lesson3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# **Pagination & Authentication & dlt Configuration** 🤫🔩\n",
    "\n",
    "**Here, you will learn how to:**\n",
    "- Use pagination for RestAPIs.\n",
    "- Use environment variables to handle both secrets & configs.\n",
    "- Add values to `secrets.toml` or `config.toml`.\n",
    "\n",
    "To read more about credentails refer to [dlt documentation](https://dlthub.com/docs/general-usage/credentials/) here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dlt\n",
    "from dlt.sources.helpers import requests\n",
    "\n",
    "\n",
    "# define dlt resources\n",
    "@dlt.resource\n",
    "def github_events():\n",
    "    url = \"https://api.github.com/orgs/dlt-hub/events\"\n",
    "    response = requests.get(url)\n",
    "    yield response.json()\n",
    "\n",
    "\n",
    "# define dlt pipeline\n",
    "pipeline = dlt.pipeline(destination=\"duckdb\")\n",
    "\n",
    "# run dlt pipeline\n",
    "load_info = pipeline.run(github_events)\n",
    "print(load_info)\n",
    "\n",
    "# explore loaded data\n",
    "pipeline.dataset(dataset_type=\"default\").github_events.df()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You could notice that we received only 1 page, only 30 records. But this endpoint has muuuch more records in total. To get all the pages you should use a pagination.\n",
    "\n",
    "When working with APIs like GitHub, data is often returned in pages. Pagination allows you to retrieve all the data when an endpoint limits how much can be fetched at once."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Pagination**\n",
    "\n",
    "GitHub has very good documentation, so it is not difficult to go through the documentation and find the relevant page: [Pagination.](https://docs.github.com/en/rest/using-the-rest-api/using-pagination-in-the-rest-api?apiVersion=2022-11-28)\n",
    "\n",
    "It says:\n",
    ">You can use the `link` header from the response to request additional pages of data.\n",
    "\n",
    ">The link header contains URLs that you can use to fetch additional pages of results. For example, the previous, next, first, and last page of results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**GitHub API Pagination example**\n",
    "\n",
    "The GitHub API provides the `per_page` and `page` query parameters:\n",
    "\n",
    "* `per_page`: The number of records per page (up to 100).\n",
    "* `page`: The page number to retrieve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "response = requests.get(\"https://api.github.com/orgs/dlt-hub/events?per_page=10&page=1\")\n",
    "response.headers\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gotcha! We can see 'Link' in the headers. To get this link we can alternatively use `response.links`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "response = requests.get(\"https://api.github.com/orgs/dlt-hub/events?per_page=10&page=1\")\n",
    "# response.headers\n",
    "response.links\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **dlt RESTClient**\n",
    "\n",
    "The response includes a 'Link' header for navigating to the next page.\n",
    "So now we can implement a pagination!\n",
    "\n",
    "When working with APIs, you could implement pagination using only Python and the requests library. While this approach works, it often requires writing boilerplate code for tasks like managing authentication, constructing URLs, and handling pagination logic.\n",
    "\n",
    "More about how to build pagination with Python and `requests`:\n",
    "\n",
    "* [Link 1](https://farnamdata.com/api-pagination)\n",
    "\n",
    "* [Link 2](https://www.klamp.io/blog/python-requests-pagination-for-efficient-data-retrieval)\n",
    "\n",
    "**But!** In this lesson, we’re gonna use dlt's **[RESTClient](https://dlthub.com/docs/general-usage/http/rest-client)** to handle pagination seamlessly when working with REST APIs like GitHub.\n",
    "\n",
    "\n",
    "**Why use RESTClient?**\n",
    "\n",
    "RESTClient is part of dlt's helpers, making it easier to interact with REST APIs by managing repetitive tasks such as:\n",
    "\n",
    "* Authentication\n",
    "* Query parameter handling\n",
    "* Pagination\n",
    "\n",
    "This reduces boilerplate code and lets you focus on your data pipeline logic.\n",
    "\n",
    "**Here’s how to fetch paginated data:**\n",
    "1. Import RESTClient\n",
    "2. Create the RESTClient instance\n",
    "3. Use the `paginate` method to iterate through all pages of data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "\n",
    "client = RESTClient(\n",
    "    base_url=\"https://api.github.com\",\n",
    ")\n",
    "\n",
    "for page in client.paginate(\"orgs/dlt-hub/events\"):\n",
    "    print(page)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pagination type was detected automatically, but you can explicitly provide it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "from dlt.sources.helpers.rest_client.paginators import HeaderLinkPaginator\n",
    "\n",
    "client = RESTClient(\n",
    "    base_url=\"https://api.github.com\",\n",
    "    paginator=HeaderLinkPaginator(),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full list of available paginators you can see in offcial [dlt documentation](https://dlthub.com/docs/general-usage/http/rest-client#paginators).\n",
    "\n",
    "![Screenshot 2024-12-13 at 16.09.04.png](data:image/png;base64,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P1NIpk73TwK8qrxKYG8855NlnVcMAsly2VPyyfTLeaXPC2MQwDJBlS++1BgMUVeFCxeWp/v1kcsuuzRT1e3c+bs81r2HvDZ2nA1r1aqF9OrR3Z67BxhI17RZC2NE8vyx1BBmF5xbsaLnZX93794tkyZNlqeeflbWb9hg/bEfR8uWze25exBkEIAhYeKEcXK+Lv8TxtEgEIYSZUiABEiABFJJgAaBVNLMYlphDAKvjP5UXnv1c5PD0UcfJoOHtpCj9DeemzhhkYwY9okRwTIww0a21tHu+TJFmTH9G+n/3GzrD6U+jAf+UeVW4L8DKJQffnCKmZEAr8MPP0QGDW4mBY8/0i+qUz+jlwzyBLD56wsDm5i4nl+sXxoEYpGJ9vezjmUQcGNhKareT6QvxwT/3Lbsjnstue2YBoGs1di+9iG9NxRFySgeskY5+7GSUR7va3Wa/avfP1NIpk73TwK8qrxKYG8855NlTYNAssRSK59Mv5xX+rwwBgEo35997nlTGfnzHydz3p8lxx13XNzKwT4DTzzZx8hgENO8jz80M0b8kV59bazcd3/GDEoo9Xt2f8yM/PfLuueYJdC8ZWvBMlBw2B/qvVnvykknZR7IFmQQQBzMPHh3xtsmLs7jORoE4tFhGAmQAAmQQE4QoEEgJ6gmmWYYgwA25P3qy/QR/NWuPV1uu+OKhLn8+eff0qbVCMFSQnAY9X3JpadFxduu65ff0m6M7NyZvsTQpZeV0iVjwq+Vj7Tb3/yK/PLLLpPuhZVKyEOP1IzKAyd+JbUrcPU15eWOu650vQKPaRAIxJLJ0886jEEAiTz7zHsyS5fdgcOGxtjYmC7nCdAgkDXG+9qH9N5QFCWjeMga5ezHSkZ5vK/Vafavfv9MIZk63T8J8KryKoG98ZxPljUNAskSS618Mv1yXunzwhgEMIL/o4/TB7FhicfeTz6esGJ27dolF1a+RJcS+tnIYgNtbKTtuq1bt8plVarq3nvpM9pr166l+82lGx5cuVjHSPuKqlfLTz9tMyJXX32VDHtpSCbxWAYBCDZu1FD69e2dKY7fgwYBPxGekwAJkAAJ5DQBGgRymnCI9MMYBNq1HS0//viLSS1IsR8rm88+/V5W66arcGeccZKU8y3PM0WXixky+EMTjhH+g19qLvnzZ55FYARi/AclMpTJcNjTaeSYGzKl4SqpsWFyj1515IH7JtnNi7s9XEMqVS4ZI4d07z1tEMCo+bRVW03ml1cpLcVLFIgq36yZy2T9uu3G7+prygn2c9i16y+Z/f5yWfD5avlp6w6zlv3JxfJLCY17zbXldROtg6LScE+SWTIIGyd7yzUdd9wRUrvuWXZZIJc10g9rEPj2243S5a6JtkhvTG4fWF60V+w14e1XsXXLDil68nFS8tSCgs2iy5Y9QQ47/GCbTrwDbN6Mev1i0RrdHO5X2a37GoBX6dKFlNfpmn/6skVop9h8F67u9WfLscceHpXshHEL7b4ZjZuclyn/MTrD5h/NC65l60o6KugAw2/GjKXy3beb5Ged7XKctvuTix1nlrDyG86iMnNOsBH3wgWr5Yfvf9L77CdZu/ZnMwsHHGBUKaMsUD9+B2ZvTVtsvDds+EU+/milOYbsVVeXs+KYDRRvbw4wQTtMW7VFr2eH7gvxt87QOUpHLx0j2CQaexLEc0sWr7f7hlQ4s4hUPLeYacOzZn5rrgvlBCtsHF5C9xPZl1yiD2l8xA0ekr5Ze4H8BaRduxujir9hw48yavRo41ekSBFp2SJ9GvhXX30t48ZPkBUrV6qh8xezLnGp004VfARWPCf2PinJKIog++LgoVpff5r8MWUd6Ydx8+d/KnM+SF8DF2sof/nlVyba2WefFbVhL86vrRbbuIsRbxNff8NsSrxh/QY5+JCD5aQTT5Ry5cpKo4YN5cQTMy8XF6Z8kHHZ/vDDannr7XdM1OOPP17Trm+TyZ8/f9SavLHq9LPPPpcJE1+XtO+/l12/75Izz6wg555bUafhnyfFi59i00t0gNF+GCm4bNm3snbdOrPZX9GiReWcs86Sxo0bCjY9zq6bMGGirEpLX4KtcaNG+uwvLjt27pQ335gks+fM0X58o86IO0zXQy5lWGN/i8MOiz/bzysTlj0Ao3ffnanPmrUCBURhXVbhlFOKyXV16sj555/niUb9zpw5SxYuWmT88h2RTzp1ujXuDMDFi5donb1t5A8//HBdB/lWfT5vtvdLMnUaVZA4J/2eekb+/nu3kbiny91y4IEHmvcDtJ2PVUm0fMUKXTLxDzlF1wmvWPEcadqkieTLl/nZGpQF9syZ88FcU+9Yf3rVqjTlVkjfic6QM04vb9JD2wzrsC/J5MlTZc2aNUZJhDaIDb2hxEJ9wM2c9Z4sXLjQHF9zzdVxnx0Q+mbpUpk4Ue9HbeMbfvxRsJHlydo2q1x+mdSoUSPbS/gleh6agv73HxRn8z/9TNAOFi9eLJv0vimt7RXXWKFChajnjBsv7HGisrjPj1Q8m/3l+vPPP039oR7XrV8vO3fs1HfjsnJWhTPNs+V0bRMHHxz8DpPoOf/114vl7XfSn3eJnsEoF/IfM+YVU0SMJG7erKm/uFHnq1evkVdefU2WL19u2smJun5+6dKl5brr6gjWQodL1iCA+wp9weefLzDPld/1GVukaBGt89P0Pmuc1Nr8UPziGYt+ac2atWZNd6zPfpkuz4L7AA71f+bZ55rjAgXyy5eLFpjjZP/D5rO4b+Dq6vMPfZfrcvJZ7OaD46z2y/tDn+dnEXQexiBwyWVV9D06fR+7IMV+ULrww7N2+fIVJvjCCy+Q8/TdwHUvDxsujz7Ww3hhhP8Hc96TQoXivxu78XE8fvxEufuee403Zs8v+GxepjRcgwA2TH5l9Ehp3LS53Q/hpSEvSrVq1/iTjjpPlUEgqO1j6SM8a3Bvbtq8xfSfUye/GZW/d5Kq/ig7fYl7T1WuVEku174QbuPGjfoMHGv2kkB7KVCwgHnPalCvnpxzTsbG1d61xPvN7ntwUBnxvvGe7p01WZ9P63Q/Ciw/deqpJfWd7zRp2KBB6HfrpcuWmb0s0KegPvBOULZMGfOcw/M0bBvO6ntjPG4MIwES2L8I0CCwD9RnGIMANh3FSGK4Jk3PlxatLjTH2f3vvnvekG+WbDDJ1G9YUTd/vCjpJLEHwU1tR8km3XAYrv2tl0ut2hWi0nGV1DAIvDmlgwzX5Yxe12WN4KD4HPhiMzk2QHnqJbSnDQL9+rxr9kpA/vfeX00uu7yUVxTz+8hDU6wyFQaO0mUKyz2dX9ePoG1Rct7JiaqkveOuqsYw4/m5v2ENAi43LAH1eO/rpYgaIzznsoZfWIMANpZuVD9j1Mvgl1pEpYu0Fqjy+/ln35dtP2VsKg1/16Es3XvWESwHFc9hz4qn+85UhUpwWojf6bYrdJ+Mk6Vjh9eMAQLpDdRlqYqp0cB1rVoMt2Ua/WrbTEr4enUH2U2UJ03toGlt042+3hDstxHkkOdtd1ypL1xHBQUbv3XrfpZnn3pPpxJvjCkDw0jXB6sbRbsr5De+uGHuMYxMQ7Qe/A77eAx58UOdhrxUlWjphg6/DM6xP8fduqF44cLBdeEuK4ZNvps2u0Du7fK6rFyxOSq5J/vWi9luowT34EmsD2mvCN9//4OOCkufeXRqyZJ6L8/ygswvNo2rc109cwyF/KQ3JxpFy/0PPBgl551gLdg2rVvJ/ffdowrdaIMUZBIpirx0MKKtdZsbzWbH8LuocmV9Fg7VTd/DKTcHDHxRnuzdx0su5m+sEXabNm2SO+7sHLWWrj8RKGPr1bteHu/ZPbSy2k1j0RdfSN3rMhT/bph7XKJEcZk7533rFVSnLwwYJL379LUy/oOePR6T1q1a+r2jznG/9Oz1uCq0x5iPs6jA/06gXO58151RBooguUR+LVvfYDcthEIASsHr6jWUFarQDnJQJvfr01ugyIjn8BF/V+cusnLVqphi+BgeOKC/FFUDl+ugYL26WnWBUgYO6yxjveUgh4/Xa66tKSvVIAbX/bFH5IY2rSWrdRqUR5DfaaXLCRS1cGkrv5PVqmzv0uU+a8jwx8HHcY/uj8r119X1B0WdwzjTufM9pvxRAc4J6n7woIFW4eAERR1CodLh1k7mIz0q4L8TpNPl7s5y041t5aGHH5URI0eZkHi8oUS686675QM1WMRyMM491a+vXHrJxbFEEvoneh56CcAgekv7W6PWzfbCvF8YGvv2eUIN8xnvHV5YmN9EZUn1s9ktE4y9vR5/0o4odsO84zNOP11eemmwFDnpJM/L/iZ6zo8dN17uufd+Ix/rGWwT0wMo4es1aGS88AyYOH6sG2yP8Qx76OFHzJrpUDj5HfqnBg3qyWOPPiJz535o6hAyGC0N5Wosl4gH0q13/XXy5BO9dIDLobGSMf5jXnlVevV6whhAgwQvuOB86dP7Ccmvy8CkwiBw2+13yqTJU0xWA/o/J3Xq1I7KNqeexVGZ/HeS1X55f+jzgnj4/cIYBG5oe5Ng9hnc7bd1knu6dPYnk6Xz+g0bCwYVwHVof4t0feC+pNOBUvXiS6sYgxkiB713+A0Cq1Z8K48/0VsGvTjY5IdlkN6bOUMKFow9uCZVBgF/28eG2zVr17XvACgQDBtrfoh+n0hlf5TdvsRdDsrbnBnvg8/3f0EHLu0yTP3/Valyubzw/LNGee4Pc89T9R7sL+O993Qx79dv6v4TQe7II480m1O3aN4sKNj4/f3339K9Ry8ZPmJkTBn0vZhBU6P6tTFlEJCd98a4CTOQBEhgvyJAg8A+UJ1hDAKu4g7Kvd6qoAtaqz+Zy8Ho4lbNh9tR+v2ebhC4iXCYNDHLAKO44c46q6j0evK6qGiuktozCOAD5647Jsj3aemj8M+/oLg88litqHjuyb5sEHj40ZryxutfCkZcw+XLd6gcfcxhxkiCUeSewwyBF4c2D1Q0hzEIjBwxTzAaHg7t4HHl7Fe8u6whF9Yg8M8//0q9ui8KfuFeGNRUR98WMMf4b/TI+TJubPRIrkMPPcjk/9PWnbrsVLoyB7Iw7DzWvbYZJY9zv8OI+L69Z6oyO+PD9rDDDjZcftdZFkgPL+CYIdBX2+XT/WalzCAAQ8f9agjzZhzgPopoHfkNE7j25wc0MSPk/eWHce7Jx6ebEfleGEbSQ4G/c8efukTW71r+9BDs33H7nVdK1asyRq+tWL5Zut4/yQiAN0b2w+EFHRw8h5H+z73Q2Ds1v+D82MPTZOnSH60/8j5eZwaA12bd6BvLhXnumGMON/cVDFZ+5z5XYBCAoee9Wd/6xSQvGARuu62j3HjTzdr+/zH1UKJEcTP695dffoniEWvjukSKIiSCkZhtbrjRKuMx4gmjxsKOEEcaQ18aJk8//QwO5c+//rIKboxoPVRHpXmuYcMGRpnrneMXI45atW6ro703WW8oeaBA/ksVwT/+uCHqnqxQ4Qy970forJf8Vj7MAT4Em+jIOLi/lSeuGw7KpSMcY0rx4sXlnbenmjD851eO1FRlFpSlcIhbQuUxWnnHjh3GD//hnnn6qb7SoH496+ce4MPxZlVwzpnzgettrgnlwuaErotVv65MvGP3Q3zYy0NlyNCXzOhRxMEMBCgF1uqoMVeph/qf/f7MTIp8Lx+MgOzY6faoj2AYbU7Q0ejuhoeQx0h3GCL8o2XxgXr7HXeZJDFK8v33ZgaOVMMazljLGQ4K6FfGjDKMs1qnJqEQ/7kGAYy+hBFlnc7igCtYoIAZBQjDBkYceg51D6NALIMQlEtQ4HvtD/HADe3oFzWOYCkJ9DNwWH+6T+8ndQRffXPu/w8GkibNWkbdOwcddJAazU8ybXO9zrL5S+9HuMd79TAjVhMZBDDTAutTY6aB66CI3rR5U9S9iLzQzhMZQNx03ONESnjIYhTsAw92s9eBdoJZAUcddbQs0NkOLvvC2vbemDguqdHjXnkSlcVvEMjus9nLt6cqq71ZY54flHO4JzFLCjN5PIdn3pAXBwmU2K5L9JzPCYMAjHTtbm5vno9eWdD2ca8fe+wxsh6zHP57jsFYg9kC7Tt0NKLxDAJ9+z1tlGtemviFsTuf1jvuDdfBaD561HBtC8GDJPr3HyB9+j3lRjHPOxiztmzZItgwFg6KyTGjRlhjfXZmCCRjEEjVszjqAp2TrPbL+0Of52CIeRjGIOAqVzFz7/UJ4wLX6o+ZSUAA2t55F1S2o/Qx8CNoE+GAqJm8MMsAsw3gLr6osox97ZUomSCDAO7dWrWvM+9eEK565RUyYvjLUfHck5wwCAwZPEj6PfW0nUXh5YdniGsQSGV/lIq+xG0PMAjkPy6/DjbrZYqPGRiYQYd34B91Rp37PlWmTGlTN3hvCHKpfA/2lxHf+/CDQxmL6awvzAJz30EQFmsGDJaluqndzdrfLoKYefcqVuxkM0Nvjc4KXb58hX1nQXjHW9vrIKX0mSs4d10q3hvd9HhMAiSwHxPQj6E84777bnnk7nvui1Q878JI0WIlzC/O4b833Y4df0RqXtvf/qlyMFNxdESxDYdsq+bDIrrMSuRf7X2y6r78Yq1Ns0mjodlKa9HCNTatppqW36ny1YZfV3ugDf7h+62R6+sMtGFvT1tsw/wHH8xZbuUe6TbFH2zOB/SfbWXGjJofKBPWs2/vGTYt5O13D3ebbMNbNhtmjoe8ODeyatUWy3L37r8jujRMpP71L1rZJ3q940/KnN952zgroyO0M8moQt6Gt7txdESXDMokAw+XNdpK2CaiMxts+oiHduk55FW31gAbPmjAnMjKlZsjqtD3RCIrlm+KdOk80crc2GZkYN5btvwWaXD9YCt3Q6sRkXmfpEXJqkI9MmL4J0ambeuRkeZNX7byujSPzdM7aKn3g3cP6WbXnrf9ddsY6gptEPWy8cdfrAyuF9dVq3rGvTht6tc23DsAz/btxtj87r/3jcjir9dFdLkoTySiy0VFnnl6lpVBmm5eVlAPPp3/vZW7Q9tAIvd0v5lWvlb1FyLjxy7QuvrTRsMz4aMPV0Zatxhu5cB41+8Z5fOEJ4xfaGVw34Kh7ikSmTL5K1OfaL+//fZH5M8/d3tR9plfVfaZ5zie5TqyLFO50tK+t+GXV6maKXzRoi9seNnyFSKlypSPVLro0sj06TP0HvrZyiOdRo2bWdlTSpwWWbp0mQ33Dnbu3GllypY7w/O2v/pBENE1cq3MDTe2i6gC0YZn5UBHEdn0cBzPIX9wAC/8nV3x/MikSVMiqGPP/bZjR2TIkJcixUuWsnI339LBC87Sr36U2LSq16wdNw23TiucVdGU48qrronAXxUKNi7416pznU0XdaJL6Nhw9+DhRx6zcsVLnhZ5/vkXIku++cY8o/VjPfLZ5wsiD3TtZmXABlyy6lq0amPT8t41VJFg8tSPVpMs6n3UqDGRMuVOt7KqwAvMUj8mo+Sur9cgosvoRNRQZeR1+nxEl/uIVKp8iU0LzHBtfoc8vPpH+/M7nX0QKXlaGSNT7vQzI6rk9ouY82TqNDCBAM9TS5W1Zbu2ei1zjPtaZ1ZESX8yb17kmmo1rCzqNOh+xHOwypVXW7mGjZpG5s2bH8F96jmw69zlHitz8iklI6qc94Ltr47Yi6DteuxKnFo6Mmz4iIgqh62Mzm6IvDZ2XATPEoRXr5EhP3LkaCvnHZg0HRlVWkV0KZiILmVlRHAvgrP77FGjSUSVNl4SSf2mpcV/HuL+QblxjeDwWI+eUc8nlFeNQpEqV1xlOeDeyopLVJZUP5tRRjWI2XLjGm9q117f1dKiio98GzRqYuXQJ2zfvj1KJtFzHm3Aayf33vdAVNygEx25bOV1JHOQSKT/CwOtDNLudNsdUe0UbR3PSF1yxcjh/vfKEOu58s706VYGsjr7KKLrt9s61yWJImo8sW0CMropa2D5Pl+w0LQZL88ateqY56orjHu0WYtWmcp31jnnumJJHYODl+fkyZmf2al+FoctXDL98v7Q54Xhgv7Kqyv84nnpd+59Dxk8E+d++FHE6zf98mHOP/zoY5sv3imyk9bcuR/atM48u2Km7Lds3WrD0Y96Tpelibj9m85U9IIy/aIde5xatrohU3hYD7fto6xIU43PEV16MZKW9r1579OBITa5VPZHqepLBgwcZFlcdc21EbznoX/FM9Z9d8YzWpccjHoGxXrupfo92C2j976H5xzeU5AXHNoc2mHliy+z13NhpYv1m3GX5e8doM/w6v/iSy+PqHHcCzK/W7f+FNUfoM9Wo1eUDE5S+d6YKXF6kAAJ7HcEYGnME27ylKn2Ies9bN1fhO8tF8YggLK5ikBP+QnDwNAhH0agkNeRw0ldwuz3v7XKQCijs+N0fwObFpSfu3dnKIqRrqukdg0CCJv05pc2ri7tElm/LkMZh3DP7csGAdTHS0M/8oqa6VdHXdtrhCyUrH4XzyAA44ZX5x1ufiXy0087/NHtucsacaDADuMmT8qoByjYXTd40Fybf+8npsdM89dfdkUp7xcvXu8mY451ZL1Nq/51L0a+V6NQLOcaQbzrz65BoHaNF9QAsSpWlpFnn37Plq/Tra9lkvvk41U2HMpz13DiCoN7t66TrOyrr3zmBtvjZAwCrhEPPMaPW2DT8R8sVwMN7jWPG4xVfucaBCDX+Y7xEdRhbnDuh3R2DQLoC6Ag15GrgZeOjyVdfsj2IY882j2TXDxFET4MPGUI8tJRy4EK20yJJvBIRvHQp+9TtvxQon76aXB7RJY6VdnKorwzZryboCSxg5NRHrt1inzxAeV+tLq5QBl7zrkX2HLqyDo32BzrdOlIseKnWhl8SMZyusyHlTv7nPOiFMex4gT5ux/iuIZ4hhoo8iHj/fmVj0hfZ5TYcCj6XMOImz8GNkCJ76WlyxS4weZ427ZtdkAE5KZOe8vKQKnoKkNRtlgumTqNlYbf31WYoGx16taL+uh35XWmQASKRO9agxSprsITSmzPgOKmg2Ncd9PmLW1azzz7nF8kAgWOlxd+x42bkEnG89CZKEZx4coHGQSgbPVkYBiCkSrI7dixM1Lt2ppWtlXrrCmJ0tLiGwRcxQaMELGc7r8RgWECZYdyBoaLZF1aWvyy+BWD2X02476CMtDjjfbiGkLd8kPR5D6rUU+ui/ech1yqDQIwWsEw4ZUdZYul1NR9byIwRnuy+A1SjKHOPOUVZHQJOfcSo45ff+NNmx4MRX4FFYTd9nnu+ZUCFVSQgwLMNeYh7z1lEEBe2X0W4xrCuGT65f2hzwvDJIxBAOnAMIW6cv9gGICBEgp5naUUJjsr88abk2xaMFRlx61evdqmhXvBb3SPZRBAnkNfetnGxf2clva9+mZ2OWEQAEsY82I9N1CKVPZHqepL3HRwDWAe7130iSd7W8aQ//iTTzIBTvV7sL+MuvxboKIfBUH7cQfbYPCR6/Au4j7r58//1A2OOtbZnvZan37m2agwnKTyvTFT4vQgARLY7wjkCYMAPpTdl4tYx3trpkBYgwBmDuj67VbB5yn6vF+MFu7Y4dX/DASrY37weK34jYmLbFqPPpxZmeLJhfnF6GOvHPjdqiOkXecqqf0GAe0DI13vf9PGh1LSHXnupbMvGwRubf+qV8zAX3T0bXSUtsdo+XcZIzO8CLEMAlAke/GgoMbo+XjOZY144JvIYQZAw3oZo/Z1aaKoKLrprn7k/Wb+/MaeKEE90b0XbHmnv7MkKhhGK1dJjZHs8RzK/njPd2x6uJ7sGgQwCyCe27B+u80PBgu/w/3qsQgade/Kz5j+jU0LM06CXDIGARhjvLbQq8fbQclF+b07IyP/xg2G6DMh2lDnGgTw/MgtxgBcpPshnQqDwLS34vPUjRJtPxKklIulKMJIOIz08vodKF9gYEiFC6t4wPMHihqvDDrtPWH2KKcnj4+LrLpklMdunSJvjLKK53Q9WVvGHj0fzyR6d5d7bTgUCvEcFIS1615v5RO1h1hpuQaBqldXiyVm/PGBjpFiHmcYMFyHUV5eWPkzzjKjvtxw//G7M2dZeRgPgtz7s2dbGRhUPEW5q8jU5UmColq/ZOrURkpw4BoEYJDRZQDixsCIO4wY9PjgY9t1uC4YDvAHpXo85147Rh37ne6HYfPp9tAj/uBM536DWpBB4KJLLrdpot7iObDwFL0wcAWNCIwXH2FpafGV8F27PWTLg9GW8Zwua2DZuiM148Vxw9LS4pfFbxBIdC8mejZj5oXXTqBcTMQP5fMMiRil6SrSYj3nI/85ty2lYoaAq0jEswJGvXhONxS214prDjIIuIbIeIY3Lx88Oz1+D3Z72PM2vzBkeWFQdmG2QDyH+xTPMi/OnjIIZPdZHO+a/GFh+2XE2x/6PP/1B52HNQjgfckdJe21E+8X96Xuh2MMBLrvSkyjsVcGV9Hduk1bzztLv+hHvHLg199HxTMI4B1Ml1G08fGuEWSUzAmDAIxwiVwq+6NU9SV+ZbvuJRX3MvBe3bhJxmxev6EzJ96D3TLCYIER/PGcLnNm24B/0Abieu0Lg3b8Bic3XfS73vuNP8+ceG908+YxCZDA/kcgTxgEsCyQ95CN9wu5veHCGgS8si1auDqimwFbxaCnIPT/YmkULCei64l7UaN+RwxLX5IF8Z7qm/URoF6i7pIyabpsjutcJbXfIAA5KFihsPSu4ZUxmS3j+7JBoP9z77uXG3iMZY6865v9/neZZIIMAmNf+9zGufP2cYEzC/wJuayRXyKDgO7NEGndMmN5GRgusORNVt1oZzbDa69Gj0Ke+0HGsk/NGr8UKgssx+Nxw292DQJzZmdm7y8IZqp4eWaHxZdfZizLBaNXkAtrEMB97C49tWxZfIWZlxeWA/OuZeGCaKWZaxDI7iwhL7899et+SKfCIBBrJLp3PRgZ6fUfl15+hedtf4MURXhpx0eoFw8fuq5yyUbO4kFYxQOWxfHKgBFIYcqAae5eHExLTnZknndJySiP3TrFB1HQlGovXfzq+su2jFgSxnX42D7jzHNs+NeLF7vBgccYaeVdc8fbbg+USeTpGgRiLbHhpuEai7CsieuGDM0YVRjUxl1ZHOMD0lv2BdfhXxLFk3eXSMLMCCgyTq9wtrl2jMaGwjeeS6ZO46XjhrkGAd002w2Keewq6sEqqw5LpXj1DqWN6zZv3hy1FAGWUknkcN+79eA3CCxessTmh1kdUFQkcmjfXhl189ZE4pnC09LiK+HdWRBY7shdDilTYtn0SFQWv0Egu89md6k23SMjVOnX6hJKmDGGP9eAG/ScdxNMtUHArXcsHRTGQfnttZUggwCWC/PCsURcIoeltjx5GJZd5z4zMXshjINRzUtvTxkEsvssDnNdnkzYfhny+0Of5113vN+wBgEvDSj73RlrXnvx/2KmC+4Lb3kWL773644a9yuIPZlkft0R3t8sXRoVNZ5BAIJQ4Hr9LK4jaGR3ThgEggZLuAVPdX+Uqr7EVbbDEJTofRDXhHbjtRG8/7nP7px4D3bLiFnEiZzuL2DLF2QwxvuXV/6gWa+J0kd4Tr03hsmbMiRAArmTwAEo9n68RYK5NH2B1Y02Nye8zEKFCsnCz+cnlEu1ADYJbdxgqE32zSkdBBvvJnKbNv0qCz5fLbqMiHy7bKPdJNUfr3iJAtLt4ZpywglHRwW5G4pWqlzCyEQJJHHy11//6Ia0g2yMYSNbR22c6250620qbIX/O/hw7grp/cQMc4aNWPs+VV/cjVD35U2FsWnsNdXK+y8p6nxA/zm6geYS43dLh8ukdp0zo8L9mwrrMlCCTYThypc/UR7tUVuOOCJj09CoyM6Jyxre1a5FuQ5wJMRsHLxx46+iyzNFtRtssPtkn3qZ2kpU5AQnr4z+VF579XMj1aLlhboRY8amfGPVf4yGw51TsZj06FXHHMf7T9fml0b1h6jxMl1q4OBmujFd9CanrVoMNxviQmL0q23lON3U2HVom2ijcEOHtdTNNI9xgzMdt2/3im5omb4Jnn9z5UzCcTwWf71eHrjvTSMRtNk2ArBBcfdHpxmZ00oVkmefb2SO/f9h8+3bOo413roXmIx//WbdADBxe7j/3jftZtctW1eSxk3Os0m7z4C6150l7W651IZl52Du3A+jNt+MlxY2Wq1W7Zp4IoFhqgw2G/Qi8Oqrqgo2DXSdKnLsxoWnliwpc2bPcoPF3bgSGx9+Nv+TqHD/iY4qFf34NN7HHnusLP5qUZSIf7PJrzX8Ft3MVpWnRq7tDW3k0UceMpuERUXMxol+6JlNa5HEze1ukoe6dQ1MTWcECDbEg8NGwW9PmxIo53rqh5So8UA3Nk3foPqN1yfI+eed64qEOlaFh6gy28gmytut09PLl5fp76TfF7Ey0ll9omvLmuCSJUvIB7PTWcNDDRqiIwlNGDZc/m7ZEu1XMzbsNgG+/3Q6utykm3fCYTPVmTPe8UkkPnU3Fe7b50lp0jj4fvZSUuW8qILXnHZ/7BG5oU1rL0h0/wZ5Z3p6n9j5rjvkrjvvsGGxDnT5DruBITYTrH5ttUyiaKvVqtcUbCKIjQVxrboUjJHDfYT7KZ5Lpk7jpeOGuZsKv/D8c1K3bm03OPD4/gceFB39bcKuq1tH+j+fvhlyoHAcz3nz54suk2Mk/JtFfvbZ56JLzJgwbLi67JuvzcbEcZIzQTVr15Wvv15sjnv16C6tWrWwUXQGgej6++a8cqVKMn5cev1bgYADd0NLtBG0lWRcoufhct2sUBXJNsny5cpJ+/Y3S7Vrrtb3juj+1Apl8SBRWVL9bFYlnOhSW6a0w14aIldffVUWSy7if84vW5pex16Cqd5UuFz5Cnaz4zD3JsrR6fY7ZPLkqaZIQZsK6/JJossomfAJ416TSpXS+zXjEfCfKnNFlWs2BH0f+kC4tje2s31cu3Y3ysPdHrRysQ5wz+LehdtTmwpn91kc61qC/MP2y4i7P/R5QQz8frj/cB96btWKbwWbriZy2Fj+/ffniM4Ik4WLFpkNqoPilCtXVl4a8mKmTc7dTV+v0WfZy0MHB0UP5aezFwT9lOfmffKhFC1SxDuVoE2FbeB/B1OnTpNbO91uzg7SjezffH2inH32WVYsJzYVxjXj2mO5VPdHqepL3Lrzv9/FuhboeqDz8dzcOe9LiRLFzWlOvAe7Zax3/XXy3LNPm7xi/efWL97N8I7mOjXgiu4RZbwOPPBAadu2jTRq0MC8o7ly8Y5z6r0xXp4MIwESyN0E8oRBQKdxha6ltavTQsumSjCrBgF//ps3/yZfLFor8+elmV9ddseKnHzycfKMKhoPOyxDITJr5jLR9dKNTNlyJ0i/pxtY+WQPkLdu/mqjvTG5g77sZRg1XCV1LIMAIvfrM1MVd9+ZdIoUOVaeH9BEDj30IHO+LxsEoNiGgjueGzL4Q5ky6SsjksggUE4NAMuW/miTe7R7bTnv/FPsebwDl3U8OX9YWGPA9p9/V2XbJvnuu42yds022bHjL0Eb/n3nX3r8pzn20vYbBAYN+EB0M18T3LDRudL6hsqeaNxfV0GfXYPApKkdBC/i8RwU71DAw8UzCPyxa7foWv3KYpPorBhVOvyh15/OY6eywLnnsmsQgIHo4W7pitxChY4SGN3CuBcHfiDTpqYzr6VGqPZqjPKcaxBo2Fjro024+vDix/rVzcsERoEwrkyZ0jLr3elhRKNk3A/p7BoEzq1YUSa9OTEqff+J+0GbyCCAuFWqXC5z5nxgk/li4WdSsGBBe56Kg7CKBx1xLQMGvmiybNigvjz9VN9Q2UNBiI87uMEvDpQa1dOV76Ei/yeUjPI4UZ3684VCW2drGG//B+OHH34kOmLVRjnzzAr2ONbBmjVrraIsq4oq1yDwyuiRctlll8bKzvi7il6/QUA3EJYFCzMMT2GuwVNCI3G/ItotyKIvvpB69RupcTjjPaFxo4bSr29vVyzwOJk6DUwgwNM1CLw3c4aULl0qQCray1VkXHLxRWqIHhMt8N/Zzp2/y1dff6VGwK/km2++USP4z/KLKqh01otRFG/blm78hbjfIKDL1Yju+WFSqnjOOTJ50uv/pRr/xzX0+OuhT99+oqNabQLJ1muQktcmFuMgkRIe0Ya+NEy69+gZlcKhhx4q55xztlx4wQUCxhdeeEG2jZqJyuIaBLL7bM6kxPt4rhQtWjTqGpM52ZMGAR31bIyyXvnmhSw7nvV45sP524rOIhLd8NRL0ijLjjrqKHse68B9rrw/a4aUKpV+f+rSJ/Lll+nvtU/36yMNGyb+jsCzR2f3mKyy+pxFZF1+QyZNTn8nGtD/OalTJ9qImMpncSwuQf5h+2XE3R/6vCAGfj/3/QlhYQ0C/nR0ORRB3w7jvW44LGjPnjvttNPkramTogyYEyZMlM5d7jUiYZ4lXlpBv8i78kUZ/fnK5cv0+/RQKxrGIABhXf9ddDagiYf3lulvT9PBPYebc1dhfEWVKjJq5DDjn+x/ybT9nOiPUtGXuMr2mjWqy4uDBoTC4Bo835g4Xs4//zwTLyfeg90ydurYQe679564ZXQHnQQZBGDQaNykuaxctSoqHfRZlbTvRf97lQ7YKFigQFS4e5KT741uPjwmARLYfwjkCYPA/jpDIF4zXL9+u/R/9n1ZsmSDFety7zVS5YrS9nzhgjXyyEPpL9MFCx4pI0a3sWHJHnyj+egyRiZavnyHyLiJN0cl4Sqp4xkEoEzVdfJF17Q38avXPEM6dqpijvOSQSAKnp4ce+zhOnK8sUBpn8i5rBPJYnToSScdI1dULSPXXnu6HOsbWe/G36QzCnRDYFmxYrPrHffYbxDQpZVkxvSlJo4/LF5Cd94+Xlb+l+++YBDQ5XsE1/LBnBVYdi1e0W1Ydg0C77/3nejG4ia9c88rJo/1qGPTjncAYwCMAnCXXnaa3PdAhlKXBoF6hkuYD0X3gzaMQcAk7Px3wQXny7jXXlFjVLqB0wnK8mFYxUOXe+6TceMnmHweuP9eubVD+ij4RBm7o5Ue79lDWrZsnihKpvBklMepVI7oZoKiSwRkKk9YDzwb1/wQ/VEWJm4yH+JIL55B4JLLqsjq1WvCZBsoc3fnO+XOO24PDIOnmzcUGzBahVEOJlOnMTP3BXgGAYyKW7n824RGW0THqNFmzVualDBC9N3pb0elqksMiE7Llyk6KlOX5YkKi3XiNwhAcQMFDpw/LFYa8HfvTb9BQJdpEowkz6q7qHJlGTf2laSiJ1LCe4lNmPi6DFSFsl8h4YVjRGz9+vWkZYtmUrhwYc87qd9EZUmlQWD9hg1SqfIlpnxQui3/9pukyuoX3pMGAbfshx12mCk7nkuJ3MyZs6TtTenv4H6DwI8/bpQLKl2UKIm44RPHjzWKKQjp2uOydu1aIz9l0hvGeBQ3sgbu2LFDdKksI0aDQPyZjn6W8Yzge6vP85cx6Nx9f0J4Vg0Cbtppad/Lvfc/IJ9++pn1xiwxzBbzHAZloE+GCzMT1IsX9OvOFkM/uXRJuiHMkw1rEIAh+uprqgvub7iWLZrL4716mOO9YRDIqf4ou32Jq2zHewzeZ8K4evUbiu5lYkSHDhkk11ZLn/mWE+/BbhlTYRBAoTEb+dHuPY3RCwZtv8OANhiLMPs0aOZHTr83+svDcxIggdxPIE8YBLrox9e4EB9fjfXh2k+n+O9pl6oZAv5y6ybEcudt42WNjuKGc5XrOMeSMTfdMAqHxg0a0lwwkyArbvTI+fqBusBELVW6kDzzXKOoZFwldTyDACJhmZWu90+yilZvdHxeMwhUOLOIbN70my698ms6V11Opne/+lEzL6Ig/3fisobXi0Oby/8CPiJRD/kL5NPlD/4XlEyUH5alwnJOv/2WPuIdyR1//FFyks7iOProwyTfkYfKkfjLd6iOoPxKtm3baeL7lf5jRn0qui+CCbvo4lOla7f0JT2iMvOdYKZLg+uH6NIl/5iQvW0QgGGkZ4+37QwCFOqYYw6XIkWP1aWK8imHQySfcgCPNJ1loBsnm3Jn1yDwycerRDdYNmmV0raAGT9hnG5KLa+OSf9guuqacnLnXVVttJwyCECxqxuu2XziHUC5DqVFsi6R8nhPKp1QdldR5F1L7Vo1zXIKGOkJ17pVS207j3nB2f51lY7xlgzC8iQYTQ13y83tpNuDD4TKG8uoYDkVuGee7icNVBGYrEtGeZyoTv15x1OOYNo1DBqea9E8fUkY7zzWr64RrvdvPhP8xOPRo6VjxXH9U2kQcGdoYLmls85MV6K5+fmPoWw78sh0w3HVqlfKVfoX5PCheW31WlGKXyz3gWU/Erlk6jRRWl64ZxDA+ReLPo87As6L4ypP/KP3oaS8qV17u3wS4kD5WLJkSSl0/PHabx1t/o455hhZunSpYCYAnF/pr/sLiK5Bb8KCDIEmIOC/ho2byvz5n5oQv0FA11CXkaNG21hh2qZbryVLlAhVTzYDPUj0PHRlcYxR3JMmTTH3P5bm8hu+oVwb++oryrOEP2rC80RlSaVBwK+I/Gbxl6beExYyhoD7nD9SnxM5uWQQZrKcefa5piQwBCz7ZrE+m46IUbIMb3fZIr9BALNhdN1+K9y8WdNQMz7c9tfuphttvWPJNrQPuBHDX5aqV15h0451ACMnlFZwNAikziCwt/o8U5EJ/vPfh6kwCCBLvFvVqFVXByqlz2R0lesIX7NmjVx8aRUcGjf7vXcFMwmy4vr0e0r6908fpX7WWWfKtCmTopIJaxBAJLxXNWnawhqqR44YJldeUUXcPm1PzRDI6f4oq32Jq2zHYBQMSgnjqlxxlaxKSzOiY0aNkMsvv8wc58R7sFvGVBkEvGvEPTN5ylR5T5fdhIED537Xof0t0vWB+6K8c/K9MSojnpAACew/BPQlf793+rJqN2nxNmsJ+oXc3nDJbiqcTBl1zXq7oeit7TNvRNdR/bwNRydOWJhM0lGyHTtkpDNON8L1O3ej26BNhf3yLw/9yJarRdOXI7/8siuyL28qjI2eE7nBL8611zRl8leZxN1NhdVQoxtE/hPRJXkiDesNtvGe6jszUzy/h8sadRtiv0J/ElGkqUhFAABAAElEQVTniI8NgL120rf3jMjmTb9GybgnuoeAlX3tlehNhae/k9EedYkpN1rMY12Sx6aHMmR3U2FsNprI6SwVm+f332+NEn+859s27I7bxkXibe779VcZGyJ3vS97mwov/WaDzRebHofZiBIFVyOCjTdi+CdR1+JuKuwPixLcB09UKWmf60Ebrqalxd9E0924EpuTJnLupnjYrMzv3M0m0b+89PIwI6Kj9mw54T9u3AR/1Cyfh9288Pn+A2wZsOltWHfm2RVtPGzWlhWXzAa0ierUn78qFm35/Bu66Wg+G6YjYv1Rc+zc3VQ4DLNHHu1uyzls+IiocmGDW+9dRZV8UWHZPdHZATZtLw9s7Lti5cqESSdTpwkT+0/A3VRYR/6Hita7T197DToiOiqOrqNrw6rXrB3R9aejwt2TT+bNs7KNmzRzgyJpaRnPEXBau25dVHjQCTbtLlvuDJvmyJGjo8See76/DUvFRpdRicc4SUvLuI7Lq1SNIRXsrevNR95+Z3oEG22fUuI0W3ZsgKgK8uBIcXzT0uKXJdXPZl0ix5ZZjTRxSpY4yH3Oo479zt1UGBt2J3Luhta6V0WUOPp4bK7u3Z/x2rAb0X2m+DcVTk+zlE1z9erE765u2v5j3C9e+V4YMMgfHHg+ffoMG2dPbSqc3Wdx4IXE8AzbLyP6/tDnxcAQ5e2+P6G9qEE6Kjw7J9hk3WuDqgzNlJQarWz4oBcHZwoP66F7Etl08E7ld4k2FfbL64AOm945514Q+emnbZGc2FQ4Udvfk/1RMn2Ju2Hv9fUb+vEFnmNzabePWvLNN1YuJ96D3TLqkkQ2r1gH7rOv3c3tY4ll8sc7BTaxfv75FyK6TKZtN2j3g4cMjZLPyffGqIx4QgIksN8QwKifPOHUyhr1APVeHrxfhO8tpyPArcKuTs0BmRS4ixevj7wy5lPzN++TtKSKuXDBapt2y+bpCio3AVd526bViMgff+x2g0Mdf/75DzYPKGzXrt2WKZ6rpA5jENDZDRHXyNCz+1t5yiCw/LtNliHqvFb1/pbx5Elf2rCgA5d1KgwCrkL+9k5jI//8oxaCOO6Zp2fZsvoNAlu2/BZ1LatWbYmTUnrQ8Jc/tuntbYOAzlKINKqfbqBBO9aZEHHL/96sZbbs2TUIbN26w6YFDhs2bI+btxd4S7sxNt7bby32vM0vDQIlTL+QEwYBF/Rj3TOUr1BO6QhYNzjLx2EVD65R4vwLK4fKT6ctR/WZuoRIqHh+oWSUx6lUjqxfvyGq/Fu3/uQvWo6cp9IgoFPc7TV07fZQysoLBbjurWTS1lkgkdffeNPmo5vhRnQj6bh5JVOncRNyAl2DwJChLzshsQ9vuLGdLbeO/rOCMPrqkiQmDPebrstrw4IOdGkDm47fIAB5Hc1swz1DX1A6nt/s2XOsPN4x/QYBl/cVVa/xouXob1pafCV82Mw/+3yBbTu4Nl3HO2xUK5eWFr8sqTYIVLnyalsfOlPKliMrB4kMAm7d3tjuloRZuAYEv0EAkStffJkt+6uvjU2YHgRwT3vfNn6DAMIvvvRyGz512lvwyrLr3OUem5au6R8qnWeefc7GoUEg/sAGP9B4RvC91ef5yxh0DkOq1yZh5PIPaIGh7ulnnjV/us56UBIx/XRZIJu2LhGcSe6pp5+14RdWujhLRsz3Z8+2aeA6gt6HkjUIwCjiGhl0RtteMQi4z6w91R+hkhL1Ja6yHf15GLd4yRJbT3jH2bYtQx+RE+/Bbhlz0iDgXvtff/0VaXPDjfY6dc8ANziSU++NUZnwhARIYL8ikGcMAqg1zAC4Wz+wK553oXmQ4hfnOTEzAKOKb1AFO/5u09HG8UZpf/nlWquwa91iOIoa5T7+aKUNx0htXb88KjzeyRBnVPo9d0/MJArlPYwQUDDiT5f+ySQTzwOK+3Y3jrbx77ojeBSjq6QOYxBAnmAIWa9s7u8j3aYEFmtA/9lWfsyo5K7FnyBGwnt5YnaC3z3cbbINT/UMAV0vPyq70XotXllQXxh5Hsu5rBEnXtuLlYbrP37sApv30CEfukGZjpFXy2bDrLzfIIAI93SeaMNxf6C8sRy4u8YQXM/enCGgGz3bssM4ksj1fmK6lQ9jEMDMhHju9o5jbXqYbZHIwQBTu8YLJg44wqjgOhoEcsYg4B85CgWlq6Q574LKESjcs+tcgwBGhcZyuvRE1EjTtLTvY4la/0mTptgPDv/oeysU4sBVHl9TrUbcGKk0CCAj5OcpId6dOStu3qkKTKVBwB1NVr1G7ZQU8bcdOyK6prrhAmV5Wtr3Jt2mzVtaVhgxGM8lU6fx0nHDXINAy1Y3uEGBx7gOjKr06hdKeM8tWLjQ+ofhdmun2618kEGgd99+NrzEqaUjmH0Sy2GGxekVzrbyKJ/fIICRoN4oxmLFT9UZkL/ESi5l/mlp8ZXwyWTkGmKgbEvWpaXFL0uqDQJQ1HjtJMwMKcx6gIHp/gcejMAQ584qTGQQwIhULy/MTEnk3NH8QQaBB7s9bNPr0PG2RMkZBZhnDEM5ggwCbp6P9eiZMM14ArrUli1fpYsu1UFFf8QTN4rgeg0a2Tj7u0EgXr8MULm5z1u27FvTl6A/qXZtzUxKfrchuDNhggYlYAaSd9+gTSRqR27a7my3oJHkUN67M2369H3KjZ7wGIp7d1R2rTrXBcZJ1iCARMDQncHkMcBvmH4wsCDqmcx7yN7oj7xyx+tLXGU7eKBfSOReHDzEtiPd8DxKPCfeg90y7imDAC7q68WL7XUWL1kqAiOB53LivdFLm78kQAL7J4E8ZRDYk1WI5V6wrIenxMVyH7HcoIEfWLluXSdnEoPCtG6tDKX929OiR/lmivCfh+5NEMGsAK8MGGkd5NwR2FAeznx3aZBYJr8//9wdeeyRqTZ9xPUrsr1IrpI6rEEAcd984wubvncd+M1rBgGMpnn04QzWMAzFWrbHZQ1W2TUIYAkoj32fJ2d4VRr4i9kMnix+gwwCUKrXqp6upIbM3XdNiOim1Doq9R+b5vbtv0dmzlgaub7OQNP28euluzcNAu6yPTB8xHMbN/6iswmG2HLHMgi4ywo1bRQ99dOf/vhxGcaZBtcPjuj+IH4Rew4lBgx0HjcYYvyOBoE9YxAAd4xQx+g074MPH667dyc/I8utQ3fk2y3tb3WDMh03b9na5o1RafGW+tB1d6OUmlCIZtW5y7FgCaJ4LtXKEUyv9nhj2aCNGzfGyz4yfvyESI1adcwfRrFmxSXzIY70XeWcf8kgKEXcpWcSKep37NgZadailSk/Rvpv2pQx08y7lru73GuZuOnpfgwRTymPD0xMT4/lkqnTWGn4/b28vfoa+lL8WQJQdHqyZctXiPog1vV2bRgGfsRzutdApPwZZ1n5IIMAFPbeQBLkCYUVRrGCt+d0A+MIRqrqJqsmLbfe/AYBxNF9CWyeuDddpbOXpvur6zzbton7JFmXlhZbCQ+FF0YcwiiEsmAUcjyH5Zk89kOGvBRPNDAsLS12WRAh1QYBtGWvvPj1L7GAPF2nG1FbeSyT5LpEBgEoZmA0Qj4w+sRbkgfPo9JlT7d5BRkEMAPDLTtms8RyWFbCNewhXpBBACNzvTRRVihr47mlS5fZtgcFnutgmHPvXcwYiOfc5UlQhv3RIJBMv5yb+zy8v5QqU962JTx3Yzk8v7w2hz7K76BMR7/jyYwaPcYvEniuG/RGMCvAi/f4E70D5eDvyeC+RF8fxuG57o7GRlwoY4NcVgwCSAcz4ryyub97yiCAMqSqP0plX+Iq28EFs6Ww5FAsh3pxn0VBS5il+j3YLWN2DQJ4tuP5jT/MlonnXMOzfwBSTrw3oiyYgRT0ThmvnAwjARLIHQRoEMjBeurWdZJVxmHkL9bB97vFX6+LUvZDCRrk3PXnoUwdPGiuKnT+DBI1ft9+uzHSts1Im3/dWgMjP/lGB3uRMePAHeWPkcQjR8yL6Aaynkim35UrN0eN9IbScVgMgwMiu0rqZAwCUGZDkeopNb3fvGYQAMMdO/6MqiesXx80W8RlDV7ZNQh8/lnGklDX1xkUQdsKcu/N+jaqLSPvIIMA4qJ9eXXp/WKvBBiYMArenRWAe+LO28dZ+b1pEMA94c5aibV8E+4P7H3hXRt+YxkEMIrflZs/Ly0Ir/HDPY9ZFZ48lgMKuk9hQHr+2fetHJ4ZMLr4HQ0Ce84gAPZffx39wZLdZWDcqd5lyp0eV+GNjyV3lFyn2+4IXBoGCh6M9vM+TDEKGyOrsuo2bPjRpoU03313ZsykUq0cgbIAoxG9a4EhJNYHJdbudT8mv/zyq5jljBeQSoMA8oHC1Ss/frHESJCDctHNu1XrzKPs3ZH9WBrAHVWGNN01dsHKH+7lm0ydenES/brscZ1oqx9/EqyodEcBQta/LjTq2B11+fKw4YHZY3kBd5YB0goyCCAy2qarsEovY6kIlLhYs9fN767OXSI9ez1h6y3IIID25c0SQFp33X1P4P2Ij3tXmQWjGpRUybq0tPhKeCz3gnLg78qrrolA8R3k5s2bH8UhlnIsKK7nl5YWvyypNgggX9SJd31oW7H2qZgydZqVgzye2a5LZBCArG7WbdOA8STI+Lpu/fqIO1IeeQUZBJBeg0ZNbHq6+XamMkEGfb7bTrxrDTIIQN4dmQuDGu6FIPfVV19HLTHkv9cQp99Tz9jyId9Ro4KVubiHMCPGKxt+90eDQDL9cm7v81wDFGbkYbS53/mfGePGBSvjXeM42glm6eB9JJbDc8JdUgvGrVhGfzxH3VH+WE4Ge9DEeh9AnrgnsByL2157Pf5krOJEsmoQwL2LfsfNB8d70iCQyv4oVX2Jq2z32IBJ0HsJBty4bQH9Ot7//C7V78FuGbNrEFi1Ki1qOb5YRiv0J1iOzmMStIdaKt8bwRD7XeB9BX0nnvd0JEAC+xeBA3A5+88WyfvWlaxYvlm6dJ4ouua6KdgJJxwtlS8+VcqUKSyq3JVvl20UVaLCKGPCz6hQRLr3rC2HHHJQpgvR0f5y3z1vyA/f/2TD8ufPJ2dUOEmKnnycnKx/u3f/q+FbRZfaka+/Wm/zRYQOHS+XmrUq2Lj+g3VrfxYdgS4bN2bsYn/Y4QfL5ZeXkpOL5ZfChY8WnREgG3/8VZYs2SBffrE2Kokrq5aR2++8Ug466MAof+9k+/ZdogpSc3rwwQfKm1M6eEEJf7du2SEdO7wmYOC58847RR7tUds7tb8DX5gjb7+1xJwXKJBPChY80oYlOqhZu4JcWbWsFevX512ZM3u5Ob/3/mpymbJw3SMPTZGFC9YYrx696sg5FYu5wZmOhwz+UKZM+sr439LhMqld58wombtuHy8rVmw2fs/1byynnnZ8VDhOdES4dL5zgvyxa7cJA/fOXa6OknNZI2Dq253kgAOiRJI6QfsE/zWrt5l4B2hiZcoWlvPOP0WKFDlWvvtuk2nLaM/HHneEVNA2+eHclUa2RcsLpUmz8wPze33CIhkxfJ5t/34htKXmLS6Qho3PFR3pLrif4AYObibFtE26rlWL4bLtp53Ga/SrbeU4LYfrdLaO/PXXP8Zr0tQOMdupF+e2jmPl+7St5vSFQU2lePECXpAM0Db2zn9tDJ5gcP4FxaVsuRNkrd5HOgNClizeIDrjQarXOEPemrbYxD3rrKLS68nrbDreAW7/Ni2Hy0//lf/AA/8nlS8qKSeeeIzkO/JQadCwoidqfnHvPfLQVHt/H3HEIXLlVWXllFPyy6GHHmTu0TlzlsuG9dttvOvrnyM33nSxPfcOJqIOhn1iTsG5dZvKXtA+//ve+7NFR26Zcl59VVUZ9vLQqDLrKFfRpW6M36klS+q9PCsqXNfxlzrX1TN+51asKJPenBgV7j/59ddfRZcCMd7HHnusLP5qUZSIvqRLmXJnGL8j8+XTdpBe71FCejLx9TdElVPWu2+fJ6VJ40b2PJmDlStXStWrrxX9oDTRjjvuOLnm6qukUKHjpXz58lKrZo2o5J5+5jnRke/W7+STT5Z611+nbaeY9h+7ZfnyFaZ8OiLayPzvf/+ToYMHyTXXRD9jbAIhDvD8uKDSxdq3bDTSuK+vrVbN5Hn00UfLrR3a21QS1akV/O9AR7WLfuSbs5IlS8gHs9/zi8jsOXPkhrbt9H5Jv/8POuggOeecs+WiypXlpJNOFP0Ik08/+0xU8WXj3tj2Bnn0kYfseTIHLVvfIDpS3ER5ZfRIueyyS+NG1+UORBXWRqb7Y4/IDW1aR8mjblUhKJ9/vsD6n3DCCXLxRZXlvPPOlV9++VXQDt6ZPl37yN+NTMECBWTixHGCdu85NeqYtqJLVWl/cIC8PmGcnH/+eV6w+dW9A6Ra9ZqmHcDjtk63yr33ZLRVTziZOvXiJPpVRae+Y6T38U883lMe6NrNlBNtr9KFF2hfXlA2bNggM2bMlEVffGGTK1+unD5jJ+szPfq9qeuDD8noMa9YObSPqldeIRX1XgevBQsXyaeffmbaffPmTUWVmEYWXMe+lhHPJqAHOpJadCaO4FkQy9Wofq280P850WUpRA0XRqxXj+7SqlWLTFFUISU6itH6H3nkkeZa0TYP1PtEl7qQ99+bLev1uuEOPPBA7X+el5o1qts4YQ8SPQ/BVPdSsckVK1ZMLrv0Ei3PhfoOWFRWrVwl8/U+mTDhddtnN2zYQJ7u18fGCXuQqCypfjajXHimqaHTssQ9cLU+KytXutC0LTyf1Eggc+d+aC8Dz89BA1+w5zgI85wfP36i3H3PvTYe7sMaNa6VEiVKyPbtv+j9tVymTXtLduzcKa1btZSRo0Yb2Qu1nU8cP9bG8w7wXNZlSkQNQcYL7aCmlu28cysK+qJ1a9fJ1LfeEl1+RHDvt29/s6hBysgGXQMCdKSnXHNtDdm27Wcjh//KlCltnovly5eTdevWyzfffCN4JnvfKMjv1VdGy+GHH27j4AD3LdiuSkuz/ni2oF8+8cQTZcvmLXrvfCzvz54j6FP6aZ/XuUs6nwIF8suXizKebTaBEAeqeJRJk6cYyQF6z9WpE/1NkOpncYgiGZFk+uXc3ueh37yuXn3zvouLx3Pj2mrXmD4W99zCRV/I6/rO472jVNL7bfTI4XLYYYdlwonnKvo6tGPPFSpUSBDntFNL6t+p8pe+pyB86bJlMm/ePJsv5GM9Z7208Dxt3eZG/Y5K/26Df758R0id2rWlVCn91j25iN5jf5hw9A14Hriufr3rBe9rBx98sOttj7f+9JN+B6Z/7xxyyCGyakXGdVihGAdqZBc1wkf1LVdUqSKjRg6LESO+d7JtH6mlqj9KVV8ycNCL8sST6f1Ly5bNZcGChabu8f7ToP71UlKfq2ocMH5oY3ieem7ggP5Su1ZN7zTqN5XvwW4ZO3XsIPfde09UXv4TnVkoN92c/s5b/dpqMkTfr13n1hva2cUXX2T64PP1XQ/Xh75DN9GW1avT2zC+Nd58Y6KULVvGTcbcb6l4b0SieGfEOzzeD+Fw7y78fL7g/Z2OBEhg/yBAg0AO1+O4sQv05Wd+wlzKlT9RevSsI1DCx3K//vqHdH90mlG+xpLx+0P50qpNJamnCsFEDun3eEw/KlShmYyLp/T10nGV1MkaBJCGriUvfXu/6yWnipDEBgErHPKg9Q2VpWGjc630vmgQQOE+/miVPNHrHVvOdrdcqh/yZ9lzlzU8s2sQQBrbf/5dumvb0M2OcRroYMh6ss/1suDz1frR+JmRSdQ2YICa/OaXqoxbJ5s3/WaU3FCwn1a6kDRucp5RiiOhfckgAAMfDE8zpi8N5OB5tlejzylqSHjgvjeNVyyDAAI/+XiVPN4zo069NE5SFkNeyqxIglHgycenG8OiJxvrt1nzC6Sp/qn+I5OjQaCeYbInDQLIUEe+iW5uafLGhyOUQFBSZ8W5abnxmzVtIr2ffNz1MsdQUuIjy/tAzyTwnwc+lPs//5xR6sSSCev/zvQZcvMtmY3AJUoUl7lz3rfJ5IRyBInDKHBrx9v1ftlh8wo6gJKw7Q1tsmwMQJruB10qDAJIE0rI2+/srMrwjD4Q/kEOH8vIt3TpUlHBHW7tJLret/Fr3qypPPlEr6hw70SXfZD6DRoZJSAUj2++PiGwbYatUy/dRL+uQSBt5XfSt9/ToqOR40Y766wzZdSI4ZI//3GZ5GCQ7fpgN9EZFZnCXI8e3R81ilDd48N4xzMIQEBHHcorr74muhmrGoDXGQVO0aJFlHdpaXdTW1UwVzLp6EjShAYBCD7f/wXREXdW6WoiB/yHj/B+fXpL3brRSs8A0UCvREp4RNLZO3Lv/Q+ocTrd+B+YkHrivRKGova33GyMNrHkYvknKktOGARQFt1cWnRkvOio/1hFs/4db21vrhEKbNeFMQhAHoYeKNjiuZtubCswIOlMASMWyyCAQBiwYAD3jLVB6aKN4N6HYhKGK7hYBgGEQamENKEoTeRQthHDXhIYrYIclEa6HEeUMjdIrtuDD0gjNSSdeXb6u/b+aBDAdYftl/eHPq9//wHSp99TQdUd5QeD0pjRo4wSPirAOYGBqq3eowsXRQ+4cEQyHUJxet+9XeSWm9tlCvN7IP0bb2pn7id/WLzzLnffJXfcfls8EXPfZdUggIQnT54qnW6/w+axpw0CyDhV/VEq+hK/sh3vtHWvb2AU1BaS7wDvLHjvbdyooS8k+jRV78H+MmbXIIDn+wM6mGHq1GnRBQ44q3DGGQLDR/HipwSEpua9EQnDUKf7nlmDNAwBCz6bl8kwHFgIepIACeQKAjQI7IFqgoJU9wmQTc7oey9bKOnOPfcUufeBaoKRvokcRhO/N2uZvDHxCzNaPJb8IYccKOeq0hwjfjGDIKzTmYui68DL1Clf6yjn9TGjYSQyRtNjlHsxHZmcyLlK6qwYBJC+q6DPywYBsBilRibd7BeHOmrwf4IZCmfqCHQ4lzXOU2EQQDq6gbQMHfKRjgxYrR/Wv8HLOLThSy4tpR+WlaWwzoJ5dcxnoQ0CXhreL0aiQSnnd3d0GqcjebcY70FDmpsZMa7Mnpwh4OU7SQ0Zs95dZu5D3DeeK60zgNrqaPwzzjhJFn+9PpRBAHEh+9qrn5uZELt2/WWSg3FkcIBBAIGYOYP79N13l8pvasxznTfLoE7ds6T86Se6QVHHNAjsHYMAlJVNmjU3I5RRIVDivq2jnI8//vio+glzgpHvr7/+phqOXtLZYT+YEVOIF0/p++WXX4muV28UxLt1xJ3r8LLfsEF9VYy3NqP93LDsHM+bP1+efba/KuO+tiO5MGrbHdWfU8oRlHvdunXmmsfp6F3/CG8oFK6qeqXceeftghHn2XE5YRBAeWDAwajiESNHCZT2fle0SBFp1+5GU++HHnpoVDBG0WI0LRxG2n8we1bc0V26mapRekMeo5unvzMtcERnmDpFGmGc3yCAOvn4k3nSS0c669INUUkULlxYbrrxBjO62j9aOUpQT4a+NEzGT5igs+9W2lkikDn77LOkW9cHBIpOXEdYg4A/fdSLX2kMme49epq8cfx4zx6CEY6xHJS9w3SWCIws3ig8T/aoo46SJk0aya3tbzF15/kn+5tICe+lB2Vyz56P66yZz2X9+vVRhooTTzxBTi9fXm67raNUPCfxIBMvTf9vorLklEEA5dClQwQj+IfrfYSR3K7D6PrTzzhdoHiCoj7IhTUIIC7aHmbuwADhzX6Bf5GTTpIH7r9PR7TXMqNewxgEEA/PsIGDBmt7nhiVHpRgtWrVkK73329mPekGraEMAkgTRtJXXxursxTGRI2cRhja9ZlnVpDbO3U0syngF89hBOuIEaPMjKetW7dGicLg/cjD3QTGd8xW2t8NAmH75f2hz0NFY/aH7hOgRtK1UfWOE7zTV7n8clVePh/ToORGwnfAxImvy6DBQ/W5vcINijpGPwel+X33dTGzB6IC45ygbmao8RODMubP/zSmJPoWzArArD2/gT0oUnZmCHjpubNecG17coaAV4ZU9UfZ7UuClO2//fabGi0GmFlV3owplBtt7CqdkYRnFfr2MC4V78FBZYyXd6IZAl5cvLNh5ijavzfzE2Fo85jJdbnOPL3zjtt1RYn4eqPsvDd6ZcEvyvLMs88bfcM9Xe6WFs3TB1C4MjwmARLIvQRoENhDdYflStJUobl27TZ9qd8uh+po6gIF88nZ55xsluPJSjEwuhpKe10zXn7RJXkOUSX9sccersqlo41y+LDDDs5KsjbOjxt+MeXFyO0tqnyEEaBQoaPk+MJHyWm6nE2+fNFKBxuRB/s9ARgdvk/bIkcfc7hZMie7bS0eMHwcNKw3RD/k0xWXYye004+KfaftYfmmlXpv/+9/B8jJRY+To47OPBU63vUFhWF5rF2/79YlmA5PuLwRZizAOKB7EaiS4B85vtCR5j7NyToJKjP99j4B3Cs/qUIPvwVUuRWkqHRLiQ8qKP10szA5+JCDVVFVRO/nkzItv+LGScUxFPK6IasaQArGnH6finyC0oDCFde7fkP6snoldHTVSaqgS8QqKK295QeFmq5BrobZLWZ5qBLFi4dStORkebNbp0EGAa+8SHu5KvTRXk8pdrK20SJm+RwvPMwvPqqXqGHhf6o8xfITWF4rJ51rGBo6ZJBZJitRflA2e/djPh2JjbYJA87ecmCGJQp2/bFLypUtm+PM9vR1YsYA7qPffv3NKFlgmM0Jh2fO4sVL5I8//5CSumwQDFrZcbgP1qxZKxt+3CAnFD5BTtX2nEgxlCg/9BlYRgjLU+F+O7loUWMQzkq6MHijHWNpliN0pllpXY4Fhq286pLtl1PNaU/1eTB66WanamhbZZbiw4yVE04obJYeK6rtKSsObQjL92zeslXfbbYawzSeiVjuELO5jjjiiKwka+Ng2cEVahj0nrswAsC4XkRnfVVQ42BeXhYllf1RVvqSeMp2KLoxw+mH1T/oMmkF7RKUtmKTONhb78FhiohnBwzBaWnfG2MvlkmCATgrLrvvjeCEvLPSJ2SlvIxDAiSw5wjQILDnWDMnEiABJfDO20vMOveAcdEl6XtqxAPz1Zfr5MEHJhmRo1XZ/uq4m+KJM4wESIAESCCXEYhnENjbl/Lhhx/JXP2DO/308nJd3Tpxi4RlKbB/ibe8y3szZ4QaYRo3UQaSAAmQAAmQQB4hEM8gkEcQ8DJJgARIYI8QoEEgBzBPm/q1vDhwbg6kzCRJIHcSmPZOJ1vwGdO/kf7PzTbn2KwXG+0eozMNgtymTb/KPZ1f143v0jeLqt+wom4QepEVrVX9BXvMg5wjcMopBWTAi01zLgOmTAIkkKcJ7MsGAWyWesWVV5uZNxiROmHca2YplaAKw6jKm9rdYjekxPIFUyen7yMTJE8/EiABEiABEiCBaAI0CETz4BkJkAAJ5BQBGgRygCwNAjkAlUnmagKuQWD37n+kbeuRZqkrXNSxxx0hFSsWkzJlCwvW38f699hvAxvnvjtjqUAerkCBfPJc/8ZG3njofzQIeCRy9pcGgZzly9RJIK8T2JcNAqibm25ubzd19tauhrIff4ULHS9rdVr/ksXfyMvDh9tNebH57itjRslFlSvn9erl9ZMACZAACZBAaAI0CIRGRUESIAESyBYBGgSyhS84Mg0CwVzom3cJuAYBUFi29Ed55un3ZMP67aGg5M+fz2ycfIrOKHAdDQIujZw7pkEg59gyZRIgAZF93SCwceNGufue+2Tu3A9DVRfW2e3Xt7dcf13dUPIUIgESIAESIAESSCdAgwBbAgmQAAnsGQI0COwZzsyFBEjAR+DPP/+WUSPmydtvLbGzAHwiuhHdYXJl1TLSvOWFunnYIf5gnpMACZAACewHBPZ1g4CH+LWx4+SJJ/voDLefPa+oXxgCrrziCnmw6/1SXDcFpiMBEiABEiABEkiOAA0CyfGiNAmQAAlklQANAlklx3gkQAIpIfDvvxGzRNDatdtk7Zqf5Z9//pVjjj1CihQ9VsqVO8EsIZSSjJgICZAACZDAPklg2bJvJaL/4MqVLSsHHHDAPllOr1CbNm2SFStXycqVK41xoGCBgnLiSSdK5UqVJF++Izwx/pIACZAACZAACSRJYOtPP8nmzZtNrIIFCkihQoWSTIHiJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIIJcToEEgl1cgi08CJEACJEACJEACJEACJEACJEACJEACJEACJEACJEACYQjQIBCGEmVIIAcJbNn8mxQ8/ig54IAczIRJZ5tAJCKydctvcnyho7KdFhPYfwjs2rVLdv7+uxQsUGD/uSheCQmQAAlkgcC+9Dzcl8qSBZSMso8QWL9hg5x04on6js6X9H2kSlgMEiABEiABEiCBFBGgQSBFIJlMagiMGf2pzJq5zCTWqnUlubJq2dQkvA+m8u+/EXmo62T56qt1cuJJx0jPXnWl8AlH51hJ//o/e1cBH9XRxKfFHUpxS3B3CpRSKNLi7lrcKUUKxd2taJFC8SLFi1uBIsXd3d218N03s2E3e+/eWXKXXMjs75fce7uz9l99M7szb99B86ZzRfrRokaCyVPrei2vjy3hW7eeQO8eK4F+c+ZKAQMGVeCPw4+tkU3qM378RJg7f74I+aF9O6hTu5YV1br166FT567wEgUCbVq3gs6dfrQK9/TLP7t2Q8dOnUWyhb/6CkaOGObpLD769Jy16UcPAFeQEfASAiE9Hzqqhi+VxVE5zcLCwjw/ctQYWLxkiSh+l86doFrVKmZVCTW/rdu2Qbefe4j8ixcvBoMHDnC7LO/fv4e69RoAtYefXyqYP3c2pEiRwu10QjsCr3mh3QKcf1hDgMeM/Rbz9bnffsk5hBFgBOwhwAIBe8h4yH/xogOwc8d5kVqp0lmgdJmsbqfcr89qePjwhYjXqXNJSJnqM7fTCCsRfp28HVavPCqK26pNEShbLpvPFX3IoHVw+/YTUa627b+BdOkSBqmM+/69DNS20lWvkQcaNiooXz3++/r1f1Ct8hSRbrRokWHx0uZBzuPQwWvw+8xdcOH8PZFGmrQJTNOKHj0yJEgQE9KmTQhFi2WA2LGjmtL5uueM6f/A0j8PqWL2H1gBcudJqd754eNEYOCgITBl6jRRud49e0CzZk2sKlq2fEU4evSY8IsSJQocOvAvxIrlvRskm7dshe8bBZShZIniMOO3gLJZFYpfHCLgrE0dRuZARoARsItASM+HdguCAb5UFkflNAsLC/N8r9594fdZs0XxBw3oDw0a1DOrSqj5rVm7Dlq0bC3yL1e2DEyeNMHtsujtQJHbtG4J3br+5HY6oR2B17zQbgHOP6whwGPGfov5+txvv+QcwggwAvYQYIGAPWQ85D9pwjZY89dxkVrtOvmgbv38bqfcqOEsILUy5EaPrQ7pMyRyO42wEiEsCARaNZ8H1649EpAOHloJsudIHiR4r155CK1bBpw+pgTatCsaJIGRq5l7UiCwY/t5GDZknatZC7qIESNAoyZfQsVKOdyK5wvEf60+BpMn/q2K8uu0upA8eTz17usPly8/gJs3HotiJk0WF0+7sXobV9rM2UdBq9ZtYfVfa0RSSZIkht3/7IAIESK4knSQaHQGRUgJBOh05NOnT0V58+bJjQI+c+FfkCrkoUinT5+BS5cvi9T8/fwgY8YMdlN21qZ2I3JAiCLgTpuGaME4M7sIhPR8aLcgGOBLZXFUTrOw0JjnzcrhyM/XmUKeEAicPXsOipf8TsEwZPBAqFe3jnoPzQd31mVe80KzpTjvsIgAjxn7rebrc7/9knMII8AI2EOABQL2kPGQPwsE3AMyPAkECJm1a47Dxg2nIAcKFWqhwChKlIjuAeYGtTcFAnTjwOj+++8dvHv3P6M3NG5aCKpUzWXj78sehN0f8/fBsaM34NtSmeG7Ull8ubg2ZfsNbzgs+3DDoTJi3wTbgJ1zBJx9FFy5chVGjxkL9+7dg3bt2kDBAgWcJxoMitBgFJUpVwGOHQsQas+cMR1KoPoFX3MDBg6GqdOmi2I1b9YUevXsbreIztrUbkQOCFEE3GnTEC0YZ2YXgZCeD+0WBAN8qSyOymkWFhrzvFk5HPn5OlPIEwIBqv/cefNh4aLFUOjLgkBqA6NFi+YIlhALc2dd5jUvxJqFM/pIEOAxY78hfX3ut19yDmEEGAF7CLBAwB4yHvJngYB7QIY3gYB76ASP2lsCgaxZk8LQEVVsCkc2Eu7izZZLF+/D/Hn/il9J1Kjxl1C1em75yr9eRoAFAkED2Nc+CkKDUeQO4yFoKAc/ljvMY19r0+DX/uNMwZ02/TgR4FqFVwRCY553F2tfZwp5SiDgLi4hRe/OusxrXki1CufzsSDAY8Z+S/r63G+/5BzCCDAC9hBggYA9ZDzkzwIB94BkgYB7eLlDHdICAb1sJByYOmWHsg9BYb+iUePkKcKO2h29PmHtmQUCQWsxX/soCA1GkTuMh6ChHPxY7jCPfa1Ng1/7jzMFd9r040SAaxVeEQiNed5drH2dKcQCgcAW5TUvEAt+YgRcQYDHjH2UfH3ut19yDmEEGAF7CLBAwB4yHvJngYB7QLJAwD283KEOTYEAlfO//95D+zZ/KPsLlarkhKbNvnKnCkwbRARYIBA04HztoyA0GEUsEAha3+FYwUOABQLBw49jh10EQmOedxctX2cKsUAgsEV9bR8TWDJ+YgR8EwEeM/bbxdfnfvsl5xBGgBGwhwALBOwh4yH/0BAIPHz4AtavOwmXL92HO3eeQYRPP4GEiWJDBjRGXPK7TBAjRhSXakenug/sv4LpPEB9rA8EIzd+/BiQJk0CSJM2AWTImBjixYvuUlpEdPz4Tfh761m4efMxPHv6GoRxU//4UAr1scf9kI67AoHg1nXunL3w/oOe+/oNC8CniNXZM3cQvxNw7eojePbsNeTImRxati6i6ukpo8KU4OKFB+Dly7ci7Zq18kLUaJFUPvRgVj4yML1+/Uk4c/oOPMK2jvdZDEiRMh5kzpwEviqc1iq+/uKOQIBoly45JJj4lEbGTIkhfwF/lZxuVNieyiBFrD0sXnQAZs3cLXyoP45CI9lm7vbtp3D0yHW4gsZwySAuYZQ6dUC/S53mc0ifPpFoK7O4Rj9qww04Hs6evYvj4amw05Aq1WfYrimg0FdpBPmbN++EjQB6oTagttAd9delH3Twx4kTDUiYobv7954DGR4mlzBhLChdNqt4Pod5bthwUvSl589fQ+LEcURbEZYZcfy44l68eIPj8KrCgvKimxWEA41FSsfYbyjd48duiHj0fASxpH5NjoySk80K6ei94Jep5avNL+G/ZdNpMW7v3X0OESN+Cp8niAX+OHZLfJsJPv88pk0c3WPTxlNw43qAQeOSSE/jnvrwGrSfQWV69PClKD8ZTPc15+yj4MiRo7B2XYBx7Vw5c8J3331rVYU9e/bCtr8DjFGTfYEiRb6G9+/fw+bNW2DFqtVw/dp1HGP/YTumhnTp0kL1atWAjBPbc+4wii5duoy6jxeppCpVrOjQ2K4ixIdFi5bAxUsXhdeixX8KGwn0UrZMaTRInUr4078KFcpD5kyZ1Lv+YLFYYPv2HbBu/Qa4dv06jr07ECdOHEiWNCnky5cXKleqhGuR6+uHnjY969iSgcXDh48Ikpw5cwh9z5Ke3kt9F2gY0qxN3717h/1xLbblerh+4wZEihgR8uTJA2REOW/evBA//mcyOae/J06ehCVLlsKlS5fg5q1bos4pkieHotj2ZcqUwfETfKPTI0eNQfss/4mydOncSRiyvnHzJixYsBAOHT6Mqtru4jyUENKlTYvlzwPlypZxWm5J8Pr1a1jy51LYt28/rvnXcO59BcmSJ4P02D9r16oJKVOmlKRWv9N/mwH3798XfunTp4cqlStZhRtfyBj38eMBtinSpEmDfb9qkNvUmLbZ+82bt2D2nDkiKFmyZFC/Xl3xTPWdv+APOHr0GJw7fx7XhyjglyoVFCv2DZQpXQrXmU/NkrPxI8Pb27b9DafPngUyiHwL80uTNjVkzZIFsuBf7ly5XO7v1B9XrFwlxg+NnTdv3iD+6XDezi7agMpI7rcZM9XYbNq0CXwe376xeBqPNH9s2LBRtOv9Bw8gUaJEkCpVSqhUoYIYkzaVctPD2XyoJ0ft8e++fXD02DFho+Q91jljxoyQMUMGyJ//C9yvptfJ3X52VhZ9/vDE3GwsIOG7cOFiOHHihJhTImA/yp49O/5lgxz4lxbHpj3nbJ5ftfovkS7FdzQHy/R37d4t+hK9FypUCAp/5diG0N69/8LyFStx73UZHj16jGu9H2TKlBHq1K6F6/3nlAy4yxSiOYnG2alTp8V6EBHn2OQ4L+bKkQNq1qwOsWPHFum68o/sQ8ybvwD3dPg9gXNsksSJcU+YHipVqgBZMmcWSXhKIDBh4mR4/vyZSLNd27Y2Y9ibc7ERi6Cuy2F9zTObu2kftWHjJliJ8+RVXKdoHm/ZvBlUr17NCBt4cu4Lzry1ePESuHAxYF9Vs0YNMa6osLR3Wbl6NZw7dx7u3rkLyZIlFXu1umjAmvZLrjpP7Lm81Z/fvXsP+/ajHTa0R0Vz/oXzF8X4p3klY8YMUBzXW7muOatvUPcoztLVw8PKmKFxsO3v7WJePXPmDFy4cBHX9YSQNWtW3Htkhty5c0GCBAn0qjl89rW5P7hj/+SpU3Do0GGxv6O9OX2D0B6D+t3Xhb8S+2SHgHAgIxBOEGCBgJcbOiQFAu/f/w/oJPCa1ceRWfDetGbEOKxb9wsgw6KO3PXrj2DsqM34YXvbLhml1b1Hacidx5xBICM+evQShg1eJwQC0k//pXRq184ndMq7KhDwVF2rVJwMb98GYLV8VSvYs/sSDMWy6i47Mk8HDw1kbnhSINCg3kx4+OCFyG7O/MY2AhZj+a5cfghdf1oKr18FMIP0ctJzrtwpoN0PxQRT2hjmqkCAmON9e68SBnQpDap/775lIWrUQGFFUAUC/+69BP37/iWK9hkKMmbPa2RVTNrQLlt6GObO3qPaxYrgw0uBgv7wU7fvIHJkx0aYl1NaKPShupu5rNmSwQ8/FoOYKCSrXTPAKCkx/Of90cSK/OaNx9C86Vzhlzx5PPh1WgAzSRKdQcZ2pw6LxSsJT0aOrgbr1p6ACeO2ShKr308++QTKV8gODRsVdGhIej8K5MaN3aL6iFUiH16SIYO9/8AKkCix9Qe1Lnwxiyf9yEByux++ka/ql/rlqBEbhTBBeRoeSIBWrHhGaN22iN226NNrpRJMDBhUQQhFOrRfBCTokA7hgFVr2spXn/k1+yjQC0cMjq7dAgzY1sOPtyGDB+rBMGnyrzBk6HDh17ZNK/ipS2f4oUNHWLZ8hRWdfIkZMyb06N4NKC0z54xRJONcvnwFqtesDbdvB8zfLVs0F+nKcGe/9Rp8D3/jR4YzN37cWKhUsYIN2b79B6Bjp87IULpiEyY9qK4dO/wAzZpZjzUZ7ux34qRfYeiwAGwd0RITa9jQwYrE2KaNGn2PRrabwZat2xSN/kBCiwXz5kKuXNZCQJ2GnokB2OHHTg5xI2HPqJEjnDLkjGkb39OmzySYxOR/8fwZOI0fgtVr1MIx9dJIKt4L44fP8GFDIDkywh05Mp45aPBQZAI+MiUj5jgx+ocOGWTz8b5x02Zo3KSZiEdCj79Wr7QrLCJhVcnvSos6EGNw5YqlkA0/YIPapqaFNXjSR2GFSgG2bvLkzg3Lly2BTSiY69GzFwo7bxmoA15Tp/aHSRPHKyajKRF6bt22Dbr89LMQetmjobTmzv4dUqRIYY9E+JNwi/qRHLtGYoo/DPGnNi3xbSk4c+asINmyaT0KFdMZycU7MZx+7NgZzl+4YBpOntS/qa7O+ojdBDDA2Xwo4xJj7OcevVQflv7yN0KECNC+XVs04tpWCLukvzu/zsri6blZlo2EOTTHzJ4zVwh7pb/xt3KlijBi+FCbcUR0zuZ5WkOWLlsukrQ3B+v5jRs/AUaMHC28OvzQHjp17KAHq+d79+5BqzbtgJhCZo7mQjKs26plC5cFAvQtMnDQYId4ULodf+wAZBDekaO0evXuAwv+WCgE60Zamp+qVasC/fr2EQKQFi1bCxISiE6eNMFI7tJ73i8KqnF9cP9eG+aat+Zis8IFdV0O62ue2dzds1cfmDU7QMArsaJ+Tf1bd56c+4I7b9Vv2EgIjal88+bMwm/n3NCzZ28xlunbx+hobWyM+xPaEzoTTHtqz+WN/kwHBWheISGsPUcC4AnjfnF6aCU4exR7eZv5h4UxQ8Kljh27wMFDh8yqIPxobp0yeZI4jGSXCAN8de4P6tindbj/gEEw8/dZdqsdN25c8W1ABz/YMQLhHQEWCHi5B4SUQICYuIMHrlGMN1ktYm6+efvOhoFctlw2XKADT71Levr9d+9lwRR/i/GkI8Yfnex98fwNPH78Ek9cBIREiPAptO9QDIqXyChJrX7pJHD3bsvh1q0nyp/ifJ4gJn7ofYqnIZ4p4UXzFoXxtM8TpWeeykflNDpP1lVnuP8yviZ07YLMdgPz2FcEAlOm14NuWD4SsJAjDC14i+PBB4GCxMnPLz6Mm1jL5gS9KwIBavN+vVcrJjAJe3r2LmPD7A2qQIBOrXf7aZkoaqxYUWHBosAPQLqRQn2FaHQXO3ZUPD0WTRgo1vskMd779C0HsTDczE2fuhOZPoetgoiWBBGPEcMnT16JMMlQb9Jotnj3hECAbhgM6PcXUJ2I2Z00aVyR33McP7pzNA7nzNoDC//Yr5ML4QEx/h/cf2HFUKcbNv36lxc3d2QEqvu8OQEf9qSuSQoJiVkXKVIESQYlSmaEFq2+Vu/0QIag+6BQSAqryC9y5AgoaIoN/+FHOd1SIKGcdGnTJYR+A8rj6Yto0kv96gKB7j1LCwHN1SsPVTg9hBeBAPUHYkSRixw5MqRE5h6dSKcTT7oj5oXZqW5njCJKg05PVq9ZC+fcAGGAIwaQnqf+3Kx5K9i5c6fwevnqFfbjgLaOGjUqRERmnXQjRgyzKScJOzp1/smKGUanP4kZTqdN6cND//ilE32jMB0Skrnjpk2fAaNHjxFR3rx9q/KLFCkSREFspaP0+/frI18Fs27K1GnivXfPHuJUODGYyFH9iCFKJw7fYprS0amixQsXiFNF0k//JcFH3foN4erVq7q3ON135+4dNfYokD7yR48agTckKlrRuvOif7T/vXUzVENhAOFKLmnSJGLeMTKU6RTeujWr7TJYiWFIjEPdRYsWDU/ExlAn/2UYMdTnzJ4JsWLFkl7i96euPwtmHb3QSeiVy5ea5lezVl3YhaeWyXXu9KNgMtJzUNuU4jpzxg/LXr26oxCltug3xGxJmiSJaH95Il+mR3WcPWumuC0i/fTf4SNHwfjxE3UvINxSpEiOTP07QDcHpKPT1bNnzRDCD+mn//6Ft1Tate+g+jKFRY8eHU+MJsP5/rlIj8YinaQkgQYJDpwJBEhQ06Zte3iF41g6YrgnxtsBdKtEd3SSkBhVdHouKM4ZE57K3gMZYHPnzVfJEyaUH82BxLyjG1PS0U0iGndUXneds7IYBQLBnZupfM9fvIAmTZqrvk1+VPYk2LdoTqK+pc8rNEamT51icyvM2TzvDYEA9YWateqI9YPKTY72CkmSJBW/16/fUG3Tt08vIez9fVbAnmnQgP7QoEG9gEjaf+pzzZEpTzdndEc3rqi9jQJMSoPSMnPUL5o1bymEJTKc1gzqs3HjxoEbuI7K9OhGGN0WaNmqjSANKYGAp+ZiWT/jb1DXZSNzk25ChaU1zzh3161TCzriHsPojAIBT819npq3dIHAHFxTZs+dBxvxlgM5OiBBa7fcI+l1o1tA438ZY1co4Mk9l6f3FnRTq0mzFkqoRvuztGnTiNsBdENQ7lOpvrQn/hX3viVLltCrr549sUdRiTl58PUxQ4cZWrVua/XtQGuNv58fPME9Bwlh5D6b5vHhw4aKW5hm1fbluT8oY//Bg4eojrg57D9wUFSX1omUKVOIW5a0tz979pzChgjatG4J3brazidmWLEfI/DRIoATRrhx+OFk6dSlqyV33vyW5Cn9xS+9k7+33MTxWy1lS40Xf3jqOUjZfN/gd5XGmdO3TdOYMnm7oqlQdqLljwX7LBcu3LPgR44FmYGWEyduWiZoZaEybdt6xiYtom/ZbK5Kq9tPSy3Hjl63lb8PMgAAQABJREFUvHr1VtE+uP/cMmb0JkVTrvR4y+1bT1S4/tCz+wqNboJlIZYLTwYrEmTuW1DVigUZ8xYqd4umgXmvXnVU0ekPnqorpVm5wiRVvto1polnarPduy5YUB0PYvfOggx4PXsrfI4cvmYV5u5L/bozVP6o/sgmul6++nVmWCqVnyTw0vFGVTSWyRO3WagdZF8zw47aUIZXqzzFJi9qix4/L1c0/fuuFvW3IUSP7X+fU3RdO/9pRmLqR20ty9C29QIrmu1/n1Vh1BeoDqheStFQ39y547ylgYbZmFGbVLj+sHvXRZUW5Uf9+Py5uzqJBdVgWaiOFI6n+xV9nZrTrejo5cb1Ryqc+qjR4U0aFV69yhTRnxs3nCX60dOnrxQ5pfNz12WKtnyZCRZkvqtw+YCCNEvFchMVHbXv+fN3LcjUlySWc2fvWDp3XKJomnw/S4x3RaA9TJ+2U9HRsyNH/UAfh3Vr/ybmCj3vly/fWJb9eciqjCiQNE22d8/AOUCOsV49Vlg2bzolcKV0Hzx4bho3tD1Rj7lYK2i9mDrVtl+g2gIV3u3nHjbFnThpsgqX606deg0syAy1IENE0OOVX8uOnf9YChb6WtHmL1AI59zAfiMTxo8ARdOocVPprX6RIW35osCXigbVHaiwoD6ULltepYcf2A6TQUaDJU26jIq+XIVKln//3WcVBwUgli4/dVM0hC2e4rGicfcFTwKp9OjZkdPbVLZJ8xatLP/u229BZp2IiqeLLBs2bFR7BSpjocJFTJMl2tJlAjHCE6UW6hfI/BP0z54/txBuNWrWUWXEj24LChFM03PFU8eY6pA6bQbL7NlzLdT+0j158sSCzFdLilSpVb6zZs2RwVa/qPZK0VBd8TS5Zec/uxQeqJrDgkIUi3+a9IoOb8ZYpUEvz5+/sHz5VRFFM3XabzY0ixYtVuHUPwg/M+dOm5rFN/odPHhI5ZsrzxcW+qO6Dhk6DOefh4ocGY+WxUv+tGTNnkvRFyj4lel4vHHjpsUvdTpFR3gfO37cat1EVUSWSpWrKhrCBxlMKj/5gLcULBkzZVV0lOf69RusaO/ff2DBWzGCpsCXhS05c+dT9NRGRkdjLUOmLIqmcpVqFhQ6WKhvkEOhkQXVQ1koL8KC/oqV+BbL/58xKZfenc2HyLhS+VC5Fi1eYpXuy5cvxbij8SHLQ30zKM5ZWTw9N1MZUSCmyk3lHz5iFO4fH6ni01yPKk6s5voKFauocPngbJ5v/8OPKh/C1Jn7Zdx4RY8qQUzJaV2SmKf0S2MZN36i5dmzZ4qW1iuaY9JlyIx9Pq2lSNHiit7evNK7Tz9FQ3HGjZtgOX7ihOjT1Mdozv25e09FQ/kvX75S5ak/jJ8wyYqubbsfrOY7GlOE21dfFxV01I9lfVAwoCfl1nOefAVUOqj2yCaup+dimwzseLizLof1NU+fu2neoPWO5sqxv4wT6xStOy9evLA8fhz4veDJuc9T8xbe8FB9qVTpcuL5m+LfWrZv32HVyhcvXrLQnkT2X/q1N8Y8vefyZH+mtb3oNyVUPWrXrW+5c+eOVV3xtqCFxqesK94ctAqXL57ao8j0nP368pihua5osZIKMzzYYNm9e48YA7JetLZ37NxF0dA+UN8fSjr69eW5PyhjX1+Had+OQgW9uhbaR+nrCe1r8UCNFQ2/MALhDQGSkoULh/pY1cQoFx79l8K94XSBwG/IiHv65JXbfw3rzVTMPDOBAOrhRmbwBEWD+u/tVmXc2M2Krm6t6VaMfoq0658LKrwFCgaI2Wzm6Hu2Z/dA5vH8ef/akBFTXTJ/6XfBfFsaGWnrljNWtERvxtT2ZF0pb53hTkxo1Hcui2T3VxeYhKRAgJjHhKk9N3Z0YNsame0Ux5FAgJjAuvBm6OC1yBQIZD4b8wyqQGBg/79UO48Ytt4qWSqz7C9rUHBgz504flPRVa4w2UJl1x0xmPUx06rFPAsxsM0c1VFn0FP+wRUIUBrEREc1Q2ZZWvBkvaV5kzmqDlN+3W5Dpwu9hg1ZZ5fRT/MJ5SVxO3bshk1a5OGOQABvJqj0aEzgjQ3TNMlz1YojipbKQIIYo9MFAkQz/pctVkwuI70vvesfBcEVCNB6U6VaDVPGItX5ypUrVszFdeusxwfROGIUXbt2zYqxN/23GRQl2M4dxkPlqtXVOpsvf0Gx8bZXAP2DN33GLII5aY/Wmb87zGO9TalNvm/UxIqBq+eFum6tGOpmHw3EKJd7CWJWEMPLzBHT4rtSZRVtg4aNzMhc8tM/2lP5p7WY9RWZEN7WUHl++10Z6a1+SWAhBSNUDzx9rMKMD38uXabSog9M44cW0ZMAiBiKlBa1K/VL6ehDLFuO3CKMmL6owkYG2fy606Y2kU089A9L2V79Bgw0oQzw2rJ1q6oH0ZsxUnWGZ+u27e3Oaw8fPrRi3qPqBJt8UaWCwpZwQ13rNjTSgxjNsg7y10wgQH1bhhODFG8ryCSsfulQTKYs2RXt5F9tDwxYRbDz4owJrzPExoz9xU4qFgueXlZlIWZHUJyzsugCAcIouHMzMWQk1vRLght7joQ/uuCWhEa6czTPE52nBQI0f+hlJwGCPaczR2UcM2Yl3vawGj/UpvacLiDOmSuvFWOL4hBziwQRMj9iYJFwxcwRg1QXrFGckBIIBHcuNquPPT931uWwvuYZ527qI7Q2O3KenPs8NW/p6VC/JKGzvj7q9aHDaDQnyT6fOWsOK+GipPX0nsuTewu93WhNI4GvmSNhji44oLlUd57eo+hp23v25TGjC0cINyngN9aFBAckhJF9yGzN9fW5X+9DVA9nY5/qrK8VZnstiZO+jo4eM1Z68y8jEC4RCBcCAfrYkROio19v3BTQBQKSaRecXzOBgM4InjbV+qSBsVcTs7TjD4sUE2/njnNWJCQAuHfvmfh79fKtVZjxhQQPsi5G5i7RDugXcPqaaPr1WWWXqSnT1ZmgFMdMIODJulK+ukCA8nfFhZZAgE6JO3LEgJbtUbXSrzak9gQCqIbH0qfnShV31IgNgmltk4DmERSBgPHU/sEDgadZaRGX/e4+3kBx5nSGP526193BA1dUXWpUnWp1y0Cnk89odNjStPFsFccTAgHjuJJ5yV+0L6DyQ5U60lv90u0UiYcjwQxFGDl8g0pr3drjKg39wVWBADaDRb+1smK59ckKPU35TP1F9jsa50anCwTMBFVGel961z8KgisQIAYqMUQdOVQXotYqM6acPUYRnYajE8O0vlE+c+bOc5SNW2GuMh6IuSvXVzrBZ8Ys1jMmBrl+yokY60F17jCP9TYlprTZTQy9HKgKSNWL8Dc6/UQ8Gjk0Blu937oVeAqcmOZmAgarCHZe9I92OpXuyNEJPNku9FFudHRCXIbTaWV5S8JIJ9+JiS7p7eU9eMgwRUP4Sad/gM2Y+bv0Nv11p01NEzB4Gj8sUc2SXUGQjDpq9FhVD7q1Y3TUfsTcpT9np+r1uhOzWnd0EpvGjMSVTvE7crReon50RU/xjAIBmhNkesRMondHjvqupCfhQVCcMyY8nYaVefyza5fDLGisSGwdEtoJdFYWXSDgibmZTqzLujliWMvi6kIPOsmpO3vzvKTR+5Inbgg0btpclZ0YqdS/HDldEEZ1NhMI6IJIR4I3yoeYn+UrVlZlQIPjVtlPm/6bCqNxSAI2Rw4NCit6Kl9ICQTszYeyrM7mYknnyq+r6zKlFdbXPOPc7ezWkKfnPk/NW7pAgNZ/VKXlsKnpNL28yUb9+I+Fi6zovbHn8uTeAo2fq3FYtXpNq7IbX4jpL+d7/WYS0Xljj2LM3/juy2OGBAASK9pHO3L6OkNrlNH5+tzv7tinbyy5DtOtNEf7MtrrShydfZsZceN3RuBjQyBcCARILZCcIBz9Ep2nnbcFAsTgr1U9QNUNMeWMalHM6jNv7l7FwBs+1PYUqlkcM7/DqC5HMgK7d1tmRfLmzX9CbYoMP3XyllW42Quddpb09GsUCHijrrpAAA3emhXLxi+0BAJmKp6MhSPVSxJDUu2kOzOBAH2IoQFhFQcN2Dr9GKQ03REI0Al+uh2il41ulzj55tSLbvP8E6opkvWkGwO601VjDRnkmLEi4+ljwhMCAWcqcEiwJ8vfDG8LBMfNQVVkMi17t3BcFQiQajGZFrWXM8YAlfvypfsqTsVyk6xUglG4LhCgW1JhyekfBcEVCHxdtJjTqqNea7VW0bVXozNjFJHaEqluiE4oGtVwGNNw991VxgOpg5Drq84EdpQfqQqSccxUZziKq4e5wzzW25RUuThzqEtWldF4iojUw8jy0wlrV8YLnXiWcVCXurPsTcP1j3Z7Kjb0iPqJKTptq7tGTZqp8pj1cZ2WnvWT0KROw8zRhxbdRpD1RAOoQi2CfK9dp55TrNxpU7MyGP2MH5ZoNNtIYvNOwiJ524HKTu0dVIf6jxUexhPYpEZGYpMjVx6XstDbgeIaBQKkrkmmaaZezJgJfTjrKqEuXLhoJHH67owJr9+CIFUx3nTOyqILBII7N5M6Hf1UOhrldVo1wpsYxPQn1YvJSGbzvAyjX08KBKiP6/PD/gMH9KxMn4khL/sW/RoFArSv1FVuOTvNTZnQ3CrTbNOuvVW++pxJqh5cccVLfqfSCymBQHDnYlfqJWlcXZeJPqyvefrcTXscezedJDaenvs8NW/pAoGKlZzvPag+UkUcjQ1aq3XnjT2XJ/cWdFtHjmk6fGFPZY1eJ7Nnb+xRzPLR/cL6mJF1IdWPsg1q1a4rvcVvWJj73R37VDFdlSLtrdgxAoyAcwQ+IZKP1kDCh4rhRysaJL3rtJoJEyaEA/v2OKVzh0A3KpwkaRw0DhfXneiC9ugRMkT2XjyPHlsd0mdIpNK4fPkBtG21QLxHRMMxS5Y1FwbAFIHJw57dF2Fg/zUihAzQTphc24TKudexozcA1a0Iwhw5ksOgoZVUpAvn78EP7QIMNZLn4qXN0dBeoKFHRWh4aFB3JqAufeFrNCrsjboi01Nhu3BJczSg6LyMrZrPg2vXHokyDsY6k9HhoLoG9bC+H4wCz5nfGOKhcVjd6eWbNqM+GniLowfbPLdsNg+uXw8oG7Urta90RqPCCxY1QUPU69CI9CVBUqFiDmiGhp1dse2pGxWmyN+VyiKzUb8oFIKbN5/AdcTq5ctAA505c6WA3n3LQuTIERWtuw8oEICTJ26JaMNGVIEsWZOqJHqgYeIjOGbINfy+IBpYzaPC7D3s+/cy9OuzWgQH16jw55/HhN/nfG8vK+FPhqHRJoR4NhpXdhjRJHDenL2wYP4+EVKvfn6oVSefDdVv0/8B1Pkv/CtXzQVNmhayoSGPlcuPwNQpO0QYGQoeO66GKZ3u+e7d/6Ba5V/RcGqA4dnho6pC5sxJFIluVLhn77JQoKC/CgvOA54aQqPagYaNHaWVNm1ayJUrpyMS0zCjYbFmzZpY0bljuLJK5Urwy9jRVvGNL7h5hTbtfhDepUt9h20x2Ypk85atgCc4hV/JEsVh0MABwoAwGRKm+X/c2DFQvnw5qzjBfSlTrgIcO3ZcJDNzxnQoUbyYaZJN0eDj+vUbRFjzZk2hV8/upnS65+49ewB16wsvMrZ78fwZt40LU2T8eIOp06aLdJzlrbdp0yaN0Xh2TxHP3j8ynNmrd18RXLdObRg6ZJAiRYEG4GlZ8V6wQAFYtDDQWKoiMjz07TcAfpsxU/g2+r6hlcFjA6ndV/y4hjdvAgyU79y+DVKlSmmXlgLwWjlcuHhR0GxcvxbIwLB0qMIHUPeyeCUDrgUK5JdBpr94Og2Q2afCjh05iEY9bfc1p0+fgbLlKwojqvHixROGcFEYIQwRb9qwThhQVImYPLjTpibRbbx043QUSHs92vM5c0W+KQ4XLwaskcOGDoY6tWs5i2IajrcNAHVeizDdkDJ5oIAAUCWRCPv668LCsK94cfCPDNhmzpKdDvUIqi2b1kO6dOlUDFTJBWvXrRfvHX/8AX7sEDCvKAKTB1RpBSdPnRIhNPfQHOSOczYfzpo9B3r26qOS/PbbkvB9wwZQ6MuCdg1mKmI3H5yVRTcqHNy5mTAj7KQ7efyIjcFtGebKr3Gen/FbgBF0GdeTRoVRyAVlylaQScOpk8cgJhoSd+b07yqjUWEa+6gLXCRBRkTPnDoO9OvI0dpBawg5mp9onpIuU+ZswmAzvRMWtPY5c23b/wArVqwSZCFlVDi4c7GzOunhrq7LFCesr3n63J0lc2ZYtzZgr67joT97eu7z1LylGxU27iX08uvP1IepL5NLhIbg9/+7WwV7Y8/lyb0FrU258uQDMvJK7rPP4kHb1q2hYsXyLq29sqLe2qPI9M1+w/qYkXXS99i0zv6xYJ4MgrAw97s79qlyKAAGvGUp6kmGlhs3/h5qVKtmte9VIPADI8AICATChUAArwO73NzXrgR8NLscwQmhLhCojYy6usiwc9c1ajgL0MioiGYUCBw6eA3QQKdKMh0y8Zy527efAqpJEWRmzE8Z//Wr/9Aa+x04c+YOXLxwD54+fQ0vXrzFvzfw4vkb8S5pjQKB/fuvQN9eAZvxhAljwYxZDSWpw9/ePVcCqpIRNEaBgDfqqjPcl69q5VSYQgULLYGAK+Vr1+YPQCO1Aj9HAgEiyJM3JRzYH4A1vc9FgURcg0CC/M2cUSBgRmPm56owANUfiX6HJ+mB+utL7HfPsd/JX+qb0hkFAq1bzIerVwM2oP0HVoDceRwzyygdnUFvNiaoPM2bzhVZJk8eD36dVldmL35pjKBhYvGcMVNiGDm6mlW48YXGUM1qAR/5zgQCj1F4cPo0jcPbcA3r9fx5wBgUWOA4pLSkC65AYNbM3bB40QGRXPESGeHHTiVk0g5/W7dEzK8EYP5zj9JQ6Ks0il4XCAwYVAFy5XbeHiqygwdUsQF4ytIBRWAQMZ0G9O8b6OHik/5R0LtnDwiOQKBtm1bQ9acuDnPWmSLOBAKUkJ9fKkDjtCJNYricP3vK44w1VxkPeOINDh46JMoyeuRwqF7d8RggwocPHwGeiBZx6N/RwwdQKBpPvbv64A7z2FmbGvPEK9eAtzWEt/EjfviIkYAnVlWU7NmzqWd7D0ePHlNBQWVU6R/tJERxxmzTGb26QIDGD40j6fz9/VxiZOp1MDKiZVr0++uUqTBo8FDdC8aOGQVVq1S28jN7cadNzeIb/fQPS2JMHDkUMM8Z6YzvOnOpS+eO0L5dWyOJeL9//z7gaTY4dPgwnD13HvdHT+HpE/x79izgGd+lMwoEevTqDWiwVQS3ad0SunX9SZI6/NUFPcZ2QAPCsP/AQRXf3b5pZPKqhBw8OGPCo5FJaNO2PaBKF6tUSKCUL19eKJD/Cyj2TVEgAW5wnbOy6AKB4M7NqPoDiNlHLnmyZLB7145gFT8kBQJbt22DBg0bu112PO0MeMtGxDP2lR07dgKqTVIYuNL3rl69pgST8eN/BocP7hfx8fYF4A0Gldbuf7ZD8uTOD+FMnPQr4OlqES+o8yxFRiPxgKpbRDoH9++FBAkSiGf5z1NzsUzP1V9X12VKL6yvefrcnSd3bli+bIlDmDw993lq3tIFAgMH9IOGDeo7rAcF6sI146EJb+y5PN2f0aYQNPi+EX6nvFR1/fTTTyFjhgyQH+f7ggULwDdFi0DUqFFVuP7g7T2Knpf+HFbGDOF65OgROHToCJw4cQK/ZR/BE9xrPPuw76A9tnRGgYCvz/1UbnfHPsWhA8A1a9UFVKlFr8rRukF7DOp3JVCo/Hn8+CqMHxiB8I5AuBAI6CdZHDW4t28IeEMggMZ4YdSIjY6q5TCMToOvWmP9gYsqXgANf8Lf286p02cOE8FAo0Bgy+bTMHrkJhGNGM/9BlRwloQInz51J272Dotno0DAG3UNzwIBY4PQKftBQyqhUORTY5DNuzsCgUiRIkCatAnwBF1mKFI0A94MiGCTnvQgoc/okRsFg176Ofs1CgSaNZkDt/BmAjljmL20UJ0SoL0B7O8AviIQuIOCkKGD18G5c85vN8l6BVcg8MuYLbBxw0mR3PeNv4Rq1XPLpB3+Dhm0Dv7ZeV7QtG5bFE8cZlX0LBAIYEoEl+lEgOqMIgWw9uAOM1GL5vDRVcZDocJFURAXIGBcuXypyzcySCAgP1q2bt4QJGagO8xjT37ooTFMQL2+DvFzFPhlwYKw8I/AE1uOaPUwT32037p1G9C4qZ60289LFv0hPrDMIqIKJShXvpI4iUbhrjBzZDrutKmM4+hX/7CkD0Iqtytu+MhRMH78REHauNH30K9vb6to165dg5at24IuJLEiMHkxCgRI4ESCJ3LGMJPoyksfm0aBwFdfFwW6ORRU16ljB+jwQ3u3ojtjwlNiqPoRRiCmCxctUidHjZnkyJFdnOirWbO6uFliDHfl3VlZPCkQoNtqP3bsLIr1TdGiMHvWDFeKaJdGn+fpNLw3bwjoZS+KjLk5s2baLZce0H/AQJg2PaCeRoEAqggDusUQVPcJfphcvRzAzLlx8ybeKvxKJEVMw7OnT7h0i2zjxk2A+rFFPBYIDAG00SOwMDvYYGwnR0Lw0Fjz9LnblTXEG3OfJ+YtXSBA6z6t/84cMcRpvae1lNzxo4fwGyWOePbGnstTewtRwA//6KDI0KEjYM/evaY8hVixYkH5cmWhfv26kDVLFj0qeHuPYpWZ9uLr+0RU9yMOqqxctVr1Da34po9GgYCvz/1UCXfHvqw42neCvv0HilvL8jatDKNfulFNa3WtmjWAbiqyYwTCOwLhQiDQGT/aF7rw0V4TJ4aRw61PswW3g3j7hgAx4YgZJ13pMoGMOOln9vsKT1hHixZwhbdNu6KKhJiQAwesUafMKYAYpMmSx8WTmzEgZszIqFYnCv5GwWv092HnjgAmoFEg8M/OC1iugCtbdGthjAuqRygvEm4Q45+cUSDg6bpSHuFdIFD467Swd89lVOvwjuBA5k02ZG4UEc+O/ukCAVJzRIx3Mxc9emSIEze6S2qIlqJKm99n7MLNDXLl0dGCnSRJbEiUODaeWo0KMbDPUb+Lif0PdeKr7IxMf12dUItWX0P5CtkVrb0HXf2VLwgEDh+6BsOGrFc3eUhwlyBBLEiKKsdix7bGYgWq+ZFqtoIrEEDD2rBq5VEBUxVULdTYjmohI46kOowwJNexcwkoVjyjIvGWQIAYPvIjSWVm5yEDnkbKlzfwJLodMhtvZx8FIcl0osLpjCJ6jxYtmlDhg8bb6FW4yZMmADFAPOV0pqMjlUGkIoJOs5H7feZvULzYN06LQCfv6PQn/ZLbs3snJEua1Gk8I4E7zGNnbWpM2xFzhNSfkDoB6erVDVB/JN/Nfp8/f47zWEwRlNrf3+bWiVkco5+nPtqNNzToBgQx45w5vQ7NmjaB1Kn9TaPQCa1Spcsp9UZ0fXv50iWQM2cOU3rd05021ePZe9Y/LOkEOgmfXHGo6x7Q1oMgNQrcduz8B1q3aadONhN21H/9/f0g3mefQZzYsXH/FBvn7Ngw/beZSnWlkemP9gVg3PgJIg+zm0EiwPCPGEUZMmVVt6SMAgHUoY43PM+JWNmyZYUc2Z2vg3q7FkfVYPbUgxmKol6dzYeKEB9ozG/evEVc7adTpMT4NTpiYBAzPHr06MYgp+/OyuJJgYB+sytzpkywfl3gfOy0oCYE+jzvbYEA3dZAA9WiFHSS/69VgTeOTYqmvHS1RUaBAKlrILUN0rkyLxLtC1SDFeODuqIhgweK6HTiNXvOgLWbxtepE8eQxnl/IEEtMa/JsUDAcwKB0Fjz9LnbFYGAN+e+4MxbukBg0sTxggkuOqiDf8TYzJ03ULPAhXOn8VBVZBHDG3suT+0tzKpEwvM/ly6D7XiD6MiRo0KdoE5HNx0nIy7fffet8vb2HkVlZHjw5X0i4di0WUul3o+KTreqUqdODQnxBhPtN+iPBEcnT54ENNIuamcUCPj63E+Fdnfsi4pq/+im5gpUxUp7jX37D4jbmlqweGzVsgV0/7mr0ZvfGYHwhQDqePvo3ZkzZ5VRFWlcxeyX6DztdKPCc9H4Z1Dc9w1+V0Y7yRip7sigqjQC2rD+TD0oSM+DB65R6aENAMupU/aNAaNtA0Xbvau1UeHjx26oMGS6OzUgKAvbtvUCFc9oVNjTdaU8daPCZAjNFRdaRoVdKZ+O3yU09qo73agw9ZkVyw6L4K1bTivMyX/j+pN6NNNnd4wKmyZg8NQN05YrPd6y6I/9llcv3xqoAl+7dlmqykx9TXcjhq1XYWNGbdKD7D7/ueSgihNco8KdflxsNx8Z8Pz5a5UfGQXXHRlbpjLIcU31uXvnqU5i9Yw2BBTtgnnmxgxdNSq8cME+lRYZA3bV1a4RaNj84IErVtF0o8LGMCtCH3xBpqRaO8wMrrpjuJKMwzlz69atV/k1a97Shlw3NklrGDLSBA0ZIJZrWvqMWXDePm0TN6gerhovrF23vioDGex0xRnXZjzJ40o0Gxp3DNA6a1Nj4shYVPXq2q27VTAZh5W4I4PMKsybL7rhPzLg68zpBn71vkFGkP1Sp1N1uHLFeuw6S9dROK1XaENApS1xQjU3FjLC6sy506bO0qJwo3E6V/saGZ6WZZ82/TeVFWFHBoBlWNt2P1iu37BeixQxPqANAUWLtgT0IIs+jxT4srBVmL0XZKio9KgMZ89a71/JgKAsGzJH7SXjUX+9Ht1+7uFW2mRYl4xsV61eU5Wbyo82U9xKRxI7K4tuVDi4c/OBgwdVmckwMwprZDGC9KvP82YGoXWjwmSw25nTDVqjrQorcjKALPsJGRd+//69Vbi9F31OmTVrjhUZrUsyTbyBZBXm7kvAHJVWpUdYu+L69O2v4oSUUeHgzMWu1EmncXVdpjhhfc3T525XjPGG5NznzrylGxUePmKU3px2n7dv36H6caYs2a3ovLHn8tTewqqgJi+0B9i1e7cFbSpZMmfNoerolzqtWKtlFG/uUWQeZr++PGZQjaHCi+YBR3MiYSzn4pq16lhV1dfnfiqsu2PfqoKGF1rbTpw8aSFj3IWLfKNwIXzwBpWBml8ZgfCFAF3fChcOJYRWg19OkPKXwr3hvC0QQNsCioFHDMTHj18GuRp4JdJSo+oUkV6l8pMseOrYYVqbN51SeRsFAsTAlAxN+kUd7A7TokDKv2K5SSqeUSDgybrKwoRngYDEgH6nTdmhcKe2NwqedFp69rRAQGfIT/l1uzE7m/fG389S5TUKBHQBBwnTUMe+TXzd4/37/1m6dFyi0gttgQDa7VBlad/2D/xARwmBAzdm9CZFH1yBgI5dw3ozHeQaGPQI5wl9rF+79jAwEJ9YIOAv1p7gMp0IVJ1RRIwz6YgRUaFiFbXGFSpcBNcC53OujO/o11XGA57GVPkTw8oVh0aUVZxceb5wJYopjTvMY09+6OFpN1X+b4p/a1o2b3h68qOd+orcB+FNE48Vd8zYX1S6o8eMtej9o1//AU7zcadNnSaGBPqHJdUXDeq5Es1CTBiJz9p161QcnSFfukx53L84PlDQsXMXlY5RIHDz5i0L2rpS4cdPnFD52HsYPGSYoqfyGQUCnbt0VeHde/ayl4xH/Z0x4V3NDO1yqLKTwOrlS/f3tc7K4kmBAJ7itWo/vCnlalVN6fR53kwgoLft9N9mmKahe+oCBKNAgIRYsn/T76VLl/Wops8k7CPBh4xnFAjcuHFThRHN/fsPTNNx1bNgoa9VeiSgdcWhsXoVhwUCjg82GPF0JAQPjTVPn7tdEQjo4yOk5j7C0Nm8pQsEGjVpZoTd9H3qtN9UP8YbAVY0+prqqT2XJ/cWVoV18ELzQ778BVU9h40YaUXtrT2KVSaGF1/dJ9LcK/ckaP/JgvryDSW3fl285E+Fq1EgEBbmfnfHvnXt7b/RNxMdNpBrGNodsU/MIYxAOEAg3AgEqC3pNGIn/EjC63diEqBfevfGzQDZd7wtEKB89FPhe/dclFm7/Xvq5C3F2CNGpDM3bMg6RW8UCFDcVi3mqfA1q485S86CalIUPTEYjQIBSsBTdZWFCa8CgWqVp0gIxC8JY1Dti8K/Qd0ZFmL02nOeFgj07L5c5e2sDxPDWWdAGwUCJACoXGGyounbe5XDGyr6GKV0Q1sgQLcjZP2mTd1hrwmEPx5StdSvM0PRuyIQcCRwefr0laVC2YkqvRvXHznMnwK3bT2j6Js3sT4pSOEsEPCOQMDIKLp9+7aFmOpyg1u3fkOXT3tSO9lzukCAbjDYcxs2bFR5f/lVEYsrJ7DpxL0sr/H0vb18zPx15jGdDHXkPPmh9+DBQ0sq/4DTqyn90liePHniKGuPhXnyo10/SdtvwECPlPHosWPq5gHdCKCPLxJQ5cyVV7Q3YbVnz16HebnTpg4T+hCof1hSn0OVMU6j6Ux/YkyjoT4VR2f+OMONTjnKfSflbRQIUKL0QSrHAupMt9y7b33DT2WMDytWrLRiQFM8o0BAv21EAouQcM6Y8K6WgU6Pyr5CdaNTju46Z2XxpECAykaMStl+rtyQovb6uUdPC92kQOPbVtVzJhCgmyoyLxonzpx+mt8oEKC4xUp8q9KbPWeus+QsqCpL0VM5jAIBSkDPc8NG125q2su4R8/eKr9WbdrZI1P+Dx8+VEwzKt/HLhBwtC4TKGF9zdPnblcEAqEx9xHOzuYtXSCQM3c+q/WE4pu5ht83Vn2fhMC688aey5N7C72szp51wUe1GrWsyL2xR7HKwOTFV8fM/gMHVH9wZV1v3ba9ojcKBKjavj73uzv2TZrSrhftU+U6Svs7V2542U2MAxiBMI5AuBIIhEZb6cxGb6gMojr9oan5ILVBD+4/d1hVNBpq6YDqgOhvvqZi5OSJQPVDxGR05G7ffoK3CaYqRqCZQGD277tVeNVKv1quXLF/SoiYz/WRCS0ZofRrJhDwVF1l3VggIJGwiNslunqqLp2W4NV38+vj3hQIrF3j+OTmVLxBoPcTo0CAarRk0QErmnFjN9v0P7q1MuO3fwQdCUhkmqEtENDV9gwfap8BS/XcveuiKjeV355AQFcrNHjgWopq1/XqsUKl2abVfPzIsa/+4PatJ5aa1QLnARrzRscCgZARCBDupKpBVwFj/IA0to0r7/RxJjfNv8+abTcKCQDkySWip1N6jhydttZPRaNeWUfkDsN0dSyoD9shrSc/9Cij2nXqKXxICONMtRvqYLagXQbxR4y/oDhPfrT/u2+/Kj+d+t35zy6HRTp58pQqv9kpR+oHdFuC+gC1r874X7Z8hcqLhEbPn9sXOrvTpg4L/CFQ/7CkslFdUT+t3aioe9aCxilVealtdTdu/EQV1qZdez3I5nn9+g2KlvI2EwjQhz4JSiic/ojxReNZ7090knLhwsUWan8a53o/MAoEiDmVMVNWlR6pt3LkqC3q1Gsg2pZUPd25c8cRuWmYIyY8XdUnFRf0R3hR+ew5UrmTPWduVXb6cHfXOSoLpeVpgQCd1JdtR21D7WnPUd1LfFtK0ZOqJN05Ewjs3r1HxaU+6uh2is40pPKZCQToRK4sO6mcM/YlvWx0GyJPvgKKnuKZCQRILYNMk9QGkcDakVu0aLGaV+h2ke5obZBp0S+derXnSC2ErkqF6D9GgYCr6zLhFNbXPH3udkUg4Mm5z5Pzli4QoH7ZpFkLe91Y+NO40vu9UTWMN/Zc+priCoNUF/zp6gipAiSslHO+frvOrNK6kNN42MXTexSz/I1+vjpmUA++6hN0yMCRu3btmpU6JjOBgK/P/e6OfVobZJ+jm6mOHN3ElOOL9kpmjtZWuk1KhzrYMQIfMwIsEPBy64aEQIBORJN6D8nQJCbes2fmH1t/bztrpTf/7JnAjz6KQ+piZDorlpt/LJ8/f9dSr/Zvio7ozQQCT568spB+dJlei6ZzTcv15s07i64TXtKbCQQ8VVfZ7CwQkEgE/J5DdTU6JmgU25rgw5unBQIzpgcw5qntm+Ep86fYd4yOFmQqj+wf8tdMIEA3Hrp2/tOGlsbJoAFrLI0bBqocqlr5V2ErQ6YX2gKBff9eVuWmmw6nDXZDJC6bN51GFVuBp/mp/PYEAls2B9qJoPo6EhqeP3fX6pYA2TAwU1v08uUbSzvN5gfNCXTDwOhYIBByAgHC3vgRuXLVamOTuPWuX78vX7GyQ/3YM2b+rjbYtNGePdv8tCndysuYOZuiJUZkcJyuxiBDpiwOmU+e/tA7fPiIuiVAdf6xUxdTBh0xKXQ1L8TwfPXKdry4goMnP9opP2Lsqw8jbBd76nToxLx+fX/yr9Y3zSgt/WQ/qTQwOmprmRca7DUGq3d32lRFcvCgf1jK/IlRacb4JiY8MWskHQk2KL7u0PCrCkdDjDbhknbJn0uthHSUpplAgOiHDR+h0pR50zihq+1onNlKgEaCAd1GgxkTl+yeyHToFw1ky2JZ/RKzVmdWNWjYyCrc1RdHTHj6sM5foJAqD40TM0frvH77gm4KOBIemKVBfo7KQuGeFghQGYsULa7ql/eLgpZbt2xtcFH9SI2JbBeyQ2GsnzOBAAmrdGEqCafMHOmIpnLIvOjXTCBAN52yZs+l6KgeZirnqJw6I1qmayYQoNs0uhoQUndiliaVm2686HMazalGp+dL4+3oUVshEWGrz7GyfB+jQMCddTmsr3n63O2KQID6jqfmPk/OW/ocK/umPUEtMcF1tVz25mRP77n0cRhcgYCueooEjfa0MZAdBl2nu5m9Lk/uUYxzi9m7r44ZmkNJVZDsP7/NmGlWfLGH028ME72ZQMDX5353x/6FCxet1kYSNJs5UkOo7/GMQiiKQ2nJPQsdYKF+yo4R+FgR+IQqFr7MKIdsbZGBCWv+Oi4yrV0nH9Stn9/tAjRqOAtQf76IN3psdUifIZFNGvv3X4H+fVYD7odFWMSInwq67DmSQ4IEMeH69ceAjFM4d/auiluhUg5o3qKweqeHiVjetR/KS+/JksWFfF/4QcZMieHatUeAaoUwnZuADFcoXSYr/LX6GJFBDsxn0NBK4ln/t2nDKRg7ZrPyihEjMhQvkQlS+X0GET79FK5dfwTI2ITHj15ClqxJIXnyuLB+3UlB36pNEShbLpuKKx88VVdKDw0ew9u370XSy1e1gogRI8hs7P62aj5PYEEEyVPEgxjRI9ulNQb88GNxSJnqM+XdoN5MePjghXifM78xxIsXXYXRg7vla9fmD7h08b5IY8Lk2uDnF1+lhye9AU/Ci/do0SLD4qXNVZj+gMxjGD1yk/Jq36EYfPtdZvVODzu2nwdUGSX8smK7DR1RxSrc3Zc7d55Cq+bzsS3eiaiRI0eEHDmTi74XKdKncPrUbdHvbtx4DFmzJQM0yguXLz0QtMMwb+o7RkftOnrkRti547wxSL3Hjh0VOnX5FtNMCniLRfjHiRMN5v3RRNHQA94mgOZN5wq/5Mnjwa/T6lqFnzlzBzp1WCz8aKyMHF3NKtz4goItqFltmvCOFSsqLFjUVJHQlNym1QK4euWh8Pvkk08gQ8ZEkDdfKjEeKS/Cg/7iYn/JhmWn9iBXD+eXWjjPGB2N3dYt5pMAWATFwnoXKJAa4n0WHVKn/hy+KpzWKsr8uf8C3h5SfokSx4ZvimWAJEniiLF/Bcu2Bcft8+dvBA2VsUevMlCgoL+KIx/69FoJB/ZfFa8DBlWAXLlTyiCf/x04aAigsSlRzt49e0CzZtb9Aj94AFXdiPB6devAkMEDreqEaklgyNDhwq9tm1bQ9acuVuHGFzxJDE2btxTepUt9B1OnTLYiQSYkIHNQ+JUsURxm/BZQNisifOnU5SdYtGiJ8I4ePTosX7oEMmXKaCRz6R0Za4BqLRRt2rRpodCXBSFWrJhQpnRp7H9ZVRj1r1q16wGq+FB++fLmgRJY1qRJk8KjR48AN/iw+q812I8CxnqcOHFwzv8LkmF4UN358+eheMlSuP79TyQRL148+LZkCUiYMAFkzpwZypUto5J21qaK8MMDMlEBjTaLt7p1asPQIYOMJICMXJgwMbCtYsaMCQXyfwFfFiwIEXBNOX/hAmzZvBVu3Lwp4kaIEAHX2nFQtkxpm7Rc8UCGGODpQEF68fwZiBQpksNo35UqCydPnRI0G9evhYwZM1jRI1Mcvi1VBh4+fKT8M2RIL8qfOXMm3D/cgBMnTgD1PzmH5M2TG+eIORAtWjQVB0+0Q/WatUU7fB4/PmzbugmofXV35cpVwNPRgMxF4T1vziz4+mvrfQgFuNOmevr2nvE2AFSoFLBO5ciRHTJlzAhobFeUv2qVypAlS2aIGjUqoA51+PPPpaqtKL0GDerBoAH9rZKmvoZMTjh79pzw/xT3M7ly5oRixYqCv58fHDpyBA4eOAR4qhM+//xzKFggP6CNBkHbudOP8EP7duLZ+A+FLDB02AjVl43h1NYdf+wANJ+Uq1AJUEgjSLZsWg/p0qWzIqcyIiMV9u3br/wTJ04sxm9eHJdPnjwVOOPpTXjx4qWgoXZbsmQhpEmdWsVx9cGd+ZDSzJkzh+hjBQp8IbA/d/Y8rFm7Fv7ZFTB/0LoycvgwqFHD8XpqVj53yuKJuZnKsP/AQUCmC+5j3ooi0djQ+9b169dFH5B9hogGDugHDRvUF/TynyvzfMdOXQBPQ8ooAsevCn0JyZInw/F6HY4dOwHrN2yA2LFx7S5aBJavWCloO/zQHjp17KDiyQdaL2jdkC5WrFhQvVpVoHkgYoSIYg6j/O7fvw9ffJFP9A+aG8nR2KAxYnRbt22DRo2bAZ7aF0ERI0aEXLlyirImTZoEkOECe//9V/VhImrSuBH07dPLmJQYZ9TfUYgqwmgOLYvzOs1DcePGhevXENu//gI8pQzUh1u2bA4015Oj+X/ypAni2d1/KFABmh/JHdy/F7+nElgl4em52CpxBy/urMthfc3T5+48uXPD8mUBexsH8Ij501Nzn76PozyDOm/Vb9gItm37WxS7R/du8Msv4+H5ixdiD0V7qWTJkuIa/FDM12vXrVdrQMwYMcQeKWVK272zp/dcnuzPNFa/KFAIkIkt6kzjtHDhr6Bg/vyQNWsWscaePHkSZs6cJXAgItpfrluzCqJEiSLiyH+e2qPI9Jz9+vKY6d6jF8yZO09VIXVqfyhe7BvIjWOD9k20DqEwGPCmHdStWxvwYI6gpX37HwsC48kEfHnuD8rY18cZ7ZcK4bpYAPscfYvQeMPDE4C38oD2ouRofC3DbyTjvrhX776At6IlTNCmdUvo1jVwjVQB/MAIfAQIsEDAy40YUgIBqgYxyocPWQ8vXwZ8jNirGn5jQfmKtsIAoseTwEBllkx5e2m0bPU1MvXjA+qdFyT2BAIUuHrVMZgyebtiJJilmRgZjiPHVMfFah+sXhnwgWtPIEDxPVFXSsddhjvF0QUC9O6OGzmmGi46iVUUXxQIUOGovVZ9aIdIkSIIhn8GTRDlaYEA5UmM7gF9V+PmMeCDj/yMLikKqEYhhoMGrBUCLgq3JxCQcU+euAUrVxyBC+fvwb17z3CjGREFT/EgZ64UULV6boiOAh28peIzAgEqNwnI+vf7C/AGj6yGzS8JTYYOrwz7911RzHt7AgGKrLepnth3pbJAux++0b3EMxp6ht9n7HY4bokwarRIyDD9Fr7I72+TBnmwQCDkBQLEkKpSrYZitNCH5F+rlgvGiWkjOfAkZk658pUAr9faUI0fNxYqVaxg5U+MXmJWSeanVaDhxd/fD/vYbyiUMu87BnKHr7379IOZv8+yoalTuxYMGzpY+XvjQ48SHzd+AuDpW+fjBZnOxOSsWLG8KpO7D578aJd508cRCZtIeOHM5Udhx+8zpgMJPqQjhjIxyPGauvCaMO4Xu3Uk4QkJUcglSZIYNm1YJxiXwkP752qbalHsPho/LBcvWoDC03pAQgxHrnatmkLQRwxIoyPmKJ5cBDzRbAxS7yRkWLxwAWzZug1QFYrwdyQQIIKrV6/C9N9mImN8lxDGkPCMxkj27Nmgfdu2kCpVAGPImUCA0sKTcNC+Q0cgYaMzR8ICEtCkT28tWHAWT4Y7Y8LTXDJp0q8wGnGQAkEZ1/gbP/5nMHb0KCiKzOygOGdl0Zl8nhIIUDlRpQM0a94C8OSlw2KToHbUyOFWwkoZwRWBAB3KadqsuRDSyXjGXxKoTJ0ySTDTR4wcLYLtCQQocNbsOUBjTgpWjenRO60lK5b/KZiZklliTyBA9CQUaN2mPR4eeE6vdh2VtXGj702FATISMbpojkJbLdLL5pfGG/Xh+w8eAKqPE+Efo0DAnXU5rK95xrnbFYEANbyn5j5PzVs6o5L6KO2VWrZuKxi3Nh35gwfNg3Nm/W518MJI68k9l6f3FiT8/AHXH7P9o7EetJccggcuiEFr5oK7RzFL056fL48Zmvu79+gJUiBrrw4D+vcVAl00sC5I7AkEKNBX5/6gjH1aH35GocmqVavtQaP8s2XNCpMmjgc/v1TKTz4MHzES8LaifBUHumivwI4R+BgRYIGAl1s1JAUCVBU6ab1qxVHYiCfz6RSy7uj0+xf5/YBuKvjjqWBHbvmyw/iRfgo/TB/ix0HAqWKip9sJjZsWQul+Ujh29IZLAgGKdxJvFqCxVMG8pHfpokaNBJWq5IRqyJil51+REe2KQIDie6KuLBCQLWH9S4KhHt2Ww/HjN0VA/PgxYOz4muoGgzcEApQRtSkxrk+dvA2owkoVipj4lSpjP6mRG090RoZuPy1zWSCgEsEHOk1DH55GR0I0tIkhvOPGjQZzF1ifBA/JGwKybHRbYtrUnXAAGf53P9wQojAq/leF0+GHcUGgk/v6aX5HAgEax3SqfxmObaoP2ocQWZUqnQXatv9GZmv1SwKJlTif0C0L2oTqLkaMKHgqOyNUQOEiCfTsORYIhLxAgNri1q3bUKZsecEYoXc6hT379xlgxtikcEcO1T/gTYnpeCJ1Cdy+fUcxjOwxfWmcrVm7DlCVBOzes8cmaWIq1a9XB+jEPZ1E9YSjj/Y//1wGU6dPF6e85Sld46l+b33oUR2IYTVjxkyg031GhifVs1atGtC6ZQtxYjw4dfb0R7ssCzHtiJE6C0+UEVNad3QCPoAh3QZKliyhB4lnuilDcckVKfI1zJ39u3g2+0fYlCpTDoXAZ0VwtapVYMzokTakrrapTUQTD7MPS0qfbgmMGTtOnQKWUbNmyQKt8URY+XJlpZfpLzFjUE0SbEWG//UbNxQNrTPlMO7PXbtAihQpYPSYX1wWCKhEPjwQg5bwNzo0KqgYLVs3bxCnK4009E7xV+PtBGLgEsPa6JInSyZuP9FYMZ7MNNI6enfGhJdxUSWVuAVBt050xjnVMbW/vzhF3g1xS5gwoYzi9q+zsnhLIEAFvXv3rsCayqDXj8Jo7suGp2OJMW88kUjh5FwRCBAdncClG2h79u4VY0ln5NPJ+T69e4nTzCSsdEUgQGlS/5gwYaIQYNG7dCTAaNa0CbRu1QIPUUQH/fSkI4EAxacbCzNm/g4L8RYCqjuSSYpfOsFZongx6NChPWTOlMkqzOyF0po0eQosWrxE3ZIiOlrXypUrA927dcPbaEnE+vMxCwSozq6uy2F9zTObu6n+rjhPzn3BnbeMAgHak12+fAUGDR4KGzdtUjdpqF4k2KpVE/cLrVoKobmzunpqz+WNvQWt92PxNgTdRLt48ZLV3ohuENK4r16tClSvXs1ZNYVgkebVoOxRnCauEYSFMTNt+gycBxfDuXPnrfoO3WDp2f1noIMbtP92RSBAVffFuT84Y59uxaFKJcTnnLoBSfWkPQ7dfCuC44/W4ciRI5O3jUNVioBGmcWNHbrtS4IDEtCxYwQ+RgRYIPAxtirW6d27/4nT0KRqiBiBSZLGwY+rWKbMUEcQvH71H54YvIcfo59ACjxVTapGguOIyXv71lP8KHiNm/Y4kDhJbLfLZMzfU3U1psvvoYvArZtP4Cb+JUocCxnOcVCdky1DxFMl1FX++PnHhwmTansqaY+kQ7cmLl28B7FRnRGp8SLhWXAc8mvhyeOXQKI+EoCYCUn09OkGBQklaD6hdkiAc0mCBLG82iZ6/vzsOwiQYAgNS2IfjIICwnhOC0andYhRSoKEuHHjCNVAiRIlctrnnCbsgIA+jh/gCVH6jY/qI8yYqQ6iBzuITibewDrfuHETYuApen88fURqY8KKI9zoij6pOCIGXorkyQUj096HU0jUK7ht6uzDkup7Fj+so+LHIp3ADwozmk4lnzxxEj7Dj0ZibBPj1FuOGF1oxFucgqU8jh89ZKOeySxvUttF4/Hu3XtCpRapN9JvepjF8aYfYUZX+KNHiy4+0nUVVN7MNyTSprny1q2bAu9P4BOhlspTAlBj+UmYd+ToMVRhSWoA/U1v3BjjOHonNR90Ipf6ix/2kZQpUwR7HiXGIM2JN27eELeRaV4kVXJBmZ9JGHL16jW4ifgmTpQY0qRJbZex46ieH0uYu+uyp+sdFtY8T859QZm3zAQCsh1IBSDdziNhYrKkycR4I6FAUFxo7LlcLSfNAaQqjJitadKmARJGB8X54h7F3Xp4aszQ7czjKGT/FIWiaXEedGVf7qisvj73Oyq7WRj1FRIkX7x4SQiLU6M6RHcORhEepO6KHSPwMSPAAoGPuXW5boxAOESAbjfMQx3471EoRq5KtVzIKInmEIm5s/cKdVVEVOirtHjdsJRDeg5kBBgBRoARCDsIOBMIhHZNdJ22ZUqXEqfkHZVp5z+78LZngN72zz6LB0cO2Z78dxSfwxgBRoARYARCDgFHAoGQKwXnxAgwAowAI8AIWCPAAgFrPDzytnrVUfh10naPpMWJMAKMgGsIrF7bVhGOHL4BDVoGqKMo+k0G+LFTcTwRYH7DgHTw90fbBVI1Vt8B5SFv3kB9guVKT1Dp8oP3ECAj5W3aFfVeBpwyI8AIhFsEfF0goKu4IVUyf8yfZ/d6Op12q1i5mjhNSg3aCtVQdf+5a7htW644I8AIMAK+jgALBHy9hbh8jAAjwAiETwRYIOCFdmeBgBdA5SQZAScI6AKBSxfvQ7s2AfqsKVrKlJ9B9pzJ0VhiItSznABevnoLd24/ha1bzljZtSBDwwMGVUR1JoGZsUAgEAtvPrFAwJvoctqMQPhGwNcFAmTzosCXhYU6LmopUjFVFG0x5MqZU+iBj4A2oMhg846d/8AffywCaSODDAGv/WtlmFJJFb57IteeEWAEwiMCLBAIj63OdWYEGAFGwPcRYIGAF9qIBQJeAJWTZAScIKALBIh0w/qTMB2N8pLBYFdcpsxJoP/A8sJosU7PAgEdDe89s0DAe9hyyoxAeEfA1wUC1D5klLpjp87CKLYr7UV2DubPnS1077tCzzSMACPACDACoYMACwRCB3fOlRFgBBgBRsAxAiwQcIwPhzICjEAYRuD+vecwYdxWOHDgqjAwalaVxIljQ6UquaBsuaxeNXRqljf7MQKMACPACHgfgbAgECAUyFjq8BGjYPacueoWgBEdMnBXrWoV6NSxQ6gaBDaWi98ZAUaAEWAEzBFggYA5LuzLCDACjAAjELoIsEAgdPHn3BkBRiAEEHj79j3cvPEYVS48hBvXH0OkyBEgXrzokDpNAvDzix8CJeAsGAFGgBFgBEILAWK0X7p8WWQfLWo08Pf3E8+++u/9+/e4Xl2Hc+fPw3n8e/fuPaoFig+p/f0hT548EBFVCLFjBBgBRoARCBsIXL16FZ6/eCEKmzJlSogZI0bYKDiXkhFgBBgBRuCjRoAFAh9183LlGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYgQAEWCDAPYERYAQYAUaAEWAEGAFGgBFgBCmsum4AAEAASURBVBgBRoARYAQYAUaAEWAEGAFGgBEIBwiwQCAcNDJXkRFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWCBAPcBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGIBwgwAKBcNDIXEVGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaABQLcBxgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGIFwgAALBMJBI3MVGQFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYARYIcB9gBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEwgECLBAIB43MVWQEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYARYIMB9gBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEQgHCLBAIBw0MleREWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYIEA9wFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUYgHCDAAoFw0MhcRUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoAFAtwHGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYgXCAAAsEwkEjcxUZAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBFghwH2AEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYATCAQIsEAgHjcxVZAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBFggwH2AEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARCAcIsEAgHDQyV5ERYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFggQD3AUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRiAcIMACgXDQyFxFRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgAUC3AcYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBiBcIAACwTCQSNzFRkBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAEWCHAfYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBMIBAiwQCAeNzFVkBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEWCDAfYARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBEIBwiwQCAcNDJXkRFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWCBAPcBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGIBwgwAKBcNDIXEVGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaABQLcBxgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEGIFwgAALBMJBI3MVGQFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYARYIcB9gBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYAQYAUaAEWAEwgECLBAIB43MVWQEGAFGgBFgBBgBRoARYAQYAUaAEWAEGAFGgBFgBBgBRoARYARYIBAO+sCbN+8gcuSI8MknrlXWXXrXUmWq0ECA2vLVq/8gbtxooZE958kIhAgC9+/fh5gxY0LUqFFDJL/QzOTGzZuQNEkSnM9dnNBDs7CcNyPACCgEXr16JeYoV8euu/QqI34Itwj46lrI61a47ZJccUaAEWAEGAFGgBHwYQRYIBCKjWOxWODRw5dw9+4zuHfvmWDaJ0wYCxImigUxYkQJcsnevn0HixYegDOn78D583fh2dPXmHYEmDylLiRKHNsmXXfpbRJgD59EYPeuizB29GZ48+Y/qFYjD9Srn98ny8mFYgSCg8DwESNh8q9Tcc6MAWNGjYCSJUsEJzmfjfv+/XuoW68B/LNrN/j5pYL5c2dDihQpfLa8QS3Y+PETYe78+SL6D+3bQZ3atYKaFMezg8CTJ0/g21JlRGi8uPFg3drVdijZOzgIvH79GiZMnAyHDh+GY8eOw6NHjyBKlCiwdfMG07HrLn1wysZxQw6Brdu2Qbefe4gMixcvBoMHDghS5o0aN4WTp06JuLN/nwkZMqS3SscX18Lwsm5ZNQS/MAKMACPACDACjAAjEEYQYIFAKDTUnTtPYc3q47Bh/Ul49uy1aQn8/OJDuQrZ4ZtiGfADMqIpjZknMff79VkNRw5ftwmeOr0eJE0W18rfXXqryGHsZfGiA/ghfgauXn0oSp4mbQKbGtDJvThxosLnn8eCHDmTQ8EvU0OkSBFs6MKCx4/tF8G5c3dFUUkgNGd+E2SaRg4LRecyMgIuIfD48WPIk68AvH37VtDnzpULViz/06W4YY1o85at8H2jJqrYbVq3hG5df1LvH8vDwEFDYMrUaaI6vXv2gGbNAuv8sdQxtOtBjOnsOfOIYsSP/xkcPrg/tIv00eVPzH1i4O78Z5dN3bZv2wL+/n5W/u7SW0XmF59GYM3addCiZWtRxnJly8DkSROCVN6y5SvC0aPHRNw1f62EbFmzqnR8dS0ML+uWagh+YAQYAUaAEWAEGAFGIAwhwAKBEGys//3PAtOn7YRVK44C3Q5wxcWMGQV+7FQC8hfwd4Ucxv+yFdavOyFoI0T4FIoUTQ+p/D6DCJ9+CsVLZoRYsaxVarhL71IhQoiI8Nyz+6LKrUDB1PDpp/bVaEyasA3W/HVc0bvyECt2VOjRqwxkzZrUFXKfohk6eB3s3HFelOnzz2PCjFkNHeLjU4XHwhw5ch1ePH8jipUpcxKIFy+6rxWRyxPKCLx79w4KfFkY7ty5I0pSoUJ5mDj+l1AulXvZ04n/p0+fikh58+SGBAlsBZUUePbsOZzDv1OJDxk8EOrVraPeP5YHFgh4vyVZIOB9jLt26w7zF/whMooYMQJUqlhRnOiO8GkEqF69Kqrxsz6c4S6992vgeg50CnzDxk0qwrd4SytChLB5kEJVwoMPISEQ8NW10NV1y9V10IPNwkkxAoyAhxE4ffoMXLp8WaTq7+cHGTNm8HAOnBwjwAgwAoyApxFggYCnEbWT3suXb2HYkHVwYP9VK4rUqT+HlKniQ2JU5fP69X9w+/ZTOHvmDjx8+ELR0an1xk2+hMpVcyk/ew8tms6FGzcei+D2HYrBt99ltkcq/N2ld5hYCAe+Rt341apMUbkuWdoCokaLpN6ND0aBQLRotqflqQ2MwpqoUSNB3/7lIGu2ZMYkffr91q0nqFbkX1RT8BJq1soL2bKHrfJ3wBsO5z/ccOjdtxx8kd/Pp/HmwoUOAsRImDBhIs6hieHHDu0hZcqUoVOQIOZaplwFoU6Eos+cMR1KoEoJe27uvPmwcNFiKPRlQSB1OtGifXy2QVggYK/1PefPAgHPYWkvpSLfFIeLFy+J4BHDh0KtmjXskQp/d+kdJhbCgS9evISMmQNPq58+eRxvI7IAXzZDSAgEKC9fXQtdWbfcWQclrvzLCDACvoXAgIGDYeq06aJQzZs1hV49u/tWAbk0jAAjwAgwAjYIsEDABhLPe9BlgJ4/LxcnnmXquXKnQH3Q+SFjpsTSS/2+e/cetm09C/OQmXsP7QtI17ptUShTNvCjS/rL31ev3kKNqlORoQ3iJPi8BU2ATrjbc+7S20sntPyDIxCoXScf1DXRqf/27Xu4jYz048dvIjN9Lzx+/EpUj9Q29elXDrLnSB5a1Q13+bJAINw1ebisMDNCrJudBQLWeHjjjQUC3kA1MM3nL15A5izZxeECOil/6MC/eMMtXiCB4cldekP0UH9lgYDjJggpgYDjUvh2KK+Dvt0+XDpGwBUEWCDgCkpMwwgwAoyAbyHAAoEQaA9S4UOqeaQjpn6rNkWATv47cnRLoHePlXD58gNBRifaJ0+pA58niGkajW4WdOywWISlTZcQxo5zfCLNXXrTTEPR0xsCAb06L168hT49V8Lp07eFd/z4MWDm7O/DlNodvT5h7ZkFAmGtxbi8QUGAGSHWqLFAwBoPb7yxQMAbqAamefjwEShfsbLwyJYtK9qMWhkYaPLkLr1JEqHqxQIBx/CzQMAxPhTK66BzjJiCEfB1BFgg4OstxOVjBBgBRsAWARYI2GLiUZ/HqK6lRbO5QMxlcoW/Tgddfw7UA+0ss2dPX0PL5vPgyZOAk+pkS6BXn7Km0U6dvAVdOgUY1MycJQkMH1nVlE56uksv4/nKr7cFAlTP69cfQfs2f6DR0vei2r37lkXVNf6+AsFHXQ4WCHzUzcuV+4AAM0KsuwILBKzx8MYbCwS8gWpgmvsPHITKVaoJj3z58sLSJYsCA02e3KU3SSJUvVgg4Bh+Fgg4xodCeR10jhFTMAK+jgALBHy9hbh8jAAjwAjYIsACAVtMPOqzcvkRmDplh0iTTvhPmV4XPvsshlt5bNpwCsaO2Szi0KWCWXMbqTSuXXsEWzadFmEPHjyHLZvPiGcyIvtNsUBjPmRguF6D/OAuvbGgJNg4cfwG6na/B+fP30VbBy9RZ3c8NFwcH+hWQg43VOrQDYj1607C5Uv30SjoMzR8/AkkTBQbDe8lgpLfZUIdtFGM2Yv3ubP3wvv3/4N3+Lfsz0OKhmwsRMR6SlejVh7UsR1oJ0C3IWBPZZCMq//2xlsCBw8E2H6oVj03fN/4Sz1YPZ/BGxpn8DbBlcsP4cqVBxApUgRIkyYBpEmbANIhNslT2FcZoBL58EB2IDYgNteuPYR7955je0eHVGhrggRK6dInFFRXrzyErVsC2pvwL/pNeqtkzp29C7v+uSD8MmRMBGR0WXfHj91QNi3IvkDuPCmBDDX/u/cybP/7LNzFNvkP1VelwHJT2UuUzATUr1xxZAvjKBoFvoK3W+iGC9nQSJ06AIvUaT6H9OkTmd60oL4ubWBs2nhK2D+g/Ap9lRaSJo2jsv66SDrwR/sbZu7t23ewfds5OHr0BmL3DEioFg/HXMKEMYVx7nxf+Dm9nTN3Dvaxd/8TyddvWECUlW7U0G2fa1cfwbNnryFHzuTQsnURsyKEqt/IUWPg3bv/RBm6dO4kjDuSXYy/1qyFf/7ZBWfPnUN7Ja8hFeraz507F9SuVctlfc9kPHLb39vh1KnTcObMGbhw4SIkSpQQjW5nhaxZMov07BnFNQNl9549sGLFKrh69So8ePAQ/PxSCSNkdWrXwnQTiSgbN22GAwcOiOdvvy0JuXNZ21JZtWo1nDh5UoRXrFABMmXKaJXV4sVL4MLFAOPjNWvUAH9/PyAVHcuWLoet27bBrVu3cZ6IimM0nYhLur6jRrWvak1PnMq9a/cexOIs3iQ6Dc+eP4csmTMjFlkgS9bMkCN7dlPjmosWLYGLlwLKtGjxn9hP74lky5YpLTCQeZCR5MyZMslXmDBxMjx/HqBGrl3btg7bjdp8+/YdsG79Brh2/bowvBwnThxIljQpEJOycqVKDuNTpt7ETlXK8GBPIHDlylVYuHixMK5MuCdMmBBS+/tDrVo1rDAyJGfzGtQ2MyZEqv327d8n7D8cPXYMLpy/CMmTJxd9iAzpFS/2DUSJYr6GGdO6e/euMEBL44raKmLEiCKtXDlyQM2a1SF27NjGKHbfyUA1GbOlU+dXr16DmDFj4nybDr4u/BX8n73rgLOiSPp1KnAcZvw8s4gIKKCgSFBRjEhQkZyTIpJzEFGSILAEyTmz5AwiEgQUJUiSpAKCioAooCigiHfz1b/X7q2ZNzNv3r63gfPV/t72THd1qo5TVV2N8QNILYEALhScO2++ulTw6JGjlClzJrrpxhsVTapUrkw33hhqIlFWJD36m8wfzymtw4EDB1Tdkcb33x+nefMX4FHVucKL5dUz/l166WXUvl0b3j9Fhm8S+Ovh119/pY2bNqv+t4v733HuQ7l5DkPfK1CggLpnxBnH6z2l/S+h/0Dei/1JFy78aexGIw/Yjs6U6TKTXbNmTenybJHte01kfoh2zLqtiUeOHqUZM2bR9h07CPXHfHJXrlxUuPADVK5sGZm97zPmpcTpM3he2kdHjx2jG/kum9y5c1P58s+rtQCR00ogkJK1EOtu4vTptGnzp2oduv2223k9v4fq1qkdcvE1cKdzXfd+/jnv675Ra2khXo+L8Hpy3333etLJa91K6TromZFPwKefbqH5CxZyub/m75afeG+ek+7htbpmjWrGnBf2A5t4TAGefOIJtU7KJIePGMV7v1+UV5A+PXPWbJUfImBP43e/Edbr1R+soRUrVvK+/zCdOHlS7YFuv/02Ks/7GqzZfrBx4ybem61TKMWLFaPHHntU7XMwp65du071TVxoPnBgglpPpk1LVLiZM2ehNq1b+iVtwqZMmcbpHFXvbnstg+jx4DYOM8reNBL6yT2ZrmpqzFH7ea8+ZWoifc57y7NnzqpL6TE/VatalfcI9kvbsXdYsHCR2pf/eOKE2oNif/9Q8WK+/U6XH25K+6CkHe4xwd4DULDgfbZ1CO/Pliqlwtz+YR8/dy7vHw4dUv0V+9VbeU9VkvtymTJlQuos05BlCNf/ne0Xy72cLFP8OU6BOAXiFLhYKBAXCKRyS3VsP58Z6EkbqIrMTK7vwUz2KwbuBHi5wRQ6zkxWAJiQ5Z4roJ43bTxEPbu/q579/mHzsHBJY4oUX6YJBnPvXu/Z7jWQ4Xgu/lBOwmXGV1zhzVADM3/8uI/5GP1uZlwmad4708HlwDVrFnG9SPnF50fyB6h7PJnOFAhO2MyPhpQKBMaNXU8L5+9QyTxWMje17/iMTlK5EJKMZaEPGNh+AMYyLvf1A5xEGDZkjWL0Y3PmBAiEnimVjxo2ekQx89/m9gA8UiIXder8rA1dmqoqXSY/NW1e0hY+d842mjThE+VXueoDVKducRqQsJLvr0gSMtiQ+eVf/8pM9flya6TlBSjzAqbVtCkbzakKN9xixe+gDp1KUebMyUwD4Enhi1s87deuwzMhAhCEvffubpo8aQMzTc9r1BD3+uuvUH20YKFbQ8K0R4UXRpryY9xs3HCI+vReroOVi/skevdJZvTYAtPxJVfuu+n8+aT6HzzwJX3DzNN27TrS1m3bXEuFTXfPHt2YQfyCa7j2BFO9TZv2tG37du0V4uIiydEjR6iP0ZBA4QFmTOMmzWj79qRxJYLUI9Jp17YNvfxSA3rjzW40afIU5d+rZw+qU6eWDb15i1a0cFGSSY7hQwcTmOgSatetrz6I4Zc4dbL6SClfoTLhY8sNIJTo368vFS1axC1Y+f33v/+lsePGExhimtZuyGDAokxOAUOtOvVoHQtWwsHQIe9Q+ReeN2iFixRXjH14bNuyibyEL59u2Upt2rZTTBsT2fEARnGbVi2pYcOXHCHJr6lBu+TU3Z+cAoEGDerR23360YSJk3jeTxJ0OWOWfrYUDRo4wFfAEW2byTxP8Ad346bNCR+hXpAnT26eywcrBq0XDta/t3r15o/+aZ51w1ho07qVYrJ6paP9cXlnr15vK0aQ9pNukSIPUr++b9O1bM/+3oIPqKDs2a+lHdu2SLSIn48fP04tW7VRl5p6RYYt/QoVXqTeb/UIGQ86Tnr0N513tHVYuXIVNXj5FZ2cp5spUybCvBwpvkzws892UqNXmxDmUS8A4yWh39shTF2JH23/u/OuvLxOJp1+lek6n7ds3mAEvM4wv/dYjVnnmvgFC7MrV6nGJ3fPuWZfgoVnGCe33Hyzazg8Qbs33uxKM2bOYqFI6H70kksuoUqVKlD3bl2VYBbtBYCwYeSIYeo50n9ln3uBFR12qWjL3l1MBVgQLyHStRDCc6QJobgTsLYMGpBg1vKpzJjs0y+BIHB0g9c7d6JXG7n3f691K6XroFv+Xn7h5mrsfzp1bE+1atagXr370KjRY1RSuAwVgi0JRYo9ZGgVpE9Xr1GL1rMSBmDWzERmzhaXyZlnMFBbt2lHB776yvg5HwoVKkgjhg/17JMjRo5S6yTiNWvamFq1bMHfT5WVwFCmNXf2TKW48cCDxZRgGGFLFy/0FegA5/Tp01Tw/ge53/+pGLNbNm8irB2RgHMcZqS9aST0k3vD1JqjtrASTI2atV2/kWGGbhTPIRAwYf7t3vMtSkyc4ToPZc2alaZMmkDFihX1bapo+iAEZX369vNNH4EQivXt0zsED8KvVq3b+u6JoUwwoH8ClXjk4ZD48Ehp+4WbH5B2kL0c8OIQp0CcAnEKXKwUiAsEUrHlfmJzQXVqTlRSd2TTf2Al10uEgxQBpwxw2gAALfxefzEit2z5hvr2fl/5Y2Ny/vyf6vkS1rbPkiWTesa/TJkuoemzXqZI8XUC0NwePmytYcRD8z7HHdkpGzOJP//8mDGJBHww4WGu6IYbQrUaUb7eby0zmuk6/auuykrnWbMbZoAklC1XQN23IP1qVhuvmLUWWTZ8CBH+wX8anKcxUioQmJ64mS8YTtIaeujhO6lzl9I6C2bO/UId282nEyfOGD88/Bt1Z34+/CEA0VAa90ewQAft44Tff7+gGOJ79xwzQRAA4ERJtsuzsCDmDOEiaABOCkAIEEuBgMWnAyAkAOB0A+qAUwLQuJcAwQPydgJOF3TutJBw8kDClXyx9ZVXZmUtPHtauFC7a7dytouve/VcRju2f6eigx5aKALBAU65aGjZ+omQMowasY6WLkn6WNZ411zzL7qS+9ZJbgcpJEBaTZo9RqWezadRba4UCAweWpUg2EN5JFwMAgF8tIL5/R1rHQOuy56dsl+XnY4ePcaabkma5vDHfSYQCkAr0A1Wrf5AMfBxskADGHx35MhBp5lBgE21bisIH/v17UOVK1XUqDYXmrHVatQ2jG0EQiP65ptv4nFxCZ8QOWqYTL179VQa4bESCEwYP1ZpsmpGLjSvr732GtbI+872MQUG/poPVrp+fIP5U40/9HUaunJI55qrr1FMOkmnB+6/nyZOGGu0EIHf8JXGtH79ehX13G+/8cmcpDkC+V7GdNWQkNDXpq3qxVjR+HChJda2XQcbgxn1xAfVTz/9rLRAdVsBv3LlSiwI7Ot6akYyaGNBO+QXDpwCAWjdjhs/QUUDfaCFf+7cWaWFremGQGifQeDjpk0fizbT5QYz9qWGjUz/BYM3V647Vbl2795tGEbAz5w5s/pwf/rpp3R04/7G7f4KMwmhvSkBTBb0HyezEoIwCMS8YOjQ4bzuDrAF63bHCRRoxQLARJg2ZRI9WvIJ9R6tQADawnXqNjD0QKI4GQFm6h8swDnGGqVS8A9mxtTJk1yZSenR31DeWNQB2sVNmjRHcvQfHs9oXwDmyazcbzVkzpKZPtu+VZ1OigRfx4dW9WuvdzFzJDTvcSrgiiuuJDCR5LyOU1bz585y1RCNRf8reH9hOv/7ed7qWLb+CiGW3IutW7taaeDrOgRxYzlmJSNy3ZrVVImFAfpU1k033ahORn7/vZ0pDpouX7bU9YQXBJMNX3lVaXTrumANBRP96quv4jXsiKEHBDM4LfBq46YKNaMIBDCfD+cTZ1AUQNmhiY61VwpdITRetXI5QbsewgYNwP3xxxM8D9sFKt27vUkN6tfTaMb1WrdSug6ahMM8QGBWrXpNm2Ac4/EmPiWHEyxY93V9E/r1USce01oggBOQTZu1MPMFqoQy3sBj1ynwQ//CGgdBjhOcDNHjx3+gOXPnOdEIAgEwtLu80ZUmT5mqwiHIgUDHD3DSoA3vKwBPP/Ukof9ECnIcZrS9aaT0Q91Ta45au2YVm5yrrAQ22F9gjsJpP7lvwzq6eOECbsc31QkllAf76Ntuu1WdqJJrLubjaVOnUOEH7gdaCETbB8eOm8AnTwapdM+zgEKPKZQ9C++BNGCv2aN7V/2qXJw0qlm7riqzDMBJ1uM/HLftHVC/gSykdFNeSkn7xWovJ8sdf45TIE6BOAUuSgrwAvO3ATbrYLVt39G6v3BR65bb7lAu3uGfGrBj+2Gr7LND1a9albEWMy9SnA2brDFpVee03GDvnqMGp33buW4oNr+g+N9/f9p6odwIlXa50kOtsWM+si5c+NOkxQxva9++4xbflWDyHz3yQxMuH+CvafJ82eHWzBmfWl999SPTxuI0/2Pt4ToMG7rG4ACXNdZlEub5t3N/2PDw7gfDRbqswe6Hagvr0/s9k8/oUfZ6ybLWrjHB2rjhoPXzz+dM/PPnL1jz5m5j+g03afBJAhMuH8Zw2po2cFFeZmRLFGvb1m+sxo0SFV7bVnMMPgsGbHh4Wf7ebhPOpw5CwufM3mrCUXbk2aXzIotN/VgsuFH46LPoxw3qTTa49epM4vALIemxmSGDg7ZdumSndfTozwYPbbz+owNWnZpJeSG/QQNWmXDnQ8vms0x6fLLFGWx7X7lir8FFuv37rbCOHTttw2FzThbGBcLxQxnZ7JUNR7+8+HxSfwcexhtctMeGT76yfjp1VvV/Fvhp9Azlstammt8wxz1bupx6rt/gZYs14m3l/GTDBuuZUmUMbo6cuay9e0P7JvpAySeeNniVq1S3NmzYaJ09e9akx8wUq0279gbn1ttzWnyE2oTrB9Yus0qXfc7g3XFnbos1vy1mLGgU7lvnLda6tPLeU8BCeOkyyfiTJ081ePqhWfOWJr1FixZrb+OyFqIJ13N/t+49rd179lj8QafwWMvK4uPwVp678xlcZuCYNOTD4sVLDA5ohjLxR41BAb3YPJPFTBCD17ptexPufJD04A8zZ7DtnbX6TJps5sIWhpf9Bw5Ysv3LPV/e2rz5Uxved0eOWO07dDLpoJ9MnDTZhqNfYk07na6fyzZoTdmeeOoZ9VywUGGLBR0W+o8GPhZvde/R0+CiHp1ee10H29xYtRnyL/n4UybP6jVrW6xZbsvr0KGvLfQdlAe/p0uVtoXrlze7djc46EdDhgxTfRL9hz+orc2fbrFe69zF4CCthQtD+zfS4xMhFsaczpPtcav4Oi+4GNs1atVROJquwL+v0AMSLaJnFlxYj5V80uTLGqSqjHJ/wGa0rDFjxlk5ct5l8F5p1Ng1n/Tob7GuAyqG9tBtwVq6rnWVnkHxDx8+rOZEpI32Zs1QC3OXBvRPZnLY+ij6mRvEsv+dOXPW1Bdlw3u0EKsxi3LIORFrQM5cedR8L9co1oC2Xu/ypm0cua03SG/osBG2+mINkmlhDLMQ3Xrk0ZIKT443r3UF6YYDjGvdr9hMWQh6JGsha7tbt9+RyxozdryZw7D2frBmjZWvQEGTz1PPPGvdleceHr9Ja51ed9DXdu3ebbFg0eBizdZrqixcuHULuJGsgzJtv2dmNJqy3ZbjTmvwkKEWn3AwUVDfqdMS1bqPvcbzL1Qw+KPHhH5nPVg0eU3HniccsDDCpPfxJ5+EoGMtlnsOvndE7R3QFwHIg02wWcWKP2LSQV/C+uCE4SNGGpx7C96vnrFWYX/Fp0rUPPHzzz9bLAhUUVkj3OAXe6iEM7mQ9zp16xv8pe8uCwkP4iHHYUbbm0ZKP9Q3teYojE3sedjUmJlL0ScwVtGP9Ryg+yvGF+YbPe+ijd9/f4Uatxq3Xv2XXJsoln0QGfTo2cuUD89+gDlE7u+xZ2bzaxabTVTRsHfAnrhK1RomTRYq2fbbOv1I2y+Wezldhrgbp0CcAnEKXKwUgMT5bwGLBBNHL5DSRXisYc0HXxjmYytmbkYDYG5qRiaY8mCeOyEog1/HC4ovGcevdVygo4e4hw6dsNicjypn5Qqjmcl33obDNtitcqWHmXqwSRtbuHwZ8s5qg1ez2jjexCZ/9Gq8tBAIsFa4VbfWRFMWMNk18J0NVvnnkhjHrFFu7WehiBdA8KHbz42GbGvfRhs23eOVlMV28S3NwNdpRisQQDod2s1zZfSjIOh/UqgBxrgTmjWZYeq4bGnox6rGZxNaBg/9RQsfdLh2gwoEfjn9m1Wl4hiTZtcuiz2Fb2fO/G69XH+KweULo3V2NlcKBCA48BLi2CJlkBf50YU5Dh8Nkmkki8knBRRDUM+FFStXlcHq+b3ly81mHB+Y+mPViQgmCBikOq1B7wx2olhsGsWEA2/WrDkhONqDNacVw0KnB9eNQRMJEwRp+H2k4ONb5ocPaCdIIQrq4wVgxOu08BEDxqMbRMIICcdYAfNR5wnmxYkTJ92yVH5gymrc3HnzKeaDE1kyaIEbLe2c6bu9S4EA8gQjik9juKEqPyncwMcymFROiFWbbdu23UYzKciSeUJYJgUHEKBJADNGfthDAOYFsn5gEkhBnI5T6tmyplzoI6z9rINsLhgFkhagbzQCgX4JA0y+aCe2v23LT75A6KT7G1wwLJyQHv0t1nVAnYIy+HX9g+JLpgeYJF7A9qQtzDmgM5i0YKxIiHX/Sw2BgOyn0c6zck0EE3z58vclOWzPfLrK9FOUwQlg0oJBrvsyhGxuTHDEg4A27935DS7iZBSBAMoCZrgbYA7V9YOLuWrxkqVuqBafKrDuznevwXcqHiBSuHULOJGsg8APB2hjWYd3Bg/xjLJk6bs2XMRLC4EAmLS6jGD0S2GFLCyU1iSNR44aLYPVs5wbkOZzL7xonTp1KgRPesg1CnOCF2DPB4EJ0oWwCIKUlIAch0grI+1NU0K/1JqjICSCEMcN2FSl6TOgIdZvtzGHuCtWrDS42Du4QSz7INKPRCCAMYY64Ic6Q0nHDbC+yD0OhFNOiLT9YrWXc5Yj/h6nQJwCcQpcjBT4WwgEsJnSi46fG+uTAvNZM1wzbLu9GZ3Awcn8ZlM0If0tKINfRwyKz6Z2TD3CadafZuYsGNb4SS1B5PnOwGQmP04Z+AEfd7TatJxt8l3/0f4QdCdNUuOEgNTaB9Ofzc6YckBLXtcVTGk/gKa87gu1WUPeCZMmfmLCITxiMz1OFNs7TmRoYQTSjVYgACGTPNlgy+yvl4S+K0wZ587ZakMBM1jTwq1v2pD5RQpZjnz3kzNYvQcVCCx7d5cp10t8koEv/HVNT3tCcIW21O3hJsiRAgGv0y46vYzmyo8ufAQcO3bMt4gfrf/Yxnj/5ptkbXdExMcgBAf4aQ0krwTB2NRzLBj1TnihfEUTzkfWncEh704mYrQCgSefLhWSh/QAY6dosYdNGZ0fyQjXtAhHV6QrNQoPHjzEPqEQCSPEj7HC9odNuaEBy/czhGYmfNCW8uSHGwNEMmijpZ3I2vfRKRCAVpwfgDkhaYjTHxJi2WaSceQmPJP5ggmr+wqbcZFBlmQ6QsvbD7COgrmjx5VTOxMf0ToMWvhgLvsBxvc9+e8zcVIqEMCcL/vj+AkT/bJVYXzPgMnXTWMxrftbatQBFQ3K4NcEC4rfucsbhn58QaeO7uryBbCm/zkFwrHsf8g81gKBWI5ZlE+uiTgF4Ac44aPHEwSlTpAMOawV4Ziu0PLV6cHNKAKBcPOXXBvKv1jRSQbbO9vKN3VkMzW2MLzIeUKfMHAiyTk83Ek5Z1y3d77Pw5QJcw3Guh841x239VCu59GeEIBmtu4XmI/x7gcrVq4y+BAeOEEyRCHACdcvEZ8vezZpsqk+Z5LmffacuQYPp9ZSCnIcZrS9aaT0S805ym9uh7Bf9xu4ffsleDYHtOAlzZ19LNZ9EAWJRCDw0COPmbqgf/sB9ttauIr+7VR6iLT9YrWX8ytzPCxOgTgF4hS4WCjwtxAIwCyQXEC9noEXS+ALWw3TcUBCqDZcpHlJDe2DbGbHCUEZ/DpeUHxoe2vmaYtmM1nTNfS4qk7TywWDv1rlJNMrSOvA/lBzF864idM2mXz79XnfGWylpkAA2v9oMzDKdd2h5Z9SwMeITue5MsNCkpHmlmBqJwh06jDfpBmtQOCVl0JNsTjLMFeYGBryzgfO4IjecRpB0wMnBtwgqEDg9dcWmrRmz9rillSIH99jYeJgnDpBCgQ2bzrkDM7Q7/IDgC/6ClRWyagPx4D1S5Av0DNzLY7LSwAjQJo12bdvnwx2fQYjS2umYd6OViDQsVNn13ykZ+06yUfjYaYmGqhQqYqhB04MuEEkjBA/xgpMzui1DaYSgoAUuEBbzwmSQZtWtJOMGWg3BwG0k6578YcfDRLFE8evzaDxq/OBBrY0E+KZoCMADP789xYy6biZ/nBEsQYOesfgN23ewhYsw6CtHAQgjNP1SKlAACaNdBrQmAaDJBx88cWXJg7GtVNQktb9LTXqABoEZfBregXFlyesYGrB64SKTtfNjXX/Qx6xFgi4ldvPz2/MIp5cE73Mbsn05QkAJ+MXJvN0v4fpoCAAYaqOk1EEAjgZ4wdSeBduHyGZgAn9B4Yk67duaeRI1kEdx8vFSSjZhny3hheq8UcflvuT1BYIYJ+l+wRMOoYDmAmSe6GvvjpoiyIZojAtFQQgsNYn1fzMBtWt18CUNQgtvfKW4zBcn9JppMXeFHmlhH66jEHcSOYoKOn4AUwK6b6zbp3djK0znhxX2J9LiHUfRNpyLsCzF8hTSDj9Ek5gh3Tk3Dstcbot6UjbLxZ7OVsB4i9xCsQpEKfARUyBv4VAQNuN1guolwu8WII0tdOzu/tx26D5wayKZqDC5ctsQ6IGZfDriEHxYc5G5g3TMDCH5GbGR6ftdKGVrdPAfQTO0wNOfLzDLI2O0/RV++KP8GgEAkgXTG3njy+1tZpwXlL7HrhTJm1AllGBrgvMJkmA4hLM0ujwz/f6a3TruOPHrjdxohUIwOZ+OFi3NvmOANApGpC2/PkSYtekggoEpLmgcHcN6IwSpyYLmyBQcIIUCMhTIU68SN5hvmX27DmBf9qOZiR5AFd+dAVhfiAOmL16XnTT7AdOEMC9BDqdqtVq2KLAnIgOw8c6tJeCgLSbHK1AwM80iy4L7NDrcsL+bjQgTfh4mVORH2zhNCP9GCt80a0pt9+HmKyPbC9olzs/yiSDNq1oJwUC4TRTdV1gIkW3GVw3U08aN5zr12agDxjoOi/YaoZ9fOc9An55yLKCwePU3naLK81fwKa3BDCTdHnCnTbQ8fAxreOkVCAwbvwEkwb6cBAAU0veJQCGvIS07m+pUQfUJyiDX9c9KL7ztCtMVsxfsNDVjJRO2+nGuv8h/fQWCPiNWZRPronyvheEuYG8FwP0kqC1VDF+wmm16ngQ4unxllEEAjAn4gfthCLVrFlz/FBtdyq4CRr81i2dcCTroI7j5ULIqukN12kyyyuevvMBcVJbIMCXUpsyQqgbBKSJGpw8kSAZos5TchLP+SxPdzhPRAJXmgsq8djjzugRvctxmJH2pqhESukXlACRzFFOQbkzj4dLJGvWh1NK0PcGoU87BQ2x7oMoZ1CBAPbWeoyC0R8EunbrYeK88WY3W5RI2y8WezlbAeIvcQrEKRCnwEVMgX+g7BflbcgRFJq1PgJjH/7mYGDccIhsd5zYTI5Cy3v3DdR/YKVwUTzDf/jhV2pQd7IJn7+oMWXOfKl5xwMzkql923nK7558N1K//hVt4c6XSPAXLthB48astyWB/HPnuYHyF7iJCha8hfLlv5n+8Q8binnZvu0wvfH6IvN+113Xm2evh++//4XY/IsKvuqqrJQ48yUb6u+/XaBKFUYbv7nzG9E/s2Yy784HNn1Ey97d7fQO+16lWmGqU7eYL96ff/6Xvj50gr788jjxXQl06tQ5Onf2PJ09+wf/4J6nP/74j0rjH0ykJcuamvTYzBLVrDbehM1d0IiyZLnMhHs9fLhuP/HJCRX8SIlc1KnzszZUvqOBhg5eo/xKl8lPTZuXtIXPnbONWDte+VWu+gDVrVfcFu584QuT6a0ey5T3Qw/fSZ27lHaimPejR35WtOCLfAnteI7pcIZpoF20nYa+CRW479ykX43bqsVs4pMk6v3NbuWoSNEcJkw/gKZs/ke/0vhJdejf/77SvHs9fLz+AL3da7kKvj1Hdho+sroNFWnq9lq4pDFddpl9rNmQA75s3baNyr8YfA4YPWoElSltb9MgWbHmMrEZFYW6euX7lDv3XWGjsaY48SWTCu+Rhx+iGdOnucY5e/YcfbbzM9q+/TPas2cP/fTTT3T6F4zTX4nt33K//8nEe/ih4jRzRqJ5Z1Mn1LhJM/V+f6FCtGhh0lxlEDwe+Ig6MQNThfbq2YPq1Kllw2zeohUtXLRY+Q0fOpief/45W3jtuvWJ7yNQfolTJ9Ojj5awhTtf+GOa2PyJ8u7RvSvVr1fXiWLe2bwEbd+xg9geKR0+fFjRQdID9NIwb84sKlLkQf1qXBZ40K5dSfPSxAnj6KknnzBhzge+dI2Y+ay8t23ZRP/3f/9nUFiTjrZt367eB/bvR5Urh+9raC9mCJs0du7YStdcc415T03amUwcD2y6gJgZo3xr16pJvXv1dGCEvjKjmXLnvYf4JJoKXPPBSsp1552hiOwTbZvxSQ+qU68+z+nJbXvJJZdQ3jx5qGjRIlS8eDF6vORj9M9//tM1/48+Wk/8kW7C7r23gHn2evj228PEQg4VnD37tbRj2xaDyuaEiBk56j1ou6OfoL8AnOkpzwD/WMOTho8YpTArV6pIAwckBIhFxNrStG/ffoXrnOPSur+lRh1QsS1btxFfEKrq+OCDhWn+3Nnq2etfJPhjx02gHj3fsiWVJUsWKlSoIBUtUoQwf6MfYp/hBrHuf8gDYyHvPflNdl/s3U3Zsv3LvEf7EO2YlWviwQNfUqZM3vtElJXtVdPezz9XxV75/nuUN28e9cz3wBALs9Uz/m34+EO65ZZbzLvXA8YJ+hqgXNkyNHLEMC9UX/+yz71AO3fuUjjL3l1MBfIn0xyesVwL+e4Smjkrqd+Gm1fY9Ayx6RJVrubNm1KHdm3Vs/7nt25pnEjWQR3Hy12zdi3v2Ruo4Ftuvpk2fPKRF6rNn+/VofeWJ+2p3+jSmV5p+LItnDWz6dix75Xfls0beK/5b1u484WZ7cRa2cp71sxEeqh48h4b8wPGvYYg64Bue8Rx7oVGjBxFb/dJ6mPNmjamjh3a66R9XRYoEp8GUTivNnqFXu/cyYbP9ypR6zbtlF+7tq2pZYvmtvBIXuQ4zEh7U9QhpfTT9U/LOYoFV/TNN9+qrMPNQXxalD78MKn/T0+cSiUeeVgXWa1RseyDSJgVOmjM2HEqD4wfjCM36JfQn/iElQmKtP8759GUtF+0ezlT+PhDnAJxCsQpcJFT4G8hEGDtFGJzFWGb6vrrr6etn24MixcUYeuWb6nrG0mMquuuu5wmTa0XNGoIHptVoY7t5yv/bNky06y5r4TgRMLgR+RI8Vev+oL41AN9dziZ6ScLcf31V9ATT+WlMsx8vjZ7NhlEaz74kviiXJtfJC/4tl2yLImZqOOlpkAga9bMVLDQLfRs6fz0QOHbdJau7ry524g1zg0D2RVJeDoFAidPnqW6tZIYkJkyXUoQCFx66SUihvvj5k1fU49uS1VgRhEIQPAzsP9KZhQnM8vcS5/sG41A4MSPZ6henUkqscyZL6N5C1/1FEol50j07TeniE+CKK+rr85K02a8JIOVkOFiFwhceumldGDfF4GEGaw5RDVq1lY0uPvuvLRi+TIbPfgIPnXo+BrxxYLEmjW2MK8Xp0CAzbpQi5atFbozzCsN+MsPDOdHMMJjyQRBekEEAmCqtWzdln788UdECQSpLRB4uERJYm0xVZbFC+crBmGQgkEgoAU5a1avoFy5cploac2gRcZSIBBOIGMKyg98QSJ9dTBJoO9G61i2GRjqffok0MZNm3DKUhZDPV9xxRX0XLmyVLt2TcqfL58tXDJgbAEBX7B+fPv1Vwab7fAqYRQ8grb7mTNniI/pqzRSKhBgDWKaNXuOSuO1Th2oSeNX1XO4f6whTe8ue0+h9X6rp6KRjpPW/S016oC6RMLgTwk+22mnEcxk5ntDNOlsLpigFStWoNq1aoQwLWPd/5BxagkEYjVmJSMyGoHAkaNHqVjxRxStIfDb98UeT8GLbJCVK1cR27RXXk5GlsQL9xwXCISjUFK4ZGKXZOHs1MlJ++twsdl2Ow0eMlShpbZAQDJ1w5XLLbxtm1bUqmULE5QShigis9kxur9wETWGIdwCg1kCn0CjVas/UP38k/XrAgnAZHz5rMdhRtuboowppV96zFGy70QjEJDpyHYK+uzsg4gn9+t+AgEpcAyan8SDcA1CNg0pbb9o9nI677gbp0CcAnEKXOwU+FsIBNqxpsusvzRd/BqsatUq1L9fHz+UiMKgGf1y/SkmzsgxNenWW5O1L01AgIepkzfy4pekFXhX7utp0OAqIbEiZfBHiq8z/IK1vtet2Ue7dh5hLYWTzBDRIUkuhB+9+pSnm2++2gRIjWx4QmM9CPzGmuRZ/9L6d2q4RyMQePSxu6hW7aKuRbiKGcTZsmVxDZOebMaJBg9aTdDU14ATCrfccg1dd102uvzyf3I6menyK5LcMaOStDScAoH//Oe/xCaKDB2HsbZ6DtZaDwfTp22m6YmbFVpGEAjMn7ddnThgqxqqTNCqv/HGK+nfN1xJV4AGl2dhmvCPaTtu7HpTvWgEAjhBUr1KkjYKhEZz5vmfEtGZspki6tRhgXpF+cZPTNbYhWdqnBA4ceIELX9/hS5CWPfREo/Qbbf5C6PcEtEfXQjbvu1Tui57+L60ePESPkHSUiXn1N6H5vvLDV81GpNAAhMxZ86cdD1rqF955ZXqd9VVV9HevXsJJwEATqY/NOWgMQe4+uqraddn29RzuH+Vq1anjRs3KbSMIBCA9jo08dhmuioTtE1vv/12uu3WW1S9QA/Q4ip2e7zVy1TPjUmNwEg0I/00LZ8uVZrYRrvKb9LE8fTkE4+bvL0e2GyT0niFC9i4YT3dfFPyaZ20ZtCiDFIgAG1EaCUGgXsLPqBOrADXqT0b6zbT5cHYmDd/AX3IAqLPPtvJQuE/dJBy0TdGDh9KpUo9Y/zBDAdTXEOtmjX0o6979uxZXk+yKZy3eydriLMJIT6NtU/5B213aBeCGQBIqUAAJ4pwsgjQ6JWG1OX119RzuH9VqtagDRuTFC8GDexPlZhxrSGt+1tq1AF1SW2BgKYXmBlsekPRE33AKZy68cYbaOb0RJ6r79BRlDAmlv0PCaeGQCCWY1auidEIBHAiDvMMAPu4z/fsCnQSApr2YIAB4gIB+8k2RRT+F8k6qON4uWxOhxq92kQFFyiQn5YtTVLM8sLX/p1ff4OmTktiMqa2QECelEIZ77s3SUCry+LmQpB7+eWXq6An+SShPE2YUoYoEmvTrgPNmTNXpbt08UK6776ksuDk532FChNO4BUrVpTmzJqhcFL6T47DjLQ3RX1SQr/0mqMkIz8agUCs+yDoGFQgwPcY0eQpUxFFQZB9kOz/Oe+4gxo2TFbkSkn76bzhpmQvJ+PHn+MUiFMgToGLmgIwGfS/Dk67q9pundMFXqwBtu+1bfi5c8JfbOWVf9PGyenM8rjcNuidADqPSPF1POkyQ9ZiZr+FS39xWa6ua83q422XD+PiWB1Wt/ZEmUSKn6O5Q2DalI0pzldHXLLoM1On6lXGWiwYCLHBrXHh6vo77xBAWO2aE0w4m5qCV1jo9uYSEyfaOwQmTbRfNuWWubzTwXmHAJtLMmXBRcyzZ25Rdzy4pQM/Pu1i8KO5QwD3L+BOCk1bFlZ5ZWnzX7J4p4nTtnWofVx5h0CQ+y5siafzi7TT6rQZ6lU0Pu5vbHOyJqMNjY/RmzDY+WXTR7Zw+SJt0jvvEDh48JBJB3NvkDsScFGptNk8eXLo5de480DP5YsWLZbFUc/SLnm4C9gQQdophZ1TCfJSVFxAiEslYT/bCypVqWbKltp3CFSvWdvkBXuqQcC5NrKpKVu0WNLOlrDPC39QmnrgXoQgABv+ug/AxWWJGlKjzXTa0mVzIhb6P+w335P/PlOeHDlzWWxSyqDyMXUThssBowWMM113Nt0RKDl5J0FK7xAYMnS4yRf9JCjg3gVdXud4TOv+lhp1AB2C3gmgaRYpvo4nXdybAbviTdle/e135DI0Lnj/g7bLh2Pd/1CGWN8hEOsxK9fEIHd2SFvt8g4B2J3GeNb9128tlG0j15SMcoeAc+zJ8uJZ3iGAu4/8AOugpknfhP4hqGl9h4C8r4iZ0IEuPEeh5QW2zOwNqceDRYubeh47lrzGhCD+5SEvkv34E/seu1r1miYtFhh5JRHYX9pQD3phr05c7ttYIK+9LT5pEdMyynGYkfamqHCk9EvPOUreIcCMbNNebg/yDgFWXLChxLoPIvGgdwjwSRzTt3CBebQQafv55Rd0L+eXRjwsToE4BeIUuJgoAI2ivwUsWrzELD564ypdhKcGyMtL2bSJjUkeNL9PP/3aMC/B+Dx8+JRr1EgZ/JHiu2YqPPfsOWqBGayZs9u3fWtCf/zhV+OP8J9/PmfCUvqQ3gIByZAHs9wPfuBLoDVd3AQCQ95ZbcJ7dn/XLykVdvLkGatqpTEmTnoLBNhskinL6FEfhi1/g3qTDX40AgFk9HKDKSYtvjchbN5AGDZ0jYnT92375WwI/18RCIwZOx7VCQv1X2po5kfWmjX4EIawaREVljNXHotNr5kwtwc2ZWHScQoEgM+aTSYcF3qGgzVr1hp8zNfpLRAYNXqMKQ+YPOGg+MOPGvzUFgiwBqrJi00zhSuaCueTISZOoQeKhMRJawYtCiAFAmwOJ6RMbh4ffviRqQeYDri8VkNqtJlO28vFBeKSeSSZZEeOHDVlRZ8GbjTQpl17kx6bzwqU1KB3Bps4KRUI4DJbvYdCXYMAm9gycRCXTd7YoqV1f0uNOqBCkTL4I8W3Ec3lBZc1Q2Cp20cygmLd/5B9rAUCsR6zkhEZjUAAdZVz+vQZM+EVFvhUjGmLuEDAfQ8Ry0uFvztyxNAbY+Crrw6GbSMIe/Lcnc/EcxMISEbsnr17w6Yp1wCnQEAKXDp3eSNsWuEQomGIou5sCkvVvdhDJUxW+sJ6CFX4tIDxT+mDHIcZbW8aKf3Sc46S/TAagUCs+yD6RVCBAJ+sNGPt8SefSWmXMvEibT8TMcyD314uTNR4cJwCcQrEKXDRUOBvIxBAi0Absm37jtb9hYuqhQgu3lPjZIDuAWDeP192uGE+sukfHRTI/eOPP62GL0018Vu39NYkiZTBHyl+kAKzTXtTVghDJDRrMsOEbdoYfoMu47o9OwUCZ8787oZm/IYLJnC0JwQuXPiPVbH8KFOfc+fsmrUm078elr27y+C6CQQgPNECA7hzZ3ufJvn99wtWy+azbPjpLRDo0nmhKU+4tsWYkHUNIhDwE7iMHf2RSS+h7/tO0oe888WjVuNGiSbO2jVfhuD8rwgEatepH1I3p8evZ85YYAZr5hGY8Bq2bN1q/EuXeU57e7pNmrUw+G4CATBGdT533JnbgraqF+w/cMDKV6CgwUe89BYISC38FStXeRVd+YPZqesKN4hAAJrbfuCnablixUqTHxjpTm1/t3Q7dups4uDZCWnNoEX+UiAApiZf1ucsVsh777f7mnrUrdfAFp4abWbLwOMFDA/d/jgpIkFqIIfrRzKe2zOb6DL5gJkD7TY/APNHaq6mVCDA5lNs2tIHDx7yy1aFsXkbU9ZHSz4Rgp/W/S016oBKRcrgjxQ/hHAuHlLIO2DgOzaMWPY/JOwUCJw+fdqWX6QvsR6zkhHdrUBeAAAGbElEQVQZrUDg9S5vmj7cuGnzsFU7deqUEapjPogLBMILBMKtg2GJzghPPPWMaSe3fYMzDXmqAO3kJhDA6Uk9p69ctdqZhO0dc4sUyjkFAvKUVpC9lS1xl5doGaL9EgaYuvEl9dYvv/xiQQkE9cWpo1iAHIcZbW8aKf3Sc46KlUAg1n0QfUQKBPyUZk6ePGVOst2W404r2jUj0vaLpD/77eUiSSeOG6dAnAJxCmRUCvytBALp1QgTx39smI8wq7NyRXjNEpT1/PkLVveuyWZhEPfAfvfNNPAjZfAHwYdAAmUAw/eN1xdZR4/8jKw8oWf3ZIHAgnnJZhIQYSabOtKMYJgNOnnijGc6CACdWjHjGz+2lR+CC8auFLZ887W/pmUsBQLMU7HY7r+pz3ff/RRSPu2BdoRZGl13N4EAcLt2WWzDWbRgh4WTABrAyPmSTeLwRdUKr9KLow1+RhIIvLdsty6yqzuGTxBoWsD1EghIs0Iw8eMFn39+zJbeB6u/8EJV/jjBoPN/8fmRbE4hVJjzvyIQwMfc2HHjfekBBoX+yM17TwFLMkwkowoCVD+AppI0leImEMCmXwtkkSeYke+/v8JmdocvMLbWrl1ngakNnIxkMkh+BE5LnO5HDmU6RtMVrpdAQJoVmjR5im+afgIBCAD0aQ7kB+0vP3hv+XIbw0JqEet4ac2gRb5SIIB68N0INpMnumza5bspzIcl8GfMnKWDlBvLNsPHLtLDD/TzA4w7lAc/aFpKGDJkmAmD2aDvv/c3dQaTHWxjW/2g3S8BAj3JaMGJAT+QR/VRtpQKBJBHzdp1TT3CtRNfeG0T8MlTE7q86dHfYl0H1EXOmy9WrKyr5+kGwcf4rlf/JdX3UOZwgjLJvBwzZpwt71j2PySMk2TSlE60SjaxHLMonxwfcn1DmBtIgYk0GQRczJN6XMPFqTgvgMk7WRfgxwUC7t8wkayDXvSW/lL54K4891gw8eIFTi1gtJObQGDgoHdM24ebZ7v36GlwkZ5TIADBrdzbYF72AwjdYP4F6wBfLm3BTJ6EaBmiBw8mm3SE2SBpLkgqicg8I32W4xA0yUh700jpJ8d1LPaCkjbh5qhYCQRi3QfRHyB8Rtvix/d4+HYRvlPM4GJNC2eele8dMPsgvujalnak7RervZwuBMbn/v379WvcjVMgToE4BS4qCsQFAmnQXHz5rE3LH2Z1Jk/awEcwf/fM/cCBH6z2beYaxiUYmBNYsOAHQRj8Mn5Q/IS+K0w5oFn9229/yGTM866d37E99+TTEE7hxdmz5626tSaatHAvghcN1q3dZzPbsu9L++ZXZ8qXNpv0oCnuB7EUCCCfVi2StfR7v/We6/0Bv/zym9XO0Y5eAoHjbFaodo3kuwQ00xr3UEDQIk0ENWE/0EjjpLdAYMK4ZKEXTrT8cvq3kKaAQGPEsLWmzLrsXgIBvrDZ4LbhkzE4leEFuNNApwcm//597v1l9aovDB7wcdeBG/wvCQTAqHF+jOo6y2PP2MCPHDVaBykXdqm1lhjCx0+YaAvXL7t277adMgCum0AA+NjI58h5l/kQAC7eK1auasGmqcyvdZt2Fj5OgYOfm6ZfWt4hIMtS4rHHLWh/OgFMIJgA0GXWrpdAQB7bfu6FF23mbpxp+wkEgIs7D3R+cKdMmeZMQr2DYQfhj8YFo8EN0oNB6xQIoIwwhcMXH4cUEfdQFCxU2NQDWufOj+lYthlMhGia5c6bz/N0IcqF/qFxnQxZmF+Q5iTATMdYcwPciyGZBdDedEL/AYNMXsjTq90x9qCNp8sFNxqBwM5du2yMYIxFt3aC0KLUs2VNvjiRBA1aJ6RHf4t1HVCnIAx+Wfeg+BgHuu2gAc0XTctkzPOGDRttcyzqKCHW/Q9pSyYVmKHRQCzHLMohx49zfnArp59AAPiSeQ1zKjt32ukLHOx35Mkl3W5xgYC7QCCSdRD0DQfQQM5/byEzXrzWazBFpUkn3U5uAgF5Cg97lk/4zhg3SJw+wzb+kKbbHgzrgs4PrlOYrdOGwFjOjXXqhp78jJQhqtOWrrxDQe81oMDhNqfLeEGf5ThEfTPS3jRS+qXnHCXnWiji+IHfHQKIF8s+iPSkKSCY4PJTdsBeRt5307pte9e+hjEq51LcQwTFIQmRtl+s9nIow+IlS41wD0IOzP1xiFMgToE4BS4mCvw/AAAA//9UP7+OAABAAElEQVTsXQW8FcUXPn8ppRQBle4OCSmRbukuke5uBaRRShrp7u5WQVBApKS7O5Uuff/zzXWHuffujQf3+R54Dj/e7k7vN7Oze883c87/glhIJMQRuHD+NvXsvoKuXLmj63rzrQiUL18KSpDwXXr//ej0+PFTunL5Dh04cIn27jmv0+GkYKFU1KpNQQofPpxTuHlx+NBl6th+kQpKmy4ODRxc0Yx2O/c3/ZEjV6hD24U6/wcfRKfMWRJS+gxx6X0+x72hzT9sOEzWaCpcJA21aVdI57FOdu48S717rKS//3YMu/Dh36CUqd6njB/Gp9ixo9KFC3/Qgf0X6fixa1YWKlPuQ2rUOI++Nk8GDVhPP206poMyZIxHyVO8R2+88T+qUvUjihIloo77btQmWr3qgLquXiMb1ayVQ8e9yMmWzcdpwDfrdNa3336Lsn6UiLJkTUB//vmIgC/u5Y8/HlKZsh/S8mW/q7T/+9//aMXq5jqfeXLt2l01Ts6dvWUGO50nShyTuvcsSefPOcYUIj/Jk5y+6FLcKd26tQdp5PCNKqzEp+mpecv8TvELF+ymqZO3qrDKVbNS7Tq5nOJdL7ZvO0V9e69WwR/nTkZdupXQSa5evUNNG82mJ0+eqbCIEcPTh5niU7bsiSlChDfoyOErjMUlunjxDx438ejevUd05vRNlXbAoAqULn1cXZZ1snbNQRo1wtF+hCVIEEOV+VbkiJSb60c/W/LH7QfUovlcwhGC/s/9STJKkyYORed+uXnzHu387Szt33fRykKpeNwN/LYihQv3hg6zTiqUHcP38pe6XLqiqdfnzsoTVo7JU6bhueSxas43X/elL7t0I4y5okWLUM4c2SlWrFh06dIlWrduA+3es0c3O22aNLRq5TK+1/A6DCddun5FM2bO0mFJkyahQgULUJYsWejEiRO0c9du+vXXHfT06VOqWbM6TZ8+U6XN/XEumjvneT5dAJ/8/MtWatykGd2583w+NONx/mmJ4jRq5HAaOOhbGjtuvIru16c3ff75Z05JW7ZqQ0uXLVdhozl9mTKlneJr1a5Lmzb9pMJmzZhGefPazyVWpp69+tCkyVPUZe9ePahundpWFM9PF6hAoaL06NEjFfbmm28S7rNQwYIUMVJE2gUsduygU6dOU86cOXge+JMOHz6i0i5aMI+yZ8+my7JOZs2eQ1982dW6pOTJk6syo0WLyhiUoAwZ0uu4j7LnoqtXr6rr3Tt/5Tkzto7DCV7n1ap/Rlu3bdPh2T7KSoULF6K4cePS7du3affuPbRy1Wp69szxrL799tu0bu0qisfxrhJI7FzL9nTdt983NG78BBXdsmVzWsVtBZ4JEyakCuXLUeLEiejB/Qe0/8ABWrJ0me6LcOHC0YzpUynPJ7mdig5knz18+JCy58zNc/ofqo533nmH8uT5hHLlyEHp06eji/xcHTp0iKZMmUb37t9XadCfa1evoEiRIjm1a+OmTVS3XkP66y/HPIPnLnPmTPRxrlzcV3Ho5MlTaiz9/vs+na9+vbrUs8dX+to6wfNerHhJOnnqlBVE2bJ9REW43+PEiUPXr13nZ+4X+nHjJp4b36DBA/tTuw6dVNqYMd+lvbt36nzBPRkydDgNHTZcZ0uQIIHqp0SJEqo54dix47Rw0WL1LCAR6p8wboyaj3Smf05CY7yh6kDeA8rDnFi+QiWcqn5YvHC+Ovf0x9/0mK/Llnv+XYdnIi+Pv5w8/hIkjE8nT5yk7Tz/LFiwSM0FqK9y5Uo0ZPBAt6oDOf5QeItWrWnZshW6nlw5c6q5C89lyxbNKFq0aDrO10kgn1nUZb4TT504yt8kEbw2Ac/SocOHVZoN69ZQ6tSpnNJjTJcqU44wH0BwjyVLfkofZc1CmBMunL9AK1atUnN/rJgxqUmTRoR5DVKK0435bpQ6D+6fkqXL0r59+1W21auWU4b0z98NCAzku7Bjpy9o7jzHuMX4wTjyJKNGj6EBAwepaMzZnTq0d0rq672FxMF5DzoV7uVi/vyF1L6jY55DsqhRo1KlihVUf0bkMXCC59gFCxfR9evXKX78+JQ504e0YuUqVeJX3bpQo4YNnErHnI7n+siRoyocc1m5smV47k/P/f42z9n8/G3fQbt276YsmTPT02dPaf9+x2+OeXNnqbndLPDvv/+mSlWq0W+/PZ9/P/jgA/X+/4jf23/+eUd9Y61Zu5bu8zsPgvG0cOE8SpY0qVkUfTdmLH3T3/Gct2jelDp36ugU78/FzFmz1feimbZxo4bUreuXZtALn5vPYVj7Ng0ufqE5R32SNz+dPXtO9cO2XzarseupU2rWqk2bN29R0bNnzXD7PgrkGEQl+E1QqEhx/o3/t6ozRowYVLRIYXrvvdiUNm1aNf+piH/+YN7A/GEJnlH8TsF3UDjWd5zgZ+rHHzaqbyukwVw7etQIKvnp89+fCA9u/wXyW65IsRJ6TkBbZvJ3aL58eXEqIggIAoLAK4HA/1iBEPRKtPQ1aOSdO4+oTy/+kcCK4uDIZ6y4rsYKbF/ir4LfKic46bdvO83K5R/5A9XxA8gqw/UI5erntXNShUpZWAnpGuu4BikwkBXpDx48sU/wTyjyl2ZFuicyAMmuswK9aePZrBR66lbW9Jl16d2YUXR4oAkBFLxu7SFCuX/95fj40ZUZJ7k/cSjrS3/q+BHojRBANpT185YTtJ7LvnDhNt269YBixIhM8Vkhnr9ASgLZAoU3FNwgmSChTQigDUePXqU+PVcqAgTXdhI33jv07dBK1K/PGkWWII0nQgCkUdtW8/lH1nW3ojp0KqqwMCNASvTpuYrOnHEQDWac63n2HImpY+ei9NZbzwkjM83rQghA+TFo8BAaM3aceXtu5x9+mJGmT51C774bwy3u2bO/mBToRnPmznOLMwP69O7JJEtKJuJqqGBvhAAS3L17VykB8AP8PCtQQA7Ejx+PUqZMSQ0b1CMolCD9vu4fZggBtGfPnr1Ur35DunHT8zhLkiQxLV+6mBo2bsoKgl+RjTwRAlAIlypdjg4cPKjSmX9GjhimFA5WmD+KFZAV7dp31IoNK6/dMUmSxEwKTiKQPHYSGgpakxDo3q0rFSiYnypUrKLIDLs2IixixIj8I3E4FS9WzDZJIPsMysDWbdrZ9pdr5VAWffNNP4oa5fl7yEwDpWyz5q2YIL1nBrud451Rr24dWzLASgylFn78WwSUFe56hHKnCiv3MmbKqqJelhBAISDsoIyylACudVrXUaJEppEjhiuiwgozj6Ex3qz6A3UPKM9fBb9Vd3DSr1+/gTp98SWT3J4XDaBcLB7p1LEDNWncSBHCVl3mMZDjD2RYQSZLHzxwKC7Nenbu2MaLXt43g3yeB/KZNRWRgSAE0Hj0WZ269TXRZXdDIIxBQuNdAQIcIoSAO5ENXILzHkR6f2Xa9BnUvUcvr3MT5qXFixbQkiXL9LeGHSGAOkHIl6tQWS0O8NSG6NGj07o1KwmkChY/QOwIAYTjeWnF75N169bj0quALMB4SpkyhVu64CpE3QrgACxgyPJRDl4M8/y3mR0hZpfXnzDX5zAsfZu+CH6hNUcFkhBAvwVqDFpjAM/blKnTrEt9rFG9Gg3o/7W+tk5GjBxFg78dqklsK9z1iPl08MABVLas86IfpHuR/gvUtxxIQrwPLFm6ZCFl5QVTIoKAICAIvCoICCHwL/cUlJzbtp6iFcv3aYWoXRMiRQrPP65SU+kyGSlhonftkriFBUfBj8zBTY+V7pMn/kwHD1yma9fu6N0AKCtWrKiUNFksqlLtI1598wGCvAqUtyuW7aMN6w/zypfHTmnxQxYKW6ziT5I0llOc3cXlS3/S7Fm8KoeJBpAulkyfxYTAu88VMSFBCKCuPbvP0xyu/8SJ63qFPMJjMhlR6/OcvFoitfpBXqqEf4QA8poCzg4KIVf5dftpRTAhPE/e5NT5y9DbIWC1Df06bsxmHltXWOH7vC8wnsuVz8SrobIoJfwXnZbo8e+JEECZ9+8/oSWL99D3vPvk5o37+oMRyvx8+VNa1eojiCEQKdgJAjLFVdKkjUMlS2XgvClsMbXSv06EAFZD/rJ1G/XjFYpYVW0KlDQN6tel2p/X4n55y4xyO58wcTLNX7CAjh8/oVc1I1EmXlXXrcuXlINX9Wzbvt1vQsC1AigTseLOVXr36UuoG/J13z5Uq1ZNpySBXBWJgr3tELAqxuqwr7r3VD8CrNXiiAOGDZjMaNa0iVICV65a3SchgHwgR8aNn8irFRfyLrKrWnkxipWn5o8ffwgBlIc5Y/WatTRt2gzVJwgzBSuLa31Wg2rWqO515W5oKGhdCYGGDesrMmDwkKE0Z848tercuhdrZW7L5s3cVvFaaaxjIPsMuyuGDR9JWLl56tRpvdsCdWHHBXbbVK5UweuqWrNdk6dMpXm8mtV1xwye3cKFClKbNq1UmVYeT0esYJ06dbra4XLjxg2nZNh90KN7N/VDFTtFAkkIoKK9e38n3Ad2nzx96kzQQ0FWuVJFJjVqq50eTg0zLkJjvBnVB+QeUF5wFPwvkh4K5r59v+YdJL/xrruL+r2IsuLE+YDSpU1LWKmNVcq+BM9FoMbfmTNn1W6RTT/9xAsZnr9/d/22nVeIvuerKW7xgXpmXRWRL7tDwGoo2vfdmHH8Xlyod+UhDvNSqVKfUpcvvlC7fTAXCyFwVcFmt7PNwtPf96CV3t/jbzt30ahRo9UOKTMPfmtUqVyZ2rVtrQgrc/GBJ0IA+U+fPsMLW4byb47ddIGfP0vw/VK+XFn6onNHgvK+eo3PfBICyItvn5W8MGLqtOmEtrpK/HjxCO9BvK9dd5pZaV9EIWrlNY9Nm7VQczjCMI+sZWIjUGL3HIaVb9MXxS805qhAEwLo30CMQWucgNxbtGgJjZ84UT0rFsGE8dufF0jYCd6Zk3ln7pq165y+p5AWu8uqVatCzZo0Vjuc7fK/aP8F4lsOY7gzk/SXL19R3zme7tGu3RImCAgCgkBYQEAIgVDsBSiyz5+/Rdeu3uUtq/f4Qy88/2iKRrHfj8ZmI2KzuZtIodg671U/eviUzp67RY9ZAZskSSyKFv1N7xk8xD579jffO98/r/QHWRIn7tsKAzsFuIcinIJhsuZPJi6iRXuTYJLp3xSs7Mfq9LtMSsSPH4NiMklio8cPWJNMkz8wSdSoiXdTKAGr2M+CML4v8f/3P4jGP47e5hWL7speP4tSyYDvbTYJFInNEfkab9j3dPvWfbrGYwv9AWIIz5avfMFpT1hNa/ejy2orFI7HWKGP7bKJEiagePxDE8qL4Ai2rh9gYuENzpc8WVLeveK+qyA45flKayoJJ4wf43EVuK9yQioeSrAzZ86wyY4EjGlCN5NLwa0XOzKw2vvNNyMFBFus+oPSAkQDzBrANBCIoBedY4N7P4FMD2zOnDlN53hHCbagJ06USJmBCG4dgewz/KCEeZ8rV65QsuTJCMqbFxGUc/Eim1W7dFHtEkvCppFg5smOJPNVPnCCovjcuXMUmVe/pkyRwivx46u84MRjbkHduJcIESPweIvH80zcl34ugtOGl037Kt0D5uNjx47Rw0cPKU3q1C88ZwRy/AF/7FS6eesWvfP2O/wtG/llu4Sf+8DOsy/dIKMAjJdz587TpcuX6IP3P6Bk/F7EriWRF0cg0O9BtATvQphauXnrJpugdLyvTXLIX0LAvCvsGIAJIbxTYc4Oq5hfRkDW4n19jc284R2XJHHiF3rHvWgbYEpuARNckO5fdVO7NV+0LNd8r9u3qev9heU5yrWt3q4DOQaxOOUmE9g4xmRzV76+Z7Bbwfp+iMLmg/AdBDOn/4a8zLcc7g+EJhY/iAgCgoAg8KohIITAq9Zj0t7XEgH4lljzj3+DtyJHYDvg3k1EQeH9ZafFyncDAGnSLB+bHcnwWmIjNxU8BLz96ApeSYFPvWXLz7SZ/0PSpUvrZA7HrjasMs2bv6A2y/DDhnW22+Xt8kqYICAICAKCgCAgCAgC/iDwIoSAP+W+KmmgjM2W42O1Uw2E1o7tW1mJ698OdX/uMSx/m/rTfkkjCAgCgoAgIAi8jggIIRACvbpyxT4a+93mEChZinydEFi5poW+Hax+b1BvhtopgcDmLfJTiZLpdbx5AjJg5vTtbJN0pwqGA99pM+ro1e+WaSIzj5yHDAI9epVSjpNDpvQXKzUs/+iC09MCBYuo1UKRI0emBfPmUMaM9kQWfpw2aNiYtvz8iwICpolWLFvyYqBILkFAEBAEBAFBQBAQBDwg8F8nBOBHBRhAKlYoT8OGfusBqRcLDsvfpi92R5JLEBAEBAFBQBB49REQQiAE+lAIgRAA9TUs0iQEcHvLl/5O48dt0XeaIWM8gs37lCnfZxNE7yhzObCLv3LFfjprOM797HN2Om3sKBBCQEMY4idCCAQf4gaNmmgHerCHWyB/fuWHAAr/93mL/Hm2y3xg/0GaNGWKdpwJW7+zZk6nj3PlCn6FkkMQEAQEAUFAEBAEBAEvCPzXCAGYZQoX7g3av/+A8ocDQgBh4cOHJ+zGTJo0iRe0gh8lhEDwMZMcgoAgIAgIAoJASCMghEAIICyEQAiA+hoW6UoIPH36F02dvJWWs7Nl2CP0R0qx0+kmTfM6JRVCwAmOEL0QQiD48MLWevuOnWnz5ufkl7dSsHV98KABylmft3QSJwgIAoKAICAICAKCwIsg8F8jBEAAfNN/oHIoa+EF30I9e3zFDuDrWEEBOwohEDAopSBBQBAQBAQBQSBgCAghEDAopSBBIDAIHDp4mUaN2MhO6m7ZFghHxdg1UKt2TsqUOYFtGgn87yLwqvzomjN3nvoxCgdmdgIioGCBAtS1yxfKWZ9dGgkTBAQBQUAQEAQEAUHgZRH4LxIClokgYAczjiOGDaFixYq+LJS2+V+Vb1PbxkugICAICAKCgCDwmiIghMBr2rFyW68+AvfvP6bz527T+fO32LfAPYoaNRLFeDcyO2ONS+/GjPLq36DcQYggcPjwEQrif5A0qVMTVnyFZbl69SodP3GSTpw4wWaxblOsmLEoTtw4lCtnTooSJXJYbrq0TRAQBAQBQUAQEAReAwSuXbtGN27eVHfy/nvvB9ShbliE58DBg7Rx408UO3YsSpUyJaVImYKiRgm53xav2rdpWOwzaZMgIAgIAoKAIBBoBIQQCDSiUp4gIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAQBhEQQiAMdoo0SRAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEAg0AkIIBBpRKU8QEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAIgwgIIRAGO0WaJAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAQaASEEAo2olCcICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAiEQQSEEAiDnSJNEgQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAKNgBACgUZUyhMEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEATCIAJCCITBTpEmCQKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoFGQAiBQCMq5QkCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAJhEAEhBMJgp0iTBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEgUAjIIRAoBGV8gQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBIEwiIAQAmGwU6RJgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCQKAREEIg0IhKeYKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgkAYREAIgTDYKdIkQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBINAICCEQaESlPEFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQSAMIiCEQBjsFGmSICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgEGgEhBAINKJSniAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAIBAGERBCIAx2ijRJEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQCDQCQggEGlEpTxAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEAiDCAghEAY7RZokCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAIBBoBIQQCjaiUJwgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCIRBBIQQCIOdIk0SBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEAo2AEAKBRlTKEwQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBMIgAkIIhMFOkSYJAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgUZACIFAIyrlCQKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAmEQASEEwmCnSJMEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBASBQCMghECgEZXyBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEgTCIgBACYbBTpEmCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoJAoBEQQiDQiEp5goAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCQBhEQAiBMNgp0iRBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUEg0AgIIRBoRKU8QUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBIAwiIIRAGOwUaZIgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAQaASEEAg0olKeICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgEAYREEIgDHaKNEkQEAT+uwgEBRHduH6XYr8X7b8Lgtz5a4/Aw4cP6f6DBxQrZszX/l5v3LhBUaNGpTfffPO1v1e5QUFAEBAEBAFBQBAQBAQBQUAQEAQEgbCPgBACYb+PpIWCgF8I9O65kk6duqHS9updmhIlfv0VbX4B8wolunz5T+redTnhmClzAurTrwz973//e4XuQJoqCPhGYO26ddS+Q2d6wIRA82ZNqUP7tr4zvaIpBg4aTGPGjqcoUaLQ0G8HUZEihV/RO/Hc7F+2bqN27TuoBHk++YQGDxrgObHEvDACNT77nE6ePKnyz509i5IkSazO5Y8gIAj8OwiMHDmaZs6erSpr3aol1ahe7d+pWGoRBAQBQUAQEAQEAUEgBBAQQiAEQDWLXDB/F2384SidO3dLBSdLHtuMVudQ+L399psUK1Y0+jBTfMr1cVKKECGcW7r/YgDw+3nLCXXr6dPHpYaN8wQbhq/7rqGrV++ofO07FKGEid4NdhmvQoa2rebT8ePXVFOHj6xKdmPtVbgPs417dp+nqVO20skT11Wwp3uKHDkixY4dlZInf4/yF0xF0aO/mitxJ0/8hRYv2qMh6N23DGXJmlBfy4kg8DogULJ0Wdq3b7+6lUiRItGeXTsoWrTXb0fMH3/8QVmz5aQnT56oe82SOTMtW7rodehCp3v44ceNVKdufRVWpHAhmjxpglO8XAQGgcJFi9PRo8dUYT9+v45SpEgRmIKlFEFAEPALgb79vqFx4x3zW/duXalhQ8e851dmSSQICAKCgCAgCAgCgkAYQ0AIgRDukO9GbaLVqw4Eq5ZorMzs+tWnBAX4f11c8fuya3HK/UnyYMHSpOEsunDhtsozZFhlSpnq/WDlf1USv46EwJbNJ2jAN2uD1QXhw4ejuvU/prLlPgxWvrCQeNXK/TRm9E+6KWMn1KT48WPo67B+cubMTbp08Q/VzLjx3qHEskslrHdZqLSvabMWtHLValV3nDgf0LZftlC4cK8OCX7kyFE6feaMan+SxIkpdepUtjg+e/aMcn6chwnpqyq+TJnSNHrkcNu0r3KgEAL/Tu8JIfDv4Cy1CAKeEBBCwBMyEi4ICAKCgCAgCAgCryICQgiEcK+5KrTfeiuiW42PHj2lIBgON+TNNyNQz96lKH2GeEbof+/UFT+QJaPHVKd3343iNxhCCPgNVZhL6EoI2D0/T58+o2fP/nZre70GualCxcxu4WE5AHPB3Nm/0f59F6lo8bRUrHi6sNxct7ZN4h0OS/7Z4VCesa/PfSAiCLgicPbsORoydBhdv36dWrZsTrly5nRNEqav+/T9msZPmKja2KhhA/qqWxeP7YU5nVGjRtMHH3xAbdu0ooQJX78dP0IIeOz+gEYIIRBQOKUwQSDYCAghEGzIJIMgIAgIAoKAICAIhGEEhBAI4c4xFdrVa2SjmrVyuNX45MlfdIVthh84cIlmz/yV/vjjoUoTKVJ46tGrFGX8ML5bnv9KgImfdc8woQJTKv6KEAL+IhX20pmEAHbM9B9Uwa2Rf/8dRNeu3aXT7D9h9qwd6mglqlvvY6pYOYt1KccQRkAIgRAGWIoPEwgEhxAIEw0O4UYIIRDCAP9TvBAC/w7OUosg4AkBIQQ8ISPhgoAgIAgIAoKAIPAqIiCEQAj3mqnQ9kQImE24f/8J9ei2nI4cuaKCY8aMQlOm16E33vhvOhY18TNxatIsH5UqncEM8nguhIBHaMJ8hD+EgHkTIAfGj9tCK5fv08Fjx7PZnQSvjtkd3fBX8EQIgVew06TJwUZACAFnyIQQcMYjpK6EEAgpZKVcQcA/BIQQ8A8nSSUICAKCgCAgCAgCrwYCQgiEcD+ZCm1/CAE0B/buWzWfy44I/1Kt696zJGXPkSSEWxo2izfxM1sYMWJ4GjG6ql/21YUQMJF7tc6DSwjg7p4+/Us9P+fPO/xGlKuQiRo0/OTVuvFXtLVCCLyiHSfNDhYCQgg4wyWEgDMeIXUlhEBIISvlCgL+ISCEgH84SSpBQBAQBAQBQUAQeDUQEEIghPvJVGj7SwigSd15l8DuXedU6yqxyZM6bPrETo4evUpHeTfB2TO36OzZmxQhQjhKliw2JUsem1KkeC9YK6MvsjPQ9WsP0fnzt9i28z220x+ZEiWKSXnypqAUKd9T1Z87e4s2/nhUnSdih6H5C6S0a5YOu3XrPq3jMs+cvsGOFe9SON7p8N770SkVO/YtUiwNRYkSSae1OzHx+7x2TtrHttX37jmvkuL+Bg+txM4o37DLqsN8EQIL5u+iB7wzA1KlWlays1OvC+OT9esO0eVLf6qgYiXSsW3o6GY0fb/hMF284HCsWqRoGoJz1T//fEhrVh+ggwcu0+3b9ylOnLdVP5XkXQ7Ror3plB9p1645qEzfoJ648d6mVKk/oHTp4up+cMrwz4Unp8KwR7992yk6d+4W/cnmqIB/0qSxqETJ9BQjRmS7omzD4Obitx1n6Nftp+jKlTuqrHd5BwvuJV/+lJQ2XRzbfFbggf0XaddOx5jOkDEewfTTw4dPGK8jHH6WbvCYw06Ytu0LUxJuH+RFCAHkQ59Om7INp2qsfcvOpO0E97Hv9wv8/NwkOMR98OAJY+N4fpImi0UpU77v9+6cu3cfqefn2LFrPNbvEEx+JUr0Ln2YKQE7wk6mqn/8+JnyEYCLN9+KQFWrfeTUrLt3HtHif2zwv/32WwQywxRgBMfDkPfei6b6EOfHuc716/nZPXeb7t17xGPybUqQMAblyJmEHZ5+gCQ+5f79x6p/LCxQF3ZWAAfMKSgHbXYVs19/ZyyP8ZwEgfPuDw1zZ7jO9XFS1+zqGmNrz+5ztG3rKYXdrZv3KWrUSBSb7xHjqkCBVLZ1m4XZPXfX2ZTUan7u0Kbbtx6oMuBYPKzJggUL6eSpU6pZVatUoSRJEqvzvXt/p+UrV9Lx4yfo2tVrFC9eXOXAtmbNGhQvrv9O5/fs2Ut79u6lo0ePqf8RI0Zkp/Vp+X96ypgxAyVP5hifqlIff06dOk1z5s6jEydO0KVLl3k+eY9SpUxJpUuV5P7OqHIfO3acFi9Zos5Tp05N5co6m3j7/fd9tGatw1l45kyZqFixok61bt/+K2366ScVBv8C+fLlpb/++ot++OFHWrZiJV04f4GJv6c8LpPyey45Va5Uiech/8b5nTt3aNOmn+jIsWO8E+8oz+WX+X2ZlNKnS8dzbDrKkjkzv5fc50WzTfALgL6BZMr0IeX+OJc6t66LFyumr1dwew8eOqSuy5YpQ2nSpNZxdido08JFi5XT4ksXL1GEiBEobpw4Kl+VypV93qfZzkBjZ9dehHkiBO7du0ez58yl/fsP0MmTpyhK1CjsQyEBlShenAoVLED/+59/Ox9ftM/s2nvo8GHC87Bv337VL2+//TalTpVK4Zs3zyc8rzq+dezymmGPHj1S/fTbbzv5m+k8vzseUrz48Sglj8fq1aoGy1fEs2d/0Qp+zn/6aTN/x52lp+yMOiU/U5l5bFWtUpnwvEJCghCAH4/5CxbRwYMH6SKPt8ePH1PcuHHYIXwiKl+uHGXIkN68bbfz0BhvdnWiYVeuXKFZs+fyHHeUcTxHMWPFVHNppQoVKHNm53ep240YAYEcb3Asvmz5Ctq8eQudv3BB4ZsyRQo1V2KcRIrk+AaeNHmK8qmCZjRoUJ9ixYxptMj5FD7H8MytX79Bjb0bN2/S+++/z98bCakczzHZsjl/Vzjn9u/KDuOXmYNXrFylxhhqh3P1tGnSeG3I1m3bFGZIlDt3bsrzibM/Irt35s2bt7j/Z9OvO35TWCZKmEi952p/Xoveeecdp/qQdvbsOYT54MyZs2qcZOa5PztjZ73HnDL8c+GJEMB4m7dgAeHdd+7cOTWPJE2ShKpVq+LzXs16XrZv7frt3v37BLzw3rt0+TL/DgtHQ4YMcmsX5qHfdrIPK56v9+3fTydPnOJFV/HV3Jg6dSo1Z1vj1WyznAsCgoAgIAgIAoLAq4uAEAIh3HemQjs4hMDECT/T0sV7VeugbO3Y2VlhAtNCE9g0CpRg3qQWK9FdlY6u6bETYdSIjUrR7+rcGGnxm71osXTUsPEnSmH4Tb81qohP8iSnL7oUdy1OXf/119+E1cKrVx5gh6+OnQ6uCaFcrFkzO8H5qCcx8atdNxcVLJSamjeZzUrPxypLterZ6LPP3f0ymOX5IgTq1JpKN27cU1mmz6xLUHJ7k65fLqXf915QSb7uX87Nx0OPr5ZrxXeffmUocZJYBGW9VYdZNhTyUIBDOQ5ZveqAUmRDOWsndeuzTfxK9jbxXQkB3MfokRuZDDhtV5QijypXyUo1PstuG28GQqE65NvvWRHnWHVvxlnnIHk683iAotpOFi7YTVMnb1VRlatmpeo1slOnDovoxPFrTsnhJwD+AiAvSgjs+PU09e65SpUBB9TTZ9VV59YfjPMl/HzNnL5d78Sx4sxjzlxJqNMXxVghE94MdjvHszpzxq8Ep8B2AufgrdsWpKhMgFWv6nBGCoX/rLn1nZJfYlKuUYOZKix+/Bg0dkJNp3gQgO3bLFBhqdN8QIOHVFLkEZ5fO4HCrXSZjIRnBwSFJ9nJhMyIYT8SFPGeJB4TW/Dd8b4LAWaSL57yIhwOklu2LuCW5NChyzSUx5ZFsrkl4IDIkSNSDZ4rXAkSM63rcwdSpA0/d+azhLlsxeoWZrYwcV6rdl31Yx2NmTVjGs8HWahbt+6sVF/q5nAeacKHD0/16tahrl2+YMLKMyF69+5d9kPTRykDkM+TdOrQXjn39RSPcCgKv/iyq2rT33+7O/HGWIOCq0f3bqzM30yNmzRTxZUq+SmN+W6UU9FQEnf+oosK+4zJjW++7usU/92YsfRN/4EqrEXzptSpYwdq3aYdLVm6zCmddRE1alSFBcryJhs3baKOnb5k0slBWtmlTZo0Cc8LUylBggRO0aO/G0v9Bzja5BThclGjejUa0P9rHdqyVRtaumy5uh49crhShulI4wRtwj2CbPAk4cKFowoVytPXfXvTm286E8lWnpDCzirf7mhHCIDU6Nvva4LizU6gYBo35jsmYJPYReuwl+kzXQifQDHbu08/mjJ1mhnsdA6lIfru0xL23zVW4nnzF1C/r/szuW//PsQzWaF8Oer/TT+t8LXyuh537d5NLVq24Z2hF1yj1DUUcv24vwsWyB9QQgCEWo9evWnOnHkKG9vKOTDbR1lpxPChSjFolyY0xptrnZ07daRRo8fQiJGjeJGBwweXa1vz58/H37nDCASQNwnUeEMdeJbbtG2viAq7OjHHDOAxkoeJKH/JHhCRbdt1oBMnT9oVqcJAfnw3eiTFjxfPYxpfEa4Yv+wcjLkN7zPISO4HV5LYtT3oy0GDh6jgNq1bUft2bZySuL4zQbSWLF2WLl++4pQOF7Fjx+ZvjEGKWMb1jBmzqP/AQQTix07wXm3SuJFdFM9p39C48RNUXPduXalevTrqXTV5ylRFUttlKlG8GA0d8q0t0WymD0TfuvYbsCtfsbJS8pt1LZw/l3LkeP7tf+PGDWravCWBUPAkqVKl5GdouFqU4CmNhAsCgoAgIAgIAoLAq4WAEAIh3F+mQjs4hACco86euUO17uPcyahLtxK6pVh93LnDYjcFs1LU8UpbKJ6hkLcEK8Gbss19Oz8EUGBiN8Khg5et5IoAgBI1Cq/QvX7tnlrFjUjsFAAJ4IsQwCror/uu1kpxq2AoQB8/eUaPHjorTUuWysAfovmsZE5HEz8oNaHA3rL5OP+IWqfS4Z4GDq5IUI56ktAkBGDuaf68XXTk8BWF6we8mh6YmiQJlJ2jx1Tn1VOXafDA9fo2sPL+9u0HbkrmRk3yUJmyH+p01olJCEBRPHH8z9oXBXZixIodlf7g8rADwZTivMuhRasCZpDTOZTrwBv9aglwjxkrKt/LXStIHUFw9OlXlkkQ99VtroQAlM8/fH/EKT8uAkEIYNX6F52WqLKxA2PO/Aa6HvgZ6PLFUkIaU6JHf5OiR39LOSh+wuPUEoytHj1LUTSOtxPgvHSJg7yz4pEWz5CJt6VQr193ukoWCEIAZF+fXqsI9wRld9y4jt0oFmFmtcfbMzZj2naaN3enlVQdQR5gPrl5476TQv0d7t9evUurHUhWBtz7rBmOuQrmmqyxHT58OEU6WekKF0lNjZvmtS7VcdPGozRsyI86DwKtsYrdEthNg90DlhQukoaJlULqXq0w62gSApgvQdBgR5MprwIhMGPaFJo+cxZt2PC9ajqU3Vixe/v2H3oFqXVPWGk5kpV1dqQAFIwVKlVxU5BACQVC7MqVy0641/qsJvXp3ZN3XIWzitfHBw8eMPFah7Aa2hIQAFiVGj16NMJKdqxChJQuXYpAAgSSEMD4hqIDgtXSCfkeLly8yHPjIxVm/QHxgLrtZODgb2nkyNFOUW+99RYr/uMzFledlEOxYsWi6dMmUwbeQWHJhImTeVXlUHX5+MkTrfyJECECReI2WVK5ciXq3auHdUn+EAJYpfp57XpORAVWYkKh94QVt5cvX3LqK6zanjFtKsWM+a6uxzpxVQgFAjurbE9HV0IAq9obNm6qxhnmgThx4vJcEJ5XMzt2dljloP2zZ81wW6lqxb9sn1nlgJRo0LAR7dy1WwVh7GKnAlZqn+PV/VjVay6GaN6sCX3RuZOV3ekIJSWUlaZgHEWJEoW/vW6YwZQ1SxaaMX0K7wK0J8m3bPmZ6jds7KTEBtEDEuDBg/tqXIJ8w5hftGAedejUWe3wQSU/fr+Od8ekcKrP3wsoQuvUrc+rgXfpLHju4/BOFNR/kZ8tU7GOfpo6eZLaDaMz/HMSGuPNtc53Y7zLZHU/1SJglYDxwzN6mVdDY1W7JVBozp0zy+Pq+0CNN9S3avUa9eyDeLEkcuTIvMsrHr9T7+m+xXO+dMlCRRxgBxfEU99u+P4Hat6ilVPfoN8+4Hn44qVLVjXqCCU4yGUoyl9EXDF+2XkkJAmByZMm0GgmhECu4dnGTgnsdjGxx3v0+w1r1TsMc7IlSHv9+g1+3h5YQerYq2d3Rbo7BfKFKyGAFfcTJ01WyeyeXSs/dpKhP6JHj24FOR0D1beu/XaVdxYuWLjIqS5cmIQAduxhHrKIcrzTkidPpuahAwcOOH1D4Pkay+/ZIkUKu5UpAYKAICAICAKCgCDw6iHwnyIE8KNv/MRJtHHjJlb6XVNbOgvwqqtGvD03ZcoX+2Hlq8tNhXZwCIEB36xVq6NRfplyH1Kjxnl0VaNHbaI1vJIcAqVj85b5lUIcCkYIlJkrV+yn6VO3sRLBQQxgFXqhwu4/DLDLYNlSh+kD5P2UyQOsujdXycOUxwRWekK5BrMhlsNjTzsExo/dQsuXOcqEOR+sQM+WPTFvyY2liIpjx66q3QjWPaBe7IDATghXMfGzCAGk+XbQBm26CIrzkd9V4x+yEVyzq+vQJASghIfiu16D3JQ3XwrVX1CawrTK4AHr9U6HxGx+6fLlP1V/QeEPEgjKdfwIO83mlgayQh4mnSAgEOYtbKh++KiAf/6YhEBCNlWD/oJZpYY8dkxzPjCNM5l3b1gmqZAdq+DRPleBwr8p78iwSJy0aeNQ2fKZKFPm+Epxi3vby7slsNL+2j/kAOoeMaoar2J2XrlsEgJQvt9hhS9M0kBZnYaV7iARHj16xsqPcHpF/ovuEMBOC4wdCMwPjRxdTZ3jj0koYXwCb+zQwDiCQAG99ZeTNH7sZl7d6lByQhHdpl0hFW/+we6Lvr1X6SCYQoK/ApjssgSmmmC+6Nftp52en5clBDAOQPy9805ktXsnHe+qsMxPYafBqJGblDkktAMEDvrElaiBWaAG9abreQKOuosUS0sYj5YpLuzgGMfP9GFeyQ+BiawJkz/n8acunf4Ex4cAdpu0avHcVwpMCgE7c6xi/M2d85syO2ZV1IRJhVK868FVTELAGl/oV5g1w7wFggNkGObMsCbmakeYrjnA5jug7OvV4yu1etRq7+nTZ9Qq9dVr1lpB1K9Pb/r888/0tXXSpetXNIOJBQjMoPTnVfhZWEFpKZGhTJ82fQaXN4j730GADeFVlJUrVbSK0MdevftqpQcCa9WqSa1btlCEgJUIJjF69emrlKswu7N7zx4V9bI7BNB2vK/z5s1D2C2AsqFEg6J067bt1Knzl8psBiqDGaVNG793Wz0P00a58+TT9wkTEjDlkDpVap6nHAQIzCR079FTK40TJkxIP2/e6DbPop4+fb+m8RMm4pQaNWxAX3Xros7t/vgiBLDzoljxktpkFMiInt2/opJMbFhtA9kyh02hfN1/gL4HrGIfN/Y7typNhVAgsHOrwCbAJATQB3/++Sc94JXaHdq1pbp1a7P5r6gqF+51PpuuAH6WwhlK2rWrV+l7tYoPZJ9hNwp2pUCgAMQqVyjoLAFhADNYA3jVMAQKsR3bfyH0hSlr162jho2a6iA8KxUrVlBmRpDn+PHjtHHTT+qZspSRNWtUVzsFdKZ/TqCUz5e/EMHcCwQmYnrw8w7TWxYpB4IBK99hTgZ9CfyALcST0lhF+vjTrn1HrSQEmdiRdwjV5jnEIi7wbK1dt5568g4Ca8U1yKnvN6xzW+UcGuPNrBM7TWBSDaQMdidV5B006AsIsJo4aQoNHzFSEz528xHSBnK8AbOChYpokhTYQcEMJSoU1hCMuYmTJqn+BQGE+dgilOz6Fgr/QoWLMpngUFxj5wZMC32S+2OlZIYy9+dfttJgJqxAlkLwu2bdGjxb4dV1cP6YGAdiHglJQgCEORTfXbt8SWXLlFLPyhMmhH7ZupVJmbb6mcFYgWmfp0+f8Lu1B5UoUUztHgBpdPjIEUW2nDp1WsGEOevg/r1uZLtJCABf/K60fXb5uf7uuzEEItkSu91wiAtk35r99u67MejWrdvKJCC+ET7KmlWt7gf5gXcoCAzce+EixfWOkzx5PuFFGoMVhla7YVIJc+PKVatVEEim9Wsd51YaOQoCgoAgIAgIAoLAq4nAf4YQWM52fLGyxpOMHjWCyvDKxkCLqdD2lxDASuzGbDbEMjEDMxswtwGBTf76dabzB+1fygTIADavkpyVvnaCVb9Y/QvJyLa8Yd7GFCiMmzedo38owRxPuw72qz7QlnatF6j6rTLsCAHYMm/HJk2s1Xat2hRkc0NprSxOx5HDf9SKvnfeeYsmTvncTalv4mcSAjCZ1KLZHL1C3ZM5ElQYmoQA6gdhU+LT5ytNEQY5efI6tW4xz3HBf/FDEYr5PHmT6zDrBIrb5k1n84/BJypozPiavLI1hhWtjiYhgIBYvIJ/2MiqrDB2EEVmYpBG6Kczpx3KCChJJ06ppRXxVtrePVfSjl/PqEso+gd9W4kVAs9Xw1rpMJY6tl+o22dn2sgkBJAPJoZ68mpzTyvvkeZFCYF+fVYre/QoAwrhDp2K4lRJy+ZzlX8GXDRvwX3DJJidYNcMTBpBYDJo7oKGfHQoDxEGZTyeRes5BT7fsk8LOx8UIOawEwf+Cix5WUIA5WDF/iDeIRMnroPMsMrGEWRS00azNJHkSiwijUnegRDq2LmYraIfq/VBDGHHA8TcxaEC/vkTHEIA2Fo7kzBWh4+qyuYc3McqisaupF9+dphIAPE3fuJnTqQl0piEAK6x8wXPnqWAQVhYFZMQQBthumTNquW2ZjqwA6Nq9Rq0g+0kQ7Di8Jctm5xsJEOBnit3XiaHnyhFGVYXZ8hgP86xah4rYyEf58rFu0UcJIIK4D9QeBQpVkIp4BFWiRWgQ1lhYCdQhJUqU04p8K14OwVccEwGoZzs2bOp1ZVQYLgK7DXnK1BYK8onjh/r5pOgR8/eBJMOEOyqgOkQu3EBEzAFCxfTijlzFaXK/M+fQBIC5opzEADz5sxW92vWZ51PnTadvure07qkSRPGUdGiRfQ1TkyFEK5fFjuU4UtMQsBKCzMuIHDsBKafWrVuq6N6siK8fr26+hongeozfIukSpNeExCe+hR1mkrLdm1bU9s2rRGsBKQMFPh4tiBQPA8b6nhuVIDxB6ZRUBYE42z50sVOBATCe7IpLyj6ISAA5syeQfD5YCcmoWHF2ymNrThvRyiNq9d4TiBiJwR2RNgJ/CzA3AjmEUiD+vWU0t1MGxrjzbVOYIzn3vVZsNoJU18w+WUJ5jjMdaYEaryhzGb8WwO+QyDYFbBsySKliFUBLn/M59+KsuvbuvUa0PfsQwUCRfTSxQs1gWPlwxHzdbkKlQjm4iDezN+oBB7+uGL8svOI+WwF2mQQbgFm5+xMxoFcL/FpaX2XIMBGsek2EG+uAlIIppss7Db+sJ5Xyjt/j5uEAPJjzp47e5aT+R2zXBDWIBshqHvVymXKX42ZJpB969pvMB81bcokXmDk/HvBqh/+VMqUq6AuMVb37v5NfTNY8dYRJELJUmU1cbBg3hzKmdO7uVYrrxwFAUFAEBAEBAFBIAwjwD+WXnvhbbhB8RMm8fkf6QItbMM9qGTxkeo/r6L2q3hemazzVCg7JojNf+h8jx8/Dbp+/a76f+fPhzrc7uTSpT90ObVqTnZLMnXKVh3fpuW8IFYSu6UxA3hlf1C50t/pPKykM6PV+bAhP+j4CeO3uMWbAazYCmrXer5O//OW42a0Ojfxmz9vp1M8K1eDSpUYpfOzs1uneOuCyRWdhh0wW8H6WPuzKTr+5o17OtzTSZcvluj0v+8975ase7dlOr5zh0Vu8WZAk4bP29ah3UIzyu2cfRfocn/4/rBbPPrQGmtlS30XxDs53NKYAbyKPKhKxXE6Dzt0NaODrl29o+OqVByvrp0SuFwAf6v+po1nucQGBbGteR2PfvM1flHA5p+O6zy+sLQqxH1Y7cCRd0JYUUG88lE/P6zI1+GeTsyxcfHCbadku3ed1fUAHzxv3oSdDgfxanydp0bViW7JUYfVdoxbV0GfWvE42j0zZh52Tq3Ts8LcjFLnt2/d13gwyegWbwawOStd1to1B8wofc6+T3QanHsSdlyu02FOsXsuzbwPHzwJMp+VxQt3m9Hq3HzumCx0iw/LAWyOR7+fEiZOFsTO/7w2l1eDBmXOml3nmTtvvlN6Xn3N4/Gy+n/r1i2nONcLXv2ny8maLadrdBAr03T8p6XKBPEqZbc0ZgCbHwhKmjyVztOkaXMzWp3Pmj1Hx7NfArf40d+N0fEJEiUNunHjplsaM4BX4ev0Y8aOM6PUOTtO1Xjwym23eDOAFdW6LLTTTtgWvU6Dc2/SomVrnXbZMudnEPMRMLe+T1hB7K0oFceKNZ2ezb64pQ80dm4V2ASwolK3CffC5ifUXGuTVAd17dZd5+EdEjrcOglUn2HsWPgmTpo8yFv/s+JbjxPXMcc+EXQ5ZcpW4O+lJ1ZTbY+8W0anx72awjtygjJ8mEXHjx033ox2O8czx/bRdXrcz7Fjx9zS+RPAympdTsNGTXxmwdxi4ZcuQyY3/EJjvJl1om28etnrfQDvqtVq6PvAM+QqgRpvrEx2mv/YdJBrVU7XmAPYvJpum13f8op/HZ82/YdBuPYm6zd8r9MXLFzUW1KPcSbGgZiDzXmVCUGP9VoRvKtD38Pgb4dawfpovjMrVq6qw+1O8hcsossqV76iXRIdxmSZTsumdnS4dcJksI5HX42fMMmKsj3i2S1RsrTOw0SgU7pA963Zb/iW8PX+Z2fPum2+cLx7756eHzHORQQBQUAQEAQEAUHg1UcAK7lfe2nfsbP+4LF+2NgdkS7QYiq0fRECN2/eC/p20HpWcjsIBCj82FzGCzcJPzQs5WHpT0e5ldPYUEavXLHPLd4u4ItOi3WZroQAFPzVKk/Q8WxqxK4Ip7BZM3/V6Qf2X+cUhwsTP1dCAPFs+kbnr1ltYhDb3Eewk4QmIcA7NJza4nqB/rb6CASNNzGVrTNsyCWTEOjVY6W3onQcO5LV9Q8d8r0Ox8mSxXt0nD/lQaEMIsK6nwsuCnSTEEBb/ZHgEAK8syZozuwdQSDRrDZ067KUFVP+1GSfhlex67IOHrjklGiUQfa5PgtOCY0Lc7wHghDAnOFNoGi3sGhYf4a3pD7jMOassoCznZhj1BshgHnNKuurrr6VA6hrxbLfdR52rOxWvUkITPJCRrhlDAMBpnKjbDnvCguruaaivm79hlZwsI9sMkC/HxMlSe6WP3+Bwjp+2jT/xlDlKtV1npclBPLmL+jWJtcAXhWp6+MVma7RwbrmFbu6LCil7CRQhMCO33bqulKkShuEvvAlR44c1XmSJEsZ5KqYMRVC/xZ2roTAvv37fd1G0JUrV/R94HvMl5LTW4G++ixTlmy6ruXLV3grymMcnjHru3H8eHcy1zXjtm3bdXpXos2MS54yjV/9DsWyVT+OL0IIsFmaoFRp0uly2Oa6a7Ntr03ywpWsDI3xZtYJpScIUF/y00+b9X2nz5g5CCTBi4q38YbxZfXTh5mz+lWFOR7s+hZKZ6tMXk3us0yQXpgbrDwnTzov9vBZACcwMQ7EPBKShMDAQd96vSWTRMV705uYczv62VVMQiB12gyu0bbXIECsvuCde05pAt23Zr+BwPclx0+c0G3DXMQ77nxlkXhBQBAQBAQBQUAQeI0Q+E+YDOIfY3qbt7fNszMBMQAAQABJREFUGrCTues3h4kdb+mCE2eavEE+y/SPWQavHFZmPWD3G6aALIHD0Fq17beQW2l8HXkltkqCLdUrVjfXyWEnnVfmKrMnCIQTWm+Oea2MsD2/eNEedelqMgi26VuwCSIIttEuXNLIzS6wijT+bN92im2wO2xRwm75KHaua4qJn2kyyEoD8xlt2ZTR6VM3VFCOnEnoqx7OW4FD02QQ2oI2eRJWyNP6dYdUdBt2llq4aBpPSWkBOyeexn4hIPDz8Nnnztt1TZNBVXjsfO7H2FmxfB+NG7NZlQn78qO+e47/133XKFv6iIQfiBo1s6t03v6Y5njg2BW+ECwxTQaVZb8Y8G3gS0yTQUhr9/zwrhm2//snwSb9gwcO0wZImylzAoJTZ5j7eVExzdrAPBfs9FvSlR0TwxcEpHYddnhdNasV5fH4244zbLvWYUrgZU0GwczO1Bl1PNaFCDilrlXDYcPW1bmy14w2kbPYSe+c2Q4zNZ/VykHVamRzS+WvySA883j2IeUrZqb67GPDl+zfd5G+7LxEJYN/iiXLm7E5jue5TJNB3bqXpJy5PD93z3P5PuOVwcSsku+EnALmBbBFP7himgzyZHPctcxly1awM3CHSRM49925wzE3uKbz55pXgKpkMGlw9vQJnYW/dShp8pRsjsfxXoLzSzhK9SWmWYWXNRlUoXw5Gj5siNcqWQnH5qEcWJQoXozGjxvjNb23yG+HDKNhw0eoJB3at6XWrVq6JQ+UySCYjIHpGAhMOq1eudytLtcA+Htg8kCbSFq8aAHBnrglpsmIfws702QQzN8cPXxA2ai22uTpyIpm+uMPh2+cCePHUPFixTwl9Rruq8+YlFJOXlEI2levXh2qUom/edimuL9ittUfcxmwX8+KZ138/t93a7NeEyZM0k5w4bh6NZsH8yWn2LZ5vgKFdDI7szI60sMJnFfDXwUE34SHDu6jqOwM2ZdUrlqdtm//VSXrxP4GWrZsrrOExngz60yaNAn9tPEH3R5PJzD1hN8Clmze9CP7tUpsXQbr6G28wV8Br2hX5cHvCRzJ+hKYo0qbLqM2tenat43YQfeatetUMa6mrDyVjX5Gf0MwH2JeDI6YGAdiHglJk0GTJ4736uS2Y6cviHe6qNv/dtBAqlKlkkco4LPD8iXSiv3kdOzQzimt+W77KGsWWsKmm3wJk7jK7J6V7sC+PWwe8W11Gei+NfvNzsSX1QbriHd85qzZlE8LhMHvQItmzahs2dJOfgSs9HIUBAQBQUAQEAQEgdcLgf8EIWApO/zpuvNnHUoqf9L6k8ZUaPuT3krjj0IXdsnPsMPZo0ev0jH+f+vWA3pw/7Gy435fHR+z7VeHIseVEIBzzZrVJqnqELdwSWPlk8Cq39ORV2wTr+RX0a6EwJ7d54lX++qscGjrS65cucP2Oh+pZHYKUhM/O0IAGc8yEdGm1XxNprRsXZB/9D73WxCahECffmUoc5aEHmFwIgTYaS2c13oSkxCwI4tMQqDzl/BFkMJTUTocNu27sGIbAnv0M2fX03Ed2y/SjmQR6E9/HmcHtJY0bZ5POQy2rk1CAMpzKNF9iSsh4Cu9Fe8vGQASDs8Pr6QnjMUH7KPhHj871tFypoxyXQmBZo1nExwGQ3r3LaMcE6sLL39MBb3deEd7GrH/EEj8+DFo7ISaTqWhrbw6XoWBwAOR500wD1StNEEl8UUIwD/AkSOMxdErdJ7v6969JzyX/IPFPcwrj3VVL0sIdGi7UDsnh7Nmb+PeqhROqHlXhXVJc+Y1cPI/YRICvp47XYgfJ2z+hueWp36kJKpT+3Pq07unX2nNRCYh0LdPL3bwWcuMtj03lQxwGnnqxFGl5HNNDAXy4cNHCLaC9/7+O11lxRivKqc7f96hOziyc1M2a6CyuRICcHyZKctHOu7Iof229oVd6zQV9C9LCMAOPezRe5N17AC1QSOHHXRfhAAcd+7evYf27N1Lx9gZKe7fxALXloQ0IWDaNoeDWjh19kcKFSmmbIUjLRwLw8GwJaZCKNDYWXW4Hk1CIHmyZLTxxw2uSWyvK1WpRr/+ukPFfd2vD9X6zHm+szK9bJ9BGVy1Wk1t/9oqF85cc+bIrux/Fy5cSDkHteLMI55/zAOWJEmS2NZ+uxVvHfft22+dOjkB/vqbAcSmrVScv/3OOz6VLwQ4n4W4Ko1VoI8/vEqeFxLUUang6Hbb1i0+cjiiu33VQzkgx5XrHBca482ss+SnJWjsmNF+3YdJ6ixeOJ+yZXPMba6ZX2a8df2qO02f7niHwzcDfDT4I7wTSzsWd+3b8uwTYOeu3bqYjBkz6HNPJ+bY8+R43lNehJsYB2IeCUlCAKQLyBdPYhICQwYPpMqVPX83mYQAiC8QYKaYhADmK8xbvgTzR8rUIHH/UkkxP2KehAS6b4Pbb2gD/BF9Xqcuf+M9wKUSfAukTpVKzY25cuWkAvnzKSfEVrwcBQFBQBAQBAQBQeD1QOA/QQiEpR0C3oYNnJFmyhyfnWGmp6wfeVYio4xFC3fzyqNftcLfW7mIcyUEbt68T2wfXWWLEAGr+Rvzyrk3fBWjHMzC0SzElRDY+ONR+naQf4oAu4qw2nfF6hZOUf4QAsiwdMledir3s8r75lsRaOToahQnjmMFzn+REMBOC+y48CWmgvqNN9j54arnK/8a1ptBly//6asIj/E1eRU5HGlbEtKEAMZxsuSxFRmUL38qJwfAVhusI8irIYM3qBX0VpivoyshwCZ46DLvTIC4xnkq6+HDJ8T+BnglICkHurPm1ndKGhqEwFUmQvp/vZZMMsepUTYXL0sINKg7XREwKPrbYZWVg2mbatyCQAiAGIC4OtZ+XQgBO4eXbkBwAJQMvMVfO/s1Vx1a6dk2uVqtain8rXBPR1dCgM26ULYcH6vkESNG5JXfB33u+kJiOL+Eo0RIWCEEzp8/T02atSBTUaYa6OVPSBMCHTp2pnnzHQTfl190omZN7Z27ujbRXPH+dV9WpNd6rkgPrkIoOGSKazusa5MQ8EXIWHlw/LJLN5o5a7YKssM6kH3GNuLZiX1fwv3aPQ/Y1Vggf36qVrWKm3NaOMvOntPxHJjtD8656cy4fcdONH++Y2VxcPodzlHhJBXiqjT2py2LFi+hNm0dCs78rOCbMc3xDegr77TpMwikAATOWL8bPVJnCY3xZtbZpnUrat+ujW6Pt5MK7CD5t527VBK7HSmBGG+mE1m7Me2pfWzehfbvP6CiXfv2k7z56ezZc56y+gwHPsApOGJiLITAc+RMQqB3rx5Ut07t55FezkzCZ9GCedpxfKD7Nrj9ZjV595491L//INr+6696p4oVh2O0aNHUs493Tfp06cwoORcEBAFBQBAQBASBVxiB/wQh0IG3i877Z7uot76qyj8EBw/s7y1JsONMhXbefCkIijQ7efudtyhKlEh2UU5hbCedhg/9gbBS3xIowLGaOFasKBQ16ptcTkSKGs1xHD/WsQLMlRD466+/lckgKCYh/iqQZ8/cQbNnOVb0uRICv/x8gr7pt9ZRIP8t8Wl6fe7t5OHDp7zqNIJK0rxlfqekJn6edgggA+6D7cXT73svqPxYPT1wcEWCkvu/SAj061+OPvwwvhOWdhfYXdH8HzNPIKQWLG6kkzVrwivgzzpWwCfn3R7+7BCAwhvlQLJlT0zZcyRW5/jzsoRADN7BAMW7nUSOHJHefieykwkZu3QIg8mrqZO3siLVMfihCIoTJzq9/0F0/tHDz03USPwc8X9+HtkOvi7GVelvmhNq3DQvlS6TUaf1dGKavQkLOwT27jlPA75Zp3fpgJSLHTsaxY33DkWP7ozFsqW/8y6k++rWXpYQgGkxmBiD9OhVSo0VdeHlD3ZEVSo/llfZOcz3TJlWm2K/F03nCClCYPacuVrprivzcJKKV9SZ5ls8JHMLNncIQNkGpZsvgYIzy0fP3ycnjx9hEszx7LFNbcJ7Dyv1LYkSJTIlTZqUx3ocZa7g7ejR+Rid+zk69ejZWyVzJQSwohEmg2BWALJh3Rq/zKwMGTqchg4brvKEBUJgy8+/ULPmLbV5GrwP48WNq0yGxHj3XTKxmDhpijYx6EmhFyiTQd179KIpUx0mRRo3akjdun6pMPP1p0rVGrRt+3aVbOiQwVSp4vN5MbgKoUATAtmzZyMovPwRdqZKq9c4vhm6d+tKDRs+J0gD3WdWe7ADZBk/Fz8waQXlsLkjxErTtElj6vJlZ+uS573bxPbg9TXMemEM+ZJ79+7xuySqStawQX1+/pKo86+696Sp06ar8+D0O0gJkBMQV6WxCvTxB2ZnYKIEglXmq1Y839HpLSueZTzTEJhbgdkVS0JjvJl1QkEJUswfMZWyM6dPpXz58upsgRpvbHeeRowcpcr1lxwDuZsqTXq9E821b80dQTAt9mFG398a5tgrVKggFeb/wRETYyEEniNnEgIwJ4d3hD+SMVNWXoByWyWFiTCYCoMEum+D22+qEcYfkGIgDjdv+ZlNYu7jRWdPjFiiCBEi0Bj+RilWrKhTuFwIAoKAICAICAKCwCuKAP/Qf+3l6NFj2mmS5djJ7oh0gRbTKa4vp8L+1G061qxeZUIQnK7CebAnsRx3si8BtyS1ak7WTjq/33DYLd4uoGf3FTqPqyNVOF216qtda4pd9mCHmfjZORU2C7x+/W5Q1UrjdRssx6fBcSp844Z3J62oz3Q0+/ve82YT1Lnp3HT3rrNu8WYAkzu6vRvWHzKj3M7nz92p006fus0t3nQqvGzJXrd4u4BNG4/qMnnVtlOSLl8s0XHr1x10inuRC9OpsC8Hylb5wXEqbOXxdmQTW/qe4LwbmD588MRjls4dnzvRPrD/olO6QQPW6bKGfuvskNkpoXHBO3t0npd1Kty+rbtjXaMqdXrv3iNdHxx+m4JpA22wnlncz7Wrd8wkTue8I0mnnTPr5ZwKw9mzVS/GhT/C5JXOg7xPnjg7hQzOc+dPff9mGtOpsC8HiVa7Nm/eot9radJltILVkZXMOi5jpixBy1es9Oq41HofwkGnq8AhqhU/f8FC12jb69p16uk8L+tU2JcTSDRg7dp1ur6GjZo4tQnvRzj3tO6hRcvWXh3Ysn1wnZZ9CTiVZV2Yjidx7k1Qn1X3smXLnZKOGDlax2EM+CvoU6tMOEs1xXQq+bLYmeV6OzedCqdN/6G3pE5xcFZq3QcroXRcSPSZLtw4gRPng4cOBY0YMSooT74Cui1o07jxz+dLtCdx0hQ6/uxZ7+91owrbU4wr675r1qptm8Y1kH0t6DzIe+xY8L9XmQDRZfjrxBrtYOJG53MdU6Ex3sw6y1es7AqV7TUcKsNpuoU777TQ6QI53mbNnqPryPlxHl2HtxNWvOo8dn1brXpNHc+28L0VFbA4E2PXPrerxNscjPSmU+HFS5baFeEUZjpuZp8MTnG4MN+ZrnOga2LeiaXxmz/f+3fTyFHf6bQDBg12LSqIyWAdX79hY7d4u4CrV6/qPOjfS5cu62SB7tvg9ptuiM0Jnpmt27YFsZ+bIMzr1rOTOGnyIDa7Z5NDggQBQUAQEAQEAUHgVUMAK//+E8IrwvTHjPVRYx4RHxJiKrQDQQiYCvltW096bTKUe5bSzY4QGDHsuTK6T69VXstC5M2b95wU7q6EwPVrd3V9qPePPx74LNNXAhM/X4QAyvpp0zHdhrKlRgcdP3Y1yBchAEW4hdOpk9d9NSmITS3p9GGVEBg25Aef94EE7KRY30uXzs8VMogzyQreqYGgl5KwQAiYCvlxY50VaXY3V6/ONI2PKyGw8ccjOq7O51OD2Ma+XRE6jHflBHVst1DnCW1C4Bg/G9a4b9ViLiuMPROLuImhQ77X6V+WEDDnnsED12uMvJ1s/un5s/1Z9UluSV8XQqBu/YZu92YXMH7CJP1OK1KshFMSUyEPRY03uXDxoi7HjhBg+8s63h8FCJQf6TJk0nlCmxAwlW1sciWIfSp4gyOoXYeOuu0hTQhAMWZ9h2TLkctru6xI3hmi8yDviZPO3wHBVQj5UuRZ9Xo7moQA2nTx4iVvyVWcq4KWfQnoPCHRZ7pwDye8EjaoTt36Glu27e2UMneefDpuxUrf30tOmV0uFixcpMv6KLt//c5OfXUeYPwihMDly5edyjhzxj9ig1fW63wzZs5yupvQGG9mna5kqFPjjIv9Bw7oe2C/YkG3bt3SsYEcb1D2onzruTaJB12hywn7lNDp7frWVGh36faVS+6QuTQxDgQhYN7DxEmTfTbaJBDCKiHw8Sf5fN4HEpjkfbIUqYN4R4jOZ+ISiL4Nbr/phvg4uXHjZhDeUda4tiNLfBQh0YKAICAICAKCgCAQBhH4zxACwB47ANrzShE2s6A+anDEdUjsDLD62lRovywh8PTpX0EVy43VSrkHD7wrIFev2q/T2hECe3af0/FQDC70slL30aOnQa1bznNK70oI4J5bNJuj0/y6/ZQFwwsfTfz8IQRQkblyG/dVoewY3SZ2HuvWlj69Vur4X7efdos3A+7ceRiEleWWIjWsEgIN6k13W0Ft3gfOsUIcq8yte4Gy3BQQTlYcFMYvK2GBEDBXpvsan+fP39L3DxxcCQEQAOXLPB9bIOuw0tCTmGMZ5YU2IWDuOJkwfounZqtw3FatGs93FPlDCHgjXLZvO6Wxrc+ki+tqf7vGjBz+o86Dc1d5XQiBTFmyBbHTX9fbc7s2lf5QKFkCZUPK1On0D/e797zveoKCz/qRb0cIsOkAHY90bJLAqsrt+ODBg6ASJUs7pQ9tQsBc8dmrT1+3NpsBeH6t7wPcqz+EAJtbMotwO/e2Q4BNSPDK8+erlk+dOu2W3zVg6dLlGl+ssHeV4CqEQoIQ8GcV88aNm/R9YPXp06fPiZqQ6DNXnOyu9+3fr9uEHQEgCSxBP1vPia9xZOXxdASpg2fNKu/4iROekupw7Byy0uP4IoQACiteopQuB6vZfQkU3NbKeii6QSqYEhrjzawTWPizWpn9qej7Ll22vHkLQYEebyCTrL7KmeuToOs3bjjVZ15g15BJINj1rfmMgtT8N8TEOBCEwISJzwlsX7uqcH9Fi32qMQyrhAD67fTpMz67wyR88N42JdB9G9x+M9vi69xchMAO4X0ll3hBQBAQBAQBQUAQeAUQ+E8RAqHRH6YS8GUJASjlypX+TivFLly47fGWHj9+6qTstSMEkLlHt+W6PKSBqRnsBLAEChIo0dk+t0pXqfw4nd6OEJg75zcdD7NBN32Y4IGZHJi6wX/2TWBVq48mfv4SAjCTgrotZbZ5tCMEZs18bgoFq6C9yYRxW5zKDauEAO4ZK/y9CfC2sAHJwQ5tnZKzv4ogs78tE0xOiYwLmN7p1mWZoz9bzXMaR0gW1giBNasPGK13Px0/drPGBzi5EgLIARLNwhBHrHw/e/amU2HAdfKkX1Q6E8/QJgTmGc/qwP7eV5Fv2/pcgY/79EQImGaFvu67xgkH8wIEQJWKz+cSX2N16y8nnYg4kJmu8roQAlAI+VqJP23aDK0sQfpdu5+TeZizkyZPpeNPnjzlCpW+Zl8DQWXLVdRp7QgBJK71eV2nNFjhiZ0AlsD0yp49e4M+r+1IlzpNep0+tAkB0yxP85atrCbbHtmevm43cPVECJhmhWBOxZt4IwSQDyZjUBf+Y6cHSBVPcu7cOafdF3arNIOrEDIVUq7mljy1wzXcdYdAqjTpgrwpua9du+ZEvGA1sCmB7DOsxq9es5b6P2ToMLMat3Os5rb6AmPYlB2/7dRxSZKlDPr5l61mtNv5oUOHg9hRrPpvt+vHVBqzHXHeYXbfrQwrAGY7LKW81b4XJQRGjR6j7wP3ePz4casatyMIkVJlyun0rrsmkCE0xptZJ/DIlTsv70h1/n4xbwZED1ZmW9gBA1MCOd5Q7s5du5wIH8yxO3b85kR6YcX1vHkLVLtAPpntc+1b7KYx59ThI0aazXc7v3fvflCNzz5XY69k6bJOc7VbYg8BJsaBIAS2bduu8WdHul53aq1fv0GnRZ+FVUIAbfM1Z2OeMJ/dOXPnOSEe6L4Nbr+BnLHmxzVr1zq1zfXCJHXq1mvgGq2uMfa8zSm2mSRQEBAEBAFBQBAQBEINgf+EU+HQdO9gOsWtXiMb1fTgVNjfNrZtPZ+OH7umkuf+JDl90aWYm3O7u3cfUe+eq+jwocu6WFenwlbEtWt3qUPbhdpZqBWeOHFM+oAdrR7Yf4nu3XusghNxWNVqHxErD9W1q1NhBD548ISaNZ5NbItfpUmcJCb1H1hBOWlVAcYfOEYeNuR7dlr1lwodOrwKpUj5npGCyMTPm1Nhp0x8se/3C9T1y6VMeDnHDBlWmVKmet8pkHcFEJtMUmHhw79BffqVpQwZ4zmlwcW6tQfZmdZP2qkpwr5m570ZXZz3Bse56YhhP9L6dYdQFLVpV4gKF0mjzu3+LJi3i9jEj4pCP9SqndMpWdtWPDaOO8aGFdG8RX4qUdLdufNvO86oMcIzj0paqHBqatu+sJVNH5cu3uvkWLdVm4JUtFhaHW+d3Lp5n4YP+4F27Tyngj7Kloh69i5tRavjyzoVTp8+LvX34FTYqSIvF1MmbSXeCaFSwHHut0MqUTR2nmsKMBn73WZatXK/GawcGqfjNpgC59xdv1hKBw5cMoPZwXdUNc5OnrhOV6/eUXFw/t3367LqeUNAaDsV3vnbWeJdDaptESOGp28GlqdULs8GIn/84Sgx0eE07j05Fd7441F2OLlBlYn7HT/hM3o3ZhR17fpnxfJ9NG7MZh3cjMfqpzZjFY6tO7RbqOYWJM6cJSE/o2V0PuskOM+dlSesHE2nwlabOnZoR61atrAu9RGOUKtWq6EdUBYskJ/nhck6HiesxFMOAXFe8tMSBEfFcBhsCivQiH/U085djucBca5Oha30bFaIWKmlne1a4alTp6KECRMSm3uhP//8UwWnSpWSWrVoTs1btlbXoe1U+MeNm4hXZaq2vPnmmzR/7mzKnDmTdQv6CEeKbL6Bx/kzHebJqTCb+qHWbdqpdHDW/NPGH+j9953fK1YhLVu1oaXLlqvL0SOHU5kyzvMimzKhMmXLc72O92C5smVo2NBvKVy4cFYR6njv/n2qVKkqsc17dR07dmzlWPadd95xShdcp5JMglCDRk1UGf46QXWqkC9++HEjsbkdp+DkyZLR0iULlQNrM+Lx48fE9r+JTeCoYDip3LB+DSVjh9eWBLLPTp06TfkLFsbiF1X8kMEDqXLlSlZV+ghH3C1btyXgASlSuBBNnjRBx+OkXoNGtGHD9yoMzoIXzJ9D6dOlc0qDi3379lOzFi3p7NlzKq5rly+oSeNGTulYyc/PcU0dVrZsaRo+dIhbv1+4cIEd1penGzdv6rQ4cXU86xTp5QLjqEiR4oRnGuKpn5hYpC+7dCM4VYdgblg4fy5ly/aRurb+hMZ4M+u02lEgf36aNHGccnpqheF48+Yt4h0BBGepEDw3mzf9oJ09IyyQ4w3lQQYOGky888Bx8c9fjJmcObLTlStX1XNsjUk4aZ4+c6aes+36dsKESdS7bz9d3qCB/ala1Sr62jpholY5lN+06ScVZPd+sNJ6O5oYB8KpMO96IzYlp5/DTh07UMsWzdyawMSJendcueJwno0EbVq3ovbt2jilNd+Zs2ZMo7x58zjFmxds9o5415IK8vT8W+mZLKIBAwepy5Ytm1OnDu2tKHU0nQpbEeXLlSU4d3eds/GMlS5dTj+7cCr+/fq1bmM0kH0b3H5jgoI6dXY4s48cOTKtWLaEUqZMYd2aPuJeatSsRbwjQoW5OoFHIJtSo06MNeaYPJ/kplkzp7v9PlWZ5Y8gIAgIAoKAICAIhBkEhBAI4a4wFdqBIAS2bD5OA75xKOTRdCgVs36UiLJkTcAKmUeKBOCVzPTHHw9ZyfAhLV/2u7pDT4QAIkEKQDEIxZsnARnQvWdJOn/utlYi2hECyL9z51nq3WMl8UJVVRyU7FDCQ3EeO3ZUunDhDyYaLmpiA4nKlPuQGjV2/6A38QsOIYAyJ0/8hRYv2oNTLXaEwMOHT6hju0V05ozjBzewyl8gJSVLHpuiRXuTLpy/Tfu5vUcOX6HUqT+gZ6wEPvGP4j2sEgLNW+anCeN+ZrLlGaVNF4dy5EhCMVlJzX4dFFkCQuAf/YgaQ6PH1qB33nlL42Sd4AcrO9alQwefk0sxWcH7Yab4lCZtHEUWYUxs3XqSHj18qrKhHCju48ePYRWjjmGBEIByvmmj2QoXNAqKcNxLtuyJ+UfaG6qPQYJdvPgHpc8Qj+/vEZ057RgXA/ieXAkBlAFCa8jgDfTzlhO4tJXoTDq071iUy4xLbPZLpQltQgB927zpHP3cY9ynSv0+gcyJx2TJ0aNXFR4Y9+/EiEwZuO1bNjvu0RMhcJ6fFRCClqIDZEvOnEkpxruRKWnSWIQ5wxKMP5B2IO8sSctjKnvOJIpQAbHJO3oUrs+e/a2SRI0aiUaOrkax34tmZdHH14UQgPJw+PCR6kd1hgzp6dMSJbg/4jJpe4t++20nrVm7jufWf/CIEoWJylVKKa+B4JMVK1ayQrKVDooZ812CwgxKk5usWNzFJAAUslAy1qtbhyZPmarSeiIEEAmFABTrx44dV2nt/oAMmDp5Ih07fkIr4UObEABWvIpTtxv3mDlTJipYMD8lSZyY9vz+O+3etYd4lwWPu1iUK2cOpdjA/XkiBE6cOEGFWKlq9UOMGDGoaJHC9N57sSlt2rSEe7bEFyGAdEOGDqehw4ZbWShBggRUoXw5SpQooSJ+gPnCRYs16YJ7mDBuDBUtWkTnsU6CqxAKNCEABWTUaNFo+fIV/P6MRpUrVWSiMSWFDxeeTp46Rbxin9hkjtVcatumNbVr6yCPrMBA95mpPAQBkTv3x6yYzUHZPsqqnjNekU0zZ83WCvyo/FwtWbyQ3/eprCapI5StRYt/ys/ibR2Oe/s4Vy7u9zT8bXORDh48qAgSaw78KGsWmj1rBr31lvv7tW27DqpfrcJArqHfEydORA/u87t6/35asnQZgURp1rQJbfj+Byb9Hc+fndLYKsfXccvPv9DntetoEgqK6koVK6h+Aml27tx5JrGWaeUfymvUsAF91a2LW9GhMd7MOmvVqsnfnLvo8OEj9MEHH/B9lOd3TVJ+Lz9RYYv4uYGC0hKQo6VLlbQu1THQ480qfMzYcdR/wCA9T1jh1hFjsV3bNgSFu0ni2vUt2shmWtQ7wMqP+839cS76iMfxn3/eIcxLvMqb7vPYgcSKGZMWLpznRLZZeX0dTYwDQQigvnbtO6rn36obz80n/CzGix+Pn50L/J19kNatX0/Ro0fn91U+TaSGVUIAhMGqVavp1KnT6h1sPrsgevHs8g4AdbsgC2ZMn6oU5db9W8dA9m1w+w1EaPacufm3wR+qOSCY8+T5hHLx/Jg+fTq6eOkSHWISesqUafo5Sp48Oa1dvYIiRYpk3YI64j175MhRHTaT7zdfvrz6Wk4EAUFAEBAEBAFBIOwhIIRACPeJqdAOBCGA5q5be0itnMfqZE/i2D1QnEp/Okol8UYIIAHKgkJzPZfNpoj4B+8DisFKwPgJYijlOFauv/HG/8hcVeyJEEB5IAUGMnGBHQPehHWQvHrLngxAPhO/4BIC7HOBsKPCUuiiPDtCAOFY4d6x/SK9mhthrhIlSiQaMboqr5b+kX7f61BihlVCYPjIqqofhwz+XvWt671Y17GYoOnLOyLQz56E/UfQ4IEbiO2+e0qiw0EWYIdFwkTv6jDrJCwQAmgLFN19eq5UpJnVNtej2j0wtBL167NGkVeI90QIWHlBmoCAw66A69fv8o+l8IoUyZQ5AVWsnIUiR47Iip1nYYYQQLv/uP2AevPumGOMiScBadKfdw/g2WczUyqZJ0IAkVj1j9X/rlKseDpegVvAKRiE1dBvv9dEg1OkywX6pEevUoqscIlSl68LIYDVjlAiNGnWQu8CsLtfKPlnTJvKRI37DiCkx8q/Ll27aaWfXRnYPTDmu1HEpoJUtDdCAAmwih0KkDlz57Jy97TaMQAlOlYZly9fVil/ofgwV9yGNiGAdt+4cYPYbAvt3esgyBHmKlCELpg3R7XdUs57IgSQt3uPXjRl6jTXYqhG9Wo0oP/XOtwfQgCJ2cY5fdN/oEfloVUgdiSMHDFcrWC3wsxjcBVCgSYEsLJ+9KgRVLlqdb3i2Wyfed60SWPq8mVnM0ifB7LPsHvly65fKaJMV+DhJEP69GpHDZTydoJV/9gNwc6c7aKdwnLwanAQZFC42wl2o0BJCsWhNynCZNPE8WMVGcE+r1RSO6WxtzJc40AKNOU5xtrZ4xpvXoO0adumle1q39AYb6514pkrW76SE9Fkth/nmJfwXFatUtk1Sl0HcryZFbCZL5o4aQr9snWrIozQ51gpnjFjBt5J1UKRfkjvixBAGjYnRq14Z5K1iwVhngRkAd4ldqu9PeUxw10x7typoxntdu7PPIL3R4OGjRRh5lbAPwH4rTJ+3HeKwB00eIgKDauEAFbJFyiYnypUrELsD8bTLfHCk4g8Jw6n4sWKeUwTqL4Nbr+hQSCcseONTaZ5bJ8VgR1s33zTj0CaugqbFHPacYgdYlmzZHFNJteCgCAgCAgCgoAgEIYQEEIghDvDVGgHihBAk/fsPk9sx5tXBF3Xq50RDoVsrc9z8urF1OrHG/sFQLA6X7G6uTr35w9Wt+HD3FVM8zp58ianzl8Wd02ir7Eae8WyfWwO4DCvWHqsw3ESPnw4yp4jMQGTJLxy2JOY+AWXEECZWPUPUzogByCeCAHEsa133uK6Q+2ywK4JS4BDgYIpqXbdjxW+WNX8KhAC2OFw7twtViT8zOPlnN4RgPuCcvr/7F0HmBRF067/UzEQREARJYMERbIBE6AgSs45CYjkHESQLCrJQJAsOStJFFABAUFFVIIYyBmUoAioGPavt9fu65mdTXd7d4Sq57mbme7qMO9098xWVVfBlVC16kU8dwboe9dHjAdYh7/Hgt6dlisqnX8bW2xXrV6Ynnq6AP/4uUYnO46XikIAncLYhOD6u53HCZbomiDEr1qtMFviFWWLzhT0fI9FESsEdB04Bps/UJDVrjFBsWInxcw5ze1iagy2bDFTpWGHxbiJcS4lkAhlRtdOC1R+vvy303B2eRSKMO/q1JyoWLDbZc78FgHsEMpP5DGyhQX+znFPbNF/Fwu/SlDG29PQbJ4bkSgEsDNo9Uff06JF36j70XPvqafvoXYdnAoBdIaHFm38lMfWsu20fZvfjYXdydu5bYxVjK2UKVPYWY7zK0khAEv+/fsP0EtDXmGrYCj1/OsXbhiCa7iKgMVwpky3OzBwX6xfv0FZnm/f8a2xVAQPhEXdu3ZhFzTVlSsQDo6oioZTCLjrh2UjyrgJblXgXgUEa1xY5doENyQ9n/dbGzdsUJ9eHjLYzqZohRqRCKOgZGF/ycTBbI27FDSK9b0i97FXz+7KMt+21g+lEMAzeeedRTRh0iRlSQ2LZFCD+vXoFRaYaIpUIQB+KCywW+M9VrpwcGhdhTrCahbW9s2eaRKwI8RmTAzs7Pq9zm2XQdrVDgSfU6dNJ/bPHiAsg9V827ZtqMwTj3tVZ9Ji/czgumnylLeVlb22okZjsHSFpX9JnncQPkKAF4rOnTunXOlMmz6T37EHHayYD35hb1t2zVPGked1gXcF+oXnZlvXgveOOzIRXKvA8hjjtMyTT/E74EdVTUIVAqiEAwYrpda8+QsCnhG+0SDAxA4it5sg1YH//iXHePNqEy5pMNamTZ9BsHrWpHBjJRXcmBUuXEgnex5jPd68Ggm2ZnKwYCOQXfPxKoIVtheh/HvsmgVzC+7j3JT5zjvp2Webq3XIbcHt5g117YVxKP5I1mCUx7OB4vOzzz9XYxn3ownrQr++L6rn9Oao0XQ5KASANZQBw0e+RnPmzHOs21BCVeDdYu15rXPvNtL3bB9j8WyjfW66fazXr78xSu0w2bt3Hyv//9ZZyu3b3fnz8/unuqe7Nc346cZN/F7vRceOHVfvKvs9qHnkKAgIAoKAICAICAKXFgKiELi0nkfUvYFlP4Tev539Q1kjwy2Mhxw/6nqDFbCFunBJ1LJVoJsfd1m4+4DF9M8sZIewMNMdN7NrhdSeCgd32eS6xo4B4Ar/53dwf2ElfTkTrPzh+ghupTJmTK0EvNdd5y24D3efGGsQHJ8+fZ7SpUupnicUDJcrHTv6KwtGfmVMUrOg9GZWVgUKOGN1b7ZAH/E1Ro+tF6uqY1IPXI3t2/szpWFXZHAbdMMN1yWoXgj7f2U3VXxQiicIZ0IR4pVgbHEwcuWuC66BMMbCFAtV5WWRZ7s0cftDhrsQWCNzIFa68447WRicRSkForkxWGZ+/8P3LLj4RbmPgCIh3LOIpn43ry2UgEBxQP++bpZkvYarpJ3f7uT1PR3lzJGDFaQ3Jag/EOrCFROO6dlNh5eSJJoGIDQ7wi6ajhw5SteluE49d7iNuvbay+89BEyOHjvGO6f2UMpUKSkbu8XBrpJoKZbPDH2Ci5K9e/cpoTtczEB4Fy2hHrgRgluNs2fPUpbMmZWyJpxCIVg78JsOdz0XWRmU567c/J10WzDWmKZjfTh2DK7yjirFIcbanSxYTui8iGknrcrs9cXtzgZCVezi2H9gP7vMyaAs8KFMi5ZiOd7CtY0+57+noNoBAN4d274OiL3hVQcE0XDl9tNPPyt3ZXCBFmw3ilf55E6DYm0rx9tIyesvdk3E5zkl9z3Y7WMe7d+/jw4eOqyeR/Zs2eL9PJLz2UIZsGfPXo51cZxdp+YiKJkiJayJUM5d7s8y0vsVPkFAEBAEBAFB4HJHQBQCl/sTTED/jx8/Sx8s36FquPGm66huvftC1sbfedSrx7smgGqrNiWpYqV7Q5aRTEHgSkUAyjjsKPnnP//21WsWUfEYQt3vzOmf09w5mxUL3Hr16h18h02oeiTvykIglEIgue8UFtAzZs5W3UidOpVnoGO7jxAIwF0MAg2DBg8aQE0aN7JZ5FwQEAQEgXgjEEohEO9KY1jQjkdR/umnPIOY281t+HQj75ZtqJLSpbuFtn4daPlv88u5ICAICAKCgCAgCAgCgoAgEAsERCEQCxRddby3bBuNG7vOlXppXL73QTvTEQg0WzSboSz3kdi2XSnlmsMwWCdQBsyc/hnNm/ulSoXF/LQZTQlBQ0HaNZG6kH+CwBWMgD2Hhg9dRWvX+F04lCqdlzp3fYItTb13GMAH/0COXaCDbfcfVImDAWYzSMkcMlAk6kn1GkXYnc3DidpGtJVfygoBWD0+8mhJZQWN+xry0iBq1LCB5y1CGTBsxEgaxa47QHBv9MVnn3I8muAxSjwrkkRBQBAQBIIgcKkrBGyXaHAVM3f2LN45FBhXCbeHnSqIf4AdYKBQcTUUg/wTBAQBQUAQEAQEAUFAEBAEYoSAKARiBKRdzeWiEECfly7eygG81pvu31vwTsp/dyYORJaRXRClZRcTF1RwWvj3PsAudDQ1bPyAY0eBCDM1MnK80hGwFQL79p5k/7BzzS1nzZqOChbOrOZPbo7hcOH3i3SCd+KsWf2DCsqrGRFoGMGXbVc4Moc0Ool7FIVA9PjC73r/AYNMwRIPPsjKrKJUuFAhypkrpwrmCRcD8GutfZyDuXu3LmF3FJhK5UQQEAQEgQgQuNQVAogn8uBDj5ogx3CRVarkY1SkcGHlH/8ajs9w6NAhQmDnuXPncxwwf/wRxHb5YPnSeLnUigA2YREEBAFBQBAQBAQBQUAQEAQcCIhCwAFHbC4uJ4UAAn5OnbKRlnLwX1h3RkIVKxekVq0fc7CKMNMBh1xcwQjYCgHc5qqVO1XgZgQMjoSgcBs4uJIKWmzzyxyy0Ui8c1EIRI8tBFYIBImAt3YQyFA1NW3SmAYN7B+KRfIEAUFAEIgagUtdIYAb+nLLV9SlazcVcDySG0S8iNkzp6vg1pHwC48gIAgIAoKAICAICAKCgCCQUAREIZBQBK+Q8ju/PUaj31zDAe1Oe94RLJmxa6BRkwcJ1s1CgoAgEIfAyZ/PqfmzZcvBoIq1229PQ1WrF6EKFQskakDXuF7J2eWCwKXsMsjGcPPmL6lnr960a9cuO9mcI1Bx4cKFeGdAV3r0kUvLLZPppJwIAoLAZY3A5aAQAMAIDj502AiaPmOm2QXgBj5t2rRUs0Z16tqlU7wD0LrrlGtBQBAQBAQBQUAQEAQEAUEgEgREIRAJSlcRz/nzf9Khg2d4O/Npji1wjn+gXE+3pLuJ7rnnDkqXPuVVhITcqiAQPQIXL/5DR4/8oubPkcO/0HUprmH/6TexW5VbKXv29NFXKCWuCgQQuPfc+fPqXrNmzUqpUl7aa+3Zs2dp1+7dtHv3Hjpy5CgH005Dt916K91//32UMWPGq+KZyU0KAoJA8iBw8tQp43M/Q/r0BOv6S5n++ecf/iY4/N+auZsQlyVDhvSUM0cOKlasGF3LLoSEBAFBQBAQBAQBQUAQEAQEgaRGQBQCSY24tCcICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgkAwKiEEgG0KVJQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBIKkREIVAUiMu7QkCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICALJgIAoBJIBdGlSEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQSGoERCGQ1IhLe4KAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgkAyICAKgWQAXZoUBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEkhoBUQgkNeLSniAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAIJAMCIhCIBlAlyYFAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBASBpEZAFAJJjbi0JwgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCCQDAqIQSAbQpUlBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUEgqREQhUBSIy7tCQKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAsmAgCgEkgF0aVIQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBBIagREIZDUiEt7goAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCQDIgIAqBZABdmhQEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEASSGgFRCCQ14tKeICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgkAwIiEIgGUCXJgUBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBIGkRkAUAkmNuLQnCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAIJAMCohBIBtClSUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQSCpERCFQFIjLu0JAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCyYCAKASSAXRpUhAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEEhqBEQhkNSIS3uCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoJAMiAgCoFkAF2aFAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBJIaAVEIJDXi0p4gIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCCQDAiIQiAZQJcmBQFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEgaRGQBQCSY24tCcICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgkAwKiEEgG0KVJQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBIKkREIVAUiMu7QkCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICALJgIAoBJIBdGlSEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQSGoERCGQ1IhLe4KAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgkAyICAKgWQAXZoUBAQBQUAQEAQEAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEkhoBUQgkNeLSniAgCAgCgoAgIAgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAIJAMCIhCIBlAlyYFAUFAEBAEBAFBQBAQBAQBQUAQEAQEAUFAEBAEBAFBQBAQBASBpEZAFAJJjbi0JwgIAoKAICAICAKCgCAgCAgCgoAgIAgIAoKAICAICAKCgCAgCCQDAqIQSAbQpUlBQBAQBAQBQSApEPjzz7/p99//orRpb0yK5qQNQSBZEPj999/p/IULlCF9+mRpPykbPXnyJKVKlYpuuOGGpGxW2hIEBAFB4KpH4Gp611z1D1sAEAQEAUHgKkBAFAKX+UM+cuQXOvnzOTpz5gKlSHEN3XLLTZQlazr+sXh9gu/M5/PRmdMX6KeffqOff/6N67+WbrstNd2WMTWlTJnw+hPcQalAELjEEbhw4SL9dOI3OnHiLEEwmy7dTXQrz6GMGdNc4j2X7l0JCGzauJdeH/kxj72/qGbtYtSw0QNXwm3JPQgCDgRWrFxJXbv1pAusEGjbpjV169rZkX8lXQwdNpzeGjeBv8FS0msjhlHZsmWupNtT9zJq1BiaOXu2Ou/YoT3Vr1f3irvHS+GG6jdsTHv27FFdmTt7FuXIkV2dyz9BQBDwRuBKeNd8unETdenaTd3go488QsOHvep9s1dx6okTJ+jAgYP0088/07///MO/226lrFmz0p133BETVM6cOUNHjh6lI4eP0F9//63qzZz5TsqQIQP93//9X0zakEoEAUFAEIgUAVEIRIpUIvL9/vtFer7HItPCiNdq0bXX/s9cu0/Onv2DFs7fQp9u2KMEje78a675H91b8E6qUbMoFSmaxZ0d9hrCy/ff20GrVu6k3377w5M/e/b0VLFyQSr9eF66/vprPXnsxHPn/qTevRarJLzsunQrwy/XdDZL2POvthykaVM3Kb67785Ez7V+LKDMAsZlw/rdAenuhFSs0EifISXlzn0bPVbyLkrLihQhQSAWCPz7r482bdxDixdtpe92HvOsEmMf465q9cJs5XmdJ48kxh4BrA9rPv6BDh48rSrPlfvWgEawPt188w38YZ6aChXOTCUeyknXXXdNAN/lkNC5w3zatesn1VUojGfMbs6CxBSXQ9elj4JAxAhUqFSFtm3brvivv/56+nrLF5Q6deqIy18ujL/88gsVu+9Bunjxoupy0SJFaMnidy6X7kfcz8EvvUzjJ0xU/H379KZnn20ecVlhjByBMk8+RT/88KMqsPqjlXTXXXdFXlg4BYGrEIEr4V3z8eo11PQZ/5patswTNGWyf629Eh9n2/Ydad/eferWBg3qT8WKFg16m3+zYH76jJn0zruLzPeEm/meu++mevXqUJPGjdxZYa/PnTtH8+YvoGnTZ9C+ffs9+aEQaNigPv/VY8OxjJ487sRWrdvyb5pDKrlFi2ZUvVpVN0vIaygnGjRsoniuvz4FLXp3YUh+yRQEBIErDwFRCFwCz/T8+T+pTs24F/Kipa2DCqDWr9tFY0d/ElRQb98OBFsNGt1PderexxpnO8f7HILMSRM30LIl2wi7AyIh7ETo3LUMPfBgjpDsv/zyOzWsN9nw5Mp1K414PbTiwzD/d7Luk1009JWV6qp48WzUf1AlNwtjs5beX74jID1Uwv/+93/UpGkJqlEr+IdCqPKSJwhoBA4fOkMDByyno7xzJxKCYq1Pvwp0++2yYyASvBLKE5/1IXWaG6j3i+WpQIHYWAYl9B6iKf/KkBVGQZohQyqaMq0JYb27XGj//lNmLt1xZ1rCfBESBNwItG7Tjt5b/r5KzpTpdtr06Xq65prLR4kHi82zZ8+q/hcvVpRuvTVQUYlMCCwefOhRNgQ5oXgrV65EY0a9oc6vpH+iEEiapykKgaTBWVq5chC4VN81P7Ml+5dbvlJAp0mThh5+qERQ0K8mhUC5pyrQzu++U1jMnD6VSpYMNCREJnjate/EBjS7guJmZzxVrhy99tpwSsU79SKhhe+8S31e7Evnz1+IhJ2NQq+ldm3bUJfOHcPuGCj9xJO0e7ffEBL9WbXyfcqSJXJjUIydosX9u4fhhnDXDzsj6qMwCQKCwJWDgCgELoFnGalCYP263UogbgvrISTJli2dchP0G+8cOMACFAhR4KpE0/0P5KBuPcrSTTcFtwwF/6svr6AtXx7UxdQxZ84MlDVbeiWw/OOPv+j48bP04w8n6PTp84YPiodmzR+iajWKmDT3iVshgPxadYopQbybN9h1tAqBa6+9xlOx8g9v/7t48Z+AZmqyQqBps4cC0iVBEIgEgZ3fHqNBrAywd9VAYXb3PXfQHXfcrASxsNbes/tnx/wET89e5Xg3T9ZImhGeBCDgVgjceGPgmoh1zl5j0Rx2cfQfWJEK3HtnAlpP+qLHjv1Ks2d+oVzK1albXO0cS/pexL/FyZM+pUXvfK0qwPuleYuH41+ZlLxiEcDW/pGvvc6uDX+m9u3bUokHH7ys7rV8xcq0fbvfkOHtKZOozBOPB+0/lAejR4/hb7LbqXOnDsqNQVDmyzRDFAJJ8+BEIZA0OEsrVw4Cl+q75qOPV9MzzVoooO+9twDv8l8aFHRRCDih2c1u02rWqkOnTvl3DiMXSvn8+fNR3rx5FDN2Un3//Q/sQtm/4xaJuXLmpEmTxlPuXLkUj9c//JYYNnwEjRo91pEN10OFChVUgvvrrruWDh46TN99932AQqJSpYrKNSB2PgYjWyEAnvvuK85eJObyb87gnibsukQhYKMh54LA1YmAKAQugeceiUIAboKaNZlGEFaB0qVPSZ27POEpRPyDA0hOnLCeVq6I0/JWqHgvtW5b0vNusRmgD7vz2br1sMmHq6EGDR+gfPlvN2n65O+//6G1a36kWSxo+pnjC2hq064Ula9QQF86jl4KASgSXh1eneD+JxKKViFQr/59vEPC22c2FBr7952iObM3O9y6wA1SKw9XRJH0T3iuXgQgeG3bag4rmv5WIMCNVr0G91OFigXILXTGfPvi833Kt7tWHsBquxPP58efyHf1gpgEd24rBIKtD1AWHufnuWPHURamf05Yu0B4pv0GVKSChTInQU+lCSAgCgEZB1cDAtEoBK4GPEQhkDRPWRQCSYOztCIIJDYCohDwRjiSHQKVq1anr7/+RlWQIkUKduHcneB6BzIKmyDcf3vqNBry8qscl+tPlZUvX15a+cHyoML31994k0aMfN1UkzMnG2h26Uzlyz/tuYtxw6cbaeTI12jzl1tMmUoVK9DYMaPMtfvErRBA/vM9e3A8pVZuVs9rUQh4wiKJgsBVhYAoBC6Bxx2JQmDWjM+V8BrdTcMuLMZPbEhwZRGKFi74iqZO2ahYEFcA7iLSsyLBTStXfEuj3lhjkiHUh/LA/TI0DP+dQKjet/dStSMBSRB8vjW+PmW4NZWbVQnVbJdBmiEju0oZPbZugNBU59vHWCoEdCpYMnwAAEAASURBVL0Qzo5/6xN6b5nf/zDe/8AWOy+EBIFIEXix9xL6+iu/D8cbboQ1eaWwLmagTINLlx94xw0IOwUmTG6k5nek7QpfdAhEohCwazx//iL167OULYOOq2Ssn29Pb3pZud2x7+dyOxeFwOX2xKS/8UFAFAJO1EQh4MQjsa5EIZBYyEq9gkDSIiAKAW+8wykENm7axG6VG5jCsKx/4IH7zbXXyVdff01VqtYwWRDWQ2jvJuwqeLpCJfrrL78hJ+IXTJs6mWOU3exmdVzDNWCnLl1pyZJlJn3yxPH05JNlzbV94qUQgMuhZUsXUYF77rFZPc9FIeAJiyQKAlcVAqIQuAQedyQKAQTk3fqN34K/3FP3UPuOpcP2/M8//6amjacSXAmBnn/hKXrk0dyOcr+cuUDPPTuT/dr5XQw9+thdyn2JgynEBepu1XIW/fqr34oWsQReZJ/obvLaIaB5yj55N3XsHHyLvOZLDIUA6oZVd+vnZtMJdocEqlvvPmrY2HtngWKQf4KAhQBcecHdlqY+fSvQgyVy6MuQRyjVWjwz3biwqs5uUZqJW5SQmCUkM1qFANo6fPgMdWg71zyjvv0rENywCSU+AqIQSHyMpYXkR0AUAs5nIAoBJx6JdSUKgcRCVuoVBJIWAVEIeOMdTiHw5qjR7NJnpCoM6/1P1nzsXZErtVGTZ2jt2k9UauPGDemlQQNdHET2zoOsWbPSh+zb/6abbgrg80r4999/qWGjJrR+w6cqOyMHGF639mPP8l4KARRCkPgPli/l3c3B3Q2BTxQCQEFIELi6ERCFwCXw/CNRCDzbbAbBLQnIS7Af7DbgmuTAAb9fPATFzO9yz7N08VaaMH69Kg4L//GTGlC6dIG7CILVj/SPVn1Hr7/mf4nCwn7azGcC6rAVAtdddw0Neqky9eq52Pjq7tO3PAtRc4ZqhhJLIYBG33x9NQfi8btYevSx3KwUeSpoX6BA+Pij7wk+46FEgBun2zKmVnEcoKyJNEDsP//8q+rYzX7ld7NfeQSkRT05cmSgbBw88777s1OKFN6BEU/+fI6Wv+ff1XDbbanZCsHvqgl9W/HBt4Q6Dx08Q9dx+UyZblZ1PfxIrrC7PuybRl3r1u6ibduO8AfDb0qxdAuPjdtuS6WCSKN/oXaRBOvjrh9/olWrdqr+nTv3B+N1M2N3i6ozX75AF1V2n/Q56oZLl927GbtdP9O/jGW2HOkJQUcxzoFfpLR370n6+MPv6OjRX9V9pkp1A2Xk51CMA1cDM+yuCUUv8i6Zr786qFjgamvQS1VCsQfkTeT5t4TnIehO3pkyflJDB8+C+Vvown8Ku9p1i4XdTYNxfIzvBVTu6cDxOJN3G/3z978qv1GTB5W1O+KCYKcQxgzcGBUqnJlatSmpeOx/scQdsU5W8zw6evQXdj12joNo/Y93F2H8p6cyT+YnBMENRR/xMzty2B+8uSzzY1cPdl28//4OFefkzOkLhN0aIzl4uab4KARQti/vEvhqi/8Zh4o1gt0eP/BuggP7T/O6e0rFMEEA9Vy5b+WP89soc5ZbdFfCHo9wYOpV7Pbt0KHTPC7P8Zp6E8eLSU9Q2t6V5zZV/iCv7WtW/6DOMeZLlfb7O9WVY65t/HSPusybL2PAGrtj+xETN+begndS0WJZCcHlv/h8P6+3P9JPJ36jv9hFXBbuN/pepmz456LbxnsNMWl0XBuMHdSRM1cGAiaY63g+brL7BDd2GJugPHkzss/VOHdNuC7xkPc7Azu/MCc3bdzLAVjP0ulT59UOnFt5rbz7nkxUunRez7btviRkntj1JMf5ggULac/evarpOrVr85zKrs6/+WYrLX3vPfZTu5uf7U+83tzBzyEvNWhQn+DTNlLC9vqvv/mGdzf9qP6wzb5Agbv5rwAVLHhvSJ+67jb27t1Hc+bOU0Hxjh49xu/A2yhvnjzK4g4+dkE//riL3l20SJ3ny5ePqlaprM71v61bt9EHK/xK2SKFC1O5ck/qLHX87LPPae0n/h/viC+AwIKIJfQx+11esuw9fvceVlZ8uXLl5Hmam2rVrMnvzcjeRQcPHqSNmz5TOHz//ff027lzdM/djAVb5t3DmBQqWNDTNcD8+Qtp7z7/M5q/4B31oxydrcCuBLJnz2b6j8DBd+fPb66XcX+/3en/VqlSubLyc2wyPU7g9xgBDfft388Buo/yN8F1dEemTKpc7Vq1wt6n11g6d/48LXp3Ma1Zu5a/S4/zO+kGJXyAz+W6dWpzzJXQu1c9uulICqYQgP/ueQsWqPEA3G+77TbKmSMH1a1b24GRozKPi/g+M3dVcJ+5+cvNKv7Dtu3bOT7QXsqcObPCFvPqicdLhxXG6Dr/+OMP9Zw2b/6S1/xDHGfod7oz852Uh8djvbp1oooVgX4t43n+ySfr+D10gNfwvykPz6kihQtRndq1+LsyhWo2MRQCCR1viTlXNdahjgjuDUHf9z/6fYYf4zUpV+6c/vnMc7pokSKUMmVkQr1Q7dh5J0+donnzFtC3335Lh48coWvY93dBXjewlhbCeprbachll1323nJVDmnutcLm0+ewiF63zv+b7+GHH6ZHH3lYZ6mj13w/cvQozZw5i/D+OPHTz+r+ly3xr8d24d9++40++/wLNR+283w4wf7W87BQEnPh3nvvDRno1q4H5xBSYl0EJkd43YKLljvuyKTWxmpVq3J93u5pdT1e4wjrFu4Pz/fosWOM8zXsnmVYVGtHcr5r9L3pI96X02fMUJf79x+g5e9/oM7h/752rTgL9nTp0lHLZ1voYhQshsAXX2ymBQvf4ffSPvqd1x+Mv2LFitJ9xYs73kmmoiAnsVzLgjQRcXI4hUD3Hs/T3HnzVX3BBPtejSEI8Zo1/m+KLLxOY+7ZhHy0rSlcbCDNZx/xDVf2yafNDoMxo94IaAf8tkJgyuSJ1PP5F8z3RPNmz1D/fi/a1Qacx0ohkNA5h/gMs+fMVbEUDh0+rAIr431apBC/t+rU4t3zaQL67pWQkPeyPafuvPNOatTQv3sEYxp927ZtO+3iAM5QsmTPlo0e53d8+aefCuoyyqt/CV3bgvURa9O8+QtU/3799Vf1zXBX7lxUtmwZ9d7y6os7DXV/sXkz4XsGca3+4W8HfHPny5tX7ZzRMTXc5byu8Z26cCF/e/J6gvUWO2Oy8PMsxd/f5cuX5+frLd/yqkvSEh8BUQgkPsZhW4hEITCw/3tKSIPKYmnB3rP7u/QtC1ZBNTio7jPxCKoL4UuLZtONhT0EiRUr3avq1P/cCoFFS1vT2+zO6B12awSCG6Sx4+pT2luCf2gnpkLgXQ5cOYUDWILuYYHyq8Oqq3P3vw9ZkD1l8kaz68KdDwF56cfzUrsOpYMK81EGOzNeeXklQfgVjCDg697zSf4QCxRuQ/DYtdMCVRRxHoaPrKnGx9gxawmCNy+CsLkn7xJBoOhw9MHyHby1cROdO+f3k+jFD0VEh06PU+EiWbyylSscdx+hrBj95hpPfmBXiWM4NHmmBL9sr/XkQSIEwRDsegWGRj788WOO1OUYEjgPRhiTI4d/aAS9XnwQSsO3f7B7xM6aBnUn0d//CdhfGVot6sCzZ3gsjBm1hpVj/h507e4MAN600VQ6edL/TKdD2ebh9svuu72baMgrVQN83lev8pbBbvGy1vTZpn3KdZFdB/zko6xNscIdwtkRwz50xCyx28E5nhviKbRpV5LnkfdY6PfiUiPMhoIRiqVOHebzbqe4MctDipa9385UH1+FwKSJG2jxu9+oekqWyqPmpamUTzAOoNgBRqEIChgE9w1FGNeYIxD0u4Mboxzu6cly99Czzz2i7v/ll/w/ArH7C8pim2x3cE+XL0Bt25eys8l2K4cg742blFDPZu0av5LBwcwXCEz/DAeQR12h6MsvDyglK551MMJ6NHBwZYLbOJugAJv29iY7yfM82E65nTuPcRC2j4xSzKsw7qM+x/ioWr2wV7ZKi+88CVphEmbY1muzZkxjRU9R6tOnLwvV45TwdnewvbzZM02p9wvPh/xhA4FPvwGDlFDFLu8+79Gtqwru6063ryHgeb5Xb9UnWMO5Ce8DCEL79e3Dwvx19FyrNoqlYoXy9NbY0Q52/FDDj2BQQ1ZuvDxksCN/7Fvj6OVXhqq0dm1bU4/u3ahjpy60aPESB5++SJUqlcICdQUj9HnipMnKuhD3EoywzR8/5N1C8oaNmyqBbbByOn3Um687FCDtO3SixUv8ASODCQhQ9sSJE+oeEYQ4GF1zzTVUvXo1GjJ4YED/dBn3WCrMQuWq1WsFBD/U/FBmDB/6ali3C5rf6+hWCDRr1lQ9vylvTzXCEXe5p58qR6+NHBFSWJvQZ2a3efLkSXat2Z4gBAlG+PE8+s03lEA0GA/S8SP+pSGvcPD3M55sCA5ZvVpV/mZ8KayCYctXX1G79p14Z9thz7ogYHmJn/fjpUux4v0ppcgC4+qPViqljmehCBJjNd4SY65G0H3FAgVX9x691NwJVgZWxDOnT1XBQIPxRJoO1yAY69NnzAw6rlFXtapVaNjQVzyfPdYxrOsg91qhEl3/bIvoTh07UNcunRwc7vkOy+YKlaoQFCWasDYf3O83NNBpEEZhjYbyIBg9Va4c38fLlDZt2mAsCod+AwbSnDnz+LvaH5PLi/m+4sXozTdeUwo4r3z3OMK9VqtRywRv12UicRGjeXFMjneN3b597nZdY+fZ5zlyZGfjrtUmyUshMHrMW/Tq0GGGx30yeNAAatK4kTs54DqWa1lA5fFICKcQmDBxEg0aPETVjGC87y70Kwfi0ZSjyPARr9Ebb45SaXhneinQHAWCXHTp1sN8b8FYYNxbYwI4bYXAksXvsIvmX6lJ02aKD3N11szpAYo/u5JYKQTiO+cgwB/80pCQ6yCUsF06d3Iotux70OcJfS/D2AU7O0Bw8bR40ULC7pvefV5k47VjuhnHEe8EuI2CIUgoguuoWKxtXn2cNXuO+p72ah/fD02bNOa4Et3ZeONGLxaVBmVpr94vmvgYbkZ8L3Zo3446dmjnaeSi+aHg7tS5a8jvWxjcjBg+LOS41PXJMWkQEIVA0uAcspVIFAK24CZjxjRKYO3lqz9kQ65MCCIbN3jbCJ0gVPYKIuwq5nmJXQbYbQCCFedLLmGil0IAL4HOHRfQPrbQBsHiHEE7g1FiKgRs5YSXYA19mjn9c5o7Z7OjexBc38jCJQj4bQKOAwZV5h+nKexkdQ6r3UEDlyurVSRAS5o5S1q2Sk/DFmY/G+Ev8rCbAkI+uGKyya0QaPHsIxwIaRF/QP+jrPZv5TgOKbhvP7F1rC04R3/g3969U8Sue9zYuJgKOv0WVtSkuflGOsWCaVtJAOt5CG0hnHOTu48QhA4asFxZIPM3Clv7pFWupuz6UEewANgQjo4d/Ql9wBbgmqBAgkU53GP9+MNP6v51HiyBXxla3VMpAAt6+P0//p+bKF0GFsQQYmL3hiZYrkMpUIqtit2E4NrDh65SycB29rwWYXcUuOsId52YCoE3RtUhKAV1sHLdF1shEEvcMdf79V1mxj7awy6Y225LoyzRocyysc/NVvUDBlViy4LAjxhbIfBCn6cJFt2wmLcJ4ywWCoHZs77gAMNfqKofejgXoT1NsEDv2e1dx7xFnhJ0s5IHyhz7nrCbpzUrTb2UVXgO2I2A3UeacA/YtZWSY0xgJ8Xvv19UWdgpgLUqlgoBH+8OwLsGhLUH94BdAtgtZFOoXWozpn1G8+Z+abMrBR/qOnXyvENhg/k7gNcj7KDQtHjRNzRrhh/rv/76x8xprJPok6YyZfPRc64A8FBkvD5ytSkD3pQpr1dxbeDe7syZ80bxhjzseOjY+QmlZMG1TbZCIJJ5YpdN7nNbqDNj2ts0na07P/zwI9UtCLthaXnmDO/MYStMm2DlNoqFLPgB4SYIGKvXrK0swu28LFmyqG+I48ePOXCHZdWggf09fzhcuHCB3fI1JVhDa8IP14y8LT5NmtTKkh3WnKBKlSoSlACxVAhgFwx+vIJgLZ2V7wGWubACswmKB7TtJuwuqFu/YYAwOF26W+iWtLcooZhdF35Yvj1lIt1yS9wOoWdbtqYNGzaoqi/8/ju/F/3vHCgOruUfXpqGDXvV0YdIFAKwTmzcpJlDsAmLtsxs8XaRf5QeO3bU8axgbTtj2lSOMZVON2uO9liC9SEEKFoIDos93PMh3mEBTDThHtas/lC1p9OiOboVArAumzR5iqoCdUOofeHCeX5/nzC4IROCFyjAvCwJY/HM9D1A+Nn82ecMvtdddx1bcedS/dqxY4djjmB8jeNxBCs9L4K7CghpbcKP9pQpU/K7w/9trPMwjmZMf5tSp06tkxzH9es3qH79zuNJkxde6NM7C+ZRtx49Y6IQiOV4cwuVEjpXNQ7hjkOHj6BRo5zCNjyHLFkyq3FmC8QzZMhA06dNoXt5R1R8Cetb8+YteXfRJlMFBC6ZePfO9fx8YCF78aL/XQ8GWGtPmjA+YEdPYioEJox/i4aPGKl25JhO8olbIYDdTr169zH9TcVjF7sCUqdOQ19u2cK7Tn8zxbHGv7twnueOF2Dc9JnmjoCqGhOM4yO8RttjG+vV1CmT1bw3Dfx34h5HJ3hHHKzf3ZTYCoHEHL9Yh+rW81sw/83rr37n4P19kyX4y549O/9uWmZu3a0QqMDvOAjwQCibg/mxu+Mc73bThGc+csQwqlnDLyzV6fYxlmuZXW9CzsMpBGzhKr4xZ8+aQdhFmFB6vEw5ozTvyUGKYYgQH1q5chW1aNlKFYW7oa1ffxmgvHcrBLCL6QUWYM+YMUuVu/3229mTwwdBYxcklkIgkjmH+dySFYnYtWMT5jbG8/nzTtlKqF0csXgv2+MB79sXX3yBatWupxSVmBvYXYm1COuzbQiCd/J0/tYuzsY3XhTLtc3dx/bt21LzFi3VNxjmaY4c2enUqdMsX/nV0ZVg2OHbszcbDM2cNdvw4x2XP38+9QywM0zHwQADFGcL5s3x/LbHTqUG7OoKuzBtwg7kEz+dcHx3whAJawoU3kLJj8BVpRDAtvMJbNG1Zs1awtYkbDcuzVYyLVs05+20dyXb04hEIWALV9FRBLfs3LWMcu2BBSA+hJgEsCYGIUDx7LnN1YdefOpCQFUIWEGw9odg1CYvhQDy4U6ic8f5Rmjdtl0p4/7GLo/zxFQI2MLFWrWLKSt1u324nnhp0Psm6Yky+ehx/ruHhc74iDh48DRt2XyAreo/MwveU+yuBTsFbMLHYZtWs5V7IKTDxQyeo+2mCcJqWOdvWL9bFc3OAu/RY+vZ1Tis7yGsB0HBg75XYz/0eAYgWK7D9cfE8RuUKxikwbJ/3MQGnpbXsHB+feTHYFOE3Q4NGj3gcIMEFx6wmNZCSygFRr5RS7kB0eVwtMcsLHIhFE2b9iZl2YxdGKlT+/t4lF2jjB61lraxexAQBKVvjq5LuG+bbOE7XI1AqIrnoAlKgW++PsT+/FcaAWbvF8sHuBXBM8CYg/IFhLlUv+H9/CyyKmwgcN2+7ShbBnxj+gQr9THj6vGPsZt1c+qI57Rg3hZ1DvclaC/WlJgKAYyTsywoRSBxuIuBG5dUqa/nHwIX+Vn5hfCxwh2KKfjih09+EITBz7Z8RAm1tVsmYL/yg5009e2NauyCD26bevWOE8AjDWTPWX0fuAe4zcF9QACN2Cb23IrvDgHEiECsCFDlqoWo5XOPqnP8GzN6Lfvp9Cup0Bas8KEQ1EoMCNMRtHw6jxW9kwRz3h67ujLbfRTS8Fyw28XeFQJXOBMnbFDKD9ynDnjspciMZocA+o6YFpgHtXm3QF6uG8oaKIS2bT3C1nirzS4wKM7Ge6whUOhgt5i+T+wUK1vubsIuJ/2M4c5s/Lj19B1b8oPgYm3ilMaeQvloYgjA5VqHdnGxHuBSCIpSKAY1waUUlLor2RWTplasVKjIO5PcZCsE9PgKNU/c5ZPz2hbiwnXNDna7AH+yA3jr+KOPPmK6tm/ffnrl1aH0/gcrTBp84eKHg5teYMuhGaxYAOHb6RW2wi/KP5i0EBk/3qZNn8H1DePn/7fiw8d+rZo11Ln9b8DAwUbAi/RGjRpQR7Y8grBI07p161kZOFgJo/ADF9aQoITuEEDf8f332GOPqh/pqBvCcvwoguufHj17KZctaAs/Ytau+SjgBzjc9rRp1wEs6v0/oF8/5YYoW7asKg1z5oMVK6lf/4EsTDyu0mrVqsk70oaqc/e/aGIIhFMI4EcqhCDaZRR+2PXv+yJB6INvFRCEkXNmz+VdYK+aZ4Vt7+PHjXV3jeyxpLFr0bwZ1axZnfLzVnL8SMaPxblz59NLL79sfsB7PaeAyoMk2AoBfJvj2z1D+vTUj8cvgjdCSAiCJdrYsW/xTg2/sgBpXjtEkB6rZwbFQpmyT9HuPXtQrZpPr48cruaESuB/+FEMa9v3lvu/GfHDetWKuO9Hzbdi5Up+B8YJijBXarDA7X7+wQ0lw65du9gt0ydqTukf5A3q11M7BXQd+giBQ8lSTyhMkOaJFysYYAk8ecrbqr8YK1poEN8dArEeb7YgV4+3hMxVjU+oIyw/H360pJkLsISGG6p8efOZOQP3CX379WcBt19hDsv5DevWxPs3E3Y0wdpcEywvn23RzFjPYz1azuPnZV5PDx06pNiwVsEC2KbEVAhA2Xf69Bm1tsFNGwRkUACfPn3KjHcoih/jcYfxid+iLfgeevXsocYv+on58u23O9VuJT1nsBttQP++9m2o8y5duxuhPdaV7rzTrAm/i7QCDJisYAFpf95BAFdlICg5P/pwZcDOIHsc6fvInSuXercVL1ZMKSygmMbaDwFfpBTNDoGkGr/oe3xjCEBJDYUNrJxf6PW8Wns03t999z31eL6XchWFNrDuYsxnZoWsm2K5lrnrTsh1OIUAvlXuLVhEvRPRDtbdgQP6KcVHNOPC7iPqzJk7rzG2xNqPd0B8CGP0nnsLm7XpYx7rbnmVl0IAgvanylekvXv3qWZhWDF29JueXUgMhUCkcw7fSNj5B8L3SZdOnXh3eGnlxgtrx9csjF7EO6D0tyf4sOuuSpVKODUUq/eyLWyH6y0Q8GnbphXvTnhWGUAgDc8YOzXxLfvLL78gSa1FMITwGjexXNvsPsLAB/eenr+P+vNu2gceuN+8Q/B9j124WumM+fvB8mUBYxH3ge9KEHZiDBo4wPHdjrG0gWNZ4JtXKx0nTniLsOPLJvSjUuVqtJ2NIkBQRHXu1EF9a2OdxncnjEkmTpxs+gSsPlq1gt3h+r+d7frkPIkR4B8uVwUtWbrMlzlrjqB/yE8uYj/qvgpPjTJ/LEDy7Aq7NzE8mr9xgym+iRPW+9i/tY8VC57lgiWuWf29qa9T+3nB2CJK5/gGpq6KT4/ysWWnoxwLq01+1UpjHXkseDV5LITxHTl8xpGvLz5Z+6Ph69dnqU52HNn1iuGZOf0zR16wi+3bDvvQZ40pC6ocrBcu/OlrVH+KyR8xbJUj375Y/XEcpqiT/Ynb2T4W3pl6alQd52OLYEe+vmDBqI+DPRte9NEmux7db4yDYLR5836+x9GmPi9szv76u692jQmGBxjzB7hnlRizHAzX8LKgN4DP3ccG9Sb7WPgfwIcEVhb4WjafYeobP25dAF/fPktMPltsB+TrBBaCGr7ne7yrk83x3YVfmfwa1cb59uz52eTZJ79fuOhr32aO4WUBtJ2tzll5YvJZSRKQH4uEJg3fNm3wDo2wVb7w/CLDv/WbQwH81SqPNfmVK4zxsRIogMdOiBXubDnuaJfdZdnNOM6XLdlqeDG+WSHnyMeF3S/wjHpjddDxqgvHZ33AHLWfwYoPdujqfKdOnfNhPUP7WLt2/XjC5LlPWBBt7qlXz0XubB8rRx1zlN0qBfDoBI7p4ViT0D7vFNDZ5oi+Ig9/7IbIpOsTds9j8sHTo9s7vj//9F6TsMZXqTjG8G/auEdXY47j31pn8lmJws/DZDlOsNZgPdB92x5kLGBOaZ5w86t714WGF8/rl18uONq0L4YMft/wYh32mlfRzhO7/uQ+Z+t7x7dOgYJFfCxU8uzWX3/97WPLf8N/d4FCPnZd4uBldyA+/oGreO7Ke7eP/ag68u2LN98cbeqqXae+naXOOe6AL2v2XIaHLRMDeHQCC+p8RYs/YHjxDdeqdVudbY68Xdrw8A8gk65Pxox9y+SjDtwv/8jR2Y7jgQMHfNlz3mX4V6xY6cjHxZPlypt8dvcRkK8Tvvhis+HLnSc/v+//0FmO49MVKhm+Dz/62JHnvmjXvqPhXbIk8J00dNgIk589Z27f558Hf1e+PXWa4QUubI3obs7nHksDB70UwKMTOFaBoz7+oayzojqyCwdHPbgP/iEZtA72A234Mbb4B2kAb6ye2VdffW3aypPvHh8LbALaQsL58+d9pUqXMbybNjm/RznWhGNss2DXsx4kvvPuIlNPlmw5fSwQCOBlwYrhyZYjt4+FAAE8OoGVXoZX/y768ccfdXZUx1iPt1jP1Uhupm+/AQYPFnoE/Y44ffq0r3DR+wxvqDEZql2MBY07jqyUDcqONfD+Bx8y/O61t0PHziaPXaAFrUdnsBsTw89uTXSyObrnOysu+Pvc+XvOMPOJ/by81nvNy8JlH9ZA3G++u+/1YfzbxMFTTb/Aw4orO9txzpbA5n0E3v4DBjnycWH3CzyVqlTz4fkllJL6XRNpf/HewH3iD++TUMTKA8ML/hIPP+bDO96LsL4VKXa/4V/qISuJ9Vrm1Y/4ptnrPluhe1Yzf/4Cc38aw7z57/GxkNTHSt2g2HhWxonHjh1z1BfsHRGsvDvdnv+YJ24q9XhZ0x67jDPZbNnN3zK5TV6w9YENJAwP5mh8Kdo5h/7Z34IcSypo0/Y7vnCR4ur9ajPH6r1s16PHAhum2E05zlevWeO4B681NdZrm7uPeCex8N/RL33BigvfY6UeN88X3wlustf8115/w51trvF8NCa8a8Kk65PxEyaafMwfNkTSWY7juXPnfayoM7yNmzzjyJeL5EEAGswrnvADVA/iUEfwJQdFqhCAooCD3xpBhhaU6CMEvm1bz/5PQXCAhfLeigV9j7ZgtH/fhClEIDzV/cCR3WToZtQxlEIAQiNbiNml43wfu75xlMdFYigE2ArfIVjzEtRxAGFzb+wTPyyuEMxrLN4as9ZxH+vX7TJ5PVn4FoqgiIDgD39uZY9b2M5uXzwxs+ufNeNz03bTxlPtLHX+/vLtJr9502k+Di4bwGMn7Nt3UglB9b26haHuPm5Yv8suHnDO8QVM+17C99YtZ5l8L0G3XSHGn8bOTsc57k33+fPPAgXNNj/qqVltvOLH/Dpz+ryd7RvQb5mpC8LVxKAmDRNPIQABbjiKBe6Y441YealxX7I4UKDh7gcUb5ofOLvJVgi0Y8VNJBQfhcAEVk7pfkDozy6uTFMQnutxBiF3KOLgyaYeYOEm3hVh8qGgDaYY1uV+ZOWDVkagfwlVCECBGUqIjnaHvRr3TBYuCBzvmB8aD7dSWPdbH9nVlrlfW8mi83GMVCHAgZdNXcDErYi168Q53letLIUr3oVushUCkcwTd/nkvLY/8PGDK9gPYd1HCAPsH/0cZE9nqSOE5xBM4S+cUIWto833VrH7HnTUgwsIv/R3GFvGswIqbj4FMHOCW/iTUIUABKonT57yasqkQRCg+/jWuPEmHScQjmks8MM/HN33QAlT1969+zzZY6UQgAIfmOu+syW4Z3t2IgTRmp/dddhZ6tweS0+ULReQbycAmwcefNjUhx/88SG3QmDCxMkhq8EYsjF0Cwhj+cw4iKu5vxq16oTsFwRleqywFa6D11aeVK5Sndf7i4589wWEEvo58fZ+RzZ+9N9bqKjJHzd+giPffQG82C+84Ue98VEIJMZ4s4VKCZ2r7vsOds0WoOY5saV7MDaVbgvgIRyOD9lKvfoNG4cUuKN+WxDTpVt3R5N2f4IJ/OwC0SgEIEwNR+yaxIwjL2GYXZ7dWBic3eMdihg9vp9t2cou5nmOd5TmZwtq/l3mfG72OMI7MNx7y7MRj8RoFAJJNX7RzYQoBEIpD1E3lDMaa6zNborlWuauO6HXkSgE0Mb06TN9OXLlMfep71cfHyzxiK9z1+4+KOHDKbqhtNPloDROKNnvNo4XElBdMIUAGF9/403TFxh7cIDugPKJoRCIZM517dbD9C2U0B0dhjwLSj2NKxQ1NsXqvewWttesXTeszGfEyNdNv/D946ZYr23uPrqxcLfPu5pM/7yE77zDxOR/unGju7jjGt+8+pvGkcEXDz1S0tSz6sOP3NmOa9STL38BxY+xgnewUPIicFW4DOrGUeTn/RdFPtQGjDp1arM/8FdCsSRKXiQug+yG4TJi3twtIQPSgh8uIBCktUq1wsr1g10HzhG4EQEcQY8/kZe6dCurzuP7jwUxvI3qX1V81Ji6lMMKXhvMZZBuC36227WeY/zTw4ULgj7aFK3LoLzsMiIvu+5wE/9mZl/cv/E23DPsq9i/1Qs8wAtBYe/gYJc2we/955/5t93BBUWoQJQoh0DB8OcPgqsPBILVBLcWrVr63S7ADc1b4+sHBNXUvKGOtjse8CGoKlx9hCIWMFKNquOhBFRsb4yu43Dz0+eFJcrlDjIR2Bfuh8IR/Jd/usG/dd7tasndx+mzOCAuYxyM4Iqoy3+BkvEMJkxyuq2AKyBWqKji8MMO91LREu8GoI7t5qli8Pk/d0FLT1cldr2sJGIXQkdUElxAwRWUpm6dFxqXLe48zZPQY2K6DELMDsTuCEWxwB2BXnt09W91R9yNhYueC7vVHu7E2vKaAMJW0tnzmqugtrqvtsug6uwmq1mLh3VW0GM0LoPgPmcqBz73B/f1VxlJUOBgjWPeVSrv91EMt1hLl7d1sGJdwPoAat22pIql4WDwuLDHZkJdBiHI73jXnHM3iSDwiLcCChbU110m2DViPsydvVllN2z8gHKN5OaN1GUQYhYgdgEIbqMQrDgcvbd0GwdoW6fY4Hpp+Gs1HUVsl0GRzBNH4WS+sN28wM0DAqOFI7g4gTsREPydT5k0IVwRz3y4dWALZZWHLcr79/rXbM1c+vGyxt1KMPdEmlcf2fKUNn3mf75ermiiceMA1wifrIlzi6fbsI+sBKAhL7+qkurXq0uvvjLEzo7qnIXGxDsFVBkELIT/VTfFymXQ5i+3UHUOnAmC//Pvd25XLn3c7dnXbAijgssiDe4Stn2zhbANXZM9loK5q9G8OCJ2AYKzgiIJcqoYXf9sl0Hoy3ffbnNxBF7a297h1mTjBqdP4sASwVNCPTO4PcEYBmG7O1ztoL1oqRn7/NVxPfr26U3PPts8ZBVsjU616vhdR8K11pdfxPmet/PQpx++2xH2ucNNmI7LgYbj4zIoMcab7eolqedqyAfwXyYLvU2w0O7duqggi5GU0zxwscQWrsZFCWI53H//fTrb8wj3FIcP+79Br73uWkdsjsR0GfRcy2epT+9enn3SiXDlAXdyIMRUeIfjA4QKXKnL2UdgUqhIMeNuDG6R4B4pHBUsXMwE4p45fapybaTL2OMI8ReWL/O7tNX58T1equ+a+LoMwrf1d99u93RzojFavWatCVIL//rz58X5GgdPLNcy3WasjuFcBtnt7N69W30DLVm6lGUZ/9hZjnOMb7jM69CurXKL4sjki08+WadiJCEd8Zo+3/SpmyWqa1YaEuLDgPqz27zmzeJkCkjzchmEdBArw6lGzTqEYPOghx8qwe4CZzp+f7EwlngnpsrH+2PXDzvVebT/oplzwLdIsfuMu533ly8NG5OFrddp5GtvqG7BZRBcB2mK1XvZdseDuhGTCC7rQhHc6OTNX8DEM0K8DrjqBCXG2ubu45bNnxkXbl79ZMMMYmWKysqRwxlgHIlwBQSXiiDE/hry0iB1Hs0/uCV9urzfjRNcjn27/RvHGPOqy/6uf+Xllwjfl0LJh8BVoRBgiynlMzYczPD3h4mV1BStQkD3D8Esv2S/9fCb/v13x5UPeZ1nH+GLvU/fCg4/8Mi3AxU/WCKH4rHLRXMO/+AQoGiaMq0JL1Cp9SUv+r9Tw3qT1TUCQy5aGuc3VTNB2AvhIwj+poeNqEHwA60pWoWALhfJEQLovv0qcHDfWwLY69WeZPzvQ2FQ4N47A3jsBATJrVtrokmaM7+F8ZcPWTxwgG9zEHxT165TnH1w3hVSWG4q++8kWmG7Lv9ci5kcmMuvBGnfsbQjGHCdmhNNwM++/SvS/Q9k18WCHhFoFQFXQYWLZKHBQ6oYXruPGTKkoqkzmpo8rxPEQGDXTCoL8QWAm03ww46Ax5owZitWKhhVHI1lLARka19Vxb0F72T/rP6XpK7T62gHzIaCzQ5kigCw7K5LFWvOAmnEb4g1JaZCYN7CluwzMEXILscCdwQcB44gBAp+/c3aIdtEJpSLNauNM0rGobwe3H13JlPOVghgfcN4CEe2QgC8XsGweWeMmiNQFiKorSYExYZCICHEu0xUcfjaXfZ+nEIA6wIUqjr4cKQB3qdM+pTefcfvWz2hCgHEC+na3S/oCnaP9hrsDq4crEywdN6xxD9M/lMIcJySuvUDhSKRKgQGD3yfPtu0VzWFOYi5GI6g5INCBYTA4YuWtuEP2LhStkIgknkSVzL4GQJ9rV69OjiDK6cE/3iD781oKVohLupfsmQZx7zpqJpyCxyjbZ8tI1UR+IE+sG+3KQ6lWM7cecyPbSgqoLAIR7aAOKEKgerVqtIbr48M2SS7ReBYIH4snn6qHK9dcd82IQt6ZCIQsw6eHEz4FyuFAHzDs3W86gUCBb//3lKPHjmTIGxkN1D8TP5WGe++s4DuKx5nDGCPpWFsMFOXDWdCUa8X+pjgdPDF/EzTJqHYPfPs540gfYveDa/Q+v77HzheydOmvh3bvg4aRNEwBTkJ9cwwhiHIwFwGwVdyuzZtlE9j/IaIlNii3whDEKDvwQcfCFn0119/JXb9ZXi2b/3K+AqGT96Bg19SeRDKQrgSjvbu3UclSz9h2OKjEEiM8WYLlZJ6rhowQpywNSix1a3i6Na1M3Xs0D4Ed2DWTg74DSGlpp07thof+TotmmNiKgQmTxxPTz4Z+pvgR47vwTuHTJfvzp+fWrVqSeW4HIKgRkI2Jvg22skKQAQmDkdQkEEZBurB8QYQXFOTPY4Q86Qf+9eOBUWjEEjK8RtfhcA9d99NKz7wCwOD4WMrjb2UdLFcy4L1Ib7p0SgEdBtYayHUX7tuPW3hoNjwxY51301p06ZlofTrDkUUeGyBLYSjmOMJocpVq6s6UYdXXKZQCgGUOXDgIJV7urxRuLkV0ImhEAg35+z3NQwRoMTGMRTZAZYRtPzDlR8Y9li9l+1nh8rDCdt1B/AuxTsVBAMSGJKAEmNts/uYKdPt9MVnG1Vbwf7ZzxdjFt8ONiH2V58X+5kkrPlNmzRWyiN8w0dC7H6SZWgDFKuX0tCrDnyr4hsChO9EfC8KJR8CV4VCQP84jQTmQwf8QoVIeGPFE1+FgLv9n9jqHcF9IRjB0dZwZ2FB92sshLvhhrgF1w4giyCYEELFl9B2sybTTPF3l7R27EqIRCGAwsOHfshB/H5Q9cBi9U3eaQCLYpAtjCpePBv1H+TXRqrM//65BX52ntc56oZld8lSediiypIG/ccMDKtWihMGQHGQkgPkhqNdHDhT01jeBZA1azp9Sd/uOMofp8voj9//Mmn4CIbipgAH24Wguvh92TyD/uoCtrAdSgV3EGfN5z4OGfwBbfx0j0q2rXLdCp3JUxtzgMc07uIB159u2E0vv7RCpWfjwKFj3orT8Np9jGR82fPASyEAAfGwV1eaHQm6M+BF4FBgV/z+7Gytd4vOCjhOZyvi+WxNrOkuFk6HI/tZuoWuI4d/RBw3QlVRs1ZRatrsoXDVRZ2fmAqBxctam6B5wToWC9zt3UgIpougupEQAnAfPOAXvCCwMAIMa7IVApHskEG5aNcH3VZtVgY0DqMMAE77951UwbSx2+X06Qt04fyf/BF+USnaML4xz0BuhQAUhA3q+hWmyMMOCr3u6T54He010T02wR9NUOFaHEi4SdMSXs2YNLxbIHwHhVMI/MIKvu+/P8F4HKdDHHQdgaqBwQXGA0pTnGtqmECFgL1Tp1OXJzjoZ35dddAjgmnXrzPJ5M+Zx4pbXks12QqBSOaJLhfqCCutqtUif88iyCuCvUZLthB38KABHJixUdgq7B9o1157Le3d/YOnhQ8Exwg2iB8l32zdSic4QC+7Q6Gzv56lszhycFNYRYHcCgEIUQsXLW7yYMEeiTWpLaBPqEKgXdvW1LNHd9WHYP/sH57hFAIQFnz9zTfE27hV8E9g8StjoDDh4/nzF0wzia0QQIDoMWPHqfYQoBbCg0gIAj0I9kDuMWePpUis5ewfebFQCERqscYuQyhPPig2/GssgvshiKgXJfSZYcdH46bPOJ4txnq+vHlVUL8SJR6k0qVKBrW6RV8RdFJTjhzZIxIKb9u2XRdxWPRjNwt2tYAife7YyQOrRh0kMD4KgcQYb7YgN9Zz1YAX4uQkB17GXMac/nHXbrWe2Wsb1jdN8VEIsPs2FagbdUDZu2njel1dvI6JqRCIZL6j0wjqPXDQYEf/Eay3SJHC9MD999MjDz+k5gW+bbzItqiOBhMIsSDMAkGANWhgf3WOf9GOI1MwzEk0CoGkHL/xVQiULfMETZk8MeRdI0j6oyVLKx63QiDWa1nIjsQjMz4KAXczCBrLsXho5aoPiV2hmEDs4MP3y7Iliyhv3jymGAJtc1wGc41vqXDCbsPscYK6UCdoxrS3qRS/W2wKpxAAL7sdI44do4qlSJFCGQvoPtsC41jtEAg39rHjATsfNGEXTzg6ePCQUaKnT5+Ovvkq7rc8yib0vYw6bGE7lP1bv96C5LDU8rnW9MGKlYrP3jmWGGub3cdIdgDjnYXA1CAvhQC+6dvyLgHsGrQJvNjR+iAHKn68dCnKnTu3ne04HzpsOI0aPdakRfI87e8Zr+96U5mcJAkCV4VC4ErdIRBqhMAKfNTrq2kHC581devxJJUqHffS2vLlQYJQDRSJBbeux+sIITf7sVdZsDiGRaVNkSoEIDxjf+DKpQ/K265hbOFXJAoBuHapUDHwJXP06K8sxI7TLIey+ocrIwhkE0KvDKuuhNV2HexfX7lsgnshD8MDZbX9yKN3UfmKBRxufXQdtrAdgnC0EQnBrQbca4AqVylELVs9qs5P/sz32XiqOocro3cWt3JYy6oMj38Q1kJoC0qb9kaaOae54bL7GAuFACqGBTXu4cNV35ldFqbB/07uynObEgiWffJuh1IK2RyDg1at3OkuEvF1wUKZacgrVQ2/baEdiYW1KRjFSXIrBNDVhOL+xmur+Zn5cYfSBMqTSAjKJiidQG3alaLy7CpKU2IrBG68MQXvesnMLqIKULHiWXWznsd3Fn7FW0s/NwJ/TyYr0a0QOHXqPHGsCMWBHVRQCGCXVDj64vP9NLC/37rrUlEInDh+ll4ZsoJsRVq4+0ioQoADnNNxbhc04vVa/OMsY7gmVT4UAlAMgN6a0MChTLxSFALz5s6ih0qUUPcY6h9+2HNAObPt2cvCmn2TE1xmaIF/qPqQ51YIHD9+nO57wK80xY/SH777NqxCEvXYwg6vHw7JIaTBD9qOnbsSfkxHSomtEOjWvSfNm79AdafX8z2oTetWEXWN4zLQ8vf930RDBg+iRo0amHLJrRCIRqnAQXxpz16/UY8X1rF8Zl99/TW98sow+uzzzz2tR2EZWqliBYWldh+gQT127DhxoEh9Ga/jwvlzlZAVhbt270Hz5y9U9UTz3LHFH1v9QfFRCCTGeItWkBuN8k7daJB/HHSdWrVpR7aQIgirSY6PQoD9rVPnLt1UHaVLlaLp06aY+uJzcikoBNDvBQvfobGsjITrDi+CoL9GjerskoLdpLLLK5s4aDZxcHmVBGEnhJ6RkG3Zirk2dswoUyzacWQKhjlJjndNmC6pbPsdGW532Mer1xDHi1HlEqoQiPVaFsm9RsMTC4WA3R6Eqy+/MtTsgkOe260gvo/wLaVpw7q1lC1b6N8Qmtd9hLCWg3Cbby7s5sCuDpsiUQiAv/mzz9EqVmqAsJPnvWWLlaIiORQCHAuBsHbFl/Ab6uD+wLUmIe9l9MUWtj/AgnC8ZyOhocNH0KhRYxRrs2ea0oD+fdV5Yqxtdh9joRBAR2FIMYzvYd78+Wb3o7oB61+hQgWpds2aVKdOLTZYu97KIeKgz8RxXRxp0VzgNwp+qwglHwJXhULgSoshEOlwgc/4Tu3n00G2zgTZwnVcQ4ACQYomt0BEp0dytAXNEMi+9kZtR7FIFQIoBFcOLzy/2PzI6j+wkrKYj1YhUI9dUDRgy1MvemnQ+2yZ4//hCBcm6K+X8YrbihRKhmBWLnY7v/9+kS0HUqgkxBzAbgcvgvBs9eofeEfHQdr1408OFyXgh3/H518ox+5QcjqK28J2WMTj2UVCY0atpQ/e36FYbZ//cJMC10gg4LDgnefohhvjdpOoDI9/dryEjLenoclvNzZcdh9jpRDQlcMa+8vN+2nD+j307bdHjQJJ5+NYiIX3L/av4NgVA5dDcIGj6enycQJmneY+2s8Sz9GOIQEsgSnIHS9CJcbg36WgENC3EV/c4aYJ7ppAkfr7B6/tI79LtzIc6yQfkhUlVCHwWMm7CIJoL7qZlVspUzo/eLz4/vzzb3rjtY/V7iWdj3mTOfMtrGRNyb64b1DKvVS8iwWK0gnj1is2t0IAChe4DNLKwdG80yY777gJR7bLrktBIQD3dXD7hvUEhLXk1ltTq7gs2MmUMtX1jAn/MbZL2I0U4jSAEqoQQPyZ/RxzAhSpv3+MZdsl1dvs5u5Wy81dYigEYH26YuUq1c9I/j326CO8uyz6H5K2EBdCEghLwpH9oxC8e3Z9zwpV/zuMgwoTvqNgqa8pZcqbKGfOnJQpUyblmuXmNGn4mIbd4KWhfv0HKja3QgA/OuAySG+//3DlB4St3+EIfmPhPxZ0KSgExk+YqIQC8M8LgvVftmzZKGuWzMoCCxjcfPPNBEy0KxfweQmpkR4rl0HYso2t26BI/H8rRv5n+3J9beRwqsmCO032WIrEYjjWOwTgkgWC10jI9inu9kkc62em+wNBMn70r2MFEQfAZqXwRZ2ljhgbb/EcLFfuSZN++vQZ5TNdJ8B3biTflefOnTPxHZ5t0ZznXw5VxYt9+9PUaf5v+WieO5QSEOiB4qMQSIzxFq0gNxYKgfUbPqU2bdsb61M8izvvuINy5MhOt6RLp+axXtsmTX7buKCNj0LA7i+EcitXLAf88aZLRSGgbwACucWLl6qYL3A1o9d6nQ8XF3NnzzJjF+mwrIWFLSgaf/+2T/HatWvSiGFDVR34F+04MgXDnIhCwBmDJ9ZrWRj4o86OtUJAd6BLtx60YIFfCYudaNiRZtMDJR4mDr6qktxKdpsv3DnWpvoNGik2yAO2ffNVwG6ySBUC2KFZ5smnCN+hoNatnqMXevVURg2xjiEQbocADBBgiKCpYYP6+jTk8fz58/xbKqXieXmIc1eSXTA+72WUt4XtsIhf83Fk3+u2q8S2bVrR8z17qO4kxtpm9zFWCgGNHRRQH3+8WhmIfME7IY8cPaqzzBFxKLCryHYJZ+/WAmMkz9P+nsmZI0fYOEqmA3KSOAjwy/qKJ/4oMZGvdYRyryP4koPOnfvDV+GpUeaPBfkx6wYLLE29bMkdUG9bTtNtL1ywJSA/0oS2rePqmTdnc0Ax9g9v2mHBV0C+O2HyxA2Gn33u+9ilhu+TtT+atH59lrqLqOsxo9YYnpnTP/PkQSK7sPBVrjDG8H780feevByA2FelYhzfsWO/evLFIpGFi75tWw/7Joxb56tdY4LpG/rJOwocTeBaP7dK5Uf7Ih0z3bosNOUWL/rG1Om/z7Emz92eYXSdsJDXlOnaeYEj1+6jO8/B+N+FPQ84BoMXS9A0jqfhw1jv2e0d0x/gM6DfMkeZObO/MPkjhq1y5MXngneQ+Co+HTd39+75OT7VhCzDluOmz2gvHPWwMNj6zaEA9mqV457zX38lbK2JFHesCXq89u2zJKBPwRLq1Z5oyn215YCDDfXoOt15DkbrItL1wSoS8nTZkq2mD+grKy197IohaBndX44lEMDTqMEUUxe7cwvI90ro33eZKcO7ngJYVnwQt/6PfnNNQD4HlTflp769MSDfnbBp4x7Dz0pVRzZumy3uTT679/L9xPMyGPGOCsM7Z9YXnmyTrPcAzoNRnxcWm7pwT5EQB602ZfBc3GtoLOdJJP2JJU/Dxk3NN8/QYSMiqnrduvWmTP57CjrKsJDZ5BUsXNS3dNl7PhaGO3jsC/19lTV7LjtZnfOOTVPX/AULA/K9Epo0bWbK8I/IAJZZs+eY/Od79Q7IHzP2LZPPbk4C8t0JK1asNPzPtmzlyGbXSiaP3VH6eJu079y58w4e+6Jm7bqGn90O2Fnm/OkKlQzPhx99bNK9Ttq172h4lyxxfge9OWqMycMYiJTwTPUz4y3ujmL2WHLnORj/u2BlkKlryttTvVjCpg0aPMTUwVaNYfnBcOLECVMG98LCGFMuMZ6Zqdw6Yfc7vo2bNvlYKeK7u0Ah05/sOXP72A2N4cQ7InvOu0z+gQPOd5thjPCEfdqbuho0ahJRKXaDYcoArx9/jP73T2KMt1jO1UiAwLPggLYGC8yvw0eOBC3KMQQML3CPlthtnCmfI1ceH+/MirYKB3+Hjp1NfWx168jzuhg2fKTh591eASzRzveACqwEjDF2Q+Fr276DjwPNm3YLF73Pd+HCBcPJwalNHsczCfluMYX4hINim3LudT3acWTXG+o8Kd81ofrhzsN7Q6/heJ+EIt5NYHifadYiFKvKYxdrhv+xUo87+GO9ljkqj8HFk+XKm76zu64Y1OivYs+evaZe4M7CdkfdrKQ1+Y2bPOPIi+aCla6mnnoNGnkWLfV4WcOD9SUU2eME32ccg8P3008/mfK8syFU8ZB50cw5FjabNlkxHbLehGZG+l5GO3hP63mENYt3e0TUfNVqNUy5iZMmmzKJsbbZfaxStYZpK9gJx8QwfeM4RMHYPNMPHT7smzlrtq9GrTqmDuDDO4wc/G+8Ocrks5LakScXlwcC0N5fFbRk6TIzWPVkt4/ITy6CUE0LiiD8dcuTtm8/4ps183P1x1btUXVzy5cHTN0QOLnJFsqwyxjfH39E/3G6efN+0wbu49Ah54sRbUarEIBwxlYyDB64PKYKAfRp1BurTb+bNHqbF37ve+ddFIaPAx+jaKLTL79c8NmC4OlTNznatIXtwHz37p8c+cEuatcYb+6FYwk42Fo0i7tP9j3uyAt2MdpSwLz68goHm93HxFYI2A1zjABzj1Dm2GOa/f2bvNYtZ9nF4n3eueN8U+frI0MLc7wa+YGVO3VZmAwlSANWfl244PwAscdfJAoHe9wktkLAvp9QuK9ZHYc7+hcJnTl93uDqta5cCgoBWyAPYXkognBcr/NeCoE3X//Y5A8asDxUVSrv1Klzvjo14xSHya0Q+PHHE6b/HdrN5R/1rCEIQa+N/MjwJ1QhYGM3fOiqEK3GZa37JE7BDKWzm64UhcAzzZ9135rn9YSJk803EgdndfDYAnkIy0MRhGn628pLIcBbi01+JMJeCHrZ/6kpk9wKAXabZPoC4Xc4Yv+/hj+xFQIQCGrs73ugRLiuqXzeGWLKoCy7/HCUi1ZAGGuFwEOPlHT0J9iFrdDKdVc+h6A1MZ5u0Oq7AAAs+UlEQVRZsH7o9JMnT/nwDPTzeHXYcJ2ljg8/WtLkLXsv/HrvKOy6YHctpq7i90f23CEI0n3DMT4KgcQYb9EIlQBDKOWdCybPS97VYXBgF0o+tpD05NOJXbp1N/zxUQhgvkGRqLGHsiohxG6bTF2TJgf+xnPXbSsQElshYLf9xeYvHffNO2pM9rFjx8w9ABf2WW/yQp2wizBTbsZM5/d8tOMoVDt2nigEnAoBYBPLtczGOhbnDz70qBkj7vcvvlVGvva6+otk7tj94V2TjvG8d+8+O1sphvUch2D52507HfmRXGCtYHdBpv/uMa7riEYhgDIwmtB9e7DEI+qdr6+TSiFw5MhR0we0jfdlUlC497ItbEe/tu/YEVG3YESjMfxgRZwsJDHWNruPia0QsG8exi/6HmHQYCt1eZekyeMdK3YxOb9MELhqFAJ4HtgB0JU/nnhrlBq4OOI6MXYG7Nt30vcMC9jx177NnAAhvz0+vmErXi0o8hKWsQ9tkw8LTFiSR0qwNtd1d+8aaI0H4b1tKc+ufyKtWvFBcP9s8xmmDQhHvShahQDqAIbYTaD7bx8TukMA9UOgxm4hTP1eOxvAN97CcOKE9UhKElr07tembxyfwdGmLWwHLgsjsIq1BXYQlHNQT0edE8evN+3BujccsfsHX+vnZpkyHAzaUcTuY1IqBDA/GtSNs1TGrgtN2GmCHRXADEJZ7EpIKGGnhR6bqDNS5YxuF89Wl3+h5yKdbI6DBrxn8j//bJ9J9zo5e/Z3x46FpFQIhMId/bLXmSOHz3h135GG8aRxaclrjJuSWyHw11//+GpUHWf66FbkuPv7/vLthtdLIcBuw0w+7jvUnIaSq2P7eQ7+5FYI2AqhcOsklN6N6sftiIhEIYB1OBhxsGODRfOm0wKs/b3K2QphnLvpSlEIwBqTA9y6by/g2hb6c5BSkw8L1jz57jEf+7+dC71LCT9a9Y8GL4UABEE6H0d27WDacp/gB4dtPQ/+5FYIwEpP958DDLq77LiGcF3z4ugWSGhm+x7DKVxC7RA4c+YMW57HWeLu3btPNxH0yO49TB/d1p8olNwKAQhPYaEajjBmNdYYyzYlxjOz6w92bivZsFPEJltxMmDQYDsr6nMIjjDX9P3v2r07bB3YOaT5cYyPQiAxxlu0gtyEKgRsIUe45wBraP37EZjFRyGABwMhjsYe9xuO8Gx69e6jBHlQbtkEa1Rd18BBL9lZnue2xXRSKgTQGSindV+x08Kmp56uaPIgdA9H2AGkdx1gjYDgzaZox5FdNtT55aAQwDMORbHcIYB2YrmWheq3znu8zJM+CLLxF2qtw7eLHiMYd25F0+nTpx1C/W3bt+smwh5XrlxlxivWXnYV5ygDxaKtjKhes7YjP5ILWFrr+ZI3/z1BhebRKgTY7Y6Pg0SbunUbOCaVQgD3b69F4b6lIsErUp5Q72Vb2A48Qn2f6vZspTIE5e7v7VivbXYfk1IhgJ0WhYsUN+MGuyE1YYeMnmuYD9iVIHR5IXBVKQSS8tFAWGQLm3d+ezRo82+N/cQIM/q8EOhOA8J0223N++9F9tKCwNd2Q/H25E89+4B0LXiDsJSDf3ryuRNhUQ+XLHbZ3bu8LdXjoxBAe7ZQXLeDYywUAqgflve63prVxqudDEi3iX3UG54qFcf6oMAJRfv2nvR1YmEd/jjgp4MVbi/g3gJ/bgt9ByNf2ILmAf2c9djCdvQf/YKleTA6d+5Pn70D4MXegePsu++OmftEnbCmD0W2oqRa5bcCLNvtPiZUIQDLeI3b0FdWhlSKYe7ZrmbcY7J3rzj3IsABio1QhPmpn+cXn+8LYEV7tmIEAkns+omEPly504E5XM64CbuD9BiFVXUospU6KJNQhUAscQfW+j6w+8feueG+p+Psmsu2fnfvkAF/cisEINS2FZaHQyg5sFZiDuj791II4J6wrtk8S1jZBMWlJggkMM85foLiw5ql+ZNbIWC7hcIcDUXY6ab7jWMwhYC9g23I4ECXSLoNKKbt3U8c10FneR6x9tquvqCMcdOVohDAj5pwlvjTps0wH/ngt7edY8zlzJ3X5GOrfDCC1Zwt7PJSCKBso8bPmPrAA+s87ATQBHdE7CfVh6326E++/AUM/6WkEMBW6lAE1zHov/4LphCw3QqxL/hQVfpCKQRQEC5jdHvY6WFbcbkrPnjwoGP3hduKHfzJrRDAvYS7jw2fbjQ/RsE/Z+48x63aCoGEPjMIXVEf/mxLQEeD/13Ywlq3aw5YTOvnBNcxuIdQtHPndz6ONaH+vHb9VKte09T3RNlybPAR3I0VfsjrH++6D/FRCKC/sR5v0QpyE6oQsN0ewbVNKLKFgMAtvgoBrHcadwiQvtwS3M0dhDDs99vwu8fvpk2fmbxHHisVcofDqlUfGl60n1CFANxpwHUE5gLGQTjFXbMWLU37EyZMckA9ekycWzes97t2BX4L6wIQvlasXNXUhbHvpmjHkbt8sOtLVSGAOa3HFFzAhaJYKwRivZaF6jvy7PUc8zcYsZ96gwnGlFtoj3K2ULp12/bBqnKk4/vEVm5VqlLNka8v1qxZa9rHs+n5/AsRu8OyXbCg7OQpb+tqA47RKgRQAb6vbOMBPXaSUiHw5pujDT5wG3T8eHAZBvo8f/4C8w7k+CFIMhSr97ItbAcmeDcDq2DEQaZ9WHc1fl4u+2K9ttl9TKhCADtX9PcM3n943wQjKNhs95JuBVq9+g0dOIRzScxxB8zzxJrkRXDHGepd4FVG0uKHwP+hWOJEJ5BaWQDGwWIPKSBy5MxAL71clQPu3eAABkFZWQnAEb7/VemdOj/BQV/iotNr5gnj19NSDsIIQsCrSpULUqMmD5jAtZpPHxHQlYUyhKC1oGs5GM2UqY1V4FPNo48XL/5D7drMoaNHflFJCARZq05xFfwTASC9aM+en2n82HW0c6c/aA54atQqSs80e8iLnYN1/U7slkHlXXfdNbRoqT+AlCezlYjR2afXYg7WdthKJSpePBv1H1TJkYaLsaPX0vvL/UFzQwUV1gUvXLioAisjeDDIHXhZ87ELD2LrbHV5000p6OWh1ShXrlt1tjnu2vUTDeWgmhxrQKU90/whqlGzqMlfuWInsTWqur7hhuto5Ou1KGu2dCZfn/z0029qXOhn0uLZRxzBbO2AvbpMhltTqfrSpfMH3NHpCFj68ksriK1oVRKe7/DXalHevBk1izmy0I1YWKauU6S4loYOr04Iuuym1R//QCOHxwVRatK0BI+ZYg42u48JDSrMMilqzgGwf2ZcQGXK5qdOXZ5wtIcLjBe2rKZpUzepvLQcHHbKtKYcHPMaw4vgzSycJdQJQl0dOj1O//sfA2MR5sXsmZ/TwgVfqVTM3akzUNe1Fpf/FPOA4xeo9pGC4KQdOj5ORYpmCeBFAitoaBzPH7aCN/lFimalQS9VNtf6BOMO4w907bX/Y54qdG/BO3W2ObKbJw5e+IlZS5Ax5JWqVJCDK9sUTbDUWOK+Z/fP1KXTAsJ4BJUqnYe6dCsbgDuCOPfs9i7t3esPfHXLLTfR2PH1OZCWc+1MaFDhSNYHGzevc94RpYKBI+/hR3KrAODu4JAIsDuw/3L6zlorwbPs/biAWrpuzPtunReaYLs6HQGGb8+UhnZsP6rGDtKzcVqdusXVOo/r5A4q/OXmA8QulNAVNUewRnqtMVg72MWPY5wGCyq8hgOujxjmX2cQrHnCxIae7zC0iaDVCF6tqU27UlS+QmDQ8IMHThPHUiGs/aBg8y6aeaLbvFSOdiBY3afu3bpQh/bt9KU5so9THkf1OaD9Xyrt8dKleP2cYvJxwsIXFTAV5xXKP00IVIyAwTaxv2h+/7egL7f410vkuYMKa37eqk/8Q8YE59TpCDCMIMosOCe2MFLJefPmoQ7t2lLb9h3VdXIHFX5pyCvEVrqqLzlyZKcli96hW265RV3rf6xEoRf79afp02fqJHUMFlSY3SjR3HnzFU+RIoXp3YXzea0PfM+AoX2HTrR4yVLFO2bUG1S5svM7iLe4U+Uq1Xh+/aN4qlapTK+/NoKuuSbuHYiMcxycr2bNOsQ/CBXfrbfeqgLLpk2bVl3rf/ZYSo6gwrof1apWIQQ8dt8HxlKlSlXp5Cl/UHEE2v1o1QoV6FmXjeUzY2UD9ejZS1WNoHrLliyiPHnu0k2ZI/qFYJAsJFVpffv0DgiaxwJS+vDDj1R+qlSpaMH8OVTgnntMHfpk27bt1KZdezpw4KBK6v3C89TquZY6Wx1ZIMjzuIFJq1KlEge8HxmI1+HD/PuhmsFLF4hPUGGUjfV4izYYLAvpqUXLVuo2nn6qHE0Y/5a+pYiOq9esJd5RonhvuOEGmj93NmEOugmBo9k9D8+rv01WfIIKozAL0gnBTvfs9X+T33777TyO3iUcbcLP8z59+5l1JH36dPT5pk/p+uvjfpexNSqxSzUY96miPbp3o/bt2tjVqPMvOEAk1lAWupm8Th07UNcuncw1TqKd7+yCiBYtXqLqwDzAfLCDTerK2UUVseDJ4OcO+o31qGzZpwjzBoRArYsXLVTB2XUdOGJtRQBPBPcF4R2zcP5cuu++4upa/4t2HOly4Y6XalBhBAdHkHBNUyZNYDzL6EvH8ePVa4gVOSqtbJknVIBQB4Prgi3riS3KVSrW10/WfOziIIrlWhZQuSuBd/XQ0GHDVWqaNGn4d9p0KlSooIMLAX1r161n1syaNaqr94eDiS/s9QN5jz32KP9eHqS+Q9y8uGZ/+4RA3qzANdnjx42l8k8/Za7tEzvoN9KffLIsvdj7BcqePZvNZs7ZMIJ49wzhPaOpaJEitOjdBQHfXDo/0qDCml8fWaGp2tLXOGIN3PWD/5vATo/kPNo5h6CyvNvDBLbPnz8fLZg3J2DOo+2lS5fx78Ueau3E9XtLFzueeazey3bAXrQDuuOOTGpdu+02pywE31it2rRVYwh8+F2H70H3+yPWa5vdx4QGFWblFv92LWmCB9eqVZNlO3HB2XFfILxfxowdR68OHaauM6RPzzKlDY53Ee+UoCrVavBvfP+3J+oa9urLAd8geP+NfO0NFfgdlaVLd4t6r2Hs2cSuFKkHfxsDv0cfeZhm8Tx3/762+eU8YQiIQiBh+IUsDcEjBA9aAHb77WmoxMO5lJAEAsHvvztOHMzWfMgVuPdOGji4kqfAka39iV2L0P59/h89aBiC3wL33kGZs9xCWfjvr7/+5fyT/APkJG3besS0C97WbUtShYr34tSTDh86o4Q5x/9TIIAJApiSJe+iLFnTUcaMaXgh/ouOHztLO3YcpW++PuSo5/En8iqhKhQPXhRfhQDqOvnzOWrbeg4BA02xUgigPihaoHABQSg8+q16/DHgFNKfPnVeKU204gC8EMgVZMEslD0Q5LE1NW3+Yr8RCue/OxMNHlKFF8y4H/bsVoWaNppKEBKCIOQsXCSLEvDmyn2rEnhDELpsyTaCYBSEZ/vG6Lo8LuKwtYXtd+W5jXLkyECrVu5UbT3+RD7KmSuDOj965FeOGP+9EaSjPowDjAcv+uXMBWrXdi7hCAIeDz+Si/Lnz0Rpbr6R2FqZIPjbvs3/0Q4eCP2GjqjBi75TQGT3MaEKAbQDwfzUKXEfYXm4XeBfgP+uZyH9wYOnaeOGPUZ5BMVHx07eCjYoDBbM24JqFUHJg7lUsGBm+t81/0eYD5v5PrUCAjj07FVOCX11GfdxxQffKoWUVjQgH9gUuy8bf1DcrJRy+/efUnOYdwyRPZbuuz87delahlK7FIaoA+Oge5d3CGVBeCFCmI7xgvGDvnKcEbWe5Mt3O/3NAnfeFaF4E6oQQCWxxH32zC9o9qwvVN/wLyOviaUfz0uZMt2sBFgHWFi7mtdErI8g3GvvF8vTgyVyqGv736WgEOCYIvQqKwA13cxzpBgrK4sWy8ICzT+UEgBKX6x/lasUoqVLtipW3JeXQgCZWEsgWIfgOhhh7enbvwIdOuhft8GX3AoBfDBindb9xj3+f3t3AmVFdedx/GYSINIwLog9odkaUZFFHTXQKMhiohB1ZjQGMVE2QRHEHQkuyOYSRWTTcRtF0bigZhJwHaOOuOAuGtRgOyDribgLejQz58z/d9sq69Wr914vr6Hp+t5zoN+r7VV9ql7Vq///3lv7dCl1B9vxX1a2i9P5QNc8/dvFkjw97Pu27JlKv4m5EgLr7Nged9rvw2ukvh8VFZ3crrs1d53svKttDoriIdb6x65964NBrqudg3tWlLvdd2/hz7nWusI9u6zSjrWqpJQS3vOvG+oTeOFM371oLAkBBQ/nzp3vf1T36NHdblwH2/5oY0mnT+wc94p75NHHfJBFm92ipMQ99uhDWTfDS5YstYDkmSGRAlMD+vf3N88fWyD2VUsCKOCjoOyokSOcPUzWT5srIaCRCvwoELdq1Xt+2qT/lAxYeOstbtV7lWHQbnsnBNZbQFU34FaTyq+ybmIOPaS3O3zgQNe0WVNv8eJLL1lCc7Udq718YuOdd9710+ZKCFitU2f9+oYEnTt39sts2bKF31/ab0EplBDQdLrZshp0wSz2G6KdO+7Yf3MdOrT3iR+Z3//Ag2HSRfvpZgukKlgRLzUNEFqrCGe1Gf1ipk+71I0cMTy+yILvZ152hbvxppv9dBMmjHcPPfSw91SySNuhYMpXW7/ywWgFI4N9oWTBojsW+pvH6IcUc59ZKxg7pxxq5/SqCjRKoPTt28f17tXLde/ezd9Yv21Jlttuu91/57Qe2p+PPrwk4+ZZwxX8OWLQL+y7+Kne+qJj/pDeve3cta9bv36DW7lypVMALwj4HnzQgXYNXWSVgXYKZgn/nnPu+X6/BgPiXlajzwdvdUM+7vSxzh4w6az2nZ+8tgkBzVzM462mQaVoQK82CQEFmK0FSnge0nfhnw84wA0c2N+Vd+zoXl+xwr326uvOWk3ZdWR319u+0wpUqNQ2IaB5lThVItZqLeut35+/PO5Y161bVx+U0zGrz4meH2fOmOaGDzvZTx/979zzJjp7jkQ4SMdPn0MPcWVty+wYWm+/D1e6xx5/3Cqk2e+t/v3ChGIxEgKvvf66T+4GH65j7jD7PlTY96Fd+7bu/cr33XI7Hy5erAozdpG2kivotOzZ59yw4SP8b0FNpySZArn6Tug8u3btOlv3P4ZJNk1z6pjR7pKLL9TLjFLT4yhj5jxvGmpCQLY6LwUJH92LDzrySH/O137X9z0o9ZEQKPa5LFjXpL9Kgv38iMFhEFPHyTFHH+WTQkqk63prXRfafcQWP3tpaanTtVfXv6QSP2/qWNM5XUkp/StpUWK/X1f55b6wfHl43dSyjjnmaKfEvH7vJhUFM08fd4azBxqHo3WOUbLmgP33d+3btXU/atLEju21VsHyHbfUrnVB5QzNoATxwttusRhMdgW+YIG1TQgooP3L44c4fYeDom3fVgkBfeZTTz9tFUnGhEFk7T8F1HUOUyDeWqQ6/Z5SsDkop4wa6aZeeknw1v8t1nU5GmxXkmnfLl18ZQ1db6PnZyX6H7DfUBs2bgzXY9iwk9xlM6aH76Mvinlui65jXRMCWsfouVLvDzhgf+9fUdGzKkG0qtI9/Mgj7rnnqypa6lifddXv3JAhx2vyjKKEgbWICIfpu1nRq6df3g/tnGTdaLon//xU6KbfbNctmOcrGoUzffdC1+V33/1rOPhO+23Xr99h4XteFFeAhEBxPbOWdu89rzjrlz9reHyAgsczZv6LD8LHxwXvFUC0Lmh8QCUYVuivfhQMG1Hha/sXmlbLV03kaE3WQvNofK5gTnTeuiQEtJz/fnqVZRofDxdZzISALoqnjbkrbE2hANbU6ceEnxW8UK1/67rHB2CDYbn+du/exk2ZdrTVlGmaNYkCZqr1qlYWhYoCv+Mn9M9qCRIPtl9ptXEvmvxHt9KSNfnKkYO62vIG+EB/rumsuxs3w2o0BwHoXNNpeM9eHd3ESUdkrZ/Gxddx1uzsi4emC4oSPiccXxUEUKD77vtGB6P8XwXaF1vtf+teJAzoZUwQeaPArGqfH3Rw8g9ATXrP3S8765IkTOBEZs94qRYBZ50z0PXrv3fG8KQ3SggpQGzd4SSNzhqmJErV9/NA+0GZNTocoITUxPMesADCF+Gw+IuSkmZu3nUnWO3rJ92KN6qCosVICBTb/YH7ldh5Ibw5jG9H8F4JyQvs2OrZqzwYlPG3ISQEtEJq9aOWSUHiN2Mlv3tT1XpgkLMu2fyQfAkBTaBlKXD9uC3buiKygNFXVgu5uU/+6pygVi1KUkVr5W/vhIDWW4nE6XYNWWXB/1xF3yedr7TuQXIo3zVEtf5V+z9ejhzUzU04a0DGYOs6yF17zRNhoiFjZOxNG0tSXGrnaCUrkkpjSQioVrcCpmPtpjR6oxnfZgX5F92+0BI13wefo9OoBtaFF10cBmui44LXaj3w79cvcNYNkB+ULyGgCXTtVbD37nvusdqyq33tOwXddBN+7LH/6n51vBLNP3TRWrzbOyGg9dYN2ahTxmTVsta4oJSXd7TKBg+6Maed7pMlGp4rIaAaVUdbLfe/WPA3XubPm+NUyz8o1UkIaFq1YrjiyqvCZE8wf/xvSUlzN3/eXKeaoklleycEVLN+wMD+9ht2iPv00+8D5/F1bdq0qd1YzvVBsPg4vS/mPlOQVjU/k/ZX/LO176644jKfbIuP03vV+ldtXd0oFyq97MZaCTLdZCcV1V5XcDiosZ00jYYpGHXLTTf4ZIQCXSp1SQho/mIdb9HgxBnjT3eTLpioxecsdU0IaMEfffSRsy5A3BtvVCXskz5MgTLVXtW5KEi21SUhoM9Q66wxp55mFW1yJ/81nWrcX2O1NnXuSyo6j44ec6pPHCWN1zD95rjpxut9guHqWbP9ZMVICGhB1hWRu+C3kwtuh+5H1YJBrVtyBVAVOFMANWgh5lc0x3/nnH2WO+fsMxOXVdPjKMdHZA1uqAkBraiS+6fa9SZeyss7umeefjIcXB8JAS28mOeycGVzvFBg/te/GWa/Ib5vsZM0qWoyL158j/9NkTRew5QUvOjiKc6648o1SeJwtc6bY63WmlhAP1/R9V0tBhctuivfZFnjdJ5eYNf/pBY30YlrmxDQMtT648jBR1mL2apKgNs6IaB1UFJg3PgzwwSOhiUVnTNU4SSeDAimLcZ1OR5sV6u9ob8+yamFVb5y4tAT3BWXz8yqDR+dp1jntvg6qiVVvmLdGvlWZJpGFRjeWvFaxuQ6Pq+32v+zrRJJoe+T7hPmzL7G9bfEcq4yb/4CZ93RFb7Ht2uqEgtqzZhUrCu4jBbH2k4lQCj1I0BCoH5cM5aqwIf1Qx4GnKMjFQQ86KAO7gKrfZwUPI5Oq9eqYPHnJ96xJuWv+xrR8fHBe9UmV01VdeWiFgTVLQr+Wf/OPgCjmq25imq9qya6ui5K6vImPl9dEwJa3qyrHrcuVqpuXoqZENCytVwtPyiq2a+a+/GibiYes5rgDy19y2piZAZndbFSbX1149HLaqXmK6qhqoC0uudRt0BBjVXNo1qranVw+M+6+MBf0nKSgu3ad2oloCCbAsjRou6Njh9ykOt7WOfo4JyvFdBWMFLdLykgGS9KYKmlQb/+eyX+GNf0SesYX070faGEQDCtup5ZeNsLvkWGPSQ4GOzXo6ztLr5W/vCRvX0LmnBkjhdKfqnWto756D7Q5CUlTa3mWFfrVuFAX6M5xyKyBst+yZI3rUbgyrAlSHwife/32eefrKl7H6fWE9UpOk7ushr2WmfVIg+KjrsBA/d2w0ce4lq1KvG1pIuZEAg+p5juChj/yVrBVNXW/r/gI/xfJTYO/3kXX6NerapylYaSEND6qWs4Jaoq7dhUUDoo2h8nD6vw26P9ZM8O8KP0OlcLgWDe6F/V/tI88RLtTkrf7UmTM5stqxup+XOf8rMN/kV3n1yMLiPa+kNdful6ka+o27GZ0x/2kxxird0uvHhw1uTa/ptveta9ate9zONUrRj2suBXb98yJNpaJF9CQOc1tRr5wx/e8OdKe2aH/8xBg7u5M84ckPX5ukY+/1ylW7rkrYyWTMGEOqbUNdygwd39dzwYHv/bmBICagavGz91nfJfTzwR1sbSNusGcOgJQ3wNwp/8JP+5aNmyZ30w7K2/rAxrZWsZ6upi4nnn2rnyOEtU/YOzhzxqsH/9weqqViB+QIH/dGOu+eNF3aqoSwIV1QRUl0XRsj2CNKp5e8mUqf6GJagtrnVSTbLRo0d5T7W4+NUJJxZMCGg+1Xq88aZbrKbv/fbb4m9hIH+BBeujN0zVTQhomQpwqrVGvNahxqnWqBIuo0YOz2oRovFBaQgJgTFjTvHJgFmzr3V3331vRmJLCaOjLFA6Yfw4py6n8pVi7jPdOM+xljf2HAHfeiF6I73zzju7rvvua77H+drQ+dZJ41STVcfw7Xfc6WuKRqfX92G//Xr4brMUICpUdK1Ql1IKiEZr12k+1bhUQFatLHQ9sb7pfc1XjatrQkDLKMbxVtNAbjESAlp3JU2tH2r3lAX8g25rNNxft+2cM3nSRN/SJtoaoq4JAS1fXZDYc0P8/o8nBlTbvoe1OlHgvtCxrRqySgAuf/FFv091Lg2KWpVcOuUSX/NTwZpiJwT0OWodNnPm5Vab92W3wVp/Ba0BNE7XlW5duzq19lH3J4WKunu5beHt7t77FmclAYOa7woMxrsJii63psdRdN58r7fHtSbf+sTHKVA+Z8589+abb4YtlOLd/NRXQkDrUsxzWXzb4u8rKyutksIUp21OKmqZdYNVUFALk+oUJehmWbJMNdKDbk/i8+l8oGP47LMm5A2KxufTewVydVwnXY+D6XW+V7eNalmnVgpJv/uDaYO/dUkIaBnRY3p7JAS0Dro267fKvffdb63nM2MrSrj87PCB7mxL/um6mq/U9bqcFGzXsaAuHa+dM8+36ot+vlpwjBs31v8ujQ7P9boY57akdcz1eRpeKCEQzKvu/6783dW+VWL0WqRjslN5uW+58Vu7Dsa7Tgrmj/5VC7hbraWokpTR30aapmXLlm7oULvnGHuab3UXnS/6Wi0SJlmiWd2h6bfqlVaxglJ/AiQE6s82Y8nqj1xdyqxb94md+D7zXZy02r3EB53VHU9tigLSCtrbA3vd59YlRVML0qvPdAU81G+4+qivS9m08XO/vh/+7Uu32brtURJgD+sbvXVpS2sC3dqCKc3qsvgdel4FnT75ZKvvUmaL1WzXPpS7no9Q06JA9AYLun9sgWQlb2RcqBQKtisorS50VBtXfY/HnytQaPnBeG3np7adH27+0n1pLUi0HK1fUtc2wTzb8q8STWs/+Ngf6+pGRcdobYoSIApebv5wi9upeRPXxrqwUbcmdSnqHkqBb9Xq13foa/sMfT9btWph38+yWu8TrZP2r1pw7GYBZ3VHlPRcg7qse6F5i+Uuoyr3L/3zEfTshdatW/rXhdahIY5XzX7tF31X2rbd1bWyrmoS4vhFW/VoQF9dEp06tm/Rll2MBek4Wf0/m313Y6qJX9drks5Hn3/2lbM//rtU6GZJXU/p+Pr4oy2+ey0dXzqH1ec+KYZbXZeRL4ir7kJUG1mBqLI2ZRYMbueTAjX5TNVIffev79pvj8/cnp06+YBPoX1Rk+XHp40GdxQImjZ1SnyS7fpeyZY1a9ZYFxntXAcL4uXq/7+6KynfzZs3235plvV8guouIzqdgoUK0m3YsNE1adrE73d1G1XX9Yx+xrZ6LZs1a1a7tevW22+R1q5jhw45a8znW6di7jPd8L5vXRuou449O+/p2paV5fvonOMURFXXG+qGQDfx7dq29ckatX6oTdH6qJuVb//+d7f3Xp3Na4/aLKbG8+zox5uC22+vfNt+X+3mAyGFaujWGChhBh3XmzZt9MmIH7gf+K6DFDipTVFQdsWbb7kSa1mgYLCSf9uybLXuvFatWmW/eb/2XW7En7FS3XUJTHTeUsJG56wy+25ti/1R3XVsyNPpHGIP5bTf1LsXrMVe7O0o9rks3/qpiyB1ffZe5fuWLP7WV1BQdzzq+qQ2RS3R9IyATZs2Weuhj31yXoalpaW+Kz89b6cuJTi/6DyvbuF0/dA1Q118ddlnH5+4rcvyd+R5ZaHv+4aNVd1el1v3gG3atEmsKFJoO2tzXS4UbNf1WV1Y/rhZM98FVW2vqQ393KZjVOfw5js19wm1pC4KC/lrvFqeBL89S6xlo/anWgFXt+g8osoy2/oaVt31a0zTkRBoTHuTbUmNQKGEQGog2FAEGomAEryPWIscFSWlhp7407xbpuD45Ase9M900YRjx/Wzbkd65J2HkekQyJcQ2N4C6it30Z2/96uhPvKTHnQcXUfdEKiWvR40rJKrH+3oPLxGAAEEEEAAAQQQQKC6AoUSAtVdDtMhsKMJkBCohz221LoLueH6Z+phySwyzQJLHzkj3Px8CYGgW5JwYl4ggECDFIh+p9W6YPSoReGDrMef0d93bZO04koG3HnHcqdn1Kiohcjti0ZktNzhPOBp6v0/PeNF3TE1pNKQEwKqGdWnb7/woWKXXzbDnXzSbxL5lAy4+prZbv786/x4NWd/aflzRak1n/iBDEQAAQQQQAABBBBInQAJgdTtcjb4OwESAvVwKJAQqAdUFumiwUMSAhwQCOz4AtHvtLbmT/+5wh78tyzcsB77lTk9r2PvvUutC6JdfPdweqaH+sf/wLomCspJw3pltSggIRDo1O9fEgI19/0P61t06rQZ4Yy9KyrcwQcf6NTMv9OenXx3OeqCRX1rBw891cQTzz+3YIuCcKG8QAABBBBAAAEEEECgGgIkBKqBxCSNUoCEQD3sVhIC9YDKIkkIcAwg0MgE4gkBPTB34a3P+wcuq3Z0dcrR9mD3sacfljUpCYEsknoZQEKg5qzffvutfwCmHiIXffhlviWNGD7MzZg+Nd8kjEMAAQQQQAABBBBAoMYCJARqTMYMjUSAhEAj2ZFsRroE8rUQSJcEW4tA4xN4e+Umt2DeU/7B4Elbp4fiqtXAycMr/IPpk6ZhWHoFGnKXQdG98vLLr7hJky/yDwSMDg9e60HFejDgxPPPc337HBoM5i8CCCCAAAIIIIAAAkUTICFQNEoWtIMJkBDYwXYYq4uABL755n/dxg2feYxmzX7k2pTtAgwCCDQyga1bv3Hr1n7q1q37xJ4tsMW1aNHM7bpbc9etWxu3W6uSRra1bE6xBPTg3i1bt/rFtW/f3rUoadjHyhdffOHeq6x0lZXvuw0bNrqdd/5Ht0fr1q5nz5+60tLSYrGwHAQQQAABBBBAAAEEsgS+/vprt3rNGj98px/v5MrLO/rX/IdAYxcgIdDY9zDbhwACCCCAAAIIIIAAAggggAACCCCAAAIIIICACZAQ4DBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCAFAiQEUrCT2UQEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBEgIcAwggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJACARICKdjJbCICCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAiQEOAYQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEiBAAmBFOxkNhEBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAARICHAMIIIAAAggggAACCCCAAAIIIIAAAggggAACCKRAgIRACnYym4gAAggggAACCCCAAAIIIIAAAggggAACCCCAAAkBjgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFIgQEIgBTuZTUQAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAgIQAxwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAikQICGQgp3MJiKAAAIIIIAAAggggAACCCCAAAIIIIAAAgggQEKAYwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRQIkBBIwU5mExFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQICHAMYAAAggggAACCCCAAAIIIIAAAggggAACCCCAQAoESAikYCeziQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIkBDgGEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIAUCJARSsJPZRAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEESAhwDCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkAIBEgIp2MlsIgIIIIAAAggggAACCCCAAAIIIIAAAggggAACJAQ4BhBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQSIEACYEU7GQ2EQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABEgIcAwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIpECAhEAKdjKbiAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAACQGOAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEUiBAQiAFO5lNRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECAhADHAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACKRAgIZCCncwmIoAAAggggAACCCCAAAIIIIAAAggggAACCCBAQoBjAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBFAiQEEjBTmYTEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAgIcAxgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBACgRICKRgJ7OJCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgiQEOAYQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgBQIkBFKwk9lEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRICHAMIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQAgESAinYyWwiAggggAACCCCAAAIIIIAAAggggAACCCCAAAIkBDgGEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIgQAJgRTsZDYRAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAESAhwDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikQICEQAp2MpuIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAJAY4BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRSIEBCIAU7mU1EAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQICEAMcAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIpECAhkIKdzCYigAACCCCAAAIIIIAAAggggAACCCCAAAIIIPD/joemQpJ+RBMAAAAASUVORK5CYII=)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Endpoint events has not so much data as for example enpoint stargazers for dlt repo. If you run the pipeline for endpoint stargazers, there is a high chance that you face the **rate limit error**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "\n",
    "\n",
    "client = RESTClient(\n",
    "    base_url=\"https://api.github.com\",\n",
    ")\n",
    "\n",
    "for page in client.paginate(\"repos/dlt-hub/dlt/stargazers\"):\n",
    "    print(page)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 1: Pagination with RESTClient**\n",
    "Explore the cells above and answer the question below.\n",
    "#### Question\n",
    "What type of pagination we use for GitHub API?\n",
    "\n",
    "#### Answer\n",
    "HeaderLinkPaginator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Authentication**\n",
    "\n",
    "To avoid this error you can use [GitHub API Authentication](https://docs.github.com/en/rest/authentication/authenticating-to-the-rest-api?apiVersion=2022-11-28):\n",
    "\n",
    "1. Login to your GitHub account.\n",
    "2. Generate [API token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token) (classic one!).\n",
    "2.  Use it as an access token for GitHub API."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**! ATTENTION !**\n",
    "\n",
    "Never share your credentials in public and never hard-code them in your code. Use **environment variables** or **dlt secrets.toml**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create an environment variable for your access token.\n",
    "\n",
    "![1_5wEevNCOf80GTHwptPTB4g.webp](data:image/webp;base64,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)\n",
    "\n",
    "If you have your token [ready in Colab](https://medium.com/@parthdasawant/how-to-use-secrets-in-google-colab-450c38e3ec75), you can directly use it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "# from google.colab import userdata\n",
    "\n",
    "# access_token = userdata.get('SECRET_KEY')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### I'll be using .env instead\n",
    "\n",
    "`python-dotenv` library should be added"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "access_token = os.getenv(\"SECRET_KEY\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So now you can use `access_token` variable in the code below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "from dlt.sources.helpers.rest_client.auth import BearerTokenAuth\n",
    "\n",
    "\n",
    "client = RESTClient(\n",
    "    base_url=\"https://api.github.com\",\n",
    "    auth=BearerTokenAuth(token=access_token) # <--- put your token here\n",
    ")\n",
    "\n",
    "for page in client.paginate(\"repos/dlt-hub/dlt/stargazers\"):\n",
    "    print(page)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So now we can rewrite our GitHub dlt pipeline using RestAPI Client and access_token."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dlt\n",
    "from dlt.sources.helpers import requests\n",
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "from dlt.sources.helpers.rest_client.auth import BearerTokenAuth\n",
    "\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "access_token = os.getenv(\"SECRET_KEY\")\n",
    "\n",
    "# define new resource - github_stargazers\n",
    "@dlt.resource\n",
    "def github_stargazers():\n",
    "    client = RESTClient(\n",
    "        base_url=\"https://api.github.com\",\n",
    "        auth=BearerTokenAuth(token=access_token)\n",
    "    )\n",
    "    for page in client.paginate(\"repos/dlt-hub/dlt/stargazers\"):\n",
    "        yield page\n",
    "\n",
    "# deifne new dlt pipeline\n",
    "pipeline = dlt.pipeline(destination=\"duckdb\", progress=\"log\")\n",
    "\n",
    "# run the pipeline with the new resource\n",
    "load_info = pipeline.run(github_stargazers)\n",
    "print(load_info)\n",
    "\n",
    "# explore loaded data\n",
    "pipeline.dataset(dataset_type=\"default\").github_stargazers.df()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that all dlt [stargazers](https://github.com/dlt-hub/dlt/stargazers) were loaded into DuckDB destination."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **dlt configuration and secrets**\n",
    "\n",
    "In dlt, [configurations and secrets](https://dlthub.com/docs/general-usage/credentials/) are essential for setting up data pipelines.\n",
    "\n",
    "**Configurations** are **non-sensitive** settings that define the behavior of a data pipeline, including file paths, database hosts, timeouts, API URLs, and performance settings.\n",
    "\n",
    "On the other hand, **secrets** are **sensitive** data like passwords, API keys, and private keys, which should never be hard-coded to avoid security risks.\n",
    "\n",
    "These can be set up in various ways:\n",
    "\n",
    "* Environment variables\n",
    "* In code using `dlt.secrets` and `dlt.config`\n",
    "* Configuration files (`secrets.toml` and `config.toml`)\n",
    "\n",
    "We're gonna use `dlt.secrets.value` to define credentials in resources and sources. dlt automatically **extracts** configuration settings and secrets based on flexible naming conventions. It then **injects** these values where needed in code.\n",
    "\n",
    "**Note**: It's important to note that while you can put all configurations and credentials in the `dlt.secrets` (or `secrets.toml`) if it's more convenient, credentials cannot be placed in `dlt.config` (or `config.toml`) because dlt doesn't look for them there.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's create dlt pipeline for both endpoints `repos/dlt-hub/dlt/stargazers` and `orgs/dlt-hub/events`, we use `@dlt.source` to combine all resources in one place."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dlt\n",
    "from dlt.sources.helpers import requests\n",
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "from dlt.sources.helpers.rest_client.auth import BearerTokenAuth\n",
    "\n",
    "\n",
    "@dlt.source\n",
    "def github_source():\n",
    "    client = RESTClient(\n",
    "            base_url=\"https://api.github.com\",\n",
    "            auth=BearerTokenAuth(token=access_token)\n",
    "    )\n",
    "\n",
    "    @dlt.resource\n",
    "    def github_events():\n",
    "        for page in client.paginate(\"orgs/dlt-hub/events\"):\n",
    "            yield page\n",
    "\n",
    "\n",
    "    @dlt.resource\n",
    "    def github_stargazers():\n",
    "        for page in client.paginate(\"repos/dlt-hub/dlt/stargazers\"):\n",
    "            yield page\n",
    "\n",
    "    return github_events, github_stargazers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we're gonna use `dlt.secrets.value` in our source to enable dlt secrets configuration. Rename `access_token` variable to `secret_key` because it's already defined.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "exit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dlt\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "from dlt.sources.helpers import requests\n",
    "from dlt.sources.helpers.rest_client import RESTClient\n",
    "from dlt.sources.helpers.rest_client.auth import BearerTokenAuth\n",
    "\n",
    "\n",
    "@dlt.source\n",
    "def github_source(access_token=dlt.secrets.value): # <--- set the secret variable \"access_token\" here\n",
    "    client = RESTClient(\n",
    "            base_url=\"https://api.github.com\",\n",
    "            auth=BearerTokenAuth(token=access_token)\n",
    "    )\n",
    "\n",
    "    @dlt.resource\n",
    "    def github_events():\n",
    "        for page in client.paginate(\"orgs/dlt-hub/events\"):\n",
    "            yield page\n",
    "\n",
    "\n",
    "    @dlt.resource\n",
    "    def github_stargazers():\n",
    "        for page in client.paginate(\"repos/dlt-hub/dlt/stargazers\"):\n",
    "            yield page\n",
    "\n",
    "    return github_events, github_stargazers\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Configs are defined in a similar way but are accessed using `dlt.config.value`. However, since configuration variables are internally managed by `dlt`, it is unlikely that you would need to explicitly use `dlt.config.value` in most cases."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you run the pipeline with `secret_key` as `dlt.secrets.value`, you will see the following error:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exception reporting mode: Verbose\n"
     ]
    }
   ],
   "source": [
    "%xmode Verbose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "ConfigFieldMissingException",
     "evalue": "Following fields are missing: ['access_token'] in configuration with spec GithubSourceConfiguration\n\tfor field \"access_token\" config providers and keys were tried in following order:\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES____MAIN____ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key ACCESS_TOKEN was not found.\nWARNING: dlt looks for .dlt folder in your current working directory and your cwd (/Users/m/code/dlt_course) is different from directory of your pipeline script (/Users/m/code/dlt_course/.venv/lib/python3.10/site-packages).\nIf you keep your secret files in the same folder as your pipeline script but run your script from some other folder, secrets/configs will not be found\nPlease refer to https://dlthub.com/docs/general-usage/credentials for more information\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mConfigFieldMissingException\u001b[0m               Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[5], line 6\u001b[0m\n\u001b[1;32m      2\u001b[0m pipeline \u001b[38;5;241m=\u001b[39m dlt\u001b[38;5;241m.\u001b[39mpipeline(destination\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mduckdb\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;03m# run the pipeline with the new resource\u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m load_info \u001b[38;5;241m=\u001b[39m pipeline\u001b[38;5;241m.\u001b[39mrun(\u001b[43mgithub_source\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m)\n        pipeline \u001b[0;34m= <dlt.pipeline.pipeline.Pipeline object at 0x1227e1450>\u001b[0m\u001b[0;34m\n        \u001b[0mgithub_source \u001b[0;34m= <dlt.extract.decorators.DltSourceFactoryWrapper object at 0x107b3c760>\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28mprint\u001b[39m(load_info)\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/extract/decorators.py:196\u001b[0m, in \u001b[0;36mDltSourceFactoryWrapper.__call__\u001b[0;34m(self=<dlt.extract.decorators.DltSourceFactoryWrapper object>, *args=(), **kwargs={})\u001b[0m\n\u001b[1;32m    194\u001b[0m         resource\u001b[38;5;241m.\u001b[39mapply_hints(schema_contract\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mschema_contract)\n\u001b[1;32m    195\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 196\u001b[0m     source \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_deco_f\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n        self._deco_f \u001b[0;34m= <function github_source at 0x121bf3520>\u001b[0m\u001b[0;34m\n        \u001b[0mself \u001b[0;34m= <dlt.extract.decorators.DltSourceFactoryWrapper object at 0x107b3c760>\u001b[0m\u001b[0;34m\n        \u001b[0margs \u001b[0;34m= ()\u001b[0m\u001b[0;34m\n        \u001b[0mkwargs \u001b[0;34m= {}\u001b[0m\n\u001b[1;32m    197\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m source\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/extract/decorators.py:280\u001b[0m, in \u001b[0;36mDltSourceFactoryWrapper._wrap.<locals>._wrap\u001b[0;34m(*args=(), **kwargs={})\u001b[0m\n\u001b[1;32m    272\u001b[0m pipeline_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m proxy\u001b[38;5;241m.\u001b[39mis_active() \u001b[38;5;28;01melse\u001b[39;00m proxy\u001b[38;5;241m.\u001b[39mpipeline()\u001b[38;5;241m.\u001b[39mpipeline_name\n\u001b[1;32m    273\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m inject_section(\n\u001b[1;32m    274\u001b[0m     ConfigSectionContext(\n\u001b[1;32m    275\u001b[0m         pipeline_name\u001b[38;5;241m=\u001b[39mpipeline_name,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    278\u001b[0m     )\n\u001b[1;32m    279\u001b[0m ):\n\u001b[0;32m--> 280\u001b[0m     rv \u001b[38;5;241m=\u001b[39m \u001b[43mconf_f\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n        conf_f \u001b[0;34m= <function github_source at 0x121bf3400>\u001b[0m\u001b[0;34m\n        \u001b[0margs \u001b[0;34m= ()\u001b[0m\u001b[0;34m\n        \u001b[0mkwargs \u001b[0;34m= {}\u001b[0m\n\u001b[1;32m    281\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _eval_rv(rv, schema_copy)\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/common/configuration/inject.py:243\u001b[0m, in \u001b[0;36mwith_config.<locals>.decorator.<locals>._wrap\u001b[0;34m(*args=(), **kwargs={})\u001b[0m\n\u001b[1;32m    241\u001b[0m     config \u001b[38;5;241m=\u001b[39m last_config(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 243\u001b[0m     config \u001b[38;5;241m=\u001b[39m \u001b[43mresolve_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbound_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maccept_partial_\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_partial\u001b[49m\u001b[43m)\u001b[49m\n        config \u001b[0;34m= None\u001b[0m\u001b[0;34m\n        \u001b[0mbound_args \u001b[0;34m= <BoundArguments ()>\u001b[0m\u001b[0;34m\n        \u001b[0maccept_partial \u001b[0;34m= False\u001b[0m\n\u001b[1;32m    245\u001b[0m \u001b[38;5;66;03m# call the function with resolved config\u001b[39;00m\n\u001b[1;32m    246\u001b[0m update_bound_args(bound_args, config, args, kwargs)\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/common/configuration/inject.py:171\u001b[0m, in \u001b[0;36mwith_config.<locals>.decorator.<locals>.resolve_config\u001b[0;34m(bound_args=<BoundArguments ()>, accept_partial_=False)\u001b[0m\n\u001b[1;32m    168\u001b[0m \u001b[38;5;66;03m# this may be called from many threads so section_context is thread affine\u001b[39;00m\n\u001b[1;32m    169\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m inject_section(section_context, lock_context\u001b[38;5;241m=\u001b[39mlock_context_on_injection):\n\u001b[1;32m    170\u001b[0m     \u001b[38;5;66;03m# print(f\"RESOLVE CONF in inject: {f.__name__}: {section_context.sections} vs {sections} in {bound_args.arguments}\")\u001b[39;00m\n\u001b[0;32m--> 171\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mresolve_configuration\u001b[49m\u001b[43m(\u001b[49m\n        config \u001b[0;34m= None\u001b[0m\u001b[0;34m\n        \u001b[0mSPEC \u001b[0;34m= <class '__main__.GithubSourceConfiguration'>\u001b[0m\u001b[0;34m\n        \u001b[0mbound_args.arguments \u001b[0;34m= {}\u001b[0m\u001b[0;34m\n        \u001b[0mbound_args \u001b[0;34m= <BoundArguments ()>\u001b[0m\u001b[0;34m\n        \u001b[0maccept_partial_ \u001b[0;34m= False\u001b[0m\n\u001b[1;32m    172\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mSPEC\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    173\u001b[0m \u001b[43m        \u001b[49m\u001b[43mexplicit_value\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marguments\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    174\u001b[0m \u001b[43m        \u001b[49m\u001b[43maccept_partial\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_partial_\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    175\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/common/configuration/resolve.py:67\u001b[0m, in \u001b[0;36mresolve_configuration\u001b[0;34m(config=<__main__.GithubSourceConfiguration object>, sections=(), explicit_value={}, accept_partial=False)\u001b[0m\n\u001b[1;32m     64\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     65\u001b[0m         log_traces(\u001b[38;5;28;01mNone\u001b[39;00m, config\u001b[38;5;241m.\u001b[39m__section__, \u001b[38;5;28mtype\u001b[39m(config), explicit_value, \u001b[38;5;28;01mNone\u001b[39;00m, traces)\n\u001b[0;32m---> 67\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_resolve_configuration\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msections\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexplicit_value\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maccept_partial\u001b[49m\u001b[43m)\u001b[49m\n        config \u001b[0;34m= <__main__.GithubSourceConfiguration object at 0x122312470>\u001b[0m\u001b[0;34m\n        \u001b[0msections \u001b[0;34m= ()\u001b[0m\u001b[0;34m\n        \u001b[0mexplicit_value \u001b[0;34m= {}\u001b[0m\u001b[0;34m\n        \u001b[0maccept_partial \u001b[0;34m= False\u001b[0m\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/common/configuration/resolve.py:164\u001b[0m, in \u001b[0;36m_resolve_configuration\u001b[0;34m(config=<__main__.GithubSourceConfiguration object>, explicit_sections=(), embedded_sections=(), explicit_value={}, accept_partial=False)\u001b[0m\n\u001b[1;32m    162\u001b[0m \u001b[38;5;66;03m# if native representation didn't fully resolve the config, we try to resolve field by field\u001b[39;00m\n\u001b[1;32m    163\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m config\u001b[38;5;241m.\u001b[39mis_resolved():\n\u001b[0;32m--> 164\u001b[0m     \u001b[43m_resolve_config_fields\u001b[49m\u001b[43m(\u001b[49m\n        config \u001b[0;34m= <__main__.GithubSourceConfiguration object at 0x122312470>\u001b[0m\u001b[0;34m\n        \u001b[0mexplicit_value \u001b[0;34m= {}\u001b[0m\u001b[0;34m\n        \u001b[0membedded_sections \u001b[0;34m= ()\u001b[0m\u001b[0;34m\n        \u001b[0mexplicit_sections \u001b[0;34m= ()\u001b[0m\u001b[0;34m\n        \u001b[0maccept_partial \u001b[0;34m= False\u001b[0m\n\u001b[1;32m    165\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexplicit_value\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexplicit_sections\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43membedded_sections\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maccept_partial\u001b[49m\n\u001b[1;32m    166\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    167\u001b[0m \u001b[38;5;66;03m# full configuration was resolved\u001b[39;00m\n\u001b[1;32m    168\u001b[0m config\u001b[38;5;241m.\u001b[39mresolve()\n",
      "File \u001b[0;32m~/code/dlt_course/.venv/lib/python3.10/site-packages/dlt/common/configuration/resolve.py:300\u001b[0m, in \u001b[0;36m_resolve_config_fields\u001b[0;34m(config=<__main__.GithubSourceConfiguration object>, explicit_values={}, explicit_sections=(), embedded_sections=(), accept_partial=False)\u001b[0m\n\u001b[1;32m    297\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m UnmatchedConfigHintResolversException(\u001b[38;5;28mtype\u001b[39m(config)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, unmatched_hint_resolvers)\n\u001b[1;32m    299\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m unresolved_fields:\n\u001b[0;32m--> 300\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m ConfigFieldMissingException(\u001b[38;5;28mtype\u001b[39m(config)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, unresolved_fields)\n        unresolved_fields \u001b[0;34m= {'access_token': [LookupTrace(provider='Environment Variables', sections=[], key='DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='DLT_IPYKERNEL_LAUNCHER__SOURCES__ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='DLT_IPYKERNEL_LAUNCHER__ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='SOURCES____MAIN____ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='SOURCES__ACCESS_TOKEN', value=None), LookupTrace(provider='Environment Variables', sections=[], key='ACCESS_TOKEN', value=None)]}\u001b[0m\u001b[0;34m\n        \u001b[0mconfig \u001b[0;34m= <__main__.GithubSourceConfiguration object at 0x122312470>\u001b[0m\u001b[0;34m\n        \u001b[0mtype(config) \u001b[0;34m= <class '__main__.GithubSourceConfiguration'>\u001b[0m\n",
      "\u001b[0;31mConfigFieldMissingException\u001b[0m: Following fields are missing: ['access_token'] in configuration with spec GithubSourceConfiguration\n\tfor field \"access_token\" config providers and keys were tried in following order:\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES____MAIN____ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__SOURCES__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key DLT_IPYKERNEL_LAUNCHER__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES____MAIN____ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key SOURCES__ACCESS_TOKEN was not found.\n\t\tIn Environment Variables key ACCESS_TOKEN was not found.\nWARNING: dlt looks for .dlt folder in your current working directory and your cwd (/Users/m/code/dlt_course) is different from directory of your pipeline script (/Users/m/code/dlt_course/.venv/lib/python3.10/site-packages).\nIf you keep your secret files in the same folder as your pipeline script but run your script from some other folder, secrets/configs will not be found\nPlease refer to https://dlthub.com/docs/general-usage/credentials for more information\n"
     ]
    }
   ],
   "source": [
    "# define new dlt pipeline\n",
    "pipeline = dlt.pipeline(destination=\"duckdb\")\n",
    "\n",
    "\n",
    "# run the pipeline with the new resource\n",
    "load_info = pipeline.run(github_source())\n",
    "print(load_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To define `access_token` secret value we can use:\n",
    "\n",
    "1. `dlt.secrets` in code (recommended for secret vaults or dynamic creds)\n",
    "2. Environment variables (recomnended for prod)\n",
    "3. `secrets.toml` file (recommended for local dev)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Use `dlt.secrets` in code**\n",
    "\n",
    "You can easily rewrite your secret right in the Python code. It's especially convenient if you take credentials from third-party secret providers, or if you want to update credentials and configs dinamically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline lesson3 load step completed in 1.33 seconds\n",
      "1 load package(s) were loaded to destination duckdb and into dataset lesson3_dataset\n",
      "The duckdb destination used duckdb:////Users/m/code/dlt_course/lesson3.duckdb location to store data\n",
      "Load package 1735470403.711078 is LOADED and contains no failed jobs\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "dlt.secrets[\"access_token\"] = os.getenv(\"SECRET_KEY\")\n",
    "\n",
    "# define new dlt pipeline\n",
    "pipeline = dlt.pipeline(destination=\"duckdb\", pipeline_name='github_pipeline_lesson3')\n",
    "\n",
    "\n",
    "# run the pipeline with the new resource\n",
    "load_info = pipeline.run(github_source())\n",
    "print(load_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively you can set:\n",
    "\n",
    "```python\n",
    "dlt.secrets[\"sources.access_token\"] = userdata.get('SECRET_KEY')\n",
    "dlt.secrets[\"sources.____main____.access_token\"] = userdata.get('SECRET_KEY')\n",
    "dlt.secrets[\"sources.____main____.github_source.access_token\"] = userdata.get('SECRET_KEY')\n",
    "...\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* `sources` is a special word;\n",
    "\n",
    "* `__main__` is a python module name;\n",
    "\n",
    "* `github_source` is the resource name;\n",
    "\n",
    "* `access_token` is the secret variable name.\n",
    "\n",
    "\n",
    "So dlt looks for secrets according to this hierarchy:\n",
    "```\n",
    "pipeline_name\n",
    "    |\n",
    "    |-sources\n",
    "        |\n",
    "        |-<module name>\n",
    "            |  \n",
    "            |-<source function 1 name>\n",
    "                |\n",
    "                |- secret variable 1\n",
    "                |- secret variable 2\n",
    "```\n",
    "\n",
    "To keep the **naming convention** flexible, dlt looks for a lot of **possible combinations** of key names, starting from the most specific possible path. Then, if the value is not found, it removes the right-most section and tries again.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 2: Run pipeline with `dlt.secrets.value`**\n",
    "\n",
    "Explore the cells above and answer the question below using `sql_client`.\n",
    "\n",
    "#### Question\n",
    "\n",
    "Who has id=`17202864` in the `stargazers` table? Use `sql_client`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>login</th>\n",
       "      <th>id</th>\n",
       "      <th>node_id</th>\n",
       "      <th>avatar_url</th>\n",
       "      <th>gravatar_id</th>\n",
       "      <th>url</th>\n",
       "      <th>html_url</th>\n",
       "      <th>followers_url</th>\n",
       "      <th>following_url</th>\n",
       "      <th>gists_url</th>\n",
       "      <th>...</th>\n",
       "      <th>subscriptions_url</th>\n",
       "      <th>organizations_url</th>\n",
       "      <th>repos_url</th>\n",
       "      <th>events_url</th>\n",
       "      <th>received_events_url</th>\n",
       "      <th>type</th>\n",
       "      <th>user_view_type</th>\n",
       "      <th>site_admin</th>\n",
       "      <th>_dlt_load_id</th>\n",
       "      <th>_dlt_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rudolfix</td>\n",
       "      <td>17202864</td>\n",
       "      <td>MDQ6VXNlcjE3MjAyODY0</td>\n",
       "      <td>https://avatars.githubusercontent.com/u/172028...</td>\n",
       "      <td></td>\n",
       "      <td>https://api.github.com/users/rudolfix</td>\n",
       "      <td>https://github.com/rudolfix</td>\n",
       "      <td>https://api.github.com/users/rudolfix/followers</td>\n",
       "      <td>https://api.github.com/users/rudolfix/followin...</td>\n",
       "      <td>https://api.github.com/users/rudolfix/gists{/g...</td>\n",
       "      <td>...</td>\n",
       "      <td>https://api.github.com/users/rudolfix/subscrip...</td>\n",
       "      <td>https://api.github.com/users/rudolfix/orgs</td>\n",
       "      <td>https://api.github.com/users/rudolfix/repos</td>\n",
       "      <td>https://api.github.com/users/rudolfix/events{/...</td>\n",
       "      <td>https://api.github.com/users/rudolfix/received...</td>\n",
       "      <td>User</td>\n",
       "      <td>public</td>\n",
       "      <td>False</td>\n",
       "      <td>1735470403.711078</td>\n",
       "      <td>lYM5xRla+IkYEQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      login        id               node_id  \\\n",
       "0  rudolfix  17202864  MDQ6VXNlcjE3MjAyODY0   \n",
       "\n",
       "                                          avatar_url gravatar_id  \\\n",
       "0  https://avatars.githubusercontent.com/u/172028...               \n",
       "\n",
       "                                     url                     html_url  \\\n",
       "0  https://api.github.com/users/rudolfix  https://github.com/rudolfix   \n",
       "\n",
       "                                     followers_url  \\\n",
       "0  https://api.github.com/users/rudolfix/followers   \n",
       "\n",
       "                                       following_url  \\\n",
       "0  https://api.github.com/users/rudolfix/followin...   \n",
       "\n",
       "                                           gists_url  ...  \\\n",
       "0  https://api.github.com/users/rudolfix/gists{/g...  ...   \n",
       "\n",
       "                                   subscriptions_url  \\\n",
       "0  https://api.github.com/users/rudolfix/subscrip...   \n",
       "\n",
       "                            organizations_url  \\\n",
       "0  https://api.github.com/users/rudolfix/orgs   \n",
       "\n",
       "                                     repos_url  \\\n",
       "0  https://api.github.com/users/rudolfix/repos   \n",
       "\n",
       "                                          events_url  \\\n",
       "0  https://api.github.com/users/rudolfix/events{/...   \n",
       "\n",
       "                                 received_events_url  type user_view_type  \\\n",
       "0  https://api.github.com/users/rudolfix/received...  User         public   \n",
       "\n",
       "  site_admin       _dlt_load_id         _dlt_id  \n",
       "0      False  1735470403.711078  lYM5xRla+IkYEQ  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Query data from 'pokemon' using the SQL client\n",
    "with pipeline.sql_client() as client:\n",
    "    with client.execute_query(\"SELECT * FROM github_stargazers where id = '17202864'\") as cursor:\n",
    "        data = cursor.df()\n",
    "\n",
    "# Display the data\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "###  **Use environment variables**\n",
    "\n",
    "Let's set ENV in the one of the dlt formats: `ACCESS_TOKEN`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from google.colab import userdata\n",
    "\n",
    "os.environ[\"ACCESS_TOKEN\"] = userdata.get('SECRET_KEY')\n",
    "\n",
    "# define new dlt pipeline\n",
    "pipeline = dlt.pipeline(destination=\"duckdb\")\n",
    "\n",
    "\n",
    "# run the pipeline with the new resource\n",
    "load_info = pipeline.run(github_source())\n",
    "print(load_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively you can set:\n",
    "\n",
    "```python\n",
    "os.environ[\"SOURCES__ACCESS_TOKEN\"] = userdata.get('SECRET_KEY')\n",
    "os.environ[\"SOURCES____MAIN____ACCESS_TOKEN\"] = userdata.get('SECRET_KEY')\n",
    "os.environ[\"SOURCES____MAIN____GITHUB_SOURCE__ACCESS_TOKEN\"] = userdata.get('SECRET_KEY')\n",
    "...\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How does it work?**\n",
    "\n",
    "`dlt` **automatically extracts** configuration settings and secrets based on flexible naming conventions.\n",
    "\n",
    "It then **injects** these values where needed in functions decorated with `@dlt.source`, `@dlt.resource`, or `@dlt.destination`.\n",
    "\n",
    "\n",
    ">dlt uses a specific naming hierarchy to search for the secrets and config values. This makes configurations and secrets easy to manage.\n",
    ">\n",
    "> The naming convention for **environment variables** in dlt follows a specific pattern. All names are **capitalized** and sections are separated with **double underscores** __ , e.g.  `SOURCES____MAIN____GITHUB_SOURCE__SECRET_KEY`.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "###  **Use dlt `secrets.toml` or `config.toml`**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Please note that Colab is not well-suited for using `secrets.toml` or `config.toml` files. As a result, these sections will provide instructions rather than code cells, detailing how to use them in a local environment. You should test this functionality on your own machine. For Colab, it is recommended to use environment variables instead."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `secrets.toml` file - along with the `config.toml` file - should be stored in the `.dlt` directory where your pipeline code is located:\n",
    "\n",
    "```\n",
    "/your_project_directory\n",
    "│\n",
    "├── .dlt\n",
    "│   ├── secrets.toml\n",
    "│   └── config.toml\n",
    "│\n",
    "└── my_pipeline.py\n",
    "```\n",
    "\n",
    "Read more about adding [credentials](https://dlthub.com/docs/walkthroughs/add_credentials) here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To set credentials via TOMLs you would first add your access token to `secrets.toml`:\n",
    "\n",
    "```toml\n",
    "# .dlt/secrets.toml\n",
    "\n",
    "[sources]\n",
    "secret_key = \"your_access_token\"\n",
    "```\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Alternatively you can set:\n",
    "\n",
    "```\n",
    "[sources]\n",
    "secret_key = \"your_access_token\"\n",
    "```\n",
    "is equal to:\n",
    "\n",
    "```\n",
    "secret_key = \"your_access_token\"\n",
    "```\n",
    "\n",
    "and to:\n",
    "\n",
    "```\n",
    "[sources.____main____]\n",
    "secret_key = \"your_access_token\"\n",
    "```\n",
    "and to:\n",
    "\n",
    "```\n",
    "[sources.____main____.github_source]\n",
    "secret_key = \"your_access_token\"\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### **Configure Secrets in Colab**\n",
    "\n",
    "You can configure secrets using **Secrets** sidebar. Just create a variable with the name `secrets.toml` and paste the content of the toml file from your `.dlt` folder into it. We support `config.toml` variable as well.\n",
    "\n",
    "Open **Secrets** sidebar, press \"Add new secret\", create variable with name `secrets.toml` and copy-paste secrets in Value field and Enable it:\n",
    "\n",
    "```\n",
    "[sources]\n",
    "secret_key = \"your_access_token\"\n",
    "```\n",
    "\n",
    "\n",
    ">dlt will not reload the secrets automatically. **Please restart your interpreter** in Colab options when you add/change content of the variables above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Screenshot 2024-11-29 at 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)"
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 ],
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   "language": "python",
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