From 3b47f8c993f08cfb5763e0a986d76e85f409414c Mon Sep 17 00:00:00 2001
From: rdingjin <rebekah.dingjin26@imperial.ac.uk>
Date: Tue, 26 May 2026 15:23:39 +0000
Subject: [PATCH] 13. 60D06-GAL4>UAS-ChRmine-attP5 with Red Stimulus and ATR

---
 13.60D05_ChRmine_Red_ATR.ipynb | 1045 ++++++++++++++++++++++++++++++++
 1 file changed, 1045 insertions(+)
 create mode 100644 13.60D05_ChRmine_Red_ATR.ipynb

diff --git a/13.60D05_ChRmine_Red_ATR.ipynb b/13.60D05_ChRmine_Red_ATR.ipynb
new file mode 100644
index 0000000..1710cd2
--- /dev/null
+++ b/13.60D05_ChRmine_Red_ATR.ipynb
@@ -0,0 +1,1045 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "082de01c-5271-479e-a491-c6849725dd1e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Phase 7 ATR (60D05) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "272d85eb-2a89-4002-9dd5-b4cf35bfecd7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ethoscopy as etho\n",
+    "import pandas as pd\n",
+    "from scipy.stats import mannwhitneyu\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "from scipy.stats import wilcoxon, shapiro, ttest_rel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "bf4d6257-9a9c-44ab-8788-868423d472f9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.1.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "etho.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "43fdfbf9-d164-4708-9943-8b0f89f9341f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "meta = '/home/rdingjin/UASxGal4_ATR_2026-05-10/metadata_phase7_60D_pulse.csv' \n",
+    "local = '/mnt/ethoscope_results'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "134f43e0-0b2c-4adb-b1c5-eb03dabe56d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "metadata = etho.link_meta_index(meta, local)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "15ade560-4ff5-4355-a634-649b23cf98c7",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loading ROI_1 from ETHOSCOPE_130\n",
+      "Loading ROI_2 from ETHOSCOPE_130\n",
+      "Loading ROI_3 from ETHOSCOPE_130\n",
+      "Loading ROI_4 from ETHOSCOPE_130\n",
+      "Loading ROI_5 from ETHOSCOPE_130\n",
+      "Loading ROI_6 from ETHOSCOPE_130\n",
+      "Loading ROI_7 from ETHOSCOPE_130\n",
+      "Loading ROI_8 from ETHOSCOPE_130\n",
+      "Loading ROI_9 from ETHOSCOPE_130\n",
+      "Loading ROI_10 from ETHOSCOPE_130\n",
+      "Loading ROI_11 from ETHOSCOPE_130\n",
+      "Loading ROI_12 from ETHOSCOPE_130\n",
+      "Loading ROI_13 from ETHOSCOPE_130\n",
+      "Loading ROI_14 from ETHOSCOPE_130\n",
+      "Loading ROI_15 from ETHOSCOPE_130\n",
+      "Loading ROI_16 from ETHOSCOPE_130\n",
+      "Loading ROI_17 from ETHOSCOPE_130\n",
+      "Loading ROI_18 from ETHOSCOPE_130\n",
+      "Loading ROI_19 from ETHOSCOPE_130\n",
+      "Loading ROI_20 from ETHOSCOPE_130\n",
+      "Loading ROI_1 from ETHOSCOPE_302\n",
+      "Loading ROI_2 from ETHOSCOPE_302\n",
+      "Loading ROI_3 from ETHOSCOPE_302\n",
+      "Loading ROI_4 from ETHOSCOPE_302\n",
+      "Loading ROI_5 from ETHOSCOPE_302\n",
+      "Loading ROI_6 from ETHOSCOPE_302\n",
+      "Loading ROI_7 from ETHOSCOPE_302\n",
+      "Loading ROI_8 from ETHOSCOPE_302\n",
+      "Loading ROI_9 from ETHOSCOPE_302\n",
+      "Loading ROI_10 from ETHOSCOPE_302\n",
+      "Loading ROI_11 from ETHOSCOPE_302\n",
+      "Loading ROI_12 from ETHOSCOPE_302\n",
+      "Loading ROI_13 from ETHOSCOPE_302\n",
+      "Loading ROI_14 from ETHOSCOPE_302\n",
+      "Loading ROI_15 from ETHOSCOPE_302\n",
+      "Loading ROI_16 from ETHOSCOPE_302\n",
+      "Loading ROI_17 from ETHOSCOPE_302\n",
+      "Loading ROI_18 from ETHOSCOPE_302\n",
+      "Loading ROI_19 from ETHOSCOPE_302\n",
+      "Loading ROI_20 from ETHOSCOPE_302\n"
+     ]
+    }
+   ],
+   "source": [
+    "data = etho.load_ethoscope(metadata, reference_hour = 9.0, FUN = etho.sleep_annotation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "fe07151b-0b01-4695-8c00-4ca3120f5735",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = etho.behavpy(data, metadata, check = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "50c5c0bc-5eb9-4c34-9d0a-7ee9429df571",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_pickle('/home/rdingjin/UASxGal4_ATR_2026-05-10/phase7(60D)1.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "94ee2ec0-407d-4dea-b746-98ca9ca1186e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ethoscopy as etho\n",
+    "import pandas as pd\n",
+    "from scipy.stats import mannwhitneyu\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "from scipy.stats import wilcoxon, shapiro, ttest_rel\n",
+    "df = pd.read_pickle('/home/rdingjin/UASxGal4_ATR_2026-05-10/phase7(60D)1.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "e02f49df-5062-497d-a068-5b25269bab1a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = df.baseline(column = 'baseline')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e469178c-93d4-4182-9d4f-6a58403eb0f8",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " ==== METADATA ====\n",
+      "\n",
+      "                                     date   machine_name  region_id  \\\n",
+      "id                                                                    \n",
+      "2026-05-10_20-03-44_13005e|01  2026-05-10  ETHOSCOPE_130          1   \n",
+      "2026-05-10_20-03-44_13005e|02  2026-05-10  ETHOSCOPE_130          2   \n",
+      "2026-05-10_20-03-44_13005e|03  2026-05-10  ETHOSCOPE_130          3   \n",
+      "2026-05-10_20-03-44_13005e|04  2026-05-10  ETHOSCOPE_130          4   \n",
+      "2026-05-10_20-03-44_13005e|05  2026-05-10  ETHOSCOPE_130          5   \n",
+      "2026-05-10_20-03-44_13005e|06  2026-05-10  ETHOSCOPE_130          6   \n",
+      "2026-05-10_20-03-44_13005e|07  2026-05-10  ETHOSCOPE_130          7   \n",
+      "2026-05-10_20-03-44_13005e|08  2026-05-10  ETHOSCOPE_130          8   \n",
+      "2026-05-10_20-03-44_13005e|09  2026-05-10  ETHOSCOPE_130          9   \n",
+      "2026-05-10_20-03-44_13005e|10  2026-05-10  ETHOSCOPE_130         10   \n",
+      "2026-05-10_20-03-44_13005e|11  2026-05-10  ETHOSCOPE_130         11   \n",
+      "2026-05-10_20-03-44_13005e|12  2026-05-10  ETHOSCOPE_130         12   \n",
+      "2026-05-10_20-03-44_13005e|13  2026-05-10  ETHOSCOPE_130         13   \n",
+      "2026-05-10_20-03-44_13005e|14  2026-05-10  ETHOSCOPE_130         14   \n",
+      "2026-05-10_20-03-44_13005e|15  2026-05-10  ETHOSCOPE_130         15   \n",
+      "2026-05-10_20-03-44_13005e|16  2026-05-10  ETHOSCOPE_130         16   \n",
+      "2026-05-10_20-03-44_13005e|17  2026-05-10  ETHOSCOPE_130         17   \n",
+      "2026-05-10_20-03-44_13005e|18  2026-05-10  ETHOSCOPE_130         18   \n",
+      "2026-05-10_20-03-44_13005e|19  2026-05-10  ETHOSCOPE_130         19   \n",
+      "2026-05-10_20-03-44_13005e|20  2026-05-10  ETHOSCOPE_130         20   \n",
+      "2026-05-10_19-33-11_30232c|01  2026-05-10  ETHOSCOPE_302          1   \n",
+      "2026-05-10_19-33-11_30232c|02  2026-05-10  ETHOSCOPE_302          2   \n",
+      "2026-05-10_19-33-11_30232c|03  2026-05-10  ETHOSCOPE_302          3   \n",
+      "2026-05-10_19-33-11_30232c|04  2026-05-10  ETHOSCOPE_302          4   \n",
+      "2026-05-10_19-33-11_30232c|05  2026-05-10  ETHOSCOPE_302          5   \n",
+      "2026-05-10_19-33-11_30232c|06  2026-05-10  ETHOSCOPE_302          6   \n",
+      "2026-05-10_19-33-11_30232c|07  2026-05-10  ETHOSCOPE_302          7   \n",
+      "2026-05-10_19-33-11_30232c|08  2026-05-10  ETHOSCOPE_302          8   \n",
+      "2026-05-10_19-33-11_30232c|09  2026-05-10  ETHOSCOPE_302          9   \n",
+      "2026-05-10_19-33-11_30232c|10  2026-05-10  ETHOSCOPE_302         10   \n",
+      "2026-05-10_19-33-11_30232c|11  2026-05-10  ETHOSCOPE_302         11   \n",
+      "2026-05-10_19-33-11_30232c|12  2026-05-10  ETHOSCOPE_302         12   \n",
+      "2026-05-10_19-33-11_30232c|13  2026-05-10  ETHOSCOPE_302         13   \n",
+      "2026-05-10_19-33-11_30232c|14  2026-05-10  ETHOSCOPE_302         14   \n",
+      "2026-05-10_19-33-11_30232c|15  2026-05-10  ETHOSCOPE_302         15   \n",
+      "2026-05-10_19-33-11_30232c|16  2026-05-10  ETHOSCOPE_302         16   \n",
+      "2026-05-10_19-33-11_30232c|17  2026-05-10  ETHOSCOPE_302         17   \n",
+      "2026-05-10_19-33-11_30232c|18  2026-05-10  ETHOSCOPE_302         18   \n",
+      "2026-05-10_19-33-11_30232c|19  2026-05-10  ETHOSCOPE_302         19   \n",
+      "2026-05-10_19-33-11_30232c|20  2026-05-10  ETHOSCOPE_302         20   \n",
+      "\n",
+      "                               sleep_deprived                         species  \\\n",
+      "id                                                                              \n",
+      "2026-05-10_20-03-44_13005e|01            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|02            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|03            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|04            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|05            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|06            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|07            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|08            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|09            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|10            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|11            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|12            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|13            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|14            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|15            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|16            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|17            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|18            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|19            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_20-03-44_13005e|20            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|01            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|02            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|03            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|04            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|05            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|06            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|07            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|08            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|09            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|10            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|11            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|12            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|13            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|14            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|15            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|16            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|17            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|18            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|19            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "2026-05-10_19-33-11_30232c|20            True  UAS_ChRmine_attP5 x 60D05_Gal4   \n",
+      "\n",
+      "                              food  baseline   sex      time  \n",
+      "id                                                            \n",
+      "2026-05-10_20-03-44_13005e|01  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|02  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|03  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|04  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|05  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|06  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|07  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|08  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|09  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|10  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|11  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|12  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|13  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|14  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|15  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|16  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|17  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|18  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|19  ATR         0  male  20-03-44  \n",
+      "2026-05-10_20-03-44_13005e|20  ATR         0  male  20-03-44  \n",
+      "2026-05-10_19-33-11_30232c|01  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|02  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|03  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|04  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|05  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|06  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|07  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|08  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|09  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|10  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|11  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|12  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|13  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|14  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|15  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|16  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|17  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|18  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|19  ATR         0  male  19-33-11  \n",
+      "2026-05-10_19-33-11_30232c|20  ATR         0  male  19-33-11  \n",
+      " ====== DATA ======\n",
+      "\n",
+      "                                    t           x          y          w  \\\n",
+      "id                                                                        \n",
+      "2026-05-10_19-33-11_30232c|01   37990  104.882353  26.882353  29.235294   \n",
+      "2026-05-10_19-33-11_30232c|01   38000   82.825000  25.000000  28.450000   \n",
+      "2026-05-10_19-33-11_30232c|01   38010   41.731707  24.902439  11.292683   \n",
+      "2026-05-10_19-33-11_30232c|01   38020   35.000000  25.000000   8.000000   \n",
+      "2026-05-10_19-33-11_30232c|01   38030   35.000000  25.000000   8.000000   \n",
+      "...                               ...         ...        ...        ...   \n",
+      "2026-05-10_20-03-44_13005e|20  464590         NaN        NaN        NaN   \n",
+      "2026-05-10_20-03-44_13005e|20  464600  108.000000  34.000000  31.000000   \n",
+      "2026-05-10_20-03-44_13005e|20  464610  151.933333  33.066667  35.133333   \n",
+      "2026-05-10_20-03-44_13005e|20  464620  430.888889  30.055556  63.833333   \n",
+      "2026-05-10_20-03-44_13005e|20  464630  451.947368  24.052632  58.421053   \n",
+      "\n",
+      "                                       h         phi  max_velocity  \\\n",
+      "id                                                                   \n",
+      "2026-05-10_19-33-11_30232c|01  14.235294  130.705882    112.948052   \n",
+      "2026-05-10_19-33-11_30232c|01  14.000000  104.725000      1.330083   \n",
+      "2026-05-10_19-33-11_30232c|01   6.512195   39.170732     11.638011   \n",
+      "2026-05-10_19-33-11_30232c|01   5.000000   18.000000     11.399315   \n",
+      "2026-05-10_19-33-11_30232c|01   5.000000   18.000000     11.399315   \n",
+      "...                                  ...         ...           ...   \n",
+      "2026-05-10_20-03-44_13005e|20        NaN         NaN           NaN   \n",
+      "2026-05-10_20-03-44_13005e|20  10.200000   75.100000     11.191254   \n",
+      "2026-05-10_20-03-44_13005e|20  10.133333   65.000000    203.178966   \n",
+      "2026-05-10_20-03-44_13005e|20   6.333333  149.000000     29.571867   \n",
+      "2026-05-10_20-03-44_13005e|20   5.105263    9.315789     54.184959   \n",
+      "\n",
+      "                               mean_velocity      dist  has_interacted  \\\n",
+      "id                                                                       \n",
+      "2026-05-10_19-33-11_30232c|01      11.500973  0.586550             0.0   \n",
+      "2026-05-10_19-33-11_30232c|01       0.812331  0.097480             0.0   \n",
+      "2026-05-10_19-33-11_30232c|01      10.005065  1.230623             0.0   \n",
+      "2026-05-10_19-33-11_30232c|01      11.399315  1.436314             0.0   \n",
+      "2026-05-10_19-33-11_30232c|01      11.399315  1.402116             0.0   \n",
+      "...                                      ...       ...             ...   \n",
+      "2026-05-10_20-03-44_13005e|20            NaN       NaN             NaN   \n",
+      "2026-05-10_20-03-44_13005e|20       7.258459  0.217754             0.0   \n",
+      "2026-05-10_20-03-44_13005e|20      33.002480  1.485112             0.0   \n",
+      "2026-05-10_20-03-44_13005e|20       5.502794  0.297151             0.0   \n",
+      "2026-05-10_20-03-44_13005e|20      29.940530  1.706610             0.0   \n",
+      "\n",
+      "                               beam_cross moving  micro   walk  \\\n",
+      "id                                                               \n",
+      "2026-05-10_19-33-11_30232c|01         0.0   True  False   True   \n",
+      "2026-05-10_19-33-11_30232c|01         0.0   True   True  False   \n",
+      "2026-05-10_19-33-11_30232c|01         0.0   True  False   True   \n",
+      "2026-05-10_19-33-11_30232c|01         0.0   True  False   True   \n",
+      "2026-05-10_19-33-11_30232c|01         0.0   True  False   True   \n",
+      "...                                   ...    ...    ...    ...   \n",
+      "2026-05-10_20-03-44_13005e|20         NaN  False    NaN    NaN   \n",
+      "2026-05-10_20-03-44_13005e|20         0.0   True  False   True   \n",
+      "2026-05-10_20-03-44_13005e|20         0.0   True  False   True   \n",
+      "2026-05-10_20-03-44_13005e|20         0.0   True  False   True   \n",
+      "2026-05-10_20-03-44_13005e|20         0.0   True  False   True   \n",
+      "\n",
+      "                               is_interpolated  asleep  \n",
+      "id                                                      \n",
+      "2026-05-10_19-33-11_30232c|01            False   False  \n",
+      "2026-05-10_19-33-11_30232c|01            False   False  \n",
+      "2026-05-10_19-33-11_30232c|01            False   False  \n",
+      "2026-05-10_19-33-11_30232c|01            False   False  \n",
+      "2026-05-10_19-33-11_30232c|01            False   False  \n",
+      "...                                        ...     ...  \n",
+      "2026-05-10_20-03-44_13005e|20             True    True  \n",
+      "2026-05-10_20-03-44_13005e|20            False   False  \n",
+      "2026-05-10_20-03-44_13005e|20            False   False  \n",
+      "2026-05-10_20-03-44_13005e|20            False   False  \n",
+      "2026-05-10_20-03-44_13005e|20            False   False  \n",
+      "\n",
+      "[1702361 rows x 16 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.display()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "596ea36d-2ce7-4b10-904c-eb869eaae6ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#define dead and/or escaped flies\n",
+    "dead_flies = ['2026-05-10_20-03-44_13005e|20', \n",
+    "              '2026-05-10_19-33-11_30232c|06'\n",
+    "             ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "3e536fd1-fcae-4d5c-a8fb-b5b7ebc0be66",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/venv/lib/python3.12/site-packages/ethoscopy/behavpy_core.py:1611: FutureWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
+      "  tdf.groupby(\"id\", group_keys=False).apply(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 750x380 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "start_hour = 0\n",
+    "end_hour = 96\n",
+    "fig = df.remove('id', *dead_flies).t_filter(start_time=start_hour, end_time=end_hour).heatmap(variable = 'asleep')\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "5c084cf8-92d7-4579-8c93-cd761ed821f7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Task was destroyed but it is pending!\n",
+      "task: <Task pending name='Task-314' coro=<_async_in_context.<locals>.run_in_context() done, defined at /srv/venv/lib/python3.12/site-packages/ipykernel/utils.py:57> wait_for=<Task pending name='Task-315' coro=<Kernel.shell_main() running at /srv/venv/lib/python3.12/site-packages/ipykernel/kernelbase.py:597> cb=[Task.task_wakeup()]> cb=[ZMQStream._run_callback.<locals>._log_error() at /srv/venv/lib/python3.12/site-packages/zmq/eventloop/zmqstream.py:563]>\n",
+      "/srv/venv/lib/python3.12/site-packages/matplotlib/cbook.py:266: RuntimeWarning: coroutine 'Kernel.shell_main' was never awaited\n",
+      "  self._pickled_cids = set()\n",
+      "Task was destroyed but it is pending!\n",
+      "task: <Task pending name='Task-315' coro=<Kernel.shell_main() running at /srv/venv/lib/python3.12/site-packages/ipykernel/kernelbase.py:597> cb=[Task.task_wakeup()]>\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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8Rdx66625x0kpIUSnAjAyMoIPfvCD+Mu//Ev82Z/9GRqNBvbv34/f//3fp+CXGAqlFKKof+U3iiXmqx4A4PAJrUI+VnFRawWwLQ7H6uSULM4QCwUhJCxrQ+WaCGLT0PZjREJCSHmuN4UgCIIgiE3Mhgp+AeCSSy7BBz/4wWUfc9ttt/XcdvDgQbzjHe84MxtFnHcY317eZ4bg7ofn038fmW5ASgXXsRALCSEVLCtT+bU4wkgglgoWuR0RxFCEkYAQElG8NYLfth/R7DJBEARBnAOoFEUQfYilgpSqb7X2Bw/N5v6+4+6TALSuhewKmC3OIKREvEUW7QRxtlFKwY8EpAT8YPOPEDTaIe57dBGPnqwhiAQeeGwx1QogCIIgCOLMQsEvQfQhjnWLZXfbs1IKR6fzdlyfv+MxAAADQxCJXMDMOYOQKhXGIghibUipEMcSrsPR9KJzvTmnTRgJVBs+Fms+FmoeFuo+mu3wXG8WQRAEQZwXUPBLEH3wwxhRLGF3VX5bfowwqeK+/GevSG9XSsF1OLwg7hG8ouCXIIbHdGE4tgU/jKFUr+iVlJtHCCsWCnGsUGsFWKoHaLZD1JoU/BIEQRDE2YCCX4LI4Ad6cX18tokwlj1qz9WGD0ALXF1xcArm3rYfY3K0iPFKAa7TGe5ljEEpQAxQqfWDGA2q+hDEQEQidOXaHFKhR/F5oebhvkcXNk0ALISEZTOEkUTbj+CHAvVWcK43iyAIgiDOC05L8OrBBx/E1772NZw4cQKA9tt91rOehSuuuGKFZxLExiKKBR54bAlhLLBvxwi8oH+Fqd7Sgep4xYVjc4yNuKg1QyzUfFywexRjFbfnOYxhYOX3waNLEFLiSVfsyt1OgjgEoZFSQSqg4HAIoSCkhJPJ284teag2A4SxQNHdcBqOPURCAsmpZbHuY6zsIqSZX4IgCII4Kwy1UgjDEG9605vwqU99CkopcK4XIlJK/MVf/AVe8IIX4L//9/8O1+0NBAhiI7JQ87HU8NH24sSeSGL7eKnncaZKO5oEuVNjRdSaIRbrHi7YPdr/xdXg4FfIXgXbx07VsVT3cPkFU6iUKAAmzm9E0vZsWxxRHPVUeMNIIIoTUblNcMnxA+0fvn2ihCiWEEKSHRpBEARBnCWGCn7f/va345Of/CRe/vKX45WvfCUuuOACMMZw5MgR3HbbbfjIRz6C8fFx/Lf/9t/We3sJ4oygFND0InDGMLPYBmPA1Fi/4FcL7oyU9CrbVHqXE+JhjA20aImF0gtfqWBxBj+IsVDzUG0E8MOYgl9iy3NspgGLM+zdMdL3/lhISKXg2BxNL9/2rJSCF8baBmmTzNWHkYDFGWyLw7a0TkAYicQm7VxvHUEQBEFsbYZKM3/605/GjTfeiDe96U24+OKLYds2LMvCxRdfjD/6oz/CC17wAnz6059e720liDOGkBKOxbF7WwWjZReVoouC07sSNaqsI2UdlFaS1uTlgl/O0Df4lYkQlswIYrWDGIt1H34YIwipFZLY2kipcGKuiRNzTYgBM7tCKkAlyulC5rooYqF09VSqDecB3G9sAgDCSMLi3Yrwsqc7pNkON9xnIgiCIIjNzlDBbxzHuOaaawbe/6QnPQlC0MKd2DwIoaCg1ZlHy27f2V2gU/kdNcFvUpltLRP8WhZHFPceD7HQi3YhdeujuQ0KKDj2sq9JbHxqzWBL+NKeSeIkmG37EYKw/3clpQIYUv/s7HxsFItUTf1semkPCmyzPHisiqPT9dxtQkgEkYBtdYT0bIsjFirn9auUwkPHlnByrrl+G00QBEEQxHDB7zOf+Ux84xvfGHj/v/3bv+G6664beqMI4mwTC5kurpfDVHhHyzo4Xk3wyzlDEPUuzGOhg14pO1YtptLj2lvD0/R85pHjVTx0rHquN2NDY2Zew0imYnLddM/4ZivEUipIocAZg3eWEg1NL8Ldjyz0TWhlqTUCzFe93G3Gtik722vs0KIoX9H2AoFqk1SgCYIgCGI9GSr4feMb34jjx4/j9a9/Pe68806cOHECJ06cwB133IFbbrkFJ0+exBvf+EZUq9XcfwSxUdHB78qPS9uek5nfUkGPzS+38LY4QxSLnkW8nvUFpFLpgj4IY4ABjq1nAcUmmWMk8sRJhY9UfJcnTsSeglAMbPHtbofOtgdHsUQsJUZKLuaq3sDW6fWk3gpSi6JByKSjo9uWSQgJoVSPhRpD/nNVGwGCSJA/OEEQBEGsM0MJXj3/+c8HoK2Obr/99tx9ph3s537u53qed//99w/zdgRxxolEr6dvN0qpnrbn8iqCX9viWpFWSBR4Z47Y+JcCerH80LElNNshOGOwk+A3jCVKpAC76Wh5EbxAQCodoDk2/Yb9MGJWxYI9sEVcSgXTZcyY9sc1BJEAFFB0LfihQBQLWGfB7igI42UTG36oj13X1ttvzi1a1VmL23UTC4kwEjh0RNufNdphmmQjCIIgCGJ9GGqVcMstt4CtokWUIDYLQqiB+/RS3ceR6TquPDiVVmKM4JWp/LZ9vXBXSuEdH70Lc1UPv/OyJ2P7RCm1TopjmRPRMkI+CnoRP7/kAQxwbSudA4xiiVLh9D9f24/g2ByOTXKyZwMviOGHMSxLV/0p+O1PFOsZd8fhaPn92/zDuDOSoI8lkXu+QlY06sxXfoVQaHoR2n6MbeO9988uthFLiSCMYVsuRCb4FVJCyt5EG2P6HPHQsSqaXojFug8lgTjpGFkpMUcQBEEQxOoYKvh9wxvesN7bQRDnlCjuX/lVSuHtf/c9AMATLt0OACi4VhpEmpnfdhBDKoVqI8BcMuf3L987hl++4XJYFk9FebIIqWDeMQgFwli3fk6OFtPF/Hq1PR86sgTbYnj8pTvW5fWI5YliCQYdKJ2NgGyzYoJX0+Z/9yPzeNxF23KV0SgW6d+cs9xsrB/E4Iylc7NnY0wgigXiWPWtVNeaAY5M11F0bUSxhBS6/dlJJoykVJAKPfoCLFGEF1JhbslLk2ZRrAXBXE5JK4IgCIJYD9alHNFoNEjdmdi0KKUGzvx+5/6Z9N8/engeADCa8d41wa+UejE8vdBK73voaBVAR9CmN/jVC38AyXyfgpSA61h6caywLt6lUiptndRHdIs4M+hKu7WuCYytSBQJcMZQdC1UGwEW6346V58+Jpb54DeZDRZSYakRwHU4OGeQSvXM1Z8JwuT9+406PHqypj+DF+rjWcncNg2aSbYSUTw/iDExWsBo2YVtcQgpsVj3z8wHIQiCIIjzkKGD37vvvhuvec1rcM011+CpT30qvv3tbwMAFhcX8brXvQ7f+ta31m0jCeJMIhMFVs57D4fvZoJfw0i5M4dnWxxFV1dlml6E6YV2el/Lj3DoyBIALWjTLeijF8UMYLryK5XCnu2V3GPWw+dTSOODKnqsV4gzQ9uP4docUKDK7zL4oa7qOraFnZNl+EGcm+kFdGLIdGVYnCFMWoE9P0LLj1BybT2ycJa+6ygSYEx3e3RbHoWRhB8IzC562D1VhlJANt6VUqHfdAXnDEEYo+VHcJOuEt39ARydbpDfL0EQBEGsE0MFv9///vfx8pe/HEeOHMEv/MIvQMrOhXlqagrNZhMf+9jH1m0jCeJMEsvBIjT9/DxNsFttBAgjkbM7+sp3juYe+6HP36f/wXotW6JYAqwj5oOut1LAuniX6oqyfp+ZxfbKTyBOC6UUwkjASrxcuy1x2n50VlSJNzpKKTSTWXQg6XhI5uMNQiqIWGJmqY3phVanvVnKTkuwm52jP/NBYhBJlIsOgjDO2TOZtuudkyVcvG8crmNBqs5xX2+FCCKBftO75nO1vQjlop5G4sl8c6MdUvWXIAiCINaJoYLfv/zLv8Qll1yCz3/+87j11lt77n/qU5+KH/7wh6e9cQRxNhBCQqr+M7+Lde2zaeZ9AeCZT9yHWEi0gwiLdT/1/M16cl6wezT998m5ZlKV6qpohQJWpgzUHQ5ZnMEPT8+7dL7qoe1HUEpXfsNY9vUn1ZYzVF1aD7TNje4kUEDuN4yFxKEji7jv8MK528ANQhAJBIGAmxGBg2K5AFZKhXo7xAc/ex/+6uM/AKCPVx34arW4dH62T4JpvdF+vALlog3PF6nQHZD4dmc8fDljUEkrdhgJPHh0CfVm2HcbOeepsJUR3uOMgXNOlkcEQRAEsY4MFfzefffdeNGLXgTXdfsq5O7atQvz8/OnvXEEcTboiNDkb9d2NXpx+6LrL8VbXncd3vK663Dx3nE02xFGyy4iIbFzsgwAOHyiBkC3OP/aL1ydvs6DR3Xrc/cCNop1O6dRg+4WwdEtnsMvepVSePRkDSfnWhASaPkx/CBO7ZoMQircc3ihb0Dmh3HfYJkYTJy00VucIY4llhpBGvCEkUCzrZWgz/eAJk7EoPIdFypXFRdS4vhsM/17qeEn8/MKUZfOhFKDZ2rXiyjWs/m2xaGgMLPU6aQw1mUmicaYObcoBJFAsx3CC+I0OM5icYZ2H7XrXZNlODbvmYMmCIIgCGI4hgp+bdvOtTp3MzMzg3K5PPRGEcTZRJiZ367gcz5RbR4fcfPVKQBBFKNScuBYHLum9L7+vQdmAWgbJNvi+Mkn7gOgZwOzQj2GWKg0+PXDuMcOhyfB00p4QYzDJ6o9C/9YKISxRBAJCCl1sB7Jnu04cqqOMPEl7eaBxxZx76OLK24D0UEICaEUOANGyy7qzRCNJHgxwmdNL8Ijx6totsPzVhArTTplgt9uH18hFOYyAWatFabtxWGYD345Y4iW8d5dD0zAblsMIyUX9WaQBqbNdoQ4Mz7BmJ7nj2OJR0/UEMUSc9U2RjKCeYaCY0FKpIm0LCXXRq1FwS9BEARBrAdDBb/XXHMNvvSlL/W9r91u45/+6Z/w4z/+46e1YQRxtkiD367Sr7Es2jHRuyBVSbulEAr7duZFqqbGigCAcsYD2OKsR7k5irXSbcGxUG+FPUI4nOnn9Js7zjJf9TBf9RF0tUgLoZWG234EIRQmRgqwbNYTbNWaARZqvlaf7iPgc6YDis1GFEscPlEdWBGXmf1pYrSAWEj4SaAWJ9XBRitEvRXi0NElTJ+nc9h6Dj3vr21b+QqokCo9DgGg7cWpsNVSw889lzP0TeBE8fopbgdhrNWnLY7xETdRUde/bRAJBJGAna3sKqDRDtHyIsRCYtdUBeVib/DLOcOe7ZWeJBugRfWiAeMKBEEQBEGsjaGC39/6rd/CPffcg9/4jd/A17/+dQDAoUOH8A//8A940YtehMXFRfzmb/7mum4oQZwpjAJrdwt/GvxOlvo+frTiolSyUXJtTIwU0vu3jevHG+Gath8lVakuIZ+k8lsuOeCMYbxSyL2PZXHEifdnP6qNADOLbVQbQdJG2yWoJbTNStuLc4v/7nZbLdAkEYb5FlOZCAvFqwjAzyfmltqYWWxjoebj6HS95/cRSVBnOgkUkAZ0cayFx7ZPlNDyIrS9GPVW0P0W5wVmHjabcyo4FlpelO6vQkjUmp2qp6my1lsBWl4M2+o82bJ43wDxnkfm8fDx6rpsc6MVQkEnpvT5QifAzOdx+rQ0t/0YTT9Cueig0Ce4XQnb0krQWSV5giAIgiCGY+jK73vf+14cOXIEv/d7vwcAeOtb34o//MM/hJQS733ve3HllVeu64YSxJlCyIzicgbTbrl9otTzeMvimBwtYGq0iLYfY++OTvV327iu/JaSCk/bj3tUbKXUrbEWZ+CMYfe2Sk/l2eIsFU/qx2Onajg6XUeYVJy6g9rFug8/FKiUHUwm1ehu4S2ldGv01FgR1aafazE1FklmxpLQ+GGMWjPE3JKHmcU2/C6/V+M3a5IpjsXhJcJIsZAAAypFBy0/Qr0dnLffrVRKO31lK782RyxkWsEVUiHItDc3PJ1EaPsxvCBOuyyAxC4o6k3s6HnbaF1mrJt+pC2sEpj5HMhbMmW3SXdUILeta8F1LDS9CCF1YBAEQRDEaWMP+8SnP/3p+NKXvoT77rsPR44cgVIKBw4cwNVXX91XBIsgNiqD7FHm07bnrsqv0hVbx+bYs72C+aqXVnuBAZXfJPg1bZ56dlCh6Aw+VszCWQgJdFWMpFTwQ6FbnZP26+7Ffa2hK4rZqrTFGVpenG6Hafm2bY7J0WLaZs2S1zRCTULInpnk85UwkghCgSgWaPtRzwy1Uvo/cxq0bY520Al+VTLnumOijGY7zAV35xNCqh6Jc87yCZ9T862cWnbTiwDWsSDLtz0zRLHItVKHiR1Sy9PK7P1matdCEAhYWT9wlg9+u+3SbIsjFqqvvRGgjyuWJMAGwRhDudDbKk0QBEEQxNoZOvg1PO5xj8PjHve49dgWgjgnCKF6bIZiIVNvzZ7gVypYjMGyOMYqLhyHY2qsE2BuH++a+Q06M7+xkHBsK5lDVH2VXw3G+7NfZdAPYwRhDM8XcBwOxpC2XxoUgFIhf4gzxuAFMU7Nt7B3x0iqRutwBsuxEIS6ilx07bR9VymtYExozIxn24/hh6In+O1uo7cTQbMwEggjkQY6pYKthZsiASHksvvCVqS/5Q+DVFrQaqHmodEK0u8bAFrtCE4yA9v9bM61tZCQKm2H9oMYQSjQ8iPMLLROK/hVSiESXZZoGR/fnsAY5hju3VYAuO/RBfz9lx7AU67chf94/aXLvrfFGbzTtD0jCIIgCGLItmcAaDabeO9734vXvOY1eOELX4gf/ehHAIBqtYoPfOADOHLkyLptJEGcSWIhe8SmFus+pAJcRwe43Y+3LAbb4rAtDouz1OsXAKZM8Ju0PXuJ2rMOdHSg5Ad6Dre7UpTF4v0rugBSn1PGzfaznsdFca93MecMizUfs1UPUSxz4kyOzRFlttG0PJtghNDEsUTBtVBrBYgi2ePFLGU+mVIs2AhCgaPTDe3tnPlNdGWwV4H7fKBfOz/nnW6EZjvCzGI7N5LQ9MKkDbhXJdtOuiuyx0HLjyCkxNRoEU0vQq05/Hx19ljpvr0jdtVb+Y3i/jPzX/z3I5AK+M79Mz2t8924DkerHdHsPUEQBEGcJkMFv9PT03jhC1+Iv/qrv8L09DQOHTqEVqsFAJiYmMBHP/pR3Hbbbeu6oQRxpshW4wzZlufuNv5Y6ODH4iwJGi3snCrjor1jeOJlO1B0dbXVtD0rpQOmOBPIthIBpOVGBMx93RVdQAe2Uins2VbR88KM5WYClVKpmnSWiZEChFSYX2qj3gogVUecyfgNmzZc7Vuq0mCE0GjbKAd7to1gpOxgqeHn7pcq385rWxx+EGOp4aMdxLAz7eOWZar751/w2+8zc8YA1bGE6m4YbnqRnpf2Ymwfz3dk8GRGPtspsVDzYXEO17FQa4R4+Nhgle4Vtzfj35yl2ghw/2OLaLTDdM7f4NgcQSh6jp/ZpXZ6jgGwopUR5zw9FgmCIAiCGJ6hgt+3ve1taLVa+OQnP4nbbrutJxv90z/907jzzjvXZQMJ4kwjxGCP326xK0BXegpOp53YsTk4Y/j1Gx+PX/7py9PbbYvDdfQhpr12VTr3u1jzUXBXVn7NCuoYtDWRBygdIJvANcws6uMkcO1eqHPOcMHuUSiFTOVXvw5LZiZPzDUQxSL3vrTo1hiVbsZ0pbzgWGi2o1wVUkot5JRlYrQAL9Ctz1krHKPonVXZPh9oehEWa97A+7XolUgDVbMbt309r35g1yiKBRtKKRybaSCMhP4uRccSSCkFL4hRcCyUCjZKRRsLdQ/VxnCeuVp5Pd+tYXGGIBI4MdsAGHpnfm2Olh9hJNMZEoQx3vHRu/LfR3v5bbItdt52CBAEQRDEejJU8PvNb34Tr3rVq3DppZf2rVwdOHAAp06dOu2NI4izgZC97cGNZDE6PlLo83iVBrWAVvMd1I5ohGrafgwGHWgHkYAXxGmFeDkUOoJcM4tt/ODBWTxyvIqlRpCbAeQ8b6UURBJxvIxIFUMqLCRVx26GgWGh5qPeCnUFTaFHIfp8RkoFiU6Q061ODPQXchopuQgTRe5sayxnDG0/Rr0VnjeBjZQKjxyvYmbRQ6XUX8hJGvutZJ+eGi+lowmtjA/w/Y8t4n/904/wsa88qNXRFdLjQEiFOJZpsmFqrAgohiDSStGHT9QGJnVkn24Hk1DKnisYY2i0I0yOFrF320jP63DGcNGe8Zzo3B+/71s9j2u0o57bspj5fxo/IAiCIIjTY6jg1/d9TE1NDbzftEATxGZAyF41VrMYHS25fR/v2p2qrWld7UdW8RkAYqnbisNlAtO2H8EzM4AZIavZpTZqzQCRkJhZbGNyNGPzwlgueIpiE2gNOMST1tLuOcYDu0YhpUK9FabCTQAFvwYhJaToqAlbnPfMZXdX6gGdnIhj1fc32bejAi+Ihm7H3Wx4QZzO3mZn5Tvo9mUjEAbo46iStBQ3vU6g+JVvHwWgg2AAUFJhNrHrCiOBqDvZwBmCUKDeCnFyvolqV8u64eHjVRw+UcvdJpOqf7a6O1pxIaUaGMR3084E7q7Dcc1l25PPtELbM1ve9owgCIIgiNUxVPB7ySWX4Dvf+c7A+7/yla+QAjSxaRCZYMZgKr8j5d5FLQNy1R/XsfoGPEAm+A1iXcUV2qJoUGD64NEl/PcPfBt/8v5vpQGVqUDFsW579PwYe7ZVctUknrQ9mwp0HKvUUmfg587MR+a8Vi2OpYaf+pMyxuCfp3Y83Wh17E6nQEedONMiPiBRIJI23O7f3bI4hMR54/frh1ole8/2yoBH6P0yjmWq9Fwu2Omx2MxUSecyc7NBGKNUtNH2o9TfN44l7EyiyrZYen/bj/raTCmlsFj3sVj3ctXffsdKwbGwa6q8rFVRluxs76uee1Ua/K9U+TXzzBT8EgRBEMTpMVTwe9NNN+Hzn/883vve96LZ1LNqSikcOXIE//k//2f84Ac/wK/8yq+s53YSxBlDKtWj9mwW2P0rU7raa7At3tPmajACOG0/1tXZTDWr33Z88HP3pX/PVz0waIskAIiEDgb8QPRYGGmbl85sbixkz9xpFpZUivt5HBddC34gsFQPks/HehSNtyq1ZoAfPjQ3sAXZzEibYIcnPq/Z71GIXkVgANi7vYJdfax2cn7O5wF+KMAYBgaMxo5LKJUeK6WCjZGkC8NUfr0gzgWDi/UABcdCmCSJoqh37t22OPxQz99HsUyPrSxGMTqM8vdH4vQTQGa2d/dUGZfsn8BIycndPggTcJPwHEEQBEGcHkP5/N544404efIk3vnOd+Id73gHAODXfu3XtGos57j11lvx0z/90+u5nQRxxhCyT/CbLLD7tjMywM74eTo2Hxhopl6/fgSL6wqqQv+Ff7Or+lNrhpgaK6QV3ziWkBIoFHtzVrbF4AXac9a2uBa/WmadzJlu4e3nl1pwLZyab6FctMG59jP2g/Oj8nt8tonFmo8HHlvE4y7e1iNg1DMjnQYlncdEsez7+xprrG6MwnG/QGwrEgu57L5pcQY/0CJipvKrxa30/SZQzKolA0C9FWDbeFELiyWBbfev4Nh6X277UToT3E0Y6USEUsDMQgs7JsuJQrq3bEJpNTRaSVItsU9bbeUX0G9NlV+CIAiCOD2GCn4B4HWvex1uvPFGfPnLX8aRI0cgpcQFF1yAn/3Zn8WBAwfWcxsJ4owhpbb6ybYyxkKmM7ejfdqelcpXfjlnAxfzpu3ZC2JYFoMfxYjiXj9QQC/es9RaAbZPFBHFIlUK3rO9goLTqxJtBHFOzbe0srAfL+shzBiDFAqNVginKyBzbAu2zVMVbItrFehuj1OlFOaqHiZHC3DslZWrNwNBFKPhheAcqDZ8bOuy05FJ8Muy363Kz/lGoldAbUVYf0urrYiIZe5484IYjt1JDOhKuA70TLt9qWCn+7NJTC3UuoPfMBG90sJQbS/qGWdwbAttP4bnx1ASfSv8xkNbSIm5JS/pkNCzxNmk1zCYcQoT9BoV6JUqvwCgGPp2ahAEQRCbn0Y7RBiJnnXHRiQWEo+drGP39krawbSZGDr4BYC9e/dSezOxqVFKpXOthlayuOZMV5yySKmrftngxizKu4NoAGl7ctvXs55B0nLZT+yq1swvgKuNQKs4J/YtYSzhDhDJMoI4CzUP81UPts1yfrI9j09abYNI9n2ca1uIExVs2+LwgggPH6/isgMT6WcMIoGj0w1EscS+Hb1Kt5uNWEj4gcD28RKqjaAjOpZ7jFZyzlV2Wb4dNQiXTzws9/7nA3Gm02J2qY2//scfYvf2Cm5+4eMTyy2g0Qq1MnrSbl8q2Om+b47P+VperKreCsGSJJARbetOFNkWQyxlmqzoJzJmLMCiWKLlR3AdC7GQaHkxDu4ePa3PXk+DXyf3/92V3+OzDTxyooafvGZf51yjzp8ECUEQxPnG4RO1TRP8tv0Y0wstOA7flMHv6aWxCWKTY1xpsrHKd+6bAaBtbLrbV2XS2p/zauU8nbntppzM/BqhIyH0HGO56EBIhX+/5xQW63oRX+uu/DYDcMYQx3r+kDH0tRYDOoI4Uin4YYwgFIOVngEwpmcvg6j/43S1V79nqWCj6UWYXWrj6EwjfYyxbRo0w7zZ0BU/rcJdcC14fm/w23fuU7G0Imd8gNdc+VVAtEW+x5WIRact/M67TyGMJY5ON9LjYKxSQL0VQkgFL8gIXnXN/JrKrwmKa60wfd0wEcvqTuywpMW8Mxvfe9DOLrUQxiI9VsNIwA9j7JgswVrmmFoNgyq/bT/vFf3Xn/gRvvTvR/CV7xxNb1PoryROEARBbH7MiNtm0P/wghhNL4LapKM4q6r8XnnllQMX3YNgjOG+++5b+YEEcQ7RlV8FxjqL2q/ddRxA/7lcKRUsjlxlz7KYbiNWCrxrKDBrdWRxlgrp2BbHl791BF/9/nFsGy/iP738Kek8YKlgJ3YwISyLIxIqp2rbD/P+MlmwMzAU3MGtyJwxKKUQxwKVPnZOPAl+TUv09vESphfaKBVsHNw9BkAHEFspYBOiI5BkWxz1Voh6K8RYpfP99FUHRkeFVwgJoVRPK/lK2BZHcJ5YHYlMW/jJuWZ6+7GZBraNl2Bxhgv3jEEm6tiAPibMNcjMxs9XdbB80b5xHDqyhHqipMyUrr4LoVBw+/8OpoW/3wxty4vh2BamxlzMLrUxWtH7xVp/0350z/yWi3Yimqb9i8cqBRyf7SSYHjleBZ56EIA+52yVRBNBEASRRztwSISxRGkdrjdnkijWbgrtPkWCzcCqgt9bbrllzcEvQWwGpFJQiTDyw8erOHRkMV0QP+dpF/Y+XurW5mxgrOdik9bXrniz3NX2HAmpxagAfO8BXWFeqPm4/9GFNOjev3MEDx2rotYK4NgcLS9EywtXnDeUUkEolYheSVh88OHNGEutjuw+VUrOGaJApAv+ctHB9oki4lim7d1CaFGhraJAGwvjecxhcYalho/DJ6p44uU708fUWyHcrlZaE5TMLXmIkwC66KztfGlx1rfNeiuS9dVeanS6HY7NNnHNZTv08cUZOFgu+DVV3KYXQimVCl5dum9CB7+JdzCYrvxK1f8YYIwlVmOsJ8OuK/cSIyUnaeUqQ5j9wj79a2DLzwvpccYwUnZRb4VotHXw+3+/3an2Ziu9ej/b+BUBgiAIYm3I5NoTxRJh1OvosdEw4p+bdd2yqm/3DW94w5neDoI4JygFSOiTzvs/c2/uvqsunOp5vG57ZjnBK4snlV9T/ZMKS3Ufk6OFtO25HcS60iRU6s+brTrd9sUH0n/v3Z4Ev80AFtNBmVIiV4HsR5ycPE0AtlyLJmfJZ5f9W3SLro25qoepsc7siWNbCJJW6aJrox3o6togW6DNhkhmQS2uA5LFup/7jYTU3rDd89o6cBVotOqpl/Na22MLroVGO8Lckocdkxt/3ud0EEILhkWxTFuYAd0C/ejJGn7zxdekrfjmwlos2CgmnQwtL4IXxKkS9ME9eg7XeOgqpdvHhOzvc22SFbbFE+uqzjEgZb5y71gMrUAAaohW9j6YVvpyZmEzUnJQb4VotkNIqfDQsWp634m5FpYaPiZHi9oq7TzpDiAIgjifEEnxwrhwrDf9NGlOhzDpggsikSSTN3alupvNtbUEsc5IqQClcN9ji7nbd06WMdJH6VkLXuUrv5bFYVk8rdJ4QYxICDS9KM3eBaGAEBJ7t1cwOVoEALABvimXXzABBh30emGsxXdEf2GqLHZipeTYFvxgedElblRxZf8TomNzXLx3PCcY5Ni6cm1afxdrHsJI28ZsheqvEbMCdIC0c7IMPxRpwBFGItcKbrA4hx/EqDa1UqOQa1d7LhVsNNshFuvLt7dvBfTMr55p72Z6oY3phRYAnWjyk+C3XLTTaqlUwMl5/ZhK0cH2RBzEKKIrIPWw7vc72BaH5+vgt3uONq3yJs+zbWvZQHotKKXgBVH6eQxm/vfRU3X88fv+ved5b/8/3wPQGUUgCIIgthYi6aITQg0lfqmUwsn5JvywtxLrBzF+9PB8Ltl8OkipUG0GKBXsobf3XDNU8HvnnXfib//2b3O3/eM//iOuv/56POMZz8Bb3vIWiH7CMASxwVBKQSrg3kc7we/UWBGv+YUf6z/zq7RYVHYhbFsMnHXEc4SQGC278MJYzyomj2sHcY+lUj8u3DOGcrLQb7ZjxMlJsd/2ZNk5WcZIycHuqTL2bK8s+1jGGJRcm4COlShEx0Ki7UdotCOMll00vKjvCXezIYTM+bi6DkcYiTTYD8Ik+O1KQhhFbi+IOoJXQ2gkWJxvyovIWjBKzIyxNPjdMVHKJWoaSQU3SDyxAR2wzlbbafXXzApPjBZQcC24jv5NzNyvod/vMFpxUSk5KBdtPSffVd3PHmsWZ4girbZ+usFvEAmYt8q2tJkk29fvOpEGt92q0iYgj7fQmAFBEAShEYntpkz+W9NzhcSPHp7HkVN1zC31JtC9MEatGfTYaQ5LGGn7zUrJQSwl4tNMysbizFS7l2Oo4Pdd73oXHnig06Z56NAh/NEf/RGmpqbwEz/xE7jtttvwvve9b902kiDOFDIRx3nkeBUA8Ppfuga/+4qnpNWYbpRSsC2eC2IZYxivFFIxmlhIuI4FpXRgVEqqPK1M1i1K1Gi7+d1XPAWMMVSSdumWrwOq1QjduI6FsUoBlsVzvrszi2188msP57J+uvIr+wr+DMIo5UaxxINHl+AFMcYqLqLkRLjZiWKZU+y2LJ47KRsLnO6WZsfmqDWDtC18WC9Wk0XdyiilEnV1ltr7jJQd/MGrn5o+ppHsp2afcmxtEcbB0qDxhAl+RwpgjKXHa6OtFZ+lUmADvkqLM0yMFlJ7sJ7gt6vF2ai+ryWhcXK+iY995RCqmeq2aXl27Pzx2e9c87iLtuXayA4dXYJtccSx6nveIAiCIDYvQqpEcJOvOcG51Agwu9jGfNXrm0CPY72GXK/EaRhLxEKhVLARxQIzi+3Ter2j0/V0DX62GCr4feSRR3D11Venf3/qU5/CyMgI/u7v/g7veMc78Eu/9Ev41Kc+tW4bSRBnCikVFusBhFQYKTnYs235iqlUKjfva6iUnfSkU2+FcCwOzoBTC610vs+I3QBatKebqbEipsZ0S3Sl1AmY92yrYO/24X10P/jZe/Ht+2bwD7c/mN6mlae1OvRaqTYDhJGE58dwbJ5Uy4bevA2DF8Q58S8T7KQVfZmvDBtKBRtTo0XsnirDD2JwxnB8toHPfuPwmtR5eSLEtJUxdlyMdY6B0bKLgmPhx6/aBaBT+c2KXUWxQKXkpK3Px2ZN5ddNHwNo+y6e+C6rFWJVxlmaaTcYxe9s8LtrqozdK5wXDNVmgIeOVfH3XzqEHz40jw9/vuN40M58nizd4xWcAddetQuve/ET0tvueWQeBceCF0apXRJBEASxOYhiiYePVwdWOLPXnrUGqfVmAAUtTNqvCmuS+GspdixHLLQdk8UZwlBiruqh7Q/fUl1rhqi3AqizaOU3lJyY53kYGeksxv/t3/4Nz3zmM1Eq6dmrxz/+8fjMZz6zPltIEGcQlVGrGyk5KwoCSKl61H4BXc0RQs8ojpRdjI9qr9IgEmmVJysJb+xasmQFrbKV337vtxaMEFBWSMe2OLwgxvjI8iJa3TDG4Acx5qptTI4VU2XerRC0GS/mHAppJbe7MpzFBGW7tlXAALz5b/XsppAKNz7rkvRxfhij2Y6wfaJX1Iqxwa3wW4VUXd1maSfCSPLdjY9qIThTLW1nxKFiqVBwrVRArpqoRJv5+aKbBL9BDMvSCRmscB3VFWL0VH7NfYOYW2rDtjgmk0SV4cGjS/jg5/L2ftMLnYy4Oc+Uu4PfLqux3/t/fhylgo1SwcbLfvYKfOTLhzC71AZPFhrHZxqYGituOoERgiCI85VaM8Dcoh7dCSOBC/eM55KskZDpNWutMWC1FaDgWFofZkDwG4vTb082mA41xhh2TZVRbQbwgji9Pq8VqbTziJAKdp/i0plgqKvnnj17cPfddwMAjhw5goceegjPfOYz0/trtRpcd22LaoI4F0il0nnV4jLS8k0vwmLdR60ZppXALBMjBYyNuKi3Q7gOx+5tFZSKNrZPlPq2PTf7VG9Gs8FvEhC0vTPXTnxg1yi2jQ9WFn74eBX//QPfwj2HF9LbONPBdLngpMG6Ups/aFPJftCj0sw6c9FRLAZIlHUoOFYugdLdyvOBz9yLv/jI91NRpyxGDXwrz3QqpX2ROevM55r9aCoJfmeTFiojDlUs2LA4g8VZTigKAHZOlZPH6ASRF8awLYYoEismskyFOJsNjzMLkH74YYy//OhdePvffa8ni/7Zbz667PuZ47/U9RlGM5VfzlmuDXpbEmDXmsl3NeKi1gpTITCCIAhi4xPFEu0gxlI9wKmFdq4TEEAamHLWa8G3HEJI+IGAa/OBhQitFYF1m6vNdsEVCzaUAmqN4eeJzfjRelWmV8NQwe8LXvACfPzjH8drX/tavOY1r8H4+DhuuOGG9P57770XF1544XptI0GcMZQCgkC3pnYvrA1CSFQbPlp+hL07KumCNEu5qFsyPT+GY3G4NsePXbwNYxW30/acDX77qO6NZRa9Zlu6T5CnyyMnqum/V5ph/IfbH0Tbj/H3X+rM94+WXbS8CJNJoAIgUabe3MGvaQnqzjoq1clyCrE6u5tsYOuH+bZn0677Vx//Qc/zOGOQ6FQf13IB3CwopUU9wFja3mySPjsndSC7UPcBIJ0jGh9xYVsMRdfuqZpetHccQKeV2FTvvSShdeRUHZ/5xmEEfQTZTHtZNtkgperb2m4w3sJAJ0g39Ducsi3OqcdvV3bcVL4B4LlPO5i7z1SXm16Eth9hYqSAWPTXCyAIgiA2Jn4Yo+VHaHohWl6YCmkaouR6zxgglin9Ti+0sFDrXIciIVN7RW2Hl183PPDYYiouuZYxrOXoTtCXizZmltpDr1mk0jZPZzPxP1Tw+9rXvha/8Ru/genpaezZswf/83/+T4yNjQEAqtUqvv3tb+PZz372um4oQZwJpFTwkxPCIFPxMJYYKbkYK7s4sGsUB3aN9n1cuWBDSIXRigvG9GK94Frp62YD2Ua/4LdP5fd0g9/uk9H7Pn3vgEf20ujTml0s2DiwczRXIeWcrVs7zbnCzLB0t5Iy1jnRB7FY1j7KcGy2kf676UUZwaz8hac7YcA5gxQqbbO++5F5zC6dnpDERiNxFgNDZwbWBIPbxnWg1/Zj+EGMo9P6e9y/YwSMabGrSiZQ3LdjJP09Smnbs4DrWGj7MUbLDv7m0/fgzrtP4fbvHuvZFsZYrrIPGMXNwdtfbXY6NrK/M5BPbhmyv7m5P/sZgHzHx74d+dn+UsFOv5cTcy0wxsAU+nafEARBEBsTP4zBwRJRKoWwaz3gBzE41waYg4QvlVI4Ot3AsZnOtSeKJWKp5285ZwhjLWzV9iP84MFZzFe1JSWYXsuuB93XyWLBRhiJxBpS9rUxHPhaSfCuNkPl17Zt3HrrrfjkJz+J2267Dddee21638TEBL75zW/i5ptvXreNJIgzhVQqrQoNCn7nqx5cl6NScjCRqXh247oWbJvlFrc252mbYzPX9qz/vW9HR0gnWwFKBXyC08vUeeHwz++29BlEv2zjZiOMtHphd9szA0svGEEgYPGVv5OZhXzAai4E3cmEf/7qw7m/rUSB28zt+KHIVRq3ArryqwNPI5BhuhwKrp1aGVWbQRpc7t0xAs4ZXMfKVU2z3QcdwStd+T2wazRVcwbQ1/5BbxB62p6XS29kL+rZBYj2u9bnkWxyLM54ILaSEYbs+cF8Bz/9Exfgx6/ahQv6JNZ2T+lzhEmEKIahFcUJgiCIs08YSYxWXBzcPQbbYlio+jmBJ9O1tJzglRfE8MIYYdQ5/7f9OLVgdB2OMJaptshSPUCzHcEPdVt0FItVi0r5QTzQwrJ7+xyLI4olwljg5HwTDx0bLOzVTZx0X3Xrb5xp1l0xY25uDh/84Afx4he/eL1fmiDWHT3zu3zlV0FhtOzi8gsmU2GdflicYaTk5IJYy+rYs+TbnnUF6QmX7khvyy6aTSXrdC2E+s0Grrb1JVsFXa7N0kp8bh89WcNS0rK62TDZ0u7KrlbFFhBJq2k/pe9uql1ZT/N3o8uD9q4H53JVR8viCCOJeitELOS6WhNsFMzML2MdQavscWcEM45M1xFGEgXHwtRYERZjcB2OkUrn2Mp+M+nMb7K/c8ZwZLqe3v/wMjYK2e84jJb3880ewyfnO+3tZn7ZtTl+9ecfh9/MKDWb9ra07Tk5P0ilsFQPMF/z8OynHMB/vP7S3plz6DlfoKMTkG3FJwiCIDY+QRjD4gyMMVico94O0fZjeEGMux+ehxdo9wy2jOtDEAlEkbZTNNet2cV2mlB2bQtRJBBEAk0vQsML4Tgc1WaASsmBWmWAGcUC9z66gHsfWehbxY2FzI3Ncc6goF87CAVafrTqdaZWuZaQUp7VpO5Qas/dtFotfPnLX8ZnPvMZfOtb34IQAvv371+PlyaIM4pSncVpv+BXKoWCY2HXVLmnXbEbi3OUCnZOnZmzjkhPq0/ld3zExe+87MloeXkF4GKmkjUsQSRwPKmeFVwr/ZwLdX9FSycgX11qtkMUBohjca4rv3NLbTTbUY8K7mYgjETfdlfT0q197eTABEkWkwCwE59go0xcT4KXctFOA78/ef+3cOtLn6T9mbluw220QlRKDkSmarhVMJXfWHRUKbMKkeWijcW6bvEFOq3QduKNuz2zD15+YCL9d7FPsujRU53gV0iFT//bI/iFn+wobwPQbc+ZxUCU2DcMItu9MbPYRpy0ytda+jceGymg6NrYv3MUjs1TP++WH+HeRDjOVK/jWKJUtBBEOhs/SKDLJNPMe58PquAEQRBbBT+IEYQSrqOTm9vGS1ioeYhiiWozwOxSG47NUXRtrco8IAgMkrZiIfXaQEYKzXYIJ0nKc8709TVWqLcCjFcKqX2mF8QII6G9hJcxEIliiXsPL6DaCNDyI1gWwxMv39nzmH6XSSG0n3CcrJdWg/Y3xqoD8/Vi6OA3jmN87Wtfw2c+8xl89atfRRAEuPzyy/Fbv/VbePazn43LLrtsPbeTIM4IUi5f+Y1jvbgtLFPxNWwbL2q598zr8KQaDHTaHgFkbF5cbJ8o9VjfZAV8huWTX3sYP3xoHoBuEXUsjmOzTSxUvRWDX1157Jy86q1woDK0Dn518LhZ2zE9P+5b1WVMB0RhJLSoxCrans1ve2DXCB49Wcfdj8zj2qt2pZXfi/eNo94McXSmgSAU+M79M7jh2gsAaLXohhdihyhDSLnlZjuNz69J6nCGtNUZ6NgAzSSiYWMVF0rpDgqLM9gWw+++4imYXmjhygun0udlfX4N3YJU/37PdG/w29X2HEVyWSG4bAJLSoWZxTb27RhBPZkFHs/M7xZdC1Es8b0HZvCv3zue3m58fWMhYVkcjtTJAMdeXfDL2eafsScIgjhfiIREJGR67rc4g5A6UAzCGE0vgm0xjI8U0rVGN8dmGqg2Am0LlIxFhUmFd0ciFtl5P5FWkg08EdKKhVzWPrPZDrFY99H2I4yVXfhhb3I2lrJvh5RIZo3XotyslahlEvyu6inrwprbnr/73e/iTW96E6677jrccsstOHbsGF72spdBKYVbbrkFN998MwW+xKZBSoUgGjzzGwsJ29bqzSvhOhYu3jeea13U9iyJbVFyUgA6LYwj5f7VZBMQ+EE8tPG3CXz169mYSqpoi12tybGQuP+xxVymrjvo7qdObbAt7XFsVAc3I309fpG0dEfaW1VbIa3gA61UWmF3ktd76FgVtWaQVn5Hy25udjzMBGwW5whCoS8ISiGKt1brs2nzNu34xYKdu6iaY2U6CVzHKgVIpWBznraMlYs2HnfRtlyQ2i9ZtFjX1dgbrj2Q3lbvaj1XyTYppbBY9xHFy7c9dx8HX7jzMQAdL+3xkd455GzgC3RUrf1QwLE5LGt5a4tO8iwT/G7SJBNBEJuT9jo7T5xPmAAve81i0ONW9VaIqbEi9u3QOhXGrih73VdK4dR8C7GQKDg2/FAHt2bNlu1WUtCdhXGscmuafu4G/ag2A4SxxAW7xlB07aTKnH+OEH06lZTuNgwzlenVEMUyadvOi0+eaVYd/P75n/85nv3sZ+OVr3wlvve97+Gmm27Cl770JXziE5/Ay172sjO5jQRxxoiETKtF/ayORDIH2i8wWg2cM1SS11XQF5A4854jA1qpzcJZqvVR6LMtjrGKXph3Cy995huHcdsX7seHP39/Gjx0B7+NPr7EndfWCoNhJBBLOXSwfi4Jov5KzpxzCKlQbYVwHWtFe6ggFOks6s8+tWNb871Ds2mr+1jZxZOv6LQR1TPfrRa9MjPISJMKWwWlAKiO0nO5y/bHiMOZluixERdKJTYOiZplv4t3RyAuTt5HYamhkzzXXNaZq//u/TO55xlPxcW6j0dP1CDk8nZWJgA9uFvP5x8+UUPLi9K5qKxie/dnA7Snrznmw0hgpOTCsviyWfJKKZn5zbY9U+WXIIizxFLdx/2PLW45AcazhQnwuq8tfqjnc12bp+sPUxXOdtEFkUAQClSbAQqOBc4Z/DDuO1frWBzNdpiO5Bg45ytWZIXQ42s219dbk5jtDmTjuH+HVMuLEMc6cb/aQkgqjMVwVteOq17R/83f/A045/jwhz+Mz33uc/jN3/xNHDx4cOUnEsQGJo7lsjO/sZAouNaq/F37oU8gPH3tphelM6COzQfOkDqZk+FKrc/ff2C2R9Cn+6RYLFgYTarM2UC22gzwnft0QPDw8Sr+5P3fwtfvOg7P7wp+W4Ozvo5tIYyknkURZ1eufj2QSZay329sJ1nYKBKYGBms9G0wv5Vjc+zdMYLnP+NCAMBXvn0U3z80C0BX+y+/YBLXXLYdALBY61TircTuKIySym/y3lsFKVWSBEqC3679v/vv8YoLmfgvW5zlFJwNQki4rr6UBaGAVCpVwAR0Nfbpj98DAPjKd47mnqvnZ/XjG+0QUi3vf22E6l7wzIvT207ON9OK8vhIxq6sK/i9+YWPx3+96ScAdC7yOyZK4CtkvE13SLMdQSmVVAY21zFGEMTmJYolFms+5msU/A5DHMse/3jGGDw/hkjGXwyWxSGEzKklR8kMbduLEz0QiYWqh6CPQKNtc+0yIGWuU00n1pevyHqhdi0wTgpat0T1KDcLKXt87Y1zih8KOIneyaq+GyHTgsGGVHt+znOeg7m5ObzmNa/Ba1/7Wnz2s59Fu721PCiJ8w8/6PiwDpr5XY3I0SCM91olY3dkDMq3jRcHitwYn2C9jYOD39mlNv7xXx/C+z9zb24BvdToKPRdun8cz3v6hWlV6kcPz6f2Tnf+6GTPa37x34/klHL1dg+u/AJIWnTlmmY9Ngoq+Z9+v4S5kISxSOdnjs828OjJGmrNoKcVzAS/Zp/Z3We2erSsf4frnrAXQKdlFtDJEiElgjBOA2//NOyqNhpSKTAAXpfNkaG7WjpadiEVUgsIcwE3xELixHwT84mVkQmsTSW2UnLg2BxPyVTas97JZn7WKGRKMbjyG0YinYOfGivi0v0TAHQnhUloZduey6XOZ5scLeDgnrHcdtuWtkFzbGuFym9nRjhMMu4keEUQxNkiltrGppUk4AbhhzHufmR+2TXL+UjLj/L2BEhGqmIBIfNty6bymw04hdBaGft3jsCxOUbLLoJQoNmOeroSXZvrueFY9SZyV3AKCMIYYaxH/dJtEZ0CEYB0jdd9nSwXHZyab6VBcb9rVLMd9hRzQqOzoc5u2/OqV/XvfOc70Ww28aUvfQmf/exn8V/+y39BoVDA9ddfjyc96UkDF/EEsZGpZ1qA+9kYCan6ti+uFs65VnwuOUDNR7MdpQHTtrH+AlKGUsFCy4+WrfzOZER9mu0oDXDNXO/e7RW8+gVXAwCW6p2A+MFjVTz+ku09tjyGQ0eXcn93z0p2s3f7SGJyHm+6GVWldDWy3znMtjjCZAaXMX2xeu8n70lP7NvGi/idlz05fW46y5rsS/18W81vZILgZjuETC4mpgU2CAVYMm88vdjqEUTbrJjZnnbQf86++28teKVgJxYQrmPlLsR+EGNytAg/FKiUHLS8CI12mCYUJpJK7J7tnSTE0elGOndrcd2yz3kyl6UkLN7/spi1Myq4VlqRrbdCzFX1cbgj8zuZ3xcARjPt0IC+4LuuhaJroeBwtLzBx4xr81Q5vOVF6b+XU4gmCIJYL8ysaMuPcHSmgX07RvqOgrX9GI1WiEdO1PBjF287B1u68Wj7OjnavS4yifXuWWAdcOaLCEYDxAScxYKNlhcCDL3Br2Oh6UUI4z5J8xWcAvxQgKHT/cSYtjDKuo7IxLGhO7CeGCmk3XGzS+2e0RylFA4dWYLrWnj8Jdszn00klpIrzyOvJ2saZBwZGcGLX/xifOADH8BXv/pVvOENb8CRI0fwlre8BUop/P3f/z0+85nPoF6vr/xiBLEBMMJTxUGtzQw5xby1YhRqO5XfEHPJ3My2if6WQMY2qFhYufKb9WDL/nsuqW5NZWyHLtjdCcRmFvT9WQXqLI+e1MewmU9cyb/XMlW5TVb5FUJioeZDAX2l+wFdwTMCVSfmWrmLx0LNz4kgeWkLvRYscx0Lr/2PT0AW85uMlF0w6Llu4wFrJbZRQkrYnKNSctBeRmxss2EunLVEHbk7KOyuBI+WXbDMBb7g5qukYay9gG2ro6peb4ZpUsh814wxXHulrv7WuyrtOmkjdIU/Gmx1ZGaIx0cKYKzzfg8dW0IsFIqulbP5yio/j5byn1P/vlpLwHGsZQWvsu/V8iJwdvZtIQiCOH8RUsFxLISRwOxiOzeqk3uc0AFyyws3pfbHmcDM6hrBUYPp7OqeBWZMWx5mK7RBJHKVY9fmaPtx3zli2+KQSuUSsQalFKrNAI+dqvcNgvvdxhnLjdGJJBGy3CggZ6ynVdof4P8bRcnIGdNrobPF0Kv6nTt34tWvfjX+6Z/+CZ/73Odw880349ixY/jP//k/4xnPeAZe9apXDfW6jzzyCH71V38VT3ziE3HdddfhbW97G8Jw+aqTYWZmBr/3e7+Hpz3taXjCE56A5z3vefj0pz891HYQWx8hVRr8DWxtVoCznCnaKrA4T6vHTS/CsRntvbtvx0jPY6VSOD7XgFQqlaP3lml7NUEE0AnkgU7ld2dGAt+2OH7+uosAAN/40YnktfXnf+Vzr8Sbf+1peOVzr8y9/r6dehuXEon95T9nItSwiVoypxfbOHKqDiUHV9EmR4tpO+vMYu+ox1xGBCSrYmy4YPcoLsy0vJrf1eIsrR42MgFZGAk02hE415XOeAv5/ZqA7eR8E0A+OQPkg1/OtbKzUp22sIJj5b6LWEiMlF3YFk8DxGozSP2t9+/sJHzGkt+w3uokiaxkpskLYowkLdLWAHE7ox5tvIfN+5lE0cE9Y7lseLYFerSS7x6JhYLj6Gp2wbEgVji2Uq9wX+8XUm2uJBNBEJuXONbJ2CAUaPtRdwdvipAymU89u1W8jUwkJKB6OwtNB8+gNuSs4FUYidxcFmMsTYD2S9bunqpgpOz23O5YFprtCLOL7b4ipv3Wbq6tfexNMsPYFS4ng8M56xHqTD2Kuz5vlIzyMPQGzGeS4UtaGS655BLceuutuP322/F//s//wYtf/GI89NBDa36dWq2Gm266CVEU4V3vehduvfVWfPzjH8db3/rWFZ87OzuLl7zkJZidncWf/Mmf4H//7/+Nl73sZasOnInzDylVGvz1VXpORJBOp/IL6PYWE1zXmkEaQO3vE/wGoRZWGim7KCSG6P3ank8ttPDuf/gB/v2eU+lt2Qpk6iPcZaVkFu5hJCGETIWtRssuXMfCga423d1Tul1USIW5peXFLqwk47iZArUwElis+3oWdRUdpP1+i6wCpmkPKnVd6A7u7m1/BjqtsVnF5707RtBoh7prIMkObxV1X2OBcHRaB6eTo/ngdyLztzQJia7Kb/frlYs2HJtj56TOdB+baWA22Vez7c6mEpudsXasZO5KKIyW3YFe1kAnaDZB7UhXNffHLsq3+W3LZPorGVV3KRWa7TBdyxSW8Vzsfn7bi1PFawp+CYI4G0Sx7oiZGC2i6UW5wCyLlNo2jpJzHaTsLyjiOBZaXgTVL5XQ5T8fhAJW1wJFKR0gr0WMtVy0EYQCXhgjinp/w36zvKWCjUY7SkUqTeV3uZEbi7PeCm8i2iWkTPeTI9P1ZOyIJe3eZ0/fZHglnwFce+21uPbaa/GHf/iHa37uRz/6UbRaLbz73e/GxMQEAEAIgT/+4z/GzTffjF27dg187tvf/nbs3r0bf/u3fwsrqdQ9/elPH+ozEOcHSqkegaIskZBwkvm+0yGr6vzoyTqE1C2SWa9XQywkHEu/p6kQmmpiLGTqdfqRLx/qsR1oZIJfY2c02pX9u+zAZPrvuarX8/m7H1/JiPa882N34fW/eA329gnaU1YQVNgIHJ2uo+Da2DVVhh/GiBNfukHtrlm8Pl6H2d/BSyu/+X3mPzzlAGIhcXVm1gXQM60n51v497tP4cqDUwB0MLRrsgzXsVIRsXiLLCSiWKYVVADYvzO/L2WtvxxbWzMwIFWtdOzeY7HgWCg4VrpfHp2uo5VJ6hiM1Ve9FeKHD81hcrSI/TtHEMYBHGuZ7o8E02VhguisoNXjLprK2VcB+cB+vNI51r0gxvhoAft26ISIZXGwFX7eXOWXMb3A3CL7BEEQGxvjfz5WcdH2o4EVOh0YdWaEiSSI7fNVWJxhx2R54LojW0To5z/v2BwtP06va6vBsTm8INbWlH1mgoXoFckquBaWmgGaXoRKyUkqv73t1lk410KS2fbopYafBL8qnWGeXmhBCJV0uMnNV/nth22vPa7++te/jqc//elp4AsAz3ve8yClxDe/+c2Bz2s2m/jCF76Al7/85WngSxArIaVKK5/FfsFvrANRdxWVmeVwbCtdWJt5w11T5b6ZMym1uE/RteAmC30/1Oq1b/ngt/Hf3nMH/n/v+/e+fnvNjHiXaaMd7ar8cs7SgGM+kcoH8pXvF/xkx8alXHBwdUa44l+/d3z5D8uw4TO+M4ttzCy0ACQV8ERgyuIrnw6NUNM1l23HTz5xH4CutuekRb27xcl1LPzcdRfj4O6x3O0mGD6atMIbCq4NxjoCWJuplXw5hJCoJrOzB3aN9g043/BLT8SebRW8+D9cmoh88PS3cR0OxjqtVwy6s8J1rFRIbKkRpEmIbMV1LBG/OjXfwse+8iDe888/SlXKhVRpu/PJuSb+7osP9BxjZqbeVH4v2juOC3aN4von78crn3tVz2KAc4ZXPe8qPOuJ+3Jew7HQc8o7p/RIgm0xqBXyLmZsop20PQu58Y8zgiC2BkHUqTByzgbqkEipYFlsSyVsT5flkgBar6J33dH9HUd9rBh3TpUxOVLo+/xBWJwjStSb+3WTxX0sjBjTFoPmum2qtstVfu1k3RLlRpQUoLSIp/EtbnkR/DCGbenrener9Jlk3Su/p8Phw4fx4he/OHfb2NgYduzYgcOHDw983r333osoimDbNl75ylfirrvuwsTEBF74whfit3/7t+E4/dV6b7jhhoGveerUKezevZvsnLYwXhCj7SeeuxaDH+RFHJrtAONlF4F/et52Ig5h8/wJcHLU7Xk/APD8ADZ3wSQDS8pBLS/EQ0cX0sBqkPVNvenDD3zEsUxVnMvF3s9VTDxRpxeanRtVDD9IAmG3c1KzLYkXXX8hHBu468EFLNTbfbfbEAYh2l4b7fbGVKGVUqHV9qEKFtrtNurNNgqOQsFWCKP+ytdZzFz1vh1lbBsv4t9+oMXFzHfSauvXsC217PdkuHivbsv1Q4Fas9W3BdbzAzSaLTh881setdoeTiXzvjsnC32/o8lRC79+o54993wfURQhDDy0WYw4jCBEjJbn6RkkFUPGAZSMYDF94cwGhRyd/bro9C5Cjk1XEUYCkc0xVuaIAPzjvz6I6QUP9z66gF969sW44oIJcN65+JcKnWPqV37ucgAY+FtftKeMi/aUIUQI09HV9gO4lpteWwI/QBiE8Hw+cEFRcPTt9VaAKArgeT6arRZsNoSliOfBCkMgDLGqXn+CIIYnOdaE523K4y0WEo1mG4wBfqAgRIRavYV2u1ews9FsQ4oIni/QbLbAVe/c6flGs9VGGIXwg9UXUaSIsFRrpt9xq+0jigT8riWKbQ2+9gzC9wO93qi30J7Ix0btlpdsa34/ZYgxu9jA/u0FtNohfD9AWGIDr1dRJND2YjQaTQiTuG23YVsSLc9HtdaESj6XEEpfe6MIrZY4rZhrLQ4IGyr4rdfrGBsb67l9fHwctVpt4PPm5+cBAH/wB3+AX/7lX8brX/96/OhHP8Jf/dVfgXOO//Sf/tNQ2xOGIe6///6hnktsfLxQYn5R71eB18SRI0dy91ebArsmHdwfzZ7W+8zVItS7qkiW8nreDwDqbYGJio16yYLX1tXApWoDh8XKAfhCtYEjR46g2tQLYsdimJ85gYWuk4FIgrzj0wv6cTbDsWNH0/tb9c6CurY0jyOqhv0TAncBqNb9vtttWGrEsKIFVGeHt4c6k0SxwpETbZRcCyyYwZHjHpQCSgWOhVU8v1rXgVurvoRKYomzVA/w6KOPgXOGxVpyf6OGI0dWDqYBXfmLhcKDDx/BWLn3ArnYiFGQi5ga2VCn66F4ZNrHoye1jdaIHeDIkSOIhcJiQ2BqVKs2Z4liiSBWeJAtouBwREJh+lQb85YW/FAKeIQvYakZY3Y+gGszhLEOcgtOfr9WSsHiQDa5fOiR49i7zUFLKERt/d1PL3SOtX/4l8P4qatHcXCnm1Z+G9U5HAkXh/4O6m2B5ogNK9TnlZYvMD3to1Xjuey+ERhhjMFv6W2aX6rj6NGjWGrGKKlFjFfWvk9w38fU9DREsQjp0uKUIM4kPAxh+T4WDx2CLPZ3eNjIhLHEkRMeXJvBtTlavsCcxdPzV5ZjcwEWGhGkAqxoAdtGN/8163Q5vhBgrhbBq6/+u/BDiWkFMH8WFgeOnvAgJLBUWJ9m3aYncChYRNzK74+PnvLgBRL1Un4dEkQSQgBONId2IHDylA+vMfjzCKnQ9CRKagHlZATs4ZMe/EgiioGCXIRSwMysj/GKhaNHGbxAV52Lcq7Xn3iVhGGIQmF1beBbYs+UyfD9M57xDPz+7/8+AOBpT3saWq0W3v/+9+OWW25Bsc9J5/bbbx/4mjfccAOUUrjqqqvOzEYT55xGO0Th+x6AANu3TeLgwb25+0uLHq44OIG9GdGcYZhYaCHgC8APOxZgV1++v68I0tyShwt2jWJsxMW9Jx8BHvNgOQVI7gDIZ8TGKy5afoRL9o3j0NEqYmXh4MGD8I9UAVSxfaKECy+8sOc9tp04ikdn5iDgAvBRLjo4ePBgev92L8Jnv1MFABy8YB92Tpaww4/xmW9X4UcK+/YfGNhqU1ps46L9Eziwa5m54HOIF8RoqDmMlF1cfuEkGnIWlsX7Cp71Q32/CSDGgX27cdHeUbBvLkEpYPuuvRgtu+D3HAIQYt+enTh4cHKllwMAjJbrWGqEmJja2fd74zNNjG+r4Kot4Ju4FE+j3tbJyqc8/iKMlBzUmiEmt2vBscmuOXgv0MIcj7tyB9zEEsjjc2DQF1jXtvD4K3dgdsmDcBYwPuJjrqoz4SNlN7dfA8D4SDM3c1yojOPySztaEnoMYD73nFZcxK49exFLnR656rILYZ+GCN7ckoeDu0dx0V6d6G22I7TZHMYrbvq6QSgwvdgGg1YLb8kl4NBhgOvPVFz0cOCCCezbMcS5qd2GNTcHjIwAq1woEAQxJEEANJvYccUVQLm88uM3GC0vQl3OY7Ss1fCbXgQlFS69bGePGCgrLaFU89D2Y4xOVXDphZOnLRi62WGPLaEw4uUEEFcijiWWGgF27ZvC9vEimpiDgsppYpwO9VYI17Fw1RU7crf7fA5+JNIRIkMQCXh+jMsv24GGF6GNReyaGiwOKaXCQs3HJZdux8RIAUopNDEHIRXafow9e0bg2hZCq5a+TtuPIaTCFZfvGPr66q4hmbuhgt+xsTE0Go2e22u1GsbHx5d9HqAD3ixPf/rT8Z73vAdHjhzBFVdcsebtYYyhvAlPVsTqCIWVVoHKRRfFQv7k5LgCYyOV094HKp5CuZQPXC/aO9UzSxwLCdsRGB0tY7TsolzSC9MwVqg2OvO8N1x7ALNVDz/7Exdg23gJM4ttHDp6F1pejGKhiGpLV253TJZ7PhMAVBKV2npLv2a54OQeV3ALuPyCSbT9CHt3jMO2OAquSiuUUcwxUu5/Ii8UJBzX3bDHjWQRbMeF47hwC0VYjotKwUbBXd2p0A/1DjM+WkapWEK56KDlRYiFhWKhiDBRUBytlPp+9/0YKRew1AgRCdb3OWMjEkJZKBSKA214NgNSKjTauvd3pORg+4RO/jQ9hckxF3NVD0tNge3jxVTYKpYRbFthZKSSJlwqpYa2RxAKIxW9r43HHG6hidFKoRP8lgo93+f4SCEX/IYRco+ptXpbrmzbhh/pTHSl6GCkcnr7tuMIjI12ziuKRSgVC3BdNz0nzNUauGD3JBrtEIuNGBOj+rFeIFAsFFEsSIA7wx1nSgGuq/+j4JcgzizmeCuVNmXwG8kAjuOgVCzqczCz4QUx3EKxR7PBcVsoFhRsWyKMAcspoLxOAdumxWqgXCquej0AACgAtbYEmI1CsQTHdWExhmJhfb7LSHAwAMViKddtZDkuilyi2HVdsCyJKA7gFIooSAsFt3e93E2tLVEoFFEul7SQq+PCZQwKETh3IRlDsdC5RivECCOBQqm0KgeEfqy25Rk4zeD3Bz/4Ab71rW9hYWEBL3/5y3HhhRfC8zwcPnwYF154ISqVtWWlL7744p7Z3kajgbm5OVx88cUDngVceumly75uEKyu/ZA4v1BKIUiClW5FZ2N9sx5Zy35CSt2Br1QKJ+eakEqrDnPOUEraRbS3ng5o+6ktG1ErPxSIhUwtiYygTjcm0DNzwd3KxIwx/MrPPa7ntrFKAYt1H7VWiMmx/ic+xja22nNqxZBYxaxk1t6N+R3KyUW/kgS/Dx1bwt996YHUX3m1lWSgo3CctarKMlZxtUeekJs6+BVSYSnZ57JK55GQcB0LiasRmu0Ik2N6n9S/D3KKmBbnCKQWqTLHrWNz2BZPjxkgr1RuGK/0VpazTCdCaFma7RAPHtGt2uMj69AmzDrq1QBSBfesMIpSCqWCjTASkFKhVNSfq52ojVucIT6LthAEQZyfGNuiVPCKDbZai4VeN20bL2Gh5m0Zi75hMWKaaxGlMhRdC412qK2BhILrrt+130p8eLVVUudaO2hm1rIYYilTZwxAC4fOLrXx+C4HCwNDInIFpH7GBZfDsThafoRY5MW1OAOESsQ9T1NkdjUM9W2GYYjXv/71eNnLXoa//Mu/xG233YZTp7TfKOccr371q/HhD394za/7rGc9C3fccQfq9U576Be/+EVwznHdddcNfN6+fftw+eWX44477sjdfscdd6BYLK4YHBPnJ1rpVS8guzNNxjx8LYHRIGxLr+qfdvVuMAa86rlX9jwmjiXKJSc9SdoWR8HpBKmtZNHbr3WmWLDT7Wx6EeZrOvjdPqDNppgEDEZWfiWLF4Oxjelnjm7gTJ8kNyr6BK9Vh6NYBxarnS+JYpHaD5SS4NYEWF/89yNp4Augp21oOSorBL+cM0glN711hBAytQuaSBSTVZJkGik7KBZsbaWgOp9TKgXHtnIXZMfm6YLMHLeWxWFxllPZrhR7s+RjXcGr8fk2fOwrD6b/viJpW7/n8AK+9C0957572+mNQAAAVD4hZlk8VfUG9HFZTKy4SgUbts3Tz+n5cZqwCfv4NBIEQawFP4xxfLYxUD3eXHfMdVJfj/o7EAghwZn2bJVS9bXTOZ+IYoE4VkMFv7alW8yjWEIqCbYOa1FDmsAQ+WutUv2rp5wxQOlEtQmS3/mxu/CRLx/CoycH6DExpH7QxuPXtjgsi0FIhcW6nxtzYoxBJTZKZ4Ohgt93vvOd+OpXv4o3v/nN+OIXv5gKcwBAoVDAc5/73GXnaQfx0pe+FJVKBbfccgu+8Y1v4BOf+ATe9ra34aUvfWnO4/emm27Cz/zMz+See+utt+Jf/uVf8D/+x//AN7/5TbznPe/B+9//fvzKr/zKhm3BJM4tQqp0ATko+B3mpNWNXphzPO/pF+L/vekncNVFvbObQirYnGNitIDRsguLszQoNUHqSMnp257LGUurh3/5ke/j6LQeHdg23n8mo9hV5e729h3ESFJhzloqdcMYNnS2VyltkSOUzsiupfJrqr6cdfaXSp+WLsb6B16DMI9tDQp+GYPcAtY2sVSpT7Kx7jHJh8nRIqbGiigX7dznlFLB7eq+cByeXoCNRZlJVGWP43K/4LcrKTHIsuPCPWOplVWW3dvW4VrCkBP2si0Gm7N0oSASf/Gxiov9u0bhOhaqSdJAQVerOWMb+jgjCGJzsFQPcHS6MfD6093JZXEGIXorvzKxtsleT4MBzhTnC0IoSCUHevlmUUrhgSOL6e9QKtipHZCUWDZJ/537pnH7d46uOkHOufaKz/6GZm203KbGQgexs0sdUcgTc82+j9VFhqTyG0vEUsKy9Jo6CGPYnKfjTWabpOpvDeUFcdqVJaRKxSdPh6FW9p/73Ofw0pe+FC95yUv6zuJecsklOHbs2Jpfd3x8HB/60IdgWRZuueUW/Pmf/zl+8Rd/MRWxMkgpIbpavp797GfjL/7iL3DnnXfi5ptvxsc//nG84Q1vwG//9m+veTuI8wMpVRpYdrchC6lgcX5awjYG22KwOCBVb7BkTjjGH++S/RMYHynAsnhPO/KgYBbotM5mTcIHVX67A+gdk4Nft997nFpoDTQj55ylrS4bEam04byQKvU4zmY6a82gpxXWYG4vFZz0Of2CXLWCAXw3K7U9W2mmfeN+r6shCGOE6fGmjyuRJJkcm+Pxl2zH5Ggxd/GTUsFx8segbVmIhYRCpvLLtRdhNrEzTNvzjgl9LNxw7YG+4iKP65O4WgsiCfazSTXGGIoFG7FQaHkRFup+Wg3eOVnCaMlBwbHSz9byIz1esIE7LAiC2BxIpeCHcdoF1013kGuufXFX5VckVbtshXhQcvF8IRYy1zK+HD94cA4f/vz9+NDn7wOg/evDWKLe0q3PgwLohZqHf/7aI7j9u8fw7fumV7VdLEmoZ7ushFDLdsKp5DFhJHLdf4OKIbrtOWM/mOwbpYINPxA9o3OMsXQkrZuTc00cm2mg2Q5x3+EFPHh0CUuNtVk8dTPUzO/CwsKyAlKWZcH3h9uwSy65BB/84AeXfcxtt93W9/bnP//5eP7znz/U+xLnH9m25+7gd3qhhT3bKz1Vp2Gwk4Vsv4P61GILYSgwNabFjMzi2+IM5a4gdfvEYIGBfgv1QSJO3ZXfXZOrq2aZCvF375/Bd++fwe+96loIqTCVOYlxxnouihsJHfsqyOQkjsx5fqnh4x0fvSsN7C87MIGX/cwVaXWx3tIn/GwCo1/ld62YVtyFan87q7TNbJMHO/NVLw1+zSx9LCRsm6d/m5lxkcw3x0Ki1LUfuw6HF8RppRjQ3xHnLP2tgP6V3+0T+URPd/BrEhAjZbfnmLrp+Y/L7evDYDoNuhcyhaSaPbvURsHVlk+2pWeBD+wexcxSG+WiAz+Z/y+6ukK+Fl9DgiCILEopzC21EYZyYNJ60PW8ez0TRAJCSLhupxvHD8/v4FckrcWrqfzeeY8eHT0+qyupnGk7vyAUOqkw4DXuOdwxabznkQU87eo9PY/54UNzWt35win92smaIvsbmuvJoPfhjCGMBFp+BM/v/K7VAVVYPZqj19fZfYgx1qNbo19f71PZgDy7be0gxpHpBk4tNBFFEuWCjcnR4a/HQ63s9+zZ0yNMleX73/8+LrjggqE3iiDOBkLoNh0gL2xlxGYqJWddFpamKtVvRiaOJcZGCmj5MRyLp+/HOUOhYOe2a/tyld+u1uWL9w5WRy92BRODhLEAnSAwJyPT9mz4/9/2XfzF338PC7VO0KYrvxt3PtXMtQgpdct7ZjMfPlbNVbQfOlbFl7/d8YmdT4LTbBKiX/C7VqXCC3Zp1eNT8y1UGwPaeRQ2dEV9JWKhM9hxGvwmas6iU/kFgKnxEsolG1Es066IbrVQO5nvdWyejgYwxuBYHAd2duzDTLImO5azc7KEZ16zN10EtDMXcSFkGgyPlJzcLD0ATI6dvjKyaSvrXmA4tgUhFRybw3Ws3LnAsbSYlwn0234EznQiZ6MeZwRBbHzCWKLZjiCU7Ls+AZKEYPdphuXPPX4Y46Gji7ngybY42olGwfmK6dZazToyqwNhgkXT9bUcM4sdh4KjM42ehO5Sw8fHvvIgbvvC/el9JtAUXcGvkIODbIszBFGsW7H9TrV30JrFiGp1Ps/y3wFLFC/77S9KKYShQBQLcMZRLjo43VLAUMHvz//8z+OjH/0o7rrrrvQ28+N+/OMfxxe+8AW88IUvPM1NI4gzi5QqXYxnK79BJGBZHPt39vrwDoMR4+k+iQkhUXAsuDZHGIm0FdTgOlZOjGo5n7isuvDPPeMivPw5+c6MMOqINWWVrW2LL+sdN7vYxvEZPUPcL8smFfDoyY5AnW1xRLHEvYcXNuSMqlKAlWRUpVS5a/rxPrMrWfXf+ZruZslWDyuZ7333VBljFRcvf06voNlyjI8UcGDXKBSAx04tIx6xgSvqKxFGQgdtyS6erfyWi50kU9G1YCfiT7HQPr6unU8mpPO9bq8Q1mjFxdWXbMPOyTIO7h5FGAkcnW6kbVqMMTz/GRfhxmddAkAv2sxx2UoCYca0oJlp0TKUVykMtxymot2tJeA6FsJYwE5mfbdl9jHHsXKBftOLMt0ACgs1LxfgEwRBrAat3quTwFEsMbvYxmMZASMhFZrtsLf6q/LVvDCSaLSjNJkJJOe0SKbVv/ORtXRrZeNjI55pW0zb+i0TPM9mgt9YSBybydvFnpjrrGHMesZcN/OVXwkpB78X5wyeLxDFMjeiNUgAlXOGKOoIXvVmUHoZlNANQpF0hOkEsW3z054nH+pq/trXvhY//OEP8cpXvhIXX3wxGGP40z/9U9RqNUxPT+Onfuqn8Cu/8iuntWEEcabR1kD6QDPBbxAJzC61MV4prKs5u+tY6YypIYq1xYvFuT6ouyqGrqMXvKbddtvE4MpvdpH+9Cfs6TmBnZpvAQw4uHusZy5yuaxkGAu4jgWlFC7aO4bHX7INLS/G4cwFsp45+dkWR60ZgHOGejMYaIl0rlAqH/BmP/nJ5CIxVnFx8d5x/OChudxJfiFV0e78DiOlTsX9OU87iCsOTq24DW0/QsG1c61QOydLODbTwEJ9wLiIGtx+thnQao+duWVzbMmMYjNgbH9MFloLZHTbkBVcK62OZjFCWC//2U7yodoIMDVeRNuPc8Ju5nhRCghDgWLBTrPZ5aKTHj/Z36i0BhGzQZiZqu42OPN9jJQcXH7BZC4h5docRddOuwyW6kGijAkcPllDoxXCdaxVC9cRBHH+cGK2Ac459mzvVarXra96RKraDLBQ8+CHAvt2jsKx9XhJy4v6jnss1n1csHsMgFY1DkKBMBapHZ/raKseL4xz4yjnE/0KAPNVD+Wi3TOWk+1CWqz52DlZhsV1YWS5tumFJCk/VnFRb4W5qqx+rU5n3lI9wEV7+2+fNDPbg9qeOUuS0h3XBmB5rZIwEtpSNFz+MxjMtb+bMJaIhEAQifRambp1DKmCPdTq3nVd/O3f/i3e8pa34MCBA7j44osRhiGuuOIKvPWtb8V73vMeWNaZ92kiiNOhHXQOYNfmiYpdG2PlAkbLzqotgFaDWZhnCWOt6mpsc7rni13bygWx25YJJJ9y5U7s2VbBT16zt2/mzrZ5epLIzgI79vLHqcV1lSoWWq7/ZT97JX7txqvxzGs6Z9ClTMDm2Bx7t49gqe4PnAU5l5gqn4I+eWYDf5PBfOVzr8TPPFWPbSzV/fR367Q9d4LfA7tGMDlaQLlo42CyEFiOWEjM17zcdwYgXVws1ft/Z4yxgSJjm4FYSEil0gDeXMBMq6+BMa3YbLoybIv3HBdjZRdjFRe8yz/b5rynuyKMBUoFq6cyanyBgc7cr1HZHBkw072ai/dKyKQtsLftWfsfTowWMVp2c/slYzoBMJnYQ52cb+rKL/TMVradnCAIwtDyIpyYa+HYTKNvd4iZsSwVbLS8CF6oA4wgmdU19n7do1ImKW9aXk1VLqsfYuyO4vj87UqJY5lLts8utfHOj92Fv/3UPT3XqnYmaDUBrGUx3eo74NoThHFaVDHJjWwQ7YcxvvjvR9K/u1uiu2d+l7vCaZVvPS6WHXWLYpnuL/nHc8SJqGy9FaZJkWVRep3VzBRUVKLNI6Veo5UKunBgAvFhGXp1zxjDjTfeiBtvvHHoNyeIc4kZ2mfQi89aK8TkSAFT4yVcfsHEur5XIZnpyyKkRLnoouhYYLw3ELVtnqsWd4tyZRmrFPCGX35i3/uUSjyLk7+zi/jlBL2kVFqp2tI2LE4mV/b8Z1wEx+b41+8dx7GZfLuw61gYHylgbqmNC3aPJRfgJsJIoOBYuPLClaujZwwF/YMrYKkRpIGOUqoT/JRdjCV2U0IqVJsBxipueqHPtp87toXX/9ITc7Y7yxHFEiMlB7VWmAuiJxK/u4HiEQybOviVSddTFJvKr96XlVI9HRa2pYPYSChUik7PRdOyOC7dP9FzPDiO1bOg0Ptw/+OmVLDQaOs530l0VCuzAe9/ePJ+/P2XD63a4ujEXBNBJHBg50jfxJJUQCEzz5v9zLbNB9pMuDbH7mRxc2Kuqe2vhF5YhJFIhcQIgiAMDx+votr0UXAsHD5RwyX7J3L3C6mS7hueBlxCyNTP9fhME7Hora6NVVwcma7jsVM1PHF0J2JhunR6r4GROH/bnttBlOtQuvvheQipML3YxlLdTx08lFK54Ne09FqcoRXJgV2IpupbKtipZ272dT75tUd6tqcDy7VlS6mWHcu1LV2FDqIYflfLcb0VYkcfYcpqM8RCzYcfxj1Cq/3QVn4Rjs00cdVFU+l2KaULBCZprZQWwNLjgsMVWtevr5MgNhleoA9gx9aL0SgSmBgr4oqDk+uuoOo6vcGvsXFxExuT7guMlXixnS4dhdne6vNylV9j9zRIqfrqS7YD0NnMbo/AUsGGF8QIwhi1ZoDjM9pHsOVHqDaC3JzK2cRYHU2NFpJ5U33C9kOR/j6VogPOGcaTSlujrTPcCjoI6Z6RLhV6W5gGoT1cLYyW3Fy21FgmZVUUs3DOBlpRbAY6ZvfJMWcWBAw986+2rfc3IRTKfeyKAGByrNgjNmZxNnCsSCjVM3ZgOjuWq/xefcl23PT8x+EVq53jVrqFPdsWlrs7SSh1U0wWL91q1AbH4un+2PbjxEJDJrZ/alPvGwRBnBlsiyGMJKrNsG9i1VTOTHeXSCq1YSThhzHq7f5dJYwxjJRceEHcI5yUxdjjnK94QQwrOd//6OF53P7djgVsdg3kJ4rOBnOtKrg2IiEH6rKcSmZ492yroFzQj8muxX708HzP9hgU8vaJsZDLjuXaFoMXxAhDmf5t3EnMaF4Wx7YQC4F6K0hmdVcOUjljWGoECDPXM5F0J7gOT6/5JhCvD5g3Xg1DV36/+93v4hOf+ASOHz+OWq3Ws0hnjOHTn/700BtGEGca40FnZm1jqZYVfzodLIuBdaXVhFRJq2MBEyPFnmPI4hxPe/wefOGOx/Dsaw8M/d6m1dL422aD7FJh8AlJKgVuMfABcxh7tlUwWnbQaEc4tdDCpZmssj7xhclFVNuzeGGM3VMVPHqyilgo7JgsnXWbFpVUfguujb3bO3L7puW56FpplrVctLFY1xcTk4mdHCue1jaLJOFRKTloelGaKTdBePe8jsHiPFVO3IyYiqypXjsOT/f3ngpuUvlVCj1iV8vRnTxSSnWCawXMLLZwwa5Oa3qp4ADw0gWBmV3qDqqvODi5qveXUsG2GUpFBy0vxmLDh80ZxjLewlKpvt7hBcfCEy7dMVhp0+ZwLJZ2IwSRgIJWyxZKbequAIIgzgxhJDFWdrVnbGJFlO2kEUKfIy2LQ0gJBoZQCMwstODYo2j7EXYNcIMoF3VgJqQc2H6a9Xo93+jMuurr2Uf/76Hc/YsZleR213XfBL8WZzkHg27MKNaOyRIqiRuHuY5lA1Jz3ci2RHPGch1DUSyXrfw6ttbaMNfrSsnB+IiLuaq3TMcahxcKxIl+Rz+qjQBf/vYR/OQ1+7BjsoSZxTb8IIZKBB3vPTwPKRUsJz8KpBQwPd/Cnm2VodZkQ1V+P/CBD+BVr3oVvvCFL6DZbGJ8fBwTExO5/8bHB1utEMS5RkqVtoAUEkEnxrCuc75ZLM4B1t32rFAuOhiruLhw7xh2dvntWpzhkn3j+L1XXYsbTiv41W2zlsUws6gzhc++9gA4A37qyfsHP08qWIylglz92Jf4tZn2m+y2m0V6248wMVrAjvESYiFxcr6FIBLnbsHe56O0+gQ+aTU2iFNDddNatBp0ANdb7XdtC5WSFlgyFXVTOW77+qQfRiJVfAQAzrGp5zrN5zQBvJ6xV7A57xG0siyWtDr1DxQHYXGWu3ib1x8fdTE5VoDb1RZtEj+dyq9eLAybANMCXRwFW7+P58U9iwKlBs8OLyfcoYXAeNpa7/lxmsyCwnmtqEoQRH+EkOCJLVwUy55rbhSL9HoYxbqLxLUtNLxIXxMVBo7z8GSmd3bJQxj1n0vNer2eb4TJ92lbDIu1XiHL7PW9u3K6WiXjk/N6Pbdrqpxet8xa5uHjVQDAvh0VvOg/XAogH2RbnCHOtKQHYQybL3+9nRorpr/nSMlN16wn+jhlALqYEIQxlMJAFel/+d4x/ODBOfzPT/wQtsUxOVpAJHTRxA9iVJshml7U0yE2WnZ0YD1kZ8FQK/33ve99ePKTn4z3vOc9GB1dHzsYgjib6MAsuxDX4jqrmUsYBsvqbclkSVWKMdYT+JrnZNtvh0UH9gxFV7ciK6Vww7UH8FNP2r+sorWpEhcKVk9m0mC2baHmYbHu51QhGYBmO0TLi+DaHI7NsdjwtedxIlYw7LzGsAxqI2+mLa+9isBeEKf3T6zSVF1IhaMzdYyW3Fwrq0jUjXdtK2O+6iESEgVupZZJsdALlH/66sP40cPz+PUbr8ZFe8cTn2iVtKKf3Wr5emA6B4z1gfa11dngbtXm7EVuLZ+Vc50NNsRCz0ptGy9BKeDBo0sIQpH+rub/20GM279zFN99YBbA6QS/+rcxftiWxWDBSo8/IKn8rrDA6IdJnpWNME0Qw3V5Khi2mbsCCIJYf5RSiIQEyySwg0jkglkviNOgdbTsAgwYLbmYr3qDPecTzGvOLLQQi17tBv0Ydt6em0RSFS9Zdhoc7pws42lX78an/+1wTvSyO/gdlDAII4GZxTb27RwBA1JbowO7RtPnmLXK3Y/olufLDkymifyWl6n8ZqyI9GvLXAKj2gxwcq6Jqy6cylVWm5nxoIN7xnDH3ad67JUMJumyXPX/waNLADoJctviaLRDHD5Rw94dFQghsWdbpUf7w3UseEGcXufXylCVX8/z8IIXvIACX2LTIqREmGTXHMdClCgvd9sNrRdmQZ8LvhQGtoIA+uJiAsXTwWTdykUbrm0hTi6IK50wTDV8rOwOrNKaSug3fngSf/7330uzjYA+uTbaIaLk5KRnm21sHy9BisFzQmcShf5jLeZCPzaSCX6TgLTtx6gnM5wTI6uzk6k1A2wfL/XMpEilLa3GKq5uNTOVUMdKA722H6ezOnfefQpAYjOgFOQafAM3EuZzpjO/yVwv56znGLCWmQdeju5A2YiwOBbH7iQznp15MsHvvYcXcrNY3W3PqyWKZZqsKrhWqrCenZeXUi17zA/CfA/pPhnE+hgSErY9uDODIIjzE5lc7HSSncELYyxlAlqjFG8S0JOjRUyOFGFbOmDpFg/sxrYY/DBGO4jR8qO+Pujnc+XXzFBzzjCfqCNfsGsEO5M28unMzG938NstKGX4/B2P4X/9049w16FZ1Fsh/FBX3HdnKr/NJDn64BEdVD75ip3pNS07VsW7HCSCjKXSPY/M4223fRf/54sP4IHkdQzZ8aDdyWeZXfLSa3wW29J+vMtd8fo5H7S8WLfTx3r8qd86wCRfhm2rHyr4fepTn4oHH3xwqDckiI2AlApBshB3bY4w1nL+y6kfnw6m8mlONmYesbvqlcVOKr/9xKbWgpQKjDNcsn8CrmulFe/VPM+2+LKt4FkfX6WAO350Mv3btD5HkYBjW2CMYXK0mKrynu7nGgY1QNAwtTHKKDmX3E7lt9ZKguPK6qrwRkyrXLR77ATcRLHQtTmmF/R8C0uSE0D+AmWy5mY/2KxBjhA6kWI+Txr8MtbTDpUGsSqpeK4SzrRHsFm0iaTFXAfYHNsnSjnRK7NfH5/Nt2ytFPxGscSx2UZPQiiOZdLS7qDgWCg6+r27F5GrEf7oxohkmX3SD2JIpbfFsTjiJLt+5FQNfh/bCYIgzi+UUpAw50WtF5ANssJYwA9EzmfdUHQttL1o2c4sxhjGKi7CZLSpn9KzbXEEgTgnie5zjRC67dniLE2ej48UsHebVu2vNoK0o66WjMeMJ8n1fm3PUil8+75pADopbp5jEukj5c5zj800oKBdJLZPlNK1RduP0gIM5515bJFYC5pr79fuOpG+76Mna7ntMNeXUsHGtokS3GRdu1jvbe0213mjat2PbEFISt0lpdurJVp+NLBzQK8vl68qL8dQK/0//MM/xJ133on3ve99qFarQ70xQZxLpEJa+XUTX9GC02tBsl4UXDutMAOdFsnl5vyMH+jpVvukUuDQn7PgWMueLKJY4LHpOtrJPKpt6aB9UOpuqst7eLTcqYyagE11GadzhmUVIs8kg75Lk5nNtiibKpsXxOmiYWyVlV8htXeim2lJDcIYDLrSyRjD2EgBxYKFuSTwNq1JtcycqJnz5YylAhCbkVhKKIW0LdmxOWRSlehVOeepSNta2pm0onknWSSERCEj6FZwrdxuPCips1Lbc9uPUCrYacLEEAupFyKcYc+2CqbGi0nwm3nQGqvZBsvisHhnLKPtR7qS7cdwkrGNaiPAsZlmutAiCOL8xegmmPNrwdHjS+Ya0vZjREL0PcdKBdRa4YoaKGOVAsJI5MaFstiWvv7NJKrE5xNmFpUxhlqrE/wWCzbGK/r7Wqj5aPtRei0x42/dzgSPnqzhbbd9N/27XLRRNQF18lpFt9M99sgJHbCayqxZW8RCpZV401X48LGqFkPL7CtG4wToTQ6bwLzgWuCMZWwae687jDHs3lZZdj8Ko3z12by258dYqvsDr5fm2jpsEWWomd89e/bgJS95Cd72trfhz/7sz1AoFMC7MvSMMXzve98baqMI4kwjpUqV7lxHt5+eqZZnQC/2C8mMgnl/i7NlF8KOzdPq6elghIMszlBwOJrtwcGvFwiMVdx0O22L5dqvu1tLs563AOBlqk6Dtp0xLUy0HjZOa0Up9E1wdCq/meC30Bv8mgvNSjDoRMBcVbcDeVJhdrENnnyfgK76V0pO2oq2Y6qM6cV2rnXcXAw4ZxCyv+r2ZiCKZO4i5STtULZl9fwexsvPtjlcZw1tz5beT6VUgKXno8YyyRjb4lBQ6Xz/oAvySpVfpXSAvBjlM91xkvAAgIN7xuCHMWYXPajsbzaghWslXIfDsTriYF4gMDVWxPiIiyCSEFLBC2L4YbxiuyJBEFsfmXj4mrPrSMlBK7EfLBcdNFohwlD2PR9NjRXQaEerEgDdt2Pw+GPBtTC92ML0Qgt7d4wMfNxWJOuhm45VJeuHidECaq0Qx2ebeP9n7k2v83u2V/DQsWrOBhEA/uZT9+T+rrVC1FumWqyDT8YYRisuqo0AjyXVWmNF5DpW2nnY8mMUXBtWYhe01PAxUnZ0J5bD0PajnCr0TJctpQl+TSJ2cqyI2SWt+VJtBHjfZ+7Bk67YiWc/ZWWRViFVrlPJD2KUCjYKjt5vwlik3U4DX+NsCl69853vxHve8x7s2rULV199Nc3+EpsOKVU67O/aFqTCGWt5NmQDT+Ohu5yaLecc1mnO/Go/UIVS8j5F11729aJYoFx0UGsGaQCigxGmZyh5PkFQ7DoxNdtZNUF9cu27GFfnJpAz1cYsQSTQSLY7W/k1M0yLdT+t2I+tIviVSW91sWAniooKsRAYG9FJBbPYGK24qLfC9DvbOanfOyseYYJu0wEgNunMr9kPAaRtyFL1n38tFqw0q7wWQTTTSWFa6jnXiwFDpehgrFJAvRViaqw4cGHXrw0wi5ASnNuJ3UJHzIoz5I5nizMwrveH2aW2TpywTgvzWnAsDsvqfB9+GCedIRaEUGiHAtVGoGf1NmmChCCI9UMqBQWAJQlrx7YQt7T9oGMLzFU9RAOuJ45tYWrs9IsBnDHsnCij7evEXPd6YStj1gFSqrSzzASjE6MFHJlu4K4HZ3NV3kv3T+Drd51AO+vH22f9VG0E6Zol2203lgS/x5Jq7USmM69ctFFrhmj7EabGimnbsBfoxLxSegxpLtlWU7wwolJm3WKCVXOd3DVZxqEjSzg514QXxFio+fjKt4/i+ifvH6jwbGh5YU6k0s8k+y/YNYbZpTZGy4OT0QwYOtk71J740Y9+FD/1Uz+Fv/7rv+6p+BLEZkAplRppu4nnaLea3HpTyASeOpBcvvJrJWJA4SpndLtRSuHEbBNCKkwlFVrXtQYujpXSAhhmjtco0xYLNlzHwkLVw+7tlZ4T2htf8iR84LP3JgIMnZO263DMVtvYMdHfJ/CcFKj6vKmp+paLdi4gMv82Nk6VkrOqeU0p9fdmRL6Oz+gL0f6dIwijTpvZzsky4lim729ayE/MdVrEGu0wrbifTovPuSYWMhXEMJ9fqf4z753Z++WPj27S4Feq1HYo+/qVkoPJ0ULaxmXa2rNcdmBixdEH83uYdmOzT3TbGJl55iASkFLh5EILo2V3KGVKy9IJKBP8ZoW7HMdCY7GNyZFCLslAEMT5i1SAylR+TWIwFhJLjQBLdR87JwbPYq4XxYKNuWobnn9+Bb+mItloh2ky1lRpzf93txTv36mr420/hpdUQRsZ0czd28qYXmgjiiVmk4psJXMd6+5Mm8w4hVSKDmrNMLVCshOtG7OdQup95HiiTH1w9xgem65DSoWWF6XbnG1NBoALduvi59GZRu661PaidA55ELWuVmk/yHcO7knmowfChl8TDbXaj6II119/PQW+xKZFKpVW88zi9UxbyBQcKzOPqHIKv4OwOB86SJRSoVS0wbmubgNJsDHgLWutEBOjBZSLNjhn2qIomSMpFWwwDpzs4+e2a6qMVz73SgBdi3LbwkV7xvvOULLTOGmdDkKpno+fGsV3LQTKXcHRlQcnV/UeRmXYtjgsi2PbeBEF19LWN0kQYzC2E0opbBvrtVFSCmgk1V+Gzdn2LBKhLrPtJiCVcrCP7/hIcU2eyoBuJzbZahOgdgfPpUJHgCyb6LA4w2+++An45RsuX9XnGSm5OQE7AFrALvN5ONcCXGEkUSrY2D1VQdG1BvpmroRjWygkbeDdi4RS0UYk9Fw1tT0TBKGUguzS24DS1+hjM41ElHE4Zfu1YHGtKrzQRxBpK2Oud6blebzipr9FP/vKX7rhMhRdOx27MXO3xst352QJv/XLT0pnbB89pVubS5nfsPt1JzLX0I7is752mCKGxRmCUEAkBZnP/NthALoDy6zdsgF4OvPr6OvYgV06+J1dbONopmut0e5vj5nFVMS7X3vVnEYH4VDR6/XXX4/vfve7Kz+QIDYoQnaC34JjAWxtyrLDkBWOioXsW3nqxrb50LOxJgDYNVVOs3uca7/h7OLZ0PK0iM7+naMYLbvgiUIkAFy8bwK7pioDq2LFVIV2dSevc7VIz7apGozg1Pau4HeyKxh98hU7V/UeJstrWwx7t1cwWnGxY7Kk29w5z3UYmOq+lGqgn3NWAGszxjVSKm3TlGy8CRCFVLCt/pX0yy+YwCX7J9b0PpwzuLZuAx5ko5QNtrPBb7FgY//O0VXZHDHorHfBsTCz2EYYCUSxhMV5rjOAMW2zZJIhRdfCWKUw1MwvADhO5/W9rkWCa1vwQwGl0NdygiCI8wshVO/1junrfK0ZDLzerMRy6xHjU99NFEs02+eXEF8UC3DGUE2u39lAdKKrQvubL34CnnS5Xl+Y6q2pis4s6Arvnu26CnpBEmyajsBs5bd7LCsX/CZBcjvjJrF7qoLd2yqIhVZNzgasT7lyV7qPZMWsTOXXzPyOll2MV1wo5C2b2kE++D0208Bff+KH6awy0M/iae1OBcOuI4e6Cr/+9a/HI488gje/+c245557sLi4iGq12vMfQWxUZCb4dZJqypmu/NpWp4obC7mqhXY/q5TVYhRz9+8axSX7xwFogarxkULOTgcAFuoegkhgMpmFnBgtwHF4ulAfq7i4YPcobKu/9ZIJJIJodbYGCuem8qv6xAWDKr/dQcrB3WOreo+shc/OyTKecOl2/NjF21BwLZRLeTstI9Kkq4lO36L8iflm7rU3G0JKKNmxVTABnFRqoKAVY8sroQ+iVLQRxSJN/HQntLTolSbbkbCWeX+WKDbv2V7B7m1ltLwIUSzg2h1BKoMRFXFsC1dcOIVLD0ys+TMZHIv3rfwCOhhveXohsVntsAiCWD9S7YPsaTSxRzPXm9UQC4n/+Y8/xP/7v76JD3z2XvzZ330v1+FlCCOBv/j77+NdH7+rx1FiYqRwxpw0NiqxkDr4TSq/E5lkw1h3hTbztwk4TdLb+Ooam8XudUg58ztmrRiLrpVrMzedbI+erPdsa6lgo1iw8f0HZgAAo2UHV104lXZfVTPqz36Yb3sGegsFAHKiWQDwiX99CMdnm/jKd46lt63W33g5hi0IDNV/9dznPhcAcP/99+NjH/vYwMfdf//9w20VQZxhpOyYY5uW4GEW22vBtnluQH81SoqONXzbsxB6jnnHRDmttjm2hbGKm8vCSqUQhNrvz5zQxiou3MSnNN0W24KdVLLcHuGrzt9GTXI5Tkeo4HSQUD2CV+YkPdpHzGrfjhGcmGti52R51fuHbjXr7E+MMRRdGxftHUfbj3oqvybB4VoWyiUnnckxPHK8hmc8fm/y2r3f2an5FnhS4d+ISKkglUytH8y+yIe0/VmO0bKL46Kprctcq+c3szgDQ6cD4Ddf/AR8+VtH8Kwn7V/1eygFWBbDnu2jWKr72jIklnBdqyeILhVsqERMbyUhrZXQtmMdwassBdeCzTnKRYZ4k4qiEQSxfoiM1U4WpdRA14N+HJ9t4kQy7vTQsWry/0t4wqU7co87MddMq5xzS15aqQT0eTeM1h7YbGb09U7hS986AiDfktxddc8WQky11gS/plJrKrymkJE+N7PWyrpvdHvrmmTH/Y8t4t9+cAI/+cR9PY/99n06+L3i4BQApMGvcaQAsm3PnevZxGgBOJX//NngVymF2SVdZPjhQ3N40fWXAugNftfa9swYG9rnd6jg95ZbbjnvsjjE1kK3PesDzSzGz3Tl1wQ6Uby81UruORZfsZIaC4l6Mq+bFaOKhYTr8B512VIxr/hcbQQoFxxIJeEkbaiuY6HoWLnXszOCQv2208xA+qFY1SzRuan8dtrA2n6Ev//SIRxObAGKfYKTVzz3SvzLd4/h+if3D476tVErpeDYdl8Ln+6LntX1nY6V3TT4vWD3KI5ON3D/Y4vp47PfmZQKP3p4DlGsZz03dPArO4sxc7zJAYJXp0Ol5IBzXd3o11lhWzz9vi2LYf/OUbz6BVev+vVNy58J2l3HgpAKsRTYOVnq+c1NMmk5VffVYicCagB6Ki+cMeyYLGtl8iEF8giC2Dr0S5SaROtaljrZsRtDd1Wv+7aHj1dzwS/nDHFScT7T66yNgpQq10Z8Wabrp9I18pa9bpgq8HwitGm+V7Om2jFR0gnc5PFZbZLtmeC3W1jxmst34MvfPgoA+MKdj+HHH7crVxmut8I0eXHdE3SyfWJUv95iMq8tkvZoIF/5nejTQp+9RmVnhk1wf/9ji7j38AIA3epda4VrrvwyNvyYz1DB7xve8Iah3owgNgrZtmftgbu87dB6YAIdP4jhOHxVNi62xVac+a23QnhBjHLRzp3MhFQouL1BmGtbOdErP4qxZ6qCdhCnVVHXsVAq2rkTqJUIOA0KxguOhSiWPQbt/eCJBdDZJrvpP3hoLg18Aa2E3c3ESCHNUhqUUmj7+ruar/nYt72Sq+ZKqVZtZ2Nx3R5ttmuu2vHUe/wl23F0ugE3M/ed/e5bfoSlRoBWO8K28eKGXVgIqRKBOaOubiUzsr0zuadLpeSg6Nqot8K+yQBj2yWkwoBx42XRz+O54LfpRSgVrJ5WNvN+2l/79G1DbKtTPY6FPn91L3A4Y31n7giCOL+QsrfLyfigr6XpqtFnVrdfQJwNdh44spirLFqcIUoU/7vtErcqcSzhJYGrxRku2tup2GbXZDsm8xVaM9P74NElRLFIK78myGWMYff2Ck4lQljZQkPBzYs4ZpkczbcmL9R87Mt4Lz90bAmA7nYz107z/yfnmlBK5dZ22WvaaB9V5+xs8fRCZ13TaIVQSuFjXzmU3rZzqpwEv2ub+dVrp7M480sQm52sMIPNGSx+5iu/PAl+20GMStFZ1YJ4Na22UioUXQtx16I3FjLXjmxgzChBJiJYjGF8tICRkoPxEX0SGyk5uGT/RE5AwbYYOBusrmcygatpXWE4N8I8MmP90P19rdaGwQ8FFuoephfaKDi8J9iQarCKcTc87QbQ39lTrtyV3vf4S7YBAMLEmD77OECLi8VCYttESQtKbdB2V6m08Ir5nlxbz8EWC3bfi+bpYBSfo1jC6XN8cc7A2crdFIMQqZI3S99v50QJu6YquZYzg5uMEqzFr3gQnDG4Lk8XtP0WCpxj6DYwgiC2DkLKniDXqOGvhe7WVCDfBmvIno+qXfd3LOjOHz2CWMhU9ClbBTf82o1XY8dkCc97+oW52w/sGsVo2UEUS9z9yELqfZtdn1ybWSd0r1tf/B8uxeRoAc+/7qKe98yKei50KS2b2eKdmWB87/YKOGdotCMs1v10befYeeHObCv2TzxOb1s2GWICdUCvnxbrfs7C08wxr73tGUMXUVa12nv3u98Nxhhe97rXgXOOd7/73avYKIZbbrllqI0iiDNNlGnfsC0OzvgZ9/m1LA6LMfhhnAaZK8EZG2hNZFBK5TyEDUKqvu3HpYKdVmkLjgWlgJJr9wgpdAcmjDE4ttVX7ALozP0Gq8je8SEuwuuBgkq/z+7WrdVW56JYYKTkoNGKUCk5CGORs68RUq26nZcxhpGygyMnPUyOFvGcpx3E7m1l/NhF2zBSdjFWcVFvhViq+ygV7Fxg44cxoHRSIoq1nZCzAW0UldL/pcGvYyEWEgXXGsrzdjkszvRsPUNfMS3b4uCW9t71ghiTo4OFWJRSmF5sY2KkkI4oZD1+AZ2xHik5fQU/AL1PrWa8YbWfzcyPe4H2gew+Ro14mg7SKbdNEOcr/a6vwwhomqDouU87iFgqfOXbR3HkVK9oUneba3YkKLWgO08Sc3rUR8FL3C/6iYtdvHcct770yT23c85w9SXbcefdp3B8ttGZsc0UMq69aicOn6zh0j6OCE+5clcuiZ7l555xET70+fsAdNqqDcapI7uWcR0LF+4Zw+ETNXz/0CyuvmR7enuWnZNl/OGrnwrb4vj+oVkAM7n11VIj/16HT3Q67kywD6xd7dl0MgzDmoLfX//1X4fruhT8EpuebOXXShbEZ1ztOanyWZytusporIkAraQ8u9TGnm2VnFCQkAoFx+ppTzKqtN1USg4c20IUCThJoLDaIMSxOVreoLbnxO5oNZVfxs7JhVDJTstR9/fVrdQ7iCiWGK24CCOdPOg2atcqxquv9O3dPoLZxXZSqbfx1B/bk943NVZEvRVise7jwK7RXLW66UVp27RSGzerrpROOHR8tbVo2rjrnhHtCOOf3W/ftziDzRlmqh4KroUwsnOtYobphRbavh4lWKh52L8zsZeI9W9kXrvgWMsmTUbLLg7uGeux0RoG0wVSdHUCqp9dmWVxhEbt+vzoLiQIog9+EPd0jtkWRxhKrOVKUU+ubyNlF9vGivgKOgFx7v0y1/1YKPihSBN/nPPzqvIrpIJEp/V3tcrahgM7R3AndLuwCX6zXXyObeEVz7lyzdt1xcFJ/PRPXICvfPsoFruD3yTw7O4WfOJlO3D4RA2PnarjsgOTfR8DdARcTXt2Nvhteflr1fG5joPFK55zJR5Lkilrn/llPR18q2VVK/AHHnhg2b8JYrMRRZm256Sdl5+BhXgWMytYKtirDrQ4Y2mbY6MVolywcXK+iYmRQk7W3rL6VFJV/+DXTsSpglBo4R+++qq3Y/GBmba07XkVM79smfbpM4lSnbbnbhP21Yh0AfrCblsc2ydKqJQcLCQXES+I9YVKrT6ZAOgLiWVxCCF7fi+jovijh+dxwe7RtMVnqe5joealitxCnhv17NUgJbS3dObiKqRadQJorbgOT5NM3TDG4DhaQb1UsHX3Q1cThvke9+0cgefHOVuwMOovbDUIzhkOJDNcp4v5PKWCjaVGkFYVcu+XHFfnyyKTIIhelFJotqOe65BtMbR8AbWG84Op2o1XXEwlox0mkM2eY7uTcfVW2Al+Gc6z4FdCCpVWw1dja5llKukkWmr46XpqPXQjgI6PcLfvsrk+d3cq7ZzUc7+LNT/t6ltuW9LgN+Pz222teTIJfi87oEfrSoXExWBAV+EgGDsLPr833HADbr/99qHehCA2Ekop+GGcnojtJCg901ZHgFbwnRor9lXH64eez9X/FlJhpOzCta1Ufc9g8XxQKpNqm233/0xGpdb4AK626u3YfODJZk0zv6fRrnI6eEGMHzw4Bz+Mc5Xfyw9MrPo7kEphaqyIJ12xExOjhVSMamapnZ7wjX3WajBzqv0WBjuTiuFDx6ppSyugL4qLdR+jZbdT+d2g/q5mfzFZ3VLBhpSqr8DYesC5CX77X95MVb7gWoj7fOdxrFXSC46FctFG9mWkVGteyKwXJqA3x1m/8QPGGNR5tMgkCKKXWEh4YdwTpFgWRxCJVXcmSaXSmd9t4yVUio5ekwA9lnzd56Ps9dUkCzfqNWq9MfZ+7SGD347Xb+c77NehNAzGGqk7IPXD3tliAGnCo9YK04r/csUbU0RoZ6q95r3MPPHJOT0DbMZ2TMDtrbHtmbHhx+dWHfyeOHEC7XZ75QcSxAYnjGVOic6y1l91dhC7t1XwxMt3rrrSmg3IldLtzdsnSigkrY9eEAMseVxWwTmIl23J1P7BWvTKiC6tBte1EEaib8uyea/VCl6di0rlh79wP770rSP4+l0n0ovzzf/x8fh/nv+4Vb8GA9L9peB0qrY8aR9nDHD6zJsOwsyC9zuJX3mh9tuLhUzEHfT33mhHGCu74Jyl2U+xQQWvTHLALI6KBRsKqxcYG+INMT5SGFh9Lzg2GNdJh377cRRL2LaFi/aNo1JywLqG7tdDvGoYjHK0WUj1U2E1M33ny2wdQRC9RLHsO/dvWxzjFTe1m1mJthdBJCKRo2UHnLO0hbf7/NMd/H7jByfyL8awYa9R640Ofjutv5VVdpUZdFK787ce4xm8RouFxKOnarl17SDKafCb/71M1bW7pblStNO1nRGuWu7abWycvCBK13gmUbJ7mxb+MisdM+ubBr9DVH6VUkMVUkgRgzjvaLZDNJOsFEvandfbb3S9sLqC2u0TJVx2YAKVkovZxTZmFluwONcnrMzx3/IilAr2QLEdy+pYHgxqER20PZwznEik77N02p5XPoEZc/KVbJzWE6VUKrn/vQc6ggzbxktrqvorAHZSDrQyVVtto6NbyNeyP1mc6Up8n6x41hdYSgWV+FO3vCi9ILEkFb9R1xWyK/h1E7uhfnND68HF+8Zx6f6JgaJyBYfDtayB1fZ6K4RtMVSKdm6RaLop1luka7WYfWssyZb3U1y1OIMQVPkliPOZKJZ6PKfPdW2sUug7DtUPU/UdKTtpIG2qdY2MCvQ3fngCR6Ybuec+eKyaT3CrczPqdC4Q8v9j78/Dbcvq8mD0HWPMbrW7PV2dU30VVUVTSKsgIgFiBCFawQTzcR8hfLkX1Ng8epN4eW5M+CKIJpgHhdjlEsCYj6AmqFEQLBu0xKqib6qK6k/V6ffZ7epmM5r7xxhjrjlXt9daZ+291z413zyGU3utNddcsxnz17y/91XGElEnfZN2fiklubG2WmW0Pkark6T6ILuhUnLSz2TRGSB4Bej4wj5LL29phehxOr9S6YRaC3/pZ/+JlbzqtY1vbJwaJ3Kiwi0hxAhqFslvgQK7QkogNt1Jz9Fqx+4ENNX9hE1srGiQ51JUyx4Cj6Fe9RB4DhgjKAWO7gDKLsV0uR4MXTAdRiHNw4iS8Tu/QirUyx6qZRdxr1WQScbGE7yCTtj28VmYXR+zx6U8oRovId3OrxUxi7mEwxgCj8FldKDNzih4Lh1YFfc91rVmMklNOqvdE8DMa1VdKX3MbGXZdRkcNp7P9TRwHc2OGHbtey6D57GBSpFSKXApwSgF6bkv7Ez2QRXKLD0+7fwOCHSeafTCAgUK9CNO5MBnxKSwyVTW8tD+23Z+w4jjT/72yfT1rHVP7xr1TLFhs/PNVuhpmlGZbPF2oTK6U9+JeFoU3Q22C51wmbNO7ER5P+HcZ8z+W4XoUYVrh9E0OW6Hmp1oY6+jPZ7GdrY5S+nuTCB6ZcLIqeLIiaK+T3ziE/jbv/3b8XaKELz3ve+dfI8KFNhjCCkRm5teJx3j+7LuN2ynlQudpNo5xpV6AM9l2NqJQChQ9l24DkUiJKgkCHyWzmoMgk5+zczvBB7HtbKHUuBAhno2MkurtgvYuDO/yvi/7urlNCNk10f7UPeNYNS4yHojAzoJppQgijk8433nYXImgeuwgdQdSvSMZxgLxFyAEKAdcQgpQWl++Z5fwSulZ8RMFdwzM/beAd1zjFJ4Lh2YHAshc4yJLPNCCDVURXo/QKm2GrNFg1HCcvNaCClQoMDegws5k8eqTXCzlmr23/YZut2T4L7gtqP4/DfOY6sRYbsZpd09SsnEgkaHFbbDPSqh3A36uOluen0Xa0wFE1ONsV3PY6mWTBgLuA4zXWp9bsp+f6Juk1+rNVMve1BKodGOUSl5ffFjJXARxZqhZuMS3bDpJvGUADcbqyZGCXyXIUoEwoiPrY5NCKCkmqrzO9EZ+epXv4pvfOMbY+5UkfwWmE9wIVN5dM9lkGp8X9b9BjVWNlzI1MMUAK4/UYdSwBcevAghJUqBk86eSkLgOWykejGlepJRKQWXsbHVa5dqPmrlVXzl4Uu4uNHOVTQnUXumBEimXLSmxaDvmpR6K43CpU2YGdXzuu1E+9aePFIFgInF0zyXQgw5FoHvIIwFOJeghKAd8j6lTbtv8wilFOJYpOratYqn51cP6J7zXIqy7wykL9sE9+ZTCwD0+SXQa0YYi1Qp/aDgOt3O8yg/7WcKvbBAgQL9EFJiIj+jIWh0+q16aqbze/cXnsarXnQtdlr58Yuy72Ch4mOrEWGrGeM683dGCeIxYoOrAUIqiESm7gzTeL1nRVHr5eGxnFQKhGhqOt2AaWgMjz8o0YlmGIvUKz5ORPrMGNj57YklF6o+IvNMF0L1+dyXAwcbO7rgbZPfSsnNxYvXHa/nYpiS7yBKRN/cr1IKX33kMq4/Xuv7Hi3wOF3hf6Iz8p73vAdvfOMbJ/6SAgXmCUIqJIZ+4zksJ2A0b9CJlk4oHafbLSPGAkkvQlxTIo1o0vp2G6uLpZEJvc11pVQTUXQJIXAd7VPcu+AEI1RoB21HL1pjf/UVY1ByOKmColIKhJA0caOmIJFwAc8JUkGHSeF7ztBgpeQ52EKEMNYqnY12PDD5ndeER0iF7aYOkMqBA28Xb9y9xkLVx63XLaHVSfD0pfycGpcqVX8HTPGJUqxtdZBwgSOLpQNL2gGkc+XA6CLTvBZCChQosPcY91nAhcSnPv8kbj65gGffuNL3+sV1LXBUHdD5BYAvPHihjwlDKcFizcPpC0jXfcAqTT8zGClcSHTM+kzIdDZFWb2P2ghKsx3HqQRd9p9P898XJwLtiGPBzA6XTEE9NHO+tuvrMDKwuNvbiV2o+QhjgXrFG8j0s8lyO+RpjFcJ3Nx2slR6QCe/W82oL36874GL+IPPPYZjy2X85JtfkHtNTwWqqQo989nuKlBgDyFE1+PXdWlXLXkOoX1+tZH3IMrljdfU8azrlsCoXrR2WjGW6sGuIk5WHVrI6breq4ulvlnZcmbB2w120drPIJ2L/kU68Cfv/OpufPdvDqPgQqFcml692J6DQd1p21EPYwEYmg8U+rr186rwy4VKqXGrCyUIIQ9MMdmiZpSyex+aOpDo3mcOI2BUz7VVy96BUZ4tXIel7I9h4wWEPHM6LAUKFOgH53IsNtdn7j2Nz3/9PP7bpx/C2mYb//7D9+JP/+50+voDT2wAyCdvN59cSP/9xYcu5USW3vhdNwHozqjmkl9KkHDxjCjMxYlIi5OB54zNrMsiO/M7Kvnlhq1ULrlwHJayGrM4s9ZEnIj0uWBFray3r7VkKgfuwH3tnVleqvrgQhq7wP7vs+9vdZJUWKscOHAYxfNuWQUAvPC2o7nP2FisN/n96iNrAICLG/1uQ3Z8bprOb5H8FnjGgYuuJ6rnaJVkOsXitB+wNkQxF/C9/vlUz2XpQua5DLHpTj3ruqXR2zVCWkKqkcp9wxB4LFVstrAS9xs74UAblt7v78787g8GVZ2DEUmYELJvUZUKYJnOL6ALKIRObmeQRaXkwvPYwMJBkPonc7iMIoxFX6GTDlEungcIIXD6vO6wriwEkApzMWNv53mz16C+H7pFDK3mTeE42iLk+Op0nf1ZwXcpXOPdHQ5JcBklmm42p9dDgQIF9hYJlxinnv/lb62l//7Te0+jE3H81ZfP4C+/dAZn15rpM+XU0Wr6vtXFEn7sB58PQKv/2uT3773oFF723BMABvvUWiX6Xn/ZqxGdkKdJ6CSU54SL1Es3S3uuVYYnv3EitCe978BlpE9U7OJGW2u1+E7a9AnSgrpJfs05GSb+mU1+CdFdWzFCUM1Sp1thgk6P4vU/fvWt+Jn/44V9Meowu6NsaP6fPv4l/M6nH+q+Bj27PM2j7uAjkAIF9hmcy3SB8FwKhTlPfgkB52rXbpnvMXgO65uLGLhdI46glOqTth8H1bKbzqJ2/9ZdoH/ho/eP7D5pb9r9pWcO2h9/yG9XSuHs5WYq7W8hpQLpsYYqew48h12Rb205cFD2nYGU8W6VVqBScrGxE/ZRnikhc9v5TYTCN59YB6DpU0qpA++gArpj36v4LERexM2qeTuM4NpjNVyzWh20qX2D5+p7HNCd3099/klcMNREC9ehaLQTPPr05kHsYoECBQ4YCRe7stm4kLlE1HZ5Ad0R/tDvfTX971PHarnPri5q1d4wFnjqoi5sLmfijiVjEbfZCNO/+Z6DRjvOdYOvRiil0OzE6fO41MMua7RjPHF+e+Dzem2zg81GCKlUeowB4Mhiqe+9FgmXKZPJdVhfwb4TJVhdCOA6DFxa8aluTAF02XqlIcJcvWrfjFEopcCM1VAvsrTntKts4hiHUaws9P8em/xu7oS5v2eL+mubHXzziXX87t0PA9Dx8Z5bHf3CL/wCXvCCF+z+xgIF5hxcZJNfPfM737Rnvc/+LnZM2gd0PKVhPePcVeGbFK7DUC25uYSydztn1ppDP2/92fazOZUM6vwO+e2tToJqyUWnpxMrlQIl+WKJ7zuoV7ypiggWhBBUh4haZKu0gae/a6VP+AFpVXfekH3IP/smPVc2D7eb9WiWPZ3f7DVhmReM0lRp/SDhuSwXoPz1V87ig7/7ldx7Sr6D9e1OKlZToECBZxYSIXeNaZrt8deH3plV32VpAfb85RYIgBtO1NPXbQF+I5PIWMHOeAIrm8MILiRiLlNdmd7O7/p2B0vVYKClT8QFyr4DzvVo0DvvuhNv+75n5+Z/+75PyvSZ5bq0r6HguQxHl8sIPJo+i9OYIrKd3y7teRCytOvFajf2IASpcGoWWdrzbtu2sMfpr796Do+f207/Pug6ffTMlm5EAKlryaQY+2l+11134dSpUxN/QYEC8wYuuyp8nqNnfue08WsCb/1/uyVXCnqBGWee0s4SlwJnKg86AKiV88kvIQTveutL0v9+6vzO0M+SA6A9x3y4MEMvtoxFg+f2eukquE6efn5ksYSbTi6MLc8/DNWSlz4ws+it0tbKXh/dSCuCzyfNdauhK/2EAKeOVAGM7yu9l7BdXSEUopingZqXSX4JIam6tzMHoniuQw3LoLuP1q/bwnMZlqrBTNReCxQocPhgnQFGYbfRpN2QXXNuPLmQ6+bZzq9VFLZwGUV7hEr91YCESwghESc20ezGbVLpMTPfGzyb67v6NTsvfN3x2q4jbEoplE3s4dB88ptwCdc4f2TtFLNsMgBo72LJlLe66sY5geeAsf6Rqyzt2bILdrN7ynaX73/gAgDN1tvo6QQDQKOd4FtPbRYzvwUKTAIhVGrubZXt5iEYHwZGKTyP7jo7cmKlguPL5bFmTCyd2mF0auVd12EIY55beKplD69/+Q0AgKcvjer8Tl+xmxbxgIfNiQEznEqplELEGM0t7JzLPpEsz2U4vlK54muIMTLQmrG3SjsI2gt6Pju/myb5tXQpEDUXYwaOUU7mUmGjEUFIqT2/ewoLJd/RBag5oGpb9ffeKvr6dp6e7zoUYSLSda5AgQLPDEipIHaxuwEGJ78rCwHe/Npn5f72z//hcwd+/sZrup3e73np9bnXPJelyY4tfgI6lomi/Jq0nwXw/UBsLI5ssT0bj203IpQ81ySM/c9rSnTcMS6LS0r9LLW6LYzRHJsuSgQCj6FkrP3sa73OHKM8fgH9PLGfue54TZ8zokftGCV9cVyW9mxHx3Ybx7vFeP4CQKuj9+e/ffrBvve96HYtlPXNx9dTv+JpLqGDf5oXKLCPUEqBiy4lxXUYKCFzEYwPgwLgMLZrR7dScnHzqcWxkjBmkl9GyVRKhBbVkodGj8n9tUf1fNCZS430wfa3XzuHd/3aPfjWaT2HaAW3pqnYTYt4AO05S9XS7xE4c6kJ32U4slSC0yMgwYVMlSxnjWG02t4q7SDY5HfeRI6UUqnaY7bLPg/FJm1ppGelpdBCV4PGBsqBi8Bz5mJOOWVs9BS4Wj0UZ89liGOBTlQkvwUKPJMglYI0Ip6bOyE++VeP4UyPpRvQTX6vyRSAOxHHtcdqoAQ4vlLGe975ctyUUXfO4h+96ha85I5j+D/f+Bxcd7zW9/pidYDiM9PinbagfGmjja88vDbStu2wITaK1laNP8vY40KiXHJQr/iDmVoEYHR8LRQhJRjrer+7Ds0VExKuxbBcR4s22tfs88PuYyelJg9vnPyzNzwHr37Rtfj25xzXHWVGUQ60knVf8ms60dvNKO3cjppbBoDjKxX8k9fowsujZ7bw7z98Lx49s933vptPLgLQ8+TE8K6niXumH1IrUOAQQkoFpZBSTlyHGs/cgw/Gh4EQLcw1zWzuMFBKQFm/ddIkOLFaweWtNrYa+eT3miMVEKKpKRs7If7XXz2Gx8/qRexjf/IATh2t4lUvPIWlejBVxW5acFOJXa77eMkdx1EpuX0WAhs7IVyHwnX1TLO1DvBdllY7pzGsHwdWfbgXvcqMwz7Lx6z47yekQoZloX8HGWDTdFBwHYYwEqBUzyFbinMWx1fK8Fw60P9wv8GY3r/eIKVXKM1hBImQ6ES8z0+xQIECewMpFTabIRYr/oExRYRUUFKBuhQf/7OH8fTFBu574AL+n9//XNx4TTeRbZhZylNHq7jzllV8+u9O4/tefiOW6wF+5i0vQmWI7Y3FykIJd73qlqGv62drK9dhdh2KTsQRJwIl38FOK8Ll7Q6a7Rj+ABGkwwghFAjprsmlTNyWCInVxVLqdpGFnWElhIzdFLA2R9Y9gRLkYog4kTixqosQ2VjPUrE7PVZHo2Kba4/VcK0RPmt1ErguQyVwU/ZUFsv1AJ5DU7adw+hIxWqLO25cTv+dfaa9620vxSf/6lG89NnHU6aiZRSoKZsoY92d/+Jf/At84QtfSP/7/vvvx8bGxohPFCgwn5BmPiDJJb/z0YkaBuvvO8vg23UYXEavKPl1GMVSvYRGO85V3lyHpUnlX3/lbJr4ArqL/fSlJn770w9BYZ87v5mF+LtfeAovvuPYwPctLwSolVwzJ0PTzq+tds6yCJGFFRDpPSa9M7+D4DCqjeznzEZCKZUed9/MTyvMz4y97+r5KtdhYJSmowBZlAMXp472dzYOApRSMEL61oJ+ewhNoS/8fgsU2D9EicD6Zoit1sEpGgshIaTE6Qs7ePpit+P7l186k3ufTUprZQ/f9W0n8W/e/u14gfFeXaoFV+zFbgUcmxlWissoEi7TjmMiJMKID7T4O6zgQkKp7vPaOkpIqZPiwHMGHlshVSqsOG4nkwsdk9jCcq93vVIqVZvOFtd7R6k6Q5LfOBnsyyykhEM13dqyp7KglOCaI11nhKW6Pxa70ndZH4vgxbcfRbXk4v/xvXfgWdctYdHMk2+34q7o1V4JXt199904d+5c+t8//MM/jHvuuWfiLytQ4KChq6LIJb9avfeAd2wEyoELz3SoZwXXoSj57Iq7mA4jWKh62GpGOHe5iaZ5oC6YKt+DTw4vkk27aE0LmwiMTPiJtnF4jlEldhlNk9E4ETlf5VnDzmErc0y2mlE6swOMnvn1XIY4EVcsYjJrKNWlf7n2gU/QZ9V0UHAdXTTQxSWj6jwHwlbDoGeP+2fDB1lkAShmfgsU2EdIqRAmfCIl5VlDSAUpgQvr7dzfs4kwoP1fAd2lGzRKcaWwApDZ5JcxndjZ+KvZTiAlkFxFRTohNUMsivOd3zgRCDwHtbKbFi+z3V8pJSjrzu+O+11uRnl70OiUTbRpxpaod5RqUPIbJwIXNlo5u6r89+qYNCuklcW1GW/oxRFq1b14+xuegx99052467tvxmtefC1e9/Ibc69bWycpFXba8dS057GS32PHjuHBB7uDx0qpuaGtFSgwCZQCJHo7v/NNe77ueA133Lgy8+3edv0yrj9xZR2t4ysVLFR9bDUiOIxifVsvlHWz2Flq1Ru+88a+z0o5nUrftMh2fgfBPoiqJTelrGWtAxKhLQX2avbTUm4tO6HZjrG22R5r5ld/nqaJ5rxA056NrVhm5mheZuw9V3sfOoxgqV5CueSkVfR5heNQXHc8P6s+qHPiMHpVzdIVKDDvkEpBCIVOxA9MyMk+V22xt1Z2QYh+fmw3I0il8Im7H8ZTF3QyfO2xvWG1VA37qzmgICukRKMdox1xOFeZAnSSCFBCUr0Fy9yKuTTCUQ48M4Ob1RPRnd9+Vs8oSKly788yGO0IlPWFzxZ1x+n8Xt7u4OhSeWBhVUqVzhn7LutTewaAk5nkd6k2WuwqC89lOHW0hpc8+zhe85Lr+ooylJJUTfziehuqx+1gXIxV6nn961+PD3/4w/jUpz6FWk3fKO9///vxG7/xG0M/QwjBH/7hH068QwUK7CWk1NJwVonPZUbwak46UYOQlcqfJXbzXRsHDqNYrAVY2+xgZbGEixstAN3Or8XNpxZRLbm5KnDMxb7O/Nrq8rDOnlVOzCa3bkbtOeFyJsdsGHTn13gfGwGmZjtOZzajmI8sPDqMpDM88wIlu0GY57JUiGVe7jd7zH2f4bpjNRxfKc9NV3oYHEpx2/VLaLZjPH2piSfP7wwMUBglCAvBqwIF9g0NQ8WUUgtrHkQhTZjvt2vCi24/hm8+sY61zQ7+7898C6960Sl85eG19P3LC+MnJpNgUOfXgguJTsjRCTkWqh5a7SRN/g47EmMzZTU6bCdXCIlyoLuWnhGhslZEQDf5Hea+IZWOTzYbIWplD47pomftGLWAqdmPRMB1aPr9WixRb6eUKagrpdIkOJtoWor2oGK/kCrtKAceAx+gXH1tZlTo2HJ55DHrRBxSqrFtN687VsP6dojf+/NH8H/+w+dM5XQxVlT9Mz/zM7j++utx7733Yn19XVMkSiUsLi5O/IUFChwktL1OtxvlOHoOYl46UYcRR5dK2GlGYIyCGkJm1pSdUYLVhQBv+Qe3Y307xB/d8ziiWKAd8n2lPSe7dH6F6QDmkl+n2/mVUqG0i1fdlYAxCkrM9xGVihvZ4odUuno87OE4yEbioCEzhSbPiIbNE9PCYRSMUZR8N3es5xkO07PJr3v5jbjna+fw5PmdVLAkC0pJQXsuUGCfwIUeO9Gq+xJCKLgHsJwIoyJsk99y4ODFtx/Dpz7/JJ662MDH/qTL4iR7GPukM789FHBl9jEhUid7HsuJYB12JEKCUpIytexvSoRMCwKuQ7VIZUbxmQuJalkLSA2Kik5f2IGSQClgCGOBEysVSKXgsG48YAv7UiokQneaU9pzZqzKN8+5KBGIkq76tp0PVkqBgCDwmU6Ye4Q0tV+x3oY/5JzZ2VwAuOGa+sD3WKxttUEIGTv5fe5NK/jyw2tohQkYJVMx3sa60hhjePOb34w3v/nNAIDbb78dP/IjP4I3vvGNE39hgQIHCUsJyiZC2urogHfsEKMcuLjz1iO4sN7CuTXt7btQ7XZ+jy2XwRjF9SfquP5EHZ+97zSiWCDhcl+pYXGPt3MvrOCE42ST30yiSdBngzNLWOsdLqROyihJaVC2IxxGfHjya2wkeh9UBwkpVWoxZWnP8yQw57kUlcA5VEEXY6TPsiKMOKKYI+EypRva4EoIORcexfsBpRTOX25hse4P9awsUGAv0A61cNPKQoBWh09FxZwF7NqQ7ea94FlH8anPP5l7HyXAP3vjc/ZsP6olvQ6tbXWw04pQNxaBjOquqCsoQPRzjwt59SS/XBrWjT7+afFaqnSEiRhv3mxhgHOJsq89gLV/bZflFcYctbIHKRVqZS+dwxVSwcvEK57DUpFOziVqFa87D8xoOlaVFe38z7//Nf266Ujb7TJGUAn0CFifi4QicEyi7ToUg7J1Qgh++p++EI12jBMrlf439MAzjYZxYoMcVZ+QqcZ7pnoi3n333Xjta187zUcLFDhQSKW0Am1G/GiegvHDjOwxzHrhHu9Z+KzwUWJUEfcL1t5qWCIgTMXWyfwOq5BoA4orVcAcBUYJqhUPsanEWk9X/aAcw+uXEMgp51/2CkKqtPuoO7+YK4G5WtnDUi3Ayh5R//YCDqOwp9iKqbRDjv/8P7+G//A7X0xFz6y4TK8NxdWMOBHYaUZotuZL9bzA1Y9uTMH07O8AKuh+wAouWTZI2XdAKenztP/5d35n6pm6F6iVu8Wn//6n30r/bZ0JIi7gUO04IYS6KvQJEi60QrJS6XM4m2hmC+8l30m79IA+byVfK0G7PXoNUawLAysLAUq+kybFBPm4y3MZHIch4RJcyFwxwRbTNcOtux+XtzoA9LPQbjelYHvMfCZ/LROiUnEt19FFjEH6LauLpZy91jBooUk69j1TLrlpDGGLvpNiqjLLyZMnAQBPP/00Pve5z6VK0Ndccw1e+cpX4tprr51mswUK7Dmsz29W/EjPScxJNH6IYRdUpVRujuj4Sn7ew1YqOZf7GiDYDqQzJPMSZn4mmxwzRkEU0m7sJEqM06BWcnHhcguuo7t1jBJjV+CgY7p7w0ApQRLrY+pOV9ecOXKdX9cIXs0R7dlzGe689chB78ZE0LQ4E1iZ4OasYVwAwFMXGnjOTSugJmgRQgJ7WLTZK8RmZm3ca0UYFdlEyH0V0itQANDPl+y1elA1J6kUoLq0Z7tGZP2+s0q8e4WS76BSctHqJHjqYgOdiKPkO2CUoBMLBKqbuCl1ddiytTocnYinMQYB4Hl63Echn/wGngMutRf75e1O2nmtBC7KgYMwFjmbw+uWy7j12kVc3gpxYb2Vbsd18mNaLiOIE5km0xapoKa5MAnyDdtsAmnZQiVTOOkdT1OZc+cwCofqAgZ1Jn+uK6Vyifk4fB1qKNKNdoJ2xJFwMTGLcGqOwfve9z587GMfg+wJXimleOtb34p//a//9bSbLlBgz6CUvrHtzewyOlAevsDkyC6u1ZKLo0slbDUjPO/m1dz7bPeUC4kpdAqmRnfOe/D5lkr1CZQ4jEAR/VmHztZreRB8zwGITcRJSjlK1RlHdH5thTY7R3TQ4EJl1J5155cAfVY9BcZH1stxEE1wu6k9Rp2Mp+ZeCrXtBToRx9MXG1iq+TiyNFosxeLiRgthxMGvki5SgcOFTsRTKiiA1LJuvyGEBEh25lff+9nktzzmbOWVgBCCf/mWF+E//s4X0ewkePpiA8+6bildl5BJoOiUc5vzBm4Kbzau8T0tqBolAr5Lc5oSnssABey0YpQ8B0JKBD4DpQTlkot22Enfa0WqiPF4t3O4ljaeheswLXRI8omxbfTYjvQbXnET/uhvHk9fr2Y69d3Or9M3mwzoWXFLp3YdmlLXp4mPuJBwHDowyR4Fm/yGEZ9K8Xmq5PfDH/4wPvKRj+Af/IN/gLe//e24+eabAQCPPfYYPvKRj+AjH/kIjh07hre97W3TbL5AgT2DFQKwcBiZa1/Pw4SuVQ/ACMGPvOn5RuEw/6DNdn57i2d7CXvehwpeCdU3T+s6DIxSNDsJFqt+ahuwV7DKjXb2hVG9qNuO8zA/VwBposynoADtFbiQ6XH3XAYFozo5L7znQ4gszW1Q8mttjzRrYHeLrHlEZDyrHUZwxNhteA4dObvcCTm40DoCUcSvGvXYAocDdlQFgKaBDpQt2nvYxLLXviaX/O7TbK3nMtxyahFfeWQNT9nk16GIOjEIuiwshxG0wsM/qsCFPvZhkrc54lzCcVhubMp3WVoFrlc9TW0276+VXDx5dgcLVV+P5qErZqVj1q5NUu8a57sMW1J3/7PrJTU05u1GjFoZeNnzTsB1KP7nXz4KAPhHr7olfa8QCuXASanP2dlkpVSu8+syCsaILroA2GpGCCPeN+5mPwsgx5Boh1rHhGAyv95uE0Wrm+9L8vuJT3wCr371q/GBD3wg9/fnP//5+E//6T8hiiJ8/OMfL5LfAnMHqbrJL6U6CB/WCSwwGaxtjF3gfJcNpFu62UVrH+mJdvZ0GO055iJX/QR0Muoyip12hKPLS3s+G24F2BKj6tyhem4zGGPmlxkxi4OaNRsELmRm5tfSnudn5vcwIssCHpT89gaRo6jy84RmO8HlrQ6uOVJJ2TlRLNBsx7iw3sJCdXQXWEgFJbWmQxgLhBEfWz20QIErgVIKUsruvakAeUAMnIRLQwPV/91Nfrs6HMGUya+QWlBuqeaPfW9de7yGrzyylo5muKbzSwhJkz3PZdhpxQgjPvW+zQMSrkse9jkd+FZAyuiJZBotWshSP+sDz8HJI9X0ty/VSzi6XMZGI8TRRb3mpTO2Zia4E/GBtoGp9RBB7vsAXXhuRwmEDMAowYvvOIYX3n60T/FbSJkW4su+i62dKH1NmsQ3K6TlGKo1AGw1QlRLWrskm+xLpfD0hQaCwMGxzDreDBMcX6kgjnm6jXFgGxWcCwil0uR7XEwV9Z89exaveMUrhr7+ile8AmfPnp1m0wUK7ClkpjNm1eWcgvY8E1iBpt0SWtv5TYTYV4puPIL2nHAB12E5iyZAL7DlwMFCxcdyfe9Fkeycb2I65pRqypSlPe+WyGha//zQnreaUY72bH1+52Xm9zAiG6gMEmBrZ5JflrHcmHdc3Ghhs9HB2mbbdNH0HOXlrRDbmetoELS3qoR9xzTBUIEC08JqiWTXtYNahRMukHAz1uV0R3UWMp3fYErtiiQR8Fyaiur1Ik4Ezq41cx28JWN502jpz1BDo+VCpc/iku8gTmT6jD6sWN/ugACpx68tWlsV/uz1Yd0dGCU4vlLOdUrrFQ+njlW787kZmrHn6FncMBa5JNTCN0JajNK+Ma4bTiygXvZzDLJBVldcKJQMY8/3GEQmppOG4ZBNugPPSf2lA9+B69I+7904FqhXvdxst1QKjBAcWSzBcehEzRDLwktMoXTSKYOpov6VlRU89NBDQ19/6KGHsLy8PM2mCxTYU1hRFEAHjlINV/8tMBmooT3vtn710lX2C8kIteco1glmbzWbEILVxRJqFW9fukiO8faVQotvlQMHW40wrQj3JjKbOyF+9+6H8dSFhtlfDDScPyhoKmpXKVv7B6JIfq8AjNLc0PQPv/6O3OutsBvYsB7V0HmFVQWPEolOrC1jXEer5iooJCI/rtILqSSk0oGZUHreMjwEv7vA1QFlJOhS1jMh+zrSk0WcyDTByDJD6rnkd7ruKhcSge8MpXTvtGIwRtLkDwAqJonKMlISLhDGPB1BsnoV4SFhqQyCdRFxGM3YHBk1/oijEuSPueNovRnfY+kxysJz9ExwL82YEO2/2w4T7ZzQk/xakUyHkZwNEqCvAc+juLzV7ktOswgjnj5i7GyyhVQKlObp1r7HtL2SkEZHh/TRkGOuO8GOsepTSuHpiw0tcuVoht1ktOfs+Nw+dX6/93u/F7/3e7+H3/zN30S73U7/3m638Zu/+Zv4vd/7Pbz+9a+fZtMFCuwpsh6/1nd0r0WMnilgxkR9t0Uo7fzus9pzKniVWbTDmGNjJ0TMJcqBM3Ae+PoTdTx/nxSBdTWYgjICh1EcX6kg8JyU4tMbHHzmvtP48sNr+NN7n9R/mKPOrzIU7DztGQXt+QrRS1S55dRirquT7fw6hh63n0WmaSCEFmrzXS3WEsciLVLZ9SQZkcwKU0hLuNTzcZRipxllXt9fT/ECzyxICSgJEHRVfg8i991shEiETAte2dneWmaNmPZeEFLBZQR0iGQhITrZzXZwq6Zo3Orw9HuPLVewmGFZEaKPnLXdOYxIuEzjiJT27Dmpan2v9onLaGpr5A5g8Fi/X+uxm+3QHluuYLkegBLal/y6jp7BdRjtY7lRSuC7DPWKN5RJEycClZKb0uRdRnOlDiW1/3B2f0q+7vxaGyU2QLyKC/2aZ6yYhNRzxSWfwXcZXCOIOS5sEyXmWmRs0mfcVOWfn/zJn8SDDz6IX/7lX8av/Mqv4OjRowCAS5cugXOOb//2b8dP/MRPTLPpAgX2FLKn8wv0CwYUmA69sx/DkFV73s+5KD6A9ry22YHraH+5647Xhn1032BFw0om4fU9Bs9jaYGmt/P71UcuAwCeOLeT/s0mmwcNLlSOaaEfbgqMsaLzewWwc+FW0MlhFO+460488vQm/tdfPZYKXgG60NSJOcKYz7XiszCzurWyi/WdEAi6vzPmWkWUG3rboLl7qbR+ABcSCxXfqJ7r9xMCPHWxgVrZxerieMrRBQpMAgXd/e12frHv2gtCKjz69BaEVN3Ob6bbmC3sDkq2RiFOBM6sNQEFXHdc2yRJpfoos1wo1CsMm41u4ckyprjQyaHvsoFaBYHnoNmONTvoED4fuNC2coHndGnPPkOUCFRLLo4slnLvtwJUUvZTlwErJKXnoynJC7OuLpZQrXjodBK4PQV7nVCztJDei9tvWMbXHrmMMOYDz4Mds1qu6+TX93S31to96s5vnvZcDlwQomMPxnSC3YnycUgiJColF2GshQmJ1M+uhaqPWtnDZaczkWhVtokCDPYZHoWpkt9SqYSPfvSj+LM/+7Ocz+8rXvEKfPd3fzde/epXH8qLt8DVDz1r0g3GgX7aSIHp4Th01xlDm/wmXILvJ+15iNpz4DlodOI99/AdB4ToB2Gt4mGh6kNBL/J2n8PMrM7TFxt9n2d09+LDfoELTb+zzyTfpejEYuCMUYHxYWfFhJBgVF+zizUft167BABodZI0gPRchu1WhCiZb7sj3bnVVonVwEM7SrBU88EZQSfSaqBSmYB7QNfJdt5WFkrGWkSZToQWIepEHAmXWFkoFbFJgZlD2xrlk9/9JlskXGjWhKEUA/2CeK9+8bV47Mw2nn/L6qBNDEWzk+DoYgmtMIHDGByHQggJ2jNTqqDtArNdOM/VxduES7Q6SZ+jgoVWMLbdw8N3j9p9z+osBJ4DziVqFW/guNVzb14d2oW3CSYXso9mDADHl8totpO+7foug+vSlBbci8BzsFTz8dTF/rltKRU2tkOcOFJJt+t7WqV6YyfE0aVyqtuRT34deC5DO+RYWQwQ+A7EdpjfuCluNloR4kQLgLkOxfNuXk3/PQkjIe38mhhjUsbbFcmqvfa1r8VrX/vaK9lEHx577DH8/M//PL785S+jUqng+7//+/FTP/VT8Dxv9w8bfOQjH8Ev/MIv4FWvehV+4zd+Y6b7V+BwQ0rZFbxy9exc0fmdHRxKx5j5tRU7AWVEEvajAJF2fjO8UdfRMzedmOy5jdG4sCIl9pgEXpeOnS0s3H3/U7nPWWP6eE5mHYWQ2m/QwHUY2hEv7rcrBGMElPTPR5VNl8d2fnzP0TP4mMxC4iDApUw7SZWSi8DXFmNlX9PrHEdf1zow7v+87fza5MNh2jc0igVcVwfjXJmZtDm5zwtcPVDQxRtbWNEzv/t7z+nkS6IdJmgYaxorNmXx2pdch9e+ZJptSyxUPdQrHm64ZgFbjQhcKLgmg5BSodGOoYbUXSuBi61mhFYnGSocyShBFMu0w3jYIIRMKcrZmV8h+y0ULfSzcPDz0GEUjBBwLgfSm4+vVICV/s+5jvYTHjXXHRiaci8a7RgLVR+njnZZcIHnoFb2sNPUat3KrLPZInbgOQhchq2dCKd8nQj3bl8p/ZusD7FUCtWym/4uh9Fhh2IgsrRnSw+fBHOlKb69vY23vvWtuOGGG/Crv/qruHjxIt73vvchDEP83M/93FjbWFtbw4c+9CGsrAy4Kgo84yGMyiBgBXiKzu8s4YwhWpCq9BlbgGHdnFkjtlZHTo9ABNPqw/Pi9/y8m1dzfja6A6yPqa3ob+yEePjprdznokToqvO8JL9SpbNnDqOpGFqR/F4ZHOur2HOf5TosIYdvgp95UwAfhF6dAGvrQSlFOaCQUqIjtFL/oEDSHgs7c8koQxiHWN8OUQ4cbUWD/RXYK/DMgdT2rulTjGB37YtZoxNyJELiuuN1/M1XNRtzqTYbhwIpFZbrAa47Xk87s1nBpJ1WjGYnhoLxoyV5WnQpcLDVjEb71BvRq/10gJglLO2Wkkzn13cgp9SVsSNQYSyG6pEMAiEEd9ywPNLC03UGR1xhLLC6GODoUp6iff3xOta3O+koiefmk3FKCUq+A0J1oYMQ0i+JRvSzK/AZthr61cDtpqCMUZCJZn7174sTASiMFPAahLlKfj/+8Y+j1Wrhgx/8IBYXFwEAQgi8+93vxjve8Q4cO3Zs1238h//wH/DqV786pWIXKJCFkBKJMAI8Ds1JyBe4cjC2u9WRm6E9S6P6tx9IO789DxFmZgvnhY7bS2Oqltx0bso+VL/+qJ71veFEHWcuNcGNyInnMMSJQJSIodXm/YIwPq1A90GllAKdkyLDYQUz9haDHvblwMF2M0Y77HZYCJl8Hmq/kXA5supPKYXEcEVPIfo/Xy15aIcJYi5gWKlaVGt2u12gAACk6rXdzu/+0547UaKL+YTg/OUWAODYypXPuNuOpgWjJKW4WkilUCm5aHc4PIelgkd2rbfCW9nP9MJhNOMLP78jGsMghEpVkbtWR1qxfpAl3W5gjMJ3GS5vdbBc9yfqhu/mTOE6WsSqd75aKYWletA3GhJ4eoaYc2kK2P37UgoclE3X12otWNjnD6NEU8GlnmPOFgUcRjBJ+pqlPYNMzm6aK27B5z73ObzsZS9LE18AeN3rXgcpJe65555dP/+FL3wBf/Znf4af+Zmf2cO9LHCYIWS38+s6FFCDfc4KTAeH7U579t2MUIHavyCB98z82qSbEW0+P6+zgJWSmwYPYcTR7CT403tPAwCee/NKOqscxUL7/0U8p/h7UJBSgdtCk3lQFb7aVw47yzuoQ5LainQyQaaanBK230i4ANvt/lPAxk6EnVbU9xI3a0kWvscQJxLtDjc+wGruiwAFDid0IpGxcCN6xGo/FcabbS1+FCciFZw6kfGOnRYxl6iWXCxmusieS7HdjNIkj1tfega4LtWdv8xvt8Jb7Wj4c8mOaMw7S2UYsmtsdub3StiFlZILpYBaZbYlu2GKzPa1XriWVSTk0E72iZUKji1XtO4CJXl7JKl9hxmjadwtlcoJr9l9GpcxYYv7UaIT6UnHveYqCnn88cdx00035f5Wr9dx5MgRPP744yM/K4TAv//3/x7vfOc7U/XpAgV6IURefZbS+U16DiOsGuAoWNpznIipJOqnRdfnV59vO2vsewzlwJ1byytGSerzG8UCX3/scvranbcc6T4EjOm9UhhqY7CfkFKllhdWmVEqjKRjFRgP1fJgqworapUtfhyGmV8rgDIKiZBodmKs9wqpQI809DJ4GNUq7mHC08LXYaVUFphvKKVyzAMKnQzv523XibRv7k5LCxl5Dh2o5jspuJBgjKSWRYDuSnoexYV13WGWSsFzKFymlZx7fV7Lvv5sZ0TnF8ChKNQNg1b31hdBd+bX0ezCKdlOlkrsDxGvmhZsiBfvMA2ctGPLtaL1oE52tezhebeswjUCndmwWguB6e5u6lPfMwKVCjmOef6znV9GCaIJXS7miva8s7ODer3e9/eFhQVsb2+P/Ox//+//HZ1OB29729vG/r7XvOY1Q187f/48jh8/nvMxLnD40e6EiGIdGFIikSQxoqiDNpuPOcnDjigKkcQxwmg4zUcp/WCIuUAYRmi1WlBi72lOqSS+4AijUKtN8wQLZYKFcgAlYrTb/QqIB404EfCoTB9Wf/u1swCAV37bCThUwHP1A6TR7iCMPMRxjGazjeoB8ztb7TY6oT6eDiMIoxBRHEEkcbGuXiGUiBFFEcKoV7lcXwvbzQ7CSCeJSRyh1e6g3Tb3ZKcDFsdAHOdmyw8KSil0oghCKMQjCAu+o38XlECn4+eS5WY7hJQScZK/f6slBi50F6IVcoRhiGh87cwCBcZCFMXgCU+vPy60OFsUhmA8AeIYotOZ6f0WxgKPntnC8eUylusBGq0OFBQub+n7vlZ2EcX9LIlxkKXDtjoRaiUPYdj14I2jCC5T4ESi3ekgjmJEMQPAQWQCwROc22nhmlXdebbaS412mK5LgxDFEZqtFmY0qryvaLU6iGK9JtvZZkI44kgfr3Z78gQ2SSJACiRJNNNnZhxxJDxGJ5SQshurxXGMOI7Qbvdfp1RxtMMQQipI4Y3cnziKEEUxOqFmAXQiDsEl4ihEFMWIoxiAguDdWCBJBHiSoA0BKcdITZWO2aNY/5Zms5/GPQpzlfxOi/X1dfzKr/wKfvEXf3EiVejdEMcxHnzwwZltr8DBQimF02c62NrWqnWt5g7OnYtQJZsoeUU3aha4vJPg/FqETmP40rLT1otWHAucOXMWJbWBsr/3x98WPdYuXYQM1xFziZgr1OlG2pmcRwipcP58B/UyxWZTYH1bBzQVp43Tp09DCf27zp67CFdsYbPBwZJ1bF462Lmp9QbH2mXtPyxFgtOnT2OzyeEk62huHL6ZrnnCRoPj3MUInUa+yMRjHaCev7SO06d1kLnV5JCddbQ29LORhiGWL1yACALIGT4vpwUXCpfWYxAKeM7owEVI4HxTgvLtLptAKlzYiHWC6w7/fKsjgWQHre2rIuwpMEdohgIbmwnijh3p0erPPhrweAIWhtj41rcgg9lkdZ1Y4tx6jK0mx2LVwbVHPDx5tgOPETx9WSfgLpM4ffr0xNuOEontlkAloKgEDNttgeWqAze5lPv+jc0E222OCxd0lztsOhBC4Ums4+KFEI2ORGdHd/NCk+Bc3tgZuU+bTQGWbGDjonPoxtEubMQ4vxmjs8NSoce1i+cRc6BCNrF+YfK5360Wx9qlCE9gE1uXZrduJULh3Nk2HEbSrrJSClstiQo2sVbq39cLGzHObep11kl8dLaGP8PbkcCFCyGa27rD3Il146FGNtAIBc6eC8EoQZVspcdFSIVz5zogBAjGiMc3m7rA0IkSnD93FpcoQRzH8P3xqv5TH83HHnsMv//7v48zZ85ge3u7b7aBEIKPfvSjE22zXq+j0ej3rtze3sbCwsLQz33gAx/Abbfdhhe/+MXY2dHBFuccnHPs7OygXC7Dcfp/6t133z10m695zWuglMIdd9wx0W8oML8QQqKBNeBbjwGIcfL4Kk6dqOP221bn2gPzMOHCRhvc2cTR5dLQ9zTaCfD5TSRC4djx47jllqNYqO59EK5wHgBw7PgxHF0qgwtte3XHbUemEqTYLyil0CFrOHUO2GxupH9/7m03oOQ7WHg4wcWtbdQWlnH99asobXZw/TV1XH+8NmKre49zl1v42tNPAGijVi3j+uuvR2mzg1tvWMLx5SsXYnkm4/JWBxHbwLGe++zJjXN46Mx5uH4F119/PQCguh3ixHIZt163qN/UboOtrQHVKjBmoDANlNK0992E19phgpbYQaXkjjEbp7DViHHkSA11Q22IE4G22obrsJGjC0ErxvJCkHajChSYFTYbEWLSxKJ5jiVcCzedumYBruRAs4kjt90GlGez7j3wxCbcTgNLgcJSzcOJU4vYFptYqHi41L4EoIkjy7V0DZgEW40I17oM260Yx5ZLWNsMcdPJ/udJFAt88Vtr2G7GOHWkgttvWEoVio+dDPHIU1twXU293owvA4+eBmH+yH0qb3WwVAsgANx6/eJcP5d74Ty1BVppo152odQ6AOCG669FJxJ49rOOoFqePMbcbEQgwSZuuXYRqwuza4dzIdEhayCkK44lpEJ1J8Ltz1pFvdIfj9UuNaGe2gYI8OxbVrAyYn86EUdI11AKHPguQ6Mdw2EUz7n9KDYbETq4jJLP8PxM7GXjHGH8gHfDQjMC7t2CkMD1110HIRVcd/w4cqrk95Of/CTe9a53wXEc3HjjjQOpytMM+t900019s72NRgNra2t9s8BZPPHEE7j//vvxkpf0G5i95CUvwW/91m/hla985cT7QwhBeUaLVYGDR8IFXNdLq1CLtTL8wEe5XC6S3xmhEgKe10LgD18YCekuO5S5cD0f5fLwZHlWsLMk7UhhqyWwVPXhOECtWhloQD9PKJcbOLFaxdcf18nvYs3HUr0KACiZa1cqgsAPEPgSjuMd+Nrl+wKK6ONa8l0EfgDXFaiWywe+b4cdlYTA85p999liTR/XVijS1wJfgTpu95grBXie/r89TH6b7RiXt0OcOlobGcRGHKCOA9/3UquiUXBdBVAnrfBLJKDUQeC7A1VILTxPgRA2dmegQIFx4UYSruvAM8E3IQIKFK7vwxdU32ul0kySX6UUFGlgZbGKxZqPixttxIKCOS7K5RKiRD/nFqvByOfwIIQxRyeOsLxYQjsG1rYTgDIs1Cp9a7YfKFTKDRDq4KZrV7FQ7z7DTwYlnF0LoQAEvoeFin4tSuTIfaqWAcoctMIEoB7K5cNzr1KnhXIQQJk1jFKCcqkEkATV6nQxJlcOFusxFutVlMuzaxBIqRAEO1BKnx9AFxHLJR0PlQeoRVcrEsxtwXcdLOyyP44rUAoa8FyGwHcQxgTlwEG5XEYsGILARynQ28nSlCuVJjoRR9CzRmdtpCzqSj9TuFAo+T7CREyk3zNV8vvBD34Qd9xxB37rt34Ly8vL02xiIF75ylfi13/913Ozv5/+9KdBKcV3fud3Dv3cu971rrTja/He974XQRDgp3/6p3HbbbfNbB8LHF5IBSgJtDqaJloOXBAUPr+zxDi2Ua7TDYQTISf2Z5sWnBtvOd/RfnVKGc/U+U58AS0GcTTTLc12r3y3K4YF6AdEss8ek4OgVFdcznO0EBohmFthscMESgloj5cmABwz18jZS810/olSciBCTxEXiGMBPkQgxcKqvo+T+AK6KJ0V+xJC9R2HYZ/TojTjI+FC1woOUQeqwAHAWGlZ6EtRQe2BeFOUCEQJh++xNNjvRDx1rrDzptOIXW01IhxfqcBlFEeXSghjgVYnGfiMZJTAYRS1soflni5grx1SV4hvtOBV4DnYaoaQEhOr9x40YqM63Im6Nkf6nNCpY8xa2cXtNyzPvDlDzbmzMQNghc3o0OczY1qlmTHtjjEKlgFgGw5ZhWjGtK0ko7QvWXUdilan/55Z2+xAKYXjGfXy7JoslHZxUVBjP0emSn4vXbqEt7/97TNNfAHgh37oh/Dbv/3b+LEf+zG84x3vwMWLF/FLv/RL+KEf+qGcx+9b3/pWnDt3Dp/97GcBYCA1uV6vo1wu49u//dtnuo8FDi+kVBBSpouTpdkdttmSeYZNfkcJD9iFlwuJJBH7ou6YtTnxHYZS4CBOZGrBMO9wXYoji93K+rFMIhxYqyMTLFBKUk/jg0RWddp1GYTQNkeF2vOVg5qkNuulCeiiiOtQNDsJvvnEBp570wooGd8+YqZQAJdypNK0kApbjXCiNZjR7rUOwHiFY9eqvy0CTCKKcvZSC1JJ3HRycez9K/DMQ+81bn1+Va//1gywY3y8jy7qZ4Dr0FwBOU2+Jkx+pVJIhMSRpRJuvGYBQkh88aFL8D02lIa6WAsApQYWvUu+kypP2+es3bdhCDyGku+i1db+3IcFesRDuy20jNJ+JXB1wZeO1xQYBELInrESGSM5W0qtyEyG+gk7jBhFZpprYAyCdlHp3hdSqnS7rqMT7EEK2J5LBz4vhJR9WnE2wZZSaRVqaezuxjzUU0Uht912Gy5durT7GyfEwsICPvrRj4Ixhh/7sR/D+9//fvzgD/4gfvZnfzb3PiklhDg8N0aB+YBSKl2YCNE+YYQUVkezBDOdVNtdHwYv4/W7H4F5Nlh2XQbP0aIU7iHo+gJIvXF/8O/dihuvqeM7nnsifc0zya/1FiREJx0HDTtTDeh7LYw5XJfuOgNaYHcwRkFJv0+j5zLccYMuSj/y9CYA0ykV++s5CuiAJ+GjvXUb7RjNNkfgj39NOIwijHi6bmQcRkbCHq9JbJ+4FCljpIBGnAhsN6dTEb5a0X+F6MRiL265jvHWtd1YxiiE6KbZYaSfA+N0fqVUOH1hBxfWW4hjgWrJxaopsupnuU54hq3ZN59cwE2nFge+Vgqc9Dlkfeo7Ec+xNh54Yh33P3AhXZsIIVis+nCc3WOIeQIXCtJY91iP9UrJ1Qml6XLOGxyat6UUQsEz9p8D32+uB50g786y8RzWTX4znV/fZaiUnPQ6y8JzWNoMaXYSPH2pAS4knAHPO0JIel3GXOr7bZLfP8F7U/zsz/4sfvInfxKvfOUr8cIXvnCaTQzFzTffjI985CMj3/Pbv/3bu25nnPcUeGZBqh7Ks7l/C9bz7OA6FIHHsNEI4TA6tPpsKVFcqH3pUsZxt+LsmapjlIhD04VkjEIq4IW3H8ULb8/7mAepz6/+jZQcDM21F1KqlH7tOdr+4dTRakEhnQEcU/VutGNQSrCU8Qa57bolfO3Ry6kfrvZ+1knftH6T0yDh0hSqswGWxLnLLSzXA1RKLuJYQEgJ3x1/ts9hFFEiEMYCobFyGedXUUoQJxJcKrAxL0EpdNdBGEpgAWBjJ8ROK0a15BbHxED2FBsp0fZaUmLKFtNwxLHIJVMOowhjnt4DNjkeJ/lNuEA5cLVdjJBwGc11Gl1HM3aGnedRdF7PZek+VUouamUXjXaCJ89v49Zrl7DZCPHfPv0QAMD3GO685Uj62XLgYG2rgxuvEYfieSGE8b/1ndRjvRw4UEofu3kcrXNYvssqpIQ/ogjpGG9gRsdrGHkuRbOT6fyaWIsQgufevDqwIGALm9vNCDutGLWyh42dEA4jkFLTqLPH0nMpOpEuyE0ay02V/P7Wb/0WarUa3vKWt+CWW27BiRMnQHt+CCEEv/ZrvzbN5gsU2BMopdA0VblaydUMCVLM/M4SgcdQK3tQ0N3WocmvWai4kFc0nyqlniPdbTEOk+53OA6F5+h5HGcOK7KD4Dl0KIWuSynr0p6F0HTTg7y2hVTghrrmugydiBfCcjOCZVhsNTrwXIaljBDrglFB3jHdOUYJoljfZ/uZrCRCQkjkugudiGNjJwSUQjlwsNOOhtLshsHOkm02QjTbMaplb6wOm/XJXtto49hKeVfqHgBIaEq1VArzH4LvD8JIIE7EREWEqx1S9jyDzDz+XtCew5jnaLS+y7C+1UnnbsN05nT38F5IBc+lIMRBJ+JYrge5bV9/vDa1JgejXVotIQTXHa/jm4+v48J6G7deu4THzmyn73387HYu+bUKwXFyOJJfLlVKG7YNlkrJ1d3gOS0QMUZyazMXCqUR14znsl0V9bPQo07dayd7XQ1bez2X4dhKGecut1Are6iWXTx9KcTJ1SpaYZJuz+6DvTbiRHeHJ2FaTJX8PvzwwwCAEydOoNVq4dFHH+17T0ElLTBvkFKhbRamatmFTBf+4lqdFQgheN4tq/jqo2u4vNkZ+j67aIkrTH6/9thlHF0s4Zoj1ZHvs11Rh1EwQlJ5/8PS+aWUDOX0lFJKmaX0m06fUqDjDsDsAXTnV++0w/TsUvmQzFjPOxxLP3MoPJem1DAAqW3YdivWnQdKIFW+A7uXEEIi5gJRLCCVyn2vZXrEXCKKBcJo8uCWUh20ca7QiQUCb7zfRSlBwgUa7RiVkoulOsPlrTYSLnFitX/9EEJCGa2ASajSVzOEkIgTbo6JBK6ykkA7SgCFiYt0UqncSkugZx6VVDPv/EZJvojlOhQnj1bT+78787v7ubG0XOIyXN7s4GTPc9QW0qaB61CAdPU/ji6V8E0Al7d1XHBps52+9+mLzb7PJlyiEwlUD4ExQFpsJpqNAwDVkgslB89DzwN6k0WlFHxv+DXjOhRHl8pYqo93TQQug8h8wThFgGPLZcRcYKsZ4chiSWudLJRw7bEaHn56Exc326CU4Piy1rZIac+JME2A8Yd+p4pE/vzP/3yajxUocKBQqpsglAPd+e1lLBSYDZZrAS6tt4e+7jldmfppac9cSHTCBOs7ZIzkV3cgHUZAqJbdP0zzp6M6uHaeyippMkoQcyM0dIA/T0jtdan3icJhBJWi8zsTEELguRSuESDJJr/1ig5OdPDI4bl6jmo/hOUAYKsZYbMRaioaJTnhmoTrhDjhIp3/qwyw1RgFq+apYIVOxFgBJgFB2XfR7CRpx2NjJ4IQEkeWyn0daN25M0KJ+zwvPa/Y2AnRiew5lCgdHieasXB+rQkuFG45tThRx04ZJfv83/So1SyhzL3TKxBnr12pVPqsG3fm1/cYlFIoBWzie3EUPJfBoRRcKLgOweqCnvG8vKWT34sb3fjgwkYr1+XVWiw4NKJXXMiUkruxoxk3y/UACth1Pvag4Dj5mV8Q7DqbfMu1ixNt3xbshZRjrdGUEizXA1RLLpbqPo4ulRGuVlEtuXjs7BYIgKWaj51WhJWFUhpHRom+JyZZpovIv8AzBkopRIb+Gnhsrqtyhx02qRwmspMKXgk59Xwq5xIJH29RDdPkl6aKhtWSeygoVYChDA35mYGfV9KkxCqbH2zALjNqz1Y4pbA5mh0oIXAdmipeWrgOTYsM281Y032F2jfF507EjSCVgueyNBhf22xjYycEJbp71WjHABnf4igLoozwpWEXjJuolAMXjBLstDSl0ircZi0/LKTqqsTLOZihnxdY8cBkDhTlZwkt0KafKXzCtVNI9CW/tus5SwipafjDnnlRLFKC0KjkV0iFTsTBhYTvMlCqZ32zLgJXCtcIJNl1Z8Ukv1aLIJv8KtVNitO/AUgOid1RwiUIdNK+bjrbKwul3KzrvKG3gDLqupoGtiDDhYTrsLFjrbLvYLkeYLHqw3MZ6hUPlGrRMM9lKAVuuvbYTnWcjFcAze3fRO/uwX333Ye//Mu/xLlz5wAA11xzDV71qlfhpS996ZVstkCBPUG2Khr4zlxX5Q47SoGTdqTctMurHxCM0XQh5EL2iYWMC26UW8c5g2GSoT1TgmrZQ73ioTrDSvdewgqoDIKl6IWxnsWjlO5rsjMM1oIAABjRCpHzOv90GMGMbRQjpK/QsVD10AoTbDcjnFitAAR7IoImpALtmbm3SYSUeh1IuLYz22nF2GpEWFkIsNWMJk4wslDodtU6YYJK4I39WUYpdpox6pVY72uiadiVnvdJKY2N0mjF6mcShJRwTcdouxmlCc1+otmOoQDUyuOf891gbRCl0te0EBKYoDA6zD5LTuK9MgY4l+BCDp3NtAVQ16EjZ+m3m1EqzFQtu9huxvDd8ROUceC6DC6jSIREAGB1Uc8k77RiXFhvYacVgxDg2FIZFzbaWN8Jcwwuh9JdfYHnBTYZE0Jiq6E7vysLAToRn1tdEUb7y46zFER0mKa9J1yvGeUxrbcYo7jt+n4bXcYISoGDo4slXNpoQSqVNlGiRKTCjmPv39jvzCCOY/zMz/wM/uzP/gxKKdTrdQDAzs4O/ut//a/4+3//7+P9738/XPdwBJYFnhnIGqcHnqPVT+d0YTrsCDwG16Vm4dOS9+cuN8EowfGValqlS7ju3kwjziQM1Wic5S5Juh1ISgnqFQ/PuWn10HQiRx2bSuCgXvGw04rx9MWG9miUVzZLPQtIqRDzrkBFca/NFvWKh5gLM4eZP9cLVR/nLrewlbGkmVa4ZhTOXWqgFDhYXex2jGz3zHWooT3q8YROlGCh6sNh2mKu0YzBrkBvQUmFaslqN4wftC9UfWzsdBAlIk1wtSZAnsMrhGVPEMyBc9hcgBumjUspwlgg4WIs4bBZ4sJGCwSzS36jmOPsWhOriyV9PUg5chRncyeEgqa1Wkgp+xkMCoYxMLuEIuaaKTWsm9gVuxp+TqRS2G5FWF0oYbMRIvAcLJ0IZt7JZ5SkQoeALtIeXSrj0mYb93xNN8yOLJZxfLWCCxttbJiOsIXD6K6+wPMCu7Z2Ip6WOyqBi1Ynmd/Ob4ZNZsW6ZvmM9j0Gh1G0w8SIZV3Zth1GEXgOFqo+As9BoxXnBK8YJRPJy021Nx/60Ifw2c9+Fv/sn/0z/M3f/A3uu+8+3Hfffbjnnnvw9re/HZ/5zGfwoQ99aJpNFyiwZ1BKIUyTX6YVPIvO757AYRSeEa0AtGfbYi2AVMDp8zvp37n1Z5uis2KT5nHiZ0vVs51fAIcm8QW6ye+g40QIwc0nFwAAj57ZNhVQHLg/qZ0LBHQ1d16DgMOKk0eruOOGZV1cUr2dX53IbTfj9G+zTn6VUmhFHI123o9TCIly4GKhGoBSQCppKJZdQZXlun5t2hlDYuy8GCXpjPOkn49jnUiUfAdbO2Hf8eFSpfopRedXI0okKCX6+Sn3T0TNQhjv8FlcylGiC0edWCCOtXWWVSdPRlQ7NhshNnbyFN3htOcr388s4kRbgw3r6lqbo6zLgpAKGzthOhrRDjkWKh5ch6Lku0b8LcDRGVKeLTwnb6dzzRHNr3jotPYgP7pcSosI6zv55JfSvSnY7QWiWNNu21H3+Ntn9ryO1mXZZFasa5bxcCVwUQkctDpcF7+vkPV186lF3HrtIiolF/WKh07Mc4JXo0RBB2GqvfmjP/oj3HXXXfhX/+pfYXV1Nf37ysoK/uW//Jf4gR/4AfzhH/7hNJsuUGDPIJXKdX6VwsQ2GwXGAzGKygmXWN/uYKsZIvAYKCGoVbx0HinhMkdhnAS2MzPObGuUm/k9fOecGgGQYcGUndXaaelOn4K2xDhICJlJfimBW9xrM4VjPDm1B2L+wlhMFZ+7nd9Zz4BLqbQaciZRsPejQwko0f8nhE40lOrO9xIQ1Mr+1PeiUgoxF1N/nhACZWyMfJdpq5KeQFtJpTsjUxbnrjZY325qfD6FtLTe/UMn4ghj3bG/knOy1Yjw5LltnL6wg43tDriUhqqvQAkdOePNhYLsGUWVSvU1eCnIzJM3LuTIAN/a3WVp0RfWW5BS4emLDaO+LlHyHTiMoOSxoXaEs4Dn5pNfK3pl7YAWKj6WarZQF+U+S804x0FrV4yDKBFgrEvTzroazOuoj76P9b+lUqB0tok6pTrW40KOZCKMi2rJTYu6R5d0vJMVvNqXzu/a2hruvPPOoa/feeedWFtbm2bTBQrsGZTK0J59lhqQF9gbVMt64YsSgWtWKyj7LlyHYmUhSDtACdd2ItN1fmWflcowWNVhx9CeDxusH/WwDlTVUACtzYLLaI7yut9QJsiywZ/j0IJlsUdwnX5/Q9sNtQElJSS9B2YFPQ+bL8hIaaYczT1GMrZEs0TgMUSJmJpNwKheP4Cub3BvkC2kzHVGnumIEgHOhRZZM12j3iRwLxAnAhfWm8YTXq/3djZ3WmzsdLDV0HOv7TBBwlU6GkMIGUoBFkJqW5tMmC2klnXua/yS2Xcud9teJ7RuFk66b1IprC6WUKt6OH1hB+2II/AcHFupoFr29tTxwHFY7jz1dpdrZReLJqHZbPQkv2btmFYTZD9hky87R53Ot5I57vwahphSuohJTLFylih5DkCA0oxdHqySdO/MLzA+22KqJ8fx48dx3333DX39/vvvx/Hjx6fZdIECewat9tzt/ALzuzBdDXCZFkahhODEahXXHquibOZT7ayGtT6ZhlYoTOdpHKske94Zo4cy+WWMpv69g1BLk1/98PVchmY7ToP2MOLpg3k/kFV6BrR4ScGy2BswNoj2bDq/hvZMyey7UFoJWebmYa1CshX/sZ1eqeRMA6uS7+LYUmXqbTJG0WpzKKUyQXb+GGb/UxyCAHyvkXCBRCg4Zi3S6/beH5ftZoSN7QhRrJNvO+4yqiAxqpgaJZriXPIdCKG7pdl7g1EM1UvgpkiiMkwBpRQk0Cd4ZYsqs8RuGhe2o2rHCS6st1AtuTiyVEIlcLFcD9AJOVyX4prVKp53y+qIrV05bAxgcWKlN/n1sGRoz1uNMPdeq2K/F0J9s4SQCoJrRkR2vhnQidisE8pZgRJi1j4z88uunJrcC89jKPlsLNutSeAaMa1S0LV5ZHSyOYOpfukP/MAP4FOf+hR+7ud+Do8//jiE0DSUxx9/HP/23/5bfPrTn8Zdd901zaYLFNgzCJlNfq2f3EHu0dUNxiiU1A/ilYUA5cDFqaM1HFksda2ODO15Ggab9d8cJzC1gkAOIwNVOecdNO38Dn69VtYP27Tz62jFZxvEfeupTTz05Ma+7Ctg5usN1ZxSAkKLEYO9wmDac7fzK02CN62f9jDo5AcmAdbfbwWkcqfaWG/NU+e/7LsQUqJW8dIEvTdR4Vym1O2Dnp+fB0SxAGTemmo/GuIJl4i4MFR3CcZ0EXBYYtlsJ3j87PbAYl+cCJy91ECSaH/phaqP5XqQK4JTQsGHsCSE1Ne6gvaZBkyiPSDJIYTMXHHfXpPD0ArzyReg14LFqo8br6mnSch+KRAzlpcBW6oHOa2Nqun8EqNG38zoBzDLyJjzuV8pdfFDd3718S/laM/zs+5lwZhe26zSuUPJzN1PSr6DWtmbub6KVTO39P5WJwajNHdf7oap0vF3vvOdePrpp/GJT3wCv/u7vwtqbiQ7h3HXXXfhne985zSbLlBgzyBlVxU18B2EMT+UXcDDAocRUKaTX6sIeu2xGoRUXaECLgE1Le1ZQUk9+7ubWnQ3+aU4jDkYpQQU/UmOhe38tkPt3agDBy0O47tMeyILOdSSY9ZQCjkKmK0yF5g9BnlA16s+KNH3SLMdG9rzrDu/gJJIE2AKBiH03wjp3mRSKHAjqLKX2IklGCHYiRVOVHa/yZfreZue3mSqEyVp4HrQyunzgDDmuUCekP2hg2v6uTK2VAIOpZBy+HevbWk/ad9luSQQ0Il0O+QIY57ODzJKtT2cFFpbgZqi7IC10upMUKk044HZ61+H3V9e4+AKeMlRB4TMfs4+4RKjllG75lZM8sUYwdHlMgLfQeA72GnFOHOpuW/ig4zS3NpECcGx5TLOXGoC0M8tSgkqgYtmJ0GzE6Ne0c8ySumh6PxKSxs2ysaAfubthYLyLMEoAaW6404pQa3szTw2qJc9HFksp3Pds0LJd+C72lEE0AUvG1+Me71MlfwyxvC+970Pb3vb2/C5z30OZ8+eBQCcPHkSr3zlK3H77bdPs9kCBfYUUdLtUAQe08nvIewCHhYwqsWlegU1KEFm5leY4GHy7Sdc6AAMxm90ZPJraM9z/DAaBWa6p8OKBKXASSvlzU6CWskFFwrcJLzcdCyEVPviba2UylDA9PkvbrW9wSCVS0YJ6lUfW40ImzsRluqBEZ0azxd7HGi6p57Ja4ccgWe6wCqf6BICtNoxFmvBiK3l8ciWQCIVnr08Xojy5TWODz+kZwYJgP/3twW4rjbBLKNCrsNk/X+ZYVscFtXZvYRWtO2unarnmO0VuNCJpjDWaY5DU9XjXrQ6CToRh5AK7Yj3FUWFlEi4SAVzLAh0gdS6AQjbDWP5ayhOhPGuJxm2g0KHS7z/GxyXQ/23m+oUFYJ0zZ3VVC2XcuRzrpf2DIXcOfNcpv3W96kQqfUIFJ66sINTx2qghOS6gCsLek2olT2d/A7q/M75yIE0c9WEICN45UKac7Ufz9tp4LmajrzVjJBEEsdWep3OrxyMUdxy7eKebLdScuGa+7PZSbqx0ZiNlCsiYt9+++1Folvg0KDd6S6snssA1T+nU2B2cByKcuCg2mNnQghJZ67jZHqrIx2EUK04u8vnY95Ve56h7eK+gVIKRoZ3fikhqJZcbLdiNFoxFiqeFhoyXsjCJMKcD7fJmCWkUrlAQP+GQ3jgDwGGHdelmkl+GxGOLJXATRdlVtIj0qhdCUmwttkGIaSvmwpo2yVNhR7vurscSvzK17Xtyc+/lGLB3/1z//WhrliOAvDgppgs+e3p0kklUyojDPVyGi/yqwVCaDXk7NJB9mCOvPc7t1oRkkTrQmw3Y12QMMnEIKHDMOZodRIs1wPECUeUiNy8oTC+u73Pfca0TY3ufhn/eaHQa2GccGFmebv2V1xIfGldpYkvADy5I/HcJb1eqxnORQsxnEGxsRPi4ae3AOhk0j5Ts7edtiBk+yb06TpakV55unhS8h08/9YjeOLcDpbrQcoIq5ZdYL07tmNBMH4n76AgjWAnJV2ro3LgpOvFvK4ZDqO4+dQiHn5qE1IBJ49UD3qXJsJi1QeIvjaEVKmjx54KXhUocBhhFybPNWqVZH7FCK4GlH0HN16z0FdlB7oz1zopHS1eMgw6EKJ67neXIMxSPh1GD+U5Z5RglNozANQMXazZjo04lg6WONeqy1zozsl+QCnkAgEAh7Ljfhhgr2chFZ44v42mCSCXTKd1sxHqLkpGfXsW0A0ZAim7Pr6DLF8YpWmFfhhiofDjf93Cj/91C1+93J23fGR7vP3tvSv+9+kEYiLxk3xhSciM96Wh2c57B2oYhFS4sN5EdAXWZ8LQfGnmHqYEM6fSZ9HsJFjf7KSdNSEFmmEM19EX2FYzwnqP324UawVw16FIhOpTOB92/Zd8B55jEkNq9BJ65ryVUmh1EnhGadZeDjEXeLKRf+8TDQFirqlZXjYJl6mSei/+5188mv57seZrazGSX3ddh3bjn32A7zJUyx4Cn2FtU5+rF912FHd99814513PS99nC+TNTv+c9ryzLpTS55iQrtpzyXcglV5X5tlRZGWhBIdRuIymdPPDgsWanmW34qnNTpIK8Y2DsTq/t99+Oyil+MpXvgLP83D77bfv2jEjhOCBBx4YaycKFNgPdCK9MKXS/ipfFS0wW1BKcHwIlcYKFejZqukEr7gRadhN+RPI0J7nlII0DhxG09nlQbABxI6hjhHoY5QI3cWIYo6zlxqo37iy5/uqlMrYbuj9KpTV9wa2s9AJEyxWfbRCjmrZS+esNndCPdMoZiseY4MMBa2Y6zAKIeRUxIpvbXWTlD8+3e3+PL4jcEOd4hvrAt95woE7wTX0tcsCLzgyHrmN0u4aAXSFu7QdiIJI9D3k7p0l6p4hTjgub4WIEonrj9en2oZSCgoyn/zS2dtnZSEVEMa600qgu62VwAWjDECCOBHY2A6xYtgGUczRaMfwHKZFuVT/rPaw659RilpZ3y/UBNC9xQ5t2yfhuQztkKfCOoxQNBL97+cuM3xjQ+CJHWlii+mcDAZBKZ3MD0tcHz+3nf570bAtKM27G3gOhe85Y4sCXSkC38Hzb1nF1x+9nHbpGKN4ybPzbjCpW0Er3/lVAJJkH/y0rgBagVuBEqDV0QWmSsnVxTM2e/ugWWOpHoxlFzlvKAcuHIehEjiIE4FWJ9He0LNMfn/sx34MhBA4jpP77wIFDhO6nV9m7DgKKuZBwVLRYjOHOM3DWBjbjcRQe0chznZ+D+k5dxw6ducXgKZyCk0/5lIfI0tF3mtIhe7MrznXh/W4zzsYJVDQ13g5cBAlmgJsLUQ2GlEqgJYIOTO+l00klmoBolhTUxMhpwqrH9jsBrjZ+s7jOxIPfD3EeqjQ5gqvv76/OzFsZOLDD0X43pbEnasMD29JvPKa4ckzoxRhxJFwAddhXRE9oo+tnTk9jNBdTHlFhQ89e5kfE6KUIBFqz0T0pNQe8Q7Tc6JcdJWO7Wseo6mw0OXtEI12nHpcA4Do6d5GXI43g0l04TALfU1IeI72LlXSUi4lYvPWO5Z08nuuJc1rmFnyq+m1g9fRLF34JXccg+cyxIlIXQIsSoGLI4ullBWyHyCE4JojVVzYaA99T5r89nR+HUpSh455hbVJI4Sg2dHnoRw4uviA+X/u3XiifigFORxGQIk+1puNqO/a2fXz47zpx3/8x0f+d4EChwFhpBdR32Wpv+O8V+WuVgSGCsuFnkedND5oh4kOhiiB5Lt3fpPMzO9hPeUuoyNno2sl6/WrH8DKeK5uG//ElXqAMBFotOM02NgzKIWOud9KgQNK909k5ZkGvY5pFoVrKJkAejq/mTnJGSW/9kok0KIuYSyQJBJkit7v6cbgxOxsq/v3BzcFXn99/3vCEbHxp59O8OmndVDU5gpvvGHwde97DDutGGFskl+TaBAzHiOnVKSfBwgzkxgnYuq5Zeutm/2stUmJEwEQkj5XgdloaSRcd08919F2R4lAxbf6AVQLcPmabcAo0xoQjMEzc6SDvK2TRICS3W8AKSS2mzFKvoOy+U79rDLU74xIo5AKZqnDsbLeNldAR5AcPfpKIQz9e1AB58zFBgDg6FIZd73qFgC6KER61l1GCW4+tTibHZoArkPT0YtBNOBaxVj19XR+GaPpLOe8whYlokSkxeUVIzDIjIDaPGOeadmjQAiB63QV3VudeJdP5DHVr/7gBz+Ihx9+eOjrjzzyCD74wQ9Os+kCBfYMnWznV+mgbd4XpqsVJb8ru5MYi7RJcP5yCzuZB+WugldZn9/DqHgF3fkd1H1SJjBPAwhDe7bBXyvkKLkOyoGLrUaI85dbe76v2c5vySusjvYSWqGWIuYi9ToEgGXT+d1uRmkyN9OZXyHTJIcSAiEALsRIK5ZBUEphrdO/X25PdBIOoeY14vzfv22F4e2391trfO3ycNaDtWSx9L/sfUZAUq/iwwgryCPE9JZN9nhk107G9Lz3ucstnLm4AwC4vNWZ2frCuYDLGCqBi0rgQEmVKgXXK55W1FVd1g/nss+KKXu9C6n1D8YZdVIKaLbidA3Tn88rmdtnFufdzm/FAcqmpdRIZkd5BrodxkEF+7PmmJ86Ws28H2Bzsu46jMJhZCh7Iu389ghesUPQ+bWz1VsNzbgpBw58T8/8Ft72ewvXoSmLcNC8+ChMnfx+61vfGvr6I488gg996EPTbLpAgT2DFfzodn4LteeDQslnaQfWzv1OglYnQRgL1CueFnYas/PLDnHn12GD1Z4vb3dwcaPdF0DYbmCcCG1oTwl819knn9+u1VHgM1BazPzuFVxG4XtdNgsxncpaxTMiaYYKT2ZHwQRgCogalFIzJzk5za+RKIRCb+v/eqme31z2Cb5tNS+SdbkzOJnYSbp/u6ZM8I9u9vCCIw7eeENe15rv9tNVV9RqqxHmZoChgEM4FgcAacIWc9EdiRiA0+d3sNWMBr42aN1xTFcu4TKlPzfacc6u5kqQiG6n2XUYluuldO1iVDsJWDs3wNjd9dCys8mvMgre41yfS3VfJ12Zn82F7F7wmXuJC4nIfE3ACOqeftNOjJnec1Lq4aBBgle24HBitauxIYS12jn4BIwxAkoGF2+BrjVTqyeBYZRcMWV/r2HPy1ZDK9Rbxo2Uat/8lJ+pYIykY1W9185u2BP5hq2tLbjurAwVChSYDUJDn/FMoEjmpCr6TASjeo4rTrT9ziTxwWYjRCtMUC25IMQE+7smv93O72GlursOGzhPGcYCrvG9AzLJL9UBL5ddmxm2xyI1FlIphDb59XTCfViP+7zD9xiqJRdSKVRLbio85ToM9bKHrWaE7WYMz6Op1cssIKTMFZKElAhjDm/CYPtMU9+bR0oESz7Fr36XDuDvOZ/g/kvda5UrYCtSWA7y+2+7xrcvUvzY87pWS99zrYe/OJOgaZp3W5Hq8yDu+01C+7LGiUjt2CzkDC1r9hNS6tbUqP0XQqITJZBKoRI4qQVN9vVeEGhF+UYrRilwzFywQswFopjD96YPL5VSiBIx8vlsv7/dSXQXWOSvR8186Vfwdse4Phll+j7KKoAL1U2GVfeZE3ORzqn7jKDmElyAQjNROOZM52E/CFLpOWP7E0+f38F/+cNv4PoTdWzs6MQrl/xKBc9jc1F0dBgFG9H5tWKNYax9lG3C7jCKTsy1zdYcJPGDoC3fgE1TOFqsasaNUmouCg9XM1xGEdjO74RFt7FXp/vvvx/33ntv+t+f/exncfr06b73NRoN/Mmf/Ame9axnTbQjBQrsJWTGB8x3aEp7LuLxgwGlBK5RL44TMbbglVIKj53ZRhgJ7fMGAGPQOW3yyyg9tN1+xvoJ20rpYI4xioqpMjfbSVrcSRJdNfcyolN8H+yOlAI6hmlR8pme+T3EStvzDEIInnPTCraaEcqBi9MXdiCk9vOtlBxsNSO0wwSu68+UuqsFkLr/7bsMrZCjttxvbTYKZ8xc77XVfKB42yLT1DQCLHoEG5HCWkdhuUer51JH/6ajpf5A82iZormjt88VsB0rLPmDr0M7JiClhBDI+cMCgDykrV/bzaaEDj3/3NhgdRoRfFffr4HvpGusyLb5M1is+QhjPUssjPBgwiViLuFfgaxAOmO8y1rtOtpbVWV9mQ0I0dR8K4gl5GRezZTk18q4R2nZHsl2hnYfOEDZWDG1uU5UZ0W20OMtXZXtj//ZtyCkwuNnuyrPJzLuCuMm+vsBZhgpw8abAt+BsdRGq5NgwVx3zBQg5tnuSJp7w9KeF2te+vexxNUKTA2HTU97Hjv5vffee9M5XkIIPvOZz+Azn/nMwPfecsst+Df/5t9MtCMFCuwlrOAHgJQiSAoq5oGBUmK6C3yizi8XuiOw04qxutjt8uyq9mzOveseYtpzZp7TIuHSKFgj7bQIqSnHlv4qRLfzSwnpUzHdC3Ah0jlrz878HtYDfwjAGMXKQklbodAuPd4GBp2YY4kERvV8tOfuuJBS5gpJtbKf2sVMApu8Hi/nA/XVEsVPPT9AxSH4n0/E2IgE1kKJ23r2/5Lp/A5Kfv/+tS5+45tdKu9GqLA0ZBcp1TOxmsYoQbLDoWR2Hbz9Bhdd1ephSYQVc9IaAUm6rtjkV0oFOiD7dRhDySdodhKcX28b2zl5xQW2MxebOnnoHfzuAWMUUSJSde5ssscoTSmzjDJIgV07/1nY68EiikVawCOEmCKJRNuscxSAQ4CSSX5DYQoGA7yvp4H1OyYA7n/wErabeQr7Ys3PFWxiLuHtcvz2C4SQlCY/CJQQlAMXzU6CVthNfqlhdc2z0rqQuvNrGVdWbVwqzE3x4WqFwyhKgX4e7Bnt+Z//83+Ot7zlLVBK4eUvfzne/e5343u+53ty7yGEoFQqwfcnfwAWKLCXkEaND+gKXhUB+cGBEpI+mCMuxha8SrgA5wInj3Qr3IQQiF2CLZuIuYd45pexbvXcJh1hLBB4DFwoMEJQ8h10Io5GO0FgijxCyrTIQzKiPnuJdkaC13f0MT+sHffDBEa1uqile1rqbifi5u8CwGxGkoScjcWNpS0fCfoDxRvrzLymv+d/PBrjZcecXNHSfv5ouX9fnrvs4H3fwfAbD4R4YkemfqyDQEynTygFKZGfHwWZ67nDUbAiT6MEz6yY00LFx04rhpSaQm/VeXsp7lnYYksU83T7VzLn2uokaEcJolik83zDYBWnz1xq6CJfpqvPGEEn1h1tbW+obbjGvWb19aDXMSm1x266jkIXDKRSsO5xvmNiYLPLHQ7jYT+j5Fd1baU+9+Uz6X7YI53r+hpP4F72wkGCMTLyuqiUTPLb6YqM2WtrnsXm7G+ytNtqWa+vSimwYuZ3T0EpQcnTx3vPOr9BECAINN/o7rvvxsrKSvrfBQrMO3Tn13SiXDvzWwTkBwVLqwN0YD5urNSJOBKu4Lrd7g8lu6uYxhmro8Na8HAdBodScKHgmu5CFHOsLpV0wKoUamXXJL8xSn7ZzODJlOpHDLVzr7w5LWwV1nVoailWzNfvPSglRtVbdztt8BtGYqaUd11UUVdcSJJKpZ6oxwYkrxbLmcT4by5wfPc13QDzcqgXj9UByTMAVFw9hwkAO/HwhcYKJElhFVyz4knIC2AdImh/XApFus/AXtjl03MZasSDFBLc0E0Z02vOsPuXQN/fofF6ppReUYGtEyXohAlqZV/bCo2AwwgabZ0sJUKA0m7jxSZOMZcoY3Kla2qKSLaAKGVXvZfSLjU7NNsNTFe4ZP63YxTWpJyNvZhOpHUB2Ab6/68feB5+45NfBwBce6yWvpcbz+/VxclGEPYSLhtOuwcGi15Zq7G57vya829dFqqlLt+/YBbuLQjR6tqAdZcY/zqZ6paUUuJv//Zvh77+53/+5zhz5sw0my5QYE8gpUo7v75bCF4dNKjpUgJAGI4/86uVoftVPXdNfm3n16Gz0vvZd5R8B77HUtVyAIgSicWqD2Y6IKnicys2vooq93MpJan/717C+h0GnmZZzKtYydUI32Xp+bUFpjDmxvplRsqzSv9/V3pWz7UkQgEEDLimMnxrz1nuFrvuu9i9/kOBVGzIquwOQt0kv6M6v7aLyE0XNJvYM0q1NsEh8/pVSiewdsQnScTAREKqrpKx5zB4LoMQKk3+tD/u8OO7UPXNvHRXWXpatEIOh+l92A0OY4bRIPt+l1VI2NwJcfr8jtZ9mOD02etBSn0chOzaJFFC02Npk1zf7K6lPXe47vjOdOYXwFMXmxBSYaHi4brjNbzwtqM4sVLBtz/nePpeW7QIvNmMOMwCrsPGS37Dng7ePjyvrgTCFIaaxme2Zjq/IJMr3xeYDLqJ0nUOmeQymerZ9Uu/9Ev47d/+7aGv/87v/A7e//73T7PpAgX2BApd0SNLey6U+A4OhGj/V8AII40989uf5PYKk/RCZgQzXOcwd34p6lUPYayDrsfPbaNcclArW0sblbM7osYjMXudUzsHvOfJrw4EfM/R9K8iCNg3+B5L57pLGXaF9uKdXedXYrDtyiT4q3M6kb2hNvq+PFqieM+3l0AAPNWUqbdv0ySzHtVKu8NQM4lxrydwFpRoNdok0b5LWXk5x3Q/51l4ZxA0nVknvg6jups7IDHtFfOy1lU2qeRjCUUpAAqMkfRZO3S/hhzHZjtGp5NMNKtaq3joRByB209kZJQgjDi2mhFanWSitZ8SUyhUXTGvVDWfEcRc4uJGu0t7tp1fS3sWmi4/q2tGGoG5J85pgaubTi6AEIIffPWt+PF/8m05inPCNdXbncCx9MoAALucSURBVCParWuERoehEgy2O5r3zm8itGaJLfha5WooHNpY47CAEgJCSHrtTFKcnOrO+PKXv4yXv/zlQ19/2ctehi984QvTbLpAgT1BTvDKdH6LgPzgQClBKUNXGXdGLOGyr3O7G50zS1f09snndq9QDVxwIbHVCHFksYRjy2Us1QM4jELKbtW50U7gOhTtiKNe6dKwst2MvYQNBEoeg1IF/Ws/4We6PbbzYwXQ+IzOu5QKulk4/Lyeb0lcDofflxfaEn9nurijur4WdY/iaEl/31NNfU/bZHZU1xdASnse1fl1mGZKxAM6hIzpwtuk1NmDhhWCooTo2V2hkAwwPI4SMVDQihuF5HGUlxerARarPigZnfwKIXH6YmOg5/DFjRa22zH8Mbq+FgQEx5YqqUhSFtWSi3aYgHNdMJxEcZ5Q3RGXJvnPUuFdh6ITcbQ6sRa2wuDOr77nZldwAoBLm20AwMmj1aHv5ULTnufpWec6dGRyUikNVu0lmK0/+ayRcJmysSgByjYRQ5H87jUsk83OWU9ynUyV/O7s7KBSqQx9vVwuY2tra5pNFyiwJ5CqO/epZ35RyNAfICghaWAeJWJsalgUC7CeB4qlPQ9L6KJM8usygsOchwW+A6kUdtpa7fr265cBAI6jOzXVTOfXYRTXH6ulD2NAd+qUUnseTHSMx69VVqfFvbZvsCJXUqpc55cQAjUj5VRNwRw+89tKFN77pQ7efX9n6LX2yFb3vnzpsfFEuK6r6ZDlaeMNbJPZqrtL8jtG55cY9sSgxI1RBiEVovhwJb9SqdTehxKCRAhs7nTS18OI48zFRk7JOPd543uslMIu47dGbE3bJAkhsWm8Z3sRc4ko4mmBzIILiTiRqATurrO+44JSipWFMiil5jdM1vkV0iph5887oxRl30Er5LCXxKCZX0qHe9tOCnsfrW3q83dkxDwvF6rPp/qgMYxpFyXa23eppjWE1rc7udf3Y0znSsC5TK/lSsnN6GsUtOe9hu78drvtk1ixT7XCnDhxAl/60peGvv7FL34Rx48fH/p6gQL7DZUJajxXCy+wGT1gC0wORkla3bdzvOMgSkTf/CgzAcawICOMrdiVnvGep2r4pCgHLgKPoVb2cCRj9eQwHdxlac9Av6Cb9VLc61jCFhxcxxSaintt31DyHfguQ5x01V7DWKR2N7OYW7UqtsNuJWs/BADr4eDvO9/W73ntKRcnx+j8Al07I7tNm/zWdun8jjPzm3axRxyeQZTheYaUefEuRik6kUipuJuNEFvNSGsD9K0VuoOrO7/jd7EY0566a5udgfTmOBEIY45GO8pdi5xLCCn3ZE5VCAnOx7c5AvSxkkbsatCzpeS7WF0ogTl6f/toz3z3kZxJoMWuJNZNUeHIUmnEexW8OaI8AyYR7Dn8Silc2mzjqYsNHDP+4E+c28H//dlvdYtmZL6TXyEl2qbYa4vPSmn7oyL53VtQSgDVnRff887vG97wBvzxH/8xPvaxj0FmKB1CCHz0ox/Fn/zJn+ANb3jDNJsuUGBPoK0KTPLrMEg1GQWqwGxBadfqKOFyrJFfpRTCiKcd+7XNNv76K2ehDC1PDKGXWUqSw6zlzkx+woGgWnIR+A4Cj6UPWsBQNqVK6T/DPO8I2R/BKyswZjvSBe15/xB4DOXARTvi+Zlf09mcxbmXyNNAe7Gd6bBuRN1/2/lRADhrVJ7HoTxbLBormy2zTfs99TE7v6PUni0kBiuhE0KGrjHzCmlYHvbnVEouWlGS2rJEifb1lVL2MWIY05oB1gZp3Pluh1JEsUTMxcB5107EEScSnUgY32kNTStXeyKOVw5ctMJ48hlYpQsInMuBiTOjFJHUf++jPQsFSnTiLWZScNKWTlIqLNV8LGTGWfpA5k/ThFHaV1gKY4FKycVSzcdShrb+9Ucv49xaE4AuSs3rrL31IO6EVunZzp4iZVsU2DvYeG6amd+peBHveMc78MUvfhHvfe978eu//uu48cYbAQBPPPEENjY28NKXvhQ/8iM/Ms2mCxTYE2Q9Dl2HQkg1dw+HZxK0z69efhI+Hu2ZCx042479xz71INa3Q4Qxx4tuPzrUXsN2IR2HgpDD3fmllOC6Y3VQSnKBnJ6n6pX974dOftWeq9baEQOX6f0qCk37B0IIlmo+NnfCtIsWRlzPzs1o3lv1dBR7sZlJeLciCYAhkQq/+KUOhAJ+9oWl1OJo3K4vACx6+r1bhmt62XSYV4PxZn5jCURCpV268y2JoyXSLc4QgCcSDiM435L4H49GeMMNHm5ZYNpSbUZdvP2CMufadrU9h6GlkrRDYtfeKJF9nrCMEkQRT3/zqPnuLAghqJS05dpTFxs4ulTOzeNGiUDgOboQwmXKABJSd8vG/Z5JUA7c3PjH2DACgVwM9zmOrKd2D+05kYAEAZGaPn6l/WypFLZ2NKPn5NHqrs+xeYtv7DMga7PXDhNUSm5qRfmy553A579+HgDw0OlNnDpaAyXD/akPGtp7WSuUA0iZV7JwE9kXWMEre2/vudqz53n48Ic/jPe85z248847sbm5ic3NTdx5551473vfi4985CPwvBFVqQIF9hlSyvQhboUX5u3h8EyClagHgCSRY6nQCqnfZwPV9W1N/3r0zLYOpIZsI4q7Hr8Eh/+BdGK1klLELJihPZd9/RBoh3xggksIZtb9G4WstZRmWRT32n7Cisllac+W8jyLee/ejmIvNqPuvWi7tE/uSFzsaF/evz6XIBQAI0hFrMaB7fyudRTe96UOvrCm7+3V0ujry2daERrodov/9kKC936pg//5eFd4yaEEUcLBKMFvPBDisR2JX/+mXmcYowijw2V3JNRgZzerXiy4RNl3EHMBp6cr6jgUXMo+AaJxEBiV982dMKe5AGjas2M8X7PHUsohO7uP6Ls3VNfTethzIzI/z3Z+g0wNIVaAUHImjAGlgO2W9u9eqQ+nPNv3zlvBkVGSei9bJEJidbGEckkLOX7vd9yQWjY99OQGAMO4mJFF26xhi4mp0rMVXpK6618wnvYWdozNiqXteedXfynFm970JrzpTW+adhMFCuwbrBw9oAWvrPppgYNB78zvOMmYEFZ4heQWOc/VnfzdBK9cRkEoDrXg1TBYepVNeoTUqrW9qqn2fXsteBUbqrntThf0r/2FZUcEmW5enAgz7z2D5Leno2hxoS3xni/mBWts8vvodjcJuvusTqiOlSmcCW7IRUNfFqpLmwa6s8DDQAjBsk9woaOwESocLQF/c15fo587z/EPb/TgMwLfdbDVirBSd9K5YpvcuIwiSsTA+2peIZWE6lXHN7O8XEhwqRD4DuqVfqVkh1E0hbZGygbxG6FE3SO7nrfleglbzSideY1iLXIluPbLJT2znEJO5sM7a3x5jeO/PhThh2/z8eKj3fvGWuUN67SGPZ1fSggCpj2oI0VAhJqJyrpUKtVyWKz1n6/s/tI5FFtijKb6HMzePko/I8q+g4RLuA7Fa158Le775gWcu9xKLfvmddxASl0EbBmP32pm9pTSw19on3cQQnIK25MU9YtyfIFnBGz3D8gE5MXCdGBgjKZqlDEfLCjSC+s5SSnJ0XpztLkBiLKCV4ec9jwMzIiJeA5NA9VOOJj6bOfY9hJ2lk9324sK+H7DYVrcKltkCmNuOr9Xvv1hQcZnnu63r7kcKiRS4dNPdzuITfPPk5XJrovAISgNyDt3oz0DwHKg1/01Q5XONsYe3uo6ARxZLIFRlnaKAaQ2OUL2K//OM6RQA2yb9CxvO+QQQg1NYgm0mIwQ3WLKkw2Bf3d/B/+/B6Oxvt9h3bV6fTvExY2W8R3W85/Zhh4f1qbeJ3z80QgKwEe/1f1txBQKxEjas/5fP3Nd2rlfuwT3+ihPAylVOqu9WB3OrNSJF507QU/PoZpNkLl/FDQV33VYeplWyx6uOaLdZL51ehME5tqYQ0gzQtRKPX6t4JUughTPvb0F7Zv5Hf+zU3d+19bW8Hu/93t44IEH0Gg0csJXgF40PvrRj067+QIFZgr7AE6pKHNYGX2mwc6nciHHmul56sIOEq5pzzutbpDNTYA3LCC3iRgzgldXYxfSqh7q+RcHjXaCdpQM7RDseec3VXumxb12AHBMl0VKhXLgIEoEOiFHueTORvBqyPWTDBBDXgslfvqe9sD3TyJ2ZbHgE3Ta3e//gRs9eGNQPG+oUTywKfCJx2IcL9OcENfX1gWet6LXIwLSVyTYjhWWgtkJhu0XBnXMKCWIEwHOBWIuQOnwLiIhBDHncJi2LPvlr4RQAL6xIXSStctayihBkggIIeEwikY7gecyeC6FAnJxY8L7bez2E9lxbi51UYCSLmNi2G+NjG+yn7kGSwzYhFZ8XsTwwuxE+ydUSkGvD/A0ttBOFvNn5ei5DOXAQbOVoBy46QiT52obseze3nxyEWfXWjhzqYlbrl2cmV3UrGGdExomHlkwRQlbpC+ee3uLdObXMJz2XO35oYcewvd93/fh137t1/DUU0/h3nvvxebmJk6fPo377rsPFy5cOFRzMQWufqTUV5elnb+rMQk6TChlSuXxoKg5A2Gq3pZ+lu38hhEHyPAAIzHbZkZ98Wp8IGXn1+2cZ6+PZgoyG7ubUcjO/NqkvMD+wXUoHEbApUptINoR75uznBbD7FvWo/5tZ62OXn+di++7vis8dMvC5PThrLLz913v4jWnxhMyetGRbq3/V74e5pSfH9rMrz+hAHhP8pt2Quc0EB8EWyzMwlJPWx0Ozxl9/CslB0Jods2j23lV/o0hFlb576LgUiHmAlJp5k6csauzhQQhJNqhOBAdjg7XzIQsrGCb9ZBXI6ye7Hj7oM5vx1xEagZ87jDi6XNvlNKzkAqU0Ll8zlUCF4kpdHdigcB3UA4cMEpyR+j4iu78Xtxoa3u+eaY9S5UW462wm5RaD6Ho/O4tmLGvDPzJnyNTdX7f//73o1wu45Of/CSCIMDLX/5yvOtd78LLXvYyfOpTn8K/+3f/Dv/xP/7HaTZdoMCewFJfU+87VXSjDholvxu07qaimiQCiZA4uqiFnrI09k7Mded3WDfKbJtSctUKL1k2g1QK9YqHS5sdbDeHUxP3vPPLuyJjQFFo2m84jIIxCiFkSglrhxzLC7OhvEeJGBjYbWWErt7yLA+/+2gMI8yMqgO87nodtL/smIPtWOG62uRBS9bTd3EXf98sjpYprqnQVGU6i+1Y5TqZ2z2WSHZued49R3sRJ7LvOccoQcIFooTvav3jMoaFqj5Hj+3kCwTn2nJXoTGHETTaQhcuuULJc9IEIWsdFZn9KfujQ9JWovA35xO87LiL+gTnfhAe3OT4Lw9EiKW+juLMZbEeKhwpGXV8CShI0CE04t6ZXyBvdwQ6m2tms6GF11yH9ilzZyENRX8eBT1LvpMei4QLVMsuPJdpJwYgvQdXFgIA+jfr60QnmfMWs0mp7RdtQp9Vew4cpyj67jEoMaNsjEzsaz3V3fGlL30Jb37zm3HNNdekC4KtJr/uda/DG9/4RvzSL/3SNJsuUGBPEKYCPPpBbufhChwcvIxoTBiP7vxGifaMtIqk9nwCuiKuKXTDqJiZ5PcqPedaTEQrqK4saCXQy1vhwPcSTDYbMw2yyuqa9ry331cgD9fRM/Uxl+l4Qdt4Uc4iEI8Tgc2Y4I9Px2gmprulFFpmlvf/emkJ33HMxXJmFve5K92AfcGnUyW+QNe2CMDECdBbb8vTRa+rmvgFSPcdABo9yW+aDKv5tV0ZBCH6/WkpIRAS4Hwyx4O1Tv6YPNnY/ThQqoswUayLl1kFYgK9DwDQaCXgXO5anPzUUzH+9+kE/+WBwWvbJPjk493CzFbP+V4Pjb0T0b7PUnZt4rYjmWNP2O6uTXj1v+1r+njP4prZ2NG/uV7xRiZVVoV9Hp91nsuQmDEnIVSaxNt5YDtPb8d1Gq0YSmo7ob0u2E4Dqbpd30rgpsUkKRU8t3jo7TUstVwqhWp5Moehqc6OlBKrq6sAgHq9DsYYtra20tdvu+02fPOb35xm0wUK7AkiQ8P0HDq3aojPNHguSx/QcTKEomuQGFEsG6xlk2X772EPR0vRZITM3RzUrOB7eo4uTkRaNb+83Rn43lGFglkhyXZ+C9rzvoMQgmrJRZKIlPZsRVmuNIi0/qyfOSfw6acS/P5jmmHQEYAN8asmQV32uyHGyhiiVOMgm/BOmvxeU6H4nmu7jJPjZYqKSVRsEg8gR4kGuskRISQtps07bLes99YjZhZcSDmRHc6GSQiftWDEr3ZGFywtfJdipx0jSUQuEWdMJ4VKKTTaEWIud/X4/atz+hp+YozEexSUUrjUGX4fWKo+AQCTfBFCcP8ljv/vfR38hdkPpRTa5tFVyjRjrddvhytQOhuq/FZD32f1EZRnQH+X67C5XHMpIagEDp6+1EAiJEpG9DKrBA1o1WSH6bnwZieZ21l7Kbtz2AsZEbKESwT+FL7SBSYCIQQuo5AS6XNuXEyV/J46dQpnzpzRG6AUp06dwuc///n09S996Uuo1WrTbLpAgT1BFHWtV4RUYJTOJS3omQRGSRp8xclou6NOxHOqpWFm5tdaJQ1TYc12fnu9LK8W+C5D2XfQDjmOLmlq+KVNLTKklMJmI8x1K/Z65jfJqj1fpSJj845S4EBIldKeW51kJjOrwljkfG1Dn+MHzbxsyySPHgVcU9TKdn5Xgtnce9mEd8GbfJtZZeijJZJ2khuZ5Hc7yR+jbUPnpkSPXJy52Ojzr503KCUh0V/kJdB0Y6Emo5Haee4XGRug0w29jd3guTSn1J/uhykkrG11EEYciyNEnAD0zeVOizZX+Im/aedmunthO7+UEkh06bifeEx3+f6X8YaOJVJhtHKm82v/3eJqJj61Silsmw5jbZcOl5QK/px2HRdqPpZqAWolD0JIuIb9ZT2A7eVECEkVrbdbkSnWzGHym7GfyhYlpFIIvMNhh3bY4blUd373I/l9xStegU9/+tPpf//Tf/pP8bu/+7t429vehre+9a345Cc/iTe84Q3TbLpAgT1BKnjlsLTiXSS/BwtNQ9bnIBaj7Y6anTh3vnpp0nEihn6eZ2Z+nauYf7uyUEIiZNr53WpEUErhm4+v4z/8ty/iz7/4tH6j2j/asxWkKHLf/Yel4PXSnq/UqifpsSazhQ2b/FbdbHLa/feJ8mwugpvqDBQ6ca1O0Vy5qd4NSk9VKapef/JrO781s33b+aVUW99sNUM0O/22TvMEKY3wzoBuKoHWUdit02rR4SoVgXresgOP6sRvfUT31IJSCiH6O82U6Gux1UnQ7HD4uyQLvbTrYd65iVSIRySb91/sFk5vrlO84nj//KxN9An0zK9lS0Q99Y62yaAZQc4aq+J27wlKyEzYFs123kt2GOa56+i7DM++aQW+x3KjZ9SIUWbXlcWafo41WvH8Jr9S6aIikHplK0M7HzWXXWB28FwGLuTEnd+pzs473/lOfN/3fR+SJIHrunjrW9+KdruNz3zmM6CU4kd/9Efxjne8Y5pNFyiwJ7DJr+dSbabOaG7mtMD+I9v5tXYYwwRYwigvsJOd+bX/Pay6nnZ+CZmI5nfYUCm5IASolfVDIOESYSzwp/eeBgDcff/TeM2LrwOZ0QzaMEipujO/jILg6p21nme4TK9vvbTncbp1oyCkRJi5fjpcK0g3TSJQySS/ty8y/PHpBC8+wnByClujQThSonjXi0qoudN5dh8rU/zE8wKEQuHZSwx/Z5KhZobqbL2Ab64zfGVdYNskQ57DEMZadTdJ5pv+LIyy96B63/JCaaIC2Jmm/q1LPkHNI1j0CS51FLZihaPl0Z8lMOsNoahkdoYammvCJaold2AizqXCf38khk+B25fyz+vNSOFIKf+ZSCj8m/va6HDgB2/y8N0n+wPibxlPZwLg/3iWj69d7j5LTlUozrRkd+aXarErbX3Vf8As5bns5Ec77D3Q5joREsIINo06UCMQJyKl1+6W/Co1v51fQLOBAp+BtbvFb2YKpFn2l+387rTiufXXlkqlhXhbZLTMwiK+3B+UAxdCTt75nTj5VUqBMYZbb70Vrqu/jBCCH/3RH8WP/uiPTrq5AgX2BVnrFS4kqmW3CMgPGFkBKs5Hd365yKuW9nZ+o1gMF7x6Bqg9A3aGmoJSinKgKdDbzShnI2VnAPdyfkoplSbXjFFQWsz8HgQcRweUgdft/FJKhtoUjQshFNoZcSiugJ/4mzZesGqS7Qz984Y6wy9+RxklZ7bXwLHyld3Hty52A9NBtGfb5bx5QSe/W7FOJF2HYqvJQQnJjV7MI7QNy+CRA4LJ2BgPb+s15MaaPu4Lnk5+e1Wxh8F1mOmI5WnPUkpIOpx+/dV1gfsvDT7OOvnN/+3RbYGOefu9l3hf8iuVSlWrf+r5AY6WKBYzc+k31HTy20x0Iu0SAiE0U2YrY+OlRQMV2km/2BWgk2FAi6jZ3yzVdMmvUnqutGluulHCPlGivZvnfbwn8By4Dk1FoQghcB2WszC0nVQ78zuPQnPSWHcB3U4v5xLOFOrDBaaDa5TCT6xWJvrcxGcnSRK89KUvxcc+9rFJP1qgwIHBBiqey8C5RHlOaUHPJLAs7XlE8iul6k9+o97Or0htM3qRCl5dxWrPQMbbVUgsmMBhqxnlCgVbzaiPXjZrSKUyM78EIAXt+SDgGrsj64HY6iRgM0h+pVJoDchHvnxZX2eVnqW1PGWHdr9gadpZwSsr7nSDSfYSqZV7CSE4slRGJXARX+Fx3GsIKSGhQGaw5tnO742GMr7oG0uoaLxjsFD1UgVfC0aRChkNW5eztlSP9ghsffKJGFEP28d2dQHgbFPmXldK4d/e10m7tZaJsOR3v/tImabCVeuhMmrVBJWSi4ud7r4oaNq3Tf4XeoTXUtoz17RndQWCTWtbHZy91ETLjC2Monde2mij5Dvw57zreHylguMrFZSD7m9xjRipRc3M0DbaiVFZn0/as2UV2hlfIRUYo3NfgLhaYHVFnn3jykRz1hOfHc/zsLq6Cs+bTFa6QIGDRMTtzK8WvNptvqjA3oPSrvpywiV2WoN9aaXSapvZDsbAzu+QZ2OSdiHJVa3w7TlaxI1zibqhjH3hwYs5D+VvPHYZhAB8FmavQyAzdjCMUlBc3cd9XuEYBdXABMKhuUeuVK1YyK7C7SBkrYgOEkLKHOthGHo7v5HoJvdHyzTt4qWKzyDpvOo8UjEtpIJWWh9zrncULpvE73jZdn71//ZaBA0DMf8vC0poOiIxTH/jcibhvNDW32UZvU83JT77dJJ7/7c2MywXAE9lVKE3IpXub9kBfPPsySa/Sx7BiukEW+pzteSh7Lu42M7/1maihie/VvDKXFNXola804qx04rQMWMLw+idUiq4LsVC1U9F7uYVy/UAz75xJTfmpFV7u8fICkjttGL9zJrDe02p7kid71nas7zqC+3zBJ386mNdmqCpNVVp4q677sIf/MEfII7nW/ChQAGLKO4KXoGgELuaA+gZXNNZERIX19sDH3DWE5AOmPldMA/ITsyHBhc8ozzMrmLBK2bm2LlU6XF54ImN3Hs+/Xensb4TQu5hFV0KmVbpGSMgdD49J692uC6D6+jur60bRbG48s6vlGibHOOWBYrvuz4fcNQmtB+aFbgQqcUWAGw1QzTaMeQuhR67v7bzaynPAdOqvYvm9e24ux1K6dx6j1oosx4mUuFSR16RwvtOkk/y7P9uR9NvkxCCKBGIEtG3Liul8IdPxPjS5f7ihe3GA8C9GfGqnVjiXFuBALjV2jE1up/fCLv7+uPPC9J/L/gERwKCZZ/g2cssteRaD/O/7UI7fx21EoVN0/nOUqeBbvIbS0CgmwBPAyUVtppxWsQc1t3iQmuZnDpaQ3AIxZZch+aOUT3t/MZQAKJ4/sYMuJDpSJ09L1JqbZl5ZrtcTfDcLuNtEkx1h9x22224++678YY3vAF33XUXTp48iSAI+t73Pd/zPdNsvkCBmcN2ADwzH1AkvwcPRruK21IqNMMEcSL6zo2UClJJMGpmaoTEpU3tYbu8EGC7Feuu1rDkNzt/epU/kAKfodmO03kpi7/3olP4iy9qe7qvP3oZN12zsGf7kLWAYUSreF7tx30ewShB4DlotGKUjA1WFHOIK0xOueh2fhc8gldd4+KPT3c7cL1dsP3CpvFBPbJYhoKmm/qeg0Y7wcIIG51qT+fXUp6XTUdwwac41xb5mU8KSD7anu2gIZUCCPA/Ho1x70WO77/RxWtPTc7Y45lOvy0UpLTnWOFcS+JYmYBNcY9bW7ZeXOoofPZMMvC1lxx18Mi2brxkv/JbW/q8napS3LLA8Mi2zCWwNlF91iLFqWo3gWSE4P/zohKk0t3gbvKbD6aztGdAXy+2UJLtHgNA4Ji5YGhRrLLqemBPiogL1MsuYm47jPnkVwgJxijOXm5iuR5gqTbaMmpe4bksl/xmVeoZIQh7pbbnADr5tbRnvb9SKbhFfLlvcMx4z6QsnKmS35/+6Z9O//2BD3xg4HsIIXjwwQen2XyBAjNH1+qI5iT2CxwcsrTnsu+Ac11FLffU0bhQELLrV/noma30NRvUhhEfWlm3NE+HXt1qzwBQ8hxwodLAweKGEwu485YQX3v0cp9VzawRZSjplOl534L2fDAo+Q42d0JUAhftkGtVdOlCKIVpBz8S3u38Vl2CoEfs58SUYlRSKbTDBJXARSfmaLZjrCwEYHT3PVVQcFjXJ1QImarKRgk3VMTB+1V3u11MpRTOmjnTo+Z3dDu/eXsnKa9cOXsvIY3lz70X9cn6gycSvOakO3FHyhYFKOkKOdlj8kRD4he+1MF3X+PgB2+ePOkaRsl+eGtworMSEHzHMQfbscIfn06wFSlwqeBQks773rbIUi/o7DnrJqr914GbWZ9sF/cvz3G88QYPnnlmXDSd37KjE9pmotKCyGJP8ksJQcUBmhxoC4KSmt5bPUkkpOza02VVhDsRx9pWGw6jqAQuamXv0KoM9z4j7DwwFwoKQJhM1vlN+HD3iFlBiMzMr287v6qY991H2PGeSWOaqZLfQuyqwGGDrc65LoNSuOqToMMAmu38Kv3Q6ES8TxhFSAkhu4JXT57fSV+77lgNX3l4DZ2ID138hKU9O1d/59d1KJTqT36X6z6uP17H1x69jMjYSu0VbDBAiQ4CXYcVFLADQsl3IKQygWQHnUhAKgdS4sqSXxOHVgfM956qThf4WbuyVpiAC4l6xUMUS5SD3fdUSi1OJJXCpc0WpAIWaz5OHqkijATCSKAUDGYgLAU6BYsl0Ey6c6LXm9+xYBKbbOfXerfu5fjAlUIqYKtnMu2Jhsz5HI+DRup53D1+y0H+HP/VOT5V8jsMTzUHr09vuskDIQT/4FoXn3k6QSL1eSk7XQr0bYsMiXkW7GSSX3v+lnZhJmSLN6cbErcuMrQShYZpRN9UZ/jGhkArwdDOL6CF3ppcz4+vYPqZXy5kjtLZm/weWSxjfbuDWs3Dc29ameo75gGMESBziDynm9TEiUCSyD7F8GGIEoEHHl/HTScXRrI+rhQJFwM7vw47nAWIwwhKdYwxqfr+2MnvL//yL+P1r389br/9drz0pS+deAcLFDhI2LkMWyW6mmc/DwsYpWnya+cQszN7Fta/1wZeT57Tye+b/t4taSAQRjxV1OytICfm845R7rya4TAKkLzwAyHAYtVPrRhsl3zQsZoFrBiZY9Q7nav8mM8zXEdfDxUjYRvGHFJ6U3ehhFSQQqJlPH1t8vtPbvbw6acS/Mhz/akLTJxLVMsONnYiUzShaHXGC2iEVQyWWqAIAGolV9t/MYJGO9Yq6AMCYZdq39rNSGEtlLhg6K0nq8M7v4ToLjOfY9qzEDJN2Cye2Jk8+bXzvvVM0lhzAZ8BWSbquInJODhvuqx3rjA8e4nh44/qLP6WBb3vhBAsGa/h9VDha+3ujtxUp+nns8nvZjy4S9uL2xa7scGFtk5+LeV50evSordimXbFFz2KTpQgjAUWqvoeqLgE6Ci0hb5WprnlhFTgvJv8ej0F3DDmOLFaAWME9Yp3qK38emMyQghKvoNmJ0GUaLaSGPN5st2MsNWM0OyMHnm4UrQ6PD2v3Zlftecd5wJ52HGvSTD2GfrN3/xNPPLII+l/b25u4o477sDnP//5ib6wQIGDgK3OOVRXr4uA/ODBKEkfElxII4DSX/GXUqUPmPOXW3jqYgMAcMOJeprQdWJhAoz+CMMGDo5z9SswMkYBhVznd7HqgzGa/q0TiT0V60lZFkx34goK2MHBcfT1YNVfOxE399OU4jtKQgJ9nd/vusbFe76jnJulnBRCKniOg4WKD8ehYJSlbI4402EZvF/K+IbrAtCxlTKOLpdBiB51CDyWm0XvxapJaC53ZJowLXrDO7+AXlfWtzoTB137BSEltnuS30udyRkf2c6vBSGkj97eHDyiOzEioXDadN/fcL2H7zzh4m23+/ipO4Ocn+6q6T6fb8tUjOrlxx14jKSJ+k6i0nVucwhFuReEEHzXCb1W2oKHpTwfL5P0mrf0eJcCVRdoRxy+x1JhJit61Ta03WnuOSEkRMbjNjvva/UxVhYCPP/WI7j12qWJtz9PYJSglwVfMs+shGsxu3G7e9uNCI12jJ3W3t2bSmmdEsB2H7v3w9UeZ8wbKoE7sYvBFUUlV6IeWKDAfiLJUl+vcsubwwJKSVotTYwxfBj1R1BSqfSZ+Pt/0S3ALdeDTELHoYCBdkc2cHAZO9SV8XHgMAIFpEUBADhiRGXssY65uCLrjd1glbjTzm/Bsjgw+C4DpaRbJDJd/2lnvqXUxShrBVRxZruOVssuluo+KiUn7VYDupOz0x5shQboxFnHzhSMASsLJa3sD63MTCmF6xAoDP7dqyWbSOXFvAAMVHsG9P201YzQmZBut1/gQqFhds3k8bjUnjz5tcWAeg9d+DuO5YmD//kbIX7/sQhrUyTYWfz2t7rn+UhJf+eLjji4eSFfWLmprn/U4zsC6+Y77d/qrqaySwW0zCNlywheDZr57UXvzLBNro+VaZr8PmwEtkpMJ22UEHguTZ83ZZv8cv2/04TL3NhpWYZBlvLcChN9v9SCq0LA0yaMOdEr3ya/Eu2I48yl5q7bkVJhYycEAcFWI9yzER8hVWo/FXj50Z4ivtxfTONrffjvmAIFxkCc2t1oVcqrPQk6LLCWDIkRqNEd3HyUIKVWLVVK4eJGG4BWLyaEoGzovWGsac8DO7/m3LNnwMyvw7Tsv+d2r++jSyUA3cApSbQy9l4lv3bEwHUYpEJBATtAeMbuyHaM2uGVdX6lMY9tG9pzZUaevsooE7sOxepiCdceraHku6CEQEi9NriMDbUt4lzC91y4LkWllFc0Xqh48F09YjEsED5iOr+P7xiGEAFs7m09bRtJnuZcK2t66zz6jwLaksomfpYu3KtYbPFUQ+DuM8nAooil9vb6N7/8uIN3v6SEZy/pbZ9pSfzlOY7//I1w6n2OhcJX1/U5eNERBmdEEnF9zXxvU6b+vcsmsWWUoGImP3YShSijUD5oPrcXtvBhE/+LHf2/xzPJr0XWh55Rml4jVhzM3ivTWKvHibaNs6M/fs+872LVv2oSLWq8cbPPpeyoDiMUm41wJIMDsCwRiaWajygW+Mbj63si8CiMRgnQnfcFkBZCCuwfLMNpEhRRSYGrHlKqdJZUdwGufvrrYUG288sYBR+gRGz/u9GOIaQCIcB3v+CU/rxRWBRCaVXMEbRnl179HX/fY3AZyz18T6xW9GsmcIqMcMhe0Z5zyuoF7flA4TrUqB5b2xAOKEzf+VUKSSaRqMzITjSMOVxG4TraH9P3HLiuntFf3w4ReAyMDVdXFlKhXnVx6mgVq4t5ufilWoBrj9W1HcaQ320ptI/v6LWi7pG0k1N1u53TXu9XRucz+VVKIeESDZN43bpIQYlO4Hs7s1IpfPAbIT75RIz7LvV3sW0C2OvfTAjBckDxlmflZyovh1pleho8sq3XjiWf4K23jZ7VtMJqa6HCpU5/d9rS1n/pyx38wROa/lpiyFGnh6HWY39lac/HSv3J75tv9aGUBKF6jVVSQUiZFobsOPI0BScu9DPNMtdsAdPS/Jdq/RajhxWMEjNLn7U70hWMdsRxdKmEZidBqzOaX6/dISQC38FOK8ZOM8bmzvQFmWEQQqJjmGpZ72WlCtrzfkM/N4BJMuCJHl1nz57FN7/5TQBAo6Hn7k6fPo16vT7w/c95znMm2XyBAnsClXl46AW2WJzmBbZiyrkAowRRLI2oRfc9thJ8/rLu+q4ultIgwHMZCNEPnE7MB1LLUp9fox55NcNzGBxHK2S+7mU3YLMR4c5bjujXzDHjQoLzvez8dmd+gcJT+yDhMF3s8w0TwHYqpqc96y6a/fQ4icQ4aEccy/UgpSoDWtynFDiIYoGS76IdJRBCoZfhJqXUnr6OkwbLWVBK4JLRdhiWXmuR9SomhOBoieJMS+JSR+JYZtaVUpIyHeYJQipI1Z3DXQ0obqpTPLot8eCmwJFS9zdc7ihYXbEHNgRedjx/DG0CWB/S5a97BMs+wUZmJvp8W6ad2Unwd0ax+Y6l3RXiBymNZ5Pf62v6nEkF/PV5vd2VYLy1yG67lehE3hY9jpVp2skFgB+8ycO3rTpIuAAlBAtVHzutCFEiUtqzPQfTFBu5kIDqrqmWwaEF3rpFrasB1BSns8+lrtcvT/UsbCw3DMIUDBgluO54HecvN/ekQCWkSr2Hc51fFG4i+w3XYRPHGRPdOR/4wAf6fH3f/e53973Pqv4VPr8F5gEKmZlfRgvrlTmC7UYmQmrKk9IzTtkIN050YHF+vQUAOLFSSV+jhCDwHHQinio+94KbLkQ2sL5aQSmB7zG02hzf9W0nc69l58UiLvbM69d2fh3jqe0Wye+BwjWUYaB7bqYtfAip0DbBvEuReqBeCZRSoIRgsRbkmBmE6M5WkggcWSrh7JpIRxiy4ELBYTRH9e8FIQSey4Z2jVZ7kqLe+dajZYIzLU0bfl7m75QSJFzsmXL6tLBjDVbtue4R3LHE0uT3ldd0E9wsFfor6wIX2hKPbQs8a5HhSIl2Ba9GWAR5PUvrhRHJ7+mGQCNReO5yPvz8y7MJvnJZX593LI23Vr/5Fg//49GuqFHWFes5ywz3XMh3speD8c6R7do2E4WLHQkFzXKouUDAtIdvIoEXHuna21Cqx01KgYutnQh1c1C2TfFgmuQ34fq7bfKbjq5wCXeXa/6wYZBfq00qs0JXu83wSqMKTVNxU7o3ya9QCHs8fq3qfOEmsr9wTOFkkjts7OT3F37hF6bYpcnx2GOP4ed//ufx5S9/GZVKBd///d+Pn/qpn4LneUM/c+nSJXzkIx/BPffcg6eeegq1Wg0veclL8NM//dM4efLk0M8VeGZASpnr/HoFDXNu4Gdoz5QSCNlNVi0i0xW+MCD5BTTlqBNxdGIxUvDKf4ac98B1sC36VS4d1q2sRyN8ka8U3ZlfTUUqquAHC9eh6dx1FHMQStAOE9BmjKVgMtpkwgU6hsY5C7ErISV2WjF8j6ES9Icj9YoHSgjKgQPfG+zlKKQEo9hVx8F3Gbabg9VfA4eg5iJNFldL+W0dK1EAApfa+XvGoRSJsaLx6PwU14RUkFKimZnXvWOJ4Y+eTPDwlkAiFVxKcKYp8MBGfobyPV/sAABOVSj+9QtLA62OevFPb/Hxq18PYZuia53BawuXCr/69RCRAP7ltxFcl0mQ77nQLUyMm/y+4oSbS36zRe3nLjP80C1eapMEdFW9d4NNfmOpZ4oB4ERFU/I9BvyrF5QgVbcgoKQChR6rqpU9bGyHGaE0vc1pCk628GuLVn7GHcFxCLyrqKDLGAUj+eQ3K9RnsZuqr5BaIDMd/SEYqRQ/LYSUqbijTdKTRMB1rq6ixGEAYzRlBoyLsZPfu+66a5p9mgjb29t461vfihtuuAG/+qu/iosXL+J973sfwjDEz/3czw393De/+U189rOfxZve9CY8//nPx+bmJn7t134N//gf/2P87//9v7G8vLzn+15gfhFmaGmUErjFwjQ3sMkvT5Nf2VfZjRMBSgk2zNzOymIp93rJd7DZiBAZG5depB6Jz5Dz7ntsYGJLiC78hLFIA/a9QGorxmhaeS9wcHBdms5dR8YSrNlOIJohllYHjywNQmKEZOwMY3kGjMt2mAAEpnPbH8g7jGKxpmc/y76Dje0OwpjnaIZKjTfSYGfQh2G1RNEwz4obaoOS337BKIcRdCKJOBED9/+gIKVCyHXyBujEdYUSLHgE27HCY9sSCx7BL365Owt5S53i0Z3u7zvTktiMZEqJHkZ7BoCbFhj+0ysquPtMgk8+EeNPn04QCoW/f8rFQkZd+bEdmXoDf2Vd5JLfC6aw8C+eG8CfoGB2tKT9fq+r9vvEfucJFxc7En9xVv+II6Xx1qIS04I4Et3kdznzO5Z7mAJSGTFNW1wnQN30a7YT/fokyW8YcTx1saGFnijpoz0nXOrC0ByxDa4UjBI4DkUUdxPVkumo2uSXkN3HDETGGhHQBardRLKmgRAq3df0vAgJ16F9NOgCewuHETh71fndD3z84x9Hq9XCBz/4QSwuLgIAhBB497vfjXe84x04duzYwM+96EUvwqc+9Sk4TvfnvPCFL8SrXvUqfPKTn8Tb3/72/dj9AnOKKFM1pOTqqpYedqQVU67n9qDynV8p9QPGYbSb/NaDgdsIByhFA93tzVNwupfwXDaUYue7DGEsEHO55zO/NhgslNUPFg5jaWIYc4nFqoeYC9QmSDCkVHj6YgNKqTR5Kc9A6VlIrcY8jnDPUt1Hox1juxnlgkup1FiK4pT1+4hmcX2V4omdwcnv0bL+YK9VEKUUEgoRF6juugf7ByFl2rH1GdJk8mSFYjsW2IwkzrTy9//LjjuougJfWe8mCl9c08/OktNVvx6F7Oz0X53j+KtzHO96YQknKvp4PrLV3faX1jjeeL2rE5rMmn+qOtl68ZZn+fjM0wnuunEwO/Bkpbu9Xnr7MBBCUHEJGonCGePnO8ofWCqVrnPMrHsBU127JUFQm2C5bbQTrG93NBWYEURJXvAq4RLV8nA25GGFwyg6shuv2Zlm22FllECI0YmsEDJ3nzNG9sSOTMiulkzJapcIiWrZvaqKEocBZIoi+1xFJZ/73Ofwspe9LE18AeB1r3sdpJS45557hn6uXq/nEl8AOH78OJaXl3Hp0qW92t0ChwR24bMm6kUnan6QrWRbiIwnRMwFhNAzPG3jqbdUz6uA2nmbMOaj1Z6fIbRnxsjQGN9Lj7fYn84vJSPtSgrsPbwM7RnQwXjJd/rGC0ah2YkRxgJCAjb/K8+A9qyUQq3sYam+e/LrMIYjS2UwRlP1fgBGBGuM5JeMpsV9z7UeVgOCWxcoFnu8YI+ajmGTaxGkLAgIOp358vrlIjPvmylSLJgEbitSON+T/J6oUPzw7T5+5Dk+XrCq14n7L+njfCSgY+lkHBmQXD6w2T1XlzKd8/VQpQm6FZQK2OSMgpvqDO98TpATIssim/weL49/zVbNWPRZm/yOoH0DSOc8HUa1t7kiqWr0jphMFTxKODoR1/RmRvtmfhVUKgZ1NcHvKdx2ac/WrWO8zm/2PmeUGsbLbIu9XMi085t1nQjcq++8HAZMyuybq7P0+OOP401velPub/V6HUeOHMHjjz8+0baeeOIJrK+v4+abbx76nte85jVDXzt//jyOHz+Odrs90fcWmD9s72hjdMehiOMYcRwV53VOQEyVN0o4wihEFEdotdtolwgubXbgMIJWO0SUdM3koXg6+xcnAq7parQ7MdrtDnyWfzimNGrJnxHnPYkjRHGMMOrvdKfHKoyxvdPCcnX23fB2x87YSfAkRhSFkOKZUXiYRyRxBCF4Kiaz0+qgLASiKEIURbt+XkqFc5caaDRjVAIH6yaBWfIU4mTwDO244JxDSj7WfgD4/7f33vFyVPX//2vOmbJ9b0u7CUlIgBBISEAQKYIm+gUEpQiSj0oRVFRARD8fPyifj1j4CPJRkWZBQZGPgij4QyxIsQuiSJNOCKSXm1u275Rzzu+PMzO7e3dvzU3u7r3n6QPhzs7unpnZOXPe7fWGQQQMKpAvlhGPSuvEcR1A6CN+BvMcuJ435JgtDfjPFbJN2OB9NABpU9ZvbsnZWFAVGSYaQ1+2gI6k3jRZDsViGVmbAdCQMBAeT8KfG/vKDFsKlXnSJECH4UEwDfskgR0FgSd3ItynwxrdtU7p9QbGtoILxzdye0q1UbsdeQfRJME2/3s6LcD1hm9lM1a6TIGDOjREKBDVXDju6AzgmD81BpkOccrC4xiM7TiIWxps25ZiY8xD2RNImQJZV4peFQulUT9/1m/pRyZXBLgJXSco2fLcE3CU7TIc2wFzbRSLzfF7myg4c1EolRH3a7MJ5Mkv2S7Kdhmu6yBfZMOex2yuAMetPP88T+pb5PKFCQ185AtFlP1WR5QIlO0yiuUyBDemxTqj2eDMhRAcw6b3VNFUxm82m23YNimdTiOTyYz6c4QQuPLKKzFz5kyceOKJ4x6P4zhKsXoK8Np2mS5LILB16xaYXi+yO+tbYij2PNu3yWtTKjtYv349+vMM1O3D2rVAT8ZFxCQYKDA885oUu7J02V4toGfARS4nP6O3P4OXX34FqVjFoBNChBGurZs3IcJ37qlDmzSyRYZtW8so5+oNW87kw3pnbx9eeqWMcmb4Xprjoae3DwBQKOSxefNmJLS+Kd9iqpnpy3nYusOGTmWa8esbNiE6MAC3VAYh5REjeh4T2Nxro+Rw5EyCbfkkABMRN4eenqENIs6BksMRNQkaiZ+Gr2t55PpHvyjN5Tz05z0kgmhsiUPneZTzwztyyg7HQL8Du9B4PCORJElkoGPDzgxi5YqB5nkCHhcwebZpsop2ZFzsyBkA4jC5jZ4eeU9SxwQQx46cja1lHYCGk2YWMMv0MNBbMYZnCQ0a0hD+QjLGi+jpGV2v1AMSMWy1dRySsvFwbwybsw7Wb+vHDzclMeDJa2QRAZtr4blcP2ABiCGhOejp6Z/AMyF5R7v8984xTP86jwOopBZ7hX70DJFymy9x8LIOVpZj7+93YHsclkgBMLAjZ8N4fT0cPjDi9zoex9rNJeRKDD06QTJGMZCVz79cth+vvVZErsSRJP3oiUytUp7erIstPTZKWb/FkS1/k2Wb4fXXX0fJESAaYLo9Q85bG3ts9OY9lLLy3Dguh8sEYrwXxgS1ZgOADT028kV5T2QH+rB+fQH9OQ/UsVDOqPXlnmZbvwPPY3VZwEPRVMbvRHHDDTfgb3/7G773ve8hFosNud/DDz885GurV6+GEAJLly7dHUNU7EHKpAfATkQjBubM6ca+e7djVsfQvwvFnsNIZoA/7AQTGhYsWIBofwnzZiWQK7goayV0piOwcja2PvEyAODg/WdhwYI5AGR6UzxtY0tmG7DdhmFFsXiffdCVrqRQytYomwEA++yzN/ab37anD3GPk8k7KGk96ExH6mqPUq+sxbb+DFKpNOZ0z8LSfbsm/PujTz0NoIT2dBrz58/GgfvPUK3FJpGegRJs2oeoVYDtOujomoX23Da4kRjmzZs5Yn1ayfZQ5FmkhYDHOLI9clG5cEYKM9JDG3sl24PlMkRM2lAAJkgbnD8vHbY8Gw2xbBnajgLSCROAgJl3MW9OEqn48DWQJduDo2URjejjcsZ0DXjYVBbgkRRmzKiMl3OBQtnFrNmphn2GJwNHy0DLSUOtKxHBjBlSIX+uzoEeho22ASZkxPfYvdMVZVyfGQCWZDy8OCAdh/t0JTCjc3TiaOfLtuLYkDfxcC/DADPwsteBgarSloVJgpcyAvDPZTnPAHB0pytjnWw6cgyoio7P7eqo6wcdYOQddHfF0OWLMWpmHn15G51lgleLAsyKYd68eVi6dN6I37utr4gdpV7s1x5F2WFIxAw8/MzzAFzMnzcbc2clUCx7OGC/GVMu9bkvW4Zr9GJGWwSapslyqL/0QQCY070XPMYhBLBkyYwhsyxEpA/RrI0OvzzKcRkKJQ/77Ns1ofena/QCJAvAw7y5s7FgbgrRvhL2X9SBme3REd+vmFhSPQVQOvrnSFPdOalUCrlcrm57JpNBOp0e1WfcdddduOmmm/A///M/OOKII3ZpPJqmDWs8K1oDrskbwjQoTNNEPBZT17VJmNHpe3YdBtO0EIsIcOjgGodhmICmo1AuoewwaADe+ob5Yb9e22WIRYFYVC56XQZErEjNta0Wukgmpsd1Z9ARjURgGFZdnXPU8h/+GgGhBqLR6IQbptyPFlmmgXgsini8ORaz05WEq8E084haBgbyDjgoTMOA0HUYpgF9hAWDyzQQSpGOmbBdhn4/BbM7YQ5bZ+V4QEI3wIWAach71HY95Isu2pMWGGeIRiji0ciY0oVjEUDXbZiGCcY5LBOIxyOwrBEWtkSHaZZAKQ1FD4tlF7bL0Ja0MHSlvKQzCgAusi4Jjyeg5ApQasCyJj6TYqxwLkAoRZELABxtERqOtyvGADAEZZNz4gQRs/GY37YXxYsDMrK1MD38tW7E3KQAUETOBTYVa8/tnDjFSxkPeSbHtrUk2yt1J3SYRnM4EFKWA6n3LGmPmjCHEHkzdA7LMsPrH497yJYY0hECwEVR6CDUGNXzh2Y9xKIRJOIxJPyps6J3EYeAjlTCRHtbcspl1HDNQDxaAKUmTIMiYknhRI8JcFDEopZUVo9Eh3SYUT2PqCXXAoC8NmW3DMOMIBabmPtTCAEQHa7f2yudiMI0LZgWQzoZRyw2thZyil0nHudjWss0R46Oz6JFi+pqe3O5HHp6erBo0aIR3//ggw/i85//PD7+8Y/j9NNP313DVLQYtt/vwdSp6jvaZKT9aI0Qsg1L0NaBc4HOdAT5oouNO2TN9oI5qdDwBeQij5JKixTP43WCV9UiI9OlxRUlGgjVwHm9MEiwYPCYgMt2T7sjxxcBoUSDru61SUensg1QYLzYLgM0DYLL1OOR4FxAQArHuBoFE34N7DDqt4BcIBoGqRHWKpY9RC0djisF1yLm2OtkdaqBaBq4EHBcBl0noxS8koI51cI3JduFoZNR9QFtNytiUXUI7La+2WOFcQ4ugHwgeFUl1JQ2a89T9xAiUQCwpI3i/KUW3ruvOeoWQdVEdQ2LU/J9z1b1Ej5/qVUlvMXhMBGqbO+bbp403niVoUswsto1qcqlD541QS/sEtPgcT4q0aVS2asxaotlF7mivJjtSWn8pRPWlDN8ASlKqVNS81yq7vVLNIAJgfVbMujPNk7DZ1zUZLNQSsD9rBUAKJTcXe77K/toV1odRUwdnsdhUAJjmnSVaDb0MdayNNVq8JhjjsEjjzyCbDYbbrv//vtBCMFRRx017Hsfe+wxfPKTn8QZZ5yBCy+8cHcPVdFC2L5MfhAFG5zipZg8TEMPr0vJ9kCIXNQKIaBTgo50JHzALJhdm3bHmOwNHAl6BfspUdV4fqqdhumj8h0YO40W49WtMhjjNSrbE4Xjf2bQ8kMxuRi67PMbXPuyyyG7iolRLcaZQKiemvENv5SpgQ4xj2byNnb0F8C4XHiKQRLLpklQchgKZS9UHx8Lsv2LVCzPFV3Eo0aNU2woCCEgAETVfUEIQSyij6oVSrsvwtPXyPhFrUr9ZMK5AOcceV+cKVllxCUMoLrssTs+/Jy4skvHEbPHH4l97761kbZLDopgZZeONt8IzzgCWwocwh9n5yhbEe0u8mUHeV+wL1F13uKGNmJUqfr1QPk57hvMRa6B85EdJPmig1zRCftyZwsOrvz+3wEAXekIYhEDHhehQTjVMKicq3ZmShjISwG7oN1RsezJ1mJcoD9vY8P2+ixRIQRcj9VdK81voSiEwPOv9eL1rdm6944Fj3F4Hg/7B1smBeNyzTJduko0G2MNajXVVVqzZg3i8TguvPBC/OUvf8Hdd9+Na665BmvWrKnp8XvOOefg7W9/e/j3q6++igsvvBALFy7EySefjKeeeir8Z8OGDZNxKIomouwbT4YujQLVg6150DQtfJAXyy4oJWBMgPPKa4WS9Hon47WLMC6kh7e6XdLgxbzre3sJ0aaN02M449eqipJ7TGD91voFxK7i+G1odELCRZxi8jB0WrMosx0GDdLJNFQ/6Gq4qBh1A46f5jdM2xePc8QiBmzXA/GTiV2PYVtfATrVYFAKxjlScXNMtb4BhGjQQFC2GVJxY9T1dTIjgiC4LQRkCDti6hDB34Mo2i5KvqJrux+t3FbkyDj1hu5obN/d1V6sGte/t/O+PZ+sulaaptVEgkcyfneVmTGCZNW0vZffwzf4/Qw4Ahvy8pyMtb/v7sC2Pdgug4AIDVeg0vZoKDQNqF5760SDplWixUWugTEx4vV/aUM/SrYXOmrXbhwIX+tMR8PvmqoGFiEaYpaOme0xFIouimUX7QnpQOnPlqVznAu4Lq90caiCcQEhUOd0FZp0ludL8jPzxV1TqWdMhL2HATmHBM541dpvchhrcKOp3EfpdBq33XYbvvSlL+HCCy9EPB7H6aefjksvvbRmP855TaPrp59+GrlcDrlcDv/2b/9Ws++pp56Kq6++eo+MX9GcBN45Q5e9ClU0qnkgmmxflC3IyG9nWoPtyPTl4DIFKV/JWG2dHeeAodcav4MNvmCxMZ1S3QnRYOo0rBOrJjhXtsv8dDoHQogJrft1/YJCQrUxpyIpJh5pcGph5LfkMBANo097rkpbDlJ+24ZIeWZc9iU1DQrbYYhHdRTLFPmSGxq7nekIXMaQiJpoS4y9Bk86MAHHZmhLWZU69lFQneLMuQDVNEQsKYDFOQcltcZ4yVd1jlg62v3evw4H/uuxEj53aDRMBybayH1c+7JlDOTKWDgnvVsdsB6TKZmNIr+ATEeGfx13t/ELyPTpx3v8CJk/Dwe/n4wt8GpWvrYwuefnisDhoUGDgAChRKbUc1ET+R18Dgd/hhCAVpNqK53sUf/nVGTSicSHifwyXwAum3ew16wkAKA/X0ntnTcrEXzhlHYq7reg3U/9zmBLTyHsAd6XLftOXQ6XaQ37lDMuwJiAPii9H0I+81jORqHsIREdXhxvJDzGUfSzRSjRYOgExbKAadKmaXc23aBEOlpHW3zSVMYvACxevBg/+MEPht3n9ttvr/n7tNNOw2mnnbYbR6VoZQIPnU5JWPelaA40TQsjMQ/+fQM++K5lfs2aCBcTYRpatD7ya5kkVJJ1vfpG9kHa83SK/AKyTipbqPduB+fKdhm62mJwPFl7OZq00dESpFLrhEwrp0OzomkaIqYeZljkSy40y0+PHUXkt3qPIPLbNkTklzEh64t1iqilIx410J8tI1tk6ExHMG9mEoRo2Nsaf09c4mfvMC7GHAGzDIps3gHjDIzJz7IMCqoRMAZUD4kLAUplDaLrcsQHfdezfQxvnesbv2TkqG4276BUlvebSXZfXaDrMTgcoahVYpDh1lOqjHPwa7uDd+1tggkHq+dV5u8g8utw4AnfMN47teeNhmzegcsYOtPR0BlCicw+qq75TQ6T6SC4ANFqny+ESCM6Ehq/GhhHQ4MtoOQwOC7DnK54uEbpy0jjVwPw5hVzw/t1KpfwREw9fE4VbQ9J/7nf658L1+PgXDrN+aD6XsY4uOCgpNa00TQNA7nK+x2PgXEx7kAI5yIslQjGyrkYlfaAYvegUyLTIkbxTAOaLO1ZodgdBIJXQeRXGb/NxZxOqYC5aUcelGh+7a4IFxM5P0VpcOSXMQ7L0BH32xe4jGOwYz1YbFAycs3WVCJi0oaL8TDy6zAYOtktdb+un/ZMqaa84E1CNGKEi7RcyZOLBGDYSFQAYxUVzaDmdyixKy7kgnJmZxRzuuKIRQwYBgUlGuJRI5x7d+V3oWlSSE3TMObFpq4TMM7Rm7GRLdjQqcwcIQR1AnEyii0NedeT5+D/7VUx4DbkKtlnRBteNItzKc7FOIe3m2uD80UHJS7Ps0kq0daAt/lG6L7DtKkaDgHRUExvKNotgvOWRrAgWTH4TarVCUgtSOx5oSCPMURMHb0DJTAmDSlDJ3AZr3EMmMM48QQENIKa3tGUoC7yyxhrmKobYDsePMZrorq9vqjTmW9fAtOgMqo5TepK21MRtCctxH3jt88/F8moGZb1DK6zD1L+69KehUBf1sb2vhJilg7X43B3QfSKVYldRS15kaWqvRK7miwMg46g11/L1L+DFNMex62K/BKV9txsnPTmvcP/LtoeHP8BBsgIpeOHMJKD+nhyIR0aCb8W2PPqDbnQECME0ykD1xpCECWosQyUtUeKRowHNxS8ItMq2t7MWAZBzA9D5f1UXmC0xq8IFxUDtry2Q0V+gzr8qKmH6YqG7s+7E+gI0XUqo21jzCzQKYEQAlGLwuMClqmHNfKDTwXzOKgviBVoB7xzoYmPLZOp2q/nKnMNJRURuUa4TEabuBA1aeQTjeMyFMsMLuS1bhSxXDXPwPlLLVxw4NjbsRRtFzv6i+jNlkeVNTAc1WbCkbN1xPZAFLoaAQFCCCIWhWFQWaNONEQs6eywqIaEP40e0D60UcO5THuvVnumRP6mLCL875LlPMMJXuWLLoSoFeQMop2dfu96j3FQqk2bCGMiZiLhO717s2UIIdCeiqAjFYHrcWzZWajZ32M8nIOq6WqLgmgaOlMRdLVFZY/xXTB+gx7lQEWQi3Ex5nZgiomD+nX2o0VdKcWUJxC80nVSl56kmHziERPphHzA7RwoIRk1wxZIgTCFqZM6cRzuK0Kn/Yejx0Ro7AYEhh2ZZpFfy6BSxGfQAjVQxi47nl/bxidcpTYwFAyl9tw06JQg5mdI5Ep+LbiGURkwHuOh4yhMe7YaLx04F35UtnLdIyZFMmoiOg5l56EwAkemNrYlTCJqIF0VTQrmlKAdSjWev5iNRvSa+2heXL5nZ1mg3w7KKsiwar7FshcK8u2q0TgcMvLFUfKnwUZpzRbVsLJLr4sIj4ZS2UV7IoKopYclJeOlWjPszH1GX4NZst2wFGZXYIzD0DV0pWOImhSOx2VLI0sPa4EvPiiK85daWNk1dIVgYGxVT3UyO0Gqiwf2kN1Ak6Ka3mypJnJoO14o9tjpO5JslyFi6dMmwmjqNFwb2A4LdSwMnSBbcNA7UKrZ3/U4IFD3rNcpQVdbNKzvZ3xk8bHh4FyExnNQTsK5ivxONi3b51ehGA8jefCCdDSdEmiq5rfpIBrQnpQP950DJbQlLaTiMrqS98WuErH6xVFwLeNV4hWDW5YEC7SxegVbnYhJpbiPf/we4yg7Hqyqml9CNAjIyN5EEtb8+mUGismHUoJ4JEh7lhEmiFFGfjkH0WTENBS88iOKtuvVpPsKIcI2LwEdqSgWdKfC395EYOgE+jiyOUyDYlF3G5IxUzrU/JRFQyd1jqJgMRsxdb/GWP6uEwbgvw2f+3sJLw0wUAowwbGjv1j3nUIIZPK273SV2Ra7C8Y5OAQK/iUZTqhpPBBCkIgZMHUSqrqPlzV+G6QTFxhjckjnik5DZf+xIvvBEiRiOiw/FZb4Ym1BoXt3nAxr+AJy/iQa6n73piHb8gR1v7LOtPHF9xhH2WY1xlNfVrb6iUX0MLpYdjx0piLTZg0TtGlL+c7wIBKuaRq60pG630Hw7Hlm7U489PcNDR1NmqaFrY/GS3Xac6Qqy2o6pKM3M2QM6zx1pRQtTV+2jBde6x22btH202Z1qvkG8PR4cLQKlBC0J+VCaGemtnF9pd63saIrpRqikcrDxx5k/AZRSKkEOH2uezRiIBk1UPI95Tv6i+gZKMEyKu1uhBCAQFhjPRFwzkOPukHItFmkNTs61cLIr8cEyhx+5Hf493EuZL0rAcqsEq0Lan6zBQcDeRv5kuPXgtaL8QSiUhMJIRpMY3yttAjRkIiZaEtaiPtK0ToldcrXUlCLwjJljWXwu9Y0DfGqZrl/2eqCEALbYcgXnLrUZ9thyBedqgjR7rN+GZP3dM6P0E+koFUQDU3GTaQSJoplt2F7qNFy2EwdN7w5juPnjz7qK1CpeR0ucue4LGxRNRRlm0EnUuAqSCOmRAvLo4YyVAtlF5mCHf7NhQhT+6uxTB2syvi1XT6ko9FxGVyP1RhP/b5AU+AYBqSWz1Tt8dsI3S+d6fAj373ZUs1rbpVmhRDCdz4J3PngS/jdPzfipfX9DT83aH00XgJnMgBEq5x6BlWR38lEKm+P7hoo41fR0uSLDoplD7ZT39YlwPZrfilV6rPNCCFaTeS3mlxp6Mgv/PooQyfhgrvkDE57rtSfTiefByUa0gkLjsdgO55chJl6aCzItC+5EPMYx/PretGbKQ33kaPC8UQotkjp9Iq2NzPSiNNDIzTjaiDQRlwAeoyDMancHUR9o7pMnQ0W/ZZB4TKObN6RpQj67r/o8YiBtqQFyxifIRC1dCya2xZGbQanPYc9gC0dlMj5pdpwqW4RVPQENGhIxU14DdIps0UHrsth+I6nic60qCY4hlzQ5mgYleKxEqQJG5QgEbUQi+i7ZECMdwy6TqBTLXRsDoZzjkzBRsn2hnQ0lGzX/62SMEUZQPjZ1O8n24hi2a35XI+Jhu22gkyzSuSX15XlBNgug+vx0AjvzZSwcXseANCWrLQD0zRMq9RaXZe10zP8Xt4vvt5XeY3WCjb252wUSi629layL9ZtzjT+YDF0icJocFwWZlVFLRrWYqua38lntKVW6kopWhqPcRRK7rCpz45vEBmUqL6jTQglGtJJadz2DDZ+CyNEfv2FaeAxH5yK51VFfqdbFNL0W0Hs8OuodaqF5xOQNWUCMlU8U3CwpSe/y99Z7YSi/sJFMfmY/qI+aBeW9aQ67VAGRIDtMrhMRqQyg9oceUz29E3GDaTjZmh4TWTbrKGIWDrmdCUm7Pc1+GNkz18NliGNI8ukNZHAExcYSPnnoadUaT8jFWgri2qPMfRny4Ame8kSTRtWFXpXCQy2rH+tUhMY+XU9Dp3IuTZqUVBCJlwsbzRjMClB1DJQtr2G0dmi7SEVNxGx9NBAGYztcqQTJuZ0yd65miZ/A4bf2oqSxo4h4RvMRKs4S4QQoYp+NZRoEAKI+D8ur6pOdDCe7zQkREOu6OD6u57CH5/cBABhL2yP8bCn7HQhcGwvX9wFAHhpQ3/4G5edISrOpu19RfRn7RoH+isbG0d+AQzpiBgNLuPhfRy19HAunE6OiVZn+txFiilJoeTCcVkoatUIp6rucyr3x2tVCNHCGt9M3q5JwQ161Qav16DJBXy18WsPjvzW1PxOL0MsULY1dYI5M2TbGcuvBQakEBwlWs09tKvpz0GWBQBQbfqd82ZF9xeRMd/4zXny2ngjLAA9j0P4AjIDfs5zIHbFmGwFtGB2Cl1t0fA9rbg4H+wYC6LdwfPC1ElNre68BMVnD5HH3G8LOH6bHC5qI79lW9ZyBjWLlGphuuTuwPPbUgWR34lMe7ZdjkTc9DOoZMr57oxiVxMYuR7jsCwdlkmhaWjYy9xlHKm4iailD2ngCCHQloyEKcTUT3XWq4+twaF5nMOgWtgaK8gQaPSbD1J2LRpk2Iiwc0H9mCvjfG5dbRlXYPxyvy9tK95f4yVIQZ/ZFpV15i4PHeRBtkZwrhyXoS1pYVtV5HdHfwk//u2LdbW/OiVDXovR4LgsNH4jfr24TgnMaXRtWh11pRQtixACxbIHj4nh056dSt/R6fTgaBWqxXhcj9eIVmX92qrU4DZHXLZfkQsWLXzoDPasV0d+p5sZRonmK9ZSdHfFsXd3Ch2paKj4XLI9GJTInoeMo1h2w16K46Vk+1kWfg2cUlZvDgIHUXCfZTyZCeF6fFjRq2pDLkh7TvsRT8fliEelMWToFIYu6+9bsSZx8O/U4zKNMUyHpfWCWHFDQ8w/1J6yTH2W6ZSVesKy44JxHoohUaLBG0H1d7zYjodc0QUlQN6Z+LRnIQQSVeKC8YgxYubARFC0XfTnynBcBo8JJKIGElEDbclIY+VsIVODY5beMDIthDRYqw0VnWgwKA0F1EyDNkyZlr2AZTYA59I5ZPi9oAej67LMKhBGdz0us20ajNl2WFg9/crGgZrX0n7aM+MCRJteOgqUaNB1AgGge4aM0m/akavs4GtWuJ7MADR1gq1++6Pgln52XW9d+jMh2q61OvJ4GHCJWjoclyHpO4YUrYG6UoqWJegBa+hk+LTnql6v4xFIUexeNC1oxSJXktXe/EwY+a01fvMlJ0wxopTA8P97cEphdc/Z6WaHBcanTmVdZmc6ipkdsUrLm6IDQydhf9JMwalLOx8rgaMp8NhPt3PezFgGDa/9T7focLjsbcvF0AaM6/Ewep8ZpPTMhQgdKaYfWY4Y+h5Je55otLrIL4dl0PDYh8oYmhmV23cUK+cwk7fx+tYsPMaQ8eugAyghNcbxRNKfs5HJ24haOrJufdrzrrRY4pyHc0mAZVIICDDOajI+Jhrb8ZCIGvA4B/xnRSJmhr1bq0W3gkisThs/6wUEirYnha6qjsUwSJjiDsj050aXKEhvDaL8+aIrHUsN0l2lmFal16/LOFwmGhrkpbIX1vvWGHcA2vxWP4yLGofMdMGgUjV7pl/325+riI0JSJ2QZ9b2yCi/Bgzk5etnn7A03G9bb20/YErGX37AGPcDLhXj1/V43RpF0dxMr7tIMaWwHVmPFjHpsCksYesVSqbdg6MVIJoGaEA6TH2uGL+BIZwe9GApOTKVMBW3YFSlGw1Oe65We55uUUjqL74MnYQLPan667e8KbowDQrbYWBcptcVy8MrpI5EkNIZqKqrmt/mwTRIaKwCwC+3SKNmuNRV22XQqYayJ7A2I++tQOkZqBiFlBLM7IhjZke04ec0O8HvNDCkpIjRoBYmWn3f7Fkxefxbq4xfIQRKtotM3kHJdmuipUFLpInurQ3IuU/edwRF3xYNIr/5koOBXBnFERSQh4IJAUoBQx907QUwkHeQL+2a8nMjBIRvVGt+inXgyNTCfw8WpuJcgPoiiKSBvofrcpRt118LVI7FMnTM6Igh6QsrNmp9BSCMPBPNz4rQpLJ+o3mO+rXDQeTX8Z2Mja697TJQKut9c8Xaa1Sd9qxpoxf0mSqYBgUXIrw21boVRJPZTdt6CyiWvTAaa+gESxZ04A37zwSAmlRoYNcyMBgXNX1+gzl1ohXtFbsXZQkoWhbbkWlQpkGH9eIFrxn69BM9agUIkemCKd/DHaQ62y4LjdlUolLzK4R8+ASCN4RoYQ/RwX3/PC8Qx5CL1+mE7qubVy/iCdEQ96N/eT/y63gM7UnpRCjZbJcEeUJxOV0DUT21mwpDp5jVEQv/7nVkiu5QokVCCDh+P+hbXihjW6mS9hxE2KrV8ztSkTCy3GpUG1JBWmx1CzVDJzCoJqOPVcxPyCXUKwPyd080DbbjheUbLpMq6wGE+KJYE1wrK4RcjFsGDet9CRCmZdt+PaQ7zjpH7vfErb6fg97pjEnV74lu4dSfLfslMLJ3dMGPjgaZBZQELYkq59JxWahATgmkw6LKKPcYRzxmorMtWpOhQIiGznQ0zCayTArSIDoofIVzSmW2mWXKkpKhoJSEkV/HfzYNLjPgXKDseNApwY6+ipEmuyBYiPt1+lJdnU47HQVZby+Q9B3gQftDAKFmRTxiYHZnPGztFzzj9t2rHQCwc1AnA0qlWNt4RK88xsGECMuzIqYOgdbUOpjOtF5xjkLhY7ssrPv0GPcf0LUPBl7V0kWndNp5TVuBICIbpA0Fqc79fv1p1NJrvKoeEzAoqTHqAu+r4zJwAQRrcq8qWjDdIr9ywU5rFChlymCQ9uxC0zR0+4qnjAvsHCiiUHbHrVpZ8bzLRdp0W6g1M4ZOsNfsJFYuasdT6/qhQS6oh4pCcj/CIQTw4kBln7SphRG2qVJGohMiU5KZACcCBq3tTazrFDolfo1nZfu+afnfGwvSsDEN4t9XFcdbNUFd8ESrJHuMh+1WcnZF7Iposl9tkPXkMilqN9b7UtabIqxdBhBGTzmXqbiuJ0AnKPMzX5KOuUTMRKHkwjIoLIOgIx0J5/ogrbjamHQ9jnTS8qOuUnAqEIqSx8ERj1mY2R5r+L0BiaiJRNRAyfbCuTBw+FgGDbUSOlLDp/kbOkFQdm27HJzXt9hhXEYgDUrClN5992rDO47c2xf28rMSuJiWBlYQ+U3FAud4xfjVdYKBXBmzO+LQKUHBb40Yj8q1QVdb4xaK1O/jPJ77kHMB1620WLIMKbylsgpbC3W1FC2L4zJomnzA8yH6tlULYanIb3MSXJMg7Tmbt+F6HFv9Op2gwX2A7TKYJkXUqiw6ggWR63FA1Hr6genZc9Yydcxoj9ZEJiiptLvJl2qVUoPWHI0W7aOlOu2MaOp+ayaon6Z68KIOAEBBBtWGjEJyIQ3f7YM00NKmjLYRotUYQ62MNJZ8Q8QXNaquCaV+dsngZ0xXVArp2QzIu0DUMtCZjlbOS6NTq2HC055dj8PzFWezg8SuXJfB1Ak6UlHEI8a41Ka5b3hV38+mQWHqFKYhxdQGl5yMlyCKnYxZmN0ZR1dbFImYgaipIx4xQmOQUgLTIDWibIyLUNRN9uutrXVmHKNS5CVElodUG0eMSXErw6CyPzCA2AjibqZOYPiRX9vl4A0ivx6T7bEo0dCfkzdbezKCWR2xMOUZkMdRnWkxXQgywxpFftNxEzPbY6GDouCX7QSR3860LMMolr2akh7pCOJwx5HlxLgsawgwDJkloMSuWgsV+VW0LLbfqoUQDa4ja2mMQf6cYpVycFCDo2gugprfIPL7+Is78PiLO8LX21O1bY4yeRvdM+I1HvcgtdDxeM16M1gY6YRMuygkJRr2X9hRu42SsHYqX2xc/1fddmOsBMI3BpVp5tMt2t7MBHNfYBzk/anRG0J8iXMBLgTW5WoX6wlTg+ty3/idGteXEg3Ub6Wi+b1cBx+bZdAaPQIAMIiGtKlhwBHYWeZImhTEz3jggjeec4ZxOIwX2+W+AUUw4Cuut1mV/rJRiyIRMxCPGujP2og26Bw3HNL4rY1wEqIhYukgVENHKop8KSuFsXbRIeJ4DFFLR/eMOEyDImrpYIxjzoxE6LgLiEdNZAvSScp8Ua6IKfehVAMhUixJEBntDtKWR8Pgul/Pd4oYuhYKapnm8Etow6CI+qetaHvgg/pAA9KoDtLKg8jv4Gce4F+DaWhgBQZ/+NwquWGWn6ZpNWUFlciv/A1YBkUqbiJbcNCbKYdlGcR39Fa3lBot0vj1ws8Psg+nylw4XZh+d5JiylCyvSrlxcYtO8p2oD6rhYayorkI1krpROOcuerIr+vJmq7ZnbV1VhE/Cux4tb1qK2rPKgUXkIv8eKyi9jwYgUrd7ngIIr96EPlVp7xpIIONX1eWwQ+llM+FNH6f768sEN8x3wD1U0mnmoCgZVAwxmE7co4ZPF8MJYLUFZH79ZYrr+lUg+Pxhr9/oo1faXYoqvs19/tpz+1+5JcxEWoixKPGuFSfuWhc0zi7M475s1JIxU1ERtDeGC2uJ5W2q0svKCVIJ6y66JpVZfgUyy4SMT3MCKKEQCcaBnI2+rKl8Lh1OrqSDjpoP+ZHv3UqI32WQUY0RiklSPl9fnO+YdYo8hsYcxlfqbg64hvABaan8esvEBJRA5omE7vWb8s23Dc/yPgFgM60XD/88i/rajIBNaCuhn80MCbCdWU0ovtlVsr4bTWm352kmBIwLuB4LBQqYQ1qaQCg5E92hk6nVJreVIL4PXgDz+5gquuzckUXbQkLnYNSoQPvr+vy6qxneF5F7Vk9muTCOxkL0p7dusW8TrTQgB0P1a2ONCV41VRQokEAiPvGgScApmlDRj8Ykwvz17Ly9c8eEsUJC+Q9yscQQWsVIiaVSq4QDXsVGwYFhKhTNe7y2x3tLFfOY1B/2OgcUapNeGug6jTqwPgNIr9ciNCQNA0KaBizOJUYoqbR9I1UnRJELB3eBPQvdhkPHTQjYfpONsal+GUqXjGQNU2DaejQKUE0YsBxvLp2TcNBw8x1+b9CyUXUf85ELR2xiAHLHP6zdKIh6dth+fIQkV+/5jdXcPDaFmnUNWqbI/yMhOmGTmVmGKkq2fnuvc/ixfV9dfuGkd8q4b1grbBxRx5fuOUxPPz4BimMifFlYHAhwhTqZMwMS0DUs661mH53kmJK4DEOz5MPZClqwRum7wXqf6oGsXmRqp0VIaaAd791H7zlkHk4aJ+ucFvZYehqi9ZFAILFquPWpj07VW2u1LWXC4igttr1eF3UT9croiHjoVxl/FKiou3NRNB3WdcrCrQFTxuy7o1zjpwn4Am5UJgVq1xLxsSUa+1hGDo4F4iaOtoHOdcAIGpSGAatU0zu9CO/O6sivxFTRzJqItLAiKZEOhzG02ZlKFyPh5GnAVuOr71BS6qopSNq6kNG+4djpJpGnZIw8jYSjSLogCxpgRA1Ed3hMA2CqEUxkJNZLINTs1MJE21JEzohKLtSEKy6XdNwBIJZQkh9EZk6Lo3SZMzE3t3pEXtaU6ohZWrQIOvni45X1+OZMQENwG/+9rp/DKShgrRAfer5dCC4DoyL8PwDwF+f3lK3byFQe66K/LYNupcf/sdGPLO2BxowLrVnxnn4PcmYMW1bULU6yvhVtCSuy+BxDp1Kg3YoL14l8kugEZWG2YxQ/7oMTuk6ZMlM/L/DF4QLN9fjMHSCtmR9SljQu9ZxPYga9c9KGq5CEosYoejL4Lpfy6AoOd6QaWUjYVfdb7ta+6eYWIifmie4QNK3LQqe8Fvv1DsOPS5Q8H8egXJwAOccljm1FuIRkyIW0ZGMmw0Ne12n0H2V2Gq6In7kt1S73TQoGuWbSFXpsUdfhyNoSQUA/b7gVbtFICAX5kFPW50SWH6EO2C0adAjLe4tU9bnBkJ6JdvFjv5CnYHheAy9mVKNaBAgjTuPc7QlIzXGy3AYOkVbKiKPveo4AzpSESyck0bEojJTjIw+8ksIoBFACI6yzZBOWDXPntE49nS/B31K951NRbfOSc9842nj9hwA4KSj9q4z/gOF7qmWbTEagvp7xnjNs73R+R9c8wsAsxooe2/uKYASLXSOjwXGRPg9yZjp15FPvxZUrc70u5MULUWu6GB7X7Fue6VOpqKq2SjyW7arFuNQkd9mJKjFHrwEG/wwcT2pWtoomhJs81htUqLjVgSvFBLDIKEHvTdTK+VrGRTZgoMtO/JDCiENR3C/BTX2iuYhiMRzgXAxnvdknXcjA4gxjrxvnwTKwYAvLERJjdDMVCBq6Zg7M4E5XY3b4FCiwTBIQ8VnoDbyOxyEAAKNNSrGA+MijPwKITBQlfbMmHQQV0cMDUpCR3Gh5KI3U0K+5KA3U2oodsd9IamRjMYZbVEkY1JN2mMM+ZKLtmSkTl26VPbQlrJQsmu/y2MclkEwpzM+plZryZgZzjeN1JApJX4fYoGIpY9alZeEEUd5fzRKhR+JoC4+7df9FsoubHew8ctRLHsY8MWuli/uqnndYxy5oitTy6eYw2k0mLoUF/MYx1ErusPt6zYP1O2b93UsqoXR9l/YgROP2huXnHkwTj12MQCgL1OSQqnjyIDwGEfRrhi/Uv9APetaDbUiVDQ1r2/JYuvOfN12x2M1/fuAxsZvoMpn6hQagar5bUKCepnB13Mw2YKDeNRo2Koi2OYxXit4xSppuAqJTghmtMsWEIMjvJQSdCQjcDw2rtYlpaq0Z7UgaC6In2EhhKgxfoNevoPxGJftkICwbjHYbuiyzcxUIxW3hhVEMg1aZ7QGkd+MI+CMooZQ04bWqBgPjHEwJp9tBQ8IbKs2K2hJRWpSfXWdICgOcTyGznQEhbKLRMwInVc1n89li52R7mdN0zB3ZhLxiIFswUEyZiBm6XW9VKUhaUDXZa1u+D0eByVkzNFNnco2M0Gv5kZIoSqtTi16OGjVc0l+xtgNT03TYJo0vN9KZa+u3psxgR1+H9rOdKTOudvTX0Su6MA06KjTwacSsl+9NH7fsP8sfOq9hwCQAmCP/KuS+swYR9Y3fqsj9JRoOOqgbtk6KilToPvztjR+x+Hg9TzprAD8tOdpWovd6qgrpmh6GqUz16lKao1l60tVkV+qan6bEpn2LCNSbzlkHgBg2eLOmn16MyVQqmHujETD9CLTkIuCwSmJQX2ePso6r+kApQQLZ6cAAC++Xi8aEvEXrOOJ/AYGs2wrph4vzUTQGkQIgVQgwuMKAPW9RwE57xYD47cq8ivVeMm0rD+0jPpev/Eqe2RLYeR7RnYnaHzOxwPjHExwUAr0+/W+SUO2YeJcgGgA0Sr3ok5l31QBAWjSoE/HTZgGbShYFfSgHY0DMVBpdjyOWMTw008rnxnk5cSjBgxK4Fb1FGdc1vCOtV9qoC+g60MbzjqliJj6mOrUqd++xmMy8j3elGODEqSovC7FshcqBQc4HseWHdLBP29mou79jAuk4ibiEX1apj1rmhY+k4Da7g+PPbsNgHTI/fKvr0EIv6PBEE6Odt8oHsjZ0DA+wSu3xvg1p20LqlZHXTFFU8NFvToiAJRsVmMEUU1rGKkKBHgMnYTK0IrmIhDi4VzgrW/YC+eeeABOPXafmn0cj2P+rFQYsRyMZQSRX4Hqn4tbJXilkJg6wYwOeR57s+U68Rmpnj4+4zdIcZTRGHWvNRNSWE4aXkk/EpVzAc4BXld04Ed+/cVhwhgsdjX9IlAAGv6mNU1Dyj8/v1o/suCTBml8Dn6uOS7DQN4eUgxqKFhQAqQR9JWDlGc533FeL/YXOKVcl8OgBF3pKPaalUIqYYZGMRcCA3kb2YKNbNFBxKSjNkotU/Y+tQwquyxoBJxzMM5h2x4o0WAa0lCtNj4Y52NKdw7QNE12AEhbQ9ZdBvXIY6lT1zQZ7fbY6CLfQ2HQqprfsgvHZTWOetdl2NQjjd9957XXvDdQ2W5LWthnXtu4vn8qEDFp+DzSNA0nH7MIQCXb7x8vbMdjz0lDmHExZH/5dKJa7JHXZYqNBpfxsOY3ETPAhVpftCLqiimaGs7rW0sAQNl2ax5GlJKGCpaVGkQViWpWNE3zRVg4CNGw3/z2mvoqxmQ924z26LCLG7mvAGrSnpXxOxhCNKT8ml/X4w3VnTWgLl1xNAQZGZRMrR6wUwFKNFA/5TZdZfwKAYgGfg7GOfKevN9SVcbvdE7zG0rE7aSFMtL0eo41XEzbTOC+1x28MuA/o7R647dnoITN2/N1NbIjwfy0dU3TsCkvL+ScmG/8Ci5bNFVBfXEox2OwTArLpIhHDSQiBiyTolT2UCy7iPhtfCyD1qjsjkTEpNB1At0gfiRXw85MCX3ZMkoO8/vvknDOrz6O8daRz+qMozPduFYbkPXcC+akxpw2LMXJpJjYeJ15uk6R0uVx5osOXMZrRMBcxtGfldoL3TNqVZ49Jo3fvWYlx3QNphqxiFFzvxy4t8wMG8jZ8BjH2o0D4WtHLp8z5OcYOglT33NFB6KBE2okHJehUK4VvJqu82Ero66YoqkJ0sOqFxRCCJQdVrO4pkSraWAeELZe8UUTFM1JMmYN2WLHY3zYlDYAYcSAcT5E5FdFIQN0Ku+FoJfk/X9bjxt++hR6M6Wa/QankI8EY7zSWkofvaqqYs9A/NRQXqX2nHNllG+w4JUQAh4Tflp0bdozMH3behh+z9HBDtnDZuqgGlBmlT671dy/wcUDG1384EUpagSBGoVt4fcOdTxvyL7LQ+FV3afrfeN3QdLPhOH1LamCvuoekyJOgUPRMnVELR0l20PJ9pCImZjdFUdnKtKw7+xQEEIQt3RYOoWhE8zujKEtYcEyKNqTEXSkLVnHqVMw/3fHOYemYbcqiI9nPtJ1ApcJEACaNr75TKdaKHiVK7rgrDabLVeww3VKdYstIQRsl8E06bQUuqrG0EmNbno8asAyKASAvmwZG3yl7GMOnou3v3H+sJ8VpD5nC86Yyw84F8jkbelsQkVYa7rOh62MWp0omhohS9JqDBqPyf6khk6wpSeP/lwZhGhh+lc1lTRMouoymphU3AwVHQfjMllTM1xKXLDAY6zWURJEIqdjfeJQUL/mL1gEPPHSDmzdWcDXfvxE5dxpY6+HYlxUaqwpger80HyYhmxzE6Rh5vy2OGLQvMm5nEvzvj8x5Ru/gdE3nvTUqYB8jmih4co5l5FwoqHL7/fbU6o9l0wI/GWrdOxl3YooVrUBFCg2y3KDMaZhulwa5EJgQ07OdwuTlS4Ig68VoVJjwWOszjCeOyOBdNJEMmZgZnsMM9tjmDcrOaaIaSpuYFZnHLGIAU3T0NUWw+yuOPaancLC7hTmdCUqbXv8Q3WZTHkej6Ly7sTUZQo38euKxwOlQJsZGL8OGOfhc45zgZ0DMuobi1RqkjN5G5t25FEqu0hEjWn//LIMCmgVVXpN09CZlo6CtRsHUCi5oETD6kPnj/hbDRwMA3kbnDcuqxsKxiuiWrGIIUsBNJVZ1oqoK6ZoamTaM2oMGtvl8DyOnQMlfPPup/Hde5+FBoCjPoXFDtVnVQ1iM9OetBC19IZ128xXlx3uARNEDAYLtgSLDGMKKtOOlyDtsVG/5GfW7gQgnU5jFeTxqtL5jEF1hormIBYx4HocKSNIe5bOosH2VhAR6bMrPWMBhIrs0/V+olQDIZV2RwN5G5m8jObOiMpz0lOudeA9s5OhXDWt9dmyJtGrivAyJlsf8UER4dHgMQ4CDXkXKHgyIjU7RkJBq8FZL0Htt6ZpdSnRpkExsz2G7q7EuB0cOqVoD3rv+qTiVuhsC8dRNZ97TITR4GaC6lIkc1eEpohG0Obfb2WHwXFZ6FhknKMvJ43faiGnfMlFKmEiV3LHFHWfqpgGhamTmqyIDt/4/eVfXwMAzOmKj+o6Bed5IFdr/Dqu7D893HPP9TiyBWn8JuO+qJaAeta1INPzCaZoIWRKXo3x63hwGcfTr+wEF3ISyxQccFafvhcKXqnIb1NjGhTphBWqc1fDGqTu1b1fr057rqr59R+WY1H5nOroVPavbEvUG79rNw0AgB8ZGusiXFRqrHVl/DYj8YgOQCDlB0dcDjgCdXWqXMj0XZsBREMY1WRMhDWb0xF57BqyBQf9ubKvIyF1KYJztHNQ5PcPW2rLOXpKHJRqNRoVtsPgMg7dF5sbCx4TIATYVpT3XkdEg0kDpef68gNK/BR40viZmIpbSDWYGyYa3e+jy4UAY7wp52jZPknbpbUD0YAY1cJ2fPmyGz6XXK9S7xs4B4QQIETub+hTr5/2eIhaOiJWbSuuzlSt+OVB+3QNfltDAuM349cLBw7bnoESnl3Xi95Mecj3Mi6QL1TqfQEAmkp7bkWm5xNM0RIIX+l5cGpKvuiCc+Dljf3htq29BXDB67zm1WnPVNX8NjVtCath3z3GRlYBDTy+jImaFM5gkRFpwoXVZEH9FL7OdL1y9paeAgC5YBtrD0SPcTh+2rPhG9iK5sLQqUyFJYDfnhY5p974FVxgq29MzY5q0P3FHeOypc50TfMjRMOM9hg62+S9I1WACRjj6GoQ+d1S4FiX5dAA7Jsm4bagx2hw3nuz5bDPrTfGml/GZOeDHSX5vlnRylxo0HqtBKIREE2OfTJb58hsLL9PMRdNl/IMSGcHpWSXssaIJqPsyag8vnzRDR2LjssxkJORxCAd1/OvG/V7pU/FftpjhRANyahR0+IySHsGgDceMAtHr5g7qs9qT0knQ3+uDC4q7RCLZQ8DORv92dKQ7/U8jlzJj/zGzFBZWompth7qiimalqDeV6A2BbNky0bx1R66rTsLYHyYtGddLcabnaEM3NEsjKrT96pTn8O052kuGFKNTmQq3+K56XBb4DXf0V+UaZRkPJHfihdd3W/NiWVSECpbzKT8wIVsdzQ48iuw1V8DdscrywTGhWxfM40jHe2pCObNSMDUKXTf+PU8jhlh5Nev5xQC339BPqMO6KBY1innsJcGGKjfg5dx6bC1bQ8RSwel2picToEwGSFamKLe4Y/D4zw0zqshRKZuS+NzEo1fXY4jU7DBOW9Kh4pONVjj6D1cTXCvJH1xpGLJC424suMhW5Bp80EmjsfkuTB1CoPSpjwvk0E6adU4jOZ0SWXsiEnx/w5fULOvEFKYqlEJQRD57c/ZgL8fAOSKsvdvtugO2f7IYyIU5kzGjDC7QpXUtR7qrlI0LUL49b68tnerxzn6BqWmZPK2FJIY5DW3B/X5VTQvpi4jEnU1NxpGjFBUv17TRkKlPddB/aiCaVAcdVA35nTG8Y4j90bU0sG4wI7+IoimjVnwyna8UKwnYk5vA6lZiZgUpiH7rrb5IlYZt3Z+BeQ9uMNP350dqzJ+WXNG6PY0hk6QiBvoSEVkv1peqfndUpSiVs/1MWzzz+G7FppY3iHnoHVZDg4plrWjrwTblSnPwT3juI3bJTWC+VlRRNOwueCnPVvyunIuYBq0YXu4dNxEOhmZ1HRNSgjiEXkOLVOf1Cj0UOg6gWnqiFnGuD9D06STIeFHfgtlN3xGlWwPed+YqjF+dQ1tSQvxqDFtxeUGk05YiJg0LBeYOyOBc088AB86ZTlikdrrY7sMRdvFgG/Y1nxO3JICqVzA8wSyBQeux1GyGRJRA2VnaMV1j3EUyzKbMBEzwYUsOVBpz62HeoopmhYeRH0HydEzJtDTL8MSxPeg54suIOp7kxb9GpGISVVqSpNjGNLL7TEOk1Q98MXIas3VNVlB6q0QInSGmE24sJosdD/d0XEYTjxq73D7nM441m3JYOvOAhbPaxtzy5VgUSC/Q9X8NiOmQRExKDwm0O5HfrOuVhch4Vxge1nOpdWRXy5EUxopexpN07DXzCQ0TepKFMseOqI6DCLrqK99uoxNvjH6lm4d3XECIQQSBpB3gW0loJ34bVMgjVhKCahvzDLOodORjZ6gLGibAzzXJ42CxemK8v1QtaqzOuMNt+9JNE3Dgjkp5IsOtvcVmtLI0ynBgtmpXTZudAIkIhXjN3hGFcpuaPymEpXe6+mEiTldccQi+rRvcxQQj+iIR02Uyl5YB73f/PaG+5ZthraEhb6cDSFEjQOIEKl30ZctI1t00J62ZJsxlyEeNVC0ZWS+0e/RY7wq8mv6kV/1rGtF1FNM0cRIoasgPSzA8zh6BqTxu99ebQBkCwFoqEnV5FyEAgmWSZV3rsmxDALDoGGvWEBeTzqKuifip/IClRoej1W6cTbjwmqy0DQNEb/lTTVBGtmWnQUQ/14abQQKQLgooL46qkp7bk6CCH/F+BV1Ke4u49jpJ9dUR36hYVJTZZuJQDE5aB9FiYZ3L5InNTB8AeDYuTIqpWkaFiTlPLQhJ895oeyibEsBJA2anw7N4XmjjfxKlejn+uT37ZsmWJSS38EhWqK3fSJmYt7MZNPO0ROxbqBU9j4G5DxZdhi27MxjIFsOnYbpuIz8MsYRMXXolKAzHW0YuZ+OaJqMhpfdelHMwTieNF6jJkWhVJ/GHKQ+Zws2GJepzJ7HEbV0uC4LHRKD4VyE1ytIe25UWqBoftQVUzQtPOzxWxv59RhHT38RQMXzlys6ELx2Ece4CNWezWlep9YKGDpF1KJwq0QtPE/WP40mbTmIcgQpZdXpz826sJosLJPWGTzdvvH76L+2oj9bDnu9jpZgwWAa1DcMJm68ionDsihs10PS7/WbcWvvFQDYOuDAk51y0G5VXUjV1qOOiKkDQio+HzXHCNPJAWD/NoquSGWZNc+Pom8tcqTiFqKWgb6sHc5vlBK4rN4ZMRRBh4Pn++X1O3xWVTKfGLlcpFkYSx/hVsTQCWKWvMb5ogvGOdZvyaLPV3rWqYaYHxlmQpUWDEUsooe9oYeDcYH2VASxiIH+vI3XtmZruoYEoleZvAPORdi+SPafptjck2/o+C07HgrlSuSXcQFNqT23JK0xMyqmJUIIv99oRcjKYxxlh6HXf2gExq/HBMouq1k0lO2KqmI0oqsJqgVIxizYVQvxQPxjNIu4IMrhsEobiYBWWQTuKSKmXhf53X9hR7gI/+1jG8CqWheNhsD4tQwi69zU/daUcC4QjxiIcBnByDjyXgkcHa7HsMVXoE2aFaXnYNGnq+tag2VSGAYJnzXzElXGbqJ23pkZleduR4nD1CniEQNdbVEk/V6uGjRAYNQlB5wL5F2BTQV57Za2S6MpyHlREanmgBISpj3nSy4YF8jkHezwy7dScasS4RVQ+iRDYBlU6sCMmJEk2yO2pyLoSkfRmY5g/dYsNvfkwYWo9PrN23401w3vlXjUQKnshXox1fTlyuG9mYzLtGdTb1xXr2hu1MyoaF6EfIjLPoAV43d7XxFCSC9ge9IKPaaDJ6xssZK6EjF0FbFoAZIxA9XPNY9J0ZbRpFpWIr9B2rP8N9HUInAwuk4w+G6IWjpOOXYxAGDTjjw8xsYkelWsjvxqKkLYrMztSiAeMdDmpz1nHOE7GOX9YjsMO/02R0HUlwuBsu2CUqVsOhjLoDANPSy32KvK4J0bH2T8+ink26t6AWv+/6qpbukyHIwLbJLdyTArqiFlVsSuCJncVkaKCjqtMn79VkcuY+FzKe3X+wIA1PNqSAxd6oIM1wvb9WS9fCxiYMHsJJbu3YFU3IRpUCTjJvJFB+1J3/jNybRnj1VKBCyTolB2sTNT2/KIMY7eARl0MXWZjcaFUK2oWhR11RRNi5/1XFPz6zGpRgsAszvj0DQtrJUplr1QCRBAKGFvGVS2VVDeuabHNCg0yMU2IGt3krHRKW3qem3Nb2AEqxrFenRab/wCwPLFXTB0GcXqy5XH1O4ojPya0hOu7rfmJGLpaEtZoWFbYkDRZaFYoO0yZBw/PdA3pjyPwzJ1mDpRC/NBEKIhZunhfDM/WTk/e9VFfuXfWUegNERdr6GTUKixmkLJDZ9pAYxzbCrKz1mYqpR2MCZrkNW1ag4MXUM6bkLT5LOtd6AMnZK6et8Add0aY+iyRddwzyWPcRiUwDQIDJ0iGTNhUIKoRZGIGiiUXXRU9/rlAozxMFOJaBqipo5tvcWazy07LLz/gkwNxviIYpyK5kTdYYqmRQgBCFlTEUSgGOMYyMkJqMtvcp7yJ6KS7aFse2FKTFDHEQkW4yoS1fSYOoGuEwzkbAz4ffoGtzEYCsNXR63U/PrGL1GG2GB0qqHR8oEQuUgDgGzeGdbDXg1jPLzf4lEDRNOgqfutaaGEIG5oiPjrtt6yCBWfS2UPWT9pps2q9IzVqYYZ7TG12GuAZdLQYbdfmmL/NorVc40wzTkgpmtI+tNZT6nxAl6nBCXbg8dqo7/b+wrY3JNH0a5kNHlMYKff37c6ysy5XMyr0oPmQNcpLEtHPFoRP5vVEQuNqUDpuWR7MHWiFJ6HwPCdb4O7elQTtIoyq+apmR0xzO5MYE5XAho0tCel8Zsruig5HlzfYA6/x6BwBpXRFcouMnn5jEtE5fXiQnWSaFXUVVM0PZQQlB3pIfUYD3u3BXUbQcpQrujAZTycGHNFOVFZpg6ijN+WQNcJdEJgu7LdgGXSMK19JIIUvyD6H6QOUkpUTc4gdEpASX2LG6Di1c6XvLq+2UPhcRFGfuMRA5pyODQ1lErDKOz168hrKIRA0faQ9eT2dkveU4zJyG9nOjppY25m9KqFtkk1XLg8glMWmQ3nnSD6u6PUeAGvU3lfuoMiwx6TLf0KRaleu623gELJDVW5qw1tLir9vBWTj040mFRD0jeaHJfB0CkyvsMwiPxmCjZmd8RDI1lRi06l8ds7UEK2UN/DF5BZKhGztsytMx3FkgXtSEQNmIZsTWT5Doay7aFoezCqRDENXTqgtvTkw222wyptjuLy+gjRGorqinrUVVM0LX7gF5RooSEjhSLkpNfuG7+BEZzxxQsCb1115JcoL3hLYFACSjVYpo65MxNYsqAjvL4jETyEgohvINZEiQbV4rkWuYjQGkZ2g0yKYsmFx0dp/HocuULgFTegQdX8NjNU06DrBCl/jZ3zRDh3eowjG6Q9h5FfgaiKRg2JqcsFNRvF/VKp+63sW/IEfrvBwetZBkpkTWO1Yyr4WwipTLtucwY7+orIFhzs9G2AWVUtqVQ/5ubDNGgY4e3PSY9F1l/LpBOmr0YMdLWr9kbD0d0Vx5wZ8Zq+8oB0KAQBkKEc5rGIjkTURNlh4bpCCKArHa1ZH1oGhe0wbNieq3GmB+UIyZgvUKdav7Us6qopmpZgWa5TErYs4lxUpT3LKERgBPfnbHhMhMZPsBiXNYhQkagWgPrKzpRoWDw3HdZ1j4ZgsRc4SoLfgU41tZgYhK4TEK2xcEjKj0LkS+6oBa+8qrTnRMz077eJG69i4tEpQSIwfl3ZX9ZxOVyPIzMo7RlCTPl2NLuCoRMYlIzqfpnlR363FyvG7W83uvjlehfXPVMG852+XtW9yTmHENKA8vzSH0oJdpYZmAB0DeioaknFmDJ+m4141EDSj+j2ZcvgQmDHgBRVak9Gwkwn1eZoeObNSmLujAQYE2F2HwD0Zssoll2UbW/IUilN05BKWHBcjo5kRfHZMige/Pt63PngSyj5Bu6crjgcl6Hs/z2Qt1GsanMEVIIzitZDzY6K5kXIhg26TuB6fkQib4eGcKdf89sZGL/ZMhjnofGTLwatV6gf/VOTVCtg6CSs7Rnr+4BK2nOl5peonrOD0IlU7W2U9pzyH+yFslvX/3UoPMbDhUgyZsBQqeZNj6lTJPx1ds4V4EI6jlhV5DdtavAYA6UElqUiv0Nh+FoFo2lRNDsm74ttVcbvc71+WY8ANhU4oKE28suk6KNlUhRtD0ST5QUOlY6qmdHaMgOpQquuVzORiJqhY7E/a2NHXxG2w2AaBDM7YrAdhqily77RimGJRQy0paywBA4AIASScRPaCEJvEZNCCBH2+u3PltGfK+P3/9yEZ9buxB+e2ARAOgcZE3Bcjh39RZRsL0x7TsVNqS2jqTaKrYq6aoqmRfj/p1MCl0mjdouvwJdOmOHDvcM3ggtlD7bNUHak6FW2WIn8KvXE1mHR3DbsNSs5ZuPJGJT27IVqz6r+dDCUEhlFahD5DWp+i2UXjq+cnS862DlQqts3wHFZWPObiBoqFawF0HWCpL/OzrvyfinZHkpcQxDATJkaPCZgUAJLCV0NiaZpaEtYsF0v7LE7FEF68taiwKY8Q7/Nsa2q/ndbob5PucdkO6qIqSNuGUgl5MJ9u6/0PDM26H7TVESq2bAsijZfaGkgb2PD9hwAYN7MJCjRUHY8tCcs5aQfBcmYgVkdMVgGDUsCqF8PPJLKebBOmNEmMwe39xXxysaB8PVnX91Z00e47HjYuD2Hvkw5NLa70hEwLkAJUQKALYpaoSiaFiGkAWzoBJ4n0/G298mmhl1VwisRUw9rPPIlB5m8TH8O1WcjajHeSqTiJrq7EmN+X/AQCmt+g7RnQtSCogERizYUtEqHglcubJchX3SwdnMGL67vw/Ov9TZsM5EtOOH5jkdN6KoXbNNDiYaEL3iV9wRKtodswUZZyG0JXWYIMC5FXdQcOjyBQzZotTYUnZYWLry+8mQZv3zdrXl9e0mAalpN1gXnHBwCRNNk33MSiGbJ7wpSqauhSuigqTApCVWGB3I2NmyTxu+C2UkAUqQsnbCGfL+iQqCWresEnsdQclgY5DANGopZNcLQCaDJVpkAsK231vjtz9l44LENAGTgZeeArK2f0RYN1Z4701GpKk1VL+1WRV01RZMj+xUyLmA7LKz3DTyoAUHqc9H2kMk7sH3xAwCIR/UaGXvF1MTyMwEqNb+B2rOK/DYiFTNDUbCgjtBjvKL2XHRRtl28tKEfPf1FZHIOtvUW64RGAGB7n4wKxyK69LyrBUHTQ2gl8ptzZWptyWHIePLapX2lZ865SqEdBYZOpaN2BNErTdPwhpmV8/n3HfJ+Cmp2d5S43+GgYvw2ytAAKqJZ1WJXQeRZ2b7NBaUEbX6qre0yPPHSDgDA/FnJ0JAazmhT1BL0HXc8jkLJRXvSwvxZSew9J4XEMGrZQXQ4SHvOl1w8v64XgKzzBYC/PbsVtstgGhQlm8FxGAr+cy/id6BgTITRZkXroa6aommpTj0BZPpJdlCftYBA9CpfdGE7DNm8Hdb8xiIGqIpETXnCtGffoHPCtGdV89uIWMSApsn7bPOOPDQiRUMCMQ/GBXJFDyXbg0EJ5s9OgjEeth2rpqdfZmSk4xa4ENDVyrvpMaiGtCFvjKwLuEzW+z61Uxpd+7fLhTjjqq5tNBCiyTTMBpkRgzljsYW3zq3UduoacPLe8r7bUeKgVPN1LuS1aJRtAVTSnmdVtzniMkKsIr/NhU61hvW8e81KwvU4DEpDB65iZCjRkIiZfh2uwIz2GNpTESzsTg+b6WWZFAaV2ROBkSwARC0dH3v3CrQlLdguw5Mv7UA8oiNXdJCIGejNSAdvZ1qqcTPOoRNNZTm1KGp2VDQtuYKDX/7lNby6aQAGJcgVnTCaO9izF4hfyZRnjkzBRr5USXtWkd+pT9BsPlh8VtKeldhZIyJ+mljJ9hCPGtJw5VIlNigj6M+VYTssTMcTAHr6SzUpmUII9AzI1h2phAnOVe/DVkCnBG0RDRoAJoDegux1+eKAvLYrOuVCXAih5s9RYpkUo7B9EdU1nLbIwn8eHMGKTooPH2hhflKe450lKaTjMR468Mq2BzrIg1f0BHKuNH5nVKU9MyZU9kUTomnSOTKrIxZu60hFEIsYMvKrayrDYoy0JSw4HkMqboXZfyNhGRSmQeC4DF1tlfK5hXNSoETD0Su6AQB/eXoLKCXo7kogFbewaYfs+Tu7U14/xoTfSUStLVoRNTsqmpbb738Br2wcwG2/fgGWSZHNO2FT+ESs1vgNerb1ZcuABvQOlOG4HJoGJOKGWghMA4Im9Z4nF4SBgab7rZMUtUQsHZZBkS04ME2K2Z1xEE1GfMP7KVNG2fHC1K6ISbF1Zx49VeJXHhOhEEjaVzNVqWDNj0EJoiZF2k+iyXgEPQ5ByQNiOrAgWbmGqt53dOiU1GUsDce8BMUHD4hgabuOTkuTAmMCeC2PUGmWc1mPPfgZtsNXi06ZGqJ6ZX7zOIfut15SNBeJmIljDpmLBbNTmD87iTNW7QtAOjoskyon7RjpTEewz7x2LFnQPuo5StM0xCI6PMZrjN+9ZkqdkYMWdwGQa8mnXu4JX399axYAsGB2CoB8Tqo09dZFzY6KpuWl9f3hf0dMHSWHhc3hg0iU7bKaSWzrziKipo51WzIAZIqKTpRYy3QgWOwFNXdByyNDJ6rmtwE6JWhLmiiWPaTiJhIxQwr2eCw0fjMFBx2pygKhPRkBoKFQkqnPZcdDX7aMTGD8JqQlpRZxzQ8hGmIRA+2+6FVZ0/FyRhpuS9ooiKZBQEBT7TxGza44fTRNw/IOuZh+2k89d10Gl0mxx8GfHdb7RmvvNc/jiFq6ugebkHhUx+yOGC44dTk+cupBWDBHGlKexxGzhq5TVTQmFjGwZEH7mIXCkjETrsdDsTEAmOOLbCZiJg7cuxMA8McnZdsjj/Ew8hu8h3EBUyk9tyzqiaZoWqpbPehUql8GNb9tCQuOy9CXLWF7XxGzO+OwDIpC2UW24GDbTlmD2N0VBzQo42caYBi1rY5sp8r4VQvBhrQlI2hLWehMR2AZNIwESyMXsB2vrsTA1AnyfvnBus1ZvLKhvyJE5y9CVKS9NYhFdLT7kd+eEsezfbX1vqGiqXIejopAW2KkdkdDsbJLlhv8s8eDJ6QDz3UZNucZvv+Si2f9fsCMCzy0SWpadMdrrw3jAjFL9YptRmKWAUpIXQ034wIRFUXcY8h+wMC+e7UhHjEQjxiYX2UIn/bWfUCJhu19RfRmStjSU4DHOGIRPQy0CNVLu6VRM6Siaan2dJdsDx4TYFxGIpJxEzsHiqHkfLHsYvG8NJ5/rQ8vb+wP0zDndMUhBJTg1TQgEAsJjN+gR62pq7qcoZjdEQfRNHS1RUGIhvZURApc+Y6Evmy57j2GQVGyPamoXrDRlysj55cjtKcifo9RZSy1ApZB0WlpAAT+uMVF0ZPiS8s65NLA9Th0napF3iihfls1zkWdA6hYdsEERzI6dJRqvzaCdktDvy3wegHoSnHYHsPvt3E8NwA838/w7ys1/OI1F9t8sat5VcavgKwXVumYzUksosMyKWyHQR/UnspqIIal2D20JSy0JSIoll1ccuZKEKIhWuUwilo65s9O4rUtWbyycSBcUyyYnapZS6h1ZeuiViiKpsWuUpWtFtmJRwwwxkEIwaK5acxqj8F2GJbMbwcAvPBaH7b4kd85nXFoUDWI04FgwRf0rq1Oe1Y0hhANszvj4f2xd3caC+akwl6/vZl649fyjd/egRIcl2NGOhoK0bUlTEBAKWC2CIZBMcNPmy360+2hM3Wk/FRolUI7NgJ9AcbrOxW4Hgdnshc9G6IdEtE0HOhH3V/JCtiObN23ST7OwAVwzZPlUJRM14DlnZVFu+dxGJQo1eAmxTQo2pMWCuVKb2fXY6C0IjKo2P1QSjCjLYKyw5CImYhF6lPO953XBgB4ZeNAWO+70E9TDzCous9aFbUqVDQljPGwrxoAbN6ZD1sXJWKGVKiN6EjHLcQiBgSApXt3QgOwZWchXLTP6oiBUk2lYU4DLEMuHhzfSRL0+1VRq9Fj6ASzOmKY0S5Tu/pzNn7x53VhWnOwD+cCmbwDx2PozZTAhfSWx6OyrZgylloDUyfoTlSWAe2WhnculAtBLmSmTSpmDvV2xSAMSqDrtWmtQgjkiw5SCROGIQWxsn6mRCMO8Ot+X84IFEseNvYWkXHr93v3IhNfflMMcaNyr7mMw9AJdFWL2LSkE1JVP6DsMEQtOmxvWsXEk4iZIBpqrkU1+wbBlNf78MLrfQAqYlce4yBEg2koE6pVUVdO0ZQEUbuA9VuzodhVMmbCdhnakpY/AVFQP21lr1mVuo1U3JRRC01TglfTAGuYml/F6IlaOmb4adAA8Ldnt+LbP38GxapohaZpsD0GzgU27ZBhqfmzk7LEgGgq06JF0DQNe7VVFt2nLTKRMoP7iMEyaZ2yvmJoCNEQs3R4HoeAgO162JkpIR410N0VRzxqIB4zQakWOukGs18bha4BvbZAkZooEpkmPTOq4aMHWjh5bwP/e0QMb5lr1Kg8A4DrcumAUs6npmWwM9ZxGRJRQ61R9jCxiAHL0OvWmgFzuuKIV0WEu9qimDdLimK5nnQyqQyL1kXlWSiakmqxKwB4aUM/En4EwjIoOBdhqoppEOhUg8c4Dti7Axu25wBIsSvOBQjRoKvFwJQnSHt2B6U9K+/s2NA0De2pKLrSEezoly2NsgUH//ujf+LkNy/Gyv1mwNQJXJcBGrBhu98CYlYSnAtomqZqoVqImEFx+gINBaGHvX0Bf1EeM2GoKOKYiEcN9GbKKJY82K4UjGtPWbBMHfNmJABNw+tbBlCyWUO1WItq2K+N4vl+hnVZjowjI1PdcYIDOnQc0NH4e4UQ4II3TOFUNA+mLlsaMb8u3PU4kiq7Yo8TtXQk4wYyeaem3jeAaBre87Z98eL6fsyflcSiuelQONV2mTSeVW19y6KMX0VTEqSNaZoUJ+jP2Xj0X1sBIOx3GET0TIPC0Clcl+HwZXPwt2e3YSBvY/G8NvmA8VPRFFObIO25IngVRH7VA2qsJKIGVh26F9Zvy2FOZxy/+POrsB2Gux5+GTv6izhi2WwUyy6IpmHDNuls2mt2MrzflOBV62AYFAd1ELQnahfgHhMqFXMcRExZI11yXHSmo+hMR5CIynMbRPeSMQvZfB6INv6M+QmC5/sZ1mYYXvLrew/uGn65li85SERNJFWkvqkxDT813mOgpg4BgYhS554Uutqi2NFXBCCdRz0DJRTLHky//Gffvdqx717tde+zHYbZHTElpNnCNN0d9+qrr+LKK6/Ek08+iXg8jpNPPhmf+MQnYJrDe8aEEPjud7+LH//4x+jr68PSpUvxmc98BitXrtwzA1dMKIEBo1OCYw6eh3v/9Gr4mmVQoKr3pE4J4lED/dkyEjETHzltOXozZSyck0K24MA0iEoDmwZUR345F2HkV6UmjZ2IRTG7M44D9u6ETgkWz0vjzgdfxsbtOfzhiU3gQqAzFcFD/9iAXNEFJRrmzUzCcRmIplodtRLBPCogoEEb9Jq6d8aKZVKYft1vWzKCVLxe3TkZN2EaFP25MtoSVt0ien5SXpMn/X6/XRENK7uGvhaMczAu0NUWVdesybEMCoMSuB5H2bGhU4qIUnqeFNqSEVgmRdnxIISMylspCkMnyBYrLf8GI4RAXDkGW5qmcs9nMhmcc845cF0XN9xwAy699FLcdddduPrqq0d873e/+11cf/31OPfcc/Gd73wHM2bMwHnnnYeNGzfugZErJprA+KVEw2FLZ2HR3HT4mqHLyFL1Qz4dN8P3pOIW9u5OQ9M0v3+erjx004DAyPUYhxCiKvLbVNNcS5CMmYhHjbDOtz0ZwQfftQxv2H8mAOAvT2/BvX9eh5wvQnfQPl2wDArGBQw/rU/RGkRMHZZOw/sFABhnoErQZVzolIBS4qsuNz5/UUvHzI4oLJOiJ1MC5xyMs7A/8L5pimTV2vpt84xhe9WXbA/xqIFUXKXPNjvUd9bbLkO+5GL+7KS6bpNEPKKjLWGhUHJRsj3EojoOXNSJ7q4EbIchk7fr3sP9dpsqWt/aNNWT7c4770ShUMCNN96IN7/5zTj99NPxH//xH7jzzjuxffv2Id9n2za+853v4LzzzsO5556LI444Al//+tfR1taGW265ZQ8egWKiqDZ+CdHwvuP2D1/rzZRgGqSm3mKoichjvGE9h2LqURP5FRXBK1WXM3Z0StCZjqJkVxTXDZ3gtLfsg/32agPnIlTJPHpFN95x5N4AZKuVmLrfWgrToLBMGs65Qgj052xETNXfd7x0tUWQipvDZp3MaI9h3owE2uImckUXA3kHA1lbpsHqGj5xUBTv3dfEhcsiOHL28PeU63Gk46YSTWoRElED2aKDWETH3BkJ5SycJKS+RQSux2G7DJ2pCNqTEczpimOfvdpQtOtl1l2PwdAJImpd0dI01Uz5pz/9CUcccQTa2trCbSeccAI45/jrX/865PueeOIJ5PN5nHDCCeE20zTx9re/HX/6059255AVu4mgp2/wMK82YBMxExFDppYFWCaFpgFbduZrvHWMq3qa6UKwUHc9GfkNeimq9KTxkYqbGNwFQtM0nHjU3uFi7YQjFuIdR+4dnmOXcaUO3IKk4iZcj8mMCU+KuXTPSCjV7nHSkYpi/uzUiMZoKmEhnbBQ9oWxDIPAdaUTYmaM4IjZBvZvp8NmLjHOoWlQQlctxKwO6fiIRQxlRE0ypkHhMdkfu81Pc9YpQUcqAp3SOvFVx+MyPVqlqrc0TXX11q1bh3e/+90121KpFGbMmIF169YN+z4AWLRoUc32xYsX47bbbkO5XEYkUp+7v3r16iE/c+vWrZg1axY2bNgwlkNQTBAvrxsAAAjOsG3bFgDAqUfPxiubClg0A8j092DjxkqvRNfjsPP9sF2GTesziJpA1q9FNJ00dm6pr7tSNBe6riOdTo+84xDkSzJK6TGOr/7wEeSK8vdRzvdjw4bGvfwUQ5Mruujv7QUrm3VG0AmHzUBfzsXMaBYvvtAfbu/NlKHbbejdqu63ZoWUy+jcvBmRzk4IS16nou0hn8thoL8fhGhIxkyUChylwiQPdhpQKDoo5XOI0yjKLkPG8RC1DNiuB8vQoVXdeqVSCZzVtmZxPA7OOGJaVtXaNyHEcWA4DsSmTRDRisJZe4TDY1CleZPMQM5Gf28v2hIRDPRyZPvlPcQ5x7bN6/F62akRkcvkHaTiJiJs6GxUxeTgOA4oHZ0zqamM32w2i1QqVbc9nU4jk8kM+z7TNGFZtQuuVCoFIQQymUxD43ckMpkMvvOd74z5fYpdZ4c3B8BeKOb68bOf1Ebvf/svjlSMoi1e+/PlXGAgk8NPf3oXOJc9FwlR4jutAOccmqbhzDPPRCKRGNdnCAFQrASDiUef7/M3cvz63p/gz2O//ac9jAts73ehEcBo0LqoWMjj6/fdDQBhZIoLua8qsW9e4pqG0zo7sfSww6DH4wAALgTyRSbLBTyBVJTiOUtFffcEjAvkigxRi4BxgXxJRnKDe8j0e/na5TL++fdH5Mbq+0vIv9VzrjmJaBradB3aM89Ab7C+VUwuriewI+MgblH8NVFZU+bzefz4jjvBeO29xQWg+2tLRXORSCRAKcW2bdswe/bsYfdtKuN3T/Pwww8P+dpb3/pW5PN5rFmzZpeiUYrxUbQ9/OKRzYiZHViy14pw+0DeRq7o4oCF7ejuite976mnnsKdd/wIkVgCsVhUKf22CMViEdlsFqtWrcLBBx887s95ZVMOf/5XT/h3d0cEq9/wISV6NU7Wb81h/bYcOtKRunP4wvPP4Bf33IFEIgkrEoEQAISsv1fGb/NCy2V4jGHZgQdi4f4VLQUhBDwmkM3boRqxYs/AGPfbIzFs3pEHIQQRk6A/K68FJRo2bXwdjz36J0QjUeimAQi5ENcQiGypm64ZIY4Dz/Ow+phjsPzwwyd7OIpBMM7x0voMurtiaEtWAmhPPfUUfnj77YhE4ohEotCIbP9GNQ2mSZWzqQnxPA+MMQwMDLSW8ZtKpZDL5eq2ZzKZYQ3QVCoFx3Fg23ZN9DebzULTtHEbr5qmYc6cOejq6hrX+xW7xsxZ3fjnC9sxu7Ni5Npbs4glgfnzZ6K7qz5CuHnzZpm2F48imUyqRXiLwDlHLpfDzJkzMX/+/HF/zvz5wOojJ3Bg05zZcxg6NvZjc0+h5j50PQ6mrQUAmKaFaDQGj3HolCiBuRZAA5Bua8OMGTPqXuve88NRVNHZ4YBSAqIBr23NwnEZOBegRgwAQHUdpmGBcQGTaMrwbQE0z8OMrq5derYpdh/z5jHolNTU1m/evBlE0xCLRUEN6dy1LA0RS1eGb5OSy+UgxOhK3JoqHLJo0aK62t5cLoeenp66et7B7wOA1157rWb7unXr0N3dPa6UZ8Xko/n/V/1jNk3Z5kgfIeeEEJV6qVDsKqZB0T0jAUo0eKwi/NGXKyMVN8J7U7aXUqmXCsWukoiZiFo6LFPHou40Fs5OwaAUQgj/HxmtIn4rKmX4KhS7hqEPLSqn6wTUX09aKuI7ZWgq4/eYY47BI488gmw2G267//77QQjBUUcdNeT7DjnkECQSCfzmN78Jt7muiwceeADHHHPMbh2zYjeiSQM4MH17MyXEIgZiER2G6j+pUOwRElG5GA/aHhXLLnSiYUZbDBo0uIyBaHJxQFQhlEIxYZgGRSphYXZXDO1JC5qmgVANlqHD0InqX69Q7GY0SONYpxqoer5NGZoqP23NmjW4/fbbceGFF+KCCy7A9u3bcc0112DNmjWYNWtWuN8555yDLVu24MEHHwQAWJaFCy64ADfccAM6Ojqw33774Y477sDAwADOP//8yTocxS4iF9QahAByJQca0bBorkxhT8WVmqxCsScwdNn2YVNPHh7jKDse9u5ug+XEQKgG09DDXsq6ikIpFBNOZzqKjnQUlGgwVJqzQrFHMQ3iO5smeySKiaKpjN90Oo3bbrsNX/rSl3DhhRciHo/j9NNPx6WXXlqzH+ccbJDc/4c+9CEIIXDrrbeir68PS5cuxS233IK99tprTx6CYgLR/GiSEAL5kosl89sb1vkqFIrdS2c6is09ebgex757tWPezCR2bpIOKlMnqh+sQqFQKKYsyvCdWjSV8QvI3rw/+MEPht3n9ttvr9umaRouuOACXHDBBbtpZIo9DdHkdS2UXMQiOmZ1xCZ7SArFtKQjHcGBizqhaRpmtEVBVN2TQqFQKBSKFkQTo5XGmmYsX74cruti5syZo26arJhYOBdwXAYBKaQzmtYbtm1jx44dIETVQ7USQghwzjFz5sy6ft2K5kTda62JJgSimoZEMgndMCZ7OIpR4nkeMpmMvN8mezCKsSEEoh0dsJT4asugnm+tR2DO/uIXv8D+VW38GtF0kd9mwXVdCCFQLpcneygTTiaTAYCm718s+05KFVmdErjOyBPQwMAAOOd+rfDU8usEqf5T0RkTHJvj90ScKrTKvTYe1L3WmjDG4ACgAMig8qFWZ0rfb5kMPM+bsr9JYOrebwBAXReeut9ahqn6fJvK95rm6wS1tbWNuK8yfodg7ty58DwPd99992QPZcI59dRTAQA///nPJ3kkE8+pp54Kz/Pw/e9/f7KHMuGce+65ADBiWUArcu6550LTNNx3332TPZQJRd1rrYm611oTdb+1Jup+a03U/dZ6TOV7DQDa2towe/bsEfdTxu8w6LqOrq6uyR7GhGOaJgBM2WMzTXPElIdWJB6PA8CUPrap9ptU91prou611kTdb62Jut9aE3W/tR5T+V4bC0qiU6FQKBQKhUKhUCgUUx5l/CoUCoVCoVAoFAqFYsqjjF+FQqFQKBQKhUKhUEx5lPGrUCgUCoVCoVAoFIopjzJ+FQqFQqFQKBQKhUIx5dHEVGpgpVAoFAqFQqFQKBQKRQNU5FehUCgUCoVCoVAoFFMeZfwqFAqFQqFQKBQKhWLKo4xfhUKhUCgUCoVCoVBMeZTxq1AoFAqFQqFQKBSKKY8yfhUKhUKhUCgUCoVCMeVRxu8gXn31VXzgAx/AypUrcdRRR+Gaa66B4ziTPawJ4+c//zlOOeUULF++HIcffjg++MEPolwuT/awxsT69evxuc99DieffDIOOOAAnHTSSTWv5/N53HDDDTj99NNx6KGH4sgjj8RHPvIRvPTSS5M04tEz0rEBQKlUwte+9jWsXr0aK1aswHHHHYdvf/vb8DxvEkY8On7zm9/gox/9KI455hisXLkSJ598Mn72s59hKLH5hx56CEuWLGl4/M3GH//4R7z//e/Hm970JixbtgyrV6/GVVddhVwuV7Pf7373O7zrXe/C8uXLcdxxx+Huu++epBGPntEem23buO6667Bq1SosW7YMb3nLW/CVr3xlkkY9dgqFAo455hgsWbIE//rXvwC09jxSTaNjA1pzHgGAe+65B0uWLKn756tf/WrD/VtpLgFGfka34jwSMNKxteI8ctZZZzX8PS5ZsgS/+tWvWnoeGenYgNadRwDg4YcfxhlnnIGDDz4YRx99NC655BJs3LhxyP1baS75/e9/j1NPPRXLli3Dsccei+uvvx6Msbr9Wnk+2RX0yR5AM5HJZHDOOedg4cKFuOGGG7B9+3ZcffXVKJfL+NznPjfZw9tlvvWtb+G73/0uPvKRj2DlypXo7+/Ho48+2vCGaGZeeeUV/PGPf8SKFSvAOa8zoLZs2YKf/OQnePe7341PfOITsG0bt956K84880zcfffdWLx48SSNfGRGOjYA+OIXv4gHHngAn/zkJ7F48WI89dRTuP7661EqlXDppZdOwqhH5gc/+AHmzp2Lyy67DO3t7XjkkUfw3//939i2bRsuuuiimn3L5TK+/OUvo6ura5JGOzYGBgZw0EEH4ayzzkJbWxteeeUV3HDDDXjllVdw6623AgAef/xxXHTRRTj99NPx2c9+Fn/7299w+eWXIx6P4/jjj5/kIxia0Rwb5xwf+9jHsHHjRlx00UWYN28etmzZgtdee22SRz96vvnNb9bNg608j1TT6NiA1pxHqvne976HZDIZ/j1r1qy6fVptLhnpGd2q8wgw8rG16jxyxRVXIJ/P12y77bbb8MADD+CII45o6XlkpGMDWnceeeyxx3DRRRfhlFNOwaWXXoqBgQFcd911OO+883DfffchEonU7N9Kc8lTTz2Fj33sYzjxxBPxyU9+EmvXrsU3vvENlEol/Od//me4XyvPJ7uMUIR8+9vfFitXrhT9/f3htjvvvFMsXbpUbNu2bfIGNgG8+uqr4oADDhB/+MMfJnsouwxjLPzv//zP/xQnnnhizeuFQkEUi8Wabfl8XrzxjW8UX/ziF/fIGMfLSMfGGBMrVqwQ119/fc32T3/602L16tV7ZIzjobe3t27bf/3Xf4lDDjmk5piFEOIb3/iGeN/73tfw+FuFn/zkJ2K//fYL543zzjtPnHnmmTX7fPKTnxQnnHDCZAxvlxh8bHfddZd4wxveILZv3z7JIxsfa9euFStXrhR33HGH2G+//cQzzzwjhGjteSRgqGNr1XlECCHuvvtusd9++zWcUwbTSnPJaJ7RrTqPjObYWn0eqWbVqlXiQx/6kBBiaswj1VQfWyvPI//93/8tVq1aJTjn4bZHH31U7LfffuIf//hH3f6tNJecd9554tRTT63Zdsstt4gDDzxQ9PT01OzXivPJRKDSnqv405/+hCOOOAJtbW3hthNOOAGcc/z1r3+dvIFNAPfccw/mzZuHY489drKHsssQMvzPNhaLIRqN1myLx+OYP38+duzYsTuHtsuMdGxCCHieVxPxAIBkMjlkCnEz0NHRUbdt6dKlyOfzKBaL4bYNGzbg+9//Pv7rv/5rTw5vwgnmENd14TgOHnvssTpP6jve8Q68+uqr2LRp0ySMcPxUHxsA/PSnP8Xxxx+PmTNnTuKoxs+VV16JNWvWYO+9967Z3srzSMBQx9aq88hYaLW5ZKRndCvPI6NZf7T6PBLwxBNPYNOmTXjnO98JYGrMIwGDj62V5xHP8xCPx6FpWrgtOI7BY2+1ueSFF17AUUcdVbPt6KOPhuu6+Mtf/gKgteeTiUAZv1WsW7cOixYtqtmWSqUwY8YMrFu3bpJGNTE8/fTT2G+//fDNb34TRxxxBJYtW4Y1a9bg6aefnuyh7RGy2SxeeeWVuuvbalBKcdppp+H//u//8Mwzz6BQKOCRRx7Bvffei/e///2TPbwx8c9//hOzZs1CIpEIt/3P//wPTj75ZOy///6TOLLxwRiDbdt47rnncNNNN2HVqlWYN28eNmzYANd16357QbpbK8wtQx2b67p4/vnn0d3djU9/+tNYuXIlDj74YFxyySXo6emZ7GGPyP3334+XX34ZF1544aj2b6V5ZLhjmwrzyEknnYSlS5di9erV+M53vlOX2t1qc8lIz+hWnkdGOrZWn0eq+eUvf4lYLIbVq1cPuU8rzSPVDD62Vp5HTjvtNLz66qv40Y9+hFwuh40bN+LrX/86DjjgABxyyCE1+7baXGLbNkzTrNkW/P3qq68CaO35ZCJQNb9VZLNZpFKpuu3pdBqZTGYSRjRx9PT04Nlnn8XLL7+MK664AtFoFN/+9rdx3nnn4YEHHkBnZ+dkD3G38r//+7/QNA3/9m//NtlD2WWuuOIKXHHFFTjjjDPCbRdccAE+8IEPTOKoxsbjjz+OX//61zX1J7/73e/w5JNP4v7775/EkY2ft771rdi+fTsA4M1vfjO+9rWvAUA4dwyeW4K/W2FuGerYBgYG4Louvvvd7+Kwww7DjTfeiL6+Pvzv//4vLr74Ytx5552TOexhKZVKuPrqq3HppZfWOGCGo1XmkdEcW6vOIzNmzMDFF1+MFStWQNM0/O53v8M3vvENbN++PdTmaMW5ZKRndCvPIyMdG+e8ZeeRajzPw29+8xusWrUKsVhsyP1aZR6pZqhja9V55NBDD8WNN96IT33qU/jiF78IQGajfe973wOlNNyvFeeSBQsW4JlnnqnZ9tRTTwGozBOtPJ9MBMr4nSYIIVAsFnHdddeF3qsVK1Zg1apV+L//+z9ccsklkzzC3cfdd9+Nu+66C1dffTVmz5492cPZZb761a/iD3/4A6688kosXLgQTz31FG666SakUil88IMfnOzhjci2bdtw6aWX4vDDD8fZZ58NQHoqv/zlL+Piiy9umCLdCtx8880olUpYu3YtvvWtb+EjH/kIvv/970/2sCaEoY6Ncw5ApvHdeOONoXe5q6sLH/jAB/Doo4+GwijNxre+9S10dnbi3e9+96j2b6V5ZDTH1qrzyJvf/Ga8+c1vDv8++uijYVkWbrvtNnzkIx9BOp1uyblkpGf00UcfPckjHD8jHduaNWsAtOY8Us1f//pX9PX1DasG3ErzSDVDHVurziNPPPEEPv3pT+M973kP3vKWt2BgYADf/OY38eEPfxg//vGPEYlEWnZd8t73vheXX345brvtNpx88smh4FW1UT/dUcZvFalUqq6FByA9IOl0ehJGNHGkUim0tbXVpG20tbXhgAMOwNq1aydxZLuXP/7xj/jc5z6Hj33sYzj11FMnezi7zMsvv4xbb70V3/rWt7Bq1SoAwGGHHQbP83DddddhzZo1o45iTQbZbBYf+tCH0NbWhhtuuCGscb7ttttACMGJJ56IbDYLQKbCcc6RzWYRiUTq0niajeDeOvjgg7F8+XKcfPLJePDBB7HPPvsAQN3cEhxnK8wtQx3bscceC03TcMghh9Rcnze+8Y2glGLt2rVNuWjdvHkzbr31Vtx0003hdQlqz4vFIgqFAuLxeLh/K80jozm2YJ9WnUcGc8IJJ+DWW2/FCy+8gJdeeqkl55KRntEnnngigNacR0Y6tlQq1ZLzyGB++ctfoq2tbUhHRSvNI4NpdGytvB658sor8aY3vQmXXXZZuG3lypV4y1vegnvvvRdnnnlmy65LTjvtNLz88su45ppr8OUvfxmGYeCiiy7CbbfdFtbUB/NFK84nE4EyfqtYtGhRXZ57LpdDT09Py9VmDGafffbBhg0bGr5m2/YeHs2e4amnnsIll1yCU045ZcpEtgNHxdKlS2u2H3DAAXAcB9u3b2/ah025XMYFF1yAXC6Hn/zkJzUiGevWrcP69esbLnAOO+wwfP7zn2+pFLElS5bAMAxs2LABq1atgmEYWLduXU3EKphrWm1uqT62aDSKuXPnDrlvs84tmzZtguu6+PCHP1z32tlnn40VK1bgrrvuAtB688hoju3cc88F0JrzyEi06lwy0jN6/vz5LTuPjHRsrTqPVFMul/HQQw/hXe96FwzDqHu91eaRaoY6tlZej7z66qt1ddmzZ89Ge3t7+Ftt1bmEEILPfvazuPjii7F582Z0d3fD8zxce+21WLFiBQC09HwyESjjt4pjjjkG3/72t2tqf++//34QQuqU01qNt771rbjnnnvwwgsvhBNVf38/nnvuuXAhNJVYu3YtLrjgArzpTW/CF77whckezoQRLBCee+45zJkzJ9z+7LPPQtM0dHd3T9bQhsXzPHziE5/AunXr8KMf/aiuJ+eHPvShOk/4zTffjNdeew1XXXUVFi5cuAdHu+s8/fTTcF0X8+bNg2maOPzww/Hb3/4W55xzTrjPr3/9ayxevBjz5s2bxJGOnepjA+Tccv/998O2bViWBQD429/+BsYYDjzwwMkc6pAsXboUP/zhD2u2vfDCC7jqqqvwhS98AcuXLwfQmvPIaI7N8zwArTePDMWvf/1rUEpxwAEHYN68eS05l4z0jG7leWQ0649WnEeq+d3vfodisRgqIVfTivNINUMdW6uuRwCgu7sbzz//fM22zZs3o7+/PzyuVl+XJJPJMNviuuuuw7x583DkkUcCQEvPJxOBMn6rWLNmDW6//XZceOGFuOCCC7B9+3Zcc801WLNmTd1ivdV429vehuXLl+PjH/84Lr30UliWhZtvvhmmaeK9733vZA9vTJRKJfzxj38EICerfD4fihG88Y1vhBAC559/PizLwjnnnINnn302fG8ikQjTUJuRkY5t2bJlWLZsGa644gr09vZi/vz5eOaZZ3DzzTfj3e9+d11LhWbhC1/4An7/+9/jsssuQz6fD8UXAOklXrx4cagyGPDzn/8c27dvx+GHH76HRzs2LrroIixbtgxLlixBJBLBiy++iFtuuQVLlizB2972NgDARz/6UZx99tn4/Oc/jxNOOAGPPfYYfvnLX+Laa6+d5NEPz2iO7fzzz8e9996Lj33sYzj77LPR19eHr33ta3jDG96AN73pTZN8BI1JpVJD/q4OPPBAHHjggejt7W3JeWQ0x8YYa8l5BJC/t8MPPxxLliwBADz88MO46667cPbZZ2PGjBmYMWNGS84lo3lGt+o8Mppja8V5pJr77rsP3d3deMMb3lCzvVXnkWqGOrZWXY8Acr3/5S9/GVdeeSVWrVqFgYGBUCvhhBNOAICWXZc888wz+Pvf/46lS5eiXC7jd7/7He69915897vfran7bdX5ZCLQRLM349rDvPrqq/jSl76EJ598EvF4HCeffDIuvfTSpszrHyt9fX246qqr8Pvf/x6u6+LQQw/FZz7zmZaYfKvZtGnTkG0EgohHIKQ0mDe+8Y24/fbbd9vYdpWRju3www9HT08PrrvuOjzyyCPo7e3F7NmzcdJJJ+FDH/oQIpHIHh7x6Fi1ahU2b97c8LWHH364oZfxsssuw7PPPotf/vKXu3t4u8TNN9+MX//619iwYQOEEJg7dy7e/va34/zzz69J+Xr44YfxjW98A6+99hq6u7vx4Q9/GKeffvokjnxkRntsL7zwAr785S/j6aefRjQaxerVq3HZZZc1VM9vVh577DGcffbZ+NnPfobly5eHfzei2eeRwQw+NgAtOY8Aslbvz3/+M7Zt2wbOORYuXIgzzjgDZ511Vk3PzmpaZS4ZzTO6FecRYHTH1qrzSCaTwVFHHYVzzjkH//Ef/1HzWqvPI8MdG9C684gQAnfeeSfuuOMObNy4EfF4HCtXrsSll15aZ/BW0wpzyQsvvIArrrgCr7zyCgApLnfJJZfg4IMPrtu3VeeTXUUZvwqFQqFQKBQKhUKhmPKQyR6AQqFQKBQKhUKhUCgUuxtl/CoUCoVCoVAoFAqFYsqjjF+FQqFQKBQKhUKhUEx5lPGrUCgUCoVCoVAoFIopjzJ+FQqFQqFQKBQKhUIx5VHGr0KhUCgUCoVCoVAopjzK+FUoFAqFQqFQKBQKxZRHGb8KhUKhUCgUCoVCoZjyKONXoVAoFFOCs846C2edddakff+SJUvwxS9+cdK+f7Q89thjWLJkCR577LHJHkoNhUIBRxxxBH7xi19M9lAmlPe85z245pprJnsYCoVCoQCgT/YAFAqFQjG9WLJkyYj7XHTRRbj44ot36Xu2b9+Ou+66C29729uwdOnSXfqsZueyyy7Dz3/+8xH3O/XUU3HqqafugRGNnR/+8IeIx+M48cQTw2033HADbrzxRjz66KPo6Oioe8+qVauw77774jvf+c6eHOqY+NCHPoT/+I//wAc+8AHMmDFjsoejUCgU0xpl/CoUCoVijzJcFOzGG2/Ehg0bcNBBB435c2+55Zaav3fs2IEbb7wRc+fOnfLG75lnnokjjjgi/HvTpk24/vrrceaZZ+INb3hDuH3+/PlYsWIFnnnmGRiGMRlDbYjruvjhD3+Ic889F5TSyR7OhLJ69WokEgn8+Mc/xiWXXDLZw1EoFIppjTJ+FQqFQrFHOfnkkxtu/+lPf4oNGzbgrLPOwrHHHjvmzzVNc1eH1vTYtg3DMEBIbdXSwQcfjIMPPjj8+1//+heuv/56rFy5suH5tixrt491LPzhD39AX18fTjjhhMkeyqgoFouIxWKj2pcQguOOOw733nsvPv7xj0PTtN08OoVCoVAMhar5VSgUCsWk88orr+DKK6/EAQccgE9/+tM1r3HO8YMf/AAnnngili9fjiOPPBKf+9znkMlkavarrvl97LHHcPrppwMAPvOZz2DJkiVYsmQJ7rnnnnD/H/3oR1i9ejUOOuggnH766Xj88ccb1g07joPrr78eb3/727Fs2TIce+yxuOaaa+A4TsNj+cUvfoHjjjsOy5cvx2mnnYZ//OMfdfts374dn/nMZ3DkkUdi2bJlOPHEE/Gzn/2sZp+gNvdXv/oVrr32Wrz5zW/GihUrkM/nR3lWG9Oo5vess87CSSedhBdffBHvf//7sWLFCrz97W/H/fffDwD4+9//jjPOOAMHHXQQjjvuODzyyCPjOqaheOihhzB37lzMnz9/l44NkIbp1VdfjWOPPRbLli3Dcccdh1tuuQVCiHCfTZs21f0eApYsWYIbbrgh/PuGG27AkiVLsHbtWnzqU5/CYYcdhve+970AgJ6eHnzmM5/BMcccg2XLluHoo4/GRz/6UWzatKnmM4888khs3rwZL7zwwi4fn0KhUCjGj4r8KhQKhWJSKZVK+MQnPgFCCL7+9a/XRXA/97nP4ec//zlOO+00nHXWWdi0aRN+9KMf4fnnn8cdd9zRMH138eLF+PjHP16X+nvIIYcAAH784x/ji1/8Ig499FCce+652Lx5My688EKkUinMnj07/BzOOT760Y/in//8J97znvdg8eLFePnll3Hbbbfh9ddfxze/+c2a7/3HP/6BX//61zjrrLNgmibuuOMOfPCDH8RPf/pT7LfffgCAnTt34j3veQ80TcP73vc+dHR04E9/+hMuv/xy5PN5nHvuuTWf+c1vfhOGYeD888+H4zi7LV05k8ngIx/5CN7xjnfg+OOPxx133IFPfvKT4Jzjy1/+MtasWYOTTjoJt9xyCz7+8Y/jD3/4AxKJxLiOaTBPPvkkDjzwwGHH1gjOec3fQgh89KMfDZ0fS5cuxZ///Gdcc8012L59Oz772c+O7aRUcckll2DBggW49NJLQ0P64osvxtq1a/H+978fc+fORV9fH/76179i69atmDdvXvjeZcuWAQCeeOIJHHDAAeMeg0KhUCh2DWX8KhQKhWJS+dKXvoS1a9fiK1/5Cvbee++a1x5//HH89Kc/xVe/+lW8853vDLcffvjh+OAHP4j777+/ZntAV1cXjjnmmIapv47j4LrrrsPy5ctx2223Qdflo3DJkiW47LLLaozf++67D4888ghuv/12HHrooeH2fffdF1dccQWeeOKJ0KAGgJdffhl33313aOyceOKJOP7443H99dfjxhtvBABce+21YIzhvvvuQ3t7OwDg3/7t3/DJT34SN954I9asWYNIJBJ+pm3buPvuu2u27Q527NiBr33tazjppJMAyGjlCSecgE996lO48847sWLFCgDSsXD++efjgQcewGmnnTauY6rG8zxs2LABq1evHnJsxx9//JCvVQuoPfzww/jb3/6GT3ziE/joRz8KAHjf+96Hj3/84/jhD3+I97///eOOLu+///742te+Fv6dzWbx5JNP4tOf/jTOP//8cPsFF1xQ995Zs2bBMAysXbt2XN+tUCgUiolBpT0rFAqFYtK47777cPfdd+Pkk0/GKaecUvf6/fffj2QyiaOOOgp9fX3hPwceeCBisdi42vU8++yzGBgYwHve857Q8AWAd77znUin03Xfv3jxYixatKjm+9/0pjcBQN33H3zwwaHhCwDd3d1YvXo1/vKXv4AxBiEEHnjgAaxatQpCiJrPPProo5HL5fDcc8/VfOYpp5yy2w1fAIjFYjVKy4sWLUIqlcLixYtDwxdA+N8bN24EgHEdUzWZTAZCCKRSqSH3ueGGG/D973+/7p+urq6a/f70pz+BUlqXun7eeedBCIE//elPoz8hg1izZk3N35FIBIZh4O9///uQkelq0uk0+vv7x/39CoVCodh1VORXoVAoFJPC66+/jiuuuAILFy7EFVdc0XCf9evXI5fL1SgZV9Pb2zvm792yZQsA1EUAdV3H3Llz677/1VdfHfX3L1iwoG6fhQsXolQqoa+vD4QQZLNZ/OQnP8FPfvKThp/Z19dX83d1+uzuZPbs2XViTMlksiYSHmwDZOQTkOMd6zE1oromdzCHHnpow1ZHg4W7Nm/ejJkzZ4bp2AGLFy8OXx8vg6+DaZr493//d3zlK1/BUUcdhRUrVuAtb3kLTjnllIYtjYQQSuxKoVAoJhll/CoUCoVij+M4Di699FK4rotrr70W8Xi84X6cc3R2duKrX/1qw9cbGUQTCecc++23Hz7zmc80fH2wYTiazwOAd73rXUP22x3cB3lPRH0BDNliaKjtgbE6nmOqJp1OQ9O00JjeEwxlhDLGhnxPI4Xsc889F6tWrcJDDz2Ev/zlL7juuutw880347bbbqur7c1ms2FKuEKhUCgmB2X8KhQKhWKP85WvfAXPP/88Lr/88mEFgObPn49HH30UhxxyyJiNwKEMnO7ubgDAhg0bwvRlQNaebt68ucZQmz9/Pl588UUcccQRo4rarV+/vm7b66+/jmg0Ghrq8XgcnHMceeSRYzqeZqWjo2OXjknXdcyfP79OIXk8zJ07F48++ijy+XxN9HfdunXh6wDC9PbBBneQFTAW5s+fj/POOw/nnXceXn/9dZxyyim49dZbaxw227dvh+u6YQRaoVAoFJODqvlVKBQKxR7lwQcfxP/93/9h1apVOPvss4fd94QTTgBjrE5VGZDG6nDRwmg0CqDewFm2bBna2tpw1113wfO8cPt9991XV7t5wgknYPv27bjrrrvqPr9cLqNYLNZse/LJJ2vqW7du3YqHH34YRx11FCiloJTiuOOOw29/+1u8/PLLdZ85mvTgZmMijmnlypV49tlnd3ksxxxzDBhj+NGPflSz/Qc/+AE0TcMxxxwDAEgkEmhvb8fjjz9es9+Pf/zjUX9XqVSCbds12+bPn494PF7XBis4tupezAqFQqHY86jIr0KhUCj2GDt27MDll18OSimOOOII3HvvvQ33mz9/Pg4++GC88Y1vxJlnnonvfOc7eOGFF3DUUUfBMAy8/vrruP/++3H55ZcPqQQ8f/58pFIp3HnnnYjH44jFYjjooIOw11574eKLL8aXvvQlnHPOOTjhhBOwefNm3HPPPXV1wCeffDJ+85vf4IorrsBjjz2GQw45BIwxrFu3Dvfffz++973vYfny5eH+++23H84///yaVkeAbIkT8KlPfQqPPfYY3vOe9+CMM87APvvsg0wmg+eeew6PPvoo/v73v+/qad7j7OoxrV69Gvfeey9ee+21OsXvsbBq1SocfvjhuPbaa8Mo/l//+lc8/PDDOOecc2qu7xlnnIGbb74Zl19+OZYtW4bHH38cr7322qi/6/XXX8e5556L448/Hvvssw8opXjooYewc+fOGuEwAHjkkUfQ3d2t2hwpFArFJKOMX4VCoVDsMV577bUwuvo///M/Q+536qmnhlGyL37xi1i2bBnuvPNOXHvttaCUYu7cuXjXu95V02ZoMIZh4Oqrr8bXv/51fP7zn4fnebjqqquw11574f3vfz+EEPj+97+Pr3zlK9h///3xrW99C1deeWVNbSchBDfddBN+8IMf4N5778WDDz6IaDSKefPm4ayzzqoz1A477DCsXLkSN910E7Zs2YJ99tkHV111Ffbff/9wn66uLvz0pz/FTTfdhAcffBB33HEH2trasM8+++Df//3fx3VeJ5tdPaa3vvWtaG9vx29+8xt87GMfG/c4CCH41re+heuvvx6//vWvcc8992Du3Ln49Kc/jfPOO69m3wsvvBB9fX347W9/i9/85jc45phj8L3vfW9IcbPBzJ49GyeeeCIeffRR/OIXvwClFIsWLcI3vvENHHfcceF+nHP89re/xemnn64ErxQKhWKS0cRw8ooKhUKhUEwTOOc44ogj8Pa3vx1XXnnlZA9n2nHTTTfhnnvuwQMPPDCkyFYr8tBDD+FTn/oUHnzwQcycOXOyh6NQKBTTGlXzq1AoFIpph23bda11/r//7//DwMAA3vjGN07SqKY35557LorFIn71q19N9lAmlO9+97t43/vepwxfhUKhaAJU5FehUCgU047HHnsMV111FY4//ni0tbXh+eefx89+9jMsXrwYd999N0zTnOwhKhQKhUKhmGBUza9CoVAoph1z587F7NmzcfvttyOTySCdTuPkk0/Gv//7vyvDV6FQKBSKKYqK/CoUCoVCoVAoFAqFYsqjan4VCoVCoVAoFAqFQjHlUcavQqFQKBQKhUKhUCimPMr4VSgUCoVCoVAoFArFlEcZvwqFQqFQKBQKhUKhmPIo41ehUCgUCoVCoVAoFFMeZfwqFAqFQqFQKBQKhWLKo4xfhUKhUCgUCoVCoVBMeZTxq1AoFAqFQqFQKBSKKc//D7F4i0MOmVKLAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1133.33x466.667 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "start_hour = 0\n",
+    "end_hour = 96\n",
+    "\n",
+    "# Generate plot from Ethoscopy\n",
+    "fig = df.remove('id', *dead_flies).t_filter(start_time=start_hour, end_time=end_hour).plot_overtime(variable='asleep', avg_window=30, grids=True)\n",
+    "\n",
+    "# Extract the main axis from the figure\n",
+    "ax = fig.axes[0]\n",
+    "\n",
+    "# Add shading stimulus shading\n",
+    "# Draw a vertical span from ZT 48 to ZT 72\n",
+    "ax.axvspan(48, 72, color='#ff4c4c', alpha=0.3, zorder=1)\n",
+    "\n",
+    "# Set custom labels\n",
+    "ax.set_xlabel(\"Zeitgeber Time (Hours)\", fontsize=12)\n",
+    "ax.set_ylabel(\"Fraction of Time Asleep\", fontsize=12)\n",
+    "\n",
+    "# Show plot\n",
+    "fig.show()\n",
+    "\n",
+    "# Save as a high-resolution PNG\n",
+    "plt.savefig(\"atr_60D_pulse.png\", dpi=600, bbox_inches='tight')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "e17495bc-5b2e-427e-8a2c-2d744b91ecb4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--- Individual Fly Sleep (Baseline: 0h to 48h, Averaged per day) ---\n",
+      "             Fly_Label  Base_Sleep_24h  Base_Day_12h  Base_Night_12h\n",
+      "ETHOSCOPE_130 - Fly 01        8.330556      4.204380        6.063889\n",
+      "ETHOSCOPE_130 - Fly 02       12.173611      6.252469        8.802778\n",
+      "ETHOSCOPE_130 - Fly 03       10.338889      3.417526        8.497222\n",
+      "ETHOSCOPE_130 - Fly 04        6.101389      2.692143        4.650000\n",
+      "ETHOSCOPE_130 - Fly 05        7.873611      2.944611        6.286111\n",
+      "ETHOSCOPE_130 - Fly 06        6.755556      4.423358        4.370833\n",
+      "ETHOSCOPE_130 - Fly 07        9.901389      4.214684        7.629167\n",
+      "ETHOSCOPE_130 - Fly 08       10.769444      4.382138        8.406944\n",
+      "ETHOSCOPE_130 - Fly 09        9.006944      3.887505        6.911111\n",
+      "ETHOSCOPE_130 - Fly 10       10.034722      4.972091        7.354167\n",
+      "ETHOSCOPE_130 - Fly 11        9.383333      4.309278        7.061111\n",
+      "ETHOSCOPE_130 - Fly 12        9.583333      3.408330        7.745833\n",
+      "ETHOSCOPE_130 - Fly 13       11.769444      5.400644        8.859722\n",
+      "ETHOSCOPE_130 - Fly 14        9.820833      6.928234        6.088889\n",
+      "ETHOSCOPE_130 - Fly 15        9.693056      4.338561        7.355556\n",
+      "ETHOSCOPE_130 - Fly 16        9.266667      4.708208        6.730556\n",
+      "ETHOSCOPE_130 - Fly 17        4.447222      1.889581        3.429167\n",
+      "ETHOSCOPE_130 - Fly 18        5.704167      3.008378        4.083333\n",
+      "ETHOSCOPE_130 - Fly 19        8.129167      1.185567        7.490278\n",
+      "ETHOSCOPE_302 - Fly 01        5.820833      3.735592        3.727778\n",
+      "... (Showing first 20 rows)\n",
+      "\n",
+      "--- Grand Summary Statistics (Baseline: 0h to 48h) ---\n",
+      "Total Flies Analyzed: n = 38\n",
+      "\n",
+      "[ OVERALL SLEEP (Scaled to 24h Baseline Average) ]\n",
+      "Mean ± SEM:   8.78 ± 0.33 hours\n",
+      "Median:       9.11 hours\n",
+      "\n",
+      "[ DAY TIME (ZT 0-12, Averaged to 12h blocks) ]\n",
+      "Mean ± SEM:   3.80 ± 0.22 hours\n",
+      "Median:       4.14 hours\n",
+      "\n",
+      "[ NIGHT TIME (ZT 12-24, Averaged to 12h blocks) ]\n",
+      "Mean ± SEM:   6.69 ± 0.26 hours\n",
+      "Median:       6.98 hours\n"
+     ]
+    }
+   ],
+   "source": [
+    "# BASELINE\n",
+    "\n",
+    "# Define baseline time period\n",
+    "start_hour = 0\n",
+    "end_hour = 48\n",
+    "\n",
+    "# Filter the dataset to ONLY include data within specific baseline window\n",
+    "base_df = df.t_filter(start_time=start_hour, end_time=end_hour).copy()\n",
+    "\n",
+    "# Exclude dead flies\n",
+    "base_df = base_df[~base_df.index.get_level_values('id').isin(dead_flies)]\n",
+    "\n",
+    "# Calculate Overall 24h Baseline Average\n",
+    "sleep_hours = (base_df.groupby('id')['asleep'].sum() * 10) / 3600\n",
+    "\n",
+    "# (72 - 0) / 24 evaluates to exactly 3 days. \n",
+    "# Dividing total sleep by 3 to average the 72 hours into a single 24-hour metric\n",
+    "days_tracked = (end_hour - start_hour) / 24 \n",
+    "base_overall = (sleep_hours / days_tracked).reset_index(name='Base_Sleep_24h')\n",
+    "\n",
+    "# Calculate Day/Night 12h Baseline Averages\n",
+    "base_df['zt_hour'] = (base_df['t'] / 3600) % 24\n",
+    "base_df['Phase'] = np.where(base_df['zt_hour'] < 12, 'Day', 'Night')\n",
+    "\n",
+    "base_phase = base_df.groupby(['id', 'Phase']).agg(\n",
+    "    total_sleep_epochs=('asleep', 'sum'),\n",
+    "    total_tracking_epochs=('t', 'count')\n",
+    ").reset_index()\n",
+    "\n",
+    "# Tracking_Hours will be ~24 for Day and ~24 for Night \n",
+    "# Dividing sleep by tracking hours and multiplying by 12 averages it to a single 12h block.\n",
+    "base_phase['Sleep_Hours'] = (base_phase['total_sleep_epochs'] * 10) / 3600\n",
+    "base_phase['Tracking_Hours'] = (base_phase['total_tracking_epochs'] * 10) / 3600\n",
+    "base_phase['Base_Sleep_12h'] = (base_phase['Sleep_Hours'] / base_phase['Tracking_Hours']) * 12\n",
+    "\n",
+    "base_pivot = base_phase.pivot(index='id', columns='Phase', values='Base_Sleep_12h').reset_index()\n",
+    "# Rename columns\n",
+    "base_pivot.columns = ['id', 'Base_Day_12h', 'Base_Night_12h']\n",
+    "\n",
+    "# Merge and clean up data\n",
+    "merged_df = pd.merge(base_overall, base_pivot, on='id')\n",
+    "\n",
+    "merged_df['Machine'] = merged_df['id'].map(df.meta['machine_name'])\n",
+    "merged_df['Tube'] = merged_df['id'].apply(lambda x: str(x).split('|')[-1])\n",
+    "merged_df['Fly_Label'] = merged_df['Machine'] + \" - Fly \" + merged_df['Tube']\n",
+    "\n",
+    "clean_table = merged_df.dropna(subset=['Machine']).sort_values(by=['Machine', 'Tube'])\n",
+    "baseline_stats = clean_table[['Fly_Label', 'Base_Sleep_24h', 'Base_Day_12h', 'Base_Night_12h']]\n",
+    "\n",
+    "# PRINT RESULTS\n",
+    "print(f\"--- Individual Fly Sleep (Baseline: {start_hour}h to {end_hour}h, Averaged per day) ---\")\n",
+    "print(baseline_stats.head(20).to_string(index=False)) \n",
+    "print(\"... (Showing first 20 rows)\\n\")\n",
+    "\n",
+    "print(f\"--- Grand Summary Statistics (Baseline: {start_hour}h to {end_hour}h) ---\")\n",
+    "print(f\"Total Flies Analyzed: n = {len(baseline_stats)}\")\n",
+    "\n",
+    "# 1. OVERALL 24H STATS\n",
+    "print(\"\\n[ OVERALL SLEEP (Scaled to 24h Baseline Average) ]\")\n",
+    "print(f\"Mean ± SEM:   {baseline_stats['Base_Sleep_24h'].mean():.2f} ± {baseline_stats['Base_Sleep_24h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {baseline_stats['Base_Sleep_24h'].median():.2f} hours\")\n",
+    "\n",
+    "# 2. DAY TIME STATS\n",
+    "print(f\"\\n[ DAY TIME (ZT 0-12, Averaged to 12h blocks) ]\")\n",
+    "print(f\"Mean ± SEM:   {baseline_stats['Base_Day_12h'].mean():.2f} ± {baseline_stats['Base_Day_12h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {baseline_stats['Base_Day_12h'].median():.2f} hours\")\n",
+    "\n",
+    "# 3. NIGHT TIME STATS\n",
+    "print(f\"\\n[ NIGHT TIME (ZT 12-24, Averaged to 12h blocks) ]\")\n",
+    "print(f\"Mean ± SEM:   {baseline_stats['Base_Night_12h'].mean():.2f} ± {baseline_stats['Base_Night_12h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {baseline_stats['Base_Night_12h'].median():.2f} hours\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "9e18111e-18d4-4001-8685-cc5f0e69170f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--- Individual Fly Sleep (Stimulus: 48h to 72h) ---\n",
+      "             Fly_Label  Stim_Sleep_24h  Stim_Day_12h  Stim_Night_12h\n",
+      "ETHOSCOPE_130 - Fly 01        2.975000      2.286111        0.688889\n",
+      "ETHOSCOPE_130 - Fly 02        6.741667      3.083333        3.658333\n",
+      "ETHOSCOPE_130 - Fly 03        1.472222      1.280556        0.191667\n",
+      "ETHOSCOPE_130 - Fly 04        4.850000      1.758333        3.091667\n",
+      "ETHOSCOPE_130 - Fly 05        1.886111      1.800000        0.086111\n",
+      "ETHOSCOPE_130 - Fly 06        4.158333      2.783333        1.375000\n",
+      "ETHOSCOPE_130 - Fly 07        3.380556      1.758333        1.622222\n",
+      "ETHOSCOPE_130 - Fly 08        8.033333      4.669444        3.363889\n",
+      "ETHOSCOPE_130 - Fly 09        2.952778      2.863889        0.088889\n",
+      "ETHOSCOPE_130 - Fly 10       11.197222      5.591667        5.605556\n",
+      "ETHOSCOPE_130 - Fly 11        4.472222      3.925000        0.547222\n",
+      "ETHOSCOPE_130 - Fly 12        1.333333      0.000000        1.333333\n",
+      "ETHOSCOPE_130 - Fly 13        9.127778      6.138889        2.988889\n",
+      "ETHOSCOPE_130 - Fly 14        1.886111      0.341667        1.544444\n",
+      "ETHOSCOPE_130 - Fly 15        3.272222      1.908333        1.363889\n",
+      "ETHOSCOPE_130 - Fly 16        2.900000      2.505556        0.394444\n",
+      "ETHOSCOPE_130 - Fly 17        7.744444      3.736111        4.008333\n",
+      "ETHOSCOPE_130 - Fly 18        0.350000      0.183333        0.166667\n",
+      "ETHOSCOPE_130 - Fly 19        0.727778      0.316667        0.411111\n",
+      "ETHOSCOPE_302 - Fly 01        0.194444      0.000000        0.194444\n",
+      "... (Showing first 20 rows)\n",
+      "\n",
+      "--- Grand Summary Statistics (Stimulus: 48h to 72h) ---\n",
+      "Total Flies Analyzed: n = 38\n",
+      "\n",
+      "[ OVERALL SLEEP (24h Stimulus Block) ]\n",
+      "Mean ± SEM:   4.92 ± 0.59 hours\n",
+      "Median:       4.40 hours\n",
+      "\n",
+      "[ DAY TIME (ZT 0-12 during Stimulus) ]\n",
+      "Mean ± SEM:   2.34 ± 0.29 hours\n",
+      "Median:       2.27 hours\n",
+      "\n",
+      "[ NIGHT TIME (ZT 12-24 during Stimulus) ]\n",
+      "Mean ± SEM:   2.58 ± 0.36 hours\n",
+      "Median:       1.89 hours\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Define stimulus time period\n",
+    "start_hour = 48\n",
+    "end_hour = 72\n",
+    "\n",
+    "# Filter the dataset to ONLY include data within specific stimulus window\n",
+    "stim_df = df.t_filter(start_time=start_hour, end_time=end_hour).copy()\n",
+    "\n",
+    "# Exclude dead flies\n",
+    "stim_df = stim_df[~stim_df.index.get_level_values('id').isin(dead_flies)]\n",
+    "\n",
+    "# Calculate Overall 24h Stimulus Average\n",
+    "sleep_hours = (stim_df.groupby('id')['asleep'].sum() * 10) / 3600\n",
+    "days_tracked = (end_hour - start_hour) / 24 \n",
+    "stim_overall = (sleep_hours / days_tracked).reset_index(name='Stim_Sleep_24h')\n",
+    "\n",
+    "# Calculate Day/Night 12h Stimulus Averages\n",
+    "stim_df['zt_hour'] = (stim_df['t'] / 3600) % 24\n",
+    "stim_df['Phase'] = np.where(stim_df['zt_hour'] < 12, 'Day', 'Night')\n",
+    "\n",
+    "stim_phase = stim_df.groupby(['id', 'Phase']).agg(\n",
+    "    total_sleep_epochs=('asleep', 'sum'),\n",
+    "    total_tracking_epochs=('t', 'count')\n",
+    ").reset_index()\n",
+    "\n",
+    "# Tracking_Hours will now be ~12 for Day and ~12 for Night\n",
+    "# Dividing sleep by tracking hours and multiplying by 12 averages it to a single 12h block.\n",
+    "stim_phase['Sleep_Hours'] = (stim_phase['total_sleep_epochs'] * 10) / 3600\n",
+    "stim_phase['Tracking_Hours'] = (stim_phase['total_tracking_epochs'] * 10) / 3600\n",
+    "stim_phase['Stim_Sleep_12h'] = (stim_phase['Sleep_Hours'] / stim_phase['Tracking_Hours']) * 12\n",
+    "\n",
+    "stim_pivot = stim_phase.pivot(index='id', columns='Phase', values='Stim_Sleep_12h').reset_index()\n",
+    "# Rename columns \n",
+    "stim_pivot.columns = ['id', 'Stim_Day_12h', 'Stim_Night_12h']\n",
+    "\n",
+    "# Merge and clean up data\n",
+    "merged_df = pd.merge(stim_overall, stim_pivot, on='id')\n",
+    "\n",
+    "merged_df['Machine'] = merged_df['id'].map(df.meta['machine_name'])\n",
+    "merged_df['Tube'] = merged_df['id'].apply(lambda x: str(x).split('|')[-1])\n",
+    "merged_df['Fly_Label'] = merged_df['Machine'] + \" - Fly \" + merged_df['Tube']\n",
+    "\n",
+    "clean_table = merged_df.dropna(subset=['Machine']).sort_values(by=['Machine', 'Tube'])\n",
+    "stim_stats = clean_table[['Fly_Label', 'Stim_Sleep_24h', 'Stim_Day_12h', 'Stim_Night_12h']]\n",
+    "\n",
+    "# PRINT RESULTS\n",
+    "print(f\"--- Individual Fly Sleep (Stimulus: {start_hour}h to {end_hour}h) ---\")\n",
+    "print(stim_stats.head(20).to_string(index=False)) \n",
+    "print(\"... (Showing first 20 rows)\\n\")\n",
+    "\n",
+    "print(f\"--- Grand Summary Statistics (Stimulus: {start_hour}h to {end_hour}h) ---\")\n",
+    "print(f\"Total Flies Analyzed: n = {len(stim_stats)}\")\n",
+    "\n",
+    "# 1. OVERALL 24H STATS\n",
+    "print(\"\\n[ OVERALL SLEEP (24h Stimulus Block) ]\")\n",
+    "print(f\"Mean ± SEM:   {stim_stats['Stim_Sleep_24h'].mean():.2f} ± {stim_stats['Stim_Sleep_24h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {stim_stats['Stim_Sleep_24h'].median():.2f} hours\")\n",
+    "\n",
+    "# 2. DAY TIME STATS\n",
+    "print(f\"\\n[ DAY TIME (ZT 0-12 during Stimulus) ]\")\n",
+    "print(f\"Mean ± SEM:   {stim_stats['Stim_Day_12h'].mean():.2f} ± {stim_stats['Stim_Day_12h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {stim_stats['Stim_Day_12h'].median():.2f} hours\")\n",
+    "\n",
+    "# 3. NIGHT TIME STATS\n",
+    "print(f\"\\n[ NIGHT TIME (ZT 12-24 during Stimulus) ]\")\n",
+    "print(f\"Mean ± SEM:   {stim_stats['Stim_Night_12h'].mean():.2f} ± {stim_stats['Stim_Night_12h'].sem():.2f} hours\")\n",
+    "print(f\"Median:       {stim_stats['Stim_Night_12h'].median():.2f} hours\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "18d0e98f-6db2-4ffd-a20f-798737e82a06",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--- 24h Total Statistical Analysis ---\n",
+      "Shapiro-Wilk P-value (Normality of differences): 0.3132\n",
+      "Result: Data is normal. Used Paired T-test.\n",
+      "P-value: 1.7753e-08\n",
+      "Significance: ****\n",
+      "\n",
+      "--- Daytime Statistical Analysis ---\n",
+      "Shapiro-Wilk P-value (Normality of differences): 0.3388\n",
+      "Result: Data is normal. Used Paired T-test.\n",
+      "P-value: 1.2184e-05\n",
+      "Significance: ****\n",
+      "\n",
+      "--- Nighttime Statistical Analysis ---\n",
+      "Shapiro-Wilk P-value (Normality of differences): 0.2020\n",
+      "Result: Data is normal. Used Paired T-test.\n",
+      "P-value: 2.3083e-13\n",
+      "Significance: ****\n"
+     ]
+    }
+   ],
+   "source": [
+    "# STATISTICS\n",
+    "\n",
+    "# Merge Baseline and Stimulus data on Fly_Label\n",
+    "paired_df = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
+    "\n",
+    "def run_paired_stats(df, base_col, stim_col, label):\n",
+    "    # Calculate the differences for the paired test\n",
+    "    diffs = df[stim_col] - df[base_col]\n",
+    "    \n",
+    "    # 2. Shapiro-Wilk Test for Normality\n",
+    "    _, p_shapiro = shapiro(diffs)\n",
+    "    \n",
+    "    print(f\"\\n--- {label} Statistical Analysis ---\")\n",
+    "    print(f\"Shapiro-Wilk P-value (Normality of differences): {p_shapiro:.4f}\")\n",
+    "    \n",
+    "    # 3. Determine Test: If P > 0.05, data is normal (use t-test). If P < 0.05, use Wilcoxon.\n",
+    "    if p_shapiro > 0.05:\n",
+    "        stat, p_val = ttest_rel(df[base_col], df[stim_col])\n",
+    "        print(f\"Result: Data is normal. Used Paired T-test.\")\n",
+    "    else:\n",
+    "        stat, p_val = wilcoxon(df[base_col], df[stim_col])\n",
+    "        print(f\"Result: Data is not normal. Used Wilcoxon Signed-Rank test.\")\n",
+    "        \n",
+    "    print(f\"P-value: {p_val:.4e}\")\n",
+    "    if p_val < 0.0001: print(\"Significance: ****\")\n",
+    "    elif p_val < 0.001: print(\"Significance: ***\")\n",
+    "    elif p_val < 0.01: print(\"Significance: **\")\n",
+    "    elif p_val < 0.05: print(\"Significance: *\")\n",
+    "    else: print(\"Significance: ns\")\n",
+    "\n",
+    "# Run for all three metrics\n",
+    "run_paired_stats(paired_df, 'Base_Sleep_24h', 'Stim_Sleep_24h', '24h Total')\n",
+    "run_paired_stats(paired_df, 'Base_Day_12h', 'Stim_Day_12h', 'Daytime')\n",
+    "run_paired_stats(paired_df, 'Base_Night_12h', 'Stim_Night_12h', 'Nighttime')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "52a71c00-97dd-4ef8-a7a6-1a6ea55f78b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 1. PREPARE DATA & CALCULATE STATS\n",
+    "combined = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
+    "\n",
+    "# Calculate the paired statistics for the brackets\n",
+    "p_values = {}\n",
+    "metrics = {\n",
+    "    '24h': ('Base_Sleep_24h', 'Stim_Sleep_24h'),\n",
+    "    'Day': ('Base_Day_12h', 'Stim_Day_12h'),\n",
+    "    'Night': ('Base_Night_12h', 'Stim_Night_12h')\n",
+    "}\n",
+    "\n",
+    "for phase, (base_col, stim_col) in metrics.items():\n",
+    "    diffs = combined[stim_col] - combined[base_col]\n",
+    "    _, p_shapiro = shapiro(diffs)\n",
+    "    \n",
+    "    if p_shapiro > 0.05:\n",
+    "        _, p_val = ttest_rel(combined[base_col], combined[stim_col])\n",
+    "    else:\n",
+    "        _, p_val = wilcoxon(combined[base_col], combined[stim_col])\n",
+    "    p_values[phase] = p_val\n",
+    "\n",
+    "plot_df = combined.melt(id_vars=['Fly_Label'], var_name='Variable', value_name='Hours')\n",
+    "plot_df['Condition'] = plot_df['Variable'].apply(lambda x: '24h' if '24h' in x else ('Day' if 'Day' in x else 'Night'))\n",
+    "plot_df['State'] = plot_df['Variable'].apply(lambda x: 'Baseline' if 'Base' in x else 'Stimulus')\n",
+    "\n",
+    "# 2. GENERATE PLOT\n",
+    "plt.figure(figsize=(7, 6))\n",
+    "sns.set_theme(style=\"ticks\")\n",
+    "\n",
+    "order = ['24h', 'Day', 'Night']\n",
+    "hue_order = ['Baseline', 'Stimulus']\n",
+    "palette = {'Baseline': '#cccccc', 'Stimulus': '#ff4c4c'}\n",
+    "\n",
+    "# Boxplot\n",
+    "sns.boxplot(\n",
+    "    data=plot_df, x='Condition', y='Hours', hue='State', \n",
+    "    order=order, hue_order=hue_order, palette=palette,\n",
+    "    width=0.6, gap=0.2, boxprops={'edgecolor': 'black', 'alpha': 0.7},\n",
+    "    medianprops={'color': 'black', 'linewidth': 1.5}, showfliers=False\n",
+    ")\n",
+    "\n",
+    "# Stripplot\n",
+    "sns.stripplot(\n",
+    "    data=plot_df, x='Condition', y='Hours', hue='State', \n",
+    "    order=order, hue_order=hue_order, dodge=True,\n",
+    "    palette=['black', 'black'], alpha=0.5, size=4, jitter=0.05,\n",
+    "    legend=False\n",
+    ")\n",
+    "\n",
+    "# 3. ADD MEDIAN LABELS\n",
+    "ax = plt.gca()\n",
+    "medians = plot_df.groupby(['Condition', 'State'], sort=False)['Hours'].median()\n",
+    "\n",
+    "offsets = {'Baseline': -0.4, 'Stimulus': 0.4}\n",
+    "\n",
+    "for i, cond in enumerate(order):\n",
+    "    for state in hue_order:\n",
+    "        val = medians[(cond, state)]\n",
+    "        ax.text(i + offsets[state], val, f\"{val:.1f}h\", \n",
+    "                ha='center', va='bottom', fontsize=10)\n",
+    "\n",
+    "# 4. ADD SIGNIFICANCE BRACKETS\n",
+    "y_max = plot_df['Hours'].max()\n",
+    "y_line = y_max + 1.0  \n",
+    "h = 0.4               \n",
+    "\n",
+    "for i, cond in enumerate(order):\n",
+    "    p = p_values[cond]\n",
+    "    \n",
+    "    if p < 0.0001: star = '****'\n",
+    "    elif p < 0.001: star = '***'\n",
+    "    elif p < 0.01: star = '**'\n",
+    "    elif p < 0.05: star = '*'\n",
+    "    else: star = 'ns'\n",
+    "    \n",
+    "    x1, x2 = i - 0.2, i + 0.2\n",
+    "    plt.plot([x1, x1, x2, x2], [y_line, y_line+h, y_line+h, y_line], lw=1.5, c='k')\n",
+    "    plt.text((x1+x2)*.5, y_line+h, star, ha='center', va='bottom', fontsize=12)\n",
+    "\n",
+    "# 5. FORMATTING\n",
+    "sns.despine()\n",
+    "plt.ylabel('Sleep Duration (Hours)', fontsize=12)\n",
+    "plt.xlabel('')\n",
+    "plt.xlim(-0.6, 2.5) \n",
+    "\n",
+    "plt.ylim(0, max(18, y_line + h + 1.5)) \n",
+    "\n",
+    "# Legend moved outside the plot to the right\n",
+    "plt.legend(title='', frameon=False, loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "plt.savefig(\"plot_atr_60D_pulse.png\", dpi=600, bbox_inches='tight')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "83159d99-663d-4bed-a270-d58744697b60",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--- Delta Sleep (Stimulus - Baseline) per Fly ---\n",
+      "             Fly_Label  Delta_24h  Delta_Day  Delta_Night\n",
+      "ETHOSCOPE_130 - Fly 01  -5.355556  -1.918268    -5.375000\n",
+      "ETHOSCOPE_130 - Fly 02  -5.431944  -3.169136    -5.144444\n",
+      "ETHOSCOPE_130 - Fly 03  -8.866667  -2.136970    -8.305556\n",
+      "ETHOSCOPE_130 - Fly 04  -1.251389  -0.933809    -1.558333\n",
+      "ETHOSCOPE_130 - Fly 05  -5.987500  -1.144611    -6.200000\n",
+      "ETHOSCOPE_130 - Fly 06  -2.597222  -1.640024    -2.995833\n",
+      "ETHOSCOPE_130 - Fly 07  -6.520833  -2.456351    -6.006944\n",
+      "ETHOSCOPE_130 - Fly 08  -2.736111   0.287306    -5.043056\n",
+      "ETHOSCOPE_130 - Fly 09  -6.054167  -1.023616    -6.822222\n",
+      "ETHOSCOPE_130 - Fly 10   1.162500   0.619576    -1.748611\n",
+      "ETHOSCOPE_130 - Fly 11  -4.911111  -0.384278    -6.513889\n",
+      "ETHOSCOPE_130 - Fly 12  -8.250000  -3.408330    -6.412500\n",
+      "ETHOSCOPE_130 - Fly 13  -2.641667   0.738244    -5.870833\n",
+      "ETHOSCOPE_130 - Fly 14  -7.934722  -6.586567    -4.544444\n",
+      "ETHOSCOPE_130 - Fly 15  -6.420833  -2.430227    -5.991667\n",
+      "ETHOSCOPE_130 - Fly 16  -6.366667  -2.202652    -6.336111\n",
+      "ETHOSCOPE_130 - Fly 17   3.297222   1.846530     0.579167\n",
+      "ETHOSCOPE_130 - Fly 18  -5.354167  -2.825045    -3.916667\n",
+      "ETHOSCOPE_130 - Fly 19  -7.401389  -0.868900    -7.079167\n",
+      "ETHOSCOPE_302 - Fly 01  -5.626389  -3.735592    -3.533333\n",
+      "ETHOSCOPE_302 - Fly 02  -2.469444  -1.103987    -3.059722\n",
+      "ETHOSCOPE_302 - Fly 03  -5.173611  -0.460215    -4.959722\n",
+      "ETHOSCOPE_302 - Fly 04  -0.930556   0.111704    -3.231944\n",
+      "ETHOSCOPE_302 - Fly 05  -5.545833  -2.714315    -4.025000\n",
+      "ETHOSCOPE_302 - Fly 07  -9.468056  -4.694898    -6.837500\n",
+      "ETHOSCOPE_302 - Fly 08   1.900000   0.862354    -0.909722\n",
+      "ETHOSCOPE_302 - Fly 09  -8.577778  -4.734559    -5.925000\n",
+      "ETHOSCOPE_302 - Fly 10  -3.951389  -0.273420    -4.645833\n",
+      "ETHOSCOPE_302 - Fly 11  -6.609722  -3.008856    -5.918056\n",
+      "ETHOSCOPE_302 - Fly 12   1.312500  -0.742952     0.202778\n",
+      "ETHOSCOPE_302 - Fly 13  -3.479167  -2.209806    -2.580556\n",
+      "ETHOSCOPE_302 - Fly 14  -0.563889  -0.801971    -1.552778\n",
+      "ETHOSCOPE_302 - Fly 15  -3.473611  -1.221051    -3.809722\n",
+      "ETHOSCOPE_302 - Fly 16   1.912500  -0.453268     0.331944\n",
+      "ETHOSCOPE_302 - Fly 17  -2.919444  -0.842370    -4.343056\n",
+      "ETHOSCOPE_302 - Fly 18   0.127778   0.966598    -2.220833\n",
+      "ETHOSCOPE_302 - Fly 19  -1.648611  -1.157461    -1.126389\n",
+      "ETHOSCOPE_302 - Fly 20  -1.713889   0.538269    -2.912500\n",
+      "\n",
+      "==================================================\n",
+      "\n",
+      "--- Average Change (Delta) across all flies ---\n",
+      "Delta_24h: -3.86 ± 0.54 hours\n",
+      "Delta_Day: -1.46 ± 0.29 hours\n",
+      "Delta_Night: -4.11 ± 0.37 hours\n"
+     ]
+    }
+   ],
+   "source": [
+    "#DELTA\n",
+    "\n",
+    "# 1. Ensure have the merged paired data\n",
+    "combined = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
+    "\n",
+    "# 2. Calculate the Delta (Stimulus - Baseline) for each fly\n",
+    "combined['Delta_24h'] = combined['Stim_Sleep_24h'] - combined['Base_Sleep_24h']\n",
+    "combined['Delta_Day'] = combined['Stim_Day_12h'] - combined['Base_Day_12h']\n",
+    "combined['Delta_Night'] = combined['Stim_Night_12h'] - combined['Base_Night_12h']\n",
+    "\n",
+    "# 3. Print the Delta for each individual fly\n",
+    "print(\"--- Delta Sleep (Stimulus - Baseline) per Fly ---\")\n",
+    "delta_table = combined[['Fly_Label', 'Delta_24h', 'Delta_Day', 'Delta_Night']]\n",
+    "print(delta_table.to_string(index=False))\n",
+    "print(\"\\n\" + \"=\"*50 + \"\\n\")\n",
+    "\n",
+    "# 4. Calculate and print the group averages\n",
+    "print(\"--- Average Change (Delta) across all flies ---\")\n",
+    "avg_delta = delta_table[['Delta_24h', 'Delta_Day', 'Delta_Night']].mean()\n",
+    "sem_delta = delta_table[['Delta_24h', 'Delta_Day', 'Delta_Night']].sem()\n",
+    "\n",
+    "for metric in ['Delta_24h', 'Delta_Day', 'Delta_Night']:\n",
+    "    print(f\"{metric}: {avg_delta[metric]:.2f} ± {sem_delta[metric]:.2f} hours\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "9213acfd-7208-4f46-aa8a-a3561ad8fe66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#export to csv\n",
+    "delta_table['Condition'] = 'Red'\n",
+    "delta_table.to_csv('delta_60D_phase7.csv', index=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}