diff --git a/main.py b/main.py
index cd70688..623681c 100644
--- a/main.py
+++ b/main.py
@@ -53,14 +53,22 @@ parser.add_argument(
 )
 args = parser.parse_args()
 
-selected = "data/tracking_losses_ntuple_B_def_selected.root"
+selected = "data/tracking_losses_ntuple_B_BJpsi_def_selected.root"
 if args.prepare_params_data:
-    selection = "fromSignal == 1 && isElectron == 1 && pt > 10 && p > 1500 && p < 100000 && !std::isnan(ideal_state_770_x) && !std::isnan(ideal_state_9410_x) && !std::isnan(ideal_state_10000_x)"
+    selection = "isElectron == 1 && pt > 10 && p > 1500 && p < 100000 && !std::isnan(ideal_state_770_x) && !std::isnan(ideal_state_9410_x) && !std::isnan(ideal_state_10000_x) && std::abs(match_chi2) < 5"
     print("Run selection cuts =", selection)
-    selected_md = preselection(
+    selected_b = preselection(
         cuts=selection,
         input_file="data/tracking_losses_ntuple_B_def.root",
     )
+    selected_bj = preselection(
+        cuts=selection,
+        input_file="data/tracking_losses_ntuple_BJpsi_def.root",
+    )
+    merge_cmd = ["hadd", "-fk", selected, selected_b, selected_bj]
+    print("Concatenate polarities ...")
+    subprocess.run(merge_cmd, check=True)
+
 
 cpp_files = []
 if args.field_params:
diff --git a/moore_options/get_tracking_losses.py b/moore_options/get_tracking_losses.py
index 5485bd5..7cfad05 100644
--- a/moore_options/get_tracking_losses.py
+++ b/moore_options/get_tracking_losses.py
@@ -40,7 +40,7 @@ tested by mc_matching_example.py
 
 """
 
-decay = "B"
+decay = "BJpsi"
 
 options.evt_max = -1
 
@@ -63,7 +63,7 @@ options.simulation = True
 options.input_type = "ROOT"
 
 options.ntuple_file = (
-    f"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_{decay}_default.root"
+    f"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_{decay}_def.root"
 )
 
 
diff --git a/parameterisations/notebooks/bend_y_params.ipynb b/parameterisations/notebooks/bend_y_params.ipynb
index d0c6616..eb3dfa2 100644
--- a/parameterisations/notebooks/bend_y_params.ipynb
+++ b/parameterisations/notebooks/bend_y_params.ipynb
@@ -2,60 +2,502 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [],
    "source": [
     "import uproot\n",
     "import awkward as ak\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
     "import numpy as np\n",
-    "input_tree = uproot.open({\"/work/guenther/reco_tuner/data/param_data_selected.root\": \"Selected\"})\n",
+    "import mplhep\n",
+    "\n",
+    "from sklearn.preprocessing import PolynomialFeatures\n",
+    "from sklearn.linear_model import LinearRegression, Lasso, Ridge, ElasticNet\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.metrics import mean_squared_error\n",
+    "\n",
+    "mplhep.style.use([\"LHCbTex2\"])\n",
+    "input_tree = uproot.open(\n",
+    "    {\n",
+    "        \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_BJpsi_def_selected.root\": \"Selected\"\n",
+    "    }\n",
+    ")\n",
     "array = input_tree.arrays()\n",
-    "array[\"dSlope_xEndT\"] = array[\"tx_l11\"] - array[\"tx\"]\n",
-    "array[\"dSlope_yEndT\"] = array[\"ty_l11\"] - array[\"ty\"]\n",
+    "\n",
+    "array[\"yStraightOut\"] = array[\"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] * (\n",
+    "    array[\"ideal_state_10000_z\"] - array[\"ideal_state_770_z\"]\n",
+    ")\n",
+    "array[\"yDiffOut\"] = array[\"ideal_state_10000_y\"] - array[\"yStraightOut\"]\n",
+    "array[\"yStraightEndT\"] = array[\"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] * (\n",
+    "    9410.0 - array[\"ideal_state_770_z\"]\n",
+    ")\n",
+    "array[\"yDiffEndT\"] = array[\"ideal_state_9410_y\"] - array[\"yStraightEndT\"]\n",
+    "\n",
+    "array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\"ideal_state_770_tx\"]\n",
+    "array[\"dSlope_yEndT\"] = array[\"ideal_state_9410_ty\"] - array[\"ideal_state_770_ty\"]\n",
     "array[\"dSlope_xEndT_abs\"] = abs(array[\"dSlope_xEndT\"])\n",
     "array[\"dSlope_yEndT_abs\"] = abs(array[\"dSlope_yEndT\"])\n",
-    "array[\"yStraightEndT\"] = array[\"y\"] + array[\"ty\"] * ( 9410. - array[\"z\"])\n",
-    "array[\"yDiffEndT\"] = (array[\"y_l11\"] + array[\"ty_l11\"] * ( 9410. - array[\"z_l11\"])) - array[\"yStraightEndT\"]\n",
+    "\n",
     "\n",
     "def format_array(name, coef):\n",
-    "    coef = [str(c)+\"f\" for c in coef if c != 0.0]\n",
+    "    coef = [str(c) + \"f\" for c in coef if c != 0.0]\n",
     "    code = f\"constexpr std::array {name}\"\n",
-    "    code += \"{\" + \", \".join(list(coef)) +\"};\"\n",
+    "    code += \"{\" + \", \".join(list(coef)) + \"};\"\n",
     "    return code"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMIAAAOWCAYAAAANzz7PAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACUY0lEQVR4nOz9X2zj6Xkn+D5UV4z2iZdFqQcLCBJwUlS88OBc7BRVlYs5VztFbhY49omzFquMeGxfTErqBHNmAQUW3fHFzl64y1R2dTPnJC21c4BjxxfVUnts2AvsWrT3boFFSWzvnbETsTqABAKL6RKLseGG002eixpxJJVEURLFP+LnAwhDSs/v5aM/1RN+/bzvL9FsNpsBAAAAANfcWL8bAAAAAIBeEIQBAAAAMBIEYQAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAADASBGEAAAAAjARBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAADASBGEAAAAAjARBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACPhRr8bYLT89m//dnz44YfxyiuvxH/6n/6n/W4HAAAA6LH/8//8P+Pjjz+OV199NX71q1/19LUTzWaz2dNXZKS98sor0Wg0+t0GAAAA0GdjY2Px8ccf9/Q1TYTRUwdB2NjYWExOTnZlzWq12vU19XK9+9HLcPSjl+HoRy/D0Y9ehqMfvQxHP3oZjn70Mhz96GU4+rmKXg7WfOWVV7qy3rk0oYempqaaEdGcmpoa6DX10n2D1I9eTjdI/ejldIPUj15ON0j96OV0g9SPXk43SP3o5XSD1I9eTjdI/ejldIPUz3V7H9/XibBPf/rT/Xz5IxKJRPwf/8f/0e82AAAAALgifQ3CdnZ2IpFIRLOPx5QdvH4ikehbDwAAAABcvbF+N9Bv/QzhAAAAAOidvh+W32w2Y25uLtLpdF9ev1arxdraWl9eGwAAAIDe6XsQtra2Fn/8x3/c1x7m5ubi93//9/vaAwAAAABXq+9bI7PZbL9biLt37/a7BQAAAACuWN+DsImJiX63AAAAAMAI6OvWSHdqpBsWFxejXq9HMpnsdyt6aWPQ+hkUg/ZzGaR+9DIcBulnM0i9RAxWP4PUy6AZpJ+NXk43aP0MikH7uQxSP3oZDoP0sxmkXiIGq59B6qUbEs0+3jZxbGwsarVa33+Yz58/j/Hx8Wg0Gn3tYxRMT0/H3t5eTE1Nxe7ubr/bYUT5O2TY+RtmmPn7Zdj5G2bY+RtmEPTz77CvWyOLxWLfQ7CIiJs3b0axWOx3GwAAAABcob4GYV/72td6+nrvv//+qV/rdS8AAAAA9FbfD8vvpYWFhX63AAAAAECfjFQQtrW11e8WAAAAAOiTvt418qLef//9qNVqHddXKpVYXV091zUAAAAAXC9DEYS9//77USwWo1QqRaVSudAazWYzEolElzsDAAAAYFgMfBD2xhtvxPLyckS8CLMAAAAA4CIGOgh79913o1gsRkREIpGIRCIhDLsmqtVqTE9Pt61ZXFyMxcXFHnXEKFlcXIx6vR7JZLLfrcCF+BtmmPn7Zdj5G2bY+Rvmqq2srMTKykrbmmq12qNuXpZoDnCydOfOnSiXy60ALJ1ORyaTiXQ6HRERr7322plrfPDBB1Gr1eKdd96J58+fx8cff3zVbdPG9PR07O3tdVT73/63/23863/9r6+2IQAAAKBr/vW//tfx3/13/11HtVNTU7G7u3vFHR010BNhByFYRMTm5mbcu3fvwmstLS3Fpz/96W61xiWNjY3F5ORk2xr/CwUAAAAMl2QyGVNTU21rqtVqNBqNHnV01EBPhE1MTMTz589jaWkpHj16dOn1fvd3fzf+9m//tgudcVEHE2H9SH0BAACA/utnNjDW01c7p4MtkHfv3u3Kequrq11ZBwAAAIDhM9BB2MFWyGfPnnV1PQAAAABGz0AHYX/+538ezWYzyuVyV9b79re/3ZV1AAAAABg+Ax2E3bx5M771rW/F48eP4+///u8vvZ6tkQAAAACja6CDsIgXd3vMZDKRz+cvtc7Tp0+7NlnWa7VaLQqFQuRyuZiZmYlEIhEzMzORz+djbW3twusuLy9HLpeL8fHxI2uWSqUudg8AAAAwGG70u4FObG5uxp07d+LTn/50FAqFmJiY6Oi6Z8+eRa1Wi52dnXjnnXeuuMursby8HIVCIVKpVLzxxhuRyWRiYmIitra2YnV1NRYWFqJYLMbq6mpks9mO1iyVSpHP56NWq0U2m4319fVIp9NRLpdbgdvB51Op1NV+gwAAAAA9kmg2m81+N3GWn/3sZ7G0tBTlcjkSicSF1mg2m5FIJOLjjz/ucndXJ5/Px8bGRmQymdje3j6xZmFhoTUVtr29HZlMpu2apVIpcrlcRETMz8+fuF10dnY2yuVypNPp2N7e7moY1s9bpAIAAAD9189sYOCDsD/5kz85sv3vIu0mEomhC8IOJsEiIvb399uGUTMzM1GpVCKVSsX+/v6pdbVaLW7duhW1Wi3S6XTs7OycWFepVGJmZiYiIrLZbGxubl78GzlmmIKwZjOiccaf21gi4oLZLAAAAIykfmYDA31G2Ntvvx2rq6ut8Ouimd2AZ30nOgjBMpnMmRNZc3NzEfEi6NrY2Di17mA75OH1T5JOp1trlkqlS51DNswazYgb32j/cVZQBgAAAAyOgT4j7GDb3sFEVzabjVwuF6lU6tznhL311lvx/vvvX2G33XP4sPp0On1m/d27d1uPnzx50gqxDqtUKkfWvX//fts1Hzx40ArVCoVCzM/Pn9kHAAAAwCAb6CDs4EywVCoVW1tbcevWrQuv9fDhw3jttde62N3VqVQqrcfnvdPlad9jsVhsPc5msx1PmUX8x0mzkwI2AAAAgGEx0FsjD8KaN95441Ih2MFat2/f7kJXV+/wtFulUjkSjJ3kyZMnrcenTZAd3t541oH6J631+PHjjq4BAAAAGFQDHYTNzs5GRGfbAzvx9ttvd2Wdq3b8+11YWGhbf7CFMZVKnTi1dXyq7PBWynYOB2btzh4DAAAAGAYDHYQtLCxEs9k8cyKqU8MyEZbJZI6EUKVSKfL5/Im1a2trrZ/P4e2Phx0+Gyyi82DxeN15t2nCoDm4WQQAAACjaaCDsLm5ubh9+3bXtuV9//vf78o6vXB8em1jY+OlMKxUKrWmxVZXV0890P7w1smIOPN8sAPHzxvb2trq6DoYJOVyOQqFQoyPj8fDhw/73Q4AAAB9NNBBWETE+vp6bG9vx7/9t//20ms9evSoCx31RiaTifX19SOf29jYiJmZmSiXy7G8vBy5XC7S6XRsbm62vavj8Ym6i06E7ezsdNg9dOYgpMrlcjEzMxPj4+ORSCRifHw8ZmdnI5fLRaFQeGmq8UA+n29toT5wcHOHfD7fWmd5edk0GAAAAIN918iIF2HMW2+9FX/8x38cf/iHf3jhdZ4/fz50W/vm5uZidXX1yBlhlUql9cZ/aWnp1O2Qh3Vra6kg4WVvr63Fn/xJ+zPcTpLJZGJ7e/vSr59IJM59TSqViv39/RO/ls/nL3Qe3ObmZmSz2Y5qa7VaPHr0KJaXl9vWHPx7LZVKrdpMJhPZbDZmZmZic3MzNjY2Xrr5w8OHD6NSqQzdv3cAAACu3kAHYQdbGf/RP/pHMT4+Hp/+9KdPPAz+LLVaLd55551ut9cTB5NeJx2YXyqVolarnbnV8aIB1vF1nz17dqF1TlKtVmN6evrS6ywuLsbi4mIXOrqYh/Pz8cUv3o9KpRKPHj1qGyJls9koFApx586djrennuXgDL1SqRSFQuHU33U6nY5CoRDZbLbtROD6+nrUarXY2tqKYrF46iRWxIsg9sGDB5FOpzv+fgqFwokB2NzcXGutg/UO7pi6vr4e77zzTiscOx5wHf+eD09SzszMdC0IBgAAGHUrKyuxsrJy6XWq1WoXurmYgQ7C3nzzzXjvvfdaz5vNZtspknaazeaFpmcGwfz8fGxvb8fa2tqRz5fL5bh161b89Kc/fWkq5ip0cyKs0WjE3t7epdep1+td6OZyUqlUayvrwsLCS7+niBdBz/Gtrt2STqdjfn6+NSl1ku3t7Y7DqlQqFdlsNrLZbMzOzp44WdXuTLqTVCqVyOVyL4VS8/Pzsbq6euI1B6FYNpuN1dXVWF5ejkKh0PFrRrwIH0/6fQAAAHB+9Xq9K+/l+2mgg7D79++33oQnEomhDbIu6yBcmZ+fj1KpdCRMqNVqMTs723ZrWiqV6kqI1a0ppoiIsbGxmJycvPQ6yWSyC910z2lB2EkTfd2WTqcjk8m8FFzNzc1d+He3sLBwYu/nCcFKpVLkcrkjn0ulUucOcJeWlmJubi5mZ2eP/D23m1Ts5t8sAADAqEsmkzE1NXXpdarVajQajS50dH4DHYQtLCzE17/+9UgkEtFsNvvdTl/kcrkolUpHzgM7KWzJ5XKnhmETExNdCcImJiYuvcaBycnJ2N3d7dp6g+K0bYed3qCgG69/PAi7zGufdO15wqVyudyVEOxwP0+fPo1bt261/qadXQcAANAb3TqeaHp6um+TZQMdhN28eTMymUy89957USwWI5PJXCiMqVQq8eabb8bPf/7z7jd5hQ62pWWz2SOH4q+urkYul4t8Pn+kPp/Px9OnT18KKi46FXM8YDBdc7bTfkbdDBGHRaVSiXv37r30+fX19Utt5U2lUrG9vX3qNtBhdnD4f6+C02FTKpU6vikDAADASQY6CIuIePDgQczMzMTXvva1C69x+/bt+MIXvjBUYUQ+n29N9px0htLc3Fxsb2/HvXv3jkzGFAqFl+rv3LlzZEqokwP2I17ecnYdg4fr5qS/8ddee62r63X67yifz78Uph6cZXZZ6XQ6lpaWLnxmYK+Vy+VYXV1tbW1OpVIxMTERqVQq0ul0PHjwICJe3PGyWCy23XpaKpUin8/HxMRErK6uXutg6OBGEOvr660bNwzSdPAo/S4AAOC6GOt3A2fJZrNde+Nz586drqxz1SqVSuvug+2mQzKZTGxvbx/53Nra2kvhw+zs7Evrd2JnZ+fIc2/y6FSpVDrxkP3Dk42X9cYbb7QeD+r2yFqtFvl8PmZnZ1vbmefm5iKbzUYqlYpyuRwbGxuRz+dbweFZ38tBXaVS6cnZc/1QqVRidnY2ZmdnY2Fhoe3dS/tpFH4XAABw3Qx8EHb79u2uvXn+V//qX3Vlnat2eKLrrPAunU6/NAG2tbV15PnxNToNwg6/IT+YXIFOnBQKXObQ/pOkUqlzHdrfD/l8vhVqr66uxs7OTqyvr8f6+npsb2/Hzs7OSwHz8QD6uGGabL2odDod29vbsb+/H0tLS/1u51Sj8LsAAIDrZuCDsIiIW7dudWWdf/Nv/k1X1rlqhwOoTrYjHg8DjgddmUzmSADx5MmTjvo4HKgNyzQd/Xf8zqYHDk9wdcvBOXnt7hzZzsHWtpmZmUgkEjE+Ph65XO7EO3+e1/LycmuSaWlp6cTQLp1Ox+bm5pGw/6ygenV1NdLpdKTT6VhfX790n4Pu+M0WBsmo/S4AAOA6GIogrFuOT0oNqsNv6s+aDjlw1uHj9+/fbz0+acvaSQ7XFQqFjq6B0wKByxyQf5qDG0mcdzKnVqvF7Oxs5HK52NjYaIVPtVotSqVSLCwsxMzMTMf/Vk7y6NGj1uOzts0tLS21Jp/OCvWy2Wzs7OzEzs7OlfxMB02/pq462eo4ar8LAAC4Dgb+sPyTvP/+++c6E6hSqcTq6urAniN03OEtiJ1uYzzt+gMLCwutKZdOzts5XJNOp50PRsdO+vu6yr+f826dOzh/6qz/HhzUbW5unrv/SqVy7v/eFIvFU6fp6K21tbVYW1s78UYlAADAcBuKIOz999+/9JvEZrMZiUSiy51djQcPHrTuhre1tdXRXR4P/1xOetOeyWQim822QoqNjY2Ym5s7db3DUz2mwehUpVI58d/ooEzLHBxeX6vVYm5uLnK5XNy5cyeePXsWm5ubJ96FMpfLxc7OzrnOyDsegpVKpY7OM3vjjTda2z3pDwffAwDA9TbwWyPfeOONmJmZibW1tdjZ2Ylms3mhj2FyEFpFvHhDfXiL1UlKpVLrjXe7Gwscnm5ot2atVmtNj2Wz2YE/kJzBcVpQ3clZd71wcDfLzc3NWF9fj/n5+da/t2KxeGrgdd5w6vgahUKhowmxg3B6WKZXr5tarTbQZ5IBAACXN9BB2LvvvhvFYrEVZA3LRFc3rK+vt6bAlpeXTz28u1KptN6kZ7PZttvEDh/oXC6XT5x+iYi4d+9eRLy4K58DoDmP04KwQbq7XrutjgeH1x9XLpc72lJ8IJVKHZniPDiTrJOJ1maz2dW7a9KZWq0W9+7dszUVAACuuYEOwg6mlhKJRDSbzbh161bMzc21DpYuFotnfhzcrW3Y3limUql4+vRpaxprYWGhdTe7gzflhUIhZmZmolarRbFYPPEN/HFzc3OxubkZqVQqCoVC5PP5KJfLrUPCZ2dno1wuRyaTiadPnw7dz42XFQqFSCQSF/qYnZ0912udNsk0KH9HqVTqzPO+0un0iZOV7aYtT3K8vlKptKZbL6tcLrcO9G/nYLpzdnb2yOsebP8bHx+PRCIRMzMzJwbjlUql9d+Zg7qFhYUTf88Hr3P8b+i4XC7XWu/wRzen4NbW1o68zvj4eMzOzp4a/pfL5bh169ZLN0c43N9pP+tOfxcHarVaLC8vRy6Xa/38D/orFAodBXGVSiWWl5dfuqHD4d/BzMxMaxswAABwSHOAJRKJ5tjYWHNsbKxZKpUutdbOzk5zbGysS5311vb2dnN+fr6ZTqebEdGMiGY6nW7Ozc01l5aWmvv7+xdat1gsNjOZTDOVSjUjoplKpZrZbLa5vr7e3W/gkKmpqWZENKempq7sNbrlo4+bzfh6+4+PPn75uoPf0eGPi/6Ozmt+fv7E1+/mRzqdPvfrb25u9uT7P25paelIH9lstuNrD/5dHP44r2w2e+LPI5PJNLe3t8+11sF/Bw73lUqlXqrb399v/ds+/Jqrq6vNZvPln8nhj/n5+dY67erS6fSpf9PH/wZOUywWO/o3sr293fHvYH19vfVzOfzfse3t7dZ/P0/qfX9/v7m9vf1ST9vb20c+Dq/Xye/iuNXV1VZ9sVhsbm9vN3d2dprr6+tHfl9zc3MvXbu/v99cWlo68v8PHPS4v7//0u/7cF87Oztn9gYAAL3Uz2xgoCfCDqZIlpaWWtv1LiqdTsetW7e60FXvZTKZWF1dPXJG2s7OTqyvr0exWLzwtM3S0lJsb2/H/v5+NJvN2N/fj83NzbaH6DN85ufnY3t7+0If571r3ml/i4MylXKefysnTY4dnxg6y2n/nsrlcszOznY8sVOpVOLx48cdTx1lMpmXDnzf3t5uTXyur6/Hzs5O7O/vH9lOfTBxmsvlolQqxebmZuzv77f+23Dw86tUKqeeM9jpeWrd/u9MqVRqvfYbb7xxZP1MJtPa5l2pVOLhw4dHrk2lUpHJZF66qcPB5w5/7by/iwOFQiEWFhYilUrFzs5OLC0tRSaTiXQ6HXNzc7G9vd3qeWNjozXte+DZs2eRy+Ve+rvc2tqKW7dutbb17uzsxOrqaut3VavVHP4PAACH9Tx6O4fZ2dnm2NhY89133+3KepedKuPyTIRdrZMmsorF4oXXOz6NE2dMhB2fqDn4OJhG6rXjU00nTdqc5mC6qBvfx2k/l4use3its6aQjk8JnTaZd3xy7fBk2GGHfyanvfbm5mZHE1z7+/tdnQibm5s782/+rHU67f1Ap7+Lw5NgZ/2uD098nTbBeLjHVCp14u/1+N9vr/4bBAAAnTARdoqDKbBnz551dT3gagz6RNh5nHT3yIt+H0tLS7G/v3/qFNTBGYCdrH9SX6c5fJOC+fn5U89HO36nxNMmAQ/3X6vVBvb3etrf4eHPd+NQ/E5/F4VCofX6Z92F96A24sWU20k3aTj8fbz99tsn/l6P/61tbW111CsAAFx3Ax2E/fmf/3k0m81zb0c6zbe//e2urAOc7LRgYGdnp8edXN5JYcoHH3xwqfXW19dje3v7pS14ES9Cj3v37nU1XOp0K+jh39t5to8O0h0W33777SgWi7G+vn5m2BTRu3B2bW2t9VqdBGfHb+5y3ps0HHb49QbpdwUAAP000EHYzZs341vf+lY8fvw4/v7v//7S6533vCPgfE6bODppqmXQnRRavPbaa5deN5PJnHr+Wrlcfun8ql646DmD3ZrW7YZUKhVLS0unnsnWrf9B5bwO38230wmyw/+OhvHfDgAADLKBDsIionWgcKcHMJ/m6dOnfXsjBKPkpGmnSqUysNvozuM82xLPMj8/Hzs7Oy+FUBsbGwMdflw0NOu1SqUSa2trUSqVTjwIv5d9nNfxv7Pr8G8HAAAGxY1+N9CJzc3NuHPnTnz605+OQqFw5Nybdp49exa1Wi12dnbinXfeueIuOY9qtRrT09NtaxYXF2NxcbFHHdEtDx48ODF0LpVKQ3dH0lQqdSSE6GYQdrDewd0cD7/O6urqqdN1tFcul6NQKEQmk7nUtsJuOfx77TQUO35HymfPng1NAAkAACsrK7GystK2plqt9qiblw1FEPazn/0sIl6cM3TR28A3m81IJBLdbItLaDQasbe317amXq/3qJvhUS6X49GjR7G+vt7vVk41Pz9/5MDvA6urq0MXhB2fxOlkqqhUKkWhUIjt7e2OXiOdTsfbb799ZOrV9OrFLCwsxNraWszPzw9ECBZxsQP6j/+PPd0OYAEA4CrV6/Uz3+/308AHYX/yJ38Sa2trERGRSCSi2Wyeew0B2OAZGxuLycnJtjXJZLJH3QyPhw8fdjwR2S+pVCrm5uZiY2PjyOdLpVKUy+W+bVE7r+MhWKcTWul0OsrlcpRKpY6vOR4QOtj8/A5CsIjLHTDfbQd/DxH/8U6bZ013HT57TQgGAMCwSSaTMTU11bamWq1Go9HoUUdHDfQZYW+//Xasrq62wq+LhGCXuY6rMzk5Gbu7u20/bIs86iBIyuVyp9Z0+/Dyi653WhBx0qTYZV3V+UlbW1tHnnc6jXoQXFx0ejWis8mzYdfNv9VyudwKwdLp9EBtI3zw4MGR5wd9tnP4LqvDNkUJAACLi4tnvt8/azDmKg30RNjBXdUOJsGy2WzkcrlIpVLnPifsrbfeivfff/8Ku4WrU6vVWlvnzvvG+IMPPuhqL50EGOl0OorF4kvBV6lUiuXl5VhaWupKL5VKJXK5XGSz2a7fFfb43f7O83NPp9NRqVSiUCh0NJ10fALseHgyTI7/t/m0CahuTr0dvrlAu3X7cej83NzckbPmVldXz/z7P/z9vPHGG1fZHgAAjJyBDsLK5XIkEolIpVKxtbUVt27duvBaDx8+jNdee62L3cHLruKNdq1Wi3v37rUChfNulep2T52ut7S0FJubmy/dAfHgIPPLHgZfKpUil8u1QrduO7y187wh20EQtry8HDMzMzE/P9+2/vD66XS6a0Fhp7+rw3VnXXPW149Ps62trb30/RyEhId180D4jY2Nl4LLk17vuOP/tiqVypHPdbKt8SSHz4CrVCptt82Wy+XWVspisThQ020AAHAdDPTWyIM3AG+88calQrCDtW7fvt2FruB0p02jXHQbWKlUitnZ2dYb4/v375/79S+zBe2yUzubm5snTlLlcrlYXl6+0Jq1Wi0WFhZaIdj29nbHYUGnwdDa2lrre5+fnz93aHc4PFlYWIiFhYVTX3ttbe3Iz+LwJNpJDv8++zHhdNhpr3/451UoFGJhYSFKpVJsbGzEwsJCzMzMvBTydPpv56TXPB6+5fP5WF5ebk0gzszMvBRqra6utm5scLDm8SDs4PdWqVSOnEF2Um/tfhdzc3NHwtp8Pn9ifa1Wi4cPH0bEi7+70wLRTn/vh3+m/f5bAQCAgdEcYNlstjk2NtZ89913u7JeuVzuyjpc3NTUVDMimlNTU/1u5Uwffdxsxtfbf3z08dFr5ufnmxHx0kc2m23u7Oyc+Zr7+/vNzc3N5tLSUjOdTr+0zvr6+qnX7uzsnPjaEdHc39+/0M8gk8mcuN7q6uq51llaWjpxnUwm09zc3Oxojf39/WaxWGymUqnWz/Ss7+v466ZSqTNf5/DPMZvNdtTbcaurqyd+v3Nzc82lpaXm6upqc35+/sjvuNO/keO/k9P+Jvb391/6WZ9mbm6uo9/v5ubmkbr5+flTX/vg93T8I5VKtX7nh2symUxzZ2fnpd9pp70drzv8USwWm83myf8+5+bmjqxz2t/qSd9rp7+LA+vr663vOZVKNVdXV5s7OzvNnZ2d5urqauvv4aDfk3T6Ozhed9G/ZQAAuAr9zAYGOghbX19vJhKJ5l/8xV/0uxW65LoGYdvb223fiHfr46TgZ39/v7m6unpq8BARzXQ63VxdXe04ENve3m5ms9m2vSwtLXUU3BzY3Nw8NVhLpVLNubm55urqanNzc7O5vb3d3NzcbK6urjaLxeKR61Kp1JmBw4GTwsF0On1q+HY4qDgekJzH5uZmq8/19fXm/Px8M5vNNjOZzJHf08H3fVYYePD3ddrvOJPJtMKTdrXpdLo5NzfX+js4HsYdD04O1tzc3Dz17yGdTp8Yxuzv7x9ZP5PJNJeWlo7UHHzu+N/R/v7+md/vSa9ZLBZbr5dOp5tLS0tH/ub39/db38fhn9lxh4PoTCZz5O/tPL+L06yurjaz2eyRUOzgutP+jbb7N3n4d7Czs9O27qzeAACgF/qZDSSazcG+peLs7GyMjY3FkydPLr3W97///fiv/+v/ugtdcVHT09Oxt7cXU1NTsbu72+922vq4EXHjG+1r/ur/uhZ/8icXvzvgeWQymdje3j7yuUQice51UqlU7O/vn/i1fD5/5GysTm1ubna8fXBjYyMePXrU2u7ZqXQ6HQsLCzE/P3+uc5MOzqM6/n2lUqm4c+dO6yDzra2t1hlQ6+vrlz7DDAAAgJP1MxsY+CCsUqnE7/7u78a7774bf/iHf3ipte7evduVQI2Lu25B2EffjHhloE/aG1y1Wi1KpVI8fvw4KpVK6yymiBeh18GNAe7evRtzc3PnvknAWa938JoHr3Pnzp3I5/MCMAAAgCsmCDvD2tpavPHGG/HBBx9ceI3nz5/HxMREfPzxx13sjPMShAEAAMBo62c2cKOnr3ZO3//+9yMi4h/9o38U4+Pj8elPf/rEO9CdpVarxTvvvNPt9gAAAAAYIgMdhL355pvx3nvvtZ43m81YXl6+0FrNZvNC5ykBAAAAcD0M9Kau+/fvR/PFnS0j4mIHgwMAAABAxIAHYQsLL+7Gl0gkWoHYRT8AAAAAGG0DvTXy5s2bkclk4r333otisRiZTCYmJibOvU6lUok333wzfv7zn3e/SUba996L+Mpsv7sAAAAAOjHQQVhExIMHD2JmZia+9rWvXXiN27dvxxe+8IULhWiMru+9d3bNVzde3DXyS7evvh8AAADgcgZ6a2RERDab7drWxjt37nRlHa6/5x9G/OkPO6t9/QcR9Q+vtB0AAACgCwY+CLt9+3YUi8WurNWtdbj+vluO+NU/dFb7y99EfKd8tf0AAAAAlzfwQVhExK1bt7qyzu3b9q/RmR/94nz1Pz5nPQAAANB7fT0j7Oc//3n8k3/yT/rZQssg9TIKqtVqTE9Pt61ZXFyMxcXFHnV01P6vr7YeAAAArqOVlZVYWVlpW1OtVnvUzcv6GoTNzs7G/v5+JJPJfrYRz58/j9nZ2fj444/72scoaTQasbe317amXq/3qJuXjX/yausBAADgOqrX62e+3++nvgZh3ToEvxsGqZdRMDY2FpOTk21r+hmQfu4zET/5d53Xf/YzV9cLAAAADItkMhlTU1Nta6rVajQajR51dFSi2ccE6JVXXhmYibCJiQkTYT0wPT0de3t7MTU1Fbu7u/1u51TPP4yYerOzA/M/9YmIvTcikq9efV8AAAAw7PqZDfT1sHxTWAyqm69G/OUfdFb71ueFYAAAADAM+n7XyKdPn/a7hdja2up3CwygL3Vwk9HvzHVWBwAAAPRfX88Ii4h4+PBhfP3rX49UKhUTExM9fe1nz55FpVKJpaWlnr4u18cfCcEAAABgaPQ9CNve3o58Pt/XHprNZiQSib72AAAAAMDV6nsQdqBf54UJwAAAAABGQ9+DsH4fmN/v1wcAAACgN/oahO3v7/fz5QEAAAAYIX0Nwm7evNnPlwcAAABghIz1uwEAAAAA6AVBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACPhRr8bYDRVq9WYnp5uW7O4uBiLi4s96ggAAAC4rJWVlVhZWWlbU61We9TNywRh9EWj0Yi9vb22NfV6vUfdAAAAAN1Qr9fPfL/fT4Iw+mJsbCwmJyfb1iSTyR51AwAAAHRDMpmMqamptjXVajUajUaPOjoq0Ww2m315ZUbS9PR07O3txdTUVOzu7va7nbY+bkTc+Eb7mo++GfGKk/YAAACgY/3MBq7dW/if/exn8eDBg/jrv/7rfrcCAAAAwAC5dlsj5+bm4vnz57GxsRH5fN72OgAAAAAi4hpOhN26dSsiIm7fvi0EAwAAAKDl2gVh6+vr0Ww249vf/na/WwEAAABggFy7ICydTsfW1lY8fPgw/u7v/q7f7fRUuVyOjY2NWF5ejlKp1NE1y8vLkcvlYnx8PBKJRMzMzEQ+n+/4egAAAIBhce2CsIiITCYTpVIpHj58GG+88Ua/27kytVotlpeXY3Z2NhKJRNy7dy+ePHkSmUwm7ty50/baUqkU4+PjUSgUIuLFJN3Ozk4Ui8Uol8uRy+Uil8tFrVbrwXcCAAAAcPWu3WH5ExMTMTMzE7lcLl5//fX44IMP4u7du/HFL34x/uzP/qzf7XVFrVaLQqEQa2trEfEi+Nvc3IxsNtvR9aVSKXK5XEREzM/Px+rqautr6XQ65ubmYnZ2NkqlUszOzsb29nakUqmufx8AAAAAvZRoNpvNfjfRTf/lf/lfRqlUikQi0fpcOp2OZ8+eRUTEwsJCzM/Px+/8zu/0qcPLWVtbi0Kh0JrUWl1djfn5+Y6vr9VqcevWrajVapFOp2NnZ+fEukqlEjMzMxERkc1mY3Nz89K9R0RMT0/H3t5eTE1Nxe7ublfWvCofNyJufKN9zUffjHjlWs5VAgAAwNXoZzZw7d7CZzKZSKVS8YUvfCFu3boVzWYzdnZ2Yn9/P/b396NYLMbMzEx8+tOfjv/hf/gf4v333+93yx0rFAqxsLBwJMQ6TwgWEZHP51sh2sG2yJMcTIZFvJggO5g+AwAAABhW124i7N13341UKhX37t2LiIjnz59HqVSKzc3NKJVKUalUWrUHU2Pj4+Px7//9v+9Lv53K5/OxsbERERGpVCqePn167u2Kh6e8IiL29/fbrrGxsRH5fL71mvv7++fu+zgTYQAAADDaTIR1USaTiYmJidbzmzdvxhe+8IV466234m//9m9jZ2cnVldXY25uLm7evBnNZrMrAc9VyuVyrRAsIi58ZlexWGw9zmazZ65xMBEW8WJL5eEeAAAAAIbNtQvCbt26Fbdv32779YcPH8Y777wTz549i+3t7fjWt77Vww7PZ21tLUqlUuv56upqpNPpC691IJPJdHTN4dd6/PjxhV4XAAAAYBBcuyDsZz/7WTx48CD++q//uqP627dvx9e+9rUr7upiKpVKLCwstJ5nMplznwl2oFwuH3l+9+7djq47HJiZCAMAAACG2bULwubm5mJjYyPm5+ejXq/3u51LOTif68Abb7xx4bUOT5VFRMdTZcfrjgdqAAAAAMPi2gVht27diogXk17JZLLP3VxcpVI5EjqlUqkjZ3ad15MnT4487/SMsddee+3I862trQv3AAAAANBP1y4IW19fj2azGd/+9rf73cqlrK6uHnmezWYj4j/eyXFmZiYSiUSMj4/H7OxsLC8vR61WO3W9w3fLjLj4RNjOzk5H1wEAAAAMmmsXhKXT6dja2oqHDx/G3/3d3/W7nQs7fLB9RMTExETMzs5GPp+PjY2NVrBVq9WiXC5HoVCI8fHxU8/xOh6EXVS7sA0AAABgkN3odwNXIZPJRKlUinw+H7Ozs/Ho0aN+t3QulUrlpcDpnXfeiWKxGPfv329ta6xUKlEsFo+EZvl8PtbX11/aRnnRAOv4Fspnz55daJ3jqtVqTE9PX3qdxcXFWFxc7EJHAAAAQDsrKyuxsrJy6XWq1WoXurmYaxeETUxMxMzMTORyuXj99dfjgw8+iLt378YXv/jF+LM/+7N+t9eR49NbqVQqnj59+lIolU6nY3V1NWZnZ4/cXfLhw4eRzWY7PgfsPLo1EdZoNGJvb+/S6wz7DREAAABgWNTr9a68l++naxeE3blzJ0ql0pGD5tPpdLz55pvx5ptvxsLCQszPz8fv/M7v9K/JMxwPwubn59uGWvPz87G9vd2aDKvVavHo0aMoFoutmlQq1ZUQq1vh2tjYWExOTl56nWG+IQIAAAAMk2QyGVNTU5dep1qtRqPR6EJH53ftgrBMJhNbW1uRzWajXC5HpVI5csB7sViMYrEY6XQ6Xn/99fjCF74wcKHY8QPp7969e+Y1hULhyBbJ5eXlI0HYxMREV4KwiYmJS68RETE5ORm7u7tdWQsAAAC4et06nmh6erpvk2XXLgi7e/du5HK5uHfvXkREPH/+PEqlUmxubkapVGpNW+3s7MTS0lIsLS3F+Ph4/Pt//+/72fYRxwOrTqaw0ul0ZDKZI5Nw5XI5MplMx2t0q5frYiwR8dE3z64BAAAAhsO1u2tkJpOJ1157rfX85s2b8YUvfCHeeuut+Nu//dvY2dmJ1dXVmJubi5s3b0az2Yz9/f0+dvyymZmZC113586dI88Pb7E8/rVOp8OOH45/0d6GUSIR8cpY+4+EIAwAAACGxrWbCLt169aZX3/48GE8fPgwIiLee++9KJVKvWitY8enrjoNrY6HVIdDrNnZ2SNfq1QqrWmxdo5v08xmsx31AgAAADBorl0Qdl63b9+O27dv97uNI9pNdrVzPEA7fJ7XSWt2EoQdDuFSqVSk0+mOegEAAAAYNNdua+SBer0e3//+9+O//+//+/j+978f77//fr9b6tjxgOr4VFanDodWmUzmSFD25MmTjtbY2tpqPT4epgEAAAAMk2sZhH3729+O8fHxyOfzUSgUIp/Px8zMTPze7/1e/C//y//S7/Y6cngLYqdbN49voTweqN2/f7/1+PCh+u0crisUCh1dAwAAADCIrl0Q9tOf/jTm5+ej2Wy+9LG1tRXZbDa++MUv9rvNMx0OnSqVSkfnhB2eHDvpLK+FhYXW407CtcM16XTa+WAAAADAULt2QVixWIxsNhubm5uxs7MT29vbsb6+HvPz85FOp6PZbMY777wT/9l/9p/F3//93/e73VNls9kjWxsfPXp05jWHg6tisfjS1zOZzJEwa2Njo+166+vrrcemwQAAAIBhl2g2m81+N9FNd+7cOXKu1XGlUimKxWL89Kc/jd/93d+Nra2tSCaTPeywc+Vy+cjdHnd2dk49rL5UKkUul4uIiPn5+VhdXT2xrlKptO4umclkYnt7+8S6Wq0W4+PjERGtYLEbpqenY29vL6ampmJ3d7crawIAAADDo5/ZwLWbCDsIeU5zEOr85Cc/iUajEfPz8z3q7PwymcyRQCuXy524RbJWq7W2PR6/5rh0Ot2a9CqXy7G8vHxi3b179yLixZ0iD0+GAQAAAAyraxeE7e/vd1SXzWZja2srtra24n//3//3K+7q4ubn52NzczNSqVRUKpW4detWLC8vR7lcbgVZt27dikqlEvPz86dOeB02NzfXWvPgZgLlcjlqtVqUSqWYnZ2NcrkcmUwmnj59euRukwAAAADD6tptjfyLv/iL2N/fjzfffLOj+kqlEn/xF38Rf/VXf3XFnV3e2tparK+vx9bWVtRqtUilUq1D7BcWFk7dNtnO8vJyPH78uHUgfyqVijt37sTCwkLMzc11/XuwNRIAAABGWz+zgWsXhD1//jzGx8fj61//esdh2Ouvvx5vvfXWFXdGhCAMAAAARp0zwrro5s2b8a1vfSu+9a1vxX/1X/1X8Xd/93dnXtPpdkoAAAAAhte1C8IiIpaWluILX/hC/OQnP4l0Oh1f/OIX4+c///mJtU+fPo1yudzbBgEAAADouRv9buCqrK+vRz6fj3fffTfW19djfX09UqlUZLPZSKfT8dprr8XOzk6sra1dyVlYAAAAAAyWa3dG2HHLy8vx9a9/vfU8kUi0Hh9865VKJX7nd36n162NJGeEAQAAwGhzWP4Ve/78ebz55pvx7rvvRqVSaX0+k8nE22+/Hbdv3+5jd6Pl4I99bGwsJicn29YuLi7G4uJijzoDAAAALmtlZSVWVlba1lSr1Wg0Gn0Jwq7t1sjDbt68GcViMYrFYkS8OBfs1q1bfe5qtDUajdjb22tbU6/Xe9QNAAAA0A31ev3M9/v9dG2DsHq9Hslk8sSvCcH6r5OJsNN+fwAAAMBgSiaTMTU11bbmYCKsH67d1sjnz5/HnTt3olKpRKFQiDfffLPfLXGIM8IAAABgtPUzGxjr6av1wMOHD2NnZyeazWasr6+fWmfbHQAAAMBouXZbIyuVSmxvb8fW1lbcuXPn1LonT57ExsZG/NVf/VUPuwMAAACgX65dEDYzMxO3b98+806Q9+7di1qtFm+88UY8evSoR90BAAAA0C/XbmtkpVLpuPYLX/hC7OzsxM9//vOrawgAAACAgXDtgrB79+7FX//1X3dcv7CwYCIMAAAAYARcuyBsfn4+lpaW4u/+7u86qk+n01Eqla64KwAAAAD67doFYel0Oubm5iKdTnc0GVapVKJWq119YwAAAAD01bULwiIiVldX45/8k38S8/Pz8Xu/93vxb//tvz2xrl6vx8LCQqTT6R53CAAAAECvXbu7Rh742c9+Fv/sn/2z2Nrairm5uYiIyGQykU6nY2JiIiqVSmtL5Pz8fD9bBQAAAKAHEs1ms9nvJq7SwsJCvP322xERkUgkjnyt2WzG+Ph4PH36NJLJZD/aGznT09Oxt7cXU1NTsbu72+92AAAAgB7rZzZwLbdGHra6uho7Ozvxta99LW7duhXNZjOazWbcvHkz5ubmolKpCMEAAAAARsC1nwhjsJgIAwAAgNFmIgwAAAAArtjAH5Zfr9ejUCjE1tZWTExMxOzsbDx48CD+8//8P+93awAAAAAMkYEPwv74j/843n333dbzzc3N+Na3vhUzMzPx+uuvx5/92Z/1sTsAAAAAhsXAb40slUqtx7dv3479/f1oNBrxV3/1V/G//W//W7z22mvxxhtvRL1e72OXAAAAAAy6gQ/C7t27F81mM1KpVPzsZz+LmzdvRkRENpuNd955J3Z2dqLRaMStW7fiz//8z/vcLQAAAACDauCDsPX19dje3o5KpRLJZPKlr6dSqSgWi1GpVOLjjz+O1157Lf76r/+6D50CAAAAMMgSzWaz2e8muqlSqcTXv/71eO+992JtbS3+i//iv+h3SxxycIvUsbGxmJycbFu7uLgYi4uLPeoMAAAAuKyVlZVYWVlpW1OtVqPRaMTU1FTs7u72qLMXBv6w/PNKp9PxzjvvRLlcjvv378fv/u7vxvr6evwn/8l/0u/WOKTRaMTe3l7bGue+AQAAwHCp1+tnvt/vp2sXhEVEvP/++/H+++/H3NxcLC8vRyqVirW1tfgX/+Jf9Ls1/oNOJsJO2goLAAAADK5kMhlTU1Ntaw4mwvph6LdGvv/++1EqlWJ7eztKpVJUKpWXaprNZiQSiZidnY2f/vSnpsP66GBrZD/GHwEAAID+62c2MJQTYT/72c9ifX093nnnnajVake+dlqu12w2Y2trK37nd34nvv3tb8cf/uEf9qBTAAAAAAbF0ARhP/vZz2J1dTU2NjZanzsIvRKJxEsBWCaTiTt37sTs7GzcuXMnbt++HRERGxsb8S/+xb+IJ0+exJtvvtm7bwAAAACAvhr4IOz73/9+FAqF1pbHkya+ms1mZLPZyOVykc1mW6HXSebm5iKbzcb9+/fj93//92NjY8NWSQAAAIARMPBB2NzcXGviK5FItD6fTqdjbm4ucrlc3Lt371xrplKp+MlPfhLLy8uRyWSiXC4LwwAAAACuuYEPwjKZTLz33nsR8WLya2lpKRYWFuLWrVuXXntpaSkymYwwDC6g2YxonHGrjbFExKH8GgAAAPpq4IOwdDod5XI5crlcvPPOO3Hz5s2urp/NZuPRo0fxz/7ZP4snT550dW24zhrNiBvfaF/z0TcjXhGEAQAAMCDG+t3AWe7evRvj4+PxP//P/3PXQ7ADc3NzsbOzE1/84hevZH0AAAAA+m/gg7CDuz9epadPn0atVov19fX4+c9/fqWvBQAAAEB/DHwQdufOnRPvFNlN+Xy+9fjx48dX+loAAAAA9MfAB2E3b96MQqFwpa9RqVRad6R87bXXrvS1AAAAAOiPgQ/CIiLu3bt3pet/61vfimazGZlMJubn56/0tQAAAADoj6EIwq7a/Px8NBqNePLkSSSTyX63AwAAAMAVEIQBAAAAMBIEYQAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAADASbvS7AUZTtVqN6enptjWLi4uxuLjYo44AAACAy1pZWYmVlZW2NdVqtUfdvEwQRl80Go3Y29trW1Ov13vUDQAAANAN9Xr9zPf7/SQIoy/GxsZicnKybU0ymexRNwAAAEA3JJPJmJqaaltTrVaj0Wj0qKOjEs1ms9mXV2YkTU9Px97eXkxNTcXu7m6/2+ESPm5E3PhG+5qPvhnxipMIAQAAOKSf2YC3qMCV+d57/e4AAAAA/iNBGHAhnYRcX90QhgEAADA4BGHAuT3/MOJPf9hZ7es/iKh/eKXtAAAAQEcEYcC5fbcc8at/6Kz2l7+J+E75avsBAACATgjCromZmZlIJBKxsbFx7muXl5cjl8vF+Ph4JBKJmJmZiXw+H6VS6Qo65Tr40S/OV//jc9YDAADAVRCEXQOFQiEqlcq5ryuVSjE+Ph6FQiEiItbX12NnZyeKxWKUy+XI5XKRy+WiVqt1uWOG3f6vr7YeAAAArsKNfjfA5ZRKpVheXr7QdblcLiIi5ufnY3V1tfW1dDodc3NzMTs7G6VSKWZnZ2N7eztSqVS32mbIjX/yausBAADgKpgIG2K1Wi3y+fylrkun00dCsMPW19cjIqJSqVzodbi+PveZ89V/9pz1AAAAcBUEYUPs4cOHMTExce5JrXw+39rueLAt8iQHk2ERLybI1tbWLtoq18yXMxG//Vud1X7qExFfyVxtPwAAANAJQdiQWltbi42NjdbUVqcqlcqRQ/Dv37/ftv7Bgwetx+1CM0bLzVcj/vIPOqt96/MRyVevtB0AAADoiCBsCFUqlVhYWIilpaXIZM43alMsFluPs9nsmdNkBxNhES+2VF7krpRcT1+6fXbNd+Y6qwMAAIBeEIQNoXw+H5lM5kio1anD2xs7DdHS6XTr8ePHj8/9moyuPxKCAQAAMEDcNXLIFAqFKJfLsbOzc+5ry+Xyked3797t6LpMJhOVSiUiwkQYAAAAMLRMhA2Rcrkcy8vLsbq6emRKq1OHzwaLiI7XOF53PFADAAAAGAaCsCFy7969mJubi/n5+Qtd/+TJkyPPO73b5GuvvXbk+dbW1oVeHwAAAKCfBGFDIp/PR0TE22+/feE1DrY3HrjoRNhFtmUCAAAA9JszwobAxsZGbGxsxObmZsdTXCc5HoRdVK1W68o6AAAAAL1kImzA1Wq1yOfzMT8/H9ls9tJrXcTx8O3Zs2eX6gMAAACgH0yEDbh79+5FOp2O1dXVfrfS0o2JsGq1GtPT05deZ3FxMRYXFy+9DgAAANDeyspKrKysXHqdarXahW4uRhA2wJaXl6NcLsf29nZX1kulUl0JsS6zPfNAo9GIvb29S69Tr9cvvQYAAABwtnq93pX38v0kCBtQ5XI5CoVCFIvFyGQyXVlzYmKiK0HYxMTEpdcYGxuLycnJS6+TTCYvvQYAAABwtmQyGVNTU5dep1qtRqPR6EJH5ycIG1D5fD4ymUwsLS11bc2LTnIdD8+6MRE2OTkZu7u7l14HAAAA6I1uHU80PT3dt8kyQdgAWl5ejkqlEtlsNvL5/Jn1h4OqR48exePHj1vPHzx4EHNzcxERcefOnSiXy0eu6yTUOn44/szMzJnXAAAAAAwaQdgA+uCDDyIiolQqnfvacrl8JOxKp9OtIGx2dvZIbaVS6Wjb5c7OzpHnl717JYyCZjOi0WxfM5aISCR60w8AAACCsJFy586dI887DcIOT5ylUqlIp9Pdbo0hNJaI+OibZ9eMqkYz4sY32td89M2IV0b4ZwQAANBrY/1ugJcVi8VoNpsdfxwOptbX1498rVgstr6WyWSObIV88uRJR/1sbW21Hh8P0xhdiUTEK2PtP0w7AQAAMEgEYSPm/v37rceHt1C2c7iuUCh0vScAAACAXhCEjZiFhYXW407OIDtck06nnQ8GAAAADC1B2IjJZDJHwqyNjY229evr663HpsEAAACAYSYIG0Grq6utx48ePTq1rlarxdraWkS8uFPk/Pz8lfcGAAAAcFUEYSMonU63Jr3K5XIsLy+fWHfv3r2IeHGnyMOTYQAAAADDSBA2oubm5mJzczNSqVQUCoXI5/NRLpejVqtFqVSK2dnZKJfLkclk4unTp0fuNgkAAAAwjG70uwEub2dn50LXZbPZ2N/fj+Xl5Xj8+HHcu3cvarVapFKpuHPnTqyvr8fc3FyXuwUAAADoD0EYsbS0FEtLS/1uAwAAAOBK2RoJAAAAwEgQhAH0yffe63cHAAAAo0UQBnAFOgm5vrohDAMAAOglQRhAlz3/MOJPf9hZ7es/iKh/eKXtAAAA8B8IwgC67LvliF/9Q2e1v/xNxHfKV9sPAAAAL7hrJH1RrVZjenq6bc3i4mIsLi72qCPonh/94nz1P/5FxL/8p1fTCwAAQC+trKzEyspK25pqtdqjbl4mCKMvGo1G7O3tta2p1+s96ga6a//XV1sPAAAwqOr1+pnv9/tJEEZfjI2NxeTkZNuaZDLZo26gu8Y/ebX1AAAAgyqZTMbU1FTbmmq1Go1Go0cdHSUIoy8mJydjd3e3323AlfjcZyJ+8u86r//sZ66uFwAAgF7q5Jij6enpvk2NOSwfoMu+nIn47d/qrPZTn4j4SuZq+wEAAOAFQRhAl918NeIv/6Cz2rc+H5F89UrbAQAA4D8QhAFcgS/dPrvmO3Od1QEAANAdgjCAPvkjIRgAAEBPCcIAAAAAGAnuGglAzzWbEY1m+5qxREQi0Zt+AACA0SAIA6DnGs2IG99oX/PRNyNeEYQBAABdZGskAAAAACNBEAYAAADASBCEAQAAADASnBEGcAXGEi/OuDqrBgAAgN4RhAFcgUTCQe8AAACDxtZIAAbS997rdwcAAMB1IwgDoOc6Cbm+uiEMAwAAuksQBkBPPf8w4k9/2Fnt6z+IqH94pe0AAAAjRBAGQE99txzxq3/orPaXv4n4Tvlq+wEAAEaHIAyAnvrRL85X/+Nz1gMAAJxGEAZAT+3/+mrrAQAATnOj3w0wmqrVakxPT7etWVxcjMXFxR51BPTK+Cevth4AAOiflZWVWFlZaVtTrVZ71M3LBGH0RaPRiL29vbY19Xq9R90AvfS5z0T85N91Xv/Zz1xdLwAAQHfV6/Uz3+/3kyCMvhgbG4vJycm2NclkskfdAL305UzE1/+nzg7M/9QnIr6SufqeAACA7kgmkzE1NdW2plqtRqPR6FFHRyWazWazL6/MSJqeno69vb2YmpqK3d3dfrcD9Ml3tiO+unF23d/cj/jS7avvBwAA6J1+ZgMOyweg5zoJt74zJwQDAAC6SxAGwED6IyEYAADQZYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAk3+t0AAKNnLBHx0TfPrgEAAOgmQRgAPZdIRLwi6AIAAHrM1kgAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAmCMAAAAABGwo1+N8BoqlarMT093bZmcXExFhcXe9QRAAAAcFkrKyuxsrLStqZarfaom5cJwuiLRqMRe3t7bWvq9XqPugEAAAC6oV6vn/l+v58EYfTF2NhYTE5Otq1JJpM96gYAAADohmQyGVNTU21rqtVqNBqNHnV0VKLZbDb78sqMpOnp6djb24upqanY3d3tdzsAAABAj/UzG3BYPgAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQdiQKJfLsbCwEDMzM5FIJCKRSMTMzEwUCoWo1WoXXnd5eTlyuVyMj4+31szn81EqlbrXPAAAAMAAEIQNuFqtFvl8PmZnZ2NtbS0qlUrra5VKJZaXl2N8fDzW1tbOtW6pVIrx8fEoFAoREbG+vh47OztRLBajXC5HLpeLXC53qZANAAAAYJDc6HcDnK5Wq8Xs7OyR8Os0CwsLsb29Haurq2fWlkqlyOVyERExPz9/5Jp0Oh1zc3MxOzsbpVIpZmdnY3t7O1Kp1IW/DwAAAIBBYCJsgOXz+ahUKpHJZFoTWzs7O7G+vh5LS0sv1a+trcXGxkbbNQ8mzCJehF6nBWfr6+sR8WLq7KAegN5oNiM+brT/aDb73SUAAAyfRLPp/5QeRGtra7GwsBBLS0tRLBZPrDkIqcrlcutzqVQq9vf3T103l8u1zv9aXV2N+fn5U2vz+XwrWDurtlPT09Oxt7cXU1NTsbu7e+n1AK6jjxsRN77Rvuajb0a84n/OAgBgCPUzG/B/Qg+oYrEY2Wz21BAs4sVE18Hk1oFarXbqQfeVSuXI1+7fv9+2hwcPHrQeH5wlBgAAADCsBGEDqFwuR6VSeSnkOkk6nX4pLDs8IXbY4bpsNnvmuV9zc3Otx7Va7cxtlwD0zvfe63cHAAAwfARhA+jx48cxPz/f8QH12Wz2yPMPPvjgxLrDd5bMZDIdrZ1Op4/0BcDV6yTk+uqGMAwAAM7LXSMH0IMHD44EUGc5HmrNzMy8VHN8Suzu3bsdr31w10oTYQBX7/mHEX/6w85qX/9BxOf+cUTy1SttCQAArg0TYQMok8l0PA0W8WLb4mEnhWjHzw3rNGg7XnfatksAuuO75Yhf/UNntb/8TcR3/GcZAAA6Jgi7Bg4mtg4c3yoZEfHkyZMjzzsN2l577bUjz7e2ts7XHADn8qNfnK/+x+esBwCAUSYIuwYOh1Pz8/Mn1hwPyy46Ebazs3PO7gA4j/1fX209AACMMkHYNbC6utp6XCgUTqw5HoRd1PFtmAB01/gnr7YeAABGmSBsyFUqlda5XcVi8dRJr4sGWMe3UD579uxC6wDQmc995nz1nz1nPQAAjDJ3jRxyxWIxIl5sYVxaWrry1+vWRFi1Wo3p6elLr7O4uBiLi4td6AhgMHw5E/H1/6mzA/M/9YmIr2TOrgMAgG5YWVmJlZWVS69TrVa70M3FCMKGWLlcjrW1tUilUrG5udm2NpVKdSXEOs/dLNtpNBqxt7d36XXq9XoXugEYHDdfjfjLP4j46sbZtW99PiL56pW3BAAAEfHiPXg33sv3kyBsiD18+DAiIn7605+eefj9xMREV4KwiYmJS68RETE2NhaTk5OXXieZTHahG4DB8qXbZwdh35l7UQcAAL2STCZjamrq0utUq9VoNBpd6Oj8BGFDamFhIcrlcqyvr0cmc/a+mItOch0Pz7o1ETY5ORm7u7tdWQtgFP2REAwAgB7r1vFE09PTfZssc1j+EFpbW4u1tbVYXV2Nubm5jq65c+fOkeedTocdPxx/Zmamo+sAAAAABo2JsCFTKpViYWEhVldXY35+vuPrZmdnjzyvVCodTZLt7OwceZ7NZjt+TQAuZiwR8dE3z64BAADOx0TYECmXy5HL5aJYLJ4rBIt4eSKsUql0dN3hybFUKnXmWWQAXF4iEfHKWPuPhCAMAADOTRA2JCqVSty7dy+WlpZiaWnp3NdnMpkj53s9efKko+u2trZaj4+HaQAAAADDRBA2BCqVSszOzsb8/HwUi8WOr1leXj7yufv377cel8vljtY5XFcoFDq6BgAAAGAQCcIGXK1Wi1wuF/fv3+84BIuIyOfzL53ntbCw0HpcKpXOXONwTTqddj4YAAAAMNQclj/AarVazM7ORjqdjkKh0NG5XpVKpTW5dfww/EwmE9lsthVwbWxstL3r5Pr6euuxaTAAAABg2CWazWaz301wstnZ2Y63MB532l0lK5VKzMzMRMSLYGx7e/vE62u1WoyPj0fEiztFbm5uXqiP46anp2Nvby+mpqZid3e3K2sCAAAAw6Of2YCtkQPqMiFYRJx6V8l0Ot2a9CqXyy+dI3bg3r17EfHiTpGHJ8MAAAAAhpUgbADl8/krCcEOzM3NxebmZqRSqSgUCq3Xq9VqUSqVWiFcJpOJp0+fHrnbJAAAAMCwckbYAOrFBFY2m439/f1YXl6Ox48fx71796JWq0UqlYo7d+7E+vp62/PDAAAAAIaNM8LoKWeEAQAAwGhzRhgAAAAAXDFBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIyEG/1ugNFUrVZjenq6bc3i4mIsLi72qCMAAADgslZWVmJlZaVtTbVa7VE3LxOE0ReNRiP29vba1tTr9R51AwAAAHRDvV4/8/1+PwnC6IuxsbGYnJxsW5NMJnvUDQAAANANyWQypqam2tZUq9VoNBo96uioRLPZbPbllRlJ09PTsbe3F1NTU7G7u9vvdgAAAIAe62c24LB8AAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAmCMAAAAABGgiAMAAAAgJFwo98NAACcR7MZ0WhGPP8w4rvvRfyPv4jY/3XE+CcjPvuZiH9++8XjRKLfnQIAMGgEYQDAUGk0I2584+Svbf5txH/z44j/31zEV2Z72xcAAIPP1kgAYKh8772za7660VkdAACjRRAGAAyN5x9G/OkPO6t9/QcR9Q+vtB0AAIaMIAwAGBrfLUf86h86q/3lbyK+U77afgAAGC6CMABgaPzoF+er//E56wEAuN4EYQDA0Nj/9dXWAwBwvQnCAIChMf7Jq60HAOB6E4QBAEPjc585X/1nz1kPAMD1JggDAIbGlzMRv/1bndV+6hMRX8lcbT8AAAwXQRgAMDRuvhrxl3/QWe1bn49Ivnql7QAAMGRu9LsBRlO1Wo3p6em2NYuLi7G4uNijjgAYFl/ORCQi4k9+GPGrf3j567/9Wy9CsC/d7nVnAACsrKzEyspK25pqtdqjbl4mCKMvGo1G7O3tta2p1+s96gaAYZJIRHx5NuL/+X+L+G454se/eHF3yPFPvjgT7CsZk2AAAP1Sr9fPfL/fT4Iw+mJsbCwmJyfb1iSTyR51A8AwuvlqxL/8py8+AAAYDMlkMqamptrWVKvVaDQaPeroqESz2Wz25ZUZSdPT07G3txdTU1Oxu7vb73YAAACAHutnNuCwfAAAAABGgiAMAAAAgJEgCAMAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAmCMAAAAABGgiAMAAAAgJEgCAMAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRcKPfDTCaqtVqTE9Pt61ZXFyMxcXFHnUEAAAAXNbKykqsrKy0ralWqz3q5mWCMPqi0WjE3t5e25p6vd6jbgAAAIBuqNfrZ77f7ydBGH0xNjYWk5OTbWuSyWSPugGA6+f5hxHfKUf8+BcR+7+OGP9kxOc+E/HlTMTNV/vdHQBwXSWTyZiammpbU61Wo9Fo9KijoxLNZrPZl1dmJE1PT8fe3l5MTU3F7u5uv9sBgGvpb96L+JMfRPzyNy9/7VOfiPirz0f889u97goA4IV+ZgMmwgAArpG/eS/iy++c/vVf/ubF1xMR8SVhGAAwYtw1EgDgmnj+4YtJsE68/oOI+odX2Q0AwOARhAEAXBPfLZ+8HfIkv/zNizPEAABGiSAMAOCa+NEvzlf/43PWAwAMO0EYsby8HLlcLsbHxyORSMTMzEzk8/kolUr9bg0AOIf9X19tPQDAsBOEjbBSqRTj4+NRKBQiImJ9fT12dnaiWCxGuVyOXC4XuVwuarVafxsFADoy/smrrQcAGHaCsBFVKpVaIdf8/Hxsbm5GNpuNdDodc3NzsbOzE5lMJkqlUszOzgrDAGAIfO4z56v/7DnrAQCGnSBsBNVqtcjn8xERkU6nY3V19cS69fX1iIioVCqtegBgcH05E/GpT3RW+6lPRHwlc7X9AAAMGkHYCMrn860Jr4NtkSc5mA6LeDFBtra21ov2AIALuvlqxF99vrPatz4fkXz1KrsBABg8grARU6lUjhyCf//+/bb1Dx48aD1uF5oBAIPhn9+O+Jv7p0+GfeoTL77+pdu97QsAYBDc6HcD9FaxWGw9zmazkUql2tYfTIRFvNhSubGxceRzAMDg+dLtiM/+44jvliN+/IsXd4cc/+SLM8G+kjEJBgCMLkHYiDm8vTGT6exgkHQ6HZVKJSIiHj9+LAgDgCFw89WIf/lPX3wAAPCCrZEjpFwuH3l+9+7djq47HJhtbGx0tScAAACAXhGEjZDDZ4NFvJj06sTxuuOBGgAAAMAwEISNkCdPnhx5ftb5YAdee+21I8+3tra61RIAAABAzwjCRsjBOV8HLjoRtrOz07WeAAAAAHpFEDZCjgdhF1Wr1bqyDgAAAEAvuWvkCLlogHV8C+WzZ88u3Uu1Wo3p6elLr7O4uBiLi4uXXgcAAABob2VlJVZWVi69TrVa7UI3FyMI49y6MRHWaDRib2/v0uvU6/VLrwEAAACcrV6vd+W9fD8JwkZIKpXqSojV6SH77YyNjcXk5OSl10kmk5deAwAAADhbMpmMqampS69TrVaj0Wh0oaPzE4SNkImJia4EYRMTE5deY3JyMnZ3dy+9DgAAANAb3TqeaHp6um+TZQ7LHyEXneQ6Hp51YyIMAAAAoNcEYSPkzp07R553Oh12/HD8mZmZbrUEAAAA0DOCsBEyOzt75HmlUunoup2dnSPPs9ls13oCAAAA6BVB2Ag5PhHWaRB2eHIslUpFOp3uZlsAAAAAPSEIGyGZTObI+V5Pnjzp6Lqtra3W4+NhGgAAAMCwEISNmPv377cel8vljq45XFcoFLreEwAAAEAvCMJGzMLCQutxqVQ6s/5wTTqddj4YAHAtPP8w4t/8rxG///+N+L3/z4v/9//9v774PABwfQnCRkwmkzkSZm1sbLStX19fbz02DQYAXAd/817E9KOIf/WjiJ/8u4gnuy/+3//Xj158/m/e63eHAMBVEYSNoNXV1dbjR48enVpXq9VibW0tIl7cKXJ+fv7KewMAuEp/817El9+J+OVvTv76L3/z4uvfE4YBwLUkCBtB6XS6NelVLpdjeXn5xLp79+5FxIs7RR6eDAMAGEbPP4z4kx90Vvv6DyLqtkkCwLUjCBtRc3Nzsbm5GalUKgqFQuTz+SiXy1Gr1aJUKsXs7GyUy+XIZDLx9OnTI3ebBAAYRt8tnz4JdtwvfxPxnc7uKwQADBFB2AjLZrOxv78fxWIxKpVK3Lt3L8bHxyOfz8fExESsr6/H9va2EAwAuBZ+9Ivz1f/4nPUAwOC70e8G6L+lpaVYWlrqdxsAAFdq/9dXWw8ADD4TYQAAjITxT15tPQAw+ARhAACMhM995nz1nz1nPQAw+ARhAACMhC9nIj71ic5qP/WJiK9krrYfAKD3BGEAAIyEm69G/NXnO6t96/MRyVevshsAoB8EYQAAjIx/fjvib+6fPhn2qU+8+PqXbve2LwCgN9w1kr6oVqsxPT3dtmZxcTEWFxd71BEAMCq+dDvis/844rvliB//4sXdIcc/+eJMsK9kTIIBwGWsrKzEyspK25pqtdqjbl4mCKMvGo1G7O3tta2p1+s96gYAGDU3X434l//0xQcA0D31ev3M9/v9JAijL8bGxmJycrJtTTKZ7FE3AAAAQDckk8mYmppqW1OtVqPRaPSoo6MSzWaz2ZdXZiRNT0/H3t5eTE1Nxe7ubr/bAQAAAHqsn9mAw/IBAAAAGAmCMAAAAABGgiAMAAAAgJEgCAMAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAmCMAAAAABGgiAMAAAAgJEgCAMAAABgJAjCAAAAABgJN/rdAKOpWq3G9PR025rFxcVYXFzsUUcAAADAZa2srMTKykrbmmq12qNuXiYIoy8ajUbs7e21ranX6z3qBgAAAOiGer1+5vv9fhKE0RdjY2MxOTnZtiaZTPaoGwAAAKAbkslkTE1Nta2pVqvRaDR61NFRiWaz2ezLKzOSpqenY29vL6ampmJ3d7ff7QAAcEyzGdFoRjz/MOK770X8j7+I2P91xPgnIz77mYh/fvvF40Si350CMKz6mQ2YCAMAAFoazYgb3zj5a5t/G/Hf/Dji/zcX8ZXZ3vYFAN3grpEAAEDL9947u+arG53VAcCgEYQBAAAR8WI75J/+sLPa138QUf/wStsBgK4ThAEAABER8d1yxK/+obPaX/4m4jvlq+0HALpNEAYAAERExI9+cb76H5+zHgD6TRAGAABExIu7Q15lPQD0myAMAACIiIjxT15tPQD0myAMAACIiIjPfeZ89Z89Zz0A9JsgDAAAiIiIL2cifvu3Oqv91CcivpK52n4AoNsEYQAAQERE3Hw14i//oLPatz4fkXz1StsBgK4ThAEAAC1fun12zXfmOqsDgEFzo98NAAAAg2MsEfHRNyOefxjxN+9F/I+/eHF3yPFPRvw/PhPx5dsRKYfkAzCkBGEAAEBLIhHxSiJi4v8S8a/+7y8+AOC6sDUSAAAAgJEgCAMAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICR4K6R9EW1Wo3p6em2NYuLi7G4uNijjgAAAIDLWllZiZWVlbY11Wq1R928TBBGXzQajdjb22tbU6/Xe9QNAAAA0A31ev3M9/v9JAijL8bGxmJycrJtTTKZ7FE3AAAAQDckk8mYmppqW1OtVqPRaPSoo6MSzWaz2ZdXZiRNT0/H3t5eTE1Nxe7ubr/bAQAAAHqsn9mAw/IBAAAAGAmCMAAAAABGgiAMAAAAgJEgCAMAAABgJAjChkC5XI6FhYWYmZmJRCIRiUQiZmZmolAoRK1Wu/C6y8vLkcvlYnx8vLVmPp+PUqnUveYBAAAABoQgbIDVarXI5/MxOzsba2trUalUWl+rVCqxvLwc4+Pjsba2dq51S6VSjI+PR6FQiIiI9fX12NnZiWKxGOVyOXK5XORyuUuFbAAAAACD5ka/G+BktVotZmdnj4Rfp1lYWIjt7e1YXV09s7ZUKkUul4uIiPn5+SPXpNPpmJubi9nZ2SiVSjE7Oxvb29uRSqUu/H0AAAAADAoTYQMqn89HpVKJTCbTmtja2dmJ9fX1WFpaeql+bW0tNjY22q55MGEW8SL0Oi04W19fj4gXU2cH9QAAAADDThA2gNbW1qJUKsXS0lJsb2/H3NxcpNPp1sRWsViMnZ2dyGQyR657+PBh23Xz+Xxru+PBtsiTHLxOxIsJsvNuvQQAAAAYRIlms9nsdxMcNTMzE+l0OjY3N9vWVSqVmJmZOfK5zc3NyGazZ9bu7++33fK4sbHRmgZLpVKxv79/ju/gdNPT07G3txdTU1Oxu7vblTUBAACA4dHPbMBE2IApl8tRqVRa2xPbSafTUSwWX7r+JIfrstnsmed+HUyERbzYUnnWtksAAACAQScIGzCPHz+O+fn5jg+oPz799cEHH5xYd3h74/EtladJp9NH+gIAAAAYZu4aOWAePHhwJIA6y/FQ6/hWyYiXp8Tu3r3b8doHd600EQYAAAAMOxNhAyaTyXQ8DRYRrcPvD5wUopVKpTNrTnK87rRtlwAAAADDQBA25A4mtg6cdFD+kydPjjzvNGh77bXXjjzf2to6X3MAAAAAA0QQNuQOh1Pz8/Mn1hwPyy46Ebazs3PO7gAAAAAGhyBsyK2urrYeFwqFE2uOB2EXdXwbJgAAAMAwcVj+EKtUKq1zu4rF4qmTXhcNsI5voXz27NmF1jlJtVqN6enpS6+zuLgYi4uLXegIAAAAaGdlZSVWVlYuvU61Wu1CNxcjCBtixWIxIl5sYVxaWrry1+vmRFij0Yi9vb1Lr1Ov17vQDQAAdKbZjGg029eMJSISid70A9BL9Xq9K+/l+0kQNqTK5XKsra1FKpWKzc3NtrWpVKorIdZ57mZ5lrGxsZicnLz0OslksgvdAABAZxrNiBvfaF/z0TcjXhGEAddQMpmMqampS69TrVaj0Wh0oaPzE4Sdw9raWiwsLHR1zUwmE9vb2+e+7uHDhxER8dOf/vTMw+8nJia6EoRNTExceo0Dk5OTsbu727X1AAAAgKvVreOJpqen+zZZ5rD8IbSwsBDlcjnW19cjk8mcWX/RSa7j4Vk3J8IAAOC6+t57/e4AgNOYCDuHbDYb6+vrXV3zvOHS2tparK2txerqaszNzXV0zZ07d1qH6ke8CLg6ed3jh+PPzMycq1cAALhuOgm5vroR8cpYxJduX30/AJyPIOwc0un0mdsQr1KpVIqFhYVYXV2N+fn5jq+bnZ098rxSqXQ0Sbazs3PkeTab7fg1AQDgunn+YcSf/rCz2td/EPG5fxyRfPVKWwLgnGyNHBLlcjlyuVwUi8VzhWARLybCDqtUKh1dd3hrZCqV6msICAAA/fbdcsSv/qGz2l/+JuI75bPrAOgtQdgQqFQqce/evVhaWoqlpaVzX5/JZI5shXzy5ElH121tbbUeHw/TAABg1PzoF+er//E56wG4eoKwAVepVGJ2djbm5+ejWCx2fM3y8vKRz92/f7/1+PB5Ye0crisUCh1dAwAA19X+r6+2HoCrJwgbYLVaLXK5XNy/f7/jECwiIp/Pv3Se18LCQutxqVQ6c43DNel02vlgAACMvPFPXm09AFfPYfkDqlarxezsbKTT6SgUCh2d61WpVFqTW8cPw89kMpHNZlsB18bGRtu7Th6+O6ZpMAAAiPjcZyJ+8u86r//sZ66uFwAuJtFsNpv9boKXzc7OdryF8bjT7ipZqVRiZmYmIl4EY9vb2ydeX6vVYnx8PCJe3Clyc3PzQn2cZHp6Ovb29mJqaip2d3e7ti4AAFy15x9GTL3Z2YH5n/pExN4b7hoJcJJ+ZgO2Rg6gy4RgEXHqXSXT6XRr0qtcLr90jtiBe/fuRcSLO0UengwDAIBRdvPViL/8g85q3/q8EAxgEAnCBkw+n7+SEOzA3NxcbG5uRiqVikKh0Hq9Wq0WpVKpFcJlMpl4+vTpkbtNAgDAqPvS7bNrvjPXWR0AveeMsAHTiwmsbDYb+/v7sby8HI8fP4579+5FrVaLVCoVd+7cifX19bbnhwEAAKf7IyEYwMAShI2wpaWlWFpa6ncbAAAAAD0hCAMAAOjQWCLio2+eXQPAYBKEAQAAdCiRiHhF0AUwtByWDwAAAMBIEIQBAAAAMBIEYQAAAACMBGeE0RfVajWmp6fb1iwuLsbi4mKPOgIAAAAua2VlJVZWVtrWVKvVHnXzMkEYfdFoNGJvb69tTb1e71E3AAAAQDfU6/Uz3+/3kyCMvhgbG4vJycm2NclkskfdAAAAAN2QTCZjamqqbU21Wo1Go9Gjjo5KNJvNZl9emZE0PT0de3t7MTU1Fbu7u/1uBwAAAOixfmYDDssHAAAAYCTYGgkAAEBXNJsRjTP2HI0lIhKJ3vQDcJwgDAAAgK5oNCNufKN9zUffjHhFEAb0ia2RAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAPfO99/rdATDKBGEAAAB0RSch11c3hGFA/wjCAAAAuLTnH0b86Q87q339BxH1D6+0HYATCcIAAAC4tO+WI371D53V/vI3Ed8pX20/ACcRhAEAAHBpP/rF+ep/fM56gG4QhAEAAHBp+7++2nqAbhCEAQAAcGnjn7zaeoBuEIQBAABwaZ/7zPnqP3vOeoBuEIQBAABwaV/ORPz2b3VW+6lPRHwlc7X9AJzkRr8bYDRVq9WYnp5uW7O4uBiLi4s96ggAALiMm69G/OUfRHx14+zatz4fkXz1ylsC+mBlZSVWVlba1lSr1R518zJBGH3RaDRib2+vbU29Xu9RNwAAQDd86fbZQdh35l7UAddTvV4/8/1+PwnC6IuxsbGYnJxsW5NMJnvUDQAA0Ct/JASDay2ZTMbU1FTbmmq1Go1Go0cdHZVoNpvNvrwyI2l6ejr29vZiamoqdnd3+90OAADQRR83Im58o33NR9+MeMVp1TDS+pkN+M8PAAAAACNBEAYAAADASBCEAQAAADASHJYPAABAV4wlXpwBdlYNQL8IwgAAAOiKRCLiFUEXMMBsjQQAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIAwAAACAkXCj3w0AAADAKGg2IxrN9jVjiYhEojf9wCgShAEAAEAPNJoRN77Rvuajb0a8IgiDK2NrJAAAAAAjQRAGAAAAwEiwNZK+qFarMT093bZmcXExFhcXe9QRAAAAcFkrKyuxsrLStqZarfaom5cJwuiLRqMRe3t7bWvq9XqPugEAAAC6oV6vn/l+v58EYfTF2NhYTE5Otq1JJpM96gYAAADohmQyGVNTU21rqtVqNBqNHnV0VKLZbJ5x81bonunp6djb24upqanY3d3tdzsAAAA983Gjw7tGOs2ba66f2YB/XgAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAwID43nv97gCuN0HYkJuZmYlEIhEbGxvnvnZ5eTlyuVyMj49HIpGImZmZyOfzUSqVrqBTAACA0dZJyPXVDWEYXCVB2BArFApRqVTOfV2pVIrx8fEoFAoREbG+vh47OztRLBajXC5HLpeLXC4XtVqtyx0DAACMpucfRvzpDzurff0HEfUPr7QdGFmCsCFVKpVieXn5QtcdhFzz8/OxubkZ2Ww20ul0zM3Nxc7OTmQymSiVSjE7OysMAwAA6ILvliN+9Q+d1f7yNxHfKV9tPzCqBGFDqFarRT6fv9R16XQ6VldXT6xbX1+PiIhKpXKh1wEAAOCoH/3ifPU/Pmc90BlB2BB6+PBhTExMRCqVOtd1+Xy+NeF1sC3yJAfTYREvJsjW1tYu2ioAAAARsf/rq60HOiMIGzJra2uxsbHRmtrqVKVSOXII/v3799vWP3jwoPW4XWgGAADA2cY/ebX1QGcEYUOkUqnEwsJCLC0tRSaTOde1xWKx9TibzZ45TXYwERbxYkvlRe5KCQAAwAuf+8z56j97znqgM4KwIZLP5yOTyRwJtTp1eHtjpyFaOp1uPX78+PG5XxMAAIAXvpyJ+O3f6qz2U5+I+Mr5Zh+ADgnChkShUIhyuXzuLZEREeXy0duN3L17t6PrDgdmJsIAAAAu7uarEX/5B53VvvX5iOSrV9oOjCxB2BAol8uxvLwcq6urR6a0OnX4bLCI6HiN43XHAzUAAAA696XbZ9d8Z66zOuBiBGFD4N69ezE3Nxfz8/MXuv7JkydHnnd6t8nXXnvtyPOtra0LvT4AAACd+aMRDsGazYiPG+0/ms1+d8mwu9HvBmgvn89HRMTbb7994TUqlcqR5xedCNvZ2blwDwAAANBOoxlx4xvtaz76ZsQrid70w/UkCBtgGxsbsbGxEZubmx1PcZ3keBB2UbVarSvrAAAAAPSDrZEDqlarRT6fj/n5+chms5de6yKOh2/Pnj27VB8AAAAA/WQibEDdu3cv0ul0rK6u9ruVlm5OhFWr1Zienr70OouLi7G4uNiFjgAAAIB2VlZWYmVl5dLrVKvVLnRzMYKwAbS8vBzlcjm2t7e7sl4qlepKiHWZ7ZnHNRqN2Nvbu/Q69Xq9C90AAAAAZ6nX6115L99PgrBzWFtbi4WFha6umclkjgRe5XI5CoVCFIvFyGQyXXmNiYmJrgRhExMTl2/mPxgbG4vJyclLr5NMJrvQDQAAAHCWZDIZU1NTl16nWq1Go9HoQkfnJwgbMPl8PjKZTCwtLXVtzYtOch0Pz7o5ETY5ORm7u7tdWw8AAAC4Wt06nmh6erpvk2WCsHPIZrOxvr7e1TUPh0vLy8tRqVQim81GPp8/89rDQdWjR4/i8ePHrecPHjyIubm5iIi4c+dOlMvlI9d1EmodPxx/ZmbmzGsAAAAABpUg7BzS6XSk0+krW/+DDz6IiIhSqXTua8vl8pGwK51Ot4Kw2dnZI7WVSqWjbZc7OztHnl/27pUAAACjbCwR8dE3z64Brs5Yvxvg6t25c+fI80ql0tF1hyfOUqnUlYaAAAAA110iEfHKWPuPhCAMrpQgbIAUi8VoNpsdfxwOptbX1498rVgstr6WyWSObIV88uRJR/1sbW21Hh8P0wAAAACGjSBsRNy/f7/1+PAWynYO1xUKha73BAAAANBLgrARsbCw0HrcyRlkh2vS6bTzwQAAAIChJwgbEZlM5kiYtbGx0bb+8N0xTYMBAAAA14EgbISsrq62Hj969OjUulqtFmtraxHx4k6R8/PzV94bAAAAnOV77/W7A4adIGyEpNPp1qRXuVyO5eXlE+vu3bsXES/uFHl4MgwAAACuSich11c3hGFcjiBsxMzNzcXm5makUqkoFAqRz+ejXC5HrVaLUqkUs7OzUS6XI5PJxNOnT4/cbRIAAACuwvMPI/70h53Vvv6DiPqHV9oO15ggbIjt7OxEs9mMZrMZc3NzHV+XzWZjf38/isViVCqVuHfvXoyPj0c+n4+JiYlYX1+P7e1tIRgAAAA98d1yxK/+obPaX/4m4jvlq+2H6+tGvxugf5aWlmJpaanfbQAAADDifvSL89X/+BcR//KfXk0vXG8mwgAAAIC+2v/11dbDAUEYAAAA0Ffjn7zaejggCAMAAAD66nOfOV/9Z89ZDwcEYQAAAEBffTkT8du/1Vntpz4R8ZXM1fbD9SUIAwAAAPrq5qsRf/kHndW+9fmI5KtX2g7XmLtG0hfVajWmp6fb1iwuLsbi4mKPOgIAAKCfvnQ74qsb7Wu+M/eijsG1srISKysrbWuq1WqPunmZIIy+aDQasbe317amXq/3qBsAAACGwR8JwQZevV4/8/1+PwnC6IuxsbGYnJxsW5NMJnvUDQAAANANyWQypqam2tZUq9VoNBo96uioRLPZbPbllRlJ09PTsbe3F1NTU7G7u9vvdgAAABgQHzcibnyjfc1H34x4xWnnQ6+f2YA/HwAAAABGgiAMAAAAgJEgCAMAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEbCjX43AAAAADCWiPjom2fXwGUIwgAAAIC+SyQiXhF0ccVsjQQAAABgJAjCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEbCjX43wGiqVqsxPT3dtmZxcTEWFxd71BEAAABwWSsrK7GystK2plqt9qiblwnC6ItGoxF7e3tta+r1eo+6AQAAALqhXq+f+X6/nwRh9MXY2FhMTk62rUkmkz3qBgAAAOiGZDIZU1NTbWuq1Wo0Go0edXRUotlsNvvyyoyk6enp2Nvbi6mpqdjd3e13OwAAAECP9TMbcFg+AAAAACNBEAYAAADASBCEAQAAADASBGEAAAAAjARBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAADASBGEAAAAAjARBGAAAAAAj4Ua/G2A0VavVmJ6ebluzuLgYi4uLPeoIAAAAuKyVlZVYWVlpW1OtVnvUzcsEYfRFo9GIvb29tjX1er1H3QAAAADdUK/Xz3y/30+CMPpibGwsJicn29Ykk8kedQMAAAB0QzKZjKmpqbY11Wo1Go1Gjzo6KtFsNpt9eWVG0vT0dOzt7cXU1FTs7u72ux0AAACgx/qZDTgsHwAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIOyaKJfLsbGxEcvLy1EqlTq6Znl5OXK5XIyPj0cikYiZmZnI5/MdXw8AAAAwTARhQ6pWq8Xy8nLMzs5GIpGIe/fuxZMnTyKTycSdO3faXlsqlWJ8fDwKhUJERKyvr8fOzk4Ui8Uol8uRy+Uil8tFrVbrwXcCAAAA0Bs3+t0A51Or1aJQKMTa2lpERGQymdjc3IxsNtvR9aVSKXK5XEREzM/Px+rqautr6XQ65ubmYnZ2NkqlUszOzsb29nakUqmufx8AAAAAvWYibIisra3FrVu3WiHY6upqbG9vdxyC1Wq1yOfzEfEi9Docgh22vr4eERGVSqVVDwAAADDsBGFDolAoxMLCQtRqtUin07GzsxPz8/PnWiOfz7e2Ox5sizzJwWRYxIsJsoPgDQAAAOiPZjPi40b7j2az310OvkSz6cc06PL5fGxsbERERCqViqdPn557u2KlUomZmZnW8/39/bZrbGxstKbBUqlU7O/vn7vvk0xPT8fe3l5MTU3F7u5uV9YEAACA6+7jRsSNb7Sv+eibEa8MwchTP7OBIfjxjLZcLtcKwSLiwmd2FYvF1uNsNnvmGgcTYREvtlQe7gEAAABgGAnCBtja2lqUSqXW89XV1Uin0xde60Amk+nomsOv9fjx4wu9LgAAAMCgEIQNqEqlEgsLC63nmUzm3GeCHSiXy0ee3717t6PrDgdmJsIAAACAYScIG1DH79b4xhtvXHitw1NlEdHxVNnxuuOBGgAAAMAwEYQNoEqlciR0SqVSR87sOq8nT54ced7pGWOvvfbakedbW1sX7gEAAACg3wRhA2h1dfXI82w2GxH/8U6OMzMzkUgkYnx8PGZnZ2N5eTlqtdqp61UqlSPPLzoRtrOz09F1AAAAAIPoRr8b4GWHD7aPiJiYmIjZ2dmXtibWarUol8tRLpejUCjE+vr6iZNjx4Owi2oXtgEAAAAMOhNhA6ZSqbwUOL3zzjuxsLAQ+/v70Ww2o9lsxs7OzkuH5+fz+RMPtb9ogHV8C+WzZ88utA4AAADAIDARNmCOT2+lUql4+vTpS6FUOp2O1dXVmJ2dPXJ3yYcPH0Y2m+34HLDz6OZEWLVajenp6Uuvs7i4GIuLi13oCAAAAGhnZWUlVlZWLr1OtVrtQjcXIwgbMMeDsPn5+bah1vz8fGxvb7e2U9ZqtXj06FEUi8VWTSqV6kqI1c1wrdFoxN7e3qXXqdfrXegGAAAAOEu9Xu/Ke/l+EoSdw9ra2pHpq27IZDKxvb3den78QPq7d++euUahUDhyrtjy8vKRIGxiYqIrQdjExMSl1zgwNjYWk5OTl14nmUx2oRsAAADgLMlkMqampi69TrVajUaj0YWOzk8QNmCOB1adTGGl0+nIZDJHDtMvl8uRyWQ6XqNbvXRqcnIydnd3u7YeAAAAcLW6dTzR9PR03ybLBGHnkM1mY319vatrHg+XZmZmLrTOnTt3jgRhlUqlFYQd/1qtVuso1Dp+OP5FewMAAAAYBIKwc0in05FOp6/0NY4HVJ1uaTweUh0OsWZnZ4987XBI1s7xbZrZbLajXgAAAAAG0Vi/G+CoO3fuHHl+/PD80xwP0A6f53XRNQ+HcKlU6spDQAAAAICrJAgbMMcntY5PZXXqcGiVyWSOBGVPnjzpaI2tra3W4+NhGgAAAMCwEYQNoMNbEEulUkfXHN9CeTxQu3//fuvx4fPC2jlcVygUOroGAAAAYFAJwgbQ4dCpUql0dE7Y4cmxk87yWlhYaD3uJFw7XJNOp50PBgAAAAw9QdgAymazR7Y2Pnr06MxrDgdXxWLxpa9nMpkjYdbGxkbb9Q7fHdM0GAAAAHAdCMIG1OEganl5ue0B96VSqfX1+fn5U+8Iubq62nrcLlyr1WqxtrYWES9Cufn5+XP1DgAAADCIBGEDKpPJHAmucrnciVska7Vaa9vj8WuOS6fTrYCtXC7H8vLyiXX37t2LiBd3ijwcyAEAAAAMM0HYAJufn4/Nzc1IpVJRqVTi1q1bsby8HOVyuRVk3bp1KyqVSszPz8f29vaZa87NzbXWLBQKkc/no1wuR61Wi1KpFLOzs1EulyOTycTTp0+P3G0SAAAAYJglms1ms99NcLa1tbVYX1+Pra2tqNVqkUqlWofYLywsHDlTrFPLy8vx+PHj1oH8qVQq7ty5EwsLCzE3N3cF30XE9PR07O3txdTUVOzu7l7JawAAAMB183Ej4sY32td89M2IV4Zg5Kmf2YAgjJ4ShAEAAMD5CcK6Ywh+PAAAAABweYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAGAk3+t0Ao6larcb09HTbmsXFxVhcXOxRRwAAAMBlraysxMrKStuaarXao25eJgijLxqNRuzt7bWtqdfrPeoGAAAA6IZ6vX7m+/1+EoTRF2NjYzE5Odm2JplM9qgbAAAAoBuSyWRMTU21ralWq9FoNHrU0VGJZrPZ7MsrM5Kmp6djb28vpqamYnd3t9/tAAAAwFD4uBFx4xvtaz76ZsQrQ3AafD+zgSH48QAAAADA5QnCAAAAABgJgjAAAAAARoIgDAAAAICRIAgDAAAAYCQIwgAAAAAYCYIwAAAAAEaCIAwAAACAkSAIAwAAAGAkCMIAAAAAroHvvdfvDgafIAwAAABgwHUScn11Qxh2FkEYAAAAwAB7/mHEn/6ws9rXfxBR//BK2xlqgjAAAACAAfbdcsSv/qGz2l/+JuI75avtZ5gJwgAAAAAG2I9+cb76H5+zfpQIwgAAAAAG2P6vr7Z+lAjCAAAAAAbY+Cevtn6UCMIAAAAABtjnPnO++s+es36UCMIAAAAABtiXMxG//Vud1X7qExFfyVxtP8PsRr8bYDRVq9WYnp5uW7O4uBiLi4s96ggAAAAG081XI/7yDyK+unF27Vufj0i+euUtnWplZSVWVlba1lSr1R518zJBGH3RaDRib2+vbU29Xu9RNwAAADDYvnT77CDsO3Mv6vqpXq+f+X6/nwRh9MXY2FhMTk62rUkmkz3qBgAAAIbfH/U5BIt48V5+amqqbU21Wo1Go9Gjjo5KNJvNZl9emZE0PT0de3t7MTU1Fbu7u/1uBwAAAIbCx42IG99oX/PRNyNeGYLT4PuZDQzBjwcAAAAALk8QBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACNBEAYAAADASBCEAQAAADASBGEAAAAAjARBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhAAAAAIwEQRgAAAAAI0EQBgAAAMBIEIQBAAAAMBIEYQAAAACMBEEYAAAAACPhRr8bYDRVq9WYnp5uW7O4uBiLi4s96ggAAAC4rJWVlVhZWWlbU61We9TNywRh9EWj0Yi9vb22NfV6vUfdAAAAAN1Qr9fPfL/fT4Iw+mJsbCwmJyfb1iSTyR51AwAAAHRDMpmMqamptjXVajUajUaPOjoq0Ww2m315ZUbS9PR07O3txdTUVOzu7va7HQAAABgKHzcibnyjfc1H34x4ZQhOg+9nNjAEPx4AAAAAuDxBGAAAAAAjQRAGAAAAwEgQhAEAAAAwEgRhQ6BWq0WhUIhcLhczMzORSCRiZmYm8vl8rK2tXXjd5eXlyOVyMT4+fmTNUqnUxe4BAAAABoMgbMAtLy/H+Ph4rK2tRS6Xi9XV1dje3o5CoRCVSiUWFhZiZmbmXOFVqVSK8fHxKBQKERGxvr4eOzs7USwWo1wuRy6Xi1wuF7Va7Yq+KwAAAIDeSzSbzWa/m+Bk+Xw+NjY2IpPJxPb29ok1CwsLramw7e3tyGQybdcslUqRy+UiImJ+fj5WV1dfqpmdnY3/f3t3sJtG1uYN/HH6ndG7irBbGilKNl3cAXZfgfEd2MkVxOx7YdT61p9aeJE9zBWk4Q4gV5CYO3D15m1FGumNS1mNZqbDt8gHAxhsbBemyvx+Egrgos4DHOzKn3NODYfDSJIkLi4uolKpPOyJTNnkKVIBAACgrP76FvG3/3PzNv/zfyN+KMGQp01mAyV4ebbT+fl59Hq9iIj48OHD0u3a7XYkSRIREYeHhzfuM8uyODk5iYiIJEkWhmAR30eIRUSkaTrZHgAAAKDsBGEFNZ62WKvVbh2RdXx8HBHfg65xeLbIycnJZLrjeP+LJEky2edgMHjQOmQAAAAARSEIK6Dp9b7Go71u8vPPP0+uf/z4ceE2aZrO7Pf169c37vPNmzeT6zeFZgAAAABlIQgroDRNJ9eHw+GdHvvjjz8uvL/Vak2u1+v1lUeZRdw+0gwAAACgDARhBbS3tze5nqbpTDC2yPQosGUjyKanN962oP6ifb1//36lxwAAAAAUlSCsgObDrEajceP249FalUplZiTX2PyosumplDeZDsyMCAMAAADKThBWQLVabSaEGgwGS8/e2Ol0JiPGpqc/TpteGyxitXXHFm1312maAAAAAEUiCCuof//3f5+53ev1roVhg8FgMlqs3W7H6enpwn3NL6B/2/pgY/PrjX369GmlxwEAAAAUkSCsoGq1WnS73Zn7er1eVKvVGA6HcX5+HkdHR5EkSfT7/aUhWERcW2PsviPCLi8vV6weAAAAoHgEYQV2fHwc7XZ75r40TWN/fz+azWacnZ3F5eVl1Ov1G/dz22L7q8qyLJf9AAAAAGzC3zZdADcbj/RatGD+YDCILMtunep43wBrfr9fvny5134W+fz5c7x69erB+/nll1/il19+yaEiAAAA4Cbv3r2Ld+/ePXg/nz9/zqGa+xGElcDp6WlcXFxEp9OZuX84HMZPP/0UHz58mFlcf13yHBH27du3+PPPPx+8n69fv+ZQDQAAAHCbr1+/5vJ/+U0ShJVAo9GITqcTp6enMRgMZqY6ZlkW+/v70e/3l06RrFQquYRYqy6yv4pnz57FixcvHryf58+f51ANAAAAcJvnz5/Hy5cvH7yfz58/x7dv33Ko6O4EYXfQ6XQWTlF8iFqtFhcXF0t/fnR0FIPBIM7OzqLVakXE/wZj89stC8P29vZyCcL29vYevI+xFy9exD/+8Y/c9gcAAACsV17LE7169WpjI8ssll9g+/v7MRgMol6vT0KwiIh2u33tjJIREScnJwsDr/uO5JrfV54jwgAAAAAemxFhd1Cv1xcGUA+xLFw6OTmJ4XAYEXHtzJER388oeXFxEYeHh5PAKsuyaDab17Y/ODiY7Gu83Sqh1vzi+NVq9dbHAAAAAPl7thPxP//39m24mSDsDpIkiSRJ1t5OmqbR6/Ui4vvUyWVtjqdVTgdUnU4nWq3WTNC1v79/bf+rLK5/eXk5c3vZGmQAAADAeu3sRPwg6HowUyMLaHpE18HBwY3bJklybQTYp0+fZm7P72N6sf2bTE+NrFQqjxICAgAAAKyLIKyApgOoVaYjnp6eztyeD7pqtdrMCLGPHz+uVMd0oHZbIAcAAABQdIKwAppem2t+euIyt011fP369eT69HphN5nertlsrvQYAAAAgKIShBXQ9BTEVacxLnv8WKPRmFwfDAa37mN6myRJrA8GAAAAlJ4grIDevHkzuf7p06eZqZLLTAdmi0KrWq02c/94Mf5lps+OaTQYAAAA8BQIwgpoOrTKsix+++23G7cfDAaTsKzVai3dbnpR/Zv2mWVZdDqdiPgeqs2vQQYAAABQRoKwgup2u5MF7s/PzyfB1Lw0TePk5CQivodWZ2dnS/eZJMlkpNdwOIzz8/OF2x0eHkbE9zNFTo8MAwAAACgzQVhBVSqV+OOPPyajsRqNRhwdHUWn04nhcBiDwSCazWZUq9XIsixarVb0+/1b93t8fBz9fj8qlUo0m804OTmJ4XAYWZbFYDCI/f39GA6HUavV4o8//pg52yQAAABAme2MRqPRpovgZsPhMNrtdgwGg8laYEmSRK1WiyRJ4tdff71XYHV+fh7v37+PNE0jy7KoVCpxcHAQjUYjjo+Pc34W37169Sr+/PPPePnyZfzjH/9YSxsAAABAcW0yGxCE8agEYQAAALDdNpkN/O1RWwMogHfv3sXXr1/j+fPn8csvv2y6HLgzfZgy038pO32YstOH2XZGhPGojAijCPRDyk4fpsz0X8pOH6bs9GGKYJP90GL5AAAAAGwFQRgAAAAAW0EQBgAAAMBWsFg+G/H58+d49erVjdv88ssvFm8EAACAEnn37l28e/fuxm0+f/78SNVcJwhjI759+xZ//vnnjdt8/fr1kaoBAAAA8vD169db/7+/SYIwNuLZs2fx4sWLG7d5/vz5I1UDAAAA5OH58+fx8uXLG7f5/PlzfPv27ZEqmiUIYyNevHjhVL0AAADwxKyyzNGrV682NmpMEEbpvXv3Lr5+/RrPnz/f+JpiailPPUVRtNelSPWopRyK9NoUqZai1VOkWoqmSK+NWspTT1EU7XUpUj1qKYcivTZFqqVo9RSpllyM4BG9fPlyFBGjly9fFnqfaslfkepRy3JFqkctyxWpHrUsV6R61LJckepRy3JFqkctyxWpHrUsV6R61LJckep5av+Pf/YIWRsAAAAAbJwgDAAAAICtIAgDAAAAYCsIwgAAAADYCoIwAAAAALaCIAwAAACArSAIAwAAAGAr7IxGo9Gmi2B7/Ou//mv893//dzx79ixevHiRyz4/f/4c3759y3Wfanna9ailHPWopRz1qKUc9ailHPWopRz1qKUc9ailHPWopRz1rKOW8T7/5V/+Jf7rv/4rl32uShDGo/rhhx/i27dvmy4DAAAA2LBnz57FX3/99aht/u1RW2Pr/f3vf4///M//jB9++CH+7d/+bdPlAAAAAI/sP/7jP+Kvv/6Kv//974/ethFhAAAAAGwFi+UDAAAAsBUEYQAAAABsBUEYAAAAAFtBEAYAAADAVhCEAQAAALAVBGEAAAAAbAVBGAAAAABbQRAGAAAAwFYQhAEAAACwFQRhAAAAAGwFQRjwJJ2fn8fR0VHs7u7Gzs5OVKvVODk5icFgsNZ2h8NhNBqNqFarsbOzM2m72WxGlmVrbZunZVN9eF6apnF0dBS9Xu9R26V4Ntkni/J5oNyK0o/8XuW+HN9CTkYAT0i/3x9VKpVRRIzq9fqo3++PLi8vR91ud5QkyeT+q6urXNu9uroaHR8fjyLixku73c61XZ6eTfXhefN9Wt/dXpvsk0X5PFBuRelHfq9yX45vIV+CMODJ6Pf7kz/Ip6enC7ep1WqjiBglSZLbwcLV1dXkIGSVy7LaYFN9eNrV1dXo7OzMQS6j0WizfbIInwfKrwj9yO9VHsLxLeRPEAY8CVdXV5NvypIkWbrd5eXl5A92vV7Ppe16vT6KiFGtVht1u93R5eXl5Fu6RQe+ETHqdru5tM3Tsck+PNZqtUZJkkz6tP+wbbdN9skifB4ovyL0I79XeQjHt7AegjDgSZg+wLztwDLPaQntdnsUEaOzs7Ol21xeXk6+qRtfKpXKg9rl6dlUHx67uLgYXVxcTG6P+7b/sG2vTfbJTX8eeBo23Y/8XuWhHN/CeuyMRqNRAJRYmqZRrVYnt6+urqJSqSzdvtfrxcnJSUREVCqVuLq6unfb1Wo1kiSJfr9/pxojIvr9ftTr9Xu3zdOxyT68zHA4jP39/cntdrsdp6enubdDMW2yTxbx80D5FLEf+b3KXTi+hfVx1kig9Fqt1uR6vV6/8SAhIuL4+HhyPcuye5+1aTgcRpqm0e12b902SZKZOsePh4jN9eGb3FYDT9sm+2QRPw+UTxH7kd+r3IXjW1gfQRhQep1OZ3K9Vqut9JgkSSbX379/f692379/H6enpysf2M5/O/bPf/7zXu3y9GyqD8Mym+yTPg/kQT+i7BzfwvoIwoBSm//W6eeff17pcdMHFPf9xuzNmzfXvgVbtc2IuDaUnO20yT4Mi2yyT/o8kAf9iLJzfAvrJQgDSm0wGMzcnv4m7Cbz291nGHetVrvTNIcsy26sge20yT4Mi2yyT/o8kAf9iLJzfAvrJQgDSu3jx48zt1f9w/3jjz/O3P706VNeJS2VpunMbQuJElGuPsx22GSf9HkgD/oRZVemPuz4ljIShAGlNv/H977fmF1eXuZW0zLTByPOEsVYmfow22GTfdLngTzoR5Rdmfqw41vKSBAGlNr8gcJ9zQ/rXod2uz253mw2194e5VCmPsx22GSf9HkgD/oRZVemPuz4ljIShAGldt8/8PNDzL98+fLwYm6QpulknYZWq2X9BCbK0ofZHpvskz4P5EE/ouzK0ocd31JWgjCAWP83ZuOz7yRJEmdnZ2tti+1k5AJFs8k+6fNAHvQjys7xLSwmCANK7S5ntXmM/SwyHA6j0+lEpVKJfr+/tnYopzL0YbbLJvukzwN50I8ouzL0Yce3lJkgDFibTqcTOzs7uV729/dn2tjb28ul1rz2s8jbt28jIuLDhw+GjJeMPsw22mSf9HkgD/oRZVeGPuz4ljIThAGldt9vuuaHiq/rG7NGoxHD4TC63W7UarW1tEG5Fb0Ps3022Sd9HsiDfkTZFb0PO76l7P626QKAp6ter0e32811n/N/0A8ODiaLdEZ8PwBY5Y/+/OKh1Wo1j/JmdDqd6HQ60W634/j4OPf9s37b3ofZTpvskz4P5EE/ouyK3Icd3/IUCMKAtUmSZO1DpeenmaVputI3U5eXlzO36/V6rnUNBoNoNBrRbrfj9PQ0133zeLa5D7O9NtknfR7Ig35E2RW1Dzu+5akwNRIotYODg5nbaZqu9LjpoeOVSiXXsGM4HMbR0VG0Wi0HCdyqiH2Y7bbJPunzQB70I8quiH3Y8S1PiSAMKLVarTYzVPzjx48rPe7Tp0+T6/MHGw+RpmkcHh7G2dmZ00izkqL1Ydhkn/R5IA/6EWVXtD7s+JanRhAGlN7r168n16fXU7jJ9HbNZjOXOtI0jf39/Tg9PY1Wq7XyY87Pz3Npn/IqSh+GsU32SZ8H8qAfUXZF6cOOb3mKBGFA6TUajcn1wWBw6/bT2yRJksv6CVmWxdHRUbx+/Xrlg4SIiJOTE2uQUIg+DNM22Sd9HsiDfkTZFaEPO77lqRKEAaVXq9Vm/tj2er0bt58+C+Bt35Z1Op1oNps3rs2QZVns7+9HkiSTbW+7DAaDyUKoTjvNpvvwIvOnYGe7bLJPrrNttoffq5Tdpvuw41uetBHAE3B5eTmKiFFEjGq12tLtrq6uJtvV6/Ub91mv1yfbRsTo6upq4Xa1Wm1mu7tc2u32Q542T8gm+/Ai3W535rGtVmvlx/I0bLJPrqNtto/fq5Sd41tYD0EY8GRMH2AuO7gc/1GvVCq3Hryu8kf9IQcJvotg3ib68CJXV1ejJElmHnvTAThP1yb7ZN5ts538XqXsHN9C/vRS4Enp9/ujSqUyiojR8fHx6OLiYnR1dTXq9/uTP+q1Wm2l/zCN9zO+9Pv9mZ8fHx8/6CDh9PR0Ta8CZfaYfXja1dXV6Pj4+No3xfOXer0+qYvtsKk+mXfbbC+/Vyk7x7eQL0EY8CS1Wq1RrVab/LGvVCqjer0+6na7K++j3++PkiQZVSqV0dnZ2Rqrhev0YYpmk30yj7bB71XKTh+GfOyMRqNRAAAAAMAT56yRAAAAAGwFQRgAAAAAW0EQBgAAAMBWEIQBAAAAsBUEYQAAAABsBUEYAAAAAFtBEAYAAADAVhCEAQAAALAVBGEAAAAAbAVBGAAAAABbQRAGAAAAwFYQhAEAAACwFQRhAAAAAGwFQRgAAACQqyzL4uTkJIbD4aZL4f8bDAbRaDRif38/qtVq7OzsxM7OTlSr1Tg6Oopms3mv9+v8/DyazeYaKl4PQRgAAACQm8FgED/99FMkSRK1Wm1y3zh4ue2yu7sbnU7n1naGw2Hs7u7euK/9/f2IiOh0Oiu3f5/LtLu2tbu7m/+bMOX8/Dx2d3fj6OgoOp1ODIfDqFQqcXx8HMfHx1GpVGIwGMT5+Xns7+/H7u5unJ+fr7z/09PTGA6HUa1WI03TNT6TfOyMRqPRposAAAAAym88Oqjdbsfp6em1n/d6vXj79m1kWXbtZ6enp9Fut+/cZpZl0Ww2Z8Kzer0e3W43KpXKzLbD4TCazWYMBoNr+0mSJJIkufaYcRsREV++fIk0Ta/Vvyhaua2tdrsd9Xr99id4T/OvdaVSiVartfB9ybIsOp1O/Pbbb5Pt71pjo9GI33//PT58+DAJQItIEAYAAAA82G0h2NhgMIijo6Nr919cXNw7QMmybDKyqlKpxB9//LEw0Brb3d1dKcxaJk3TmamfV1dXS9tb1NZDnusq5qcr1uv16Pf7tz5uPKV1Ory77f2cdnJyEr1eb+3P7yFMjQQAAICC6PV6my7hXjqdTjSbzTg7O7s1NKnX63F8fHzt/k+fPt27/S9fvkyut1qtG0OwiIiDg4OZ27dtPy9Jkvjw4cNKj5tvKyLWGhI1m817hWAR31+Hfr8fSZJM7ms0GitPlex2u1Gr1eLw8HDhqL8iEIQBAABAAfR6vfjtt982Xcad9Xq9aDQaUavVotVqrfSYRdvdZ1rk2HhkVqVSWWn00l2Dr2X7WOX5zreVR9vLjNf6mm6r2+3eeT/9fn+mzmVTPBfpdruRZVkcHh7eud3HIAgDAACADRtPtSubLMvi7du3EbE43FomSZJro8KGw+G9zzI5DtFWncK3t7d3r3bmrbJ+Vl5t3WY8rXHaKqPjFkmS5NpreXJystIor/Fjx2ukFY0gDAAAADZs0ZpZZTAOR2q12p0Xfl8UnN1nRFyWZZPRSo1G486Pf4gkSRYuyr8JzWbzWlC1ajC4yK+//jpzO8uyld+fcQB2fn6+8kiyxyIIAwAAgA06OjqKNE03Xcad9Xq9ScgxH5qsIkmSa+FZr9e789pS47NF1mq1mbWtHsui9c4e2/isj9MeEoJFfJ9WOf/cVl0rbPq9fexw8jaCMAAAANiQ+TP0lcn06KD7hkGLps7ddVTYeFrkfcK4+8qyrFCLwc+HYBGRy1TbRSMVF7V102PTNF35MY9BEAYAAACPLMuyqFar184SORwOY2dnZ+YyGAxiMBjE7u7utZ+NL9Vqdel6TEdHR9ceW61WH1T/YDCYrOf1kDMg1uv1a6O47hKaDAaDyWi6xxyZNX9mxk17//79tfsWna3yrhZNd1118f3px95l/bh1E4QBAADAI/vy5Us0m81rZ0qsVCrRbrdnLgcHB1Gv1+Pq6mrhdLdutxuXl5dLw4Z+vx9XV1eTdazOzs7i8vLyQfVP133XtcHmzQdKi6b53VbHQ6cB3tWnT58etb3bzJ9koFKp5LJuWZIk1/az6gjG6YA0TdNroe+mCMIAAADgkY3PrHd6ejoTNEzfv+jn7Xb73gFHlmVRqVRyGZ0zHWr8/PPPD9rX/HOMWG0EUZZlkzoecx2qh5zdch0W1ZLHaLCxRWe9XHVNu+mQtN/v51bTQwjCAAAAoETm18JaJWAYB0Z5jJyaD17yWKB+vq40TW8deTS9SP5DpmeuarzW1eHh4drbuotFoVSeZ7FctK9Vg7Dp9+X333/Pq6QHEYQBAABAiZydnc3c7nQ6ty7cPp5CmMfIqfmAKo8gbNFC97eNCsvzOWVZtnT9tel11RqNRqEWyY/4Ps123qJRXPe16P1d9TX48ccfZx5ThLOjCsIAAACgZBaFYctkWRaDwSCSJMkltPr48ePM7TxGH1UqlWujwqYXwp83HA4nP8trfbDx67PskucoqzwtCqXWXeui8G2R+f5WhCmlgjAAAAAomfkRVL/99tvSbcdT0vI6y+G6RkQtqm/ZqLDx883rTJGVSiUuLy9vvFxdXcXFxcWjTMO8i0WhV57v0aJ9rTribL62VQO0dRKEAQAAQMnMj6CaXjh+XrfbjYiI169f59L2usKMJEmunYFy0bTP6ee6aErlOtVqtcnrWRSLQqk836NF+3rICRs2TRAGAAAAJTQ/gmrRiKrxtMjj4+PcpstNhxl5T8Fb9Bzmp32OR7glSbKR0VmLArtNesgaXqtYND111Sm28yHdP//5z1xqeghBGAAAAJTQfCCz6EyL4xApjwXlF8l7hE+9Xr8WssxP+xxPl1zXc1pFrVYrzJphi8LAPBelX/Qe57HW3KYIwgAAAKCk5tfQmr/9/v37qFQquY5gWncAND8qLMuySaC3jkXy76PVat16VsvHNB+GpWmaS0i5aHH7u/Sl+WmV02eR3BRBGAAAAJRUrVabCUGmz7SYpmkMh8PcA6N1jwY6PT29FraNQ6fpRfKLMiKrCBaFU/OjA+9j0T6Ojo7uvb8ivGeCMAAAACix+QXjxyOqxgvK5z2FcH7dp3UsgD4f3qVpGr1eb23PKQ+9Xu/RFoNvNpszo7UWnTSg3+8/uJ1F+7hLsDr/ehRhSqUgDAAAAErs+Ph4JmAYBzLtdjuSJMk9fJgfEbSOs0guCnZOTk4ioniL1Ud8Hzl1cnKytjNqThsOh3F+fj7zvlYqlTg+Pp7Zbv4kA/cxPyLs7OzsTqO65tcqOzg4eHBNDyUIAwAAgJKbX1fr5OQk0jRdeBbGh5oPofJcmH2sUqksHXlUxNFgjUYjKpXKo4x4evv2bSRJsnT66LSHhGHn5+cztyuVysKA8ibTZ4lcVPMmCMIAAACgIO47te709HQmhBmP5Hn9+nUeZc2YD3zymIK3yLIQL481z/IcudVsNiNN06Wj1PJuazgcXhv9FfE9aGq329e2v0+fyrLs2tk6u93unYOs6ZC0KKP4BGEAAACwQdOh0kNGV82PCFrngvLTQUwei7IvsmgKZL1ez+U55bWW1/n5+WTk1Js3b9baVrPZnLS1bMH609PTmaAwy7LJlNK7ODw8nKm71WrdK8ia7hv3qWMdBGEAAACwQfPT6eaDpUajsVKYMr9W2DqnEE5PkZtetD1v86PC8prq+enTp5nbWZbdKbDq9Xqxv78/U8+yoGhRW6u+ZmmaRqfTiWq1OjNV8aZQqt1ux9nZ2eT2eP2yVZ5flmVxdHQ0U9/8/lY1/ZoWaV23ndFoNNp0EQAAALCter3ezGiZSqUyGd01XvC+2+2utK/xqKFKpRJXV1drqXe+rYjv0yPXFXRUq9VI0zSX55SmaTQajaWj2Gq1Wuzt7S0cdZZlWaRpunDUXq1Wi4uLizu1NV4za/4snF++fIksyyb/zqvX6ytNR+31evH27duZfbTb7aVTSzudzsxUykqlEt1u997va6fTmYSxN7X72ARhAAAAsGHjsGfeqqHH2Dh8ODs7W7h4ep6yLIvd3d2IiLW2l8dzmg5l1mG6tnW31Wq17jRCq9lsRqfTmQnE6vV6JEkyCdumw7rxovj3GQU2bX9/P4bDYSRJEpeXlw/aV54EYQAAALBhWZbF27dvYzAYRJZlUavVotFo3HkUzcnJSfR6vbi4uIharbamav/XOPRZ9wi03d3duLi4eJSzMj5Vg8Egut1ufPr0aTK6bTwiLUmSqNVq8ebNm1z6TZqmUa1WIyIerS+uShAGAAAAT8TOzs7CaXrrNA7fijT9jc06OjqKwWDwKCMT70oQBgAAAE/AeHTWJgKparUaX758iT/++GNtZ6qkHAaDQRwdHT16ILsqQRgAAAA8AeMwat2L5C8yngp3fHy88sL+PD1ZlsVPP/0Ue3t7cXFxUchQ9NmmCwAAAAAe5vz8PNI03djUxCRJ4uLiInq93loXiqe4siyL/f39QodgEUaEAQAAQGk0Go1I0zRqtVocHR3FwcFB/P7775MF6zc9NXE4HMbh4WG8fv062u32xurgcY1DsCRJotvtFjYEixCEAQAAQCk0m804Pz9f+vOiLFafpmmcnJzE3t5e4UMRHm4cfv76669xdna26XJu9bdNFwAAAADcLsuypT87Pj4uRAgW8b/TJM/Pz+PLly+CsCcuTdP48OFD1Gq1TZeyEiPCAAAAoASGw2Hs7+9fu98C9bA6QRgAAACURJqm0W63I03T2Nvbi5OTk6jX65suC0pDEAYAAADAVni26QIAAAAA4DEIwgAAAADYCoIwAAAAALaCIAwAAACArSAIAwAAAGArCMIAAAAA2AqCMAAAAAC2giAMAAAAgK0gCAMAAABgKwjCAAAAANgKgjAAAAAAtoIgDAAAAICtIAgDAAAAYCsIwgAAAADYCoIwAAAAALaCIAwAAACArSAIAwAAAGArCMIAAAAA2AqCMAAAAAC2giAMAAAAgK0gCAMAAABgKwjCAAAAANgKgjAAAAAAtoIgDAAAAICtIAgDAAAAYCsIwgAAAADYCoIwAAAAALaCIAwAAACArSAIAwAAAGAr/D+cIGvfFIcBiQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-200, 200, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"ideal_state_770_y\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"y (VELO)\")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-200, 200, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"ideal_state_9410_y\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"y (T)\")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-1, 1, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"ideal_state_9410_ty\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"ty (T)\")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-1, 1, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"ideal_state_770_ty\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"ty (VELO)\")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-0.5, 0.5, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"dSlope_yEndT\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"dSlope y\")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMIAAAOWCAYAAAANzz7PAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACDP0lEQVR4nOz9XWxjaXoneD5Upo0slItBRRoNaCRgHJRzUMZejIOK7AvfTQe1PRfOtd0pZRquqTKw7ZDKXmN2oUFJFVWXi8woRaME7PbCXVKWL7aMAiZSKrcNewB3iZlzNReNlJg1d4WxxUwDoSbQmAoxaXtdsDPJvYiRrE+Kko54DnV+P4BIMfTyPQ8/Dpn86/0odLvdbgAAAADADTeSdgEAAAAAMAiCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC5IAgDAAAAIBcEYQAAAADkgiAMAAAAgFwQhAEAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIhRfTLoB8+fznPx8//elP44UXXoh/9s/+WdrlAAAAAAP2n//zf47PPvssXnrppfi7v/u7gR670O12uwM9Irk2MjISXnIAAABAoVCITqcz0GMaEcZAHQ7BxsfHU6zk4prNZnQ6nRgZGYmxsbG0y7mQYa19WOuOUHta1J4OtadjWGsf1roj1J4WtadD7ekY1tqHte4Itadld3c3IiKVgTKCMAZqZGTk4ER9+vRp2uVcyMTEROzu7sbY2JjaB2RY645Qe1rUng61p2NYax/WuiPUnha1p0Pt6RjW2oe17gi1p+WFF144yAYGLdUg7JVXXknz8EcUCoX43/63/y3tMgAAAAC4JqkGYTs7O1EoFFJdM2r/+IVCIbUaAAAAALh+gx+DljEWbgcAAADIh9TXCOt2uzEzMxPlcjmV47darVhbW0vl2AAAAAAMTupB2NraWvzO7/xOqjXMzMzEv/yX/zLVGgAAAAC4XqkHYdVqNe0S4tVXX027hNzpdDoxMTHRs83CwkIsLCwMqCIAAADgqlZWVmJlZaVnm06nM6BqTko9CLt9+3baJZCS3d3dnr9vt9sDqgQAAABIQrvdPvf7fppSDcLs1Jg/X/jCF+KTTz6JQqEQ/8V/8V/0bFssFgdU1c23sLAQ7XZ76B7TYa07Qu1c3DA/7mpPxzDXPqyG+TFXezqGufZhNsyP+7DWPqx1Rwx37VlVLBZjfHy8Z5v/9J/+U3S73fjCF74woKr+SaGb4raJIyMj0Wq1Un/BffLJJzE6Oprq0Ly8mJiYiN3d3RgfH4+nT5+mXc6FDHPtkBfOU8g+5ykMB+cqZN8wn6dp1j4y0KMds7y8nHoIFhFx69atWF5eTrsMAAAAAK5RqkHY1772tYEe7+OPPz7zd4OuBQAAAIDBSjUIG7T5+fm0SwAAAAAgJbkKwra2ttIuAQAAAICUpLpr5GV9/PHH0Wq1+m7faDRidXX1QrcBAAAA4GYZiiDs448/juXl5ajVatFoNC7VR7fbjUKhkHBlAAAAAAyLzAdhDx8+jMePH0fE8zALAAAAAC4j00HYD37wg1heXo6IiEKhEIVCQRhGahYWFqLdbkexWEy7FOAMzlPIPucpDAfnKmSf8/RyCt0MJ0v37t2Ler1+EICVy+WoVCpRLpcjIuLll18+t4+f/OQn0Wq14t13341PPvkkPvvss+sumx4mJiZid3c3xsfH4+nTp2mXAwAAAAxYmtlApkeE7YdgERGbm5tx//79S/e1uLgYr7zySlKlAQAAADBkRtIuoJdSqRQRz0Osq4RgERHlcjnu3LmTQFUAAAAADKNMB2H7UyBfffXVRPpbXV1NpB8AAAAAhk+mg7D9UWDPnj1LtD8AAAAA8ifTQdg3vvGN6Ha7Ua/XE+nvu9/9biL9AAAAADB8Mh2E3bp1K771rW/FkydP4m/+5m+u3J+pkQAAAAD5lekgLOL5QvmVSiVmZ2ev1M9HH32U2MgyAAAAAIbPi2kX0I/Nzc24d+9evPLKK7G0tBS3b9/u63bPnj2LVqsVOzs78e67715zlQAAAABk2VAEYe+//35EROzs7MT8/Pyl+uh2u1EoFJIsCwAAAIAhkvkg7Hd/93djbW0tIiIKhUJ0u90L9yEAAwAAAAat243onBNjjBQixBaDk+kg7J133jlY4P6yIVhEXPp2AAAAAJfV6Ua8+M3ebT59K+IFQdjAZDoIOx6CVavVmJ6ejlKpdOF1wr7zne/Exx9/fI3VAgAAAJBlmQ7C6vV6FAqFKJVKsbW1FXfu3Ll0Xw8ePIiXX345weq4imazGRMTEz3bLCwsxMLCwoAqAgAAAK5qZWUlVlZWerZpNpsDquakTAdhpVIpPvnkk3j48OGVQrD9vu7evZtQZVxVp9OJ3d3dnm3a7faAqgEAAACS0G63z/2+n6ZMB2FTU1Px/vvvR7lcTqS/d955J5F+uLqRkZEYGxvr2aZYLA6oGgAAACAJxWIxxsfHe7ZpNpvR6XQGVNFRmQ7C5ufn47333otGo5FIf0aEZcfY2Fg8ffo07TLImVarFaVSKe0yAAAAbqx+ljmamJhIbdTYSCpH7dPMzEzcvXs3njx5kkh/f/zHf5xIP8DwqNfrsbS0FKOjo/HgwYO0ywEAACBFmR4RFhGxvr4ev/iLvxj//t//+/iN3/iNK/X16NGj+Ff/6l8lVBlwVfV6PZ48eRL1ej0ajcbBLq+lUinK5XLcvn07KpVKTE9PR7VaPXH72dnZaDQasb29ffBvrVYrarVaPHnyJGq1WrRarQHeIwAAALIs80FYuVyO73znO/E7v/M7VwrCPvnkk6jX6wlWBhFra2sxPz9/4dtVKpUj4c1lFQqFC9+mVCrF3t7eqb+bnZ2NjY2NC/e5ubl5alB1mlarFY8ePYrHjx/3bLN/vtZqtYO2lUolqtVqTE5OxubmZmxsbESlUjly2wcPHkSj0XC+AwAAcEKmg7D9qYw///M/H6Ojo/HKK6/EzMzMhftptVrx7rvvJl0exNzcXLzxxhvRaDTi0aNHPUOkarUaS0tLce/evcTWqep2u9FoNKJWq8XS0tKZo5/K5XIsLS1FtVrtufnE+vp6tFqt2NraiuXl5ajVame2XVxcjDfffDPK5XLf92dpaenUAGxmZuagr/3+Go1GNBqNWF9fj3ffffcgHDsecB2/z+vr6wc/T05OJrbGIAAAAMOv0O12u2kXcZZ79+7Fhx9+eHC92+1eagTM4dt+9tlnSZXHJewviDc+Pn4jF8ufn5+PtbW1E/8+MzNzJKC5Do1GIyYnJ0/93d7e3qXCt6mpqVNHVq2ursbc3NyFapuenj4RSs3NzcXq6mpffTx+/DiWlpZO/Hu5XI6dnZ1Tb3P8+RjE8wAAALDvs07Ei9/s3ebTtyJeyPQK7slLMxvI9EP9xhtvRLfbjf2s7rIhGAzKWdMkLzN98qLK5fKJaYIRz8Ofy45AO6vui4RgtVrtxMisUqkU29vbfYdgEc9HoO3s7Jy4L8+ePTvzNnaIBAAA4LBMB2H7X8ILhcJBIHbZCwzCWdMOe01HvO7jX+XYp932IuFSvV6P6enpE7d/7733Tg3t+qnno48+OlKDxfABAADoV6bXCLt161ZUKpX48MMPY3l5OSqVSty+ffvC/TQajXj77bfjRz/6UfJFwiFnhUSXed0Ou0ajEffv3z/x7+vr65cKwfbtjyY7axroMNtf/H9QwemwqdVqfW/KAAAAcJpMB2EREW+++WZMTk7G1772tUv3cffu3Xj99ddzGUaQL6e9xl9++eVE++v3PJqdnT0xWmtubi6RIKNcLsfi4mLPnSezpF6vx+rqatRqtWg0GlEqleL27dtRKpWiXC7Hm2++GRHPd7xcXl7uOfW0VqvF7Oxs3L59O1ZXV290MLS/EcT6+vrBxg1ZGuGbp+cCAABuiswHYdVqNT744INE+rp3714i/QC91Wq1UxfZX15eTuwYDx8+PAjCWq1WJtcDa7Va8eDBg4PdRMvl8sHOt41G42AXzMO7jZ431XM/YGy1WjE/P3/mRgHDrNFoxOzsbDQajUxPfc3DcwEAADdNptcIi3g+miupL8///X//3yfSD9DbaYvsX2XR/tOUSqULLdqfhtnZ2YOQa3V1NXZ2dmJ9fT3W19dje3s7dnZ2TowiOi9MycPI1nK5HNvb27G3txeLi4tpl3OmPDwXAABw02Q+CIuIuHPnTiL9/Nt/+28T6Qc42/70v+MePnyY+LFmZ2cjovfOkb3sT22bnJyMQqEQo6OjMT09HWtra1eu7fHjxwfT+RYXF08N7crlcmxubh4J+0977A5bXV2Ncrkc5XI51tfXr1xn1h3fbCFL8vZcAADATZD5qZFJ2traSrsEuPHOCgSuskD+WarVaiwvL194ZE6r1Yr79++fmL7ZarWiVqtFrVaL5eXlKy3s/+jRo4OfTxshd9ji4mL85Cc/icePH58b6lWr1VxNwUtr1NX8/Hysrq72bJO35wIAAG6CoQzCPv744wutG9NoNGJ1dTXTa83ATbE/Cuqw61xE/KJT5xqNRkxNTZ37frDfbnNz88L1X2Ztq+Xl5TNH0zFYa2trsba2dm4QBgAADJ+hCMI+/vjjK39J7Ha7USgUEq4MOKzRaJx6jl7HaLDLaLVaBwucz8zMxPT0dNy7dy+ePXsWm5ubp+5COT09HTs7O1Euly90nMNqtVpf65k9fPjwYLon6Wg0GueO4AMAAIZX5oOwwzvDdbvdlKsBejkrqJ6cnBxwJafbH6122iivarUa8/PzMT09feJ+zM7Oxvb2dt/HOR6aLS0txRtvvHHuZgH7O0pmdRfMm67VamV6TTIAAODqMr1Y/g9+8INYXl4+CMCM6IJsOysIy9Luer2mOu4vXn9cvV4/dcrnWUql0pEgq9VqxdTUVF8jWrvdrhAsBfvrxpmaCgAAN1umg7D9xaYLhUJ0u924c+dOzMzMxOLiYiwuLsby8vK5l/3d2nyxJK+WlpaiUChc6jI1NXWhY521LlZWzr9SqXTuel/lcvnILo77Tvu3Xo63bzQaMTk5mciOlPV6Pebn588daddqtWJtbS2mpqaOHHd/+t/o6GgUCoWYnJw8dVpoo9GIpaWlg101JycnY35+/tTnef84x19Dx01PTx/0d/iS5BqOa2trR44zOjoaU1NTp97HiOeP5507d05snnC4vrMe636fi32tViseP34c09PTB4//fn1LS0t9BXGNRiMeP34ck5OTR2o+/BxMTk4eTAMGAAAO6WZYoVDojoyMdEdGRrq1Wu1Kfe3s7HRHRkYSqozLGh8f70ZEd3x8PO1Srk1EnLjs7e0N5Nhzc3OnHj/JS7lcvvDxNzc3B3L/j1tcXDxSR7Va7fu2pVLpxP24qGq1eurjUalUutvb2xfqa3t7uzs3N3ekrlKpdKLd3t5ed3l5uVupVI4cc3V1tdvtnnxMDl/m5uYO+unVrlwun/maPv4aOMvy8nJf58j29nbfz8H6+vrB47K+vn6kj3K5fGbte3t73e3t7RM1bW9vH7kc7q+f5+K41dXVg/bLy8vd7e3t7s7OTnd9ff3I8zUzM3Pitnt7e93FxcWD+3G4xr29vRPP9+G6dnZ2zq0NAIDr8eln3W58vffl08/SrnLw0swGMj0ibH8UyeLiYty/f/9KfZXL5bhz504CVcFwmZubi+3t7UtdLrpr3lkjv7IyKuUiI9NOGzl2fMTQeTY3Nw/W/Trez9TUVN8jdhqNRjx58qTvUUeVSuXEgu/b29sxNTUV9Xo91tfXY2dnJ/b29o7surm2thb1ej2mp6ejVqvF5uZm7O3txd7eXmxubh48fo1G42DE7nH9LvZ/2uNyFbVa7eDYDx8+PNJ/pVKJ9fX1iHhe+4MHD47ctlQqRaVSObGpw/6/Hf7dRZ+LfUtLSzE/Px+lUil2dnZicXExKpVKlMvlmJmZie3t7YOaNzY2YnJy8shr49mzZzE9PX3idbm1tRV37tw5mNa7s7MTq6urB89Vq9Wy+D8AABw28OjtAqamprojIyPdH/zgB4n0d9VRZVzdfuo7MjLSHR8f73n59re/nXa5lxIZGxG2vLx86f6Oj8aJc0aEHR9Rs3/ZH400aMdHNZ020uYs+6OLkrgfZz0ul+n3cF/njUI6PkrorJF5x0euHR4Zdtjhx+SsY29ubvY1gmtvby/REWEzMzPnvubP66ff2vf1+1wcHgl23nN9eMTXWSMYD9dYKpVOfV6Pv34H9R4EAMBReRwR9u1vf/vc7/sjIyNGhJ1mfxTYs2fPEu2P9HU6ndjd3e15abfbaZfJBWV9RNhFHN/5MeLy92NxcTH29vbOHAW1v1tlP/2fVtdZDm9SMDc3d+b6aMd3SjxrJODh+lutVmaf17Neh4f/PYlF8ft9LpaWlg6OPzc311fbiOej3E7bpOHw/XjnnXdOfV6Pv9a2trb6qhUAgOzqdiM+6/S+/B97Daaq3W6f+32/0+mkVt+LqR25D9/4xjfi3/ybf3Ph6Uhn+e53vxu/8zu/k0hfXM3IyEiMjY31bFMsFgdUDUk5KxjY2dkZcCVXd1qY8pOf/ORK/a2vr0e9Xo8HDx6ceF+r1Wpx//79eO+99xLbXKDffg4/bxc5dqPRODGdMC3vvPNOvPrqqwdTDc8zqBBvbW3t4Fj9BGdzc3OxtLR0cJvl5eVzN3g4S7lcPgj87IYJADD8Ot2IF7/Zu82nb0W8cHLPqoEqFosxPj7es02z2UwtDMt0EHbr1q341re+dbAD5Be+8IUr9be6uioIy4ixsbF4+vRp2mWQsLO+sJ82qiXrTgstXn755Sv3W6lUYnt7O9bW1k6s3bQfku2vZzUolw3ekhqtm4RSqXRkvbPDkvpjymVsbm4e/NzvCLJqtRobGxsRMZznDgAA+bawsBALCws920xMTMTu7u6AKjoq01MjI+JgQeF+F2A+y0cffZTqlyHIi9NGCDUajcxOo7uIi0xLPM/c3Fzs7OycCKE2NjYyHX4kNVrtujUajVhbW4tarXbqQviDrOOijr/ObsK5AwAAWZHpEWH7Njc34969e/HKK6/E0tLSkXVvenn27Fm0Wq3Y2dmJd99995qrBCIi3nzzzVND51qtlvhOgdetVCodCSGSDML2+9vfzfHwcVZXVy89HS7v6vV6LC0tRaVSieXl5bTLOfK89huKHd+R8tmzZ0MTQAIAQNYNRRD2/vvvR8TzdYYuuw18t9uNQiHlibJwRfV6PR49ejTwqXMXsb/G0XGrq6tDF4QdH4nTz6iiWq0WS0tLsb293dcxyuVyvPPOO0dGvRq9ejnz8/OxtrYWc3NzmQjBIi63QP/xP/YkHcACAECeZX5q5O/+7u/G9PR0fPjhh1EoFKLb7V74AjfFgwcPMj9NqlQqnRp41Wq1oQp4jj/O/Y7QKpfLUa/XLzS98fjjZWHzi9sPwSIiMyFYxNEQq9+dNg+vvSYEAwCAZGU6CHvnnXdidXX1IMy6bKglDOMm2A+Spqenz2yT9OLll+3vrCDitJFiV3VdweDW1taR6/2ORt0PLi47ejWiv5Fnwy7J12q9Xj8IwcrlcqamEb755ptHru/X2cvhXVaHbRQlAABkXaanRq6urkZEHIwEq1arMT09HaVS6cLrhH3nO9+Jjz/++BqrhevTarUOps5d9IvxT37yk0Rr6SfAKJfLsby8fCL4qtVq8fjx4zN397uoRqMR09PTUa1WD94vknJ8t7+LPO7lcjkajUYsLS31NTrp+Aiw4+HJMDn+3txqtU4NppIc9XZ49F2vftMYTTkzM3NkrbnV1dVzX/+H78/Dhw+vszwAAMidTAdh9Xo9CoVClEql2Nraijt37ly6rwcPHsTLL7+cYHVw0nV80W61WnH//v2DQOGiU6WSrqnf/hYXF2Nzc/PEFMH9hcyvuhh8rVaL6enpg9AtaRsbGwc/XzRk2w/CHj9+HJOTkzE3N9ez/eH+y+VyYkFhv8/V4Xbn3ea83x8fzba2tnbi/uyHhIcluSD8xsbGieDytOMdd/zcajQaJ6Y2XqbGw2vANRqNqNVqZ77+6/X6wRTi5eXlTI1uAwCAmyDTUyP3vwA8fPjwSiHYfl93795NoKr07I9+OfwF/TIeP34c09PTMTo6GoVCISYnJ2N2dvZCaxpxurNGo1x2GlitVoupqamDL8ZvvPHGhY9/lSloVx21s7m5eepIqunp6Xj8+PGl+my1WjE/P38Qgm1vb/cdFvQbDK2trR3c97m5uQuHdofDk/n5+Zifnz/z2Gtra0cei8Mj0U5z+PlMe724s45/+PFaWlqK+fn5qNVqsbGxEfPz8zE5OXki5On33DntmMfDt9nZ2Xj8+PHBCMTJyckTodbq6urBxgb7fR4Pwvaft0ajcWQNstNq6/VczMzMHAlrZ2dnT23farXiwYMHEfH8dXdWINrv8374MU37tQIAAJnRzbBqtdodGRnp/uAHP0ikv3q9nkg/g7a3t9edmZnpRkQ3Irqrq6uX6mdzc7NbKpW6EdGtVqvdzc3N7s7OTnd9fb1bLpcP/n1vby/ZO3DI+Ph4NyK64+Pj13aMNM3NzR08T4cv1Wq1u7Ozc+7t9/b2upubm93FxcWD5+TwZX19/czb7uzsnHrsiLj0c1qpVE7t76KvwcXFxVP7qVQq3c3Nzb762Nvb6y4vLx95DZ93v44ft1QqnXucw49jtVrtq7bjVldXT72/MzMz3cXFxe7q6mp3bm7uyHPc72vk+HNy1mtib2/vxGN9lsPvL72e383NzSPt5ubmzjz2/vN0/FIqlQ6e88NtKpVKd2dn58Rz2m9tx9sdviwvL3e73dPPz5mZmSP9nPVaPe2+9vtc7FtfXz+4z6VSqbu6utrd2dnp7uzsdFdXVw9eD/v1nqbf5+B4u8u+lgEAuJpPP+t24+u9L59+Nvi+0pZmNpDpIGx9fb1bKBS6/+bf/Ju0S0nF3t7eqV/KLhOEHf5SdNYXp/0vdeVy+drCsJsahG1vb/f8Ip7U5bTnZW9vr7u6unpm8LD/nK6urvb9vG5vb3er1WrPWhYXF/sKbvZtbm6eGayVSqXuzMxMd3V1tbu5udnd3t7ubm5udldXV7vLy8tHblcqlc4NHPadFg6Wy+Uzw7fDQcXxgOQi9kPn9fX17vr6endubq5brVa7lUrlyPO0f7/PCwP3X19nPceVSuUgPOnVtlwud2dmZg5eB8fDuOPByX6fm5ubZ74eyuXyqe8pe3t7R/qvVCrdxcXFI232/+3462g//O91f0875vLy8sHxyuVyd3Fx8chrfm9v7+B+HH7MjjscRFcqlSOvt4s8F2dZXV3tVqvVI6HY/u3OOkd7nZOHn4OdnZ2e7c6rDQCAZAnCTpdmNlDodrO9peLU1FSMjIzEBx98cOW+/viP/zj+1b/6VwlUdf0eP34cq6urUS6XT0xZXF1dPXfNocNarVbcuXMnWq1WlMvlIzuSHdZoNGJycjIink9tOm+K1mVMTEzE7u5ujI+Px9OnTxPvf9DW1tautDvgRVQqldje3j7yb4VC4cL9lEql2NvbO/V3s7Ozl5p6u7m52ff0wY2NjXj06NHBdM9+lcvlmJ+fj7m5uQutm7S/HtXx+1UqleLevXsHC5lvbW0drAG1vr5+5TXMAAAAPutEvPjN3m0+fSvihT4Wrkqyr7SlmQ1kPghrNBrxi7/4i/GDH/wgfuM3fuNKfb366quJBGrXbT8g2F/35njYctEgbHp6+iBMO++2h4OQix6nHzctCOPyWq1W1Gq1ePLkSTQajYO1mCKeh177GwO8+uqrMTMzc+FNAs473v4x949z7969mJ2dFYABAACJEYSdThB2jrW1tXj48GH85Cc/uXQfn3zySdy+fTs+++yzBCsbjHq9HlNTUwfXLxJQHR7lFRGxt7fXczTNxsbGwe5mvUYOXZYgDAAAgLwQhJ0uzWzgxYEe7YL++I//OCIifv7nfz5GR0fjlVdeOXUHuvO0Wq149913ky5vYC4yDey4wzuVVavVc/s6/Pi2Wq3Y2Ni41GMOAAAAkDWZDsLefvvt+PDDDw+ud7vdePz48aX66na7l1pPaditra0d/Lw/1fI85XL5YIrakydPBGEAAADAjZDpAXNvvPFGdJ/vbBkRl1sYPM+OL0b+6quv9nW7w4HZZRZOBwAAAMiiTAdh+wvEFwqFg0Dsspc8Or7bZL+LjR9vd9Hd/QAAAACyKNNTI2/duhWVSiU+/PDDWF5ejkqlErdv375wP41GI95+++340Y9+lHyRGXZ8h8x+1xp7+eWXj1zf2trqe1olAAAAQFZlOgiLiHjzzTdjcnIyvva1r126j7t378brr79+qRBtmO2v87XvsiPCdnZ2EqsJAAAAIC2ZnhoZ8Xynw6SmNt67dy+RfobF8SDsslqtViL9AAAAAKQp8yPC7t69G8vLy4n0lVQ/w+KyAdbxKZTPnj27ejHHNJvNmJiYuHI/CwsLsbCwkEBFAAAADKtuN6JzzhiakUKEPfiuZmVlJVZWVq7cT7PZTKCay8l8EBYRcefOnUT6uXv3biL95M11jAjrdDqxu7t75X7a7XYC1QAAADDMOt2IF7/Zu82nb0W8IAi7kna7nch3+TSlGoT96Ec/il/+5V9Os4QDWaolKaVSKZEQq99F9i9iZGQkxsbGrtxPsVhMoBoAAADgPMViMcbHx6/cT7PZjE6nk0BFF5dqEDY1NRV7e3uphxmffPJJTE1NxWeffZZqHUm7fft2IkHYdWwyMDY2Fk+fPk28XwAAAOB6JLU80cTERGojy1JdLD+pRfCTkKVaknLZkVzHw7PrGBEGAAAAMGipBmGFDK1Sl6VaknJ8l8x+R4cdXxx/cnIyqZIAAAAAUmNE2A02NTV15Hqj0ejrdjs7O0euV6vVxGoCAAAASEuqQVhExEcffZR2CbG1tZV2Cdfi+IiwfoOwwyPHSqVSlMvlJMsCAAAASEWqi+VHRDx48CC+/vWvR6lUupZF2Xt59uxZNBqNWFxcHOhxB6VSqRzZOfKDDz6ImZmZc293OBg8HqYBAAAADKvUg7Dt7e2YnZ1NtYZut3sj1wiLiHjjjTdibW0tIiLq9Xpftzncbmlp6VrqAgAAABi01KdG7ut2u6lcbrr5+fmDn2u12rntD7cpl8vWBwMAAABujNSDsLQDqWEIw/rd7fE0lUrlSJi1sbHRs/36+vrBz0aDAQAAADdJqlMj9/b20jz80Di+yP1Fg7HV1dWYnJyMiIhHjx6duU5Yq9U6mEZZrVZjbm7u4sUCAAAAZFSqQditW7fSPPxQaLVaJ0ZmPXny5EIL/JfL5VhfX4/Z2dmo1+vx+PHjU29///79iHi+U+ThkWEAAAAAN0HqUyM5qdVqxezsbExPT8fo6OiJEWH1ej0KhUJMT08fhFvnmZmZic3NzSiVSrG0tHRwu1arFbVaLaampqJer0elUomPPvooSqXSNd07AAAAgHSkvmskJ13XiKxqtRp7e3vx+PHjePLkSdy/fz9arVaUSqW4d+9erK+vnzltEgAAAGDYCcJyaHFx8UJTKwEAAABuAlMjAQAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAABy4cW0CyCfms1mTExM9GyzsLAQCwsLA6oIAAAAuKqVlZVYWVnp2abZbA6ompMEYaSi0+nE7u5uzzbtdntA1QAAAABJaLfb537fT5MgjFSMjIzE2NhYzzbFYnFA1QAAAABJKBaLMT4+3rNNs9mMTqczoIqOEoSRirGxsXj69GnaZQAAAAAJ6meZo4mJidRGjd24xfLff//9ePPNN+MP//AP0y4FAAAAgAy5cSPCZmZm4pNPPomNjY2YnZ01vQ4AAACAiLiBI8Lu3LkTERF3794VggEAAABw4MYFYevr69HtduO73/1u2qUAAAAAkCE3Lggrl8uxtbUVDx48iL/+679OuxwAAAAAMuLGBWEREZVKJWq1Wjx48CAePnyYdjkAAAAAZMCNC8Ju374dr776aiwvL8dXv/rVKJfL8eqrr8a3v/3ttEsDAAAAIEU3btfIe/fuRa1Wi3q9fvBv5XI53n777Xj77bdjfn4+5ubm4hd+4RfSKxIAAACAgbtxI8IqlUqUSqV4/fXX486dO9HtdmNnZyf29vZib28vlpeXY3JyMl555ZX49re/HR9//HHaJQMAAAAwADcuCHv11VdjfX093n333firv/qr2Nvbi/X19Zibm4tyuRzdbvcgHFtcXIzJycn4+Z//+bTLBgAAAOCa3bipkZVKJVqt1sH1W7duxeuvvx6vv/56RER89NFHUavVYnNzM2q1WrRardjb20upWgAAAAAG5cYFYXfu3Dn39w8ePIgHDx5ERMSHH34YtVptEKUBAAAAkKIbNzXy/fffjzfffDP+8A//sK/2d+/eja997WvXXBUAAAAAabtxI8JmZmbik08+iY2NjZidnY1isZh2SQAAAABkwI0bEbY/NfLu3btCMAAAAAAO3LggbH19Pbrdbnz3u99NuxQAAAAAMuTGBWHlcjm2trbiwYMH8dd//ddplwMAAABARty4ICwiolKpRK1WiwcPHsTDhw/TLgcAAACADLhxQdjt27fj1VdfjeXl5fjqV78a5XI5Xn311fj2t7+ddmkAAAAApOjG7Rp57969qNVqUa/XD/6tXC7H22+/HW+//XbMz8/H3Nxc/MIv/EJ6RQIAAAAwcDduRFilUolSqRSvv/563LlzJ7rdbuzs7MTe3l7s7e3F8vJyTE5OxiuvvBLf/va34+OPP067ZAAAAAAG4MaNCHv11Vdjeno67t+/HxERn3zySdRqtdjc3IxarRaNRiMiInZ2dmJxcTEWFxdjdHQ0/vf//X9Ps+zcaTabMTEx0bPNwsJCLCwsDKgiAAAA4KpWVlZiZWWlZ5tmszmgak66cUFYpVKJTz755OD6rVu34vXXX4/XX389IiI++uijI8FYq9WKvb29tMrNrU6nE7u7uz3btNvtAVUDAAAAJKHdbp/7fT9NNy4Iu3Pnzrm/f/DgQTx48CAiIj788MOo1WqDKI1DRkZGYmxsrGebYrE4oGoAAACAJBSLxRgfH+/ZptlsRqfTGVBFR924IOyi7t69G3fv3k27jNwZGxuLp0+fpl0GAAAAkKB+ljmamJhIbdTYjQ3C2u32wZpg5XI5KpWKnSIBAAAAcuxGBmHf/e53Y35+/sS/T01NxfLycvw3/81/k0JVAAAAAKRpJO0Ckvbee+/F3NxcdLvdE5etra2oVqvxm7/5m2mXCQAAAMCA3bggbHl5OarVamxubsbOzk5sb2/H+vp6zM3NRblcjm63G++++278V//VfxV/8zd/k3a5AAAAAAzIjZsa+ezZs9ja2jryb3fv3o3XX389IiJqtVosLy/He++9F1NTU7G1tWV3QgAAAIAcuHEjwiYnJ3v+fn+02A9/+MPodDoxNzc3oMoAAAAASNONC8L29vb6aletVmNrayu2trbif/1f/9drrgoAAACAtN24IGx6ejq+8Y1v9NW2VCrFD3/4w/jOd75zzVUBAAAAkLYbt0bY3NxcjI6ORkTE22+/fW77/QX0AQAAALjZbtyIsFu3bsW3vvWt+Na3vhX/7X/738Zf//Vfn3ubfqdTAgAAADC8blwQFhGxuLgYr7/+evzwhz+Mcrkcv/mbvxk/+tGPTm370UcfRb1eH2yBAAAAAAzcjZsauW99fT1mZ2fjBz/4Qayvr8f6+nqUSqWoVqtRLpfj5Zdfjp2dnVhbW4uZmZm0ywUAAADgmt3YICzieRj2+PHj+PrXvx4Rz6dAbmxsHPx+f22w5eXlVOoDAAAAYHBu5NTIwxYXF2Nvby++9rWvHSyMv3+pVCqxvb0dv/ALv5B2mQAAAABcsxsfhEU8X0B/eXk5/uqv/io6nU7s7OxEp9OJra2tuHv3btrlAQAAADAANzYIa7fbZ/7uzp07A6wEAAAAgCy4cUHYJ598Eq+88kqMjo7GN77xjbTLAQAAACAjblwQ9uDBg9jZ2Ylutxvr6+tntus1YgwAAACAm+fG7RrZaDRie3s7tra24t69e2e2++CDD2JjYyP+3b/7dwOsDgAAAIC03LggbHJyMu7evXvuIvj379+PVqsVDx8+jEePHg2oOgAAAADScuOCsEaj0Xfb119/PZ48eRI/+tGP4pd/+ZevryhOaDabMTEx0bPNwsJCLCwsDKgiAAAA4KpWVlZiZWWlZ5tmszmgak66cUHY/fv34w//8A/jX//rf91X+/n5+Xj06FE8efLkmivjsE6nE7u7uz3bWMcNAAAAhku73T73+36ablwQNjc3F6+++mpUq9X4L//L//Lc9uVyOWq12gAq47CRkZEYGxvr2aZYLA6oGgAAACAJxWIxxsfHe7ZpNpvR6XQGVNFRNy4IK5fLMTMzE+VyOdbW1s4dGdZoNKLVag2mOA6MjY3F06dP0y4DAAAASFA/yxxNTEykNmpsJJWjXrPV1dX45V/+5Zibm4t//s//efz7f//vT23Xbrdjfn4+yuXygCsEAAAAYNBu3Iiwfe+//378i3/xL2JraytmZmYiIqJSqUS5XI7bt29Ho9E4mBI5NzeXZqkAAAAADMCNDcJu3boV29vbMT8/H++8805ERNTr9ajX6wdtut1ujI6OxvLyclplAgAAADAgN3Jq5GGrq6uxs7MTX/va1+LOnTvR7Xaj2+3GrVu3YmZmJhqNhkXZAQAAAHLgxo4IO+zOnTuxvLxs5BcAAABAjt34EWEAAAAAEDEEI8La7XYsLS3F1tZW3L59O6ampuLNN9+M//q//q/TLg0AAACAIZL5IOx3fud34gc/+MHB9c3NzfjWt74Vk5OT8dWvfjX+h//hf0ixOgAAAACGReanRtZqtYOf7969G3t7e9HpdOLf/bt/F//xP/7HePnll+Phw4fRbrdTrBIAAACArMt8EHb//v3odrtRKpXi/fffj1u3bkVERLVajXfffTd2dnai0+nEnTt34hvf+EbK1QIAAACQVZkPwtbX12N7ezsajUYUi8UTvy+VSrG8vByNRiM+++yzePnll+MP//APU6gUAAAAgCzLfBAW8XxK5P5IsLPcunUrlpeX44MPPoj/8B/+Q7zyyivxP//P//OAKgQAAAAg6zK/WP5FlcvlePfdd6Ner8cbb7wRv/iLvxjr6+vxhS98Ie3SAAAAAEjRUIwIu6iPP/44Pv7445iZmYkf/vCHUSqVTJcEAAAAyLmhHxH28ccfR61Wi+3t7ajVatFoNI78vlAoRLfbjbm5uVhdXY333nvP6DAAAACAHBrKIOz999+P9fX1ePfdd6PVah35XbfbPfU23W43tra24hd+4Rfiu9/9bvzGb/zGACoFAAAAICuGJgh7//33Y3V1NTY2Ng7+bT/02h/1dVilUol79+7F1NRU3Lt3L+7evRsRERsbG/Gv//W/jg8++CDefvvtwd0BAAAAAFKV+SDsj//4j2NpaelgyuNpI7663W5Uq9WYnp6OarV6EHqdZmZmJqrVarzxxhvxL//lv4yNjQ1TJQEAAAByIPNB2MzMzMGIr0KhcPDv5XI5ZmZmYnp6Ou7fv3+hPkulUvzwhz+Mx48fR6VSiXq9LgwDAAAAuOEyH4RVKpX48MMPI+L5yK/FxcWYn5+PO3fuXLnvxcXFqFQqwjAAAAAgIiK63YjO6cuPHxgpRBwaq8MQyXwQVi6Xo16vx/T0dLz77rtx69atRPuvVqvx6NGj+Bf/4l/EBx98kGjfnK3ZbMbExETPNgsLC7GwsDCgigAAAOB5CPbiN3u3+fStiBcEYadaWVmJlZWVnm2azeaAqjkp80HYq6++Gu+99178h//wH67tGDMzMzE3Nxe/+Zu/Gf/j//g/Xttx+CedTid2d3d7tmm32wOqBgAAAEhCu90+9/t+mjIfhO3v/nidPvroo2i1WrG+vh5f//rX45d/+Zev9XhEjIyMxNjYWM82xWJxQNUAAAAASSgWizE+Pt6zTbPZjE6nM6CKjsp8EHbv3r1Td4pM0uzs7MHPT548EYQNwNjYWDx9+jTtMgAAAIAE9bPM0cTERGqjxkZSOeoF3Lp1K5aWlq71GI1G42BHypdffvlajwUAAABAOjIfhEVE3L9//1r7/9a3vhXdbjcqlUrMzc1d67EAAAAASMdQBGHXbW5uLjqdTnzwwQfWpQIAAAC4oTK/RhjcBN3u8y14exkpRBRsvwsAAADXRhAGA9DpRrz4zd5tPn0r4gVBGAAAAFwbUyMBAAAAyAVBGAAAAAC5IAjjXI1GI6anp9MuAwAAAOBKBGE51mq1olAonHuZnJyMcrmcdrkAAAAAVyIIy7G1tbW+2y4tLV1jJQAAAADXTxCWY48ePeqrXbVaNSIMAAAAGHovpl0A6VhbW4tWqxWLi4vnrv917969AVUFAAAAcH0EYTm1vLwc5XI5lpeX0y4FAAAAYCAEYTm0sbERjUYjVldX0y4FAAAAYGCsEZZDjx49ilKpFG+88UbapQAAAAAMjCAsZ+r1etTr9Wi1WjE6OhqTk5MxPz8fGxsbaZcGAAAAcK0EYTmztLR05Hqj0Yi1tbWYnZ2NQqEQs7OzUa/XU6oOAACArOp2Iz7r9L50u2lXCb1ZIyxHGo1G1Gq1nm02NjZiY2Mj5ubmrCEGAADAgU434sVv9m7z6VsRLxQGUw9chiAsR8rlcqyurkar1YqdnZ2o1WrRaDRObbu2thZbW1uxvb094CoBAAAArocgLGfm5uaOXG+1WrG2thaPHj2KVqt15Hf1ej2mp6djc3NzgBUCAAAAXA9BWM6VSqVYXFyMxcXF2NjYiAcPHhwJxGq1Wjx+/DgWFxcTPW6z2YyJiYkr97OwsBALCwsJVAQAAAD0srKyEisrK1fup9lsJlDN5QjCODAzMxPVajXu379/ZMH8R48eJR6EdTqd2N3dvXI/7XY7gWoAAACA87Tb7US+y6dJEMYRpVIptre3Y2pq6iAMa7VaUavVolqtJnackZGRGBsbu3I/xWIxgWoAAACA8xSLxRgfH79yP81mMzqdTgIVXZwgjFO98847MTU1dXB9c3Mz0SBsbGwsnj59mlh/AAAAwPVKanmiiYmJ1EaWjaRyVDKvUqkcCb7O2l0SAAAAYFgIwjjT9PR02iUAAABwQ3W7EZ91el+63bSr5KYxNZIzlcvlg59v376dYiUAAADcNJ1uxIvf7N3m07ciXigMph7ywYgwznQ4CCuVSukVAgAAAJAAQRhn2traOvjZNEkAAABg2AnCONPOzs7Bz0nuGAkAAACQBkEYZ9rY2IiIiMXFxZQrAQAAALg6QRin2tjYiEajEaVSKR4+fJh2OQAAAHAl3/8w7QrIAkFYTtRqtRgdHY1CoRDT09NRr9fPbNtoNOLBgwcREfHee+9ZKB8AAIBM6yfk+u0NYRiCsNxYX1+PVqsVEc9DsampqZifnz/Rbv93t2/fjp2dnahUKgOuFAAAAPr3yU8jfu9P+2v71T+JaP/0Wssh4wRhOTE7O3vi39bW1mJ0dDRmZ2djfn4+pqamYnp6Oubm5mJ7ezvK5XIKlQIAAED//qge8Xf/2F/bv/2HiO+dPUGKHBCE5US1Wo2dnZ2Ym5uLcrl8ZLpjvV6PZ8+excOHD2Nvby+Wl5dNhwQAAGAo/NmPL9b+zy/YnpvlxbQLYHDK5XKsrq6mXQYAAAAkZu/vr7c9N4sRYQAAAMDQGv3c9bbnZhGEAQAAAEPrtS9erP2vXrA9N4sgDAAAABhaX65EfP5n+mv7cz8b8ZXK9dZDtgnCAAAAgKF166WIP/i1/tp+59cjii9dazlknCAMAAAAGGpfunt+m+/N9NeOm00QBgAAANx4vyUEIwRhAAAAAOSEIAwAAACAXHgx7QLIp2azGRMTEz3bLCwsxMLCwoAqAgAAAK5qZWUlVlZWerZpNpsDquYkQRip6HQ6sbu727NNu90eUDUAAABAEtrt9rnf99MkCCMVIyMjMTY21rNNsVgcUDUAAABAEorFYoyPj/ds02w2o9PpDKiiowRhpGJsbCyePn2adhkAAABAgvpZ5mhiYiK1UWMWywcAAAAgFwRhAAAAAOSCqZEwZLrdiE63d5uRQkShMJh6AAAAYFgIwmDIdLoRL36zd5tP34p4QRAGAAAAR5gaCQAAAEAuCMIAAAAAyAVBGAAAAAC5YI0wyDEL7wMAAJAngjDIMQvvAwAAkCemRgIAAACQC4IwAAAAAHJBEAYAAABALlgjDAAAAG4oG2TBUYIwAAAAuKFskAVHmRoJAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAADgBvj+h2lXkH0vpl0A+dRsNmNiYqJnm4WFhVhYWBhQRQAAAJBd/YRcv70R8cJIxJfuXn89Z1lZWYmVlZWebZrN5oCqOUkQRio6nU7s7u72bNNutwdUDQAAAGTXJz+N+L0/7a/tV/8k4rVfiii+dK0lnandbp/7fT9NgjBSMTIyEmNjYz3bFIvFAVUDAAAA2fVH9Yi/+8f+2v7tP0R8rx7x+79yvTWdpVgsxvj4eM82zWYzOp3OgCo6ShBGKsbGxuLp06dplwEAAACZ92c/vlj7P/9xekFYP8scTUxMpDZqzGL5AAAAABm29/fX2z5PBGEAAAAAGTb6uettnyeCMAAAAIAMe+2LF2v/qxdsnyeCMAAAAICUfP/D89t8uRLx+Z/pr7+f+9mIr1SuVtNNJggDAADghG434rNO70u3m3aVV5OH+0i6+gm5fnvj/Ha3Xor4g1/r75jf+fWI4kv9tc0ju0YCAABwQqcb8eI3e7f59K2IFwqDqec6JHkfu93n/fUyUogoDPHjxcV88tOI3/vT/tp+9U8iXvul3gHWl+4+D816+d7M83acTRAGAAAAV5SH4JCL+aN6xN/9Y39t//YfIr5Xj/j9X7naMX9LCHYuUyMBAAAAEvZnP75Y+z+/YHsuRxAGAAAAkLC9v7/e9lyOIAwAAAAgYaOfu972XI4gDAAAACBhr33xYu1/9YLtuRxBGAAAAEDCvlyJ+PzP9Nf253424iuV662H5wRhAAAAAAm79VLEH/xaf22/8+sRxZeutRz+D4IwAACAlHS7EZ91el+63bSrBC7rS3fPb/O9mf7akYwX0y4AAAAgrzrdiBe/2bvNp29FvFAYTD3A4P2WEGygjAgDAAAAIBcEYQAAAADkgiAMAAAAgFwQhAEAAACQC4IwAAAAAHLBrpGkotlsxsTERM82CwsLsbCwMKCKAACAYdDtPt9ts5eRQkTBTpuQipWVlVhZWenZptlsDqiakwRhpKLT6cTu7m7PNu12e0DVAAAAw6LTjXjxm73bfPpWxAuCMEhFu90+9/t+mgRhpGJkZCTGxsZ6tikWiwOqBgCAmy7JUURGJAGcrVgsxvj4eM82zWYzOp3OgCo6ShBGKsbGxuLp06dplwEAQE4kOYrIiCSAs/WzzNHExERqo8YEYQAAAFwro+iArBCEAQAAcK2MogOyYiTtAgAAAABgEARhAABAJnW7EZ91el+650y343p9/8O0KwC4GFMjAQCATDKdLl39hFy/vRHxwkjEl+5efz0ASTAiDAAAgCM++WnE7/1pf22/+icR7Z9eazkAiRGEAQAAcMQf1SP+7h/7a/u3/xDxvfr11pM3pgXD9TE1EgAAgCP+7McXa//nP474/V+5nlryaJinBX//w4ivTKVdBZzNiDAAAIAMS2NB+r2/v972DKd+142ziQJZJggDAABISVaDhdHPXW97ho9147gpBGEAAAAx+LApy8HCa1+8WPtfvWB7ho9147gpBGEAAMCNl8WRV1kOFr5cifj8z/TX9ud+NuIrleuth/RdZt04yCJBGAAAcKOlMfKqn0Aty8HCrZci/uDX+mv7nV+PKL50reWQAdaN46YQhAEAADda0iOvkhpdlvVg4Ut3z2/zvZn+2jH8rBvHTSEIAwAAhtagR14lObrsJgQLvyUEyw3rxnFTCMIAAIDEdLsRn3V6X7rd/vrK4sirJEeXJR0sJPnYw3HWjeOmeDHtAgAAgJuj04148Zu923z6VsQLhd5tLjry6rVfOnudqiRHXl1mdNnv/8rpv/tyJeLrf9FfsNZPsJDUYw+n2V837rc3zm9r3TiyzIgwAAAgc7I68irJ0WUWpB8Og9xJNOusG8dNIAgDAAAyJ8l1vZKc0pX0ul6ChXQlNf2Wf2LdOLJOEAYAAGROVkdepbFguGDheiS58QEwPKwRRiqazWZMTEz0bLOwsBALCwsDqggAYHh0u8/Xg+plpBBRGOK1oK5j5NV5axv1M/Iq6XW9SM9lpt+etd4b8E9WVlZiZWWlZ5tmszmgak4ShJGKTqcTu7u7Pdu02+0BVQMAMFySXhQ9i8Haa1+M+OFf9t9+UCOvLBh+cyS58QHwT9rt9rnf99MkCCMVIyMjMTY21rNNsVgcUDUAAPmWxd0GszzyKqnRZaQryem3wD8pFosxPj7es02z2YxOpzOgio4ShJGKsbGxePr0adplAACQgu9/GPGVqd5thn3klXW9si/p6bfDrJ9zMi1Zro3T9bPM0cTERGqjxiyWDwAAJCbJXfjsqMh1SmPjgzRkeWfMLNfGzSUIAwAAEpHGLnxGXnFZX65EfP5n+ms7rBsfZHlnzCzXxs0mCAO4AbrdiM86vS/dcxZBBuBmSWMExWV24YN9g37N7k+/7UdS028HfR+zfE5muTZuNmuEAdwAWVzkGIDr0+90ohdGBjtt0C58nCWrr9kkNz7I4n3M8jmZ5dq42YwIAwCAIZLl6UR24eM0WX7N9qOf6bdZvY9ZPiezXBs3myAMAAAGIKlp7GlNJ+pntItd+DhNHqbAZfU+ZvmczHJt3GyCMAAAOEOSazDuT2Pvden00ddlphOdJ6md2/KyCx8Xcx2v2fMMei2uNO5jP7J8Tma5Nm42QRjx+PHjmJ6ejtHR0SgUCjE5ORmzs7NRq9XSLg0AIFVJhVdJSno6UZJTuvKwCx8Xl/RrNqngNklZneaX5XMyy7VxswnCcqxWq8Xo6GgsLS1FRMT6+nrs7OzE8vJy1Ov1mJ6ejunp6Wi1WukWCgDAgaSnEyU5pSuNXfj6NVJ4vnFMr8uITWWuRZKv2ayuxZXVaX5ZPiezXBs3myAsp2q12kHINTc3F5ubm1GtVqNcLsfMzEzs7OxEpVKJWq0WU1NTwjAAgDMkOeqkn76Snk6U9JSufnbD63cXviTDq0Lh+W59vS4FQdi1SPI1m9W1uLI8zS/JczJpWa6Nm0sQlkOtVitmZ2cjIqJcLsfq6uqp7dbX1yMiotFoHLQHuIgk19YBSEOSU7CS6ivp6URpTOnqZxe+COHVTZHkazara3EN+zS/fs/JNGS5NobTi2kXwODNzs4ejPDanxZ5mv3RYRsbG1Gr1WJtbS3m5uYGVCVwE+yvrdPLp29FvOBLDJBBF52C9dovnT11J8m+9qcT/fbG+X31M50oq1O68mJ/1Nt5bYZZkq/ZrK7FlfR5CVwfI8JyptFoHFkE/4033ujZ/s033zz4uVdoBgCQFUmNRk1yClbS07mSnE6U5SldeTDoUW8Xmcqb5NTUpF6zWQ5uTfOD4WBEWM4sLy8f/FytVqNUKvVsPzMzc/Bzq9WKjY2NI/8GAJCEbvf5KNJPfhrxRx9G/E8/fj6SY/Rzz4OX/+7u85/7CQSSGo16mSlYv/8r199Xv/qdTvTlSsTX/6K/oC6LU7rSkNVRXP1Ov31hpL8wplAY7Kjtfl6zr30x4od/2X+fWQtuTfOD9BkRljNra2sHP1cq/f1fTLlcPvj5yZMnidcE1ynLa1RluTaAQdsPr17+f0b8P/48YvOvIrZ2n//3//7nz//9jxJc9LqfwCDJKVhZnc4VYee2y8ji2mVZ3U0xacO+FheQPiPCcqReP/p/j6+++mpft6tUKtFoNCIiYmOjj0nvkCFZXqMqy7UBDFqSI1mS6ivJKVhZns4V8fxxOG9tI1O6su0y02+vOuowDdbiAq7KiLAcObw2WMTRkV69HG93PFADALiKJEeyJNlXkmtnJb0OV5JrN/XLlK5sy+puitfBWlzAVRgRliMffPDBkevnrQ+27+WXXz5yfWtrq+9plQAA50lyJEuSfSW5dlbS63ANeu2mi8jq+lk3XZan36ZBcAucxYiwHNmf3rjvsiPCdnZ2EqsJho11vQD+yf574rP/X8T/63+J+D//YcSr/5/n//1//y/P/72f98QkR7Ik2VeSa2flaR2uLK6flQdZn34LkBVGhOXI8SDsslqtViL9wDCyrld69neU62Wk4MsVDFKv98T9Re7/vzMRX5nq3U+WF6VPcu0s63BxnYZ9N0WAQRGE5chlA6zjUyifPXt25VqazWZMTExcuZ+FhYVYWFi4cj9A9gkhuW55CVuTvJ8WpX8uySlYpnNxWUlPvwU4zcrKSqysrFy5n2azmUA1lyMI48KSGBHW6XRid3f3yv202+0r9wHAYGU1cMpL2JrU/bzoovSv/dLZ0/2SHMliVMzlWNdr+NlNERiEdrudyHf5NAnCcqRUKiUSYvW7yH4vIyMjMTY2duV+isXilfsAYLCSDJyyGqolbdD38/sfnj+dMS+L0icZEGU5bMry4vv0z/Rb4LoVi8UYHx+/cj/NZjM6nU4CFV2cICxHbt++nUgQdvv27Sv3MTY2Fk+fPr1yPwDkW1ZHcSUdXCV5P5OazniZRenPCsKSHMmS9KiYJAMiYRNZYPotcBVJLU80MTGR2sgyQViOXHYk1/HwLIkRYQBwk2U1oEtyOmPSi9J/uRJRiIjf/dPTR3N9/meeB1f9jGRJsi8A4GYRhOXIvXv3ol6vH1xvtVp9hVrHF8efnJxMujQAGAr9TBlMy6CnMya9KH2hEPHlqYj/y//peZ1//uPn4dno556v4/WVSv9rGiXZFwBwswjCcmRq6uj/HTcajahUzt8uZmdn58j1arWaaF0Awy4v61TddElNGbwOWZzOeF2L0t966fkxzzruRSTZFwBwMwjCcuTevXtHrvcbhB2eGlkqlaJcLiddGsBQy+o0OAFd/5KcMtivfkeXZXU6Y9KL0gMADMJI2gUwOJVK5chUyA8++KCv221tbR38fDxMAyC79gO6XpfzgrK8uMyUwV76HcHVT7ska0tyOuP+ovT96GdRegCAQRCE5cwbb7xx8PPh9cJ6OdxuaWkp8ZoA4Dr1EzZdZsrgWS46gqv9095tkqzttT6nJ+47bzrjlysR35t5vvj8aT7/MxF/NGtRegAgOwRhOTM/P3/wc61WO7f94TblcjlX64N1uxGfdXpfukZSwFByfmdfP+FVv+36GXmV5JTBpEeXJT2d8azQ6rh+pjPuL0q/+42If/taxL98JeKfTzz/7799LeI/fSPivzMlEgDIEGuE5UylUolqtXoQcG1sbMTMzMyZ7dfX1w9+zttosKyu+QNcnfM7XUkt/J7k2llJThlMckH684510fb70xl/e+P8fi4yndGi9ADAsDAiLIdWV1cPfn706NGZ7VqtVqytrUXE850i5+bmrr02IH1GS3Gdkpw2mOTIqySnDCY5givCdEYAgCQJwnKoXC4fjPSq1+vx+PHjU9vdv38/Ip7vFHl4ZBhws1lgneuUZHiV5NpZSU4ZTHIEV4TpjAAASRKE5dTMzExsbm5GqVSKpaWlmJ2djXq9Hq1WK2q1WkxNTUW9Xo9KpRIfffTRkd0mAeCykgyvkhx5leQOiEmP4Lqu3Rn3pzP+xf814j/+357/9/d/xe6OAMDNJgjLsWq1Gnt7e7G8vByNRiPu378fo6OjMTs7G7dv34719fXY3t4WggGQmCTDq6RHXvUzFfB7M+e3S3oEV5K1AXBz9LuxDHCUxfKJxcXFWFxcTLsMADKs2z1/SuxI4fm0u16SDK9e+2LED/+y/77OG3nVj9/qI2i6rgXpz9NPbQAMh6Q2lgFOEoQBmZPUF26Gw/c/jPjKVNpVcJ6kdtpMMrz6ciXi63/R35pj/Y68SsqX7p4fhF1kBNdI4fnje14bAIZfkrsiAycJwoDMSeoLN+nz18yLu+lBcJLhVVojr5JykRFchYL3PIDrkMU/NFxmY5nf/5XrrYmT/DF3eAnCAHJi0B/W/pp5OYMOggf9ukg6vEp65BUA1yOLgVNENv/QcJmNZQRhyfLH3JtNEAZwA2Txw9pfM9OXxddFxODDq35HXmX1SxpAv7L8PpbFwCmrktxYhovzx9ybTxAGMOSy+mHtr5npyurrol9pLPye5Je0LH8ZBW4uYdPNkPSuyFyMP+befCNpFwDA1Vzmw3oQ0vhrpm3E/0lWXxd5USg8H2nX6zKs67wBcL1eu+Aux0nsisw/ucwfcxkugjCAIZfVD+uk/5rZ7zS/rIZhg64rq68LAKC3L1ciPv8z/bUd9K7IeWBq6s0nCAMYcln9sE7yr5kXnebX/unFjn1VWQzpsvq6AAB6299Yph9Z3BV52JmaevNZI4xUNJvNmJiY6NlmYWEhFhYWBlQRDK+sflh/uRLx9b/ob3reeX/NzPJaDVldiyurr4ukWYsLgJvIrsjpee2LET/8y/7bm5p60srKSqysrPRs02w2B1TNSYIwUtHpdGJ3d7dnm3a7PaBqYLhl9cN6/6+Z5/1PXMT5f83M8sL7WQ3p0nhdfP/DiK9MXb2fi7AwNED++CPIc2lsLJMHSf4xN6/a7fa53/fTJAgjFSMjIzE2NtazTbFYHFA1MNyy/GGd1F8zszzNL6shXdKvi36nf74wcv7z6QsMAFfhjyBcpyT/mJtXxWIxxsfHe7ZpNpvR6XQGVNFRgjBSMTY2Fk+fPk27DBLU7UZ0ur3bjBTsknYdhv3Dup+/ZmZ5ml9WQ7okXxdJT//0BQYAyDJTU6+mn2WOJiYmUhs1JggDEtHpRrz4zd5tPn3Ll9/rctM/rLM6/TMi2yFdUq+LrE7/BABIi6mpw8uukQA5Mcwf1mlsI97vDo9J7o6Zhn5eF5eZ/gkAAFkkCAMg85LeRrzf9a76aZdGSDdoWZ3+CQAAFyUIA2Ao9DOts59pfhdd76r9095tkg7psijL0z8BAOAirBEGwI3RzzS/61jvatBrtH3/w4ivTCXTVz+yvEYbAGSFXZFhOBgRBvTU7zpJXA+Pf/LSWu+q3zXakpy2mZQ8TP8EgKsqFCJeGOl9sYM6pE8QBjmWxS/ceeLxT0eW17tKetpmUvIw/RMAgHwQhEFOZfULd154/NOT5fWuLjNtc1CSWqMNAADSJAiDnMryF+488Pin57ULrl81yPWu0pq2mZR+p38CAEBaBGGQU8P+hXvYefzTk+X1rrI8bRMAAG4Cu0ZCTvnCnS6Pf3r217s6b5fHiMGvd5XlaZsAAFlm1076JQiDnPKFO10e/3R96e75QVga61299sWIH/5l/+3Pm7bpfwgBgLwoFCJe8P819MHUSMipLK+TlAce/+xLY72rpKdt2sYdAACOEoRBTmV5naQ88Phzmv1pm/0Y9LRNAAC4CQRhkFO+cKfL489Z+pmOmca0TQAAuAkEYZBjvnCna5gf/+9/mHYF+ZbGtE0AALgJLJYP9OQLd7rSePz7Cbl+e+P5+lJZDOm4HhbeBwDgJjAiDIADn/w04vf+tL+2X/2TiPZPr7UcMsTC+wAA3ASCMAAO/FE94u/+sb+2f/sPEd+rX289AAAASTI1EoADf/bji7X/8x9H/P6vXE8tAABcneUN4ChBGKloNpsxMTHRs83CwkIsLCwMqCJIzvc/jPjKVNpVXM7e319v+5vK/2ACAFlVKES84P9DGKCVlZVYWVnp2abZbA6ompMEYaSi0+nE7u5uzzbtdntA1UD/bvpC8qOfu972N5X/wQQAgOfa7fa53/fTJAgjFSMjIzE2NtazTbFYHFA10J+LLiT/2i9FFF+61pIS99oXI374l/23/9UvXl8tAADA8CkWizE+Pt6zTbPZjE6nM6CKjhKEkYqxsbF4+vRp2mXAhVxmIflhWz/ry5WIr/9Ff/fz53424iuV3m1MGQQAgHzpZ5mjiYmJ1EaN2TUSoE+XWUh+2Nx6KeIPfq2/tt/59fNHvBUKz6eJ9roUBGEAAMCACMIA+pSXheT7WdvsezPDuQYaAACQb4IwgD5ZSP6f/JYQDAAAGELWCAPok4Xk05WX9cbycj8BACANRoQB9OnLlYjP/0x/bftZSJ6Lyct6Y3m5nwAAkAZBGECfkl5IHgAAgMEShAFcgIXkAQAAhpc1woDc+/6HEV+ZSq4/C8lnn3W4AAAgnwRhwI32/Q/Pb/PbG8/XXTKKKz8KhYgXBF0AABfij4ncBKZGAjfWJz+N+L0/7a/tV/8kov3Tay0HAACGmk19uAkEYcCN9Uf1iL/7x/7a/u0/RHyvfr31AAAAkC5BGHBj/dmPL9b+zy/YHgAAgOFijTDgxtr7++ttnyXWawAAADifIAy4sUY/d73ts8Ti7wAAAOczNRK4sV774sXa/+oF2wMAADBcBGHAjfXlSsTnf6a/tj/3sxFfqVxvPQAAAKRLEAbcWLdeiviDX+uv7Xd+PaL40rWWAwAAQMoEYcCN9qW757f53kx/7QAAABhugjAg935LCAYAAJALgjAAAAAAcuHFtAsgn5rNZkxMTPRss7CwEAsLCwOqCAAAALiqlZWVWFlZ6dmm2WwOqJqTBGGkotPpxO7ubs827XZ7QNUAAAAASWi32+d+30+TIIxUjIyMxNjYWM82xWJxQNUAAAAASSgWizE+Pt6zTbPZjE6nM6CKjhKEkYqxsbF4+vRp2mUAAAAACepnmaOJiYnURo0JwgAAACBDRgoRn751fhvg4gRhAAAAkCGFQsQLgi64FiNpFwAAAAAAgyAIAwAAACAXBGEAAAAA5II1wgAAAICBsykAaRCEAQAAAANnUwDSYGokAAAAALlgRBgARxiiDgAA3FSCMACOMEQdAAC4qUyNBAAAACAXBGEAAAAA5IKpkQApsRYXAADAYBkRBhnx/Q/TroBBKxQiXhjpfSkIwgAAABIjCIMB6Cfk+u2N5MIwoRoAAACcJAiDa/bJTyN+70/7a/vVP4lo/7R3m0GHagAAAHBTCMLgmv1RPeLv/rG/tn/7DxHfq5/9+6RDNQAAAMgTQRhcsz/78cXa/3mP9kmGagAAAJA3gjC4Znt/n1z7JEM1AAAAyBtBGFyz0c8l1z7JUA0AAADy5sW0CyCfms1mTExM9GyzsLAQCwsLA6ro+rz2xYgf/mX/7X/1i2f/LslQbdh9/8OIr0ylXQUAAACHraysxMrKSs82zWZzQNWcJAgjFZ1OJ3Z3d3u2abfbA6rmen25EvH1v+hvba+f+9mIr1TO/n2SoVqW9bsz5gsjEV+6e/31AAAA0J92u33u9/00CcJIxcjISIyNjfVsUywWB1TN9br1UsQf/Nrz4OY83/n1iOJLZ/8+yVAtqy66M+Zrv9T7MQMAAGBwisVijI+P92zTbDaj0+kMqKKjBGGkYmxsLJ4+fZp2GQPzpbvnB2Hfmzl/dFOSoVpWXWZnzN//leutCQAAgP70s8zRxMREaqPGLJYPGfFbfU7x62cqYD+hWlbZGRMAAIDrIgiDG6jfUC2L7IwJAADAdRGEAZliZ0wAAACuiyAMyJTXLrjT5bDujAkAAMDgCcKATPlyJeLzP9Nf22HdGRMAAIB0CMKATNnfGbMfw7ozJgAAAOkQhAGZc9N3xgQAACAdgjB6ajQaMT09nXYZcMIw74wJAABAOgRhOdVqtaJQKJx7mZycjHK5nHa5AAAAAFf2YtoFkI61tbW+2y4tLV1jJTBcRgoRn751fhsAAACyRxCWU48ePeqrXbVaNSIMDikUIl4QdAEAAAwlQVgOra2tRavVisXFxXPX/7p3796AqgIAAAC4XoKwHFpeXo5yuRzLy8tplwIAAAAwMBbLz5mNjY1oNBrW/SIV3/8w7QoAAADIM0FYzjx69ChKpVK88cYbaZfCDdNPyPXbG8IwAAAA0iMIy5F6vR71ej1arVaMjo7G5ORkzM/Px8bGRtqlMeQ++WnE7/1pf22/+icR7Z9eazkAAABwKkFYjhyfDtloNGJtbS1mZ2ejUCjE7Oxs1Ov1lKpjmP1RPeLv/rG/tn/7DxHf8zIDAAAgBYKwnGg0GlGr1Xq22djYiKmpqZifnx9QVdwUf/bji7X/8wu2BwAAgCTYNTInyuVyrK6uRqvVip2dnajVatFoNE5tu7a2FltbW7G9vT3gKhlWe39/ve0BAAAgCYKwHJmbmztyvdVqxdraWjx69ChardaR39Xr9Zieno7Nzc0BVsiwGv3c9bYHAACAJJgamWOlUikWFxdjb28v1tfXo1QqHfl9rVaLx48fp1McQ+W1L16s/a9esD0AAAAkwYgwIiJiZmYmqtVq3L9//8iC+Y8ePYrFxcXEj9dsNmNiYuLK/SwsLMTCwkICFXEVX65EfP0v+lsw/+d+NuIrleuvCQAAgGStrKzEysrKlftpNpsJVHM5gjAOlEql2N7ejqmpqYMwrNVqRa1Wi2q1muixOp1O7O7uXrmfdrudQDVc1a2XIv7g1yJ+e+P8tt/59YjiS9deEgAAAAlrt9uJfJdPkyAsZWtra4nv0lipVK600P0777wTU1NTB9c3NzcTD8JGRkZibGzsyv0Ui8UEqiEJX7p7fhD2vZnn7QAAABg+xWIxxsfHr9xPs9mMTqeTQEUXJwjjhEqlEtVqNWq1WkTEmbtLXsXY2Fg8ffo08X7Jtt8SggEAAAytpJYnmpiYSG1kmSAsZdVqNdbX1xPt8/ii95cxPT19EIQBAAAA3ASCsJSVy+Uol8tpl3HC4Zpu376dYiUAAAAAyRhJuwCy6XAQlsQIMwAAAIC0CcI41dbW1sHP09PTKVYCAAAAkAxBGKfa2dk5+DnpHSMBAAAA0iAI41QbGxsREbG4uJhyJQAAAADJsFg+J2xsbESj0YhSqRQPHz5Muxy4kpFCxKdvnd8GAACAm8+IsByo1WoxOjoahUIhpqeno16vn9m20WjEgwcPIiLivffes1A+Q69QiHhhpPelIAgDAADIBSPCcmB9fT1arVZEPA/FpqamYm5uLlZXV4+0q9VqMTs7G7dv347t7e0jO0cCAAAA6THbJRlGhOXA7OzsiX9bW1uL0dHRmJ2djfn5+Ziamorp6emYm5sTggEAAEDGmO2SDEFYDlSr1djZ2Ym5ubkol8tHpjvW6/V49uxZPHz4MPb29mJ5edl0SAAAAOBGMjUyJ8rl8ompkAAAAAB5YkQYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuCMIAAAAAyIUX0y6AfGo2mzExMdGzzcLCQiwsLAyoIgAAAOCqVlZWYmVlpWebZrM5oGpOEoSRik6nE7u7uz3btNvtAVUDAAAAJKHdbp/7fT9NgjBSMTIyEmNjYz3bFIvFAVUDAAAAJKFYLMb4+HjPNs1mMzqdzoAqOkoQRirGxsbi6dOnaZcBAAAAJKifZY4mJiZSGzVmsXwAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC5IAgDAAAAIBcEYQAAAADkwotpFwCkZ6QQ8elb57cBAACAm0AQBjlWKES8IOgCAAAgJ0yNBAAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALL6ZdAPnUbDZjYmKiZ5uFhYVYWFgYUEUAAACQrJFCxKdvnd/mJllZWYmVlZWebZrN5oCqOUkQRio6nU7s7u72bNNutwdUDQAAACSvUIh44YYFXedpt9vnft9PkyCMVIyMjMTY2FjPNsVicUDVAAAAAEkoFosxPj7es02z2YxOpzOgio4ShJGKsbGxePr0adplAAAAAAnqZ5mjiYmJ1EaNWSwfAAAAgFwQhAEAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAcuHFtAsAOG6kEPHpW+e3AQAAgIsQhJGKZrMZExMTPdssLCzEwsLCgCoiSwqFiBcEXQAAAENnZWUlVlZWerZpNpsDquYkQRip6HQ6sbu727NNu90eUDWX9/0PI74ylXYVAAAAkA3tdvvc7/tpEoSRipGRkRgbG+vZplgsDqia033/w/Pb/PZGxAsjEV+6e/31AAAAQNYVi8UYHx/v2abZbEan0xlQRUcJwkjF2NhYPH36NO0yzvTJTyN+70/7a/vVP4l47Zciii9da0kAAACQef0sczQxMZHaqDFBGJzij+oRf/eP/bX923+I+F494vd/5XprAgAA4PrZvOtmG0m7AMiiP/vxxdr/+QXbAwAAkE2FwvMlcHpdCoKwoSUIg1Ps/f31tgcAAAAGTxAGpxj93PW2BwAAAAZPEAaneO2LF2v/qxdsDwAAAAyeIAxO8eVKxOd/pr+2P/ezEV+pXG89AAAAwNUJwuAUt16K+INf66/td349ovjStZYDAAAAJEAQBmf40t3z23xvpr92AAAAQPoEYXAFvyUEAwAAgKEhCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuvJh2AcDNMFKI+PSt89sAAABAWgRhQCIKhYgXBF0AAABkmKmRAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAcsFi+aSi2WzGxMREzzYLCwuxsLAwoIoAAACAq1pZWYmVlZWebZrN5oCqOUkQRio6nU7s7u72bNNutwdUDQAAAJCEdrt97vf9NAnCSMXIyEiMjY31bFMsFgdUDQAAAJCEYrEY4+PjPds0m83odDoDqugoQRipGBsbi6dPn6ZdBgAAAJCgfpY5mpiYSG3UmMXyAQAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCsCHUaDRieno6NjY2rtTP48ePY3p6OkZHR6NQKMTk5GTMzs5GrVZLqFIAAACA7BCEDZFWqxWzs7MxOTkZtVotnj17dql+arVajI6OxtLSUkRErK+vx87OTiwvL0e9Xo/p6emYnp6OVquVYPUAAAAA6Xox7QI4X6vVikePHsXjx4+v3FetVovp6emIiJibm4vV1dWD35XL5ZiZmYmpqamo1WoxNTUV29vbUSqVrnxcAAAAgLQZEZZxjx8/jqmpqajX61fua39EWcTz0OtwCHbY+vp6RDyfgrnfHgAAAGDYCcIyrF6vR7VajZ2dndjc3DwzuOrX7OzswXTH/WmRp9kfGRbxfATZ2tralY4LAAAAkAWCsAyrVCpRqVQOrt+7d+/SfTUajSOL4L/xxhs927/55psHP/cKzQAAAACGhSBsiFxlra7l5eWDn6vV6rl97Y8Ii3g+pfKqO1QCAAAApE0QlhOHpzceHmXWS7lcPvj5yZMnidcEAAAAMEiCsBw4vtD+q6++2tftDgdmRoQBAAAAw04QlgOH1waLODrSq5fj7ZLYuRIAAAAgLYKwHPjggw+OXO93rbGXX375yPWtra2kSgIAAAAYOEFYDjQajSPXLzsibGdnJ7GaAAAAAAZNEJYDx4Owy2q1Won0AwAAAJAGQVgOXDbAOj6F8tmzZ1cvBgAAACAlL6ZdAMMjyRFhzWYzJiYmrtzPwsJCLCwsJFARAAAA0MvKykqsrKxcuZ9ms5lANZcjCMuBUqmUSIjV7yL7/eh0OrG7u3vlftrtdgLVAAAAAOdpt9uJfJdPkyDsAtbW1mJ+fj7RPiuVSmxvbyfa53G3b99OJAi7ffv21Yv5P4yMjMTY2NiV+ykWiwlUAwAAAJynWCzG+Pj4lftpNpvR6XQSqOjiBGE5cNmRXMfDsyRHhI2NjcXTp08T6w8AAAC4XkktTzQxMZHayDJB2AVUq9VYX19PtM8kw6Wz3Lt3L+r1+sH1VqvV13GPL44/OTmZdGkAAAAAAyMIu4ByuRzlcjntMi5samrqyPVGoxGVSuXc2+3s7By5Xq1WE60LAAAAYJBG0i6A63fv3r0j1xuNRl+3Ozw1slQqDWUICAAAALBPEJYDlUrlyFTIDz74oK/bbW1tHfx8PEwDAAAAGDaCsJx44403Dn4+vF5YL4fbLS0tJV4TAAAAwCAJwnJifn7+4OdarXZu+8NtyuWy9cEAAACAoScIGyKH1+y6qEqlciTM2tjY6Nn+8O6YRoMBAAAAN4EgbIgcX+T+osHY6urqwc+PHj06s12r1Yq1tbWIeL5T5Nzc3IWOAwAAAJBFgrAh0Wq1TozMevLkyYX6KJfLByO96vV6PH78+NR29+/fj4jnO0UeHhkGAAAAMMwEYRnWarVidnY2pqenY3R09MSIsHq9HoVCIaanp2N2dravRfBnZmZic3MzSqVSLC0tHdyu1WpFrVaLqampqNfrUalU4qOPPjqy2yQAAADAMHsx7QI423WNyKpWq7G3txePHz+OJ0+exP3796PVakWpVIp79+7F+vp6zMzMJH5cAAAAgDQJwnJscXExFhcX0y4DAAAAYCBMjQQAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC58GLaBZBPzWYzJiYmerZZWFiIhYWFAVUEAAAAXNXKykqsrKz0bNNsNgdUzUmCMFLR6XRid3e3Z5t2uz2gagAAAIAktNvtc7/vp0kQRipGRkZibGysZ5tisTigagAAAIAkFIvFGB8f79mm2WxGp9MZUEVHCcJIxdjYWDx9+jTtMgAAAIAE9bPM0cTERGqjxiyWDwAAAEAuCMIAAAAAyAVBGAAAAAC5YI0wGDIjhYhP3zq/DQAAAHCUIAyGTKEQ8YKgCwAAAC7M1EgAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC5IAgDAAAAIBcEYQAAAADkgiAMAAAAgFwQhAEAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBceDHtAsinZrMZExMTPdssLCzEwsLCgCoCAAAArmplZSVWVlZ6tmk2mwOq5iRBGKnodDqxu7vbs0273R5QNQAAAEAS2u32ud/30yQIIxUjIyMxNjbWs02xWBxQNQAAAEASisVijI+P92zTbDaj0+kMqKKjBGGkYmxsLJ4+fZp2GQAAAECC+lnmaGJiIrVRYxbLBwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC5IAgDAAAAIBcEYQAAAADkgiAMAAAAgFwQhAEAAACQC4IwAAAAAHLhxbQLIJ+azWZMTEz0bLOwsBALCwsDqggAAAC4qpWVlVhZWenZptlsDqiakwRhpKLT6cTu7m7PNu12e0DVAAAAAElot9vnft9PkyCMVIyMjMTY2FjPNsVicUDVAAAAAEkoFosxPj7es02z2YxOpzOgio4ShJGKsbGxePr0adplAAAAAAnqZ5mjiYmJ1EaNWSwfAAAAgFwQhAEAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBceDHtAiAPRgoRn751fhsAAADg+gjCYAAKhYgXBF0AAACQKlMjAQAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIhRfTLoB8ajabMTEx0bPNwsJCLCwsDKgiAAAA4KpWVlZiZWWlZ5tmszmgak4ShJGKTqcTu7u7Pdu02+0BVQMAAAAkod1un/t9P02CMFIxMjISY2NjPdsUi8UBVQMAAAAkoVgsxvj4eM82zWYzOp3OgCo6qtDtdrupHJlcmpiYiN3d3RgfH4+nT5+mXU5Pn3UiXvxm7zafvhXxgpX2AAAAoG9pZgO+wgMAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgbAg1Go2Ynp6OjY2NgR0LAAAAYNgJwoZIq9WK2dnZmJycjFqtFs+ePbtSX4VC4dzL5ORklMvlBO8FAAAAQDoEYUOg1WrF0tJSjI6OJjYKbG1tre+2S0tLiRwTAAAAIE2CsIx7/PhxTE1NRb1eT7TfR48e9dWuWq0aEQYAAADcCC+mXQBnq9frUa1WY3FxMSKej+Kan5+/cr9ra2vRarVicXHx3PW/7t27d+XjAQAAAGSBICzDKpXKketJhVLLy8tRLpdjeXk5kf4AAAAAhoEgbIiUSqUr97GxsRGNRiNWV1evXhAAAADAELFGWM48evQoSqVSvPHGG2mXAgAAADBQgrAcqdfrUa/Xo9VqxejoaExOTsb8/HxiO1ECAAAAZJkgLEeWlpaOXG80GrG2thazs7NRKBRidnY28d0pAQAAALJCEJYTjUYjarVazzYbGxsxNTWVyM6UAAAAAFljsfycKJfLsbq6Gq1WK3Z2dqJWq0Wj0Ti17draWmxtbcX29vaAqwQAAAC4PoKwHJmbmztyvdVqxdraWjx69ChardaR39Xr9Zieno7Nzc0BVggAAABwfQRhOVYqlWJxcTEWFxdjY2MjHjx4cCQQq9Vq8fjx41hcXEz82M1mMyYmJq7cz8LCQiwsLCRQEQAAANDLyspKrKysXLmfZrOZQDWXIwgjIiJmZmaiWq3G/fv3jyyY/+jRo2sJwjqdTuzu7l65n3a7nUA1AAAAwHna7XYi3+XTJAjjQKlUiu3t7ZiamjoIw1qtVtRqtahWq4kea2RkJMbGxq7cT7FYTKAaAAAA4DzFYjHGx8ev3E+z2YxOp5NARRcnCLuAtbW1xHdUrFQqmVuU/p133ompqamD65ubm4kHYWNjY/H06dNE+wQAAACuT1LLE01MTKQ2smwklaOSaZVK5UjwddbukgAAAADDxIiwC6hWq7G+vp5on6VSKdH+kjI9PR21Wi3tMgAAAAASIwi7gHK5HOVyOe0yBuLw/bx9+3aKlQAAAAAkw9RITnU4CMvqqDUAAACAixCEcaqtra2Dn6enp1OsBAAAACAZgjBOtbOzc/Bz0jtGAgAAAKRBEMapNjY2IiJicXEx5UoAAAAAkiEIGyKtVmsgx9nY2IhGoxGlUikePnw4kGMCAAAAXDdB2BBpNBpHrvcbjNVqtRgdHY1CoRDT09NRr9d7HuPBgwcREfHee+9ZKB8AAAC4MQRhQ6LVasXS0tKRf3vy5Elft11fXz8IzWq1WkxNTcX8/PyJdvu/u337duzs7ESlUrly3QAAAABZIQjLsFarFbOzszE9PR2jo6MnRoTV6/WDUV6zs7NnjvSanZ098W9ra2sxOjoas7OzMT8/H1NTUzE9PR1zc3Oxvb0d5XL5Wu4TAAAAQFpeTLsAzlYqlWJ9ff3K/VSr1djZ2Ynl5eWo1Wrx7NmzgxFi9Xo9KpVKPHz4MKrVqqmQAAAAwI0lCMuJcrkcq6uraZcBAAAAkBpTIwEAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAcuHFtAsgn5rNZkxMTPRss7CwEAsLCwOqCAAAALiqlZWVWFlZ6dmm2WwOqJqTBGGkotPpxO7ubs827XZ7QNUAAAAASWi32+d+30+TIIxUjIyMxNjYWM82xWJxQNUAAAAASSgWizE+Pt6zTbPZjE6nM6CKjip0u91uKkcmlyYmJmJ3dzfGx8fj6dOnaZfT02ediBe/2bvNp29FvGClPQAAAOhbmtmAr/AAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhAAAAAOSCIAwAAACAXBCEAQAAAJALgjAAAAAAckEQBgAAAEAuCMIAAAAAyAVBGAAAAAC5IAgDAAAAIBdeTLsAyKqRQsSnb53fBgAAABgOgjA4Q6EQ8YKgCwAAAG4MUyMBAAAAyAVBGAAAAAC5IAgDAAAAIBesEUYqms1mTExM9GyzsLAQCwsLA6oIAAAAuKqVlZVYWVnp2abZbA6ompMEYaSi0+nE7u5uzzbtdntA1QAAAABJaLfb537fT5MgjFSMjIzE2NhYzzbFYnFA1QAAAABJKBaLMT4+3rNNs9mMTqczoIqOKnS73W4qRyaXJiYmYnd3N8bHx+Pp06dplwMAAAAMWJrZgMXyAQAAAMgFQRgAAAAAuSAIAwAAACAXLJYPfVpZWYl2ux3FYjEWFhbSLgc4hfMUss95CsPBuQrZ5zy9HIvlM1DDvFj+MNcOeeE8hexznsJwcK5C9g3zeWqxfAAAAAC4ZoIwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5MKLaRdAvvzt3/7tkf8yGCsrK9Fut6NYLMbCwkLa5fRtWOuOUDsXN8yPu9rTMcy1D6thfszVno5hrn2YDfPjPqy1D2vdEcNd+zBLMxsodLvd7sCPSm698MIL0el0YmRkJD777LO0y7mQiYmJ2N3djfHx8Xj69Gna5VzIsNY+rHVHqD0tak+H2tMxrLUPa90Rak+L2tOh9nQMa+3DWneE2tOSZjZgaiQAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAABy4cW0CyCfOp1OTExM9GyzsLAQCwsLA6oIAAAAuKqVlZVYWVnp2abT6QyompMK3W63m9rRyZ1CodB32y984QtRLBavsZqLaTab0el0YmRkJMbGxtIu50KGtfZhrTtC7WlRezrUno5hrX1Y645Qe1rUng61p2NYax/WuiPUfh3a7Xb8zd/8Td/tBx1LCcIYqJGRkYG/yAEAAIDsKRQKAx8dZmokA/W5z30ufvrTn8YLL7wQ/+yf/bO0ywEAAAAG7D//5/8cn332Wbz00ksDP7YRYQAAAADkgl0jAQAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAAIBcEIQBAAAAkAuCMAAAAAByQRAGAAAAQC4IwgAAAADIBUEYAAAAALkgCAMAAAAgFwRhcIZGoxHT09OxsbExkOM9fvw4pqenY3R0NAqFQkxOTsbs7GzUarWBHB+GRdbPlf33Drhp0jz3sn7eQ5Zk/XzxOUne+Z6ZPkEYHNNqtWJ2djYmJyejVqvFs2fPrvV4tVotRkdHY2lpKSIi1tfXY2dnJ5aXl6Ner8f09HRMT09Hq9W61jog69I+V1qtVhQKhXMvk5OTUS6Xr6UGSEOa517a5z0Mk7TPF5+T0JvvmRnSBbrdbre7t7fXXVxc7EbEkcvq6uq1HXNzc/PgOHNzc6e2qVQq3Yjolsvl7t7e3rXVAlmWhXNleXn5xPvDWZednZ3Ejw9pSPPcy8J5D8MiC+eLz0k4ne+Z2SMIg+7zD+5yudytVqsDe4Pa29vrlkqlgzefs+zs7BzUUq1Wr6UWyLKsnCv7NZx3cZ5yU6R57mXlvIdhkJXzxecknOR7ZjaZGknu1ev1qFarsbOzE5ubm7G6ujqQ487Ozh4MQ90frnqacrkcMzMzEfF8eOva2togyoPMyMK5sra2Fq1WKxYXF2Nzc7PnZX19PbHjQprSPPeycN7DsMjC+eJzEk7yPTO7Ct1ut5t2EZAl9Xo9pqamDq6vrq7G3NxcosdoNBoxOTl5cH1vby9KpdKZ7Tc2NmJ2djYiIkqlUuzt7SVaD2RVVs6V/Rp2dnYS6Q+yLs1zLyvnPQyDrJwvPifhfL5nZocRYXBMrzeKpCwvLx/8XK1Wzz3mflIf8XyRxUHtMAJpy8K5srGxEY1Go+df1OCmSfPcy8J5D8MiC+eLz0noj++Z2SEIgxQcHnZaqVT6us3h3XWePHmSeE2QRVk4Vx49ehSlUineeOONK/cFwyLNcy8L5z0MiyycLz4nITuy8J4wDARhMGD1ev3I9VdffbWv2x1+I8tLUk++ZeFcqdfrUa/Xo9VqxejoaExOTsb8/LxzkBstzXMvC+c9DIssnC8+JyE7svCeMCwEYTBgtVrtyPXDCXwvx9sdf6ODmyYL58rxaR6NRiPW1tZidnY2CoVCzM7OOhe5cdI897Jw3sOwyML54nMSsiML7wnDQhAGA/bBBx8cud7vXPGXX375yPWtra2kSoJMSvtcaTQaJ/6H4riNjY2YmpqK+fn5Sx0DsijNcy/t8x6GSdrni89JyJa03xOGyYtpFwB502g0jly/bFJvVx5uurTPlXK5HKurq9FqtWJnZydqtdqJmvatra3F1tZWbG9vX+pYkCVpnntpn/cwTNI+X3xOQrak/Z4wTARhMGBn/Q/CRbVarUT6gazKwrlyfEvrVqsVa2tr8ejRoxP91uv1mJ6ejs3NzUsfD7IgzXMvC+c9DIssnC8+JyE7svCeMCxMjYQBu+wby/Ghrc+ePbt6MZBhWTxXSqVSLC4uxt7eXqyvr584Vq1Wi8ePHyd2PEhDmudeFs97yKosni8+JyE9WXxPyCpBGAypPCT1kITrOldmZmbio48+OrE19aNHj67leDBs0vyc8hkJ/fM5CRyWh89QQRgMWL+LFg6qH8iqYThXSqVSbG9vH/mf/Farde7iwZBlaZ57w3DeQ1YMw/nicxIGZxjeE7JCEEbmrK2tRaFQSPQyNTWV9t06cPv27Uz1A5cxiPN0mM6Vd95558h1658wzNI894bpvIe0DdP54nMSrt8wvSekTRAGA3bZhP34ENU8JPXk2zCdK5VKJarV6sH1pBYrhTSkee4N03kPaRum88XnJFy/YXpPSJtdI8mcarUa6+vrifaZpZP53r17Ua/XD663Wq2+6ju+aOHk5GTSpUHfBnGeDtu5Mj09baoHN0Ka596wnfeQpmE7X3xOwvUatveENAnCyJxyuRzlcjntMq7N8elfjUbjxCKip9nZ2Tly/fBf1WDQBnGeDtu5cvjxyMOQcm6uNM+9YTvvIU3Ddr74nITrNWzvCWkyNRIG7N69e0eu9zs0/PCQ1VKpdKPDQogYvnPl8HGyNAoVLirNc2/YzntI07CdLz4n4XoN23tCmgRhMGCVSuXIh/8HH3zQ1+22trYOfj7+Jgc30bCdK4ePOz09PbDjQtLSPPeG7byHNA3b+eJzEq7XsL0npEkQBil44403Dn4+PI+7l8PtlpaWEq8JsmiYzpXDw8rzMKScmy3Nc2+YzntI2zCdLz4n4foN03tCmgRhkIL5+fmDn/tZNPRwm3K57H8eyI1hOlc2NjYiImJxcXFgx4Trkua5N0znPaRtmM4Xn5Nw/YbpPSFNgjA45vj2sZextrYWS0tLZ87LPr6F9P7/GJzl8O58eUnpIeJ6z5XzztOL2NjYiEajEaVSKR4+fHjl/iBtaZ57PiOhfz4nYXj4npkhXeCI9fX1bkQcXJaXly90+2q1euT2e3t7p7bb2dk5aFOpVM7sb29v76BdtVq9UC1wE1zHuXLeebq5udktlUoHfW1vb/esb79tr3YwbNI4967z2HBT+ZyE4eB7ZnYIwuCQvb29brlcPvIG0+vN4zSHbxsR3dXV1TPbHn4zPOuNsFKpdCOiWyqVznyzg5su6XPlvPN0bm7uRJu5ubkT/ex/ESiXy92dnZ1L3z/IqkGfe9d5bLjJfE5CtvmemS2CMHJvb2+vOzMzcyJhP36pVqvdmZmZc/+Stf8Xr/3L5uZmz/aH/6K23//e3l53c3Pz4M2pUqnk7s0JjkvyXDnvPN3c3Dz1faBUKnVnZma6c3NzB8dcXFx0fnKjDfLcu85jw03ncxKyxffM7BKEQcI2Nze75XK5WyqVuouLi33fbnl5uVupVA7erEqlUrdarXbX19evsVoYPkmcK/2cpzs7O925ubmDdvvHKpfL3ZmZme76+nou/8eB/BrUuXddx4a88DkJN5PP0OQUut1uNwAAAADghrNrJAAAAAC5IAgDAAAAIBcEYQAAAADkgiAMAAAAgFwQhAEAAACQC4IwAAAAAHJBEAYAAABALgjCAAAAAMgFQRgAAAAAuSAIAwAAACAXBGEAAAAA5IIgDAAAALiSer0eS0tLMT8/n3YpR7RarbRLIGMEYQAAAMCF1Wq1mJ+fj8nJyZiamorHjx9Ho9Ho+/b1ev3g9oVCIUZHRw/6OR5gNRqNePz4cd/9Pn78OKampmJ0dPQid4kcKHS73W7aRQAAAADDY3p6Op49exb1ev3Iv1er1djc3Dz39vPz87G2tnbk38rlcjx79uwgBJuZmYn5+fm4fft2LC0txdbWVuzt7Z3a39raWmxubkatVjsRook9OOzFtAsAAAAAhst+2FWr1WJ6errv27VarZiamjoYOVapVGJ5eTmq1epBm0ajEaurq/H48ePY2Njoq8+IOKijn9v8/9u739tG0TWMw7elU8DrdLDQAc5WEOjAJBXEdGBrK4jiDsAVZE0H9lSwYzowW8EmdODzYQ6If8ZmQnZ8xO+SRgo2fnmN59Ot53nAeFERBgAAAAAAftpkMin+vlQR5nme9vu9pB8VYMfj8ey5aZrK87xKu+XHx4eMMZ37sW278hliD5QxIwwAAAAAAHy5JEmKEEySwjDsPN+yLB0OB1mWVbx2zQyy8vlAHUEYAAAAAAD4cvXgq9wOeY4xRtvttjh+f3+/6jPAOQRhAAAAAADgy33//v2nPpfPEZOuqwgDuhCEAQAAAACAL1d/mmO5TfKSxWIhSZ0zxYBrEIQBAAAAAIAvV5/dtVqtrv6sMUau6zbCNKAvgjAAAAAAAHBWHMfyPE/T6VSTyUSz2UxBEPRuU6wHYUmS9ArDVquVZrNZr2v2FcexfN+XbduaTCaaTCaybVu+7yuO415rpWmq1Wql6XTauEb5ftq2/VP3M8uy4p7ka02nU/m+36vabmwIwgAAAAAAQEOapkUI9P7+rtfXV+12Oz09PWm/38u2ba3X66vX832/8dp6vW59vY3rukWL5NDy7+P7fhEw7XY7hWEoY0wlIOsKxLIsUxRFms1mxf3Jq9iyLNNsNiuCqvz1NE0VRVGv+5kHbFEU6e7uTq7ryrIsZVlWBG2e5w1SQef7fhG0tf2bzWZFiBcEQeu5tm3fTjXfCQAAAAAAoORwOJwknSSdXl9fW89ZLBbFOfk/13U713Ucp/EZSSfHcU7H43GQvc/n88ral4RhWJy7XC5bz3l9fa2s2XZPlstl63eTdDoejydjzEnSybKsk+u6Z+/Fufudc1337Hnl75Jfayhtv3fbHsr/dxzHOX18fAy2hyFQEQYAAAAAAAppmhYtiPP5XMvlsvW8MAzlOE6vtTebTevrSZLItu1erZJDiONYQRBI+jGQP386Zd1yuaxUo61WK0VRVDmnq+LJ8zzd39/rcDjoeDxqt9vpcDjocDi0zk471yYZBIH2+72Wy2Xr77JYLCr7TNO0V9VelzAM5bpu5bW2hxfkTwd1XVeHw0HGmEGuP5TJ6XQ6/epNAAAAAACA2zCbzZQkiaQfQUc9qCnb7/fyPK84dl1Xu92uc/0kSfTw8HA2ODLGaLPZaD6f99+81JjndS72yLJMv/32W7GPS99VkqbTaWXfbZ9JkqQxy2w+n2u73V61j3Pnl9f9+Pg4GzDlLa05Y4w+Pj46v9e1sixrzDwr7yX/LpL0999/31wIJjEjDAAAAAAA/E8cx0UI5jjOxWDo/v6+9zUcx2mthMplWSbf9+V5Xu8B8n28vLwU4VM+Y+uSesVYWwWb4ziNSrlzlWbSj6Cq/n4cx42gML+W67qdAZNlWZX387lhQzDGKAzDymvPz8+Vv7Ms03a7vckQTCIIAwAAAAAA//Py8lL8nbcMdvnZsMOyLB2Px87h9/kA+6FCnLpyy+C1LZ6Pj4+V47bASpLu7u4qx5dCtrb7UH7yY5qmxXG5Au+cekB5qUqvj8ViUWmRjONY+/1eURQpjuPG+7eGIAwAAAAAAChN06IaTLoc3gwhDEMdj8fO4MT3/cFnh5VDJkmVVsIuxphGaFZfKz+vr3oYVg6vytdYrVZnn+CY/6vvKZ/bNZR6VVj+G1mW1Xjv1vznV28AAAAAAAD8evXw5N8IwvLr7HY7xXFctNbV5dVbXS2GfZQDv3wP17q/v698frfb/fQ8szLP8yoD+N/f3yvXyC0Wi8YMskvqFWqfZVmWXl9fi4Ay/82+ffs26HW+AkEYAAAAAADQ4XCoHP9bQVhuPp9rPp83ht3n1uu1PM8bpO2u7WmH16pXj5UDq8+oV5GV56OV//Y8b5Dg7bOWy6Xe3t4aoeKtozUSAAAAAAB86WD6Prbb7dnKL9/3B7lGPbw69wTLNl2B1WfUg8dyFVd5f0MFb0OoP9lyqN/nKxGEAQAAAACARsDyK4Ox5XLZOmsqy7LWmVyf1Sdc6gqsPqO+bjlwK+/vM9VsQ6v/RmmaDj7PbWgEYQAAAAAAoKFPldSldX4mHFksFq1PUxyiFa8eXtXbQvt8dqgW0vr9Lq9bvuZXBIE/I0kSrdfrRpvmer2+6XZJgjAAAAAAANAIeIaqCDPGaL1et879uqStRfKvv/769J7qc776PFWxfl+ufeJk33V///334u9ydViSJIOFlJ/h+76MMdpsNq1PkbxVBGEAAAAAAKBR2VR+UuEQa7+8vPT+nDHmS4b21wfu96lgqrdRDjW4vh6ElfdYvwd//vlnr7XjOB60ZTEIAqVpqs1mI2OMFouFHMcp3k/TtHjS560hCAMAAAAAAPI8r3LcN2zpYlmWkiT5qaqw+nD6IYIxx3Ea617bclie0WVZ1mBBXTkIc123sr/6b3PuYQJtsizT8/OzgiD49B6lH/cpiiK5rlsJAeuD81er1c08gKGMIAwAAAAAADSqpLIs6x1cnRs6n4dFz8/Pvdv66tVaT09PvT5/zh9//FE5bhvO36Z8T4assipfvx5aPT4+Vo77DKV/eHiQ67qDBXZ522M9+LIsqxHQ3WKLJEEYAAAAAACQMabR5ncpuKqHVOfOzedoZVnWKxypV2k5jlNpwWtT38O5PS2Xy0rVVRzHF0O6JEmKKifHcVqH+V+zp0vr1n8HY0wjqFyv153th1mWaTabKUmSXhVkXXzfV5ZlCsOwUVEn/bin5cAtH6h/SwjCAAAAAACAJGmz2VSOsyzTw8NDa5CTpmkj1ErTtLXFsByO7Pf7q8OwemVUvQqpTb0d71yVmiR9+/atcvz8/Ny5dnnO2TV7yUVR1Pl++brn1m2rWFutVprNZorjWGmaKssyJUmi1Wql6XSqJEm03W4HqQaL41hxHMuyrM4AsK1F8paeIkkQBgAAAAAAJP2oPKoHGUmSaDqdKggCxXGsKIoUBIFs225UKUk/5llNJpNKiFWv4orjWLZtn229TJJEtm1XQq3dbncx0ImiqBGEdbUQOo5T+b5dQ+XzJ18aY3Q4HHqFS6vV6uy6vu8XQVHXupZltYZhSZLI933Ztq3pdKrZbFZUYYVhOMgw/3J4eWm9tv0/PDzcTBg2OZ1Op1+9CQAAAAAAcDvy4KOrpW+xWCgMQ00mk+I1y7IUBIHm83kjEJlMJnJdV6+vr0rTVG9vb0UQ5jiOLMtSlmVK07QSZuVhVVfw5Hmevn//fna/+dMnN5tNa2tlkiR6fn4uwhrHcRQEQbGnMAy13+/luq7CMLwYgvm+Xwn5lsul1uu1jDF6fHyUbdv6559/FEWRsiyTZVlXBX2SiiCySx6atQWVfeRVf/UQy3VdbbfbRnvker1WGIZnh+Rf81t+NYIwAAAAAADQar1e6+3trWi7y2dVBUFQhCy2bWs+n+vp6alzfpdt241wJssyRVGkt7e3IgQzxuju7k6u68r3/U+HOX3s93uFYViZ2WVZVu+91IOw0+mkJEn08vJSrG2M0f39fREc9lG+b/lvY1mWHMeR53lXzy4bI4IwAAAAAACAAbUFYbgNzAgDAAAAAADAKBCEAQAAAAAAYBQIwgAAAAAAADAKBGEAAAAAAAAYBYIwAAAAAACAAWVZ1nmMX4cgDAAAAAAAYEBpmnYe49chCAMAAAAAABhIFEWN4Gu1WlEVdiMmp9Pp9Ks3AQAAAAAA8P/M933Fcdx5jjFG9/f32u12/9KuUEcQBgAAAAAAgFGgNRIAAAAAAACjQBAGAAAAAACAUSAIAwAAAAAAwCgQhAEAAAAAAGAUCMIAAAAAAAAwCgRhAAAAAAAAGAWCMAAAAAAAAIwCQRgAAAAAAABGgSAMAAAAAAAAo0AQBgAAAAAAgFEgCAMAAAAAAMAoEIQBAAAAAABgFAjCAAAAAAAAMAoEYQAAAAAAABgFgjAAAAAAAACMAkEYAAAAAAAARoEgDAAAAAAAAKNAEAYAAAAAAIBRIAgDAAAAAADAKBCEAQAAAAAAYBQIwgAAAAAAADAKBGEAAAAAAAAYBYIwAAAAAAAAjAJBGAAAAAAAAEaBIAwAAAAAAACjQBAGAAAAAACAUSAIAwAAAAAAwCgQhAEAAAAAAGAUCMIAAAAAAAAwCv8F8RW9/9C22ksAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-1, 1, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"dSlope_xEndT\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"dSlope x \")\n",
+    "plt.ylabel(\"$y_{corr}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['dSlope_yEndT' 'ty dSlope_yEndT_abs' 'ty tx dSlope_xEndT'\n",
-      " 'ty dSlope_xEndT^2' 'ty dSlope_yEndT^2' 'tx^2 dSlope_yEndT'\n",
-      " 'ty tx^2 dSlope_xEndT_abs' 'ty^3 tx dSlope_xEndT']\n",
-      "intercept= 0.0\n",
-      "coef= {}\n",
-      "r2 score= 0.9971571295750978\n",
-      "RMSE = 2.422206064647647\n",
-      "straight RMSE = 45.67726454181064\n",
-      "constexpr std::array y_xEndT_diff{4039.5218935644916f, 1463.501458069602f, 2210.102099471291f, 1537.0718454152473f, -411.54564619803864f, 2594.7244053238287f, -1030.7643414023526f, 14904.842115636024f};\n"
+      "intercept= 0.16257747434812642\n",
+      "coef= {'dSlope_yEndT': 4379.8079670973475, 'dSlope_xEndT dSlope_yEndT': 37.76975769672208, 'ideal_state_770_ty dSlope_xEndT^2': 1224.0422108322969, 'ideal_state_770_ty dSlope_yEndT^2': -18042.13200642719}\n",
+      "r2 score= 0.8441034202616307\n",
+      "RMSE = 10.185808113150346\n"
      ]
     }
    ],
    "source": [
-    "from sklearn.preprocessing import PolynomialFeatures\n",
-    "from sklearn.linear_model import LinearRegression, Lasso, Ridge\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.pipeline import Pipeline\n",
-    "from sklearn.metrics import mean_squared_error\n",
+    "features = [\n",
+    "    \"ideal_state_770_ty\",\n",
+    "    # \"ideal_state_9410_ty\",\n",
+    "    # \"ideal_state_770_y\",\n",
+    "    # \"ideal_state_9410_y\",\n",
+    "    \"dSlope_xEndT\",\n",
+    "    \"dSlope_yEndT\",\n",
+    "]\n",
+    "target_feat = \"yDiffOut\"\n",
+    "order = 3\n",
+    "\n",
+    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
+    "target = ak.to_numpy(array[target_feat])\n",
+    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
+    "                                                    target,\n",
+    "                                                    test_size=0.2,\n",
+    "                                                    random_state=42)\n",
+    "\n",
+    "poly = PolynomialFeatures(degree=order, include_bias=False)\n",
+    "X_train_model = poly.fit_transform(X_train)\n",
+    "X_test_model = poly.fit_transform(X_test)\n",
+    "\n",
+    "poly_features = poly.get_feature_names_out(input_features=features)\n",
+    "\n",
+    "# keep = [\n",
+    "#     # \"ideal_state_770_ty\",  #\n",
+    "#     # \"dSlope_xEndT\",  #\n",
+    "#     \"dSlope_yEndT\",  # keep\n",
+    "#     # \"ideal_state_770_ty^2\",  #\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT\",  #\n",
+    "#     # \"ideal_state_770_ty dSlope_yEndT\",  #\n",
+    "#     # \"dSlope_xEndT^2\",  # do not keep\n",
+    "#     \"dSlope_xEndT dSlope_yEndT\",  # keep\n",
+    "#     # \"dSlope_yEndT^2\",  #\n",
+    "#     # \"ideal_state_770_ty^3\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT\",  #\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_yEndT\",\n",
+    "#     \"ideal_state_770_ty dSlope_xEndT^2\",  # keep\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT\",  #\n",
+    "#     \"ideal_state_770_ty dSlope_yEndT^2\",  # keep\n",
+    "#     # \"dSlope_xEndT^3\",  # do not keep\n",
+    "#     # \"dSlope_xEndT^2 dSlope_yEndT\",  #\n",
+    "#     # \"dSlope_xEndT dSlope_yEndT^2\",  #\n",
+    "#     # \"dSlope_yEndT^3\",\n",
+    "#     # \"ideal_state_770_ty^4\",\n",
+    "#     # \"ideal_state_770_ty^3 dSlope_xEndT\",\n",
+    "#     # \"ideal_state_770_ty^3 dSlope_yEndT\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT^2\",  #\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT dSlope_yEndT\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_yEndT^2\",\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT^3\",  # do not keep\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT^2 dSlope_yEndT\",  #\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT^2\",\n",
+    "#     # \"ideal_state_770_ty dSlope_yEndT^3\",\n",
+    "#     # \"dSlope_xEndT^4\",  #\n",
+    "#     \"dSlope_xEndT^3 dSlope_yEndT\",  # keep\n",
+    "#     # \"dSlope_xEndT^2 dSlope_yEndT^2\",  #\n",
+    "#     # \"dSlope_xEndT dSlope_yEndT^3\",\n",
+    "#     # \"dSlope_yEndT^4\",\n",
+    "#     # \"ideal_state_770_ty^5\",\n",
+    "#     # \"ideal_state_770_ty^4 dSlope_xEndT\",\n",
+    "#     # \"ideal_state_770_ty^4 dSlope_yEndT\",\n",
+    "#     # \"ideal_state_770_ty^3 dSlope_xEndT^2\",\n",
+    "#     # \"ideal_state_770_ty^3 dSlope_xEndT dSlope_yEndT\",\n",
+    "#     # \"ideal_state_770_ty^3 dSlope_yEndT^2\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT^3\",  #\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT^2 dSlope_yEndT\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_xEndT dSlope_yEndT^2\",\n",
+    "#     # \"ideal_state_770_ty^2 dSlope_yEndT^3\",\n",
+    "#     \"ideal_state_770_ty dSlope_xEndT^4\",  # keep\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT^3 dSlope_yEndT\",  #\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT^2 dSlope_yEndT^2\",\n",
+    "#     # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT^3\",\n",
+    "#     # \"ideal_state_770_ty dSlope_yEndT^4\",\n",
+    "#     # \"dSlope_xEndT^5\",  #\n",
+    "#     \"dSlope_xEndT^4 dSlope_yEndT\",  # keep\n",
+    "#     # \"dSlope_xEndT^3 dSlope_yEndT^2\",  #\n",
+    "#     # \"dSlope_xEndT^2 dSlope_yEndT^3\",\n",
+    "#     # \"dSlope_xEndT dSlope_yEndT^4\",\n",
+    "#     # \"dSlope_yEndT^5\",\n",
+    "# ]\n",
+    "\n",
+    "keep = [\n",
+    "    \"dSlope_yEndT\",  # keep\n",
+    "    \"dSlope_xEndT dSlope_yEndT\",  # keep\n",
+    "    \"ideal_state_770_ty dSlope_xEndT^2\",  # keep\n",
+    "    \"ideal_state_770_ty dSlope_yEndT^2\",  # keep\n",
+    "    # \"dSlope_xEndT^3 dSlope_yEndT\",  # do not keep\n",
+    "    # \"ideal_state_770_ty dSlope_xEndT^4\",  # keep\n",
+    "    # \"dSlope_xEndT^4 dSlope_yEndT\",  # keep\n",
+    "]\n",
+    "\n",
+    "# keep = [\n",
+    "#     \"ideal_state_770_ty dSlope_yEndT^2\",\n",
+    "#     \"ideal_state_770_ty dSlope_xEndT^2\",\n",
+    "# ]\n",
+    "remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
+    "\n",
+    "X_train_model = np.delete(X_train_model, remove, axis=1)\n",
+    "X_test_model = np.delete(X_test_model, remove, axis=1)\n",
+    "poly_features = np.delete(poly_features, remove)\n",
+    "# print(poly_features)\n",
+    "lin_reg = LinearRegression()\n",
+    "# lin_reg = Lasso(fit_intercept=False, alpha=0.000001)\n",
+    "# lin_reg = Lasso(alpha=0.1)\n",
+    "# lin_reg = LassoCV(max_iter=2000)\n",
+    "# lin_reg = ElasticNet(alpha=0.1)\n",
+    "# lin_reg = Ridge(alpha=0)\n",
+    "lin_reg.fit(X_train_model, y_train)\n",
+    "y_pred_test = lin_reg.predict(X_test_model)\n",
+    "print(\"intercept=\", lin_reg.intercept_)\n",
+    "print(\"coef=\", dict(zip(poly_features, lin_reg.coef_)))\n",
+    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
+    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 148,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "koeffs = dict(zip(poly_features, lin_reg.coef_))\n",
     "\n",
+    "remove = []\n",
+    "for itr in koeffs.items():\n",
+    "    if abs(itr[1]) < 1.0:\n",
+    "        remove.append(itr[0])\n",
+    "remove"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ls_koeffs = []\n",
+    "for itr in koeffs.items():\n",
+    "    ls_koeffs.append(itr[0])\n",
+    "# ls_koeffs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['1', 'dSlope_xEndT^2', 'dSlope_xEndT^3', 'dSlope_xEndT^6']"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 149,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-40, 40, 50)\n",
+    "ax = sns.regplot(\n",
+    "    x=y_test,\n",
+    "    y=abs(y_test - y_pred_test),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    "    label=\"bla\",\n",
+    ")\n",
+    "ax2 = ax.twinx()\n",
+    "ax2.hist(y_test,\n",
+    "         bins=20,\n",
+    "         range=[-40, 40],\n",
+    "         color=\"#2A9D8F\",\n",
+    "         alpha=0.5,\n",
+    "         align=\"left\")\n",
+    "ax.set_xlabel(r\"y$_{corr}$ [mm]\")\n",
+    "ax.set_ylabel(\"Mean Deviation [mm]\")\n",
+    "ax2.set_ylabel(\"Number of Tracks\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "features = [\n",
-    "    \"ty\", \n",
-    "    \"tx\",\n",
+    "    \"ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx\",\n",
     "    \"dSlope_xEndT\",\n",
     "    \"dSlope_yEndT\",\n",
     "    \"dSlope_xEndT_abs\",\n",
@@ -65,82 +507,101 @@
     "\n",
     "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
     "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    data, target, test_size=0.2, random_state=42\n",
+    ")\n",
     "\n",
     "poly = PolynomialFeatures(degree=6, include_bias=False)\n",
-    "X_train_model = poly.fit_transform( X_train )\n",
-    "X_test_model = poly.fit_transform( X_test )\n",
+    "X_train_model = poly.fit_transform(X_train)\n",
+    "X_test_model = poly.fit_transform(X_test)\n",
     "poly_features = poly.get_feature_names_out(input_features=features)\n",
     "keep = [\n",
     "    #'dSlope_xEndT',\n",
-    "    'dSlope_yEndT', # keep\n",
+    "    \"dSlope_yEndT\",  # keep\n",
     "    #'dSlope_yEndT_abs',\n",
     "    #'ty dSlope_xEndT',\n",
     "    #'ty dSlope_yEndT',\n",
-    "    'ty dSlope_xEndT_abs', # keep\n",
-    "    'ty dSlope_yEndT_abs', #keep\n",
-    "    'ty dSlope_yEndT^2', # keep \n",
-    "    'ty dSlope_xEndT^2', # keep\n",
+    "    \"ideal_state_770_ty dSlope_xEndT_abs\",  # keep\n",
+    "    \"ideal_state_770_ty dSlope_yEndT_abs\",  # keep\n",
+    "    \"ideal_state_770_ty dSlope_yEndT^2\",  # keep\n",
+    "    \"ideal_state_770_ty dSlope_xEndT^2\",  # keep\n",
     "    #'tx dSlope_xEndT',\n",
     "    #'tx dSlope_xEndT_abs',\n",
     "    #'tx dSlope_yEndT',\n",
-    "    'ty tx dSlope_xEndT', #keep\n",
-    "    'tx^2 dSlope_yEndT', # keep\n",
+    "    \"ideal_state_770_ty ideal_state_770_tx dSlope_xEndT\",  # keep\n",
+    "    \"ideal_state_770_tx^2 dSlope_yEndT\",  # keep\n",
     "    #'ty^2 dSlope_xEndT',\n",
-    "    #'ty^2 dSlope_yEndT', \n",
+    "    #'ty^2 dSlope_yEndT',\n",
     "    #'ty^2 dSlope_xEndT_abs',\n",
     "    #'ty^2 tx dSlope_xEndT',\n",
     "    #'ty tx^2 dSlope_yEndT',\n",
-    "    'ty tx^2 dSlope_xEndT_abs', # keep\n",
-    "    'ty^3 tx dSlope_xEndT', #keep\n",
+    "    \"ideal_state_770_ty ideal_state_770_tx^2 dSlope_xEndT_abs\",  # keep\n",
+    "    \"ideal_state_770_ty^3 ideal_state_770_tx dSlope_xEndT\",  # keep\n",
     "    #'ty tx^3 dSlope_xEndT',\n",
     "    #'ty^3 dSlope_yEndT_abs',\n",
     "]\n",
     "do_not_keep = [\n",
-    "    'dSlope_xEndT',\n",
-    "    'dSlope_yEndT_abs',\n",
-    "    'ty dSlope_xEndT',\n",
-    "    'tx dSlope_xEndT',\n",
-    "    'tx dSlope_xEndT_abs',\n",
-    "    'tx dSlope_yEndT',\n",
-    "    'ty^2 dSlope_xEndT',\n",
-    "    'ty^3 dSlope_yEndT_abs',\n",
-    "    'ty tx dSlope_yEndT',\n",
-    "    'ty tx^3 dSlope_xEndT',\n",
-    "    'ty tx^2 dSlope_yEndT',\n",
+    "    \"dSlope_xEndT\",\n",
+    "    \"dSlope_yEndT_abs\",\n",
+    "    \"ideal_state_770_ty dSlope_xEndT\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT_abs\",\n",
+    "    \"ideal_state_770_tx dSlope_yEndT\",\n",
+    "    \"ideal_state_770_ty^2 dSlope_xEndT\",\n",
+    "    \"ideal_state_770_ty^3 dSlope_yEndT_abs\",\n",
+    "    \"ideal_state_770_ty ideal_state_770_tx dSlope_yEndT\",\n",
+    "    \"ideal_state_770_ty ideal_state_770_tx^3 dSlope_xEndT\",\n",
+    "    \"ideal_state_770_ty ideal_state_770_tx^2 dSlope_yEndT\",\n",
     "]\n",
     "reduce = True\n",
     "if reduce:\n",
-    "    remove = [i for i, f in enumerate(poly_features) if (keep and f not in keep )]\n",
-    "    X_train_model = np.delete( X_train_model, remove, axis=1)\n",
-    "    X_test_model = np.delete( X_test_model, remove, axis=1)\n",
-    "    poly_features = np.delete(poly_features, remove )\n",
+    "    remove = [i for i, f in enumerate(poly_features) if (keep and f not in keep)]\n",
+    "    X_train_model = np.delete(X_train_model, remove, axis=1)\n",
+    "    X_test_model = np.delete(X_test_model, remove, axis=1)\n",
+    "    poly_features = np.delete(poly_features, remove)\n",
     "    print(poly_features)\n",
     "if not reduce:\n",
-    "    remove = [i for i, f in enumerate(poly_features) if (\"dSlope_\" not in f) or (\"EndT^\" in f) or (\"abs^\" in f) or (\"EndT dSlope\" in f) or (\"abs dSlope\" in f)]\n",
-    "    X_train_model = np.delete( X_train_model, remove, axis=1)\n",
-    "    X_test_model = np.delete( X_test_model, remove, axis=1)\n",
-    "    poly_features = np.delete(poly_features, remove )\n",
-    "    #print(poly_features)\n",
+    "    remove = [\n",
+    "        i\n",
+    "        for i, f in enumerate(poly_features)\n",
+    "        if (\"dSlope_\" not in f)\n",
+    "        or (\"EndT^\" in f)\n",
+    "        or (\"abs^\" in f)\n",
+    "        or (\"EndT dSlope\" in f)\n",
+    "        or (\"abs dSlope\" in f)\n",
+    "    ]\n",
+    "    X_train_model = np.delete(X_train_model, remove, axis=1)\n",
+    "    X_test_model = np.delete(X_test_model, remove, axis=1)\n",
+    "    poly_features = np.delete(poly_features, remove)\n",
+    "    # print(poly_features)\n",
     "    lin_reg = Lasso(fit_intercept=False, alpha=0.000001)\n",
     "else:\n",
     "    lin_reg = LinearRegression(fit_intercept=False)\n",
-    "lin_reg.fit( X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict( X_test_model )\n",
+    "lin_reg.fit(X_train_model, y_train)\n",
+    "y_pred_test = lin_reg.predict(X_test_model)\n",
     "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\"coef=\", {k: v for k, v in zip(poly_features, lin_reg.coef_) if abs(v) > 1.0 and k not in keep and k not in do_not_keep})\n",
+    "print(\n",
+    "    \"coef=\",\n",
+    "    {\n",
+    "        k: v\n",
+    "        for k, v in zip(poly_features, lin_reg.coef_)\n",
+    "        if abs(v) > 1.0 and k not in keep and k not in do_not_keep\n",
+    "    },\n",
+    ")\n",
     "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
     "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(\"straight RMSE =\", mean_squared_error(array[\"y_l11\"], array[\"y\"] + array[\"ty\"] * ( array[\"z_l11\"] - array[\"z\"] ), squared=False))\n",
+    "print(\n",
+    "    \"straight RMSE =\",\n",
+    "    mean_squared_error(\n",
+    "        array[\"ideal_state_9410_y\"],\n",
+    "        array[\"ideal_state_770_y\"]\n",
+    "        + array[\"ideal_state_770_ty\"]\n",
+    "        * (array[\"ideal_state_9410_z\"] - array[\"ideal_state_770_z\"]),\n",
+    "        squared=False,\n",
+    "    ),\n",
+    ")\n",
     "print(format_array(\"y_xEndT_diff\", lin_reg.coef_))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -159,7 +620,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   },
   "orig_nbformat": 4,
   "vscode": {
diff --git a/parameterisations/notebooks/magnet_kink_position.ipynb b/parameterisations/notebooks/magnet_kink_position.ipynb
index 24ab396..56ea448 100644
--- a/parameterisations/notebooks/magnet_kink_position.ipynb
+++ b/parameterisations/notebooks/magnet_kink_position.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14,32 +14,48 @@
     "import mplhep\n",
     "\n",
     "mplhep.style.use([\"LHCbTex2\"])\n",
-    "input_tree = uproot.open({\n",
-    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_def_selected.root\":\n",
-    "    \"Selected\"\n",
-    "})\n",
+    "input_tree = uproot.open(\n",
+    "    {\n",
+    "        \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_BJpsi_def_selected.root\": \"Selected\"\n",
+    "    }\n",
+    ")\n",
     "array = input_tree.arrays()\n",
     "\n",
-    "array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\n",
-    "    \"ideal_state_770_tx\"]\n",
+    "array[\"dSlope_yEndT\"] = array[\"ideal_state_9410_ty\"] - array[\"ideal_state_770_ty\"]\n",
+    "array[\"dSlope_yEndT_abs\"] = abs(array[\"dSlope_yEndT\"])\n",
+    "\n",
+    "array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\"ideal_state_770_tx\"]\n",
     "array[\"dSlope_xEndT_abs\"] = abs(array[\"dSlope_xEndT\"])\n",
     "array[\"x_EndT_abs\"] = abs(array[\"ideal_state_9410_x\"])\n",
+    "array[\"x_EndVelo_abs\"] = abs(array[\"ideal_state_770_x\"])\n",
+    "\n",
+    "array[\"y_EndT_abs\"] = abs(array[\"ideal_state_9410_y\"])\n",
+    "array[\"y_EndVelo_abs\"] = abs(array[\"ideal_state_770_y\"])\n",
     "\n",
     "array[\"z_mag_xEndT\"] = (\n",
-    "    array[\"ideal_state_770_x\"] - array[\"ideal_state_9410_x\"] -\n",
-    "    array[\"ideal_state_770_tx\"] * array[\"ideal_state_770_z\"] +\n",
-    "    array[\"ideal_state_9410_tx\"] *\n",
-    "    array[\"ideal_state_9410_z\"]) / array[\"dSlope_xEndT\"]"
+    "    array[\"ideal_state_770_x\"]\n",
+    "    - array[\"ideal_state_9410_x\"]\n",
+    "    - array[\"ideal_state_770_tx\"] * array[\"ideal_state_770_z\"]\n",
+    "    + array[\"ideal_state_9410_tx\"] * array[\"ideal_state_9410_z\"]\n",
+    ") / array[\"dSlope_xEndT\"]\n",
+    "\n",
+    "array[\"z_mag_corr\"] = array[\"z_mag_xEndT\"] - array[\"match_zmag\"]\n",
+    "\n",
+    "sel_array = array[\n",
+    "    (array[\"z_mag_xEndT\"] < 5700)\n",
+    "    & (array[\"z_mag_xEndT\"] > 5000)\n",
+    "    # & (array[\"match_chi2\"] < 5)\n",
+    "]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -50,11 +66,13 @@
    ],
    "source": [
     "fig = plt.figure()\n",
-    "plt.hist(array[\"z_mag_xEndT\"],\n",
-    "         bins=100,\n",
-    "         range=[5100, 5700],\n",
-    "         color=\"#2A9D8F\",\n",
-    "         density=True)\n",
+    "plt.hist(\n",
+    "    sel_array[\"z_mag_xEndT\"],\n",
+    "    bins=100,\n",
+    "    # range=[5100, 5700],\n",
+    "    color=\"#2A9D8F\",\n",
+    "    density=True,\n",
+    ")\n",
     "plt.xlabel(r\"z$_{Mag}$ [mm]\")\n",
     "plt.ylabel(\"Number of Tracks (normalised)\")\n",
     "mplhep.lhcb.text(\"Simulation\")\n",
@@ -63,12 +81,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -80,13 +98,13 @@
    "source": [
     "bins = np.linspace(-0.4, 0.4, 50)\n",
     "sns.regplot(\n",
-    "    x=ak.to_numpy(array[\"ideal_state_770_tx\"]),\n",
-    "    y=ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_tx\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
     "    x_bins=bins,\n",
     "    fit_reg=None,\n",
     "    x_estimator=np.mean,\n",
     ")\n",
-    "plt.ylim(5100, 5700)\n",
+    "# plt.ylim(5100, 5700)\n",
     "plt.xlabel(\"dx/dz(VELO)\")\n",
     "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
     "mplhep.lhcb.text(\"Simulation\")\n",
@@ -95,12 +113,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-0.25, 0.25, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_9410_tx\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "# plt.ylim(4500, 5700)\n",
+    "\n",
+    "plt.xlabel(\"dx/dz(T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -112,13 +163,13 @@
    "source": [
     "bins = np.linspace(-0.25, 0.25, 50)\n",
     "sns.regplot(\n",
-    "    x=ak.to_numpy(array[\"ideal_state_770_ty\"]),\n",
-    "    y=ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_ty\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
     "    x_bins=bins,\n",
     "    fit_reg=None,\n",
     "    x_estimator=np.mean,\n",
     ")\n",
-    "plt.ylim(5100, 5700)\n",
+    "# plt.ylim(4500, 5700)\n",
     "\n",
     "plt.xlabel(\"dy/dz(VELO)\")\n",
     "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
@@ -128,42 +179,107 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 67,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# bins = np.linspace( -300, 300, 50 )\n",
-    "# sns.regplot(x=ak.to_numpy(array[\"x\"]), y=ak.to_numpy(array[\"z_mag_x_fringe\"]), x_bins=bins, fit_reg=None, x_estimator=np.mean)"
+    "bins = np.linspace(-0.25, 0.25, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_9410_ty\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "# plt.ylim(4500, 5700)\n",
+    "\n",
+    "plt.xlabel(\"dy/dz(T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 68,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# bins = np.linspace( -300, 300, 50 )\n",
-    "# sns.regplot(x=ak.to_numpy(array[\"y\"]), y=ak.to_numpy(array[\"z_mag_x_fringe\"]), x_bins=bins, fit_reg=None, x_estimator=np.mean)"
+    "bins = np.linspace(-300, 300, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_x\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"x (VELO)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 69,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# bins = np.linspace( -1.0, 1.0, 50 )\n",
-    "# sns.regplot(x=ak.to_numpy(array[\"dSlope_out\"]), y=ak.to_numpy(array[\"z_mag_x\"]), x_bins=bins, fit_reg=None, x_estimator=np.mean)"
+    "bins = np.linspace(-300, 300, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"x_EndT_abs\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"x (T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMIAAAOWCAYAAAANzz7PAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACh7UlEQVR4nOz9X2xbZ5rn+/4ouzIOkqJJpYHZggR0mUR6Ujen26Q8+6CuzpTI6d5AjGQqpD1IkAQbE1FJUBgcaDpkXLl2FLKqhAMMTsaiq3EOHAS7bbJTCRLgVId0+vqMpeXqu8xUcTkFSOCei0jLrBTinXLIfaFNFilR5CK5Fv9+P4BQkvXw5SPJTkk/Pe/7emq1Wk0AAAAAAADAlJsbdQMAAAAAAADAMBCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJhCEAQAAAAAAYCYQhI2AaZqKRqMj7SGTySgajcrv98vj8SgYDCoej6tYLI7VmgAAAAAAAE4hCHOQZVnyeDxdX4LBoAKBwInr1IOkfl7W1tY69lgsFuX3+5VKpSRJuVxOpVJJ6XRahmEoGo0qGo3KsizbH7cbawIAAAAAADjNU6vVaqNuYlpkMplGGNRNqVRqG4bl83nF4/G+e8jlcorFYm3fVywWG5NoiURCW1tbx2rC4bAMw1AgENDOzo58Pl/H53NjTQAAAAAAADcQhDnI7/fbmnqKRCIqFApt3xeNRgfaSnjSl9OyLJ07d06WZSkQCKhUKrWtM01TwWCwa59urQkAAAAAAOCW06NuYFpks1lZlqVkMtn1/K/l5eW2f26aporFogKBgFKplCKRiObn57s+dzgclmmaikQiJ9bE4/FGSNdpai0QCCgWiymfz6tYLCqbzSqRSAxtTQAAAAAAALcwEeaQ+sTTSVNRdqRSKeXz+Z62DzZPW21tbbUNmJprJOng4KDj+s3bM30+nw4ODoayJgAAAAAAgJs4LN8B+XxepmnaPh/sJNlsVrlcrqcztPL5fOP1S5cuta1Jp9ON1yORSNf1m88Ysyyr5TncXBMAAAAAAMBNBGEO2NjYkM/nOzGIsiuXyykUCvX0mJs3b0rqHEZls9nG63bXbz7Iv/4cbq8JAAAAAADgJoKwARmGIcMwZFmW/H6/gsGg1tbW+pp46nTGVzuWZckwDEk68abJ+vvrLly4YGvt5nDr6MfixpoAAAAAAABuIwgb0NHtkKZpKpvNKh6Py+PxKB6PHwuOnNI8lXXSNNrRGyibp7I6OVrX/DG4sSYAAAAAAIDbCMIGUL/lsZN8Pq9wOKy1tTXHn7++vTAUCp24LfLOnTstb9s9f+yJJ55oeXt7e9vVNQEAAAAAANx2etQNTLJAIKCtrS1ZlqVSqaRisSjTNNvWZrNZbW9va2dnx5Hnbt4Wefny5RPrjvbT7/RW822YbqwJAAAAAADgNoKwASUSiZa3LctSNpvVxsaGLMtqeZ9hGIpGoyoUCgM/761btxqvN9/IeNRJwVyvmj8WN9YEAAAAAABwG0GYw3w+n5LJpJLJpPL5vFZXV1sCn2KxqEwmo2QyOdDzbG1tSTrcFtlpIqvfsOnodsf9/X1X1+zVY489pq+//lq1Wk1zc4Pv8P3ud7+rxx9/fOB1AAAAAACYVl999ZV+//vfD7xOtVqVx+PRo48+qj/84Q8OdGYfQZiLYrGYIpGIVlZWWg6G39jYGCgIs7st0kluTG8NsmY9BJMO/wEN6v79+7p///7A6wAAAAAAgO5qtZq+/vrroT8vQZjLfD6fdnZ2FA6HG+GVZVkqFouKRCJ9rWl3W2T9+Z0IsZqnudxYs1f1EEzSRE2ElctlVatVzc3NaWFhoefH71U6v3/R685a3fp2si8nDfr5HqVJ7Z2+h4u+h4u+h4u+h4u+h4u+h2uUfQ/yfbJbfbv9vfs4/D3p52Ns1/eofv7qxbA/305OhEmtP9sPC0HYkFy/fl3hcLjxdqFQ6DsIq2+LDAQCXQ+qn5+fdyS0mp+fd3XNXs3NzTX+sX/77bcD9zIsS0tL2tvb08LCgnZ3d3t67LdV6fRbnWt+d1U6ZSMX7HWtTn072ZfTBvl8j9qk9k7fw0Xfw0Xfw0Xfw0Xfw0XfwzWqvgf9PtmNvofxvfuo/570+zEe7XuUP3/1YtSf736dOnWq8TP9sI3gR9PZFAqFWoKvfg+cb94W2W0aTOp/6upo0HV0IszpNQEAAAAAANw20omwJ598cpRP38Lj8ei///f/7upzRKNRFYvFgdZo3hZp53yw5eXllvPJLMuyFUAdPcg+GAy6uiYAAAAAAIDbRhqElUoleTyekewJras/v8fjcf25mrcx9rstMJfLSTqcpgqFQl3rm7djSoeTaHYeVyqVWt5unmZzY00AAAAAAAC3zfzWyGGGcM1BWD/bAuuH7EtSIpGw9Zjl5eWWt+1uyWzexujz+Vp6d2NNAAAAAAAAt438sPxaraZYLDayUMSyLGWz2aE81/b2duP1aDTa8+N73RYpHZ5N1nzL4507d2ydLdbc69Hgy401AQAAAAAA3DbyICybzeqVV14ZaQ+xWEx//dd/7frzNG8N7GdbYK/bIusuXbrUCPuaz/bqpLkulUoNZU0AAAAAAAA3jXxr5DicE3XhwoWhPE8+n5ckJZPJnh/bvC3y0qVLPT12bW2t8bqdw/qbawKBQNuvkRtrAgAAAAAAuGnkE2H9Hho/afL5vEzTlM/n05UrV3p+fPO2yHg83tNjQ6GQIpFII4zK5/MdtzLWJ8+kkye33FizF9/97nd1//59ffe73x14LXS3vr6uSqUir9c76lZ6Mql9S5Pb+6T2Pakm9fNN38M1qX1Pqkn9fNP3cE1q35NqUj/f9D1ck9r3pBrlz/Se2givbDx16pQODg5G/hft/v37mp+f17fffmv7McViUfF4XJZlKRKJKJ1On7hd0TRNhcNhWZalnZ2dnrY11kWjURWLRfl8Ph0cHPT8eNM0FQwGJR2GWDs7O23rLMuS3++XdDitVygUhrqmXUtLS9rb29Pi4qJ2d3cHXm9YBun726p0+q3ONQ+vSqdszHmO61rAqEzqf1OAaca/S2D88O+yN+P4ffI49uQ0pz7GSfmZaVL/XY6y75H+9R5hBndMr73kcrnGYfHFYlHhcLhlu2Bd/X3z8/MqlUp9hWDN2yL73VIYCAQaU1mGYSiTybStW1lZkXR4DlnzFNew1gQAAAAAAHDLSIOwdDo98mkwSTp79qzS6XRPj2m3PTGbzcrv9ysej2ttbU3hcFjRaFSJREI7Ozt934zZvC2yXdhmVywWU6FQkM/nUyqVUjwel2EYjaAtHA7LMAyFQiHdu3dPPp9vJGsCAAAAAAC4YaRB2BtvvDHU5/viiy9OfF+vvUQiEZVKJSUSCQUCgZaAxzAM7e/v68qVKzo4OFA6nR4oAGqeohr0kPlIJNLoyTRNraysNMK7+fl55XI57ezs9NSvG2sCAAAAAAA4beSH5Q/T2tqa/vEf/9Gx9QKBgLa2thxb7yROnKl1VDKZ7Ov2ymGvCQAAAAAA4JQJPgKvd9vb26NuAQAAAAAAACMykRNhX3zxReOgejtM09TW1lZPjwEAAAAAAMB0mYgg7IsvvlA6nVaxWJRpmn2tUavV5PF4HO4MAAAAAAAAk2Lsg7ArV64ok8lIOgyzgEm2vr6uSqUyFrelAvgT/m0C44d/l8D44d8lMH74d9m7sQ7C/uEf/kHpdFqS5PF45PF4CMMw0dbX10fdAoA2+LcJjB/+XQLjh3+XwPjh32XvxjoI29jYkKRGABYIBBQKhRQIBCRJTzzxRNc1vvzyS1mWpVu3bun+/fuu9gsAAAAAAIDxNdZBmGEYjXO9CoWCVlZW+l4rmUzqySefdKo1AAAAAAAATJi5UTfQic/nk3QYYg0SgklSIBDQuXPnHOgKAAAAAAAAk2isJ8ICgYDu3r2rCxcuOLLe1taWI+tgfJTLZS0tLXWsWV9fZ980AAAAAABDsLm5qc3NzY415XJ5SN0cN9ZB2MrKiu7evav9/X3H1sN0qVar2tvb61hTqVSG1A0AAAAAALOtUql0/Tl9lMY6CPvJT36in/70pzIMw5H1fvGLX+iVV15xZC2Mh7m5OS0sLHSs4RpZAAAAAACGw+v1anFxsWNNuVxWtVodUketxjoIO3v2rN555x2l02ml02l997vfHWi9ra0tgrAps7CwoN3d3VG3AQAAAAAAZO94oqWlpZFNjY31YfnS4UH5oVBI8Xh8oHXu3bvn2GQZAAAAAAAAJs9YT4TVFQoFLS8v68knn1QqldL8/Lytx+3v78uyLJVKJd26dcvlLgEAAAAAADDOJiII++yzzyRJpVJJa2trfa1Rq9Xk8XicbAsAAAAAAAATZOyDsNdee03ZbFaS5PF4VKvVel6DAAwAAAAAAABjfUbY9evXtbW11Qi/+gnBBnkcAAAAAAAApsdYT4RtbW1J+tMkWCQSUTQalc/n6/mcsGvXrumLL75wsVsAAAAAAJxVq0nVLrMdcx6JjVCAPWMdhBmGIY/HI5/Pp+3tbZ07d67vtVZXV/XEE0842B0AAAAAAO6q1qTTb3WueXhVOkUQBtgy1lsjfT6fJOnKlSsDhWD1tc6fP+9AVwBmnWVZo24BAAAAANCHsQ7CwuGwJCkQCDiy3vXr1x1ZB8DsMQxDqVRKfr9fq6uro24HAAAAANCHsd4auba2ptu3b8s0TUfWYyIMmE6GYejmzZsyDEOmaTbOBvT5fAoEApqfn1coFFI0GlUkEjn2+Hg8LtM0tbOz0/gzy7JULBZ18+ZNFYtFpsAAAAAAYAqMdRAWi8V0/vx53bx5U3/7t3878HoffPCBfvSjHznQGeCsbDartbW13h/4L0PS/7rTva6bd44fKHD6nc4P8fl8Ojg4aP/OX8al/5a3vVZdoVBoG1S1Y1mWNjY2lMlkOtYYhiFJKhaLjdpQKKRIJKJgMKhCoaB8Pq9QKNTy2NXVVZmm2Xg8AAAAAGDyjfXWSEnK5XLa2dnRL3/5y4HX2tjYcKAjwHmJREIHBwfa2dlRLBbrXPy9iPTvC9L/88CZEEyS3qxJr5akv9mS/oXvxLJAIKCtrS2VSqWTQzBJ+ne5w/7+feGw3w6SyaR2dnZ0cHBgOwSrb1E8GoLFYrHGfzMODg5Uq9VUKpVUKBSUSCQa5w4ahqFMJqO1tTXl84eB3dGJr/o6tVrNse3ZAAAAAIDRGvsgLBAI6Nq1a3rllVcGWuf+/ftMdmCs+Xw+hUIh5XI5JRKJ9kX/KvancOmMz+EGAtJfJTqGazs7O0okEvaCoTO+Rmh3dNqqbmtrS+l0WqFQqBFSdWKapoLB4LEALJFIqFarKZfLKRaLtawXCAQUiUS0tbWlg4MDpdPp7r0fYTegAwAAAACMt7HeGvnBBx9Ikv7sz/5Mfr9fTz75ZPdpmTYsy9KtW7ecbg9wzdramrLZ7PF3nO9j+2SvfIHDLZf/ozU4jsVitsKqdlZX1/Taa8d7Pxr41WqH10O3UywW9Td/HW1t1efT7du3Twza2kkmk4rFYgqHwy1TYPv7+yc+pt+PGwAAAAAwXsY6CHv77bd19+7dxtu1Wq3jeUCd1Go1eTzHz0ECxtGJE1e+IW3R8wWOBWGDbA881+ax7cKlak06/VabBf53Q/r/Dh6C1QUCAd27d0/nzp1rhGEchg8AAAAA02+st0ZeunRJtVpNtdrhiAhBFmbFiRNIZ+aH2odTPvvtAA+2TOl/Wzn2x7lcrq8QrM7n87XcEgkAAAAAmH5jHYTVb9HzeDyNQKzfFwA9ePR44PbEE0+0LX3/bts/bpG5c3y9+Xmbod4v49L/YbX8USKRcOTcrkAgoGQyOfA64ySfz8s0zVG3MbaKxeKoWwAAAAAwQmO9NfLs2bMKhUK6e/du40Bt2z88NzFNU2+//bZ+/etfO98kMMPuP5Be/8jFJ/iieGyLpqS+Drw/yZUrVxpbri3LGtvzwAzD0NbWlorFokzTlM/n0/z8vHw+nwKBgC5fvixJWl1dVTqdPvnCBR2GQfF4XPPz89ra2prqywBM01SxWFQul2uEYOP0y5FZ+loAAAAA42CsgzBJunz5soLBoN54442+1zh//ryee+65vkI0ACd7z5D+8EcXn+BXxw/Yf+65/g/tb8fn8ymRSLS/nGAMWJal1dVV5fN5SYdTbPVLQ0zTlGEYMgyj8f76YzqJx+OyLEuWZWltbU2lUsm1/kfFNE3F43GZpjnW57/NwtcCAAAAGCdjvTVSkiKRiGO/vV9eXnZkHQCHPv7cxcW/KB6eD3ZE6s0rjj9VPB6X1PnmyE7qUz3BYFAej0d+v1/RaNSRcC0ejzdCrq2tLZVKJeVyOeVyOe3s7KhUKh2bIuoWpszCLwUCgYB2dnZ0cHAw1ttfZ+FrAQAAAIyTsQ/Czp8/79g2qP/4H/+jI+sAOHTwtYuLf55r+8eDHJB/kkgkonQ63XMoYVmWwuGwotFoy9lclmWpWCxqbW1NwWBQhnF8e6cdmUymsZ0vmUy23e4YCARUKBRa/jvZ7Yywra0tBQIBBQIB5XLtP8/TJBqNdi8akVn7WgAAAACjNvZbIyXp3Llzjqzzn//zf9bTTz/tyFoYD+VyWUtLSx1r1tfXtb6+PqSOZov/URcX/6LNoebfc+/8pF6nhkzTVDgc7rrtrl5XKBR6Pv9pY2Oj8Xr98pCTJJNJffnll8pkMl0n2yKRyExtwRvV1NXa2pq2trY61sza1wIAAADTb3NzU5ubmx1ryuXykLo5biKCMKdsb2+PugU4rFqtam9vr2NNpVIZUjez5+JT0qe/cWFhy2y7LVL/0vlpsH5YltU42ykWiykajWp5eVn7+/sqFAqNw/ebRaNRlUolBQIBW8/Rz9lW6XS6cZg+RiubzSqbzXYNwgAAAIBpU6lUuv6cPkoTGYR98cUXPf2AaJqmtra2xvrAZPRnbm5OCwsLHWu8Xu+Qupk9L4akN3/lwoH57UIwSfIHHX6i/tS3K7ab8opEIlpbW1M0Gj0WSMXjce3s7Nh6jqP/vSoWiy1bI2s1qdrm+MRU6oouX47r26o055E8HltPBweZptl1gg8AAACYVl6vV4uLix1ryuWyqtXqkDpqNRFB2BdffDHwpEOtVpOHnwinzsLCgnZ3d0fdxsw6e0Z69xnp5Xz32p6cFISdGZ+DxTttdayf2xUMtgZ3hmGoWCza2iJ5dHIslUrp0qVLjRszqzXp9FvtHnl4o+Tp/2Tp4c99OsV/9obKsqyxPpMMAAAA0vt3pZfCo+5ietk5nmhpaWlkU2NjH4RduXKlsc3IqdsjAfQulUoplUoN58keWO3//IxvOM/fhc/n6xpmBQIBpdPpY5+zdDptKwjz+Xzy+XyNybD6wfyFQqH79so3+W/lKFiWpZWVFbamAgAAjND7d7vXvJyXTs1JL5x3vx+Mn7G+NfIf/uEflE6nGwEYE13AjLDG+/Dw5eVlW3XJZLIxwVVX31Zpx9Ebc03TVDAYVDabtb3GSQzDaNxq2YllWcpmswqHwy3PW9/+5/f75fF4FAwG256NZpqmUqmUgsFgo25tba3tVvX683g8npaXo6LRaGO95hcnt79ns9mW5/H7/QqHw20/Runw83nu3LljN4Q293fS59ru16LOsixlMhlFo9HG57/eXyqVshXEmaapTCZz7FbT5q9BMBhsnIUHAAAwCe4/kF7/yF7tqx9KlQeutoMxNdYTYfUb0zwej2q1mgKBgEKhUGMa4oknnui6xpdffinLsnTr1i3dv3/f1X6BaZZIJNqee/RtVfrX/+/Oj/0v//O2XnuthzOT/oWv/Z+fNCk2ZEfDrU4ikYjy+da9o4ZhKBTqfvB/IpFQLpc7Fp41biP8v12X/if7FwgYhqGtrS3dunWrEW60+1jq4dfNmzePBTvS4XTg0UCoHniVSqXGAfEn1WWzWRWLRe3s7LQ8fyKRaPw96xT2FQoFSVImk3F8SjGfzysej8vn8+n69euKxQ63mhqGoXg8rlQqpa2trWO9BwIB3b59W8VisaWnk86Es/u1OCqbzTb+HabTaaXTafl8PhmGoY2NDWUyGWUyGcViMeVyuZbHWpaljY0N5fP5Y2FZfZqt+ettmqZM02x8rexe9AAAADAq7xn2zy/+6hvphiH9+Afu9oTxM9ZBmGEYjWmAQqGglZWVvtdKJpN68sknnWoNmDnBYLBtePNtVdL/1PmxYXsDVH/y6Akh94P9HhcavcuXLx8Lwra3t20FYdLhf/vi8XjbME1GWPpXMel/ud5126hpmrp586btqaNQKCSfz9cSfu7s7CgcDmt+fl65XE6hUEjz8/ONAEb6U1CTSqUat2jWJ+i2t7cbE0amaWpjY+PY1Jt0eKmAnam3WCzmaBBWLBYVj8clHW7Lr4dg0uHnI5fLKRwOyzRNra6utgRNPp9PoVBI+/utf0fbfZ17/VrU1YNFn893LJgKBAKKxWKNvyv5fF7BYLAlsNvf31c0Gm0EnXXb29taWVlRJBJROp1WIBBoBHqWZcmyLK2trTUCSAAAgHH18ee91X/yOUHYLBrrrZH1b96TyeRAIZh0+EPCuXPnHOgKgOtOCnXGZCKsF+2maHrdapbL5doGRpKk/5aX/l9+6dedg6P6mWXJZFJXrlzpWFs/Ay2RSLQEOdlsVul0WoVCQbFYTIFAQD6f79i5Z+FwWIFAQDs7O4pEIo3zziKRiK5fv96y3iDm5529PKE+yXaS5s/F0WCyF718Leqy2WwjbKyHVe3kcrnG+0zTbAR79eeNRCLHPs5UKqVcLqdcLqdIJKJAIKBEItHytSoWi2yRBAAAY+/ga3frMR3GOgirfzN/4cIFR9br9kMOgDHhO2EL1pifHdZOu+1uX375Zc/rJJNJHRwctEwptfjVmvT3UVthYS9b3JrDpkQiceJB/0dvSjzpv7fN/denjcbRSdsUm//ciUPx7X4t6pNvPp9PiUTCVq10GGC1O5eu+eO4fv1626/r0b9r29vbtnoFAAAYFf+j7tZjOox1EFafAju61WTQ9QCMue+dcKviF/YPmh8X7YIOO+cbtuPz+ZTL5bSzs9N+a+UXRel/W3F0cs7ueWjNH2cvZ6iN0w2L169fVzqdVi6X6xo2Sb1P9vUrm802nstOcJZIJFq+BidOE9rQ/Hzj9LUCAABo5+JTvdU/3WM9psNYB2E/+clPVKvV2h7W3I9f/OIXjqwDYAj+ZZugxzLHdoKoF4MeOh4KhfRf7+xIf9Nm6up/GNL/b3Wg9fvRS/jVzKlfdDjB5/MpmUy2nbozDMOx/y/qVfPZXHb/7jRPePVyUykAAMAkezEkPfYde7WPPyK9ZP/eKUyRsQ7Czp49q3feeUc3b97U73//+4HXY2skMEG+f7ntH9+ewB/qj4ZEjt2+91cJ6dXS8Vs2/1t+rKfn+g3Nhq35hstQKGT7ggM3+ujV0b9j0xAgAwAAdHP2jPTuM/Zqrz0rec+42g7G1FgHYdLhuTihUKjlwN9+3Lt3b2S/zQfGjWEY0i8H+zflur9qvzUtm528QPtoCOFooOILSP/rzvEw7O7kfZ7GhWEYikaj2tra6ngu2rA0//2xG4odvZFynCbvAAAA3PTC+e41N2L26jCdTo+6ATsKhYKWl5f15JNPKpVK2b4pbH9/X5ZlqVQq6datWy53CUyOV9dWpf/D2Rv3HHfGJ/2r2OF0U5Pbt4syDGNk0zm9OhqC2QlVisWiUqmUdnZ27D2JLyD9L9elD5vCzf9B8N+PtbU1ZbNZJRKJgc7WclI/B/Qf/f9Jx6YQAQAApsDzhGAzbSKCsM8++0ySVCqVtLa21tcatVpNHo/HybaAiVQsHgZJ+n90+CH/a2enR/qeRvk36WNBmHR4K17zuUlOsCzLlS17R2/as/PfsEAgIMMwVCwW7U8jPXXkXCuLg817VQ/BpMEOmHda/e+D9KebNrv9XW3+N0cIBgAAAPzJ2G+NfO211xSNRnX37l15PB7VarWeXwAcsizrT9uMjwYnXXz55ZeO9mIrHPMF2gZ2xWJRmUzGsV5M01Q4HO47aO/k6EHn7Q5iP6oeXAzUT7vLBqaMk9v9DMNohGCBQGCszjG7fLn1vLx6n52USqXG63b+zgEAAACzYqyDsOvXr2tra6sRZvUbahGGYdK4cbC1ZVlaWVn50zSJr7cpEad7sr3e/z0pfe/4VFQqlXLkNrxisdg4T8mNKaB8/k8Tbb1c2BEIBGSaplKplL0HHJ0AO+GygUlwdFvfSX9X+jlE/iTNf5c6rTuKQ+djsVhLMGfn71Hzx3PlyhU32gIAAAAm0lhvjax/s1+fBItEIopGo/L5fD2fE3bt2jV98cUXLnYLOOfEH8Qf7B+endWjYrGotbW1xrrx+CVd7/SANtvqBpm+uTdoYPHvC4eH+x/ZJhmNRpVOp5VMJnte0rIspVIpZbNZBQIB7ezs2J4CshuGZLPZxue810PX60FYJpNRMBhUItH+8oCG5sPxfYHDANEBdj/W5rpuj+n2/qPnv2Wz2WNf43Yh4f7+vmOTXPl8/tgkVbvnO+roNkTTNFv+rN8tuNevX29Mc5qm2XHbrGEYja2U6XR6rKbbAAAAgFEb6yDMMAx5PB75fD5tb2/r3Llzfa+1urqqJ554wsHuAPecOPHxqzXpb7a6TnNZlqXt7W0VCgXl8/ljwVokEtX1uyc92Gx70Ho+nx/gh/j2H0/9UHJb/l1O+qeU9P9v3RKZSqV08+ZNpdNpW0GTZVnKZrPa2NiQZVmKRCLK5XI9fVxHz/1qxzTNxtbGSCTS0zSY1BqorK2taWdn5+RQ49fZ1s/Lv+98flpzgDOKCadmJz1/JBJpTDWlUimVSiXF43FZlqVCoaBsNqtCodD4M+l46FR3NLBq9/f4aPgWj8eVTqcVCoVkGIa2trYUCoUaAaX0p3+nhUJBV65ckc/nO/b8a2tryuVy2t/fVzqdVjAYbAn17H4tYrGY0ul0I4yLx+O6d+/esY/Dsiytrq5KOgxfTwqJ7X7dm//bMeq/KwAAAIATxnprZP0b/CtXrgwUgtXXOn+eqyEw3gzDUDweP/kMoC+K0rWg9I6n7cvpUx55PB75/X5Fo1FlMpm202Ur7QKjB9ZhoPL/CZ/YXzgcVjabtf8D8f9uSH8fbUynHLW2tqZUKmV/i9u/SetX/1g4FloYhqFoNCq/39/4/NUvBSgWi8pms8pkMgqHw/L7/Y0wIZfLqVAodA3Bjp7VZVmWgsHgiVsz8/m8wuHDz2MsFuvrYP/64+uy2Wzj40ulUrqezR4Go9eCh/8rHW4hfbXUNSg9Gso1b99sZllWy8fYKQC8efPmsX7bOfo5O+lzczSczGazikajisfjunXrlgqFwrHgs/536ejfz6Mfb7tbhCORSNsJsGg0qlQq1Qi0mp8zn88rGo3KNM2WXpvDp2KxKL/f39h+ezSYsvu1qD+2/nmxLEvnzp1rTB2apqlsNqtwOCzDMJROp08MX+1+DezWAQAAAJPEUxvjA7Si0ag+++wz5XI5/ehHPxp4vbt37xKGTYmlpSXt7e1pcXFRu7u7o25nYNls1pWD2tsJhUL6r3d2dPqtpj98p/cbVX0+nw4ODvRtVa1rSW23Mdrxq38s6G/+qfNU18Or0qm5w8BgY2PjxJDtJIFAQGtra0okEj1NgdW34h0NKnw+n5aXlxvhxPb2dmPi6Ghw0otisah4PK7r1w83sRYKBZmmqf39/daw51/4DgOw82vHzlKrf66kw7BwY2NDxWKxbZAZCoV0+fJlJZPJjrWBQEChUEjXr1+Xz+fT2tqaisVi2zCzvp09mUyqWCwqnU63DQ8DgUDbqbn69tX6+qFQSJFIpOUst3A4rEgkorW1tWNbEFdXVzt+vMvLy8eeM5PJaGtrqzFdFovFGtNe9XXj8biKxWLL5+yo+t+Vet9XrlxpBG29fC1Oks1mlcvlWv6+BQIBXb58+cS/24ZhnHi2XvPXoD7NeFLd2tpaX9uRAQCYNW2/Tz6i+fs1t9dxeq1xxed9MozyZ/qxDsLy+bwuXbqkTCajv/3bvx11Oxgj0xaE2TGu/yEe9Vr1qaWbN282AqJ6KFO//S8QCOjChQuKxWJtt8714ujz1Z+z/jzLy8uKx+N9B2B28X+mAAAA441AZjT4vE+GUf5MP9ZnhMViMZ0/f143b950JAj74IMPHJksAzA+fD6fYrHYsW1t0/J8AAAAAADnjH3emMvltLOzo1/+8pcDr7WxseFARwAAAAAAAJhEYz0RJh1ubbp27ZpeeeUV/bt/9+/6Xuf+/fs9nyWE8Vcul7W0tNSxZn19Xevr60PqCAAAAACA2bW5uanNzc2ONeVyeUjdHDfWQdgHH3wgSfqzP/sz+f1+Pfnkk31tR7Isq+0tYZh81WpVe3t7HWsqlcqQugEAAAAAYLZVKpWuP6eP0lgHYW+//bbu3r3beLtWqymTyfS1Vq1Wk8fT+814GG9zc3NaWFjoWOP1eofUDQAAAAAAs83r9WpxcbFjTblcVrVaHVJHrcY6CLt06VJjO6PH4yHIwjELCwszc2vksL1/V3opPOouAAAAAACTxM7xRPVbI0dhrA/LX1tbk3QYgtVqtYFeAPzJ+3e717yct1cHAAAAAMCkGOuJsLNnzyoUCunu3btKp9MKhUKan5/veR3TNPX222/r17/+tfNNAhPm/gPp9Y/s1b76oXTx+5L3jKstAQAAAAAwFGMdhEnS5cuXFQwG9cYbb/S9xvnz5/Xcc8/1FaIB0+Y9Q/rDH+3VfvWNdMOQfvwDd3sCAAAAAGAYxnprpCRFIhHHtjYuLy87sg4wyT7+vLf6T3qsBwAAAABgXI19EHb+/Hml02lH1nJqHWCSHXztbj0AAAAAAONq7IMwSTp37pwj65w/f96RdYBJ5n/U3XoAAAAAAMbVSIOwcTq8fpx6Adx08ane6p/usR4AAAAAgHE10iAsHA6rUqmMsgVJ0v379xUOh0fdBjAUL4akx75jr/bxR6SXQu72M+5qNenbaucXh44xBAAAAAC4bKS3Rjp1CL4TxqkXwE1nz0jvPiO9nO9ee+1ZyXvG9ZbGWrUmnX6rc83Dq9Ipz3D6AQAAAAD0b6QTYR7P+PzkOE69AG57wcZxeTdi9uoAAAAAAJgUIw3CmMICxtfzhGAAAAAAgCkz8lsj7927N+oWtL29PeoWAAAAAAAA4LKRnhEmSaurq3rzzTfl8/k0Pz8/1Ofe39+XaZpKJpNDfV4AAAAAAAAM38iDsJ2dHcXj8ZH2UKvVOCMMAAAAAABgyo08CKsb1XlhBGAAAAAAAACzYeRB2KgPzB/18wMAAAAAAGA4RhqEHRwcjPLpAQAAAAAAMENGGoSdPXt2lE8PAAAAAACAGTLyrZEAMCtqNanaZTf2nEfi6EIAAAAAcAdBGAAMSbUmnX6rc83Dq9IpgjAAAACMyPt3pZfCo+4CcM/cqBsAAAAAAADue/9u95qX8/bqgEnFRBgmWrlc1tLSUsea9fV1ra+vD6kjAAAAABg/9x9Ir39kr/bVD6WL35e8Z1xtCVNqc3NTm5ubHWvK5fKQujmOIAwTrVqtam9vr2NNpVIZUjcAAAAAMJ7eM6Q//NFe7VffSDcM6cc/cLcnTKdKpdL15/RRIgjDRJubm9PCwkLHGq/XO6RuAAAAAGA8ffx5b/WffE4Qhv54vV4tLi52rCmXy6pWq0PqqBVBGCbawsKCdnd3R90GAAAAAIy1g6/drQfq7BxPtLS0NLKpMYIwAAAAAACmnP9Rd+sHUasd3rDeyZxH8nC7OhxAEAYAAAAAwJS7+JT06W/s1z/9lHu9HFWtSaff6lzz8Kp0iiAMDpgbdQMAAAAAAMBdL4akx75jr/bxR6SXQu72A4wKQRgAAAAAAFPu7Bnp3Wfs1V57VvKecbUdYGQIwgAAAAAAmAEvnO9ecyNmrw6YVARhAAAAAABAkvQ8IRimHEEYAAAAAAAAZsJUBmH379/Xa6+9Nuo2TmSapqLRqGPrGYahfD6vTCajYrFo6zGZTEbRaFR+v18ej0fBYFDxeNz244e1JgAAAAAAgFOmMggzTVPZbFa/+93v9Nlnn6lSqQzleS3Lksfj6foSDAYVCAQGep5MJqNwOCyPx6OVlRXduXNHoVBIy8vLHR9bLBbl9/uVSqUkSblcTqVSSel0WoZhKBqNKhqNyrIs2/24sSYAAAAAAIDTTo+6ATcUi0XVarWWsCmVSuntt9929Xmz2azt2npo1AvLspRKpRrPEwqFVCgUFIlEbD2+WCw2JtESiYS2trYa7wsEAorFYgqHwyoWiwqHw9rZ2ZHP5xv6mgAAAAAAAG6Yuomw27dvN0KmWq3WeEmn0/rJT35y4uNee+01Pfnkk7pw4YJ+8pOf9DVFtrGxYasuEon0PBGWzWZ17ty5Rgi2tbWlnZ0d2yGYZVmKx+OSDgOq5sCqWS6Xk3Q4VVevH+aaAAAAAAAAbpm6ibBUKqVYLKbLly8rFArJNE19+umn+ulPf6p0Oq21tTX9+Z//ectjnnzySZmmqVqtJkna2dlRLpfTzs6OvF6vrefNZrOyLEvJZLLr+V/dti+2+5gymYykw8CpUCj0HKTF4/HG1sRO02j1Ka58Pq9isahsNqtEIjG0NQEn1GpStda5Zs4jeTzD6QcAAAAAMB6mLgiTpFu3bjVeP3funFZWVnTlyhWFw2GlUin9/d//feP9r732mkqlkjwej1KplDY2NhpbEFdXV3Xz5k1bz5lOpxUIBJROpx39WOLxuPL5vCTJ5/P1tbXQNM2WA+svXbrUsf7y5cuN50ylUm1DKzfWBJxSrUmn3+pc8/CqdIogDAAAAABmytRtjfScMOJRD5FKpVLLn29tbcnj8SgWizW2Nvp8Pm1tbeng4EBffPFF1+fM5/MyTbOvc786iUajjfBIUt/nazWHc5FIpOsasVis8bplWS09uLkmAAAAAACAm6YuCPP7/fr5z3/e9n0+n09+v7/x9vXr1xuvt5vkSqVSLVNPJ9nY2JDP5+s6FdWLbDbb8txbW1t93zTZfIh/KBSy9Zjm52o3FefGmgAAAAAAAG6auiAsmUzqjTfe0Ouvv972wPuDg4PG6/VpsEgkou9973vHapeXl49NkB1lGIYMw5BlWfL7/QoGg1pbWxto4sk0Ta2trTXeDoVCfW8lNAyj5e0LFy7YelxzuHX0Y3FjTcCu9++OugMAAAAAwKSauiAsEolodXVV165dk9/v1+XLl/Wzn/1MP/vZz3ThwgWVSiX99V//ta5cudIIdJpDp2Znz56VaZodn+/odkjTNJXNZhWPx+XxeBSPx48FR90cvVnxypUrPT2+2dGJNrtTZUfrmj8GN9YEJHsh18t5wjAAAAAAo8fPJZNp6oIw6XDS67nnnlOtVlM+n1cqlVIqlZJhGLp9+7a8Xm/LVsiTtvbdvXtX8/PzJz7P0QPj28nn8wqHwyeGbe3WbA6IfD5fy/lavbpz507L23bPGHviiSda3t7e3nZ1TeD+A+n1j+zVvvqhVHngajsAAAAAZhi/pJ9eUxmESVIul9O1a9e0srKiWq2ms2fP6tatWzp//rxyuZyee+45+Xw+Xbt27cSQKpvNKhgMnvgcgUBAW1tbSqfTSiQSHSejstmswuFw1763trZa3o5EIpIOA7V4PK5gMCiPxyO/369wOKxMJiPLsk5c7+hEW7/TW81bRN1YE3jPkP7wR3u1X30j3WCgEAAAAIAL+CX9dDs96gbclEgkTjxbK5fLNV73+/26cOGCfvGLX+gv//IvValU9PbbbyubzbacKXbSczSzLEvZbFYbGxvHAirDMBSNRlUoFE5cr/kQekman59XOBw+to3QsqzG+WSpVEq5XK7t5Fi3rZ12NX8sbqwJfPx5b/WffC79+Afu9AIAAABgdvXzS3p+NpkcUzsR1otYLKZ4PK7z58/r1KlT8vv9+ulPf6p33nlHXq+3p7V8Pp+SyaQODg6Uy+WObRssFovKZDJtH2ua5rFw6NatW1pbW9PBwYFqtZpqtZpKpdKxAC4ej7c9gL7fsOlo3/v7+66uCRx87W49AAAAANjRzy/pMTmmeiKsF8lkUoFAQNlsVj6fT5cvX9Zzzz030JqxWEyRSEQrKystE10bGxtKJpPH6o9OWvl8Pt27d+9YgFTfknn07LHV1VVFIhHbZ3b1wo3pLSfWLJfLWlpaGnid9fV1ra+vD7wO+ud/1N16AAAAALCDX9KfbHNzU5ubmwOvUy6XHeimP1MXhH322Wf64Q9/2LXugw8+UCQSaZn4isViAx1M347P59POzk7L9kbLslQsFhvnf9UdDcISiUTHUCuRSGhnZ6exndKyLG1sbLRcBODz+RwJnJr7cGPNflWrVe3t7Q28TqVSGXgNDObiU9Knv7Ff//RT7vUCAAAAYHbxS/qTVSoVR34GH6WpC8JisZju37+vSCSiaDSqSCSiv/qrvzpWt7KyoldeeUWZTEbf+973XO/r+vXrLYflFwqFY0HY0cPjL1y40HXdVCrVcq5YJpNpCcLm5+cdCa2ab890Y81+zc3NaWFhYeB1et0CC+e9GJLe/JW9vfiPPyK91P6yVwAAAAAYCL+kP5nX69Xi4uLA65TLZVWrVQc66t3UBWHhcFi3b99WsVhUsViUdDh5tLy83BKMnT17VtevX1ckElE+n9ef//mfu9pXKBRSJBJp9NTuwPmj4ZKdialAIKBQKNSy9dIwDIVCIdtrtNOpFzfW7NfCwoJ2d3cHXgejd/aM9O4zh1cQd3PtWcl7xvWWAAAAAMwgfkl/MqeOFVpaWhrZZNnUHZafz+cViUR0/vx5nTt3TrVaTQcHByoUCkqlUgqHwzp16pT+5m/+Ru+8844ODg5aztlyUzQa7fj+YDDY17rLy8stbzeHbEffZ3eS6+hB9s29ubEmIEkvnO9ecyNmrw4AAAAYd+/fHXUHaKf+S3o7+CX95Jm6ICyRSCibzWp7e1u//e1vVa1WVSgUtLq62rh1sVar6dNPP1Umk5FpmioUCkPpLRAINF5vty3w6ISU3YDpaKDUHDg1b8eU2k+itXN0m2bzNk431gTsep4QDAAAABPATsj1cp4wbFzxS/rpNXVBWK1WO3bm18rKira2tnRwcKA33nhDoVBI6XRazz33nEKhkN55552h9NYchLXbFthpsquTo2s1h2z9rtkcwvl8vpbe3VgTAAAAAKbF/QfS6x/Zq331Q6nywNV24BJ+ST+Zpi4Iu3///onvO3v2rNLptHK5nO7cuaNMJqPt7W298cYbQ+lte3u78Xq7bZL1c73qjk5Q2dUcMIVCoZag7M6dO7bWaO71aPDlxpoAAAAAMC3eM+ydLyVJX30j3TC61wFwxtQFYefOndPPf/7zrjW3bt1SIpHQ7373uyF11hpsnbQtsPnP6wfrd3N0C+XRQO3SpUuN15sP1e+kuS6VSh17vxtrAgAAAMA0+Pjz3uo/6bEeQP+mLghLJpN644039Mtf/rJr7a1btxSJRFSpVIbQ2eFB/tJhjydpDohM07R1Tli3gK35MgA74VpzTSAQGNqaAAAAADANDr52tx5A/6YuCAsEAnrnnXcUi8X0+uuvd6z1+Xw6f/683nzzTdf7yufzMk1TPp9PV65cObEuEom0bG3c2NjounZzyJROp4+9PxQKtQRP9UDuJLlcrvH6SZNbbqwJAAAAANPA/6i79QD6N3VBmHQ4cfWjH/1I165d05/92Z/p5z//+YlTX/Pz87p582bPz1EsFuX3++XxeBSNRjtuDzRNU6urq5Kk27dvtz0ov1lzaFS/2bJTH/X3JxKJY9si67a2thqvdwrXLMtSNpuVdBjKJRKJE2vdWBMAAAAAJt3Fp3qrf7rHegD9m8ogTDoMk1ZXV7W/v69kMim/36/Lly/rF7/4hX7961/r17/+ta5cuaJsNmtr+2G79euPKxaLCofDLdsF6+rvm5+fV6lUOjGoahYKhVpCpmg02rZHy7Iaz3n0MUcFAoFGwGYYhjKZTNu6lZUVSYfTcs2B3LDWBAAAAIBJ92JIeuw79moff0R6qfuPiQAcMrVBmHQ4sXTr1i15vV7VajXl83mtra0pHA4rHA43ghs74dRR8Xj82J9ls1n5/X7F4/HG80SjUSUSCe3s7LRseewmkUioUCjI5/PJNE2dO3dOmUxGhmE0Qqdz587JNM3G+t3EYrHGmqlUSvF4XIZhyLKsRmBnGIZCoZDu3bvXdXLNrTUBAAAAYJKdPSO9+4y92mvPSt4zrrbjilpN+rba+aVWG3WXwHFTHYRJh0HNwcGB3nnnHZ09e1a1Wq3lxefz6fr16z2vG4lEVCqVlEgkFAgEWgIewzC0v7+vK1eu6ODgQOl0uq8AKBKJ6ODgQFtbW1peXtbGxobC4bBWVlZ08+ZNJRIJlUqljpNgJ62ZTqdlmqZWVlYa4d38/LxyuZx2dnZ66teNNQEAAABgkr1wvnvNjZi9unFUrUmn3+r8UiUIwxg6PeoGhiWZTCqZTOru3bsyTVOmaTZuLzx79mxfawYCgZ5CqH4lEgnHz9Wqfz7GfU0AAAAAmFbPT2gIBkyyiQ3CXnvtNf2X//Jfen7c+fPndf48/7UBAAAAAACYNRO7NfLWrVv6/e9/P+o2AAAAAAAAMCEmNgg7ODjQ9773Pb322mv67LPPRt0OAAAAAAAAxtzEbo2UJMuylM1mlc1mJR0e2h6NRhWLxfS9731vtM0BAAAAAICZN+eRHl7tXoPhmNiJsLrmGyCLxaJSqZSCwaCeeOIJvfbaa/rggw+6rvGLX/xiCJ0CAAAAAIBZ4/FIp+Y6v3gIwoZmYoOwd955R7VaTR6PR8FgUFJrKHZwcKBsNqt4PK5Tp07pwoUL+tnPfqZf//rXx9YqFApD7h4AAAAAAADDNrFbI5PJpCKRiOLxuPb395XP51Wr1fT3f//3un37tizLUq1Wa9QbhiHDMCRJPp+vsY1SkvL5/Eg+BgAAAAAAAAzPxAZhkhQKhVQqlZRKpRSPx7W2tqZcLidJunfvnvL5vAqFgorFYksodnBwoHw+TwAGAAAAAAAwQyZ2a2SzdDqtO3fu6NNPP9Vf/MVf6J//+Z917tw5vfHGG/r0009VrVZVKBSUSCQUCAQktW6jBAAAAAAAwPSb6ImwZqFQSL/97W+1tramUCikVCqlt99+u/H+lZUVraysSJLu37+vW7duKZfLqVgsjqplOKBcLmtpaaljzfr6utbX14fUEQAAAAAAs2tzc1Obm5sda8rl8pC6OW5qgrC6ra0txeNxXbp0Sfl8XrlcTn/5l3/ZUnP27Fmtrq5qdXVVxWJRf/3Xfz2ibjGoarWqvb29jjWVSmVI3QAAAAAAMNsqlUrXn9NHaeqCMEmKRCIyTVOrq6sKhULKZDL6T//pP51YW58Uw+SZm5vTwsJCxxqv1zukbgAAAAAAmG1er1eLi4sda8rlsqrV6pA6ajWVQZh0eDNkLpdTPp/XpUuXdPPmTeVyOf35n//5sdp4PD6CDuGEhYUF7e7ujroNAAAAAMAYmPNID692r4F77BxPtLS0NLKpsak4LL+TWCym/f19nT17VoFAQD//+c+P1ayuro6gMwAAAAAA4CSPRzo11/nFQxA206Y+CJMOp8MKhYI2Njb0xhtv6F//63+t3/3ud6NuCwAAAAAAAEM0E0GYJH3xxRdaXl5WMpnU9va2AoGA/u7v/m7UbQEAAAAAAGBIpuKMsC+++EKmacqyLJmmqVKpJNM0ZZqm9vf3ZVlWS73H41GtVlMikVAul1Mul9N3v/vd0TQPYOK9f1d6KTzqLgAAAAAA3UxsEHbhwoVG+NVJrVbr+L5PP/1UP/zhD3Xnzh2HOwQwDd6/273m5fzhWQMvnHe/HwAAAABA/yY2CNvZ2WlMdnXi8/kUCAQaL8FgUPPz8423z549O6SOAUya+w+k1z+yV/vqh9LF70veM662BAAAAAAYwMQGYc38fr8uXbrUEngRcgEY1HuG9Ic/2qv96hvphiH9+Afu9gQAAADMIo4jgVMm+rD85557TqFQSAcHB8pms9re3tbBwYH8fj8hGICBffx5b/Wf9FgPAAAAwP5xJHbqgG4mNgiLRCK6detWI/y6efOmarWaksmkgsGgnnzySb322mv6p3/6p65rffbZZ0PoGMCkOfja3XoAAADACZMcEPV6HEnlgavtYAZMbBAWjUYbr589e1axWEy3bt3S/v6+7ty5ox/96Ee6c+eOVlZWdOrUKV24cEE///nP9etf//rYWltbW0PsHMCk8D/qbj0AAADQzbRPS/VzHAkwiIk9I+yNN9448X2hUEihUEiSdP/+fRUKBd26dUtXr15VMpmUz+dTJBLRhQsXJEn5fH4oPQOYLBefkj79jf36p59yrxcAAADMnlm4vKmf40g4lxeDmNiJMLvaTYu98sor2tnZUTKZVCqVGnWLAMbUiyHpse/Yq338Eeml0ODPOam/yQMAAIDzZmFaiuNIMGxTH4QdFQqFlE6n9dvf/lbb29v64Q9/OOqWAIyps2ekd5+xV3vt2e6/fZv2sXYAAAA4axYub+I4EgzbzAVhzUKhkAqFgs6fPz/qVgCMqRds/OfhRqx7HYeAAgAAoFezMC11scfjRTiOBIOa6SCsLp1Oj7oFABPseRth2SyMtQMAAMBZszAtNYrjSDDbCMIkraysjLoFAFNuFsbaAQAA4KxZmJZy+jgSoJuJCMJ+9rOf6bPPPht1GwDQt1kYawcAABiFWk36ttr5pVYbdZf9mZVpKaeOIwHsmIgg7L/+1/+qaDSqv/u7vxtonevXr+vUqVP6i7/4C/3zP/+zQ90BQHejGGvn0H0AADALqjXp9FudX6oTGoQxLfUndo4jAeyYiCBMkmq1mhKJhH7yk5/0vUYqlVKtVtNvf/tbhUIhffHFF841CAAdOD3Wzg2UAAAAs4FpKcBZExOE1X366ae6fPlyX489d+6cAoGAEomEVldXlUqlHO4OANpzcqydGygBAADQjGkpwL6JC8K2t7dVrVZ14cIF/f73v+/psTs7O/rtb3+ra9eu6dq1azIMrmUDMBxOjrVzAyUAAAAA9GfigjBJyuVyisfjCoVC+t3vftfXGvfu3dP+/r7DnWHYyuWylpaWOr5sbm6Ouk1AknNj7dxACQAAAGBcbW5udv05vVwuj6y/0yN75gElk0mFQiGFQiHl83n9m3/zb2w/9v79+4pGo1peXnaxQwxDtVrV3t5ex5pKpTKkboDB2Rlr5wZKAAAAAOOqUql0/Tl9lCY2CJOkSCSiO3fu6N/+23+rK1eu6D/8h//Q9TGfffaZ4vG4LMvSm2++OYQu4aa5uTktLCx0rPF6vUPqBhiOUdxACQAAAAB2eL1eLS4udqwpl8uqVqtD6qjVRAdhkhQIBLS9va1Lly6pVCrp7bffPrH2pz/9qd58803VajX5/X698sorQ+wUblhYWNDu7u6o2wCG6uJT0qe/sV/f7QZKAAAAAHDK+vq61tfXO9YsLS2NbGpsIs8IO8rn8+nTTz/V/v7+iTdKXrlypRGCeTwepdPpIXcJAM5w8gZKAAAAAJglUxGE1V27dk0rKyvHbpS8fft2I/jyeDwKhUJMgwGYWE7eQAkAAAAAs2TigrB/+qd/6vj+RCKhra0t/fCHP2zcKFkPwWq1WsvbADCpnLqBEgAAAABmyUQEYefOnZN0GGQlEolGwHWSUCikmzdv6rnnntMHH3ygYrEoj8fTeN8Pf/hD13sGMN7evzvqDtxn5wZKAAAAAJglExGEpdNpHRwcKJfLaWVlRZFIRL/4xS86PqZ+iP61a9caf+bxeE48QwzA9LATcr2cn40wDAAAAADwJxMRhEnS2bNn9dxzz+natWv6zW9+Y/uMr08//VRvvPFGY1tkKMSp0cA0u/9Aev0je7WvfihVHrjaDgAAAABgjJwedQPDkE6ndeHCBV26dEn37t0bdTtAX+Y80sOr3Wtm3XuG9Ic/2qv96hvphiH9+Afu9gQAAAAAGA8TMxE2qFgspu3tbd28eXPUrQB98XikU3OdXzwEYfr4897qP+mxHgAAAAAwuWYmCJMOt0V++umno24DgIsOvna3HgAAAAAwuWYqCAMw/fyPulsPAAAAAJhcBGEApsrFp3qrf7rHegAAAADA5JqJw/IBTAYnLgR4MSS9+St7B+Y//oj0EhfJAgAAAK54/670UnjUXQCtmAgDMDacuBDg7Bnp3WfsPd+1ZyXvmYHbBgAAAGbO+3e717yct1cHDBNBGICp88L57jU3YvbqAAAAALS6/0B6/SN7ta9+KFUeuNoO0BOCMAAz6XlCMAAAAKAv7xn2jiKRpK++kW4Y7vYD9IIgDAAAAAAA2Pbx573Vf9JjPeAmgjAAAAAAAGDbwdfu1gNuIggDAAAAAAC2+R91tx5wE0EYAAAAAACw7eJTvdU/3WM94CaCMAAAAAAAYNuLIemx79irffwR6aWQu/0AvSAIAwAAAAAAtp09I737jL3aa89K3jOutgP05PSoGwAGUS6XtbS01LFmfX1d6+vrQ+oIAAAAAKbfC+ell/Oda27EDuswWzY3N7W5udmxplwuD6mb4wjCMNGq1ar29vY61lQqlSF1M5vmPNLDq91rAAAAAMyW5wnBZlKlUun6c/ooEYRhos3NzWlhYaFjjdfrHVI3s8njkU4RdAEAAAAAdPgz+OLiYseacrmsarU6pI5aEYRhoi0sLGh3d3fUbQATrVaTqrXONXOew9ATAAAAADqxczzR0tLSyKbGCMIAYMZVa9LptzrXPLzK5B8AAACAycetkQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJp0fdAAAAAAAAmF1zHunh1e41gBMIwgAAAAAAwMh4PNIpgi4MCVsjAQAAAAAAMBMIwgAAAAAAADATCMIAAAAAAAAwEwjCAAAAAAAAMBM4LB8TrVwua2lpqWPN+vq61tfXh9QRAAAAgElVq0nVWueaOc/h4e4A2tvc3NTm5mbHmnK5PKRujiMIw0SrVqva29vrWFOpVIbUzeTgemIAAADguGpNOv1W55qHV7nhEOikUql0/Tl9lAjCMNHm5ua0sLDQscbr9Q6pm8nB9cQYd/w2FgAAAJhMXq9Xi4uLHWvK5bKq1eqQOmpFEIaJtrCwoN3d3VG3AcBh/DYWAAAAmEx2jidaWloa2dQYh+UDAAAAAABgJhCEAQAAAAAAYCYQhAEAAAAAAGAmEIQBAAAAAABgJnBYPgAAAADAFm52BjDpCMIAoIM5z+HthN1qAAAAZgE3OwOYdARhANCBx8M3cgAAAAAwLTgjDAAAAAAAADOBIGwETNNUNBod6ZqZTEbRaFR+v18ej0fBYFDxeFzFYrHvHtxYEwAAAAAAwCkEYQ6yLEsej6frSzAYVCAQGMmaxWJRfr9fqVRKkpTL5VQqlZROp2UYhqLRqKLRqCzLsv1xu7EmAAAAAACA0zgjzEHZbNZ2bT00GuaaxWKxMTWWSCS0tbXVeF8gEFAsFlM4HFaxWFQ4HNbOzo58Pt/Q1wSmFQfvAwAAAMBoMRHmoI2NDVt1kUjE9kSYU2talqV4PC7pMKBqDqya5XI5SYdbLev1w1wTmGYej3RqrvMLV40DAAAAgHuYCHNINpuVZVlKJpNdz+paXl4e+prxeLyxNbHT5Fh9iiufz6tYLCqbzSqRSAxtTQAAAAAAALcQhDkknU4rEAgonU6P3ZqmabYcWH/p0qWO9ZcvX1Y+n5d0GHC1C63cWBMAAAAAAMBNbI10QD6fl2mats/9GvaazUFaJBLpekZXLBZrvG5ZViPAcntNAAAAAAAANxGEOWBjY0M+n6/rVNSo1mw+cD8UCtl6TPN5Yzdv3hzKmgAAAAAAAG4iCBuQYRgyDEOWZcnv9ysYDGptbW2giScn1zQMo+XtCxcu2Hpcc7h19HndWBMAAAAAAMBtBGEDOrp10TRNZbNZxeNxeTwexePxY8HRMNdsPsdLku3bKo/WNT+fG2sCAAAAAAC4jcPyB3D0wPh28vm88vm8EomEtra2hr7mnTt3Wt7udpZX3RNPPNHy9vb2dmOiy401AQAAAADumvNID692rxn2WsAwEYQNIBAIaGtrS5ZlqVQqqVgsyjTNtrXZbFbb29va2dkZ6ppHH9vv9FapVHJ1TcBJ/J8yAAAAcJzHI51y6PtgJ9cChokgbECJRKLlbcuylM1mtbGxIcuyWt5nGIai0agKhcLQ1jwpROtV8/O6sSbgJP5PGQAAAMAg+OX69CIIc5jP51MymVQymVQ+n9fq6mpL4FMsFpXJZJRMJoeyZr9h09Htjvv7+66u2a9yuaylpaWB11lfX9f6+vrA6wCzrFaTqrXONXOew6ASAAAAGGf8cr29zc1NbW5uDrxOuVx2oJv+EIS5KBaLKRKJaGVlpeVg+I2NjZ6CMLfXtMON6S0n1qxWq9rb2xt4nUqlMvAawKyr1qTTb3WueXiVbygAAACASVWpVBz5GXyUCMJc5vP5tLOzo3A43AiuLMtSsVhUJBJxfU2fz+dI4NQ8zeXGmv2am5vTwsLCwOt4vd6B1wAAAAAAYJp5vV4tLi4OvE65XFa1WnWgo94RhA3J9evXFQ6HG28XCoW+g7Be1pyfn3cktJqfn3d1zX4tLCxod3d34HUAAAAAAEBnTh0rtLS0NLLJMoKwIQmFQopEIioWi5KcOXDezpr9Tl0dDbqOToQ5vSYAAAAATBMOWwfG09yoG5gl0Wh06GsuLy+3vG13kuvoQfbBYNDVNQEAAABgmng80qm5zi9cIgQMH0HYEAUCgcbrTmwLtLNm89ZJyf4kWqlUanm7eculG2sCAAAAAAC4jSBsiJpDK6e2BXZb8+j0lt3QqnnKy+fztTyPG2sCAAAAAAC4jSBsiLa3txuvO7VNstuaoVCoJSC7c+dOz+seDb7cWBMAAAAAAMBtBGFD1Lw10KltgXbWvHTpUuN1wzBsrdtcl0qlhrImAAAAALjh/buj7gDAuCAIG6J8Pi9JSiaTQ11zbW2t8Xr9hslOmmsCgUDbgM2NNQGML755BAAA48rO9ykv5/l+BsAhgrAhyefzMk1TPp9PV65cGeqaoVCoJXiqh2cnyeVyjddPmtxyY00Ao8E3jwAAYFLdfyC9/pG92lc/lCoPXG0HwAQgCOtTsViU3++Xx+NRNBrtuD3QNE2trq5Kkm7fvn3iQflurFm3tbXVeH1jY+PEOsuylM1mJR1utUwkEkNdE8Bw8c0jAACYZO8Z0h/+aK/2q2+kG/ZOdQEwxQjC+pTL5Rq3IBaLRYXD4ZbtgnX1983Pz6tUKikUCg11zbpAINCYyjIMQ5lMpm3dysqKpMNbHZunuIa1JoDh4ptHAAAwyT7+vLf6T3qsBzB9CML6FI/Hj/1ZNpuV3+9XPB7X2tqawuGwotGoEomEdnZ2FAgEhr5ms1gspkKhIJ/Pp1QqpXg8LsMwZFlWI1wzDEOhUEj37t3rOmXm1poAhodvHgEAwCQ7+NrdegDT5/SoG5hUkUhEpVJJ6XRaxWJR+/v7jWmuevBz5coVRSIR2+GPG2u2e46DgwNlMhndvHlTKysrsixLPp9Py8vLyuVyisViI18TwHDwzSMAAJhk/kfdrR8Hcx7p4dXuNQDsIQgbQCAQaDkna1zXbCeZTDp6e6VbawJw1yx88wgAAKbXxaekT39jv/7pp9zrxS0ej3SKoAtwDFsjAWCGXezxm8FJ/OYRAABMrxdD0mPfsVf7+CPSS92PVwYw5QjCAGCG8c1jb2o16dtq55dabdRdAgAwO86ekd59xl7ttWcl7xlX2wEwAdgaCQAzrP7N48v57rV88yhVa9LptzrXPLzK9gUAAIbphfPdv5e5ETusAwAmwgBgxtn5ppBvHgEAwCR7nu9jAPxfCMIAAF3xzSMAAACAaUAQBgAAAAAAgJlAEAYAAAAAAICZwGH5ADCB5jyHh7J3qwEAAAAA/AlBGCZauVzW0tJSx5r19XWtr68PqSNgODwebiYEAAAAMH42Nze1ubnZsaZcLg+pm+MIwjDRqtWq9vb2OtZUKpUhdQMAAAAAwGyrVCpdf04fJYIwTLS5uTktLCx0rPF6vUPqBgAAAACA2eb1erW4uNixplwuq1qtDqmjVgRhmGgLCwva3d0ddRsAAAAAAED2jidaWloa2dQYt0YCAAAAAABgJhCEAQAm0vt3R90BAADoV60mfVvt/FKrjbpLANOIrZEAgLFjJ+R6OS+dmpNeOO9+PwAATLJaTap2CZXmPIe3Ug9LtSadfqtzzcOr3JINwHkEYQCAsXL/gfT6R/ZqX/1Quvh9yXvG1ZYAAJhohE4A8CdsjQQAjJX3DOkPf7RX+9U30g3D3X4AAAAATA+CMADAWPn4897qP+mxHpOHc2QAAADgFLZGAgDGysHX7tZj8rClBwAAAE5hIgwAMFb8j7pbDwAAAGB2EYQBAIbGzm2QF5/qbc2ne6wHAAAAMLsIwgAAjrATcr2c7173Ykh67Dv2nvPxR6SXQvZqAQAAAIAgDAAwsPsPpNc/slf76odS5cHJ7z97Rnr3GXtrXXtW8p6xVwsAAAAABGEAgIG9Z0h/+KO92q++kW4YnWteON99nRsxe3UAAABOsjMFD2B8EYQBAAb28ee91X/SY307zxOCAQAAhzl11AOA8UUQBgAY2MHX7tYDAAC4zcmjHgCML4IwAMDA/I+6Wz9tajXp22rnl1pt1F0CADBbnD7qAcB4Oj3qBgAAk+/iU9Knv7Ff//RT7vUyCao16fRbnWseXpVOeYbTDwAA6O+ohx//wJ1eALiHiTAAwMBeDEmPfcde7eOPSC+F3O0HAACgVxz1AMwGgjAAwMDOnpHefcZe7bVnJe8ZV9sBAADoGUc9ALOBIAwA4IgXbNzieCNmr85JnMcFAADsuNjj0Q2zftQDMKk4IwwAMDTPDzkEkziPCwAA2PNiSHrzV/YOzOeoB2ByMREGAAAAAJh5HPUAzAYmwjDRyuWylpaWOtasr69rfX19SB0BAAAAmFQvnJdezneuGcVRD8Ak2dzc1ObmZseacrk8pG6OIwjDRKtWq9rb2+tYU6lUhtQNAAAAgPfvSi+FR92Fe0Zx1AMwSSqVStef00eJIAwTbW5uTgsLCx1rvF7vkLoBAAAAptv7d7vXvJyXTs0xNQXMKq/Xq8XFxY415XJZ1Wp1SB21IgjDRFtYWNDu7u6o2wAAAACm3v0H0usf2at99UPp4vc5RwuYRXaOJ1paWhrZ1BiH5QMAAAAAunrPsHejoiR99Y10w3C3HwDoB0EYAAAAADigVpO+rXZ+qdVG3WX/Pv68t/pPeqwHgGFgayQAAAAAOKBak06/1bnm4VXplGc4/Tjt4Gt36wFgGJgIAwAAAAB05X/U3XoAGAaCMAAAAABAVxef6q3+6R7rAWAYCMIAAAAAAF29GJIe+4692scfkV4KudsPAPSDIAwAAAAA0NXZM9K7z9irvfas5D3jajsA0BeCMAAAAACALS+c715zI2avDgBGgVsjAWDGzXkOb7DqVgMAAGDH84RgAMYYE2EAMOM8HunUXOcXD0EYAAAYsvfvjroDANOIIAwAAAAAMFR2Qq6X84RhAJxHEAYAAAAAGJr7D6TXP7JX++qHUuWBq+0AmDEEYQAAOIjfXAMA0Nl7hvSHP9qr/eob6Ybhbj8AZgtBGAAANrGNAwCAwX38eW/1n/RYDwCdEIQBAGAD2zgAAHDGwdfu1gNAJwRhAADYwDYOAACc4X/U3XoA6IQgDAAAG9jGAQCAMy4+1Vv90z3WA0AnBGEAANjANg4AwDDVatK31c4vtdqou+zPiyHpse/Yq338EemlkLv9AJgtp0fdAAAAk4BtHACAYarWpNNvda55eFU65RlOP046e0Z695nDC2a6ufas5D3jeksAZggTYQAA2MA2DgAAnPPC+e41N2L26gCgFwRhAADYwDYOAACG63lCMAAuYGskJlq5XNbS0lLHmvX1da2vrw+pIwDTim0cAAAAQHebm5va3NzsWFMul4fUzXEEYZho1WpVe3t7HWsqlcqQugEw7V443z0IYxsHAAAAZlmlUun6c/ooEYRhos3NzWlhYaFjjdfrHVI3AMA2DgAAAMw2r9erxcXFjjXlclnVanVIHbUiCMNEW1hY0O7u7qjbAAAAACba+3ell8Kj7gLANLBzPNHS0tLIpsY4LB8AAAAAptj7d7vXvJy3VwcAk46JMACAI+Y80sOr3WsAAMDw3H8gvf6RvdpXP5Qufp8LXwBMNybCAACO8HikU3OdXzwEYQAADNV7hvSHP9qr/eob6Ybhbj8AMGoEYQAAAAAwpT7+vLf6T3qsB4BJQxAGAAAAAFPq4Gt36wFg0nBGGABg7HDeGAAAzvA/6m49AEwaJsIAAGOH88YAAHDGxad6q3+6x3oAmDRMhAEAAADAlHoxJL35K3sH5j/+iPRSyP2enMYkOYBeMBEGAMAEq9Wkb6udX2q1UXcJABiVs2ekd5+xV3vtWcl7xtV2XMEkOYBeMBEGAMAEq9ak0291rnl4VTrFDwAAMLNeOC+9nO9ccyN2WAcA046JMAAAxtD7d0fdAQBgljxPCAZgRhCEAQAwZHZCrpfzhGEAAACA0wjCAAAzb5iB0/0H0usf2at99UOp8sDVdgAAAICZQhAGAJhq4zZ99Z5h7+YuSfrqG+mG4W4/ADDruHQEAGYLh+UDAKZWr9NXF7/v/m1ZH3/eW/0nn0s//oE7vQAAuHQEreY8h1/vbjUAJhcTYQCAqTWO01cHX7tbDwAA+ufxSKfmOr94CMKAiUYQBgCYWv1MX7nN/6i79QAAAABORhAGAJha4zh9dfGp3uqf7rEeAAAAwMkIwgAAU2scp69eDEmPfcde7eOPSC+F3O0HAAAAmCUEYQCAqTWO01dnz0jvPmOv9tqz7h/eDwAAAMwSgjAAwNQa1+mrF853r7kRs1cHAAAAwL7To24AGES5XNbS0lLHmvX1da2vrw+pIwDjpD599XK+e+24TV89P4IQrFaTqrXONXMebssCAADAyTY3N7W5udmxplwuD6mb4wjCMNGq1ar29vY61lQqlSF1A2AcvXC+exDG9NWhak06/VbnmodXpVMEYQCAAc15Dv8/pVsNgMlTqVS6/pw+SgRhmGhzc3NaWFjoWOP1eofUDYBJNYrpKwDAbHr/rvRSeNRdjJ7Hwy9WgGnl9Xq1uLjYsaZcLqtarQ6po1YEYZhoCwsL2t3dHXUbAAAAgN6/273m5bx0ao5JZADTy87xREtLSyObGuOwfAAAAAAY0P0H0usf2at99UOp8sDVdgAAJyAIAwAAAIABvWdIf/ijvdqvvpFuGO72AwBojyAMAAAAAAb08ee91X/SYz0AwBkEYQAAYOLZOZcHANx08LW79QAAZxCEAQCAsWb38GnCMACj5H/U3XoAgDMIwgAAwNji8GkAk+LiU73VP91jPQDAGQRhAABgbHH4NIBJ8WJIeuw79moff0R6KeRuPwCA9gjCAADA2OLwaQCT4uwZ6d1n7NVee1bynhn8OdkSDgC9IwgbAdM0FY1GB14nGAzK4/Eon8/3/NhMJqNoNCq/3y+Px6NgMKh4PK5isdh3P26sCQCYbRw+DWCSvHC+e82NmL06zkcEAHcQhDnIsix5PJ6uL8FgUIFAYKDnSqVSMk2z58cVi0X5/X6lUilJUi6XU6lUUjqdlmEYikajikajsixrpGsCACBx+DSA6fO8jRCM8xEBwD0EYQ7KZrO2a+uhUT+KxaIymUxfj6sHUolEQoVCQZFIRIFAQLFYTKVSSaFQSMViUeFw2FZw5caaAADUcfg0gFnE+YgA4B6CMAdtbGzYqqsHRf2wLEvxeHygxwUCAW1tbbWty+Vykg63b3Z7HjfWBACgGYdPA5hFnI8IAO45PeoGpkU2m5VlWUomk13P/1peXu77eVZXVzU/Py9JPU1XxePxRn2nabT6JFc+n1exWFQ2m1UikRjamgAANKsfPv2yjeMwnTp8GgBGjfMRAcA9BGEOSafTCgQCSqfTrj1HNptVPp/Xzs6OVlZWbD/ONM2WA+svXbrUsf7y5cuNA/hTqVTb0MqNNQEAaOeF892DMLuHTwPAJOB8RABwD0GYA/L5vEzTPHFroBNM09Ta2pqSyaRCod72fTSHc5FIRD6fr2N9LBZrvG5ZlvL5fMufubUmAAD9snP4NABMiotPSZ/+xn79MM9HnPNID692rwGAccUZYQ7Y2NiQz+frOhU1iHg8rlAo1NfEWfMh/nZDtOYzzG7evDmUNQEAAACM9/mIHo90aq7zi4cgDMAYIwgbkGEYMgxDlmXJ7/crGAxqbW2tsQ3QCalUSoZhNA6d77W/ZhcuXLD1uOZw6+jH4saaAAAAQC9qNenbaueXWm3UXfanfj6iHZyPCAC9YWvkgI4eEm+aprLZbGNiKhaL6cqVKz1vZ6wzDEOZTEZbW1t93TTZfI6XJNtrHK0zDKPxMbixJgBMAraDAMD4qNak0291rnl4VTo1of9d5nxEAHAHQdgAjh4Y304+n1c+n1cikejrDLGVlRXFYrG+D5e/c+dOy9vdzvKqe+KJJ1re3t7eboRWbqwJAJPA45ncH6iGrVY7/CG1kzkP22cAYBB2z0fkFzkA8CcEYQMIBALa2tqSZVkqlUoqFosyTbNtbTab1fb2tnZ2dmyvH4/HJUnXr1/vu8ej/fQ7vVUqlVxdEwDgnvfvSi+Fh/uc0z6pAQCThF/kAMCfEIQN6OiklmVZymaz2tjYkGVZLe8zDEPRaFSFQqHruvVJskKhYHviqp2TgrleNX8sbqwJAOjP+3e717ycPzy8mO0zAAAAmHUEYQ7z+XxKJpNKJpPK5/NaXV1tCXyKxaIymYySyeSJa1iWpXg8rkQioUgkMlA//YZNR8O3/f19V9fsV7lc1tLS0sDrrK+va319feB1AGCY7j+QXv/IXu2rH0oXv8+BygAAAOjf5uamNjc3B16nXC470E1/CMJcFIvFFIlEtLKy0nLT4sbGRscgbGVlpbHtcly4Mb3lxJrValV7e3sDr1OpVAZeAwCG7T1D+sMf7dV+9Y10w5B+/AN3ewIAAMD0qlQqjvwMPkoEYS7z+Xza2dlROBxuhGGWZalYLLad9spkMjIMo6ezxLo9vxOBU/M0lxtr9mtubk4LCwsDr+P1egdeAwCG7ePPe6v/5HOCMAAAAPTP6/VqcXFx4HXK5bKq1aoDHfWOIGxIrl+/rnD4TycVFwqFY0GYYRhKpVJKp9OO3aY4Pz/vSGg1Pz/v6pr9WlhY0O7u7sDrAMAkOvja3XoAwKFRXDoCAOPIqWOFlpaWRjZZNjeSZ51BoVCoJfhqd+B8PB5XKBTquG2yV/1OXR0Nuo5OhDm9JgCgd/5H3a0HgFlg99IRO3UAgPHHRNgQRaNRFYvFtu/LZDIyTVORSETxeLzrWs2h0sbGhm7evNl4+/Lly4rFYpKk5eXllvPJLMuyFUAdPcg+GAw2XndjTQBA7y4+JX36G/v1Tz/lXi8AMIm4dAQAZg9B2BAFAoHG60e3BX755ZeSdGJQ1olhGC3BVCAQaARhzdsxpcNJNDvbLkulUsvbzdNsbqwJAOjdiyHpzV/ZOzD/8Uekl5zZdQ8AU4NLRwBg9rA1coiag7BhbQtcXl5uebvdlsx2mifOfD5fS+9urAkA6N3ZM9K7z9irvfYsUwwAcFQ/l44AACYbQdgQbW9vN16PRqMt70un06rVarZfmkOkXC7X8r50Ot14XygUagnd7ty503OvR4MvN9YEAPTnhfPda27E7NUBgNtqNenbaueXWm14/XDpCADMHrZGDlHz1sBhbgu8dOmSstmsJLVsoeykuS6VSg1lTQCAO54nBAMwJqo16fRbnWseXpVOeYbTD5eOAMDsYSJsiPL5vCQ5eiukHWtra43X7ZxB1lwTCATahnZurAkAAAAM08UeLxHh0hEAmHwEYUOSz+dlmqZ8Pp+uXLky1OcOhUItwVM9kDtJLpdrvH7S5JYbawIAAADD9GJIeuw79mq5dAQApgNBWJ+KxaL8fr88Ho+i0WjH7YGmaWp1dVWSdPv27aEdlN9sa2ur8frGxsaJdZZlNbY8RiIRJRKJoa4JALNgznO49afTy9yQtgUBwCzj0hEAmD0EYX3K5XKNWxCLxaLC4XDLdsG6+vvm5+dVKpUUCo3m10iBQKAxlWUYhjKZTNu6lZUVSYe3OjZPcQ1rTQCYBR6PdGqu84uHIAwAhoJLRwBgthCE9Skejx/7s2w2K7/fr3g8rrW1NYXDYUWjUSUSCe3s7LTc9DgKsVhMhUJBPp9PqVRK8XhchmHIsqxGYGcYhkKhkO7du2drcs2NNQHASUxfAQAGxaUjADA9CML6FIlEVCqVlEgkFAgEWgIewzC0v7+vK1eu6ODgQOl02vEAqFQqqVarqVarKRaL9dR3vSfTNLWystII7+bn55XL5bSzs9NTv26sCQBOYfoKAAAAQN3pUTcwyQKBQMs5WZMkmUw6fnulG2sCAMbL+3ell8Kj7gIAAADoD0EYAACQdBhydfNy/nCKbhLPyqnVpGqtc82chwlBAACAaUYQBgAAdP+B9PpH9mpf/VC6+P3Juz2tWpNOv9W55uFV6RRBGAAAwNTijDAAAKD3DOkPf7RX+9U30g3D3X4AAAAANxCEAQAAffx5b/Wf9FgPAAAAjAOCMAAAoIOv3a0HAAAAxgFBGAAAkP9Rd+sBAACAcUAQBgAAdPGp3uqf7rEewOSq1aRvq51fal1uZAUAYFxwayQAANCLIenNX9k7MP/xR6SXQu73NM5qtcNbKDuZ80gebqDEFODGVQDANCEIw0Qrl8taWlrqWLO+vq719fUhdQQAk+nsGendZ6SX891rrz0rec8M/pzv35VeCg++zigQDAAAALS3ubmpzc3NjjXlcnlI3RxHEIaJVq1Wtbe317GmUqkMqRsAmGwvnO8ehN2IHdZ18/7d7jUv56VTc/bWAwAAwGSoVCpdf04fJYIwTLS5uTktLCx0rPF6vUPqBgCm3/M2Qqv7D6TXP7K33qsfShe/78yEGTDp2HLrvEmePJ3zHE6WdqsBgHHj9Xq1uLjYsaZcLqtarQ6po1YEYZhoCwsL2t3dHXUbAIAm7xn2zhqTpK++kW4Y0o9/4G5PwCRgy21vpn3y1OPhaw1gMtk5nmhpaWlkU2PcGgkAABz18ee91X/SYz0A9Dp5WnngajsAgAlCEAYAABx18LW79QDQz+QpAAASWyMBAIDD/I+6Ww8A/UyeDmMLNud6AcD4YyIMAAA46uJTvdU/3WM9AIzr5KnHc3gmWacXLjsAgNEiCAMAAI56MSQ99h17tY8/Ir0UcrcfANOHyVMAQL8IwgAAgKPOnpHefcZe7bVnJe8ZV9sZe7Wa9G2180utNuougfHC5CkAoF+cEQYAABz3wnnp5Xznmhuxw7pZV61Jp9/qXPPwqnSK7VSYEe/flV4Kd655MSS9+St7B+YzeQoAaEYQBgDABJvkg5mfJwQDZs77d7vXvJw/PEurU1BenzztFrhLTJ4CAFqxNRIAgAnGwcwAJsX9B9LrH9mrffVDqfKgc42diVImTwEARxGEAQAAAHDde4a9rYyS9NU30g1j8Odk8hQAcBRBGAAAAADXffx5b/Wf9FgPAIAdBGEAAAAAXHfwtbv1AADYwWH5AAAAAFznf9Td+n5N8qUjAIDeMREGAADwf7Fzox2A/lx8qrf6p3us7xeXjgDAbCEIAwAAM8FOyPVynjAMcMuLIemx79irffwR6aWQu/0AAGYTQRgAAJh69x9Ir39kr/bVD6XKA1fbAWbS2TPSu8/Yq732rOQ942o7AIAZRRAGAACm3nuG9Ic/2qv96hvphuFuP8CseuF895obMXt1AAD0gyAMAABMvY8/763+kx7rATjneUIwAICLCMIAAMDUO/ja3XoAAABMhtOjbgAAAKCTOY/08Gr3mk78j/b2nL3WAwAAYDIwEQYAAMaaxyOdmuv84ukShF18qrfnfLrHegAAAEwGJsIw0crlspaWljrWrK+va319fUgdAQDG0Ysh6c1f2Tsw//FHpJdC7vcEAAAwjTY3N7W5udmxplwuD6mb4wjCMNGq1ar29vY61lQqlSF1AwAYV2fPSO8+I72c71577VnJe8b1lgAAAKZSpVLp+nP6KBGEYaLNzc1pYWGhY43X6x1SNwCAcfbC+e5B2I3YYZ0T3r8rvRR2Zi2gV7WaVK11rpnzdN9WDABAr7xerxYXFzvWlMtlVavVIXXUiiAME21hYUG7u7ujbgMAMCWetxmCvX+3e83L+cPzy5wK1oBeVGvS6bc61zy8Kp0iCAMAOMzO8URLS0sjmxrjsHwAAIAe3H8gvf6RvdpXP5QqD1xtBwAAAD0gCAMAAOjBe4a9Q/cl6atvpBuGu/0A48DOlCQAAOOAIAwAAKAHH3/eW/0nPdYD48buVmDCMADAJCAIAwAA6MHB1+7WA+OErcAAgGlDEAYAANAD/6Pu1mPy1GrSt9XOL7UuNziOK7YCAwCmDbdGAgAA9ODiU9Knv7Ff//RT7vWC8TDNNzT2sxX4xz9wpxcAAJxAEAYAACRJc57DH9a71Qx7rXHzYkh681f2pmQef0R6KeR+T4Bb2AoMAJg2bI0EAACSJI9HOjXX+cVjM7xycq1xc/aM9O4z9mqvPSt5zwz+nBxCjlFhKzAAYNoQhAEAAPTohfPda27E7NVxIx/G2cUet/ayFRgAMO4IwgAAAFzwvI0QjBv5MO5eDEmPfcdeLVuBAQCTgCAMAABgRLiRD70a9mTgKLYCAwDgJoIwAACAEennRj5Mr3HdJuvkVmAAAEaNIAwAAGBEuJEPdZO+TdbOVmAAAMbB6VE3AAAAMKu4kQ91/WyT/fEP3O1p3M15pIdXu9cAANCMiTAAAIAR4UY+1LFNtncej3RqrvOLhyAMAHAEE2EAAAAj8mJIevNX9iaBuJFvus3KNlmmuAAAo8ZEGAAAwIhwIx/qRrFNdtiH7ktMcQEARo8gDAAAYIS4kQ+S89tkx/UGSgAARo2tkQAAYCZM8pYsbuSbfk5uk+31BsqL32faEAAwO5gIAwAAM4EtWRhnTm6T7ecGSgAAZgVBGAAAADAGnNomyw2UAACcjK2RmGjlcllLS0sda9bX17W+vj6kjgAAANxjZ5vsrNxACQAYT5ubm9rc3OxYUy6Xh9TNcQRhmGjValV7e3sdayqVypC6AQAAk6JWk6q1zjVznsncLjuKGygBAKirVCpdf04fJYIwTLS5uTktLCx0rPF6vUPqBgAATIpqTTr9Vueah1elUxMYhF18Svr0N/bru91ACQBAL7xerxYXFzvWlMtlVavVIXXUiiAME21hYUG7u7ujbgMAAGBsOHkDJQAAvbJzPNHS0tLIpsY4LB8AAACYIk7eQAkAwLQhCAMAAACmjFM3UAIAMG0IwgAAAIAZZOcGSgAApg1BGAAAAAAAAGYCQRgAAMCUqNWkb6udX2q1UXc5Od6/O+oOAACA07g1EgAAoEdzHunh1e41w1atSaff6lzz8Kp0agS9jRs7IdfLeenUHOdoAQAwTZgIAwAA6JHHcxiQdHrxEDaNrfsPpNc/slf76odS5YGr7QAAgCEiCAMAAMBMec+Q/vBHe7VffSPdMNztBwAADA9BGAAAAGbKx5/3Vv9Jj/UAAGB8EYQBAABgphx87W49AAAYXxyWDwAAMELjevD+NPM/6m59O+/flV4KD74OAAAYDBNhAAAAIzSuB+/XatK31c4vtdrw+3LCxad6q3+6S73dGyjt1AEAAHcxEQYAADBD7E4mVWvS6bc61zy8Kp2awGm1F0PSm7+yd2D+449IL4VOfn+vN1Be/L7kPWOvHgAAOI+JMAAAgCnBZJI9Z89I7z5jr/bas52DK26gBABgshCEAQAATIFeJ5MqD1xtp8HJLZZOrvXC+e41N2Ld67iBEgCAycLWSAAAgCnQz2TSj3/gbk+Ss1ssh71d83kbYRk3UAIAMFmYCAMAAJgCTCaNxihuoAQAAP0jCAMAAJgCTCaNhtM3UAIAAHexNRIAAGAKMJk0Gk7eQDnnOdza2cncCG7pHNe+AADoB0EYAADAFLj4lPTpb+zXM5nkjPoNlC/nu9d2u4HS43HufDMnwysn+wIAYNTYGgkAADAFXgxJj33HXm23yST0xqkbKJ3k8Uin5jq/eAi3AAAziIkwTLRyuaylpaWONevr61pfXx9SRwAAjIaTk0l2vX9Xeik8+DqzwM4NlAAATIPNzU1tbm52rCmXy0Pq5jiCMEy0arWqvb29jjWVSmVI3QAAMFovnO8ehNmdTHr/bveal/OHk0XDnHRyCudeAQDgjkql0vXn9FEiCMNEm5ub08LCQscar9c7pG4AABh/diaT7j+QXv/I3nqvfihd/L4zE2bDxLlXAAC4w+v1anFxsWNNuVxWtVodUketCMIw0RYWFrS7uzvqNgAAmCrvGfZuQZSkr76RbhjSj3/gbk8AAGAy2DmeaGlpaWRTYxyWDwAAgBYff95b/Sc91gMAAIwKQRgAAABaHHztbj0AAMCoEIQBAACghf9Rd+sBAABGhSAMAAAALS4+1Vv90z3WAwAAjApBGAAAAFq8GJIe+4692scfkV4KudsPAACAU7g1EgAAYErMeaSHV7vXdHP2jPTuM9LL+e61156VvGdstQcAADByTIQBAABMCY9HOjXX+cVjIwiTpBfOd6+5EbNXBwAAMC4IwkbANE1Fo1HbtWtrawoGg/J4PPL7/QqHw1pbW5Npmn33kMlkFI1G5ff75fF4FAwGFY/HVSwWx2pNAAAwvp4nBAMAABOGIMxBlmXJ4/F0fQkGgwoEAl3Xy2QyCgaDymazjdDLsiwZhqFsNqtgMKhMJtNTj8ViUX6/X6lUSpKUy+VUKpWUTqdlGIai0aii0agsyxrpmgAAAAAAAE7jjDAHZbNZ27X10Ogk0WhUxWJRPp9PkUhEgUBApmnKMIyWSbBUKqVAIKBYLNb1OYvFYmMSLZFIaGtrq/G++hrhcFjFYlHhcFg7Ozvy+XxDXxMAAAAAAMANTIQ5aGNjw1ZdPdg6SSqVUrFYVDqd1sHBgXK5nNLpdMukVbN4PN71OS3LatQFAoGWwKpZLpeTdLgls9u6bqwJAAAAAADgFibCHJLNZmVZlpLJZNfzv5aXl098n2maymQyKhQKikQibWuSyaRKpVLLBJphGAqFTr67PB6PN7YmdppGq09x5fN5FYtFZbNZJRKJoa0JAAAAAADgFk+tVquNuolpEAwGJUmlUmmgdeLxuC5cuKBkMtmxzrIs+f3+xtvpdPrEx5im2ehPkg4ODjpuT8zn843JLZ/Pp4ODg6Gs2YulpSXt7e1pcXFRu7u7A60FAACO+7YqnX6rc83Dq4c3UQ5jHafXctK49gUAwLga5c/0/N+xA/L5vEzT7Hrulx31qbJufD5fy/bKTiFU81bKSCTS9Yyu5vPGLMtSPp8fypoAAAAAAABuIghzwMbGhnw+ny5dujTwWoVCwXbt/v5+4/VO2y2bt1B22j7ZrDlku3nz5lDWBAAAAAAAcBNB2IAMw5BhGI2tisFgUGtra65PPFmW1TifKxKJnBhGGYbR8vaFCxdsrd+83tGPxY01AQAAAAAA3EYQNqCj2yFN01Q2m1U8HpfH41E8Hj8WHDnh1q1bkg6nrOq3MrZTLBZb3u50W2WnuuaPwY01AQAAAAAA3MatkQMwTfNYKHRUPp9XPp9XIpHQ1taWI89rWZbW1tYUCoWUy+U6ns91586dlre7neVV98QTT7S8vb293ZjocmNNAAAwXuY8hwe8d6sBAACYJARhAwgEAtra2pJlWSqVSioWizJNs21tNpvV9va2dnZ2BnpO0zQVjUbl8/l0+/btriHU0X76nd5qvg3TjTUBAMB48XikUwRdAABgyrA1ckCJRELJZFJbW1sqlUo6ODhQOp1uG1AZhqFoNNr3c+XzeQWDQZmm2TiTLJPJdHzMScFcr+rnkbm1JgAAAAAAgNsIwhzm8/mUTCZ1cHDQdttisVjsGl41syxLmUxGwWBQ8Xj82PtTqVTbP29+fD+O9t18Q6UbawIAAAAAALiNrZEuisViikQiWllZaTkYfmNjQ8lk0tYaxWJRpVJJkUjkxDPJ8vm8MpmM7TX74cb0lhNrlstlLS0tDbzO+vq61tfXB14HAAAAAIBptbm5qc3NzYHXKZfLDnTTH4Iwl/l8Pu3s7CgcDjfCMMuyVCwWFYlEuj4+FospFou1/Fk2m1UqlWoJklKplBKJxLGpK5/P50jg1LyuG2v2q1qtam9vb+B1KpXKwGsAAAAAADDNKpWKIz+DjxJB2JBcv35d4XC48XahULAVhLWTSCQUiUQUDodbAqlsNntsKmx+ft6R0Gp+ft7VNfs1NzenhYWFgdfxer0DrwEAAAAAwDTzer1aXFwceJ1yuaxqtepAR70jCBuSUCikSCTS2No46IHzgUBAt2/fbgnX7ty5c6yu36mro0HX0Ykwp9fs18LCgnZ3dwdeBwAAAAAAdObUsUJLS0sjmyzjsPwhGuTGyHZCoVDLtsl24dry8nLL23YnuY4eZB8MBl1dEwAAAAAAwG1MhA1RIBBovO7EtkBJunz5svL5vKT2gVTzxJh0GJaFQqGu65ZKpZa3m7dxurEmAADApJrzSA+vdq8BAACjx0TYEDUHYU5sC5TUEkC1W/Po9JbdLZnNoZrP52vp3Y01AQAAJpXHI52a6/ziIQgDAGAsEIQN0fb2duN1p7dJSscDKukwKGsOyNqdI9ZOc69H13VjTQAAAAAAALcRhA1R89ZAp7YFNk9jnRSuXbp0qfG6YRi21m2uS6VSQ1kTAAAAAADATQRhQ1Q/yyuZTDq2Zj1c8vl8LQfnN1tbW2u8Xr+1spPmmkAg0Da0c2NNAAAAAAAANxGEDUk+n5dpmvL5fLpy5Ypj625sbEiSrl+/fmJNKBRqCZ7qgdxJcrlc4/WTJrfcWBMAAAAAAMBNBGF9KhaL8vv98ng8ikajHbcHmqap1dVVSdLt27c7HpSfyWQUDoeVSqXa3gLZrF6TTCZPnAar29raarxeD8/asSxL2WxW0uH2zUQiMdQ1AQAAAAAA3EIQ1qdcLtcIqorFosLhcMt2wbr6++bn51UqlVpueTzKsiylUikZhqFMJiO/33/i9FQ8Hlcmk1E6nVY6ne7abyAQaExl1ddvZ2VlRdLhVsvmKa5hrQkAAAAAAOAWgrA+xePxY3+WzWbl9/sVj8e1tramcDisaDSqRCKhnZ0dBQKBjmv6fL5jNfVALB6PK5VKKRqNyu/3Szo8fL+X88ZisZgKhYJ8Pp9SqZTi8bgMw5BlWY3AzjAMhUIh3bt3r+PkmptrAgAAAAAAuIEgrE+RSESlUkmJREKBQKAl4DEMQ/v7+7py5YoODg6UTqdtB0A7OztKJpMKhULH1jRNU/F4XPfu3VMul+sarJ3Ud70n0zS1srLSCNrm5+eVy+W0s7PTU2DlxpoAAAAAAABO89RqtdqomwB6tbS0pL29PS0uLmp3d3fU7QAAgBN8W5VOv9W55uFV6ZSNX886uRYAABidUf5Mz7cJAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCadH3QAwiHK5rKWlpY416+vrWl9fH1JHAAAAAADMrs3NTW1ubnasKZfLQ+rmOIIwTLRqtaq9vb2ONZVKZUjdAAAAAAAw2yqVStef00eJIAwTbW5uTgsLCx1rvF7vkLoBAAAAAGC2eb1eLS4udqwpl8uqVqtD6qgVQRgm2sLCgnZ3d0fdBgAAAAAAkL3jiZaWlkY2NcZh+QAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAmnR90AMIhyuaylpaWONevr61pfXx9SRwAAAAAAzK7NzU1tbm52rCmXy0Pq5jiCMEy0arWqvb29jjWVSmVI3QAAAAAAMNsqlUrXn9NHiSAME21ubk4LCwsda7xe75C6AQAAAABgtnm9Xi0uLnasKZfLqlarQ+qoFUEYJtrCwoJ2d3dH3QYAAAAAAJC944mWlpZGNjXGYfkAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJp0fdADCIcrmspaWljjXr6+taX18fUkcAAAAAAMyuzc1NbW5udqwpl8tD6uY4gjBMtGq1qr29vY41lUplSN0AAAAAADDbKpVK15/TR4kgDBNtbm5OCwsLHWu8Xu+QugEAAAAAYLZ5vV4tLi52rCmXy6pWq0PqqBVBGCbawsKCdnd3R90GAAAAAACQveOJlpaWRjY1xmH5AAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJp0fdADCIcrmspaWljjXr6+taX18fUkcAAAAAAMyuzc1NbW5udqwpl8tD6uY4gjBMtGq1qr29vY41lUplSN0AAAAAADDbKpVK15/TR4kgDBNtbm5OCwsLHWu8Xu+QugEAAAAAYLZ5vV4tLi52rCmXy6pWq0PqqBVBGCbawsKCdnd3R90GAAAAAACQveOJlpaWRjY1xmH5AAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEjYJqmotGorVrDMLS2tqZgMCiPxyOPx6NgMKhUKiXLsvruIZPJKBqNyu/3N9aMx+MqFotjtSYAAAAAAIBTCMIcZFlWI6zq9BIMBhUIBLquFY/HFQ6Hlc1mZZpm432maSqTycjv9yubzfbUY7FYlN/vVyqVkiTlcjmVSiWl02kZhqFoNKpoNNpTyObGmgAAAAAAAE47PeoGpkkvoVQ9NGrHsiyFw+GW8Oska2tr2tnZ0dbWVtfaYrHYmERLJBItjwkEAorFYgqHwyoWiwqHw9rZ2ZHP5xv6mgAAAAAAAG5gIsxBGxsbtuoikUjHibB4PC7TNBUKhRrTVaVSSblcTslk8lh9NptVPp/v+Jz1CTPpMKA6KTjL5XKSDqfO6vXDXBMAAAAAAMAtTIQ5JJvNyrIsJZPJrud/LS8vd1ynWCwqmUwqnU63vK8+YbW2tqZ4PC7DMBrvW11dVSwWO3HdeDze2JrYaRqt/hz5fF7FYlHZbFaJRGJoawIAAAAAALjFU6vVaqNuYhoEg0FJUqlUGnidQCCgQqHQsc40zcZz1hUKBUUika61BwcHHbcn5vP5xuSWz+fTwcHBUNbsxdLSkvb29rS4uKjd3d2B1gIAAO75tiqdfqtzzcOr0ikb+xScXAsAAIzOKH+m59sEB+TzeZmm2XEqyg7DMGSaZmMrYSeBQODYxFjzhFiz5rpIJNL1jK7myTLLstpuu3RjTQAAAAAAADcRhDlgY2NDPp9Ply5dGmidmzdvKpFI2D5M/uj015dfftm2rvkQ/1AoZGvt5jPMbt68OZQ1AQAAAAAA3EQQNiDDMGQYhizLkt/vVzAY1NraWl8TT5cvXz425dXJ0QDq6FbJen/NLly40PPaRz8WN9YEAAAAAABwG0HYgI5uhzRNU9lsVvF4XB6P59ih9p2EQiHb02CSGgfV17W7ibJYLHataedoXfPH4MaaAAAAAAAAbiMIG4BpmsdCoaPy+bzC4bDW1tZcef5m7Q7Kv3PnTsvbdoO2J554ouXt7e1tV9cEAAAAAABw2+lRNzDJAoGAtra2ZFmWSqWSisXisXCqLpvNant7Wzs7O449f3OQlEgk2tYc7aff6a3m2zDdWBMAAAAAAMBtBGEDOhpAWZalbDarjY2NY1sXDcNQNBpVoVBw5Lm3trYar590Y+VJwVyvmj8WN9YEAAAAAABwG0GYw3w+n5LJpJLJpPL5vFZXV1sCn2KxqEwmo2QyOdDzmKbZOGMrnU6fOJXVb9h0dLvj/v6+q2v2q1wua2lpaeB11tfXtb6+PvA6AAAAAABMq83NTW1ubg68TrlcdqCb/hCEuSgWiykSiWhlZaXlYPiNjY2Bg7D67ZKBQGDgtexwY3rLiTWr1ar29vYGXqdSqQy8BgD8n+3dP29b3b4f+J98ngT3IOdqKJ1KsCqqmTaUzysw2U2QKUg/RTBJZap3IcG49R1DKlwGIz5dgin8iF3Skc8rsMRppyFPY0OdtKN7Lm6Q3CNOYZBDUv8oidx7U/vzAQST8uLavy1jcYtfr7U2AAC8ZFdXVwv5DJ4lQdiSlUqlODs7i93d3XEYliRJdLvdWze3n0ev14tWqxWlUunBZZalUmkhgdPkbK5l9PlUr169iq2trWf3s76+/uw+AAAA4CVbX1+P169fP7uf8/PzuL6+XkBFjycIS8kvv/wSu7u74+edTufJQdj79+8jIuK33357cKP6zc3NhYRWm5ubS+3zqba2tuLbt2/P7gcAAAC436K2Fdre3s5sZtmrTI5aQJVKZSr4euqG83t7e9Hr9eLk5CQqlcqD7Z8662o26JqdEbboPgEAAACWTRCWolqt9qzXt1qtaLVacXx8HPV6fa7XvHnzZur5vDO5Zjey39nZWWqfAAAAAMsmCEvR5DLGxy4L7Ha7sbe3F8fHx9FsNud+3eRyzIj5Z6L1+/2p55Oz2ZbRJwAAAMCyCcJSNBmEPWZZYK/Xi1qtFoeHh48KwSJuzt6aN7SanOVVKpWmal9GnwAAAADLJghL0enp6fjxvMskB4NBvH37Nvb392N/f//Rx6xUKlOh29evX+d63WSts8HXMvoEAAAAWDZBWIomlwbOsyxwMBjE7u5uNJvNODw8nOsYg8Egjo6Opr737t278eNerzdXP5PtDg4Obvz9MvoEAAAAWCZBWIra7XZExFwzu5IkiVqtFu/evZs7BIuIaDQaN0K2vb298eNut/tgH5NtyuXyraHdMvoEAAAAWCZBWEra7XYMBoMolUrx8ePHe9smSRK7u7tRLpfj4OAgBoPBg1/dbne8iX2lUpnqr1KpTAVPo0DuLicnJ+PHd83cWkafAAAAAMu0NhwOh1kXsYq63W40Go1IkiSq1WocHh7eCKBGRksckySJs7OzO9uN7O7uzr3ccNZdd5UcDAaxs7MTET9CrLOzs1tfnyRJbGxsRMSP5ZudTufOYy2jz3ltb2/H9+/f4/Xr1/Ht27dn9wcALMdfryN++rv72/zz30f8bo7/nl1kXwBAdrL8TO/XhCc6OTkZ3wVxNBtrcrngyOjvNjc3o9/vLzUEi4g77ypZLpfHs7J6vd6NfcRG3r59GxE/7uo4OYsrrT4BAAAAlkUQ9kSNRuPG91qtVmxsbESj0Yi9vb3Y3d2NWq0WzWYzzs7OolwuP9jnMkKwkXq9Hp1OJ0qlUhwcHIyPlyTJOLDr9XpRqVTiz3/+89SdIdPsEwAAAGAZLI18hsFgEIeHh9HtduPi4iKSJIlSqRSbm5tRqVTi559/jmq1msvw5+joKL58+RKDwWBc95s3b2Jvby/q9Xpu+ryLpZEAsBosjQQAZmX5mV4QxkoShAHAahCEAQCz7BEGAAAAAEsmCAMAAACgEARhAAAAABSCIAwAAACAQhCEAQAAAFAIgjAAAAAACkEQBgAAAEAhCMIAAAAAKISfsi4AnuP8/Dy2t7fvbfPhw4f48OFDShUBAABAcX3+/Dk+f/58b5vz8/OUqrlJEMZKu76+ju/fv9/b5urqKqVqAAAAoNiurq4e/JyeJUEYK+3Vq1extbV1b5v19fWUqgEAAIBiW19fj9evX9/b5vz8PK6vr1OqaJogjJW2tbUV3759y7oMAAAAIObbnmh7ezuzWWM2ywcAAACgEARhAAAAABSCIAwAAACAQhCEAQAAAFAIgjAAAAAACkEQBgAAAEAhCMIAAAAAKARBGAAAAACFIAgDAAAAoBAEYQAAAAAUgiAMAAAAgEIQhAEAAABQCIIwAAAAAApBEAYAAABAIQjCAAAAACgEQRgAAAAAhSAIAwAAAKAQBGEAAAAAFIIgDAAAAIBCEIQBAAAAUAiCMAAAAAAK4aesC4DnOD8/j+3t7XvbfPjwIT58+JBSRQAAAFBcnz9/js+fP9/b5vz8PKVqbhKEsdKur6/j+/fv97a5urpKqRoAAAAotqurqwc/p2dJEMZKe/XqVWxtbd3bZn19PaVqAAAAoNjW19fj9evX97Y5Pz+P6+vrlCqaJghjpW1tbcW3b9+yLgMAAACI+bYn2t7ezmzWmM3yAQAAACgEQRgAAAAAhSAIAwAAAKAQBGEAAAAAFIIgDAAAAIBCEIQBAAAAUAiCMAAAAAAKQRAGAAAAQCEIwgAAAAAoBEEYAAAAAIUgCAMAAACgEARhAAAAABSCIAwAAACAQhCEAQAAAFAIgjAAAAAACkEQBgAAAEAhCMIAAAAAKARBGAAAAACFIAgDAAAAoBAEYQAAAAAUgiAMAAAAgEL4KesC4DnOz89je3v73jYfPnyIDx8+pFQRAAAAFNfnz5/j8+fP97Y5Pz9PqZqbBGGstOvr6/j+/fu9ba6urlKqBgAAAIrt6urqwc/pWRKEsdJevXoVW1tb97ZZX19PqRoAAAAotvX19Xj9+vW9bc7Pz+P6+jqliqYJwlhpW1tb8e3bt6zLAAAAAGK+7Ym2t7czmzVms3wAAAAACkEQBgAAAEAhCMIAAAAAKARBGAAAAACFIAgDAAAAoBAEYQAAAAAUgiAMAAAAgEIQhAEAAABQCIIwAAAAAApBEAYAAABAIQjCAAAAACgEQRgAAAAAhSAIAwAAAKAQBGEAAAAAFIIgDAAAAIBCEIQBAAAAUAiCMAAAAAAKQRAGAAAAQCEIwgAAAAAoBEEYAAAAAIUgCAMAAACgEH7KugB4jvPz89je3r63zYcPH+LDhw8pVQQAAADF9fnz5/j8+fO9bc7Pz1Oq5iZBGCvt+vo6vn//fm+bq6urlKoBAACAYru6unrwc3qWBGGstFevXsXW1ta9bdbX11OqBgAAAIptfX09Xr9+fW+b8/PzuL6+TqmiaYIwVtrW1lZ8+/Yt6zIAAACAmG97ou3t7cxmjdksHwAAAIBCEIQBAAAAUAiCMAAAMvV//z9ZVwAAFIU9wiBFnz9/jqurq1hfX39wzTSQHmMTlmeekOs/tCN+9yri3/3r//97xiXkj3EJ+WNcPt7acDgcZl0EPNZoY73Xr1+v1Gb5q1o3vHTGJizHf/vvEa//z4h//J8Pt/3Dv4z4/jFi/W9+PL9tXP71OuKnv7u/n3/++x+hGrB4rpeQP6s6LrOs268JAAAsxX/uzReCRUT85X9E/KfecusBABCEAQCwFP/l/31c+//6yPYAAI8lCAMAYCku/2m57QEAHksQloHBYBC1Wu1Zr22328+q4ejoKGq1WmxsbMTa2lrs7OxEo9GIbrebqz4BgNW18fvltgcAeCxB2AIlSRJra2sPfu3s7ES5XH50341GI3Z2dqLb7cbFxcWTaux2u7GxsREHBwcREXFychL9fj8ODw+j1+tFrVaLWq0WSZJk2icAsPr+zf/6uPb/2yPbAwA8liBsgVqt1txtR6HRQ5IkiYODg9jY2Hj2LLButzsOpJrNZnQ6nahWq1Eul6Ner0e/349KpRLdbjd2d3fnCq6W0ScA8DL8H5WIf/Uv5mv7h38Z8e8ry60HAEAQtkCfPn2aq90oKHrI0dFR7O7uRq/3/FsojWaURUSUy+U4Pj6+td3JyUlE/FiCOWqfZp8AwMvxv/xNxH/8t/O1/b/+94j1v1lqOQAA8VPWBbwUrVYrkiSJ/f39B/f/evPmzYP99Xq9qFarsb+/P+5/b2/vyfU1Go3xbKz7ZqONZnK12+3odrvRarWi2Wym1ue8/vKXv0z9yXJ9/vw5rq6uYn19PT58+JB1OXNb1bojVrf2Va17Va3qz1vd6cq67n/3ryP+wwOT2v9T/Ue7lyDrn/dTqTtdq1r3qlrVn7e607Wqda+qLD/Trw2Hw2HqR32BdnZ2IiKi3+8vpf9erxe7u7vj58fHx3OHSYPBYFxfRMTl5WWUSqU727fb7fHMrVKpFJeXl6n0+Ri/+93v4vr6Ol69ehV//etfn9VXmra3t+P79+/x+vXr+PbtW9blzE3d6VvV2tWdLnWnS91P89friJ/+7v42//z3Eb+bWadwW91P7StNWf+8n0rd6VJ3utSdLnWna1XrzvIzvaWRC9But2MwGMy979dT3BcyPeTw8HD8uFqtPthXvV4fP06S5Na9yZbRJwAAAMAyCcIW4NOnT1EqleLdu3dZl3KryU38K5X5dqGd3MPsy5cvqfQJAAAAsEyCsGfq9XrR6/UiSZLY2NiInZ2d2Nvby82Mp9mN9v/0pz/N9brJcGv2XJbRJwAAAMCyCcKeaXY55GAwiFarFY1GI9bW1qLRaCzkro9P1e12p57Pc7fK29pNnsMy+gQAAABYNkHYMwwGgxuh0Kx2ux27u7vPuuPjc3z9+nXq+bx7jf3xj3+cen56errUPgEAAACW7aesC1hl5XI5jo+PI0mS6Pf70e12YzAY3Nq21WrF6elpnJ2dpVrjbD1Pnb01eTfMZfQJAAAAsGyCsGdqNptTz5MkiVarFZ8+fYokSab+rtfrRa1Wi06nk1p9dwVzjzV5LsvoEwAAAGDZ1obD4TDrIl6qdrsd79+/vxH4HB4exv7+/qP6GgwGsbOzM35+fHx8I4S7zdra2tTzef+5u91u1Gq18fN6vR4nJydL6/OxJmt49er5K3z/9m//Nv7whz88u5+HnJ+fx/X1dbx69Sq2traWfrxFUXf6VrV2dadL3elS99N9v7r/71+v3/zeXXU/pa805eHn/RTqTpe606XudKk7XWnX/Ze//CX+4R/+4dn9XF9fjx+nHUsJwpYsSZJ4+/bt1MbwpVIpLi8vH9VP1kFYtVodz2RbRp+P9erVq9QHCwAAALA4a2trU6FYGiyNXLJSqRRnZ2exu7s7DsOSJIlutxvVajWV4y9iCeLkhvjL6POxfv/738c//dM/xXA4XKkZYQAAALCqFjkjbG1tLX7/+98voKrHEYSl5Jdffond3d3x806nk0oQtrm5uZDQanNzc6l9PtY//uM/Pvv4AAAAQLE8fyoNc6lUKlPB16I2nH/IU2ddzQZdszPCFt0nAAAAwLIJwlI0uT9WWt68eTP1fN6ZXBcXF1PPJ/cnW0afAAAAAMsmCEtRuVweP37OssDHmFyOGTH/TLR+vz/1fHI22zL6BAAAAFg2QViKJoOwtJYFzs7emje0mpzlVSqVpmpfRp8AAAAAyyYIS9Hp6en4cVrLJCuVylTo9vXr17leN1nrbPC1jD4BAAAAlk0QlqLJpYFpLgt89+7d+HGv15vrNZPtDg4OUukTAAAAYJkEYSlqt9sREbG/v5/qcff29saPu93ug+0n25TL5VtDu2X0CQAAALBMgrCUtNvtGAwGUSqV4uPHj49+/bx3ZrxNpVKZCp5GgdxdTk5Oxo/vmrm1jD4BAAAAlkkQ9kTdbjc2NjZibW0tarXavcsDB4NBvH//PiIifvvttydtlD+7If1jg7Hj4+Px40+fPt3ZLkmSaLVaEfFj+Waz2Uy1TwAAAIBlEYQ90cnJyTiM6na7sbu7O7VccGT0d5ubm9Hv96NSqTz6WEmS3JhF9eXLl0f1US6Xx7Oyer1eHB0d3dru7du3EfHjro6Ts7jS6hMAAABgWdaGw+Ew6yJWUbfbvfXOj6VSKarVamxubsbp6Wn0er3Y39+Pjx8/PmomWJIk8f79+0iS5N49uKrV6ni55TwhW7fbjUajEUmSRL1ej48fP0a5XI7T09M4ODiIXq8XlUrlUTPXltEnAAAAwKKZEfZE1Wo1+v1+NJvNKJfLUwFPr9eLi4uL+PjxY1xeXsbh4eGjA6DR7KlOpxPD4fDOr06nEycnJ3PPNKtWq+OaBoNBvH37NjY2NqLRaMTm5macnJzE2dnZo+pdRp8vxWAwiFqt9uAeaotydHQUtVptvGx3Z2cnGo3GXDc0gJcs72Nj9F4BL0GW4y3vYx2ykvex4TpI0ficmLEhsHCXl5fDer0+jIhhRAyPj4+XerxOpzMslUrDiBhWq9Vhp9MZ9vv94cnJybBcLo+/f3l5udQ6IG+yHhuXl5fj94GHvprN5lJqgLRkOd6yHuuQV1mPDddBmOZzYj4IwmCBLi8vh/v7+zcu7Mt8g+t0Og/+AlGpVIYRMSyXy4V7k6O48jA2Dg8P5/4A0O/3F358SEuW4y0PYx3yKA9jw3UQfvA5MV8EYbAgh4eHw3K5PKxWq6m9wV1eXo4T/nK5fGe7fr8/rqVarS6lFsiTvIyNUQ0PfRmXrLIsx1texjrkTV7Ghusg+JyYR/YIgwXo9XrjfeM6nU4cHx+nctzRTQoi4sadRSeVy+Wo1+sR8ePmBq1WK43yIDN5GButViuSJIn9/f3odDr3frmjLqssy/GWh7EOeZSHseE6CD4n5pW7RsIS9Hq92N3dHT8/Pj6OZrO50GMMBoPY2dkZP7+8vLz3hgTtdjsajUZE/LgZw+Xl5ULrgbzIy9gY1dDv9xfSH+RRluMtL2Md8iYvY8N1EG7yOTEfzAiDJUjjDpmHh4fjx9Vq9cFjjpL+iIgkSVK7QwmkLQ9jo91ux2AwuPd/4OAlyHK85WGsQx7lYWy4DsLtfE7MB0EYrKjJaauVSmWu15TL5fHjL1++LLwmyIM8jI1Pnz5FqVSKd+/ePbsvyLMsx1sexjrkUR7GhusgZCcP7wF5JwiDFdTr9aae/+lPf5rrdZNvhEVI+imePIyNXq8XvV4vkiSJjY2N2NnZib29PWOOFyfL8ZaHsQ55lIex4ToI2cnDe8AqEITBCup2u1PPJxP8+8y2m32jhFWXh7ExuwxkMBhEq9WKRqMRa2tr0Wg0jD1ehCzHWx7GOuRRHsaG6yBkJw/vAatAEAYr6OvXr1PP511r/sc//nHq+enp6aJKglzIemwMBoMbv4DMarfbsbu7G3t7e086BuRFluMt67EOeZX12HAdhGxl/R6wKn7KugDg8QaDwdTzpyb97uLDS5P12CiXy3F8fBxJkkS/349ut3ujppFWqxWnp6dxdnb2pGNB1rIcb1mPdcirrMeG6yBkK+v3gFUhCIMVdNcvFI+VJMlC+oG8yMPYmL0FdpIk0Wq14tOnTzf67fV6UavVotPpPPl4kJUsx1sexjrkUR7GhusgZCcP7wGrwNJIWEFPfWOanRp7cXHx/GIgR/I4NkqlUuzv78fl5WWcnJzcOFa3242jo6OFHQ/SkuV4y+NYhzzI49hwHYT05PE9II8EYVBgLz3ph6da1tio1+vx5z//+catrD99+rSU48EqyPJa5DoIt3MdhGJ76ddHQRisoHk3PUyrH8iLVRgbpVIpzs7Opj4EJEny4ObCkDdZjrdVGOuQhVUYG66DsDyr8B6QB4IwXqRWqxVra2sL/drd3c36tMY2Nzdz1Q/MI41xuUpj45dffpl6bn8UVk2W422VxjqkaZXGhusgLN4qvQdkSRAGK+ipCf3sFNeXnvRTPKs0NiqVSlSr1fHzRW1uCmnJcryt0liHNK3S2HAdhMVbpfeALLlrJC9StVqNk5OThfaZpzeDN2/eRK/XGz9PkmSu+mY3PdzZ2Vl0aXCnNMblqo2NWq1mKQgrK8vxtmpjHdKyamPDdRAWa9XeA7IiCONFKpfLUS6Xsy5jaWaXgw0Ggxubjt6m3+9PPZ/8XzhYtjTG5aqNjcmfx0ufgs7Lk+V4W7WxDmlZtbHhOgiLtWrvAVmxNBJW0Js3b6aezzuVfHLKa6lUetFhIcW0amNj8jh5mnUK88hyvK3aWIe0rNrYcB2ExVq194CsCMJgBVUqlalfFr5+/TrX605PT8ePZ98k4SVYtbExedxarZbacWERshxvqzbWIS2rNjZcB2GxVu09ICuCMFhR7969Gz+eXAd+n8l2BwcHC68J8mCVxsbkNPSXPgWdlynL8bZKYx3StEpjw3UQFm+V3gOyIgiDFbW3tzd+PM8mo5NtyuWyXzZ4sVZpbLTb7YiI2N/fT+2YsEhZjrdVGuuQplUaG66DsHir9B6QFUEYLMHs7WefotVqxcHBwZ3rumdvOT36ReIuk3frK0LKT3Etc2w8NC4fo91ux2AwiFKpFB8/fnx2f5CFLMeb6yDcznUQ8svnxJwYAgt3cnIyjIjx1+Hh4aNeX61Wp15/eXl5a7t+vz9uU6lU7uzv8vJy3K5arT6qFlhFyxgbD43LTqczLJVK477Ozs7urW/U9r52sAqyGG/LPDa8BK6DkE8+J+aDIAwW7PLyclgul6feoO5787nN5GsjYnh8fHxn28k307veSCuVyjAihqVS6c43S3hpFj02HhqXzWbzRptms3mjn9EHhXK5POz3+08+P8iTtMfbMo8NL4XrIOSLz4n5IQiDBbi8vBzW6/UbCf3sV7VaHdbr9Qf/52v0P2Sjr06nc2/7yf+BG/V/eXk57HQ64ze3SqVSqDc3GA4XOzYeGpedTufWcV8qlYb1en3YbDbHx9zf3zceeXHSHG/LPDa8JK6DkC2fE/NJEAY51Ol0huVyeVgqlYb7+/tzv+7w8HBYqVTGb3alUmlYrVaHJycnS6wW8m8RY2Oecdnv94fNZnPcbnSscrk8rNfrw5OTk8L9okHxpDXelnVseIlcB+FlcH1cjLXhcDgMAAAAAHjh3DUSAAAAgEIQhAEAAABQCIIwAAAAAApBEAYAAABAIQjCAAAAACgEQRgAAAAAhSAIAwAAAKAQBGEAAAAAFIIgDAAAAIBCEIQBAAAAUAiCMAAAAAAK4aesCwAAAADIu16vF1++fIkkSeL4+DjrchbupZ/fiCAMAAAAWBkbGxtxdnYW5XJ56cfqdrtxcnIS3W43BoNBRERUq9WlH/cxNjY2IkmS6HQ6j65tFc5v0QRhAAAAwEo4Ojoaz1g6PDxc6rFqtVpcXFxEr9db6nGeo9vtRpIkEfH4AGsVzm8Z7BEGAAAArITRkr1Wq7X0Y3U6nTg7O4tOp7P0Yz3VyclJRETU6/VHv3YVzm8ZBGEAAABA7rXb7fHyvSRJot1up3LcPC8V/PXXXyMi4ueff35yH3k+v2UQhAEAAAC59+nTp3ufF02v13vyssgiE4QBAAAAudbr9W7sZXXb94pktEy0Wq1GqVTKtpgVIggDAAAAcu2u2V+jMKiIRssiG41GxpWsFkEYAAAAkFuT+4GNNocfSWPT/DyaXBb57t27bItZMYIwAAAAILdGs8GazWbU6/Uol8tTf1/EMOzLly8REVGpVCyLfCRBGAAAAJBbo6Dr4OBg6s+Rw8PDZx+j3W5HrVaLjY2NWFtbi93d3djb2xvfpTJvRjPk5r1b5Kqd3zIJwgAAAIBcarVakSRJVKvV8UywZrM51WYwGES3231S/4PBIHZ2dqLRaMTFxUUcHh5Gp9OJn3/+Obrdbuzs7MTR0dGD/TQajXHIdNvX7u7uOHTa29u7te3Ozs54ueNDNY/6qtfrqZxfxI8A8q7ze+hrd3d3rmOkYW04HA6zLgIAAABg1s7OTgwGg+h0OlGtVsff39vbm1oSWa/Xb+wf9pBerzcOaA4PD2N/f/9Gm9njRPy4S2On07m1z9va39b35LErlUr89ttvcy9xPDo6ioODgyiXy9Hv9+9st+jzG7Utl8uxt7d3Y4nqyNevX2+Ea7P/fln6KesCAAAAAGZ1u90YDAZRLpdvhCizAU673Y4kSeYOkwaDwTgkqtfrt4ZEET/uSnl6ehq9Xm+ufo+Pj2/MULstrDo9PY2I+0O1u4z2B7tvNtiyzq9UKt0bvkXcvMNns9nMTQgWYWkkAAAAkEOjvb9m9wSL+DGLqlKpTH3vMZvmNxqNG8d5qI553XZny8klj0mSxMHBQZRKpUfPYkuSZBxa3bc/2LLO7+PHj/f+/dHR0VSoViqV4vj4eO7+0yAIAwAAAHJlNKuqVCrd2BNsZG9vb+r57Eyku7Tb7XFYU6lU7lziN/LmzZu5+h25Lfx5//791OMkSeLk5OTRd3z89ddfx8eYDQJHlnV+FxcXdx4z4se/2Wxo+digLw2CMAAAACBXRrOU7grBRn83GSQlSTK+m+J9JgOz2TDtNo8Nq0a1TS4HbLfb0e12o9VqRbvdfvJywVGw9O7duzvbLOv8Dg8P7615chZaRP6WRI4IwgAAAIDcSJJkvMzxoaV4s4HQQ8vwBoPB1NK9h2ZLPcdsLY1GY7zJ/VOXC472HpsNnUaWeX739dVqtW4siXzsktK0CMIAAACA3BiFYPV6/cHZSrNL8UYb7N9lchP7iOUGYeVyeSoMSpJkvCTyKUaz3Uql0p0zrdI8v5HBYHBj5tlTln2mRRAGAAAA5MZoad9Ds8EifgQ9s/tW3TcT6ezs7Mbrl2l/f//efbUeY3S3yPuWG6Z9fhE3l1/W6/VcLokcEYQBAAAAudButyNJklvvCnmX2cDsvrtH3jdbbFlmZ4DdtazxIaMZYffdLTLt82u1WlOz0EqlUvzyyy+p1vBYgjAAAAAgFx4zG2zktiWUd4VhFxcXU8/TCI5m9wO77e6KD5kMm+r1+p3t0jy/JElunMcvv/yS2yWRI4IwAAAAIHO9Xi96vV6USqV7w57bzN5dct7N6JMkedRxHqvX68XR0dGN8zk6OpraXP4ho1llj/25LPP8Go3GVP/1ev3R9WVBEAYAAABk7imzwUZm96kahWqzNjc3p54ve0ZYo9EYLxe87S6S8/r1118j4v5lkRHpnV+73V65JZEjgjAAAAAgU0mSjPfAmp3dNY9yuXxjg/ZRsDbbblKn03n0sea1t7cXg8FgvFyw2WxO7Xs2GAzi6OjowX663e545tVDm9CncX5JksT79++nvrcKSyJHBGEAAABApkahVbPZfHKgMjsrbLTx/qRarTb1fDTTatG63W60Wq2oVqtTywVnN84/ODh4cNbW6DXVavXBn00a5/f+/ftHL4k8Ojq69yYGaRKEAQAAAJkahSSP3UR+0jyb5s/OqJqciTav2Q3pbzNa9jgbfJXL5Tg8PLy17V1GYdY8SymXfX7dbneqv3mXRHY6nRvLNrMiCAMAAAAy02q1IkmSqFarN5b2PdZDm+bfthH/7AynWbN7jT20Af1oE/nj4+NbZ3Dt7+9PnedoQ/27jj063rt37+49bsTyz282jJtnSWSSJNHtdp/9b7sogjAAAAAgM6MZUs+ZDTYyu9H+YDCY2tQ9Im7MYEqSJN6+fXtrADQYDG6EP7f1OdJut6Pdbke5XL53r7Pblkjetrn/ly9fIiKiUqnMvWR0Wee3t7c31cfsss+7jPYTy0sQtjYcDodZFwEAAAAUT7fbHe9rtaigZHbPrWq1emPT+Ha7fetSw2azGbVaLS4uLuLs7CxarVY0m80797dqNpvjWWeT57K/v39jCeSkJEliY2Nj6nulUil+++23qQ31d3Z2YjAYxOHhYezv799z1tMWfX6T5zZyfHx8679ZkiRxcXER/X4/2u32+N8jL/GTIAwAAADIRK1Wu3N21SL1+/0boU232x0vY7zLKAhaW1sbf69cLsfe3l7U6/Uol8vjWVWzM7qq1WqcnJzcmMl1dHQUx8fHd26SX6lUxjPGdnZ27qz/IYs6v4iI3d3dW2eszatUKsXl5eWTX79IgjAAAACgsI6OjuLLly8xGAwiSZIolUpRrVZjb29vvPn8zs5O1Ov1+Pnnn6dmbC27roODgyiXy9Hv95/VTx7PLyuCMAAAAICcGc3CemiZJY8jCAMAAADIkck9xM7Ozl78LK00uWskAAAAQI78+uuvEfFjby0h2GIJwgAAAAByZLRZ/rt37zKu5OURhAEAAADkRJIk4ztpNhqNjKt5eQRhAAAAADkxCsFGd3dksWyWDwAAAJATSZKMH5dKpczqeKkEYQAAAAAUgqWRAAAAABSCIAwAAACAQhCEAQAAAFAIgjAAAAAACkEQBgAAAEAhCMIAAAAAKARBGAAAAACFIAgDAAAAoBAEYQAAAAAUgiAMAAAAgEIQhAEAAABQCIIwAAAAAApBEAYAAABAIQjCAAAAACgEQRgAAAAAhSAIAwAAAKAQBGEAAAAAFIIgDAAAAIBCEIQBAAAAUAiCMAAAAAAKQRAGAAAAQCEIwgAAAAAoBEEYAAAAAIUgCAMAAACgEARhAAAAABSCIAwAAACAQhCEAQAAAFAIgjAAAAAACkEQBgAAAEAhCMIAAAAAKARBGAAAAACF8P8B2QSodwWV0a8AAAAASUVORK5CYII=",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMIAAAOWCAYAAAANzz7PAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACseklEQVR4nOz9X4xb933n/78OpRhy41DkuFhgQAKNOHXhXnVFjvYivWqGbBaojaQ1KS3in21gG3Ec/7K94K6HUYzvpTPmpCXwRfeXilT2C/yUGlhpmKwDp0Cqobx3C/xWM1R6Z2wzlAMMQWCBiEesDQuJxfO7mCVDzh/y8M85h3+eD4DIUPPm57xHnFF8XvP5Y1iWZQkAAAAAAACYcz6vGwAAAAAAAADcQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFcNbrBoBRfP7zn9fjx4915swZ/at/9a+8bgcAAAAAANj0v//3/9aTJ0907tw5ffLJJ65e27Asy3L1isAE+Hw+8a0LAAAAAMDsMgxDrVbL1WsyIwwzqTsEC4VCHnYynHq9rlarJZ/Pp+XlZa/bsY2+3TervdO3u+jbXfTtLvp2F327i77dRd/uom93zWrftVpNkjyZ4EIQhpnk8/k6P+wHBwdet2NbOBxWrVbT8vIyfbtgVvuWZrd3+nYXfbuLvt1F3+6ib3fRt7vo21307a5Z7fvMmTOde3q3sVk+AAAAAAAAFoKnM8Kee+45Ly/fwzAM/a//9b+8bgMAAAAAAAAO8TQI29/fl2EYnm563r6+YRie9QAAAAAAAADnLfzSSE4eBAAAAAAAWAyeb5ZvWZaSyaQikYgn1zdNU8Vi0ZNrAwAAAAAAwD2eB2HFYlHf+MY3PO0hmUzqK1/5iqc9AAAAAAAAwFmeL42Mx+Net6BLly553QIAAAAAAAAc5vmMsKWlJa9bwAz6whe+oEePHukLX/iC160shEwmo2azKb/f73UrQ5nVvqXZ7X1W+55Vs/r3Td/umtW+Z9Ws/n3Tt7tmte9ZNat/3/Ttrlnte1Z5eU9vWB7uFn/mzBk1Gg3Pv9EePXqkpaUlPXnyxNM+YF84HFatVlMoFNLBwYHX7dg2q30D846fTWD68HMJTB9+LoHpM6s/l1727enSyGk6sXGaegEAAAAAAMDkeRqE5XI5z2eDSdL58+eVy+W8bgMAAAAAAAAO8jQIe/PNN1293kcffXTq59zuBQAAAAAAAO7y/NRIN62vr3vdAgAAAAAAADyyUEHY7u6u1y0AAAAAAADAI2e9bmAUH330kUzTtF1frVZVKBSGeg0AAAAAAADmy0wEYR999JFyuZzK5bKq1epIY1iWJcMwJtwZvFav1xUOh/vWZDIZZTIZlzoCAAAAAGBx5fN55fP5vjX1et2lbo6b+iDs2rVr2traknQYZgHdWq2WarVa35pms+lSN4NlMhk1m82pOC0VwG/xswlMH34ugenDzyUwfabx57LZbA68T/eSYU1xuvSjH/1IqVRKkjqzucZp1zAMPXnyZCK9wVvhcFi1Wk0+n0/Ly8t9a5kRBgAAAACAO+zOCGu1WgqFQjo4OHCps0NTHYStrq6qUqnIMAxZlqVIJKJoNKpIJCJJevbZZweO8atf/Uqmaer27dt69OgRQdicaAdhXvzQAAAAAACA0Xl5Tz/VSyPbIZgk7ezsaG1tbeSxNjY29Nxzz02qNQAAAAAAAMwYn9cN9BMIBCQdhljjhGCSFIlEdOHChQl0BQAAAAAAgFk01UFYewnkpUuXJjJeoVCYyDgAAAAAAACYPVMdhLVngT18+HCi43mtWq0qkUhMbLxKpaJSqaStrS2Vy+WJjTtsn1tbW0okEgoGgzIMQysrK0qlUhPtCQAAAAAAYFRTHYR95zvfkWVZqlQqExnvBz/4wUTGOY1pmjIMY+BjZWWlM9tt1OtsbW0pFovJMAytra3p3r17ikajWl1ddb3PcrmsYDCobDYrSdre3tb+/r5yuZwqlYoSiYQSiYRM0xz5awYAAAAAABjXVAdh58+f1zvvvKNbt27pX/7lX8Yez+mlkcVi0XZtOzQahmmaWl9f7wmddnZ21Gg0lMvlFI/HO/uqudVnuVzuhFzpdFo7OzuKx+OKRCJKJpPa399XNBpVuVxWLBYjDAMAAAAAAJ4xLMuyvG5ikEQioTNnzuhnP/vZyGM8ePBAv//7v68nT55MsLNewWDQVtATj8e1s7Mz1NjFYlHZbLYzfqFQUDqdHqHLyfVpmqYuXLgg0zQViUS0v79/Yl21WtXKyoqtMe3y8qhVAAAAAAAwOi/v6c+6erUR7ezsaHV1Vc8995yy2ayWlpZsve7hw4cyTVP7+/u6ffu2oz0Wi0WZpqmNjY2B+2rZWb7YLZvNamtrS9LhAQI7OzsjL62cZJ+pVKoTqPWbOdaeHVYqlVQul1UsFkcO8QAAAAAAAEY1EzPCPvjgA21sbKhSqcgwjJHGsCxLhmE4NiOsPePptFlRo0qlUiqVSpKkQCCgBw8e2Fr+eJpJ9dk9y0uSGo1G375KpZJSqZSkw6+j0WiMdf1ZmRFmWVJrwE+Yz5BG/LYGAAAAAGDmMCOsj29+85udPa0Mw9Aoud2o4ZldpVJJ1Wp14nuQJRKJnhMX9/b2xgrBJtlnLpfrfGxnb7JkMtn52DRNlUqlnj+bVy1LOvtW/5rP3pbOEIQBAAAAAOC4qd4s/8aNGyoUCp3wa9TJa05Petvc3FQgENDly5cnNmaxWOwJwQqFwlgnTUqT7bN7w/1oNGrrNd3937p1a+weAAAAAAAAhjHVM8LaM5faM8Hi8bgSiYQCgcDQ+4Rdv35dH3300cR7rFQqqlQqkg43oY9EIp0+R53xVK1Wtb6+3nkejUbH3lNrkn22x2m7dOmSrddFo1FVq1VJ6iz3BAAAAAAAcMtUB2HtPcECgYB2d3d14cKFkce6evWqnn322Ql2d+joJvHValXFYrEzYyqZTOratWu2Z01J6uyl1Xbt2rWp6rN7ppok2zPVjtZVKpWh/l4AAAAAAADGMdVLI9v7Tl27dm2sEKw91sWLFyfQ1W9Vq9VjodBRpVJJsVisZ4bXoDG7Z1wFAoGx99KadJ/37t3reW5337KjQeTu7q6t1wEAAAAAAEzCVAdhsVhMkv0ZR4PcuHFjIuO0RSIRFQoF5XI5pdPpvn0Wi8XO19PP0Y3s4/G4pN+euriysiLDMBQMBhWLxbS1tSXTNF3ts728sXt8O47WTfqEzVn17n2vO8CwBv3MAQAAAACm01QvjVxfX9fdu3ePBS+jmvSMMEnH9u4yTVPFYlGbm5vHbpYrlYoSiYR2dnZOHa97E3pJWlpaUiwWO7Yvl2manX2/stmstre3+84cm2Sfk3o/FiFMsBNyvVaSzviklyf/7YkJqlQqunXrlorFouLxuLa3t71uCQAAAAAwpKmeEZZMJnXx4sWJnTD44x//eCLj9BMIBLSxsaFGo6Ht7e1jywbL5bK2trZOfG21Wj0WDt2+fVvr6+tqNBqyLEuWZWl/f/9YsJVKpYbagH6cPkcNsI5e4+HDhyONMysePZbe+Im92tffk5qPHW1nrrUD4UQioZWVFQWDwZ6Zk4lEQtls9tQlwqlU6thMSNM0OzMxh5mBCQAAAACYXoZlWZbXTfRTrVb1+7//+/rRj36kP//zPx9rrEuXLh3b38pppmlqbW3t2L5fjUbjWG25XFYikeipe/Dgwal7cBWLxZ49vQbVT6pPwzB6ntv9Fjr69cXj8b6z4/oJh8Oq1Wry+XxaXl4eaYxumUxGmUxm7HG6/ef/If2H920W/7wo/czePnLdotGo9vb2hn7dUUffUztO+/6Qhg9m23Z2djrLgQcxTVObm5unBrb9RKNRxeNxraysaGdnR6VS6djfZSqVOrZnX1symWRGGAAAAICFk8/nlc/nxx6nXq+r1WopFArp4OBgAp3ZN9VLI6XDfaWuX7+ub3zjG2MFYY8ePTrxhtZpgUBAe3t7PcsbTdNUuVw+dsN/dMlhOp3uG2ql02nt7e11llO2g4FcLudon4FAYCKzYkYJ7I5qtVqq1Wpjj9NsNsce46j3Pxyi+F+n9eU/u6zvfamqzc3NviFSPB5XNpvV6urqRP4OpcMws32oQjabPfX9jUQiymazisfjffeG297elmma2t3dVS6X63tYw8bGhq5cuaJIJGL768lmsycGYMlksjNWe7xqtapqtart7W3dvn27Z1lxt6Nfc3fQtbKyMrElwQAAAAAwKsuSWgPmovgMaYS5DrY0m82J3IN7aaqDsPZSxt/93d9VMBjUc889N9IJiqZp6vbt25Nubyg3btzoWXp10syXo5vHX7p0aeC42Wy2Z1+xra2tkYKwYfpcWlqaSBC2tLQ09hiTmhHm9/vHHuOoxqfD1X9sBBSNRrW9va319fVj+8VJzs5EikQiSqfTnZlSJ9nb27MdVgUCAcXjccXj8RP3uZMOD4c4usy3n2q1qkQicWJofPSgibZ2KBaPx1UoFLS1taVsNmv7mtJh+HjS+wEAAAAAbmpZ0tm3+td89rZ0xqEgzO/3KxQKjT1Oe0aYF6Y6CPvud7+r+/d/u9u4ZVkjLYNqv3aU5V+T0l6K1Z4Zc9LskqPhkp3AIRKJKBqN9oQMlUpF0WjUsT5HnYU0ytc3yPLysuvTKO0KPj16/WlBWPdSWKec9D0lHYZwo75n6+vrJ/Y+TAh2dGmtdPg9dPfu3aG+3zc2NpRMJhWLxXq+J/vtWTepmXcAAAAAMMsmta1Qe7sjL0z1ZvmXL1/ubBAvjbaP0TQ5ehN/1GmzcAZZXV3teT7uEq5BfR69nt3ZYUeDhlG/3lnx4vPD1b/QVX/assN+yxEn6aTrjHPtk147TLjUPsn06OuHDcG6+zm6nx6b4AMAAADA/JvqIKw9g8QwjE4gNupjGnSHASctCzwaDNi9MT8aKI17GuOgPo+ermc3eDu69NPupuiz6pWo9PnP2at95inp1a4857SQaBLLSWdNtVrV2trasT/f3t4eeeaj9Nt98eZNqVRiP7M++u1XBwAAAGD+TXUQdv78+c6Nbi6X087Ojvb29oZ+bG9v6+LFix5/Nb0B00lBx6gzu46ONW5Y4lSf3cFeIBBwbXaTV86fk77/VXu1178m+c852s5QTvoeevbZZyc6nt3v01QqdSwUbu9lNq5IJKKNjY2xx3FDpVLR+vq6VlZWZBiGgsGgVlZWFIvFOqd0lkolXb16dWDYUy6XO6+f92CoWq2qWCwqkUjIMIyBM17dtkjvBQAAADANpnqPMEm6cuWKVlZW9Oabb448xsWLF/XSSy95Pptmd3e38/FJN2NHZ7ccnUFl17gBk50+u0+OvHfvnq1DDLrHPRqmzauXL0qvnX4ApCTpZvKwDseVy+UTN9kf50CIo65du9bZe9A0zanbD8w0TV29erVzkmgkEun8vFWr1c4JmN0njQ6aTdoOF03T1Pr6+sj/1kyzarWqVCqlarU61cteF+G9AAAAgLvevS+9Ghtct6imekaYdLh8blJLG70OX7pvcE6bzdL953ZnBxy9yRtnuZhkr8/Lly93Pj4pqDhJd92wp/bNs68Tgp3qpA32x9m0/ySBQGCoTfvd1p7tJR2esrm/v6/t7W1tb29rb29P+/v7A0+gPcrrXwq4IRKJaG9vT41GY6pn/S3CewEAAIDJeff+4JrXSvbqFtXUB2EXL16c2OyPv/qrv5rIOKNq38z2uynrDojszmSwE1wNw06f3QGFncCuuyYSicz9/mAYX7lcPnHZ7bVr1yZ+rVQqJWn0/fXK5bJSqVTPssVEInHiyZ/D2Nra6vzsbGxsnBjYRSIR7ezs9Pw7OWi5cqFQUCQSUSQS0fb29lg9zoJpWw7ZbdHeCwAAAIzu0WPpjZ/Yq339Pan52NF2ZtbUB2GSdOHChYmM87d/+7cTGWcU7Q2sA4FA3xv5eDzes7Rxc3Nz4NjdIdO4oaHdPqPRaE+Y1b0s6yTdN3jMBoMdp4UC4854PEk8Hlculxt6do5pmorFYkokEj2b1JumqXK53NnTy+6syaO6f/5Pmh3XbWNjoxNeDwr04vG49vf3tb+/78jf57TxatbVoPdMWrz3AgAAAKP7YUX65Df2aj/+tXRztNuQuTcTQdikdO9RNa72BsftzZf73ehWq1VdvXpVknT37t2By7q6A4Ctra2+szu6Z82k0+ljN1JO9lkoFDof9wvsTNPszIyJx+NTvQwN0+OkmYZOziTc2NgYaslltVrVhQsXBoZc1WpVsVhs6I3QR9nbKpfLKRqNcmrkFCgWi2PPCAQAAAC6vf/hcPU/HbJ+UcxkEPbRRx/p5z//ue3Hj3/8Y33lK1+Z6IbJ29vbnfHK5bJisdiJv/1vf25pacn2b/yj0WhPyJRIJE7svb258kmvcaPP7qU8lUqls+H4UWtra5IO92Ji6Q/sqFarJ4Y50zJjxjTNzibnyWRShUJBe3t72tnZOXVJcSKRGCqgOvozbzdIu3bt2lRvDr8IqtWqrdlgAAAAwDAanzpbvyim/tRI6TD4yuVyp+4ZZIdlWTIMY2I9pVKpY7/tLxaLun37tuLxuJaWlrS7u6tKpaKNjQ1du3ZtqNkm6XRakUikc+rZhQsXdO3atc6MmHK5rM3NTZmmqXQ6fWII5kafyWRSOzs7SqVSymazunfvnq5du6ZIJKLd3V1ls1lVKhVFo1Fbs8zmjc+QPnt7cA16nfZzvrKy4nInJ2uHUjs7O8dmqcXjca2vr58YfKVSKe3t7dm6xtHTX7PZrC5fvjzwZ6h9ouQ0noC5CEzTnOo9yQAAADC7gk87W78opn5G2LVr17SysqJisaj9/X1ZljXSY9La+7q0A6vuG85KpaKHDx/q2rVrajQayuVyI92QxuNxNRoNFQoFra6uanNzU7FYTGtra7p165bS6bT29/dPDcHc7jOXy6larWptbU3BYFCpVEpLS0ud0+0W8abcMKQzvv6PCeazc+O0IGyaTtg7KQRra29gf1SlUrE9sysQCPT8zLT3I7PzywDLshby581rpmlqbW2NpakAAABwxIvPD1f/wpD1i2Kqg7Af/ehHyuVynSBrkjO6JiESiahQKGh/f1+NRkOWZanRaGh/f1/b29tKJpMTuRlNp9Pa2dnpucbe3p5yudyxWSNe9rmxsaG9vb2ea+zs7HRmqGC2ZbNZGYYx0iMWiw11rdOW9k1LuBMIBAbuVxaJRE48vGKYAy2O1lar1c4vBsZVqVQ6m/n3097jLxaL9Vy3vfyvvQfhysrKicujq9Wqstls50TNlZUVra+vn/get69z9PvnqEQi0Rmv+zHJJaHFYrHnOsFgULFY7NQl4JVK5cQ947r7O+3v2u570Waapra2tpRIJDp//+3+stmsrSCuWq1qa2vr2GEO3e/ByspKZwkwAAAAvPdKVPr85+zVPvOU9Op07CwzdQzLielSE7K6uqpKpSLDMGRZliKRiKLRaCf8efbZZweO8atf/Uqmaer27dt69OiRnjx54nTbcEE4HFatVlMoFNLBwYHX7TjipACg0Wi4Egatr687vtF3JBLR/v7+UNfvNwvLSdlsticAicfjJ874OkkwGDwWJAzzz24ikThxFlk0GtWNGzeG2jetUqmoUCjo9u3bnZ4CgYAajUZPXTv8unXrVk9IUigUlE6nj/19dOteqt2vLhKJnDpT9Oj7f9rf19bWVs8ptKf9fFQqlZ4wtt/ff6lUUiqVUiAQ0I0bNzpBfqVS6SxVP6l30zRVrVZVLpd7ejq6FLb9ftl9L44qFoud/cdyuZzi8bgCgYAqlYo2Nzc771cymTy2J6Npmtrc3Ow54bTdYyQS0dra2omHPwQCgU4NAAAAvHVzT3qtNLju7y9LL190vp9ReXlPP9V7hLVDMOnwBri96fooNjY29Nxzz02qNWDhpNPpkTcA393dHeq1p4V90zIzZZgwMh6Pq1Tq/X+q9r55drT34DtpjFgspmQyqRs3bgzsqVqt6tatW7ZnHUWjUQUCgZ73bW9vr3Ooxvb2tqLRqJaWlrS5udkJvNpBTTab1cOHD7Wzs6PV1VVJh98H7RlG1WpVm5ubJ86QO2lvw5Mkk8me0Glc5XJZqVRK0uGy/O7ZrNFoVNvb253lqVevXu0JmgKBgKLRqB4+fNgz5knv87DvRVs7WDwpmIpEIkomk53vlVKppJWVlZ7A7uHDh53DV7r/fnd3d7W2tqZ4PN6ZadwO9EzT7BzMYjf8BQAAgHNevjg4CLuZnO4QzHPWFAsGg5bP57O+/e1vT2S8lZWViYwD74VCIUuSFQqFvG7FMZKOPRqNhivXTqfTx66dy+VGHm9vb+/YeJFI5NT6XC534tdfKBRG7mEcGxsbPX0kk0nbr93e3p7I13Ha38koY3aPFQgE+tZGo9Ge6+zs7JxYF4/He+rS6fSJdd1/H6dde2dnp2es0zQaDVs/H0e//06TTCYHfr8PGsdu721234tCoWD7vY5EIp3aeDw+8OsIBAInvq9Hv3fd+vcHAAAAp/vsiWXp2/0fnz3xusvBvLynn+o9wtq/7b506dJExuu3qTyA6THtM8KGcdJyslG+jo2NDTUajVP33GufVGln7GGWuHUfUJBOp09dmnr0pMTT/r3t7r8922ganfY92P3nk9gU3+570Z75FggElE6nbdVKh7PcTlpa2/113Lhx48T39ej32u7urq1eAQAAgGk21UFYeynk0aUm446H+VGv1xUOh/s+8vm8121iSKeFA6ftKTbNTgpUfvWrX408VvsU1pOW3JXLZa2trU00XLK7DLT7PRtm6eg0nbB448YN5XI5bW9vDwybJPeC2WKx2LmWneAsnU73vAfDHNBwVPf1pum9AgAAwPTK5/MD79Pr9bpn/U31HmHf+c539L3vfe/EzXtH8YMf/EDf+MY3JjIWpkOr1VKtVutb02w2XeoGk3LarKOTZrZMu5OCCzsHffQTjUa1t7fXs3F6W6VSObZ/lRtGPcRhUr/omIRAIKCNjY0TPzep/x8aRffeXHZnkHXvTTeLPzcAAACYXc1mc+B9upemekbY+fPn9c477+jWrVv6l3/5l7HHY2nk/PH5fAqFQn0ffr/f6zYxgtM2GZ/WpXTDmNTpe+l0Wvv7+8dCqFKpNNXhhxsnn05CtVpVsVhUuVxWNBod6oTOSfcxrKPfY/PwcwMAAIDZ4Pf7B96n+3zexVFTPSNMOtwXp31q2s9+9rORx3nw4IGnv9GHM5aXl10/ahXuuHLlyok/s+Vy+dR9sqZVIBDoCSImFYS1x2qf5th9jUKhcOrMOvRXqVSUzWYVjUbHWlY4Kd3vq91Q7OiJlA8fPpyZABIAAACn8xnSZ28PrvFSJpNRJpPpWxMOhz2bNTb1QZh0uCxkdXVVzz33nLLZbM/mzf08fPhQpmlqf39ft2/fdrhLYHZUKhVtbm66vnxuGOl0umfT77ZCoTBzQdjR2TiDZhaVy2Vls1nt7e3ZGj8SiejGjRtKpVKdPyP4H836+rqKxaLS6fRUhGDSaBv0H/3/yUmGrwAAAPCOYUhnPA66Zt1MBGEffPCBpMONso/uh2OXZVkyDL5bAEm6evWq7UDZK4FAQMlksrPPUVu5XFalUvFsmdqwjoZgdmZpRSIRVSoVlctl27O6joaDbGw+vHYIJo23wfyktb8fpN+etDlodlf33muEYAAAAMBvTfUeYZL0zW9+U4lEQvfv35dhGLIsa+gHgN9qB0mJROLUmklvYD7qeKeFESfNFBuXU3so7e7u9jy3E+a3g4tRg39p8KyzeTDJ79NKpdIJwSKRyFQtI7xy5UrP83af/XSfsDprMygBAAAAJ011EHbjxg0VCoVOmDVqqEUYBhwyTbOzfG7Ym+Nf/epXE+3FTogRiURODMPK5bK2trYm1ku1WlUsFhsreDrN0RP/7P69RyIRVatV26Hf0RlgR8OTWXJ0tuJpIeUkZ711Hy7Qb1wvNp1PJpM9wZydg1+6v55r16450RYAAAAwk6Z6aWT7P/bbM8Hi8bgSiYQCgcDQ+4Rdv35dH330kYPdApPjxM22aZpaW1vrLKsadrnUpHuyO177wIyjpyC2NzMfd0P4crmsRCJxaug2ru6lncOcXNsOwra2trSysqJ0Ot23vnvsSCSijY2N4Zs9gd33qbtu0GsGff7obLZisXjs6zkpJJzkhvClUulYaHnS9Y46+nNVrVZ7/szOssaTdO8BV61W+y6brVQqnaWUuVxuqma3AQAAAF6b6iCsUqnIMAwFAgHt7u7qwoULI4919epVPfvssxPsDnDOaTNSRr3RL5fLWl9f74x7+fLloa8/zjK0cWfutE+OPbpfWCKRUC6XGyn0MU1T2WxWxWKxc/Ki3b9bu+FQsVjsfO3pdHqo0K47PFlfX9fe3t6poUaxWOyZIdc9C+0k3e+lFzOcup12/Xg83gk/s9ms9vf3lUqlZJqmdnZ2VCwWO98X7TGOhk5tR793TwqjjoZvqVRKuVxO0WhUlUpFhUJB0Wi0E1BKvw0fd3Z2dO3atRMD5vX1dW1vb+vhw4fK5XJaWVnp+X61+14kk0nlcrlOGJdKpfTgwYNjX4dpmrp69aqkw++503427L7v3T+7Xn+vAAAAABNhTbFgMGj5fD7re9/73kTGi8ViExkH3guFQpYkKxQKed2KI9LptCXp2CMej1v7+/sDX99oNKydnR1rY2PDikQix8bZ3t4+9bX7+/snXluS1Wg0Rvp6otHoieMVCoWhxtnY2DhxnGg0au3s7Ngao9FoWLlczgoEAp2/00Ff19HrBgKBgdfp/nuMx+O2eutWKBRO/FqTyaS1sbFhFQoFK51O97y/dr8/jr4fp30/NBqNY3/Pp0kmk7be252dnZ66dDp96rXb79HRRyAQ6Lzf3TXRaNTa398/9n7a7e1oXfcjl8tZlnXyz2YymewZ57Tv05O+VrvvRdv29nbnaw4EAlahULD29/et/f19q1AodL4f2v2exO57cLRulO9jAAAA4CRe3tNPdRAWj8ctn89n/ehHP5rIeJVKZSLjwHvzGoTt7e31vRmf1OOk4KfRaFiFQuHU8EGSFYlErEKhYDsQ29vbs+LxeN9eNjY2bIU3bTs7O6cGa4FAwEomk1ahULB2dnasvb09a2dnxyoUClYul+t5XSAQGBg6tJ0UDkYikVPDt+6w4mhIMszX2e5xe3vbSqfTVjwet6LRaM971P6aBwWB7e+t097faDTaCU/61UYiESuZTHa+B46GcUeDk/aYOzs7p34vRCKRE8OYRqPRM340GrU2NjZ6atp/dvR7qNFoDPx6T7pmLpfrXC8SiVgbGxs93++NRqPzdXT/nR3VHUJHo9Ge77Vh3ovTFAoFKx6P94Ri7ded9vPZ7+ex+z3Y39/vWzeoNwAAAGAQL+/pDcua3p3kS6WSLl++rK2tLf2n//SfvG4HUyQcDqtWqykUCung4MDrdsZWLBYd2aj9JNFoVHt7ez1/ZhjG0OMEAgE1Go0TP3fSMkY7dnZ2bC8fLJVK2tzc7OyFZFckEtH6+rrS6fRQy0zbe1Id/boCgYBWV1cVCARkmqZ2d3c7S++2t7fH3sMMAAAAAOaNl/f0Ux2ESVIsFpPP59O9e/fGHuvHP/6x/uIv/mICXcFr8xaEYXSmaapcLuvWrVuqVqsyTbOzr1EkEuns23Tp0iUlk8mhDwkYdL32NdvXWV1dVSqVIgADAAAAgFMQhPVRrVb1+7//+/rRj36kP//zPx9rrEuXLk0kUIP3CMIAAAAAAJhNXt7T+1y92ggikYiuX7+ub3zjG2ON8+jRo6GXUAEAAAAAAGB+nPW6gX5+/OMfS5J+93d/V8FgUM8995ySyeTQ45imqdu3b0+6PQAAAAAAAMyQqQ7Cvvvd7+r+/fud55ZlaWtra6SxLMsaaUNwAAAAAAAAzIepXhp5+fJlWZal9jZmBFkAAAAAAAAY1VQHYevr65IOA7B2IDbqAwAAAAAAAIttqpdGnj9/XtFoVPfv31cul1M0GtXS0tLQ41SrVX33u9/Vz3/+88k3CU/V63WFw+G+NZlMRplMxqWOAAAAAABYXPl8Xvl8vm9NvV53qZvjpjoIk6QrV65oZWVFb7755shjXLx4US+99NJIIRqmW6vVUq1W61vTbDZd6gYAAAAAgMXWbDYH3qd7aeqDsHg8rnv37k1krNXV1YmMg+nh8/m0vLzct8bv97vUDQAAAAAAi83v9ysUCvWtqdfrarVaLnXUy7BmYAOtBw8e6MKFC2OPc//+fV28eHECHcFr4XBYtVpNoVBIBwcHXrcDAAAAAABs8vKefqo3y2+bRAgmiRAMAAAAAABggXkahE3T5vXT1AsAAAAAAAAmz9MgLBaLTcVG5o8ePVIsFvO6DQAAAAAAADjI0yBsmrYnm6ZeAAAAAAAAMHmeBmGGYXh5+R7T1AsAAAAAAAAmjxlhAAAAAAAAWAienxr54MEDr1vQ7u6u1y0AAAAAAADAYWe9buDq1av69re/rUAgoKWlJVev/fDhQ1WrVW1sbLh6XWAUliW1Bkyi9BkSq3wBAAAAADiZ50HY3t6eUqmUpz1YlsUeYZh6LUs6+1b/ms/els7wrQwAAAAAwIk8D8LavNovjAAMAAAAAABgMXgehHm9Yb7X1wcAAAAAAIA7PA3CGo2Gl5cHAAAAAADAAvE0CDt//ryXlwcAAAAAAMAC8XxpJAAAAAAAwLyyrMPDz/rxGRJbmLuDIAwAAAAAAMAhLUs6+1b/ms/els4QhLnC53UDACbn3ftedwAAAAAAwPQiCANmhJ2Q67USYRgAAAAAAKdhaSRmWr1eVzgc7luTyWSUyWRc6sgZjx5Lb/zEXu3r70kv/qHkP+doSwAAAAAAHJPP55XP5/vW1Ot1l7o5jiAMM63VaqlWq/WtaTabLnXjnB9WpE9+Y6/2419LNyvSt77kbE8AAAAAABzVbDYH3qd7iSAMM83n82l5eblvjd/vd6kb57z/4XD1P/2QIAwAAAAA4D6/369QKNS3pl6vq9VqudRRL4IwzLTl5WUdHBx43YbjGp86Ww8AAAAA8M6796VXY153MRl2ticKh8OezRpjs3xgBgSfdrYeAAAAAOAMDj6bLgRhwAx48fnh6l8Ysh4AAAAAMHnDHnzWfOxoOxBBGDATXolKn/+cvdpnnpJejTrbDwAAAABgsFEOPoOzCMKAGXD+nPT9r9qrvf41yX/O0XYAAAAAADaMcvAZnEUQBsyIly8OrrmZtFcHAAAAAHAeB59NH4IwYI58nRAMAAAAAKYGB59Nn7kMwh49eqRvfvObXrcBAAAAAAAWGAefTZ+5DMKq1aqKxaJ++ctf6oMPPlCz2fS6JQAAAAAAsGA4+Gz6zGUQVi6XZVmWIpGIEomEgsGgvvOd73jdFgAAAAAAWCAcfDZ95i4Iu3v3rrLZrCTJsqzOI5fL9Q3DvvnNb+q5557TpUuX9J3vfIdZZAAAAAAAYGwcfDZdDMuyLK+bmKTV1VVFIhFduXJF0WhU1WpVd+7c0fe+9z0ZhqFqtarf+73f63nNc889p2q1qu6/ipWVFe3t7cnv97v9JcCGcDisWq2mUCikg4MDr9txxZOWdPat/jWfvS2dmbt4GwAAAABmF/dyx3l5Tz+XQdju7u6xPzdNU7FYTJcuXdJ//a//tfPn3/zmN1UoFGQYhjY2NrS5uSnTNJXNZmWapm7duuVm+7BpEYMwy5JaA35afYZkGO70AwAAAAAYjCDsOC/v6efur9k4JQUIBALa29vT/v5+z5+3Q7BkMqnNzc1ObaFQUKPR0EcffeR0y4AthnH4D2O/ByEYAAAAAACnm7sgLBgM6m/+5m9O/FwgEFAwGOw8v3HjRufjXC53rD6bzapcLk++SQAAAAAAALhu7oKwjY0Nvfnmm3rjjTdO3PC+0Wh0Pm7PBovH4/riF794rHZ1dfXYDDJgHljW4fTcfo/5WjQNAAAAAIB01usGJi0ej+vq1au6fv26CoWCksmkLl26JEm6deuW9vf39ZWvfEXRaFSVSkWGYWh9ff3Esc6fP69qtepm+4ArWpbNNeostQQAAACAsfiMw/urQTVwx9wFYdLhTK+HDx/qRz/6kUqlkkqlUudzu7u7+u53v9uzFDIajZ44zv3797W0tOR4vxhdvV5XOBzuW5PJZJTJZFzqCAAAAACA3zKMxZpkkM/nlc/n+9bU63WXujluLoMwSdre3laxWFSpVFK5XFYgENCNGzd08eJFbW9vK5VK6e7du8rlclpfX9c//uM/HhujWCxqZWXFg+5hV6vVUq1W61tz0hJZAAAAAABOY1mHK2n68RkcWHaSZrM58D7dS3MbhElSOp1WOp0+8XPb29udj4PBoC5duqQf/OAH+qM/+iM1m01997vfVbFY7NlTDNPH5/NpeXm5b43f73epGwAAAADAPGA7mdH5/X6FQqG+NfV6Xa1Wy6WOes11EGZXMplUtVrVxYsXZXTFue+88w4hypRbXl7WwcGB120AAAAAAADZ254oHA57NmuMIOz/2NjYUCQSUbFYVCAQ0JUrV/TSSy953RYAAAAAAAAmxOd1A5P2wQcf2Kr78Y9/fGzvqGQyqTt37uj27duEYFh47973ugMAAAAAACZr7oKwZDKpM2fO6Ctf+Yr++q//Wj//+c9PrFtbW9M3vvENffTRR672B0wDOyHXayXCMAAAAADAfJm7ICwWi8myLJXLZWWzWcViMT377LPHgrHz58/rxo0bSqVS+uUvf+lqj9VqVYlEYmLjVSoVlUolbW1tqVwu23rN1taWEomEgsGgDMPQysqKUqmU7de7NSYm79Fj6Y2f2Kt9/T2p+djRdgAAAAAAcM3cBWGlUknxeFwXL17UhQsXZFmWGo2GdnZ2OsHYmTNn9G//7b/VO++8o0ajofX19Ylc2zRNGYYx8LGysqJIJDLWdba2thSLxWQYhtbW1nTv3j1Fo1Gtrq72fW25XFYwGFQ2m5V0eHrm/v6+crmcKpWKEomEEomETNO03Y8TY8I5P6xIn/zGXu3Hv5ZuVpztBwAAAABmEStoZpNhWZbldROTdOXKFeVyOX3xi1/s/Nndu3d1+/Zt3bhxo6fWMAxZliXDMPTkyZOxr721tdUJgwbZ398fOgwzTVPZbFbFYlGSFI1GlcvlFI/Hbb2+XC53ZqKl02kVCoVjNbFYTJVKRZFIRHt7ewoEAq6PaUf7hIlQKMSpkUP6yv8j3fnnIeqfk372753rBwAAAACmzc29w+1iBvn7y9LLF53vZ954eU8/dzPCLMvqCcGkw/3ACoWCGo2G3nzzzU6A9NJLLykajeqdd96ZyLU3Nzdt1cXj8aFDsGKxqAsXLnRCsEKhoL29PdshmGmaSqVSkqRIJHJiYCUdzuaSDpdvtuvdHBPOa3zqbD0AAAAAzDK2k5lvZ71uYNIePXp06ufOnz+vXC6nBw8eKJvNamtr61hoNqpisSjTNLWxsTFw/69ByxePavcqHQZOOzs7QwdpqVSqszSx36y1SCSiZDKpUqmkcrmsYrGodDrt2phwXvBpZ+sBAAAAYJaNsp3Mt77kbE+YnLlbGvn666/rueee03/8j/9xYO2f/umf6saNG/q93/u9sa+7srIi6XDJ4ySlUimVSofzMQOBgB48eDD00sJqtdrpT5IajUbfMUqlUmfmViAQUKPRcGXMYbA0cnT/+X9I/+F9+/V/+yL/qAMAAABYHGwn4zyWRk7QxsaG3nzzTf23//bfBtbevn1b8XhczWZzrGuWSiVVq1Xb+4PZlUgkOiGYpJH318rlcp2P4/H4wDGSyWTnY9M0e3pwcky445Wo9PnP2at95inp1aiz/QAAAADANGE7mfk2d0FYJBLRO++8o2QyqTfeeKNvbSAQ0MWLF/Xtb397rGtubm4qEAjo8uXLY43TrVgsqlwud54XCoWRT5ps7ysmHW6wb0f3tW7duuXKmHDH+XPS979qr/b61yT/OUfbAQAAAICpwnYy823ugjDpcFbYX/zFX+j69ev63d/9Xf3N3/zNqbO+lpaWxgplKpWKKpWKTNNUMBjUysqK1tfXx5rxVK1Wtb6+3nkejUZH3lOrUqn0PL906ZKt13WHW0e/FifGhLvsnGpyM8npJwAAAAAWz4vPD1f/wpD18NZcBmHS4UmFV69e1cOHD7WxsaFgMKgrV67oBz/4gX7+85/r5z//ua5du9bZ5H5UR5dDVqtVFYtFpVIpGYahVCp1LDga5OjJiteuXRu5v+5ZZZJszyo7Wtf9NTgxJqbP1wnBAAAAACwgtpOZb3MbhEmHywlv374tv98vy7JUKpW0vr6uWCymWCzWOYnR7tK+o6rV6rFQ6KhSqaRYLNYzw2vQmN0BUSAQ6Nlfa1j37t3reW53j7Fnn3225/nu7q6jYwIAAAAAMA3YTma+zXUQJh1u0t5oNPTOO+/o/Pnzsiyr5xEIBHTjxo2Rxo5EIioUCsrlckqn031nRhWLRcVisYFjFgqFnufxeFzSb09dXFlZkWEYCgaDnTCv34y2arV6rGc7jtZ1n4bpxJgAAAAAAEwLtpOZX2e9bsAtGxsb2tjY0P3791WtVlWtVhWJRBSPx3X+/PmRxz26d5dpmioWi9rc3DwWUFUqFSUSCe3s7Jw6Xvcm9NLhHmaxWOzYMkLTNDv7k2WzWW1vb584c+xoaDWq7q/FiTEBAAAAAJglbCczm2Y2CPvmN7+pv/u7vxv6dRcvXtTFi859twYCgU7oViqVdPXq1Z7Ap1wua2trSxsbG8deW61Wj4VDt2/fVi6X0+XLlztLEKvVqnK5XE9olkqlTgzDRg2bji53fPjwoaNjjqperyscDo89TiaTUSaTGXscAAAAAADmVT6fVz6fH3ucer0+gW5GM7NB2O3bt7W1taUvfOELXrdyqmQyqXg8rrW1tZ4ZXZubm6cGYd0CgYAePHhwLEBqL8k8uvfY1atXFY/Hbe/ZNQwnZm9NYsxWq6VarTb2OKedKgoAAAAAAA41m82J3IN7aWaDsEajoS9+8Yu6fPmyUqmUvvzlL3vd0okCgYD29vZ6ljeapqlyudzZ/6vtaBCWTqf7hlrpdFp7e3udmWGmaWpzc1O5XK7n+pMInLr7cGLMUfl8Pi0vL489jt/vH3uMWeIzpM/eHlwDAAAAAECb3+9XKBQae5x6va5WqzWBjoY3s0GY9Nv9uNpBUDweVyKRUDKZ1Be/+EVvmzvixo0bPZvl7+zsHAvCjm4ef+nSpYHjZrPZniWSW1tbPUHY0tLSREKrpaUlR8cc1fLysg4ODsYeZ9EYhnSGoAsAAAAAMIRJbSsUDoc9m1k286dGdp8AWS6Xlc1mtbKyomeffVbf/OY39eMf/3jgGD/4wQ8c7zMajfYEXydtOH80XLIzYyoSiSgajfb8WfcyzFFnXfXrxYkxAQAAAACYFu1VNP0erKKZTTMbhL3zzjuyLEuGYWhlZUVSbyjWaDRULBaVSqV05swZXbp0SX/913+tn//858fG6neK4yQlEom+n29/HcNaXV3ted4dsh39nN2ZXEc3su/uzYkxAQAAAACYFoYhnfH1fxgEYTNpZpdGbmxsKB6PK5VK6eHDhyqVSrIsS//1v/5X3b17V6ZpyrKsTn2lUunMlAoEAp1llJJUKpVc6TkSiXQ+PmlZ4NEZUnYDpqOBUnfg1L0cUzoMyY7OIDvJ0WWa3bPZnBgTAAAAAADAaTM7I0w6XG64v7+vb3zjG0qlUrp79662t7f18OFD7e/vK5fLdcKWo7PFSqWS1tfXe05ddFp3EHbSssB+M7v6OTpWd8g26pjdIVwgEOjp3YkxAQAAAAAAnDbTQVhbLpfTvXv3dOfOHf3BH/yB/umf/kkXLlzQm2++qTt37qjVamlnZ0fpdLoTvnQHY27Z3d3tfHzSMsmjs6qOzqCyqztgikajPUHZvXv3bI3R3evR4MuJMQEAAAAAAJw2F0GYdBjO/OIXv9Cf/MmfKBqN6jvf+U7P59fW1nT9+nX94he/UKPRUKFQcH1pXnewddq1u/+8XC7bGvfoEsqjgdrly5c7H3dvpN9Pd102mz32eSfGBAAAAAAAcNLcBGFthUJB//iP/6jr1693Zocddf78eV29elV37tzRnTt3XOutvRfZxsbGqTXdAVG1WrW1T9iggK17+aedcK27JhKJuDYmZpNlSU9a/R8uTrwEAAAAAOBUcxeESYdhULVa1R/90R8pGo3qb/7mb/rWrq2tOd5TqVRStVpVIBDQtWvX+vbTvbRxc3Nz4NjdIVMulzv2+Wg02hM8DTocYHt7u/PxaTO3nBgTs6llSWff6v9oEYQBAAAAAKbAXAZh0uFm7Nvb27p165befPNN/Zt/82/0y1/+8sTaVCo19PjlclnBYFCGYSiRSPRdHlitVnX16lVJ0t27d0/cKL9bd2i0tbXVdzP6crnc+Xw6nT719MZCodD5uF+4ZpqmisWipMNQLp1On1rrxJgAAAAAAABOmdsgrC2ZTOrhw4c6f/68IpHIibPD2iHVMLa3tzvLFsvlsmKx2IknULY/t7S0pP39/VODqm7RaLQnZEokEicukTRNs3PNo685KhKJdAK2SqWira2tE+vas+PaQWI/TowJAAAAAADglLkPwqTDAGZnZ0ebm5sDZ4fZddIssmKxqGAwqFQqpfX1dcViMSUSCaXTae3t7fUseRwknU5rZ2dHgUBA1WpVFy5c0NbWliqVSid0unDhgqrVamf8QZLJZGfMbDarVCqlSqUi0zQ7gV2lUlE0GtWDBw8GzlxzakwAAAAAAAAnGJa1GNtYf/TRR6pWq7pz5462trZkGIaKxaL+8i//cuQxq9WqcrmcyuWyHj58KNM0FQgEtLS0pGg0qitXrigej48d/hSLRW1vb2t3d7dzjfaG8+vr60MFbG1bW1u6detWZ0P+QCCg1dVVra+vK5lMjtSnE2OeJhwOq1arKRQK6eDgYKJjYzhPWof7gPXz2dvSmYWI3QEAAAAAg3h5Tz8XQVg75DJNU9VqVfv7+6pWq6pWq52A6ijLsjr7e21vb+sLX/iC+41jZARh08NOEPb/TUqvxtzpBwAAAAAw3by8pz/r6tUm6NKlS53wq59+OZ9lWbpz546+/OUv6969exPuEFgM794fXPNa6XBG2MsXne8HAAAAAIDTzGwQtre3J8Mw+gZdkjrLCNuPlZUVLS0tdZ6fP3/epY6B+fPosfTGT+zVvv6e9OIfSv5zjrYEAAAAAMCpZjYI6xYMBnX58uWewIuQC3DeDyvSJ7+xV/vxr6WbFelbX3K2JwAAAAAATjPTQdhLL72karWqSqWiYrGoZDKpYDCoYDBICLYg6vW6wuFw35pMJqNMJuNSR4vl/Q+Hq//phwRhAAAAADDP8vm88vl835p6ve5SN8fNbBAWj8d1+/ZtSdKjR4+0s7Oj27dva2NjQ48ePeqcqnj58mX9yZ/8Sd+xPvjgA335y192o21MWKvVUq1W61vTbDZd6mbxND51th4AAAAAMFuazebA+3QvzWwQlkgkOh+fP39eyWRSyWRSklSpVHTr1i3dvXtXhUJBhmEoGo3q3/27f6e1tTX963/9r3vGKhQKBGEzyufzaXl5uW+N3+93qZvFE3za2XoAAAAAwGzx+/0KhUJ9a+r1ulqtlksd9TKsQbvNz7ju2WLlclmPHj1SIBBQPB7XpUuXJEnZbFZPnjzxuFMMw8ujVvFb//l/SP/hffv1f/siSyMBAAAAOMeypNaAlMNnSIbhTj84mZf39HMfhB3Vni32ox/9SNVqVcb/+e4nCJstBGHT4dFjKfRdexvmP/OUVLvGqZEAAAAAnPOkJZ19q3/NZ29LZ3zu9IOTeXlPv3BvfTQaVS6X0y9+8Qvt7u6yJBIYw/lz0ve/aq/2+tcIwQAAAAAA3lq4IKxbNBrVzs6OLl686HUrwMx62caPz82kvToAAAAAAJy00EFYWy6X87oFYK59nRAMAAAAADAFCMIkra2ted0CAAAAAAAAHDYTQdhf//Vf64MPPvC6DQAAAAAAMOPeve91B/DSTARh//N//k8lEgn9l//yX8Ya58aNGzpz5oz+4A/+QP/0T/80oe4AAAAAAMA0sBNyvVYiDFtkZ71uwC7LspROp7W/v6/vfve7I42RzWZlWZZ+8YtfKBqNan9/X1/84hcn2yiwYHzG4fHDg2oAAAAAwEmPHktv/MRe7evvSS/+ISfbL6KZmBHW7c6dO7py5cpIr71w4YIikYjS6bSuXr2qbDY74e6AxWMY0hlf/4dBEAYAAADAYT+sSJ/8xl7tx7+Wblac7QfTaWZmhLXt7u4qlUrp0qVL+uCDD/SFL3zB9mv39vZ6nj/33HOTbg8AAAAAAHjg/Q+Hq//ph9K3vuRML5heMzcjTJK2t7eVSqUUjUb1y1/+cqQxHjx4oIcPH064MwAAAAAA4IXGp87WYz7MZBAmSRsbG/q7v/s7RaNR/ff//t+Heu2jR4+USCS0urrqUHcAAAAAAMBNwaedrcd8mNkgTJLi8bju3bunq1ev2j5R8oMPPlAkEtGDBw+USqUc7hAAAAAAALjhxeeHq39hyHrMh5kOwiQpEolod3dXt27d0ne+852+td/73veUSCTUaDQUCAT0jW98w6UuAQAAAACAk16JSp//nL3aZ56SXo062w+m08wHYZIUCAR0584dPXz48NQTJa9du6Zvf/vbsixLhmEol8u53CUAAAAAAHDK+XPS979qr/b61yT/OUfbwZSaiyCs7fr161pbW9OlS5f0L//yL50/v3v3bif4MgxD0WiU2WAAAAAAAMyZly8OrrmZtFeH+TRzQdigjfHT6bQKhYK+/OUvd06UbIdglmX1PAcAAAAAAIvl64RgC+2s1w3YceHCBUmHQVY6nVa5XNbv/d7vnVofjUZ169YtvfTSS/rOd76jcrkswzBkWZai0ai+/OUvu9U6HFav1xUOh/vWZDIZZTIZlzoCAAAAAGBx5fN55fP5vjX1et2lbo6biSAsl8t1Aq2dnR3F43Fls9m+yxvbm+j/6Z/+aefPDMM4dQ8xzKZWq6Varda3ptlsutQNAAAAAACLrdlsDrxP99JMBGGSdP78eb300kt66aWXhnrdnTt3lM1m9b3vfa+zPxjmh8/n0/Lyct8av9/vUjcAAAAAACw2v9+vUCjUt6Zer6vVarnUUS/Dam+cNedKpZIuX76sGzdu6C//8i+9bgdjCofDqtVqCoVCOjg48LodAAAAAMAUsCypNSDl8BmSYbjTD07m5T39zG2WP6pkMqnd3V3dunXL61YAAAAAAIADDEM64+v/IARbbAsThEmHm+jfuXPH6zYAAAAAAADggYUKwgAAAAAAALC4CMIAAAAAAACwEAjCAAAAAAAAsBAIwgAAAAAAALAQCMIAAAAAAACwEM563QAAtFmW1LL61/gMjjsGAAAAAIyGIAzA1GhZ0tm3+td89rZ0hiAMAAAAADAClkYCAAAAAABgIRCEAQAAAAAAYCEQhAEAAAAAAGAhEIQBmCnv3ve6AwAAAADArGKzfABTw07I9VpJOuOTXr7ofD8AAAAAnMfp8XATQRiAqfDosfTGT+zVvv6e9OIfSv5zjrYEAAAAwAWcHg83sTQSwFT4YUX65Df2aj/+tXSz4mw/AAAAAID5w4wwzLR6va5wONy3JpPJKJPJuNQRRvX+h8PV//RD6VtfcqYXAAAAAMBo8vm88vl835p6ve5SN8cRhGGmtVot1Wq1vjXNZtOlbjCOxqfO1gMAAAAAnNdsNgfep3uJIAwzzefzaXl5uW+N3+93qRuMI/i0s/UAAAAAAOf5/X6FQqG+NfV6Xa1Wy6WOehGEYaYtLy/r4ODA6zYwAS8+L935Z/v1LzzvXC8AAAAApsu796VXY153ATvsbE8UDoc9mzXGZvkApsIrUenzn7NX+8xT0qtRZ/sBAAAA4I537w+uea1krw4YhCAMwFQ4f076/lft1V7/muQ/52g7AAAAAFzw6LH0xk/s1b7+ntR87Gg7WAAEYQCmxssXB9fcTNqrAwAAADD9fliRPvmNvdqPfy3drDjbD+YfQRiAmfJ1QjAAAABgbrz/4XD1Px2yHjiKIAwAAAAAAHii8amz9cBRBGEAAAAAAMATwaedrQeOOut1AwDQ5jOkz94eXAMAAABgPrz4vHTnn+3Xv/C8c71gMTAjDMDUMAzpjK//wyAIAwAAAObGK1Hp85+zV/vMU9KrUWf7wfwjCAMAAAAAAJ44f076/lft1V7/muQ/52g7WAAEYQAAAAAAwDMv2zgZ/mbSXh0wCEEYAAAAAACYal8nBMOEEIQBAAAAAABgIRCEAQAAAAAAYCGc9boBAAAAAACwuHyG9Nnbg2uASSAIAwAAAAAAnjEM6QxBF1zC0kgAAAAAAAAsBGaEYabV63WFw+G+NZlMRplMxqWOAAAAAABYXPl8Xvl8vm9NvV53qZvjCMIw01qtlmq1Wt+aZrPpUjcAAAAAACy2ZrM58D7dSwRhmGk+n0/Ly8t9a/x+v0vdAAAAAACw2Px+v0KhUN+aer2uVqvlUke9DMuyLE+uDIwhHA6rVqspFArp4ODA63YAAAAAAIBNXt7Ts1k+AAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkGYB6rVqhKJxNyNubW1pUQioWAwKMMwtLKyolQqpXK5PNG+AAAAAAAARkEQNkGmacowjIGPlZUVRSKRuRmzXC4rGAwqm81Kkra3t7W/v69cLqdKpaJEIqFEIiHTNG31BwAAAAAA4ISzXjcwT4rFou3admg062OWy+XOrLF0Oq1CodD5XCQSUTKZVCwWU7lcViwW097engKBgO3rAwAAAAAATIphWZbldRPzIhgM2pr1FI/HtbOzM/NjmqapCxcuyDRNRSIR7e/vn1hXrVa1srIydJ/9eHnUKgAAAAAAGJ2X9/TMCJuQYrEo0zS1sbExcF+t1dXVuRgzlUp1ArV+M8faM8NKpZLK5bKKxaLS6bStfgEAAAAAACaFGWET0p7xdNqsqHkbs3uWlyQ1Go2+Sx5LpZJSqZQkKRAIqNFojHV9ZoQBAAAAADCbvLynZ7P8CSiVSqpWq7b36JqHMXO5XOfjeDw+cN+vZDLZ+dg0TZVKpbF7AE5jWdKTVv8HvwIAAAAAgMXD0sgJ2NzcVCAQ0OXLlxdmzO4N96PRqK3XRCIRVatVSdKtW7d6wjFgklqWdPat/jWfvS2dMdzpBwAAAAAwHZgRNqZKpaJKpSLTNBUMBrWysqL19fWxZjxN+5iVSqXn+aVLl2y9rjswY0YYAAAAAABwG0HYmI4uM6xWqyoWi0qlUjIMQ6lU6lhwNOtjlsvlnueRSMTW647WDfs1AAAAAAAAjIMgbAzVavVYKHRUqVRSLBbT+vr63Ix57969nueD9gdre/bZZ3ue7+7u2nodAAAAAADAJLBH2BgikYgKhYJM09T+/r7K5XJnD6yjisWidnd3tbe3N/NjHn3tqDPCJnkaJjCsd+9Lr8a87gIAAACYTZZ1uDdvPz5DMtiXF1OGIGxM6XS657lpmioWi9rc3JRpmj2fq1QqSiQS2tnZmekxTwvRhnX0usCkvHt/cM1rJemMT3r5ovP9AAAAAPOGA6owq1gaOWGBQEAbGxtqNBra3t4+tmywXC5ra2trpsccNcA6eo2HDx+ONA7Qz6PH0hs/sVf7+ntS87Gj7QAAAAAApohhWdaAyYwYh2maWltb69kYPhAIqNFozOyYxpG5rXa/hcrlshKJROd5PB4fOJPtNOFwWLVaTT6fT8vLyyON0S2TySiTyYw9Drz3n/+H9B/et1//ty9K3/qSc/0AAAAA8+hJy+aMMKbfzJV8Pq98Pj/2OPV6Xa1WS6FQSAcHBxPozD6WRjosEAhob29PsVisEzKZpqlyuax4PD6TYwYCgYksa7S7yX4/rVZLtVpt7HGazebYY2A6vP/hcPU//ZAgDAAAAHAC+/LOn2azOZF7cC8RhLnkxo0bisV++y/Azs7OyKGV12MuLS1NJAhbWloae4xJzQjz+/1jj4Hp0PjU2XoAAAAA7Mu7qPx+v0Kh0NjjtGeEeYEgzCXRaFTxeFzlclnSZDac92rMUWdyHQ3PJjEjbHl52fVplJhuwaedrQcAAAAW3bD78r74h5L/nKMtwSWT2laovd2RF1it66Lu/bFmeczV1dWe53Znhx3dHH9lZWWovgA7Xnx+uPoXhqwHAAAAFt0PK9Inv7FX+/GvpZuVwXWAWwjCXBSJRDofT2JZoFdjdi+dlOzPRNvf3+95Pu4yTuAkr0Slz3/OXu0zT0mvRp3tBwAAAJg3o+zLC0wLgjAXdQdMk1gW6NWYR2eE2Q3CumeOBQKBnusAk3L+nPT9r9qrvf41pmgDAAAAw2JfXswygjAX7e7udj6e1JJGL8aMRqM9Adm9e/eGHvdomAZMkp3NOG8m2bQTAAAAGAX78mKWEYS5qHtp4KSWBXo15uXLlzsfVyr2Fnx312Wz2RG7Aybj64RgAAAAwEjYlxezjCDMRaVSSZK0sbEx82Our693Pm6fMNlPd00kEmF/MAAAAACYUezLi1lGEOaSUqmkarWqQCCga9euzfyY0Wi0J8xqh2en2d7e7nzMbDAAAAAAmF3sy4tZRhA2onK5rGAwKMMwlEgk+i4PrFarunr1qiTp7t27p25qPytjthUKhc7Hm5ubp9aZpqlisSjpcKllOp3uOy4wLp8hffZ2/4fP8LpLAAAAYHaxLy9mFUHYiLa3tzunIJbLZcVisZ7lgm3tzy0tLWl/f1/R6OlzQmdlzLZIJNKZ6VWpVLS1tXVi3dramqTDkyK7Z4YBTjEM6Yyv/8MgCAMAAAAcxb68mEYEYSNKpVLH/qxYLCoYDCqVSml9fV2xWEyJRELpdFp7e3uKRCJzMWa3ZDKpnZ0dBQIBZbNZpVIpVSoVmabZCdcqlYqi0agePHgwcJYZAAAAAACAUwzLsiyvm5hV1WpVuVxO5XJZDx8+lGmaCgQCWlpaUjQa1ZUrVxSPx4cKf2ZlzJNsbW3p1q1bqlarnWusrq5qfX1dyWRyrLGPCofDqtVqCoVCOjg4mOjYAAAAAID+nrSks2/1r/ns7cPVGMBRXt7TE4RhJhGEAQAAAIB3LEtqDUgTfAZbkuBkXt7Tn3X1agAAAAAAYOYZhnSGkAsziEmKAAAAAAAAWAgEYQAAAAAAAFgIBGEAAAAAAABYCOwRhplWr9cVDof71mQyGWUyGZc6AgAAAABgceXzeeXz+b419XrdpW6OIwjDTGu1WqrVan1rms2mS90AAAAAALDYms3mwPt0LxGEYab5fD4tLy/3rfH7/S51AwAAAADAYvP7/QqFQn1r6vW6Wq2WSx31MizLsjy5MjCGcDisWq2mUCikg4MDr9sBAAAAAAA2eXlPz2b5AAAAAAAAWAgEYQAAAAAAAFgIBGEAAAAAAABYCARhAAAAAAAAWAgEYQAAAAAAAFgIZ71uAACmmWVJrQFn6/oMyTDc6QcAAAAAMDqCMADoo2VJZ9/qX/PZ29IZgjAAAAAAmHosjQQAAAAAAMBCIAgDAAAAAADAQiAIA4AxvXvf6w4AAAAAAHawRxgA9GEn5HqtJJ3xSS9fdL4fAAAAYFQcBAUQhAHAqR49lt74ib3a19+TXvxDyX/O0ZYAAACAkXEQFMDSSAA41Q8r0ie/sVf78a+lmxVn+wEAAAAAjIcgDABO8f6Hw9X/dMh6AAAAYNqw/y3mHUEYAJyi8amz9QAAAICb7O5/SxiGeUYQBgCnCD7tbD0AAADglmH3v20+drQdwDNslo+ZVq/XFQ6H+9ZkMhllMhmXOsI8efF56c4/269/4XnnegEAAADGMcr+t9/6krM9YT7l83nl8/m+NfV63aVujiMIw0xrtVqq1Wp9a5rNpkvdYN68EpW+/TN7/8HwzFPSq1HnewIAAABGMcr+twRhGEWz2Rx4n+4lgjDMNJ/Pp+Xl5b41fr/fpW4wb86fk77/1cN9Ega5/jXJf87xlgAAAICRsP8t3OL3+xUKhfrW1Ot1tVotlzrqZViWZXlyZWAM4XBYtVpNoVBIBwcHXreDOfakJZ19q3/NzaT0SsydfgAAAIBRfOX/GW7bj688J/3s3zvXDxabl/f0bJYPAGP6+kWvOwAAAAD6e3HI/WzZ/xbziiAMAAAAAIA590pU+vzn7NWy/y3mGXuEAUAfPkP67O3BNQAAAMA0Y/9b4BAzwgCgD8OQzvj6PwyCMAAAAMyAl21s6XEzaa8OmFUEYQAAAAAAQBL732L+EYQBAAAAAABgIbBHGAAAAAAAC4D9bwGCMAAAAAAAFoJhSGcIurDgWBoJAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFQBAGAAAAAACAhUAQBgAAAAAAgIVAEAYAAAAAAICFcNbrBoBx1Ot1hcPhvjWZTEaZTMaljgAAAAAAWFz5fF75fL5vTb1ed6mb4wjCMNNarZZqtVrfmmaz6VI3AAAAAAAstmazOfA+3UsEYZhpPp9Py8vLfWv8fr9L3QAAAAAAsNj8fr9CoVDfmnq9rlar5VJHvQzLsixPrgyMIRwOq1arKRQK6eDgwOt2AAAAAACATV7e0zMjDABcYllSa8CvHnyGZBju9AMAAAAAi4YgDABc0rKks2/1r/nsbekMQRgAAAAAOMLndQMAAAAAAACAGwjCAAAAAAAAsBAIwgBgirx73+sOAAAAAGB+EYQBgEvshFyvlQjDAAAAAMApBGEA4IJHj6U3fmKv9vX3pOZjR9sBAAAAgIVEEAYALvhhRfrkN/ZqP/61dLPibD8AAAAAsIgIwgDABe9/OFz9T4esBwAAAAAMRhAGAC5ofOpsPQAAAABgMIIwAHBB8Gln6wEAAAAAgxGEAYALXnx+uPoXhqwHAADAfLIs6Umr/8OyvO4SmB1nvW4AABbBK1Hp2z+zt2H+M09Jr0ad7wkAAADTr2VJZ9/qX/PZ29IZw51+gFnHjDAAcMH5c9L3v2qv9vrXJP85R9sBAAAAgIVEEAYALnn54uCam0l7dQAAAACA4RGEAcAU+TohGAAAAIb07n2vOwBmB3uEYabV63WFw+G+NZlMRplMxqWOgNP5jMP9GwbVAAAAAG12Qq7XStIZHysLMB3y+bzy+Xzfmnq97lI3xxGEYaa1Wi3VarW+Nc1m06VugP4Mg01MAQAAYN+jx9IbP7FX+/p70ot/yF6z8F6z2Rx4n+4lgjDMNJ/Pp+Xl5b41fr/fpW4AAAAAYHJ+WLF36rgkffxr6WZF+taXnO0JGMTv9ysUCvWtqdfrarVaLnXUy7Asy/LkysAYwuGwarWaQqGQDg4OvG4HAAAAACbuK/+PdOefh6h/TvrZv3euH2BSvLynZ7N8AAAAAACmUONTZ+uBRUQQBgAAAADAFAo+7Ww9sIgIwgAAAAAAmEIvPj9c/QtD1gOLiCDMA9VqVYlEwtMxt7a2lEgkFAwGZRiGVlZWlEqlVC6XR+7BiTEBAAAAYFG9EpU+/zl7tc88Jb0adbYfYB4QhE2QaZoyDGPgY2VlRZFIxJMxy+WygsGgstmsJGl7e1v7+/vK5XKqVCpKJBJKJBIyTdP21+3EmAAAAACw6M6fk77/VXu1178m+c852g4wF8563cA8KRaLtmvboZGbY5bL5c6ssXQ6rUKh0PlcJBJRMplULBZTuVxWLBbT3t6eAoGA62MCAAAAAA69fFF6rdS/5mbysA7AYIZlWZbXTcyLYDBoa9ZTPB7Xzs6Oq2OapqkLFy7INE1FIhHt7++fWFetVrWysuLZmHZ5edQqAAAAALjlSUs6+1b/ms/els6w3gszxMt7emaETUixWJRpmtrY2Bi4V9fq6qrrY6ZSqU6g1m/mWHsWV6lUUrlcVrFYVDqddm1MAAAAAAAApzAjbELaM55OmxXl5ZjdM7IkqdFo9F2eWCqVlEqlJEmBQECNRsOVMYfBjDAAAAAAi8CypNaAu3afIRmGO/0Ak+DlPT2TJyegVCqpWq3a3vfL7TFzuVzn43g8PnCPrmQy2fnYNE2VSscXpDsxJgAAAACgl2EcLnvs9yAEA+wjCJuAzc1NBQIBXb58eSrH7N5wPxq1d55u9wmUt27dcmVMAAAAAAAAJxGEjalSqahSqcg0TQWDQa2srGh9fX2sGU+THLNSqfQ8v3Tpkq3XdYdbR6/rxJgAAAAAAABOIwgb09Gli9VqVcViUalUSoZhKJVKHQuO3ByzXC73PO+eldXP0bru6zkxJgAAAAAAgNMIwsZQrVaPhUJHlUolxWIxra+vezLmvXv3ep4P2sur7dlnn+15vru76+iYAAAAAAAATjvrdQOzLBKJqFAoyDRN7e/vq1wuq1qtnlhbLBa1u7urvb09V8c8+tpRZ291n1zpxJgAAAAAAABOIwgbUzqd7nlumqaKxaI2NzdlmmbP5yqVihKJhHZ2dlwb87QQbVjd13ViTAAAAAAAAKcZlmVZXjcxr0qlkq5evXos8MnlctrY2HBlTOPIObp23+5yuaxEItF5nkwmtb297diYwwqHw6rVavL5fFpeXh5pjG6ZTEaZTGbscQAAAAAAmFf5fF75fH7scer1ulqtlkKhkA4ODibQmX3MCHNQMplUPB7X2tpaz8bwm5ubIwdhToxphxOztyYxZqvVUq1WG3ucZrM59hgAAAAAAMyzZrM5kXtwLxGEOSwQCGhvb0+xWKwTXJmmqXK5rHg87viYgUBgIoFT94b4Tow5qknNCPP7/WOPAQAAAADAPPP7/QqFQmOP054R5gWCMJfcuHFDsVis83xnZ2fkIGyYMZeWliYSWi0tLTk65qiWl5ddn0YJAAAAAMAimtS2Qu3tjrzg8+SqCygajfaEVJPYcN7OmKPOujoadB2dETbpMQEMx7KkJ63+D3aABAAAAIBeBGEu6t4o3q0xV1dXe57bncn18OHDnucrKyuOjglgOC1LOvtW/0eLIAwAAAAAehCEuSgSiXQ+nsSyQDtjdi+dlOzPRNvf3+953j3zzIkxAQAAAAAAnEYQ5qLu0GpSywIHjXl09pbd0Kp7llcgEOi5jhNjApi8d+973QEAAAAATBeCMBft7u52Pp7UMslBY0aj0Z6A7N69e0OPezT4cmJMAMOxE3K9ViIMAwAAAIBuBGEu6l4aOKllgXbGvHz5cufjSqVia9zuumw268qYAOx59Fh64yf2al9/T2o+drQdAAAAAJgZBGEuKpVKkqSNjQ1Xx1xfX+98XC6XB47ZXROJRE4M2JwYE4A9P6xIn/zGXu3Hv5Zu2suqAQAAAGDuEYS5pFQqqVqtKhAI6Nq1a66OGY1Ge4Kndnh2mu3t7c7Hp83ccmJMAPa8/+Fw9T8dsh4AAADjsyzpSav/w+KUb8B1BGEjKpfLCgaDMgxDiUSi7/LAarWqq1evSpLu3r176kb5TozZVigUOh9vbm6eWmeaporFoqTDpZbpdNrVMQEM1vjU2XoAAACMr2VJZ9/q/2gRhAGuIwgb0fb2ducUxHK5rFgs1rNcsK39uaWlJe3v7ysajbo6ZlskEunMyqpUKtra2jqxbm1tTdLhqY7ds7jcGhPAYMGnna0HAAAAgHlFEDaiVCp17M+KxaKCwaBSqZTW19cVi8WUSCSUTqe1t7enSCTi+pjdksmkdnZ2FAgElM1mlUqlVKlUZJpmJ1yrVCqKRqN68ODBwFlmTo0JoL8Xnx+u/oUh6wEAAOAOTvgG3GdYFquSR1WtVpXL5VQul/Xw4UOZpqlAIKClpSVFo1FduXJF8Xh8qPDHiTFPsrW1pVu3bqlarXausbq6qvX1dSWTyakZ8zThcFi1Wk2hUEgHBwcTHRuYdo8eS6Hv2tsw/5mnpNo1yX/O+b4AAADwWzf3pNf6b6UsSfr7y9LLF53vB5gmXt7TE4RhJhGEYdHxH1YAAADTi19cAv15eU/P0kgAmEF2wq2bSUIwAAAAL/ywYi8Ek6SPfy3dPP2cNAATRhAGAHPq64RgAAAAnnj/w+HqfzpkPYDRnfW6AQDA8HyG9Nnbg2sAAADgvsanztYDGB1BGADMIMOQzhB0AQAATKXg087WAxgdQRhmWr1eVzgc7luTyWSUyWRc6ggAAADAonvxeenOP9uvf+F553oB3JbP55XP5/vW1Ot1l7o5jiAMM63VaqlWq/WtaTabLnUDAAAAANIrUenbP7N/auSrUed7AtzSbDYH3qd7iSAMM83n82l5eblvjd/vd6kbAAAAAJDOn5O+/1XptdLg2utfk/znHG8JcI3f71coFOpbU6/X1Wq1XOqol2FZluXJlYExhMNh1Wo1hUIhHRwceN0OAAAAAPR40pLOvtW/5mZSeiXmTj/ANPHynt7n6tUAAAAAAIAk6esXve4AWDwEYQAAAAAAAFgI7BEGAAAAAMCE+Qzps7cH1wBwF0EYAAAAAAATZhjSGYIuYOqwNBIAAAAAAAALgSAMAAAAAAAAC4EgDAAAAAAAAAuBIAwAAAAAAAALgSAMAAAAAAAAC4EgDAAAAAAAAAuBIAwAAAAAAAALgSAMAAAAAAAAC4EgDAAAAAAAAAuBIAwAAAAAAAALgSAMAAAAAAAAC4EgDAAAAAAAAAvhrNcNAOOo1+sKh8N9azKZjDKZjEsdAQAAAACwuPL5vPL5fN+aer3uUjfHEYRhprVaLdVqtb41zWbTpW6A2WRZUsvqX+MzJMNwpx8AAAAAs6vZbA68T/cSQRhmms/n0/Lyct8av9/vUjfAbGpZ0tm3+td89rZ0hiAMAAAAwAB+v1+hUKhvTb1eV6vVcqmjXoZlWQPmAQDTJxwOq1arKRQK6eDgwOt2gJn2pGUzCGNXSQAAAAAT4OU9Pbc1AICB3r3vdQcAAAAAMD6CMABYcHZCrtdKhGEAAAAAZh9BGAAssEePpTd+Yq/29fek5mNH2wEAAPCUZR1uG9HvweZCwGxjs3wAWGA/rEif/MZe7ce/lm5WpG99ydmeAAAAvMIhQsD8Y0YYACyw9z8crv6nQ9YDAADMG7aLAGYbQRgALLDGp87WAwAAzBL2TgXmH0EYACyw4NPO1gMAAMwK9k4FFgNBGAAssBefH67+hSHrAQAAZsUoe6cCmD0EYQCwwF6JSp//nL3aZ56SXo062w8AAIBX2DsVWAwEYQCwwM6fk77/VXu1178m+c852g4AAIBn2DsVWAwEYQCw4F6+OLjmZtJeHQAAwKxi71RgMRCEAQAG+johGAAAmHPsnQosBoIwAAAAAMDCY+9UYDGc9boBAIC3fIb02duDawAAAOZZe+/U10qDa9k7FZhdzAgDgAVnGNIZX/+HQRAGAAAWAHunAvOPIAwAAAAAAJvYOxWYbSyNxEyr1+sKh8N9azKZjDKZjEsdAQAAAACwuPL5vPL5fN+aer3uUjfHEYRhprVaLdVqtb41zWbTpW4AAAAAzDL2TgXG12w2B96ne4kgDDPN5/NpeXm5b43f73epGwAAAACzzDCkMwRdwFj8fr9CoVDfmnq9rlar5VJHvQzLsixPrgyMIRwOq1arKRQK6eDgwOt2AAAAAACATV7e07NZPgAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFsJZrxsAAMwHy5JaVv8anyEZhjv9AAAAAMBRBGEAgIloWdLZt/rXfPa2dIYgDAAAAIBHWBoJAAAAAACAhUAQBgBwzbv3ve4AAAAAwCJjaSQAYCLshFyvlaQzPunli873AwAAFgP7lAIYBkEYZlq9Xlc4HO5bk8lklMlkXOoIWEyPHktv/MRe7evvSS/+oeQ/52hLAABgQbBPKTBd8vm88vl835p6ve5SN8cRhGGmtVot1Wq1vjXNZtOlboDF9cOK9Mlv7NV+/GvpZkX61pec7QkAAACA+5rN5sD7dC8RhGGm+Xw+LS8v963x+/0udQMsrvc/HK7+px8ShAEAAPe8e196NeZ1F8Bi8Pv9CoVCfWvq9bparZZLHfUiCMNMW15e1sHBgddtAAuv8amz9QAAAKdhn1JgutjZnigcDns2a4xTIwEAYws+7Ww9AADASYbdp7T52NF2AMwAgjAAwNhefH64+heGrAcAADjJKPuUAlhsBGEeqFarSiQSY4+zsrIiwzBUKpUm0NVxw/a5tbWlRCKhYDAowzC0srKiVCqlcrnsSH8ApscrUenzn7NX+8xT0qtRZ/sBAACLYZR9SgEsNoKwCTJNU4ZhDHysrKwoEomMda1sNqtqtToVfZbLZQWDQWWzWUnS9va29vf3lcvlVKlUlEgklEgkZJrmSP0CmH7nz0nf/6q92utfk/znHG0HAAAsCPYpBTAsgrAJKhaLtmvbodEoyuWytra2Rn79JPssl8udkCudTmtnZ0fxeFyRSETJZFL7+/uKRqMql8uKxWKEYcAcs7P57M0km9QCAIDJYZ9SAMMiCJugzc1NW3XtoGgUpmkqlUqN9Nq2SfXZ3UskElGhUDixbnt7W9LhUstxewcw275OCAYAACaIfUoBDOus1w3Mi2KxKNM0tbGxMXBfrdXV1ZGvc/XqVS0tLUnSSLOrJtlnKpXq9NBv5lh7dlipVFK5XFaxWFQ6nR66dwDTzWdIn709uAYAAGBSXolK3/6ZvQ3z2acUgCQZlmVZXjcxD1ZWViRJ+/v7jl2jWCxqfX1de3t7Wltb64RQ29vbSiaTtsaYVJ/VarUzliQ1Gg0FAoFT60ulUmc2WCAQUKPRGOv64XBYtVpNoVBIBwcHY40FAAAAYHbd3JNes3F+2N9fZosGYFp4eU/P0sgJKJVKqlarY+37NUi1WtX6+ro2NjYUjY72a4xJ9pnL5Tofx+PxviGYpJ6gzjRNx066BAAAALBY2KcUwDAIwiZgc3NTgUBAly9fduwaqVRK0Wi0J4Aa1iT77N5w324w173f2K1bt8buAQAAAADsYJ9SAG3sETamSqWiSqUiSQoGg4pEIorH40okEraXKw6SzWZVqVTGWs44yT7b47RdunTJ1uui0aiq1aokMSMMAAAAwESwTymAYTAjbExHlxlWq1UVi0WlUikZhqFUKnUsOBpGpVLR1taWCoXCyCdNTrrPcrnc89xuX0frxvl7AQAAAABJMgzpjK//wyAIA/B/EISNoVqtHguFjiqVSorFYlpfXx/pGmtra0omk2OdsjjpPu/du9fzfND+YG3PPvtsz/Pd3V1brwMAAAAAAJgElkaOIRKJqFAoyDRN7e/vq1wud5b+HVUsFrW7u6u9vT3b47dPWbxx48ZU9Xn0taPOCHPyhE0AAAAAAICjCMLGdHSmlmmaKhaL2tzclGmaPZ+rVCpKJBLa2dkZOG6pVFKpVNLOzo7tGVdu9XlaiDaso9cFAAAAAABwEksjJywQCGhjY0ONRkPb29vHQqxyuaytra2+Y5imqVQqpXQ6rXg8PnV9jhpgHb3Gw4cPRxoHAAAAAABgFIZlWZbXTcwz0zS1trbWszF8IBBQo9E49TWxWKyzjPE0wWCwE0htb2+PfULlMH0aR3aatPstVC6XlUgkOs/j8bit2XEnCYfDqtVq8vl8Wl5eHmmMbplMRplMZuxxAAAAAACYV/l8Xvl8fuxx6vW6Wq2WQqGQDg4OJtCZfSyNdFggENDe3p5isVgnZDJNU+Vy+cTZXltbW6pUKkPtJeZ2n4FAYCLLGiex5LPVaqlWq409TrPZHHsMAAAAAADmWbPZnMg9uJcIwlxy48YNxWKxzvOdnZ1jAVOlUlE2m1Uul1M0GnW7RUn2+lxaWppIELa0tDT2GJOaEeb3+8ceAwAAAACAeeb3+xUKhcYepz0jzAsEYS6JRqOKx+Mql8uSTt5wPpVKKRqNamNjw+32Ouz0OepMrqPh2SRmhC0vL7s+jRIAAAAAgEU0qW2F2tsdeYEgzEWJRKITMB21tbWlarWqeDyuVCo1cKzuUGlzc1O3bt3qPL9y5cpYe4b161OSVldXe/YSM03TVqh1dHP8lZWVkXsEAAAAAAAYFkGYiyKRSOfjo8sCf/WrX0lS3wDqNJVKpSeYikQiYwVh/fqU1LN0UjqcNWZnKefRzf+dOhETAAAAAADgJD6vG1gk3QHTJJYFOmVQn6urqz3PT1o+eZLuWWyBQKDnOgAAAAAAAE4jCHPR7u5u5+NEItHzuVwuJ8uybD+6Q6Tt7e2ez+VyOcf6lA73EesOyO7duzf0uEfDNAAAAAAAAKcRhLmoe2ngNC8LtNPn5cuXOx93L8vsp7sum82O2B0AAAAAAMBoCMJcVCqVJMnTUyHtsNPn+vp652M7+5p110QikakOAgF4z7KkJ63+D8vyuksAAAAAs4bN8l1SKpVUrVYVCAR07do1r9s5ld0+o9Go4vF4J+AqlUp9N+jf3t7ufMxsMACDtCzp7Fv9az57WzpjuNMPAAAAgPnAjLARlctlBYNBGYahRCLRd3lgtVrV1atXJUl37951daN8J/ssFAqdjzc3N0+tM01TxWJR0uFSy3Q6PcRXAAAAAAAAMBkEYSPa3t7unIJYLpcVi8V6lgu2tT+3tLSk/f19RaPRuekzEol0ZnpVKhVtbW2dWLe2tibp8KTI7plhADCOd+973QEAAACAWUMQNqJUKnXsz4rFooLBoFKplNbX1xWLxZRIJJROp7W3t9dz0uO89JlMJrWzs6NAIKBsNqtUKqVKpSLTNDvhWqVSUTQa1YMHD1ydDQdgdtkJuV4rEYYBAAAAGI5hWWw3PKpqtapcLqdyuayHDx/KNE0FAgEtLS0pGo3qypUrisfjnoc/bvW5tbWlW7duqVqtdq6xurqq9fX1vvuHjSIcDqtWqykUCung4GCiYwPw1qPHUui70ie/GVz7zFNS7ZrkP+d8XwAAYHIs63BP0H58hmSwHygwl7y8pycIw0wiCAPm13/+H9J/eN9+/d++KH3rS871AwAAJu9Jy+bBOKxhAuaSl/f0/LMCAJgq7384XP1Ph6wHAAAAsLgIwgAAU6XxqbP1AABgNrAXKAAnEIQBAKZK8Gln6wEAgPc4GAeAVwjCAABT5cXnh6t/Ych6AADgrUePpTd+Yq/29fek5mNH2wGwYM563QAwjnq9rnA43Lcmk8kok8m41BGAcb0Slb79M/unRr4adb4nAAAwOT+s2Pv/eUn6+NfSzQoH4wCzJJ/PK5/P962p1+sudXMcQRhmWqvVUq1W61vTbDZd6gbAJJw/J33/q4fLIQa5/jXJf87xlgAAwASNcjAOQRgwO5rN5sD7dC8RhGGm+Xw+LS8v963x+/0udQNgUl6+ODgIu5k8rAMAALOFg3GA+eb3+xUKhfrW1Ot1tVotlzrqRRCGmba8vKyDgwOv2wAwYT5D+uztwz1E/v6+9A8fHv5HcPBp6c+el165KAXYJB8AgJnEwTjAfLOzPVE4HPZs1hhBGABg6hiGdMaQln5H+qs/PnwAAID58OLz0p1/tl/PwTgAJolTIwEAAAAArnklKn3+c/ZqORgHwKQRhAEAAAAAXNM+GMcODsYBMGkEYQAAAAAAV9k58IaDcQA4gT3CAAAAAACu4mAcAF4hCAMAAAAAuIqDcQB4haWRAAAAAAAAWAgEYQAAAAAAAFgIBGEAAAAAAABYCARhAAAAAAAAWAgEYQAAAAAAAFgIBGEAAAAAAABYCARhAAAAAAAAWAgEYQAAAAAAAFgIBGEAAAAAAABYCARhAAAAAAAAWAgEYQAAAAAAAFgIZ71uABhHvV5XOBzuW5PJZJTJZFzqCAAAAACAxZXP55XP5/vW1Ot1l7o5jiAMM63VaqlWq/WtaTabLnUDYBpZltSy+tf4DMkw3OkHAAAAmGfNZnPgfbqXCMIw03w+n5aXl/vW+P1+l7oBMI1alnT2rf41n70tnSEIAwAAAMbm9/sVCoX61tTrdbVaLZc66mVYljXg9+TA9AmHw6rVagqFQjo4OPC6HQBT7EnLZhDGrpkAAACAK7y8p+c/+wEAC+/d+153AAAAAMANBGEAgLlmJ+R6rUQYBgAAACwCgjAAwNx69Fh64yf2al9/T2o+drQdAAAAAB4jCAMAzK0fVqRPfmOv9uNfSzcrzvYDAAAAwFsEYQCAufX+h8PV/3TIegAAFo1lHR5E0+/BcWwAptlZrxsAAMApjU+drQcAYNG0LJunMRvu9AMAw2JGGABgbgWfdrYeAAAAwGwhCAMAzK0Xnx+u/oUh6wEAwHGcxAxgmhGEAQDm1itR6fOfs1f7zFPSq1Fn+wEAYNbZCbleKxGGAZheBGEAgLl1/pz0/a/aq73+Ncl/ztF2AACYaY8eS2/8xF7t6+9JzceOtgMAIyEIAwDMtZcvDq65mbRXBwDAIvthRfrkN/ZqP/61dLPibD8AMApOjQQAzDWfcXh61aPH0t/fl/7hw8PTIYNPS3/2vPTKRSnAJvkAAAz0/ofD1f/0Q+lbX3KmFwAYFUEYAGCuGcbhEe5LvyP91R8fPgAAwPAanzpbDwBuYGkkAAAAAGCg4JAzqIetBwA3EIQBAAAAAAZ68fnh6l8Ysh4A3EAQBgAAAAAY6JWo9PnP2at95inp1aiz/QDAKNgjDDOtXq8rHA73rclkMspkMi51BAAAAMyn8+ek739Veq00uPb61yT/OcdbAjCF8vm88vl835p6ve5SN8cRhGGmtVot1Wq1vjXNZtOlbgAAAID59vLFwUHYzeRhHYDF1Gw2B96ne4kgDDPN5/NpeXm5b43f73epGwAAAABfJwQDFprf71coFOpbU6/X1Wq1XOqol2FZluXJlYExhMNh1Wo1hUIhHRwceN0OAAAAsBAsS2oNuIP0GZJhuNMPgNnk5T09M8IAAAAAALYYhnSGkAvADOPUSAAAAAAAACwEgjAAAAAAAAAsBIIwAAAAAAAALASCMAAAAAAAACwEgjAAAAAAAAAsBIIwAAAAAAAALASCMAAAAAAAACwEgjAAAAAAAAAshLNeNwAAwKywLKll9a/xGZJhuNMPAAAAgOEQhAEAYFPLks6+1b/ms7elMwRhAAAAwFRiaSQAAAAAAAAWAkEYAAAT9O59rzsAAAAAcBqCMAAAbLITcr1WIgwDAAAAphVBGAAANjx6LL3xE3u1r78nNR872g4AAACAERCEAQBgww8r0ie/sVf78a+lmxVn+wEAwC7Lkp60+j+sAaciA8C84NRIzLR6va5wONy3JpPJKJPJuNQRgHn1/ofD1f/0Q+lbX3KmFwAAhsGpxwDclM/nlc/n+9bU63WXujmOIAwzrdVqqVar9a1pNpsudQNgnjU+dbYeAAAAmAfNZnPgfbqXCMIw03w+n5aXl/vW+P1+l7oBMM+CTztbDwCAl969L70a87oLAPPA7/crFAr1ranX62q1Wi511IsgDDNteXlZBwcHXrcBYAG8+Lx055/t17/wvHO9AAAwDLunHp/xSS9fdL4fAPPNzvZE4XDYs1ljbJYPAIANr0Slz3/OXu0zT0mvRp3tBwAAOzj1GAB6EYQBAGDD+XPS979qr/b61yT/OUfbAQDAFk49BoBeBGEAANhkZ7nIzSTLSgAA02OUU48BYJ4RhHmgWq0qkUiMPc7KyooMw1CpVBr6tVtbW0okEgoGgzIMQysrK0qlUiqXyyP348SYADBNfMbh8fK/+r+k//sF6U9/X7oUOvzf//sF6eH/Jf2/WBIJAJginHoMAL0IwibINE0ZhjHwsbKyokgkMta1stmsqtXq0K8rl8sKBoPKZrOSpO3tbe3v7yuXy6lSqSiRSCiRSMg0TU/HBIBpZBiHGwkv/Y70V38s/eNfSv/zW4f/+1d/LAV/57AGAIBpwanHANCLUyMnqFgs2q5th0ajKJfL2traGul17Zlo6XRahUKh87lIJKJkMqlYLKZyuaxYLKa9vT0FAgHXxwQAAAAwGZx6DAC9mBE2QZubm7bq4vH4yDPCTNNUKpUa63WRSKQnsOq2vb0t6XD55qDrODEmAAAAgMnh1GMA6MWMsAkpFosyTVMbGxsD9/9aXV0d+TpXr17V0tKSJA211DCVSnXq+81Ga8/iKpVKKpfLKhaLSqfTro0JAAAAYHLapx6/ZmNbYU49BrAIDMuyLK+bmAcrKyuSpP39fceuUSwWtb6+rr29Pa2trXVCqO3tbSWTyVNfV61WO/1JUqPR6Ls8sVQqdWZuBQIBNRoNV8YcRjgcVq1WUygU0sHBwVhjAQAAAPPsSUs6+1b/mptJ6ZWYO/0AgJf39MwIm4BSqaRqtXrq0sBJqFarWl9f18bGhqLR4eYr53K5zsfxeHzgHl3doZppmiqVSseCNifGBAAAADB57VOPHz2W/v6+9A8fHp4OGXxa+rPnpVcuSgE2yQewINgjbAI2NzcVCAR0+fJlx66RSqUUjUZ7Aii7ujfxtxuide9hduvWLVfGBAAAADB5nHoMAL9FEDamSqWiSqUi0zQVDAa1srKi9fV1lUo2FuHblM1mValUOpvOD9tft0uXLtl6XXe4dfRrcWJMAAAAAAAApxGEjenoJvHValXFYlGpVEqGYSiVSh0LjoZRqVS0tbWlQqEw0kmT5XK557ndMY7WdX8NTowJAAAAAADgNIKwMVSr1WOh0FGlUkmxWEzr6+sjXWNtbU3JZHLkUxbv3bvX83zQXl5tzz77bM/z3d1dR8cEAAAAAABwGpvljyESiahQKMg0Te3v76tcLqtarZ5YWywWtbu7q729Pdvjt09ZvHHjxsg9Hu1n1Nlb3adhOjEmAAAAAACA0wjCxnR0ppZpmioWi9rc3JRpmj2fq1QqSiQS2tnZGThuqVRSqVTSzs6O7RlXJzktmBtW99fixJgAAAAAAABOY2nkhAUCAW1sbKjRaGh7e/tYiFUul7W1tdV3DNM0lUqllE6nFY/Hx+pn1LDpaN8PHz50dEwAAAAAAACnMSPMQclkUvF4XGtraz0bw29ubmpjY+PU162trXWWXU4LJ2ZvTWLMer2ucDg89jiZTEaZTGbscQAAAAAAmFf5fF75fH7scer1+gS6GQ1BmMMCgYD29vYUi8U6YZhpmiqXyyfO9tra2lKlUhlqL7FB159E4NQ9m8uJMUfVarVUq9XGHqfZbI49BgAAAAAA86zZbE7kHtxLBGEuuXHjhmKxWOf5zs7OsSCsUqkom80ql8spGo1O5LpLS0sTCa2WlpYcHXNUPp9Py8vLY4/j9/vHHgMA7LIsqWX1r/EZkmG40w8AAABgh9/vVygUGnucer2uVqs1gY6GRxDmkmg0qng8rnK5LOnkDedTqZSi0WjfZZPDGnXW1dGg6+iMsEmPOarl5WUdHByMPQ4AuKllSWff6l/z2dvSGYIwAAAATJFJbSsUDoc9m1lGEOaiRCLRCcKO2traUrVaVTweVyqVGjhWd6i0ubmpW7dudZ5fuXJFyWRSkrS6utqzP5lpmrYCqKMb2a+srHQ+dmJMAAAAAAAApxGEuSgSiXQ+Pros8Fe/+pUknRqU9VOpVHqCqUgk0gnCupdjSocz0ewsu9zf3+953r2M04kxAQC93r0vvRobXAcAAADAPp/XDSyS7iBsEssC7VhdXe15ftKSzJN0zzgLBAI9vTsxJgAsknfvD655rWSvDgAAAIB9BGEu2t3d7XycSCR6PpfL5WRZlu1Hd4i0vb3d87lcLtf5XDQa7Qnd7t27N3SvR4MvJ8YEgEXx6LH0xk/s1b7+ntR87Gg7AIApZVnSk1b/hzXg4BUAwHEEYS7qXhro5rLAy5cvdz7uXkLZT3ddNpt1ZUwAWAQ/rEif/MZe7ce/lm7a+ycWADBn2ger9HsMOoEYAHAcQZiLSqWSJE30VEg71tfXOx/b2YOsuyYSiZwY2jkxJgAsgvc/HK7+p0PWAwAAADgdQZhLSqWSqtWqAoGArl275uq1o9FoT/DUDuROs7293fn4tJlbTowJAIug8amz9QCAxcFekgAwPIKwEZXLZQWDQRmGoUQi0Xd5YLVa1dWrVyVJd+/edW2j/G6FQqHz8ebm5ql1pmmqWCxKOly+mU6nXR0TAOZd8Gln6wEA84GDVQDAGQRhI9re3u6cglgulxWLxXqWC7a1P7e0tKT9/X1Fo1GXOz0UiUQ6s7IqlYq2trZOrFtbW5N0eKpj9ywut8YEgHn34vPD1b8wZD0AYPZxsAoAOIcgbESpVOrYnxWLRQWDQaVSKa2vrysWiymRSCidTmtvb6/npEcvJJNJ7ezsKBAIKJvNKpVKqVKpyDTNTmBXqVQUjUb14MEDWzPXnBgTAObZK1Hp85+zV/vMU9Kr3vz+BADgIQ5WAQDnEISNKB6Pa39/X+l0WpFIpCfgqVQqevjwoa5du6ZGo6FcLjfxAGh/f1+WZcmyLCWTyaH6bvdUrVa1trbWCe+Wlpa0vb2tvb29ofp1YkwAmFfnz0nf/6q92utfk/znHG0HADCFOFgFAJxjWJbFobuYOeFwWLVaTaFQSAcHB163AwBDedI6PPa+n5tJ6ZWYO/0AAKbLv/n/SPeG+E/cfxOW/n//b+f6AYBJ8/Ke/qyrVwMAAPIZ0mdvH+4B8/f3pX/48PB0yODT0p89L71yUQqwST4ALCwOVgEA5xCEAQDgMsOQzhjS0u9If/XHhw8AANpefF6688/26zlYBQDsY48wAAAAAJgiHKwCAM4hCAMAAACAKcLBKgDgHJZGYqbV63WFw+G+NZlMRplMxqWOAAAAgPG9fFF6rdS/5mbysA4Apkk+n1c+n+9bU6/XXermOIIwzLRWq6Varda3ptlsutQNAAAAMBkcrAJgVjWbzYH36V4iCMNM8/l8Wl5e7lvj9/td6gYAAACYDA5WATCr/H6/QqFQ35p6va5Wq+VSR70My7IsT64MjCEcDqtWqykUCung4MDrdgAAAAAAgE1e3tOzWT4AAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWAkEYAAAAAAAAFgJBGAAAAAAAABYCQRgAAAAAAAAWwlmvGwAAAKOzLKll9a/xGZJhuNMPAAAAMM0IwgAAmGEtSzr7Vv+az96WzhCEAYDj+OUEAEw/gjAAAObcu/elV2NedwEA849fTgDA9GOPMAAAZti79wfXvFayVwcAcB7/HgOAtwjCAACYUY8eS2/8xF7t6+9JzceOtgMAC49fTgDA9CMIAwBgRv2wIn3yG3u1H/9aullxth8AWGT8cgIAZgN7hGGm1et1hcPhvjWZTEaZTMaljgDAPe9/OFz9Tz+UvvUlZ3oBgEU3yi8n+DcZwDzK5/PK5/N9a+r1ukvdHEcQhpnWarVUq9X61jSbTZe6AQB3NT51th4AYB+/nACAQ81mc+B9upcIwjDTfD6flpeX+9b4/X6XugEAdwWfdrYeAGAfv5wAgEN+v1+hUKhvTb1eV6vVcqmjXgRhmGnLy8s6ODjwug0A8MSLz0t3/tl+/QvPO9cLACw6fjkBAIfsbE8UDoc9mzXGZvkAAMyoV6LS5z9nr/aZp6RXo872AwCL7MUhf9nALycAwBsEYQAAzKjz56Tvf9Ve7fWvSf5zjrYDAAuNX04AwGwgCAMAYIa9fHFwzc2kvToAwOj45QQAzAb2CAMAYIb5DOmzt6VHj6W/vy/9w4eHGzAHn5b+7HnplYtSgH1oAMAVL1+UXiv1r+GXEwDgLYIwAABmmGFIZwxp6Xekv/rjwwcAYHp9nRAMADxFEAYAAAAAE9CepTuoBgDgHYIwAAAAAJiA9ixdAMD0YrN8AAAAAAAALASCMAAAAAAAACwEgjAAAAAAAAAsBIIwAAAAAAAALASCMAAAAAAAACwEgjAAAAAAAAAsBIIwAAAAAAAALISzXjcAAACmg2VJLat/jc+QDMOdfgAAAIBJIwgDAACSDkOws2/1r/nsbekMQRgAAABmFEEYZlq9Xlc4HO5bk8lklMlkXOoIAAAAAIDFlc/nlc/n+9bU63WXujmOIAwzrdVqqVar9a1pNpsudQMA8+/d+9KrMa+7AAAAwLRqNpsD79O9RBCGmebz+bS8vNy3xu/3u9QNAMy2d+8PrnmtJJ3xSS9fdL4fAHAD+yMCwGT5/X6FQqG+NfV6Xa1Wy6WOehmWZQ34Zx+YPuFwWLVaTaFQSAcHB163AwAz79FjKfRd6ZPfDK595impdk3yn3O+LwBw2pOWzf0Rfe70AwCLwMt7ev45BwAA+mHFXggmSR//WrpZcbYfAJgmdmbMAgBmA0EYAADQ+x8OV//TIesBYFrZXRZOGAYA84EgDAAAqPGps/UAMI0ePZbe+Im92tffk5qPHW0HAOACgjAAAKDg087WA8A0Ylk4ACwegjAAAKAXnx+u/oUh6wFgGrEsHAAWD0EYAADQK1Hp85+zV/vMU9KrUWf7AQA3sCwcABYPQRgAAND5c9L3v2qv9vrXJP85R9sBAFewLBwAFg9BGAAAkCS9fHFwzc2kvToAmAUsCweAxXPW6wYAAMB08BnSZ28fnqL29/elf/jwcBlQ8Gnpz56XXrkoBZgNAWCOvBKVvv0zexvmsywcAOYDQRgAAJAkGYZ0xpCWfkf6qz8+fADAPGsvC3+tNLiWZeEAMB9YGgkAAABgYbEsHAAWC0EYAAAAAPTxdUIwAJgbLI0EAAAAsLDa+yMOqgEAzAeCMAAAAAALq70/IgBgMbA0EgAAAAAAAAuBIAwAAAAAAAALgSAMAAAAAAAAC4E9wjDT6vW6wuFw35pMJqNMJuNSRwAAAAAALK58Pq98Pt+3pl6vu9TNcQRhmGmtVku1Wq1vTbPZdKkbAP//9u4ntpHzvv/4h9q1sf4DZSgDBbbSpcP+ABc9Lbm+1Mcl+zvEbnIgdw/u2sCvCJlfkPqgA9lFEDQ9uAJ5EBC0CCIu8DvY8cEmDwnsAG05e+2hK85eDRQcX1YRUKDiWLCRRWJrfgeVDKk/5FAczh/y/QIGJqWHz3xX3mcofvZ5ngEAAACw2o6Pj6d+To8SQRgSbW1tTTdv3pzYZn19PaRqAAAAAABYbevr69rc3JzY5vDwUCcnJyFVNC7leZ4XyZmBOWxtbeng4ECbm5t6+vRp1OUAAM7wPOlkym8YaykplQqnHgAAAMRHlJ/pmREGAAACd+JJ1380uc3X70nXCMIAAAAQIu4aCQAAIvHhk6grAAAAwKohCAMAAIHzE3K90yYMAwAAQLgIwiLgOI4KhYLvtpVKRZlMRqlUSul0WrlcTpVKRY7jxKZOSWo0GioUCkqn00qlUspkMiqVSrIsa4FVAgDi5otn0g9+5a/t938pHT9baDkAAADAEEFYgFzXVSqVmnpkMhmZpjm1v0ajoUwmo2azOQy9XNeVbdtqNpvKZDJqNBqR12lZltLptGq1miSp1Wqp1+upXq/Ltm0VCgUVCgW5rjtzrQCA5PnAlr76vb+2X/5Oet9ebD0AlpPnSd+cTD64LRgA4Cw2yw9Qs9n03XYQGl2mUCjIsiwZhqF8Pi/TNOU4jmzbHpsJVqvVZJqmisViJHValjWcNVYul7W3tzf83qCuXC4ny7KUy+XU7XZlGIbv8wMAkueTz2Zr/+ln0g//YjG1AFhe3JQDAHAVzAgL0M7Ojq92g2DrMrVaTZZlqV6vq9/vq9VqqV6vj820GlUqlSKp03Xd4blN0xwLwUa1Wi1Jp0stZ60VAJA8/d8utj0A+MU+hACAs5gRFpBmsynXdVWtVqfuq3X79u1Lv+c4jhqNhjqdjvL5/IVtqtWqer3e2Mwu27aVzWZDq1M6DeAGyx0nzRwbzAxrt9uyLEvNZlPlcnlqrQCAZEq/sNj2ACD5vynHtTXprVuLrwcAkAwpz2PlfBAymYwkqdfrzdVPqVTSa6+9pmq1OrGd67pKp9PD5/V6feprgqzTcZxhX5LU7/cnLnlst9vD2WCGYajf7891/q2tLR0cHGhzc1NPnz6dqy8AQLD++d+lv/3Ef/t/epOlkQBm88UzafMf/e1H+PLz0sEDaf3G4usCAPgT5Wd6lkYGoN1uy3Gcqftp+TGYrTWNYRhjyxb97LsVZJ2jyzPz+fzU84/uYea6rtrt9tw1AADi6X5Weuk5f21ffl56e/qEZgAYw005AABXRRAWgJ2dHRmGobt3787dV6fT8d326Oho+HjaMkYp2DpHl2X6WZIpaSy4++ijj+auAQAQT9+6If3sO/7a/vy7zNIAMLur3JQDAACJIGxutm3Ltu3hUsVMJqNKpbLwGU+u6w7358rn81PDqCDrtO3xf1J77bXXfL1utEZmhAHAcvOzH8/7RfbtAXA13JQDAHBVBGFzOrvM0HEcNZtNlUolpVIplUqlc8FRED7++GNJp7OsBndlDKtOy7LGnk+6s+Skdov4uQAA4mEtJX39nvTfP5Z++ob0l38qvbZ5+t+fviEd/Vj6a5ZEArgibsoBALgqgrA5OI5zLhQ6q91uK5fLqVKpBHZe13VVqVSUzWbV6XSm7s8VdJ2PHz8ee+5nfzJJeuWVV8ae7+/v+3odACB5UqnTO7VtvCi9+7r0r38j/ccPT//77utS+sXTNgBwFW++Olv7N2ZsDwBYXtejLiDJTNPU3t6eXNdVr9eTZVlyHOfCts1mU/v7++p2u3Od03EcFQoFGYahR48e+Qqhgq7z7GuvOiNs3jtXAgAAYDXdz0p/9y/+7xrJTTkAAAPMCJtTuVxWtVrV3t6eer2e+v2+6vX6hQGVbdsqFApXPle73VYmk5HjOMO9vhqNRuh1XhaizWqwxxkAAAAwC27KAQC4qpTneV7URSyrdrut733ve+cCn3q9rmq16qsP13XVbDa1t7d3aQBVLBZ97RMWVJ2pM2tZ/P4VsixrLGCbp+6trS0dHBxobW1NN2/evFIfo7a3t7W9vT13PwAAAAjHNyfS9R9NbvN+UbqfC6ceAFgFu7u72t3dnbufw8NDnZycaHNzU0+fPg2gMv8IwhbMdV3duXNnbGN4wzDU7/d9vb7dbqvT6UiavNfXLOHavHUGFYTl8/nhn21WgyAsKH//93+vn/zkJ4H1BwAAgMXyPOnEk754Jv3iifTrz07vDpl+Qfr2q9L9W5LxAvsRAkCQfvKTn+gf/uEfAusviiCMPcIWzDAMdbtd5XK5Ycjkuq4sy1I+n5/6+mKxqGKxOPa1ZrOpWq02NoOrVqupXC773rh+njoNwwhkWeNVax0V1Iyw9fX1ufsAAABAeFIp6VrqDzflePf1qCsCgOW3vr6uzc3NufsZzAiLAkFYSB4+fKhc7g/zsjudjq8g7CLlcln5fF65XG4skGo2m3PNCvNb58bGRiBB2MbGxtx93Lx5M/T0GAAAAACAVRTUtkJBr/KaBZvlhySbzY4FSvNuOG+aph49ejT2tcePH8/Vp+SvzqvO5DobngUxIwwAAAAAAMAvgrAQzXPHyItks9mxZZNB3c1xWp23b98ee+53dtjR0dHY80wmM1NdAAAAAAAA8yAIC5FpmsPHQSwLlKR79+4NHwexXFGaXufo0knJfwDX6/XGnl91aSgAYLV43und4SYd3PoHAAAAfrBHWIhGA6aglgVms9nA+5xW59kZYY7jjNVxmdGgzjCMsfMAAHCZE0+6/qPJbb5+73TTbAAAAGASZoSFaH9/f/g46GWS0vmA6qqm1ZnNZscCMr97k432G1StAABI0odPoq4AgB/M8AQARI0ZYSEaXRoY1LLA0WWJQYVrfuq8e/eums2mJMm2bV/9jrar1WpzVAgAWCV+Qq532tK1NemtW4uvB8DVMcMTABA1ZoSFqN1uS5Kq1WpgfQ7CJcMwxjbOn4efOiuVyvCxZVlT+xxtY5om+4MBAHz54pn0g1/5a/v9X0rHzxZaDoAQMMMTALBIBGEhabfbchxHhmHowYMHgfW7s7MjSXr48GEg/fmtM5vNjoVZg/DsMq1Wa/iY2WAAAL8+sKWvfu+v7Ze/k973N0kZQET8zvAkDAMALApB2BVZlqV0Oq1UKqVCoTBxeaDjOPre974nSXr06NHETe0bjYZyuZxqtdrUu0AO2lSr1Utngy2qTkna29sbPh4EchdxXXe4jDKfz6tcLk/sFwCAgU8+m639pzO2BxAeZngCAOKAIOyKWq3WMKiyLEu5XG5sueDA4HsbGxvq9XoT767ouq5qtZps21aj0VA6nb509lSpVFKj0VC9Xle9Xg+1zgHTNIczvQY1X+TOnTuSTpdvjs4MAwBgmv5vF9seQHiY4QkAiAOCsCsqlUrnvtZsNpVOp1UqlVSpVJTL5VQoFFQul9XtdmWa5sQ+DcM412YQiJVKJdVqNRUKBaXTaUmnm9pP229sEXWOKhaL6nQ6MgxDtVpNpVJJtm3Ldd1huGbbtrLZrD7//POps8wAABiVfmGx7QGEhxmeAIA4IAi7onw+r16vp3K5LNM0xwIe27Z1dHSkBw8eqN/vq16v+w6Aut2uqtWqstnsuT4dx1GpVNLnn3+uVqvlK7BaVJ1nzzF4veM4unPnzjBo29jYUKvVUrfbJQQDAMzszVdna//GjO0BhIcZngCAOEh5nudFXQQwq62tLR0cHGhzc1NPnz6NuhwAwIJ88Uza/Ed/y6lefl46eCCt31h8XQBm97//n/Rv/zlD+/8l/cv/WVw9AIDoRPmZnhlhAAAgtr51Q/rZd/y1/fl3CcGAOGOGJwAgDgjCAABArN3PSu8XpZeeu/j7Lz0nfVCS3roVbl0AZnM/e/k4Puvl56W3p9+7CQCAmV2PugAAAIBJUinpfk76qz8/vevcp5+d7h2UfuF0xsjbWWaCAUkwmOH5Tnt6W2Z4AgAWhT3CkEiD9cRra2u6efPmxLbb29va3t4OqTIAAABc5psT6fqPJrd5v3gafgMAkml3d1e7u7sT2xweHurk5CSSPcKYEYZEOzk50cHBwcQ2x8fHIVUDAACASdZS0tfvnd4I4xdPpF+PzPD89qvS/VuS8ULUVQIA5nF8fDz1c3qUCMKQaH5mhK2vr4dUDQAAACZJpaRrKWnjRend108PAMByWV9f1+bm5sQ2gxlhUWBpJBIpylutAgAAAACAq4vyMz13jQQAAAAAAMBKYGkkAABYCZ4nnUyZB7+WOl26BQAAgOVEEAYAAFbCiTf9bnVfv3e6fxEAAACWE0sjAQAA/seHT6KuAAAAAIvEjDAAALAS/IRc77Sla2vSW7cWXw+QFCwrBgAsE4IwAACw9L54Jv3gV/7afv+X0pt/Jq3fWGhJQGKwrBgAsExYGgkAAJbeB7b01e/9tf3yd9L79mLrAZYNy4oBAElBEAYAAJbeJ5/N1v7TGdsDy8zvsmLCMABAEhCEAQCApdf/7WLbA8tq1mXFx88WWg4AAHMjCAMAAEsv/cJi2wPLimXFAIBlQxAGAACW3puvztb+jRnbA8uKZcUAgGVDEAYAAJbe/az00nP+2r78vPR2drH1AEnBsmIAwLIhCAMAAEvvWzekn33HX9uff1dav7HQcoDEYFkxAGDZEIQBAICV8Nat6W3eL/prB6wKlhUDAJbN9agLAAAACMNaSvr6vdO74P3iifTrz06XcaVfkL79qnT/lmQwmwUYcz8r/d2/+Nswn2XFAIAkIAgDAAArIZWSrqWkjReld18/PQBMNlhW/E57eluWFQMAkoClkQAAAAAuxbJiAMAyYUYYEu3w8FBbW1sT22xvb2t7ezukigAAAJYLy4oBALPY3d3V7u7uxDaHh4chVXMeQRgS7eTkRAcHBxPbHB8fh1QNAADA8mFZMQBgFsfHx1M/p0eJIAyJtra2pps3b05ss76+HlI1AIBV4XnSiTe5zVrqNEAAAABYJevr69rc3JzY5vDwUCcnJyFVNC7led6UX+OA+Nna2tLBwYE2Nzf19OnTqMsBAKyYb06k6z+a3Obr96Rr7MaKiBDWAgDiLMrP9MwIAwAAWIAPn0hv56KuAqvqxPMZ1hKEAQBWDP9OCQAAMKMPn0xv807bXzsgKvz9BACsIoIwAACAGXzxTPrBr/y1/f4vpeNnCy0HuBBhLQAAFyMIAwAAmMEHtvTV7/21/fJ30vv2YusBziKsBQDgcgRhAAAAM/jks9nafzpje2BehLUAAFyOIAwAAGAG/d8utj0wL8JaAAAuRxAGAAAwg/QLi20PzIuwFgCAyxGEAQAAzODNV2dr/8aM7YF5EdYCAHA5gjAAAIAZ3M9KLz3nr+3Lz0tvZxdbD3AWYS0AAJcjCAMAAJjBt25IP/uOv7Y//660fmNyG8+TvjmZfHje3GVjhRDWAgBwuetRFwAAAJA0b92S3mlPbvN+8bTdNCeedP1Hk9t8/Z50LeW/PiST553+fZhkLSWlpvxdGIS10/6OSv7CWgAAlglBGAAAwIzWUqfh1BfPpF88kX792emG4+kXpG+/Kt2/JRkB7rv04RPp7Vxw/SGeggxFgwxrAQBYJgRhAAAAM0qlTsOIjReld18/Pa7qwyfT27zTlq6tEVrAfygadlgLAEBSEIQBAABE5Itn0g9+5a/t938pvflnLGNbZkGGokGGtQAALBM2ywcAAIjIB7b01e/9tf3yd9L79mLrQXRmDUWPny20HAAAlhZBGAAAQEQ++Wy29p/O2B7JQSgKAEA4WBqJRDs8PNTW1tbENtvb29re3g6pIgAA/Ov/drHtkRxXCUV/+BeLqQUAgHns7u5qd3d3YpvDw8OQqjmPIAyJdnJyooODg4ltjo+PQ6oGAIDZpGfcrHzW9kgOQlEAwLI4Pj6e+jk9SgRhSLS1tTXdvHlzYpv19fWQqgEAYDZvvir923/6b//Gq4urBdEiFAUALIv19XVtbm5ObHN4eKiTk5OQKhqX8jzPi+TMwBy2trZ0cHCgzc1NPX36NOpyAAC4ki+eSZv/6G9vqJeflw4ecNfIZfXP/y797Sf+2//TmyyNBAAkV5Sf6dksHwAAICLfuiH97Dv+2v78u4Rgy+x+VnrpOX9tX35eeju72HoAAFhWBGEAAAAReuvW9DbvF/218zzpm5PJB2sB4olQFACAcLBHGAAAQITWUtLX750uk/zFE+nXn51uhJ5+Qfr2q9L9W5Lhcz+oE0+6/qPJbb5+T7qWmr9uBO9+VkpJ+r+/uni57EvPnYZgfkJRAABwMYIwAACACKVSp8HUxovSu6+fHov04RPp7dxiz4GrSaWk+znpr/5c+sCWPh0JRd949XQ5JDPBAACYD0EYAADAkvjwyfQ277Sla2vTZxV53ukMs0nWUqfhTRj9BN1XkIKu61s3TjfCZzN8AACCRxAGAACwBL54Jv3gV/7afv+X0pt/Nnl2UVDLLINcrhlkX0GGVyxJBQAgOQjCAAAAlsAH9sX7Sl3ky99J79vzzzhK8jLLsMOrJP+sAABYJtw1EgAAYAl88tls7T+d0t7vMks/7aYJoo8o+wrzZwUAAOZDEAYAALAE+r8Nrv2syyyPn13+/SBDojj2FeTPCgAALB5BGAAAwBJIvxBc+6sss7xIkCFRXPsK6mcFAADCQRAGAACwBN58dbb2b0xoH9QyyyBDorj2FfSSVAAAsFgEYQAAAEvgflZ66Tl/bV9+Xno7e/n3g1pmGWRIFNe+glySCgAAFo8gDAAAYAl864b0s+/4a/vz70rrNy7/flDLLIMMieLaV5BLUgEAwOIRhAEAACyJt25Nb/N+cXq7oJZZBhkSxbWvIJekAgCAxSMIAwAAWBJrKenr96T//rH00zekv/xT6bXN0//+9A3p6MfSX09YEjkQ1DLLIEOiuPYV5JJUAACweARhAAAASyKVkq6tSRsvSu++Lv3r30j/8cPT/777upR+8bTNNEEtswwyJIprX0EuSQUAAItHEIZEOzw81NbW1sRjd3c36jIBAEicIJZZBhkSxbUvKbglqQAALIPd3d2pn9MPDw8jq+96ZGcGAnBycqKDg4OJbY6Pj0OqBgCA5TFYZvnFM+kXT6Rff3a6aXz6Benbr0r3b0mGj7223rolvdOe3MZvSBTXvoL6WQEAsAyOj4+nfk6PEkEYEm1tbU03b96c2GZ9fT2kagAAWB6plHQt9Ydllu++frV+ggyJ4tpXUD8rAACWwfr6ujY3Nye2OTw81MnJSUgVjUt5nudFcmZgDltbWzo4ONDm5qaePn0adTkAAAAAAMCnKD/Ts0cYAAAAAAAAVgJBGAAAAAAAAFYCQRgAAAAAAABWAkFYBBzHUaFQ8N22Uqkok8kolUopnU4rl8upUqnIcZwr19BoNFQoFJROp5VKpZTJZFQqlWRZVqz6BAAAAAAACApBWIBc11UqlZp6ZDIZmaY5tb9Go6FMJqNmszkMvVzXlW3bajabymQyajQaM9VoWZbS6bRqtZokqdVqqdfrqV6vy7ZtFQoFFQoFua4baZ8AAAAAAABB466RAWo0GsMwaJperzcxDCsUCrIsS4ZhKJ/PyzRNOY4j27bPzQRrtVoqFotTz2lZ1nAmWrlc1t7e3rk2uVxOtm3LNE11u10ZhhF6n35w10gAAAAAAJIpys/0BGEBSqfTvmY95fN5dTqdS79fq9XUaDRUr9dVrVbPff+iwG3a/0bXdfUnf/Incl1Xpmmq1+td2M5xHGUyGV91LqJPvwjCAAAAAABIpig/018P9WxLrNlsynVdVavVqft/3b59+9LvOY6jRqOhTqejfD5/YZtqtaper6dmszn8mm3bymazl/ZbKpWGId2kWWumaapYLKrdbsuyLDWbTZXL5dD6BAAAAAAAWBRmhAVkMOPpsllRfpVKJb322msXzgQb5bqu0un08Plls8ek8RlZktTv9ycuT2y32yqVSpIkwzDU7/dD6XMWzAgDAAAAACCZovxMz2b5AWi323Icx/f+YJMMZpVNYxjG2B5jk0Koer0+fJzP56fu0TW635jrumq326H0CQAAAAAAsEgsjQzAzs6ODMPQ3bt35+5rlv2zjo6Oho8nLbccXUI5afnkqMHm/JL00UcfnduMfxF9roLd3V0dHx9rfX1d29vbUZcD4H8wNoH4YVwC8cO4BOKHcTk7lkbOybZt5XK54XPTNJXP51UoFBYa9IwujZy0Af3Z+vzeYbJUKo3N2hr9a7KIPmeV1KWRSa0bWHaMTSB+GJdA/DAugfhJ6rhkaWSCnV0O6TiOms2mSqWSUqmUSqWSbNsO/Lwff/yxpNPgrdVqXdrOsqyx56PLKSc52270z7CIPgEAAAAAABaNIGwOjuOcC4XOarfbyuVyqlQqgZ3XdV1VKhVls1l1Op2J+3M9fvx47Pm0vbwGXnnllbHn+/v7C+0TAAAAAABg0dgjbA6maWpvb0+u66rX68myrOEeWGc1m03t7++r2+3OdU7HcVQoFGQYhh49ejQ1hDpbz1Vnb43eDXMRfQIAAAAAACwaM8LmVC6XVa1Wtbe3p16vp36/r3q9fmFAZdu2CoXClc/VbreVyWTkOM5wj7BGozHxNZcFc7NyXXehfQIAAAAAACwaQVjADMNQtVpVv99Xq9U6F4hZljU1vBrluq4ajYYymYxKpdK579dqtQu/Pvr6qzhb9+gdKhfRJwAAAAAAwKKxNHKBisWi8vm87ty5M7Yx/M7OjqrVqq8+LMtSr9dTPp+/dE+ydrutRqPhu8+rWMTsrSD6PDw81NbW1tz9bG9vc6tZAAAAAAAm2N3d1e7u7tz9HB4eBlDN1RCELZhhGOp2u8rlcsMwzHVdWZalfD4/9fXFYlHFYnHsa81mU7VabSxIqtVqKpfL52ZdGYYRSOA02u8i+ryqk5MTHRwczN3P8fHx3H0AAAAAALDMjo+PA/kMHiWCsJA8fPhQuVxu+LzT6fgKwi5SLpeVz+eVy+XGAqlms3luVtjGxkYgodXGxsZC+5zVl19+KUlKpVL64z/+47lrWV9fn7uPZba7u6vj42Otr68nauZcUuuWklt7UutOqqT+vKk7XEmtO6mS+vOm7nAlte6kSurPm7rDldS6w7a+vq7Nzc25+/nNb34jz/OGn+1D5SE0+Xzek+RJ8orF4tz9dbvdYX+X9ZnNZsfa+NVqtcZeV61WF9rnrNbW1jxJ3tra2pX7iMLm5qYnydvc3Iy6lJlQd/iSWjt1h4u6w0Xd4aLucFF3uKg7XNQdLuoOV1LrjvIzPZvlh2ieO0ZeJJvNji2bvOhujrdv3x577ncm19mN7DOZzEL7BAAAAAAAWDSCsBCZpjl8PM+ywFH37t0bPr4okBpdjildHJZdpNfrjT0fXca5iD4BAAAAAAAWjSAsRKNBWBAbxUuns8Im9Xl29pbf0Go0VDMMY6z2RfQJAAAAAACwaARhIdrf3x8+DnqZpHQ+oJJOg7LRgOzx48e++hqt9Wy/i+gTAAAAAABg0QjCQjS6NDCoZYGjs7EuC9fu3r07fGzbtq9+R9vVarVQ+gQAAAAAAFgkgrAQtdttSVK1Wg2sz0G4ZBjG2Mb5oyqVyvCxZVlT+xxtY5rmhaHdIvoEAAAAAABYJIKwkLTbbTmOI8Mw9ODBg8D63dnZkSQ9fPjw0jbZbHYseBoEcpdptVrDx5fN3FpEnwAAAAAAAIuU8jzPi7qIJLIsS6VSSa7rKp/Pq16vj21cP8pxHOVyObmuq263e2k7SWo0Gvroo4+Uz+f14MGDiZvq12o1NRoNVatV1ev1ifU6jqNMJiPpNMTqdrsXtnNdV+l0WtLp8s1OpxNqn36lUqnh483Nzbn7C8vh4aFOTk60trammzdvRl2Ob9QdvqTWTt3hou5wUXe4qDtc1B0u6g4XdYeLusOV1LoPDg6Gj0OPpTxcSblc9iSNHeVy+Vy7TqfjGYbhmabp9Xq9iX32+/1zfVar1QvbFotFT5JXr9d919xqtYb9Xva6bDbrSfIMw/D6/X4kffqRSqXO/aw4ODg4ODg4ODg4ODg4ODiSc6RSqUAygpnyBM9jRthVWJZ14eb0hmEon89rY2ND+/v7sm1b1Wp16uyugUwmM7YB/mifpmnKtm3t7+8PZ6GZpjlz3YOZbMViUQ8ePJBpmtrf31etVpNt28pms3r06JGvehfV5zQvvfSSnj17pmvXrumP/uiPAukTAAAAAAAs3n/913/pm2++0Y0bN/TVV1+Fem6CsDk4jqN6vS7LsnR0dCTXdWUYhjY2NpTNZnXv3j3l8/mZwh/XdbWzsyPLsuQ4zrk+C4WC7t69O3egNFiCOXqO27dvq1KpXLrpfhR9AgAAAAAABIUgDAAAAAAAACuBu0YCAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQvkOI4KhYLa7XYo52s0GioUCkqn00qlUspkMiqVSrIsK5TzA3EV97ExuFYAyyDK8Rb3sQ5EJe5jg/dBrBo+J0aLIAxYANd1VSqVlMlkZFmWjo6OFno+y7KUTqdVq9UkSa1WS71eT/V6XbZtq1AoqFAoyHXdhdYBxE3UY8N1XaVSqalHJpORaZoLqQEIS5TjLeqxDsRV1GOD90FgHJ8TY8IDEJh+v+9Vq1VP0tixt7e3sHN2Op3hecrl8oVtstmsJ8kzTdPr9/sLqwWIkziMjXq9fu56cNnR6/UCPz8QlijHWxzGOhBHcRgbvA8Cp/icGC8EYUBA6vW6Z5qml8/nQ7vA9ft9zzCM4cXrMr1eb1hLPp9fSC1AnMRlbAxqmHYwLpFkUY63uIx1IG7iMjZ4HwT4nBhHLI0EAmDbtvL5vHq9njqdjvb29kI5b6lUGk5jHUx3vYhpmioWi5JOp8c2m80wygMiE4ex0Ww25bquqtWqOp3OxKPVagV2XiBsUY63OIx1II7iMDZ4HwT4nBhXKc/zvKiLAJaNbdvK5XLD53t7eyqXy4Gew3EcZTKZ4fN+vy/DMC5t3263VSqVJEmGYajf7wdaDxAXcRkbgxp6vV4g/QFxFOV4i8tYB+ImLmOD90HgPD4nxgMzwoAFmHShCUq9Xh8+zufzU885SPql000aw7pDCRC2OIyNdrstx3Em/gscsAyiHG9xGOtAHMVhbPA+CFyMz4nxQBAGJNTotNVsNuvrNaN34/noo48CrwmIgziMjZ2dHRmGobt3787dFxBnUY63OIx1II7iMDZ4HwSiE4drQNwRhAEJZNv22PPXXnvN1+tGL4SrkPRj9cRhbNi2Ldu25bqu0um0MpmMKpUKYw5LJ8rxFoexDsRRHMYG74NAdOJwDUgCgjAggSzLGns+muBPcrbd2QslkHRxGBtnl4E4jqNms6lSqaRUKqVSqcTYw1KIcrzFYawDcRSHscH7IBCdOFwDkoAgDEigx48fjz33u9b8lVdeGXu+v78fVElALEQ9NhzHOfcLyFntdlu5XE6VSuVK5wDiIsrxFvVYB+Iq6rHB+yAQraivAUlxPeoCAMzOcZyx51dN+rmLD5ZN1GPDNE3t7e3JdV31ej1ZlnWupoFms6n9/X11u90rnQuIWpTjLeqxDsRV1GOD90EgWlFfA5KCIAxIoMt+oZiV67qB9APERRzGxtlbYLuuq2azqZ2dnXP92ratQqGgTqdz5fMBUYlyvMVhrANxFIexwfsgEJ04XAOSgKWRQAJd9cJ0dmrs0dHR/MUAMRLHsWEYhqrVqvr9vlqt1rlzWZalRqMR2PmAsEQ53uI41oE4iOPY4H0QCE8crwFxRBAGrLBlT/qBq1rU2CgWi/r888/P3cp6Z2dnIecDkiDK9yLeB4GL8T4IrLZlf38kCAMSyO+mh2H1A8RFEsaGYRjqdrtjHwJc1526uTAQN1GOtySMdSAKSRgbvA8Ci5OEa0AcEIRhKTWbTaVSqUCPXC4X9R9raGNjI1b9AH6EMS6TNDYePnw49pz9UZA0UY63JI11IExJGhu8DwLBS9I1IEoEYUACXTWhPzvFddmTfqyeJI2NbDarfD4/fB7U5qZAWKIcb0ka60CYkjQ2eB8Egpeka0CUuGskllI+n1er1Qq0zzhdDG7fvi3btofPXdf1Vd/ZTQ8zmUzQpQGXCmNcJm1sFAoFloIgsaIcb0kb60BYkjY2eB8EgpW0a0BUCMKwlEzTlGmaUZexMGeXgzmOc27T0Yv0er2x56P/CgcsWhjjMmljY/TnsexT0LF8ohxvSRvrQFiSNjZ4HwSClbRrQFRYGgkk0O3bt8ee+51KPjrl1TCMpQ4LsZqSNjZGzxOnWaeAH1GOt6SNdSAsSRsbvA8CwUraNSAqBGFAAmWz2bFfFh4/fuzrdfv7+8PHZy+SwDJI2tgYPW+hUAjtvEAQohxvSRvrQFiSNjZ4HwSClbRrQFQIwoCEunv37vDx6DrwSUbb1Wq1wGsC4iBJY2N0GvqyT0HHcopyvCVprANhStLY4H0QCF6SrgFRIQgDEqpSqQwf+9lkdLSNaZr8soGllaSx0W63JUnVajW0cwJBinK8JWmsA2FK0tjgfRAIXpKuAVEhCAMW4OztZ6+i2WyqVqtduq777C2nB79IXGb0bn2rkPJjdS1ybEwbl7Not9tyHEeGYejBgwdz9wdEIcrxxvsgcDHeB4H44nNiTHgAAtdqtTxJw6Ner8/0+nw+P/b6fr9/Ybterzdsk81mL+2v3+8P2+Xz+ZlqAZJoEWNj2rjsdDqeYRjDvrrd7sT6Bm0ntQOSIIrxtshzA8uA90EgnvicGA8EYUDA+v2+Z5rm2AVq0sXnIqOvleTt7e1d2nb0YnrZhTSbzXqSPMMwLr1YAssm6LExbVyWy+Vzbcrl8rl+Bh8UTNP0er3elf98QJyEPd4WeW5gWfA+CMQLnxPjgyAMCEC/3/eKxeK5hP7skc/nvWKxOPVfvgb/QjY4Op3OxPaj/wI36L/f73udTmd4cctmsyt1cQM8L9ixMW1cdjqdC8e9YRhesVj0yuXy8JzVapXxiKUT5nhb5LmBZcL7IBAtPifGE0EYEEOdTsczTdMzDMOrVqu+X1ev171sNju82BmG4eXzea/Vai2wWiD+ghgbfsZlr9fzyuXysN3gXKZpesVi0Wu1Wiv3iwZWT1jjbVHnBpYR74PAcuD9MRgpz/M8AQAAAAAAAEuOu0YCAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAABgJRCEAQAAAAAAYCUQhAEAAAAAAGAlEIQBAAAAAAAsgXQ6Lcdxoi4j1gjCAAAAAAAAEq7RaMh1Xe3t7UVdSqylPM/zoi4CAAAAAAAAV5fJZOQ4jgzDUL/fj7qc2GJGGAAAAAAAQIK12+3hkkjXddVutyOuKL6YEQYAAAAAAJBguVxOtm0Pn2ezWXW73Qgrii9mhAEAAAAAACSUbdtjIdhlX8MpgjAAAAAAAICE2tnZufDrQW+a77qums1moH1GgaWRAAAAAAAACeS6rtLptCSp1WqpVCqNfT+oyMd1XeVyOWWzWbVarUD6jAozwgAAAAAAABJoMBusXC6rWCzKNM2x7wcxg8t1Xd25c0eO46hQKMzdX9SYEQYAAAAAAJBA6XRaruuq1+vJNE01m01VKpXh903TVK/Xm+scoxvx9/t9GYYxV39RY0YYAAAAAABAwjSbTbmuq3w+P5wJVi6Xx9o4jiPLsq7Uv23bymQywxDMNM3Eh2ASQRgAAAAAAEDi1Ot1SVKtVhv7+tkwbNZN823bVqlUUi6Xk+M4w68bhqFmszk8koqlkQAAAAAAAAliWZYKhcKFSx9t21Yulxv7mt8lje12+9yG+xcxDEP9fn+mmuOCGWEAAAAAAAAJctlsMEnKZrPKZrNjX/M7g6tYLMrzPHmep06nM/a9wdc9z0tsCCYRhAEAAAAAACTGYN8vwzDOLYMcGN0wX/rD3SVn0Wq1ho/PBmtJRhAGAAAAAACQEIPZYJeFYIPvjS6FdF1X7XZ7pvOMbrJ/79692YqMMfYIAwAAAAAASADXdZVOpyVN3/erUqmMLYnM5/Pnljv6OY8kdbvdpZkVxowwAAAAAACABBgEW8Vicerm92f3D7Msa+wukJOMzgaTWBoJAAAAAACAkA32+nrw4MHUtqZpnguwBssqpxmdOZbP52eoMP4IwgAAAAAAAGKu3W7Ldd0L7wp5mbOBmd+7R3788cfDx6VSyX+RCUAQBgAAAAAAEHOzzAYbuGgJ5bQwzHEcua47fM6MMAAAAAAAAITGtm3Zti3DMFQsFmd67dm7S+7t7U1sP7o/mGEYMk1zpvPFHUEYAAAAAABAjF1lNthApVIZez4I1S6zzPuDSQRhAAAAAAAAseW6rtrttqTzs7v8ME3zXKA1CNYuMjoj7N69e77O4TiOGo2GCoWC0um0CoXC2Pdd11WpVFI6nVaj0Zih+uARhAEAAAAAAMTUILQql8vn9vvy6+yssMHG+2dddX8wy7KUz+dVKBTkuq4syxrOOnNdV7lcTrZty3XdsRlnUSAIAwAAAAAAiKnB5va1Wu3KffjdNH8w80w6nUk2+ppJm+yXy2Vls1lVq9Xh1wYzy0qlklqtlnq9nnq9HkEYAAAAAAAAzms2m3JdV/l8fu5N6/1smn/Z/mCzLGccvK7T6ajRaKhUKimbzUpSLDbeJwgDAAAAAACIoXq9Lmm+2WADZzfadxxnbD8waXx/sME+X+12W51Ox/f+ZIPXWZY10+vCcj3qAgAAAAAAADDOsiw5jiPp/B5fQanX68MZXGfvJPn48WMdHR1pb29Pjx498t3n6EyyQZAXJwRhAAAAAAAAMTMaIg0CsaANwjbTNM+do9FoyDRNdbvdmTbpHyyDlKSjo6OgSg0MSyMBAAAAAABiptPpyPO8hR+DfbuKxeLwzpSmaapararX6818p8rRQC3qjfEvkvI8z4u6CAAAAAAAACRfLpfTxsaGLMtSNptVt9uNuqQxBGEAAAAAAACYW6VSUS6Xk2maw03z4xY7sTQSAAAAAAAAc7EsS0dHRyqXy7p9+/bw66Ob8DebzShKG0MQBgAAAAAAgJm4rivLsiSd7gtWr9fVarUkSYZhDDfN39vbk3Q6W2w0IIsKQRgAAAAAAABmUiqVVCgUlE6nVSgUhiHYQD6fl3Q6CyyTySiXy43dUTIqBGEAAAAAAACYSalUkmEY2tjYUKfTOXd3yQcPHsg0TRmGoUqlonK5HE2hZ7BZPgAAAAAAAFYCM8IAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBIIwgAAAAAAALASCMIAAAAAAACwEgjCAAAAAAAAsBL+P6FythAlUcIXAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -173,17 +289,15 @@
     }
    ],
    "source": [
-    "bins = np.linspace(-1, 1, 50)\n",
+    "bins = np.linspace(-1.0, 1.0, 50)\n",
     "sns.regplot(\n",
-    "    x=ak.to_numpy(array[\"dSlope_xEndT\"]),\n",
-    "    y=ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"dSlope_xEndT\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
     "    x_bins=bins,\n",
     "    fit_reg=None,\n",
     "    x_estimator=np.mean,\n",
     ")\n",
-    "plt.ylim(5100, 5700)\n",
-    "\n",
-    "plt.xlabel(\"$\\Delta$dx/dz\")\n",
+    "plt.xlabel(\"$\\Delta t_x$\")\n",
     "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
     "mplhep.lhcb.text(\"Simulation\")\n",
     "plt.show()"
@@ -191,67 +305,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 71,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# # import matplotlib.pyplot as plt\n",
-    "# bins = np.linspace(-2000, 2000, 50)\n",
-    "# sns.regplot(\n",
-    "#     x=ak.to_numpy(array[\"x_l0\"]),\n",
-    "#     y=ak.to_numpy(array[\"z_mag_x_fringe\"]),\n",
-    "#     x_bins=50,\n",
-    "#     fit_reg=None,\n",
-    "#     x_estimator=np.mean,\n",
-    "#     label=\"T1X1\",\n",
-    "# )\n",
-    "# sns.regplot(\n",
-    "#     x=ak.to_numpy(array[\"x_l4\"]),\n",
-    "#     y=ak.to_numpy(array[\"z_mag_x_fringe\"]),\n",
-    "#     x_bins=50,\n",
-    "#     fit_reg=None,\n",
-    "#     x_estimator=np.mean,\n",
-    "#     label=\"T2X1\",\n",
-    "# )\n",
-    "# sns.regplot(\n",
-    "#     x=ak.to_numpy(array[\"x_l8\"]),\n",
-    "#     y=ak.to_numpy(array[\"z_mag_x_fringe\"]),\n",
-    "#     x_bins=50,\n",
-    "#     fit_reg=None,\n",
-    "#     x_estimator=np.mean,\n",
-    "#     label=\"T3X1\",\n",
-    "# )\n",
-    "# plt.legend()\n",
-    "# plt.xlabel(\"x [mm]\")\n",
-    "# plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
-    "# mplhep.lhcb.text(\"Simulation\")"
+    "bins = np.linspace(-0.5, 0.5, 100)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"dSlope_yEndT\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_xEndT\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"$\\Delta t_y$\")\n",
+    "plt.ylabel(\"$z_{Mag}$ [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['ideal_state_770_tx' 'dSlope_xEndT' 'dSlope_xEndT_abs' 'x_EndT_abs'\n",
-      " 'ideal_state_770_tx^2' 'ideal_state_770_tx dSlope_xEndT'\n",
-      " 'ideal_state_770_tx dSlope_xEndT_abs' 'ideal_state_770_tx x_EndT_abs'\n",
-      " 'dSlope_xEndT^2' 'dSlope_xEndT dSlope_xEndT_abs'\n",
-      " 'dSlope_xEndT x_EndT_abs' 'dSlope_xEndT_abs^2'\n",
-      " 'dSlope_xEndT_abs x_EndT_abs' 'x_EndT_abs^2']\n",
-      "intercept= 5092.708143256812\n",
-      "coef= {'ideal_state_770_tx': 2018.6886668629327, 'dSlope_xEndT': 389.7888543955816, 'dSlope_xEndT_abs': 1464.867616153959, 'x_EndT_abs': 0.09763035198073229, 'ideal_state_770_tx^2': -4259.173364636334, 'ideal_state_770_tx dSlope_xEndT': 887.6220587366868, 'ideal_state_770_tx dSlope_xEndT_abs': -677.4689885623392, 'ideal_state_770_tx x_EndT_abs': -0.9313147953743464, 'dSlope_xEndT^2': 179.9382929971653, 'dSlope_xEndT dSlope_xEndT_abs': 88.39317926994904, 'dSlope_xEndT x_EndT_abs': -0.19078236037510163, 'dSlope_xEndT_abs^2': 2.3666592074995823, 'dSlope_xEndT_abs x_EndT_abs': -0.48044427953929886, 'x_EndT_abs^2': 5.0288654463924435e-06}\n",
-      "r2 score= -0.09609938850755273\n",
-      "RMSE = 356.01344182664485\n"
+      "intercept= 5303.132333467949\n",
+      "coef= {'ideal_state_770_tx': -13.441950438394027, 'dSlope_xEndT': -4.369407701653064, 'dSlope_xEndT_abs': 230.37763264120008, 'x_EndT_abs': 0.026704166547390083, 'ideal_state_770_ty': -14.30702118941663, 'ideal_state_770_tx^2': 77928.66766333766, 'ideal_state_770_tx dSlope_xEndT': 69687.8060631645, 'ideal_state_770_tx dSlope_xEndT_abs': -86.35194840522867, 'ideal_state_770_tx x_EndT_abs': 0.00970580581706756, 'ideal_state_770_tx ideal_state_770_ty': -180.61816411073835, 'dSlope_xEndT^2': 7579.721527263535, 'dSlope_xEndT dSlope_xEndT_abs': -49.35311026671389, 'dSlope_xEndT x_EndT_abs': 0.015857700483615466, 'dSlope_xEndT ideal_state_770_ty': -35.74149120660231, 'dSlope_xEndT_abs^2': 7579.723402132595, 'dSlope_xEndT_abs x_EndT_abs': -0.22195273681292957, 'dSlope_xEndT_abs ideal_state_770_ty': 1.9491174288661794, 'x_EndT_abs^2': -0.0009034030507007965, 'x_EndT_abs ideal_state_770_ty': 0.0034286491846703187, 'ideal_state_770_ty^2': -2489.6827607187365, 'ideal_state_770_tx^3': 2357.797471515544, 'ideal_state_770_tx^2 dSlope_xEndT': 1960.401925113787, 'ideal_state_770_tx^2 dSlope_xEndT_abs': -20252.830218161023, 'ideal_state_770_tx^2 x_EndT_abs': -13.500325039413802, 'ideal_state_770_tx^2 ideal_state_770_ty': -766.130872351457, 'ideal_state_770_tx dSlope_xEndT dSlope_xEndT_abs': -19474.231043469852, 'ideal_state_770_tx dSlope_xEndT x_EndT_abs': -11.598943144027315, 'ideal_state_770_tx dSlope_xEndT ideal_state_770_ty': -626.8199943500564, 'ideal_state_770_tx dSlope_xEndT_abs^2': 573.5326109010182, 'ideal_state_770_tx dSlope_xEndT_abs x_EndT_abs': 0.001095488438740151, 'ideal_state_770_tx dSlope_xEndT_abs ideal_state_770_ty': 330.5306955155975, 'ideal_state_770_tx x_EndT_abs^2': -3.111920124211576e-05, 'ideal_state_770_tx x_EndT_abs ideal_state_770_ty': 0.06268520395759442, 'ideal_state_770_tx ideal_state_770_ty^2': 95.20495106050294, 'dSlope_xEndT^3': 42.93032905404232, 'dSlope_xEndT^2 dSlope_xEndT_abs': -4365.747480960424, 'dSlope_xEndT^2 x_EndT_abs': -1.2192562284269424, 'dSlope_xEndT^2 ideal_state_770_ty': -134.19763413582538, 'dSlope_xEndT dSlope_xEndT_abs^2': 42.930335617557944, 'dSlope_xEndT dSlope_xEndT_abs x_EndT_abs': -0.023890507178523725, 'dSlope_xEndT dSlope_xEndT_abs ideal_state_770_ty': 106.84806568209468, 'dSlope_xEndT x_EndT_abs ideal_state_770_ty': -0.009451904933143932, 'dSlope_xEndT ideal_state_770_ty^2': -8.505381537855747, 'dSlope_xEndT_abs^2 x_EndT_abs': -1.2193799254865163, 'dSlope_xEndT_abs x_EndT_abs^2': 0.0002552425918335738, 'dSlope_xEndT_abs x_EndT_abs ideal_state_770_ty': 0.01563137413267504, 'dSlope_xEndT_abs ideal_state_770_ty^2': 2033.0314554223403, 'x_EndT_abs^3': 1.5428826370868625e-07, 'x_EndT_abs^2 ideal_state_770_ty': 6.223748596200707e-06, 'x_EndT_abs ideal_state_770_ty^2': 0.5895518247828866}\n",
+      "r2 score= 0.8237497474212265\n",
+      "RMSE = 34.7702514276615\n"
      ]
     }
    ],
    "source": [
     "from sklearn.preprocessing import PolynomialFeatures\n",
-    "from sklearn.linear_model import LinearRegression, Lasso, Ridge\n",
+    "from sklearn.linear_model import LinearRegression, Lasso, Ridge, ElasticNet, LassoCV\n",
     "from sklearn.model_selection import train_test_split\n",
     "from sklearn.pipeline import Pipeline\n",
     "from sklearn.metrics import mean_squared_error\n",
@@ -262,34 +370,101 @@
     "    \"dSlope_xEndT\",\n",
     "    \"dSlope_xEndT_abs\",\n",
     "    \"x_EndT_abs\",\n",
+    "    # \"dSlope_yEndT\",\n",
+    "    # \"dSlope_yEndT_abs\",\n",
+    "    \"ideal_state_770_ty\",\n",
+    "    # \"ideal_state_9410_ty\",\n",
+    "    # \"ideal_state_770_x\",\n",
+    "    # \"x_EndVelo_abs\",\n",
     "]\n",
+    "\n",
     "target_feat = \"z_mag_xEndT\"\n",
+    "order = 3\n",
     "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(\n",
-    "    data, target, test_size=0.2, random_state=42\n",
-    ")\n",
+    "data = np.column_stack([ak.to_numpy(sel_array[feat]) for feat in features])\n",
+    "target = ak.to_numpy(sel_array[target_feat])\n",
+    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
+    "                                                    target,\n",
+    "                                                    test_size=0.2,\n",
+    "                                                    random_state=42)\n",
     "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
+    "poly = PolynomialFeatures(degree=order, include_bias=False)\n",
     "X_train_model = poly.fit_transform(X_train)\n",
     "X_test_model = poly.fit_transform(X_test)\n",
     "\n",
     "poly_features = poly.get_feature_names_out(input_features=features)\n",
+    "\n",
+    "keep = [\n",
+    "    \"ideal_state_770_tx\",\n",
+    "    \"dSlope_xEndT\",\n",
+    "    \"dSlope_xEndT_abs\",  # keep\n",
+    "    \"x_EndT_abs\",  # keep\n",
+    "    \"ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx^2\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT_abs\",\n",
+    "    \"ideal_state_770_tx x_EndT_abs\",\n",
+    "    \"ideal_state_770_tx ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT^2\",  # keep\n",
+    "    \"dSlope_xEndT dSlope_xEndT_abs\",\n",
+    "    \"dSlope_xEndT x_EndT_abs\",\n",
+    "    \"dSlope_xEndT ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT_abs^2\",\n",
+    "    \"dSlope_xEndT_abs x_EndT_abs\",\n",
+    "    \"dSlope_xEndT_abs ideal_state_770_ty\",\n",
+    "    \"x_EndT_abs^2\",\n",
+    "    \"x_EndT_abs ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_ty^2\",  # keep\n",
+    "    \"ideal_state_770_tx^3\",\n",
+    "    \"ideal_state_770_tx^2 dSlope_xEndT\",\n",
+    "    \"ideal_state_770_tx^2 dSlope_xEndT_abs\",\n",
+    "    \"ideal_state_770_tx^2 x_EndT_abs\",\n",
+    "    \"ideal_state_770_tx^2 ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT dSlope_xEndT_abs\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT x_EndT_abs\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT_abs^2\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT_abs x_EndT_abs\",\n",
+    "    \"ideal_state_770_tx dSlope_xEndT_abs ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx x_EndT_abs^2\",\n",
+    "    \"ideal_state_770_tx x_EndT_abs ideal_state_770_ty\",\n",
+    "    \"ideal_state_770_tx ideal_state_770_ty^2\",\n",
+    "    \"dSlope_xEndT^3\",\n",
+    "    \"dSlope_xEndT^2 dSlope_xEndT_abs\",\n",
+    "    \"dSlope_xEndT^2 x_EndT_abs\",\n",
+    "    \"dSlope_xEndT^2 ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT dSlope_xEndT_abs^2\",\n",
+    "    \"dSlope_xEndT dSlope_xEndT_abs x_EndT_abs\",\n",
+    "    \"dSlope_xEndT dSlope_xEndT_abs ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT x_EndT_abs ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT ideal_state_770_ty^2\",\n",
+    "    \"dSlope_xEndT_abs^2 x_EndT_abs\",\n",
+    "    \"dSlope_xEndT_abs x_EndT_abs^2\",\n",
+    "    \"dSlope_xEndT_abs x_EndT_abs ideal_state_770_ty\",\n",
+    "    \"dSlope_xEndT_abs ideal_state_770_ty^2\",\n",
+    "    \"x_EndT_abs^3\",\n",
+    "    \"x_EndT_abs^2 ideal_state_770_ty\",\n",
+    "    \"x_EndT_abs ideal_state_770_ty^2\",\n",
+    "]\n",
+    "\n",
     "# keep = [\n",
     "#     \"ideal_state_770_tx^2\",\n",
     "#     \"dSlope_xEndT^2\",\n",
     "#     \"dSlope_xEndT_abs\",\n",
     "#     \"x_EndT_abs\",\n",
     "# ]\n",
-    "# remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
-    "# X_train_model = np.delete(X_train_model, remove, axis=1)\n",
-    "# X_test_model = np.delete(X_test_model, remove, axis=1)\n",
-    "# poly_features = np.delete(poly_features, remove)\n",
-    "print(poly_features)\n",
+    "remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
     "\n",
-    "# lin_reg = LinearRegression()\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
+    "X_train_model = np.delete(X_train_model, remove, axis=1)\n",
+    "X_test_model = np.delete(X_test_model, remove, axis=1)\n",
+    "poly_features = np.delete(poly_features, remove)\n",
+    "# print(poly_features)\n",
+    "\n",
+    "lin_reg = LinearRegression()\n",
+    "# lin_reg = Lasso(alpha=0.1)\n",
+    "# lin_reg = LassoCV(max_iter=2000)\n",
+    "# lin_reg = ElasticNet(alpha=0.1)\n",
+    "# lin_reg = Ridge(alpha=0)\n",
     "lin_reg.fit(X_train_model, y_train)\n",
     "y_pred_test = lin_reg.predict(X_test_model)\n",
     "print(\"intercept=\", lin_reg.intercept_)\n",
@@ -300,23 +475,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(exptext: Custom Text(0.0, 1, 'LHCb'),\n",
-       " expsuffix: Custom Text(0.0, 1.005, 'Simulation'))"
+       "['ideal_state_770_tx x_EndT_abs^2',\n",
+       " 'dSlope_xEndT x_EndT_abs^2',\n",
+       " 'x_EndT_abs^3',\n",
+       " 'x_EndT_abs^2 ideal_state_770_ty']"
       ]
      },
-     "execution_count": 72,
+     "execution_count": 77,
      "metadata": {},
      "output_type": "execute_result"
-    },
+    }
+   ],
+   "source": [
+    "koeffs = dict(zip(poly_features, lin_reg.coef_))\n",
+    "\n",
+    "remove = []\n",
+    "for itr in koeffs.items():\n",
+    "    if abs(itr[1]) < 1e-4:\n",
+    "        remove.append(itr[0])\n",
+    "remove"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ls_koeffs = []\n",
+    "for itr in koeffs.items():\n",
+    "    ls_koeffs.append(itr[0])\n",
+    "ls_koeffs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1200x900 with 2 Axes>"
       ]
@@ -326,7 +538,7 @@
     }
    ],
    "source": [
-    "bins = np.linspace(5150, 5300, 30)\n",
+    "bins = np.linspace(5150, 5700, 50)\n",
     "ax = sns.regplot(\n",
     "    x=y_test,\n",
     "    y=abs(y_test - y_pred_test),\n",
@@ -336,16 +548,12 @@
     "    label=\"bla\",\n",
     ")\n",
     "ax2 = ax.twinx()\n",
-    "ax2.hist(y_test,\n",
-    "         bins=30,\n",
-    "         range=[5150, 5300],\n",
-    "         color=\"#2A9D8F\",\n",
-    "         alpha=0.8,\n",
-    "         align=\"left\")\n",
+    "ax2.hist(y_test, bins=50, range=[5150, 5700], color=\"#2A9D8F\", alpha=0.8, align=\"left\")\n",
     "ax.set_xlabel(r\"z$_{Mag}$ [mm]\")\n",
     "ax.set_ylabel(\"Mean Deviation [mm]\")\n",
     "ax2.set_ylabel(\"Number of Tracks\")\n",
-    "mplhep.lhcb.text(\"Simulation\", loc=0)"
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()"
    ]
   },
   {
@@ -354,9 +562,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "median_z_mag_x = np.median(array[\"z_mag_x_fringe\"])\n",
-    "print(median_z_mag_x)\n",
-    "params_per_layer = [[] for _ in range(12)]"
+    "fig = plt.figure()\n",
+    "plt.hist(\n",
+    "    sel_array[\"z_mag_corr\"],\n",
+    "    bins=100,\n",
+    "    # range=[5100, 5700],\n",
+    "    color=\"#2A9D8F\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.xlabel(r\"z$_{Mag}$ correction [mm]\")\n",
+    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -365,12 +582,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def format_array(name, intercept, coef):\n",
-    "    coef = [str(c) + \"f\" for c in coef if c != 0.0]\n",
-    "    intercept = str(intercept) + \"f\"\n",
-    "    code = f\"constexpr std::array {name}\"\n",
-    "    code += \"{\" + \", \".join([intercept] + list(coef)) + \"};\"\n",
-    "    return code"
+    "bins = np.linspace(-0.4, 0.4, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_tx\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "# plt.ylim(5100, 5700)\n",
+    "plt.xlabel(\"dx/dz(VELO)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -379,54 +603,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_diff_straight_l0\"] = (array[\"x_l0\"] - array[\"x\"] - array[\"tx\"] *\n",
-    "                               (array[\"z_l0\"] - array[\"z\"]))\n",
-    "array[\"x_l0_rel\"] = array[\"x_l0\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    # \"x_l0_rel\",\n",
-    "    \"x_diff_straight_l0\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "poly_features = poly.get_feature_names_out(input_features=features)\n",
-    "keep = [\n",
-    "    # \"tx\",\n",
-    "    # \"ty\",\n",
-    "    # \"x_l0_rel\",\n",
-    "    \"tx^2\",\n",
-    "    # \"tx x_l0_rel\",\n",
-    "    \"tx x_diff_straight_l0\",\n",
-    "    \"ty^2\",\n",
-    "    # \"x_l0_rel^2\"\n",
-    "    \"x_diff_straight_l0^2\",\n",
-    "]\n",
-    "remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
-    "X_train_model = np.delete(X_train_model, remove, axis=1)\n",
-    "X_test_model = np.delete(X_test_model, remove, axis=1)\n",
-    "poly_features = np.delete(poly_features, remove)\n",
-    "print(poly_features)\n",
+    "bins = np.linspace(-0.25, 0.25, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_ty\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "# plt.ylim(4500, 5700)\n",
     "\n",
-    "lin_reg = LinearRegression()  # Lasso(alpha=0.004)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\"coef=\", dict(zip(poly_features, lin_reg.coef_)))\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l0\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[0] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"dy/dz(VELO)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -435,45 +625,41 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l1_rel\"] = array[\"x_l1\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l1_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(-0.25, 0.25, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_9410_ty\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l1\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[1] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "# plt.ylim(4500, 5700)\n",
+    "\n",
+    "plt.xlabel(\"dy/dz(T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": []
+   "outputs": [],
+   "source": [
+    "bins = np.linspace(-300, 300, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"ideal_state_770_x\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    ")\n",
+    "plt.xlabel(\"x (VELO)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
+   ]
   },
   {
    "cell_type": "code",
@@ -481,162 +667,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l2_rel\"] = array[\"x_l2\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l2_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
-    ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l2\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[2] = [lin_reg.intercept_] + list(lin_reg.coef_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "array[\"x_l3_rel\"] = array[\"x_l3\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l3_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
-    ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l3\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[3] = [lin_reg.intercept_] + list(lin_reg.coef_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "array[\"x_l4_rel\"] = array[\"x_l4\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l4_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
-    ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l4\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[4] = [lin_reg.intercept_] + list(lin_reg.coef_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "array[\"x_l5_rel\"] = array[\"x_l5\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l5_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(0, 500, 50)\n",
+    "sns.regplot(\n",
+    "    # x=ak.to_numpy(sel_array[\"ideal_state_770_y\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"x_EndT_abs\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l5\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[5] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"x (T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -645,39 +688,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l6_rel\"] = array[\"x_l6\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l6_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(0, 500, 50)\n",
+    "sns.regplot(\n",
+    "    # x=ak.to_numpy(sel_array[\"ideal_state_770_y\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"y_EndVelo_abs\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l6\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[6] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"y (VELO)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -686,39 +709,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l7_rel\"] = array[\"x_l7\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l7_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(0, 500, 50)\n",
+    "sns.regplot(\n",
+    "    # x=ak.to_numpy(sel_array[\"ideal_state_770_y\"]),\n",
+    "    x=ak.to_numpy(sel_array[\"y_EndT_abs\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l7\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[7] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"y (T)\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -727,39 +730,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l8_rel\"] = array[\"x_l8\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l8_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(-1.0, 1.0, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"dSlope_xEndT\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l8\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[8] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"$\\Delta t_x$\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -768,39 +750,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l9_rel\"] = array[\"x_l9\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l9_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
+    "bins = np.linspace(-1.0, 1.0, 50)\n",
+    "sns.regplot(\n",
+    "    x=ak.to_numpy(sel_array[\"dSlope_yEndT_abs\"]),\n",
+    "    y=ak.to_numpy(sel_array[\"z_mag_corr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
     ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l9\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[9] = [lin_reg.intercept_] + list(lin_reg.coef_)"
+    "plt.xlabel(\"$\\Delta t_y$\")\n",
+    "plt.ylabel(\"$z_{Mag}$ correction [mm]\")\n",
+    "mplhep.lhcb.text(\"Simulation\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -809,130 +770,77 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "array[\"x_l10_rel\"] = array[\"x_l10\"] / 3000\n",
     "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l10_rel\",\n",
+    "    # # \"ideal_state_770_tx\",\n",
+    "    # \"ideal_state_770_ty\",\n",
+    "    # \"ideal_state_9410_ty\",\n",
+    "    # # \"dSlope_yEndT\",\n",
+    "    # # \"dSlope_yEndT_abs\",\n",
+    "    # # \"ideal_state_770_x\",\n",
+    "    # # \"ideal_state_9410_x\",\n",
+    "    # # \"x_EndVelo_abs\",\n",
+    "    # \"y_EndVelo_abs\",\n",
+    "    # # \"y_EndT_abs\",\n",
+    "    # \"dSlope_xEndT\",\n",
+    "    # \"dSlope_xEndT_abs\",\n",
+    "    # \"x_EndT_abs\",\n",
+    "    \"ideal_state_770_tx\",\n",
+    "    \"ideal_state_770_ty\",\n",
+    "    \"ideal_state_9410_ty\",\n",
+    "    \"ideal_state_9410_tx\",\n",
+    "    \"dSlope_xEndT\",\n",
+    "    \"dSlope_xEndT_abs\",\n",
+    "    \"x_EndT_abs\",\n",
+    "    \"ideal_state_770_x\",\n",
+    "    \"x_EndVelo_abs\",\n",
     "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
-    "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
     "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
-    ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l10\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[10] = [lin_reg.intercept_] + list(lin_reg.coef_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "array[\"x_l11_rel\"] = array[\"x_l11\"] / 3000\n",
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"x_l11_rel\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
+    "target_feat = \"z_mag_corr\"\n",
+    "order = 4\n",
     "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
+    "data = np.column_stack([ak.to_numpy(sel_array[feat]) for feat in features])\n",
+    "target = ak.to_numpy(sel_array[target_feat])\n",
     "X_train, X_test, y_train, y_test = train_test_split(data,\n",
     "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
+    "                                                    test_size=0.1,\n",
     "                                                    random_state=42)\n",
     "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
+    "poly = PolynomialFeatures(degree=order, include_bias=True)\n",
     "X_train_model = poly.fit_transform(X_train)\n",
     "X_test_model = poly.fit_transform(X_test)\n",
     "\n",
-    "lin_reg = Lasso(alpha=0.01)\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"intercept=\", lin_reg.intercept_)\n",
-    "print(\n",
-    "    \"coef=\",\n",
-    "    dict(\n",
-    "        zip(poly.get_feature_names_out(input_features=features),\n",
-    "            lin_reg.coef_)),\n",
-    ")\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_l11\", lin_reg.intercept_, lin_reg.coef_))\n",
-    "params_per_layer[11] = [lin_reg.intercept_] + list(lin_reg.coef_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "features = [\n",
-    "    \"tx\",\n",
-    "    \"ty\",\n",
-    "    \"dSlope_fringe\",\n",
-    "]\n",
-    "target_feat = \"z_mag_x_fringe\"\n",
-    "\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(data,\n",
-    "                                                    target,\n",
-    "                                                    test_size=0.2,\n",
-    "                                                    random_state=42)\n",
+    "poly_features = poly.get_feature_names_out(input_features=features)\n",
     "\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
+    "# keep = [\n",
+    "#     \"ideal_state_770_tx^2\",\n",
+    "#     \"ideal_state_770_x\",\n",
+    "#     # \"x_EndVelo_abs\",\n",
+    "#     \"dSlope_xEndT^2\",\n",
+    "#     \"dSlope_xEndT_abs\",\n",
+    "#     \"x_EndT_abs\",\n",
+    "# ]\n",
+    "# remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
+    "# remove_term = [\n",
+    "#     \"ideal_state_770_x^2 ideal_state_9410_x\",\n",
+    "# ]\n",
+    "# remove = [i for i, f in enumerate(poly_features) if f in remove_term]\n",
     "\n",
-    "poly_features = poly.get_feature_names_out(input_features=features)\n",
-    "keep = [\n",
-    "    # \"tx\",\n",
-    "    # \"ty\",\n",
-    "    # \"dSlope_fringe\",\n",
-    "    \"tx^2\",\n",
-    "    \"tx dSlope_fringe\",\n",
-    "    \"ty^2\",\n",
-    "    \"dSlope_fringe^2\",\n",
-    "]\n",
-    "remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
-    "X_train_model = np.delete(X_train_model, remove, axis=1)\n",
-    "X_test_model = np.delete(X_test_model, remove, axis=1)\n",
-    "poly_features = np.delete(poly_features, remove)\n",
-    "print(poly_features)\n",
+    "# X_train_model = np.delete(X_train_model, remove, axis=1)\n",
+    "# X_test_model = np.delete(X_test_model, remove, axis=1)\n",
+    "# poly_features = np.delete(poly_features, remove)\n",
+    "# print(poly_features)\n",
     "\n",
-    "lin_reg = LinearRegression()  # Lasso(alpha=0.01)\n",
+    "# lin_reg = LinearRegression()\n",
+    "lin_reg = Lasso(alpha=0.1, max_iter=2000)\n",
+    "# lin_reg = LassoCV()\n",
+    "# lin_reg = ElasticNet(alpha=1)\n",
+    "# lin_reg = Ridge(alpha=1)\n",
     "lin_reg.fit(X_train_model, y_train)\n",
     "y_pred_test = lin_reg.predict(X_test_model)\n",
     "print(\"intercept=\", lin_reg.intercept_)\n",
     "print(\"coef=\", dict(zip(poly_features, lin_reg.coef_)))\n",
     "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
-    "print(format_array(\"zMagnetParams_dSlope\", lin_reg.intercept_, lin_reg.coef_))"
+    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))"
    ]
   },
   {
@@ -941,18 +849,27 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import scipy.optimize\n",
-    "\n",
-    "\n",
-    "def parabola(x, a, b, c):\n",
-    "    return a * x**2 + b * x + c\n",
-    "\n",
-    "\n",
-    "params_1 = np.array([p[1] / params_per_layer[0][1] for p in params_per_layer])\n",
-    "x = [array[f\"z_l{n}\"][0] - array[\"z_ref\"][0] for n in range(12)]\n",
-    "print(params_1)\n",
-    "print(x)\n",
-    "plt.plot(x, params_1, \"o\")"
+    "bins = np.linspace(-200, 200, 50)\n",
+    "ax = sns.regplot(\n",
+    "    x=y_test,\n",
+    "    y=abs(y_test - y_pred_test),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    "    label=\"bla\",\n",
+    ")\n",
+    "ax2 = ax.twinx()\n",
+    "ax2.hist(y_test,\n",
+    "         bins=30,\n",
+    "         range=[-200, 200],\n",
+    "         color=\"#2A9D8F\",\n",
+    "         alpha=0.8,\n",
+    "         align=\"left\")\n",
+    "ax.set_xlabel(r\"z$_{Mag}$ correction [mm]\")\n",
+    "ax.set_ylabel(\"Mean Deviation [mm]\")\n",
+    "ax2.set_ylabel(\"Number of Tracks\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()"
    ]
   },
   {
@@ -960,44 +877,14 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "params_3 = np.array([params_per_layer[0][3] / p[3] for p in params_per_layer])\n",
-    "x = [array[f\"z_l{n}\"][0] - array[\"z_ref\"][0] for n in range(12)]\n",
-    "print(params_3**2)\n",
-    "print(x)\n",
-    "plt.plot(x, params_3, \"o\")"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from sklearn.preprocessing import PolynomialFeatures\n",
-    "from sklearn.linear_model import LinearRegression, Lasso\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.metrics import mean_squared_error\n",
-    "\n",
-    "feautures = [\"tx\", \"ty\", \"dSlope\"]\n",
-    "data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
-    "target = ak.to_numpy(array[target_feat])\n",
-    "X_train, X_test, y_train, y_test = train_test_split(\n",
-    "    data,\n",
-    "    target,\n",
-    "    test_size=0.2,\n",
-    "    random_state=42,\n",
-    ")\n",
-    "poly = PolynomialFeatures(degree=2, include_bias=False)\n",
-    "X_train_model = poly.fit_transform(X_train)\n",
-    "X_test_model = poly.fit_transform(X_test)\n",
-    "lin_reg = LinearRegression()  # or Lasso if regularisation is needed\n",
-    "lin_reg.fit(X_train_model, y_train)\n",
-    "y_pred_test = lin_reg.predict(X_test_model)\n",
-    "print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
-    "print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))"
-   ]
+   "source": []
   }
  ],
  "metadata": {
diff --git a/parameterisations/parameterise_magnet_kink_electron.py b/parameterisations/parameterise_magnet_kink_electron.py
index adde60a..582d117 100644
--- a/parameterisations/parameterise_magnet_kink_electron.py
+++ b/parameterisations/parameterise_magnet_kink_electron.py
@@ -43,6 +43,8 @@ def parameterise_magnet_kink(
         + array["ideal_state_9410_tx"] * array["ideal_state_9410_z"]
     ) / array["dSlope_xEndT"]
 
+    # array = array[(array["z_mag_xEndT"] < 5500) & (array["z_mag_xEndT"] > 5000)]
+
     model_endt, poly_features_endt = fit_linear_regression_model(
         array,
         target_feat="z_mag_xEndT",
diff --git a/parameterisations/parameterise_track_model_electron.py b/parameterisations/parameterise_track_model_electron.py
index 93c18ae..fb75759 100644
--- a/parameterisations/parameterise_track_model_electron.py
+++ b/parameterisations/parameterise_track_model_electron.py
@@ -54,8 +54,10 @@ def parameterise_track_model(
             "dSlope_yEndT",
         ],
         keep=[
-            "ideal_state_770_ty dSlope_yEndT^2",
-            "ideal_state_770_ty dSlope_xEndT^2",
+            "dSlope_yEndT",  # keep
+            "dSlope_xEndT dSlope_yEndT",  # keep
+            "ideal_state_770_ty dSlope_xEndT^2",  # keep
+            "ideal_state_770_ty dSlope_yEndT^2",  # keep
         ],
         degree=3,
         fit_intercept=False,
diff --git a/parameterisations/result/track_model_params_electron.hpp b/parameterisations/result/track_model_params_electron.hpp
index e1002c3..e1d6d43 100644
--- a/parameterisations/result/track_model_params_electron.hpp
+++ b/parameterisations/result/track_model_params_electron.hpp
@@ -1,7 +1,9 @@
-// param[0]*ideal_state_770_ty dSlope_xEndT^2 + param[1]*ideal_state_770_ty
+// param[0]*dSlope_yEndT + param[1]*dSlope_xEndT dSlope_yEndT +
+// param[2]*ideal_state_770_ty dSlope_xEndT^2 + param[3]*ideal_state_770_ty
 // dSlope_yEndT^2
-static constexpr std::array<float, 2> bendYParamsMatch{-1604.57100708853f,
-                                                       66.0556032125645f};
+static constexpr std::array<float, 4> bendYParamsMatch{
+    4378.628600433391f, 38.37918880066809f, 1223.4312216138976f,
+    -18070.58880714184f};
 // param[0]*dSlope_yEndT + param[1]*ideal_state_770_ty dSlope_xEndT_abs +
 // param[2]*ideal_state_770_ty dSlope_yEndT_abs + param[3]*ideal_state_770_ty
 // ideal_state_770_tx dSlope_xEndT + param[4]*ideal_state_770_ty dSlope_xEndT^2
@@ -10,6 +12,6 @@ static constexpr std::array<float, 2> bendYParamsMatch{-1604.57100708853f,
 // dSlope_xEndT_abs + param[8]*ideal_state_770_ty^3 ideal_state_770_tx
 // dSlope_xEndT
 static constexpr std::array<float, 9> bendYParams{
-    292.25509372378673f, -102.98897190277876f, -3210.784313935311f,
-    5496.265661754457f,  -296.2025342631322f,  4252.751889560355f,
-    621.5026566906829f,  2860.5216504191094f,  25376.702017410385f};
+    2728.3487088712513f, 175.88471572180072f, -1794.526612484905f,
+    2743.4537706915407f, 460.1711356139729f,  41200.84474708236f,
+    3211.085060418981f,  -399.0908682713831f, 21207.05933957606f};
diff --git a/parameterisations/result/z_mag_kink_params_electron.hpp b/parameterisations/result/z_mag_kink_params_electron.hpp
index f840ba6..64e2b31 100644
--- a/parameterisations/result/z_mag_kink_params_electron.hpp
+++ b/parameterisations/result/z_mag_kink_params_electron.hpp
@@ -1,5 +1,5 @@
 // param[0] + param[1]*dSlope_xEndT_abs + param[2]*x_EndT_abs +
 // param[3]*ideal_state_770_tx^2 + param[4]*dSlope_xEndT^2
 static constexpr std::array<float, 5> zMagnetParamsEndT{
-    5182.686831161441f, 751.3593035656784f, 0.013739767853469087f,
-    -3123.1016408330274f, -41.266857851983644f};
+    5309.217539295354f, 37.908060765784256f, 0.011167156481561233f,
+    -1735.25693147613f, 293.74242595645825f};