJeI7LUoRxyi/f/c66Yg8dThhxWRHLqPrJbWrcr4hMOErPycsPKEfNFHVoKSnBPp7Slao6ORw3CVgOwQxBrMWPJ1aQEo8ps+8RsX750sSo0mORCcy+LW0K8V+d3356pXaaUbZrtE5vY/msKTUr8q5nFxBmsaqvSfaOeiUKDivu/bJZ1oJTn7BMt7uCWimIDbJRb4T7zveUn+UzwNU6zvJNI3ltHvf2mqJBsuz7AkeTGWoF7dv1p0SmNP+LvGZadKZgl46/ur1KIvk5Gma1l/TG+VLn53n0zFzGbk4wvalK67MJ9umX06+5/pIi73eRtJj0gH78PKpTOLrErxLuYHz7rKkPMPbnOLcLjdodjjxr888GkefSX1wfHe4tYuRqXzjvY2/l2kxm+1QRn3ne7LTtut8EosT1tKXkp2p7KmN7u5x4cfl8O+X5GGMwYyJqQ/WnV6sn/S4O9Wxa58yuv55wof24osMvJZ0NuV1LhN5TPWof/bDxVPWTzHQ43cag2ksyVvCl1RnsvFdzpHGptU7jZmndDxR5UMXJgMQpdXjNGCanevlqzH+mUfNnp5eP7wpge0UjJojsa6/TsDsJIAn3aWEmU6bDF33JvChHOmceRrHafxa2ycOk8bUj3G4DlIyl9pP+vUVziRrcrp0dCn115Kq9ll97EB8Cuo7ENIr7SY40CQbScBNHp+enl74LPmkHJf6JGVJcp7YgMvIB+jQdlmH7Xj/ra9W3uXYJU3UB3WRxsvl4ZEhb2uHddRHSh6d14b57MOvNfxQOY5rk5lJSyurz1wlphw8JUQeidGMX64jx1eSJ3rtrxzYlr/rs/8FlfPabGitLw/Qcfn9fyepC445dUZSuy7XZHPpVIVTwmXGvvYinWA9ryVq4zFdm3COsrTjhKyf+Gpj0/DI25/GlTwmGbwvH890gsL7bIs4zV4aPzueGb/S59Sv/N9xdor3KedIeJiuJ/6Ja+ke9dzadRsjJqpumvjxt6dXV1cv/omD+pJ83Dk+0btjSLMHPlhLeOz5SOIr+UjS6+T7Ps70G9qzdEAb9DGa4kD6nuyT8Ya2uNM1+Uq6abhwKTUM2tHxRPXTp0/xdyX87O9kjoyyvAZNn/k0Ma7Wq+90vVFT/i55a/VTezsAas6UkrfE68RjAufGi5woOTB1PAFzS1ooCwNyOufvBjwdx0q2k/TR7LTVn8atUQsK/EwnPUmqpuTNr3kCkAJD4mmXfHC8PaFrQM97jf9mMx4MGz/kq+mkBaHE0w4LThKjiQ/p71Qm9tv4mnjf2VuqS/37vcl/XNbTAJd8kjiU5HDc2iVop5jMP71v7TQMpI6cmPy4HH7tRBfUG3lhv8m//Xv631rib+In8aB2mQBTVydt7SiNw2nik3xqV6/Fj8SPt5viZhuTZr9TLPG+W/wmXz/E77wsYzv5br+nU30tRvO3hXpPvkI+Go/tZ2SJn/Q94eM09knfU4wjpThFfnbYlWSZ5EuvyV5aXGjxnePc7HrKT3g/LTROP09q/Ykv/07/avpm3fSTsaY7b5P2zTo+FkmeS2y62aXfuxQDfTK+q5uwWbbUbD/R8UT148ePLwbDFU/HnQL+pEwfFO2m3tzcPP89Dc9FS2GerEyJuhMHa9r9JZ9ev8lGHi4FsBSIeC8lHo2P9Nllb6DsvCcdsD2XOwUvjaPvlntbHrgSEKW2m3wEld0R9UlPbcwaMOpaA8EJEKejI+TLfxPRAJN8nvCRgG1qN/GWbMZlol6YZHAByj9P9uo8eDtr5f/M29mS8+j3WtKSeGV70+LaFMBT2+Qj4QKDZLIVHwMmGNPuWuI58ZquT5iz1su/r3Demg2xz2SzTV/6nHjnSnnbLeXuccJm2mTirZ1ccp7Tde8j6Y3y+Ykl/21gSkrSLvZkd9Qh67q8SbZTcv7aJImfndfET/LlFgeafbcx9v4bf5fUS+OW+GIsmcYg8dNi0hRPpvFNk1RdbzmO5G11prhKefg94TtPeDXMJ5Y1fEk8pL55jXG0jVmTf5enNN4SjjTsSfbRJquMP5P9Ee/TOHnZJov644Nhk6xJXylWnWDhiV02HT49vf4ZCPMJz3X8+5R37WyYZRKx39Tf5IeX4PzxRPX+/v7VjmrrSPd9IjIBD58Wdn39/ZPE3r9/v25ubtbNzc2zsXPyobbkEOmJVOkIpPjkoDKw75ysGaneTxwygUAq6444AW76nsj7fHp6evWwAE7uJhBd68t/USY+UvBxB2Q/E1g0IpgL4PRfXF7fx8wfxETZdv05n+n3Gye/6aBs7Tc65L8defEA63I46NG2m5wNMKfkxnl2H+M98bHTi9d3cNwlZZwM0qa87pSwNDtMAJ3adH59N5B10ncGA/ZB/KGMbRXcMdPrEf9clxPPEzVbp+21pEDlfPePky8Gc070vP0psDYdC0P8SF/6/WeanDj+p8liKsu/g3M9qp1Lkgrnl7biL9pt2lX1CWuKa+mnFqk90kkMm2KkbJq4OyVT3s/OjxtWTm0nSjjX2kj9uf+KZA8np8soRzru6e2y7/baTRZT3D/VkeO97M7zlZP4etpfuq5+XA/ps+qcyLhWzhl2xAcsqr6oLc6xH24eEFv12TGLuJz65v2U23KB3culnw6wn7ag6vpJOnh8fHz+D+n7+/sXeMY+SK4TyeebZ6ksqfnaydinuL7jdcrf9J74oW8TA10PksvfL8kPTuh4opoCVSIqR9f0zpd21tp/p/pguHIYSJR06Tc3DKYnv8NIskwAMhmpv6us+GkrRCfEpPXkevveAm4KELv+ps8ExaSfprNElHOXiKjOxHPio4FXSx6bvZwC0MTrjjhOJyBG3mkb9JWWyCU6SaJPEwvywbGZ7Di1lT6zDMdg0iftZMKXqc9dGb/PALEjyuLJXbK1S+x3V8YXR07bSb89TYkwkxrJ6nI3mSbbbrg3Efml7dC+EzanWJXGJ+1wn3zn57S4KPqh497ihcq7jnRtigmpvxY7mq7/WDrxbdIOBxrmNVt0W5jsmteSHC6P5yYTZk92pPq7GDjhfOI15SI+SWgJf/I1Juc7HaW2U9y5JEb456nehD+TD7QY7n22sfHcm5/Jk59c9L6nuO99Mi9Xeecl9e1xQPm+3kU++eW8hTo48SeXb4dZTpMfT3Q67inONCxJ/SafcBxIC7EpDif+m+9fGlNFxxNVB4apw5TcK6HgKoiuacfU/0fVDYkrHtwV0nU3KO2saiVcn/09OdQlQCoeEgA2I04GkYypGYA7a+Jd724szTnSNY2L+kgP1khtNKfRizuqXlfBssmd5Es8NEdMQJzodCcz2Uvin8DN8m21ksftTqgFFJaZbPvq6urVAk8rR50kmZP8KrPzrxbw3Ab8d4VenmPMQNX6a+Rj5ZRWR30c/Fqy2Z1/Ol9JxztZaP/ND1NQ4Xe3KfbP8Wx46tjCPpoP0BfTTirr0ifJE3WVbEgxpN2jbIno65RT7y6r+uT/RbJd0XTiR2WnxMH/RiTFIuLBxJP7n/NCnhkTFPtPYy9t7xLyvGJ3/wSnnIe0g7/z1RQnk/+I0kN6kj+3Bf9mK54zcUd/wnK2QyIPxOaGG/pOf3EZfILtZej77XQF26duEk4l255821/Jf1qcbnR1dbVubm4q9rmv8oRc0k+yd9884vgoR2jYmOzRf74h/vgQVOpYLz9NqfviTc+wub6+fv55oPhUH7JpnQjVNb3c9jWWPldJ48pTndqwStjZxtBlbZjXbEX9EUPTQi552eGl+4qfTvWxTfwyF+OiQOrnEjqeqN7c3Kynp6fnyQuP/aTkZa2XR5RUn0aodzcSCaMXJ8me+PjE1R3OgyxByonO1ZKflqilaw6CBL8dLxOl3YkWUFuC5f14O+TTx9gDaDqu0nSawD8FS5fPASHRTvdNHl5j/QSa7K8lOq7jlPixb4J8C5CJhyY3k8Ika/p/s9Y+iePReHLeTgAy2Sfv+Wq9Vk/TIpFoShoaMRGhHtsuVtL31M4UAFudSUeUgbRLyFJ5n8BMyaRfa3jniWXik3rZ4ayX8YBIn0rYt9MjFxnYT7IjjnvCPh5JpW5SEuKxK/m5t+ttc7KTEg3y3XTW9OkyePvpfuqXSRZlmHDaddqwM9Vn/0kHrteEX8wnkq0mfTR7m/yDceSkjVQvxVxip09ufCLhunFbpX6Z57Hu09OXJ8W73idsUQ6y0+WUh7CMjydtLWGubwj4LiLzO42f45Njktd1npxoNwlHPUdmDuhjSD59vPU9vXzTyMfb7d7baz6y1ut4ljA6xTzilfjRQ1W1mUVdeJvSw/39/Xp4eFh3d3fr4eHh+eW57dXV1fMT0bmBQL6pb/Gs8hOGTmO+I7c1Hx/+bDLp0nmZ+mduQEwiH14v+WSi0zyGdDxRff/+/avtfjp+Yoov1fPjvv5U3zTgNGwCU6u31sv/ZnJq3xtwtsSHZXeA3iiBZOIpBbXGR5KDfaYdaScPLn5tCo6pfV5n0FSZFPgneaYx8f7avV0S4G1MdMIr+dglHx7sUl8tMXB+qWv3l9Re4vtUvtbelFhM9fy6Fqv0vfnGJTxPicJJQGE71HnSvSgthu12Yn0C02znJBDtaEomT8l5b3jRMIF6aVjQ5EkLlAlXHKvJr4+H++GlWDFhgffn/fhCbXqnjrz9pEO9p91018mUZFGPrX9+Zrxi3PZ3bzfZcdMrKWFfsi9/T9jj/kZ9pB0U/7zj1fVD+ZPsye7cftPCI+18yhmenp5e7ECl3b+GbyqXjgy6LrzcNM66fopXCWubL7RcII3XZCcTL+TBx2mSeWrPN3L4LxhrrReTM6+XbNhzgOvr6xft+URV5X1Mp7ibcIL5+pSzJHwUr3peDTe2mPe7Hh4eHuJENW2A8G8w6Zcun/t4k4s+kSj5Rhv/tV7+hlcTVB8756O1s7Nf1nHbIb64HK6fxn/DyxM6nqje3t6+2N30I7RMoCioDP/du3fr9vb2xUOSdNxX5RgoHh4eXl1f6+URMP0u1ZXgK4PO56liJidq11OwSu3Q+akrJwJDcyIvs9bLoJGMLQU46dlXzpTgpCMA/Nz0kHg7CZzkm7rmmHvf/nkXOFP7iVJwTgDV+EmBPo1jajvd47XUD3l3QPP6UwD5ocQEggkD77X+WbbZV7Jt2UlKwE6SoJ183vfJtZO2ksxN9oQhCQeIq638Wq9PTHj/TIiTDGyb2KbvaUdMsk0B0T+nugljk717Xy6nkr1LjyeJhG+p74bfTPYu9UnFPO+Puk/JJhM82pTaY+xM4+byT9hKW3KadlRpQ2yjxcNLfLElZo3S/+9SFlLKCdSvL8jtfKy1yRiRdO/X/bg5H0aZMCL5ueQ9yX1O8HDXl/eZ2rrEX7iQxna5W+y7cWt9wYk23hP/xCHnx23bd864i+jkuZWfRCQP3o7n35r4OH4RG4gRKUfhq+Ghyyme9E8fen///v26vb19cXpSPKQjveJXD03y6677Rp43Mu9Iumz+Rdt0f7okx1Id/7tOjRP/EcV1ksaNsa99TzGk6crtwceYvtT6OKGLf6PqHdMxk4DuXK5kvXRddbytSTgHQyZhDiYJfNkX2zvVxxQcSH4/JY/cedwBtPPMPtr3JIMDBQO766QBK/mdxpBE4EhjvOO/jacTj0Qk2VpQnfomsa3WhgMW22u2zvqNhylpa8H8BDwI2Mn3pnrsnyCuQOagl/yD12mzDHwOoCeJEdtnH/5+ep9EX0r1pwQxjdXT08sdM9ZpsrVyiR99Trs3zd7Sy9tJkyImREx4Tnx+IurfP0++2/pLiUzyXdn4xLcnSSlOqJ2GP3xnYpfsIb1Sm8l2muws68cRVS/hoLdJeXc2RbmS75yMYYuFXOBJcZE8NHmmPOESH2VfrXyz75aPqL6/Uj6QKJ2QOpEl6WuSq40pc5TWTuuj2WayuYRLJ7Km6zv8T+PV8CItsp34jtdVe77R0yaqSY9JLl7zCbNvZnGC6pPUNhnVZ84B3K4SD/zc8la2SV03DEzjmnKYZIcea/nAWd8FJn9p3pNOGJH3hgGer015I98p60nOmOh4ouorM1KQO3NSvitSu6e+o5qOMLREhIom+WBwcNIK7w7EGawSPwSoKcg3Hl1mXwDYgcoEDn5vt4tMQ/RrHNtJT378QJRWV1xvE9/Oi3/2utT9Tj8N+FPQZl22kWzUjwymdqiHlOw4D9MKoOsg2Uuipp9dcHO5p8SQMoq39HCCdKzGQdZXrU/sN+mCvE280k78ux8zSpPBRjt7phyTDEmmdFqC/XM3oAWiiS+Omx8Nm2iXFPk18cbfyCX8OrXJtV7+9IPjQPtKGJf6JQ+klPg3PJ2CfOp/krX5MXdTNY4TBiRsJC8tvpGnXdKc/IpjTP+7uvqyw9D04Pzs8KD5xbRLSKxjm4lSTpH8WmOWYh3b83KMyaKUYLfxpZ2l2K3y3HVi3ZYTnegqEeM8+2J7zLFam6Tka/x7rF2+kGIL73kOMOGlj1N6AFrKYXY44u25PGpX7fA00pSbtO9JrqurqxcPRdKk1HdSXee+Y6hjvff3968ekJROjvhPDRNxHFtsSDnKJflTW3BvdRzz0kOkfBw1Ufcjzy4PZTyJO27rbqvu/2nhhO0m/5t8knQ8UdVTnSYHo7AeXPgUsWQMLQA7McCu9fLoSluJT7y6DOTdqcmddgQSTQOidtKPw1vS3YIMQdzLJ1lkZGnS0HQqnttYtaAxBZFELXCqfU6sRWk1dwqOkpG6SQ7N8U68uAOnoHFi46ldv+73qRvuzDf5p3ZP+9O9NMZMLt2ek12nFdodrymZYpscxx0401eTTpr9N2yjXxKLThemWgLW+twlUGkcXG9N136NlAJWGpskm6/a+9Pa2cZ03JP9epCkb3gATjJwkjzpnzzufK7ZYtNbsnW2J/nev3//ilfupia5ybv63I1nwjfKlsaPvwvzXYL0H+ytf+rB7aad2qFuaLc7fXsCt9brB1glXmm71BNjEieBXp58ETdSvsby1JXkmPhnf1NZ+kH63HKZSY9OJ3nG5I/kyScyDcv0U7MmgyjlCvo8xTs/ejvhW7uWeHasn+Kvy8Fd1OQjKU/jd++XL01MtXvKuYL48B3TT58+vZiUtYmS65K7ttSBL4xysZRPB/Zyk+1OvnNyPeGFYiMXp56evux8+2Q9YZrjQuJ7srF2Iuj0mvc5+TvpoqO/a71+NHJignWSs3G1UO/J0BlUOXDJqSbjnYL0TpaW/J0qnO25QXJrPx2x2614S7YTcHZASoljS1AczJNDpWRgem8kWZSE6T3Zi9snedgtJkwJycSX85CCtpfb8dASkMSjy8pgcGlg8zFr8jcwbbxOvDlu0KdSv37P66V2KGPyjak/v3diCy1R88+tzzbGbRx3fHuZdDzL+2ztq/4UQBwzEv4n3G34TcxxDPeEgDo5Sdbc/+ivE09NB6eY1fyi8b9rt9kE7TRhYbP/9LndY9uUsxH17otUTB6ZuLaTC5SlxXa3fU4WWKftCDSsOfHjpLfdwjP5pe68PNv3mL9bqKTdpPb8vvPaFodTnrDDsRabJ/02+58wfsqDUp+OGYl8TCjDzqdSXpb4TZjHNnf5gt/z/Ky93A6JxSmW0r+dP9oJn1DLhwFpouq/lRUpFtzf36+7u7vniSr/Yoa6YL6RMMZ/cqjx9L9/8g2MtvHAsSAPiaZ4mPCS+k3/E5smzmy/UcsZpzhL/k/8jTH5Erp4R1Ud+IA6Ezw64ALpHldP3Yn8GledpgRLPNCBklG5Uidjcp4fHh5i2TYBaYHdHdkdyX+vmyaqbpDeZzqC0RwlJS40bjoNweXq6sujvL1dX+nhi31PRpoc4Orqy//9pTFgOTpaGqPER7KfFIS8rNuvj6uDStK9t+m+QhBruknfyedO105p0kEe1+r6IF9c8fOJjY6kOI9cwfQ+ZHOOAZON+65cmrSdAiUXX3ynMQX+SXcMHNKHdMIFwFQ37S6yv+Tjfj8lQi1p3fVBfE6JTgua3iex2ttx4rjvArDXS7bTyPl3W2k6dXI/ok9NATz5/im/Kuvv+tzwpOHQiV80DE7f5Sf6mc/0Gysv77y5PXi8Sjvek/235DzZM+NN++1b0pcnxymv8djCBFN9tTyF11Iyu9Z6PpFAHbCc88xFgoQL/t3HwPXnumOu4LzT9ydqNnyyADzleP4S7qZFuCYDZWF+xv5Ut41NGnfvI9VJfLoNplNNLOu+NMXKU8z1/uT7ynE1MZV98BirH+fV7und3d3z9fv7+xjTk4zCmZRfu41zviE9J593Gdd6vXHj9Xe5aIrDbk/eny/ekk+Pb+l4M+dlzpPz4e2d5nqyH5ZtdkzdnNDxRNWpCcjkgwEwgXIKTBwoKq4lVg7a00rqLiFLgbs5a2vLB8nvc7XJg1cKmJ64TkHY+UkJzykxoRPA+MOv3r9//0JOTQrWehlkW0JAnbXEz1eHqVPXJZM56ugE4EkOYIm3BC5TO6QkU7OZHY/eZmrvpP4umPv3S8gnrDzKRt9uq5aSxZPelKA5xsgmU9s7ndCeWpI0XWs7i9SNU9u10TX3pWl8Ew4lmnA8yezjxoUIv/709HoBjL5LHlK8YN9pbCjHCU0+5fzwdMYlWJISD28r8UGba+OQdNnKpdjKdiZ8TvyeYJJjtE9K/TdnKY6nI2uJP/LU4nPzZX/3BfTUp3+fJqkncdbrtV0rlttR86k0nl7GY9y0o53socUF2ibzkZM4Q37T7nrqkzqZ+mO5xtPko/69ye08XpKHkY/GQ+KHeWWyD/HYYsQuBk51vH/unnoeqTZ9Z1QTUU5Udc3juvOlPj2mthNXjF/iwXOHlI9M+kl6cszgNZXVGCR9Sx7/nPy5YR/vn+Zxjgu7XGMiteMLEdx8O6XjiWo7SsOA7gr1clK4/m7G/6fJBdA1f592EmiYTIZ1bQLX5MgtUHr5BBIe7JwvL8N7dBjpSwOcEkGuYCSgvySx4Hg50Oj3Ax8+fHgxUV3ry9GMFPifnl6uUra+RdRbWn3yXSeOdWrrJPllnQmgE/90OganlpgmmdOY7QLcZNutzXQv7QAlW/PPLUGaZHGbS8lfGis98CHtXqstPlSBv3OcEpqkD+e12ZnLwe8tyO2SslM7nMabek7vuyQn8TcFPZd5mqim9na22TD3khMtrY3Ez1rrRYxKciY9pBhBTPTyk4+0MWR8I/8tAUi+qs9MgvS+O1pHnsUTY0g7JdT06/xMNkMsaRif4hxl4u4gvzefJk44P5MPemKcTgJR5p3uUw6T8MfLOJ76A2faQ2eom2bfrlNRs1XqxCnJOeEn6044yHLkTX1N2CS5Unn108aAbbcYnuJAwzFiB/NLnhJh/6ndlNM2P/J+aVPTE3w/f/786mjv4+Pji2O+zEcon3bCeSLL5UzxQrmD+2R6WFLzeY6Lt8uFek5aaTNpTLmRlWhn54zFjk/JHpKvJZrwVG24Dfju+m7TwOl4osonSNFgXFga9gTqaRVvCoJODFgOvGvl3z80kGPgTGCWjvul4DwFRW/PiQasNvVi4rCbfDe+E1GPrkPuSvG/rBhw0xGJtV4+4CPtjBOE+DnxyFUa3ec4pnFNQch5bqtxSW9TIuCUEpokK+uQUhtNV0mW5I+TnF6v8e+fp0TixCfawo4+K5CkPj3pO0l6eD2deKBfNCyiX+6otd9wUP2k36Iwsd+N6xRk0ykX9+mWYHIc0uLmpIt0LZ0mcR+f5Gl9pEDtQXXya+p8KseArTop6WnvCacmYiyedvbdR6ZkuvXhn9PPeDgJSvp3PtqYtpjb2vI6Ka/gIozq87/XfbGLdp0Su8R78pnUFuWgrDufTnnACQZRbi4opImO19nhnfPvi8yNVM5lTp8pQ8L2NN7MM0gpZjD+7WyQlPB0hyEcS/frlpsk3tpuXsoBqIeUk5EnttFipMctb+/h4eH5pUmp+5z0pz44duovXVMfj4/fPynYeaXcCSen+HmS17Q2T/ySbSfbSxgz+WOyOS78i9jH1C79laczuKvu5U51cTxRTUCbjJUKnQB4CkCn/Pj3Vk79Oo9+rbXr8qXEIwXl1M+OzxZkZHjOZ3L2JK/Ll645tYQoGWYLXOnlbbNd15EHbbVJ2yEfrpdLHZ91Jqc+bWMi+ojXb8F3aifV4U4c/TDxoPd2vJnyNTla+TZ+Se6UkLV+RJycN6Cmnez6Zj33bwZNb/cSm0rYx2OSLeA7LqTkq/l4+9ySvFaf/DCZYyLWAlzDhNZfwqfGB/tpWNF8JvXtfJEXypR8h/GE8ia7b/K2ayn+pPLJd3Z41uyC/jHFdNoGefA2W8xl/4yRa+WHN/l38qOkTQtgvmN4qX7TPU+kp6eFJpklj7+3/II6bpTivOOIP3WV+vIF6bRA6uS7QfQdH2fnyctTn9TtFB8mG2x+nHSZYnbT3yn+UCepz4aZu5i+G1u/3nCHtrnLCxoGeFv+JGvx4hPVu7u7V6cL0m+7k9zTMWcusrKOy5TsONlPItpV889ms1OM1vsuPiYZiBWXYEO61sZ/rdf/i+uYmxYxJv91+kG/UfWBdwA+cSCWSQkWwdHJy0/H6nhkaa0vD4SafvPghj0569XVl/+Aokw83uQvn2i67uhMa614hGFaeU7fE+C15Mhl9zHRsYy00ingkT64I+U/lk+rN9KDfoOg4x/TbphockwHN7dVH+N2MsCTn11CQH2Q55Od2XQ/Aau32UDZdxp3fCU7pU7W+jIJbgDndp/snPWoE723CVpLNtLOftMF63rfnrymfgm2asPfWz8t8Lkv8H/k6EdsTwm1P7zMf7ejI1Ded1pIa4GPSYyf6khj4X6lnSj584n/OD9JPw2vUxuSdcJ4joXLzHKXJGopOSPWOGYkSvpNGMY+yEdqNyUvO99u92gffGdZPtyH/ur8T6eTHJdFaefWd3BbAq12NT6OhTwN4Al20ov7TIpHjHkTNiQ/TRPsNE5Jt2xjF0vFo2Nd80/Jm055NHyhvL4rlvyNsrB+o+YnomSnyR+S3+z8wom5HseW9akDlk9xsrXl8TzxvYtj6TrzmvT0brcN7Wa6b/nvTdNiJvMf+fbEM2O3cKflVmnxmWPgvuN+NY0/edlhLGVIL7/H/sSXx2jqxMu5Dae+mFd53033GnefDyU+/UFrJ/oQHU9U0xGspJQWYFqZVIe0M2Rvm59pJCfKoVESbClf6rd9v76+fhEEnBjs/L21N/XZjJxO5P07mDDwNcNN40KD90DJJzs/PX3//2WfP39+fvfkO/Xv/flvZMlbSy4IhAnEk102u2523o7CtHrsh3xwd0D3KRvthgCaykvPKbHe+Rllcv0nH0jyTskB2+F4nSRH5LsFqqQ31w95mE4VJDkok/vGZDPc5Wk25byxL09U0+Q16TLx7L6t/xUkf/Lv6Zigt59OqOz8J40px5XjlvrWd+eNp1ZcD5cE2dSnt9VkTP55KSV9+7tfp/8RWyefTPbF/iccp26nxIv2QnmIL23RQ/3opwRaXNEOD/+nMfHgekmY5Nj8/+Pt33os6bLzPDQyK7Pq62Z3i2yJB9GCJNOwfEfA//9P+MKAAQuyvLFpaZOiRJGt7q6qrMrcF1+PrCeffN8RkdW0JrCw1oqYMec4vmPMQ0S02M2224SZ5Z/w278tJz7UhCVhPHXla+zL/u88wvG42TrpNW2tNLny2jRhmTDvzL83vD2jsdl76m/z0auY75jutrd4aftlPeZyc6zdujfX8kFJYyd+eNEmH/K3ydTXpRwo5RitnbmWuwvozymmpOtdL+Vp7XMVD25ubiI9Z3aXcMw5znG83slhmzGtyQ5I91tj2pveozrCaDMECYQaOBv87BAsm8O5XbafAsdmnC7TRuLRtFmBUzcFjbmuJQdsJwFY4rkdO/udZhUpo7OXGpPGqZvkT8ebG6pTsnt3dxcfhjOfdFO9g/MWvJqcfXzaoq22VX72y/+28xQILMPUbgKvtjpwHPs9gVuyw4SD96SbnsZzop08pDYSbVdw5Tjyfbnud6NnS5rMI5M21tswxjQkIG/BvSUljeami81utj5sJ0N7W5WZtoyFk6hyQOBr+DsNUDf9pGuv6DR9G5PPrjG2b8U00Rba674Sr1vfZ3JKvFB2tuFt23Zrx8W8eHWJ1/Ma2k6jgTsPWM8TwbbdiTUT32ZgyoFqesjRWSxtE3z0h3Sd9dnkmErCH7ZDv+dA1XbePsMXfcS20fID6tA0NR9sMc1tO95bJ0keljuLddHw7WohrW132NVY2uKZ66ecqMWizeZMS9IR4wAHqmyPORYXHuhX6VVMbsP8tjyhye2ssB3jRsorr+Czr5niXQPeIeJYZpoan8lPGv9b7tBs/y3f8ztNGJPGNEHRyuWBanuZbCo0ThK+Of+02RLwzSDayshxvH5/0FUezEvqOynDYExlNMMjTRyQtf7MYwP5FPxTmy0xI5AksB3eCUjmaa7n6uiAG+V0f39/PD09PQ9UeQ1n3tJDmxxUW1BzSbI0f21LSwoIPMbkYI552zcBuyVv1ju38iSf8i4AFsvE73j1LLnl5oSrnXf/foLkpptkp82+aANp29gGoAysvMa0ue80SGMxKLPwurRKQdtOCV1KCIefRCOvb68F2RIb006fbxidtnQx2U/Yd1ZSgpKSAX7zHGWfEoJEy/gw+TdNyWbox23C6Epb1kXy9SaT1rZ5N74k36fvNpt2DLAeXGiv8/FqX4pLCetJxzZRQf7Zlp8S3lYH3Ubqx3Js+ku4tMnWdX2sDYRGHnydl/Mr6ptPV9121ZxhxRW/MW/+uD5x3u2Z9y2mJHm6nNG22bZts/lCkovpb98briT7a3Y0bTY7n5jBhYWWF01xDsEV05ZjmAbLq8mQ/0mD742kradrKJ828WVZXS3NXuxXCTtvbr4tDFJ/bSfJZtM8b3leifv2h+PI8rN9mP/BFT8w66x81z2qm9PztwGrOf+URPgGCm5r/jNZbKP51JcDun+nfts5/t5WUac40fZqbjOWJoONdrdh2TgBSElQAoEkAwIWHZIDqsTP9MEV/JHT1G9JQQI/05dmrOhYCYzteAbc9A5Z0nhmy9ZN8g/+TnUsw3Zt+n+2gnJWzoLx1euSH6Y2HYBagE722/y/ycm+6G+3f4X3qTO+MPfTMBi5D+ppk8uWnKRCPk2X+99sMz2V3G3wmo1u68LHTH9LCo6jbxMlDc22Ul/8nehs/9OxmTDasHTT4eav1qt5bROfU9+rCu7PsjxbBW0Jj+OJMZZ9nPlkw0y3wdjk5ClhbWsv2fAZ/+24sSvx5HbSwJCDiu2BNPQX+17yY+cKzX+32GQ+ff3ZZN8WSxPWp+OtnvsyXQlj7GP+3tpu5SwGJztlfDCPbReMfxMP+KTWeXZCi0/H8XpRiJPx/O8JeudqbnfzPZ7ntVwoaHjQ4rjj35lPJx00P0t+nvQxddgv6TJuN5tvdF3BVMuEvkn6XN/9e3Liv8tAlUZ6NoOZrjUzU4Zo3mx7pd3tvK+foNu2rZiWs375YWDndhcrdku46Kjbwwk2+aRzZ0Fv+iaQTL0BKzutZ9McwGikx/Ht/bC3t7fHw8PDMwAOmBBQvEpGuszrfE+fswLgLSWkMfEwdNzf3z+/lJp1kkyP43j1QJv5piwou7aa3sAylbSSYHm04iQtJSCWL8s/hq9v22ZaW0l2prv5M2kZDLCfpnZTW3ONbSL5e6OTNA3mjd0kO5j+vDqfdms0+0mBkf8pl0RvCr7sz7sc7K8Ns9rqQMMT0sp6WxkcI1Z7JaDhaKIhxRDTktpLWEQ52abSClhKBJLcGg2tbkpQGI9SP/aL1ucWh4ZPb392H56c2XzccSTpyDjo9m3jltOW0Fkmvpb/m3y3OJD8L+FFmgBI9CTb8sBi8zPbahrEbHEm8T2/p2/6Im3zqv83/G1lbMN47sl5x7KWO57FZvPl60zXlhe5/zQBb3qSzUwuxIf8GRNtJ7y3m/d+ux5tyvY1cY4xL5VGO/PK+U26+b35Oe2Px5PcHSedE3gHXFqIavyxj7HJFI9t54lX+1LLm0yb8x6vphpjiL1pVZ0P17tS3rT118KY/1si75KE2uob7Fqg20A9GdmWaLRguAUmOspxvHS0tPVgMwoDEcHwStCfY/OEYzuHgwlL2wJEepKOKFvykwyRs2mUFdtKEwnWm2U1/xsQmB47HQfM/lhWDCqpn+HBs4kG5jP7TyXNlnKGLfHL/i3PCYTH/QABAABJREFUJqMEgvzeknzbs88l30/+Nd8NY0ZnlLMf2GD6yHvzpamX7P7MByk//0+8n+HL+AcDHdvkiv20k1bJpjhgJnxNPFiG1huD19QnBjV67u5ehiDabJLL1ZJ05H42WZg/yjjh01nZYszQkWbKTQ99vvXR7JP6SbjqJJKfqz5ue3IM8vHUxhTT1nCLPutvx6UW75MdJFya6xoupjot3iffa7rb8gX2M3hhmSebS3JOMkk+xDyDWNVyi+QvyQbahATtcJN/0kfDW8sulcfHl6/qYcxPdpS+GwZttA0Plr/tec613Gz7UF/c5jsDvPv7++en0TMWTGydAekMRP0QsqmTcIV8eiDNvGsbqJJHLzjMgJUD1Q2Dm07OdOX2bHf2Z8fM9G3+zCt9LN1W1XKOlGOYnw2Tkw96Mowxxjlw8/sr5fJA1TOmdlYLkHUdVFogoMM1wE6Azm/3t4HeNrAyqDYgSAOENDPeAl46lj5zrvHtPrlaREAzMKUV35as+EFGSc5thcR1Nqfx+bNBVZJlspFmr3Y2A0GabDAdtive+5Rm36zbrWz2bNnxeNKnJz+2Ngx0lG36vkp3Kg2k0yw9wZCzi2Pz6UmCKUil4M36LQGhzyU+7Xf8nRKXTTYcvCScMpYmu0/9XAkWnrlN8nAbjgtTp9lX22Fgeq8U9uE4tOmZ9KRimtJ/09Gwqvl949l24/qtblrxdxKRMGtw3rQm2Vyxoc0XEv/871iTJpeTrFs7SfbJTtuuiETnVt5qv8eR7/tyW6bZvnjFjvkMDMu5+W76ToOd5tP+nPlh8rGN1yvYlya6Ew1ug7i2YdT32Ee7Jvmur28+2PAu5T18heAMTrmSen9//9wfV07ne3ta9tnDOEmLafCulxb/bH9nA9VtsSPpI9E9fTdb2Nq7Uqwz8up8yP7icqX/MxzfrksPaSOmMP80L1fL5YHqb37zm+cObFhcYvejql28xczbRNIKG383p3S5YmwGNvfh1UQP4DgA+fr16zPf5I/Kc5vJWThQbwPcxLedhasFdnjzfDZ7NXQRfNKM2Rii9WED9gy3r01JiGmm0XsQmBJTyoXfToRm++WA3Gx/ofwoi0+fPr0alPKpkW2QnXRBnq8EMX43nXlGaxugpgTB8p06V3ZRuB3yta3Op2CaBqrTzvgbX6XB4HSWpNqPWiKz8UV6GEjIj3Xsa1MAJm2cfGIdy8+0midPBrZrW3Gb9rNmu8aglgCPDyf5+5htxX7vAGr6t50OzZ5Z3O620rnp2rwZv2nXW/+bT5I/PrAuYUTT4VkCtdnkFsu2WJhiZrqecSH5vXkzX4n+tySZW3LquGVdbTudGOv4O/HAvrlSP8dt6/N7vttkAHmwvFIsIO3Nlpq8kp43uzuO/mAXtmc5NnzhN3OMZOdndnPFfpzP+FxqnzL3ooTrNLnNYI5bez98+PBiRXVw1Xnf58+fnz8fP36MOdAWb4c23v86dMw38+mUu7g9fzzYdRvO5X08vXWCOX+ybduasajt7rCOku7n492SzivSIlPDTtpNmmBKcSflZOaJMqAeU9tXypu2/pIgJohDgBltg1USexyvHXUDuylbwtbq8b9XC9K5cVC346BHo/G1lkEymg3MEw+pJMC1Ebl/Dk7nvwPPnKODud6cH9BsA+w0WCIQOKFM8km88pqzIOL2LZehg/qlHuc/Adsg7T35po10p6C78T51ec1mYwmoWgJCn7hyXZK3aTzTWUp8SA8DWgLNpM8WhBo9yVaTjNhnWn037dZN88eNDp9rdDXsfGtpic1Z4Eu2kuz+Kn1bfbfrwJn0QR62bWipn/S/YdSVdhpfrMtriI38vV23xRfKICU1Q19KJs4SqbOY364lbZterthRs9HtuoRhbC99b+22nCbR436T3N1P6s+27v4227wis7NYlfo70+lZrL9aGLfSuTP8In/pWKOpxb/U/1bsVy2fOY7Xq7utn0QXMbLFpinMf3i/6ZcvX54HqQ8PDy/uQU07yEz7zc3LJwrPYJUruMYR5mUpFqaBqrHFmJcm5/jZdnJctdNm/2+JFTzHMQllm+x062eudT7h8+zDtAwdfrbGFI6FbJetz1a+a+vvgMIk8KN8r8idzaAfxzeGmzDOwIXtp378rjXXn37eIryhmQ/SYbvcgjCfrXyPkVwF+Jubm+dJhq9fv76YZZrPbLU4juPFMn7S39PT03F/f/+8zePu7u6VPEjTfBPADBA3Nzcvnnhqvs5+m99mC8fxcoLCIHQcL5/Aent7+8yjZ+Vmu8t8EwDTwGhkS3q2megpnkU0ny3AjJxbEmr5eOYxATQxgL9Tssp+TLd/p8BiG52Bagum1rUfpmX8OitbckY+rUfrNA2aKOP5PWVLHFMSstHo+q0tt7lhdbKNkW8b9BzH/ioo95100H7PZJu3H224yQmloX2+U8KbkpOWEGy2lXhr+pjYOudoS5RD6892bx7SkzinpElc9kn6kz4YNxLu8DrycZZkbTi5xYnUjn9fyT3MT+MlyaXRnvTe9JraS7yw3SQXY4Q/ZzsuLDP6jNvk8yiS3BqtZ3JivxOPmi6nbsIt0kJ/u1KM8Y3mLTdr/5Ou7Vfkfdsx5dVmP3/DNDNHm2OT733+/Pn48uXL8fHjx+dB6wxUKd8pxOTJM/3hQDXhR9pJZH/mCmrClTSQTvfPUl8bBjjHa7j0+5TpM+UNlLVt4ziOV5ieaLRNJhttOzymLp8DQvwffTgHmrqeKDkrb37qbwJWnjN42ZETcWSkPVmMxtZAy3SYFraZjC8B3dngI9HhrRh+kvGUFsi235YJeU9yScZq4xmgmEGZt16YXhrhvP/0OI4XQckgyk9aebRu2CfbTL8pe+t66nowxBVv0uBrh8bpj7NxTvhIf7Il0zvbxZNttOCW7NXXtKDcAmNLokZOpqXJyrbqb4KqrzEutGQs0Wi7oH06gHo1f+NlW6Gjb2wrqo2PlMS0gNgSvBYE+N36I56yDq/z4JK0vXv3Lr6sPWFrkm8LwImPhJPEIs+ik5/pj77gd0WSxrSrgPaV+OX1Z/i+JQtOTHx9w4oUo8g32zZmUS7W0eg50ZOwibQk2WxysZ5SfGv4lWzbds7z7DvRk/rafPA4+mt+tvOJrtR36q8dM71NT6kkHs+wJdmm/TjZy1wzv88wL/lJooV9Wg7NntJEqa91SfX4f5u0a/Q2O7cdJzk0TJriAYQHEtOGn9Q7/c5AdQanc8uTMaTJlROKXDXl/bFDu/PFJseElTxGO/ItDpzIT4O6pFvH3aEn5cgJn6lD67v5crMzYke7PuHCGX8pntlGkj16hfz+/v55HMH7hK2nq+XyQHVrmET7PjHP5mxgR8Bzvw7CDcgccBtQJ+NPQOEgTgNtgdugS0Wn0uRqI2HylPizjig780Z5Pj4+vkjsj+N48ZLnuS4lxfyf9s6nF4gTNPx0Yb+LNCU9LgbpVDfNuG6BjUDgFZc0uE56awGz8ZWSxaTPZv8pKTsLsg7ObykJEzZ92Z55rAWbJj/2l/phkDSoJx37+tROmlAjjW1wmmRsjLJuky3wOtKXjlu+tlf3ubXRjg0WzoSP296wt/GVdNFiT5Nt4tXJwraystHcSpJdimmp/SaPhLPmN8WhFouGdw9U3dbWb4p5rT/ysiVUv29x/y22N307fiSfaPqd783HU5wx/Wf+aPpS25a9+b3i08eRd8Jtukt4nGR61t6W27j99J99NnmYZtPj1TzS0uJmi8XGHcus4Zrbol83LG98TkmDVA/Qn55e5l+cjOdAdW55Yr6R+kvx0ztg0oKIMcq8WgaO8SlfTvfip2d3nPnI5tObj0wfqa02RjIPaWJrjrmNxsvVsl1r2dN3OFCd+515r/OUqwt/U77rPaoJbKh4bpv0o64JBslIKYA5zlcYeLBApaV3Z9IAE9BQ4XTQZwHhZu+5bgZYs09/uydxnJRbF88SpDnP19zYcJIDO4jZwL0yPWXut3x6ejo+f/58fPr06VUiTqAhLwY8D2ZHdzTulDSmAW17KbT5nskRO5Dl2lbjbRPzuyW37H/00/rk/8aD+08gn/hIW3tbgE9lmzyxbszLXE979pMkp/ApfMl+Ut8O9B5UWsbpvcOpvulPfZs/+8AWmFIy6qQt8TrnnSil5CrRmvwr0WP+04r50Hm2mst2LHsnaKn9rbC9KxMAxontYWaNJiYObrfJ29cQg9tqZOLV7SdZW8dTUiwg5ls+TS7TD29daf6WkifT/pYkzkmM43PqIyU7qQ/jkzF96qeEceTAHKT5E9s2zbRl0pNiwsbL75N8tjJ6TitDpivxttkAYyQfuDn1E1al1ZsN2zdMnbLZytSn/w7NzW7ndxuIbvSwnybXhC+J73SdY9Xkn7wP1G8zGLzkMzfoJ8x5N56Zt3iL8QxYvKKa8tW0Sks8JV1PTz/mrVPS5G3KlfhsEdKf4stZvJljrjdlMI22T3qd71HfaXyR/KHZavMPx3f7wfRNGlnS05V/+OGH4/3798f79++fB6r2Z9J3lgdMefPDlK4kaolhJ7VXZpmvzHK4TQuj0boFECemVpLPb0BFMHfwZV8ESF57c/P6lT1um+eSkzrBsZPZ+WbgmtpOAGhQave5Tlt01umTqzMtkBsUvC3XNtNAw21ZtzyebClNflCOzQmp6xZkXZJdMKE0PwSfNMA3Lckvmj8mwOO5lkS1gLbpxbbQJoLStY1Gy8+/fV3yebZFnzYdqQ/7vfnlhEcKQA0vk9zOMJPBY3hJbfEYaWnyMS++njSbrvTfWJvkkSaQ0iSX+24yth5czzpqNmR+jf2pjuuzfeM46zbfSQnOVVwgHYPRjmGky/R6gsGySthJGijvDV+aPKcMv8nnzvQw16dJrRQrmm5cf8OyKWmVJOVNLa9pk3sJe32MuqHsUqy0PSQeJo9K+eNZXCGmkQZjVCv0afPnfKZNuPMa/r69vX2V8PP85M2OZazX8JztNPtP13OiiXwR802PnwLeBkZn/jxy4yCmrZ5Of4mmJMtWbOu81Y513I8fgumcyLymtpIuHF8bpvq6NFClnVFfaeGE7V3xC9Y1bU2vLNSrdfv4+O05LqQnxaUr5c0DVSdnCfxmho4EcQ9zS1JS8Ev1zgCaTp6E7AQkBQ0aC2my4REAvfrTZJX48mzmHB+DtJzNw7RhBzMPBiAa/ZxP79EjrRO4OUt6f3//4gXRHLRuNE377969e0FHSiZ8zO/s8ux4SpS4naWBb9JLCpTWYwPUlCikoOX6I2cPPBKQJfmkVWqWNplgmZBe68NgmQB4CzSpLdOc/m8JXgssiTYe53nrJSVTyZ5pJwncTT/llwKs+2gypR9zldp8pFV6yp5JS6LXgewqFm/YzuvTsW1yNOFDs5VGj+VsO051p05rk3JwO81+fb4lSSnAG9OT7ze7SzIf+hnD0sNXfE2KUynpd7E8nOhZts3HU7uTj2yDd9un7Z36ME0JH1PbCWe23/Z1fqdBLHlwLuJ2t9VC12/ytd0nu0z9JR9mm81Ok09s/sf+N/wZ+vygyWaz7j/5+pR59gdX7ux7xJ3GS7MBy5Z8eAVyCjFhVlGbzSY9OObRZzlQ9QAmrZ622xCoB5dmi7Z5ysb1uErMhRlfs+GW63mgmeTVcjlen3yT2G6+E36lYl5SrEt5s/VNutPi1OiV4wjSapu7Ui4PVGdpPQGkGXp6enpmeAQxT3VNDsjj24pfAzobRwIs/m5OviUAnn1x8m/jdEkDkrmOfHoQ57qUfzKezcHsMA4Aac++Z2XdHu1ijHWe3sYtAQmwkt4TSLbj0y8f6JRWVH3N/G6r4SmIOkFJAGFApGynPw8wvSpq3cy7vJLt8j5iBwC3xRXrqbdNOg299g3rwW1SFulDmpK92/fbQD7ZgnXY9Od6rG/duV/z4msb/6b9zH6Ip8RStuOSVizIO+slPl0n+V+TyaaHK3VSsU+nyRnXT75s3+Bkgq9Pq9G2G8uFx8gz7SVdm3hhm/TDs5Jiq0vyz81nSc/t7e2rlQf242Rnjl0dEE1fzQ8tE9v2ZstvSYh4fdud03w76XIK7aol+ZTXcXyLDZvMzB/jt5N/4i3lmXRjm002nHx7w8G5Nq1eWV7pv49v9nEcL1dzm7zm/BX7PI6X+QX5aTZGuvhmhS1+pWNJNx4YzTdvsZkyk/mc1OdDLbc+ec6rtMOXY1Ub6HM103ZqzHSOk+Kv7ci+4NuR2KdlMe3NAkHDOOYxzmHaQJW0txhFW2JfzMVHdunWFsolTZKnQnqoW/JJ+TE3vb29fR7XjY48SZ7yBrdzpbx5RTUFDBvKEDPn20pICuL8tMHd1KUjJacgnaaZTuZEkAKkE49hEAAJ1DSYRKO/afBsr9GfHLkFiSuJ0vZJNKc2pnDld1Z1ZraK4DkJj4Pm1m8KAk1OWzLbErmzBI+TL4meLeiw3eQzbMMyoB9sCZptgtdxME47Jr0pOW90pyS/2S0D2hXgpA7pZ0MrQTsBIIuTq3b+rB7rJ1rPAmfzPfKRrk2J60YP6UqTibzGOG0a0kC2rdCc0UI5b3WvtGnsTD7Ivvl9HDvOtn7Ozjc6rdOtr4ZFLpu92p7527Ftw76WpKT+Ur0rvtRKasvxtdGXbJq/acMt3pG3zbbO+DVGb9faTujvKZalOGk623fDosTHZmcbP+l/w6HUj/XSkl3WdZvJjq/a5RW9N58nPc77Gg6cxbGN7hZ7fB1lyQUXDhYTrQnHvGLKhQcPUK1LDozbfZdDx7TRJlqSHDbZJptqEwzNZppPkHevRj49vbwNhnKhzBs+W3/87Ymos3iYzl/xRf7nANN5qfXTxn0tj9jKd71H1YXEzgCF239ncMJjZK6Vq8G+zdAdx0ujpzC5uscVv7mGbY9zvX///oWzzZaBtL3KhmXHZD926rQykvhzUrltaWrGTx43vdCI0/YD9j2PMJ9BquXuh2o15zgbuPu4z1keaRYnBbRkQ9bbfFoyYmA3gPG45cjtyXyKtttuAW7Oz0rzbKt+enp6ngGbldrp0zxvfPGb8nBQGf78wK05b5lsNkpw5hP8kl4anc3OriQzKRFK70luycIU+xqvo020Wf4UYI1pprtdbzqGJ8uLNPtpjFdLS0jcF+vzOIM+r2m+kdrd8Nn9pmA6bTUeEn42nEv/j6M/cXXjx9dzRcD4YvrOEiTXc1spvhAXUzLj+gmD+d3spuGD9dxuZdns72pp8XWOcTJ7Slutacmu+zIfPsf+k//P91nMI30pFiQMc3w7ozvtBnJCnrDabbb4YfrSN0uz17PieJn69nslWW/bceeS5OjzHsDwNikOFBvt1uXca5oeysT3n04709fDw8Pzq274oKb0KkPz7RzHvz0hO/1PvjN0OPdO8ff+/v5VLpLGA9SJt4ozt230WnfErLSTzMebn5/lLg2/XdrkQYqVHoCn79QfMflquTxQdcIwHVpgs5pGQc9AlQbD4gEJE2c7TaKHx9KWg/mdBg1DI/t0YsFvDsQnKbAS0/YbAkUDmisAxN/cJmCD9v7w1l7S4ZawuE4KZJa3+7LzUr8NlNpv05QSs5aY+9qxX69i2Q5tr04IaGN8sIH7arwn4NoCCftJfjH28Pj4+Bw0+KTnFCQb8FGfDiYOHE6+2nnWaz48A9PhgUF3A/FUki2lpK1hiHcIpMFhKmc7REhXWuV2ECM9nvwhHU5avDraeDYvyYcpn2Qz9I1tu8+mM9PW9Jz4SPi0Bf7U9tVjGy3Nnvy7teV+vQrSEgjb95yfYy3ebMnN5jeJnyQ38+brm0yotzYRmT6WBeNmyyVMZ9LjFq997fze8ouNTvvuFZ/Zntx8HN+eg9B0bbo2W00Y6usnFiUbss7SLg7GHfbriZmGRel3ovlsB1CzA8bx1Gfrt+3oS220CTbKyv7ggaknS7zDZ2zn9vbHW6vmzR3ztN55HglXVG9ubl4s5Hz9+vV5oPrly5fnJwaTliT/tLjhXOM4Xr9i0Xn3tmq7yTfF9bmOtPihockmrM90PulweGuLW5ZZyxVSX8kPKFvjPO2KeYknOoynLmy3xYpWLg9UCQBnyn96evkgEa48pqBhgONMRgJzC5pG1GYkt6RhFGHHmDbZ/vA2AJ9Ag6sPaeYqzSakRMmgx+KZvzl2Fsh8zAlxCi5nQfuqsZkG6psrOXN+ngg3dNKJLS8DBttKiQyLgbGtMKaEI9moZ9jMX1pJTMljAprkdw7UbvM4vs0s3t3dPQ/y0uSJ+d10yODBkujZfHLO8cFc9MPR3fjSvGycr4ZioE2gno772PQ1cksTFmlguAWnRMMVIG/XboFqs/0pzQfYZkuCWptzXWqLbWx41mg5w236wJRka8bDxNP8bmWTG2loetlkdIahjXafa+0lrGltz3faOXMc+WEwV2LBFo9arDYvw3t6qvOW1FkW7VjiIdHS+uD/tHJqW3BfxAf6jOPY2Qqc9ZzonPaZAzS+Uj6QaG/0tHIW45Kt8ff8T7u0Ej5sfnjVRxIdx/F6weVMTslvzHOylenHk1XHkXe7Jd8wf6w//HP19P7+/vm1IxP/PAlPv+QglfE66ZR8OvduA8AW11KeeGaXyd89sZ7OcRdm0iFppWy3OGhfb3h2Fhddn/ZEOvhJNPt68pFKOp543SaUUnnzimorHIxx9N1mOVsfW0DYEhcaOY0ozcZc6T8FZQ+SuO3Pgp/EegYDXIltWxenXz60wrRxpY5lM+pUzpLNlMRt9VKfdA5voxgd8QXBlP3T09OLgchxvHwX1uiCTkYAII1tSwX7IgCl5JJ9+uEDSTebHbZ+2qDHOuNEyBQ/kp6DqZHd4+O37TczUJ3V1ZZ8sqQJAicuyS/5mzogX1OPNjEDV/b/+Ph4fPjw4dW2ovRC70Sv7SQV85RkmmbAnWBNSaA8xzwrzEDia+Y6J1T2mzO+tqStBX8/LZt1kzzNxyYL/k9tM3ExjT7vicZ0rRPzM7mZvy2JbDhg/tjW1WDdSluh8+90bPo/ixfspyW5bLP1mRJO/+Y1xuCzW23a9amtpvsWd033tqqZ2jANraSJ0tRnozutBm55QYo5XmFLvJi2+c38hTuJGGvdd2uTiwGuyxhqvycPbceQ47HbsMyd/5nWJtvm45SZsc3tbbmZP0mOZ3r3gItx+MOHD885Gp/cO7Hg48ePzzHi8+fPx5cvX46PHz8eDw8Px+fPn593QHmBJvkF483Nzc2L1drku8nOU67W+G+y4njG36aFts3crGGE+0kxb/ILx53G93HkV8xZ17Q1+1B63eG04QUB68I4mezy9ymXB6pnJSlyMyI/QXALFmw3rUad9cs+5hwFTrCikRzHyyfDtv78n8brJ72dGcQc5zfbH5rOki3Te5YUJLlvxvWW5Ip6pzzPHIp8U0emj98t6Kb+/L0NVFM7pNfXpEFnkxntZdpq9tB06KB3lijRzrlymRIHA3GSXfKHs9JA2CUlKLzvdoIC5Za+6RMbTrQEhr67+VUKTCnguZ10Da/1QMHXJtxI59Kqjq+5OjOd+jHdCduTnZCOlFwmm2N722qVsTnFnTP+Nt9PfW4ycBuN18YLy8bz1qZ9xiW11eLDmc1v8mn9X01uzuJZwuQtiUp247jDWHZ2rX8nupMfbPh4hd+kZ8v7TC+NvhQbUtl03GKF297qGavZF+Obr3GsTwNVL1IkzDDNG28Jd5J8ruY183uzjc2+m39bPmyL8X/kw51Zs83348ePL3Y9Mf6Oblo/pHueqWF75rev9UT1/G5Y6zYSLqSFo21CyTF0rvG55jtn2JfwtuUh9qPW3hZXGDdTv9YR5XNlAv6s/F4PU2qGnt5HRcNj/Xfv3r24kXnOJUbYdmPUIDOfNGM1/ft9T2w7PRRqigdOm6yY6NqA2gxx420z0nYN+7oCtD53llht5xJQmAYmmSkxpn444/b09PJBVdP2W+RqGtJ2jiR7gm7bpjL9T9CkL3DCwQ9NMi88luRDUHh6+vZAgaEnPXHPW4zMt+1767eBGK+bY222krsQrBPar2kcfqf+tEXfdaA0jfR7r4j5vXS89swXk2z4v+GSC+lxsa27Pbdpvlw3rUon+Tnh4uCyJRcsaeVz6tJPtsSkraa0PmkzW/KTeGzn2woj5dcS2c0mWdd12gO83L552zAw2S3baklKsjl+t+tpe2d+Zd8cTKP8Nt/xJyVzpmPLR7ijp/lG4nmb9NnscYtbc22LQbbhpFdfwxjK/ptMEp1nOdoVnpIcPSHsnDDFbPr7XDc7diw79s/47cLYsRXHGNPFOi132WR4Jkdf03w7fY7jeLFjaV5H+PT0bYDKZ0bwGFfgpo/R13yog+lr2pt8wHReKZSh8xxiAOny9X61zXF82wk4+UWLX9QjdZtuWUg68rkzDE82v8mG8m7xx+/NTn6QMHSKJ4p4Pk1Eb+XyQLUFayqdIJC2YfCGaibUwxSTscScgTglofye653MDEjN76lPUGpAbF7nOAHd2yzHidNWBPI61zaAJi3p/VDWiXW1JZ2Jt9YO+2CQoEy8IuMVYIJQO58ePGUQMBhyu09LtlOZoDSDR5Zki00v6fckVWOD1HOjqR2jHEgnH2zAh31RLgwCE0imHdubZ5kbbU0O22fap/85KI6MEg/pEfsp8bR/Dq/Jv9PsOvHMvDe9cRBEOiyXzcdsf3ONJ/mME9O3Z71NLydHrMMWZKnvNLhu/mWbbRhtmbUgbb2Zz624nbQixnq+Jsmj+QKv47mUDDY62K5txX2eJXBbHGhtGe+S7dNWEr/TX6K/ydnH7Yu2lTRJyb6P4/X9g8aJlnO0RLQda9fb/xyDPWFE2lvs5e+Epw17XZLevQpknki3j7nthhOOzywJJ9kPsZp8J75YWD/lLux/2iCPXGgwPb7W+jZvjec0kcz+msyNg46BiWbLLrXJtw+QNw9KvT3UuuHglE8NZux/fHx8zmGmbZeEybRR5oDG/KYjx6aRRZJZkqHjePKlwTLqKNkAMS3FtYbbKWfZ/DJhk2WRfJ980SY8KZsWflI8vFJ+r62/iYE2yBuh82m0HHEbdNgW+0iCT4LmsZkB4T1vbXbLfGxJWwv+dDKvYpGuprjkFMmxfIx1k4xcWK8ZZWuP4GPQ5wAyrRQOLZxd8uz009OPr7lJPKa2Nl7PAvWZnEhbS1wSnY0ODgzPAMnBJgX9aWf8KelyG6imwOuBavK7JgvTZ1pTosHrxy54jrbCe2s3/VN2KVFlv0OLn+SX+OJ3k4f9d3Tga1s/yR44sGxJxnw32Sddp5L8xdh05lPJFxgE3Xb6fwW3El+t//bfNPn85p+tJHvbcJ71mn21JOqsuI4TWtJrHbNe0+l8WybmJ51ncZvJLlISlTDa7U4d+tuGRe43/U+TDEk3Z3iY5LHZNktbFWy+mWS+2dAmE2JQm9A0TpBvx6DN7v3hk+7tR4me43j50CVOwiYdUMdNDgl/reMZnIwNpnykYXbTfZN3qr/5d4sh1AcXRZgHc8uvB9Ye3N/c3Dzf4zr3vfrVbtPOzc3Nq0lo09RyK9N4NX4Y3y0PYwblmMYS8+0VS2Prltt5EYb0m5ZGj3OC1o77Jx2pL7ZpP6Z8aacJt6+WywNVP7wnEX4cr0f1Q+QInMkW96/74SkJgOwIo8xJWBNgHcfxvM+dfAw96bUOx3G8MJRxVg9WDW5zDbcupCceb4kUQSMFAK+CmW9f67INlp0Iky4bF3XrrdMzMcCBRJv1Zp8GjSSzZFukMwUL31donZ0dS8XyS7SajikbwLleA1DbjlcZnbDQNr2yn8Bs6pvm8ZfZkcAZZgIv+06TQ20waDpTgOfuhCTTKU5KrDv6ztBzd3f3qs3j+PZeOD5MiDKZ/5zAYX+Wue0kydlyTME3+Qdtztsj2RbboY7IC4v9Ymj1bgjbTksW+Pss4UyycCBO2H8cxytbSavMqaSksiUCTmatq7nODz1r/u/Ey205kdpsycUJumOFJxqT3ZH2ScQTvib6kswTJrZk0zkA63HguMnmTE6eQGxxgrGq9ZN8lzZAfSQ8TrZA2jce7Ys+dxzfngjvNjZ/bLd3UXaD1Vt8ZB5nHh0nKCvGoLagYZ90Hcs7ybTpgzJMdsq8kXLmsWbXXpE0XX6TgO2ENpvkY7qpu7Td1YswPp76mxXTeaWN7cXvGx06vKBzd3f3gjfLfuxne2iSdZOK7dz9TV+zIDDXzOrw8MW8f64jP20M4/MpDpjWwRDL1PGptd14T3JrcWoKx3ktXvD7LPa6fNdTf50c8FgCFM9eDUNMAgkuSZDDXKIlbcdo9I/CHKwdeN1OcpYEWOM0Blv2vcnXtNhAtmIDTtduRmk5ka/5bUPjDNhxvDTYtJLcHCXpL818057ag22aY7Z67ViTDX8nPaXAZzrMY5KB20xgysFcAkPWo20mQNkCtr/p026Hds4g6cSMvnEcLxNk023gTzscpo3pj6vMBu4kZ/uq6zffcbJjDPFALmFASpya7291/HGS1QqTj9S2/ydfsFybP9neNrxreNt8sfHFcx74Tpk4wgQsTU5u8mHb/nYbyafNZzqe9J9k6pL0l/yQ8dgDNdsh2279XjlO/zNPnlg4s+Uznn3t6DjZXkruWtxoMkiyS3JJmN/ib+Ix2VLDvCvFuOf421ahz+LwVrdhbfpvW7B+2+SB5dHin883PNpyjNTG1sdx5O3UlD9v80l9Ut7myZO/5ivxlyaLKUtOcg5tflJwytdMz0wE85NoTDJj2ez7TP4btowMBh/H9j0p2+zcNCZM2WKer28f92ndbfE0xdXUHtu8WlIsvHr9m9+jOh0auDYQs+MNo3zyrx3VzubASpr80JQkIAqGbQ59Z/dazrVMpp1wpuRm5DDHx7BtlJQBnXrKlS0AlP+8i5Ig5hU38pCCQAMHyoZA4v7SwCM5LPXaAu38Htnw/gZfl1YD2L+DqF97szlPSgzJ91sST/pICkpp5ppPjB7a52l7aRtOCjYbj6NfTuYkX7G/JH5p2+RhAlezT9M/fCawTTImDyNP6s/JVZqY8moir2/8OlEy/s2MqxPQ1kfqi3XYv3GJNLBekxu/20x+CmbTx7Zqs/Fqft23r3c84fWJtjmWdgT5WvfXcH7qJfpJn+ul/kjzWdBOSVrSjftIGJvi9bQ7vtMmGi2n6cOT0S4N23mNB6otjsx3WoFIfbQErtHG863vxN+VhI/tM54mOz1L6ij/ZAvjz43e5P+p/5bbOR46t/OgyH0k29rwgL4y7Sabs384Rp/JkfI0Jmwyc0xj+6aJ51LsN845fvpBRNNWmrimPvw/bbFtH+qBu6sm55zV09naO6uNtG3H83kI0zy/hjsSLbuWzyWdW74JP/1/y4uO4+WK8/BifTV5nY0XGj/mqS0C0mad4215X4sh7jfhMW2X9YhpqY+3lt9roJoGqOm9kYlxX5sY8EwnZzDSaigVfBYwWkDfBDk08H65KVbi1G+BnfS0AJ7kT0NMvLR397FvAkdy7gbMqb+WWPo3+3BQGLuhHbXA60Fbsh0O2CxDB84J4vNJQd2gkBI9JlwtKWozks2XKIO0RZ1BaB5AMGDPJNPgatBOtB5HfviW7WKbUbfeE1/GFU+gpIcmUW7s00DbnpJrukx3w4701F+eT37nNhjMRsaJJra36YrbyeyrKWlKvp0+g7G2uRTMGobMsZYgNNxrMp7/6SFQjjVJ76a99ce4M/JPSUZLMNlXw5LGZ7KpK/QnDLGOGp7Ob9ZJftZ44jn/bvVIY6ObNu7kaBJEXjcTsMYf4waPtcTUJfkAfzsOJBtMPmdbaHhw9jvZs3l0zkC60rd1sm0tJH9tEJT0kvi1LaY+HScTX2dycznLz0YGSW7WZcqf2E6S+fDCidxkU9u7vHmceSqfm5Li6VlxDsQHI82glANV8sA+Rh6To817VvlOdO9ItMwoc08gXSkNa1O83vyYz9JIk3SebDdv9gnbVyumiTJt9s0+m4+YD9sXY6/lkWQ0/bbY0ia3U/nugeocM2iklUkr/CzIGmjZvx00GdPZ7BmPb8aY/qekKyV/W51Ex0Yrz9GIeK7J2nQkuWwB1QDh/tqg0okejxHYkw1tASj1dSXo8vyZHtx2sm3fa5ZmQNlfml1mcEuBKNm0wdCB3YBF/Q1oTHuWS9K1kwzy03xsS7obHpCmNMnSdOOSsGTzK5eUqPB3S1SSL/BckoVx4goWUB70UwbFJGeeSyvNxqn57USjyTXZW6Kd3xufjSbKiphGWj2ZYzqNX667YaR9rcWRJo+EFaluwzv6irFjm/xtOkm+689bSkuEUp8pjqSBqvWy+VKLw7yu4dUVOjf6HRtMMxNKxgG22ZK31neTI31+PrZ1tt3iJdtsO5jYpuOd8SnVNT/833JJ5wnOE81DwuVUTNO0mfDU19iP3QdjZupz+OFW2elvk32TLQdH24OPkiysC9M2z5S5u7s7fvjhh+eB6t3dXX3jwNA0dMxOsHn36tBG2SV8tu1sOcJZLHLb5jnp23JOz/sg32nAamwjzf7eclXHwg2vz7A8+ZlxKZ1L9PEYJxVZ/y3x5bsfpmSC/fTXNBs07aRrbdwuTs7mAUktwU+rKQ70PubEx1uOtseGb7Ruwb8pvhlnkt9Z0PAWWAN+opvbqe04TohMo/s/jtezS2w78ZCSU8vj4eEhys3bR8jDFYe2fMY2Zzu1g0kaXE/7aTXAwHbV8VsgnyD3+Pjjk625pYazqGmGu8k8DaZ9nHQ0OXqQ31aUpm0HKvLofjedpcTkzOb4f/psbVpfgznz34/qJx3+nWxyJhu2Vc+xdcvbdJo37qRI7dtnmt15lj0F9IQD5p90M5lzYGfykvzXkyfWT/IrYjn9k7S7JDvYYhfrpYcpNVklvPUxD5BMH2WXtvj5YS9eEXNSdYYdCasoA/qUE/fBMPLuuOWJIscTP7DGOw2uJkmOccwn2uSqscK4NfL0U8vJg8tge4r5CfP4gCHLyTkBeaXM7Sv2oyR/8sUH4aWBEdulX7S8kb+HXsZgnzvjwbhieVNntuOmC/bBdrZ4axtP9uO2adN8UGfybQ9UWY800O+sl9HNDERn9XTuQZ3jyea4asrBsgfOaeeXJ+bHDyzHMz+2vK/UtfzT4oDtzDhE+c/bK5Kemi25v3+MssVz8pFyLGIZ9dD0kfzK+dD/KyuqZm4ITjMtTkoNJFZ0UlIC4rOtfOm6lFS4jFMZaGhYKfFkMstAPf/bsrcNJoFdc6hk4NaPAZbO7jaSQSVZ8n8a5Jufq0acHGPoT0mtaTPvx/HyQU6jhyQj053aIo2kh4BDP/A17Z5L8tnsksUDPidCaSuP/ebx8fHFBESS6/xvkwleqeE11COT5zZ4Mtgx0eHTatNAdUt6UvGM4MiU9LAt8p4GAE6QWO84jvjCc8rdSbp9wiUFBvs56WtyasdSMbYN328JnI3H1FcKkOm/jzm2bHZAGq4OwqaPFMvY70af/YGxjDobe0mrbVv8Oo7jVQwjj81+nNieySH5XSqpnu018XzFtiwP++u0w++38pQGRraBNGhxu0nWbMeTMKYn2VX7tJyr6d9tpv5arGYs44CI/9tg0JMsaeI3yZXfbZLYGJjiG22FMmh4mmQzxznh5AGNcwbKM9G12Y8nutuEUtNXywGpk/n2Z7by3t/fPz/Nl0+6Hbo5KTT0PTw8vBioMjcz3eQ/5QxXJn2n7pYnMK65JGyxXpjr2dasI05IGYccq6/GSpcNk9nHFjvmnDE4xbGEA9v/aXfaeAtvU77rPap0TO5Vv729fd6jnt5HaFBNbTI5TWBGYfha/+f1rmfH9kifIGwjc1tWih/hbQdMfM9v1tuCajL2BOjz3ZKTzWhasNgSfF5Hox1+Hh+/PYnVs/lMLkZ2Sb6JxySnbSY38doKgddA4+Rg6s8nvUqF9DTAI/9Tb3yAM8mkLwXGCaZpsJdkYMBtMiePTcYOdslnCObpxeGmu8lnA2F/G2taksm6HIQa//ibdTyDnZJFA/dZcpPkbF9owcKlreKkgJloSHLzdaZrC8YpmFI+LYlIH/fRMDDx6P4dS9xXwkPjZUrIkww5ubZhV4svlqdtIfHLtjbb5LGWzEw7qVhu087gpGln2/Od5EaZzODPiX3TfYsFtiUPVJ1XWE5pkpW+vfnOlcIcyTTxXKKJcrccNl3anminvu8xDZ4oSz4QcfLH9pA+xhvKLu3iS7mHdT9xxfqxbFPfrL8NllnPxxwzE/4732AeMQMf7vxg2+TDvBgHzTdXT/l04Rmo8h5U8jQTzKaT9562VV32P3I9w/KUL53FO/aTYg3b3nLERtvoxDsJvGBCPtLkhvl6S3Fek3If98X+fI3tJw1UjyNPiJqPNAi+yuPlgWpi1IkoAYdAbkaTglLwTzM7CQQoFM423dzsW2H8m//TLGyivSknBWuD75ZcbbPbpjElSpb5cbzefku6Eq3tnI2zXZvo9uA/tXulJKAxSHuAdhz53sxtIqXpZZwugZpnFVPgNui2xMs8edY5BRu345lP1uU1aeCbAJPn+QATJmFO5pzwzPUEdF4/38adm5u8QuLgkxIG89AmXFjH9ssAML9ndpl6Se9/4yB8Eurhh/y7NL2RrpGxk6BWkt0cR/YPBjEnwilpMLa2oJswMAUy65GyT++RY3LJ5KDRY94THniipdkM2xwZMQGfeGSsbrHDvsjj/jbOndGYaDbeOTFhn/xNGo25TY7mgXxY19MO7bDxaDxrg44r8rE9JluYYj01mbE98pD8JOVFjAPNJ9nnZvObf17JaaYt3rpFObStpvZZbh9t8jXtzO3Sbrtkg8dxvMDe5IsJ19xuu+Vno5dyTHkYJ20ZK0aOfgK35Zn6TbiXdE09TB7vrdWUjZ/aOw9ydDxPD9ZKdDY7pw5SvkOZ8n/69nnnCske3A5lOvVs7x6ovsXHpqQJokRf49E2SZ5TPpHkn+y7xXvrifKdY86Hmz5T+a4V1VQSo2ZsS0z8P81eu6/57ZkKJrxMCqfOVUM2f2mgemWwlQxjeDwzPidbqT0ea3KdBMKDgSvtubTk6Oz81cQ10XC1/tRrM6aN12a/iSceS3prK/IpkUngnMpcwy2x5Nc2xd8JPMh3s+uWIJNP6ygBmuVHwOIDFNp1WxKQ2nc7LflLOr2acPj42az6BLHBpATUCZvOeE9JiPHiKg+2p5bgGreanNuxK/Sc1dsCauPDK0puK/nh2SBg4zFhcapLupzEXpnYa/HBvnRFron+TYdtcGa8SbHOmNHicJL1WezZ4khLppq/XMkPkh+eFcuinbdte/Bg2ySNZ3jQEmX/Txh6HC/vV5vC20s4+TnXmZcUfzfZ8HhLyK0H+/xZv2d+s8ncJeVzvrf0OF6+Vi8NVFM8bjTbrpuOKcfb22/P4ZgFJ+YFbocD69nm6wciEb/cp38nnXDSa36niT3bYfv27y0ONN0mmTaer+DAGY1nshvb/h7/JT9XbP9qPubSfPpqW981UKVjjTGdjZAT0Hp/vwOWEwPOgnmUb2VxgOpg2BKw5OxvAS/SbvrP2uV58rkZm2XQZiKTTujsrX7iNxn8FgAJUskh22A9FScZ5p91eMx2ZXrTgzLSqnnjhTZn0OLH9jy00abbK3cMgE5ap42x+2Q7POb228ywg0zyn7kmydH100zrtMFZ6qk/25zYP/mlbKybDQyJQ6Y3+easirHfbcax9Tk6SnbCkhKsNtmW7DOV78WyFuSutnOlXEkoLHv7TvLd4/h2z/rYVZoYSXHJvA5NyfdT8sOJHE5OGAP4u01ybUnPloS4Xmqn1U/JBet64iX55pmt0OfSOdLu/74nt/HRBjP+3f4b686wcoufrXBif/pNtt3sNPHoiQ6WhM1JDs4vkmzYZpNJWo2l74x/sq02IdZyphRzzXP6TnRZj5Q9++R3wwPjM+/XnC3vlFHC9MTLW+yr+aFtinGQ2/FJ+1zHFVWuIja5M+ekbCzj9KFcxhaJ6dwG3Sb4tniWJk9SYXv8Htq2CQV+J3pSDtP83uMl20pqq5UtJ2i+67rJ7xLOMrcbO7tS3vx6mi1BsmLSEw5tDAkEbLwGMAt1A9tJ3DeaN6dgAElCpQEymA5/Z8kj+W28pNXBZPhMhMhHAnG2l5IxntuSlRb0p9+RS1rNSLrf2jYdHGRs1/J609ESnbO2Gr8t4Jh3r9Rsq+tzHQdxprMlerRbv3+SfXLAODykp1zTfzgJZB3yWOOfK/zu2/WTHni9ZzGTjPx/tuey76HbTxBPj933/VRpso3fnD1POvYgvtldK9R3C8ZtBab1swW75MfJJq4kWy05SfVS36aVx43FyR6SfCgDJhMp+XbMIh3eeWB6TXvCjWRPCa8S/s93wqetjeN4eU+o5ZEGQg2HzK/LVZ9N8tow3HbA+kmmjc4kGx9L+UujPcVl1yHd6Xpe40mQs4mOMywx74ODiYbWFs8xDvnazWasM7frY21wwjavYk6yh2Y7WzFt3MbLJz+nPpynjkz4bTk7HpGXJGvSl3iyv/P4cVybjGj41+znzBfNG2VhORP7LectDm42R1l5kGx9sCQZOx5bh3Oe93Q7phGD0yIGv40nmwxMa2on+fAZ1qRJi628aaCaDJjL7lMIbCkx2gyECQ8VleqkQO4yNLp+u3fC17I/05B+H8e3rS/DR5rRuRokU7Brjp3A7Ay8eY1BuCV0m2EbfAyCia/NFlqxM8+xxPecazNryTa3knSV+G7XEng8UHX71Ktt1GB9Bfjnt/2BSfz8Pxuozu80QG0+Q16GHwNs4qEFXAc9D1hZx22RHuKNdeN7dpL8k2zTpxXS32Zl3QdpSHy6nldijHdJ9htO2e84KOUgpiV3yV7ShE3jsfmcAyfbIz3pvDHEdu8nW25ynyTpahLQcNnnXMfyajJiApfa2/Rh2qjflKAmHt2O67TY12Tg+J348W/aojEw9dGu32ym1Sef1EOLJ77O32kCxLabBsO23WQ3iU/zyLLxkPyINGy6SNiZ2uW9b/w2TU2P6RjjkuWdJnvShHnSxWC87zudfvmaM34cs3g8Yb15nt/Jj4a3Ntk+PDdft4zPYi/73dpyuykPsI0MDxzM+Vkhbs/lzH/527bmSeaUoySss6/54weODa9cgNgwccMqypW21DDZcuPx5q+sO32kHCSVN71H1QRYkCZ+nNBEOiF59+7di0Rx6nk2iSsb7ofgn96feRznTwkdhbOet4GZxy0geJXqLFDzu5UEerwuzaIR5Nzf0JnAi20ywU0flrQyxKfeTjFoWf82ftOd+j6TL9ujLKctAjava8GPNHKFrgXjJKvjOF7Jx0Gn7U5g3ZQEmIckE26hox23QaoDJ+WTAon5mqd3UxfuOyUtg0FtMMQEYH6nxGJ85MuXLy9mpxkMjGmPj48v3tvLmf70/jfKOAWISUbu7++f+fX71lIyST3QTmkLpMH+lFaA7WfkOdmN+6GsbDserKYAN//TrSAOZqTt8fHx+QEejjUtwLYEjrb++fPn52O2xZQMOMFopQVv+9e025IZ054S5BTLEgabvvEPHnMMp47Ta7FaafpJsfiMzuPYHxhlWbY2rtBNOhP2phjkhPh7+jTOpZhjvzd2TWK79Wt/9LGrZfilnhkTkvxSTHLe1Eo758FqGqQ4jzXupMkx+6xjVcJpYmCb+OX3hiUceKW685sDGebnpjsN6llS7N52WJCXKwOQlFsxth3H8by91/qY9tugftqc98pzYoCY5fyTvG26aPE62VfLybZcaSbG53VA1CnjLHXvfDNNyh5HHgd5YmLaS+O7ZBeTD9n3fWzDza28eUWVCvWTz7wqlAJYmpVrCa4TrtSmDZMf0sritt0W6aCyCWLTzhZwHQASKF8tNqSUzLeSJhEMDMlxLQOuENiBLTPr4S2JSQpoU5Lum46dAG4JVUscfb3rJno3XhO9DaxaUpSO8xrabAuIpoeBwUFsa8dyNm0pid74b2VLGuY/+5/VPV9ju55vvx4pJVTmmXWbPFvQTn50xebT/xZg204W80OeUjFNTIhSP8ZiY7rp5rmEtYmH0RknUDcfTnaT7KLhIttteHMFq66cOytn/RxH3mKW/qfjtOsvX75EfjdMtT+c9W+ZbrLYYmwqVzE/tWebSTS2uNlWn96i52aTpCXh7NRJmNLizJxLMaXRPn7I/xs2JZ9ONnTmg6k0O7AMU06SJsjabhl/O/a5bw9Un55eTto79k+8SHibcNZ0jPyO44gDsjmfZLzJMsWYJu/NJ7c4cxVnt/PNXlr+M8ecp5zhTOq/+TxtL+VwHj959TQ9t8R8Jv15cN9yOP6+wn+6fvPZM3u4Ut58j+pxHC9Wd2YWz6+OSStEKWE6jhxU2b63MrRBG1dS2I7BZwyhKd4vJJ4+bVQ07nT/BgfXiV4eG0NqNG2zXrzGwcl8T7u8Ad7tD92kww7oPkivV+VSSQFso9ffbZY/BWleaxq4MmY5zHfiYbNn68OyIK/pwS3+nfpo9cjXtsLUwJyz0GczrQnozJ8Db+IjTWqk9qbYPtk/dZbqzbnGw+DZ/f39CzkxqTJdfqhJSnKSDLla/vT09LzSzETj6opVCnz0Ictp2ve1zZ5S+9sWYtugfTvRw3rzm22lY97pY8xkHy2wt4RvK82eG743HGx9Wh9bgmc/v8oDr0nf/j108NvHzrDhe+hqfZ/5V4q3W3F8Jx0NP736x+MpRrX22H+6JrUx17i4jbQTyoXtNvkSC9nX8MschnWZcxE3nDfMhw/l8bvLLa/E083Ny1s53L71M7HCuUDy67SyneIk6U2TdhsfzKsTpk/xgJv9jexSX7ymYXLCm2YXln3DkyRP/3ZJC2Bsw3w79/SrfrZdnpt/sJCfhv+NRsfR2SXKcVR7rzDb98QL/YR5j2lM8ZFy8HM3mMcZ4yjzRNu0aSxNsjwrlweqW3Ix52n0Axbpeh5LwZH1CSJTrxnHtoqaaPRAMvVPxcwxJmhns4QpWF4NnAmg+bsN8MwjAW8DzCnJgNPM6RbwSCPlmei+ChSN5gbWV0CHAZZtNV3Z7m5vb1/di0YboBO3hM6Bwfp+enpaba7JaRv4Jf4cxFtiwN/bIMU2mTAkvWeN9CT7aWC90ZuAmcc5aOM7UMd/ho8zmZjuKZ504UvQ57H+8+2JsoZP0w/7ddKQZJ7soSUhc4yJn3dYpOTadmdcMk38TVo88GdcYOLhANx4tA7pe2dYkdpqScDQ+PT0+l5Ey7nJnvJoicLZN+lNMvexlkgk2p3EtDZ9jvJK12w5gWVlHbjthBuJpuPIt7i0GNzkxBxhw66t3WYrprn5He1/fHebQEt6SD7Xrh0c4sCPJeUmrW/W9SQA+zMNaWKBMiB++3uu8aRa8rkWr9NKbYrDlqPzNK6mzQCGMhu5DK5wEDx9Jj3Nse0dwFthDJh25rh5sow23GL7id6k1zQBmVb00mp2snWXFB+a3Sea2Qbls2Ey22Vc45OXzbN/O17ah6deGrTTVkkf/7t/0uuYTblRh23H3ll500B1U3IK3p7pnTYSILDOFApgmDyOfm/KWSBKyUXjxW3aQcZZmyHz2rRKZ2dgvzboFLTmdzNMDmwITl5FSaX11/jzsZRM0FiTrTTAM01nYMP+Gxi6XQ4izgDVxbY8vxPtpnOutw/4fAIig0Fq/yzpSXZtH0qAs+mVxzewdDB5y+ohafVALtF2FmzYlmehR87jR6lYhynoWs4zIOUAtQ1SE3+2c2Nnw1Sfu1LcF/HdcrWfsn6yoeZrvobfI3MnIzxmOzZubnxusjvjZYrpSsn7FE+COMFLdDa88PeG36Zn69P8+Zp0vsUCXmuak/2kvua75QK2ycaX7cK6veo/yb4c34zpyb+3SRbT4uPm2TtHNhxMtLukScmpyziaBuiJvoZDaSfMDIRbXG32P33P9aYxDXrmeLLRVBzLNrumXIxtXE3jw/sSfiVM4UKN9ed23uLnCcOTL5K+FMd9zBi1YTRl2QalPpaOm84z3sk/eTM/LQ8zT41n09x439rnRNu2c2GKbdx1xl+MI/5ONkd78X3E9rkr5U3vUR3npiD47aCRlGCjt/OwjSRkG4fpc3JDWjgLxNm/LcgnBU0yOzd6M2nzoKfNsrG0ZGLodYJs2bWZUtM+iTiT4jOwarpIdRMQWMepn7P2kvxS206aaG+tXzvOlcDUAlhbPXTbZwMQ98VkhLZg37H8aI9JVmO/nOWyvtuK1hborsrCM4feMkK/avYzxxk8uVOCfKXAZbmRHgL/JA739/ev5PJWu3l6enqxojqD07QN/4xvFl83gcZ6SJMLlEH6Pz7iGd6Ej2d4kGTS+Ev2N7xtCUmyY7absNF8zLdtxG1u8jsrTY+us+HDfJvvq/03GzBmsY8rOJfiekt4UkLp37SVxF/SMfvkw9iMi/7NGJ8SvBYfN/nb1lNOY+zy9d5ZMx/26XaJawkDfK3zGdPMb9oq2062wXs0mUf5+rkta/glznoV0au4LT+k7J6enp4f4OkJLuuG1yccYV/ze3swomOHFxTaSirpartsUtlwlO1ZVqkd+3HDgEavaW4THyzkta0kTx8p195iC/myTJwX+trku6PPdu1xvLTt+ZA/64JybHKnbowJpMG5VpKZ4wj7TSXJN2Hr/E/joyvlTQNVd35mqCkJYSKR2klJAB3E7bR+U4LOJN8zUim5oiG573RdCkTbN2WUZMU6/k6yYhs0AhpHMtDNmQ1QLg2EWvLTjjU74TnLrSUmLdk8SxLO6Ekl8b35BftsTroBVarXAou/TRNnmQlU1nnbLkR+2u8UaP1pNpT4SAmi+22TUP7tbS1zzfA6v00fV1evArj7Ttu2rKupn3hPNj/f3IruANcSjeQzGy61+smXpiT73eQ3sk91nbzYn0j7TMbM9VuClJIMB9t0zjGNK/H85jXJf5Nc0wpTu/6tdZJ/0W64SpMw6EppcdF+2uS99Ws7Tfwm+SYfYHstNvL65iPfIyvTyzbtv/w4r0mYmvBlm6ziMfLlwWCSEXHTPtsmIxINKda3dk3DloukvCb5crIl4+4UL1YkGtzntuMo6Ytt2leYB7XVuDQJzDrJ/vw/0bvR1yYCkjwtJ5eWf7XyFrxMOnMcSDbCc1di5HHsT8E+iw/2/9YO+3FeRL3Yx+a7xVr/JgbyGPlp8cWr8mfl8kCVSRo7TnVSoOF5ftsJ2Ed6qmRrb/pMr+/gTcrHkV+bQ3pNdzPs+b3JogW69p/tkq+00pxmqQ0Sbr/NQG1G68Sc/Y3BeebZOtgS2HYsBbQpaSKCn6tbdwhI5N00p3asd96z11ZbqB++KDrxkq5tPLhsQZZ1htaUGCRQZLH9pAdfJDCyDDxp1ALh9pvtcnCQBi/TXxpEp29vyZ1Z79QG6UjBrA2ej+Pl+5eZdDhxsozs/yyexZ9+bm5evsbAepk+HKTSseN4/VAFl6sBaavb5Gr7cRtcTSI2tNUK6ygFcSf6IxfaHP3qSqLVkh8OsrfvFqc4Udlk5GPJ5lIbV3Sd/OoMTzd7sf2l3CTFnjlH3dEvqP+UyNE3tzjGZCzFP8u20Wkab29vj/v7+xe5zPgx2/aKY/KNhunJt5Pe0o4G95F8zMU4T/+kHFqct0ybPFPh6nVbtLCM2n/KZVZrrU/nbW11dnbzTHxpvkC7HRrevXv3YofUlMk1pu0mT+uN/53XbPnA2B13Slk/Cbs233IbyXZ8TcKUdCzZugfYZ/a0xX3WYd/GCfNGuXvFnXrcYiJ5STSlWLbJZerZ/zdd2OY4uXOlvOmpv9PBtveZBKbAyGTRdcbBBnzH8eg4KVDOh4MmJiYjSA4MtgdcvMVRPDPmujQSt23nTLIjAFoPBFIbTivThx+w1ECAnzSwbYPdDey3kgArOcnYSEo85ptAY51cBU73n+SbbD8l+7aH1g5lsQXmtE0kybmB4Bb80zEXBvr50E6a/MYX09O12W6ivR2zHAnWSW8t+TAQs73ZmjsrdJwAS7qZ0uxwA/atNP6TbRMH6RPEq7Qz4Swom9eEcWd8pYm0KQ3nyDfp9O+p6zgzvFs2qd20smqbT3KznV4ZsF45znbPVsSmeIIztW1fTXjXYkSizX21+NDw5oxWy2qbVEs4tGFkiqsubDPlMVscN/2enHdeMb9nUom3Hkx79CMPUFtMT4MV0uf4bv4T3qVV3G2SZX5Pe0lXlDP72bDdZctXjNWmk7JKu2j4m9s+U4xvsie/ptOTar4m+UnDQsu1xf0kP/JDHDTN82nbc1OhXJL8U1408qb9DE0p3iYZs73mp77+DJ/a/ymbrfm45TE4wHe9D+1PTy+31DcfMfY4B2glyYd9+5hlOrpkzn4lx5jypocptYDQPimYmyEfS0vjV8CI7Vg4898rFKy/BXu2ncBhC2gp4ZlrUlsbP7z2OF4aV5JNCtbb9XZEJ0SmJwFxc2Yb8EZvkm+jzTR6S4F13ej29xZE3EbS5RnwJbujXrag1gJPOtbsa0tctutaW0N3GjzTD7ZAzvrJTpKe6Oebrh24eV3TQfLfNAhPWJUGqrx3aeqlAJH4nGvIw4Y5DQfdXvJ7fqf20/UtCXD9swDv41fwNp3n7xRIfX6zRf9vMnb9zYfeEqRZGIftr4me5tNpAJ/0uCU6G9ab1yRfXtvwxxibiieLN79I/Td66J8Nc+f4tiOE/Sf7a6sN3g1xe/vytXpJRylBNY9bbLGuiYNsw3ZDPr1TaIt1V3DnLH40rDjz3bTqeSanRGPywSSbK3JPcjuO1w8W3WTGPo4j54mNr2S3LN8T37f44HbIQ6tLmTX7dBvWi9trsr9C9xV6U4ywvFsbrHdz8/oVMtNmwgAP2hO9pm/aM71n/LGkXUm0/y3/S+XyQJWPzE7bT5JibUQWhoU1dVK9NNO5JSzsdx4AQqGk4ODSAmyimTOHaXXhLYnJ0HTmZGd0paBvmdtoNnlutLJ+kuUA3Blo0WlS23bYlJikILttMTC97js97TXN1jVgTsGKskqBxSBEO23bgdIx8tiSny1ovqWYDwKkAxl1lIIfy5kfpOD69PT04qEBlg9lnbY00VbbLOgc54OXEgAnebYZzOk3zVhvdnQlAeAqx/Qxtk29zcpAasc63IKs8Ya0nAV2f5rNs62EA00WU5hU207TtbSH0fvQkOjy9cb1hhO8fvjntq+2/cs0Nt+Z+mn1jbS0dzH6O8VjX/M915FmtjX2a9tIOMDdU6k/2zG30hIrN7rYxjZgTvxvuxvM+/BDvfm9oykpHftJOVTaDTa/W5xLMX/q0xZnF8pxvPa1JMfjOOIOFdYb2766M2k7vtlkwpwmpw2HU6xPNuL8Ickr0dd86Ap2Wj5n+czmZ+2TZGc6ndc0+79Ks1d2W+5gWbWSYlJqj35AmhI2XInhg0cp7zOffkiSJwvSDiF/2rM3WmxK2JHiKPlMC4Zn5fJAdQDIiR+dwQymrSCNYf/mf7bRAN3JShJ0S5JMQxLuWdutjGy2/s7kwOObkzSQSbQaePzbDsbz6fjVpOMsOUv13yL3BJRMqueTJhNan7zWPJsfnm/gzra2gHVVnolu9sMZuLPVh8aPS/NV00J8GAxI29wSPiQ7ScDL/qmTM/tqAd8lBVBiXpo9ti7cZ8OAp6eX9zk2ObMd49X0vSUXQ3fCpsTrcbwc8M61M0GXdJLKhj+bjBKPDobu23rY8CNNqKREa8PYFEdan7Zz95N85P7+/sXTpyd54Ra4oZ/vyuMxyzjxsvm/r6P8Wh6QcM/nkt9vZbPphAFJxtNXsnfrrsXvxuPm463uyG+zkfTUW+s4+TPbT3hmu95yt4ar6Tgni401KUYfR36nZ9LFGc4nOc//pvckM/c1NG541+yt0efjm6xJmwcxbdLdtPl787+zmJZicorZqf0zH9nsjHbDyag0gZH6sZxS8XH7DnVF2qxDttfsy31apjPpM3q/ubl5gQHOc40lHkRb1k0GTX6t/uaXzGua36ZyeaDqIOf7A+0wFCJnwMzQtMe2fWzq8mmWE5AMwskI0oN+3PcoshWDbKMx8WFjdtkUntpKwcXfG4CfAajrsO/5bdDakn0HqZYAUActcUs0JqBIySadN632u72hM9mV6WmBsiVmWzumN8mT/dEXhjcnJm1WLrWZZGGetsSAbXIwZxuwHtrkgQGb4Nz69/VJDy1RZJ8JX9zfw8NDTC6s/7N2KJfhM12ffqc+zwKybY320gLq0PX09HR8/vz5Wa9ti9GWcDUaW6EejXEJ8+xH7M80poEq+7HcKHMnJuSt4f7mQxx88v/79++fB6vv379/XlnlChRn179+/Xo8PDy8eEexbYp8bpN3DdstI8fRhqHuh7nBJrNES8OMadc2kWJ56iPZVIp9c67lHwnzt3Np4muOzaqJE3PnWm6bO0eon4Sz7K+9nmfTE/ufVVy2SRo92N7sbrO/tAvC8j6Lx77OMiLffrZCym229pu8/DvJmpjAnY7cIWPaU3x3XG3XbHVdL+nBgxPLpcU11mu00KauTBhvOf6V0vIBy+xs8r1hl+NCw2VOyHlHTPPxqePcd4vBLYdouRZlkLCF17ecIJU3raiOg86Wp9n+y61I3pJkEOd2hs2JHYiSo85v0kCa5tp5ChtnHahgB9O0pWgb+DQAPXO4tmoyxTMgpNXXvCUhOgN+9u3+mvGdBTzWJdi1rXN2/DQxQb35ulSXPKTXg5he1rddpJnDzeFdzpzUck/b7FsAmOPcwplstwH+ZuPJ3rcEgH5oOfvDrStn9rB9phiQSWuzfco0DW5s7w4kKQH1Odvy2FdKKthGC+5zzdDcfJJ9zze3Ac9KXUp+Et9ctfPAyAMk20Wz/aRD416a3Gg2cIZ/PnYcL7f6b3U9KbvxRdp9zL7GWObYmh7gRdmNzLh9ddqe/zPhO7GYkw1OijZ8br5gfTkRNb1XC30gnRteiDWpDN+2JfOWbOk4+rtO7aMesHtlhHSzMNciPpovY5nzHscwr7iQJ9LS4jZzN9q786fU/tiSccM0uCSe59txpMV+2nzK7dougOGdcWmLOQkX2GaaoKCubAsjs9Et8WD6mWPpITXESL4XOOU9Lsk3ks+7MG+kTdof7K/Us2Xmvjw4tf43elrsd95DOSSfHt5YmpxafpnkaFrbQkbKBxrdbJc0nMWsJI9pu/XL4wlb2W67PpU3vZ7GwMdzTrgY5BrY+xh/nyWUDOoUjGcNLRTOWJJ+00kapmyzlVcF7j7bfx9rRnOF7qv0tMRt/vN76hNceM0EB9NIG0ntug7rWpeJRztwoo1tkratzUT7Vq7UazrakjvS1OTkOimo8r/B3kFj2k+gT3otr1Rnk0kKZKl+GlinQJOS1bbqkeRL/k2Lj5m3FDhS+7w29ZN8sNFquhptTBISnRwsbQNVJp63t7cvtibxyev2dRfHlCZz89XaSjjWAvmGcQnbW4KQJisSj8mnSUuadGUy6qQv+XPrc2If/djtENOTPCmHs4SLhf3S/lr9K8Xxxm2lWMDrzvhKttYwrGF1iovuy/169dR4x1zGNup++J0mum3bzZ6SPHjszM8T/2fnWw7AvtOA2oV8t/yA/ZG/NBhqNk9de0L3LG8xv2zPE1cclLbVM8f2+c2dFWmygfKYQtxIfKfrjGfM1Ulfeur/W3zkLFb6/OaniZ+W6yR/s/4ov6GjTXJd6dvjHbedZJFkdxYn3BZLss9mz2z/e/Cd5U0rqsfxWjAGwjE8Ok9akRkGWCb5SddNSQ7Atu0QvIb9pgeGGPiTMTv5be8i9H8H6CsJWDtmmsgjj7mO20yJfOJ/c0o+jMWvvPEN3gl0Em/N4TcA83nawQQqT46QzxT02EcKdGzrip4YrFICzL5ozwb3xrttPoE6E53Ea7KPmXDgbCJppHzY//Rhn2/yvb+/f0Hv2A9p9ytt0oxqAmLKcmyVT9BMumurMglL0rmk29RPsynKK5VthXr6dMCiHZLubUXC9ExJsWDaJL5S5+TXQS8NvpLMPPNuX07083oHel/P98z6emMEVxAp8+TjpoO0z2fuPeU9qKkdPrwv4UFbAWIxJqYZcNsP6d+ww1jNiQvLYPpJsjqLAfaTkVVr+2zVr8Xo1GbCQ/aTEstNdrMTIWGb8Y3faSWKvPCWqVY2fGJpsS/p1TIbPojfximvIPk/r3e8T3a70U/fI930a8egxvvZZ+onHE3Hbacp36VMSf/8tm0Zt8yzbcT98xrbYMJb83139224YXmO7/o4bYSvXzHetFVstm+5WGZjB2kCqLV1tipJ/s17yosTbngBLtlBo4m7F+w3DZ9YEu6YN+eAm69Yjhsmsbzp9TR2Gs7ytADgJMDgTgEkI3V7wxyByW05cbAxtECWDNTbDFLwcn9JUcmxU0lg4xlu890GCzx2JaFg+80hks6od9vB6GmevDwypWzNow04BcNUKJskt9RmkpVpoI6H7ma7lu/066SKekvytOzb1hSWZHMcpHs1JV3Da5NuLKsWmIZ+rgiliQL2lbbIMDHxIDUFrCR7YpZXqZrsWgJA+dkek0yTn11JqLbryWcKerSV4ZEYZTs2ds1xTjo2Pqb+bP2dYy2AJb6SLTkpSr5qzPbKY4pJCX/PkkZeO36UdJLk0hK/lIzYNk03PynxsS2MXug7ydcSr1NSEn+GDamdRHeSm9s4oy/ZT8Lb+U5+m2ysxW8WT8j7HG0g6THlFjMoSv7c5EXZbnZ+Beu3kuSY5JziOY87l9p02+hMPLeY5njX4rqxM8m90Uq5JBpMC2lv8YTtnNnTFNtjsusWKxMmJ16S7hPdW5ybc47pzQ9bfEvtp0nLaetKOym22EfS/1ZMw/w2tjpvSnQ4bzTmze82SZl82G1S9qbRfCU6yBvbotzeWt48UGVA5axvS1xbYG7O5nuaCEgGmaQAg2RayUt8mU7338DVwNGCivlM8mU98pJoHyPaku0NTJpMHIRM3xlQuw0+En+KA7R53JKZDcwbj81JtzaH/wROTVcEVbfbeGpA0AAkJSCJb36nFagUzPmbdp8GhKlY7zOZ9fj4+OK+OuLFzNSmGV7aRlpFPQsWaVbSv8/4t/2kwQfxqekg9bPV25K2hA8tMPk6JyTGt/nc3NwcX758eZZXwrV0LWVlXadrWxk6W7JovTIe+YXoXjVxHEn0bDhtbHiLTttA2gnKFE+QbYMW+8vT08vto9vKUEuUea8r9T3HnIBt8abJJB13+6zr31Ov5SA+ttF1Fn9STEw0p7gz51P8O/Pj1D7pSTrc+Ej0bDbPvh1Hfd02Ab3F5E2ODZPnm/5t+WzYbH032af8xzQnGySfZ/JN103hqnjKgZ+enmou3vo9iw3bNU338z9NhKU20yCV9bio8T2DL2M//Y0y5P3SKV+gPW/+adklGyHd3tHiOLCNmVq7Kb6znmXUsL/hTOMlfVsm2/hoK5cHqtP5JAR88qAdxwRSwZ4dSOC6CToVtp+Oz28KMS2l8yZ1Xpvut6Lgm9MmmZzxsxkgz1OuNDpf1wwnGXyjc+q2QfEGTvN9f3//qm3Opl2RTXKoLUgmwEgrBOz7DIRakLD9NXnPtbbLBBRsc5vdTYW2wX68AuKgkHSTEo+UMNCfubqVHs6TcIA0ue0245qundIm0MjHFtQtuyTjZq+Us+nYMLKVpqezxCJhU1qt4wNe5mF5rMM+N5mTpjZLa/kkf2uJiL8Tjm8rkuybfrs9MMV92icbzvK2COqCMh0eSIfbth8k+6Vs34JlDUOm/sPDw4s2jRGsy2vNK5O9q4k02zLN7ViKVY23Jpunp6eqM5fRwzZhz3aTHFMdF9sd+SCdCU9TzDQtqb+3Fg/AaSPWUfKFxL8nWRKtbaLTtnZz83Lybc5x9coxjLYwddNOM8qWsuDHtDR9uTjG8niKC5Ytr+HumJTPJbpT3tFWbo1P7sd8tntmE+8tPpL25v8pH3NsdL/M+Yl59psNQ5PO2D9t6YptOUa1vClNavKBnNbhhsEjz+a7lqv/U4ZXFz1cvmvrb/pYaMeRZ1FTkEjMGYRbaQynPhM/Tm5GIV45Sfy0BMV8bJ+tJIDYeKUjUy9nQbvp6UwHTa5uIyW2ibetryvneD7JKiWumx423U450+FZMHNAcfKWkjnT1ZLV7Viin4EmPXHSbbG++R27m+tn5dT+xvtEExhygmtsadpteknyZF0GmOQf1lkKtE4Qmn3brokZCQsTH/bRq7abfI/8WSaTyFEmTCSZ4DjQXQlalI//OxExf2cB0u2Y94a/tvdNvklm5tU0cka/XZtwt00OzTdtONlk8lfTkPr3NZRBWvWbes3XWOwLV2OK27CMGcsp99a2k9OWb2w2Z9uwPtxmsrmNv4b/1o1LmrhOdc8mdJMuNxkkn9nir+O0dWJ5nSXn/L99j0xSDJi4xHrmgxNixkDSTL0lGZ7lMUm3zCfNm/G++WPzuxabGm0bnrjd9N3oTv1uNpVoaPlWs/X53Wxws80rZatnfW2YaF9obW/0ESfP+rrCV5P19NXoeYv8juM7VlS3mepWyFBa5XEfZzSM4bREYbsuBaEBqPS4aYNlmvXZ+knXe6XKPGzbpJmwT+Gsrovrt+BCnlsg2IDMicLT09OL1VI7hh2+JXrs64phNx2nNjlbu7XjYnn4wSaUx7aqdzWQb/w0vkzvGbhNSTZqGg2c5uX29vaFTNLTCufYDz/88PxalPv7++dr5iEW85vtJlmyb8vP/M33lkRsCZr7bclSurYF4yslDV7cNvtLg6RmOxyEtCRn/hMrE64m226JLHGwzZgbq+1rcy1t1vg4K6amoyUelAuLd2QkGaRkNm0/420ulkXyLccV0nMWN6kH82g79soYr22y8g4Jl7GLhmumMe14SFul3R5lnfhOsS7lEduWu9aWfSfJLGH+9Pf09PKesCu2mmIzc6QW/9sEo+WcdJnwP02m2B7ObIN+PO2c5UrWw0brceSHZA2e8dWK3oK/YbqPX8H3kU+LG9t1Z7bE3wnvr6wGu62zPJF9HcfLBxM1vU8b44O2g002iX6uTBr/WxvzzR0f3g1gGlI+1XxlKy2HmzZts44PzQYci8lr4p91mw02Xs94Nu6QjxbvU3nTiupxHC+AJDlvmm1K4O0gzW8LoW0PHHrYBwFySlu2phAttLMbvJOxXAly89ARPk2OAY7Blk+fJI+p3Qaq6RUxlnlKhCiX0Zf1QqPlKte02V7indonDZbn5pymOdHo/hPv6VrTk5KEBhS22bOAz2v98CHrOwUht7OVLYhxcmGKZ5/Pin3ST5szj2NHM1Al34M3Nzc3z4ONaZN9mT/7zRTLOmENE7zG7xWQbTa4YQmv3RIRbuGyPhsNrpce2OCA1eSV5MFrk4803NySrhbM3QYHqB6opFlo89f6ppxdHLwti9lBQDkP5hEbuYU29dUwpvn/ma01PTKRsCz4f5us5fVptYltJoycOsa+qTs7MLi9e+ptq9fk3XKwjpN8ku1usWW71rJNfQ3dvj4NtFgvxe+Ef4luy8b6Sj6bJjLnO9HTbDwl42xznhhr2yPOpzbnO+Fawk8+ZG/swIsr49dJjrwuycOyoA83+/DvTfbu++y6Znsb3W5v49/XuG1OehrLBxttF2exwgNj2mLTO22k6cJYk2SYYl2Tgyd52tgp+SxtZs61ycIrccW20WKe5bblBKzL9tsYcitvWlGdDv10RxI9Jc12HkdeFUgGaIEnBZCm+XZixs+25O2Z47Z6auPwdTR69kmerw5Ux/gowxSIDXbsz+BsmbENtkVeXJqhNqNM/bFeo2tkkFZdkn7nGtLBfs5kYLnyWEs2DHqWD+Vk3luSkQA3rRI0vTu4JN7O/IIDtc3n2jH7SbKR29vbF/cMpdU/b9X6+vXri3uHrFfbxFkikMC2Aa+xpYFsC/5XbdAys0y82kReGv3JttoWto0unk+Bd86lFRbXaTTyd1sxTElXw6zm/2f9U2a0r6Q/n2e8I74Tzzxzz+vaquDVJCHxm2SVrmkysWzc3tZOwu2Nj4TptFnuzpj6niBOuvGkm/XVeDf+b/Es+WfLcdwHf6eB6hW/JH/pXNOz85oUR0lPauuKPaacou12IF61mNniE6/ZeODEUpLxJsu0in6GxWex0zbC481nr9hx01uLfVuMO2sn1W/4RT+een52ycbDlmclGRjPyavl6LzC1zRez1Y+Wy7ASZAzTEp8td0AZ/hFmk3j9xbK2RNR7uusvOk9qtNRegLZCIhlklAqljMkBHYbMgdqacvPtgJgQ5w209ZDKtQ3+k4bVL5nXth/chjyaIDeZnLprJSD67VtOmlGijwlWm3czdnIa3rXYOqnrUwkx5hv37juIOekruklzd6kFfdGmydUeIy0sI2ml1SPv29vb188dIi0JD2Qb9ZzabbDSZGxs8Sf7dg7IlKftivSO7L8/Pnz8eXLl+Ph4eH4+PHjqyS02SCTVyeGHoAxELpe8xvLKgF/C+QpYFpW9o/5nfqeMvaQVhVanwlfRr7c6kb5OJB4ADrfCS/cb7MNYxppTDxRbi2p9XXWX5KR44flZB7MN/VA+nmcvkL/8crjlgCxLdOZ+kylrQL4fOKb7W+JD/E2lRQ70qRJ+m7xnx/nBWnAZd6aH7uw3cSXsYPf6enJZ220SX3TlGhM59xX+r21c6Xd1pfxIZ1P9jT9GZ9cJ2GO7zvntaTD2MJcbdtRQfpSnLctJJxIK2cpH045Q2rX9CSbNY/OCdxfw16e5zXuj3Q6x5kHLTKPfHz89rqz29vbV4s6yX7YJ8cdbeHCxbs/zFebzPc1zLtHxnMLU/MB5jRb7tImLxtPqa5lyG/21Xw9xdZmp45ZTX9XyptXVKfDMToSnxhJBu9l/ORovqaBGOuf1RnDn+Q2LZEfR5/du/Ix/VP81LoxCiq5XduCWjs3x5lU2knOkha3nQz7OPJj01Mivel4/rteC6DbbwI8+3fd1D+/24pQAuFk51uQT07tJMwgyAmHTSabzBJgb3zSRqdu03VL4NJKHfuYoEJ/JFizGDeabFuie0UeGw9nyQeLgza/XS/533aMs89sw9cQl4zJbSLFfVk2W1KWEoiGU8SlM/5bopQ+jc9Wkgxt+2Of5NW0Jj7TsTSYaXQ3Wt130sVmn01XyX54buOb7b4Vt1P+0AajrTQ7Svwk+pNvp7aTHOa/43mjPckoxWgvDiRfNL1JnqTxqp1uuUmL0Q3jfH0qG07w2zGpfSgzr/w3zN7KyJQD2BRvpkysMq2Uw5YLNPmQh8aL43TCp4Yxqb9tYjBdYyye4h0RaaBKX3K/HiRbJsn+XJe2kHRofhxzU/xOvmU6PTmw4XKS8ZV4kHi0/NIgNfHScIT1KJsN5xo9b/HDywPVJqgUWLgqwiRmMzo6jo0hDe6sxAGRp6dvr9ZI9dpgYPjZBNmUcCb4xu9sYZw6W7EzDQgSDFOfbal9wCytaGxJDtvnN3lh/6ld/vdMlZ17fp/NbI6deXXN9ukZtnQNfzsQs6/5TVtK+rRDky5+eH+M5TgzdOlhQgaTJOtEGwOai+XNQDDXEqwcILZAST/gRAevM/hRvtvKhRPc5OdTP9laCkSmz3JLq/yUx/RlGxl6U7/tWLOvFiQceFrynxKZhofJtuxXlK/pT31Z/7Y96j1N1pBG24xl5/8bRjSZk3fqekumfK2vd98teUo0JHn4O9G2xa6m74YZrZ1kb3N8cgXXsywsr4l7lB/1n2zX+r4qy43vMxn6ORNNZi1Hms/Dw8OLONBoP9NP+3Z7xDhjmelm+46NpMn6Ie2bzzw9fXtGBlfhGRuJC3PM7w021m36tGyNKQkz0gTicRzPq4Nsz7ZNOSR5JFlfobflCdYjz6f2Kd/m4yP7FpvSK+vu7+9f3Kc69m6bcR674QxLkiPrcoW3+c6Z7fN78gPGKO6iafFg6tlGp98UkxId4yseFG+xs+UebdfKnB8Mds5FGjlOaXh8pbxpoGrieYzbFa3YIboRmAzo5ubb01RHgTTi9IQ2tjHCmfaP4/W2j/YE0RbYttIcfkoKjluSkcDHx7eBRhtAT106ZptZIr0eVCcDduAw76aBAch8mvf59kpj05ODS3O2JCv231ae7+7uVmdLoH/2Tjk/+Mq63gB6gD753/jOyNt8tkmo1OfU5Vb4lnxYrykAe6aR/TAxaYnetJtAnjZ55r+kf/Nj80jsScHduESbbH2c0elkYPpxPX77wUm81kmIA7JXsS0f+4jxo2F+63/aTIGvXZ/8+jhevqev0TvHNgxPyVIqbZDLktqe4ynOMn7Zz5rP0d9Jf6InJXIbraY37QBpdCV8Zx37SFsRP9MV202rg43vjbZUbL+kh/HNNpra2BI4D8pTf/zt1T2eIwbQLowBjp+evHTM4rVNVqTHddnHZkOWG387nqSY79/kj4seLtTrNnA4jmPdAZXshbI1L5TV1idptMwZB6YYTzZcmWvbpH7Sj2U6OfvETS+8WH/knR/bHHlhv3zVELHU9HiRjbxYNkkupHse+Pjw8PDiXfQNq2yLfk3mtJ92Lg7fnphJ77du8WrOmQ5jBPm3rEgb8wwvHKbFuqvluwaqbbDaZoDtUDSaFHhHGBRiSkQ8E7sF2U1pKTljAtTa9P8WhAm+5uEscPm4f6cglRK/xGtKDlKxrqh/6oD3FJimxqdp3Iw3AXWT+VlJgaslC8n+0kTAVXqaThyobJfp2hYwPPj0rNaVJ402Pth+Sp7NV6PXfdm+mXQlO2+2zzZSe7RnXp9obb6RVnPSQGBLeN4C1CxXE4v0nXzI3+Sp2V0r1MMZnrS+jyO/Yzi1cWZfTPoSbQyqHqyeFWMw/aLFtyb/M0zesIVt2B5pk96CxX4T32dxgTynBIXFciENjvGbDNL3Rqd9nvzPueSjrbjvtFKRdE4eSVfC/PQ/8dUSviYH0sCBEXE2ydQTvYk3y6jZ/xVMSVie/GaLWynXGh7n2/ElDVJSDOZvYouPnekw6bvJ6GqMNiam860N8+D4mLBqvo19881xge9Jt1yJV9vEvPkwvjvfdj7kMUsaqCa+Ez4mOrj7zZO8Lpah9ULeEh5OP9xFmla1G82mJWGp47V1sNGX6El0nZXvvkd1ipd2Wz0TR7CkYXkWJdWl4J6enp5vVk4rQ3N9SiZaYf1mwMO7ATkFaM+WuZw5QgKtMydu24OGlzHqWRls7TS6uJptmczqq2c13aZXuKeurzFfV2mc7zS76sTJTrU5Ou0xJRguDvhJn04op02ukCaaPEOZZuSmTc6+zbHjONYVcIOn5TXHk01alyn4bSsx1kdLnHw9AdwA2ibczC/7S+CbBvqk1UF3dDV9pFWOJG+Xt9qbr7Me5r/tua1wJ1sk7xywkBYnEw0veU2SfwtuKfbw0+i2vTkxSPUSRiW8Sv21MvX8GrCEm46NoyvaVHqIHidXEn1t0rnpwP40JWGo7eKK7s9WaRuetNjRcJeYnEqKDcSBFm+JIelVWaQl/Te2EFNsA1vbV/xnSsLJpjvLpcntapwwvaZ1/nv1jdcle0yxzbbCfKYNXNmWcTL5qfu2bPid8t5pN7WV/CdhCGmbc6Y36WLONdzk+YTTbKv5o9tlfjKDvK39ZE/ja+0eWNqG9ZvsO5XNn/x6v4RRrc2pzzZoh0mWDRO2Pox3GybRNzb6p6RdgfRRtnPWFst3DVRNCI3EwSmVMabmpDye6jDxmYFyA7XkPJuhpeBs4Bs6GDyceJ0FEbaTeE80+borija4GfgSEJwZrgHaASQFKPfLNpLTbACy8UmeUntpJSy1Zf2xjRa02+x66rsFsuZLSZb+tkyTbkxX47OVs2TDPG3AuZ2n3zefZL/Jj5N9p3bSNq5Un+02WkcHbwHiMx6SPMnf1tZZAtF49nnz37Au9ZcC6YYV1lvih7/PbIw8Jh9Ismhls7sN4+dcS6BdJq6xXhuk8FjCpQ1vKYeU3PGWHg8CGj5zRcF0mTZjqdsz3+TZMbn5UcJaysTtN9xNqz3bQPU4Xj4/4yy2Jtp53PGj2fLUoc253WYLjW/7WpIfeU45A/Xa8GvjqdVJv1kvxeO2K/AqDrCYhqvXnfVBfb9l1X+uSfJI8d72fibzKQ3vmzy4a6XR1vws0ZPiR4vzXjlt2OW2ze9Ghyenz1aF3b/9i/LbYkuSg/knflwtW+7kOkl2jabE/1m5PFDdACUFHQvYTLM93/9IcOTsAmeDuFLph9C0gEU62ixFAq4UBIZGPgo7KaYBb6rHY8mhaRDJ6CYgum4yFgb6bWUp9TEyb8kQHdUyMK8JPG0nvH7a30DDbUzxdpOk19Zmo23qeHWd8jJIMPAkG+C1rMNvBwD2OW17NXYDjS1wmb6kM8vojOaNLtstEy5fw3MtKCTfbni0BSe3w+Jg5Vlty2jasb8ZS3x9qttK49dtsP3ZHUMe3R8n6Lb+HPxp82k3BX83H2/8kM7Nj5ucNhtw/82Hmu0kfTUaWejXT0+v7y+3nI0D5Nu6MG0coL5///64u7s77u7ujp/85CfPv7lS4T6I+3N/1jwAyAmbd3AwliSa0wRQs/vmMw130kCz0ZGucVLNwjylrfS6nPmpd2c53qW2UhxI+UEa0BlnKVfynXw44YaPJ1lveQhpT+1su0imrvXRVtiav7S46boNw1w/lTO9t2uSDW7x+IyOhnXbChtlzeut/9affSvZBetueD2l7TRL7fh34oWF8XBif1q0YHts0zpy/cRza5NtMx5z2/XWVypbHBuZmt9GU6LxSrk8UL2/vz81FCvGq24jsGQw89sBIwGoGWWbLFeEwGvT+wVTYkG65uZpvn7GDsZVX4OrwX5zuhZ0+T1tDV3eokhAHxpGvtuyfAJvJ23NiZLDur4DIh14A8Mz2ZB+OupbZ5csPzutndUJBPvkJEzix79b0J7zXNXnh+0TRJM+rgaAdCxto267JBJ/V8B32iROpO2720BmaPTxRus2YeX/vo4D57GHtMLUkp7028kWvy1Ply35S+fsI04Yps78H/wkdg4d89TLwaQ02ZTwJdlG2s69JR7NXofmKwmXz6eBmn+32GPatvjG+o4rnLR1O2f2QP7nqZt3d3fPA9QPHz48H0vv2k0YyFtI7u/vn2PQbONjnDyOPOFIXyGvDU8tn8a3+/F1CZ+ankyPv5O+qZeUKKdrpr79rfHhQvsmFg09jANbTGg0u8/mj7SZNNGY9NB0nfplPy0/JV+0fW4HdYwmz1uuMDoyX3Mu0b3FupZ3ua8mC8rAb944jv09smy30XEFN10sjyYjX/P09PQ82dXeo2pbmxx4/k+ekLCRcf/s3c/znXJ75lZ+4u42wTByPpNFojeVpCOObdJEzIZfrR/X2WItaUtYdsV+juM7HqaUFN0IbiA7dRIA2BA2AZwpbH4b+MfAaEQEKivWvJq3OectMmOwV1Y1LLcrPKf26Mh84uBZEGhJbCubbgj4bRbtH0unCbgTDy1Rb4OU1lYCcdOYEvBGh4OP+dvaPgt4/O+BaqqbbOV79dTsbn4nsEx9sJ77Hh+jvTnpaDppCV/rJ/GYjnGXh5OD8c9tYHIlcBGbfO+bE7O0ipEK6XfSRh62ZJa4eXf3LbS8e/fuxYPW0sqf9czBfaN1igN+s13Tmgb5bjf1nezySsBP9DVfPKvvnTPpWJLZ8M/V03lNxPyeb97b1QYr9CVPbLBfT1onGSUeNxyyPTZcZ79NpqY75SEbPWdxkzZjjGS/tuXWh2N+qmuMfSs/1HvzV/4+m/xtfJnGZCvNZhK/ia6U96TPVif1m+hvPFoOZ/XY7tZHiheWxcjAO4/8e2tz2mEfV3OtFm9pExz00RbS5JV1z34TNp9N4qUdEa438ci/vaKa6LI8E/3+fyW2NFlvO8fOsCrRkniifFy4M4v8pzztSrk8UOX2ERLt5PfMkGbw1ADQSVZS/vRLh6fhb4Fwfk9bvC6tyDqBM61MTNPTt9pql2VLuuhYG3ik1cHhh/RsOiFtraQgxhXZJqO0upwCpXlNQcW8Nhld4aV9eP6sNPBoAL+dH75a3+bfMvDg07sLNn7NQ0tkUqE+bAtsL/nwFRmbtikc6BAIeU98A+s55/Y2eiwf6sttO5DPNRPYOOPadJACG3nlIII8Jv+yrJN+6GMcwNHOBnNbUjyD1Pv7+xerc7zu4eHhxepqGrQaN8/eG2n5nfnQDNK8W4aTjak4qWoxxglR8znSTBpbXDN/6X+KccfxDZeH7/v7++PDhw/H3d3d8cMPPxx3d3fH/f39cX9//3z+bOfJFf91bGy+PN8pIaVs7L9zrd/FnGTghKnFw8ar5XuW+NEW3J/j55kOWyI+39463ehuA4BEl1dktpXg5IuOTZbBGU2p3Q3DW9nqO444J007aaau5Zow/SqtW4xN9tDqn+UeXtFOW9hdKAsO+FO99OE50sl33FqW3n3jvPosHzEWDK+MX5apfZW/KSPGo/TKFfK7TYQmnbaSeE65jXMB1nN7yaZT8W6auT4NzknHcRwxH2s+dVYuD1RHWDaAtBQ+51mYyE69M2LJUAJxJn5MQJqx0ijT+cfHx+d3RfEpqi1QzLH5pmIM/k2m6dsysDyO46UBcdZ79MGkcHvgQ3saoWk8O87rOXvH+pS/dbHJgLJs9zM3eZEerm6z7SZjO7/tyoMAX08aLF9uMUpAlOp7u1JL5lMSTt9rCZED3dCWJjsIdmkbkHWTZNz03gYLlIX1kbCkJQ32fa/+Nx2wXdot7b0lbSOvFExSApL6TgFwA30mJo2H1MdZ8HR/G9/8P9eOHSc+Ex5YLpueWWiXxEu+Q3qz08TPJpOWiDAmXkniHE/p2y1GsH//5iSCB6q8H/Wf/g//w/GTn/3sW8y7uTlufmzkxz5+9/t3hDz3//j16/Gf/+qvjkcNRv3bWHVlhcQ6YPEK8pZPGLvc35Yopr433OF568G26DwqxWhi91uSu23gPzQdx8scwJM5XlUnTQ2/0qSE7brRkxYLLNN2Lv0emdmH2sqXY0qK+Q2fEn43unwt5WiZpu+tzdT/2cSTaWL7I78pniz3a2fSgMTtplvSmjwatg4tLu537JExP8ms9e/JlE3ODbsaRvs70ZP4S+VK7mAc2nK4RDvxJE0ceMWUxz0Jfoa5LJcHqml2Pq2WHUdPjM4Cj53awYeGMoOOoYHJYltpSCsx066Nku23xJg0T90BfRr0FiQbaLuYbq6o8Jt83t7eHg8PDy+A5nuTglS2OpRLAgnyfaXv5sSbc7PPBBSklfodus+c2bQn8DJoksaWIFknEwxs255xZLu0e4NhAl3bZKKtAXWadCKvCbTsf5ZLK9TFNlB9i08le3Ed1zMOUsamwUB+JSA1u2j+yvNOKtxHwh8nzUmm6X86l/CWsqMOWwLSZHBmH6SLvpyeRXBz8+0+7ibPhN2bbthOGmAaa4grx/HtQUNpteMMt4lP9Lvne1B/d+/pbPO9u78/Prx/f9y+e3fcvXt3/OKP//j4+S9/WZOsZn9fHh6O//rXf/1jn8dxPP3I8HH87v/N09OPA9ybm+Pm9vbHc7/7/1wCbreSsJ+Yt11PDHNJ/t/qNNxxXessJWspZpmOLV60Mrxy4Jj0SD+Zz0xq+L7zaZc+zt/bjgR/mlwth2TjPu6SZL/17/aNUzy/6SjR1nhL8fQspznjnXWd75rGxkPry3p3TuRctE2Ym/eWTzWZuWw+mbBi86E0edYW39gn6dgK7dJ4lfRgXNjynZbP+BpOQI2O/Aoql6FlbuHxzp8pbYz0322g2pKptxiOnf6spITjOF7PFI7Qvn79+uremqS8tKrBdqmQ9km8pIHM/OcA2yDPYHK2mkSl8xUC83v6vLu7e95CwacwchW60U3azxycie5swUqObUDjbxp92o7k/igLH0tJXVoV5bdX4j0IulJGBuQrfdO5DdyprzQLz7Y4WE3ym3PjH6l/b+EwPdRRGlxsgOMgT/mwn8a/sWNAlXpLvkzanDSkZCMNKuabPKcEiN+Uu2XTEk3TdyUpnQm0loC67xSAyfc8vTztOpjjlhMTDSfDnz9/fpWkpGstu7NE6ao/0naJlxyoUjZp+yT1kDAqFd7Gsc32pxUH0rNtmTSP5tUJyMSIf/WXf3l8+OlPj3e3t8ftu3fH7c2PA8ebHxs5vt7cHP/wD//wQg9ONhx/hsc/+zf/Zog6Hr9+PR6fno5HPEjp8+fPx5evX48v8yRgyvrp6fibf//vj//2X/5LxfumG8o0JY1NdqkP/k4xzD6REkaf4zFPlNA+xv444dhWQhs/iQ7boOXD0mIe7Z/HSCdXy317Q7Nd69CFtJCPJA/GE/P6loT4ys4Knm+JufO44TXJsPXB3y0fStd54piyNiYnG3L9NLHcbJCTG7a/NDB1DJo89eHh4ZXOib/sb5PvtmCUSvK5hjXJX8iTdbPFdOPcFotSvJhv568p/s0D9DhYTXY8bT4+/njbDvuc9ra4NLoxPS1f28qbVlRdNsU3hVqpbyl2vAR8ToBSMsffaRAztLWZlJQ4kS8qkEpJSeJ8ZjCwbfU6AynS40fSe4DRgi7bY7utz0RX0o37S/1eWfVNMk/6uJKUUO/p064lfXY4JzDJvqgrtnkmI9M6/zlocYJg2bjPSY68LY8PsUl+dCWBYl/WXdKV5Zr43+SbArz7a3RvWOYthqld1uPvJrNmPyzN35OtJPzi56pfkEbynXbPtHrJL9vuG/PA68bOGy5YFg2vnTw0/9tsOvHkwJ14sA5t124r0ZHsYPOHSSLu378/fv7LXx63v0tIfvrznx/3Hz68wvkZNH759GmlwRNF6UmSNzc3LybNvj4+Hl+fno6vx3E83dwcx7t3x83t7XGr9n/4+c+Pr1+/Hr/9+79fdWPakx8mWTluJD+wb1q/jumOX+mbtpwwK9Fk+9xicOLVv9Mgbiv01/nvQQN9apssTbKkPqzrRGc73+SV6GzYtRXrxDKibJouWd+26+PNfkkP++E1G265L8sh5fYtxrLPRO8m2+Qzzn2HRvfHHCTx7wlW622biG68XOFhw/d2ffKFoefMRpvPbHTyvyeh2e/8tp1uOUOjp8Wmq3J2+e6BqoWbClc10ypGUogB0bM+DjpzjPWHXjvZzHZ7loEf8jvtua9xCvefDHdTzrTPB4vMDPQ8xr85kwMF+2MSMb9nhXjuXU0rl5t+LAfSdtWwkx1wNo2gRV1uTj+fkUNy4JTcDC18BQOTMNrUGbAnvfM4B5VzPAXxFAxY0iyZ5fj09PImfwL48OsyNsh7milT0pjobgA7v9OsJxM/ytT27qQuAW+abT+zgVZakNiC0vw+m2g5jvzgpsSXMS61y/pp8sKTXqYnyWR4uL29fbUCT/vnit/j4+OrGfSEkeTJ2DN9toSYffH+Jrdl/5zjX758iTPH5KnJN+nIgb0lMMlu3B8/7b4f/qfceH/h/J+HI/30F784/se//MvjFq9dm+vH1z9//vzs/57ksixGfu1ZENZZ2qlB+ll+9sd/fPzkD//w+P/8b//b8fV3q/vWbdID20srSbzOukpY0ZJDt2lscj3KLCVrDefv7u5eYHdbmWw4xzapo5HPNmFkPzuOl37DidapTxo9GNhoJK2mgdvxp1/3mehPNpP6PosRZ8m06aXdbble63uzpWS3LQ9rfRrDjY/2m+N4aTu8p9/tbnid4qVj9uSmNzffJrhSzPfCwVkMvZKbXC2b7yd60nnWYV3b8oaXbNfyTfHHq5hpIY7tbLbbZDfXp2PW95kOt3J5oPrw8PDMjAHBSUdLTJOgCHBOgNiHf09JznAc/SbrRHcCGhshV5pmMPP4+PqhS8mhGzgNnXM/iAFjAJurWxzIjXyHphl0MYEZ2h4fH4/7+/tX7zTkoNW0MmhcDeC8lon7DLwNyvN/3sPHlcG0/S3JkG1On07gKL8BXw7m0+DUvxNopgAy8h++bKNpoJtkyN/DG1fgCUApOTTtfjAY6Zn2vnz58sK+7SeWjQdnra5Leu3I0GXeLQfLLa3stAkiAzftfPwhlcZLoicFkCle3Zhv2gQTFPKRkhjaJPXrWeqZgJi+5pj5Yl3K1BNKpnewK+Eg+WzB1RhqG6OtcZXVPKaJO9NCLJqSBvWcWPIEFnk6K5Txtuo0fI+dj09ukzicXL29vT1+/k//6fFH//yfH/d3dz+unsKP50mbnz9/frHNzpOlLdlM9ufj5NdxqrXxrPvjOP74L/7iuDl+9On//Fd/dXz69a9f2ELqO8WGbRDJgY/zj3S9Yxbtgt/p2BYfU/7UsM/F/Ce5EGssnzSpxsloy8/yMW4me052bltg343OhiWp7ha7XexPtveWE1kHaSDQ+m/nXWyv7s98bPH27JhtnMdTfuTrp/+bm2/3/NPH0sDTcenx8fH4/Pnz8+TZ4JFpdy42x5Ktp9hBHZ/ZB0vyC7az+ffWdjvXMM38J3w7juNZrhO3SItvizSGNnt3sd03DEpvjHlruTxQ9YvWyUgzpnTOiRp/04DPylmQOAuqpp/OloCxgVgD9iSL+TZtI5M0O5WCw7TBFcRx1pYYzDkOsDmT1QJFC6BNvqnucbwcmIzh0oBnu/TwZeBJydqUFLQTbXSqdtO/Ze1+UtvU4ZxL75P0DFYKetRnk+XIY+TXEgODs0HFIDgTGvPfbbvNBmwOEGc4Mf2RVvNvzJmJjAbY1ollwJn6FuSvBHjSR9rbQDmtjrWAsGFbsr8rOLf5Eeuy3/HJkfn8NrYcx/nrrpzwm0fHF5aU9HqgkWakpy/jKftKEzu+vvnP5q+Uy9PTUxyojsxsG9YlaRv7fR6o3twc7z98OH76i18cv/hn/+x58nP65kOaPn369Py8Ar8uyPJNejzDRWP++MNxvJxAIg8zyfrTP/zD5/+//ru/Ox6/fDm+fP4c+3R/CSuty/R/6tOmp1DvjB1JDqbHPmhak7w3Hq/ghOnwtRtmX9W5MTitplKmxp5Ec+KP7SRcS7LZ5LkV9tHiQGqzTWAkPlKeYqwyPcb91s5c43xxyzX4P+FxG4C0Mv5DDE4LRsTqwSFOlqXX0VBWKeazXrLDZlfNRppPnckj+VXSm9u1fs4mHs5ocN+UnW1rrrEfM1dwfnsc3/J459Epz7JsLK+z8uatv2fJxNS9ubl53jZC5twGmbi9va3vW5t2zwDVAZx9+dUepPXm5ubFI9lJm2VAx5kBw9CfBqw2RNJqOcxTGbnaye3AMwM+gzn2Mw9EGVqcWLGfWcH0IHX6+/Tp06vVEwc4Gj1ldTZYcjJLGjkDZAAeeucY5TvF282tk/TZkkPSx+/kpGyD9UcW3l7n+lMouy0pNPjwmPU19WgznMlkkBgbSIX+nIDyLBliQGKyRhrt2+23+TVNaSaa13PwNR++323TU0oghlfLO2HVWSKVZNuCQJpht8znek5upNWklGSaL6/y0sbd//y37DgoI+5MoX1QN26fdKfBJunm5JRlnPjjeT5cz9jBvnksPbl3mxRpk7TNxmkf9+/fH//yL//yuLu/P56enp6f9j4xlZj+6dOnZ5/3zhrb0JYIWYb+Jq9pgDq7Wri1kCsyf/IXf3F8/u1vj//v//6/H08Bj5JfJ3q3Yly3fB2bHDPa5MmcS/KZkuJqo3+Lpy2WppiS4gRlkdo0r/ObEyDJ/3nt0JaOW7bsd8NJHk878bbf33u+ySpNFFoOjkf0r4S/PE8bpe69yJFkn/IAfyd7aXGzyYF9Te4/OOi2J8+YfJa5R4pLx5F3ybUJ2sE05tDJVxO/5s/9GC9azpPyhzYeSgtJ5t8ybJMcrE//TDjHssXwFJuIWfP+dMZY3lKXMHLLf1ze9NTf7T8LE6Hj+LYaewbGc25zCjLrehykJsDe2j6O1wkB/6dkYRzg9vY23gOVeKWhkOYWaDggpRM25yfdlEcKaE6sRmdMGHy/IvXI0uzBDskPbSSBJRPwlvDz2qHDsmzbEZM9ODiznt8XZqd3200+my8xsd0GqiO/Lag3Xg2mKcFPvLA/fnvlkv5J++Kkx9hUS9KS/Kc0mSc5peSMQMmg6QkWDj4S30kf5sMlJRGJbgfFFpxTXylwOsC2QES+vVXYvCVcbbbdkqc02UL9ePLEvKXgygFCslnLgzK1fK0Xts/+hjYeb/Se2QT7TInOfD785CfHH/zyl8fT4+Px7v7+OG5uji9fvx5Pv5tsmTIynK11M2BtsjVdlJ152ewwDapGvk7I5pxvWXl3f3/84k/+5PjtP/zD8dtf/epVH80vkzxTsd/6w7ZsV/YXDlDn+6qfJjm7Ltvm8StxrdnfFp/Zb8ILJ/6m23y1+OE+kw7P2ndOeIbBDa/bdc1HrY8tHm30pLaOI7+Ohxg+/8/oTnnO1RVT9ttk1j6JHmKmJ4pTHtJioidpKUfbULIV8+L/V22JnxRHkxyTfFJ/aQEk+cqGdY6LiYYrMajFz1lc47ffvGKdbDJN5bsGqgSE1KnB7ebm9esLGpAm0GXZZhG8ypAM4szobFwp+SEPZ4OWZBh8cFNSKoFoEp7nwP277ZlphojJ0iQBU78N4G2o0xcnGTgoNshTRuY3yZt9Dl3z7fOcQZs+eE/WnEuzVO6v1Wu2yG/qjeDYAKfZjwN6suXRY1rVpFxaMHfyaLuc0gbDlj37aLpNOw8scwanm5ubV1sN3X9LqM74SradVgatBwcbDqqHR08qsT/SmEpLPBN/CVMcsNKkWAqabtt0jm+RZ963nna4JBxkW0wY7Ase5DmAmg9OIvghYSlp3RIdnvfAlNhoHSef3RJ2+3lKAlKCkM7zN18ncHNzc/zkF784/vQv/uKZhoewjddb6XhfqpMq0+g4b900G271KO9Z6Z2HB801npC8vbs7/tm/+lfHf/6rvzp+/fd//yoOnfleikspqdvaSbwa141lKdexDbIe6Uj0JftgLGbcnz5TP/PdcCzZfvqkQWqTabLrht9nsTMN1P0/4VPTIelK+UGix7o1jqWYxN+JjrbCRB1z1W1K0iOvIw/UfctbTW8qTZ/tk3glpnPCzO2mxQHufBxZOD5MX9b7mc26pDi35RDkzRPzbNP5kftqx5qdJrtKsue3f2+8J1nwwX0cqFo39snjeH0L1Fm5PFAlodv5NBDyQ2tckjG1fjdlppkWKnUTzBmQOeBdKVbMONkkHPPgmlF0G2SPDA3cfjASAz63PEx/A3LewpQM6P3798+G6ARn2x5pWTOhS/LjijEHpre3ty+2hCXwT8c9gD8rm87dVxvwJSA0ECUwS8DGpMcrWdMeH3TDPi3flHxT52yTdjAJj2XiIDD1Z8s5648dUzZcoZxztOsGrNZz4qkN7hyYTI9llhK25Jdn5awefYT9kL9mc5Z1s2HPoLp/28TgBSeqaL/mK9Hp/pN989O2mCd5MSkZ3abJnjMaqc+0/dRyPI7jxUDEK6VOpO0jjj1JFz7uOEn6393dHX/2P//Px/0PPzy/o5QrpQ8PD89P892209nnUrzzgzd4LvnU6CcVy2xwhvHs8fHHJ0i/f//+xdOFZ7tyW0VxP06q+HvsOyW1KSmbOrRV690lTWa22OL/KZl2vPMApZUU4xN9qZzZtmnjdW1AkJJW13e8SbjB65KM2gDOMnEsTPpKk8wsY0u2tdSv65wNZFI7xr2Jt/xvui1X4+H00SZkTVv6z+vTc0go66HNE+KpTLuTx/qp486t5s0WfMMFMS9hcbKVZKPUi/GAsWG7hZFyo/yIi7a1hGHHkd8vnPhzHJxzxnxPGvt6LqzNcwVmrDA6YlsNJ8/yI5c3DVRNvI8lMKXRJuNPwZFtNmVvgaiBRQvKPtaMZKtjRVgpI4sJxFxNnPY5oEz32LLtcZqRbdo6MUbCwDwgwS1XiVbqjKuq3ArspM3BPcnGch/aSKvtJw3cm8ORtjSI3sAjtUWZ2BYSb+SjDdRYj6unnGV0u+SZq+TJZyjbdj7Jk/wTPM2rAS3hQUpS2qRG+p14MWhux+Z3079t35MCpuMtwHql7hYYr/aXkg8ep19SDp7pNN2cuLAcSZcHfsYo4secawnDlUBGuZC+K0mn8eRs8oHJoIPulkAzQSE91rX5SiXp5u79++P+hx+ODz/72XFze/s8KJ17Tx8eHuJA1clqk3NKcpLsWTfFPcsl6dsrKCMvx4N3794dT8dx3L5/fzzp1Wq2ebafZJ+wrvGy8UgcTO23XIS0pXLm8wn7Nrpb22fYbT7Nq23c/ZzF2URvGhBeybfs/620+PIWvE4yT7JI9W0XKReaegmXNpma9zM7Tj67yaedv4Kx6Rq3m+IMr2l54NBPbG73u7ps+jeNCVsaJpCHs5jkfjm57n4TvZaTaUv2l/hzX6m/weKZ3OVilic0jRum58zfXN609ffp6fUN4fPNEXcaoBpY2yDiTFjpGJ3hrQIYWq70P3VIbxoUJafgQJUDxXn67swS8ZuzFMng3r9/fzw9PT0PfL1lj32P8dJ4mnMaYIZm3vieBqqWi++DciAaedzefrvH17o1TV4lpN4of/e1OcjZtq2WFLgfb293sKHsvUrN7Xi0R5fxMfJPWXGCg1vBud28AX3rk3U8Q3lz83L11TJrck8r38n3HATd9nb+OI5X24ToB7x3b16/5aQsga35GRm/ZZXDATzJ+zjyU3R57QwCKecUNJN8bUfmlcGJfDbMt0zYzuDR2Eui70pxUsPA7nhD2pt9DO/tVgqvQloXruuBaqLdNky7bPYzffzRn/7p8fM//uPjtx8/vnow0nzPSkKTr20lJUyWteN5om++HRuMka43x29ubp5XTWe2fnYc3f3sZ8ef/pt/c/z1//l/Hl8/fXp+GOBWGn4nmrfCeqabsYyymuLcZOIdj5neDXOarhKdm/29hVfHJdYbes9k7GMtxk17PsZ7l1O8v4ojzi/OZJauZ9xMK2D+T742DGDubD87s4nE4/xmvpl8kXodP9ye4koZml7fHkX60wCSdKaJZfI4n8HZoX1yTb8bmu2zpFXcNKB2Sflkasc43vIV6y5N3LXCRadkA1t+0XhIdjkfvsViHpz0/v37V3F2aEv+tPF+Vt78eprjeL2dtjm8j9HBWc4AIjHoVdrNWd3X9ptO2K5LM+rNKdyGE+AZpHFQ6pmL2RacjOg4vumDT/RMhs7EkdfbQB1I5//9754o2baUsJ8ZhA14EGDSDIsTlpubmxcPqJo6U//KlhHboJNBtrUlLaaRHw/AyVeaDCBg+6l0DkQJUBgceS7pk/3NdXxyKoMGr7OsGh/H8Xpb1HF8m4BIvjS/PQBIxQm8bTd9kn80/Z1NLiWdUk5b3y1QtPMp6TJuzvVMDB3cea2TQcvbW8gbHUmOx/EtWA499NM5T/tzm44blhNpGjv0Of7nwDk94ddP5zZ+ezdDo5syazaS9HaWqNhvqav7H344fvZP/+lx+/798enTpxdP8OU7UXkriO2n9e1+XTfJOsXXMx8afmyX3g0wMXHi3+Pj4/PA9Rd/8ifH10+fjs//8A8xITatPu/Y3SagHD9bfnJFx2zD/trylHa++fp8p9/TDpPard8tvqW+U65xxkvCnLNrpm4aMKc6V/hM363vqdPsZZNt8iPHC0922CeTrDeanSv5+pRfHEd+ym+Ld2lByhPCYz+c5Hbe0fx4aEyLErRPDlS327/OcI19GOMTXWwr8UDetrzEfbN96ystDGy4PMUPYE02y+fl0A7SMep2sM38WGYpHl0pb3o9DRv1YNXEJNDc6p0BXXPstOTMPvz7SsBJyQxLAvCU1G1GNknR1EuzaZy54IwG61MeBKL5TqvFiVYOkuf6ZMBNVzbeSTTm/qnj+OYoM9tvcOAsEemyPgiCvH5zEF5rx7aDbcHP4JtWY+m00w/9Z0CVDz1Jg4pWHITTb+rDDypgO6Q9yYG2YFlbFmy3gbbBv+mNM+cNzFpimOhtdHsFm7a1+TYnShig28QZ5evrU3+UqScSGBi35IXfnhhIPFGu/HaS4N/HcTwPKBo/SY7kIRX6Du1gJkJSW57koz4GOylTThrx9gniu2lKiVwKwvarlrQ0+35u8/b2ePf+/fGHf/7nx6dPn46PHz8ev/3tb1/cn8pJwO0hZRsd5iPR1fxx07ntj3Zo2RLbRoek6Rd/8ifH46dPx9/+6levJiLcFtskHWkCIsnC/KW207WMyQk3k+0muaY4x3ZSztNsdosnpOXMd1uxb2/YneRnbGl9bPaX6l4tV2W22YwfiLn10WJWiyHE+Yb3qbgd4i11doU289oGquaZg8kU3xqmHsfrV/A55x7M46LI9NPkc4a5V+TKkibH2Y/16b65862VlMOwH+O5r00yGNo5wcttvGkHHnd3EsMn/p/lXYmGK+W77lGdzpvDTKL69PT0yjG8Wncc+/u1qAQPzM4YTQprAMQ200C1zdBs9DrQOFBZLjYO7gX3jct8R1HikyUlCSn59U3qA0LcNrrJd44ZsDlAvbu7Ox4eHl6AlB2Bg3KCIb+tf84azveAWAJI6ntWGbcEzAlOmpF3wkDdUOd+0t0WVN8aLJygWRY8tu1GsBzTCjDlk/jf+DF4XQGtBPwpQJAeTgzR9l0n+Xmy0bSzYQZALWBNG4luypB2ZhkxkHng6P7SoDQNEBJ/vHc90Wn5TBt+KFKzC7aVArePpXo8ltqmDIzp8z1yTp8WWNm25ZYG88lezxIKynls4E/+p//puP/hh+Pjx4/PW3354CQmbZaH9TD9Dg8pViU/Jk1NJgknU/xLdsF2iJnGuMfHx+Pr7z7vHr/dRtP8zvlJwlv7VcISF9tswgbqfbMp5k2WTfueNp2vMC5exdSNV7ef6E74k/yT7XlA1vKsJLfWZqPxzOY8kXQWU2w7c53zJ9qxdZvaTxidYkSyAbbra/mbPJL+VK/hF387F/NkZVs99TigyZsPJ2JbxBo+SK5Nyqe8KNlMwgXSln47ZzZPvGbq2c7PJnlJk2Pihl+JN/vS09Prh1o6p0w+zjbSILXZwJxPeN3K5YFqS7LcMQXP/1YwSyN2u8YO67ZSH1RyApvEF42gJSgpsTNNCehsqL6Ws/5znLNFLQnbZHgWKBPfW9LWys3Nt6R36JonHRMsDIBMTDgYT6B4RhPlufHN/5SXE4i2osq6m+OlQLPR03hKg/fkK7a7rc0kh5QsNPtNvG78bdcm/0nJTZJ1o/lsBXwLDi1QX8FD8nOGEZ7cMH08xsCQgoj5Tgk67TAlL+SZdG72YD06kTJfW0m0btcYx9g/B65T17chpLLFqk3/6fxmA0mOt/f3x+39/XH/k58ct7/bneLdGL4ntunYcuI11G+63nid2mQCmZLFFA/d1iv+EXuY7Dw+Ph6PX78eX+WLbbBiOlq+YNwkfbbl1u5mD0kW5jnZufWVcP4KHantLUZs/bQy9pQmxBL/zjNMZ5tYS22ZDtuuz5s3Dzha/LKPpLhgzDR/DeONCU1/zR7PMPUMv8xD+p943vIDyrrFPn7zutvb23g/6mANV1GNOy0e+XyKT0lGx5Gf5p1y08anjzv+pLiY7C35Jj/NVrZ40PSVVsobxqW20kTN6PbMXqdcHqi+f/9+BYVUuCeahKWg0kDX/UxffDgH60/bTN7PVl8TGLBwIDirxRR+Aj0XJ442zm2myitYt7ffHj7EAYtfseAg0IC0AcvweCUIJxlwJfaHH354BpS52Z18pwdv+SFS7GtbwfFx8poSqAREU9crh57VS6sYlrH1Yb64CsF2yAPbTA/csh6GF8rZsmhBjoFneE0PmzlLQDb/bTJLiQNtPIEm22sgmYCyAbTpaqv4U8cDzBTM+b+VlDAkHjlxdTa4bQ8yS7oiNptv08m+OLO9FduPZ1nJYwt0zYam/eEj0dJsh3omna2eV0xSUmA+KDfHqPFNYs3Xr1+PX/zZnx0//9M/PT5+/Pj8JN958NdsdZvdIO6LMmGfU488NqxtiURKrNgmY7Pl1ZJCT/gN7WPjtDGuJM/xFv9s522iM+HtfJv3hAEp1xi5+L/b2+yasm19WtYpcXZf7CfR4HYTljU++EwK2ucU+qnzEj+UhblWwsSW15meM590zrG9qWJo80qhY3qj1X7AfIv087pEQztuGSSsJxZSBo65KTabH/qhcYU8e1ec+aTsHBum/bkvn1jg/Ons+SVcvWz6td17AoO/t9zA+pj+xy7bSvHUt++7v4Z3c934GeXd8h1i+JwbfbXFEF+fdtO4r82vWnnTimojkAQkZTHZSADI67bVCxaD+bRpg3JS4WsacKe2U3BPJbUz/benY7meAWyMYAYnU4dGbXmmQDQyTjyyzWnDztP0Rtr92zK7v79/Jcs0k0mg9WDs5ubmlVNssk/tJMBm3y0hoZwof8vHwZC0GZxGNtQjZTF08mmYTC5TUmR6WFg3naN+vn79+uIeRMvBpbWdbCLJNk1W2C6cFFAG5CG1bxpaksjrWlJwJSFxYB5+qKPkn1yZaPZtupIMUrDwb85GpwDtYzzuAVdqf/jezie84seySDpKbZNH22Pz11YvxZNkc4Odrkeb5MPvpo0vX74ct3d3xy/+/M+P+5/85Hkw+vDw8OL1M5OgNX2mkmQ59FE2lsdx5GdSJL+jHbRkKsnNbVhmnOS8vb09fvkv/+Xx8e///vj8619Xenmc8Yx6vRI/WH8rjgntesu5+a/lS9xLExAtfrbPVsf0tY/597UNg6iPFiNY0qA7yT/x1PhkvDHe2XYTxvMhjE0OpjVhiyfPHN9ckhwSXvk4C/OO8dWmI25pZpvOE3jMfnccL5+wTh6TrLyDItmRMSfJaYvdnnhJftl8dGikHbcFAxbz5+cibLaTfMDxyFhIHacYPNfz7QjpY9+gPof/aX9iyUw+pgmuK+NJlssD1aTQdj6VLaHfAtoAgvttQdLttdlv/rbh83xKqJoBb4EvXcOkoa0sHMfxaoaafTkY24gSHfxOwc8gYp6S0ZqOFuhnsGWefeO26TDtpMmz8S3Yug3bCI8TgAeEkkzmfOuPtJO+bUaWdNmWPVBttsuSAkyzB8uauklJHuU+JQVP/2/+MfRuqwIulMGGCwnDks00Xrbg0+zdtjzBgeeb3Y4sjA3WQ5KD6d/s4zjyQCVh6N3d3as6HhQk/Es0bp+UlJi3hg3uNyVULT6kdps/Wr7+nXzLNnocLycsv379etzc3x8//eUvn1ekOFjlFrertuv/Z/VT8sMYTP64ut/yAttViqlb4arply9fjvv7++Nn/+yfHV8+fjw+/upXz/i8tcOkbMMQy23D8att8NoUb2wrlO8ZT/OdbG3sjPblZLh9m/+ECUk+1ufUS/1u8WH+X1lwaD5IDJ3jvP9/zqfdXIn3Ruv8bgMp1mu6om22iY7Uf2pvW91Lk1vTJ3Of+e3Xe1Ee3LXS+B76HBvScRYPVL1gQjqsn7aokuSV7LnhmWM1bTvF6Q1nfO9tilHW3VWMHVo4+TB6ZXu8Nj0DJuVh7bVF6TaaFrMbH1u5PFB1gjKEkIDjeL11cupthCWAGaExwPCTVjPPwHZ+p4SozWYkvtxnA4XGt+WWtm+ma2ngY4icvaasnFiYvjTQNE++3oO3+U4Ax7anfQaGlnSaDh+b49xq4oFikrWTwxQA/ZvXcFa/bYNtiSH/W6/TX3oQQwqc1El6uFNLtqzvRjOvoV3Ob98bxzYSUG/ASnvd9JDkmQLblUTze4t5S/Zq2iiXm5tvr1tKwdC4xH6n720HgQfopu8twY7tEv9mooQBzclRempuSjRSUG6yTLic6E48pHMb1pj3acMJm5OW1KaTH7b99PT0atva4+Pjj/ehHsfx6ePH48vv8Obj796ZyvcDUqam16X5gLE6JS3zajS+Iu048opHwqIUZ63bRBN/p0nCx8cfH6g0D+izPXGljk+ZH3mbhpY7UH5n3xtfc5w6avaX5LHlH/M9ExvmK+lkoz/14eSfeZrjWXpNnrc5biXJhblFonmLw+k6xh5jceqb7bjelYGGfcxtWUe201a4MLHxkOhqt1vNfz/UMuErdcvXz7hf64d9W04j08fHx+PTp0/Pv3lvKrEqyTvJ3+fsW42/5ptzfOyaeRx3PaaHerbc0X5O+yCvczwt4vE85cmB6xTGda+gJixOduyVVcsyxe80aN7Km1ZUmzDab6/qbUSZEYPsFRrYjgF8M8IGckxApq9tyToFvS0Y2UndTpONgw6NkXJKwc0g2QCINDHoJF6bQfuc2zwz0hRcknzSNUl37RoXBwt+X0nA2E77b/kngLgyi8z/iQ7rur0Wxf/ZJ4NhGujOJ61qtKDBPtJgtdlkkutx5B0W89824WOtzSvnr9RvWHTFBxxUrONkB43XM1zgd/q96eUsqNM2jFlnsk0yarbj0mjacNl+elasc8vyzJY54Hv/B39w3P3ww48rqL9bRZ33o6bBaaOb9Df5GWecrDJx4f3wxMaEgzzWBtP+P+2SXk/U0cb4lOYZnHmiL8WLhp3tXJNh0nHC01RsJ0l/yfdcd+r7nnXLyp9Ef+vH/VFHWyynDtuKd+J3y+9sM+6b/Kfr2UbKTRptqTR/TnmPsbPJizJqOk+0tXY9OZ/qe1B6tqLWZNDobav5Q1saqN7c3LxaceRn6zOVZq/ON8zTtkK+2Q0nyaYd54lX/bHxuvme6yT9n/GS9NT6aROWZ+WK7qa8+R7VKWfBPzlOUsaW6DDY8VhL4E3ffJqjpb43vtrKJz9tZaPJZRyG/XA2zfRwls0DhwSSaYaGjuqVEfPFAEwgTY5HHhLAJT00wG+lBd0zx026peynDlevvn79+iJRJGh65ehKsSx4nykTwS3p3gDBiYT79uworxme+FACT3z4YTPW/9mM8vye+vPNgLklb76O9JMG192C0dUA5GLfbv7DttOEGekzrS1QTfJnGZ7hzZZ0pGK9mEc/aCwlgfQx+0vSlXGTAxjWPUv8mt00v9pksOm2YaATsORzlOMMuP7kX//r4/1Pf3p8/PjxxcOT0u4Rtn+Vh2Rn1jEHp3xFmgeqadU8rQrNtt00iLAuSVuy02nzy5cvx8Pv5HNz822A4hg919BHTAN1Zx1Psd80u2MbV+IC2zN+23/cNuXcchfj5ZTZIUc60iCf1/oBlrymrfimlZm0sjPnkh/bX1IOwcnU5JOpzXTcfVIP7tu6c87V4sP0kex/y13awCnlPk3vLMwJ+IBG54XNLub6OcZ7dgfXGkaYtpQfMA9JNp7ieeK5YR3joduhvBPupjh7HN8mjbxrI/GQ9Hf2TR1s2HNWNnubPGXb2j3XcRHHeTFpSbrb8NPlzfeo8n+a3dicJrV3JngaPFeD0jI4r3cSNMEy1R/DbUlACppbwsxrE29u03QNIPLalHgxGZj/5GUAh+1Of3N85LIlsJO8JD5T4jbXGBSGXm9LvmqspsmztM346VymLwExk0fK1gGZA7kGDlcCxpzf2qO+N9Bm/bPZUgYCyiclQp5ZSwnEWTDhcQ+0yHtLeprMkv3N+RZQKNOzpCnZVQuSqe8z/HN/bWBI26Xv0DbNi22cgbnR5muNq8Y86oBYZpy7ubl53r7FQDgrYm1ybtOh+Wh4lGTuYv2aF8qAsmh25uSI2OyJvp/8k39y/OSP/ui4+d1raDhATU9STPRSBrSlhHOmMX0o2zQhRT7SCgjrpC3hSX8txk7/fD3bp9+9T5a5CO/dN6a3QZVxsCWmyZ7ZBv1hK47rLX40fXjCy5hHOZ59b/SRr+nX59OqFGlPNrvxm/p1n4wVpIPXOe42e0t9t+sa/rdVQV+fsMntpJzJPuctttQP+z3LOZgLTm4wW/zTltIW793W+OP4XKLDCzqW1dlAhzzQ160n68W8p9y34cGca77EuikXSr55Zoculof5atfYZxK+EyedI250fE9JmLGV7x6o+lgC1bNrfLwldzPoaslH6m/aozPRkTceWvsN7JITpYC7JQQNBPnd+k88Pj09vQjYU3/6ZLLogUxKZihTbjUyPRvAM1lICUOTXzrX5JfaHDvgrH5zkpQQGhCmHQ/aWltso/HnRMd2SNBMwd9tWUZOKDY/SAF1SkoInHg13bN909oAz3S1us32UmlJzJY8XcG2Rnc7ltprOhqfTe0l359ifzOebbJ3sc7Tqo6f0syEYPr1wCvZzVsCYNLjhkXJptL59nvDCNZlwpmwlfq8//Dh+IM/+qPjN7/5zfGlbPV1X6ad55Lsz7DdcmGClp5M6YEqB6VpMO9JDhbyY33Rvvkkya940NRxvJy8Jt8pQXRJdBnbUtxKNvc9yVuzwbO6V9vk/5Sb+Df/J39nnYRVV+J3Kw2XrKMzPq7g+7TjPOlKadjNCa5kE40P+yxz3sk5GAcSxp3F0eEzYRMHrL730+1vq/jkxW2YZv42X4wPm7zSb5c0gZryo8Zvw5GUNzlOWAeW0/Y/yfgsVqY2eLzlyMfxbazFthq/rbR4PL+v4hfLm96j6sJA22bWSOhm2GfJIoWVZp7cfwqg7svtt20jje6UYPGcv/1J/Pt3quu2nRQcx+v7dXwtHXMA6v3798/bP/xuVgdn9uOVdX5PPW4bmoFu0tuV1bSp61V1Xp90560MfgKg9cl+KOPHx8fj/v7+RT+NBrbHNpIdeHWCbadjTSYp8Jkur3o0n3h6enrxIDWet1+nAJpWPJ30TCCmHlJST11NG571O/Md1kmBPtWjPNP7Jh2YSONZUmK5bsXB0qDfjjVf3BKywVDLn3y1hMlBP63qzvcMMjygIX2bbs58Yvq3X7gt2l77bP2SZ+5kGD5T/+SX7wflK2j8ftoznRnf0wRVkwMHpVPvy5cvNWYlDDGenOGAi7Hx8fHxxftReWvCgwaqfo8qdcNv+yLll5K69HvaaRMJ1gevsQ6afNN1bN/9+H/DpZGzddDoTfjaZJj6d6zfeHSfm80kG9p4b/Uanje5jN4ZU7f+r/K6+WjCpzm/YcIUDtQm3/vw4cOrbf339/eveKWdc+eEX63iJ9jymHcpbHjCWM+80Q+c9G/LK8mf8YmTh47rjEOm27qinCZXTE/zTbG5lWT/ibZ0DcdH1j1lRZ44UTFypl14K/hZoa0k3yM9V8p336PKDtlpAqO3go3bTEDH67jNIAFk6yvROcfZ9pwzvwnAE/3m5Qrvpsc0e4Ui0e2gyOvpCNya9e7duxerrPOkUhp+GvSPrFOf7m/qpARxC4BuizylQfmcY1BJSQVpaMft7MmO0pPsaD8ELoNcA575cMtbkgXpaoM80pt8JA3yj+ObfTm5Id1JJ9SzZeu6pMv/7XtTOEilbk0D+0wJc6LFMrbezkCWtFsObNc2b/mmRIj8XMEQ9+P+2zFijWVj+TXMT/3QF2eyaWyMidCVeNH4p0235I+0Jbsjxp7pjbyd4R8TsuPm5vj5H//xcffTn75K8pzcsf1N54mWZtdJjp6U2Appbu2+pTScirTLt43Xk2DNcU8gJr49qX2FlsRnk3uzFdpZyz1M81UcTfowBjaM5XX2gStla5NtNd5SnHX7rJN2jVzl88rxDXvSSlTTE+umCZBNt8S2M/lMmdyEg5EZiMz3nG80TB/Nhrwo5HzBNt7ap/6Ye/LJtB5gkvc0eTT0so+028Q2MjE48dByQebB/D7LNVqOtGFzwrFkk+SRODhtnb07lX0b6xmvJ0/lmCLFryu4wPJ7PfU3nU8DhiG2JYk0ipYseBV12mP9WWEhDVRUCqpzLiVx2zbLlMA0uaRBTpLDRk9y3pZ8pHYdIBkE5z5V3q/atoOQhkZf4nP6mu9N52cBnm21a+iMnqwwgI4sHNiZ4BBwZjDP/i2zpItmf3Rwy4tPHW7AS8B5fHx8AeRsc/jwig95T1t++Hh1P/24PULf9kb5Jf21iQbrJfldsi+eS9sVUxA1iJN22pGDXOPJQWpLHMkfgxFts/G8BeUtUCb5tmDa/G8KH7STAqhlbVkOzswsPTGefbVdACk4t1XFxF/i90rMS8dSgCedfM3V7f398ct/8S+OL4/fXsVAO+UK4tlq/kZjkxVLi0c8l9pNx6/QlZK87fMqoS80Jyw+jm8Pe/FOAK8WeSIx2cEWZx0jmw0lHo8j3wfusu2CoX+5/5SD0ca2nKFhb8tDWDdhF/9bF82mUixIMvCkBFfq3K5jU6qzYeScd6xN/DYM8iLM5LJun7w5Vqf4NYU75ObDgSrznISv7D/Z63zahPpxHDE+tHrE7hlY39/fv3jwk3P94fvh4SGuhiY9cAFmznORh/V9bbJp+z7zri2+smz4m+ywTa6Z1jRumP+8N9m7KZ0/JHwihl7JsfjgrSvl8kA1OXESyNn1CZASMDGRTqN7Czwpg3UJyC2YbkZEum2o5ntLkPjdjGvOW8EGbLY/dYfX5qDugzKYLVTsz+/aur39tj0kzUilPkgXj3uwS1rPjJigmdq0nm07fmJpAp3N5vluPuvj9vb2FVB6lYRyNu2jT24h4TsXk+9QvkPXBLvZjsIEjkCUJoEsa9LDAWt6EqR/00abjTBgTJ8zYHFd64RtG8xH30lmacKgYYDxJd1zaJ7NT8K7JOuWNBlDt6Df5NwSUZa0cp4wzPba5Nu2ADlJ4JO1OXHjgQWDIWdw2a7xkde3JJ6l2V+6LuHltDHy9Ja5L1++HL/8F//i+OEXv/hxC6semjTtMqDbTyl78mfbotzT7yux2/rbbO5KjtCuT3jKVRPmBk7u+YRhP0eBydHNzc0LWaecZNoc7HD8SgnYmQxanuBzCYNTW5xATR/XS8kmV0nSUz6bbbS8xr8bj+6H8vfEMX83elKuRFyac2cr/3NNyk1Sf447bJ+213jZcgzHS+qx2VLCn+P4NlC9v79/9URvv7Iu5Rks9sM5z7cC2Oaaf3HyYK6nf89gmgPryVsot4R920KTeXGMcdxhfeMt+2uDM8r3zLdZlzSPrOzHzq+STKgvb+Mdu+AkAPMXypJ587YAkHj3sS3muLx5oMoOz363djZDYDsUrgNWGgS2mfPkJFvA3M5fFe4WOAiGm+F6QHMlaZpy1nYqBl/SPA5BGXvWxTJPsvCxVP8KnQmwk4x9zgM6ftvBXSxnO2QLygZs0u2EggAxgD+yn+SLT05N9DF40tcMyJRHSsamXnpQSkpcz+ixrJxkzfmWQBCMf5/iAOM+Xde8mJ+0cmK+iHduO8k8/Tb9pu0K9rY6iYZkr+a1YbHbSlhm+UxxMHaiw0L/4PVnmMl6SQ5MBMyvf7dPStJmtv/Lly/H7fv3x/1PfnJ8/PixriS5v6sDVdt1wrQrmNvsr8nQdG0xK8VWY6knnjc5G6Pm4wmVxEs6bvn5fErIrthcO5bw8qydhKusYx8jzeYx5WOkxXid7PP3LZtNfk/7xC0PoFr/V3D0ar7SsOgtOEw7n2udo6XJObblHXINez2hfgU3mt867055ScM4vxbr/v7+eZCddn2xHz5TpMXKVlKuttVt11Eu7DflTWel+VfzQ2MnJ9dHlp5w50p7wtabm29Pq3dOMzliynEazW8tlweqQ9gWeDbAYiDxzBnb8P8kTN7w65WhKZxxT9vJLOy2ejPXeDar8Th9z+8WaNN1NmDOcLbkJ838sY80q8Q+DJ6JRl47ScDImzdcN3rcflp9TQ6eaDD/rm/ndOCeGUDOFpme1IcTPs/q0f5Gd5ztmnoeoDGJ4v0jBIZpbx628vnz5+f/Qw/5TDIgADFpTjqyPpwI2r7T9ZsNUE68ZvOp+Z2Cvf3Hs+Zt5wKvIzaQL/fBlfKpR7qSHc71bVuMbYx2k2yIxRNHLh7ctcDIJJ91nVQMDcbdwQDTSJyi3aeHVxBn+Z7HOWef4pZFFmNMkl/yWdu72zevxPYN0xiH6LufPn487j59Oj5//vzKJjxpNYVyJl3UrfEryajF3pS8bsdTYVuWH2WT6N7iEeXsZIrxe56xMLYymJ9WjvideGTc8znHqLNVuCSj7RyT/bOcY0sAN9v0veFjh2zbtNl/GzYlfE05lvs647PlMqSPWDS/vcqXeN2wlnIzD8aBDRfYTmuPtNiP7NPOl1K/aXD68PDwwj+IsXxyd8MG+g1vd5q6bM/53d3d3Ytr6dczmJrtvsz9p551mHajDI1nujQW+InrlnOShfs2VrW6Z75mOn1uYpBzYd/PO4P++/v74yc/+cmLMRT1Z1nRLiYf4TNLmrw2u+fvs3xxyuWBarppmSUNDIYYK2Yb1JBBGmIKelxttVFMHRYKkobZluzdzlnC6/oOgumT2khJRqrr1QT3cxzHCxBqKxIuZwbGd9IymUs6cLtNV6n/JKPktNQLr/W9tU5yKK+t/5Ssb8mfaZy+2YYDKpNTt59AqrU5enASbb7O+uDx+U79Wv5s3/R6ENj68v+UeDgYt6DD/q3XRMdV8GxJxlZsg1dnrelfLTFtCS2v8XejjUk/220TQJQH2+Pv7eOJhVa2hM6ySSXZpZOHNrFn/tsDJxIWc6A+A/DHx8fjJsjwOL75b8O6ZqMJH5tMKK9nepaEqrW/4ad/mxZjC+sZ05mgsk6yHbZFvtJrkSZO8PjEVcvB+GHMbfxahp7carLzsSQn9n3WVmpnBgFMeJ10si79oOUwyU6ITclmks1O30Nvwsh0DQembCPRZr+9Ql/i13ltipvsY86nCRDza39IbbNdYrbbTDRR12eDNMeWFGus8y0HTjmaF6I4OZhoTjkJY1mLs84VbBvmw7JIv5PM3Bf11GKydd+wd2yc8vJ9phzoj2y9sm77IL4+PT09T7TOYsk8bb1NbNEPjBXOg66UywPVCbBpBnqOO4GhQlivKec4vg2IG7CkIJkAcGZUHRimbQKyA14yQpcEXClAp3ptti0F4XT9FCaQc50HKabBfBqozSO/zfvT08tVIvfrdrYgl343+tge+Wo2OVtG5tjGs0FnQNH13V8DQLabkkVe0xLFBlAOSi2RaomOAdOAnORt/2/Jhfl2362PZOvslzbE1aUUdGbF2P5P+W20p3LlfLOrNtBM9pJksa2sND4Y2M9obn5+HHk7Ea+z/SRbNN88l2i3T/m820vnt+LA6qSA7aUkwANVY5QDMwsfXGf/nATONE2dzU+TT1on9kVfZ/kkDPK1rXiAOcd8bcK+ROsz7j0+Ho9l1Yd9MmGaZzCYvrmOdjx9pwnslHj5u2EjeWpYx99Xrk3+ktpL+QplNTbXVqict9gGW7I/nxSXpo2WjJO+zWZpB54QTXbcJldbTtbky+O0NfdJmXkSquF/4tM0m3/HOrZDWbZJ3mbzcw37dhu0H9qp+xx8m9zMWMqVvinGzxZjHU8oH/t24jdhqH3NsuXOooaRLb43jCBNaTBIex35cfWZsvTAn7KmfkdXHpw+Pj4+37Iyr07zjr6GBykGtsnurXzXU3+dZFFwrJ+2dw1z7dHFTt6njJD4sISZJaCCpo0rgzw7lWmw8NsrExLwkodmoAbLBKiWaWrH19GwPXNOA0/0u2x0tPrp+s1+Wh/cHjLHGi3DT3LwcRg6aLrfuZXNJieoPz4+xif3kk4PkhsYpkTOM4gGZNrSBEz32+yTNCaZpGsI/Cmwsb05nmY3W4JCmmg/KVmhbu1bTBSenp6ebap9eJ1l0WzEAb0lY6zLB1wNXnlA4mJcavJIbdCPkk7Z7iQQTUdu236Zfk8iM+1NQGTwmrbGl8jTyGyu53UMronXVMwbE930aTP75tErR7PliuXr16/Hw8PD8Yd/+IfHH/zRHx0fP358nqGeGDff89uDBz9tu8W548j32V6RzVy7td363/oY/RhLj+M19t3e3j6/y3Xk/vk3vzn++t/9u+Ppy5fj6fHxxerBbBkkftF+GS+8qjD1+H7IxBMTu4QdV2Q1vLVzbylptc30Wh+pbw5EvZWT7fn31EtYtG2ZTriY8oe5Jvn1/PfWxUTLceQBMelJk4Etvrk/x1nTYPkl/Ei6d1v2Y58zNnJCjHpNftHabzwzxo9NjxynnzTINKbylif21QYz1KcHcvTH9NaETd7OT1yXuJUGfKaPOdJxfMuBmqwbn7RTDjy5OspB/7Q3MuWxZBfsLy3izSrq58+fX6ykWu9sr+WdzMnPYtGUNw1U5zsBNhltwZ7XtBWNtGJDo5xzfAy2QYJOmJLjs0Bgekk3g/7VgHJVGQbjKwkFv+f3WYLagOgs+JifFgzSsRZA2wrGzc23LYij3ybvFkBpN7S7GRgYZDZezRfPGRxbYpRodcLMuuQ3PaUy+QjBlIla8kPy43Ob75rvljwke5rvNHPf8IByackj5UZ9O8B4ZtIB29dMu+aJwcaz5V5ls/ySnEYWlKvp3HRjObcg2/TS2hyf8YCutUM+bYsbXyyk4QpWu9+34GfSN6/dZM3rEr1MLNjGYM8PP/xw/PDDD8dxHM8DVQ7M5jslYaThTE5X9G9b8e8zOaZjzT7Ormu08/vh48fjHZJcf7zaw2/6qHVjW5qS/GLyi4QrLG4rYXSz1ZRn+P+VgerWR8PUhPW+hvTZn9pigX0m0ZLiuHndypncWrz5nrzuDJMpj8HSRMfVvtJ3qs94xAeSJhxJ/TRdNN2wjbPVsm3yfGubsuSnPcV72/qb+HbfV+yh5Rdz3dnYI/HvvGe+OSHnFen0rJ40eUK7SLHL8pvVU37SpPqVXPGM71a+e6BKoqyImbWxUI7j5SOsGwPHcbx4VcHUm+tubm5ezDh/+fLlePfu3YvtVAwk26DVPFqZ5H3KleSgyW6rswGC+00f1uF9ZslQN3Dd+LIxNvrmO630cTXAM/acmfGKk/khDfM99sUEgt9Tl6sjMzvFGfZNDyy0NSY7nEVLdM5vvyjZ9UceKQHwroB0PUvSt+vRf7Z78Kif0WMD9RRY0vaRxINXvj1zeBzHq2TTSa3bNpgmGaaEKCWblmcbqDYbGlm3Vea04mddJjp9PUu6zoNtBzAnBKTlLYX4lJIZ+rED/WbvqR37Wqt3HPmWlC3hvLl5vcWQurENcAA1/v6zn/3s+IOf/ey4u7t7TgBmxvrT7x6yNNvXZ4U5TZQ2OZDejXfHlU0GbympPR5PdslJNZ8frH68uzs+6LUV9/f3x4cPH1483I/9HcePsvNWONblIIL2x/xlytjhXMM8g3XIm+XgYvyyTW56eos/TNxpMaK1vSXaxNomj5aobvnRmY1brmmCgm2dyYlxwzZo+hJeNtvla9xa3tSK+9mK45xjZsqNxxaSz2w5Z8sjBu84SD6OfXfG0DPXJj3QvoZuPiw1rZ6mPMz5DHk8mwynPoytm6xafpN+U7aTh93cfHtA0mBdeoKzaUlteiKP8ud230+fPj3Hod/+9rcvdvd4op5yoY2Nzt1Xk20rlweq9/f3LwhL4OTkjUnJBKC0gpWCGOu2QEtQtHN6gJISnWaAyQFJzxg0+2EwJH1ug322ZXLSM98bcLSA4P63WeZmSJZNoi3p0rK3caYAZPmnLQpJP5ve0r1e/J7kiEnLFhBaMjeAMfrnq2S2AEkbnv+Wc9N/Wgm0LrdiWdm2mBRbvsexv7PX9DDojF6O4/W9gVfoTSVhiK/dbNZ+nPTsttIA/kz2rX6in9hG3DIPCW/TAPgKXeyfiUtKyFh/Shrwpgk/JkpsY7Mj09f0nP4nvdBfWzE9acKAcc/YseHS3bt3L2bHPWAa/gZDZsWVttAmIkjvFf2Tx3bsig0l3lOcJI2Ui/F/Vg0Gm//b3/zN8fDx4/EHf/AHL16pMAmcJxpNx5yj3DgJOro03x7Y2QYTf/afzVavYna7/WhoSr8b7rkkDLqCg6lN527E/rP8osmZ16aYQpsxVlHXnvxLckj26fjacg/Sartie/59Zg+cxDkryQcmx2m5gn83vSce538atDgOpHZ4DWnxfeWkPU2iO9+ffs/4tZxMm38TM5JM2kLcli80mxgeiXOOGcfxGtPYFj9+iNLgm1dPP3369HxPKhcG6ZMjcy6o2AdpE1fiUCpvfurvceSBqgeLDAgUvAXnwjaZALjYKNx3SjytPIOH6UhG5cFqeuUE6ePvxreDc5NTS+L8SonjyI+9TgHAdKRrku4sD17rxNqOm77NKx3UgcfgxBX8bfWPtuXkZHTJp8+5JCdLdHkAua0COdFpemB9+tbVJNTFwda+0NpswT8B+ZybwkkDDlQ9cZT8nvQ2GU5pQSLxYBnYt1pyxtnMlISl691fO0aZEl9myw2vSxNc7L/Jy7+NM+bLwS7ZinGs1bVcriREqdg+Em5RTqlN89za93WUkTGb/ZuWF/J4ejqOp5evTeGKXpugc4x04mlf+F6MaLynssWIt7RH++G9V/P74de/Pr58/Hj88MMPL46PTxq3k14pD95eckYrdd6wnXylWN5i7plcHCc2nSZ/b7y5/YRfm67SJBR97qrdJP+wv13B8zP8mfopP7I8zvDA/c/vhG2pL9rEyOqqDaa+myw2/Jg2m1xNN3OPJpOtX7fb8tM573vxXbj7a/qYmNlWR5uv057Jd6OxxbDkS0kubjP5Agd9xkMODo1Jjglsl7pjbpEGqvPbrxmyPTqfTvKib5zhkcvlgeqHDx9eCI8dUzhtcOKVpjbi5qzyJLYc7TMBs9HMNqkNHKYkx2lGvDlxmtGZazaj5bXt40GTDXgKHxDjvs3HBlDNsK2v5nAcnFwJdKQhDS7SA49SAHK9ke02k+cVC/PsWTXKhjQ4oXxrQtjk2ZKgFLzZ1tV+eGzk5WNDg23dNpmCVloJ9OryAOQ8RMaTPab9OF7a2GDC7e3t8zvhElg2WbRdDJSrJ0vok2nlva3e27cSDtjfKT/jX9LrXJPsJQVYfm+rDKSNk0L83vxz5DJ8eGKPfHoykTsdBud4bWvPdp1k0CbzEg9tVjjho79b+U//9/99/Ne//uvjn/8v/8tx+7sZcmJfmyxLcXbD2TP8ZUn2fNbGceR78Oc6+1TCWidj8xCqd+/efdvmdnt7/PpnPzu+/G4VeupdifdTmMQ2vZHGLUltvjbnt2TeiV566BD7SdsaLfsrJeU9TDb5P/HtY6m9+X3FHlNscfwxTrFfx2HG4zObPI7z7aib//4+hXlKkt9W6EfOFWnHbYeYfZH+6dw65VU+t9lKy8unrvPK4zheTMqm+NVyJuLnxIM51ga8pmkwZdrYctiWV7L/p6enF3aY8oeW329xhf05fra83hPeLQbPeb7f26XFQdvO+GST09VyeaBqwU2hcfPbg1QKz05B5/DHsyJefWF7V4LqBqwupjkFr6nDGTHzuSUSThqHFrbnAYJn3wg2qW3TmhLTZHTHsT94gnIz76kt05DsgQZMu9gG9TOYasErJf7bSt7w3eRCmSQbOnPgFKgdIBxMKSe2QSBPgTXpqx0jPdukhHVKexw60jGXp6en54Hq3GPeeGz2zdsKzgJnCqKWVbpm+zhYGQfn2wE3+XtKmMdOk3xSMd5M3baiOGXa9hb0ZO+W0+afbIv9Jxwi3Sl4++Nki21bp6k4xiTbTzQ0jGsf62e+vzw8HE/Hcfzqb//2uP/JT473P/3pK1vY7M7B/izGtGIMMSb6WCqe0KLd2fbNX3qK5f39/YuB6pdPn46H3/zmuL+7O27fv3/xZN+rOk+YOfGj0ek2x1YbpqX+vvc866W4yfNbHGq4SHsmZju/2UrDTOYuG62mJcmctrXZYMoDXb9NIJLXK32ZRl93RffGsK2u+zQuMzfzDgMO4K3z48jP2Uh6YNspDpBW53bH8XoVlnwRzzbd8Ld5MQ9TJ/lLKgmvzYP7N//WKW3QOkk4TzrsF6Yvxc82sGQdrp46V3BubP743/ZCm/ROlyb7qxj4poEqHSJ1ZEYn+aExeQaLyvMssoPyJGtJuAl8GiCmAUYDNCfOdsQ088G6zRAosxSAbKSUPwMLE7qU3LnYoG2UBgHrZkvADBLUpZMKrq5Q3tvAOSWAlI/rk3bTmfo7sx06YKIxBRTrxNexL8+UEdhJZ3p1Attp8mqJSjveZvXsP77OQXjkOu9ipj74Cg7ylfRkXKH+pqRBhmfWfZ70JNumLBx40u+ETSzN1x3AXN9Bv8lq6GSdpLM5Pu3RJ3mdadp803wmHkyzfbG1nRKQ8Q0/Mdl+3Hwuzfa6H9PS/Dxhttsh3t3e3h5fPn8+/uO//bfHP/mzPzv++F//69qGk4BJ3meHkm2ulRS7UxJGO+e5pmPbP+tRDhyMDj7PPVezijoPSJrf9/f3x9/9h/9w/P1f//Xx4e7uOH73dMstdqay+R19xytRjuuDWcPPHE9x1HJisW0muhuPidfGt/k1T8atdJ3Pmc8k10RTa590pZJyr9QuX2W0tXNmN8azzb5azEj0JbtIg8KzwhyHvsRcje/OJI0tt2XbKV44R088ptiXcH/K4GDKnZueU66Z2k7HUpuW6/CXJm6mDQ+6TQcnvua8scUTDI3GTc4pL2o5B9+JOlt80/hk6jcfTvmV+eN4wXlDks9ZuTxQZfA7S1TT7AiDvEfrQ/gInMynkfoI3YlOmxFshjbtniVU/G6/rwJtc9wz4CDdNKoUUEmHf8+17QlpG2BZZ6TtOPb7wFiPM9Kjz2S4G1ixOEGfPm1LbNMDYsvfzpgCyMieumhy46ww6ScoOhn2De58oEeaOTO4GChYUnLNYwQaPyGTNCY7pR54nDhg2XjCxDphPd7Y7yd5Nx6TjyRfSbq2T1LXvC7J4Wry6P6TznzrA22gDfhIc0vELBdOMCaZUL8NOyy/FFibz9HW0v2b5Guu4+RRW1FpfbUEqSWfSY7Jb1KAbuXXf/d3x8OnT8cf/vmfH+/wRNsZtNFGZwv92OHYwvTBOOjkwHRYjz6WbDjZekq+5jdXP/nU3Umwh8f5nmP/9T/8h+NXv/3tcffu3fHl06fjw4cPL2jftsKf8Za2slNvTPI5SWXMpf/xWPLhFN+aTU1h3+7HbZ7Z+9hAwwHHJes+5SotvzrDvVTfcZKFdmb7THJJciWPzRcb3Y5pLI1m95vodvwnDS22jk3ah8bfOFD1tfNtu3U8b/yk1U7yuJWznIu8Oj61flyPNtTieSpXcSPlJ2ki3G2n35PjOf64nylpUOvxwLSZcifnvs7jHBsb3Uk/W+5CXjzuOrOZKZcHql7FOUvMmMTbCCwsHp/6nLmxgpioUdgUSkqgEqASJFswSDzzWAKCLbHzt5O25Ch2Ig72eJ4GkAzJcp62zgA8JTepUOeWieU2dHCVmHySxwY2Saf8doBJOm4g5GDSnDzRaXm7JOd2UpQSv42HtyQHjRYn3EzamIRbHvbzLdgkOlPQsi+MnX7+/Pl5FXZmBdPTMMkTZWjZk54NZM+CeJNtkrX725Iz/jcGGzdasKN/0b4SbfZh0kI7bxiW+k71rG/qKtma2yXNPO84McUTpGPn83vjYdMJ7SqtYLgknr9+/nz85tOn45/82Z+9GqhPwsnVbuqOD/XaPs3vtnIW5+c/6TV28OEffEovt/tyoHo8PR3H4+Px5Te/OT796lfHFwwqPSDnIMH+nGTAgYF15cG0Jx08QXUc3+Iwk8Sm82S7Z7jdZG47v9qnYxV9nfhAmbi9tJuj8ZVoe0v9hLkp70mxY7P379WF48uZ/7jPhlPTHnXCfmkHxgbixdiudZd4STG65SuJ/nT+Cu7ZJz2AdZy2DFq/5sv8Wr+Wu49v9Ldyhd7W1iZ7tpliWor99NWtXuMhTZ7M8cbrlRhz5mepXB6o/uY3v3nhHAnQxonI0IC3AY5E+x1Tcx1nO50MkAZezzafnp7ijcOkg4PdbUWRvxtIt+RuZJEcohmOjcznElhOIHZizg/5Np0t8DUHImgSGJNRp4B3f3//PMgYPXE7QrsnLxl5An3rxnz7XDvuSYE5x6Tx8fExPryAKz18aisTBQaY+c8+Hh8fn9+vOHrlexVpwzxmvVg+acWUsrT9tCBgu7QPpP5drgD7nB+7mYGqH6gzsmmrPO7PyQN9LmFPCvLJf8/4Y0Cg/Jq/cXsreR3b2vyUxVjkPpMeaGNcxfOH97omeiwfx442QE20+5NWaZNcrdsptv/WnvGNiSJ9ZfTqB+XM8TtvYT2O4/3v7s388uXLcX9//0zvxLmpyz5mou/Dhw8v9OVkJe2eaYPzlHiMvBKvsxLqAejcazqrwh7ITnu85lf/6T8df/1//V/H199t4/RqJfXqHGTzJdZL2yOtS7Y9g+SR43xm0uzdu3fPWMQY1uRMemiHxhnXS7xZDi0/cTsph3P/SZ6jB+IP+zHGpniR6LLdpd9sIxXaB+lIMkt279Xws5h0Bd/St23NPtHsgv43kz7Mh2k3jdb53d6JnWRj3Ei6OZPZhqfuz6uizqvYpmMFJ/S23VakffIDYzX9ySXFc9PM6z3Bk3ZjpHbOVlKTHVIn7Mfvrp9CP0822HSbcqApWz7RcpVWLg9UZ+8/A2UCVT7ufQjxTOgYegqSI1jPTFJQnAWcc6NQC4JJ7Pz23uypP+1PaY7SjIPtbAGf7Z/VH5mQpwbydogt+DUw2tp10CfPdiTaQHJ2OyLpbY/C9vXbbwe6DXisA38nmcx5J05pEMC6pGMGkwwCV+zPQS7xw2Ob7DmI9Gy7+U2TLaTfiRP79/+hgzSZB9PMPo/jW6LPBw3NhMFc44Gq+0y6Jg5RXmmw7uuSPyebZJ30xE/20xKGNEC0zNj3NqE0Je2usA/PdU4GzpID852Oj8zThELjxXbsfkyft1BTXvw27roe46AnBi3nhq+MZ09PT8dv/ut/PR4+fTre//znL/qa+Mv3rpI/Fic0HFTQXtqTpEmf4+74mwedaSB6f3//TC/f+2ccubm5OX77939/PHz8eLx79+74+N/+2/EYJp+tV9PcbI79Tf9Dj1/14I9lYVkNBtlv5liyHx8j3hKDPcG3Yc20Yd9O8Y5tmEf69lybBttn/t3yni1nYuxhabE82QRllvzv6kT1lnNs/G05j/lhe94pwNyIPsfJlTTpkzA95XrH8XISnbq+ubl5EU/boMi2M7SzPdrK2cMAmx5Mm/Xh+mlBKtW1DpPtNTxxO80e3I5laBpt57Yjt5/yZOcYjtFnt0x4Utp1Go+NXx9L9c7K5YHqvP5hDG4cZhyJRmTmfB/iJOgcOJpwJ28jWIPP/J6gkwTJ+zG/fPnyvDrlAVFKiFrw2gTsFVC2yeS3GbzlSCDgAN4GObwSFNyu+/RqNAGS9Dv5bIZN2tkO7YPfMyAYOzJvdsImq+Z0Pt+A0oGsBSr3ydcdXJnNtHzaDGUDBCbGrY/R1UZ/SqiHH9djImUd+VrKME2Q/GMUJ55jPymYtuS4AanlaF5t97xujrHNNEvOa1x/+uGtD+zLAy4OPhLeWN+bLpKP+Nsz2A6CTmy2Yl2czSz7nFcibG+kj3g/fuf+KBvbdqPZvsQJkanL1bgNk5+eno5f/c3fHPc//HD82S9/+SIZ/fr163F3d/e8i+D9+/ervU/b1Am3zM993g8PD6905Qkx2w9XTidpnoGfE2rWe+b5RwG8oP1Xf/u3x6/+9m9fyNg47knBLQlKWMcBtu+JbbhtekY+rJNwfPIN0p1iDP3L9n7Gbxt0JdvdfDHFHvp1wqmUMyXbZvsp8U60k670Yf8p4ea1jVfSnPySfZg/Xn+GEbYh80abMIbY58aP0v3T5okytbzoF7zWOvdg1fZoXpgrpPauxoXUR5Nh4tETzLZDXuM2khwTDmx2lvRvWSR5UOfEleN4/RYK6pO6SX5yHC9f5+fbpJL/0z5bDjMl2UXyzytY1MrlgeowQoIMljRWJ9MU+ghtjlNw6Z1LfjgDZ2tnxnauSUkeB0tfvnw5bm9vn4N2A+KhzUBMo+JgzudTm1NnA2sOepKDeMbQ/VI30x7b8axUAti5judTYKShM9gbgFMwcP92upS0NtB3ve89T92kIMjf3q5O4Hf75jEFJPJvoDiOb0/co17PAGLjn/R64De/udIwgavpzvJpQL7p5h+rmMc2QEsyovzsg8Q0BgIGdPt2A/ekI+rD+DGY6UFXk7lpdAD3d6J54+dM5km+5nmbpOGAL612zfWW38YX+/CEHa8zzb7OeGxfdj3jScL1qXdzc3PcPD0d//nf/bvj8enpeHp8PL4+Ph4ffvrT40//5b98YQMpETBvxNNPnz4dj4+P8d5uy3H4bVtj2Y/jpAe0gyOff/Ob4//3b//tt0R4YsPj4/HxN795hS/J1lISZl3x//Q1PuXt1rzOGGqbYHyy7B2zSa+PJ/9gbsRr2bfpYq41dT352PhJcY3+mPhouJZ0NMUTqu4zXXNmA6SH3+SV2HgWn8wz23NpMb7x1QrjxRQ+wdsY0iYBm16NNy0Psz9xUWfebZ4mQ5stpMGv44+v2+SXaDXetDYanicZbdjPttJEpG3P19O3U35m30100DZoC2fvVvfDJmnrSZfscxYBfE2KnVf9bkqaZNvK5YGqjW2YmELwtQLn/CQ/U49AayU6SaMjOJGjMzuAkjYb1PR7BQAIZA1UeR37aeDP9rbrLNetbP24Hn+3oJOuv0KHg58Hvi1gGlQTDU2eidargeNKXetkaGiJua9zGymYOGAme0zJiPuy/KY4qBzH6xVKHjuO4xXImbbU97TXBkeJ7nR+Czrm5y3JVJPPldISKSaPLcCSJ//2MdtGCjqJJg8gtgBPjHS/nNk1P6Q1+WLSB9ue37aPtqqZ+GAcGFvzoMBxa8OORGfDfPuhJ0SSnBIdqe3jOI4vHz9+o/Hp6Ti+fDnePT0dN8dxPN3cHD/87Gcx4bAvML59+PDh1USHcZk6uLl5PVAl35bj14eH4/PHj8fN09NxPD7+SPfTjwPRx5ub4+vnz8fDx4/Ho544//j4eDw9Pr6S2RZneazFWMcT2ognRNl+kgnbca7SYpbthf/pX8ZV9pm+U9v26yar9j/lHO7D8abhq7Eo8f69xVh0JRdIWJniuP3VvJxheWvLvrKtTk2bbJ+22lbPiJMpfqSPaXt6enoxgeX3bSa/2GTTdMA+PaHS2ndfbIfHtkIMME2b/ST+zvTntjdsSH0kmqYN387oOMpPyxem7lVfdJzd8OMMt0jv1fLme1QZsPwYbM+CszDwGahn1s3L4sNMepLe58+fn7fu8MET86CV9IAYbkua+nyID2eTRqCpJIOiglog47XeJtG2ciYlTzt+h16SYTPQ+XZylfqa315hanLgtc+z59pmTTpcNr79u/VvXls/bi/RkOhND/pKW8jcdlqFGPlM4cRMsiUni0kGbfYzBUley+Njs9yab/lsPjJyop3NxzJI17Z258N7bBx8bKek25NT5qn1SfmfgbyTiLPgM7+t9+TPXgmzHbQVcgd4DzjYticKk34YsKZuWlVigOV/Yvy0y8lGJ/KOLdMPt32ngWra7pSKEzHKl1htex5b5Hcrxn3asWVmef/dv//3P/J4d3f8j//r/3rcvX//KjFlfcq42RL78PVnyZnj29//zd8cf/f//D/T4PGO9nUcx9Pj4/GTH3549ayI7d61LRbQNpLe2kDUds1bmKYwF2Cybiy2DChvxwvnAebhCq8svsb+w+stA7c/PE+99PEk0hm+uN+GgebTdVr94bfla540TGU7R/qT3W88Mv/1tXPeMk00jb3M6ubY4uTd3M6e+jF906bj3/znKmrK2b5XhpaRbektbSX8vVroa/OfNtT6o5yazhIeJLtuOOvfbHv6no9XuZOf39y8vNd424XFvhMNzEmbfx/HN5/zokvCzreUywPVNJhJCccIhyUlGn6ADs9zZrwBNZOlSaSn7y9fvrx4d5uTCfZ7d3f3nOD4nlkGFgo4gZYVkYBgaEzJiuXqgQvPkX/LeZNVCz6pHRtYK80u+M3C9raARiN3McA1oNvOm0fXS+2xXU/WTOCwXTiIclZqPvPfLytPSSjlsw1WvULWZGIfM60JgHldAx3bWNsymOSeeDrDjrTVrfGafHaKB07sOyUovj7pySXJcP6bZ+oxrSCmQWT6pEKZmrfNfqbOBMFtO5yxcOhNuGI5Wj4JcxkHJm60LeopKG80kCfbsOW4lWRrps/++6oPtvf4ePyXv/qr4/bdu+O4uTmO0ZPqHcdxPD49/Xj+5ub4wz/7s+Md7m3dym//4R+OX//d3x3Hzc1zm880gc7j6emYlj79+tfPt+Ecx8tJucfHx+NJE8fkO+mhxdaEVw2LjEOU8eQK83/O02bPJlftM8Qi+qZ58HHyQ/m064lHiV/+93G3fVVm9nPbrItpTHUbNid7sM9QR1ue4smrhItbzmJeSffV2JV4YH3a3pY3Ged4v3jrl31Z75YhJ4/OFjpS2XDF/DuHSTqg7Wz5jvuxzSU7SxN4qRCrGHeajs/klI6nfMwyo558XdItefNurHT9cfQnNxt7fF3zpSv4faVcHqim5IeETNKSnHmCwAhi/t/d3b2aQWcClsDLCdUoYZie4JNWctKTB0nPbAkib21pPSlwozldn+TlhC4Z32bo2/GkQ+vJPDUHTm2dBUAbqJOVRG9r62rQaO20magNeFxvEtf5ZhLLIJDkOmXsjcm1Z2P9m/Y77XmG8ixgpG8fcxKQVqWSnZJW+mB6rdUmWwYmyjbNaDa7SbKwbhpwMjjRvlPC1PodTGF945fl31YpiCWDFekew1YcvPl7+np8/PZgKstk9DKF2Nn0OXZDeSa+03XG+2Sn9C9i+uZDSY/m1fU9CGl4m/gwppsu62Vr++bm5nh6fDz+7j/+x0v9P/Nwe3v84Z/8yfEuTEym8t8+fjz+4a//OtJLmn2eA9VXdEvn22oI5XYcR/TXRofpTXjC+J5oSAPLs7ibfDXFG2MmbXzzI2Lw+Oq07dixxf0mO/JJu09tJN9JPuWHNbpfrvw6h3JJuDsf7zBpk6G2CbdpnbT+t3xl2zGU2uTOP9dp8Xhi4t3d3QuboK1f8S8OTse+0oDIPDe5nfHK38nOUr7r+meLIykmMIbw03Al8TE+l/KQFK/Nc/qfeE24cByvV8KJZaxvzKF/8FrS7d+NNvO28ZvoupqruFweqKZZBDvHOM98Pnz48Mpp0+omDebz58+vZnm2rUGkhdt4WZgo+5He83j6cfqnp6fnpzTOzFUyEPLvmWMaM+U3tPC3g1caqFLhm4Elw5nrfH0qCag356VNpPcfji6SoW9BMNHiaw1YGzCk1baUOGwg4uLVetNum2kDoy3gTT9Our2aO/bKupttWAZt24vrpVWGbSabeppA7BXRZKfkIck5Jasp0Uu7BUxfotf00Bfch69L51NJCRx55rYultHXfNIMuGdcW4LAd++x/VTfuH0cL7f139/fx90DgwFOGCxXXkdaaGdtJ8ocM2ZuuOBCHo/jm50mrLKsLKNU7Ptb3SuFyZOPkafnc4+Px1/9H//Hmjjx+q9hu//vUxjLz5LDlkyaRtJPXEh68YfnaafT1tSZNwm472SrifY5Rn7Tlue5fco8zbcx1wPplBds7ZneVFyH8km6Sn3aTvnfPrPRlPx4iz3HkV9L5Ne5JJ4t47N+SGPDixZrGMPJF2mxLfFp0vN7MJb8eeJ8rvX7fpM/Dm2J9rcc22SV/HHKpv+UyyRZ0c7PaNt8O9n7/E74b/2n+NZsPeWnvjb5OOM+7be9ZojY5xwg0Zf83PI9i7esw2uvlDc9TCkRkMBy/qeZnaTMucYrBQwgTsCS4OjELJPkzG/TlvhyGXpTIkd6yAODIAelNEQbSJs1bkq1cVC2NvJk7AlAzeOVflnYt5+MnIzbv+e/JwbmeEs4Eo1DD8u0mYK8S5Jdopf2mRKJFLAbMLckaK4n/dazwZO0Np0aNJK92W7PgjjpTInWVfuivs+CFGm1fltCNX2l/wlM22z5FaBOSYd9ogXvK/7f6qXAfRwv35W4tZ2whPxQNs1fWpuWR8KG7ylnGJZ07mTDT3hMuth8q/FHeyQtbwncZyXF6YePH2vdt/a9Ycn0x29PPm++O/VbcuS69teRsVfYPenldlLSZZ9uOjMub/zM/znfYhCPpYlsymfDnc02SaNlYTu9Up9tWzbJbxp9vM50p9/EnhT3HEvaIGzonAWFJGv3nehO/bPYNpsPNj8hDWnxwzF2eOADkphXJx8grY1HH7uaSyXdnOH1GcbaH2xvzXa2Y1v/KRdoeYBp+h7MNT3TLj9e4Es2fLUkuXoSfKON/y0fxv8r5U2vp0kEOQjTyXnT9+Pjt3dlesWAy/7zMCSvGjw9vdx6mB58lJyM/x8eHp4FxH59z5uVTkBIhmhA4IzVvArgOI5XNE+bbTaj/WdQ5DEnV24jBbXmSENbK5sz0hhnlfrK6vjGM/udQJMeFd4SmySroYtBrtHRgLwFspRIJJ34v/vxamcKvFxR9XslCQhOuPzt5KkllwbBpKPmT5Rf+zCZSO/JnOJVFmMAV/ypqyug3YKz9Wifa+BtGtMDqpJcEhZ5Io/Bo7U3v3m8DVQpQ8ueCZADGHkkjZy5Z7tOHJLv0iZ4bcPglihdSYLMq3eJmFb705w7S0Lo2ynB2Wjd+Lly3X/vYuy/MmC1TRkzXHiMsToNTL2Ct+HXllM4aeO1afeHH/g1+ZB5S7iTcixj9ZWSEs/kd2fHE8/euupFBX7P75FDsn0vYiQ5zO9kFymepJU71nWxfRpvmw2wzbYgkiZLnD+0yRr2kcrUnRhjLG73K27yS1ibaDnbKUKZXW0znbONmhfjMGNd4vtMDpv9TL2zOq00/Er5YKLz6enbLiuPnYwXia+3yDnJONmKB/H27f9XB6pWgJNXCpmB/suXL88POBqAvr+/f7HtdgPqEQpnuZLiJvA7IfMxXkvlTp0EslQCtzH62M3NzYstyPNy9dvbH29+//Tp03OfNzff3nNkOU/7/J904MSuBVa3na53+82A20pmk7tpTAlKSvoYyNm3ExD3lXjiNx2Xq+Smc+omsEi235w5ydClBWFfy3P0h+Hl8fHxxTayLblpD0xIMm9Ak2bYzhIB6pu69P2+2yrIXEvdnemdtJAm2x/p2WzcfWw6Hhq3oJBopn1N4PGT/Mi7/TclSc2Ok/xmstEyo8yT7Xtml4neFqAsTycALi3hYDK0xZU57yfvcvKUdKWSfJf/E7+0W05GJVzl8UTLZp+mj3VsDy5nsWLrM9HuVa/hv61Ysc5ZTHTZBiXmxVhkbGD/xlP7nv2t2adtknaY4s3QwIEd6Wgx235KLHFJdky9WXZJbnM+xcQtrlEGyc7dBmXBa63XZGfGlLMBbJIF2zJfPmf/H1xN19LuTYt5ol8lm+XHr5hpuwpYWp7VSoun7mObjEnF9mI7TbFnK96d0Pom39sg1PF0s9s5tsV/2xzbcZu8jYBjGU9E0K44Zkk+Rx44oDTdlg/bPLMZ+saV8l0rqnawcQQyM0kzk+mpw4eq0HjTKJwJwwz2ZrA7x6d4BWXa3YL32c3+FjZBmzT64U1DL/mcAfvZSlADa543Ly0RMj9JBmzb34kOG6N5MZDO9ZxBTXJ2P6lemh2lnThYue0Geq2QHgJb2lZhvZ7x4joOWmeF/mb/G17pPw6caZDT+G9BP/nKGQ/WNQenc6/41dlJ0tQSIevBvCS7p521QU6iZdOvcelMzy04tQCd+PMgbwIRr90CtgOX9ZHoSO1us/dbSVjSkrt2/XH0B5Sl1dkrATTpmhhwhb453iYq5zd5OPOFhvvEhk1e/9jFduMJgGQzrE8MSxOTqb9kL1t8JG3Jvn2dMX/DT8thi/NnWJf0Rn2mtmjPTNC3uHMWl90/9Xompw1n2J75SJiX/ORKfD2Ob3kfE3FPghgTHDM84HEfc67JlHKyXUxMbHZq+SRbb/i7yZe0up8rcXDTLWWZ5NCu2fpp9tTw5Yqt87dj6Jl/Xulz2m34Rfmk38fx+p7/tvM0yTXxlHS04etx5IkMLzBsePqWnOBNA9Uk6Bk8WpApUbm5uXl+5+nXr1+P9+/fP6+ucmX16enpxZPIbDTT92wrJdA0wOAxb9+YkhwxBUmv/PAdesdxvFhxvbu7Oz58+HDc398fDw8Px83NzfH58+dXT1rjqgMHu1Z0eudeS2AIpMOrdbiBsw2N8kmzMnMddc7V5RRs3FdK4BuI2YnJTwMgt0vHTn2M/GiTadaqARJL2yq2JUqzRX5rb3jgxJDfe5xWIlpQSUlUkh3POVFI2/tIbwq+wysnsq6WVD8lM/aBFui285s9/WMW2jMf9satPcfxEs98fQu+G+0pOLaAx7rGISdy9pu0IpzoIi7SvvidaDffxnL+Nx98kFUKuKbPyWGixXib7HB4Tat1ptm0XbntY+Lkf68ytIw8zWfChi0+XHlPLeNIS9ySnTT6p453jzDmk4+Hh4d4Pfudc4NRnDBvCa+Pbfx727rj1hzb8NBxqfGTYi1trNk0f3ticHhI7wfdcruWoCf8ajYwOkltJj9vSb7tJtFNmQyvfMgd7Zlx3P5j+6FPUXe0C+Ng081ZXLuS1yU83orxrvXniXif9w6CZq+t7zN79zHbh/tK+TXpSDjlNn1b5PaAOtI+9uPbqabeXOv8es6niYuxqWQjtrMpjPtXy5tXVDcASEow00xYOHjx/ao0rASUbDclB3aWOdYMrzkoQYvAw5XiGYTTeRjIuMJ6HD8OPmZbMAf5W1I/H8+Gso4BdkpLTAwEG5icgfkGEtSDHW+zmdSnC0HI/WyJJXWXJkS269KDCJrTpSSA9uVVdyZjDtxuZ2SYEih+bI9N1qbH1xvULC8HSQ9Wkz2Yv9FnWulqpekrBQHbfArGzdbP6EjFdnF2vfWcsKsFavdHbOLEl+3Q/RojN1qn3qYv9seJKz690vbB9pO9uq75oTwoNx6jD01/s1vHuNZsIuHalQBsjDfdqT5ptR9RD7Yb0mY5TEm+ciaDM5rdNvsf202YaLrJ35WBKuXg3S7T9hbrGh3Jb8zn+MGWf5zFBB73sbPiZJR2wcHM4IInWilz038WHykHxwTirvlPsc4J9RaT2R5jjmlr+UNra7t+w/WGgY2GRot3nxkzWv6R+kgxO+UeloXt8Go8voJpifcki61uyvUS3puPt2CufeKM1s020nWOyY3OxLvzmVYn5VvNrxrtKR/kmI3123nb0BXbOI43PvW3gew4VGLKyp36M/NI8JxVFV9v0LSzTHuz4mAanAina73HOwGX+bu9/fZu1qenp+dVD25d5IrI4+Pj8eHDh+cHLP32t789Hh4ejk+fPh1PT69nfplAeYafdHg2rQWZ9HCQpB/qNtkA9Wh6rOMpaau2/9PpkiNZNvO7PdjnDCASLUnGU4YnbuFuybXbdTBNvtOCtZMzr0hxdb4V2qvt9MxemPz4lSkJbOhD6X6JJFsmTTNQvQqqW7s8fxyvX32TglkC/4Rl/p1oMG1nwNzOs10m+J5hZzvs2xidZEI+Gx+NtjbBYewdzJ/v8SVO/rBNT9pMW76/OiUf1Ofg71w77XGScfrlzh7bQooJtCP76hz3xFhaTbYvJnwydlHeM4F6JQFx299zzVbPbaXc4KykVeUzOpPsrYNEX+NjdJbu6bS9J9xobTKGmd408Z76Jb9zbPDZ2G4smH68IJDiPvs1L62k/M308hh3p01Jq6zGO+cZfKqtaWxY4YmyLfdL+Yh5buVMp3PcD9vc4o5zibHtlH8ne22ySRPMLSc3/84T2T+PJV+d416QuYo9bpcTd15Q2nIm4sSVGN7a2fLJOUb7PfP9uc7+3lbtnVeaHtpwy+dbTpi2+ZIHY+Lkds0Gt/Km96gyMaJQEhClwsT169evr7bQ2sh5nY/bUVpi2ZxqhEuw42x/WkpnQjAyme28MxM/W5nJF5MXbu/gyuqnT5+ev7mkb4caup3AORH1A6qcTLZix9wAYmijTKivs0Dmb9Pl2cOxHx7zb9NHHlp9A/r0zd8Oigb2lvykgEigTDqhfY0t0r7T5IrpSD4019DebR/zwDMCTLonOfGXgpx9Z367+HwKtKlcBTqWNLNP+ltyxeIEwe1tYJyC9hWemMikybUWrIbnpjvS6cFS4ovXW14b34NblAEDLnGy2QoHmxzsJRkynjTfHFv3a814G8dgOdtt8mml2T9pcEmr5U0Xx/Ey4U6Y3+TwVh9Kcb/VSXTPtWc+1mxo2nwL3c32W6wyTif6j+OodnEFB73acBzfdmuZLid9bsf+66fwJmxiW46n27djxhxLk0ptYpztURbJT5rf0LeTvFOO4PPHcbzKsyz30cfkWUlW/u3iHKnVoUyv5FEsll9b6Zq2mTM2LGt2QV148MOcK+VfPJ50m3KipPvmk0knCbM4wZhW4Nnulqcl/hJdST6+5myhZGKVV8Pb7WEtDqT8lQPelBPMb97qmHycfjJ0O2e9+vaPKW++R3VLCub31XZGKDQYtndlFWUEfLUk4TupoVF7FjYZ6xgP5eN92zQYDwxm9nNWk+flzQ8PDxF4ExBxsJpWJd+ajFAOLJbRHHOd7T9lvdlNSha2ve0G0Namfxs0DYSetW2FDp/43oJlq5fA1wNn+lJK4HiMbdJeOPM45+yTllmiuX3cTpOf/dD6atc3e91KS4IbnW/Rp8Gd9d2G+23JHPtLT/hLA1XLtMlgG9AkzLmSrDW9pwSdwdaJk+NFs63UF/9vuMXVpak3PkG6tkQitUsamhybvu1zzccpB15DvtMEhPs5O3ZWkg9ewYCURLtek5FL8pexnbQC54FHo/uKThNvtl3qIq1uEPdIZxr42V9TnDcftu1p03wm3jmwSU9ld+KaVnASbeTvav7oklYWvTqVBrLH8XKgSrqcC7rNJi/TyvxySrKZpr/kV76Gcmxtud/kK+7b9RpfZ7EztZNotC23fGNrs/GxlS1/aP6VeLeO07Upt/E189t8+JzHTjzHfhP+p8l202vc2XY5JBqcs1y9Zc7lu9+jSuIHuDaFpAFfYpoz2HMsgSiF4Af1mE7TyCeLsg63Nc5Ak6tbpH+OTbHgOYPALZOU0wxM379/f3z48OH4+vXr8dOf/vT48uXL8fnz5+eHLv32t799sUXOcmSA4MoEeaS8huetbEE66aTZSGub38khTUfalk1nnXa2FaFkI/5Pfac6DsBsk7S2YGr+OFh0ULWdOenyVnFen5Kg43j5tEPuKuBgdXYH0E89+0q/NY+kzQP8xGuyJQMlBwusw7oNNP+xS7N58tsebpECA3GJekhJF+0r2YDpYz/8Po68tc51iGfznWiaemlVJT3kh7tPjANMUri1va0eb/jRsMrHZpb39vb2eaLw8+fPr7ZSEsu9vXKzDdKT7DThiIM9f6fEPOE09etbUraJ4DMezs5vMSMlfb8vDbTTlBxtE3tbPGHbiYYrsvB3w076PvslDvrWqMZLWs2d4i225pttmT7WbYn4W8vmM9YXaaNO51aCNnFnX3FbWzzymyHMpwfEiYe5bpMTdZpim2Oi2/J/09Ryn4YltCHT2eKsc38fm9/pNrRm91NSn8nvE88tliZ9JXotM/ZhudhHkq+01fuEF6OHlvsM/5uNJHsxDdNPsi9PvCcbti54+xcf/sT+r5Y33aM6jdNgDLxJICS6GSEZmvPHsW9/SsHdxsP+np6eXhl+CkZeRn9rn1MvzdDRoLwCenv7+h7C2Z4572PlKiv5Gt0MP9wLbsNqv11SwmFZXW1zA/PkoJTbJuNpm9duASHRsAVKt8dB2yRC3s7gAWkLFFuQYRLihNX6T235mPlp/E0Z3hg4aUv0efO3Jc6UB4t1bV2OHyS6j6M/Yc59JBn595k9tLY8yDRv0zZ/s61JsignBtf0m5Mim1ybT3pm1Dju/pKOz+zY/kOZuQ7PTfspBjhpoWxdl235GsuK8p8J0Ensff3IwBjcihOIJIdGv+tSD9trpqYOY8wMuIe3Jgv3u8WKjefUTtO15bC16cSItkps5msb0kCV7RrvEuYcx2u8STGWtzN5UvwMo1oe4y3q5D/JgjJN/JkXy590pMms9r3x5tKusS7t39Tl2VP4m39MHL9Cq7Gu6ch80ffegoHJvozPZ3QnGaQ6CSdT3DBd/iT+bYNJFhsdU5g7J/qT3bfBacKaxIfxieesR+vO+k/HLB/3y//0W8vJvploMW9tbJXoTfxZ/vyd5D598vfV8qZ7VCksEu9Z2kTAAEICABqgH1rA/lry0ZywOSSNuCVW26B7rk3AaCDloGb4m7bnN2eX7u/vn6+fgerM7n/+/Pm4vb199eAR0zVBeeiex50Pf9ZdCyBnx9lmAt+mq7bK1oKdk4mWzFHOKXloNLHt9tuANQ/umpXuGUilgErdpPYti83e0yDVwGJQTTJLAEZ58V5gT3qkINXku8nV16QkkrJooHkcr+/JZv9JxiM38sRzZ9c6gWuJzXHkSRraCWf/XZyM+Zp2He1g+jUNx3G82EVyc/P6lRDu25Mxth3P/HJipwXyZEu0HeuTAy+2sc2YN7tjsb4oJ8408xhl22Q8chj50uaYfJDOlKglP+MEmesxntLmp1/PkrsMz80XtrL56tDOb/OV2tniOQemnkD0inwbpDbZNKyc2J0wkPJOukyxJ9kPc67kX8ZLJ4pT2oCaPLQVrqHjLT70vedZOEjlqnji1bkY+0s4YPs0llofvsY8JV91HunXGFKmbeDCa9NEIusb+xz3E04dx+sVY/ObvtNDT68WT46SB8uz+YHtlHbgnMv+sNkCddPomG/6jc+R3ibbqzKjHsdfkx9s17vP1nfKJcl/K7atpIuR1ffEkzffo0ri5xjBk2DqjxOdBAITTL58+fJii1US8ny7LScYHLwNbTOwcPCh4aWBjvknWCTgIA1s0/0mXuf4DF4po0kAk9KZoMz/actbkCmzDeAtW8uM9KX25iE9LXFOkwYt+Rpj31YuDWytWA9zLAX5BPyz+s0nmc43bc/tJvCgLNK5RG/yM8vuOPITNNOWU/vrTJRMf06UzMdGSwK9lGykLc1boEmyaaDsQGO/SAl7wpbGd5rtnqDONlISlp4sSrrH7v3kvAb8TQfpN/HQ9m49uA+vypH3ZC/2NetrrrPu6Rd87ZfjwOCj6U50mG5jLz9Mqtogtelw2h3d2daaHGwr9pfUR0ucSO9cO/7dEkU/PdUYMu22gdBZ2Ww3FT9NnDkFBzPtnddpMJPs3jL0uflMvG4PM9li6tgubcHJra+x3Q1tST/kLeVubM+xqeUV/k4+32TQkt7mT44Jtnm3kya0iB+WS8px3GbKD0wnfcv2wsHM2Ep7T6rxzrbQ5NlkMNdTtsSnxMNZPN90/xabSTIdvmmzxrhkKyyzU4R8NXmdxW3rgXk6dWf6TGPrm99bmX5mccQx0X02+aS8yTJoC3TbpCz1z3HOXNd85y3lTQPVphQnA/Np90FwptbgwXaZgDixSdeQrvlOCdemqKH76enp+duBnjQ22ST5mKb5jLE5GDoh8IxvomPr2+1YXqmYLwPOlpikgMk2UhA/a4vnnaiazg3kEy/Nts4GqikZuLn5lpQmwEgAns43vgyupNXXj73QRwm2nlFPfp6+m5zm20G8+YMT8fQUxi04JTs70+n4+Uw0DMakhNP0uh3iho/5k2inzs4CWpJf0olLwq/j2N/LmezdbZJu85F81n1sM7iN19TOFMcWt5GubThgmTOpbzI908P4X4ofzWbbSvGG/cn/2B6PMb4mOfs4z9vXHS+3dq4U6789RIyrqKznukluyQaMoVxRdy6R6jd+k86uDBaT3jccZI5gfaT+N32RnhZr3bd/J9uxXhN/jg2J1obx0/YVe0tyT3EttbXhm+lz7E4D1aEnDcq9KOR+00Sr+9/kkbDQecGZrbS2SKPxn3wSw8m7620+bMxO44202k3eUg7uHTGkJ9FqGs+w1fIjfhN/kgy2PKL1m3Ta4hD7tH2+haf0+6xcHqhyQEKBMejd3Ly+79JG4PcwboDrGQIPfD2wvCLEOZ+2S80nzXgZwNL5KdxKwUCaaJ/ruEo6CfMWmEzTHEvBxPRaf21llqUl3k7mzkBwHM7OZpD2df72sbGpBHxbsGR7LcFK/U0bXo18fPzxQUTbfaumwyDeaDoDkOM4Xq3oGBi4zZwPV3HgaDJyf/N7eGdAYMAYGaQEhB8nkw40lKHbtC+0V0cQi/hgtZn1tlyTjVJefgCcV+OIncln2ZZtgnQMP0y8pz2vfG3FPrtdt/mK8bklN82nGOyNZw0DjuP1vXL2H8qiJXym030cx8t7hrnibPr9IMHW3pShJ/mqJz2SrxizW8yzHqZ+wnIWJs8bH443Kfacla0++eJOKw9KPWD1wL49dI79HMfrW4Ga3TJZ5Su+5jzxZbNj9s2V9t9Xds5NUjlL9H28YSh52FZ5Wt/UkXdOpLYbTeZh/qdYQr/xJEGSQzs211vGST7OkycPcr2UCzW7tRycW6eY7dzaNtD4Zmn+k+qRHuaf3iU5NHliiThoHlL+xML4SH1Zdozd9MEUG1ouue3YmOuNjymHMT+UX7olJ+VCDe+SD6fcbc5zvOWFsZFt4tt0eHzhuHulXB6otq0tx/F6Ftu/UwCwwvg9v+daJ2ZktA1M0r1U8822aWhDd9oG52SeBk46DKxtloPHEugmQ/eKTwL2aYNJ1N3d3auE3ICe+qSumixMi6+ddudpX1vgaOUsAWozdJQxHXIDX/aV5JKCNYMOJ2pmwGodNb43Obu/RLePtUCbwNkBk/20gNcSnQaMntVkHz5GndFH2rVJppwwsh3zOm5vTg8naoDvAf8EVq/ouV/TMPUZWE03Zc8AQXtK1yc9sbSJCdbnuYa3Cf9c132b5zP7cZLlMueJuW0ljPS0xCthpOmaWGNd+dttt2Qr4VMK8inpSQnBnKOOktwSfwnr03ey00R747lh+8T+edo9B6dnPplibxpAbbqn76Y+NsxMGGle07n09oSz9pI820SR22mxzfwex+vVc8vNsj0rDeeSPRD/m724/nzzyeKOGbSDNEBObfK8sd70ttgzbSRbNo22V8qAuUKigTpJGGHdbrpotnxFH02OG+a7JH/3+fTN0gbynhBvPm55+vjm80mWxiT7XsJPxv80QPRk3VxrmSWcn0kEYmfCEH574WvoM08s7Xgrb1pR3UCXHZPYYd6DCQ6WknLn+HF8m22k4Dxo9XUevFHpTF6YmE6bfBBRGpT6dTCkgUBiULHhJTm24v5oDPyQ3ql/f38faW19m2brLM0EJseyzKd4Bik541nZkiufpz6ol9bmWTDcZtp43BM4Uy8N6smH7x1tYJH0b1pS0pJ8kjSzDctnvi3DZjOWCeXLwQxts81Kki/215L7lAhxO7/BnfbaEodpj7PD43ecnGJ94x3lQxxL+ED9TZucwNuCs22euuB588t6yc/cj+ud0WIdmffUH9s4wwj7yvTFAf2GPWf+3+onbE08p2/WHxrd17Rv2+b5ZPe0Q/bl38YLxwxjhdtJsjGvSWYs5GcGpnPPP19Dl4pzFNrXYI0HJ6YrxTC2nzCV/ZH+tpqY5MKYnvA+9ZF8I9GY+ibfyZ6SPZPO5OtJN2c00Ec2m0qTM832TGPS0+gnxdDGS8Jnt9nk2Phjrry12ehivKH9sB9elxY10oMIz/CvyTbV2+zZdc/yjo22LZZtfSfdNVweGaZ79/nNaxPN1Id1m+LGceRXJrbneSTbTjJImM+8lbkO40myc8aupHfL8IpNTLk8UOWNvIlZM27ns8BSwGM7bWaxAQ6vmVkBC5n15zUvfP+WDfbp6ds9iGMUw9c8eYurKKRrClddmtxoKF65nmsnwX7//v0rh3Sy7c/23r/jeLn9Zv6bBtLYAvn8p1OQf8vXjmSZpNcE+TrLLwVTO1MCFTtzSkS2Nl2sAycjCUinzdHT6N0Pvhp6KYfkR1uAJP8GuON4uS2xXZcSAE8qnYGcZ7sZCPyx3Of79vb21dOWG+20/7MJkxYYp8/Ry6zI8l5XbglsD4VrAdjymP8jS+4Sse5pW5R5ai8F9hTkW0lYc0WevHb4om7oz+zfu2P4mzR4YO/APW2lFRTLewr1mSbshvcru34smzSATPbn96D62mavpKv5iD9Nzm8t05fvP3ffSWf2f8eoFMvczvQx+iZ/nrBoO5OsS9K8TfpOv6mvlqydrUa2GJT01653sZ+m3xs2GW8oJ27dTHGS7afFENNi3hOGzoe4mx6W523k3lpP2t4SVy07H9twMcnlOF6u3HoVzbtXmoxMe7PpjQ+uPDab22IwfY/f5tWx7Onp5c6j1A8H2abHeXLjizmMZUYaN4y0j2wPh2y5m9the77eMkn5XJr4tOyZq9tv0m1iqc30tPU2GXSGVSxveo9qSkKuBrNkXDbMZPRWnFc+XG8EPkkkB6w0nOP4dg8S207GYbo5C9YGdcexb5duyQITqeYMCUwoG8vD99ClgEogsJ6pJ7ftc2cATcfZVhbd99ZuSsCGn+T4lHMLzK6/1TEwJN7OkkHL8soKBvXVkha3bZoNguRx000qLXCndjaAP0sEkj3R/pLe2G5qJ/Gf6Cet9DcH1JQwtfvQko3//2l7t+W4lWTLFpRISqtr90P//xf2a1tVrSVSYp6HMk8NDs7pANfeJ8zSEgkgIvw63eOSwGb7SbdpMNR43HhtxTJtyZn7azHBeqDtc0DK+xLWpjZaX44RLbHYVsKan7Atn99Wydr5xMPQbXw4qzs2mXhJGHFVZ+Q34SjPpyRx82/iabPZhH3mK91PjPYElzGIcZFtn8Xc+d7864rMTX/TV8LMKzhmuVkGrX7SS1qNS7aQCuXdsMW88hptgbhLn/EDc5I9eXcOsSLlqRut9omEj1te7N++hzyn3CbJN8mDE+HNF89o3GzN/TNeJV4Z0zcek021+ModFdNnm6h03eYPvi/VmTaNO85TjF0pniQMbXHdfbCwHZ/3BChjR4ubPObD7jhQtZ3bz87K5YGqH43PkmaZh7EhKg0CXX+cZ/rjwwiSMuh07JP/x/SK1O12u7fNh2XQGeb/lCwpQM2Al8vlfg+hE4QGjjSeNICzfDyzPnK2ERGI2sC5zaIlmadCPbQk5Nu3b/eZlpeXl3eTBVyFIw2Ur9ukA5GOdOx7Ei8Odmm2O8khAZAnMDzoTKtFppt+NrbF4GJ5uI2UxCSabc8p4DlAtf6SzVtWrR0mKGNH/L8ndyQMvbOS+fb29u7hY+wr0ZtsOk0sbDzM/ca419fXD7L3TGUaaDgRIl1zLdmtZzhbkkS5pYdWUS6uY5mkINr6uyJTJpYe1J8lB5SdsbzRs828Uy5tlX5KSmrnPPFreLPetxVX83cmC5czn/2fKmnA51XTVEzT/KZ/+Qm/fvhUWvXyMbHZ/3Vl243G43j/7sKHh4d3/2nfPlPXq10b7h9HTwCTTs3z2Ddjhtvn77FNxy36kOWZdNziZHtdU6MlYbV5tkxJV5JPmpznfYOtZ/jkyf4NY3zOPDmBN//UpzFo6E0TKO7H8YYrZfOXsLbwYfkybvAc6U+0cvDTHjI47XnhiLFm+vD9xG3fQzqY0yV9pZzpKnZuOSUxMuFN68+5RhsbJJu7sgjU9MxB/ehqdhS5v0bDYETD2LMxhcunV1RpTAavOUdHTsS0RM6CGOdLT06d+nxYENu3EzjJmv6+f/9+vL29Hd++fXuXALO/4dFASYfzEz+HtunLSrRzzbU009Cchfdb8QawzyYqVxJW0+jvLRkheKWVXNPOTwsA055ptONbt5uMaIc850SffpGcMtl4S06Y5NhHnHwkPt1348l2mGYY2XZLdlL7KZFqtFnv5H+2jHuyyTrY+ErX7B9pINj04+tJB56F9IRaajcliUnf7Je+w2Pz7L5Mewsa9j1PjDVZt/5c7F8pOTEtI5fB2MEE0phkOW2Yvnbdkx/JBxLmJh4dI/0qoyQ790sb4k6hhrVXS4rT6Vx7yq5j84bPLMS0SYTY/gws08w8ZZswlTGxbfGcZGqjN+UoSeZpst56OpOF+7QeUtyZupYD73d7jkPs1/Gz5VHT51kcbbjfYonp8nlP9rhdy2aLP0kuSU+Wl+2FcT/hb6ItDVZYnEuc3T/nSL9t1nmqccnt8nja8muCzialLQOPHdIiBCdanBukmGZdpxjlQZPjVZqsSH54hm3mdXCMg9U2qZJkeZannck73Wc7pezsV9R1aj/ZNf2iYZbbOiufeo+qGSZTNMAEWHMtJV0E98TADBz9B+aUkMyHCQz7531pFYZGTYP2k4Dt9O2clW7+UtJEvpKsGkBvuqKO2r1XkjDKNAWBZPAJhK2LNliyE893oq312xKQxJPpTU7PBMdO2GRL4E19JjtgkpF8ZUsICKwNvDYb3L5TGV25jbP6DsSpT/qR+TIN1AmfNJ305XqWz5kdJP5SQng2QPXvJsOtb2NG64dtJf4aT/ZD1k92RB6a/pNPXaGJKwpDE+81zplXtt98aOhuAT3Rt51nsD+bnEvnSUvDxCSrxusZvck+nXilJ5pvuNyuk37yzn4Yi6/InfJKA1UmsKzb/CX5AG3becDkF+avlZQzOYlPucpxfJzcSXFj2nH8vOL3V4rx3+1dyTnO4pnpSnbT6DFetbiY2rYc3E9LyDffNk0Nnxr+NOyyTZIfLqIkm3L99E2a0kDyrDBGT/Eg0fS5vifFGv2uk16BN2XyszO6z2KKJ2/ThN6Zrbrf+W5/U0j3+lwqycfaYDnxx0/jjxjV/OFKuTxQfXp6uivbAXKSajs7iUizjVsCQ4N6eXm5903mx/FeX1/vK6uPj4/H09PT8fPnz+Px8fH49evXu4fSTGFinAaUNjTS49WtDWTIX3J4zkwleZnGFCS3hGDoTXSxOHlt9yWezvRJnoaP2+327n2jXMW27Gw3pM/A1UoK8FfudbvNMV3OEuMEJom2pNsmbwcugoTbSvXcZgraG73crnnF37egbhr8LmYHYCf+TnD50DSvzmzJhPnegnpLZqe0mUXfdxzvH0I2g9Cxn4QF9Ks0UCMPU4/0pF0ryS5Ykg9s+GI+nUha1q7fbH6jk/JmG+7XWEv6Nszw9aZjJo+e0PS29iY74icf4DX+QN15xbnpkGXbocBB3jyIkDZpv29y4vHr62vkuyVBlmlLmtyPV0/TispGq/VAWdIXubvqOI577sFJpGbz1NfomX3ZFrnl0jKxj1E39OutbLF/+plv+hAnkZjTbLhA/pqtGu9HZqTt4eHhXY7IwdDIJa1+2u4TdrOfZp/tgZzTVlp8MJazTssXSNuZTTJmXhmosl/HgOP4vcskxXLLx8W6ZZ0kc+vwM36Z+p16XOGcc/4/M+3MuibN7jPZFHlof1GyzHjsSfZWr8Uoy/WsNB0xxrX2Xc92k3D+Srk8UKVjefWjHTfA3BJXM8FkKCWWA05JeAxQE9SdqJg28+yZNYJpSuDT1obNeVoQ4bGBx7JtxcZyHP2pgkkubGOrk+SX2prirR3Tj2fK2AdBITlm66vRkRzegcT3M1k4k4nbaAnCpsfEawowlkuy79RXOr8NMEnHFpBYrCPT32bgSKMDEROh5IvT3tjZ6HX+a5EGqubLExDUP2VFupov2MZaUCKfxBknUcObbYp4caYjtkHe2sQLCwcoCWN8viUQW4BN8vQEhc+l/s+CuPHXfW/ya5jV5N5s/wzLE47QRubb2/Isn62flIjYbp2QO2ljnbN+2me770qbadJkW9U4o5d9+PfDw/tdLxwMWddnuwVGhsZi80h9p3ZMH69z1cj0uJ8ptJs0aKCsB29J25XVZPfV8oktLrFv+zx5vWIDyVc2+7R9sW/en/rwoIhtE3/aroXWHmXFASrxwP7OthrtlEPKdRpWzvcWGx3nW0kybjojzdaVn7tjfTiOpmPnHu6v6eqMn3R/WsFuMSfFQ+vK+HAc7//ieFVficbGj+3kLPZN+VsDVZ9PwTYJxceNyC3AzHX2Q4BinS9fvhyvr6/3WWf/r2eKk94EglzVMD+kmSDz9vZ279OyoBF4NdVy9MrtlvRt15uDu7/mDL5v+53qk/40AeCBxRTPXKVk2r+bvM6SIQd40p5AIcnBNkRdJ900P7AuHFiajlLAT0El9Z0CXuo3JSrHcXyok+yJbbRVHNL28PBwn2ziysX8f9U8TzvzupipO/5oXPHHgczybTJOfmy+UiKd/JFy5OpEWpEzrp7hCeniLpGmj0Qr5Z6SrFbs281v55OeA8D/dzKosu80mL7iI7fb7V37qd6cm7jDRDjZMfujHOZcegBX6t+JA23iOI77fzo94ZZWa1yavrcYzT4o9y22T9008E141hKjVNIgJPl6mixyoQ7SwN20eMVu5N4mhsmnbZirVkmWye5Tu3Mvr3MgmXIYx18m7GerW/Q3D75a7EkYahtPeYN9g7iXMMu6Tw+D8kq2eU3xL8URly3vM6ZRT8mOjWlsf9pJq4M+t+mxXbN/NjtKuSDlx768YJHapkwS35s9Jxx4e/vP3xf8XmbGHNpd65ODW+cebpf1qcMNg6akAXPKXSiftEDm2GI6Es0Jc4k9Sfakkb8TPVf4P45PDFT5BE4DfTLSjYCk+ClMEm1cqZ0BdgpqDHGSiElU5yln6d2UA65O9KgIOrt5SbNpNOYG1FeSys/MSl4ppKFtOZnvJHc75BwngErH/E3QHtBKQGwZMnjSKanDuTcBFsuWPNOZEzAm2bREM8lwA/kWcC2fJvskk5b8uO82S7gFZst64yElkKbdvubgPlvG+ZTv5itcgTOwnyUgG78JbJkIbYmA+2SbXqmx3uc3g6qTusG0LamwTaWk/Djeb/VLQZLtJb0nv0vypL5mMoLvddsm7UwH+2ZSQvtqvpDaJJ0tMUlPx6dfpATBDwJMekrnRqaMe+6PCTmvm7+kS15PKw2pnun3b+tlsyPTnUrDd7ad3mNoO23xeXhP9yT+LFtPHKQ4chzH/anC9m8nwU0G6Vyqt/lc0+Uc+13wtpXkU60vt+G+rsQrlpQ3+p2otpNGT8KudJ7XGq/2d9+XsH+O0+JIw2heY2ww5lGmzpXYB/tJ/+tk3pUWeRJGeJKEbRkHp9AvEq4m+542ZzD68+fP+19/5pgYwcJBYcrlrNszv0zxgzl/2glAOhpWO576OMV88pRs2efcL/kaHadFPveZsDz5wlYuD1S32SoStjlkY5zFCWJLEqmI6Z9tz/cEKQZYJ29uy2X4So/UboEvXZu2/PuzQeizSiYtc9wSIbedjDRdJximeonW1jZpcbIwx5zNIm+etLCzjC1wIGAwSg6bZJXOb7xsQTkB+NDQAC+ds9wSvU33rVh+CdzS/a3u2f9ESU+y2QmSb29v7watnDkmr4n/s75SEu0kgfXap/F3RY6s5wTCejSmka/Ev2mfhCD1bRscHWw4b1n6uktKnrwisL33r2Esbcw2l5IA8+923cdmA5YDdcek7WpsTOXsfvbb+G7xld98VVzrYwpt0vaZ+jzDktTH9EP+mt+elQ0j0nHD/i2O8Dv1Z1+b48G4RHPCed+z5Q/uL9U9ixutP8tgk13r6zM8tAm05IsbP3OPJ5yMY8SUqUdZmv4z/PeEu7+5Op9wK/HI+zkYIk2e+EvtpwnlNhhK+bH5bjaUfHXaJF5yEDfnrHsOSn/+/PnuOTfkh3ba7CxhveNhwyZfa762YYN9Ka3kJsxJPJkmtjmlTcyQHrfrBYJk92nS6Gr51EB1Cp1rSvqvEIlKA85E9DAzMyC32+3DEr3LBjjuZ+73+7Cs+LnfiZK3BJAv8zgJNBPLNFjzGVQAAQAASURBVPs0NJ2VJsczWVjGvM9B8GrSZBpakGF/bpv8NKDcAkpyqC3oGuzmfs/aeabtTM4G5hYcxw7byn0C+BR822ygA4VXW+a6Z8FcEg8pYJkG+87InMGD7VAmqf/0e3jgsbdQkT+upHKLVQJ28jGrd/Pb+rAcuLo19zferNc0mPXM91ynvzDZeHp6qnpIQcYYNvJpA+vpd3SY2k98kmbT7kJ9UW/pSeobhqZEa/6fzAe38XoqKcEYGhLm2y95zAeNOQ6w/xYPWmLCkhLdsZ15cF3DtbOkgTrcYlXSycPD74fcTF+fiWXJhkhz8knLZc7bbh07THeyyZYY+jt93HbrkzTxGmV4JU5dKewnDQLmHq+8NT5cPnPf9HW73U4nR/jNlWv7bduBMeeJbePDfjK07eos4W450HwPHsyOIOPc3NdyLPNp2dgOeW2zaz9wdFYmNz8dTEgTKizWg2VDO7QsibuWAXU2D3v79evX8fLych+opm2+aQzQfDvxT3zi7xSPUqxPbbZ4caZzyilh5FYvxbkpnqSxvZA/y4UTyn4gFHPAK+XyQJWEGvRZSLy32Y0xUQDpw4CfgtkGdsexz46wjzPwdLKYZp7oYAnc3T/rtS1FqQ7l0gLy0Jza8v3Di2Vlo2NJzpKMPMlz00e7LwVx95sSDrdNm7V9NX5aItOChvtIvCY+OQgx/6nO0OEVCl53v7RP0rjZ/ma7U7ya7Xsps+TTrT9vNWoBYmgYrPFkEr/Tu43Nz/x2srCVFKTo23OPg5RLmrF2YtMeJjT3c8eI9W0a2S8HqJ4ZJf2bj7nYVtm/aXS9ljhMn1vCY7o2vGzBvPkDbTkFZw9i0wCpyYp0W29zjjHLf10ZXsnHVnyP9U758beTFuthwxTy2Eqrl+ygYYRjcuLX9RKeN9ty3DyLReZrk8+Z/NwO6TKNtJetbDGWPHKyYe5Pvp1oTBNvSX4sKUZdsZ32H8Mtto7eJvbwLQQJPz4b53lM3Uwfg+9tEtmYluKo8xPaQZJV+qRBsvWe6m8LMMYxyyWVFGNSnsaFrZmIfHl5uU9IcmLVdt7+NjPtO0dseQjbP8sbjB2WUZJD0l8bFx3Hx4m5M99JMXjuT/Q2+oZ/x7D2+Uz5WwNVlwTCYwjDjF/oPQ7EJC4ZxcZYMrBW2A9H8ykxIx+eyef1ZKDsy78JUGl2yPTymAP9Bh5z72ZUpP1qEpXA9ywgt4DaeGz1UxCl7Cmb43i/8pP684yOAc98batiTW++noJJ0v+ZLbKeZX8WRNnG8HXmO5su2E+a2U+/eX8qDIzbO88sM/qpHyaRglJLnnicdlCYF9OWghVxzrOTV9qjnhxY2Q/xmfxb1knf00dLvIjZrDPX3a7PNXmTh604ISDupoQu+XhLNrdvt53uMZ18WNcWkDd83OJeWtWb79Tn5uPm00mNE45kn0mn5KslSs2fWc80sjiOu60N185yixRzpp7jIeunCTi3l/hlX8Yo+t6ZjFg8mdJoaLyat9RPskO3wVXLtFrovox9my5b3y2esj/76ORW27t7mStZNtbFmd9TLow5Ld80H4wjScebTjYZpjrkmzpvOw1Sm0kG5mm+yde2a4C5wsvLy7uBqlfFOYnreMqdVsfx8e8im7wtD+pz8/d2PmFTypkadpEu/255l22auQDjfrJ3ysixea5dfQ/2Vj711N/5bgZtAyZzyZBHIOmpiW5vrtHR/SGdLKOgAaHb7XbfcjEGmx5oMX0OjdOv7+ODpqiIBL78bqsKLDTUpmyCvsH9SpKQyrTheqld3ncG1KZhCzSJbgJOc96WxBD4OJDlJIDvO5tNTYE3+YXlYX2l1XXKO63iNFDbkq+pxyCZ7rEfJz21oJJsLYEteSCgOVloNkVaHHQS1phHbgd2fdOb/NpPBU7yd7Chrfl409nwwM/Xr1+Pb9++Hbfb+yfVJlxMhbZH+6Lv21fMW2rThXpqM9guDTun8MnPXkFOcqZvtySTPLdkKvnxpnvLICW0P3/+fNeej4k1czwTv20SNfV3NWFJ51KcSknrhoNnfV6Ru7HdmLjFvdZvwzjnGqk+dU77mU+aWNhyiDRQ5S406prYS4xpJa1qmh62dybT5A++n3nT9O+3Lzjemq6kY9tcyqmsj+M43uGBj7kClxZOEn+22RTrp42U19huUsxyvwljUp1kc15QYXuJT/KabLOVz2DA3JdyG267pr48GTm68zZt8k0Z+WOfMn9JH1OcJxlzz2RsOQwd5C/J5jje/5e6+SJtoN23FeqGvmEdT2zh8ejG93NMd6V8+vU0Jizd43tbgkmQpmKcPBEQEg1XgmH6TNmEZZA+6yOBSDKOFChbcaLr9mz4KZniN5MVG1fiK51LAG1aEg1bu+1e6n5zxk3Hja+WaDaHvgLqV/kkrwTIFPga725nu77Zhvt2gLL/sTQAtN2d0Wk75wCj0dpwJiUwrjuJ5PQ5g7/p2zZtf07/+dvsn/xtA9WETSnA3m6/n3hOmbUJAfKe5GmZJlk60bFdtbru94q9jqwa3dO3E/j0xPhki0k+7TvdSzqvJAsNC64Ga2Mu+3c77m+LN6nNjbaUlPFe13eik9rfsMOydU7QaOP1JmPLJX22CZ+z+HF1oJruS/QnGZifZBP0E59P/Phci/XN9hpN5JHtprwmTc42mnjeffN8wmDv3mmTho3HKzE+5ZHug3nYlksY/1pptsz+SEvKaRo/pps5AHP4LW9IOGrMTnGS27IZi6038pr+NpMG3u2TZGJdJT5brOC5rY77vBJ7tjiQSsPahNn2T8uBnzReSfnllfKphym1ZIVKN+FWDAegfNz5GN6sphzH8W4WfEoKHl6VYuFqid+n6nZSG16lYdmSEhc64tx3VuiEaSuk5eKVkSlOgh8efv+ZP72PsfGSHNbGyftSMNwc7SzBTv2RjllVok5Jy/A85wb85nHlKUixHcqeNmrQS/7QCvmnPW4ByzaQkguXlNikhGSTc3qicjq2nBi8ph/WSxMlDFpbmbbmqb88xz78gnsmboMzKXglmZm3KcSRqW/7GR8emzuO4+7bpM16tV0MJk37T09Px8vLy71O8oHkN5av+Z1z885aDuSbzyR/93f6v5vrGRNIOxMY4jbt5izJSLr0/UkWqU7qhyugLqntdM+Ve+lbvj9hSHo1W9PnGUYkelu/bKPxc5aIMfltCVSSw0Z/wrorOJz4YWxpA4+Em2d9pOu0+RSfnGgSa2cngrG5lbTSad6HTvptwp7X19dVvo5Vzi2IIfT9qUMdpkIZMa9K/dPWGp0+b97TwNd2btsjfwlPWZr90I7Tqjn5YtuML47Z/LbM0q4kv9LIxVg9OplxwGzj5dggyXOKB8eOmckuJjdMg+Nk3/Nh/KX8Em3JFrb7qQfqIMnCuL3ha8txpv3h3/mXMa7hKGXc9OR+r5RPvUd1Gk+CZkLlQJ0SmbStg+e9omph+AXGNkDXc8CbciXRaslSErSdnu2cBWfXdQLhfhpojvxMkwfJBBwnrKm/KdRd4tHAy74s26SXJjvLadMB7XX65tYQBxP244G9z6fBE4N9oynJy7+nD7e1AYblkgK026PfuV1fSzbdeGQyObRQftOOAzttk6+USn6TeEnB3L7a/MvBOtktaZ1v85X8keVqUGmBwNceHh7u20b/+uuvewD7+fPnh+SkBRaeS1uhUmFAut3ev//OsqVMt+BpengtyX/K0MsJuibbFrdSDNh4b7Gk3d/knY6v9J9+E3fHd7a6yfebLbY2NrrP8PyMr3SNz7ygXdAn3ceGlxtNYw9efSE9KaZNW/4rUcMT8pOS6KlztkqV+E1l6tFHWhxtdVNJMmb7x/HxXdZnuEm5p4nnLa9xneF3Jgjn4TtpoJRsN/HdZOcJqm2QyLbTRGfTMeXF0uJd8o2GpZwETXjXZNNyyDb5e7vd7lt2OejiJ23F3vIr56m2H8qd22b5btVtAtZ62XA0xe2UPyRcan3N58pg2vTZP87wO/nCFg+GL+q39f3Z8qmBagN8GpCd1wxvyUhLLJPxeaUzCcDJJ2mfkgYY3h7h4OKHtbCkxIjHBCmDVTN6t7UlxAbpsyA5PCbZJCA17cmJ5nybuUmFtCWHaDS6Tc4CEqSYdNiZEl0G9gQoSfdnPLZEhTI905GL+918IdnCWXKTkgOed98+N+07gDPAEXRn4MGBKvu6Cnr0Bd7bElrXSzJKCU2auEjFgc99Jh2YFuPqbIOa6xP4PeDcgszDw/vX9/B/n43WKZ60SgF5zqfgmdo0bWzX8p7fpLcF2ISpDWPPyhkPLYE0b+n4StvJhnm8tdHijOWxlYYjLJ+Va/OB4/j4UKhmF0mfnIxqcmt0jm3ZxrYchTQmnTuWnclnw6g5PrPlzZ/a4LjZc8KC5J8pvjIGJBpJJ+XOPO1MbtYNbWNeXcLXHyZ9GLdS7E75ZZKXZWcsN83WR8OFs7yPfSafZ5tj24P9Hqhy4NhyGN5LWaZnRjB++f+llL19uvmbV+dHFo79x/FxwnhboWz6IX/JzmivlLkxaRtssl+3cVZvji07f2gDpNXlKk5RHgkjt3xtK5cHqvM0w/TAGSo1GSSJTwOo+T3Cp0H43Uxp1t9tJeVwlYZBh1sCOWs5dT04Y1LHLcR2hAYODAwJnLwCZQf1SmFyzmYQja72hLtNd/xm+9Mm9Tcy2/RkmlzSjKrlOqU5B3U3evj58+fxxx9/fPijPh+8ta2CNSe33kbOvndzfvPo/lqgG/vmPU0eiYdGBxM+g/YZACU6pm3qg1vz28pe87l0PfmD/Zn30E5b4pWCPGlotpn0RV0ln0s7WVjou6+vr+8GmlxV3fyMQX1wLQV+8+AVEusqBfXNzzdsoP8xBiUaW1vNZ2kPZ76Q6o8szu5l/0zY2T9/s+2/yx/tN70P8gxj3NfV0tpq7Tre8XraHcTvtDI3vxlvk44bBps21kt6+Ewspj1vKysJT5IfNr9hXWIa842tH/tV2jkx9Z1HpPvmbwPH0R9QZXlutp9kl+RBOfNdyqS1xXH+Nm08Z/xr+Ugr5JM7EdmW9bDlelPvDM/4Wjc+MT/FV+JWy0NIb4vJ47NjM/yY3oSrm7+2eECf499v0gMckz1tumX7M3HsBy3ye2wn5ZUpT0v8J9361XvuO2FHKp5MSrG40cW+aK/8vcWaVi4PVI+jC88dp2TUzm1QmoTNA7a5bqMx47wvgfX0wXvMGx3MfSa6Z+XCtKQBIYNwGtRzQGyZUh7JIfm7TQQ4OWIfySi3VaJ0rSVJDPINPFw/6ScFX2+jsGw5S7j16cB9HL+fwuinhc5xClQ8fyYbX7sSbK4EnineKeBA6j5bop1oTefOwGurn3xmbCW99D3RarzYsMr3OCFqiaU/cy3ZdLo3tZ90Yhue480v/H/+GfQ3P3ZblINXZEnHNgGS2ibub/I7s01jcvOJFuiTz/M7xYxWmq+2hC21t8WYdP9m05Rx4nWOiZOJtoS9juGJlha3ko802XmQynJ2fotVzjuanq/I25jR4i+xyzw7Roy/N9k3WSY8Zz3zdCUmNayaj1c1Wa9NgrvPpAPLbs5tA33S21aWeN2D6WSnpsd0n/GS7HTDtdSnbSrd0yYRmYNs/boPP/WePKb7U3uWjeul66R1+LIszyYAz7AhYVtaOW1+YH6cuydbbAPe1EeKhZRps5ctr0g2sbU1Za5zrJHkZ5pT+7RT2uu0y0WPK+VTA9UkmCugT8JpnAamt7e3D+8KbCDuPud4jIX9UmlebbIwr/DC9rclfoNoSgAsC6+ENGA6C1JbQuPirZZtppc8N51YFrNi/fr6eueF1z37OnUa4LpuC1aUH1eYLAeCFGljcty2g2w0edslv1NJNnhWbPstkWLbDVSuBBWeayCTQOzMdx08KA9PrjQ5GIta8GSxvxnct+DT2rZveFeE+yKtBPKEkS1AsL820Tffbsv2zHuH1vT+VvpHs92UaCZcSQkXafE9rNt0Yn8nf6SZOkwrLM1uUknxg7JO9/J8S8qSP29/eWGf3E43s/2NPttU4oX0NL9pK2pb/Eq4OvfRzhKPrSQfSyXx3RK/5reWR1oxZJ3xVeYjaTvfyNPY3SakyQPbM59+uJzrJgxyrsM6bbDYZM2YS3s2Xxv2Tb8NA0hbki3pHIzZMCsV6ofyMw/Gm7P8jMfE9MHj5EcjC5+37ab80g8Gajm0edhsqPHJa9zB02Jmaucs/yMftpsttyVtKQ5598Z8M0fg99ZXk5N5TfjjdlKM4PUzXn2cYlnypaYr+rR3xQ693n2xlcsDVb7rzYDCrTVNKGl0baEMUzSG1OaWRLi9lGBxBim99JdK2hJFb+WcYvoSzSmxMp0pAG7JSaPh7N62KsxjGqmvbyB+HOeDMCeeHrS0IJXswQGHyQD/v0peWwKXgovtNvGYgt0GVmd63ZIE35fooP1sPtOSnuZ3Izvf7+/N9p10OIkhfYmOtErExMNJgsGUyY75SHaf/Iq0pcBkuuw/zTeaTfI3gX5svW0l4nfSS8JkHhPnncjwyclz7/TvVwO4/zagpByoh/kbygy+2ipJW7UkDZa1dZp8nrZzhkUbPrKfqbPhQMK5hDcNJ5LuLYdWbMdnidWGdamOaSCtjk2pjvVz1p9por7dTvr2cYrbG15Pf9wx8uXLl3dbBvl3JdNqbJs6aUK1rXZah857WJ/9tBhFP7Y+N9kS/+izbMcrVMbnhMuuy3ODSzw3fJPXz8Qxt09emX9cnZCaJ62TNk+GUO+WpdvmN49vt995V6PtDCM2PEj9kV9OhNiOP9PeGd4aG9oE2JVYSb/kPZ7UsC+Yviu41nyOhbJK+XyijTJpMY6yorwYS5nDJAxJeZEn0c7K5YEqZ2qcjLC05fTPBFUDcPo4CWlBKw0A0yCw7c9ngm9wPBP0ZrC+ngYiNorUVzJ0t3/F0Ae4GTSnrmc+CCZXyhXHTLLdgpNByX141ScFkBTITGdKDBoos9/m7BvN7K9d34qTFz8Zm20m37zSh/V2Ntvs72TH6ZxpaTOurp+SHJ6znFObZzY39xjD2qzuFTmaX/JwRS+sQyzZcNa8UEbJPpgMHcfvmJDuJY44MTE9zf7sBwyWTmTmP07NN6/KMdW3X/GetlpjG9r6TtecBLFN6iLReOZvqX/r3rJLbdnvUpsuxuOrpWHJcXz8W8zG31Y2m9zabvZ7hmlN78PbHE+c9eJAijHHkXMJXt/ygis+43sSTSnOsH6Tm218fqdcgPicaPb1Fm+NTy3Gb3Gu2bSxY5s0Zr9zn+3ccjbPbaBJPlwnDdhaHtJ4b321upa7z7mPxIP9etNBo8V4doWOhGG8tvWVcp+tbLY1JeU3toOEmy1+cAXfWOH755i2ab4YH/3qm6tx4FMrqmnbgQXDxK5t52GZexjwW2I43ylguu0GEGlrydTzQ5K8mjrf7Y/XlkUyMAPsZryJ53ESL6enciUxM9CkwOzg4xnWlgxtQdz3GXA8uPLg1SuujTc6RytXB9wpGZzzx/E+kGwPj/JkTgvclK1XF/ntcyM7PsFvrm0TSaQz0UufTj7a6POK2QbiW2JB+2/ttJKCPBOirdh2UxLWkiC3kxKAs/vO+DJOelWi0d9ooHyIyQ8PD3FrGdvjdp/b7Xa6iuCyYVGKMU9PTx/eMW1eNxs1z6R1C8TT9jyYZXYWtN0Z7qeVkdfEoOP4uErWYmvjjzJIySExw8ek4Sw+z7FXSLYJuhTrzEOynYSNV2NNO2/9n9Ux3V5xcNtsy/Lz7qGE0Y7VlgXpOY73W0Z9LfmZ20wxyfIhHm8PTfG5K3ExyeJKrN7il3PWZjNpl0YraUeIY/CXL1+Op6en+7m5v/njyDnxnfTVYmKz3cEu0+GVWec67iv1u8WbKUnH28Pe3KYHU46DU9c2Nbtw3t5+v8uc79Ft+t5sodlHsr+z8pn2bT+jj4m99vu2ojo5osdIU9cTGWOXnjibY9ajfPk5y8ldLg9UU2DncQI+b1kxI/PbgNSSadb7DJNzf0taSBdBooFuq8v6TSYNfA2uBJExijHCSRhNd+LD9F2VFb/TioFBLDnAFVo8a+NzSWY2dhq9V31c/7Ml8Wz6Ep8pqaBfNMBoCWZqpyX1bfeAfS/5VksQ0vlGo+XREqwtuDbaUhsDnOyTxy0ZIW1XAv34ou/bfODKd+LJdtDqt0Ce6En9bMcOcM2nWW8C5Mhqvm0f/O1B4Jku7N8TaJONGFdbIX+bDZGO4YvBPSVM5LHpibK2Pac44VWkjZeW/FGWTFY4UTt8bbibJg235M3Xt+OGBZSbfd+2vPm0zzcba76S6N4wj7Q3DHXMYVsJz6lnJqnGhqSTJlsPuhNWWhZXdd9iHG3pDFPbccsbeF+Ly1fypBTTHLfnXNrVxJic2uWxc4kkP8vy6iTLlRwgybTZxMZL69ef1MYW+8yj2+GELbGLnzRoupIXJZ5czuqdlS22J3m0vIF1jG/G/rRARDue88bVKzgwfRJbr8rk8kDVANkMkETb0FIAsYGkmdtWkrFuYOPgbtoab7w/DdjorG4nyS3x6KA/M/StXbZ9HO9fbtz63eRmB98CCJMxPlHXukk6aUlGmwVKNDbAmfMPD+//62w9Nhm0e6fQyZgcmW/yx3MEXwO89ZkSUrfFNk1nsofjOD7IpQUO2ievp0kVJ1mmqyVX5OksiUrgxza4wyAB8hmIu02CcQrKCb9SSRNepnHOu31eSzpOAYNy2vqkbs7kcJZMTDttRnauc/WFbTjpSzKZ++iDKTEz7f5OMafFLn63MjSM/c3/yugnDYcbPYNnvtcrDuaL587iGXFhBqez+jMrP05OPEM+q8kzaZria7KfbSCSSpIF+2s4m2JbSzJZ53a7fXgNXFplbzHEKxAuxtmGaQ3rTc8WExxXpv8U44f2ZLtJzs4FNjtMek6xhDGHckjy3Ozb8qUNNZl5YaXFdp5vA08vLFBv1kmyL55vdnIVo1JOkWxwwxXLm9hAmRt3yFfDgxb70jnakvWQsHS+J0+c3S9cWU253BY7UixsGHOGc812t/uS3s9sIeklffwKqoeH35Pzc8+2oybxSzuYkux9K5cHqk9PT+8YJjEtYUsDBf+BfRxlipOyswTpOHIy2AIMaUuOlgaJcz9ptSLsVAYj00ij2ba1kH8bZjO+AZI2WHHxjL0BfqOh8Uu5mI+2SseSgm3SE7+nnXE4O1hbddkmRJrztUFlSprYD9tMwJ4SnpTIbIlQ8p9tBYbn5n6/fDu1Pfc3W5nriccUeChH07mBd/KL49i3dplurhqmAD2FA0TKq9FBv2j2Th1NHcvC/Jj/hB2UP2U4vz2LmjCSvjZ24XYneLGdqeP2+c0nTTZsMt0JZy2fxAvbabK3braB15xjkjPJW9JxilFTN/1vp71zeVudbjbLc7ZR45h93u1QX5b30O3Ej7jLT8ML05t893a7RTyf+9OW86ZnHvN+23QbfJhWY5DlSF93gt1wPeUzVz5zr3lu/kGa5r400Ue52XaTf5kXy77p3frcZMI+R38jZx5bzklmY1vmy3XSKtTkILz+8PDw7q84m77IwxTymBYkrpazhSDzPHWG5/m2LKfuHA+vljVlZN6SP6Y8wfe4HvVFPJp2OGnf/I0+yhwm5SaJPp5v32d92+aMEQnPU5u2lfQgWeuKfafJKNqJ41aKKyn+bzHf5VNbf5tQbTQW7NR3e1NoqDbabXaNwSApLdF9ZiBOEqg0JrNu+yxQsI+NHxrVGeDTgWxcrMPrSf4GYxujS9JlSnan7+TAqaQgmmQ89zExdHDlE/PojCmpO9svn66lpDSBi+Vk+W42fBwfHxOfvs/objQloOf9LZDxuH1Sv9vAMbXX+m2+la6l/pqts98UnFNg5nfysRZQ0kDEfKbf5pXHn/W3qefVM15rNmA7mG8mMPw9H/+H1f/FNH6QJ69C+NsBuflHsmFioCctyIsTFcvGCSvPJ5xO9r5N3KY+2zmXFB9t76aL9zuu0O4/a3emh327P/ftNhznmg3QzqZYnxvezrEngBO9PHemv0RjOm75RZqM9kpW8+XUl/tkcpl4sM87BjS+G9azXw7ykiwti2SXfEr4mWyncIfXtirbBqrp+qanpK+WD/3dgWqLLcbcVsfH5IP63mIyZeP+jbfJ/+Zay1mch7V4zAlnY1eK5ym2J3mlknw2nSMfLTbQ5/ntvpJs20A10dHwwLkS5dh0Zj+4EqNdLg9USRhHzzYUFq+eejWChj6zl3P/169f320xuhOsd2JOuy2AUKjJUAxAadXL/E1fpIX/62HQm3qzIpGSJMqLM3l2vLaay/ZmRmNbnW2JhgFw+HKhXhM/rQ/SPDTSntjOfLdkgEA5NNLOmHynBDfR2EAyOdPUo21uYE3dcavy9NESq5FPoiMlA+k8+0mgOPeYtk1GU8crfr7HsrA+TXM6bvae2kuB4ErZaKFPeEBn2XhVgfhiOSSZNt9M9JrfpK+rxX5K7OGH/Te/Oo6PqxlTJjjO9tKfP3/ej6c/rtCR15TwJR0kzLHsfEzc5Sz8bBl7fX1dYwKxh/JxPykxSkmJ4xDpaqshLCmRSO/O5LMOKAvK3NfNv2kjL8kfNn2wr2b3aTLAdrj5/Zmv8D3e9PevX78ej4+Px9PTU3zvpGMTS4rjTQae9E3yc8xIHxbbTVsAcB/sh7lakyXrm+ctlrB/9sf/TXtQtq3gju3bXob2tjLG315xazJLeEQ9OB+x7VjextZE39W45pIGlsPbhivWVftPo+Nk8+1tIWbaSTiTfLZdZ33Kc/qexYzJe/j99vb27i0YyWebfMxre1CRMdYx1zg6dfh9RkuigQNV+5N14XadExiPyJ/tfY6ZE10tn36Ykomdc8mJKehJWFKiOtf8FF333QyfdI1RMsDO9VbGQM1DA7ExdANfWrFL96WSBiotIWoJU0p0tjojHwJDSrD88SyOSwMMtsnvNlObSpIJafc95jWVNMBKdCZamr5S0PeA0Umt22KdM7kkuhO9LajTTv0U1Q24Up8J/MzXGU/WKc9bTrZf3ufEzXI3Pc2+2gxg4+VMXokn2+tWbNPJh67Il5ON5i9NSLKvsxVO90X60qD3OP4zSLAvTKBrwS3ZXrvvTCYpsZ16TiDmnvneaLNsaTdneEq/HBpm4pPJQvJVXrvSz3G8H7xaNuYxYUiLNalNy2bTX8N1n3NMcxtnuGae5/hs8OBzV+7daOTv5qMpXvv7jNdmmw1DPUBOMcT4dNb+th02xUbTn8673+P4PSHVsCDFaPNgXXibOX1tzqeJc2N+0wP5vmp/qdgP/V558ueFEt4zddOAJ9lLytVIyza51fRku0s7Ys5ynXYtPfHZsXCzNfuJ9c/7Uz7jNtMg1fJ1/WYTSQat/5QPpXq2XfPv/hvvW/nUw5S2gERwGgI9kJ1kY4qTomZsToxSILJB06F4vRnqNiBISZeDSRqAJl6a0aXVTPdPo+HMz3zPAGPTEduxcRk8KXPLv9WjXmwX5oFy5ezVXN+czcdJRj5uiZqdZUua3J9nBk3fcXycqRodJ3tN7STwaTSna9tMWbIRD1Zb38kO5pgyt28kH3D7tI8GZmlyLNHiVTjrzpjQwL7RkWwv1W/1zpKPrR3a02ZDc5z8wj5qe3dwSv21JOssYHoA1lZM5z/nTh5ZnCRdkUWi2ysErJNWHXjs+EZbm2/T5WTYn6GVPjmvVvCn2bLlxOOEmf5tnW820hKaZB+2J9NlPjwwb6X5assBXNe6S4OlJrfUp9s/uz/xSZlx50GKa1sMa7+TzNKqLe/3pP34DBcyyLNzCa+YthhN/c/vq/p330muScaW7cQy+4R3erC+70n62uK6eWq5VOJ9y4lG9rxn2nfe3vidwSq3ZSfMTbmx/ZnfHqieycHteNdAwmfjgGMRB6tp4aXlbrZv7wqwnbVFEsvJfTlGbfWJpTxOdVu+kHIE80C+Eu5MO8m3zsrlgeokCuxoc6pWWiC1QXCbUlIOv6cYVFLAJw3H8T7w2bDtKC1QPTw8HK+vrx9mmBJvdFrOutGoU3/zu8mO94/8LG/y57bYBxOHtGWA23Da01bdtrfItkTGMm51hoezD9ulTjxjzeI+TCfvScE4tZX6MW3m1TKx/TYgd//NX6Zw4JiAuE0umX6v6o3NMZm5WpxcNL6SHXFQMPSfyYkyTny0AMX7Gu1bYpLobjpvq3kpOG6YydnhLaiTlrbLosmy+TJxw7Q27Bh5MlFMA3Mmus123HbCoGkrDZyH5hbHkgwtkyTP+U7/G5r+eMx47EnLFOcSj5ZJilG+j8dbfEp9N0ymHbit6csDt4TfZzjX+DEN1MPz83McSF3B1ZRzJPk0m0zyo90Y11LsS/wex8enpPN742mK4791w0lzD2BNu3067Q6xbSdbIj+O3cRW8z39pPYTFs+xbcVPim7tuJzFplRGrmk1svVP2aQ44ElD4sHobtphfjny5WID6fNqpOW9+cWmZ7eT8LDJznU8Qb+9R9c65Yc24LyZPjf3UIZ+mrr7ZhxIvCWdX9lFMzbByaWUEyScaL7HesOb67QJ51Q+/TClFrDPViSdhJwZ6dzbHJ33MdGmU821BHyNR19P9EwfNqK3t7cIVq2vdOxzjeckL5fkYJTpltBQjgShMS7rxrOJiY9NtpsMmBRtSYGBIn2TX88StXY3XrZBHPuy834mODVdNf1vck7lSjKVaL4ShK+UBGwOVo3WtKrqOqmv1BbPb7p0f+l3Gtid6WHuZVJ1putW335pedIOmYBs9vl3bZffiba2GjxldMzdIunJq+Qv7XTY6GvXpi0/tt8frzwkmxr++fssobTs2L9ltPlJ8uNEn/t2YVspKWlxKWFFGjykYrkkHhrOtvY22myfvr/h1YY5bXWGtLv9Rq/PJxtqPKY2U4z8bD/EOLYz+QMXORKv9J+0yuRJduKk6UyxNtlcyglch/elPGRyjpYDncnWtLO02E7M4YCKcmq6Gry3TbYVTcuSkw5sgzunTCMHquYr5Rop9iddGHu33CXJtdHZMMT2vsWy4/i4ayANzBIOtJjymQn3Fk/PbKrh0mdifuKL35+Jz1MuD1TZwXH8Ht3byG1cJv448pbY+STD9ExbE6r3j7dZ8Y2/5Ajup81mzFYIDu5Ie5JNCrwbjS2o+TzbSHKjHpJTmDfy8/Pnz3f/G0szzgNkwzdXQ9rMvYNPCyQbr+146vBP8wmQLddpx8Gu1UtAkYJx0mFKEM+Sz6T/BjApqbBdp/+Jn4GUA8tG51a/yaf1ZRtqM3SkKQXTZE9bQEmFsm1tJeC2DrYEp9ld0peTudQOfZLFCWDCCfPiCRsnhA7e8/EKYuKJM97TthMD4tPt9vv9zmlG+Qxfzcftdjuen5/fzTgPz2n1yDbGOpOspYkMz5iTn2QXjo88n3Q3s/RXy6aThkEbbyn5p28wyU78Ug7MPxp9PJ/42mJuS/Lmw8S8tUN78KrVGc4l+fDa9sTOxKfxoOGFeeV1HiebY9vzMEy+V7it2s25KW0lzHY08j7L61iXeOEFDGNhwqUUj5Mezuj5TGkx2it/vt80z7cHjpxIaHFu+p5XN76+vt7bbK+CSjEq0cPrLTZaFykPSKugjZcUX5LcxsZsNw8PD+92FqbdAPYV1nWs4CDeYyrLLGFVOmeZD241eTT5nLXbcknLNGHa2YrvlMsD1ZeXlw9EJUKak7g0x9pAMTkCgwOTJhrtGEhK2tqgMxl6czbSxoTKMmjBkPSfBRDL0Mmjg0jid+STglMrnA19eHi4P/RkgtJ8j5w3sHACRx2mVwNN/wOudiDyvG2dpqycfJvOs+SmJRBMpNz/BqLNYdPg3nRfKUlmBiTKt602p0SMvLdA8xn6Uj37uQHY9n4lcUiATB6uJK/pupMo95n6HpxKyTrrNX+1TY1PtEA9xZjIgMqAk/xueEzyT/JKOM126APJztPgl9j++Pj44YnkbTue5WEMoA+0GESsf3h4eBdvbFfWA2NEm2Bx4T1O2B0zzAtx2jqgPBvNxggXyy3R3HSQsJTnWxv0GdOaML3RPLpj+3zy7/Th+Makk/5OWXmlqsWATf8NzxLetBjW8HDDuC03cP4wsXd+e+KbMkvYnlbbSEdavUr0mWd+U0dXsNz9mWYfb7I9i4PNJmhHzIHSwCzJtcnEdNLOSY9zghSfznZGNJs17ykeG9eSvZp35wkJm+yfCUOTv3FQPvGGMSjZZpLP2PsM/j3pYJ9uMbYNPIlfc7+fuEueqVfHr2ZfU2bywjJ3fHe8M15t5fJA9efPnx8CdWIgGauNshHZwCHNxrJvJlUUUgIz05eCqsE08WnQa46X5JBkZKNkIGyDmGREpsW/x0HSqwrYbioj07EFBqVU1yCxfTY6HOjTBAnthuc3edlJ2WYaBBJwOHtMGuY+rv6wzQTCbof0O0i1geqWcFgHPr+tmLX2TX+6doYLLsSEMxDzvenDazxOOGBarwDoxlMKqg1HqIc2uCRdZxjrktpzEKP/8D/2HKR6Ao5tJ8xp2MhEwjPGU5zgm+9tltr9tdU80t90Yxk3P2C8SdiU2mttNww3/yMTY5X74wCavJL+FL94zH7O+EltGw83bGCfLSdgG5Z5wtdEo/lI30O7Zefkk+01rKa9fwYfyf8WLxOP/KZ90Wdasmu6qBfiVLLVs/wn4XRqz/zT30lXm5gwLdZ7o5XXTat9IrWR4lOTMds0lqSJDr8KqtmU8xvL0vLnN+Xl3IttpWOfm378tyzzPm0nXabBXsLFDZ/5nfrdfNL254Gqt/e2PNT9jz7T6njCOvPtmJNwe+SXbIztpzxp08nck17R6PuTnTW/SOXyQPVf//rXhxkDB7gWWChIBiyvBLquBwZpxoKKeX19fadwK9KK8qAnBcRkFFy984uoaexUMg2mGRcVaUNznWlryvDkrQg2hhlkjpxYGlhP/wSpaf/Xr1/H169fj58/f963QqSZ1e1jPc6Hqzgpcd2cp/HD+zagSzOLKagycCcboS0Z6BN9iaYEtAlUU+ChLRJULG/y1RKMK8X9b/e4JHtI95unJAfXs09PGZ2kAWIbRPl6S7BIT7L3Tc7NDnjduNX6SvXdT/vPZ6KnycPybjLx/QkraK/J/xhHyPfMGs8DKfh+a8YRy8orxj5OtkY8Su8RteySXFLMS7Eu2QblQjxsukvvv3ZMHFnYvka2x/HxPdpnmH7Fdlp7pHvk57bow1++fIkPEkw6mWI/vt1u7+Lb6Gb6mASV7VHvZ++X3zDOeh6e+CDDOd9kYvtosnAS6jzGtNEH0+6GkRuT4hRHUzLOOhxEWw5+nypjQZvQPY7fE/RpwcX8Jtm7jleLeJwG061QJun96mmg2mza+YXLFnf9e1b65tt5QmuD+nDftvFka+l6wo6WX1GelN3w4letObaYXmLz169fj+fn53dPO/YgtY15SN/Epp8/fx6vr6/vVlSTvBpOnNkX5cP4Trm4PfsF/dz+Szlv+uQ56uMKD1MuD1THidJMzDA4CrdhJaCzcdjBU+LvjwUxgWWM0oUK4vYJ1ndS4/5tuKYlJTjk42xVwk40dFNuLXFKwcqOQ/lNO57lToHUQOUVWQcc10sJzGdKclDK6yxpclvJMcnP1SRnftsvDBBukyUF7dRPKpZ1ArhNB8nervY3ZfTA71ZSQuZrZwkceWp+MN8Ni3hvsqf/TrnaRrPpNCE37SZ9H8dR65imlhQkDEq22nRrLLgaSHl8xXfNk+meIMjrDdedUDf/mOvpPOOJ20mJXdN5khl9yn7F9hNtpp088J5Ntq3YXxjnGl6e2UKiveUKqc5Vm0ltJN9w3Oa5FMPTJIvbbLz6mrEqYQL7N61J3swBNhpaXLAuNp0kvyQdXhm+3d5vl096b/yTltSu+Zh724COdDNPmlg+19Ik5fBhuW/Fg6nb7eMKlX24xeymdxdipe/x6ilfUcd7z3TffDHZZ7L3M2z0OMB240+bREzFfU6u//Xr1+Pp6el+3AaoQwNp8XHqg/a5+aWvp3Nu+0qMMY1JLsbIpuNEe+PlSrk8UE2zb8fx+7HUJnAz6HQPDYK/PRPupXYaxtPT07vZinH6cbYZwKYZFgNU2nv+9PT0juf5pAQiOWxyxE0eU48z3ClBabL16ibpe3p6eheAb7f3rzywgxus7JRz75cvX+6zJc34k9P4mw5EerjP3mA6+vZ1O4od2LRRVq0Nv+Q6TeDYnltx20w8vBI4M/us1+TLexqokIaroGOwdfKytdMSsdTfmb84iCceRmZum8kRz7Fd8tL0dzWwpASCGNoSMssugbz9KQUj10/XjuPjXwJs/w3XP4v9lkGiae5JvKb2bQf8H13y1TbBaLnYtnxsGW2B/owH+uv4uvkf3hKdPke5JFqu8LjxMsWJFuNVoimVRINp8SDRcSrpcaNj49P+Of0k//LunyQj09PiDm2WuYZX6mwLrs/J0ja5n3KKpKvBy61YRw2/jLtuwyvSCdOa/TE2Oo9h3TSgbLFjYjhzzi3WpAnDFkdpu21XRottbnto9LWznMb2zRz6Cvabryb3KW1Sn/JLeQ/79j0tZ+W22uRzxlbSwzHH7KKYFVXvpEx6sn/x2rRLmh8eHj7EsGnHMvb5xENa7PuM7tx2uzcVY5Tb3DAylU+9R9UCJzg4QHmQmQY8FsbcZ6P1Nhv2RQCe+o+Pj/dtwLfb7b60zsEpB62mf9rxgJW8Dc1Db5rtoxO4tMShzRqyv1R/zg3dli1pHzDj8XEcHxz8bEDfEuOhpYG5Hce8tmTCNkAauXWiJTOWJenhOdYzTek+9zGy5fccO3g10PHHNjd2bb8aOpr9EJz5nYrpJa2k4Qxs3H/78B7LyAHFNp2A3To3H3PN+NLua9eNaQbxFnAb3+04JYpNhqSHOm76bomQE5szm7lqC6Yv+YL1bLs4jvyOWuO5i1dWr2B0Om6JSMM902sdG7c2jLVttSTJekvtpgH7GU+kefoZ/oxFCbvNf5LpXG8rwk6qUoJ/pdC+LCPHf8rbfLKe+WqytT7YH7cWerDk/Mp62TDW9KTV4LPVJ7blhDX5k8/R9nxtnhTcfGliP38zHnkLbYutpKvhz/xmHKLsrMc0kZF8159tcWCzY2NjyzdId5K58cGrlQ0LrYOrq5bss8XusXfTZzrGHkb3k/u/vLzE7dQpr7HfM/efQSonjBybmDc3X6CdOG4R29jO2URxslHiMnlKi3zJPqa0XULJH5tPnZWrGP2p96i64WRobaaKK14OrlOPAYrtpkCWgCAl8y3Au5ivNLPIBxFNP2k1ZIpngc4AZwsq5L059nZfklObleJA/uHh9zZfAqcDjdsi3xuPV2cfE4+kiYnTOHqShwFp5OB+U+LBewyoTkrYL+u5/8RbSpiSLTGQ0F/m40ER278CEMkOCYZbAEtgnZITDxoorwaIjb4rfLUgkoC/6Y5tGZ/STKF5nePU9pn/+PeGGZZFk0+S82dLsuNUHBxTAjL3pTrpnhSsrbvkX+l/uZ+JFQljt2B+Rn/Dmqt+bP8fLJ9rCec22zlLUsZv0wB7k0nyqxbPhu4k8xSjk82n77mXeNbiU9vhQHosTx4nezBN08/T01McqKbV0bHfeRWT2zzzG+Y1I09O0s858moZUw/bKoltmHrdYmyapEg7ipi7XB1kJ9/ffN427M/mx8lmWluWt48bP3NfiwnJ3kee5p32n67Th9PkxpnsKS/HgDO+jRfTNxehvJJqnmiHiefxKw9QU8xw/9aDJ5J8LfnBtNkWiJpMEpY2e2iYbYxNdLg+eW4xnW1/tnzqPaok0IFwCt8j2ohNM3AcDFmZNo45l/7UPH0OXV+/fj2+fft2PD09Hd+/f/+wojrGPMZtAKGhc+A2/T4/P98NevomvdOeZ6fGCOwcHLDbWJKRbMBK2hncvD2Edbyi6u0oI1smUVfBnnT72PxO21NSUjL3PD093Wdh532H80f10W0KJmwjyWLuY5Lg+rSZ9uCXFCymbK/PSOcIBmNXX758+fCOxLlmH0wy9/acMyBxgmW+UhDnPcQH2g/bcrKR7MbA7vt43hMa7Jv1zh4U02RhGaRVjm1S5gp4z38vnTy7Dct8+mkJHGWfZmLH9l0sW7dru2orwlubKcD6fgd509B4ph2mLfr0s4S/jSb2nfpMPJhX2qXx0DbMNiwX9p0mVfmgmGRL1C0HA3PNsX6uO3klNtpXW8xIOiNvDRtGn544tq+6D+Ma7d66Sbg8Jfl5SuKnH67aPD093f8Hl1ZUU/z675bZUZLiLelNE9mMrcw1mP+4GFdox1tOkPIi3pf4SsXxw7E1HQ//k7M1fSb7SFhM3VtWbNerWikXJE/OAdifr6cJBusmxfW57hXULW7bXh17jU8p5tIfKAvm9NyyPP0wFyImpMliDkrHJ6df5yfzYe5FPbI92g/1cLvd7jT/+PHjXd59lpu5L+MN76PMZsyTYl2KWdaLsZ33ptJo/Ez59H9U2fFG1Lay4N82WLeV/ms011NySMWk2dgxLhr46+vr8fLy8mH2IAnXyvr169e7fsxLC6hO0l2nJcgNCFMi2GZl2Id5c3scPB/HcZ/BbSDEexNgJR23wJjapBx4bLCg/posU5usR3BryawH0S1wznknBMlH0rkUDDawOEtqbGPWW7Lb+Z3apA5SYpGCZaJ1k91Znf9uAufkJ9ny3y0pkZl2aaNzL8+zf+qes7Fsj9+042QrTpTapNCmF+v4OPpgPZUm58ZLum+TRfpN30v9NN9IbTX7THVS3DNvPnZpGNkK+Uz9pMEV6yW/YOLm/2g6iaU8NozadGefcJxiP4PZ20B1wyHTtMnGPLkdtsFrXC2dldSzh7X8TxTb7ejWq5a2+9Gx//PXZGk5JP/eVuMd67ZYlfpNmLHpNMWRhDem67M8u3/TQj9qcTb5EssVvPJgxu0bT92m6U7ybN9nvrXRTP/3wkrSC30o5dykw6unnkgwvnnigLy4LuXov621HNLYmcqWiyXaE9a29rd72e4ZbrsN5yJn5fJA9SoY8V4y4ICRZjMM/HamacfK5yxX2kNukH94eHi3PWAGqX/++ed90NoMkArlIHD6GRrMF+9xe04S0kyV6eDKD/lKxj5tJkBID2Lg9zYrmYCQHwOhdZHuawFoM37SMvKdwTRn4FLgS2CdwKsNVEfnBFDOnJkv2qtB2g++Ii3TBgHZM6JDDwGqBc0mi5R4NF9KQcl0WBaNNrYxMrUdXJnBa8lJ+p2CQEuMNl5bSbwSA3hPs/WEuQ7Ybt90Nv6NwYNnc8y+rtDFflPfbdXONuj+jMMNkziheVbYNrc7OhFKGOx22vWNjm11PcXERLuP+TvR0+zYMcV0sh4nRyizaT8ljLTxbVU92XDivWGAbaRhVZPZHG87URJtzlvYFjFtvvl/0/Q00bZjotG/ySEV2gh1tb3Wp+nW9Gy2m/yK550XtJh0FYcaTWcYsWF9o2nDX9uFdZtwgDmC/egM35xneCKHPDSar+QOpj3t7rgSl64UxzzrwfmQ8wAuNrQFIvpkWu2mD3jXCPtif471XIWdsQdXgFs8aZMKW3Hf057jpP2PffA89ZzoTP7JYh9wjryVywPVswCTkg8O4txOS65SScvRc85PxOUKpw3R23NnBnM+j4+Px8+fP+9/wk5PC7NzDR18L5Cdlx//34Q0TiEvlnWaGbKskkNtujNvDvRniQNpbskdJxPSxAETorGRZsgt+TCAzvm0AtnkQp5a24nvNohKTsyH9yS7oq9xImFbqUh9JiBK9KSA5WSA9VPgT4A2xYDp4kBsGU77Xtm/QjNpmHsTniRa2GZLLFLyZd81XZ4pT4E3ybEFfQbGRB99ypg4/dMf+G05Ui7JDloCkGRHeQwNZwHUOml6dGk6NR2WbQu6qV/GJfbDe1JcSmXbYWN+Wl8u9rGR+8PD77+zNFm3CbI5Tu8ppJytx81+yEPD4jNMZp9u0/1Sbsl+24B3o2/k6y2HfnIo85CzvkjnleLkN01MMkfwQNUytQ1afp74cnGbQ6PjfyvNRrZ+7HdXfDW1Ncctbj48PLybgLDvtraNOS60n8Rfsj+WhGfTXproTjjS/It2bdtgGw2nkz00Holdjrlsl5NttBdu3/UYpP0+jo+xkA+wJA1pccyLMpQ336Oa4j5XHJOcks2kHC3JNN2zxSLq4TMl4ftG/1Y+/TClRMTWcSOwCSYZqK+PoMeI7MTcW+9glQx1jsfgjuM/A88xtDQIsfDtSKSnOVWiocnMydUG2i1AsTT5G3woc+qH7ac2XBLIJ0dJCdiZ7bHNqetBDeVnebT+kn6vBPAmg1QMHg28N6A4C+5sf6PB9VoQTIBKX9sCUEr0kt43Os4AL9FJm9voajq2z6fZyoZZW0l1k99ZHrZRBsazXRu8Lw1GP1O2thNWJXv0uabfM/s/C7RXrl2RQ7OhhhGkb1spY/vzfcb/hqlsy3WYINs/Up8cpHqyj8db0vt3bMz1mjwaVs1xi3Xzbdvc/D2VrX/2R1/dJp2vxg/3aXs4jjzBSX1xSy9p3/Cf+dJn/K7FyTMdzXH6bDJwPbflGJH6Zx61FeNf4oE0bjjPeqn+cXyccN3irvk5GyDPvSkHSnidYkjDMd4/tKR8ijySZuOV++OEmxeI0oTFFm+mX+LcmS0kDDWvLVdI9p3uPaOZv9M9820dtnjRbKr11/jxtasx4W8PVKdsq1Lc7pJm2H1/E4gZIqg+PPxepfPKpfubWZX55rmhdbbgzIwH/7eaeHAAM1jwj8vT9xg+jeMMpClv92+n40CTW7XYpsEn9WM6DNip38TL2VYJzzzN91W5JHDjtjQOWtnXXG8DVzu3Hz2ekgK23QJMAjL3Y3mwnh9+8dnBRqK7gabPeVvN1T5bYDD4N503AExba1Ky0oI4g4GDg+slvpPdJhrPsC9tJzOdtOHj2N+V5kDN974RG+mbHmSQjoRzxlDz13zX+uf9Cat4bytbsEz9JxrTBJ/vaXGQ/VqPjEcbLpy133iz3q7SOPpnv1vilgY2abtd8r9Eb/OnLZa0hC3lCL5/2uWqC3cOjY1fxTTLJ+EC8STZFeMU+Z7vxGs7ZxxJkwh+WAvpaXbY4oL5Tf7i2O62kq8Tm4zNzZfsc02HvO9KrOH9SQ7kMeWfrZ3NjqdNy880bpMnWz5gGtrkUsJ8x6Am8xTvvFLp2GObNA9NZ8Zzysyr3C4tFpO3tpONfXvSiW0lXhkbLEPHaMosyaTZVcJVY0vKf6jLlltexeX02/HiSvnUe1TZ0XG8XxZPQGMlJuOlgghMbMvnCTQGnTRLOZ/Z3jTfXA2afmyk5D/xlZKuDSCYjM/x29vbO/lyRcSJwLTNBzi1WTzOJCVayGcy6HQv2x9aW2KRnMfASDmk/lICZUelbOYJbAaXjY/Es/lMsmqlOWn7dvuJxtYWEx3XS8WBwHQ22lj/s+cSNrhOwhB+e3Kj0eptSFtC0AZXBmlPsNCPXegXyTdanSZv2/9ZUEwBZzDCk1q8fpaQuU3S4SesXuVn6Jo+05Z408i6xjAf2y5MW8MTH1sezU99z5TRS4ohls2ZnaQdDKSpYUrrq/1O/BjDia+Om02maZsbafD3GR7NtS03OLPptMqyxSzXP473/8+znbKN+f3ly5d3u7Y4+NpWWDf5WgbUTVpRtW6SDlha3PS1xH+7J5WrukqYnWyH7aZVSMf4xNMZdidd+XiKJyFaTHNc9/1pEJto52/bpO/d8LetBjYsNF/NphI+uVhHPsf+0g6fVJ/9toF3y2MSj0kWt9vvnNQPaR2f32TqmGvZpZ0uZwPqacuLXonH1k4q9nfyYb9r+NPK31pR3YydCUHa3sLrBnHPaDroJCEex8ckNq0qjGJmdWH+HzLtMmGywpPDmRfSuxVvX+CKn0HKckoDL8680dinDz8gg23ZYKnfK85NWTNRJR0J3LwqR7thf+TDMpp77KT8D8HVlUbT0JKWRntqLzm0JxLcBmneEgbLyhM5CcBbMEk02/6SHUy/Z0mT+fWx20s0+b4mm7mfeOAAQB6vvJpjAgwn5Uy76XHbaceA658lOqab/jZtpfaMrcdxfBgQGvPYd7KpOW5PR9xsl/S1hMDnTNvo2Hi3JaG255ZYsK6PzxK21G7SrfHSMkv4kfDI11woM2Jp6zPVT3He540Dbbac8uO5FtdbnE0ySn0zDiSbTHhnGrbYkehx8WCRPDcsSu9qTO1tNFJP6bV7CZ+T7yb98P7U79XfbPssRpvGLQYkfmy3afV3ftu3iCEJ85ssEl3ug/bX2kp5B22G97ddAVvO4nicYgIXVc5wwbpJ8bXpsMnAejFfbXBq3064TRo2nzIGJ3qTn/kVQ7fb7wla2lSSK88njOIzTNgPcxbKYa5vvrThcZrs5n22pRSvjqO/0q6VT7+eJgVwFg9OvRUiJW1pYHG2NExheQCQwJ30UVmmi4pOic6VkhwyAYf7oDHSsNJ7Wed+D1JSUJ97CTrcvsVB7mcAl7J1gmDHTDPumy0NKI4cCD4EgOFl+OGKKtvdAtzZyhcHLE0mrW3y1SYE0n1u1/Q4UI6Mms9sQZp2Sn+de1rScwZw5tEy8TftJrXd5OGSJkySHXgQSZqnHfqVMamBPG3JQXK+2ySK/TcNsNJODifBU4crNlP40CIPukgniweBPDf9NxxONt8mJbdATSzZ6m8zymyTPKTEP93ffIH9sIw+5mF7fkdfmsgwrZsc5/gKxs41xxjHqJRsOWlNiQdpYNl8NfliyhkSzzxHTDKGuPC++X0c72N8mlRM8kzt8t5Uh3GEfZN3T0RNu15BYRspr0r9b3bkfILfKQYlH+E5/kUrxbokz5RrecFj8xFjzNDrPhO9/J1W466W1LZlneKZ7cf151yyk0RnssHGL++nHWyxgTQ1m6EN0DaZhx5Hfh1iigNtJTD5jWWQ4t3QY91YT8dxvKPXvCaspZ+yvaQz+9ft9nvhxXxPGRud3RkbRqU40u5vNtLwJPl2i58+d6VcHqi+vr7eG29E27AdhOxUKZEwsDUQTsbk4yaM5HibwlqwtEOQf55LhUHdT9ub/jajSw5s2diArJdEXwPmDQS3Y9enjNpAlkHZSQjb57uoPrOKSnA1z1tgSk52Fmx8/xXbSP1dpb+1kfSf/M+v4mFdvrokrX76OCUUpCslDMk+G58JH85K0lfiwedsf9v9xAvznCZxGh2N1hQQWwBgEsFZcdpAW8k+Cyr03RnIk3/6r3k8a3sL4M0GSE9LSCwv3pNs0vekFa0zvpxgOEHiQNXJcUuamu0lunnN95yV5qfze8OeRp/93IPUZCtndCc9Jr16giP5xNCa8LzFli2fOLMr8vj29p+/Ac03ZTf0XolziffmU40H08g6aYdTK0l3yZb42+16gLrhd9LdlZjEdvhpOSt5SbE08TXnmj9SB2lxqNHd8HWz2cSTMZS2ttlcovdMXr7WJh+nLQ4SU87VVvsatjecoWzIx+32ewXU+N/iDAvp3XD+OD7urkuD3bmv+UayY+cmjebm2wmzWlup7pX7Urk8UP3nP/95P26AwRXA+cz9fD+RmZukJs0cTN2rSrfCEwCmAOngm1YH+H/PBHYpSUoJzfz2H8m5+jHBigG1teMtBdvyPHlK30m+SaYNXF3fgM36fAXQllimGTKvCnumK9GdZLEFrCRfDtJof2n2lfykmTXLhdcIAtPG2CWvpaDc+DDQsj5Xeub3tOeXU1NnfPATaTA4JnmnYEpefX/yt2aLtj0HPQbRMx9J75fckrnGo1/x4b7Okinb3WfKNhhlux5wmle3adxhO6R1C5atGKfZ7yYjv5qLWOGPccfJlgNzW1FkcR3aBgf1yXcsJ8fBOebDsVL/ZzTyXtOd/CrFeRbaDYt/s27il2VbFW32Y10OVvG6J1EmZxma2isukox4Lq3KUwaWdVttMY3bCpHPmx6WFuN5ftthwXs3H2znUmnxL2Hhho9p9Tn1n/LP1HdawZ37WSfhReLR1z1BwvuS76X2Uj6R2mky5nHKVbiV1DsmbNPJnhPtpJH3tFVh3jfjgBYH2+rylk8mO90GvKOz+Z1yj6lHmyN97iP1N7Hr4eEhPoSJdSemcKDPQW6Lo83PEz9sy3ErLdgxv/qfKJ9eUR3CZtWFDNiAZhtmAt00I0eHSVsMj+PjgM0GYYVbsckAeR/v59Msz2b06KRsqyUiKQCOwXHg5uL25rttlzKQ2Dj9kKwkpwTWSW6b4dNwvWpOvRkw7RhpEiDxlewqrfDw/pRstUDGOkk3ppHtpKSM7Vmm6b6UwDQ6yPNcS+8U5lZE0zjn0kyr9U35tsBxxiP5tMxtI2eBmXVICxP/oTM90CfZe0tK+fssAXEd32/+E19JTin4MpFoCfDcm4LZVqyHhFFsOyWBvGbM8YpGkndLGuZ7bNf1Gj8Jy5os0gz1ZovH8XFXgmMYZcGHbrD+VbyYYntvPmma7HsJ09hm87/px3abJvnO6PJEG++1rdMfJ7cgX3M/n85v2lIy1krCj2RLps3+O3164mjr3zpx28y/3Obt9nsik++nZ3u204Y3jZfRXbKToYExOPU35503uFhevHfwoNmX220Ys/mN608h/570afHUeYrjeYpLzEe3+MBi23Scn7b9N6iEC9ZXkm+a0Ezl4eHh3cLElk+kNhhDEwae9c+255MGrHNPmlhtMS31O9dnQtKTrdMXeWMOkxY0Wp49umOblBu/k3zbAswVmV4tlweqnpVMjjLHcy8HqimIWYhvb28f3oHK+44jP1hjyhbwtpISHCfunHFtzmcaG58JMAguBp/mTAaftJpqg2yBx8UBogU2026jd5KQEhWCiBMNlsRLSgDIg/tPhTI/m71ugdmlAcFmm9Yb2/pMaSBhn6XdeMsv5UDQ44pskn3SQaIj3Z/sOyWKthHTkyZ5Ep7Ytjn51uwqJSv8bvq4Utp91ptldAVXUjA9C+pngaa1ncq0wdcFJGwdPrhi2PDsOPK7BFsgb0GYdScpaPiS6joGsp10f6Mx3esJR7aR2mp+1RKzVhp/Te5Jljyf7M34n/pLvG/3bfHBbbH+TBKnmEr8SbHwCiYYnyjD2+32bsKYsYK4a7rdP+8nZjg/OI78gBvHqYaXrp90R3ltuJRKGqiyrWnf+UQryZ+O4/iwIJDaajbvc2d+RexiX5yESLGzDSDc55ntNznaVrd2yLNfoUfbMe7YHm+32wf7SLJrds5yhs2N94lB9m22m/RhO557vcMg7crYJndcks9vuGY/P6ObcmsTNpZf4/2MD/Pwd8rlgSqNz7PnHiC9vb3dHx7x8PBw/Pnnn/f3kz4/Px9fv369/04Dg+knAeAW8Hhfo98lPSCHyUECeit5eGb9FASmDSZpyfhSopSMnbyzr+SoNvwGfBsgtjL1HGx//fp13y7q2b2pl2YHGTy41bTZRioGD9JlubBdrmLMuZa4kr4kpy2Bsd7aQIy03W63d1tCNptwMa88R3ufAOT/TZt3B7bU19ZPCm626c8AO1dQ2G+SvXWQZjqth7HnswFxC9amycHEfXp2lJMIvHdoYOKQksT0OwUpHjtQJl+a++njLsRsryZwIDDtfPny5c7P4+NjTYQsM2/vdcIwfbBN1k36tS6vJESebKWd/Pz5M9ZP/kk5cwWoxT7LxgnY+HRKEnnf5msJA3k+rWL602gnv6mktkZmtmXGi4bDbscD+TMca7JPSaDpoI3Ob9PjPKH13ezQ5xqeemJ5fJPHUz9NXBt3vFrPknKddh+/yYdje7KjhO+Oky0epWPSkvyU/p50k/x6rjc9Mg7wHj+EjX7QBh0jrzSAsr5dvPXUft5ynOkjxSPaM2VnOdhfWr4xE5vHkf8WkGKHsfRKX1PSqmWKDZsfsC/z4zGWY//If2LlxM23t7fj9fX1g4+YFk+AepFp7jEWWV7UG3mh3hMebLJN5fJANRUzOQJmGYJHqLfb7f4u0+1/Ni1AOMgcxw6MpDM5lPsgzf4wKNpZ0/YIt52ANSmQx6adxpe2KW5y4PUEtlv9TUd2+FaSXNI9lKcHIFf6cftXAzqde64nObXgswFdAsgWZFvbCSRI0yabpr/NNhMNycYN0MnGCVxsq/XVkosWWNxH86vkL5seXN/JiIF6C1DN/tJ5rix65XH64qDviq2f8bjR2epfCepbG7fb+0HFxAoOzub+toqX7M8Tivy+4guUacJ+y4D13M+2+mMfSTZPObtuknmyR193om9aUmnxIiW5TU5u38nO1pfrUP+OwSkeN9yattIkZtKL+29yanHgCm9b/TPc3+iyrDfayLcn2BvOp/6TH7bY6GJet4FykqH5bvob/bd4ZP6a76W6m60wmW8xNbXV4rVxyHg01zxI54Tn/E4Pq9z8q8kgxWnrwvLld5Jnkwllyv49duC1DXsc31O/idaGu+zzDNM3vyLukg4/O2SL9wnfWhmde9Ih6dG02v7M55XyqRXVMwWbsClfvny5J1w/f/48vn79+i4BS8DLT3tfnweRiY4R8Ea3AxH7m8H0GAUHTlwtZCJip0nJiPunrNJKTXL2ZqzNYJJu0n1nwLC1k+5pNGwBjUDZXgtD+pJzWyYexFBntpWUyLluksW00x4QRb35tUMOOo1Xf48PnJXN9hz8yYtXBbxi4vbSzHULrOkzpfk66UgrqMlet+CY7OI48muWyB8xoSWQZ0ma5UVeiUXWL1e8UxBueNCKbTAlrJQVZentgi3JS5MIt9vtvvtmHrGfYsAUyqL5uh9ER92xUBeW1+b36W8wQ1PyjWaP/m1bSCsmqWxYsfHte7fk3/U2WyButFWXRNtZTEmTlS35s5/5viSHZvOzA8z+z3sbPW635R5N5luZtmYCa+uv+WaqQ56IQc/Pzx8Gqo0m+x/POdY2mcxxWjRw3tdwJ9GXYsBx5KfOcjJw7jHfbccV7adhgOPa3LflgA3brRP7nvlOiwH+DD5PHtZoIg3+bTugvbdVv4a/W9xO9abflF/QLk0zMXfoZD37bNJHwoA2wHfuQTo8hjiO36/JGdq4E8m8p2P2MfaXfHLonIHvDFZTDHa7U9IA9zg+98rPT71HtRHVwJ8KHUYnGeG23zT7zf3js014vvlEYSaNrE9AMp3JcRIImIcpfgqqkzUCuZOWkeUU32eQaPSmBMa8byXR9XeKQZ08cLDWtu4OkJPm5FBMzKckgGofz8Q6YJLGtnJDupNdUQ5p29D0y8Siyd82SF8xv5tcTHfrg/S43RQ0GGDObKldT/abAn1KTFJAcCJr+V6Rtdt0u+73ON4HnwTC3lbjYJsGqu142pvBmB+w0Hg5O78lHNbBnKN8vPOB7RmjrXPWceJiGnyPAznvbwkK25v7ku140DntePVjrlOv7frmhw27XFqSk9odX93uY5vWk69TLk6mqSMWyzHxlWJc49nYm+JAy0nmHifpppl0zHa6M72YpnR/wm/bMq8bH5JuZjt5svdk+5Yhi7HIu7bGlkbPxrn5TvqyDvg8gE2WKR47rjZ7Sr+nTnqoljEt2fLUsd+aP3/absNkJ4km02fbsJ6YzyS/Sn5s/KbNOcezXBMPrN9K07GxPa2msw3is2lju7aFNLZp/k2+uUjEto1HaYKG7aS3CkxJ79oeWdg+PXHfMJPXzav93f5p+0u5hX+nsdFnBqnH8Tf+o5rObwBJJ2Ky3YIngXCU9Pb2djw+PtZ2WWgsGwBOWzZ20uB75jvt2WefTm5YNwXkBB4bgJOmFAx4rSU6bqvRk+rwXHLAlrgaSFIAHwfwQ20MxFMMjAazaZtB3/TPMfWewD0l6a0d034mT/PE0hKZdG9qY7vXfpTudd9N/o3+qZOAcX43wGs0H8fHp2ISV67wbfpIZ/LBBrC0B9NGTElJqgfhtl0/xI1JD3V3hs9nJeEA+UsfY0aykZZYmLYUEE3XmR6N5S0++DfjiW0qJautneN4v813k59llNpp8jJWncmlyS6V5tvuuyUxU6/J3TJofX+WVvbB38kO5j5PimwYvOFXqtNikOOVf3P1zXjQMDgNDNunyY40JzwavZvHlBgnG93kZLrSb2Iec8Qzu075F/u0b1zJvdhe82frdei9ig22Ua7sMqYM/V7soZ960M22bTcsWyzz/S1GpF0hm62m9kwT2026OssT2a+P04KX6Zxif5h+zmJxsy+31XYPTFu2ldR+i6+pzy3OprpnccV9t1h9pXxqRZUd2DnpCAaaEQBnY5owCELzmf+z/vr1676qylWF2+3je/xIB0f+zaj5+3Z7v3Uz0TllnIZ/5t4Ubedq/c+9m4NtPDQ6Gj2fNRyvQvJhJJzhnWIeWBigqTMHew98Ke+5L+khJQksY0cpkCQbYLBsoMB7t4SDJQXPuddP5U3yHFooM9uSS0rI0j0jm5lASMC52fRx9AB31v/UZb9O7nhPaj8lAUlvaXaZ9dMDjWifrVzxs2QrLcFl8ph4meMt6eI9Q9+2zd62NDbcZoQT3fYb7rxIM9ukPSX+/DsIkwzLxzPh5mnuIZb9/Pnz3buDkywTvVuC5X5JI+9N8YL2aYxPmNJ8frtOHbUE0ys1zcZSO2kbZGunYUPivcXJhs8jr9ky1/SwYUWyzbQi6YdHpjxhbN++lPDLPJ6dazwkudLOjuP3wwKZ4wyfzrnYT6LB2NZomK2mI5c5P7bp3Xi2+xbD2KexyPJLfjH9NXz2vS7NDpM9TKF8ZyLW/kLcpvz4IMq0o4044/Mp7xp/cY7HOnyqO9tzzJqPH9pIWTFm+uFF5oG69Ep5k2+SX8OSdEwduR5jUcIi5y8jO+ui5Vkju9fX13us+vHjx/2bMm4YnXj1+Q07Eh7Tpoy91FPaGbKVywPVrUEH1Sv1mvJpoFQIr0+yzO1vnnnYBgJnfDRBuxiwWzChHBqgW9k8Ji80PA9IuG+9BcTpx0lhAudNRmfnLKdkG2kFc0taLBsDBGVBnq4G6C1gtISgJULm2/wP8KedBQYxA5xtLfmS+914s33Q/+Zc2hLUAP2qn7m9dJ2/R17ectJs8syeyWfSJ+9LduZ2NlC3H6dJtSR71j8rje5NFuw3JW7k7zjy4CMlW+mc7cl2nQI96yXZ83pa8UkBsdla8kfGoeTfjeckx4YTCQNaQtCwca43mbudhAeWfeKH8nAilHhlO82HNox2m823rpSURLEuV6Va3URrwljG7jTRaHrIY/rtOpRFipmpnYTz5jHpnINWYsoMGrc8Y/qhPBLmz71nMr2Sb222Z363WHSGadt9LmcYTFq2GJ1WTu2XHqBuA1W33/qm/I/juD85nffQvlP+ebYTo/WZdLjhRdJHmswwlqU2zn4nH07nNv6IEam/aYsTujOJ+vLych+wvr6+vntujmOW9XUF67YYzu/kh5bTnOeY7ip2Xx6onoE4iUvXk5HxuCWbx3G8m8Hln4a/fv16vL6+vgsC8wAkz+i0koyM2yzmHivaM3p+gnHjywlYSzzSVkA7l/ngQLUlI6btszMbpj2VLXCnrcAJZFMia/BLn+mXSWtyrhQ4HFSbfgxuG+g6CPlcSx4MrlzttX2YT8v4LAi50L6aDKZuW00zv00H6f7UznzPYGID2jMQbXU2eixzX0t9b/JP2DRyT/ac5Mm+UqC9ssLm7WMpwLHfNBk2dtCSCtPsQQ772eqnYnlZ1pzZbrFgw8OhMe0SYf1tYjDpi9caX23l9ywJaklZ2yFku2yyajp0u46TbivZ5lkh/Ul+zVaaHadiHE1+3vTv+1IS2l7xMPYz/rXRNiXtTNhwL2FPuyfhjSdTuAOq5VlsI8Uz32scM52WIxclEn6nXIE8sK+E067jnJD2cgWryFeLj75GOZEG6t8rlHwIJT9uh/xdWZX26q5Legc7S1qMYH9NX56YuBKrW1vua+jxYpj5brHtzOY3vOWkS5p8oaze3t7erZ5yoPrz5893g1S/Km6zxyS7pAuW1HbCeB8/PHwcW10t/yMD1SHYn43Z4/i4FZBJGfuboD0D1IeH3w9l4tODHx8f75+np6d3ymcZgbXkiA5pECK/nxF8at9BxomSDXjqpIF0umbeEx/b+a1wVYt6oQ6d2DgQ+fyWAJ0FkcSLg2sCSAND+rQEj3p0SSDcgpGLaeI7Mglyfgq2Ew0H/8S7/dS+a15sx9uMepKjA01KJFMCwIkHJyaJV9Mxdbwa6z4pBydNjcc0qG+JQeqPddn/w8P7l5KPvaWtX+SJ269cTL9laZtOMuYTAKfNGchxAs9+NQmBZWZ7H37nm3GgFeNEmuhryQVlntpMcmvJUZoccB/kNdFhuq1jy34+6W8Bls2VpMXx+EwezZeS3fN6mnhMhZMp41fb6kw6f6Wc1Uk6p6y4PZy2MH7IQVaqb9xwX4kWxsxGP2Vr/2zxNMnQOxaIpS0fYX9TPy0ipNhEOifPa9unE05ZXp/Jcxp2pFWqZO/JbxKNid4WazhpNrZC3fP6tvXT+jKGOO/0al/zEedepIm2vcV8y90PTTUvaYJ2mzynv9hfN0x3ntUG48kWGFuNm46TU/zA1l+/fh0/fvy4r57O+dfX1zsvZ/mtdbTRP4UTwa3NxC/9wrsAWj69lU+9R/Wqo9t52z3zbcNNRtO2R91ut3fgP/d4BcqC5sqAnWPj3U6ygVRLiFKykfrybyY6A/zJyXgu0ZKOr+qWcnDQmvNpdtigRRnyWpqhNy+Uo49dbGdpIOOJg8/IgfSd3cc+kxwTWLMOPzN54wDUaGoB8Yret4CytUUbb8EgBa2r9FxJToaO5BOJJ4Ms70kJpvtPtKQAuF2fc4mu49hfh3Ac74P6VprczmyC9dzPYCKxjfenJ2unyQMnxZt+k10T2+njzeabnyZdntFiOkxT6od1zvwyYV/DdLa94UXiZ6N56nMA4mumb0v2Wuwd3aU+znyQfKR2071JFq1Pype+Sf5nUEHZp5UT+/hZOcOPrThXuZIDWJ6OQabfcko7HywD3k//3VadSN+Gvy2H2OR3ljttvrFda3TzHOVwHMe7wYi/iaeDsW2Qyj7abhTev62CN17YvgfSrWw5afOThvtJfpRjGii1/CXh1hV8PivJ9olxMzidQalXT0fHr6+vd9ma1yt+3crmEy1+bv5iXWy2kMqnBqrufMoVoExJxRbwt+Dy8PBwVxRXSqYeP21LmpOtaccz1e7fsxZjXPMuQBp22q/P4pmGBiZTrgBrSgzaTPu09XcM2QbIhGK+Rz7bjE9b7WM/DPSJT9NE3hpQs7REi3I0CHgwkNpPYJj4c1+cyfQ9pDe9moQ2kgb/BnYDsWlNMmWikniY+2zb2ycV0+Mk4UpiyfsTPy34nrVNuU6wcMCY/mYFkvrkf4Za0BzfTdueLDvWGR/ko+YbDwl/UtBJsqdNtcDTfJJ8p5eTz7Ena9xWOu+VnjShaB1xFp4JFh+sxPOJJrfL/pIsUmKVkkfqOsmZckh6I4Ymec0582aajflsN2FA8l9jXOon9d+w88y+jyM/EC8ldlsMaivlKQZwsoarInx/fMPdFjM2Prf3qLqdK307diSMIe+MS8lH2R8nHazbFscS3llnaaWTNAwmJptMcWjqkMeUc1wpyVbsQ2lQebv9ntjjg93Siun47exua6tWtlfnl6MjPzSRT59PxW1ysPyZQYltItHn+32uLQAlPacYSzk0PtleumeL1W4r5SYzGH15eTleXl7eraJS/1dyn60kmhIGNTtI8k/8pPzzM7T/j71HNS31p3LVyRvgua1J+sZB+d9Vbk30cUom0zbKRBMNLwE/V3j9eokUIPj04iQ3AmaSTwtQdJihgd8psfmM3lLQSGUzzpZspDbPgMQg30DCQTAlTGnrYQObq7pIPHLwYrkkMHAim4LNlLGp9MRSy+/MdnxPm2X8bBBPbdsuW/vU1dSjPDa7SnbUAJfHaaZ6+uT5FiRTAsb2TR/17aQs+caXL1/uk2bbDhHzx/vSypdtbuxq+B5am98m+ZqWlNCcydG8J3ob383m0v3UsWlrekw463r8nWw+ycN4lPx02+7c+PegxPU2Wpqt8N7mx0l+ltNn6GJJkykbRrdEzZOZZ/HyOPL/c9m+sfw4fk/atJL6S7Ej1Rs+3HdqO62CEWeph4YjjS7Lzt/eYcHzM+A0bylG2/9M5xbLqe+0GyPF5qa35AekiboxvpOG9v71tJq65VxnO25SjDI2u/0UDxs+tb74vY03Gj42ezKdqR2v2jt2no1vmrxZp+UHSU4zUE0PSWI+Z1vf+E/0bfcdR/4rUIpTKX+x7Bq+XimfHqg6OG0G2gLM5txbYjHH/D0D1OP4z4Dv58+f7/4Lwj33/J9D6jcFiS15sVy833zOOZgnMPeK7pnTmY6WfPi39be1SRoT+Ps7AcHWls83OiwvrzimAEua2kCu9dPaZrtnEzKpbQdfO3jyiTMwbjwdR36h99xvkNmCCW2dtNLuSQdtPA2WNpltAS3JhXQYe5wIkPapm/5/kuihHNmW+9x2QFBu9hdjZpJlm3iwPtMuklasJ/fLHSvzGVqSzhr2n9GS5LHdZxrJM20uJQSN7nZ/8yHf39qc+5KftfjIkmSW5L/tBnI72woU77cNt/NJ/g0P5lyi4Uw/U7hrh3QludgmU5xy2fSYsDzJ7cqD5nx+iymbvpKPbXy1gWqL7zzeYgVpadd4nHyegxTiqzEoyT/R2OTV7GIwNvHj40SPS4qB1hEnEJLMnJNYb1PSKhtlkXIcFrc954yBpNO74pq8TWvqe74pU9N0thtgw3IWtuP/QHOM4NXrFqtaPOfunLa7w3Ry9ZSD1JRnuGzXzmIscxTKibEr2UiTMek5w9ytXB6o+o/QY+hMnkhY2zJC4zib+Z5CwdrBHXxnq42B20Y4TwZ+fn7+MMB0fy0I8GOQ4yCB7+lsqxMpeHow1MDlDCgH+M/uc50mZ8p6+z/Ew8PD8fT0dNxut+Pl5eU4juOdbCwH8vPw8PsBLYmOceY5TgP8lGBsgXL4aokMr/G/dklWDUjdJgv5eHj4vcrf2uC5pKcGaskf/D/vBIotYLMvAtkkay3wNdros8Pf4It9yDxz9wH1mBIzP6iIyaXrpiBHAE+BdbMB44wDmfvzuZRcNYxNMnNJyRcn+Aa/np6e3tXxBFvzry1B4f2k8SyoWj6ehW94aflZJqOHeS9d2pHAekxWz/ppq9xu27t+HEvPZMHt1MlPtsTROkj901dSjJzrTuRJy8jVTypNdNm/UmLvGEx8Tvozz/6mjm0nc7z9vYfned0DLvO5+Qtxs+VXlnWTD/loPBLDU+7mvxWlWGy6eb/pbXZJ+c3/ftOkYMI6xuiXl5eKL/6Yx7TK1h4QNHxRx2cYzAfobLt20qRZ2vlF+5i3UqT3TjOPJ4YO34+Pv4cJc097v/SmV/PA4vhjvNxWO1vcaL6f7Drplseja2679d93khxcf+7hQ5C8Qkr/tq/TlqiT6cd1ed2+1SbVz3zRdnIWpxyT5/hqXnAcnxioUmhTCKocfCRDdDtW6tRNhLcAsyU1Fo7/0zr3cUuF20/9+diCZx0nTtN/cywaCfuxMyT5NPA7u5Z4S79dZ3R+ZTuCz7v9dF+610GVdGxGn5Kos0Qg2VwLHNTdcZw/dKD1O8Ug0Jy62Xu6bnmkb/NM4Jv7DDaUJeXB7UVbwpTomuMG/PaRDeTNV7KFRtuZvs/KhiVX22++n+pbLynJarbpRGHqeqLB71J0f/ObNDVdpH55znwex/snwFq2qQ/HmFRSHxw8bYMd+86Gt1tJtrL559U+UpIwv+nbvtd9sL4HX+3TEvwUMxONqTh+b3h3Fg+aLhO+Ndo2PElxfr49YLOdfjZGJbr47TYbL1fONd4tpyaLoaEtWniF7jjeT5w7LrH9RKOxwcekyXLloIlyTLJtq4xT5j5iMNtwDHAOTRlRj5NXGqdoYzMY80CVPu1Y74G16fP7WclPwmfy2eL/me0kH/M9lrX74r1pkcq0MgZwEiE9Z8IxcWzBeYkHvi3nMJ9Ntmm81XCwyd+2uk1+8P424LWdX8H3Vj619TclrnPNQGtAnN8cMDYDTIGZ5zdmHcSa8DloZULWHJRtuv2UAMw9HshsM54GFc54NbDdgstZ0tTaODMoOi8fNrI9Ipt0nw3kDH5XyllSYlAiPZ6xaoCV6lAWqc/5nWzKtDReGuA0fn1fGwD4P4b2rzST53a4HcnySeDUApRtwv67rVh5NdKveKD+/bcAB2EGjrZawyDjvlKCYr5tXw58zf7OziWeZ3cJ5ZySxoR9s5Jqm+dqMusnHTUsZJ2zlQbLnjstkqyTPs4whzr3rPm20j1tc3JpeEvYcxaojZttl0NrJyVurW/L9Yy+tMKU2k4DWfLmxG3odXKU8DHFXOcklAHvZW7iJGy+KbMm203m24p5yk3Syirptj0k+0s5iHViWfgBTBtfqVjmXjmkHDb8JxZPoX2kGJRWFJ07zS42xrKzCUzz7pjcFhocQ9wXfZb+Y9/wQ3JYZ1ZEWYd9pR0J/HjykXbXdjEkH0uTeC4PDx9f2+gc0O3yvnm1JPk3386jRjekwav9yQ7nwx0YfPesdWq9Jts5jo8rntaTV6RNl9tK9jnFOceGEwnz/D0yY0xwPpT0aRw09prmDXtcLg9U/+u//uvDExCP4/cMe1JamjlKhjelJXJzn8HPwkpOwGIHmvZmiyVBzryQ5k0BPMdE2C9DNrizzhh12zaZaErtzf1tm8+UNkPutpJMncQ6gPGeJFM7SCsGm0kOU1vkq/Fnmvw7AX4KPnQ4f5NmB7k5bxo3n0jyd0l9n/lbCjbk3TJl2xvIXqHZ9JnOqeugQTAdG2+TJExMbaNJFvwkXiapGBzkVrSkrw2brtyXPr62ydbnPIt8HO99hNcpUw7I0sQCg5x1e7vd7k+SpI2SHg4eSC8T14T5CTcsl/Z+yiTLNPmWBolzzGcbJN4TLpu/FGtG/lvb5qG1k/qfvo/jo1+7mB/biQcqyY/tfynpa/w1Xm2TPE+/Jx2mJyXclqXpc6FM0iCXeUeSIWNQir1n/Se/aXXN16b3jQ73P/zwHfbJFpiPTI4zeqC/Jd9rtKVVe+rek4/JZ/jNwZxlyVhufZN2Y5b9h3rnwgljlTGSdbzocbvdPmzTtf5SnS1PJ8/DH3XofrZ2LO8pjAv0gzRhTLqT/nhMmREbnDMwhnOQ2v7WZj9NmJsmSfwXhzTYP8uV3B95JW3Du/GVstv6aTHeOEb6W+xpsfAz5fJA9Y8//rg/herLly81MTShG/Fm7jjyqD/d1+psxY6QgoZnchJfia6kFCrQCZ6PLRsalletXMdG0BLdJC+Drelye1v7qZ+UbNgmqBcDkWXfQKkVA71B2YHhOD7O2JnPs8Bp+21Oa7mclZSMnAGbAZs8tnantAEs7aMlgb7Oc/xu59xesxMGnTOdEGhNm5PWtqrPhIoPPLD9J7/YJgTa7+ZfDScb3yzpIS9MlMYnRgbUD3Es4ZWxI9k7i30zXSdmzz1OOHm8yW+T0XyYTLSVmIQPttGzoLwlOk7uKCve1/j2PanvhsmtDcaKRGfrM/lXwlHSn3Da/bhPx0JjTqNnSpu88nHrtw3MaAtznGIS8SzpI9nYlXJFdseRdx20Pszjw8Pvwd08/4M71dh2evYE/6+cVgrp7ynnSnzN95af8Nh63PRpOaQBIGNN8qFpm4NA2ol5TT7X/NC6cmH7qQ+vCFJP5mvzk5TrOC9K56mvLc+wLlK7Xt1LMZyYPxPQxn/37f6OI0/Stf/ibxPimz7bddJwlnOctWt7b7nQ1ofl40nFMx5ZLg9U/8//+T/Hr1//ea/PX3/9dX/x7Ovr6/1BOWcGm45d7Dj+3hS0AXir69n6AdwGTE1pdnK2w2MOCj0jPcnhHPspxXPsgWUqpLM9JZTtke4ryQaT9OTQll0CxhY4DPyUlUHBCU8aYMw94yjuuyXPbauDi+WVEjA6tOW/8e3+edz0lILjZs9bOw2gGEx8zfel67xm3SSw9MCoBW320+wh1bWvtK0pbJc+kPh1gnQ2mL6ir63edo5tEOvSPbZX7qBJOHemj8ZLwslk95QfZ7+HF7bbZNcGnAkDjHXWWZppZklJNX3G8poHVDmAmzbKm/aZ/PRKEkD9NCx0wpwmX90WZ/PdzrZClrB++mw8brx78MDBK21q4i7tqiXD0y5td2K1bXjDYus6yT7x5HMpUWd7TiQ9AUAeuJMs+cbww7zBb1X4+vXruxVV8jptOJGmXYx/M8dIK96k/zg+Phjv7e3tAz9NrqRxcq7Rp1dLN7uY9qb+1DGttm/buldjqSPKcVY1z/yDfND/0k470+XrI5fhIz1QiTyy/hb7zuqQP8eEuY/f014qrOu/dtAOW8wwXQlfeOyBquWQdLcNXpNeeZ02Qrsylm/5G2Og+3Z/KefhPVwAnGOOO66UywPVb9++3UH9OI77a2AoqC3JS0Gbx1T6MLg5THKulnik0kA99ev7NtBsNBPkHaiG9gFXG9QA1XG832LUeOCxky0COwfB/pj2Jr+UALiOj89mrs1XM+Yzu7CzeaV0S844s51skn0l+reA5gRr+poAu63EJLBKftUSoGQLTY6WH/lpiRP7a4lUkmmTsdtNMqcNUncOQKTLfTJ4Nb7JP2dFufLY7C/5omViLGzFdZseLLN0nfJLtFN+ll1adbDOr+Dw2USZ5efJpqv9+X7rJt2XAm/TmevaNzmz70GU41eLQ8SMJMtE51aS3Z3FUE90tFiXZGp7Iq1ndCQ/8nWW5JOJ/4Sj/CYtvj/F4hYvW5w1b2clxaHW7nZfmxC3DBLWckDH5PPh4eP/KRMN9ue05XKbALc8aDPNtpI8yFP62HamnaRz8srE3H1tcmEcM50pllzdlZB2oCT/TZiTZOUJdtsv63PFOGGw+6D82/95/X0WCxI2bANVx+rU1/wemXg3BO+xDad4meIO7Trhasulm4zT7ySrhkebXbjQpjmhZ71eKZcHqv/rf/2v+9bfp6en4+fPn8fLy8vx48ePe+fzv63X19cPxFuxZMZObiB1aYkDHdj3uaR6Z/SYD9NEoDmO9zNw3i5BHh8e3v9Xw0Fj7uNx276XgIzJt2dDPdnQZMXCARVn+tw/dTHX2+yoi2lKwG6Zp08CG+rsLDFw8EnAsq2+ecXe7c7/2yhHBsE0y5hsaPrjN4+37SszQZJAxzJsvG6+MufpVylhct9b2+nclLH5eQS8V+EsQ/LKybYmS8rU8kirbVti0XjYkgbTtcnC97h4kGhZsC8nEmMzfjpwC/itDN3+X1ji1fFjzm2JD23Mqw8NE4wZyfda37Sf8S/yxRUftzv8JVxuWGZc8YqNaUvycRK0JTfUgRMn41FKgDxpRNnQt5I+Ujvp2LSPHkwvaeDzIVKe4nsdp0n3VpfntqTQ9Y/j44O7Wj7B9p07MPbzVX1pJ5l9YOqmgWrDGOuCsppV05eXl/uqNnH76lNlTfMcb7Fz5GmZOK+hHDfcdnxLPG/nPeGfbMS4amylrsZOUmwdjEmyTPGb7T48/H5ljWlkfud4t2HtFNrl2FnKKYwFZ3mYj+f+9NedRnfz1cEUytkropbfHBsrvZLb9NtsKvWZ5HPWZrKvJNvkV57seXx8fPdxznelfGqgOgzPDMTr6+vx48eP46+//jr++c9/Hq+vr8eff/55vLy8HK+vrx8Ch0HcTs3r47RO8JOxt8C4FRqOFcr2EjAyqbByvYd/SlrK5yB1FPfr16+7k1J209c4AUFx2nl8fHz3YI8p3kqS6GbZAg6Typaw0dm4usWte27zMzSQZtej3Uw5m3lMfdKJ5rit2rkPB5LpLyV3KalkEDUNBoQklwSspoFtpcGV20sytG8kXtyXfb4FIPefEg62exy/E5/X19d3A9XRU5I5fXn6azOqKRBaFi1QtmDVivne+rC+zpK51l+jOdHOJJW4meS12czfKY4J016z75YYsJ4nFT8TS6a9lAyQJuI3k1L/Zy8NOEgz7zOfXLVNcnOxjFIS5v7MM2lzoup7jUUp9rc67bxjzVmhv1PWqf8mY+cAiU5POHpSKNlw+m378aqbc4CJz+SVcduDMq5ysI71Rbo9wZ5sg7GP+uFfJmaA+vLyUgcI018aTCb75XfSvWXhpHq+N/9rOmt9trLRycl/P5V2i4tbbGt23OhKmOP8pC0MnWG9bZNbx2mbxNbjON6ttPshi4lP00MeHfe3ydUze2h5Vqrf7JZ5f8u9GsaaL+cFHkskHpJsWiGd9CnzlyaxSM+VcnmgyqeJTUc/f/68O/bb29v9v6pDIP/b1Ij6O4LaDOQzxYrcaNoAJRnFXLOz0lg4i+zZu1H+XEv9sU5Kvs8+pHcDq/SbRujC//0QbKekmckk140WnjtzqpREbsUA2pIS958Gqi3xSzw0WloQYntuhzTa967Yg2XXwM+BILU3xYPtJIfGA/to8uGM/AxUkwyY8LUgmnTKAGG+6a+tPdN95T5iyZXAYZpSn2xzfvt+20/CNMriLFFMCRWvJbvebMLt+th0ud1k78OrebGMzvyjJQnESwb4xI9t07y1hMD9J9xqtmuZmR6WhLnJbxNWWqatJF7cj9tkSTbVYs0Ww90WddP4ZJtz7AmKTb+mN/FO+Xmg5dXRodu7IDgoo46TbJNtNCw3bnqi2ljN14IlfQ1fT09PH1aAKdO2EpbkysGvd4k4v9ls9UpO4fuaP2w+NHL0wLDhHietmgzM4xWeGqb6njP/nvtou1ytd1yxDDhQbc9h4afJmvw2DG95UrOxhOnJd3wPr00b3NnUVmpbTErnWiydvs9w1WXTc8IG+/iVcnmgOk/7HWN6eHi4g8Z8Xl9fjz/++OP48ePH8ePHj+Pf//73hwfutCA2CpgA7JH6xlSbYW+/U/BzoYMng2qBymWcMN3HFc7hkyuqM9B7fX19txWC22+8dWdom2DkJXaD81miMHQOGJjnVo/y5Wwt7/GgnX1S7wbmbWaINuYnq10Bn5SYbDpPq8fNvjzhYD6bLN1OupYA6IxnziSzvSlXZkpTe1vgTH7IpGb69TW+D9T8k970WHmW8cW0iuKkZ+5Ls7aJvxaQ/H01AKR+UmnBirSxjaRvDzo3+9ywNMkh0Z38IvXTVuW2xKu1ZTwf/RLrLZuEMdy14vi1JQ/sPw0KNpnRf2hDzZ/bql+Th3Ww6T/F7TObTv0n/tP1dI11PPFpHhMv1i/tIk3MtKSSsablC8Y/66e1vcUgHlPn8yCj9D9R21DC5CvFK6WWKwcRP378uE8azqA0PU07xRD+fn5+Pr5+/Xo8Pz/fV9zIowfGjv8pJqeB6t+Rx/Bt2fDa9vH9bnN4ZI639Ws9t/ZaOVtVNE/OgaY490yyoY7Hdn3v2JInoNMKaMt1+Em+f6aLqyXJy9jf5HEWN01jGk+ZL/fXeN14pr+0aw1f6Ic/f/6ME55XyuWB6r/+9a/7svwY1ADEw8PDuye9zX2zFdUANULmY6ANWBsjZ0CyJXRU3lkC5bo2OtZJ7aYg2YL19GHAfXh4ePfgKsrZT9nzLOn0wQEsg2WT3WdAthk8ZW3QS/UtB55PAxffl+jytplN9ptNuQ8PTCnbvwt45o025YTSycsmBwebBJhNBkzi0z3mL62wmUceO5lIwDttziSJ22u68XXWYfK+0duK9Wsf33DgSoBo9ROdqZ2zNr1zw3I4S6B5bvDFiZ6PN3/jICnpP/kx+W5Bssllw7CGEb6W7C71Z392IpbKpm+2yzabTTZejSscfLPfNIngiaVE/+yksSwdJ8+OTbNpoCw2GzUdST5zzoOBhHm2r6lj/ubbT6VNA4lE+3GcP6eAgy3mAp/Bpa1/FvOXYkmbHLaf+oE8psn55AxO28Q87cB5QvtOixxJN+Z56p99eB8nYk1HikVJZz42FiTcSzywJMzlyi3rmLfWdrIdTwqmHIXxacrQs70OLg3CSNsV+nzv8Eu+LTPek+TRzqV2UzsT9zwZkCYTWizbcoatb9ZtuUHyE9tgiy2tz1QuD1T/3//7f8fj4+Px/Px8fPv27Q4Y09kMTJ+fn4/n5+fj9fX1+P79+4ctHnyiW/p/QmIggeEwnX4TTKa+fztwbomUkxfXYQJiZSYAMo0JxEZuDJ7e2jOf5+fnO6h/+/btXVB0kNwCk3n1+eQUHkQmeQ1f6f50rx3IjnllsOrfDEpnTtN0z5ni9JCHtkrC+k3eA0i2Lyf+Y2sGDLZn+XIAyWPWOQvKb29vH5JP9sfgY7q8q2Dau93e/1/JGNCSf/OZAlQDwxbYXWezhxa8nOBs/nY14LOkFenhIyU/5ok2NcU+mAaYbXWOfBKPOInmLXoutuOxASYjfi2N7WTqc1tjwg/KPfmGdbHZu38337ZPtDiUZMIHKiU7t43ODhzLdMPbLSFvMSOthLm9oZ8Trm6f31x92XZ5kIa0DTLV2XxqMNF4lbB1e7BPk+F8p9VurwQ33LFO/WFO8PT0dJd9Kwkbm8xS3XTNmOgYSf/3d+tvG6jaLk1Xy+vsPy3noH48kcb7nc+kAbrzlhaTKKe0urvZ8dYeZZ2wwTwwT291+M0+Un5hfZB/vtqtYRcHqs7/zPNZTuBP8nXjfmoz4b3zJucYtKVNZ+7H321S3+2w7dZfw1fyM8dtks1Y3b5ZUmzdyuWB6v/9v//3eHx8PL59+3b88ccfx9PT0/H9+/d34MHg+u3bt3eJDZftZ+D6559/Hq+vr/f3sqZExIxyJXd+N4c+jjzTYqN0PQvejuMAlII1aW9BgO0zsKRkhLMqNJqHh4fjzz//vOvh5eXl+Pr16/Hy8vJhdXu2z5wBHelk0pH+p2yQ5nFaLZt6V4zUWy4NqgmIeG6bZSMP6XhL9NxWSqoSgDSQYp/8ZpsjS9q6g0/ji+f8/w7Ovm+J19lWIvPNdlJCOd9+uXYCOdpLAuQrYOvA5GSYNNuunXBNHa82ERvaZMKGD+mb987EVWr3y5cv91Vnvh+PT5XmvUwck1yMcWkQSH9wIs6VDz8ZNH1YqG+vqHqiKL3D1gllwh/y5r4TrvnF8GdJEeVzZWWC9skVMq+WTpuOcUysqX9+z/U0+E73j6zTvdNeSvgYo2lL9uOkdz4oZ861v5yQZ+YEpHNss9ncXG96clI7/c/1s0lg+g8nckin+2Ud+lTSUaL175S/W8+Fk1TEdb+LufVvf6KPcrKK+mA/aWtx6pcyI66mByzRBlpOseUYIxfHllTHPmJcSzJK8XH6PKtn+3MONO1YDkPX6Jn1PDFovuYe4mvD6DMZNzzl9XSOfGxY7nyj6Xm7Znt3/n+lfx8b6ylT02U5JJwwLhorjUONn0Z7Kmf5MMvlgeoMhgYEnp6e7t/Pz8/3IDMEMLk5juNe9/Hx8f4Qpqkz31+/fn2XuA6zZ6tAG8jaUK8C8ibkFJzPgsRmwCl5nW8rngkc+yVgjB64PWaShrlu2dl5WJgMkPYUUAg+LP5NsCN/TYZnAGs9nzn9BJ0kd8slJUipXzvsldIAI123vIf++d0SgM22bEeu05Ld5lcbyG7nz4JDOs9zWwJHnpKcrC/KJgVR99cC0VaoN9My3ynI3m77hMcZbjkJ86ppGqgygeMAwitrHqg6OXd/TX7JRnnMRJQrr26DHwb0kWGa5HTd6WeeIM1ZfdPFb+u4JRBnONESFR/TP4/j4+C1+XTyW2JeSn54D3+7ve1+0+FzGwY03EkxwP0lrNsGUKn+HDPHaXY05+kPniCjD9GP6Ddn+cXfLVtutOUs7fzwTH4Yp3yvv+mrc96re5TJ3O8JTw96thhnmoh3zvPSZHWL4c5tkk85l6HvOe+a723SPmFB8udtwM36pocTZ+R3i91zrvHNSYZEU5KxdcayYUC6L8nQ188G0Wxn6yddO+vf/NuXGja2kuze2OhPGqi2vlJu8xksSeVT/1H98uXL8ddffx1//vnn8fj4ePzxxx/3rb7fv38/Hh8fj+/fv9//x+qXQRNU5n+XP3/+PJ6fn+/n/vrrrw+zYi8vL9Hg2+zsWeLB+whic5xW+1IylxKd5JwcuFHxTP5ScsjXADkxsuInOZyHXr28vNxXNeZ4Jgi4fSY9hr0VBxrSahm8vb29m9jgNjDKw8DvBHZLntJMdKLZwNXOsVDP/J10TdmMjTfw3mTaACQVJzemm/dtCUhKDCZQp8QuJWROdtNstu+n7EhzCr6pPo8b2DIhTLwz+KSBxhktm82xj0TzxtcWeFubpNcyGH36P+3cQkd9JyxKts8VpjQATk9vTIU2mmTMwTHlZ9tNekurKoxJ27Zk1mcinJ5eyvdBjv3ziZSksU3iffny5V1S3mawzS/b8QTxtLMl6Y6l/KTV2YSBg3lpFYdyb9jBmGe5OO5s+JNKSrxYb3IT2hUx2zE/bWtnu7RD+hdt7jN0/v9ZjMP/E/2yjfbwn7E5+9LsuvPAxZNizA/ahCJpoP01WzyO/zw0lHjYJtemtIk+75Ajr9MHeXQuY3lSdl6NTPEp6dG+nWJzamP7Gwf1SZqS7hItaXJh4yNhgONp4mv6nHubTBNPiYcNxyzHFps2+bR+Ul/mv8kwYV86R9/wYpzL1ZzI9zYdtXJ5oDqd87+lt9t/tvTOe1Ofnp7uA88ZfHowNEbChGkC1Nvb2/H8/Pwu+M/WrvQwpmG+BdEkKILdJFhsx4m9B05WbEoWkiEyUeLKM/9/0QLlGSjxvkkY+PTgAZofP37cJxCmT76zyqBLvfN4S7ItN15zQBlaHx4e7nr2KmcKEAPylI37T7JKYJJAiX3QUVPQTbL48uXLva77YF1/b6C09bcB+QYuLSCkhOkM5KY9+uXouNHWeHcgdX+brNKAit8ESPupg3e6fhaQmqwT/01HCVfO2mZd2uvIhIkG/0fqZCwFpS3wGJ+4NdjJCttOg+Fmf+SVgT0FyeN4vxV/fJAPdEgThG2gylUNTrjdbrd7fHIbE6uIIbQ/xgPbOVcxOPGQ4kLSfUqYKUvGPPKZvqdN232bsLPd2oYSXriNjY4U368mj822U8LtwQ7t6suXL+/+L5n+NpFwIvlYK2fXP1PO/Me8Jn+4EoPSvVevj3+OP3Gg6gEoc4Yp5mfK8MI4vg06iU2jQ/pSm8AjjiTcSp/BiDRQ3eREftPgbsNt63yLKeSffc3fhTwZTp48YdDsxbGAOEcdNnlYFqSz9UdMt0+Y/3TsGGPaXCflFy3nSLhhXDHvqb1m0w17jBHMp2kHye8S3Vu+YHlfLZcHqtMBjXJmwuZ/p/OUXw4y/bAfPqmNDwEY4p+fn++zTi8vL8fLy8v9PwQpuDugXBFUGgzREDZnt1GyXgKBBApz3AaqfrIZQYL1k27mHj4p2A9bmP8aj24mefUTAx8e3v8nzf01OdOZ5z6uFjDYcGBtYHNCkWRI3lnSLNVmFynQMcjZ0a+AsPtMwHfFYbf+CL6Jv0RH65f8JWBL30z0SFuyWa/sbP7WQNf3bLymoJEw5GwCyN8paLic+UzTS+uj6d28z7ETKA/OPDlFXE7yS/Q0uXJFb67ZTpOdnSWR096Gg5atdUpZOB6ldmiHxncmbLzHQd5ynIksY0BLLPk78e3Y1+R7xa6STFvbprH5qid7pziZvcrfRqv7T/0mGuezrZzQr7gzKSVp5Nt9tXKGKVu9rV3exwEffx9Hf3XXWayd+0hL0lPDuqGDuePklowjzB1SG44ZaVV0zjnOM9/xBHWa9Bl5eVW98edcLn2SPLe2OBHoeilGmQbrJfkfMXAm6mzbibfNRlhv2rKNUcaJB9Pb+k5yTINS1zvDooRp1o+Lr6d7nSPww3vTAN10ml7jk/m0/6T7k1/T55sfpL4+Uz41UJ1CRc9Wjdly+uPHj/uK3Twd+Pv37/cB0ffv39+BvZkjSP348eN4eXk5Hh4ejtfX1/vv9HjqRONmgFOScKmUmTF/e3u7z6COkaaVPLcxA72pwySRDxxhmwPI8+HLsNl24sPJ98PDw7uB4QDrjx8/7jTMuRm8cmvwPEUwzSZeAaMBoQE5zmaN/YwcN+fbjL+Bl/VLZ3WiSHlZ1gykBqakg+TUKUFjAt/aS0BC2iaocuud++eEQeon8eBAneRu2TGh8KPkDWRJRg7c5HV8MNFAWVFmxCkG0y1gXEn4Uv/m5aykwZjpv1rsl9zW70mW4zg++BUxgnzxPicoXvGwv3kFwnZLLOJvJ3/exmpfTzHAyWRK2JysWI7mn/cSu/zxkynd98iPE4DJDlMbCduoG+K/k1jqYZs8tRzSShSTptRGwj3bIOv8ncTFPG3nPtumbSbFPccEJ64NN6/w83fKFeyiXaWHgrVE8yx/SpNP9v/j+O1PzG9mkePHjx/3PHLevZpWVJNeTJdtIOUApM8DUU/kcULK8hkcmGPHGedyHoA717lit+0e6pE5599pz9g0ecYsGnlrc4qjtqc2qX2FJ8rID4RkHnk2YGs8tuL67T/p1Llpb7ab9JTyI+esnmxnLplkns4n2bJt895kSD5avf+J8umtv42QYZAv473dbveBzu12ezcoSuDBZJPHs1o7gDHO4ieFml47GwsTYIO8HXwcwsbp+5ISeUx+vV1kS74YPJOxNL7N6/AysnNSNI44v7na4BWXlqA0+lLSxHZGHmnFa+g26KdtM1uCYQBItB/H70HRGR/+3WatWhsJ3FuA8b0sBCnacjpnGVkWZ4mKeaavUx/U0ZQNNIcPtz00XVlFa7Rbbu0cvxPeudjWLPuNzlZa8GT7bcWR+OJkkTqmnM/kNmUSFU40+T3YpKkFRtLrVYrBGU/mXRnkGF/oy0n+KdloskjBPWFRSq5TST5pGaUELd3Ltnj//J661L8xp9GY5JUGqi0J246P4/0kpjEo4ezYoOkjH4mnxOPmp8lmLV/bPHG77W5p/bk0fL5yr885nraVtIYP9qvkZ57EmEkYtzsfTurM2yDm72PzcXxvE0tN1w13UmxpcmWuRBulzZEGT36Tdn78F7bkQ4k+5yyJH/PQCnOvVm+Lb402HjNWpbLRR57oc2mg74kM0z3fSX6Jl8TPFsvsK9tEZWrb/Wz3uD/b4tVCHbeJyxRfWoxstLZzny2XB6otWbAxDrjMigpfS/P09HTcbv8ZsL69vX0YuBLwJlGZbbHTxsy8zStt+KAhJwmcGfVMAc9fMYopTNjm/mRgDsjzTd64kjp9efA9MmjGSD7Ms+lIoGrZeUV1VsrT4L0lKG2rjGmeOuRxeGAy8Pb29s6OGMQa2FEvV0HGANuCXlqpG5mcgU1K8DZgNcAm2l03tbPJKPFKvzaoOSg4ofBMJ+l14tsSpG1FqfExbV4F7pQct3vOiu3n6v22gWTT1mUbfDFRpA+yz7MBVKKBPk2b8OCsJTiWic+lvvjgJ/+3lonw1cTg6qy1V1nSYH/4nd09k2T/+vXr+PHjxzuezhJrXku40FYIXOg/20RbasuyGJotFz/0jzRS9saTJMPUF1fc7A+MbUlXKbEyD1djgmmb9hgzRxYzgU37TKuJlvP/ZGGbxtCkH/I/9jL3pcEA61lWjvmDP85t3Da3+c5AlQNXD0Ia387FWp6aildRiW2zGDLPziAfTSabnJJfGyPSQNf6Sthp2x179Q4wfw9OnMXXKQknkw9ZDpaBZZhklnKB9OT1xLsn57Z4Y94S3SyeVDNOXc3vLM9kswkD7RPjb6Zhrg29zhmcuzXdG1OdW7U8ucn+75bLA9Xn5+d7hwbwRMjtdns3iPTTaJ+fn+9bg//44493//cYAJkB7bwKhwOW2R5isPM5/l+2vcpgSkoEyWNKGlLgbm07OZ32nMwfx8cHgrCdOe+VEdbnNwev7ptBysnnOEEyMho65TR1vBpC+rfgR/lQBpZxA3s6kds5jvwwHdLhVT/bgoM/v00fi/3G/Vu/piXd34DNJQUT227i1Xbpgegmk2SbBM0N3Mh3m+1znRQ0k8x5r/2x3ZdknHR4lgAzMUx6Na5SJ0ymtiSY/teCU5oAaPjhRJSDgqRv03Qc/X1pxiLyPQMT7qbhgNUytRzPMJ70WX5pEtK4y4SJg/WzpCPp3bbodlJd028Z2C/s5/bBkfkU3kPde7DaVjSS3yf9p2PqIPmjMcSl8Wq7mW9jFY+N6yk+tQnZGeQkHdjftuIYla6ffcy3J/ETvnPCkXVT3KROOPhLWzPTf1DTBLRtyjJwrGwTS7Q/r/4OP9NX0k3C+oT5rp90087Rz1mMQcnOUt0rvjEYa1rn2PHEE6At3vHTJk689Zx1G574f9UtbpMW8pJ0x29ilts5izFX5O3zxjLb43F8/D+tj6371k/jZauX4shxfHx/dpo432SxxedWPr2iehx5wJaIoEHxgUjzqpRfv37dZ8xHKExKprCdedjSt2/f7mA3bfF/DjNofXl5eSfMbTangcDwNfXTfVOSEhjUODPspCTJ9CwxSbNHqf+WDHmGiAPXSRQ3PhlYDGzcrk0eaD8JhJ3oJP4pAwKHB6VuL8nGfThJo91ztYJgwn6ugGf67cCabOMziU27ZptyEmc+6H8pgUkz9wbWFChcUhC9wm+yi9RfClBntNEmk3ysb9PsRGTsx5NHTS70Cz8Aqd3XEoj53vSUEhXadkogXDcFYdNhmkzLyGiSVw9U2b7bc3DfsN7BmNd8zjLwFj7rItGWkgbaF+PEhv/J5o3zzUbS/6xs57Yh4iInL+c844AfjOd2TfcZf01H5t20m14/tb3JktiefP84Pm6ptU84LnOSp7V5Vtp9KeFvfKa8xXRz4uVsoOq2vZrPdnjMb59zP2fysa6d+PN4/GvuabEhYVO7N/kR22n62fhK7RlXrtRP7fkc7dI4Rpl6V0uLM8SA5BfWvXHV562HM95ZruYc/L1hTMP7VHfDLA/2Wp4x2JraTT6YeEl1jJdNNi02JntsJengqv6mXB6oOlllYGzCG9Ai2M0M+WyXmocsEdgtHD+Z0cIeB5unBL+8vBx//fXXfYvwDGDTn/QdWCzIFPxakrA5xfTFoD7tMimx/FLSYdnPvbN9dvpLtDiAstjwEk1zPgF4a8tyG9qTszoJmrb9VOTZBkz7coIwn2RbpNOF8nVbyeZZh79Tu0lOqbREz/Va/ePINjBteaDUtoAkvkhTWvE0nSk4sm6rdxzH8fj4+IGOzd8SEPN8Cx7Jp01Pk419Od1PmV8JDNssNh/Ek/zZdjnfm7wT78MbJ6+a/8yzCOjPnqRKgZ74zR0vM0FmPGTbIwueNw9nciZdrDd4yntaEsV2/ZCkhKn8dtuMB16t9ODIxbHKGJueUJsmEjzwIi3DI3VCm6ZdOj4126GNEVs2vdqW7IdXZ/mTTm6327vJ8yTvJmO2MZPzx/H+4VkpDk2dluCf+W2Lty1nmvf98gFgM+GfBhKJVtosY3fqs7WdBidph9lxfHyv8PzmQynTZF6KFSmeuL9Eg/2CA/NU1zg3unJMts2m37x32rZ9cJWUNuZziR7LnvL9zEqqJx7SVm5PhCTcsW7Ih/u1nFPsZyHvG1/mzbJze2nQZlnPd/uwOCYMLqa/VtmOWq5hmSZeNpqmJExv/ZzlY2fl0w9TSuBJAlKiNscj8JkhHyDnqucErM1wpk22+/DwcE8sGByO43fSMVuJ20yeZ4JT8DtTHvvn8WaE5scyTW0xIDUQ9qcNXFhaEmQ6WuBMTtASNQ9Kxz6aA7AtAnIK5ClZTIDhQhk1gGxtbH7RbCKVxMtZotLqMKi6f4O6k5LkA+6Psk12Y12m5GErzT/GVhIQOlHycaLHPLuc6bTR7PNOIBM94xuezbbPb4HoOPJTj5Nvmi+3k3jjMX2MPpoSxrTizIduDR7z2hQmxZRTkmuzLWIR5ZgGZ6+vrzGZsy34HsqANLYEwHg69RyrSEOa0TeftjPHZmLtYCplPjP5Tr7SANK47snOFP+S7zoGW5eu48lm6t/82l9asmScGZ4tA/tk0mtqP/GTfHWbBLyq8yQv5jvbcx+o4xRfkryJ0+TNA1XScoZPxBM/1NHP1Gi7Thzjto/5vIKRW9zY4pyxwvHO923F+Q19MK3aJftKEwEt7x2bbZMNzqvbimnKJSy/TY7GotRusivy50kW1mFbyR8ajlyJ0bwvDXJJq2lJuepmI5utJttLuUrLHxpvrTRsbOXyQHXekZoA9TjeG+sQkLZEjEEMQN5ut/sDKKbdmflN2zimrbRVkQPTh4eH+yzb8/NzfIrc7Xa7Px6d24XT/nkrbpshJr1nifokJG0GMIF1CoaWxRx7MM7kftp0nQ0YzIvpHluYj3kgL3bisYs0gJ0y9Ti76sBOWcw3QZDfLkPzTKa8vf1nq3q7v8msya7xxbYaSLZ7r9LTksW0UpbkSZlbj3Odep/7km232fpmXz5POVlG7XjTu2W3tWUbajjgc/Thdh8DJ2ezvavEPJn2zS543UHoLDlOgSv5dsIr9znf8/eNL1++3B+qknZJWL6pz1YGM0wX+abtTrKV7k94nuijLv2gneM4Is7NyhvjbVqJSjI4KxykTF3SN/KeuEwebBfkxfY8uyBMX0p4UuwhNthn6e9t0JGwptFBXrZ47tL0uk1EOZmmTlLi2krCVJ+zz9xut3fvKJ3B4zwMLOUFzaeoI78q0Hwdx/HuWSEe3CR8TfkOH67Ge+accTOt7o5PezWXtkS5JdqSzaU4ZnlRd7arlted4Rn5Sn1Qhkke1OEUxpk0CZN8NT2AywtBzd8pB9LsPozP5DXJK8UO25e3NKcciJjSYmbKtWwXiWfjm/sh1k4dj69aLuVcpcnEOGX9pwmflhucYdZZ3NzKp1ZUJ3E6jt9PcbPDUpCuexzH/b2oAzDT3l9//XX861//Op6fn4+np6d3D1jiOz3nOCVkr6+v92NuFZ0g3GYlZnD648ePd+/04lOFG9i0GVUHxRRQ2d605afQpWPXSw42vBGcOVvNNs5A3PebZvNH0Dc48DitNLRBYUpOpq2xEfKeSgL/cf6mn7e3t/vKCmWfHhLhug3YKHOXDdiaDjZeE5AnG01gm/qgbszXWcB2X1++fHm3YpYKA0UDyEmkSXfysdSOj5uPJv9vDxozHVMn/TdwrrFdBtG5tyUmaVY12daGO+bBfpvuSeftX0ObJzfmXPo9zy+YVR4PWu1fbLthG3my/RH7Nt03fyVfif/xCz6B0wMb2oNXNCxnJ3PWh8vZgMD8U2/H8f6dhTOZ4JjnAQKT40Tb8JAGLaaXyZvrpMR16vC+JjsmZi6JZstwsIsTD6TX/mgdG38TJm80JXoSrlB/k+twUGEMdZ/GeeZ61hvvsT2xH0+Qp/jE7bzpicppIaP9j3L6SQ9yGppTHCeNaQEj2UfS5dBGmzMeJL1Ths7NzoplR1poL2c4wAcnkkfml7YDysk26Rw2YRrbHpvhsUuL1QmDUs6e2ko5BelOuVrzh1RSHrbF04QPsyuVejW/W7Hsxzcti/Y7teX7bAOJt7Py6YEqQZVKmXtI3IAgCWVdDl5//vx5fP369f4f1re3t/vAdL6nv/R/DyqN5znjy//o2Lje3t6O5+fne/+zwvr169e4LdgOZjBIAJ+AhvTMObfHpyGnQORvgwlnXhLAznmCt2fCeL9pMIBZrhutluOA0aanpINk+Fed4wxoabNTHDha8CCfV5w+JWmtvVboX00uTRZnyZHvtf5dx3pufDRZNLpcknwTrdt1J7iNlunvihwtl7MJp61dBlD7ha+775Q4NH1sujiTo2my/7eVq5kEpWw4sKePsc0zui2HlEwkfydtPHdmZ75u7GCi3lY70vGZbVDGiXfHYH63VSTLzPQMPxOjJimeyWReNw1stw16KDPXcTxrvpIKB6/W+SbXhuHMddxGwgHytenS/plyhUZ/knPCiqHDfBmnzLvtgH6S/Cj1Yxps3/7v6Zz3QHTa4rU0+HPOYDmRvharN3uhjEZ2pCHRzUF368v+eYY/1o8/lsNgkuOF+fUnTRbZN7f8hf1TBsZMttOwKuURTdfGprO8wO36d7ONrWw4/pl6Z/Eo0cu20nE7dyUHs6yv2MCV8qmtv9PovC6Gj+efQYaNmMWDublvtv6OsT48PBz//Oc/7wD1/fv34+np6fj+/fsduJKhv739fr/ZPNyDr0jhqluawfr+/fvx69ev4x//+Me7bTEzw88nDA+fZ4PJ6W94ndU5O0Ay8JSwbLPsTfFtptSgQn06KUx1p+2ZoSUfyXkt7wnuDk5pQN4CH2WyTRi0oHocvweqtGl+p+Sp6YvfPk4zVSl5aGCb2t/6b0DjAOCEobVncE7AleyfdRgsUnspIKT2Nj2kcuYjLYljfR8zKXEQTH3TLtN9bNt92Aa3hNA82M99PeGMZeQVqibHZKtO1uabq26T1M2E5ExWDu5uvjj80KbOArllktqcuv6+WizrqZ9wYORD+RInk65tc5S9+2wrQYleloT/vH9o8ANXJgZ7RYe0EnfTzhTySb42Pq7gJHml/j8bV6cdT8jbDmn3G5Z5Aqb1Pfz7v3+s69g4/Y9fcfLHk1gJnxzHZ7GA8uMkt3OHNHlG3tJ/zdPqqFftXSwvTyZ7Mr7lYQ1fR24NC4bO2Y48342XZNtD22zBZ37rlWjSnDCbbdM2x37se/573LRj+ZxNltp2tlyEPA6NXFwaWrnFONmSj3muxfR0j3OUtrKaFujcrvttuWGSS6Ld8rfs07Ex0RMlU2yPV0rKbRIt/91yeaA6Az8aOp1+/t85hmUH2AZwVsQEsXHqt7e3+yqn/zTv2ba5N21FMrAZJEgj6w5f3I7mgbgVZYMc0Bj5EehofJ4xGpoppzRY5bHlnGZMed9ctxyn31SPNI9sZ2vY6M+ruVM8W+cEriW61puDsR2MoOfrDrxMOGZLjAN6Cl4bSDRHbYl2KqZ7A1YGhDNfo92n+xncfO4qraSR+mc7KeA3mlqfje4UJFrit/G50ZESr6QzJn8pEUx8TX0nDF592uRxpbREx/wlHhvfKVhTnuNb3Lpku2kD6xQ3TMf8bj7rj/HOtCR/YJ9JZsnmGT8bbwmj/DE9SfbTnwdSqU+fu1qmTWMabZbPHWi62f7L5jqmtWEVv01z6iPJMq26JNvgtRSD3K75OZMvfzO/GtmZjzQ5QHq4Qy3VbxjZ/MgDwjYBlPzL8iadXh1NOxBsd6Yr/aVp7m0lyWDTCc87P+UEDvna+rCMyH+KlxuetFxl05116HocpDWfbCXZwsgu+cjwP/fz//Spv1Q/+dlZrEzxp8WChDcpD2nHlEOjt9VL7W7xcaN369eYmMZ0Z/yf8dHK5YHq8/PzHQCn0KCfnp7evTLkdrvdB6988bUZoDGQeBru6+vruxlaHvPcbBOmURvYNsOdetPm29vb/fvp6em+uupVtykJvAzAkzj4Pg6SxmC8UjyD9G3gvzlRMwyCAQNd4sX9TRLCVfWhMc3UHcdxXxmZNjwrSz15lp5Avz2prSUbKQmk7Nj+yN0z1y0omA8nAQ6mKVC2xNO64DFpbyCWQIh2YptJ+nb/iXbaOoNaAs3PFuvXbTkQpz5SAEvnPgOuKcgyKZm20+xla9P8pOTPck0ycZKabMC/iZ8twNuv0i4Xtzs0Wy9pwskJlHVr3KUOKfOUMDvhOksKriYmx5G3zJFG908Zb8mGbTL5bsILnz9LHsw7S0pCyLf7HfwjVjfZ8UGNTSamw7phzLzCl2Wa4k6SrWU4dpbkxFiSVpWbHSX8or1yhWliDH1v4nJagZxzw7+fE5Dw8DiOdzlBkmOKk37Y0laSPBy7OcgjDZQLc47J00iXfcQ8b30nfCN/vtdtuP70lfDdckj0JjxzXkHaZhI+1UmD+jTwN6ZRD02WpIX9W/dJbnPdeUXCp4QxiQbe4zYSNhubzmzIck+Yk+jfrpkHy6/FMuc4pp08bvFrxlhzPHjgnN38NPknPlv51H9U/edsXhuQIijMIPWvv/66D+rmCXMUCp3B701k8CFIPT8/H4+Pj/fvL1++3LfuTtscQHmWKwX0xLODDh+YYAUn4xl6k9KTUXCFYeoO3fM/3rZKaJBtfE2fc31LClId1vUkAYMFgyk/fIfbtlpJ2cwxAyxn9Zy88AFac64lz6w3sp0Z58R3AwMGy9kizne9ekt1Wg0zqCQQSPQ0INoSvQ3MU9BIPKcARZpo682+aION1vS7AWACwiaH5CdbYnWW4Gzbu9j+GfY4AUtJhTEnBept1SD52tjcVmxvnnxrQZU+y/v8neokPz2Oa69QGP/z7ogZPFiGjQ+eT7Ke/jb7aed5ne0YJ0zn0J8GQmzHJa3op6Ss8e5z/J62yAOfLGoamsxTvGk003YnTqQ6jjMNQwd30wP/kgyaLPiEZX9SMt7k4ETXdpbkxrYY29zHWR6T7CoVvse9ybphGHOh9O28hu1zl1uaHOfkP2VhGTFH5K685+fn++KIYyIHTyxNT0OPH1Bk2adJ+2R/1CH5O4unlMPo7Xb7/ZcLT7ZTtsZxt8v2t/5tI36qOXlpMeSsnPnWdu6snbP6W96Y4kDzebdnejgR5li25Wduc+PTvwfTnWecYQTrf6ZcHqg24B7wG2Onsw2AfP369b4aeRy/X0eQHDTN+BzH+5mOh4eHd6u0b29v96dF0gE4WPFA1QnO8JicwskSC+lOSaPpvzKDb5mnJJd0JyBLs7dn/aXf5NE0OLjz/2ZMnAx2nonhCo6da2TG87YNr8T4HgbiLQGgnFpATw7sPvlf5pEFnyC9yfVMFzzfAPAsmUz2k+7nREm6Z6O/2Uvjx4Md083fpNtA3H4n2pIsyFcLDC34JZk5GW0BIsnE38m2meBdTRamODnc6iTdt/NJ10mmjWcet37md/prR7MZ4uk2c9z8nG1tyeIZr76eEhjH0mbXnKxL9Cf+UnF8JT1nfKf+W1/mu7X3d4r55vdZvXavk2bGK/dF2Sc5Wn6bbE1fwwO3m/BsSuoj3ee3AzB3cZ0Nn01/yn0ab5YbcwDa/nza8zXsR0ObcwFOfFEvky9yR1vKHUnvtH+7/R6UUgZtlTLln8lmbH+WWcMu/2Y77M90Uv7c+dB8q9lHwqiU2yU7S3Fw6+fMxl0SBm/1/y5WeVV4jlsfScYtFmw00X5SXnSW36T+zuKF20jx/Wq5PFD98ePHfRvsDAxni+w8nc1ONcDx559/3l/58q9//et4fX09/vrrr/ufxQk4Zm7KJH8DDgNOt9vtvnJ6HP95RQ2TF9LF2TJeHyBi36MEbvMd0OGWEp63gXOGoymsFcqSMtrqM0jxv7zb6k4rVxMmgrnlTPpnO9LDw+9JBoJuW+0072k7TnoMu9saehMoJKdNgX87x8KA+ePHj/vK6rz+6PX19f7h/51TwL6ayKXgzjopwHqGnby7TkuAUsKfQN/neY2zqFuQaPbr9pteEg0t6TAWbQPQFnA2OtqMYsOLJDvbTSqJhrPksAX6pPuRCVeORl7u3wPJllCTznTMwQOxPMnaOzAmeXRSm+RhuaZgfoV2/p4JPCaB9nNj31lh26Yz0XIc/TkHTpxb/8ZB97vZjGOZbc920RK2FFMpi01fyb5Zn7+NK2kCmdcnnp35Xtpyy3fQmg6Xs7i0xSjSm/gnrnD1j/JKeqafD43mw7hvHGsDleTHxsGEh/SDNhn69vYW8wfnF1uekWQ4v7k4kwbTze6so4eHhw9Yy7ItTDQ/TbjDz9DufDflhanf9Nc78+lPk0uSh4+9RZ39UC++Pm2keJDiF6+fxQufM74n/7ZMNjxP/TC+sNhHpp5zm7Z7YX7zDR3G3YZ7V/MWl8sD1XmQ0AiWq2HpiWzj/H5Iwqx8kniCFd/tdAay08bQ9PLy8gGcOQDlOSY6nC2zgpzccPaOMtkA8jjeD1rt1MnJW6KTEksWGs4kRNz+3IKLSwKM5DSjZ66gelZyvkeu8zJ79sOtYU5QU5I6bTqJINB4JrVNhKRkhMnG1E//iXViQDpvt9ud11+/fh3Pz8/Hr1+/jpeXl/vAlf/jvgJcm85YUjAyCKVV93aveU2ys32n8+aRwGa7MfBugdVysz6oF8rSskjBgPdwwEr7MB1nk26UefLpKyCeZMEyNuwg1/RkuZwF6W2QQv+x7Bq+sz3SZgyyjXrCxTRSFtTLYMKWLFnepG1+2/aSHkcmaXVnm4Bx374n2Wyq53MJn12HsmuxiXmAdeO2RwepnRRXWrGtm7fUf6LHx+azYVCiwf14MOt46f6vTiInes4Gp6ndJqeZvB8eW1KbdMs6Lmxre1qx257rky94cNvoM6/2f18fDPEgdOhlO5PrmL/5Zr44k9FezEg5R5JpirXJ9iyv48iTBFf8q/k6r9sXms1Rpg2jPTE2vuOJsuQrKaf1qiXbbvZp3tpx0wfL9nuO2wSpS2qr2UHCI9sQr/GbuS1znClpIaW1m+zDfuHJr7PyqYEqt9LODNSssk6HNMwR0jxoaeqmBI+MWEhOtCgkG6GF5sDooMpV4VFWe6rc9DXAw1fVNONPMw5J0TQqJuwtSdgM28DcEkXSZ3qSQzXHnPYoPxf2y6SXg1zzRQCkfCkTrlBM2x6MbMHQfdquRhcjv+GfPHi1jW3Mfz7mydG/fv26P5hr/IfbghOgJnmbhyRv05c+Xk3cBqdnW4Ab8Np/vPtgS/jSOesoycq+n/AmBbvBOJY04LLcnDyR76SrRNvY+Rl4J/m0Qh+gT/P7LNixHdqVk7OmM+JCmgxM/tMSDA8AUoLfjrdVNscg103t2X5TbEr3OoFIs9BJjolulkRHwlMfm7+mc/dBHDTWnpUko+2eZG9JvsY2DyqabczvFAuazC1vT4okv7D+EwYlOdi2Goan/+amdlM/njxL/p3aM3a53pS26rn5L3GA+EVcSHbaeGx8+8P+uRWaE/K8h7TebrcPixktMXdsaTQS/1qMsI6aj2845dKwxhiczs2Hu15Su5aZJwZS27b7hJvOO5h7NB6tA/sm7yWdZ7G0Ydc2aLaPtJwqxXjykM7xt3lMMdrtbMV9WAf/vw5Uj+P9IGuCwOvr6/Hy8nL8+PHj/nCjp6en+8CPM9gziOWe/+M4PrwXaYzWzFOI/L9pMryWwNjA2wpuA88BLht9A4Xh04bldmmwQxNptiNuwXNoTHXtgN6yTT4ddNhHOp7/CDfHPo7/2M28h3f0nP7HwYRx6pkHDximvU1GtAHKc3hJzsqHh9HmPMDjYHna8f+i397+8wTpb9++Hd+/f3+3ouqHUG3bgm0LTSe2jbELrrLTLy0ryzGdM+i6f153ndE7+/bWceuJ7dpOzwJ1GtDyM3Sk9ty3B00u1EvSSfK1BOqeLJq6TphI25WSfMqJZaKXv+1LxGdP/KXJMtvgnKcc2kPXEu3WG2Vi7KPdJbzzhGEqZ9dbHdNjmW4xaGvT8SUVD6gaVk+fyZ+pH7ZJHlynlRZ7Nj7TfabVk5if5XPONzrMF22PE7D2VWMobb9dt6yY+I8eHc9bQt54PY73T9mfeGF7ZfEqmGXCOsZW00Re3Pb8dr+pH/exFcqOsm6TkB4YkC4PQOgfzilSHktfTLkQF0bYduI74aPltNlw8u8ZcKa+bauJV/bh2Dh6IN7fbrcPW+GZbzWcSQ+qOsPFhLvbcyZsp5aLcci8XqGF/A6mUE7mjXZjeSWM5fm2omqeOe5pg2xjgf8uOd9XYtWUTw1Up9F5X+YQNYTMwHRWjcbIhvCvX7/eByn+vyJf+zJ10syRwWFL1JKTcqbT7bSk1MDvLRwuZ6BJZ/M9CTySE10JoJaDjXb4T+2egWEKSuz7LNFKsnYC1PQ45xJYNXthPQdsg6bl4EDJawSH+e0BjHUxoD/l7e3t3dP2Zhb2y5cvH/4LciU4twDkZCPZMAGY/LXZ0NY372MbzW4oHweIVBIwNzBmSe2xnnlP/VKWTixIi20rtUM6vXLINs8CUOPN9uxAnGZPW7JluqekgapXKCjfdI/9OcnH8rcsLBfLgUkXfTTx4/43nDtLOkwHj2kn7GtosG5Yb9rf7CTJqcmWdZp8N158vOHyGW4ba63j5J8tKWP7za+tx4R7LpveU7+mrSXbrQ1jijHoao4wbW1lrvM/3il2tNhMXlt/Kda2kvyBbaZYsdk5f6fJhLRax5Ly1NaX9c2tsGmgStonn2Dyz3abDzY60j2tXpPRXEv+5snPpN+Gq1M/4SLrJbtK+GcbJe1u+8x3rmBgutfYftZmo8Nx0ViQJnFbu6Yt8TttJp+/IgPqwBM9yWfOyqdeT3Mc72eyfvz48W415vHx8fj27dvx7du34+np6fjjjz8+JCz/+Mc/7vdMQv7vf//73cNlZvZofk//bXbm6mzuBmTbtbneVhjODC4ZhB1nZDu/3VcD0xYAEv2sP9f5h2jykpLURE+if2a00qpY0hWdzdsDBtiTfJM9JFmcnb/iaPObqywPDw/3CZoG0A30+GCv0cXwPU/I9sOW2tYV09wGOZ7to02l/2l7gOEHSWxByPbE+2j3fEDbFA9gyJ/1Rpu2f6T7vQOj+XAaHKRgOHVTMGLbDp5p8Edb46sVPGkz34nvZGvUJ3e0cOdLkrXfF016bIfGkIZ36ZMSDydVU3/oSUlXSpiGlwm6ye/t69aXdbTVSfo3jVcCPnfEWC4teWk0Wj5pwL4NyNy/k6WzPn0uxZsWi5tOGQMTnSyNtjN+Hbsth0RLu06s4kQcaRxsJL0tttF32gOY/rsl4cnQlfKCZJtnD9LhsWOUZUjZ+dkjKSZ5gpe2Sv/yIMwxL8Ug0poWVUwPVyTThzmEZZPkf8WWW27La4PlvC/FwiTjdj7RypiW4h37dX5AehtuMn9KGMxdcE1+CWMtr5GZc6kUn7cczH0YQxLuJT6dM2/5iWN8WuyjnpJcSEeKp43n9GrGNrZI5dMrqgZRG+BxHPf/482raWYA+/j4eHz//v243W7HH3/8cSf+f//v/31fUZ2tkC8vL/eHzjBp4zawGdCmVQEnaC2ZS8bZQICDPJ9LTz227ChDK3qbYXByM7+9umb6kxNNPYOi65tO9mE+p12DQFutNZ0MPJaZ+6YOHURc2vYUts/v1DdtZ84R2D1xMN8MQAYb92Map970ZxBqW0ms2/SUQfNN25q6LShxoOqgnmQ3OvKg03Y7CbPtLc0iW1YubQcA67je1o6xgisMWz/zm/pKEwjpfl+n7TUfSP8fHp8k7TNAncRpBqtpy2B6qubgMXfApMQj+W6SF21u80362NPT04e2SHcLxldmdBtGOSBTX2O/0+aW6KTrqc/mUz7XbMZymN/GrBQXUxykHbF/23ajyxMzxCkOzo4j+3CKI6Yp2Y8TV19v8c1tEyudA8x9LW8gLf5LjidstjaIB9Sb5Xlmf8mWt9L80v4+5WwAk2hhXtcmWhMWeKDHvpgneqKtTXD4zRDOMdwO++KW04TVyf/mfv79ybHePKQJGxbLK2HHpl9+Uu5GuST8SO1Qd8w5brePg1HagP+v6rpuu00WJfmklXBiVWvnrN0mX8oo3ZtsJcmUbQ3PI6vmk5Sv29q+E9YmmRlvKcc0sN7kmMrfmoprYGdAPo7jvmLCVddRCI1xVlI5UJ2nok5yNP+H5f7mqW+QpyLHuW0ovC+VKwZKx3VC7kC9OQi/U18OkClQpmTD7Rvokqx4b+I/9TP6TPJhQKZjTcAgTS1wpjY2Q7ecmmx4f0toSG9KYti+7cHyPktmyKtnjelfpJkB3nxuCYu/PVBlG0zGbefNh9LEUZKbzw09W+LGkmx3zjvgnpWEbUmmDfQTzdRRCrBb/+734eH94H8GmG2gyt+Dv/MC+xm0Pj09Hc/Pz9XOSPes8g8WM4nyQ0fIAwMXz5G+K35iHhsmb3Z+ZlOtzamfdNySi42Xs75Y/8yXz5Ik03jWP3XTkifKgr6WVhtI2zaTvsXENPBJWMy2UpxN7afEb+PzrNi2Gz+cAGTbzlMos8FgruRPjtVs0PJoeUQqrS3TlewqtZ9WfrwAkXJKYvnIL70yZq77WR+MX2yb97hN/0/POnLukuwp6YR8sf3bLQ84OOGSJiTMJ9u5knMkuuY3FxHoIzwmDS3GneUI7iOtuqX47Pa2XI845VU+056KeXfZ6iVMSXyb7g3nGbPpH463G65u7ac41+rYVtMEPe34Sj425fJAlf+hc0Aao+LIfo5na+MYOwes379/vwPDABSTHr7GY969+ueff96PZ4A7CRMHsKPAWdXl4CGBTzKa43gPCnw9TxI0E8kpdgo6RAvYW1K9OREHEDb66c8zGi24JWfwTCSdlgMrznR6xnj6GB3PyszXr1/vkxEbwJrGlHA0mZIX3tccyfe3JGB4G1mOzXvFwEmevx2UKWPS6ic73m7vt2nOuaenp/u3g1eaLHFgsMySPsk/68y59tqnqyC1JTykzW2aRyehbnMLUJtPsS7bSvXdT8KA1A+D0diZVxK2PkwnkyNilld1kq/NK5a4+4UPRPMDwMyj7c6JTksshgbfkxI1XyfPbQWwFfY/pT05kg8ITHJP9tUwIWHQcXwcmKVkJPEwdS2f9IRNJt5ns/xzH8+lbXZeLTuO/7xJwDS2OJzwwpNzjb5kL8RaF9ttmhS1Plu/LaZO31++fLn/faS147oJI4gHyacSPl+JnS1uDr229/l4MYEfPiQx8edBQ5Idc4+pY3v1fQ0fz2ybdDA/Nc4lfijb4evsiaepbooJKbeaft7e3j68SWDa3CaSUp9pQoX3Mp90DmP8bzjd6OAOphabXa/lFi1WGKMS/prOhNuUQcotfG+iaQptpNlY4i+t1ruNM59qcXujl7aXYmbLd66Wv/3nhiQ4A8zMaNlo00pLAlcaxGxRe3p6Ol5fX4/n5+f7/1q/fn3/ig8bCQeYBqfpL209JU9zbKcbOkfB3LLZgPGq4SWZs6SELPHWZqVaEGJfTnJSUDPQe1Zy5Et5bIMbP0CoyWF4OHM+2tIVZ08l9cn7ybt1bRm1AGGQ31agEjhzssC0c6Dqmetmk+SV/XLl1bzZJ5hApGDY6hsTWvGWFMtveErYYr2OfMj7tOfB9jbotr0x4bUvtnZSQKdv22dTYKQMpnAS8eHh4f5/z9fX13tCQtoSb9yqxcSYT7b2bHXyZfPVfDPpKrWTguiGcUluW/kMZiccSTxewaekg41G9mX/Tff6N+3H9be+U7usN7Zlm5w6TW/u94oOzuhNcmnJV4uNDS+vlvGN5OtbcXwnziSMIGY1/PMx5dHkMm1SFk6IEwYk/E8TbbQT5m/mmXRx4qK1lfTA4xS7eV+yiaTDhtG2n2aDbsvnPVE57Y5OuLiUVgzTADLx6ElR02M5Jv23XOKszvR1BatoK2f+3/o5K2c41GJUayvlTebr6njBurHNbD6f7JA2xfOJD7bV/OMszm/l8kA1GZWvDRFcWR3wMFA1YQ1T3NY2K1R//PHHffZ+VlZ//Phx/POf/zxeXl6OP//888MgJ62CeoaNM8DmOQGs7xm+Z1UwPSzBM8ppRp9AswEBg8TmXDaYodNO0ACR7bBvJu6UWwI2/tfDvMx9tJN51ygHUnM/j5Ne0upUkp+PfX+TferHAXuujyzSYIntmYcEVKYpyYSyTwmWB6qzeu1V2M3Oz4DIuj+O9wOjKVzFcR0HYf9HqCUEQyN9LD0UgD7gCYHb7fdKQNKvd2MkOTeZsU0nQKav2aHx8Wx12CtYnDjgQ6w4mcAZ+vSQJevs7e3tPlHoJ79zQqRNviSZnSVB5rcNqOca41NKYpO+LcutNAxmcN7uudLPhvNbPPbE8JU2vPriuHFGW+LXOOlVHd/bEuKzZCdhBeu5z80HaecckCW6r+iuYfhxfHx41tV2LKtpxytt4wfGjSul5QQpxpg3+r0nbUkjj41fKXcklqSHAZ3tMHEb5MU2Rv69gkf/sJ+l2LDFfPeTBh7m0QNV5h5eHbNMz2yt+cBmp16UoozTalqSRVtYaTjXrl/BTMcG0u027H+JTn6nknTsmGQZegzj9lPO0DD/ipxTfuN+G4+TE7Cez216aeXyQJXJxiQxyTDs8JMI//XXX/ftYtz6O6ukZsACt8C+f/9+/5/UPEH43//+94cHLs32NAMeQZUOb+BvCnE7fIdoa2dLRgzOrYwcOPBrA+zUdguwBOdkSAykNDr+F/N2+73F2zNp3NrEPufYAwDPAPqYSTdlk2aVk3wSoDWQ2wIX6/JBDWP3tNv0BEH3sRX6leXiWXPezz44iJsBBu+13pp8zugfGRikEu3UE32IEx3zACDySN1SN0zKEj5N/3xI25TZLp3oa5+zgYB9mvZt2i3zJPdpM51P/pL8ZyYQfv78efz48SM+HCP9VSKtyng73MgsJfkt2DVcPEvy7DPuY5sgvFJSUpAGUWnW+6yfvxOwnQydxRTiNWPdcXzECmLrFidSQpZ4STZsP0hJ0ZbQfEZ3rJN82nSQFk/amCcOqlKbbCfxkvT2P8kz66U8Zot1DY8c63xu/CvtiHp4+P10Yg6uPLE6bXnAxcHOtkrreELafK8HJOMr1q11mHLVZCOWddI370nxJNlDmkg88x3qxxO5yacdBxpdxjvHupFni0VNj4l/TxLQDs/iSsoDeE+ThelhPsP2Nrp9fdMX2x7ZsGxYQJxPE4yWcxv8nuU1LeZsOYJl8tnyqRXVz3TohHBWbyZBmpn3eSJwGyw6KaUw5tUKx3Hct67NQHXA8vHx8d2TKvl0taFtnIuDrg14klwIfmegkc7bOZqSU1s+74QsgYN5mP6S0yV+HVhME/tszk2aLJcWtBvvXjk5jvzfwo2nLeEz75YV+/aM0pSzpxSnhGlKml11Pbfhe62L8QP6VwPU49hXQSgDg6EHk77XID3Bkat/HHyOPFIwSIHNMkqB2XKyn7Tg0vTR5DN8fnZVI7VrGpO/JxocxB4efm8BPo6PiVBb+XCbaUA+7ZnGxMMW/NwX9Zp4dPsJEzcMa4WxyX03/2ix8yyhaiXJzH43fdkn5lqbTN38hBNPjZ7GdzvXcMsy3uSyYZ9lw3ObL28xg/c1vTV+2HeS29WYx+L4bXqMN2fx3dcHL2ZxovFBHNgwlBORxhK2O/eS/jnfbMt883jo8znS5rrNDow/LQ/b5LqVZIP0WdvWWc5jDEwDSNPIv20lPZkvxhN+Nl3Zdsi/5THfxjjf02yg4TDbNY2+lza/lZSf2dY2nDmLi+6nYVuLtw0TSd8cX7HjxIPx1LHoM+VT71Ft4N8EOaA1D0ZiW1++fDmen5+Pr1+/Hn/88cf9P6h//PHHffDKGX3WPY7j/sTK5+fn+wM+/vGPf7zr89evX++eHDzbheebg9Zpk/2R5/RUTSrAzprkxz4YvJJBemCXZrcayBOQWjA8C8bJgBNPDCYzCZG2HyUw9czLFug2GZOH2S4+/fj61G/bic5setrbkrAku5aQpIkYn9t+O1E4ez9c09/IpAVG1t9s3cF/2kx8zn1OfB8eHt6t+M2W+qk3q6zplVCmf+i0/zpADg6kbdBnq0AsaQXFPG+rApRtC9bUQdpV4OMkozn24Io0MFHhsftxvda361O2qX7SadKf6ef1kbVfpZPklfowH1whpn2ND3kSNNn4hh1ntDSetzYty4lx1CvvaQks5Tk8JT1cnSRN+k28zzFl4PotJp7Frg0fhxevPLd75zvlCK5LHqyns5icEkfGAvPpXQ2OIQlr3K5jeMKttCpF/Hd7lP3cm1Z9mu2cDbSS/FJstmwZDygHTzYQJ1MbPE60NRti8QRhygeaPNm/cyJOOpA+4pR31DhuJP2bDmIj5cacIz18bfMBYqLtKvFtuRo/qI+RpxcbUgxKA2vjKPuzHZh+0r3ZcaLd8tlwL/lXuu8sZs19aXFv6pzxcbVcHqjOk0PJQHN6bv9KgWXKJA8PD/95mMdsu5s/gc/g1UBhZ5htgTT0GYTO9sF5wuCs1Mzgav6T5oA0PE3ffv8Z+UlGk5yjBRK22QK5A/FmqAbMpINt8JHoT+eo33E6O3ma4TMA0qENmi0Qpd9XZJ3aS0DdbJvttPtMI2mizJkkjNy44mnQSzJNOvKMtUGkBU/btgfOKeC0BIHgbD6b3hLYk162xQkR092CdjrHay2ZYJ3N/52EJf6IZbbTFvh8btpNdsbrruPr6ZptjrbUEqGNNveX7GC737KY89sAm7+Z/DY+t0LMsn5NnzFkzpmGK9iaaGyJQMNE1+cT97cklElk0pHxL10nzTxP2Tieb76z4bxl7bzjSkn+RptN9uuSbNY0p3ObH/pai08JM9N95CX1v/mE7cp2ML9JYxpoeaeG+Uq+u+UCpCmVFE9bjmAsnt8tjrqN1F7DONJOHiizkdVMyrb4RV5b/6m/+TbfLc9IA3B+82N+mZ9PO22lds6x7fQ2iIYR/lifDUvZf8pHrvjNhgH0v8FD+9HUbcemO/H1WfxLpfmI73GOl2R+Zvtn5dMDVb6CIBFNgfl/h/M9zHCb7tevX+/vSJ2+np+fj6enp/vq6tT3zOkEXgpjaJyVVw9U56E9c58fme7EogXTNBubgkP7TZ5aHylJYltsL9G9JWnJSVpC1X7T4R4e8jZC8snZfK90pYGqZ1o3Gh2IyC/rtH5SH6kfyj9dT4mp5e7ZQA9SzRfvI68uI9dJFNoj5RmUGii3+mwjAZKxgB/3u/mUk5/p13Usn8Ef1jFuEFRTQtFk0oLWliyNTM6CGMvW3tDpJze7vYZLyb7c58iLAxsnLfa35J9bQtns5Yy2hqs+l1ZpyF96PQvpsk2lyY/jeD8Baj9IfsLS9NVsyjow/w1vtoGq+2xJn2Xv6wm/eN0P1Ws8GmcsJ8qBuxW21VHWcxspViZ7tqxY96y0ZI0l4VhanUp5hPtpPthwOdGY8gTXY0xJtJEX47NXnUhvGwAlHpJfTjuMq4y5HkzZ5qbutJX6Mc1NDk1ftmHKhh/uHjLek4Z0jqXt+Gm2RLtwfuRBacJatuN4m2K3ZTx/10t4k2TfbL/5wOYXlBllcebrSZamw3Eo8TKy4PuAN94aXVewaavXsIE0JP0mm/+7tFweqBJQNuPl9wi4BSe3//Xr1/vrZv7666/j8fHxvh14tvlOkJ2X1tOwbVyTODw9PR2/fv26r6z+8ccf9xfXz2dedTOrrFN/SkouCGCppDoGEyflnEEb/uaYOkhGahBzX81RB2D4js0rfCR+LQ8ms5Zpcnza00wuJNA/KwbJ+WZbbYBqmgjMTR4bT7YTJ5AGAspsa5fFq54D8PS/BCQMLqbDwYO26vrHcXyY7DHdbqvNrnPldmjzlkrT6T6MC20VuvnL1qbbTwGuAfZ8OzFpOnYy3Pzc76Ce87OVmTKddr2N18lxWm3j/Z7AMKakYJXwyHSdBbh2zbojT2k3AGeC22DWerccSdPooeFJWkX3d8NH2xbbSINV09Vkk+5/eHj44HcbViZ9mPeGZ5ahv7ccY5NTw1jbEe3AGGH/bCXhe+Ox1U/0J3pabCc/qR1ire3ItDT9NfxumMq6jd+JH5OHpXcxt8lQ4/BxfHywJHWzYYjP25emfpqISau91odzVOO/j6kjLqTQN61r65QTs803tuIYnORmXGsr5Gzzdvv4GkfGf/LNnHGzBX7bZze9u37z4Q2vWkm5RVppTphP3tLkZ8JG6t3tpZiT2nadMztJsTqV1NaVelP+1ntUk9O34G2CGBRc30Fy/p92HL9nVmY7MFfmEk3T/sxEzX0z+OUDluZpxLOi+/LyEmeLpp+rJQVzA9o4I+9pAYYys7M6wLTZQvc/yYiTvY0XtpPK5uRbwGBiRCdM/W8lBZn5Tk7+2YFq6o/tb3T59yaLs3IFTB8eHj7MyE37LbhuNHOG+SrfDs7jj359Ea/TNqmvRFdKuOZ+0sYgYBmkbUUpgUwJhv029eE2TbMT0o2GlCSxTw7km36T7SQ/mT4SDWnw6/atEx4nmpIum7zSt88ln224axuzTPhJvDQ/asnCma8Nzz7fko7Ep2lqmOr75t75a4zx0ny52A/OSpoEbBjF6/Nt2/EklelMdDWdzXeyhcT3Jpd0f+pnayfZ33wbi5hH8Hfr23QlmthmmgBMsTe1y/tpW+kdzGlwQv8l1id/S32e+Y5xMJWr8bvJr+naPJ+VK/2d2ebmE/ar2+33YDPhiXFmi0OWQXq1mT9ux32bh02PZ9daSTaeeG4TGXNf8rsWr6/a7EZvut58v8Xj5mMp39nauBofLg9UbSBOyhLIE8zOHJ4zJbPCOX28vLwcj4+P9wcnPT09HcdxHM/Pz8e3b98quE8yPPd///79bjg0nnkq8b///e/j5eXl+Ouvv+4rrPN6m5eXlw8KbEkQeU0zKCyeDRzAZSJFYKOMUzAhHTaO5DBciWnboFO5kpTZRuZ3erCNgWloY2kJwlUAsr0a+JqNXnEmOmSjz/xwJnILeKaNchy7mMEo/7eZ3gnKTwOVKbTFoZftsM7tdvtgnz5mvaenp3c7I8ZXORCmPQxvHnx6RTLJsdkakyDP4rO+22mrjc0+51pa0UjybMmLE4/j+L3ldAr/c5982diUMHN0SVuivGfHR3rAnOnldxuMsDiJTolSSvCSvBPP83vkY8wlr00nbts7UWybXuVx8pImzK4G8KGPONIm1MY2ZtLWK+J8X98czy6jRFd6sN+VROk4PiaTfuex6yQc3/rgw9emTtIDdT12v21Pbr6dPp4I4fHm765jelPccm7GXVjbCmhacXNJGLutNDvO+nwqbTCSbI86pt42Hlj3im9RllxcGT8j/94p4UGzfYRx23GJODIxj/LjpG57Gm+ShW1/4zv5uge6Z3q1XTqfS3qaODwPQZ1Fo8lR0wPxEh3EljbY33yZ32d2Y99JuX+Sp2WT+rbPua2xryR7HhOTk9ym2B5pi4nXVIexdPjb4vTV8qkVVYMwE5UUHA3Yw8xc4zYBK5JJFFc/Z2vw29vbfTvwJLlMeqcPr7gyGRt6pq0vX77c/yM7fY2jMJH1wK4lYAQcG3xKapKMnbjzPhpBkzO/k7GMDknPlYmFpOvtdyoGMX7fbr+3LbLNljTSWRxAUmHAMdhZdgm0zJ8BYc5tcmyOnMDRtMy5DQw2cPb9BMNEJ+kd39xKCxBj05M0z6CnJZEcUAyd1leyhyZ3ypGyIJal4NKCRJJp8gUmPEx06OMJA5KNe0BPOSVMsN0m+/KWrTbYGTpSEnwWkJIMmy6T/DgwmnN8yMhm/+yPdswB+WB7Sh6SjpJ/Ui+bDIh94wtDg5OQ5rNNtp78PI73k07zLnMnGWmbr+VB+3p7+/3EzpQAbThm+dB2zXOru8kn+Q/vZdtJJ8wRbF9u2zI3/wmTWjw2T6Sz2ZUxbejddq0kv2uD1kSn85h0/1lO0PCgYUPi2fGIv1P9hu/0c/dHXue8cYe2YGxopV1vdrHpKb0Z40wfpiXFtyYTyzHRSZm0dhi75u94P378eDdQ9aQF20gY03KP1PeV+5KMWG/z2VY2P6YNWYbGs20ix/w4lvm+lC+0sUDCo2bztKcrtpjKp96jasUwufP/xua+lkTQkDmLZiU8PPx+OA8HqrMNeD5fv349vn//ft/ayz/qk440YzrKnqRl/itLR5lV16Fh+J3BlAelZyA/dWZGPwUbG+VmMC4O8Mkop1A/XL1KSUcK1md88rglBtziwXOWpXXpvlNAMi1bHdKYnNn2bR6T3A38qY5n3y2fJGsPfBwkW6A2YCUZmOfRx2afqU6akJkXv4/PMdCy3jb4Il+JHidRLSmxjMYfvVrR9El6Nn/w+TRQTX9jSH42cmMQ4U4E8uLgR76bf1pnDQeGbq7eJDuzTViWlpPrpoHw9M+VeNtQCqK2rWn/OI53A1b7bMIaF8s8FWOLbczyZp+UDfWQ2iA9bNeTTfYXfyd6NsxLvNqO0iRIyhs2+W2y8e8WH1noO/627hOGJppaPDgrWzzb6qQ85/Hx8Z4ftYfiTUkTTyzGP/OTfDSV5Itb24mO1N5xnD/fwf7TZJnaJuZP7pbyk+SLpHuzgyYzxwrKuu0CSP22fprcN19MvGy+4m/KaRZ+ZnGIuXbDwzlOMcW2k2wyxSP3k+7f8Paq3BIviYYUT5L9Nqx1WylXIR3OQ6/s8mny32K8eT8rlweqfrANO00J79xrB0tJV9vKchxHnNU9juMdGA8Qf/v27T5wnUHr9+/f7/9rfX5+fkfj0MetULfb7fj+/fu797DOIJUzPq+vr8eXL1/uMz+URwJKby100ObAcF7JM+c5IZAegEI5krczA3NhYtOckWBt3dq4rc9Ek69fcYxk4AwY6T5fS0kt79mCZwKEBBxuPwVe+kUDBwdK+lULvBNMLZtUpwF/koeLA8WcS4HyOH5vKSRozo6FtPXks6UFyGnPg1zz4NUkYhP99zjyA5FI+2YvHCikwNYC7GCAMZX98LVEg3nsP/HT/J19+3h4mL9psGxJ6xXdWia0ea7iDe98OAf5TfrwVt2Hh4f75KYx6yxJ4/HYTPKJDQfTSgGPk53wQ5t1fGHhwDzhlWklHU1f06+T9tSO+eLvLaFMk+CJjoSBbj8NwHiPbY5/N2jt2ifT6laiM8nBb0rwh5N8TY6ewElPjE38J5qmr3Y/6Ui5D9uwnc7ghHkWJ5BSn+wvTfDbbk1DwmIeb3+VOI7feWfCzOT3bus4jvvCC2NHypGZjyX7pA4GgxlXP1NSHEk4YJkkGfv36Im4y/eWz++xBS5QjL0nWTpmDz3bYJl1PQG99ZGK5ZxiTpLR8EX6+b0V+4CvTd8Js9PCR4vRrZ9mF44d5v8KRmzlU0/9TUZIYtuxHS8lIHONKyhpZtfGOZ+hbwz+drvd/5s6T/ydhCYliSw09hkEDwDw4UxD5zyQyYZpg6AT2mAoUyY8lPvIxHJMPKQkaCufSQJoxNRdMtY2AE1BwmWzo+RkSZZnTkEna2A2xxPE2naLs4/7PXNat392b6rr+rSfM8Bz242PZB/28dY+/eEs2TCgsm9vcWzgaPA0r15xYlLlQci2HZS4dSaDdH0LckOnsbSVMzw2rayT+k9+doXmFAhpgwkTiDWWJwM85cF7HERNF/+T6x0uKQCzJJtP8mj4xwTXdFEuCeOYJDk2j+1ewf3W74YBSZ+pryQz12t+6hhK+ny+8el7xoacYG78NHmQ3iv23uhL50x3ord9OFjmd+Kr2W+azLNv+kP/TH7giT+f846QK/kIedhWUk1La7OdO+N9K2e2zt00Xs3+TI5AvNx2Sl1tjxMGLT86s/2m45mgmJyKA1n2S3wmHSlObLxewal0bYvZW/xOvpXqJ3melUZT2pFHWq7g5RX/Ofud+mNbV/KVVD71HlUaMAPtFowSiDZiHcRp4A72U2jYP3/+vG/9neMfP368W3F9fHy8f/M/G56FmT6G7/k/7Nvbf97v+vPnz+P5+fnDXno/cXN4ne3K6X+tBBc7rAHLM7eTpHilYWSzPc2Uv1MAazI/jt8rkgRX65Ft2GaSnaTvK7bEa3ZY2xfbpNwTqDmA0g698mLdb6sboy8mhikApnrNb8xfqk+eDSgOdm5jC8ytnwSM1NFx/J5d3v46QB03DOEq7RnmtFUV+80MWmaCaZKxuS/RkRIol8RXk2eSuQdlyX6TDi2X1n7zB5+fum0lJO2iMZ9t8JmKMeTh4eG+En+25SzZRfN3/l8+rTwnHprvtsQv6WVLyFqgJ4a0GX7GoVSIK21rWOKr9XWVh/ThfZafS1vxbvJptKdYM+1vhfSODXDHk21yo2noSn+voL3bfo/j96v9ZiLd+QHzCvbT4nrC0ZYfNDvw4IOvn0kxxLLZ4kyb9Gn2zbpTWgzgvY0/90n/aTZuv6KMrS/npOx7yz0Spnh13VuEW/ujr7bQscXiKdb7/GWOD/DcbIH8m2/iLuVO+poMXd/jmGZ/LS6mthPGpNVx1uV3O8f2juP4kPOf8Zrw2bkR23d/ia4zrCfPpu9quTxQ/a//+q93hsyg7sHkFCZDXqkw0CbFPT4+vmvbr6rwAOI4/mPQs033y5cv71ZEZ3A6/9vg/zfmeJw5Bc6hex7gNNuJ56nAfOATBy6UxfBm5aYEMBngJNAz8J0V4vROQ4PYlC1Bno/1mu6bPr0d2XSznzRbyzoteLRkYtpMCbjbTm06aWVgH4CnnU17HrSO3dH+mWSQ7ua0tmsHXx8n8Giz0uSJbTMJcsDd7ND8uDgpZx3uavBkjPkhr/Np299TcsAkwH2npNRJAP2zrWwkuYwsvSMi2ZyLA4sDOv3M9Ro95CHZ4fDmRKn5B2XFpCPZSwtQxsHBsaR71qU8N/9KyaCTtZGZ8ZKxzSsAqVBXqRibyGPajUJ7NJ1bwkSbs0+3WfeW5KU6pLHpkViU5GBbYh8N01KSatpNd7J33uvjhnOJB9Obcp/k+5t85rp/J7rI3+RJnDzmToHpi9sr579/yRaTbiyfVNcxiLpKO2daUjyFcTD1sxXrNOFGsnvKPdGWYgtXRXlPw86Eq/bnFhcoj7MJtPmeiU3KgTyyzclhOFC9Mtna+iWO8on0Wz5xHDlf3ngmLTxPPW/5TLJr+0XjO9lK4s+xJmHCRk+Tl/MS1h95Wd+pj9R2+t3yj0Rfs5ErPsxyeaD67du3ewccxPD/ZV5VshIsGAOVZ7kIam7PDzFKxw8P72fc+eH/Vme19Nu3b/f/vBqo2beBZoBg+jqOjw/mICidGYiDnmXI2Vs6CZMoOjUd20CYksDR4zbITb9TUrOBfgOj1lcrW+LmZOJKfSc81OG0MQMeTwZwADZ24X5M33Hs7711vbMky9+8t4F4C5S0xTP7YftOVkxvkssGaPSfje62okr8YHLhfs4GXBv/LrZ90uTXRJhn2tac930+Jk7O+aTzNFglpnFQP98puWoTiE5Gml37OAXTxK9l5evU+/CQ9GjsYzI/iRUHqi1pS3QmH3Ucm0JcSRNHvLZhFYtt4Yxe1z37TX2zLX6uJLi2w2mHfbRPojH5fpNPk0XCqzNZEpM4KEh6JA+2jUaP63DC33zZXuaYg4+Xl5eoJ/u4fSTRxevGgXQfnw/hHMDtpAUQ+1izp0TbHDffaXFtivNIYiP/C5xwtdnlFR9NvpXs1DGHbXjQxrY52c4JjQ3z3H5rM000sY2kPx63mNBoIXa4XsO7rW3f2zCX7W96aFjgNlrMY5umJ+UCk8M2LGLbzaYsA/ZxFkNSf61eK58aqE5JhsiZGIMMHYuJ1ww2ud2lOfYw7NmU2+39i4cNvgOGNpYBi9kq/Pz8fPzxxx/H09PTu63BFLpp5HlvqfCMPB+CkGRiRTLYWe7JqGeWNIFTmrllUJ1CffJP7uzTIOz3tc0105oCKulsQcfO4kE3+WgAQjqcCLotzo7O77RdxsE0De5TEuA2KG9O/HiQYlnYplOSlwCC/M9xWn3wKk/THc9R9+OT/l/ntDfnzQ/5mPu2vrgSmBKrlCDQ9823eXVg8ACb9LiO6fXqnvs0Rs416tPtu23rJ+FFSnLtg5YTd5vMPWlQn5IT3jfHtAvS51VHy8O6Mc6Yr/lNP53VJCdQc8zVU8cyY3WLDean0e52iPuTYFDn9tmWsMw5ytZyTMkDv0fHLZHkb8vRcTrVS6tNToKmbdtUKvbzFgss8y15Ih2WseXLtjg5Rv4d9xOODe0pbqXJion9nJhJGMDYwgnoxHeTWePbuO246vgwMZYJtO3HW+/dF3l1HEj0m77ku1v+yYEp8dCDVuarXozZ5EodJ92Zl6FpZMHftrc0+ZZk4vuSrNiuJ+ltS0m2ji8tb5t+BgdTTpJyLtNoWubDCROv9jJPSvRaFsRsY3vja8sN07nUVpKdfck4vPnq1j7jwfzecKPhEOPp1fKp19Pwewih4t7e3t4pPwWv9LFgU+BKwMikqRkHgYd0TZ1xyinzaGzu65920iCGdHvv/SjfCWFy6LmWQDXpwbNjKVl1YsXzySiTbtLDnyjXocMPA5i+aCfmwccp6XJy4Nlq6qYNlIdGJ33Uh2WTgkyyx9vt9m511fo1SDSZcyYzTRJYlg78CZgSDSwpULpN39d0MyBtXXorJ4vtwn01OyEdDg5poMP+KD8+GC0B/pVAMfd9BnRNG+VPrHRwSfaTJhl4n22/8WNcTH1vq1NJzomeFOQsCwc3n99kbZv3ZM9xHB8mllId172CzY3eloRtJeFdspvph37wmT5SzGw8WK8NZ85oSPJosmw4mmhL9ZItXSkpLs15Ys9c35JOY2oaAHhw6jaTDOYzSfzDw8M9l7FPGldanCDvZ3br+2yXpnWOvcvNdmgcTDmMdT/23+Jik0nygcG6lO95kjMNVBv2WUZJt6a55YrOB/y06CnEMP9P1G2OzL3IwpIWNrg4ZXk7LqWczTm6i3NSy4z3NNkxhqWxBR+Oyjjo2LdNPFg/ti/Ler5TfHQ7jkdnJdlTy28Sns635WSsvVKXWJZs7kq5PFD1jI6JnRXD5pjeLjz/65wk3YbYZi/mm4bVFMJ7KTAPvkgPwWf+hzrn+AAmDsiGzzT49n1MHNNsvtvbAnjSh5PJVD8li+zT/z1OgOUElkDdVllTctroa7Ob5p8822ZSwPOf+BMQU2dpoiLpw8dJR0kHQ8v8t9n/cU5brw0gbGfsOU0StZLoSzPdc28DI9u7B43m3zpNdCWbYRseHDu5SwmZ7SUFTdJIffHYIOz7htah0RMBvMcJWrJx9sG2k4+YDg5iTMPQNjPX1D37YPvbAC/pifqcNm2n5m3DCMquXSNNtGX+T49YkPx4a5s8Mc4lnLA+znij78y3BxpTnFi5bEmV/a9h1obDtoGGNbZPxg/H783nmTDZ3qmHxAdLw9V0fWgkbS2OHkd++vict+4p25ZIJ17cdqJ7O5/81hNk7qf1ZxqTXyfa01OJ04fFk+SjG+aO9Pfpj/6x2cW0OYsV3HnDXKed23RCOhPONTylzIihzLlSoT4G8ybPaHFrBp+Dz9YZY8C06/4sT7ZvmTHfTrHpdru9y0mNhSwemCcfS7xMn6ndtGBB2pwbGMcSPqTi9plfjK1/pmwxpvlz81Ofcyxv2G67SrnPlXJ5oMpZk8SIjc9Jn5MEPoBo3qHFp8IloGqglxza4EchTpJkEKNT897mUP6fGQFm2mHibmBKQYH3sTgAzDnSagNqoExHSkmHB/OU0UbT7fZ7Rcvbptts2RmNc9yCpoM7AXvqcyvftprCeiPXkcOVQJRo9PV2bbace+uvgbPZC69zcsEBr4FXApm5j0lfC5xOOK8AoOlPAJaSpqu24ntGDgysiQceH8fHgVoLeqTzM8HBvKbgal9t9Jue8Yf2lE/iB1dmhm/Llh/+R5WTKinJMl/zzf+Q+l4P+IyjiSbzn+7hYGrTVytuP/m19dJ0ngJ3SlgsV25VI49ntLLdJJutHccM1k9JrzGvycR2NoVxNF23HSRs8L1n/pn0ZB01bB9aN17Zt/1q+uEAjHU2G03Yab4STlgmiddkP0mOrN/s3fxsONl4mr8NJAweW0krX7QzTtw5dltmpsmYOff5P6qJ1y3WNZ63+MRBueXmh8I1H7IOvViR/Jh1W+xLky7sw7R4oDrXuXLL3DTlc3P/mb+4cCIqxRnLLMnwqo5beyl+pN9nuUWKg5+Rhdts1ygn+lvDFePzhtculweqVj47J5Ee2FlYM2s/r6WYgMuXIG8rC1tAawA5bRmceD21x7oMIANI/G9tos9BvCUMpmszdF6jodhAtsBIHhuAsH8bXiqmm/K2QSbjZF8EKDurgfrh4f3WzTQ5Mltzp3iFu/GTZrG22e6WBBAAmyzHL8Z/pn/rw/SmpGfbitx8KgGjbb8FVZ9LOm/lM6CekiD7TUoiLT/3RZ1sg1Iep/tSsEh4dSWZS22m+1uCxWPibsOSlICkPpKN0FY37CY9Zwmd6xxHfsF66qvFAH6PDj3AajjVdGXakqx8zXw63pj3qTd49Pb29g7TbNObHJJcko+c8e2+SHuKcylX2Nrf4uGVclUGjjst5p2153iRsMHJWsPT5metTsMa0+JdGfPtiYLmBwm3mq9dlXvS6ZnNbf3Qp5h/JEx0LP1Mv6zTPry/xaAz3lMMSucoD2MyB6xpgt67Mzjw80CVuepGs2Xj+5KebMuMKf5LFCed00R8kmGKlaarxe72bf22xQ+XhJ0pt2kxP9GxxZ6G1W630brdd5YDtfY+g+mfHqi6jPFym0Rayqfgbrfb/SFGE3T5viWvJqVzNIgWTGwwCTzMS0oIxyFmJYb/sThzgpn9mXu4ZWQGvO5rDJ6rzykhY2CkHFJgtHGkAc+ZTFLwTg48ctpm+1MiwvPkiaA824rTK4QciOksbIeDdK/gz3luU0i6SzKY0mYSHVRcpg/PpB/HEW0gJbi0gwTgaeBJHlOgGNoav8lnjBefAcGWfLT6ycdNb5Lb1q4xizZg++PgdeqSLq9Is+80E+ndKNylMLZpWtlGS8xSopDsZsrgOV/jxV0k838n9plW801bm+xJfzNI95OHbSLFhXhJHEjYmuzEWMJjYgNpTzpxm3xwSfIbruzPPXxYWXpCO2Njkp1pmLYSDpuX+d2KJ1Ats0YDz5GeNumR6HNJ8k++YLtrg4DUP+Mxf9O3/Sq3jX9jAfsjtltebmNo5rVkn+xjfMQr9rz/dvu42yHRTNq2VS7iKuumHRqul3Sb7K71m3Bv2uFEUOuPbTE3cd+2Z+/ocxyZ75ZLJ54pKw7uXl9fjz///PP4+fPn8ePHj/t1ysUDP8qbspx6my+zjuXGe4235Gdy3/l7YMqDUzvH8f7vWinu2HaTXZBfy7fx6Xjk3Mm5p2U2sm0LavblRAf7SjG+8THXncOYx9RXwgO2yTjFnbltkSiVywPVROAAixN3O3aa2Rpnfnt7O759+3Y8PT29Y8QKT47o+/hQJNLSBNIAx23wm8Y7s0EpgCdDHH4H0PhfTrZBoJn/Ffi9Vo2nkVHbbkw+NmewjFKCYrC0DCmnBFJJzq2MjEbmDGz8D0lKGJNz+h7LKtUlSLuuwc3njuN3Ip5Ae6NhK43m1P/t9v4J2eTPeqSdjU00X7Ss0/9q+d2O24DEfKVBxWZPxB4nb8kuWr/u2wEwyTv10WibDwMxfcdP9Z4Eb2jYtgl7ks/0cUXfWN0StNE7/W9sfNpz8p8CmjHL11sd3pvsxjZBvzVG2oaSzpJPWvbeXWR+kj2kWW/bOjG18Xf1fONr4/FK2VaVGy2ON2c8XL1+te2k+3S//al9t37mv8tsK8kp+VqSIbFsa2frJ8ngTBbmrWGD207Hx/FxUJFkZ9qI3x5IW0b2T97XdMZ2Ez5vO/MGA4nFbHPiY5uQojxcjOuMyVzUmfYnf5zBqhd8kt49wWi5Ws+WJWN5Gh8keXOibc4xB06TeNZluuZj+p7bSP7tMYhjp/lgHdu643rDlM3n3V+rQ9xrvpyw8Qwvm1znd8pr08Sz6b5SLg9UE5CmQRaV5eQwgRq3Ot5ut3cj7pZAHMfv2bb0cKY0eLXi2H8rG5BNG4m3JLsBsbn/y5ff73L1NunhYcDlr7/+urebHhKRAN6zMykA2TCvOkm6JwVOG2jSa+vTjjzt+il7Dw+/nyL48PB7VnN4T7KhDrbB6tiQA4t9wAnAJOmJt0ZXsnMPAn1vW/FhXwnEGr/me3h+fHz8AMRpxt2+535bQnYc7wcxaRJg7Iez0SlwUI5ptZJ2yHam7pbcTR3b+pzz/Y0ulzTAdLHtcZLGEzdpAGadOpAOHQ0nG93HcXyYKHp7+8+Kn59abdnajpPuXZe0JVrSPQ3z0z28Lw3ofa+xJsVG85oG8NOfV3pbDKIdt5J8PfHReEs+m9pvSUui+4zWs6SotXEWD1PdlGO4X8ra7TTcnbqc5GMbtpPjyP+Dd3uU0dgJY1nCIPtUijE8Nka4f+uJ1zw4cx8enJHvKZ6ISR/Ll3Eyyc34mGRBf3I8IF/0T/M0A1SvgJqXeT2Wi/E7FccvD0o5IOVWWb9yy4Nby9z9neUPc834xychtzynfZPe5KO0tbGDq/hhH+HCWYqbXmluPJxhcsNzlrSYwZLwiDkIeU64yDhIeTSeGu7zd8IuL1CZhi23cLk8UKXzpMRtiOJWsHmKLh3Q2ycNbHy9jQVBJ546NCI+eptbB9IME42Q32dB1wa+BReX4YkAwUAyDjMPQHl+fj7e3t6O5+fn+9Pa/vrrrzhDxoQw0WkazGNyYN7fEpnE4wY+/m402uGdgDPZc6D2TJ4DjfnkdiyDDleZkuOl9trAo9mIQYL6bBM343tJ5qkfy2JbESZfvmZ/oS74ih3apWXgx/j7Y5k62Ps/uC0wJPvaBg9MUlJbSV6Wu8G++RvL6LHZxnbOcrO8zIP5m/tnsuw4fstonhvAgRTrTPtMRGwXlgFXFc5KwpyEDRvuUi/Jb/h9FS+39mfHgpNy+01K2i1rxgvTwl0Lqc2U3FkOxo2zJI/tpGvklde3hKv5eOOjJVPbd8PgljTSljm5nLBsvtsAyzJIWMfBasLdJsPEx7TrNxQcx+8nvxo7E/alnQHpeouztE0PDpPvuo7xI9kEZZLwhNg2vsnzLNP2tEOevIiQsJ9x1zHMurLv2/d+/fp1/8tFitejP8bZ9JBI9tMGqgmDzmLmGd5eKZy8cLvkN00sJHy2PVuu6V7y6lyKA/lkh5+J85u8fP3Kvc41zFei6SwHbjJNbSWbHprYtu2L/W2TMal8+vU0iVAzTLCisydwYzut0FkNhjSq5+fn+0B1kubHx8e7886glSuvM7uVAuHQ5mRko9cKT8ZAmrlNhPeT16enp3e0jCzTwNu0pABr42kB2A6R6ieeedwCTarrPpzwHMdvZ/RsEAPIBKeRn7cDX5VL0qVldpaINBBieykpSwnEBpIpObI86X/pPvM4x36Cs5OIseWHh9+r22l7E9tNg/lt8Gr/88qT5es+rZspDkbetrxhA69vdpxoae1stLs926tXJ3jNtrMlIbQT2uBMEFiGjVf6KK+nZC/xmHw09cO66Z7kUzzvOqmtzQY8gWWcmHvsNy7pfEu8Gh9NL5s8zL9pTzo4k3crLTnyPcTXka8x04kS+95oSDK2DN2PY0aSR7MNt2n6LYuUxDU/ML8tF2u/U0xh/8YH0rt9zFfDjERzimnNX9LxFRqbjKdwkmLaSqu2ppd2Ylqmj8QTcZX3psG/B6WeaHX727fpSPraYlCSuWXa+ku/N5xJuDH1R1duK2GjZdxkknT4GRlscfIKn76esKfRbb45YZTaaX0mXinbREfy4cbr1XJ5oPrvf//7XSdXAGCInoHqJLyzYuiBZ2LEbbdkbPobZ5135HHl8cePH/dVyfnf53G8H4RbuAySfjCSZcHZtyleBZ4+vALsLXzcDvzly5fj+fn53QOoZoX1169f7/4g3wx1+vV3Mrom2/T7ii5ut9uH/w+znDk/2xqH84yvbebXr193WU6dmVm1PkybbXrqNX6T7W4zRnZe80f9pRWwKV5ZnJIGiCMD+h4Bk4NN+xu3dpJm9jX+4acLeuvOfPzQqKGp+TtBljJLeNRWFluy4y1Uid4rs6pbkLb+tiCwAXuiyfy7OEmac55lnQmGl5eX48uX339NeHp6uh9zlt+YR97Sg8dMp2k/S6iaDlvcsazSKvzWthOdM4xMdCT7OavLOum5DazDYn9qyYvlkWgZeihL22yTj2m0zlMSnOrP/WeDCuKPr/k3+SX2NfkmG08YY/7aqpn5HswlPg/PySZ4TJuyj7cYQr2m2NJ2A7k0nDZ/E6OGJ+ZTx/Fx62/C7DO/4/0+bvkq702YnnSfcC5hvo+tu+Z3zGu4y4a2xZiaHn7mXO4Me5Mck8yuliYTy6LZJ2ne/G0r7YFlqW7ye9ucB3ieOHS7m9w+E0/cP9uzzJodsx/vbiC96TcH/6ndxqvxybE39XlWPvXUX3Zgx6cD2FEo1BkUUBgN9NkGheCSwHEExFWBx8fH4+fPn8fT09P94URcheWgyoHAM2xDy1wjjV7+Jp0PDw/vkvg5P3KYz2wBJlB6hXCCwKwatwGCZbcBRytO/Jy8WCY21v9OSYlQSnhaoHUQ50ONLA/aUAKblGC5OBD42EliSjxSAGoJEu2yyZq80vbcP/u53X4PKNN2Ecthkizyl7YiebJhaDCWpEFQ44urgNb/ZuOkhUmU6WWi0AYM7NczmJYV6yZfPCvWe+KZbfp4eLddUA+z24MD1Kenp3c4NThkGvxf8rmeZv6dlCf6x2+bHRCTvMKQgiTxqyUPTQ+8l7ofGnlf82vr0rhCH0i2mdppg4XET8IZ3+/VQOJDaivJjHxsNKU27De01WTnqXw2ITK2pX5oO40v+qftLvE+52k/aUCZ7MmxcH777QRzLemI9PlzJifHDl5zDkV6U3vEfA7i08CO/dsmfd22TBrS5NXoj3yR1k1WxhbLa/TRMMfPPDAv6em3qVivPKZtNUxK7Zz1l+yCv3nccMy4utkkcyj7auLbfmBcJZ+JvomJbQKedpx8h/2SbtOf4oFlaNlTp+1++yrr+5i+kj6kdeOV9G1+vJVPPfV3OuexDd/Xhshh2NsIudJqY0wzxK1YoUyimBDNfze4kskBHldj+ZlzVBSd3EA8tDv5S8onD8P3169f70nh8/PzXU5clZ6B6hhA+iO9+2hGZ+cZelJQcXut7baKYKfY9Mp2GbwoL+rb5zfgnJJmehisWhJiGbRA5X79PjDS1sCbdHDG0PLbZM3rZwNVtsP/LrZk2PW2/8xwu3uimwOX9Ior8pYCcAqYyWenL8vSAWzKnDPWpf7JU5vks+/b70h/499B2YH4LBkgjckvHx4e7n+l+PLly7vkNz1hm7jrFXnLJdGebGIweAvWCYc4QLWsk5xTW5ZFCvyJ5i1OtOIZb06+uK80WcL6Cf9Mt2kyjyl5SnZonllcZ0toEo412Te9JSzeivMU083zSffpfpcUl5LMt7hMvadJTvuQ/7PZ8DDR2vSccM+ySP6Q/DDRzH7Ih/Gy0dDuSbJsWOk6bIsyZ4xKk7i0W7ZJXprfGIstZ8bT1O7032Rke2y4lnKqZEepv6QHL9psekzxnOeSn1vebsv024cSdica00TRhn2ua/6JAZvet2L/mXMp9jiHTvWNhYmO5vOmm3WuLKqk8rdeT5NKSrhZ5tUKs63MT6kc4UxSw3ey8h1+TpbPAhHLtDH/+bzdbsc//vGPD0CWHsD048eP+yos/xvqhxM4GTegXQn08+HsDd9p6Laen5+P4ziO79+/v9sWkoID+fRAIj1h7YzGtELic7ahZtgtyLj+WbJj+lLd1ldLVnjO17zSzQ9lMDKn/aTJD9LlIEjfYcBz8DIf3kJmnc2HtI+/3G6/H2CUtqinxIQ0e2BN2zUtjdfZsmzdWV7k0TpL9e0Pvq+tnhJw02quV/QoW7bTgmQKJJvP+NzZvSn48/s4Pj5kbPDCtpoSJLdJ+fA6cd3bil2c3CSMarbdZGm5877Ub/PR1p5tK2Ei7c6JNB8umBIP23qz+5TItgTE/TVMvJKc0u7TgDvZfdKJ+0s+Yxptz2w74cbcQxvkqqjj5HGcP7vD7ZIe6n1bgWk46dUq2mMaPJH2hE+kI+GB6bL8Eha1VWXat2PB2F3q5wznk09QVrZFt0M62+Td7fZ+oMq/sXwmJ21+xHOOzw3byEuSrdtuWMc2WhxJJcnP7ftaym3sJ22XzdDHNpKP0KbcHuulQWtb1Pi7q4LDM22otdX8qvlYum/62OKh5ULfo+5SfbaTjnlPotv3buXTr6dxSYHS4Df1Hx4e3q2m2DCZrHCAehzHu/9xtkGfAa8FdDrRDFpJO5U7g4qvX7/e/9c63zOI5Aqmldyc3bQmWZMGX7cz0+iO44j/AXTi5MDl13U0fR/HxxdEz6p0AsEkdyc8LSDZATZwNsAYyKyP5CRsyzw3HqYfrjQZhFPSMoGEdCebcNBqW5dN8xYsGngR1K0f2pZ1M4Uz/h6gERQ50GYSv8nZ9KfAnfRqf+K9nrDxhIvvtwyOI6/mU2Y+Zjtb0jFts12WLYC1wMC20kQaedkCYJM3++Cgy7KZPof/wVwn2ezTq0lbSYnWWRJpOn3e8YFySj5m+0/YMvU3fY2cRi6OUVdk0Y5bfCIf6fzVBNb1mgwSVjUaWt3j+Dhp5NjoBM6269zCA9Wxaa9qUi7+HnrsX8k2U7xoxXJMODx0JUxr2GPaN/z1uUSf2z7jtWFh4jvlDu4r9ZvaaniaJuTaqlTqI2Em+zetSRZtFc/3JjqSHW/6JHYnvNvqpe+ki7ZS2iZIzuwt9XWGHfSHtpW36cP0bH1Zr9THWUkxjMe8nuK0J2g27GQ79t2GE60N07jJ40r59NbfKcmpnUycOecce6A6s+zzAKGfP3++2/qaZlweHj4+3XWKkxsHIjvFt2/f7nTzKcLzMCY+PXgGqHNuBrabUhKNSb4jQz5afF4ZMfxyYOSk9mywStD1J+kqyZSvJBne5zr7Y3sbmKfZsDke4JxEw23MxMEc27as5y3QbyBkcJ3vsV2uDFGmYytz3qveKRhZHmeJ6ZUkxz5Kfs07k+O3t7d3/umVTrc9hTZqnztL8gy4Tri8jdoDy+mfxXbFQOU+ku5TMutCGpP9U17JDtjXWRJzFjxTEPdqZsIQ65R8uR8nIm7DMiQNM+m3/R9684EtkPNBaG4n+bblfQUT0qrT+M4ZrpG/NuHSbOwMY13oV3PcEqaEC6bJffH7ShJmmrx6Qj2n9pLejTFpVSnhrPMBxwvixMS5+SQ7YgKZ6Gl8DA/N751MtsRwsDH5cbP9RPcMVJovzvemH9vKGaYZD00T++R12qZjtGWa7LbJo9ky4xMHc2mibYsFyU6NB6l+oofyTavVya9T2+SBA1vLJeFnk3WK/+3eJAfSar75TcxvMZEy9e62pKdWmj5oszymnNJ505hit/tuMWp8l/pr46DWdrO5Vi/JpdnK1RhxHJ8YqHrlsRHDrTBbcsNCY52khQPU2S6cjJ6/24qrjY7JkLcwGlR5P5+468HZDFT5NN4EAFw92hyAMuX9W/AbcEqyaDO5TqiuJD108BkcTtI75zxLlZKKzcFut/fvEHXSYnm4bQYv1jcAJ1k3p2UfBFr2wXatKweONOvtCQNu5R7ZX6F5zqUAlUDDvuJgwUSNOp0t/ZaXZTCFyajlkHyF/ZCOkYkfHsZ2/ORE62Tzv5RwDP1toJpkzGSD8j1LgEgDvyk3JnWtnRRQmMgYQ9ITExt/ntCiP2w+RPnwLxJnCXrSlwe1xBr+puzPEj7zynNpcJgSjtbG0JVkatk4WU9/zfhMDNmKdXWlXePF2bexeWTgWD73pEkn9p8mHp0fbHFvGzwk/plnsO1G60bH1ofpTDayxb3jyAl9wp6Eja4zcc2TPq6X7DydTxPhlKPtvNGYBt3sy7JPWEgZNJtv7TcMTBjke9rkln2fsYzyYFup7ZRv0OapG08MPDx8nKBI/smS+jaecyEp+UWTt2WSiuWeaHR7/Oue3/2edMbjq3lEopPfZ3S6juXPe2ybE4snH5/vNJbgN21gi8UNv3ycfNS+c1YuD1S3VQmeM5EmhoGe9UYoFPDb2+9397HNObbTz8OH/A5N82EHpkLTjDoD6ih8tiJzazC3J3OWJq3WpGLDtIJZyDcfODD9k1fyzvoboLqOEwg+mc5J+9DEQZydwLwkYBpnoW20gLElb0yqXK99NyChXdMe6Hi0J/ZLW+Jv0j+2w/79FMArtmS+p7QZ9QSgBkYCDPlKM+7T9sjItPN3WuEwLSlgcTIoDVTba4fapNcUY52xILWR6KQNWx+bbw8Npo++6PqewLAe+cA6z7i3wWEqV/SUguBca+2MH1kXbC8lTJSH9fbZkvjfMIJ8bHVTPxuPqf3kt3O/Jz3PMCJh4IbPGy+tbDZgWtukD/HB7bCPKx/XYRxPCXCKBdQT/7bhyWe3ZTkk2pJ8k57S78/ovpUr/t/ykNZeq5PoSvE50We7Mo6wfsLNrTQZpJX9hOVM7JPtJz5sX9OfB6obvm/tb3pNGJzw275pGng9fVrcTbokXaZxK+16apMy9SS5ZU1ekx+T/6s0Nb4b3UmPzYd83CbiNrrZb6M9xfVm9/YT1rla/sdeT8NkfT4zUPO20Ea0hTt1X19f351nIQjNqi/p8qpB2kI812aQNzOmLA8PD3d+SDNXZN/e3o5v377dX3nDGRuv/LANGx3vmeKENAVf8jtP6eTAnQP4VJftniXiHOzPhMLT09OH2ak0I8gP+0tlZJa2dtpBzsCQNrQlcNZ9cnTKe1bSuSqVgDolJldAmMnb+NlxHO8GZ012/x9v/7rjRrJkW6ORKkm1ujew3/9FG1illJLnxzqWmjlyTPNgVe/PAYJkhF/sOs38wiB5sLoEywY4GYyzbgZoypa/STc7TNywZGPet6R9JsSJRd++fdMkJttQT/ZArFOhTik3LkaMPzAZyfF40qOtPI/8U4Z53ybWTOCu6+NJj8ZT9ptYnPokDlkb2n7+tj0/G0a0Vfq04aYz2v60b/w+kyyZr7GYPVHnaePE0Gd2gm0Bh7xZX0Zf9mvJEX1lix0ce+rkCaApyXeLU40Gjkl+iHlNvpbU5TuxmfkBk1/ilNFjctqS0rnfcjP6E3W/2WXqssVBkzVldYcn2kTWszi67agST3nPxjO7zbpciJgxUr8Zf9iH2QBjUcoofZ/FZEhekyfGiMypnunb9MD4bradsqD/G/2kpd1nXcYZ5kikI/vecDs/k1fyazlKw80mg+yLfN+JA1MyX5z+Wi6R8XaTx9S/ww/7f4b2LLcnqnRqCw4J3AkmZIyOuymDfdDImSRPYXKTxmUT1ZmgZiJNp8xE0IwwlZDGO8aRjkNwTUUy4G1gxACVdAwPIyNLKFuCQaAnQKcjTj0+jdYmqky80tEbf7kQYCtf2bYBJG3PwIN12AfbJp9fvnz58Pth2hyT7JQpbYEJfXN8SxZI/ylB4Ts/m0+fQIm0pC1zUmaBw2ignRpvLbFPGrJfLizM5yabxl97vwv0p4DV9NzqkU/6PPH3REPSbAFq+srxzDfp2yYTC5BpP7nw8fLy8TTJyd8pF8qGftMmn5QR6d58gphp/Y3cKMsWBzdeGVPo03eSM/Jp9U4+a30YNlHmjG+t3zsl++dCQMZu0mh8tsSL2G7xjFi/0d980HSxjZv323gN+ymLrNsWmI1+YmNbYDX60k9ZGFeMV45JH8k6eT37po200mJB4m7SRbtu7Thu9mM4nLLICUs+yT/vtdhhOTTzGNJndk3Ma37c+N38k7E+84EWi3Py2nRgNFAvW/3Ge6vX+ptrd/hqYzTMJMZufJBn6tNKkx8X1rfy1I7qGDQncVkyCF7X52OLLy8v6qhzn8w0YMr6+WRgc2wzxHzgTSap3HnlfwDm+CfQyqejDjhYUBz58r6tho+BtJ3F4TcTOkvIt5UxBijqN3WUMh69f/369f1+/sZyruXDodJmaDvD5/zX7cZ39mO2Mu/crX4mqOfn1An/sy7rJ7DPU6wJ9KTTQCiBKvluiZAFWNpptic9Qzt/u216Yp9Gz8hsbNNsLmlqNmrASOBr/+FKvm0XlT8VmGL+wL7Jr8nb9Eq5kT8L6uwjk40MdPb3QUmr9W8JS+Nn5JB1E7uJ7w0rT8UWbwy/sjR/Md2zJD5Z2zsJusUzYqbJ3PqmnRmONVwc+ZmcTvZq18nfKVnJSTFtcXiyU0SGvYYFJgO2n7F4Mqc9DMn4aGNtMWOuEd/nGmOBxTTDfvoYZdx0Srzd7m+402yXMmo2YXHJ9LbtpBJPGjZc1+//9d4wqO26Gc5PvZG99cv2vJfFfKhhjNk5d/azr+yHJxZGnpxYZt5iJ/La39IR7ymv7WX2TVk1304/tlzxVCintqDB18hvw4uGVeyfdU2+Nkk1mWy5wkbn9p34naUtaKWf5muw+G4+cHuiOrtFaaAtqSMD3759u15eXt6PhvLV/vPzuvzhMQmAX758/k1f1rUZuyUJTELopKeJmz2YhEn94/F7wpo8kl5+zuCax48zEaTsRq6jA9JDEKM85rqtnBmoJrjm9TzOljqlbmzhg5N3W/2ethaATX7Z79SzgMBAN4CU9sNJc0tchj57uikDsdkWdUgwT1luk9MtSI+cjB6CUAPnJos7gZc+mHJ7eXl5f7rwKfHJBTX7DSv10hKylH+zzeYXcz9lMtcokw382SbH2GwuP+diEGmc70xu8h6/twSCNL+8vLzLnH45Je2hBdb2nfIglmU99p27lDkZNVmSvoadrf7mc5ves3BSNdeSbtJ/sgvSaPc3nua9XWs+tdFs41Hu7Sh86ydtNvHAYhDbkG/a/d0kq/GdtDVdkEfSm/ZAX+UE6mTbSVd7TeHCH2kyPZi+7HP6lclh+iLPWXfD85ZrJv9JV9oKsWxo5CSX/Z0Wds2nyNcdXMq/dZy8O+0gJ3TcKR3ZsG+Wx+Pj8x/oK4zh1lfjt8WpoT1pTH5aLnaHn/RDy5mytHyt+ZjZr41POqxsO/sN20kHC9vfwfjWh/GT13Jh5PH4OBc6ldsT1fZAF1MaP/PBA5lUPh6P6/X1dd0BoeElmHE1fz63I7b5niX5sGMObQc5AWJeQ1+CgcnGVranHXnN3xNk4p08cQJH/m3HtIHE3RcnUBZ06dAGiqcdq3yaMHeYqaMZJ1dRuTvS7MbsIWlMeU4/nCSyTl7Lna+xFwL6s+DTgn6WXCyZ96afebddSPN7jp1tM1DPJDLHZGKyvbIdaaZNZlJhycXdYnVP4LrpxYLh1k8mQ6Z/W2E1OlvCd4eGZh9b/bQDyj/Lyabby8bb+sw6LdnfdDM8ZHJsSUtLyPj9FPxbaYmQxbnWpo3f+r3Lg/mk9ce+iDU2TvbXFiQattmCZ9M1bYmFfJySN8ZUq2OLXuR7o8n6PtHd+mHcOvVnfdpY5I91mv02X0wdJ/5nnSaTjFu0gcSrxLDNh5L+O7TY56yTsdr0T/vOuMdcKPPPlJu9chG8xb0NF0zGlieYHLZ+yHvqxE7sse6GYVPvLl2WT2RpuGJ20cZv9w3n7vj1nbyAvrrZLPtKOk4+Rzs78T7l9kT1r7/+eh+kPejj5eXzMbqpZ0esxtjm/0jnwUn5H2XceR3mcqdgjDQdsq06tETESnNoCv3l5eXDf2jOilY+xt5WhGeMfDea52nCb29v7w+IyYk9H9SU8hk557sFQ45pyVjySlvIo9TtN75bcmY64gQmE5p0/JH90JMymAcd5QO9CBoWLLbE4vH4fXw5n+yc+hp5MxlJOdKHjIYEAAug20TF7Iw2YW0sSDdgNt1l/8nz6GaOhluQpa2M3GYFdwP71Ht+N4C/rt+LbyljO+pvY6T82zhW2K7JdNNN3tuSbuvHAlJLUAwXGl0cb/TQZJnjt8D5jEyvy3eVSFPatNnEFpytLuMfd07sfjud0wpt9JmkJEsukmXflFPzH9JkY0/sze8N98mT2Xa2m74nxmQ/TJYML+/E/YZvptcTT/ZivY0uxqK0pazT+m75ENtup3qm2ELCxv8du0ndsG3S0vDpji9s8bzRnXZIvKA9p0+NjDZ/N3pND6QtF1tyTE5OT6e0rEw/b29vustlO8p26iknxbaDfMLTrV7GTT6kNOXDvk3GmxxOscp8MGk82f0dG2w4SF8x+ZkvNUzb+jFcOMVrwzr6a552O/lvltsT1SFmjDU/X9fn/+Ybx+XfIiR4JgDlpGcM0IxxPs9EgccATIDkgQLM7w1oLWjka/6iZiZFOXnLFx/kdAdQUsa5q5c7R6mXudeSsQ0gCO5WBix5zDLbDj3kcQPjLYnMQDG0tZ1v8pYJT+50U6/kmY6Z79PPPORpFhMSUG0CSb55BLHJn3ZioHiy0bQPA3cbj/ppYNnK8MNxJyBuyVIbp9ml2VDjp7W3h/NkWx6/Mf9iIJs67PsU1Iw+e2/tuHJp7S3wnL5zPHun3u/QezdoJV9WcmzqLbGKyfcd+zC7ypMC20SVOyV5P7+TtzuLGvTdTJrnvSUk8+I4eVpkSyqafRDLNnwiD9ZnxoDMPWjPKWuTz8SulMsmX46X8uDYJlfD4CY/0srYyYe9NbmlfScuZp/Gp/nkyU9SD5udZJ3Wl2FPyrmdhsjPjIfWl9HYsNLsY9PRy8vn/wxt/Wd76y/tLvOtrMtcMvmh3bZTX2ab5svEMPph5qFGD/nf9Mk4yd+Xn/KXLHyav9GU1zY8oA00m01akl/mcCzmX/Sbu762XbPx83vGtdbGbMi+Z9vNB1t5aqI6xX4TOkTl7mkGlgyYxlROfHIHlYY5rx8/fnz4C5gMtHcFYAEylW+AlbxysjO82W8R8+FM3JHOv3LYgojRmjteKfMGtgkwBmQ2HvU17TgZNpDi6uJMUshn6tYSM/KfAM2VxCkj0wRDtt94z9IAjTv+eY1yNl2kzSbfpKFN8FNHU4+Ba/vjb9q1FdKYfFjy0+gk78bjSeabvkyOxJ8GnFP4oKfWhkeNiAG0+aGDtmJ4leOSthZYLEhb0tKwsQU16tx4fTz8N66noNhKwzrWeSZI0+5p+5mAWdKWfdC2MqFkm7nHRdm5d2fSbYsjVoh9xovRl/rMhMrqG30tKcv2jCOWA7APxjPjt2GI4UuOkwusxlMrTE6Nf/Ji/LYxrV7GKsYBk/V17X9NRnxKO2GcYL/GW35v+Qfbb7LYSsM/y3es7eY/ra9WKLOcnGZulxhBTN36S1u2Ra5p0xZ5cwd0Svvf4CaL+Tx9ZJ9pV+lXbN9ibrMVa0v8a/RRnvPOk2uNnozX07bZEj833EssI4+MJaS7xfJGV8orxzb6Nhs/3eN9o3XLA1vfrdyeqObDTObdjCx/FzgBeiaU6cC2yziTOCqCoPt4/D4u/Pr6ev3111/vRzxnLIKCHQ0YwzRD5/es03ZMhu9Jdsnj7LLyKWr2cB0LSBbMRp5MvjYAT3r5202+c6JJGTVZzGerm/zOvW2Hioaf9CSAZuKRes8E3xx/u04+sr7JhMUmonlSYGz1x48f7/Xs9xaW8HBC2ibuZksGyNf1+fdf13V9oJcBo42ffUxdBp3pm2CdMn0GzJIHJgNNvxYwCbrZhnaa9bMNnypO/200sq+kcTCYCyEnOSWdW7BnsZVr6jGTFu4MzvspKGbhgl1LcniNfZt/z/3EDWubCT37o30aXli/GRsG8+ez/W/3tNkm1obXpNHsm3IzWT5TNt/i59FDrtYziSMt5J0yIHZNHTt6bn0mPpscttiQdbibxrb2mfJuC5LEcspqSsY8699ie+Yoc6/FYhbzm21BZXCCtFgONvVzItSS36xvOHG3tPbMOSyXaTGX9kmsnHvZNsdMGTTbZNvkJb/zJ3UnDGB8a/a3+eYpR5rSYpNhefbP2Jr4PfXsJz22mMNiGJax1Oqf2px4uy5/0OApXmfJReSmU9N9o2srlmfNZ4vjSd/d8tTf07TAeF2fQZMBIQP0ED4T1PlNp/19SvaVY/3xxx/Xz58/3yd+P3/+/PDOJ34OLdkHHcwEZ7ya4Bv/OVYmpzNRSDkk8M3nGY9GREPO3cPmRObULRkzAGxORRkwiSadQyPBxvoi7Se5z+cZf2yP9HDlfQuU2ed8pvxbcGr0jF3O4sqMn5NU21l+ppxscmg3Hsjf8GwLItmWk2fzs/xsNtJ0MW1osyfftf4pF0tQmFxa3SZXTnZMfybn6+o7qqmHlEVLCDnuHX/f2uc9jpu7xtnnZoMmj033pMF0YX3a94Y5WzJA394SCL6b/eSibPY/9ThJ3XZhyBt3NqiLlsDw2ma/raQeT7je7GvzLfvO2JbXrH+O1TBqvm9+Q9y8828I7Mu+38XA1q/RbThNzG40Jrbdke0z2HTCB57WIm1bMRmkzsevJr61Pkxe3GggRpxslnQ9yw+/pxwtB7HnmTDeUW/ky2hNfi02WH3q4W6MmHY5J6EcGp2nsuEN+btr261/YneLxxyzxZbt88YP3xt+N9zMXMf4a3Gz4YOV2xPV19fXTyDXEtIJrPkIaxI+Dv7169frv/7rv65v375d379/v75///5h8soAP9/nyO/Pnz/fjwH/9ddf1+vr6/uLD9J5fX39QN91fT4j3wwn31mo1HnnBOTl5eNRENsBs/+sysTVdqxIf9Jh/E27mTg3Xtsrd4gSAGe82SXkbmbyQFnMi8eC53NOwPPaFFuEYKJncjgB8PTN9umc1Gk+ATonItxd/fXr1/vJgO/fv3+y3ZRj6sYCB/XN4GP2wnuN9qS37dybPVMXaR8pE55ESFmSzka7JZlM1g1ouWtodsLxtuR6/CkXY7Kcjl2dsOZuPeLc1KVM2Ifxz+DFcWyCYLsmp8BJW2ptqC8bv71bontKmLOOYQTx9pR0cUd1/vqNPDdfm3uNxy9fvnzaTaSsmr03+2/3eW+zWyZWW6KZNJ/6s/YtwWKuwnFM1tluPmf+YnErx219Gt2mV943LEzM2+K5HUk1X7OTGm3h1OK12R3lwh1s2kf23/CU4zFfoBz4d3mzacDPzJ1SfszXMlczfhrWNgxnu80Hsk3itOUrk6fZ30EOHfOcjUZjs5nmu6kf+50oZcUFzyan7Jt9bKdyTMZ3MLu1J7/s2wpluO0uTr92QqLFuVaYJ7G/FkvZf8POxufweHdn3crtieq///3vDwPyqEgrFEQGqWFyjrRd1+cnE/IoQ74PPRMsHo/Hh0le7uLmg5rsKBVBcjNyo2XanAJ/HrXl8Yjccc6FgATCeeovx6Dh2K5X0slXytp4TiPN5D5fA4B8KhvBx47H2KTdAujJ1gwALcDekYfpke1yFTaDXNKTQJ3B5O3t7fr69ev169ev69u3b+9y+/Hjxyc5Gv0NoE6Bz/jeAmvqaJvYUaepi5RNJguWrCRN5Mn80wIfP9tChh1lPgXIEx7wcyaWrc6dMcynW/usk3UZFO+Oc8eetuBlfsWgyfoTWwyTkp87QZLtaHNZuLC0JWgmZ/qq6Yk2kUm12bOVtqv18vJ7wafJjTLMtkn30Jp+Otesz/ne4sfGI5O15I34muMa5rO99Zk05Wkk8y9i7Rzrn4kqd1HN97b4Q70MnfnecC9pzM8pTy508z7pNlkavpAeW1g3mXKM9IGxhZSF0WA8Zx07fp1jT86SMc0W4E/x7YSNxFHap71baXoxDDZZM27nvZZLpF+ZfRm/U1JOp4eHWi7O2GM22HzAJtEnX8mYsMUV8tzkb/JN2+bu/NRrsZXF8MDo2OISsfMOv/a+lZQnF4WSj1N5ekc1ndX+nqYZfRJOJl9fX9/rz66nAY61p9PM9zQKBiOuKLXAZAaQ49xRFHnPNpmwjMHy960j53R2AgcfbtUAy4B+A15zuvnMyel8zp3A+Z6GObxy7FzptVVfynHo5zUD0AYgKYct+LDefKYd2FjpM+xj6M0J669fv67v379fb29vH/6qiQHH5EH7srKBnvlC0myBlX2ecIDAOU/vJo2NhuyPSRLb5iqk2YAtWLWEaONnrllCYjI3vGH9hp25w94CuU3ETFbcBZi2GVhIiyUU5D/vNdmZzXEsBndrezfQUe95LcfLd1uZb/hAnba40u5bknXizcbbYm/yYjxTJ7SNZt9GV/PV7ZSE0TT6J240/Gl0JW7x+6aXpDVjVT68EPKVAAEAAElEQVRXw06QJK2Nv01+do0056KK+VmTeb4oww3TbaEg71nybfKw74kf7dTHyXZnbPPflGPKMPGuve7ozmzwjo9k3RZjSHv7bDK2+ymzJsetmC00O+fGVhuDi3Xsh3LgvayzLW62dsSF1o50NMwnrrexTyeHtkLfJr0ne2421q7z88ZjK3d8w8rtiSqdYMoYYf6PaNsNY9sE8jnC+/r6+t7ft2/frq9fv354MAmZTLoSKN/e3t4nd9++fbve3t6u79+/f3rYkiWrd2Rh/BjYEzBYd4Ajj7bQwYfOl5ffD+OwXUeC+MlJHo/fvx02oycPQ8csJjweH/8mqL0IkOMMOVHPo9EGbCZPSx4b6M64lsQ352XAOy3MUE/TRy4uvLx8/GH/0PX9+/cPfcyOah7ZmfdcGDD9bJNZJulJf/Y5fI9OmmzYPxMBJjA51kzQudqb/pi/L7dEi8lY6pUTVZbm7xsOGAblIswmn6TDJugms0yiUq/UcfNZymiwNcdgG/NdS4SSNp5YIQ3JH+ltiwX0My5Ipj9Tdxw7xzH/MPxg0tviWfr46a9viBe0k8QNk9UpOUj+W8LHOGMYljtO2SdXxXMSafhA3bWkzGg2uvg5+2CSeff+jDE4R7wg1tjPIjYZT24yxXYzc9z0NconfTptj7QyP6B8m/209hzH5GM4b3a1PR3fcqiN3pR15gwtgc9NiqEzF/8S05Ju0mP5jGHIdV3v9kL9thi9+f2MbbbC2NDyWuop9dpkaz5AmSStFnfa8fjEmLyePBlu5HWT/0af9cM+W86Q1+mblgtwjEbvfKaP5wm0Gcva2n/KNntrNtawifwa/xvfxvM2DsvtiWoKzpSVCrI/DU4CKUT+9m0eijQPRvr27duHVToySgfPyWkmTxlkLPFvK+3kg/SnHPhuCdt8zokag4+BDyc8dkzYgkoWBuwNHMmDBRZOpCxRtX4pZ+ObDkuZM0CO7vNe48UcLOWf9zIojT1NHU5800cyIDIhpI6S7rRFs0vybEHLkpzr8slbSyrsnuluu05dGViZbVlyQBqZILS6DDpbkpC6tckvC4OM8brhSSuGJaf6hjsbHdTF3M+JCPXRJmIpv8Rb3p+S7Q0j8zr72uTRgt+G0/OZesuXrfjT74wm+g/x+Q6927Xmn3cL2zX+c3xi3UbblkCSN5OV3W+0b3Vz3NauJY7G00YfYy/paQm7+ZotrjT+kr5Nb8ZX+n7mSXz4ZesnY1La9nxOPhJfuCjWYvOpGD8n7LXx7uIusYkxmf6edBpOZ13L31qM50bAdflR2g0ntmuj9+RvPifdp9hzkuWzxey4+cUJC5gztO8bnen7Lc5a7mPYmPHabDh1y8W7tAWza5OB8dG+t/pbjmRtno1XT/09TQv26Ti/fv16PxbDpM92CVKwBDs7XmOvBNJsd12/d4mGrvnO46n2I3MKnqsNVs8SsjvXLKkb+Q2406hzpYoBpv3lQTP6mYDNNQMZJqCpPwZZC2RWElyYlNr/RlJeDBImJ/JK4NmSj9TDXEvbNt0MHdTNvM8CTHvac9Izx+JzgjxgmIkD6eUEel7bo+kzOKZPtlVCC6iUXQvEs5g1uGJ2NLv9ec8AmUE06UsaKZ/8bliUfjDyYRBLuVkQsuA5/nZKokze/Myg1eQ+hbsi5I8+z6To9fX1g31ln1mfWLqt8lKmOX7+3ZnFj+SDvFKeDOK2AJR02OISbZ50NLkzWbGJKhMTS5AoK+6a3Wk/fA+m2E4Z/ZR1zXdONrvFScM+9kM9my9m/y1JZjvGO8MSYqDRyfZ5EiVjAHklLk0uMg+JtL8rI68chz4y/Tdf4+eJXfybLY5nfPPatCG+20SV+cOpGI9Gm9mHLY4mf8Zrjjd64UI5fT37MV1nDpbx3Saria3bg5HoK4bzlNMU2lH+DttsPsfkMzXyfv6sjXzdyfNYpl36MP0++be2LQ5NO2LyRp/FXqtvuE0MSv1ZLmYLxxaLsrS41Wzg9Dn5Nt/ZSovTrTy9o5rEWLLbrlsQYJ0R/HX9DqL5H6z54m8a07ltMjV9pjHkahj5asWSojQgcxBLxto4NsG4rt9Onv1zApQOwFUwq89E1BKtLVhPHQIs6We/dj11dteIk2fueDRwsj62a0lzBpc2Fq/ZU55fX18/PV2X/y2bQcl2/XOMJvfTAkICvYF71jP5WRsDv6SFAE1ekvevX79++Pse8sfCIMUEK9sTH1JO5CPlaPo2fkgXyzZRNdu1Oo335ks50Ux7nIWtsUPi5fQ/OsnAlGNkUM+EahLuWRwcWoznllAQr80OGn4Q3/M68dbutf6fxSlidfMxi41Gv42T/bV+pi8utiWt46tMfonjNsFo+GnvU6Y9Zcv6XKQaOk0Wd/TDMduCFx/OY7rkYnHievpXxgTiT/6bQeqAuUnKLxfzzI8Yz/mySTR/bsWx08ZyHOK/LVZtR3/Jm+mL4xkGGL/XdX1aqE06WrKdfWbuRJ4zfuT4p7xn7vFBm2bXpNcmKLTn3LhgrniyiaGFciAtpMH0Nf0QVzOvysm75ZvEmOkz6eUCvuEA6U3ZTxvaOTHJfM3sOWkgdm45VLOXZxZzsi2fZUPaSEfa39185OR/zCnulqcmqlNOAxBU2f5OEOHEaYLpMDrf535OVOnkNNgMwGnUNsHdksl5Z1BvCUijJ68/A8TjQCnn/K0Yg08GdfJJmW+l8cpC/ZnDGZ8tWUme5z4/t+8WfBhsDXiyrdmzjZvv9jcAeeqAiQztdksEbaXbbCjfp75NeOmjLAbQDcw2GVo9jj80ZgJ7SmA2kMz2LeA22dkiSPLddsf4eUuA7lw/FQbXLJZYJVaaL8x72hsTZ44/dfOUCnHKFgNYmsySv5NcaU/NfoyfEw4a1nDMZo//G8Xs24olsLxPu2n9WRLVruXY9tlkS/trOtn0bva74ccdGW71LQ7kJHVe+V/xNlHNSU7GjonZxE3Kq8k1dUIa552L2nMt5dj8MO9tmJcYa7tATaccM3lqcflk5zbmNv4ppzA6sm2rt9GQMYb8cJJttKSe2wMq7dX+QsbKjG8n37JtvsyG2U+Lx6Rl44Ny22Ii84OtTfN565f0t/yA90xu5i/ZP2lt9VocYPw3fW1xOu9nvpDvm6xO5fZENQsJGjClImxVwUDTAj77ua6PCeP0w4fWtB1F9pvX54jL/K7VVqy4gpt9z3UrNJRWh7s5XGFs/dCQBpSGTiYUDHhZZwscW0AnyNlvcFKW9jc226pcymn6yrFz0mXOYYDBhy6Ql2w7Y266bImQrWByJyv1lhMHBqqpZ7sypP/x+H1EOeWXdpAyNfC1gJwgNPTn2Cy2wpgP8Mo+U07WJmlhMdpMTrkbnn5nK/pTN2VouyZJe9JjiQn1NH2m/FqQsYWdLTilXEznyQ+Po3/58uVDcp12S3s2/M6J6vz10uvr64f/vJ7kxOLG9Gf+SVmNjjaMNZs2nM33ps8tWTKfnYkGF4jIh9GcOsrSEo679Fpc3LDXSvqR9ZGv8encudjw3hIkXuNuSsqJdTfeDEfN16ZO+80eF4nTZ8aXcqcy8WfoyAenZBznAqYllfO57cZd16UPvczdthyjyavJjA/3Yz/2+br8N72NBtLT6qTOLQ/hxIi0mP0l7TZpaPmT+bjxkbHyTjy2foaHlne0YvjeaJv6pxzN4qnVb1iccqRfWxxmHcPajWbihC08GA02xrzTvoiZDT/TlraFHbPTUxy091bvVIZ+5kHMC4Yu5jN3Y81TT/3NzxRWvtI5KUgKk30YaJnTznFg7iZmYjCGTMFlodFl8KCRkA8GR5OZGev0kTLgzgMTc+uHn3NCnzuq2+8gLYCcAgQT95QjA7Qlhtzx5UR1C3ItsUzdjQxTzib/5kjUD+ufCmVFvxgZzOeUV9PXNvlqdpG8TNKTwNL8uMknPyetvEc5E7gZAKibDZA3P950ZIB4p77RljIcOTZ5me3lPcqH/J/84g7tp4RiSu705+SKiyeZ4Nr14SdteSas8zdMf/zxx6ff3xEHiK/ErZSvJQb0Ceq6xbSTzgxLSF9ebxMpSyzyPmNLfm7J/Xy2RYmUKXfvrK8mA8NNjkG6Lc7cWZy0MU3ezf+sX2KKxRmLicaT5TyJEcNnJunTJpP/XLCdB0nOQm7DrqGPCfl28ueOXK0Y/6TDZNZ2/Kww5rKv7ZX1G3/X5Q8asnpZuGjRdrY2/CBvJiuztcQQls0/mxzzu+UR0z77IEZTXsmL7YQaTpAuw+fs23w948tm25tsTvbW2qd/n+J9w/Acv+H3tpB+4tNobv7e+rzrWw2Lsy1x4f/JRJWrITkAk2czuHynw8+9tuJjAs5kPx1qkqUJFnmtKcro5qqbOejQ3CZlm+MyeM/vt0hzTrxoqATMnKDO/96mM89qak6AqKP5fAKVdFbuYuYkxlaCh9cvX77ojqoFEu7M0X7y3YJO9pkypj5oG1nYL53ZHO8UEOk7OQHIHa6ZELYVT8qs+dXssjbbNBqN3unLFirY19hI+lHSbqBPHVNGLZBQJjnGdfkDRbjgZXJkm5zE5S6t6cdsibyS55OOKGPSaMF2S8K4q9Mmp/mAOwbAXLhIuucviN7efv838Pfv3z8k45Og82EcFlua3zGhajhmMqfcN5nbvZZomV00/Liuj4uteTqG/dFP8nNLADZbaLhr/SRP2Ze9M7GzWGa4YHRuq/aNz8ZfXh/a7iwOJ54xB0mMmRgz98a2Ez/Tx+kfb2//+W13TmJPtpyFu3Imi9Y2+dxiQaOFPDEe2TtpIfbRtk88tPHIP3k2XjaebCLe4unWN9vRZ+zkSaO/9d1sIhexs870xd3UKYx1Nqk6beSQdtPB9MMFP45/sok7dFB+bJ9xhfjG9q0YvRyX8b8tPjVepxhmUhYnLOA92qZtoFiMttfd8tRE1RQ3TmTG04KJBdMJFFx5zPf8bGftjbbs3wRotE6dPEJDWqdtHkGwMdmW/IwsZvKWf81jCZjJcOSW/83ItslHBtjk0eRsAJzvE7A5rhkvAd/4avYyNObCwfSZwcIc2gAx++FEwxY1mr6z/+2IRrMJA4dcWOARlzminpOFkQP7ZcKYMhiZNnBvdKbtm+wodwvEMy7HstXuNmnZEqAWZEjHyDmDtB1NtP5yR8rsooH3KVCc7IflTtI4n1sywDbzpGnzy1w4+fPPP68//vjj+v79+/si2Pfv3z8sjk3bxJvBucGBOQ6cSToTwKQheSCuJL4kHlh8oJ1NsQDK8VK+OdlvccL0T5+0hbNT8tB8zGg3OZxilOHx3RhvdGSSk4tX+ayIeW0x3bC98WLfkwYuUtFvDPvslQ/GSwwY3DZZNVx9PH7/R7n5APm2nCLpmn5+/vx5vbz8ztnmZIPRnX670T0vPiSJMX6LM9SP6aB9H7m0Ps1mSANftiB+J64bPXeLLfyYrtl/s0OLQdvCMvkiro2dTRtia8ZpO0XCuG9jbrKxRWDrw/qzTbCUR/M1K7l4nvUsD7N+si1jUPpS46XR1uLAlnuQ/m3MxkP2k/aVOLvF7jvl6aO/reNcibGE1QS7BZtsZ0pvwSLBJQNhS46TZnNm9m30W38tgLcEa2RIoMiAnmWMOQPSXG905likpfHDsgH09D108ajb1L27W2Q2kyvZDbSbHHifshsap/+51nbjuYiRYxpvGxCwLVfsM6l4PPrvl1qhD/Kz+Vq2bfROu6TBkibKwfCkrZannlMH1u+J3qxLPQ4NWVqiwEBFm5k69AHyYWOZnp7xzRa4jX/rc3SWk8Wpz9Mes1s6k9f5PBPXxmf61ExS8ucPxidtjJjPoMhr2SdxhFhv45OXTFjarkPTgdmC2T2vpT5SV61suDV0G69bX/YyXq1f+oy13bDbcCvH2ey+xWIbu8mdWEQ7HB9JWb+8vHyYqNrC8JTMWbb40fyKdJpMGz/juw1vrZjMSL/d4/ib3iznOOnW5NbuG902UTXbOJUWU1nH3hnXLTbQzgZP571NWJtcKI87+EJakoYcL20rx8r3NkbyaHRysemflk02HMNs8C4NJ7zfdG79sM/GB+m9WzKmkqZn+rVcZyu3J6pjZM1ouavFI3FD3BagtyRlylzPhKkxnH0yIFtCSifjytDmDOlMBAhOekgfJyZ51LPJfFYr7f3x+M/KadJJeidJyHE3/gycW+KWD7iadwueLLQPCyZ5j7pvgYT2wXu5Mkib5ap4W5mbuky+WrJBWiw5SVkMDTkJyJ3VfChTHkdLvRjNUywotoBMmnNXfWhtScuM3Wy68c+A13bdpp/kyWxh7Cfvz/XcKZ5+Ekss4Zp6s2ORuyvp19uOvSWplrS1JMoSqruBwIJP9mn1//rrr+vLly/X9+/f3/n517/+9b6zag9jGh5mBfvt7fdxxzxFQv4pK06Cs/7Yo526yDI6aWVLolI23DXiy46Uphwt+Uid8qFeTafNX0b29hcVJ765sGkJI+k1vzQZcvWd/vVPS0v4895GHwv9ivJusWPuZWxvyXzS0mjcEsWTzLn4lPbFY+f5ftJ7+kHzY/7M52QrzZ6t3F0gSjxrfp33Wafdt/i65TNz7c4is/XZ9NR2My3e5Gfj1eIxx09cSdvOhyzSX6xsPk9ZWszj6bzE3WlDvnLnP3m0jaHsM22p0ZufMw4nxm2820aMyTBlYLadeX6O3eLOqbB/ts3Nn/T9lHPDsa3cnqj++eefOqA58hC8AY4JyRScffJzBu4EXgY99m2JS9KTwmYwzT4a8MyEZiYUttqVvNBJ8vdfNhYTsnznH0Bvzp/lFOCsrQEf+2HisdFDA96CxNQzJ+NYJrs7wSqTw+v6vOPH8RM0ucNiADU8WN/kk7RP/dllzd0hS0STXyZwTK6abM0mcyfRdg/ZLnlt5RRch4d20sDsk/iwyTz9nvcGG2xXgDv0GQi5Q97+JuC6Pq88m8zTtjiBuQv+lFvDtA2HH4/Hh9/D//vf/37/+YI96XQKJ6pvb296/Grs2ehttFsyzIQ4E7n8bAsJ23imC8ZJexiJ6Yh20OLUdX2efDFWTXuLsUxoKdd82eki29kYXjMG2cInfZMxIv2XdFlhIph9t7pb36SlxYktVjFRI461CcT0u9HY4ke7xvjUeL6u632RLWlsk2nbFR7a28INJwannCD7tzjAYvg0fNNfLY6fdNLabzG79WmxjfKgzeTn9uJPLkw+zAXM5htfU3LR5du3b7qokbLL0uyz1TNcpK1NTJ6FF8ZMtuO9HMNskwt2Ru9Wmm2ytLwr3xsvbEPb3l7P0Gg02aT9rt/cKU9NVNMQ0iAMxEmIgTUTAgs4Gcg4xnV9TA5zJyVX01mMtmlHWrkD2vqYIP3ly5d3x+VTNGk8FtxyVfPkbMNzvqfcxkBYTkDWSgsaBJCsf9cYTc9N56R9CzCk6+QwpuMpubPBScn0Pe+n3S0LTo2mpte3t99HLq/r938Ct2BBOngciHK0ZCRpps01u5q+bAFlA2XyzXrJi/mSYUnyYABKH2388wRC9jk2kjxzopqfLSk02XMSlDxteJf0NX4scDT/TR7n/mBfruDOU37zrzCmz5zM8Lfd1LPx0DBxZEFZzQmT6TMXdTLpyol17rYaRpiP57j2B/aWpFsSlOPa3zrwadtmq/ycr0xuWWyXgW2Js21xlIso7b3Zb0scLWdo/rr1xfZp28lfK0aX4Ufy1+LN3y2UhcmkxdUmV4sLeZ+LHRYHaRfbwmDSs8WEvNbwPwt90+hJm7aFmeyHu1fm+3fluGEbec/YYCf20qctt0ge8vP0aXbJuEieBitzotpitsXXk37zui3CtTicdYi3lg9f1+8dzKQ79cq++bmVk38/K4sWj9k+dUY/bQuxprONH7Zv9kMdXNdzf01zXU9MVP/1r3+9DzpHtWYlnEZtAWuIp9IzQUvm7d0MKeukgOazGVMLFJYQnAJy0jAGkEes+L9l49QERAKROYwpPXez5vV4/OdJm+ZwTT/NAPPaM8dU2JZy5Jj/pN/N+eY9gcoC6NwzuiwIbU5ssiRAN8A0HpOH7DsXM/iQqSYPtmdASDvN3dJGG23IAHbqDb30m+bPk+BtgcMCUEtesn1OJNIWUh450c+Su6Rb0Mj6qZuXl99P5Z5xeBIjJ0sMVEn/HC2e43Y28dtoNJulnKivKbSN1M084I2Jmj10LifqdwL78Ej5Ji/cvWn+mzY592wX6Q5+MekbPdhElVhDv9gSfLazxD5xccaav3SbfmyhquGFYUVL2ii/pNES2YlXyRd5otwof/pswwDjjXQlfXNkNxflWl7RaGLdLf5ucm39t8WA03i0e46d41DvowvbbEh7zQc8ttJkmXTerT9tyGNbSGGbtC/6x3Vd77ndlkekfXAxMuU34zWasj0npyMH6pz+YZix3WvYllifueD4CDHZ+OOuMHHndCLEFuBHF/Mib6ablB31YbbSsCIxq8m4yZS2Qv6JmZZrNbooK1vQmPrtAaC8lsX0Yf1YrGsYdSpP/0Y1J0Z02Ou6NPkjcJDhFpxYj0H0BAbTxkAgjaE5p31PXlMBXJHJJCF/p/Z4PD4dkWj0E/yHVxoUH6yT1/KVusnAazpImWTy1XRDubKcZMuxTu2tUGapiy1h4jgbACQtd0CeAH/irYEj66cOJ0Bk4nCaqFI2c23oTXulXOe+AXRLGE/+SH4NLPlqfWV7s/HNlrbEsIE2A+cd/th+2uVOmWEEA81g8NjBfM5305O9m243HZucLFCbXyY/m0/YOxd5GAyTH9o822SSPxPrmdCRdivN3tMWErPtt1TkJW3fJtv8nOOa/Q4dbH+KOfmeiyyGoyn/5JH1SavJYfPBlgNYXbvWbNrGJa1bkmU2lvKl/3KRh0lzs7k7cZD1N9/M78YraWS/hrH2OtFoOH2nrrXZMJvJvPG38U7cmhyP2E9dN8yzpyJnsYkqbYVyMFm0a4aXjXeTzWZfiTlzreUb1+UYs2FvjsXF583+tnzuju0ZHyc5nmRLX7rD96k0+ZHWFlfaidmc+yX9tljAMf9uuT1RzSMF3759+8BUBtRZSc/V5B8/fnxSoCXS/N5WfKnMpO0E8C24jdDN4Lbgl4E8y9DJSenslvBhOEx42A+TzuFjJsIMlGlsueKV31ugaY7OyW0LbE2+d8odR92ShhMocUFhgs3j4ZN7S0ByrHRwKwTfra8E9WxPvpP+2VVLX8n/N23FkigGRaN16Dz9t1/ra/PPlGXaa5PNKXHMxR22Gxnmrij7Sx/PCQP7svp8p1+x/cvLxweuzPv3798/PUV3cOS6rveTE7kIlb/5NIw2G99exhPtMO/Nfdruly+/HzaVq7zpI7SFUwDkuFYyqcz6I6OXl9+T0zlNkL+9YoLIXZeMPzkmF3cfj98nXSgzxsMttrbJa45N+XAiT1ptIkW/3RJjxonr+vjAK2ubhbuC7PtusTicfG9YnbHQMCFjx7ZDZ1ia/2Fuv0/f4r75xcYz69J/TD4ZOzKeZF8pP/4O0Pq07w1Ppt7W1xZrLU5aOeUO1pZ64v2xhUzsx3/4swf2n/5t8aUtVlI3zR5PvGYfmy0T5wzDsm+L2Yl103fKnDjUcrtcmH99fb1+/vx5/fXXXx/+l5t2n3qcvhp9Lc432WR7m/SxbPZpdVsf2/0pnEwmrXM/63KianiatpO4aLb7eHzMq42HO+X2RLUF7QysYzgTUOf/8eaPqwfgkhECpQFJm4i2+tf1GajpiKY8lpaEbcGT1ycRmv5eX18/HOvLyWsDNgtis/Nij72/ruuDvDlRHSMkPwmYeZTQQInJH51vSyg3x8u+zZBtAmXBI2nYkmkDQwNttmeiaHw1wG3jsVAm1nbGT7mkzbG9BYWxxZRVBlsmqvQpozsT3bQZs2fKwgKIyXkLZknLyXetTuvvTjuznSarbJN+mpO40Q9/C8QgOTTN9XxyOMds9m08bt/v3ssEM7G3/Q/v1LUJNvs1GrYYkjK3VeEZP/8ffGRJnY+eeKS5xSLDH/omx6G9tySh2Rcxa8MpSxYN220MJjDUCeNI6jjlSVmQzml/knGLIy3pPNk2dce2aWtjE2kX9AGLYWYPLVehnyeNGZ/Stzhhpd5zkWxK+gRpp3xN/1NS99kf5dxsx8abkjLgeEbXFjfMx8wXmEtup2GSvtQTca/ZZaPByobZxJW0kYZPuZub9sFdXvrddflzLAxrUmaGo8SOec3ElHFiW1gmf7QpYmraauZIzcZz/JHB3Ms+Nj1ZTmn8b9if/soNE8tVmH/dXdyiH5B23m88b+X2RHUmRLkjmAnTMDeT01+/fl3//ve/r58/f77/195MgIb4TGTTWMmETdSmcOKSDpLfKXgKmXVZ7tbLOi3RyESUK2/5nsHDgmC2H30k/zZRzdW/oSnr5mopQY38bckM6z1TWpstCWI7c+INtGws6nyTxWYLNlar33hrwZt6srHmWgsSufI1dbnLlfXIswEuaTMbMWBrALzJv8mU/XOsrd+Tvu371qfJi3XyL3ESV9O3zfeNTwv4qb/Gi8nOdGYB/05p8rAEcLOL7G8L+I23pqOUe0uosnDnzPDQaOdC5DO+cOK32fu26Jg0kfehces/k6Kpm/ac9YcWmzjbAu3dpI7lFEd47S5Gm58Z7dwlT/7Z98h8e16H0d98b0smUy4tHnAMxlajhfRYDG240vgzflqbO/rbJoV3xzT7Txqo94YdNpbRa1j+d0rDpeSFvnhdV52oZgya/ikP5ueUT963TYjE6nwNdnCiuuVitHujM9tPn2bPtGPStp24MHpI05aTtNhFupI23iOvFnc4/vRx1x5P/vVMuT1Rva7fRM5E9fv375/+2D2NZoyIu6xc/cjJqzF9UsqpjPHwyGvyxfdMHqePprzT2FuyYYEtjwN/+fL7AUwvLy/vRwEfj8f17du367quD3VbUGSikqtNpq9ZXBjdcYWKCRrBmQ7bAIdyoF5TXs02zB5OIJHB1+q0a3cAiLRsxfq5k8SSxlydNrCxpM90lslK0sOJkSU4vGYJf9JNnVoAnWt8OJi1t8DLezzaknaacpzrc818mHrk+x0bMR0yWeArjxDag3+4qpzXmnxnEpur65sNt+C38dps5U4SZ+Mkfk29oXtLXJmMsF/u8G3J98kHOLb1y0ku45VNMNtuFHkk5pN/th16jM6m64bjaX9Zt8VC9j0TXSbCFq/Zt90nDSa/KW03wehkH4yBTBZtApu63xJAszfamemePBJjmINkPcbuVsxWkq607ZeXz/9tP4UnL8j/8GsTm4a/zU9Zl352XZ8fstlssGGaHaHcfDL7mPvJa/Zlu193aDP+W6F92CKp8baVkx0bfzOHyPkE/7PXZJkxgbI0WVCm3MRpcs6Yu2FMixNmjxm3229G2fbkrw1v81qLV83H2SfpaHK4W25PVKk0EpHEj4DnIUJfv359N6ivX79+2qp/fX1VgGnJH4Hf6ufOYY6VRkgDbgHZHGBzRAvaWRpvCeB57Ozt7fdDch6Px3tyOvKcazkpODmjyerLly8fdnvz71j436DPTlRzXDpyM3h+twSJdU22TQdpRzae0WKBntfMpqy0sVvAM3rNHps/kCdeS3/IeqlrAqxNqvNzSwxYb8ZpfJleSKcFq/nOyRsDUksceH/z/zs4kYHT2lqfXITgZ/q7+VjSTz1kmQnrXZu1e7T/vNaSpWzfdJj9mf+abzwTEDMh2HzartuEljJIHtL3eHrhuq5PmNtkRJlkvZPtMoY2u6C+mg0aLayf9TimlYw3Numz0jDc6Njamf3xWpNd0p3XG685XrObuUYbO8XFVqwv85dGb95rPt/G3XRxyq3MNq1QllbX4seG32bvw8/YqPXLsvllYsp8585e0sscq9GWfbI8o4OsQzugDJPu5N30aMUmqnwxRpIe0kt8y+tJN8fkJNTsvG1k0L/aZkTKkPxYv9P3Vt/KKSaSNzttsekv5dn6vxuXr+uJiWo+CTGPBOSg6Qj5+6jZrct3e/jH3KexTD/X9dsQ6Kx5n7smPNLKFa4tecqSDtGAjH1MMm9OkO1z1Y60jOzn8x9//HH9+vXrw0M/cofly5cvH34Hm0e0DZDmNbuoP3/+vL59+/Zp9Sqdd2ibvvkbLXPquXYy4pZ8Wn1eS9De9EnAasHPkgsD3zt93CmnhMGC25aopF+wH9J2SpK4ipo7fGlfXCEkuGXdbGs7DeTnlHi0iSZ3T7MeJ6oWbJkMtNKSHNrGZtd5P995lDJ1aAtFLWDaODam8WVB8br6w+RSX3YMzBKEO8F1k6ElJzke+6Jvc7zNf09xoyUjNgYTHsqiYZUlXieZml2wDv227WA1fU3cs+uGrxYf8x6T7JYomW5Njs0vrFCm2S/7axPqkSHbZl0m8Q2H78jA7CfHnGs2xoZxWRLjyeuG43f63OhrbRJPWruGAeYvW2wlr6M72yFreSztKeXJ3922eGe+bDY3NNrJKOM1x6Dd5jXip/mK0cN7DaMmfufcYb63XUb7TvvPFzfisn87VdjkvcmROZLtTDMXmQ2ju76T+rE25ltbvMx6LdZZ/rLFOvZ9p9yeqDKIcMJyXZ8T2Qw2PNo0iVeuls4urCWUSQf75iTquq5PE+J27Dd5M0VQuBZoWpKUvGZ5efn9REgLfNl3tkmgsd+55qQ0f0e8PaiJYJrvQ0sCL9tykpK2kH1l4Gx/YUQ5WsBozrcFFtOnBbLNEY13ToqMruwjPxu/1/VxIaYF0mZTTRa0rxYc2ztp45g56Uw5zmeuxvG37XmPcjP+8tVWIw2rzOY4Ru6A2JGvpuvNf00nZocNd5I++mvDrBkz+TFesq9Wj7yf7K9haPPlk002maQPEofJwylwpo+n/WxtjM62Y8EJyCa/vM+TMY0O9tns1O7dqWc2YnGLfGyLViln+kOT8x3+tiSq1d101+qnf7UTJKfJPeWUxXRv8an5XPr+5ruWDzR93NH5SVeneHnH9y0/MpryGse2Rc0mT9bLic2G1RPjWgw2jJl+E9tMJsaT0XFd/nOitnhmfUwuOX3lzwNsvJaHpb+nHhq+MY6nTHKusB2LPfGWNLZdVPtbsc1eyfczL27GZd+0mROusB7tOvXC0uJmyxG2sZqd3bG/6/obE1VLANMZcmeNidR1XR8maEnoGMaMxUkwGeIkmLRQ2eZATTnb8bdRKpWbn+fevMxo7DqdgI5M3glCOQnlRDXf+Zc5OX46K5N6Az2Oy4CWvHLSyuPEcz1llH2ljE6Gf9LzFlxOzpN8kz4r1KclDBZAW5A0sGSiQ3mxD+5YND+jPI1X20HI/vJUQSZ2Wf+OXs3ep0/6iwU426Uin4kfBuAt2Wuyoa+bXkxmjb7U3+BeHjlryS3pJC+JWY2vLcGiHebY5ovNnhvfrb8t4JpN/R1cNztlvxyzlS1m8N1eNjb7PPkwedkSi5bUbHgwhXFifJYxOm3QxjWaWWjHJhuTCT+fZMOYRrnld/LffMtos/ZNLibn1BNx0bDH3u1z9ru1M/42W7lj/9nPFqNP8XtK5iNJl8kzZdgW9JPfpHmbqG540Gxsk/PmH8MbeT7Jy+wwF/QMXxoNM27mtA13ps0Wt6dO1ttkdOrD/iGj6XroTOxiPm2+u2F51ruu61PedJJxjss+SYPZ/t2+72Cs2c3fLU/9RjUJGkXmbh537fio8xRWOg4Vw13WFhCu66PT50rIPH349fX1/b+W5kFOc7w4+8j3zdgtAFBRttNmhpx9bt+z8PfBDWxyvNGDHRG2x7q3CeoGKHnf6KGeRg+cRCRv+QCdlHPayny3gLjt2OaK4AYa3NW1QJS0Gc+Uqe3qGY1m51kSbNrKrhWjNW325eXz0ydTL+wnecz60w/llf3kgtQGfkmLLcykX9lE1VZck07aUp5cIK+nJMPo3sopUCdfeS1lkLJImd95iqjZVkswm+2eiiV3mz5OCdlpXNLHmDPjmT+PP9mOetJq9BOjzLbbfV5rOx9MROhXk9hkQth0xdib8SLHzjHMNq1PO73Dk1WMlckXFz3SfrJdLpq0HaoWH5vNJSbYqY/k3/yJupzPprv00/RlPiSx+QT5ybEos7xm8rH+5xr/7qrxn3Iw/6D9nMYm32Z/LT5av2a3PBmW31NmPKE3DwK1coqZG5adsNH43GRBuedC8alkPEl5tHFOuHxdv3/qZv5GzOGieh7NnZ8N8qdzVoiD+eLPAjk5tpze5jUnjDD9Me9NXx15ZB9N5nfjMum7E8eTjy0HbLzfiRtbeeo3qhnAv3z58uG3k9y9y0kr/+uTAJKTBv5FgyVZzRDngUK/fv16/5wT1XmQUz7S2gyjJW1m5CwElylcETklL3ad42ygkMnZfH57e/swUbUgaLxSdyPbtvNsfHAH/Lp+B4fs/8TX9MsXHZVBxYLz9NWSMgJk0nUnWJhTJwASJLb+21hbkjT3U4fcgdvs0RKBDRBTdpnk5d8mTRI29fMeeeT4c43AbnXTp5ufteN67HN4YN8mvw272mez5wT1zSbIZ9JN3bdEJ/lo18mftdtw8+TXpOuEAa0Y/61evnOh45SQtZI6sET1Lq1p53fob/fbSvxme6e/2uF72h77TH5Ix7NYx+vNtw0D+b4ddyWvSa9hNvm5ro//PTrjUTbEy6nHBbi7OxObbzc58Vq+b+WOP5gNjExMboYvbdNgw50cP9/ZfmRgccAmHLnoyQWTNg5zjhOtJxxu+Zb5Gu83GzrJMnMHxj+j/RncTB1Z/Jr+cmNj8vl5zf3UGfHIZJe0Ebt4Wo47yIYDaasmE9JB3Gyya/i0tWmxuPFudpXlhMNWLFb83XJ7ovr6+qpOnMFtHuwzk9WZ0I4RcbX2uvwR4+MEmTBknS0gcodudlV//vx5/fXXXx++b0cDzSFtgpFlA/5MeptyW6AxELMgmc401zJYzgSewc90kN+5ynhd1zrBMF5IW4IfV6/mPcejjPiavvn3SANsOQ77sYdNjewI0BvPvJb8mI1xsmP6NN45Jj83PaaNpF0kv1MsSTa6W1DkTunUm4Wr+ZygzfEYLAzgydOWTJrdMDFM3tMOKT/KyAJj05fpijRlHQtoU8zfc7Evnx5u+P13CvFrC5KmB+rDeL3TxnyAcrLEZ0rKmb6WOr6TcJHnDeNZL9vTH8ZP2YfZjo2z2R1fc4/+kPcNJ1rcm/op/+SLNG79WKFeTvIwHzAbzP7zOmNUw8Hk0XZlbRGA8bjVM95aLmJ0nWy5yWIbp7W3/ho2ZEncbzbQ5D3j0J43fqgr2nvmkvz9osWXLPwJm8mm+dZcMzzMPjY8NFs3zOE7MXN0x/yJi/l8tzzC+t5kNHldPtwoJ6pZtpzC8H90OPdGVlwMHxuwflMmTaZ36KF/Jk3Z5k47i52b72++TvvafNz6aKdcnilP76jS8Kdw52p2XHP3bY6fvrx8XLXN5G8mvG3naYoFmjEEJrh//vnn9evXr+u//uu/Pj3WOo9wjCPMO39QncHKjIBAfAdkt3ppqJaQWt2WfGTJgHsKgum0dF4mM6l7Sw5zjGnfgpW1HVkYrQko8z76+/bt24fvlJ/1mQCbPBsAmYxJDwPeCTQscG66sqSk9UvaT6C2XWP/lMF1ffz/rwkO+dCvxIGkM/udyS3p2BKApHGTZSaFaZdDI3nNpPOUPCQ9p2SlJUpTcnHIdM2gm33d3ZVpNJutJd5vdJEns+H0L/rN3M/6I/ttskl+MsakL2TftK0ZhzsITYaGabS1LBk3yP+WENgxuY1/0r61yfGpM56iSXqzPe3C6Mj3xO3UidFmn+nHZq/Evuaned/iFGMi+TdebYeUskr5Dk5aLLdrJqeTL5HXJgvrN/k2rNhomranJ7Zu/W5YmgvrlH/rd+NvFrr5DwjNRjf55X3yY75i9mV6NH9uJ8WSz+a7Le7M9012d3KkzAcyfpHnyZd4zNdykrFF+zcSs8mcY/DJuoa9m66mj6xvMfFkF1M3dZY4YDbX7JlYyRfrWN1W7mAFeWrt75TbE1XukJjhc6c0A0Qe+WOyOhNTOl6byDTja8nSjDXjprHn8dABonwfQ2k7RO196EzD47WkcQuiKXPKKHWRbbaktwV7K0ziRoap8+w3ExkLLJszpdzyXguqrZ4B+Eyg+TAv9p9839Ex5ZPXr8v/v/Mkc8oiXxZ0sq4lZcajJSvWLu+RN+uX9+c7dykTL5rdtABDmki3BbE7pdlivrjL3xJA+nOTlfnIM3SeeDbMPiVHm8/mOHd22M3O7vB3Cqak9yTHE74afdvnxoe1ab67JRJZzC8tGWyy3nCUhbaci76tGP5lsSTbaNxsabMbO7KZdNuk/2452QPj7VzbsGuz7ZRD+3uS5DXHNlyy/huffLVcxvg/xReO0zD7uvzJ99SvjWnXWixperF4bbuoG+/U+4Yz5O8u5hnGmw8Y5qSN0ees/6yfCzRJf7M3k0/jJ8eg7GcjiafijE6TifnjluecYjXrZL5nfG2y2HA476fPUKebbTFG5KvZnMUoo3eLhY2nLVa08tTR3xnEVmrymO/r6+v7MeCXl5frx48f70eCp5/ruj48jZZ9t3G2Yxy2cpgv26mlQwz985rjwukkTciWtNJQDSiy/vBGx2qT9nasrznmHTDZgmuC1cvLywdd88hSfrYHdLTxWRqQGqhwgeTxeLzbV/Kfq7nDFx9HnqBJ2zI7sBMADMB/5xjElvS0ugShLZEg4LUAbLIw3XCcWeQZjMjjqPM7d9oH7XiO+NDWZ1w++KbRYoHslMxykYl8Zx/m7/luIJ9JLu1rsznTj/GchfKz0myI76Rxs4H8bIFq8yv7CYDFhuYj1HmTTeo1ZTE0bDzaWBbLNj+22MBYZrTl/ea/zafNVjnG4Df7PuFR6pl42/S/XbOxLWYyviROtDFok5u8GX8bfWZvnOywZB+2KJn64M94BkfTtxnfOM7wkLhL+VgOQhmZnVKG037+r33iQsMRYmbyyF3p5DfpPeFd6iQ3MDIHYGxpOiGtzedybPtM+Zo8k6d85d8R5rNfMu9hLpt4Y3LLPrhJMfF8+uFCAheOjP+kreVeOTlNOzSfzLr2Mp3wGRS0XcYB5gvJQ4uXZgeNtq2N9WHYn/mK0ZRyZbxpcTTH2njJQrxrOcBWnj76e13XpyNxdNoBkvxd6zxxNuvb/3umkyVwMnnK61zlovFygplKakeOhoaZgM1vblsSMe93lN2SkaS/OdUpIcwjRHPNQPVEI8cyGq/retdT+1/X+ZxytcUGA3ibnBs9z9A+YzCQD6BmYDKHG9nlhJg6adcaz1YvdTm7wSewnWvG9wkU6FMGnHnyIX0o/cz4yJLBbvrn4odNPloCdycxMP1nmyanzT95xKolWkwIbKxtFfa0W2l85XfTu9kd21swSj8mrSe/S2zdStK22cC8bNcpx76LG0ljW3yxIJxjWt2TPZPmbYKa700epCc/p/5sRyTlwPbpny0uJb2Mcc0HsqR9nOJS8p0l8bnJr411sk3KZfMtjp3XTot7zHWo59kQ4CkU4/fx8CP6XBwzPZNv4nuz01PJycvQlg/F4RP5x88zfzjZPP0v6U9+cmJkdnuyySzPxCLDRt43P2QczH9vyIlqYiN5ykkscYB0zj3GssxJUlY8JdXyUMraXrTdHPsuDlOmpzrG+3V9jvF3sK/pcKPXMH17bbwSa+yVE9U78jjR2DahDC+eKU8f/Z1iq2t5jwH69fX1ExO5ozrO8+eff75PWHOndQvwY8AG6hYomnOkIMfRx+EGQNl2M85mUAaGJ2NgW8qc39OZKXfKaQPKLbkYkHp5efmwS5ZPfR7d5rhmzKdkrvFudG1Bk4lM1h8+MknIdlM3+b6TeGxgZfVmDPJ7JzjfkQ/lke0bCE3JwJMr0Nf1ceVsm2DN/ZRzHq0/AXPu7tyxG9Nj0+2WfJkcLCFIWby9vX06skSMMBxtiUwrZleDW3fr87olR80nG26wJN93eDG7vLOLmrTkuFsAZptG04n+Vn/zsZNcGj4Tq5r+iFlbfGyfT7JOuiy+bXGujZO+mf3PvclDuIvS4j7Hzv7bCQOOvxXDbtJwN+ZPX20BkXlGXmOyb7saRjNPRRnd03/DyeSlfc73pLPhfvP5lA9lZLaVNskdPJPPyV+t2ObKJnPTicmSdOTGzuTS/EeH1NvIeuIC7exE28hv6uZCuvH49vb2vnvOQh20TaO8RjwxzLNxGk9Wr8ndfKDFl1MMPMWORsO2O508bvOSxErLW+/QlhhN3+QpEOIhabhbbk9U0zgmOeWqZTOgZCAdJJ3s69ev17dv3/5D1P///zPHkNPhpnBSZMCWtJ0mpknv9Pl4PK7v379/Msh8ANN2TIEKnTFo1DZhpRwJJM0ZGLCzL5uwmo75mXXMJrgjNqul+VdGeY/B3PRpE9o7wL4V2kfKKIPWgLkdC6K8eb/p8yRbynWjn5/JzyY3G4t2Q2Ck3GbMnKSl3RtYEhgN6I030sDd+7EbS1oot2ZbM37qmGCassnTArmglvzPax4CwSeNk0YmDNflu7rECMOYTFTY7k4/KUs7AZH6Y8KRCdEWE1JeKWPS2WzCguqGrVZ3oyuvm3+Z/ZLuTOrYnmNYgnY3qJsfTYymb/FzK3flbX7+DN61MXm90c3Y3GzLYj19h2Pcwer8TPulXjbMu66Pi8oW/7KP4Zf8ZCzLOjkeMZC4mffSdqdv2uzdQjmkfWdekMV09Hg8PuwikrcsGcf51zK0V8PSU8zgd44/PFHPm1/mSTSWrMO/gsyfSRiO2JOLt8VMy9mSJ+YO6QMWD6f9fP/x44fS0Oyq4cMU86+81vB+s5+sn3zmmHPfFq1tXCsNb+mvOX6Ok6cTjH/DZvP/UzF6LFecYgsZW9y0cnuiuiUp+Z2Dj1ANLK/rs8NOoJmJDsfKurnTSSFZ0kxnIX+WuCS/U3JFaj7nU5GZxGyBMGVgSYm1S/6oD6N304sBbwPcbGc0kRY6SLOh6/r4V0RcOTqBE2nZrqeOGNzJ49CRu8WUUU48Ri8Z0Jt/GMBTNlZoo2nvd2Rk/WeQnu88XrbJc0ouDk2xpJXj5nULdAbe8532kwsmpJlB12w2/ZcBjP3YXz0l37Z4YbZHuSRNSdsWuLcX5drkzD7Jd76T5pTL2E/SvfWTNBo97dq0Nd4sPp3kvSUoG34bXe37CVON9hM9zXaafvO+9WF6NZ+6k2TcTUQ2Od/FNdoBxz/R0uRoOr3L16l/w/LGb/JHnGMs2+yItpEv27XZfObv8J/xz/I6a3cae2tni8kn/7quzycD82cGp/zKaN/yptRl2zkjlmc84w74dV2fFtnv/L1O0nKKKUlv0p30csGDtHGB0+R2wgHLIZrss88NV0742upu8THfbXHgjvyz0IdSpg2zMu/McVucYD2j45m48CymT7k9UWUSOoJpgcWMLoWUu2wpuPxfJBN2Gvs4gh0vzWK7O6SZitoC5hxnmN+tTpLMv74xMGS/JpcNmBMcNuNLnpicpmw3mdxNyDawTScyGyKfTPoT7O6AZqPH+CKQZlDLRRA7dpL05w779MFAkAsn1FcLdHeSXspnZGgy2cBr2o2NpAzmmk3ImnxzwsKJPBeLaAcWoKavGT/lmHQSB2g7OcFMvVtgNL/I5CAfaEJ7TNpy0p+B+RQAE+8yAKU8jC7qJdvcGdOClmGJyY12dhqv8Wv9ZII24/Ga0XXC0i0ZyHo5ZvZN3yZPxuedYvjWaGzxZktA7tDaZJNyN5lzwc7wZ+PV+G48G793sJQJGuk0+zEMPvFl4yaf7bvRnz9Nyclq4hnbc7GROJ1HRvPoKOndMHsrhhmnTQO2s2PBudDb4jjjMXdPUz5p04mnPO1Fvow345u64QTPNlxarCXmpg0Pj/PvFXPy7/F4fPjrRfaTtJAOToZz7GnHh94ZXZw4zykjtnkmbmQx7G+2mgsCTeamQ+uz5UeNxhaPjQ6T7ejYHgDa/mrn78rUcMVw7bo+/0S09XOSEctTO6qmtBMBDGIWGBJQxmG/ffv2/qTg+XG47e7kbiZpIa2ke0tmjEcacNLDFcjNQUw2GXxacCB/CYxJi7WhPCwgs74FQAMCC7QWhFmMR07gWp9JWzr3HAMyGjaZpGyMl9ytI9DkRIQT3Twmn7LjgkTq3o5sNXAc/+HK5Un2TRdNZhmArV37vtliJhusazSbr9jChiUaj8fj0wSVD+K5ro9+bIlUkyl9hb41NKeNbIWBKPnnuOanrN8WWijflO3ms9nmJJuGubxvOMC21HP6+tYf6WpxqiVJLVHZ4svdQvr5vSVRSRvpyrb5dNXm2/Z+XR9/D/4MDe1z+sNcT9oYRy12cUwrGy7Rjhrv2/Vsa7uP7Lv5ndU3W2ZhHxlX8nqL84ybyUdiE0+mNbqNHsog+WuL1iffbZOKzIXm3TDP8iTDEIsp5C/j7bwbNlAWLUa1EzqtT8YR8s2fpiWNlGfqhX6Y/TPXyoWO3DBKuuevZZLG/E9UyrX5IHVG20ieiOeGjVlSH9RxLoiYD2xxhbQyrrW8i/Sk/+WEnz8nSh8wGu3dcL3hp8XaUy5DvpqctvLUb1Tn/e8E5A1wqbzZqfz169f19evX9wcs8Y+Gp37b2eW4J4MnXQaWFqjHoBgo7gS/BB0DJgN9BtepkztipwB30l86SvJNfREwTq+sS7pMLs2BkzbuahnItnI38SHNSVMmgAm+LYjmWOQ5F294vbWb+hsIGQ9/Vz5bomU22pKODJhWzEYscDT7mN1wTk5TV+ZLzc83+bTAmTY59CRebHxasmcy2ui15Kb1lWOzTsMg47mVO1hMHLCFq+Sbn9t4WyEtRtuWhG4YcrIhw7dT/TZW0k9coOxaO/Y7nw1f79jbSU60c/qhlTsybvZJzJkxT3HA4lz2u9mi2fUd2i2Wb3Fz4/Fuab7I+9NvwybaHGlh20yyjYdpYzt7xLd5b1jHts/GxCwmL7N58s3dPPu7obRNns5qu8R5mo8P8TMdzNhTKN+Wi027ebZM/kPG0J0L9VzwSPqb/Gn75kcNP+9gR/OT7PPxeHya+J6Kyc7Gz/rEVeIIbTtP8bVFGfLI9xOOGy2cyDeekrdT7LlTbk9Uk6AGTmZAU4ZBnvOfNjMxnacDjxN8/fr1+v79+/t3TkqmmJEZXayfbbKk4slT1k0jmXu2U5O0MPmxZKIFNvKUPDRHumscyV+ulqUTJW10nmxPG9nAiIDMMbIf6pArkfl/rncfsGNgyKMqHDtlnUd4Ho/f/xO3AQgdN2U54JMg1J6OZ7Kx9+YrST8DkcmI7wwSzf+Sv7xGXZiOrsufImzt88XfFs9uex5x49i07eQhyyQFaXMT1CizlHMuJpFnYoPp3QptnAEt+yQvptfEI8qciVbTl9m3+TdlamPymgW/DeNavGJJ3bfkqvmz8d+SqC2RSFvh9zzVsdGdtG9xkfSYveczIxo2sGwLmU0HjCEpG45h3+1l9U12/H5KvDassusnu2u2u+UtJsvBpOv6jOmt/4kziUs5Zuq++fwzhfZodrvlDMlPHmOdHboWa7fcpNE4JfHQ8hPDi5OMLFcj7RPDuAOZ+UGeviKuJD128mg7ytvkPnHz27dv1/fv399fc21yrqEzH5aUsTx/J5s0UzbceX+2nPyZcY8nSNhPTrwtN9mw5rquD4sChqdWuGuacYgLAdkPfY1HzbcxjUare9eHGMP538Sn8tRE9ZQQWN1MKhqIm4FmopWKsv9XtTEbIM1nKov02sv4JzhuATKTLNKTsrCAkZ8JhFM/nfoU3Jvs5nOurBmgEQBsMngKku373YQy6SC9eRx3o21zKL43uTN5SH3Y5GAb+/H4PVFNMM9rLWmmL7XrlEPSvgUG6+dOaf7E0pK/6/r8v393gkKOk4n7YEteo78ZjSk77tTmES7DEba3xIE2wtVpo8nkk/YxtGY7fk/+DHdOsjU9EPvps1tClP1vNncncFKuW9ns1HytlRaHTjGA8je7ZNKxxYcTjfnZxm78UGZWGs5sOE8b5aLOdX1+OuXdhOtOOWGTYWYb2/S84Vu2y3tNF1n35Ms2lumFp3LyxZyr4dZpvMbrFOp3i2c5UZ342Pw/+bhLL2017ze6pu3JNq7r84KObcDYzll7gnGTafPdrVhekK/8OxzuwA5v7eFNJj9+pqxMlk0fLCdcHNnlQmDTX+aVRofReBeHSe98brF/6Gm5EG0/7zV7PvmsxaM7/tT4u1uefpgSJ4jG7BQKqJ17vy7/L9S5/vr6+t6+7agObZngbSV/GJ8gnMZ8Wj2felswsiDLBGg7BmjjJDAxoCcPWbZk0q5Rlk3f+Wj4zQC3BKXVs8BhgSH/rmTkQGC9E4CThtQ/V3nNzs1+WGzs5HPGzVWyDMYMyqdJa65YbqvNKTPapfFEXWZSZskA6WJCsdmhyaeB4wbIyb/tEp1A23Q67TK42dG0rLvtXmcZv8q/6rob8NImZiX+5eXl3X5Sfom7pt8NUzbsy1cLlq2QDktw7rSfz1uMajxtiSgLcYp2RTlsiVmujOdCBXfsjWajl/wbzfM9abR7bSV+42fzY5NrfuYDdLbcg2WzAdYz7GwJ2528h9ez7omHk32mnpJ+q8fvp7ETx+aVzwcxu75Da9bNGJC7gE3ejMMZ8/i3X+wrxx3e+fdFGz8n37frJqfUUeotYwf55kSUD2dssZjyJ49WzN5pK3nKMX+Tmj/HSx38+PHjen19vf7666/r9fX1Qx7DCfqWZ5tNJk+U6VYslxtc5XUbK/vnbnXDzRM9psv2Tls+5QO8T9u7E9Oaf6TsbSzWIx8n2bA8NVFNwGoJPssIIycSVpfHANpEKY06r2UbC44tacgVEgILAeak2C2INaMfsGpjUKnmUKeAvwEzV4ZOgMx+EtC2JI/9WGHdFujaEbzH4/FhUcNsyPi3iQInqWlvdwN1lgayLajO2DNhaRPVlAflkseFGPCY3JxAtoEqAWtk1wI/eTV5tqMwNtYmZ/tO3p/BC/IxhX9N1QJdngZJ/Gm2bhN+FvNL+0/Tr1+/fnoieVuFNz7ow2lvdhwq321ybrohXzPmttjC5GELmpscE7+2Y1S8bvfyumHk0JD2bDTmokK242Q15ZTyIW4lDo6s2g4lPz9zXMwSPmL48LcVww87BZF16Q/zuWFGyiz1Tv1kQmrxorWbsXna6ZTgUQ4t5mTfph/GOmLsyGD6mjb5H/fTzh6slfLJMXNsq5P1Ho/Hhyfm054Z3yw2k1eOT3mMDAz7UxbmT42PlKnlHkZ32h0XU/nvETauLXZbsTiWfQydo2/mTHNtbCDx6fX19cPYb29v7xPUmbD++vXr/Rhw6oubN4breZ+8NB1boU4zz8pFQcayTZbPxhvq0xaZLNe8rv1Bj3dsN6+xzV28ZNn4b35lcedUbk9U8/d+9tu/JISfM7iaw7UJrAnKnDYdxICKrww4LQC1pOhOYLGyAaYFXSYYmwwakNn4DFpNhw0wWn9MwmwF0cbZrlFncz+Bn8lFgkcmY+Q7+2hHVwgmyXPKr9kjnb0B2ynBMGDJpDyDuQX7lBX10XykAZ/J2QrtodV5trTEgn1u2JE0teSGvmEy2Ma0ydlgTP42ti2o2CqtYYjZBscem5jJ6pb8ZF92ciVtzX5LTXpO9rXZwPSVsqB9M/DSLjeZncopFrV7zY+yLjHe8CP5y4TK8CbrWHxofG82tvnXJguzAYszxvtmH+Q5650SK8qb/VmhfjY5cuy7sm/tKQNbhLc4Y/Z1wvcpmZy3yUreT1pbTCO/tNFZ6GqngxjTiDMcb4thqQuzc+p6e5m+7BQX5ZZxmd9zwS8nqlnP6D35bMrArjX7YFxifmwL5fP9r7/+ev+NKv82ZcZkfDVMv4PVTZ934oL5+BYbSZPVNf/kZ9o3C+2Xn7fvKWPmx433NkbD4zvY2eLb9HM3Dl/XExPV//7v/74dRKbYynQ6pq2u5P+o5tNTTyCb/TbgbglhCwQsLRjld1MId1AaKBDETdYZKLjr20o6Sa6Okq/mTOwrjSz1l31yJ89obP1QN+x7+htb2ZLvBsL2wKtsawmf2cysQPJI+h3AGzpy8cdAlno0eVNHI5e3t/8ckZrjNxM4cjJjK8u2aEMdNv8egGQ/lmQnzbmyvIHkBuKtWHDJ6+aPWahTGzuvc7fo5eVFd14zqeHDnWhr9Iekk/xwBZyTV7Zh0pH4Y4s78wAT7vDbkybNH003G+6mX6UdcVdlStspfDwe6jfZPrHV+jjZ2xZD5n7ysOGDjTf6mtJ2mLKfvM5FNhvjLq82DrGFp1YyvqXfN1ywe7aQ0+g/ndBgnw0fbCF83k+YRJ4ZV5iH5PWMLbazbXJgLN/0OfKxnfrRz8vL74fTbbLP+Jl9jM3mwlb+x2fuqNqCarPrJvu8lrTkA/bYl+mr9Wn5Ip/aO/2YvQzGTJ3Ml5g3Nb7tdMHYV8qO/BFL8/+5h7evX7++f06ZcBFh8ovRa578ou1lTGH+xXyJOQdzDZO/xTWOm2O3uJT2yj7NNkk/5X06CcSSOsxrbRd16ysxzTa8yD/laf7V+mBpJ2aaXW7l6aO/RviWBJIR1k2CCeRtDBYaedZPp0zgMh6a4bcAtMkgS4IjjYCFybwBatKabe4WA61Wr00wrV3qL+s2+kw32TcXFHKc67o+HENJgMs6aUsG5qSfgMT2mTyQ36xn9mByJgCzPwI3+9ps9du3b9fb29v1/fv39yDy119/1QlFK/Qt3jN+tyTKkqGUU8rCXnbcyXzx2WCQ47ZitrzVN2yk/42d8z/l8h53XvMJ6DaWYY1NGqYddyyMvvk+dfNvxCwJTZ4pJ/PZk9ws+bWgl7bS7PJU2ikWo68Vi0W8bvbP3SomPVPH+jHbNFkwKTN8NFmZLptMLeZlH629xRUb+1m/s13dEw/EdtZvOZHpOmnJPptdjc03veSYpi+Tl9nCXX6ZU5Hn4Y0/L+DnthO32VbD9JaHkKa08y2ekb9tTHvZuFNy0jX8c3LKncc78XnGI29bfEs7GN9I+/r169d7fsVNAuqOD38cHW/jzrWGBVwMMUw02zCdNaziQkHKJP0u+2sLsPxOeq0+aU+Z5DsXNf5OMd9K+kw3rX2LucS2ptu7MTjL7YlqSxQ3UGhHtO6MlYWA3hRuY2QQtl2eWTWZY1UpTK68nQKdJR003re3t/Xva9hP8mF1T3WyTwtsLfhacLdANSWPpbHudf1+OMxGP/vOld7Uxehx+pu+aWtMbAnElBnbZx9DT4LGnADIvz3ZEh7aF/2kBToGBzo8ZWbAM4Hwx48f7zuruSNGID4FPfpjS35asmT8sT13ASm/LfE6JSKndwtSc69NDrdieDCfbcfHdJqJw9hD2x2gL861/M1Zys0mgU0+c3/+F5YT1UlULAHN/u3vCUw+trvABC7xzBKxLXaY7Mdft5h26sd42u7dscONf6PFdN1s2/jYMNvsotnwnbGsb+J2oyX7p70NZtoC9cZbjm1yMCwynjbf37AzsZ6x97r8L2iajBhTjQ6TX9qZLaTRlnKHjZOuNg5pafxYH3mPem98NrtJ2djkLHmnDJgLpTyIQXktJ6o5WWX+kuNteJL0clyzhYkhuVia922XPXGe9HJHPMe0/lhne994tg2KrZ/E95SZjbfZXeMj49GUPKlDXLGYu+ma9Gw4bdeIIbxuWNVwmIv3G6Zlm2fK7YnqX3/99cmAt4StBahT4CNAWJt2/04gNAWOYHmUYox5rhEwNgeaflsCwb5zzOnXVlHsmBcByWi84/SkkYlek90m/+HxdJQubcs+054ej9+JcoLj6QFDSYvZpSXsQyPlkMegcgLbZL0B0Sm4NjvKI57z3o4g5fGcedABH+1PWeaKqemw+SD1RlukfE9AO7RtxxWn3F2Fzj4Mr2wxI49ob4Hr5G+2mmvF/GF2MueJnORhbODl5eX9v6i/ffv24c/ZN/yiz2w6HvrHVr59+/bJjky+tgtreJZYZ/VS3sSRKcRL83/T33bf6uf7M23Mp07JWUusEpvGFkzXp5h5ottiIPm5EyPZlt8zLrOknAwrmxyflUWzrY0/5hQbhrMf27Vp+ZVhA/XO/IL9tdh3Gne+T72cnNpk6+Rv9pnjZml9b/EhfwrRXtku8SL10vIE5hiMmVaPcuPkfpPV9JVYnDiXY2Vbsx1eb3kX+WD/mQsljcOf2dDYLOm0CQ1jw7ymTBvmW1s/efx549FwymR5wr4W60wPhn/ms8yvWOhjWW/Dsfyc+uAC+52c6I5srNyeqNrTVFsQpLBpWNflAHxSLOvbdQNWGqAF1CZc7t41R7b2NHQ609DVgn4LqG0ctj0ZhYHMM+UUeFLOp+DDYDHX5p3BwxzbEhSC7GknYrMF4582bUF8Pm8r+qdAzsJxcsLK/zfLIJa7+jPheX19fR+fO2L55NE7QTe/mw0ysbFd+Kx38gnWp68/I0/yNZ8tEPPeCfBPpQWWvN4SdvrQFP6MYOqmvfD6dV26sk/foo/R1iwQMoEYW5x6PC7MZGRk0BJUSxayDheSzOfMjsyeaJeU4ZStXYtl/NzwIj/Tz/KYuPlSS8LuJBF3E44T3Vt908PJp5/F0FPuQNoalrU4ZzImf62/ljNZzjD1U+cnOfDkDOnlYg5txHzMFtHJ/x2cs/un68aztbNJaS7s5mm36c/+GiZfySNlYTlJyqHJrMlqk9dGW9ZJexkaDLtbbkXZWj3z2S2GZF93MIg88h5lbfmjTerbCZ8T31tpi6Tm39nf3RhwF/OarE51rBj+kCbT7bzfwagstyeq//73v6/rutTBMynm/5PSQHgm3wSQjN5hZquT4E4ntZWX7K8p8e4KXLahI2SyyH5SfqSBif1MOrYglnzy3QLWnWT75ER3y9CXj0WnTBO4GgjPtUl+cxKUO69bIGl9ko4Gei2RYdvUyxaM+L0F+fG7/G+zlGPKbh6SkD7IiSpXd/OYT/LN99zNznuWvI/88xhrtmEZ3ZoMt+SwBTPr3/Sa7UcHY1utH+uPMmi63xJY7sImhib2zq5pjjN9jJ0kHbSTl5ffT4lO3LJEaJOtTYQT46Z97sKm7JPXsU3+JpYP7TDMSx/NUwWpL+rI4sVdfbFsNm18WtzZMNb8gTtrRiNjVfOl1Jnh2F1aLa62hHVrnzTZPZaN3nZSJMewXZI7ifS8b7jNPtMvki7SaG03neT79Gd8cOJkJyMGs3lqgX6Y122DYvMLJuvsl3zaZ+aS6R+pU5uoTjv6ZGKInTyxmJHFdGP6sWtT+F+w1s/WfuQxOcvpoYxGV8aNlgObfKYw3z3hSvLVdquNx+SVvtQWY5vcsl/TKxd/UwaUxTZG9pnvdo/X7mJv+ljqgXmN5bDM00+YeCcmnMrtiaqt6g1YzWSJKzQDurlFzBXe7C/HOTHRhGNgMZ8zCCR43g0+bQwD5s0gs+4kvVyhNIOZe9fluyUJjkwKSdtpYsCSY5OmDVjsc+s/nSBBpukl+Uu+uLI8D7Ni4p0yMRoNYHPcGfsOyFrZEpjpO+mwJDIBN2Xx8vLxz9rNJnJHa/oYuSew2oMRGLwZnDb7oh2anFvgpZxtMk665noDVX6mj+S4LThTJxvPpk/ythXz3+Rv9DhPGbYnMM4xYCZUJ182f8j2+b0FRwuQ+W7jPR6/H96UiaIdk8sxbPKXeGEnW7aFPRvL3pv88jsxaPyRcj7FE/JtmHSX1vSjzUdam9Yfr2UOcTf+WtK02d2dHKEtDlhb4tM2NukkTaQlcTfxa0oulOSk6uXl/P+mZq85ZpNNszPSRR6tvS3sbXbc6o6f5NjZv9mF0dviNhez58TRLOjmRJUxwnjYfIwyoD7M3xOzzAazf9MxcT7tKOU47Y2eFrfSRue75QInXLJidszFQ4v7hk3MORoGbMVyFU52h/f23/XJi30mRj7jL0ljix+0BeZZ7P9ufmI8NDpPfU15aqKazIxTD2gy6Ns1M2Y6+zOJ0LxTMI/HQ1fMqbhnHaUpqdHQeEn5EVQoY/ZPwDf+2IagnePeMRQmFBxj9Eo6KG+2NTobiDW6ruvz3wrM9W2iwpUvKwlAyY/JgAswW9kAx+yMiUfWJY35l07JJ4M76R5AHVlawpx6TrnmhJarhyZb+ofZCe/bX1UNPyl7oyttghPbRhuDHeVlk/+NJ07gTfe056QpdU5aU99Msq7LH4Iy2Gx4YwkSv98J6kmvLaSQb2uXPE1SNXGHE1WTRcYY2vFcN92yn6Rji0/Nb8lLxkZil/l145GYaRi60Ul/znKKeVnvTjF5WH9b2/xuccLiVJaGL4ydrV2O0ca6e81wj/idn9NOxxc40WD/m92Yv5DXpIE2mr5DHOQi30m+Oa7ZFnGTmGx4zPES8za6Ez9//vz56e9XbHfMcMNk22hrNkNMoN2Zj+Y12qjFMv6v9xTbTTcaTZaTUyQf5Jf9tZjHOubz8958usXNzebvlsTqoSnjfR4dJ0+NlzbOHVpIl8WRHNc2veaeYSw/0y4bnWa3d8vtiaoplwZvnxuovry8vB9DNCDNcVogMWBKxTwev48jZn/2OR2LY+e4BGnbArdySiKYrDQe2xhbIGf7lpw846wb4CQ/tpqW30dPCcYEfLMJ8jbXCbRDQzt+cV3Xp6MvSWO2N2dux8JMtgw2yU+Oa8HU+hubzX7nv2UnAJkf8jesX79+vR6Px/t7swMGdQvsTV7NRtpn82PSkXhjpwasDf9XlGPySGm25aq9+b0Fzdn9y+NiXH3dcCyDAHm39vx98cvLy/Xjx4/3Y+F//vnn9fXr1+tf//rX9e3bt/fX2Agnf5v9G+40fc7nO9iWuJHYMCWP6yWWtDEHVzKR4MM70k+uy3cXWiJk/GQxm+Z7yjrtj/1T1ukD3OlPDDbMJhYRs+9gkfX9TBJyXT4RGRpsrCYL4lP2vWFui7mkY7N/80v2zb42vD3t/s04qd8No08ySPry2jYBs74GZ63vNl6+n/zYZNHsjnlGW/A0/7O/jjH9MwaxtDhn2EnsabuR5IHYSb3nGKS5LbpO/YyjaQuGNdRV9sV8gHiy2SbziGz78vLyQT+2eEmb5ufTf2u37zl+FmL6Vsw+thzsutwnLTYZDTxx2MbiuKkL+49Z8tByg6Thbnn66C8JYRKVqwqZHD8ejw+/m2KSMP3wz3jN4C25sQBFxZ2CX/LXAnImj9nfNrlqAcZotu8WTLOu3WuBbQu0bfzNaezeBpRtnLQvS6yyDcG28XMC9MaTXTOntn7znSBpIMTP6UMbzZQ9E/v0ywSmBHRO2jafIi22Wz3XKS/affLdgJm+yxX66/r8RFwmZjbZ5EOmOF4+TMoSIxvfimHP4MSW9KQ+twRns2VL+ifxmvG/fv16vb29vU9Sv3///kFHDY8S3xuvht1Gu9meyaLh9QnTWW94HxtI+pi4GQ1pWw2jt7YpP5s8zctOHVHeOa5NZDhuS9SyLhcjzP43PDK/5LjGc15r8cgK9Z+yapNTyq7JheNsvmgy4Bi26GG8nWIW8STfEwc3OTY8zXo2dvtM3RErLX6zbbuf45FX2rrxS79lnGTd/B9QLtCZ3jefOOGg+fGcFiHP27gcf2zAThVm2xa/trhk35s/t7hA+puP8p75a/p703PSY3Z0p2z+ajZ8shn2sY1DeWT8aHGmYX/qPRdmLb+Zzw1jN1qNt+bXd8pTE9WWMJBBCiV3cfLvETIpyPpTmqHTObmiSAFuSR8LA11TzIzFSQWVbkctCRDmVKdVGOOjreTmEY/NOYdXynvTOwGnOem02cZrgccmUl++fPnw9xwWuLagbwBDGke/mThaIG0rqSa7LXiRx+mbgYv9ZT8zGTG5pD/O35bwtAPl1WQzQZXXDERz9+sZWVjgMvlk/Uww8v9hp02jZdp/+/bt05HSVk4gO348O9Ujs81Hsl2+b75OOSbflgz9+9//vr58+XJ9//79w44q8Zo2QF1nsd/h2NjcsbTgyKSk6cCCtCVKU7dhX8MQk23r+zRGYpwlTEyuEhutWNJndU46SbykzZOvbWGG8Y07L9nfnR0+2gXjt+GwxZ8TxrfSdH3CA+YEc/1ky8Y38xnmCclL+q7ZL0uevMl30kK9b3FhxqINZLkrR9og/4fddD/v9rITVbTDOydHWi6RdJhtG36zT9q0YUDzSerAYoflMBvtbWyT+R3+Nxzf/LTdy0VV+x/a05jGk9F1itWkkddabLHS5Mf+TsXw1B6y2X7f3sbYcHvTIXW8+b+V2xNVK8ZYXmvHhiaJzN8bZR9bkCDDHI91xqAZgE3pOf60yeBAYyVdBmbjPCOLDLLNMFqiZLJvAdvoo7xsLIJ4C46m4wZu9srx5nObnNuEaOrmjj37bJOCJjeTM+W0yXFzxNT5s+B50jEBca5xx3E+v73958EQ87AdW1njzmOCWtKbushrOW4+kZj+aK8mt03+Yz/5v7Apn1O/7JuTStNp9sU6zfa4Y2m0mc/RBhJfeH/jafTIh9/9+PHjg19Qj82HmxyyZF92XIz0nxKMpDvxipiV/RKvKB+OkW2pR9qF2WTjcQvmqZOWFKV9Gf1J49Rrdkw8sonqyKCdQqBcDUuoA/OLFo+b/xHDKWOLl8mzlc3XBzdbabHA7MBKLt6YvWwYuWFio5O22mIydZD1N4yweL7xb3QkvcRCysXwPn1gruXPU0y2jGUneyE9STPpNnlvp4yyXcrDZG4bPIklyT/HGtu2GNlsbZNP8mk2xH5p1zaG2VL2cTq91wrjasOR0wko6m7Te7On6/J/A9jkRT02PLaffN0pxseGtUmHxcKpYznOVp76jSoJ5veTEozALWlowexOoZBaoGnJ3QbYjZ7hzxTFPgg4lhzYu9FqyUPS2I6SbvKedqeJan7Ptib/Zh/NyS1IzTg5kWh9bfq6k0DcDfSkbeuz+UfTycmfbCyzNdJLX8jkMo8gvbx8nKDmgovxwPEMJPPvlNLWtkBtNpdlbDwDdP4t0UmeyV8LCuYvfN/4oY7vBJwcMxMPk0mOQx3ZJHXa2rH7bNMWPLZCus1etmsb1m9yTLm3pGqTXX6nDM0uGrZv7fL95PfZVybcbbfKZMG425KPtpuU8rBYY7QOjYaX9BeOY2XDeeM/C0+ktBi0xaHWd/pa8mdxm+3YB6/neHd2iTb5bH58J8a8vHz8WRdpt+S3TVTvYEfD+rRl2x21BUJb0DJ/aHGi4X5+P/Fm+mVdW8RsfZg+jUbKYfi03WTyctdueSqS78THpPEO3mc/p7pbTDGftGu0H74222w0bL52tz9iAe+lzHOCOqcP8y8gDdNO2G9jpu0Q3zecbcfSW3n6N6rtmKOtDA0xs4M69UZhI7jcaeExXjJvDLZVvTx+Qmec95OgLHHNz6a0zVCTXm7FZ/9mGHR2C3CWxJF/FgK1GTB5mXcaKZNk/rVJ1qGOLeFpNL68vHzYEUydn5KKBhhtlaclG1th8pL8caXT6DsV0w1tb2zr169f75PNPC6dNIx/kpbxz5xwzufk0/TFMcz+Evxbstb4z7HtyM/Jv+c+T3RMv2lL9KecGPMeebBEJ9sM3XwIhAV2+ld+Z33b6U56MmCY72ViY/xQT0lf+uW8z7F0Loo0nOH3POWSsk86GIcyUOeYHCNtqC3O8TjjKaE5LcoyHlB2qY/R1UYjx76zqECftLhxXZ+fHJ08MEFK/ZBXjnUX7xoGm92bDfIe4/aGGS1uksekaa5tsuDOs/my4abJq9kcx6Rf5qJVOwVixXbOU17EtKTb6LfnJVhMaJNU+7lD2zWlzMx+suRCv+nilFecYhBl0/CJfpfy5081xo44gU/8yL/YyVhH2VnhOBZfmjw3mW9YwDoWNybOWEksy9hD38v6xNusOznQyT9PO5iGIbxn35uPZq42D0mcn/Y03WQ+leMwz9rGZeECOGOY8dfK039PYzuGyRCLKX/qDrGTwGQ5KchoMzBmkKJCLABuQN0M7o4Sk286Bp2PxmG0Mplpzs7Ek/SSb7tufNiYdwBn7tuqrumGAJp9jByY4FkhKBngtYC18XcnEG1y4OdTgLjr3NMXgxHHbe2u6z/y5hNIU05Jj62gG0a0gD79mWy3YJABJYGQE7+0p9Qj8cPGID3UwdheJqYNV/Izd7E2Gsiz+Wj6QEsc7iYKiVEnXyBf2W5kwgnqvEyWLKmfaZMLPtxtzuuZkHNhMGUyNtMWDCyI82W7kht/xCNiId8zwTIZzdgpo3ynvixRaTae/GxxMG1gs5/23cbdaKIdZ2xpSWJLyqxsWGl4tvFqtFscmvc7uMCcxuyNdFrMTBuxRZZ82cSSPmC+0OyBdm9+YHxNX1xUTEywiRgXtBkXmq6aXJPOFjfu+HbLYRiziKd8vsQUWziizVFnd3bvif0nGeQY1/X54Y9bXyYL9kNbs9hmtJvMLJYabdSp0WmfjT7SQp9OXhsmZHvz+VNp+LHhEse2z0M7MaHZlpWn/57GhNAmByagXJ3nX8c8Hr+f+pvj5v28xjozJo3o7wRCHiFjX5mEbQJv4JABI0G10dOMLYFoq0dAymsngE46SD/HvOMUI8cJIBk0yS8B1oyctnhyUOqTOmyBk5/NVua62QVtoQW05JWyaPycbDr132ym0ZuJ+2mnhj4zPs1dOR4LzDbk1eTZAuH8PnV+q0q/40KbJQpmPxbEjda2Gt7wxZKnFoAsGJvdWhLakpCWANGmTDfE2uS7JXWkjZNpsws7WkZZGaZO/dlR5V+kUVe0Gwusdionr+UKvNmClWb3rGOng5of2ASVPsjSEskT3eYnJ/vJNrYIZeO2ydN85iKI5SYtQdqw5RTTaNts0/KPTEbzM+nhONln2n/qe4uR9D/TYf48Ywp912JA+glzqMZPoyn7M5lMfYtzSc/EO9pP20E+2TzHN32ceGUbytNsl20Sx8wXp9gpjPQ54p3JarPHXHBsMcywtPlxi4HZhrFsW/Dd8gvKzXCAvkD7Yn3KKvFwwxLGbPrA5AC8NsVOZ5gM7xTjd5MB5f2M/u+U2xPVDJJJHJM/a9OEaQ6WTFMpOX6WZ5RG5W/KyEL+aHjWv103BbbATGNoddrO5BQewzkZCYMWx2tHoU7FjJkr3223w/R/CpqtD8rJ+GGfI2eOncnfHVDf7HHebdf4ZGd54uGks+Elf3tqNpjfGeTMt43vL1++fDiinbTO/ZSP8cj7lE3SxZ1U42fzTf5+k3LJwHiiKXFsdMOVf5OB8b3pKfk/BYSmZwu4jQ6jiXSfgnnrz3B77NT+79j8mHRzV5XH30dHo5ORkdk/+UmZkoe7gb5NOtu16/Kf4BDfJsEaWgxXsm3+Ncck9+ZH1KHJ5YSBw8PJduY7846U750JKuk4JUn0zVO9hl8m5/xsRwqt7hYHmIdQXmab+TOONsFuuUI7Cpk6yLrNfvLznRiebTJ2Zf/2cDmLDclHYrrhptFLebKeTWDtc+5mN2xl3238KeRhFnB//fp1/fjx4/1BinPt9fX1g5wo000PHM9OCxrmpU22QjtmfGu7cxa3TB8trp/yY9Jm4zZ+SUPqkL8hnXrpb5vschMix8/FA9qW2Xs7EcG8JWXYfNpk8XfKUxPVDHosd66ZAZmhUjBm6DYGg78lQlu7k9FvJQNGU0oDncZbo3MKQaHJlMZIEN7oyvbz+X9zopoyowNvejfdppOy3ZbsWFCi/Wzy4RjNeRtozmdrl23zntVhcKYccsJEm2GfZsvmX5t9vrz8/l1i1rXJvfGW7wzINrYlHRzH/JsJRpuEZvvNx9nOVplPi3j0hbQbtruuj6vm+WRL/h8sk5GUF+WT9jjtGXw2zLB3oz+TNcqAJ062JMT6bvhPOlN+fKU9GS/sizTMvcSbvH7qN2m/G/BnrFxgtmSCNKQdNHrvxAvSajHqDi+G22Z3Jm+jodFq95rN2LgbRm+YfKeY3tq1De8SR80v+L3lX6Sdek2svuM35p9NVvl5272jjPjzMuYAxL+2CzafT3K8O/G0ehvON7kxP5v3PCUyE9WZpObpI/p/G4/ypfyazRv+N92RH8b0fG99Uz4bZtHGLb6fbLjxdrL5iXm5kNrirOERx2A8T33arr3h/rYQQN2feKfvPIN7WW5PVP/8888Pxm8D8tqsbnGVrQHry8vH3a0tubTPpjADE6PlbtA0HqZkkmv0tHZ3ypYcz4/Dp18DfXPmLRCnwbcVFisbKLeAk3oxndkY5CGT3el/AzJLwK6r75xk8MmEuiWdJpO2+tr4Y/tNFiO7FmiStuRjA8EtiU573mzCbOHr18+wY7QzmDfgo63y6JKBbvbFHc22W2UyMDvm56mbu6kbn7Rrs5kt4OZRrtfX1082zaRmVtwzsTFdWNBP37YEkYWJ66aHec3uSf7X67znQ0T4N1V8H5xMWpPnfNluC4vhW8O4TBxoh/QlG6clKTmuLdRk3dNCB+3T/L/5AOVk7YaHlL35myVPlEPzkU22jDMtLlxX/2kC5dd8cvMBS/rm3U6YnPojD4Y91s/IIB8uQ/8+5XlZ3xbaBusbLre4Y58bv1lSb2lXX79+vd7e3t4xwhajxu8Hq2d8k72dDLRJh+14kn7D1Rwn5UXbSdpTn29v//nLscGznKhu/zdqNmlyJg0Zn81uzWaarbadbbvWaG2fs59tnKxHfY1eyGd+N+zKkv+EwJ3UlMXQaf9TbvKd+hnnOAmm3Mkv/8KpyZx4utlK2gev3Sm3J6rzp/UDarYq34THYyLX9XFSl0cC0zHz/eQ4I4RToN+Eyf6s/zs0WOKStBmwt/HvKtPobf2ZEzM4pJO0pK0lTrzWdMh26WTpAGxL3rh7ln21ZKTpvyVqKa+Xl9/JszmflfSZNq59nu8G6neSEevbdlatXdOn6ZF6MZ/jrtgWgAj6LYEyO+XO4vTBcdLOxhdTRyZfC17GbwvC9k5/3PpoOsn3xNDBbfo0ZTYy4lOAye+GZ0Zfs9GkYeq0yfHoZ3ZFMgnMutb/3OMEgHaTE9TT05ezH+P5lGBR/yYffr4jV9sZ4Xj0vYbPGz4anyM75gYNI822jd5NLmw3YzPJyjF56qb1mRjRkrDGQ96nnMjjhtXZz2YrptM24c32GTfJlx2V3GjkvZTddX2cqLb4Zn00XznJ3PjOBYoZk7if2LCNleNwcsr/DCdvTcfk/7r6TtdcG7+zhcbX19dP93My3miZvtP2N/ub78Tj5h92jz572hRpeGjvFoc5xmZrbewTRhrupa2MnfDnRiYLW1jZaDH5nvhKmql3YszGZ45v/be4sJWnJqoTiOavLLbASsJIvAk6JyZNEZYgcBezJRXNaO8E5Tb+CdA4DmVhQYE7ICdlMgHZgPCUjNBxmfRvQbYljidQ4fhTOGkweTeAakDMfswmTQaknb/vtKCUn1viaHxbH+T12eQlE4ZJ1oY3+pHZOGlqwfvkeywm8/lux18aUA4vfOpvW2SZthM4ZlUz7ZyLZqSTcmrHwSi7Zpcmt3afxXZDSC93DvL9un6fzHh5efkkN9OZ0Wvjs1Bfdj/7sERwXmZX5DcxNutwN4X2QnpS51s8avhB20nZGf+NBmuX/OZYbG9YRhvOzxYv2R+T/Bwned184g6/ydPsjuUY1Gfim2H05lOGtdvxcytm+/Qp4ghzmYZ52/gn7J5xrms/Dmh6SxpOsYyxPCdJW7+brIzHLPn02xyDtpOfrS/LD6yMTU0MsckH+83f0Z7kl/oiZuUC20xKc8I6p2mI5Q2/aW/5fbPD9D/baTaMbJhi9FKXduJp8wGORWxmTkDZW9/t1FWOQVq44/7169f3v4+hX04f/Esy4q3RZ3yTv1Mx//knpcWju/3enqhmUpCGOcrmahUJzNXWUdZ8HqeeQsMyZ8lrBq4EyRPgsNApWhLajJ5JA3lh0tOCBeVofWYdfk6H4xb9BF8CePLTgM1KA/0cv/FsdKdDNmfk51MSkgGaZePV7pGvudaOlrGvBowpJ656pywscbrLz3V9POlgR5SabXJMs0mu+rJPa2eFgboFHgvGCex8wnjSOXLMxDfHtyQnaTgd72J9yo91ZxzKf5sIb0nW8DCymO+DwZNYMZlsO4zJUyZq9IPUQ/JNmSbPlH/Kyo7WzYO6aJeGH2Z3GcOYxJhemm0wRo382DcTAPM9tmlyyX5GPsaf7cSkDi0mtEL9pf4Hr5gPUIeGXzl+0md2krxZ3GyJOXk1H9xkPK982mqLedan+YONdYrpp0K7akf+7sTj5KvppY3/8vLy6a/NWLYYSd80/jhenrawNhyXR2vnBAp5ZzvG61xAM1tOntrkkS9uWNgrJ6pvb2/6xPLkf/Mn00diRBbmXi0m2wKh4X7D4Iwz9pRji+l3/TDpb/yb/7S+2Xba5cMA+b/e7aFgZvdG73zn/RYTiccnDOSpxjZu6+eUF93FtKceppTMZwLDHRozniSMQH0niaORJEg1QXLsTWhtXGtnTppOyQC6AVZOHtMpOU4DL+NzAx3yxdW9HGebqG4BjXJ7BkwIGubExg8TQKPR+Oe1u46zJRBN/hznTlBoNPO9jTFlk4nRksmAJZRbAE+6aI/UaZPR+FQGJAsWLYAnvfRFJqx3+mrY1fhKvz7pKuVHudiOx3bklbpgoLEgNvcTj+YzJx2WNNpElXLJtnMt8fIOVjHGbBN3jm2ndTZ9N1os2bX61p/pMRMZ6oKLItylzD5M94/Hxyf4znXG6IY5d/mmT7VFa/Pfdi1t1naB7+jKyhZTGm6nrK/r42/y2mKhxULiibXb6N545LXRAbHbJnCn8ZLfjQb2Z3WanEwXd2ITP7dTFjlG1m/jbnIhTZw4MU7Qp3MxcJusWh/m35z4powY67J9bqpshRjR5EteWx6b9E/dpu+Tn7Sc02jaPrdiscX6b5j28vLyfgy8/Zf3KR7doXPG5fiNV2K28cS+jU8rFrv/KW+3J6rfvn17H9iOIcx3e+KkrarRyVqyk2UzhpbA8nMrWxJnQZR0ZgDIVZLcTUqZTQDO3YEE2+wj2yY/pnBLDoYHAtLW3hYcKKettGDKRGPrh/cMrFlShtZH9kUAbn3eSU7t3kZnG+fvyIOAZ4HHknrugPHF/53MZK3RQ/tJH2cg3wITabJjVKzPvpLuGZu7Ss3HRo60V6Mvf9dpGJL3muxMhtku8aEd87XPyQPrDM7kuMRz7qgm9hsWnGzi58+f73Y1fU//aR/Zln1d1+9jynlcOXc2qI/sg3Q1X2xJUgvs1vcU+l/ivv1dzul3subD5HHknXLm59au7YhaXfM7yqPJ0N5zzMfj9396Nnqn/xyjtbmju1YSw9L3ib8zDneTrN7d0uJUs+GM+ekb+Z0Yk/21UzDX1f9WKNvbJMsWi9jWdv2TjswT029sgtr8MO3xhKGkjXiWfObzW7IeT6a034luujR6SNN1XZ/yRrbPdokBDQetnHwkS4ufd8cz22z12j3aUtupzH4srrVYzjq0U/vf7inUX9pVw//m60ND49/a3uHLitkY43fWNd2fFkiy3J6ofv/+/QNRzfDsR9224sM+MrFtwshrtpq2KckC/VzfkpK5lsrkxDITYQvQueNMWqjUXP02JzWAMnA3422AdQcwGajy2uYkOa4l8lytNQCx4MO6BmZpK0Yf5bTRkOO0QJLjbrI0utN+GlhaOYG/gWfzG9oMXzZBIpgzGOR70jhBe44qZdCn/1zXx99PboX6ySQm+9vkyZVpk7f11WTEfp7RaR6pzCNtOWml/ZH/5j+0Pd5PGrINV8sNGzIoJ9Z8+fJFJ5lpEy1GmN8lVk5JfOZuJQOk4SCL2Xm2z+uGu2kXuZDWdoQfj88PwWo0Uc5N3jlRyWI75FYMvza8afetr7SpbRep0ZZyy8/Xdf4fVPbb/NZ8mjzSt5JPTpDI42m8xFWOZbwQQxOzEk/mWmILfze+4VmLnaYzfm5+ZGMzhnFjY8NpyoI4nS+j1XY/eRKNfpTXbRe1Lbpsxfx7k1vynJ9TDsSdHIv6MTucsVp+0+jfaM7PtiiyYYrhcdKbNtEm1WbbucBD3CW9NjcwzDjFNZtHGf+Gi80nLGcxfrJNe6feyZ/ReMfOrTy9o0qCsqRQc6Wcn0cRtmpsx3yyMChd1+edE7a15MvubfzRUZhsjKK34JEBY+SVidvUGRkwCTXgtZ3PkzEQRC34teSgBVRzSJOl1WsOuNFu1y3hGZlvR+RasDXeE+RbXdNDc15z+LxmdG8A0XbQCKA5ed9sN/swH2s+l7sqFiTyKaEZ9Pl+F9ia/WUA2foy36LN5vUW5DghsTqnay25mu9TcofEaBv7aX2TN/bDevPejg8yoaTdJq5xbJM7cYp88J02nRNV9r0leVla8tquJU9pCzyamM9laHaW70ZLS4Cu6/eOrNWj3dwtDc+arfAz2/Oz+RXrGtacxt36a32YjW790WcYK5q8txyHvtkwP/tpeHJd/SdJidVs32yoyYAlcYCY0HjPGEfc4Qm07URBu2YnU1osY7w95WEp63m3iWqzwYb1yYfhvNHb+qEtbXpt92jPG46fCmVODCUdm37pf3nfdNf4vGNT5N9OPbFe2gVjG+txkrrFbqPrhB3X9dEXyGvD6Hk3+3pGvnft47qemKj+3//7f9VBkogUfDoM/+Np/myYk9q8xh3YZJBMJgBviWIWJsdWmrAnKZr3STymzvCaO6k8Yjd0z7WfP3++1x+DT36TJgMZA+LWPq8P7U0OZrT8nnLgmOasrU8rBIDr+ujkd3hvMpj3eYo1x83PmWyMzc540xcTgRxvA8JNDgSxE0+tv0xEmMBnneFr7JEBnYn2pvcMNpbAjV/Q3xMD8uEQd+wmx22TZcrJfHLrP9uQloY/FkhPSVvWy90PTk7vtGl10yaGfpPZFuTZ33XtD1bja/SU2En8ZwJHfJyjgLbbYrJJ2nK3kYnkZnM8ncCVdD78I2XRdH+yccOBHJN+xMQ2422z9S1umi0wHhEb854lNSe+G3aeYnzaE+05+yB/I0cbuxXyMv2Y3vk54761bdiXOrcFyEYjfS1POGyJpsWMpCnpTtoTi0bmyTv72fK+Fv9Yt107xV3Lc9qOKne6uLs7ffE/mjOm2Zhsn36Tfs0jxFPX6KBtZqw/5Q5mVxYH065OOJfXEj/Zd9op2yTNFsPv8GUysmL2lnzOd8OYyS8Z0zYMzX5yUZ/0tDhAjCT2Zr1mizZRPpUmR/OrZ8rtieq//vWvTwmEHaEi2D4ej/c/fZ42nJS+vr6+J8ZzdHie5khHtEQoJwhJw2aId45N8LsZaoIRASbBY76b49JwmUCcdkWmL+u7AXPKpwFLG6sZYgNc69faW53mfBnYya8lc8Z/o3vamr7SrjdZtHLqz+i7kyy1RCZ5bMA4ddoCVMqxTVQTKK/r3o4EQTZpJe9Gu/GafSZ2mL6tz5agbjpoCYUF2uYjlgCMHM1mbOyskxPP5tt53Y7QcaJrPM/nzYZNh3Od/mo8GM+kk/ZHGrakpeHK5uNs32RJHhsNzxZL1uadK/Bm583e8rPt1ufnDUvG/1pcsvqNz43vrZziVNoVZWly+TslfYN5gL0n/rR8goW+e1c+pPO6PifT1l+zvdZvYmCL0/P+eHx88Fn2wX5bHLiTdzDGtDajk8fj48IPF9GyH56UmDb8qQP54PjGM9uTH8qaMtpiKMc0/KKucjyzg5NfJ15y0cL4JM1bLN/8hr7YaDU587Qe/dvildmN0XrHr6iP7cU8zPilDpPOTbf/X5bbE9X//u//vq7r4x838//4NmYyiXg8Hu8T1V+/fl0/fvy4Xl9f39/ncdtTJ3/HNu0JXjR8XiNt9v99VHBTfvadk8pmZObcI5OWzKUz2JGdrJu0c2zSQ+cwo2U7S1LYb64qTr9tddf0Qh1Rn7Y6n59boL4LPiyno3FNxqYD0kf+5r35EIOpJTw5pvFnQJR9jZ+xPgsnqLmTxIfCzGf7PV7S2fwiwZW7rkYfJ87tuCj72JKzpGkLaDaGBXGjvdlu9sOAQ3sizbZrbqvW7JM0tkSAK8eGCcRDBsCN9zyx0uJK9sEd1NSr0cH4keMav1situmjjU36Nxuwa/k9bTd3btJnOAFKm0p9Jp0WC1jnzjFGWwRJ32axuHS3tFjVMH9sjHS3PluMST9ofG0lT+tMn2ZTRuOc1kpakkejt+UT2zHDmWjdnRhv9Dd+DP/IT2IrebBJT8OnzW6zHfPdlj8xVzEZJg2Ghcnfhu8zFn11w6qWw2X/9iLtTV7t+zbOdX1ejDVcMVla3rNdS9o2f877/D4+YDHO+CYdhrNZGMPmnbon7cx9mh6brIa23GVP+7zjx+aPrTyL60/9PQ0HGoXxiJ05SwLItJm63759ez8O/OPHj+vnz5/X6+vr+2T1x48fegyQwk5goTBoXAZWyaMliA3snlEKQdD6I80tGTKjpbFwl6wF7wnYFrizTuqQdJyc3cYkTbxHnba+2W+C/ommzWnopMlr6sZ4an3bzg8nNqTVAoclRE2WBpQcf97Tj7kQM3TygTVpG3M/+z4FlfzORTAmUKR1Sq5YN98gj5aYWSClH1K2TJz4nXrc7INlaLUEysqMMROWDGRcZGgBjXJoAfdOksAXdWnxIrE3aUmZ5Pt1ff7Lss3msl/7nn08Ho8PCUraEdumrmyB0cZvp0aMvil8mMsUTkpzwWJsIuk2G7LkjXGlYY+V3KW+Y++WiGX/W7xt8TjtmL7X/Nra2+c2/obNlGXDCZMDPzd5TJ1csNr8yHxy2vDzabI69bmL+Pb29iFftIkl6TFsSF7aRMds7ZQ3sP+kg7IlLhrd9lO2hv3NHqc+j08nJmVMJDaT34aBqQfzCZPbZgOsy/hobRgf7NXGalhrWHWHXrtOjDdfb37fsCnpsYXVLMzH0gf4rB7GFqOFcdniG3Xd/GroJ9//G+X2RHUGvq6PADhgY1vaFsiT0Uxwv379+v50wvkLgz/++ON6fX19D7DjnJbo5LgsBPgWMJtjb/eeVcYJAJ7pp302x2ifs6QjnsDnTj0mN/nOa03Od4Aw6WHfbezs76SLxucW9K0PO8a50U+AH+DhIgrHMf5t8YbtGmhZAM8x5rvtqm99G59Zp01orE8LnJbsZ185CbY+bKJkvjttOc4WIM2ezC/pk+bXVj/rDi+5sMCExBapmLAZr00PZstb3axP+Zg+WoyhLDLomi2bD/HoXspg81HKn23ZZ95LHbGYHW0nC7Kd4YT9FjHHuIOL5HOzd/JN/DjVs/utXsP4/G5tN79m+4YF9NGtH47TcpSWr9AH8z1tu8WbLKdFI9Mt7WaTAzHZTqEZptjOrsnLfC5pvHPNeEv58HqL+0NL7sJuscpkaHraYi/107Dm1KdhrpUtpm15GPswHNhihcWJfDeaOHEivX+3GI9b/Luu/tc9+f1Z+6TMB+8thpos24KAjWOlYW/T2am/Vm5PVP/nf/7nE0DbSvAIZFZRr+ujo2eSneA1DH39+vV6e3t7PwI8R4N5HDjvM+G0YwOb8zcHT0NvCZz1l4WK2o4ZGSBzPAMTSzZocPxsTj86a8HxBGDGA480tbrNQbbSgJafzVk4mWqg2fjddG16vPt7P9LbjuRtoMaSk5Rsb7S01WP7/nj8nuzlbyJzEpSrwPTT5CnH3FZTCa7bhHqbqLYjblPHEgCzL17jEeEmO9NBWwlPXBtfMqwyXpOHlBfxm0e5See2KGIr4HZsKONC2kLGjClGG2WV47dAbt/n2siy6eGflPGN+dwwN+0sFxG2o/KkkXE59ZX2Pou91/XxYWnk12Jd0p/2ZLojrfn9LrZf1+fdOGtP/7Kf02Rdk+VGdysNQ4nxm102jGnXnqHV+mk6OS160LbmWsNX5g+0GZMXeaWf2Dsxi/1aTtHi6ZQ2KTUczD75kKRcDE2+yFNbFNuKxdccb67lz9s2/2vjneyLPFj7xIbmC+ZDzA/u0MHrk5e0+M22Zg9bIT/MbazexoPRk33bK9vzxNTLy+eHvF5Xz69I65bHTOHptpTBtrN/OjHEcnuimkfI7M+VRxCzS8qn3KYRNAN5PP5zDDiTmbe3t/fd1jkSbL9hzeSzPQ0txzPaTWgGvFm2xJOGRqDPzzQUOgFpsPE2pVvwsNKCSeO79XFqf6JxC/B5/Y6hmyOaLDlWAsCA3lxn3+b05GuctyU4tmtIXvPaafLfaGzA2IIp5cF+c9wByfa/pwaM7XtePx0HMpmf5NDask3ze/Ph5l+bn9IOm/75mbQzMTzxYn3y2Kjx1mRxJ8jlRJk2n4EtFz6eDeAcn3RYnbuYk+24Q90S2eSz/RVTtqE/nDA76SLfrQ5/5sKEzj4njew/29+xM9K4xVaT1Z24e+qXPDWdtPbPYNtdvi3WP1O2pHfDkDsYSr7NNo32tDkm0nY0kWMy9qb/ZR/kM3GFn6/rIxZt9kOfznie+acd8+VRzs1uT4X62+LYy8vHf3O4i21Zmv6vyxezSKvpwj6bD2y0bj6z0cD2Jn/G34ZBmy4a3RsNLZd4Bv/Txtkf/cNk03B+48v4bnksfcx01srtierr6+v75HMemsKygQ9XGlIA+Zox6OwDBDNR/euvv95BYn7Dao8At90bAkde2wI8v9tvvNrKXivTLhNEU7IFOjvaY8lK8mjHbpLW6/r4e8mTDFq566hTl7Ty3kmOJzo2eTbaUp9M3jiG7c4R9Nh36+NEH4HU6hqg5I75dX1+QJDt9rekKvtvv9fgOM3eLIi1a9tkPmne/HkD66zT6KXP58uSfpPf9Jc6yN/1kmcmBoand4vxy+A2R/TyqLmNtcnRguXQnX9LRN229jkex88jdkP/lgwYnUYDx0s8mJ+nfP369cPTsElrJrGUmRUmG022SdMp8c0xuSNjJ5FyzJRN9mdx1HCH/ZkfkSfyyRix6fYOHjYsM/uz/ixOEZ+22L3FAcOeTbfshzLJuJ5jNJ0YXTaOtWu05CSVrzaWnQCy31DarmRiS04g+cwD9sXxbYKc/eeDy15fXz/5OmWXNLfYZHI0fdnCbeLGtCd+5zj0c47dfM7KM3nIFsNbOeUQjS/2kX0ZhjGXafnIdn8b13gyeVvssR1byiMx3nSfNCbPeZ122E7MMC4kDRyHsrir9+t6YqKaDjCrwnza3HV9fvLmEERm5/v0R+elIAk4M2GdiWr+5c3svG6rXCwtOMw7k7i8n3WS9rnO1eY2hvFtgZLXtwBPQ7yuPrFocuA4nOzkO2WRNBiNBgy0G3Mkjr2BbAZqAxbjd0sKkq5nAJd2l/Q1gDglKK3kcfqN/qQjP7fEgzSSfrtv+rD6pwSq8WP8Gd1JD5OAebfrpz5bYvby8qIPMiGWbEkL/yg+x6ENWx+DeznOaeFgxsxJqmEj9WX6yUSyyWpK2uwpKTK6T/qyXc/Ug8WZDPiU9UxQ5312V2f8jZemu7v+nryeFhLsv/DGNpOWhpfzORN/6vx09DcL48gJ5yhDe809iydG04YNxAGOQdpSBtsxWvbR+jJfazJqMaTh/rxvC9Zb2WKH6TPxcBZ28ni7LezbQrnlXhve8cnX9AH6p9GbeEAZ2vMN6NOWv+W1LcHneIazdholZZN5Z9Ol3bcYlTow2hqNd2yx0fjy4j/N2Pg59Wn1iRcnWVOfhjXT751yhw6bs7D9fB65TZ+U3zP+zsXJTZfkwepk3vAMHU9NVGegdFwLFCfDbAzwPft+PH6fN397+8+T4waM5vM8OXiuvb29ffi/1gQXo8WK0WPHu5oTWxBtY0y7lrQ+S2cb62QgG1jSCVIv5MW+G70J3gyCp+RiS1oo1/bbOI7VnJv9be8tUJlc57M5/DO6Mh2YXd7t++642z0DX37ONgwGSWfDCrbfZH/Sxd0AZ7ZB+7OJYfPTZl/TPu015dHs/YQzJ5nktTbRnDrEU7PD1IfJ2vyvjddkt/mrycl0YbaXGDefTa/ma7Tz3CU6+WvDFtZjMmc+w2K/K7M4zmQ47TCvT1wwbLXS/OJuMX9K2q3ciaH0qbxnfTVse6a0+mbf7feA2VeLK6dYYZPAFs+Nrs0v8oh8Hpnf5Gr2TPqSx7G93LSwnVTiVvbJkxhGF/2CMqesKO8tv9p0lWMP/UZD7jBzLMbjlO8zOUGL5duuvfHVfIZ0/pNcpdFv32lL9nlrn/TfpaPZBMduY925fsIN68d0fIdP8mM8Tl935XR7ovrjx4/r5eXl/Qjwly//+d9E/kYnf7ybhKdzGTPTloEiQYm/q3k8/rPa9eeff36YlOaOagJW/pZgCzQpzKSPAGZK3JKEljjleCOXLdgTVCkj26GZPgli20qNycKCRh4ppZyaMdr1U3IzdaZkYOQOVgb11AcXLRr4MABzfOrcALkloyaLf1pOwLm1aTbIa/l9A63Ug9XfAJU0pb0OtrSfFrSdR5PJ0MjAutGXbVtCxqRsdhCyHXk2GbVjXaYfJlikkXTaQpsFwmlnCR11a4WY2AJ/66PRyhiSfWfbfM/Pp1V6ypK2QX0nP4krhjGNtjaWJUnTtiXXORnOa0OrYfjwnXhH20v/4mf+Tm/TMeVH/baSst/qGBY2fLQYZJ9tnNZXnjSzvrd+01ctvjX8mGI+Zr5hMfPOwkHaCulsDwKbe/Yf3C1PoXwtt8rX2F9uVtguKmXV9GMxZouxz8Tb/GxxhzIwGW3Y2XJHG6fxT3w78dJere7dvNNimt3PuHjykTt6IH61I7f06buYdrIdYq+N2cpmE43OpMP02DCEfWZfSfddfbfy1G9Umfy8vr5+SMZy8srVOQOL/M4jpExUWZgU228Xcuc1j7LNK2kw52pGRsWcQCfrsj2BkLsn1+WAagFh5GX9ZpI2Y0x9S4CmGBianCyJaDxTTybb/L7p4ZS4WDDMBDzt0kCxJQg2DuV04v+OrW33WG+7xmOPZjcJ9q0YMLV3a0u6WkBLmkmv+Z/ZX5ML+xx/GHA1GTQ67rw2mTwej08LZy0Baf21pC99nrhI+ZitNhlQHoZ1G2awMCFKWnOCRZoej8c79j8bCDOQNptpOJ80Zl+WoJjeT1jCPk730vbtePPmY1lywtH0ZwkcTzhljE2MNf5ThiaXloC25PNZrDTc3+pn2eJd62Ojk7ixncgw3djCgNkyx8gdzg1HjNakcZuotnxl4yOv8Tfo1/VxsyIXTNIONzylfIxvO5pshXq1Uya0Y8N8fm/2teFKs7FNFuzjTgxr+EBb3Hg9jZ33TEdGD+naaD7lO9aH3Us739rZou/Wt9nAnRznjo6bfdzZsW+xhuNQ76Thbnl6ojqEzvsQ++3btw9P/OWfz9puh+0QWMDaHNQMOpObBK2hIyeqz6zyn4zMlJLGRqfP75wwZbJnhmpBjP0maD4e/gPrlnzm+HRuyix5N5mQ17YTtek4x7BCnm3Fl0A29+c30iy2kk0aTM5GO2Wb8rlrc9Zv0mSBI2nMyajZYwO8FqgoX6NnA9FT0MoXT2qYDKfYRCz7va7PfwtgGESbznfbFTgFHfY5+GSr/pxEtZMSlFXydCc4mD00/pN3S+BOdtjoTjrITy6sJK3kk6ceLFmxBPhUmt+S96TD7GZLnlpy02w96SffqZ+UUxs/P+fOWt5jP7TTXPzcnoJKXtoYWWzsbHvSIW2Xtj39NP0SR7OvO3E46badZvZrpx+4eM/SdrApA/p5TlBzs8Fkx8L4Ov1QFi3ON5scTKTP5j87TMnTUTlptX99aNhkvDI/MMwxO04MY35ktkf6TvEwP+dYrNfsYMaxHesco9lL45syoM1nvUbXaczmm/x8B9NP9ZteSC/th3Q2+hqe8FraFDcYNnrvlsSnaUvbof4avxuub7Z2t9yeqP78+fMTwUnst2/f3ndZ8yETSSCdi0ymU+cuB4Mu35MmHl3KvjKYTjs+BY7X2HfycHKgVLglXkxkmtGksWSbbcWVshm+pv63b98+GY3tHjYAbbIyp2aSYoHA7IG7vSa3fLf7zSFSbvmk6S1IbbsUY6fZP2mzlScmManvsdkWvKZ9vpM2o8dssYGS+SwTFOq3ASl5bbJqNG6F9Un7CUhNt4ZZ7Zhblre3t/efSkzdfM9xqSvS0xIo8nLneJBhxNCb4+UuS9JtuyKGw4MLfAgJg7RhIAsXHeiLm09tNk2fo4xMhi32MWknH813t3Ho+4xRPMplMqAs7Ciy8dAwa8OJbJu+YXGNbbcki3zYgvcmy3Ztwx9rs8WUrW6+z0I+Y2eWtvBlftLylGxj9pnvQ1fGZsZp4k7SkDTmZsAmoy0+cBee3+kHLT9J/lmmHheu8lqzj83ONjpSRiefaHI+xbOGaVsxnEi6ifMsaSt3x7aFjLne+j/Rb/XvyuC67v+3aI7BBb35nPeJVXdpMiym7k9xZmt/6msK5zxsM/e2/GriwTP6YLk9UTXl0dhy56qB5xB/XX4sM8fbjM4SJKu7KTw/W+KV75uSSSdBJXk1xzQ+6fhpFORtk2MWCx7kizQ28EkeN5Dc2ie/WaZf26012W4laWyyMCc7AQV9wQLbnXGmcMLXeGyg0Yr56IxnPJ78aca3CarRkzrMz5s+jN9sY/qk/JveT+PZ9ZZ0UX6UkyUWFiDuBsa812xp8w3qqQXYDWPI87P+eLdsdkja74xtbY12w/dpz/omixZHWrGxsi9LIHOSSjviBC7b2/FJ0m87wqfSYkebqFps3641GZoemy1uPsz7m07s+ok+9tH6afSaH9hk7TTmicfWR4u/bHt3NzbvT9+cmGY+Ybs83F19Bg/MPzc/pR02m9wmuRzrpDO2b3H/hC9Zn37d/ItxwT4bHdxQoY1M/YYXLZb+05KyazmbnVx7Bk+y72zb7uf3fxLPLD5kH83nT3Z1p2z4fLKVrZ6Vpyeq2XkGk58/f74Hpnnqbh4XZgCburkDajt6NJaNjvncVuQIcKbsBoTk4W5pSR6v391tI79WKAtLBKiPFjz5e6V5P+1kcPz5X1vWbXQnnazTkkMLntfl/yVl/NrxLfbVALjRS9qfCU78bno81aOOW2B4poyPv7x8/n8t1sv3pLOBGwNqS9iM9k22Dcj5OVdBLbhvfLaSO+Qt2bCAQ6yYaye/2Wg2+97keOLNaOGCS362JLGN2e4bj1sQJo05gTod3d7sL8fb8Id8Wf9s305vZDvKbHbx2S7jiI0/i065s56Lzhv+5Gml5NnGNexKnDJ5sZ8WBxtuG07cwcG/g4ukneXvjpG8Z/+2I2tl9JMyztNVufBhi8PzbrkZ7ZVYZbxs/JFH2/W8G0d5n3Wb/Cy32fo2eu7Sl8Xkm+/P9NHGTR1Pv+14py0EpD8Sa0mDHWP/J371TGk2Q5tqpeW3+d7upQ7u2MGWC9k15goWl/LzFqMsLk+fNk7zJ9oD65jMn/GNp/+ehgMMgwSUX79+fTrmSqOdBy8x8E2bHIvBMmk5BbXt9wotoAyNdwxsM9z5zD45gchxk1/r6/S6Lj9ikvwZrUxMjDe2bb9VSzB7e3u7vn79WmndZGaF9PLejJmypK625Cn5NJlsJevedcy0Bdop+8prZjdtR+Q0KZnSgpYBlAHTnULdbwHZ/H/eN/0a3TZewxk78sJ+TwFvS4Qbrek3j8fn35UzCDZ7Jr5kgpJJq9GQWM92DX9Jvx33Py1ubdht8qJseRw47eKOrSatJxxuCbudILCTBBbzUkYct+E7+yetp+N4Q3v+RnH4z0Xk7DPf7Scg9iAbyrXRm/y2/76kLJMXvm9JmtVppcWaO98NR7YxDaObLTUstX7ymu1+mmwTi8wnEo8sfzGMZf/XdX3a7b/7Od+3YnVPcZ9tW38nm+SYLc+z0mTK/k8yMX1OSVy/u0vfaJzv/L3yjEOZbHSmzT1j4zmG5fDtJ2XJC3kyPDX/S9qtf/LSbOuU+3KchnMbvjGebDSditkoF/tnnGf8dspTO6p37ucqlQksfyNxXf5XAAS/05gJ4mZEd0Bvyilo3RVuq5fKs4STckq6kuYEFf6OY6PhJM87iVlea+BjPBkY2li0gRyPQGt0baCc9PFzk3frfysNgFksCWjBjnSmrTZ/2mizYLTp/1Q/6554t2RnCzp5j5OyZwDPZJZ03sGb+Wz4MWNYf3fkkn03221YkPdNvrYQQjpygSd3y3IM0m/JM3mmjhsdxLI7f/HCeEEZNNs6+QntY7NP478tkLKkL5neLYbZRNV23QyL5z6Tisfj40SZJ0wMNy0WzemZTW8mA/Y9us+Jr8ktZZffm5+TjpMdEJs3vNliGvu7s3NnemxyMJ/n9XbPbC6vN5xNX9sSZcrguvqke8Oodt/6v6PXu7hw8t0WB5L3drLuRCPfGaObbdjnZj+MOcQX5lzcCCBtzPMtJt3xo2Zz2YfZN/GNvLHNhnuJj4kBg093cxDS1bA+rxl/lAOL0c/J+ck2TjjX+Nt0vGHYqfztiaoZx5QxBPsNWwpxjp/MsWE+Hr0BbbvWwIvBNI2Mfc6r/T6igaQVOneOMe3HiPgAE36etlzhzhXskefQmL8j3GjdAprRbquxbDvjtYdVtaM+dFSC8qnwmBNBqS1qMHBsPG7Jm8lgPp+C05ZQtURn+rMH3pCWtGcejzfQ3xKptIUWgFuyYf1YAKaN2OTlVGyXjePZGHdAlfhm/tN0fjpWld/ZR8rWVsApx9HT+Ebah/GXPp4/0aDvk376LbGcO3TUZz6wj7Y67ynXoS/7Mzu0n3o0HuhnTffNh5P+/Jz00BbtmO/JJucBcKObrJefbYfXeB48eHl5+fBXdMaXyeo0tmFnFltkpf63YtibOMQEdOSWR1/v9Hu3UEbE138yHvvgPyywTsPqE/1mxye6st9nxuG1RstdbG65jI3/TDnJg7GZP+/KWM28xPo+ydMwYuPN8ogcM/s7bfxs9mbjWpxg26mbE6tndNTy0+xn01uL2UPPLMINZmw5tvm6nXg78Zm4QV6ytDxsw/G7vtVkZjGNNJuun/W7p4/+EvxzcDP8RlT2MYaZx4VZt11rjsFE7BlwsyRuc9ZnS2uXfZ7kx+s0Sjr6nSCzXbcgtL1nvUyE8hghj/hlUmnO1YIPeePRRdNnOxI347AP0nQ6Eke6Ethb8Pm79mTlGX1a4DCeDcxtgmw7lfPebNYCt02m04ay72YbbQzyRV3lmHd8cYpNjPOdR/hMPgzoLeBYG8rXVr6tfZaUh01UG95y7BboDBNmoS1fj8fnHVUL8qZbyuuEhaegTF7vlOzH7IFB3vxjwz2Ok7bK+Go41+RgE7fNzvL7HfobLU0H7Sc4d3S51b0TF1t/UywGma3d0aONSXu/mws1O7v7O8G0G8PY7drY0Lzn/e1lfCcWX9f9UwqUx9S171vc5vc2HuXNuJjf8ynLKS9b4KGMN3vb5NA+s7+R7eRnbcJqfTTMbXKy96SBWGRx6pn3LQa03ID0sI3ZFMdufr/FXaOjlRnjLjbf9Z0tr0i+T/hu7e6cJslye6KaP76ncprgDahz1Tt3VLdELN9pULkTmddaP1PHDIJ98zgtQSSTAhYmmds4TKwIoNvODfnIoN7OnW8A0oo5feMheeFK+ySkj8fH/zybPltS0ujm/ZRdA5HNoZstmyyMLus7+aftbg5vdKRdcVXvpMMT0Ntn6pgTlvS/ORExuz05bgO87DdLTlw4ickgtvHE5Ix+T5mm7XCSagkE+7CTEcQO2wG1IGiyaroyu857xtumm6F9Fg7zpEtbjLAEmPSxXZ4GmSOjJz23RGnDWLZtSQdlbqUlP7xP+gbb7IgZ/x6L+N/sNgsxlrIj36fYYDJvdmo2Sftj/3znbi/zAdOn+X87Iky8zDFzoeBuUjn3yBv9nRhAH7D+KXvaeLYzeyeNhoVJcyuJf+SxxSriSxvDcMfqbSfbtrLFQvoVdbT1v8XH67o0Fn79+vXD81h4oiXxj/7baM/vzEnJI2nnzlvKgjQRozf8ZYxtPtPyRvJ0kgX5uhMHUt/Zpy2uN/zLe6T7ZB+G67xGvkhXK8TSU3uj1fKFFi+ZZ2zvU56doE55+ujvJC8JoBOESRgBNwk1g7UxzfnYxpLm0zhMpuf+FO6MZJCxo5Km9OY0PH5jxyftOBhlkPc5DhPKu4bEPu16jpdyNmdjSRnyGIQ5A2WZNsFjbQ1MGk8bqG0JSgJBC9qWxDzT1sp2nfbfbKnxfgoGBs7k0fzHxk3ssONoTM5Y/7o+TnKa3VhSZvSa3W5HerZCm6WN85hm0sQEbxvD3u/49DO7ZSO/+WkGsYv6MhrJl+mDC1jp22zDWGGft1jS5JM2tvVthTEvS/O/bLclQptfGr5YYkCMbfo22d+x/YZjd/i1MU7xMvtofd9N9tMniDVZd7MFizMtZ9nksn1OeWTeYPXaGCMTk+U2JmlP3Dc+W/wlPVnXxmxli81GQ9o9+7mDocT0FrMzns3E9OvXr5/+c3v+SeG6Pi7ecxfT8ueGDRZPki+e6JjPLUZafkK/sliXY5jcTrKkPzadND1u181uzC4aNo6cbZzruj7olffms+UUxpfpi/Q0/Ev/NJ5NP3nvhCeMJyaTE/7diRdZbk9UZ9A0YBJMAltAohMQMLYAnoXtExA4UePnLbHKa+ZUFtCyPSe57MsCL+tR7pscjH6ja3NAft4K9b+N2fomuCVtJifWs2Ohj8fH3x7f4e1uUCSNdwIsfYSTKgaCO/S1BIOBMuU3izK0VwM06zs/J9Ay0D0LPtnGwDLpzYQ7J3staclgmvfv+g7x6Z/YT/Nz+nNe28Zq8j4lh1Y2X5kTL8l/w65tXJu8Jb3p0ydMuesvm8ypz22MhqPz3vDhRCttM2XAvkwmdxY1Gl8WTxrdhg+ma+YGrGcxvfE27xYHNn+2vk8+QXrNNk565FhbXGi2dfJbxsE7dN2Jw+Qh3xN774xldry1abIi7Wa/d2KN0dX65Of5bnZohfF3Jqr5NG3LZajHmaz++vXrk6zycy46mA+YDMh3k4EtaDS8eDwen/jJa+SbMk3aksapz3yjyf7vlGav22Sy+cjd8XLcVu7EeeKx2XnDYuq+8cK8ZOPpdL3F47vlqYnqHcC+rv0R6naM1VZi0lE2J8k+Z1XKjuC9vPyeyM4Yd5IfAlXuBCaNBBuCmgVg8mAgkvJNgKJT2xhNRybDk2EZ+F3XpY8hZ1sCb46ROqF8vn79+l6HMssdNR4fbKDedsjokAyWDci3NpQjx7xzPOoUVFoAzgkq5deOblqfBHHaHf2MC0Xkg/SNLMljjsVdNtp/rj6fxks5N1lYMkP5bCXlxWA99pz9pJzbE25TPoaXm50Tp1gysWgBdGi7rs8nAnKcLDzOb+NS9qknnpJpseDOg7VOifbQk3Ql7/lODDklHPST7Hswn0d1p18bg/Gj6XRLDLYV8NbG/MJiSPr0nf7/zi6M8Um7GFtpR+2bjIxui9d5v+mK/BGDSft19UWdluRvpd2nv2z0t3iW/t/aWTxk3DzRTzvfcpjr+nykvflQ9p/xa3ZAc6KZWMRYxLizxdnTRHd25GZyy0V34nzmPUlLiyEsd+5b3KUf0Q5OGG62u/H1bGn0nGS5YXra7RSzzw0bE9/vYE8rlnPe9WeWWYzOYrbDkzkb/pzG/Dvl9kTVJhPzOd9PAqKR5zUaQZYMPFswtGCf9M5Ek07DZGpLGJN2cz7bzTXe7HgSjz20tslXm+hZcG3Bw+S9JWwn+tJ5WCcBf5MlAX+uTfI7Cwe0jaQ1AW/umV557RRoSbvxybKBmNUlCFnfxksuenCyZLy1hSVLngzsCYzNb6bkwyQMuC2Q5Of5LU/+hnVL8MbnjZbkiZ9Z2j3T+11boE2mHbMe/T37N1xsPkaeGp4a/Q3v2WdLDOc6k3XyeZqoMnGyhYo79Nt1wz2e4KCd09/msy3gtNjZaM57xHbSmjJiMZ8lLyffNT9NvZ54sP5avNviAvuiHWRs2OR4p1ismPftiHHS33aWqDPGxlb+jo2bvpqv2skJszXKw+jINvy82Y3hhtGd77RFltRB/o50dkG/ffv2/p67oUnH4/H4sEhuMkzZGQ4nrhiWnPqw0ydTuGBphfG/+cKWm5BftiO/hqtJr/0d1eZXjcbNX5M2/iPF3ykWWzme8bLF5DZGw+Y7dn/qP22v+WTzT9PzCQueLX9ropoD303IrquvwGb/psB0qAFy7mpyDDpfKpRJ3/RlhmbJSOvLXm0VLcew3caRiSVrKa8W6HnNnKQZtgUpCxB3E6zr+nh+fwvEbQWau3RpA5OUPB4P/f3HvHJiY+M3IGHJIHA3qUuesp+WKGx00E5Zn3wwwG1BsOlmG2vkMbqgrkg7F2PYZ0ueM6hwJ5273OknnCDYUxfzffPXU70cf+vH5MPk+g6+ZFse1W0+lrRPHe6oNt7og9T/Jo/Tqiwxc5JIk2X6ccYFo735ocUZiznUvdnb+BcnJNtElfQkHy3YG9YPXUmf4UC+cwFow7OMdSzTzykHaDg5ciI/2abZPPsb+RHjLH7be5Zmyyc5kyaLY8Zn+mzbdTnJOD9vpy5y3OSJtJrscozNvswum/w2Ho0Pvjfbtn5TD7N7Ojuo3759u75//359/fr1+vPPP9/vWax8fX19P8HVnpWQfG4bKxudU4+YbvoY27f/9yQP1D/jIfkxe83rjbeMZxb3GdNP8bzRm++8Tposl2DZfI/3Gl5zTOP/Tq5AHk8x2tob7Zv/Wv12veE26zecvFNuT1Tzd25G7JQ0TDqiKcQCyinwbYVAa0beaNoSlgSNTIqsvo07zpDBjcfpWCgHS3Ta5wQ0S04oM8puvp8M99TGkqm7hXq08a/r+hBUU09MovNze3BL0pl9kP4NmMjDM/eon+Tn1J/1m3XNrxqv2c8dQEwbs0SpAb8lLhmkkm/TxxYccgFj+hjf3RLsO8kQ7xPz5lrDIeqVckg52TEyKy8vL592q02WWcy+GoYRp3NyY4sLpJ/9pBw5fk7y8hrrnk5KELezbzutQXuYxa0ca+jIBUaeXEja7eg9+W7Bnb7EeJT9JH1NJiazVkz/+Z50U/dNDylns2tLeMy/OLFu+G4TiC3PyGtbPjD1TrtXmZw2DM6S8mhxx2wg7bphRfNTO5FlbZsch5YWL7cYY+Pw3XIpypK+YjSmX+Yx3//6r//6NFH9/v37hwWm6/qNBfPzojwuOrbAcQcjaM+brIlFTY5//PHHB4wfmvJlO7Ych/LiZJHxiP7QfChxprUnPflTMuqP5RSXs2yL30ZHo5E8tnvs77o+btbYqahTX8/4z5RN/0OH6XTe21jEX4sTd/i7W25PVA0cWQxU8nr2Y8wYEG7OeirTPt+tTuOxOSWN1Oo0oOGkaeMlV9iZoM37iaeNz5TR8H3HSdsYpIt93DVaM34b9w4NeY3BuU2M5pollBt/jZY75a4uT3Z/klleMxC8Sxf7ykCdu0Lm70nTvNtiQqPjju8nXcarfW60zedmBxwrJ8GWTNkYtL/5nKcGpg/21UqbUCS9WZeTiO34Xwv6JqMTDjDxtKSbycuMMcG/4SknqtvLaJtr1OMd+fH3+5SF2X5eP8WYO3TaIlzWS+zf8DQ/8xr9bEtQ8/M2UW1lszfGV5OpyWsb9+514gz5T/uc+8ylMr9Imi3us/3Isp1AmH6IUfmifW+4eZIR7azFsZN878Qu+pfFmrnOSeoff/xx/fnnn+9/ITM7qXP0d7AhbbvhYhs3ZWu6pExMFi3fGDtI2uwob8Pm7P+6Ph4bbruq7XvjwWI5+c++EossLm7XGw2GsQ0Tmh1l/yfet/451j8ptB/DnS0+T5uJo3fo2XIJxhbStNnTVv7XHqaU983Q+LmVLbC063ZtVsFTaCfDYMJDJ0rQyutTNsO+G1DZn61cWJBrfbRJ9xQek9qSqfzO+w2A28pYc/QcJ/vMY402/lbaMUsCcq7Cn/puSard3/Tcglt+b6v17MMSSH5+1h9ZWnsmx5RJ01v63Cb35mvEnC0x3+hPWhrfLdjP95ygW/88FtrGyLbml03fzX9TxpTR0DIPepqgxYkWkzPKY+6x740/4iDthkdnc/wJrLO7kX3lAyJyB5M7qcNr08e0yQTwzk6DJbKpU9q8Pcgj+0v5zj1LRufe4/FxYcMSFe5Oc2fGfMn4tWKJtcmCO9W0a/OHxGg7crnF0+yn0ZU0WBzkOK1Qdvk/9GMf88Ce06IQ6TMcoO1tvDPu0QdNrndyqNF7LlTYAkjaJK9f10ef3eJmyu7bt2/r4tO88m9jps6ff/753t/0k3g4suIxX9t0mJInLMz/WGyx3PRGmZCG1J/Rup3eSzqMTi7mZWxNrDIeTM+G9RbbSP+GUWxvmxHJb7Zrvt/oN3yya639s+WUA5hN2Pcs6asnGRgeWty6rs+5kJXT/SxP76i273ndEhgKqSUxJtAtuJyAfTMWM7hsQ+GfkhPKYCscn7Sm7H7+/Plh56AlxC0gbAZo9xoQzTtXp+Yag+0dm6GsTskB622r8c1umKhNsvvy8vJ+VCcd/ARaWwC34NKc3Hi4U0y32ed2tPnUJ+3slKDRHyxxOgVc0rDxasH0hDN3/PNUTIY85rfdP51MIQ93Aue2c8dkJrFkZDY7DdOWf2tEujP4N5+fay2gzwRw+jO+Nnnkcar8bRZlwkUC+0xZpfxy7MTfjf+5Z4mCTXgbXlkCd0qqWmxocky7Hbry1An1cMKpOzSlnNLGDB/mO5Pxxt+JznZ9yzusXurz1MbGH3vaEvVNlvPZcDfvk975h4TH4+NTVmkTm72QFvoedWefT/KhDeT4syNqT+k9TVTzQUntXwWmzPd5iB8xdNNNlsRg8mYLRc0WWSd9No/82iJew1jTEesl5uVn2snmQ4ZfmYu12NUWVhqNLHfi56nQ5nlyxHSU38m35SmWd2005Ds32IirbQORNFt+tMW35G3a80Riw7O7ePm/tqNqRJG4phhzoOmLTnvnWGG2P9Ha2mxGNp8zMLC+KTvbUk42HvmfsdrxEzOcpDGNlm2tH5OrJRk5ro3BBCT75rXmoFYaf41WC37mWNf1W8bp/M1+W3CnHi2xys8NmDZ7JS1ZtrE2wGp6swDaaKF9Gx8WcFufFuAaz7y22dNdoNwK/T15sdMZY2+NPvNjo5X3OSljXQv4mdDRf9/e3t4nq0n7lHZclCXtyGzAJn5Gu9HBP1lPnBxZTDKabVNmlGe+25GxlHnDrKzP30sy2b0jP/Kdumr4d7fPbJt6ML7n8x0M4LXNfhlDruvzLhNtl5MJ0nmibcPW03des/E5WTQ8TPs8xeU7ZYvxSev4d8ZA+n/r22jbYm+Lh61Y28TRkVvujraJKmWR8uZTfZOuPOVgiyM2WaUcs0/D38QG6/u0+0l8yn7ypMYpxvJ0hd3PsQ3DSd8dfCCWpf1N4Y6x8WI2yfENO088sE/2ZfHvhBN5bct3273te8MKy582vDT/Yz8bb0n/xsszudftiWoC2nxvwNQIN6AeJlpQomPPhKLtHhjdbVxruxmP9UvwzSQ0A77JY8rwYk7IoPzz588PjrLxYQlOthvApmGyPwIVgdF4NPlk+yaL5oiZWGbAIf8MOgY45GEmpD9//ry+fPnyvtrMZHKjm/cbuDYZ/G+WO0nCBjCZ/M419mM7CGk7Fnx4HPF/i9cTT7zORYlTacme0dDoYzvDpBPd7Tv7av46xY71/fr16/rjjz+u19fX96Qv/6KhHZElDeYrdtJiS4SNLyvsc7As9Ws718SvudbizSR95JdxgvTkLofhQZsEb77B+Msk/G65Ewev6/og05ST0bkld4zDfLdEqiWdOcYdWbVrDb9P8fpUd+onX3aMfhZP0mYbz6fYM32P3NpxYtafxarH43F9/fr1A743bE3eT3mHFfo3PzdMMZnORNXkyx1qyuLx+M9pquHXJpBcDJnX7FaedvUNS3ISaf8Zuu3WUo6bvrbdU5O/6eMUmzb8am2zj8HJec+xzf7M5jLXMD9p9pg7opbH5Pe7uSYXJTe/MVqJk4YDW64xfGUd5l7Wn/V9x/7ulhMmnMpTE9UtMGzgviUlW/Ca981g7wJjGgFBvY39jKLS6I321n4LQOaA/AsKSzYY7JMmBqdNTtOXBVADSeOD/DRHaMBotNhxvs0GNhnn59w9GnDiqqS1I39Zh2CR3+84usmqgfHWXwOjxo/ZFeluQHxdHyeDLQi2ALcV4hCxofWRpxFakGDZQJV9bHraZN7kfEfvvE47aL5mdko7H3n9+vXr+vr164ff2DV85NiNxzv+mjhkOLWV7NN23fh9eLadCCaRhkc5ZiYEdlQtk1GbqDZfaHhqJ3ruyuiEoW1MxqTND6yvZ3Ah5WafWddwzHhn2bDjmdLi5snXGddTDlnP6M92YxMjJxuv9ZkLHdkH8ZU+yTFOO/z0Ib5vMZKnJebddk/NzlK29MXcNc2JqMnL8gJ7z9zIdmbt6dRtIcjkaG3uxHeTPe81/9/oeNaHzJ4sVp3iYBv3xOMdeolRzWY3XbRYRvoz7rV6Zh8t7hu+Up+kr2HhKR9q8tn4vWsvTx39NcFsAJ+AYQHedm34P5gzLp2ZD9dJkLzjgATxtuJwkoeBrtVpZaMxA48dFWOi0Y74st+WmDT6tqOEQyf/C9bq87tNcE+7L/OdR6XM+drROvKdD2vJY0EMKsmHjZd8zeeRj4FX25XMdybJtCeTgU0m7gQTrkbnsdChZXxnvltwThnNosjLy8uHyY7xarydyhbgsh87ibGNQ+xq8tuCKgOVlZR3YokF50yajIdmZ6eS+DxJ2svLy/sJAz7MiLbVrqdsKXv6d8Ov6a8lBSnHLJZgb7oZ2bWJqvlc6o485hg22U18sl0b0xFjFOXD/rNsOuFRyemPeuJvnGyi3RYtGz6Zvc/ntmBg+G76yf7JO2VzitGt3cirjUv7br+HNH/fyimuWxzdsC9tIWmwHSL6kvl2k9kmH6Orxbv8Tr4ydjJOm/3MQ5J+/fp1/fjx43p7e3v/n9S0MTupkt9ZKKf097aAtul9G4PjtX7MH4idm/6SDtsBPY3ZeGj+9f+qGEbZd2LWZt+Px8dFItrZlkfwe8sFLGa02Gv3t3snW9p0ZHjEeomVjdZWnpqonkobmLuNTNBNoW2SkYKZujbJbIppdN41HhvHlMA+yGuWO+A+gGKym7EpZwP0BO80RBp6ynU+J4/kpwU/yq05rAWX4WHGTxC4rnsPj6EeUmYs7G8mWaejOGY7m023I39Gf+qWbS0JSbmxDE8GypmoWPI6dM2x6DwebeDWEkWCLHlu8tzkfRfwkv+W6JFm0yk/sx/jhTJu380Pp+R/8m20tqOmpNkS29R3+jyTEpMtP2f/hhOb/A1DTslrmyTS5lrCsPlp0j+vmXTkYozRyQmW9U0dNtlkaZjU8K/hg/FnOpr3tIXEbdJkiZ3hwbQnVlIPmeC3XSfTgeGdtTVZtri+xZiJUzaxv679ODrjX8qxlZO+eSyWvs6/Uco+GQcpK/P1hv0szedbHG39knbyn/iTT8SdazMpnf9I5QQ17X3GaYu0jRfDrOZvhten+NhswOT17H3WyZyM9k3/M52YvCibO4U2tx11n/FabN5+NnHyv6wzfY5sEr+uaz9SnzTZ56TbMGLeiX/sjxh94sveSQfrZzG7MBveyt+eqLYBmvGx2ITJgncLRFa2gMh6z/BDZTMBs75bcCOP5mxGYyqaBpLXWx0D7QFc4yMDk7Wd0o4h2NgsNvHOzyZr2k0LUqeyORknDgk60/bkYAxyGRxtokpfaDrKRHFo3ux+sxsmCZnIWPIyJXlKmzDwvetrz8r2WaCbus02T0HOaEwdsT9+H1ny957czbfxpozdtKN1c59/4ZHXzE+ZvE7JyVcLoNMPsYK7Dy1wtqBLfGMb+gAn/Iwp20SVMjdbTv6SPlsgsrjGUwjcVXmmnJKb5h+0Gyaa877FMI67+X4W85Ecsz1winjZJqgcY8tDzMdbXkH5GE5bP3y3BUIbi3lBjsn2xKOWW8zYeVJoMChjaPPZtBOTo/ntCUfv+LzxlW3yu8mXecrj8XifiObR3rlmf8vDfgwTzUbuYOcdWU0bWwja6GS/LQ63sbcYnnaV93kqyNpanKde8/OGJ2PTzF3sxBaxmGNa7Lc67Z71YQt6iQcbVhsd89nGNN/hd76YE265Y7vfZGFjW51TjJlye6L6+vr6PpAJh0HXAt8WHE1pXIFsgNmOlG1lS6C3gNv62Qw9DTPBMJVnCXP2fTLmNq45/IxPXZoD5FElM7YE0GboRhf7IriwzcjNZJU0zmfS0freEpmZRGzgav1Sb/Oi7k3/Oc62G8vxOGb643ZSgb7J1XbSlbaSO/TTtwXnO4F46LxT0h5Nf63/+cz6s0M89kN+rQ97JxZQXt++fXt/QuU8qCj/z8/wyzCgYd0E4XxAx+vr64e/LEj9c2d33lPODO6G2ZSX0bfZwOwU22mRO/prOJZ2ZbtBGwayH35Omacf8CnJ8267bHf4yX6yDRPXhptZEj9fXl4+xIHkwfSVtDCWUb7ZB32b14hJdi15yTjR7GpLnBpPo5uk1Yolig0baEvEZjtymQsf7UnATDQZY/L+8DP6zd3/tAPSb76YJzqSXsNhTmJMRozlJs/sj9hjNsf7iV85Kc2d03zC75Sc9CReWp5jNsndaaO74Rxppo6bfXPcvG7lmbjZxuP1O/F4+mY9LgZaGYydRV77X9zBYC52TRzM02BTtkXixs8JZ7jplPj/zCJciwNNVpaTm/0YPxtm3tEr6Whx6YTNLLcnqvN0tC2JnWKBNUGTbZoACWLNeEhHU+j2nbRsxcaz5CP7SuChAo3mljCwDgPiRnvSw4ejtPFasjglHc2SuRbEjRcb90RH0s2dTyYIGdi3saYtk6FsewIy6iTHN0BKoLSJ5Rao+M4x2u4EA0ybMCUttOEtYd7kYsF5481kSvvPQr88+QWTPrNf44X+Z7g4Mp1J6kxUJ8Dab0C3BK75awbkx+Px/iTfnLzmb8npO83/J7hbYE1cbzGBMmpynLp3dMbS2jyDI0nPnfGmnU3wWoKw4Q/bb3hsfTfa7yQfLUkkPWkDFsuyT9O/0c6/AmlyanQ9W5q8Z8y2IJ5jE8fYL+uaz278bDE5x8vxW93E6flOXWb8zL7NLxt9puMNQ2fMrGv9GMYlzlHujJ08YcLd05yAN/6TlhMOE0tbbGy+Y7GfC4VNPlaszTP9UO8nXD71c6KH+Um+52SU/4XLnyqlbaVf20LRdgKo8UwMMPtt+YnVZf76TCG9OX4bc7Mb8nxH55RbFvv+DHbfnqj++PHjnSD7PROJ3sArP9N4W9smtDS8TJxOyZHR1JIkBhQG4AY2DOR3AIcJ3xbU8vcSPPY29cj79D/v/N0K26RMKRdLwKyPprsc32TNNlzpHr6v69KdDB7La8GnFePD2toKvLUjcNpYlOcE1NZ/03HKjLtsbfz8r8mk0+jh4/u34GO2m/etn5SHJQTtNyX03xONHHOSFq6GNh6Ig5aU2kR1JqizKsyHrBjGJp3bxNJ0bhPVpJe8pv38/Pnz05/dz0JX07slYrYIssUHu2/1hk7it9lf9s1xLKYlxvPFvsZ+LC6StjbJS3rMxi3hPSWdzVeu6+MCA5MHs+kcc8PT4bHhOTGFfkocOPnh3dIwiT7WdlVtfMsZjP7UqflAs8nGR8PxeTc9jU7GTpnc2zht59JwmW0pF+Ibd41tsTT5yZ2xefCRxbS2OMsF1qRv8qLrut7lk3kFabPjpua3uQiUdNjPMajXhqVzz3YCT3GO/tV2YZtfEwf+bqH/8HPWSXkzdtJujNY8LZGnR6Zvw7ekh9c27NlkkuMQH9P+snAS/cyYyX+LrQ2/hh6zO46RcXKjh+PdxfCnf6M6gcUC2xDdkjxjuCUUBoIpiAxuTKwskSDwncDZ6My+yF/2ZQDZHJCfjZaWQOTYLbBuidDcHzrt+B8n/was806QyDat/dCTY7dEj+DJZOjt7e1Twk9+0zbvgM0Gxi2hZGKQtFr7LQkcmk+TreyH/883cmFSmOO0pCMBa2hhAGCdJksLfi0oGK9Mbmzl2vrkSqXZ35ZwkW7WTzr4f6OWhKVuUrfcPZ2EckrWm/7M3lsSstXL++lreayKO+ppSylj+iWTmxw/k7e7Sc8pkWj1DUOpQ6NxZJ/+RB6ZqLY+Ld5t+rkbyLc2bbeU8rGy+cYpIbNYQRlu/m8JEPt/Rj4pZ8Y6s3vGfNNXi21mc0ZHFrM7llZn+KAfki4uVG95CHlm3cZj88mGu0M3MTT7zYW2eUpvTlQZe8zuts+pS8N1ysc+c7OAcTZ5sJ+AbfHPdvlN7ps+sqTd2wJ1a0+bf7aMXGkbd/x5ZEtd2yQsaSfuZF/8nO2TTy5w2CKc0UV7yP6Ig5wUMh6Tt6TReG24vs3PqAPuQhve5bUNQ+Z79ncXv//Rw5RsRSCZaUExPzfnsuSOSY3t9tlKdQu0W+De+D4VUyLHbd9PAcqCY64WZZ8p100eDBgNqDLYGV0nOWyGPXyYUTPhpVwJPgTD7CcDutF9J7jye8ovbdPkkX0wGA6NmUzwOBb74Sv5ymSEdjP3U0ZJD0vaB2VOO9zkl/0RgG0iT1unfdgqqsnLrqcMG9/GCxMqmziedk6IYUkfdWZ6H1xMv6EN2vgtMJwSBO4kMOG1YEs8snEaTm710y7IL/tocqBMKL9GI5Me0jey4USnlYbDjRbj+U5MSnlYnG59neynYRL7Spvg5KLFKY5vxWR8snHTOWMM27UFTuL2Nmbr/w5enuJQXm+0WLJJX2Jf9PsTbXdyBYv/NlFNPnNxbCaq9hcyW2l5DfWZ+Eq+mz/QLogV9t5yIisbdpMf8yeLLa1fw4NmK4ylmx4Mj7e6Oa7Ft4w9FmuSRsr5JIPsZ8ujWMxPmReZzvmacU6nDSkP+35qz/vcwT3F2s1m5525z4kWln/89zRkIpMXW7VkW3OuKXY0hUZ6Xb9BbACsJUgUlh0NZZssW0LRyqaYO+AzPNv3PMZDWowvc9K2G8SEu9Fy4mcD5Qb6KS9LrsgTQctWybeg0/gy0KHejXabYNLBzZY4iX48fq/Cpq2nHDabzMn6JNCzszr6TmBkYkKfyyTh69evn4IugZIyNPs0ebd+mEQQH8z2TI/UG/swf+M1rkhvyY3pPxMvsynSSprps9SZydR00oKu0cCgm6vLaSNpt5yQmFxzrDYhyLrcwbVCfLPkl+PlOJZQcpJFmjYsJ541/2h+QZr4F0Qcy2wqsZBy4HhT2ikJ9m14kX0Z/tkiU/a75Q13aOK1pLUdd3zm81bapO66fj887JT0tVhzoqPJPPvdsCLf80THHLO8EzftOnel7sRE9pm+Zw9BeqYQB9Iu+NwAFuak3NVlXORJjG3Ha2gzGzLsfpZXls3Ht/YtdrS2J79l7tFsIG3oNMcgrVOH8drotfiTT4s2/M38gfmM8ZtxI2NDxtasT/oYE8hrfue7nRjIjcHkO8eyMUhXyyWbbk/lqYnqs6CQk4cTYVs9Kqbdb3RmuxPItj7t+ua8/6SPEyg0OSSPrEeAY4JlzkJHMh6njQUZG7OBMx1+xrcx79ghx9lskIlVc8iWABrQmR0Y0JyANieTG21bwkDfajQPjQYmj8fj/Xch85CeAcdTAsIx7NqzSS6BcEsqTglRm+y2AGv1Gh3Gz9Z3u9YAnqu92bf1sZVGa2tvmJ07ikn3xqfZC21vsIrjGU324vG2rJu8zHgzFk9mnMZNmluy3orhLP3eJqo5liUEhu055h2dn+x4SxSTjsERkxHjdMMhyifr22e+/5MJMEuL9+arFpPsfdqf8qGNlmd4IG2b7d6xc+YqW/8n3zcac9GtYUv20+oy5mUcsCcuG92tz82XZoxTLL9jn433zRYa7aT1NL7hzylWzrV8n8/b7n3q3fKMdrqT+DSfOV5r2+IQaUkaUw4TQ1rZchZ+N6zbsJv82LUWLzfc3xZlrR+T8yYTK7cnqrZLaUBKpjZDzc9mnLzf+rDvpCmB34wv+zHjvVNOgGnft+SH17YEvoE9wYifs94kmLPzZoGJfTAJsd3vllykE/MIoYHoyeHaGNlfs9ntRRmcVjobfdzBb86c97N/Jqlc1Wt6TloscTuBVsqIT03kzllLcigPfredrRx3O96V8mOwMxvkuLaS24Ipr7UAwtICT9PbvJ+CquEtadnwLOmY720ydcLi8RUuMJ1kYhjB9oMVpC1PLuQ1s4WTLpOWuZ5HfJM3xkP6ytQxHzJ7yfiUddvklA8gytKwxXCVWG4yoWxsB7ctmDQ8SzxuNmLyyULfaQuBlIklweaflIvJI99Jbzvyx9MNzYfvlObTd+paXG74nTq28Sw32XAqfWSLF0avYV2TneV3LBMD+J/WmdeQ11MsIp08AZKLbhv+n2Sxfd54Po1BzDzZyhZnW1xtOMW/GEwbyTwxv9vik018s55hg9Gd+pwYxP/cNZ8e/SZeWp6z4e5Jt9muYWXTf8t7eOqQfFmsM5rYp8n+ru//o6O/dwDVDDrbJiOZ6GRATIC0YDlM24/CTYlNQc2pGng0gM771i7ltyVyd8opKciEIGluNKVz0XlZL99pkGzbklF7CmnS3XgzgEtnyATz9fX1/b4d0yTgJH1G21bMvrN9e7VjEkzEmAgkeDSgzLbNxpPW5qPTz8hp/DCPezZ/sEBnfTNQ0YZy7CztGAuTQ9phC3JJW5vwGBbdDdYJ1BuOtADCwj6or3bMiTTYf/1SftSH8ZHy3BYgr6s/fM7kYnKdkrzSfhrmUR7NPgznWC/9kTZOWznp1Y4Zb8d92Wez3cbrnRi4HV003+FfR1BfNtm2HYkW10wHrMdxzQfS9nPsvL/FsqaH/LzRueFF1rf2W0nd2ThTtpMw1NkzpfVn7yeZst9sm9da3Y2OwcaWuyR9ecSXdZjgk7d8ZY6burkjj6bPhr9/txC/8hqxecNnYhHzMMObeZ/Nk+mfcXNK6u40jtlEo4HXvnz58uF/WNMeDMfYD3OFeWdOk3Zwp5Duu3Zgdp4/R2r0ZXuLIfxu/v5MuT1RbQHJrm3JKZkap02DpDLp9Nlf0jDBMRODvJefW1BnnfluvGyfrS5p5bUMiKfgYnKnQ1nZ9Jh1TmNbYspjcuSzJZ8NYC2ps5fpPGWQwDV2lsB2AlzKjivLxk/KcSvPJAKpW9Kc/Dc75JjNBlnfaE3fHXq4atx8JBMjJgypT75S/qTPdlOSdx6VtLaN76TPJqqkzfphsMzjjxy74UWzE8rFsM4mqvk523LiaJMHtt+Kjcm2TNiaLd9NiHKMzaaJua1ejmO00Ca2eGE02LV52QQ+292JbXcTBdqpxaPEUrOFaT9Pi95+70fsMgxqcW6zv43/TYdNvltc+H9V7vrXCUOYW7Bu8ncn7jdaT7mP0XGXR47F982H+Jnt22kV9mN+TVtqss7x7tjSSS7P2uMp32PdhomnXCnzgsTjjEGJCcy5SRdzStI874ytHI8TVdOnxQ7aBRcYTvbCPu7UTznewWvr13yE/WxxtfnyFn82eoznZ8rf2lE9OaQRkgH3uj6DTO7UzDXO7KekweVY/FuOEaolLjTedKisO/VpNDMGt/zJuxlg8kDnsOTgTtmc4S5AMliZjglU2Scf6tQCQLbbjoxuAJqy46pZ0pB0JEDm/29RTjYmg7nR2YDbXpw0tABoR+6bnqkbCzamT9NpA9qkhRO8tuuW92YH1uRF/aaP2sSOMuE1YsCMb+2nEKM2/zO7zsCa8k6dk8ctqcm+t9KCeo5t/tFsYWSRf6XAHb5Wth03ymw7HmsY08rmU6fkinLIwhhyXR//s5ntjfa0/exn293jsfrml/NO+7L4QnrTNsfHzE5zjCbX5CV9NrGXfL68vHywsaYnHu/b5HcqlpyZnT2bSCVPxByO0053XNdnfzT+NrrZx+kaaWb/+d4KsaT5bo7VaLozjuEYfZJ+1+TUci7mKMaPxZxsv/F3+qnMFt+3YvhOHtkvT7VxTMtxt3Ez3uRrFq4y/yKm5Ge7ZrEiaUgcM0wkX9YPabCNgev6HR83e2+5BGMg2z+T57Akrrd6iUVZeEol6xK//gltxuNWbk9UcxLSnPtUEqTm+5QUggEf21jwtWsMxnOtBXUqeMa2BNTAxoTfwHrGSvmZgTUD2IzBrjUw4Dj8vdGdIG608NhGkwdfBixZP/UyjjbjGEC3HdC7srZ7G7hl3bayaPxmW/JuAZ7+sdFLmlOvBrTNhppehi8r6SNvb2910pn9WGAxGho95J/2kfdNtpRF8tBozH4scBkfbSf4FMSNB15vycpdXzadpv2azQ4m2v8ENn+jHDIBeCZJspI6I88mM14/yZX1zGbsd9zWv8VHw2HKgUfemu6N7xb3mqxoE4lzeb9huCV8pIExg/fv+F+OYX3ZvZzY3IkL5IN9Mgk83Sf9LM1vGya079nGsP/OWObTrb/Nbzfca/UNM/J0FGW82SCvmx8bTzNW2tO0Zd7Dvu48EX2Lf82ezR/oh+Y3Ock/8U0a+Z664c5pTlT5O1RiNMcgzyd52Is8Mg9r/Ge7wYe3t//8y8jb29uHv0myn0ckH0kj6WHZsOB0v8V7tmtYcaqzxZNpn/6Yc4pT/mHlqYmqGbsFxSSSZQsAQ7gJNo2LjmnGyGDahJ2frZ9GH42xgV8DG6PBaDH6G5CbvLfAne80PKuT/ZwCC4Px5ox3wHDjN48tWiCbwhW0LUhuAfO6rg87AEkP2/NIyrbjRp4NbDaasv0G0CmPtGWObf3e+c73HOOUFLX+2++Cml9Y4NswYGiaI4222kodbCch5n1bLbV+Gq1NXoYV059NKF5ePh7tbX2bHZ/Gf3l5+fB3SnzghNE716bO/P5nxslgd0cGpoNTaZjLOiPTVjdpHV4mMc2HjzVeKBOTu+Fk7mBuWGL83rE9kxGxbcNdS3otTk5bSz4bDVZnSzzp7y0+tmPyhqnbi+WZPOFO25PvtnKHXpMN6dh8butv6Mv2bfc9eTnZXMYai+F3aePPz8wmN/luixTb6ZRn43zSsvlExgROVhuvzA049uaXOSHNU2w2/ma3bVE7cz/eN1xmu9Znvmy3lBPRmbAy1jPGUm4nHDFejWb2zWL1W2w72bTVbyXxlhtff6c89dTfGYhHcU5B/ro+n+220gAmlZc7aC1wtf63YJxj2FHhGfsU4Dgek63sj/IxGjMhyPuNF+OrJVT5nuOxnzsBsu2mUW9ZNoc5lRYsuWtJPuxkgI3N95b4kCbSkcfp5j53QKwP0p39Gv0ZiDJQzGva5GcGzjySO/enWFAibS1I0q9OwEsZW/2xOeqY5Y4/tDFtEWpkOAHUElrKbsOGDGbcVTSZXNfnXQLaU65iU+b0x/zf6U0XKS/bBTY/yUDFPpLuxKFZKBjd2n9Oks7teGnaN3GY9DQbJ62GHeQjx5+Vd+4Ub7urxnPzC8aJlhAktmQb05vZK7HNZHFdv23LEjfT3/TPndRWj7ZG+jn2FrMpH8rKjnkPHVtb6z/bEYvvFsNmltPPG0gjT4tYG/PFtL+kLcdtvNF3cgLD3baWn9Dmkpf0NXs+wR2/u6uXTc/ZX7NF0+cp9ia+0/c5fmtH/KUct8lWy0NYJ3dP5zXxiYU4TkzfsLAtCG8vnvrhAkLiNvGb/kMamUuxpMw3XGRpdan3ZsOsd4oX2Y7xbWJ7y1WYa5OGuzxf1xMT1cZYAw4WgtqpGOil8M2xW9+2s7AFxAzoVjalmuANICkPO260lQZsBroNSPh5M9o2tvHTeN2McqOv1bd+bSHEjh8zyUq7ao7UAp0lOBvvGRSsbuojbX6AIRNGk8Xp6FxeY/93bTBl1WyGfPD61jcnT2Y7M6GxMTZ6Gw1bMpFtNtkyULB/0rKNw3bJ9yZbo8f6YZBvxbDe3o0O48fq8z5tnMkH60xSQ/lnUmKJxcbvFiPm2oa3oxsmakyKTjKzBC39g3LYEg/e5w5ms3/Gi83mk8aU952k5OTHFmdMTttJhhMtW3yzuhtmWBmZMdlv41APFqvuxJtGe/ad79beZGrxz3y+XTO7p2+dfMOOXXLXstnCCW+3XMnqk3bD17nPY7dbLjA20xYkbeGb8ssdTtY/yS7L6TRR06vZPmm0jZn8vPk0dW36Z9zLzzMZ/fXr1/tOaR7Vtomq6f+0MWM+xT6s0O9ZeG+zc/PJE461OMDxNn62nKSV2xPV7chFM/pMxE4BKAuFbceBNqC8Ll/lTppPhsKdqCnZB3d/TwlfUyJXl9JZ6djszxzGjDh1RV4IKGZ8pJ1JFo9mngL83GsOR9rJlwXmpJNg3JyU93nskPwbTy1QnYDBQLPV5bWXl5f34/hpi79+/fqwYpnySB4tyNKGTmDVZGvyaP7KPq1dk7f5dku2nhkrMcvqW9BvfXLnrOn/uj7/DZfRbH5OeTQZW3Dmg2y25HCTra2spp1sAf3kBzbmdnIg+x/aOFE1mySN+ZARYr3hZd7nMdyMO2kXKTPiVePHeNjw+w7G5mSSssj3LT7Miw+BSrqMnuY79j71mVOkrhv9p9L6G3xNWjf+t/6p33YMcsNLi0W2KHCHnnk/xVjGQ8oqx7EdO46TNNCm6BOki/zZ5Momrlsc2XKmvEecsbhhMiG/W95MmSeOzg7lvHOy2uJH4uW0y2O19F3uJqZtkR8W2stc4+TWJqQNq9LeGrZNPsRd0YxxLS4m/2wz8aPZ1OafySd9iGM3mT6Dl/n5Du6nL1v8zX5M7sSuxt8/Lbcnqt++ffsUQBNgbIueJQF/SgNLc95tspb1UmBjuKSXfZCmUZoBZdIzY0092wbfFN/oycTIJsVWGv+t3waEBp4EqpZ8bgE33ymHVrYAOsVW7PO3ctzRIJ2W+BiA2hGPUyLGRIJ0mGwbIOQ4aXMMCjzKNQCeoJm+1FYWyV/WN3mabI3HtBv6Jnm94/MZBKddCwQMGMajJScmv7aDNfRMPQNt+mrzo9PnpDVl2ZKFCd4MSkw0s+9ToKRf0Cd4ciD5zjZbkEy68jOf8MhCvJtkhHZhExzb7bCdzJTV169f3+sNbfn3WZPgDK0ZQ/gy+VPXlLnp0wp1OHS3Pm1yn/Xse75Sb7R5S9Y2uhsNIxejs8nRfLfxznZJzxbjcxzD/8Yn+R3+csz2OsmVsc5yEOtz433ezU/5Mjs1Ookd+XmbnDYbaDLgddpE0n3CO+LulMGB+a3mYIMtdNJviDFfvvznN5/8mxe2z34ML+dem5TlYprFzNSFFdrO4O+0YWwlFqZOqI/E8tfX13e6f/z48WEH1J6VMONbHLDrQ8Pmb6TVcgbTs73zfvZN/Gh1WNrYzANaf9TjhukNpzm20Wnl9kQ1/84jBcH3xswGFvPOvsiUlabYBlIbvUkHwcacNOv/nQDUji2aQ7WEfd4JmK0Y7eSjTVTb2PlO/hMozZiN/6Tvuj4vUBgtBPYEvOkrJxd0qC3AsM7G2ymB4Rg2yTa7o11aMJ1606ftAjVbnc/ZNsd/PH5PBpP/vGYrpM2uRzacoBNjNiw4JTkWSGiDlPN8Tnna8ap22mLaJXgnfW03jzQZLhq9trqfyR3t0Z5A27AjdbDhOvmhPCyQZd0tOKe9p8xtwSDppx5Iq9keSzvJY5PVxGi24fVZeLSTNJR784WcRFOPpNHG4Pdt9zY/21gmo2ybNm6nBtqOl9lisyOjZesvFwryHv2UD81rMYxjMB60vMn6tT43frfJmcWgLdZxjNMuWtJGmTDW0E8bjRbXDCN4NLPZfcPShrusZ/GS9HEcyuvl5fekNCeY2zFc4ve8pn32Qzy+ruvTLiJ1YHqwSb+VTX9ZyEfqiD7YfGrrdyajuQuaT+HNh9iR9rQZ85vGL2lgveTJci7LuxreEmsyDrbScqeTHI3/1kfLLzaM5pjPlNsT1f/zf/6POmIC+7wPIfZk1CwtCeW77cJuoJBtW2mB/Lr8SGMmPNOOQYJ8kNb8fjIm9rf911UrNs6WADUnOiUz9nmSEtLDAH6Hh1YsQTk9LGk+t4dkGD8cK7+T35HtfE56zNYSyE03DTiv67p+/vypwNiCPsfI+2YHpGcDSLOvKeMj40M/f/78NJFrtPydYrLibiPHm3cLMLZrZ3RvADx1/vjjj9sg3cZLHptNZR+0JdZloJrPuRO/JSKn5JDvDTeMLl4zG23tr+v3JGiOsjGxZWl0n3yKOwPccc/4wZMFzwZtxt/pmydeSHd+b34/dUZPjOe2wGHxr8XGZ+yA+GBlk2FiI3XEOkbfdV16PHKL9fN+wtdGa/ZpMm67PRaXst/Nxkx+5h9mU0xOk1f6aIudJhOTVfoP7XHzZ4thtMOMw6Qh/ZljtPhlNHCi+scff7yfVLQndpMGwxfG/bSRyUnslN+8Jza+vX38q5XNp1LvrSQtPFHWTiaZHDffGBuYHdWZtG4T1SlJ2wlnhtaJ3/mZOPe/lcdM4Wkxo23zoxbLqBvLKVJn7J9+367fsZVTuT1Rzd+4meEkIWQ6CW0JSAN/9vV3FU8lbIne8JMCbzSfAkMznC1wUcnkYQt07J+rmHn9uj6v/BgdNu5JF5tc+f0ZA37W2A2IUgbc2eBRQbPrZtsbLxM0Gj8nm2jlGVBkImUyYTAc+toOYdLfJp95/e3t7cMxw5botcLgN+XOKuMd22lyoH4abfYyOZNnoyP52oJ1a0varL1da8lSa28LUvNOm2m+xLYbjfRJ0pYvOxrYfq9EP76TFBieJy2tjybj1HuzDcOlO2WLsTl2yiYnBfaUzJMt3Y3fd+3Y6D31cdJTa0NeJja0hRmLs0nnM7lLw5KWdzRb2JJJq8/+rJzwy/KMDQOe6Xsbx/oihlu+Y1idbfMIf6P1ROd1XTpRnWO8nKhuGGO8WF5LPzWszMlc4mWTZX7PmL7h9hQ74TV1m19usWdwaSbbnKjmfcu9mly2Yn604Y7xmXyQp1Mh9o3d5wJ4wx/2Q1/caLiD4UZf0sjY+Uz5xxPVIS5XdbmDcl2fjye1I3DJbH6moE7J1NbPppx0vDvHddh+6m2Ay/tUvhl/OhoNkv0aQDMB2oJpS2i2cidpMCNPXhgs5nubhCRPaXMsBNL8/Mcff3y43wBzC65s31YwDSyTl5wcbuDCdmZrFjjyniXCaRN5tKjZ8vj6tKEuCabzmXIhDa1wBbDJ0wLy5pMnv2mThgRfYh9xxhKOZnN3sG07lkUaT9jXkt5tpdmOCpkct7FSl9f10U6IATMmj+MajdRFTk75ecbKF/2PsqGubKfO2mZp9ZP3rJM8p69tCUaLp1vdrJMvm6hufZnO7yY7htVpT600bGx+Z/RaPExaNh42/z7Ruvky8yXDvqaL6+qLeC3ON1wmjpqdmowTI8kT+94Kc5OcsDWaE8+J6ckrc8CZPE4cnJi4/cyg9Zf0zqtNVNkPZWrypV3kghwnbqfXtuhoJ+omh6K/b/lL9pk2tcnO5Du4lLzO0V/mCY0u833SQF3MtcxvLBcxXznh752Yzv7Nv43PHN9OIpzGbrG+xUvqmRj6TLk9UZ1jhjbRycG3ySmNJx2KTLJsicAzAj7dS6Hn0TcLOg0ct9LAzRLVZ4zXjGi+29HNFlCsv42P/L612Y5at+vDiyWjLVm0BGm+5wJEXjvZdNozaSXwXtdnH0gZjD5SZjkeVx03GWU/p+MhpLV9T1rz6P4E06R72nDymbvUWxL/bDGQtTo8WnkCxxa8NllxPL4s0aBM8h5trvGf7yff5eesy0SNE8ATZt7BJvrtKSHKukwyhsYt4LP/tjhqi6SGL6dFlbme9s74Zkml8b35LDGN/bRrlBFjcdM15dLkeadsCRNlkPXpH+yLWLWVO3ySlnbkvl17tu5deu/E37vY1pJJw0jKxPqlnLbTH8kPFxqbzltMm+tfv35MX82HMzfIa5k8W/2vX7++L9R++/bt0xPeiUN3fMuOu9pvVBtmU47X9RlvbKJqsclopRzMB42uwbkWI62flhcQn0+v5HU+z2+XG8bTJ/Jew9XTy+Rnxery+x1sNds2PLOY1+IIJ7xNNxzrpPOGNXdjyHU9MVGdSRsdzpgyoLIdwelrm8Rs/W5B+5nCNtaHgfldWk/j2vgcq43druWxVjrciTYLlKfAZe1a+9Ym+TTgoPEb8LBvcwrbQZ26tqO5ARPpGODe2m32dtLP3J9xcsJhkx6zo5YU2lgZEJ7VO/3h2UTO5JR2YkBKWZ52Hu9OEJpdPh6/f4vPHSf2fzcANfswX5l346P5brbLybPZacOXjRf6MtttwZpJYLY96TxlbxPdkx83mk6F/dH/jMc7Y5HuNlE8faZO264/2ydtz0xSDcvv2r7ZdMOpZ/WXuGR8Z5u2U7+VFrda3e1es9Pr6piyyXlLnhsPbE/7brpizCUvdxaKrst1kGPbTzIMS5odmVxn0vjt27f3yeq3b9/eF2pzUpm4c5oIJI/t95nGg+FnfucEtE1Kt0W6lDOPRp/sxvy72Y/1zb4avcZL8punZO7sEhoeb7EuxzNdGN+n2N9oYOywdpsMr+vjM4O2RUb6bYtTFtNPujfa7sYCltsT1f/5n/95NzYeVzg5W36fYwIJaMMEDTDbNqPO1ZyttMB1Cix5va3cbnxvfRqgNbrvJqIWTPK4ybwP79wlS3k00D3xaEGKCxUWxEg3j8M0+dChLFFq9a+r/y6Vsth4vC5/2NQGDLyW9NiYST91l76Ydcm/HX8ymWQdgh/r5SJWtsnFkjbuqVigpo7Jb7YzHZ6C5Nwfu8gnnmex1dx2dIqFu/vk1QJiCyamuw1Pxm4yCZgj8NvucMOqLRFscWBLFq/r8xMh816WxJdcSW8T1WzD8c3HZ9yWsE2d/A+/Vp9+ONcaj+l3jI92CmmTD5Ms7mqlrgwvjI8mr6yT+hy60z6zXvtZisnlZIsmg5bU5ffEL/rRHZshLRvGUV6n/m0sng460dRoM5la7KLut/us0yZz0zb7MDugrUweakdnT7JPvi1XmolqHs9t8ZW0nWwm65MWuz+6bZOyjDspW/vvaNKUn81nT3SyHyu5e2wleRm68/Pct4e5Gc6bfO/aQ/JjL/ZpY7U+re32uY2ZPpan3sy/7HkM1G/afdM352PN/5PGLU6cNhBYbk9Uf/z48c7QJJ9cYWpBhkxc10eAzSdpDQMjjAQSMst+26T1jkE1BZ2C213jtz5ODj680ADYBwGT/TajSF0Zr6Q5HaLxRNqybQvE/N4M3GRyXX5ssfHTAiLHNvAgbbS1k83n9WdA0wr1fLLVjTZLlO/4dKM1g8r4NVeiEyBPfSWwMSEznrfV5eGRiXG2H5pN76xnfdKOMskxX05+jQfSkG03HlowaVjcdJ3BcMOR7JO08HOrM/zeTTqZ5GwryHdxN8f/J8kI7aZhKLEsryUPbSGXNkga7HVnosoYvMnBZNzwl/fu5AtsSxqf0RP723gxGzJejfZGT8OVZ2nn51P8njp3bfmOrvNzw3Kj2Wgn9uT3xE7GJibZd+KVxcaXF3/67uPx+LAQxX5oI3fubzEo6Uk/zd9jnnDuzotyYLHF1KTv1D75NF8jPXYyySbo/B9si8VNF4Zpd3hpPNgY13X+mdg2jtkmv7N/xoe5RrkkL1tuR/vYNk+Sr2bPG6beKbcnqn/99dc7Eb9+/fqwokUHtx1WAgmTVgugtkpigXOu5e4PSwt8IzyWHOOOU9MYWt1ngIJ0N+Vv45pTTh3T00b3vFMvjZ8tCSBv25gsTRZGw2kMS5x432hqCdIpSN4NnnmNtpXXyffdHb2h3WTJ4L+BmdlBymZ263Kylt+b7BMPuFuWr0YTg1za7PA27W1SmjtjrVDeiT8t2SIObjzbxIT92qkD+kHSNG2yzLVmE9uxoYZPZp9txyd53ORGmVHXTGRsV/qEEdvnU4J2wkAG67y+BfqpY7smhkebHigzyoY+SZ1ksZhBeljMn07JW9Yhnw2DSRflMfWMTuqJO1aWJBodpg/yy89tV2OTi+nHfP+ZOJdt+Xm+0wbzmR5JW/bNRWXybW3ZD3GBC4HW5pSXZJ/Zrp2iMzmc7tPPctz5nO/ZPiep+f+xbfzTNd6jnB6P3wsPiQGkj/2TD9NBvm8T0pF9m5wbvhsvafsNq6w03LNrGeNGdrlxZvQZDa0ey4bnrDN9bS/SQ/lS5k0mxLC0dfOFu+X2RPW6fhtsrrAPYbn6QmLtCOBcT6YpdDvSMIWg+/LycbXrrsJbSaNuhp59t+SCtNxRkvVpTtXGbIBEY6aMmmNuDkEHJe9GJ/Xf+DdZWT+plxYIWQzEqd+mbzrfVrbjtRw/ZTn2fCeBSPDYxqFN89jUy4tPfFqy1YCfPCV4z3fTXWv79vb2/iQ/2qHx1kB8CjGKR2DmffpKXpPurGP8p503H7iuz78nySQkJxNzzRK3OyV1zGsbBvOhHNZ2Fh8MJ7bdTeptk50trFnyYoG16Yl6bTK7WxoemE0aLZPsJ26wruHixkMrW1wz2mwMo4lyP9HA9zuJ4xZrSHPW43jkv8W6tnt12pHmZ6Pv7+QnyVOzJ9ab8QaLT/00ezP7y5L+ui12Ju/205Dsy2SUP3fZfoaWcsnJQ5PT1Bv6bGFiChd7DEcZg9I37p4gGfzPiRx1Zvli42/zi3kRi7KkLTH3a/0kbRYbLObZYnPzP8qU9FhJ+6OM+P0Ub03X5GdrZzlWK8QvXrP2zS84ttluvphHNr9mLpO0PVuemqgmE+lg830SlgTg+Wy/OZrSfhOS/dMhLNDcAfyToMwATmMYIObnFlStfX5vSYHda/2bAc5n28Hg52x3Ar/GH+V2Jym5E3BJszncP+n7Tkn73MDQjtc2Wzf+WI/0tsCT1/I9/Xb8k7t9s7hkE+bGA22U4NaCsPWTgcp2VC1JJK9mu9OuTVBzB6/Zrn1vumpJE2ltEzsLzpvvGH3EY0tMUj4pe/6JuvE3tjJjbfwk3yd/S165iJD2teET5UwdNJnxM2PUnfHy+ylpsRhIP7sb8Jkw52fz0c2OG761vk+6mDFMtix3sNjyhlN9a0tssc/EnW2iyp8BbLRvceuOLE8xOO9xTLOtzWYsbuVnYmlea7Jgm+zPZENMsNdpITH7omzIr2FXs/fBQ4tXzX4oC8o1+2g7qZusTnJoeSDrE7fzteWxGXvyZb+jbX7YMGbDm5ZLW77b/KLlriZfymI+2+kV00XTQSt2iqvJYtN7XtvkbP0Yhm2x/w5fLE9PVK/r+nReP4Wav1vlcb9hZr6zLZnN36zmCtedoNTqNcP43yx3g/WMTaPcku5s18Zm/1u9eShHAypLzOjUAzhbQMnP87L/DuOOjdF9Cv7W16lYsDIaTkmA9WmyZd+pX9JitDZ6Scu82w5THtuf1+jRHiBktLdxOQYTmAxEtlNHureATxlbYDXApTyTxvwfWT4Bcu6bPqy0hKMlPA0/ZkzydwogWefLly/vPj+2w6RuXj9//rx+/vx5/fjx4/rx48f7ir7JnJN7k/2WTCQNDPyUsSWn6SvT10yet7GTRi5OZMy6kxS1fq/r+qTvUzti1522Kcesb/6SbVpf9rnptiUkjFkNz5quydep3I35vE984S7OdTkW0f+2eEkbT7xpvtJkmeWOXDaZNMzZcCV5yOuZ33FHlceaTT4Te050W0w57d5ufCZmTG6b2JK2kf1d1+fTZC8vL592B6/r+nAtd1ctZlKmOSYfkEMdkD9eM5+0PDTrTOEJFaOj+Tjj/p04mNetri38GT/te7NJ8mjyaBhJfeWCr2FIjmX+1GRKG0z6uQO99Uf5mE2eSvrG9LMdTW88tfK3JqpJXL6ngt7e3j7srs71/H4CFDvSdQrYTODvCMNA2+6R12Y8SUcrm9HMO52SnzmGOVQav8m5jb05SI6VtPDaBiBJm42Xemzj2zGeLSCR3nnfjufedbDmC+xjkzmvMclussiEvNFkgXb4/fnz56cgv61UNxlwXLaz3yGddpjaOwOXydPA2GTC9lwgy/rXdamsk74TLcSzxDrrp/XFJIptT5+zHZ8i+3g86nFfk73thNh4eY02xMWurJdtbZc1X/ME45eXlw8Lcc2emFjkb7PulqbrVhgTSU/TV763sVtbi72mB+Nji9P8bjGqxfps28Y3Whnn2c/mD5Q38cT8s2Fovij7HCsnpGm7Y6f5s4gtjprttsWj5DvHPsmBpR3FTf9jfd7niR3y0Y7skk6j32hIfjKPzOSZ9m32dV2XHkndZNbsptkS2/OkG/u0CQj5aKXxOPfsPfs026f90S7Sfxv/DT+oxzZ2O/VlP0U0HKMMmlxavmZ4mRO3oWH6yVNdhpXpDyea7J1yMBtt+mebLecj7xtecqzNTlluT1RPwZfOS0FP+zyvzKNc1+X//9Mmq0ajAZC9k+7mHKx7koHRk9+NnibbFkjMce7IxJKE/J73GViNzxMgcvWNIJZBuh0Nak6Wn+84renX7ISfNz4tKWy6zOC41cvxU0aNhukrgdoCaft+Gp+gyVejKdsTqK39M8CVQTP52ZKok9/n2NyRYqJkR/rYT+Ob9Q3njJemDyYQlM/Gs9HN9pYEm/xzomrBi33wOoMi6eb3lEXu3kzhkfVcfLA+s9+8d5qsUjfZ/jQWP28+bjjXaNhotZjEPs3u8n0+Nywx+u7En+u6PiVwxEub7GQf6Ves0/RgbTY/2e4Zzry8fPydXvKwnULYaKF8N1lbOcUg9k08y5Mnd9rwabobL8Rb4/PEK/Wau1qNf2L1tM+fPZxy0IanJzsyXoklW8wy+bCY/1o76uZ0/DZxNTF5i5Xz3k5MsWz1sr/EC4uXya/JsZ3oSx21mG4ynnfaam5CUA/P4OWGR9PXHV/POq1N6yOvm05srOY/rdyeqH779m0F0ywWSH7+/PkBsNsxjc0htkLFcufoui5N8MzZtjH+N4oFfpaNfyYbbYxTAmOAOvW5jc++N+cwfeUuCGkkb9NHAxa7z1eCFnlOHq7r+pRENL6NryZD+79ABsETIDweH59kfQKOzSYaPxtvZj+2Ump9ZR98cULT2m60J80M9BagchLTxshAdF0fg+Pr6+v15cuX66+//qoJUo41gdr+7iBpb8cMTW7z4rG0O7JjEGKbvDYPT+LPN3LBcO6n7L98+fKe1OWYxlOj+RRbsp8sQxvv5U5V8jF9W2LBsRqNp50s9nPit/nvpi+z+0bHybe2hKn1mzZ/2iXYyoa7SRtti7HozgmshuEmHzuiaLmCxbC8ZzHp8fj4tycNJ7Jf2uyz+ZHFIOJ71k85207pyd6b7bQYnTIhv4xB6VNtoW7b7LCd2OwzsS7f23HT9r7hf/bTdp742XRtMfBUNv3NffMri1Xs03CevFIfzVeJka3ufM+flFmOYAtS2X7eidn0lw0ns//cfNtkfyeet3yB7VqcbbZj2ELarB37bTGUdU54xXJ7ospdhm2gFkyTwC0InsDXAI/XuZLD8Sgsu7aNnYZ/RxYbIGzAY4C4GRT7uEsf+9/GIm1msOT7lPBsgNwczoJr43GzqemLCZYBZgOSk8xYnzxtDt6un2yx2d7Ue2a3iOOxr6SDNFkyZH2egiaLBSHr03zgFBwzIU77yOOpJteZ3M1fdzUZZBDLV+PVZGr3Sc+ztpV8WF8THOd47Vxj0tiSeaOpJQXGU9afpOPxeNQE+24cMToMd7LPU1KxJY0ph1M/JhNrY7sX1r7RaPrKHT/iLLH9zi7B9GXxt8nKeDHe0j6ZjGb9LdbYeIZrbLPF2i2Osn3LbfKajXknzrOu4Vd7XZcvUp5w5E7c37BsozHr2ouTq7xG3Mr+s8+ZoD4ej3Wimm03GZK/Zlsmh02/TX5Jj9Fm9fMa5Un/Mgygr09Jn2y7tCfet9i43cuTaZQ3cd/o2OJQ+q710zBx+2w7k822s+0W604y2vCLdY1HtjnF+GfKUxPVJC4JbMcTT4nwdX0OUJYgNWe3ILglkc2B6NR/FxDa9RZwTkHX+sn3O+PTObbjkFN/Cz7T3x2gyXHa8Qtzgs2xyfPcOz1oxu7ZuNf18dhgglvj08oWnK1sCQlt1kCAq2ubLqYOf2tJfz0Bar4TD05B3Ppp16yfjdepZ6c3pmx+M3WZyDR/mTZ5DPXbt28fHlJlOJbBvx05yvonPKVfcOGl0bC1n3eeqKG+c8I4D2F6ZrJqMm1BMGlMHduOz115GY1t5f2UWA1t897o2RKAHKdda3TTr+/Ek+YbTDD4W8OMKxvuGK35fqrHa81GGg62+1aYbLb+mm2fSvZhcm/+3+hkLnE3f0msMx/K6zbmxqvhDXM70r7ZKOmdwomjHdHNmHQnX8nx2iS39WN8t/jGPk6n+lpOcdfu7uqONp7Hppvc0n54PH9e7W91Tn6Y35NXO96/8ZLXNvxpbea96aHlso2mZiMm/2dt5e+U5neNrhNvWYhRz5Z/9BvVDIxcsWjAmYb2zLsp1GihoJohnABsSwbs81a3BaRTu2fKKfEcGjL53pwtExCj72R4Zqg23hQe3UkdWH3qlck+6W2gSJry+FrWb0kL+WrB+WS7+bkFFPt8F6S3gDnFFom279N32kPiwZ2+jNfNV04BJ+8lHm34lTQlH3eDedrM+Ne8z0TVksA7tsRdrGa/Zjfc0aVsm7ymvk306ZPDfz7RMH+D3o40U+bkwTAm9ck6b29vH2Q1n+3Id9tto1ypI3tvbbOPzY+ot0bjNq4lSPzceDUc32zs7e3tw8IL9XMXM7b7HLPFbuODC5aM9YlNpH/7Lfm0zzhDnZziFO2h+XT213DBxruTm2zxqpXE9RyXvst7HKPRnHyycLEw8dYmpebb1GH2Q//bStZrNnBHXzx5YC8bcwoXvU74YDbO/o0Ps/kWo8yWso+UvfG22avZyMSZZj+b3WUcOfliu8Z7jE2nvmY8HvlvNmsLL9bfHZqt/sZfs40WT5o+t3h7Kv/oqb8E0hYg7VoDJwt8d8CUba19E3QDimeE2vg33p8pBKQ79abunSRk66MF3g1UTu1ZzAn4bjZB/u6ACe2Pn+d7Lrq0ZNWSlC1AGWCe/CV53r5vhbQSsO+M0cYjSOfnO/39nQTMrjXd37GNFsi2YsF8vtN2fv369T5R5c4qCxdHGq0WnPiZDxdq9nfy54a/6YfD8/CaMqE9nHg42RFL0p7HsqkH1jf8N/5P+NnsfLP/E1a12LSVO7hCHDX/be3pp1s8fgafWjvDheSDvmfjDu3zAB0+YMvGHN/heLaQeocX9tnsI/ttsanF45OvJL13/emEwSe73/S30XDC+rTVPJK75W12j3bUZGh834k3W4wzW2q7g9ZX870tJm4yJyZv2DN1bXK64exd+8n2DZ9Yf2R0wl5intFrdFA+Vv9OPsKyYS4XXE4nAlqcowxO1xqdzW+e6etOPtbK7YnqaTUkH1pxIiaNfb7/3eDWxqLxzrW/Y0SnsgWf7Ku9Zz+nvjYa2gNjTuOybgZ0rsDdBR5ebytyG70bjQn4z9Bj/SWPPMa+BabGgyV+JssZb+PBjkyz76YTGyf73gB8G4+fNwDPzxa0eT/f/w74t/ZGb0sA8shrK5Q55T8Pj7uuj083b2Nd1/Vh53U+54rrHUxgPZsct4RiSu40JJ88bpS+PTuqLy+/nwRqE4Mp+fTNOzy1RML4yPr2Wyq2u4PPp8RqrtHu0xZbcpmybb9/O407pe305GdLyluCnvLjaYGTj1vfLcmx3xi3XXG233bRZhc1cxMrze+nH5Nxyin7OfFgxXA89ZT9TYzmuOYjDQPNRxr9pmvu6p38kuOZrxmtds2OotqCxR05NHobtnPC0OgkPe334xzz2WJ2Y/6Vhb5qvy1n3LFYttFk/DS8aLw8Ho8aJyyWp6/8vyynWLSVdlIv+057HhlsR9CHFstnjM4moy0vMDsj/YadLa48W25PVO8G7TRoS/pbfSZGExCz3ilhaf22OjmugfFJqCYH0reB7zP9p2ysDgNqvt8JCnOdfDO4Gygava2cAgTptGuU8ybHu2DCsUx+rf87r2YXJ3lmUkI7beCx8Wx8trbmK6eAfwcE7wSTljAYD9s4d/o4BVDS1YJFsxPDQUsGR9eDnVwwar/xYsn+RsfteJYVYkbym/+3mvLlBIu/kzQZtoBn/f8TbGl9ZHLDd5Zmv1ss5LjN5jb7OSVFeb0dF27tDEsbPVn3mYkqZWoJFu3G8JO024I48dBeWzE8bG2Iw+bPd/xti8l3Y7T1lXLdfMveSXPGMPtMebT3pLNhp9kK2+ZTeKe0nfWWh5Fm1nkmZrTfZxtfTcd36Gt0NnqtnPQ8/djPRsj3xitpsrbNLniUe4sjp+uG5ydMJY13YkJeu9Nv0kJ5NRkQN0lDjn3nGQ1GC+k62VTDj63vv1Oe2lHdDDYJPK1iZ9mCQq6EmkIaSDbwMSFy1yLHPdE73zcwtLZb0DRwuFMGwBkk22p0C2Bz7RmQ3BI38p08ngJz0mL9ZPk7MjP6TgkFx7wuT654zfozMCAQzVHK5JH2vdE2n1OWJ/m1caw0wDR+t+92b5NP4+HU750g3vqnzk67XynvFrDTVtJm8u9tcpf1RG+zQ+7Unvwlfe7nz58fksM7gT55sETouj4+CIUybnza90bPKYimv99NSKzPpIE0bfRt5WTL7Dtt8vT7pbSLjK0nPRA/mg/yyDl5uZPAbg/fezx+n/rJPm3HwXy0HbG3XKPxSf7S3+4sCqUMTw9GyXuzgGV6sHd+Jj3NR+aVv/3O+20y3nwteUndkN5s12wwd5hMRuY7jW8rW35kfLFey7OIL+ZHm27ujMey6WbzL+qdfdvphO3EghXykIuhw08uRpz6Gh7af+Waz2yyYbsTfrfYkOMxD2s5hR31TfrYv9HQcL1dy7LlXM23U3Z38exueWpHNZXFIJ/E5g7QCUw3whlocxx7wmMmcicwJjhMP3fo3Opw7ByPBm8A1YyA/Tbj4pHdzcE2g7pjaAYEWxsz+DvjbaUlBPx+l08LJlYnx8kAS/tPOmzH48Q3+96Sn6Sp0Wc62wKXycjG2ujaQI8g3MZubcmnFQsI06YdVTnxcir/v/berEey5LgS9qjMyqysqu6q6o3dpKhtKHAEQUNhgHkYYB7mL89/mAfpgZIw30jQcEBRXFps9t61Z+US30PDbp84dY6Z+Y0oDh/SgEDcuNfd3NzclmNxN5e0MoCBbbl4dQDYxTn+4BMZ8WXsihAwXF9f7xSqrghylwI6GfGYWmPVfk2M6ManmAN+V/6mZGcg0pGvAhfqtzqm/nnnvqxzlc8z0DuGfkAV/sY/ftU4Lndtt68XoKx3BHQMbLkoVeOE7WdxBbfxOD9URhVwLo7yumIsjjk7bMC/1UOA3Bx4fkouhUvUpaqMY3je6j5ctQbudhclhyLGN0q/jlSOwX7d3KziilojxYtjWhUrlM6VPGpdYls9KIznHv3Zv5RfVX6dxW2Xx/lZD9n6V7zxdxb3sziHv13+VmNlY6J+1XbHZrL1nMk93RyjfMblrH3ztaOpQnUm+ca36oO8sqTCzpAZEBaZLkkw39jmsStA43jhPje2IwUy1bFZ6sx1xqCy9UIZ3XEV7DI+bl/o2IGDGdDXDbAdXtncZpJhyKHuFXFgCMdxvsdjZECD+bkY4ORy+shso2vjWUxRbTEpIKnbC2Ibv5k6PpkFeOUHHDdiTeLb3euK7d0+trlsvRH4X11dLR/Un/IZdT87U2bzrAdlSxlv3K8eJKXGwTasc9yu+KB9dfyuIuUva2MqA9HOmPx7NqdmYzh58LebE+oZP8q3FR5gn3Dyd2I1+3WWtysAi22xXbYmPD8lo9Kfi+F8nDEa8+B5o9/iXJiUPiv9KFn5kttufmJZlK6cz3F/Xm9ek0z+ihQvNzfFP8sJagz0rex7jNevsHTyKrkrPbs41onDqo+yK+X/mS4dZfhN+RDHE/zzS/0J7GRXuuC2M7HeURavXMxyY3VzhKKpp/5yIECFqkV2Nw6rpFKNi988Nr58PsbEB3pwIEenU0aEpAIROmuX2LCUs86CXiZ1Xbqa4yGoG2wVVTK46+uVfTknVvsdkHHkEm43ofIY7iESakzsg/vXXFoW39VYPD8OqgpguIKAz+iz73XjCD5FNgOXjpS/K51iYaJ0w/pW+lf/PHcAGJ8RYtniN145gmdI4xjbBiZf1GEVSzjG8SW/0Sb0qB7GgTpjflnczdaUgSC3rXxU2Q7bHuoQL5NWZ58ZbGR+U5HTheOR/cYcw+QAqyNcY+ynYiPLWoFj5sc81fyry3pxXDxDjraIssa2Oxtb4QMcj+eXgWP2DbXN/DiuKL68r2N7rPvMb4I4l+IaugcwqXG5rzru+mEBpf5Ac3OM307Hmd+qmK7mybetYSxGXmjXLIeSjXkpGdhXHTlbj3jPfwbhfcHOxlEPKsZyDla539lNFkeyOWYyVjYa5K4CUOulbCuLX8qXlIzOXpTvV7FdxQz3p2yVm1U+d23WUrtQxUf/j1EHkdh2AQov8akUoXhgW/x3B50Kgyb3UwHJJTzuy4Eqkz/TgZqLaqMctBPYs6DnqGPgyKcTqBRvd6wKHupY1qdaGweaOm1VG6Uft14OlCjd4Zis+ywIVICH5a4CVRWQq3FdYHfEekTKgIJry6BwjN2z1rxWatslTAVwFLhw88/ujQ85oy+DQXXGVcnswA3KopKsuleI5+Ke0KjiPG5zwkY51aXZVTxTa6N8Rc2TZcC+zJeBHecUtgend369Bsu5lng8BWCzWKl0FfNlfarbGtg+1djONnlsNQ7OU62VWz+lZ8ebdaOI7ZJjDVInn7l44uIwk9JBlh9wvXg+/J3JHX3VVSpZDHJxyM0500OWE3jerJcOXnH+onI77lfzZJtx683bGBvRF7PYjv3ZznG9+LYPd9VCN+4yubWLnKb4MV+Hj5xMFdbIdDXjc6xjZ7v8yXxJyVDlv9jvcBXzzfyD5XfUyVVVLMpo+vU0LugrJ0fApIzQCa4MSyWw2B/OisUpXzKJPBQ/Nb9OMlAy4281pjOgav4K8KjjawGPAgvIxyVglxhVIHbBH4NvljD4N8vMvJVOuL+Sg9vhfDr6dECK5+GCouvL6+C+q0CV+W2lU5YnfDs7Y6cSZcZXzUdRB+jEgyFUoEf+KHdV7DFhMnc6jTE49lT64n1xKS7P1V0arGRXPpWBHJyX0gPfU+Tuu1FzYt5uDNShWsMsJqPvqhwSdqLyjTrLHu0R1OE+p7OMj4vf3EfpUP2udOl4KR2FD/Elf5g/MY/yONmZf/Y3nAPKovzL2XaVy3CbfTeLnY5UXFY+pnwA23GcivbZ1UAcQzI/Vt981g/lwtgV7d2DroKnKlTdmmN/F+OzHNnJs44HH1e+Wsml4lGWU5kQ76hikOMCr0noleVWeEXFYx4v5FBFapWPOa+5Y05PiB+q++CZlD3g2E4e7IPtMptzNsaYo4rp2Mf5qvL76kpOXPsqBqi+bp/K00p2p+9OLnPULlQzgJOBh2jDIJZ5Ilhwx3m/kifGxTPASnYcE2XFOWVULTiOx4EGA84+1FkT16fiGaScbUbuaOvuBcTfvCYoQ/ab51utHcumLq/E48FTfZBUwlB/1qj+3WAcvsTjcDu3/ir58ZgK6MVxniP/seCCJCZFF2irBz5UQV9RlVCVDAys1LtIsT8n/SwpKl+t2qhx8JiLL8HLrWemH26P35xElUyuUM3iOAMtJx+2R19woGyM7y4hVyDB2WzkEAZOzJ/XvQMGXFuWr2MX7h4n/kb/Uj6I/JQNuyJV6T36KGygbCEDSE4fuB+/M8rihfIlR5WfuX0ZuXko3TlbjnisHobEsiNvnouSq3tpIMrmcl62Ziq+q3yL/eNWryrnKXtkXoowvmSyODuOP3pwnOrbzQHHw/jUsTOXO12/aj+vZ2xneYXjAx9HvpmMLg8ycXxXsb6yZ8VP6aHCI2oeak4Yn3meTr+KT9WuY3OKXxYv9pHH0d6Fqkvyrg3vD55oRG7MKugy3ywZqif8dgwgG98FeJVwu+NkhumcrVqTfQ1LGWln7pksfK+jW1M3RhZQMxkYTLgnFzK4c+vnHF6NW4Gzju4dcGAwmIEJ/M2+yHIrsIpyKQDHMmUJRemA+/F6zvhsZfvKHnhfJb/a72KBGtvJynyULpXvq/VkPpkeHOiNvsov3L2o2ZyVvanYyb95ziqxZ/9CZ7ktSM2RbTOLCW5uTu5OjHZz78YWt55VXlTz5/1ubBd/VL8K3FRAycU4t2Ycyyr5lO26mJzxccSxwMnKvF0MVu2cPCq/u6eEB4+ZODxjp+q74x8ZT7e2+2Ij3h9z5DErfNaxQZVzK/ldPK3yEo+ZtRlD38bSyb1O1i4mrOaRyeRsTfVxuSbrk1HHtzv8FJ+qP9vNbBx2/Dvr1aV2oeqCVOZwSJwEFJ8xdt8bifudHGwwzniZD99zpZK9kk/J7RKBkqcCNGrbJUjWaQXiOpQBCSevStIo1xjDvjpI/XagUM3N8cj4s9zqYTpqrCqoM7ALgJzZB+/rgD6Uneczw1vJwzpVY+C2SvDcVtkUy6Dut6mAZfDp6tfJxMfQFviSNR53n+CL4ztdsuwVwNtsNjtXk4T8HV9RYFCBoPhWD6iK/jNxTvme44HtWF8KHFX3PamHgSlbZz2xTbsYzTFGzU/xw3ZqXCeP8k0eowNy1H7FL7N/FQ/xt7rKysnD9sdrhXyVTpEn/4lS/alS5X60JSUX6myM189Yu/mo8Vg25M8xhH0K++ND6rLxXG5HOTr2j30iPil7VDKtibEom7q02+UtZac4x0r3KobGdswb/wx3+cvNKbNP1mNGzn+wb4zncjvPk8fO9JzJ2NXHDLlYpNp1Ylu0xbnsiwUcn0ofalzn1y73cpsK33Tj1SF0MsaKM6pMnUVX+zPeWfLCY8oRmHdHPlZoJ3HwIiuZ2JDd/KN/BSR4nAw4u+8sQbjEjm3VnDn4IrlAx21Yjgy8xRz4ic4sSwdsIGDCB3w5oNGxN5TR6UHJx4/bV7phfi6oOLlc4sjsnIlBQMbP3Wui1hOPKVt0VOlIyZXxdgGc2zAfLLYrX87WuYo9zq4zkKx4KUCm+Li1YF91cd0lRweEq1hZ/ZGF4yr7zJ6KmenJ2YuaO+vcFWUqnyl9hq+5sRQ5v+oACJfXXHzGtkwqVmU5w8lT2Q3KqYpPnkc2r67vZ/uCsgerYC6LttWYkfdUTlJ6YRvD9eec4/qob95GWV38x3HcbV7ZZenRBtdIxWLUjStS1VxUPnU2w/I4njxH5MNX9ineQdVl1I4yX0cebi2rbcWzijOVj/E4zueydehQhjtcPqvWelaGajzk6WytIyseUzECebKP8Xq5vjwnxWcNTb2eZu1AlQMoJThSib4jEzu1C1ysWPVPeAccqvZVwKgctwLPLhny2JnDZUnIJb9MLlyfTnDLkgPzjf3uFSlVoGRSD1PpzImBB4/h5q/G6iRq3MfJzvVzxzloOV91tuJshIFpJhv2Vfsr28V2FUhwtsqJ37VR8s7GAze2Al+Kt7Knjt1WcTbTi1sTdYzlUXPKEqWTXW27fWF77oxpBYB4jtnYHUCW+Z8jFQvV/aPMy+W4bkx1slQ8lK+r2Ohya0axZngvorvSIfSEZ9L4uJLPydvJzU5mVyQpzFHx4t/ON7kd2zvGD5VrVA4b4/V7oGPb+TWOyzpQoLeKubwezrc6sSmLw45nxbdDPE919jjLq1mbLC5U8s7YXxY7GRe5WJqtH46T5UGWW43Hsrk2Lg4oms1F6riKk931VH0YE3TilWur1iTDrs4OHJ81vjP9HlX8Vseqfd1xlDGuSRbMr3oljkogajFiH56Ny2Tk9jwnd6M99s/4h+z7BtNZHVcJJgNGlcOjPOo9ftX7wjLw6JzcJVrmz0+6zcCMG4fnmIE8fLK10s8sIdDDhwU5+UMGXlclj9OfAkvBS/lEJT/2VzIj7w4puXCuLmnyHLMEqORVQJbn6YAdv+czS4DsSzjnbgJBftmD79wl046qJxlyuwxYVOCG5+PGqEA8knqYS2aXCnTH7zcVtzt2iTbsbMLJXo3N7fihcNUcOEYo24+YxO8mdr48S2xbWY4I4tjJx9TvzHYZl7gCMsbFe8y7dtYFzRWoVbGNfbWDn5R8PDavQ/ikG5tfC9XBKWxPyh7Ut7I5twZKP8xL6RVtweHHylez42uw4doaQMUENb7TL9s60poY28WXlT11xs1woBujqhecTWXz6MrXIbcWXZo+o3oIAbrGx3zZwLoGMANSsjZqsZ0zKWdwBlEVOp12WTJQ1NG7CjQ4fiaLkkm1cb+dXrvAQPHE4wy4VXCoAFQ2TgUIttvtziVcHFCyoBTUAeKuX/ZR/VFXsQ/bZ7quirdIsFVicrIxgHW26+Rj+bM444Cq8nv8Dnky3k4+BwYRrLv1q5Jy5qOVXEwdm6p8RfFkHXTii5Mrfmdz6sRtx78z1wqIuJgQ681zVvOazW2VjIpcPuqC4lniefMrc9Ae1AdlyuSufitbqmwL5+DaVX7K29n6jfF6XnPgXdlSl5QMGMsrWavc0x2Tc0AH87lcUfk/t3U5gcfo4CueU3asG6cUXnPzzXigzJnszv8r2zsUdXJ6RV1s5fo6/LfvfDv20vWlDvZYQ2vzaEZTheoax15bbCi+Y+SPbc7GrKiSIzN0BIzunXvqm/lnhtYBQGsB1Rj6YVkq0eP4bAcOLGRyZ5S9r43nxfJm46kggmugihAHLFzSUuvhwKUKbE5GNffOa12QDz8kCPlkxc6tW7eWd0ayPB2wk82FX52h5qX4KlDP+zLfyXwb1yZ7D3TmO+ryQyWLkzGzefzwero5sl1lrwuKcfDS8k4RwnLxvJTdON+IbwU6Qn4lC581PnTyZr/hbdVvBrygrOo+NiWLGy/WuALGa4gLBDUH9EXVf4ZwHvxMAc4/lW0rGVysqYoRR119u1yBc8JjVTzB/u6BfpXss4RyKWwQ3ypmoT4zPjyea6PWtMJhjj/3qWw+sxXmn8meyafiAcbCDmbq2JTqw/l1LXV8Q+V27u9yw+x4Dl+ofWr+rJsqz1Vxv4qnjHG6mCQbX/VZQ10f69JeT/11L7V1i9t14ODFiQfHcApwCxfyusAX42WgltvHOBwsUA5s3108p5dusplJnCi/CwL7GNuavkoOtW7u0rzOurnxuC3bhQIUDlCrMZSdufaZ7iPRc8Gi5qDsHvdzcMwANx7jgKyAiaKq0I158QvA2UZnE2WV2HC98b13eNaGi3uOa7Gt3nXbSVIuAXI7tH1eD/wgaOd5xj51CW/wZZmYh5rDDLHvqDzB42QPPYt9DIgzH8ExWLcuZnN+Qn3z3KJ9lQOYhwJoHRtR9sLFrtJtJy87/ryNc1gDaN3aZ3J0QJjCIPit2rrf3N8BV9e3Qwr3OLylfNLFy2qtlZ1lcazCNipuZnN1GI2/nc+5p5B3Hkim8nls8wONsD3u53iW+TvLoeIrbnde/aV0o8ZXMjpd4DdjxqzPPviR+7t1U/pBGTKeuI9jroq1a2XO8By3VZhM6Zv17vCgwjwd2icOZzFrlvZ+PU0XtGQJwgV4987GbBzkiQmagYXiuY9hMq+OQ2V81Gt4mNiAK7ld8OomhRhTUZZ4sjbdtuykWTJzsqgxOkCiAkAqobsk78Z1MqtkqQJSFpzcPUr4OxK7emJylcCyZOkoAzg4x7jPiO8FZjueCaR8TH1YjzgmXz2B+sgo04+TUfkfrxnKwHLxvBDkxNlx9m1lq/FRQM8BXbYR/nZj8X7l01msdv6QASgFUCqAgW3VWecOCFV+pOaj5od8q23un+mOtzuAQ8lYzaOTC7tgt5or8uraBPbL/LvyfbdesziDbaeDMVTc6OKcKtc7u1C2EX/8KT9j6pwFdzHI6UB9eI6Z7eN2zIfnyPKp+WXjZX7M+o1Yzm0VqeMd3INtOU5l65fxWdNPUYZPFJZQfbsyuFyX2Yjy1c64GXbEdVC8uF3H19T4M9TBLdn6dOmghSoHAPdOSrXNbRjYYHDAfS5BqmPqDAIr0snN8lY3/++zKG+S3FPmMnKgL1sDlSC5TTWeGvvQ+px1TOzHwV7ZRAZE1TzH2D3jqAKe6qPAUOxzAEf5UzxYiR9Qgny7IFsldJTVyRNt1CWVmd2tSUAOYG2329fetTzGd5dNHx8f7xSs8Y2FvntFRldG1YfXP97Nh3Lgw7GUPPEQESxUsT2vB+pZFbY4nvNdBXRQp9ge564eVobf7uFKyjaySyCVnrPY6JKve0ei46n8mo8xuXio1li9s5Nz62xM5TkocIXHHK0Zu7t+DNJUvOiSm1scC7lUu/ijLfyKH+DTlSn4sz+syYcqrrA9cfzoyJnd4hDzx5iS2Tf/5tzG20o+5b9uHnj1DH7jGOhP6l5xNb7KnzgfLN5V4alyiNPzWvt2sqttHCvzi4reFJ4bw9cqOJ77rqiKJbxObl/WX+Fnbp/NUWF1zH1rdO78NdunMCfv71K7UJ1ZSOzjQHuXeNFwvzKYbAwO8A48uteUKKDUkXuGXALKeClQVIF4Z0DBD7/VeBUx6O3KrmgmKLuENUsVf1c4KXvB39m6Vv7C4LAjb9WG5ameYlzZIY/jfA35sU6RhwrweIZYAZiO73QCZwaOAnBGEojLURngINBwhauKYy5huQTmbEXpBNuyjyrQ6ojtHu854+8OPycvjznG64CymkOVHLE960rFSAf2VV/Xn+Mt+9wsQFR2pubodMM83R+6yMP9VuPxdudWnO54aj3UnKo42QFkyi/VGGqtMj1V8rGNZb7i9JHxVuNncRv5Oh3M5N41eRr7ujzJgJn15mJotlYdWSMuOt2iPCgnyse2hNR9Urpam8qXu1il47s4ZoW9VfyrYiKPURWqzh54jO4aOzmyGsDFcIUnZ3G4w0Rq7plcLnZmdoH7ZvRYUbtQVWfi1Hb8zpyhC4CwLRqtWsQs2ONZA/xnLwvm6v6srgFxEnOAQ/XLHJn38b1p6ml7agxlQFmy7cy1Mz9HygGUjJlMGXjLZKmAA8uDoBxBc2YXmb6zeQZvtT9bOx6bZY/f6t+9CtA4vePaqMvW1Yfnh7K4ZOJ8MtNF9yoCxdPZZpyNrBKLm3sFjioAg3Iqm4x22StWjo6OWglFxQYc79atW+Po6GjnbDx+FGXzYt0p2fmeN5YVr56J9Qp+WMhlvqv8mGXmdvhnRTYvdx+Vix1ZG5Yve4BXpjPmkYE5lxP4jw+Xo1VblqfKLZ04y31UP8UjGx/9F32U9zm5HACscojKGc4O8TjbfEXdPINycC6ZmaOyPxUPlVyKh8vfmT9GP+dvmOcq3NTBThzn1dqqfBQxK74djnXyVeTynuKZ5VFeL9yv+Kwh1S97AKeSG22XcwePwfKr+WGbal7KzjvPHWGq8oHyf+cPuHa8hh1ZMt7Ip8sraFWh2gEU6FDYxwnoAlzsYyPBcVSiUDz4cg0HipUsldyZTlRCqZIZ81KUJQd1OR3/VrrgdlnCdCD7UJSB7AwAKcoSWuXosZ0lSpQpu0we+aogydtxaSfPeQx9qZD6zYRBUcmVyY39WR/x291brvygAukqkXftL4sZ+K368j7FC2WrZHExKb4dcIvLj3neyi4rO1gDDNz6ZICTkyPLy3agjjk7YdvN7nsLGa6vr8fl5eVrco2x+yoN5O8AGq5BBYiC1OXJ6PsV8ZwV4FN6U7JwYehA4gAA4sdJREFUHKvGjPbKDlzOcHw65NrxfNeAnejbjQlB2ThZPnIPKePf3FfFEuc/VZxB28niPM/fPbyO2ylfRnzjcEhGak7Bs4rdKi7hfDhGZOviYpeaN/ZRfJlcTOC5MSEW3m5fx9hqfRRxn8weVazOYhevTadPtN2X1NhZTAobdb7q+jo743G32+2C4WK9Kl6ObzbnzJ/VR+mL+zv9MVW4K4up3bwwXahmztnZ7wIM7lNtMoV1J6vACAfBzEgrOVgeF3wUj06Q6ozHVDmUo0wPOF6muw7/DFipBxZgEaSSINuPGnfWcVi/zm4j6Lm5q4DtAK6bgwLS3QSXyd4BuJVsGWX9lX2GPWXFOAdTtMHKDpTN8vFuvHF/GFX2n8UBJasjBcCYV7Wt9JvNx63ZGPqJxzwPB35UMlUJ3MXT7fa74hTPquIZVeTvYmOW/KMfntlA/awFDY5CPnepbMf/Z3x2jX+rtclioBunM4cqhnfzM+9zcqt4FftVzIptdU90ljt4Dt35KBkVhsKYU/3Jyf153bgdrw1+qznx/Du6z3IdYwJHFfjO4qjyWScH81NzYZ4VL1cQsM3hsWqOCm9X+EXN25HCKWo+ma2rXKRkV7JVOMCRsw+25QznZnFQ+QRfpZfJr/zPYSR3vKLMT3DsjFS+HkP/EZZRu1C9uLhoCxbfHKiYVOJRwQ2/sZ/ads7ABsBnV9WNz8yLHz7jnsyrgk+WWDPqJl0nK86fH3qSjZetWeUA7HjdpMt6q14T4cbpgAN3fE1gC1vo6BcDLALP7hP8lNwzASNLQqhjtnVeDzcn3segKJNVrcPR0ZG9FGeM1+2cL3+tqANaeB/b52xCCp1UAK1K7PyniNKRuwQUx8mOZSAT+8aZX+fvmc5Ypzh3nCfON3wN26nCNC7Rxvyl9Mr5RSV9JiWXe/gMxzacq5OJ9Zk96Ir5qHyp/JNJASDVRvlq5kturh3A5fxK5YLMRtU83HbFJ9rgFS9KXvYhJy8eU5e1sx85jMH6c3zY73iOnYevZLbBOaGTgxkHhhw8t+wBfeyLCqfhHB1xoZBhO0Uc37CvmpfTCX67Nll/dZzXh7FBFjuqeSuayftdUjbGY8Z3Feey2KtkzHIi8kdMovwgw69ubJZdfWfbwU/Z5wx18iOPydsz6z51RjVLXjEwCsFVc7aojofbdopyCRud1iX3KvDw4leLNcMfZVU8FCDlvhkAUMBHGQ8HMB5PBW3eDt54WV33SWwuITkdumCLx1WSzsBFRg6EVEAN26whNS8ONi4pKd2o+as58Lo62fi48ldnv5i8VVBWsSRLMO438svI6ZJtc3Y9ORZ2AcrMuuJYKHMmkyNeN8efbdHJ03kKsiqsVUEY43KMUGdT46Pm20nULvYou+U1Vrmmk0uiP37P5K6ZeTo7V8cULwd6Kjt2cd/lrth2uKBD3RzcjXXV2BnmqfCQiptKPy5nshzKjrLxK7tUa83743dcXolYwNk3xxSOHVmhGmN1sGJ1+WqFuVw/5uHWK+PbxSdsEzO+oNpX9hV9ZvTifFT1rfJRx1a4jxsnizPYvzqmxsna83gql3fjRmfeVR6p1tLlmixOcJ5243fp4IXqGN/9G1U9QTTILbC6jLID9BiUqCdDdoCdC3AdUNChmQWrxsRxlZwxL/e0WpUcZ4Iz6w0TEsukAAsnD+bp5syOoECMc363D7fdmS/n4JnO1JxwrCrQ8bjYLwuoDhgoGTDZd+y6CrpufsqeM39gfk6Xa4Gjoyxpd3zSja0SDusrA39s5/GN7RQQ64KDCli4GOOSLBaPrm98szzxUCZ+WBwDl/ioy3wduGXAw/Pv+DPrvws4mA+Pjdsutmc5WcV05u/mlJGK4S5fKN3wWOrjrlZQl8ep8Tr6UfyVjjrbGSk/Vvpy/q5sBeeVXTLflSsbi/uwzhyhf1xdXS1+nGEBHEPFXPzTyc0jxmJfZLkqO3cPbHP6QN5KD/gbv5H/TH5Sf5ZW9svjOjnVGV+FDzKc2MH8FSaK78pWsjFUWx5X4RUlRzUf5I39FW7EY4GX1Vpl4zJfHFfFR+SXrZ+LmyquqliNHx4nWzNHU+9RdSADJ4FC4D/NM4k7KPq79/S5RKkAWzeoZpQZOrZR312Dy+TrEhqI44NBvCN/1VY5Po8XpB4kEN8cIF3g7QR0lVDZjrrBFPdtNhtrU8wX21RPmq4SCvtXZhPZvDqXGWegEbcdcFF2gzxVQsQ5ZvNRMaAKrMxrTbBUfDpJWtkbgyDe5jjjeCtSiXLGVjL/UDnA2Wln7GoeY3xX5KJMfMmlsq191zfkr/Sd+a3z9yzfcKys3mVZzdfFl9iXrVG8B7Tyyeq30hGf9cZ9Y4ydPxzYbxAA4T4+w97xT9yHMTba8H1/HV3wXJUPKzzDa6G22cbdPLPcrfjxWBnG684b+8Q6qyskkJfSVTyhXL2/NPMLh3M6WK86luXiNc90ycbPYgr2UWuTxQWV39m+FF+cO/9xUOEK7FPFQiyI+cF3Slb8dv6ajRf91Ddvq7lmtqn4Zfsz/eKxQ+Y7R7OxJ+Oj4lxFqwpVPsuUBVY2FBfolZEF8SUjPFEXVLLEsg9lhqESXSajIreIM8FVARDlVGuoM68s+ThDr4BmBqA7lNkC21QGKGfk46TmAMWsnXIw5N/Ox1xQd2O49VDjdwMw9snetav0q/io9tkaZfw6ckRft2YOMCi7yMar/JNjzUw/JRvLr3TrEhaSkonHyOSqwLoC+GP03yvIvCrfmznWibdKd2rOircCyVnSZ8BZUacIy8BXlpO5H7at/BLld7G6ei2Q48cyOiCVxdxsHCUL2rA7O5XlzKyNK8xUjMjybzbHLI6p/ogF+Uo7jotsQ50c6mTg+as5dEjJxDxVPJ4F5EquLK/NxPpOuyrnZr4f/XGd0Gczm+vKk7VTfbJclMVEZXvc11GGhzrx1c1L7c/ycEadPJ79dpgoviucPitzu1A9Pv62KV/Ctd3Wr9hgo+0SBzb+dzcUkSmwmwTjWLUY3WNrio+MOgapgr67/NbxUQBKOanTa8Wbnav6R4h1iMndye72qwDDQdZ9FGFARhtX61CBXdafmk8VHBXtE9jU/B0ACD/F9w+zXMpfg0f2ry7+dgBJ2Z9auywBjfH65TKceBUv5peBOOSrtis7YN2yf2QJKLNjNweW2ek10w3zzmKDurRPzU2NofRYEfJ0l/pl69nVk4sjWT7i3xnw6ay7WiP0XxfXs/zJx5Xsld3hNj88DbcV+Nlud1//4GTIxlVzqvIEE69RlT9wLq6v2lZ8WD4nm4up1Ro5u3frgds4P3fJLvLh13fEvu5D8rIcx+uePQwz48/k1sDpN/NHF8uRX0ZVHK74VPlVkXv1D8+/Iz9T9tyKjn4qzDArjyOVi7s5hOXt5A6Fm7trn/WZpQzvKmy9dszpM6r4r2UEntlHDVeAI47x4uPlXtmYiq/bRh68zd8zilbyu3YdYhmzZOn6MlhkPq6/AzjIM7ZdIZIBKMW3IqVXN7YC/0HqchKmrH/sj8DhHNYBwI49xxiow047BAhZslD2gceUTrm/ClZqDHUs4krIxnFFjcm6Uval/kDjtXFrhmMo8IV8s6d0Ov2tfcozrr+zbZ4/7lO6QP0HX6Vf5FnFDdYrzyPrm4E15F31VZTFGJ5z5wFw7ljmZ7jN9uZkdr7l4jCftWL/UDmA/cHpopPnO/Fe6Sj4I95A+divOvmrOjbbtjqeYZI4jnp28dXZfvBw4LiDXVzsVPKzfVbxkufi8IbSEV9mje+4zPIMyrAm14V83asFXT7n+SjsM4NzWHYnm5LP7WM5q/e+q75ZPFZzHqP33vcK33A7pwuWy8XYzjhqXVX/blzktkpvme9yWyVXtc/pL8NtuI/zBu7nbUWz9t8uVFUwUuByjWDOeJRBhwKyh9xUcivj43GcwSgHVf2rhcooAyxq3G6yZuDRWRPn5Er3Ss6MbzUvJXeVeFQblLMTCBUAcLxxP/ZBH8mAJu6vgHHlZy6QuScmOrCjZMzGYvmzYKV44cPX2N/wDwAc2yV7FeDdcRVY+bdLyGhHGXCKbRU7siTreHSok8RxfwUkq6Sp2qoxunJnYDcbv/Lp2TYcx1ScVfFI2Z7yec6jTA4QVTGeAZqS2z3osNrOYkEFsGb8NYuXqv9acnbv9FbZP/ZXD3HkMTNby2wM+aixFW5x9oRjrPEPHlcVB508o+ba8Xe2lSxXsu+p4yrfcN5wuuTtzgPtlO6VbXSowlDO7lAOh5fcPNnWlP1l8nbiQ0a8Fipnu+MVz6x95Q8qfvA27nMPG1TYwfGp5pTF6gwfKx26+Wd66OYxpnahiqQCpfrH1S2IM2hHyvD4qW6uX5ev68dBvnKEMfTTimdILaxLaLjtHiSBa8QACfvPJOPKsDNyiTbTLeuzAjWqIFN8XH93aTEGFEXqxncek9/vttl8d1k7ysB8MmJAwoEPH1bCY2Dyzmy3u4+PZ7bLelGgYJbYJrsB0YEp5s02enl5uaNDXFuWqePbqp/a79pXyd/xVzxnYoLrg9SdY+iR51Px32638uqEjh12fJ8/PCcXW9gucJ8Dg2qsGdDnbK16gJmLVaw3NR5fqrsWVKEcvPbOJtYAe+67Nuaw3F0eyr+cz6G9KD9169N5Omzml/GdnXnrzFfduuXGxN8xB/alo6Oj1/xJzRH15y4hjr5ZDuJ9jIFmdKH8gufO80W7ymxEjVPJ4PTOPDEezOYGHs9hlCwucXysMIWyNV6zDlU+x+vD83T7OMdldqHWCUnFsCyGqm3m4ey5Ey9cnw7OYmoXqqxYXhROuPjteCnDVdQNaO5Yl4eTzfVhI83GUtSVOTOUyqAyedb0yfp1X4fhxsicQiVWDg4cUB0PJ2N3DdWTB7NAoJKMegl0dh9O5x2U8V1d6ptR5cPK5jNdOb/rBPVMvs6xyg+zYN6hLDBXTxrv+B36tppbFaNmYypTBV5m1iorBLI4yHac+V0Q6z7TddZO5acAVI5QP2hf/OcUtsnikgIvTq/cj7dZPgY06mmsTj6Xw6s2GZ8MD2TzQ+qAINafA2rVnBXNgrqKv9Kpk5ntK/N/x6eKr6zfbB7ueMhaxaBOfOE3S3C/GVym8CzrhH/zNsdv9a34OFnZDxnsM181p25ec76jZFCydsZhjBLbyCeTz7XLZOjkm8pvs+NVHMexXFzrxDTednJl41djIV+F9XjMGczUiTGO9jqjypcsOUdzx8bYNdzOfVvq8sCuzFnS7YABnkNloC4YzRqK44X7nSM5GTtBtBuAlAN2gk7mkMhDBQS+zFQVpm5clJn1oy7VdfNE4JqBLJY9fuOZn3hghHoVBfKsHjoU+xyYzi4zRP3jazEUD3eZr9O7AlZ83IHVjr84UjJlMqJNOPk40cRHvbsvu5xbydqljj46umKbVPJUCdaN1ckNig/zclcwKLuPb7ZHdUamc6m9s0k1LwV60K/VH1EoI4+ZXbmRkfMdJo51mZzI1+mnC6JdvnVYwPFyv7O82emDfd2xGaqAcqYrld9VH84nsQ+32Z46Y+N3xDh3STPPUem6Av+urWqPPq1ehYj9lG26uVaxX+VjNVYVo6OtiiexnhmGU3PpxMmOTNxOyZHpiseo9MLrx/J1/bMbKxw5zNkZu6JuTHfzr2yX+zs9ZznBrXMmqyLHPxs7o+kzqoqcsWKQ5UnzP38KQDtgxAuQvZcT+6sg2TEalLcLzLF/ligrmSr+2cJn86+CaGds1T4DdW48BnYZ4ZpzYFOXn3fWxwW8CiBw4HFrwUAUwTMfdwWmu3/BzUW9WB23O4lAyeIebuLmi/PO/Fm9S5G31RgOlClyfpjx5zaZ/jnmhfxdH1cxxektm9vscZ5TBqy7D1NCUmA7+lWgEftn8cyNqy7B5nVy88jySTYe+iDvU7LgdieWOBDFc1PAiH3XAWFVKEa/itScqtwcvBEvzNoVg3wlF8fiKv9x3OTjbjvzD6UXbKcAe8femY+Kcd14ovSP/ZVeWF8qruDaYM5eE7OZN46h8sEsnuE5O3vJ1jDbdr6ufJzn4OSofEZRJp+LjwpHdHIjyhnt+HLi6qFLnTlmuETxdO0zbIjzyuxCvSO6I7/zP5bbrQXfCpgVqVU+YB2gDGpfN8Z0aapQzRZLtXfCsBIwsapkifyqb5a3UlhHiVXQcDS7WJkjqT4Vf5y/04V7ZHxnnzJcXEvlFPybwQmOx4kaeWCSq/ioOWS/3VpxYqkSmJuL4pk9fRiDjntABG6rZOPABcvIcvH2GGN5EiM/KdbZpQNI8cFAri5bzoIrzjnzS7ZNlLNKwKyHLNmwPlwcVL+zBOH82PFTcrk1rZKnWgcX/6t4xnyZKvDfTfRqfJcjKplUzHJjIfBWl/siT47BWU5V4BXH5bhbXU7HRQPanuLjZHHk/NflA44dVczCfUoXh8jN7ngmU9Yv9ql1zygbg+dexS0XT51uFU/88w3Xi082OH9lefiPHNZvtHN4gOXl+Ti86ebOcmbkdJRhkWxMPJblAR6zk5uQT4WNVL5UMiApP69wlYpf0RZ16+RR81Jr6zAOxxknG8vv8rGyg9m8xf2RD+9DGTLfW1ukduxUydWNaVWcDpq69FcZSwfQOWNQwSP28VN9+Z83F3wxwWKiZTmvrq5ek0HJlgU8R51g3V2gLKBWTsDBnQO9W7ssaWWkwMWM0fK++GRnGSNB8qWqnQCkqKMf3K4Cp/tGoJiBZWffjh/vV0kedcN9nS5wX6dYdj6Jcxrju8v81HvBsqTodOUSh1tXlViyeXWoAkHdfZVsHcoAmuOvihxlfw7ErNFZJTduc27IyMWALH/xfpe3XGJ3vo15KdMjj8U8cT+3jTEcyMI1wss4uW3IGXlSyZM9MGzWdmNsPKvCV28o38Q4Fv1ZN5XPO3l4HStbdsfZ1tzZaubRzbuO1MMVlc925oB8kDeuD/7ZqvxL+QmudezP8h/zZNncFQ3OLtw4mEsQh7A/dZ4HMbOGsxiTYwrPqyuHi5E8J44Hqr3jrWxNrQnjByVLZsMYl2JbvUIOx+TtLkZQ+IIpi++OGCPhvll5Mtmqt1K8CVrDf/rSX+Xcri07dezDftzGGSa2RT7qWAXA1HiKNwMvDGBqHDW+moMCdE4+5uv6ZuR03OnjxlZ6i98Y3CtdVdTph+vL9wm6dXTBqgOwOJiqduz0KhCofbNBzSWYqijp2I/SG48T7zZ246lX43AQ5mNKtsqGnT12Egm37dJam854VfaXjZn5YsVjZpyMR+ZrbJezccj5M7ddsy6ZH7n26sPHFM8MdCmZuGDiYx0emfzuuIojOBZf1q7aVeBybfGn5qL4ZlgE+6v46NZ3H9onZuBcMllc3HdYJ367kwFBMw+IUz6qdMm25EB3N8+qe8KPjo4W/+H5Id/sD9jtdrvzZH7EgpjDnG5Z9upsesfWOjGE2zu/YBnRd9WbDLIxmJSv4z6Fp9QcuT3zyXBVdYk5j9mxxWreSMofMj4uT+BvF6MzX2Fduvh26Fya7e9Qu1B1Z7XcwimlBJ9w7uzBLuwgsSDqMiqVaBQ/llUtOI6l+HSpY7jYrgtcZsCeSmgduRyIcE7hQEKsl1pLJhU4u+AdKQqnbC6Vw2SyqN/KzpEQZLpgzbwwESp+lexZ4Krmp/SngmwmY7RR/zire8rxLJ7TE/NWY3fXCakLmhVl8aTDM1sv/D2TYPl3ZQtOZ9FfzcfJyGO68d1v7OP0WPlElQ+4j/PDmbjjgJLjp/KRA18VmKjmyHbBvFyuVvMI2eO7k19m8qaynSof8Zy4XSe/s11n/Lrzy+x0JrZn8TrLHcxDzTmzMeanzqAr/bu5ZLbMGAH3uxiR8cVClR9UqPi7Iryy/9CB6o+xk/uoeWX6ykj5rrPJrn+6W3Ay3o5fFhv5DwqFD3he6sGZ6hYG7uvWUvl+tl6dteNxK5zgxnPYTY3VWaPMb9w8mGdmj4pPJ09VtFehWhmsC6yxrS4V4f68wHzpgUv+YfBrHVYl97WU9WUDdf+0KUfPjGttcq36I4B0YNK9eiUbuwJFnXlUoLYTvNy8nY1W8lVPFuXvbjJQvDo2HeTA6exY6nIoFWxdkFeAKr4rmbL1VAl7BlBmsuE8XDJVOnE2xO2qOWYyquOzscv9+xyATMmM8SDaZvrDfooUAHaXvao1zxK8Ss7KHxwfjjMsowPizid43mrN1Lh4bAx/H5K6vFfpkeVQrzrJ9KBkm6WZvJTlvw6PDNzx5e8zeuuMG+NVPqKI44uys0oG9URZtlsXz5WcyubVvLN2XVK+xg8u4z+GGTuqPOTiuSJuqx62ycTPYoh9PK84A6zWg+NUzFM9a8StVScnVldC8ViKr9qvYjnLwjbNGDKLN1mOVPPuYLBZLKbG746HsVyNrebL+uAxMKdktlDZu9quZHLrMavTvZ762wV+XaEcqOoG8woEhGzZ4vDidmgW5Kt9zmAdDwfMWSbnnFnAqebjghCPo3g76oyt5oLrlM1ZrbsDhZWj8RjVHFxinlkbHqMrW5cX96/s34EXFWi78mRjVbKrNXOAq+ITbavAjvxm4gVTBv5c0j4kOUDhZKnWU/lUpRuVXBWPri7cemSFTraGyt4VAK/4Zk/TrWzJtWf77sYmBRJVG9a78onOWlT6VbxZL1kh5Hhmbbg965X3rR2/I0OlR5fzOvHVrTsXRJmO0b7Uujh/rbBKRdxePU3bFaghB8rsbK2yF5VHGItlc9xsXv+jT71XOXtFnqOZXN6JxSq3Z+2rbdcna8/z7xSqbk0d1sJ93fnGuFlMYL5qO9uXyeDGc3gWZZmJlVk+UX2z3LovTZ1RnQ2CKpii4yhndEAwtqsHuWSKZeDQdT5HnUVwAa8LgHEf6rHjtGpM5SDYdx/DChndUwHVPFSQR+oUC10Qwjw5ybAcLBPPKdNfxkfJ1gmSnJRxH/Lp0kyArY6vDbL7BrJI7O4MActUgUfXh2NPBXJYDwr8q/GruVb7qvmp/jM2o3h3wFqVF5hC5wjk4naRTrKdAR3cx+Udl7j5Sb+x7XxUbUc71o2zE3W2s5qrW4/qtQkMgNz706v43Ykp6pjy6Yw6IJPnhHnJvdJH8enIkAHL2SIioy5mmS1+XIzJ8k22lu4J9zwe53a0P/UOYMWTZVQ+zral/FXFAZSLZVByR/zKrnxwdq5iD+opfFLlrW4cVH1xLMZuawh5oF6QXB6PM82K50zsV/42i51Czi5l66HGZRzSHSOTr7t2+6zvm6LpS39dcq1ACRKDkApsORniG9/LlQVIJgVK3WLyHJlHBc6U3Lg/A77ByyXWDLi54JWNwU/QVfPF7SoYuLHUtuPTce5MVsWTg+8+QTgDMwpsVknFzSXTVXc9Ognd7UNeDmBVIK0b4LO1QGAQv12Sx/Wt5EEdVgnN6Zv1owoQbKvGdwnZyZ3tc3KpfZV/qfjB8mdFhYphmXwciwLkVb6t9nG8xPvZ1fjuj4kKYCt94O8MmMRYSrcobxZfVd+KnP+qNm6+VUETc++MpXSc/UmhxlS67uiEQT/yrexVzUP5uFrHGZ+fWVs1ruOvZFFrof6Mxm21zz1fxM3JxbeOntw+RVm8Cj74ca/0Cx7ZZa3cXsmQrVGFEdjmEdPhsRn81MHz6pv58DzV8TH0rQrdtcn0gzw7uXmGnHwVzyoXdPJ59QqxCttmOl4TZ1A2R7N893rq7+zg6nHpWdBxx1gGByjWyNpNcBxgnQNWRpoZjwO0PE4VPLqOXOmu49Szjo6JvAJYzgZd/wzQZv0zMO1kyqjSFSa/DojdpxhxQFfxcbZSxYIq0HJgdOMoG1fgWI03C+hm23fWvfIPp6cK+MexNUm1sg93jO3GrVcVC3Ff9dTY2Mf2m4G5zI7QzzsFj+JZ2bPLCyyHk9Udr2Kjkifj3wH7Ll4gGMfxVJzC79h2fzhnc8mAvONRxTuV01Xcq8BvljexeED5lU0peZ29KfufjXVKXtUOZcffWQzh/Qo7oBwzT2XN8M9aPWSUYSfn89l4LGNsq9dZKRn4WPBQfCsfqGKb2q/WWGEM5jGTmzs6RZ24M93V3Gb0o/ZnOFGtiVs3JWNHLjVnh4kcZTlNybgW++xDU4Vq5hwuCCkjj7bZZbwc3NW43Ae3MwPE/i7oZgaEVD1tLHMwfAKy04MLjIqnGmOM/IXyOE7XGDPAmPXJeOH8ssRfyaR4dvpmes54udeqcPLhRM+f6pJ25IPrxLKpghfHqQBfBWKUTSk9ZbrbZ21cQsD5zD4Z3CVilQSzF2dnc3DjKLldopnxhdl93ePuEthOks7kzQAuvi/Zyel82M3N2afqUyV+F/OzbTzDUQESFZdVDMh0nekHf3MbvgyW7dX5DudxNW/1UdSxIaXLLqjq8M7yuKIsZrlLX3nMCuNkeVPJ4UjJiq95Q7m5j9NBFqPVbRpVoarymRrP4cUOVunoyvHGy5Ez/k5vaL+cgyPv8KvcshyO/Lbb7y4NVm/SYBnZvlB/Sn7GAg5LuRiq+qic2c1HLuY6HpzXOcZWVPmx+o266uImlLt6vZHrl5Fa91nebh1n+TG1C1VHKhmrCfPCdAI8Jzn8Vm0zGddQxXPNgjIPB7zHGBLMuKBbBXgHShVQmnlUe+aISg5HznFVXx7DjanspyuT0rnqWwGsClh3Aw6Cm2ztHehHeavEwXPk3xmw3Ce4zeox41vZkCsQ1BwRJDj51FhObmyf3f7ASc2N56jrgy5GODvK1j+IY1elYzXmvvG1498OLCJVvlKBitljDAhZ5oxfx+YUP5575pNqvZytun7uWEYuD+DvGB8LrSoe8v614CpbM4drOqT8oJOLeeyZeJLlLT6e2TGPk9lGhbeqMV2R5Aj1k/Vz8a7KuyznTPzk/t1cmRH6hVtLbh/f2dplcRr7uaePOx9B4jaVPrL8X+luLd6o4gbr0Nl85ScdGatcj2NVvtchzvVunLU0Vagqw3X7XDI/OjpawN8YtUJVQO0EtW6AinZrruF3MrvfDgC5AKfeF8V8KgAy63DxzU7HY7v7A5lfN4C7OVbrnM0l9FA5veoXxO9fi2PZ4+DdmvCc+eycsx/mnSU5pzdni7yG3FclBN6Hdsx83FkXV/g5286Kg+AX43G7LDErH4y2+A92FrNUAlL6we3Kdrk/z9vx2Cd+IQ9eb6UfJPWahUpep1OXW5CfoiyWdoCtymFuLhm5OMrj8L5qLmwH3fVXvqlyoOKnzmLHuuHrPlBX6PMc55zvu/myX7FPKJ2o2IDjo47iT6jq6q7sNWOsm4oYa1T2tC8p/m7NXd7IclUWn6q4zfan4neVy5i6wLsTf9huWH5cx7iHfDYOqTkhDxeLWaYOjuK2rAMVK7g/jxnb+KwY1mMVOx1WdDgxw008l45PqodR8ThOLifDGK/rjfdnsilMwXGDz5SjTXR9gHmq3NCZI/NV47j2FbUL1aOjo2UQBz4q40ZS/+yM4f8pY77sLGohHTmDxO9ZMFIFfDc319aN7xI0joE6iKfM4TGURfHJ9IeJC/u5xFTJ6Aya5zFDyrkyp8vWpRu8VKIbQ1/OqcauHlamfis5OgGqA1CzPq6/4ucSiloXB1YVod4wYLt5ZeNlgGCN/XXkz+JDFuSjbwYAMn1WY/LcK0Cg5uP0ltmbsiHX3sWp2bVy/VlvLnFXMd7pIAM+WT5lPrw9k/cyftmxzhjqWRSZP7nYmI2rcq6Th2Xh7RhLjd3JlwqPqDk4uZg69peN4fBZR46OD+FaKr1tNrsPW6qwkdKji91j1A+PqfJQtk/x5T74jXHY3ZqQ5f1sTLwqAMfgd/wq+Zy8qk2FA5zPsE+7XMRYKOOfzSH4Ve0zymIKy63s2+UIRcpuXU5lvrjmnfnN2JiLpdk6ZuN27XqmDdOqQjW+Z5IoK0IBSmU4HWUhZUrInMy1zcZX8irjnqVq3i4gdwBVB2x1dR6ghIFzh2fXoWbXX+l+dk0yEOiAu7Nt3Mf/OHYCLvNygc61n5lbBXgzu1HrngFDN47i0fHB7lkKXAd1zK1tBxgeipwd4HgIXBShzTl+Dripj5MLx2Oqno5ZxQqVO1iOGZ/utnUApbPOXRvfNz/gd2zP6inWtuPLTgb1m8d1746t+FRzcJjC5flZ++1gHBXvXTytAC8XW8r+Mszh5FNzZH0oGR1Pp1MFsrm/s308FlfduVyu1tI9l4DnlM0X+2Rg3dkk3zLFuCwjFRNxW2E75yv8jVcwdHKusuU1eRH3Zfk4yzPKvpxsPK7CYTPEvujiSza20p/bVlRhASdzhzI9Z3w7eKxqO5v/Vl36O/OEtg7o6hhjxiObtDPsKnGxLMpoVRDlYI3HusEiA6BqHJaRic9edwxdBZgM7ERblN0likqWTmCfoWzOar4doMb81Ti8Nuqf4I4Nun0umatxuF/3UjbHgxMqkgJB262/zErJUyU4bKfaZGeo1T3Y0T57V+qMbC428HjcJkvaSvfqwSRK3gr4qcsjOzFSUcgQf26qY1XfNQnOAXlc8858KhldMq5AnRuDwaeK/04m5Ye4dmxnSkY+Q8O5zh1T32oslMlRVlQ44lekbDYb+QqfKt+qBwe5IiCTXf12/hbtslxX6UT1y97FqfrP+rjLdXisyhEKwGN7xhNqDB5P3frBelZzYNmQeB7Kn/C4isPKFhxui7VT70lnnVWYarvdjqurq9fiu5sfzwV/89VzmT+xP7J8ShcqVnXGcJSt+5q8Uo2jtvke+Yx/xqfqM+u/nTjbybFVvJ/lW9H062mq4OqCV5d/d9G647h2ncSpHNv1Uzpx4DCTNyi7vEPx6QR0pAy0caBVxp2BALfPAZcqYbBsM9QBKzzXKkF2AS/3y/xGUZbsZoCU44u/qzk5m2BdVWuv/IcLqTV2oH53/xhQtlhtr014VYJwsiges4WXWgd1/+C+88gAv9tXjTULLtX+ak4ZsHZydWRV68k+4/wJZc9kcoVAd95Orixu4u8MuGTxwc1Dya/mUuUftd2JM1VMU7J3fVvlko698dhV/qrky7AR61r9dnPm/hzfsZ3qXz3V1lGGzdw+55O8L+RXV6hwoVnp39lB8Fe3C7lCtcK3EdM5rmc5N37jvFwOn4nDKh4qv5jBMo66sStry224rYsz6vcs4ZpUOKBDzrZdPOI+KtZwn058XquX6dfT8D9WLqBni9k1lpngVsne2afGdu33McRsrrHtbkzP5OkEBydLlezYabLLSdTZiyqwZlQFw+5aZIHLJZiufBXw6QI+d0wRJk1s7/49xY9Kqt25ZqB6lhx4dIGP17zzSoDqmEpC3DcDbd0xZxNxBpyqsdy4fBmme9BMJkPl1w6odWylA8DYVhygw75Z3GG/U3EvkzcbrwI4PG5s8ytMZnVaxUYHPDq+wDI7XalXYnSJ44CSgQFzJ7ewnewTv5wN4TH2LT5rFPErw0ZqDnzVUlYgKZlQNncskyXzNzWmArMcc5Qt8XzcNvNWIDyTscppzl8UXsLcivPEbeUTrtDleSI/xmEc0/GJ9cqfeR6hCxwTC1X0aRfTXAxRulBzcLrnNlnsczJk8bPKz85ulVzqqi0ndxd7OXL9la2in7DPcL/YdrbPc2LeTPvE2+nX01xfX8tLZVAYbMv71G/enyVIDmyHIhcA+bcauxPkFMDKwJLi6xyWZWPiZOn0zAY8S8po15KTR61FRpkTZ+AiG0PJ0uG1hmZAQBD7JycdlVyxXTZnJ5tLhGzjLKvSWzW+AihOPhcwkY+y1Wpus+Byhtxj/Jk646rkqmJBly/Hr8zXO4CC7SEDOSxDtm4KvKnj3ZhcjVGNz+1YDwwcVE5B3w0bcfm4WmOeI/8BXfVVPsD7qrEzcjkz+Cp53O8KjFb8OqCL2zj75D8X1Tore2Q9q4cVqbbZHLJ4n1GWL7r6jf0z9oX7uY2yO5Yvw1XoVyonqnlwH1doRr/qfaMqn6t5ufd6b7f15b5Kz+rVdxFXnI9nPlXFPOXbWRzOZEeeSh4lWzdfV3HbtVFj7YMRXI5z2LbLsxsf2B+6cb0TN7u06j2qnYXD311lZm1dUFxrANwvKzoqHi6wsbyVDN02KjirsTJD7gSwjE8WUBzAUP0OBYrVGFUblUyUDNzP6aIitO9sbboBqCpilE3yZUUcsDrjuwSbAZY1/uVsWwXZyo66+zPAuw/NrufaBFeBQvy48d2YCjxmybiaj/O/TEY1LvJlcKLmPMM3s5EKmHWATsZbATkll5OxkmuM1+PgDDl7UGPMgCsGRe47k0vJycc7OnT7eE74jWNmsSnDDY4c3yoPKzkznVa5Rf3OYmfHjxQ/JX/Hlhg7RHtVbM3kjk7udzGN+XCMwz+fsrioXpvGx3C7oio/Vpg2i7GVTc3Encrn1+AKlqOK6dg2tivb7sYtxV/x7fKZGdvh8iw/uDha5W787tJehWqlrExg178KBFWCcP0cVYVKJW+HKj2o9p3kPsNXgcru2nAQ6BQdMw71+6ZuYsqSf8WHAwSvlQusGbjJ9F6BTQ482XbIV327Y5nsmb10iXU5C7RVjOkmOgVwXBDfbDavXerXSRacHCpAymOqPi7xVnOoxnSXILp9bgyWNbtctLNOCsSxHli+7Xb3IRjVOKzTmVjcIQY7KCvLjdtKNvxGijMnLBfHLZeXVa7C/uxbLi90dcf3CP4+c3KQmi+TyrdK3soWMqCpLi9U/V08CZ7xlN2OvVRjZf1ijDW4APviPpwH71fy4dzjflB1T2wWr0JnwSP68ZsxuB8+sE/FueDDZ3VxXIxpjo+bO8uT/Y7cxWuK3yyHateRKb7VAx45ns36beY/wRdj3cwcujrNYuca6shZjc3b3THH2L0yQK2Hksdhmy5NP0ypEoSDRwWsMlJBYwYEdSgDaLjddTwHvDptlQwcnDPQOlvcdMd2SZf5zia4TJ5s3p3+zCvjncnXmYtLoLHt9OLkqPTsfuO+GSDo+GSBNwPEbt0y8ObadRNTtqZZIHfzZTCnLsd161SBsa5/xLgziUDNJbNBJX8mswPoLhZVPt75Zr6o331iP8vSATWdfRl185WyxY4dKGBXyRpgk2Xjgsz5ayYzU6bjym8Ub/QPxh4qXrKMM+tXxdCOPc7mscrWeY1n8n0HPzhy/l8VeNXYzMfZfIaDHH/GM2H3bk5KviB8ynDwvLy8LOevPjhGVaiOMcbV1dUiA/PO1r/Kj9hfxeBsDp3YzbEE1yOTr0MzOdjFCz7uxsn8pou73H61fpk8HX3PEscbxmIK+3X54meGpgtV5WAhBG53lJtRBgZx3wwg6oynFiEzNl7MjjwMghXfLrCcSUwVuOCxVWGx2Wx2AiTz4O1OseWCTGcu2ZxUkHV9MmDl/q3M5l3Jo9pm74LLZMyOOTCI43VtVwUq98qZ+FZrud1uX7tXy/XN5qKoKqDcvFx/ZZ9uTfYFvSqe4Os2Kn6qkHA+gPLzuiPoqWw2S6ZON2q7irVqfC6keE5se5n/M3/kvTbhK7lQvmr8jFcGKrNcrdYuzoi4V5uo38hPxfwsHmZrw/NicKtkQH68xi4/qD4ZKVzg1iNIFf8Z74wynSr9V/NW/Hks57+cp1zscZjK2QPzdNRZMxfnstiY8cCcmT3dN8s/Kn8qGRVvpcOKD28rmsEq/AClDi7iubOcQe6VhmqtM6yW6Zv3dWzO2bKSA23M8eN1qzCXG7d6AJXzj0yvuN/FeKU3JzP/7uAYR9NP/eUPg959hAniiTln6ySBGVoDSCrws9nU70TNvpVsASp4HCdHFuQyWZB3lfwUodGrYK6e2DoDHrpUOVcGCl1iY/7qO+OpSL0LjsdxSR3XiOfLCYXnpooV/FaBSr3zjINppnMEccqGKl3yXNQj/VFeZdPuFVBVYFXJT7Wp5K3a7EsqQR+SkKcqLpzd4W+nexzDjc3t0Z7wQSBsr+osigOeM9Tpq46rWO7sq1v08NkWPOZ0HH3UQ5tUPHAxZjbWxn4HjpzsIZ96SI3yYYx33fji2jD+cTlOxZ3ZfKHm4WRTfzaovlnMd+T04MBtfG+32+UPN1cgIA8XrzOdVHJ2jyvbRtmiQOjGCC4MsrVWMaiKh8q3K0xayav6s17UPFBu9TocF2szOTtj8m/Vzt0CovyUY11mZ2o87ufWTPFCHpkNVFgyu4za2VQ2phsrk62Lnzq096W/LlAxVYrFNridKU8ZuQuEXXIJUgGy+F0ZKh9D3llbdgQes6N3nsc+lIHGGYA2G+SZTxaUu2uvApOaRzd5dwBhJmdHZnc8+12BC5ZNJWj3mZGJx8lkw+1sLgpodddPBfvMDlgGlKXz+g0EyJigO8FfHXO6cDGjsjcly2zMYB4O7HX5zACtTqyo8ojLJ44/81oDDHlMlpHttFtUuDhZyZrFrC7wYLA7M1b0Z/9wcuGnexlnjDFDnHNZVuU7ag5ZvmDZO4C00lFnXln8RJq5D1LlErU/yOnRHXdxXvGZiTkZZbnI4QnFfwavVfhGUQd3dnl1eTK5P2KjT/bHMn8rf0NeGfZjvKJ+4/cabD1DFS5S+YDlUHbYsa2OjVf5b7a/o9n4u+phSs4IldIcKOg4ugIQM4rIlIs83cLPgjxn2LjPPXyEdVa9i5QTIZ5BqII4y8THcN/awIjHXGBh6hQuPOZm891LuDMw4+ay3X73b68LUpxkt1v9RL2uE88knWoMtInQhRqL+yhbiodBuDZqm+dWzSuzsczenE1X4IrbMIhm+1KAiOemPk5elXgymbs+p8Zi+dRxR2jv1cMxGGywLLOxmvtHPKviQfzuAkzkzfs7/Q9BOCZeUeIuu1X2GaTkVpdlRrxiYhtFedQaurO0HTBT+anCBEoeRRG38H2PTrZ4r2TFk2VTMqp5q7VTseCQNqV0y3hE6ZHX3fmuios4X8QiLEe8LiUwza1bt5Z9a96vG7I5f0HZUPaKn5ovblcY0PHFb3XvqbuqbCYvYt5HLOh4V8T2qmzGyclzYJyU4c+O3issiWNm8rk5Z7K5sdmnu2NnGEb5YgeHocxu7Wdij4p3h+g7iw1WnVHlwdQirwFjLglnoG+M/DKnNcBvhirHYcIClAExEgYedJTsvgD1bjWWM7YZvCl+ai5d0Bvf6imaaxJ2BgpYp07GzF6zMZ0MlS7cOE630S5LLm4bQZoDDyx3BXq5jZK1AwJ4bso2K3vsyletjXoARQUCOknV9Ve/qzV2VNmt8pFZHoo6duLidcXXgRxHaB9q7bpzdom8yktKFubZWUt+0qjr48BPFcvQdvHJvm4ebg7VtxvbHXO/OW6pMTJe2J91lr3PfRaIYXzpxtFunsh8oYMzurks8wGOecoWnKxKtrg0e7v99g9h/KMgnjasZHRzU8UXyo3zcjklm3NlP3g8i+9qLKVbzgVriwGnnwprVDaw2fg/sFA/+I06Yx2oeXbyqcqdyJcv/3djRzx042Tju7iLfThOq1yl/G8m9nTwRje3c/tZ+/t99Vl1RnWMupBUzpcBDNV+Jvm5IMpju6Dggl/XKDrgTOmh0iMaPL7cPePv5tQ1ZAUaKuIgH8RFJM+vIw/Khd8srwJ9SifVWjmw6tZN8eb9LGvGw8mmAp8Lei75VPPsHu/MoZpPxpN9M1urCpggVYWqstMMTGQ6qtZhTXLIEqT6xm23LhVAyEBpJR/LWiV41cfxrYAzypTZaXc9O1TZQ4zL83X3p3P8Zz78reyV80kmn/LBKp9mcd1RJl+1Bll8qQBjtHXguDv2WlDoYk3wqV7LlOUPletUTMR8meGbym6y3MpzwiKGn9RcxSr87eJxVqDhfB0/1BHKxq8AqnIF83b6UfNgytaHiefocinPn+eEx0On8SoenheeLcXYhGtd5YP4zuxQfSu5VX5ifagCOuOjZHFtFJ9OXJlZYxXTXCzi+VVxaiaOoUxqu5JnNs+uLlR5cGXIIRQK5xbYBVn8dmMoqozEOZFydJ5HJ+ApWRRAUQFV8YjA4UALAwf3cKtO4KjIyavm58apQG/HaVivnUQffDvvS8xAjLJX9Vvx5gTSWRO+HNMFquDNr1NxgE7NJSNee6WbKrl0gnxFzrerwOjAK/NWPtyxSQVE3P04bk5uPu5pmx07dclMjd1NsKp/trZurdbaIspagR31eqG11M1BjhyAVEB5DP1OWBw/5oZPJFXyZuPOzKVaI+U76jj6SOar6l2TzIfHxb7BTz1Bmy8TrOa13epXVan5Vg+cU/2rXKRwkWubrTPmv5iT4lnhOidjENojFjysc14HHrPSOed9lx+ZJ8+P1w6vbOOi1WFSp6fMx1j3GT7oxEiFV6vxcU63bt1a1osL1TH0O3xVjForfzfGdmORkqerR46Zszqt/JXHUzwy3qrtvjmuQypmVhhmLbUL1TULsgbwBGF7fEKoMhBOcgr4uCTN8+C5sExu/MxwK8dYA9xZz1n/WSBSkZs7yqWou18FhkORstEMMM/YbwageD2UfakEp76Vjbv2yp6765Dpg8fFMToAqgI9QRWfal0y/TkgoHh04h9uc7zqysZ8nY1U9tGljA+32Yf25YdrVcVx1TcDTjNAqor1Wf+O3E5Pym6D8KqVWdtG2WYom/sMIFZ+ouJlxce1DdAdsmVxrBvjY46ZHXRzege8qvYVnlF5gMdivKOe9eAKsczGM4r12G71HxDKdqtY2gHM3UJB9UUe/FvZocLDTmYX42ftwuX2jq04n8z4hvxxtlw9syObF8vkcqgjteaMKTpzR7kqUr5U9atyTWc8xbPCjzNydvCP23Z+p9ZiH2oXqvwACkdxfOZG+cqZsV18ozPhv20YADkxOcPOAGH0zQJBx7EqYM4GpfSndNF1mH1JJavqwT0uuOGxKqFWACLTfadI2Gw2O/8OzgL94NGxAe7T8SUHrphiDldXV8u9P5z0M0DVBVZqf1aEKJvgh5m4cfASMXcJVqcIUbbGMmexoEMZWGaZ1e9DJBKlC5UkHEjv2n3H3lGmDOysTWBdHfP+zjqzzWRgNBvT8a5kyHKWsltuzzHjUPkB5c34uTXnefPDpLA/5j8uoJz+eBt/x1h4jyTH/YoUCFPkChY1zowvVfIoO3Dy8Z//vCaXl5c2x2f2lPlUkLr0l+9XxX6dvKUKpegf+mf7YB0o38ny2WzOcGuSYanMJqpcG+1cHnDEsY2vRAj/5CK1who8LxWbsnl3sSC2d/Ex65vZd0fnuF/FLcfLya5kU99qfIWn11Lla2+Sps6oOtAzA7gqZ+L9rh0HOww0KFcFonFcDFqqjzNyZzDKQCrjVH2ZXHLOAHdHt1XyyQCb2udAFT/RGPW/Bli5ZJ8lOCWXsxVlty5hKVKBOFtfF1A56Sq+akxMNC5gOb044rXrrtfMula24HxxDA3ekCrAweNm/sHrUMUBZ2fZerr2lT4zu1CxMkt6GW8Xb2YAldrmfipx47HKj1FWJTPHJdWnoqxNFjc4f6lvxdvlZDUfbIPzcmCmWjuXt1385Ke18mfm3cbcRl2OuNlsdrACEz5oKotlzo8YPyCpP/erHKt+q/jiiH25yiEoJ98OE+vBtp+tjcsrmd26OVVYhv0z6898kAdjSfxmXm4sZQ+KjyLGRO4BlNi+O47SgeMT3+q5Ik5mpacs52T+4mRGWStbwbY4tssDbm4ubjLPKh84u3G4U43Px7q2Wa1hJmuVhyoenXgxQ6uf+puBxIrHGkGRBya0MfRj6eO7UrBz+i7oUvyy/Z1kqGRSOuN/oZ1hdNaqMzcnRxVweD4MKrP5dmTK5OkEZqa1enB8Mp2pNh2gWCVpx6Nq6/Zna1wBJ9WnQ8pesH/XNrJ2HFBVoJ/1+Wx+XRDTBTjx3YmtWeLjWLlPjGY5KsAzI6+yt86aVeAE+86Aj+56dpJ1lbcq2aN9B2RhWy5EuA2DxE5hwvbIfqbuD+R5dObNY+K4ije/xgNzaPV8Azdut31GKq7H/rW+WOV9xFL4PUb+hwLag5NZ4R2XBznOu/xdkdOVi+/KR/bJV9E/y09Zvsx05AoQh5+U/CoGZf6LBXyVcyvM5dpm5PBgFn8qmvWlSredvIvHnewVJq3aODw5o6MqlvN6qBzr4j3znV2HvV5Pk+3P2mVJaE1hoh5asIYXB8yMnwvAPJ/qUdgzsnWACvfJ9jFAVTwr8Mb9XcLCoKoeYLEvOOaAsja5MLn92XsJq75VmyopcFuVoKOvA1/ZuLNUyVv5iCsuou8hCiclL247HSo7VXPIQEb2m/vPFCkzdlIR+npFbq2yuXVJFR183BU3qA/V361xR4/7FAw4Tgf4cMHFcuB3Zo+OP35Xt+iwDWKx54CIOiuaAV4ulqq8pObi9KZk3Gy+fUDM9fX18qCYeI0K8mM5MxkU8JzNQVnfTiHYJbduSPgwIVz3KGCYH9oFysgPI+J+vHauEFG2hNtunbM5K2zDY1Z+nxUbLrdUWI3bduxoTQ7IChP0SRxfveZKraGaSze3IGXxz/kAyjETT/6QCGWd/QONeXTnXdULakwVZ7MCdS21C1V1WQ1TB7CqfbNFwhrKgJ4DL7MAqwqsFRBySa/TvhorKwLU8UweJZ+av2pTgQAX1CubUiBQra9a224xwWOq/a4Ic/PL9JrZAQcGN8dZO87G4m0eT+3neXTXZF+Z1ybuTgJkqoqfSn9O5gyQdXl0yAG1Q41R2bBqX8UlBplO3x2ZZuVT7ZyvufjEdpbFOQfcK79T8+BxXRxX1M0tPC+OVer+SOzbBZaoM5dbgr/ih8UVyxztu0C7yu3d9mzTytazuFTpzgFKVxAxYI71U28VcHbs/FnJjLaR5Wg1VjfOsj6yYijTTTYPxUt9Y39FqOcMN2U+n8nLfTJMluFlXL9qTkrm2XjsdM6xIFuTjhxKV7N4MfpXa56t7yxVMXoNqXk6m3A67sR1RVNnVJ0DZuC841RdcFHJ5/i7ADYb2Dog0SUTbqeCK4/VAT1qjK7BVzIqYMTz5PlEW1eQdQNZVcioeWBfZVOYABU/52wuuWayKOCsAGPlK5l8sY9BA57RUHPNbK4a28nAAI/nkwW5aNtd45mk3DmOPDNfYhlU/FB+4+Sp/Bd/M79qDJcQFGDqJO5Z4NGhbnzi35kPM6l43Omb2Tu36/DDNqpwqmSpQKKKtR37RB4sK/cN4nvYKt/ktnxZKZOLIU4e7FPlVt6HhSquS6WTDNzGOF27cHgoy1esH6czlMc9GMnlauSL7dQ9v5lNb7f6tSU856oNjuVyvOLLMmaxL/bHN7/ySfXhs3bOB5D4tq1qvtFOrQ3qOdNH5VNKN7zuTj6UQ70qKJtr5u8ok8uLbDtKLygrfjt7zeIJ60nNh0nFgY6tK1I5nKn7MNZKxkyGji7xt4pZXdr7PaoVoQNUoLwDKCs6BPh4U+O79irodkEPEuu3Mkw+liX4TC41lguaWfHEAd0VMlVBE20CULnLVdS+ThCoQIMj1u8M0FbyxDYnPbxn283DBf+11Cl2OqA/k6mTYGdJ+VAmm9rn+kQCxUvmurpwfozHHY/qz6DKP11blbCVzH8oVMUJ14fbMUCp7E21V7xYFqV7vI9S5U/mreRlnpiP40FrKhajTB1bj28HDGMcjssudjig2Yk1GQis1q4DNN0aoxzOVpSMmZ1W+WYNAFR6dPijE6tccZI9IbSzVh08F9sVbql8hPmp+3TVWGjXnHfVPJRPKWzA6xGfq6urVE+OR5d4zo6Ps7u4jL6zrh2bVXzYvvg989yO58XEl/2jTSNfV6xX1PFjRVUcVjlhhg7NT/VDna6lgxaqFTDC344woXX5d+TqBFsXqDv8HTEwqRyyI4PST6focbJ191dy4fEKDPOxCghV82P7csEqo04w2LcwclSBKpdMHXCr5FNzU3LsM0/n95lNzFLVZ19bDh6ZLTueDMxn55cl6E7BkPHlOKOKE9U24zFDoY8ukGG54lgAB7w1BXOI8t1Mh3hZI8uSAXm+L1MVMhwXXXGDfN2a8DwzPoqcHFkB42INbrN+WTZ13xvPD3lV8ncpKyBQj7zWSl61nkoutM8Mz7AOs3jDOnb+ns0VSc2LSdl012+xgMhiJY+V2ZDKiewLVU5T+dzp3m07eXi7ixfUfJhmCx0Vpyt9OBmqcTK+Kk505sD2wP1Vgcl9eT6KJ/Po+lXlBzh+NwY4XJxhwcouHE8+VsnGc5nFV91+TO1C9ejoaGegWWDCfVzyc87hgocyTt6nklSVdHEM3u7ML9tX8XBARpGTayYwxrgzyR/1mTlrJ+HEdhaYs+Dm1pHn5P7BzxKMm1+W0B0pQFSBMe672bz+xEwlr7unPNMz968oC9guwLrtfX1nbQCMvs6mOLlVNurk4eCePZSCt5n3jJ0pOWM7A8RrCeeo/Orq6mpst9txfHz8WnyI/u4sDO4L+z45ORkXFxfj1atX4/bt21Kvt27dWh6as91ux4sXL5Z9yO/y8nJcXl6OO3fu2Pnh2YIoavFBPCcnJzvzinHOz8+XMyEhY8h0cXGxw3+z2Sxt2VYuLi7G1dXVODk52ZEnttn3nX5xXbbbb8/SxNjxTsusyIh2V1dXO2AxHlCEeok1D1vjd5rG2PhaDr68VF1+Gb+jbbxDOvQXfK6ursbV1dW4vLwcx8fH4/j4eFxeXi5rfvv27XF8fLzM5fr6erGlsBWU5/T0dLGVIJwD6iLkfPXq1dL25ORk2Rdj3r59e+kXOnDxu4rv2+12XF5ejtPT03F8fLxjXwzUXQ7HPBU2jOuoCgMV8/hBly4uKB68xoqqXKaOYb8M1MfcWR62TaUP9eAopOyqF547y17NdRa3xJiMj1S+cPMJUvOq5M4wnrrMPMuTLF+GlfAdsBhvkUcXm1TzzfzMkfNvd6zClZHvKrvK/CeOz2IG1uUMthtjxXtUeRAMrDPgPSsWmF+1uKqv6pcdU/JhUHOOqgBfZbRMCgx0+nX1oMZSY2RgvRo3c9xsHx9XOnDfFV+3hmqcLHGpJKbGqqhre4pflbycvJlu1DgOJDlbUn7q+jLQ7FDFe4ZHBf7GGK+BeOahjrn2WULI7iGZjaMdnVTJJePvAKnSCQLpKBpUWwS9mSxVXoli4fbt29LuuIjabrdLUYD9b926tRQxWPixHJeXl9J3+F7HKJYCBAX/6FOdaYpCPnhg3OIn1AZxrENCPjhe8EGd4GV7CG4QzG632/Hq1atxdHS0FDFRoCrgjjyurq7GxcXFzhN3Q7cx7+CN46E88ScBrjG3ZQAac4wiFflhYYtn6VnGkI3nxfcyhjzRB/+YCZlizOPj40VuPqMf7dGXcEz0TyyM44+My8vLHbsJnqrwQ5sKeS8uLpb96g8kHBNtKf4ccL6scgJTli8cBlCXnFYFVoZV+H5s9D3u6/arGBptqvys5JrJiR2ci7bEfwgxf5fXsrmgHNxWzcfNtzO3LubFfMDH0d4Y42T7nFwKczpZ1TGlf6XPTB8Z3mP9O1tVvDv2dQg62HtUHZDrBgzHrwKIGYCuaCaYOb7OmSvHnaVZMJrpN3Oqajzkn61Zx7mdfIciN2ZXDhc4O8lVHe86P//ObAz5uKCPCQ0DcfZQDHfJWqW3yqdibOcv7qP0tLZAc8DH2S0fY8Cl5jOTMLN2KDOSAhQZD55XBgJ5LkpmxR8BK55tVLz4PiuWjfnxmFj0HB8fj9u3b++AcqWPKErv3LmznMmLfaenp8uZtW+++WZst9tx586dZczwlYuLi3F8fLxzNnaMsVNssNxRgN2+fXsZFwtHLLJjvDhTHEUVrle8WiXAVuwPv42ziGir2+13BfPp6emy//LychwdHY3T09PlbC3aNt8jG9uXl5fj/Px8nJ2dLcV9yPbq1avFBsYYO7q6devWuLy8HK9evRqnp6fj6Oho3L59e5yfn4/r6+vlDGAUskHBK/SMheXl5eW4devWot+QJdb39u3b4+joaBwfH49Xr16N8/PzpW+cSQ07iv1RoMX8o0C5vr4eL1++XAp0jKVoa7Ev5nV2drasAer59u3b4/bt2zs646ISz9aiX+BVAni2Hs/ih32jj0Q79CX2r9AlFvUqFvAfBqi/i4uL12xbxSEVi7oAdzZn8JwdT5xLdutGB7dUebnCiuiPPB+Ve9w43C+28c8YdwYy+LCtuHE6GAvjl9Otm3uXWE51qfAa7On8wbVl7NUhhZ8q3IftHW7k7Qw/dufF47i5xDffKlPR1D2qHUfloMRUCbbGaBz/zFlc+0NQFpjfNDm9x7FuIEPjy3iq/vuSs6lZUsXRTALMeKrLiA9hP1mw7wR+tc8VARxg9k0Gar+yJW6TBUWUleXsFGjMx9mC0pd6mEJ8Z5eiMV815xnKCkmng2oMBxr5WAYC1TxjX1zeeHJyMv7zf/7Py6WUl5eX4/nz5+OnP/3puLy83ClY3byw8IvfP/nJT8Y777wj1xKBNZ7FjEL2/v37S6G13W7Hs2fPxk9/+tPx8uXLpd+jR4/Gf/kv/2UBbnGGKYqiKISC8MxcyPAP//AP4+nTp2OMMf7Df/gP4/vf/74s3PHMm1qL27dvj+322zN5WMR8+umn41/+5V92Ll9T4Asv6Q2ef/ZnfzY++OCD5cybexgOAtco/KLYe/z48fjiiy/G06dPFz2HDURh+NFHH40f/vCHS8GC84rCLArUuOT44uJiWZuLi4vx+eefj6dPn45nz54tZ7TjrN3FxcU4OTkZjx49Gj/60Y/kWfwY6+LiYiniouCNgjT0HPRP//RP47PPPlvmhGcWQ2djjPFXf/VX4+233x73799f/liIwv3y8nL88z//8/j88893CtE4cx9xJPQVRXvY05//+Z+P+/fvj7fffns5uxyF9cXFxeITL1++HC9evBgvXrwYP/vZz8bLly+Xtnfu3BkXFxfje9/73vhP/+k/LfNGW8IzyPE7jkfBynHx+Ph4vHz5cvzt3/7tMreTk5OdP0kyqkCui5kVmEZ+Wc7vxmD0J7TvmRjOPpnNhSmL/bPjRf/48B9Qlb7QDvjhRRkGyD6YY2fwR4Wxna7dbSXV2Mo+uzh/X3ylqKP7bn/mU9lkHFP41OVw5aMztPphSrPOWi1WF9DxPxMc6JTBd4wok83Jq/pzUFDyqLk60Mjj4TGUQW1XslfEPFWgzozaFUNrDLVDWeKrqONIGMSVPTvHXEvdpOh8pwo4fFkT2+qaOWTyqqDmZGRQ2y1SWX5sr8CLa19RNZZr0yHnN13K1n02TqgP81Lyoz09fPhw3LlzZwGxjx8/Tp+e6OwRtx88eDDee++9nX4IuENWLlTHGOPs7GwpuG7durXcVxr94qzje++9t/TlZzSMsXtWmC87jbNg8fvu3bvjnXfe2QGEvE6xLz7RDi/DRNt9/vy51Z/Taejn7t2749GjR8uZvrjUFmVDGTabzXJf5qtXr5Z7gl+8eLHca8k2e+vWrXHnzp3x8OHD5Sxu7A9+cYYZixw86xi8xxjLuAx0Y50fPny4c/lxyB0F4vn5+VKkRvGvCtUounhNcK2j4H306NF49OjRuH///nj16tVOoXpxcbHMmy/1RhlxbUJnZ2dn49133x1vvfXWePjw4Y4txB8Gwff58+dLsfrw4cPx9OnT8eLFi531v3Pnznjvvfd2ClWcS9hI/H7+/PniB6FntO+jo6PlTxi2s5hn5uPOTqu2LhYhsZ25GMw4Khtb2UElK/5W+TjL0ZxDOG85H+/GaB4na49+xldy8BwyrKv8ttJpp4BU83X24m7tcftm8YBbR25b0Symr2TL9mc44VBjcRunL0erClUuOrLFYaCohJ6hCkw6Q+vImMmWLfZsUVSNtbbIyordfQwdeWTFhaIsGFSJhvfN2A+uS0c/Gb/sQR4ZHUrnnf1sq26NGEwq/1Tzq45VACDzpUwW3M9U2WGnOHVyqIeVsO6q/ciXQakrZpFnN+gjr27ywbbZ2ipQ5eTg35eXl68VV7dv314KQxybic9ms4x4KSNeMhmkHqoTBd/z5893wHQUSMH3+Ph4eRBNFE5R1EaBg3JtNptlnmdnZ4vsceYx1gjvU8R1w4f8xMN1Yl9cShu6w4Ln+vp6OfMVsuCDf6JdFHpxxjLOLEfRhpeNht6igMQ1iMLl7t274+rqarz11lvj6OhovPXWW+NnP/vZci9lnD1HMBr6jTPSUfjjusQZ9uPj43H37t1lbR89ejT+/d//fWw2m/Hll1+OV69ejRcvXixF6dOnT8dbb721yBpF6fHx8VIAbzab5VLu7fa7s9P4J0Xo1Nk6Fl73799fitS7d+8u97PipaJY+MYZU9YH3isb6/ijH/1o/Mmf/Mk4OzuTxXasNZ7ZvX///hhjjEePHo1PP/10/P3f//1y+S2etY01VQ9vinUIedF2ODZEsYxniMOvTk5OdmzLFTD4rXIAUwd3hA/gd1Y84VhVrsX43SEuxLo5mueT4Q11hrCLqzi28zhc4OF3Jn/wyebtnlHQzf2KWFbc5/TixlqD6RkfO/k6Y3Bed/7BNViVrw9Rq3T5dDBDV56pQpUXMlsY3O9AIoO32MeTUTwz2dzxDvCrACTKVAUY12+WKjnwNxuw0ntXF9WYXUdwa9sx0ix48BplttFZj44dV2PhMZeMkXeXZooETBQuOSlZuZ+yJVX0Kdk4eKpgymurCiY3DsceNdfMFmf9s+ODcelcFjtmAFls89xn/KYTPyufVlQlY753Mtrj01IDPCsgU61rnNkLQIoFV7TByxD5Ml225RgjLk/Gy5L58sggvKcrComQCW0c/+hS9+bg/a9BcSYYC3D0QQSOx8fHO8Up3//LthDFZNwPut3uvuaHz0jHurH9HB8fj3v37i1PmMXLokOOzebbAjH28QOHcM1DF9fX1+PFixfLvC4vL8fdu3fHe++9N77++usduVDPsS9kQ7ljbrEe0Y//SMHtKNZDvijeYr5xBne7/e6ScFzP6+vr8f77748xxvj888937vcM28c/We7evTt+8IMfjPfee2/nydN8OW3YXfjRycnJwvfOnTvj7bffHh999NH4/PPPx5MnT2xxgZf5cqxGv8ArDdBPQv4oWtmO8Y8ZLl5w7dBGVbsuqXWM9cYxcJ4oRwas4xg/TMkR6juLrxkmUnhDPbBpFhPjmnBblTfYflw+r8bGOWRYwMmmeHG+yXAG8+H7tNUcqvXK9OGwo+Kl7EDJj7E6+nF+cHZcyeNqnzW+2KEZ/Dv1MCUVBBwo6wBHZQhZkJp1SNUuA4HZ2MoYlFx4Gc2axWbghGNnvBQgdcaObSo+jpQzuGCTOaTrH78zGZRTdooVpE6w6Ogfj2XBLQsQGc/MlqqiyMnngi7bnvN9tT6cQFSi5kuOcSzmy9sZ0Onarpq70oPTQcU387sOOd2xLCoWZWM5n8TjFY+sD+/DoiWKeAT/mEMqkIhybTbfXYYaD8o5OjpaLhdF2eMMJY4XRWCAcD4bGzLG/igq4swq2iSC17hkFQuVMcYC6FE+p98oouMVKlFIhVyRX/iBTChPXHbMOsN1QZ0FDy62o+8YY5kXgv6jo6PlDHLck7zZvP60YzxrGR8sINlmQo/3799fdHnnzp3x7rvvjn/9139dinNcIz6TfHR0NC4vL5cHH8X8sMDabrc7Z67RBlHOmC/q/vbt2+Ptt99+zaaDf8z33XffHcfHx+Prr7/eOUuNax38z87Oxp/+6Z+O+/fvj9u3b+/8cYFjRL94KNS9e/d25Lp///748MMPx9OnT8fjx4+XY3ifbciJhSrbNNpZnGVl7BfrfH19vVzmHJdYh9y4xllsUttog25flptcTgnZMPYoPKHk7GC5LM+qeao8wbG64uf6V3JVGEfldOaF7bJ82cGCVc50GCPTucK/a7Gim7+aXxczqH1qTRQec3pfk8+ZZ6etkp2PV+tR0fTDlKrFZaXhfge4u0phXjEOG103GCqgrL4VVYupAGWMmwXe7Klr2B/BPs9Pjevmp/hUc/9/TV27yYKS48n7UEedJNClffTbsfWsTdg+X17JxVXsmw1yaqwYjxOKAhFum/lmxEkE/Yv5of2rosgFfzfnjLL4lwECtr/Kx9XcOAbNxt9MByxXFBxxpgUfSoQPrRnj9cstlb9iATHGWC5BHePbIur58+fjf//v/z0eP348Xr58ufSLS3WjSNlsNuPZs2fLZbybzWan4IkiKC5fDTkuLi7GZ599Nv7pn/5pAfx8j2rwigIgLoV8+fLl+P/+v/9v/N//+393LjHFs5h//ud/Pv76r/96KXyeP38+fvnLX47f/OY3SyERl8WibmN+WLRGERfbMX+cy/n5+Tg/Px+np6dLQfYP//AP4/PPP9/JQXHp8snJyfjhD384Pvroo3H//v1lrmdnZztF4fX1d+8gjUttnz9/vvOam5///Ofjl7/85U7hGJcjn5ycjHfffXd5AFPc7xlPx0X543jMLy7PDtv+3e9+N/7lX/5lWSO8vzPs8uzs7LWnKx8dHY3nz5+PzWazY6sYO+LMJZ5tjLPwp6enS5+33nprbDab5UFdcX90rFnYYRTu9+/f33k/7eXl5fj666/H48ePx9OnT8fPf/7zRa4f/vCH4+233x7vvvvu8tTqsIkPPvhgfPLJJ+Orr74am81mfPLJJ+N//I//sbO2YcNnZ2fjnXfeGf/1v/7XnTl+9tln4+/+7u9e8/HN5rt3wG42m3F6erpT8EbBGoV2Nz52cJtrH3PCy34x7rj4yXEwi8lj+AfsVXPISOEylZ+qXKRiv4rzVVEX+2bmogq0jEeFSysMnhWLiifjatZhJwfyOnTm1cGMrth1+R5/O9nDB2ap4tshNU+Vz2fsa/XraXDwGQDU3YdjVMCoS6pQrShTJoNABxJVgHFBRQVVNQ8VYDPnQTlxfNavc6zZJLKGnIO6djNFg9J5J0jNOG7HR7qyzozT4a3a4CVwXeomZpUMlZ1yEYb2r8CEk0et5UysWWNT6jgXXI5HBY6YD8eRrpyuXZVwu3PI4j0CR+XTVdyvxuH+z58/H0+fPl2KgjHGTiEXxdLLly+XggTHQz9X8eLi4mJ88803y9k2dXYMXyWC9vvy5cvlXlPmv91ulyIPgdX5+fn45ptvdgobvg8SzyKqXBQFCcd8pe8XL14sD7qKdYszrq9evRpfffXVuH379jg7O1v0qtbKfUKu8/Pz8eTJk7HdfncGMgrteGLt2dnZUnzhnPCe4u129+EoPJ+Li4vx9OnTZWy85zgK1ThLjpdAxxlXnlvIwLLFsSdPnoxnz56NDz/8cDlrH/dqqtyPZ2HVeGN8a6uffvrpePLkyXj+/Pl48uTJYm93795dXuPz4MGD5ax2/EmAl9XjQ6lCLtQF3r+L9h7jMWFROsbr7wUOXtXllZ1jnbYKP6nCh/sofMbkYmWWaxy+6hLLU8nIVOWbKl92MIiLx0pWFf+Vb6ltNQ8no8M9jp9bHyXjGGMnrvNJHt7u4OdMhi4OVserGgL7VfhW5eKKsjYzdhy0V6GaCaQA6Ux/PM6KVAHDGYsb3zlX7FOJZa38KhiyQbsg6+Sv9qk5ROJYGzx/38S67wBctrkOKF8rm9pGmk0uLoE43mvJBWsVsLr+zcewjfsg8b2dAbhQBiVLN9EGb770smsXrn2VTBQpsOCSPsquEqOST8n2JigDetvt9rWH2agCzyVYB9JCV/GgmDG+e8hPnCnjtYqCJvSH4DoKBLy/Mc6Moa7DFuMhPXwZrPr3Oi6vdffq4aXB2+12nJ+fLw+iOTs7G2OM8eLFi+XMLz/gJvTHD1TBteBjwSfOUPJ7NVFPcbYvxvz3f//38emnn46PPvpoeRpsXFKKr1yJMfGS0ZALb43BM9ahg1evXo1PP/10fPbZZ+Odd94ZDx482LlP9OTkZBl7u93unLHHNYhtvHcUHyoVa4BnU1Ee1F/oImz6/fffHw8ePFhekRP0m9/8Zvz6178e77zzzs7lxGGf5+fny7tFY73Rl6NwxLl8/fXX43//7/89zs/Plz8q4qFKv/rVr8bp6el49uzZcslwzC/OagfPeFduzBVfdxN6infq8tzxrHHsx208u49+jn26GKoLgrMitMJR6Is8rsILuI//9HF5hnnicSaHU1zRxX0yUjm304fbMT4eQ8cWNS9FnDNc3M+KqA5OYVtRfTMsw/xRHvyjH+N5JpPD9Qq7VAWkmks2tqLMhmbW803T3oUqH6sAV5ArBCvwhcBjhiqnrgJOFtTWULXgqqDNQPkMSO6MN0sqICjA2JHDzRn7dZyz41TZfF2y4/5ZYMdgtsbJ1drOJjVOCpmPqvEz28j80PFlnQUA4GKV9yldK1tRccPNK/P7IJVU3ZwQBHFhonRT2Qbrv7JX5uUSNcvs5u/m4IBdrBe+noXvE8XL85QulA5wXLy/DkETAv0gvMcwiM/+jLH7dFNsxzrA94Hi/bDYP4A6gnS+F5bjStzLiTrD8Xi9Qt982XS04yf94nywQEc+m81mp1BhfXz00Ufjww8/XM7GxT2ucSlu3O/JcnIRjzaAugt5Hzx4MD788MNx586dHZ6Xl5fjxYsX4+XLl8slwXwPZYzLxSf7MOoq5FOXieLv7Xa7XFYbl/DG2dBXr16Nly9fLgVlyBFF6o9+9KPx+eefj08++WQ5Qx7zQjlwPW7dujXefffd8Td/8zfLGdXf/OY3y1zj0uCvvvpqvHz5cvzyl79c5nh0dDR+97vfje32u4dA4f3VeO8zrn/IEDKyTLh+uI1PEUa7UbcWubzqQLxq49YS5US/VX/Qu7PYPJ6Kbzgeb3eIY6+K0RgvXIxUsuM8HTZR2xxbFF7jPId9Kt5Kfkcux6IMGb8sR7t+mY4yW8X7vt36VPN2dp3l7opPZyzHr4MflZ1U8s22CZp+mNKhBQhyBs6/2bEdAOyC+ExeNecKtFZgSwFUF3Qr6gTHjHcWoJWMnbFZLw70z8iryMnU7Rvt1fhK7llC2+FvJQv+rnwNbShL3MgvkzPbnyWMDs22ZXkzu+sGWvUbx1O8OOZk8cQlcQQ3amw1losHlV5Yzo79MlhCvmqOjif6egB3BWaiDX8UYOR7wfA4nkHDIuf27dvj9PR054xZXG6LZ/WQJ77LM1vjMcby2hTsG3PGJwTj+z4Z5LAeguLsFuoOC4L4zWd0lJ6YR4wX+/iPg+12uzwQKV6JEhTF39HR0XjvvffGH/3RH70mTxSrcS+pe+pwbMflw8EH/+w6OjoaDx8+HN///veX1/Hgg5PigVTxgCZlPzHHuIQYdY82x3aPD3LiYir6HB0djbfffnucnJzs/BkT71CNwjmObTbfXnL8wQcfjFevXo1PPvlk508E1EF849j37t0bP/zhD8c333wznjx5Mr788sulTdjYq1evxtOnT3fuCY37fsO2wsbjMmS0V7QVtDlcM9Qzryn+ucLH2Pd5nZRvuN/sn9lx1iPLxfLN5HsVr5XMMznUPSuE23M85DiieDv9z5CK51nOPAR+Yj4qzyJ1c342xgyhPjGOZpRhzox/po9u7ZDhXm7T3V/xq6jbd/phSvEdAY2T4awQmXE5QNrhqwwGDYr3O6NXgaAi50h4HL/VPUduTBX43Rx4vNjOAkqm/yowKP4MzBAcOb7VGDxON1HMrKPSM/6LrJIuj8t2oHTPvHnbrUGls85cHaDIEl0VHBEoqP6d9cR9DHqV/E5edX+k6j9LCmTwmsd+/Hbjcgx1/smg0snj5FVFjYsl6KtKZuyP/OIsUwD5KGACsON9edEPgXsUoHGfKZ8RY33F9u3bt8d/+2//bafQwLlg+7jE8ejoaPzP//k/x2effbZTDKlLzjebzfjggw/Gf//v/33nUtJog/eo/p//83/Gz372sx094VlBLAZwLq4QiN8dQI22z3xi3NAz09/8zd9IGaNvXN4bBdJ2ux1fffXV+PLLL5dx8InBIQ+D63hPKL/aJcaMQgt1+uLFi/Hs2bPlkuV4QBPaTKxHzPEHP/jB+PDDD3fkQF2H3aB//O53vxt///d/v7THM8RxSW088CiKt4uLi/H48eOlqP7iiy/G1dXVeO+99xbZ3nrrreU1MrguUXgfHx+P8/Pz8W//9m/jww8/HA8fPlzkun379njnnXfGo0ePxg9+8IOl6Hzx4sXyTtnf/OY345NPPtmZa9yzGk8Hjt9sayEjPqk31p6fcs12htuY111Ojt8ZFlN8XRxifUZbvjSfbZCJ/7hQVMXATCeKF2Ih7BPb6oyqk0fFi25+c1iVZQuZmPiS+S7ecvgRKe4dd7jX8eO4j3pUuMxR1kbJwXGVdatyMPPL1lxRVTNVtqF0W+FLZfMsQ2cOXRudKlQr5ixgB/Di7yzBMX8ni1MeHp91YjVeNUbHEThQjbF7uUeXKodXAS0LcpXxOcqCs3IW15cpA/YzMip9z1AGFBk4Ox1WsmcAdU3gquRX9qzGcmADj3FSc3LhQ2wcb97fTRSzvqPkRZ1XBWEHnHQKDCW7WxuWqfItJ68bvwM0cI0YUHEy5nsEA+Djn3NqP4613b7+/jjWcRRSeHmuWzMEMrzWIQPPa7PZ7JxRRZCM7eK+P2U7qvCeoSo+uDXM4nHIE4VMFKo8d5Y9Lj1V7+F0hPdHRqGK+sLLd0O/V1dX45tvvhm/+93vxosXL3Yu745LkBVwivuDu/oMWXDuaLN37txZHiSF/eK+2hcvXowxxvjiiy/GrVu3xvvvv78j0+np6Xjw4MF4+vTpciY/5Bzj2/ufP//88+Upunfv3n3tz1G85Dn+XDk9PV2+49Lox48fL2OzDhzWYjviQsXFQhX/3TEcT+FARxxbO0Ba8eA58fzV/JBnlQ9mqROPcfxO3xm9zsrk5OP+a+JbpV+VVzNZKlyBMVLhGcen2u/addpX80DdZnpW8Z2PVTa1jw11+s3wbBeqLgG6yarEhQbiwJYKaKqdky8jldBdfxw7uwbdjdM1Tk4E8VH/eLO8M6AT9yujrXg7J1akziCpArySQ1ElrwpCSJX8LsgrPt2kpfyDQaACxYckZY8umHEwdPPIxkH+PE72ryOChgxIIKHfuLnxeA6wuD5qjlki7ayfSx5Zexc31e9MdubJvLl9lvR5raKA4Qe2xINkohiKoiWKA7y0E4sBfHVJyIyvlNlutzv3osaDbDabzc4Da+J4nNnCS2Ajtofs+LqSmF+cUYs+eOkmXkqJY6G+ttvvioYYK1sztnkHllVOzvxB2Sie4eX7WrE9nj2J9cIzrBw3ONbhw4+iza1bt5Y1xrN68bm6uhq/+93vxj//8z8v/e/du7dcbov8+V2jSNgOH2jEx8KGxvj2SdJRVN+/f395um6s3xjfPpn35z//+cLnN7/5zdhsNuMv/uIvFju6vr4ed+/eHR999NH4t3/7t0X2k5OTcXJyMs7Pz8eLFy/Gr3/96zHGt74Sr+iJs8Uhd4wTrwm6d+/eePTo0bi6uhqffPLJ+OKLL8bz58+XJ/3GnyuoU7w6A31B2QpeRsu6YptCcvE6+CmcoK5m4L5MjEVdfK+AOe5TvqfkcZjW8eYxuJ0aJ8PSSg7GuVVO6Kwn81Xzie8MP6o+TgbVL6sTMDY5vKBiJY+jsIeSrUvKlrI6Ro2n5HG1DI9RYSHF28nE8rg58PYarI/ULlSrwmmMfNLKsDjAxLbiyzw7wK6S1Y2lwJfr4xbCgQpFynCrM6td+dQYFSjF+SgH6571ZbnWGO1McHBjZAmhokyn+1An2Kzh6RKK00EnkWX2lSUDtb9j053gmRGPU+kBfyu9qSTWSbKOsuTi5uP2ZwlE9eMHGMW2ir8V0MK+8cH7Q7fb3fshsX08DAbvq+OHteA6YtGIZ2Lxnljkgw+0icID793EYvro6Gi8ePFiORZnZfG1IsE3Xp8SPJXdhGxRPN++ffu1e2TxQT8OFFZroCjzL9Sf4ssFOMoYxA83+uCDD8bbb789xvj2CbWfffbZjj/E/ZoxPhbqsQ8fjIV/Cv/2t78djx8/Hp9++ul4/vz5siZjjOXybnzlzGaz+95T1HP8jrWJAhXP5obNxH3NeEns8fHxePTo0Xj06NF49erVzrty49JafBDR5eXlePr06fIam+Pj43Hv3r3x8OHDcXJyMl6+fLn8GRMge4xvz65++eWX48mTJ+Nf//Vfx6NHj8af/dmf7bwzNuwT5xCfd999dxwfH4/nz5+PL774Yjx79mwpTi8uLl6z3dBR+K2LdSHjTJ7q5PmwA3WbRhXHVS5CGw++6n5V5KdyjbvPeyZuZ+Nw/24xofpjH5yny+9ZznC40mHibL7dXOLm4vY5Xbh5sa10bRivDMp0vgZXZm0dduOHhLm+2brzB++Nz+yyg/vc/DoYs6LpM6qZMeC+2QRbkQPaCpRnwBEX2R3PnDIzSlwQZUwKlCCfGcCrgqsDPCr4uyBfzZHnyfLgb7WPZcmCpmvDxzM53RpXxLK6xOjG7pKz3xkbcP3Udtcv9+mrKLMXFUC7MYTXv7JNx7Orf9ZFZcOODxc2ak4ZdfwtI2crs/ah4hDy5yIy2uJxPsNSxVV3xcbLly+XYgPvN42zuni2LQrVGFs9AAjliIckff311zuXrqJMMa+4r49BLuqpspGuD2S2UoFJPv78+fPlrDeeeQtdxPbdu3eXce/cuTNOTk7Go0ePxsXFxfjss89ekw31EPcfxz3I8YCqWCd8kNGrV6/Gs2fPxqeffrqMjwAL+6CNhT1cXFwsZ0RxPTabzfIHSZyxHOPbIjzkig/O/86dO+POnTuvnZG8devWUqyHLZ2enr52aXg8RIqLRfzjd7PZLGdX4x7UBw8ejDt37iwF6u3bt5ezumGHKOPV1dV4+PDhePr06Xj+/PnOGVOV/x0mqGypm5txO/p0cImTB2NOFn8r/8liWIar1BwVXsh445zVXFWszMbnAoU/VX7L8onKybNYQOEnJY/DrE7ObLxO+07sVbz2wZZI3QLQzUf5UHZSEXMV5l8ugjleOvtWc8B9nTXv0Kp7VMeYBzYzBU8XqCkg0CHnpNmNzng8SD34SAFnHGeNnMyjGwQjkSFVCakil9Qy3SG45ADK81N9Z+TtJDcnpxt7VoYZ2WZ8oErAKqmxbTvKgq4D1Wt0grbACbBaG5e8VDGg5O3yXzPHzjjIiy+ni/aZTzgwwfrjMV0swg8mL9cvS0gI3GN/nOnabr8tDu/cuTNevHixXObJxWK0i6JQzR8vB8Uke3l5Of72b/92fP311zv3/8Ulnsgvioa4py/uc4y5xH2XLMPHH388/u7v/m5ph2eDo+BBPzs9PV3mFXqI9nF5bRU3WaduHVRf3o58gO9GDd0fHR2Nf/zHfxy//e1vF51FsRf9Pvjgg/H++++PH/3oR8s7WENvH3744bi6uhq//e1vlzPJp6enS4GF84yHTV1dXY1Hjx6Nv/qrvxoPHz4cZ2dnO5dQP3z4cIwxxr/+678ueoizgnfv3l3WPs5aos5ivX7605/uPPgI7XWMb/0wzni/fPlyjDHG2dnZ4g9R+L169WqcnZ2Ne/fuLWsaY3/44Yfjo48+Wi7nvXPnzo7/xLi3b98eb7311vIHBxZtITteGn16ejqePn06fvrTn+7IE2P/5V/+5XjnnXcWXlGovvXWW+NP//RPx9dffz0+//zzJa6gjsK2VcxDQn05/89yqYs/uB5ZXKlI5Ty+jQafiYC+pHzPxVEeT/FzfCqeFf5RMR6LEvzGQoUvhWV+8RsfCqfGm5kLzmdGr2wnDgNxmy5fh7MUD4dFDoEB15CSAdcbdYKFJc4BcyUXqjgG2rHSV4e6eWpGn6sK1QpUKsUqw3PA0wGuKoDMkAJ98d3lpYKkW+RKjln5mZR+MrDr9M3ycHsFplEPHGSUjtSYmW1kxLamAo6a3wzx3JR8ruBwbRR15XRrg2PPzBn5ccJy/bPikGXpyKBkcWNmfTN7cPwPkYAyH1JUxTMlm7PtTsJmuSoAEr8ZGLBMDPzxzGQkTZUgsZiM8fiMD+sR70NVAOTVq1fLeywjkcdTh/HJsiHH1dXVUjQrO0XeUUDj5ZOoQ5xrtHV/DsUYPH8VN6o4mfHn36FjLJrx4UFRoONl08jryZMniy4fPnw4/viP/3jRA17ejE/zxfdx4vixRq9evRq//vWvl3HigU7b7Xacnp6O+/fvjw8++GA8e/ZsPH/+fBwfH+/oHy9bxbniH7R46TEDtDF2n1SMfK6vv30/6u3bt8eDBw+WPyPijPx2u1sEhWxxL3XoEc9M3759ezx8+HC5AiDk+PM///OlX+joyy+/HM+fPx9ff/31svZRYG632/Hb3/52fPPNN+OLL74Y3/ve98YHH3yw2F1c0sxXKeD8O0CSAf5srHQxydm1whAZn84Y6kxyJ26qmKd04Xw2i/EZXqjiM84l/tRwhSrKgZ/qMlKll06OUXqYIdadw5pIXezL42A+ynLfm6LMbh3+4UI19qv+OEfMv7z2EZ9xDOUvjlx86BS6XR1PvUc1vtmBVFtlTFWl7YxNBa5qvBlSwaALZHGxVb8sEHTG7AS7Luh14/N+t6Y4pupbFavYTxVTVeDPqFOkZvwqm3RzU/27CUpRdeazorXBIbMH3l/ZW5ao3fw7Nsw2VfWr5uT4dpKcGntWfid7HFPHVRyuAITr42TO/Br34TeeteL+eNYz+EcBifcPIqDEojKOR7GJxRU/MRgfyhPvkoxEHAVkFMlxbIyxc8+eAoJRiKGMWLCwjqPwC9m6QDSzPQYPCkSobd6HxTk+ERYBTVCs661bt8azZ8/GkydPxr//+7+PP/qjPxp/8Rd/sZyVjQdYjfEdQH758uWi61izWPcxvi1KLy4uxi9/+ctxdnY2Tk5OlrOR2+12nJ2djaOjo/H9739/fPLJJ8vradhm8OFP8Y33lqpXIuGZ5Hj/6f3798cYY+ds/dXV1bhz58549OjRTqEa7fAPmuCHZ8sRHIYdvfvuu+PWrVvj448/XuT58Y9/PB48eDC22+3yh8svfvGL8dlnn40vv/xy8Qc8+/Xxxx+PMb49c31ycrK84zbWdbvd7jwVGX0p5l/dd6ryydpiVcVvblPtU3Ipm8fYyXGGx0A/ZP/KgDcf5zmiHDP5NX4rLIAxAF/NpC7RR5lxnnypucvTWV5Zg7c7uAHbMOZyushiniu2UBc8T2WvvKZrMKpqi3JWvFTOU325AI84wDEg+inbUbVF1xacj6OM2boqmi5UlZAZ2NqXOsVLd7IVSObL12aMDxeX/53gcVBuB0aV07o5ZMGGaQbUKl4KzFV6UkBtH+rYWxVk18qA69IBlbMOiePgN/LtfLOsLJeSl8fuyMi8cdsBFHU5OtoUXgqqxlR0iFgTfDoxZ4zXz1asJWer3dg3G6fi2+lZATVOjrzNZ1JjneO+ugD3Z2dnO+/GwzOP/K5RTJ740KQoLPDS1SiGjo+Pd4ohXKNI2EqXWHRGH3yo0IsXL8bFxcUC+q+ursbJyckiV/SN3/GAHbRpzDEshwJMbk1wPdi3KoAZ8+NP/Alw+/btRTbkEXqOy3jjSbSxFihDXBJ99+7dnbOLm81m0dnV1dV4/vz5op+PP/54PH78ePzkJz9ZXgETReg777wznj17Nr788sudPzzi8lgE9DH/ODOMdoNnivHy55jXs2fPlgIg7O7i4mKcnZ2N733ve6/N5fj4eLx8+XJsNpvl3tXr6+tlXvinSuj98vJynJ2djfPz8x27efr06Tg+Pl7mHpdax5N88aFkYftxz+wHH3ww7t27tzwxe7PZLPexnpyc7DwcKnSETw9WuYwB/iyeq9qyPWOumImFikLX4WsYY1R/VxBmc3F51MnL88MPH894YTHh/mRwhZ4ryNR4Kq5Uc+VtHkMVPYwRVAyrcHv0786vo/NDU4UBs2MY85Xd4TzUpb34rbAg25XClNkaOFniW9m76+9oVaGaDdYpWvDbGXJF2Nb1U8FXUbf4qHjzIneCq3JQPNYdv7OvW7jNOK6yBVcgZf26/KtxO7SmsOjorhvMu/y65OysI1tH9i45f+z4Kh5bowPmU8nDx1VwVm1ngEW1r5oj60LFTCVHN6nMgsksnrGuMZZiUZXF+6Ojo51igvsyIFJ2wuCa/3zkecRHnQlGCjAbRVYGigIY8PuC8fgM+OO+VT5R28gXH76jZOFnL8Q2Pszn3r17MnbE3HE/8sK2UUzg/aHn5+fLGCFL3Ot6dnY2nj171ppj7Oc/KjLd4VlG5BUFJL+OKC7P3W634+7du0sxGX+03Lr17Wt0Tk5Ods5cRwGJr4S5uLjYOdMd93Tfu3dvPHjwYJyfn4+Li4ulMB5jjPv374/79++Pd999d7l3leeCT+FG/at8pHCQA5hK59k6uOPduLgGox0yl7jfPF6XTxXDuR/jSzc2xjz28e5aqvEzvXNcrvjNYl03tiuK8LizpUrG7HeHB/djn5qhrs2pS3vdurs5dXyr67e8LijDrC72PqPKlAGIrhJmF3LWaBzhpUFd/jwvDChqzioBqNPx2aLzeDPB+/dBnQQ1xn4FsQK8Xftycjl5XGBVa8zBaQ1xcqhAxix15ZpNap3xsmQ8Mx4ncN6HY3VsYybZuiKlWyByv2zeM0WikscVaGO8XkCqeay1NfVP7tXV1bi4uFgu4YyzXmN8W6SenJwsZ+iiiDk9PV3uO8WH0MSlpqhDfE1J7IuCIF4rw5c5RUH08uXL5VK60Bve1xpFWrxa5Pr6uwcNYRHb1QsTxxK1plzk8fH4zgBaFECnp6eL/kIPMW91f+cYY7z99tvj0aNH4wc/+MG4d+/euL6+XvrFGULUfxRXITsC6NiOdT8/Px/Pnz8fT58+Xc5ExmW09+7dG+++++64uLgYv/jFL5ZX5OBlxzG/WK/T09Nx69atpfBFWxnjuwdh4RnxmAteHh6y3LlzZ8dfvvnmm/Hll1+Of/7nf15sJ/rcvXt3bLffnln+0Y9+NN5///3xwQcfLGf8Hzx4MK6ursaLFy/GGGO5CiD8Ic7Cnp6ejg8++GCcnZ0tr6z55S9/udwH+6Mf/Wi8++67yytpYv/V1dV4+vTp4jPoN5n9oN3wtvpWMUlhIUVZzK7+NOqSwqCH4Mv83TgVDsL9CtdxP9ZnrBG3DR9UMUWts5Kd54EydnIK6wjHV9vq2+nJtXE4o8LvGVX59veFu6tCnf1G5QCFlRwvbIN20Jkv532Vk2b11i5UZy6P4GLVFWvqGDpDlnSxvaLM4XDczKAd8M2UjPdDZHOM784idoGoIgXSO86ZyeOukVeFQVYsdI11zRy7/KsiIrar4B0AZ0b2bhCsCgeVQLI5dGRwvtDpr/hl/WZkw/1ZsYrbrFMHuBTN/jvJ9qHk6iRsZ8+ZzNn6q7583MXETD88D7bDSFpjjKW4uHv37vjJT37y2iWb+MAdBFn/9m//tpy5CopEiOP9+Mc/XgpSlt3F+Vu3bo0XL16Mf/qnf9qZA96LGO222+3y4J0oJqLIiTNX+NRazpm8BnzmTtkIxx78KNCm9nF8isIf8+zFxcX4sz/7s+WBPMonz87OxtnZ2bh79+7OU46vr6/Hs2fPlvd6BkWRGoUkX64da40PCPrlL385vve974179+699tqVhw8fLn9wxDpFAbrdbne2Ly8vx6NHj8ZPfvKTZa0QwOM6qXjwi1/8YnzzzTfjnXfeGW+//fZyyXLI/fXXX49f/epXyxzxCdGhh+12Oz799NNxfn4+3n///WVfFJQffPDBePr06Xjx4sX4+c9/Pt57773x13/918sly3hP7Onp6Xj33Xd3nvIbZ1LxYVKhzydPnoyXL1/u/FHAc8Rv/JMGbUk9cAbtz4HYKi+oOKb4d/lV4yjqyMixPPO5im+GI6siwGFhl2fC3xVGq/CU0j/KocZWOVjlI5dHMx2yLJiTnXzYPyue3bwUVq364bgOB7icVJHDLApH4Jh8G8sYu/pQfRweYT9XfbL7qpHXrD+vfuovC6IATSZMF/yo8ToLzAbRGc/xdqAxG7OS04HeIAQLjqczepatA1h5jGotXWHA4JENX/XLKNOzC/iK3Fq4YOKIx3b9XFJbm3Cd/p2PoLzx3Q2MFc9MLuZRjTHLl4+rwOn6uyTCcrGPVUnVxZoO+OBt5Ss8TseGKhmDnM5mkii2V5d9YqE6xrcFz49//OPXABE/xGe7/fYs6VdffTUeP3688/AjntMYY/zJn/zJ2Gw2O+8BjbOiJycnO/f4hYzb7bdnx/7lX/5FPrE41j3i8cXFxc6Dg0KGSP7xypY4K8fHkTeDKbW2bHf8UJgKOPMYMQcGftfX1+MHP/jBTjGGZ7HR9rjgu7y8HE+fPl0u3w2AFPeS4tlG9bTn0NkYY3zyySfj9u3b44c//OFyhnOz+fbe1rfeems5o42vFMKiE+/lfOutt8aPf/zjnbXhtQidbjbfvVt1u/22wHzy5Ml48ODBuHfv3s5Z2+3223tKf/e73+08WAmfDL3ZfFtEf/XVV8vZZlybeKhSnP38+OOPx8XFxfjLv/zLpbCOM7AnJyfj7t27Y4wxvv/97+/onmNCvErnyZMn4/z8fFkDto3og0+IVbaF/qt8z+V0Z4MdLLcGI3QxYcYj66fGUDmhyvtqbu5KjCo/BJ8sFzpddjBvR18u/6q5qI8b3+XULp7BWKmwUydeMj8lq8OgzmYyOSrKMB4fQxlYtirPO1vHbTVH5w/ItzMfRasK1c5idooHd9wVN5mROmN34820V/0z58yCQOaczK9zKRn2cUbD46sAMEPIezapHIJiLPXQKnbCKqBFu9+n/Gr87DvzJRV0eM78u7LZjLKgp/ji2ZOZwLSGsiKGqaMDJ7NaAwUMZmzK+ZH6V1yNh7Kqs8COlM25ginGy3QS6x2FIT5x9NWrVwuYj31cHMYljHFWih+wFAVUyIjvncRCLH5HIRFFyBhj50wdPniJ56uKzjjLFWOP8d27WhEcoYy8Pi7+4jj4GhbUQSe3sJ3g2oSMoZvQC55Rw4cs4T2OUdjgQ62iYPrHf/zH8fTp050HYcWrZrA4vXPnzqLDOAvJ70B9+vTp+PWvfz2+//3vL/d43r17d5yeno4/+ZM/GV9++eX41a9+9ZrtxHxw3VDemE+sEf6REf3DJvEs5ltvvbXoIM4eX11d7VwurR7eFYXz1dXVYs/xJOLj4+Pxve99bzx79mx89tlnY7PZjJcvX45f/OIX4/333x9vv/32su5oz/EwK7QnLDCfPn06Pv300/H3f//3qb2gn/OfOphf8WneFWWxRuWf4MvxpjoDpuKqy4MZD4VTXdxWvqtip8s7HF+zOKvkxss6Vc4NXtUDlpTcrJfsWJaDHPaKj7OhTsHWwQ+MCzs1As9Fjau+VTuO626N15LDfoyv0A6draDcal68JpVfZHwyWbvULlQ7ymYwwwuGxxxPbK+cvtpXgTLHV8lRkQOXPKb6XRUOHd4d+ZQ+eJ2UUbKMLnBlOu3qGsfMxuP2WdAMHm6O2dgouzteyYY8MlvmbQ44Sm7FrwMQ1hzncVVix9/Mu0oAa0npJgM0Dpi4vuwj3F6N43w2s7ssDmRggOdfJVKmLC7M9OHjCH5DXi4kswQYgCb2YdHE83Vxn/k7u4j+fK8unmUK+fC1NyGji3nZb5SP58Pz5jYdQMXjOqAQYyi7UmMh2MQz048fPx6PHz8eT5482XkqMhMWh2qMmG/cT/zVV18tl7biPcBvvfXWzqW/YWt4fyxfChtjIYiPs5H8ep7oHxRP4cW5RzGcXYIY8sSxly9fLmdHQ5Y7d+4sZ0/H+PbPlM8++2xcX3/7lOm49xTPaqsrFkKei4uL8emnn44vvvhinJ+f7/gc2wXKicdcLu3iv8zeuZ2Ta01u6OQahQ1meCm/ZcqwXFXkhI9xjHTAnvGPWjvHx/F0OHANDlWxaxZTdfN753clqxtnhhTem8mrFcao+s/SmnV14zt7OsQY04WqAmEqEOF+dqQKQKpjmJg40M0A1s4cFY9On4pmweQsrQGrhzAiRVWR1klo3XEcvxjbPSTrkOQSRRa0nN/gMfxWRcqbWj+cQ7Zd7VPJqVNkdigr0lzwz8AYy67kdn2y+JiRKyi4TRZ31bzdsQrwOBncfPh3FCp4VgtfUfP8+fPlzE2cXYo+FxcXy2WpZ2dn4/r6ermfEs+e4SWe8ToVPJOnnjLM9oYP0IkzY3FWKX6fnJwsPPB9oHHpKa7LvuA6CqDT09Ox2WyWBzZtNt9daouXn2ZnJ5SNs17iElEs1KKIxNezoK5ijpeXl+Py8nKcn5+P//W//tf41a9+Ncb49szo6enpePXq1Wtn/eIMe5yNRP0Gz1jHb775Zpyfny9nVHE+77777o7u4iz0xcXFePHixbhz587OQ7nwNUJoE3Ev84MHD3baxgO8Yt5xf2qceY4n756fn4/z8/MdOfCy6VjPKHIfP348Tk9PxzvvvLOcxQ9ZQ7YXL16MX/ziF+Pjjz8ep6en4z/+x/843nnnnfHhhx/uvNs1/CnGeP78+fKHwc9+9rOlKA55+BLh+IS+Y73xbHPYTedM6j4U64/+lOE3VeBWQNmRwyBZIZrFUBWnuY2Ln1ykdvIG2p2bj+M9o6tqTRiP8Po4HOawjZLdyaW+s7lkfKo2mW10cVinaJ3l1bEX5M211Bj6j43MD9bSWn6bbbMn3sSvBlbBovNvXebcncKrAqmK1JjdQoLnUgWnDETy2GpfFXxcPycD/64KkKpfBfp5ztwv03uWJLm/uuSl8xQ0Ja8rAlS/SBYI7Lr2nAWYLBkqGbrFipIP12CmaHF9eDtLznzcJVBns6ptRtX8XHzL2mTUTSLB18UTBmRrwVk2ttp2fDPbwuLr1q1b44//+I9fu4QwLmGMT+yLgjCKxTHG+O1vfzuePHmyc/bpww8/HGdnZzv+yg9jcvOL3/iApI8//niMMZZLUs/OzsYf//Ef7/R5/vz5+Oyzz5aime+FHWP3oRUdCrnefvvt8c477+zo4osvvhhfffXVIhe+IxaLIsXTFazb7bdF94cffjjefvvtnaff4j210T6O4+XNeAbz8ePHy9NrOT+OMcbDhw/HO++8sxPTHz9+vFwmHDrDWB3833///XF2drazXlEgf/bZZzs2eO/evfFHf/RHO5dOsy3E/Lfb7c69pQH2Q57NZjO+/vrr8erVq/HgwYNx+/btnacMn5+fL4UhXv6LusF8cOvWrfHw4cNxcnKy6DHG+eqrr8bXX38tsUX0uXPnzs59uHEc1yuK9dBL9Nlud98Zi2enQ3fX19fj9PR0fP/7319s6NatW+P58+fj448/Louvbtx3+ysM0YnV+2A+99vtc7J1cJD6PVtwoI10HmzJn0wGRbPY2rXt5H3ug3FBjdHByR2q8H+Vc50sa7CK65Ph1e7+4DMj14w9V7hVUeS4jNqFavyTmS2oMjIWGL95P9MawFXJ1TGmjmNigVIt5CyYzGScKUJmDNu1d3J3AzSOyX0y3UUCzYjv31PrOBNgVHDnfqxfThqdws6tYUf/3WSdya/AhVrXah7xPRugUb5qbXguTJ0g6igDWbP71Pjd+aEs1XgKdFT2s49dVTblElMA/yg6oy3eaxevq4mHz5ydnY2Li4vlFR1x1jXO0J2cnOzwGWPsPCyG71FFfYadbjab5V5FLIzHGMu9gy9evFgAfswlCuso3Dab7+7DDZmjQEJ/6hDGj7iX8e7du8slnSjDq1evxuXl5Y4u1Lrh/HFtQ96zs7NxfHw8nj9/vvDHQib6xH2kcQkuxuRYW7xn99WrVztnCWO9Q298qesYu0VwPHjp/Px8KSaxMA89x72nURQeHx+Pu3fvjhcvXozLy8ulwI08En1inDhjH69Kwnf4Xl9fj7Ozs3Hr1q3ldTnx2pfoH2cjYxx8onHMA4vb0C/fwxtnc3HdYl5cTKKN45zwoVPPnz9fXukTr7uJd97GWNEv+kTBi/oJ3aO8M0Wkwj/sF1nOmSlG1JjRnvt2YmF3XD7efabImvzA4/KaZDiK84Uarxrf5QElW0VuzkpGl1+qMTsYHsndF63WyvE9VKHqqFMnYb5bu04O71Zt1Xgdv/v666/TMcaYKFTfe+89KWDHIKr9M8AyvjuLNsO/WyxXxZYDeBXfjizctzKKqlCdNaqqYMP9bv6dIBvts3uAkJ87k9kF1krurNCr5uKKRyWXkqGyJ0Vdu0d5+TIvx8/xdPbj5sLzqYIpjjMbcGdjitvuJEU3djY/BdJcXMvWtkoqyjeqtc7GrgBP8OdLIYMQ7AcFKL9z584CpgM04xkvPEsWZ5jwzCwCbixsxvjurF3IHPzwgTP48BilRyzottvdy8DwMlmll8pXULdReMWxKBawsM7sEG0K158Ln+vr7x5wFYVvrFEQ6hTXK3iEzcY6XF5eLu8wjbF4XiEf/skQPJFPFMHxpwe2V/F2s9ksfOLyXWyDlx7GE4q5WAzbij9K+J2Uyre329ffucu+jH8AoP6YcB/eD40yRFGsbDX+FIq1vbq6WoppvIQb7YJtbrv97jVMeAZ4BrO4+JThAvWttmeKEIUPOhitE5fVWBU/nsNsseL4z9BM8aTyzRp76GCiGf5dquwtqFOoZvyQZ5ZrO37i5lDhc9ax0mk2RoZz3bidMSrf+eabb9LjY+z5eholXBaY+PiMQWJAjT6d4OHokE6wRhalm2yMNVQFBPxG/bJjMC9nsDNJ5BD6Dz5Ktso2M3lYJ4qUDtg2ZxIq81ABLvOX7lxVYc3jqeIE969ZO/VHQMZzH99mynTBMcW1UzIpnSkg6+TJ1iCbgwOBars6hvuUrFWc4uPBC4s5JH6YDl6FEJe1IpBG4qe8oswMSFUhw0+DjIIE9yl+7APM3+kn8/9q7fBMVrTFgsXZFtu0eigT9sMzwMpmGaTjvPHBSaGvOCPoYrI6Q6fsBM8cKn2p/iGT0zkWiGwLUUCOMZazq/iHiXrQFfbHPzJQh+gPeD8hrwnOO/iGfvlKneDPl9OzvoIXvzOXYx7KwPcpY5/uGUMm9sWZvMy0JvdgPu7mZWWTWV9ur3BwViB3C7uZXJwVTlnxXeVop0vmwXNwYzteVe45FIbs8OQ1xPZVUefW1sXITDaWI7MbJZ8aY1aPqn9H7rXjjTFRqHZAslNA1sf9DsIF7ATKNQbvxldG4BbdGazio9qvoSrQVMdmDKYja8XPFXL7yBuJOgM9s1TxqgoL1+cQgXWfIMM2mSWrMfw9vi65ImDMwAHL7o5VPtSh2cDv+uEcXFJR81F8VMJWNlXFzSpJcZ+1cTAbw+kOH4CEcRtlOTo62nklyMuXLxed3LlzZwH+cfkkPoRJFRpxNmmM3TN0KCcWDldXV8uTV+OyTCyw1dNW47JhtAG+JFb5SgboIrfheKqgw2IHX7ej1sMBwxgvdI9nMPmZEviNhEVh9IuiKtYedRjtY5xY1ziLi+9rHeP1JwQrH0FdhV42m+9ebxQP5Qrdhv5j3eOMK9po2Fdc/n11dTXu3r27cwY/+rDvok3iVQMh16tXr5Z7XXGeaDshf/R1f6LgmOgj2+12557jWN84O4pXFXBBHfoOX4v7v/GydjzrzvYQxDHSAfcs9ma0Jo924l+V6xW/2K6AOufEGZndsTju7uHE8TiOdPIOxjwlUxYfKiyv8pbChIfCOh3q4GLWkdJjZ+wZnJzx6+ge5VN+UNnkoebCbWd9uH3p76NHj+zgFeBU1DFC5Uwdg3AKyUCeopmCY63RKtl4X8dxsnbd413g2+nfMavZ8SobYf13HKMjZycJKdus/CEL/GptM35V0GI98W+2NXxqZ5aIMyBbzSfGcaTWsWrLlMWZrn3z2nbGc5eAqnXI5OisgZNptr3bx/yUTmMeAeiRT+xD8M1gP0gVYnhGSZ3xYRtmuVhmtSZYIMTTaPGJqNEPx+b7Y1E+bJ+tXezns5FY/Gw23xV5sU8Vqtl68hyiwAlAimdr1S0B6Kd8WfZms9kphqJf8I5CNOaIYwY/fg0LEs47+OKDj3Dt8Yw8F/84Jyzo8L7omBfKFmPw2cooEGNcPKvKeo/7sGONUVe4JnzZcMgT88ezvfhAqOgTTyJGvrFOaON8OTGuM84ly6nK7lzRxDwq3DiLoTr5qeKjYry6dYLl7uRHlwe7sjG5sVVx2snHsQ/XBq9AqDCQko23qxNN3E/NzbWv9NutTWYLKEUVbunmZcZ2PN8MI2a4sCND9N1Hbyy38/cnT56UskyfUUVwgAI5UOCIlZA5cNfZmRfL6dqtPd6VcTYIIXXnsLZI7ci51nk7Ms2C5Q6/KvG59t1xK9Cr9rt9nXG7SYKTqUq8Tg/uuyqQ1PyzWNGdV4c6tuvsoTqGNCtnljAqf1YydmVwifwQII77VbGbwS+3R3COH1Wwsd2yfl1iVzmKZcZ7WFlulFGNzWAf+XZtxoE8LHpUOzxL6Hi5fUF8JtjFhziG64Ht2efxOBZ3UeDhHxf8jfy4EMOHK/HTfGMsfhAR88diGY/zQ6LQdtUluzi28zOlS/fHHPLke7vZN4LUk4vxCcrKfvFPBtYf6z+O8dULTDiGyjlqrtz3EAWC8m/ORY6yHNWRz8UXFWN5/h1SelWyoe272KRiDsZk9clkcrhDxc6MOrjN5R03NyWHkrMjX1euDB/O2FHlS4p3hdfcmJ39s/jV2egaWnWPqqIZwN9ttxZIvUl+nWC3hrdy6FnQ0+Ff6WBtwRvHZnky+FlLziEyvgps7CvDzH483pn/PnKqhKVkVIHOjdspAKsgiAlSHXfjI6jj+WVyuuDu5qOOZfOr+DFfDOYVddY/S4xrfDfG7VAUAkH4NF182JECttvtdjl+dHS0PMkULy+NfvHuVD7Lh2fB8EwkzwPnEw/sict/4/2iAdCx+MFxEMB3qPIJPOMY+gidYF+UQ42RERZdUZzFmuFThPFe4XgwEp7Vi/HPzs6W99yenZ0tPogPfIonAMeltDH2ZrMZ9+7dG2N898AmfnBRzAkfwKSKUeyHD6GKuSDFmdhoF5f74mWtvA4qT+AfHHjmFtcIt6+vv3v/aVxKi/6Ar2OKMWLe+McNXqrMlzTj+uLlxCH31dXVYu/R9ujoaNERzgVjBT5QazZPZ4ULF8Wqzcw43eNr5pARF/nZOJ1C3vXp4NfOPLNcj/uqM6lqjCpvd/NR9O8US28Su+3Da3au0a5bP3XG6Ra9Tp4Kc3C8dn8KOPm61C5Uq2KiU213C1TVt+OYWf9qnE6RwYaBgdYBTnT82SKxs6hVgYHbVSGN8ziEceHYHfvo8GF5ZmRT81dr0+U/s4YdPlWh4OTq/qGhCgTk4UAF2kVnHJ6Tsz0sWtbYWKU3JSuP7wLsGl/Edt2EoebvAA7LO1u0Mr/ZPp32fPYFi1cEuqrQUpdMxjwRCDpwhX2qS69ZfjwLpeI08lb33uJZQi4qlbwK0GU2wH6k2rh9MSbrfLPR91ZiwYfzxblEUa9ynnr4D152GmO7y7+xX/CPS4hDV+qyWeSjnpiL+uGHTCm/dfpF3qxT1ke0dePyGXOUBe/nZf2P8d16xX6+V5j/9IjxkWe0c/kEn2acEcc3/O22Wa8OpHdiMcuf4Q2WIfOpCrew3J2CYAbzdPqqHKbyLP5mYvt3a8HjdjAlbvPadDGr482Y1eFtJcta2mf9ZsjNA491cEC0y7APj5PhsmqNHIbE71lqF6oqION25dC8nbVT+6vgpAw+W2hHiqcyCgU0ZgqpCkTuu7DIK74V2IkxXBCZGT9b6zfl3F35KvtSvNT8M8d0fd1aZjLN2G5lS9FGBZ5uIs0CVzU2JzRXbK3xlaxdB3SqhFzNtZKnczxLAh2QtUaeTuKfkafqy+O6QjQI7zsNwndT8lku5MEPVHOxC+fPlxgrW8RCInjyw2Wc3XXipwIHSkfb7fa1M12OjzuOZ1JjH96DG7rG18LEQ4nw4TtROF5eXi4PL0I5+fd2u925/zPG5vtAmbDIxPE2m83OGXDUeRDOle+3DDm4YMNvFadiX1whwPdOcz81nzirjGuiCkrOAfwUXsUbH/QV9rLZbHYKXnyyMesYY2HoPOTFBzFllMXgIJc/VS7O8FhXBhyHc0JVaCmeqCuVP7Bdtq8bi7vYyWE73p7BAJ24wmNnODi+0V+qsZ1PqedoMO5y+qjy6JqaYV8s2hmDx3MYtTMmY0yMczxmxo8xJu5XOBiPdaldqLoXP2eFT0Vushk5A8v6KQVWlAXKitDBOgG3GxSYP++rZHUOH/rDm+eZhwJUHZmVEa8JAhV/Reqy0MrOMpCbyaiSbydp8G+XSA9Bzu6QMhCBxQDzZHlVrFBndDI5u+T0qgI424G7/4oD7GwymiEFTvlY1ndWJhefsvEzXY7x+tlQVQS4ooDHY7voXGLb0QOuOcuIbXA91NnE7J49LnC6sqkctQZEV+2cncf4UZCErzOwZFJP5sWijougDDBlc4vLs2Of+4MhZMCz3sqeOC+p+1Zd/sMHOc3iFe4Tunb+FR++J5cp5oT22imeOa/zOofOeX8Vu53d8LyUbOxDbyr+8npnGJFlyjBelhO32/7bKzrHVcxwcri++CeUmkcVpzGeulqAbdg9OK2LzRmz7msXa3Am22jWl3WzVl5lW66OyGyzWmPFC7+5nZKRn0/A1ImfQavfo5oFTWfYKKCjCtxXgV/JWB3rKgsTbncs7JMBatXOLW4mn5KnWiN0/Mrp3LE1gZV/HzIJMWjmsRhMogyzjtUJrh1eM7bVBa/VWs7Izva/VrYOdeV2hVXGU/kx2+GaOXDCqNqqmJDFP97fSdAKyDhfdMA/k2Emlq8lFyNm4jZuKz1kMdol8Wq9lb8ocnrP5qHG6fZx82Q5K9ldHOj4AfftrCWeAZ8ZR60/z8nldpyTkjlrr7bdbyXLzD3QSlYHYHk+PK5qo9bYxSqezyxm2CduzGCImbYZzoxvZZcOr1b242TIvp1svJ3xyfyReRwivmc41fkNF0AuF3bzMI81szZZDnb67fBU8VTFZTeOmoviw3OYiXEsH/Ni/vvg+1X3qO5roJXCqz5q/5siNi4H7tTj3meBK34fqgBwSSq+K2fv8FNyqYB3KODalW3GZqvAjL/X+sFsYhyjdzapM061tg7MZTyzwKv24z1pSp5KRgeiZijGyPzLJW4Xg7B/NxFlSdUVBx3f5Hnx00p5rOC7dsyMZtZoH1/qysjxGcftgLOuXDNzYZDg5FPb1ThVAafyb+UbKDfLgTakjs/KmsnWiWXVevN81JOU8biKP2tyPG4zXwUsD4G3WJfuYVz8JGiWtTOW2s7kibF5rbA94xOXOxwWcXIogO4owxeZjhQWiv4u57FNxCfDA9vt61fDzRZRyucUnyxOoTyzuNLNa4yxc8VfNr99cZkq0jqY6k1iTd7vaqfu3F38Ufyy2KnWoeuvMzRVqDph9xEgIzc5Vm4HjHVJJd01c+0mGRfYlaF0qeP0mYFyUFVJpeKP2xnPmUKnCrrYrpN48HgFFiraF+S6wFCtfzWuW2+XoF3CUtvqdyUj69V9r6UOnxgfganye+Q5G2i7tpqRWpusrStusvjF9rEPqMhAmuOjAJDju8ZWurabJdUuVWC16sf7Ml+sbMH9ViBjVkYXGzMgnsW3ah5ubDWXTpGqxkDe2dwdZSB/hjrzc8CayRVWrBMsBPBp2fHNMihysUe1c/Kovmw7Di9lPudyH+u0wg0st1sj/u3aVkUQjhn7+PabKk8p+avfbIPKvmZxKa5dF/u5/DR7VYXim42/JkfjtssrXRmqOMTxtxPDlLz4m/Gvom5+OxSWQ1pdqCJlANi1U6ScVzmiWuzZZO6IHTBzpk6y7pCbq0t8a+al+DtgwWN0ErzaVn2c3ip53T7Fs+K/li+27doIk9NrF2Bla5bJ4ZJYNbdMl7PJysmjfJrHUdsVOKlI3XOreDue+/h6B1h2KQPj2fwUCOgCHeab2Yiy2ehTzbVrI11Zq7g1u6YOPFfzcmBNgVuX3zrjBM+Or2a24uKr01u27hVVQGsmRqh9Ll9lMX8G/CHN2KrDMxW/Stb4zQ+VwoJru93KexU7eY7HcbLzcc5znTmpYorHZDtVa+qwVhc3ON90/dhnMnkc8ROssW/055zWXRMlRzcGuf7Mp9vPxfwsT3XjtopXSr7ZGFu1q3KNw2FunllMdzaJ67imPsN2Vds12Cijg71HdYz9hMuAggIpFTjIwBvzzPqoAMbOW4H9taRAC/PvBgynt+6T/LqAKOs/G9x5XZ1tOJ5VIGBSCX7WprvtXdLm7WosDtwqSc/KdQjb7fLoyNi1F7XdaduxyVk9VlSB6RlfzyiLl1ni3ydhOx11/KsT5/ehLhA9NO8MPFaX9x/CJ2fm7WwBj2frxHxwnblYUuMo3m67QxVIrGjW7tfyVv7RjXsqfqmC0F3y6wopftqz61vhLTzm9OT2r7V/ZSsV3ukWrLN4ppJTjcmFdtUf++A2zkk9NEwV+YpvZw7V706uj+8qjziea+ylW9y7HI3fLD/rsYsrs3Wv5jiLQ3lb8donP67BEUjTZ1Q7BlbxyNo7Z+2OocacWdCq4HH9XbDoyIfjzgQH1a4CdocEfrPFQVbcd8j164L5NQCiI6+z4Wr9nG1WPoH7smIj85sM1HRk5zHW9J+1h33+LHFtZ2Q4RKHUkceNpfZ1YlVmF8pusrV04znZlC+oIlzJxXzXJF8lq6NKvx1/7uS/jq9U8WZfcOzGU6BvDeh0QBNlZ912x5nR8YzMig/bb4Z/Orpj/tn4Mzgk68+FZDYGy8bvF1axYqZI5bl09NPRuePrYhyPsQ9+6MSIiv+M7TiZlL0wH97u6Dnjr3g6Xl37zdaMZXF2OTuXzvFD4Q+FOSpsy386VHGuS908MpOPO38UzOauvc+oZgmJqUrIGWhypIIw7usEDh63m4idzLz4zujRSNkQlZxqn9Npx9nXAr9Z58jazxq0c+iOc3TGYR7VP5BMs2ACt2dAeZWIZ8Hdvvpjftnv2Lfdvv6P/dq17Sb2TK59+q9JEG7/bOFSxRfFg33Q+eQ+dlHF8qxIzWJXpQtVXPBYswVEpoOO7amclMVvJ6eLRfsAbVVkrS2weCyVW6uiqQt8lTwVmD7kuruiiI935a2KmIxcDFC2pnyEtyMuuyctV2Nn+4NmYqbygyr3VWNkcU7hQhcnWbfZOI4yDDlbtDn+m81m55VF6ntWdl6D7j3Ns+Mg8bMllB8eCstkVNUuIZ+ShS+zj7aZfykbzeSpZOZ4W8UfFecqLH+odWgXqs4AO0B4DF9wzAJMVdQxCKgAQGy738r4Z+bGY6p74VhGBabiN74PNJsT/q7AhwtQnYDFesrW0IH5TnCdMfKYr7uMzjkxyq+CQFc/FVWJQb27Vv1WYK47PgekLshzVCWEGRCm1gD7Ol7d5DRrSx0enfkxX+WLnWRV8VUgi8kBVP6t7GPWNjI5q8T4JsjFKZZFFX+8XxHz7oDGNXz5mJITv1V791vxyAoalWdVTq3W2/l316ez2NABk6qvy1v4e00MdnKrcWfHcvmP33HM4zh5Ql/Ktlmm7vEK5HJ+ywC34ulI2WwnvsXcVZ6qcGeFC8cY8k8AN/eO3G4c3s7WH+eRFT/s3/w7G1PJqXxXxQ633ihz1UbJw/0rGbkv+0nm51ETYNGd2Xq15s6vuuRwZWabLndWcTubh6OpM6pqAWccAX+rANhJyo6/ChbOuGfmMSNHl59azAxcdseZ2aeMKXPC7HfHMN06Hwq4OiDakWmmr3PoTh9OZFVynxnHBS8H+lz7al8HOHb347G1wY1jyRr5YvyKVGDG3w5sxXYGfl27Q9As8Hf71bxm/KHj52/KBytyvqLi1Bqes7y6AK+KKfibn46/j/5Unq3ApuKhvl3bKmfN5EjXjvWJfDsYofJdlwsquTptVC5VBdSsrF3ZskJLAWnUd5aDnd67wNzZmbMd5/98DPs6PWd5Gf2j0o+aS5Vv1LjRnuNLJ392iphMhllsFh+WV6076yDLr9He5XPXv4pBXR9TvqrGrmxSzavrC7yv8kE1VtWmqmlm7OFgD1NaG7i5zcx7I5WzKpniG/+96jxEqGOAqmjLZHDAuhOoOGB1Cotou9nsPmq+KmwcTxeMM0dROjk0GHdjd4A52oXrNwP21wBa/F5DzkYx2PN4SHxJUMYXj80kaKQMwL4JykDJLHXtTMUGlRBU0lT9Xazp2DhvV/Y+S5Xdu8SFNoq/MXkqedWYHT1ksYvlzWhWXyoPZDJWa++AasR5lU+urq5e45XlLweS8YFILi4q21Zrr8boABm2GzcfbOuuWsn07ng7W0ZyuYLHWWN/HcI5o3xKvxmWckUCF1hodwrLMKkYmBUlXZ10YuiM/3ZiG25na8vzUTpT7Z2PVHIq/XObOKuHdoE4vFrPtbmjixnX4qm11LFZFzM6+I/tI1v7Kj91cWtHFq69lO917Inl7+7PaKpQdQEua4ukFN8BtLOkFNENnkwumKLsrBcXLLi/6oOGqwBsFWixPbdR743kuWbUGdsBiApUq+Ti1ic7njlBBlaR3yyI7zpdN9lVvLv7OPmob7WNenL2jqBVyVDZpwMg+ySZfYutjE8HTCpdMV8V+9hmO9vKziu77+q2ApWOZwfQOSCq5OV+qs+M72VrM5MTMnkru1/L28W1CiRVMTKzPTdWJ2dzvu2CPje3TJ7qeIyh7gvL8nkcV7K6dh35qvxzCHIYIrOhOJ5hJ/7Nl66qtcfvztzVdpePOsZz4TGqYsCNo2RFXhmAz3SVzaOKwU53Gb5Qx/hEzgx2draStT2E7VdjBWW20tGZ64v9+XcnT2U2qHAcyqj81vm7shEV35gX2nfHx5T8a2n6qb+x3QXzmYErg3HB3/VT4EeBocrRsqDi5l4VTBnfrK0LYJhI1gCKDMh0QYhK6qEjdWZyNnBU8rp+ylb43pwKEG2329fORjBxcJiZD8qWJQ7eXuvkrijoBmEGcWx7Af7cHDId8vFKnn3sqBssZ4oe/q2Cd+WjHdDl+FQguRqfKYu1mf5ULM7kUsCuoiq+dygrRpxsnMSZl+IT/tEBqxl18k6HT5ecflyez0Bydt8dUtyndX19/Voc6QKhDmEs47VhHWf2zDnvULQGEFftVIx3YBa/MWcqGRmXOKzi8Es1J3WlW2ZDWV538sTvbnHL/KoCsSN3JwcrXllsUXGhGodzl8LTzNPJo9q7qxgUz1nKsKZao269oWwX2yhMyf2dHJWdVWuF8mXrX9UIKr911h3bB0Xs7uK5NXi2XahWiVe1nTmOiSR+uyA4hk+sqpBz/ZwRq30cELl9VRAw8M/IgQQMKlnCQaObAecu6GcBnceK7QqoZEkM5+FkroAmyoGXtnT6Zcdx39pk16FZXllCVt9uPPSfzqeSHcfDF5ZnoJZ5cJ+ODhQfJ6sDHxW5IiWTP/Z33+enxsmSfrYmik8HyOB29h5GbN9NWl3A1rUBbp+B2A5xDEc+6p2gzvYrWXmb86A6pnzRxdMqlipddXyiKh5m7WDm1h/mO6vvGXtS48yOOysbj7uWF5ID3vF9dXVlbSfL626d1XaGUdSaOB9mX3TzdBgyuxVqZh0ctnG0dj07sVLJ24l9vDbqGG5nRZLro/rN0Bp/y2wZ2zjdOtuL9nE7BfPPckKFGWfyoeqbzSdbywzTzch3SBwc9EYK1RmenYTKgc3JtbYoywyUf691yApEqvm5RKqcgQM/86uS8wzAdcTjOVnUXLJ5dwqPcEwF2Crb6Dhex+47NrgPVUmzU3g4fvF79lPxxaDZAb5KLrW/O8cYNwPhmVyzvsLHM3vo6gPbZ75UjZMlzA646vhS1mYGwHVsoOIxQzO6cLY/Eyez/SzLTI7LxlSARPlzJ9dVY1UyMM34M7efwSaz9pPhjTWYKLPxfXPHvnnOtXNFaTdeOjkd5nE0q6+OvF3K+q5d/zfRRxWQGc4+VCG+r193Csouv6pIVDxn12W73bb+bHZ6zsabqWOcbGuOrWmHpDDVoWjV62lQqC7NgKvgrf5dZTCevTZHGWx8Hx/vTn1N0J0Fiw4AxD5XaDk+Hdlm10k5swp+eGwtaMhkcPsyWToFQhVQ1xZRWTuVDCodzzp7B1TO/OkQPFDeo6OjctxOEeParwluMwVDh/9sEegoKwQ7xaZb/7XFakVZUmW5nKzOFlxsq8aueFf6c4VZxaNrk67vGuDDfJGPixncHmVSOsa54CvPsrw0S1k8qOLdGGM5o+deycYFIuvIjR3bnYcoKvlmcm6XOphjTf6eJVV8r+VZ5YNO8djJU9kfYQobqj6dV9ll462hQ8dtpGrtOnrN8pYbY4bW4o81/Kp8xMey8VTsUrEE//RzfxAoHziUTczymY1rHby39g/OjFY99XfGOIIw+VZFBLZh50Ij2xewqX8AZv5xcP/OsJyur+oXRqtkywCFAmWOqrlmBT/L6vp0aXb9XFsHRPGT8ZoJiF0woex2NlDHd6d/5lcZ8FPtHdCNj7sEtPJvx9tRBryrvhm9KbBQjdPxuTFeL0izAqtKFtmYGWBU7TvFkpNJjdOZh5t7N3ao9g6sqHE684h9WTE+Q8pXlD1UsRjHViAjK1SZZ9dnXKydybdsa7weDvDh+DN5vfLTQwP2TlHhqFNsHEKeLnXyn9LfrH+5+MKYMOPP9q78qAO+UU4XKzI/eBP5ZyZmdXIub3fGd3y6VPk0bndj6oy/VLhdbat2Ll4oHpmtVtSJ/4pnV4eduJcVrzMxOKN2oTr72hhFHSdFxasXVeN2tfgdGauEEb8rsKj4doNBtq8D/vCYa98x3o6sne3ZcWYBJ7fl1yV0daZ4Ofm4faVbF1hVssiAJ4NTHt8FCcXbycFzUIEz+t66dWvn6dF43AFpBbidvE4eRWuCbXe9Z4Pqmj8gqjZq3deOqcZ1oKArl+Ot/NCNMxvznN11SMVwN3YWn93cXfHrfHQtkFP91XYWCzlervG/DrnY1eHfATkzttsB0hiruvPeN8ewLhzQ6/r72rVTuY1/V0VcluPVGc4uDhpDv0JN5Tv1rXyhOqOaFUmdOVQ2ewgAz7JUvuVw6Uy+dfsy3J/xnZED13s2/1XzdrK6ebt176zBzHg8V4UN8Ziz31l9ZaRiVoY5q3qoonahipf9dQEHE4NY1RcVv91ulwewxDFUiFqA6MtPG+NF5ZugWR43RwwGHcVXQGqtE6v9GRiIfUq+NbRm7Xl7NmBGsuN5OtDVCaIzcs8Q2i3ymQl6zIvXlt9/pmReU3QFcT/0qRg3/iRwIAfbr5FDJXO3xtkcugnoD5n2DfbMi79nAEom30zh2OU504fp0OucFRZu3CwmuctR18TrKtc4/zyEjmYLqU5MUOuf9cn0zPmB45KSi/ED8sziLvbt2m9WIO1LnXGR3kRsZNDatbsO0J/lMYZ/d7gbM/Nzxq0zclR2lFHWd8bPMvmqcR0OxzXO8nDG/xAYzhH6fyYXF2IsTwdnr62ZZqiah+uD1J0j9q/wH/vHjHxB06+ncQbIwld8qrEwMLixMtDvnOQQxu7Ak1pUBWqywOvGmz3emWsXCDG4V+tQgdxO0aZk5uKMbaNbsKi5ZPsqB107FvPH35VPdX1wtnjrkEs0WLQ6ntl4WfJ37d3au4RcBXDFp1qPDs30y9aMfSDr6/wno258mRmnC8hmkvysvE7OzppmttQlZaczMU/Jj/tm/dfZtMq3s1TFebWGLi+vKZyyItIVqmo8lquKlRVI24cOgVcqW+f5OdtwvGbz79r5dPy2yrfKBp3tK9yxRmYcP5Mt+51RVljMxtK1+SrLn2os5VNdLOpkXaPD8G8X65GX4+f0fMhYMIupMjkyP6pwfFYHZPGX26zxp1X3qDKtBXJZsZEBY+x/6OSAcswmb+X0WdBX+zPeVRt1aQ2DhTU6cwCzW4hlAFfxVcTjVcExA19ZcFaJao3c7jfyU+8OZJnXBOtMh10KO3H2e3V1NXU7APLBfp2glSXFLIHEtwvqOLbyx0MUq4ekLvBBWpOU1tBMXOnGA7VuXZDD7V0htBaoZYQFUYzrfKW7DvsA/OifXY2Svd6jkosLQSVDpX9+VQh+OmCM5xTbzM/Jz/lFxQ0HGJHHIfDIvjwciJzBMDwXh11m5er2rwroDl7i32oOyna7+dPh1X3iyIyOsnYOs62N+5WfVzF4bRGMPNy+bj5x8nRwbFcm19bFvy5VxarL8V1esT/DdCqusO47OGCNDa5+6u8ah+RAkAHHLChwH9dun+TBhqWcIStOONFlRZRKroo/8+X2FaCfNdxszh2dzgJSt53NWfWL35lDrCmIXdCaSQAzhWiWXKpEznywrTrm1rpaN/fU7WwuDEo7QLRjxyyHuvwfec5QR78zyUz1dzQTa9fGuxnb7cjDfqziUdAMcO3KmvWveCp5Fak2quBztoN2muW9zK66eZL7cQ7K4jrHoawQZHnDVqpcqOTv+Hw3x1f2o2JMyF3pCNt1QK/azubAumc5KsAe/bCvKtgcCM181j2kbw2xjeBYzm4VD84zLleq733s6BBYdK0/428Xu5zPV8Rr3Ml3nRzhYo3jp2Tmtct07Pwzax/fa+z7ED4xO06mgw7O72KcChdmNINngqbPqCqD6QLgqiDh9o5XR+G4b2asiioDcI6aBUkVULBfx5C4nwMTmezMS4EJXAPedkFzRmdd+Rw5wDnbv0qayhYzAKbGyYKKWvMOP8dnbdLIkrGz8YpPxweVTzg/yWzJBcWubSh7r+RdY8czvtnh96aoAmdB6o/NMXaLgLWJfB87V+TWyz3Zmrc7BYYbq+PbOEZmz125lGydHMQgmLfxg3zUH1Mud2R5KwPeXVyC+92c8d7/DmaJ3y6udWNIZ5xOvyxOdnNOBz9sNv41QpWMvB08Krusxop1cJhEjaty/OxcFFU+1eUzQzNxhPVT5bcsrnT9pBpH8UTfqtbOye5kqeRR8+7GlTU5f4ZcXGE7O4R9udgfx9S4ajvbl9FBLv2dpS6YdMFRJUM3zr5gT/HoFo5M3eIR23MwicTgLvPt8nbUSRSz/NiRZoK0Sl54zI25DwjOEnoXWGb88buiNePMgOm11F1DBUwrnkr3al3cOiNYmRkvtg9Nb7qoXBOD1P5DJTTnIzGGW79MtuCXgT+eRzcOVDzV/q5fZfGiCxJdny5lcldP1sdx9wHzVR6NhzUe6gwdjqfyrpOD45Qqgjm+uCJ5Rl+V/2VF3Sxl9p3ZgtqH9uNkxX3dONP1SeavCtXr6+v0j4Q/RMpwWKW/NQVZ1r4qUp0MbyLvZcV19ufEmyjelDzB//dJnT8QXIxy/RQpm2R+iv8+f1YETReqDBSVMFlxgced0Grhs38POoGSySXN2SDA86iSUydZur7V8RmD6Og/A4gV7fsHAVKWlA+RcDLbQtq3OFW/O+vTCaycVNYAyapNtz33zWRRcQL7KL9U8UXpqBsos1il2qs57JusDpncZoHKIUAvgsOqbSVPJVvXf950vOjG4GrsqnDg+XZyVFacMfDMdNuxC+c/qqDLilU1X2yvbjOoYlM2Xrbf6SG+3RUDvE/ppWM31Rz2KWQyORRl81Djq7ypYvyMrBVlthpnyNXTtd1adHJopyg6FHVyVLSb4enIxQ38nhmrsk913K1pJy4pDMvHKhvsrr+z7RnqxNisX1ZXcOxaK2P049rPyXnIGmCvp/66QdEAsiToCgEFPuMbL8eqEpvivQ+5eSEpw6mKkY5DoHFst9+9mkTpCvUy88AbJ6MC9Z2gyXzwm3l3Eh33V/I5x3XBsQN64x/Z4DMb4N3+Q4Fm5q3+5WbieawJMFw8rqEM9Gd+7eyvA/hc3Mlsek0iOSSIUXraNzky37Vzj/HZx2fmmrXNigj+3S0UVVxWfByYccBKkSsqMtt3Mjr+Gak4pz7cJ76zQjTa8IOasI3S4QwQxrzncl4296yoc7IwKdu+vr5eip9bt269lifiW4HErm9kOs/4dPxA6cNhnOxhV4gzunnnkAUXE9pzjOWepZBhDdfG5fA1Mnf6VNioy9vluQyjz8qc5dguv45vVHmwmyedLSrMm2GLitZipY6fVNhJHUefcDluH5kOTe1C9fLy0h7LFtEVNmsWSxViawunGdqn6FCFBCdaNhjF0xVcVWHkSPFxBl8FnU6Cd/tVIlc8VWGVJX4ugisglsmrxpm1tQ7gdTJkgFXZl2rjeGeyVby6NpBRFxhUc8TLu2Ieyq9ivbfbrbwXbZ/kjNvOjmZAaiYP8stk5LWPgqJTIHRjCOpdJfhsPg54zeSKNxX3lSxqnmP4tVXAv6MnNZaSwxEXErwvfrOcOJeMlN2598Eq2Xh89RvzI347ORyvjv1UbXB9GYcE4Zm7ym+VXGoNMhBa8clyL+e/Sl6cd/wRqj6VPByjlZwKJyl+bl9WoCn5KlJYYp+ipeqjcIuLAZmvOtyQ9XNxqmPXswWP6tvp3+E/k0cyfNTFB3gsG2cmhndim+qj1pbnqPSS+Z2b/2azee2kWabPtThx+qm/nSRTObFKIl3jnHEC7rNm4VWbNQGP+yuDZWCSJVsVhNYawRoeGbgKPlUgrcZnHlhkuD5Vcne/eUzXvwtqqnFQ3mxfFVwzcDBjD2uSyxp7U2unbL6zhsjT+bpLPLidFREz8+kCRAecDhXUK1krQJyBGLWP9d+1WR6rWrMOSOKxMjkqHjPgd02sy8au2mTtne+4uNSVeUY/lTxVG+YdZy87gDHjv49PVQAw2xf7q/imfNPx4u+uzzJ/FQOir8ubzh87YL36QyPDFSg3H6uA/+zaM5ZRPCrfqUB7VgC47Y6/On/P1luRK6yqNapkU7zV9qy+M+rkJtW+wpuOR+bjszijK6OTN4vVM3m1quWqsavxHP0/eZjSLLEy8FP12xdA4PhrnIZBlgOliq8q+pQ8ncKIDZUD16FBcUXKqVUSjLnj2a+QO+OL7WbBTTdpIO0bQN3vTmBwgcjZiSvEZ+dQrUGXR9WeAYjyQy6WZgDEjCyHJFUgxn5upwqjQ8rQAbmzQLg7/qHm0qEuOKv+dDgUzeSQGXlUzMv+CFBUFbMdYNaRMbYRxI0xds6kZg/EUT5UFYWz8qnfjnd1u82aPwkqPhU5363ifpaTOzJEPxyLz8CwfMr/qrXoXtqbYTE3FvKuHmKpxnX4as08eV+3CFhrZ1kucmNmf2BUsig9dPCX41NRhe3deoQNz9JMvuvgIiVjdy5qPPQJvCLNxQn+A7GKC2trjTdWqGYBMKv+mUe0dwb1+wSWztk6CSxb7H3+NaqK1Y5xZuuRyTwbcFg23p+t8WwRkRVuauxqe5ayZBnHs0SdUce3qj5doPGmgfrsnwA8D1e48/EK4DqaLQzWkop1yoeypNMBjYqqGNyZ25o/J6qk7QBP5TeVD8wCgC6/CiCrMdxvNU7VTlHoOAMIHd7Of7h4UeNUc3U2jx81troXfwYfzMbAjq11/CDzdebP22tykpO/g7+wHb5xINa5eoVTxhvlYPkq+avfan5Z/s/G7q4F277yk8zXXH7u2gbLNBtbXb8Km2T4vBoD9dvBPR2eVdtOHMxy02bz+lUBytacHtfkbuSR2eNsDM/asS3N8D80TT9MKUsE7Fxrk4RSUHW8A9xnCrhDUTWmK8oqo8r2rTUmFfT20VM3UHaC3JqiInNq5t2VIXNiHKNKMGp/lbw4uVeBz/mGSqhVAqrmwDJ2KNN5pSulb96P+un8SZGNXc17DZh0saHjc268LmBYW/h0ycVsHrcCWpn9ZWDH+QT7xZriXY2Psrs4sZYywFPxr+4rY36uqAli8B3FYlenap26wNiN3aF9wKHi0wGMVd5W8bzKGQ5jzcSnrv3wmqIt8WuNVNHqchT7B8vRiYWdnLkmJjMf5qUeKoW6cH7v9O/GUf2q/RXmqOJTJmOHVA6ueCubZ7nW8Ha8qtjEMjl+/PAwZcNZ3OY5zdpqhtcyWdbgHc6bqk8nF2V1XEXtQjXec+YIlRRCdIPnIQqUDAh1DBWPd4zGJZyOrF1+mQwzi7wWlGayVobfHWs2gbwJYK2CdZVAO68nyI531iQCxKHA7iH4dGxzjZ114gWOWfloprdZMFCt1UwRnFE3Zs3oS60XA899fMqthSqYOwCUyflgtjYVeOWHaB3CL5Ssb5Iy/fHcuK2zCeyfAWfsHzakHkymeHbAuSJlT2+aXAFexY8qTjBARb5XV1dybKZZ+53FZkreWDOOHRFr8QnILv5m++IbeUdBwHpS8SvTGT9jhbfX5p7oe319/VqhHvK7p0Grb6WXTFbnt9zPxYHMzzNCvpX9qbm6cZFfVpwq3p16wvXHy1yztViDx5yMmX/P1ilqrFkZu3FLbWeX86Pvro3f02dUFWXBvAPu1hiYkgG31fgzBasbIwNglY5YHidLxxmqAmE28MzQGicI2rcw3adY6MpRFS6zcmWJBb9dEbhGVtc2C3Cz6zpToKk5rgVO2TqusS9VCOJ2tU5q/Jm1c8AeeXbmjvNRsnZ1o5Jp1laN0QEZXZopDLLk3eXPNDsHZ1OZnc3wX0uzxU3GJ9unjrtXIWRzrnx7tthSvuPGmI1NXZlcsaraBD/nz249O2s7K2fWP8ZnGZRMri3z6pCzZZfnOnmd5emsT8Y/8ofKIxVGnYnDOBbycdi80k+VP6o4r747NQEXqpnMnRjCVGGfbE2yeLRPPMXxlK+r2JVhOZa/089hnC6WWIPrZtbtD+5hSp3AmB13oM8ZgOI/m5y6cs0AptmipRMEOv1naS3omQVNM6AEf1fAPpNLjYuBsyPTTCBR4+C/tDOgritPN5DsG4hnZFI0O35VTFYAI/bP+hWDMCdLZ3xHFShAOfByPbTtTpLv+Cb78Gz7jNbahfNZtTYzdEgf2De/OFkq8JQBnFkwhH2urq5aBb3zDfcAoixeqfvE4jsDvBkOOBStjceOxxpMkhXD/D76NeRiGL8CC9ejA+7VvBm/bbf6XfKusHG40I1bycM8GQ/EXN14+/j/jC10ittZmWaxaIaVnJ92ZHdydYhly55EvRbjqlzXiaeuOMTfHQygeOMYFRaYzdUqVjv5ZvXZLlTjkpRskMwg9wG9M4tRHQ8ZWYYsIXKArMg5WzZvBpGY+DvBpgoG6ju2M33sC6gy6gChjgzOmSsnc3PMgK4Cc9ynWocZqhKd4jnzZ0THX/m3AqSZHG/ShvbhzzqsgjZv875OgbqPnIpnZsOZTGuLwO7+LH6wXB3fwbXiOag5dhJjF6iqNp2YpcD1IWlmfWZ0HDy6QGVNEdDxJ2XD/CRKHKuTX7u5VM2nC7wz3mqbZVS/Z8CyKtbYb7rFhtrPNu1i/yx+cTLMgnBFM76tYqzze7em6pLlGVk6srrYyt+HGi9oTWxbg4nd7VWduN3F2jP9sP92u7V/rmVzdVi7spEq1rtCUf3mApV5ZX7Q3e7Euhmafo/qGG/uH8jM4DMQqfh0qKN4/J0tPH6r7U5CQAeKT1VQ4z73DzNvc+JSekenWgOwZgBd1r87ToenOt6ZGyf8GJf3s/PPBO+OrO53Bhi6QaK7r7KHys7XxI6uLXULFCWX25clwSrhdv3GFW2zVNlKldDdvLKkOWv7Fb+sb8W3olnb68bsNZStRZens/GskJi19xn/qdZNyZP5kip2ZuNsB0x38r26h03Jnum3ip0uB6u+HbDv8kJnTWfzPvLke1S7xTCvaRXPHL8qfmf7+dis/0T/Chs6/c7Gk2p+Kt6ujaHKFjM7qfi5nInr2LGBWftWvlTZqpKhs1azsqm2+/iwktPFYNzObH5fP11D7UK1YyCKFMBXSs+A3oxhdEkBrLVFVVUsjOGdkvupRV87b5VweCx8H9Q+xYSjLCgreXF7zbuq3sQcmFyxyjIo2d4EoOZxu+PsS10/Rlojm/PPmaTVLS4zXh0Z9+FRUZZcIk5kIF6BpypmrZHfrZcCcGpM1d7x7QA1JUtGMwVIN3aGng9ZoEbfTl7KZHN9Zte+U4h15FFACnXnbJzt39kLnu3icR3/Q2CPTKdujEMVLmuok7dxbWLsW7dupU9krgoU905UlqmKDZW8jvbROeNcHkvFtzX4KJPjkDluxiar9c7iVHw7H87GydpksQax6fHxcToHFVOyPKuKzBl/UDyxfTeP8vhvoohEelP8D3qP6gwIXwtW15BaoI6xKz5d4qSkfncK8UyubhDKimR+yMWacWb7VQUHBxnllFlhX8kzC96U/M75OUB07ZYTHI7Fx/mY+13NoUtZonXHura8tsDrFK/7AG4lgxprNvhnhVi2T9nFGpDBcs/EbMd/TWx2hZtK8rzP6axTWFf2hjw6YNYV04p/Fse4f6XTQwCCbnzu8uF1crz3KZgzcMj9UTZ1zO3PQGgQ83X+xDGiM3YlK4+lZOG+M/gmsws1duYzGZBW+l5j9x0cxfJldtHVnyt+4rsbSyqehy5QHWZR41Z6msnfKlZmBWA3DnVsItNNxzaCVzffd/Xi9NupCVRu5D4KM2Sx0umtwtXddVtbS6x66q9zwK6TzTgRtt8nOXeAPrfvBl3kpxxRgVP8HILUOlTyuiKV3xF1SPkO4eyd9hlQwf2Vzc4WIQpoV3wUSA6q3hW43b7+IAC2q33WkfXED+HIig1l567QUPPaR24cR4GHrFCbKXayhzB0gEPXF6rkyvpFu3gTiUPFrzXxsurD4LgqSDpgw8XdDuBmkM5JPosdlR+vAetVnFMxqJJDbTMpvz80xfjxvAaeh/K9NYUO7nfz79h2Bs6VfcQY1diKZgugDlWgPrbVq16Yx5r43Y2DnULJ9cXvQxD7QZbLmdi+WGeuqHNjr5U/O5bp18mb5dZoV2GCWVmZTxbfszg/Q9laYRs+1sEF0bZb/CmcqWJWFouyh9NVsmZzUOPP0urX06jK2yVm1ze2MwCSyeDGZaoKBgSuijj4uMSiEqgyVO7rDLcC0kq/hwjCam3VcTymZFX9O8nYrVGVoLJLhWN9HMB3Y1fAGPd1AkvI4Ao85o3k9Mg2WRUQ1f6MZgItt3G+HseyfTNgO45nNulkcUG8Iy/LF2PgOyY7fFi/KrFWMRTHzRIlj6fkq+KXm0sGVIIQ9FZAf4xdH1d6UuNX8cTJr+YwY7+O9gXxlR1VuUX5sIpdVT50fHjbydotNFw7lYsroObmUgFK19/ZghtLxRcVq7I5V2N1fNbF8Q5mq4qbzp+rKl85v+4SA3E1p1m/Y/vo4MS11M1pQSqXoW92MGZHpgpPZLydvLzmWRxQ+Q/7qLlnPFgW5pHJMhPnuR/z32w26Z8+KFcmy2xOdzxc/mbduRjB/NSxmI97EJWj1Zf+qiQ/kwiij3OCrtK4T7WoGfHYHOyypOaoShgV2HIyZollVh+d+WRBoBNssvG77ZUMVYLl9iqoY5uOXEqvawCT0+kaINuRjWXojtPVbWd/t63y/wqs8v6sqKgKjpl4ofqyvWZrzby6Pl4BpkiErrCo5uQA7qFIzaEjXxbzkNbIXek0s8tqjAoUHUK3mb3H2FmfDLig7I4X29pa0Md2WI2b9Y/fmbxrqAJljn+Wx/aRLbOlDIesLd7UtuM1U7CoK7qqnMY+5XBbZ15OL1Uxs48tVVTl6yqHumKmM4/MXjJczuOrtXayO1mydjOYi2k27leyOFrDp4tJeWxnL8qXsloBiX3T2WWGC9f4yV4PU1pLrmitxnEBEh+OkDlENo5LFFnwVcFRgdLMCaKtuqQyk43n06Von102lY1dyXaIwmWGVOLIAH62Fh1wtQ+hPXWLji51A00mG36rY+545l+ZL3bl6AKNQ1HHb6u+uK3eK9iVo7LLSp/8z6UDsx2ZMiDcSYhZHO3GkTWkfKNbVIZ8VVzrggoHHrvFw4wPvCm/yXLiDK0BLZVe0F9cLMnGPPSfCA7EdfnNxAre7o6BNqdwTBzr6J5zrXowktNrbOOrEFU7Ryrvz2CAjE98O5Cv+B4qhlVFqmqP3yzP9fX1InfoCG2A1zHaIx0dHbXlrzB5hTdnqGOnKNc+4yCf2QJ4dixcoxmenGPUOqg8zZ/qDOgs/pzVy8EeptQBliqZVwnB8eiA50MVHRkvZ7Au4Ks5rAEUKihmYKmTyNz8siIQt53DKtm6wI7HUKR4ugQV83FzqhKCs4UsyWdtZ/lz230K1Cqhq99qfPzN24eQL5NjDe9sjp1k0LGRrJ8qRpyPuLZrZKvWquLD8lRyZMQ+4Hwzi7lVzIv9yHPNulU0CySVDp3duXjbaaf2KxmrPKXax3cG/vbJvR19ZvGzE8Mzvso2mUeXOnaaUaUHZTuzoDbzjw4+cfqZkSmLW1X8Y//o5I5MBs6JztbiW4H/LEZ21mW2eHKkYsxsflaxv8ozSi/4HbzUWLw9g1kd32xOjrLjDmMqHs7/KztZS931QWKbx9dMZf6t1rgbs7q0+h5VdSwLDi64zATxaIenn1m58e/PLG81FgOJLJG7cdQidxJpJ+Gzw3cSqgtMarzQ5yyAqeTu8Oq2yRw/K+5mx2IHVHPFcbMz1qHT7rqqYOGAapeU72R+7BJbljj2Cb5KnrXFVcbb9V+TwJwukK+Lkd1kVdkuAwrumwFI5sWgP+M/C0jRX9hXM9m6OuvMr9u2Q1nMcZQBOLZltp+unfOxGbuv9Ba/u0VJN0Y5PfI+tM2OzWOftb42u7ZK7k7fCvx2cuKsLWfgVum6w29GHgeIu8UJ8nGvIEIe7BfVx80Pz1But1v5jJKuzir/rNrFt8vX2I63cSzG2G5M7KfWuxMHKjxcjce81LzW8EJ+FT4KPspvZ2JkJkMlq6Pueqhcr+43z3COm08VzypaXah2fs8EmIzf2oARxzoKdIbIfTsO1QGTMzw6oBzly/irhDMDsCIQo64Y0DLvfcDfDPF8qqdCVnrC9k4/Sg/b7XbnQTYdX3CAHHXbSVZraMYmlX/hccdfbe8rD47ZHZt9XPlABGjndxn4UUFbFTH8UKCMZ/ab5xi2x2278RD7z9JaP2e5mN+sLeD2LA/mE7/ZH6s+GR3KbzN+Kq9V/RV4R+rOseuTnXzL+50/Z3LwvjV2eug1q4jjhwLgWVE5k9OjD46jYsA+/t0d280Vf1dr6OzW9cEzRzHvmTcfKKzAY3doXxvDdc/GZh9yNrUG6zoc42RaE5ezHNaNOYpnJlMWs7CN4lP5YienV3bUyUmM3bg/+59aM8aAa+LpTFwKOlih6trMTkgZQmYcmRLxeOYgWSG8NjgzCF0bhDJHVHyxOApyCX2NwSiZHJ9ZQ3Zr7nhXMs4mav7dCfquTwfcoqxuX5ZIXMCZTeRuP4+d+ZeSpwuAK1rrPwqsd4B7B3Bka+YKHRcTuvPLEp2zvU5/R109VbyzWO54dG2py6OjmwwAObmq/TyHrDhjG8F+/P0mioaKrzqe2XwG/tgfO7r/fVAWU6t2a6iTXyq/d3bdzV8OhHcLriyfZHpTmMv5CPbt4ooMAzqcmeWpNcVCt383v1XyVXjT2Tdvz+ajrP2aYnTNcXdsFoOjX0X/+K54zMbQbsxTeYFlq3g6n+nmZ+Sx3b7++ruZdZ7Fcwe59NcRA9tZw64MhG/UxzGy9xtm4/I42StPOoSXIscYOJYLPA5MOUON47xdGTYHf+ZTkSuoOuveLZh4rA6tsVfuxzpSRWCmZwYS2ZiHSGJdygJ61Yd9LAtSVQCbnZfSk0pC6FuxH/81ZxmrS7G5Lf7G79m5qO217fA4z9MB2o4dZL7ofBt13qVMlxl4rfjxPqWDrEjFPoo391HyqdiA+9wDr7oAyeU6B7YcdcB/Rk5H+Jtlmo0BWSzO5prFJyUvtzt0DGZCe1SxqMJOLs9neV1hkTVrsg8pv1F4ibfHeP098DxXzE9d7Kmeku7sJNM5yo85RvHdx+dwXJULgz8WFy5mdda9U5RkfpjZY0cPOMd99cZ8efsQsWrtGld5OvNVjo1ZXHf+pd7BznNZq/818WXvhyl1g/0Y+T8bChzwcVVc4fGOAt3CZoUG9nOysQyOuH/HIPeh2eKuk5Td+nXBn+I3ExAqMMv7OzroJjLXPks+3QDM290i5VABpOLL1LWXWZDl1lcVGniM+TmbUu0d2OHtrm7d2nW2O5QVYu54JmN2rIrXrr/j7+zVFR6OMl/r2JBq58C8owzIZnycfpU/dfWo+uB83R8H+8SPNfkpm2MXhFYYoYqh7CsOAHfmp3xuTQ5lcjpQxUKVkx1PlXuzGKL6Z2tVFSZuDStdZn6bxWr3fBPFM6MML6o/nhgb4fY+RReunVsvpQ/8rbDtzDofwg73yVdd3c2ubwc/VD46I5daD5ZJyel4ujXrYOyMHAar+mS/K1r9epoqOTvBKiDFClYA1QEbt48VOguWO0VCRippRt/ugrkE4gA3j4P67BYYLL+aA8rAQbh6BU7X2LuBnB1dBXHWXaWLmXG74BeJAyLuz4Blx+6rMV2iVvuqxK9kdNQBqorPGj9S+nW6w/14vzu2cbyVXOpYFbA78VFtuzYdu67igAPGMzHEkboqZjbeOgCG1AEX0c7tc/G3m9PUvpkE7mIYfs+sR8aHt5ky2Wd9X/GYpc66qWMqB8z6zBrdZ4A+fGKfAgb7u9jq5OnkL7QXhc2q/lUblodty2GOjJ/Ke24dHDbpxnsnC+Ya/ITuOljayaFiHOIwHpPlU+s3m9+QMh3wvmx+6tiMX2Tzq8as5uX2ddtktutsropT2THsy/pw83f5vxoL5+Jk667j1BnVmWTmEnF3HKegfcjJs5Z/Rw/81KxDzCVzuMoZ2WlnjUb1UcHx0KSARVfG6K/6qkSrEkZ3TjM+4mzBXabqxnJUJRkFnhXfChR0bdr5XuUf++iCQQfyUoABC1R1+Us1tw4QCp4dQIy/HZDJ+naS2YwdZfuymM9+NTMn5qN+d/TSBR1BOBd3eW58x6V97jLcmKfi07lEOtPfIYnzrgManQJbrZWLv4eiTI4ZgKtio/OX2RyagchsHKZD4CO0oy4IrnzwUPIo26hykNqH3+p99ZWN84OVZuyI58AFKf8hynPojhHffGkv5jGkwBgqP6Ks/J3l2Uwu7n8obD8T03lMF59wO7OR7ni4XWGpjDLM5vCduq2pE1+QX5af1uDk2Zw/xoozqh0grgJ3BcpYeVkC6yRTN26VGF3Qcm2csWWOr3hmMnSSB/btAmC1T42d7cscr0rgDOr5mOqrCuyMVIGbFatqzFmb+H9NHZtjm+oE4gpEBL/smBu/Ws+q4FsD3BH8H6IA6BapeKwbB1jOrv1X8aATl5V/sAwMdJnPrJ4z/czEX9cv2+eKMAU4+Xc2/xkZVBvWX2fO1Tid+WfHsxyt+Ltc0i3OZojXo7K5CnPMjsfjIp9Ou9lYNnNsBhyrfWuAu+Pr4ouy8QrkqvjoYnK2Fio/zcbsjFS8cPaq5FJtVHzo4q4Mh2Vxr5pvFau7+SwbZ3Y9uvbTXcssnqjfHf25wlMdU3yw7UyeV/2z9c/msG/OQ3pjZ1Rn2iFxEZolDgdQnfNGP8VnBvip70NSBQSczNkZoEwHGblkoX5XwQQdZkYGxys7no2vEqMCgFmQn5FRzTmTP/4Fm7HNmQRXBS312+mqCoQ8pkv8awFiVqSyzAyGHfDn4P0mQPRMvFkTa/bxLyeH0oPzZ7bHrMDift0Ysc96ZCCuC55CVvWuaSdbtI2H9EX/bDyUVZ2BQbmDN/eP45XOWAZ3JrlDld84/+xSpgPHr8qNKjegTbqiCsdfS07+TjFQxfRMbjd/V8x0Hz7XoWq+nXycHYtP98Fuar6oBzy7mvlTx9dYfodNHH/8dmNW8dRdvVXFJDdepw9+7+vzig5lmzFeh1d3vTqUYaUZqmoz9q2sNurkN15b9zCz4D1Dq576O7MormhQvzk4qkCp2jPhk3q7oGiWZosPPp4tnJt3xq8jb9eBqwIuk8mNm/Wp1siN6YBKN8lzsnHfPDbbXZX88TfbttMNzyPTd6dY7ADBzD4ykNMBiDiHLqjHtopvtwBCHs628TuLC12/VbEq46OOKZtxYyvqAt2MspilZHT9qrWp/CHrq7ar8SsAUtky9ud7wJyMvK/SGW9n/BWoqPixDDMAubKtLP8iD7Xt2jOxnzLIz/h1fcnNU7WvbLxDHfmZb+YzLjZ334rQWZ99SMm+Nm5la6IKL+Ur1Zj89F737fjNYIVqfKaOTXfi0Xarb0eocoGTieON0tMsNujIgjyd/7r8NYNR3BidPhWuCz7shxkurmJT19ZxbIV341iHd1bfdGiqUN1sXv83rRuwY7IdIbPgpfirheqCIzcHlr2SFcflPjMAT/F07TrgQ43H/ao5hC45uc0A6Gz9snXqgEk3pgOaXPyoxKLGnQEn1bGOL6hAnm3jPhdAKnDYAY8qUVfAXtmKk0+RA8gqWFaUAYlM3i51Ci4nc9fuXEHi5Ml8bs0cmWaKDJW0nD90/VGBrSoGd+KLmwvanXplUVU8ZFTFI7V2lf5c38r+q3WdjYncrmPDlYxZn0z+CmcoftXxfahT6DB15sCxmQuRLH5ibHdju1gyK3tlS93conxHjdG5WoB15citnfI/Nw7nsm5+QOpgsWoOnf0VBo99lbz7HO/kBrxyRVGFW5CXG1/5V4c6+I/5OVvuylrps8JnansWM282/SscgtqF6pr3kjJVgJJBMi5IlSgUL26vtrOgofbzGDOA1oEP5nN1dbUDPPiR6o5HJmtHHrcP5xvHMBDw+AyeVN9OAA/eyjmz5NkJ1moOs043C06CPwa2LDln9sbyONDAa4t+XIFcJdO+1Ikjav0OUUwx/wyEBakk5oCROsb7ub36vZZU4aTI+aSStZJzBphmvLPxsljXkRuPOXAR+zhmKZ7ZGdRKDgajlbzZsSr3ZPE9tqtYOQu+ok8HgHbaYXsm9ceps8dubFM6q/x/LSn7Qr2oJ49ncrv8kAFxBtiHjrNVcenI+ekMFlTryjirkn2z2excrl+NF+NkMcJhn278ruLgDM0WgmtyVaxZJ8+y/rqy7jt/hbXcuC7+Yjs8obdvfj86OnptX+bP7DudInUNKb10dBWfGXlWv56GBcF2+wDeQyozS8KuQOgmhmpMDqjsiPs6P4/HcqqxsoRcAc4sWVfgXMnIzt0BIkxVwnLrndkoJ0YHWLq2kAXCTpJw+9YC/hlb6xQK+FvFAsdzllTQdyBgNibxOrm1mS3sXF81btUP+3I/BY5mqAP+OrZX+XTHTx2Ii+2OrlUMz5Io/nbgupsLDlXEqLlWfrdmTGfn3WJAtcl8qBp7hjr9WZY16ztTwHViYLVuh9BLx4/3BbAuvitsoKiDAZiP8gGXE2byayc/dO2Z822F9bDdIQoblrsi16aDVdf8EdGd3z74u+pTzUnFvwzH4nY3/rmxebsa181ljS11sVM3dnA8yMbKaOphSmoQFzg6QSIDbTFBV/A5eToy8jEHeLtnkZ1cbHTZ4rJx4/zH2L3pfW2RwmN3jZh1hXJkSWQ2ILnAhOMq4BHrN6ubbH5uDvsUAYpH5sizVPmcSppVIM5stit3BzxkazDG639aZHasiqoO2HQFkepbAflqPJ5npt9MTvzGhxd0xnXzmgHma6ibeBnwxTY/0AS3VZ+uPBw/uvFsRleddXeyufGq8WdBE8ZSdU+eG7PrM2+KnO3O2HOVi4JU3lPrwrpXfRyG6toIy6mwhvMLNc9D+H6FVWbmpPyS+6v3MbtxquIK9X/r1q2dV0/x623UeO7DVK2Na++OObvP8no2zhqsOEY/Hir/yORxcmR1wRp60/kPxwnK4unMpedq35uOuzFGNs6++lxdqM5SR9B9Km7Ha23xEn3XLnKWLOO6eQU0FY/t9ruiGd/LWgGrjoydYkXNwRWpnFzVPBlcqrFZts7cGGhxsu+upypulMwVAOmM6+aHlyOrPq7AUEG9O3ZVfM3Iz7RPsHT2k8lzKKrihwvQFUivQKjyBZeMqoSn+CnqAJPZmJFRBqD47DAWIXHJXhV7HG9l586nHL/M7l0/Je9Mgp+JhdhOxUMlH8+B7cHpa7vdvnYvmMt/rgB0saeDCbKiMssFFV/Hn3lH/yyXZbxZXrzkN+PZjU1Z4dHx85niaUaP2YmArn+5q0jcumSkbIWLU7wti/k7rOPyspJ7RuY3WVDN4KTM1rMCLMZR8RvzAOrD+ZmSoaufrg6VPyofcT5X8a5iJ8vLMdPhXRX7UX7kVeUsh4MdH/QjzhkztOr1NDiJakAWeNZwOtsZnwrErAGZzJvbVrIpsOCAQQAzNkD1qWTuAC4nfwZOHfjJDJm3FYibBWYoZ3f+TJlNd52LdVPZxGyg5/2YDLt65t9rEt5MH6fXDo8qmDo+2dw6AbMDBiuZnV8G345PZnwcmGW5ZwAk88T+Kg50AYFKnpk8bM9OLrfOGcjtUJW8q3HUHFl3m82mBNu47fQ8m/gzudVvte6bzWb545TnW+WQau0zHSugm8ldkQKaVd81BUaVJ2Pb+TT+dn7eyQHZPjzWwXdd6so0Rt+/WFdr8QnzVfaAuEsVFRXu6RzL5uqOuX5Vzqt8n3VQ4ZBZbK7achzZbnf/AMv0kM2/65MZOftFuTq23RlDyYVz7/oN51vXp8sP93VjY6WHrv5XnVHlhZkVvguOK+PvGmMlD/JTzsLBpTIIbJclQA62LqjhGPiYdQQLSh/d5KQuZ3Ft1Zy538wcVdIN8KNuIq+CQqZD1xbH7wTxjJRtu0s3uiCK+8wkgo7frUksHbnYJzhOzIyr+GUydWJMVnzFd0fGNYAOL9N1V1Iw8Vn2LMEEj+yyIdc/A3Dq+Mz8u+DZvYNNjR3fnTlXsvEcMxln7VeN4eK0GlvlGG4/E1My+ZVtKj9x6+HGXAPgZkgVAvGdXTLeWfdsPMWnw0PJOBPbOF8rDMP91bhdrIDUsX+1Dry9xo/cWB1MWemEfyPmwr5ZfnDz3odm8PChxnM4mX9382SGLx3+dlTlkhmqbKHa1/UVFwd5LhxXcLtbP+1DHGOU3Ao/ZT6IunpjT/1Vg4WwMwEZlT1TqGb73P6ZAoYVnSncjaV04RKCSqgKyLNRKiN1ztJxNldcKHlc0KqAWycIYJGa3Y8b+nIBzwE4N27sd0VQJveM/XZ04PZ3kwDycEWi87ts7RRAdbJzUOvEB2WD2VgdH+22iTFUOyf3GpBQgTXnQ0oXWODwpVHZeE6mqp3r2wETjndWuOD8KtmUT3Z9S9lnVw+dPrP7u+Phb9xfPUxrJp8pPgpsuaIok6E7/65cM7bypsDdbO7I+DBlxapqF9vOR7P80JXXxSkFajN8onTWtSVFHdvPckrGw8mv+HIMczJlmI1zQoYBHXXiVGUL2K7a79ZrDebI2lTUiQdxvOO3M36N+yqdVfOcyX2OqlzL47siNfZlOBj/aFO8u1ibae97VGeDv3O+Q1Hm+Eyu2Iljam6zc1VJtAMA4jd/srE6+3g/z3M2KaDBVa+qQWCNpOaJBWsmv9rG7wyMVrzdnBVVdqKSmpMXif9hzyh0x/OuitSMX+Xfs/5b6S8DZQxesiKjGwQrv6le55Ml4Gx9KwDB/HmcOOOI682vRNhsNu0nZyv5K5p5ZdkasFnFS8d/Jie5Qr8CVhUI5T5rgAgfz2y+A4xdTOjI77bRzvbJ5Vnhw3NQv2cKq31yuqMOoMT1cTE5s8Msb7m1wTXvvged7YzjqsvfPPYY9QPeKtyVgf7MNrJXF81iHZcjZvSmZO60r+bQiUmdGJ9hUNdHkYvDa7BWNi7bCMdFzH2Z3+DxmRy1lvYZoyPnmlpM9e/yUXaEcScbe0YXexeqleMwqSC0RrluHJfIuE815ps0XgcWsgIOj3cTSBfEV+vQcXBXFLniQsnO80WDr5LLzDp1134Nb+yTFVJctLigUdm7I9b3IcDYmyYH3saYBxVsd8i/S6pgUnJ1Lq/tFBKqHyfjIPQvZ0uzxdQMzRRYVZ8s7iidd+NUBnLxeJanDg3OZmTOxuLY4vip/d15qXyZgUYFULo5qUMqLs/Yt/vjk9u6QqkrF/OakbVDKqcegnCNHfhXbfmYkrVLKta6GLiG7yF1Vfma81FXZKlchbZbjRv81Pbvm2aK7gpvOdzkjiuMua+8jtwaK3lU205uO9Q6ZrJ2/1Do6PVQsQBp7/eojpEDzC7fQ07OFWFZoMuAVVbwzcjKwUnpzRkuJ4kugKuATZaQsgThHK+SMZujkruz3wWvDIhmdqACXcf+K7k6MmZ6roJiJouTQfWrAi/2UYHX6bsCP2vk5mOz8WJtvML+mU7WrNlMslXgsWsrMzI5+dzxzj7m1xk7O96Rmds7HVd2msUIFy8rGdW43D/b3y1Su3KofW5eXVurfLVjw7N5mfdVBY/KexWYVjxmdTNLSr5uTs7yveKvjrv9+847K94UaHZro+Iw4xLll52ckPlRpz/LoPCSwoXsg4wh3pStBX+kTqxSa9ipE6If3yOv+Dv51uCMiiof6WLsii8f66xrhauVzXHbqqZxvuXGcWPP0qqn/ipDVMbnEptK8GzIXVlwrKrNDB3S+bPisxsg3WV2s0C/cqQs8LoAeWjqFG+urduHpIJ/1i8Ds505xPbMpZIVoOzOsWrf9TdF1aVk+J0FKiWr4l3ZWwfgdwBqBgScvC4BrKFsTAVeWP7uQ5dU32w7eM2sZ8eHMxvcxz5Z5tk+KMMMdeJC5de8nbVTYys7Ua+8OkQxpeKlso0OUOkUXLOyZjkvy3uzpHCRon3HynJDNReX31UsiThc2TOv9z75kufhbAnHUflCEdtUFVsy8N6NVxV2wbm5s6YKXyt8UflFhXuUjIcgpS9XG4zx3SuB+NJd99omJrXOFc20yfTW0emhimYnlzoW2y5XV/XTvni/kqOiqTOqaxIHLp4DghW/GbCpyC1CFdRngoBrk829Ozbynpk7O0cniXWTa/DLCh8HWPleujG+A1H83jI1dmUPmSNUDunIBb/OeqLuMyDK7TIA4Xg63hVwcMmk4pGR8v014Ds71tW/4qViQBWbYj/qXQGqLGmo492x3L5svhkdAkw7u3FyOp1ncborm9Jrdmk2AnJFWfGRyVX5kgOd6juTnX9n+YbJ5ZiM1NrNAo8sF7m5V/aoeLIOsFB3eaoz1lrA5vhmebmLU3CM2difjYv9swJg31jk8sMMHsnk4La8/pk9BO2z7g6/ZfvVMz9Yju68GUt0CpOK3yw2ruwlYvD19fVSlPLT3zu2zDGps7ZK3k571r8rpDO8qPZ1/EDhq6y9Oz6L+Vk+fCp2Jqva7tLel/4qxc4USGqh11BlwBlYXZuYurK6gBj7mE/2z5Fz+A5w7Rgkrgc7a5YcOo7Nhs6v6EBAMZPgNpuNBKNOJ1lw7wYZJQO34YKSx8FvbJcBqaxInSn0FM9qvlnRNGOTbCuzgJxJvV7J+RjaHa61OtvEMmdFi9NLZn8uPnXWsRO3soQxkyTV2NkYyBv1oPi6V2O58dQclOwcc7t9u3Ov4hz/ZjmQr/LnLA4pnm6+2TxUjukAGDdHN45q52IbyobHM1CWyav00p1XBbi6/TOfrfw487kukHRzUf1wXFyH2K58qfKPWZyG+9hP1X43BvKKBzUyb3zbAMqL4/EfWi6/IZ9sjZ3e4yGKGB87ub6jP3Xc8c7iYYY5s/HUOqGer66uln3dd0xn887kmcnRWT5y8TTjmcXqju3MUJZDs3zOuZyJH5Y2G8u6tPfDlCqqwMYYtSO9CaoUukaZGT8GIzPJsrPAnQTV1a9zxG4fZdx8r4FylPiOQKUc2emGL1FyQK8DNDuk9OqAg5I5C5Bdf2AgMUuVLlRSzpIMzk3NL0uIa+eQ6cqBZ0XVv4Jr7H8tdWyr0l1V8HRj0Qw5u3bxQ/0hxQm6A4iifSWX29cFffvoyfka+0q2boekCoBmNFPAVbGsspVD2GcnjipZOv27he2bwhP78BjDA9C1uWVfuWbHiW/8ozFbxyhS1WW2qkh1xEUJ+3fw5z/iurrBs4sd+19ju44YJ+2Tl5lUnIvvTrGnxvl/UT+Mkf+JhPvY1mZx+D7YbmZfZvud+qJLa2yqXaiuSV5Ma5KjAhhO4U7R7l8BNCoFoF0hMUM8Xla0VoBS8ZwZX1EWlA4xTjeAdhxrJoDymipddhwzk33WFjoFguJdBY19gQHrw9lAlpgVz26xt9bmYnyWpfoTKqMMBFYJCeXp/MHU8c3OMTdeJ+lXxWA3Bs6Ci4yXkqsqKpU8Xf/s5p6sbdaf5d+XryrkZnTE9qH6uDjZWXuWY22crNo4qnAGy7cmjs7EmtCPmleGSdx8OnzcMfVHUCW72o+8svH2IWd3Dkdl46v1yuxa+UZHJzP4zs3ZrX3Hj/aJLTPxquLd9U/WcxaT1Bi8rocuAqu1zmRTv1387I7vxupgky4/1TbTVxfn7UPtQrW6NA5pX8ErY2OlubMh+D0LYqsF6crIvzvFyqGp61CzBVFVpGSJE78VcJqhbr+qWN1Hhuib/e7I1+HfKT6432wCW5M09iXnfy5Zd3wo05kL6B2/dOAzYk3Gg2XJ/ER9KpmqdVM+sG8s4vE6AGbNeF0QzONk96ki3848snXo+rzTubLvim8Vb7E/5sysSMnsDeVWfNi+u/Y7xuvvjc4KjK6uO8C7o1+m2bhT+WKWizvyuL7s59UYbwJoMnX1WdmM8pFOzFM62Ww29p7Ibh5042byM981hf7vA0d2xp/BxaFfF0Oq8dYWqU6mTvxUcmTUqYVmMWeF79bEOJajWo/ZPwT2pakzqhzw8ZgSDg2o67DuN/NFhWYGq7YZlGSUAatKRtyXJcoMQGd6z2TNDAuPdZ9Eq8BHBUodH/W76wiuyM1oJqlXx5weO0m/A947vJ2uOgG7axcZYR93b7DbtwYczRQFCLI7IIOB0FoQOEsOjGSgEkH8LHB2Mqix+Xflm9k6cJ+OjBXIr+au/MHd64XjrFnLLjAL/uwHHVAR2zNPDc/kmOmj7LDrWzw29g+aiYkV72w8Lkb2Jbdmat06AFHl01ldzYw9U1CoPip+deSr5tNd9+qPh6xP9MP+yq7ZZ4NHlTOrWDTGri+7AtrxrObDtAandUjNrVMghQ/O1BRrsdOh5tzh4+xI+YrLQWvHVnKsoQ6mdWuj8nb8Vn1mZNzrYUpuEUIQ/t0FgDMBebaQXBPUqu0qWWYgrQpMKontW5ypwJjx6ADRitR4HRDqfs+MfegArQAFH+Pt+N0BHmosxY/5oI/NFHdqnAyEzIINF4TVuneSasXLtVFysgxOf50xO+M63Tlbwf3qfqXu706MZllmgHbGj4+hTGvWUtlm6Mv5QqYH3J/5W3d+XfmzfDYDZDqUrX8Wfztjcv8KLLttbOd4qmIik6dL1bwrG8fChvvPyONAHf+u4mPmw/sA2RnK8CHKlPnOGrzjfKiKvdl3VYzN4srgE2ulipzMJvcF/kquGezi5sOx1uFXLlIPQWtx6hpZHPbLitJMx9narcHaKudVPCp5MgzYyauz2BdpVaHaSeaZU82M5YJ05VRj5A9ImQk2Xfm7gcIFaCXfZrP+H2AXVNGhlB4zPXCbNcangAbaTScgujGzOfw+knNFhw7OQarIyvSYAarK/yreGXWLn315bjb+ck8GlThG9UoAZbuHsCsFVHBsl+xRVpc8mVclb6cQOJQNu9jdaavk2W5fP/O83e6+fka9HkutZwWwsjXjcXgOGSBV8+vqqbs23bjdiQmxLz74kKzMR/gBe2pcHK8Tcyp7RfDseM5SFhu4jcNHCvAeWi7cvxafqTytCo+Z2JjJMmPPWbuq0Kz6YF/Fq5MvsM3R0VEZf9bEwmoua6gaa0anSh7GorO+cMj8y7IdkrJijWuB/xfUyQlqrZXfOz7oQzN6nnrqbzfoZBV2kFoYNcnZoD3j7E6emeP7BJeqSHNJt0POGDipdORW8rkAXRWIbBvqN29nCcHJytsq+O0bEDo2ngEnVYAcimYLvKqAmSmCkbf63RnH/Y59lbzZcTXfKkirWOTAWUaqGKraVgVRJndXnoxnlXwy3lk8cGtU6aaSuYqb1fjYrlNYdGVxRerMfFzh6HjzuLM0kx9im+O1yzUuJqixDh0nM1zRzeUdDMOFSpYPmDqxodr/JkGvWo9unFd0iJzczXsqz2T21SmCFT/8Zj1113dGJ1mBkZGzz5k45/Jg5u9djF/hSidrB2+ujStr7Fttd8epsJHi72R0+uyuA9cEma1n/bt08NfTVMCE22UK5SCviMGGAh9q/OpdnbNAv5pDtj8zuE4CV/uyfy06yVPRWkeL9jFOnPFwRSoDnY5xZ/qs2nf7rKFusdrp74qGNQGWizXlN8ouu+Nl86768baz4cr/3KP9s3d/dZOWkq0TD2I/36OktlU/1ivbD/evYmFVgDhQN0tdW+jI49qGrLjuXUCvxsnsLmtTxVQH6jIQVc2bx6/GzWTD7WqNXJGagSb1wJqOvqoHYq2lbJ0zoLfG1zprU+W8KoZWtq34ZnL9vmitr3IbtzYKUB9CZl47JyPvU+C+wnuz5HKDihmdwk8R5yVcE7R9vsIxkzWTa4ay+DrLp4u/cSyHoVz/GSxe4YZD20/VbrvdpjE6w0wVTRWqbqHXFAYZP9Vv7QLy/pnF6xZGFWXBR4ETd6M9k7pMsQPuO0UJ01qwmgFjlgMDHht9t1iJti7wKl3ypYKow1lnzwCo2scBrQrWmUyqkFFt4lttK34VVUVbVTQ4Pg6w8Twz+SsQrBJK1z+yJIUPiwieyN/1G2P3CeuZXBUfR5lPxvizwKtb1KxJns5+9gUxzAvHyXhn+lU2jGB2bd5YQ8pWOrEh21flRPb7zH6UPip7W1tcMIh2RXUWR1AGjtn7rpWSpVusZvHV6U7FWMV/n8JpDSDNchvzjP1qTZ0szn4cFlG/VWHWjRkOH6i5Iy7J5q/GybZVXu/i+o4vOlzGY2W5PfutvjOqdKj2udg0M66aX2WHlc9kPHE7k1NhnkwmRcp+Z7DiLK1+6m82eBecdoEw93HyxXcnUB3iyX8dqgJ9ByRn1HWGDNTPrEHmFExZUKmKLTUmjsdFCPNjoJTpNbPDjm72ASmY4JzdZknS8ctkrBJJl5zNueTCfTKeuHYO/Fd64LGd7NzP6a8reyabs8Ns3moea+KqSrRVTHLxVPU5RBtFzj/2WSvmz+NUPLpgWPnuHwodqghRfBnIZ3xYL063HUCUxYSO7MijirH7FqdOHtZFJ8925qT4ZjaL313brfxxjc6yAnKGMvtRvuDyWFXEdOXL4juP0S0GOsVHZruza5zpck18cXaoqNKZIxeTlX8o25uxwS4+d3NS7TKeyGefeDFDs3lyjRyb7aGi7Q3d0A3d0A3d0A3d0A3d0A3d0A3d0AHozdz0cUM3dEM3dEM3dEM3dEM3dEM3dEM3tJJuCtUbuqEbuqEbuqEbuqEbuqEbuqEb+oOim0L1hm7ohm7ohm7ohm7ohm7ohm7ohv6g6KZQvaEbuqEbuqEbuqEbuqEbuqEbuqE/KLopVG/ohm7ohm7ohm7ohm7ohm7ohm7oD4puCtUbuqEbuqEbuqEbuqEbuqEbuqEb+oOim0L1hm7ohm7ohm7ohm7ohm7ohm7ohv6g6KZQvaEbuqEbuqEbuqEbuqEbuqEbuqE/KLopVG/ohm7ohm7ohm7ohm7ohm7ohm7oD4r+fxPrAnqVE8lFAAAAAElFTkSuQmCC","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","import numpy as np\n","\n","color_seg = np.zeros((pred_seg.shape[0], pred_seg.shape[1], 3), dtype=np.uint8)\n","palette = np.array(ade_palette())\n","for label, color in enumerate(palette):\n"," color_seg[pred_seg == label, :] = color\n","color_seg = color_seg[..., ::-1] # convert to BGR\n","\n","img = np.array(image) * 0.5 + color_seg * 0.5 # plot the image with the segmentation map\n","img = img.astype(np.uint8)\n","\n","plt.figure(figsize=(15, 10))\n","plt.imshow(img)\n","plt.axis('off')\n","plt.show()"]},{"cell_type":"markdown","metadata":{},"source":["**ผู้จัดเตรียม code ใน tutorial**: ดร. ฐิติพัทธ อัชชะกุลวิสุทธิ์ และ Peeranut Buabang"]},{"cell_type":"markdown","metadata":{},"source":[]}],"metadata":{"accelerator":"GPU","colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.9.13"}},"nbformat":4,"nbformat_minor":0}