diff --git a/Cost_Reduction/CostReduction_exploration_mode.ipynb b/Cost_Reduction/CostReduction_exploration_mode.ipynb
index f6800e6..d97e72e 100644
--- a/Cost_Reduction/CostReduction_exploration_mode.ipynb
+++ b/Cost_Reduction/CostReduction_exploration_mode.ipynb
@@ -21,7 +21,14 @@
    "id": "40096a23-ff7b-4541-b710-9f0a9f9a595d",
    "metadata": {},
    "source": [
-    "# <center>Cost Reduction Framework for Nuclear Reactor Power Plants</center>\n"
+    "# <center>Cost Reduction Framework for Nuclear Reactor Power Plants</center>\n",
+    "This notebook demonstrates the impact of various levers on the cost of a nuclear power plant.\n",
+    "\n",
+    "It begins with a baseline cost sheet, followed by an estimation of how each lever affects the overall cost. Levers that may influence the cost include design completion, modularity, interest rates,.etc\n",
+    "\n",
+    "This notebook is useful for exploring how these levers contribute to cost overruns or savings, step by step. Users who are only interested in the final result can utilize the last section, which includes a Python function that calculates the impact of all the levers in a single step.\n",
+    "\n",
+    "For a detailed understanding of the details behind this framework, please check [this report](https://www.osti.gov/biblio/2361138)"
    ]
   },
   {
@@ -37,16 +44,33 @@
    "execution_count": 1,
    "id": "12fb6329-dc95-493f-ba1d-86235e71b512",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n\\n\\n# RB_safety_related is false all the way or True all the way\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import pandas as pd\n",
     "import numpy as np\n",
-    "from src import prettify, update_high_level_costs, ITC_reduction_factor\n",
+    "from src import prettify, update_high_level_costs, ITC_reduction_factor, update_cons_duration, sum_lab_hrs, update_cons_duration_2\n",
     "\n",
     "import warnings\n",
     "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
     "\n",
-    "pd.set_option('display.max_rows', None)"
+    "pd.set_option('display.max_rows', None)\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
+    "\n",
+    "# RB_safety_related is false all the way or True all the way\n",
+    "\"\"\""
    ]
   },
   {
@@ -67,659 +91,659 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_f9b61 caption {\n",
+       "#T_bc600 caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_f9b61_row0_col0, #T_f9b61_row0_col1, #T_f9b61_row0_col2, #T_f9b61_row0_col3, #T_f9b61_row0_col4, #T_f9b61_row0_col5, #T_f9b61_row0_col6, #T_f9b61_row12_col0, #T_f9b61_row12_col1, #T_f9b61_row12_col2, #T_f9b61_row12_col3, #T_f9b61_row12_col4, #T_f9b61_row12_col5, #T_f9b61_row12_col6, #T_f9b61_row29_col0, #T_f9b61_row29_col1, #T_f9b61_row29_col2, #T_f9b61_row29_col3, #T_f9b61_row29_col4, #T_f9b61_row29_col5, #T_f9b61_row29_col6, #T_f9b61_row39_col0, #T_f9b61_row39_col1, #T_f9b61_row39_col2, #T_f9b61_row39_col3, #T_f9b61_row39_col4, #T_f9b61_row39_col5, #T_f9b61_row39_col6, #T_f9b61_row47_col0, #T_f9b61_row47_col1, #T_f9b61_row47_col2, #T_f9b61_row47_col3, #T_f9b61_row47_col4, #T_f9b61_row47_col5, #T_f9b61_row47_col6, #T_f9b61_row54_col0, #T_f9b61_row54_col1, #T_f9b61_row54_col2, #T_f9b61_row54_col3, #T_f9b61_row54_col4, #T_f9b61_row54_col5, #T_f9b61_row54_col6, #T_f9b61_row55_col0, #T_f9b61_row55_col1, #T_f9b61_row55_col2, #T_f9b61_row55_col3, #T_f9b61_row55_col4, #T_f9b61_row55_col5, #T_f9b61_row55_col6, #T_f9b61_row56_col0, #T_f9b61_row56_col1, #T_f9b61_row56_col2, #T_f9b61_row56_col3, #T_f9b61_row56_col4, #T_f9b61_row56_col5, #T_f9b61_row56_col6, #T_f9b61_row57_col0, #T_f9b61_row57_col1, #T_f9b61_row57_col2, #T_f9b61_row57_col3, #T_f9b61_row57_col4, #T_f9b61_row57_col5, #T_f9b61_row57_col6, #T_f9b61_row58_col0, #T_f9b61_row58_col1, #T_f9b61_row58_col2, #T_f9b61_row58_col3, #T_f9b61_row58_col4, #T_f9b61_row58_col5, #T_f9b61_row58_col6, #T_f9b61_row59_col0, #T_f9b61_row59_col1, #T_f9b61_row59_col2, #T_f9b61_row59_col3, #T_f9b61_row59_col4, #T_f9b61_row59_col5, #T_f9b61_row59_col6, #T_f9b61_row60_col0, #T_f9b61_row60_col1, #T_f9b61_row60_col2, #T_f9b61_row60_col3, #T_f9b61_row60_col4, #T_f9b61_row60_col5, #T_f9b61_row60_col6, #T_f9b61_row61_col0, #T_f9b61_row61_col1, #T_f9b61_row61_col2, #T_f9b61_row61_col3, #T_f9b61_row61_col4, #T_f9b61_row61_col5, #T_f9b61_row61_col6, #T_f9b61_row62_col0, #T_f9b61_row62_col1, #T_f9b61_row62_col2, #T_f9b61_row62_col3, #T_f9b61_row62_col4, #T_f9b61_row62_col5, #T_f9b61_row62_col6, #T_f9b61_row63_col0, #T_f9b61_row63_col1, #T_f9b61_row63_col2, #T_f9b61_row63_col3, #T_f9b61_row63_col4, #T_f9b61_row63_col5, #T_f9b61_row63_col6 {\n",
+       "#T_bc600_row0_col0, #T_bc600_row0_col1, #T_bc600_row0_col2, #T_bc600_row0_col3, #T_bc600_row0_col4, #T_bc600_row0_col5, #T_bc600_row0_col6, #T_bc600_row12_col0, #T_bc600_row12_col1, #T_bc600_row12_col2, #T_bc600_row12_col3, #T_bc600_row12_col4, #T_bc600_row12_col5, #T_bc600_row12_col6, #T_bc600_row29_col0, #T_bc600_row29_col1, #T_bc600_row29_col2, #T_bc600_row29_col3, #T_bc600_row29_col4, #T_bc600_row29_col5, #T_bc600_row29_col6, #T_bc600_row39_col0, #T_bc600_row39_col1, #T_bc600_row39_col2, #T_bc600_row39_col3, #T_bc600_row39_col4, #T_bc600_row39_col5, #T_bc600_row39_col6, #T_bc600_row47_col0, #T_bc600_row47_col1, #T_bc600_row47_col2, #T_bc600_row47_col3, #T_bc600_row47_col4, #T_bc600_row47_col5, #T_bc600_row47_col6, #T_bc600_row54_col0, #T_bc600_row54_col1, #T_bc600_row54_col2, #T_bc600_row54_col3, #T_bc600_row54_col4, #T_bc600_row54_col5, #T_bc600_row54_col6, #T_bc600_row55_col0, #T_bc600_row55_col1, #T_bc600_row55_col2, #T_bc600_row55_col3, #T_bc600_row55_col4, #T_bc600_row55_col5, #T_bc600_row55_col6, #T_bc600_row56_col0, #T_bc600_row56_col1, #T_bc600_row56_col2, #T_bc600_row56_col3, #T_bc600_row56_col4, #T_bc600_row56_col5, #T_bc600_row56_col6, #T_bc600_row57_col0, #T_bc600_row57_col1, #T_bc600_row57_col2, #T_bc600_row57_col3, #T_bc600_row57_col4, #T_bc600_row57_col5, #T_bc600_row57_col6, #T_bc600_row58_col0, #T_bc600_row58_col1, #T_bc600_row58_col2, #T_bc600_row58_col3, #T_bc600_row58_col4, #T_bc600_row58_col5, #T_bc600_row58_col6, #T_bc600_row59_col0, #T_bc600_row59_col1, #T_bc600_row59_col2, #T_bc600_row59_col3, #T_bc600_row59_col4, #T_bc600_row59_col5, #T_bc600_row59_col6, #T_bc600_row60_col0, #T_bc600_row60_col1, #T_bc600_row60_col2, #T_bc600_row60_col3, #T_bc600_row60_col4, #T_bc600_row60_col5, #T_bc600_row60_col6, #T_bc600_row61_col0, #T_bc600_row61_col1, #T_bc600_row61_col2, #T_bc600_row61_col3, #T_bc600_row61_col4, #T_bc600_row61_col5, #T_bc600_row61_col6, #T_bc600_row62_col0, #T_bc600_row62_col1, #T_bc600_row62_col2, #T_bc600_row62_col3, #T_bc600_row62_col4, #T_bc600_row62_col5, #T_bc600_row62_col6, #T_bc600_row63_col0, #T_bc600_row63_col1, #T_bc600_row63_col2, #T_bc600_row63_col3, #T_bc600_row63_col4, #T_bc600_row63_col5, #T_bc600_row63_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
-       "#T_f9b61_row64_col0, #T_f9b61_row64_col1, #T_f9b61_row64_col2, #T_f9b61_row64_col3, #T_f9b61_row64_col4, #T_f9b61_row64_col5, #T_f9b61_row64_col6, #T_f9b61_row65_col0, #T_f9b61_row65_col1, #T_f9b61_row65_col2, #T_f9b61_row65_col3, #T_f9b61_row65_col4, #T_f9b61_row65_col5, #T_f9b61_row65_col6, #T_f9b61_row66_col0, #T_f9b61_row66_col1, #T_f9b61_row66_col2, #T_f9b61_row66_col3, #T_f9b61_row66_col4, #T_f9b61_row66_col5, #T_f9b61_row66_col6, #T_f9b61_row67_col0, #T_f9b61_row67_col1, #T_f9b61_row67_col2, #T_f9b61_row67_col3, #T_f9b61_row67_col4, #T_f9b61_row67_col5, #T_f9b61_row67_col6, #T_f9b61_row68_col0, #T_f9b61_row68_col1, #T_f9b61_row68_col2, #T_f9b61_row68_col3, #T_f9b61_row68_col4, #T_f9b61_row68_col5, #T_f9b61_row68_col6 {\n",
+       "#T_bc600_row64_col0, #T_bc600_row64_col1, #T_bc600_row64_col2, #T_bc600_row64_col3, #T_bc600_row64_col4, #T_bc600_row64_col5, #T_bc600_row64_col6, #T_bc600_row65_col0, #T_bc600_row65_col1, #T_bc600_row65_col2, #T_bc600_row65_col3, #T_bc600_row65_col4, #T_bc600_row65_col5, #T_bc600_row65_col6, #T_bc600_row66_col0, #T_bc600_row66_col1, #T_bc600_row66_col2, #T_bc600_row66_col3, #T_bc600_row66_col4, #T_bc600_row66_col5, #T_bc600_row66_col6, #T_bc600_row67_col0, #T_bc600_row67_col1, #T_bc600_row67_col2, #T_bc600_row67_col3, #T_bc600_row67_col4, #T_bc600_row67_col5, #T_bc600_row67_col6, #T_bc600_row68_col0, #T_bc600_row68_col1, #T_bc600_row68_col2, #T_bc600_row68_col3, #T_bc600_row68_col4, #T_bc600_row68_col5, #T_bc600_row68_col6 {\n",
        "  font-weight: bold;\n",
        "  color: white;\n",
        "  background-color: white;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_f9b61\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> FOAK Capital Cost Summary - Baseline hypothetical well-executeed project <br><br> </caption>\n",
+       "<table id=\"T_bc600\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> FOAK Capital Cost Summary - Baseline hypothetical well-executeed project <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_f9b61_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_f9b61_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_f9b61_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_f9b61_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_f9b61_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_f9b61_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_f9b61_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_bc600_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_bc600_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_bc600_level0_col2\" class=\"col_heading level0 col2\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_bc600_level0_col3\" class=\"col_heading level0 col3\" >Site Material Cost</th>\n",
+       "      <th id=\"T_bc600_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_bc600_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_bc600_level0_col6\" class=\"col_heading level0 col6\" >Total Cost (USD)</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_f9b61_row0_col0\" class=\"data row0 col0\" >10</td>\n",
-       "      <td id=\"T_f9b61_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
-       "      <td id=\"T_f9b61_row0_col2\" class=\"data row0 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row0_col3\" class=\"data row0 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row0_col4\" class=\"data row0 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row0_col5\" class=\"data row0 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row0_col6\" class=\"data row0 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row1_col0\" class=\"data row1 col0\" >11</td>\n",
-       "      <td id=\"T_f9b61_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
-       "      <td id=\"T_f9b61_row1_col2\" class=\"data row1 col2\" >$ 11,000,000</td>\n",
-       "      <td id=\"T_f9b61_row1_col3\" class=\"data row1 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row1_col4\" class=\"data row1 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row1_col5\" class=\"data row1 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row1_col6\" class=\"data row1 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row2_col0\" class=\"data row2 col0\" >12</td>\n",
-       "      <td id=\"T_f9b61_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
-       "      <td id=\"T_f9b61_row2_col2\" class=\"data row2 col2\" >$ 1,598,891</td>\n",
-       "      <td id=\"T_f9b61_row2_col3\" class=\"data row2 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row2_col4\" class=\"data row2 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row2_col5\" class=\"data row2 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row2_col6\" class=\"data row2 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row3_col0\" class=\"data row3 col0\" >13</td>\n",
-       "      <td id=\"T_f9b61_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
-       "      <td id=\"T_f9b61_row3_col2\" class=\"data row3 col2\" >$ 24,382,988</td>\n",
-       "      <td id=\"T_f9b61_row3_col3\" class=\"data row3 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row3_col4\" class=\"data row3 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row3_col5\" class=\"data row3 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row3_col6\" class=\"data row3 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row4_col0\" class=\"data row4 col0\" >14</td>\n",
-       "      <td id=\"T_f9b61_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
-       "      <td id=\"T_f9b61_row4_col2\" class=\"data row4 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_f9b61_row4_col3\" class=\"data row4 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row4_col4\" class=\"data row4 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row4_col5\" class=\"data row4 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row4_col6\" class=\"data row4 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row5_col0\" class=\"data row5 col0\" >15</td>\n",
-       "      <td id=\"T_f9b61_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
-       "      <td id=\"T_f9b61_row5_col2\" class=\"data row5 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_f9b61_row5_col3\" class=\"data row5 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row5_col4\" class=\"data row5 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row5_col5\" class=\"data row5 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row5_col6\" class=\"data row5 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row6_col0\" class=\"data row6 col0\" >16</td>\n",
-       "      <td id=\"T_f9b61_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
-       "      <td id=\"T_f9b61_row6_col2\" class=\"data row6 col2\" >$ 3,972,186</td>\n",
-       "      <td id=\"T_f9b61_row6_col3\" class=\"data row6 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row6_col4\" class=\"data row6 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row6_col5\" class=\"data row6 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row6_col6\" class=\"data row6 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row7_col0\" class=\"data row7 col0\" >18</td>\n",
-       "      <td id=\"T_f9b61_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
-       "      <td id=\"T_f9b61_row7_col2\" class=\"data row7 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_f9b61_row7_col3\" class=\"data row7 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row7_col4\" class=\"data row7 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row7_col5\" class=\"data row7 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row7_col6\" class=\"data row7 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row8_col0\" class=\"data row8 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col1\" class=\"data row8 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col2\" class=\"data row8 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col3\" class=\"data row8 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col4\" class=\"data row8 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col5\" class=\"data row8 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row8_col6\" class=\"data row8 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row9_col0\" class=\"data row9 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
-       "      <td id=\"T_f9b61_row9_col2\" class=\"data row9 col2\" >$ 78,991,565</td>\n",
-       "      <td id=\"T_f9b61_row9_col3\" class=\"data row9 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row9_col4\" class=\"data row9 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row9_col5\" class=\"data row9 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row9_col6\" class=\"data row9 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row10_col0\" class=\"data row10 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
-       "      <td id=\"T_f9b61_row10_col2\" class=\"data row10 col2\" >$ 254</td>\n",
-       "      <td id=\"T_f9b61_row10_col3\" class=\"data row10 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row10_col4\" class=\"data row10 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row10_col5\" class=\"data row10 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row10_col6\" class=\"data row10 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_f9b61_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_f9b61_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_f9b61_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_f9b61_row13_col2\" class=\"data row13 col2\" >$ 244,678,343</td>\n",
-       "      <td id=\"T_f9b61_row13_col3\" class=\"data row13 col3\" >$ 64,350,801</td>\n",
-       "      <td id=\"T_f9b61_row13_col4\" class=\"data row13 col4\" >2,899,407 hrs</td>\n",
-       "      <td id=\"T_f9b61_row13_col5\" class=\"data row13 col5\" >$ 145,691,462</td>\n",
-       "      <td id=\"T_f9b61_row13_col6\" class=\"data row13 col6\" >$ 34,636,081</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_f9b61_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_f9b61_row14_col2\" class=\"data row14 col2\" >$ 145,108,928</td>\n",
-       "      <td id=\"T_f9b61_row14_col3\" class=\"data row14 col3\" >$ 57,583,605</td>\n",
-       "      <td id=\"T_f9b61_row14_col4\" class=\"data row14 col4\" >1,605,670 hrs</td>\n",
-       "      <td id=\"T_f9b61_row14_col5\" class=\"data row14 col5\" >$ 81,082,169</td>\n",
-       "      <td id=\"T_f9b61_row14_col6\" class=\"data row14 col6\" >$ 6,443,153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_f9b61_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_f9b61_row15_col2\" class=\"data row15 col2\" >$ 9,518,418</td>\n",
-       "      <td id=\"T_f9b61_row15_col3\" class=\"data row15 col3\" >$ 620,964</td>\n",
-       "      <td id=\"T_f9b61_row15_col4\" class=\"data row15 col4\" >102,399 hrs</td>\n",
-       "      <td id=\"T_f9b61_row15_col5\" class=\"data row15 col5\" >$ 5,280,509</td>\n",
-       "      <td id=\"T_f9b61_row15_col6\" class=\"data row15 col6\" >$ 3,616,945</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_f9b61_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_f9b61_row16_col2\" class=\"data row16 col2\" >$ 90,050,998</td>\n",
-       "      <td id=\"T_f9b61_row16_col3\" class=\"data row16 col3\" >$ 6,146,232</td>\n",
-       "      <td id=\"T_f9b61_row16_col4\" class=\"data row16 col4\" >1,191,337 hrs</td>\n",
-       "      <td id=\"T_f9b61_row16_col5\" class=\"data row16 col5\" >$ 59,328,783</td>\n",
-       "      <td id=\"T_f9b61_row16_col6\" class=\"data row16 col6\" >$ 24,575,983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_f9b61_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_f9b61_row17_col2\" class=\"data row17 col2\" >$ 661,334,797</td>\n",
-       "      <td id=\"T_f9b61_row17_col3\" class=\"data row17 col3\" >$ 559,862,844</td>\n",
-       "      <td id=\"T_f9b61_row17_col4\" class=\"data row17 col4\" >1,809,704 hrs</td>\n",
-       "      <td id=\"T_f9b61_row17_col5\" class=\"data row17 col5\" >$ 97,213,739</td>\n",
-       "      <td id=\"T_f9b61_row17_col6\" class=\"data row17 col6\" >$ 4,258,215</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_f9b61_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_f9b61_row18_col2\" class=\"data row18 col2\" >$ 238,844,021</td>\n",
-       "      <td id=\"T_f9b61_row18_col3\" class=\"data row18 col3\" >$ 189,802,947</td>\n",
-       "      <td id=\"T_f9b61_row18_col4\" class=\"data row18 col4\" >874,096 hrs</td>\n",
-       "      <td id=\"T_f9b61_row18_col5\" class=\"data row18 col5\" >$ 46,348,086</td>\n",
-       "      <td id=\"T_f9b61_row18_col6\" class=\"data row18 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_f9b61_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_f9b61_row19_col2\" class=\"data row19 col2\" >$ 197,558,121</td>\n",
-       "      <td id=\"T_f9b61_row19_col3\" class=\"data row19 col3\" >$ 167,738,159</td>\n",
-       "      <td id=\"T_f9b61_row19_col4\" class=\"data row19 col4\" >559,709 hrs</td>\n",
-       "      <td id=\"T_f9b61_row19_col5\" class=\"data row19 col5\" >$ 29,819,961</td>\n",
-       "      <td id=\"T_f9b61_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_f9b61_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_f9b61_row20_col2\" class=\"data row20 col2\" >$ 41,285,901</td>\n",
-       "      <td id=\"T_f9b61_row20_col3\" class=\"data row20 col3\" >$ 22,064,788</td>\n",
-       "      <td id=\"T_f9b61_row20_col4\" class=\"data row20 col4\" >314,387 hrs</td>\n",
-       "      <td id=\"T_f9b61_row20_col5\" class=\"data row20 col5\" >$ 16,528,125</td>\n",
-       "      <td id=\"T_f9b61_row20_col6\" class=\"data row20 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_f9b61_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_f9b61_row21_col2\" class=\"data row21 col2\" >$ 67,451,645</td>\n",
-       "      <td id=\"T_f9b61_row21_col3\" class=\"data row21 col3\" >$ 13,662,941</td>\n",
-       "      <td id=\"T_f9b61_row21_col4\" class=\"data row21 col4\" >767,077 hrs</td>\n",
-       "      <td id=\"T_f9b61_row21_col5\" class=\"data row21 col5\" >$ 41,345,409</td>\n",
-       "      <td id=\"T_f9b61_row21_col6\" class=\"data row21 col6\" >$ 12,443,295</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_f9b61_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_f9b61_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_f9b61_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_f9b61_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_f9b61_row23_col2\" class=\"data row23 col2\" >$ 25,655,316</td>\n",
-       "      <td id=\"T_f9b61_row23_col3\" class=\"data row23 col3\" >$ 8,372,438</td>\n",
-       "      <td id=\"T_f9b61_row23_col4\" class=\"data row23 col4\" >278,805 hrs</td>\n",
-       "      <td id=\"T_f9b61_row23_col5\" class=\"data row23 col5\" >$ 15,110,212</td>\n",
-       "      <td id=\"T_f9b61_row23_col6\" class=\"data row23 col6\" >$ 2,172,665</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_f9b61_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_f9b61_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_f9b61_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_f9b61_row26_col2\" class=\"data row26 col2\" >$ 1,517,766,756</td>\n",
-       "      <td id=\"T_f9b61_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_f9b61_row27_col2\" class=\"data row27 col2\" >$ 4,883</td>\n",
-       "      <td id=\"T_f9b61_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_f9b61_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_f9b61_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_f9b61_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_f9b61_row30_col2\" class=\"data row30 col2\" >$ 146,051,997</td>\n",
-       "      <td id=\"T_f9b61_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_f9b61_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_f9b61_row31_col2\" class=\"data row31 col2\" >$ 506,256,125</td>\n",
-       "      <td id=\"T_f9b61_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_f9b61_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_f9b61_row32_col2\" class=\"data row32 col2\" >$ 21,298,226</td>\n",
-       "      <td id=\"T_f9b61_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_f9b61_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_f9b61_row33_col2\" class=\"data row33 col2\" >$ 1,793,334</td>\n",
-       "      <td id=\"T_f9b61_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_f9b61_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_f9b61_row34_col2\" class=\"data row34 col2\" >$ 136,778,270</td>\n",
-       "      <td id=\"T_f9b61_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_f9b61_row36_col2\" class=\"data row36 col2\" >$ 812,177,951</td>\n",
-       "      <td id=\"T_f9b61_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_f9b61_row37_col2\" class=\"data row37 col2\" >$ 2,613</td>\n",
-       "      <td id=\"T_f9b61_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row37_col6\" class=\"data row37 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row38_col0\" class=\"data row38 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col1\" class=\"data row38 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col2\" class=\"data row38 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col3\" class=\"data row38 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col4\" class=\"data row38 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col5\" class=\"data row38 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row38_col6\" class=\"data row38 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row39_col0\" class=\"data row39 col0\" >50</td>\n",
-       "      <td id=\"T_f9b61_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
-       "      <td id=\"T_f9b61_row39_col2\" class=\"data row39 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row39_col3\" class=\"data row39 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row39_col4\" class=\"data row39 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row39_col5\" class=\"data row39 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row39_col6\" class=\"data row39 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row40_col0\" class=\"data row40 col0\" >51</td>\n",
-       "      <td id=\"T_f9b61_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
-       "      <td id=\"T_f9b61_row40_col2\" class=\"data row40 col2\" >$ 3,510,602</td>\n",
-       "      <td id=\"T_f9b61_row40_col3\" class=\"data row40 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row40_col4\" class=\"data row40 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row40_col5\" class=\"data row40 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row40_col6\" class=\"data row40 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row41_col0\" class=\"data row41 col0\" >52</td>\n",
-       "      <td id=\"T_f9b61_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
-       "      <td id=\"T_f9b61_row41_col2\" class=\"data row41 col2\" >$ 10,484,751</td>\n",
-       "      <td id=\"T_f9b61_row41_col3\" class=\"data row41 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row41_col4\" class=\"data row41 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row41_col5\" class=\"data row41 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row41_col6\" class=\"data row41 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row42_col0\" class=\"data row42 col0\" >54</td>\n",
-       "      <td id=\"T_f9b61_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
-       "      <td id=\"T_f9b61_row42_col2\" class=\"data row42 col2\" >$ 14,606,673</td>\n",
-       "      <td id=\"T_f9b61_row42_col3\" class=\"data row42 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row42_col4\" class=\"data row42 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row42_col5\" class=\"data row42 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row42_col6\" class=\"data row42 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row43_col0\" class=\"data row43 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col1\" class=\"data row43 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col2\" class=\"data row43 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col3\" class=\"data row43 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col4\" class=\"data row43 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col5\" class=\"data row43 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row43_col6\" class=\"data row43 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row44_col0\" class=\"data row44 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
-       "      <td id=\"T_f9b61_row44_col2\" class=\"data row44 col2\" >$ 28,602,027</td>\n",
-       "      <td id=\"T_f9b61_row44_col3\" class=\"data row44 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row44_col4\" class=\"data row44 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row44_col5\" class=\"data row44 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row44_col6\" class=\"data row44 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row45_col0\" class=\"data row45 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
-       "      <td id=\"T_f9b61_row45_col2\" class=\"data row45 col2\" >$ 92</td>\n",
-       "      <td id=\"T_f9b61_row45_col3\" class=\"data row45 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row45_col4\" class=\"data row45 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row45_col5\" class=\"data row45 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row45_col6\" class=\"data row45 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row46_col0\" class=\"data row46 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col1\" class=\"data row46 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col2\" class=\"data row46 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col3\" class=\"data row46 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col4\" class=\"data row46 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col5\" class=\"data row46 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row46_col6\" class=\"data row46 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row47_col0\" class=\"data row47 col0\" >60</td>\n",
-       "      <td id=\"T_f9b61_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
-       "      <td id=\"T_f9b61_row47_col2\" class=\"data row47 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row47_col3\" class=\"data row47 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row47_col4\" class=\"data row47 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row47_col5\" class=\"data row47 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row47_col6\" class=\"data row47 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row48_col0\" class=\"data row48 col0\" >62</td>\n",
-       "      <td id=\"T_f9b61_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
-       "      <td id=\"T_f9b61_row48_col2\" class=\"data row48 col2\" >$ 592,300,800</td>\n",
-       "      <td id=\"T_f9b61_row48_col3\" class=\"data row48 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row48_col4\" class=\"data row48 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row48_col5\" class=\"data row48 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row48_col6\" class=\"data row48 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row49_col0\" class=\"data row49 col0\" >-</td>\n",
-       "      <td id=\"T_f9b61_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
-       "      <td id=\"T_f9b61_row49_col2\" class=\"data row49 col2\" >$ 592,300,800</td>\n",
-       "      <td id=\"T_f9b61_row49_col3\" class=\"data row49 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row49_col4\" class=\"data row49 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row49_col5\" class=\"data row49 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row49_col6\" class=\"data row49 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row50_col0\" class=\"data row50 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
-       "      <td id=\"T_f9b61_row50_col2\" class=\"data row50 col2\" >$ 1,906</td>\n",
-       "      <td id=\"T_f9b61_row50_col3\" class=\"data row50 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row50_col4\" class=\"data row50 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row50_col5\" class=\"data row50 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row50_col6\" class=\"data row50 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row51_col0\" class=\"data row51 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col1\" class=\"data row51 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col2\" class=\"data row51 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col3\" class=\"data row51 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col4\" class=\"data row51 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col5\" class=\"data row51 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row51_col6\" class=\"data row51 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row52_col0\" class=\"data row52 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
-       "      <td id=\"T_f9b61_row52_col2\" class=\"data row52 col2\" >$ 1,596,758,321</td>\n",
-       "      <td id=\"T_f9b61_row52_col3\" class=\"data row52 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row52_col4\" class=\"data row52 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row52_col5\" class=\"data row52 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row52_col6\" class=\"data row52 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row53_col0\" class=\"data row53 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
-       "      <td id=\"T_f9b61_row53_col2\" class=\"data row53 col2\" >$ 5,138</td>\n",
-       "      <td id=\"T_f9b61_row53_col3\" class=\"data row53 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row53_col4\" class=\"data row53 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row53_col5\" class=\"data row53 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row53_col6\" class=\"data row53 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row54_col0\" class=\"data row54 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col1\" class=\"data row54 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col2\" class=\"data row54 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col3\" class=\"data row54 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col4\" class=\"data row54 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col5\" class=\"data row54 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row54_col6\" class=\"data row54 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row55_col0\" class=\"data row55 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
-       "      <td id=\"T_f9b61_row55_col2\" class=\"data row55 col2\" >$ 2,408,936,272</td>\n",
-       "      <td id=\"T_f9b61_row55_col3\" class=\"data row55 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row55_col4\" class=\"data row55 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row55_col5\" class=\"data row55 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row55_col6\" class=\"data row55 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row56_col0\" class=\"data row56 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
-       "      <td id=\"T_f9b61_row56_col2\" class=\"data row56 col2\" >$ 7,751</td>\n",
-       "      <td id=\"T_f9b61_row56_col3\" class=\"data row56 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row56_col4\" class=\"data row56 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row56_col5\" class=\"data row56 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row56_col6\" class=\"data row56 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row57_col0\" class=\"data row57 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col1\" class=\"data row57 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col2\" class=\"data row57 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col3\" class=\"data row57 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col4\" class=\"data row57 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col5\" class=\"data row57 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row57_col6\" class=\"data row57 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row58_col0\" class=\"data row58 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
-       "      <td id=\"T_f9b61_row58_col2\" class=\"data row58 col2\" >$ 2,437,538,300</td>\n",
-       "      <td id=\"T_f9b61_row58_col3\" class=\"data row58 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row58_col4\" class=\"data row58 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row58_col5\" class=\"data row58 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row58_col6\" class=\"data row58 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row59_col0\" class=\"data row59 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
-       "      <td id=\"T_f9b61_row59_col2\" class=\"data row59 col2\" >$ 7,843</td>\n",
-       "      <td id=\"T_f9b61_row59_col3\" class=\"data row59 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row59_col4\" class=\"data row59 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row59_col5\" class=\"data row59 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row59_col6\" class=\"data row59 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row60_col0\" class=\"data row60 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col1\" class=\"data row60 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col2\" class=\"data row60 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col3\" class=\"data row60 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col4\" class=\"data row60 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col5\" class=\"data row60 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row60_col6\" class=\"data row60 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row61_col0\" class=\"data row61 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
-       "      <td id=\"T_f9b61_row61_col2\" class=\"data row61 col2\" >$ 3,029,839,099</td>\n",
-       "      <td id=\"T_f9b61_row61_col3\" class=\"data row61 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row61_col4\" class=\"data row61 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row61_col5\" class=\"data row61 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row61_col6\" class=\"data row61 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row62_col0\" class=\"data row62 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
-       "      <td id=\"T_f9b61_row62_col2\" class=\"data row62 col2\" >$ 9,749</td>\n",
-       "      <td id=\"T_f9b61_row62_col3\" class=\"data row62 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row62_col4\" class=\"data row62 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row62_col5\" class=\"data row62 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row62_col6\" class=\"data row62 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row63_col0\" class=\"data row63 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col1\" class=\"data row63 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col2\" class=\"data row63 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col3\" class=\"data row63 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col4\" class=\"data row63 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col5\" class=\"data row63 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row63_col6\" class=\"data row63 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row64_col0\" class=\"data row64 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
-       "      <td id=\"T_f9b61_row64_col2\" class=\"data row64 col2\" >$ 2,437,538,300</td>\n",
-       "      <td id=\"T_f9b61_row64_col3\" class=\"data row64 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row64_col4\" class=\"data row64 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row64_col5\" class=\"data row64 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row64_col6\" class=\"data row64 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row65_col0\" class=\"data row65 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_f9b61_row65_col2\" class=\"data row65 col2\" >$ 7,843</td>\n",
-       "      <td id=\"T_f9b61_row65_col3\" class=\"data row65 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row65_col4\" class=\"data row65 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row65_col5\" class=\"data row65 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row65_col6\" class=\"data row65 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row66_col0\" class=\"data row66 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col1\" class=\"data row66 col1\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col2\" class=\"data row66 col2\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col3\" class=\"data row66 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col4\" class=\"data row66 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col5\" class=\"data row66 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row66_col6\" class=\"data row66 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row67_col0\" class=\"data row67 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
-       "      <td id=\"T_f9b61_row67_col2\" class=\"data row67 col2\" >$ 3,029,839,099</td>\n",
-       "      <td id=\"T_f9b61_row67_col3\" class=\"data row67 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row67_col4\" class=\"data row67 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row67_col5\" class=\"data row67 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row67_col6\" class=\"data row67 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f9b61_row68_col0\" class=\"data row68 col0\" ></td>\n",
-       "      <td id=\"T_f9b61_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_f9b61_row68_col2\" class=\"data row68 col2\" >$ 9,749</td>\n",
-       "      <td id=\"T_f9b61_row68_col3\" class=\"data row68 col3\" ></td>\n",
-       "      <td id=\"T_f9b61_row68_col4\" class=\"data row68 col4\" ></td>\n",
-       "      <td id=\"T_f9b61_row68_col5\" class=\"data row68 col5\" ></td>\n",
-       "      <td id=\"T_f9b61_row68_col6\" class=\"data row68 col6\" ></td>\n",
+       "      <td id=\"T_bc600_row0_col0\" class=\"data row0 col0\" >10</td>\n",
+       "      <td id=\"T_bc600_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
+       "      <td id=\"T_bc600_row0_col2\" class=\"data row0 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row0_col3\" class=\"data row0 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row0_col4\" class=\"data row0 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row0_col5\" class=\"data row0 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row0_col6\" class=\"data row0 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row1_col0\" class=\"data row1 col0\" >11</td>\n",
+       "      <td id=\"T_bc600_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
+       "      <td id=\"T_bc600_row1_col2\" class=\"data row1 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row1_col3\" class=\"data row1 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row1_col4\" class=\"data row1 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row1_col5\" class=\"data row1 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row1_col6\" class=\"data row1 col6\" >$ 15,000,000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row2_col0\" class=\"data row2 col0\" >12</td>\n",
+       "      <td id=\"T_bc600_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
+       "      <td id=\"T_bc600_row2_col2\" class=\"data row2 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row2_col3\" class=\"data row2 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row2_col4\" class=\"data row2 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row2_col5\" class=\"data row2 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row2_col6\" class=\"data row2 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row3_col0\" class=\"data row3 col0\" >13</td>\n",
+       "      <td id=\"T_bc600_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
+       "      <td id=\"T_bc600_row3_col2\" class=\"data row3 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row3_col3\" class=\"data row3 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row3_col4\" class=\"data row3 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row3_col5\" class=\"data row3 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row3_col6\" class=\"data row3 col6\" >$ 107,009,772</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row4_col0\" class=\"data row4 col0\" >14</td>\n",
+       "      <td id=\"T_bc600_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
+       "      <td id=\"T_bc600_row4_col2\" class=\"data row4 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row4_col3\" class=\"data row4 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row4_col4\" class=\"data row4 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row4_col5\" class=\"data row4 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row4_col6\" class=\"data row4 col6\" >$ 4,721,019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row5_col0\" class=\"data row5 col0\" >15</td>\n",
+       "      <td id=\"T_bc600_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
+       "      <td id=\"T_bc600_row5_col2\" class=\"data row5 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row5_col3\" class=\"data row5 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row5_col4\" class=\"data row5 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row5_col5\" class=\"data row5 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row5_col6\" class=\"data row5 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row6_col0\" class=\"data row6 col0\" >16</td>\n",
+       "      <td id=\"T_bc600_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
+       "      <td id=\"T_bc600_row6_col2\" class=\"data row6 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row6_col3\" class=\"data row6 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row6_col4\" class=\"data row6 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row6_col5\" class=\"data row6 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row6_col6\" class=\"data row6 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row7_col0\" class=\"data row7 col0\" >18</td>\n",
+       "      <td id=\"T_bc600_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
+       "      <td id=\"T_bc600_row7_col2\" class=\"data row7 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row7_col3\" class=\"data row7 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row7_col4\" class=\"data row7 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row7_col5\" class=\"data row7 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row7_col6\" class=\"data row7 col6\" >$ 36,194,482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row8_col0\" class=\"data row8 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col1\" class=\"data row8 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col2\" class=\"data row8 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col3\" class=\"data row8 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col4\" class=\"data row8 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col5\" class=\"data row8 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row8_col6\" class=\"data row8 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row9_col0\" class=\"data row9 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
+       "      <td id=\"T_bc600_row9_col2\" class=\"data row9 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row9_col3\" class=\"data row9 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row9_col4\" class=\"data row9 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row9_col5\" class=\"data row9 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row9_col6\" class=\"data row9 col6\" >$ 162,925,273</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row10_col0\" class=\"data row10 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
+       "      <td id=\"T_bc600_row10_col2\" class=\"data row10 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row10_col3\" class=\"data row10 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row10_col4\" class=\"data row10 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row10_col5\" class=\"data row10 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row10_col6\" class=\"data row10 col6\" >$ 154</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_bc600_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_bc600_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_bc600_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_bc600_row13_col2\" class=\"data row13 col2\" >$ 90,263,521</td>\n",
+       "      <td id=\"T_bc600_row13_col3\" class=\"data row13 col3\" >$ 233,056,140</td>\n",
+       "      <td id=\"T_bc600_row13_col4\" class=\"data row13 col4\" >$ 591,583,081</td>\n",
+       "      <td id=\"T_bc600_row13_col5\" class=\"data row13 col5\" >11,824,706 hrs</td>\n",
+       "      <td id=\"T_bc600_row13_col6\" class=\"data row13 col6\" >$ 914,902,742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_bc600_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_bc600_row14_col2\" class=\"data row14 col2\" >$ 65,728,880</td>\n",
+       "      <td id=\"T_bc600_row14_col3\" class=\"data row14 col3\" >$ 83,309,639</td>\n",
+       "      <td id=\"T_bc600_row14_col4\" class=\"data row14 col4\" >$ 264,358,228</td>\n",
+       "      <td id=\"T_bc600_row14_col5\" class=\"data row14 col5\" >5,420,558 hrs</td>\n",
+       "      <td id=\"T_bc600_row14_col6\" class=\"data row14 col6\" >$ 413,396,748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_bc600_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_bc600_row15_col2\" class=\"data row15 col2\" >$ 1,136,505</td>\n",
+       "      <td id=\"T_bc600_row15_col3\" class=\"data row15 col3\" >$ 5,661,559</td>\n",
+       "      <td id=\"T_bc600_row15_col4\" class=\"data row15 col4\" >$ 8,458,991</td>\n",
+       "      <td id=\"T_bc600_row15_col5\" class=\"data row15 col5\" >163,947 hrs</td>\n",
+       "      <td id=\"T_bc600_row15_col6\" class=\"data row15 col6\" >$ 15,257,055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_bc600_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_bc600_row16_col2\" class=\"data row16 col2\" >$ 23,398,136</td>\n",
+       "      <td id=\"T_bc600_row16_col3\" class=\"data row16 col3\" >$ 144,084,942</td>\n",
+       "      <td id=\"T_bc600_row16_col4\" class=\"data row16 col4\" >$ 318,765,862</td>\n",
+       "      <td id=\"T_bc600_row16_col5\" class=\"data row16 col5\" >6,240,200 hrs</td>\n",
+       "      <td id=\"T_bc600_row16_col6\" class=\"data row16 col6\" >$ 486,248,939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_bc600_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_bc600_row17_col2\" class=\"data row17 col2\" >$ 1,530,752,484</td>\n",
+       "      <td id=\"T_bc600_row17_col3\" class=\"data row17 col3\" >$ 20,897,278</td>\n",
+       "      <td id=\"T_bc600_row17_col4\" class=\"data row17 col4\" >$ 261,886,915</td>\n",
+       "      <td id=\"T_bc600_row17_col5\" class=\"data row17 col5\" >4,903,888 hrs</td>\n",
+       "      <td id=\"T_bc600_row17_col6\" class=\"data row17 col6\" >$ 1,813,536,678</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_bc600_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_bc600_row18_col2\" class=\"data row18 col2\" >$ 534,245,006</td>\n",
+       "      <td id=\"T_bc600_row18_col3\" class=\"data row18 col3\" >$ 5,827,355</td>\n",
+       "      <td id=\"T_bc600_row18_col4\" class=\"data row18 col4\" >$ 125,502,354</td>\n",
+       "      <td id=\"T_bc600_row18_col5\" class=\"data row18 col5\" >2,364,645 hrs</td>\n",
+       "      <td id=\"T_bc600_row18_col6\" class=\"data row18 col6\" >$ 665,574,716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_bc600_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_bc600_row19_col2\" class=\"data row19 col2\" >$ 486,396,295</td>\n",
+       "      <td id=\"T_bc600_row19_col3\" class=\"data row19 col3\" >$ 0</td>\n",
+       "      <td id=\"T_bc600_row19_col4\" class=\"data row19 col4\" >$ 89,623,114</td>\n",
+       "      <td id=\"T_bc600_row19_col5\" class=\"data row19 col5\" >1,682,189 hrs</td>\n",
+       "      <td id=\"T_bc600_row19_col6\" class=\"data row19 col6\" >$ 576,019,409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_bc600_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_bc600_row20_col2\" class=\"data row20 col2\" >$ 47,848,711</td>\n",
+       "      <td id=\"T_bc600_row20_col3\" class=\"data row20 col3\" >$ 5,827,355</td>\n",
+       "      <td id=\"T_bc600_row20_col4\" class=\"data row20 col4\" >$ 35,879,240</td>\n",
+       "      <td id=\"T_bc600_row20_col5\" class=\"data row20 col5\" >682,456 hrs</td>\n",
+       "      <td id=\"T_bc600_row20_col6\" class=\"data row20 col6\" >$ 89,555,306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_bc600_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_bc600_row21_col2\" class=\"data row21 col2\" >$ 28,461,247</td>\n",
+       "      <td id=\"T_bc600_row21_col3\" class=\"data row21 col3\" >$ 25,920,606</td>\n",
+       "      <td id=\"T_bc600_row21_col4\" class=\"data row21 col4\" >$ 86,126,547</td>\n",
+       "      <td id=\"T_bc600_row21_col5\" class=\"data row21 col5\" >1,597,897 hrs</td>\n",
+       "      <td id=\"T_bc600_row21_col6\" class=\"data row21 col6\" >$ 140,508,400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_bc600_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_bc600_row22_col2\" class=\"data row22 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row22_col3\" class=\"data row22 col3\" >$ 0</td>\n",
+       "      <td id=\"T_bc600_row22_col4\" class=\"data row22 col4\" >$ 0</td>\n",
+       "      <td id=\"T_bc600_row22_col5\" class=\"data row22 col5\" >0 hrs</td>\n",
+       "      <td id=\"T_bc600_row22_col6\" class=\"data row22 col6\" >$ 451,686,471</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_bc600_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_bc600_row23_col2\" class=\"data row23 col2\" >$ 65,401,342</td>\n",
+       "      <td id=\"T_bc600_row23_col3\" class=\"data row23 col3\" >$ 19,049,439</td>\n",
+       "      <td id=\"T_bc600_row23_col4\" class=\"data row23 col4\" >$ 129,937,710</td>\n",
+       "      <td id=\"T_bc600_row23_col5\" class=\"data row23 col5\" >2,408,453 hrs</td>\n",
+       "      <td id=\"T_bc600_row23_col6\" class=\"data row23 col6\" >$ 214,388,491</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_bc600_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_bc600_row24_col2\" class=\"data row24 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row24_col6\" class=\"data row24 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_bc600_row26_col2\" class=\"data row26 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row26_col6\" class=\"data row26 col6\" >$ 4,200,597,497</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_bc600_row27_col2\" class=\"data row27 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row27_col6\" class=\"data row27 col6\" >$ 3,978</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_bc600_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_bc600_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_bc600_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_bc600_row30_col2\" class=\"data row30 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row30_col6\" class=\"data row30 col6\" >$ 691,371,059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_bc600_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_bc600_row31_col2\" class=\"data row31 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row31_col6\" class=\"data row31 col6\" >$ 2,734,393,138</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_bc600_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_bc600_row32_col2\" class=\"data row32 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row32_col6\" class=\"data row32 col6\" >$ 115,036,083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_bc600_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_bc600_row33_col2\" class=\"data row33 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row33_col6\" class=\"data row33 col6\" >$ 9,686,167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_bc600_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_bc600_row34_col2\" class=\"data row34 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row34_col6\" class=\"data row34 col6\" >$ 738,767,483</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_bc600_row36_col2\" class=\"data row36 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row36_col6\" class=\"data row36 col6\" >$ 4,289,253,931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_bc600_row37_col2\" class=\"data row37 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row37_col6\" class=\"data row37 col6\" >$ 4,062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_bc600_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_bc600_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_bc600_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_bc600_row40_col2\" class=\"data row40 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row40_col6\" class=\"data row40 col6\" >$ 187,500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_bc600_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_bc600_row41_col2\" class=\"data row41 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row41_col6\" class=\"data row41 col6\" >$ 38,204,331</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_bc600_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_bc600_row42_col2\" class=\"data row42 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row42_col6\" class=\"data row42 col6\" >$ 8,141,760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_bc600_row44_col2\" class=\"data row44 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row44_col6\" class=\"data row44 col6\" >$ 46,533,591</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_bc600_row45_col2\" class=\"data row45 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row45_col6\" class=\"data row45 col6\" >$ 44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row46_col0\" class=\"data row46 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col1\" class=\"data row46 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col2\" class=\"data row46 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col3\" class=\"data row46 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col4\" class=\"data row46 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col5\" class=\"data row46 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row46_col6\" class=\"data row46 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row47_col0\" class=\"data row47 col0\" >60</td>\n",
+       "      <td id=\"T_bc600_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
+       "      <td id=\"T_bc600_row47_col2\" class=\"data row47 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row47_col3\" class=\"data row47 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row47_col4\" class=\"data row47 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row47_col5\" class=\"data row47 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row47_col6\" class=\"data row47 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row48_col0\" class=\"data row48 col0\" >62</td>\n",
+       "      <td id=\"T_bc600_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
+       "      <td id=\"T_bc600_row48_col2\" class=\"data row48 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row48_col3\" class=\"data row48 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row48_col4\" class=\"data row48 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row48_col5\" class=\"data row48 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row48_col6\" class=\"data row48 col6\" >$ 3,202,161,761</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row49_col0\" class=\"data row49 col0\" >-</td>\n",
+       "      <td id=\"T_bc600_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
+       "      <td id=\"T_bc600_row49_col2\" class=\"data row49 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row49_col3\" class=\"data row49 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row49_col4\" class=\"data row49 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row49_col5\" class=\"data row49 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row49_col6\" class=\"data row49 col6\" >$ 3,202,161,761</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row50_col0\" class=\"data row50 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
+       "      <td id=\"T_bc600_row50_col2\" class=\"data row50 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row50_col3\" class=\"data row50 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row50_col4\" class=\"data row50 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row50_col5\" class=\"data row50 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row50_col6\" class=\"data row50 col6\" >$ 3,032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row51_col0\" class=\"data row51 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col1\" class=\"data row51 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col2\" class=\"data row51 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col3\" class=\"data row51 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col4\" class=\"data row51 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col5\" class=\"data row51 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row51_col6\" class=\"data row51 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row52_col0\" class=\"data row52 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
+       "      <td id=\"T_bc600_row52_col2\" class=\"data row52 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row52_col3\" class=\"data row52 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row52_col4\" class=\"data row52 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row52_col5\" class=\"data row52 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row52_col6\" class=\"data row52 col6\" >$ 4,363,522,770</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row53_col0\" class=\"data row53 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
+       "      <td id=\"T_bc600_row53_col2\" class=\"data row53 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row53_col3\" class=\"data row53 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row53_col4\" class=\"data row53 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row53_col5\" class=\"data row53 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row53_col6\" class=\"data row53 col6\" >$ 4,132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row54_col0\" class=\"data row54 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col1\" class=\"data row54 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col2\" class=\"data row54 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col3\" class=\"data row54 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col4\" class=\"data row54 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col5\" class=\"data row54 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row54_col6\" class=\"data row54 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row55_col0\" class=\"data row55 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
+       "      <td id=\"T_bc600_row55_col2\" class=\"data row55 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row55_col3\" class=\"data row55 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row55_col4\" class=\"data row55 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row55_col5\" class=\"data row55 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row55_col6\" class=\"data row55 col6\" >$ 8,652,776,701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row56_col0\" class=\"data row56 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
+       "      <td id=\"T_bc600_row56_col2\" class=\"data row56 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row56_col3\" class=\"data row56 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row56_col4\" class=\"data row56 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row56_col5\" class=\"data row56 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row56_col6\" class=\"data row56 col6\" >$ 8,194</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row57_col0\" class=\"data row57 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col1\" class=\"data row57 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col2\" class=\"data row57 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col3\" class=\"data row57 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col4\" class=\"data row57 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col5\" class=\"data row57 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row57_col6\" class=\"data row57 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row58_col0\" class=\"data row58 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
+       "      <td id=\"T_bc600_row58_col2\" class=\"data row58 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row58_col3\" class=\"data row58 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row58_col4\" class=\"data row58 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row58_col5\" class=\"data row58 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row58_col6\" class=\"data row58 col6\" >$ 8,699,310,293</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row59_col0\" class=\"data row59 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
+       "      <td id=\"T_bc600_row59_col2\" class=\"data row59 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row59_col3\" class=\"data row59 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row59_col4\" class=\"data row59 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row59_col5\" class=\"data row59 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row59_col6\" class=\"data row59 col6\" >$ 8,238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row60_col0\" class=\"data row60 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col1\" class=\"data row60 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col2\" class=\"data row60 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col3\" class=\"data row60 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col4\" class=\"data row60 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col5\" class=\"data row60 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row60_col6\" class=\"data row60 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row61_col0\" class=\"data row61 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
+       "      <td id=\"T_bc600_row61_col2\" class=\"data row61 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row61_col3\" class=\"data row61 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row61_col4\" class=\"data row61 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row61_col5\" class=\"data row61 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row61_col6\" class=\"data row61 col6\" >$ 11,901,472,053</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row62_col0\" class=\"data row62 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
+       "      <td id=\"T_bc600_row62_col2\" class=\"data row62 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row62_col3\" class=\"data row62 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row62_col4\" class=\"data row62 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row62_col5\" class=\"data row62 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row62_col6\" class=\"data row62 col6\" >$ 11,270</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row63_col0\" class=\"data row63 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col1\" class=\"data row63 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col2\" class=\"data row63 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col3\" class=\"data row63 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col4\" class=\"data row63 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col5\" class=\"data row63 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row63_col6\" class=\"data row63 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row64_col0\" class=\"data row64 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
+       "      <td id=\"T_bc600_row64_col2\" class=\"data row64 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row64_col3\" class=\"data row64 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row64_col4\" class=\"data row64 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row64_col5\" class=\"data row64 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row64_col6\" class=\"data row64 col6\" >$ 8,699,310,293</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row65_col0\" class=\"data row65 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_bc600_row65_col2\" class=\"data row65 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row65_col3\" class=\"data row65 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row65_col4\" class=\"data row65 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row65_col5\" class=\"data row65 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row65_col6\" class=\"data row65 col6\" >$ 8,238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row66_col0\" class=\"data row66 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col1\" class=\"data row66 col1\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col2\" class=\"data row66 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col3\" class=\"data row66 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col4\" class=\"data row66 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col5\" class=\"data row66 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row66_col6\" class=\"data row66 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row67_col0\" class=\"data row67 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
+       "      <td id=\"T_bc600_row67_col2\" class=\"data row67 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row67_col3\" class=\"data row67 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row67_col4\" class=\"data row67 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row67_col5\" class=\"data row67 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row67_col6\" class=\"data row67 col6\" >$ 11,901,472,053</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_bc600_row68_col0\" class=\"data row68 col0\" ></td>\n",
+       "      <td id=\"T_bc600_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_bc600_row68_col2\" class=\"data row68 col2\" ></td>\n",
+       "      <td id=\"T_bc600_row68_col3\" class=\"data row68 col3\" ></td>\n",
+       "      <td id=\"T_bc600_row68_col4\" class=\"data row68 col4\" ></td>\n",
+       "      <td id=\"T_bc600_row68_col5\" class=\"data row68 col5\" ></td>\n",
+       "      <td id=\"T_bc600_row68_col6\" class=\"data row68 col6\" >$ 11,270</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1279f0850>"
+       "<pandas.io.formats.style.Styler at 0x1299d9350>"
       ]
      },
      "execution_count": 2,
@@ -751,8 +775,10 @@
     "\n",
     "\n",
     "# Example\n",
-    "reactor_type = \"Concept B\"\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
+    "reactor_type = \"Concept A\"\n",
+    "reactor_data__ = (reactor_data_read(reactor_type ))[0]\n",
+    "reactor_data = reactor_data__ [['Account',\t'Title', 'Factory Equipment Cost' , 'Site Material Cost' , 'Site Labor Cost' , 'Site Labor Hours' , 'Total Cost (USD)']]\n",
+    "reactor_data\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "Reactor_data_pretty = prettify(reactor_data,\\\n",
     "    f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> FOAK Capital Cost Summary - Baseline hypothetical well-executeed project <br><br> \", \"no_subsidies\")\n",
@@ -777,108 +803,108 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_d812f caption {\n",
+       "#T_8ba64 caption {\n",
        "  color: blue;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_d812f_row0_col0, #T_d812f_row0_col1, #T_d812f_row0_col2, #T_d812f_row0_col3, #T_d812f_row1_col0, #T_d812f_row1_col1, #T_d812f_row1_col2, #T_d812f_row1_col3, #T_d812f_row2_col0, #T_d812f_row2_col1, #T_d812f_row2_col2, #T_d812f_row2_col3, #T_d812f_row3_col0, #T_d812f_row3_col1, #T_d812f_row3_col2, #T_d812f_row3_col3, #T_d812f_row4_col0, #T_d812f_row4_col1, #T_d812f_row4_col2, #T_d812f_row4_col3, #T_d812f_row8_col0, #T_d812f_row8_col1, #T_d812f_row8_col2, #T_d812f_row8_col3, #T_d812f_row11_col0, #T_d812f_row11_col1, #T_d812f_row11_col2, #T_d812f_row11_col3 {\n",
+       "#T_8ba64_row0_col0, #T_8ba64_row0_col1, #T_8ba64_row0_col2, #T_8ba64_row0_col3, #T_8ba64_row1_col0, #T_8ba64_row1_col1, #T_8ba64_row1_col2, #T_8ba64_row1_col3, #T_8ba64_row2_col0, #T_8ba64_row2_col1, #T_8ba64_row2_col2, #T_8ba64_row2_col3, #T_8ba64_row3_col0, #T_8ba64_row3_col1, #T_8ba64_row3_col2, #T_8ba64_row3_col3, #T_8ba64_row4_col0, #T_8ba64_row4_col1, #T_8ba64_row4_col2, #T_8ba64_row4_col3, #T_8ba64_row6_col0, #T_8ba64_row6_col1, #T_8ba64_row6_col2, #T_8ba64_row6_col3, #T_8ba64_row8_col0, #T_8ba64_row8_col1, #T_8ba64_row8_col2, #T_8ba64_row8_col3, #T_8ba64_row11_col0, #T_8ba64_row11_col1, #T_8ba64_row11_col2, #T_8ba64_row11_col3 {\n",
        "  background-color: yellow;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_d812f\">\n",
+       "<table id=\"T_8ba64\">\n",
        "  <caption>User-Input Global levers <br> (highlighted in yellow if different from the baseline) <br></caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_d812f_level0_col0\" class=\"col_heading level0 col0\" >Lever</th>\n",
-       "      <th id=\"T_d812f_level0_col1\" class=\"col_heading level0 col1\" >User-Input Value</th>\n",
-       "      <th id=\"T_d812f_level0_col2\" class=\"col_heading level0 col2\" >Lever baseline value (for a hopothetical well-executed project)</th>\n",
-       "      <th id=\"T_d812f_level0_col3\" class=\"col_heading level0 col3\" >Range</th>\n",
+       "      <th id=\"T_8ba64_level0_col0\" class=\"col_heading level0 col0\" >Lever</th>\n",
+       "      <th id=\"T_8ba64_level0_col1\" class=\"col_heading level0 col1\" >User-Input Value</th>\n",
+       "      <th id=\"T_8ba64_level0_col2\" class=\"col_heading level0 col2\" >Lever baseline value (for a hopothetical well-executed project)</th>\n",
+       "      <th id=\"T_8ba64_level0_col3\" class=\"col_heading level0 col3\" >Range</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row0_col0\" class=\"data row0 col0\" >Design Maturity</td>\n",
-       "      <td id=\"T_d812f_row0_col1\" class=\"data row0 col1\" >1</td>\n",
-       "      <td id=\"T_d812f_row0_col2\" class=\"data row0 col2\" >2</td>\n",
-       "      <td id=\"T_d812f_row0_col3\" class=\"data row0 col3\" >0 - 2</td>\n",
+       "      <td id=\"T_8ba64_row0_col0\" class=\"data row0 col0\" >Design Maturity</td>\n",
+       "      <td id=\"T_8ba64_row0_col1\" class=\"data row0 col1\" >1</td>\n",
+       "      <td id=\"T_8ba64_row0_col2\" class=\"data row0 col2\" >2</td>\n",
+       "      <td id=\"T_8ba64_row0_col3\" class=\"data row0 col3\" >0 - 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row1_col0\" class=\"data row1 col0\" >Design Completion</td>\n",
-       "      <td id=\"T_d812f_row1_col1\" class=\"data row1 col1\" >0.800000</td>\n",
-       "      <td id=\"T_d812f_row1_col2\" class=\"data row1 col2\" >1</td>\n",
-       "      <td id=\"T_d812f_row1_col3\" class=\"data row1 col3\" >0 - 1</td>\n",
+       "      <td id=\"T_8ba64_row1_col0\" class=\"data row1 col0\" >Design Completion</td>\n",
+       "      <td id=\"T_8ba64_row1_col1\" class=\"data row1 col1\" >0.800000</td>\n",
+       "      <td id=\"T_8ba64_row1_col2\" class=\"data row1 col2\" >1</td>\n",
+       "      <td id=\"T_8ba64_row1_col3\" class=\"data row1 col3\" >0 - 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row2_col0\" class=\"data row2 col0\" >Procurement (supply chain) experience </td>\n",
-       "      <td id=\"T_d812f_row2_col1\" class=\"data row2 col1\" >0.500000</td>\n",
-       "      <td id=\"T_d812f_row2_col2\" class=\"data row2 col2\" >2</td>\n",
-       "      <td id=\"T_d812f_row2_col3\" class=\"data row2 col3\" >0 - 2</td>\n",
+       "      <td id=\"T_8ba64_row2_col0\" class=\"data row2 col0\" >Procurement (supply chain) experience </td>\n",
+       "      <td id=\"T_8ba64_row2_col1\" class=\"data row2 col1\" >0.500000</td>\n",
+       "      <td id=\"T_8ba64_row2_col2\" class=\"data row2 col2\" >2</td>\n",
+       "      <td id=\"T_8ba64_row2_col3\" class=\"data row2 col3\" >0 - 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row3_col0\" class=\"data row3 col0\" >Architecture & Engineering Experience</td>\n",
-       "      <td id=\"T_d812f_row3_col1\" class=\"data row3 col1\" >0.500000</td>\n",
-       "      <td id=\"T_d812f_row3_col2\" class=\"data row3 col2\" >2</td>\n",
-       "      <td id=\"T_d812f_row3_col3\" class=\"data row3 col3\" >0 - 2</td>\n",
+       "      <td id=\"T_8ba64_row3_col0\" class=\"data row3 col0\" >Architecture & Engineering Experience</td>\n",
+       "      <td id=\"T_8ba64_row3_col1\" class=\"data row3 col1\" >0.500000</td>\n",
+       "      <td id=\"T_8ba64_row3_col2\" class=\"data row3 col2\" >2</td>\n",
+       "      <td id=\"T_8ba64_row3_col3\" class=\"data row3 col3\" >0 - 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row4_col0\" class=\"data row4 col0\" >Construction service experience</td>\n",
-       "      <td id=\"T_d812f_row4_col1\" class=\"data row4 col1\" >1</td>\n",
-       "      <td id=\"T_d812f_row4_col2\" class=\"data row4 col2\" >2</td>\n",
-       "      <td id=\"T_d812f_row4_col3\" class=\"data row4 col3\" >0 - 2</td>\n",
+       "      <td id=\"T_8ba64_row4_col0\" class=\"data row4 col0\" >Construction service experience</td>\n",
+       "      <td id=\"T_8ba64_row4_col1\" class=\"data row4 col1\" >1</td>\n",
+       "      <td id=\"T_8ba64_row4_col2\" class=\"data row4 col2\" >2</td>\n",
+       "      <td id=\"T_8ba64_row4_col3\" class=\"data row4 col3\" >0 - 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row5_col0\" class=\"data row5 col0\" > Land Cost Per Acre (2023 USD)</td>\n",
-       "      <td id=\"T_d812f_row5_col1\" class=\"data row5 col1\" >22000</td>\n",
-       "      <td id=\"T_d812f_row5_col2\" class=\"data row5 col2\" >22000</td>\n",
-       "      <td id=\"T_d812f_row5_col3\" class=\"data row5 col3\" >1000 - 100000</td>\n",
+       "      <td id=\"T_8ba64_row5_col0\" class=\"data row5 col0\" > Land Cost Per Acre (2023 USD)</td>\n",
+       "      <td id=\"T_8ba64_row5_col1\" class=\"data row5 col1\" >22000</td>\n",
+       "      <td id=\"T_8ba64_row5_col2\" class=\"data row5 col2\" >22000</td>\n",
+       "      <td id=\"T_8ba64_row5_col3\" class=\"data row5 col3\" >1000 - 100000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row6_col0\" class=\"data row6 col0\" >ITC </td>\n",
-       "      <td id=\"T_d812f_row6_col1\" class=\"data row6 col1\" >0</td>\n",
-       "      <td id=\"T_d812f_row6_col2\" class=\"data row6 col2\" >0</td>\n",
-       "      <td id=\"T_d812f_row6_col3\" class=\"data row6 col3\" >0 - 0.4</td>\n",
+       "      <td id=\"T_8ba64_row6_col0\" class=\"data row6 col0\" >ITC </td>\n",
+       "      <td id=\"T_8ba64_row6_col1\" class=\"data row6 col1\" >0.060000</td>\n",
+       "      <td id=\"T_8ba64_row6_col2\" class=\"data row6 col2\" >0</td>\n",
+       "      <td id=\"T_8ba64_row6_col3\" class=\"data row6 col3\" >0 - 0.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row7_col0\" class=\"data row7 col0\" > Interest Rate</td>\n",
-       "      <td id=\"T_d812f_row7_col1\" class=\"data row7 col1\" >0.060000</td>\n",
-       "      <td id=\"T_d812f_row7_col2\" class=\"data row7 col2\" >0.060000</td>\n",
-       "      <td id=\"T_d812f_row7_col3\" class=\"data row7 col3\" >0 - 0.15</td>\n",
+       "      <td id=\"T_8ba64_row7_col0\" class=\"data row7 col0\" > Interest Rate</td>\n",
+       "      <td id=\"T_8ba64_row7_col1\" class=\"data row7 col1\" >0.060000</td>\n",
+       "      <td id=\"T_8ba64_row7_col2\" class=\"data row7 col2\" >0.060000</td>\n",
+       "      <td id=\"T_8ba64_row7_col3\" class=\"data row7 col3\" >0 - 0.15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row8_col0\" class=\"data row8 col0\" >BOP grade </td>\n",
-       "      <td id=\"T_d812f_row8_col1\" class=\"data row8 col1\" >non_nuclear</td>\n",
-       "      <td id=\"T_d812f_row8_col2\" class=\"data row8 col2\" >nuclear</td>\n",
-       "      <td id=\"T_d812f_row8_col3\" class=\"data row8 col3\" >nuclear or non-nuclear</td>\n",
+       "      <td id=\"T_8ba64_row8_col0\" class=\"data row8 col0\" >BOP grade </td>\n",
+       "      <td id=\"T_8ba64_row8_col1\" class=\"data row8 col1\" >non_nuclear</td>\n",
+       "      <td id=\"T_8ba64_row8_col2\" class=\"data row8 col2\" >nuclear</td>\n",
+       "      <td id=\"T_8ba64_row8_col3\" class=\"data row8 col3\" >nuclear or non-nuclear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row9_col0\" class=\"data row9 col0\" >Reactor Building grade</td>\n",
-       "      <td id=\"T_d812f_row9_col1\" class=\"data row9 col1\" >nuclear</td>\n",
-       "      <td id=\"T_d812f_row9_col2\" class=\"data row9 col2\" >nuclear</td>\n",
-       "      <td id=\"T_d812f_row9_col3\" class=\"data row9 col3\" >nuclear or non-nuclear</td>\n",
+       "      <td id=\"T_8ba64_row9_col0\" class=\"data row9 col0\" >Reactor Building grade</td>\n",
+       "      <td id=\"T_8ba64_row9_col1\" class=\"data row9 col1\" >nuclear</td>\n",
+       "      <td id=\"T_8ba64_row9_col2\" class=\"data row9 col2\" >nuclear</td>\n",
+       "      <td id=\"T_8ba64_row9_col3\" class=\"data row9 col3\" >nuclear or non-nuclear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row10_col0\" class=\"data row10 col0\" >modulariziation</td>\n",
-       "      <td id=\"T_d812f_row10_col1\" class=\"data row10 col1\" >modularized</td>\n",
-       "      <td id=\"T_d812f_row10_col2\" class=\"data row10 col2\" >modularized</td>\n",
-       "      <td id=\"T_d812f_row10_col3\" class=\"data row10 col3\" >stick_built or modularized</td>\n",
+       "      <td id=\"T_8ba64_row10_col0\" class=\"data row10 col0\" >modulariziation</td>\n",
+       "      <td id=\"T_8ba64_row10_col1\" class=\"data row10 col1\" >modularized</td>\n",
+       "      <td id=\"T_8ba64_row10_col2\" class=\"data row10 col2\" >modularized</td>\n",
+       "      <td id=\"T_8ba64_row10_col3\" class=\"data row10 col3\" >stick_built or modularized</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row11_col0\" class=\"data row11 col0\" >standardization</td>\n",
-       "      <td id=\"T_d812f_row11_col1\" class=\"data row11 col1\" >0.800000</td>\n",
-       "      <td id=\"T_d812f_row11_col2\" class=\"data row11 col2\" >0.700000</td>\n",
-       "      <td id=\"T_d812f_row11_col3\" class=\"data row11 col3\" >0.7 : 1</td>\n",
+       "      <td id=\"T_8ba64_row11_col0\" class=\"data row11 col0\" >standardization</td>\n",
+       "      <td id=\"T_8ba64_row11_col1\" class=\"data row11 col1\" >0.800000</td>\n",
+       "      <td id=\"T_8ba64_row11_col2\" class=\"data row11 col2\" >0.700000</td>\n",
+       "      <td id=\"T_8ba64_row11_col3\" class=\"data row11 col3\" >0.7 : 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td id=\"T_d812f_row12_col0\" class=\"data row12 col0\" >Startup duration (months)</td>\n",
-       "      <td id=\"T_d812f_row12_col1\" class=\"data row12 col1\" >16</td>\n",
-       "      <td id=\"T_d812f_row12_col2\" class=\"data row12 col2\" >16</td>\n",
-       "      <td id=\"T_d812f_row12_col3\" class=\"data row12 col3\" >3 : 24</td>\n",
+       "      <td id=\"T_8ba64_row12_col0\" class=\"data row12 col0\" >Startup duration (months)</td>\n",
+       "      <td id=\"T_8ba64_row12_col1\" class=\"data row12 col1\" >16</td>\n",
+       "      <td id=\"T_8ba64_row12_col2\" class=\"data row12 col2\" >16</td>\n",
+       "      <td id=\"T_8ba64_row12_col3\" class=\"data row12 col3\" >3 : 24</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1123d3590>"
+       "<pandas.io.formats.style.Styler at 0x1097d8ad0>"
       ]
      },
      "execution_count": 3,
@@ -890,7 +916,7 @@
     "## ## User-defined Independent Variables (Global Levers)\n",
     "\n",
     "# reactor type: Concept A or Concept B\n",
-    "reactor_type = \"Concept B\"\n",
+    "reactor_type = \"Concept A\"\n",
     "\n",
     "# Which reactor unit: first of a kind : nth of a kind \n",
     "n_th = 1\n",
@@ -932,6 +958,8 @@
     "# modularity : \"stick_built\"  or \"modularized\"\n",
     "mod_0 = \"modularized\" \n",
     "\n",
+    "    \n",
+    "\n",
     "# cross_site_standardization :\n",
     "standardization_0 = 0.8 # 0.7 corresponds to 70% standardization for PWRs\n",
     "\n",
@@ -940,7 +968,7 @@
     "RB_grade_0 = \"nuclear\"\n",
     "\n",
     "# #investment tax credits subsidies\n",
-    "ITC_0 = 0 \n",
+    "ITC_0 = 0.06\n",
     "\n",
     "#number of reactors claiming ITC\n",
     "n_ITC = 3 \n",
@@ -1028,195 +1056,195 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_8d026 caption {\n",
+       "#T_f804c caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_8d026_row12_col0, #T_8d026_row12_col1, #T_8d026_row12_col2, #T_8d026_row12_col3, #T_8d026_row12_col4, #T_8d026_row12_col5, #T_8d026_row12_col6 {\n",
+       "#T_f804c_row12_col0, #T_f804c_row12_col1, #T_f804c_row12_col2, #T_f804c_row12_col3, #T_f804c_row12_col4, #T_f804c_row12_col5, #T_f804c_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_8d026\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Factories Cost Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
+       "<table id=\"T_f804c\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Factories Cost Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_8d026_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_8d026_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_8d026_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_8d026_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_8d026_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_8d026_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_8d026_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_f804c_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_f804c_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_f804c_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_f804c_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_f804c_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_f804c_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_f804c_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_8d026_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_8d026_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_8d026_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_8d026_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_8d026_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_8d026_row13_col2\" class=\"data row13 col2\" >$ 244,678,343</td>\n",
-       "      <td id=\"T_8d026_row13_col3\" class=\"data row13 col3\" >$ 64,350,801</td>\n",
-       "      <td id=\"T_8d026_row13_col4\" class=\"data row13 col4\" >2,899,407 hrs</td>\n",
-       "      <td id=\"T_8d026_row13_col5\" class=\"data row13 col5\" >$ 145,691,462</td>\n",
-       "      <td id=\"T_8d026_row13_col6\" class=\"data row13 col6\" >$ 34,636,081</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_8d026_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_8d026_row14_col2\" class=\"data row14 col2\" >$ 145,108,928</td>\n",
-       "      <td id=\"T_8d026_row14_col3\" class=\"data row14 col3\" >$ 57,583,605</td>\n",
-       "      <td id=\"T_8d026_row14_col4\" class=\"data row14 col4\" >1,605,670 hrs</td>\n",
-       "      <td id=\"T_8d026_row14_col5\" class=\"data row14 col5\" >$ 81,082,169</td>\n",
-       "      <td id=\"T_8d026_row14_col6\" class=\"data row14 col6\" >$ 6,443,153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_8d026_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_8d026_row15_col2\" class=\"data row15 col2\" >$ 9,518,418</td>\n",
-       "      <td id=\"T_8d026_row15_col3\" class=\"data row15 col3\" >$ 620,964</td>\n",
-       "      <td id=\"T_8d026_row15_col4\" class=\"data row15 col4\" >102,399 hrs</td>\n",
-       "      <td id=\"T_8d026_row15_col5\" class=\"data row15 col5\" >$ 5,280,509</td>\n",
-       "      <td id=\"T_8d026_row15_col6\" class=\"data row15 col6\" >$ 3,616,945</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_8d026_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_8d026_row16_col2\" class=\"data row16 col2\" >$ 90,050,998</td>\n",
-       "      <td id=\"T_8d026_row16_col3\" class=\"data row16 col3\" >$ 6,146,232</td>\n",
-       "      <td id=\"T_8d026_row16_col4\" class=\"data row16 col4\" >1,191,337 hrs</td>\n",
-       "      <td id=\"T_8d026_row16_col5\" class=\"data row16 col5\" >$ 59,328,783</td>\n",
-       "      <td id=\"T_8d026_row16_col6\" class=\"data row16 col6\" >$ 24,575,983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_8d026_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_8d026_row17_col2\" class=\"data row17 col2\" >$ 680,565,566</td>\n",
-       "      <td id=\"T_8d026_row17_col3\" class=\"data row17 col3\" >$ 579,093,613</td>\n",
-       "      <td id=\"T_8d026_row17_col4\" class=\"data row17 col4\" >1,809,704 hrs</td>\n",
-       "      <td id=\"T_8d026_row17_col5\" class=\"data row17 col5\" >$ 97,213,739</td>\n",
-       "      <td id=\"T_8d026_row17_col6\" class=\"data row17 col6\" >$ 4,258,215</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_8d026_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_8d026_row18_col2\" class=\"data row18 col2\" >$ 250,382,483</td>\n",
-       "      <td id=\"T_8d026_row18_col3\" class=\"data row18 col3\" >$ 201,341,409</td>\n",
-       "      <td id=\"T_8d026_row18_col4\" class=\"data row18 col4\" >874,096 hrs</td>\n",
-       "      <td id=\"T_8d026_row18_col5\" class=\"data row18 col5\" >$ 46,348,086</td>\n",
-       "      <td id=\"T_8d026_row18_col6\" class=\"data row18 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_8d026_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_8d026_row19_col2\" class=\"data row19 col2\" >$ 209,096,582</td>\n",
-       "      <td id=\"T_8d026_row19_col3\" class=\"data row19 col3\" >$ 179,276,621</td>\n",
-       "      <td id=\"T_8d026_row19_col4\" class=\"data row19 col4\" >559,709 hrs</td>\n",
-       "      <td id=\"T_8d026_row19_col5\" class=\"data row19 col5\" >$ 29,819,961</td>\n",
-       "      <td id=\"T_8d026_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_8d026_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_8d026_row20_col2\" class=\"data row20 col2\" >$ 41,285,901</td>\n",
-       "      <td id=\"T_8d026_row20_col3\" class=\"data row20 col3\" >$ 22,064,788</td>\n",
-       "      <td id=\"T_8d026_row20_col4\" class=\"data row20 col4\" >314,387 hrs</td>\n",
-       "      <td id=\"T_8d026_row20_col5\" class=\"data row20 col5\" >$ 16,528,125</td>\n",
-       "      <td id=\"T_8d026_row20_col6\" class=\"data row20 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_8d026_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_8d026_row21_col2\" class=\"data row21 col2\" >$ 67,451,645</td>\n",
-       "      <td id=\"T_8d026_row21_col3\" class=\"data row21 col3\" >$ 13,662,941</td>\n",
-       "      <td id=\"T_8d026_row21_col4\" class=\"data row21 col4\" >767,077 hrs</td>\n",
-       "      <td id=\"T_8d026_row21_col5\" class=\"data row21 col5\" >$ 41,345,409</td>\n",
-       "      <td id=\"T_8d026_row21_col6\" class=\"data row21 col6\" >$ 12,443,295</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_8d026_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_8d026_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_8d026_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_8d026_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_8d026_row23_col2\" class=\"data row23 col2\" >$ 25,655,316</td>\n",
-       "      <td id=\"T_8d026_row23_col3\" class=\"data row23 col3\" >$ 8,372,438</td>\n",
-       "      <td id=\"T_8d026_row23_col4\" class=\"data row23 col4\" >278,805 hrs</td>\n",
-       "      <td id=\"T_8d026_row23_col5\" class=\"data row23 col5\" >$ 15,110,212</td>\n",
-       "      <td id=\"T_8d026_row23_col6\" class=\"data row23 col6\" >$ 2,172,665</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_8d026_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_8d026_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_8d026_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_8d026_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_8d026_row26_col2\" class=\"data row26 col2\" >$ 1,548,535,987</td>\n",
-       "      <td id=\"T_8d026_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_8d026_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_8d026_row27_col2\" class=\"data row27 col2\" >$ 4,982</td>\n",
-       "      <td id=\"T_8d026_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8d026_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_8d026_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_f804c_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_f804c_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_f804c_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_f804c_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_f804c_row13_col2\" class=\"data row13 col2\" >$ 914,902,742</td>\n",
+       "      <td id=\"T_f804c_row13_col3\" class=\"data row13 col3\" >$ 90,263,521</td>\n",
+       "      <td id=\"T_f804c_row13_col4\" class=\"data row13 col4\" >11,824,706 hrs</td>\n",
+       "      <td id=\"T_f804c_row13_col5\" class=\"data row13 col5\" >$ 591,583,081</td>\n",
+       "      <td id=\"T_f804c_row13_col6\" class=\"data row13 col6\" >$ 233,056,140</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_f804c_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_f804c_row14_col2\" class=\"data row14 col2\" >$ 413,396,748</td>\n",
+       "      <td id=\"T_f804c_row14_col3\" class=\"data row14 col3\" >$ 65,728,880</td>\n",
+       "      <td id=\"T_f804c_row14_col4\" class=\"data row14 col4\" >5,420,558 hrs</td>\n",
+       "      <td id=\"T_f804c_row14_col5\" class=\"data row14 col5\" >$ 264,358,228</td>\n",
+       "      <td id=\"T_f804c_row14_col6\" class=\"data row14 col6\" >$ 83,309,639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_f804c_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_f804c_row15_col2\" class=\"data row15 col2\" >$ 15,257,055</td>\n",
+       "      <td id=\"T_f804c_row15_col3\" class=\"data row15 col3\" >$ 1,136,505</td>\n",
+       "      <td id=\"T_f804c_row15_col4\" class=\"data row15 col4\" >163,947 hrs</td>\n",
+       "      <td id=\"T_f804c_row15_col5\" class=\"data row15 col5\" >$ 8,458,991</td>\n",
+       "      <td id=\"T_f804c_row15_col6\" class=\"data row15 col6\" >$ 5,661,559</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_f804c_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_f804c_row16_col2\" class=\"data row16 col2\" >$ 486,248,939</td>\n",
+       "      <td id=\"T_f804c_row16_col3\" class=\"data row16 col3\" >$ 23,398,136</td>\n",
+       "      <td id=\"T_f804c_row16_col4\" class=\"data row16 col4\" >6,240,200 hrs</td>\n",
+       "      <td id=\"T_f804c_row16_col5\" class=\"data row16 col5\" >$ 318,765,862</td>\n",
+       "      <td id=\"T_f804c_row16_col6\" class=\"data row16 col6\" >$ 144,084,942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_f804c_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_f804c_row17_col2\" class=\"data row17 col2\" >$ 1,832,767,447</td>\n",
+       "      <td id=\"T_f804c_row17_col3\" class=\"data row17 col3\" >$ 1,549,983,253</td>\n",
+       "      <td id=\"T_f804c_row17_col4\" class=\"data row17 col4\" >4,903,888 hrs</td>\n",
+       "      <td id=\"T_f804c_row17_col5\" class=\"data row17 col5\" >$ 261,886,915</td>\n",
+       "      <td id=\"T_f804c_row17_col6\" class=\"data row17 col6\" >$ 20,897,278</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_f804c_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_f804c_row18_col2\" class=\"data row18 col2\" >$ 677,113,177</td>\n",
+       "      <td id=\"T_f804c_row18_col3\" class=\"data row18 col3\" >$ 545,783,468</td>\n",
+       "      <td id=\"T_f804c_row18_col4\" class=\"data row18 col4\" >2,364,645 hrs</td>\n",
+       "      <td id=\"T_f804c_row18_col5\" class=\"data row18 col5\" >$ 125,502,354</td>\n",
+       "      <td id=\"T_f804c_row18_col6\" class=\"data row18 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_f804c_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_f804c_row19_col2\" class=\"data row19 col2\" >$ 587,557,871</td>\n",
+       "      <td id=\"T_f804c_row19_col3\" class=\"data row19 col3\" >$ 497,934,757</td>\n",
+       "      <td id=\"T_f804c_row19_col4\" class=\"data row19 col4\" >1,682,189 hrs</td>\n",
+       "      <td id=\"T_f804c_row19_col5\" class=\"data row19 col5\" >$ 89,623,114</td>\n",
+       "      <td id=\"T_f804c_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_f804c_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_f804c_row20_col2\" class=\"data row20 col2\" >$ 89,555,306</td>\n",
+       "      <td id=\"T_f804c_row20_col3\" class=\"data row20 col3\" >$ 47,848,711</td>\n",
+       "      <td id=\"T_f804c_row20_col4\" class=\"data row20 col4\" >682,456 hrs</td>\n",
+       "      <td id=\"T_f804c_row20_col5\" class=\"data row20 col5\" >$ 35,879,240</td>\n",
+       "      <td id=\"T_f804c_row20_col6\" class=\"data row20 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_f804c_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_f804c_row21_col2\" class=\"data row21 col2\" >$ 140,508,400</td>\n",
+       "      <td id=\"T_f804c_row21_col3\" class=\"data row21 col3\" >$ 28,461,247</td>\n",
+       "      <td id=\"T_f804c_row21_col4\" class=\"data row21 col4\" >1,597,897 hrs</td>\n",
+       "      <td id=\"T_f804c_row21_col5\" class=\"data row21 col5\" >$ 86,126,547</td>\n",
+       "      <td id=\"T_f804c_row21_col6\" class=\"data row21 col6\" >$ 25,920,606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_f804c_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_f804c_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_f804c_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_f804c_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_f804c_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_f804c_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_f804c_row23_col2\" class=\"data row23 col2\" >$ 214,388,491</td>\n",
+       "      <td id=\"T_f804c_row23_col3\" class=\"data row23 col3\" >$ 65,401,342</td>\n",
+       "      <td id=\"T_f804c_row23_col4\" class=\"data row23 col4\" >2,408,453 hrs</td>\n",
+       "      <td id=\"T_f804c_row23_col5\" class=\"data row23 col5\" >$ 129,937,710</td>\n",
+       "      <td id=\"T_f804c_row23_col6\" class=\"data row23 col6\" >$ 19,049,439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_f804c_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_f804c_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_f804c_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_f804c_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_f804c_row26_col2\" class=\"data row26 col2\" >$ 4,231,366,728</td>\n",
+       "      <td id=\"T_f804c_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_f804c_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_f804c_row27_col2\" class=\"data row27 col2\" >$ 4,007</td>\n",
+       "      <td id=\"T_f804c_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_f804c_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_f804c_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1664f4d10>"
+       "<pandas.io.formats.style.Styler at 0x12ff7c090>"
       ]
      },
      "execution_count": 4,
@@ -1239,13 +1267,14 @@
     "\n",
     "\n",
     "    Reactor_data_fac = update_high_level_costs(db, power)\n",
-    "\n",
+    "    ref_tot_lab_hrs = sum_lab_hrs (Reactor_data_fac)\n",
     "\n",
     "    Reactor_data_fac_ = pd.DataFrame()\n",
     "    Reactor_data_fac_ = Reactor_data_fac[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\\\n",
     "                    'Site Material Cost']].copy()\n",
     "    \n",
-    "    return Reactor_data_fac_ \n",
+    "    \n",
+    "    return Reactor_data_fac_  , ref_tot_lab_hrs\n",
     "\n",
     "\n",
     "\n",
@@ -1254,11 +1283,11 @@
     "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "\n",
-    "Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "Reactor_data_factory = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[0]\n",
     "Reactor_data_factory_pretty = prettify(Reactor_data_factory,\\\n",
     "    f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> Capital Cost Summary - Factories Cost Included  <br> Displaying Direct Cost only<br><br> \", \"no_subsidies\")\n",
     "\n",
-    "# list of rows to hide (not affected by this cost change)\n",
+    "# # list of rows to hide (not affected by this cost change)\n",
     "list1 = list(range(0, 11))\n",
     "list2 = list(range(29, 69))\n",
     "hidden_list1 = list1 + list2\n",
@@ -1284,447 +1313,447 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_bb7fa caption {\n",
+       "#T_44785 caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_bb7fa_row0_col0, #T_bb7fa_row0_col1, #T_bb7fa_row0_col2, #T_bb7fa_row0_col3, #T_bb7fa_row0_col4, #T_bb7fa_row0_col5, #T_bb7fa_row0_col6, #T_bb7fa_row12_col0, #T_bb7fa_row12_col1, #T_bb7fa_row12_col2, #T_bb7fa_row12_col3, #T_bb7fa_row12_col4, #T_bb7fa_row12_col5, #T_bb7fa_row12_col6, #T_bb7fa_row29_col0, #T_bb7fa_row29_col1, #T_bb7fa_row29_col2, #T_bb7fa_row29_col3, #T_bb7fa_row29_col4, #T_bb7fa_row29_col5, #T_bb7fa_row29_col6, #T_bb7fa_row39_col0, #T_bb7fa_row39_col1, #T_bb7fa_row39_col2, #T_bb7fa_row39_col3, #T_bb7fa_row39_col4, #T_bb7fa_row39_col5, #T_bb7fa_row39_col6 {\n",
+       "#T_44785_row0_col0, #T_44785_row0_col1, #T_44785_row0_col2, #T_44785_row0_col3, #T_44785_row0_col4, #T_44785_row0_col5, #T_44785_row0_col6, #T_44785_row12_col0, #T_44785_row12_col1, #T_44785_row12_col2, #T_44785_row12_col3, #T_44785_row12_col4, #T_44785_row12_col5, #T_44785_row12_col6, #T_44785_row29_col0, #T_44785_row29_col1, #T_44785_row29_col2, #T_44785_row29_col3, #T_44785_row29_col4, #T_44785_row29_col5, #T_44785_row29_col6, #T_44785_row39_col0, #T_44785_row39_col1, #T_44785_row39_col2, #T_44785_row39_col3, #T_44785_row39_col4, #T_44785_row39_col5, #T_44785_row39_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_bb7fa\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost and taxes Included  <br><br> </caption>\n",
+       "<table id=\"T_44785\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost and taxes Included  <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_bb7fa_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_bb7fa_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_bb7fa_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_bb7fa_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_bb7fa_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_bb7fa_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_bb7fa_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_44785_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_44785_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_44785_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_44785_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_44785_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_44785_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_44785_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_bb7fa_row0_col0\" class=\"data row0 col0\" >10</td>\n",
-       "      <td id=\"T_bb7fa_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
-       "      <td id=\"T_bb7fa_row0_col2\" class=\"data row0 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row0_col3\" class=\"data row0 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row0_col4\" class=\"data row0 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row0_col5\" class=\"data row0 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row0_col6\" class=\"data row0 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row1_col0\" class=\"data row1 col0\" >11</td>\n",
-       "      <td id=\"T_bb7fa_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
-       "      <td id=\"T_bb7fa_row1_col2\" class=\"data row1 col2\" >$ 11,000,000</td>\n",
-       "      <td id=\"T_bb7fa_row1_col3\" class=\"data row1 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row1_col4\" class=\"data row1 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row1_col5\" class=\"data row1 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row1_col6\" class=\"data row1 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row2_col0\" class=\"data row2 col0\" >12</td>\n",
-       "      <td id=\"T_bb7fa_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
-       "      <td id=\"T_bb7fa_row2_col2\" class=\"data row2 col2\" >$ 1,598,891</td>\n",
-       "      <td id=\"T_bb7fa_row2_col3\" class=\"data row2 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row2_col4\" class=\"data row2 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row2_col5\" class=\"data row2 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row2_col6\" class=\"data row2 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row3_col0\" class=\"data row3 col0\" >13</td>\n",
-       "      <td id=\"T_bb7fa_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
-       "      <td id=\"T_bb7fa_row3_col2\" class=\"data row3 col2\" >$ 24,382,988</td>\n",
-       "      <td id=\"T_bb7fa_row3_col3\" class=\"data row3 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row3_col4\" class=\"data row3 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row3_col5\" class=\"data row3 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row3_col6\" class=\"data row3 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row4_col0\" class=\"data row4 col0\" >14</td>\n",
-       "      <td id=\"T_bb7fa_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
-       "      <td id=\"T_bb7fa_row4_col2\" class=\"data row4 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_bb7fa_row4_col3\" class=\"data row4 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row4_col4\" class=\"data row4 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row4_col5\" class=\"data row4 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row4_col6\" class=\"data row4 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row5_col0\" class=\"data row5 col0\" >15</td>\n",
-       "      <td id=\"T_bb7fa_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
-       "      <td id=\"T_bb7fa_row5_col2\" class=\"data row5 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_bb7fa_row5_col3\" class=\"data row5 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row5_col4\" class=\"data row5 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row5_col5\" class=\"data row5 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row5_col6\" class=\"data row5 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row6_col0\" class=\"data row6 col0\" >16</td>\n",
-       "      <td id=\"T_bb7fa_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
-       "      <td id=\"T_bb7fa_row6_col2\" class=\"data row6 col2\" >$ 3,972,186</td>\n",
-       "      <td id=\"T_bb7fa_row6_col3\" class=\"data row6 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row6_col4\" class=\"data row6 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row6_col5\" class=\"data row6 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row6_col6\" class=\"data row6 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row7_col0\" class=\"data row7 col0\" >18</td>\n",
-       "      <td id=\"T_bb7fa_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
-       "      <td id=\"T_bb7fa_row7_col2\" class=\"data row7 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_bb7fa_row7_col3\" class=\"data row7 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row7_col4\" class=\"data row7 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row7_col5\" class=\"data row7 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row7_col6\" class=\"data row7 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row8_col0\" class=\"data row8 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col1\" class=\"data row8 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col2\" class=\"data row8 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col3\" class=\"data row8 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col4\" class=\"data row8 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col5\" class=\"data row8 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row8_col6\" class=\"data row8 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row9_col0\" class=\"data row9 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
-       "      <td id=\"T_bb7fa_row9_col2\" class=\"data row9 col2\" >$ 78,991,565</td>\n",
-       "      <td id=\"T_bb7fa_row9_col3\" class=\"data row9 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row9_col4\" class=\"data row9 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row9_col5\" class=\"data row9 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row9_col6\" class=\"data row9 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row10_col0\" class=\"data row10 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
-       "      <td id=\"T_bb7fa_row10_col2\" class=\"data row10 col2\" >$ 254</td>\n",
-       "      <td id=\"T_bb7fa_row10_col3\" class=\"data row10 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row10_col4\" class=\"data row10 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row10_col5\" class=\"data row10 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row10_col6\" class=\"data row10 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_bb7fa_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_bb7fa_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_bb7fa_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_bb7fa_row13_col2\" class=\"data row13 col2\" >$ 244,678,343</td>\n",
-       "      <td id=\"T_bb7fa_row13_col3\" class=\"data row13 col3\" >$ 64,350,801</td>\n",
-       "      <td id=\"T_bb7fa_row13_col4\" class=\"data row13 col4\" >2,899,407 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row13_col5\" class=\"data row13 col5\" >$ 145,691,462</td>\n",
-       "      <td id=\"T_bb7fa_row13_col6\" class=\"data row13 col6\" >$ 34,636,081</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_bb7fa_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_bb7fa_row14_col2\" class=\"data row14 col2\" >$ 145,108,928</td>\n",
-       "      <td id=\"T_bb7fa_row14_col3\" class=\"data row14 col3\" >$ 57,583,605</td>\n",
-       "      <td id=\"T_bb7fa_row14_col4\" class=\"data row14 col4\" >1,605,670 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row14_col5\" class=\"data row14 col5\" >$ 81,082,169</td>\n",
-       "      <td id=\"T_bb7fa_row14_col6\" class=\"data row14 col6\" >$ 6,443,153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_bb7fa_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_bb7fa_row15_col2\" class=\"data row15 col2\" >$ 9,518,418</td>\n",
-       "      <td id=\"T_bb7fa_row15_col3\" class=\"data row15 col3\" >$ 620,964</td>\n",
-       "      <td id=\"T_bb7fa_row15_col4\" class=\"data row15 col4\" >102,399 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row15_col5\" class=\"data row15 col5\" >$ 5,280,509</td>\n",
-       "      <td id=\"T_bb7fa_row15_col6\" class=\"data row15 col6\" >$ 3,616,945</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_bb7fa_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_bb7fa_row16_col2\" class=\"data row16 col2\" >$ 90,050,998</td>\n",
-       "      <td id=\"T_bb7fa_row16_col3\" class=\"data row16 col3\" >$ 6,146,232</td>\n",
-       "      <td id=\"T_bb7fa_row16_col4\" class=\"data row16 col4\" >1,191,337 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row16_col5\" class=\"data row16 col5\" >$ 59,328,783</td>\n",
-       "      <td id=\"T_bb7fa_row16_col6\" class=\"data row16 col6\" >$ 24,575,983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_bb7fa_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_bb7fa_row17_col2\" class=\"data row17 col2\" >$ 680,565,566</td>\n",
-       "      <td id=\"T_bb7fa_row17_col3\" class=\"data row17 col3\" >$ 579,093,613</td>\n",
-       "      <td id=\"T_bb7fa_row17_col4\" class=\"data row17 col4\" >1,809,704 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row17_col5\" class=\"data row17 col5\" >$ 97,213,739</td>\n",
-       "      <td id=\"T_bb7fa_row17_col6\" class=\"data row17 col6\" >$ 4,258,215</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_bb7fa_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_bb7fa_row18_col2\" class=\"data row18 col2\" >$ 250,382,483</td>\n",
-       "      <td id=\"T_bb7fa_row18_col3\" class=\"data row18 col3\" >$ 201,341,409</td>\n",
-       "      <td id=\"T_bb7fa_row18_col4\" class=\"data row18 col4\" >874,096 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row18_col5\" class=\"data row18 col5\" >$ 46,348,086</td>\n",
-       "      <td id=\"T_bb7fa_row18_col6\" class=\"data row18 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_bb7fa_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_bb7fa_row19_col2\" class=\"data row19 col2\" >$ 209,096,582</td>\n",
-       "      <td id=\"T_bb7fa_row19_col3\" class=\"data row19 col3\" >$ 179,276,621</td>\n",
-       "      <td id=\"T_bb7fa_row19_col4\" class=\"data row19 col4\" >559,709 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row19_col5\" class=\"data row19 col5\" >$ 29,819,961</td>\n",
-       "      <td id=\"T_bb7fa_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_bb7fa_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_bb7fa_row20_col2\" class=\"data row20 col2\" >$ 41,285,901</td>\n",
-       "      <td id=\"T_bb7fa_row20_col3\" class=\"data row20 col3\" >$ 22,064,788</td>\n",
-       "      <td id=\"T_bb7fa_row20_col4\" class=\"data row20 col4\" >314,387 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row20_col5\" class=\"data row20 col5\" >$ 16,528,125</td>\n",
-       "      <td id=\"T_bb7fa_row20_col6\" class=\"data row20 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_bb7fa_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_bb7fa_row21_col2\" class=\"data row21 col2\" >$ 67,451,645</td>\n",
-       "      <td id=\"T_bb7fa_row21_col3\" class=\"data row21 col3\" >$ 13,662,941</td>\n",
-       "      <td id=\"T_bb7fa_row21_col4\" class=\"data row21 col4\" >767,077 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row21_col5\" class=\"data row21 col5\" >$ 41,345,409</td>\n",
-       "      <td id=\"T_bb7fa_row21_col6\" class=\"data row21 col6\" >$ 12,443,295</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_bb7fa_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_bb7fa_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_bb7fa_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_bb7fa_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_bb7fa_row23_col2\" class=\"data row23 col2\" >$ 25,655,316</td>\n",
-       "      <td id=\"T_bb7fa_row23_col3\" class=\"data row23 col3\" >$ 8,372,438</td>\n",
-       "      <td id=\"T_bb7fa_row23_col4\" class=\"data row23 col4\" >278,805 hrs</td>\n",
-       "      <td id=\"T_bb7fa_row23_col5\" class=\"data row23 col5\" >$ 15,110,212</td>\n",
-       "      <td id=\"T_bb7fa_row23_col6\" class=\"data row23 col6\" >$ 2,172,665</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_bb7fa_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_bb7fa_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_bb7fa_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_bb7fa_row26_col2\" class=\"data row26 col2\" >$ 1,548,535,987</td>\n",
-       "      <td id=\"T_bb7fa_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_bb7fa_row27_col2\" class=\"data row27 col2\" >$ 4,982</td>\n",
-       "      <td id=\"T_bb7fa_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_bb7fa_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_bb7fa_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_bb7fa_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_bb7fa_row30_col2\" class=\"data row30 col2\" >$ 146,051,997</td>\n",
-       "      <td id=\"T_bb7fa_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_bb7fa_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_bb7fa_row31_col2\" class=\"data row31 col2\" >$ 506,256,125</td>\n",
-       "      <td id=\"T_bb7fa_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_bb7fa_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_bb7fa_row32_col2\" class=\"data row32 col2\" >$ 21,298,226</td>\n",
-       "      <td id=\"T_bb7fa_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_bb7fa_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_bb7fa_row33_col2\" class=\"data row33 col2\" >$ 1,793,334</td>\n",
-       "      <td id=\"T_bb7fa_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_bb7fa_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_bb7fa_row34_col2\" class=\"data row34 col2\" >$ 136,778,270</td>\n",
-       "      <td id=\"T_bb7fa_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_bb7fa_row36_col2\" class=\"data row36 col2\" >$ 812,177,951</td>\n",
-       "      <td id=\"T_bb7fa_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_bb7fa_row37_col2\" class=\"data row37 col2\" >$ 2,613</td>\n",
-       "      <td id=\"T_bb7fa_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row37_col6\" class=\"data row37 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row38_col0\" class=\"data row38 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col1\" class=\"data row38 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col2\" class=\"data row38 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col3\" class=\"data row38 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col4\" class=\"data row38 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col5\" class=\"data row38 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row38_col6\" class=\"data row38 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row39_col0\" class=\"data row39 col0\" >50</td>\n",
-       "      <td id=\"T_bb7fa_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
-       "      <td id=\"T_bb7fa_row39_col2\" class=\"data row39 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row39_col3\" class=\"data row39 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row39_col4\" class=\"data row39 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row39_col5\" class=\"data row39 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row39_col6\" class=\"data row39 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row40_col0\" class=\"data row40 col0\" >51</td>\n",
-       "      <td id=\"T_bb7fa_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
-       "      <td id=\"T_bb7fa_row40_col2\" class=\"data row40 col2\" >$ 3,510,602</td>\n",
-       "      <td id=\"T_bb7fa_row40_col3\" class=\"data row40 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row40_col4\" class=\"data row40 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row40_col5\" class=\"data row40 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row40_col6\" class=\"data row40 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row41_col0\" class=\"data row41 col0\" >52</td>\n",
-       "      <td id=\"T_bb7fa_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
-       "      <td id=\"T_bb7fa_row41_col2\" class=\"data row41 col2\" >$ 10,484,751</td>\n",
-       "      <td id=\"T_bb7fa_row41_col3\" class=\"data row41 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row41_col4\" class=\"data row41 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row41_col5\" class=\"data row41 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row41_col6\" class=\"data row41 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row42_col0\" class=\"data row42 col0\" >54</td>\n",
-       "      <td id=\"T_bb7fa_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
-       "      <td id=\"T_bb7fa_row42_col2\" class=\"data row42 col2\" >$ 14,606,673</td>\n",
-       "      <td id=\"T_bb7fa_row42_col3\" class=\"data row42 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row42_col4\" class=\"data row42 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row42_col5\" class=\"data row42 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row42_col6\" class=\"data row42 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row43_col0\" class=\"data row43 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col1\" class=\"data row43 col1\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col2\" class=\"data row43 col2\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col3\" class=\"data row43 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col4\" class=\"data row43 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col5\" class=\"data row43 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row43_col6\" class=\"data row43 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row44_col0\" class=\"data row44 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
-       "      <td id=\"T_bb7fa_row44_col2\" class=\"data row44 col2\" >$ 28,602,027</td>\n",
-       "      <td id=\"T_bb7fa_row44_col3\" class=\"data row44 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row44_col4\" class=\"data row44 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row44_col5\" class=\"data row44 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row44_col6\" class=\"data row44 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_bb7fa_row45_col0\" class=\"data row45 col0\" ></td>\n",
-       "      <td id=\"T_bb7fa_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
-       "      <td id=\"T_bb7fa_row45_col2\" class=\"data row45 col2\" >$ 92</td>\n",
-       "      <td id=\"T_bb7fa_row45_col3\" class=\"data row45 col3\" ></td>\n",
-       "      <td id=\"T_bb7fa_row45_col4\" class=\"data row45 col4\" ></td>\n",
-       "      <td id=\"T_bb7fa_row45_col5\" class=\"data row45 col5\" ></td>\n",
-       "      <td id=\"T_bb7fa_row45_col6\" class=\"data row45 col6\" ></td>\n",
+       "      <td id=\"T_44785_row0_col0\" class=\"data row0 col0\" >10</td>\n",
+       "      <td id=\"T_44785_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
+       "      <td id=\"T_44785_row0_col2\" class=\"data row0 col2\" ></td>\n",
+       "      <td id=\"T_44785_row0_col3\" class=\"data row0 col3\" ></td>\n",
+       "      <td id=\"T_44785_row0_col4\" class=\"data row0 col4\" ></td>\n",
+       "      <td id=\"T_44785_row0_col5\" class=\"data row0 col5\" ></td>\n",
+       "      <td id=\"T_44785_row0_col6\" class=\"data row0 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row1_col0\" class=\"data row1 col0\" >11</td>\n",
+       "      <td id=\"T_44785_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
+       "      <td id=\"T_44785_row1_col2\" class=\"data row1 col2\" >$ 15,000,000</td>\n",
+       "      <td id=\"T_44785_row1_col3\" class=\"data row1 col3\" ></td>\n",
+       "      <td id=\"T_44785_row1_col4\" class=\"data row1 col4\" ></td>\n",
+       "      <td id=\"T_44785_row1_col5\" class=\"data row1 col5\" ></td>\n",
+       "      <td id=\"T_44785_row1_col6\" class=\"data row1 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row2_col0\" class=\"data row2 col0\" >12</td>\n",
+       "      <td id=\"T_44785_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
+       "      <td id=\"T_44785_row2_col2\" class=\"data row2 col2\" >$ 0</td>\n",
+       "      <td id=\"T_44785_row2_col3\" class=\"data row2 col3\" ></td>\n",
+       "      <td id=\"T_44785_row2_col4\" class=\"data row2 col4\" ></td>\n",
+       "      <td id=\"T_44785_row2_col5\" class=\"data row2 col5\" ></td>\n",
+       "      <td id=\"T_44785_row2_col6\" class=\"data row2 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row3_col0\" class=\"data row3 col0\" >13</td>\n",
+       "      <td id=\"T_44785_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
+       "      <td id=\"T_44785_row3_col2\" class=\"data row3 col2\" >$ 107,009,772</td>\n",
+       "      <td id=\"T_44785_row3_col3\" class=\"data row3 col3\" ></td>\n",
+       "      <td id=\"T_44785_row3_col4\" class=\"data row3 col4\" ></td>\n",
+       "      <td id=\"T_44785_row3_col5\" class=\"data row3 col5\" ></td>\n",
+       "      <td id=\"T_44785_row3_col6\" class=\"data row3 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row4_col0\" class=\"data row4 col0\" >14</td>\n",
+       "      <td id=\"T_44785_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
+       "      <td id=\"T_44785_row4_col2\" class=\"data row4 col2\" >$ 4,721,019</td>\n",
+       "      <td id=\"T_44785_row4_col3\" class=\"data row4 col3\" ></td>\n",
+       "      <td id=\"T_44785_row4_col4\" class=\"data row4 col4\" ></td>\n",
+       "      <td id=\"T_44785_row4_col5\" class=\"data row4 col5\" ></td>\n",
+       "      <td id=\"T_44785_row4_col6\" class=\"data row4 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row5_col0\" class=\"data row5 col0\" >15</td>\n",
+       "      <td id=\"T_44785_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
+       "      <td id=\"T_44785_row5_col2\" class=\"data row5 col2\" >$ 0</td>\n",
+       "      <td id=\"T_44785_row5_col3\" class=\"data row5 col3\" ></td>\n",
+       "      <td id=\"T_44785_row5_col4\" class=\"data row5 col4\" ></td>\n",
+       "      <td id=\"T_44785_row5_col5\" class=\"data row5 col5\" ></td>\n",
+       "      <td id=\"T_44785_row5_col6\" class=\"data row5 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row6_col0\" class=\"data row6 col0\" >16</td>\n",
+       "      <td id=\"T_44785_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
+       "      <td id=\"T_44785_row6_col2\" class=\"data row6 col2\" >$ 0</td>\n",
+       "      <td id=\"T_44785_row6_col3\" class=\"data row6 col3\" ></td>\n",
+       "      <td id=\"T_44785_row6_col4\" class=\"data row6 col4\" ></td>\n",
+       "      <td id=\"T_44785_row6_col5\" class=\"data row6 col5\" ></td>\n",
+       "      <td id=\"T_44785_row6_col6\" class=\"data row6 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row7_col0\" class=\"data row7 col0\" >18</td>\n",
+       "      <td id=\"T_44785_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
+       "      <td id=\"T_44785_row7_col2\" class=\"data row7 col2\" >$ 36,194,482</td>\n",
+       "      <td id=\"T_44785_row7_col3\" class=\"data row7 col3\" ></td>\n",
+       "      <td id=\"T_44785_row7_col4\" class=\"data row7 col4\" ></td>\n",
+       "      <td id=\"T_44785_row7_col5\" class=\"data row7 col5\" ></td>\n",
+       "      <td id=\"T_44785_row7_col6\" class=\"data row7 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row8_col0\" class=\"data row8 col0\" ></td>\n",
+       "      <td id=\"T_44785_row8_col1\" class=\"data row8 col1\" ></td>\n",
+       "      <td id=\"T_44785_row8_col2\" class=\"data row8 col2\" ></td>\n",
+       "      <td id=\"T_44785_row8_col3\" class=\"data row8 col3\" ></td>\n",
+       "      <td id=\"T_44785_row8_col4\" class=\"data row8 col4\" ></td>\n",
+       "      <td id=\"T_44785_row8_col5\" class=\"data row8 col5\" ></td>\n",
+       "      <td id=\"T_44785_row8_col6\" class=\"data row8 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row9_col0\" class=\"data row9 col0\" ></td>\n",
+       "      <td id=\"T_44785_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
+       "      <td id=\"T_44785_row9_col2\" class=\"data row9 col2\" >$ 162,925,273</td>\n",
+       "      <td id=\"T_44785_row9_col3\" class=\"data row9 col3\" ></td>\n",
+       "      <td id=\"T_44785_row9_col4\" class=\"data row9 col4\" ></td>\n",
+       "      <td id=\"T_44785_row9_col5\" class=\"data row9 col5\" ></td>\n",
+       "      <td id=\"T_44785_row9_col6\" class=\"data row9 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row10_col0\" class=\"data row10 col0\" ></td>\n",
+       "      <td id=\"T_44785_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
+       "      <td id=\"T_44785_row10_col2\" class=\"data row10 col2\" >$ 154</td>\n",
+       "      <td id=\"T_44785_row10_col3\" class=\"data row10 col3\" ></td>\n",
+       "      <td id=\"T_44785_row10_col4\" class=\"data row10 col4\" ></td>\n",
+       "      <td id=\"T_44785_row10_col5\" class=\"data row10 col5\" ></td>\n",
+       "      <td id=\"T_44785_row10_col6\" class=\"data row10 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_44785_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_44785_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_44785_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_44785_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_44785_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_44785_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_44785_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_44785_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_44785_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_44785_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_44785_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_44785_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_44785_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_44785_row13_col2\" class=\"data row13 col2\" >$ 914,902,742</td>\n",
+       "      <td id=\"T_44785_row13_col3\" class=\"data row13 col3\" >$ 90,263,521</td>\n",
+       "      <td id=\"T_44785_row13_col4\" class=\"data row13 col4\" >11,824,706 hrs</td>\n",
+       "      <td id=\"T_44785_row13_col5\" class=\"data row13 col5\" >$ 591,583,081</td>\n",
+       "      <td id=\"T_44785_row13_col6\" class=\"data row13 col6\" >$ 233,056,140</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_44785_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_44785_row14_col2\" class=\"data row14 col2\" >$ 413,396,748</td>\n",
+       "      <td id=\"T_44785_row14_col3\" class=\"data row14 col3\" >$ 65,728,880</td>\n",
+       "      <td id=\"T_44785_row14_col4\" class=\"data row14 col4\" >5,420,558 hrs</td>\n",
+       "      <td id=\"T_44785_row14_col5\" class=\"data row14 col5\" >$ 264,358,228</td>\n",
+       "      <td id=\"T_44785_row14_col6\" class=\"data row14 col6\" >$ 83,309,639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_44785_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_44785_row15_col2\" class=\"data row15 col2\" >$ 15,257,055</td>\n",
+       "      <td id=\"T_44785_row15_col3\" class=\"data row15 col3\" >$ 1,136,505</td>\n",
+       "      <td id=\"T_44785_row15_col4\" class=\"data row15 col4\" >163,947 hrs</td>\n",
+       "      <td id=\"T_44785_row15_col5\" class=\"data row15 col5\" >$ 8,458,991</td>\n",
+       "      <td id=\"T_44785_row15_col6\" class=\"data row15 col6\" >$ 5,661,559</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_44785_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_44785_row16_col2\" class=\"data row16 col2\" >$ 486,248,939</td>\n",
+       "      <td id=\"T_44785_row16_col3\" class=\"data row16 col3\" >$ 23,398,136</td>\n",
+       "      <td id=\"T_44785_row16_col4\" class=\"data row16 col4\" >6,240,200 hrs</td>\n",
+       "      <td id=\"T_44785_row16_col5\" class=\"data row16 col5\" >$ 318,765,862</td>\n",
+       "      <td id=\"T_44785_row16_col6\" class=\"data row16 col6\" >$ 144,084,942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_44785_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_44785_row17_col2\" class=\"data row17 col2\" >$ 1,832,767,447</td>\n",
+       "      <td id=\"T_44785_row17_col3\" class=\"data row17 col3\" >$ 1,549,983,253</td>\n",
+       "      <td id=\"T_44785_row17_col4\" class=\"data row17 col4\" >4,903,888 hrs</td>\n",
+       "      <td id=\"T_44785_row17_col5\" class=\"data row17 col5\" >$ 261,886,915</td>\n",
+       "      <td id=\"T_44785_row17_col6\" class=\"data row17 col6\" >$ 20,897,278</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_44785_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_44785_row18_col2\" class=\"data row18 col2\" >$ 677,113,177</td>\n",
+       "      <td id=\"T_44785_row18_col3\" class=\"data row18 col3\" >$ 545,783,468</td>\n",
+       "      <td id=\"T_44785_row18_col4\" class=\"data row18 col4\" >2,364,645 hrs</td>\n",
+       "      <td id=\"T_44785_row18_col5\" class=\"data row18 col5\" >$ 125,502,354</td>\n",
+       "      <td id=\"T_44785_row18_col6\" class=\"data row18 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_44785_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_44785_row19_col2\" class=\"data row19 col2\" >$ 587,557,871</td>\n",
+       "      <td id=\"T_44785_row19_col3\" class=\"data row19 col3\" >$ 497,934,757</td>\n",
+       "      <td id=\"T_44785_row19_col4\" class=\"data row19 col4\" >1,682,189 hrs</td>\n",
+       "      <td id=\"T_44785_row19_col5\" class=\"data row19 col5\" >$ 89,623,114</td>\n",
+       "      <td id=\"T_44785_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_44785_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_44785_row20_col2\" class=\"data row20 col2\" >$ 89,555,306</td>\n",
+       "      <td id=\"T_44785_row20_col3\" class=\"data row20 col3\" >$ 47,848,711</td>\n",
+       "      <td id=\"T_44785_row20_col4\" class=\"data row20 col4\" >682,456 hrs</td>\n",
+       "      <td id=\"T_44785_row20_col5\" class=\"data row20 col5\" >$ 35,879,240</td>\n",
+       "      <td id=\"T_44785_row20_col6\" class=\"data row20 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_44785_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_44785_row21_col2\" class=\"data row21 col2\" >$ 140,508,400</td>\n",
+       "      <td id=\"T_44785_row21_col3\" class=\"data row21 col3\" >$ 28,461,247</td>\n",
+       "      <td id=\"T_44785_row21_col4\" class=\"data row21 col4\" >1,597,897 hrs</td>\n",
+       "      <td id=\"T_44785_row21_col5\" class=\"data row21 col5\" >$ 86,126,547</td>\n",
+       "      <td id=\"T_44785_row21_col6\" class=\"data row21 col6\" >$ 25,920,606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_44785_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_44785_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_44785_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_44785_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_44785_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_44785_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_44785_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_44785_row23_col2\" class=\"data row23 col2\" >$ 214,388,491</td>\n",
+       "      <td id=\"T_44785_row23_col3\" class=\"data row23 col3\" >$ 65,401,342</td>\n",
+       "      <td id=\"T_44785_row23_col4\" class=\"data row23 col4\" >2,408,453 hrs</td>\n",
+       "      <td id=\"T_44785_row23_col5\" class=\"data row23 col5\" >$ 129,937,710</td>\n",
+       "      <td id=\"T_44785_row23_col6\" class=\"data row23 col6\" >$ 19,049,439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_44785_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_44785_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_44785_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_44785_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_44785_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_44785_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_44785_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_44785_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_44785_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_44785_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_44785_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_44785_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_44785_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_44785_row26_col2\" class=\"data row26 col2\" >$ 4,231,366,728</td>\n",
+       "      <td id=\"T_44785_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_44785_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_44785_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_44785_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_44785_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_44785_row27_col2\" class=\"data row27 col2\" >$ 4,007</td>\n",
+       "      <td id=\"T_44785_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_44785_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_44785_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_44785_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_44785_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_44785_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_44785_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_44785_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_44785_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_44785_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_44785_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_44785_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_44785_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_44785_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_44785_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_44785_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_44785_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_44785_row30_col2\" class=\"data row30 col2\" >$ 691,371,059</td>\n",
+       "      <td id=\"T_44785_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_44785_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_44785_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_44785_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_44785_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_44785_row31_col2\" class=\"data row31 col2\" >$ 2,734,393,138</td>\n",
+       "      <td id=\"T_44785_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_44785_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_44785_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_44785_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_44785_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_44785_row32_col2\" class=\"data row32 col2\" >$ 115,036,083</td>\n",
+       "      <td id=\"T_44785_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_44785_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_44785_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_44785_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_44785_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_44785_row33_col2\" class=\"data row33 col2\" >$ 9,686,167</td>\n",
+       "      <td id=\"T_44785_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_44785_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_44785_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_44785_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_44785_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_44785_row34_col2\" class=\"data row34 col2\" >$ 738,767,483</td>\n",
+       "      <td id=\"T_44785_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_44785_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_44785_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_44785_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_44785_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_44785_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_44785_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_44785_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_44785_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_44785_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_44785_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_44785_row36_col2\" class=\"data row36 col2\" >$ 4,289,253,931</td>\n",
+       "      <td id=\"T_44785_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_44785_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_44785_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_44785_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_44785_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_44785_row37_col2\" class=\"data row37 col2\" >$ 4,062</td>\n",
+       "      <td id=\"T_44785_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_44785_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_44785_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_44785_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_44785_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_44785_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_44785_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_44785_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_44785_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_44785_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_44785_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_44785_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_44785_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_44785_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_44785_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_44785_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_44785_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_44785_row40_col2\" class=\"data row40 col2\" >$ 187,500</td>\n",
+       "      <td id=\"T_44785_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_44785_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_44785_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_44785_row40_col6\" class=\"data row40 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_44785_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_44785_row41_col2\" class=\"data row41 col2\" >$ 38,204,331</td>\n",
+       "      <td id=\"T_44785_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_44785_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_44785_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_44785_row41_col6\" class=\"data row41 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_44785_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_44785_row42_col2\" class=\"data row42 col2\" >$ 8,141,760</td>\n",
+       "      <td id=\"T_44785_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_44785_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_44785_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_44785_row42_col6\" class=\"data row42 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_44785_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_44785_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_44785_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_44785_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_44785_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_44785_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_44785_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_44785_row44_col2\" class=\"data row44 col2\" >$ 46,533,591</td>\n",
+       "      <td id=\"T_44785_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_44785_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_44785_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_44785_row44_col6\" class=\"data row44 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_44785_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_44785_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_44785_row45_col2\" class=\"data row45 col2\" >$ 44</td>\n",
+       "      <td id=\"T_44785_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_44785_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_44785_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_44785_row45_col6\" class=\"data row45 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x166459b90>"
+       "<pandas.io.formats.style.Styler at 0x15a35d0d0>"
       ]
      },
      "execution_count": 5,
@@ -1771,7 +1800,7 @@
     "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "\n",
-    "Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "Reactor_data_factory = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[0]\n",
     "\n",
     "Reactor_data_factory_land_taxes = add_land_cost(Reactor_data_factory , land_cost_per_acre_0, reactor_power)\n",
     "Reactor_data_factory_land_taxes_pretty = prettify(Reactor_data_factory_land_taxes,\\\n",
@@ -1797,199 +1826,206 @@
    "id": "51d27779-5c59-424c-9368-0d456dbcac09",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The current construction duration (months) =  99\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_3bfff caption {\n",
+       "#T_b322a caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_3bfff_row12_col0, #T_3bfff_row12_col1, #T_3bfff_row12_col2, #T_3bfff_row12_col3, #T_3bfff_row12_col4, #T_3bfff_row12_col5, #T_3bfff_row12_col6 {\n",
+       "#T_b322a_row12_col0, #T_b322a_row12_col1, #T_b322a_row12_col2, #T_b322a_row12_col3, #T_b322a_row12_col4, #T_b322a_row12_col5, #T_b322a_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_3bfff\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost, taxes and BOP/RP grades Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
+       "<table id=\"T_b322a\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost, taxes and BOP/RP grades Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_3bfff_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_3bfff_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_3bfff_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_3bfff_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_3bfff_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_3bfff_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_3bfff_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_b322a_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_b322a_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_b322a_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_b322a_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_b322a_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_b322a_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_b322a_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_3bfff_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_3bfff_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_3bfff_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_3bfff_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_3bfff_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_3bfff_row13_col2\" class=\"data row13 col2\" >$ 240,870,976</td>\n",
-       "      <td id=\"T_3bfff_row13_col3\" class=\"data row13 col3\" >$ 64,102,415</td>\n",
-       "      <td id=\"T_3bfff_row13_col4\" class=\"data row13 col4\" >2,858,447 hrs</td>\n",
-       "      <td id=\"T_3bfff_row13_col5\" class=\"data row13 col5\" >$ 143,579,258</td>\n",
-       "      <td id=\"T_3bfff_row13_col6\" class=\"data row13 col6\" >$ 33,189,303</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_3bfff_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_3bfff_row14_col2\" class=\"data row14 col2\" >$ 145,108,928</td>\n",
-       "      <td id=\"T_3bfff_row14_col3\" class=\"data row14 col3\" >$ 57,583,605</td>\n",
-       "      <td id=\"T_3bfff_row14_col4\" class=\"data row14 col4\" >1,605,670 hrs</td>\n",
-       "      <td id=\"T_3bfff_row14_col5\" class=\"data row14 col5\" >$ 81,082,169</td>\n",
-       "      <td id=\"T_3bfff_row14_col6\" class=\"data row14 col6\" >$ 6,443,153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_3bfff_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_3bfff_row15_col2\" class=\"data row15 col2\" >$ 5,711,051</td>\n",
-       "      <td id=\"T_3bfff_row15_col3\" class=\"data row15 col3\" >$ 372,578</td>\n",
-       "      <td id=\"T_3bfff_row15_col4\" class=\"data row15 col4\" >61,440 hrs</td>\n",
-       "      <td id=\"T_3bfff_row15_col5\" class=\"data row15 col5\" >$ 3,168,305</td>\n",
-       "      <td id=\"T_3bfff_row15_col6\" class=\"data row15 col6\" >$ 2,170,167</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_3bfff_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_3bfff_row16_col2\" class=\"data row16 col2\" >$ 90,050,998</td>\n",
-       "      <td id=\"T_3bfff_row16_col3\" class=\"data row16 col3\" >$ 6,146,232</td>\n",
-       "      <td id=\"T_3bfff_row16_col4\" class=\"data row16 col4\" >1,191,337 hrs</td>\n",
-       "      <td id=\"T_3bfff_row16_col5\" class=\"data row16 col5\" >$ 59,328,783</td>\n",
-       "      <td id=\"T_3bfff_row16_col6\" class=\"data row16 col6\" >$ 24,575,983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_3bfff_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_3bfff_row17_col2\" class=\"data row17 col2\" >$ 680,565,566</td>\n",
-       "      <td id=\"T_3bfff_row17_col3\" class=\"data row17 col3\" >$ 579,093,613</td>\n",
-       "      <td id=\"T_3bfff_row17_col4\" class=\"data row17 col4\" >1,809,704 hrs</td>\n",
-       "      <td id=\"T_3bfff_row17_col5\" class=\"data row17 col5\" >$ 97,213,739</td>\n",
-       "      <td id=\"T_3bfff_row17_col6\" class=\"data row17 col6\" >$ 4,258,215</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_3bfff_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_3bfff_row18_col2\" class=\"data row18 col2\" >$ 166,743,850</td>\n",
-       "      <td id=\"T_3bfff_row18_col3\" class=\"data row18 col3\" >$ 129,630,761</td>\n",
-       "      <td id=\"T_3bfff_row18_col4\" class=\"data row18 col4\" >650,212 hrs</td>\n",
-       "      <td id=\"T_3bfff_row18_col5\" class=\"data row18 col5\" >$ 34,420,102</td>\n",
-       "      <td id=\"T_3bfff_row18_col6\" class=\"data row18 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_3bfff_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_3bfff_row19_col2\" class=\"data row19 col2\" >$ 125,457,949</td>\n",
-       "      <td id=\"T_3bfff_row19_col3\" class=\"data row19 col3\" >$ 107,565,972</td>\n",
-       "      <td id=\"T_3bfff_row19_col4\" class=\"data row19 col4\" >335,825 hrs</td>\n",
-       "      <td id=\"T_3bfff_row19_col5\" class=\"data row19 col5\" >$ 17,891,977</td>\n",
-       "      <td id=\"T_3bfff_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_3bfff_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_3bfff_row20_col2\" class=\"data row20 col2\" >$ 41,285,901</td>\n",
-       "      <td id=\"T_3bfff_row20_col3\" class=\"data row20 col3\" >$ 22,064,788</td>\n",
-       "      <td id=\"T_3bfff_row20_col4\" class=\"data row20 col4\" >314,387 hrs</td>\n",
-       "      <td id=\"T_3bfff_row20_col5\" class=\"data row20 col5\" >$ 16,528,125</td>\n",
-       "      <td id=\"T_3bfff_row20_col6\" class=\"data row20 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_3bfff_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_3bfff_row21_col2\" class=\"data row21 col2\" >$ 67,451,645</td>\n",
-       "      <td id=\"T_3bfff_row21_col3\" class=\"data row21 col3\" >$ 13,662,941</td>\n",
-       "      <td id=\"T_3bfff_row21_col4\" class=\"data row21 col4\" >767,077 hrs</td>\n",
-       "      <td id=\"T_3bfff_row21_col5\" class=\"data row21 col5\" >$ 41,345,409</td>\n",
-       "      <td id=\"T_3bfff_row21_col6\" class=\"data row21 col6\" >$ 12,443,295</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_3bfff_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_3bfff_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_3bfff_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_3bfff_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_3bfff_row23_col2\" class=\"data row23 col2\" >$ 25,655,316</td>\n",
-       "      <td id=\"T_3bfff_row23_col3\" class=\"data row23 col3\" >$ 8,372,438</td>\n",
-       "      <td id=\"T_3bfff_row23_col4\" class=\"data row23 col4\" >278,805 hrs</td>\n",
-       "      <td id=\"T_3bfff_row23_col5\" class=\"data row23 col5\" >$ 15,110,212</td>\n",
-       "      <td id=\"T_3bfff_row23_col6\" class=\"data row23 col6\" >$ 2,172,665</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_3bfff_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_3bfff_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_3bfff_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_3bfff_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_3bfff_row26_col2\" class=\"data row26 col2\" >$ 1,461,089,987</td>\n",
-       "      <td id=\"T_3bfff_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_3bfff_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_3bfff_row27_col2\" class=\"data row27 col2\" >$ 4,701</td>\n",
-       "      <td id=\"T_3bfff_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3bfff_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_3bfff_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_b322a_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_b322a_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_b322a_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_b322a_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_b322a_row13_col2\" class=\"data row13 col2\" >$ 908,799,920</td>\n",
+       "      <td id=\"T_b322a_row13_col3\" class=\"data row13 col3\" >$ 89,808,919</td>\n",
+       "      <td id=\"T_b322a_row13_col4\" class=\"data row13 col4\" >11,759,127 hrs</td>\n",
+       "      <td id=\"T_b322a_row13_col5\" class=\"data row13 col5\" >$ 588,199,484</td>\n",
+       "      <td id=\"T_b322a_row13_col6\" class=\"data row13 col6\" >$ 230,791,516</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_b322a_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_b322a_row14_col2\" class=\"data row14 col2\" >$ 413,396,748</td>\n",
+       "      <td id=\"T_b322a_row14_col3\" class=\"data row14 col3\" >$ 65,728,880</td>\n",
+       "      <td id=\"T_b322a_row14_col4\" class=\"data row14 col4\" >5,420,558 hrs</td>\n",
+       "      <td id=\"T_b322a_row14_col5\" class=\"data row14 col5\" >$ 264,358,228</td>\n",
+       "      <td id=\"T_b322a_row14_col6\" class=\"data row14 col6\" >$ 83,309,639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_b322a_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_b322a_row15_col2\" class=\"data row15 col2\" >$ 9,154,233</td>\n",
+       "      <td id=\"T_b322a_row15_col3\" class=\"data row15 col3\" >$ 681,903</td>\n",
+       "      <td id=\"T_b322a_row15_col4\" class=\"data row15 col4\" >98,368 hrs</td>\n",
+       "      <td id=\"T_b322a_row15_col5\" class=\"data row15 col5\" >$ 5,075,395</td>\n",
+       "      <td id=\"T_b322a_row15_col6\" class=\"data row15 col6\" >$ 3,396,935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_b322a_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_b322a_row16_col2\" class=\"data row16 col2\" >$ 486,248,939</td>\n",
+       "      <td id=\"T_b322a_row16_col3\" class=\"data row16 col3\" >$ 23,398,136</td>\n",
+       "      <td id=\"T_b322a_row16_col4\" class=\"data row16 col4\" >6,240,200 hrs</td>\n",
+       "      <td id=\"T_b322a_row16_col5\" class=\"data row16 col5\" >$ 318,765,862</td>\n",
+       "      <td id=\"T_b322a_row16_col6\" class=\"data row16 col6\" >$ 144,084,942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_b322a_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_b322a_row17_col2\" class=\"data row17 col2\" >$ 1,832,767,447</td>\n",
+       "      <td id=\"T_b322a_row17_col3\" class=\"data row17 col3\" >$ 1,549,983,253</td>\n",
+       "      <td id=\"T_b322a_row17_col4\" class=\"data row17 col4\" >4,903,888 hrs</td>\n",
+       "      <td id=\"T_b322a_row17_col5\" class=\"data row17 col5\" >$ 261,886,915</td>\n",
+       "      <td id=\"T_b322a_row17_col6\" class=\"data row17 col6\" >$ 20,897,278</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_b322a_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_b322a_row18_col2\" class=\"data row18 col2\" >$ 442,090,029</td>\n",
+       "      <td id=\"T_b322a_row18_col3\" class=\"data row18 col3\" >$ 346,609,565</td>\n",
+       "      <td id=\"T_b322a_row18_col4\" class=\"data row18 col4\" >1,691,770 hrs</td>\n",
+       "      <td id=\"T_b322a_row18_col5\" class=\"data row18 col5\" >$ 89,653,109</td>\n",
+       "      <td id=\"T_b322a_row18_col6\" class=\"data row18 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_b322a_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_b322a_row19_col2\" class=\"data row19 col2\" >$ 352,534,723</td>\n",
+       "      <td id=\"T_b322a_row19_col3\" class=\"data row19 col3\" >$ 298,760,854</td>\n",
+       "      <td id=\"T_b322a_row19_col4\" class=\"data row19 col4\" >1,009,314 hrs</td>\n",
+       "      <td id=\"T_b322a_row19_col5\" class=\"data row19 col5\" >$ 53,773,868</td>\n",
+       "      <td id=\"T_b322a_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_b322a_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_b322a_row20_col2\" class=\"data row20 col2\" >$ 89,555,306</td>\n",
+       "      <td id=\"T_b322a_row20_col3\" class=\"data row20 col3\" >$ 47,848,711</td>\n",
+       "      <td id=\"T_b322a_row20_col4\" class=\"data row20 col4\" >682,456 hrs</td>\n",
+       "      <td id=\"T_b322a_row20_col5\" class=\"data row20 col5\" >$ 35,879,240</td>\n",
+       "      <td id=\"T_b322a_row20_col6\" class=\"data row20 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_b322a_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_b322a_row21_col2\" class=\"data row21 col2\" >$ 140,508,400</td>\n",
+       "      <td id=\"T_b322a_row21_col3\" class=\"data row21 col3\" >$ 28,461,247</td>\n",
+       "      <td id=\"T_b322a_row21_col4\" class=\"data row21 col4\" >1,597,897 hrs</td>\n",
+       "      <td id=\"T_b322a_row21_col5\" class=\"data row21 col5\" >$ 86,126,547</td>\n",
+       "      <td id=\"T_b322a_row21_col6\" class=\"data row21 col6\" >$ 25,920,606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_b322a_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_b322a_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_b322a_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_b322a_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_b322a_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_b322a_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_b322a_row23_col2\" class=\"data row23 col2\" >$ 214,388,491</td>\n",
+       "      <td id=\"T_b322a_row23_col3\" class=\"data row23 col3\" >$ 65,401,342</td>\n",
+       "      <td id=\"T_b322a_row23_col4\" class=\"data row23 col4\" >2,408,453 hrs</td>\n",
+       "      <td id=\"T_b322a_row23_col5\" class=\"data row23 col5\" >$ 129,937,710</td>\n",
+       "      <td id=\"T_b322a_row23_col6\" class=\"data row23 col6\" >$ 19,049,439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_b322a_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_b322a_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_b322a_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_b322a_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_b322a_row26_col2\" class=\"data row26 col2\" >$ 3,990,240,758</td>\n",
+       "      <td id=\"T_b322a_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_b322a_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_b322a_row27_col2\" class=\"data row27 col2\" >$ 3,779</td>\n",
+       "      <td id=\"T_b322a_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_b322a_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_b322a_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x167274c90>"
+       "<pandas.io.formats.style.Styler at 0x15a60ecd0>"
       ]
      },
      "execution_count": 6,
@@ -2003,10 +2039,17 @@
     "\n",
     "# If the reactor building is non nuclear, the cost reduction factor for acount 212 is 0.6\n",
     "\n",
-    "def add_BOP_RP_grades(Reactor_data_updated_1, RB_grade_0, BOP_grade_0, power):\n",
+    "def add_BOP_RP_grades(Reactor_data_updated_1, RB_grade_0, BOP_grade_0, power, reactor_type, n_th, mod_0):\n",
+    "    \n",
+    "    RB_grade = RB_grade_0     # Does not change when building more units. it is either always nuclear or always non nuclear\n",
     "    \n",
-    "    RB_grade = RB_grade_0     # Does not change when building more units\n",
-    "    BOP_grade = BOP_grade_0   # Does not change when building more units\n",
+    "    \n",
+    "    # If n >=2: BoP commercial = True : non_nuclear\n",
+    "    if n_th == 1:\n",
+    "        BOP_grade = BOP_grade_0\n",
+    "    elif n_th >=2:\n",
+    "        BOP_grade = \"non_nuclear\"\n",
+    "             \n",
     "    \n",
     "    db = pd.DataFrame()\n",
     "\n",
@@ -2069,25 +2112,48 @@
     "    Reactor_data_updated_2_ = Reactor_data_updated_2[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\\\n",
     "                    'Site Material Cost']].copy()\n",
     "    \n",
-    "    return Reactor_data_updated_2_  \n",
+    "\n",
+    "     \n",
+    "    if reactor_type == \"Concept A\":\n",
+    "        duration = 125\n",
+    "    elif reactor_type == \"Concept B\": \n",
+    "        duration = 80\n",
+    "          \n",
+    "    new_dur = update_cons_duration(Reactor_data_updated_1, Reactor_data_updated_2,  duration)\n",
+    "   \n",
+    "     #apply modularity factor affecting the construction duration \n",
+    "    if n_th == 1:\n",
+    "        mod = mod_0\n",
+    "    elif n_th >= 2:\n",
+    "        mod =  \"modularized\"\n",
+    "   \n",
+    "     \n",
+    "    if mod == \"modularized\" :\n",
+    "        mod_factor = 0.8\n",
+    "    else:   \n",
+    "        mod_factor = 1\n",
+    "    \n",
+    "    new_dur_1 = new_dur * mod_factor \n",
+    "    return Reactor_data_updated_2_ , new_dur_1\n",
     "\n",
     "\n",
     "# # Example \n",
     "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "\n",
-    "Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "Reactor_data_factory = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[0]\n",
     "\n",
     "Reactor_data_factory_land_taxes = add_land_cost(Reactor_data_factory , land_cost_per_acre_0, reactor_power)\n",
-    "Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power)\n",
-    "\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades_result = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0)\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades = Reactor_data_factory_land_taxes_BOP_RP_grades_result[0]\n",
+    "current_cons_duration = Reactor_data_factory_land_taxes_BOP_RP_grades_result[1][0]\n",
     "\n",
     "\n",
     "Reactor_data_factory_land_taxes_BOP_RP_grades_pretty = prettify(Reactor_data_factory_land_taxes_BOP_RP_grades ,\\\n",
     "    f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost, taxes and BOP/RP grades Included  <br> Displaying Direct Cost only<br><br> \", \"no_subsidies\")\n",
     "\n",
     "\n",
-    "\n",
+    "print(\"The current construction duration (months) = \", int(np.round(current_cons_duration,0)) )\n",
     "Reactor_data_factory_land_taxes_BOP_RP_grades_pretty.hide(subset=hidden_list1, axis=0) # show direct cost only \n"
    ]
   },
@@ -2110,195 +2176,195 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_59213 caption {\n",
+       "#T_48d8e caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_59213_row12_col0, #T_59213_row12_col1, #T_59213_row12_col2, #T_59213_row12_col3, #T_59213_row12_col4, #T_59213_row12_col5, #T_59213_row12_col6 {\n",
+       "#T_48d8e_row12_col0, #T_48d8e_row12_col1, #T_48d8e_row12_col2, #T_48d8e_row12_col3, #T_48d8e_row12_col4, #T_48d8e_row12_col5, #T_48d8e_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_59213\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost, taxes, BOP/RP grades , bulk ordering Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
+       "<table id=\"T_48d8e\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Factories Cost, land cost, taxes, BOP/RP grades , bulk ordering Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_59213_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_59213_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_59213_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_59213_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_59213_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_59213_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_59213_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_48d8e_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_48d8e_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_48d8e_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_48d8e_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_48d8e_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_48d8e_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_48d8e_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_59213_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_59213_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_59213_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_59213_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_59213_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_59213_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_59213_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_59213_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_59213_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_59213_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_59213_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_59213_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_59213_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_59213_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_59213_row13_col2\" class=\"data row13 col2\" >$ 240,870,976</td>\n",
-       "      <td id=\"T_59213_row13_col3\" class=\"data row13 col3\" >$ 64,102,415</td>\n",
-       "      <td id=\"T_59213_row13_col4\" class=\"data row13 col4\" >2,858,447 hrs</td>\n",
-       "      <td id=\"T_59213_row13_col5\" class=\"data row13 col5\" >$ 143,579,258</td>\n",
-       "      <td id=\"T_59213_row13_col6\" class=\"data row13 col6\" >$ 33,189,303</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_59213_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_59213_row14_col2\" class=\"data row14 col2\" >$ 145,108,928</td>\n",
-       "      <td id=\"T_59213_row14_col3\" class=\"data row14 col3\" >$ 57,583,605</td>\n",
-       "      <td id=\"T_59213_row14_col4\" class=\"data row14 col4\" >1,605,670 hrs</td>\n",
-       "      <td id=\"T_59213_row14_col5\" class=\"data row14 col5\" >$ 81,082,169</td>\n",
-       "      <td id=\"T_59213_row14_col6\" class=\"data row14 col6\" >$ 6,443,153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_59213_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_59213_row15_col2\" class=\"data row15 col2\" >$ 5,711,051</td>\n",
-       "      <td id=\"T_59213_row15_col3\" class=\"data row15 col3\" >$ 372,578</td>\n",
-       "      <td id=\"T_59213_row15_col4\" class=\"data row15 col4\" >61,440 hrs</td>\n",
-       "      <td id=\"T_59213_row15_col5\" class=\"data row15 col5\" >$ 3,168,305</td>\n",
-       "      <td id=\"T_59213_row15_col6\" class=\"data row15 col6\" >$ 2,170,167</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_59213_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_59213_row16_col2\" class=\"data row16 col2\" >$ 90,050,998</td>\n",
-       "      <td id=\"T_59213_row16_col3\" class=\"data row16 col3\" >$ 6,146,232</td>\n",
-       "      <td id=\"T_59213_row16_col4\" class=\"data row16 col4\" >1,191,337 hrs</td>\n",
-       "      <td id=\"T_59213_row16_col5\" class=\"data row16 col5\" >$ 59,328,783</td>\n",
-       "      <td id=\"T_59213_row16_col6\" class=\"data row16 col6\" >$ 24,575,983</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_59213_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_59213_row17_col2\" class=\"data row17 col2\" >$ 469,343,190</td>\n",
-       "      <td id=\"T_59213_row17_col3\" class=\"data row17 col3\" >$ 367,871,237</td>\n",
-       "      <td id=\"T_59213_row17_col4\" class=\"data row17 col4\" >1,809,704 hrs</td>\n",
-       "      <td id=\"T_59213_row17_col5\" class=\"data row17 col5\" >$ 97,213,739</td>\n",
-       "      <td id=\"T_59213_row17_col6\" class=\"data row17 col6\" >$ 4,258,215</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_59213_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_59213_row18_col2\" class=\"data row18 col2\" >$ 118,425,483</td>\n",
-       "      <td id=\"T_59213_row18_col3\" class=\"data row18 col3\" >$ 81,312,394</td>\n",
-       "      <td id=\"T_59213_row18_col4\" class=\"data row18 col4\" >650,212 hrs</td>\n",
-       "      <td id=\"T_59213_row18_col5\" class=\"data row18 col5\" >$ 34,420,102</td>\n",
-       "      <td id=\"T_59213_row18_col6\" class=\"data row18 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_59213_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_59213_row19_col2\" class=\"data row19 col2\" >$ 77,139,583</td>\n",
-       "      <td id=\"T_59213_row19_col3\" class=\"data row19 col3\" >$ 59,247,606</td>\n",
-       "      <td id=\"T_59213_row19_col4\" class=\"data row19 col4\" >335,825 hrs</td>\n",
-       "      <td id=\"T_59213_row19_col5\" class=\"data row19 col5\" >$ 17,891,977</td>\n",
-       "      <td id=\"T_59213_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_59213_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_59213_row20_col2\" class=\"data row20 col2\" >$ 41,285,901</td>\n",
-       "      <td id=\"T_59213_row20_col3\" class=\"data row20 col3\" >$ 22,064,788</td>\n",
-       "      <td id=\"T_59213_row20_col4\" class=\"data row20 col4\" >314,387 hrs</td>\n",
-       "      <td id=\"T_59213_row20_col5\" class=\"data row20 col5\" >$ 16,528,125</td>\n",
-       "      <td id=\"T_59213_row20_col6\" class=\"data row20 col6\" >$ 2,692,988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_59213_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_59213_row21_col2\" class=\"data row21 col2\" >$ 67,451,645</td>\n",
-       "      <td id=\"T_59213_row21_col3\" class=\"data row21 col3\" >$ 13,662,941</td>\n",
-       "      <td id=\"T_59213_row21_col4\" class=\"data row21 col4\" >767,077 hrs</td>\n",
-       "      <td id=\"T_59213_row21_col5\" class=\"data row21 col5\" >$ 41,345,409</td>\n",
-       "      <td id=\"T_59213_row21_col6\" class=\"data row21 col6\" >$ 12,443,295</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_59213_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_59213_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_59213_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_59213_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_59213_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_59213_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_59213_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_59213_row23_col2\" class=\"data row23 col2\" >$ 25,655,316</td>\n",
-       "      <td id=\"T_59213_row23_col3\" class=\"data row23 col3\" >$ 8,372,438</td>\n",
-       "      <td id=\"T_59213_row23_col4\" class=\"data row23 col4\" >278,805 hrs</td>\n",
-       "      <td id=\"T_59213_row23_col5\" class=\"data row23 col5\" >$ 15,110,212</td>\n",
-       "      <td id=\"T_59213_row23_col6\" class=\"data row23 col6\" >$ 2,172,665</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_59213_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_59213_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_59213_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_59213_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_59213_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_59213_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_59213_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_59213_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_59213_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_59213_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_59213_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_59213_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_59213_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_59213_row26_col2\" class=\"data row26 col2\" >$ 1,201,549,244</td>\n",
-       "      <td id=\"T_59213_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_59213_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_59213_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_59213_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_59213_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_59213_row27_col2\" class=\"data row27 col2\" >$ 3,866</td>\n",
-       "      <td id=\"T_59213_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_59213_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_59213_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_59213_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_59213_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_59213_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_59213_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_59213_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_59213_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_59213_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_59213_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_48d8e_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_48d8e_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_48d8e_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_48d8e_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_48d8e_row13_col2\" class=\"data row13 col2\" >$ 908,799,920</td>\n",
+       "      <td id=\"T_48d8e_row13_col3\" class=\"data row13 col3\" >$ 89,808,919</td>\n",
+       "      <td id=\"T_48d8e_row13_col4\" class=\"data row13 col4\" >11,759,127 hrs</td>\n",
+       "      <td id=\"T_48d8e_row13_col5\" class=\"data row13 col5\" >$ 588,199,484</td>\n",
+       "      <td id=\"T_48d8e_row13_col6\" class=\"data row13 col6\" >$ 230,791,516</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_48d8e_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_48d8e_row14_col2\" class=\"data row14 col2\" >$ 413,396,748</td>\n",
+       "      <td id=\"T_48d8e_row14_col3\" class=\"data row14 col3\" >$ 65,728,880</td>\n",
+       "      <td id=\"T_48d8e_row14_col4\" class=\"data row14 col4\" >5,420,558 hrs</td>\n",
+       "      <td id=\"T_48d8e_row14_col5\" class=\"data row14 col5\" >$ 264,358,228</td>\n",
+       "      <td id=\"T_48d8e_row14_col6\" class=\"data row14 col6\" >$ 83,309,639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_48d8e_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_48d8e_row15_col2\" class=\"data row15 col2\" >$ 9,154,233</td>\n",
+       "      <td id=\"T_48d8e_row15_col3\" class=\"data row15 col3\" >$ 681,903</td>\n",
+       "      <td id=\"T_48d8e_row15_col4\" class=\"data row15 col4\" >98,368 hrs</td>\n",
+       "      <td id=\"T_48d8e_row15_col5\" class=\"data row15 col5\" >$ 5,075,395</td>\n",
+       "      <td id=\"T_48d8e_row15_col6\" class=\"data row15 col6\" >$ 3,396,935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_48d8e_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_48d8e_row16_col2\" class=\"data row16 col2\" >$ 486,248,939</td>\n",
+       "      <td id=\"T_48d8e_row16_col3\" class=\"data row16 col3\" >$ 23,398,136</td>\n",
+       "      <td id=\"T_48d8e_row16_col4\" class=\"data row16 col4\" >6,240,200 hrs</td>\n",
+       "      <td id=\"T_48d8e_row16_col5\" class=\"data row16 col5\" >$ 318,765,862</td>\n",
+       "      <td id=\"T_48d8e_row16_col6\" class=\"data row16 col6\" >$ 144,084,942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_48d8e_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_48d8e_row17_col2\" class=\"data row17 col2\" >$ 1,255,252,471</td>\n",
+       "      <td id=\"T_48d8e_row17_col3\" class=\"data row17 col3\" >$ 972,468,277</td>\n",
+       "      <td id=\"T_48d8e_row17_col4\" class=\"data row17 col4\" >4,903,888 hrs</td>\n",
+       "      <td id=\"T_48d8e_row17_col5\" class=\"data row17 col5\" >$ 261,886,915</td>\n",
+       "      <td id=\"T_48d8e_row17_col6\" class=\"data row17 col6\" >$ 20,897,278</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_48d8e_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_48d8e_row18_col2\" class=\"data row18 col2\" >$ 297,567,727</td>\n",
+       "      <td id=\"T_48d8e_row18_col3\" class=\"data row18 col3\" >$ 202,087,264</td>\n",
+       "      <td id=\"T_48d8e_row18_col4\" class=\"data row18 col4\" >1,691,770 hrs</td>\n",
+       "      <td id=\"T_48d8e_row18_col5\" class=\"data row18 col5\" >$ 89,653,109</td>\n",
+       "      <td id=\"T_48d8e_row18_col6\" class=\"data row18 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_48d8e_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_48d8e_row19_col2\" class=\"data row19 col2\" >$ 208,012,421</td>\n",
+       "      <td id=\"T_48d8e_row19_col3\" class=\"data row19 col3\" >$ 154,238,553</td>\n",
+       "      <td id=\"T_48d8e_row19_col4\" class=\"data row19 col4\" >1,009,314 hrs</td>\n",
+       "      <td id=\"T_48d8e_row19_col5\" class=\"data row19 col5\" >$ 53,773,868</td>\n",
+       "      <td id=\"T_48d8e_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_48d8e_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_48d8e_row20_col2\" class=\"data row20 col2\" >$ 89,555,306</td>\n",
+       "      <td id=\"T_48d8e_row20_col3\" class=\"data row20 col3\" >$ 47,848,711</td>\n",
+       "      <td id=\"T_48d8e_row20_col4\" class=\"data row20 col4\" >682,456 hrs</td>\n",
+       "      <td id=\"T_48d8e_row20_col5\" class=\"data row20 col5\" >$ 35,879,240</td>\n",
+       "      <td id=\"T_48d8e_row20_col6\" class=\"data row20 col6\" >$ 5,827,355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_48d8e_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_48d8e_row21_col2\" class=\"data row21 col2\" >$ 140,508,400</td>\n",
+       "      <td id=\"T_48d8e_row21_col3\" class=\"data row21 col3\" >$ 28,461,247</td>\n",
+       "      <td id=\"T_48d8e_row21_col4\" class=\"data row21 col4\" >1,597,897 hrs</td>\n",
+       "      <td id=\"T_48d8e_row21_col5\" class=\"data row21 col5\" >$ 86,126,547</td>\n",
+       "      <td id=\"T_48d8e_row21_col6\" class=\"data row21 col6\" >$ 25,920,606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_48d8e_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_48d8e_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_48d8e_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_48d8e_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_48d8e_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_48d8e_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_48d8e_row23_col2\" class=\"data row23 col2\" >$ 214,388,491</td>\n",
+       "      <td id=\"T_48d8e_row23_col3\" class=\"data row23 col3\" >$ 65,401,342</td>\n",
+       "      <td id=\"T_48d8e_row23_col4\" class=\"data row23 col4\" >2,408,453 hrs</td>\n",
+       "      <td id=\"T_48d8e_row23_col5\" class=\"data row23 col5\" >$ 129,937,710</td>\n",
+       "      <td id=\"T_48d8e_row23_col6\" class=\"data row23 col6\" >$ 19,049,439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_48d8e_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_48d8e_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_48d8e_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_48d8e_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_48d8e_row26_col2\" class=\"data row26 col2\" >$ 3,268,203,480</td>\n",
+       "      <td id=\"T_48d8e_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_48d8e_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_48d8e_row27_col2\" class=\"data row27 col2\" >$ 3,095</td>\n",
+       "      <td id=\"T_48d8e_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_48d8e_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_48d8e_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1673b7e10>"
+       "<pandas.io.formats.style.Styler at 0x15a791490>"
       ]
      },
      "execution_count": 7,
@@ -2355,10 +2421,10 @@
     "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "\n",
-    "Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "Reactor_data_factory = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[0]\n",
     "\n",
     "Reactor_data_factory_land_taxes = add_land_cost(Reactor_data_factory , land_cost_per_acre_0, reactor_power)\n",
-    "Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power)\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0)[0]\n",
     "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder = add_bulk_ordering(Reactor_data_factory_land_taxes_BOP_RP_grades , num_orders, f_22, f_2321, reactor_power)\n",
     "\n",
     "\n",
@@ -2381,199 +2447,206 @@
    "id": "8b6f2170-d021-47fa-bc5d-568f7fd66f13",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The Current Construction Duration is 127 months\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_64a2a caption {\n",
+       "#T_2effe caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_64a2a_row12_col0, #T_64a2a_row12_col1, #T_64a2a_row12_col2, #T_64a2a_row12_col3, #T_64a2a_row12_col4, #T_64a2a_row12_col5, #T_64a2a_row12_col6 {\n",
+       "#T_2effe_row12_col0, #T_2effe_row12_col1, #T_2effe_row12_col2, #T_2effe_row12_col3, #T_2effe_row12_col4, #T_2effe_row12_col5, #T_2effe_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_64a2a\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor Capital Cost Summary <br> Factories Cost, land cost, taxes, BOP/RP grades , bulk ordering, reworking and productivity Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
+       "<table id=\"T_2effe\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor Capital Cost Summary <br> Factories Cost, land cost, taxes, BOP/RP grades , bulk ordering, reworking and productivity Included  <br> Displaying Direct Cost only<br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_64a2a_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_64a2a_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_64a2a_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_64a2a_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_64a2a_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_64a2a_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_64a2a_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_2effe_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_2effe_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_2effe_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_2effe_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_2effe_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_2effe_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_2effe_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_64a2a_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_64a2a_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_64a2a_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_64a2a_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_64a2a_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_64a2a_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_64a2a_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_64a2a_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_64a2a_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_64a2a_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_64a2a_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_64a2a_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_64a2a_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_64a2a_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_64a2a_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_64a2a_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_64a2a_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_64a2a_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_64a2a_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_64a2a_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_64a2a_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_64a2a_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_64a2a_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_64a2a_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_64a2a_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_64a2a_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_64a2a_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_64a2a_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_64a2a_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_64a2a_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_64a2a_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_64a2a_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_64a2a_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_64a2a_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_64a2a_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_64a2a_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_64a2a_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_64a2a_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_64a2a_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_64a2a_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_64a2a_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_64a2a_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_64a2a_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_64a2a_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_64a2a_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_64a2a_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_64a2a_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_64a2a_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_64a2a_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_64a2a_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_64a2a_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_64a2a_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_64a2a_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_64a2a_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_64a2a_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_64a2a_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_64a2a_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_64a2a_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_64a2a_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_64a2a_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_64a2a_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_64a2a_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_64a2a_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_64a2a_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_64a2a_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_64a2a_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_64a2a_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_64a2a_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_64a2a_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_64a2a_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_64a2a_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_64a2a_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_64a2a_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_64a2a_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_64a2a_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_64a2a_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_64a2a_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_64a2a_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_2effe_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_2effe_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_2effe_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_2effe_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_2effe_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_2effe_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_2effe_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_2effe_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_2effe_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_2effe_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_2effe_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_2effe_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_2effe_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_2effe_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_2effe_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_2effe_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_2effe_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_2effe_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_2effe_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_2effe_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_2effe_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_2effe_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_2effe_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_2effe_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_2effe_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_2effe_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_2effe_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_2effe_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_2effe_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_2effe_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_2effe_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_2effe_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_2effe_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_2effe_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_2effe_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_2effe_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_2effe_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_2effe_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_2effe_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_2effe_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_2effe_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_2effe_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_2effe_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_2effe_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_2effe_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_2effe_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_2effe_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_2effe_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_2effe_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_2effe_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_2effe_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_2effe_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_2effe_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_2effe_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_2effe_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_2effe_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_2effe_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_2effe_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_2effe_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_2effe_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_2effe_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_2effe_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_2effe_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_2effe_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_2effe_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_2effe_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_2effe_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_2effe_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_2effe_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_2effe_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_2effe_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_2effe_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_2effe_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_2effe_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_2effe_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_2effe_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_2effe_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_2effe_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_2effe_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x167532e10>"
+       "<pandas.io.formats.style.Styler at 0x15b8a3550>"
       ]
      },
      "execution_count": 8,
@@ -2582,7 +2655,7 @@
     }
    ],
    "source": [
-    "def add_reworking_productivity(Reactor_data_updated_4, reactor_type, n_th, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, power):\n",
+    "def add_reworking_productivity(Reactor_data_updated_4, reactor_type, n_th, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, power, prev_cons_duration, baseline_lab_hours):\n",
     "    #Reworking = f(AE, CE, design completion)\n",
     "    \n",
     "    if n_th == 1:\n",
@@ -2602,7 +2675,7 @@
     "    if reactor_type == \"Concept B\":\n",
     "        reworking_factor =  (-0.9*design_completion+ 1.9) * (-0.15*ae_exp+1.3) * (-0.15*ce_exp+1.3) \n",
     "\n",
-    "    if reactor_type == \"Concept A\":\n",
+    "    elif reactor_type == \"Concept A\":\n",
     "        reworking_factor =  (-0.69*design_completion+ 1.69) * (-0.125*ae_exp+1.25) * (-0.125*ce_exp+1.25) \n",
     "\n",
     "    db = pd.DataFrame()\n",
@@ -2627,15 +2700,22 @@
     "            ((( Reactor_data_updated_4.loc[ Reactor_data_updated_4.Account == x, 'Site Material Cost']).values)[0])*reworking_factor \n",
     "\n",
     "\n",
-    "    # update the construction duration\n",
+    "    \n",
     "\n",
     "    Reactor_data_updated_5 = update_high_level_costs(db, power)\n",
     "    Reactor_data_updated_5_ = pd.DataFrame()\n",
     "    Reactor_data_updated_5_ = Reactor_data_updated_5[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\\\n",
     "                    'Site Material Cost']].copy()\n",
     "    \n",
-    "    return Reactor_data_updated_5_  \n",
-    "\n",
+    "    # update the construction duration\n",
+    "    if reactor_type == \"Concept A\":\n",
+    "        reactor_type_ref_duration = 125\n",
+    "    elif reactor_type == \"Concept B\": \n",
+    "        reactor_type_ref_duration = 80\n",
+    "        \n",
+    "    new_dur    = update_cons_duration_2(Reactor_data_updated_4, Reactor_data_updated_5_, reactor_type_ref_duration, prev_cons_duration, baseline_lab_hours)\n",
+    "    return Reactor_data_updated_5_  , new_dur\n",
+    " \n",
     "\n",
     "\n",
     "# # Example \n",
@@ -2643,18 +2723,23 @@
     "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
     "\n",
-    "Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "Reactor_data_factory = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[0]\n",
+    "baseline_lab_hours = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))[1]\n",
     "\n",
     "Reactor_data_factory_land_taxes = add_land_cost(Reactor_data_factory , land_cost_per_acre_0, reactor_power)\n",
-    "Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power)\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0)[0]\n",
+    "prev_cons_duration = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0)[1]\n",
     "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder = add_bulk_ordering(Reactor_data_factory_land_taxes_BOP_RP_grades , num_orders, f_22, f_2321, reactor_power)\n",
-    "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity =\\\n",
-    "    add_reworking_productivity(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder , reactor_type, n_th , design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, reactor_power)\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_results =\\\n",
+    "    add_reworking_productivity(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder , reactor_type, n_th , design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, reactor_power, prev_cons_duration, baseline_lab_hours)\n",
     "\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity = Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_results[0]\n",
     "\n",
     "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_pretty = prettify(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity,\\\n",
     "        f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor Capital Cost Summary <br> Factories Cost, land cost, taxes, BOP/RP grades , bulk ordering, reworking and productivity Included  <br> Displaying Direct Cost only<br><br> \", \"no_subsidies\")\n",
-    "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_pretty.hide(subset=hidden_list1, axis=0) # show direct cost only "
+    "\n",
+    "print(f\"The Current Construction Duration is {int(np.round(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_results[1][0],0))} months\")\n",
+    "Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity_pretty.hide(subset=hidden_list1, axis=0) # show direct cost only \n"
    ]
   },
   {
@@ -2675,195 +2760,195 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_5545b caption {\n",
+       "#T_04f42 caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_5545b_row12_col0, #T_5545b_row12_col1, #T_5545b_row12_col2, #T_5545b_row12_col3, #T_5545b_row12_col4, #T_5545b_row12_col5, #T_5545b_row12_col6 {\n",
+       "#T_04f42_row12_col0, #T_04f42_row12_col1, #T_04f42_row12_col2, #T_04f42_row12_col3, #T_04f42_row12_col4, #T_04f42_row12_col5, #T_04f42_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_5545b\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Direct Cost Updated <br><br> </caption>\n",
+       "<table id=\"T_04f42\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Direct Cost Updated <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_5545b_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_5545b_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_5545b_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_5545b_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_5545b_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_5545b_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_5545b_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_04f42_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_04f42_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_04f42_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_04f42_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_04f42_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_04f42_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_04f42_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_5545b_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_5545b_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_5545b_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_5545b_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_5545b_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_5545b_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_5545b_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_5545b_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_5545b_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_5545b_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_5545b_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_5545b_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_5545b_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_5545b_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_5545b_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_5545b_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_5545b_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_5545b_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_5545b_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_5545b_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_5545b_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_5545b_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_5545b_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_5545b_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_5545b_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_5545b_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_5545b_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_5545b_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_5545b_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_5545b_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_5545b_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_5545b_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_5545b_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_5545b_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_5545b_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_5545b_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_5545b_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_5545b_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_5545b_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_5545b_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_5545b_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_5545b_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_5545b_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_5545b_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_5545b_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_5545b_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_5545b_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_5545b_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_5545b_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_5545b_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_5545b_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_5545b_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_5545b_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_5545b_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_5545b_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_5545b_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_5545b_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_5545b_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_5545b_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_5545b_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_5545b_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_5545b_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_5545b_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_5545b_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_5545b_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_5545b_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_5545b_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_5545b_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_5545b_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_5545b_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_5545b_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_5545b_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_5545b_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_5545b_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_5545b_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_5545b_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_5545b_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_5545b_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_04f42_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_04f42_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_04f42_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_04f42_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_04f42_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_04f42_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_04f42_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_04f42_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_04f42_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_04f42_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_04f42_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_04f42_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_04f42_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_04f42_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_04f42_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_04f42_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_04f42_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_04f42_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_04f42_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_04f42_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_04f42_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_04f42_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_04f42_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_04f42_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_04f42_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_04f42_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_04f42_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_04f42_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_04f42_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_04f42_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_04f42_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_04f42_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_04f42_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_04f42_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_04f42_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_04f42_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_04f42_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_04f42_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_04f42_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_04f42_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_04f42_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_04f42_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_04f42_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_04f42_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_04f42_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_04f42_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_04f42_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_04f42_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_04f42_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_04f42_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_04f42_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_04f42_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_04f42_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_04f42_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_04f42_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_04f42_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_04f42_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_04f42_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_04f42_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_04f42_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_04f42_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_04f42_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_04f42_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_04f42_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_04f42_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_04f42_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_04f42_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_04f42_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_04f42_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_04f42_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_04f42_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_04f42_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_04f42_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_04f42_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_04f42_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_04f42_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_04f42_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_04f42_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_04f42_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1665144d0>"
+       "<pandas.io.formats.style.Styler at 0x15b9401d0>"
       ]
      },
      "execution_count": 9,
@@ -2874,102 +2959,31 @@
    "source": [
     "# Combine the previous functions in one function\n",
     "\n",
-    "def update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons):\n",
-    "    reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "    reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "    Reactor_data_factory = add_factory_cost(reactor_data , reactor_power, f_22, f_2321)\n",
+    "def update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0):\n",
+    "    reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "    \n",
+    "    Reactor_data_factory, baseline_lab_hours = (add_factory_cost(reactor_data , reactor_power, f_22, f_2321))\n",
+    "    \n",
     "    Reactor_data_factory_land_taxes = add_land_cost(Reactor_data_factory , land_cost_per_acre_0, reactor_power)\n",
-    "    Reactor_data_factory_land_taxes_BOP_RP_grades = add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power)\n",
+    "    Reactor_data_factory_land_taxes_BOP_RP_grades , prev_cons_duration = (add_BOP_RP_grades(Reactor_data_factory_land_taxes  , RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0))\n",
+    "\n",
     "    Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder = add_bulk_ordering(Reactor_data_factory_land_taxes_BOP_RP_grades , num_orders, f_22, f_2321, reactor_power)\n",
     "    \n",
-    "    Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity =\\\n",
-    "    add_reworking_productivity(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder , reactor_type, n_th , design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, reactor_power)\n",
+    "    Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity , new_dur_2=\\\n",
+    "    (add_reworking_productivity(Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder , reactor_type, n_th , design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, reactor_power, prev_cons_duration, baseline_lab_hours))\n",
     "    \n",
-    "    return Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity\n",
+    "\n",
+    "    return Reactor_data_factory_land_taxes_BOP_RP_grades_bulkOrder_rework_productivity, new_dur_2\n",
     "\n",
     "# example \n",
     "\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "\n",
+    "direct_cost_updated, current_const_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)\n",
     "\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
     "direct_cost_updated_pretty = prettify(direct_cost_updated,\\\n",
     "        f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> Capital Cost Summary - Direct Cost Updated <br><br> \", \"no_subsidies\")\n",
-    "direct_cost_updated_pretty.hide(subset=hidden_list1, axis=0) # show direct cost only "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a96c43fe",
-   "metadata": {},
-   "source": [
-    "### Section 3-5 :Update construction duration from labor hours"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "c4ad50cf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "def update_cons_dur(Reactor_data_0, db, mod_0):\n",
-    "\n",
-    "    #sum of labor hours for Account 20 in the initial estimation (well exectued scenario)\n",
-    "    sum_old_lab_hrs = (Reactor_data_0.loc[Reactor_data_0.Account == 21, 'Site Labor Hours']).values +\\\n",
-    "    (Reactor_data_0.loc[Reactor_data_0.Account == 22, 'Site Labor Hours']).values +\\\n",
-    "    (Reactor_data_0.loc[Reactor_data_0.Account == 23, 'Site Labor Hours']).values+\\\n",
-    "    (Reactor_data_0.loc[Reactor_data_0.Account == 24, 'Site Labor Hours']).values+\\\n",
-    "    (Reactor_data_0.loc[Reactor_data_0.Account == 26, 'Site Labor Hours']).values\n",
-    "\n",
-    "\n",
-    "\n",
-    "    # #sum of labor hours for Account 20 in the new estimation \n",
-    "    sum_new_lab_hrs = (db.loc[db.Account == 21, 'Site Labor Hours']).values +\\\n",
-    "    (db.loc[db.Account == 22, 'Site Labor Hours']).values +\\\n",
-    "    (db.loc[db.Account == 23, 'Site Labor Hours']).values+\\\n",
-    "    (db.loc[db.Account == 24, 'Site Labor Hours']).values+\\\n",
-    "    (db.loc[db.Account == 26, 'Site Labor Hours']).values\n",
-    "\n",
-    "\n",
-    "\n",
-    "    # # # change in labor hours for account 20\n",
-    "    labor_hour_ratio = (sum_new_lab_hrs)/sum_old_lab_hrs   # note that this number can be positive or negative\n",
-    "    labor_hour_ratio \n",
-    "\n",
-    "    # \tFrom the literature   we know that if labor hours changed from 3.8M hours to 20.5M hours (5.4 times), the construction duration changes from 33.2 months to 74.3 months (2.2 times).\n",
-    "    # \tWe also know that if the labor hours multiplier =1, the cons duration multiplier should be 1.\n",
-    "    # \tUsing these two points: \n",
-    "\n",
-    "    # construction duration multiplier = 0.3 * the labor hours multiplier+0.7\n",
-    "\n",
-    "\n",
-    "\n",
-    "    #     # modularity (applied on civil construction only) \"stick_built\"  or \"modularized\"\n",
-    "    mod = mod_0\n",
-    "\n",
-    "    # Modularization effect on the construction duration\n",
-    "    if mod == \"stick_built\":\n",
-    "        mod_factor = 0.8\n",
-    "    elif mod == \"modularized\":\n",
-    "        mod_factor = 1\n",
-    "        \n",
-    "\n",
-    "    # # This is a hypothetical well-executed project taking 64 months (TIMCAT simulation)\n",
-    "    if reactor_type ==  \"Concept B\": \n",
-    "        baseline_construction_duration = 64/mod_factor # months\n",
-    "    elif reactor_type == \"Concept A\":  \n",
-    "        baseline_construction_duration = 100/mod_factor # months\n",
-    "\n",
-    "    actual_construction_duration = baseline_construction_duration*(0.3*labor_hour_ratio+0.7)\n",
-    "    return actual_construction_duration \n",
-    "\n",
-    "# example\n",
-    "\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
-    "act_con_duration = update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n",
-    "# print(f\"The construction duration of the {reactor_type} reactor, without accounting for supply chain dealys, is { np.round( act_con_duration[0]/12 , 1) } years\")"
+    "direct_cost_updated_pretty.hide(subset=hidden_list1, axis=0) # show direct cost only \n"
    ]
   },
   {
@@ -2977,12 +2991,12 @@
    "id": "6a45171f",
    "metadata": {},
    "source": [
-    "### Section 3-6 Learning by doing effect on the cost"
+    "### Section 3-5 Learning by doing effect on the cost"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "id": "d290af08",
    "metadata": {},
    "outputs": [
@@ -2990,198 +3004,198 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_1e59e caption {\n",
+       "#T_4555d caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_1e59e_row12_col0, #T_1e59e_row12_col1, #T_1e59e_row12_col2, #T_1e59e_row12_col3, #T_1e59e_row12_col4, #T_1e59e_row12_col5, #T_1e59e_row12_col6 {\n",
+       "#T_4555d_row12_col0, #T_4555d_row12_col1, #T_4555d_row12_col2, #T_4555d_row12_col3, #T_4555d_row12_col4, #T_4555d_row12_col5, #T_4555d_row12_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_1e59e\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Direct Cost Updated plus learning effect <br> Displaying Direct Cost only<br><br> </caption>\n",
+       "<table id=\"T_4555d\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Direct Cost Updated plus learning effect <br> Displaying Direct Cost only<br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_1e59e_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_1e59e_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_1e59e_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_1e59e_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_1e59e_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_1e59e_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_1e59e_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_4555d_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_4555d_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_4555d_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_4555d_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_4555d_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_4555d_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_4555d_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_1e59e_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_1e59e_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_1e59e_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_1e59e_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_1e59e_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_1e59e_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_1e59e_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_1e59e_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_1e59e_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_1e59e_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_1e59e_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_1e59e_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_1e59e_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_1e59e_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_1e59e_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_1e59e_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_1e59e_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_1e59e_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_1e59e_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_1e59e_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_1e59e_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_1e59e_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_1e59e_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_1e59e_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_1e59e_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_1e59e_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_1e59e_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_1e59e_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_1e59e_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_1e59e_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_1e59e_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_1e59e_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_1e59e_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_1e59e_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_1e59e_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_1e59e_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_1e59e_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_1e59e_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_1e59e_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_1e59e_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_1e59e_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_1e59e_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_1e59e_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_1e59e_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_1e59e_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_1e59e_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_1e59e_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_1e59e_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_1e59e_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_1e59e_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_1e59e_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_1e59e_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_1e59e_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_1e59e_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_1e59e_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_1e59e_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_1e59e_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_1e59e_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_1e59e_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_1e59e_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_1e59e_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_1e59e_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_1e59e_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_1e59e_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_1e59e_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_1e59e_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_1e59e_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_1e59e_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_1e59e_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_1e59e_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_1e59e_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_1e59e_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_1e59e_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_1e59e_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_1e59e_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_1e59e_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_1e59e_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_1e59e_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_4555d_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_4555d_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_4555d_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_4555d_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_4555d_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_4555d_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_4555d_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_4555d_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_4555d_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_4555d_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_4555d_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_4555d_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_4555d_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_4555d_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_4555d_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_4555d_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_4555d_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_4555d_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_4555d_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_4555d_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_4555d_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_4555d_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_4555d_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_4555d_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_4555d_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_4555d_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_4555d_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_4555d_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_4555d_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_4555d_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_4555d_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_4555d_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_4555d_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_4555d_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_4555d_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_4555d_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_4555d_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_4555d_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_4555d_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_4555d_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_4555d_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_4555d_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_4555d_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_4555d_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_4555d_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_4555d_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_4555d_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_4555d_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_4555d_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_4555d_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_4555d_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_4555d_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_4555d_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_4555d_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_4555d_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_4555d_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_4555d_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_4555d_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_4555d_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_4555d_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_4555d_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_4555d_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_4555d_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_4555d_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_4555d_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_4555d_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_4555d_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_4555d_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_4555d_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_4555d_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_4555d_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_4555d_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_4555d_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_4555d_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_4555d_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_4555d_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_4555d_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_4555d_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_4555d_row28_col6\" class=\"data row28 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x16732c0d0>"
+       "<pandas.io.formats.style.Styler at 0x15a37a510>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3245,9 +3259,14 @@
     "    return Reactor_data_updated_6_  \n",
     "\n",
     "\n",
-    "# # Example \n",
+    "# # # Example \n",
     "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
+    "direct_cost_updated = (update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0))[0]\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
     "direct_cost_updated_plus_learning = learning_effect(direct_cost_updated , n_th, standardization_0, reactor_power)\n",
     "\n",
     "direct_cost_updated_plus_learning_pretty = prettify(direct_cost_updated_plus_learning,\\\n",
@@ -3260,12 +3279,12 @@
    "id": "7f1a11ae",
    "metadata": {},
    "source": [
-    "### Section 3-7 supply chain delays"
+    "### Section 3-6 supply chain delays"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "6b94464b",
    "metadata": {},
    "outputs": [],
@@ -3330,14 +3349,12 @@
     "\n",
     "\n",
     "# example\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
     "\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
-    "act_con_duration = update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n",
+    "direct_cost_updated , act_con_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, \\\n",
+    "    design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)\n",
     "\n",
-    "cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n",
-    "# print(f\"The construction duration of the {reactor_type} reactor, accounting for supply chain dealys, is { np.round( cons_duration_plus_delay[0]/12 , 1) } years\")"
+    "cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n"
    ]
   },
   {
@@ -3345,15 +3362,23 @@
    "id": "0d98be43",
    "metadata": {},
    "source": [
-    "### Section 3-8 Learning by doing effect on the construction duration"
+    "### Section 3-7 Learning by doing effect on the construction duration"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "id": "2f8af5f9",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The final construction duration of the Concept A reactor is 138.72 months\n"
+     ]
+    }
+   ],
    "source": [
     "def duration_learning_effect(n_th, standardization_0, actual_construction_duration_plus_delay):\n",
     "    \n",
@@ -3361,22 +3386,20 @@
     "        standardization = 0.7\n",
     "    elif n_th >1:\n",
     "        standardization = standardization_0  \n",
-    "        \n",
     "    # now the effect of learning on the consturction duration\n",
-    "    fitted_LR_duration = 0.15*standardization/0.7\n",
+    "    fitted_LR_duration = 0.103719051*standardization/0.7\n",
     "    duration_multiplier = (1 -fitted_LR_duration)**np.log2(n_th)\n",
     "    final_construction_duration = duration_multiplier *actual_construction_duration_plus_delay\n",
     "    return final_construction_duration \n",
     "\n",
     "# example\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
-    "act_con_duration = update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n",
-    "\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "direct_cost_updated , act_con_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)\n",
     "cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n",
+    "\n",
+    "# cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n",
     "final_con_duration = duration_learning_effect(n_th, standardization_0, cons_duration_plus_delay)\n",
-    "# print(f\"The final construction duration of the {reactor_type} reactor is { np.round( final_con_duration[0]/12 , 1) } years\")"
+    "print(f\"The final construction duration of the {reactor_type} reactor is { np.round( final_con_duration[0] , 2) } months\")"
    ]
   },
   {
@@ -3384,12 +3407,12 @@
    "id": "20719832-5c0c-47ce-8ce7-b712d8b852c3",
    "metadata": {},
    "source": [
-    "### Section 3-9 Calculate the Indirect Cost and the standardization impact"
+    "### Section 3-8 Calculate the Indirect Cost and the standardization impact"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "id": "b0db81dd-fca3-45a3-bcd3-7b2094729da1",
    "metadata": {},
    "outputs": [
@@ -3397,279 +3420,279 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_3e4d6 caption {\n",
+       "#T_090e7 caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_3e4d6_row12_col0, #T_3e4d6_row12_col1, #T_3e4d6_row12_col2, #T_3e4d6_row12_col3, #T_3e4d6_row12_col4, #T_3e4d6_row12_col5, #T_3e4d6_row12_col6, #T_3e4d6_row29_col0, #T_3e4d6_row29_col1, #T_3e4d6_row29_col2, #T_3e4d6_row29_col3, #T_3e4d6_row29_col4, #T_3e4d6_row29_col5, #T_3e4d6_row29_col6 {\n",
+       "#T_090e7_row12_col0, #T_090e7_row12_col1, #T_090e7_row12_col2, #T_090e7_row12_col3, #T_090e7_row12_col4, #T_090e7_row12_col5, #T_090e7_row12_col6, #T_090e7_row29_col0, #T_090e7_row29_col1, #T_090e7_row29_col2, #T_090e7_row29_col3, #T_090e7_row29_col4, #T_090e7_row29_col5, #T_090e7_row29_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_3e4d6\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) <br><br> </caption>\n",
+       "<table id=\"T_090e7\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_3e4d6_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_3e4d6_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_3e4d6_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_3e4d6_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_3e4d6_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_3e4d6_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_3e4d6_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_090e7_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_090e7_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_090e7_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_090e7_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_090e7_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_090e7_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_090e7_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_3e4d6_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_3e4d6_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_3e4d6_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_3e4d6_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_3e4d6_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_3e4d6_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_3e4d6_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_3e4d6_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_3e4d6_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_3e4d6_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_3e4d6_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_3e4d6_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_3e4d6_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_3e4d6_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_3e4d6_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_3e4d6_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_3e4d6_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_3e4d6_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_3e4d6_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_3e4d6_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_3e4d6_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_3e4d6_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_3e4d6_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_3e4d6_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_3e4d6_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_3e4d6_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_3e4d6_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_3e4d6_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_3e4d6_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_3e4d6_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_3e4d6_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_3e4d6_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_3e4d6_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_3e4d6_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_3e4d6_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_3e4d6_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_3e4d6_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_3e4d6_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_3e4d6_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_3e4d6_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_3e4d6_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_3e4d6_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_3e4d6_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_3e4d6_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_3e4d6_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_3e4d6_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_3e4d6_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_3e4d6_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_3e4d6_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_3e4d6_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_3e4d6_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_3e4d6_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_3e4d6_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_3e4d6_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_3e4d6_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_3e4d6_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_3e4d6_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_3e4d6_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_3e4d6_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_3e4d6_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_3e4d6_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_3e4d6_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_3e4d6_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_3e4d6_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_3e4d6_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_3e4d6_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_3e4d6_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_3e4d6_row30_col2\" class=\"data row30 col2\" >$ 288,869,950</td>\n",
-       "      <td id=\"T_3e4d6_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_3e4d6_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_3e4d6_row31_col2\" class=\"data row31 col2\" >$ 1,086,805,413</td>\n",
-       "      <td id=\"T_3e4d6_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_3e4d6_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_3e4d6_row32_col2\" class=\"data row32 col2\" >$ 45,645,827</td>\n",
-       "      <td id=\"T_3e4d6_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_3e4d6_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_3e4d6_row33_col2\" class=\"data row33 col2\" >$ 3,803,819</td>\n",
-       "      <td id=\"T_3e4d6_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_3e4d6_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_3e4d6_row34_col2\" class=\"data row34 col2\" >$ 293,437,462</td>\n",
-       "      <td id=\"T_3e4d6_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_3e4d6_row36_col2\" class=\"data row36 col2\" >$ 1,718,562,471</td>\n",
-       "      <td id=\"T_3e4d6_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_3e4d6_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_3e4d6_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_3e4d6_row37_col2\" class=\"data row37 col2\" >$ 5,529</td>\n",
-       "      <td id=\"T_3e4d6_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_3e4d6_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_3e4d6_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_3e4d6_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_090e7_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_090e7_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_090e7_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_090e7_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_090e7_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_090e7_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_090e7_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_090e7_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_090e7_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_090e7_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_090e7_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_090e7_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_090e7_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_090e7_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_090e7_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_090e7_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_090e7_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_090e7_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_090e7_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_090e7_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_090e7_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_090e7_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_090e7_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_090e7_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_090e7_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_090e7_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_090e7_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_090e7_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_090e7_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_090e7_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_090e7_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_090e7_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_090e7_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_090e7_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_090e7_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_090e7_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_090e7_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_090e7_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_090e7_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_090e7_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_090e7_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_090e7_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_090e7_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_090e7_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_090e7_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_090e7_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_090e7_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_090e7_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_090e7_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_090e7_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_090e7_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_090e7_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_090e7_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_090e7_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_090e7_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_090e7_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_090e7_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_090e7_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_090e7_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_090e7_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_090e7_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_090e7_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_090e7_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_090e7_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_090e7_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_090e7_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_090e7_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_090e7_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_090e7_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_090e7_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_090e7_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_090e7_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_090e7_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_090e7_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_090e7_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_090e7_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_090e7_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_090e7_row30_col2\" class=\"data row30 col2\" >$ 1,351,122,731</td>\n",
+       "      <td id=\"T_090e7_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_090e7_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_090e7_row31_col2\" class=\"data row31 col2\" >$ 5,218,449,814</td>\n",
+       "      <td id=\"T_090e7_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_090e7_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_090e7_row32_col2\" class=\"data row32 col2\" >$ 219,540,497</td>\n",
+       "      <td id=\"T_090e7_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_090e7_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_090e7_row33_col2\" class=\"data row33 col2\" >$ 18,485,556</td>\n",
+       "      <td id=\"T_090e7_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_090e7_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_090e7_row34_col2\" class=\"data row34 col2\" >$ 1,409,900,054</td>\n",
+       "      <td id=\"T_090e7_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_090e7_row36_col2\" class=\"data row36 col2\" >$ 8,217,498,651</td>\n",
+       "      <td id=\"T_090e7_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_090e7_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_090e7_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_090e7_row37_col2\" class=\"data row37 col2\" >$ 7,782</td>\n",
+       "      <td id=\"T_090e7_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_090e7_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_090e7_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_090e7_row37_col6\" class=\"data row37 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x16702e4d0>"
+       "<pandas.io.formats.style.Styler at 0x15a566210>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3687,8 +3710,7 @@
     "    # When the standardization is  70%, the engineering service accound (Acct 35) does not change\n",
     "    # The account 35 multiplier is\n",
     "\n",
-    "\n",
-    "    factor_35 = -3.33 * standardization + 3.331\n",
+    "    factor_35 = 10/3* ( 1 - standardization)\n",
     "\n",
     "\n",
     "    db = pd.DataFrame()\n",
@@ -3717,11 +3739,11 @@
     "\n",
     "    db.loc[db.Account == 32, 'Total Cost (USD)'] =  sum_new_lab_cost *0.36*3.661* final_construction_duration/72\n",
     "\n",
-    "    db.loc[db.Account == 33, 'Total Cost (USD)'] =  0.042 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )\n",
+    "    db.loc[db.Account == 33, 'Total Cost (USD)'] =  0.04207006 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )\n",
     "\n",
-    "    db.loc[db.Account == 34, 'Total Cost (USD)'] =  0.0035 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )\n",
+    "    db.loc[db.Account == 34, 'Total Cost (USD)'] =  0.00354234616938 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )\n",
     "\n",
-    "    db.loc[db.Account == 35, 'Total Cost (USD)'] = ( 0.27 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] ))*factor_35 \n",
+    "    db.loc[db.Account == 35, 'Total Cost (USD)'] = (0.27017603 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] ))*factor_35 \n",
     "\n",
     "\n",
     "    Reactor_data_updated_7 = update_high_level_costs(db, power)\n",
@@ -3735,15 +3757,19 @@
     "\n",
     "\n",
     "# # Example \n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
+    "_, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "direct_cost_updated , act_con_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
     "\n",
-    "act_con_duration = update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n",
     "cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n",
     "final_con_duration = duration_learning_effect(n_th, standardization_0, cons_duration_plus_delay)\n",
     "\n",
     "direct_cost_updated_plus_learning = learning_effect(direct_cost_updated , n_th, standardization_0, reactor_power)\n",
+    "\n",
     "direct_cost_updated_plus_learning_with_indirect_cost = update_indirect_cost(n_th, standardization_0, direct_cost_updated_plus_learning, final_con_duration, reactor_power  )\n",
     "\n",
     "direct_cost_updated_plus_learning_with_indirect_cost_pretty = prettify(direct_cost_updated_plus_learning_with_indirect_cost,\\\n",
@@ -3764,21 +3790,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "id": "ad4b0aa8",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0):\n",
-    "    reactor_data = (reactor_data_read(reactor_type ))[0]\n",
+    "def calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0):\n",
     "    reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "    direct_cost_updated = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n",
+    "    direct_cost_updated , act_con_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)\n",
     "\n",
-    "    act_con_duration = update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n",
     "    cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)\n",
     "    final_con_duration = duration_learning_effect(n_th, standardization_0, cons_duration_plus_delay)\n",
-    "\n",
     "    direct_cost_updated_plus_learning = learning_effect(direct_cost_updated , n_th, standardization_0, reactor_power)\n",
+    "\n",
     "    direct_cost_updated_plus_learning_with_indirect_cost = update_indirect_cost(n_th, standardization_0, direct_cost_updated_plus_learning, final_con_duration, reactor_power  )\n",
     "    return direct_cost_updated_plus_learning_with_indirect_cost, final_con_duration "
    ]
@@ -3788,12 +3812,12 @@
    "id": "e1c48177-8116-4762-803f-3daa3b5d7707",
    "metadata": {},
    "source": [
-    "### Section 3-10 :  Insurance"
+    "### Section 3-9 :  Insurance"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "id": "a2561757-dbc9-4a67-ad25-6311bc9939cc",
    "metadata": {},
    "outputs": [
@@ -3801,351 +3825,351 @@
      "data": {
       "text/html": [
        "<style type=\"text/css\">\n",
-       "#T_f4c4a caption {\n",
+       "#T_0dcf2 caption {\n",
        "  color: red;\n",
        "  font-size: 20px;\n",
        "}\n",
-       "#T_f4c4a_row12_col0, #T_f4c4a_row12_col1, #T_f4c4a_row12_col2, #T_f4c4a_row12_col3, #T_f4c4a_row12_col4, #T_f4c4a_row12_col5, #T_f4c4a_row12_col6, #T_f4c4a_row29_col0, #T_f4c4a_row29_col1, #T_f4c4a_row29_col2, #T_f4c4a_row29_col3, #T_f4c4a_row29_col4, #T_f4c4a_row29_col5, #T_f4c4a_row29_col6, #T_f4c4a_row39_col0, #T_f4c4a_row39_col1, #T_f4c4a_row39_col2, #T_f4c4a_row39_col3, #T_f4c4a_row39_col4, #T_f4c4a_row39_col5, #T_f4c4a_row39_col6 {\n",
+       "#T_0dcf2_row12_col0, #T_0dcf2_row12_col1, #T_0dcf2_row12_col2, #T_0dcf2_row12_col3, #T_0dcf2_row12_col4, #T_0dcf2_row12_col5, #T_0dcf2_row12_col6, #T_0dcf2_row29_col0, #T_0dcf2_row29_col1, #T_0dcf2_row29_col2, #T_0dcf2_row29_col3, #T_0dcf2_row29_col4, #T_0dcf2_row29_col5, #T_0dcf2_row29_col6, #T_0dcf2_row39_col0, #T_0dcf2_row39_col1, #T_0dcf2_row39_col2, #T_0dcf2_row39_col3, #T_0dcf2_row39_col4, #T_0dcf2_row39_col5, #T_0dcf2_row39_col6 {\n",
        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_f4c4a\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance <br><br> </caption>\n",
+       "<table id=\"T_0dcf2\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_f4c4a_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_f4c4a_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_f4c4a_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_f4c4a_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_f4c4a_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_f4c4a_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_f4c4a_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_0dcf2_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_0dcf2_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_0dcf2_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_0dcf2_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_0dcf2_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_0dcf2_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_0dcf2_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_f4c4a_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_f4c4a_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_f4c4a_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_f4c4a_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_f4c4a_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_f4c4a_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_f4c4a_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_f4c4a_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_f4c4a_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_f4c4a_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_f4c4a_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_f4c4a_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_f4c4a_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_f4c4a_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_f4c4a_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_f4c4a_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_f4c4a_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_f4c4a_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_f4c4a_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_f4c4a_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_f4c4a_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_f4c4a_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_f4c4a_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_f4c4a_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_f4c4a_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_f4c4a_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_f4c4a_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_f4c4a_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_f4c4a_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_f4c4a_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_f4c4a_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_f4c4a_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_f4c4a_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_f4c4a_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_f4c4a_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_f4c4a_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_f4c4a_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_f4c4a_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_f4c4a_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_f4c4a_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_f4c4a_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_f4c4a_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_f4c4a_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_f4c4a_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_f4c4a_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_f4c4a_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_f4c4a_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_f4c4a_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_f4c4a_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_f4c4a_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_f4c4a_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_f4c4a_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_f4c4a_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_f4c4a_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_f4c4a_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_f4c4a_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_f4c4a_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_f4c4a_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_f4c4a_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_f4c4a_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_f4c4a_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_f4c4a_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_f4c4a_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_f4c4a_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_f4c4a_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_f4c4a_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_f4c4a_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_f4c4a_row30_col2\" class=\"data row30 col2\" >$ 288,869,950</td>\n",
-       "      <td id=\"T_f4c4a_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_f4c4a_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_f4c4a_row31_col2\" class=\"data row31 col2\" >$ 1,086,805,413</td>\n",
-       "      <td id=\"T_f4c4a_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_f4c4a_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_f4c4a_row32_col2\" class=\"data row32 col2\" >$ 45,645,827</td>\n",
-       "      <td id=\"T_f4c4a_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_f4c4a_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_f4c4a_row33_col2\" class=\"data row33 col2\" >$ 3,803,819</td>\n",
-       "      <td id=\"T_f4c4a_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_f4c4a_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_f4c4a_row34_col2\" class=\"data row34 col2\" >$ 293,437,462</td>\n",
-       "      <td id=\"T_f4c4a_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_f4c4a_row36_col2\" class=\"data row36 col2\" >$ 1,718,562,471</td>\n",
-       "      <td id=\"T_f4c4a_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_f4c4a_row37_col2\" class=\"data row37 col2\" >$ 5,529</td>\n",
-       "      <td id=\"T_f4c4a_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row37_col6\" class=\"data row37 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row38_col0\" class=\"data row38 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col1\" class=\"data row38 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col2\" class=\"data row38 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col3\" class=\"data row38 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col4\" class=\"data row38 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col5\" class=\"data row38 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row38_col6\" class=\"data row38 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row39_col0\" class=\"data row39 col0\" >50</td>\n",
-       "      <td id=\"T_f4c4a_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
-       "      <td id=\"T_f4c4a_row39_col2\" class=\"data row39 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row39_col3\" class=\"data row39 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row39_col4\" class=\"data row39 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row39_col5\" class=\"data row39 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row39_col6\" class=\"data row39 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row40_col0\" class=\"data row40 col0\" >51</td>\n",
-       "      <td id=\"T_f4c4a_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
-       "      <td id=\"T_f4c4a_row40_col2\" class=\"data row40 col2\" >$ 3,510,602</td>\n",
-       "      <td id=\"T_f4c4a_row40_col3\" class=\"data row40 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row40_col4\" class=\"data row40 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row40_col5\" class=\"data row40 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row40_col6\" class=\"data row40 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row41_col0\" class=\"data row41 col0\" >52</td>\n",
-       "      <td id=\"T_f4c4a_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
-       "      <td id=\"T_f4c4a_row41_col2\" class=\"data row41 col2\" >$ 16,308,494</td>\n",
-       "      <td id=\"T_f4c4a_row41_col3\" class=\"data row41 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row41_col4\" class=\"data row41 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row41_col5\" class=\"data row41 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row41_col6\" class=\"data row41 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row42_col0\" class=\"data row42 col0\" >54</td>\n",
-       "      <td id=\"T_f4c4a_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
-       "      <td id=\"T_f4c4a_row42_col2\" class=\"data row42 col2\" >$ 14,606,673</td>\n",
-       "      <td id=\"T_f4c4a_row42_col3\" class=\"data row42 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row42_col4\" class=\"data row42 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row42_col5\" class=\"data row42 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row42_col6\" class=\"data row42 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row43_col0\" class=\"data row43 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col1\" class=\"data row43 col1\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col2\" class=\"data row43 col2\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col3\" class=\"data row43 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col4\" class=\"data row43 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col5\" class=\"data row43 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row43_col6\" class=\"data row43 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row44_col0\" class=\"data row44 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
-       "      <td id=\"T_f4c4a_row44_col2\" class=\"data row44 col2\" >$ 34,425,770</td>\n",
-       "      <td id=\"T_f4c4a_row44_col3\" class=\"data row44 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row44_col4\" class=\"data row44 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row44_col5\" class=\"data row44 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row44_col6\" class=\"data row44 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_f4c4a_row45_col0\" class=\"data row45 col0\" ></td>\n",
-       "      <td id=\"T_f4c4a_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
-       "      <td id=\"T_f4c4a_row45_col2\" class=\"data row45 col2\" >$ 111</td>\n",
-       "      <td id=\"T_f4c4a_row45_col3\" class=\"data row45 col3\" ></td>\n",
-       "      <td id=\"T_f4c4a_row45_col4\" class=\"data row45 col4\" ></td>\n",
-       "      <td id=\"T_f4c4a_row45_col5\" class=\"data row45 col5\" ></td>\n",
-       "      <td id=\"T_f4c4a_row45_col6\" class=\"data row45 col6\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_0dcf2_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_0dcf2_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_0dcf2_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_0dcf2_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_0dcf2_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_0dcf2_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_0dcf2_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_0dcf2_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_0dcf2_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_0dcf2_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_0dcf2_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_0dcf2_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_0dcf2_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_0dcf2_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_0dcf2_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_0dcf2_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_0dcf2_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_0dcf2_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_0dcf2_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_0dcf2_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_0dcf2_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_0dcf2_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_0dcf2_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_0dcf2_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_0dcf2_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_0dcf2_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_0dcf2_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_0dcf2_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_0dcf2_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_0dcf2_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_0dcf2_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_0dcf2_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_0dcf2_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_0dcf2_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_0dcf2_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_0dcf2_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_0dcf2_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_0dcf2_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_0dcf2_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_0dcf2_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_0dcf2_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_0dcf2_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_0dcf2_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_0dcf2_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_0dcf2_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_0dcf2_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_0dcf2_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_0dcf2_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_0dcf2_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_0dcf2_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_0dcf2_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_0dcf2_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_0dcf2_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_0dcf2_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_0dcf2_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_0dcf2_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_0dcf2_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_0dcf2_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_0dcf2_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_0dcf2_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_0dcf2_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_0dcf2_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_0dcf2_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_0dcf2_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_0dcf2_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_0dcf2_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_0dcf2_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_0dcf2_row30_col2\" class=\"data row30 col2\" >$ 1,351,122,731</td>\n",
+       "      <td id=\"T_0dcf2_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_0dcf2_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_0dcf2_row31_col2\" class=\"data row31 col2\" >$ 5,218,449,814</td>\n",
+       "      <td id=\"T_0dcf2_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_0dcf2_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_0dcf2_row32_col2\" class=\"data row32 col2\" >$ 219,540,497</td>\n",
+       "      <td id=\"T_0dcf2_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_0dcf2_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_0dcf2_row33_col2\" class=\"data row33 col2\" >$ 18,485,556</td>\n",
+       "      <td id=\"T_0dcf2_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_0dcf2_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_0dcf2_row34_col2\" class=\"data row34 col2\" >$ 1,409,900,054</td>\n",
+       "      <td id=\"T_0dcf2_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_0dcf2_row36_col2\" class=\"data row36 col2\" >$ 8,217,498,651</td>\n",
+       "      <td id=\"T_0dcf2_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_0dcf2_row37_col2\" class=\"data row37 col2\" >$ 7,782</td>\n",
+       "      <td id=\"T_0dcf2_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_0dcf2_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_0dcf2_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_0dcf2_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_0dcf2_row40_col2\" class=\"data row40 col2\" >$ 187,500</td>\n",
+       "      <td id=\"T_0dcf2_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row40_col6\" class=\"data row40 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_0dcf2_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_0dcf2_row41_col2\" class=\"data row41 col2\" >$ 59,621,066</td>\n",
+       "      <td id=\"T_0dcf2_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row41_col6\" class=\"data row41 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_0dcf2_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_0dcf2_row42_col2\" class=\"data row42 col2\" >$ 8,141,760</td>\n",
+       "      <td id=\"T_0dcf2_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row42_col6\" class=\"data row42 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_0dcf2_row44_col2\" class=\"data row44 col2\" >$ 67,950,326</td>\n",
+       "      <td id=\"T_0dcf2_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row44_col6\" class=\"data row44 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_0dcf2_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_0dcf2_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_0dcf2_row45_col2\" class=\"data row45 col2\" >$ 64</td>\n",
+       "      <td id=\"T_0dcf2_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_0dcf2_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_0dcf2_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_0dcf2_row45_col6\" class=\"data row45 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1675d6510>"
+       "<pandas.io.formats.style.Styler at 0x15b80cc10>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4175,9 +4199,8 @@
     "    return Reactor_data_updated_8_  \n",
     "\n",
     "# Example\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "tot_base_cost = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0))[0]\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "tot_base_cost = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons,  Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0))[0]\n",
     "tot_base_cost_wz_insurance = insurance_cost_update(reactor_data, tot_base_cost , reactor_power)\n",
     "tot_base_cost_wz_insurance_pretty = prettify(tot_base_cost_wz_insurance,\\\n",
     "            f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance <br><br> \", \"no_subsidies\")\n",
@@ -4193,12 +4216,12 @@
    "id": "d17b48a1-153c-4273-b346-fe0b9577fc8a",
    "metadata": {},
    "source": [
-    "### Section 3-11 :  Interest"
+    "### Section 3-10 :  Interest"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "id": "9616088a-1f2c-4147-a288-eb0bb7f259c7",
    "metadata": {},
    "outputs": [
@@ -4206,662 +4229,662 @@
      "data": {
       "text/html": [
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-       "#T_8cda1_row64_col0, #T_8cda1_row64_col1, #T_8cda1_row64_col2, #T_8cda1_row64_col3, #T_8cda1_row64_col4, #T_8cda1_row64_col5, #T_8cda1_row64_col6, #T_8cda1_row65_col0, #T_8cda1_row65_col1, #T_8cda1_row65_col2, #T_8cda1_row65_col3, #T_8cda1_row65_col4, #T_8cda1_row65_col5, #T_8cda1_row65_col6, #T_8cda1_row66_col0, #T_8cda1_row66_col1, #T_8cda1_row66_col2, #T_8cda1_row66_col3, #T_8cda1_row66_col4, #T_8cda1_row66_col5, #T_8cda1_row66_col6, #T_8cda1_row67_col0, #T_8cda1_row67_col1, #T_8cda1_row67_col2, #T_8cda1_row67_col3, #T_8cda1_row67_col4, #T_8cda1_row67_col5, #T_8cda1_row67_col6, #T_8cda1_row68_col0, #T_8cda1_row68_col1, #T_8cda1_row68_col2, #T_8cda1_row68_col3, #T_8cda1_row68_col4, #T_8cda1_row68_col5, #T_8cda1_row68_col6 {\n",
+       "#T_c9c31_row64_col0, #T_c9c31_row64_col1, #T_c9c31_row64_col2, #T_c9c31_row64_col3, #T_c9c31_row64_col4, #T_c9c31_row64_col5, #T_c9c31_row64_col6, #T_c9c31_row65_col0, #T_c9c31_row65_col1, #T_c9c31_row65_col2, #T_c9c31_row65_col3, #T_c9c31_row65_col4, #T_c9c31_row65_col5, #T_c9c31_row65_col6, #T_c9c31_row66_col0, #T_c9c31_row66_col1, #T_c9c31_row66_col2, #T_c9c31_row66_col3, #T_c9c31_row66_col4, #T_c9c31_row66_col5, #T_c9c31_row66_col6, #T_c9c31_row67_col0, #T_c9c31_row67_col1, #T_c9c31_row67_col2, #T_c9c31_row67_col3, #T_c9c31_row67_col4, #T_c9c31_row67_col5, #T_c9c31_row67_col6, #T_c9c31_row68_col0, #T_c9c31_row68_col1, #T_c9c31_row68_col2, #T_c9c31_row68_col3, #T_c9c31_row68_col4, #T_c9c31_row68_col5, #T_c9c31_row68_col6 {\n",
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        "</style>\n",
-       "<table id=\"T_8cda1\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance and interest <br><br> </caption>\n",
+       "<table id=\"T_c9c31\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance and interest <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_8cda1_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_8cda1_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_8cda1_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_8cda1_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_8cda1_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_8cda1_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_8cda1_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_c9c31_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_c9c31_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_c9c31_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_c9c31_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_c9c31_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_c9c31_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_c9c31_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_8cda1_row0_col0\" class=\"data row0 col0\" >10</td>\n",
-       "      <td id=\"T_8cda1_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
-       "      <td id=\"T_8cda1_row0_col2\" class=\"data row0 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row0_col3\" class=\"data row0 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row0_col4\" class=\"data row0 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row0_col5\" class=\"data row0 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row0_col6\" class=\"data row0 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row1_col0\" class=\"data row1 col0\" >11</td>\n",
-       "      <td id=\"T_8cda1_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
-       "      <td id=\"T_8cda1_row1_col2\" class=\"data row1 col2\" >$ 11,000,000</td>\n",
-       "      <td id=\"T_8cda1_row1_col3\" class=\"data row1 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row1_col4\" class=\"data row1 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row1_col5\" class=\"data row1 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row1_col6\" class=\"data row1 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row2_col0\" class=\"data row2 col0\" >12</td>\n",
-       "      <td id=\"T_8cda1_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
-       "      <td id=\"T_8cda1_row2_col2\" class=\"data row2 col2\" >$ 1,598,891</td>\n",
-       "      <td id=\"T_8cda1_row2_col3\" class=\"data row2 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row2_col4\" class=\"data row2 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row2_col5\" class=\"data row2 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row2_col6\" class=\"data row2 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row3_col0\" class=\"data row3 col0\" >13</td>\n",
-       "      <td id=\"T_8cda1_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
-       "      <td id=\"T_8cda1_row3_col2\" class=\"data row3 col2\" >$ 24,382,988</td>\n",
-       "      <td id=\"T_8cda1_row3_col3\" class=\"data row3 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row3_col4\" class=\"data row3 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row3_col5\" class=\"data row3 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row3_col6\" class=\"data row3 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row4_col0\" class=\"data row4 col0\" >14</td>\n",
-       "      <td id=\"T_8cda1_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
-       "      <td id=\"T_8cda1_row4_col2\" class=\"data row4 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_8cda1_row4_col3\" class=\"data row4 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row4_col4\" class=\"data row4 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row4_col5\" class=\"data row4 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row4_col6\" class=\"data row4 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row5_col0\" class=\"data row5 col0\" >15</td>\n",
-       "      <td id=\"T_8cda1_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
-       "      <td id=\"T_8cda1_row5_col2\" class=\"data row5 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_8cda1_row5_col3\" class=\"data row5 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row5_col4\" class=\"data row5 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row5_col5\" class=\"data row5 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row5_col6\" class=\"data row5 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row6_col0\" class=\"data row6 col0\" >16</td>\n",
-       "      <td id=\"T_8cda1_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
-       "      <td id=\"T_8cda1_row6_col2\" class=\"data row6 col2\" >$ 3,972,186</td>\n",
-       "      <td id=\"T_8cda1_row6_col3\" class=\"data row6 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row6_col4\" class=\"data row6 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row6_col5\" class=\"data row6 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row6_col6\" class=\"data row6 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row7_col0\" class=\"data row7 col0\" >18</td>\n",
-       "      <td id=\"T_8cda1_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
-       "      <td id=\"T_8cda1_row7_col2\" class=\"data row7 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_8cda1_row7_col3\" class=\"data row7 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row7_col4\" class=\"data row7 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row7_col5\" class=\"data row7 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row7_col6\" class=\"data row7 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row8_col0\" class=\"data row8 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col1\" class=\"data row8 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col2\" class=\"data row8 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col3\" class=\"data row8 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col4\" class=\"data row8 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col5\" class=\"data row8 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row8_col6\" class=\"data row8 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row9_col0\" class=\"data row9 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
-       "      <td id=\"T_8cda1_row9_col2\" class=\"data row9 col2\" >$ 78,991,565</td>\n",
-       "      <td id=\"T_8cda1_row9_col3\" class=\"data row9 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row9_col4\" class=\"data row9 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row9_col5\" class=\"data row9 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row9_col6\" class=\"data row9 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row10_col0\" class=\"data row10 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
-       "      <td id=\"T_8cda1_row10_col2\" class=\"data row10 col2\" >$ 254</td>\n",
-       "      <td id=\"T_8cda1_row10_col3\" class=\"data row10 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row10_col4\" class=\"data row10 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row10_col5\" class=\"data row10 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row10_col6\" class=\"data row10 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_8cda1_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_8cda1_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_8cda1_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_8cda1_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_8cda1_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_8cda1_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_8cda1_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_8cda1_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_8cda1_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_8cda1_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_8cda1_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_8cda1_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_8cda1_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_8cda1_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_8cda1_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_8cda1_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_8cda1_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_8cda1_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_8cda1_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_8cda1_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_8cda1_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_8cda1_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_8cda1_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_8cda1_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_8cda1_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_8cda1_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_8cda1_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_8cda1_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_8cda1_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_8cda1_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_8cda1_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_8cda1_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_8cda1_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_8cda1_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_8cda1_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_8cda1_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_8cda1_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_8cda1_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_8cda1_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_8cda1_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_8cda1_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_8cda1_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_8cda1_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_8cda1_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_8cda1_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_8cda1_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_8cda1_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_8cda1_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_8cda1_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_8cda1_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_8cda1_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_8cda1_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_8cda1_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_8cda1_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_8cda1_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_8cda1_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_8cda1_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_8cda1_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_8cda1_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_8cda1_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_8cda1_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_8cda1_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_8cda1_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_8cda1_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_8cda1_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_8cda1_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_8cda1_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_8cda1_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_8cda1_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_8cda1_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_8cda1_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_8cda1_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_8cda1_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_8cda1_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_8cda1_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_8cda1_row30_col2\" class=\"data row30 col2\" >$ 288,869,950</td>\n",
-       "      <td id=\"T_8cda1_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_8cda1_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_8cda1_row31_col2\" class=\"data row31 col2\" >$ 1,086,805,413</td>\n",
-       "      <td id=\"T_8cda1_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_8cda1_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_8cda1_row32_col2\" class=\"data row32 col2\" >$ 45,645,827</td>\n",
-       "      <td id=\"T_8cda1_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_8cda1_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_8cda1_row33_col2\" class=\"data row33 col2\" >$ 3,803,819</td>\n",
-       "      <td id=\"T_8cda1_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_8cda1_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_8cda1_row34_col2\" class=\"data row34 col2\" >$ 293,437,462</td>\n",
-       "      <td id=\"T_8cda1_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_8cda1_row36_col2\" class=\"data row36 col2\" >$ 1,718,562,471</td>\n",
-       "      <td id=\"T_8cda1_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_8cda1_row37_col2\" class=\"data row37 col2\" >$ 5,529</td>\n",
-       "      <td id=\"T_8cda1_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row37_col6\" class=\"data row37 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row38_col0\" class=\"data row38 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col1\" class=\"data row38 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col2\" class=\"data row38 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col3\" class=\"data row38 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col4\" class=\"data row38 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col5\" class=\"data row38 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row38_col6\" class=\"data row38 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row39_col0\" class=\"data row39 col0\" >50</td>\n",
-       "      <td id=\"T_8cda1_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
-       "      <td id=\"T_8cda1_row39_col2\" class=\"data row39 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row39_col3\" class=\"data row39 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row39_col4\" class=\"data row39 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row39_col5\" class=\"data row39 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row39_col6\" class=\"data row39 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row40_col0\" class=\"data row40 col0\" >51</td>\n",
-       "      <td id=\"T_8cda1_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
-       "      <td id=\"T_8cda1_row40_col2\" class=\"data row40 col2\" >$ 3,510,602</td>\n",
-       "      <td id=\"T_8cda1_row40_col3\" class=\"data row40 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row40_col4\" class=\"data row40 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row40_col5\" class=\"data row40 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row40_col6\" class=\"data row40 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row41_col0\" class=\"data row41 col0\" >52</td>\n",
-       "      <td id=\"T_8cda1_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
-       "      <td id=\"T_8cda1_row41_col2\" class=\"data row41 col2\" >$ 16,308,494</td>\n",
-       "      <td id=\"T_8cda1_row41_col3\" class=\"data row41 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row41_col4\" class=\"data row41 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row41_col5\" class=\"data row41 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row41_col6\" class=\"data row41 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row42_col0\" class=\"data row42 col0\" >54</td>\n",
-       "      <td id=\"T_8cda1_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
-       "      <td id=\"T_8cda1_row42_col2\" class=\"data row42 col2\" >$ 14,606,673</td>\n",
-       "      <td id=\"T_8cda1_row42_col3\" class=\"data row42 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row42_col4\" class=\"data row42 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row42_col5\" class=\"data row42 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row42_col6\" class=\"data row42 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row43_col0\" class=\"data row43 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col1\" class=\"data row43 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col2\" class=\"data row43 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col3\" class=\"data row43 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col4\" class=\"data row43 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col5\" class=\"data row43 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row43_col6\" class=\"data row43 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row44_col0\" class=\"data row44 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
-       "      <td id=\"T_8cda1_row44_col2\" class=\"data row44 col2\" >$ 34,425,770</td>\n",
-       "      <td id=\"T_8cda1_row44_col3\" class=\"data row44 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row44_col4\" class=\"data row44 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row44_col5\" class=\"data row44 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row44_col6\" class=\"data row44 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row45_col0\" class=\"data row45 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
-       "      <td id=\"T_8cda1_row45_col2\" class=\"data row45 col2\" >$ 111</td>\n",
-       "      <td id=\"T_8cda1_row45_col3\" class=\"data row45 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row45_col4\" class=\"data row45 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row45_col5\" class=\"data row45 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row45_col6\" class=\"data row45 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row46_col0\" class=\"data row46 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col1\" class=\"data row46 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col2\" class=\"data row46 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col3\" class=\"data row46 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col4\" class=\"data row46 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col5\" class=\"data row46 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row46_col6\" class=\"data row46 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row47_col0\" class=\"data row47 col0\" >60</td>\n",
-       "      <td id=\"T_8cda1_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
-       "      <td id=\"T_8cda1_row47_col2\" class=\"data row47 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row47_col3\" class=\"data row47 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row47_col4\" class=\"data row47 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row47_col5\" class=\"data row47 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row47_col6\" class=\"data row47 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row48_col0\" class=\"data row48 col0\" >62</td>\n",
-       "      <td id=\"T_8cda1_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
-       "      <td id=\"T_8cda1_row48_col2\" class=\"data row48 col2\" >$ 1,276,775,002</td>\n",
-       "      <td id=\"T_8cda1_row48_col3\" class=\"data row48 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row48_col4\" class=\"data row48 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row48_col5\" class=\"data row48 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row48_col6\" class=\"data row48 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row49_col0\" class=\"data row49 col0\" >-</td>\n",
-       "      <td id=\"T_8cda1_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
-       "      <td id=\"T_8cda1_row49_col2\" class=\"data row49 col2\" >$ 1,276,775,002</td>\n",
-       "      <td id=\"T_8cda1_row49_col3\" class=\"data row49 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row49_col4\" class=\"data row49 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row49_col5\" class=\"data row49 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row49_col6\" class=\"data row49 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row50_col0\" class=\"data row50 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
-       "      <td id=\"T_8cda1_row50_col2\" class=\"data row50 col2\" >$ 4,108</td>\n",
-       "      <td id=\"T_8cda1_row50_col3\" class=\"data row50 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row50_col4\" class=\"data row50 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row50_col5\" class=\"data row50 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row50_col6\" class=\"data row50 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row51_col0\" class=\"data row51 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col1\" class=\"data row51 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col2\" class=\"data row51 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col3\" class=\"data row51 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col4\" class=\"data row51 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col5\" class=\"data row51 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row51_col6\" class=\"data row51 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row52_col0\" class=\"data row52 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
-       "      <td id=\"T_8cda1_row52_col2\" class=\"data row52 col2\" >$ 1,984,538,942</td>\n",
-       "      <td id=\"T_8cda1_row52_col3\" class=\"data row52 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row52_col4\" class=\"data row52 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row52_col5\" class=\"data row52 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row52_col6\" class=\"data row52 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row53_col0\" class=\"data row53 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
-       "      <td id=\"T_8cda1_row53_col2\" class=\"data row53 col2\" >$ 6,385</td>\n",
-       "      <td id=\"T_8cda1_row53_col3\" class=\"data row53 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row53_col4\" class=\"data row53 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row53_col5\" class=\"data row53 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row53_col6\" class=\"data row53 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row54_col0\" class=\"data row54 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col1\" class=\"data row54 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col2\" class=\"data row54 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col3\" class=\"data row54 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col4\" class=\"data row54 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col5\" class=\"data row54 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row54_col6\" class=\"data row54 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row55_col0\" class=\"data row55 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
-       "      <td id=\"T_8cda1_row55_col2\" class=\"data row55 col2\" >$ 3,703,101,413</td>\n",
-       "      <td id=\"T_8cda1_row55_col3\" class=\"data row55 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row55_col4\" class=\"data row55 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row55_col5\" class=\"data row55 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row55_col6\" class=\"data row55 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row56_col0\" class=\"data row56 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
-       "      <td id=\"T_8cda1_row56_col2\" class=\"data row56 col2\" >$ 11,915</td>\n",
-       "      <td id=\"T_8cda1_row56_col3\" class=\"data row56 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row56_col4\" class=\"data row56 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row56_col5\" class=\"data row56 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row56_col6\" class=\"data row56 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row57_col0\" class=\"data row57 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col1\" class=\"data row57 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col2\" class=\"data row57 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col3\" class=\"data row57 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col4\" class=\"data row57 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col5\" class=\"data row57 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row57_col6\" class=\"data row57 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row58_col0\" class=\"data row58 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
-       "      <td id=\"T_8cda1_row58_col2\" class=\"data row58 col2\" >$ 3,737,527,183</td>\n",
-       "      <td id=\"T_8cda1_row58_col3\" class=\"data row58 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row58_col4\" class=\"data row58 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row58_col5\" class=\"data row58 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row58_col6\" class=\"data row58 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row59_col0\" class=\"data row59 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
-       "      <td id=\"T_8cda1_row59_col2\" class=\"data row59 col2\" >$ 12,026</td>\n",
-       "      <td id=\"T_8cda1_row59_col3\" class=\"data row59 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row59_col4\" class=\"data row59 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row59_col5\" class=\"data row59 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row59_col6\" class=\"data row59 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row60_col0\" class=\"data row60 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col1\" class=\"data row60 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col2\" class=\"data row60 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col3\" class=\"data row60 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col4\" class=\"data row60 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col5\" class=\"data row60 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row60_col6\" class=\"data row60 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row61_col0\" class=\"data row61 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
-       "      <td id=\"T_8cda1_row61_col2\" class=\"data row61 col2\" >$ 5,014,302,185</td>\n",
-       "      <td id=\"T_8cda1_row61_col3\" class=\"data row61 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row61_col4\" class=\"data row61 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row61_col5\" class=\"data row61 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row61_col6\" class=\"data row61 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row62_col0\" class=\"data row62 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
-       "      <td id=\"T_8cda1_row62_col2\" class=\"data row62 col2\" >$ 16,134</td>\n",
-       "      <td id=\"T_8cda1_row62_col3\" class=\"data row62 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row62_col4\" class=\"data row62 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row62_col5\" class=\"data row62 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row62_col6\" class=\"data row62 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row63_col0\" class=\"data row63 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col1\" class=\"data row63 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col2\" class=\"data row63 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col3\" class=\"data row63 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col4\" class=\"data row63 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col5\" class=\"data row63 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row63_col6\" class=\"data row63 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row64_col0\" class=\"data row64 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
-       "      <td id=\"T_8cda1_row64_col2\" class=\"data row64 col2\" >$ 2,437,538,300</td>\n",
-       "      <td id=\"T_8cda1_row64_col3\" class=\"data row64 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row64_col4\" class=\"data row64 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row64_col5\" class=\"data row64 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row64_col6\" class=\"data row64 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row65_col0\" class=\"data row65 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_8cda1_row65_col2\" class=\"data row65 col2\" >$ 7,843</td>\n",
-       "      <td id=\"T_8cda1_row65_col3\" class=\"data row65 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row65_col4\" class=\"data row65 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row65_col5\" class=\"data row65 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row65_col6\" class=\"data row65 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row66_col0\" class=\"data row66 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col1\" class=\"data row66 col1\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col2\" class=\"data row66 col2\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col3\" class=\"data row66 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col4\" class=\"data row66 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col5\" class=\"data row66 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row66_col6\" class=\"data row66 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row67_col0\" class=\"data row67 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
-       "      <td id=\"T_8cda1_row67_col2\" class=\"data row67 col2\" >$ 3,029,839,099</td>\n",
-       "      <td id=\"T_8cda1_row67_col3\" class=\"data row67 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row67_col4\" class=\"data row67 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row67_col5\" class=\"data row67 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row67_col6\" class=\"data row67 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_8cda1_row68_col0\" class=\"data row68 col0\" ></td>\n",
-       "      <td id=\"T_8cda1_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_8cda1_row68_col2\" class=\"data row68 col2\" >$ 9,749</td>\n",
-       "      <td id=\"T_8cda1_row68_col3\" class=\"data row68 col3\" ></td>\n",
-       "      <td id=\"T_8cda1_row68_col4\" class=\"data row68 col4\" ></td>\n",
-       "      <td id=\"T_8cda1_row68_col5\" class=\"data row68 col5\" ></td>\n",
-       "      <td id=\"T_8cda1_row68_col6\" class=\"data row68 col6\" ></td>\n",
+       "      <td id=\"T_c9c31_row0_col0\" class=\"data row0 col0\" >10</td>\n",
+       "      <td id=\"T_c9c31_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
+       "      <td id=\"T_c9c31_row0_col2\" class=\"data row0 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row0_col3\" class=\"data row0 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row0_col4\" class=\"data row0 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row0_col5\" class=\"data row0 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row0_col6\" class=\"data row0 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row1_col0\" class=\"data row1 col0\" >11</td>\n",
+       "      <td id=\"T_c9c31_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
+       "      <td id=\"T_c9c31_row1_col2\" class=\"data row1 col2\" >$ 15,000,000</td>\n",
+       "      <td id=\"T_c9c31_row1_col3\" class=\"data row1 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row1_col4\" class=\"data row1 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row1_col5\" class=\"data row1 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row1_col6\" class=\"data row1 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row2_col0\" class=\"data row2 col0\" >12</td>\n",
+       "      <td id=\"T_c9c31_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
+       "      <td id=\"T_c9c31_row2_col2\" class=\"data row2 col2\" >$ 0</td>\n",
+       "      <td id=\"T_c9c31_row2_col3\" class=\"data row2 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row2_col4\" class=\"data row2 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row2_col5\" class=\"data row2 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row2_col6\" class=\"data row2 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row3_col0\" class=\"data row3 col0\" >13</td>\n",
+       "      <td id=\"T_c9c31_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
+       "      <td id=\"T_c9c31_row3_col2\" class=\"data row3 col2\" >$ 107,009,772</td>\n",
+       "      <td id=\"T_c9c31_row3_col3\" class=\"data row3 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row3_col4\" class=\"data row3 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row3_col5\" class=\"data row3 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row3_col6\" class=\"data row3 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row4_col0\" class=\"data row4 col0\" >14</td>\n",
+       "      <td id=\"T_c9c31_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
+       "      <td id=\"T_c9c31_row4_col2\" class=\"data row4 col2\" >$ 4,721,019</td>\n",
+       "      <td id=\"T_c9c31_row4_col3\" class=\"data row4 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row4_col4\" class=\"data row4 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row4_col5\" class=\"data row4 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row4_col6\" class=\"data row4 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row5_col0\" class=\"data row5 col0\" >15</td>\n",
+       "      <td id=\"T_c9c31_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
+       "      <td id=\"T_c9c31_row5_col2\" class=\"data row5 col2\" >$ 0</td>\n",
+       "      <td id=\"T_c9c31_row5_col3\" class=\"data row5 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row5_col4\" class=\"data row5 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row5_col5\" class=\"data row5 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row5_col6\" class=\"data row5 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row6_col0\" class=\"data row6 col0\" >16</td>\n",
+       "      <td id=\"T_c9c31_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
+       "      <td id=\"T_c9c31_row6_col2\" class=\"data row6 col2\" >$ 0</td>\n",
+       "      <td id=\"T_c9c31_row6_col3\" class=\"data row6 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row6_col4\" class=\"data row6 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row6_col5\" class=\"data row6 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row6_col6\" class=\"data row6 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row7_col0\" class=\"data row7 col0\" >18</td>\n",
+       "      <td id=\"T_c9c31_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
+       "      <td id=\"T_c9c31_row7_col2\" class=\"data row7 col2\" >$ 36,194,482</td>\n",
+       "      <td id=\"T_c9c31_row7_col3\" class=\"data row7 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row7_col4\" class=\"data row7 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row7_col5\" class=\"data row7 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row7_col6\" class=\"data row7 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row8_col0\" class=\"data row8 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col1\" class=\"data row8 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col2\" class=\"data row8 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col3\" class=\"data row8 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col4\" class=\"data row8 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col5\" class=\"data row8 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row8_col6\" class=\"data row8 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row9_col0\" class=\"data row9 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
+       "      <td id=\"T_c9c31_row9_col2\" class=\"data row9 col2\" >$ 162,925,273</td>\n",
+       "      <td id=\"T_c9c31_row9_col3\" class=\"data row9 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row9_col4\" class=\"data row9 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row9_col5\" class=\"data row9 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row9_col6\" class=\"data row9 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row10_col0\" class=\"data row10 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
+       "      <td id=\"T_c9c31_row10_col2\" class=\"data row10 col2\" >$ 154</td>\n",
+       "      <td id=\"T_c9c31_row10_col3\" class=\"data row10 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row10_col4\" class=\"data row10 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row10_col5\" class=\"data row10 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row10_col6\" class=\"data row10 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_c9c31_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_c9c31_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_c9c31_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_c9c31_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_c9c31_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_c9c31_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_c9c31_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_c9c31_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_c9c31_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_c9c31_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_c9c31_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_c9c31_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_c9c31_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_c9c31_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_c9c31_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_c9c31_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_c9c31_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_c9c31_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_c9c31_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_c9c31_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_c9c31_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_c9c31_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_c9c31_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_c9c31_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_c9c31_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_c9c31_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_c9c31_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_c9c31_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_c9c31_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_c9c31_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_c9c31_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_c9c31_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_c9c31_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_c9c31_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_c9c31_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_c9c31_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_c9c31_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_c9c31_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_c9c31_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_c9c31_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_c9c31_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_c9c31_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_c9c31_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_c9c31_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_c9c31_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_c9c31_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_c9c31_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_c9c31_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_c9c31_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_c9c31_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_c9c31_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_c9c31_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_c9c31_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_c9c31_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_c9c31_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_c9c31_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_c9c31_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_c9c31_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_c9c31_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_c9c31_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_c9c31_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_c9c31_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_c9c31_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_c9c31_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_c9c31_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_c9c31_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_c9c31_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_c9c31_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_c9c31_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_c9c31_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_c9c31_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_c9c31_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_c9c31_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_c9c31_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_c9c31_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_c9c31_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_c9c31_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_c9c31_row30_col2\" class=\"data row30 col2\" >$ 1,351,122,731</td>\n",
+       "      <td id=\"T_c9c31_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_c9c31_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_c9c31_row31_col2\" class=\"data row31 col2\" >$ 5,218,449,814</td>\n",
+       "      <td id=\"T_c9c31_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_c9c31_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_c9c31_row32_col2\" class=\"data row32 col2\" >$ 219,540,497</td>\n",
+       "      <td id=\"T_c9c31_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_c9c31_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_c9c31_row33_col2\" class=\"data row33 col2\" >$ 18,485,556</td>\n",
+       "      <td id=\"T_c9c31_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_c9c31_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_c9c31_row34_col2\" class=\"data row34 col2\" >$ 1,409,900,054</td>\n",
+       "      <td id=\"T_c9c31_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_c9c31_row36_col2\" class=\"data row36 col2\" >$ 8,217,498,651</td>\n",
+       "      <td id=\"T_c9c31_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_c9c31_row37_col2\" class=\"data row37 col2\" >$ 7,782</td>\n",
+       "      <td id=\"T_c9c31_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_c9c31_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_c9c31_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_c9c31_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_c9c31_row40_col2\" class=\"data row40 col2\" >$ 187,500</td>\n",
+       "      <td id=\"T_c9c31_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row40_col6\" class=\"data row40 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_c9c31_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_c9c31_row41_col2\" class=\"data row41 col2\" >$ 59,621,066</td>\n",
+       "      <td id=\"T_c9c31_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row41_col6\" class=\"data row41 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_c9c31_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_c9c31_row42_col2\" class=\"data row42 col2\" >$ 8,141,760</td>\n",
+       "      <td id=\"T_c9c31_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row42_col6\" class=\"data row42 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_c9c31_row44_col2\" class=\"data row44 col2\" >$ 67,950,326</td>\n",
+       "      <td id=\"T_c9c31_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row44_col6\" class=\"data row44 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_c9c31_row45_col2\" class=\"data row45 col2\" >$ 64</td>\n",
+       "      <td id=\"T_c9c31_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row45_col6\" class=\"data row45 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row46_col0\" class=\"data row46 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col1\" class=\"data row46 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col2\" class=\"data row46 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col3\" class=\"data row46 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col4\" class=\"data row46 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col5\" class=\"data row46 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row46_col6\" class=\"data row46 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row47_col0\" class=\"data row47 col0\" >60</td>\n",
+       "      <td id=\"T_c9c31_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
+       "      <td id=\"T_c9c31_row47_col2\" class=\"data row47 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row47_col3\" class=\"data row47 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row47_col4\" class=\"data row47 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row47_col5\" class=\"data row47 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row47_col6\" class=\"data row47 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row48_col0\" class=\"data row48 col0\" >62</td>\n",
+       "      <td id=\"T_c9c31_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
+       "      <td id=\"T_c9c31_row48_col2\" class=\"data row48 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_c9c31_row48_col3\" class=\"data row48 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row48_col4\" class=\"data row48 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row48_col5\" class=\"data row48 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row48_col6\" class=\"data row48 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row49_col0\" class=\"data row49 col0\" >-</td>\n",
+       "      <td id=\"T_c9c31_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
+       "      <td id=\"T_c9c31_row49_col2\" class=\"data row49 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_c9c31_row49_col3\" class=\"data row49 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row49_col4\" class=\"data row49 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row49_col5\" class=\"data row49 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row49_col6\" class=\"data row49 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row50_col0\" class=\"data row50 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
+       "      <td id=\"T_c9c31_row50_col2\" class=\"data row50 col2\" >$ 6,703</td>\n",
+       "      <td id=\"T_c9c31_row50_col3\" class=\"data row50 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row50_col4\" class=\"data row50 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row50_col5\" class=\"data row50 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row50_col6\" class=\"data row50 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row51_col0\" class=\"data row51 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col1\" class=\"data row51 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col2\" class=\"data row51 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col3\" class=\"data row51 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col4\" class=\"data row51 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col5\" class=\"data row51 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row51_col6\" class=\"data row51 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row52_col0\" class=\"data row52 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
+       "      <td id=\"T_c9c31_row52_col2\" class=\"data row52 col2\" >$ 5,194,552,469</td>\n",
+       "      <td id=\"T_c9c31_row52_col3\" class=\"data row52 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row52_col4\" class=\"data row52 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row52_col5\" class=\"data row52 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row52_col6\" class=\"data row52 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row53_col0\" class=\"data row53 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
+       "      <td id=\"T_c9c31_row53_col2\" class=\"data row53 col2\" >$ 4,919</td>\n",
+       "      <td id=\"T_c9c31_row53_col3\" class=\"data row53 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row53_col4\" class=\"data row53 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row53_col5\" class=\"data row53 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row53_col6\" class=\"data row53 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row54_col0\" class=\"data row54 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col1\" class=\"data row54 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col2\" class=\"data row54 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col3\" class=\"data row54 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col4\" class=\"data row54 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col5\" class=\"data row54 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row54_col6\" class=\"data row54 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row55_col0\" class=\"data row55 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
+       "      <td id=\"T_c9c31_row55_col2\" class=\"data row55 col2\" >$ 13,412,051,120</td>\n",
+       "      <td id=\"T_c9c31_row55_col3\" class=\"data row55 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row55_col4\" class=\"data row55 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row55_col5\" class=\"data row55 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row55_col6\" class=\"data row55 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row56_col0\" class=\"data row56 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
+       "      <td id=\"T_c9c31_row56_col2\" class=\"data row56 col2\" >$ 12,701</td>\n",
+       "      <td id=\"T_c9c31_row56_col3\" class=\"data row56 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row56_col4\" class=\"data row56 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row56_col5\" class=\"data row56 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row56_col6\" class=\"data row56 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row57_col0\" class=\"data row57 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col1\" class=\"data row57 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col2\" class=\"data row57 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col3\" class=\"data row57 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col4\" class=\"data row57 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col5\" class=\"data row57 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row57_col6\" class=\"data row57 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row58_col0\" class=\"data row58 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
+       "      <td id=\"T_c9c31_row58_col2\" class=\"data row58 col2\" >$ 13,480,001,446</td>\n",
+       "      <td id=\"T_c9c31_row58_col3\" class=\"data row58 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row58_col4\" class=\"data row58 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row58_col5\" class=\"data row58 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row58_col6\" class=\"data row58 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row59_col0\" class=\"data row59 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
+       "      <td id=\"T_c9c31_row59_col2\" class=\"data row59 col2\" >$ 12,765</td>\n",
+       "      <td id=\"T_c9c31_row59_col3\" class=\"data row59 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row59_col4\" class=\"data row59 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row59_col5\" class=\"data row59 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row59_col6\" class=\"data row59 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row60_col0\" class=\"data row60 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col1\" class=\"data row60 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col2\" class=\"data row60 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col3\" class=\"data row60 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col4\" class=\"data row60 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col5\" class=\"data row60 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row60_col6\" class=\"data row60 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row61_col0\" class=\"data row61 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
+       "      <td id=\"T_c9c31_row61_col2\" class=\"data row61 col2\" >$ 20,558,611,899</td>\n",
+       "      <td id=\"T_c9c31_row61_col3\" class=\"data row61 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row61_col4\" class=\"data row61 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row61_col5\" class=\"data row61 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row61_col6\" class=\"data row61 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row62_col0\" class=\"data row62 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
+       "      <td id=\"T_c9c31_row62_col2\" class=\"data row62 col2\" >$ 19,468</td>\n",
+       "      <td id=\"T_c9c31_row62_col3\" class=\"data row62 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row62_col4\" class=\"data row62 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row62_col5\" class=\"data row62 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row62_col6\" class=\"data row62 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row63_col0\" class=\"data row63 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col1\" class=\"data row63 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col2\" class=\"data row63 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col3\" class=\"data row63 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col4\" class=\"data row63 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col5\" class=\"data row63 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row63_col6\" class=\"data row63 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row64_col0\" class=\"data row64 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
+       "      <td id=\"T_c9c31_row64_col2\" class=\"data row64 col2\" >$ 8,699,310,293</td>\n",
+       "      <td id=\"T_c9c31_row64_col3\" class=\"data row64 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row64_col4\" class=\"data row64 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row64_col5\" class=\"data row64 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row64_col6\" class=\"data row64 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row65_col0\" class=\"data row65 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_c9c31_row65_col2\" class=\"data row65 col2\" >$ 8,238</td>\n",
+       "      <td id=\"T_c9c31_row65_col3\" class=\"data row65 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row65_col4\" class=\"data row65 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row65_col5\" class=\"data row65 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row65_col6\" class=\"data row65 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row66_col0\" class=\"data row66 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col1\" class=\"data row66 col1\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col2\" class=\"data row66 col2\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col3\" class=\"data row66 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col4\" class=\"data row66 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col5\" class=\"data row66 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row66_col6\" class=\"data row66 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row67_col0\" class=\"data row67 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
+       "      <td id=\"T_c9c31_row67_col2\" class=\"data row67 col2\" >$ 11,901,472,053</td>\n",
+       "      <td id=\"T_c9c31_row67_col3\" class=\"data row67 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row67_col4\" class=\"data row67 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row67_col5\" class=\"data row67 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row67_col6\" class=\"data row67 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_c9c31_row68_col0\" class=\"data row68 col0\" ></td>\n",
+       "      <td id=\"T_c9c31_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_c9c31_row68_col2\" class=\"data row68 col2\" >$ 11,270</td>\n",
+       "      <td id=\"T_c9c31_row68_col3\" class=\"data row68 col3\" ></td>\n",
+       "      <td id=\"T_c9c31_row68_col4\" class=\"data row68 col4\" ></td>\n",
+       "      <td id=\"T_c9c31_row68_col5\" class=\"data row68 col5\" ></td>\n",
+       "      <td id=\"T_c9c31_row68_col6\" class=\"data row68 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x16730be10>"
+       "<pandas.io.formats.style.Styler at 0x15a36ff10>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4872,34 +4895,34 @@
     "    sp = pd.read_excel('inputs.xlsx', sheet_name = \"Ref Spending Curve\", nrows= 104, usecols='A : D')\n",
     "    Months = sp['Month'].tolist()\n",
     "    CDFs  = sp['CDF'].tolist()\n",
-    "\n",
+    "    \n",
     "    annual_periods = np.linspace(12, 12*int(final_construction_duration/12),int(final_construction_duration/12))\n",
+    "   \n",
     "    if max(annual_periods) < int(final_construction_duration)-1:\n",
     "        annual_periods_1= np.append( annual_periods, (final_construction_duration)-1)\n",
     "    else:\n",
     "        annual_periods_1 = annual_periods\n",
+    "    \n",
     "    annual_cum_spend = []\n",
     "    for period in annual_periods_1:\n",
     "        new_period = 103*period/int(final_construction_duration)\n",
-    "        annual_cum_spend.append(np.interp(new_period, Months, CDFs))\n",
     "        \n",
-    "    annual_cum_spend1 = np.append(annual_cum_spend[0], np.diff(annual_cum_spend ))\n",
+    "        annual_cum_spend.append(np.interp(new_period, Months, CDFs))\n",
+    "    annual_spend1 = np.append(annual_cum_spend[0], np.diff(annual_cum_spend ))\n",
+    "    \n",
     "    tot_overnight_cost =   (Reactor_data_updated_8.loc[Reactor_data_updated_8.Title == 'Total Overnight Cost (Accounts 10 to 50)' , 'Total Cost (USD)']).values[0]\n",
     "\n",
-    "\n",
-    "    annual_loan_add =  annual_cum_spend1 *tot_overnight_cost\n",
-    "\n",
+    "    annual_loan_add =  annual_spend1 *tot_overnight_cost\n",
+    "    \n",
     "    interest_exp = ((1+interest_rate)**((final_construction_duration -annual_periods_1)/12)) * annual_loan_add - annual_loan_add\n",
-    "\n",
-    "    tot_int_exp_construction = sum(interest_exp )\n",
     "    \n",
+    "    tot_int_exp_construction = sum(interest_exp )\n",
     "    if n_th == 1:\n",
     "        startup = startup_0\n",
     "    elif n_th >1:\n",
     "        startup = max( 7 , startup_0*(1-0.3)**np.log2(n_th)  )\n",
-    "\n",
-    "    int_exp_startup = (tot_int_exp_construction + tot_overnight_cost)*((1+interest_rate)**(startup/12))-(tot_int_exp_construction + tot_overnight_cost)\n",
     "    \n",
+    "    int_exp_startup = (tot_int_exp_construction + tot_overnight_cost)*((1+interest_rate)**(startup/12))-(tot_int_exp_construction + tot_overnight_cost)\n",
     "    db = pd.DataFrame()\n",
     "\n",
     "    db = Reactor_data_updated_8[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\\\n",
@@ -4922,11 +4945,8 @@
     "\n",
     "\n",
     "# Example\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "tot_base_cost_results = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0))\n",
-    "tot_base_cost = tot_base_cost_results[0]\n",
-    "final_construction_duration = tot_base_cost_results[1]\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "tot_base_cost, final_construction_duration = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0))\n",
     "\n",
     "tot_base_cost_wz_insurance = insurance_cost_update(reactor_data, tot_base_cost , reactor_power)\n",
     "tot_base_cost_wz_insurance_interest = (update_interest_cost(tot_base_cost_wz_insurance , final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power))[0]\n",
@@ -4936,7 +4956,7 @@
     "tot_base_cost_wz_insurance_interest_pretty = prettify(tot_base_cost_wz_insurance_interest,\\\n",
     "            f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor <br> Capital Cost Summary - Base Cost updated (Direct and Indirect costs) plus insurance and interest <br><br> \", \"no_subsidies\")\n",
     "\n",
-    "tot_base_cost_wz_insurance_interest_pretty\n"
+    "tot_base_cost_wz_insurance_interest_pretty"
    ]
   },
   {
@@ -4944,12 +4964,12 @@
    "id": "285ff958-5114-480f-93e1-d1874988ab69",
    "metadata": {},
    "source": [
-    "### Section 3 - 12 :  ITC Subsidies"
+    "### Section 3 - 11 :  ITC Subsidies"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "id": "f5b6baa7-0224-483b-bcd3-59301602ba3e",
    "metadata": {},
    "outputs": [
@@ -4957,657 +4977,657 @@
      "data": {
       "text/html": [
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        "  font-weight: bold;\n",
        "}\n",
        "</style>\n",
-       "<table id=\"T_c07c2\">\n",
-       "  <caption> The Concept B 310.8 MWe Reactor <br> Capital Cost Summary  <br><br> </caption>\n",
+       "<table id=\"T_e227c\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor <br> Capital Cost Summary  <br><br> </caption>\n",
        "  <thead>\n",
        "    <tr>\n",
-       "      <th id=\"T_c07c2_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
-       "      <th id=\"T_c07c2_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
-       "      <th id=\"T_c07c2_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
-       "      <th id=\"T_c07c2_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
-       "      <th id=\"T_c07c2_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
-       "      <th id=\"T_c07c2_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
-       "      <th id=\"T_c07c2_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "      <th id=\"T_e227c_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_e227c_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_e227c_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_e227c_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_e227c_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_e227c_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_e227c_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td id=\"T_c07c2_row0_col0\" class=\"data row0 col0\" >10</td>\n",
-       "      <td id=\"T_c07c2_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
-       "      <td id=\"T_c07c2_row0_col2\" class=\"data row0 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row0_col3\" class=\"data row0 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row0_col4\" class=\"data row0 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row0_col5\" class=\"data row0 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row0_col6\" class=\"data row0 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row1_col0\" class=\"data row1 col0\" >11</td>\n",
-       "      <td id=\"T_c07c2_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
-       "      <td id=\"T_c07c2_row1_col2\" class=\"data row1 col2\" >$ 11,000,000</td>\n",
-       "      <td id=\"T_c07c2_row1_col3\" class=\"data row1 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row1_col4\" class=\"data row1 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row1_col5\" class=\"data row1 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row1_col6\" class=\"data row1 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row2_col0\" class=\"data row2 col0\" >12</td>\n",
-       "      <td id=\"T_c07c2_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
-       "      <td id=\"T_c07c2_row2_col2\" class=\"data row2 col2\" >$ 1,598,891</td>\n",
-       "      <td id=\"T_c07c2_row2_col3\" class=\"data row2 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row2_col4\" class=\"data row2 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row2_col5\" class=\"data row2 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row2_col6\" class=\"data row2 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row3_col0\" class=\"data row3 col0\" >13</td>\n",
-       "      <td id=\"T_c07c2_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
-       "      <td id=\"T_c07c2_row3_col2\" class=\"data row3 col2\" >$ 24,382,988</td>\n",
-       "      <td id=\"T_c07c2_row3_col3\" class=\"data row3 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row3_col4\" class=\"data row3 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row3_col5\" class=\"data row3 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row3_col6\" class=\"data row3 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row4_col0\" class=\"data row4 col0\" >14</td>\n",
-       "      <td id=\"T_c07c2_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
-       "      <td id=\"T_c07c2_row4_col2\" class=\"data row4 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_c07c2_row4_col3\" class=\"data row4 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row4_col4\" class=\"data row4 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row4_col5\" class=\"data row4 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row4_col6\" class=\"data row4 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row5_col0\" class=\"data row5 col0\" >15</td>\n",
-       "      <td id=\"T_c07c2_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
-       "      <td id=\"T_c07c2_row5_col2\" class=\"data row5 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_c07c2_row5_col3\" class=\"data row5 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row5_col4\" class=\"data row5 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row5_col5\" class=\"data row5 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row5_col6\" class=\"data row5 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row6_col0\" class=\"data row6 col0\" >16</td>\n",
-       "      <td id=\"T_c07c2_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
-       "      <td id=\"T_c07c2_row6_col2\" class=\"data row6 col2\" >$ 3,972,186</td>\n",
-       "      <td id=\"T_c07c2_row6_col3\" class=\"data row6 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row6_col4\" class=\"data row6 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row6_col5\" class=\"data row6 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row6_col6\" class=\"data row6 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row7_col0\" class=\"data row7 col0\" >18</td>\n",
-       "      <td id=\"T_c07c2_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
-       "      <td id=\"T_c07c2_row7_col2\" class=\"data row7 col2\" >$ 12,679,167</td>\n",
-       "      <td id=\"T_c07c2_row7_col3\" class=\"data row7 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row7_col4\" class=\"data row7 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row7_col5\" class=\"data row7 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row7_col6\" class=\"data row7 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row8_col0\" class=\"data row8 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col1\" class=\"data row8 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col2\" class=\"data row8 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col3\" class=\"data row8 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col4\" class=\"data row8 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col5\" class=\"data row8 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row8_col6\" class=\"data row8 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row9_col0\" class=\"data row9 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
-       "      <td id=\"T_c07c2_row9_col2\" class=\"data row9 col2\" >$ 78,991,565</td>\n",
-       "      <td id=\"T_c07c2_row9_col3\" class=\"data row9 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row9_col4\" class=\"data row9 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row9_col5\" class=\"data row9 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row9_col6\" class=\"data row9 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row10_col0\" class=\"data row10 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
-       "      <td id=\"T_c07c2_row10_col2\" class=\"data row10 col2\" >$ 254</td>\n",
-       "      <td id=\"T_c07c2_row10_col3\" class=\"data row10 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row10_col4\" class=\"data row10 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row10_col5\" class=\"data row10 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row10_col6\" class=\"data row10 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row11_col0\" class=\"data row11 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col1\" class=\"data row11 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col2\" class=\"data row11 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col3\" class=\"data row11 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col4\" class=\"data row11 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col5\" class=\"data row11 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row11_col6\" class=\"data row11 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row12_col0\" class=\"data row12 col0\" >20</td>\n",
-       "      <td id=\"T_c07c2_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
-       "      <td id=\"T_c07c2_row12_col2\" class=\"data row12 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row12_col3\" class=\"data row12 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row12_col4\" class=\"data row12 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row12_col5\" class=\"data row12 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row12_col6\" class=\"data row12 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row13_col0\" class=\"data row13 col0\" >21</td>\n",
-       "      <td id=\"T_c07c2_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
-       "      <td id=\"T_c07c2_row13_col2\" class=\"data row13 col2\" >$ 440,882,959</td>\n",
-       "      <td id=\"T_c07c2_row13_col3\" class=\"data row13 col3\" >$ 106,559,047</td>\n",
-       "      <td id=\"T_c07c2_row13_col4\" class=\"data row13 col4\" >5,557,506 hrs</td>\n",
-       "      <td id=\"T_c07c2_row13_col5\" class=\"data row13 col5\" >$ 279,152,503</td>\n",
-       "      <td id=\"T_c07c2_row13_col6\" class=\"data row13 col6\" >$ 55,171,408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row14_col0\" class=\"data row14 col0\" >212</td>\n",
-       "      <td id=\"T_c07c2_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
-       "      <td id=\"T_c07c2_row14_col2\" class=\"data row14 col2\" >$ 264,076,459</td>\n",
-       "      <td id=\"T_c07c2_row14_col3\" class=\"data row14 col3\" >$ 95,722,667</td>\n",
-       "      <td id=\"T_c07c2_row14_col4\" class=\"data row14 col4\" >3,121,808 hrs</td>\n",
-       "      <td id=\"T_c07c2_row14_col5\" class=\"data row14 col5\" >$ 157,643,178</td>\n",
-       "      <td id=\"T_c07c2_row14_col6\" class=\"data row14 col6\" >$ 10,710,615</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row15_col0\" class=\"data row15 col0\" >213</td>\n",
-       "      <td id=\"T_c07c2_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
-       "      <td id=\"T_c07c2_row15_col2\" class=\"data row15 col2\" >$ 10,386,814</td>\n",
-       "      <td id=\"T_c07c2_row15_col3\" class=\"data row15 col3\" >$ 619,346</td>\n",
-       "      <td id=\"T_c07c2_row15_col4\" class=\"data row15 col4\" >119,453 hrs</td>\n",
-       "      <td id=\"T_c07c2_row15_col5\" class=\"data row15 col5\" >$ 6,159,946</td>\n",
-       "      <td id=\"T_c07c2_row15_col6\" class=\"data row15 col6\" >$ 3,607,522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
-       "      <td id=\"T_c07c2_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
-       "      <td id=\"T_c07c2_row16_col2\" class=\"data row16 col2\" >$ 166,419,685</td>\n",
-       "      <td id=\"T_c07c2_row16_col3\" class=\"data row16 col3\" >$ 10,217,034</td>\n",
-       "      <td id=\"T_c07c2_row16_col4\" class=\"data row16 col4\" >2,316,244 hrs</td>\n",
-       "      <td id=\"T_c07c2_row16_col5\" class=\"data row16 col5\" >$ 115,349,380</td>\n",
-       "      <td id=\"T_c07c2_row16_col6\" class=\"data row16 col6\" >$ 40,853,271</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row17_col0\" class=\"data row17 col0\" >22</td>\n",
-       "      <td id=\"T_c07c2_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
-       "      <td id=\"T_c07c2_row17_col2\" class=\"data row17 col2\" >$ 807,606,906</td>\n",
-       "      <td id=\"T_c07c2_row17_col3\" class=\"data row17 col3\" >$ 611,521,554</td>\n",
-       "      <td id=\"T_c07c2_row17_col4\" class=\"data row17 col4\" >3,518,498 hrs</td>\n",
-       "      <td id=\"T_c07c2_row17_col5\" class=\"data row17 col5\" >$ 189,006,816</td>\n",
-       "      <td id=\"T_c07c2_row17_col6\" class=\"data row17 col6\" >$ 7,078,536</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row18_col0\" class=\"data row18 col0\" >23</td>\n",
-       "      <td id=\"T_c07c2_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
-       "      <td id=\"T_c07c2_row18_col2\" class=\"data row18 col2\" >$ 206,565,176</td>\n",
-       "      <td id=\"T_c07c2_row18_col3\" class=\"data row18 col3\" >$ 135,167,625</td>\n",
-       "      <td id=\"T_c07c2_row18_col4\" class=\"data row18 col4\" >1,264,169 hrs</td>\n",
-       "      <td id=\"T_c07c2_row18_col5\" class=\"data row18 col5\" >$ 66,920,930</td>\n",
-       "      <td id=\"T_c07c2_row18_col6\" class=\"data row18 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
-       "      <td id=\"T_c07c2_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
-       "      <td id=\"T_c07c2_row19_col2\" class=\"data row19 col2\" >$ 133,275,069</td>\n",
-       "      <td id=\"T_c07c2_row19_col3\" class=\"data row19 col3\" >$ 98,488,776</td>\n",
-       "      <td id=\"T_c07c2_row19_col4\" class=\"data row19 col4\" >652,925 hrs</td>\n",
-       "      <td id=\"T_c07c2_row19_col5\" class=\"data row19 col5\" >$ 34,786,293</td>\n",
-       "      <td id=\"T_c07c2_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row20_col0\" class=\"data row20 col0\" >233</td>\n",
-       "      <td id=\"T_c07c2_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
-       "      <td id=\"T_c07c2_row20_col2\" class=\"data row20 col2\" >$ 73,290,107</td>\n",
-       "      <td id=\"T_c07c2_row20_col3\" class=\"data row20 col3\" >$ 36,678,849</td>\n",
-       "      <td id=\"T_c07c2_row20_col4\" class=\"data row20 col4\" >611,244 hrs</td>\n",
-       "      <td id=\"T_c07c2_row20_col5\" class=\"data row20 col5\" >$ 32,134,637</td>\n",
-       "      <td id=\"T_c07c2_row20_col6\" class=\"data row20 col6\" >$ 4,476,621</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row21_col0\" class=\"data row21 col0\" >24</td>\n",
-       "      <td id=\"T_c07c2_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
-       "      <td id=\"T_c07c2_row21_col2\" class=\"data row21 col2\" >$ 123,782,437</td>\n",
-       "      <td id=\"T_c07c2_row21_col3\" class=\"data row21 col3\" >$ 22,712,248</td>\n",
-       "      <td id=\"T_c07c2_row21_col4\" class=\"data row21 col4\" >1,491,382 hrs</td>\n",
-       "      <td id=\"T_c07c2_row21_col5\" class=\"data row21 col5\" >$ 80,385,388</td>\n",
-       "      <td id=\"T_c07c2_row21_col6\" class=\"data row21 col6\" >$ 20,684,801</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row22_col0\" class=\"data row22 col0\" >25</td>\n",
-       "      <td id=\"T_c07c2_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
-       "      <td id=\"T_c07c2_row22_col2\" class=\"data row22 col2\" >$ 279,724,434</td>\n",
-       "      <td id=\"T_c07c2_row22_col3\" class=\"data row22 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row22_col4\" class=\"data row22 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row22_col5\" class=\"data row22 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row22_col6\" class=\"data row22 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row23_col0\" class=\"data row23 col0\" >26</td>\n",
-       "      <td id=\"T_c07c2_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
-       "      <td id=\"T_c07c2_row23_col2\" class=\"data row23 col2\" >$ 46,907,265</td>\n",
-       "      <td id=\"T_c07c2_row23_col3\" class=\"data row23 col3\" >$ 13,917,713</td>\n",
-       "      <td id=\"T_c07c2_row23_col4\" class=\"data row23 col4\" >542,064 hrs</td>\n",
-       "      <td id=\"T_c07c2_row23_col5\" class=\"data row23 col5\" >$ 29,377,876</td>\n",
-       "      <td id=\"T_c07c2_row23_col6\" class=\"data row23 col6\" >$ 3,611,675</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row24_col0\" class=\"data row24 col0\" >28</td>\n",
-       "      <td id=\"T_c07c2_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
-       "      <td id=\"T_c07c2_row24_col2\" class=\"data row24 col2\" >$ 78,200</td>\n",
-       "      <td id=\"T_c07c2_row24_col3\" class=\"data row24 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row24_col4\" class=\"data row24 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row24_col5\" class=\"data row24 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row24_col6\" class=\"data row24 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row25_col0\" class=\"data row25 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col1\" class=\"data row25 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col2\" class=\"data row25 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col3\" class=\"data row25 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col4\" class=\"data row25 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col5\" class=\"data row25 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row25_col6\" class=\"data row25 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row26_col0\" class=\"data row26 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
-       "      <td id=\"T_c07c2_row26_col2\" class=\"data row26 col2\" >$ 1,905,547,377</td>\n",
-       "      <td id=\"T_c07c2_row26_col3\" class=\"data row26 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row26_col4\" class=\"data row26 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row26_col5\" class=\"data row26 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row26_col6\" class=\"data row26 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row27_col0\" class=\"data row27 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
-       "      <td id=\"T_c07c2_row27_col2\" class=\"data row27 col2\" >$ 6,131</td>\n",
-       "      <td id=\"T_c07c2_row27_col3\" class=\"data row27 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row27_col4\" class=\"data row27 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row27_col5\" class=\"data row27 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row27_col6\" class=\"data row27 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row28_col0\" class=\"data row28 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col1\" class=\"data row28 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col2\" class=\"data row28 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col3\" class=\"data row28 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col4\" class=\"data row28 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col5\" class=\"data row28 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row28_col6\" class=\"data row28 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row29_col0\" class=\"data row29 col0\" >30</td>\n",
-       "      <td id=\"T_c07c2_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
-       "      <td id=\"T_c07c2_row29_col2\" class=\"data row29 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row29_col3\" class=\"data row29 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row29_col4\" class=\"data row29 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row29_col5\" class=\"data row29 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row29_col6\" class=\"data row29 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row30_col0\" class=\"data row30 col0\" >31</td>\n",
-       "      <td id=\"T_c07c2_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
-       "      <td id=\"T_c07c2_row30_col2\" class=\"data row30 col2\" >$ 288,869,950</td>\n",
-       "      <td id=\"T_c07c2_row30_col3\" class=\"data row30 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row30_col4\" class=\"data row30 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row30_col5\" class=\"data row30 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row30_col6\" class=\"data row30 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row31_col0\" class=\"data row31 col0\" >32</td>\n",
-       "      <td id=\"T_c07c2_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
-       "      <td id=\"T_c07c2_row31_col2\" class=\"data row31 col2\" >$ 1,086,805,413</td>\n",
-       "      <td id=\"T_c07c2_row31_col3\" class=\"data row31 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row31_col4\" class=\"data row31 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row31_col5\" class=\"data row31 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row31_col6\" class=\"data row31 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row32_col0\" class=\"data row32 col0\" >33</td>\n",
-       "      <td id=\"T_c07c2_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
-       "      <td id=\"T_c07c2_row32_col2\" class=\"data row32 col2\" >$ 45,645,827</td>\n",
-       "      <td id=\"T_c07c2_row32_col3\" class=\"data row32 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row32_col4\" class=\"data row32 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row32_col5\" class=\"data row32 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row32_col6\" class=\"data row32 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row33_col0\" class=\"data row33 col0\" >34</td>\n",
-       "      <td id=\"T_c07c2_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
-       "      <td id=\"T_c07c2_row33_col2\" class=\"data row33 col2\" >$ 3,803,819</td>\n",
-       "      <td id=\"T_c07c2_row33_col3\" class=\"data row33 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row33_col4\" class=\"data row33 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row33_col5\" class=\"data row33 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row33_col6\" class=\"data row33 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row34_col0\" class=\"data row34 col0\" >35</td>\n",
-       "      <td id=\"T_c07c2_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
-       "      <td id=\"T_c07c2_row34_col2\" class=\"data row34 col2\" >$ 293,437,462</td>\n",
-       "      <td id=\"T_c07c2_row34_col3\" class=\"data row34 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row34_col4\" class=\"data row34 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row34_col5\" class=\"data row34 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row34_col6\" class=\"data row34 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row35_col0\" class=\"data row35 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col1\" class=\"data row35 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col2\" class=\"data row35 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col3\" class=\"data row35 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col4\" class=\"data row35 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col5\" class=\"data row35 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row35_col6\" class=\"data row35 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row36_col0\" class=\"data row36 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
-       "      <td id=\"T_c07c2_row36_col2\" class=\"data row36 col2\" >$ 1,718,562,471</td>\n",
-       "      <td id=\"T_c07c2_row36_col3\" class=\"data row36 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row36_col4\" class=\"data row36 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row36_col5\" class=\"data row36 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row36_col6\" class=\"data row36 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row37_col0\" class=\"data row37 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
-       "      <td id=\"T_c07c2_row37_col2\" class=\"data row37 col2\" >$ 5,529</td>\n",
-       "      <td id=\"T_c07c2_row37_col3\" class=\"data row37 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row37_col4\" class=\"data row37 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row37_col5\" class=\"data row37 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row37_col6\" class=\"data row37 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row38_col0\" class=\"data row38 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col1\" class=\"data row38 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col2\" class=\"data row38 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col3\" class=\"data row38 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col4\" class=\"data row38 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col5\" class=\"data row38 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row38_col6\" class=\"data row38 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row39_col0\" class=\"data row39 col0\" >50</td>\n",
-       "      <td id=\"T_c07c2_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
-       "      <td id=\"T_c07c2_row39_col2\" class=\"data row39 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row39_col3\" class=\"data row39 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row39_col4\" class=\"data row39 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row39_col5\" class=\"data row39 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row39_col6\" class=\"data row39 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row40_col0\" class=\"data row40 col0\" >51</td>\n",
-       "      <td id=\"T_c07c2_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
-       "      <td id=\"T_c07c2_row40_col2\" class=\"data row40 col2\" >$ 3,510,602</td>\n",
-       "      <td id=\"T_c07c2_row40_col3\" class=\"data row40 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row40_col4\" class=\"data row40 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row40_col5\" class=\"data row40 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row40_col6\" class=\"data row40 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row41_col0\" class=\"data row41 col0\" >52</td>\n",
-       "      <td id=\"T_c07c2_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
-       "      <td id=\"T_c07c2_row41_col2\" class=\"data row41 col2\" >$ 16,308,494</td>\n",
-       "      <td id=\"T_c07c2_row41_col3\" class=\"data row41 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row41_col4\" class=\"data row41 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row41_col5\" class=\"data row41 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row41_col6\" class=\"data row41 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row42_col0\" class=\"data row42 col0\" >54</td>\n",
-       "      <td id=\"T_c07c2_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
-       "      <td id=\"T_c07c2_row42_col2\" class=\"data row42 col2\" >$ 14,606,673</td>\n",
-       "      <td id=\"T_c07c2_row42_col3\" class=\"data row42 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row42_col4\" class=\"data row42 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row42_col5\" class=\"data row42 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row42_col6\" class=\"data row42 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row43_col0\" class=\"data row43 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col1\" class=\"data row43 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col2\" class=\"data row43 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col3\" class=\"data row43 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col4\" class=\"data row43 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col5\" class=\"data row43 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row43_col6\" class=\"data row43 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row44_col0\" class=\"data row44 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
-       "      <td id=\"T_c07c2_row44_col2\" class=\"data row44 col2\" >$ 34,425,770</td>\n",
-       "      <td id=\"T_c07c2_row44_col3\" class=\"data row44 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row44_col4\" class=\"data row44 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row44_col5\" class=\"data row44 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row44_col6\" class=\"data row44 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row45_col0\" class=\"data row45 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
-       "      <td id=\"T_c07c2_row45_col2\" class=\"data row45 col2\" >$ 111</td>\n",
-       "      <td id=\"T_c07c2_row45_col3\" class=\"data row45 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row45_col4\" class=\"data row45 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row45_col5\" class=\"data row45 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row45_col6\" class=\"data row45 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row46_col0\" class=\"data row46 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col1\" class=\"data row46 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col2\" class=\"data row46 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col3\" class=\"data row46 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col4\" class=\"data row46 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col5\" class=\"data row46 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row46_col6\" class=\"data row46 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row47_col0\" class=\"data row47 col0\" >60</td>\n",
-       "      <td id=\"T_c07c2_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
-       "      <td id=\"T_c07c2_row47_col2\" class=\"data row47 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row47_col3\" class=\"data row47 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row47_col4\" class=\"data row47 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row47_col5\" class=\"data row47 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row47_col6\" class=\"data row47 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row48_col0\" class=\"data row48 col0\" >62</td>\n",
-       "      <td id=\"T_c07c2_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
-       "      <td id=\"T_c07c2_row48_col2\" class=\"data row48 col2\" >$ 1,276,775,002</td>\n",
-       "      <td id=\"T_c07c2_row48_col3\" class=\"data row48 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row48_col4\" class=\"data row48 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row48_col5\" class=\"data row48 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row48_col6\" class=\"data row48 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row49_col0\" class=\"data row49 col0\" >-</td>\n",
-       "      <td id=\"T_c07c2_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
-       "      <td id=\"T_c07c2_row49_col2\" class=\"data row49 col2\" >$ 1,276,775,002</td>\n",
-       "      <td id=\"T_c07c2_row49_col3\" class=\"data row49 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row49_col4\" class=\"data row49 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row49_col5\" class=\"data row49 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row49_col6\" class=\"data row49 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row50_col0\" class=\"data row50 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
-       "      <td id=\"T_c07c2_row50_col2\" class=\"data row50 col2\" >$ 4,108</td>\n",
-       "      <td id=\"T_c07c2_row50_col3\" class=\"data row50 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row50_col4\" class=\"data row50 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row50_col5\" class=\"data row50 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row50_col6\" class=\"data row50 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row51_col0\" class=\"data row51 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col1\" class=\"data row51 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col2\" class=\"data row51 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col3\" class=\"data row51 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col4\" class=\"data row51 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col5\" class=\"data row51 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row51_col6\" class=\"data row51 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row52_col0\" class=\"data row52 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
-       "      <td id=\"T_c07c2_row52_col2\" class=\"data row52 col2\" >$ 1,984,538,942</td>\n",
-       "      <td id=\"T_c07c2_row52_col3\" class=\"data row52 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row52_col4\" class=\"data row52 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row52_col5\" class=\"data row52 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row52_col6\" class=\"data row52 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row53_col0\" class=\"data row53 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
-       "      <td id=\"T_c07c2_row53_col2\" class=\"data row53 col2\" >$ 6,385</td>\n",
-       "      <td id=\"T_c07c2_row53_col3\" class=\"data row53 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row53_col4\" class=\"data row53 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row53_col5\" class=\"data row53 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row53_col6\" class=\"data row53 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row54_col0\" class=\"data row54 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col1\" class=\"data row54 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col2\" class=\"data row54 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col3\" class=\"data row54 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col4\" class=\"data row54 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col5\" class=\"data row54 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row54_col6\" class=\"data row54 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row55_col0\" class=\"data row55 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
-       "      <td id=\"T_c07c2_row55_col2\" class=\"data row55 col2\" >$ 3,703,101,413</td>\n",
-       "      <td id=\"T_c07c2_row55_col3\" class=\"data row55 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row55_col4\" class=\"data row55 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row55_col5\" class=\"data row55 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row55_col6\" class=\"data row55 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row56_col0\" class=\"data row56 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
-       "      <td id=\"T_c07c2_row56_col2\" class=\"data row56 col2\" >$ 11,915</td>\n",
-       "      <td id=\"T_c07c2_row56_col3\" class=\"data row56 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row56_col4\" class=\"data row56 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row56_col5\" class=\"data row56 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row56_col6\" class=\"data row56 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row57_col0\" class=\"data row57 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col1\" class=\"data row57 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col2\" class=\"data row57 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col3\" class=\"data row57 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col4\" class=\"data row57 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col5\" class=\"data row57 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row57_col6\" class=\"data row57 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row58_col0\" class=\"data row58 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
-       "      <td id=\"T_c07c2_row58_col2\" class=\"data row58 col2\" >$ 3,737,527,183</td>\n",
-       "      <td id=\"T_c07c2_row58_col3\" class=\"data row58 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row58_col4\" class=\"data row58 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row58_col5\" class=\"data row58 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row58_col6\" class=\"data row58 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row59_col0\" class=\"data row59 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
-       "      <td id=\"T_c07c2_row59_col2\" class=\"data row59 col2\" >$ 12,026</td>\n",
-       "      <td id=\"T_c07c2_row59_col3\" class=\"data row59 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row59_col4\" class=\"data row59 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row59_col5\" class=\"data row59 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row59_col6\" class=\"data row59 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row60_col0\" class=\"data row60 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col1\" class=\"data row60 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col2\" class=\"data row60 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col3\" class=\"data row60 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col4\" class=\"data row60 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col5\" class=\"data row60 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row60_col6\" class=\"data row60 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row61_col0\" class=\"data row61 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
-       "      <td id=\"T_c07c2_row61_col2\" class=\"data row61 col2\" >$ 5,014,302,185</td>\n",
-       "      <td id=\"T_c07c2_row61_col3\" class=\"data row61 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row61_col4\" class=\"data row61 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row61_col5\" class=\"data row61 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row61_col6\" class=\"data row61 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row62_col0\" class=\"data row62 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
-       "      <td id=\"T_c07c2_row62_col2\" class=\"data row62 col2\" >$ 16,134</td>\n",
-       "      <td id=\"T_c07c2_row62_col3\" class=\"data row62 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row62_col4\" class=\"data row62 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row62_col5\" class=\"data row62 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row62_col6\" class=\"data row62 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row63_col0\" class=\"data row63 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col1\" class=\"data row63 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col2\" class=\"data row63 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col3\" class=\"data row63 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col4\" class=\"data row63 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col5\" class=\"data row63 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row63_col6\" class=\"data row63 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row64_col0\" class=\"data row64 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
-       "      <td id=\"T_c07c2_row64_col2\" class=\"data row64 col2\" >$ 3,737,527,183</td>\n",
-       "      <td id=\"T_c07c2_row64_col3\" class=\"data row64 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row64_col4\" class=\"data row64 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row64_col5\" class=\"data row64 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row64_col6\" class=\"data row64 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row65_col0\" class=\"data row65 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_c07c2_row65_col2\" class=\"data row65 col2\" >$ 12,026</td>\n",
-       "      <td id=\"T_c07c2_row65_col3\" class=\"data row65 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row65_col4\" class=\"data row65 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row65_col5\" class=\"data row65 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row65_col6\" class=\"data row65 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row66_col0\" class=\"data row66 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col1\" class=\"data row66 col1\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col2\" class=\"data row66 col2\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col3\" class=\"data row66 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col4\" class=\"data row66 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col5\" class=\"data row66 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row66_col6\" class=\"data row66 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row67_col0\" class=\"data row67 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
-       "      <td id=\"T_c07c2_row67_col2\" class=\"data row67 col2\" >$ 5,014,302,185</td>\n",
-       "      <td id=\"T_c07c2_row67_col3\" class=\"data row67 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row67_col4\" class=\"data row67 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row67_col5\" class=\"data row67 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row67_col6\" class=\"data row67 col6\" ></td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td id=\"T_c07c2_row68_col0\" class=\"data row68 col0\" ></td>\n",
-       "      <td id=\"T_c07c2_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
-       "      <td id=\"T_c07c2_row68_col2\" class=\"data row68 col2\" >$ 16,134</td>\n",
-       "      <td id=\"T_c07c2_row68_col3\" class=\"data row68 col3\" ></td>\n",
-       "      <td id=\"T_c07c2_row68_col4\" class=\"data row68 col4\" ></td>\n",
-       "      <td id=\"T_c07c2_row68_col5\" class=\"data row68 col5\" ></td>\n",
-       "      <td id=\"T_c07c2_row68_col6\" class=\"data row68 col6\" ></td>\n",
+       "      <td id=\"T_e227c_row0_col0\" class=\"data row0 col0\" >10</td>\n",
+       "      <td id=\"T_e227c_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
+       "      <td id=\"T_e227c_row0_col2\" class=\"data row0 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row0_col3\" class=\"data row0 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row0_col4\" class=\"data row0 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row0_col5\" class=\"data row0 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row0_col6\" class=\"data row0 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row1_col0\" class=\"data row1 col0\" >11</td>\n",
+       "      <td id=\"T_e227c_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
+       "      <td id=\"T_e227c_row1_col2\" class=\"data row1 col2\" >$ 15,000,000</td>\n",
+       "      <td id=\"T_e227c_row1_col3\" class=\"data row1 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row1_col4\" class=\"data row1 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row1_col5\" class=\"data row1 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row1_col6\" class=\"data row1 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row2_col0\" class=\"data row2 col0\" >12</td>\n",
+       "      <td id=\"T_e227c_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
+       "      <td id=\"T_e227c_row2_col2\" class=\"data row2 col2\" >$ 0</td>\n",
+       "      <td id=\"T_e227c_row2_col3\" class=\"data row2 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row2_col4\" class=\"data row2 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row2_col5\" class=\"data row2 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row2_col6\" class=\"data row2 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row3_col0\" class=\"data row3 col0\" >13</td>\n",
+       "      <td id=\"T_e227c_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
+       "      <td id=\"T_e227c_row3_col2\" class=\"data row3 col2\" >$ 107,009,772</td>\n",
+       "      <td id=\"T_e227c_row3_col3\" class=\"data row3 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row3_col4\" class=\"data row3 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row3_col5\" class=\"data row3 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row3_col6\" class=\"data row3 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row4_col0\" class=\"data row4 col0\" >14</td>\n",
+       "      <td id=\"T_e227c_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
+       "      <td id=\"T_e227c_row4_col2\" class=\"data row4 col2\" >$ 4,721,019</td>\n",
+       "      <td id=\"T_e227c_row4_col3\" class=\"data row4 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row4_col4\" class=\"data row4 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row4_col5\" class=\"data row4 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row4_col6\" class=\"data row4 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row5_col0\" class=\"data row5 col0\" >15</td>\n",
+       "      <td id=\"T_e227c_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
+       "      <td id=\"T_e227c_row5_col2\" class=\"data row5 col2\" >$ 0</td>\n",
+       "      <td id=\"T_e227c_row5_col3\" class=\"data row5 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row5_col4\" class=\"data row5 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row5_col5\" class=\"data row5 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row5_col6\" class=\"data row5 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row6_col0\" class=\"data row6 col0\" >16</td>\n",
+       "      <td id=\"T_e227c_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
+       "      <td id=\"T_e227c_row6_col2\" class=\"data row6 col2\" >$ 0</td>\n",
+       "      <td id=\"T_e227c_row6_col3\" class=\"data row6 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row6_col4\" class=\"data row6 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row6_col5\" class=\"data row6 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row6_col6\" class=\"data row6 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row7_col0\" class=\"data row7 col0\" >18</td>\n",
+       "      <td id=\"T_e227c_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
+       "      <td id=\"T_e227c_row7_col2\" class=\"data row7 col2\" >$ 36,194,482</td>\n",
+       "      <td id=\"T_e227c_row7_col3\" class=\"data row7 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row7_col4\" class=\"data row7 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row7_col5\" class=\"data row7 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row7_col6\" class=\"data row7 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row8_col0\" class=\"data row8 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col1\" class=\"data row8 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col2\" class=\"data row8 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col3\" class=\"data row8 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col4\" class=\"data row8 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col5\" class=\"data row8 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row8_col6\" class=\"data row8 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row9_col0\" class=\"data row9 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
+       "      <td id=\"T_e227c_row9_col2\" class=\"data row9 col2\" >$ 162,925,273</td>\n",
+       "      <td id=\"T_e227c_row9_col3\" class=\"data row9 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row9_col4\" class=\"data row9 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row9_col5\" class=\"data row9 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row9_col6\" class=\"data row9 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row10_col0\" class=\"data row10 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
+       "      <td id=\"T_e227c_row10_col2\" class=\"data row10 col2\" >$ 154</td>\n",
+       "      <td id=\"T_e227c_row10_col3\" class=\"data row10 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row10_col4\" class=\"data row10 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row10_col5\" class=\"data row10 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row10_col6\" class=\"data row10 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_e227c_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_e227c_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_e227c_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_e227c_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_e227c_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_e227c_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_e227c_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_e227c_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_e227c_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_e227c_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_e227c_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_e227c_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_e227c_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_e227c_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_e227c_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_e227c_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_e227c_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_e227c_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_e227c_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_e227c_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_e227c_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_e227c_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_e227c_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_e227c_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_e227c_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_e227c_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_e227c_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_e227c_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_e227c_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_e227c_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_e227c_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_e227c_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_e227c_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_e227c_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_e227c_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_e227c_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_e227c_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_e227c_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_e227c_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_e227c_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_e227c_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_e227c_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_e227c_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_e227c_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_e227c_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_e227c_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_e227c_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_e227c_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_e227c_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_e227c_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_e227c_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_e227c_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_e227c_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_e227c_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_e227c_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_e227c_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_e227c_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_e227c_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_e227c_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_e227c_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_e227c_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_e227c_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_e227c_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_e227c_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_e227c_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_e227c_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_e227c_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_e227c_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_e227c_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_e227c_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_e227c_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_e227c_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_e227c_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_e227c_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_e227c_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_e227c_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_e227c_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_e227c_row30_col2\" class=\"data row30 col2\" >$ 1,351,122,731</td>\n",
+       "      <td id=\"T_e227c_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_e227c_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_e227c_row31_col2\" class=\"data row31 col2\" >$ 5,218,449,814</td>\n",
+       "      <td id=\"T_e227c_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_e227c_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_e227c_row32_col2\" class=\"data row32 col2\" >$ 219,540,497</td>\n",
+       "      <td id=\"T_e227c_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_e227c_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_e227c_row33_col2\" class=\"data row33 col2\" >$ 18,485,556</td>\n",
+       "      <td id=\"T_e227c_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_e227c_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_e227c_row34_col2\" class=\"data row34 col2\" >$ 1,409,900,054</td>\n",
+       "      <td id=\"T_e227c_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_e227c_row36_col2\" class=\"data row36 col2\" >$ 8,217,498,651</td>\n",
+       "      <td id=\"T_e227c_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_e227c_row37_col2\" class=\"data row37 col2\" >$ 7,782</td>\n",
+       "      <td id=\"T_e227c_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_e227c_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_e227c_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_e227c_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_e227c_row40_col2\" class=\"data row40 col2\" >$ 187,500</td>\n",
+       "      <td id=\"T_e227c_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row40_col6\" class=\"data row40 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_e227c_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_e227c_row41_col2\" class=\"data row41 col2\" >$ 59,621,066</td>\n",
+       "      <td id=\"T_e227c_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row41_col6\" class=\"data row41 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_e227c_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_e227c_row42_col2\" class=\"data row42 col2\" >$ 8,141,760</td>\n",
+       "      <td id=\"T_e227c_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row42_col6\" class=\"data row42 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_e227c_row44_col2\" class=\"data row44 col2\" >$ 67,950,326</td>\n",
+       "      <td id=\"T_e227c_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row44_col6\" class=\"data row44 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_e227c_row45_col2\" class=\"data row45 col2\" >$ 64</td>\n",
+       "      <td id=\"T_e227c_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row45_col6\" class=\"data row45 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row46_col0\" class=\"data row46 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col1\" class=\"data row46 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col2\" class=\"data row46 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col3\" class=\"data row46 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col4\" class=\"data row46 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col5\" class=\"data row46 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row46_col6\" class=\"data row46 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row47_col0\" class=\"data row47 col0\" >60</td>\n",
+       "      <td id=\"T_e227c_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
+       "      <td id=\"T_e227c_row47_col2\" class=\"data row47 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row47_col3\" class=\"data row47 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row47_col4\" class=\"data row47 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row47_col5\" class=\"data row47 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row47_col6\" class=\"data row47 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row48_col0\" class=\"data row48 col0\" >62</td>\n",
+       "      <td id=\"T_e227c_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
+       "      <td id=\"T_e227c_row48_col2\" class=\"data row48 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_e227c_row48_col3\" class=\"data row48 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row48_col4\" class=\"data row48 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row48_col5\" class=\"data row48 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row48_col6\" class=\"data row48 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row49_col0\" class=\"data row49 col0\" >-</td>\n",
+       "      <td id=\"T_e227c_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
+       "      <td id=\"T_e227c_row49_col2\" class=\"data row49 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_e227c_row49_col3\" class=\"data row49 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row49_col4\" class=\"data row49 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row49_col5\" class=\"data row49 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row49_col6\" class=\"data row49 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row50_col0\" class=\"data row50 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
+       "      <td id=\"T_e227c_row50_col2\" class=\"data row50 col2\" >$ 6,703</td>\n",
+       "      <td id=\"T_e227c_row50_col3\" class=\"data row50 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row50_col4\" class=\"data row50 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row50_col5\" class=\"data row50 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row50_col6\" class=\"data row50 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row51_col0\" class=\"data row51 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col1\" class=\"data row51 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col2\" class=\"data row51 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col3\" class=\"data row51 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col4\" class=\"data row51 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col5\" class=\"data row51 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row51_col6\" class=\"data row51 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row52_col0\" class=\"data row52 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
+       "      <td id=\"T_e227c_row52_col2\" class=\"data row52 col2\" >$ 5,194,552,469</td>\n",
+       "      <td id=\"T_e227c_row52_col3\" class=\"data row52 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row52_col4\" class=\"data row52 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row52_col5\" class=\"data row52 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row52_col6\" class=\"data row52 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row53_col0\" class=\"data row53 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
+       "      <td id=\"T_e227c_row53_col2\" class=\"data row53 col2\" >$ 4,919</td>\n",
+       "      <td id=\"T_e227c_row53_col3\" class=\"data row53 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row53_col4\" class=\"data row53 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row53_col5\" class=\"data row53 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row53_col6\" class=\"data row53 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row54_col0\" class=\"data row54 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col1\" class=\"data row54 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col2\" class=\"data row54 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col3\" class=\"data row54 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col4\" class=\"data row54 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col5\" class=\"data row54 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row54_col6\" class=\"data row54 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row55_col0\" class=\"data row55 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
+       "      <td id=\"T_e227c_row55_col2\" class=\"data row55 col2\" >$ 13,412,051,120</td>\n",
+       "      <td id=\"T_e227c_row55_col3\" class=\"data row55 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row55_col4\" class=\"data row55 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row55_col5\" class=\"data row55 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row55_col6\" class=\"data row55 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row56_col0\" class=\"data row56 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
+       "      <td id=\"T_e227c_row56_col2\" class=\"data row56 col2\" >$ 12,701</td>\n",
+       "      <td id=\"T_e227c_row56_col3\" class=\"data row56 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row56_col4\" class=\"data row56 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row56_col5\" class=\"data row56 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row56_col6\" class=\"data row56 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row57_col0\" class=\"data row57 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col1\" class=\"data row57 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col2\" class=\"data row57 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col3\" class=\"data row57 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col4\" class=\"data row57 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col5\" class=\"data row57 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row57_col6\" class=\"data row57 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row58_col0\" class=\"data row58 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
+       "      <td id=\"T_e227c_row58_col2\" class=\"data row58 col2\" >$ 13,480,001,446</td>\n",
+       "      <td id=\"T_e227c_row58_col3\" class=\"data row58 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row58_col4\" class=\"data row58 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row58_col5\" class=\"data row58 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row58_col6\" class=\"data row58 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row59_col0\" class=\"data row59 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
+       "      <td id=\"T_e227c_row59_col2\" class=\"data row59 col2\" >$ 12,765</td>\n",
+       "      <td id=\"T_e227c_row59_col3\" class=\"data row59 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row59_col4\" class=\"data row59 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row59_col5\" class=\"data row59 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row59_col6\" class=\"data row59 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row60_col0\" class=\"data row60 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col1\" class=\"data row60 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col2\" class=\"data row60 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col3\" class=\"data row60 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col4\" class=\"data row60 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col5\" class=\"data row60 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row60_col6\" class=\"data row60 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row61_col0\" class=\"data row61 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
+       "      <td id=\"T_e227c_row61_col2\" class=\"data row61 col2\" >$ 20,558,611,899</td>\n",
+       "      <td id=\"T_e227c_row61_col3\" class=\"data row61 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row61_col4\" class=\"data row61 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row61_col5\" class=\"data row61 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row61_col6\" class=\"data row61 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row62_col0\" class=\"data row62 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
+       "      <td id=\"T_e227c_row62_col2\" class=\"data row62 col2\" >$ 19,468</td>\n",
+       "      <td id=\"T_e227c_row62_col3\" class=\"data row62 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row62_col4\" class=\"data row62 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row62_col5\" class=\"data row62 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row62_col6\" class=\"data row62 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row63_col0\" class=\"data row63 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col1\" class=\"data row63 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col2\" class=\"data row63 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col3\" class=\"data row63 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col4\" class=\"data row63 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col5\" class=\"data row63 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row63_col6\" class=\"data row63 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row64_col0\" class=\"data row64 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
+       "      <td id=\"T_e227c_row64_col2\" class=\"data row64 col2\" >$ 12,806,001,374</td>\n",
+       "      <td id=\"T_e227c_row64_col3\" class=\"data row64 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row64_col4\" class=\"data row64 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row64_col5\" class=\"data row64 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row64_col6\" class=\"data row64 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row65_col0\" class=\"data row65 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_e227c_row65_col2\" class=\"data row65 col2\" >$ 12,127</td>\n",
+       "      <td id=\"T_e227c_row65_col3\" class=\"data row65 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row65_col4\" class=\"data row65 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row65_col5\" class=\"data row65 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row65_col6\" class=\"data row65 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row66_col0\" class=\"data row66 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col1\" class=\"data row66 col1\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col2\" class=\"data row66 col2\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col3\" class=\"data row66 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col4\" class=\"data row66 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col5\" class=\"data row66 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row66_col6\" class=\"data row66 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row67_col0\" class=\"data row67 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
+       "      <td id=\"T_e227c_row67_col2\" class=\"data row67 col2\" >$ 19,884,611,827</td>\n",
+       "      <td id=\"T_e227c_row67_col3\" class=\"data row67 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row67_col4\" class=\"data row67 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row67_col5\" class=\"data row67 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row67_col6\" class=\"data row67 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_e227c_row68_col0\" class=\"data row68 col0\" ></td>\n",
+       "      <td id=\"T_e227c_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_e227c_row68_col2\" class=\"data row68 col2\" >$ 18,830</td>\n",
+       "      <td id=\"T_e227c_row68_col3\" class=\"data row68 col3\" ></td>\n",
+       "      <td id=\"T_e227c_row68_col4\" class=\"data row68 col4\" ></td>\n",
+       "      <td id=\"T_e227c_row68_col5\" class=\"data row68 col5\" ></td>\n",
+       "      <td id=\"T_e227c_row68_col6\" class=\"data row68 col6\" ></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x167058b50>"
+       "<pandas.io.formats.style.Styler at 0x15a624990>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5648,7 +5668,6 @@
     "    Reactor_data_updated_10_ = pd.DataFrame()\n",
     "    Reactor_data_updated_10_ = Reactor_data_updated_10[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\\\n",
     "                    'Site Material Cost']].copy()\n",
-    "    \n",
     "    return Reactor_data_updated_10_ , ITC_reduced_OCC/reactor_power, levelized_NCI \n",
     "\n",
     "\n",
@@ -5656,18 +5675,11 @@
     "\n",
     "\n",
     "# Example\n",
-    "reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "tot_base_cost_results = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0))\n",
-    "tot_base_cost = tot_base_cost_results[0]\n",
-    "final_construction_duration = tot_base_cost_results[1]\n",
+    "reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "tot_base_cost, final_construction_duration  = (calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0))\n",
     "\n",
     "tot_base_cost_wz_insurance = insurance_cost_update(reactor_data, tot_base_cost , reactor_power)\n",
-    "tot_base_cost_wz_insurance_interest_results = (update_interest_cost(tot_base_cost_wz_insurance , final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power))\n",
-    "tot_base_cost_wz_insurance_interest= tot_base_cost_wz_insurance_interest_results[0]\n",
-    "tot_overnight_cost = tot_base_cost_wz_insurance_interest_results[1]\n",
-    "tot_cap_investment= tot_base_cost_wz_insurance_interest_results[2]\n",
-    "\n",
+    "tot_base_cost_wz_insurance_interest, tot_overnight_cost, tot_cap_investment = update_interest_cost(tot_base_cost_wz_insurance , final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power)\n",
     "\n",
     "\n",
     "Final_Result = update_itc(tot_base_cost_wz_insurance_interest, tot_overnight_cost, tot_cap_investment, n_th, ITC_0, n_ITC, reactor_power)\n",
@@ -5679,6 +5691,14 @@
     "Final_Result_pretty"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "331d4f39",
+   "metadata": {},
+   "source": [
+    "## Section 4 :  The Final Result"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8c3ac763",
@@ -5689,38 +5709,770 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "id": "eb42caa1",
    "metadata": {},
    "outputs": [],
    "source": [
     "def calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
-    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0): \n",
+    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0,\\\n",
+    "        interest_rate_0, startup_0, ITC_0, n_ITC): \n",
     "\n",
-    "    reactor_data = (reactor_data_read(reactor_type ))[0]\n",
-    "    reactor_power = (reactor_data_read(reactor_type ))[1]\n",
-    "    tot_base_cost_results = calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0)\n",
-    "    tot_base_cost = tot_base_cost_results[0]\n",
-    "    final_construction_duration = tot_base_cost_results[1]\n",
+    "    reactor_data, reactor_power = (reactor_data_read(reactor_type ))\n",
+    "    tot_base_cost , final_construction_duration= calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0,\\\n",
+    "        N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0)\n",
+    " \n",
     "\n",
     "    tot_base_cost_wz_insurance = insurance_cost_update(reactor_data, tot_base_cost , reactor_power)\n",
-    "    tot_base_cost_wz_insurance_interest_results = (update_interest_cost(tot_base_cost_wz_insurance , final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power))\n",
-    "    tot_base_cost_wz_insurance_interest= tot_base_cost_wz_insurance_interest_results[0]\n",
-    "    tot_overnight_cost = tot_base_cost_wz_insurance_interest_results[1]\n",
-    "    tot_cap_investment= tot_base_cost_wz_insurance_interest_results[2]\n",
+    "    tot_base_cost_wz_insurance_interest, tot_overnight_cost, tot_cap_investment = update_interest_cost(tot_base_cost_wz_insurance , final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power)\n",
+    "\n",
     "\n",
     "    Final_Result = update_itc(tot_base_cost_wz_insurance_interest, tot_overnight_cost, tot_cap_investment, n_th, ITC_0, n_ITC, reactor_power)\n",
-    "    Final_Result_COA = Final_Result[0]\n",
-    "    levelized_net_OCC = Final_Result[1]\n",
-    "    levelized_NCI = Final_Result[2]\n",
-    "    \n",
-    "    return Final_Result_COA, levelized_net_OCC, levelized_NCI, final_construction_duration "
+    "    Final_Result_COA, levelized_net_OCC, levelized_NCI = Final_Result\n",
+    "\n",
+    "    return Final_Result_COA, levelized_net_OCC, levelized_NCI, final_construction_duration[0] \n",
+    "\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4298e941",
+   "metadata": {},
+   "source": [
+    "#### Examples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "a310b9e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style type=\"text/css\">\n",
+       "#T_76074 caption {\n",
+       "  color: red;\n",
+       "  font-size: 20px;\n",
+       "}\n",
+       "#T_76074_row0_col0, #T_76074_row0_col1, #T_76074_row0_col2, #T_76074_row0_col3, #T_76074_row0_col4, #T_76074_row0_col5, #T_76074_row0_col6, #T_76074_row12_col0, #T_76074_row12_col1, #T_76074_row12_col2, #T_76074_row12_col3, #T_76074_row12_col4, #T_76074_row12_col5, #T_76074_row12_col6, #T_76074_row29_col0, #T_76074_row29_col1, #T_76074_row29_col2, #T_76074_row29_col3, #T_76074_row29_col4, #T_76074_row29_col5, #T_76074_row29_col6, #T_76074_row39_col0, #T_76074_row39_col1, #T_76074_row39_col2, #T_76074_row39_col3, #T_76074_row39_col4, #T_76074_row39_col5, #T_76074_row39_col6, #T_76074_row47_col0, #T_76074_row47_col1, #T_76074_row47_col2, #T_76074_row47_col3, #T_76074_row47_col4, #T_76074_row47_col5, #T_76074_row47_col6, #T_76074_row54_col0, #T_76074_row54_col1, #T_76074_row54_col2, #T_76074_row54_col3, #T_76074_row54_col4, #T_76074_row54_col5, #T_76074_row54_col6, #T_76074_row55_col0, #T_76074_row55_col1, #T_76074_row55_col2, #T_76074_row55_col3, #T_76074_row55_col4, #T_76074_row55_col5, #T_76074_row55_col6, #T_76074_row56_col0, #T_76074_row56_col1, #T_76074_row56_col2, #T_76074_row56_col3, #T_76074_row56_col4, #T_76074_row56_col5, #T_76074_row56_col6, #T_76074_row57_col0, #T_76074_row57_col1, #T_76074_row57_col2, #T_76074_row57_col3, #T_76074_row57_col4, #T_76074_row57_col5, #T_76074_row57_col6, #T_76074_row58_col0, #T_76074_row58_col1, #T_76074_row58_col2, #T_76074_row58_col3, #T_76074_row58_col4, #T_76074_row58_col5, #T_76074_row58_col6, #T_76074_row59_col0, #T_76074_row59_col1, #T_76074_row59_col2, #T_76074_row59_col3, #T_76074_row59_col4, #T_76074_row59_col5, #T_76074_row59_col6, #T_76074_row60_col0, #T_76074_row60_col1, #T_76074_row60_col2, #T_76074_row60_col3, #T_76074_row60_col4, #T_76074_row60_col5, #T_76074_row60_col6, #T_76074_row61_col0, #T_76074_row61_col1, #T_76074_row61_col2, #T_76074_row61_col3, #T_76074_row61_col4, #T_76074_row61_col5, #T_76074_row61_col6, #T_76074_row62_col0, #T_76074_row62_col1, #T_76074_row62_col2, #T_76074_row62_col3, #T_76074_row62_col4, #T_76074_row62_col5, #T_76074_row62_col6, #T_76074_row63_col0, #T_76074_row63_col1, #T_76074_row63_col2, #T_76074_row63_col3, #T_76074_row63_col4, #T_76074_row63_col5, #T_76074_row63_col6, #T_76074_row64_col0, #T_76074_row64_col1, #T_76074_row64_col2, #T_76074_row64_col3, #T_76074_row64_col4, #T_76074_row64_col5, #T_76074_row64_col6, #T_76074_row65_col0, #T_76074_row65_col1, #T_76074_row65_col2, #T_76074_row65_col3, #T_76074_row65_col4, #T_76074_row65_col5, #T_76074_row65_col6, #T_76074_row66_col0, #T_76074_row66_col1, #T_76074_row66_col2, #T_76074_row66_col3, #T_76074_row66_col4, #T_76074_row66_col5, #T_76074_row66_col6, #T_76074_row67_col0, #T_76074_row67_col1, #T_76074_row67_col2, #T_76074_row67_col3, #T_76074_row67_col4, #T_76074_row67_col5, #T_76074_row67_col6, #T_76074_row68_col0, #T_76074_row68_col1, #T_76074_row68_col2, #T_76074_row68_col3, #T_76074_row68_col4, #T_76074_row68_col5, #T_76074_row68_col6 {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "</style>\n",
+       "<table id=\"T_76074\">\n",
+       "  <caption> The Concept A 1056.0 MWe Reactor (1th of a kind) <br> Capital Cost Summary  <br><br> </caption>\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th id=\"T_76074_level0_col0\" class=\"col_heading level0 col0\" >Account</th>\n",
+       "      <th id=\"T_76074_level0_col1\" class=\"col_heading level0 col1\" >Title</th>\n",
+       "      <th id=\"T_76074_level0_col2\" class=\"col_heading level0 col2\" >Total Cost (USD)</th>\n",
+       "      <th id=\"T_76074_level0_col3\" class=\"col_heading level0 col3\" >Factory Equipment Cost</th>\n",
+       "      <th id=\"T_76074_level0_col4\" class=\"col_heading level0 col4\" >Site Labor Hours</th>\n",
+       "      <th id=\"T_76074_level0_col5\" class=\"col_heading level0 col5\" >Site Labor Cost</th>\n",
+       "      <th id=\"T_76074_level0_col6\" class=\"col_heading level0 col6\" >Site Material Cost</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row0_col0\" class=\"data row0 col0\" >10</td>\n",
+       "      <td id=\"T_76074_row0_col1\" class=\"data row0 col1\" >Capitalized Pre-Construction Costs</td>\n",
+       "      <td id=\"T_76074_row0_col2\" class=\"data row0 col2\" ></td>\n",
+       "      <td id=\"T_76074_row0_col3\" class=\"data row0 col3\" ></td>\n",
+       "      <td id=\"T_76074_row0_col4\" class=\"data row0 col4\" ></td>\n",
+       "      <td id=\"T_76074_row0_col5\" class=\"data row0 col5\" ></td>\n",
+       "      <td id=\"T_76074_row0_col6\" class=\"data row0 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row1_col0\" class=\"data row1 col0\" >11</td>\n",
+       "      <td id=\"T_76074_row1_col1\" class=\"data row1 col1\" >Land & Land Rights</td>\n",
+       "      <td id=\"T_76074_row1_col2\" class=\"data row1 col2\" >$ 15,000,000</td>\n",
+       "      <td id=\"T_76074_row1_col3\" class=\"data row1 col3\" ></td>\n",
+       "      <td id=\"T_76074_row1_col4\" class=\"data row1 col4\" ></td>\n",
+       "      <td id=\"T_76074_row1_col5\" class=\"data row1 col5\" ></td>\n",
+       "      <td id=\"T_76074_row1_col6\" class=\"data row1 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row2_col0\" class=\"data row2 col0\" >12</td>\n",
+       "      <td id=\"T_76074_row2_col1\" class=\"data row2 col1\" >Site Permits</td>\n",
+       "      <td id=\"T_76074_row2_col2\" class=\"data row2 col2\" >$ 0</td>\n",
+       "      <td id=\"T_76074_row2_col3\" class=\"data row2 col3\" ></td>\n",
+       "      <td id=\"T_76074_row2_col4\" class=\"data row2 col4\" ></td>\n",
+       "      <td id=\"T_76074_row2_col5\" class=\"data row2 col5\" ></td>\n",
+       "      <td id=\"T_76074_row2_col6\" class=\"data row2 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row3_col0\" class=\"data row3 col0\" >13</td>\n",
+       "      <td id=\"T_76074_row3_col1\" class=\"data row3 col1\" >Plant Licensing</td>\n",
+       "      <td id=\"T_76074_row3_col2\" class=\"data row3 col2\" >$ 107,009,772</td>\n",
+       "      <td id=\"T_76074_row3_col3\" class=\"data row3 col3\" ></td>\n",
+       "      <td id=\"T_76074_row3_col4\" class=\"data row3 col4\" ></td>\n",
+       "      <td id=\"T_76074_row3_col5\" class=\"data row3 col5\" ></td>\n",
+       "      <td id=\"T_76074_row3_col6\" class=\"data row3 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row4_col0\" class=\"data row4 col0\" >14</td>\n",
+       "      <td id=\"T_76074_row4_col1\" class=\"data row4 col1\" >Plant Permits</td>\n",
+       "      <td id=\"T_76074_row4_col2\" class=\"data row4 col2\" >$ 4,721,019</td>\n",
+       "      <td id=\"T_76074_row4_col3\" class=\"data row4 col3\" ></td>\n",
+       "      <td id=\"T_76074_row4_col4\" class=\"data row4 col4\" ></td>\n",
+       "      <td id=\"T_76074_row4_col5\" class=\"data row4 col5\" ></td>\n",
+       "      <td id=\"T_76074_row4_col6\" class=\"data row4 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row5_col0\" class=\"data row5 col0\" >15</td>\n",
+       "      <td id=\"T_76074_row5_col1\" class=\"data row5 col1\" >Plant Studies</td>\n",
+       "      <td id=\"T_76074_row5_col2\" class=\"data row5 col2\" >$ 0</td>\n",
+       "      <td id=\"T_76074_row5_col3\" class=\"data row5 col3\" ></td>\n",
+       "      <td id=\"T_76074_row5_col4\" class=\"data row5 col4\" ></td>\n",
+       "      <td id=\"T_76074_row5_col5\" class=\"data row5 col5\" ></td>\n",
+       "      <td id=\"T_76074_row5_col6\" class=\"data row5 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row6_col0\" class=\"data row6 col0\" >16</td>\n",
+       "      <td id=\"T_76074_row6_col1\" class=\"data row6 col1\" >Plant Reports</td>\n",
+       "      <td id=\"T_76074_row6_col2\" class=\"data row6 col2\" >$ 0</td>\n",
+       "      <td id=\"T_76074_row6_col3\" class=\"data row6 col3\" ></td>\n",
+       "      <td id=\"T_76074_row6_col4\" class=\"data row6 col4\" ></td>\n",
+       "      <td id=\"T_76074_row6_col5\" class=\"data row6 col5\" ></td>\n",
+       "      <td id=\"T_76074_row6_col6\" class=\"data row6 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row7_col0\" class=\"data row7 col0\" >18</td>\n",
+       "      <td id=\"T_76074_row7_col1\" class=\"data row7 col1\" >Other Pre-Construction Costs</td>\n",
+       "      <td id=\"T_76074_row7_col2\" class=\"data row7 col2\" >$ 36,194,482</td>\n",
+       "      <td id=\"T_76074_row7_col3\" class=\"data row7 col3\" ></td>\n",
+       "      <td id=\"T_76074_row7_col4\" class=\"data row7 col4\" ></td>\n",
+       "      <td id=\"T_76074_row7_col5\" class=\"data row7 col5\" ></td>\n",
+       "      <td id=\"T_76074_row7_col6\" class=\"data row7 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row8_col0\" class=\"data row8 col0\" ></td>\n",
+       "      <td id=\"T_76074_row8_col1\" class=\"data row8 col1\" ></td>\n",
+       "      <td id=\"T_76074_row8_col2\" class=\"data row8 col2\" ></td>\n",
+       "      <td id=\"T_76074_row8_col3\" class=\"data row8 col3\" ></td>\n",
+       "      <td id=\"T_76074_row8_col4\" class=\"data row8 col4\" ></td>\n",
+       "      <td id=\"T_76074_row8_col5\" class=\"data row8 col5\" ></td>\n",
+       "      <td id=\"T_76074_row8_col6\" class=\"data row8 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row9_col0\" class=\"data row9 col0\" ></td>\n",
+       "      <td id=\"T_76074_row9_col1\" class=\"data row9 col1\" >10s - Subtotal</td>\n",
+       "      <td id=\"T_76074_row9_col2\" class=\"data row9 col2\" >$ 162,925,273</td>\n",
+       "      <td id=\"T_76074_row9_col3\" class=\"data row9 col3\" ></td>\n",
+       "      <td id=\"T_76074_row9_col4\" class=\"data row9 col4\" ></td>\n",
+       "      <td id=\"T_76074_row9_col5\" class=\"data row9 col5\" ></td>\n",
+       "      <td id=\"T_76074_row9_col6\" class=\"data row9 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row10_col0\" class=\"data row10 col0\" ></td>\n",
+       "      <td id=\"T_76074_row10_col1\" class=\"data row10 col1\" >10s - $/kWe</td>\n",
+       "      <td id=\"T_76074_row10_col2\" class=\"data row10 col2\" >$ 154</td>\n",
+       "      <td id=\"T_76074_row10_col3\" class=\"data row10 col3\" ></td>\n",
+       "      <td id=\"T_76074_row10_col4\" class=\"data row10 col4\" ></td>\n",
+       "      <td id=\"T_76074_row10_col5\" class=\"data row10 col5\" ></td>\n",
+       "      <td id=\"T_76074_row10_col6\" class=\"data row10 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row11_col0\" class=\"data row11 col0\" ></td>\n",
+       "      <td id=\"T_76074_row11_col1\" class=\"data row11 col1\" ></td>\n",
+       "      <td id=\"T_76074_row11_col2\" class=\"data row11 col2\" ></td>\n",
+       "      <td id=\"T_76074_row11_col3\" class=\"data row11 col3\" ></td>\n",
+       "      <td id=\"T_76074_row11_col4\" class=\"data row11 col4\" ></td>\n",
+       "      <td id=\"T_76074_row11_col5\" class=\"data row11 col5\" ></td>\n",
+       "      <td id=\"T_76074_row11_col6\" class=\"data row11 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row12_col0\" class=\"data row12 col0\" >20</td>\n",
+       "      <td id=\"T_76074_row12_col1\" class=\"data row12 col1\" >Capitalized Direct Costs</td>\n",
+       "      <td id=\"T_76074_row12_col2\" class=\"data row12 col2\" ></td>\n",
+       "      <td id=\"T_76074_row12_col3\" class=\"data row12 col3\" ></td>\n",
+       "      <td id=\"T_76074_row12_col4\" class=\"data row12 col4\" ></td>\n",
+       "      <td id=\"T_76074_row12_col5\" class=\"data row12 col5\" ></td>\n",
+       "      <td id=\"T_76074_row12_col6\" class=\"data row12 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row13_col0\" class=\"data row13 col0\" >21</td>\n",
+       "      <td id=\"T_76074_row13_col1\" class=\"data row13 col1\" >Structures & Improvements</td>\n",
+       "      <td id=\"T_76074_row13_col2\" class=\"data row13 col2\" >$ 1,533,300,048</td>\n",
+       "      <td id=\"T_76074_row13_col3\" class=\"data row13 col3\" >$ 136,536,219</td>\n",
+       "      <td id=\"T_76074_row13_col4\" class=\"data row13 col4\" >20,909,198 hrs</td>\n",
+       "      <td id=\"T_76074_row13_col5\" class=\"data row13 col5\" >$ 1,045,892,208</td>\n",
+       "      <td id=\"T_76074_row13_col6\" class=\"data row13 col6\" >$ 350,871,621</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row14_col0\" class=\"data row14 col0\" >212</td>\n",
+       "      <td id=\"T_76074_row14_col1\" class=\"data row14 col1\" >Reactor Containment Building</td>\n",
+       "      <td id=\"T_76074_row14_col2\" class=\"data row14 col2\" >$ 696,644,770</td>\n",
+       "      <td id=\"T_76074_row14_col3\" class=\"data row14 col3\" >$ 99,927,411</td>\n",
+       "      <td id=\"T_76074_row14_col4\" class=\"data row14 col4\" >9,638,431 hrs</td>\n",
+       "      <td id=\"T_76074_row14_col5\" class=\"data row14 col5\" >$ 470,061,974</td>\n",
+       "      <td id=\"T_76074_row14_col6\" class=\"data row14 col6\" >$ 126,655,384</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row15_col0\" class=\"data row15 col0\" >213</td>\n",
+       "      <td id=\"T_76074_row15_col1\" class=\"data row15 col1\" >Turbine Room and Heater Bay</td>\n",
+       "      <td id=\"T_76074_row15_col2\" class=\"data row15 col2\" >$ 15,225,731</td>\n",
+       "      <td id=\"T_76074_row15_col3\" class=\"data row15 col3\" >$ 1,036,695</td>\n",
+       "      <td id=\"T_76074_row15_col4\" class=\"data row15 col4\" >174,911 hrs</td>\n",
+       "      <td id=\"T_76074_row15_col5\" class=\"data row15 col5\" >$ 9,024,686</td>\n",
+       "      <td id=\"T_76074_row15_col6\" class=\"data row15 col6\" >$ 5,164,350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row16_col0\" class=\"data row16 col0\" >211 plus 214 to 219</td>\n",
+       "      <td id=\"T_76074_row16_col1\" class=\"data row16 col1\" >Othe Structures & Improvements</td>\n",
+       "      <td id=\"T_76074_row16_col2\" class=\"data row16 col2\" >$ 821,429,547</td>\n",
+       "      <td id=\"T_76074_row16_col3\" class=\"data row16 col3\" >$ 35,572,113</td>\n",
+       "      <td id=\"T_76074_row16_col4\" class=\"data row16 col4\" >11,095,856 hrs</td>\n",
+       "      <td id=\"T_76074_row16_col5\" class=\"data row16 col5\" >$ 566,805,548</td>\n",
+       "      <td id=\"T_76074_row16_col6\" class=\"data row16 col6\" >$ 219,051,887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row17_col0\" class=\"data row17 col0\" >22</td>\n",
+       "      <td id=\"T_76074_row17_col1\" class=\"data row17 col1\" >Reactor System</td>\n",
+       "      <td id=\"T_76074_row17_col2\" class=\"data row17 col2\" >$ 1,975,878,221</td>\n",
+       "      <td id=\"T_76074_row17_col3\" class=\"data row17 col3\" >$ 1,478,440,482</td>\n",
+       "      <td id=\"T_76074_row17_col4\" class=\"data row17 col4\" >8,719,725 hrs</td>\n",
+       "      <td id=\"T_76074_row17_col5\" class=\"data row17 col5\" >$ 465,667,671</td>\n",
+       "      <td id=\"T_76074_row17_col6\" class=\"data row17 col6\" >$ 31,770,067</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row18_col0\" class=\"data row18 col0\" >23</td>\n",
+       "      <td id=\"T_76074_row18_col1\" class=\"data row18 col1\" >Energy Conversion System</td>\n",
+       "      <td id=\"T_76074_row18_col2\" class=\"data row18 col2\" >$ 475,506,379</td>\n",
+       "      <td id=\"T_76074_row18_col3\" class=\"data row18 col3\" >$ 307,232,636</td>\n",
+       "      <td id=\"T_76074_row18_col4\" class=\"data row18 col4\" >3,008,178 hrs</td>\n",
+       "      <td id=\"T_76074_row18_col5\" class=\"data row18 col5\" >$ 159,414,434</td>\n",
+       "      <td id=\"T_76074_row18_col6\" class=\"data row18 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row19_col0\" class=\"data row19 col0\" >232.1</td>\n",
+       "      <td id=\"T_76074_row19_col1\" class=\"data row19 col1\" >Electricity Generation Systems</td>\n",
+       "      <td id=\"T_76074_row19_col2\" class=\"data row19 col2\" >$ 330,105,050</td>\n",
+       "      <td id=\"T_76074_row19_col3\" class=\"data row19 col3\" >$ 234,488,390</td>\n",
+       "      <td id=\"T_76074_row19_col4\" class=\"data row19 col4\" >1,794,686 hrs</td>\n",
+       "      <td id=\"T_76074_row19_col5\" class=\"data row19 col5\" >$ 95,616,660</td>\n",
+       "      <td id=\"T_76074_row19_col6\" class=\"data row19 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row20_col0\" class=\"data row20 col0\" >233</td>\n",
+       "      <td id=\"T_76074_row20_col1\" class=\"data row20 col1\" >Ultimate Heat Sink</td>\n",
+       "      <td id=\"T_76074_row20_col2\" class=\"data row20 col2\" >$ 145,401,329</td>\n",
+       "      <td id=\"T_76074_row20_col3\" class=\"data row20 col3\" >$ 72,744,246</td>\n",
+       "      <td id=\"T_76074_row20_col4\" class=\"data row20 col4\" >1,213,492 hrs</td>\n",
+       "      <td id=\"T_76074_row20_col5\" class=\"data row20 col5\" >$ 63,797,774</td>\n",
+       "      <td id=\"T_76074_row20_col6\" class=\"data row20 col6\" >$ 8,859,309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row21_col0\" class=\"data row21 col0\" >24</td>\n",
+       "      <td id=\"T_76074_row21_col1\" class=\"data row21 col1\" >Electrical Equipment</td>\n",
+       "      <td id=\"T_76074_row21_col2\" class=\"data row21 col2\" >$ 235,820,328</td>\n",
+       "      <td id=\"T_76074_row21_col3\" class=\"data row21 col3\" >$ 43,269,546</td>\n",
+       "      <td id=\"T_76074_row21_col4\" class=\"data row21 col4\" >2,841,261 hrs</td>\n",
+       "      <td id=\"T_76074_row21_col5\" class=\"data row21 col5\" >$ 153,143,767</td>\n",
+       "      <td id=\"T_76074_row21_col6\" class=\"data row21 col6\" >$ 39,407,016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row22_col0\" class=\"data row22 col0\" >25</td>\n",
+       "      <td id=\"T_76074_row22_col1\" class=\"data row22 col1\" >Initial fuel inventory</td>\n",
+       "      <td id=\"T_76074_row22_col2\" class=\"data row22 col2\" >$ 451,686,471</td>\n",
+       "      <td id=\"T_76074_row22_col3\" class=\"data row22 col3\" ></td>\n",
+       "      <td id=\"T_76074_row22_col4\" class=\"data row22 col4\" >0 hrs</td>\n",
+       "      <td id=\"T_76074_row22_col5\" class=\"data row22 col5\" >$ 0</td>\n",
+       "      <td id=\"T_76074_row22_col6\" class=\"data row22 col6\" >$ 0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row23_col0\" class=\"data row23 col0\" >26</td>\n",
+       "      <td id=\"T_76074_row23_col1\" class=\"data row23 col1\" >Miscellaneous Equipment</td>\n",
+       "      <td id=\"T_76074_row23_col2\" class=\"data row23 col2\" >$ 359,435,749</td>\n",
+       "      <td id=\"T_76074_row23_col3\" class=\"data row23 col3\" >$ 99,429,457</td>\n",
+       "      <td id=\"T_76074_row23_col4\" class=\"data row23 col4\" >4,282,531 hrs</td>\n",
+       "      <td id=\"T_76074_row23_col5\" class=\"data row23 col5\" >$ 231,045,490</td>\n",
+       "      <td id=\"T_76074_row23_col6\" class=\"data row23 col6\" >$ 28,960,802</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row24_col0\" class=\"data row24 col0\" >28</td>\n",
+       "      <td id=\"T_76074_row24_col1\" class=\"data row24 col1\" >Simulator</td>\n",
+       "      <td id=\"T_76074_row24_col2\" class=\"data row24 col2\" >$ 0</td>\n",
+       "      <td id=\"T_76074_row24_col3\" class=\"data row24 col3\" ></td>\n",
+       "      <td id=\"T_76074_row24_col4\" class=\"data row24 col4\" ></td>\n",
+       "      <td id=\"T_76074_row24_col5\" class=\"data row24 col5\" ></td>\n",
+       "      <td id=\"T_76074_row24_col6\" class=\"data row24 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row25_col0\" class=\"data row25 col0\" ></td>\n",
+       "      <td id=\"T_76074_row25_col1\" class=\"data row25 col1\" ></td>\n",
+       "      <td id=\"T_76074_row25_col2\" class=\"data row25 col2\" ></td>\n",
+       "      <td id=\"T_76074_row25_col3\" class=\"data row25 col3\" ></td>\n",
+       "      <td id=\"T_76074_row25_col4\" class=\"data row25 col4\" ></td>\n",
+       "      <td id=\"T_76074_row25_col5\" class=\"data row25 col5\" ></td>\n",
+       "      <td id=\"T_76074_row25_col6\" class=\"data row25 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row26_col0\" class=\"data row26 col0\" ></td>\n",
+       "      <td id=\"T_76074_row26_col1\" class=\"data row26 col1\" >20s - Subtotal</td>\n",
+       "      <td id=\"T_76074_row26_col2\" class=\"data row26 col2\" >$ 5,031,627,196</td>\n",
+       "      <td id=\"T_76074_row26_col3\" class=\"data row26 col3\" ></td>\n",
+       "      <td id=\"T_76074_row26_col4\" class=\"data row26 col4\" ></td>\n",
+       "      <td id=\"T_76074_row26_col5\" class=\"data row26 col5\" ></td>\n",
+       "      <td id=\"T_76074_row26_col6\" class=\"data row26 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row27_col0\" class=\"data row27 col0\" ></td>\n",
+       "      <td id=\"T_76074_row27_col1\" class=\"data row27 col1\" >20s - $/kWe</td>\n",
+       "      <td id=\"T_76074_row27_col2\" class=\"data row27 col2\" >$ 4,765</td>\n",
+       "      <td id=\"T_76074_row27_col3\" class=\"data row27 col3\" ></td>\n",
+       "      <td id=\"T_76074_row27_col4\" class=\"data row27 col4\" ></td>\n",
+       "      <td id=\"T_76074_row27_col5\" class=\"data row27 col5\" ></td>\n",
+       "      <td id=\"T_76074_row27_col6\" class=\"data row27 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row28_col0\" class=\"data row28 col0\" ></td>\n",
+       "      <td id=\"T_76074_row28_col1\" class=\"data row28 col1\" ></td>\n",
+       "      <td id=\"T_76074_row28_col2\" class=\"data row28 col2\" ></td>\n",
+       "      <td id=\"T_76074_row28_col3\" class=\"data row28 col3\" ></td>\n",
+       "      <td id=\"T_76074_row28_col4\" class=\"data row28 col4\" ></td>\n",
+       "      <td id=\"T_76074_row28_col5\" class=\"data row28 col5\" ></td>\n",
+       "      <td id=\"T_76074_row28_col6\" class=\"data row28 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row29_col0\" class=\"data row29 col0\" >30</td>\n",
+       "      <td id=\"T_76074_row29_col1\" class=\"data row29 col1\" >Capitalized Indirect Services Costs</td>\n",
+       "      <td id=\"T_76074_row29_col2\" class=\"data row29 col2\" ></td>\n",
+       "      <td id=\"T_76074_row29_col3\" class=\"data row29 col3\" ></td>\n",
+       "      <td id=\"T_76074_row29_col4\" class=\"data row29 col4\" ></td>\n",
+       "      <td id=\"T_76074_row29_col5\" class=\"data row29 col5\" ></td>\n",
+       "      <td id=\"T_76074_row29_col6\" class=\"data row29 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row30_col0\" class=\"data row30 col0\" >31</td>\n",
+       "      <td id=\"T_76074_row30_col1\" class=\"data row30 col1\" >Factory & Field Indirect Costs</td>\n",
+       "      <td id=\"T_76074_row30_col2\" class=\"data row30 col2\" >$ 1,351,122,731</td>\n",
+       "      <td id=\"T_76074_row30_col3\" class=\"data row30 col3\" ></td>\n",
+       "      <td id=\"T_76074_row30_col4\" class=\"data row30 col4\" ></td>\n",
+       "      <td id=\"T_76074_row30_col5\" class=\"data row30 col5\" ></td>\n",
+       "      <td id=\"T_76074_row30_col6\" class=\"data row30 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row31_col0\" class=\"data row31 col0\" >32</td>\n",
+       "      <td id=\"T_76074_row31_col1\" class=\"data row31 col1\" >Factory and construction supervision</td>\n",
+       "      <td id=\"T_76074_row31_col2\" class=\"data row31 col2\" >$ 5,218,449,814</td>\n",
+       "      <td id=\"T_76074_row31_col3\" class=\"data row31 col3\" ></td>\n",
+       "      <td id=\"T_76074_row31_col4\" class=\"data row31 col4\" ></td>\n",
+       "      <td id=\"T_76074_row31_col5\" class=\"data row31 col5\" ></td>\n",
+       "      <td id=\"T_76074_row31_col6\" class=\"data row31 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row32_col0\" class=\"data row32 col0\" >33</td>\n",
+       "      <td id=\"T_76074_row32_col1\" class=\"data row32 col1\" >Start-Up Costs</td>\n",
+       "      <td id=\"T_76074_row32_col2\" class=\"data row32 col2\" >$ 219,540,497</td>\n",
+       "      <td id=\"T_76074_row32_col3\" class=\"data row32 col3\" ></td>\n",
+       "      <td id=\"T_76074_row32_col4\" class=\"data row32 col4\" ></td>\n",
+       "      <td id=\"T_76074_row32_col5\" class=\"data row32 col5\" ></td>\n",
+       "      <td id=\"T_76074_row32_col6\" class=\"data row32 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row33_col0\" class=\"data row33 col0\" >34</td>\n",
+       "      <td id=\"T_76074_row33_col1\" class=\"data row33 col1\" >Shipping & Transportation Costs</td>\n",
+       "      <td id=\"T_76074_row33_col2\" class=\"data row33 col2\" >$ 18,485,556</td>\n",
+       "      <td id=\"T_76074_row33_col3\" class=\"data row33 col3\" ></td>\n",
+       "      <td id=\"T_76074_row33_col4\" class=\"data row33 col4\" ></td>\n",
+       "      <td id=\"T_76074_row33_col5\" class=\"data row33 col5\" ></td>\n",
+       "      <td id=\"T_76074_row33_col6\" class=\"data row33 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row34_col0\" class=\"data row34 col0\" >35</td>\n",
+       "      <td id=\"T_76074_row34_col1\" class=\"data row34 col1\" >Engineering Services</td>\n",
+       "      <td id=\"T_76074_row34_col2\" class=\"data row34 col2\" >$ 1,409,900,054</td>\n",
+       "      <td id=\"T_76074_row34_col3\" class=\"data row34 col3\" ></td>\n",
+       "      <td id=\"T_76074_row34_col4\" class=\"data row34 col4\" ></td>\n",
+       "      <td id=\"T_76074_row34_col5\" class=\"data row34 col5\" ></td>\n",
+       "      <td id=\"T_76074_row34_col6\" class=\"data row34 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row35_col0\" class=\"data row35 col0\" ></td>\n",
+       "      <td id=\"T_76074_row35_col1\" class=\"data row35 col1\" ></td>\n",
+       "      <td id=\"T_76074_row35_col2\" class=\"data row35 col2\" ></td>\n",
+       "      <td id=\"T_76074_row35_col3\" class=\"data row35 col3\" ></td>\n",
+       "      <td id=\"T_76074_row35_col4\" class=\"data row35 col4\" ></td>\n",
+       "      <td id=\"T_76074_row35_col5\" class=\"data row35 col5\" ></td>\n",
+       "      <td id=\"T_76074_row35_col6\" class=\"data row35 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row36_col0\" class=\"data row36 col0\" ></td>\n",
+       "      <td id=\"T_76074_row36_col1\" class=\"data row36 col1\" >30s - Subtotal</td>\n",
+       "      <td id=\"T_76074_row36_col2\" class=\"data row36 col2\" >$ 8,217,498,651</td>\n",
+       "      <td id=\"T_76074_row36_col3\" class=\"data row36 col3\" ></td>\n",
+       "      <td id=\"T_76074_row36_col4\" class=\"data row36 col4\" ></td>\n",
+       "      <td id=\"T_76074_row36_col5\" class=\"data row36 col5\" ></td>\n",
+       "      <td id=\"T_76074_row36_col6\" class=\"data row36 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row37_col0\" class=\"data row37 col0\" ></td>\n",
+       "      <td id=\"T_76074_row37_col1\" class=\"data row37 col1\" >30s - $/kWe</td>\n",
+       "      <td id=\"T_76074_row37_col2\" class=\"data row37 col2\" >$ 7,782</td>\n",
+       "      <td id=\"T_76074_row37_col3\" class=\"data row37 col3\" ></td>\n",
+       "      <td id=\"T_76074_row37_col4\" class=\"data row37 col4\" ></td>\n",
+       "      <td id=\"T_76074_row37_col5\" class=\"data row37 col5\" ></td>\n",
+       "      <td id=\"T_76074_row37_col6\" class=\"data row37 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row38_col0\" class=\"data row38 col0\" ></td>\n",
+       "      <td id=\"T_76074_row38_col1\" class=\"data row38 col1\" ></td>\n",
+       "      <td id=\"T_76074_row38_col2\" class=\"data row38 col2\" ></td>\n",
+       "      <td id=\"T_76074_row38_col3\" class=\"data row38 col3\" ></td>\n",
+       "      <td id=\"T_76074_row38_col4\" class=\"data row38 col4\" ></td>\n",
+       "      <td id=\"T_76074_row38_col5\" class=\"data row38 col5\" ></td>\n",
+       "      <td id=\"T_76074_row38_col6\" class=\"data row38 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row39_col0\" class=\"data row39 col0\" >50</td>\n",
+       "      <td id=\"T_76074_row39_col1\" class=\"data row39 col1\" >Capitalized Supplementary Costs</td>\n",
+       "      <td id=\"T_76074_row39_col2\" class=\"data row39 col2\" ></td>\n",
+       "      <td id=\"T_76074_row39_col3\" class=\"data row39 col3\" ></td>\n",
+       "      <td id=\"T_76074_row39_col4\" class=\"data row39 col4\" ></td>\n",
+       "      <td id=\"T_76074_row39_col5\" class=\"data row39 col5\" ></td>\n",
+       "      <td id=\"T_76074_row39_col6\" class=\"data row39 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row40_col0\" class=\"data row40 col0\" >51</td>\n",
+       "      <td id=\"T_76074_row40_col1\" class=\"data row40 col1\" >Taxes</td>\n",
+       "      <td id=\"T_76074_row40_col2\" class=\"data row40 col2\" >$ 187,500</td>\n",
+       "      <td id=\"T_76074_row40_col3\" class=\"data row40 col3\" ></td>\n",
+       "      <td id=\"T_76074_row40_col4\" class=\"data row40 col4\" ></td>\n",
+       "      <td id=\"T_76074_row40_col5\" class=\"data row40 col5\" ></td>\n",
+       "      <td id=\"T_76074_row40_col6\" class=\"data row40 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row41_col0\" class=\"data row41 col0\" >52</td>\n",
+       "      <td id=\"T_76074_row41_col1\" class=\"data row41 col1\" >Insurance</td>\n",
+       "      <td id=\"T_76074_row41_col2\" class=\"data row41 col2\" >$ 59,621,066</td>\n",
+       "      <td id=\"T_76074_row41_col3\" class=\"data row41 col3\" ></td>\n",
+       "      <td id=\"T_76074_row41_col4\" class=\"data row41 col4\" ></td>\n",
+       "      <td id=\"T_76074_row41_col5\" class=\"data row41 col5\" ></td>\n",
+       "      <td id=\"T_76074_row41_col6\" class=\"data row41 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row42_col0\" class=\"data row42 col0\" >54</td>\n",
+       "      <td id=\"T_76074_row42_col1\" class=\"data row42 col1\" >Decommissioning </td>\n",
+       "      <td id=\"T_76074_row42_col2\" class=\"data row42 col2\" >$ 8,141,760</td>\n",
+       "      <td id=\"T_76074_row42_col3\" class=\"data row42 col3\" ></td>\n",
+       "      <td id=\"T_76074_row42_col4\" class=\"data row42 col4\" ></td>\n",
+       "      <td id=\"T_76074_row42_col5\" class=\"data row42 col5\" ></td>\n",
+       "      <td id=\"T_76074_row42_col6\" class=\"data row42 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row43_col0\" class=\"data row43 col0\" ></td>\n",
+       "      <td id=\"T_76074_row43_col1\" class=\"data row43 col1\" ></td>\n",
+       "      <td id=\"T_76074_row43_col2\" class=\"data row43 col2\" ></td>\n",
+       "      <td id=\"T_76074_row43_col3\" class=\"data row43 col3\" ></td>\n",
+       "      <td id=\"T_76074_row43_col4\" class=\"data row43 col4\" ></td>\n",
+       "      <td id=\"T_76074_row43_col5\" class=\"data row43 col5\" ></td>\n",
+       "      <td id=\"T_76074_row43_col6\" class=\"data row43 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row44_col0\" class=\"data row44 col0\" ></td>\n",
+       "      <td id=\"T_76074_row44_col1\" class=\"data row44 col1\" >50s - Subtotal</td>\n",
+       "      <td id=\"T_76074_row44_col2\" class=\"data row44 col2\" >$ 67,950,326</td>\n",
+       "      <td id=\"T_76074_row44_col3\" class=\"data row44 col3\" ></td>\n",
+       "      <td id=\"T_76074_row44_col4\" class=\"data row44 col4\" ></td>\n",
+       "      <td id=\"T_76074_row44_col5\" class=\"data row44 col5\" ></td>\n",
+       "      <td id=\"T_76074_row44_col6\" class=\"data row44 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row45_col0\" class=\"data row45 col0\" ></td>\n",
+       "      <td id=\"T_76074_row45_col1\" class=\"data row45 col1\" >50s - $/kWe</td>\n",
+       "      <td id=\"T_76074_row45_col2\" class=\"data row45 col2\" >$ 64</td>\n",
+       "      <td id=\"T_76074_row45_col3\" class=\"data row45 col3\" ></td>\n",
+       "      <td id=\"T_76074_row45_col4\" class=\"data row45 col4\" ></td>\n",
+       "      <td id=\"T_76074_row45_col5\" class=\"data row45 col5\" ></td>\n",
+       "      <td id=\"T_76074_row45_col6\" class=\"data row45 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row46_col0\" class=\"data row46 col0\" ></td>\n",
+       "      <td id=\"T_76074_row46_col1\" class=\"data row46 col1\" ></td>\n",
+       "      <td id=\"T_76074_row46_col2\" class=\"data row46 col2\" ></td>\n",
+       "      <td id=\"T_76074_row46_col3\" class=\"data row46 col3\" ></td>\n",
+       "      <td id=\"T_76074_row46_col4\" class=\"data row46 col4\" ></td>\n",
+       "      <td id=\"T_76074_row46_col5\" class=\"data row46 col5\" ></td>\n",
+       "      <td id=\"T_76074_row46_col6\" class=\"data row46 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row47_col0\" class=\"data row47 col0\" >60</td>\n",
+       "      <td id=\"T_76074_row47_col1\" class=\"data row47 col1\" >Capitalized Financial Costs</td>\n",
+       "      <td id=\"T_76074_row47_col2\" class=\"data row47 col2\" ></td>\n",
+       "      <td id=\"T_76074_row47_col3\" class=\"data row47 col3\" ></td>\n",
+       "      <td id=\"T_76074_row47_col4\" class=\"data row47 col4\" ></td>\n",
+       "      <td id=\"T_76074_row47_col5\" class=\"data row47 col5\" ></td>\n",
+       "      <td id=\"T_76074_row47_col6\" class=\"data row47 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row48_col0\" class=\"data row48 col0\" >62</td>\n",
+       "      <td id=\"T_76074_row48_col1\" class=\"data row48 col1\" >Interest </td>\n",
+       "      <td id=\"T_76074_row48_col2\" class=\"data row48 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_76074_row48_col3\" class=\"data row48 col3\" ></td>\n",
+       "      <td id=\"T_76074_row48_col4\" class=\"data row48 col4\" ></td>\n",
+       "      <td id=\"T_76074_row48_col5\" class=\"data row48 col5\" ></td>\n",
+       "      <td id=\"T_76074_row48_col6\" class=\"data row48 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row49_col0\" class=\"data row49 col0\" >-</td>\n",
+       "      <td id=\"T_76074_row49_col1\" class=\"data row49 col1\" >60s - Subtotal</td>\n",
+       "      <td id=\"T_76074_row49_col2\" class=\"data row49 col2\" >$ 7,078,610,453</td>\n",
+       "      <td id=\"T_76074_row49_col3\" class=\"data row49 col3\" ></td>\n",
+       "      <td id=\"T_76074_row49_col4\" class=\"data row49 col4\" ></td>\n",
+       "      <td id=\"T_76074_row49_col5\" class=\"data row49 col5\" ></td>\n",
+       "      <td id=\"T_76074_row49_col6\" class=\"data row49 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row50_col0\" class=\"data row50 col0\" ></td>\n",
+       "      <td id=\"T_76074_row50_col1\" class=\"data row50 col1\" >60s - $/kWe</td>\n",
+       "      <td id=\"T_76074_row50_col2\" class=\"data row50 col2\" >$ 6,703</td>\n",
+       "      <td id=\"T_76074_row50_col3\" class=\"data row50 col3\" ></td>\n",
+       "      <td id=\"T_76074_row50_col4\" class=\"data row50 col4\" ></td>\n",
+       "      <td id=\"T_76074_row50_col5\" class=\"data row50 col5\" ></td>\n",
+       "      <td id=\"T_76074_row50_col6\" class=\"data row50 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row51_col0\" class=\"data row51 col0\" ></td>\n",
+       "      <td id=\"T_76074_row51_col1\" class=\"data row51 col1\" ></td>\n",
+       "      <td id=\"T_76074_row51_col2\" class=\"data row51 col2\" ></td>\n",
+       "      <td id=\"T_76074_row51_col3\" class=\"data row51 col3\" ></td>\n",
+       "      <td id=\"T_76074_row51_col4\" class=\"data row51 col4\" ></td>\n",
+       "      <td id=\"T_76074_row51_col5\" class=\"data row51 col5\" ></td>\n",
+       "      <td id=\"T_76074_row51_col6\" class=\"data row51 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row52_col0\" class=\"data row52 col0\" ></td>\n",
+       "      <td id=\"T_76074_row52_col1\" class=\"data row52 col1\" >Total Direct Capital Cost (Accounts 10 to 20)</td>\n",
+       "      <td id=\"T_76074_row52_col2\" class=\"data row52 col2\" >$ 5,194,552,469</td>\n",
+       "      <td id=\"T_76074_row52_col3\" class=\"data row52 col3\" ></td>\n",
+       "      <td id=\"T_76074_row52_col4\" class=\"data row52 col4\" ></td>\n",
+       "      <td id=\"T_76074_row52_col5\" class=\"data row52 col5\" ></td>\n",
+       "      <td id=\"T_76074_row52_col6\" class=\"data row52 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row53_col0\" class=\"data row53 col0\" ></td>\n",
+       "      <td id=\"T_76074_row53_col1\" class=\"data row53 col1\" >(Accounts 10 to 20) US$/kWe</td>\n",
+       "      <td id=\"T_76074_row53_col2\" class=\"data row53 col2\" >$ 4,919</td>\n",
+       "      <td id=\"T_76074_row53_col3\" class=\"data row53 col3\" ></td>\n",
+       "      <td id=\"T_76074_row53_col4\" class=\"data row53 col4\" ></td>\n",
+       "      <td id=\"T_76074_row53_col5\" class=\"data row53 col5\" ></td>\n",
+       "      <td id=\"T_76074_row53_col6\" class=\"data row53 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row54_col0\" class=\"data row54 col0\" ></td>\n",
+       "      <td id=\"T_76074_row54_col1\" class=\"data row54 col1\" ></td>\n",
+       "      <td id=\"T_76074_row54_col2\" class=\"data row54 col2\" ></td>\n",
+       "      <td id=\"T_76074_row54_col3\" class=\"data row54 col3\" ></td>\n",
+       "      <td id=\"T_76074_row54_col4\" class=\"data row54 col4\" ></td>\n",
+       "      <td id=\"T_76074_row54_col5\" class=\"data row54 col5\" ></td>\n",
+       "      <td id=\"T_76074_row54_col6\" class=\"data row54 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row55_col0\" class=\"data row55 col0\" ></td>\n",
+       "      <td id=\"T_76074_row55_col1\" class=\"data row55 col1\" >Base Construction Cost (Accounts 10 to 30)</td>\n",
+       "      <td id=\"T_76074_row55_col2\" class=\"data row55 col2\" >$ 13,412,051,120</td>\n",
+       "      <td id=\"T_76074_row55_col3\" class=\"data row55 col3\" ></td>\n",
+       "      <td id=\"T_76074_row55_col4\" class=\"data row55 col4\" ></td>\n",
+       "      <td id=\"T_76074_row55_col5\" class=\"data row55 col5\" ></td>\n",
+       "      <td id=\"T_76074_row55_col6\" class=\"data row55 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row56_col0\" class=\"data row56 col0\" ></td>\n",
+       "      <td id=\"T_76074_row56_col1\" class=\"data row56 col1\" >(Accounts 10 to 30) US$/kWe</td>\n",
+       "      <td id=\"T_76074_row56_col2\" class=\"data row56 col2\" >$ 12,701</td>\n",
+       "      <td id=\"T_76074_row56_col3\" class=\"data row56 col3\" ></td>\n",
+       "      <td id=\"T_76074_row56_col4\" class=\"data row56 col4\" ></td>\n",
+       "      <td id=\"T_76074_row56_col5\" class=\"data row56 col5\" ></td>\n",
+       "      <td id=\"T_76074_row56_col6\" class=\"data row56 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row57_col0\" class=\"data row57 col0\" ></td>\n",
+       "      <td id=\"T_76074_row57_col1\" class=\"data row57 col1\" ></td>\n",
+       "      <td id=\"T_76074_row57_col2\" class=\"data row57 col2\" ></td>\n",
+       "      <td id=\"T_76074_row57_col3\" class=\"data row57 col3\" ></td>\n",
+       "      <td id=\"T_76074_row57_col4\" class=\"data row57 col4\" ></td>\n",
+       "      <td id=\"T_76074_row57_col5\" class=\"data row57 col5\" ></td>\n",
+       "      <td id=\"T_76074_row57_col6\" class=\"data row57 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row58_col0\" class=\"data row58 col0\" ></td>\n",
+       "      <td id=\"T_76074_row58_col1\" class=\"data row58 col1\" >Total Overnight Cost (Accounts 10 to 50)</td>\n",
+       "      <td id=\"T_76074_row58_col2\" class=\"data row58 col2\" >$ 13,480,001,446</td>\n",
+       "      <td id=\"T_76074_row58_col3\" class=\"data row58 col3\" ></td>\n",
+       "      <td id=\"T_76074_row58_col4\" class=\"data row58 col4\" ></td>\n",
+       "      <td id=\"T_76074_row58_col5\" class=\"data row58 col5\" ></td>\n",
+       "      <td id=\"T_76074_row58_col6\" class=\"data row58 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row59_col0\" class=\"data row59 col0\" ></td>\n",
+       "      <td id=\"T_76074_row59_col1\" class=\"data row59 col1\" >(Accounts 10 to 50) US$/kWe</td>\n",
+       "      <td id=\"T_76074_row59_col2\" class=\"data row59 col2\" >$ 12,765</td>\n",
+       "      <td id=\"T_76074_row59_col3\" class=\"data row59 col3\" ></td>\n",
+       "      <td id=\"T_76074_row59_col4\" class=\"data row59 col4\" ></td>\n",
+       "      <td id=\"T_76074_row59_col5\" class=\"data row59 col5\" ></td>\n",
+       "      <td id=\"T_76074_row59_col6\" class=\"data row59 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row60_col0\" class=\"data row60 col0\" ></td>\n",
+       "      <td id=\"T_76074_row60_col1\" class=\"data row60 col1\" ></td>\n",
+       "      <td id=\"T_76074_row60_col2\" class=\"data row60 col2\" ></td>\n",
+       "      <td id=\"T_76074_row60_col3\" class=\"data row60 col3\" ></td>\n",
+       "      <td id=\"T_76074_row60_col4\" class=\"data row60 col4\" ></td>\n",
+       "      <td id=\"T_76074_row60_col5\" class=\"data row60 col5\" ></td>\n",
+       "      <td id=\"T_76074_row60_col6\" class=\"data row60 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row61_col0\" class=\"data row61 col0\" ></td>\n",
+       "      <td id=\"T_76074_row61_col1\" class=\"data row61 col1\" >Total Capital Investment Cost (All Accounts)</td>\n",
+       "      <td id=\"T_76074_row61_col2\" class=\"data row61 col2\" >$ 20,558,611,899</td>\n",
+       "      <td id=\"T_76074_row61_col3\" class=\"data row61 col3\" ></td>\n",
+       "      <td id=\"T_76074_row61_col4\" class=\"data row61 col4\" ></td>\n",
+       "      <td id=\"T_76074_row61_col5\" class=\"data row61 col5\" ></td>\n",
+       "      <td id=\"T_76074_row61_col6\" class=\"data row61 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row62_col0\" class=\"data row62 col0\" ></td>\n",
+       "      <td id=\"T_76074_row62_col1\" class=\"data row62 col1\" >(Accounts 10 to 60) US$/kWe</td>\n",
+       "      <td id=\"T_76074_row62_col2\" class=\"data row62 col2\" >$ 19,468</td>\n",
+       "      <td id=\"T_76074_row62_col3\" class=\"data row62 col3\" ></td>\n",
+       "      <td id=\"T_76074_row62_col4\" class=\"data row62 col4\" ></td>\n",
+       "      <td id=\"T_76074_row62_col5\" class=\"data row62 col5\" ></td>\n",
+       "      <td id=\"T_76074_row62_col6\" class=\"data row62 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row63_col0\" class=\"data row63 col0\" ></td>\n",
+       "      <td id=\"T_76074_row63_col1\" class=\"data row63 col1\" ></td>\n",
+       "      <td id=\"T_76074_row63_col2\" class=\"data row63 col2\" ></td>\n",
+       "      <td id=\"T_76074_row63_col3\" class=\"data row63 col3\" ></td>\n",
+       "      <td id=\"T_76074_row63_col4\" class=\"data row63 col4\" ></td>\n",
+       "      <td id=\"T_76074_row63_col5\" class=\"data row63 col5\" ></td>\n",
+       "      <td id=\"T_76074_row63_col6\" class=\"data row63 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row64_col0\" class=\"data row64 col0\" ></td>\n",
+       "      <td id=\"T_76074_row64_col1\" class=\"data row64 col1\" >Total Overnight Cost - ITC reduced</td>\n",
+       "      <td id=\"T_76074_row64_col2\" class=\"data row64 col2\" >$ 12,806,001,374</td>\n",
+       "      <td id=\"T_76074_row64_col3\" class=\"data row64 col3\" ></td>\n",
+       "      <td id=\"T_76074_row64_col4\" class=\"data row64 col4\" ></td>\n",
+       "      <td id=\"T_76074_row64_col5\" class=\"data row64 col5\" ></td>\n",
+       "      <td id=\"T_76074_row64_col6\" class=\"data row64 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row65_col0\" class=\"data row65 col0\" ></td>\n",
+       "      <td id=\"T_76074_row65_col1\" class=\"data row65 col1\" >Total Overnight Cost -ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_76074_row65_col2\" class=\"data row65 col2\" >$ 12,127</td>\n",
+       "      <td id=\"T_76074_row65_col3\" class=\"data row65 col3\" ></td>\n",
+       "      <td id=\"T_76074_row65_col4\" class=\"data row65 col4\" ></td>\n",
+       "      <td id=\"T_76074_row65_col5\" class=\"data row65 col5\" ></td>\n",
+       "      <td id=\"T_76074_row65_col6\" class=\"data row65 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row66_col0\" class=\"data row66 col0\" ></td>\n",
+       "      <td id=\"T_76074_row66_col1\" class=\"data row66 col1\" ></td>\n",
+       "      <td id=\"T_76074_row66_col2\" class=\"data row66 col2\" ></td>\n",
+       "      <td id=\"T_76074_row66_col3\" class=\"data row66 col3\" ></td>\n",
+       "      <td id=\"T_76074_row66_col4\" class=\"data row66 col4\" ></td>\n",
+       "      <td id=\"T_76074_row66_col5\" class=\"data row66 col5\" ></td>\n",
+       "      <td id=\"T_76074_row66_col6\" class=\"data row66 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row67_col0\" class=\"data row67 col0\" ></td>\n",
+       "      <td id=\"T_76074_row67_col1\" class=\"data row67 col1\" >Total Capital Investment Cost - ITC reduced</td>\n",
+       "      <td id=\"T_76074_row67_col2\" class=\"data row67 col2\" >$ 19,884,611,827</td>\n",
+       "      <td id=\"T_76074_row67_col3\" class=\"data row67 col3\" ></td>\n",
+       "      <td id=\"T_76074_row67_col4\" class=\"data row67 col4\" ></td>\n",
+       "      <td id=\"T_76074_row67_col5\" class=\"data row67 col5\" ></td>\n",
+       "      <td id=\"T_76074_row67_col6\" class=\"data row67 col6\" ></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td id=\"T_76074_row68_col0\" class=\"data row68 col0\" ></td>\n",
+       "      <td id=\"T_76074_row68_col1\" class=\"data row68 col1\" >Total Capital Investment Cost - ITC reduced (US$/kWe)</td>\n",
+       "      <td id=\"T_76074_row68_col2\" class=\"data row68 col2\" >$ 18,830</td>\n",
+       "      <td id=\"T_76074_row68_col3\" class=\"data row68 col3\" ></td>\n",
+       "      <td id=\"T_76074_row68_col4\" class=\"data row68 col4\" ></td>\n",
+       "      <td id=\"T_76074_row68_col5\" class=\"data row68 col5\" ></td>\n",
+       "      <td id=\"T_76074_row68_col6\" class=\"data row68 col6\" ></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x15a594c10>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Example 1\n",
+    "result = calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "        num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0,\\\n",
+    "                startup_0, ITC_0, n_ITC)\n",
+    "\n",
+    "FOAK_cost_pretty = prettify(result[0],\\\n",
+    "            f\" The {reactor_type} {np.round(reactor_power/1000,1)} MWe Reactor ({n_th}th of a kind) <br> Capital Cost Summary  <br><br> \", \"subsidies\")\n",
+    "FOAK_cost_pretty"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "faafd516",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "The Cost of reactor unit # 1 (1th of a kind)\n",
+      "ITC-reduced OCC = 12126 $/kWe\n",
+      "ITC-reduced TCI = 18830 $/kWe\n",
+      "Construction Duration = 138.7 months\n",
+      "\n",
+      "\n",
+      "The Cost of reactor unit # 2 (2th of a kind)\n",
+      "ITC-reduced OCC = 6677 $/kWe\n",
+      "ITC-reduced TCI = 9048 $/kWe\n",
+      "Construction Duration = 100.1 months\n",
+      "\n",
+      "\n",
+      "The Cost of reactor unit # 3 (3th of a kind)\n",
+      "ITC-reduced OCC = 5099 $/kWe\n",
+      "ITC-reduced TCI = 6560 $/kWe\n",
+      "Construction Duration = 85.1 months\n",
+      "\n",
+      "\n",
+      "The Cost of reactor unit # 10 (10th of a kind)\n",
+      "ITC-reduced OCC = 3737 $/kWe\n",
+      "ITC-reduced TCI = 4461 $/kWe\n",
+      "Construction Duration = 65.1 months\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Example 2\n",
+    "for n_th in [1,2,3,10]:\n",
+    "    results = calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "        num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc,\\\n",
+    "            standardization_0, interest_rate_0, startup_0, ITC_0, n_ITC)\n",
+    "    print(\"\\n\")\n",
+    "    print(f\"The Cost of reactor unit # {n_th} ({n_th}th of a kind)\")\n",
+    "    print(f\"ITC-reduced OCC = {int(results[1])} $/kWe\")\n",
+    "    print(f\"ITC-reduced TCI = {int(results[2])} $/kWe\")\n",
+    "    print(f\"Construction Duration = {np.round(results[3],1)} months\")\n"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
diff --git a/Cost_Reduction/CostReduction_exploration_mode.py b/Cost_Reduction/CostReduction_exploration_mode.py
new file mode 100644
index 0000000..e152504
--- /dev/null
+++ b/Cost_Reduction/CostReduction_exploration_mode.py
@@ -0,0 +1,802 @@
+#!/usr/bin/env python
+
+# This notebook demonstrates the impact of various levers on the cost of a nuclear power plant.
+# 
+# It begins with a baseline cost sheet, followed by an estimation of how each lever affects the overall cost. Levers that may influence the cost include design completion, modularity, interest rates,.etc
+# 
+# This notebook is useful for exploring how these levers contribute to cost overruns or savings, step by step. Users who are only interested in the final result can utilize the last section, which includes a Python function that calculates the impact of all the levers in a single step.
+# 
+# For a detailed understanding of the details behind this framework, please check [this report](https://www.osti.gov/biblio/2361138)
+
+# ###  Importing the libraries
+
+# In[1]:
+
+
+import pandas as pd
+import numpy as np
+from src import prettify, update_high_level_costs, ITC_reduction_factor, update_cons_duration, sum_lab_hrs, update_cons_duration_2
+
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+pd.set_option('display.max_rows', None)
+
+
+# ## Section 1 : Reading the Baseline reactor Cost Summary Table 
+
+
+# A function to read the inital reactor data from excel
+
+def reactor_data_read(reactor_type):
+    
+    if reactor_type == "Concept A":
+        # Reading excel or csv files
+        Reactor_data_0 = pd.read_excel('Inputs.xlsx', sheet_name = "Concept_A", nrows= 69)
+        reactor_power = 1056 * 1000 # kw
+        
+        
+    elif reactor_type == "Concept B":
+        # Reading excel or csv files
+        Reactor_data_0 = pd.read_excel('Inputs.xlsx', sheet_name = "Concept_B", nrows= 69)
+        reactor_power = 310.8 * 1000 # kw    
+        
+    db = pd.DataFrame()
+    db = Reactor_data_0[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    Reactor_data = db
+    return Reactor_data, reactor_power
+
+
+
+# ### The Cost reduction framework: levers and variables impact the costs as shown in the figure (below)
+
+
+# ## Section - 3 : Updating the Cost Summary based on user inputs
+
+# ### Section - 3-0 : Adding the factory cost to accounts 22 and 232.1
+
+
+def add_factory_cost(Reactor_data_0, power, f_22, f_2321, num_orders):
+    db = pd.DataFrame()
+    db = Reactor_data_0[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    db.loc[db.Account == 22, 'Factory Equipment Cost'] = None # clear old values
+    db.loc[db.Account == '232.1', 'Factory Equipment Cost'] = None # clear old values
+
+  
+    db.loc[db.Account == 22, 'Factory Equipment Cost'] = ((Reactor_data_0.loc[Reactor_data_0.Account == 22, 'Factory Equipment Cost']) + f_22/num_orders )
+    db.loc[db.Account == '232.1', 'Factory Equipment Cost'] = ((Reactor_data_0.loc[Reactor_data_0.Account == '232.1', 'Factory Equipment Cost']) + f_2321/num_orders)
+
+
+    Reactor_data_fac = update_high_level_costs(db, power)
+    ref_tot_lab_hrs = sum_lab_hrs (Reactor_data_fac)
+
+    Reactor_data_fac_ = pd.DataFrame()
+    Reactor_data_fac_ = Reactor_data_fac[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    
+    return Reactor_data_fac_  , ref_tot_lab_hrs
+
+# ### Section 3-1 : The land cost & Taxes
+
+# In[5]:
+
+
+# The cost of the land is 22000$ per acre (500 acres
+# The cost is multiplied by the new $/acre divided by the old one
+# Accounts 11 and 12 are changed
+
+def add_land_cost(Reactor_data_fac, land_cost_per_acre, power):
+
+    db = pd.DataFrame()
+    db = Reactor_data_fac[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+   
+    db.loc[db.Account == 11, 'Total Cost (USD)'] = None # clear old values
+    db.loc[db.Account == 12, 'Total Cost (USD)'] = None # clear old values
+    db.loc[db.Account == 51, 'Total Cost (USD)'] = None # clear old values
+    
+
+    db.loc[db.Account == 11, 'Total Cost (USD)'] = (land_cost_per_acre /22000)*(Reactor_data_fac.loc[Reactor_data_fac.Account == 11, 'Total Cost (USD)'].values)
+    db.loc[db.Account == 12, 'Total Cost (USD)'] = (land_cost_per_acre /22000)*(Reactor_data_fac.loc[Reactor_data_fac.Account == 12, 'Total Cost (USD)'].values)
+
+
+    # The taxes scale with increasing the land cost 
+    db.loc[db.Account == 51, 'Total Cost (USD)'] = (land_cost_per_acre /22000)*(Reactor_data_fac.loc[Reactor_data_fac.Account == 51, 'Total Cost (USD)'].values)
+
+    db.loc[db.Account == 51, 'Total Cost (USD)']
+    Reactor_data_updated_1 = update_high_level_costs(db, power)
+
+
+    Reactor_data_updated_1_ = pd.DataFrame()
+    Reactor_data_updated_1_ = Reactor_data_updated_1[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    return Reactor_data_updated_1_
+ 
+
+# ### Section 3-2 : Whether the Reactor Building and BOP are nuclear grade equipment
+
+# if the BOP is non-nuclear, the cost reduction factor for account 213 is 0.6
+# Also, the cost reduction factor for account 232.1 is 0.6 (for factory and labor but not material)
+
+# If the reactor building is non nuclear, the cost reduction factor for acount 212 is 0.6
+
+def add_BOP_RP_grades(Reactor_data_updated_1, RB_grade_0, BOP_grade_0, power, reactor_type, n_th, mod_0):
+    
+    RB_grade = RB_grade_0     # Does not change when building more units. it is either always nuclear or always non nuclear
+    
+    
+    # If n >=2: BoP commercial = True : non_nuclear
+    if n_th == 1:
+        BOP_grade = BOP_grade_0
+    elif n_th >=2:
+        BOP_grade = "non_nuclear"
+             
+    
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_1[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    db.loc[db.Account == 212, 'Site Material Cost'] = None # clear old values
+    db.loc[db.Account == 212, 'Site Labor Cost'] = None # clear old values
+    db.loc[db.Account ==  212, 'Site Labor Hours'] = None
+    db.loc[db.Account ==  212, 'Factory Equipment Cost'] = None
+
+    db.loc[db.Account ==  213, 'Site Material Cost'] = None
+    db.loc[db.Account ==  213, 'Site Labor Cost']  = None
+    db.loc[db.Account ==  213, 'Site Labor Hours'] = None
+    db.loc[db.Account ==  213, 'Factory Equipment Cost'] = None
+
+    db.loc[db.Account ==  '232.1', 'Factory Equipment Cost'] = None
+    db.loc[db.Account ==  '232.1', 'Site Labor Cost'] = None
+    db.loc[db.Account ==  '232.1', 'Site Labor Hours'] = None
+
+
+    if RB_grade == "non_nuclear":
+        db.loc[db.Account == 212, 'Site Material Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Material Cost']).values)
+        db.loc[db.Account == 212, 'Site Labor Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Labor Cost']).values)
+        db.loc[db.Account == 212,'Site Labor Hours'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Labor Hours']).values)
+        db.loc[db.Account == 212,'Factory Equipment Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Factory Equipment Cost']).values)
+
+    else:
+        db.loc[db.Account == 212, 'Site Material Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Material Cost']).values)
+        db.loc[db.Account == 212, 'Site Labor Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Labor Cost']).values)
+        db.loc[db.Account == 212,'Site Labor Hours'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Site Labor Hours']).values)
+        db.loc[db.Account == 212,'Factory Equipment Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 212, 'Factory Equipment Cost']).values)
+
+    
+    if BOP_grade == "non_nuclear":
+        db.loc[db.Account == 213, 'Site Material Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Material Cost']).values)
+        db.loc[db.Account == 213, 'Site Labor Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Labor Cost']).values)
+        db.loc[db.Account == 213, 'Site Labor Hours'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Labor Hours']).values)
+        db.loc[db.Account == 213, 'Factory Equipment Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Factory Equipment Cost']).values)
+
+        db.loc[db.Account == '232.1', 'Factory Equipment Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Factory Equipment Cost']).values)
+        db.loc[db.Account == '232.1', 'Site Labor Hours'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Site Labor Hours']).values)
+        db.loc[db.Account == '232.1', 'Site Labor Cost'] = 0.6*((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Site Labor Cost']).values)
+
+
+    else:
+        db.loc[db.Account == 213, 'Site Material Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Material Cost']).values)
+        db.loc[db.Account == 213, 'Site Labor Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Labor Cost']).values)
+        db.loc[db.Account == 213, 'Site Labor Hours'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Site Labor Hours']).values)
+        db.loc[db.Account == 213, 'Factory Equipment Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == 213, 'Factory Equipment Cost']).values)
+
+        db.loc[db.Account == '232.1', 'Factory Equipment Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Factory Equipment Cost']).values)
+        db.loc[db.Account == '232.1', 'Site Labor Hours'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Site Labor Hours']).values)
+        db.loc[db.Account == '232.1', 'Site Labor Cost'] = ((Reactor_data_updated_1.loc[Reactor_data_updated_1.Account == '232.1', 'Site Labor Cost']).values)
+
+
+    Reactor_data_updated_2 = update_high_level_costs(db, power)
+
+    Reactor_data_updated_2_ = pd.DataFrame()
+    Reactor_data_updated_2_ = Reactor_data_updated_2[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+
+     
+    if reactor_type == "Concept A":
+        duration = 125
+    elif reactor_type == "Concept B": 
+        duration = 80
+          
+    new_dur = update_cons_duration(Reactor_data_updated_1, Reactor_data_updated_2,  duration)
+   
+     #apply modularity factor affecting the construction duration 
+    if n_th == 1:
+        mod = mod_0
+    elif n_th >= 2:
+        mod =  "modularized"
+   
+     
+    if mod == "modularized" :
+        mod_factor = 0.8
+    else:   
+        mod_factor = 1
+    
+    new_dur_1 = new_dur * mod_factor 
+    return Reactor_data_updated_2_ , new_dur_1
+
+
+# ### Section 3-3 : Bulk Ordering
+
+
+#The factory equipment cost of  accounts 22 and 232.1 has to be divided by the number of orders
+# The factory equipment cost of account 22 is multiplied by a reuction factor
+# The factory equipment cost of account 232.1 is multiplied by a reduction factor
+
+
+def add_bulk_ordering(Reactor_data_updated_3, num_orders, f_22, f_2321, power):
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_3[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    # esimtated learning rates
+    lr22   = 0.1802341659291420
+    lr2321 = 0.2607462372040820
+
+    # These reduction factor are calculated as follows
+    reduction_factor_22 = 0 # initialization
+    reduction_factor_2321 = 0
+
+    for ith_unit in  range(1,num_orders+1):
+        reduction_factor_22+=((1 - lr22)**np.log2(ith_unit))/num_orders # for account 22
+        reduction_factor_2321+=((1 - lr2321)**np.log2(ith_unit))/num_orders # for account 232.1
+
+
+        
+    for x in [ 22, '232.1']:  
+        db.loc[db.Account == x, 'Factory Equipment Cost'] = None # clear old values
+
+
+    # note that the cost reduction factor impacts the cost of the component not the cost of the factory
+    db.loc[db.Account == 22, 'Factory Equipment Cost']       = reduction_factor_22   *  (    ( Reactor_data_updated_3.loc[ Reactor_data_updated_3.Account == 22, 'Factory Equipment Cost']   ) - ( f_22/num_orders) ) + (f_22/num_orders) 
+    db.loc[db.Account == '232.1', 'Factory Equipment Cost']  = reduction_factor_2321 *   (  ( Reactor_data_updated_3.loc[ Reactor_data_updated_3.Account == '232.1', 'Factory Equipment Cost']) - ( f_2321/num_orders)) +(f_2321/num_orders) 
+
+    
+
+    Reactor_data_updated_4 = update_high_level_costs(db, power)
+    Reactor_data_updated_4_ = pd.DataFrame()
+    Reactor_data_updated_4_ = Reactor_data_updated_4[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    return Reactor_data_updated_4_ 
+
+
+
+# ### Section 3-4 : Reworking and labor productivity
+
+
+def add_reworking_productivity(Reactor_data_updated_4, reactor_type, n_th, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, power, prev_cons_duration, baseline_lab_hours):
+    #Reworking = f(AE, CE, design completion)
+    
+    if n_th == 1:
+        design_completion = design_completion_0
+        ae_exp = ae_exp_0
+        ce_exp = ce_exp_0
+        
+    elif n_th > 1:
+        design_completion = 1   
+        ae_exp = min( (ae_exp_0 + (2/N_AE)*(n_th-1) ), 2)
+        ce_exp = min( (ce_exp_0 + (2/N_cons)*(n_th-1) ), 2)
+    
+    # # labor productivity factor = f(construction experience level)
+    productivity = 0.145*ce_exp + 0.71        
+            
+
+    if reactor_type == "Concept B":
+        reworking_factor =  (-0.9*design_completion+ 1.9) * (-0.15*ae_exp+1.3) * (-0.15*ce_exp+1.3) 
+
+    elif reactor_type == "Concept A":
+        reworking_factor =  (-0.69*design_completion+ 1.69) * (-0.125*ae_exp+1.25) * (-0.125*ce_exp+1.25) 
+
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_4[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    for x in [212, 213, '211 plus 214 to 219',22, '232.1', 233, 24, 26]:  
+        db.loc[db.Account == x, 'Factory Equipment Cost'] = None # clear old values
+        db.loc[db.Account == x, 'Site Labor Hours'] = None
+        db.loc[db.Account == x, 'Site Labor Cost'] = None
+        db.loc[db.Account == x, 'Site Material Cost'] = None
+
+    for x in [212, 213, '211 plus 214 to 219',22, '232.1', 233, 24, 26]: 
+        db.loc[db.Account == x, 'Factory Equipment Cost'] =\
+            ((( Reactor_data_updated_4.loc[ Reactor_data_updated_4.Account == x, 'Factory Equipment Cost']).values)[0])*reworking_factor  
+        db.loc[db.Account == x, 'Site Labor Hours'] =\
+            ((( Reactor_data_updated_4.loc[ Reactor_data_updated_4.Account == x, 'Site Labor Hours']).values)[0])*reworking_factor/productivity
+        db.loc[db.Account == x, 'Site Labor Cost'] =\
+            ((( Reactor_data_updated_4.loc[ Reactor_data_updated_4.Account == x, 'Site Labor Cost']).values)[0])*reworking_factor/productivity 
+        db.loc[db.Account == x, 'Site Material Cost'] =\
+            ((( Reactor_data_updated_4.loc[ Reactor_data_updated_4.Account == x, 'Site Material Cost']).values)[0])*reworking_factor 
+
+
+    
+
+    Reactor_data_updated_5 = update_high_level_costs(db, power)
+    Reactor_data_updated_5_ = pd.DataFrame()
+    Reactor_data_updated_5_ = Reactor_data_updated_5[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    # update the construction duration
+    if reactor_type == "Concept A":
+        reactor_type_ref_duration = 125
+    elif reactor_type == "Concept B": 
+        reactor_type_ref_duration = 80
+        
+    new_dur    = update_cons_duration_2(Reactor_data_updated_4, Reactor_data_updated_5_, reactor_type_ref_duration, prev_cons_duration, baseline_lab_hours)
+    return Reactor_data_updated_5_  , new_dur
+ 
+
+
+
+# #### Combine the previous functions in one function
+
+
+# Combine the previous functions in one function
+
+def update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, 
+                       num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0):
+
+    reactor_data, reactor_power = reactor_data_read(reactor_type)
+    
+    reactor_data_factory, baseline_lab_hours = add_factory_cost(
+        reactor_data, reactor_power, f_22, f_2321, num_orders
+    )
+    
+    reactor_data_factory = add_land_cost(
+        reactor_data_factory, land_cost_per_acre_0, reactor_power
+    )
+    
+    reactor_data_factory, prev_cons_duration = add_BOP_RP_grades(
+        reactor_data_factory, RB_grade_0, BOP_grade_0, reactor_power, reactor_type, n_th, mod_0
+    )
+    
+    reactor_data_factory = add_bulk_ordering(
+        reactor_data_factory, num_orders, f_22, f_2321, reactor_power
+    )
+    
+    reactor_data_factory, new_dur_2 = add_reworking_productivity(
+        reactor_data_factory, reactor_type, n_th, design_completion_0, ae_exp_0, N_AE, ce_exp_0, 
+        N_cons, reactor_power, prev_cons_duration, baseline_lab_hours
+    )
+    
+    return reactor_data_factory, new_dur_2
+
+
+
+# ### Section 3-5 Learning by doing effect on the cost
+
+
+def learning_effect(Reactor_data_updated_5, n_th, standardization_0, power):
+
+    if n_th  == 1:
+        standardization = min(0.7, standardization_0)
+    elif n_th >1:
+        standardization = standardization_0    
+        
+    # # Creating the table for the learning rates
+    # #These rates are from KS-TIMCAT results.
+    # # The learning rates are multiplied by the standardization divded by 0.7 (since the standatization of PWRs was 0.7)
+    fitted_LR = pd.DataFrame()
+
+    fitted_LR.loc[:, 'Account'] = Reactor_data_updated_5.loc[:, 'Account']
+    fitted_LR.loc[:, 'Title'] = Reactor_data_updated_5.loc[:, 'Title']
+    fitted_LR = fitted_LR.loc[fitted_LR['Account'].isin([212, 213, '211 plus 214 to 219', 22, '232.1', 233, 24, 26])]
+
+    fitted_LR['Mat LR'] = np.array([0.099588665391, 0.099588665391, 0.099588665391, 0.080817992281, 0.0000000, 0.099588665391,\
+                                    0.099588665391,0.099588665391])*standardization/0.7
+
+    fitted_LR['Lab LR'] =     np.array([0.180678729399, 0.180678729399, 0.180678729399,0.146555539499, 0.137148574884,\
+                                        0.180678729399, 0.180678729399,0.180678729399])*standardization/0.7
+
+
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_5[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    for x in [212, 213, '211 plus 214 to 219', 22, '232.1', 233, 24, 26]:  
+        db.loc[db.Account == x, 'Site Labor Hours'] = None
+        db.loc[db.Account == x, 'Site Labor Cost'] = None
+        db.loc[db.Account == x, 'Site Material Cost'] = None
+
+
+    # # # # Bulk order reduction	
+    for x in [212, 213, '211 plus 214 to 219', 22, '232.1', 233, 24, 26]:
+        mat_cost_reduction_multiplier = (1 - (fitted_LR.loc[fitted_LR.Account == x, 'Mat LR'].values[0]))**np.log2(n_th)
+        lab_cost_reduction_multiplier = (1 - (fitted_LR.loc[fitted_LR.Account == x, 'Lab LR'].values[0]))**np.log2(n_th)
+        
+        db.loc[db.Account == x, 'Site Material Cost'] =\
+            (( Reactor_data_updated_5.loc[ Reactor_data_updated_5.Account == x, 'Site Material Cost']))* mat_cost_reduction_multiplier
+
+        db.loc[db.Account == x, 'Site Labor Hours'] =\
+            (( Reactor_data_updated_5.loc[ Reactor_data_updated_5.Account == x, 'Site Labor Hours']))* lab_cost_reduction_multiplier
+    
+        db.loc[db.Account == x, 'Site Labor Cost'] =\
+            (( Reactor_data_updated_5.loc[ Reactor_data_updated_5.Account == x, 'Site Labor Cost']))* lab_cost_reduction_multiplier
+
+
+    Reactor_data_updated_6 = update_high_level_costs(db, power)
+    Reactor_data_updated_6_ = pd.DataFrame()
+    Reactor_data_updated_6_ = Reactor_data_updated_6[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                 'Site Material Cost']].copy()
+    
+    return Reactor_data_updated_6_  
+
+
+
+def act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, cons_duration_no_delay):
+    
+    if n_th == 1:
+        Design_Maturity = Design_Maturity_0
+        proc_exp = proc_exp_0
+    
+    elif n_th>1:
+        Design_Maturity = 2
+        proc_exp = min( (proc_exp_0 + (2/N_proc)*(n_th-1) ), 2)
+             
+    # For the accounts 21, 22, 23, 24, 25, 26, 
+    # The delays are D_21,D_22,D_23,D_24,D_25,D_26 
+    # The tasks lengths (in months) are B_21,B_22,B_23,B_24,B_25,B_26
+
+    # task length ratio between SFR and HTGR is 100/65
+    # We use this ratio to convert SFR to HTGT task lengths
+
+    if reactor_type == "Concept B":
+        task_length_multiplier = 1
+        ref_construction_duration = 64
+    elif reactor_type == "Concept A": 
+        task_length_multiplier = 100/64
+        ref_construction_duration = 100
+        
+    B_21 =  42.1 * task_length_multiplier # months 
+    B_22 = 60.2 * task_length_multiplier
+    B_23 = 14.8 * task_length_multiplier
+    B_24 = 3.6* task_length_multiplier
+    B_25 = 10.1* task_length_multiplier
+    B_26 = 43.9* task_length_multiplier
+
+
+    # The delays are 
+    D_21 =  - 6 * Design_Maturity  - 3*proc_exp + 18
+    D_22 =  - 6 * Design_Maturity  - 3*proc_exp + 18
+    D_23 =   - 6 * Design_Maturity  - 3*proc_exp + 18
+    D_24 =   - 6 * Design_Maturity  - 3*proc_exp + 18
+    D_25 =   - 6 * Design_Maturity  - 3*proc_exp + 18
+    D_26 =   - 6 * Design_Maturity  - 3*proc_exp + 18
+
+
+    # The tasks completion times (in months) are T_21,T_22,T_23,T_24,T_25,T_26
+    T_21 = B_21 + D_21 
+    T_22 = 0.09*(B_21+D_21)  +B_22+D_22
+    T_23 = 0.24*(B_21+D_21)  +B_23+D_23
+    T_24 = 0.24*(B_21+D_21) + 0.34*(B_23+D_23)  +B_24+D_24
+    T_25 = 0.18*(B_21+D_21)  +B_25+D_25
+    T_26 = 0.21*(B_21+D_21)   +B_26+D_26
+    T_end = max(T_21, T_22, T_23, T_24, T_25, T_26)
+
+
+    supply_chain_delay = max( T_end - ref_construction_duration, 0)
+    actual_construction_duration_plus_delay = cons_duration_no_delay + supply_chain_delay
+    return actual_construction_duration_plus_delay
+
+
+# ### Section 3-7 Learning by doing effect on the construction duration
+
+
+def duration_learning_effect(n_th, standardization_0, actual_construction_duration_plus_delay):
+    
+    if n_th  == 1:
+        standardization = min(0.7, standardization_0)
+    elif n_th >1:
+        standardization = standardization_0  
+    # now the effect of learning on the consturction duration
+    fitted_LR_duration = 0.103719051*standardization/0.7
+    duration_multiplier = (1 -fitted_LR_duration)**np.log2(n_th)
+    final_construction_duration = duration_multiplier *actual_construction_duration_plus_delay
+    return final_construction_duration 
+
+# ### Section 3-8 Calculate the Indirect Cost and the standardization impact
+
+def update_indirect_cost(n_th, standardization_0, Reactor_data_updated_6, final_construction_duration, power ):
+    
+    if n_th  == 1:
+        standardization = min(0.7, standardization_0)
+    elif n_th >1:
+        standardization = standardization_0     
+    #   I use here the indirect cost correlations prepared by Jia
+
+    # When the standardization is  100%, the engineering service accound (Acct 35) is zero, 
+    # When the standardization is  70%, the engineering service accound (Acct 35) does not change
+    # The account 35 multiplier is
+
+    factor_35 = 10/3* ( 1 - standardization)
+
+
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_6[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+
+    for x in [31, 32, 33, 34, 35]:  
+        db.loc[db.Account == x, 'Total Cost (USD)'] = None # clear old values
+
+
+    # # total direct mat cost, labor cost, labor hours
+    sum_new_mat_cost  = 0 # initilization
+    sum_new_lab_cost  = 0 # initilization
+    sum_new_lab_hrs  = 0 # initilization
+
+    for x in [21, 22, 23, 24, 26]:
+        sum_new_mat_cost +=     (db.loc[db.Account == x, 'Site Material Cost']).values
+        sum_new_lab_cost +=     (db.loc[db.Account == x, 'Site Labor Cost']).values
+        sum_new_lab_hrs  +=     (db.loc[db.Account == x, 'Site Labor Hours']).values
+
+
+    # The new indirect costs   
+    db.loc[db.Account == 31, 'Total Cost (USD)'] =  (sum_new_mat_cost*0.785* sum_new_lab_hrs/final_construction_duration/160/1058)\
+    + sum_new_lab_cost *0.36
+
+    db.loc[db.Account == 32, 'Total Cost (USD)'] =  sum_new_lab_cost *0.36*3.661* final_construction_duration/72
+
+    db.loc[db.Account == 33, 'Total Cost (USD)'] =  0.04207006 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )
+
+    db.loc[db.Account == 34, 'Total Cost (USD)'] =  0.00354234616938 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] )
+
+    db.loc[db.Account == 35, 'Total Cost (USD)'] = (0.27017603 * (db.loc[db.Account == 32, 'Total Cost (USD)'].values[0] ))*factor_35 
+
+
+    Reactor_data_updated_7 = update_high_level_costs(db, power)
+    Reactor_data_updated_7_ = pd.DataFrame()
+    Reactor_data_updated_7_ = Reactor_data_updated_7[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    return Reactor_data_updated_7_  
+
+
+
+
+
+# #### Combine the previous functions in one function
+
+
+
+def calculate_base_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, mod_0):
+    reactor_power = (reactor_data_read(reactor_type ))[1]
+    direct_cost_updated , act_con_duration = update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0)
+
+    cons_duration_plus_delay = act_cons_duration_plus_delay(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, act_con_duration)
+    final_con_duration = duration_learning_effect(n_th, standardization_0, cons_duration_plus_delay)
+    direct_cost_updated_plus_learning = learning_effect(direct_cost_updated , n_th, standardization_0, reactor_power)
+
+    direct_cost_updated_plus_learning_with_indirect_cost = update_indirect_cost(n_th, standardization_0, direct_cost_updated_plus_learning, final_con_duration, reactor_power  )
+    return direct_cost_updated_plus_learning_with_indirect_cost, final_con_duration 
+
+
+# ### Section 3-9 :  Insurance
+
+
+
+def insurance_cost_update(Reactor_data_0, Reactor_data_updated_7, power):
+    # insurance increases linearly when increaing the sum of the 20s and 30s account
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_7[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    db0 = Reactor_data_0
+    db.loc[db.Account == 52, 'Total Cost (USD)'] = None # clear old values
+
+    change_in_insuance_cost = (db.loc[db.Title =='20s - Subtotal', 'Total Cost (USD)'].values\
+                            + db.loc[db.Title =='30s - Subtotal', 'Total Cost (USD)'].values)/ (db0.loc[db0.Title =='20s - Subtotal', 'Total Cost (USD)'].values\
+                            + db0.loc[db0.Title =='30s - Subtotal', 'Total Cost (USD)'].values)
+
+    db.loc[db.Account == 52, 'Total Cost (USD)'] =  (change_in_insuance_cost[0])* (Reactor_data_updated_7.loc[db.Account == 52, 'Total Cost (USD)'])
+
+    Reactor_data_updated_8 = update_high_level_costs(db, power)
+
+    Reactor_data_updated_8_ = pd.DataFrame()
+    Reactor_data_updated_8_ = Reactor_data_updated_8[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    return Reactor_data_updated_8_  
+
+# ### Section 3-10 :  Interest
+
+
+
+def update_interest_cost(Reactor_data_updated_8, final_construction_duration, interest_rate, startup_0, n_th, power):
+    # Read the ref spending curve
+    sp = pd.read_excel('Inputs.xlsx', sheet_name = "Ref Spending Curve", nrows= 104, usecols='A : D')
+    Months = sp['Month'].tolist()
+    CDFs  = sp['CDF'].tolist()
+    
+    annual_periods = np.linspace(12, 12*int(final_construction_duration/12),int(final_construction_duration/12))
+   
+    if max(annual_periods) < int(final_construction_duration)-1:
+        annual_periods_1= np.append( annual_periods, (final_construction_duration)-1)
+    else:
+        annual_periods_1 = annual_periods
+    
+    annual_cum_spend = []
+    for period in annual_periods_1:
+        new_period = 103*period/int(final_construction_duration)
+        
+        annual_cum_spend.append(np.interp(new_period, Months, CDFs))
+    annual_spend1 = np.append(annual_cum_spend[0], np.diff(annual_cum_spend ))
+    
+    tot_overnight_cost =   (Reactor_data_updated_8.loc[Reactor_data_updated_8.Title == 'Total Overnight Cost (Accounts 10 to 50)' , 'Total Cost (USD)']).values[0]
+
+    annual_loan_add =  annual_spend1 *tot_overnight_cost
+    
+    interest_exp = ((1+interest_rate)**((final_construction_duration -annual_periods_1)/12)) * annual_loan_add - annual_loan_add
+    
+    tot_int_exp_construction = sum(interest_exp )
+    if n_th == 1:
+        startup = startup_0
+    elif n_th >1:
+        startup = max( 7 , startup_0*(1-0.3)**np.log2(n_th))
+    
+    int_exp_startup = (tot_int_exp_construction + tot_overnight_cost)*((1+interest_rate)**(startup/12))-(tot_int_exp_construction + tot_overnight_cost)
+    db = pd.DataFrame()
+
+    db = Reactor_data_updated_8[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    db.loc[db.Account == 62, 'Total Cost (USD)'] = None # clear old values
+
+    (db.loc[db.Account == 62, 'Total Cost (USD)']) = int_exp_startup +tot_int_exp_construction 
+
+
+    Reactor_data_updated_9 = update_high_level_costs(db, power)
+
+    Reactor_data_updated_9_ = pd.DataFrame()
+    Reactor_data_updated_9_ = Reactor_data_updated_9[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 'Site Labor Cost',\
+                    'Site Material Cost']].copy()
+    
+    tot_cap_investment = Reactor_data_updated_9.loc[Reactor_data_updated_9.Title =='Total Capital Investment Cost (All Accounts)', 'Total Cost (USD)'].values
+    
+    return Reactor_data_updated_9_, tot_overnight_cost, tot_cap_investment
+
+
+# ### Section 3 - 11 :  ITC Subsidies
+
+
+def update_itc(Reactor_data_updated_9, tot_overnight_cost, tot_cap_investment, n_th, ITC_0, n_ITC, reactor_power):
+    
+    ITC = ITC_0 if n_th <= n_ITC else 0
+    
+    db1 = Reactor_data_updated_9[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 'Site Labor Hours', 
+                                  'Site Labor Cost', 'Site Material Cost']].copy()
+
+    ITC_cost_reduction_factor = ITC_reduction_factor(ITC)
+    ITC_reduced_OCC = tot_overnight_cost * ITC_cost_reduction_factor
+    OCC_cost_reduction_due_to_TCI = tot_overnight_cost - ITC_reduced_OCC
+
+    db1.loc[db1.Title == 'Total Overnight Cost - ITC reduced', 'Total Cost (USD)'] = ITC_reduced_OCC
+    db1.loc[db1.Title == 'Total Overnight Cost -ITC reduced (US$/kWe)', 'Total Cost (USD)'] = ITC_reduced_OCC / reactor_power
+    db1.loc[db1.Title == 'Total Capital Investment Cost - ITC reduced', 'Total Cost (USD)'] = tot_cap_investment - OCC_cost_reduction_due_to_TCI
+    
+    levelized_NCI = db1.loc[db1.Title == 'Total Capital Investment Cost - ITC reduced', 'Total Cost (USD)'].values[0] / reactor_power
+    db1.loc[db1.Title == 'Total Capital Investment Cost - ITC reduced (US$/kWe)', 'Total Cost (USD)'] = levelized_NCI
+
+    Reactor_data_updated_10 = update_high_level_costs(db1, reactor_power)
+    Reactor_data_updated_10_ = Reactor_data_updated_10[['Account', 'Title', 'Total Cost (USD)', 'Factory Equipment Cost', 
+                                                        'Site Labor Hours', 'Site Labor Cost', 'Site Material Cost']].copy()
+    
+    return Reactor_data_updated_10_, ITC_reduced_OCC / reactor_power, levelized_NCI
+
+# ## Section 4 :  The Final Result
+
+# #### A Python function to combine all the previous ones
+
+
+def calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,
+                           num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, 
+                           Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, 
+                           startup_0, ITC_0, n_ITC): 
+
+    reactor_data, reactor_power = reactor_data_read(reactor_type)
+    
+    tot_base_cost, final_construction_duration = calculate_base_cost(
+        reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, 
+        design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Design_Maturity_0, proc_exp_0, N_proc, 
+        standardization_0, mod_0
+    )
+    
+    tot_base_cost = insurance_cost_update(reactor_data, tot_base_cost, reactor_power)
+    tot_base_cost, tot_overnight_cost, tot_cap_investment = update_interest_cost(
+        tot_base_cost, final_construction_duration, interest_rate_0, startup_0, n_th, reactor_power
+    )
+
+    Final_Result_COA, levelized_net_OCC, levelized_NCI = update_itc(
+        tot_base_cost, tot_overnight_cost, tot_cap_investment, n_th, ITC_0, n_ITC, reactor_power
+    )
+
+    return Final_Result_COA, levelized_net_OCC, levelized_NCI, final_construction_duration[0]
+
+
+
+
+
+
+# # factory building cost (associated with accounts 22 and 232.1)
+# f_22   = 250000000
+# f_2321 = 150000000
+# land_cost_per_acre_0 =  22000 # dollars/acre
+# startup_0 = 16
+# staggering_ratio = 0.75
+
+
+
+# # reactor type: Concept A or Concept B
+# reactor_type = "Concept A"
+
+# # Which reactor unit: first of a kind : nth of a kind 
+# n_th = 1
+
+# # number of firm orders
+# num_orders = 7
+
+# # land cost
+# # From the SA report: the cost $22,000 per acre. The land area is 500 acres including recommended buffer
+# land_cost_per_acre_0 =  22000 # dollars/acre
+
+# # start up duration (months) 
+# startup_0 = 16 
+
+# # interest rate :
+# interest_rate_0 = 0.074
+
+# # Design completion
+# design_completion_0 =  0.463# 1 means 100%
+
+# # Design maturity
+# Design_Maturity_0 = 1
+
+# # #procurement service experience (supply chain experience)
+# proc_exp_0= 0.196 # 2 means procurement experts. This is ideal. 
+   
+# # #  architecture and engineeringexperience
+# ae_exp_0 = 0.69
+    
+# # #  Construction service experience
+# ce_exp_0 = 0.19
+
+
+# # numb er of projects for full efficiency of procurement, A/E, Construction
+# N_proc = 3
+# N_AE  = 4
+# N_cons =5
+
+# # modularity : "stick_built"  or "modularized"
+# mod_0 = "modularized" 
+
+    
+
+# # cross_site_standardization :
+# standardization_0 = 69.6979/100 # 0.7 corresponds to 70% standardization for PWRs
+
+# # # Determining if the BOP and reactor building (containtment) are non-nuclear or nuclear grade equipment (safety related)
+# BOP_grade_0 = "non_nuclear"
+# RB_grade_0 = "nuclear"
+
+# # #investment tax credits subsidies
+# ITC_0 = 0.3298
+
+# #number of reactors claiming ITC
+# n_ITC = 2
+
+# aa = (calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,
+#                            num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, 
+#                            Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, 
+#                            startup_0, ITC_0, n_ITC))
+
+# print(aa[3])
\ No newline at end of file
diff --git a/Cost_Reduction/cost_sampler1.py b/Cost_Reduction/cost_sampler1.py
new file mode 100644
index 0000000..4626218
--- /dev/null
+++ b/Cost_Reduction/cost_sampler1.py
@@ -0,0 +1,303 @@
+import numpy as np
+import pickle
+
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+from src import sampler, sheet_info
+import multiprocessing as mp
+import time
+from CostReduction_exploration_mode import calculate_final_result 
+import csv
+
+# cpu_count = os.cpu_count()
+
+
+# meta data
+n_samples =  1000000
+num_cpus = 100
+batch_size = 5000 # the number of samples that you store per time
+
+filename = f"{n_samples}_samples_resultss.csv"
+pickle_filename= f"{n_samples}_samples_resultss.pkl"
+
+
+# Declaring Excel File Path
+path_data_file = 'levers_info.xlsx'
+
+# Declaring Subsheets within Excel File
+subsheet_names_dict = {}
+# subsheet_names_dict['n_Samples'] = 'n_Samples';  
+subsheet_names_dict['Levers'] = 'Levers'; 
+
+# Extracting Declared Sheets as a Dictionary
+df_dict = sheet_info(path_data_file, subsheet_names_dict)
+
+
+Lever_samples = sampler(n_samples, df_dict['Levers'])
+
+# hard coding for the ITC amount
+possible_values = [6, 30, 40, 50]
+
+# Function to find the closest value
+def find_closest(value, possible_values):
+    return min(possible_values, key=lambda x: abs(x - value))
+
+# Update the second row
+Lever_samples[1] = [find_closest(value, possible_values) for value in Lever_samples[1]]
+
+
+
+
+
+
+
+
+# A function for the average results (averaged over all the reactors built)
+
+def calculate_final_result_avg_all(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\
+    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0,\
+        N_proc, standardization_0, interest_rate_0,\
+        startup_0, ITC_0, n_ITC, staggering_ratio):
+    
+ 
+    OCC_list = []
+    TCI_list = [] 
+    durations_list = []
+
+    for n_th in range(1, num_orders+1):
+
+        # the following results are: # The ITC_reduced OCC (levelized),The ITC_reduced TCI(levelized), cons duration 
+        _, OCC_result, TCI_result, duration_result  = calculate_final_result(reactor_type, n_th, f_22, f_2321,\
+            land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\
+        num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons,\
+            mod_0, Design_Maturity_0, proc_exp_0, N_proc,\
+            standardization_0, interest_rate_0, startup_0, ITC_0, n_ITC) 
+
+
+        OCC_list.append(OCC_result)
+        TCI_list.append(TCI_result )
+        durations_list.append( duration_result  )
+        
+    # Convert lists to numpy arrays for efficient computation
+    OCC_array = np.array(OCC_list)
+    TCI_array = np.array(TCI_list)
+    durations_array = np.array(durations_list)
+    occLastUnit =  OCC_array[-1]
+    TCILastUnit =  TCI_array[-1] 
+    durationsLastUnit = durations_array[-1] 
+    avg_OCC = np.mean(OCC_array )
+    avg_TCI = np.mean(TCI_array)
+    avg_duration = np.mean(durations_array)
+                            
+    # Calculate final startup duration
+    final_startup_duration = max(7, startup_0 * (1 - 0.3) ** np.log2(num_orders))
+    
+    # Calculate cumulative construction duration with startup
+    cons_duration_cumulative_wz_startup = (1 - staggering_ratio) * np.sum(durations_array[:-1]) + durations_array[-1] + final_startup_duration
+    
+    
+    # note that all the OCC and TCI here are TCI-reduced
+    return OCC_array, TCI_array, durations_array,\
+        cons_duration_cumulative_wz_startup, occLastUnit, TCILastUnit,\
+            durationsLastUnit, avg_OCC, avg_TCI, avg_duration             
+              
+              
+# 6 parameters that are not sampled
+reactor_type = "Concept A"
+# factory building cost (associated with accounts 22 and 232.1)
+f_22   = 250000000
+f_2321 = 150000000
+land_cost_per_acre_0 =  22000 # dollars/acre
+startup_0 = 16
+staggering_ratio = 0.75
+
+
+def results_sampling(sample):
+    vars_sampled = Lever_samples[:, sample]
+  
+    # Unpack only the necessary variables
+    n_orders, itc_0, n_ITC, interest_r, design_comp, Design_Maturity_0, proc_exp_0, N_proc, ce_exp_0, N_cons, ae_exp_0, N_AE, standard, mod_0,\
+        BOP_grade_0, RB_grade_0 = vars_sampled
+    # Directly access values from arrays without intermediate variables
+    num_orders = int(n_orders)
+    ITC_0 = itc_0/100
+    interest_rate_0 = interest_r/100
+    design_completion_0 = design_comp/100
+    standardization_0 = standard/100
+    
+    #modularity : "stick_built"  or "modularized"
+    if mod_0 == 0:
+        Mod_0 = "stick_built"
+    elif mod_0 == 1:
+        Mod_0 = "modularized"
+        
+    if RB_grade_0 == 0:  
+        RB_Grade_0  = "nuclear"
+    elif RB_grade_0 == 1:    
+        RB_Grade_0  = "non_nuclear"
+        
+    if BOP_grade_0 == 0:  
+        BOP_Grade_0  = "nuclear"
+    elif BOP_grade_0 == 1:    
+        BOP_Grade_0  = "non_nuclear"    
+        
+        
+    # Call the function with the necessary parameters
+    OCC_array, TCI_array, durations_array,\
+        cons_duration_cumulative_wz_startup, occLastUnit, TCILastUnit,\
+            durationsLastUnit, avg_OCC, avg_TCI, avg_duration  = \
+        calculate_final_result_avg_all(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_Grade_0, BOP_Grade_0, num_orders, 
+                                       design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, Mod_0, Design_Maturity_0, 
+                                       proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0, ITC_0, n_ITC, 
+                                       staggering_ratio)
+    
+    keys = [
+        'Num_orders', 'ITC', 'n_ITC', 'interest rate', 'Design completion', 'Design_Maturity_0', 
+        'supply chain exp_0', 'N supply chain', 'Const Proficiency', 'N const prof', 'AE', 
+        'N AE prof', 'standardization', 'modularity', 'BOP commercial', 'RB Safety Related'
+    ]
+    
+    results_data = {key: vars_sampled[i] for i, key in enumerate(keys)}
+    
+    
+    # Update results_data with each element of the arrays
+    for i, occ in enumerate(OCC_array):
+        results_data[f'OCC_{i}'] = occ
+        
+    for i, tci in enumerate(TCI_array):
+        results_data[f'TCI_{i}'] = tci
+        
+    for i, duration in enumerate(durations_array):
+        results_data[f'duration_{i}'] = duration
+      
+    results_data['cons_duration_cumulative_wz_startup'] = cons_duration_cumulative_wz_startup
+    results_data['occLastUnit'] = occLastUnit
+    results_data['TCILastUnit'] = TCILastUnit
+    results_data['durationsLastUnit'] = durationsLastUnit
+    results_data['avg_OCC'] = avg_OCC
+    results_data['avg_TCI'] = avg_TCI
+    results_data['avg_duration'] = avg_duration
+    
+    return results_data
+
+
+
+# # File to store results
+
+# start_time = time.time()
+# results = []
+# all_keys = set()
+
+# with mp.Pool(num_cpus) as pool:
+#     for start in range(0, n_samples, batch_size):
+#         end = min(start + batch_size, n_samples)
+#         batch_results = pool.map(results_sampling, range(start, end))
+        
+#         # Accumulate results and collect all keys
+#         for result in batch_results:
+#             results.append(result)
+#             all_keys.update(result.keys())
+        
+#         print(f"{end} samples", flush=True)
+#         print(f"{(time.time() - start_time)/end} sec/sample", flush=True)
+
+# # Static keys in the desired order
+# static_keys = [
+#     'Num_orders', 'ITC', 'n_ITC', 'interest rate', 'Design completion', 'Design_Maturity_0',
+#     'supply chain exp_0', 'N supply chain', 'Const Proficiency', 'N const prof', 'AE',
+#     'N AE prof', 'standardization', 'modularity', 'BOP commercial', 'RB Safety Related'
+# ]
+
+# # print(all_keys)
+# # Extract and sort dynamic keys
+# occ_keys = sorted([key for key in all_keys if key.startswith('OCC_')], key=lambda x: int(x.split('_')[1]))
+# tci_keys = sorted([key for key in all_keys if key.startswith('TCI_')], key=lambda x: int(x.split('_')[1]))
+# duration_keys = sorted([key for key in all_keys if key.startswith('duration_')], key=lambda x: int(x.split('_')[1]))
+
+# # Combine all keys in the desired order
+# headers = static_keys + occ_keys + tci_keys + duration_keys +\
+#     ['cons_duration_cumulative_wz_startup'] + ['occLastUnit']+\
+#         ['TCILastUnit'] + ['durationsLastUnit'] +['avg_OCC'] + ['avg_TCI'] + ['avg_duration']
+    
+    
+# # Save results to a CSV file
+# with open(filename, mode='w', newline='') as file:
+#     writer = csv.DictWriter(file, fieldnames=headers)
+#     writer.writeheader()
+    
+#     for result in results:
+#         # Ensure all dictionaries have the same keys by filling missing keys with None
+#         full_result = {key: result.get(key, None) for key in headers}
+#         writer.writerow(full_result)
+
+# print(f"Results saved to {filename}")
+
+# # Save results to a pickle file
+# with open(pickle_filename, 'wb') as file:
+#     pickle.dump(results, file)
+
+# print(f"Results saved to {pickle_filename}")
+
+
+
+
+# Static keys in the desired order
+static_keys = [
+    'Num_orders', 'ITC', 'n_ITC', 'interest rate', 'Design completion', 'Design_Maturity_0',
+    'supply chain exp_0', 'N supply chain', 'Const Proficiency', 'N const prof', 'AE',
+    'N AE prof', 'standardization', 'modularity', 'BOP commercial', 'RB Safety Related'
+]
+
+# File to store results
+start_time = time.time()
+results = []
+all_keys = set()
+
+with mp.Pool(num_cpus) as pool, open(filename, mode='w', newline='') as file:
+    writer = csv.DictWriter(file, fieldnames=static_keys)
+    # writer.writeheader()
+
+    for start in range(0, n_samples, batch_size):
+        end = min(start + batch_size, n_samples)
+        batch_results = pool.map(results_sampling, range(start, end))
+
+        # Accumulate results and collect all keys
+        for result in batch_results:
+            results.append(result)
+            all_keys.update(result.keys())
+
+        # Extract and sort dynamic keys (only once, after the first batch)
+        if start == 0:
+            occ_keys = sorted([key for key in all_keys if key.startswith('OCC_')], key=lambda x: int(x.split('_')[1]))
+            tci_keys = sorted([key for key in all_keys if key.startswith('TCI_')], key=lambda x: int(x.split('_')[1]))
+            duration_keys = sorted([key for key in all_keys if key.startswith('duration_')], key=lambda x: int(x.split('_')[1]))
+
+            # Combine all keys in the desired order
+            headers = static_keys + occ_keys + tci_keys + duration_keys +\
+                ['cons_duration_cumulative_wz_startup'] + ['occLastUnit']+\
+                ['TCILastUnit'] + ['durationsLastUnit'] +['avg_OCC'] + ['avg_TCI'] + ['avg_duration']
+            
+            # Update the CSV header
+            writer.fieldnames = headers
+            writer.writeheader()
+
+        for result in batch_results:
+            # Ensure all dictionaries have the same keys by filling missing keys with None
+            full_result = {key: result.get(key, None) for key in headers}
+            writer.writerow(full_result)
+
+        print(f"{end} samples", flush=True)
+        print(f"{(time.time() - start_time)/end} sec/sample", flush=True)
+
+print(f"Results saved to {filename}")
+
+# Save results to a pickle file (optional)
+with open(pickle_filename, 'wb') as file:
+    pickle.dump(results, file)
+
+print(f"Results saved to {pickle_filename}")
+
+
+
+
+ 
diff --git a/Cost_Reduction/orders.png b/Cost_Reduction/orders.png
new file mode 100644
index 0000000..cc6850a
Binary files /dev/null and b/Cost_Reduction/orders.png differ
diff --git a/Cost_Reduction/scenarios.ipynb b/Cost_Reduction/scenarios.ipynb
deleted file mode 100644
index 5bb5cfd..0000000
--- a/Cost_Reduction/scenarios.ipynb
+++ /dev/null
@@ -1,227 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "ee4fa393-2ded-480c-bbf0-547d0cc0ddac",
-   "metadata": {},
-   "source": [
-    "<center><table>\n",
-    "    <tr>\n",
-    "        <th><img src=\"./INL1.png\",align=\"middle\",height=\"10000\"/></th>\n",
-    "        <th><img src=\"./MIT1.png\",align=\"middle\",height=\"10\"\\></th>\n",
-    "        <th><img src=\"./ANL.png\",align=\"middle\",height=\"10\"/></th>\n",
-    "    </tr>\n",
-    "</table>\n",
-    "</center>"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "40096a23-ff7b-4541-b710-9f0a9f9a595d",
-   "metadata": {},
-   "source": [
-    "# <center>Cost Reduction Framework for Nuclear Reactor Power Plants</center>\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f2256ae0-712f-4811-99d9-d37188782036",
-   "metadata": {},
-   "source": [
-    "###  Importing the libraries"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "12fb6329-dc95-493f-ba1d-86235e71b512",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "\n",
-    "import warnings\n",
-    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
-    "\n",
-    "pd.set_option('display.max_rows', None)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "7b9a01a8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Just running the other jupyter notebook to bring all the functions from there\n",
-    "%run CostReduction_exploration_mode.ipynb"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "c31cae49",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def calculate_final_result_avg(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
-    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0):\n",
-    "    \n",
-    "# A function for the average results (averaged over all the reactors built)\n",
-    "\n",
-    "    OCC_list = []\n",
-    "    TCI_list = [] \n",
-    "    durations_list = []\n",
-    "    \n",
-    "    for n_th in range(1, num_orders+1):\n",
-    "        results = calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
-    "        num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0) \n",
-    "        \n",
-    "        OCC_result = results[1] # The ITC_reduced OCC (levelized)\n",
-    "        TCI_result = results[2] # The ITC_reduced TCI(levelized)\n",
-    "        duration_result = results[3] # cons duration\n",
-    "        \n",
-    "        OCC_list.append(OCC_result)\n",
-    "        TCI_list.append( TCI_result )\n",
-    "        durations_list.append( duration_result  )\n",
-    "    last_plant_OCC = OCC_list[-1]\n",
-    "    first_plant_OCC = OCC_list[0]\n",
-    "    avg_OCC = np.mean(OCC_list)    \n",
-    "    \n",
-    "    last_plant_TCI = TCI_list[-1]\n",
-    "    first_plant_TCI = TCI_list[0]\n",
-    "    avg_TCI = np.mean(TCI_list)\n",
-    "    \n",
-    "    avg_dur = np.mean(durations_list)\n",
-    "    \n",
-    "    return last_plant_OCC , first_plant_OCC, avg_OCC,  last_plant_TCI , first_plant_TCI, avg_TCI, avg_dur "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3c0d5583",
-   "metadata": {},
-   "source": [
-    "### Scenarios\n",
-    "These scenarios correspond to the scenarios in the cost reduction report: https://inldigitallibrary.inl.gov/sites/sti/sti/Sort_109810.pdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "6a4a23ef",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "UnboundLocalError",
-     "evalue": "cannot access local variable 'task_length_multiplier' where it is not associated with a value",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[4], line 57\u001b[0m\n\u001b[1;32m     54\u001b[0m     ITC_0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.4\u001b[39m\n\u001b[1;32m     55\u001b[0m     n_ITC \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m4\u001b[39m \n\u001b[0;32m---> 57\u001b[0m avg_results \u001b[38;5;241m=\u001b[39m \u001b[43mcalculate_final_result_avg\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreactor_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_22\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_2321\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mland_cost_per_acre_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRB_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mBOP_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     58\u001b[0m \u001b[43m\u001b[49m\u001b[43mnum_orders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdesign_completion_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mae_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_AE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mce_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_cons\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmod_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDesign_Maturity_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproc_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_proc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstandardization_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minterest_rate_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstartup_0\u001b[49m\u001b[43m)\u001b[49m          \n",
-      "Cell \u001b[0;32mIn[3], line 11\u001b[0m, in \u001b[0;36mcalculate_final_result_avg\u001b[0;34m(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0)\u001b[0m\n\u001b[1;32m      8\u001b[0m durations_list \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m n_th \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, num_orders\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m---> 11\u001b[0m     results \u001b[38;5;241m=\u001b[39m \u001b[43mcalculate_final_result\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreactor_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_th\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_22\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_2321\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mland_cost_per_acre_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRB_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mBOP_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m     12\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnum_orders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdesign_completion_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mae_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_AE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mce_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_cons\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmod_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDesign_Maturity_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproc_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_proc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstandardization_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minterest_rate_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstartup_0\u001b[49m\u001b[43m)\u001b[49m \n\u001b[1;32m     14\u001b[0m     OCC_result \u001b[38;5;241m=\u001b[39m results[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;66;03m# The ITC_reduced OCC (levelized)\u001b[39;00m\n\u001b[1;32m     15\u001b[0m     TCI_result \u001b[38;5;241m=\u001b[39m results[\u001b[38;5;241m2\u001b[39m] \u001b[38;5;66;03m# The ITC_reduced TCI(levelized)\u001b[39;00m\n",
-      "File \u001b[0;32m/var/folders/fn/9991pz_174vgdscjw2zf2tbxtn5546/T/ipykernel_63785/3212539402.py:6\u001b[0m, in \u001b[0;36mcalculate_final_result\u001b[0;34m(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0)\u001b[0m\n\u001b[1;32m      4\u001b[0m reactor_data \u001b[38;5;241m=\u001b[39m (reactor_data_read(reactor_type ))[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m      5\u001b[0m reactor_power \u001b[38;5;241m=\u001b[39m (reactor_data_read(reactor_type ))[\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m----> 6\u001b[0m tot_base_cost_results \u001b[38;5;241m=\u001b[39m \u001b[43mcalculate_base_cost\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreactor_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_th\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_22\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf_2321\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mland_cost_per_acre_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRB_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mBOP_grade_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_orders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdesign_completion_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mae_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_AE\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mce_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_cons\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmod_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDesign_Maturity_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproc_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_proc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstandardization_0\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      7\u001b[0m tot_base_cost \u001b[38;5;241m=\u001b[39m tot_base_cost_results[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m      8\u001b[0m final_construction_duration \u001b[38;5;241m=\u001b[39m tot_base_cost_results[\u001b[38;5;241m1\u001b[39m]\n",
-      "File \u001b[0;32m/var/folders/fn/9991pz_174vgdscjw2zf2tbxtn5546/T/ipykernel_63785/896935451.py:7\u001b[0m, in \u001b[0;36mcalculate_base_cost\u001b[0;34m(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0)\u001b[0m\n\u001b[1;32m      4\u001b[0m direct_cost_updated \u001b[38;5;241m=\u001b[39m update_direct_cost(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0, num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons)\n\u001b[1;32m      6\u001b[0m act_con_duration \u001b[38;5;241m=\u001b[39m update_cons_dur(reactor_data, direct_cost_updated , mod_0)\n\u001b[0;32m----> 7\u001b[0m cons_duration_plus_delay \u001b[38;5;241m=\u001b[39m \u001b[43mact_cons_duration_plus_delay\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreactor_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_th\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDesign_Maturity_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproc_exp_0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mN_proc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mact_con_duration\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      8\u001b[0m final_con_duration \u001b[38;5;241m=\u001b[39m duration_learning_effect(n_th, standardization_0, cons_duration_plus_delay)\n\u001b[1;32m     10\u001b[0m direct_cost_updated_plus_learning \u001b[38;5;241m=\u001b[39m learning_effect(direct_cost_updated , n_th, standardization_0, reactor_power)\n",
-      "File \u001b[0;32m/var/folders/fn/9991pz_174vgdscjw2zf2tbxtn5546/T/ipykernel_63785/1160249579.py:25\u001b[0m, in \u001b[0;36mact_cons_duration_plus_delay\u001b[0;34m(reactor_type, n_th, Design_Maturity_0, proc_exp_0, N_proc, cons_duration_no_delay)\u001b[0m\n\u001b[1;32m     22\u001b[0m     task_length_multiplier \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m100\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m64\u001b[39m\n\u001b[1;32m     23\u001b[0m     ref_construction_duration \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m100\u001b[39m\n\u001b[0;32m---> 25\u001b[0m B_21 \u001b[38;5;241m=\u001b[39m  \u001b[38;5;241m42.1\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[43mtask_length_multiplier\u001b[49m \u001b[38;5;66;03m# months \u001b[39;00m\n\u001b[1;32m     26\u001b[0m B_22 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m60.2\u001b[39m \u001b[38;5;241m*\u001b[39m task_length_multiplier\n\u001b[1;32m     27\u001b[0m B_23 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m14.8\u001b[39m \u001b[38;5;241m*\u001b[39m task_length_multiplier\n",
-      "\u001b[0;31mUnboundLocalError\u001b[0m: cannot access local variable 'task_length_multiplier' where it is not associated with a value"
-     ]
-    }
-   ],
-   "source": [
-    "reactor_type = \"Concept A\"\n",
-    "\n",
-    "# scenario independent params\n",
-    "mod_0 = \"modularized\"\n",
-    "BOP_grade_0 = \"non_nuclear\"\n",
-    "RB_grade_0 = \"nuclear\"\n",
-    "\n",
-    "land_cost_per_acre_0 =  22000 # dollars/acre\n",
-    "startup_0 = 16 \n",
-    "interest_rate_0 = 0.06\n",
-    "\n",
-    "# numb er of projects for full efficiency of procurement, A/E, Construction\n",
-    "N_proc = 3\n",
-    "N_AE  = 4\n",
-    "N_cons =5\n",
-    "\n",
-    "# factory building cost (associated with accounts 22 and 232.1)\n",
-    "f_22   = 250000000\n",
-    "f_2321 = 150000000\n",
-    "\n",
-    "\n",
-    "for scenario in [1, 2, 3 ]:\n",
-    "    if scenario == 1:\n",
-    "        num_orders = 13\n",
-    "        design_completion_0 = 0.8 # 1 means 100%\n",
-    "        Design_Maturity_0 = 1\n",
-    "        proc_exp_0= 0.5 # 2 means procurement experts. This is ideal. \n",
-    "        ae_exp_0 = 0.5\n",
-    "        ce_exp_0 = 1\n",
-    "        standardization_0 = 0.8 # 0.7 corresponds to 70% standardization for PWRs\n",
-    "        ITC_0 = 0 \n",
-    "        n_ITC = 0\n",
-    "\n",
-    "    elif scenario == 2:\n",
-    "        num_orders = 18\n",
-    "        design_completion_0 = 0.6 # 1 means 100%\n",
-    "        Design_Maturity_0 = 0\n",
-    "        proc_exp_0= 0 # 2 means procurement experts. This is ideal. \n",
-    "        ae_exp_0 = 0\n",
-    "        ce_exp_0 = 1\n",
-    "        standardization_0 = 0.7 # 0.7 corresponds to 70% standardization for PWRs\n",
-    "\n",
-    "        ITC_0 = 0 \n",
-    "        n_ITC = 0        \n",
-    "        \n",
-    "    elif scenario == 3:\n",
-    "        num_orders = 13\n",
-    "        design_completion_0 = 0.8 # 1 means 100%\n",
-    "        Design_Maturity_0 = 1\n",
-    "        proc_exp_0= 0.5 # 2 means procurement experts. This is ideal. \n",
-    "        ae_exp_0 = 0.5\n",
-    "        ce_exp_0 = 1\n",
-    "        standardization_0 = 0.8 # 0.7 corresponds to 70% standardization for PWRs\n",
-    "        ITC_0 = 0.4\n",
-    "        n_ITC = 4 \n",
-    "    \n",
-    "    avg_results = calculate_final_result_avg(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
-    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0)          "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8187e003",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
-    "#     num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0)"
-   ]
-  }
- ],
- "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": "3.11.8"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/Cost_Reduction/scenarios_and_sensitivity_analysis.ipynb b/Cost_Reduction/scenarios_and_sensitivity_analysis.ipynb
new file mode 100644
index 0000000..bfdfc25
--- /dev/null
+++ b/Cost_Reduction/scenarios_and_sensitivity_analysis.ipynb
@@ -0,0 +1,398 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ee4fa393-2ded-480c-bbf0-547d0cc0ddac",
+   "metadata": {},
+   "source": [
+    "<center><table>\n",
+    "    <tr>\n",
+    "        <th><img src=\"./INL1.png\",align=\"middle\",height=\"10000\"/></th>\n",
+    "        <th><img src=\"./MIT1.png\",align=\"middle\",height=\"10\"\\></th>\n",
+    "        <th><img src=\"./ANL.png\",align=\"middle\",height=\"10\"/></th>\n",
+    "    </tr>\n",
+    "</table>\n",
+    "</center>"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "40096a23-ff7b-4541-b710-9f0a9f9a595d",
+   "metadata": {},
+   "source": [
+    "# <center>Cost Reduction Framework for Nuclear Reactor Power Plants</center>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f2256ae0-712f-4811-99d9-d37188782036",
+   "metadata": {},
+   "source": [
+    "###  Importing the libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "12fb6329-dc95-493f-ba1d-86235e71b512",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "import warnings\n",
+    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "pd.set_option('display.max_rows', None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "54b734af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "\n",
+    "# Just running the other jupyter notebook to bring all the functions from there\n",
+    "%run CostReduction_exploration_mode.ipynb "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1c0185bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A function for the average results (averaged over all the reactors built)\n",
+    "\n",
+    "def calculate_final_result_avg(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0,\\\n",
+    "        startup_0, ITC_0, n_ITC):\n",
+    "    \n",
+    "    \n",
+    "    OCC_list = []\n",
+    "    TCI_list = [] \n",
+    "    durations_list = []\n",
+    "    \n",
+    "    for n_th in range(1, num_orders+1):\n",
+    "        results = calculate_final_result(reactor_type, n_th, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "        num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc,\\\n",
+    "            standardization_0, interest_rate_0, startup_0, ITC_0, n_ITC) \n",
+    "        \n",
+    "        OCC_result = results[1] # The ITC_reduced OCC (levelized)\n",
+    "        TCI_result = results[2] # The ITC_reduced TCI(levelized)\n",
+    "        duration_result = results[3] # cons duration\n",
+    "        \n",
+    "        OCC_list.append(OCC_result)\n",
+    "        TCI_list.append( TCI_result )\n",
+    "        durations_list.append( duration_result  )\n",
+    "    last_plant_OCC = OCC_list[-1]\n",
+    "    first_plant_OCC = OCC_list[0]\n",
+    "    avg_OCC = np.mean(OCC_list)    \n",
+    "    \n",
+    "    last_plant_TCI = TCI_list[-1]\n",
+    "    first_plant_TCI = TCI_list[0]\n",
+    "    avg_TCI = np.mean(TCI_list)\n",
+    "    \n",
+    "    avg_dur = np.mean(durations_list)\n",
+    "    \n",
+    "    # note that all the OCC and TCI here are TCI-reduced\n",
+    "    return last_plant_OCC , first_plant_OCC, avg_OCC,  last_plant_TCI , first_plant_TCI, avg_TCI, avg_dur   "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "517dc2d3",
+   "metadata": {},
+   "source": [
+    "# Scenarios\n",
+    "\n",
+    "These scenarios correspond to the scenarios in the cost reduction [report](https://inldigitallibrary.inl.gov/sites/sti/sti/Sort_109810.pdf)\n",
+    "\n",
+    "See Table 10\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6d749168",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "Scenario # 1\n",
+      "Last plant ITC-reduced OCC is 3600 ($/kWe)\n",
+      "First plant ITC-reduced OCC is 12800 ($/kWe)\n",
+      "Average ITC-reduced OCC is 5000 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Last plant ITC-reduced TCI is 4200 ($/kWe)\n",
+      "First plant ITC-reduced TCI is 19500 ($/kWe)\n",
+      "Average plant ITC-reduced TCI is 6400 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Average Construction Duration is 77 months \n",
+      "\n",
+      "\n",
+      "Scenario # 2\n",
+      "Last plant ITC-reduced OCC is 3600 ($/kWe)\n",
+      "First plant ITC-reduced OCC is 15900 ($/kWe)\n",
+      "Average ITC-reduced OCC is 5000 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Last plant ITC-reduced TCI is 4200 ($/kWe)\n",
+      "First plant ITC-reduced TCI is 25700 ($/kWe)\n",
+      "Average plant ITC-reduced TCI is 6500 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Average Construction Duration is 77 months \n",
+      "\n",
+      "\n",
+      "Scenario # 3\n",
+      "Last plant ITC-reduced OCC is 3600 ($/kWe)\n",
+      "First plant ITC-reduced OCC is 8000 ($/kWe)\n",
+      "Average ITC-reduced OCC is 4100 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Last plant ITC-reduced TCI is 4200 ($/kWe)\n",
+      "First plant ITC-reduced TCI is 14700 ($/kWe)\n",
+      "Average plant ITC-reduced TCI is 5500 ($/kWe)\n",
+      "\n",
+      "\n",
+      "Average Construction Duration is 77 months \n"
+     ]
+    }
+   ],
+   "source": [
+    "reactor_type = \"Concept A\"\n",
+    "\n",
+    "# scenario independent params\n",
+    "mod_0 = \"modularized\"\n",
+    "BOP_grade_0 = \"non_nuclear\"\n",
+    "RB_grade_0 = \"nuclear\"\n",
+    "\n",
+    "land_cost_per_acre_0 =  22000 # dollars/acre\n",
+    "startup_0 = 16 \n",
+    "interest_rate_0 = 0.06\n",
+    "\n",
+    "# numb er of projects for full efficiency of procurement, A/E, Construction\n",
+    "N_proc = 3\n",
+    "N_AE  =  4\n",
+    "N_cons = 5\n",
+    "\n",
+    "# factory building cost (associated with accounts 22 and 232.1)\n",
+    "f_22   = 250000000\n",
+    "f_2321 = 150000000\n",
+    "\n",
+    "\n",
+    "\n",
+    "for scenario in [1, 2, 3 ]:\n",
+    "    if scenario == 1:\n",
+    "        num_orders = 13\n",
+    "        design_completion_0 = 0.8 # 1 means 100%\n",
+    "        Design_Maturity_0 = 1\n",
+    "        proc_exp_0 = 0.5 #     \n",
+    "        ae_exp_0 = 0.5\n",
+    "        ce_exp_0 = 1\n",
+    "        \n",
+    "        standardization_0 = 0.8 # 0.7 corresponds to 70% standardization for PWRs\n",
+    "        ITC_0 = 0 \n",
+    "        n_ITC = 0\n",
+    "\n",
+    "    elif scenario == 2:\n",
+    "        num_orders = 18\n",
+    "        design_completion_0 = 0.6 # 1 means 100%\n",
+    "        Design_Maturity_0 = 0\n",
+    "        \n",
+    "        proc_exp_0= 0 # 2 means procurement experts. This is ideal. \n",
+    "        ae_exp_0 = 0\n",
+    "        ce_exp_0 = 1\n",
+    "        standardization_0 = 0.7 # 0.7 corresponds to 70% standardization for PWRs\n",
+    "\n",
+    "        ITC_0 = 0 \n",
+    "        n_ITC = 0        \n",
+    "        \n",
+    "    elif scenario == 3:\n",
+    "        num_orders = 13\n",
+    "        design_completion_0 = 0.8 # 1 means 100%\n",
+    "        Design_Maturity_0 = 1\n",
+    "        \n",
+    "        proc_exp_0= 0.5 # 2 means procurement experts. This is ideal. \n",
+    "        ae_exp_0 = 0.5\n",
+    "        ce_exp_0 = 1\n",
+    "        standardization_0 = 0.8 # 0.7 corresponds to 70% standardization for PWRs\n",
+    "        ITC_0 = 0.4\n",
+    "        n_ITC = 4 \n",
+    "     \n",
+    "     \n",
+    "    avg_results = calculate_final_result_avg(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "    num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0) \n",
+    "    \n",
+    "    \n",
+    "    print(\"\\n\")  \n",
+    "    print(f\"Scenario # {scenario}\")\n",
+    "    \n",
+    "    # note the results are rounded to the nearest hundred\n",
+    "    print(f\"Last plant ITC-reduced OCC is {int(100*np.round (avg_results[0]/100, 0))} ($/kWe)\")\n",
+    "    print(f\"First plant ITC-reduced OCC is {int(100*np.round (avg_results[1]/100, 0))} ($/kWe)\")\n",
+    "    print(f\"Average ITC-reduced OCC is {int(100*np.round (avg_results[2]/100, 0))} ($/kWe)\")\n",
+    "    print(\"\\n\")\n",
+    "    print(f\"Last plant ITC-reduced TCI is {int(100*np.round (avg_results[3]/100, 0))} ($/kWe)\")\n",
+    "    print(f\"First plant ITC-reduced TCI is {int(100*np.round (avg_results[4]/100, 0))} ($/kWe)\")\n",
+    "    print(f\"Average plant ITC-reduced TCI is {int(100*np.round (avg_results[5]/100, 0))} ($/kWe)\")\n",
+    "    print(\"\\n\")\n",
+    "    print(f\"Average Construction Duration is {int(np.round(avg_results[6],0))} months \")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98846560",
+   "metadata": {},
+   "source": [
+    "# Sensitivity Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "93dacf75",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of orders = 4\n",
+      "number of orders = 5\n",
+      "number of orders = 6\n",
+      "number of orders = 7\n",
+      "number of orders = 8\n",
+      "number of orders = 9\n",
+      "number of orders = 10\n",
+      "number of orders = 11\n",
+      "number of orders = 12\n",
+      "number of orders = 13\n",
+      "number of orders = 14\n",
+      "number of orders = 15\n",
+      "number of orders = 16\n",
+      "number of orders = 17\n",
+      "number of orders = 18\n",
+      "number of orders = 19\n",
+      "number of orders = 20\n"
+     ]
+    }
+   ],
+   "source": [
+    "startup_0 = 16\n",
+    "interest_rate_0 = 0.06\n",
+    "design_completion_0 = 0.8\n",
+    "Design_Maturity_0 = 1\n",
+    "proc_exp_0 = 0.5\n",
+    "ae_exp_0 = 0.5\n",
+    "ce_exp_0 = 1\n",
+    "\n",
+    "mod_0 = 'modularized'\n",
+    "standardization_0 = 0.8\n",
+    "BOP_grade_0 = 'non_nuclear'\n",
+    "ITC_0 = 0\n",
+    "n_ITC = 0\n",
+    "RB_grade_0 = 'nuclear'\n",
+    "\n",
+    "reactor_type = \"Concept A\"\n",
+    "\n",
+    "\n",
+    "\n",
+    "TCI_list_avg = []\n",
+    "OCC_list_avg = []\n",
+    "orders_list = []\n",
+    "for num_orders in range(4,21):\n",
+    "    print(f\"number of orders = {num_orders}\")\n",
+    "    OCC_list = []\n",
+    "    TCI_list = []  \n",
+    "    # for n_th in range(1, num_orders+1):\n",
+    "    results = calculate_final_result_avg(reactor_type, f_22, f_2321, land_cost_per_acre_0, RB_grade_0, BOP_grade_0,\\\n",
+    "num_orders, design_completion_0, ae_exp_0, N_AE, ce_exp_0, N_cons, mod_0, Design_Maturity_0, proc_exp_0, N_proc, standardization_0, interest_rate_0, startup_0)\n",
+    "        \n",
+    "    \n",
+    "    OCC_list_avg.append(results[2])\n",
+    "    TCI_list_avg.append(results[5])\n",
+    "    \n",
+    "    orders_list.append(num_orders)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7706a195",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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edYUdO3YIUrsu6LOE+y5MuO/CRMi+Z2dnM9VnCcu6s2531vos4b4LE6H6zj0Xpj7ruluSeh1gqivExsYiJycHADBp0iSDq/JrLjy+c+dOneO7d+/Wm1YTOzs7vPDCCwCAq1ev4ubNm1rHCwoKcOLECQDAgAED0LhxY735REREwMnJyWBZ6jL1eYG2+q7PEu67MOG+CxMh+25s+vt/HZZ1Z93urPVZwn0XJkL1nXsuTH3WdbckPMBUA5w+fZq+79u3r8F0Xbp0gb29PQDgzJkzBvNp1aoVGjRoYDAfTY2K+cTHx9NFxIyVRSqV4tlnn6XnlJWVGUxb12jWrJkgteuCPku478KE+y5MhOy7jY0NU32WsKw763Znrc8S7rswEarv3HNh6rOuuyXhAaYa4O+//6bvAwMDDaaztram0940zwHKRx6lpaVVmkfF4xXzMbUsmscVCoXOSKi6jL6pg0LQrgv6LOG+CxPuuzARsu9CugmtiJBv/lnrs4T7LkyE6jv3XJj6rOtuSXiAqQa4f/8+AMDe3h4uLi5G0zZp0gQA8OTJE63tCtPS0uiOdoamtVXMQ1Nb3/+rk09lWL/yCrBhA1BSYtZ5NUF0dLTFNeuCdl3QZwn3XZhw34WJkH3Py8tjqs8SlnVn3e6s9VnCfRcmQvWdey5MfdZ1tyTC3QO5BsnPzwcAODg4VJpWPUUOKB+1pI5mqvMwJZ+KeegrS3XzUSOXy7UCYeovh/jgQeDAAZB334Vi9Wqohg41qlWTKJVKrTJZEpbaLPXVmkKsO2ttlvrcd+47K1j7XlpaCkIIVCoVk3UTWGiqf+RS19uSxMbGol+/fnqPyWQyuLu7o127dggPD8fLL79s0v1WVWC9RsZ/1ff79+9j69atOHbsGG7duoUnT55AqVTCzc0Nbdu2RZcuXTBlyhQ0b968VvQrg/tes/rFxcVo1KgRfWaYP38+5s6dqzdtTWjfv38ffn5+NK+1a9di4sSJlZ4nxPV4WPbzaqqqq1QqsXPnTuzduxcJCQl4/PgxSktL4e3tjcDAQAwdOhQvvfRSpYM9KuqXlZVhx44dOHz4MBISEpCRkYG8vDw4OzujWbNm6Nq1KyIiIhAaGmpwnWVNEhMTsXPnTsTExOD+/fvIzMyEjY0N3N3dERQUhP79+2Ps2LGVltNQ2QkhKC0thUgkMvk8S99PiYj6SvsPkJKSQv84TZo0CevWratSPvPnz8eCBQsAlO/4FhwcbDS9v78/7ty5gyZNmiA1NdVo2okTJ2LDhg0AyjtE9Sij06dPo0+fPgCAuXPnYuHChQbzUKlUdGe4fv364fjx4/TYlClTsGbNGgDA7du34efnZzCfNWvW0J3tNmzYgAkTJuik0WwLTXIBOAFQXzxbxo3DjUqm5HE4HA6HUx+wt7dHz5494ePjA2tr/ltcbXPu3DmMGTPGpLSNGzfGmjVr0LZt21ouFTu6d++OtLQ0jBkzBsuWLWNdnCojl8uxePFirF+/vtIHHJFIhGHDhmHu3Lnw8fGxUAmFSW1fX7t27cI777xD/+/r64uzZ8/WuI6aH374ge6ODQC9evXC1q1ba02PY3ni4+Px0Ucf4caNG0bTubq6Yvbs2XjppZdMyvfIkSNYsGAB7t27V2laPz8/fPbZZ+jfv7/e4+np6Zg7dy6OHDlSaV4ymQyvv/46pk+fDltbW5PKCpQva5Oeno6zZ8+isLDQ5PNKSkqwePFi5Obm0k2+ahN+11QDyGQyAKbtPKP5B1bzglLnYUo+hvKoyXzUzJ49Gx988AH9f15entbUOhEAIhJh3OHDKP35Z0BDv7a4ePEiOnXqVOs6dU2bpb5cLsd3332H999/n9kcYu47911I2iz1ue8X0aZNG6SlpcHDw0Pr76olKCoqgp2dnUU1gfJftB8/fgxvb2+zfhmtCdzc3Oj7qVOn4q233qL/z8zMxPXr17Fs2TLcuHEDaWlpmDRpEv7++284OjrWWBlYtbs+ffWPiLa2tkY3fakJasv3rKwsjBkzBufOnQMAODo6Yty4cQgNDUXjxo0hkUjw6NEjnDt3Djt27MDt27exb98+hISEYPr06TVWjsqoS75bCvX1BaBWvu979+4FUD6ToqCgACkpKbhz5w6ee+45rXQ1Vfc9e/Zo6Z07dw4KhcLoUiEsfWepzbKfB6pW96ioKEycOJE+t4aEhGDcuHEIDAyEjY0N7t27h/379yMyMhLZ2dmYNWsWHj16hKVLlxrVX7x4MT799FM6qqtfv34YPnw4WrduDRcXFzx9+hQ3btzAvn37cPz4cdy5cwfffvut3gEZFy9exPDhw/Hw4UMA5ZuFjBs3Ds899xy8vb1RWlqKO3fu4PTp09i9ezeysrKwfPlyTJ482ayRmyUlJSgoKMAbb7xh1v3ZkydPsHjxYpPTVxceYKoB1Dc4hqaZaaIZbdQc4q15k1RZPobyqMl81NjY2FR6AYsIAXJyYLNvH6DnS1fT3L17l+6AZ2lYatcFfVOuh9qC+859F5J2XdAXsu8dO3aESCSCWCw2aUh8TSKXy2ttCpgx1NMG1PW2JJp63t7e6NChg9bx0NBQTJkyBUOGDEF0dDQePnyI3377DTNmzKixMrBqd2P6lvCiNnxXqVR48cUXaXApLCwMa9euhZeXl07a4cOHY+bMmTh06BA+/PBDi19/ddF3S1LT7f3w4UOcOHECADBv3jwsWbIEWVlZ2LhxI3r16qWVtibqHh8fj2vXrgEAvvnmG0ybNg0KhQKbN2/Gxx9/bPA8lu3OUptlPw+YX/eLFy/i5ZdfRmlpKaRSKdavX49x48ZppenevTteeOEFzJw5E8OGDcP9+/fx7bffokWLFlo/Vmjqb9iwAXPmzAEAeHp6YuvWrQgJCdHRHzhwIN555x1cuXIF7733HrKysnTaLSMjA+Hh4TS49Mknn2DevHk6909t2rTBpEmT8N133+Hrr7/GF198YfY9hlgshkgkglQqNev+zNL3cnyR7xpAHSEvLCxETk6O0bTqxbQ9PT21zNaMsqt3k6ssD0B7oe6azMdsxGJg167q5cHhcDgcDoejB6lUivnz59P/Hzt2jF1hOEZZvnw5Xb6hf//+2LNnj97gkhqxWIyJEyciMTFRJ7jIqV9s3LgRSqUSVlZWePnll/HCCy8AALZt21Yr68CsX78eQPnUqMmTJ2PAgAEAgN9//73GtTiWRaVS0eASAL3BJU06dOiA6OhoGsCaMWOG3qVrHjx4QANPdnZ2iI2N1Rtc0qR9+/Y4duwYZs6cqXPszTffpMGl+fPn4/PPPzca0HF0dMSCBQtw4sQJODs7G9Wtr/AAUw3Qpk0b+l4dRdeHQqHA7du3AQCtW7fWOubg4ECDPMbyqHi8Yj6mlkXzuLW1NVq0aGE0baWoVMDTp9XLw0TGjx9vEZ26pl0X9FnCfRcm3HdhImTf3d3d9R8oKSnfvXXUKCA4uPxfRru5siIoKIi+r2z32+vXr+Pdd99F27Zt4ezsDFtbW/j5+eGVV15BUlKSTnrNdn/48CFWrlyJ0aNHo2XLlrC3t4eNjQ18fHwwfPhwbN261eSFalNSUvDRRx+hc+fOcHd3h0wmQ/PmzRESEoJvvvmGPgC5u7sjODgYIpGIrgeyfv16iEQirZehdUHPnDmDl19+Gb6+vpDJZHBxcUGnTp3w6aef4smTJwbLFxsbCx8fH1hZWSE2NhYqlQpr1qxBSEgIvL29IRaLMXnyZJPqCpQvmKuemiKTybB27dpK1zFTt33jxo0RGhqqN01paSlWrlyJkJAQeHp6QiqVokGDBggLC8PGjRuN+jF58mSIRCL4+voCAHJycjBv3jy0bdsWTZs2hYuLC/r06YNNmzaZVMf8/Hx88803CA0NRYMGDWBjY4NGjRqhe/fu+Oijj/ReX2oIIYiKisKoUaPQpEkT+Pj4wNXVFd26dcOiRYuM/lBdsR7p6en44IMPEBAQADs7O3h6eiIsLAyHDh3Se37F62v79u2wsrIy6foyFfU6s/369UODBg3odKLs7Gzs27dPK63Bvs5ESktL6VpLY8aMgVQqpXp///03Lly4oHPOggULIBKJ4OHhgZs3b1aqERYWBpFIBG9vbygUCr1p4uPj8frrryMgIAAODg6wt7dHYGAgpk2bpldDXe9169bRdk9JSYFcLseyZcvw7LPPwsPDAyKRSCuoXlpain379uGdd95B165d4erqColEAnd3d3Tv3h3z589HZmZmpXUCytf+jYiIgLe3N2QyGfz8/DB16lTcunULwL/XSmXXQ1paGmbPno2goCC4urpCJpOhadOmGDt2LGJiYgzW3RT27duHv/76CwAwdOhQo8ElNS1atMBnn30GoHyx+e+//15H/7vvvqOzeBYsWKD17GwMsVisMz3ur7/+olM0n3nmGXz66acGz69Y9z59+jDb2KDWIf8h7t69S1C+7jSZNGlSlfP57LPPaD4xMTGVpj9y5AhNv3jxYoPp4uLiaLrZs2frHB8/fjw9/vDhQ4P5vPnmmzTd9evXtY7l5eURqVRKAJDBgwcbzEMulxMnJycCgPTo0aPSOqrJzc0lAEguQIjmSywmJCLC5Hyqw+7duy2iU9e0WeqXlJSQ+fPnk5KSEib6hHDfWcB9576zgrXvxcXFJDk5mRQXF1tcPzs7W/fDPXsIcXX99++t5r+uroTs3VttXaVSSdLT04lSqax2XuYSExND72s+++wzg+mKi4tpug4dOhhMt3DhQmJtbU3TVnyJRCIyb948rXPU7a5QKIhYLDZ4rvo1YMAAkp+fb7ReS5cuJRKJxGg+ffv2pfp9+/atVFedXo1SqSTTpk0zeo6zszM5evSo3jKeOHGCpjt06BDp37+/zvnm3FPv27ePnjdhwgSTztF7zWuQkpJCWrdubbSOvXr1IllZWXrPnzRpEgFAmjVrRv7++2/i6+trMJ9p06YZLcuxY8eIh4dHpT7pIyMjg/Ts2dPoed7e3uSPP/6otB4JCQnEy8vLYD7Tp0/XOb8q15c5JCUl0Xx+//13+rmfnx8BQMLDw7XSV+Z7ZezcuZPqnTp1ihBCSGFhIXFwcCAAyP/+9z+dc27dukXPmT9/vtH8nzx5QvsRfXmVlZWRt956y2h7SiQS8uuvv2qdp6732rVrabqEhATSsWNHnfM1+0O1/8Ze7u7u5MyZMwbrpFQqyaxZs4hIJNJ7vqOjIzly5Ai9VoxdD7/99huxtbU1Wp4pU6aQsrIynbqbwsiRI2k+hvovfeTk5NByubu7E5VKRY89ffqUeHp6EgDE3t6e5ObmmpyvPmbMmEHL+NtvvxlNW93rnRBS5XuTjIwMAqDa9TUVPoKpBggODqZD3NavX08XC6uI5q52I0eO1Dk+YsQIvWk1KSoqwrZt2wCUj1YKCAjQOu7o6Ei3+j1+/LjBaXI7d+6k24fqK4vZqFRATeRjAkVFRRbRqWvadUGfJdx3YcJ9FyZC9l2pVGp/sHcvMGIEoB7ZoB6pof43JwcYPrw83X+c5ORk+l49iqMi8+bNw7x586BQKPDcc8/ht99+Q1xcHC5cuIBNmzahR48eIIRg4cKFWL58OT1P3e7qe7jQ0FAsXboUhw8fRmJiImJjY7FmzRr06NEDQPkUvWnTphks66JFi/Dhhx+irKwMLi4u+OSTT3Ds2DEkJSUhOjoaX3/9NXr27EkX2lUqlVi7di2uXLmCRo0aAShfn+jKlStar7Vr12rpfPzxx1ixYgUAoHnz5vj5558RHx+PmJgYvP/++5BIJMjNzcWwYcNw6dIlo+370Ucf4fjx43j++eexc+dOJCYm4uDBgxgyZIjR8zQ5efIkfT9s2DCTztG55jUoKChAaGgo/v77bwDl98p79+7FhQsXsH37dvTt2xdA+QiuYcOGGc2rqKgIzz//PLKysvDpp58iNjYWx48fx6pVq+gSEytWrDC4C1RMTAyGDBmCzMxMWFlZYfLkydi1axcSExNx9uxZrFq1ChEREZBIJDrnFhYWom/fvjh79iykUinefPNN7NmzB9HR0Th9+jQ+//xzuLu74/HjxxgyZIjRXa2KioowZswY5Obm4uOPP8apU6dw/vx5/PDDD2jYsCEA4Pvvv8e3336rdV7F62vQoEG4dOmS0evLHNTT1ezs7LSeLdQ7eh0+fFhrNJ0xr8zR8/X1pes7aWpv2bIFZWVlWuf4+/uje/fuAFDpiLWtW7fSUUv6diWbMmUKfvrpJwDAkCFDsHHjRsTHxyMhIQGrVq1C27ZtUVZWhjfeeENr9Ja+ek+ZMgWXLl3CxIkTceDAASQmJmLXrl20rED5TBg/Pz/MmDEDW7duRVxcHBISEhAVFYWpU6dCKpUiKysLI0eOREZGht46RUZG4quvvgIhBK6urli8eDHOnTuHc+fOYcmSJbC2tsa4cePolC9DrFmzBq+99hqKi4vRrl07LF++HGfOnEFSUhJ27NiBsLAwAMDq1avx0UcfGa27IU6fPg2g3FNDIxv14ezsTHdmz8rK0vq7kZycTK/B3r17V3tHNXP6u+pe7/UKi4SxLASrEUyEEDJ37lx6zldffaVz/Ny5czQKbigaXFpaSvz9/QkA4uTkRG7duqWT5u2336Y6a9eu1ZuP5q9Rzz//PFEoFFrHnzx5Qpo2bUoAEBcXF/L06VOT6kiIgRFMIlH5L6gW+qVX/SsFC1hqs9SvCyMauO+Wh/vOfWcFa99ZjmDKy8v79z/FxeV/X0Ui7VHDFV818He4Poxg0hzprTlCQk18fDwdffTpp5/qzUOpVJIJEybQX+vVvyqr212lUpGbN28aLe+8efMIUD4S6saNGzrHExMTaTkCAgLI/fv3DealPqbpe7NmzUy6l718+TLVadeund5fyA8dOkTTdOvWTee45j0jADJ37lyjmpUxYMAAmpe+ttGH1jVfgZkzZ9L89HmqUqnISy+9RNOsXLlSJ43myA8XFxdy9epVHe2bN28SmUxG750rUlRURBo2bEgAEDs7O6PPB6mpqTqfvfPOOwQoH02WkJCgt+4pKSlUQ9/oL816SCQScvLkSZ006enppHHjxrScjx8/1kmjvr7GjBlTY9/3srIyOqLqxRdf1Dp2/fp1Wu7vv/+efm7M98rIzMykowM/+eQTrWOaM0v27Nmjc+4PP/ygNXLIEM899xwBQPz9/XWORUVF0TxWrVql9/zi4mISGhpKABBfX186kkddb80RTADI6tWrjdb51q1bWqNxKnL58mU6ekvfd6WkpIR65ObmpjMLhpByr9zc3GiZ9D2zpqamEjs7O9pHaY5Q0uSTTz4hAIhYLKZapnqelpZGy2DOTBs1s2fPpudv2rSJfv7bb7/RzyteN1VBfQ02atSo0rTVud7V1JcRTPU6wHT69Gmydu1a+lq6dCm9aHr27Kl1zFAwhhCik2748OE0n48++kjr2OnTp/XmkZeXRwICAuh5b7zxBomOjiZxcXHkiy++oF94W1tbcvHiRYNlOXDgAL0R8Pb2JsuXLyfnz58nhw8fJqNGjaL59+rVSydwpMm4ceNo2pCQELJnzx6SkJBA1qxZQ4NYAMjPP/9sanMTQowEmGpgeL6pZGZmWkyrLmmz1K8LD5zcd8vDfee+s4K17ybfxKlUhBQU1OirLCfn3/+vWmU8sFTx9dtvVdZV5uWRBzdvEmVenv40Rh5sqouxAFNmZiY5ffo0GTJkiNYDR2lpqU4+6vukzp07G30Qy87OJjY2NloPh4YekvShUCjoNKmvv/5a57j6HkwkEpGkpCST8tTUNzXApDk9Jy4uzmC61157jaaLj4/XOqYZYAoICDB6b2kKnTp1ovmZ+jBjqO1LSkqIi4sLAUDatGljsGy5ubnE3d2dpquIZmDmhx9+MKit9s3V1VUnj59//pnm8d1335lULzVPnjyhwSvNAEtFfUIIWblyJQ0gFRYWGqzHO++8Y1Bv69atNJ2+H71rI8CkOTXy4MGDOse7du1Kv5tqzPnOVWT58uVULzk5WeuYQqGggbpRo0bpnPv48WP6o/97772nN3/NQQsVp9MSQkjnzp0JADJy5Eij5UxOTqb5HDt2jBDyb701A0yhoaEm1bsy3nvvPRpwrkhkZCTVW7ZsmcE8vv/+e6MBJvW0sEaNGhn9G1lWVkZ8fHwIADJnzhz6mSn8+eeftAyVtbE+li1bpvc7/+233+oNdlYF9TMxANKpU6dK01fnelfDA0wWwJS5qJovQ5iTh7E/9jdv3iQtW7Y0eK6TkxPZt29fpfX69ddf6TpK+l7dunUjT548MZpHUVERCQsLM5iHWCw2+iuhIdRfphzNX1MHDjQ7n+qwefNmi+rVFW2W+nXhgZP7bnm479x3VrD23eSbuIIC8wJA9flVUFBrba4ZYDL2sra2JhMmTNB7k1xaWkp/Vf/yyy8r1ezSpQsBQF599VVCiOGgpnpk17Vr18iVK1foS71eyssvv6yTXh0UCQ4ONrkNNPVNDTCp7zn1BVU0OX/+PG3DL774QuuYZoCpuqOXCCGkRYsWND9Tg1WG2v7s2bM0L32BEk00g20PHjzQOqZ+XhCJRDpamv/X/KG64miw8PBwApSPCqoY+KmMjRs30nwrrrFasTxXr16laSuO5NR87klMTDSoV1paSq/BgXru0WsjwDRmzBgCgHh5eel9kNYMWqgDQtX5IUEdsAoKCtJ7/P333ycAiI2Njd6Rfeq1xho2bKi3DT7//HNa3mvXrmkd0xxdExkZWWlZ1cHohQsXEkL+rbdmgKmy0Uv6ePr0Kbl16xa5evUq7Zfmz59Pn/MqBuHVgWaxWGy07bOysugaTfoCTOrv+JtvvllpGUePHk00A2imen769GnaNqau5abJqlWr6Pn/93//Rz9Xj6oCKl8zqTI0r4NevXpVmr4mfjirLwEmvgZTDdKiRQtcvHgRS5YsQZcuXeDi4gI7Ozu0atUK77//Pi5fvmzSfPTXX38diYmJeP311+Hn5weZTAZ3d3f06tULP/30E86ePQsPDw+jedja2uLAgQPYtGkTBgwYAC8vL0ilUjRp0gQvvvgizpw5o7UzgbmowsKAuXPL/1NaClSY48zhcDgcDodTkwQEBGDWrFl6181ITk6m62fNnj1bZ/e1ii/1DlOPHj3SyYsQgo0bNyIkJAQODg7w8fFBYGAg2rdvT19//vknAOjs2nT37l26E5h6HZDaQC6X0x2qNNdp0UenTp3oukBXr141mK5Dhw7VLpejoyN9r96pqapolrWyOmoeN1RHDw8Po7tYubm50ff5+flaxy5evAgA6NKlC+zs7IyWpSKau5k1bNhQ6zpU7xamfrVr146m1XdtAoBUKjXqlUQiQadOnQAY97umyMnJwd5/1oAbN26c3l0DNT///fffq6V37do1JCQkAIDOrl5q1J/L5XK605wmo0aNAlC+Y2R0dLTOcfX6TF26dEGrVq20jmn6OX78+Er7GnUfYchPwPTv3pUrV/Dqq6+iYcOGcHNzQ4sWLdCuXTvaL6mf7VQqFbKzs7XOVV8LTZs2haurq0ENNzc3+Pn56T2Wm5tLd5r75ZdfKq17VFRUpXXXh2Y/UlBQYNa5Fc/R/Hvh4OBA31e3f6rJvu6/hvF9Q+s469atM7gYtjkQA4tyVwV7e3vMmjULs2bNqlY+7dq1w6+//lrt8rz44ot48cUXq51PRRRr1wKensCQIcCzzwL/LFJpCdQLbLKApXZd0GcJ912YcN+FSb3x3c4OqMLNrzHkcjlsbGzK//Pii8D+/f8u6G0MsRgYNgzYvLlKuiqVCo8fP6Zb0+tg5kN1VXnrrbfw9ttvAyhf1PbBgwfYu3cv1qxZg+TkZAQHB+PcuXM6D32GFrWtDHVQSv3gUVJSgoiICINbvVekuLhY6/+aASf1gsumoPngYwqaD4/e3t5G06q3Mn/06BGePn1qMJ2xh05T0fwB9PHjxyYtomuo7pplrayODRo00HueJvoCQ5ramtd9xQV51b6a46ma6l6bFXFzc9MbxNFE3V7G/K4ptm7dCrlcDsBwwMfLywsDBgzAoUOHsHHjRnz++edmX/Nq1It7W1lZYfz48XrTBAUFoU2bNkhOTsbvv/+ON998U+v4Cy+8gJkzZ6KwsBCbNm1C//796bE///yTLgytb3HvmuprNDHlu7d69WpMnTqVLjxeGRX7JnWfYSzIqsbT0xO3b9/W+bw26q4PzTKaG5wCyvsefXmpF7ivmKYqODk5QSKRoKyszKS8qnq910fqdYCJUwdg8BCQm5trcc26oF0X9FnCfRcm3Hdhwtp3zYdVo4hEgL19jeorRaJ/gzmjR5u+O5xKBYwZU/XyqFQgdnbl5+sLMFkILy8vrVEcHTt2RFhYGMLDw/H888/j6dOnePHFFxEfHw8rKyuaTjMgsHTpUgwePNgkPft/2kt9/ueff06DS3379sW0adMQFBSEBg0awNbWlgYh+vTpg9OnTxv9kVJkxo9v1dlhyBQdU35M1WzPqvLMM8/g2LFjAICkpCS0bNmy0nNMqXtldazqj8Xmtrs5nlbUkEqlSExM1DpWXFwMW1tbveepd7arShlq8sfzytAckdStW7dK06elpSEmJqZKPySoVCo6ukipVJoU8Dt37hxu3bqFFi1a0M9kMhmGDx+OzZs3Y+fOnfjpp58gk8kAAJv/CdKLxWKMHTtWJz/Na2bTpk0mjz5SB5H0XXOVffeuXbtGg0teXl748MMPERoaCl9fXzg6OtIRimvWrMGUKVMA1M41oFn29957j2pVhlQq1TnfGD4+PvDw8EBmZiYuX74MpVJpVv+UlJRE3z/zzDP0fdu2bfWmqSrPPPMMLly4gAcPHtAfaAwhpF3keICJUzPk5AA//gjMmgX804nUFsnJyVqdhSVhqV0X9FnCfee+C0m7LuizhLXvFUfHWJLi4uJ/R1qMGQNMn17+N9bYw4JIBLi4lAek/qMMHToUU6dOxcqVK5GUlIR169ZpPdxo/kpdVlamFaQyBfWD/m+//QYA6NWrF6Kjo/WP5gJ0pp+o0RzB8+DBA7P0zZl6pTniobJf+BUKBR3JojkNrDbo27cvvv76awDAgQMH9D6gV8RQ3TXL+ujRIwQEBBjMQ3MEgTl1NLXdPTw8kJaWZpanatTXZmlpKdzd3bWCIllZWSaNKNEkKyur0gdu9UiT2vb71q1bOHfunNnn/f777+jYsaPZ0w2jo6Nx//59s/U2bNiABQsW0P8XFxdjwoQJ2Lx5M/Ly8rB//36MHj0ahBBERkYCAPr166c3gKXpV8VpjaZg7ncdKJ+1o1AoYGVlhdjYWLRu3VpvOkP9EvBvn5GVlVWp3pMnT/R+rln3oqKiWqu7SCRCr169sHv3bhQVFeHEiRMYOHCgSRq5ubk4ffo0gPLrv02bNvSYr68vDVydPn0aeXl5Jo2yNETfvn3plMkDBw7g1VdfNZi2Kr7XV/gaTJzqQwjQp0/5mkw//si6NBwOh8Ph/DeQyYB/poMYnIqu/nz9+vL0/2E+++wzOuJowYIFKC0tpcfatm1LfyU/evRolfJ/+vQpDda88MILBoNLBQUFuH79ut5jzZs3pw9yp06dqlI5TBmhYmNjQ0cHnT9/3mjaixcvouyftTLNfSA0l4EDB9JpKNu3b0d6enqV89Isa2V1jI+P13teTREUFASgfP0dQ1PXDKFeDwmo+rWpSWlpKS5dumTwuEKhoGuE6WuLqozCMoTm6KWffvoJkZGRRl/qkYU7d+6s0ro1aj0bGxts2rSpUr3OnTsDKA8wVRzRM2DAAHh6egL4d9TSqVOnkJaWBkD/9Dig5v00hb/++gtA+YgZQ8ElQHt9qIqoR++kpqYanTr59OlT3LlzR+8xT09P+Pj4AACOHz9eqyPlJk2aRN//8MMPJp/366+/0umBkyZN0rreRSIRJk+eDKB83ST1DwpVRZ0XACxfvlxQo5SMYpGlxDn/GdS7yGVkZGgfWL26fJcZZ2dCKtnhrrrUxDaP9VGbpX5d2FWK+255uO/cd1aw9r2qO7XUBCqVSvfDPXsIcXUt/zsrFmv/6+pKyN691dZV75ZWU7tKmYPmLnKV7XD7wQcf0LS//vqr1rEhQ4bQY+fPnzerDCqVijx69Iiev3jxYoNpNbfA1rfL0ksvvUR3LUtKSjJZX01gYCABQMaNG2f0HM2d0+Li4gyme+ONN2i6+Ph4rWOau8jFxMSYVNbK0NwKfNCgQZXuJqeu+/3798mJEyfo5yUlJXQ3tLZt2xrMJy8vj+7UpW9HPfXua82aNTOoTYj2rl53797VSqe5K9V3331ntD4VSUtLIxKJhAAgzzzzjFb/pvf7bgDNXeTeffddg+m2bdtmdPc99fU1fPjwan3fVSoVad68OQFA2rVrZ9I5+/bto2Vbv369WXoFBQXE3t6eACDDhg0z6Zzly5fr3ZVP3e7vvPOO1m5zr7/+OgFAZDKZ0R232rRpQ9Pdu3fPrHqotY1dbxUZPHgwAUACAwMNpnn48CGxtbU1mOfmzZvpsWXLlhnMR3PHP339m2a/s23bNqPlrog517tSqaTXKkzcse/mzZvEwcGBepOSkqKjn5aWRncctbe3J3///bfJ5dmwYYPO588//zwt46JFiwyeX7Hup06dInfu3DFJWw3fRY4jLCZNAjp2BHJzgc8+q1Wpw4cP12r+dVW7LuizhPsuTLjvwkTIvutdf+r554EHD4ANG4ARI4Dg4PJ/N2wo/zw83MKlZMeHH35I10pZvHix1i/Gc+bMob9Wjxs3Tu8itWqUSiU2b95MRyvk5ubC09MTLi4uAIAtW7ZojZBSk5CQgE8//dRoGWfOnAmxWAxCCMaNG0c19KGpr0Y9LcdY+YHyBdHVo6zeeOMNvdfO0aNHsXr1agDl6+N07drVaJ41wfTp0xESEgIAOHLkCEaOHGlwyg1QvgvZpk2b0LlzZ1y+fJl+bmNjg9deew1A+QgOzSlOaggheOedd+gi3O+8845ZZTV1vbcJEybQkRtz5szByZMnDaat6LePjw9eeeUVAMClS5fw5ptv0oWa9elnZGRUOrLip59+wpkzZ3Q+f/ToEWbOnAmgfFFzzVEgatTX171794xqVMbp06dx9+5dAMBoE6fnDhw4kE5JWrt2rVl6O3bsoKOeTNWLiIigfYLmaCt1u6tHKcnlcmzevJnuevb8888bnTql7gPUmwIYu77lcjlWrlyJkpISLW1zUI9WvHHjBv744w+d40VFRXjxxRd1FvbWZOTIkfDy8gIALFy4kO5CqcnNmzf1fs80+fDDD+lGFFOnTjU6agoADh48SL/X5tRdLBZjw4YNdH2pSZMm6d0RUM3ly5fRr18/uoPc0qVL0axZM600ubm58PHxwY//zLgpLCxE3759jX6fgfKp84MGDaLTfzX55Zdf6NpLc+fOxbx58/T+7VDXvbCwEAsWLEC/fv3+u2ttWiSMxfnPYHAEEyGExMT8+6vqlSu1VobNmzfXWt51WZulfl0Y0cB9tzzcd+47K1j7znIEU2ZmpsU1Cak/I5gIIWTatGk0/e+//6517LPPPqPHHBwcyPTp08mBAwdIUlISiYuLI5GRkeTdd98ljRo1IgDIlX/uV9Ttrpl3t27dSGRkJElISCDHjx8nH3zwAZHJZMTDw4MEBAQY/IWfEEIWLVpE83FxcSFz5swhx48fJxcvXiQxMTHku+++I7179ybBwcFa+oQQMmfOHHrul19+Sf78809y8+ZNcvPmTZKWlqal8+GHH9K0fn5+5JdffiHx8fEkNjaWzJgxg46ckUql5OLFizrlrI0RTIQQ8uTJE9K9e3eat6OjI5k6dSrZtm0bOXfuHElISCD79u0jc+bMIS1btjQ4OigvL4/4+fnR4yNHjiT79u0jiYmJJCoqigQHB9NjPXr00DvKydgIJs12r2xESXR0NLG2tiYAiJWVFZk8eTLZs2cPSUxMJOfOnSNr164lY8aMIVKpVOfc/Px80q5dO5p/mzZtyLJly8j+/fvpNfHjjz+SESNGEKlUSjp37mywHp6enqRZs2ZEJpOR2bNnk9OnT5P4+Hjy448/0usaAPnmm2/0eqN5fX3xxRdGry9jvPrqqzSfK2bc97/44osEABGLxWbphYaGEgBEIpGQp0+fmnzec889RwAQZ2dn2qdr+t6iRQv6PVXXZ8+ePZXmqzmizMPDg8yZM4ccPXqUXLx4kZw5c4asX7+evPbaa8TNzY0AIPn5+Vra5oxgio+Pp2ldXV3Jl19+SU6ePEnOnz9PVq5cSb9DPXv2NJrnxo0btfJZsmQJiYuLI3FxcWTJkiXEzc2NuLi40PzU/VNFNMsulUrJlClTyK5du0hiYiI5f/482bFjB/noo4+Iv78/AUD27dun0+6msmXLFiKVSqleaGgo+e2338iZM2dIfHw8iYqKIhMnTqTfTQBk+vTpevPS1F+4cCFND4AMHDiQrFixgkRHR5OkpCRy/PhxsnLlSjJ06FBiZWVFRyDqIyEhgXh7e9O8fH19ySeffEIOHDhAEhISyNmzZ8nq1avJ1KlTiaenJ02nr082Rn0ZwcQDTByzMBpgIoSQkSPLg0wDBxJixjBIc4iOjq6VfOu6Nkv9uvDAyX23PNx37jsrWPvOMsBkqRvAitSnAFNqaip94AgMDNQp83fffUdsbGy0Hh70vaRSKbl58yYh5N92z8nJIR07djR4jpubGzl58iTp27ev0QATIYR88cUXWg89+l7q8zV9T0tLow+lhtKrUSqV5O233zaq4ezsTI4cOaK3jLUVYCKk/GFo+vTpWg+Hhl4ikYhMmDCBpKen6+Rz9+5draky+l49e/YkWVlZesthLMCk2e6mPPAfPnyYuLq6VloffWRlZdGpTpW9QkJCjNYjISGBTgvU9zI2hc6c68sQRUVFxMnJiQAgrVq1MukcNTt37qR6xqaianL//n0iFosJUD7t0hw0p2xu2bKFEKLt+7x583S+43K5vNJ8FQoFmTVrFg0+GHvZ29uToqIiLW1zAkyEELJgwQKjGjNmzKg0T6VSSWbNmkVEIpHePOzs7MiBAwdI7969CQAyePBgg+XZsmULvQaMvcRiMf2bXtW/bydPniStW7euVMvV1ZWsXLnSYD4V9Xfs2EF8fX1N+k62bdvWYD9KCCEpKSlk6NChJuVlb29fpfus+hJg4rvIcUxixYoVWLFiBR2Kvnv3bjg4OCAiIgInTpxAbm4uvLy80P2zz2C7dy+sjh5F2qpVyO/dmy40OHz4cJw5cwZZWVlwc3NDnz59sHv3bgBAhw4dIJFI6PatQ4cOxYULF/D48WM4OTlh4MCBdNhq8+bNcefOHbrg46BBg3D16lWkp6fD3t4ew4YNo0MoW7VqBQ8PD5w9exYA0L9/f9y4cQOpqamwsbFBREQEtm7dCpVKBX9/f/j4+NBFOYODg5Gamoo7d+7A2toaY8aMwePHjxEZGYlmzZrB398f0dHRAMp3m8nIyMCNGzcAAOPHj8eePXtQVFSExo0bo02bNnQhwB49eiA3NxfJyckAgDFjxuDw4cPIz89HgwYNEBQUhIMHDwIAunbtipKSEly5cgVA+Y4Whw8fRnZ2Njw8PNCjRw/s27cPwL+LDl68eBEAEB4ejri4OGRmZsLV1RXBwcHYtWsXAKB9+/aQyWRISEgAAISFhSEpKQmPHj2Co6MjBg8ejO3btwMA2rRpQ7fQjYqKwuDBg5GcnIy0tDTY2dlh+PDhdMeNgIAAeHl50WHboaGhuH37Nu7duwepVIpRo0Zh+/btUCgU8PPzQ9OmTREbGwugfMvn9PR03L59m24Nu3PnTsjlcjRt2hTNmjWjOj179kRmZiZdZHXs2LHYv38/CgsL4ePjg3bt2uHIkSMAgO7du6OgoIAukDh69GgcPXoUeXl58Pb2RpcuXXDgwAEAQOfOnVFWVkaH8o4YMQKnTp1CRkYGjh49il69emHPnj0AyrfOFovFdJvTYcOGIT4+HhkZGXB2dka/fv2wc+dOAOWLbNrZ2dFFSIcMGYJLly7hwYMHcHBwQFhYGLZt2wYACAwMhJubG92VZcCAAVAqlYiMjIStrS1GjBiBLVu2gBCCli1bokGDBnS3jJCQEKSkpODu3buQSCQYPXo0oqKiUFZWhubNm8PX1xcxMTEAgN69e+PRo0e4efMmRCIRxo0bh927d6O4uBhNmjRBYGAgbcPU1FQUFBTg2rVrAMoXvz148CAKCgrQqFEjPPPMM3Rb727duqGoqAhXr14FAJ0+olu3bti/fz+A8kVTVSqV0T4iLS0NkZGRZvURbdu2hYODQ7X7CPXUE3P6iB07dqC0tLRG+gh13c3pI0aOHInY2Nhq9REqlQoAcOfOHepNZX2Es7Mz4uLiAJRPgahuH1FSUoLz58+b1UcEBATg+PHjAKrXRwwYMACxsbHw8PBAQUEBJBIJcnJyAJRvaU8IoYv8urq6Ij8/HwqFAtbW1nBwcKBp7ezsIBKJ6JQOFxcXFBYWoqysDNbW1nB0dKQ7/tja2kIsFtO0CoUCxcXFKC0thZWVFZydnemirLa2trCysqLTAJycnFBSUoLS0lKIxWK4urri6dOnIIRAJpNBIpEgPz+fppXL5ZDL5RCJRHBzc6Np1Qtkq8vk6OiIsrIylJSU0LTZ2dlQqVSQSqWQyWTIy8sDADg4OECpVNLpGW5ubsjNzYVSqYRUKoWtrS2dCmBvbw+VSkXTurq60roA5duQq3c5qtjeLi4uKCgogJ2dHcaPH4/169fj2rVrWLduHcaPH0/b++WXX0ZERARWrFiB6Oho3L17F7m5ubCxsUGDBg3Qvn179OvXDwMHDoSrqysUCgUIIcjKyoKVlRXOnDmDzz//HHv27KHf70aNGmHAgAGYMWMGPD096aLZAAy294wZMzBkyBD8/PPPOHXqFNLT01FaWooGDRrA19cX4eHhGDx4MLKysmBnZ4fCwkKUlJRAJpMhPj4eCxYswJkzZ/Dw4UM6vaasrAxyuVyrvX/88UcMHToUa9euxfnz55GRkQGpVApfX18MGTIE06ZNg729PbKysrSuWYlEorVIr1wuR3FxsVZ7G7pmK17fzs7OKCoqQllZGb1mCwsLMXfuXLz11luIiorCsWPHcPv2bWRlZYEQAhcXF7Rp0wYhISEYNmwYmjRpAplMhtLSUq1r1sPDA9HR0di4cSMOHDiAK1euID8/H66urujYsSNGjBiB0aNHw8HBgbah5jUrl8tpHdXXloODAxQKBcrKyujfHM3FuxUKhVZadXt36dIFt27dwrJly3DkyBHcunUL+fn58PDwQKNGjdCvXz+MGTOGnluxj9i/fz/27t2LqKgoxMfH49GjRygpKYGjoyP8/f3RqVMn9OvXDwMGDIBKpdLqI9T34CqVCh07dsSpU6ewbNkyHDt2DA8fPoSdnR06deqEadOmISwsjJahYh/h4+ODI0eO4Ntvv0V8fDzS09Pp9UUIQUFBgd4+wsbGBjY2NsjLy8OOHTvo9z8sLAxPnz41uY/o2rUr7O3tUVhYiHXr1uHtt9+utI9YtWoV/ds0cuTISvsIdXs7OjoiNDSU+rpu3Tr0798fQPk02cLCQoSFhWHhwoU0zbBhw2ifoO6bnJ2ddfrknJwczJo1i/ZFJ06cwP3795Gfnw87Ozv4+Pigffv2GDZsGPr27YuioiLaNllZWVr9XnZ2NpycnLTaULO9AeDjjz9Gu3bt8OOPP+LixYsoKiqCh4cHgoKC8Nprr2Ho0KH4+eefaZ7FxcW0nTT75OnTp2Pw4MH4+uuvkZCQQO+He/fujWnTpqF79+746KOP6PdcqVRq/V0Dyqfk9e/fH7dv38aKFStw7Ngx3LhxAzk5OZBIJPDy8kKbNm3Qt29fDB48GD4+Pjr9rLG/axXbu0+fPoiNjcXevXtx9OhRJCUl4fHjx1AoFPD09ESrVq0QGhqKcePGoXnz5lrXrFQqpf2J+rpT9xERERHo2bMndu/ejdjYWCQlJSEjIwMFBQVwcnJC06ZNERQUhGHDhmH48OHIy8tDVlaWzt81BwcHeHp6Yv369UhKSsLx48dx4sQJpKWlITs7G1KpFB4eHujQoQMGDRqEUaNGwdramt5jmHofIZPJUFJSgv3798POzs7kZw2LY5EwFuc/Q6UjmAghZNYsQl55hZAHD2qlDKynTrCET5kRnjZLfe47950VrH3nU+TYwKrurLVZ6nPf64/vxkZimQv3XZjapvheWlpKFwv/9NNPa1S/Pn3f6qI2H8HEES6LFxveTpnD4XA4HA6Hw+FwOHUO9Wh2AHj22WcZl4ZTH+G7yHFqnorBJY0dXmoCS+yAUhe164I+S7jvwoT7LkyE7Lu9vT1TfZawrDvrdmetzxLuuzARqu+sPVfv/KePlJQUfPDBBwAAb29vDBo0qEa1WdddyL5bEj6CiVN73L4NzJgBNGsGfP99jWWrnifOApbadUGfJdx3YcJ9FyZC9p1orIkjNFjWnXW7s9ZnCfddmAjVd9ae9+3bF0OGDEF4eDjatm0Le3t7ZGRkICYmBj///DNd/+frr7+GtXXNhgpY113IvlsSPoKJU3vcuQPs2QOsXAn8szhwTaBezJYFLLXrgj5LuO/ChPsuTITsu+ZCw0KDZd1ZtztrfZZw34WJUH1n7blSqcT+/fvx5ptvolevXujUqRMGDRqExYsXIycnB2KxGF988QUmTJhQ49qs6y5k3y0JH8HEqT0GDADCw4F9+4CZM4F/do7icDgcDofD4XA4HI5lWbduHc6fP4+4uDg8fvwYWVlZsLGxgY+PD4KDgzFt2jS0a9eOdTE59RgREdJ4LU61ycvLg7OzMzIyMuDp6Vn5CTduAG3bAgoFcOQIMHBgtcug3sKXBSy1WerL5XIsXrwYH3/8MWxsbCyuD3Dfue/C0mapz30vnyJ39+5dNG/e3OLlUKlUEIstP8BcpVLh0aNHaNCgARN9dRmEqM1Sn/vOfRdi2wtZm6XvQv2+1ZR2SUlJle5Nnjx5Ai8vL+Tm5sLJyalaZTAFPkWOU7sEBADvvFP+/oMPygNN1SQ2NrbaedRH7bqgzxLuuzDhvgsTIfuen5/PVJ8lLOvOut1Z67OE+y5MhOo791yY+qzrbkl4gIlT+8ybB7i5AX/9Bfz2W7Wzy87OroFC1T/tuqDPEu67MOG+CxMh+66ogR9i6iss68663Vnrs4T7LkyE6jv3XJj6rOtuSXiAiVP7uLoCCxaUv1+9GqjmrEwPD48aKFT9064L+izhvgsT7rswEbLvEomEqT5LWNaddbuz1mcJ912YCNV37rkw9VnX3ZLwRb45luHNNwGRCHj11fJ/q0GPHj1qqFD1S7su6LOE+y5MuO/CRMi+29vbM9VnCcu6s2531vos4b4LE6H6zj0Xpj7rulsSPoKJYxkkEmDaNMDWttpZ7du3rwYKVP+064I+S7jvwoT7LkyE7HtOTg5TfZawrDvrdmetzxLuuzARqu/cc2Hqs667JeEBJo7lUSqBw4dZl4LD4XA4HA6Hw+FwOBxODcEDTBzLUlYGdOsGDBkCxMRUKYtOnTrVcKHqh3Zd0GcJ912YcN+FiZB9t7OzY6rPEpZ1Z93urPVZwn0XJkL1nXsuTH3WdbckPMDEsSwSCaBe3+L998tHM3E4HA6Hw+FwOBwOh8Op1/AAE8fyzJ8PuLgAly4Ba9eaffrFixdrvEj1Qbsu6LOE+y5MuO/CRMi+FxUVMdVnCcu6s2531vos4b4LE6H6zj0Xpj7rulsSHmDiWB4PD2DevPL3n34K5OWxLQ+Hw+FwOBwOh8PhcDicasEDTBw2TJsGtGwJPH4MfPmlWaeGh4fXUqHqtnZd0GcJ912YcN+FiZB9d3FxYarPEpZ1Z93urPVZwn0XJkL1nXsuTH3Wdbck1qwLwKkfrFixAitWrIDynzWTdu/eDQcHB0RERODEiRPIzc2Fl5cXunXrhv379wMAgoKCoFKp8OeffwIAhg8fjjNnziArKwtubm4I/vxz2LzwApTffIPbwcFA8+ZITEwEAAwdOhQXLlzA48eP4eTkhIEDByIqKgoAQAjBs88+i/PnzwMABg0ahKtXryI9PR329vYYNmwYtm7dCgBo1aoVPDw8cPbsWQBA//79cePGDaSmpsLGxgYRERHYunUrVCoV/P394ePjg1OnTgEAgoODkZqaijt37sDa2hpjxozB+vXr4ebmhmbNmsHf3x/R0dEAgF69eiEjIwM3btwAAIwfPx579uxBUVERGjdujDZt2uDo0aMAgB49eiA3NxfJyckAgDFjxuDw4cPIz89HgwYNEBQUhIMHDwIAunbtipKSEly5cgVAeeckEomQnZ0NDw8P9OjRg26prV6YVj29Izw8HHFxccjMzISrqyuCg4Oxa9cuAED79u0hk8mQkJAAAAgLC0NSUhIePXoER0dHDB48GNu3bwcAtGnTBra2tgCAqKgoDB48GMnJyUhLS4OdnR2GDx+OyMhIAEBAQAC8vLxw5swZAEBoaChu376Ne/fuQSqVYtSoUdi+fTsUCgX8/PzQtGlTxMbGAgD69OmD9PR03L59G2KxGGPHjsXOnTshl8vRtGlTZGZm0uGlPXv2RGZmJq5fvw4AGDt2LPbv34/CwkL4+PigXbt2OHLkCACge/fuKCgowF9//QUAGD16NI4ePYq8vDx4e3ujS5cuOHDgAACgc+fOKCsrw+XLlwEAI0aMwKlTp3D9+nUEBgaiV69e2LNnDwCgY8eOEIvFSEpKAgAMGzYM8fHxyMjIgLOzM/r164edO3cCANq1awc7OzvEx8cDAIYMGYJLly7hwYMHcHBwQFhYGLZt2wYACAwMhJubG86dOwcAGDBgAPbt2weZTAZbW1uMGDECW7ZsASEELVu2RIMGDXD69GkAQEhICFJSUnD37l1IJBKMHj0aUVFRKCsrQ/PmzeHr64uYfxbX7927Nx49eoSbN29CJBJh3Lhx2L17N4qLi9GkSRMEBgbSNkxNTUVBQQGuXbsGAHjhhRdw8OBBFBQUoFGjRnjmmWdw6NAhAEC3bt1QVFSEq1evAkC1+og+ffpgzZo18PT0RIcOHSCRSEzqI9q2bQsHB4dq9xFPnz7FtGnTzOojduzYgdLS0hrpI06ePAlPT0+z+oiRI0ciNja2Wn2ESqUCANy5c4d6U1kf4ezsjLi4OADAwIEDq91HPHz4EN27dzerjwgICMDx48er3Ue4uroCADw8PFBQUACJREK3F7a3twchhPZFrq6uyM/Ph0KhgLW1NRwcHGhaOzs7iEQiFBYWAijvvwsLC1FWVgZra2s4OjoiOzsbAGBrawuxWIzCwkIoFAq4u7ujuLgYpaWlsLKygrOzM54+fUrTWllZoaCgAADg5OSEkpISlJaWQiwWw9XVFU+fPgUhBDKZDBKJBPn5+TStXC6HXC6HSCSCm5sbTSuVSgGAlsnR0RFlZWUoKSmhabOzs6FSqSCVSiGTyZD3zwhkBwcHKJVKFBcXAwDc3NyQm5sLpVIJqVQKW1tb5Obm0jZUqVQ0rWYbqlQquLm5GWxvFxcXFBQU0PbWbENj7W1lZQUnJyet9tZsQ2dnZ+Tk5EAkEum0t0wmg7W1tVZ7q9uwsvZ2dHREaWmpVnur29DGxgY2Nja0DcViMaRSKUpKSgAA7u7uyMnJ0duGxtpbIpHAzs5Oq70NXbPqtGrf1e8129vQNVuxvZ2dnVFUVETb29g16+zsrHV9i8VilJWV0fY2dM1WbG8bGxtIpVKt9jZ0zVZsbwcHBygUChQUFMDa2troNVuxvV1dXZGXl0fb297evsp9RHFxMQghlba3Zh+hrw3N7SPU+RYVFWm1obE+omIbVrePyMrKgpWVlVl9RGXtbWofoVAo4OHhYVYfYai9ze0jSktL6d9Zc/oIzfYGqt5HAIBSqaR1rayP0Gzv6vYR2dnZEIvFZvcRLi4uyMrKou1d1T5Cs581tY9Qt3d1+4jMzExYW1tX6z5CJpOhpKQE+/fvh52dncnPGhaHcDhmkJubSwCQjIyM6memUhHSrx8hPXsSkpxs8mmbN2+uvnYVYanNUr+kpITMnz+flJSUMNEnhPvOAu47950VrH0vLi4mycnJpLi42OL6mZmZFtckhBClUknS09OJUqlkok8Iu7qz1mapz33nvrNCqL6z1Gbtu1C/bzWlXdV7k4yMDAKA5ObmVrsMpsBHMHHYIRIBUVGAs3P5exNR/7rMApbadUGfJdx3YcJ9FyZC9t3aWri3ZizrzrrdWeuzhPsuTITqO/dcmPqs625J+BpMHLa4uJgVXALKp6WwgqV2XdBnCfddmHDfhYmQfXd0dGSqz4LY2FiIRCI6DVzzZWtri8aNG2PIkCFYuXIlnUJR07Bud9b6tcn9+/exdOlSDBw4EM2bN4eDgwNsbW3h4+ODQYMG4YcffsDdu3eZlI11u7PWrw2Ki4vh7OxMv8MLFy7Um66m6n7//n1YWVlRvd9//73Sc1i2+3/Rc1Mxt+6afwuaNWuG0tJSo+nXrVtH06un1xvTLysrw5YtWzBp0iS0bt0a7u7ukEgk8PDwQOfOnfHWW2/h+PHjdEpjRXx9fSESieDr61tpXYTkOw8wceoGubnArFnApk2VJlWvI8QCltp1QZ8l3Hdhwn0XJkL2Xb1+BaeckpISpKen4/Dhw5g2bRratWuHS5cu1bgO63bX1Fc/tEyePJldgWoAuVyOGTNmoGXLlpg1axaOHTuGlJQUFBYWoqSkBA8ePMDRo0cxb948+Pv7Y+zYsbh//75Fy1iXfLcUvr6+sLKywnvvvVcr+e/atYuuYwMAGzZs0Juupuq+YcMGrQCAKQEmlr6zvuZYUp26p6amYtWqVTWmv2fPHgQGBmL8+PH4/fffce3aNTx9+hQKhQJZWVlISkrCzz//jAEDBqB169Z0vdaa0P6vwwNMnLrBmjXA0qXAhx8CtfTrJIfD4XA4nLrNW2+9hStXrtBXTEwMfv75ZwQEBAAA7t27hyFDhtBFWzl1k6ysLISGhuLbb7+FXC6Ho6Mj3njjDWzduhVnz55FfHw89u7di48++gh+fn4ghGDbtm3YsWMH66Jzqok6wOPg4AAAuHXrFt24pDZQB7DUejExMUhLS6s1PQ47vvjiC7rodnX48ssvMXLkSNy5cwdA+QYvy5cvx4kTJ5CYmIhjx47hxx9/xKBBgyAWi3Hjxg3MmTOn2rpCgQeYOHWDt98G/PyAhw+Br74ymrR9+/YWKlTd0q4L+izhvgsT7rswEbLv6l16hIqXlxfatWtHX8HBwXjzzTdx5coVhIaGAgAePnyIX3/9tUZ1Wbc7a/2aRKVSYdy4cTSoEBYWhlu3buGXX37BCy+8gOeeew5du3ZFeHg4Fi9ejMuXL2P9+vXw8vKyeFlZtztr/Zrm4cOHdDfPefPmwd3dHYD+UUU1Uff4+Hi6w+0333wDa2trqFQqbNy40eh5LNv9v+a5OVS17h4eHgCABw8e4KeffqqW/oYNG/DJJ5+AEAJPT09ER0fj2LFjeOeddxAaGoqgoCD0798f06ZNw+HDh/Hnn3/Svz3VQUi+8wATp25gY1M+ggko/zc11WBSmUxmoULVLe26oM8S7rsw4b4LEyH7LjJzXUKhIJVKMX/+fPr/Y8eO1Wj+rNudtX5Nsnz5chpk6N+/P/bs2WM0eGRlZYWJEyciMTERHTp0sFQxAbBvd9b6Nc3GjRuhVCphZWWFl19+GS+88AIAYNu2bZDL5Vppa6Lu69evB1C+OcPkyZMxYMAAAJVPk2PZ7v81z82hqnUPCwtDu3btAABLlixBUVFRlfJ5+PAh3nrrLQDlAZ/Y2FiEhIQYPad9+/Y4duwYZs6cWSVNNULynQeYOHWHkSOBvn2BkhJg9myDyRISEixYqLqjXRf0WcJ9Fybcd2EiZN8LCwv1HygpATZsAEaNAoKDy//dsKH8c4EQFBRE31e2Vs/169fx7rvvom3btnB2doatrS38/PzwyiuvICkpSSe9Zrs/fPgQK1euxOjRo9GyZUvY29vDxsYGPj4+GD58OLZu3Wpw0deKpKSk4KOPPkLnzp3h7u4OmUyG5s2bIyQkBN988w1S//lBrbCwEMHBwRCJRLh37x6A8ofnioueG1qE/syZM3j55Zfh6+sLmUwGFxcXdOrUCZ9++imePHlisHyxsbHw8fGBlZUVYmNjoVKpsGbNGoSEhMDb2xtisdistaDKysqw9J8fDGUyGdauXVvp7knqtm/cuLHBkQKlpaVYuXIlQkJC4OnpCalUigYNGiAsLAwbN2406sfkyZO1FuLNycnBvHnz0LZtW7i7u8PFxQV9+vTBJhPWAQWA/Px8fPPNNwgNDUWDBg1gY2ODRo0aoXv37vjoo4/0Xl9qCCGIiorCqFGj0KRJE7i4uMDV1RXdunXDokWLkJOTY3I90tPT8cEHHyAgIAB2dnbw9PREWFgYDh06pPf8itfX9u3btRbHNnZ9mYp6ulq/fv3QoEEDTJgwAUD5+jP79u3TSmuwrzOR0tJSbN26FQAwZswYSKVSqvf333/jwoULOucsWLCAbh5w8+bNSjXCwsIgEong7e0NhUKhN018fDxef/11BAQEwMHBAfb29ggMDMS0adP0aqjrrbkgdUpKCuRyOZYtW4Znn30WHh4eEIlEWkH10tJS7Nu3D++88w66du0KV1dXSCQSuLu7o3v37pg/fz4yMzMrrRMAnD59GhEREfD29oZMJoOfnx+mTp2KW7duAfj3WqnsekhLS8Ps2bMRFBQEV1dXyGQyNG3aFGPHjkVMTIzBupuLSCTCggULAACPHz/Gjz/+WKV8vv32W1qGBQsWoE2bNiadJxaL6bVVVap7vdcrCIdjBrm5uQQAycjIqB2BxERCRCJCAELi4vQm2bx5c+1omwBLbZb6JSUlZP78+aSkpISJPiHcdxZw37nvrGDte3FxMUlOTibFxcUW18/MzNT9cM8eQlxdy/82isXa/7q6ErJ3b7V1lUolSU9PJ0qlstp5mUtMTAwBQACQzz77zGC64uJimq5Dhw4G0y1cuJBYW1vTtBVfIpGIzJs3T+scdbsrFAoiFosNnqt+DRgwgOTn5xut19KlS4lEIjGaT9++fal+3759K9VVp1ejVCrJtGnTjJ7j7OxMjh49qreMJ06coOkOHTpE+vfvr3P+pEmTjNZTk3379tHzJkyYYNI5eq95DVJSUkjr1q2N1rFXr14kKytL7/mTJk0iAEizZs3I33//TXx9fQ3mM23aNKNlOXbsGPHw8KjUJ31kZGSQnj17Gj3P29ub/PHHH5XWIyEhgXh5eRnMZ/r06TrnV+X6MoekpCSaz++//04/9/PzIwBIeHi4VvrKfK+MnTt3Ur1Tp04RQggpLCwkDg4OBAD53//+p3POrVu36Dnz5883mv+TJ09oP6Ivr7KyMvLWW28ZbU+JREJ+/fVXrfPU9V67di1Nl5CQQDp27KhzvmZ/qPbf2Mvd3Z2cOXPGYJ2USiWZNWsWEYlEes93dHQkR44codeKsevht99+I7a2tkbLM2XKFFJWVqZTd1PR7INUKhVtI3d3d5KXl6eTXrNNY2JitI6pVCr63bW3tye5ublmlUUfzZo1o9/Jyqju9U4IqfK9SUZGBgFQI3U2BR5g4phFrQeYCCHk1VfLb5pDQ/UezsnJqT3tSmCpzVK/Ljxwct8tD/ed+84K1r6zDDBp3owTQsqDSyLRvz++VHypj+3ZUy3d+hBgSkxMpOmef/55vWnmzp1L0zz33HPkt99+I3FxceTChQtk06ZNpEePHvT4Dz/8QM9Tt3tZWRkRi8UkNDSULF26lBw+fJgkJiaS2NhYsmbNGq3zJ06caLCsCxcupOlcXFzIJ598Qo4dO0aSkpJIdHQ0+frrr0nPnj1JcHAw1b1z5w65cuUKadSoEQFAhg8fTq5cuaL1unPnjpbOhx9+SHWaN29Ofv75ZxIfH09iYmLI+++/TwNcUqmU/Pnnnzrl1AwwdejQgbbtzp07SWJiIjl48CDZsmWLwXpWZObMmTQ/U8/TueY1yM/PpwEKAGTEiBFk79695MKFC2T79u1aQZMePXoQhUKhk4f6wdzT05O0bNmSODo6kk8//ZTExsaSP/74g6xatYo0btyY5nP48GG9ZYmOjqYBBysrKzJ58mSya9cukpiYSM6ePUtWrVpFIiIiiEQi0Tm3oKCABsmkUil58803yZ49e0h8fDw5ffo0+fzzz4m7uzsBQFxdXUlKSorRevj6+hIbGxvy8ccfk1OnTpHz58+TH374gTRs2JDW45tvvtE6v+L1NWjQIHLp0iWj15c5TJ8+nQAgdnZ2WsFX9XdSIpFoPT8Y890Uhg8fTgAQX19folKp6Ocvv/wybafS0lKd87p3704AkJYtWxrN/8cff6RtqS/oN3HiRHp8yJAhZOPGjSQ+Pp4kJCSQVatWkbZt29LjezV+BFDXWzMY0qFDByISicjEiRPJgQMHSGJiItm1axc5ePAgPe+ll14ifn5+ZMaMGWTr1q0kLi6OJCQkkKioKDJ16lQilUppvR8/fqy3Ths3bqSarq6uZPHixeTcuXPk3LlzZMmSJcTV1ZW4urqSgIAAowGm1atX03zatWtHli9fTs6cOUOSkpLIjh07SFhYGD3+wQcf6NTdVDQDTIQQsnfvXvrZokWLdNIbCzBdvXqVHhs8eLBZ5TCEOQGm6l7vhPAAE+c/ikUCTA8eEPL664Skpek9HB0dXXvalcBSm6V+XXjg5L5bHu47950VrH1nGWDSugEsLi4foWQouKQZZHJ1LU9fRepDgGn8+PE0neYICTXx8fF09NGnn36qNw+lUkkmTJhAf63Pzs4mhPzb7iqVity8edNoeefNm0eA8pFQN27c0DmemJhIyxEQEEDu379vMC/1MU3f1Q8tlY0cunz5MtVp164drYsmhw4domm6deumc1wzwASAzJ0716hmZQwYMIDmpa9t9GHsoUczYKXPU5VKRV566SWaZuXKlTppNEd+uLi4kKtXr+po37x5k8hkMoPBy6KiIhq8sbOz03l41SQ1NVXns3feeYcA5aPJEhIS9NY9JSWFaugb/aVZD4lEQk6ePKmTJj09nQbL7Ozs9AYa1NfXmDFjauz7XlZWRkdUvfjii1rHrl+/Tsv9/fff08+r87CbmZlJg6effPKJ1rEjR45QvT16Au8//PADPa7pRUWee+45AoD4+/vrHIuKiqJ5rFq1Su/5xcXFJDQ0lAbB1AEGdb01gyEAyOrVq43W+datW1qBtIpcvnyZjt7S910pKSmhHrm5uZHr16/rpLl+/Tpxc3OjZdIXYEpNTSV2dna0jzIUOPnkk08IACIWi6mWuZ5XDDARQki3bt1ogKzij1HGAkybNm2ixypeM1XFnABTTQR36kuAia/BxKl7NGwI/Por4OOj9/CjR48sXKC6oV0X9FnCfRcm3HdhUu98Lyw0/Kq4RpKxtMXFKCsr+zftxo1AdnZ5GMkYhJSn27RJf74VF0QtKtKbTlRUpJu2uNj89qhBsrKycObMGYSFhSEyMhIA0KNHD4wbN04n7ZIlS6BSqdC5c2csXLhQb35isRjLly+HjY0N8vPzERUVBQC03UUiEVq0aGG0TPPmzYOHhwcIIdi7d6/O8aVLl0KlUkEkEmHLli1o3LixwbzUx7R8N5GffvqJrj20atUquLi46KQZPHgwXn31VQDla8UYW2MsICAAn332mdnl0ERzDRhvb2+TzjFUd7lcjt9++w0A0KZNG631aNSIRCKsXLmS7lZW2dosCxcuRNu2bXW0W7RogREjRgAoX5+mIr///jsePnwIAPj888+Nrk3TpEkTrf9nZmbSeixcuBBdunTR0QeAZs2aYe7cuQCArVu3Gl3I+M0330SfPn10Pm/UqBG++eYbAEBRURFdBLu2OXz4MDIyMgBAZ62agIAAdO3aFYD24ttVuebVREZG0vMr6vXr1w8NGzbU0VMzduxYui6YoXW3UlJS6C6IL730ks7xL7/8EgAwcuRIvPbaa3rzkMlk9HpMSUlBbGwsAP31Dg0Npd9TQ/j7+xtdKLp9+/a0LLt379Y5vmvXLurRvHnzEBAQoJPGlD7g+++/R1FRERo1aoSff/7Z4BprCxYsgI+PD1QqFfWhOp5r5guUr+v17bffmnxeVfqmmqQm6l5f4AEmTt0nLU3rv46OjowKwla7LuizhPsuTLjvwqTe+e7gYPg1apR2Wi8vw2mHDIGVldW/aadNM68cr72mP99/Hu4oXbvqpBE7OaFhy5YQ/bNTD0XPQ2xtol6EV/3y8PBA7969cejQIVhbW2PChAk4fPgwJBKJ1nllZWV0cePRo0cbfRBzcXFB+/btAQBxcXEAoN3uGqhUKjx48ADXr1/H1atXcfXqVfz99980MHTp0iWd9IcPHwYA9O3bF506dTKp3ob0jaHeqa1NmzZ49tlnDaZ7/fXXdc7Rx9ixY6tUDk3y8/Ppe3t7e5POMaSZmJhIF72ePHmywXROTk50t7Lk5GQaCKqISCTCiy++aFC7c+fOAMofXCsutn3gwAEA5TtPvfHGG8YrVIEjR46g5J9As7qc+vQB0KBRWVkZEhMTDeb5yiuvGDw2cuRIGmw05ndNog4geHl50Z3cNFEHgRITE/H3338DqNo1X1EvKCgIrVu31jpmZWVFA9D79+/X8dLLy4sGCA0t2L9582b6vuI1k56eTr2p6GdFWrduDQ8PDwDG+xp9QazKyM7Oxu3bt/HXX3/Rvknte3Jysk5A48SJEwAqX7B6woQJRvvPPXv2AADCw8ON7rpqbW2NHj16AKi8nzWHwYMHo2fPngCAZcuW4enTpyadV5W+qSapibrXF3iAiVN3yc8HIiKAVq2A9HT68eDBg5kViaV2XdBnCfddmHDfhYmQfXd2dv73PybuVCYUAgICMGvWLDg5OekcS05OpiM+Zs+erbP7WsWXeocp9Yg1zXYnhGDjxo0ICQmBg4MDfHx8EBgYiPbt29PXn3/+CQA6uzbdvXuXPtDqG2FiCC3fTUAul9Mdqrp37240badOnWhA7urVqwbTdejQwawy6EMzQGvqrkmG6q5Z1srqqHncUB09PDzoSCd92m5ubvS95sMoAFy8eBEA0KVLF9jZ2RktS0U0dzNr2LCh1nXo6uqq9f92GgFeQ6MppVKpUa8kEgkNbBrzu6bIycmhI/nGjRund0SL5ufq4JC517yaa9eu0ZF4hgIl6s/lcjndaU6TSZMmASjfMTI6OlrnuHpkU5cuXdCqVSutY5p+jh8/vtK+Rt1H6Otr1Jj63bty5QpeffVVNGzYEG5ubmjRogXatWtH+yX1KD+VSoXs7Gytc9XXQtOmTeHq6mpQw83NDX5+fnqP5ebm0p3mfvnll0rrrh4haqzuVUE9QjUvL4/uWlkZVembapKaqnt9gAeYOHUXBwfg8ePy4fpz5tCPt2/fzqxILLXrgj5LuO/ChPsuTOqd7wUFhl87dminzcgwnPbQIe1fY8PCALGJt2piMfD88/rzrTgtKiFBJ40qLw8Pb94EqfhAeuqU+e1RDd566y1cuXIFV65cwcWLF3HgwAG8+eabkEgkSE5ORnBwMK5fv65znnrqh7mog1Lqdi8pKcHQoUPx8ssvIzY2FsWVTBGseFwz4KSepmMKpv4Kr0bz4bGy6R7qrcwr0zH20Gkq6tEaQPl24qZgqEyan1dWxwYNGlSan77AkGZascZ3TalUaqVT+2qOp2qqe21WxM3NzeC0JDXq9jL3uqoKW7duhVwuB2A44KM5smnjxo1QqVRVLpt62p+VlRXGjx+vN01QUBDdgl7fNLk+ffrQUSwVp8n9+eefSE5OBqB/ZFFN9TWamPLdW716NYKCgrB27VqTpnJX7JvUfUbFIKs+PD099X5eG3WvCqGhoXQU2vLly/HkyZNKz6lK31STWOK7WFcw3jtxOCwRiYBly4Bu3YD164F33gE05q1zOBwOh1MnMGe4fWVpNR8qR48G9KzxoxeVChgzxrSy6BuBoVKB2NnpHrO1NU2/hvDy8tIaxdGxY0eEhYUhPDwczz//PJ4+fYoXX3wR8fHxWlMONAMCS5cuNXkkWsWpEp9//jmdate3b19MmzYNQUFBaNCgAWxtbWkQok+fPjh9+jSIkfWxjE0zqUlM0TFWTjU1MYXjmWeewbFjxwAASUlJaNmyZbXzBCqvoyn1s0Q59KG+NqVSqc60t5ycHL1rZwEwuHZXTfldU2gGcLp161Zp+rS0NMTExKBjx45ma6lUKhoQUiqVJgX8zp07h1u3bmmtrWZvb4/hw4dj8+bN2LlzJ3766Sc63Us9PU4sFmPs2LE6+Wn2NZs2bTJ59JGxIFJl371r165h6tSpUCgU8PLywocffojQ0FD4+vrC0dGRjlBcs2YNpkyZAqB2rgHNur/33ntUqzKkUmmNl2XRokXo3bs3CgsLsWTJEnz99ddG0z/zzDP0fVJSUo2Xh/MvPMDEqdt07Qq8/DKwYQPw3nvA6dP0FwkWsNSuC/os4b4LE+67MBGy77aaAZ0xY4Dp04GcHOMLfYtEgItLeUDqP8rQoUMxdepUrFy5EklJSVi3bp3Ww43mr/JlZWVaQSpTsLW1BSGELsbcq1cvREdHa41q0aTi9BM1mr+SP3jwwCx9c9B8WK1sNINCoaC/nmtOA6sN+vbtSx/0Dhw4oPcBvSKG6q5Z1kePHuldlFiN5ogEc+poart7eHggLS3NLE/VqK/N0tJSuLu7awVFioqKzJ5yl5WVBaVSaTQooR5pUtt+37p1iy6GbQ6///47XZ/HHKKjo3H//n2zz9uwYQNdHBoo933ChAnYvHkz8vLysH//fowePRqEELqZgOZi4Zpo9jUVpzWagrnfdQBYt24dFAoFrKysEBsbq7PulBpD/RLwb5+RlZVVqZ6hEUGadS8qKrJI3Q3Rq1cvDBgwAMeOHcPKlSsxc+ZMo+nbtGkDDw8PZGZm4vTp08jLy9M73bq2qMm613X4FDlO3eeLL8p/QT17FoiKYjqHlfX8Wdb6LOG+CxPuuzARsu9aD40yWfkIXqA8iKQP9efr15en/w/z2Wef0RFHCxYsQGlpKT3Wtm1b+iv50aNHzc7bysoKT58+pcGaF154wWBwqaCgQO80PQBo3rw5fZA7Zcb0Qk3fTRmhYmNjQ0cHnT9/3mjaixcv0gV/zX0gNJeBAweiUaNGAMqnm6ZrrKFpCEOBEs2yVlbH+Ph4vedVVbsiQUFBAMrX3zG2u5s+NBd6r3htVmXUWGlpqc7i8pooFAq6Rpi+tqjJkXWao5d++uknREZGGn2pRxbu3LmTLnxeFT0bGxts2rSpUj31wu0bNmzQGtFjZWWFAQMG0Klg6lFLp06dQto/mwsZWnjbmJ+mUBXP//rrLwDlo3AMBZcA7fWhKqLePTE1NdXodK2nT5/izp07eo95enrC559dvo8fP272KKmaXuh60aJFAMqnA6p39jOESCTCyy+/DKB8DSb1jwmWQkiLfPMRTByTWLFiBVasWEGHRu7evRsODg6IiIjAiRMnkJubCy8vL3Tr1g379+8HUP7HWKVS0T9yw4cPx5kzZ5CVlQU3Nzf06dOHbqPZoUMHSCQSOnR46NChuHDhAh4/fgwnJycMnjkTVosWoWDaNByfNw+hYWH0ZmPQoEG4evUq0tPTYW9vj2HDhtEF/Vq1agUPDw+cPXsWANC/f3/cuHEDqampsLGxQUREBN1Bwt/fHz4+PvSGMDg4GKmpqbhz5w6sra0xZswY7Ny5Ew0bNkSzZs3g7+9PFwbs1asXMjIycOPGDQDli/7t2bMHRUVFaNy4Mdq0aUP/CPXo0QO5ubl0fveYMWNw+PBh5Ofno0GDBggKCsLBgwcBAF27dkVJSQmuXLkCoHxo6rVr15CdnQ0PDw/06NED+/btA/DvHzz1QpTh4eGIi4tDZmYmXF1dERwcjF27dgEo38pUJpPRRRLDwsKQlJSER48ewdHREYMHD6brkLRp04ZG3aOiojB48GAkJycjLS0NdnZ2GD58OP21JyAgAF5eXjhz5gyA8jnSt2/fxr179yCVSjFq1Chs374dCoUCfn5+aNq0Kd22tU+fPkhPT8ft27fpsOSdO3dCLpejadOmuHnzJmxsbAAAPXv2RGZmJr3BHzt2LPbv34/CwkL4+PigXbt2OHLkCIDyhT8LCgroH+fRo0fj6NGjyMvLg7e3N7p06UJ3h+ncuTPKyspw+fJlAMCIESNw6tQpXLlyBR06dECvXr3o7hkdO3aEWCymw2yHDRuG+Ph4ZGRkwNnZGf369cPOnTsBlN/g2dnZ0RvgIUOG4NKlS3jw4AEcHBwQFhaGbdu2AQACAwPh5uZGfxEcMGAADhw4ADc3N9ja2mLEiBHYsmULCCFo2bIlGjRoQLdUDgkJQUpKCu7evQuJRILRo0cjKioKZWVlaN68OXx9fRETEwMA6N27Nx49eoSbN29CJBJh3Lhx2L17N4qLi9GkSRMEBgbSNkxNTUVBQQGuXbsGoPzB6+DBgygoKECjRo3wzDPP0Ckl3bp1Q1FREV1Msrp9RFRUFHx8fCrtIwYOHEgXk2zbti0cHByq3Uc8fPgQH3zwgVl9xI4dO1BaWlojfcSxY8fg4+NjVh8xcuRIxMbGVquPUO+oc+fOHepNZX2Es7Mz3SVm4MCB1e4j7t27h969e5vVRwQEBNAdk6rTR6hUKri7u8PDwwMFBQWQSCR00WZ7e3sQQugDpqurK/Lz86FQKGBtbQ0HBwea1s7ODiKRiC4m6uLigsLCQpSVlcHa2hqOjo7012b11Cv1cQ8PDxQXF6O0tBRWvXvDedcukEmTIM7NBRGLIVKp/v3X2RnFv/yC4ueegzg7G66urnj69CkIIZDJZJBIJHTBYicnJ8jlcsjlcohEIri5udG06uCMukyOjo4oKytDSUkJTZudnQ2VSgWpVAqZTIa8vDwAgIODA5RKJV3zw83NDbm5uVAqlZBKpbC1tUVubi5tQ5VKRdO6urqioKAAalQqFf2FvWJ7u7u7Y/LkyVixYgXu37+PtWvXYvQ/o7bs7OwQEhKCI0eOIDY2FnFxcWjbti3KyspgZWUFJycnrfa2srKius7OzsjNzdX6ZT8zMxNZWVmQyWSwtramaZ2cnLBy5UqtHZoqtne/fv0QFRWFkydP4uzZswgMDNRpQxsbG9jY2NA2JIRAoVCgpKSETnfJz89HVlaWThuq27tXr164efMmkpOTcezYMQQFBUEikcDOzk6rvX/++Wda1tDQUOTm5kKhUEAikWg9IMrlchQXF9P2NnbNVry+nZ2dUVRUhLKyMkybNg1z5sxBSUkJJk6ciN27d0MqlWq1N72+raygVCpRUFCABw8eIDU1FQMGDEB+fj58fX3h4uKCnJwcrFmzBq+88go8PDxoe9vY2EAqleLBgwe0Tw8MDIRUKsXTp09pe6vXBwL+Hb3h4OAAhUKB/Px8SCQSuLm5aQWOFAqFVtpBgwZh7969KCoqwi+//IJXXnkFSqUSEokE9vb2RvuInj17QiKRoKysDN999x0GDx4Ma2tr2NnZoaCggAYyK+sjNKcnrV27Fi1btqRt6OzsTIMGhw4douf16NGDfo9LS0shFovpVLDS0lIUFRVBKpWa1EdUvGYdHBywYcMGAOW7pU2dOrXSPkK9y2JBQQE2b96M8ePHm9RH5OfnIzc3l95X9e3bF4MGDdJpbxcXFxQUFNA++cmTJ0hMTMTdu3dx4sQJ9OrVi7axp6cnRo4ciV9//RUHDx7E06dPsXr1agCATCZDWFgYvQY0r1kPDw+0adMGycnJ2LJlCz766CM0b95cq49Qt6FYLNbpk4uLi1FQUKDV72VnZ8PJyclgH6Fui4KCAlomd3d35OTk0H42NzeX3qMC5UEXdVo3Nzc8++yzWL16NVQqFTZs2ICJEyfqvWY3btxI+wWlUgmlUqn1dy0sLAyrVq3CnTt3sG3bNgwZMsTkPiInJwfW1tY616y+PrniGlLqumj+XWvRogXCwsJw8OBB/PLLL5gxYwZNn5ubi4KCAq3r+5VXXsEvv/yCoqIizJs3D2FhYfD29tbbJ6v7iJKSEnrdhoeHa/1dU98vqdtP85rNy8vT6iOys7Pp+6reR8hkMpSUlGD//v2ws7Mz+VnD4hAOxwxyc3MJAJKRkWFZ4cJCQho3JqRJE7L/q68sq63B5s2bmWmz1C8pKSHz588nJSUlTPQJYdv23Hfuu5D0ue+bSXFxMUlOTibFxcUW18/MzNR/oLiYkA0bCImIICQ4uPzfDRvKP68BlEolSU9PJ0qlskbyM4eYmBgCgAAgn332mdG0Dx8+JDKZjAAgfn5+RKFQ0GNnzpwhIpGIACDNmzcnt27dMpiPQqEgmzZtIvfv3yeElLe7UqkkLi4uBADp2LEjkcvlOufFx8cTBwcHWt6+ffvqpLl48SIRi8UEAAkICKAa+tDUVxMSEkIAkK5duxpti8uXL1Od9u3bk5ycHJ00R44cIVZWVgQA6datm87xEydO0LrExMQY1TMVpVJJ6wCAhIeHG71vfPLkCdm4cSPx8vIi3333ndaxmTNn0nzmzp2rc65KpSITJ06kaVauXKmTZtKkSQQAadasmc4xzXZfu3Ytzefu3bta6YqLi4mPjw8BQOzs7EhsbKzB+ujz+4033qB5v/rqq6SsrExHX83jx4/JqlWrDNYDAJFIJOT06dM6aR4+fEiaNm1Ky/n48WOdNGpvOnbsWK3v+8mTJ2l55s+fb9I5crmcODk5GfzuGGP9+vVUb926dSadk56eTvuE1157jX6ubve4uDia54oVK4irqysBQF544QWj+W7evJme17lzZ6PXd0lJCVmxYgX9e6LWNna9VeR///sfAUDEYjGJi4vTOV5YWKj1nTN0DXt5eREAxM3Njdy4cUMnnxs3bhA3Nzej/dudO3eIjY0NzSchIcFo2Q8cOEAuXbqkVXdTUZdj0qRJBtMkJibSdB4eHkb7s8zMTLJmzRqaxsvLy+h3mRBC/vrrL9K/f3/yzDPP6Bxr1qyZwb5Fn3Z1qeq9SUZGBgFAcnNzq10GU+ABJo5ZMAswEULIpUuEFBXVyBe0qrDUZqlfFx44ue+Wh/vOfWcFa99ZBpjUD56Wpr4EmAghZNq0aTT977//rnXss88+o8ccHBzI9OnTyYEDB0hSUhKJi4sjkZGR5N133yWNGjUiAMiVK1cIIf+2u2be3bp1I5GRkSQhIYEcP36cfPDBB0QmkxEPDw8SEBBg9CF50aJFNB8XFxcyZ84ccvz4cXLx4kUSExNDvvvuO9K7d28SHByspU8IIXPmzKHnfvnll+TPP/8kN2/eJDdv3iRpaWlaOh9++CFN6+fnR3755RcSHx9PYmNjyYwZM4hEIiEAiFQqJRcvXtQpZ20EmAgpDxp1796d5u3o6EimTp1Ktm3bRs6dO0cSEhLIvn37yJw5c0hgYCBNVzHAlJeXR/z8/OjxkSNHkn379pHExEQSFRVFgoOD6bEePXpoBRzVGAswabZ7ZQ/80dHRxNramgAgVlZWZPLkyWTPnj0kMTGRnDt3jqxdu5aMGTOGSKVSnXPz8/NJu3btaP5t2rQhy5YtIzExMfSa+PHHH8mIESOIVColnTt3NlgPT09P0qxZMyKTycjs2bPJ6dOnSXx8PPnxxx/pdQ2AfPPNN3q90by+vvjiC6PXlzFeffVVmo/6e2QKL774Ig2WmKMXGhpKg2tPnz41+bznnnuOACDOzs60T9f0vUWLFvR7qq7Pnj17Ks1XM+Dn4eFB5syZQ44ePUouXrxIzpw5Q9avX09ee+01GrDJz8/X0jYnwBQfH0/Turq6ki+//JKcPHmSnD9/nqxcuZK0bNmSACA9e/Y0mufGjRu18lmyZAmJi4sjcXFxZMmSJcTNzY24uLjQ/NT9U0U0yy6VSsmUKVPIrl27SGJiIjl//jzZsWMH+eijj4i/vz8BQPbt26fT7qZgSoCJEEJGjBihFVwz1J+p9RcuXKiVduDAgWTFihUkOjqaJCUlkePHj5OVK1eSoUOH0gB9dQNMNfG3nQeYOP9JmAaY/uHUqVOC1GapXxceOLnvlof7zn1nBWvfWQaY8vLyLK5JSP0KMKWmphKpVEoAkMDAQJ0yf/fdd/QXdmMvqVRKbt68SQj5t91zcnJIx44dDZ7j5uZGTp48Sfr27VvpKIwvvviCBiQMvdTna/qelpamNYpAX3o1SqWSvP3220Y1nJ2dyZEjR/SWsbYCTISUPwxNnz6demXsJRKJyIQJE0h6erpOPnfv3tUKQul79ezZk2RlZekth7EAk2a7m/LAf/jwYTrKxdhLH1lZWWTw4MGVnguAhISEGK1HQkKC1miNiq93331XbxkIMe/6MkRRUREdidSqVSuTzlGzc+dOqrd48WKTzrl//z4drTdo0CCz9L799luqt2XLFkKItu/z5s3T+Y7rG71YEYVCQWbNmkUDEMZe9vb2pKioSEvbnAATIYQsWLDAqMaMGTMqzVOpVJJZs2bRUV0VX3Z2duTAgQOkd+/eBAAZPHiwwfJs2bKFXgPGXmKxmERHR+u0uymo86gswHTp0iWdOunrzzT1d+zYQXx9fU36PrZt21ZvH2pOgKkm/rbXlwATX+SbU+9IT00FfvsN+GdtEEuiXviPFaz1WcKy7qzbnbU+S7jvwkTIvmsuXM3RT5MmTTBp0iQA5dt379ixQ+v4e++9h9u3b2Pu3Ll49tln4eHhAWtra9jb2yMgIACjRo3Czz//jPT0dLp1ubrdnZ2dcfbsWSxatIiuV+jg4IDWrVtj5syZuHTpEvr06WNSOWfPno3k5GS89957aNeuHZycnCCTyeDn54d+/fph2bJl2LJli5Y+APj4+CA+Ph5TpkxBixYt6Jo5+hCLxVixYgVOnTqFl156CU2bNoWNjQ2cnJzQsWNHfPLJJ7h58yYGDhxoegPXEDKZDMuWLcPNmzexePFi9O/fH02bNoWtrS1kMhkaNWqEgQMHYs6cObh79y42bNhAFwjXxNfXF5cuXcKPP/6Ivn37wt3dHRKJBN7e3hg8eDA2bNiAU6dOVWnHNHO/b4MGDcKdO3fwxRdf4LnnnqNl8fHxQffu3fHJJ5/QNfEq4ubmhkOHDuHEiRN45ZVX0LJlS9jb28Pa2hpubm7o2rUrpk2bhoMHD+LYsWNGy9GlSxckJSXh3Xffhb+/P2QyGdzd3TF48GAcPHgQ33//vcFzfXx88Mcff2D8+PGVXl+G2L17N12rZtSoUWadO3jwYLpYv3oNp8rYsGEDXe/GXD3N9OpFwjV9r7iY9+jRo+madMawsrLCkiVLkJycjBkzZqBTp05wdXWFlZUVHB0d0bZtW7z00ktYv349Hj58SNczrWofP2/ePBw4cAADBw6Eq6srpFIpGjdujIiICBw9epTu3lgZ06dPR0xMDEaMGAEvLy/Y2NigWbNmePXVV3HhwgWEhYVRb41tejF27FikpKRg8eLFCA4OhpeXF10Dzs/PD+Hh4fj222+RkpKCkJCQatW9Mjp06IAxY8ZUmk5TPyIiAtevX8emTZswYcIEtGrVCq6urvT7GBQUhLfffhsnTpzAlStXqt2HCupvu0XCWJz/DHVhBNONiAhCAEL69iVEpbKo9u7duy2qV1f068KIBpZtz33nvgtJn/u+m+kIpuzsbItrEsJ2BJMaVnVnrc1Sn/vOTttcfWMjscyF+y5MbVN8Ly0tJba2tgQA+fTTT2tUvz593+qiNh/BxOHUEi2//bZ8K+aTJ4F/dqGzFMOHD7eoXl3TZwnLurNud9b6LOG+CxMh++7i4sJUnyUs68663Vnrs4T7LkyE6ntd91y9ozAAPPvsszWaN+u6c98tAw8wceodkefOAeptKD/8ENDYfrbWtf/ZapsVrPVZwrLurNudtT5LuO/CRMi+q7diFiIs68663Vnrs4T7LkyE6jtrz+/evWvwWEpKCj744AMAgLe3NwYNGlSj2qzrLmTfLYk16wJwOFXi44+B1auB27eB5cuBmTNZl4jD4XA4HA6Hw+Fw6ix9+/bFkCFDEB4ejrZt28Le3h4ZGRmIiYnBzz//jJycHADA119/DWtrHirgmA+/ajj1joCAAMDBAfjyS+CVV4BFi4BJkwBPT8toM4S1PktY1p11u7PWZwn3XZgI2feqLLj7X4Fl3Vm3O2t9lnDfhYlQfWftuVKpxP79+7F//369x8ViMf7v//4PEyZMqHFt1nUXsu+WhE+R49Q7vLy8yt9MnAgEBQF5ecC8eZbVZgRrfZawrDvrdmetzxLuuzARsu8SiYSpPktY1p11u7PWZwn3XZgI1XfWnq9btw5vvfUWOnbsiIYNG0IqlcLR0RGBgYGYOnUqLl26hNmzZ9eKNuu6C9l3S8IDTJx6x5kzZ8rfiMXAd98Bzz1XPpLJktqMYK3PEpZ1Z93urPVZwn0XJkL2PT8/n6k+S1jWnXW7s9ZnCffdNNatWwdCCFJSUmqvQBZEqL6zvuYGDBiAH3/8ERcvXsSDBw8gl8uRl5eHv//+Gz/99BPatWtXa9qs6y5k3y0JnyLHqd/06QOcOQOIRKxLwuFwOBwOh8PhcDgcjmDhI5g49Y7Q0FDtDzSDSwqFZbUtDGt9lrCsO+t2Z63PEu67MBGy705OTkz1WcKy7qzbnbU+S7jvwkSovnPPhanPuu6WhAeYOPWO27dv635YUFC+s1znzkBZmWW1LQhrfZawrDvrdmetzxLuuzARsu9yuZypPktY1p11u7PWZwn3XZgI1XfuuTD1WdfdkvAAE6fece/ePd0PVSpgzRrg8mVg5UrLalsQ1vosYVl31u3OWp8l3HdhImTfhXQTWhEh3/yz1mcJ912YCNV37rkw9VnX3ZLwABOn3iGVSnU/dHIC/u//yt8vWABkZVlO24Kw1mcJy7qzbnfW+izhvguTuuI7IcTi+mKxcG/NWNaddbuz1mcJ912YCNV37rkw9WtCm8U9SVUQ7hXOqbeMGjVK/4EpU4AOHYDs7PIgkyW1LQRrfZawrDvrdmetzxLuuzBh7bv6RlClUllc39XV1eKadQWWdWfd7qz1WcJ9FyZC9Z17Lkz9mtBWKpUA2AfqKqNul47D0cP27dv1H7CyAr79tvz9ypXA339bTttCsNZnCcu6s2531vos4b4LE9a+SyQSWFlZobCw0OL6T58+tbhmXYFl3Vm3O2t9lnDfhYlQfeeeC1O/JrSLiopgZWUFiURSAyWqPaxZF4BTP1ixYgVWrFhBI6e7d++Gg4MDIiIicOLECeTm5sLLywvdunXD/v37AQBBQUFQqVT4888/AQDDhw/HmTNnkJWVBTc3N/Tp0we7d+8GAHTo0AESiQSJiYkAgKFDh+LChQt4/PgxnJycMHDgQERFRQEA8vLycOfOHZw/fx4AMGjQIFy9ehXp6emwt7dHeHg4RPv2If3FF/F49Wp4eHjg7NmzAID+/fvjxo0bSE1NhY2NDSIiIrB161aoVCr4+/vDx8cHp06dAgAEBwcjNTUVd+7cgbW1NcaMGYP79+8jMjISzZo1g7+/P6KjowEAvXr1QkZGBm7cuAEAGD9+PPbs2YOioiI0btwYbdq0wdGjRwEAPXr0QG5uLpKTkwEAY8aMweHDh5Gfn48GDRogKCgIBw8eBAB07doVJSUluHLlCoDyyPXhw4eRnZ0NDw8P9OjRA/v27QMAdOrUCQBw8eJFAEB4eDji4uKQmZkJV1dXBAcHY9euXQCA9u3bQyaTISEhAQAQFhaGpKQkPHr0CI6Ojhg8eDB9wGvTpg1sbW0BAFFRURg8eDCSk5ORlpYGOzs7DB8+HJGRkQCAgIAAeHl54cyZMwDKd2O6ffs27t27B6lUilGjRmH79u1QKBTw8/ND06ZNERsbCwDo06cP0tPTcfv2bYjFYowdOxY7d+6EXC5H06ZNUVhYSHV69uyJzMxMXL9+HQAwduxY7N+/H4WFhfDx8UG7du1w5MgRAED37t1RUFCAv/76CwAwevRoHD16FHl5efD29kaXLl1w4MABAEDnzp1RVlaGy5cvAwBGjBiBU6dO4d69ezh69Ch69eqFPXv2AAA6duwIsViMpKQkAMCwYcMQHx+PjIwMODs7o1+/fti5cycAoF27drCzs0N8fDwAYMiQIbh06RIePHgABwcHhIWFYdu2bQCAwMBAuLm54dy5cwCAAQMGICMjA5GRkbC1tcWIESOwZcsWEELQsmVLNGjQAKdPnwYAhISEICUlBXfv3oVEIsHo0aMRFRWFsrIyNG/eHL6+voiJiQEA9O7dG48ePcLNmzchEokwbtw47N69G8XFxWjSpAkCAwNpG6ampqKgoADXrl0DALzwwgs4ePAgCgoK0KhRIzzzzDM4dOgQAKBbt24oKirC1atXAaDafcS9e/cQGRlpVh/Rtm1bODg4GOwjhg0bhq1btwIAWrVqZbCPePjwIQCY1Ufs2LEDpaWlNdJHqOtuTh8xcuRIxMbGVquPUI/auXPnDvWmsj7C2dkZcXFxAICBAwdWu4+4d+8ezp8/b1YfERAQgOPHjwOoXh+hUqlw8OBBWFtbo0mTJnBzc0Nubi4AwN7eHoQQFBUVASj/RTI/Px8KhQLW1tZwcHBATk4OAMDOzg4ikYgGqVxcXFBYWIiysjJYW1vD0dER2dnZAABbW1uIxWJ6XKFQoLi4GKWlpbCysoKzszO9ObW1tYWVlRUKCgoAlO9MU1JSgtLSUojFYri6uuLp06cghEAmk0EikSA/P5+mlcvlkMvlEIlEcHNzo2nVUwPVZXJ0dERZWRlKSkpo2uzsbKhUKkilUshkMuTl5QEAHBwcoFQqUVxcDAC0zZRKJaRSKWxtbbXaUKVS0bSabahQKKBUKmkbVmxvFxcXFBQU0PbWbENj7W1lZQUnJyet9tZsQ2dnZygUCmRlZem0t0wmg7W1tVZ7q9uwsvZ2dHREaWmpVnur29DGxgY2Nja0DQkhKCwsRElJCQDA3d0dOTk5etvQWHtLJBLY2dmZdM2q06p9V7/XbG9D12zF9nZ2dkZRURFtb2PXrLOzs9b1TQhB1j9LGxi7Ziu2t42NDaRSqVZ7G7pmK7a3g4MDFAoFSktL6d8cQ9dsxfZ2dXVFXl4ebW97e3uD12xlfYRSqaR1N7WP0NeG5vYR6nyLioq02tBYH1GxDavbR5SVlSErK8usPqKy9ja1jygrK4NSqTSrjzDU3ub2ESqVinpuTh+h2d5A1fsIoPx5Ql3XyvoIzfaubh+h9tzcPsLFxaVG+gjNftbUPkLd3tXtI9R9TVXvIwghyM3NRUZGBhITE8161rA0IlJfJvNx6gR5eXlwdnZGRkYGPD09mZTh/Pnz6N69u+EEN24AbdsCEgnw119A8+aW065lWOnL5XIsXrwYH3/8MWxsbCyuD7Bte+47911I+tz3cu2ioiLcu3cPTk5OaNSoEUQikUX0CwoK4ODgYBEtTVQqFR49eoQGDRowG37Pqu6stVnqc9+579x34Wiz9l2o37fqahNC8ODBA+Tl5aFZs2Y00GcqT548gZeXF3Jzc+Hk5FSlMpgDH8HEqXc0bdrUeIKAAOD334HevYHGjS2rXcuw1mcJy7qzbnfW+izhvguTuuC7nZ0dGjdujLS0NBQXF8PJyQl2dnawsrKq1WCTSqWiv5haEpVKRX+tZfXAyarurLVZ6nPfue/cd2Fps/RdqN+3qmgTQqBUKlFUVIS8vDyUlZWhcePGZgeXWMADTJx6R2xsLMaPH288UWXHa1O7FmGtzxKWdWfd7qz1WcJ9576z1HZ0dESzZs2Qm5uLnJwcOkS/NiksLIS9vX2t61REPfy+oKDAYqO1KsKq7qy1Wepz37nv3HfhaLP2Xajft+poW1lZwdHREc7OzvUiuATwABNHCJw6Vb67nIsL65JwOBwOp55hZ2cHOzs7NGjQAGVlZbW+s9z+/fsxbNiwWtXQR2lpKQ4ePIg33niDrsdkaVjVnbU2S33uO/ed+y4cbda+C/X7VlVtsVgMiUTCLAhcVXiAiVPv6NOnj+mJP/oI+OorYMYM4OuvLatdC7DWZwnLurNud9b6LOG+C5O66LtIJLLIDXmPHj0gk8lqXaci6oVE1QudsoBV3Vlrs9TnvnPfue/C0Wbtu1C/b6y1LQ2bSbccTjVIT083PXFoaPm/P/wA3LxpWe1agLU+S1jWnXW7s9ZnCfddmHDfhQn3XZhw34WJUH3nngtTn3XdLQkPMHHqHbdv3zY98aBBwJAhQFkZ8OGHltWuBVjrs4Rl3Vm3O2t9lnDfhQn3XZhw34UJ912YCNV37rkw9VnX3ZLwABOn3mH2rgfffANYWQF79gDR0ZbVrmFY67OEZd1ZtztrfZZw34UJ912YcN+FCfddmAjVd+65MPVZ192S1OuaZmRkYP/+/Zg3bx6GDBkCDw8PiEQiiEQiTJ482ez8Dh8+jIiICDRu3Bg2NjZo3LgxIiIicPjwYZPzKCoqwtKlS9GtWze4ubnBwcEBrVu3xsyZM5GammpyPn/99RemTp2KFi1awNbWFp6enujTpw9++eUXKBQKk/PZsmULBg0ahIYNG0Imk8HX1xcvv/wy/vjjD5PzqGuMHTvWvBNatwbeeqv8/fvvA0ql5bRrGNb6LGFZd9btzlqfJdx3YcJ9Fybcd2HCfRcmQvWdey5MfdZ1tyT1OsDk7e2N8PBwLFq0CIcPH67y9sGEELz55psYMmQIdu3ahfT0dJSWliI9PR27du3CkCFD8Oabb4IQYjSf27dvIygoCLNmzUJCQgKys7NRWFiIa9eu4ZtvvkGHDh1w8ODBSsuzevVqdO7cGb/88gtu376NkpISZGZm4vTp05g6dSp69+5daV1LSkoQHh6O8ePH4+jRo3j06BHkcjnu3buHjRs3omfPnli0aJFZ7VRX2Llzp/knzZ9fvovc5cvAmjWW1a5BWOuzhGXdWbc7a32WcN+FCfddmHDfhQn3XZgI1XfuuTD1WdfdktTrAJMmTZo0wcCBA6t07qeffopff/0VANCpUydERkYiPj4ekZGR6NSpEwDg119/xdy5cw3mUVBQgGHDhuH69esAgNdffx0nTpzAuXPn8Pnnn8PBwQG5ubkYM2YMLl++bDCfI0eO4I033oBcLoe3tzd++OEHnD9/HocOHUJERAQA4I8//kBERITRrZKnTJmC/fv3AwBCQkKwe/duxMfHY/Xq1fD394dKpcK8efPw22+/mddYdQC5XG7+Se7uwGefAY0bAx4eltWuQVjrs4Rl3Vm3O2t9lnDfhQn3XZhw34UJ912YCNV37rkw9VnX3ZJYsy5AdZg3bx66du2Krl27wtvbGykpKWjevLlZedy6dQtfffUVAKBLly44deoUbG1tAQBdu3bF888/j759++LChQtYsmQJXnnlFfj7++vk8/XXX+PatWsAgK+++gofaiwo3aNHD4SEhKBPnz4oKirCe++9h2g9awEpFAq88847UKlUcHJywtmzZ7W0Bg8ejGnTpmHlypU4deoUNm7ciIkTJ+rkc/LkSWzevBkAEB4ejl27dsHKykqrTp07d0ZqaipmzZqF0aNHw8XFxax2Y0nTpk2rduK0acAbbwB2dpbXriFY67OEZd1ZtztrfZZw34UJ912YcN+FCfddmAjVd+65MPVZ192S1OsRTAsWLMCwYcPg7e1d5Ty+++47uqbR8uXLaXBJjZ2dHZYvXw6gPAC0bNkynTzKysrw/fffAwBat26NGTNm6KTp0aMHpkyZAgCIiYlBYmKiTppdu3bh1q1bAIDZs2frDWQtXboUrq6u9L0+1AEzKysrrFy5kgaX1Hh4eGDJkiUAgOzsbKxevVpvPnWVgICAqp0okVQruFQt7RqCtT5LWNaddbuz1mcJ912YcN+FCfddmHDfhYlQfeeeC1Ofdd0tSb0OMFUXQgj27NkDAAgMDMSzzz6rN92zzz6LVq1aAQB2796tsxZTbGwscnJyAACTJk0yuEq85sLj+uZh7t69W29aTezs7PDCCy8AAK5evYqbN29qHS8oKMCJEycAAAMGDEDjxo315hMREQEnJyeDZanLHD9+vHoZKJXl6zBNm2Z57WrCWp8lLOvOut1Z67OE+y5MuO/ChPsuTLjvwkSovnPPhanPuu6WRNABprt37yI9PR0A0LdvX6Np1cfT0tKQkpKidez06dM66fTRpUsX2NvbAwDOnDmjc1ydT6tWrdCgQYNKy6Ivn/j4eDrH01hZpFIpDajFx8ejrKzMYNr/HDdvAq+/DqxcCZw6xbo0HA6Hw+FwOBwOh8Ph1HsEHWD6+++/6fvAwECjaTWPa55nTj7W1tZ02lvFPAoKCpCWlmaxsmgeVygUOiOh6jI9e/asXgaBgeVrMQHA++8DRhZLr3HtasJanyUs68663Vnrs4T7Lky478KE+y5MuO/CRKi+c8+Fqc+67pZE0AGm+/fv0/eGppKpadKkid7zNP9vb29f6WLZ6nyePHmitZp8WloanXpXE2Wpbj51mczMzOpnsnAh4OQEJCUBv/9uWe1qwFqfJSzrzrrdWeuzhPsuTLjvwoT7Lky478JEqL5zz4Wpz7rulqRe7yJXXfLz8+l7BwcHo2nVU9uA8tFG+vKpLA99+djY2NRKWaqbjxq5XK4VCMvLy9P7uSVJTk5G27Ztq5eJkxOsZs+G9ezZILNnozQ8HDDBvxrRrgas9NVes9xik2Xbc9+570LS575z31nBfee+C0mbpT73XZjarH0X6veNtbal/RaRiitW12NSUlLQvHlzAOWLba9bt85o+kWLFmHevHkAgBMnTiA0NNRg2ujoaPTr14+e9+mnn9Jj/v7+uHPnDpo0aYLU1FSjmhMnTsSGDRsAlI8aUo8yOn36NPr06QMAmDt3LhYuXGgwD5VKRXeG69evn9aiYVOmTMGaNWsAALdv34afn5/BfNasWUN3ttuwYQMmTJigk2b+/PlYsGCBzucff/wxZDKZ0brWdawUCry9YgXcsrNxqk8fxBjxn8PhcDgcDofD4XA4nPpESUkJFi9ejNzcXLrJV20i6BFMmgGS0tJSo2k1I3+2trZ686ksD2P51HRZqpuPmtmzZ+ODDz6g/8/Ly0OTJk0wbdo0eHp6Gs2/tlCpVAZ36jMXcfv2wNix6J2QgO5btgBubhbTrgqs9OVyOb777ju8//77dNSdpWHZ9tx37ruQ9Lnv3Hfuu3D0ue/cd+67cLRZ+y7U7xtr7SdPnmDx4sUW0xN0gMnR0ZG+NzRFTE1hYSF9X3HqmTqfyvIwlk9Nl6W6+aixsbHR2wEZ+twS7N27F88//3zNZDZmDHDuHETjxsGmYUPLalcB1vr/Gd/rkXZd0Oe+s4G1PvedDaz1ue9sYK3PfWcDa33uu7C01bDynXXdheq7pb0W9CLfmotgq3dwM4TmItiai2Nr5lNYWIicnByT8vH09NQyu6bLUt186jKagbFqIxIBy5YBzz5ree0qwFqfJSzrzrrdWeuzhPsuTLjvwoT7Lky478JEqL5zz4Wpz7rulkTQAaY2bdrQ99euXTOaVvN469atq5SPQqHA7du39ebh4OBAgzyWKIvmcWtra7Ro0cJo2rqEj49P7WWelgaoVGy0TYC1PktY1p11u7PWZwn3XZhw34UJ912YcN+FiVB9554LU5913S2JoANMzZs3R6NGjQAAJ0+eNJr21KlTAMovDl9fX61jvXr1ou+N5XPhwgUavezZs6fOcXU+169fx6NHjwzmo6lRMZ+uXbtCKpVWWpbS0lL88ccfOufUB9q1a1c7GX/xBdCiBRAZaXltE2GtzxKWdWfd7qz1WcJ9Fybcd2HCfRcm3HdhIlTfuefC1Gddd0si6ACTSCTC8OHDAZSP5lEHXCryxx9/0NE+w4cPh0gk0joeHBwMZ2dnAMD69ethaGM+zV3tRo4cqXN8xIgRetNqUlRUhG3btgEoH60UEBCgddzR0ZHudnf8+HGD0+R27tyJvLw8g2Wpyxw5cqR2MhaJALkc+PhjoKjIstomwlqfJSzrzrrdWeuzhPsuTLjvwoT7Lky478JEqL5zz4Wpz7rulkTQASYAeO+992BtXb7W+f/+9z8UFxdrHS8uLsb//vc/AOVTyd577z2dPKRSKd59910AwN9//42vv/5aJ01cXBxWr14NAOjbty+6du2qk2bkyJHw9/cHAHz55Zd0Op0mH374IbKzs+l7ffw/e2ceF9V1/+9nRhBZlIiIRsCNuASNuxgUCe6KGBDBJUmTNP1la5K2aZM07TeLaZtvTJNvkyaxTWz2DVFUiKhI3IqoEcFdggtoUFwQ0UFE9vv7Y2TiggvC3Dt4Ps/rxcth5s55nzNP5pPj8d5zn3vuOcB6Sd5TTz1FTU3NJa8XFRXxxz/+EYDbbruN//f//l+97SjHs89Cly7Wy+TqcSgIgiAIgiAIgiAIQv0067vIpaenc+DAAdvvRUVFtscHDhy44iyghx9++Io2evbsyXPPPcecOXPIzMxkxIgR/PGPfyQgIIDc3FzefPNNtm3bBlgXdHr06FFvX55//nni4+PZt28fL7zwAgcOHGDmzJm4urqydu1a/vd//5fq6mpcXV159913623D2dmZ9957jylTplBSUsKIESN46aWXCAoK4vTp0/znP/9h0aJFgPVyul/84hf1tjN69GhmzpzJ/Pnz+e677xg3bhy/+93v6NSpE7t27eL1118nPz8fgDlz5tC2bdt623FUhg0bZp+GW7WCv/8dZsyAN9+ERx6BizZNt2v2DWJ0vpEYOXajP3ej841EvKuJeFcT8a4m4l1NVPUuztXMN3rsetKsF5g+/vhjvvjii3pf27BhAxs2bLjkufoWmABef/11CgsL+fTTT9m2bRszZ8684phf/epX/O1vf7tqX1q3bs2yZcsIDw9n//79zJs3j3nz5l1yTJs2bfjmm28YMGDAVdsJDw/nww8/5Omnn+bEiRO2s6cuJigoiCVLltCiRYurtvPpp59SUlLC8uXLWbt2LWvXrr3kdbPZzMsvv8zjjz9+1TYcldLSUvs1HhsL770HGzbAn/8MX36pX/YNYHS+kRg5dqM/d6PzjUS8q4l4VxPxribiXU1U9S7O1cw3eux6ovwlcmBdbPnkk09YtmwZkZGRdOrUiZYtW9KpUyciIyNZvnw5H3/8MWbztT+uO+64g23btvHmm28yZMgQbrvtNtzc3OjVqxfPPvssO3fuJCIi4rr9efTRR8nKyuLRRx+le/futGrVinbt2hESEsK///1vNmzYgLe39zXbcHV1ZdmyZXzzzTeMGzcOHx8fWrZsib+/P/fddx/p6enMnj27IR+Tw7Bnzx77NW4ywTvvWB9/9RVs2aJf9g1gdL6RGDl2oz93o/ONRLyriXhXE/GuJuJdTVT1Ls7VzDd67HrSrM9g+vzzz6+6GfbNEB4eTnh4eKPacHd354UXXuCFF15oVDt9+/a94gyom+G+++7jvvvua3Q7SjF0KDz4ICxcCHv2WH8XBEEQBEEQBEEQBOGqyBlMQrMjJibG/iFvvgl798Jll1Xqkn0NjM43EiPHbvTnbnS+kYh3NRHvaiLe1US8q4mq3sW5mvlGj11PZIFJaHakpqbaP6RjR/D3Nyb7GhidbyRGjt3oz93ofCMR72oi3tVEvKuJeFcTVb2LczXzjR67njTrS+QENSkpKdE3cPVq6+VyJ08y5Mcf4dNPISrKuiF4q1a6dkX3sTsQRo7d6M/d6HwjEe9qIt7VRLyriXhXE1W9i3M1840eu57IApPQ7OjQoYN+YW+8Yb2bHIDZTIfaWuulc4sXw29/C198AVOm6NYdXcfuYBg5dqM/d6PzjUS8q4l4VxPxribiXU1U9S7O1cw3eux6IpfICc2OIUOG6BP03XfwP//z8++1tZf+eeYMREZaj9MJ3cbugBg5dqM/d6PzjUS8q4l4VxPxribiXU1U9S7O1cw3eux6IgtMQrNj2bJl9g8pL79ig+8r0DTrnw8/bD1eB3QZu4Ni5NiN/tyNzjcS8a4m4l1NxLuaiHc1UdW7OFcz3+ix64lcIifcEHPnzmXu3LnU1NQAkJiYiIeHB9HR0axevRqLxYKPjw9BQUEkJycDMGjQIGpra9m+fTsAkZGRpKenc+rUKby8vAgNDSUxMRGAfv364ezsTFZWFgCTJ08mMzOTEydO0KZNG8aPH09CQgJgvYY1Ly+PzZs3AzBhwgR2795NQUEB7u7uREREEB8fD0CvXr3w9vZmw4YNAIwdO5Z9+/aRn5+Pi4sL0dHRxMfHU1tbS0BAAL6+vqSlpdF1/XqCT5++/gejaXD6NKc++ohDISHs27cPgFmzZpGUlERZWRl+fn4EBgbaNncLDg7GYrGQnZ0NQGxsLCkpKZw9e5aOHTsyaNAgli9fDsDQoUMpLy9n165dANTU1JCSksLp06fx9vYmODiYpUuXAjBw4EAAtm3bBsCUKVPYtGkTRUVFtG3blrCwMJYsWQLAXXfdRatWrdiyZQsA4eHhbN26lePHj9O6dWsmTpzIwoULAQgMDMTV1RWAhIQEJk6cSHZ2NkeOHMHNzY3IyEji4uIA6NmzJz4+PqSnpwMwevRocnNz+emnn2jZsiXTpk1j4cKFVFdX0717dzp37sy6desACA0NpaCggNzcXMxmMzNmzGDx4sVUVFTQuXNnKioqbDkjRoygqKiIvXv3AjBjxgySk5M5d+4cvr6+9O3bl5UrVwIwbNgwSktL2bNnD2C9i0NqaiolJSV06NCBIUOG2Ir+4MGDqaqqYufOnQBERUWRlpZGQUEBqamphISEkJSUBMCAAQMwm81s3boVgIiICDIyMigsLMTT05MxY8awePFiAPr27YubmxsZGRkATJo0iR07dnD06FE8PDwIDw9nwYIFAPTu3RsvLy82btwIwLhx4yguLiYuLg5XV1eioqKYP38+mqbRo0cPOnbsyPr16wEYNWoUhw4d4uDBgzg7OxMTE0NCQgJVVVV069aNrl27snbtWgBGjhzJ8ePH2b9/PyaTiZkzZ5KYmMj58+fx9/end+/ets8wPz+f0tJScnJyAJg+fTrLly+ntLSUTp060b9/f1asWAFAUFAQZWVl7N69G6DRNaKgoIC4uLgG1Yg+ffrg4eHR6Bpx7NgxgHprBEBYWBj5+fnk5eXh5OREbGwsixYtorKyki5duhAQEMCaNWsACAkJobCwsEE1om7sDakRU6dOZd26dY2qEbUXztLMy8uzublejfD09GTTpk0AjB8/vtE1oqCggM2bNzeoRvTs2ZNVq1YBjasRtbW1LFu2rEE1ori4mHbt2jVJjSgoKODMmTMNqhE5OTkcPny4UTXC/8KNLRISEjCbzTdUI77//nsAhg8fTnFxcaNrRFFREWfPnrX7PKK+GnHq1Cni4uKabB7R0Bpx/vx5srKy7D6PuLxGDB482Oa97rE95hHXqhGALvOI+mpEXZ219zziajWitLTUNnZ7ziMurxGLFi2yufbz87PbPOJaNeLEiRPExcXZfR5RX40oKCigpKTE7vOI+mpEeXm5zbm95xGX1wiLxQKAxWJh9erVgH3mEVB/jSgqKiIuLk6XeUR9NaK8vJyMjAy7zyPqqxF1tUaPeQRcWiN0RxOEBmCxWDRAKywsNKwPe/futX9IdLSmmc2aZl1CuvaP2Ww9Xgd0GXs9lJeXa7Nnz9bKy8sNydc048ZudLaR+eJdvBuFeNcf8S7ejUK86494VzPbaO+qft+Mzi4sLNQAzWKx6JInl8gJzY6qqir7h5w69fNeS9ejthaKi+3bnwvoMnYHxcixG/25G51vJOJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWASmh11pxTalXbtwHyDXw+zGby87NufC+gydgfFyLEb/bkbnW8k4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBKE+oiKatgZTFOn2rU7giAIgiAIgiAIguDIyAKT0OyIioqyf0hsLLRtCybT9Y9t2xZiYuzfJ3Qau4Ni5NiN/tyNzjcS8a4m4l1NxLuaiHc1UdW7OFcz3+ix64ksMAnNjrq7s9iVVq3giy+sj6+3yHT//dbjdUCXsTsoRo7d6M/d6HwjEe9qIt7VRLyriXhXE1W9i3M1840eu57IApPQ7CjWaUNtpkyBxES47Tbr73V7MtX9WbeoNG8e/PCDLl3SbewOiJFjN/pzNzrfSMS7moh3NRHvaiLe1URV7+JczXyjx64nssAkNDvatWunX9i998LRo/DVVxAVRXG/ftb9mb76ynqnualTobISoqOtx9kZXcfuYBg5dqM/d6PzjUS8q4l4VxPxribiXU1U9S7O1cw3eux64mR0BwShoYSEhOgb2KoVPPAAPPAArcrKwM3t59e++AL27oXsbJg2DdatAxcXu3VF97E7EEaO3ejP3eh8IxHvaiLe1US8q4l4VxNVvYtzNfONHrueyBlMQrMjKSnJcbJbt4akJOtldD/8AE89BZqmX75COJR3xfKNRLyriXhXE/GuJuJdTVT1Ls7VzDd67HoiC0yC0FjuuAPmz7fuzfTDD1BSYnSPBEEQBEEQBEEQBEFXZIFJaHYMGDDA8bInTIDFi2HTJvD01D9fARzSuyL5RiLe1US8q4l4VxPxriaqehfnauYbPXY9kT2YhGaH2Wzcuug1syMjL/29uhqcmvYrZuTYjcZhvSuQbyTiXU3Eu5qIdzUR72qiqndxrma+0WPXE3VGKtwybN261bGzNQ3eegtCQuD8ef3zb1Ec3vstnG8k4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBKEpqawEN58EzZvhsces+um34IgCIIgCIIgCILgCMgCk9DsiIiIcOzsDh0gPh5atICvv4Z//lPf/FsUh/d+C+cbiXhXE/GuJuJdTcS7mqjqXZyrmW/02PVEFpiEZkdGRobjZ48ZA2+/bX383HOwerW++bcgzcL7LZpvJOJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWASmh2FhYXNI/u3v4UHH4SaGpgxAw4e1Df/FqPZeL8F841EvKuJeFcT8a4m4l1NVPUuztXMN3rseiJ3kRNuiLlz5zJ37lxqamoASExMxMPDg+joaFavXo3FYsHHx4egoCCSk5MBGDRoELW1tWzfvh2AyMhI0tPTOXXqFF5eXoSGhpKYmAhAv379cHZ2JisrC4DJkyeTmZnJiRMnaNOmDePHjychIQGAqqoq8vLy2Lx5MwATJkxg9+7dFBQU4O7uTkREBPHx8QD06tULb29vNmzYAMDYsWPZt28f+fn5uLi4EB0dTXx8PLW1tQQEBODr60taWhoAYWFh5Ofnk5eXh5OTE7GxsRQVFREXF0eXLl0ICAhgzZo1AISEhFBYWMi+ffsAmDVrFknffUfF6NFMysigdU4Op8PCSP3rXxkWGorFYiE7OxuA2NhYUlJSOHv2LB07dmTQoEEsX74cgKFDh1JeXs6uXbsAcHd3JyUlhdOnT+Pt7U1wcDBLly4FYODAgQBs27YNgClTprBp0yaKiopo27YtYWFhLFmyBIC77rqLVq1asWXLFgDCw8PZunUrx48fp3Xr1kycOJGFCxcCEBgYiKurKwAJCQlMnDiR7Oxsjhw5gpubG5GRkcTFxQHQs2dPfHx8SE9PB2D06NHk5uby008/0bJlS6ZNm8bChQuprq6me/fudO7cmXXr1gEQGhpKQUEBubm5mM1mZsyYweLFi6moqKBz5860bNnSljNixAiKiorYu3cvADNmzCA5OZlz587h6+tL3759WblyJQDDhg2jtLSUPXv2ABATE0NqaiolJSV06NCBIUOGsGzZMgAGDx5MVVUVO3fuBCAqKoq0tDQKCwtJTU0lJCSEpKQkwHq7UbPZbNu0LyIigoyMDAoLC/H09GTMmDEsXrwYgL59++Lm5mb714tJkyaxY8cOjh49ioeHB+Hh4SxYsACA3r174+XlxcaNGwEYN24cZWVlxMXF4erqSlRUFPPnz0fTNHr06EHHjh1Zv349AKNGjeLQoUMcPHgQZ2dnYmJiSEhIoKqqim7dutG1a1fWrl0LwMiRIzl+/Dj79+/HZDIxc+ZMEhMTOX/+PP7+/vTu3dv2Gebn51NaWkpOTg4A06dPZ/ny5ZSWltKpUyf69+/PihUrAAgKCqKsrIzdu3cDNLpGFBYWEhcX16Aa0adPHzw8PBpdI4qKigAaVCMWLVpEZWXljdWIpCTKysrw8/MjMDCQ1NRUAIKDg7FYLLaxN6RGTJ06lXXr1jWqRtTW1gKQl5dnc3O9GuHp6cmmTZsAGD9+fKNrRGFhIZs3b25QjejZsyerVq0CGlcjPDw8WLZsWYNqRHFxMe3atWuSGlFYWMiZM2caVCNycnI4fPhwo2qEv78/YK3zZrP5hmrE999/D8Dw4cMpLi5udI04e/YsZ8+etfs8or4ace7cOeLi4uw+j7hajTCbzWRlZTWoRtzMPOLyGjF48GCb97rH9phHXKtGeHp66jKPqK9G1NVZe88jrlYjNE2zjd2e84jLa8SiRYtsrv38/Ow2j7hWjTh9+jRxcXF2n0fUVyMKCwspKSmx+zyivhrRokULm3N7zyMurxEWiwUAi8XC6gtXV9hjHgH114jS0lLi4uJ0mUfUVyNatGhBRkaG3ecR9dWIulqjxzwCLq0RemPSNNmBWLhxSkpK8PT0pLCwkPbt2xvSh4qKClxcXJpP9uHDMHw4/OlP8OSTYDLpm98EVFRUMGfOHF588cXm9dnfAtlG5ot38a7iZy/exbtK+eJdvKv42aucbaR3Vb9vRmefPHkSHx8fLBYLbdq0sXueXCInNDvqVmqbTba/P+zdC7/+daMWl246/xah2Xm/hfKNRLyriXhXE/GuJuJdTVT1Ls7VzDd67HoiC0yCoAdubj8/Pn0afvjBuL4IgiAIgiAIgiAIQhMjC0xCs6Nv377NNzs/H4KCYOJE2L9f//xmTLP23szzjUS8q4l4VxPxribiXU1U9S7O1cw3eux6IgtMQrPD7eKzgZpbdocO4OMDFgtERsLZs/rmN2Oatfdmnm8k4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBKaHXW74zfLbBcXSEiATp3gxx/hwQfhwh2bdMlvxjRr780830jEu5qIdzUR72oi3tVEVe/iXM18o8euJ7LAJAh6c/vtsHgxtGwJiYnwt78Z3SNBEARBEARBEARBaBSywCQ0OyZNmtT8s4cNgw8/tD5+9VX47jt985sht4T3ZppvJOJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWASmh07duy4NbJ/+Ut4+mnr45degpoaffObGbeM92aYbyTiXU3Eu5qIdzUR72qiqndxrma+0WPXEyejOyAIDeXo0aO3TvY//gGurvD889Cihf75zYhbynszyzcS8a4m4l1NxLuaiHc1UdW7OFcz3+ix64ksMAnNDg8Pj1sn29kZ/v534/KbEbeU92aWbyTiXU3Eu5qIdzUR72qiqndxrma+0WPXE7lETmh2hIeH37rZn30Gr71mXL4Dc0t7d/B8IxHvaiLe1US8q4l4VxNVvYtzNfONHrueyAKT0OxYsGDBrZmdmQmPPAKzZ8PChfrnOzi3rPdmkG8k4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBIER2HIEHjuOevjhx+GnTsN7Y4gCIIgCIIgCIIg3CiywCQ0O3r37n3rZr/xBowbB2VlEBUFxcX65jswt7R3B883EvGuJuJdTcS7moh3NVHVuzhXM9/oseuJLDAJzQ4vL69bN9vJCebPh+7d4eBBmDkTqqv1y3dgbmnvDp5vJOJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWASmh0bN268tbO9vCAxEdzd4fvv4cUX9c13UG557w6cbyTiXU3Eu5qIdzUR72qiqndxrma+0WPXE1lgEgRH5K674IsvwGSC1q1B04zukSAIgiAIgiAIgiBcFSejOyA0D+bOncvcuXOpqakBIDExEQ8PD6Kjo1m9ejUWiwUfHx+CgoJITk4GYNCgQdTW1rJ9+3YAIiMjSU9P59SpU3h5eREaGkpiYiIA/fr1w9nZmaysLAAmT55MZmYmJ06coE2bNowfP56EhAQAOnfuTF5eHps3bwZgwoQJ7N69m4KCAtzd3YmIiCA+Ph6AXr164e3tzYYNGwAYO3Ys+/btIz8/HxcXF6Kjo4mPj6e2tpaAgAB8fX1JS0sDICwsjPz8fPLy8nByciI2NhZN04iLi6NLly4EBASwZs0aAEJCQigsLGTfvn0AzJo1i6SkJMrKyvDz8yMwMJDU1FQAgoODsVgsZGdnAxAbG0tKSgpnz56lY8eODBo0iOXLlwMwfMUKzvr6smv+fABCQ0NJSUnh9OnTeHt7ExwczNKlSwEYOHAgANu2bQNgypQpbNq0iaKiItq2bUtYWBhLliwB4K677qJVq1Zs2bIFsN46c+vWrRw/fpzWrVszceJEFl64k11gYCCurq4AJCQkMHHiRLKzszly5Ahubm5ERkYSFxcHQM+ePfHx8SE9PR2A0aNHk5uby08//UTLli2ZNm0aCxcupLq6mu7du9O5c2fWrVtnG1tBQQG5ubmYzWZmzJjB4sWLqaiooHPnzgwePNiWM2LECIqKiti7dy8AM2bMIDk5mXPnzuHr60vfvn1ZuXIlAMOGDaO0tJQ9e/YAEBMTQ2pqKiUlJXTo0IEhQ4awbNkyAAYPHkxVVRU7L2ywHhUVRVpaGpWVlaSmphISEkJSUhIAAwYMwGw2s3XrVgAiIiLIyMigsLAQT09PxowZw+LFiwHo27cvbm5uZGRkADBp0iR27NjB0aNH8fDwIDw83HZ3id69e+Pl5WX7l45x48bRrl074uLicHV1JSoqivnz56NpGj169KBjx46sX78egFGjRnHo0CEOHjyIs7MzMTExJCQkUFVVRbdu3ejatStr164FYOTIkRw/fpz9+/djMpmYOXMmiYmJnD9/Hn9/f3r37m37DPPz8yktLSUnJweA6dOns3z5ckpLS+nUqRP9+/dnxYoVAAQFBVFWVsbu3bsBGl0jKisriYuLa1CN6NOnDx4eHo2uEXU0pEYsWrSIysrKJqkRdWO/Vo0YOnQo5eXl7Nq1C4CpU6eybt26RtWI2tpaAPLy8mxurlcjPD092bRpEwDjx49vdI2orKxk8+bNDaoRPXv2ZNWqVUDjakRYWBjLli1rUI0oLi6mXbt2TVIjKisrOXPmTINqRE5ODocPH25UjfD39wesdd5sNt9Qjfj+++8BGD58OMXFxY2uER4eHpw9e9bu84j6akTbtm2Ji4uz+zziajWib9++ZGVlNfk84no1YvDgwTbvdY/tMY+4Vo0YN26cLvOI+mpEXZ219zziajXijjvusI3dnvOIy2vEokWLbK79/PzsNo+4Vo1wcnIiLi7O7vOI+mpEZWUlJSUldp9H1Fcj+vXrZ3Nu73nE5TXCYrEAYLFYWL16NWCfeQTUXyPatGlDXFycLvOI+mpEv379yMjIsPs8or4aUVdr9JhHwKU1Qnc0QWgAFotFA7TCwkLD+rB+/Xols7Vz57RNycmGRJeXl2uzZ8/WysvLDcnXNIW9G5gv3sW7UYh3/RHv4t0oxLv+iHc1s432rur3zejswsJCDdAsFosueXIGk9DsOHz4sHrZ+fkQFUX38+dh/HhwdjamHwaipHcHyTcS8a4m4l1NxLuaiHc1UdW7OFcz3+ix64nswSQ0O+ou11Iq+9w5OHAAn5wc+P3vjemDwSjp3UHyjUS8q4l4VxPxribiXU1U9S7O1cw3eux6IgtMQrMjKipKvew774Svv7Y+/uAD+PRTY/phIEp6d5B8IxHvaiLe1US8q4l4VxNVvYtzNfONHrueyAKT0OyYf2HDa9WyufdedsXEWB8/+SRc2HhQFZT17gD5RiLe1US8q4l4VxPxriaqehfnauYbPXY9kQUmodmhaZqS2QC7o6Jg6lSorIToaDh2zND+6InK3o3ONxLxribiXU3Eu5qIdzVR1bs4VzPf6LHriSwwCc2OHj16KJkN0KNXL/jiCwgMhKNH4YknDO2Pnijt3eB8IxHvaiLe1US8q4l4VxNVvYtzNfONHrueyAKT0Ozo2LGjktm2/NatISkJxoyB994ztD96orx3RRHvaiLe1US8q4l4VxNVvYtzNfONHrueyAKT0OxYv369ktmX5N9xB6xaBV26GNofPRHvaiLe1US8q4l4VxPxriaqehfnauYbPXY9kQUmQbgVSEqC9HSjeyEIgiAIgiAIgiAoipPRHRCEhjJq1Cgls6+av3gxTJsGPj6QmQn+/vp3TAfEu5qIdzUR72oi3tVEvKuJqt7FuZr5Ro9dT+QMJqHZcejQISWzr5o/YQL07w+FhdY7zJ0/r3u/9EC8q4l4VxPxribiXU3Eu5qo6l2cq5lv9Nj1RBaYhGbHwYMHlcy+ar67OyQmQrt2kJVlvbPcLXgrTPGuJuJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWASmh3Ozs5KZl8zv2tXiI+HFi3gyy9vybvLiXc1Ee9qIt7VRLyriXhXE1W9i3M1840eu56YNO0WPNVBsBslJSV4enpSWFhI+/btje6OcDnvvgvPPmtdaEpNhdGjm6TZiooK5syZw4svvoiLi0uTtCk4PuJdTcS7moh3NRHvaiLe1US8q8nJkyfx8fHBYrHQpk0bu+fJGUxCsyMhIUHJ7BvK/+1v4Re/gJoaWLtWn07phHhXE/GuJuJdTcS7moh3NVHVuzhXM9/oseuJ3EVOaHZUVVUpmX1D+SYTfPQRREVBdLQufdIL8a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xM5g0lodnTr1k3J7BvOd3W9dHGpuvqW2PRbvKuJeFcT8a4m4l1NxLuaqOpdnKuZb/TY9UTOYBJuiLlz5zJ37lxqamoASExMxMPDg+joaFavXo3FYsHHx4egoCCSk5MBGDRoELW1tWzfvh2AyMhI0tPTOXXqFF5eXoSGhpKYmAhAv379cHZ2JisrC4DJkyeTmZnJiRMnaNOmDePHj7edWujr60teXh6bN28GYMKECezevZuCggLc3d2JiIggPj4egF69euHt7c2GDRsAGDt2LPv27SM/Px8XFxeio6OJj4+ntraWgIAAfH19SUtLAyAsLIz8/Hzy8vJwcnIiNjaW3NxcDh48SJcuXQgICGDNmjUAhISEUFhYyL59+wCYNWsWSUlJlJWV4efnR2BgIKmpqQAEBwdjsVjIzs4GIDY2lpSUFM6ePUvHjh0ZNGgQy5cvB2Do0KGUl5eza9cuAIYPH05KSgqnT5/G29ub4OBgli5dCsDAgQMB2LZtGwBTpkwhc8UK7pw9mzN3302XuXNZsmQJAHfddRetWrViy5YtAISHh7N161aOHz9O69atmThxIgsXLgQgMDAQV1dXwHp658SJE8nOzubIkSO4ubkRGRlJXFwcAD179sTHx4f09HQARo8eTW5uLj/99BMtW7Zk2rRpLFy4kOrqarp3707nzp1Zt24dAKGhoRQUFJCbm4vZbGbGjBksXryYiooKOnfujJeXly1nxIgRFBUVsXfvXgBmzJhBcnIy586dw9fXl759+7Jy5UoAhg0bRmlpKXv27AEgJiaG1NRUSkpK6NChA0OGDGHZsmUADB48mKqqKnbu3AlAVFQUaWlpHDt2jJKSEkJCQkhKSgJgwIABmM1mtm7dCkBERAQZGRkUFhbi6enJmDFjWLx4MQB9+/bFzc2NjIwMACZNmsSOHTs4evQoHh4ehIeHs2DBAgB69+6Nl5cXGzduBGDcuHGcOXOGuLg4XF1diYqKYv78+WiaRo8ePejYsSPr168HYNSoURw6dIiDBw/i7OxMTEwMCQkJVFVV0a1bN7p27craC5dOjhw5kuPHj7N//35MJhMzZ84kMTGR8+fP4+/vT+/evW2fYX5+PqWlpeTk5AAwffp0li9fTmlpKZ06daJ///6sWLECgKCgIMrKyti9ezdAo2tETk4OBw8ebFCN6NOnDx4eHo2uEbW1tdx9990NqhGLFi2isrKySWpE3dgbUiOmTp3KunXrbrhGbNq0iaKiItq2bUtYWBhLliyhtrYWgLy8PJub69UIT09PNm3aBMD48eMbXSPOnTuHyWRqUI3o2bMnq1atanSNCAkJYdmyZQ2qEcXFxbRr165JakRFRQW9e/duUI3Iycnh8OHDjaoR/v7+gLXOm83mG6oR33//PWD9f1NxcXGja4Sbmxtnz561+zyivhpRXFxMXFyc3ecRV6sRd955J1lZWXafR1xeIwYPHmzzXvf4ejUCGj6PuFaNGDZsmC7ziPpqRF2dtfc84mo1ArCN3Z7ziMtrxKJFi2yu/fz87DaPuFaNyM/P5+DBg3afR9RXIyoqKggMDLT7PKK+GuHm5mZzbu95xOU1wmKxAGCxWFi9ejVgn3kE1F8jTp48SVxcnC7ziPpqRJ8+fcjIyLD7PKK+GlFXa/SYR8ClNUJ3NEFoABaLRQO0wsJCw/rw7bffKpl9U/mffaZpoGkmk6atWHHTueXl5drs2bO18vLym26jsYh3/RHv4t0oxLv+iHfxbhTiXX/Eu5rZRntX9ftmdHZhYaEGaBaLRZc8uUROEG5lHnoIHn3UeoncrFlw4IDRPRIEQRAEQRAEQRBuQWSBSWh2jBw5Usnsm8o3meD99yE4GM6csW7+ffasPbpmd8S7moh3NRHvaiLe1US8q4mq3sW5mvlGj11PZIFJaHYcP35cyeybzndxgUWL4PbbYc8e61lNF/ZYaU6IdzUR72oi3tVEvKuJeFcTVb2LczXzjR67nsgCk9Ds2L9/v5LZjcq//XZYvBhatoQlS+DNN5u2Yzog3tVEvKuJeFcT8a4m4l1NVPUuztXMN3rseiILTEKzw2QyKZnd6Py774Z//xvuuAPuvbfpOqUT4l1NxLuaiHc1Ee9qIt7VRFXv4lzNfKPHricmTdM0ozshNB9KSkrw9PSksLCQ9u3bG90d4WY4fx5cXRv0loqKCubMmcOLL76Ii4uLnTomOBriXU3Eu5qIdzUR72oi3tVEvKvJyZMn8fHxwWKx0KZNG7vnyRlMQrMjMTFRyewmy794cWnjRuvm380A8a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYLpAeXk5//rXvxgzZgzt27enZcuW+Pr6MnnyZOLj42+4nZSUFKKjo/Hz88PFxQU/Pz+io6NJSUm54TbKysp46623CAoKwsvLCw8PD+68806ee+458vPzb7idPXv28MQTT3DHHXfg6upK+/btCQ0N5aOPPqK6uvqG23E0zp8/r2R2k+d/9RXccw/cfz/U1DRdu3ZCvKuJeFcT8a4m4l1NxLuaqOpdnKuZb/TY9cTJ6A44Anv37iUyMpK9e/de8vzRo0c5evQoy5cv5/PPPychIQF3d/d629A0jSeeeIJ58+Zd8nxBQQFLlixhyZIlPPbYY3z44YfXvAYzNzeXyZMnX9GXnJwccnJy+Pjjj/n2228JDw+/5pg++eQTnnrqKSoqKmzPlZeXs379etavX8/nn39OcnIy7dq1u2Y7joi/v7+S2U2eHxgITk6wfDm88gq8/nrTtW0HxLuaiHc1Ee9qIt7VRLyriarexbma+UaPXU+UP4Pp5MmTjBs3zragExsbS3JyMlu3biU5OZnY2FjAembSrFmzrtrOSy+9ZFtcGjhwIHFxcWRkZBAXF8fAgQMBmDdvHi+//PJV2ygtLSUiIsLWl0cffZTVq1ezceNGXn/9dTw8PLBYLMTGxrJz586rtrNy5Uoee+wxKioq6NChA++99x6bN29mxYoVREdHA/DDDz8QHR1NbTO8XX3v3r2VzG7y/MGD4T//sT7+3/+FhQubrm07IN7VRLyriXhXE/GuJuJdTVT1Ls7VzDd67Hqi/ALTa6+9xuHDhwF49dVXWbBgAZMnT2bgwIFMnjyZBQsW8MorrwCwdOlSFi9efEUbBw4c4O9//zsAQ4YMYcOGDcycOZOhQ4cyc+ZM0tPTGTJkCABvvvkmubm59fbl7bffJicnB4C///3vzJs3j9GjRxMcHMyf//xnUlNTcXJyoqysjN/97nf1tlFdXc3TTz9NbW0tbdq0YcOGDTzzzDMEBQUxceJEFi1axK9//WsA0tLS+Prrr2/+wzOI77//Xslsu+Q/8AD8/vfWxw8/DNdYuDQa8a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xOlF5hqamr45ptvAOjSpctVzy565ZVX6Ny5MwBvvPHGFa+/8847tj2N3n//fVwvu0OXm5sb77//PmBdAHr33XevaKOqqop//vOfANx555384Q9/uOKY4OBgfvWrXwGwdu1asrKyrjhmyZIlHDhwAIA//elPBAQEXHHMW2+9Rdu2bW2PBcV5800YMwbKyiAqCoqLje6RIAiCIAiCIAiC0MxQeoFp//79nLlwB61x48bRokWLeo9r0aIF48aNAyAzM5NDhw7ZXtM0jaSkJMB66tvdd99dbxt33303vXr1Aqy7yGuadsnr69ats/XloYcewmyuX83DDz9se1zf2VQX71B/8bEX4+bmxvTp0wHYvXs3+/fvr/c4R2X48OFKZtst38kJ4uOhWzc4eBA+/rjpM5oA8a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xOlF5iKLzpTo0OHDtc89uLX09LSbI8PHjxIQUEBAPfcc88126h7/ciRI5csUgGsX7/+iuPqY8iQIbaNxtPT0694va6dXr160bFjx+v25WrtODLFBp5hY2S2XfPbtYPERHjrLXj+eftkNBLxribiXU3Eu5qIdzUR72qiqndxrma+0WPXE6UXmC6+I5zFYrnmsRe/np2dbXv8448/2h5fb/Oui1+/+H0NacfJycl22dvlbZSWlnLkyJFG98XRqdunSrVsu+f36wfPPQfXuMuhkYh3NRHvaiLe1US8q4l4VxNVvYtzNfONHrueKL3AdMcdd+Ds7AxcelZSfVz8en5+vu1x3QbhAH5+ftds4+LbE178vot/d3d357bbbruhdk6ePElFRYXt+SNHjtguvWtMXwSB0lLrBuCbNsFXX+E0cyYPfvYZTjNnwldfQXm50T0UBEEQBEEQBEEQHAgnoztgJO7u7owZM4aUlBR27txJXFwcs2bNuuK4uLg4du3aZfv97Nmz9T728PC4bl4dpaWll7xW18712qivHRcXlybty8VUVFRcsohVUlJS7/N6EhkZqWS2nvktXnwRp2++Qfv2W0yahtlsplttLdrhw5CYiPab31D9ySfUTp5s977UId71z6/LVHHsRmcbmS/exbtRiHfxrlK2kfniXc1so72r+n0zOlvvXKUXmABee+01Vq1aRXV1NQ899BC5ubk8+OCD3H777Rw7dowvv/ySv/zlL7Rs2ZLKykoAzp8/b3t/+UVncrRs2fKaWXULQZe3cXE712vjWu00VV8u5o033uC111674vm5c+fSqlWr6/ZVaJ70OXaMaYDpwhlxptraS/7kzBmcpk1j/syZ7LvO5ZhC8+edd94xuguCAYh3NRHvaiLe1US8q4l4V4tyna88UX6BKSgoiE8++YRHH32UyspKXn75ZV5++eVLjmnRogXvvvsuzzzzDACtW7e2vXbxIkvdAtTVuHj10NXV9ZLX6tq5XhvXaqep+nIxf/rTn/j9739v+72kpAR/f3+eeuop2rdvf92+2oOFCxcSGxurXLZu+eXltOza1boX02V3O6zDBGgmEzNTUqj88EPQYbFRvOufX1FRwTvvvMOzzz57yaK0noh38a5StpH54l28i3d18sW7mtlGe1f1+2Z09smTJ5kzZ45uecovMAE8+OCD9O/fn9dff52UlBTbpWZms5lRo0bx+uuvX3JJWdu2bW2PL15sutalZgDnzp2zPb78Era6dq7XxrXaaaq+XIyLi0u9Behqz+uBv7+/ktm65S9YAGfOXPcwk6bBmTO4LF1q3a/Jzoh34/Ll+24MRueLd2MwOl+8G4PR+eLdGIzOF+9qZddhlHejx66qd71zld7k+2L69+/PggULOH36NIcPH2b//v2cPXuWVatWMWzYMHbu3Gk7NjAw0Pb44s206+7gdjUu3kz74k22L27n3LlznLnOX+7r2mnfvv0l/8E0VV8cnf79+yuZrVt+YiKYb7A0mM2wZIldu1OHeFcT8a4m4l1NxLuaiHc1UdW7OFcz3+ix64ksMF1GixYt8PPz44477sDNzc32fHp6uu3xsGHDbI8vXmy63u0HL379zjvvvOS1G22nurqa3Nzcetvw8PCwLRY1pi+OzooVK5TM1i3/1Cmo22vpetTWQnGxfftzAfGuJuJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWC6ASorK0lISADA19eX4cOH217r1q0bnTp1AuC///3vNdtJS0uztdG1a9dLXgsJCbE9vlY7mZmZtsvbRowYccXrde3s3buX48ePX7WdizPqa0dQmHbtGnYGk5eXffsjCIIgCIIgCIIgODyywHQD/POf/+TkyZMAPPHEE7Ro0cL2mslkIjIyErCeFfTDDz/U28YPP/xgO2soMjISk8l0yethYWF4enoC8MUXX6BdZXPlzz//3PZ46tSpV7weFRVV77EXU1ZWxoIFCwDrmVM9e/as9zhHJSgoSMls3fKjohp2BlM9/x3aA/GuJuJdTcS7moh3NRHvaqKqd3GuZr7RY9cTWWAC8vPzr/ra0qVL+Z//+R8AevTowXPPPXfFMb/73e9wcrLul/7MM89w/vz5S14/f/687Q50Tk5O/O53v7uijZYtW/Kb3/wGgB9//JG33377imM2bdrEJ598AsA999zD0KFDrzhm6tSpBAQEAPDGG2/YLqe7mOeff57Tp0/bHjc3ysrKlMzWLT82Ftq2td5F7nq0agXTptm/T4h3VRHvaiLe1US8q4l4VxNVvYtzNfONHrueyAIT0LdvXyZMmMDHH3/Mpk2byMrKYtGiRcycOZN7772Xqqoq2rZtS3x8PK3quR17z549bQtPmZmZjBgxgvj4eDIzM4mPj2fEiBFkZmYC1gWdHj161NuP559/3nY20QsvvMDjjz/O2rVr+eGHH3jjjTcYP3481dXVuLq68u6779bbhrOzM++99x5ms5mSkhJGjBjBBx98QEZGBitXriQmJoZ//etfgPVyul/84heN/fh0Z/fu3Upm65bfqhV88YX18fUWmcrL4cUXb/yMp0Yg3tVEvKuJeFcT8a4m4l1NVPUuztXMN3rseuJkdAccgdraWlJTU0lNTa339cDAQL7++msGDhx41TZef/11CgsL+fTTT9m2bRszZ8684phf/epX/O1vf7tqG61bt2bZsmWEh4ezf/9+5s2bx7x58y45pk2bNnzzzTcMGDDgqu2Eh4fz4Ycf8vTTT3PixAnb2VMXExQUxJIlSy653E8QbEyZYr2b3MMPw+nTaGYzptpa25+0bWs902nePHjvPbBY4OOPwUlKiiAIgiAIgiAIgoqYtKtt9qMQ8+fPJzU1lYyMDI4dO0ZpaSnt27enX79+xMTE8Itf/AJnZ+cbamv58uXMmzePLVu2UFRUhLe3N0OHDuXxxx9n0qRJN9TGuXPnmDt3LgsXLuTAgQNUVlbi7+9PeHg4v/3tb+nSpcsNtbN7927ee+89Vq9ezdGjR3F3d+fOO+/k/vvv5//9v/9nu6yvIZSUlODp6UlhYSHt27dv8PubgoqKClxcXJTLNiS/vBwSEqhZtIj87dvpPGAALaZNg5gY65lOX39tXYSqqbHu3RQXZ33eDoh3/fMrKiqYM2cOL774opKfvXgX7yrli3fxruJnL97Fu2rZRnpX9ftmdPbJkyfx8fHBYrHQpk0bu+fJJXLAzJkz+fTTT9m9ezenTp2ioqKCI0eOsHz5ch555JEbXlwC69lDiYmJFBQUUFFRQUFBAYmJiTe8uATg7u7OCy+8wJYtWzh9+jTnzp0jJyeHf/zjHze8uATWS//mzZtHbm4u58+fp6ioiPXr1/PEE0/c1OKSo7B69Wolsw3Jb9UKHniA6vnz+fLhh6mePx8eeODnRaQHHoDFi8HFxXrG0wcf2K0r4l1NxLuaiHc1Ee9qIt7VRFXv4lzNfKPHrieywCQ0OywWi5LZjpBfL/feCykp8ItfQD0b2DcV4l1NxLuaiHc1Ee9qIt7VRFXv4lzNfKPHrifN9zQWQVl8fHyUzHaE/KsSFmb9qaOmBoqLoQkvoxTvaiLe1US8q4l4VxPxriaqehfnauYbPXY9kTOYhGZHUFCQktmOkH9DaBo8/jgMGwZ5eU3WrHhXE/GuJuJdTcS7moh3NVHVuzhXM9/oseuJLDAJzY7k5GQlsx0h/4Y4dQrWrYODByEkBJrotpziXU3Eu5qIdzUR72oi3tVEVe/iXM18o8euJ7LAJAhC0+LtDevXw113wbFjEBoKmzcb3StBEARBEARBEATBjsgCk9DsGDRokJLZjpB/w9x+u/UsprvvhtOnYcwYaOTdE8S7moh3NRHvaiLe1US8q4mq3sW5mvlGj11PZIFJaHbU1tYqme0I+Q3Cywu+/x7GjoVz5yA8HBITb7o58a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xO5i5xwQ8ydO5e5c+dSU1MDQGJiIh4eHkRHR7N69WosFgs+Pj4EBQXZrjEdNGgQtbW1bN++HYDIyEjS09M5deoUXl5ehIaGknhhwaFfv344OzuTlZUFwOTJk8nMzOTEiRO0adOG8ePHk5CQAEBJSQkuLi5svnDZ1YQJE9i9ezcFBQW4u7sTERFBfHw8AL169cLb25sNGzYAMHbsWPbt20d+fj4uLi5ER0cTHx9PbW0tAQEB+Pr6kpaWBkBYWBj5+fnk5eXh5OREbGwsK1asYPv27XTp0oWAgADWrFkDQEhICIWFhezbtw+AWbNmkZSURFlZGX5+fgQGBpKamgpAcHAwFouF7OxsAGJjY0lJSeHs2bN07NiRQYMGsXz5cgCGDh1KeXk5u3btAqCmpoaffvqJ06dP4+3tTXBwMEuXLgVg4MCBAGzbtg2AKVOmsGnTJoqKimjbti1hYWEsWbIEgLvuuotWrVqxZcsWAMLDw9m6dSvHjx+ndevWTJw4kYULFwIQGBiIq6srAAkJCUycOJHs7GyOHDmCm5sbkZGRxMXFAdCzZ098fHxIT08HYPTo0eT9z//gZ7Hgu3Ur5pYtWbhwIdXV1XTv3p3OnTuzbt06AEJDQykoKCA3Nxez2cyMGTNYvHgxFRUVdO7cmf3799v+WxoxYgRFRUXs3bsXgBkzZpCcnMy5c+fw9fWlb9++rFy5EoBhw4ZRWlrKnj17AIiJiSE1NZWSkhI6dOjAkCFDWLZsGQCDBw+mqqqKnTt3AhAVFUVaWhq7du3i8OHDhISEkJSUBMCAAQMwm81s3boVgIiICDIyMigsLMTT05MxY8awePFiAPr27YubmxsZGRkATJo0iR07dnD06FE8PDwIDw9nwYIFAPTu3RsvLy82btwIwLhx41izZg3bt2/H1dWVqKgo5s+fj6Zp9OjRg44dO7J+/XoARo0axaFDhzh48CDOzs7ExMSQkJBAVVUV3bp1o2vXrqxduxaAkSNHcvz4cfbv34/JZGLmzJkkJiZy/vx5/P396d27t+0zzM/Pp7S0lJycHACmT5/O8uXLKS0tpVOnTvTv358VK1YA1k0My8rK2H1h763G1ohly5axffv2BtWIPn364OHh0egacezYMe68884G1YhFixZRWVnZJDXi+++/Z/v27Q2qEVOnTmXdunWNqhF1k6C8vDybm+vVCE9PTzZt2gTA+PHjG1QjcnNz+emnn2jZsiXTpk1j4cKF/PTTT5SUlDSoRvTs2ZNVq1Y1ukbU1taSl5fXoBpRXFxMu3btmqRGFBQUcPvttzeoRuTk5HD48OFG1Qh/f3/AWufNZvMN1Yjvv/8egOHDh1NcXNzoGlFUVISfn5/d5xH11YjVq1ezfft2u88jrlYjzp8/T1lZmd3nEZfXiMGDB9u81z22xzziWjWirKzM5vhGa8TNzCPqqxF1/3+19zziajUiPT3dNnZ7ziMurxGLFi2yufbz87PbPOJaNWLlypVs377d7vOI+mpEQUEBvr6+dp9H1Fcj9uzZY+uvvecRl9cIi8UCgMViYfWFKwvsMY+A+mvEqlWr2L59uy7ziPpqRHl5OWfPnrX7POJqNWL79u26zCPg0hqhO5ogNACLxaIBWmFhoWF9+Pbbb5XMNjK/vLxcmz17tlZeXn5zDVRVadqmTY3qg3jXn0Z7bwLEu/6Id/FuFOJdf8S7eDcKVb0bmW20d1W/b0ZnFxYWaoBmsVh0yZNL5IRmR2RkpJLZjpB/0zg5WfdjquPAAXjrLdC0G25CvKuJeFcT8a4m4l1NxLuaqOpdnKuZb/TY9UQWmIRmR90pkaplO0J+k1BaCuPGwQsvwG9/Czd4TbJ4VxPxribiXU3Eu5qIdzVR1bs4VzPf6LHriSwwCc2OU6dOKZntCPlNgocH/OEP1sfvvw+//CVUV1/3beJdTcS7moh3NRHvaiLe1URV7+JczXyjx64nssAkNDu8vLyUzHaE/Cbj6afhq6+gRQv48kuIiYHy8mu+RbyriXhXE/GuJuJdTcS7mqjqXZyrmW/02PVEFpiEZkdoaKiS2Y6Q36Q88AAsXgwuLpCUBJMnw9mzVz1cvKuJeFcT8a4m4l1NxLuaqOpdnKuZb/TY9UQWmIRmR93tRlXLdoT8Jufee2HFCutlc2vWwHPPXfVQ8a4m4l1NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBIEwVhGjYK1a+Gee+B//9fo3giCIAiCIAiCIAg3gZPRHRCEhtKvXz8lsx0h324MGWJdZDKZfn7OYgFPT9uv4l1NxLuaiHc1Ee9qIt7VRFXv4lzNfKPHridyBpPQ7HB2dlYy2xHy7crFi0sffgh33gm7d9ueEu9qIt7VRLyriXhXE/GuJqp6F+dq5hs9dj2RBSah2ZGVlaVktiPk60JVFXz0ERw7BqGh8MMPgHhXFfGuJuJdTcS7moh3NVHVuzhXM9/oseuJLDAJguBYODtbN/wODobTp2HsWFi1yuheCYIgCIIgCIIgCNdAFpiEZsfkyZOVzHaEfN1o2xa+/x7GjYNz52DyZCJragzrjtGfu9H5RiLfdzUR72oi3tVEvKuJqt7FuZr5Ro9dT2SBSWh2ZGZmKpntCPm64u4OS5fCtGlQWYnrQw/B558b0hWjP3ej841Evu9qIt7VRLyriXhXE1W9i3M1840eu57IApPQ7Dhx4oSS2Y6QrzsuLjB/PjzyCKbaWjh61JBuGP25G51vJPJ9VxPxribiXU3Eu5qo6l2cq5lv9Nj1xMnoDghCQ2nTpo2S2Y6QbwhOTvDxx2zx82Pon/5kSBeM/tyNzjcS+b6riXhXE/GuJuJdTVT1Ls7VzDd67HoiZzAJzY7x48crme0I+YZhMjHgpZfAZLL+fvYs/OMfUFurS7zRn7vR+UYi33c1Ee9qIt7VRLyriarexbma+UaPXU9kgUlodiQkJCiZ7Qj5RmIbe20tREfDH/4ADz8MVVX6ZRuE0flGIt93NRHvaiLe1US8q4mq3sW5mvlGj11P5BI54YaYO3cuc+fOpebCnbwSExPx8PAgOjqa1atXY7FY8PHxISgoiOTkZAAGDRpEbW0t27dvByAyMpL09HROnTqFl5cXoaGhJCYmAtCvXz+cnZ3JysoCrDvtZ2ZmcuLECdq0acP48eNtX8ySkhLy8vLYvHkzABMmTGD37t0UFBTg7u5OREQE8fHxAPTq1Qtvb282bNgAwNixY9m3bx/5+fm4uLgQHR1NfHw8tbW1BAQE4OvrS1paGgBhYWHk5+eTl5eHk5MTsbGxHDt2jLi4OLp06UJAQABr1qwBICQkhMLCQvbt2wfArFmzSEpKoqysDD8/PwIDA0lNTQUgODgYi8VCdnY2ALGxsaSkpHD27Fk6duzIoEGDWL58OQBDhw6lvLycXbt2AVBTU0NKSgqnT5/G29ub4OBgli5dCsDAgQMB2LZtGwBTpkxh06ZNFBUV0bZtW8LCwliyZAkAd911F61atWLLli0AhIeHs3XrVo4fP07r1q2ZOHEiCxcuBCAwMBBXV1fAWhwnTpxIdnY2R44cwc3NjcjISOLi4gDo2bMnPj4+pKenAzB69Ghyc3P56aefaNmyJdOmTWPhwoVUV1fTvXt3OnfuzLp16wAIDQ2loKCA3NxczGYzM2bMYPHixVRUVNC5c2cqKipsOeMiImi3di2mr77iSHY2ndLSSF61inPnzuHr60vfvn1ZuXIlAMOGDaO0tJQ9e/YAEBMTQ2pqKiUlJXTo0IEhQ4awbNkyAAYPHkxVVRU7d+4EICoqirS0NAoKCkhNTSUkJISkpCQABgwYgNlsZuvWrQBERESQkZFBYWEhnp6ejBkzhsWLFwPQt29f3NzcyMjIAGDSpEns2LGDo0eP4uHhQXh4OAsWLACgd+/eeHl5sXHjRutYx42juLiYuLg4XF1diYqKYv78+WiaRo8ePejYsSPr168HYNSoURw6dIiDBw/i7OxMTEwMCQkJVFVV0a1bN7p27cratWsBGDlyJMePH2f//v2YTCZmzpxJYmIi58+fx9/fn969e9s+w/z8fEpLS8nJyQFg+vTpLF++nNLSUjp16kT//v1ZsWIFAEFBQZSVlbF7926ARteIgoIC4uLiGlQj+vTpg4eHR6NrxLFjxwAaVCMWLVpEZWVlk9SIurE3pEZMnTqVdevWNapG1F44MzAvL8/m5no1wtPTk02bNgHWf6VrbI0oKChg8+bNDaoRPXv2ZNWqVQCMGDGCoqIi9u7dC8CMGTNITk6+oRpRW1vLsmXLGlQjiouLadeuXZPUiIKCAs6cOdOgGpGTk8Phw4cbVSP8/f0Ba503m803VCO+//57AIYPH05xcXGja0RRURFnz561+zyivhpx6tQp4uLi7D6PuFqNOH/+PFlZWXafR1xeIwYPHmzzXvfYHvOIa9UIQJd5RH01oq7ONqRG3Mw84mo1orS01DZ2e84jLq8RixYtsrn28/Oz2zziWjXixIkTxMXF2X0eUV+NKCgooKSkxO7ziPpqRHl5uc25vecRl9cIi8UCgMViYfXq1YB95hFQf40oKioiLi5Ol3lEfTWivLycjIwMu88j6qsRdbVGj3kEXFojdEcThAZgsVg0QCssLDSsDzt27FAy28j88vJybfbs2Vp5ebkh+ZpWz9i/+07TXFw0DTRt1ChNKynRL1tnxLt62Ubmi3fxbhTiXX/Eu3g3ClW9G5lttHdVv29GZxcWFmqAZrFYdMmTS+SEZoeHh4eS2Y6QbyRXjH3KFEhJgdatYe1aGDMGTp3SJ1tnjM43Evm+q4l4VxPxribiXU1U9S7O1cw3eux6IgtMQrOj7nRV1bIdId9I6h17WBisWQPt2sGWLTBjhn7ZOmJ0vpHI911NxLuaiHc1Ee9qoqp3ca5mvtFj1xNZYBIEoXkzZAikpUHfvtY7ywmCIAiCIAiCIAi6I5t8C82OCRMmKJntCPlGcs2xBwbCjh1gvmjNvLwcWrWyf7YOGJ1vJPJ9VxPxribiXU3Eu5qo6l2cq5lv9Nj1RM5gEpoddXeVUC3bEfKN5Lpjv3hxaf16uOMO+OEHfbLtjNH5RiLfdzUR72oi3tVEvKuJqt7FuZr5Ro9dT2SBSWh2FBQUKJntCPlG0qCx/+//QkEBjB0LF243qlu2HTA630jk+64m4l1NxLuaiHc1UdW7OFcz3+ix64ksMAnNDnd3dyWzHSHfSBo09oQEGDcOzp2DyZNh8WL9su2A0flGIt93NRHvaiLe1US8q4mq3sW5mvlGj11PZIFJaHZEREQome0I+UbSoLG7u8PSpTBtGlRWQmwsfP65Ptl2wOh8I5Hvu5qIdzUR72oi3tVEVe/iXM18o8euJ7LAJDQ74uPjlcx2hHwjafDYXVxg/nx45BGorYVf/hLefVef7CbG6Hwjke+7moh3NRHvaiLe1URV7+JczXyjx64nssAkCMKti5MTfPwx/OEP1t/T062LTYIgCIIgCIIgCEKT4mR0BwShofTq1UvJbEfIN5KbHrvJBG+9BYMGWS+ZMzd8Xd3oz93ofCOR77uaiHc1Ee9qIt7VRFXv4lzNfKPHridyBpPQ7PD29lYy2xHyjaRRYzeZ4L77rJfNgfUspo8/hqoq+2c3AUbnG4l839VEvKuJeFcT8a4mqnoX52rmGz12PZEFJqHZsWHDBiWzHSHfSJp07C+8AI8+CjExUF6ub/ZNYHS+kcj3XU3Eu5qIdzUR72qiqndxrma+0WPXE1lgEgRBPcLCoFUr+O47mDQJzp41ukeCIAiCIAiCIAjNGllgEpodY8eOVTLbEfKNpEnHHhEBKSnQujWsWwejR0NRkT7ZN4HR+UYi33c1Ee9qIt7VRLyriarexbma+UaPXU9kgUloduzbt0/JbEfIN5ImH/s998CaNdCuHWRmQmgoFBTok91AjM43Evm+q4l4VxPxribiXU1U9S7O1cw3eux6IgtMQrMjPz9fyWxHyDcSu4x9yBBYvx58feHHH61nMlVW6pPdAIzONxL5vquJeFcT8a4m4l1NVPUuztXMN3rseuLU1A0eOHCAL7/8kk2bNnH8+HHOnz9PSkoKd9xxh+2Y3bt3k5+fj7u7O/fcc09Td0GwA3PnzmXu3LnU1NQAkJiYiIeHB9HR0axevRqLxYKPjw9BQUEkJycDMGjQIGpra9m+fTsAkZGRpKenc+rUKby8vAgNDSUxMRGAfv364ezsTFZWFgCTJ08mMzOTEydO0KZNG8aPH09CQgIAZWVl5OXlsXnzZgAmTJjA7t27KSgowN3dnYiICOLj4wHrLSG9vb1tG6uNHTuWffv2kZ+fj4uLC9HR0cTHx1NbW0tAQAC+vr6kpaUBEBYWRn5+Pnl5eTg5OREbG8uJEyeIi4ujS5cuBAQEsGbNGgBCQkIoLCy0rU7PmjWLpKQkysrK8PPzIzAwkNTUVACCg4OxWCxkZ2cDEBsbS0pKCmfPnqVjx44MGjSI5cuXAzB06FDKy8vZtWsXAE5OTqSkpHD69Gm8vb0JDg5m6dKlAAwcOBCAbdu2ATBlyhQ2bdpEUVERbdu2JSwsjCVLlgBw11130apVK7Zs2QJAeHg4W7du5fjx47Ru3ZqJEyeycOFCAAIDA3F1dQUgISGBiRMnkp2dzZEjR3BzcyMyMpK4uDgAevbsiY+PD+np6QCMHj2a3NxcfvrpJ1q2bMm0adNYuHAh1dXVdO/enc6dO7Nu3ToAQkNDKSgoIDc3F7PZzIwZM1i8eDEVFRV07twZTdNsOSNGjKCoqIi9e/cCMGPGDJKTkzl37hy+vr707duXlStXAjBs2DBKS0vZs2cPADExMaSmplJSUkKHDh0YMmQIa194gbA33+Tcr3/N6f372blzJ+bKSqZWV3P6s88IOX6cE3PnctvDD5Po7Exty5YMGDAAs9nM1q1bAYiIiCAjI4PCwkI8PT0ZM2YMixcvBqBv3764ubmRkZEBwKRJk9ixYwdHjx7Fw8OD8PBwFixYAEDv3r3x8vJi48aNAIwbN46SkhLi4uJwdXUlKiqK+fPno2kaPXr0oGPHjqxfvx6AUaNGcejQIQ4ePIizszMxMTEkJCRQVVVFt27d6Nq1K2vXrgVg5MiRHD9+nP3792MymZg5cyaJiYmcP38ef39/evfubfsM8/PzKS0tJScnB4Dp06ezfPlySktL6dSpE/3792fFihUABAUFUVZWxu7duwEaXSOOHTtGXFxcg2pEnz598PDwaHSNKCwsBGhQjVi0aBGVlZVNUiPqxt6QGjF16lTWrVvXqBpRW1sLQF5ens3N9WqEp6cnmzZtAmD8+PGNrhHHjh1j8+bNDaoRPXv2ZNWqVY2uEc7OzixbtuySGrFs2TIABg8eTFVVFTt37gQgKiqKtLQ0iouLadeuHSEhISQlJQHcdI04duwYZ86caVCNyMnJ4fDhw42qEf7+/oC1zpvN5huqEd9//z0Aw4cPp7i4uNE14vTp05w9e9bu84j6aoTFYiEuLs7u84ir1Yjq6mqysrLsPo+4vEYMHjzY5r3usT3mEdeqES4uLrrMI+qrEXV1trHziJutERUVFbax23MecXmNWLRokc21n5+f3eYR16oRRUVFxMXF2X0eUV+NOHbsGCUlJXafR9RXI2pqamzO7T2PuLxGWCwWACwWC6tXrwbsM4+A+mvEmTNniIuL02UeUV+NqKmpISMjw+7ziPpqRF2t0WMeAZfWCL0xaZqmNUVDtbW1/PGPf+Tdd9+ltraWumZNJhO7du0iMDDQduyKFSuYPHkyTk5OHDx4EF9f36bogqADJSUleHp6UlhYSPv27Y3ujqATFRUVzJkzhxdffBEXFxeju2MfKiuhZUvr4+++g4cegjNnwGyG2tqf/2zbFr74AqZMMbS7eqCEd+EKxLuaiHc1Ee9qIt7VRLyrycmTJ/Hx8cFisdCmTRu75zXZJXKPP/44//jHP6ipqaFTp07ExMRc9dhJkybRvXt3ampqbCvFgnCj1P2LgWrZjpBvJHYf+8WLS1FR1sUlsC4qXfznmTMQGWk9TifEu3rZjpBvJOJdTcS7moh3NVHVuzhXM9/osetJkywwrVu3jk8++QSAP//5zxw6dMh2mubViI2NRdM022mWgnCj1F2+oVq2I+QbiS5jLy+Hhx+Ga53YWffaww9bj9cB8a5etiPkG4l4VxPxribiXU1U9S7O1cw3eux60iQLTB9++CFgvbbyb3/7Gy1atLjue4KCggBs1yoKwo0SEBCgZLYj5BuJLmNfuBBOn77+cZpmPU6nMzDFu3rZjpBvJOJdTcS7moh3NVHVuzhXM9/osetJkywwbdq0CZPJxK9+9asbfo+fnx8Ax48fb4ouCAph5J5dRu8XZnS+kegy9sRE615LN4LZDBc2MrQ34l29bEfINxLxribiXU3Eu5qo6l2cq5lv9Nj1pEkWmOrutNOtW7cbfo+Tk/UGdlVVVU3RBUEh6u7Oolq2I+QbiS5jP3Xq572WrkdtLRQX27c/FxDv6mU7Qr6RiHc1Ee9qIt7VRFXv4lzNfKPHridNssBUdwvzsrKyG35Pfn4+AG3btm2KLgiCIDSedu0adgaTl5d9+yMIgiAIgiAIgtBMaJIFprozl7Zt23bD70lOTgYgMDCwKbogKERYWJiS2Y6QbyS6jD0qqmFnMIWH27U7dYh39bIdId9IxLuaiHc1Ee9qoqp3ca5mvtFj15MmWWAaP348mqYxb968G9ohPSsri6+++gqTycTEiROboguCQtSd/aZatiPkG4kuY4+NhbZtwWS69nEmE7RqBW++CTt22L1b4l29bEfINxLxribiXU3Eu5qo6l2cq5lv9Nj1pEkWmJ5++mlcXV3ZtWsXjz766DX3VVq0aBETJ06ksrKSNm3a8NhjjzVFFwSFyMvLUzLbEfKNRJext2oFX3xhfXy1Raa65z08YP9+GDYM5s613lnOToh39bIdId9IxLuaiHc1Ee9qoqp3ca5mvtFj15MmWWDy9fXlvffeQ9M0Pv/8c7p3786vf/1r2+uffPIJTz75JD169GD69OmcOnUKk8nEvHnz8PT0bIouCApRt0G8atmOkG8kuo19yhTr3eRuu836e92eTHV/3nYbJCXBjz9CRARUVMDTT0N0tN02/Rbv6mU7Qr6RiHc1Ee9qIt7VRFXv4lzNfKPHricmTWu6f3b/9NNP+c1vfkNZWRmmev71vy7KxcWFDz/8kIceeqipogWdKCkpwdPTk8LCQtq3b290dwSdqKioYM6cObz44ou4uLgY3R19KC+HhARYssS6cOTlBVOnQkyM9UwnsJ619P778PzzUFkJ/v7w7bcQEmJs35sIJb0L4l1RxLuaiHc1Ee9qIt7V5OTJk/j4+GCxWGjTpo3d85rkDKY6HnnkEXJycvj9739PQEAAmqZd8uPr68uTTz7Jjz/+KItLwk2zaNEiJbMdId9IdB97q1bwwAOwaBGLnn4aFi2y/l63uATWy+V+8xvYtAl69IDDh60bf58+3aRdEe/qZTtCvpGIdzUR72oi3tVEVe/iXM18o8euJ01+rpafnx9vv/02b7/9NiUlJRQWFlJTU0O7du3w9vZu6jhBQSorK5XMdoR8I3Fo74MGQVYWPPUUjBxp3Shcz/xbGIf2fovnG4l4VxPxribiXU1U9S7O1cw3eux60uAFpkGDBhEaGmr7udaiUZs2bXQ5DUtQiy5duiiZ7Qj5RuLw3lu3hi+/vHSz702brJfXTZ5s//xbFIf3fgvnG4l4VxPxribiXU1U9S7O1cw3eux60uAFpu3bt7Njxw7ef/99AHr16nXJgpOfn1+Td1IQLiYgIEDJbEfIN5Jm471u/7nTp2HmTMjPh2efhTfegJu83l28q5ftCPlGIt7VRLyriXhXE1W9i3M1840eu540eA8md3f3S/ZV2rt3L//5z3/4xS9+QZcuXejevTsPP/wwn332Gbm5ufbos6A4a9asUTLbEfKNpNl5d3OzbgoO8M47MHw47N+vX/4tQrPzfgvlG4l4VxPxribiXU1U9S7O1cw3eux60uAzmCwWC9u2bWP9+vWkpaWRnp5OUVGR7fVDhw7x008/8dVXXwHQsWPHS85w6tOnT9P1XhAEwVFxcYF334UxY+CXv4StW617Nf3739bNwgVBEARBEARBEG4hTJp28YYhN0dOTg5paWmsX7+e9evXk5+ff2lI3SUjgJeXFyEhIbYFp0GDBl3yuuCYzJ07l7lz51JTU8O+ffuYN28eHh4eREdHs3r1aiwWCz4+PgQFBZGcnAxY9+uqra1l+/btAERGRpKens6pU6fw8vIiNDSUxMREAPr164ezszNZWVkATJ48mczMTE6cOEGbNm0YP348CQkJgHXRskuXLmzevBmACRMmsHv3bgoKCnB3dyciIoL4+HjAegmnt7c3GzZsAGDs2LHs27eP/Px8XFxciI6OJj4+ntraWgICAvD19SUtLQ2AsLAw8vPzycvLw8nJidjYWL766iucnJzo0qULAQEBttXokJAQCgsL2bdvHwCzZs0iKSmJsrIy/Pz8CAwMJDU1FYDg4GAsFgvZ2dkAxMbGkpKSwtmzZ+nYsSODBg1i+fLlAAwdOpTy8nJ27doFQFBQEPv37+f06dN4e3sTHBzM0qVLARg4cCAA27ZtA2DKlCls2rSJoqIi2rZtS1hYGEuWLAHgrrvuolWrVmzZsgWA8PBwtm7dyvHjx2ndujUTJ05k4cKFAAQGBuLq6kpcXBx33HEHEydOJDs7myNHjuDm5kZkZCRxcXEA9OzZEx8fH9LT0wEYPXo0ubm5/PTTT7Rs2ZJp06axcOFCqqur6d69O507d2bdunUAhIaGUlBQQG5uLmazmRkzZrB48WIqKiro3LkzrVu3Zs+ePQCMGDGCoqIi9u7dC8CMGTNITk7m3Llz+Pr60rdvX1auXAnAsGHDKC0ttb03JiaG1NRUSkpK6NChA0OGDGHZsmUADB48mKqqKnbu3AlAVFQUaWlpFBQU4OfnR0hICElJSQAMGDAAs9nM1q1bAYiIiCAjI4PCwkI8PT0ZM2YMixcvth7r7U3X//kfXC983pUzZ/LDI49QUFSEh4cH4eHhLFiwAIDevXvj5eXFxo0bARg3bhybN2+mpKQEV1dXoqKimD9/Ppqm0aNHDzp27Mj69esBGDVqFIcOHeLgwYM4OzsTExNDQkICVVVVdOvWja5du7J27VoARo4cyfHjx9m/fz8mk4mZM2eSmJjI+fPn8ff3p3fv3qxcuZIDBw5w3333UVpaSk5ODgDTp09n+fLllJaW0qlTJ/r378+KFSts/42WlZWxe/dugEbXiLi4OFxdXRtUI/r06YOHh0eja0RNTQ0PPPBAg2rEokWLqKysbJIakZWVhaura4NqxNSpU1m3bl2jakRtbS0HDhxg+vTpNjfXqxGenp5s2rQJgPHjxze6Rpw9e5Y+ffo0qEb07NmTVatWNbpG3H333WRnZzeoRhQXF9OuXbubrhF9+/bFzc2NjIwMzp8/T3R0NDt27ODo0aM3VCNycnI4fPhwo2qEv78/q1ev5o477sBsNt9Qjfj+++8BGD58OMXFxY2uEa1atWLs2LF2n0fUVyM2bNhAaWmp3ecRV6sRPXr0wGQy2X0ecXmNGDx4MO+//z533HEHgwcPvqEaAQ2fR1yrRgwaNMhWE+w5j6ivRmzfvh1XV1e7zyOuViOKi4ttf2+60RoBMGnSpEbViG+//Zb9+/czYcIE/Pz87DaPuFaNWLhwIZqm2X0eUV+NOH/+PDExMXafR9RXI5ycnGz/b7L3POLyGmGxWDhw4ABPPvkkq1evvqEa0ZR/11i3bh1lZWW6zCPqqxG9evWiurra7vOI+mpEQkICrq6uuswjLq8RAPfddx8Wi0Wf/bE1O5Cfn699/fXX2uOPP64FBgZqZrNZM5lMth+z2Wz78fT0tEcXBDthsVg0QCssLDSsD5mZmUpmG5lfXl6uzZ49WysvLzckX9NuAe/V1Zo2e7ammc2aNnWqptXW6pt/E4h3+b4bhXjXH/Eu3o1CvOuPeFcz22jvqn7fjM4uLCzUAM1iseiS1+A9mG4Ef39/7r//fj788EP27NlDYWEhixcv5tlnn2Xw4MGYzWbbHk5nz561RxeEW5i6lXvVsh0h30iavfcWLeDVV2HdOvj44583Ay8vv/TOc/bKb6Y0e+/NON9IxLuaiHc1Ee9qoqp3ca5mvtFj15MG78F0M7Rr147Bgwdz7tw5SktLOXnyJIcPH0Zr/NV5giAIzYuRI39+rGnW/ZnKyuDTT6FdO+P6JQiCIAiCIAiC0AiaZA+m+ti7d69tX6a0tDQOHz5se60u0tPTk+HDh9uuWxYcn5KSEjw9PSksLKR9+/ZGd0fQiYqKCubMmcOLL76Ii4uL0d25dfjxRxgwACorwc8PvvkGQkON7pUN8a4m4l1NxLuaiHc1Ee9qIt7V5OTJk/j4+Oi2B1OTXCKnaRrbtm3jn//8JzExMXTo0IHAwECeeOIJvv76a/Lz89E0DT8/P2bMmMEHH3zA9u3bKS4ulsUlocHUbXymWrYj5BvJLen9zjth82bo2ROOHIFRo+C116CmRp/8ZsAt6b2Z5BuJeFcT8a4m4l1NVPUuztXMN3rsenJTl8hVVVWRkZFhO0Np48aNtr2U6s5OMplM9OnTh5CQENtP586dm67ngrKUlZUpme0I+UZyy3ofMACysuCZZ+Dzz2H2bFi7Fr7+2npWk73zHZxb1nszyDcS8a4m4l1NxLuaqOpdnKuZb/TY9aTBC0xhYWFkZGRQUVEB/Lyg5OLiwpAhQ2yLSSNGjOC2225r0s4KAoDfhb90q5btCPlGckt79/CAzz6DsWPhiSfgv/+F8HDYvh3MZvGuYLYj5BuJeFcT8a4m4l1NVPUuztXMN3rsetLgBaa0tDTrG52cGD9+PCNHjiQkJIShQ4fSsmXLJu+gIFxOYGCgktmOkG8kSni//34ICrL++eabYDbrm++AKOHdQfONRLyriXhXE/GuJqp6F+dq5hs9dj25qT2YTCYTNTU1bNy4kfXr17N+/XoyMzOprKxs6v7pRmVlJZ988gkTJ07k9ttvx8XFBQ8PD3r16sUjjzzCDz/8cEPtpKSkEB0djZ+fHy4uLvj5+REdHU1KSsoN96WsrIy33nqLoKAgvLy88PDw4M477+S5554jPz//htvZs2cPTzzxBHfccQeurq60b9+e0NBQPvroI6qrq2+4HUcjNTVVyWxHyDcSZbz36AE//GDdj+kCu998ExS6venFKOPdAfONRLyriXhXE/GuJqp6F+dq5hs9dj1p8BlMv/3tb0lPT2f79u2cOXOG5cuXs2LFCgBatmzJ0KFDbWc1jRgxQpedyhvL4cOHmTx5Mrt27brk+crKSvbt28e+ffv47LPPePbZZ/m///s/TCbTFW1omsYTTzzBvHnzLnm+oKCAJUuWsGTJEh577DE+/PDDet9fR25uLpMnT2bv3r2XPJ+Tk0NOTg4ff/wx3377LeHh4dcc0yeffMJTTz1lu5QRoLy83LYg+Pnnn5OcnEw7uS26IDge5ovW/vfvZ/j778O//gX//jf84hfG9UsQBEEQBEEQBOEqNPgMpnfeeYctW7Zw5swZVq5cyUsvvURoaCitWrWioqKC9PR05syZQ0REBF5eXgwYMIBnnnmG+Ph4jh49ao8xNIrq6upLFpf69evH559/zqZNm0hNTeWVV17B3d0dsI797bffrredl156yba4NHDgQOLi4sjIyCAuLo6BAwcCMG/ePF5++eWr9qW0tJSIiAjb4tKjjz7K6tWr2bhxI6+//joeHh5YLBZiY2PZuXPnVdtZuXIljz32GBUVFXTo0IH33nuPzZs3s2LFCqKjowH44YcfiI6Opra2toGfmPEEBwcrme0I+UairHd3d6oHDIBz5+DBB60/F26qoALKeneAfCMR72oi3tVEvKuJqt7FuZr5Ro9dT27qLnIA7u7ujBs3jnHjxgHWO8tlZmbazpDZsGEDZ86cYefOnezatYt//etfAHTp0sV2htPIkSPp3bt304zkJklKSrItLgUHB7N+/XpatGhhe33cuHHce++9BAcHU1VVxRtvvMGzzz6Lk9PPH92BAwf4+9//DsCQIUNIS0vD1dUVgKFDh3Lvvfdyzz33kJmZyZtvvskvf/lLAgICrujL22+/TU5ODgB///vfef75522vBQcHM2rUKEJDQykrK+N3v/sda9asuaKN6upqnn76aWpra2nTpg0bNmy4JGvixIk89dRT/Otf/yItLY2vv/6aBx98sDEfoe5YLBYlsx0h30iU9d6pE/vmzqX/8uXw6qvw1VfWS+jmz4dBg4zrl04o690B8o1EvKuJeFcT8a4mqnoX52rmGz12PbmpPZjqw9nZmeDgYF544QWWLl3KqVOn2LFjBx988AHTp0/n9ttvR9M0Dh06xNdff80TTzxBnz598PHxaaou3BQbNmywPf7Tn/50yeJSHYMHDyYiIgKA06dP2xaB6njnnXdsexq9//77tsWlOtzc3Hj//fcB6wLQu+++e0VGVVUV//znPwG48847+cMf/nDFMcHBwfzqV78CYO3atWRlZV1xzJIlSzhw4IBtPPUtZL311lu0bdvW9ri5kZ2drWS2I+QbidLe9+6Fl16y3l3O3x/274fgYHjvPUP7pQdKe5fvu3LZjpBvJOJdTcS7mqjqXZyrmW/02PWkyRaYLsdkMnHXXXfx61//mri4OI4cOcKBAwf44IMP6NatG5qmoWkap06dslcXboiLNybv3r37VY+7eKHm4n2NNE0jKSkJgN69e3P33XfX+/67776bXr16AZCYmIimaZe8vm7dOs6cOQPAQw89hNlcv5qHH37Y9njx4sVXvJ6YmFjvsRfj5ubG9OnTAdi9ezf79++v9zhBEByMkBDYvh2ioqCyEgoKjO6RIAiCIAiCIAgCYMcFpjrOnDlDcnIyf/zjH7n//vt59tlnOXjw4DU3utaTnj172h7n5eVd9bjc3FzAunDWo0cP2/MHDx6k4MJf8u65555rZtW9fuTIEQ4dOnTJa+vXr7/iuPoYMmSIbU+o9PT0K16va6dXr1507Njxun25WjuOTGxsrJLZjpBvJOL9Al5esHgxfPst/O1vPz/fjO8MeS3Eu5qIdzUR72oi3tVEVe/iXM18o8euJ02+wHT8+HEWLFjAM888Q//+/fH29iYyMpK3336bjIwMqqqqbGcvubq6XndRxt7MmjXLdqe7N998k5qamiuO2bZtG8uWLQNg5syZl9wZ78cff7Q9vt5+Uhe/fvH7GtKOk5OT7Wyqy9soLS3lyJEjje6Lo5OSkqJktiPkG4l4vwiTCWbNAmdn6+9VVXDPPdY9mm6xhSbxribiXU3Eu5qIdzVR1bs4VzPf6LHryU1v8l1HXl4eaWlprF+/nrS0tCvOArr4UrA2bdowfPhwQkNDCQ0NZejQoTjX/QXJINq3b8/nn3/O/fffz4YNGxg6dCi/+93v6NmzJ6WlpWzYsIH/+7//o7KykgEDBvCPf/zjkvcfPnzY9tjPz++aWf7+/vW+7+Lf3d3due22267bzs6dOzl58iQVFRW4uLgA1jOj6j7vxvTF0Tlr4B20jMx2hHwjEe/XIDERNm60/qxdC998Y92r6RZAvKuJeFcT8a4m4l1NVPUuztXMN3rsetLgBabdu3fbFpTWr1/PsWPHbK9dvq+Qt7c3ISEhtgWlAQMGXHVvISOZOnUqmZmZ/OMf/+DTTz/loYceuuT1Dh068Nprr/HYY4/ZLk+r4+L/WDw8PK6Zc/F7S0tL623nem3U107dAlNT9eViKioqLtlzqqSkpN7n9cTb21vJbCPz6zJVHLvR2TeUf++9mD//HKdnnsG0fj3agAFUz5tH7YWbE9ws4t3BvdsJ8S7ejUK8i3eVso3MF+9qZhvtXdXvm9HZeueatMtXha6D2Wy27Z90+Vv9/PwYOXKkbUHpzjvvbLqe2pGqqipee+01/vOf/1BYWFjvMUOHDuXVV19l8uTJlzz/17/+lVdeeQWA1atXM3r06KvmrFmzhjFjxtje99JLL9leCwgIIC8vD39/f/Lz86/Z3wcffJCvvvoKsJ59VHe20vr16wkNDQXg5Zdf5i9/+ctV26itrbXdMW/MmDGsWrWq3uNmz57Na6+9dsXzL774Iq1atbpmPwVB0Je2p04Rk5BApwsL/5uDgvh+3DhqDD5TVBAEQRAEQRAE/SkvL2fOnDlYLJZLtvqxFzd1iVzdwlJAQIBtMSk0NJRu3bo1aef04Ny5c4SHh5OWlkaLFi144YUX+OUvf0n37t0pLy9n8+bN/OUvfyE9PZ0pU6bwzjvv8Nvf/tb2/osXWS6+I119XLx66Orqeslrde1cr41rtdNUfbmYP/3pT/z+97+3/V5SUoK/vz9PPfUU7du3v25f7cHChQsN2yjNyGwj8ysqKnjnnXd49tlnbWfM6Y14v8H811+n+pVXcHr3XYZlZDCkRw+qP/nkpnLFezPy3oSId/Eu3tXJF+/iXbyrk220d1W/b0Znnzx5kjlz5uiW1+AFpieffJLQ0FDuueeea96lrLnw6quvkpaWBsAnn3xyyeVxLVu2ZNy4cYwaNYrx48ezdu1afv/73zNq1Cj69esHQOvWrW3HX+tSM7AuZtVx+SVsde1cr41rtdNUfbkYFxeXegvQ1Z7XgxYtWiiZ7Qj54t0YGpTv4gLvvAPjx8PTT9Pi1Vdp0ci+i3djMDpfvBuD0fni3RiMzhfvxmB0vnhXK7sOo7wbPXZVveud2+ANkebOncuMGTOabHHJyA2vNE3js88+A6Bnz55X7L1Uh5OTE3/9618B66Vlde+BSzfTrruD29W4eDNt/8s24K1r59y5c5w5c+aG2mnfvv0l/8E0VV8cnaFDhyqZ7Qj5RiLeG8ikSbB3L/To8fNzixdDM9tkULyriXhXE/GuJuJdTVT1Ls7VzDd67HrSJDtuv/HGGzf1PovFwrhx45qiCzfFiRMnKC4uBmDgwIHXPHbw4MG2xzk5ObbHgYGB9T5fHxe/fvn+VDfaTnV1Nbm5ufW24eHhYVssakxfHJ3y8nIlsx0h30jE+03gdNFJqmvXQkwMDBoEWVlN0zEdEO9qIt7VRLyriXhXE1W9i3M1840eu540yQLT//zP/zBv3rwGvcdisTB27Fi2bNnSFF24KZwu+stXdXX1NY+tqqqq933dunWjU6dOAPz3v/+9Zht1l+L5+vrStWvXS14LCQmxPb5WO5mZmbbL20aMGHHF63Xt7N27l+PHj1+1nYsz6mvnejj98pfw1VdgwJdl165dumc6QrYj5BuJeG8krVqBvz8cOADBwdbL6Bp2jwdDEO9qIt7VRLyriXhXE1W9i3M1840eu540yQITwFNPPcXChQtv6Nji4mLGjBlDVlaW7Y50RuDl5WXbSX3Tpk3XXGS6eEHm4s3MTSYTkZGRgPWsoB9++KHe9//www+2s4YiIyOvGHdYWBienp4AfPHFF1fcoa+Ozz//3PZ46tSpV7weFRVV77EXU1ZWxoIFCwDrmVM9e/as97hrYV6+HB58EDp1gqVLG/x+QRB0JjgYtm+HqVOhqgp+/3uIiICTJ43umSAIgiAIgiAItwJaEzB16lTNZDJpLi4u2sqVK695bFFRkTZgwADNZDJpLVq00ObNm9cUXbhpZs2apQEaoM2ePbveY4qLi7XAwEDbcZePce/evZqTk5MGaEOGDNHKysoueb2srEwbMmSIBmhOTk7avn376s15+eWXbRl///vfr3h948aNtpx77rmn3jYqKyu1gIAADdDatGmjHThw4Ipjfv3rX9tyPvvss3rbuRoWi0UDNIv13AdNM5msP0lJDWqnMZw/f163LEfKNjK/vLxcmz17tlZeXm5IvqaJ9yajtlbT/vUvTXNxsX6Hb79dA7gj6gABAABJREFU09asqfdQ8X4LeW8A4l28G4V41x/xLt6NQlXvRmYb7V3V75vR2YWFhda/v1ssuuQ1yRlM8+fPZ9SoUVRWVjJt2rSrnsVz8uRJRo8ezY4dOzCbzXz00Uc8+uijTdGFm+aVV17Bzc0NgNmzZ3PvvfeyaNEitm3bxqZNm3jnnXcYMGAA2dnZAIwZM4bx48df0kbPnj157rnnAOslbCNGjCA+Pp7MzEzi4+MZMWIEmZmZADz//PP0uHjT3Yt4/vnnbWcTvfDCCzz++OOsXbuWH374gTfeeIPx48dTXV2Nq6sr7777br1tODs7895772E2mykpKWHEiBF88MEHZGRksHLlSmJiYvjXv/4FWC+n+8UvftG4D7DuTKuHH9btcrl169bpkuNo2Y6QbyTivYkwmeDJJyEjA+68E44dg7y8S48pL4evvsJp5kwe/OwznGbONOySWPGuJuJdTcS7moh3NVHVuzhXM9/oseuJ0/UPuT4tW7bku+++Y9SoUWRmZjJ58mT++9//0rdvX9sxJ06cYOzYsezZs4cWLVowb948fvnLXzZFfKPo3bs3SUlJzJo1i6KiIpYuXcrSq1zyNXr06KteBvj6669TWFjIp59+yrZt25g5c+YVx/zqV7/ib3/721X70rp1a5YtW0Z4eDj79+9n3rx5V+xt1aZNG7755hsGDBhw1XbCw8P58MMPefrppzlx4gTPPPPMFccEBQWxZMkSWrRocdV2bhhNg9OnISEBHnig8e1dh9OnT9s9wxGzHSHfSMR7E9OvH2zZAt9+C4888vPziYnW30+fxmw20622Fu3wYevzv/0tfPEFTJnS9P25CuJdTcS7moh3NRHvaqKqd3GuZr7RY9eTJtuDyd3dnZSUFHr37s3p06eZMGECBw8eBOD48eOMGjXKtrj0ySefOMTiUh1jx44lJyeHN998k7CwMNq3b4+zszOurq5069aN6dOnk5iYyKpVq2jbtm29bZjNZj755BOWLVtGZGQknTp1omXLlnTq1InIyEiWL1/Oxx9/jNl87Y/8jjvuYNu2bbz55psMGTKE2267DTc3N3r16sWzzz7Lzp07iYiIuO6YHn30UbKysnj00Ufp3r07rVq1ol27doSEhPDvf/+bDRs24O3tfVOfV72YzbBkSdO1dw2atN/NKNsR8o1EvNsBd3d49FHrWU0A33xj3aPpzBkATLW1l/zJmTMQGQnffWef/tSDeFcT8a4m4l1NxLuaqOpdnKuZb/TY9cSkaU17G6EjR44wYsQIDh8+TPfu3Zk/fz4PPPAA+/bto0WLFnz22Wc8oMNZLoJ9KCkpwdPTEwvQ5vIXw8Kst0K3M6WlpXh4eNg9x9GyjcyvqKhgzpw5vPjii7i4uOieD+Ld7vnl5dC27fUvgzOZ4Lbb4OhR653p7Ix4l++7StlG5ot38S7e1ckX72pmG+1d1e+b0dknT57Ex8cHi8Viu8GZPWmyM5jq8PPz4/vvv6d9+/YcPHiQYcOG2RaXvvzyS1lculUxm8HLS5eoq13CeKtnO0K+kYh3O7Nw4Y3tsXTxJbE6IN7VRLyriXhXE/GuJqp6F+dq5hs9dj1p8gUmsG56vXLlSlq3bo2maTg7O/PNN98wa9Yse8QJjkBtrfXSGkEQmieJidaF4htBx0tiBUEQBEEQBEFoHjRok+8vv/yyQY3HxMTw6aefMnnyZMrLy6/6/gcffLBB7QoOiJsbxMToEjVw4EBdchwt2xHyjUS825lTp6wLxTdCbS0UF9u3PxcQ72oi3tVEvKuJeFcTVb2LczXzjR67njRogenhhx/GVLcZ7A1iMplISkoiKSnpqq/LAtMtwPnzkJoK995rdE8EQbgZ2rWznpl0I4tMOl4SKwiCIAiCIAhC86DBl8hpmtbkP0LzQ6tbaGzbFsaMse7LMmMGbNhg9+xt27bZPcMRsx0h30jEu52JimrYGUxwY3s2NRLxribiXU3Eu5qIdzVR1bs4VzPf6LHrSYPOYDp48KC9+iE0M2rDw2HmTOtlcU5O1v2XkpMhIgLS06FPH6O7KAhCQ4iNhd/+Fs6csS4YXw2Tyfr64sXW7/m778KUKXr1UhAEQRAEQRAEB6VBC0xdunSxVz8EB2fu3LnMnTuXmpoaABIiI/Fo0YJok4nVqamUTpvG+IMHuW3PHspCQ/l+9mx6jx9PbW0t27dvByAyMpL09HROnTqFl5cXoaGhJCYmAtCvXz+cnZ3JysoCYPLkyWRmZnLixAnatGnD+PHjSbhw16qAgADy8vLYvHkzABMmTGD37t0UFBTg7u5OREQE8fHxAPTq1Qtvb282XDizauzYsezbt4/8/HxcXFyIjo4mPj6e2tpaAgIC8PX1JS0tDYCwsDDy8/PJy8vDycmJ2NhYzGYzcXFxdOnShYCAANasWQNASEgIhYWF7Nu3D4BZs2aRlJREWVkZfn5+BAYGkpqaCkBwcDAWi4Xs7GwAYmNjSUlJ4ezZs3Ts2JFBgwaxfPlyAIYOHUp5eTm7du0CYPz48aSkpHD69Gm8vb0JDg623ZWg7treuhXyKVOmsGnTJoqKimjbti1hYWEsubAx81133UWrVq3YsmULAOHh4WzdupXjx4/TunVrJk6cyMKFCwEIDAzE1dXV6j0hgYkTJ5Kdnc2RI0dwc3MjMjKSuLg4wLrBv4+PD+np6QCMHj2a3NxcfvrpJ1q2bMm0adNYuHAh1dXVdO/enc6dO7Nu3ToAQkNDKSgoIDc3F7PZzIwZM1i8eDEVFRV07tyZ4cOH23JGjBhBUVERe/fuBWDGjBkkJydz7tw5fH196du3LytXrgRg2LBhlJaWsmfPHsC6N1xqaiolJSV06NCBIUOGsGzZMgAGDx5MVVUVO3fuBCAqKoq0tDSqq6tJTU0lJCTEdrnvgAEDMJvNbN26FYCIiAgyMjIoLCzE09OTMWPGsHjxYgD69u2Lm5sbGRkZAEyaNIkdO3Zw9OhRPDw8CA8PZ8GCBQD07t0bLy8vNm7cCMC4cePo0KEDcXFxuLq6EhUVxfz589E0jR49etCxY0fWr18PwKhRozh06BAHDx7E2dmZmJgYEhISqKqqolu3bnTt2pW1a9cCMHLkSI4fP87+/fsxmUzMnDmTH558kmFvvAEmE6Z6FpnqntH+8AcqPv8c17w8uPdeqsaPJ2XiREo7diQoKIiysjJ2794NQHR0NKtXr8ZiseDj40NQUBDJyckADBo06Lo1orq6mri4uAbViD59+uDh4dHoGtGiRQuABtWIRYsWUVlZ2SQ1om7sDakRU6dOZd26dY2qEbUXzlDLy8uzublejfD09GTTpk2AtU41RY3YvHlzg2pEz549WbVqFdC4GjFx4kSWLVvWoBpRXFxMu3btmqRGVFdXc+bMmQbViJycHA4fPtyoGuHv7w9Y67zZbK63RiQmJnL+/Hn8/f3p3bs333//PQDDhw+nuLiYnJwcAKZPn87y5cspLS2lU6dO9O/fnxUrVgBcs0bcdtttnD17tkE14mbmEfXViPbt2xMXF2f3ecTVasSgQYPIysqy+zzi8hoxePBgm/e6x/aYR1yrRkyZMkWXeUR9NaKuztp7HnG1GhEYGGgbuz3nEZfXiEWLFtlc+/n5Ndk8oiE1olWrVsTFxTWoRtzMPKK+GlFdXU1JSYnd5xH11YihQ4fanNt7HnF5jbBYLABYLBZWr14N2GceAfXXCC8vL+Li4nSbR1xeI4YOHUpGRobd5xH11Yi6WqPHPAIurRG6ozWQzMzMhr5FuIWwWCwaoBUWFl754qlTmhYYqGmgab16adrJk3bpQ2pqql3adfRsI/PLy8u12bNna+Xl5Ybka5p4142kJE1r21bTQKs1my/5U2vbVtO++8563NmzmvbHP2qas7P1tZYtNe2llzTt/Pkm7Y541x/5vot3oxDv+iPexbtRqOrdyGyjvav6fTM6u7CwUAM0i8WiS16D92AaOnQofn5+PP744yQnJ1Ouwx4cQjPBywtWrgR/f9i713q53LlzTR5TVFTU5G02h2xHyDcS8a4T994LR4/CV19Re++9HOzaldp774WvvrI+X3c5nIcHzJkDu3bB+PFQWQmLFsGFs36aCvGuJuJdTcS7moh3NVHVuzhXM9/osetJgxeYAI4ePcrHH39MZGQk7dq1Y8qUKcybN8+YU7AEx8LPz7rI5OUFmzdb93WpqmrSiLZt2zZpe80l2xHyjUS860irVvDAA1TPn8+XDz9M9fz58MAD1ucvp1cvSEmx7sn00Ufg7Gx9vrISLpzG3RjEu5qIdzUR72oi3tVEVe/iXM18o8euJw1eYDpy5Agffvgh4eHhtGrVivPnz7Ns2TKefPJJ/P39GTx4MLNnz7ZdAy8oyJ13wrJl4OoKK1bAI4/c+N2pboCwsLAma6s5ZTtCvpGIdwfGZLJu9D9y5M/Pvfsu9O0LL74IpaU33bR4VxPxribiXU3Eu5qo6l2cq5lv9Nj1pMELTJ06deKxxx5j6dKlFBUVkZSUxKOPPsrtt9+Opmls27aNv/71rwQFBeHr62s79vz58/bov+Co3H03JCRYL5f5+mv44x+brOm6zeOMwMhsR8g3EvHezNi2zXr24ptvQu/eEB9/7bvTXQXxribiXU3Eu5qIdzVR1bs4VzPf6LHryU1dIleHq6srU6ZM4aOPPuLIkSNs2bKFV155hYEDB6JpGseOHeOTTz4hKioKb29vuZRONcLD4dNPrY/fftv6IwiCGsTFwdKl0L07FBTAzJkwZgxcuMOGIAiCIAiCIAi3Fo1aYLqcusvjMjMz5VI6wcqDD8Jbb1kfP/88fPllo5u86667Gt1Gc8x2hHwjEe/NkIgI64LSX/5i3b9p7Vro3x8+/viGmxDvaiLe1US8q4l4VxNVvYtzNfONHrueNOkC08VcfCndqVOn+O677655Kd3jjz/Ojh077NUdwUieew7+8Afr40cegeXLG9Vcq/o2GtYJI7MdId9IxHszpVUrePll+PFHiIoCsxlCQhrwdvGuIuJdTcS7moh3NVHVuzhXM9/oseuJ3RaYLqZVq1ZERERccindq6++ysCBAwE4duwYH3/8MUlJSXp0RzCCv//deheqmhrrneV++OGmm9qyZUsTdqz5ZDtCvpGI92ZO166wZIn1jKbevX9+/r334Br/uCDe1US8q4l4VxPxriaqehfnauYbPXY90WWB6XIGDx7Mq6++SmZmJocPH+bDDz9k8uTJuLm5GdEdQQ/MZut+TJMmQVkZTJ5sPaNBEAS16NHj58dbt8LvfgeDBsEzz8CZM0b1ShAEQRAEQRCERmLIAtPF1F1K99133/Hcc88Z3R3Bnjg7w8KFEBQExcUwYQIcOdLgZsLDw+3QOcfPdoR8IxHvtyA+PtYzGmtr4YMPoGdP60J0ba3tEPGuJuJdTcS7moh3NVHVuzhXM9/oseuJ4QtMgmK4u8OyZdCrFxw+bF1kKi5uUBNbt261U+ccO9sR8o1EvN+C+PlBfDysWgV33gknT8KvfgXDh0NmJiDeVUW8q4l4VxPxriaqehfnauYbPXY90WWBKS8vjxdffJGIiAiioqJ4+eWXOXjwoB7RgiPi7Q0rV4KvL2Rnw5Qp1svmbpDjx4/bsXOOm+0I+UYi3m9hxoyx7sP09tvg4QGbN8PEiVBWJt4VRbyriXhXE/GuJqp6F+dq5hs9dj1xasybMzMz+e677zCZTLzwwgu4u7tfcUxycjLTp0+noqLC9tzSpUt5++23+eKLL5g+fXpjuiA0V7p0gZQUGDkSNm6EGTOsGwA7Xf8/ydatW+vQQcfLdoR8IxHvtzjOzta7Td53H7zwgvUsJjc369g1zfpj1vekW6M/d6PzjUS+72oi3tVEvKuJqt7FuZr5Ro9dTxo1W//3v//N66+/zvr16+tdXDp+/DgPPPAA5eXlaJpGQEAAvXv3xmQyUVFRwUMPPUROTk5juiA0Z/r2haVLrbcxT06Gxx6z/iXyOkycOFGHzjletiPkG4l4V4Tbb4evvoInngAujH3pUuvebY24++TNYPTnbnS+kcj3XU3Eu5qIdzVR1bs4VzPf6LHrSaMWmFatWgXAfffdV+/r//znPykpKaFFixYsWrSIffv2sWfPHlavXo27uzuVlZW89957jemC0NwJCbHuwdKiBXz2Gfz5z9d9y8KFC3XomONlO0K+kYh3xTCZAFi4YAHMng1ZWRAcDI88AoWFunTB6M/d6Hwjke+7moh3NRHvaqKqd3GuZr7RY9eTm15gqqqq4vDhwwCEhITUe8yCBQswmUzcf//9TJ061fb8Pffcw3PPPYemaaxZs+ZmuyDcKtx7L8ybZ308Zw68+66h3REEwYEwmWDFCnj4Yevvn31mvUnABx9AdbWhXRMEQRAEQRAE4WdueoHpxIkTtsddu3a94vVjx47ZNvKOjY294vWYmBgA2yKVoDiPPAL/+7/Wx88+C3FxVz00MDBQp045VrYj5BuJeFeTwMBA6NDBurC0cSMMGgRnzsAzz8DgwXa9bM7oz93ofCOR77uaiHc1Ee9qoqp3ca5mvtFj15MGbfLdrVs3TBcuW6iqqrI9X98HdvGm3k8++SROl23erF3Ya6e8vJzu3btf8lpeXl5DuiXowNy5c5k7dy41NTUAJCYm4uHhQXR0NKtXr8ZiseDj40NQUBDJyckADBo0iNraWrZv3w5AZGQk6enpnDp1Ci8vL0JDQ0lMTASgX79+OEdHo/33v/RauRLtoYfYcfgwP/r706ZNG8aPH09CQgIAPj4+5OXlsXnzZgAmTJjA7t27KSgowN3dnYiICOLj4wHo1asX3t7ebNiwAYCxY8eyb98+8vPzcXFxITo6mvj4eGprawkICMDX15e0tDQAwsLCyM/PJy8vDycnJ2JjY9mxYwfZ2dl06dKFgIAA2xl4ISEhFBYWsm/fPgBmzZpFUlISZWVl+Pn5ERgYSGpqKgDBwcFYLBays7MB6wJsSkoKZ8+epWPHjgwaNIjly5cDMHToUMrLy9m1axcAgwcPJiUlhdOnT+Pt7U1wcDBLly4FYODAgQBs27YNgClTprBp0yaKiopo27YtYWFhLFmyBIC77rqLVq1asWXLFgDCw8PZunUrx48fp3Xr1kycONF2KmdgYCCurq4AJCQkMHHiRLKzszly5Ahubm5ERkYSd2FBsGfPnvj4+JCeng7A6NGjyc3N5aeffqJly5ZMmzaNhQsXUl1dTffu3encuTPr1q0DIDQ0lIKCAnJzczGbzcyYMYPFixdTUVFB586dcXd3t+WMGDGCoqIi9u7dC8CMGTNITk7m3Llz+Pr60rdvX1auXAnAsGHDKC0tZc+ePYB1cTs1NZWSkhI6dOjAkCFDWLZsme3zraqqYufOnQBERUWRlpbGkSNHOHHiBCEhISQlJQEwYMAAzGaz7bajERERZGRkUFhYiKenJ2PGjGHx4sUA9O3bFzc3NzIyMgCYNGkSO3bs4OjRo3h4eBAeHs6CBQsA6N27N15eXmzcuBGAcePGkZ+fT3Z2Nq6urkRFRTF//nw0TaNHjx507NiR9evXAzBq1CgOHTrEwYMHcXZ2JiYmhoSEBKqqqujWrRtdu3Zl7dq1AIwcOZLjx4+zf/9+TCYTM2fOJDExkfPnz+Pv70/v3r1tn2F+fj6lpaW2PfOmT5/O8uXLKS0tpVOnTvTv358VK1YAEBQURFlZGbt37wZodI3IzMwkOzvbWiPatWPr739PwJo1DFm8GNPOnaxbsoRzp05dUiP69OmDh4dHo2tEdXU1/fv3b1CNWLRoEZWVlU1SI+rG3pAaMXXqVNatW9eoGlFbWwtY/19c5+Z6NcLT05NNmzYBMH78+EbXiJKSEsrLyxtUI3r27Gm7dL8xNWLo0KEsW7asQTWiuLiYdu3aNUmNKCsro0uXLg2qETk5ORw+fLhRNcLf3x+w1nmz2XxDNeL7778HYPjw4RQXFze6Rri4uNC9e/ebn0c4O5OVlQXA5MmTyczM5MSJE1fMI+qrEYcOHSI7O9vu84ir1YiAgACysrLsPo+4vEYMHjzY5r3usT3mEdeqEf3799dlHlFfjdi2bRvZ2dl2n0dcrUaUlJTYxm7PecTlNWLRokU2135+fnabR1yrRmRnZ5OdnW33eUR9NaKsrIxu3bo1qEY01d81zGazzbm95xGX1wiLxQKAxWJh9erVgH3mEVB/jTh48CDZ2dm6zCPqqxE9evQgIyPD7vOI+mpE3ZxOj3kEXFojdEdrAK+++qo2e/Zsbfbs2dozzzyjmUwmrUWLFtorr7xie77uZ/jw4ZrJZNL8/PyueK3ux2w2ay1atLjiecFxsVgsGqAVFhbaJ6CmRtNmzbLeM8rdXdMyMq445Ntvv7VP9g1gZLaR+eXl5drs2bO18vJyQ/I1TbwbgUN7P3lS0+bOvfS5rCxNq6y0f7ZOiHf1so3MF+/i3SjEu/6IdzWzjfau6vfN6OzCwkIN0CwWiy55DTqDafbs2bbHx44d44MPPkDTNKZPn06fPn0uOTY9PR2TycSYMWN49dVXr2jr/PnzvPbaa7Ru3bre1wVFMZvh88/h5ElYtQrCw2HDBujZ0+ieCYLgSHh7w69//fPvJ07AqFHg62vdn2n0aOP6JgiCIAiCIAgKctN7MN1+++20bdsWgPfff/+S13788UfbqWjjxo2r9/11p5vVnZItCDZatoTFi637qxQVwfjxcNHpfePHjzesa0ZmO0K+kYh3NbnhsefkWGvHjz/CmDEwYwYcOaJPtp0wOt9I5PuuJuJdTcS7mqjqXZyrmW/02PXkpheYwHpNrKZp/Oc//+HRRx9l6dKlfPLJJ0yaNImamhratm17yd3jLqbu+t0BAwY0pgvCrUrr1rB8OfToAT/9BBMnWjf2Bdv1xEZgZLYj5BuJeFeTGx77PffA3r3w1FPWMyEXLLDebW7OHLhoT0C7ZNsJo/ONRL7vaiLe1US8q4mq3sW5mvlGj11PGrXA9Je//AVvb280TePTTz8lKiqKxx57jPz8fEwmE6+//jpubm71vvfzzz/HZDJd9QwnQcDHB1auhI4dYdcuuPdeOH+eI408K6ExGJntCPlGIt7VpEFj9/KyXh6XlQXDh0NZGfzpT9Y7z93EIpPRn7vR+UYi33c1Ee9qIt7VRFXv4lzNfKPHrieNWmC6/fbb2bBhA2FhYWiaZvu57bbb+Oc//8njjz9e7/sSExPZtWsXrq6uVz3DSRAA6NYNUlKgTRtYvx7uuw83FxfDunO1BVNV8o3EyLEb/bkbnW8kNzX2AQMgPR2++AI6dIBx4+Am6obRn7vR+UYi33c1Ee9qIt7VRFXv4lzNfKPHricmTdO0pmjoxIkTHDx4EFdXV/r06YOT09X3D//xxx8pLCykTZs2ttsdCs2DkpISPD09KSwspH379voF//e/MGGC9SyERx+Fjz4Ck0m/fMWpqKhgzpw5vPjii7gYuMAn6Mst4d1isdaKNm2sv+/eDUuWwPPPQ6tWxvbNQbklvAsNRryriXhXE/GuJuJdTU6ePImPjw8Wi4U2dfNhO9KoM5gupkOHDtx9993079//motLAHfeeSf33HOPLC4JN84998C331r3VvnPf8CgOw/GxcUZkuso+UZi5NiN/tyNzjeSRo/d0/PnxSVNs+7R9Mor0KcPJCfbN7uRGJ1vJPJ9VxPxribiXU1U9S7O1cw3eux60mQLTIJgd6Kj4V//sj7+619h7lxj+yMIQvPjySehUyfIy4MpUyAiAnJzf369vBy++gqmTWP0X/8K06ZZfy8vN67PgiAIgiAIgtAMkAUmoXnx+OMcrdvb65lnrHeK0pGePXvqmudo+UZi5NiN/tyNzjeSJh27yQQzZ1rvNvfCC+DsDMuWWc9meuUVWLjQuvj04IOQmEiHH3+ExETr7506wdKlTdeXG0C8q5ftCPlGIt7VRLyriarexbma+UaPXU9kgUlodtT8+c/w619bL3d54AFYvVq3bB8fH92yHDHfSIwcu9Gfu9H5RmKXsXt4wJtvws6d1g3AKyqsZ0XOmAFnzliPqa299M8zZyAyEr77run7cxXEu3rZjpBvJOJdTcS7mqjqXZyrmW/02PWkUQtMhw4d4p///Ce/+c1v+N3vfseHH37IsWPHbvi9o0ePZsyYMY3pgqAg6Rs2wHvvQUwMVFXB1Kmwdas+2enpuuQ4ar6RGDl2oz93o/ONxK5j790bVq6EuDio2zvwave9qHv+4Yd1u1xOvKuX7Qj5RiLe1US8q4mq3sW5mvlGj11Prr0b9zV46aWXeOutt6iurr7k+WeffZann36av/3tb9fcnf7cuXOsW7cOk9wJTLgZWrSAr7+GU6dg7VqYNAk2bIA77jC6Z4IgNCdMJutC9WX/L6sXTYPTpyEhwXr2pCAIgiAIgiAINm7qDKYXX3yRN954g6qqKjRNu+SnoqKCf/zjHwwZMoS9e/c2dX8FgdGjR1sfuLhY90cZMAAKC2HCBDh+XJ9sgzA630iMHLvRn7vR+Uaiy9gTE613qLwRzGZYssSu3alDvKuX7Qj5RiLe1US8q4mq3sW5mvlGj11PGrzAtHPnTt566y0A2rdvz/vvv8/u3bvJysri//7v/+jcuTOaprFnzx5GjBjBli1bmrzTgtrkXnzHpzZtYMUK6N7deleoSZOgpESfbAMwOt9IjBy70Z+70flGosvYT536ea+l61FbC8XF9u3PBcS7etmOkG8k4l1NxLuaqOpdnKuZb/TY9aTBC0wfffQRmqbRtm1bNm3axFNPPUVgYCADBw7k2Wef5ccff+Spp54CoLi4mDFjxrB27dom77igLj/99NOlT3TsaN1HxccHtm+HqCjrpr16ZOuM0flGYuTYjf7cjc43El3G3q7djZ/BBODmZr++XIR4Vy/bEfKNRLyriXhXE1W9i3M1840eu540eIHpv//9LyaTiWeffZbu3btf8bqrqyvvv/8+X331FS4uLpSWljJ58mSSk5ObpMOC0LJlyyufvOMO65lMrVtb92R64AGoqdEnW0eMzjcSI8du9OdudL6R6DL2qKgbP4MJYNasnx/bccNv8a5etiPkG4l4VxPxriaqehfnauYbPXY9afAC0+HDhwEYNWrUNY+7//77WbFiBa1bt6a8vJxp06YRHx9/c70UhIuYNm1a/S8MGmTdS6VlS+smvL/5zdXvCNXU2TphdL6RGDl2oz93o/ONRJexx8ZC27bWDb+vhckEt91mvYMlwLFj4OcHzz9v3QeuiRHv6mU7Qr6RiHc1Ee9qoqp3ca5mvtFj15MG30Wu/MK/1rq6ul732LCwMFavXs2kSZM4deoUDzzwAOfOneORRx5peE8FQ5k7dy5z586l5sJZQYmJiXh4eBAdHc3q1auxWCz4+PgQFBRkO1tt0KBB1NbWsn37dgAiIyNJT0/n1KlTeHl5ERoaSmJiIgD9/j975x0W1bH+8c+uIIgIioiGYiMq9o5dMUZjQUEUNc2YntzExNRrfjfJNbkpmn4TTTHtJiZBBBQRew0WFHtHjQ3FKGJZRKS55/fH0FREVtg9izOf59mHLWfPd2a/7Mvwnpl32rXD0dGRrVu3AjBs2DC2bNnCmTNncHNzY9CgQURHRwOQmZnJgAED2LRpEwD33Xcfe/bsITU1lZo1axL8yy8YHngAw9dfc8psJv+NN1i/fj0A9957LwcPHiQlJQUnJyfCwsKIjIzEbDbj7++Pj48PCQkJgPj9TUlJ4ciRIzg4OBAeHs7nn39OgwYNaNSoEf7+/qxatQqA3r17k5aWxsGDBwG4//77mT9/PllZWfj6+tKqVSuWLVsGQI8ePTCZTOzbtw+A8PBwlixZwqVLl2jQoAGdOnVi0aJFAHTt2pXs7Gx2794NgMFgoHbt2ly4cAFPT0969OjBggULAOjYsSMA27dvB2D48OEkJiaSnp5OnTp1CAoKYl5BceK2bdvi7OxcVCNt6NChbNu2jdOnT1OrVi0GDx5MVFQUAK1atSr6vkdHRzN48GD27dvHyZMncXFxISQkhIiICACaN2+Ol5dX0Vac99xzD4cPH+b48eNUr16dUaNGERUVRX5+Pk2bNqVhw4asWbMGgL59+5Kamsrhw4cxGo2MHTuWuXPnkpOTQ8OGDTl69CjVqlUDoFevXqSnpxdtJDB27Fji4+O5fPkyPj4+tGnThqVLlwLQrVs3MjMz2bt3LwCjR49m2bJlZGRkUL9+fbp06cLChQsB6Ny5M3l5eezatQuA0NBQEhIS2LNnD23btqV3797Mnz8fgA4dOmA0Gtm2bRsAwcHBJCUlkZaWhru7OwMGDGDu3LkAtGnTBhcXF5KSkgAYMmQIO3fu5NSpU7i6ujJ06FDmzJkDQEBAAB4eHmzYsAGAgQMHEhUVRe3atalRowahoaHMnj0bTdNo1qwZDRo0YO3atYBI/B87doyjR4/i6OjI6NGjiY6OJi8vjyZNmtC4ceOiJct9+vTh9OnTHDp0CIPBwLhx44iNjeXKlSv4+fkREBBQ9BmmpKSQmZlJcnIyAGPGjGHRokVkZmbi7e1N+/btWbx4MQCBgYFkZWWxZ88egArHiK+//hpvb2+LYkTr1q1xdXW9eYwIDi664NGiRQs8PT05+thj9P3sMzAYMJSSmC585vznn7Os4Hs0bN8+3M6dg08+If/LL3F4/nniW7bkUs2alRIjVqxYgbe3t0UxYuTIkaxZs6ZCMcJcMJvryJEjRd7cKka4u7uTmJgIwKBBgyocI1JSUujdu7dFMaJ58+asWLECqFiMMBqNuLq6WhQjzp8/T926dSslRpw6dYrHH3/cohiRnJzMiRMnKhQj/Pz8ABHnjUZjuWLE8uXLAejZsyfnz5+vcIw4d+4cjzzyiNXHEaXFiNmzZ1OnTp2bxojKGkfExMSQm5t7Q4zIzc2lTZs2Vh9HXB8jOnfuXOR74X1rjCPKihG5ublFu1JbcxxRWoxYvXo13t7eVh9H3CxGJCYmFo2xrDmOuD5GxMTEFHnt6+trtXFEWTFi+vTpeHl5WX0cUVqMOHXqFE8++WSljiPKGyOSk5NxdHQELIsRlfG/hslkAsBkMrFy5UrAOuMIKD1G/Pbbb3h4eNhkHFFajMjLyyMgIMDq44jSYsT333+Pt7e3TcYRcG2MsDmahdx1112a0WjU4uPjy/2ePXv2aN7e3prBYNCMRqP25Zdfanv27Cl6rKg6mEwmDdDS0tJ0a8Mff/xx64OmT9c0MX9J07791rbaVkQv/ezsbG3KlCladna2Lvqapu9nr3yXxPf58zWtTh0RN4zGa3/WqaNpcXHXHm82a9rChZoWGFgcb5ydNW3SJE07darCzVG+y6etp77yXfmuF8p326N8l1Nbb99l/b7prZ2WlqYBmslksomexUvkWrVqBVCUpS0PrVu3JiEhoWiHuUmTJjFt2jRLpRUKgFJrf93Ac8/BW2+J+//4BxRkd22ibUX01tcTPfuu9+eut76e2LTvI0bAqVMwaxaEhmLq1EnUZ5o1Szw/fPi1xxsMMHQobNwoasB17y5qMn3xBbRpA1lZFWqO8l0+bXvQ1xPlu5wo3+VEVt+V53Lq6913W2JxgqlXr15omlY0tbK8+Pv7s27dOpo3b46mafz++++WSisUADRs2LB8B77zDjz5pCje+8AD8OefttO2Enrr64mefdf7c9dbX09s3ndnZ7FJQEwMWfHxEBMjHjs73/w9BgMMHgwbNogdLXv0gPHjr91t7tw5i5uifJdP2x709UT5LifKdzmR1XfluZz6evfdllicYBo0aBAAf/31V9EaxfJSuMa3ffv2aJVcfFkhD4XraG+JwQBffy1mIOTkiNkJO3faRttK6K2vJ3r2Xe/PXW99PalSvhsMMGgQrF8PU6cWP79xI/j4wMSJcPKk9fTvIKqU73eYvp4o3+VE+S4nsvquPJdTX+++25LbmsHk5+eH0WhkypQpFgvWq1ePNWvW0KNHD4vfq1BYjIMD/PEH9OkDGRlilsHRo3q3SqFQ3MkYDODkVPx43jyR5J4+Hfz9xbLdgh1ZFQqFQqFQKBSKOwWLE0wAx48fJy8vr6h6u6W4u7uzevVqjh49ypEjR27rHAp56du3r2VvqFED4uKgbVs4fVrMMLjNLcUt1q5k9NbXEz37rvfnrre+ntwRvk+dCqtWQb9+kJsL33wjEk3PPAPHj1tfvwpyR/heRfX1RPkuJ8p3OZHVd+W5nPp6992W3FaCqTKoXr06jRo1olGjRno1QVFFSU1NtfxNtWvDkiXQqBH89ZcozHvpkm20KxG99fVEz77r/bnrra8nd4TvBgP07w9r1sDq1RAUBHl58N13cO+9ok6cNfWrIHeE71VUX0+U73KifJcTWX1Xnsupr3ffbYluCSaF4nY5fPjw7b3R2xuWLQNPT9i6FcLCxGwCW2hXEnrr64mefdf7c9dbX0/uON+DgkSS6c8/4Z574JVXwFjwpzg/H44ds65+FeGO870K6euJ8l1OlO9yIqvvynM59fXuuy1RCSZFlcNorMCvbfPmsGgR1KwJK1bAI4/cdPZApWtXAnrr64mefdf7c9dbX0/uWN/79oWVK+Hpp4uf++03aNYMHn8cjhxRvkuobQ/6eqJ8lxPlu5zI6rvyXE59vftuS3Tr6dWrV0lJSSElJUWvJiiqKGPHjq3YCbp2hblzRQHw2bPhpZegnLsaVli7guitryd69l3vz11vfT254303GIrvb9woZjH99BM0b87YJUvEkl4JueN9t2N9PVG+y4nyXU5k9V15Lqe+3n23JbedYMrKyuL999+nY8eOuLm5Ubt2bbp3787nn39Odnb2Ld+fnJxM48aNadq06e02QSEpc+fOrfhJBg2CX34R97/88totxa2tXQH01tcTPfuu9+eut76eSOX7t9/Chg1it8urV+F//4OAADHT8tAh27ZFZ6Ty3c709UT5LifKdzmR1XfluZz6evfdltxWgunEiRN06tSJt99+m127dpGZmUlGRgabN2/m1VdfJSAggD///LNc59LKOXNEoSgkJyenck70wAPwxRfi/v/9H/z4o+20bxO99fVEz77r/bnrra8n0vneowcsXgwbN5LaoYNINP36q9hxTiKk892O9PVE+S4nync5kdV35bmc+nr33ZZYnGC6evUqo0aN4uDBg2iahqOjI126dKFt27ZUq1YNTdNISUlhwIABfPzxx9Zos0JyGjZsWHkne/FFmDxZ3H/qKYiLs532baC3vp7o2Xe9P3e99fVEWt+7dePY9OmwaRMMGwZvvVX82rlzkJysX9tsgLS+24G+nijf5UT5Liey+q48l1Nf777bEosTTFFRUWzZsgWDwcCYMWM4deoUSUlJ7Ny5k9TUVF555RUcHBwwm81MnjyZ119/3RrtVkhM8+bNK/eEH3wAjz4qin2PHQvr1tlO20L01tcTPfuu9+eut76eSO97YCDEx4vd5wr55BNo1UrMwty/X7f2WRPpfZcU5bucKN/lRFbfledy6uvdd1ticYJp9uzZAHTt2pWIiAg8PDyKXqtXrx4ff/wxa9euxdfXF03T+PTTT3lGsqn9CuuyYsWKyj2hwQAzZ0JwMGRnw/DhsGePbbQtRG99PdGz73p/7nrr64nyvRROnhQbE0REQOvWMG4c7N1r28ZZGeW7nCjf5UT5Liey+q48l1Nf777bEosTTFu3bsVgMPDCCy9gKLn7TQm6devG5s2b6dSpE5qm8f333/Pggw9y9erVCjdYobAKDg4QGQk9e8LFi3DffXD8uN6tUigUihuZNQu2b4eRI0WiKTIS2raFMWNumhxXKBQKhUKhUCisjcUJpvT0dABatmxZ5nH169dnzZo1BAUFoWkas2fPZtSoUeTl5d1eSxWKAnr16mWdE7u4wIIFYunJqVMiyVTw+2517XKit76e6Nl3vT93vfX1RPl+Ezp0gLlzYccOGDVKJJqiomD6dFs1z6oo3+VE+S4nync5kdV35bmc+nr33ZZYnGCqVq0aANnZ2bc81tXVlcWLFxMcHIymaSxYsIDg4GCuXLlieUsVigLSr0v6VCoeHrB0Kfj5wYEDorjuuXNixsCoUdQJCxP/zM2aJZbT2Rir9t3O0bPven/ueuvrifL9FrRvD9HRsHOnmMH0xhvFrx04IBJQVRDlu5wo3+VE+S4nsvquPJdTX+++2xIHS9/g6+vLoUOHOHToED169Ljl8U5OTsybN4+HHnqIyMhIVqxYwX333ce0adNuq8EKfZgxYwYzZswoWuYYGxuLq6srYWFhrFy5EpPJhJeXF4GBgcTHxwPQqVMnzGYzOwr+wQkJCWHdunWcO3cODw8P+vbtS2xsLADt2rXD0dGRrVu3AjBs2DC2bNnCmTNncHNzY9CgQURHRwOQkZFB7dq12bRpEwD33Xcfe/bsITU1lZo1axIcHExkZCQALVq0wNPTk/Xr1wNw7733cvDgQVJSUnByciIsLIzIyEjMZjP+/v74+PiQsHYtbi+8wJAPPsCYlIS5fn2MV6+C0Ugtsxnztm0Y587FPHEia594glOdO9O7d2/S0tI4ePAgAPfffz/z588nKysLX19fWrVqxbJlywDo0aMHJpOJffv2ARAeHs6SJUu4dOkSDRo0oFOnTixatAgQtc6ys7PZvXs3IHZxTEtL48KFC3h6etKjRw8WLFgAQMeOHQHYvn07AMOHDycxMZH09HTq1KlDUFAQ8+bNA6Bt27Y4OzuzefNmAIYOHcq2bds4ffo0tWrVYvDgwURFRQHQqlUratSoAUB0dDSDBw9m3759nDx5EhcXF0JCQoiIiABEATsvLy/WFRRKv+eeezh8+DDHjx+nevXqjBo1iqioKPLz82natCkNGzZkzZo1APTt25fU1FQOHz6M0Whk7NixzJ07l5ycHBo2bMihQ4c4cOAAIK4CpKenFz0eO3Ys8fHxXL58GR8fH9q0acPSpUsBsWQ3MzOTvQU1akaPHs2yZcvIyMigfv36dOnShYULFwLQuXNn8vLy2LVrFwChoaEkJCSwe/du0tPT6d27N/PnzwegQ4cOGI1Gtm3bBkBwcDBJSUmkpaXh7u7OgAEDmDt3LgBt2rTBxcWFpKQkAIYMGcLOnTs5deoUrq6uDB06lDlz5gAQEBCAh4cHGzZsAGDgwIEkJiZy4MABatSoQWhoKLNnz0bTNJo1a0aDBg1Yu3YtAP379+fYsWMcPXoUR0dHRo8eTXR0NHl5eTRp0oTGjRuzevVqAPr06cPp06c5dOgQBoOBcePGERsby5UrV/Dz8yMgIKDoM0xJSSEzM5Pkgp3LxowZw6JFi8jMzMTb25v27duzePFiAAIDA8nKymJPwVKtisaIVatWceDAAYtiROvWrXF1da1wjPj777/p1KnTjTEiIQGAoKAgUlJSOHLkCA4ODoSHhxMTE0Nubi6NGjXC39+fVatWAdxWjCjse7lixN69EBrKyPr1WbNkCRcuXGDA9Ol4bdjAyc6d2TNqFI1HjixXjDCbzQAcOXKkyJtbxQh3d3cSExMBGDRoUIVjxPHjx8nLy7MoRjRv3ryoxkFFYoTZbObvv/+2KEacP3+eunXrVkqMSE1NpWnTphbFiOTkZE6cOFGhGOHn5weIOG80GssVI5YvXw5Az549OX/+fIVjRHp6Os2aNbP6OKK0GLFhwwYOHDhQOeOI24gRV65cQdM0q48jRo4cyZo1a4rGEZ07dy7yvfC+NcYRZcWIrKysou+qNccRpcWIwjhr7XHEzWLE1q1bi/puzXHE9TEiJiamyGtfX1+rjSPKihEJCQkcOHDA6uOI0mJEamoqd999t9XHEaXFiL179xZ5bu1xxPUxwmQyAWAymVi5ciVw6xhRmf9rrF+/ngMHDthkHFFajMjOziY/P9/q44jSYkRhrLHFOAKujRE2R7OQsWPHagaDQXvkkUcsep/ZbNaeeOIJzWAwaEajUfPz8yu6r6g6mEwmDdDS0tJ0a8Mff/xhG6GPPtI0sfCk9JvBIG7z59umPZoN+34d2dnZ2pQpU7Ts7Gxd9DVNv77rra2nvvK9Cvuel6dpDzwgYlRhzBoxQtO2bLnlW5XvVdj3CqB8V77rhfLd9ijf5dTW23dZv296a6elpWmAZjKZbKJn0DRNsyQh9e233/KPf/wDV1dX/v77b2rWrGlRQuvll1/miy++wGAwoGkaBoNBFf+uQmRkZODu7k5aWhr16tXTpQ1msxmj0eLVnZaRnQ3e3qLgd1lfEYMBatcWNZucna3bJmzU91LIyclh6tSpTJ48GScnJ5vrg35911tbT33l+x3g+/798N57MHs2FMxMIjgY3nkHOnW69tjsbIiK4urcuaRs307Djh2pFhYG4eE2iW8lUb6r77tM2nrqK9+V78p3ebT19l3W75ve2mfPnsXLywuTyYSbm5vV9Szu5bBhwzAYDFy+fJlvvvnGYsHPPvuMt99+GwvzWgpFEYXTYq1KVBRcuFB2cgnE6xcuiBooNsAmfbdT9Oy73p+73vp6onyvIC1bwu+/w7598NBDYDRCfDwULOEpIi5OJNXHj8cYF0eT48cxxsXB+PHi+YLp8bZC+S4nync5Ub7Liay+K8/l1Ne777bE4hpMfn5+vPnmm5w6dYpz587dluiUKVOoW7du0ZpBhcISLl++bH2R2Fjxj1jhFf+yMBph3jzxz5uVsUnf7RQ9+6735663vp4o3yuJFi3E5gRvvQVffglPP1382gcfwJtvFj00FMS9wp9cvAghISIujhhReW0qA+W7nCjf5UT5Liey+q48l1Nf777bEosTTADvvPNOhYUnTpzIxIkTK3wehXz4+PhYX+TcufIll0Acd/68ddtTgE36bqfo2Xe9P3e99fVE+V7JNG8O06cXP87KEkmnsmZrappYDjxhgs2WAyvf5UT5LifKdzmR1XfluZz6evfdlui3CFKhuE3atGljfZG6dcXMpPJgNIKHh3XbU4BN+m6n6Nl3vT93vfX1RPluZX77rXzJdBsvB1a+y4nyXU6U73Iiq+/Kczn19e67LVEJJkWVo3BLSKsSGmrZDKaC7b+tjU36bqfo2Xe9P3e99fVE+W51EcuS6QXbD1sb5bucKN/lRPkuJ7L6rjyXU1/vvtuS21oiVxrHjx9n//79nDhxgszMTK5cuUKNGjVwdXXFz8+Pli1b0qhRo8qSUyisS3g4vPjirXeRK2TzZhg3Dhwq7SulUCgU1sdOlwMrFAqFQqFQKKoeFfpv+OjRo3zxxRfExsZy8uTJWx7v4+NDaGgoL774Iv7+/hWRrhSCgoL4888/LXrP6tWrCQoKKvW1JUuWMHPmTJKSkjh79iz16tUjMDCQp556isGDB5fr/FlZWcyYMYOoqCj++usvcnNz8fPzY9iwYbzwwgs0bNiwXOfZu3cvX331FStWrCA1NRVXV1datmzJgw8+yOOPP45DFU6EdOvWzfoizs7wyy+isK3BUHqSqeTzX34JO3dCZCTUr2+1Ztmk73aKnn3X+3PXW19PlO9WpnA5cHmSTAYDHDgAK1bAgAHisZVQvsuJ8l1OlO9yIqvvynM59fXuuy257SVyb7/9NgEBAUyfPp0TJ06gadotbydPnmTGjBm0atWKt956qzL7YROMRiPNmjW74XlN03j66acZMmQI8+bNIzU1ldzcXFJTU5k3bx5Dhgzh6aefRrvFTJjDhw/TqVMnXn/9dTZv3syFCxe4fPkyycnJfPrpp7Rr145Fixbdsp0//vgjnTt35rvvvuPw4cNkZ2eTnp7O2rVreeaZZ+jTp89t7wBoD2RmZtpGaPhwsWtS7driceEyksKftWuLrb1jYsDVFf78Ezp3ho0brdYkm/XdDtGz73p/7nrr64ny3cpYshxY0+Dvv2HgQGjZUhQLz8iwSrOU73KifJcT5bucyOq78lxOfb37bktuK8H07LPP8v7775OXl4emabRo0YKnnnqKzz77jKioKBYtWsTKlStZtGgRUVFRfPbZZzz11FMEBASgaRp5eXl88MEHPF1ym2Qd+Pnnn9m9e3eZt8jIyKLjBwwYUGoF+DfffJOZM2cC0LFjRyIiIkhKSiIiIoKOHTsCMHPmzDKTapmZmQQHB3PgwAEAnnzySVauXMmGDRt4//33cXV1xWQyER4ezq5du256nqVLl/LUU0+Rk5ND/fr1+fLLL9m0aROLFy8mLCwMgI0bNxIWFoa5vP9U2Bl79+61ndiIEWLXpFmzIDSUMy1bin/IZs0Szw8fDmFhkJQEAQGQmgp9+8K335ZvaZ2F2LTvdoaefdf7c9dbX0+U71YmPBzq1Ln1bCSDAdzc4JlnREL9wAGYOBF8fOC552D//kptlvJdTpTvcqJ8lxNZfVeey6mvd99ticXrpJYuXcp3332HwWCgS5cufPXVVxZN+dq4cSMvvPACW7Zs4YcffmDUqFEMGjTI0mZUCk2aNLnlMbNmzSq6P378+Bte/+uvv/joo48A6NKlCwkJCdSoUQOArl27MmLECPr168eWLVuYNm0ajz76aKnLAz/55BOSk5MB+Oijj3jttdeKXuvRowf9+/enb9++ZGVlMWnSJFatWnXDOfLz83n++ecxm824ubmxfv36a7QGDx7Mc889x9dff01CQgK//fZbqX1SXIezMzz0EDz0EKsiIrj//vtvPKZlS5FkevRRMaPp2Wdh0yb4+mso+H1QKBQKu6O8y4FB7Dg3fDhMmyaS7NOnQ3KyiHOOjvDFFzZtukKhUCgUCoXCztAsJCwsTDMYDFrnzp21rKwsS9+uaZqmXblyRevUqZNmNBq1kSNH3tY5bMHVq1c1Hx8fDdBcXV21y5cv33DMP/7xDw3QAC0xMbHU8yQmJhYd8/zzz9/wem5urla7dm0N0Fq2bKldvXq11PM8/fTTRefZsmXLDa/PmTOn6PUPP/yw1HNcvnxZq1OnjgZobdq0Kav7pWIymTRAS0tLs/i9lUVubq79apvNmjZtmqYZjZoGmtapk6YdPWo7fSuRnZ2tTZkyRcvOztZFX9Ps3Pc7VF/5LpHv8+drWp06mgaauSB+Ff7U6tTRtLi4G99jNmvaihWaFhqqaQcOFD+fmKhpH36oaRX4O6F8tz3q+6581wvlu+1Rvsuprbfvsn7f9NZOS0vTAM1kMtlEz+IlcklJSRgMBl5//fWimTqW4uzszD//+U80TWPz5s23dQ5bsHLlSlJTUwEYPXo0Li4u17yuaRrz588HICAggO7du5d6nu7du9OiRQsAYmNjb6jFtGbNGi5evAjAI488gvEmW0ZPmDCh6P7cuXNveD02NrbUY0vi4uLCmDFjANizZw+HDh0q9Th7ZtmyZfarbTDA66/DsmXg6Qnbtom6TJXUZj37rjd27fsdrq8nyncbUWI5sHnECI42box5xIhrlwNfj8Egin3PmwfNmxc//9ln8MYb4OcHEybAli0WN0f5LifKdzlRvsuJrL4rz+XU17vvtsTiBNPZs2cBKrwLXOH709PTK3Qea/Lrr78W3S9tKdnRo0eLElD9+vUr81yFr588eZJjx45d89ratWtvOK40unTpQs2aNQFYt27dDa8XnqdFixY0aNDglm252XnsnQwrFZWtVO0BA2DrVujSRWzrPXgwfPBB+YvpVlT/DqRK+H6H6uuJ8t2GFCwHzp89m18nTCB/9myxPNjZ2bLzhISI2JeTI5bfde0K3buLJXY5OeU6hfJdTpTvcqJ8lxNZfVeey6mvd99ticUJpnr16gFix7OKUPh+T0/PCp3HWmRmZjJv3jwAGjZsSFBQ0A3H7C9R1DQgIKDM85V8ff91xVDLex4HB4eixNz158jMzOTkyZMVbktVoH79+lVDu2FDWLsWnnhC1DX5179EQXCTyTb6dxhVxvc7UF9PlO9VkAcfhM2bRR26hx+G6tWL799zT7lOoXyXE+W7nCjf5URW35Xncurr3XdbYnGCKTAwEE3T+Pjjj8kp55XI68nOzmbatGkYDAa6du16W+ewNjExMVy+fBmAhx9+GEMpO+ycOHGi6L6vr2+Z5/Pz8yv1fSUf16xZk9q1a5frPGfPnr3m8z958mTR0ruKtKUq0KVLl6qj7ewM338vbtWrw/z5EBgI+/bZRv8Ookr5fofp64nyvQoTGAi//gonTsD774Ovr9i1rpDsbFi9utTC4sp3OVG+y4nyXU5k9V15Lqe+3n23JRbvIvfkk08yb948tm3bRr9+/fjqq68sShIlJSUxceJEtm/fjsFg4KmnnrK0CTbhVsvjAC5dulR039XVtczzFS5tAzHbqLTz3OocpZ3HycmpUttyPTk5Odcksgqn913/vC2Ji4sjvOQ/KVVB++GHMQQE4Hj//RgOHkQLDCR/5kzMo0bZRr+CFHqtl+dQRX2v4vrKd+V7peDuDq+8Ai++CPn5RcvkjL//juMTT2Bu2ZKrzz6L+YEHoODvl/L9DvD9NlC+K99l0tZTX/kup7bevsv6fdNb29Z+G7TrK06Xg6effprvv/++aFZPQEAA/fr1IyAgAF9fX1xdXalevTq5ublFS7eSk5P5888/SU5OBkSB7Mcff5zvv/++cntUCZw8eZJGjRphNpvp3r07iYmJpR73n//8h7fffhsQBcHvKWPq/6pVqxgwYEDR+958882i1/z9/Tly5Ah+fn6kpKSU2bbx48cza9YsQMw+KpyttHbtWvr27QvAW2+9xbvvvnvTc5jNZqpVqwbAgAEDWLFixU2PnTJlCu+8884Nz0+ePBlnS+tyKHC5fJlR0dE0PXoUgA09erDi3nvRCvxQKBQKWei+YQP9V6+mel4eANlOTuzs0IHNXbtyzk6XzysUCoVCoVBUJbKzs5k6dSomkwk3Nzer61k8gwngu+++w9PTk48//pj8/HySk5OLEke3QtM0HBwcePXVV3n//fdvR97q/Pbbb5gLijE/8sgjNz2uZIIlNze3zHOWzBxev/te4XludY6yzlNZbbmeN954g5dffrnocUZGBn5+fjz33HNF9bhszV9//cXdd99ddbX//W/y//1vHD79lJ6JiXR3dCTvt9/Ay8s2+rdBTk4On3/+OS+99FLRrDlbU+V9r4L6ynflu7V910wm8n/7DeM33+D8119027SJbps2kdmzJ46LF4MOv3fKd/V9l0lf+a58V77Lo62377J+3/TWPnv2LFOnTrWZ3m0lmADef/99HnvsMT777DPi4uKKdlMrC29vb0JCQpg0aRLNmjW7XWmrUzhDyMnJibFjx970uFq1ahXdv9VSs8J6TnDjErbC89zqHGWdp7Lacj1OTk6lBqCbPW8rqrS2kxN88gn06AETJmBMSMCpZ0+IjoZu3ayvXwGU7/qhd9/11pdRW299m/ju5QUvvwyTJsGKFTB9OsTHg9mMU8mrbFlZ4OJi3baUQPku53dO+S7nZ698l/Ozl1W7UF+vNthD32XTtrWuxUW+S+Lv78+MGTM4ceIEhw8fJj4+nm+++YaPPvqId999l48++ohvvvmGBQsWcPjwYU6ePMmMGTPsOrm0ZcsW9hUUYA4ODqZOnTo3PbZkMe3CHdxuRsli2iWLbJc8z+XLl7l48WK5zlOvXr1rflkqqy1VgV27dt0Z2qNGQVIStGgBJ09C377w3XelFry1in4V447xvQrq64nyXRKMRhg0COLi4PBhEkJDi1/7+2+46y547DHYts3qTdH7c9dbX0/U911OlO9yIqvvynM59fXuuy257RlM19OkSROaNGlSWafTjZLFvctaHgfQqlWrovu3WiJY8vWWLVvecJ6YmJii47p3717qOfLz8zl8+HCp53B1dcXPz48TJ05UqC0KG9OypUgyTZgA8+bBM8+IxzNmiB3oFAqFQjaaNMHUsGHx43nzICMDfv5Z3Hr0gOefh9Gjxe6cCoVCoVAoFAq7oEIzmO408vLymD17NiBmCA0ZMqTM45s0aYK3tzcAf/75Z5nHJiQkAODj40Pjxo2vea13795F98s6z5YtW4qWt/Xq1euG1wvPc+DAAU6fPn3T85TUKO089k5oySvbd4K2mxvExMDUqeIq/k8/Qe/ecPy4bfSrCHec71VIX0+U73JyTd+ffRbWr4f77wcHB0hMhAcfhIYN4e234cIF62nrgN76eqK+73KifJcTWX1Xnsupr3ffbYlKMJVg8eLFnD17FoAHHngAB4eyJ3gZDAZCQkIAMSto48aNpR63cePGollDISEhRbvvFRIUFIS7uzsAv/zyCzfb2O9///tf0f2RI0fe8HrJX9ySx5YkKyuLOXPmAGLmVPPmzUs9zp4pTNbdUdoGA/zzn7B0KdStC1u3QufOsHy5bfSrAHek71VEX0+U73JyTd8NBujZE/74A1JS4J13xJK5M2fg44/LXFZcYW0d0FtfT9T3XU6U73Iiq+/Kczn19e67LVEJphKUXB43fvz4cr1n0qRJRYmoiRMncuXKlWtev3LlChMnTgTAwcGBSZMm3XCO6tWr88ILLwCwf/9+PvnkkxuOSUxM5McffwSgX79+dO3a9YZjRo4cib+/PwAffvhh0XK6krz22mtcKLja+9prr5Wrj/bG+fPn71zte+8tTi6dOweDB4uZTQX/QOnZd725o323c309Ub7LyU37ftddYtbS8eMwZw689x54eBS//thjMHMmlNjMotK0bYTe+nqivu9yonyXE1l9V57Lqa93321JhRJM69ev56WXXmLEiBGEhoYyefJktpWzAOehQ4do2rRpUUJEby5cuEB8fDwAbdq0oVOnTuV6X/PmzXn11VcBsYStV69eREZGsmXLFiIjI+nVqxdbtmwBRELnZgXOX3vttaLZRK+//jpPP/00q1evZuPGjXz44YcMGjSI/Px8atSowRdffFHqORwdHfnyyy8xGo1kZGTQq1cvpk+fTlJSEkuXLmX06NF8/fXXgFhO9/DDD5f787En6tate2drN2oE69bB44+D2QxvvCEKgmdk6Np3vbnjfbdjfT1RvsvJLfvu6Ajh4fDKK8XPbd0qajQ9/TT4+Ijd6f76q/K1rYze+nqivu9yonyXE1l9V57Lqa93322Kdhvk5uZqDz74oGY0Gku9jR49WktLSyvzHHv27NEMBoNmNBpvpwmVzjfffKMBGqB99NFHFr336tWr2mOPPVb0/tJujz/+uHb16tUyz3Po0CGtWbNmNz2Hm5ubtmDBglu2Z+bMmVr16tVvep7AwEDt7NmzFvWxEJPJpAG39NeaXL58WR7tmTM1rXp1TQNNa9FCy9qyxbb6BWRnZ2tTpkzRsrOzddHXNMl8txN95bvyXS9uq+8XLmjaZ59pmr+/iJmgaQaDpg0dqmmLFmlaWX+Dr1zRtF9/1bSwMC2/Tx9NCwsTj69cue0+3C7Kd/m09dRXvivf9UJW3/XU1tt3Wb9vemunpaVpgGYymWyid1szmJ544gn++OMPNE0r9TZ37lzatWvHunXrbjvxZWtmzZoFQLVq1XjwwQcteq/RaOTHH39k4cKFhISE4O3tTfXq1fH29iYkJIRFixbxww8/YDSW/XHffffdbN++nWnTptGlSxdq166Ni4sLLVq04KWXXmLXrl0EBwffsj1PPvkkW7du5cknn6Rp06Y4OztTt25devfuzTfffMP69evx9PS0qI/2xPz58+XRfvJJWLsWfH3hwAEcevWCqCjbtsFOkMp3O9PXE+W7nNxW32vXhpdegoMHYdEiGDpUPF94v2CW8g3ExYG3N4wfD7GxVFu7FmJjxWNvb1iw4Ha7cVso3+XTtgd9PVG+y4msvivP5dTXu++2pOwq1qWwbt06Zs2ahcFgoFmzZnz66acEBQWRm5vLmjVrmDZtGklJSZw5c4ZBgwYxe/ZsRowYYY22Vyrr16+v8DmGDh3K0MIB7W1Ss2ZNXn/9dV5//fUKnadNmzbMnDmzQudQ2AmBgWLpx7hxOK5eDWPGwKuvwocfih2VFAqFQlGM0QhDhojbX3/BN9/AsmXFCScQSScfH1HLqeTOLmbztT8vXoSQEJFwqgJjGYVCoVAoFAo9sXgGU2GhaR8fHzZs2MCwYcOoWbMmderUYeTIkSQmJvLxxx/j4OBAdnY2o0eP5vfff6/0hivkpUOHDvJpe3nBsmWce+wx8fiTT2DQIEhL06c9OiCl73airyfKdzmptL7ffTd8+ins2lWckM/PF3WaOnQQ9e0KF9SVRuHzEyZAdnbltOkWKN/l07YHfT1RvsuJrL4rz+XU17vvtsTiBNOGDRswGAy88soreJTcuaWAwteWL19OnTp1yM/P55FHHuHbb7+tlAYrFLdaaninauPgQPrrr4udk2rWhNWrxW5zSUn6tcmGSOu7HejrifJdTiq97wZD8f2LF6FnT/Fcfv6t36tpcOECREdXbptugvJdPm170NcT5bucyOq78lxOfb37bkss7umpU6cA6NGjR5nH9evXj4SEBLy9vTGbzTz33HN88sknt9dKhaIE5d2p8E7TLtIPDxdJpebN4eRJ6NMHvv9e13bZAul9lxTlu5xYte+enhAZCYMHX5t4KgujEebNs16bSqB8l0/bHvT1RPkuJ7L6rjyXU1/vvtsSixNMeXl5gCiGfStat27N2rVradKkCZqm8c9//pN///vflrdSoVBcS6tWsHkzjBwJubnw1FPwxBM2W8KhUCgUVZ6srJsvjbsesxnOn7duexQKhUKhUCiqOBYnmLy8vABISUkp1/FNmjRh7dq1tGzZEk3TeO+993jllVcslVUoiijPTnp3ovYN+m5uEBMjin0bjfDjj2I20/Hj+jXQiijf5UT5Lic26XvduiJ2lpezZ8WsUSujfJdP2x709UT5Liey+q48l1Nf777bEosTTG3atAFg7dq15X6Pt7c3CQkJdOzYEU3T+OKLL5g0aZKl0goFAEk61hzSU7tUfYMBJk+GJUvEP0tbtoi6TCtW6NNAK6J8lxPlu5zYpO+hocW7xZWHvXuhYUMYMAD+9z+4dMkqzVK+y6dtD/p6onyXE1l9V57Lqa93322JxQmmPn36oGkaUVFRaOWdWg7UrVuX1atX07NnTzRNY9WqVZZKKxQApOm4c5qe2mXqDxwIW7eK5NK5c3DffTB1avmXf1QBlO9yonyXE5v0PTwc6tS5dR0mgwFcXKB3bxFTV62CRx8VhcKtgPJdPm170NcT5bucyOq78lxOfb37bkscLH3D4MGD+de//sWpU6eYO3cuo0aNKvd73dzcWL58OaGhoSxfvtxSaYWOzJgxgxkzZnD16lUAYmNjcXV1JSwsjJUrV2IymfDy8iIwMJD4+HgAOnXqhNlsZseOHQCEhISwbt06zp07h4eHB3379iU2NhaAdu3a4ejoyNatWwEYNmwYW7Zs4cyZM7i5uTFo0CCiC3bwycvL48iRI2zatAmA++67jz179pCamkrNmjUJDg4mMjISgBYtWuDp6cn69esBuPfeezl48CApKSk4OTkRFhZGZGQkZrMZf39/fHx8SEhIACAoKIiUlBSOHDmCg4MD4eHhpKenExERQaNGjfD39y9KlPbu3Zu0tDQOHjwIwP3338/8+fPJysrC19eXVq1asWzZMkAUyDeZTOzbtw+A8PBwlixZwqVLl2jQoAGdOnVi0aJFAHTt2pXs7Gx2794NQM2aNVmyZAkXLlzA09OTHj16sGDBAgA6duyI4ccfcZg0Cf81a+CNNzgTH0/Co49Sy8eHoKAg5hUUqW3bti3Ozs5s3rwZgKFDh7Jt2zZOnz5NrVq1GDx4MFFRUQC0atWKGjVqABAdHc3gwYPZt28fJ0+exMXFhZCQECIiIgBo3rw5Xl5erFu3DoB77rmHw4cPc/z4capXr86oUaOIiooiPz+fpk2b0rBhQ9asWQNA3759SU1N5fDhwxiNRsaOHcvcuXPJycmhYcOGVK9evUinV69epKenc+DAAQDGjh1LfHw8ly9fxsfHhzZt2rB06VIAunXrRmZmJnv37gVg9OjRLFu2jIyMDOrXr0+XLl1YuHAhAJ07dyYvL49du3YBEBoaSkJCAmlpaSxbtozevXszf/58QGw3ajQai4r2BQcHk5SURFpaGu7u7gwYMIC5c+cCYuani4tL0dWLIUOGsHPnTk6dOoWrqytDhw5lzpw5AAQEBODh4cGGDRsAGDhwIFlZWURERFCjRg1CQ0OZPXs2mqbRrFkzGjRoUDSjtH///hw7doyjR4/i6OjI6NGjiY6OJi8vjyZNmtC4cWNWr14NiIsFp0+f5tChQxgMBsaNG0dsbCxXrlzBz8+PgICAos8wJSWFzMxMkpOTARgzZgyLFi0iMzMTb29v2rdvz+LFiwEIDAwkKyuLPXv2AFQ4RqSlpREREWFRjGjdujWurq4VjhHp6ekAFsWImJgYcnNzKyVGFPbdkhgxcuRI1qxZc9MYAbB9+3YAhg8fTmJiIunp6dSpU6coRpgLZvUcOXKkyJtbxQh3d3cSExMBGDRoUIVjRFpaGps2bbIoRjRv3pwVBbM3yxsjvB97jL6ffQYGA4ZSEvJaQfIp4dlnOdW5M93eeYeasbHUiI7mePPm3H3lCgkJCVxMSyMwPp4GkyYRe/QoGAy3HSPS0tK4ePGiRTEiOTmZEydOVChG+Pn5ASLOG43GcsWIwrFcz549OX/+fIVjxKVLl7h06ZLVxxGlxYjLly8TERFh9XHEzWKE0Whk69atVh9HXB8jOnfuXOR74f1bxQiwfBxRVoxwd3e3yTiitBhRGGetPY44f/48devWvWEcoWlaUd+tOY64PkbExMQUee3r62u1cURZMeLChQtERERYfRxRWoxIS0sjIyPD6uOI0mJEtWrVijy39jji+hhhMpkAMJlMrFy5ErDOOAJKjxGZmZlERETYZBxRWoyoVq0aSUlJlTqOgPLFiMJYY2mMqIz/NWyNQbNkGlIB/fr149SpU7Rs2ZK4uDiLRfPy8hg3bhzz5s3DYDAUJS0U9k9GRgbu7u6kpaVRr149XdqQk5ODk5OTdNrl1tc0savc889DXh60aCF2P2rZskK6U6dOZfLkyVJ+9lXCdyvpKt+V73pg077HxcGECXDhgqjJZDYX/6xTB375BYYPv/Y9miY2WChsY2ys2HQBoE0bePhhePBB8PGxuDnKd/m09dRXvivfZfzsZdbW03dZv296a589exYvLy9MJhNubm5W17N4iRzAn3/+yaFDh24ruQTg6OhITEwMZrNZJZcUFlOYqZVNu9z6BoPYVW7tWvHPzYEDEBgoCoJXYZTvcqJ8lxOb9n3ECDh1CmbNgtBQzrRsKeozzZolnr8+uQQizpYcKHp7w+jR4rk9e+Cf/wQ/P7F8+ddf4fLlcjdH+S6ftj3o64nyXU5k9V15Lqe+3n23JbeVYFIoFFWAbt1g2zYICoLMTPHPz+uvQ36+3i1TKBQK+8LZGR56CGJiWPXWWyIh/9BD4vnyEBgIUVFw+jTMnCl29NQ0seHCI4/csbt7KhQKhUKhUJREJZgUVY7CnQxl074tfS8vWL4cXn1VPP74Y1EA/OzZym+clVG+y4nyXU6qrO+1a8OTT0JCAhw5Au++K4qJt2pVfMwLL8Arr8COHaVuxKB8l0/bHvT1RPkuJ7L6rjyXU1/vvtsSlWBSVDlcXFyk1L5tfQcHkViKjISaNcUOSJ07Q0HRvaqC8l1OlO9yckf43qQJvPUWFBTeBcBkEjXyPvsMOnaEdu3go48gNbXy9asgd4TvVVRfT5TvciKr78pzOfX17rstUQkmRZWjsDq+bNoV1h8zBjZtgubN4cQJseX2999XXuOsjPJdTpTvcnLH+u7iArNnw6hRUL36tfWa7r0X4uOV7xJq24O+nijf5URW35Xncurr3XdbohJMCoVMtG4NSUkQEiJ2QHrqKbGcIztb75YpFArFnY+jo4i/0dGiXtN334lkv6bBypWwf3/xsXl5oDZCUSgUCoVCUYVQCSZFlWPIkCFSaleavrs7zJ0L778vdkL64QdRkDYlpeLntiLKdzlRvsuJFL7XqVO842dhvaYHHijWnz1bzGx69VXYudM2bdIZKXy3U309Ub7Liay+K8/l1Ne777ZEJZgUVY6dOg609dSuVH2jEf7v/2DJEvDwgC1bRF2mlSsr5/xWQPkuJ8p3OZHO98J6TT4+xfqxsfD33/Dpp9Chg6jX9PHHcOqU7dtnI6Tz3Y709UT5Liey+q48l1Nf777bEpVgUlQ5Tuk4uNZT2yr6gwbB1q3QqROkp4vHH31UvLNRdjbMmoXDuHGM//lnHMaNg1mzdFlSp3yXE+W7nCjfgYgIkWQqrNe0eze8/rqY1TR4sFjmfIehfJcT5bucyOq78lxOfb37bktUgklR5XB1dZVS22r6jRvDunUwYQKYzaLgbHi42HXO2xvGj8cYF0eT48cxxsXB+PHi+QULKr8tZaB8lxPlu5wo3xFJpZL1mr79Fnr1EnE6O1u8Xsj27XdEvSblu5wo3+VEVt+V53Lq6913W2LQtMKpCgrFrcnIyMDd3Z20tDTq1aunSxuuXr1KtWrVpNO2ur6miYKzL7wgisuCqNFUWogwGMTP2FgYMcI67bkO5bvt9XNycpg6dSqTJ0/GycnJ5vqgfFe+y6VdLv0jR+DiRTHzFCAtTST969eHBx6Ahx8Wy+ksRPlu575bCeW78l35Lo+23r7L+n3TW/vs2bN4eXlhMplwc3Ozup6awaSocsyZM0dKbavrGwzwzDOwfHlxAulm+efC5ydMsNlyOeW7nCjf5UT5XgZNmxYnlwD27hWbN5w6BZ98Au3bi5pNn34qajjdCjtaCq18lxPlu5zI6rvyXE59vftuS1SCSaFQXEtKys0TSyXRNLhwQSzfUCgUCoU+9O8vEknz5kFYmFg6t3On2H3O1xfi4m7+3rg4u1oKrVAoFAqFomqjEkyKKkdAQICU2jbTj40Vu8yVB6NR/FNjA5TvcqJ8lxPlu4VUrw6hoRATI5JN33wDPXuCg4Oo21TIqlVilurVqyK5FBoqltsBBrP5mp9cvChqQJWVoKpklO9yonyXE1l9V57Lqa93322Jg94NUCgsxcPDQ0ptm+mfOyeKyJYHsxnOn7duewpQvsuJ8l1OlO8VOoFY7vzMM6I+U926xa+9+SYkJsJddxXH7rKWQhsMYin0qVPg7FyxdpWr6cp3GVG+y4msvivP5dTXu++2RM1gUlQ5NmzYIKW2zfTr1rVsBpONAqbyXU6U73KifK8kvLyK7+fni9pMdeqIWU45ObdeDm3jpdDKdzlRvsuJrL4rz+XU17vvtkQlmBQKxbWEhlo2g6l3b6s2R6FQKBSVgIMDfP21SC51717+99lwKbRCoVAoFIqqjVoipygXM2bMYMaMGVy9ehWA2NhYXF1dCQsLY+XKlZhMJry8vAgMDCQ+Ph6ATp06YTab2bFjBwAhISGsW7eOc+fO4eHhQd++fYmNjQWgXbt2ODo6snXrVgCGDRvGli1bOHPmDG5ubgwaNIjogiuoDRs25MiRI2zatAmA++67jz179pCamkrNmjUJDg4mMjISgBYtWuDp6cn69esBuPfeezl48CApKSk4OTkRFhZGZGQkZrMZf39/fHx8SEhIACAoKIiUlBSOHDmCg4MD4eHhaJpGREQEjRo1wt/fn1WrVgHQu3dv0tLSOHjwIAD3338/8+fPJysrC19fX1q1asWyZcsA6NGjByaTiX379gEQHh7OkiVLuHTpEg0aNKBTp04sWrQIgK5du5Kdnc3u3bsB6Nu3L0uWLOHChQt4enrSo0cPFhQUYe3YsSMA27dvB2D48OEkJiaSnp5OnTp1CAoKYl7BPwlt27bF2dmZzZs3AzB06FC2bdvG6dOnca9ZkyG1a8PFixjK+J3QQLz+xhvs2rCB/cHB3N2mDV5eXqxbtw6Ae+65h8OHD3P8+HGqV6/OqFGjiIqKIj8/n6ZNm9KwYUPWrFlT1LfU1FQOHz6M0Whk7NixzJ07l5ycHBo2bEjnzp2JiIgAoFevXqSnp3PgwAEAxo4dS3x8PJcvX8bHx4c2bdqwdOlSALp160ZmZiZ79+4FYPTo0SxbtoyMjAzq169Ply5dWLhwIQCdO3cmLy+PXbt2ARAaGkpCQgK5ubksW7aM3r17M3/+fAA6dOiA0Whk27ZtAAQHB5OUlERaWhru7u4MGDCAuXPnAtCmTRtcXFxISkoCYMiQIezcuZNTp07h6urK0KFDi3aXCAgIwMPDo+hKx8CBA6lbty4RERHUqFGD0NBQZs+ejaZpNGvWjAYNGrB27VoA+vfvz7Fjxzh69CiOjo6MHj2a6Oho8vLyaNKkCY0bN2b16tUA9OnTh9OnT3Po0CEMBgPjxo0jNjaWK1eu4OfnR0BAQNFnmJKSQmZmJsnJyQCMGTOGRYsWkZmZibe3N+3bt2fx4sUABAYGkpWVxZ49ewAqHCNyc3OJiIiwKEa0bt0aV1fXCseIQiyJETExMeTm5lZKjCjsuyUxYuTIkaxZs6ZCMcJckGA+cuRIkTclY0StWrUYPHgwUVFRALRq1Qp3d3cSExMBGDRoEPv27ePkyZO4uLgQEhJS9N1t3rx5uWJEbm4umzZtsihGNG/enBUrVgAVixFBQUEsXLjQohhx/vx56tatWykxIjc3l4sXL1oUI5KTkzlx4kS5Y0QTk4n6lBOzmTPJydSHG2LE8uXLAejZsyfnz5+vcIxwdXXl0qVLVh9HlBYj6tSpQ0REhNXHETeLEW3atGHr1q1WH0dcHyM6d+4MQHR0dNH9io4jLI0RAwcOtDhG3M44orQYURhnrT2OuFmMuPvuu4v6bs1xxPUxIiYmpshrX19fq40jyooRDg4OREREWH0cUVqMyM3NJSMjw+rjiNJiRLt27Yo8t/Y44voYYTKZADCZTKxcuRKwzjgCSo8Rbm5uRERE2GQcUVqMaNeuHUlJSVYfR5QWIwpjjS3GEXBtjLA5mkJhASaTSQO0tLQ03dqwdu1aKbVtqh8Xp2kGg7iJRRLX3gpfa9Om+Dl/f02Lj7dak5Tvtic7O1ubMmWKlp2drYu+pinf9UD5LoHvYWGaZjSWHt9Lu7m7a9qUKZq2a5emmc1Wa5by3fao77vyXS9k9V1Pbb19l/X7prd2WlqaBmgmk8kmemqJnKLKceLECSm1bao/fLjYTa52bQC0gppMhT+pXRvmz4dduyAiQmxnffgwBAeL9x45UulNUr7LifJdTpTvVsaSpdAAJhNMmQLt2kGzZlBwVbyyUb7LifJdTmT1XXkup77efbclKsGkqHLUqFFDSm2b648YIXYOmjUL84gRHG3cGPOIETBrlnh++HCxw9C4cXDgALz+uqjxER8PrVrBv/8NV65UWnOU73KifJcT5buVCQ8Xxb4NZS2ERrzu7g4zZ4q/Cc7OIv43blx8THw8LF8OeXkVbpbyXU6U73Iiq+/Kczn19e67LTFo2q22EFEoisnIyMDd3Z20tDTq1aund3MUNiInJ4epU6cyefJknJycbn5gcjJMnAgF65dp3Bg+/xxCQm79j4zC7ii374o7CuW7JCxYIGIzlL6bXGHMnj9fXFAAyMwUM1d79iw+rk0b2LtXJKyCgyEsDAYNAhcX67ZfUSmo77ucKN/lRPkuJ2fPnsXLywuTyYSbm5vV9dQMJkWVY/bs2VJq24P+LQkIgGXLxJbWfn5w7BiMHAlDh8KhQxU6tfJdTpTvcqJ8twHlXQpdmFwCcHW9NrmUmysee3nBhQtihuvIkeDpKRJNBcVHy4vyXU6U73Iiq+/Kczn19e67LVEJJkWVQ89Jd3pP+NNbv1wYDDBqFOzfD//3f1C9OixZIq5y/+tfcPnybZ1W+S4nync5Ub7biPIshS6L6tXF8rlTpyAhAV56CRo1Esuj582DuLjiYzUNTp8u83TKdzlRvsuJrL4rz+XU17vvtkQlmBRVjmbNmkmpbQ/6FlGzJrz/PuzZA4MHiyvdH3wALVuKGU4WBlrlu5wo3+VE+W5DnJ3hoYfInz2bXydMIH/2bHjoIfF8ealWDfr0gc8+g6NHYds2eOstmDCh+Jjt28WGEL16waeflroZhPJdTpTvciKr78pzOfX17rstUQkmRZWjQYMGUmrbg/5t0awZLFoklmI0bgwnTogCs4MGiVlO5UT5LifKdzlRvldhDAbo2BHefReCgoqf37hRXFjYsAFefRX8/aF9e3jnHVHXSdOU75KifJcTWX1Xnsupr3ffbYlKMCmqHGvXrpVS2x70bxuDQRST3bcP3n4bnJxEIfB27cTuc5cu3fIUync5Ub7LifL9DuQf/xAXGKZPh3vuEbOedu2CKVNEomntWuW7pCjf5URW35Xncurr3XdbohJMCoXCdtSoIa5W790ranvk58PHH4vi4BERFi+bUygUCkUVwtcXnnsOVq6EM2fg559FHSgfn2uLh7/3nkhILV8OeXn6tVehUCgUCoVFqASTosrRv39/KbXtQb/S8PcXxV/j46FpU1Eg9oEHxFXtPXtKfYvyXU6U73KifJeAunVFjab588WOow4Oou+aBt9/D998I5ZSe3nB+PGiaHhWltWao/fnrre+nqjvu5zI6rvyXE59vftuS1SCSVHlOHbsmJTa9qBf6QwbJmYzvfuuKCi7Zg106AAvvwwm0zWHKt/lRPkuJ8p3yXBwAAr6rmnw3Xfw5JMiuXTxotjVLiwMPD3FDCgroPfnrre+nqjvu5zI6rvyXE59vftuS1SCSVHlOHr0qJTa9qBvFZydxW5D+/fDyJFw9Sp8/jm0aCH+qShYNqd8lxPlu5wo3+Xk6NGjYDSKnUdnzhSzWxMS4KWXxCYRV66I1wvJzxfH/f135WjriN76eqK+73Iiq+/Kczn19e67LVEJJkWVw9HRUUpte9C3Ko0bw9y5sGSJ2HnuzBmxLKJvX9i5U/kuKcp3OVG+y8kNfa9WDfr0gc8+gyNHYNs2ePHF4tfXrYOnny6u4fTJJ3D4cPkFs7PFhYxRoxjw3nswapR4nJ1dOR2yAOW7fNr2oK8nsvquPJdTX+++2xKDpqmquoryk5GRgbu7O2lpadSrV0/v5ihsRE5ODlOnTmXy5Mk4OTnZQlDMYvrPf0TNDaNRLIt4912oXdv6+gpAB98VdoHyXU6qpO8rV8K//gWbNl37fLt2YkbsE0+IwuKlERcnakBduCD+xpjNxT/r1IFffhGbUdzhVEnfFRVG+S4nync5OXv2LF5eXphMJtzc3Kyup2YwKaoc0dHRUmrbg77NcHKCyZMhORnGjBED/q++gubNxa5DZrNNm6P35663vp6o77ucKN/lxOK+DxgAGzfCyZMwfbp4XK0a7NoldiwtuXTOZCr+2xEXB6Ghor4TFD9f+PPiRQgJEcfZCOW7fNr2oK8nsvquPJdTX+++2xKVYFJUOfJ03LJYT2170Lc5fn4QGQkrVmDy8YGzZ+Gxx6BXL7FUwkbo/bnrra8n6vsuJ8p3Obntvvv4iFmuK1aI5dX/+5+YndSlS/ExL70kjnviCXjwQfHczSbxFz4/YYLNlssp3+XTtgd9PZHVd+W5nPp6992WqASTosrRpEkTKbXtQV83BgwgOSICPv4YXF3FFesuXeDZZ+H8eavL6/25662vJ+r7LifKdzmplL7XrQuPPCJmuxoM4jlNE8XCT5+GH3+EzMybJ5cK0TSxfM5GV52V7/Jp24O+nsjqu/JcTn29+25LHPRugKJqMGPGDGbMmMHVq1cBiI2NxdXVlbCwMFauXInJZMLLy4vAwEDi4+MB6NSpE2azmR07dgAQEhLCunXrOHfuHB4eHvTt25fY2FgA2rVrh6OjI1u3bgVg2LBhbNmyhTNnzuDm5sagQYOKphb6+Phw5MgRNhXUXLjvvvvYs2cPqamp1KxZk+DgYCIjIwFo0aIFnp6erF+/HoB7772XgwcPkpKSgpOTE2FhYURGRmI2m/H398fHx4eEhAQAgoKCSElJ4ciRIzg4OBAeHs7hw4c5evQojRo1wt/fn1WrVgHQu3dv0tLSOHjwIAD3338/8+fPJysrC19fX1q1asWyZcsA6NGjByaTiX379gEQHh7OkiVLuHTpEg0aNKBTp04sWrQIgK5du5Kdnc3u3bsB6NmzJ0uWLOHChQt4enrSo0cPFixYAEDHjh0B2L59OwDDhw8nMTGR9PR06tSpQ1BQEPPmzQOgbdu2ODs7s3nzZgCGDh3Ktm3bOH36NLVq1WLw4MFERUUB0KpVK2rUqAGI6Z2DBw9m3759nDx5EhcXF0JCQoiIiACgefPmeHl5sW7dOgDuueceDh8+zPHjx6levTqjRo0iKiqK/Px8mjZtSsOGDVmzZg0Affv2JTU1lcOHD2M0Ghk7dixz584lJyeHhg0b4uHpSYSPDzWmTWPgsmXUnD8fvv2WnN9+w/GTT4ivX5/LV67g4+NDmzZtWLp0KQDdunUjMzOTvXv3AjB69GiWLVtGRkYG9evXp0uXLixcuBCAzp07k5eXx65duwAIDQ0lISGBv//+m4yMDHr37s38+fMB6NChA0ajkW0FM6mCg4NJSkoiLS0Nd3d3BgwYwNy5cwFo06YNLi4uJCUlATBkyBB27tzJqVOncHV1ZejQocyZMweAgIAAPDw82LBhAwADBw7k4sWLREREUKNGDUJDQ5k9ezaaptGsWTMaNGjA2rVrAejfvz/Hjh3j6NGjODo6Mnr0aKKjo8nLy6NJkyY0btyY1atXA9CnTx9Onz7NoUOHMBgMjBs3jtjYWK5cuYKfnx8BAQFFn2FKSgqZmZkkJycDMGbMGBYtWkRmZibe3t60b9+exYsXAxAYGEhWVhZ79uwBqHCMSE5O5ujRoxbFiNatW+Pq6lrhGGE2m+nevbtFMSImJobc3NxKiRGFfbckRowcOZI1a9ZUKEaYC5YJHTlypMibW8UId3d3EhMTARg0aFCFY8Tly5cxGAwWxYjmzZuzYsUKAHr16kV6ejoHDhwAYOzYscTHx3P58uVbxojevXuzcOFCi2LE+fPnqVu3bqXEiJycHAICAiyKEcnJyZw4caJCMcLPzw8Qcd5oNJYrRixfvhwQf5vOnz9f4Rjh4uLCpUuXrDOO2LmTdf/5D11/+omaZ89SkHoqE7PBgOnnn7nUt2+ljSNuFiNatmzJ1q1brT6OuD5GdO7cucj3wvvWGEeUFSO6detmk3FEaTGiMM5aEiNuZxxxsxgBFPXdmuOI62NETExMkde+vr5WG0eUFSNSUlI4evSo1ccRpcWInJwcWrVqZfVxRGkxwsXFpchza48jro8RJpMJAJPJxMqVKwHrjCOg9Bhx9uxZIiIibDKOKC1GtG7dmqSkJKuPI0qLEYWxxhbjCLg2RtgcTaGwAJPJpAFaWlqabm34448/pNTWUz87O1ubMmWKlp2drYu+ppXS9zVrNK1NG00T15k1rWtXTdu0yTbaNkb5Lp+2nvrKd+W7Xtik7/36Ff/dKM+tTx/rt0lTvsuorae+8l1Obb19l/X7prd2WlqaBmgmk8kmemqJnEKhqJr06yfqMH3xBbi5webN0L07PPkkpKfr3TqFQqFQ2CN164rd4srL+vUwZAj8979w4MCtl9YpFAqFQiExKsGkqHL06dNHSm170NeTUvvu6AgvvigG/ePHi4H/Dz+I3ea++QYKlnRaRduG6K2vJ+r7LifKdzmxSd9DQy3bidRshiVLYNIkCAiA776zSrOU7/Jp24O+nsjqu/JcTn29+25LVIJJUeU4ffq0lNr2oK8nZfa9QQP45RdYtw7atxeFWf/xD+jaFQrWc1tN2wbora8n6vsuJ8p3ObFJ38PDoU6d4gLgN8NgEMdt2waffgoDB0L16mL2bCGzZkH//jBtGuzcWaHZTcp3+bTtQV9PZPVdeS6nvt59tyUqwaSochw6dEhKbXvQ15Ny9b1XL9iyBaZPh9q1Yft26NlTbDV95ox1ta2I3vp6or7vcqJ8lxOb9N3ZWVyQgJsnmQqf/+UX6NgRXn4Zli0Tu5YGBBQfFx8Pa9bA5MnQoQN4e4u/N7Nnw7lzFjVL+S6ftj3o64msvivP5dTXu++2RCWYFFUOw62uOt6h2vagryfl7ruDAzz3nFg299hj4rlffoEWLeDLLyE/33raVkJvfT1R33c5Ub7Lic36Pnw4xMaKCxFQXJOp8Gft2jB/vjiuJDVrXpuU+vBDmDFDHFezJpw+Lf7e3H+/mFlbsGNTeVC+y6dtD/p6IqvvynM59fXuuy0xaJqqVqgoPxkZGbi7u5OWlka9evX0bo7CRuTk5DB16lQmT56Mk5OT3s2xjI0bRcKpYItP2rYVM5z69tW3XVWAKu274rZRvsuJlL5nZ0N0NMybJ2YneXjAyJEwerSY6WQJOTmiIPiSJeJWowYUbHEOQFiYWGI3eDDcdx/cdVfl9uU2kdJ3hfJdUpTvcnL27Fm8vLwwmUy4ublZXU/NYFJUOWJjY6XUtgd9PbntvnfvDklJ8O234p+H3btFDY2HHoK//7audiWht76eqO+7nCjf5cTmfXd2Fn8LYmKIffFFiIkRjy1NLgE4OcE998BHH8GuXWLpXCEmEyxYAJGR8OijYildhw5iad2aNZCbq3yXUNse9PVEVt+V53Lq6913W6ISTIoqx5UrV6TUtgd9PalQ36tVg6efhoMH4amnxBKH338Xy+Y++wzy8qynXQnora8n6vsuJ8p3ObmjfK9Ro/i+qyv8+Se89ZbYfMJgEEXBp00TRcIffFD5LqG2Pejriay+K8/l1Ne777ZEJZgUVQ4/Pz8pte1BX08qpe9164otppOSIDAQLl2CV14RV5JXr7722OxssUPQqFEM+egjGDVKPM7Orng7LET5Lp+2PejrifJdTu5Y36tVExtOvPuu+Ptz5oy4yPHww+DlBffcU6x/9KgoJD5pklhqJ8E/JXes71VAX09k9V15Lqe+3n23JQ56N0ChsJSAkju4SKRtD/p6Uql979IFEhPh55/FEoV9+8TShrFj4ZNPRL2mCRPgwgUwGqltNoslD3PnwosviiKu1xd/tSLKd/m07UFfT5TvciKN7/XqwQMPiJvZDPn5BGRkiNeWLhWbVBw4AP/9r1iu16+fqN00eLCYeXuHFYuVxnc71NcTWX1Xnsupr3ffbYmawaSocixfvlxKbXvQ15NK77vRCI8/Lgbxzz0nHkdGwt13Q2goXLwojjObr/158SKEhEBcXOW2pwyU7/Jp24O+nijf5URK341GqF69WP/++8XFjKeeAj8/MWt26VJ46SVo2RLi4/VppxWR0nc70dcTWX1Xnsupr3ffbYlKMCkUCrnx8BC7ym3ZIgqC5+SApolbaRQ+P2GCLsvlFAqFQnEH4+4udrL77js4flzMsP3sMxg0SNRyKrkD6nvviccffCBm3hZeCCkPBcvAHcaNY/zPP+Mwbpxuy8AVCoVCceegEkyKKkfPnj2l1LYHfT2xet87doRnny3fsZomls9FR1u3TQUo3+XTtgd9PVG+y4ny/ToMBjFr6aWXxCymc+dEAqqQ+HhYuxb+9S/o3BnuugvGj4c//oCzZ28uFhcndrIbPx5jXBxNjh/HGBcn3uvtLXa8syHKdzmR1XfluZz6evfdlqgEk6LKcf78eSm17UFfT2zS9/nzxXKF8mA0wrx51m1PAcp3+bTtQV9PlO9yony/BdWrX/v4jz/g669hxAioWRPS0sQspAcfFIXCS85oKpx9Gxd3zTJwQ8ExBh2XgSvf5URW35Xncurr3XdbohJMiipHcnKylNr2oK8nNun7uXPlX2JgNoON/lgo3+XTtgd9PVG+y4ny3UKaNhUzb+fPF3+PVq2C11+Hdu1gwIDiCyaaBp06id1Q77+/+LnS0GEZuPJdTmT1XXkup77efbclahc5hUKhKKRuXTEgL2+S6Q7byUehUCgUVZTq1aF/f3GbNg3y8opfO3AAduwQt/JQchn4Qw9Zo7UKhUKhuENRM5gUVY4xY8ZIqW0P+npik76HhlpWJHX1ahg4UFw1vtnV4EpA+S6ftj3o64nyXU6U75WIo2Px/bvvhg0bxLK58mLDZeDKdzmR1XfluZz6evfdlqgZTIpyMWPGDGbMmMHVq1cBiI2NxdXVlbCwMFauXInJZMLLy4vAwEDiC7bQ7dSpE2azmR0FV8xCQkJYt24d586dw8PDg759+xIbGwtAu3btcHR0ZOvWrQAMGzaMLVu2cObMGdzc3Bg0aBDRBQWVc3Jy6Nu3L5s2bQLgvvvuY8+ePaSmplKzZk2Cg4OJjIwEoEWLFnh6erJ+/XoA7r33Xg4ePEhKSgpOTk6EhYURGRmJ2WzG398fHx8fEhISAAgKCiIlJYUjR47g4OBAeHg4M2bMoF69ejRq1Ah/f39WrVoFQO/evUlLS+PgwYMA3H///cyfP5+srCx8fX1p1aoVy5YtA6BHjx6YTCb27dsHQHh4OEuWLOHSpUs0aNCATp06sWjRIgC6du1KdnY2u3fvBqBGjRo4Oztz4cIFPD096dGjBwsKinF27NgRgO3btwMwfPhwEhMTSU9Pp06dOgQFBTGvYLDYtm1bnJ2d2bx5MwBDhw5l27ZtnD59mlq1ajF48GCioqIAaNWqFTVq1AAgOjqawYMHs2/fPk6ePImLiwshISFEREQA0Lx5c7y8vFi3bh0A99xzD4cPH+b48eNUr16dUaNGERUVRX5+Pk2bNqVhw4asWbMGgL59+5Kamsrhw4cxGo2MHTuWuXPnkpOTQ8OGDUlNTS36/evVqxfp6ekcOHAAgLFjxxIfH8/ly5fx8fGhTZs2LF26FIBu3bqRmZnJ3r17ARg9ejTLli0jIyOD+vXr06VLFxYuXAhAlw4daOrmhjEjg7LmJmmA5uiI4epVDCtWwIoVXO3cmT0jRrDP3x/3OnUYMGAAc+fOBaBNmza4uLiQlJQEwJAhQ9i5cyenTp3C1dWVoUOHMmfOHAACAgLw8PBgw4YNAAwcOJB58+bh6upKjRo1CA0NZfbs2WiaRrNmzWjQoAFr164FoH///hw7doyjR4/i6OjI6NGjiY6OJi8vjyZNmtC4cWNWr14NQJ8+fTh9+jSHDh3CYDAwbtw4YmNjuXLlCn5+fgQEBBR9hikpKWRmZhZN7x0zZgyLFi0iMzMTb29v2rdvz+LFiwEIDAwkKyuLPXv2AFQ4Rnz33XfUr1/fohjRunVrXF1dKxwjzp49ywsvvGBRjIiJiSE3N7dSYsTq1aupX7++RTFi5MiRrFmzpkIxwlyQZD1y5EiRN7eKEe7u7iQmJgIwaNCgCseI1NRUevToYVGMaN68OStWrAAqFiNcXFxwcHAoNUZ07tyZvLw8du3aBUBoaCgJCQmcP3+eunXr0rt3b+bPnw9Ahw4dMBqNbNu2DYDg4GCSkpJIS0vD3d39pjHizJkzTJgwwaIYkZyczIkTJyoUI/z8/AAR541GY7liROG2yz179uT8+fMVjhEmk4kHH3zQ6uOI0mJEdHQ0tWrVsvo44mYxovD7YbVxxLFj3GMwUJ9yYjZj3rqVLV98wdG6dXGvV69C44iyYoTRaCQzM7PoM7DWOKK0GJGQkED9+vUrbRxhaYzYsmULDg7i37HyxgiwfBxxfYyIiYkBxN8DX19fq40jyooR3377LR4eHlYfR5QWI86cOcNjjz1m9XFEaTHiyJEjaAUXJa09jrg+RphMJgBMJhMrV64ErDOOgNJjxOzZs3Fzc7PJOKK0GGEwGGjatKnVxxGlxYiffvqJ+vXr22QcAdfGCJujKRQWYDKZNEBLS0vTrQ1//PGHlNp66mdnZ2tTpkzRsrOzddHXNBv2PS5O0wwGcRPzkq69Fb4WF6dpR49q2nPPaZqzc/HrrVpp2q+/alpubqU1Sfkun7ae+sp35bteKN+tTFiYphmNpf9tK+vm4qJpgwZp2gcfaNrJk5XeLOW77VHfdzm19fZd1u+b3tppaWkaoJlMJpvoqSVyiiqHt7e3lNr2oK8nNuv78OEQGwu1a4vHhUVSC3/Wri0Kqg4fDo0bw/TpcOwYvPEGuLnBvn1iq+dmzWDGDLhypcJNUr7Lp20P+nqifJcT5buVsXQZeNeuojZhVhYsWwb/93+Qnl78+q5dsHHjtfWebgPlu5zI6rvyXE59vftuS1SCSVHlaN++vZTa9qCvJzbt+4gRcOqU2O45NJS83r3FwHzWLPH88OHXHl+/PnzwAaSkwIcfgpcXHD8Ozz8vklAffggF05JvB+W7fNr2oK8nync5Ub5bmfBwqFPn1htUGAziuIQESEsTiaQvv4QHH4S2bYuP+/RT6NFDHDt4MEydelsJJ+W7nMjqu/JcTn29+25LVIJJUeUoXKMtm7Y96OuJzfvu7Cx2z4mJIfof/4CYGPHY2fnm73F3h8mTxYymGTNEciktTVz1bdhQzHI6c8bipijf5dO2B309Ub7LifLdyjg7wy+/iPs3SzIVPv/LL+J4o1EklSZOhN9+K57NC1CrFnh4wOXLsHSp+BvXo4d4buhQyM8vV7OU73Iiq+/Kczn19e67LVEJJoVCoahsatSAf/wDDh4Us55at4aMDHF1t3FjeO45kYRSKBQKhcKWXLcMXCtIGGmlLQO/FdOnw9mzsHMn/Pe/MHKkSC5lZkJqKjiU2Eto8mSYNg02bSp34kmhUCgUVQ+1i5yiyhEYGCiltj3o60mV9N3RUcx6euABiI8Xy+g2bYKvv4bvvhPP//OfIgFlDf07gCrp+x2iryfKdzlRvtuIwmXg0dGYY2JI2bGDhh06UG3UKBg9uuyZutdjNEK7duL2wguixtOePXDhQvEx2dnwxReQkyMeu7pCnz4QFARBQQR26lSZvbMIqXy3M2T9vivP5dTXu++2RM1gUlQ5srKypNS2B309qdK+G41iQJ+YCKtWwcCBcPWqmN3Upo2o71SwFa5V9KswVdr3Kq6vJ8p3OVG+25CCZeD5s2fz64QJ5M+efetl4OWhMOHUr1/xc/n5YgZvSIiYIZWZCYsXiwss3brh+fzz157j6tWKtcECpPPdjpD1+648l1Nf777bEpVgUlQ59uzZI6W2PejryR3hu8EA/fuL3Xi2bIFRo8Rz8+dD9+5wzz2wfLnYGNoa+lWQO8L3KqqvJ8p3OVG+36G4usKkSWJpXno6bN8On30mLrzUrs2R+vWLjz1+XCyzCw6GTz4RfyutmHDS+3PXW19PZP2+K8/l1Ne777ZEJZhKkJ6ezkcffUSvXr1o0KABTk5OeHt7061bN1577TUSExNveY4lS5YQFhaGr68vTk5O+Pr6EhYWxpIlS8rdjqysLD7++GMCAwPx8PDA1dWVli1b8uqrr5KSklLu8+zdu5dnnnmGu+++mxo1alCvXj369u3Ld999R75a/65Q6EvnzhAdDfv2waOPiloVq1fDoEFia+iYGMu2k1YoFAqFwt6pVg06dICXXhIXV9LTOTRwYPHrCQmiZuHChfDaa+LvoYeHqAn16adw9KhuTVcoFApFOdAUmqZp2pw5c7S6detqwE1vISEhN32/2WzWnnrqqTLf/9RTT2lms7nMdvz1119aixYtbnoOd3d3beHChbfszw8//KA5OTnd9Dzdu3fX0tPTLf2YNJPJpAFaWlqaxe+tLLKzs6XU1lM/OztbmzJlirSfvU20U1I07cUXNa1GDU0Tc5g0rUULTfvpJy07I8P6+qWgfFffd72QVVtPfeW78l0vrtHOz9e0bds07dNPNW34cE1zdy/+mwiaNmdO8bEpKZq2ZYt4jyVcuaJpv/6qaWFh2tW+fTUtLEw8vnKlUvpjCcp3pW1rbT19lzXO6q2dlpamAZrJZLKJnprBBPz666+MGzeOc+fO4eXlxb///W+WL1/O1q1bWbhwIV9++SUDBw7E0dHxpud48803mTlzJgAdO3YkIiKCpKQkIiIi6NixIwAzZ87krbfeuuk5MjMzCQ4O5sCBAwA8+eSTrFy5kg0bNvD+++/j6uqKyWQiPDycXbt23fQ8S5cu5amnniInJ4f69evz5ZdfsmnTJhYvXkxYWBgAGzduJCwsDHMVnCGxcuVKKbXtQV9P7njf/fxEEdSUFHjrLVGn4sABeOwxzP7+Yoeey5et3w4744733Y719UT5LifKdzm5pu/VqkHHjvDyyxAXB+fOwdatYvZScPC1tZ1++QW6dIG6dcVyu88+g23byl5SFxcH3t4wfjzExmJMSBBL98aPF88vWGC1fpaG8l1py4TefVe+2wbpd5Hbv38/Tz31FGazmT59+rBgwQLc3d1vOG7ixInk5uaWeo6//vqLjz76CIAuXbqQkJBAjRo1AOjatSsjRoygX79+bNmyhWnTpvHoo4/i7+9/w3k++eQTkpOTAfjoo4947bXXil7r0aMH/fv3p2/fvmRlZTFp0iRWrVp1wzny8/N5/vnnMZvNuLm5sX79+mu0Bg8ezHPPPcfXX39NQkICv/32G+PHj7fgE9Mfk8kkpbY96OuJNL57esK774qlAd99B599Ro2//xb1K957D158EZ57DurUsV2bdEQa3+1QX0+U73KifJeTMvterRp06iRuL7987Ws5OeDmBiaTSAwVJodq14a+feH778HLq/j4uDixqUYhhRdZC39evCgKkcfGioSVDVC+K22Z0LvvynfbIP0MpokTJ5KTk4Onpydz584tNblUSPXq1Ut9/vPPPy+qafTVV18VJZcKcXFx4auvvgJEAuiLL7644Rx5eXn897//BaBly5a88sorNxzTo0cPHn/8cQBWr17N1q1bbzhm3rx5/PXXXwC88cYbpSayPv74Y+oU/HP68ccfl9one8ar5GBBIm170NcT6XyvVQtefRWOHCF50iRo2lQUR33rLWjYEF5/Hf7+2/btsjHS+W5H+nqifJcT5buc3Hbf//MfOH9eFAL/5BMYNkwknC5eFDu2engUH/vf/8K4ceL+dRtpFFH4/IQJkJ19e22yEOW70pYJvfuufLcNUieYkpOTi6arPf/883h6elp8Dk3TmD9/PgABAQF079691OO6d+9OixYtAIiNjUW77o/bmjVruHjxIgCPPPIIRmPp1kyYMKHo/ty5c294PTY2ttRjS+Li4sKYMWMAUdH+0KFDpR5nrwQGBkqpbQ/6eiKt787O+Lz7rlgu98cfYvvnzEz4+GNo3BieeQYOH9avfVZGWt/tQF9PlO9yonyXkwr1vVo1sWnGK69AfLxYUrd5M/z0k9g8o5APPoArV26eXCpE0+DCBbEJhw1QvittmdC778p32yB1gikqKqrofnh4eNH9CxcucOjQIc6dO3fLcxw9epTU1FQA+pVcF14Kha+fPHmSY8eOXfPa2rVrbziuNLp06ULNmjUBWLdu3Q2vF56nRYsWNGjQ4JZtudl57Jn4+Hgpte1BX0+k993BAe6/H3bsEIPoXr0gN1cso2veHB54AMqozVZVkd53SVG+y4nyXU4qte8ODqIuU4lxPWbztUvlboXRCPPmVV6bykD5rrRlQu++K99tg9QJpo0bNwLg7u5Oy5Yt+f3332nfvj0eHh40b94cT09PmjZtyjvvvENmZmap59i/f3/R/YCAgDL1Sr5e8n2WnMfBwaFo2dv158jMzOTkyZMVbotCobBjDAaxDGDdOrGd85AhYvAcEQHt24siqOvX691KhUKhUCjsA6NRFAIvL2YzLF4Mjz0GP/wA+/YV12lSKBQKRZlInWDat28fAI0bN2bixIk89NBDN+zOdvToUaZMmUKPHj04derUDec4ceJE0X1fX98y9fz8/Ep9X8nHNWvWpHbt2uU6z9mzZ8nJySl6/uTJk0VL7yrSFnunU6dOUmrbg76eKN9LoU8fWLQItm+HsWPFIHrhQujdWxQ4Xbz41ssB7Bzlu5wo3+VE+S4nNul73brib2R5uXIFfv4ZnnwSWrcW7x8yBObMqdRmKd+Vtkzo3Xflu22Qehe58+fPA6IW086dO6lduzZTp04lLCwMNzc3du/ezdtvv83ixYvZs2cP4eHhrF279pr6SJcuXSq67+rqWqZe4dI24IYZUYXnudU5SjuPk5NTpbalJDk5OdcksTIyMkp93pbIqq2nfqGmjH3XW7tc+i1bwi+/YHjrLap99hnG337DsHYtrF2LuX17rr76KuawMFGrwkLdkj/1QPmuvu8yaeupr3xXvuuFLfpuHDYMx1Jql96M/BdfhOrVMW7ahGHLFgwXL8KSJeT36sXVwraePInDtGmYu3fH3L272IzDYLCoXcp3+b7vemuX/KmHvvqd00fblkidYLp8+TIgPvRq1aqxePHia4p0d+nShfj4eIKDg1m8eDEbNmxg7ty5jB49uuiY7BK7TNxsl7lCChNBAFeuXLnmtcLz3OocZZ2nstpSkg8//JB33nnnhudnzJiBs7PzLduquLP4/PPP9W6C4lY0bEit55+ne2IiXbZsofrOnRgffphzL77I+l692NW+PVcdLAv9ync5Ub7LifJdTu5036vl5fGKszPO2dmUlQLSgGxnZz51deWqoyPccw+Gfv2of+YMfidOcOzvvzk7dSoArXfvZnRMDNW+/x6Ayy4unPDz46SfHyf8/Djl7U2+o6P1O1cB7nTfFaWjfJeLbBvtilmI1AkmZ2fnoiRTeHh4qTvAGY1GPv74YxYvXgxARETENQmmkkmW3NzcMvVKZg9r1KhxQ1vKc46yzlNZbSnJG2+8wcsvv1z0OCMjAz8/P5577jnq1at3y7Zag6ioqGuKssuirad+Tk4On3/+OS+99NI1yUlbony3XF87d478b76h2tdfU/f8eUYsWMDwrVu5+uKLXH38cbjFTEfle9X0vaIo35Xvynd59GXy3dipE4wejQYYSlk+rhXMPnL4/XdeGzbslucz7NxJvp8fxo0bMWzbRs2sLAIOHCDgwAEA8n77DXPh/wxpaZCTAyVKVIDyXcbvu57aevsua5zVW/vs2bNMLUiM2wKpE0y1atUqSjANGTLkpse1bt0aHx8fUlNT2bx58w3nKKSspWZQPGMKblzCVnieW52jrPNUVltK4uTkVGoAutnztiAsLExKbXvQV77rw23re3vDf/4D//wnfP89fPophtRUHP75TxymTYOJE8Xt+uKn2dkQFYXD3LmM376dmjt2UC0sTOzKY+OZi8p39X2XSdse9JXv+qC3vhS+h4VBbCxMmAAXLoiaTGZz0U9D7drwyy84Dh9evvMFBoobiOTRtm2wYQMkJsL69Tj26weF/frtN/i//wNfX+jZE3r0gJ49CQsOVr4rbZujl+96911W322tK3WR75KFrstbFDstLe2a50u+r3AHt5tRspi233VXMArPc/nyZS5evFiu89SrV++aX5jKaou9s27dOim17UFfT5TvFcDVFV56CQ4fFjviNGsG58/DO+9Ao0bw8suQmiqOjYsTianx4zHGxdHk+HGMcXEwfrx4fsGCinfIApTvcqJ8lxPlu5zYtO8jRsCpUzBrFoSGcr5dOwgNFY9PnYLyJpeux8lJJI1eeQWio8W5Sv5vceaMqIN48qQoFP7SS9CtG07164sNO0rZSOhOR9bvu/quy6mvd99tidQJptatWxfdv3r1apnHFr7ucF3tklatWhXdT05OLvMcJV9v2bLlbZ0nPz+fw4cPl3oOV1fXomRRRdpi75w7d05KbXvQ1xPleyXg5ASPPw7794sBbseOcPkyfP45NGkCAweKgXZBkttQsC1z4U8uXoSQEJGEshHKdzlRvsuJ8l1ObN53Z2d46CGIiWHp5MkQEyMeV+YM3euLfX/xBZhMsHo1fPABBAeDhwfVcnNh61YoWXbi3/+Ghx+Gb76BHTsgP7/y2mVHyPp9V991OfX17rstkTrB1Ldv36L7hUmbm3HkyBEAfHx8rnm+SZMmeHt7A/Dnn3+WeY6EhISiczRu3Pia13r37l10v6zzbNmypWh5W69evW54vfA8Bw4c4PTp0zc9T0mN0s5jz3h4eEipbQ/6eqJ8r0SqVRPL3bZuhSVLoF8/yMuDFStA08StNAqfnzBBLKOzAcp3OVG+y4nyXU6k8b1mTQgKgjfeELOB09NZ+8MPEBUFJYuBx8SIJXX/+Ie4EFSnDgwYAG+9BQU1YW+b7GyYNQuHceMY//PPOIwbJ2Zv2bgIMEjkux1p643efVe+2wapE0wjRozAsSCgzy1j69I///yzKOvYp0+fa14zGAyEhIQAYlbQxo0bSz3Hxo0bi2YNhYSEYLjuykZQUBDu7u4A/PLLL2g3+Qfvf//7X9H9kSNH3vB6aGhoqceWJCsrizlz5gBi5lTz5s1LPc5eKZkYlEnbHvT1RPluBQwGuO8+WLNGDFzLg6aJ2hXR0dZp03Uo3+VE+S4nync5kdZ3g4EuDzwA1xcU//xzMYtp4ECoVQsyM2HVKnjvPZg06dpjFy0Ss5ILZxqXhZ0tgZfVd/Vdl1Nf777bEqkTTHXr1uWJJ54AYPny5cyePfuGYy5dusSkEsH86aefvuGYSZMmFS2dmzhxIleuXLnm9StXrjBx4kRALLGbdP0fB6B69eq88MILAOzfv59PPvnkhmMSExP58ccfAejXrx9du3a94ZiRI0fi7+8PwIcffljqzKzXXnuNCxcuFN2vasTGxkqpbQ/6eqJ8tzJ794pCp+XBaIR586zbngKU73KifJcT5bucKN+vY+BAmDIFli0TF3R27YJvvxWJoBI7WZOfD2PGQKtW4OkpElXvvSeSUddv9hMXZ3dL4GX1Xe/fOT3Ru+/Kd9sgdYIJ4J133qFhw4YAPPzww0ycOJHVq1ezdetW/ve//xEYGMiOHTsAePbZZ0tN6jRv3pxXX30VEEvYevXqRWRkJFu2bCEyMpJevXqxZcsWQCR0mjVrVmpbXnvttaLZRK+//jpPP/00q1evZuPGjXz44YcMGjSI/Px8atSowRdffFHqORwdHfnyyy8xGo1kZGTQq1cvpk+fTlJSEkuXLmX06NF8/fXXgFhO9/DDD9/2Z6dQKO4gzp0r3xVQEMdJtJZcoVAoFApdqFYN2raFp5+GX36B998vfu3cOejSBWrUEImoRYvEbOQBA8DdHZ57ThyXnS2WtoNdLYFXKBR3Jg63PuTOpl69eixZsoQRI0bw119/MX36dKZPn37DcY899hj//e9/b3qe999/n7S0NH766Se2b9/OuHHjbjjm8ccf57333rvpOWrVqsXChQsZOnQohw4dYubMmcycOfOaY9zc3Pj999/p0KHDTc8zdOhQvv32W55//nnOnDlTNHuqJIGBgcybN49q1ard9Dz2Srt27aTUtgd9PVG+W5m6dYu3bC4PmzbBv/4Fjz0GBbMmrYHyXU6U73KifJcT5fttUr++WOKelwc7d8KGDZCYKH6mpECDBuK4qCiRgLoVJZfAP/TQ7bernMjqu96/c3qid9+V77ZB+hlMIHZR27FjBx9//DHdunXDw8OD6tWr4+vry9ixY1m1ahU//vhjUb2m0jAajfz4448sXLiQkJAQvL29qV69Ot7e3oSEhLBo0SJ++OEHjLdYgnL33Xezfft2pk2bRpcuXahduzYuLi60aNGCl156iV27dhEcHHzLPj355JNs3bqVJ598kqZNm+Ls7EzdunXp3bs333zzDevXr8fT09Piz8oeKMuHO1nbHvT1RPluZUJDy59cAnGF84MP4O67oX9/UZD0uuXBlYHyXU6U73KifJcT5XuFTyJmMr3wAkREwPHjcOIEPPWUeD029sZd7W6GDZfAy+q73r9zeqJ335XvtkElmAqoWbMmr776Khs3buTcuXPk5ORw4sQJZs+eTf/+/ct9nqFDhxIbG0tqaio5OTmkpqYSGxvLkCFDLGrL66+/zubNm7lw4QKXL18mOTmZzz77jEaNGpX7PG3atGHmzJkcPnyYK1eukJ6eztq1a3nmmWeKakZVRbZu3Sqltj3o64ny3cqEh4udam41CDUYoHZt+P13GDxYPF6zRmypfNddYtebbdsqrVnKdzlRvsuJ8l1OlO9WwNdXzHACsZTuZkvjrsdsFgmq556Dn3+G3btFrScrIKvvev/O6YnefVe+2waVYFIoFAoFODuL+g5w8yRT4fO//goPPCC2Sz5+HN59Fxo3BpMJvvkGOncWWyt/9RWcP2+T5isUCoVCoSiFwiXw5cFohNxc+PprsQS+XTtRz6l3b7GD3e+/qxqMCoWiTFSCSVHlGHb9dq6SaNuDvp4o323A8OFiKn3t2gBoBQPSwp/Urg3z54vjCvHzE0VFDx+G5cth3DhwcoIdO8R0fW9vuP9+WLHCsiV4BSjf5UT5LifKdzlRvlsZS5bAm80wciS88gr06weurpCVBevXw3//K2oz/fVX8fGbN8OcOXD0aPlnSRUgq+96/87pid59V77bBpVgUlQ5Cnfkk03bHvT1RPluI0aMgFOnYNYszCNGcLRxY8wjRsCsWeL5ksmlkhiNcO+9ov7DqVPw5ZfQvj3k5MDs2WLbZX9/+M9/RG2IcqJ8lxPlu5wo3+VE+W5lLFkCX6cOvPEGfPKJWP5+8SLs2ydmLr/wAvTqJWY1FfLTTzB2LDRtCp6ecN998Oab4mLVyZNlJp1k9V3v3zk90bvvynfboBJMiirHmTNnpNS2B309Ub7bEGdneOgh8mfP5tcJE8ifPVtctXR2Lt/7PTxg4kTYvh22bIFnnxVT7I8dg7ffhkaNYMgQsVNNbm6Zp1K+y4nyXU6U73KifLcyliyB/+WXa//WV6sGLVuKOov//S+sWwc1ahS/3qSJWBbv6CiWxC9bBu+/L2ZB+fldu5zu4EFISyt6KKvvev/O6YnefVe+2waVYFJUOdzc3KTUtgd9PVG+V0EMBjHw/PrrollRBAWJK5pLloirqj4+8PLLsHdvqadQvsuJ8l1OlO9yony3AbezBL48vP66uJB06ZJYLvfNN8W1m+6+W8xqKuT550Xh8YYNYdQoOi5ZIpbW61CrUebfOT3Ru+/Kd9tg0DQLF8wqpCYjIwN3d3fS0tKoV6+eLm3Iy8vTbatHPbX11M/JyWHq1KlMnjwZJycnm+uD8v2O8v2vv8TuNP/7n0g8FdKtGzz+uKjjVKsWoHy/o3y3AOW78l0mbT31le+S+Z6dDdHRXI2JIWXHDhp26EC1UaNg9Ojyz1IuL/n5UHLX6l69IDGx9GVznTuLRFUhublQvXrltqcEsv7O6f19l+77ZifaZ8+excvLC5PJZJNEV9Xdq15hU2bMmMGMGTO4evUqALGxsbi6uhIWFsbKlSsxmUx4eXkRGBhIfHw8AJ06dcJsNrNjxw4AQkJCWLduHefOncPDw4O+ffsSGxsLQLt27XB0dCzawnHYsGFs2bKFM2fO4ObmxqBBg4iOjgZEkmvgwIFs2rQJgPvuu489e/aQmppKzZo1CQ4OJjIyEoAWLVrg6enJ+vXrAbj33ns5ePAgKSkpODk5ERYWRmRkJGazGX9/f3x8fEhISAAgKCiIlJQUjhw5goODA+Hh4Xz11VfcddddNGrUCH9/f1atWgVA7969SUtL4+DBgwDcf//9zJ8/n6ysLHx9fWnVqhXLli0DoEePHphMJvbt2wdAeHg4S5Ys4dKlSzRo0IBOnTqxaNEiALp27Up2dja7d+8G4OrVq3h6enLhwgU8PT3p0aMHCxYsAKBjx44AbN++HYDhw4eTmJhIeno6derUISgoiHnz5gHQtm1bnJ2d2bx5MwBDhw5l27ZtnD59mlq1ajF48GCioqIAaNWqFTUKpkNHR0czePBg9u3bx8mTJ3FxcSEkJISIiAgAmjdvjpeXF+vWrQPgnnvu4fDhwxw/fpzq1aszatQooqKiyM/Pp2nTpjRs2JA1a9YA0LdvX1JTUzl8+DBGo5GxY8cyd+5ccnJyaNiwIYcOHSr6Y9irVy/S09M5cOAAAGPHjiU+Pp7Lly/j4+NDmzZtWLp0KQDdunUjMzOTvQUzZEaPHs2yZcvIyMigfv36dOnShYULFwLQuXNn8vLy2LVrFwChoaEkJCSwe/du2rVrR+/evZk/fz4AHTp0wGg0sm3bNgCCg4NJSkoiLS0Nd3d3BgwYwNy5cwFo06YNLi4uJCUlATBkyBB27tzJqVOncHV1ZejQocyZMweAgIAAPDw82LBhAwADBw4kMjISDw8PatSoQWhoKLNnz0bTNJo1a0aDBg1Yu3YtAP379+fYsWMcPXoUR0dHRo8eTXR0NHl5eTRp0oTGjRuzevVqAPr06cPp06c5dOgQBoOBcePGERsby5UrV/Dz8yMgIKDoM0xJSSEzM5Pk5GQAxowZw6JFi8jMzMTb25v27duzePFiAAIDA8nKymLPnj0ApceIzZuhTRs6LVuGy9q18NNP+GzbhnHTJti0ifyJEznTty+e//wnX23bho+vr0UxonXr1ri6ulY4Rvz999+8/PLLFsWImJgYcnNzKyVGLF++HB8fH4tixMiRI1mzZk2FYoS5oBjskSNHiuL3rWKEu7s7iYmJAAwaNKjCMeL48eP06dPHohjRvHlzVqxYUeEYYTabqV27tkUx4vz589StW7dSYkRqaipPPPGERTEiOTmZEydOVChG+Pn5ASLOG43GcsWI5cuXA9CzZ0/Onz9f4RiRnp7OhAkTrD6OKC1G/PHHH9StW9fq44ibxYgrV67Qvn17q48jro8RnTt3LvK98L41xhFlxYisrCwKseY4orQYsWrVKnx8fKw+jrhZjFi3bh2urq6AdccR18SIhx4i0mjkUIcO3Hffffj6+rK2wNfKHkdcEyOmT+evbduoc/w497i6cmj2bLxPnaLWmTPkuboSXfB3IjAwEN/+/cm+epXzTZviN3IkSWYzJz09qevnd9v/a7Rv0YI6K1aQHx2Ndu4cd7VuzaHWrdkdEICrp6dVxhGlxYi9e/fiXJDMs/Y44voYYTKZADCZTKxcubJcMaIy/9f49ddf8fT0tMk4orQYkZ2dTevWra0+jigtRsycORMfHx+bjCOujxE2R1MoLMBkMmmAlpaWplsb/vjjDym19dTPzs7WpkyZomVnZ+uir2nKdz2wqe+nT2vaRx9pWosWmiaub2oaaKa77tK0adM07e+/rd+G61C+q++7TPrKd+W7XijfbY9d+X7unKYdOlT8wrlz14wDim7Vqmlau3aa9t57lovNn69pdeqI8xiN1/6sU0fT4uIqp1PlQM/fOb19l/X7prd2WlqaBmgmk8kmeqoGk6LK0bp1aym17UFfT5Tvdzj168Nrr8H+/aKI6KOPQs2auP39N/zzn+DrK7Zajo8X0+5tgN6fu976eqK+73KifJcT5bucFPXdw0PUayrEwwNOnxZ/76dMgeBgMUa4ehV27bp2J9rsbOjeXWwm8uOP4vXrxwhxcWL8cPGieFwwS7fo58WLEBIijrMBynM59fXuuy1RS+QUVY7CqcSyaduDvp4o3yXBYBB1Gnr1gv/+l7PTp1MvLg42bhQFSOfPh7vuggkTRCHRkoPSSkbvz11vfT1R33c5Ub7LifJdTsrse/36MGyYuIGYw5SaKuo0+foWH7drFxQsry+iRg3o0AG6dBFFyydMKD5HaWiaGHtMmCDqQlZ2LarrUJ7Lqa93322JmsGkqHJsKvlHRCJte9DXE+W7hNSqxYrGjUVR0D17xG5znp7w99/w4YfQrJnYlW7WLChRw6Oy0Ptz11tfT9T3XU6U73KifJcTi/puMBTPZO7Spfj5Zs0gMlLMgO7fX2wQcuWKGDd89ZWY1XThws2TS4VomjiuoAaTNVGey6mvd99tiUowKRQKhcL+ad0aPv1UXMGMjoYhQ8BohD//hPHjxaymZ58VVzfV5qgKhUKhUNz51KkDY8bARx/BqlViuVtyMvz2G0yaBGfPirFCeTAaoaBAtUKhuH1UgklR5bjvvvuk1LYHfT1RvsvJDX2vXh1GjYJFi+D4cfjPf6BJE8jIgG+/ha5dxdT4L7+Ec+cqV9vG6K2vJ+r7LifKdzlRvsuJVfpuNEKLFvDgg/D556JuU2GtpVthNsP58+L+1q0wdSosWSLqQVUiynM59fXuuy1RCSZFlaNwa2PZtO1BX0+U73JSZt99feHNN+Gvv2DFCrj/fnByEjUZXnwRvL1h3DhYvrz8A8zyatsAvfX1RH3f5UT5LifKdzmxSd/r1rVsBpOHh7i/aBG88YaYLX3XXaIm1H33iU1H/vhDLKe7TZTncurr3XdbohJMiipHamqqlNr2oK8nync5KVffjUYYMEAM+v7+W9Rd6NABcnNFbYZBg6BpU3jnHUhJKftc2dmiptOoUbR45hkxW2rWLPG8jVG+y6dtD/p6onyXE+W7nNik76Ghls1gGjlS3G/bVlygCggQY4y0NFi2TCzFe/BBUQy8kOXLYfp0sQNuRsYtZZTncurr3XdbohJMiipHzZo1pdS2B309Ub7LicV9r1MHnn8etm8XU9z/8Q9wdxfL6aZMgcaNxVXIOXMgJ+fa98bFiVlP48dDbCz19++H2Fjx2NsbFiyopF6VD+W7fNr2oK8nync5Ub7LiU36Hh4uxgUGQ9nHGQziuNGjxePQUIiIgP374dIlsUvdd9+JMUXfvmIZXiG//QYTJ0KfPmK84e8vLk69+64YV1x3gUp5Lqe+3n23JQ56N0ChsJTg4GApte1BX0+U73JSob536iRun3wCc+eK3WRWrxZXIZctE1PnH34YHn8cjhwRA8pCCq94Fv68eBFCQkTCacSI22+TBSjf5dO2B309Ub7LifJdTmzSd2dn+OUX8ffbYCh9E5DC5NMvv4jjr8fFBQIDxa00uncXtZt27ICTJ8V44sgRMe4wGkWCqpDoaIIzMsSxrVqJupISoffvu8yxxpaoGUyKKkdkZKSU2vagryfKdzmplL7XqCGmtK9aJeo1/etf4OMjioB/8YWYCh8WJgaeN9uBrvD5CRNstlxO+S6ftj3o64nyXU6U73Jis74PHy4uDtWuLR4X1mQq/Fm7NsyfL467HZ59VsxwPnEC0tNh5Ur47DMx+3n4cJGgKuTzzzE+/jh07Ag1a0L79vDII+L4Vavu+F1w9f59lznW2BI1g0mhUCgU8uDvD++9J+oxLV0qZjXFxoqdZm6FponCntHR8NBDVm+qQqFQKBSKSmDECFE3KToa5s3jzP791G/ZUtRcGj269JlLt0PdunDPPeJWGv37c+biRer//bcYT+zaJW4gNi45caL42P/9D1xdRU3Jpk3LX6y8NLKzISoKh7lzGb99Ow47dogLa+Hhldd3haIAlWBSVDlalFz3LJG2PejrifJdTqzW92rVYOhQcQsOFjvGlOfKodEI8+bZJMGkfJdP2x709UT5LifKdzmxed+dncXf7oceInXbNup36mRbfYD33iM1LIz6HTuKZNKOHbBzp/hZr17xcZoGr78OZ8+Kx66u0K6dSDa1bw9du4pZUOUhLk7Mvr5wAaPRSBOzGe3ECXFx7cUXxdLA2529ZSF6/77LHGtsiUowKaocnp6eUmrbg76eKN/lxCZ9z8ws/7R0s1ksrbMBynf5tO1BX0+U73KifJcTWX339PQUdZ8aNhS30uo65uaKulE7dsCePWKcsmGDuAEEBYmakoXMmCFmaHfoAA0aFD8fF3dNfUlDQV1Jg071JfX+fdfdd0lQNZgUVY7169dLqW0P+nqifJcTm/S9bl3Lpp5v2iR2jFmzBvLzrdYs5bt82vagryfKdzlRvsuJrL6XS9vJCb7/HjZvFkXC9+6F338Xs5oGDRIJpkJMJrF77pAhcNddUL++2C335ZfhgQfEMXZSX1Lv33e79/0OQc1gUigUCoXchIaK3V7KS3Y2TJ8ubvXqifePGgX9+0u3I4xCoVAoFAor4uAgdpxr1ao4YVSSzEwYN07Mdjp4ENLSinfLLQ+qvqSiklEzmBRVjnvvvVdKbXvQ1xPlu5zYpO/h4VCnTvFWxTfDYBC7zcydC48+Ch4eoj7C99/D4MHiquEjj4gp6ZVwJVD5Lp+2PejrifJdTpTvciKr75Wu7eMDERGwf7+Y7bRpE8ycKQqDlxeDAT79FJKTK7dt16H37/sd5bsdoxJMiirHwYMHpdS2B309Ub7LiU367uwsilzCzZNMhc//+qvYdeann+D0aVi+HJ55RiSXLl4Ur4eEiJlN48ZBVJS4ungbKN/l07YHfT1RvsuJ8l1OZPXdqtouLhAYCE8+CX5+5X+fpokZUHFxxc8dOyaW2f34o0haXbpU4ebp/ft+x/puZ6glcopyMWPGDGbMmMHVgq28Y2NjcXV1JSwsjJUrV2IymfDy8iIwMJD4+HgAOnXqhNlsZseOHQCEhISwbt06zp07h4eHB3379iU2NhaAdu3a4ejoyNatWwEYNmwYW7Zs4cyZM7i5uTFo0CCio6MByMjI4K677mLTpk0A3HfffezZs4fU1FRq1qxJcHAwkZGRgKjY7+npWbTu9d577+XgwYOkpKTg5OREWFgYkZGRmM1m/P398fHxISEhAYCgoCBSUlI4cuQIDg4OhIeHs2nTJlJSUmjUqBH+/v6sWrUKgN69e5OWllYUPO6//37mz59PVlYWvr6+tGrVimUFU1V79OiByWRi3759AISHh7NkyRIuXbpEgwYN6NSpE4sWLQKga9euZGdns3v3bgCuXr3KpUuXuHDhAp6envTo0YMFCxYA0LFgN4nt27cDMHz4cBITE0lPT6dOnToEBQUxb948ANq2bYuzszObN28GYOjQoWzbto3Tp09Tq1YtBg8eTFRUFACtWrWiRo0aAERHRzN48GD27dvHyZMncXFxISQkhIiICACaN2+Ol5cX69atA+Cee+7h8OHDHD9+nOrVqzNq1CiioqLIz8+nadOmNGzYkDVr1gDQt29fUlNTOXz4MEajkbFjxzJ37lxycnJo2LAhhw4dIiUlBYBevXqRnp7OgQMHABg7dizx8fFcvnwZHx8f2rRpw9KlSwHo1q0bmZmZ7N27F4DRo0ezbNkyMjIyqF+/Pl26dGHhwoUAdO7cmby8PHYVbBkbGhpKQkICu3fv5vLly/Tu3Zv58+cD0KFDB4xGI9u2bQMgODiYpKQk0tLScHd3Z8CAAcwtWHbVpk0bXFxcSEpKAmDIkCHs3LmTU6dO4erqytChQ5kzZw4AAQEBeHh4sKGgkOPAgQPZsWMHKSkp1KhRg9DQUGbPno2maTRr1owGDRqwdu1aAPr378+xY8c4evQojo6OjB49mujoaPLy8mjSpAmNGzdmdUFRyD59+nD69GkOHTqEwWBg3LhxxMbGcuXKFfz8/AgICCj6DFNSUsjMzCS54MrWmDFjWLRoEZmZmXh7e9O+fXsWL14MQGBgIFlZWezZswegwjEiMTGRlJQUi2JE69atcXV1tSxGZGbi8/LL9P7hB4wmE2aDAaOmidpMZjM5Li4cf+cdanbqRELB73tQUBAptWpxpG9fHIKCCPf25tC0aXgnJlLz/HmIjITISPIdHcm95x7O9OrFVm9v8lxcyhUjCvtuSYwYOXIka9asqVCMMBcU/zxy5EiRN7eKEe7u7iQmJgIwaNCgCseI48eP4+DgYFGMaN68OStWrKhwjDCbzVy8eNGiGHH+/Hnq1q1bKTEiNTWV1q1bWxQjkpOTOXHiRIVihF/BPyPR0dEYjcZyxYjly5cD0LNnT86fP1/hGJGenk67du2sPo4oLUZs376dlJQUq48jYmJiyM3NvWEcceXKFZydna0+jrg+RnTu3LnI98L71hhHlBUjsrKyiv6+W3McUVqMKIyz1h5H3CxG7Nu3r6jv1hxHXB8jYmJiirz29fW12jiirBixefNmUlJSrD6OKC1GpKam0rZt28odR5QzRhS+BpbFCEv/16jt4IBb4VjmFmhAtrs7Gy5dold2NmvWrMF18WJ6f/nlNcfleXuT06wZKW5uHO/Viz7PPWdxjEhJSbHJOKK0GJGdnY2jo6PVxxGlxYjCWGOLcQRcGyNsjqZQWIDJZNIALS0tTbc2xMTESKmtp352drY2ZcoULTs7Wxd9TVO+64GUvl+5ommzZmlaWJiW1rq1poWFicdXrpT/HGazpm3apGmvvaZpTZtqmrg2KG6Ojpo2ZIim/fCDpp09W+ZplO/yaeupr3xXvuuF8t32KN8l0P7112vHH7e6zZp17fu3btW0SZM07d57Na1BgxuPL9mPVas0LTRU0958U9MiIjRt925Ny8m5oUmyft/01k5LS9MAzWQy2UTPoGnl3ZtZoRCzh9zd3UlLS6NevXp6N0dhI3Jycpg6dSqTJ0/GyclJ7+YobITyvRLQNNi5E2JixG3//uLXqlWDfv1EgfCRI8XuL3aA8l1OlO9yonyXE+W7BGRng7e3WL5f1r/7hfUlT50SJQNuxrlzYje7vXthzx6xo12jRuK1Dz+E//u/a493cIDmzaFNG3j7bWjduqI9UtwmZ8+excvLC5PJhJubm9X1VA0mRZWjcEqqbNr2oK8nync5qfK+GwzQoQP85z+wb5+4/ec/4rmrV2HVKnjuOVGks3dv+PxzOH688vSrKFXe9yqsryfKdzlRvsuJrL7bTNuS+pK//FJ2cgmgbl3o2xeefRZmzChOLgEEB8MXX4jaTz16gJsb5OeLMc+cOWK8Q0Hfv/4aOnYUO9ZNnQrx8XD0KBQsz690srNh1iwYNYq01q3FRb1ZsyplMxZLkOm7rmowKaocZmsFIDvXtgd9PVG+y8kd53vLlvDmm+J25EjxzKZNm2D9enF7+WXo0oUWd98NnTpBs2aV3w47547zvQrp64nyXU6U73Iiq+821R4+HGJjYcIEuHABzWjEYDYX/aR2bZFcGj68Yjpt24pbIZoGJ08Wz3Zq0QIo6Pu2baKgeEHdrCJq1oRWrUT9yiZNxHPZ2eDkdOtdfm9GXFxR3zEa8TKbxU55c+fCiy9WTt/LiUzfdZVgUlQ5/P39pdS2B309Ub7LyR3te9Om8Npr4nbiBMybJ5JNa9fCli102LIFZs8Wg7ZRo8StdevbH2hVIe5o3+1cX0+U73KifJcTWX23ufaIEWL5W3Q05pgYUnbsoGGHDlQbNQpGj771zKXbwWAQu9j5+cHgwUVP+/v7i9naI0aIxNOePSIJlZwMly/D5s1iF95CXnkFfv9dLLNr3Vr8LLzdqlRLXByEhhY/LkzwFP68eFHs+hsbK9pjZWT6rqsEk6LK4ePjI6W2PejrifJdTqTx3c8PXnhB3M6cgdhYsv/4A+f162H3bnGbMkXUMyhMNnXqdMcmm6Tx3Q719UT5LifKdzmR1XddtJ2d4aGHyA8P59eC2lvVdKi95ePjI0oC+Pldm9TJz4e//hI3V9fi5/fvB5OpeIZ3SerVEzPBC48/dgzc3aFOHTHzacIE8fzN6k9pmhhDTZhw6/pTlYBM33VVg0lR5Sjc/lc2bXvQ1xPlu5xI6Xv9+vD008x75hlIS4Offxb1DapXh4MHRTHNLl3EDKhXXoENG6xXu0AnpPTdTvT1RPkuJ8p3OZHVd+V5KTg4QECAGOuUZPFisVHKH3+IIuIhIeDvLxJDDg7XJqOeeQY8PEQCq2tXsSzuVnuZaZo4Ljq6Yh0rBzL5rmYwKRQKhUJhr3h4iKtrEyZARgYsXCiW0S1eLK7WffaZuHl7i53oRo2CPn3EwEuhUCgUCoWiquLkBO3aiVtJsrIgNfXa5y5cED9PnRK38mI0ihIFDz1UsbYqilAzmBRVjqCgICm17UFfT5TvcqJ8L4GbG9x/v7jSdvasSDQ98ADUqiUGUzNmwD33iGTTU0/B0qWQm6tL2yuK8l1OlO9yonyXE1l9V55XAi4uN26AsmmTqKu0YYMoJ1BezGZYsULsgPfpp+K+FZDJd5VgUlQ5UlJSpNS2B309Ub7LifL9Jri4QFiYKH559qzY5vfRR8WMp7Nn4fvvRWHN+vXhkUdEsctbbclbsJWvw7hxjP/5ZxzGjdNlK19QvsuK8l1OlO9yIqvvynMr4u4OPXqIIuBGC9IcGRnwww/w6qvwr39d+9qLL8Lbb4tletu2iWLkt4FMvqsEk6LKceTIESm17UFfT5TvcqJ8LwdOTjBsGPz0E5w+DcuXi1oE9euLq3m//irqFtSrB+PGQVQUZGZee464ODHzafx4jHFxNDl+HGNcHIwfL55fsKDS+1cWync5Ub7LifJdTmT1XXluA0JDLatN+Y9/iCTSmDFw333Fz+flwddfw3/+Aw8+CJ07i7pPjRqJ4z79tNwSMvmuijQoqhwOOtYW0VPbHvT1RPkuJ8p3C3F0hHvvFbfp08VU8ZgYcTt5EiIjxc3ZWcxwGjUKqlUTA6cCDAWDMoNOW/mC8l1WlO9yonyXE1l9V57bgPBwMfPo4sWyC30bDFC7tkgUlbaLXF4eTJsGycnitn8/pKdDSoq41a1bfOzVq+DrC40bi4LlJW9Nm0rlu0HTblVeXaEoJiMjA3d3d9LS0qhXr57ezVHYiJycHKYWbGvqpMO2pgp9UL7fQWgabN4s6jfFxIitfS2hcBBmg618Ffqgvu9yonyXE+W7nEjl+4IF4uIYlJ5kMhjEz/nzYfjw8p83PR0OHBAJp4YNYeBA8fzhw3D33aW/x9FRzJL64gvx2GyGrVuhRQtRX9NaZGdDVBQXIiPxWLgQk8mEmzX1ClBL5BRVjpiYGCm17UFfT5TvcqJ8ryQMBggMhI8+gr/+v737Dovi2v84/l4EqYIiokGxYY+9BjXWxK7YsCQm+ku/6bk39d4U0027JjfXm0RNMUUsqNiNlVhjxYpYEEWxIEgRkbrz+2PcFWRBENiBnO/reeZh3Z2d7wwf9jgczpw5CRER8Oab+uVvxWHHW/mC5K4qyV1NkruaVM1dMreT4cP1kdfVq+v/tszJZPlavXrJO5cAfHygRw949NGbnUugdzYdPAgLFsB77+k3YenQQZ8zMzubo3nvenfunH5O5uWlj3q67z549ll95Pn69RAff4cHnUfeqQ9WrSr99kpAnbFa4i8jy8C7IhlZuyLUN5LkribJvRyYTNC+vb5ERuonYMWZq8COt/KV3NUkuatJcleTqrlL5nY0YoQ+8jo0FJYs4dLRo9Ru2RJGjYKxY8t2RLaTE7Rpoy95mc1w7hxRK1fS0vLcpUtQp44+b2ZcnL5s2HDzPa+9BtOm6Y8TE+Hbb29ebtekiT73ZlGWLdPnobrBZOcL1qSDSVQ6DRo0ULJ2RahvJMldTZJ7OUtMLP5EmGazfgL08cf65Jbt25fsLi0lILmrSXJXk+SuJlVzl8ztzMVF/8PYpElEb99O7e7d7VvfwQHq16d2u3Y3n+vSBS5c0OeIOnZMn9vJMs9TVJR+FzyLgwf1EecWVapA48Y3O5zGjtVHQ1lkZMCUKfpjg2ZCkg4mUekEBAQoWbsi1DeS5K4myb2c1aypn/wUt5MpJQX++U99qVULBgzQO5vuv1//a1wZkdzVJLmrSXJXk6q5S+Zq1rdZu3p16NZNXwrj5aXf0dcyyfjVq3DihL4sXw7Nmt3sYNq9W183KalcjqG4ZA4mUels3LhRydoVob6RJHc1Se7lrKS38p08WR9y7uEBly/Db7/pJzN33aWPaHrtNdi4ETIzS7VbkruaJHc1Se5qUjV3yVzN+ndcu2NHmDMHdu7U/8hnuZxuxgx47rn8nVMHDugdUQaTEUyiWGbMmMGMGTPIzc0FICwsDA8PD0aPHs2GDRtISUnB19eXrl27smLFCgA6duyI2Wxm//79AAQFBbF161YSExPx9vamV69ehIWFAdC2bVucnJzYu3cvAEOHDmXPnj1cunQJT09PBgwYQOiNyWVTU1M5deoUO3fuBGDgwIEcPnyYuLg43N3dGTZsGPPnzwegefPm+Pj4sG3bNgDuu+8+jh8/TmxsLM7OzowePZr58+djNpsJCAigbt26bN68GYA+ffoQGxvLqVOncHR0JDg4mAsXLhASEkKDBg0ICAiwNhY9e/YkPj6e48ePAzBx4kSWLl1Keno69erVo1WrVqxduxaAwMBAUlJSiIyMBCA4OJg1a9Zw9epV6tSpQ8eOHVl1YzK2Ll26kJGRwaFDhwDIzc1lzZo1JCUl4ePjQ2BgIMuXLwegQ4cOAERERAAwfPhwduzYQUJCAjVq1KBPnz4sWbIEgDZt2uDi4sLu3bsBGDJkCPv27ePixYtUq1aNQYMGsXDhQgBatWqFq6srAKGhoQwaNIjIyEjOnTuHm5sbQUFBhISEANCsWTN8fX3ZunUrAP369SM6OpozZ85QtWpVxowZw8KFC8nJyaFx48bUr1+f8PBwAHr16kVcXBzR0dE4ODgwfvx4Fi9eTGZmJvXr1yczM9Nap0ePHiQkJHDs2DEAxo8fz4oVK7h27Rp169aldevW/P777wB069aNtLQ0jhw5AsDYsWNZu3Ytqamp1K5dm86dO7Ny5UoAOnXqRHZ2NgcPHgRg5MiRbN68mbi4ONauXUvPnj1ZunQpAO3bt8fBwYF9+/YBMGzYMHbt2kV8fDxeXl7079+fxYsXA9C6dWvc3NzYtWsXAIMHD+bAgQOcP38eDw8PhgwZwoIFCwBo0aIF3t7ebN++HYD777+fK1euEBISgqurKyNHjmTevHlomkbTpk2pU6cOW7ZsAaBv376cPn2amJgYnJycGDt2LKGhoWRnZ9OoUSMaNmzIpk2bALj33nu5ePEiJ06cwGQyMWHCBMLCwrh+/Tr+/v60aNHC+j2MjY0lLS2NqBv/aY0bN45Vq1aRlpaGn58f7dq1Y/Xq1QB07dqV9PR0Dh8+DFDqNiIuLo6QkJAStRF33303Hh4epW4jLly4AFCiNmLRokVkZWWVSRthOfaStBGjRo0iPDy82G3ETm9v7nV3xyk9vchr9DWTiRx3dxb37Yt7zZoMCgkhfNo07jpwgEYnTuB29Kh+YnPgAHz6Kbmurlxs0YLETp1o+8orhOzZAyZTsduIuLg4du7cWaI2olmzZqxfvx4oXRthNptZuXJlidqIK1euULNmzTJpI+Li4khOTi5RGxEVFcXZs2dL1Ub4+/sDejvv4OBQrDZi3bp1AHTv3p0rV66Uuo1ISEjg6tWr5X4eYauNSExMJCQkpNzPIwprI65fv87evXvL/Tzi1jaiU6dO1twtj8vjPMLLy4sdO3YAMGDAgHznEYBdziNstRGWdra8zyMKayPS0tKsx16e5xG3thGWyZYjIiKoV69euZ1HFNVGXLp0iZCQkHI/j7DVRsTFxZGamlru5xG22oiMjAxr5uV9HnFrG5GSkgJASkoKG27M+VPa84iStBEJCQmEhISUuI0oq981MjIy2LVrV7mfR9hqIyxtTanPI44e1duIhg3p/+ijehtx+DCtW7fGs1kzqvv54XX+PIbShCiBlJQUDdDi4+MN24fY2FglaxtZPyMjQ5s6daqWkZFhSH1Nk9yNILkrkvuyZZpmMumLfsV+/sXy2rJlhW/j0iVN+/VXTXvoIU2rXbvgNho21LQnn9S0xYs1LTn5trskuduffN4ld6NI7vYnuatZ2+jcVf282bX26NGa5uCQ7xwsBTRAS0lJscsuyCVyotKJL4tbN1bC2hWhvpEkdzVJ7nZwy618tRsTd2sluZWvry88+CD8/LN+x5aICP0OKH376ndWOX0avvsORo/W532691744AN9vgAbl+hJ7mqS3NUkuatJ1dwlczXr2612Sac+KAfSwSQqHcvQUNVqV4T6RpLc1SS524nlVr6//IJ5xAhiGjbEPGIE/PKL/nxRnUu3cnDIPx/TlSv6RJTPPqtPRpmbC1u3wltv6RNT+vrCxInw0096LSR3VUnuapLc1aRq7pK5mvXtVjs4GGrUAJPJPvVskDmYhBBCCGG9lW9OcDA/T5vG66+/ThVn59Jv18MDhg3TF4CYGFi7Fn7/XZ+oMjER5s3TF4A2bWhfvz74+OgjnVxcSr8PQgghhBB/dS4u+qTgQUF6J1MR82uWF5OmGVBVVFqpqal4eXkRHx9PrVq1jN4dYSeZmZlMu/ELp3NZ/MIpKgXJXU12zT07W78zyu+/68uePflPhlxdoXdvGDhQX1q0MPSvcn9l8nlXk+SuJsldTZK7QpYtgylTICmJFJOJ6ppGSkoKnp6e5V5aLpETlY5lZn3ValeE+kaS3NUkuf/FOTlBz57w/vuwaxfEx0NICLH9+sFdd8H167BmDbz0ErRqBQ0bwuOPQ2goJCWVyy4Z/X03ur6R5POuJsldTarmLpmrWd/utfNOfTBkiF1LyyVyotJJT09XsnZFqG8kyV1NkrtifHxgwgS2aRr1J0yAw4dvjm7asgViY2H2bH1xcIBu3W6OburSBapUKfUuGP19N7q+keTzribJXU2q5i6Zq1nfkNqWqQ8GDtTnu7QT6WASlU69evWUrF0R6htJcleT5K6mevXq6ZfCtWmjLy+/DOnp8McfN+dvOnoUduzQl6lT9Ukt77vvZodTSb5/GRmwcCGEhTH41Cl9hNTIkfpkmXaeA0r53BWsXRHqG0lyV5OquUvmatY3+tjtSTqYRKXTqlUrJWtXhPpGktzVJLmryeaxu7nB4MH6AvpoJktn0/r1+iVzCxfqi76Rm51NvXrp8znZkmeeAhwcqG42w8GDsHgxvPCCPllmSe6iV0qSu3q1K0J9I0nualI1d8lczfpGH7s9yRxMotJZu3atkrUrQn0jSe5qktzVVKxjr18fHntM71C6fBm2b4d33oF77tEvn4uMhOnTYdAg8PbWO5q++EK/7M4ykfiyZfpIpeRk/d9mc/6vycn6nViWLSvjIyyc5K5e7YpQ30iSu5pUzV0yV7O+0cduT9LBJIQQQojKzdERAgP1S+V27NA7nBYsgEcf1S+Vy8jQRzu9/LJ+yZ2/Pzz8MDzwgP7+wm6oa3l+yhR9G0IIIYQQolDSwSQqncDAQCVrV4T6RpLc1SS5q6nUx+7trc+fNHu2findkSPw73/ro5hcXCAuDn75Ba5dK7xzyULT9MvnQkNLt0/FJLmrV7si1DeS5K4mVXOXzNWsb/Sx25N0MIlKJyUlRcnaFaG+kSR3NUnuairTYzeZ9PmYXnoJ1qyBK1f0eZuaNi3+NhwcYMmSstunIkju6tWuCPWNJLmrSdXcJXM16xt97PYkHUyi0omMjFSydkWobyTJXU2Su5rK9dhdXWHAAPDzK/57zGbYuxfWrYO0tPLbNyR3FWtXhPpGktzVpGrukrma9Y0+dnuSu8gJIYQQQj01a+ojkywTet/OmTN6x1SVKtCxI9x7r353up499W0JIYQQQihORjCJSic4OFjJ2hWhvpEkdzVJ7mqyy7GPHFn8ziWAHj2gYUPIzYXdu/U5nUaOBB8faN0ann4aQkLg3LlS7Zbkrl7tilDfSJK7mlTNXTJXs77Rx25P0sEkKp01a9YoWbsi1DeS5K4myV1Ndjn24GCoUUOfo6koJpO+3vr1EBOjTxr+22/w5JPQsqW+zpEj8M03+l3p/P2hcWP9znPffw8nTtx+IvE8JHf1aleE+kaS3NWkau6SuZr1jT52e5JL5ESlc/XqVSVrV4T6RpLc1SS5q8kux+7iAnPmQFCQ3olkqxPI0vk0Z46+PugdSA88oC8Aly/D1q2wZQts3gwREXpHVEyM/j6A2rX1y+l69dIvrWvTRr88zwbJXb3aFaG+kSR3Namau2SuZn2jj92epINJFMuMGTOYMWMGubm5AISFheHh4cHo0aPZsGEDKSkp+Pr60rVrV1asWAFAx44dMZvN7N+/H4CgoCC2bt1KYmIi3t7e9OrVi7CwMADatm2Lk5MTe/fuBWDo0KHs2bOHS5cu4enpyYABAwi9cYtok8nEqVOn2LlzJwADBw7k8OHDxMXF4e7uzrBhw5g/fz4AzZs3x8fHh23btgFw3333cfz4cWJjY3F2dmb06NHMnz8fs9lMQEAAdevWZfPmzQD06dOH2NhYTp06haOjI8HBwSQlJRESEkKDBg0ICAhg48aNAPTs2ZP4+HiOHz8OwMSJE1m6dCnp6enUq1ePVq1asXbtWkC/TWVKSop1srfg4GDWrFnD1atXqVOnDh07dmTVqlUAdOnShYyMDA4dOgSAj48Pa9asISkpCR8fHwIDA1m+fDkAHTp0ACAiIgKA4cOHs2PHDhISEqhRowZ9+vRhyY27ILVp0wYXFxd2794NwJAhQ9i3bx8XL16kWrVqDBo0iIULFwLQqlUrXF1dAQgNDWXQoEFERkZy7tw53NzcCAoKIiQkBIBmzZrh6+vL1q1bAejXrx/R0dGcOXOGqlWrMmbMGBYuXEhOTg6NGzemfv36hIeHA9CrVy/i4uKIjo7GwcGB8ePHs3jxYjIzM6lfvz7VqlWz1unRowcJCQkcO3YMgPHjx7NixQquXbtG3bp1ad26Nb///jsA3bp1Iy0tjSNHjgAwduxY1q5dS2pqKrVr16Zz586sXLkSgE6dOpGdnc3BgwcBGDlyJJs3byYhIYG1a9fSs2dPli5dCkD79u1xcHBg3759AAwbNoxdu3YRHx+Pl5cX/fv3Z/HixQC0bt0aNzc3du3aBcDgwYM5cOAA58+fx8PDgyFDhrBgwQIAWrRogbe3N9u3bwfg/vvvJzs7m5CQEFxdXRk5ciTz5s1D0zSaNm1KnTp12LJlCwB9+/bl9OnTxMTE4OTkxNixYwkNDSU7O5tGjRrRsGFDNm3aBMC9997LxYsXOXHiBCaTiQkTJhAWFsb169fx9/enRYsW1u9hbGwsaWlpREVFATBu3DhWrVpFWloafn5+tGvXjtWrVwPQtWtX0tPTOXz4MECp24iEhARCQkJK1EbcfffdeHh4lLqNSE5OBihRG7Fo0SKysrLKpI2wHHtJ2ohRo0YRHh5eqjbCfOOysVOnTlmzuV0b4eXlxY4dOwAYMGBAqduIhIQEdu7cWaI2olmzZqxfvx4oWRvR99tv8XnlFRxTUzGbTDhoGprJhEnTyHZ3J3v2bJampUFIiO02Yt8+rmRkUHPQIHp+8AErQ0LwOXGCNsnJuO3di/OBA1S5dAkWLtQXINvdHYdevThUvTrxzZvjN3w4rl5e7Nq1i4SEBJKTk0vURkRFRXH27NlStRH+/v6A3s47ODgUq41Yt24dAN27d+fKlSulbiOuX7/O1atXy/08wlYbkZmZSUhISLmfRxTWRri6urJ3795yP4+4tY3o1KmTNXfL4/I4jyiqjahTp45dziNstRGWdra8zyOuXLlCzZo1C5xHODk5WY+9PM8jbm0jFi1aZM26Xr165XYeUVQbkZqaSkhISLmfR9hqIxISEkhNTS338whbbYS7u7s18/I+j7i1jbDcySwlJYUNGzYA5XMeAbbbiIyMDEJCQuxyHmGrjXB3d2fXrl1lfh5RnDbC0taUtI0oi9817M2kaSUYty2Ul5qaipeXF/Hx8dSqVcuQfUhJScHLy0u52kbWz8zMZNq0abz++us4OzvbvT5I7pK7WrWNrK9k7hkZEBoKS5aQEx+Po68vjBoFY8feHLlUmm3v3q2PbtqyBbZtK3gnOldXuOce6NWLtI4d8ejfH9zdS1e3hJTMvYLUNrK+5C65S+7q1DY6d1U/b0bXvnz5Mr6+vqSkpODp6Vnu9WQOJlHpWP4qp1rtilDfSJK7miR3Ndn92F1cYNIkWLSIhU8/DYsW6f8ubeeSZdv33gv/+hesWQNJSbBnjz5J+KhR+h3orl+HTZvg3XfxCAqC6tUhMBBefRVWrNDfowD5vKtJcleTqrlL5mrWN/rY7UkukRNCCCGEsBdHR+jUSV9eekmf++noUescTtfWrMH9yhX48099+ewzfS6oNm30jirLPE533WX0kQghhBBC5CMdTKLS6dKli5K1K0J9I0nuapLc1aRU7iYTtGqlL08+yYUTJ2ji5HRz0vAtW+DYMTh4UF9mzNDf16TJzc6mXr2gUaPb3xHPlowMWLgQx8WLeTgiAsf9+2H0aP0ue2UxgqsElMq9gtU3kuSuJlVzl8zVrG/0sduTdDCJSicjI0PJ2hWhvpEkdzVJ7mpSOvfMTGjaFBo2hIce0p+8dEnvaLJ0Oh04ACdP6ssPP+jr+Pnl73Bq1arQO9VZLVsGU6ZAUhIODg40MpvRzp6FsDB44QX9LnjDh5fj0eandO7yeVeudkWobyRVc5fM1axv9LHbk8zBJCody10OVKtdEeobSXJXk+SuJsn9FrVr6xOOf/UVRETAlSuwciW8/jp07w5OTnD+PMybB888o19OV6sWBAXBF1/Arl2QnZ1/m8uWwciRcONuiaYbdw+0fCU5WX//smXldqy3ktzVJLmrSdXcJXM16xt97PYkI5iEEEIIISqT6tVhyBB9AX2S8J07b15St3273gm1bNnNDiJ3d33i8F69oFs3mDxZf76wmwlrmn7J3ZQpeueVnS+XE0IIIUTlY9K0ws4shCgoNTUVLy8v4uPjqVWrliH7kJGRgYtBJ7pG1jayvtG3NQXJXXJXq7aR9SX3v0Du2dn6SCdLh9OWLaW7E90vv+h31Stnkrt83lWqbWR9yV3N2kbnrurnzejaly9fxtfXl5SUFDw9Pcu9nvKXyJlMpmItffr0ue221qxZw+jRo6lXrx7Ozs7Uq1eP0aNHs2bNmmLvT3p6Op999hldu3bF29sbDw8PWrZsycsvv0xsbGyxt3PkyBGeeuopmjRpgqurK7Vq1aJXr15899135OTkFHs7FVF4eLiStStCfSNJ7mqS3NUkuZeSkxN07QovvwxLl0JCAhw6pE8QPn58yUYjOTjAkiWl36dikNzVJLmrSdXcJXM16xt97PYkl8iVAU3TeOqpp5g5c2a+5+Pi4liyZAlLlizhiSee4Ntvv8VUxB1eoqOjGTp0KMeOHcv3fFRUFFFRUcyePZu5c+cyxDIkvhDff/89zzzzDJmZmdbnMjIy2LJlC1u2bOGnn35ixYoV1KxZ8w6O1nhJpfkrbCWuXRHqG0lyV5PkribJvYw5OEDr1vry9NPQpw/88Ufx3ms2w+7dEBqqd1r5+9/Z3eqKQXJXk+SuJlVzl8zVrG/0sduTdDDd8Le//Y2nn3660Nfd3d0Lfe3NN9+0di516NCBV199lYCAAKKjo/n000+JiIhg5syZ1KpViw8++MDmNtLS0hg2bJi1c+nxxx9nwoQJuLq6smnTJj7++GNSUlIIDg5mx44dtG3b1uZ2fv/9d5544gnMZjO1a9fmX//6F926dePKlSvMmjWLxYsX8+effzJ69Gg2bdqEw+3uMFMB+fj4KFm7ItQ3kuSuJsldTZJ7OatZU+90skzofTtnz0JwsP64dm29o8mydOkCNWqUyW5J7mqS3NWkau6SuZr1jT52u9IUB2iA9s4779zR+0+cOKE5OjpqgNa5c2ctPT093+vXrl3TOnfurAGao6OjdvLkSZvbeeedd6z78umnnxZ4ffv27dY6ffv2tbmN7OxsrUmTJhqgeXp62qz19NNPW+vMmTOnxMebkpKiAVp8fHyJ31tWrl69qmRtI+tnZGRoU6dO1TIyMgypr2mSuxEkd8ndKJJ7Ofv5Z03Tp/Eu3tK/v6Z17Khpjo62X2/aVNMefFDTvvpK0/78U9OuX7+j3ZLc7U8+75K7UVTN3cjaRueu6ufN6Nrx8fEaoKWkpNilXuUbvlLBTJ8+3Tqn0ddff42rq2u+193c3Pj6668ByMnJ4csvvyywjezsbL766isAWrZsyT/+8Y8C6wQGBvLoo48CsGnTJvbu3VtgnSVLlnDy5EkA3njjDQICAgqs89lnn1Hjxl8aP/vss+IeZoWyfPlyJWtXhPpGktzVJLmrSXIvZ8HB+qij213qZjLp661YAXv3Qmqqfoe6L7+EBx6AJk309U6cgN9+gxdegHvuAU9PfWTTM8/AnDlw9GixRktJ7mqS3NWkau6SuZr1jT52e5IOplLQNI2lS5cC0KJFC+655x6b691zzz00b94cgLCwMLRbbtwXHh5OcnIyAJMnTy70srUpU6ZYHy9evLjA62FhYTbXzcvNzY1x48YBcPjwYU6cOGFzPSGEEEL8Rbm46B0/UHgnk+X5OXNuTgru6gqBgXpH0m+/6R1LCQmwZg289x4MGwa1aul3sduzB/73P5gyBVq10juq+veHN97QJw2Piyv3wxRCCCGEfckcTKUQExND3I0TpN69exe5bu/evTl27Bjnzp3j9OnTNGrUyPrali1b8q1XmM6dO+Pu7s61a9fYunVrgdct22nevDl16tQpcl++++47ALZu3UrTpk2L3PeKpkOHDkrWrgj1jSS5q0lyV5PkbgfDh0NYmN4BlJSE5uCAyWy2fqV6db1zafjwordTsyYMHKgvoF80d+YM7Np1c7GMftq4UV8s6tbNN59TJwPPR5TJvQKSz7uaVM1dMlezvtHHbk/SwXTDwoULCQkJITY2FkdHR+rUqUP37t2ZMmUKffv2tfmeo0ePWh+3aNGiyO3nff3o0aP5OpiKux1HR0cCAgI4ePBgvveAPkn4uXPn7mhfhBBCCKGgESPg/HkIDcW8aBGx+/dTv317qowZA2PH3hy5VBImEzRsqC83RkyTkwORkfk7nQ4d0kcxLVmiL0BTkwlatMg/iXjbtlC1apkdshBCCCHKj1wid0NkZCTHjx8nIyODtLQ0Tp48yc8//0y/fv0YNWoUKSkpBd5z9uxZ6+N69eoVuX1/f3+b78v7b3d3d6pXr16s7Vy+fJnMzEzr8+fOnbNeeleafakMIiIilKxdEeobSXJXk+SuJsndjlxcYNIkcubN4+cpU8iZNw8mTbqzzqXCODrqHUWPPQYzZ8L+/fqIps2b4fPP9Y6ohg0xaZo+X9OcOfr8TV266PM53XpZ3i1TDdyxjAz45RcYM4Yao0fDmDH6vzMyymb7JWD0z52R5POuJlVzl8zVrG/0sduT8iOY3NzcGDFiBP3796dFixZ4eHhw+fJl/vjjD7799lsSExMJCwsjKCiIdevW4eTkZH3v1atXrY89PDyKrOPu7m59nJaWlu81y3Zutw1b23F2di7TfblVZmZmvo6s1NRUm8/bU25urpK1jaxvqanisRtd28j6krvkbhTJXYHcHR1vjlK6Ydns2YysWxfT7t047NmDac8eTFeuwJ9/6ssNWo0aaJ06Ye7cGa1LF8ydO0Pt2iUq77BiBY6PPYYpORnNwYHaZjPasWOYFi9Ge/55cr7/HvPQoWV2uLejTO42yOddcpfa9mF07qp+3oyube+6Ju3WGacVk5ycXOiooUuXLjF48GBrj+NXX33F888/b339/fff5+233wZgw4YN9OvXr9A6GzdupH///tb3vfnmm9bXAgICOHXqFP7+/sTGxha5vw8//DC//PILoI8+soxW2rJlC7169QLgrbfe4r333it0G2azmSpVqgDQv39/1q9fX+i6U6dO5d133y3w/Ouvv45LWf51UwghhBAiL02jRlISdc+do25cHHXj4rjrwgUcc3MLrJrs5UVc3brW5cJdd5F9449wt2oWFcWEefMAsDXFueXEeN6ECRy/zbQDQgghREWWkZHBtGnTSElJwdPTs9zrKT+CqahL0mrXrk1oaCgtW7YkKyuLr7/+Ol8HU94OlqysrCLr5O05dHV1zfeaZTu320ZR2ymrfbnVG2+8wd///nfrv1NTU/H39+eZZ56hVq1at93f8rBx48YiO/P+qrWNrJ+Zmcn06dN56aWXrKPm7E1yl9xVqm1kfcldcq/IuedmZ2M+fBjTnj047N6tj3I6epTqKSlUT0nh7shIADQHB7RWrdA6d7aOdNLuvhtycqjasCGYTPoleTaYAM1kYsKaNWR9+23ZXi5YCMldPu/2JLmrWdvo3FX9vBld+/Lly0ybNs1u9ZTvYLqdxo0bc//997Ny5UpOnjzJ+fPn8fPzA6BatWrW9W53qdm1a9esj2+9hM2yndtto6jtlNW+3MrZ2dlmA1TY8/aQnJysZO2KUF9yN4bR9SV3YxhdX3I3htH1K3zuzs5wzz36YpGaqt+pLs8k4qZz5zAdPgyHD1Plp5/09Vxdwd8fkpNvuy8mTYPkZJyXL9fnpCpnkrt6tStCfcldrdoWRuVu9LGrmru968ok38XQqlUr6+O4uDjr47yTaVvu4FaYvJNp551kO+92rl27RvJtTnos26lVq1a+H5ay2pfKoEaNGkrWrgj1jSS5q0lyV5PkrqY7PnZPT+jbF157DRYtgrNn9TvUhYXBP/8J992nr3P9Ohw/XvztOjhY73BX3iR39WpXhPpGUjV3yVzN+kYfuz1JB1MxFDZNVd6Op6ioqCK3kff1li1b3tF2cnJyiI6OtrkNDw8Pa2dRafalMujTp4+StStCfSNJ7mqS3NUkuaupTI/dzw+CguDDD2HdOkhKgqgoKMmcSmYzHDmi3/WuGNMYlIbkrl7tilDfSKrmLpmrWd/oY7cn6WAqhsgb1/MD1svjABo1amT99x9//FHkNjZv3gxA3bp1adiwYb7XevbsaX1c1Hb27NljvbytR48eBV63bOfYsWNcvHix0O3krWFrOxXdEjv9NbGi1a4I9Y0kuatJcleT5K6mcj12Bwdo3hxatdIfF9exY9ChA3h4QPv2MGUKfPklhIfrnVZlRHJXr3ZFqG8kVXOXzNWsb/Sx25N0MN3GqVOnWLduHaDPx1S3bl3rayaTiaCgIEAfFfRnnlvo5vXnn39aRw0FBQVhMuW/Z0mfPn3w8vICYM6cOYWOmPrJMocAMGrUqAKvjxw50ua6eaWnp7NgwQJAHznVrFkzm+sJIYQQQvzljBypj0wqrhYtoHp1yM6GAwdgzhx46SX9kjxvb2jUCEaNgnffhaVL4cwZUPsGzUIIIRSmdAfT8uXLycnJKfT1S5cuMXbsWLKzswF45plnCqzz4osv4uioz5X+3HPPcf369XyvX79+neeeew4AR0dHXnzxxQLbqFq1qvXudEePHuXzzz8vsM6OHTv4/vvvAejduzddunQpsM6oUaMICAgA4OOPP7ZeTpfXK6+8QtKNv7i98sortg+8gmvTpo2StStCfSNJ7mqS3NUkuavJLsceHAw1asAtf+wrwGTS14uIgCtX4PRpfU6nqVP1TirLaHRbz3t76x1QL72kd0gdOHDbS+wkd/VqV4T6RlI1d8lczfpGH7s9KX0Xueeee47s7GzGjBlDYGAgDRs2xNXVlYSEBMLDw/n2229JTEwE9MvPbHUwNWvWjJdffplp06axZ88eevTowWuvvUZAQADR0dF88sknREREAHqHTtOmTW3uyyuvvML8+fM5fvw4r776KidPnmTChAm4urqyadMmPvroI3JycnB1deXLL7+0uQ0nJyf+85//MHz4cFJTU+nRowdvvvkmXbt2JSkpiVmzZrFo0SLr8Tz00ENl8F20Pxc73C64ItauCPWNJLmrSXJXk+SuJrscu4uL3ukTFKR3ItkabWTpfJozR18foEEDfbkxch3QL5E7eFCfo8myHDmi36UuPFxfLJyc4O679cvsLEu7dvroKCR3FWtXhPpGUjV3yVzN+kYfuz0p3cEEcP78eb7++mu+/vrrQtcZM2YMs2fPLvQWfx9++CHx8fH88MMPREREMGHChALrPProo3zwwQeF1qhWrRorV65kyJAhnDhxgpkzZzJz5sx863h6evLbb7/Rvn37QrczZMgQvv32W5599lkuXbpkHT2VV9euXVmyZAlVqlQpdDsV2e7du2nSpIlytStCfSNJ7pK7SrUrQn0jSe6Se7kaPlwfdTRlit5J5OCgXzZn+Vq9ut65NHx40dupUQN699YXi6wsiIzM3+m0fz+kpNx8nFfDhtC+PderVIGHHtI7nurXv/0Iq78Q+bzL511qq8HoY5fc7UPpDqY5c+bwxx9/sGPHDk6dOkVCQgKpqanWO7J1796dyZMnExgYWOR2HBwc+P777xkzZgwzZ85k9+7dJCQk4OPjQ5cuXXjyyScZPHjwbfenSZMmREREMGPGDBYuXMjJkyfJysrC39+fIUOG8MILL9CgQYPbbufxxx8nMDCQ//znP2zYsIHz58/j7u5Oy5YtefDBB3nsscesl/UJIYQQQihnxAg4fx5CQ2HJEi4dPUrtli31+ZTGjr05cqmkqla9OULJQtP0uZlu7XQ6c0a/xO70adoA3BhlTvXq+Uc6tW8PLVvq2y4rGRmwcCGOixfzcEQEjvv3w+jR+iWECv2lXQghRNkyaYXNKC2EDampqXh5eREfH0+tWrUM2YeUlBTrpOgq1TayfmZmJtOmTeP1118vdCRfeZPcJXeVahtZX3KX3CV3O0lK0udn2r+frF27qBoZqV9iZ2t+0KpVbV9idyf7vGyZdfSW5uCAyWy2fqVGjeKN3ipDyuVeAerL513N2kbnrurnzejaly9fxtfXl5SUFDw9Pcu9ntKTfIvKad++fUrWrgj1jSS5q0lyV5Pkriblcq9RA/r0gRdfZNvjj+ujmtLSYN8++OEHeP556NULPD31S+8iIuDHH+GFF/TL8qpXh8aN9ZFH772ndxzFxhZ9F7tly/TJyJOTAfROpTxfSU7W55latqz8jvsWyuVegeobSdXcJXM16xt97PYk10mJSufixYtK1q4I9Y0kuatJcleT5K4myR1wdoYOHfTFQtP0S+luvcQuNhZiYvRlyZKb69eoYfsSu9xcfeSSZZu2aJo+/9OUKfolhHa4XE5yV5OquUvmatY3+tjtSTqYRKVTrVo1JWtXhPpGktzVJLmrSXJXk+ReCJMJGjXSl1Gjbj5/5Yr1EjvrEhmpX3q3aZO+WFStCnfdpb92O5qmrxcaCpMm3eERFZ/kriZVc5fM1axv9LHbk3QwiUpn0KBBStauCPWNJLmrSXJXk+SuJsm9hLy9oW9ffbHIzLx5F7uIiJsdT1ev6pOKF5eDgz4qyg4dTJK7mlTNXTJXs77Rx25PMgeTqHQWLlyoZO2KUN9IkruaJHc1Se5qktzLgOUSu//7P/jPf2DzZn1epehofZLw4jKb9fe+/TbMnw+HD+vzQJUDyV1NquYumatZ3+hjtycZwSSEEEIIIcRflYODPhl48+Zw9KjeeVQcCQnw/vs3/+3oCM2a6R1VeZcmTcDJqXz2XQghRKUiHUyi0mnVqpWStStCfSNJ7mqS3NUkuatJci9nI0fC4sXFX/+BB/RJvo8c0Ze0NP3yu8hIyPvXeCcnvfPq1o6ngAC9U+o2JHc1qZq7ZK5mfaOP3Z6kg0kUy4wZM5gxYwa5ubkAhIWF4eHhwejRo9mwYQMpKSn4+vrStWtXVqxYAUDHjh0xm83s378fgKCgILZu3UpiYiLe3t706tWLsLAwANq2bYuTkxN79+4FYOjQoezZs4dLly7h6enJgAEDCA0NBcDX15dTp06xc+dOAAYOHMjhw4eJi4vD3d2dYcOGMX/+fACaN2+Oj48P27ZtA+C+++7j+PHjxMbG4uzszOjRo5k/fz5ms5mAgADq1q3L5s2bAejTpw+xsbGcOnUKR0dHgoODOXDgAJGRkTRo0ICAgAA2btwIQM+ePYmPj+f48eMATJw4kaVLl5Kenk69evVo1aoVa9euBSAwMJCUlBQiIyMBCA4OZs2aNVy9epU6derQsWNHVq1aBUCXLl3IyMjg0KFDAHTq1Ik1a9aQlJSEj48PgYGBLF++HIAON+44ExERAcDw4cPZsWMHCQkJ1KhRgz59+rDkxl1m2rRpg4uLC7t37wZgyJAh7Nu3j4sXL1KtWjUGDRpkHcrZqlUrXF1dAQgNDWXQoEFERkZy7tw53NzcCAoKIiQkBIBmzZrh6+vL1q1bAejXrx/R0dGcOXOGqlWrMmbMGBYuXEhOTg6NGzemfv36hIeHA9CrVy/i4uKIjo7GwcGB8ePHs3jxYjIzM6lfvz7u7u7WOj169CAhIYFjx44BMH78eFasWMG1a9eoW7curVu35vfffwegW7dupKWlceTIEQDGjh3L2rVrSU1NpXbt2nTu3JmVK1dav7/Z2dkcPHgQgJEjR7J582bOnTvHpUuX6NmzJ0uXLgWgffv2ODg4WG87OmzYMHbt2kV8fDxeXl7079+fxTdO5Fu3bo2bmxu7du0CYPDgwRw4cIDz58/j4eHBkCFDWLBgAQAtWrTA29ub7du3A3D//fcTGxtLZGQkrq6ujBw5knnz5qFpGk2bNqVOnTps2bIFgL59+3L69GliYmJwcnJi7NixhIaGkp2dTaNGjWjYsCGbbkz6eu+993Lx4kVOnDiByWRiwoQJhIWFcf36dfz9/WnRooX1exgbG0taWhpRUVEAjBs3jlWrVpGWloafnx/t2rVj9erVAHTt2pX09HQOHz4MUOo2Ys+ePURGRpaojbj77rvx8PAodRuRk5NDu3btStRGLFq0iKysrDJpIyzHXpI2YtSoUYSHh5eqjTDfGN1w6tQpaza3ayO8vLzYsWMHAAMGDCh1G5GamkpGRkaJ2ohmzZqxfv36UrcRXbp0YeXKlSVqI65cuULNmjXLpI1IT0+nQYMGJWojoqKiOHv2bKnaCH9/f0Bv5x0cHIrVRqxbtw6A7t27c+XKlVK3Ec7OzjRu3LjczyNstRGnT58mMjKy3M8jCmsjAgIC2Lt3b7meRziYzYyrXh1SUjAVdhc5QAOy3N3J/uordkRE6G1E9er0CQjgz++/x+vcORpeu4ZrTAxVjh3DKTNTv4TuRqYWuU5OpN51l7XD6ZDZTEq9enR/8EEijx2zthHt2rWzy3mErTYiIiKCyMjIcj+PKKyNSE1NtR57eZ5H3NpGLFq0CND/P6hXr165nUcU1UZERkYSGRlZ7ucRttqI9PR0GjVqVO7nEbbaCAcHB2vm5X0ecWsbkZKSAkBKSgobNmwAyuc8Amz/rhETE0NkZKRdziNstRFNmzZl165d5X4eYauNsJzT2eM8AvK3EXanCVECKSkpGqDFx8cbtg9z585VsraR9TMyMrSpU6dqGRkZhtTXNMndCJK75G4Uyd3+JHdFcl+2TNNMJn3R7xeXf7G8tmxZ8baXm6tpMTGatmKFpk2bpmkPPaRpHTtqmqur7e2Dprm4aFqHDpo2aZKmffyxFv6Pf2hadLS+LTtTJvdbyOddzdpG567q583o2vHx8RqgpaSk2KWejGASQgghhBBCBcOHQ1gYTJkCSUloDg6YzGbrV6pXhzlz9PWKw8EBGjbUl6FDbz6fmwunT9+8vM6yHD0KGRn6He5ujILoDfDFF+DmBi1bFrzUrn59vU5ZycjQL/ELC6Pf0aMQGqpfPhgcrF8SKIQQ4o5JB5OodAYMGKBk7YpQ30iSu5okdzVJ7mqS3O1kxAg4fx5CQzEvWkTs/v3Ub9+eKmPGwNixZdPJUqWKPgdTQIBezyI3F06dytfplHPwII4nTkB6Ouzdqy95eXhAq1YFO57q1QOTqWT7tWyZtXMNBwdqm81w7Jg+N9ULL5Ssc60MGP1zZyRVP++SuZr1jT52eyrDPwcIYR+W64lVq10R6htJcleT5K4myV1NkrsdubjApEnkzJvHz1OmkDNvHkyaVP4jeKpUgaZN9RFD//oXzJ3Ljm++gWvXICpKH0307rswbpzeieTkpE8uvmsX/PgjvPwyDB6sj2qqXh0CA+Gxx2D6dFi7FuLi9AvxbFm2TK+bnKz/23I3PcvX5GQICtLXsxOjf+6MpOrnXTJXs77Rx25PMoJJVDrnzp1TsnZFqG8kyV1NkruaJHc1Se5qOnfunH63uebN9WXMmJsvZmfDiRMFL7U7fhxSU+HPP/Ulr+rVb454at365h3tpkzRXy+sA0rT9BFRU6boI7zscLmc8rlLbaUYfeySu31IB5OodNzc3JSsXRHqG0lyV5PkribJXU2Su5qKPHYnJ72zqFUrfY4ki6wsvZPp1o6nEyf0kUjbt+tLSWmafvlcaKg+oqucSe5SWyVGH7vkbh/SwSQqnaCgICVrV4T6RpLc1SS5q0lyV5PkrqY7OvaqVfXRSa1b538+I0OfU+nWjqeTJ4u/bZMJfvpJH0nl6lryfSsByV1qq8ToY5fc7UPmYBKVTkhIiJK1K0J9I0nuapLc1SS5q0lyV1OZHruLC7RrBw88AB9+qN8x78QJuPfe4m9D02DDBnB31++ON3AgPP88zJgB69fD2bM3520qJcldaqvE6GOX3O1DRjAJIYQQQggh/rpq1QIHh+J3DDk56fM/nTmjL2vX5n/dzQ2aNbs5b1Tz5jf/Xa1a2e+/EEJUEtLBJCqdZs2aKVm7ItQ3kuSuJsldTZK7miR3Ndnl2EeOhMWLi7/+99/rI5eOHbu5HD+uf42OhvR02L9fX2511135O54sS8OG+l308pDcpbZKjD52yd0+pINJVDq+vr5K1q4I9Y0kuatJcleT5K4myV1Ndjn24GB44QV9AvDC7iIH+vxL1avr67u4gK9vwcvrsrMhJiZ/55NliY+HCxf0JTw8//uqVoUmTfKNeKpXvbre8VSzZpkebqEyMmDhQhwXL+bhiAgc9++H0aNvHq8dqfp5l8+6mvWNPnZ7kjmYRKWzdetWJWtXhPpGktzVJLmrSXJXk+SuJrscu4sLzJmjPzaZbK9jeX7OnKI7W5yc9Mvhhg+Hl1+GWbNg82a4dEm/A93OnfDzz/Cvf8HYsdCmjb69rCyIjIQlS2DaNHjkEWqPHg0+PvrSowc88gh88ok+d9TRo/p7ysqyZeDnBw8/jMOyZTQ6cwaHZcvg4Yf155cvL7taxaDq510+62rWN/rY7UlGMAkhhBBCCCH+2oYP1ztupkzRO4IsczJZvlavrncuDR9+5zWqV4euXfUlL7MZYmMLXHJ3LSIC98RESEyE7dv1Ja8qVaBRo/xzPFmWOnUK7yy71bJl+mWCN5huzEVl+UpyMgQF6d+fESPu5MiFEAKQDiZRCfXr10/J2hWhvpEkdzVJ7mqS3NUkuavJrsc+YgScPw+hobBkCZkXL+Jcpw6MGqWPNiqvy8QcHPRL4Sx3pbsh7dIl3D089Dvd2brkLi0NTp7Ul5Ur82/T07Ngp1Pz5tC0qT4JuUVGht6pBoVfHqhpemfVlCn698cOl8up+nmXz7qa9Y0+dnuSDiZR6URHR1O7dm3laleE+kaS3CV3lWpXhPpGktwld5VqV4T6RrL7sbu4wKRJMGkSe7dvp3v37varfYvo6Ghqd+8O7dvrS16aBhcv2u54iomB1FTYs0dfblW//s3Op5QUfcTW7Wiavl5oqP79KWeqft7ls65mO2v0sduTzMEkKp0zZ84oWbsi1DeS5K4myV1NkruaJHc1Se6FMJn0O9L16QNPPgn//rc+iunkSf0udkeO6HfG+/hjfeRR9+43JwuPjYX162HGDPj11+LvkIODPkeUHaiau9E/c0Yy+tgld/uQEUyi0qlataqStStCfSNJ7mqS3NUkuatJcleT5H4HnJ2hVSt9uVViYv7RTrNn688Vh9kMf/wB//iHfse7gAB9adAAHMv210ZVczf6Z85IRh+75G4fJk0r6l6dQuSXmpqKl5cX8fHx1KpVy+jdEXaSmZnJtGnTeP3113F2djZ6d4SdSO5qktzVJLmrSXJXwJgx+uTdlgm974Sjo97JlLfTyfK4cWNwdS2z3RXlRz7varp8+TK+vr6kpKTg6elZ7vVkBJMolhkzZjBjxgxyc3MBCAsLw8PDg9GjR7NhwwZSUlLw9fWla9eurFixAoCOHTtiNpvZv38/AEFBQWzdupXExES8vb3p1asXYWFhALRt2xYnJyf27t0LwNChQ9mzZw+XLl3C09OTAQMGEBoaCkBaWhr9+/dn586dAAwcOJDDhw8TFxeHu7s7w4YNY/78+QA0b94cHx8ftm3bBsB9993H8ePHiY2NxdnZmdGjRzN//nzMZjMBAQHUrVuXzZs3A9CnTx9iY2M5deoUjo6OBAcHM336dOrUqUODBg0ICAhg48aNAPTs2ZP4+HiOHz8OwMSJE1m6dCnp6enUq1ePVq1asXbtWgACAwNJSUkhMjISgODgYNasWcPVq1epU6cOHTt2ZNWqVQB06dKFjIwMDh06BIDJZKJ69eokJSXh4+NDYGAgy2/cVrZDhw4AREREADB8+HB27NhBQkICNWrUoE+fPiy5Mey5TZs2uLi4sHv3bgCGDBnCvn37uHjxItWqVWPQoEEsXLgQgFatWuF648QhNDSUQYMGERkZyblz53BzcyMoKIiQkBAAmjVrhq+vr/VWnP369SM6OpozZ85QtWpVxowZw8KFC8nJyaFx48bUr1+f8PBwAHr16kVcXBzR0dE4ODgwfvx4Fi9eTGZmJvXr1ycmJoYqVaoA0KNHDxISEjh27BgA48ePZ8WKFVy7do26devSunVrfv/9dwC6detGWloaR44cAWDs2LGsXbuW1NRUateuTefOnVl5Y+LMTp06kZ2dzcGDBwEYOXIkmzdv5vDhw7Rp04aePXuydOlSANq3b4+DgwP79u0DYNiwYezatYv4+Hi8vLzo378/ixcvBqB169a4ubmxa9cuAAYPHsyBAwc4f/48Hh4eDBkyhAULFgDQokULvL292X7jTjL3338/CxcupHr16ri6ujJy5EjmzZuHpmk0bdqUOnXqsGXLFgD69u3L6dOniYmJwcnJibFjxxIaGkp2djaNGjWiYcOGbNq0CYB7772XixcvcuLECUwmExMmTCAsLIzr16/j7+9PixYtrN/D2NhY0tLSiIqKAmDcuHGsWrWKtLQ0/Pz8aNeuHatXrwaga9eupKenc/jwYYBStxH/+9//8PPzK1Ebcffdd+Ph4VHqNuLSpUu8+OKLJWojFi1aRFZWVpm0EevXr8fPz69EbcSoUaMIDw8vVRthvvFLyKlTp6zZ3K6N8PLyYseOHQAMGDCg1G1EbGwsPXv2LFEb0axZM9avX1/qNsLBwQEPD48StRFXrlyhZs2aZdJGnD9/nkcffbREbURUVBRnz54tVRvh7+8P6O28g4NDsdqIdevWAdC9e3euXLlS6jYiMTGRyZMnl/t5hK02Yt68edSoUaPczyMKayOysrJo3bp1uZ9H3NpGdOrUyZq75XF5nEcU1UZkZWWRk5MDlO95hK02YtOmTfj5+ZX7eURhbcSOHTus51jldR4xrH9/qt3YTnHEDxnCFU3D8/Jl/K5fJ/f4capkZ0N0tL7YkO7tjVvr1pxxciK5Zk2cW7Wids+ebIiJIdvd3WYb8d///hdfX99yP4+w1UacP3+exx9/vNzPI2y1EVFRUTg5OQHlfx5xaxuRkpICQEpKChs2bADK5zwCbLcRv/76K97e3nY5j7DVRmRnZ9OiRYtyP4+w1UbMmjULPz8/u5xHQP42wu40IUogJSVFA7T4+HjD9mHu3LlK1jayfkZGhjZ16lQtIyPDkPqaJrkbQXKX3I0iuduf5C65G0VyL2fXr2tajRqaZjJpmj6Vt+3FZNLXu349//tzczXt3DlNCw/XtO+/17R//lPTxo3TtE6dNM3Lq+htgqZ5e2ta166aNnGipr31lqb99JOmbdmiLf7f/zTNbC7/48/7ffj5Z00bPVq72LKlpo0erf/71uMtZ0b+zBn9eVfi81YBa8fHx2uAlpKSYpd6MoJJVDqNGzdWsnZFqG8kyV1NkruaJHc1Se5qktzLmYsLzJkDQUH6xOG2ZkcxmfSvc+bo6+fl4AB16+pL7975X9M0uHJFH9l08uTNUU6Wxxcv6q/v2qUveYwCeOUV/RI7y+V2eS/B8/cvu3mfli3TJ0JPSgIHB2qbzfr8VIsXwwsv6Mc9fHjZ1LoNo3/mjGT0savc1tiTdDCJSqd+/fpK1q4I9Y0kuatJcleT5K4myV1NkrsdDB+uz8N0o5NFc3DAZDZbv1K9+p11sphM+p3rataErl0Lvp6WBqdO5e90uvFVi43FdO0aHDqkL7dycoKGDQt2PDVpAo0aFewIK8yyZTBy5M1/W+aisnxNTtY738LCYMSI4h/7HTL6Z85IRh+7ym2NPTkYvQNClJTlOlrValeE+kaS3NUkuatJcleT5K4myd1ORoyA8+fhl18wjxhBTMOGmEeMgF9+0Z8vjxE8Hh7Qti2MGqWPVvr2W1i/HmJiWPDTT/ooolWr4D//0UcSDRsGLVpA1aqQnQ0nTsCaNfDf/8JLL+nH0KoVuLlB/frQty889hhMmwYLF0JEBKSm3qyfkaF3qoHtkVt5n58yRV+/nBn9M2cko49d5bbGnmQEkxBCCCGEEEL81bm4wKRJ5AQH8/ONu4lVMehuYmZHR2jWTF9ulZsLcXEFL7mzPL56Fc6e1Rdbv7j7+OgjnUwm/bK429E0fb3QUJg0qdTHJoTKpINJVDq9evVSsnZFqG8kyV1NkruaJHc1Se5qktzVVOSxV6mij1CyjFLKS9MgIcH2nE8nT8Lly/rrCQkl2yEHB1iwoNw7mCRzNesbfez2JJfIiUonLi5OydoVob6RJHc1Se5qktzVJLmrSXJX0x0fu8kEtWpBYKDeGfTOO/plftu3Q3w8pKTol8otXKjP1VRcZjMsXw7e3tCxI4wZA//4B3z9NaxYAYcP63NKlZJkrmZ9o4/dnqSDSVQ60dHRStauCPWNJLmrSXJXk+SuJsldTZK7msrt2D09oX17GDsWOnTQRyaVRFKS3kG1eDH8+9/w/PP6/FRt2kC1anrnVpcuMG4cvPoq/O9/sHo1HD0K6em33bxkrmZ9o4/dnuQSOVHpOJT0P4q/SO2KUN9IkruaJHc1Se5qktzVJLmryS7HPnKk3lFUXDNn6iOjTp+GmBj9a97HSUk3L7/bs8f2NmrX1u9+16iR/jXv4/r1jck8IwMWLsRx8WIejojAcf9+GD0agoOLfze+MmD0z7vKbY09mTStsCn1hSgoNTUVLy8v4uPjqVWrltG7I+wkMzOTaTcmg3Q2aDJIYX+Su5okdzVJ7mqS3NWkTO4ZGeDnB8nJhd9FDvTL7qpX1++mV1SHS0pKwU4ny+OYGH3y8dvx8yu8A8rfX7+DXllatky/Q15SEpqDAyaz2fqVGjVgzpzyuYOgqDAuX76Mr68vKSkpeHp6lns9dbrSxF/G4pL8JeIvVLsi1DeS5K4myV1NkruaJHc1Se5qssuxu7joHSigdyLZYnl+zpzbj+bx8oJ27SAoCF58Eb78EsLC4MABvfPpyhXYuxcWLYIvvoBnn4Vhw+Duu8HdXd/G+fP6fFG//QYffgiPPw733aff9c7VVZ/YvFcvmDxZn1/qxx/1O+WdPg05OSU7/mXL9FFcycn6oZrN+b6SnKwfy7JlJdvuHTL6513ltsae5BI5UelkZmYqWbsi1DeS5K4myV1NkruaJHc1Se5qstuxDx+udwLdGMWDg4M+obfla/XqZTOKx2TSRwTVqKFPEn4rTYPERH7/9lsGNm9ecBTU6dNw/TqcPasvW7YU3EaVKvoop1tHPlm++vnp64A+emvKlJu1bdE0fb+nTLn96K0yYPTPu8ptjT1JB5OodOrXr69k7YpQ30iSu5okdzVJ7mqS3NUkuavJrsc+YoTegRIaCkuWkBITg1ejRjBqlD4ZuD3mITKZwMcHj759oUePgq9rmn4XvLwdT7d2QGVl3Xxsi5OTPgKqYUPIztY71G5H0/T1QkP1u/KVI6N/3lVua+xJOphEpdOsWTMla1eE+kaS3NUkuatJcleT5K4myV1Ndj92Fxe9A2XSJLIuX9bvBmeAQo/bZNInCK9dG7p1K/i62QwXLxY+AfmZM3qnUnS0vpSEyQQ//6x3uFku5SsHRv+8q9zW2JPMwSQqnfXr1ytZuyLUN5LkribJXU2Su5okdzVJ7mpSNfc7ru3goF8C1707PPgg/OtfMGsWrF8PJ0/ql8TFxsLmzfolfw0bFn/bmgbr1oGHB/j4QIcO+txMzz0Hn30G8+fr80adOwe5uXe2/xj/814pc6+EZASTEEIIIYQQQghRWVnmZ/L3h3vvhaVL9Q4ny4Tet+PoqE8inpioL/v3F16nXj29Tv36N5e8//byKnxSdXvLyICFCyEsjH5Hj+qXAo4cCcHB9rk0UkHSwSQqnR62rltWoHZFqG8kyV1NkruaJHc1Se5qktzVpGrudqs9ciSU5M5lP/6oT3QeG6tPMh4be3Ox/PvcOb0T6swZfSlMtWoFO53q16df1apw6pTeQVW1aqkP8baWLcs3uXttsxmOHdO/Ly+8UDaTuxeTSp916WASlU5CQoJhE6UZWbsi1DeS5C65q1S7ItQ3kuQuuatUuyLUN5LkLrlL7XIQHKx3oiQnF34XOdBHGlWvfnOy8zZt9MWW3Fx9HqhbO6DydkIlJMDVq3DkiL7kUTtvzTp1ih4FVatW6UZBLVumd7JZWEZyWb4mJ+uXAYaF6ZPAlzOVPuvSwSSKZcaMGcyYMYPcG9fdhoWF4eHhwejRo9mwYQMpKSn4+vrStWtXVqxYAUDHjh0xm83svzHEMigoiK1bt5KYmIi3tze9evUiLCwMgLZt2+Lk5MTevXsBGDp0KHv27OHSpUt4enoyYMAAQkNDAUhNTaV69ers3LkTgIEDB3L48GHi4uJwd3dn2LBhzJ8/H4DmzZvj4+PDtm3bALjvvvs4fvw4sbGxODs7M3r0aObPn4/ZbCYgIIC6deuyefNmAPr06UNsbCynTp3C0dGR4OBgwsPDOXbsGA0aNCAgIICNGzcC0LNnT+Lj4zl+/DgAEydOZOnSpaSnp1OvXj1atWrF2rVrAQgMDCQlJYXIyEgAgoODWbNmDVevXqVOnTp07NiRVatWAdClSxcyMjI4dOgQALm5ucTHx5OUlISPjw+BgYEsX74cgA4dOgAQEREBwPDhw9mxYwcJCQnUqFGDPn36sGTJEgDatGmDi4sLu3fvBmDIkCHs27ePixcvUq1aNQYNGsTChQsBaNWqFa6urgCEhoYyaNAgIiMjOXfuHG5ubgQFBRESEgLoE9j5+vqydetWAPr160d0dDRnzpyhatWqjBkzhoULF5KTk0Pjxo2pX78+4eHhAPTq1Yu4uDiio6NxcHBg/PjxLF68mMzMTOrXr8+JEyc4duwYoP8VICEhwfrv8ePHs2LFCq5du0bdunVp3bo1v//+OwDdunUjLS2NIzf+kxs7dixr164lNTWV2rVr07lzZ1auXAlAp06dyM7O5uDBgwCMHDmSzZs3c+jQIRISEujZsydLly4FoH379jg4OLBv3z4Ahg0bxq5du4iPj8fLy4v+/fuz+MZfjlq3bo2bmxu7du0CYPDgwRw4cIDz58/j4eHBkCFDWLBgAQAtWrTA29ub7du3A3D//fezY8cOjh07hqurKyNHjmTevHlomkbTpk2pU6cOW27cyrZv376cPn2amJgYnJycGDt2LKGhoWRnZ9OoUSMaNmzIpk2bALj33nu5ePEiJ06cwGQyMWHCBMLCwrh+/Tr+/v60aNHC+j2MjY0lLS2NqKgoAMaNG8eqVatIS0vDz8+Pdu3asXr1agC6du1Keno6hw8fBih1G7Fx40aOHTtWojbi7rvvxsPDo9RtxIULF+jYsWOJ2ohFixaRlZVVJm2E5dhL0kaMGjWK8PDwUrUR5hsnX6dOnbJmc7s2wsvLix07dgAwYMCAUrcRZ86cITs7u0RtRLNmzaxzHJSmjTCbzVy4cKFEbcSVK1eoWbNmmbQRcXFxNG7cuERtRFRUFGfPni1VG+Hv7w/o7byDg0Ox2oh169YB0L17d65cuVLqNiIhIYGmTZuW+3mErTZi+/btHDt2rNzPIwprI65fv46maeV+HnFrG9GpUydr7pbH5XEeUVQbkZ6ebv2slud5hK02wtLOlvd5RGFtxN69e63HXp7nEbe2EYsWLbJmXa9evXI7jyiqjdi8eTPHjh0r9/MIW21EXFwcTZo0KffzCFttxJEjR6yZl/d5RPIjj9Dr3/8GkwmTjU4myzOx773H9huf7WKdR8TEADD8qacKtBHL5s3DLTGRuz09cUtIIH7PHtwTE/E3mUiLjKRaUhKO2dlw4YK+3PiZvpW5alXSvL3JrFWLWp06cSg1lfSaNanRrh3VWrViy+nT5Lq42GwjFv32G8OffBInsHnc+sFrYDKR9cADLJkxg3pNmpTZeYStNsLS1tjjPALytxF2pwlRAikpKRqgxcfHG7YPc+fOVbK2kfUzMjK0qVOnahkZGYbU1zTJ3QiSu+RuFMnd/iR3yd0okrv9Se4K1V66VNNq1NA00MwODvm+ajVqaNqyZXbblblz52qa2axp8fGatmePpi1ZomlffaVp//iHpgUHa9o992ian5+mmUz6/t1uqVlT09q317QRIzTt2Wc17dNPNS0kRNPeeqt477csv/xin2M3SHx8vAZoKSkpdqln0rSixswJkV9qaipeXl7Ex8dTy6Dbe5rNZhwcjLkBopG1jayfmZnJtGnTeP3113F2drZ7fZDcJXe1ahtZX3KX3CV3depL7pK75K5A7YwMCA0ld9EiYvfvp3779lQZM+bmZXF2Uuxjz8qCuLjC54M6c0a/DK8sODjol9LdGNVXXoz8mbt8+TK+vr6kpKTg6elZ7vWMa1GFuEOWYbGq1a4I9Y0kuatJcleT5K4myV1NkruaVM3dkNouLjBpEjnz5vHzlCnkzJsHkybZ/S5qxT72qlWhUSPo3Vvfz3/+E779FlatgkOHIDVVn0Pp4EFYsQK++QbeeAMefFC/g15JOk3NZli5Eu65R+9we+EF+OwzmDsXNm+G6Gi9g66UVPqsyxxMotK5du2akrUrQn0jSe5qktzVJLmrSXJXk+SuJlVzl8zLiJdX4ROSjxmjT95tmdD7djIzYedOfSlMzZr63e/q1i38q5dXoROTG5J7RgYsXIjjjfnC7EU6mESlU7duXSVrV4T6RpLc1SS5q0lyV5PkribJXU2q5i6Z28HIkXBj8utimToV2raFc+f0S/Nu/Xr9OiQm6suBA4Vvx9290A6o5lev6nfg8/XVL8srb8uWwZQpkJSEQ2nuxncHpINJVDqtW7dWsnZFqG8kyV1NkruaJHc1Se5qktzVpGrukrkdBAfrl7olJ+vTeBfGZILq1eG11wq/XFDTICnJdsdT3q9JSXDtGhw/ri+36Ajw5JPg6Ah+fkWPhPLzK9llfrdatkzvZLMcpp2n3JY5mESlY7klpGq1K0J9I0nuapLc1SS5q0lyV5PkriZVc5fM7cDFBebM0R8XNnrH8vycOUXPRWUygbe3fine4MHw2GP6iKdZs2D1an0eqCtXbnYubdoEv/wC06bBs8/CqFHQpQvpNWro28rJ0Scr37EDFi6EL7+El1+GiRP1+aMaN9b3x9cXOnaE4cPhb3+DDz6An36Cdevg6FF9HipbMjL0kUtQdOdaOZIRTEIIIYQQQgghhPhrGD5cn4fpxmViODjoczJZvlavrncuDR9eNvXc3KBpU32xYWlICBODg/XL5IoaCRUXp88JdfmyvkREFF6zWrWCI6Aso6kMJB1MotLp1q2bkrUrQn0jSe5qktzVJLmrSXJXk+SuJlVzl8ztaMQIOH8eQkNhyRKux8XhWreuPqpo7Fi73kWvW7du+uVx9erpS2E0TZ/r6XaX5KWkwNWrEBWlLxWIdDCJSictLU3J2hWhvpEkdzVJ7mqS3NUkuTODoCcAAD2tSURBVKtJcleTqrlL5nbm4gKTJsGkSZw4eJC2bdvafx8owbGbTODjoy/t2hW1Qb2zydLhZOl8mj9f76AykMzBJCqdI0eOKFm7ItQ3kuSuJsldTZK7miR3NUnualI1d8lczfplXtvDA5o3h3794OGH4Z//hBkzoHdv+9ylrgjSwSSEEEIIIYQQQghRmY0cqc8xZSDpYBKVztixY5WsXRHqG0lyV5PkribJXU2Su5okdzWpmrtkrmZ9u9UODgbLHesMIh1MotJZu3atkrUrQn0jSe5qktzVJLmrSXJXk+SuJlVzl8zVrG+32i4u+t3xwLBOJulgEpVOamqqkrUrQn0jSe5qktzVJLmrSXJXk+SuJlVzl8zVrG/X2sOHQ1gYVK8OgGbnjibpYBKVTu3atZWsXRHqG0lyV5PkribJXU2Su5okdzWpmrtkrmZ9u9ceMQLOn4dffsE8ZIhdSzvatZoQZaBz585K1q4I9Y0kuatJcleT5K4myV1NkruaVM1dMlezviG1XVxg0iRyBg4EX1+7lZURTKLSWblypZK1K0J9I0nuapLc1SS5q0lyV5PkriZVc5fM1axv9LHbk4xgEsUyY8YMZsyYQW5uLgBhYWF4eHgwevRoNmzYQEpKCr6+vnTt2pUVK1YA0LFjR8xmM/v37wcgKCiIrVu3kpiYiLe3N7169SIsLAyAtm3b4uTkxN69ewEYOnQoe/bs4dKlS3h6ejJgwABCQ0MB/RrWU6dOsXPnTgAGDhzI4cOHiYuLw93dnWHDhjF//nwAmjdvjo+PD9u2bQPgvvvu4/jx48TGxuLs7Mzo0aOZP38+ZrOZgIAA6taty+bNmwHo06cPsbGxnDp1CkdHR4KDg7lw4QIhISE0aNCAgIAANm7cCEDPnj2Jj4/n+PHjAEycOJGlS5eSnp5OvXr1aNWqlXVyt8DAQFJSUoiMjAQgODiYNWvWcPXqVerUqUPHjh1ZtWoVAF26dCEjI4NDhw4BkJuby5o1a0hKSsLHx4fAwECWL18OQIcOHQCIiIgAYPjw4ezYsYOEhARq1KhBnz59WLJkCQBt2rTBxcWF3bt3AzBkyBD27dvHxYsXqVatGoMGDWLhwoUAtGrVCldXVwBCQ0MZNGgQkZGRnDt3Djc3N4KCgggJCQGgWbNm+Pr6snXrVgD69etHdHQ0Z86coWrVqowZM4aFCxeSk5ND48aNqV+/PuHh4QD06tWLuLg4oqOjcXBwYPz48SxevJjMzEzq169PZmamtU6PHj1ISEjg2LFjAIwfP54VK1Zw7do16tatS+vWrfn9998B6NatG2lpaRw5cgTQ7+Kwdu1aUlNTqV27Np07d7Y2+p06dSI7O5uDBw8CMHLkSDZv3kxcXBxr166lZ8+eLF26FID27dvj4ODAvn37ABg2bBi7du0iPj4eLy8v+vfvz+LFiwFo3bo1bm5u7Nq1C4DBgwdz4MABzp8/j4eHB0OGDGHBggUAtGjRAm9vb7Zv3w7A/fffz5UrVwgJCcHV1ZWRI0cyb948NE2jadOm1KlThy1btgDQt29fTp8+TUxMDE5OTowdO5bQ0FCys7Np1KgRDRs2ZNOmTQDce++9XLx4kRMnTmAymZgwYQJhYWFcv34df39/WrRoYf0exsbGkpaWRlRUFADjxo1j1apVpKWl4efnR7t27Vi9ejUAXbt2JT09ncOHDwOUuo2Ii4sjJCSkRG3E3XffjYeHR6nbiAsXLgCUqI1YtGgRWVlZZdJGWI69JG3EqFGjCA8PL1UbYb5xe9tTp05Zs7ldG+Hl5cWOHTsAGDBgQKnbiLi4OHbu3FmiNqJZs2asX78eKF0bYTabWblyZYnaiCtXrlCzZs0yaSPi4uJITk4uURsRFRXF2bNnS9VG+Pv7A3o77+DgUKw2Yt26dQB0796dK1eulLqNSEhI4OrVq+V+HmGrjUhMTCQkJKTczyMKayOuX7/O3r17y/084tY2olOnTtbcLY/L4zyiqDYCsMt5hK02wtLOlvd5RGFtRFpamvXYy/M84tY2YtGiRdas69WrV27nEUW1EZcuXSIkJKTczyNstRFxcXGkpqaW+3mErTYiIyPDmnl5n0fc2kakpKQAkJKSwoYNG4DyOY8A221EQkICISEhdjmPsNVGZGRksGvXrnI/j7DVRljaGnucR0D+NsLuNCFKICUlRQO0+Ph4w/bh2LFjStY2sn5GRoY2depULSMjw5D6mia5G0Fyl9yNIrnbn+QuuRtFcrc/yV3N2kbnrurnzeja8fHxGqClpKTYpZ5cIicqnezsbCVrV4T6RpLc1SS5q0lyV5PkribJXU2q5i6Zq1nf6GO3J+lgEpWOZUiharUrQn0jSe5qktzVJLmrSXJXk+SuJlVzl8zVrG/0sduTdDAJIYQQQgghhBBCiFKRDiZR6YwcOVLJ2hWhvpEkdzVJ7mqS3NUkuatJcleTqrlL5mrWN/rY7Uk6mESlY7k7i2q1K0J9I0nuapLc1SS5q0lyV5PkriZVc5fM1axv9LHbk3QwiUrnypUrStauCPWNJLmrSXJXk+SuJsldTZK7mlTNXTJXs77Rx25P0sEkKp2aNWsqWbsi1DeS5K4myV1NkruaJHc1Se5qUjV3yVzN+kYfuz1JB1MRXn31VUwmk3UJDw+/7XvWrFnD6NGjqVevHs7OztSrV4/Ro0ezZs2aYtdNT0/ns88+o2vXrnh7e+Ph4UHLli15+eWXiY2NLfZ2jhw5wlNPPUWTJk1wdXWlVq1a9OrVi++++46cnJxib6ei6dmzp5K1K0J9I0nuapLc1SS5q0lyV5PkriZVc5fM1axv9LHbk3QwFeLAgQNMnz692OtrmsaTTz7J4MGDWbJkCXFxcWRlZREXF8eSJUsYPHgwTz75JJqmFbmd6OhoOnbsyKuvvsru3btJSkri2rVrREVF8cUXX9C2bVtWrVp12/35/vvv6dSpE9999x3R0dFkZGSQkJDAli1beOqpp7j33ntJTEws9vFVJEuXLlWydkWobyTJXU2Su5okdzVJ7mqS3NWkau6SuZr1jT52e5IOJhvMZjOPP/44OTk5+Pr6Fus9b775JjNnzgSgQ4cOhISEsGvXLkJCQujQoQMAM2fO5K233ip0G2lpaQwbNoxjx44B8Pjjj7Nhwwa2b9/Ohx9+iIeHBykpKQQHB3Pw4MFCt/P777/zxBNPkJmZSe3atfnPf/7Dzp07Wb16NaNHjwbgzz//ZPTo0ZjN5mIdnxBCCCGEEEIIIURhpIPJhv/85z/s3r2bFi1a8Oijj952/ZMnT/Lpp58C0LlzZ7Zt28aECRPo0qULEyZMYOvWrXTu3BmATz75hOjoaJvb+fzzz4mKigLg008/ZebMmfTr14/AwED++c9/snbtWhwdHUlPT+fFF1+0uY2cnByeffZZzGYznp6ebNu2jeeee46uXbsyaNAgFi1axNNPPw3os9n/+uuvJf32GK59+/ZK1q4I9Y0kuatJcleT5K4myV1NkruaVM1dMlezvtHHbk/SwXSLs2fPWkcZffPNN1StWvW275k+fbp1TqOvv/4aV1fXfK+7ubnx9ddfA3oH0JdffllgG9nZ2Xz11VcAtGzZkn/84x8F1gkMDLR2eG3atIm9e/cWWGfJkiWcPHkSgDfeeIOAgIAC63z22WfUqFHD+riycXAw7sfWyNoVob6RJHc1Se5qktzVJLmrSXJXk6q5S+Zq1jf62O1JnSMtpqeffpq0tDQmT55Mnz59bru+pmnWaypbtGjBPffcY3O9e+65h+bNmwMQFhZWYC6m8PBwkpOTAZg8eXKhP4RTpkyxPl68eHGB18PCwmyum5ebmxvjxo0D4PDhw5w4ccLmehXVvn37lKxdEeobSXJXk+SuJsldTZK7miR3Namau2SuZn2jj92epIMpjwULFrBixQq8vb2LPbInJiaGuLg4AHr37l3kupbXz507x+nTp/O9tmXLlgLr2dK5c2fc3d0B2Lp1a4HXLdtp3rw5derUue2+FLYdIYQQQgghhBBCiOKSDqYbkpOTeeGFFwB9nqRatWoV631Hjx61Pm7RokWR6+Z9Pe/7SrIdR0dH62Vvt24jLS2Nc+fOlXpfKrphw4YpWbsi1DeS5K4myV1NkruaJHc1Se5qUjV3yVzN+kYfuz1JB9MNr776KhcvXqR79+7Fmtjb4uzZs9bH9erVK3Jdf39/m+/L+293d3eqV69erO1cvnyZzMxM6/Pnzp2zXnpXmn2p6Hbt2qVk7YpQ30iSu5okdzVJ7mqS3NUkuatJ1dwlczXrG33s9uRo9A5UBFu3bmX27Nk4Ojry7bffYjKZiv3eq1evWh97eHgUua7l0jbQRxvZ2s7ttmFrO87OzmW6L3llZmbm68RKTU21+bw9XbhwQcnaRta31FTx2I2ubWR9yV1yN4rkLrmrVNvI+pK75G4UVXM3srbRuav6eTO6tr3rmrRbZ5tWTFZWFu3bt+fo0aO88sorfPrpp/lenzp1Ku+++y6g37nt1om/33//fd5++20ANmzYQL9+/QqttXHjRvr3729935tvvml9LSAggFOnTuHv709sbGyR+/zwww/zyy+/AProI8topS1bttCrVy8A3nrrLd57771Ct2E2m6lSpQoA/fv3Z/369TbXy3v8eb3++uu4uLgUuZ9CCCGEEEIIIYQwRkZGBtOmTSMlJQVPT89yr6f8CKaPPvqIo0ePUr9+fd55550Svz9vJ0tWVlaR6+btPXR1dbW5ndtto6jtlNW+5PXGG2/w97//3frv1NRU/P39eeaZZ4o9T1VZy8zMtI7aUqm2kfUzMzOZPn06L730kpLfe8ldclepvuQuuav4vZfcJXeV6kvu6tY2MndVP29G1758+TLTpk2zWz2lO5iioqL4+OOPAfj666/zXTZWXNWqVbM+LupSM4Br165ZH996CZtlO7fbRlHbKat9ycvZ2dnmh6Gw5+1h8eLFTJw4UbnaFaG+5G4Mo+tL7sYwur7kbgyj60vuxjC6vuRuDKPrS+5q1bYwKnejj13V3O2dtdIdTNOnTycrK4vGjRuTnp7OvHnzCqxz+PBh6+ONGzdy8eJFAIYPH467u3u+ybQtd3ArTN7JtPNOsg36pNw7d+7k2rVrJCcnFznRt2U7tWrVyvcDU1b7UhTLFZVXr1417D+k9PR061xQKtU2sn5mZiYZGRmkpqZK7grVl9wld8ldnfqSu+QuuatTX3JXs7bRuav6eTO6tmWeZrvNjKQpbPLkyRpwR0tMTIymaZoWHR1tfe7JJ58sst4TTzxhXffUqVP5Xnvrrbesr+3YsaPQbWRnZ2vu7u4aoPXq1avA6/7+/hqgNW/evMh9mTt3rrXeDz/8UOS6eeU9XllkkUUWWWSRRRZZZJFFFllkkaViL9HR0cX+nb80lB7BVBYaNWqEn58f58+f548//ihy3c2bNwNQt25dGjZsmO+1nj17Wh//8ccf3HPPPTa3sWfPHuvlbT169Cjwes+ePQkJCeHYsWNcvHiROnXq2NxO3n21tZ3CeHt7AxAbG4uXl1ex31eWunTpwu7du5WrbWR9y9xbZ8+etcvkcLZI7pK7SrWNrC+5S+6Suzr1JXfJXXJXp7bRuav6eTO6dkpKCvXr17f+Hl/elO5g+umnn/jpp5+KXOd2d5EzmUwEBQXxzTffEBUVxZ9//mmzc+jPP/8kKioKgKCgIEwmU77X+/Tpg5eXFykpKcyZM4dXX321wDqWfbYYNWpUgddHjhxJSEiIdd3XX3+9wDrp6eksWLAAgFatWtGsWbMivgP5OTg4AODl5WXYf0hVqlRRsnZFqO/p6ank997o77vR9SV3YxhdX3I3htH1JXdjGF1fcjeG0fUld7VqWxiVu9HHrnrult/jy72OXar8xb344os4Oup9dc899xzXr1/P9/r169d57rnnAHB0dOTFF18ssI2qVavy/PPPA3D06FE+//zzAuvs2LGD77//HoDevXvTpUuXAuuMGjWKgIAAAD7++GOio6MLrPPKK6+QlJRkfVzZPPPMM0rWrgj1jSS5q0lyV5PkribJXU2Su5pUzV0yV7O+0cduTyZNs9dsT5XT7UYwWbzxxhvW2/916NCB1157jYCAAKKjo/nkk0+IiIiwrvfRRx/Z3MbVq1fp3Lkzx48fB+CJJ55gwoQJuLq6smnTJj766CPS0tJwdXVl+/bttG/f3uZ2Vq1axfDhwzGbzdSuXZs333yTrl27kpSUxKxZs1i0aBGgX04XHh5OlSpViv39SE1NtY60MroXVtiP5K4myV1NkruaJHc1Se5qktzVJLmryd65K32JXFn68MMPiY+P54cffiAiIoIJEyYUWOfRRx/lgw8+KHQb1apVY+XKlQwZMoQTJ04wc+ZMZs6cmW8dT09Pfvvtt0I7lwCGDBnCt99+y7PPPsulS5eso6fy6tq1K0uWLClR5xLotzl85513DLvjhDCG5K4myV1NkruaJHc1Se5qktzVJLmryd65ywim2yjuCCaLVatWMXPmTHbv3k1CQgI+Pj506dKFJ598ksGDBxer5rVr15gxYwYLFy7k5MmTZGVl4e/vz5AhQ3jhhRdo0KBBsbZz+PBh/vOf/7BhwwbOnz+Pu7s7LVu25MEHH+Sxxx6zXtYnhBBCCCGEEEIIURrSwSSEEEIIIYQQQgghSkUm+RZCCCGEEEIIIYQQpSIdTEIIIYQQQgghhBCiVKSDSQghhBBCCCGEEEKUinQwiTvy6quvYjKZrEt4eLjRuyTKSUJCAp9++ik9evSgTp06ODs74+fnR7du3XjllVfYsWOH0bsoylBWVhbff/89gwYN4q677sLZ2RkPDw+aN2/OI488wp9//mn0LooSiI+PZ8WKFbz99tsMHjwYHx8fa7s9ZcqUEm9vzZo1jB49mnr16uHs7Ey9evUYPXo0a9asKfudF3esLHLPyMhg6dKlPPfcc3Tr1g1vb2+cnJzw9vYmMDCQqVOncuHChfI9EFFsZf1Zzys9PZ3GjRtbt9ewYcMy2WdReuWR+65du3j66adp2bIlnp6eeHh4EBAQwNChQ/n3v//N5cuXy/YgRImVZe5nzpzh9ddfp1OnTlSvXt3aznfv3p33339f8q5A9u3bx0cffcTgwYPx9/e3nqM3a9aMKVOmsGXLlhJtr9zO6TQhSmj//v2ao6OjBliXTZs2Gb1bohwsWLBAq1mzZr6sb12CgoKM3k1RRmJjY7U2bdoUmTegvfTSS5rZbDZ6d0UxFJXj5MmTi70ds9msPfHEE0Vu74knnpCfiwqitLkfOHBAq1at2m3bgmrVqmnz588v/wMSt1VWn3Vb/vGPf+TbXoMGDcpkn0XplWXuGRkZ2mOPPaaZTKYit7tkyZJyORZRfGWV+2+//aa5ubkVub2aNWtqGzZsKL+DEcXSq1ev2/6fDGgPPfSQlpmZWeS2yvucTu5TL0rEbDbz+OOPk5OTg6+vL/Hx8UbvkignP//8M//3f/+H2WzG19eXv/3tb/Ts2RNvb28uXrxIdHQ0y5cvx8nJyehdFWUgJyeHoUOHcujQIQDatm3L3//+d5o3b87Vq1fZunUrX3zxBdeuXWP69OncddddvPLKKwbvtSgJf39/WrZsydq1a0v83jfffJOZM2cC0KFDB1599VUCAgKIjo7m008/JSIigpkzZ1KrVi0++OCDst51UQp3kntqaipXr14FoEePHgwbNozOnTtTs2ZNLl++zOLFi5k9ezZXr17lgQceoFq1agwePLi8DkGUUGk+67eKiIjgyy+/xMXFBScnJ+vPhah4SpN7VlYWo0aNYvXq1QDce++9PPzww7Rs2RJHR0fOnDnDgQMHWLhwYVnvtiilO819x44dPPzww+Tm5uLg4MDkyZMJCgrCz8+P2NhY5syZw/Lly0lMTGTEiBEcPnxYRi8aKC4uDgA/Pz+Cg4O59957qV+/Prm5uezYsYMvvviCuLg4fvnlF3Jycpg7d26h2yr3c7o76pYSypo+fboGaC1atNDeeOMNGcH0FxUZGak5OztrgHbvvfdqycnJha57u15yUTmEhoZaP8+BgYFaTk5OgXX27NmjOTk5aYBWo0YNLTs724A9FSXx9ttva8uXL9cuXryoaZqmxcTElPivnCdOnLCOWu3cubOWnp6e7/Vr165pnTt31gDN0dFRO3nyZFkfhiih0ua+bds2bdy4cdqRI0cKXScsLMw60iEgIEBGrxmsLD7rt8rJydE6deqkAdp7772nNWjQQEYwVTBllftbb71lfd/nn39e5LpZWVml2WVRBsoi92HDhlnfM2PGDJvr/P3vf7eu89xzz5XV7os7MHToUG3+/Pk2z881TdMuX76sNWvWzJrX5s2bba5nj3M66WASxRYbG6t5eHhYO5Teeecd6WD6i+rfv78GaD4+Ptrly5eN3h1hBy+99JL187xs2bJC1xs1apR1vUOHDtlxD0VZuJOT0Kefftr6nh07dthcZ8eOHdZ1nn322TLcY1EWyqKzwZYxY8ZYt7tv374y264ovbLI/IsvvtAArXnz5lpmZqZ0MFUCd5J7dHS09Y9HU6ZMKd8dFOXiTnKvUaOG9RK4wiQnJ1u326lTpzLaW1Feli9fbs3r+eeft7mOPc7pZJJvUWxPP/00aWlpTJ48mT59+hi9O6KcREVFsWHDBgCeffZZfHx8DN4jYQ9ZWVnWx40bNy50vYCAAOvjzMzMct0nYTxN01i6dCkALVq04J577rG53j333EPz5s0BCAsLQ9M0u+2jME7fvn2tj6Ojow3cE1HWzpw5w9tvvw3AN998Q9WqVQ3eI1FeZs6cSXZ2NiaTyZq5+OuznPc1atSo0HW8vLysvwfIOV/Fl/f3c1v/J9vrnE46mESxLFiwgBUrVuDt7c1nn31m9O6IcpT3+vrg4GDr46SkJE6cOEFiYqIRuyXKWbNmzayPT506Veh6lv+wTCYTTZs2Lff9EsaKiYmxXvffu3fvIte1vH7u3DlOnz5d3rsmKoC8v3A4OMgp5V/J008/zbVr13jooYfydSSKvx7LeV/nzp2tnQ1ms5lz584RExPD9evXjdw9UU4s530xMTGFrpOamkpCQkK+9UXFlfePxbb+T7bXOZ2cDYjbSk5O5oUXXgDgk08+oVatWgbvkShPltvQe3l50bJlS3777TfatWuHt7c3zZo1w8fHh8aNG/Puu++SlpZm8N6KsjJx4kQ8PT0B/XOem5tbYJ2IiAhWrlwJwIQJE6zri7+uo0ePWh+3aNGiyHXzvp73feKv648//rA+vt3Ph6g85s2bx6pVq6hRowaff/650bsjytHly5etf1QKDAwkNTWVF198ER8fH/z9/WncuDGenp707t3b+v+/+Gt48sknAUhMTOTbb7+1uc77779fYH1Rcd3u/2R7ndPJXeTEbb366qtcvHiR7t278+ijjxq9O6KcRUZGAtCwYUOee+45ZsyYUWCdmJgYpk6dSmhoKL///jt+fn723k1RxmrVqsVPP/3Egw8+yLZt2+jSpQsvvvgizZo1Iy0tjW3btvHFF1+QlZVF+/bt+fe//230Lgs7OHv2rPVxvXr1ilzX39/f5vvEX9OBAwesv3DefffdtGrVyuA9EmUhKSmJF198EYBp06bh6+tr7A6JcmU55wNwdXWlY8eOBS6tycnJYfPmzWzevJmXXnpJ/v//i3jsscfYsmULv/32G8888wx79+5lxIgR3HXXXcTGxvLrr7+yZMkSAF577TUGDBhg8B6LopjNZqZNm2b997hx4wqsY69zOhnBJIq0detWZs+ejaOjI99++y0mk8noXRLl7MqVK4A+F9OMGTOoXr063377LfHx8WRkZLB7927r7agPHz5McHAwZrPZyF0WZWTUqFHs2bOHRx99lP379zN58mQCAwO5//77mTp1Km5ubvz73/9m69at1KlTx+jdFXaQ95bkHh4eRa7r7u5ufSyjG//aMjMzeeyxx6wjHT/66COD90iUlVdeeYVLly4RGBjI448/bvTuiHJmOecD+PLLL4mOjqZ79+788ccfpKenc+XKFX777TfuuusuAKZPn17oaBdRuVSpUoVff/2V+fPn065dO2bPns2IESPo0qULY8aMYcmSJfTt25fff/89X8eFqJimT5/Orl27AP18vnPnzgXWsdc5nXQwiUJlZWXxxBNPoGkaL730Em3atDF6l4QdXLt2DdB/gahSpQqrV6/mySefpFatWjg7O9O5c2dWrFhh7WTavn07ixcvNnKXRRnJzs5m7ty5LF++3OaEfpcuXSIkJITw8HD775wwREZGhvXx7Sb5dXZ2tj6WOTv+2p599ln27NkDwOTJkxkxYoTBeyTKwubNm/nhhx/kj4oKsZzzgX7e16lTJzZs2ECvXr1wdXWlRo0aPPDAA/zxxx/WXzjffvttaeP/IqKiopg7dy6HDh2y+fqOHTv4+eefuXDhgp33TJTEH3/8weuvvw6Ar68v33zzjc317HVOJx1MolAfffQRR48epX79+rzzzjtG746wExcXF+vj4OBgm3cYcHBwyDfZe0hIiF32TZSfa9eucd999/Hhhx+SmJjIq6++ytGjR8nMzCQlJYW1a9fSs2dPdu/ezfDhw/nqq6+M3mVhB3nbg7yTR9qSd8JnV1fXctsnYayPP/6Y2bNnA9CpUyebl1GLyiczM9P6R8UXXniBtm3bGr1Lwg7ytvEAH374YYHnAJo2bcrf/vY3QJ+3af369XbZP1F+tmzZQmBgIEuXLqVu3br88ssvXLx4kaysLM6ePcuMGTNwdXXlt99+o2vXrjK3YgV15MgRRo0aRU5ODs7OzixYsIDatWvbXNde53TSwSRsioqK4uOPPwbg66+/zjdMTvy1VatWzfrYMkrJlrvvvpu6desCsHv37nLfL1G+3nnnHTZv3gzA999/zyeffEKLFi2oWrUqnp6e3H///WzatIm+ffuiaRp///vfOXjwoMF7Lcpb3vbgdkOk8/4l/HZDr0Xl9N133/HPf/4TgObNm7N69Wo5P/iL+PDDDzl27Bj+/v5MnTrV6N0RdpK3ja9atWqRdwwcOHCg9bGc91VumZmZTJw4keTkZOrUqcOff/7JpEmTqF27Nk5OTtSrV4+nn36aLVu24OLiwrlz53j44YeN3m1xi5iYGAYMGEBSUhJVqlQhJCSkyLvD2eucTib5FjZNnz6drKwsGjduTHp6OvPmzSuwzuHDh62PN27cyMWLFwEYPny4nHBWYv7+/tYsizMBXFxcHPHx8fbYNVFONE3jxx9/BPTb0E6ePNnmeo6Ojrz//vv07NkTs9nMjz/+yPTp0+25q8LO8rYB586dK3LdvJNA5p0cUvw1hISE8PTTTwPQoEED1q9fL3eV/Qv55JNPALjvvvtYsWKFzXUsv3Bcu3bNel7o6+tLv3797LOToszlbatr165d5GUzedeV877Kbc2aNdbb1T/33HOFzqt59913M2nSJGbPns2ePXs4cOAA7dq1s+euikKcP3+e++67j/Pnz2Mymfjhhx8YNWpUke+x1zmddDAJmyzD4k6dOsXEiRNvu37e21jGxMRIB1Mldvfdd1v/MmXrVvV5WV53dJSmpDK7dOmSdaLPDh06FLlup06drI+joqLKdb+E8fLeGex2eed9vWXLluW2T8L+li1bxsMPP4zZbOauu+5iw4YNt/0DhKhcLJdL/Pjjj9Y/OBQmISHBem7Yu3dv6WCqxJo2bYqTkxPZ2dnFPucDOe+r7PJe7taxY8ci1+3UqZP1suioqCjpYKoAEhISuP/++zl16hSgX21UnBFm9jqnk0vkhBD59OrVy/r41lvV3srSsFkulROVU94TxZycnCLXzc7Otvk+8dfUqFEj/Pz8AH0SyaJYLrGsW7cuDRs2LO9dE3ayYcMGxo0bR05ODjVr1mTdunUEBAQYvVtCiDLg5OREYGAgoP+xKe9lMbfKe04o532Vm5z3VV4pKSkMHDiQyMhIAKZNm8YzzzxTrPfa65xOOpiETT/99BOaphW55J34e9OmTdbn5ReLym3EiBE4OTkBFHl3uD/++IPExEQA7r33Xrvsmygf3t7eeHp6AvodQ4o62cj7H1KjRo3Kfd+EsUwmE0FBQYD+16w///zT5np//vmn9a9dQUFBcvepv4jt27cTFBREZmYmnp6e/P7779x9991G75YoB7c759M0jQYNGgD6JZKW5+SuopXfmDFjAH2E0tKlSwtdL+85oZz3VW55z9+2bNlS5Lpy3ldxpKenM3ToUPbt2wfAv/71L1577bViv99e53TSwSSEyKdmzZo89thjAKxbt87m/FtXr17lxRdftP77ySeftNfuiXLg4ODA0KFDAf2a7g8//NDmeklJSfn+Ixs2bJhd9k8Y68UXX7T+1fK5554rcLva69ev89xzzwH6Xzfztg2i8tq/fz9Dhw7l2rVruLu7s2rVqnyXyAoh/hoeeeQRfH19AfjnP//JpUuXCqwTHh7OL7/8AkDr1q3p0aOHXfdRlK3+/fvj5uYGwDfffMOhQ4dsrrd69WqWLFkC6CNZ2rdvb69dFLfIyspi1KhRbNu2DYAXXniBDz74oMTbscc5nYxzE0IU8O6777Jy5UpiY2N56KGH2LZtG6NHj8bT05NDhw7xySefWHu2//a3v9GlSxeD91iU1ttvv83SpUtJT09n6tSp7N27l8mTJ9O4cWMyMjL4888/+fLLL4mNjQX0k5MBAwYYvNfidrZu3crJkyet/05ISLA+PnnyJD/99FO+9adMmVJgG82aNePll19m2rRp7Nmzhx49evDaa68REBBAdHQ0n3zyCREREQC88sorNG3atFyORRRfaXOPjo5m4MCBJCcnA/DBBx/g5eWV7+Yet/L19bX+kirsryw+66LyKYvcPTw8+M9//sPEiRM5c+YMXbp04fXXX6dr165kZGSwevVqpk+fTm5uLo6Ojnz77bcyStVgpc29evXqvP7667z99ttcvXqV7t2789xzz3H//fdTo0YNLl26xNKlS5k1axZmsxnQL8VycJCxKUaZOHEia9euBaBfv348+uijRf6fXLVqVZo1a1bgebuc02lC3KF33nlHAzRA27Rpk9G7I8pYZGSk1qRJE2vGtpZHHnlEy8rKMnpXRRlZt26d5uPjU2TmgNavXz/typUrRu+uKIbJkyffNs+8S2Fyc3O1Rx55pMj3Pvroo1pubq4dj04UprS5//jjjyV6P6C988479j9QYVVWn/WiNGjQQAO0Bg0alO3OiztWlrn/97//1apWrVroez08PLSwsDA7HZkoSlnkbjabtRdffFEzmUxFvtfJyUn77LPP7HyE4lYl/T+5qHa6vM/ppBtSCGFTy5Yt2b9/P5999hndunXD29ubqlWrUq9ePcaPH8/GjRv5/vvvrfM1icrvvvvuIyoqik8++YQ+ffpQq1YtnJyccHV1pVGjRowbN46wsDDWr19PjRo1jN5dYUcODg58//33rFy5kqCgIPz8/KhatSp+fn4EBQWxatUqZs+eLX/dFEKISuqZZ55h3759/O1vf6NJkya4urri4eFB27ZtefXVVzl+/Lh1/hZR+ZlMJqZPn87u3bt56qmnaN26NdWqVaNKlSp4eXnRqVMn/v73v3P48GFefvllo3dXlKHyPqcz3egRE0IIIYQQQgghhBDijsifGoUQQgghhBBCCCFEqUgHkxBCCCGEEEIIIYQoFelgEkIIIYQQQgghhBClIh1MQgghhBBCCCGEEKJUpINJCCGEEEIIIYQQQpSKdDAJIYQQQgghhBBCiFKRDiYhhBBCCCGEEEIIUSrSwSSEEEIIIYQQQgghSkU6mIQQQgghhBBCCCFEqUgHkxBCCCGEEEIIIYQoFelgEkIIIYTSpkyZgslkomHDhkbvitL69OmDyWSiT58+Ru9KkU6fPo3JZMJkMvHTTz8ZvTtCCCFEhSEdTEIIIYQodykpKcyYMYMhQ4bQsGFD3Nzc8PLyolmzZjz44IPMnz+f3Nxco3ez0vjpp5+snRy3Lg4ODnh6etK6dWueeuop9u3bZ/TuVjgnTpzg1VdfpWvXrnh7e+Pk5ISPjw+tWrViwIABTJ06lfDwcDIyMozeVSGEEKLScDR6B4QQQgjx1zZ79mxef/11EhMT8z1//fp1UlNTOXHiBHPnzqVVq1Z899139OzZ06A9/WvQNI2rV69y5MgRjhw5wqxZs/jXv/7Fe++9Z/SuVQgffvghU6dOJScnJ9/ziYmJJCYmcvToUdatW8e7777La6+9xrRp0wzaUyGEEKJykQ4mIYQQQpSbV155hc8//xwAR0dHJkyYwIgRI2jQoAFZWVkcO3aMkJAQNmzYQGRkJPfddx+//vorY8eONXjPK48PPviAoKAg67/NZjOXL18mPDycL7/8krS0NN5//30aNWrE//3f/xm4p8b77LPPePPNNwHw8vLiySefpHfv3tx1111kZWVx7tw5du7cyfLly4mKirK5jYYNG6Jpmj13WwghhKgUpINJCCGEEOVixowZ1s4lf39/li9fTrt27fKt07NnTx599FHmz5/Pww8/TGZmJg8++CBNmjShffv2Bux15VO3bl1at25d4Pn+/fvTp08f7r//fjRN49NPP1W6gykxMZF33nkHgHr16rF9+3b8/f3zrdOtWzfGjBnDp59+yq5duwqMuhNCCCFE4WQOJiGEEEKUuTNnzvDyyy8D4OHhwcaNGwt0LuU1fvx45syZA0BWVhYPPfSQjBIpA/3796dTp04AREVFkZqaavAeGWft2rVcv34dgNdff71A59KtunbtyuDBg+2xa0IIIcRfgnQwCSGEEKLMffnll9YJkt955x2aNGly2/dMmDCBoUOHAnD48GFWrFhRYJ1b7zR24sQJnn32WZo2bYqbmxsmk4nTp0/ne09kZCSTJ0/G398fFxcX/P39eeCBB9i9e3eJjikpKYkPPviAwMBAfHx8cHZ2xs/Pj6CgIBYvXlzkey0TcE+dOhWAjRs3EhwcjL+/P05OTuV6B7u82y5q0uqsrCz+97//0bdvX2rVqkXVqlWpU6cOQ4YM4ddff8VsNt+2VlpaGtOmTSMwMBBvb2+cnZ2pV68eY8eOtZlnSc2dOxcnJydMJhOBgYEkJSUV+71nzpyxPi7Oz2NhirqLXFGTr9taLD8Pt9I0jdDQUMaMGWP9ua1RowZdu3bl/fffJzk5+Y73XwghhCgvcomcEEIIIcqUpmn8/PPPALi6uvL4448X+73PP/88K1euBODHH39k+PDhha67dOlSHnzwQa5du1boOvPmzWPy5MlkZWVZnzt37hwhISEsXLiQ7777rlj7tWrVKh588MECv9hfuHCBZcuWsWzZMoYOHcq8efPw8PAoclv/+te/+Oijj4pVtyxYOtxcXFyoVauWzXXOnDnD4MGDOXr0aL7nL126xOrVq1m9ejXfffcdS5cuxdvb2+Y2IiIiGDZsGOfPn8/3fFxcHIsWLWLRokWMHj2a3377DRcXlxIfx3//+1+ef/55NE3j/vvvZ8mSJbi7uxf7/VWrVrU+Pnr0KAMHDizxPtjD5cuXGTVqFNu2bcv3fGZmJrt372b37t3MmDGDpUuX0q1bN4P2UgghhChIOpiEEEIIUaaOHDnClStXAOjVqxdeXl7Ffm///v1xc3MjPT2drVu3FrpebGwskyZNws3Njbfeeot7772XKlWqsHv3bmsHz86dO3nooYfIycnB2dmZl156iSFDhuDs7MzOnTv56KOPeOqpp2jVqlWR+7Ru3TpGjBhBbm4uDRs25G9/+xvdunXD09OTuLg45s+fz6+//srKlSuZPHkyixYtKnRbS5Ys4eDBg7Rp04aXXnqJ1q1bc/36dfbv31/s71FJbNq0iX379gEwfPhwTCZTgXXS0tLo168fp06dAmDkyJE88sgj+Pn5ERMTw3//+1/++OMPtm7dyrBhw9iyZQtVqlTJt424uDj69+9PUlISJpOJKVOmMGHCBGrWrElkZCRffPEFBw4cYPHixUyePJn58+eX6Djee+896/xJY8aMYe7cufk6jIqjQ4cO1scffvghffv2LfKyzTsxcuRIOnfuXOQ6r7zyCmvWrAGgQYMG+V67du0avXv35ujRo1StWpX/+7//Y8iQIfj7+3Pt2jU2b97Mv//9by5dusTgwYOJiIgosA0hhBDCMJoQQgghRBn69ddfNUADtDfeeKPE7w8MDLS+Py4uLt9rvXv3tr7m5+ennTlzptDtdOrUSQM0Jycn7Y8//ijw+rlz57R69epZt9egQYMC66SlpWm1a9fWAG3AgAHatWvXbNaaOXOmdTvr168v8LrlNUDr37+/lpGRcZvvQtF+/PFH6/Y++OAD7dChQ9blwIED2oYNG7S3335b8/T01ADtrrvu0o4dO2ZzWy+//LJ1W2+++WaB181ms/bggw9a1/nf//5XYJ2xY8daX589e3aB1zMyMrS+ffta11m1alWBdSzZ9u7dO1/t559/3vq+xx57TMvNzS3Bd+qm3NxcrW3bttZtmUwmrXfv3tr777+v/f7771pSUlKxthMTE2Pdxo8//liiffjvf/9rfe+DDz5Y4PVnn31WAzQvLy9t9+7dNrdx+vRp7a677tIAbdKkSSWqL4QQQpQn6WASQgghRJn68ssvrb9Ef/XVVyV+/8iRI63vP3jwYL7X8nYw/fzzz4VuY+fOndb1nn322ULXmz9/fpEdTF9//bUGaC4uLtqlS5eK3O+uXbsW2nFgqeHg4KDFxMQUuZ3iyNvBVNTi7Oysvfrqq9rZs2dtbicjI0OrXr26BmitWrXScnJybK6XkpKi1axZ07peXufPn9eqVKmiAdrAgQML3eeYmBjN0dFRA7QhQ4YUeP3WDqbs7GztoYcesh7LK6+8UszvTuFOnDihNWnSxOb3ymQyaW3atNFeffXVQjvjLMdxJx1M69evtx5/165dtevXr+d7/fLly5qLi0uxPjf/+9//rJ2nhXV6CiGEEPYmk3wLIYQQokxdvXrV+rgkc+TYek9hdz2rWrUqwcHBhW5j/fr11sf/93//V+h6o0aNonr16oW+vnTpUgB69+6Nr69voeuBfjkgwI4dOwpdp0ePHuU6ofetMjMz+eWXX/jll19s3pVv79691nmlpkyZUuDSNwtPT0/GjRsH6JOmX7hwwfrapk2byM3NBeDRRx8tdF8aNmzI/fffD0B4eLj1PbZkZGQwevRofvnlFwA+/vhjPv300yKOtHiaNGnC/v37mTZtGgEBAfle0zSNQ4cO8emnn9KqVSv+8Y9/kJOTU+qaoE9GHxwcTE5ODnXr1iUsLKzAPFS///67dRJ2y/e6MJaftezsbPbu3Vsm+yiEEEKUlnQwCSGEEKJMVatWzfo4LS2txO/P+x5PT0+b6zRt2rTIiaIPHToE6B1Rbdu2LXQ9JyenfHPz3GrPnj2A/sv/7e4I9vnnnwNw8eLFQrdX1L7cqR9//BFNH5VuXa5evcquXbt47LHHuHDhAv/85z+ZOHFigU6mw4cPWx/fbsLovK/nfd+dbCM9Pd0659Otrl69ysCBA1m+fDkODg589913vP7660VutyTc3d157bXXOHnyJFFRUfzwww88//zzdO3aFQcH/dQ4NzeXf//73zz22GOlrpecnMzw4cNJSkrC1dWVpUuXctdddxVYz/KzBnDXXXcV+bPWunVr67pF/bwJIYQQ9iSTfAshhBCiTNWsWdP6+E5++b106ZLNbeVVo0aNIrdhuX29t7c3jo5Fn+7Url3b5vPZ2dl3dDv49PT0Ql+73X6XFQ8PD7p06UKXLl3w9fXlo48+Yv78+QwYMIBHHnnEup5lMnYo/PtgUadOHZvvK4tt5GWZlBzgqaee4oknnihym6XRvHlzmjdvbv13XFwcU6dOZfbs2QDMmTOHxx57jJ49e97R9nNzcxk/fjzHjh0D4KeffqJTp042142Pj7+jGkX9vAkhhBD2JB1MQgghhChTee/MFRERUaL35ubmcvDgQQBq1aqFn5+fzfUKu5TLwjJSx9Zd0wpb19a+WIwbN4633nrrttu6ndvtd3n4xz/+wbRp0zCbzXz//ff5Opjyut33qrDvU0kUZxt33303OTk5HDt2jO+++45evXoxfvz4Utcujrp16zJr1izS0tKYN28eAAsXLrzjDqaXXnqJtWvXAvD2228Xeemb5eetatWqJbrsrV69ene0b0IIIURZkw4mIYQQQpSp1q1b4+3tzZUrV9i8eTMpKSl4eXkV673r16+3jsi401/qQR+5BJCYmEhubm6RHTuFjRxxcXHBzc2N9PR0kpOT812WVJl4e3tTq1YtLl26ZL10MO9rFhcvXqRZs2aFbifvyLK878v7+NKlS9SvX7/E28jLx8eHuXPn0qdPH06cOMGkSZOoUqUKY8eOLXS7Ze3xxx+3djCdPHnyjrYxc+ZMvv76awDGjBnD1KlTi1zfMlovKyuLmjVr2ryMTgghhKjIZA4mIYQQQpQpk8nEQw89BMD169eZNWtWsd9r+YUc9Emn71SbNm0A/Zf1AwcOFLpeTk4O+/fvL/R1y/xM27Ztq9SXIlkmq87Ozs73fN5Os507dxa5jV27dtl8351sw83NjUaNGhW6np+fH5s2baJJkybk5OQwceJEwsLCitx2Wco7cs4yL1NJhIeH8+yzzwL6z9DPP/982xFieecCs4x6EkIIISoT6WASQgghRJl74YUXcHZ2BuDdd98t1iiQefPmsXLlSgBatWrFsGHD7rj+fffdZ308Z86cQtdbsmSJdb4mW0aMGAHAtWvXmDFjxh3vj5FiYmJITEwEwN/fP99rnTp1st5Fb86cOYXe2e3q1assWLAA0LPJO7qmT58+1hFi33//faH7ERsby7p166zvud3cWHXr1mXjxo00btyYnJwcxo0bx7Jly4p8T1FKcolf3gm3i+oIsyU6OpqxY8eSnZ1N7dq1Wbp0KW5ubrd93+DBg3FycgJg+vTpZXYHOyGEEMJepINJCCGEEGWuUaNG1tvKp6Wl0b9//yJHEi1YsIDJkycD+hw0v/zyyx2NHLHo2rUrHTt2BOCbb75h69atBda5cOECL7/8cpHbeeqpp/Dx8QHgrbfeYvXq1UWuv23bNjZv3nyHe132zGZzvjuwDRkyJN/rzs7O1julHTlyhHfffbfANjRN49lnnyUhIQHAOjLHws/Pj1GjRgH63fZ++OGHAtvIysrikUcesY6gunUbhfH392fTpk00bNiQ7OxsgoODrZ2QJTVr1iyeeOKJ23Z2njlzhn/961/WfwcFBRW7RmpqKsOHDycxMRFnZ2fCwsIKdOoVpm7duvzf//0fAAcOHODJJ58sspMpPj7eOhm5EEIIURHIHExCCCGEKBfPP/88p06d4quvviI2NpbOnTszceJERowYQYMGDcjOziYqKoq5c+eyYcMGQO9c+vnnn62dQ6Xxv//9j549e5Kdnc3999/PSy+9xJAhQ3B2dmbnzp189NFHJCQk0K5du0I7vzw9PQkJCWHw4MFkZmYybNgwxowZw5gxYwgICAD0jqq9e/eyZMkSDh48yNdff02vXr1Kvf/FFRcXx+HDh/M9d+3aNSIjI5k1axY7duwA9Dl+8nY2Wbz99tssXryYU6dO8f7773P48GEeeeQR/Pz8iImJ4b///S/h4eEABAYG2ryr2/Tp09mwYQNJSUk89thjbNu2jQkTJuDt7U1UVBSff/659VLEcePGMXjw4GIfX/369QkPD6d3796cOXOGMWPGEBYWxqBBg4q9DdA7uWbNmsWsWbPo3r07AwcOpFOnTtSuXRsHBwfi4uLYtGkTs2fP5urVq4A+gq1///7FrvHss89y9OhRAF588UU8PDwKZJOXr68vvr6+1n9/8cUXbN++ncOHD/PDDz/w559/8sQTT9CpUyc8PDxITk7myJEjrF+/nlWrVtGmTRtrB6EQQghhOE0IIYQQohx98803mre3twYUubRo0UILDw8vclu9e/fWAK13797Fqj137lytatWqNus5Ojpqs2bN0iZPnqwBWoMGDQrdzoYNG7Q6derc9hgAbc6cOQXeb3ntnXfeKdZ+386PP/5YrH2xLI0aNdL27t1b6PZiYmK0Fi1aFLmNHj16aImJiYVuY9++fZqfn1+R2xg9erR2/fp1m++/XbanTp3S/P39NUBzcXHR1q5dW6Lv2fz58wv9WbC1PPDAA1p6errN75VlnR9//NHmMRR3sfXzkJiYqA0aNKhY7+/bt2+JvgdCCCFEeZIRTEIIIYQoV0899RQTJkzg119/ZeXKlRw5coTLly/j6OhI7dq16dKlC0FBQYwdO/a28/KU1MSJE2nXrh3Tpk1jw4YNJCQkUKtWLXr06MHf//53unXrZvPyuVv169eP6OhofvzxR1asWMGBAwdITEzEwcGBWrVq0bJlS3r37s2YMWNo3rx5mR7DnXBxccHHx4d27doxYsQIJk2aVOQ8QA0bNuTAgQPMmjWLhQsXcvjwYVJTU/H29qZDhw48+OCDPPDAA0VettihQweOHTvGf//7X8LCwjh27Bjp6en4+Phwzz33MGXKFIYPH37Hx9SoUSM2bdpEnz59OHfuHEFBQaxYsYJ+/foV6/3jxo1j4MCBrF27lj/++IN9+/Zx6tQp6xxcnp6eNGnShMDAQB588EE6dep0x/taGt7e3qxevZqNGzfy66+/snXrVi5cuEBGRgaenp4EBATQtWtXhg4dyoABAwzZRyGEEMIWk6aVYMZDIYQQQgghhBBCCCFuIZN8CyGEEEIIIYQQQohSkQ4mIYQQQgghhBBCCFEq0sEkhBBCCCGEEEIIIUpFOpiEEEIIIYQQQgghRKlIB5MQQgghhBBCCCGEKBXpYBJCCCGEEEIIIYQQpSIdTEIIIYQQQgghhBCiVKSDSQghhBBCCCGEEEKUinQwCSGEEEIIIYQQQohSkQ4mIYQQQgghhBBCCFEq0sEkhBBCCCGEEEIIIUpFOpiEEEIIIYQQQgghRKlIB5MQQgghhBBCCCGEKBXpYBJCCCGEEEIIIYQQpSIdTEIIIYQQQgghhBCiVP4fcbD6ahtyqNEAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1300x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(13, 9))\n",
+    "plt.plot(orders_list, OCC_list_avg, linestyle='-', marker='o', markersize=8, label= \"Reactor Concept A Average OCC\", color='red') \n",
+    "plt.plot(orders_list, TCI_list_avg, linestyle='dashed', marker='o', markersize=8, label= \"Reactor Concept A Average NCI\", color='red')\n",
+    "\n",
+    "\n",
+    "\n",
+    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
+    "\n",
+    "\n",
+    "plt.xlabel('Order Book Size', fontsize='20') # x-axis name\n",
+    "plt.ylabel('2022$/kWe', fontsize='20') # x-axis name\n",
+    "\n",
+    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
+    "plt.legend(loc='upper right', fontsize='20') # Add a legend\n",
+    "plt.tick_params(labelsize=20)\n",
+    "plt.xlim(4, 20)\n",
+    "\n",
+    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
+    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
+    "plt.minorticks_on()\n",
+    "\n",
+    "plt.savefig('orders.png')\n",
+    "plt.show() # Display the graph\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Cost_Reduction/sensitivity_analysis.ipynb b/Cost_Reduction/sensitivity_analysis.ipynb
deleted file mode 100644
index 7c9c070..0000000
--- a/Cost_Reduction/sensitivity_analysis.ipynb
+++ /dev/null
@@ -1,951 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "ee4fa393-2ded-480c-bbf0-547d0cc0ddac",
-   "metadata": {},
-   "source": [
-    "<center><table>\n",
-    "    <tr>\n",
-    "        <th><img src=\"./INL1.png\",align=\"middle\",height=\"10000\"/></th>\n",
-    "        <th><img src=\"./MIT1.png\",align=\"middle\",height=\"10\"\\></th>\n",
-    "        <th><img src=\"./ANL.png\",align=\"middle\",height=\"10\"/></th>\n",
-    "    </tr>\n",
-    "</table>\n",
-    "</center>"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "40096a23-ff7b-4541-b710-9f0a9f9a595d",
-   "metadata": {},
-   "source": [
-    "# <center>Cost Reduction Framework for Nuclear Reactor Power Plants</center>\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "dfc0a6a4-10b0-4229-81ad-ba16943cc3a1",
-   "metadata": {},
-   "source": [
-    "## Section 0 : Essentials to Run the code"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f2256ae0-712f-4811-99d9-d37188782036",
-   "metadata": {},
-   "source": [
-    "### Section 0 - 1 : Importing the libraries"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "12fb6329-dc95-493f-ba1d-86235e71b512",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Importing libararies\n",
-    "import numpy as np\n",
-    "\n",
-    "import warnings\n",
-    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "from src import *\n",
-    "\n",
-    "\n",
-    "reactor_type_list = ['SFR', 'HTGR']\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "7a34753d",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "SFR\n",
-      "HTGR\n"
-     ]
-    }
-   ],
-   "source": [
-    "\n",
-    "startup_0 = 16\n",
-    "interest_rate_0 = 0.06\n",
-    "design_completion_0 = 0.8\n",
-    "Design_Maturity_0 = 1\n",
-    "proc_exp_0 = 0.5\n",
-    "ae_exp_0 = 0.5\n",
-    "ce_exp_0 = 1\n",
-    "\n",
-    "mod_0 = 'modularized'\n",
-    "standardization_0 = 0.8\n",
-    "BOP_grade_0 = 'non_nuclear'\n",
-    "ITC_0 = 0\n",
-    "n_ITC = 0\n",
-    "RB_grade_0 = 'nuclear'\n",
-    "\n",
-    "for reactor_type in reactor_type_list:\n",
-    "    print(reactor_type)\n",
-    "    TCI_list_avg = []\n",
-    "    OCC_list_avg = []\n",
-    "    orders_list = []\n",
-    "    for num_orders in range(4,21):\n",
-    "        OCC_list = []\n",
-    "        TCI_list = []  \n",
-    "        for n_th in range(1, num_orders+1):\n",
-    "            results = calculate(num_orders ,n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type ) \n",
-    "            OCC_result = results[0]\n",
-    "            TCI_result = results[1]\n",
-    "            \n",
-    "            OCC_list.append(OCC_result)\n",
-    "            TCI_list.append( TCI_result )\n",
-    "            \n",
-    "        avg_TCI = np.mean(TCI_list)\n",
-    "        avg_OCC = np.mean(OCC_list)\n",
-    "        \n",
-    "        TCI_list_avg.append(avg_TCI)\n",
-    "        OCC_list_avg.append(avg_OCC)\n",
-    "        orders_list.append(num_orders)\n",
-    "        \n",
-    "        \n",
-    "    if reactor_type == \"SFR\":\n",
-    "            OCC_list_avg_SFR = OCC_list_avg\n",
-    "            TCI_list_avg_SFR =  TCI_list_avg\n",
-    "    elif reactor_type == \"HTGR\":\n",
-    "        OCC_list_avg_HTGR = OCC_list_avg\n",
-    "        TCI_list_avg_HTGR =  TCI_list_avg\n",
-    "          \n",
-    "  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "8a456bc9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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N4OBgQkND2bp1KwBt2rQhNTWVv/76C4ChQ4eybds2UlJSqFy5Mi1btmTjxo0AtGjRguzsbP78808ABg4cyO7du7l+/Tqpqal06NCBdevWAdC0aVPs7Ow4cuQIAH379iU6Opr4+Hi8vb3p1q0bq1evBiA0NBQ3Nzeio6MBCA8P59ixY1y7dg0PDw8iIiL45ZdfAKhfvz5+fn7s378fgB49epCSksLSpUtxdXVl4MCBLFu2DCEEdevWJSgoiD179gDQpUsXLl26xMWLF3F0dGTo0KGsXLmS7OxsatWqRUhICJGRkQB07NiRGzducPbsWXQ6HSNHjmTt2rVkZGRQvXp16tevr7RhbGwsqampnDp1CoDhw4ezadMmUlNTqVq1Kk2aNGHz5s0AtG7dmvT0dE6cOAFQ6j7izJkzXL58uVh9RMOGDfHw8Ch1HyGEoF27dsXqI1atWkVWVlaZ9BGmuhenjxg0aBBRUVGl6iNMv7JduHBB8aawPsLb25sDBw4A0LNnz1L3EWlpadjb2xerj6hXrx47duwodR/RsWNHoqKiCAgIIDU1FUdHR+7cuQOAu7s7QgjS09OB3G2D7969S05ODg4ODnh4eChp3dzc0Ol0pKWlAeDj40NaWhrZ2dk4ODjg6empDJl3dXXFzs6OtLQ0hBC4uLiQkZFBVlYW9vb2eHt7c/v2bSWtvb09qampAHh5eZGZmUlWVhZ2dnb4+vpy+/ZtJR9HR0fu3r2rpNXr9ej1enQ6HX5+fkpaJycn4H/D+D09PcnOziYzM1NJm5SUhNFoxMnJCRcXF1JSUgDw8PDAYDCQkZEB5K41kZycjMFgwMnJCVdXV5KTk5U2NBqNSlrzNrS3t8dgMFhtbx8fH1JTU5X2Nm9DW+1tb2+Pl5dXnvY2b0Nvb28MBgOJiYkF2tvFxQUHB4c87W1qw8La29PTk6ysrDztbWpDZ2dnnJ2dlTZ0dXUlLS2NzMxMAPz9/blz547FNrTV3o6Ojri5ueVpb2vXrCmtyXfT3+btbe2azd/e3t7epKenK+1t65r19vbOc327u7uTmJiotLe1azZ/ezs7O+Pk5JSnva1ds/nb28PDg5ycHDIzM9Hr9Tav2fzt7evrS0pKitLe7u7uJe4jAKXuRe0jLLVhcfsIU77p6el52tBWH5G/DUvbR2RlZZGYmFisPqKw9i5qHyGEUD5zRe0jrLV3cfsIOzs7xfPi9BHm7Q0l7yMgd5FoU10L6yPM27u0fUROTo7Ffraw9vbx8SmTPsK8ny1OH5G/DUvSR5j6mtLcR7i4uJCZmcmGDRtwc3Mr8rNGuSMkkmKQnJwsAHG7Tx8hfvpJiIyMci/Dzz//XO6aFUFbTf3MzEwxbdo0kZmZqYq+ENJ3NZC+S9/VQm3fMzIyxMmTJ0WGCt9xCQkJ5a4phBAGg0HExcUJg8Ggir4Q6tVdbW019aXv0ne10Krvamqr7btWP29lpV3Se5P4+HgBiOTk5FKXoSjIKXKSEmG3aRM89hhUrQr//DoukUgkEolEUlyioqLQ6XQEBASg0+nyvFxdXalWrRrh4eHMmTNH+YVbcv9w5coVZs6cSc+ePalVqxYeHh64uroSHBxMr169+OSTT7h48aLaxZSUERkZGXh7eyuf4enTp99TvStXrmBvb6/o/fTTT/dUT6IOBoOBFStWMGbMGOrVq4e3tzeurq6EhIQQHh7OV199pYz8KQ7Z2dksW7aMsWPH8tBDD+Hv74+joyMBAQG0aNGCp59+mh07dhR5DaWYmBgmT57Mww8/THBwMM7Oznh5edGyZUuGDh3Kt99+W6Jy3leUSxhL8q/BNIIpGYQAIXS63Ne6deVWhtjY2HLTqkjaaupXhBEN0vfyR/oufVcLtX1XcwSTXq8vd00h1P1lOzIyUgBFetWsWVMcPXq0zMugVrtb0q9Zs6YAxNixY++57r30PTMzU7z00kvC2dm5UF91Op0YPnx4uX/2K5Lv5YXp+ho2bNg98X3JkiV5vH3ggQcspiurur///vt59Lp161boOWr6rqa22iOYSlr3PXv2iAYNGhTaj/j7+4t58+YVWX/t2rWidu3aRfruqVevntiwYYPVvGNjY8WAAQOKlJerq6uYPHmySE9PL1Y7yBFMEm0gRO6/48bBP3NU7zXx8fHlolPRtCuCvppI37WJ9F2baNn37OxsVfXV5umnn+b48ePKKzIykm+++YZ69eoBcPnyZcLDw5U1NcoKtdtdbf2yJjExka5du/Lpp5+i1+vx9PRkwoQJLF++nH379hEdHc2vv/7K66+/zgMPPIAQgl9++YVVq1aVaznVbne19e8FphFEHh4eAJw7d05ZV9Kcsqr7okWL8uhFRkZy9epVm+eo2e7/Rs+LSknqvnLlSrp3766sXdulSxfmz5/Pnj17iI6OZsWKFTz22GM4ODiQmJjIhAkTeOWVVwrV//DDDxk0aBAXLlwActfgnD17Njt37iQmJobt27fz1Vdf0atXL+zs7Dhz5gxvvfWWxXz/+OMP2rRpo6zTWrNmTd544w3Wr19PdHQ0e/fu5ccff+TJJ5/E39+fjIwMPvjgA2WdyH8bMsAkKT1CQFIS/LPA7r3GtEiuGqipXRH01UT6rk2k79pEy75nltOPNRWVwMBAQkNDlVdYWBgTJ07k+PHjdO3aFYDr168zb968MtVVu93V1i9LjEYjI0eOVIIKERERnDt3jm+//Zbhw4fTrl07WrVqRb9+/ZgxYwb79+9n4cKFBAYGlntZ1W53tfXLmuvXryubLUydOhV/f38Ai9PWyqLu0dHRygYkn3zyCQ4ODhiNRhYvXmzzPDXb/d/meXEobt3/+OMPHnnkEfR6PU5OTixdupRdu3bx5JNP0qFDB1q1asXQoUNZuHAhMTExVK9eHci9FubOnWtVf9GiRUyePBkhBJUqVWLXrl1s376dZ599lq5du9K8eXO6d+/OpEmT2LJlC0ePHlW+f/ITHx9Pnz59uH79OgCTJ0/m9OnTfPjhh/Tt25dWrVrRvn17+vbty/z587l48SJTp07FweHfu9eaDDBJygY7O/hnhzKJRCKRSCSSssTJyYlp06Yp/9++fbt6hZHYZPbs2UqQoXv37qxbt85m8MjOzo7HHnuMmJgYGjduXF7FlNwDFi9ejMFgwN7enkcffZThw4cD8Msvv6DX68tcb+HChUDuTlzjxo2jR48egOWAluT+wmg08uijj5KVlQXkej1y5Eir6Rs3bsyuXbuUkWwvv/wysbGxBdJdu3aNp59+GsjdpS0qKoouXbrYLEujRo3Yvn27xZFREydOVIJL06ZN4/3338fZ2dlqXp6enrz77rvs3LkTb29vm7r3LeUyEU/yr6HAGkzmr7AwtYsnuUdUhDVZJOWP9F2bSN9Lvs7BPSUjI3f31sGDhejcOfffMtzNtaKswfTOO+9YTZeamqqka9Cggc08T506JZ577jnRoEED4eXlJVxcXEStWrXEuHHjRExMjM1zr127Jr7++msxZMgQ8cADDwg3Nzfh5OQkqlatKvr37y+WLVtW5Ha6ePGieO2110Tz5s2Fn5+fcHZ2FiEhISIsLEzMmjVLXL58WUnbuXPnQtfu6Ny5s0WdPXv2iDFjxoiaNWsKZ2dn4e3tLZo2bSreeustER8fb7V8O3fuVPKOjIwUBoNBLFiwQISFhYnAwECh0+mKtRZUVlaWCA4OFoBwcXERV65cKfK5ttDr9eLrr78WYWFhIiAgQDg6OorKlSuL8PBwsWjRIpt+jB07Vlm/SwghkpKSxNtvvy0aNGgg3NzchLe3t+jYsaNYvHhxkcqSkpIiZs2aJbp06SIqV64snJycRJUqVUTr1q3Fa6+9ZvP6MhqNYsWKFWLw4MGiWrVqwtnZWfj4+IhWrVqJ6dOni6SkpCLX4+rVq+K///2vqFu3rnB1dRUBAQEiPDxcbNq0yeL5pbm+ikqjRo0EIHr27CmEEGLfvn1K3itWrChV3vnR6/XC399fAGLChAlCiLzrPx06dKjAOdOmTVOOnzlzplCN8PBwAYjAwECRnZ1tMc3BgwfFk08+KerWrSvc3d2Fm5ubePDBB8UzzzxjU+OHH35QynLx4kWRmZkpPvvsM9GmTRulXub9oV6vF7/++quYNGmSaNmypfDx8REODg7Cz89PtG7dWrzzzjvi1q1bNutj6uejoqLEoEGDRGBgoHB2dha1atUSEydOFGfPnhVC/O9aKex6uHLlinjjjTdEs2bNhI+Pj3B2dhbVq1cXw4cPF7t27bJ5bmGsXbtWaZ8+ffoU+byZM2cq57300ksFjr/yyivK8ZkzZ5aqjCdOnBA6nU4AokmTJiInJ6dU+RXG/bIGkwwwSYqF1QCTnV3uzW45sHbt2nLRqWjaaupXhAdO6Xv5I32XvquF2r6rGWCy+IC5bp0Qvr7/+741/9fXV4hffy217v0QYMrIyFDSNW7c2Gq66dOnCwcHB5sLSk+dOjXPOaZ2z8nJEXZ2doU+iPfo0UPcvXvXZr1mzpwpHB0di/RAn5SUVKIAgMFgEJMmTbJ5jre3t9i2bZvFMpoHmDZv3iy6d+9e4PziBJjWr1+vnDdmzJginWMrqCKEEJcuXRIPPfSQzTp26NBBJCYmWjzfPDDz999/i5CQEKv5TJo0yWZZtm/fLgICAgr1yRLx8fGiffv2Ns+rXLmy+P333wutx6FDh0RgYKDVfF544YUC59/rANORI0eUfH766SflfdMiyv369cuTvjDfC2P16tWK3u7du4UQQqSlpQkPDw8BiOeee67AOefOnVPOmTZtms38b926pfQjlvLKzs4WTz/9tM32dHR0LLDotKne5gGmQ4cOiaZNmxY437w/NPlv6+Xv7y/27t1rtU4Gg0G89tprSlAk/8vT01Ns3bq1SAGm7777Tri6utosz/jx4/ME5orj+aBBg5R8rPVflrhz545SLn9/f2E0GpVjt2/fFpUqVRKAcHd3L3XA5eWXX1bK+N1339lMW9rrXYj7J8Akp8hJygajEQYNKhep9PT0ctGpaNoVQV9NpO/aRPquTbTsu8FgyPvGr7/CwIFg2tbYtFWy6d87d2DAgNx0/3JMi7wChISEWEwzdepUpk6dSk5ODu3ateO7777jwIEDHD58mCVLltC2bVuEEEyfPp3Zs2cr55naXfyzeUnXrl2ZOXMmW7ZsISYmhqioKL7//nvatm0L5E7RmzRpktWyvvfee7z66qtkZ2fj4+PD5MmT2b59O0eOHGHXrl3MmjWL9u3bo9PpFP0ffviB48ePU7VqVQAGDBiQZ8Hz48eP88MPP+TReeONN/j6668BqFWrFt988w3R0dFERkby3//+F0dHR5KTk+nbty/Hjh2z2b6vv/46O3bsoH///qxevZqYmBg2bdpEeHi4zfPM+e2335S/+/btW6RzClzzZqSmptK1a1f+/vtvAAYOHMivv/7K4cOHWbFiBZ07dwZg79699O3b12Ze6enp9O/fn8TERKZMmUJUVBQ7duxg/vz5VKtWDYCvv/6arVu3Wjw/MjKS8PBwEhISsLe3Z9y4caxZs4aYmBj27dvH/PnzGTx4MI6OjgXOTUtLo3Pnzuzbtw8nJycmTpzIunXr2LVrF3v27OH999/H39+fmzdvEh4ezuXLl23WY9iwYSQnJ/PGG2+we/duDh48yJdffkmVKlUA+OKLL/j000/znJf/+urVqxfHjh2zeX0VB9N0NTc3NwaZPRM88sgjAGzZsoVbt24p79vyqjh6ISEhdOjQoYD2smXLCiwqXadOHdq0aQPAkiVLbOa/fPlycnJy8tTBnPHjxyvr/ISHh7N48WKio6M5dOgQ8+fPp2HDhmRnZzNhwgTWr1+vnGep3uPHj+fYsWM89thjbNy4kZiYGNasWaOUFSAnJ4fatWvz8ssvs3z5cg4cOMChQ4dYuXIlTz31FE5OTiQmJjJo0CCrm1UsXbqUjz/+GCEEvr6+yhpo+/fv56OPPsLBwYGRI0cqU76s8f333/Pkk0+SkZFBaGgos2fPZu/evRw5coRVq1YREREBwIIFC3j99ddt1t0ae/bsAXI9tbb+kSW8vb3p1KkTkLvZgPn3xsmTJ5VrsGPHjnh5eRU5X0sUp78r7fV+X1EuYSzJvwaLI5h0utxfUMvpl17TrxRqoKa2mvoVYUSD9L38kb5L39VCbd/VHMGUkpLyv/9kZOR+v+p0Baell/H38P0wgmnUqFEWR0iYiI6OVkYfTZkyxWIeBoNBjBkzRvm13vSrsqndjUajMk3EGlOnThWQOxLK0hSYmJgYpRz16tWzOU3MdMzcd9M28oWNHPrzzz8VndDQUIu/kG/evFlJ07p16wLHzUcwAeLtt9+2qVkYPXr0UPIqyhQkIfJd8/kwn85iyVOj0SgeeeQRJc2cOXMKpDEf+eHj4yNOnDhRQPvs2bPCxcVFAKJ///4F8khPTxdVqlQRgHBzcxORkZFWyxwbG1vgvWeffVZA7mgy86lb5nW/dOmSomFp9Jd5PRwdHcVvv/1WIE1cXJyoVq2aUs6bN28WSGO6voYNG1Zmn/fs7GxlRNXo0aPzHDt9+rRS7i+++EJ535bvhZGQkKCMDpw8eXKeY1u3blX01q1bV+DcL7/8Ms/IIWu0a9dOAKJOnToFjq1cuVLJY/78+RbPz8jIEF27dhWACAkJUUbymOptPoIJEAsWLLBZ53PnzuUZjZOfP//8Uxm9ZemzkpmZqXjk5+cnTp8+XSDN6dOnhZ+fn80RbbGxscLNzU3po6xNHZw8ebIAhJ2dnaJVVM+vXr2qlKFt27ZFOsecN998Uzl/yZIlyvvfffed8n7+66YkmK7BqlWrFpq2NNe7iftlBNN9HWC6efOmWL9+vXj77bdF7969lfmqRflStsTmzZvFoEGDRHBwsHBychLBwcFi0KBBYvPmzUXOIy0tTXz88ceiVatWwtfXV7i7u4v69euLl19+Oc88+8I4ceKEmDhxoqhTp45wcXERAQEBomPHjuKbb76x+kG2xNKlS0XPnj1FUFCQcHZ2FjVr1hRjxowRBw4cKHIe5lgNMJXB8PyikpCQUG5aFUlbTf2K8MApfS9/pO/Sd7VQ2/ci38QZjUKkppbpK/vOnf/9f/5824Gl/K/vviuxriElRVw7e1YYUlIsp7HxYFNabAWYEhISxJ49e5S1UEwPHFlZWQXyGTJkiABEixYtbD6IJSUlCWdn5zwPh8W5t8rJyVGmSc2aNavA8ZEjRyoBqCNHjhQpT3P9ogaYzKfn2Lqve/LJJ5V00dHReY6ZB5jq1atX6jVEmjVrpuRX1IcZa22fmZkpfHx8BOSuuWWtbMnJycozgKW1ucwDM19++aVVbZNvvr6+BfL45ptvlDw+++yzItXLxK1bt5TglXmAJb++EELMmTNHCSClpaVZrcezzz5rVW/58uVKuo8//rjA8XsRYDKfGmlpDahWrVopn00TxfnM5Wf27NmK3smTJ/Mcy8nJUQJ1Q4YMKXDuzZs3lalvL774osX8L168qOSffzqtEEK0aNFCAGLQoEE2y3ny5Ekln+3btwsh/ldv8wBT165di1TvwnjxxReVgHN+li5dquh9/vnnVvP44osvbAaYTNPCqlatavM7Mjs7W1mP7a233lLeKwpHjx5VylBYG1vi888/t/iZ//TTTy0GO0uC6ZkYEM2aNSs0fWmudxP3S4Dpvp4iV7lyZfr168d7773Hli1bSExMLFE+QggmTpxIeHg4a9asIS4ujqysLOLi4lizZg3h4eFMnDhRGTZtjfPnz9O8eXNee+01Dh06RFJSEmlpaZw6dYpPPvmExo0bs2nTpkLLs2DBAlq0aMG3337L+fPnyczMJCEhgT179vDUU0/RsWPHQuuamZlJv379GDVqFNu2bePGjRvo9XouX77M4sWLad++Pe+9916x2skc8c+QbgD69IF+/UqcV3HZtm1buWlVJO2KoK8m0ndtIn3XJveN7+np4OFRpi8HH5///f8//yle4Z98ssS6dl5eVKlbFzsvL8tpymnq4LvvvotOp1NeAQEBdOzYkc2bN+Pg4MCYMWPYsmVLgWlI2dnZbN68GYChQ4cqU88s4ePjQ6NGjQA4cOAAAMnJyRbTGo1Grl27xunTpzlx4gQnTpzg77//VqZU5Z92ZjQa2bJlCwCdO3emWbNmRaq3NX1bmHZqa9CgAQ8//LDVdP8xu45M51hixIgR2NvbF7sc5ty9e1f5293dvUjnWKt7TEwMd/6ZGjpu3DirZfPy8lJ2Kzt58qTV6T06nY7Ro0db1W7RogUASUlJiq6JjRs3ArnTdSZMmGC7QvnYunWrsj26qZyW9AFlak92djYxMTFW83z88cetHhs0aBA+Pj6Abb/LEtOubYGBgcpObuaMGTMGyPXUNN2xJNd8fr3mzZvz0EMP5Tlmb2+v7Da2YcOGAl4GBgYSFhYG5E6DM5qmG5vx888/K3/nv2bi4uIUb/L7mZ+HHnqIgIAAwHZfY2kKXmEkJSVx/vx5/vrrL6VvMvl+8uTJAtMDd+7cCeTu2mjywxJjxoyx2X+uW7cOgH79+uHi4mI1nYODgzKluLB+Nj8l6UfMMT8nJSVF+TshIaFU+ZpT3DKW5nq/37ivA0zmVK9enZ49e5bo3ClTpjBv3jwAmjVrxtKlS4mOjmbp0qXKjcG8efN4++23reaRmppK3759OX36NJD7Zb5z507279/P+++/j4eHB8nJyQwbNow///zTaj5bt25lwoQJ6PV6KleuzJdffsnBgwfZvHkzgwcPBuD3339n8ODBFjtEE+PHj2fDhg0AdOnShbVr1xIdHc2CBQuoU6cORqORqVOn8t133xWvsf7BGBEBpjm16emgpXmlEolEIpFIyp169erx2muvWVw34+TJk8r6WW+++WaeIJWl1+HDhwG4ceNGgbyEECxevJguXbrg4eFBcHAw9evXp1GjRsrr6NGjQN4HFoCLFy8qD7SmYMG9QK/Xc/bsWYA867RYolmzZkpA7sSJE1bTNW7cuNTl8vT0VP5OS0srVV7mZS2sjubHrdUxICAAf39/q3n4+fkpf5s/PAL88ccfALRs2RI3NzebZcmP6VoDqFKlSoEAqvn/Q0NDlbSWrk0AJycnm145Ojoqzy+2/C4r7ty5w6//rAE3cuRIHBwcCqQxf98UHCopp06d4tChQwBWAyWm9/V6PcuXLy9wfMiQIQBcv36dXbt2FThuWp+pZcuWPPjgg3mOmfs5atSoQvsaUx9hzU8o+mfv+PHjPPHEE1SpUgU/Pz8eeOABQkNDlX5p2rRpQG6gOykpKc+5pmuhRo0a+Pr6WtXw8/Ojdu3aFo8lJydz7tw5AL799ttC675y5cpC624J834kNTW1WOfmP8f8+8LDw0P5u7T9U1n2df827usA09SpU1m/fj03btwgNjaWb7/9tth5nDt3jo8//hjI7UT27dvHyJEjadWqFSNHjmTv3r20bNkSgI8++ojz589bzGfWrFmcOnUKgI8//ph58+bRtWtX2rZty+TJk9m2bRsODg6kp6fz4osvWswjJyeHZ599FqPRiJeXF/v27eO5556jdevW9O7dm1WrVvHMM88AsHv3bhYvXmwxn99++02JvPfr14/t27czYMAAWrVqxRNPPMHvv/9OjRo1AHjttdcKRPaLQs4PP8CMGbB7N+zYAaX8xas4mKLhaqCmdkXQVxPpuzaRvmuT+8Z3NzdITS3Tlz4x8X//798f7Ip4q2Znl5u+hLrGlBSunz2LMSXFcppiPlSXlKefflpZcPiPP/5g48aNTJw4EUdHR06ePElYWJjyY5451ha1LQxTUMr04JGZmUmfPn149NFHiYqKIiMjw+b5+Y+bB5xMCy4XBfMHn6Jg/vBYuXJlm2kdHR2VwMrt27etprP10FlUTKM1AG7evFmkc6zV3byshdUxKCjI4nnmWAoMmWvbmX3W8i/Ia/K1OJ6aKO21mR8/Pz+LQRxzTO1ly++yYvny5ej1esB6wMd8ZNPixYsxGo3FvuZNmBb3tre3Z9SoURbTNG/enAYNGgCWA1rDhw9XRp3kX+z76NGjysLQlkYWlVVfY05RPnsLFiygefPm/PDDD0UK2OTvm0x9hq0gq4lKlSpZfP9e1N0S5mUsbnAK8vY95nmZFrjPn6YkeHl5KYH7ouRV0uv9fsR271TBeffdd0udx2effabsEDB79mxcXV3zHHdzc2P27Nm0bduWnJwcPv/88zy7jkDuMNYvvvgCyB0K+fLLLxfQadu2LePHj+fbb78lMjKSmJgYZSiuiTVr1ihR4TfffJM6deoUyGfmzJksXbqUpKQkZs6cyWOPPVYgjSlgZm9vz5w5cwoMKQ4ICOCjjz5i1KhRJCUlsWDBAotlLhIdO5bsvFKg5hBDtYc3qq2vJtJ3bSJ91yZq+27+sGoTnQ5KOcw+Pwad7n/BnKFDi747nNEIw4aVvDxGI8LNLff8oga17gGBgYF5RnE0bdqUiIgI+vXrR//+/bl9+zajR48mOjo6z/2NeUBg5syZ9O7du0h6podM0/nvv/++MtWuc+fOTJo0iebNmxMUFISrq6sShOjUqRN79uyxuXyCrWkm+SnNDkNF0SlsmQeg1NPjAJo0acL27dsBOHLkCHXr1i30nKLUvbA6FqV+JdUuTjlsaTg5ORWY9paRkVHg2cOEaRpmScpQ0vYoCeYBnNatWxea/urVq0RGRpbohwSj0agEhAwGQ5ECfvv37+fcuXM88MADynsuLi4MGDCAn3/+mdWrVzN37lxlupfpR3o7OztGjBhRID/za2bJkiVFHn1kCiJZuuYK++ydOnWKp556ipycHAIDA3n11Vfp2rUrISEheHp6KoGO77//nvHjxwP35howL/uLL76oaBWGk5NTgfNtERwcTEBAAAkJCfz5558YDIZi9U9HjhxR/m7SpInyd8OGDS2mKSlNmjTh8OHDXLt2jZs3b9oMhGtpF7n7egRTaRFCKPNI69evb3X++sMPP6wMj1y7dm2BD2xUVJQyCmjs2LF5fgExZ9y4ccrfq1evLnB87dq1FtOa4+bmpsz3PXHihDI82kRqaqoyx7ZHjx5Wv5wGDx6sDBm0VJZic+cOfPJJuUyVM99usrxRU7si6KuJ9F2bSN+1iZZ9z/Or87Bh4OubG8iyhU6Xm27o0HtbOBXp06cPTz31FJD7YPDjjz/mOW7+K3V2djahoaFFetWqVQvIbXchhLJ0QIcOHdi1axfDhg2jTp06uLu757m/yz/9xIT5CJ5r164VuX6FjZTKj/mIh8J+4c/JyVFGsphPA7sXdO7cWfnbtG5RYViru3lZC6uj+QiC4tSxqO1u8rU4npowXZtZWVn4+/vnuf5q165t9do0raeTn8TExEIfVk0jTe613+fOnWP//v3FPu+nn34q9jUPsGvXLq5cuVLs8xYtWpTn/xkZGcpoq5SUFGVZESEES5cuBaBbt24WA1jmfY1pWmNRXsHBwYp2cfnxxx/JycnB3t6eqKgoXnnlFZo3b46fn1+e9eis9Uvwvz6jKGsW37p1y+L75nVPT08vct3r1asHFL3uOp2ODh06KDqmZ9uikJyczJ49e4Dc6980kg0gJCRE+Szv2bMnz/pMJaE4/V1JfL9f0XSA6eLFi8TFxQF5LxBLmI5fvXqVS5cu5TlmuogLy6dly5bKL2V79+4tcNyUz4MPPmjz11Nzjfz5REdHK8NUbZXFyclJCahFR0cXWAiuWBgM0KoVvPIK5OvAJRKJRCKRlBAXF/hnOojVIJPp/YULc9P/i3nnnXeU+6h3332XrKws5VjDhg2VX8lLukj87du3lUDG8OHDrf5gmJqaanGaHkCtWrWUB7ndu3eXqBxFGaHi7OysjA46ePCgzbR//PGHcp9nPjrsXtCzZ09lGsqKFSuU++ySYF7WwuoYHR1t8byyonnz5kDu+jvWpq5Zw3yh97LYwCArK6vA4vLm5OTkKGuEWWqLkozCsob56KW5c+eydOlSmy/TyMLVq1eXaN0ak56zszNLliwpVM80W2TRokUFBgj06NFDmQpmGrW0e/durl69ClhfeLus/SwKf/31F5A7Yib/oubmmK8PlR/T6J3Y2FibUydv377NhQsXLB6rVKmSEijbsWPHPR0pN3bsWOXvL7/8ssjnzZs3TwnmjB07Ns/1rtPplEEcaWlpJV6L2IT5gJDZs2drapSSTcplr7pywnxLycK2dhVCiA0bNhR5y1HzbQ03btyY59jQoUOVY0lJSTbzady4sQBEpUqV8rx/9+5dodPpBCAGDBhgM48jR44oeq+++mqeY1999ZVybM2aNTbzef7555W0f/31l820JkxbMsbHx+c9MHNm7hbJVarkbmd8DymLbR7vR2019SvCtuXS9/JH+i59Vwu1fS/pVsBlgdFoLPjmunVC+Prmfs/a2eX919dXiF9/LbWuwWAQcXFxZbZteXGIjIxU7kfeeecdm2lfeuklJe28efPyHAsPD1eOHTx4sFhlMBqN4saNG8r5M2bMsJrWfAtsS9t4P/LIIwIQOp1OHDlypMj6JurXry8AMXLkSJvnPP3000o5Dhw4YDXdhAkTlHTR0dF5ju3cuVM5FhkZWaSyFob5PXOvXr1ETk6OzfSmul+5ckXs3LlTeT8zM1P4+PgIQDRs2NBqPikpKSIgIEAAokGDBgWOjx07VgCiZs2aVrWFyLtt/MWLF/Okmz9/fpGfGfJz9epV4ejoKADRpEmTPP2bxc+7FUz1AMTzzz9vNd0vv/yipPv4448LHDddXwMGDCjV591oNIpatWoJQISGhhbpnPXr1ytlW7hwYbH0UlNThbu7uwBE3759i3TO7NmzFb3du3fnKbsQQjz77LMCEM7OziIpKUn85z//EYBwcXGxuaV7gwYNlHSXL18uVj1M2raut/z07t1bAKJ+/fpW01y/fl24urpazfPnn39Wjn3++edW8/niiy9s9m/m/c4vv/xis9z5Kc71bjAYlGsVEEuXLi30nLNnzwoPDw/Fm0uXLhXQv3r1qnBzcxOAcHd3F3///XeRy7No0aIC7/fv318p43vvvWf1/Px13717t7hw4UKRtE2U9N4kPj5eADav6bJE0yOYzIdYWptKZqJ69eoWzzP/v7u7u9XhrPnzuXXrljLSCHJHRol/osBlUZbS5lNsnnsOatWC69dh5szS5VUIpu1/1UBN7YqgrybSd20ifdcmWvbd4vpT/fvDtWu5o4QHDoSwsNx/Fy3Kfb9fv3IupXq8+uqrylopM2bMyPOL8VtvvaX8Wj1y5EirG7NA7noYP//8szJaITk5mUqVKin3ccuWLcszQsrEoUOHmDJlis0yvvLKK9jZ2SGEYOTIkYqGJcz1TZim5dgqP+QuiG4aZTVhwgSL1862bdtYsGABkLs+TqtWrWzmWRa88MILdOnSBcjdHXnQoEFWp9xA7i5kS5YsoUWLFnl2WnZ2dubJJ58EckdwWFp7VQjBs88+qyzC/eyzzxarrEVd723MmDHKyI233nqL3377zWra/H4HBwfz+OOPA3Ds2DEmTpyorP9qST8+Pr7QkRVz5861OBvixo0bvPLKK0Dushrmo0BMmK6vy5cv29QojD179nDx4kUAhhZxem7Pnj2VJTp++OGHYumtWrVKGfVUVL3BgwcrfYL5aCtTu5tGKen1en7++Wdl17P+/ftb3K3ShKkPyMzMZPDgwTavb71ez5w5c8jMzMyjXRxMoxXPnDnD77//XuB4eno6o0ePtjkNa9CgQQQGBgIwffr0AsusAJw9e7bQNY5fffVVnJ2dAXjqqadsjpoC2LRpk/K5Lk7d7ezsWLRokTIFcOzYsRZ3BDTx559/0q1bN2UHuZkzZ1KzZs08aZKTkwkODuarr74Cckcxde7c2ebnGXKnzvfq1YtZs2YVOPbtt98qay+9/fbbTJ061eJ3h6nuaWlpvPvuu3Tr1u1fu9bmfb3Id2kx34K0sJXd3c0Wzcy/XaIpn6KsDp8/H9MHtKzLUtp8TOj1+jyBMNNc1fzvA9j93//h+MgjiI8/Juuxx+CfL+Ky5s6dOwW0yws1tdXUN2lqse5qa6upL32XvquF2r5nZWUhhMBoNGI0GstV32AwWNZ0coLRo3Nf+SmDMpp+5DLVuzwx1ytMPzAwkCeeeII5c+Zw4cIFFi9ezKOPPgrkbqjy9ttvM336dC5evEjTpk154okn6NGjB1WqVEGv13Pp0iV+//13Vq1axbVr1zh27BhVq1ZVAlWjR49mzpw5HD16lI4dO/LCCy/wwAMPkJyczObNm5k7dy4eHh5UrVqVM2fOFCg/5G45Pm3aNKZOncqZM2do1KgRzzzzDGFhYfj7+3Pnzh2OHTvGmjVrsLe3Z+fOnXl8b9u2LZGRkRw6dIgPP/yQ3r17K/dsrq6uSqCjYcOGvPTSS8yaNYvjx4/TvHlzXn31VZo1a0Z6ejobNmxQpm04OTkxd+7cAmUVZlNcyvJ6X7ZsGf379+fgwYOsX7+eOnXqMHr0aLp06UK1atVwdHTkxo0bHDx4kBUrVigPu/n9nzJlCqtXr+bChQu89957HD9+nMcff5yqVaty8eJF5syZQ1RUlNJuTz75ZKF1NMe83c2P5W8LJycnFi5cSO/evUlPT6dbt26MGTOGgQMHUq1aNfR6PadPn2bz5s38+uuvBR70Z86cyf79+zlx4gTff/89v//+O//5z3+oW7cuVapU4c6dO5w8eZIdO3awefNmGjVqxBNPPGGxHpUqVcLNzY0ePXrw4osvEh4ejrOzs3K9mNaJmj59OgEBAQXqbLq+jh49yowZMwgPD7d4fRWG+TpogwYNKtK14+DgQJ8+fVi6dCm7d+/mypUrRdYz7R7n6OhI3759i6QXFBRE27Zt2b9/PytWrOCLL77AxcVF8b1169Y88MADnDt3jrfeektZU3fUqFE28x8xYgRbtmzhp59+IiYmhgYNGjBhwgQ6depEpUqVSEtL4/z58+zdu5c1a9Zw+/ZtxowZg5OTk6Jt63rLzyOPPMLs2bMxGo1ERETw6quv0rZtW1xcXIiJieGLL77g7NmztG/fnn379lnM08nJiU8//ZQxY8Zw+/Zt2rRpw+uvv07HfzZs2rNnDx9//DFGo5G6dety9uxZdDpdgXLVrFmTOXPmMH78eG7fvk379u0ZM2YMffr0oUaNGuTk5HD16lUOHTrEqlWrOH/+POvWrSM0NNT695sVmjdvzsKFCxk3bhxZWVmMHDmSefPmMXLkSOrXr4+TkxOxsbGsX7+epUuXKoHb559/nmeeecbq533s2LFcuXKFd955h/j4eMLCwujRowcDBgygfv36+Pj4cPv2bc6cOcOmTZvYunUrBoOBJk2aFMgzMDCQX3/9lf79+3Pz5k3ee+89Fi1axKhRo2jXrh2BgYFkZWVx5swZoqOjWb16tRKQLG6fazQaEUKQlZVVrKmu5X0/pROiHLcZuMdcunRJWaxx7NixBRaAzM97773H1KlTAdi5cyddu3a1mnbXrl1069ZNOc/816s6depw4cIFqlevTmxsrE3Nxx57TFlo7sqVK8oooz179tCpUycA5ebIGkajUVlJv1u3buzYsUM5Nn78eL7//nsg95ev2rVrW83HfKeBRYsWWdxadNq0aRYj2W+88YbyC6KCEDz+/ffUuHKFo02asG7QIKvaEolEIpFUVNzd3Wnfvj3BwcGFbgcuKT379+9n2LBhALz00kuF7mwbFxdHhw4dyMrK4oEHHiAyMjLPeknz58/nww8/LPSm2snJiV27din3jpD7Q9rQoUOVNU/y4+Pjw4IFC5g1axYHDhygbdu2yqiH/MyePZtZs2YpDz2WsHT+9evX6d69u/Kwayu90WhkypQpysO3Jby8vPjmm28srs1p3vYrVqygXbt2VvMpLpmZmXzwwQcsWrTI4i/65uh0OgYNGsRbb71VYB3SK1euMGbMGGWnZUu0atWKH374weJ27y+++CIrVqygWrVqNtdyWr58OS+99BIAv//+e56R/iaioqKYNGmSRW/MsbT2VFJSEs899xyRkZE2zwVo164dK1assFqPefPmKYECS4wfP97qs0Rxri9rZGRk0KxZM+7evUudOnWKtd7Y5s2blZFpkydPZtKkSYWec+3aNdq0aYPRaCQsLEzZSa4ozJs3T3mWmTNnDgMGDMhzfNasWXz22WfK/318fPjjjz+UNd2sYTAYmDFjBt9++22ha++4ubnx559/5tkxsCjXmzmfffaZxRE0JiZOnMiDDz5YaJ5ffPEFM2fOtLh+kqurK99++y1ff/01Bw8epEuXLixevNii3rp163j99dfzDG6whJ2dHcuWLaN9+/Y209ni999/54033rA46socHx8fXnvtNYsj9yyxadMmpk+fXqSZPA8++CDvvPOO1TWOr169yuTJk4u0ILmbmxtPP/00kyZNUgabFIWcnBzi4uLYt29fsdYwy8zMZMaMGSQnJ9scmVdWaPquyTxAUtgXn/lNSv7tRE35FJaHrXzKuiylzcfEm2++qXRUkHvjVb16dSZNmqQsjGeOrls36NSJpseO0WDuXMQ/iyKWJcnJyXh7e5d5vhVdW019vV7PZ599xn//+99idYRlifRd+q4lbTX1pe/JuLi4cPXqVQICAgr+mHKPKe52zGWFEELZZrksFwEuCuY7XXl4eNjc6ARyRyU89thjfPfdd5w7d459+/YpQRLI/aHuiSeeYN68eezYsYNz585x584dnJ2dCQ4OJjQ0lO7duzNkyBBlRyFTuwcFBfH777/z2WefKSNrHBwcqF69OhERETz//PNUq1ZNWXTWycnJannff/99xo0bx9y5c9m5cyexsbFkZWVRtWpVatWqRd++fRk+fDhBQUF5fA8KCiI6OpoZM2Yoiw6bptdY0vv+++95/PHHmTdvHnv37uXmzZs4OztTu3ZtwsPDeeGFFyzes0He3ej8/PwKbfviMm/ePKZMmcKyZcvYsWMHZ8+e5datWwgh8PPzo2HDhnTs2JExY8YUmM5iIigoiOPHj/Pdd9+xcuVKTpw4QUpKCn5+fjRt2pTRo0czevRoq4uym+5xTf6aY97u5n1OpUqVLLbFyJEj6d27N9988w0bN27k9OnTpKSkEBgYSLVq1ejatSsjR460eG5QUBA7duxg165dLFmyhH379nH9+nUyMzPx8vKiTp06tGrVioiICHr27FmgHzCvR69evThy5AiffPIJmzZtIi4uDnd3d1q2bMlzzz1HeHi4NUsICgri4MGDTJs2jUOHDhV6fVli6dKlSmDBdA0XlZEjR/LCCy+QlpbGunXreO+99wo958cff1RGelhrX2uMGzdOCTCtX7+eiRMn5vF9woQJeQJMw4YNo0aNGkXKe/bs2Tz33HPMnz+fyMhILl26REpKCm5ubtSoUYMmTZrQo0cPBg0ahKenJ/C/a64o15s5H330EZ07d+bLL7/k8OHDpKWlERgYSKtWrZg4cSI9evTIM7jCUp5CCF544QXCw8P5/PPPOXDgAMnJyQQFBdG1a1defvllHnroIT755JNCyzVx4kSGDx/O/Pnz2bp1KydPniQpKQlHR0eCgoJo0KABXbp0YciQIUqgq6TfbwMHDqRfv36sXLmSX3/9lcOHD3Pz5k2ys7OpVKkSDz30EBEREYwZM8ZikNlEfv0nnniCMWPGsHLlSrZs2cLhw4eJj4/n7t27eHl5ERISQps2bRg8eDBdunSx+d0YFBTEtm3bOHToEKtXryYqKoorV66QmJiIk5MTgYGBNGvWjB49ejBixIgSBXoyMzNJTU1lwoQJxbo/u3XrFjNmzCi2Xokpl5WeyoniLvI9d+5cJf2KFStspl2xYoWS9ptvvslzrE2bNspCYYXRp08fJR/zBVT//vtv5f1JkybZzOPWrVtK2vwLQL7++uvKsUOHDtnMZ+bMmUraLVu2FFp2IWws8m3OmDFCPP64ENeuFSnP4vLzzz/fk3wruraa+hVh0V/pe/kjfZe+q4Xavqu5yHdCQkK5awqh7iLfJtSqu9raaupL3+8f320tVl5cpO/a1C6K71lZWcpi4VOmTClT/fvp81YRteUi3/cB5otg21qAEfIugp1/uKEpn7S0tEKHzJryqVSpUp7IY1mXpbT5lIqFC+H77+GfRQQlEolEIpFIJBKJRFKxWbt2rbKG2MMPP6xyaST3I5oOMDVo0ED5+9SpUzbTmh9/6KGHSpRPTk6OsiNI/jw8PDyUIE95lMX8uIODAw888IDNtMUi/xDlMl7mqzx2QKmI2hVBX02k79pE+q5NtOy7+QYcWkPNuqvd7mrrq4n0XZto1Xe1PTft/GeJS5cuKUujVK5cmV69epWpttp117Lv5YmmA0y1atWiatWqAIVuT2havC44OJiQkJA8xzp06KD8bSsf03xZwOJCZ6Z8Tp8+zY0bN6zmY66RP59WrVopi9LZKktWVpayzaX5OWXK2bMwaBD8s05BWWGaJ64GampXBH01kb5rE+m7NtGy7+Lfs/dKsVGz7mq3u9r6aiJ91yZa9V1tzzt37syAAQOYN28e+/bt4+jRo2zbto0333yTZs2aKTNgZs2aVeabXKhddy37Xp5oOsCk0+mUnQROnTqlBFzy8/vvvyujfQYMGFBgga+wsDBlobaFCxdavYDyb+eZn4EDB1pMa056ejq//PILkDtaqV69enmOe3p6Krvd7dixw+o0udWrV5OSkmK1LGVCVBSsXQvvvgtWdrkoCcePHy+zvO4n7YqgrybSd20ifdcmWvY9PT1dVX01UbPuare72vpqIn3XJlr1XW3PDQYDGzZsYOLEiXTo0IFmzZrRq1cvZsyYwZ07d7Czs+ODDz6wuLt4aVG77lr2vTzRdIAJcrf8NEVnn3vuOWXOqYmMjAyee+45IHcq2YsvvlggDycnJ55//nkA/v77b4tbSB44cIAFCxYAuZFjS0PwBw0aRJ06dQD48MMPlel05rz66qskJSUpf1vilVdeAXKn5E2aNKnA1pkJCQm8/vrrQO52jqatQsucJ56ARo0gKQmKsEOERCKRSCQSiUQikUjuDT/++CNPP/00TZs2pUqVKjg5OeHp6Un9+vV56qmnOHbsGG+++abaxZTcx+jEfTxea+/evZw7d075f0JCghJ0ad++fYHAybhx4yzm8+abbypb9zVr1ozXX3+dOnXqcP78eT766CP++OMPJd0HH3xgMY+7d+/SsmVLzpw5A+RueTly5EhcXV2JjIzkgw8+IDU1FVdXV/bv30/Tpk0t5rNp0yb69euH0WikcuXKTJkyhdatW5OUlMT8+fNZtWoVkDudLioqyupWj6NGjWLZsmUAdOnShRdffJGqVaty/Phx3n//fSV49c033zBx4kSLeVgiJSUFb29v4uPjrW55m4ft26FnT3BwgL/+gnwjrkpCZmZmuW8bXRG01dTX6/XMmDGDN954Q7Vty6Xv0nctaaupL33PnSJ38eJFatWqVe7lMBqNVrdbv9e6N27cICgoSBV9Uxm0qK2mvvRd+q7Ftteytpq+a/XzVlbamZmZJbo3uXXrFoGBgSQnJ+Pl5VWqMhSJctmr7h5h2q6zqC9rGAwG8cQTT9g8d/z48YVu5Xn27FlRt25dq3l4eXmJ9evXF1qvefPmCScnJ6v5tG7dWty6dctmHunp6SIiIsJqHnZ2duKdd94ptCz5SU5OFoCIj48v+knh4UKAEAMHFlvPEps3by6TfO43bTX1K8K25dL38kf6Ln1XC7V9L+lWwGXBnTt3yl1TiIqxbbladVdbW0196bv0XS206rua2mr7rtXPW1lpl/TeJD4+XgAiOTm51GUoCpqfIgdgZ2fHggUL2LhxIwMGDKBq1ao4OTlRtWpVBgwYwKZNm/juu+8KjTo+8MAD/PHHH3z00Ue0bNkSHx8f3NzcePDBB/nvf//Ln3/+Sd++fQstz3/+8x9iYmL4z3/+Q+3atXFxccHf358OHTowd+5c9u3bR0BAgM08XF1d2bhxI0uWLKFHjx4EBgbi5ORE9erVGT16NHv37mXatGnFaaaSM2sW2NvnrscUFVXq7ExTBNVATe2KoK8m0ndtIn3XJlr2PScnR1V9NVGz7mq3u9r6aiJ91yZa9V16rk19tetenpTt0vDlzI8//mh1MeySEBERQURERKnycHd357XXXuO1114rVT6hoaHMmzevVHkAjB49mtGjR5c6n1LRoAFMmABz58Jnn0FYWKmyKyy4di9RU7si6KuJ9F2bSN+1iZZ9d3R0VFVfTdSsu9rtrra+mkjftYlWfZeea1Nf7bqXJ/d1gElyH/Huu1CzJvyzGHppaNu2bRkU6P7Trgj6aiJ91ybSd22iZd/d3d1V1VcTNeuudrurra8m0ndtolXfpefa1Fe77uWJnCInKR8qVYLXXwdX11JntX79+jIo0P2nXRH01UT6rk2k79pEy77fuXNHVX01UbPuare72vpqIn3XJlr1XXquTX21616eyACTpPwxGOCfnfkkEolEIpFIJBKJRCKR3P/IAJOkfImPh2bNoEMHuHatRFk0a9asjAt1f2hXBH01kb5rE+m7NtGy725ubqrqq4madVe73dXWVxPpuzbRqu/Sc23qq1338kQGmCTlS6VK4OEB6ekwZYrapZFIJBKJRCKRSCQSiURSBsgAk6R80eng009z//7xxxJNlftDxel1ampXBH01kb5rE+m7NtGy7+np6arqq4madVe73dXWVxPpuzbRqu/Sc23qq1338kQGmCTlz8MPw8iRIAS8/HLuvxKJRCKRSCQSiUQikUjuW2SASaIOH34Izs4QGQnF3LGnX79+96hQFVu7IuirifRdm0jftYmWfffx8VFVX03UrLva7a62vppI37WJVn2XnmtTX+26lycywCRRh5AQ+O9/c/9+5RXIyiryqQcOHLg3Zarg2hVBX02k79pE+q5NtOx7Wlqaqvpqombd1W53tfXVRPquTbTqu/Rcm/pq1708cVC7AJL7g6+//pqvv/4ag8EAwNq1a/Hw8GDw4MHs3LmT5ORkAgMDad26NRs2bACgefPmGI1Gjh49CsCAAQPYu3cviYmJ+Pn50enFF9HNmcNdnY7b+/ahCw4mJiYGgD59+nD48GFu3ryJl5cXPXv2ZOXKlQCkpKRw4cIFDh48CECvXr04ceIEcXFxuLu707dvX5YvXw7Agw8+SEBAAPv27QOge/funDlzhtjYWJydnRk8eDDLly/HaDRSp04dgoOD2b17NwBhYWHExsZy4cIFHBwcGDZsGMePHychIYGaNWtSp04ddu3aBUCHDh2Ij4/nzJkzAIwaNYp169aRnp5OtWrVaNCgAdu2bQOgbdu2JCcnc/LkSQCGDRvGli1buHv3LkFBQTRv3pxNmzYB0KpVKzIzMzl+/DgABoOBLVu2kJSUREBAAG3btmX9PyPATDsfmdYP6devHwcOHCAhIQFfX1/CwsJYs2YNAI0aNcLFxYVDhw4BEBERwZEjR7hx4waenp707t2bFStWANCgQQNcXV0BWLlyJb179+bkyZNcvXoVNzc3BgwYwNKlSwGoV68egYGB7N27F4CuXbty/vx5Ll++jJOTE0OGDGHFihXk5ORQu3ZtatSoQVRUFACdOnUiLi6O8+fPY2dnx4gRI1i9ejV6vZ4aNWoQFxen6LRv356EhAROnz4NwIgRI9iwYQNpaWkEBwcTGhrK1q1bAWjTpg2pqan89ddfAAwdOpRt27aRkpJC5cqVadmyJRs3bgSgRYsWZGdn8+effwIwcOBAdu/ezfHjxxFC0KFDB9atWwdA06ZNsbOz48iRIwD07duX6Oho4uPj8fb2plu3bqxevRqA0NBQ3NzciI6OBiA8PJxjx45x7do1PDw8iIiI4JdffgGgfv36+Pn5sX//fgB69OjBmTNnSEhIwNXVlYEDB7Js2TKEENStW5egoCD27NkDQJcuXbh06RIXL17E0dGRoUOHsnLlSrKzs6lVqxYhISFERkYC0LFjR27cuMHZs2fR6XSMHDmStWvXkpGRQfXq1alfv77ShrGxsaSmpnLq1CkAhg8fzqZNm0hNTaVq1ao0adKEzZs3A9C6dWvS09M5ceIEQOn6iE6dOHbsGAkJCTRu3BhHR8ci9RENGzbEw8Oj1H3E9evX6dGjR7H6iFWrVpGVlVUmfYSp7sXpIwYNGkRUVFSp+gij0QjAhQsXFG8K6yO8vb2VwEzPnj1L3UdcvnwZLy+vYvUR9erVY8eOHaXuI4xGI1FRUQQEBJCamoqjoyN37twBwN3dHSGEspaCr68vd+/eJScnBwcHBzw8PJS0bm5u6HQ65abSx8eHtLQ0srOzcXBwwNPTk6SkJABcXV2xs7NTjru5uZGRkUFWVhb29vZ4e3tz+/ZtJa29vT2pqakAeHl5kZmZSVZWFnZ2dvj6+nL79m2EELi4uODo6Mjdu3eVtHq9Hr1ej06nw8/PT0nr5OQEoJTJ09OT7OxsMjMzlbRJSUkYjUacnJxwcXEhJSUFAA8PDwwGAxkZGQD4+fmRnJyMwWDAyckJV1dXkpOTlTY0Go1KWvM2zMnJwd3d3Wp7+/j4kJqaqrS3eRvaam97e3u8vLzytLd5G3p7e5OZmamkNW9vFxcXHBwc8rS3qQ0La29PT0+ysrLytLepDZ2dnXF2dlbaUAhBWloamZmZAPj7+3Pnzh2LbWirvR0dHXFzc8vT3tauWVNak++mv83b29o1m7+9vb29SU9Pt9iGltrb/Po2GAwkJiYq7W3tms3f3s7Ozjg5OeVpb2vXbP729vDwICcnRymzrWs2f3v7+vqSkpKitLeta7awPkKv1yt1L2ofYakNi9tHmPJNT0/P04a2+oj8bVjaPiIjI4Ps7Oxi9RGFtXdR+4js7Gzc3d2L1UdYa+/i9hFZWVmK58XpI8zbG0reR0Du84SproX1EebtXdo+wuR5cfsIHx+fMukjzPvZovYRpvYubR9h6mtKcx/h4uJCZmYmGzZswM3NrcjPGuWNTgi5AI6k6KSkpODt7U18fDyVKlUqfYaXLkHNmrmLfxeRLVu20Lt379JrlwA1tdXU1+v1zJgxgzfeeANnZ+dy1wfpu/RdW9pq6kvftxAWFsbFixepVasWLi4u5aqfnJyMt7d3uWpCbmDtxo0bBAUFYWenzgB3tequtraa+tJ36bv0XTvaavuu1c9bWWlnZmaW6N7k1q1bBAYGkpycjJeXV6nKUBTkFDmJuoSEFCu4BLmjBtRCTe2KoK8m0ndtIn3XJlr23dPTU1V9NYiKikKn0+Hj44NOp8vzcnV1pVq1aoSHhzNnzhzlF+6yRu12V1v/XnLlyhVmzpxJz549qVWrFh4eHri6uhIcHEyvXr348ssvuXjxoiplU7vd1da/F2RkZODt7a18hqdPn24xXVnV/cqVK9jb2yt6P/30U6HnqNnu/0bPi0px627+XVCzZk2yCllS5ccff1TSm0Y/29LPzs5m2bJljB07loceegh/f38cHR0JCAigRYsWPP300+zYsUMZ2Z2fkJAQdDodISEhhdZFS77LAJOkYpCcDK+/DufOFZrUNM1LDdTUrgj6aiJ91ybSd22iZd9N0wskuWRmZhIXF8eWLVuYNGkSoaGhHDt2rMx11G53c33TQ8u4cePUK1AZoNfrefnll6lbty6vvfYa27dv59KlS8oUlWvXrrFt2zamTp1KnTp1GDFiBFeuXCnXMlYk38uLkJAQ7O3tefHFF+9J/mvWrFGmGQEsWrTIYrqyqvuiRYvyBACKEmBS03e1rzk1KU3dY2NjmT9/fpnpr1u3jvr16zNq1Ch++uknTp06xe3bt8nJySExMZEjR47wzTff0KNHDx566CFlOY2y0P63IwNMkorBU0/Bxx/nBpkkEolEIpFokqeffprjx48rr8jISL755hvq1asHwOXLlwkPD1fW1JBUTBITE+natSuffvoper0eT09PJkyYwPLly9m3bx/R0dH8+uuvvP7669SuXRshBL/88gurVq1Su+iSUmIK8Hh4eABw7tw5ZV3Je4EpgGXSi4yM5OrVq/dMT6IeH3zwgbImUmn48MMPGTRoEBcuXABy19+cPXs2O3fuJCYmhu3bt/PVV1/Rq1cv7OzsOHPmDG+99VapdbWCDDBJKgZTpoCdHaxeDf8soGuNRo0alVOhKpZ2RdBXE+m7NpG+axMt+25aRFWrBAYGEhoaqrzCwsKYOHEix48fp2vXrgBcv36defPmlamu2u2utn5ZYjQaGTlypBJUiIiI4Ny5c3z77bcMHz6cdu3a0apVK/r168eMGTP4888/WbhwIYGBgeVeVrXbXW39sub69evKZgtTp07F398fsDyqqCzqHh0drWxA8sknn+Dg4IDRaGTx4sU2z1Oz3f9tnheHktY9ICAAgGvXrjF37txS6S9atIjJkycjhKBSpUrs2rWL7du38+yzz9K1a1eaN29O9+7dmTRpElu2bOHo0aPKd09p0JLvMsAkqRg0bAgTJuT+/dJLYGWuK1DuC65WFO2KoK8m0ndtIn3XJlr2XVfMdQm1gpOTE9OmTVP+v3379jLNX+12V1u/LJk9e7YSZOjevTvr1q2zGTyyt7fnscceIyYmhsaNG5dXMQH1211t/bJm8eLFGAwG7O3tefTRRxk+fDgAv/zyC3q9Pk/asqj7woULgdyduMaNG0ePHj2AwqfJqdnu/zbPi0NJ6x4REUFoaCgAH330kbIDW3G5fv06Tz/9NJAb8ImKiqJLly42z2nUqBHbt2/nlVdeKZGmCS35LgNMkorDu++CpyfExMCSJVaTHTp0qBwLVXG0K4K+mkjftYn0XZto2XfTdsQFyMyERYtgyBAIC8v9d9Gi3Pc1QvPmzZW/C1ur5/Tp0zz//PM0bNgQb29vXF1dqV27No8//jhHjhwpkN683a9fv86cOXMYOnQodevWxd3dHWdnZ4KDgxkwYADLly+3uuhrfi5dusTrr79OixYt8Pf3x8XFhVq1atGlSxc++eQTYmNjFf2wsDB0Oh2XL18Gch+e8y96bm0R+r179/Loo48SEhKCi4sLPj4+NGvWjClTpnDr1i2r5YuKiiI4OBh7e3uioqIwGo18//33dOnShcqVK2NnZ1estaCys7OZOXMmkBus/eGHH3BwcLB5jqntq1WrZnWkQFZWFnPmzKFLly5UqlQJJycngoKCiIiIYPHixTb9GDduXJ6FeO/cucPUqVNp2LAh/v7++Pj40KlTJ5bYuPc05+7du3zyySd07dqVoKAgnJ2dqVq1Km3atOH111+3eH2ZEEKwcuVKhgwZQvXq1fHx8cHX15fWrVvz3nvvKduTF6UecXFxvPTSS9SrVw83NzcqVapEREQEmzdvtnh+/utrxYoVeRbHtnV9FRXTdLVu3boRFBTEmDFjgNz1Z9avX58nrdW+rohkZWWxfPlyAIYNG4aTk5Oi9/fff3P48OEC57z77rvK5gFnz54tVCMiIgKdTkflypXJycmxmCY6Opr//Oc/1KtXDw8PD9zd3alfvz6TJk2yqGGqt/mC1JcuXUKv1/P555/z8MMPExAQgE6nyxNUz8rKYv369Tz77LO0atUKX19fHB0d8ff3p02bNkybNo2EhIRC6wSwZ88eBg8eTOXKlXFxcaF27do89dRTnPtnLVzTtVLY9XD16lXefPNNmjdvjq+vLy4uLtSoUYMRI0YQGRlpte7FRafT8e677wJw8+ZNvvrqqxLl8+mnnyplePfdd2nQoEGRzrOzs1OurZJS2uv9vkJIJMUgOTlZACI+Pv7eCMyYIQQIERwsRFqaxSQ///zzvdEuAmpqq6mfmZkppk2bJjIzM1XRF0L6rgbSd+m7Wqjte0ZGhjh58qTIyMgod/2EhISCb65bJ4Svb+73o51d3n99fYX49ddS6xoMBhEXFycMBkOp8youkZGRAhCAeOedd6ymy8jIUNI1btzYarrp06cLBwcHJW3+l06nE1OnTs1zjqndc3JyhJ2dndVzTa8ePXqIu3fv2qzXzJkzhaOjo818OnfurOh37ty5UF1TehMGg0FMmjTJ5jne3t5i27ZtFsu4c+dOJd3mzZtF9+7dC5w/duxYm/U0Z/369cp5Y8aMKdI5Fq95My5duiQeeughm3Xs0KGDSExMtHj+2LFjBSBq1qwp/v77bxESEmI1n0mTJtksy/bt20VAQEChPlkiPj5etG/f3uZ5lStXFr///nuh9Th06JAIDAy0ms8LL7xQ4PySXF/F4ciRI0o+P/30k/J+7dq1BSD69euXJ31hvhfG6tWrFb3du3cLIYRIS0sTHh4eAhDPPfdcgXPOnTunnDNt2jSb+d+6dUvpRyzllZ2dLZ5++mmb7eno6CjmzZuX5zxTvX/44Qcl3aFDh0TTpk0LnG/eH5r8t/Xy9/cXe/futVong8EgXnvtNaHT6Sye7+npKbZu3apcK7auh++++064urraLM/48eNFdnZ2gboXFfM+yGg0Km3k7+8vUlJSCqQ3b9PIyMg8x4xGo/LZdXd3F8nJycUqiyVq1qypfCYLo7TXuxCixPcm8fHxAiiTOhcFGWCSFIt7HmDKyBCiZs3cm+b33rOY5M6dO/dGuwioqa2mfkV44JS+lz/Sd+m7Wqjtu5oBJvObcSFEbnBJp8t9QcGX6di6daXSvR8CTDExMUq6/v37W0zz9ttvK2natWsnvvvuO3HgwAFx+PBhsWTJEtG2bVvl+JdffqmcZ2r37OxsYWdnJ7p27SpmzpwptmzZImJiYkRUVJT4/vvv85z/2GOPWS3r9OnTlXQ+Pj5i8uTJYvv27eLIkSNi165dYtasWaJ9+/YiLCxM0b1w4YI4fvy4qFq1qgDEgAEDxPHjx/O8Lly4kEfn1VdfVXRq1aolvvnmGxEdHS0iIyPFf//7XyXA5eTkJI4ePVqgnOYBpsaNGyttu3r1ahETEyM2bdokli1bZrWe+XnllVeU/Ip6XoFr3oy7d+8qAQpADBw4UPz666/i8OHDYsWKFXmCJm3bthU5OTkF8jA9mFeqVEnUrVtXeHp6iilTpoioqCjx+++/i/nz54tq1aop+WzZssViWXbt2qUEHOzt7cW4cePEmjVrRExMjNi3b5+YP3++GDx4sHB0dCxwbmpqqhIkc3JyEhMnThTr1q0T0dHRYs+ePeL9998X/v7+AhC+vr7i0qVLNusREhIinJ2dxRtvvCF2794tDh48KL788ktRpUoVpR6ffPJJnvPzX1+9evUSx44ds3l9FYcXXnhBAMLNzS1P8NX0mXR0dMzz/GDL96IwYMAAAYiQkBBhNBqV9x999FGlnbKysgqc16ZNGwGIunXr2sz/q6++UtrSUtDvscceU46Hh4eLxYsXi+joaHHo0CExf/580bBhQ+X4r2Y/ApjqbR4Mady4sdDpdOKxxx4TGzduFDExMWLNmjVi06ZNynmPPPKIqF27tnj55ZfF8uXLxYEDB8ShQ4fEypUrxVNPPSWcnJyUet+8edNinRYvXqxo+vr6ihkzZoj9+/eL/fv3i48++kj4+voKX19fUa9ePZsBpgULFij5hIaGitmzZ4u9e/eKI0eOiFWrVomIiAjl+EsvvVSg7kXFPMAkhBC//vqr8t57Fp4TbQWYTpw4oRzr3bt3scphjeIEmEp7vQshA0ySfyn3PMAkhBDLlwsxdqwQV69aPLxr1657p10IamqrqV8RHjil7+WP9F36rhZq+65mgCnPDWBGRu4IJWvBJfMgk69vbvoScj8EmEaNGqWkMx8hYSI6OloZfTRlyhSLeRgMBjFmzBjl1/qkpCQhxP/a3Wg0irNnz9os79SpUwXkjoQ6c+ZMgeMxMTFKOerVqyeuXLliNS/TMXPfTQ8thY0c+vPPPxWd0NBQpS7mbN68WUnTunXrAsfNA0yAePvtt21qFkaPHj2UvCy1jSVsPfSYB6wseWo0GsUjjzyipJkzZ06BNOYjP3x8fMSJEycKaJ89e1a4uLhYDV6mp6crwRs3N7cCD6/mxMbGFnjv2WefFZA7muzQoUMW637p0iVFw9LoL/N6ODo6it9++61Amri4OCVY5ubmZjHQYLq+hg0bVmaf9+zsbGVE1ejRo/McO336tFLuL774Qnm/NA+7CQkJSvB08uTJeY5t3bpV0VtnIfD+5ZdfKsfNvchPu3btBCDq1KlT4NjKlSuVPObPn2/x/IyMDNG1a1clCGYKMJjqbR4MAcSCBQts1vncuXN5Amn5+fPPP5XRW5Y+K5mZmYpHfn5+4vTp0wXSnD59Wvj5+SllshRgio2NFW5ubkofZS1wMnnyZAEIOzs7Rau4nucPMAkhROvWrZUAWf4fo2wFmJYsWaIcy3/NlJTiBJjKIrhzvwSY5BpMkorH8OHw448QHGzx8I0bN8q3PBVEuyLoq4n0XZtI37XJfed7Wpr1V/41kmylzcggOzv7f2kXL4akpNwwki2EyE23ZInlfPMviJqebjGdLj29YNqMjOK3RxmSmJjI3r17iYiIYOnSpQC0bduWkSNHFkj70UcfYTQaadGiBdOnT7eYn52dHbNnz8bZ2Zm7d++ycuVKAKXddTodDzzwgM0yTZ06lYCAAIQQ/PrrrwWOz5w5E6PRiE6nY9myZVSrVs1qXqZjeXwvInPnzlXWHpo/fz4+Pj4F0vTu3ZsnnngCyF0rxtYaY/Xq1eOdd94pdjnMMV8DpnLlykU6x1rd9Xo93333HQANGjTIsx6NCZ1Ox5w5c5Tdygpbm2X69Ok0bNiwgPYDDzzAwIEDgdz1afLz008/cf36dQDef/99m2vTVK9ePc//ExISlHpMnz6dli1bFtAHqFmzJm+//TYAy5cvt7mQ8cSJE+nUqVOB96tWrconn3wCQHp6urII9r1my5YtxMfHAxRYq6ZevXq0atUKyLv4dkmueRNLly5Vzs+v161bN6pUqVJAz8SIESOUdcGsrbt16dIlZRfERx55pMDxDz/8EIBBgwbx5JNPWszDxcVFuR4vXbpEVFQUYLneXbt2VT6n1qhTp47NhaIbNWqklGXt2rUFjq9Zs0bxaOrUqdSrV69AmqL0AV988QXp6elUrVqVb775xuoaa++++y7BwcEYjUbFh9J4bp4v5K7r9emnnxb5vJL0TWVJWdT9fkEGmCQVn3w3t56enioVRF3tiqCvJtJ3bSJ91yb3ne8eHtZfQ4bkTRsYaD1teDj29vb/SztpUvHK8eSTlvP95+FOoVWrAmnsvLyoUrcuun926lGw8BB7LzEtwmt6BQQE0LFjRzZv3oyDgwNjxoxhy5YtODo65jkvOztbWdx46NChNh/EfHx8aNSoEQAHDhwAyNvuZhiNRq5du8bp06c5ceIEJ06c4O+//1YCQ8eOHSuQfsuWLQB07tyZZs2aFane1vRtYdqprUGDBjz88MNW0/3nP/8pcI4lRowYUaJymHP37l3lb3d39yKdY00zJiZGWfR63LhxVtN5eXkpu5WdPHlSCQTlR6fTMXr0aKvaLVq0AHIfXPMvtr1x40Ygd+epCaZdj4vI1q1byfwn0GwqpyV9QAkaZWdnExMTYzXPxx9/3OqxQYMGKcFGW36XJaYAQmBgoLKTmzmmIFBMTAx///03ULJrPr9e8+bNeeihh/Ics7e3VwLQGzZsKOBlYGCgEiC0tmD/zz//rPyd/5qJi4tTvMnvZ34eeughAgICANt9jaUgVmEkJSVx/vx5/vrrL6VvMvl+8uTJAgGNnTt3AoUvWD1mzBib/ee6desA6Nevn81dVx0cHGjbti1QeD9bHHr37k379u0B+Pzzz7l9+3aRzitJ31SWlEXd7xdkgElScYmNhcGDoW/fPL/e9u7dW7UiqaldEfTVRPquTaTv2kTLvnt7e//vP0XcqUwr1KtXj9deew0vL68Cx06ePKmM+HjzzTcL7L6W/2XaYco0Ys283YUQLF68mC5duuDh4UFwcDD169enUaNGyuvo0aMABXZtunjxovJAa2mEiTXy+F4E9Hq9skNVmzZtbKZt1qyZEpA7ceKE1XSNGzcuVhksYR6gLequSdbqbl7WwupoftxaHQMCApSRTpa0/fz8lL/NH0YB/vjjDwBatmyJm5ubzbLkx3w3sypVquS5Dn19ffP8P9QswGttNKWTk5NNrxwdHZXApi2/y4o7d+4oI/lGjhxpcUSL+fum4FBxr3kTp06dUkbiWQuUmN7X6/XKTnPmjB07FsjdMXLXrl0FjptGNrVs2ZIHH3wwzzFzP0eNGlVoX2PqIyz1NSaK+tk7fvw4TzzxBFWqVMHPz48HHniA0NBQpV8yjfIzGo0kJSXlOdd0LdSoUQNfX1+rGn5+ftSuXdviseTkZGWnuW+//bbQuptGiNqqe0kwjVBNSUlRdq0sjJL0TWVJWdX9fkAGmCQVF6MRNm2CXbtgwwbl7RUrVqhWJDW1K4K+mkjftYn0XZvcd76nplp/rVqVN218vPW0mzfn/TU2IgLsinirZmcH/ftbzjf/tKhDhwqkMaakcP3sWUT+B9Ldu4vfHqXg6aef5vjx4xw/fpw//viDjRs3MnHiRBwdHTl58iRhYWGcPn26wHmmqR/FxRSUMrV7ZmYmffr04dFHHyUqKoqMQqYI5j9uHnAyTdMpCkX9Fd6E+cNjYdM9TFuZF6Zj66GzqJhGa0DuduJFwVqZzN8vrI5BQUGF5mcpMGSe1s7ss2YwGPKkM/laHE9NlPbazI+fn5/VaUkmTO1V3OuqJCxfvhy9Xg9YD/iYj2xavHgxRqOxxGUzTfuzt7dn1KhRFtM0b95c2YLe0jS5Tp06KaNY8k+TO3r0KCdPngQsjywqq77GnKJ89hYsWEDz5s354YcfijSVO3/fZOoz8gdZLVGpUiWL79+LupeErl27KqPQZs+eza1btwo9pyR9U1lSHp/FioLt3kkiUZOQEPjvf2HGDHjlFejdG/INiZdIJBKJRHWKM9y+sLTmD5VDh4KFNX4sYjTCsGFFK4ulERhGI8LNreAxV9ei6ZcRgYGBeUZxNG3alIiICPr160f//v25ffs2o0ePJjo6Os+UA/OAwMyZM4s8Ei3/VIn3339fmWrXuXNnJk2aRPPmzQkKCsLV1VUJQnTq1Ik9e/YgbKyPZWuaSVlSFB1b5TRRFlM4mjRpwvbt2wE4cuQIdevWLXWeUHgdi1K/8iiHJUzXppOTU4Fpb3fu3LG4dhZgde2usvK7rDAP4LRu3brQ9FevXiUyMpKmTZsWW8toNCoBIYPBUKSA3/79+zl37lyetdXc3d0ZMGAAP//8M6tXr2bu3LnKdC/T9Dg7OztGjBhRID/zvmbJkiVFHn1kK4hU2Gfv1KlTPPXUU+Tk5BAYGMirr75K165dCQkJwdPTUxmh+P333zN+/Hjg3lwD5nV/8cUXFa3CcHJyKvOyvPfee3Ts2JG0tDQ++ugjZs2aZTN9kyZNlL+PHDlS5uWR/A8ZYJJUbN58ExYsgDNn4Jtv4LnnlF8k1EBN7YqgrybSd20ifdcmWvbd1TygM2wYvPAC3Llje6FvnQ58fHIDUv9S+vTpw1NPPcWcOXM4cuQIP/74Y56HG/Nf5bOzs/MEqYqCq6srQghlMeYOHTqwa9euPKNazMk//cSE+a/k165dK5Z+cTB/WC1sNENOTo7y67n5NLB7QefOnZUHvY0bN1p8QM+Ptbqbl/XGjRsWFyU2YT4ioTh1LGq7BwQEcPXq1WJ5asJ0bWZlZeHv758nKJKenl7sKXeJiYkYDAabQQnTSJN77fe5c+eUxbCLw08//aSsz1Mcdu3axZUrV4p93qJFi5TFoSHX9zFjxvDzzz+TkpLChg0bGDp0KEIIZTMB88XCzTHva/JPaywKxf2sA/z444/k5ORgb29PVFRUgXWnTFjrl+B/fUZiYmKhetZGBJnXPT09vVzqbo0OHTrQo0cPtm/fzpw5c3jllVdspm/QoAEBAQEkJCSwZ88eUlJSLE63vleUZd0rOnKKnKRi4+UFpp1gpk2DpCRV57CqPX9WbX01kb5rE+m7NtGy73keGl1cwLQLlLVRC6b3Fy7MTf8v5p133lFGHL377rtkZWUpxxo2bKj8Sr5t27Zi521vb8/t27eVYM3w4cOtBpdSU1MtTtMDqFWrlvIgt7sY0wvNfS/KCBVnZ2dldNDBgwdtpv3jjz+UBX+L+0BYXHr27EnVqlWB3OmmcXFxhZ5jLVBiXtbC6hgdHW3xvJJq56d58+ZA7vo7tnZ3s4T5Qu/5r82SjBrLysoqsLi8OTk5OcoaYZbaoixH1pmPXpo7dy5Lly61+TKNLFy9erWy8HlJ9JydnVmyZEmheqaF2xctWpRnRI+9vT09evRQpoKZRi3t3r2bq1evAtYX3rblZ1Eoied//fUXkDsKx1pwCfKuD5Uf0+6JsbGxNqdr3b59mwsXLlg8VqlSJYL/2eV7x44dxR4lVdYLXb/33ntA7nRA085+1tDpdDz66KNA7hpMph8Tygu5yLdEUpF48klo0ABu34b/+z9lJwI1UFO7IuirifRdm0jftYmWfU9NTc37Rr9+sHZt7ggl+N+aTKZ/fXxg3brcdP9yAgMDmThxIgBXrlzJswW7m5sb3bp1AyAqKipPwKEopKamkpOTo/zfVhBhwYIFVrectrOzIyIiAoDffvtNWRy6KPomTFN1TOvaWKN79+5A7gLnv//+u9V05g9SpnPuFU5OTspIgszMTMaPH19gPaP8mOp+9erVPAsut2jRQpk+tnDhQqv53L17l19++QXIHaVQnHWSCnzerNDvn89Xeno68+bNK3L+AOHh4coUps8++yzPdVZU/fyYX/v5WbNmjTKSxZLfpuvLPEBbEkyL4UNuIOupp55i5MiRNl+T/tkZMzU11eLi27ZIS0tj9erVAPTo0YPRo0cXqjdu3Dggd/H9vXv3Knmlpqbi4OCgjLDbtGkTd+7cUabfubi4MGjQIIvleOCBB5SRrsuWLSM2NrZY9SiJ56Zrxla/dOPGDWWHN0uY+kfzaYaWWLx4sc3AUf/+/QG4cOGCsoh3USnp9W6NNm3a0KdPHyB30XFTcNAaTzzxhDJicOrUqZw6dapIOkajUbnWS0pZ170iIwNMkoqPgwN88knu3+vWYWflpk4ikUgkkn8l/fvDtWuwaBEMHAhhYbn/LlqU+74GgksmXn31VeUBecaMGXmCDm+99ZYyOmPkyJGcP3/eaj4Gg4Gff/45zwNJpUqVlIDGsmXLLD6AHzp0iClTptgs4yuvvIKdnR1CCEaOHGnzocfSMVOAxFb5IXdBdNMoqwkTJpCcnFwgzbZt21iwYAGQuz5Oq1atbOZZFrzwwgt06dIFgK1btzJo0CCbi/AKIViyZAktWrTgzz//VN53dnbmySefBHJHcJhPcTI/99lnn1UW4X722WfLsioKY8aMUUZuvPXWW/z2229W0+b3NDg4mMcffxyAY8eOMXHixDxBpvzEx8cXOrpi7ty5eQImJm7cuKEE+Nzc3JTd0swxXV+XL1+2qVEYe/bs4eLFiwAMLeL03J49eyrTkoobYFq1apWy+1dR9QYPHqz0CZYW+zaNUtLr9fz8889KwKR///42p0+Z+oDMzEwGDx5s8/rW6/XMmTOnRCO2TJhGK545c8ZiMDk9PZ3Ro0fb3JRg0KBBBAYGArm7sJl2oTTn7NmzFj9n5rz66qs4OzsD8NRTT9kcNQW5wTvzz3VZY9pRTq/X88UXX9hMW6VKFb766isgN2DZuXNnm59lyA3g9+rVq9A1niT/Q67BJCkSX3/9NV9//bVyI7d27Vo8PDwYPHgwO3fuJDk5mcDAQFq3bs2Gf3Z8a968OUajURmmO2DAAPbu3UtiYiJ+fn506tSJtWvXArnbczo6OiqLH/bp04fDhw9z8+ZNvLy86NmzJ4eeeYarrVtT/YEHuHDhgjJculevXpw4cYK4uDjc3d3p27ev8qX14IMPEhAQwL59+4DcX3LOnDlDbGwszs7ODB48mOXLl2M0GqlTpw7BwcHKkPawsDBiY2O5cOECDg4ODBs2TJmbXbNmTerUqaP80tahQwfi4+M5c+YMkLtt6bp160hPT6datWo0aNBAGUbbtm1bkpOTlR0qhg0bxpYtW7h79y5BQUE0b96cTZs2AdCqVSsyMzM5fvw4kLu2wZYtW0hKSiIgIIC2bduyfv164H9Ddk2/lvbr148DBw6QkJCAr68vYWFhrFmzBoBGjRrh4uKibPMaERHBkSNHuHHjBp6envTu3VvZSalBgwbKvOGVK1fSu3dvTp48ydWrV3Fzc2PAgAHKfPV69eoRGBio3PR07dqV8+fPc/nyZZycnBgyZAgrVqwgJyeH2rVrU6NGDaKiooDcBVPj4uI4f/68srDi6tWr0ev11KhRg5YtWyo67du3JyEhQZmiMGLECDZs2EBaWhrBwcGEhoaydetWIPfXjdTUVGV48dChQ9m2bRspKSlUrlyZli1bsnHjRiD319Ls7Gzli3DgwIHs3r2brKwstm3bRocOHZRfh5o2bYqdnZ2yUGDfvn2Jjo4mPj4eb29vunXrpvzSFhoaipubm/KLenh4OMeOHePatWt4eHgQERGh/Ppav359/Pz8lDUNevTogb+/P0uXLsXV1ZWBAweybNkyhBDUrVuXoKAg9uzZA0CXLl24dOkSFy9exNHRkaFDh7Jy5Uqys7OpVasWISEhREZGAtCxY0du3LjB2bNn0el0jBw5krVr15KRkUH16tWpX7++0oaxsbGkpqYqv/QMHz6cTZs2kZqaStWqVWnSpImyKG7r1q1JT09XtsMtbR+RlZXF0qVLi9RHmG4MGzZsiIeHR6n7CBPF6SNWrVpFVlZWmfQRproXp48YNGgQUVFRpeojjEYjkPvrpMmbwvoIb29vZeRPz549S91HZGVlcfDgwWL1EfXq1WPHjh1A6fqILl26EBUVRUBAAKmpqTg6Oirbzru7uyOEUH5F9vX15e7du+Tk5ODg4ICHh4eS1s3NDZ1OpzwQ+fj4kJaWRnZ2Ng4ODnh6eiqjDEyLR6elpSGEICcnh4yMDLKysrC3t8fb25vbaWkQHo7r4MHY29srv4Z62duTefcuWVlZ2NnZ4evry+3btxFC4OLigqOjo7LlupeXF3q9Hr1ej06nw8/PT0lrml5mKpOnpyfZ2dlkZmYqaZOSkjAajTg5OeHi4kJKSgoAHh4eGAwG5eHGz8+P5ORkDAYDTk5OuLq6KsEPd3d3jEajktbX1zfPL7tGo1FZIyR/e/v4+ODq6sojjzzCggULuHDhAvPmzWP48OG4ubnRokULXnnlFWbOnMnFixdp2rQpjzzyCF27dqVOnTokJCQQGxvLH3/8wbp167h27Rp79uwhKCgIBwcHkpKSGDp0KN999x1Hjx6lbdu2PPfcc9SrV4+bN2+yfft2fvjhB9zd3alcubISAMrf3tWrV+f111/nww8/5MyZM4SGhjJ+/HgiIiJwdHQkKSmJU6dOsWHDBoQQrFu3Djc3N9LS0sjMzKRZs2ZERkZy6NAhpk6dSu/evfHz8+Pu3bu4urpSt25dDAYDVatW5ZlnnuGrr77i+PHjNG3alBdffJHWrVtz69Yttm7dyvz58xUfPvroI4xGo3LNOjo65hmpoNfrycjIyNPe1q7Z/Ne3t7c36enpZGdnY29vz/LlywkPDycmJob169dTp04dhgwZQseOHalbty5Go5G4uDiOHDnCxo0ble+XrKwssrKylGv2zTffZNWqVVy8eJH33nuPEydOMGzYMCpXrsz169eZP3++8oD48MMP88gjj5CYmJjnmjUfCWa6tjw8PMjJyUEIoXznmI8OycnJyZPWaDTy1VdfMWzYMNLT0+nWrRvDhw+nf//+1KlTh8TERM6dO0dkZCQbNmxQ1moy9RGTJ09m7969nDx5ku+//559+/bx5JNP0qRJExwdHUlOTiY2NpZt27axbds2GjRowBNPPJGnjzDdgwcEBODu7k6PHj146qmn6NmzJ/7+/kRFRfHZZ58p0zzfeOMN7O3tlc+xqY9o164dkZGRHD16lPfee48+ffoo10GlSpUICAiw2Ec4Ozvj7OysfO5/+OEHpb1MI6WK0kf06NGDVatWsWfPHk6cOEHNmjUL7SPu3r2rBN0cHR3p0KEDiYmJFvsI02hEBwcHgoKCaNWqFdHR0axYsYKZM2diMBgQQmAwGGjQoAG1atXi4sWLvPXWW0r/PXToUPR6vdI3eXt75+mTR44cya+//sqyZcuIiYmhQYMGPPbYY7Rr144aNWpw584dzp49y++//87GjRu5ffs2ffr0ISAgADc3NxITE/P0e0lJSXh5eeXpZ83bu1+/fsyePRuj0Uh4eDjPPfcc3bt3Jzs7myNHjvDtt99y/vx52rRpo9z7ZGRkKNewn58fmZmZvPfee0ycOJHbt2/TunVrnn/+ebp27Qrkrm81e/ZshBDUqVOH8+fPYzQaMRgMeb7XgoKCmDVrFs899xy3b9+mffv2DBs2jPDwcB588EGSkpK4du0ax48fZ82aNVy4cIElS5bQoEEDHBwcSExM/N/32j9T9VxdXfN8r5na2xxTXfJ/rzVq1Ii+ffuyYcOGPLt4Jicnk5qaipOTk5LWzc2N4cOHc+bMGWbMmEF8fDxhYWF06dKFfv36ERoaioODA3fu3OHq1ats2rSJ7du3YzAYaNKkCXfu3MnzvWa6XzJdg+bXbEpKCgaDAUdHR+U6tXTNFuc+wsXFhczMTDZs2KCM2i3Ks0a5IySSYpCcnCwAER8fr1oZdu/erUltNfUzMzPFtGnTRGZmpir6Qkjf1UD6Ln1XC7V9z8jIECdPnhQZGRnlrp+SklLumkIIYTAYRFxcnDAYDOWuHRkZKQABiHfeeafQ9LGxscLJyUkAon79+gXK/NlnnwlnZ2clT2svJycncfbsWSHE/9r9zp07omnTplbP8fPzE7/99pvo3LmzAETnzp2tlvODDz4QDg4ONstgOt/c96tXrwo/Pz+b6U0YDAbxzDPP2NTw9vYWW7dutVjGnTt3KukiIyMLbfvikJGRIV544QXFK1svnU4nxowZI+Li4grkc/HiRVG/fn2b57dv314kJiZaLMfYsWMFIGrWrFngmHm7//DDD0p+Fy9etJjXli1bhK+vb6H1sURiYqLo3bt3oecCokuXLjbrcejQIREQEGD1/Oeff95iGYQo3vVljfT0dOHl5SUA8eCDDxbpHBOrV69W9GbMmFGkc65cuSLs7OwEIHr16lUsvU8//VTRW7ZsmRAir+9Tp04t8BnX6/WF5puTkyNee+01YW9vX6if7u7uIj09PY92Ua43c959912bGi+//HKheRoMBvHaa68JnU5nMQ83NzexceNG0bFjRwGI3r17Wy3PsmXLlGvA1svOzk7s2rWrQLsXBVMeY8eOtZnu2LFjBepkqT8z11+1apUICQkp0uexYcOGFvvQmjVrWu1bbGmXlJLem8THxwtAJCcnl7oMRUFOkZPcd8TFxsLKlblbMpczhc3t/bfrq4madVe73dXWVxPpuzbRsu+lXRdFC1SvXl2Z+nPq1ClWrVqV5/iLL77I+fPnefvtt3n44YcJCAjAwcEBd3d36tWrx5AhQ/jmm2+Ii4tTti43tbu3tzf79u3jvffeU0b7enh48NBDD/HKK69w7NgxOnXqVKRyvvnmm5w8eZIXX3yR0NBQvLy8cHFxoXbt2nTr1o3PP/+cZcuW5dGH3ClV0dHRjB8/ngceeECZEmgJOzs7vv76a3bv3s0jjzxCjRo1cHZ2xsvLi6ZNmzJ58mTOnj1Lz549i97AZYSLiwuff/45Z8+eZcaMGXTv3p0aNWrg6uqKi4sLVatWpWfPnrz11ltcvHiRRYsWKQuEmxMSEsKxY8f46quv6Ny5M/7+/jg6OlK5cmV69+7NokWL2L17d4l2TCvu561Xr15cuHCBDz74gHbt2illCQ4Opk2bNkyePFkZUZofPz8/Nm/ezM6dO3n88cepW7cu7u7uODg44OfnR6tWrZg0aZIyasIWLVu25MiRIzz//PPUqVMHFxcX/P396d27N5s2bbI5VSg4OJjff/+dUaNGFXp9WWPt2rXK6KQhQ4YU69zevXsri/UvWrSoSOcsWrRIGS1SXD3z9KZpcua+51/Me+jQocqITlvY29vz0UcfcfLkSV5++WWaNWuGr68v9vb2eHp60rBhQx555BEWLlzI9evXldkAJe3jp06dysaNG+nZsye+vr44OTlRrVo1Bg8ezLZt24o8heuFF14gMjKSgQMHEhgYiLOzMzVr1uSJJ57g8OHDREREKN7a2vRixIgRXLp0iRkzZhAWFkZgYCCOjo64ublRu3Zt+vXrx6effsqlS5eUKbP36vutcePGDBs2rNB05vqDBw/m9OnTLFmyhDFjxvDggw/i6+urfB6bN2/OM888w86dOzl+/Hip+1BNfbeXSxhL8q9B9RFMRqO41aCBECDEokXlLr927dpy16wI+hVhRIOabS99l75rSV/6vlbVEUxJSUnlrimEuiOYTKhVd7W11dSXvqunXVx9WyOxiov0XZvaRfE9KytLuLq6CkBMmTKlTPXvp89bRdSWI5gkknuBTkfAP1tM8uabUMytYkvLgAEDylWvoumriZp1V7vd1dZXE+m7NtGy76ZFprWImnVXu93V1lcT6bs20arvFd1z03qckLuuWVmidt2l7+WDDDBJ7juWV6kCNWvC1avw6aflqm1aqFYt1NZXEzXrrna7q62vJtJ3baJl300LmWoRNeuudrurra8m0ndtolXf1fbctPOfJS5dusRLL70EQOXKlenVq1eZaqtddy37Xp7IXeQk9x1GJyf48EMYPRpmzIDx4+GfLVclEolEIpFIJBKJRFKQzp07Ex4eTr9+/WjYsCHu7u7Ex8cTGRnJN998o+xgNmvWLBwcZKhAUnzkVSO576hXrx40bw5ffAEHD8Lbb8M/W5eWi7aKqK2vJmrWXe12V1tfTaTv2kTLvpdkwd1/C2rWXe12V1tfTaTv2kSrvqvtucFgYMOGDWzYsMHicTs7O/7v//6PMWPGlLm22nXXsu/liZwiJ7nvCAwMBJ3uf9Pjvv8ejh0rP20VUVtfTdSsu9rtrra+mkjftYmWfXd0dFRVX03UrLva7a62vppI37WJVn1X2/Mff/yRp59+mqZNm1KlShWcnJzw9PSkfv36PPXUUxw7dow333zznmirXXct+16eyACT5L5j7969uX+0awfDh0PbtrkBp/LUVgm19dVEzbqr3e5q66uJ9F2baNn3u3fvqqqvJmrWXe12V1tfTaTvRePHH39ECMGlS5fuXYHKEa36rvY116NHD7766iv++OMPrl27hl6vJyUlhb///pu5c+cSGhp6z7TVrruWfS9P5BQ5yf3NggXg7l5uASaJRCKRSCQSiUQikUgkBZEBJsl9R9euXf/3Hw8P9bRVQG19NVGz7mq3u9r6aiJ91yZa9t3Ly0tVfTVRs+5qt7va+moifdcmWvVdeq5NfbXrXp7IKXKS+47z588XfDM5Gd54A+bNK3/tckRtfTVRs+5qt7va+moifdcmWvZdr9erqq8matZd7XZXW19NpO/aRKu+S8+1qa923csTGWCS3Hdcvny54JvLl8NHH8HkyfDP9prlpl2OqK2vJmrWXe12V1tfTaTv2kTLvmvpJjQ/Wr75V1tfTaTv2kSrvkvPtamvdt3LExlgkpSIxx93YNEiyMwsf20nJ6eCbz7xBDz0ECQmwvvvl692OaK2vpqoWXe1211tfTWRvmsTLftuZ6fdWzM16652u6utrybSd22iVd+l59rUV7vu5Yl2aiopUzZtsuOxx6BqVVi/vny1hwwZUvBNBwf45JPcv7/8Eu7RFAeL2uWI2vpqombd1W53tfXVRPquTbTsu6+vr6r6aqJm3dVud7X11UT6rk206rv0XJv6ate9PJEBJkmJECJ317Y7d2DAAPj11/LTXrFiheUDvXtDz56QlZW7HlN5apcTauuriZp1V7vd1dZXE+m7NtGy77dv31ZVX03UrLva7a62vppI37WJVn2XnmtTX+26lycywCQpFULk/jtuXPlNl8vJybF8QKeDWbPAzg5WroS9e8tPu5xQW19N1Ky72u2utr6aSN+1iZZ9F6YvVg2iZt3Vbne19dVE+q5NtOq79Fyb+mrXvTyRASZJqRECkpJyYzrlQe3ata0fbNQIxo/P/XvKlPLVLgfU1lcTNeuudrurra8m0ndtomXfnZ2dVdVXEzXrrna7q62vJtJ3baJV36Xn2tRXu+7liQwwScoEOztYs6Z8tGrUqGE7wfTp8OSTsHhx+WvfY9TWVxM16652u6utrybSd22iZd/VXmRcTbS8uLva+moifdcmWvVdeq5NfbXrXp7IAJOkTDAaobymlkZFRdlOEBQE8+dDtWrlr32PUVtfTdSsu9rtrra+mkjftYmWfb97966q+mqiZt3Vbne19dVE+q5NtOq79Fyb+mrXvTxxULsAkvuDr7/+mq+//hqDwWDxuE5nJCcngbt3XdmwYQMAzZs3x2g0cvToUQAGDBjA3r17SUxMxM/Pj06dOrF27VoAGjdujKOjIzExMQD06dOHw4cPc/PmTby8vOjZsycr/5mDl5KSwoULFzh48CAAvXr14sSJE8TFxeHu7k7fvn1Zvnw5AA8++CCVDQZ2nzsHQPfu3Tlz5gyxsbE4OzszePBgli9fjtFopE6dOgQHB7N7924AwsLCiI2N5cKFCzg4ODBs2DCuX7/O0qVLqVmzJnXq1GHXrl0AdOjQgfj4eM6cOQPAqFGjWLduHenp6VSrVo0GDRqwbds2ANq2bUtycjInT54EYNiwYWzZsoW7d+8SFBRE8+bN2bRpEwCtWrUiMzOT48ePA2AwGNiyZQtJSUkEBATQtm1b1v+zjV+zZs0A+OOPPwDo168fBw4cICEhAV9fX8LCwljzzzCzRo0a4eLiwqFDhwCIiIjgyJEj3LhxA09PT3r37q0sdNugQQNcXV0BWLlyJb179+bkyZNcvXoVNzc3BgwYwNKlSwGoV68egYGB7P1n/auuXbty/vx5Ll++jJOTE0OGDGHFihXk5ORQu3ZtatSooTzMderUibi4OM6fP4+dnR0jRoxg9erV6PV6atSogV6vV3Tat29PQkICp0+fBmDEiBFs2LCBtLQ0goODCQ0NZevWrQC0adOG1NRU/vrrLwCGDh3Ktm3bSElJoXLlyrRs2ZKNGzcC0KJFC7Kzs/nzzz8BGDhwILt37yYuLo5t27bRoUMH1q1bB0DTpk2xs7PjyJEjAPTt25fo6Gji4+Px9vamW7durF69GoDQ0FDc3NyIjo4GIDw8nGPHjnHt2jU8PDyIiIjgl19+AaB+/fr4+fmxf/9+AHr06MHt27dZunQprq6uDBw4kGXLliGEoG7dugQFBbFnzx4AunTpwqVLl7h48SKOjo4MHTqUlStXkp2dTa1atQgJCSEyMhKAjh07cuPGDc6ePYtOp2PkyJGsXbuWjIwMqlevTv369ZU2jI2NJTU1lVOnTgEwfPhwNm3aRGpqKlWrVqVJkyZs3rwZgNatW5Oens6JEycAGDx4MDt37iQ5OZnAwEBat25drD4iLi6OpUuXFquPaNiwIR4eHkXuIwICAti3b1+BPuL69esAxeojVq1aRVZWVpn0Eaa6F6ePGDRoEFFRUaXqI4xGIwAXLlxQvCmsj/D29ubAgQMA9OzZs9R9RFxcHAcPHixWH1GvXj127NgBlK6PMBqNREVFERAQQGpqKo6Ojty5cwcAd3d3hBCkp6cDubvC3L17l5ycHBwcHPDw8FDSurm5odPpSEtLA8DHx4e0tDSys7NxcHDA09OTpKQkAFxdXbGzs1OO5+TkkJGRQVZWFvb29nh7eysLhLq6umJvb09qaioAXl5eZGZmkpWVhZ2dHb6+vty+fRshBC4uLjg6Oio3tl5eXuj1evR6PTqdDj8/PyWt6ddVU5k8PT3Jzs4mMzNTSZuUlITRaMTJyQkXFxdSUlIA8PDwwGAwkJGRAYCfnx/JyckYDAacnJxwdXUlOTlZaUOj0aikNW/DnJwcDAaD1fb28fEhNTVVaW/zNrTV3vb29nh5eeVpb/M29Pb2xmAwkJiYWKC9XVxccHBwyNPepjYsrL09PT3JysrK096mNnR2dsbZ2VlpQyEEaWlpZP6zoKW/vz937tyx2Ia22tvR0RE3N7c87W3tmjWlNflu+tu8va1ds/nb29vbm/T0dKW9bV2z3t7eea5vgMTERKW9rV2z+dvb2dkZJyenPO1t7ZrN394eHh7k5OSQnZ2tfOdYu2bzt7evry8pKSlKe7u7u5e4jzAajUrdi9pHWGrD4vYRpnzT09PztKGtPiJ/G5a2j8jJySExMbFYfURh7V3UPiI7OxuDwVCsPsJaexe3jxBCKJ4Xp48wb28oeR8Buc8TproW1keYt3dp+wiT58XtI3x8fMqkjzDvZ4vaR5jau7R9hKmvKc19hIuLC5mZmWzYsAE3N7ciP2uUNzqhpRWnJKUmJSUFb29vIBnwynNs0SIYM+belyEuLo7g4ODCE6akwOOPw7ZtcPZs7sim8tK+R6ilr9frmTFjBm+88YZqc4jVbHvpu/RdS/rS9zj8/f25ePEitWrVwsXFpVz1s7KyVBlKbzQauXHjBkFBQdjZqTPAXa26q62tpr70XfoufdeOttq+a/XzVlbamZmZJbo3uXXrFoGBgSQnJ+Pl5VX4CaVETpGTlBqdDnx9YejQ8tGLi4srWkIPD7h6FVJTYerU8tW+R6itryZq1l3tdldbX02k79pEy75nZ2erqq8matZd7XZXW19NpO/aRKu+S8+1qa923csTGWCSlAkLF0J5/ch7/vz5oiW0s4NPP839e8EC+GfaU7lo3yPU1lcTNeuudrurra8m0ndtomXfTcPxtURUVBQ6nQ4PDw90Ol2el6urK9WqVSM8PJw5c+YoUyjKGrXbXW39e8mVK1eYOXMmPXv2pFatWnh4eODq6kpwcDC9evXi/fff5+LFi6qUTe12V1u/LMj/mc3/+a1evTr9+vVj0aJFeZbaKKu6Z2Rk4O3trWhOnz690HPUbPd/g+clpbR137x5MxMmTKBBgwb4+fnh4uJC9erV6dKlCx9//HGh08Es6QshWL9+PU899RSNGjUiMDAQR0dH/Pz8aNSoEU888QRr164tcoDo1KlTTJ8+nc6dO1OjRg1cXV3x8PCgfv369OvXj08//ZQbN26UqP73CzLAJCkROt3/Zla6uECLFuWnXawhne3bw7BhuauQv/wylHJGqFrDiCuKvpqoWXe1211tfTWRvmsTLfuu0+lU1a9oZGZmEhcXx5YtW5g0aRKhoaEcO3aszHXUbndz/ZCQEHQ6HePGjVOvQGWAXq/n5Zdfpm7durz22mts376dS5cuKWugXLt2jW3btvHhhx9Sp04dRowYwZUrV8q1jBXJ9/IiJCQEe3t7XnzxxXuulZmZydWrV9mwYQOPPfYYDz/8MLdu3QLKru5r1qxR1s0BWLRoUaHnqOm72tecmpS07n/99Rft2rUjIiKC+fPn8/fff5OUlIRer+fq1atERUXx+uuvU69ePd5//32srQCUX3/v3r00a9aM/v378+2333LixAlu3bpFTk4OSUlJnDhxgh9++IFBgwYREhLCjz/+aLWMd+7c4fHHHyc0NJR33nmH3bt3c+XKFTIzM0lLS1M+By+//DLVq1fn6aefVtag+rchF/mWlIiICCPDh8Ps2bmbtZVnXzlixIjinTBjBqxbBzt2wObNEBFRftpljNr6aqJm3dVud7X11UT6rk3U9l3NX5j9/PxU064IPP300zzzzDPK/02LtX/66aecOXOGy5cvEx4ezunTp/H09CwzXbXbXW39siYxMZH+/fsrG1Z4enoyatQounXrRrVq1XB0dOTGjRvs27eP1atXc/bsWX755Rfatm1bLoEPE2q3u9r6ZUnLli354Ycf8ryXmprKiRMn+Oqrrzh27BiHDx9m6NCh/Pbbb2VW959++gnIXWg5NTWVc+fOsX//ftq1a2f1HDXb/d/keXEpSd337NlD//79lYWvW7RowdixY2ncuDEeHh7KDxALFy4kLS2NKVOmcOLECX766SccHR2t6i9atIjx48crI5PatGnDkCFDaNq0Kf7+/iQnJ3P+/Hk2bdrExo0buXbtGi+++KLFwP+lS5cIDw9XNsOpVKkSo0ePpnPnzlSpUgWdTse1a9eIiopi1apVxMXF8c0339CrVy8GDhxY7Dap8AiJpBgkJycLQMTHx//z//Ivw6pVq4p/0iuvCAFC1K8vRFZW+WqXIWrpZ2ZmimnTponMzExV9IVQt+2l79J3LelL31eJjIwMcfLkSZGRkVHu+rdv3y53TSGEMBgMIi4uThgMhnLXjoyMFIAAxDvvvGMxjV6vF127dlXSzZo1q0zLoFa7W9KvWbOmAMTYsWPvue698N1gMIju3bsrXkVERIibN29aTZ+QkCAWLlwoAgMDxWeffVZm5SgKFcn38sJ0fQ0bNqxMfDf53LlzZ6tp0tLSRP369ZW0v//+e5nU/dq1a8Le3l4A4uOPPxb+/v4CEBMnTrR5npq+q6mtZj8vRPHrfuXKFeHn5ycAodPpxCeffCKMRqPFtBcvXhRNmjRRrrHXXnvNqn5kZKRy3bi5uYnly5fbLMfFixfF8OHDhbe3d4Fj6enpIjQ0VNF9/PHHRUpKilVtvV4vPv/8c+Hu7i7WrFlTSAvkpaT3JvHx8QIQyeX04K7d8feSMiH/QvRmU6vvGXq9vvgnvfUW+PvnLvhdinn+JdIuQ9TWVxM16652u6utrybSd22iZd+NRqOq+hUVJycnpk2bpvx/+/btZZq/2u2utn5ZMnv2bHbs2AFA9+7dWbduHYGBgTbPeeyxx4iJiaFx48blUUQFtdtdbf3yws3NjWeffVb5/8GDB8uk7osXL8ZgMGBvb8+jjz7K8OHDAfjll19s9uVqtrtWPLdEces+YcIEZRrZBx98wEsvvWR1ml1ISAg7duygWrVqAMycOZODBw8W0M/IyOCRRx7BYDBgZ2fH+vXrlevGGiEhISxfvpwvvviiwLHJkydz4sQJAMaNG8f3339vcXStqe5OTk688MILHDx4kOrVqxfSAvcnMsAkKRNu3YJHHoHnnrv3WjVq1Cj+ST4+udPjTp+GevXKV7sMUVtfTdSsu9rtrra+mkjftYmWfXd2drb4fmYmLFoEQ4ZAWFjuv4sW5b6vFZo3b678XdhaPadPn+b555+nYcOGeHt74+rqSu3atXn88cc5cuRIgfTm7X79+nXmzJnD0KFDqVu3Lu7u7jg7OxMcHMyAAQNYvnx5kR+ULl26xOuvv06LFi3w9/fHxcWFWrVq0aVLFz755BNiY2MV/bCwMHQ6HZcvXwZg4cKFBRZNDgsLs6izd+9eHn30UUJCQnBxccHHx4dmzZoxZcoUZc0bS0T9P3vnHR9F0f/xd8pdKmkEAoSOICV0CFU6GHpvgoINFewP9q4PNnx+qA/4qIiiqJFO6D2hSQ1IMQKhQyiBENL7ze+P89ZLcne5tNuEnffrdS+W29n5zMxnd7L7vZnZqCiCg4NxcXEhKioKg8HA999/T+/evQkKCsLZ2blYa0Hl5OQwe/ZsANzd3fnhhx9wdbW9Ioep7WvXrk2fPn0spsnOzuarr76id+/eVKtWDb1eT40aNRg0aBA///yzTT+mTp2Kk5MT9evXB4xrpbz99tu0aNGCunXr4ufnR48ePfjll1/sqmNKSgr/+c9/6NOnDzVq1MDNzY1atWrRqVMnXnnlFYvnlwkhBMuWLWP06NHUqVOH4OBg/P39CQ0N5YMPPlCmAdlTj7i4OF588UWaNGmCp6cn1apVY9CgQWzYsMHi8QXPr6VLl+Li4mLX+VUWmMoNxrWZrPV1xcG03lLfvn2pUaMGkydPBiAxMZE1a9YUSm+6pgIDA5UgqC2mT5+Ok5MTer2ehIQEi2lK2teYXm7g5ORk17VnMBjYvn07M2fOpFu3bgQGBqLT6fDz86NNmzbMnDlT6U+K4tixYzz44IMEBwfj7u5O3bp1mTx5slLegueaNRITE/n3v/9Nly5dCAwMVK6F4cOHs2LFCqt1t4ejR48q53KrVq146aWXijwmMDCQOXPmAMZr7dNPPy2k//333yuLgT/11FNW+xxLTJkyJd//b926xbfffgtAjRo1+PLLL60eW7DuLVq0oL0jFzF2JA4ZJyW5ayg4Rc5EZKRxBhoIsXt3+ZahoLYjUVNbTf2KMGVG+u54pO/Sd7VQ23c1p8hlW5jGHREhhL+/8W+ss3P+f/39hVi9uvS6FX2KnBDG6QGmdK1atbKa7v333xeurq5K2oIfJycn8fbbb+c7xtTuubm5wtnZ2eqxpk///v1FSkqKzXrNnj1b6HQ6m/mYphVlZ2eLnj17FqlbcBpSXl6emDFjhs1jfH19xebNmy2Wcdu2bUq6DRs25JvaZvoUZ6remjVrlOMmT55s1zGWznlzLly4IJo1a2azjt27dxcJCQkWj58yZYoARL169cRff/0l6tevbzWfGTNm2CzLli1bRGBgYJE+WSI+Pl5069bN5nFBQUFi3759Rdbj4MGDonr16lbzee655wodX5Lzyx7sPXbu3LlK2vDw8CJ9L4rDhw8r+f3000/K9w0bNhSAGDp0aKFjkpOThYeHhwDE1KlTbeafk5OjeG0pLyFK19eY93v2XHvvvPNOkf55enqKFStWWK1TXl6emDNnjtV+SafTiYULF+Y716yxbt064efnZ7M8gwcPztdPFsfzF154Qcnn22+/tfu4vLw8Ubt2bQEIZ2fnfNPysrOzRfv27RVvYmNj7c7XEv/973+VMr755ps205b2fBei8kyRkwEmSbGwFmASQohHHjHe7DZrJkR5Ppf8+uuvpcsgN1eIBQuEOHfO8dqlRC39ivDAqWbbS9+l71rSl77/qmqA6datW/n+HxEhhJOT8QOFP6Z9ERGl060MAabo6Ggl3bBhwyymeeutt5Q0Xbt2Fd99953Yu3evOHTokPjll19Ely5dlP1ffvmlcpyp3XNycoSzs7Po06ePmD17tti4caOIjo4WUVFR4vvvv893/EMPPWS1rO+//76Szs/PT7z++utiy5Yt4vDhw2L79u3is88+E926dRO9evVS9M+dOyeOHz8uatWqJQAxfPhwcfz48XyfcwXuXV566SVFp0GDBuLrr78WBw4cEJGRkeKFF15QHiT1er34448/CpXTPMDUqlUrpW1XrFghoqOjxfr168Vvv/1mtZ4FmTlzppKfvccVPOfNSUlJUQIGgBgxYoRYvXq1OHTokFi6dGm+oEmXLl1Ebm5uoTxMD8vVqlUTjRs3FlWqVBFvvvmmiIqKElu3bhXz589XHkgBsXHjRotl2b59uxJMcHFxEVOnThUrV64U0dHRYs+ePWL+/Pli1KhRQqfTFTo2NTVVCZLp9XrxxBNPiIiICLF9+3axa9cuMWvWLGX9IH9/f3HhwgWb9ahfv75wc3MTr776qti5c6fYv3+/+PLLL0XNmjWVevznP//Jd3zB8+v+++8XR48etXl+2YM9Aab09HTRvHlzJQgSHx9v03d7eO6555T8zIMYpj5Ap9NZfF4ZP368AISPj4/NPn7t2rU2z+XS9jXm/Z49194bb7whatasKaZPny4WLVok9uzZI6Kjo8WqVavEyy+/LLy9vQUg3N3dRUxMjMU67dixQwmge3h4iNdff105f+bNmydq164t9Hq9aNu2rc0A0+bNm5U1jOrXry8++eQTERUVJQ4fPizWrFkjJk+erNRt1KhRhepuD6ZAECCuXbtm93FCCPHEE08ox65du1b5/vz580q5mzZtWqw8LTFmzBhFx1pg2ERpz3chZIBJcpdiK8CUkCBE9erGG9533y2/MpT6wWPGDGMhx41zvHYpkQ+c2tNWU1/6Ln1XC7V9rygBpowM4wgla8El8yCTv78xfUmpDAGmiRMnWhyxYOLAgQPKw5O1X5Pz8vKUh58qVaqIxMREIcQ/7W4wGIr8Vfvtt99WfgE/ffp0of3R0dFKOZo0aSIuX75sNS/TPnPf7V3k+9ixY4pOSEiIUhdzNmzYoKQJDQ0ttN88wASIt956y6ZmUfTv31/Jy1LbWMLWg5d5wMqSpwaDQUyaNElJ89VXXxVKYwrMmIJ9J06cKKQdGxsr3N3drQYv09PTleCNp6eniIyMtFrmS5cuFfru6aefFmAcTXbw4EGLdb9w4YKiYWn0l3k9dDqd2LFjR6E0cXFxSrDM09PT4uLq5bXId4cOHQoFRPfv3y8WLFigBCycnJyUYEtpHrhzcnKUEVwPPPBAvn2nTp1SyvTFF18UOnb16tXK/qVLl1rVeOCBBwQgvL29RXp6er59ZdHXmPd79lx758+ftzkK5vLlyyI4ONjq+SOEUBbB1uv1Ys+ePYX237hxI19A11KAKTU1VQQFBQlADBgwQKSlpVnU+vbbb5V8tm7dmq/u9mAKjtesWdPuY0x88803ivasWbOU79evX698X/C8KQmNGzcWppFSRd0zyQCTRGIFWwEmIYT47Tfjza5eL4SV4HmpuXjxYukyOHbsn7kFFjrXctUuJWrpV4QHTjXbXvoufdeSvvT9ot03cQaDEKmpZftJSMhUtufPtx1YKvj57ruS6yYn54nY2KsiOTnP4n4rL+4pE2wFmG7duiV27dolBg4cmG+kiqUHrdGjRwtAtG/f3uqbhoQQIjExUbi5uQlAzJ8/XwghinW+5+bmKlNnLL3NbsKECcrD9OHDh+3K01zf3gDTU089pbTJ3r17raZ77LHHlHQHDhzIt888wNSkSROLI4CKgymQUJyHGWttn5mZqUzBad68udWyJSUlKaN/mjdvXmi/eWDGfCRJQW2Tb/7+/oXy+Prrr5U8ivumu5s3byrBq4IBj4J1/+qrr5QAUsEHd/N6PP3001b1Fi9erKT79NNPC+0vrwBTUZ/+/fuLLVu2KMeV5m+M+VTM9evXF9rfsWNHpS8oSHZ2tnK+jBgxwmL+qampwsvLS4DlkYpl0deY93tlce0JIcTnn38uwDg6q2C59u7dq+g9//zzVvOIiIiwGWAyTQtzd3e3+XZIIYQIDQ0VgJg0aZIQwn7P79y5o5Shbdu2dh1jzqpVq5TjX3zxReX7ZcuWKd+/8MILxc63IP7+/lb7jIKUxT1VZQkwyUW+JWXKuHEweDBkZ8Pjj0N5vCjh1q1bpcugZUt49FHj9gsvFKuQpdYuJWrrq4madVe73dXWVxPpuzapLL6np4O3d9l+qlZ1U7Yff7x4ZX/ssZLr+vg407hxTXx8nC3uT08vZkOWkPfeey/fosOBgYHcd999bNiwAVdXVyZPnszGjRvR6XT5jsvJyVEWhB0zZozVNw0B+Pn50bJlSwD27t0LQG5ursW0BoOBq1evcurUKU6cOMGJEyf466+/lDcVHT16tFD6jRs3AtCzZ0/atm1rV72t6dvCtEhx8+bN6dy5s9V0j5udSLYWNh4/fjwuLi7FLoc5KSkpyraXl5ddx1ire3R0tLLo9dSpU62WzcfHR3kLVExMDNeuXbOYzsnJiQceeMCqtmnB3cTExEKLba9btw4wvg1t2rRptitUgE2bNpH592r8Bd9WVbDuPXr0AIznc3R0tNU8H374Yav7Ro4ciZ+fH2Dbb0cTFRXF119/TVxcHFCyc97ETz/9BED16tXp379/of2mxb6jo6P566+/8u3T6XSMHDkSgPXr11tcWD0iIoK0tDQAJk2alG9fefQ1Jbn2kpOTOX/+PH/++afSN3l6eubbZ862bduU7YceeshqvoMHD6Zq1apW90dERADG/q2ot0Oazuei+tmClKQfMcf8mOTkZGU7KSmpVPkWxFROe/Iqzfle2ZABJkmZ4uQEX31lvBk9dw4uXCh7jVOnTpU+k/ffNxbywAFYvNix2qVAbX01UbPuare72vpqIn3XJlr2XWKdJk2a8PLLL+Pj41NoX0xMDOl/R8Fee+21Qm9fK/g5dOgQANevXwdQAgAAQgh+/vlnevfujbe3N8HBwTRt2pSWLVsqnz/++AMoHJA8f/688sBqeriyh8xivg4wKyuL2NhYADp16mQzbdu2bZWAnOl12pZo1apVscpgCfPXc5se0IvCWt3Ny1pUHc33W6tjYGBgoQdnc+2AgABl2/wBF+DIkSMAdOjQQXmItxfTuQZQs2bNfOeht7d3vv+HhIQoaU3nZkH0er1Nr3Q6nRLYtOV3WdOzZ0+EcXaM8snOzub8+fPMmzcPX19fli9fTufOnTl9+nSxz3kTd+7cYfXq1QBMmDDB4lsKzb83BaPMMQWYsrOzWbZsWaH9pjcKBgUF0bdv33z7yrKvMWHvtXfx4kWeeeYZ6tevj6+vLw0bNiQkJETpl8yDnwX7JtO54Obmlu88K4iLiwtt2rSxut9Un02bNhVZ988++6zIulvCvB9JTU216xhzzI8x/3uh1+uVbXv7J1uYymlPXiU93ysjMsAkKXPq1oXVq+Gvv6BhQ7VLY4UaNeC114zbr74KGRnqlkcikUgklQ5PT0hNLdvPxYsJyvawYeBs552as7MxfUl1k5MNxMZeIznZYHF/MZ+pS8xTTz3F8ePHOX78OEeOHGHdunU88cQT6HQ6YmJi6NWrl8UgYHx8fIn00gsMzcrMzGTw4ME8+OCDREVFkVHE/UHB/eYPdTVr1ixRmewhMTFR2Q4KCrKZVqfTKYGV27dvW03n7+9f6nIFBgYq2zdu3ChVXuZlLaqONWrUsHicOUUFhpzNLra8vLx8+0y+lsTTsjo3TQQEBFgMqphjai9bfjsCnU5H/fr1mT59OlFRUeh0Oq5cucJjjz1W4jwXL15MVlYW8M9IpYKYj2z6+eefMRSYrRAaGkr9+vWBf4JJJm7dusXmzZsBY6Cq4MiisvYT7Lv2NmzYQPPmzZk7dy4XL14sMn3BvsnUZ/j5+RU5WqpatWoWv8/JybE44qsobNXdEr6+vso5bi3Qagvzvsc8qGy+Xdr+Cf7p75KSkpRzUgK2eyeJpIT07l1+eY8fP75sMnrhBfj6a7h0CT7//J+AkyO0S4ja+mqiZt3Vbne19dVE+q5N1PY9OzvbrrROTlAGo+zz4ekZgGnGxZgxxh9s7MFggLFjS14egwE8PQVeXvYHtcqD6tWr5/t1vU2bNgwaNIihQ4cybNgwbt++zQMPPMCBAwfyPSSZBwRmz55NWFiYXXqmqQ2m0SuzZs1Spr/07NmTGTNm0K5dO2rUqIGHh4cShOjRowe7du1CCGE1b1tTZwpiPnqmuNijY6ucJko7PQ6gdevWbNmyBYDDhw/TuHHjIo+xp+5F1dGe+pVUuzjlsITp3NTr9YWmvQkhrOZpmoZZkjKUtD3KkxYtWjBo0CAiIiLYtWsXCQkJNqdiWcN8RFJoaGiR6a9cuUJkZGS+kUhVq1blgQce4MMPP2Tnzp3ExcURHBwMwJIlS5TpTAWnx0HZ9TXmFHXtJSQk8MADD5Ceno63tzczZ87k/vvvp1GjRvj6+iojc7Zv367UszzOAfO6jxs3jrfeeqtYxxfnemvVqhWHDx/m+vXrXL9+PV8QuSgOHz6sbLdu3VrZ7tq1Ky4uLuTl5eVLU1Jat25NbGwsBoOBP/74w+ZIy9L08ZUNOYJJUq4IAQsXwtq1ZZfn2rLKzMMDPvoIOne2OyJWZtolRG19NVGz7mq3u9r6aiJ91yZa9t18jYixY8HfH4p6nnRyMqYbM6acC6cigwcP5sknnwSMDw8LFy7Mt9/8QTUnJ4eQkBC7Pg0aNACM7S6E4LvvvgOge/fubN++nbFjx9KoUSO8vLzyjXAxH0FkjvkInqtXr9pdP3Pf7cF8xENRv/Dn5uYqI1nK+yGnZ8+eyrZp3aKisFZ387IWVUfz0QjFqaO97W7ytTiemjCdm9nZ2VStWjXf+VenTh2r56ZpHaWCJCQkFBphVRDTKJuK9lDbtGlTZXv//v3FPv7MmTP8/vvvxT6u4DS5pKQkZfSTwWAgPDxc2Wca0dS4cWM6duxYKK+y6GuKy9KlS5WRQytWrOCdd96hc+fOVKtWLd+0L2v9EvzTZ9y5c6fI8+fmzZsWv3d3d1dGAt65c8fuupt+NChO3c2nGK+295cWjH6uX78eMI5K7Nq1q7JPCKFM/zt16hRnzpyxO19LFKe/K4nvlRUZYJKUKwsWwMMPw7RpUFbXVVnMmVV44AH4/XdjkMnR2iVAbX01UbPuare72vpqIn3XJlr23fzG390dfvzRuG0tyGT6/scfjenvZt555x1lFMB7772Xb6RZixYtlAct0/SW4pCXl8ft27eVQMa4cePyBZTMSU1NtbpWV4MGDZQHuZ07dxZL34Q9I1Tc3NyU0UFFPagfOXKEnJwcAJtrr5QFAwYMoFatWoDxodi0oLMtrD3smpe1qDoeOHDA4nEl1S5Iu3btAOP6M8Wd7mO+0HvBc9NefXOys7MLLS5vTm5urrJGmKW2KMkorLLCfKHjkkwpMg8U/e9//yM8PNzmxzS6aMWKFfn69ry8PJo1a6Z48+uvvwJw4cIFZUFqS6OXoGz6muLy559/AsaAoaVFzU2Yr/dVkBYtWgDGdj9+/LjN8pnOH0uY2mzPnj3FvhaKU/cpU6Yo2/PmzbP72OXLl3PlyhUAhg8fni8Yn5eXpyyQL4Tgyy+/tLs8lpgwYQIeHh4AfPfddzbvH0rie2VFBpgk5crkydC4MVy7ZlzqqCwwDWEtE5yc8t+1FzGctEy1S4Da+mqiZt3Vbne19dVE+q5NtOy7+a/RAEOHwqpVYBrMYIp5mP7184OICGO6u53q1avzxBNPAHD58mV+NEXfMK6vY5oaEhUVlS/gYA96vT7fw6+tB6cFCxYoAZuCODs7M2jQIAB27NihLA5tj74J978jhUU9gPfr1w8wLjq8b98+q+lMo7LMjykv9Ho9M2fOBIzrWT366KNFPliZ6n7lyhW2b9+ufN++fXtlFM+PP/5oNZ+UlBSWLFkCGN+oV5x1kgpeb9YY+vcFlp6ezrfffmt3/gADBw5UFlmfM2dOvvPMXv2CmJ/7BVm5cqUyksWS36bzy96pwGXJwYMHlW3TGkj2Ylp8H4yBsyeffJIJEybY/MyYMQMwBoVXrFih5GVqd1MQ6ciRI/z111/8+uuvytSygm8cNFEWfU1xMZ0zWVlZhdaTMpGenm5xQXMT5lMEFy1aZDXdunXrSEhIsLp/2LBhgPHHmHnz5tksd0GKU/c2bdowYMAAAI4dO8bs2bOLPObWrVu8+OKLgDGQ+vLLLxfSf/jhh5XpdvPmzWPHjh12l6lg+wYGBipv6bx27RrPP/+81WML1v3PP/+0+abISo2QSIpBUlKSAER8fLzdx0RGCmGM3Aixa1fpy5CQkFD6TAqSlCTEa68JMWyYEAaDY7WLgVr6mZmZ4t133xWZmZmq6AuhbttL36XvWtKXvieIjIwMERMTIzIyMhyun5OTY/H7jAwhFi0SYtQoIXr1Mv67aJHx+7IgLy9PxMXFiby8vLLJsBhERkYKQADinXfesZn22rVrwt3dXQCiYcOGIjc3V9m3e/du4eTkJADRoEEDcebMGav55Obmil9++UVcvnxZCGFs97y8POHn5ycA0aZNG5GVlVXouAMHDghvb2+lvD179iyU5siRI8LZ2VkAokmTJoqGJcz1TfTu3VsAomPHjjbb4tixY4pOy5YtxZ07dwql2bRpk3BxcRGACA0NLbR/27ZtSl0iIyNt6tlLXl6eUgdADB061OZ9Y3Z2tvj5559F9erVxZw5c/LtmzlzppLPW2+9VehYg8EgHnroISXNV199VSjNlClTBCDq1atXaJ95u//www9KPufPn8+XLiMjQwQHBwtAeHp6iqioKKv1seT3tGnTlLwfeeQRRdfS9X7jxg0xf/58q/UAhE6nE7ss3FRfu3ZN1K1bVynnjRs3CqUxedOmTZsyud5tXQvmrF27VkkbGBhY7P51x44dyvHvvvuuXcdkZWUJHx8fAYh+/fop35vaPS4uTrmG3njjDdGiRQur14o5pe1rhMjf7xV17f3nP/9R0i5evNiixsSJE5U01vJs1aqVAIRerxd79uwptD8+Pl40bNhQycPSNZOUlCQCAwMFINzc3MT69ettln337t1ix44d+epuLxcvXlT6ZCcnJzFnzhxhsPKcduHCBdG6dWul7P/6178KpTHpb926VfHdy8tLLFu2rMhyjB8/Xvj6+hbal5aWJpo3b67oPvbYYyIlJcWqdnZ2tvjyyy+Ft7e3WLlyZREtkJ+S3pvEx8cLQCQlJRXruJIiF/mW2MW8efPyDU9ctWoV3t7ejBo1im3btpGUlET16tUJDQ1V1q9o164dBoOBa9f+oFevUKKiGvHAA6n8+9/rCAryo0ePHqxatQowLuSm0+mUSO7gwYM5dOgQN27cwMfHhwEDBiivEU1OTqZ///7KcOn777+fEydOEBcXh5eXF0OGDGHx4sUA3HvvvQQGBrJnzx7A+EvO6dOnuXTpEm5ubowaNYrFixfjee0agz/7DOecHKJefZVrbdrQq1cvLl26xLlz53B1dWXs2LEsXLiQmjVrUq9ePRo1aqT80ta9e3fi4+M5ffo0ABMnTiQiIoL09HRq165N8+bNlWG0Xbp0ISkpiZiYGADGjh3Lxo0bSUlJoUaNGrRr106ZO9yxY0cyMzOVoax5eXkEBgaSmJhIYGAgXbp0Yc2aNcA/Q1ZNv5YOHTqUvXv3cuvWLfz9/enVqxcrV64EoGXLlri7uyu/JA0aNEhZSK9KlSqEhYWxdOlSwPhroGn457JlywgLCyMmJoYrV67g6enJ8OHDlbnrTZo0oXr16uzevRuAPn36cPbsWS5evIher2f06NEsXbqU3NxcGjZsSN26dYmKigKMc63j4uI4e/Yszs7OjB8/nhUrVpCVlUXdunWJjY3Fzc0NgG7dunHr1i1lisL48eNZu3YtaWlpBAcHExISwqZNmwDjq4tTU1OV4cVjxoxh8+bNJCcnExQURIcOHZR50+3btycnJ4djx44BMGLECHbu3Mnx48dp1aoV3bt3JyIiAjD+suLs7KwsEjhkyBAOHDhAfHw8vr6+9O3bV/m1LCQkBE9PT+VXroEDB3L06FGuXr2Kt7c3gwYNUn59bdq0KQEBAcoaA/3792fx4sUEBATg4eHBiBEj+O233xBC0LhxY2rUqMGuXbsA6N27NxcuXOD8+fPodDrGjBnDsmXLyMnJoUGDBtSvX5/IyEgA7rvvPq5fv05sbCxOTk5MmDCBVatWkZGRQZ06dWjatKnShpcuXSI1NZWTJ08Cxqkj69evJzU1lVq1atG6dWtlUdzQ0FDS09OV1+Ha00eYhmIPHz6c3bt3k5CQQEBAAD169OD7778nODi4WH1EixYt8Pb2LnUfce3aNV588UUWL16MwWCgUaNGBAcHK9NeLPURy5cvJzs7u0z6iC1bthAcHFysPmLkyJFERUWVqo8w/Tp67tw5xZui+ghfX19lWsGAAQNK3UdcvHiR++67r1h9RJMmTdi6dWup+wiDwUDVqlUJDAwkNTUVnU6nrH3h5eWFEEIZ3eLv709KSgq5ubm4urri7e2tpPX09MTJyUkZMu/n50daWho5OTm4urpSpUoVZZSBafFo0/7AwEAyMjLIzs7GxcUFX19f0tJuM3AgjBrlgYuLi/IaZhcXH1JSMsnOzsbZ2Rl/f39u376NEAJ3d3d0Op3yynUfHx+ysrLIysrCycmJgIAAJa3p11VTmapUqUJOTg6ZmZlK2sTERAwGA3q9Hnd3d5KTkwHw9vYmLy9PeWtRQEAASUlJ5OXlodfr8fDwUNaf8PLywmAwKGn9/f3zvVLaYDAov54XbG8/Pz88PDyYNGkSCxYs4Ny5c3z77beMGzcOT09P2rdvz8yZM5k9ezbnz5+nTZs2TJo0iT59+tCoUSNu3brFpUuXOHLkCBEREVy9epVdu3ZRo0YNbt++jYuLC2PGjOG7777jjz/+oEuXLjzzzDM0adKEGzdusGXLFn744Qe8vLwICgri7NmzAIXau06dOrzyyit89NFHnD59mpCQEB599FEGDRqETqcjMTGRkydPsnbtWoQQREREIITAw8ODzMxM2rZtS2RkJAcPHuTtt98mLCyMgIAAUlJS8PDwoHHjxuTl5VGrVi2mT5/O3LlzOX78OG3atOH5558nNDSUmzdvsmnTJubPn6/48Mknn2AwGJRzVqfT5VsIOCsri4yMjHztbe2cLXh++/r6kp6eTk5ODi4uLixevJiBAwcSHR3NmjVraNSoEaNHj+a+++6jcePGGAwG4uLiOHz4MKtXryY2NhYwjqrJzs5WztnXXnuN5cuXc/78eT744ANOnDjB2LFjCQoK4tq1a8yfP18ZgdC5c2cmTZpEQkJCvnPWfCSY6dzy9vYmNzeXlJQUdDodAQEB+Uat5ebm5ktrMBiYO3cuY8eOJT09nb59+zJu3DiGDRtGo0aNSEhI4MyZM0RGRrJ27VplrSZTH/H666+ze/duYmJi+P7779mzZw+PPfYY9957L1WqVCEpKYlLly6xefNmNm/eTPPmzXnkkUfy9RGme/DAwEC8vLzo378/Tz75JAMGDKBq1apERUUxZ84cZZrnq6++iouLi3Idm/qIrl27EhkZyR9//MEHH3zA4MGDlfOgWrVqBAYGWuwj3NzccHNzU657Ux9hIi0tjT179iCEQKfTodfruXPnDteuXSMqKooffvhBSTtr1iySkpJIS0uzq49ISUnJN3Ksb9++JCQkWOwjUlNTlT65SpUq9O/fn+XLl7N9+3bOnj2Ln58fOTk5VKtWDW9vb7p3787OnTuZN2+e0n+PHTuWrKwspW/y9fXN1yd37drVYl/Tq1cvGjZsSGpqKmfPnuXQoUPK+bBr1y78/f3JyMjAyckp35o8SUlJ3L59O18/a97e/fv3x83NjaysLKZOncrevXsZOnQoTk5OxMTEsGDBAo4cOUKnTp2Ue5/MzEzlHDb1yR9++CHDhg0jOzubfv368dRTTzFo0CD0ej379u3jiy++ID4+npYtW3L8+HGEEOTl5eX7u6bT6fjmm28YP348WVlZDBkyhKFDhzJ8+HBatGhBcnIyN27cICYmhjVr1nD8+HE+/vhjunbtSkJCAq6ursrfNdPacB4e+f+umdrby8uLn3/+mQceeIDk5GReeOEFFi1axIMPPkijRo3w9PQkOTmZDRs28Ouvvyr90bBhw/jXv/5Famoqer1e6U9M/WybNm34/PPP+de//kVaWhpjxoyhY8eOjBkzhsaNGyvnyNmzZ9m0aRMbN24kKysLHx8fEhISCp2zy5YtY/jw4cTGxvLdd9+xevVqxowZQ+fOnalduzZubm6cOnWKAwcOsG7dOi5fvgwYR1+a98lF3Ue4u7uTmZnJ2rVrlZF09jxrOByHhLEkdw0lGcEkhBC3bwsRFGQcxVTEj5NF8uuvv5YuA2vMnGksYLNmQliJsJebtp2opV8RRjSo2fbSd+m7lvSl77+qOoLp1q1bDtcUovKMYBJCiEuXLgm9Xi8A0bRp00JlnjNnjnBzc8v3a76lj16vF7GxsUKIf9r9zp07ok2bNlaPCQgIEDt27BA9e/YsctTGhx9+KFxdXW2WwXS8ue9XrlwRAQEBNtObyMvLE9OnT7ep4evrKzZt2mSxjOUxgslERkaGeO655xSvbH2cnJzE5MmTRVxcXKF8zp8/L5o2bWrz+G7dulkd+WhrBJN5u9sawWRi48aNwt/fv8j6WCIhIUGEhYUVeSwgevfubbMeBw8eVEaRWPo8++yzFssgRPHOL3uwpz6mj06nE5988okQonh9XXp6ujIS6d577y1W+VasWKHof/zxx4W0v//++3xldHFxEdevX7cr79L0NcUZwWQqp2nUjaXP+PHjxdatW23mmZeXJ+bMmSN0Op3FPFxdXcX8+fPFgw8+qPSv1ti2bZuoUaOGXb7/+OOPhdq9OBw7dkx06tSpSB1PT0/x7rvvWv07VlA/KipKhISE2FWHunXr2rw3SUhIEA8++KBNj8yvg2effdbiqFNbVJYRTDLAJCkWJQ0wCSHE4sXG+I2bmxB29tsWOXv2bMkPtkViohBVqxoLaWGIdblq24la+hXhgVPNtpe+S9+1pC99P6tqgEmtdq9MASYhhHj88ceVY5YsWVJo/5UrV8Rbb70lOnfuLAIDA4Wrq6vw8vISTZo0EaNHjxZff/21uHnzppLevN3T0tLEBx98IFq2bCnc3d2Ft7e3aNasmZg5c6YyzcWeAJMQQpw+fVo8//zzIiQkRPj4+Ah3d3fRsGFD0bdvX/H555+La9euFdIXQogzZ86IRx99VNxzzz3KlEBbejt37hSTJk0SdevWFW5ubsLHx0e0adNGvP766zbv2cozwGTi4sWL4uOPPxb9+vUTdevWFR4eHsLd3V3UqlVLDBgwQLz33nviwoULNvPIysoSc+fOFT179hRVq1YVOp1OBAUFibCwMLFo0SKb562tAJN5u9sTYBJCiMTERPHhhx+Krl27KmUJDg4WnTp1Eq+//ro4fvy4zbps27ZNPPzww6Jx48bC29tbuLq6ioCAANGxY0cxY8YMsX79+nxTP63V49KlS+LZZ58VjRo1Eu7u7qJq1aoiLCysyClLQhjPy4kTJ9p9ftnC1oO0i4uLCAgIEKGhoeKVV15RgixCFK+v+/XXX5U8X3/99WKVLz09XXh5eQlAtGjRopB2UlJSvjYYMGBAsfIvaV9T3ACTEELs2bNHjBgxQlSrVk3odDpRs2ZNERYWpkybKypPUz9/5MgRMWnSJFGrVi2h1+tFcHCwGDdunNi3b58QQojhw4cLQHTq1MlmedLS0sTcuXNFWFiYqFmzptDr9cLd3V3UqVNHDBgwQMyaNUucPHmyUN1Lytq1a8Wjjz4qmjZtKnx9fYVerxe1atUSPXr0EB999JG4cuWKzeMt6efl5YmIiAjx+OOPixYtWige+vn5iZCQEPHII4+IiIgIu6f3xcTEiHfeeUd0795dBAcHCzc3N+Hp6Snq1Kkjhg4dKubMmWNx6qo9yACT5K6kNAEmg0GI558XYvfu0pXh6NGjpcvAFnPnGgNMgYFCWIgql6u2HailXxEeONVse+m79F1L+tL3o6oGmNLS0hyuKYS6ASYTatVdbW019aXvlcd3W4Gy4iJ916a2vb43atRIAGLy5Mllql+ZrreKqF1ZAkzyLXISh+HkBHPmQLdupcvHtE5GuTBtGjRtCrduwYcfOlbbDtTWVxM16652u6utrybSd22iZd9N645oETXrrna7q62vJtJ3baJV3yu65wcPHlTWl+vcuXOZ5q123aXvjkEGmCSqceYMqLHumE10OjC9BvPbb8Fs4VGJRCKRSCQSiUQiqaycP3/e6r6EhAQef/xxANzc3Bg/fryjiiW5i5BvkZOoQng4PPIIhIXB3y82s5sxY8aUT6FMDB4MH30EkyaBt7djtYtAbX01UbPuare72vpqIn3XJmr7bnpbkxr4+/urpq02atZd7XZXW19NpO/aRKu+q+35xIkTueeeexg5ciStWrXC19eXxMRE9uzZw1dffcW1a9cAePPNNwkMDCxTbbXrrmXfHYkcwSRRhZAQyM2FVavg77cr2o3pVd7lhpMTvPoq1KnjeO0iUFtfTdSsu9rtrra+mkjftYmWfTe9AlyLqFl3tdtdbX01kb5rE636rrbnQggiIyN59tln6dWrF23btqVPnz689dZbSnBp+vTpvP7662WurXbdtey7I5EBJokqtGwJr7xi3H76abhzx/5jHX6BRkeDEOpoF0BtfTXR8h8FtfXVRPquTbTsu5qjp9RGzbqr3e5q66uJ9F2baNV3tT3//PPPefHFF+nQoQPBwcG4ubnh5eVFo0aNmDJlCnv27GHevHk4O5d9mEDtumvZd0cip8hJVOPNN2HpUjh92jhg6Ouv7TsuKCiofAtmzsMPw8KFMH06XL9O2NmzsGwZjBgBY8eCu7vjyoKD617BULPuare72vpqIn3XJlr2XafTqaqvJmrWXe12V1tfTaTv9rFw4UIWLlxYfoVxMFr1Xe1zrkuXLowcObJcAkhFoXbdtey7I5EjmCSq4e5uXEcb4JtvYNcu+47r0KFD+RWqINnZxn+/+gpWrcL/6FHjvL6HHoJatWDNGseVBQfXvYKhZt3Vbne19dVE+q5NtOy7l5eXqvpqombd1W53tfXVRPquTbTqu/Rcm/pq192RyADT32RmZvLVV1/Rt29fqlWrhl6vJzg4mMGDB7N48WK789m4cSOjRo2idu3auLm5Ubt2bUaNGsXGjRvtziM9PZ3Zs2cTGhpKQEAA3t7eNGvWjJkzZ3Lp0iW78/nzzz958sknueeee/Dw8KBatWr06NGDb775htzcXLvzKU969oTHHjNuT5sGWVlFH7Nu3bryLZSJ1auNq5GbMBjy/3vnDgwfbkznIBxW9wqImnVXu93V1lcT6bs20bLvd4ozZ/wuQ826q93uauurifRdm2jVd+m5NvXVrrsjkVPkgFOnTjF8+HBOnTqV7/urV69y9epV1q9fz8KFC1m2bJnV6KMQgieffJJvTUNy/iYuLo6VK1eycuVKpk2bxtdff42Tk5PVspw9e5bBgwcXKsvJkyc5efIk3333Hb/++iuDBg2yWacFCxYwY8YMsswiNpmZmezatYtdu3axcOFC1q5dS9WqVW3m4wg+/RQ2b4aJE43ra1cIMjNh6lTbaYQwFnjqVLh61eHT5SQSiUQikUgkEolEIqkoaH4E082bN+nfv78S0Bk7dixr167l8OHDrF27lrFjxwLGkUkTJ060ms+bb76pBJfatm1LeHg4Bw4cIDw8nLZt2wLw7bff8tZbb1nNIzU1lSFDhihlefzxx9m2bRu///47s2bNwtvbm6SkJMaOHcuxY8es5rNp0yamTZtGVlYWQUFBfPnll+zfv58NGzYwatQoAPbt28eoUaMwmEbjqIi/P5w6BW+/DXp90enbt29f/oVauhQSE5XFva0ihDHdsmXlXyYcVPcKipp1V7vd1dZXE+m7NtGy71oaRl8QLU9fUFtfTaTv2kSrvkvPtamvdt0dieYDTO+99x6XL18G4J133mHJkiUMHjyYtm3bMnjwYJYsWcLbb78NwJo1a1ixYkWhPM6cOcOnn34KGNdu2LNnDxMmTKBjx45MmDCB3bt3K2s6fPLJJ5w9e9ZiWT777DNOnjwJwKeffsq3335Lnz596NKlC6+//jqbN2/G1dWV9PR0nn/+eYt55Obm8vTTT2MwGPDx8WHPnj0888wzhIaGEhYWxvLly5k+fToAO3fu5Oeffy5545Uh5oN/cnL+mYVmiZycnPIv0KpVYO/id87OsHJluRbHhEPqXkFRs+5qt7va+moifdcmWvZdFPXDxl2MmnVXu93V1lcT6bs20arv0nNt6qtdd0ei6QBTXl4ev/zyCwD16tWzOrro7bffpm7dugB89NFHhfbPmTNHWdPov//9Lx4eHvn2e3p68t///hcwBoA+//zzQnnk5OTwxRdfANCsWTP+9a9/FUrTpUsXHn30UQAiIyOJjo4ulGblypWcOXMGgNdee41GjRoVSjN79mz8/f2V7YrEoUPQsaPtN8rZGr1VZiQk2I5ymWMwwO3b5Vuev3FI3SsoatZd7XZXW19NpO/aRMu+p6enq6qvJmrWXe12V1tfTaTv2kSrvkvPtamvdt0diaYDTLGxscqCW/3798fFxcViOhcXF/r37w/AoUOHuHDhgrJPCEFERAQATZs2pXPnzhbz6Ny5M/feey8Aq1atKhTFjIqKUsoyZcoUq6+OnGq2LpCl0VSrVq2ymNYcT09Pxo0bB8CJEyeIjY21mE4N9u2Do0fh1VfhyhUVC1K1avFGMAUElG95JBKJRCKRSCQSiUQiqcBoOsB022zUSVBQkM205vt37typbJ8/f564uDgAevbsaTMP0/4rV67kC1IB7Nq1q1A6S3To0EGZw7l79+5C+0353HvvvdSoUaPIsljLRy2eego6d4aUFHj6actLII0YMaL8CzJiRPFGMI0cWa7FMeGQuldQ1Ky72u2utr6aSN+1iZZ9N40w1iJq1l3tdldbX02k79pEq75Lz7Wpr3bdHYmmA0zmi20lJSXZTGu+PyYmRtn+66+/lO2mTZvazMN8v/lxxcnH1dVVmfZWMI/U1FSu/D3spzRlURMXF5g/H3Q6iIgAC4O08gX4yo2xY42rjxf1WjsnJ2O6MWPKv0w4qO4VFDXrrna7q62vJtJ3baJl31NSUlTVVxM16652u6utrybSd22iVd+l59rUV7vujkTTAaZ77rkHnU4HFH1Dab7/0qVLyrZpgXCA2rVr28yjTp06Fo8z/7+Xlxd+fn525XPz5k2ysrKU769cuaJMvStNWdQmJAReecW4/fTT8PfMQYXbjljvyN0dfvzRuG0ryCQEzJqVf5XycsQhda+gqFl3tdtdbX01kb5rEy37blrTUYuoWXe1211tfTWRvmsTrfouPdemvtp1dySuahdATby8vOjbty8bN27k2LFjhIeHM3HixELpwsPDOX78uPJ/8wik+ba3t3eReiZSU1Pz7TPlU1QelvJxc3Mr07KYk5WVlS+IlZycbPH7smbmTFiyRMfp087MnJnHvHn/XJS+vr7lqq0wYADOS5fi+thjON25g3B2xslg+OdfFxec8vIwfPEFOWPGgI9PuRfJYXUvgElTDW0TatVdbW019aXv0ne1UNv37OxshBAYDAYM9k6XLiNcXV0drgn/vOHGVG81UKvuamurqS99l75rse21qq2271q93spK22AwIIQgOzsbp6Jm2Zjh6PspTQeYAN577z22bt1Kbm4uU6ZM4ezZszz00EPUrFmTa9eu8dNPP/H++++j1+vJzs4GICMjQzk+MzNT2dbr9Ta1TIGggnmY51NUHrbyKauymPPRRx/x3nvvFfp+3rx5uJfzqJ2uXety+vTDbN16mX//exGurv9clAcPHixXbXNcZsygeUwMTU+exCMjgwwPD042bcrFevV4dMECfE6d4lyPHiwZN87+hcFLgSPrXpA5c+aopg3q1l1NbbX1pe/qIX1Xh5iYGLp168atW7dwdXX8rVJaWprDNU3cuHFDNW1Qt+5qaqutL31XD+m71HY0avqudt0rs++5ubkkJSWxfv36YuVlHiNwBJoPMIWGhrJgwQIef/xxsrOzeeutt3jrrbfypXFxceHzzz/nmWeeAaBKlSrKPvMgiykAZQ3z6KGHh0e+faZ8isrDVj5lVRZzXnvtNV588UXl/8nJydSpU4cZM2ZQrVq1IstaWiZNyqZbt5o4O7+sfLd06VLGjh1b7tqWMGk3+vv/TqNGIfr1o9nJk7zh4kKeaW5fOes7mqysLObMmcMLL7yQLzjpSCqC72ohfZe+OxLp+1KGDRvGlStXCAwMLPcfUwqSmJioymKgQghu3LhBUFBQsX4ZLUvUqrva2mrqS9+l79J37Wir7btWr7ey0s7MzCQ1NZVp06YV6/7s5s2bfPzxx6XSLg6aDzABPPTQQ7Ru3ZpZs2axceNGZaqZs7MzvXv3ZtasWfmmlJmfHObBJltTzSB/1LLgFDZTPkXlYSufsiqLOW5ubhZPYGvflzX9+hX+zsXFRbWHnkLa990H8+bB44/j+u67uA4YYHwNnqP0HYyjfLdEhfJdY/rSd3VQW1/Lvuv1epycnHB2dsbZASNTC6KGpmnovqneaqFVbbX0pe/Sd622vRa1K4LvWrzeykrb2dkZJycn9Hp9se6RHH0/pelFvs1p3bo1S5YsITExkcuXLxMbG0tKSgpbt26lU6dOHDt2TEnbvHlzZdt8MW3TG9ysYb6Ytvki2+b5pKWlcafgqtZW8qlWrVq+E6asylIRSU2FF1+EEyegTZs2qpXDovZjj8ETT8Crr0LHjo7X1wgVzncN6auJ9F2baNl3T09PVfXVICoqCicnJwIDA3Fycsr38fDwoHbt2gwcOJCvvvrKrh/iSoLa7a62fnly+fJlZs+ezYABA2jQoAHe3t54eHgQHBzM/fffz5dffsn58+dVKZva7a62fllQ8JoteP3WqVOHoUOHsmjRIvLy8pTjyqruGRkZ+Pr6Kprvv/9+kceo2e53g+clpbh1r1+/vuJrlSpVuHnzps30pr8lTk5OLFy4sEh9IQRr1qzhySefpGXLllSvXh2dTkdAQAAtW7bkkUceYdWqVeTk5FjU69Wrl6JXFFryXQaYCuDi4kLt2rW555578p0Iu3fvVrY7deqkbJsHm06ePGkzb/P9zZo1y7fP3nxyc3M5e/asxTy8vb2VYFFpylIRefFFmDMHpk0DNU9bq5Hn//0PPvwQXFzU0dcAlfkXh8qurybSd22iZd/Vmq5SUcnMzCQuLo6NGzcyY8YMQkJCOHr0aJnrqN3u5vqmh6qpU6eqV6AyICsri3/96180btyYl19+mS1btnDhwgXS0tLIzMzk6tWrbN68mffff59GjRoxfvx4h7/ZuCL57ijq16+Pi4sLzz//fLlrZWZmcuXKFdauXctDDz1E586dlSBBWdV95cqVykuIABYtWlTkMWr6rvY5pyalqXtqaiqffvppmenv3r2btm3bMmzYML755htOnDjBzZs3yc3NJTExkRMnTvDDDz8wcuRI6tevbzFgVVLtux3t3r0Wg+zsbJYtWwZAcHAwXbt2VfY1aNCAWrVqAbBjxw6b+ezcuVPJo379+vn2de/eXdm2lc+hQ4eU6W3dunUrtN+Uz6lTp7h+/brVfMw1LOVT0Xj7bahSBfbuhU8/TSn6gHLi8OHDlneYdxpZWfDdd/D3mxocoq8B1Ky72u2utr6aSN+1iZZ9V3sBVLV56qmnOH78uPKJjIzk66+/pkmTJgBcvHiRgQMH5ntzblmgdrurrV/WJCQk0KdPH/7v//6PrKwsqlSpwrRp01i8eDF79uzhwIEDrF69mldeeYWGDRsihGDJkiUsX77coeVUu93V1i9LOnTokO/aPX78OHv37mX+/Pm0bt0aMD7HjBkzBii7uv/000/AP0t+nDlzht9//93mMZV5oefKTGnrPm/ePJvPt/bqL1q0iD59+ig/VnTq1IlPP/2UzZs3Ex0dzfbt25k/fz4jR45Er9dz9erVUgdkteS7DDDZwRdffKFE25988klczEapODk5MXz4cMA4Kmjfvn0W89i3b58yamj48OGFopi9evXC19cXgB9//FF5jWRBzKOnI0eOLLR/xIgRFtOak56ezpIlSwDjyCnTTVtFpnZt+Ogj4/bixa0pYgagehgM0L8/PP44/N//qV0aiUQikUgqFdWrVyckJET59OrViyeeeILjx4/Tp08fAK5du8a3336rckkl1jAYDEyYMEF5yB80aBBnzpzhm2++Ydy4cXTt2pWOHTsydOhQPv74Y/bt28ePP/5I9erVVS65pDR4eXnlu3ZDQkLo3Lkzjz32GL///jtNmzYFjD+479+/v0w0r127xtatWwF4++23qVq1KvBP0ElydxAYGAgYp0N+ZHogLCFRUVE8/PDD5OTk4OnpyeLFi9m3bx8vvfQS/fv3p127dvTu3ZvHHnuMFStWcOrUKcaNG1cW1dAMMsAEXLp0yeq+NWvW8MYbbwDQuHFjZs6cWSjN888/r7zG+JlnniEjIyPf/oyMDOUNdK6urhYjoHq9nmeffRaAv/76i88++6xQmr1797JgwQIAevbsSUcL6/2MHDmSRo2M7zj76KOPlOl05rz00kskJiYq25WFp56CLl0gI0PHjBnlMkCoSIYMGWI7gbMzjB9v3H75Zdi2zbH6dzFq1l3tdldbX02k79pEy777+fmpql9R0ev1vPvuu8r/t2zZUqb5q93uauuXJf/973+Vh/5+/foRERFhM3gUEBDAQw89RHR0NK1atXJUMQH1211tfUfh6enJ008/rfx///79ZVL3n3/+mby8PFxcXHjwwQeVQMCSJUvyvTG7IGq2u1Y8t0RJ696iRQsGDRoEwDfffENcXFyJ8nFzc2PSpEnk5eXh7OzMmjVrigwe1a9fn8WLF/PFF1+USNOElnyXASYgJCSE+++/n++++469e/cSHR3N8uXLmTBhAsOGDSMnJwd/f38WL15s8XXFTZo0UQJPhw4dolu3bixevJhDhw6xePFiunXrxqFDhwBjQKdx48YWy/HSSy8po4lefvllnnjiCSIjI9m3bx8fffQRAwYMIDc3Fw8PDz7//HOLeeh0Or788kucnZ1JTk6mW7duzJ07lwMHDrBp0ybGjBnDV199BRin0z344IOlbT6H4ewM8+eDq6uB1avBwaOoAThw4EDRiaZPhylTjKOZxo+Hixcdq3+Xombd1W53tfXVRPquTbTsu7Vh9JmZsGgRjB4NvXoZ/120yPi9VmjXrp2yXdRaPadOneLZZ5+lRYsW+Pr64uHhQcOGDXn44YctToM0b/dr167x1VdfMWbMGBo3boyXlxdubm4EBwczfPhwFi9erLyNqSguXLjAK6+8Qvv27alatSru7u40aNCA3r1785///Ef5kTMtLU1ZMPbi3/cNP/74Y6FFk3v16mVRZ/fu3Tz44IPUr18fd3d3/Pz8aNu2LW+++abNhXGjoqIIDg7GxcWFqKgoDAYD33//Pb179yYoKAhnZ+dirQWVk5PD7NmzAXB3d+eHH35QfoS1hqnta9eurYxSK0h2djZfffUVvXv3plq1auj1emrUqMGgQYP4+eefbfoxdepUnJyclOUp7ty5w9tvv02LFi3w8fHBz8+PHj168Msvv9hVx5SUFP7zn//Qp08fatSogZubG7Vq1aJTp0688sorNqfZCiFYtmwZo0ePpk6dOnh5eeHv709oaCgffPCBzRf9FKxHXFwcL774Ik2aNMHT05Nq1aoxaNAgNmzYYPH4gufX0qVLcXFxsev8KgvMlwfJzMwskylDpvWW+vbtS40aNZg8eTJgfCX8mjVrCqU3XVOurq5KENQW06dPV97alZCQYDFNSfsa8wWp7bn2DAYD27dvZ+bMmXTr1o3AwEB0Oh1+fn60adOGmTNn2hw0Yc6xY8d48MEHCQ4Oxt3dnbp16zJ58mSlvAXPNWskJiby73//my5duhAYGKhcC8OHD2fFihVW614STIu3Z2VlMWvWrBLl8c0333D16lXAOB3bWn9jiSlTppRI04SWpsghJMLLy0sAVj/NmzcXhw8ftplHXl6eeOSRR2zm8+ijj4q8vDyb+cTGxorGjRtbzcPHx0esWbOmyDp9++23Qq/XW80nNDRU3Lx5s1jtJIQQSUlJAhDx8fHFPrasGDnyuAAhmjYVoojmLHN+/fVX+xKmpwvRvr0QIES7dsb/O1K/jMnMzBTvvvuuyMzMVEVfCPXqrra2mvrSd+m7Wqjte0ZGhoiJiREZGRkO179161ah7yIihPD3N/5JcXbO/6+/vxCrV5deNy8vT8TFxRV5n1IeREZGKvcn77zzjtV0GRkZSrpWrVpZTff+++8LV1dXq/dATk5O4u233853jKndc3NzhbOzs837OUD0799fpKSk2KzX7NmzhU6ns5lPz549Ff2ePXsWqWtKbyIvL0/MmDHD5jG+vr5i8+bNFsu4bds2Jd2GDRtEv379Ch0/ZcoUm/U0Z82aNcpxkydPtusYS+e8ORcuXBDNmjWzWcfu3buLhIQEi8dPmTJFAKJevXrir7/+EvXr17eaz4wZM2yWZcuWLSIwMLBInywRHx8vunXrZvO4oKAgsW/fviLrcfDgQVG9enWr+Tz33HOFji/J+WUP9h47d+5cJW14eHiRvhfF4cOHlfx++ukn5fuGDRsKQAwdOrTQMcnJycLDw0MAYurUqTbzz8nJUby2lJcQpetrzPs9e669d955p0j/PD09xYoVK6zWKS8vT8yZM8dqv6TT6cTChQvznWvWWLdunfDz87NZnsGDB+frJ4vreb169fKdW8OHDxeA0Ov14sKFC4XSm7fpDz/8UGh/69atFV9iY2OLVRZLmF9TRVHa810IUeJ7k/j4eAGIpKSkUpfBHmSASQgRHh4uHn74YdGiRQsREBAg9Hq9CA4OFgMHDhQLFiwQ2dnZdue1bt06MXz4cFGrVi2h1+tFrVq1xPDhw8X69evtziM1NVV88sknokOHDsLPz094enqKe++9V7zwwgsWLyZrHD9+XDz++OOiYcOGwt3dXVStWlV0795d/O9//xM5OTl252NORQgwrVy5QTz3nBBXrzpee926dfYnvnhRiMBA4xPAQw8JYTA4Vr8MqQgPnGrVXW1tNfWl79J3tVDbdzUDTHfu3Mn3/4gIIZycjB8o/DHti4gonW5lCDBFR0cr6YYNG2YxzVtvvaWk6dq1q/juu+/E3r17xaFDh8Qvv/wiunTpouz/8ssvleNM7Z6TkyOcnZ1Fnz59xOzZs8XGjRtFdHS0iIqKEt9//32+4x966CGrZX3//feVdH5+fuL1118XW7ZsEYcPHxbbt28Xn332mejWrZvo1auXon/u3Dlx/PhxUatWLQGI4cOHi+PHj+f7nDt3Lp/OSy+9pOg0aNBAfP311+LAgQMiMjJSvPDCC8qDpF6vF3/88UehcpoHmFq1aqW07YoVK0R0dLRYv369+O2336zWsyAzZ85U8rP3uILnvDkpKSlKwAAQI0aMEKtXrxaHDh0SS5cuzfeA16VLF5Gbm1soD9PDcrVq1UTjxo1FlSpVxJtvvimioqJEVFSUmD9/vqhdu7aSz8aNGy2WZfv27UowwcXFRUydOlWsXLlSREdHiz179oj58+eLUaNGCZ1OV+jY1NRUJUim1+vFE088ISIiIsSOHTvErl27xKxZs0TVqlUFIPz9/S3e75vXo379+sLNzU28+uqrYufOnWL//v3iyy+/FDVr1lTq8Z///Cff8QXPr/vvv18cPXrU5vllD/YEmNLT00Xz5s2VIEh8fLxN3+3hueeeU/IzD2KY+gCdTmfxeWX8+PECjD/a2+rj165da/NcLm1fY97v2XPtvfHGG6JmzZpi+vTpYtGiRWLPnj0iOjparFq1Srz88svC29tbAMLd3V3ExMRYrNOOHTuUALqHh4d4/fXXlfNn3rx5onbt2kKv14u2bdvaDDBt3rxZuLi4CEDUr19ffPLJJyIqKkocPnxYrFmzRkyePFmp26hRowrV3V4KBpiOHj0qnJycBBgHbhTEVoApKSlJKXPTpk2LVQ5rFCfAVNrzXQgZYJLcpVSEAJOaDz3F1t62zfgzs5+fEMUIDpaZfhlRER44taqtpr70XfquFmprqxlgMg/wZGQYRyhZCy6ZB5n8/Y3pS6Nb0QNMEydOtDhiwcSBAweUh6c333zTYh55eXnKw0+VKlVEYmKi8r0QQhgMhiJ/2X777beVX8FPnz5daH90dLRSjiZNmojLly9bzcu0z7zdTQ9VRY0cOnbsmKITEhKi1MWcDRs2KGlCQ0ML7TcPMAHirbfesqlZFP3791fystQ2lrB1zpkHrCx5ajAYxKRJk5Q0X331VaE0psCMKdh34sSJQtqxsbHC3d3davAyPT1dCd54enqKyMhIq2W+dOlSoe+efvppAcbRZAcPHrRY9wsXLigalkZ/mddDp9OJHTt2FEoTFxenBMs8PT3FjRs3CqUxnV9jx44tk+vdVKYOHToUCoju379fLFiwQAlYODk5KcGW0mjn5OQoI7geeOCBfPtOnTqllOmLL74odOzq1auV/UuXLrWq8cADDwhAeHt7i/QCMxHKoq8x7/fsufbOnz9vc9DD5cuXRXBwsNXzR4h/RvDo9XqxZ8+eQvtv3LiRL6BrKcCUmpoqgoKCBCAGDBgg0tLSLGp9++23Sj5bt27NV3d7KRhgEkKIsWPHCkC4urqKM2fO5EtvK8C0Z88eZV/Bc6akFCfAVBbXmgwwSe5KKkKAqeDUic2bS3dTXRptu/jpJyEKdIAO1S8DKsIDp9pTZtRE+q49bTX1pe/FnyKXmmr9UzALW2nT0/MPo58/33ZgqeDnu+8s51vw/j8trXCa5OQ8ERt7VaSk5L8JLqMZ3jaxFWC6deuW2LVrlxg4cGC+kSqWHrRGjx4tANG+fXthsDFqODExUbi5uQlAzJ8/X9Gxl9zcXGXqzGeffVZo/4QJE5SH6aKWWDBhrm9vgOmpp55S2mTv3r1W0z322GNKugMHDuTbZx5gatKkicURQMXBFEgozsOMtbbPzMxUpuA0b97catmSkpKU0T/NmzcvtN88MGM+kqSgtsk3f3//Qnl8/fXXSh5z5syxq14mbt68qQSvCgY8Ctb9q6++UgJIBR/czevx9NNPW9VbvHixku7TTz8ttL+8AkxFffr37y+2bNmiHFeaKUPmUzEtzRLp2LGj0hcUJDs7WwQEBAgwjoizRGpqqrKEiqWRimXR15j3e2Vx7QkhxOeffy7AODqrYLn27t2r6D3//PNW84iIiLAZYPrvf/8rwDhSylIA05zQ0FABiEmTJgkhSj9FTggh/vzzTyW4V9AbWwEm83q98MILxSqHNeQUOcvIRb4llZrnnoMBA6CEa705hgcfhL/f7CeRSCSSuw9vb+uf0aPzp61e3XragQPzp50xo3jleOwxy/kWfOlsx46F0/j4ONO4cU1CQpzype3Ro3hlKC3vvfdevkWHAwMDue+++9iwYQOurq5MnjyZjRs3otPp8h2Xk5OjLG48ZswYnJycLGUPGN/m07JlS8D4hl5bGAwGrl69yqlTpzhx4gQnTpzgr7/+onbt2gAcPXq0UPqNGzcCxjf+tm3btngNUAxMixQ3b96czp07W033+OOPFzrGEuPHj8fFxaVUZUpJSVG2vby8SpVXdHS0suj11KlTrZbNx8dHeRNUTEwM165ds5jOycmJBx54wKpe+/btAePCxQUX2163bh1gfBvatGnTilMNNm3aRObfq/EX9caqHn9fcDk5OURHR1tN9/DDD1vdN3LkSOWNVfYsZO0ooqKi+Prrr0v8BjBzfvrpJwCqV69O//79C+03LfYdHR3NX3/9lW+fTqdj+PDhAKxfv97iwuoRERHKosyTJk3Kt688+pqSXHvJycmcP3+eP//8U+mbPD098+0zZ5vZm60feughq/kOHjyYqlWrWt0fEREBGPs3W2+HhH/O56L62eLQvHlzJkyYAMAvv/zCqVOn7DquLPsmiW1kgElS6QgJCVG2TTe+H38MJ044VrtEbNoEgwaBjVenlqt+JUbNuqvd7mrrq4n0XZto2XcPDw9l284XlWmGJk2a8PLLL+Pj41NoX0xMDOnp6QC89tprhd6+VvBjervv9evXgfztLoTg559/pnfv3nh7exMcHEzTpk1p2bKl8vnjjz8AuHXrVr5ynD9/Xnlg7VGM6Jy5vj1kZWURGxsLQKdOnWymbdu2rRKQO2HjZqlVq1bFKoMlqlSpomzb+9Yka3U3L2tRdTTfb62OgYGBhR6czbUDAgKUbfOHUYAjR44A0KFDB+Uh3l5M5xpAzZo1CwVQzf9v3v+Yzs2C6PV6m17pdDolsGnL77KmZ8+eCOPsGOWTnZ3N+fPnmTdvHr6+vixfvpzOnTtz+vTpYp/zJu7cucPq1asBmDBhgsW3FJp/bwpGmWMKGmVnZ7Ns2bJC+01vFAwKCqJv37759pVlX2PC3mvv4sWLPPPMM9SvXx9fX18aNmxISEiI0i+ZBz8L9k2mc8HNzc3m3zkXFxfatGljdb+pPps2bSqy7p999lmRdS8J77zzDi4uLuTl5fHuu+/adUxJ+qaypKzqXhmQASZJpcP8D/uoUTB8OOTmwuOPQ16e47SLTUoKTJ4MGzbAM884Xr+So2bd1W53tfXVRPquTSqb76mp1j/Ll+dPGx9vPe2GDeDs/M+t2aBB4GznnZqzMwwbZjnfgwfzpz14sHCa5GQDsbHXOHFC5Eu7c2exm6NUPPXUUxw/fpzjx49z5MgR1q1bxxNPPIFOpyMmJoZevXpZ/MU6Pj6+RHqmB0VTu2dmZjJ48GAefPBBoqKiyMjIsHl8wf3mD3U1a9a0uxzO9hr9N4mJicp2UFCQzbQ6nU4JrNy+fdtqOn9//2KVwRKBgYHK9o0bN+w6xlrdzctaVB1r1Khh8ThzLF3b5trm23kFbihNvhbHUxOlPTcLEhAQYDGoYo6pvWz57Qh0Oh3169dn+vTpREVFodPpuHLlCo899lixz3kTixcvJuvvH2pNI5UKYj6y6eeff8ZQIFrftWtX6tevD/wTTDJx69YtNm/eDBgDVQVHFpVVX2OOPdfehg0baN68OXPnzuXixYtFpi/YN5n6DD8/vyJHS1WrVs3i9zk5ORZHfBWFrbqXhCZNmvDggw8CsGTJEv78888ijylJ31SWlFXdKwO2eyeJpAJy4MABGv095czJCebNg+3bYd8++N//4OmnHaNdbKpUgUWLjE8M8+dDhw5QzGHWpdKv5KhZd7XbXW19NZG+S9/V0B45cmSxjinOaPui0iYkpOHu7g7AmDHw9w/1RWIwwNix9pXFUgzNYABPT1Fon6N/dK1evXq+X9fbtGnDoEGDGDp0KMOGDeP27ds88MADHDhwIN9DknlAYPbs2YSFhdmlZ5oqkZZmbPdZs2Yp01969uzJjBkzaNeuHTVq1MDDw0N5SOjRowe7du1CCGE1b1tTZwpi0i8J9ujYKqeJ0k6PA2jdujVbtmwB4PDhwzRu3LjIY+ype1F1tKd+JdUuTjksYTo39Xp9oWlvd+7cUaazFcQ0DbMkZShpe5QnLVq0YNCgQURERLBr1y6OHTtGaGhosfMxH5Fkz/FXrlwhMjIy30ik9PR0HnjgAT788EN27txJXFwcwcHBgDFgkZubCxSeHgdl19eYU9S1l5CQwAMPPEB6ejre3t7MnDmT+++/n0aNGuHr64terwdg+/btSj3L4xwwr/u4ceN46623inV8afq5grz99tv88ssv5OTk8M4771gciWZOSEiIMurp8OHDZVKG4lCWda/oyACTpNITHGycIjdjBrz2mnFEU506apfKCmFhxgWjXn/dGAlr1QpsrJsgkUgkEu0ydqxxrcE7d4zLeFvDyQn8/IwBqbuVwYMH8+STT/LVV19x+PBhFi5cyKOPPqrsN5/6lJOTU6KpjkIIvvvuOwC6d+/O9u3brf7qbD6CyBzzX8mvXr1a7DLYi/mIB2tTqUzk5uYqI1nMp4GVBz179lSmxaxbt47x48eXOC/zsl6/fp0mTZpYTWs+IqE86hgYGMiVK1dK5Knp3MzOzqZq1ar5RkElJCTYXO/GEgkJCeTl5dkMSphG2ZS338WladOmyho+f/31V7EDTGfOnOH3338vtu5PP/1UaKrb5MmT+fDDDzEYDISHhzNz5kzgnxFNjRs3pmPBBewom76muCxdulQZObRixQqL606B9X4J/ukz7ty5Q15ens0RNTdv3rT4vbu7O56enqSnp3Pnzh1Vp5Q3aNCAqVOnMn/+fFasWKFMW7aGj48PISEhHD16lFOnTnHmzBnuuecexxRWY2hnrJbkrmFgwVVQgSefhK5djcP8Z8ywfSNe1trF5tVXjXP7cnKMq78WcWNY5vqVFDXrrna7q62vJtJ3baJl3319fZVtd3f48UfjtrVBC6bvf/zRmP5u5p133lFGAbz33ntkZ2cr+1q0aKH8im+a3lIcfH19uX37thKsGTdunNUHsNTUVKsLyzZo0EB5kNtZjPmF5r7bM0LFzc1NGR20f/9+m2mPHDlCTk4OUP5rjA0YMIBatWoBxodiexZ0Nq+7OeZlLaqOBw4csHhcSbUL0q5dO8C4/oy1qWvWMF/oveC5aa++OdnZ2YUWlzcnNzdXedi21BYlGYVVVphGBgGFFuq3B/PRS//73/8IDw+3+TGNLlqxYkW+dXd8fX1p1qyZ4s2vv/4KwIULF5QFqS2NXoKy6WuKi2kKWEBAgNXgEuRf76sgLVq0AIzrtx0/ftxqury8PJvBGlOb7dmzp9jXQknqbos333wTvV6PEIJ33nmnyPSPPPIIYPwx4csvvyzTshRFWde9IiMDTJJKh6U/qs7OxllnDRsa36JTXn87bf1BtxsnJ1i4EJo1g6tXjT9Rm90kl7t+JUXNuqvd7mrrq4n0XZto2feC62YMHQqrVhlHKME/azKZ/vXzg4gIY7q7nerVq/PEE08AcPnyZX40Rd8wrq9jGqEQFRWVL+BgDxkZGfkefm09OC1YsEAJ2BTE2dmZQYMGAbBjxw5lcWh79E2YplFkFfFCkH79+gHGRYf37dtnNZ1pVJb5MeWFXq9XRoJkZmby6KOPFlrPqCCmul+5coXt27cr37dv316ZPvbjjz9azSclJYUlS5YAxjdMFWedpKLW2DIx9O8LLD09nW+//dbu/MEYtDYFU+bMmZPvPLNXvyDm535BVq5cqYxkseS36fzKtvPesyw5aLYgXFFvICuIafF9MAbOnnzySSZMmGDzM+PvV3GmpqayYsUKJS9Tu5uCSEeOHOGvv/7i119/VaaWWXvjYFn0NcXFdM5kZWUVWk/KRHp6usUFzU2Yj+BatGiR1XTr1q0jISHB6v5hw4YBxilf8+bNs1nugpT0fLdG3bp1lbdkrl69Ot/5ZYnx48cr67XNmzePHTt22K1lq23toazrXpGRASZJpcPa8OTmzeH0aeMip47WLjZVqhifGHx84N577R5yVZ7D7Ss6atZd7XZXW19NpO/aRMu+W3roGzbM+HvEokUwYgT06mX8d9Ei4/daCC6ZeOmll5QH5I8//jhf0OGNN95QRmdMmDCBs2fPWs0nLy+PX3/9lStXrgDGdq9WrZoS0Pjtt98senHw4EHefPNNm2WcOXMmzs7OCCGYMGGComEJc30TpgCJrfKDcUF00yiradOmkZSUVCjN5s2bWbBgAWBcr8bSlJ+y5rnnnqN3796A8U1TI0eOtDrlBowPzb/88gvt27fn2LFjyvdubm489thjgHEEx3vvvVfoWCEETz/9tLII99PFXIjT3iDL5MmTlTV63njjDZsPpgX9Dg4O5uGHHwaMAewnnnhCCRhY0o+Pj88XFLTE//73P3bv3l3o++vXrysBPk9PT6ZMmVIojen8smeh6LJk3bp1yqi+wMBAWrZsWazjd+3axfnz5wEYY+d84AEDBihvnTQPEJjafeLEico19MsvvygjmUJDQ22uH1bavqa4mMqSlpZmca2hvLw8HnvsMZt/v7p06aK8re6rr76yONXw5s2bvPDCCzbL8uSTTypTgd966y1lzTpr7NmzR/G9PIKar7/+uvI34dNPP7WZ1tXVlZ9//hlnZ2cMBgODBw9mecE3cRTg0qVLTJgwgWeffbZU5VQjoKsWcg0miV3MmzePefPmKTdyq1atwtvbm1GjRrFt2zaSkpKoXr06oaGhrF27FjAOJzYYDMowy+HDh7N7924SEhIICAigR48erFq1CjC+nlOn0ymLHw4ePJhDhw5x48YNfHx8GDBggNKhZmVlce7cOWW49P3338+JEyeIi4vDy8uLIUOGsHjxYjIyXGnTphGBgYHs2bMHMP6Sc/r0aS5duoSbmxujRo1i8eLFGAwGGjVqRHBwsNIJ9urVi0uXLnHu3DlcXV0ZO3YsN2/eJDw8nHr16tGoUSPll7bu3bsTHx/P6dOnAeMfrIiICNLT06lduzbNmzdXhtF26dKFpKQkYmJi8PzgAwY/9RQbN20iJSWFGjVq0K5dO9avXw9Ax44dyczMVIayenh4sHHjRhITEwkMDKRLly6sWbMG+GfIqunX0qFDh7J3715u3bqFv78/vXr1YuXKlQC0bNkSd3d3JdI/aNAgDh8+zPXr16lSpQphYWEsXboUMP4aaHq15rJlywgLCyMmJoYrV67g6enJ8OHDCQ8PB4xvdahevbpy09OnTx/Onj3LxYsX0ev1jB49mqVLl5Kbm0vDhg2pW7cuUVFRgHHB1Li4OM6ePYuzszPjx49nxYoVZGVlUbduXVxcXBSdbt26cevWLWWKwvjx41m7di1paWkEBwcTEhLCpk2bAOOri1NTU5XhxWPGjGHz5s0kJycTFBREhw4dWLduHWD8tTQnJ0e5wR0xYgQ7d+7kxo0bbN68me7duytrB7Rp0wZnZ2dlocAhQ4Zw4MAB4uPj8fX1pW/fvsqvZSEhIXh6eiq/cg0cOJCjR49y9epVvL29GTRokPLra9OmTQkICFD+8Pfv35/U1FTCw8Px8PBgxIgR/PbbbwghaNy4MTVq1GDXrl0A9O7dmwsXLnD+/Hl0Oh1jxoxh2bJl5OTk0KBBA+rXr09kZCQA9913H9evXyc2NhYnJycmTJjAqlWryMjIoE6dOjRt2lRpw0uXLpGamsrJkycB49SR9evXk5qaSq1atWjdurVygxEaGkp6erryOtzS9hE3btwgPDy8WH1EixYt8Pb2LrKPALj33nut9hGmB6Li9BHLly8nOzu7TPoIU93Hjh3Lxo0b7eojRo4cSVRUVKn6CNOvo+fOnVO8KaqP8PX1VaYVDBgwoNR9xI0bN9i/f3+x+ogmTZqwdetWoHR9hKenJ1FRUQQGBpKamopOp1PWvvDy8kIIoYxu8ff3JyUlhdzcXFxdXfH29lbSenp64uTkpEzL8PPzIy0tjZycHFxdXalSpYoyysC0eHRaWhq5ubnk5uaSkZFBdnY2Li4u+Pr6kpZ2m4EDYdQoD1xcXEhNTQXAxcWHlJRMsrOzcXZ2xt/fn9u3byOEwN3dHZ1Op7xy3cfHh6ysLLKysnByciIgIEBJa5ryYSpTlSpVyMnJITMzU0mbmJiIwWBAr9fj7u5OcnIyAN7e3uTl5Sm/0AYEBJCUlEReXh56vR4PDw8l+OHl5YXBYFDS+vv7K3UBMBgMyq/nBdvbz88PDw8PJk2axIIFCzh37hzffvst48aNw9PTk/bt2zNz5kxmz57N+fPnadOmDZMmTaJPnz40atSIW7ducenSJY4cOUJERARXr15l165d1KhRA4PBQGJiImPGjOG7777jjz/+oEuXLjzzzDM0adKEGzdusGXLFn744Qe8vLwICgpSHioLtnedOnV45ZVX+Oijjzh9+jQhISE8+uijDBo0CJ1OR2JiIidPnmTt2rUIIZS/K2lpaWRmZtK2bVsiIyM5ePAgb7/9NmFhYQQEBJCSkoKHhweNGzcmLy+PWrVqMX36dObOncvx48dp06YNzz//PKGhody8eZNNmzYxf/58xYdPPvkEg8GgnLM6nS7fQsBZWVlkZGTka29r52zB89vX15f09HRycnJwcXFh8eLFDBw4kOjoaNasWUOjRo0YPXo09913H40bN8ZgMBAXF8fhw4dZs2aN0jdmZ2eTnZ2tnLOvvfYay5cv5/z583zwwQecOHGCsWPHEhQUxLVr15g/f74S7OncuTOTJk0iISEh3zlrPhLMdG55e3sr15rpb475qDXT96a0BoOBuXPnMnbsWNLT0+nbty/jxo1j2LBhNGrUiISEBM6cOUNkZCRr165VHvRNfcTrr7/O7t27iYmJ4fvvv2fPnj089thjNGvWDC8vL5KSkrh06RKbN29m8+bNNG/enEceeSRfH2G6Bw8MDMTLy4v+/fvz5JNPMmDAAKpWrUpUVBRz5sxRpnm++uqruLi4KNexqY/o2rUrkZGR/PHHH3zwwQcMHjxYOQ+qVatGYGCgxT7Czc0NNzc35bo39REm0tLS2LNnD0IIdDoder2eO3fucO3aNaKiovjhhx+UtLNmzcLJyYmEhAS7+oiUlJR8I8f69u1LQkKCxT4iNTVV6ZOrVKlC//79Wb58Odu3b+fs2bP4+fmRm5tLXl4e3t7edO/enZ07dzJv3jyl/x47dixZWVlK3+Tr65uvT+7atavFvqZXr140bNiQ1NRUzp49y6FDh5TzYdeuXfj7+yv1Ng8IJyUlcfv27Xz9rHl79+/fHzc3N7Kyspg6dSp79+5l6NChODk5ERMTw4IFCzhy5AidOnVS7n0yMzOVc9jUJ3/44YcMGzaM7Oxs+vXrx1NPPcWgQYPQ6/Xs27ePL774gvj4eFq2bMnx48cRQpCXl5fv75pOp+Obb75h/PjxZGVlMWTIEIYOHcrw4cNp0aIFycnJ3Lhxg5iYGNasWcPx48f5+OOP6dq1q9K/m/6umdaG8/DI/3fN1N7mo7VMdSn4d61atWo8+uijzJs3L99bPFNTU0lNTUWv1ytpnZyc6Ny5M59//jn/+te/SEtLY8yYMXTo0IGRI0fSvn179Ho9ycnJXL9+nU2bNrF+/XqysrLw9fVV1q8ynbPm5396enq+czY5OZm8vDx0Oh1eXl5Kn1Ka+wh3d3cyMzNZu3atMpLOnmcNhyMkkmKQlJQkABEfH69aGXJzc4tM8/33Qvj7CxEV5XjtUmQuxMWL6unbIDMzU7z77rsiMzNTFX0h1Ku72tpq6kvfpe9qobbvGRkZIiYmRmRkZDhc32AwOFxTCCHy8vJEXFycyMvLc7h2ZGSkAAQg3nnnnSLTX7p0Sej1egGIpk2bFirznDlzhJubm5KntY9erxexsbFCiH/a/c6dO6JNmzZWjwkICBA7duwQPXv2FIDo2bOn1XJ++OGHwtXV1WYZTMeb+37lyhUREBBgM72JvLw8MX36dJsavr6+YtOmTRbLuG3bNiVdZGRkkW1fHDIyMsRzzz2neGXr4+TkJCZPnizi4uIK5XP+/HnRtGlTm8d369ZNJCQkWCzHlClTBCDq1atXaJ95u//www9KfufPn7eY18aNG4W/v3+R9bFEQkKCCAsLK/JYQPTu3dtmPQ4ePCgCAwOtHv/ss89aLIMQxTu/7MGe+pg+Op1OfPLJJ0KI4vV16enpwsfHRwDi3nvvLVb5VqxYoeh//PHHhbS///77fGV0cXER169ftyvv0vQ15v2ePdfe999/L5ydna1qjB8/XmzdutVmnnl5eWLOnDlCp9NZzMPV1VXMnz9fPPjgg0r/ao1t27aJGjVq2OX7jz/+WKjd7aFevXp2nZfXr18Xnp6e+TR/+OGHQunM9aOiokRISIhd5a9bt6749ddfC+Vn+jtg7Zq3pl1SSnpvEh8fLwCRlJRU6jLYg5wiJ6l0mEZ62GL/fkhMhGnTIDPTsdolIjERBg+G++4DG8PIy02/EqBm3dVud7X11UT6rk207LvpF12JderUqaNM/Tl58mShKQ7PP/88Z8+e5a233qJz584EBgbi6uqKl5cXTZo0YfTo0Xz99dfExcUpbxEytbuvry979uzhgw8+UEb7ent706xZM2bOnMnRo0fp0aOHXeV87bXXiImJ4fnnnyckJAQfHx/c3d1p2LAhffv25fPPP+e3337Lpw/GKVUHDhzg0Ucf5Z577rH5amtnZ2fmzZvHzp07mTRpEnXr1sXNzQ0fHx/atGnD66+/TmxsLAMGDLC/gcsId3d3Pv/8c2JjY/n444/p168fdevWxcPDA3d3d2rVqsWAAQN44403OH/+PIsWLVIWCDenfv36HD16lLlz59KzZ0+qVq2KTqcjKCiIsLAwFi1axM6dO0v0xrTiXm/3338/586d48MPP6Rr165KWYKDg+nUqROvv/661QWUAwIC2LBhA9u2bePhhx+mcePGeHl54erqSkBAAB07dmTGjBmsX7+eLVu22CxHhw4dOHz4MM8++yyNGjXC3d2dqlWrEhYWxvr16/niiy+sHhscHMy+ffuYOHFikedXaXFxcSEgIIDQ0FBeeeUVYmJiePnll4Hitf2qVauUkVOjR48uVhnCwsKUlwOY1h4y1x49enS+Nujbty9BQUF25V2avqa4PPzww+zatYsRI0ZQrVo1dDodNWvWJCwsjMWLF/Pbb7/ZfLOgiXHjxnHgwAEmTZpErVq10Ov1BAcHM27cOHbv3s1jjz2mtLWthalNI5Dnzp1LWFgYNWvWVEa31qlThwEDBjBr1ixOnjzJQw89VKq6F0VQUJBd02PN9Xv27MnRo0eJiIjg8ccfp0WLFop/fn5+hISE8MgjjxAREcHZs2eZOHFiqcqoqb/tDgljSe4aKsIIJksR5ILcuSNEzZpCgBBvvOFY7RKRmChE48bGAvfpI0ROjmP1i6AijGhQq+5qa6upL32XvquF2r6rOYLp1q1bDtcUQt0RTCbUqrva2mrqS98rj++2RmIVF+m7NrXt9b1Ro0YCEJMnTy5T/cp0vVVEbTmCSSIpJ5o2bVpkGl9fmDvXuP3JJ2DjbZxlrl0i/Pxg5Urw8oLt2+HVVx2rXwlQs+5qt7va+moifdcmWvbdtOadFlGz7mq3u9r6aiJ91yZa9b2ie37w4EFlfbnOnTuXad5q11367hhkgElS6bB3CPSoUca37OTmwuOPQxFvyS1T7RLRogUsXGjc/s9/4O9h8w7Tr+CoWXe1211tfTWRvmsTLftuzxSHuxU16652u6utrybSd22iVd/V9tz0Jj5LJCQk8PjjjwPGtziOHz++TLXVrruWfXckMsAkqXRYeq2mNebOBR8f45pMX33lWO0SMWbMP6OXHn0UzF7X6xD9CoyadVe73dXWVxPpuzbRsu/mb1TTGmrWXe12V1tfTaTv2kSrvqvt+cSJE+nXrx///e9/2bFjB3/88QeRkZH8+9//pmXLlhw9ehSAN998k8DAwDLVVrvuWvbdkbiqXQCJpDwJDoaPP4YZM0CNtzSWiH//Gw4fhs2bYdIkOHoUnGUsWCKRSCQSiUQikZQcIQSRkZFERkZaTTN9+nRef/11B5ZKcjchA0ySSkf//v2Llf6JJ6BrV2jd2vHaJcLFBcLDYexY41Q5s+CSQ/QrKGrWXe12V1tfTaTv2kTLvvv4+KiqryZq1l3tdldbX02k79pEq76r7fnnn3/O77//zs6dO7l27Rq3bt3C1dWVGjVq0L17d6ZNm0bXrl3LRVvtumvZd0cih0VIKh0nT54sVnpn57IJLpVEu8QEBMC2bdCmjTr6FRA16652u6utrybSd22iZd8zMzNV1VcTNeuudrurra8m0nf7WLhwIUIILly4UH4FciBa9V3tc65Lly7Mnj2bgwcPcuXKFTIzM0lNTeXMmTMsXLiw3IJLoH7dtey7I5EBJkml4/LlyyU+9vRp48CgxETHa5eK/fth3Tr19CsAatZd7XZXW19NpO/aRMu+Z2dnq6qvJmrWXe12V1tfTaTv2kSrvkvPtamvdt0diZwiJ6l0lPQ1j0LAhAlw5Aj4+sJ33zlOu1Ts3Qu9eoFeT7UPP3S8fgVBy68WVVtfTaTv2kTLvjtreM09Neuudrurra8m0ndtolXfpefa1Fe77o5EOzWV3DWMGDGiRMc5OcGXXxq3FyyAqCjHaZeKjh2Ni0ilptJv3jxISnJ8GSoAqrR9BdCuCPpqIn3XJlr23d/fX1V9NVGz7mq3u9r6aiJ91yZa9V16rk19tevuSGSASVLp+O2330p8bPfu8OSTxu1p0yAjw3HaJcbVFRYvhjp14NQpeOghMBgcXw6VUaXtK4B2RdBXE+m7NtGy77dv31ZVX03UrLva7a62vppI37WJVn2XnmtTX+26OxIZYJJUOoQQpTr+44+hZk2IjYV//9ux2iWmenVYsYI8nQ5Wr4ZZs9Qph4qo1vYqa1cEfTWRvmuTiuK7GuWQvmtPuyLoq4n0XZto1XfpuTb1y0Jb7fazFxlgklQ6GjduXKrjfX1h7lzj9qefwrFjjtMuFR06cOnVV43b77wD69apVxYVULPtVfW9AuirifRdm6jtu2mtBIMKo0Xd3d0drllRULPuare72vpqIn3XJlr1XXquTf2y0M7LywMq/npOFbt0EokFatSoUeo8Ro2CESMgNxf+7/8cq10adNOmwfTpxhXLlyxRtSyORs22V9t3tfXVRPquTdT2XafT4eLiQlpamsP1dTqdwzUrCmrWXe12V1tfTaTv2kSrvkvPtalfFtrp6em4uLio3o5FIQNMkkrHrl27yiSfuXON0+Xmz3e8dknZtWsXzJljXKX8hx9ULYujUbPtK4TvGkX6rk3U9t3JyYkqVaqQnJzs8CHpKSkpDtWrSKhZd7XbXW19NZG+axOt+i4916Z+abWFECQnJ1OlShWcnJzKqFTlgwwwSTRLcDC88gpU8CBwYfR6eOQRMA2PFML4kUgkEkmZ4evrS05ODlevXq006x5IJBKJRCK5uxBCcPXqVXJycvD19VW7OEXiqnYBJJLi0rt37zLPMzsbli2DiRPBVlC4PLSLQyH99HR4/HFo1coYLbuLUbPtK5zvGkL6rk0qgu+enp7Url2bK1eukJGRgY+PD56enri4uJTrr4d6vZ7MzMxyy98aBoOB3NxcMjMzVVvfQa26q62tpr70XfoufdeOttq+a/V6K4m2EIK8vDzS09NJTk4mJyeH2rVr4+npWY6lLBtkgElS6bhw4UKZrs+RmwtdusDhw+DiAuPHO067uBTSj4iAX3+F336Ddu2gf3/VylbeqNn2Fc53DSF9l76rqV2lShXq1atHUlISd+7cISEhodz1dLq92wABAABJREFUs7KycHNzK3edggghSEpKIjU1VbXh92rVXW1tNfWl79J36bt2tNX2XavXW2m0XVxcqFKlCr6+vpUiuAQywCSxk3nz5jFv3jxl9fpVq1bh7e3NqFGj2LZtG0lJSVSvXp3Q0FDWrl0LQLt27TAYDPzxxx8ADB8+nN27d5OQkEBAQAA9evRg1apVALRq1QqdTkd0dDQAgwcP5tChQ9y4cQMfHx8GDBjAsmXLAEhOTqZ69ers378fgPvvv58TJ04QFxeHl5cXQ4YMYfHixQDce++9BAYGsmfPHgD69evH6dOnuXTpEm5ubowaNYrlyxdTv35zDh9uydNP55GcvApv72x69erFpUuXOHfuHK6urowdO5bff/+d8+fPU69ePRo1asT27dsB6N69O/Hx8Zw+fRqAiRMnEhERQXp6OrVr16Z58+Zs3rwZgC5dupCUlERMTAwAY8eOZePGjaSkpFCjRg3atWvH+vXrAejYsSOZmZkcP34cML494M6dOyQmJhIYGEiXIUO40asXjaKiyBs7lgvLlnHg5k0Ahg4dyt69e7l16xb+/v706tWLlStXAtCyZUvc3d05ePAgAIMGDeLw4cNcv36dKlWqEBYWxtKlSwFo3rw5Hh4eACxbtoywsDBiYmK4cuUKnp6eDB8+nPDwcACaNGlC9erV2b17NwB9+vTh7NmzXLx4Eb1ez+jRo1m6dCm5ubk0bNiQunXrEhUVBUCPHj2Ii4vj7NmzODs7M378eFasWEFWVhZ169YlNjaW8+fPA9CtWzdu3brFqVOnABg/fjxr164lLS2N4OBgQkJC2LRpEwCdOnUiNTWVP//8E4AxY8awefNmkpOTCQoKokOHDqz7+4187du3Jycnh2N/v1pwxIgR7Ny5k+PHj5OcnEz37t2JiIgAoE2bNjg7O3P48GEAhgwZwoEDB4iPj8fX15e+ffuyYsUKAEJCQvD09OTAgQMADBw4kKNHj3L16lW8vb0ZNGgQS/5etL1p06YEBATw+++/A9C/f3+io6M5f/48Hh4ejBgxgt9++w0hBI0bN6ZGjRrKejW9e/fmwoULnD9/Hp1Ox5gxY1i2bBk5OTk0aNCA+vXrExkZCcB9993H9evXiY2NxcnJiQkTJrBq1SoyMjKoU6cOTZs2Vdrw0qVLpKamcvLkSQDGjRvH+vXrSU1NpVatWrRu3ZoNGzYAEBoaSnp6OidOnAAodR+xe/duzp8/X6w+okWLFnh7e5e6j7h27RqdO3dm8eLFGAwGGjVqRHBwMDt37gSw2EcsX76c7OzsMukjTHUvTh8xcuRIoqKi/ukjunRhzZo1ALRt2xaAI0eO2OwjTG9OO3funOJNUX2Er68ve/fuBWDAgAGl7iMuXryIk5NTsfqIJk2asHXr1lL3EQaDgYSEhHx9hKkMbdu2JScnR8m3X79+HDp0iDt37uDn50f79u3Ztm0bAM2aNcPZ2VnJt3fv3hw7doyEhASqVKlCly5dFM+bNGmCu7s7x44dIz4+njFjxnDy5Eni4+Px8vKiR48eyjXWsGFDfH19FR+7devGuXPnuHbtGu7u7vTr149169YhhKB+/foEBgZy6NAhpa5xcXFcuXIFnU7H/fffz6ZNm8jJyaFmzZrs3buXevXq4eTkRIcOHbh16xYXLlzAycmJwYMHs3XrVjIzM6lZsyYNGzZUrpu2bduSlJTEuXPnAGMft3PnTtLS0qhevTpNmzZVrptWrVqRmZmpXAsDBgxg7969pKSkcOfOHUaOHKn0Uy1atMBgMPDXX38B0LdvX6Kjo5X27tChg+L5vffei6urq9LevXr14sSJE9y6dQtvb2+6deumeN64cWM8PT05evSocn2uXbsWPz8/PD096dWrl3KNNWjQAH9/f6Wv79q1KxcuXODq1avo9XoGDBjA+vXrMRgM1K1bl6CgIOVva2hoKNeuXePy5cu4uroSFhbG5s2byc7OJjg4mDp16rBv3z7A+PDRtGlT5e/ckCFD2LZtGxkZGdSoUYNGjRrla++UlBTOnDkDQFhYGLt27SItLY1q1arRvHlzduzYARj/3mdlZSnt3b9/fw4cOEBSUhL+/v60aNGC9evXU69ePVq0aAGg3J/07t2bP/74g8TERHx9fQkNDWXLli3KOevm5qb0PT179iQmJoabN2/i5eXFfffdx8aNGwG45557qFKlSr5z9uzZs1y/fh0PDw8yMjIw0aBBAwICApS+vnPnzly+fJm4uDilvTdu3Ehubi516tShZs2ayt/Wjh07cuPGDS5duoSzszODBg1S2rtWrVrUr19f+dvarl07EhMT2b9/P9WrV2fQoEFERUWRnp5OUFAQjRs3Vvqp1q1bk56eTmxsLGD8m7Jnzx5SU1MJDAwkJCRE6SNatGhBbm6u3X3EsWPHlIdGe/sIMPaHpekj1q5dy4ULF+jevTs1atSwq4+oXbs2wcHByt/W0vYRP//8M1WrVi1WH1G1alVatWpV6j4iPj6ecePGFauPiI2N5caNG6XuI86cOYNery92H9G+fXtu375dqj4iNTWVixcvMnHiROVvdlF9RJs2bZT2bt68ean6iIiICPz8/IrdR/Tt21e5dyxNH5Gdnc0999xTrD7C1N6l7SOWLFlC9erVi91HODk5Kf1LSZ81HI6QSIpBUlKSAER8fLxqZVi6dGmZ55mZKUSzZsbFjB55xLHaxcGifkaGEB07GgvfurUQaWllrpuZmSneffddkZmZWeZ524uabV8hfXcA0nfpu1pI3x2P9F36rhbSd8cjfdemttq+a/V6U1s7Pj5eACIpKckhek5CyJUrJfaTnJyMr68v8fHxVKtWTe3ilCm7d8N99xm3t2+HSrX8yeXL0L493LwJkybBokW2F5MqJllZWXz88ce8+uqrqg5tlTgW6bs2kb5rE+m7NpG+axPpuzaRvmuTmzdvUr16dZKSkvDx8Sl3PfkWOUmlwzQNpqzp3h2efNK4PW0amI3YLndte7GqX6cOLF1qXETql1/gyy8dWzAHoGbbV1jfNYD0XZtI37WJ9F2bSN+1iVZ9l55rU1/tujsSGWCSVDpycnLKLe+PP4ZateDMGZg1y7Ha9mBTv2dP+M9/oFo1aN3acYVyEGq2fYX2/S5H+q5NpO/aRPquTaTv2kSrvkvPtamvdt0diQwwSSodDRo0KLe8fX1h7lzj9LgpUxyrbQ9F6j/7LPz5J/Tq5ZDyOBI1277C+34XI33XJtJ3bSJ91ybSd22iVd+l59rUV7vujkQGmCSVjvr165dr/iNHwrZt0Lix47WLokh9JyfjCCYTsbGQmVmuZXIUarZ9hff9Lkb6rk2k79pE+q5NpO/aRKu+S8+1qa923R2JDDBJKh2mV2WWJ+brY9+65VhtWxRLf+1a48LfM2bAXbCWv5ptX6l8v8uQvmsT6bs2kb5rE+m7NtGq79JzbeqrXXdHIgNMEokVMjPh6aehYUP4/HMYPRo++KAPo0cbX9JW4QcGubtDWhp8/z18843apZFIJBKJRCKRSCQSyV2MDDBJKh333XefQ3T0eoiMhJQUeOEFWLUK/voriFWr4KGHjIuBr1njkKIoFKvu/frBRx8Zt599Fn7/vXwK5SAc5XtF064I+moifdcm0ndtIn3XJtJ3baJV36Xn2tRXu+6ORAaYJJWO69evO0Rn7Vr4669//m8w5P/3zh0YPhxWr3ZIcYAS1P2ll2DsWMjJMQ7Bunq1fArmABzle0XTrgj6aiJ91ybSd20ifdcm0ndtolXfpefa1Fe77o5EBpgklY7Y2Nhy18jMhKlTbacxLWs0darjpssVu+5OTsYpci1awPXrxmBTdnb5FK6ccYTvFVG7IuirifRdm0jftYn0XZtI37WJVn2XnmtTX+26OxIZYJJUOpzMV+AuJ5YuhcTEotfGFsKYbtmyci8SUMK6e3sb5/f5+hqnyc2dW+blcgSO8L0ialcEfTWRvmsT6bs2kb5rE+m7NtGq79JzbeqrXXdH4iTEXfB6KYnDSE5OxtfXl/j4eKpVq6Z2ccqN0aONMRnTdDhbODvDiBGwfHl5l6qUrFsHmzfDZ5+BTlesQ7Oysvj444959dVXcXNzK6cCSioa0ndtIn3XJtJ3bSJ91ybSd20ifdcmN2/epHr16iQlJeHj41PuenIEk6TSsWrVqnLXSEiwL7gExnS3b5dveUyUqu6DB8MXXxQ7uFRRcITvFVG7IuirifRdm0jftYn0XZtI37WJVn2XnmtTX+26OxIZYJJUOjIyMspdo2pV48gke3B2hoCA8i2PiTKre04OvPMOxMeXTX4OwBG+V0TtiqCvJtJ3bSJ91ybSd20ifdcmWvVdeq5NfbXr7khkgElS6ahTp065a4wYUbwRTCNHlmtxFMqs7k89Be+/D+PGGYNNlQBH+F4RtSuCvppI37WJ9F2bSN+1ifRdm2jVd+m5NvXVrrsjkQEmSaWjadOm5a4xdiz4+xtfwlYUvr4wZky5Fwkow7r/61/Gxb937ICXXy6bPMsZR/heEbUrgr6aSN+1ifRdm0jftYn0XZto1XfpuTb11a67I5EBJkmlY8uWLeWu4e4OP/5o3C4qyFStmuMGAZVZ3Zs1g59+Mm5//jn8/HPZ5FuOOML3iqhdEfTVRPquTaTv2kT6rk2k79pEq75Lz7Wpr3bdHYkMMEkkVhg61PgmOT8/4/9NazKZ/vXxgSpV4MwZGDUKsrPVKGUpGDkS3njDuD1tGvzxh6rFkUgkEolEIpFIJBJJ5cVV7QJIKgfz5s1j3rx55OXlAcaV8L29vRk1ahTbtm0jKSmJ6tWrExoaytq1awFo164dBoOBP/4OXAwfPpzdu3eTkJBAQEAAPXr0UFbUb9WqFTqdjujoaAAGDx7MoUOHuHHjBj4+PgwYMIBly5YBEBQUxLlz59i/fz8A999/PydOnCAuLg4vLy+GDBnC4sWLAbj33nsJDAxkz549APTr14/Tp09z6dIl3NzcGDVqFIsXL8ZgMNCoUSOCg4PZuXMnAL169SIo6BJz5lzg0KH6XL3aiZiY61SpksPAgRk88ogvP/30B7Nm9WHrVh1DhtxmypRNODvDxIkTiYiIID09ndq1a9O8eXM2b94MQJcuXUhKSiImJgaAsWPHsnHjRlJSUqhRowbt2rVj/fr1AHTs2JHMzEyOHz8OQIcOHdi4cSOJiYkEBgbSpUsX1qxZA0Dbtm0BOHLkCABDhw5l79693Lp1C39/f3r16sXKlSsBaNmyJe7u7hxq1owerVtT6+hRMgYOZP177+FWqxZhYWEsXboUgObNm+Ph4QHAsmXLCAsLIyYmhitXruDp6cnw4cMJDw8HoEmTJlSvXp3du3cD0KdPH86ePcvFixfR6/WMHj2apUuXkpubS8OGDalbty5RUVEA9OjRg7i4OM6ePYuzszPjx49nxYoVZGVlUbduXZo3b67odOvWjVu3bnHq1CkAxo8fz9q1a0lLSyM4OJiQkBA2bdoEQKdOnUhNTeXPP/8EYMyYMWzevJnk5GSCgoLo0KED69atA6B9+/bk5ORw7NgxAEaMGMHOnTvJyMhg8+bNdO/enYiICADatGmDs7Mzhw8fBmDIkCEcOHCA+Ph4fH196du3LytWrAAgJCQET09PDhw4AMDAgQM5evQoV69exdvbm0GDBrFkyRLAOIQ2ICCA33//HYD+/ftTpUoVwsPD8fDwYMSIEfz2228IIWjcuDE1atRg165dAPTu3ZsLFy5w/vx5dDodY8aMYdmyZeTk5NCgQQPq169PZGQkAPfddx/Xr18nNjYWJycnJkyYwKpVq8jIyKBOnTo0bdpUacNLly6RmprKyZMnARg3bhzr168nNTWVWrVq0bp1azZs2ABAaGgo6enpnDhxAqDUfURGRgbh4eHF6iNatGiBt7d3qfuI3NxcAJt9xKVLlzh37hyurq6MHTuW5cuXk52dTb169WjUqBHbt28HoHv37sTHx3P69GnAvj7CVPfi9BEjR44kKiqqVH2E4e8F6M6dO6d4M2jQIA4fPsz169epUqVKoT7C19eXvXv3AjBgwIBS9xEZGRns37+/WH1EkyZN2Lp1K1C6PiI0NJR169YVq4+4ffs2VatWLZM+IiMjgzt37hSrjzh58iSXL18uVR9hWh9i2bJlODs729VHmH6R7dq1K7dv3y51H+Hm5kZKSkq530dY6iO8vLwIDw8v8/sIe/uIe+65h+jo6GL1ESW5jyjYR7Rv317x3bRdnPuIgwcPAqXrI7p27eqQ+whLfYSpny3v+whrfUSdOnWUupfnfUTBPmL58uWK17Vr1y63+whbfQRAeHh4ud9HWOojMjIySE5OLvf7CEt9RJMmTRTPy/s+omAfkZSUBEBSUhLbtm0Dyuc+Aiz3ER4eHoSHhzvkPsJSH9GkSRMOHDhQ7vcRlvoIU1/jiPsIyN9HOBwhkRSDpKQkAYj4+HjVynD48OEKpb1pkxA6nRAgxNNPC2EwOFa/1Ny+LUTDhkJ4ewuxY4fFJJmZmeLdd98VmZmZZa9vJxXNdy3oS9+l72ohfXc80nfpu1pI3x2P9F2b2mr7rtXrTW3t+Ph4AYikpCSH6MkpcpJKh+nXj4qiPWDAP+s1nTgBWVmO1S81/v4QEQEHDkCPHmWffxlR0XzXkr6aSN+1ifRdm0jftYn0XZto1XfpuTb11a67I5FT5CSSMmDiROOaTH37GhcIr3SEhOT/f24uuMruQSKRSCQSiUQikUgk9iFHMEkqHaZ52xVNe/Dg/MGl2FjH6pcZO3bAvfcah2NVICqq71rQVxPpuzaRvmsT6bs2kb5rE636Lj3Xpr7adXckMsAkqXSYFq6sqNpCwMsvGwcF/b0OokP1S4UQ8NFHcO6c8S1z16/DokW4TpjAQz/8gOuECbBoEWRmlm85LFDRfb+b9dVE+q5NpO/aRPquTaTv2kSrvkvPtamvdt0diQwwSSodqampFVrbYICzZyE7G4YPh79ftOAw/VLh5AQ//wz16sGZM1CnDjz0EM6rV9Pg4kWcV6+Ghx6CWrXg7zdKOIqK7vvdrK8m0ndtIn3XJtJ3bSJ91yZa9V16rk19tevuSGSASVLpqFWrVoXWdnGBX36BXr0gJQXCwoyxGkfpl5rAQHjuOeP2369pd/r7teWmf7lzxxg9W726/MvzNxXd97tZX02k79pE+q5NpO/aRPquTbTqu/Rcm/pq192RyACTpNLRunXrCq/t7g6rVkGbNhAfD/ffD9euOU6/VGRmwgcf2E4jhPHfqVMdNl2uMvh+t+qrifRdm0jftYn0XZtI37WJVn2XnmtTX+26OxIZYJJUOjZs2FAptH19YcMGaNjQuKTRwIHGgT+O0i8xS5dCYmLR6YQwplu2rPzLROXx/W7UVxPpuzaRvmsT6bs2kb5rE636Lj3Xpr7adXckMsAkkZQjNWrA5s0QFATHjsG2bWqXyA5WrQJnO7sGZ2dYubJciyORSCQSiUQikUgkkoqPq9oFkEiKS2hoaKXSbtQINm6EU6dg9GjH6xebhATjSuX2YDDA7dvlW56/qWy+3036aiJ91ybSd20ifdcm0ndtolXfpefa1Fe77o5EBpgklY709PRKp92mjfFjIjUVvLyML21zhH6xqFrVODLJniCTszMEBJR/maicvt8t+moifdcm0ndtIn3XJtJ3baJV36Xn2tRXu+6ORE6Rk1Q6Tpw4Uam14+Kgc2d480119ItkxIjijWAaObJci2OisvtemfXVRPquTaTv2kT6rk2k79pEq75Lz7Wpr3bdHYkMMEkkDiYyEv78Ez78EL74Qu3SWGDsWPD3t294lY8PjBlT/mWSSCQSiUQikUgkEkmFRgaYJJWOUaNGVWrtyZNh1izj9vPPw6+/Ola/SNzd4ccfjdtFBZmcnSE2tvzLROX3vTLrq4n0XZtI37WJ9F2bSN+1iVZ9l55rU1/tujsSGWCSVDq2qfgqtrLSfu01ePZZ4/aUKcZFwB2pXyRDhxrfJufnB4D4+61ypn/x9YX69eHOHejZEw4eLPci3Q2+V1Z9NZG+axPpuzaRvmsT6bs20arv0nNt6qtdd0ciA0ySSkdSUlKl13ZygjlzYOJEyM01vl1u/37H6dvFsGFw9SosWoRh2DDO16+PYdgwWLQIrl+Hw4ehUydITITBg40rl5cjd4PvlVVfTaTv2kT6rk2k79pE+q5NtOq79Fyb+mrX3ZHIAJOk0lG9evW7QtvZGRYuhPvvh/R0mD4dhHCcvl24u8PkyeT+9hs/TZ1K7m+/Gef4ubsb12nasgX694cFC8Dbu1yLcrf4Xhn11UT6rk2k79pE+q5NpO/aRKu+S8+1qa923R2Jq9oFkEiKS2ho6F2jrdfDsmXw9NPGdZmKWvJIzbpbpEoV2LQpf8EzMsDDo8yl7ibfK5u+mkjftYn0XZtI37WJ9F2baNV36bk29dWuuyORI5gklY61a9feVdre3saRTMHB/3xnbSSTmnW3inlw6dw5aNoUfv65zGXuNt8rk76aSN+1ifRdm0jftYn0XZto1XfpuTb11a67I5EjmCR2MW/ePObNm0deXh4Aq1atwtvbm1GjRrFt2zaSkpKoXr06oaGhygXUrl07DAYDf/zxBwDDhw9n9+7dJCQkEBAQQI8ePVi1ahUArVq1QqfTER0dDcDgwYM5dOgQN27cwMfHhwEDBrBs2TIAkpOTOXfuHPv/XrTo/vvv58SJE8TFxeHl5cWQIUNYvHgxAPfeey+BgYHs2bMHgH79+nH69GkuXbqEm5sbo0aNYvHixRgMBho1akRwcDA7d+4EoFevXly6dIlz587h6urK2LFjuXbtGuHh4dSrV49GjRqxfft2ALp37058fDynT58GYOLEiURERJCenk7t2rVp3rw5mzdvBqBLly4kJSURExMDwNixY9m4cSMpKSnUqFGDCxc68emnqbz8chT33deOzMxMjh8/DkBeXh4bN24kMTGRwMBAunTpwpo1awBo27YtAEeOHAFg6NCh7N27l1u3buHv70+vXr1YuXIlAC1btsTd3Z2Dfy/OPWjQIA4fPsz169epUqUKYWFhLF26FIDmzZvj8feIpGXLlhEWFkZMTAxXrlzB09OT4cOHEx4ebmyzLVuoeekS4qGHOBgVRb1Zszh79iwXL15Er9czevRoli5dSm5uLg0bNqRu3bpERUUB0KNHD+Li4jh79izOzs6MHz+eFStWkJWVRd26dcnKylJ0unXrxq1btzh16hQA48ePZ+3ataSlpREcHExISAibNm0CoFOnTqSmpvLnn38CMGbMGDZv3kxycjJBQUF06NCBdevWAdC+fXtycnI4duwYACNGjGDnzp3ExcWxefNmunfvTkREBABt2rTB2dmZw4cPAzBkyBAOHDhAfHw8vr6+9O3blxUrVgAQEhKCp6cnBw4cAGDgwIEcPXqUq1ev4u3tzaBBg1iyZAkATZs2JSAggN9//x2A/v37c/v2bcLDw/Hw8GDEiBH89ttvCCFo3LgxNWrUYNeuXQD07t2bCxcucP78eXQ6HWPGjGHZsmXk5OTQoEED6tevT2RkJAD33Xcf169fJzY2FicnJyZMmMCqVavIyMigTp06NG3aVGnDS5cukZqaysmTJwEYN24c69evJzU1lVq1atG6dWs2bNgAGH+hSU9P58SJEwCl7iPi4uIIDw8vVh/RokULvL29S91HXLt2DaBYfcTy5cvJzs4ukz7CVPeCfUS7du1Yv349AB07dszXR4wcOZKoqKhS9REGgwGAc+fOKd4U1Uf4+vqyd+9eAAYMGGC1j2jSpAnVq1dn9+7dAPTp08diHxEXF8f+/fuL1Uc0adKErVu3AqXrIwwGA+vWrStWH3H79m2qVq1aJn1EXFwcd+7cKVYfcfLkSS5fvlyqPqJOnTqAsZ93dna2q4/YsmULAF27duX27dul7iNu3bpFSkpKud9HWOojEhISCA8PL/f7CGt9REZGBtHR0WVyH1GcPqJ9+/aK76bt8riPsNVHAMXuI0pyH2GpjzD1s+V9H2Gtj0hNTVXqXp73EQX7iOXLlyte165du9zuI2z1ETdu3CA8PLzc7yMs9RFxcXEkJyeX+32EpT4iMzPzn/vmcr6PKNhHmNYBSkpKUhadLo/7CLDcR9y6dYvw8HCH3EdY6iMyMzM5cOBAud9HWOojTH2NI+4jIH8f4XCERFIMkpKSBCDi4+NVK8PJkyfvWu07d4QIDBQChBg4UIjsbMfqWyMzM1O8++67IjMz03bCvDwhnnnGWAEQYvbsMivD3ex7RdW32/dyRPrueKTv0ne1kL47Hum79F0ttOq7mtpq+67V601t7fj4eAGIpKQkh+jJKXKSSofp1/W7UdvXF1avNi5htGEDPPIImEuqWXe7cHaGL76A114z/v+ll+Ddd4tevdwO7mbfK7q+mkjftYn0XZtI37WJ9F2baNV36bk29dWuuyORASZJpcM0DPZu1e7Sxbjwt4uLcSmjmTP/ic+oWXe7cXKCDz80fgDeey9/JUrI3e57RdZXE+m7NpG+axPpuzaRvmsTrfouPdemvtp1dyQywCSRVEAGDYIffjBuz5kDn36qbnlKxGuvwZdfGrejoiA9XdXiSCQSiUQikUgkEomk/JCLfEsqHcOHD9eE9oMPwq1b8OKL8Oqr0KmTunUvEc88AzVrQq9e4OVVqqy04ntF1FcT6bs2kb5rE+m7NpG+axOt+i4916a+2nV3JHIEk6TSYXprgBa0X3gBXnnFuJRRz57q1r3EjBkDgYH//D8iAjIzi52NlnyvaPpqIn3XJtJ3bSJ91ybSd22iVd+l59rUV7vujkSOYJJUOhISEjSl/dFHxmWN1NIvU777Dh5/HPr3h5UrizWqSWu+VyR9NZG+axPpuzaRvmsT6bs20arv0nNt6qtdd0ciRzBJKh0BAQGa0jYFlwC8vavyyCNw9KjDi1E2NGxoDCpt2QL33w9JSXYfqjXfK5K+mkjftYn0XZtI37WJ9F2baNV36bk29dWuuyORASZJpaNHjx6a1AaIjOzNDz9AWBicO6dqUUpGnz7G4JKvL+zZA337GheasgMt+662vppI37WJ9F2bSN+1ifRdm2jVd+m5NvXVrrsjkQEmSaVj1apVmtQGaN48gpYt4fp14wCgGzdULU7J6NLF+Fa5atUgOtq4uNS1a0UepmXf1dZXE+m7NpG+axPpuzaRvmsTrfouPdemvtp1dyQywPQ32dnZLFiwgLCwMGrWrImbmxve3t7ce++9PPLII+zbt8+ufDZu3MioUaOoXbs2bm5u1K5dm1GjRrFx40a7y5Kens7s2bMJDQ0lICAAb29vmjVrxsyZM7l06ZLd+fz55588+eST3HPPPXh4eFCtWjV69OjBN998Q25urt35SCoOXl45bNoE9evDmTMwcCAkJ6tdqhLQpg3s3Am1akFMDNx3H6SkqF0qiUQikUgkEolEIpGUELnIN3D58mUGDx7M8ePH832fnZ3N6dOnOX36ND/88AMvvPAC//nPf3AyXxTnb4QQPPnkk3z77bf5vo+Li2PlypWsXLmSadOm8fXXX1s83sTZs2cZPHgwp06dyvf9yZMnOXnyJN999x2//vorgwYNslmnBQsWMGPGDLKyspTvMjMz2bVrF7t27WLhwoWsXbuWqlWr2synItKqVStNapv0a9aEzZuhWzc4cgRGjoT168HNTdWiFZ+mTWHXLujXD6ZMgSpVbCbXuu9aRfquTaTv2kT6rk2k79pEq75Lz7Wpr3bdHYnmRzDl5ubmCy61atWKhQsXsnfvXjZv3szbb7+N199vupozZw6fffaZxXzefPNNJbjUtm1bwsPDOXDgAOHh4bRt2xaAb7/9lrfeestqWVJTUxkyZIgSXHr88cfZtm0bv//+O7NmzcLb25ukpCTGjh3LsWPHrOazadMmpk2bRlZWFkFBQXz55Zfs37+fDRs2MGrUKAD27dvHqFGjMBgMxWwx9dHpdJrUNtdv3Bg2bABvb9i+3fhitkpJw4bGKNmbbxaZVPquTaTv2kT6rk2k79pE+q5NtOq79Fyb+mrX3ZFoPsAUERGhBJe6dOnC4cOHmTJlCp07d6Z///6899577NixQzkpPvroo0LTy86cOcOnn34KQIcOHdizZw8TJkygY8eOTJgwgd27d9OhQwcAPvnkE86ePWuxLJ999hknT54E4NNPP+Xbb7+lT58+dOnShddff53Nmzfj6upKeno6zz//vMU8cnNzefrppzEYDPj4+LBnzx6eeeYZQkNDCQsLY/ny5UyfPh2AnTt38vPPP5euAVUgOjpak9oF9du3h1WrICgInnhCvTKVGl/ff16Vl5oKQ4fCgQOFkknftYn0XZtI37WJ9F2bSN+1iVZ9l55rU1/tujsSzQeY9uzZo2y/9tpruLi4FErTvn17hgwZAkBiYqISBDIxZ84cJej03//+Fw8Pj3z7PT09+e9//wsYA0Cff/55IY2cnBy++OILAJo1a8a//vWvQmm6dOnCo48+CkBkZKTFE3XlypWcOXNGqU+jRo0KpZk9ezb+/v7KtqTy0rev8W1y3bqpXZIy4p13YO1aY8V27lS7NBKJRCKRSCQSiUQisRPNB5iys7OV7YYNG1pNZx6oMV/XSAhBREQEAE2bNqVz584Wj+/cuTP33nsvYFxFXgiRb39UVBR37twBYMqUKTg7W7Zm6tSpyvaKFSsK7Tdfod48rTmenp6MGzcOgBMnThAbG2sxXUVl8ODBmtS2pu/p+c/20aPw/fcOLFBZ89570Lu3cSRTWBiYLY4vfdcm0ndtIn3XJtJ3bSJ91yZa9V16rk19tevuSDQfYGrSpImyfe7cOavpTNPanJycaNy4sfL9+fPniYuLA6Bnz542tUz7r1y5woULF/Lt27VrV6F0lujQoYOyJtTu3bsL7Tflc++991KjRo0iy2Itn4rMoUOHNKldlP6FC9CjBzz2GCxZ4rgylSne3rBuHQweDBkZMGwY/B1Ilb5rE+m7NpG+axPpuzaRvmsTrfouPdemvtp1dySaDzBNnDgRHx8fwLg+Ul5eXqE0R44cYd26dQBMmDBBSQ/w119/KdtNmza1qWW+3/y44uTj6uqqjKYqmEdqaipXrlwpdVkqOjdu3NCkdlH69erBgw+CEDB5Mmzd6sCClSUeHsag0tixkJMD48bBokXSd40ifdcm0ndtIn3XJtJ3baJV36Xn2tRXu+6ORPMBpmrVqrFw4UI8PDzYs2cPHTt25KeffmLfvn1s3bqV9957j549e5KdnU2bNm34v//7v3zHX758WdmuXbu2Ta06depYPM78/15eXvj5+dmVz82bN/NN17ty5Yoy9a40ZanomAf4tKRdlL6TE3zxhTEek5MDI0ZApQ2W6/UQHg4PPwx5efDSSwS4uqpWnIrs+92OvN61ifRdm0jftYn0XZto1XfpuTb11a67I1Hvia0CMXLkSA4dOsT//d//8f333zNlypR8+4OCgnjvvfeYNm2aMj3NREpKirLt7e1tU8f82NTUVIv5FJWHpXzc3NzKtCzmZGVl5QtiJScnW/zekfTs2VOT2vbqz58PN2/qiIx0ZuBAQWRkDo0bC5vHFIVJ0+F1nzcPl6pVMYwdS7fmzaXvDkY1382Q17v0XUvaaupL36XvaiF9l75Lbcegtu9avd7U1na0rgwwYXyD26+//sqaNWsKLb4NxiFt4eHhNGnSpNACXZmZmcq2Xq+3qWMKBAFkZGRYzKeoPGzlU1ZlMeejjz7ivffeK/T9vHnzcHd3L7KsEnXo3FnPyZNTuHatFt27p/Poowvw8bEeSLSXOXPmlEHpiom3N2zYYPwA/rdvk+jvbxyyJXEIqvguUR3puzaRvmsT6bs2kb5rE+m7tjCPETgCzQeY0tLSGDRoEDt37sTFxYWXX36Zhx9+mIYNG5KZ+f/snXlcVFX/x98zgoCiuOCSgBuFiPuGqaioaYooqLi1mC1a1mOL7U+b9eRTv6yszCezbLNCRRQ3XHIhUUnccg01NxQXQnQQWQS5vz8O4IbKwMy9wDnv14sXw8y993O+85lzvPP1nO/JYsuWLbz33nts3LiRQYMGMW3aNJ577rnC869Nsly7I11RXJs9dHFxue61guvc6Rq3u46t2nItr7/+OpMmTSr8Oy0tDS8vL5555hnq1Klzx7bag4iICIYPHy6dtrX6Tz8NvXrl0bBhdV5//V9Uq1Zy3ezsbKZNm8YLL7xwXXJSTyIiIhjh4YFjcDBXnniCK//3f7olmcqT77akrPiu+ru+KN+V78p3efSV78p35bs82kb7Lmt/M1r7n3/+4cMPP9RNT/oE0zvvvMOGDRsAmD179nXL4ypXrkzfvn3p1asX/fr1Y/369UyaNIlevXrRunVrAKpd8639dkvNQCSzCrhxCVvBde50jdtdx1ZtuRYnJ6ciB6BbPa8HrVu3llLbWn1PT/j9d6hdG5u12WjfK2/eDBkZOHzxBQ4ZGTBzJlSqpIt2efHdHhjtu4zaZUFf+W4MRusr343BaH3luzEYra98l0u7AKN8Nzp2WX3XW1fqIt+apvH9998D4OPjc1PtpQIcHBz4z3/+A0BeXl7hOXB9Me2CHdxuxbXFtK8tsn3tdS5dusSFCxeKdZ06depc94GxVVvKOsWpU1URtUui36ABFHxENA3mzxcFwMsjrq6u8NRTMHs2mM3w7bdi2zwdAipvvlckVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1ROoE09mzZ0lNTQWgXbt2tz22Q4cOhY8TEhIKH/v5+RX5fFFc+3rz5s2ve62418nNzeXw4cNFXsPV1bUwWVSatpR1tmzZIqV2afVffx1GjoRx40SyqbxRGPtjj4kd5hwcxO/hw8HOa4vLs+/lHdXf5UT5LifKdzlRvsuJrL4rz+XUNzp2PZE6weRwzbbnubm5tz0255pZEtee16RJExo0aADA77//fttrFCzF8/DwoHHjxte9FhAQUPj4dtfZtm1b4fK2bt263fR6wXUOHDjAmTNnbnmdazWKuo6i4tGtm1hN9uOP8OqrRremlIwYAYsWielZixfDoEGQkWF0qxQKhUKhUCgUCoVCWqROMNWqVYvq1asDEBcXd9sk07UJmSZNmhQ+NplMhISEAGJW0B9//FHk+X/88UfhrKGQkBBMNxQnDgwMxM3NDYAff/yxyN3sAH744YfCx0OGDLnp9dDQ0CKPvZaMjAzmz58PiJlTPj4+RR5XVrn//vul1C6t/qBBYlUZwNSp8PHHNmqUTtwUe3AwREdD1arix9FRP22dMVrfSFR/lxPlu5wo3+VE+S4nsvquPJdT3+jY9UTqBJPZbGbgwIEAnDp1iilTphR53Pnz53n1mikfwcHB173+/PPPF85qmjhxIpmZmde9npmZycSJEwEx++n555+/SaNy5co8++yzAPz11198XMS3/7i4OGbPng1Az5496dSp003HDBkyBG9vbwA++OCDwuV01/Lyyy9z/vz5wsfljb1790qpbQv9sWPho4/E45dfhp9+Kn2b9KLI2Hv3hs2bYd48uyaYyrvv5RnV3+VE+S4nync5Ub7Liay+K8/l1Dc6dj2ROsEE8Pbbb1OlShUAJk+ezODBg4mMjGTnzp3ExcUxbdo02rZty/79+wHo06cP/fr1u+4aPj4+vPTSS4BYwtatWzfmzZvHtm3bmDdvHt26dWPbtm2ASOjcc889Rbbl5ZdfLpxN9Morr/Dkk0+yfv16/vjjDz744AP69etHbm4uLi4ufPbZZ0Vew9HRkS+++AKz2UxaWhrdunXjyy+/JD4+nlWrVhEWFsb//vc/QCyne/jhh0v3BhpAUlKSlNq20n/5ZXjxRfH4scdg+fJSX1IXbhl769bXVzJ//304fVofbZ0wWt9IVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1xOHOh1RsfH19Wbx4MaNHjyYlJYWlS5eydOnSIo/t3bs3ERERRb42ZcoUkpOT+e6779i5cyejRo266ZjHH3+c999//5ZtqVatGsuXLycoKIhDhw4xa9YsZs2add0x1atX55dffqFt27a3vE5QUBAzZ87kX//6F2fPni2cPXUt/v7+LFq0iEo6bPFua6pWrSqlti31P/oI/vkH5syBU6dsckm7U6zY338f3n4bfvgB1q6FRo3007YjRusbiervcqJ8lxPlu5wo3+VEVt+V53LqGx27npi0WxX7kYxz584xe/ZsVqxYwb59+7hw4QIODg7Ur1+fTp068cADDzB48OCbaifdSHR0NLNmzWLr1q2kpKTg7u5Op06dePLJJxkwYECx2nLp0iVmzJhBREQEf//9N5cvX8bLy4ugoCCee+45GhXzS/PevXv54osvWLt2LadOnaJq1ao0b96cBx98kCeeeOK6YuXFJS0tDTc3N5KTk6lTp47V59uCvLw8zGZjJt8ZqW1r/ZwciIuDHj3ufGx2djYffvghr732Gk4Fs4V0plixHz0KffqI315esGYN2KDGWEXy3RrKje8VUNtIfeW78l35Lo++8l35rnyXR9to32Xtb0Zr//PPP9StWxeLxVJYf9qeSL9EroDatWvzyiuvsH79epKTk7l8+TIZGRkcOXKEefPmFVmYuyiCgoKIiooiKSmJ7OxskpKSiIqKKnZyCUSG85VXXmHr1q2cP3+eS5cukZCQwKefflrs5BJAy5YtmTVrFocPHyYzM5OUlBRiY2N56qmnSpRcKivMmzdPSm1b6zs6Xp9cOncOEhNtdnmbU6zYmzSB2Fjw9YUTJ0SAu3fro21HjNY3EtXf5UT5LifKdzlRvsuJrL4rz+XUNzp2PVEJJoVCwYkTEBAAffuKpXPlGg8P2LAB2raFs2chMBDi441ulUKhUCgUCoVCoVBUaFSCSVHuaNasmZTa9tQ3mSAjAw4ehKAguHjRLjKlwqrY69SB9euhSxc4fx4GDACLRR9tO2C0vpGo/i4nync5Ub7LifJdTmT1XXkup77RseuJSjApyh3u7u5SattT39MTVq2C2rVh2zYYOhQuX7aLVImxOvYaNWD1ajEta8YMcHPTT9vGGK1vJKq/y4nyXU6U73KifJcTWX1Xnsupb3TseqISTIpyx6ZNm6TUtre+ry9ER0PVqqI29pgxYlbTnDkwapQD338/hlGjHJgzB7Ky7NaMW1Ki2F1dRebs2l0ds7P10bYhRusbiervcqJ8lxPlu5wo3+VEVt+V53LqGx27nqgEk0KhKMTfHxYtEgXA582DWrVEomnJEjPHjzdhyRIzY8ZAgwawdKnRrS0m1xbnP3kSWraEn34yrj0KhUKhUCgUCoVCUQFRCSZFueO+++6TUlsv/b594dlnxeOCyT55eabrfl+4ACEhsGSJ3ZtTiE1i/+Yb+PtveOQR+OorfbVLgdH6RqL6u5wo3+VE+S4nync5kdV35bmc+kbHricqwaQodxw8eFBKbb30s7Lgu+9uf4ymid9jx+q3XM4msb/zDkycKB4//TRMnaqfdikwWt9IVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1RCWYFOWOxMREKbX10o+IEBuv3QlNE8ctWGD3JgE2it1shs8/h3//W/z9yivw9ttXM2b21C4FRusbiervcqJ8lxPlu5wo3+VEVt+V53LqGx27ntg8wfT333/z9ttv07dvX1q1asXdd9/N33//fd0xe/fuJTo6mt9//93W8goJcHJyklJbL/2oKJGHKQ5ms6jZpAc2i91kgilT4L//FX//5z8wadJtk0wy+F5WUf1dTpTvcqJ8lxPlu5zI6rvyXE59o2PXEwdbXSgvL49XX32Vzz77jLy8PLT8L2smk4nLN+x3fuLECYKDg3FwcODo0aN4eHjYqhkKOzFjxgxmzJjBlStXAIiKisLV1ZWhQ4eydu1aLBYLdevWxd/fn2XLlgHQvn178vLy+PPPPwEICQlh48aNnDt3jlq1atGjRw+ioqIAaN26NY6Ojmzfvh2AgQMHsm3bNs6ePUv16tXp168fC/KnyrRo0YIjR46wZcsWAO6//3727t1LUlISVatWJTg4mHnz5gHQrFkz3N3dCyv333fffRw8eJDExEScnJwYOnQo8+bNIy8vD29vbzw8PNiwYQMAgYGBJCYmcuTIERwcHBg+fDiaphEeHk6jRo3w9vZm3bp1AAQEBJCcnFw4/XH06NEsXryYjIwMPD098fPzY/Xq1QB06dIFi8XC/v37ARg+fDgrV67k4sWL1K9fn/bt2xMdHQ1Ap06dyMrKYs+ePQAMGTKElStXcv78edzd3enSpQtL86ttt2vXDoCdO3cCMGjQIOLi4khJSaFmzZoEBgayKD8b1KpVK5ydndm6dSsAQUFB7NixgzNnznDwYF/y8oq3lWZeHqSmQnh4OAA+Pj7UrVuXjRs3AtC7d28OHz7M8ePHqVy5MsOGDSMiIoLc3FyaNm1Kw4YNiYmJAaBHjx4kJSVx+PBhzGYzI0eOZOHChWRnZ9OwYUO6d+9eqNOtWzdSUlI4cOAAACNHjmTZsmVcunQJDw8PWrZsyapVqwDo3Lkz6enp7Nu3D4CwsDBWr15NWuPGtJ84kWbTp2OJiOC3li1p3b07OTk57N69G4DQ0FA2bNhAdnY2q1evJiAggMWLFwPQtm1bzGYzO3bsACA4OJj4+HiSk5Nxc3OjT58+LFy4EICWLVtSpUoV4uPjARgwYAC7du3i1KlTuLq6EhQUxPz58wHw9fWlVq1abN68GYC+fftSt25dwsPDcXFxITQ0lLlz56JpGvfccw/169cnNjYWgF69enHs2DGOHj2Ko6MjYWFhLFiwgJycHJo0aULjxo1Zv349AN27d+fMmTMcOnQIk8nEqFGjiIqKIjMzEy8vL3x9fQvfw8TERNLT00lISABgxIgRREdHk56eToMGDWjTpg0rVqwAwN/fn4yMDPbu3QtQ6jEiOzub8PBwq8cIV1dXm4wRgFVjRGRkJJcvX7bJGFEQu7VjRExMTKnGiLy8PACOHDlS6M21Y0S1atXo378/ERERAPj5+eHm5kZcXBwA/fr1Y//+/Zw8eZIqVaoQEhJSojFiy5YtVo0RPj4+rFmzxiZjxPLly0lLS6NevXp07NiR5cuXA9ChQ4cix4jU1FRq165tszHiwoULVo0RCQkJnDhxolRjhJeXFwALFizAbDYXa4z47bffAOjatSupqak2GSMuXryoy33EjWOEu7s74eHhdr+PuN0YsX37dl3uI64dIzp06FDoe8Hj0t5HWDtGDB06VJf7iKLGiIJxtkT3ETYYI1q0aFEYuz3vI24cIyIjIwu99vT0tNt9xO3GCEdHR8LDw+1+H3GrMSItLU2X+4gbx4jOnTsXem7v+4gbxwiLxQKAxWJh7dq1gH3uI6DoMaJmzZqEh4frdh9R1BgRHx+vy33EjWNEwVij133EtWOE7mg24oknntDMZrNmMpk0T09Pbfjw4ZrJZNLMZrO2b9++m4739vbWzGaz9tlnn9mqCQodsFgsGqAlJycb1oa5c+dKqa2X/tChmmY2a5qY0nP7H7NZHK8Hdot97lxNS0oyRruYGKWflZWlTZ48WcvKyjJEX9NUfzcC5bvy3SiU7/qjfFe+G4WsvhupbbTvsvY3o7WTk5M1QLNYLLro2WSJXExMDLNnzwbg3//+N8eOHSvMot+KgtkgBVlwhaK4FPzvumzaeumHhoqZScUhLw+GDLFrc67RslPsI0dCgwZX/165UlQuz8qCOXNg2DAC330Xhg0Tf+tV1fwajP7cGYnq73KifJcT5bucKN/lRFbfledy6hsdu57YJME0c+ZMQEx9e//996lUqdIdz/H39wconEqmUBQXb29vKbX10h8+HGrWFKWK7oTJBD172r1JgE7v/a+/QlAQ3Hsv3HUXjBkDUVHU++svUZxqzBiRjMqfKqwXRn/ujET1dzlRvsuJ8l1OlO9yIqvvynM59Y2OXU9skmCKi4vDZDLx+OOPF/scT09PAM6cOWOLJigkwsiaXUbXC9ND39kZfvxRPL5Vkqng+dBQyC/bYXd0ee/vugsqV4Zdu+DCBfFcwf84FPy+cAFCQmDJEvu3Jx+jP3dGovq7nCjf5UT5LifKdzmR1XfluZz6RseuJzZJMCUnJwPQpEmTYp/j4CDqi+fk5NiiCQqJKCieKZu2nvqDBokJOzVqiL/NZu263zVqQESE+CkgNRXs2Z11ib1LF5Fguh0Fu82NHavbcjmjP3dGovq7nCjf5UT5LifKdzmR1XfluZz6RseuJzZJMLm4uACQkZFR7HMSExMBqFmzpi2aoFAobMzgwXDqlCg7NHhwHo0bH2Xw4DzmzBHPh4VBwWrY7GyRlOrXD1JSjG13qYiIgIsX73ycpsH585C/24hCoVAoFAqFQqFQyI5NEkwFM5cKtiwsDgXbS/r5+dmiCQqJCAwMlFLbCH1nZ3joIZg7N5exY39i7txcHnpIPH8t+/bB7t0QEwOdOkH+Tqc2RZfYo6LAXMxh0WyG/K1Y7Y3RnzsjUf1dTpTvcqJ8lxPlu5zI6rvyXE59o2PXE5skmPr164emacyaNatYFdK3b9/OnDlzMJlM9O/f3xZNUEhEwew32bTLgv6taN8e/vgDmjaFY8fESrOoKNtq6BL7uXPWbaGXmmrf9uRTVn3XA9Xf5UT5LifKdzlRvsuJrL4rz+XUNzp2PbFJgulf//oXLi4u7Nmzh3Hjxt22rlJkZCT9+/fn8uXLVK9enfHjx9uiCQqJOHLkiJTaZUH/drRoAfHx0Ls3XLoEQ4bA++9fLVlUWnSJvXZt62Yw1apl3/bkU5Z9tzeqv8uJ8l1OlO9yonyXE1l9V57LqW907HpikwSTh4cHX3zxBZqm8cMPP9C0aVOefvrpwtdnz57NhAkTuOeeexgxYgTnzp3DZDIxa9Ys3NzcbNEEhUQUFIiXTbss6N+J2rVh5UqYOFH8/dZb8Oqrtrm2LrGHhlo3g2nIELs2p4Cy7rs9Uf1dTpTvcqJ8lxPlu5zI6rvyXE59o2PXE5Om2Wp+AXz33Xc8++yzZGRkYCpif/MCKScnJ2bOnMkjjzxiK2mFTqSlpeHm5kZycjJ16tQxujkKncjOzubDDz/ktddew8nJqVjnfPMNvPkmxMaCj4+dG2grsrKgQQO4cKF4U69mzYJx4+zeLKMoie+K8o/yXU6U73KifJcT5bucKN/l5J9//qFu3bpYLBaqV69udz2bzGAq4LHHHiMhIYFJkybh7e2NpmnX/Xh4eDBhwgT++usvlVwq5zz6qANz5ui2S/t1REZG6i9aBrTLgr41jBsHhw9fn1xKTi759XSJ3dkZfvxRPC4iSX7T8+PHw6OPijWBdqQ8+W5rVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1xKYJJgBPT08+/vhjDh48yIULFzh48CB//fUXycnJnDhxghkzZtC4cWNbyyp0JjrazJgxYrLH0qX6al++fFlfwTKiXRb0rcXV9erj336Dxo1h9uySXUu32AcNEhXKa9QQfxfUZCr4XaOG2D3uvffEcz/8AP7+Yis9O1HefLclqr/LifJdTpTvcqJ8lxNZfVeey6lvdOx6YvViwPbt29OjR4/CH3d391seW716dV2mYSn0R9PELI4LFyAkRHwfHzxYH+1GjRrpI1TGtMuCfmmIiIDMTHjiCdi9Gz75BKxZjqxr7IMHw6lTsGABLFqE5ehR3Jo0ETWXwsLETKfQUOjeHUaPhv37xWymjRtvPfOpFJRn30uL6u9yonyXE+W7nCjf5URW35XncuobHbueWJ1g+vPPP9m1axfTp08HoFmzZtclnDw9PW3eSEXZRdPE9+mxY8X3cWdn+2t6e3vbX6QMapcF/dLw9dfQsKEo/P3FFyInM29e8Tdi0z12Z2d46CF46CGyzp7FrV69m48JDIRdu2DCBPjgA7skl6B8+15aVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1xOolclWrVr2urtKBAwf45ptvePjhh2nUqBFNmzZl7NixfP/99xw+fNgebVaUMTQNzp8Xkz30YN26dfoIlTHtsqBfGkwmUfR74UKoWhXWrBEry/bvL975Zdb3unUhMvL6YlNffw179+qjX8Eps75LoG8kync5Ub7LifJdTmT1XXkup77RseuJ1Qkmi8XC1q1b+fTTTwkNDaV27drXJZyOHTvGnDlzeOKJJ/Dx8cHDw4PRo0fz1Vdfsc+ONUoUxmI2i7I0CsWdGDIE4uJEPabDh+Hee+HIEaNbZUNiYsSMJn9/+O674u1Gp1AoFAqFQqFQKBTlHKuXyJnNZjp06ECHDh14/vnnAUhISGDDhg3ExsYSGxtLYmJi4fGnT59m/vz5zJ8/H4BatWoREBBQuKSuffv2mOy0rEShH3l5kJqqj1ZAQIA+QmVMuyzo24pWrWDrVlHOqGlTaNLkzueUG9/9/KBvX1i9Gh5/XCSc/ve/6yue21O/glFufK+A+kaifJcT5bucKN/lRFbfledy6hsdu57YZBc5X19fxo8fz5w5czh27BjHjx9nzpw5jB8/nubNmwMUznA6d+4cS5Ys4aWXXsLf35+aNWvaogkKgzGbi19Lp7Qkl2av+3KsXRb0bYm7u9hZ7quvrpYuSksThcCLotz4XrcurFgBU6aIjjFnDnTqBHv26KNfwSg3vldAfSNRvsuJ8l1OlO9yIqvvynM59Y2OXU9skmC6ES8vLx588EFmzpzJvn37SE5OZuHChbzwwgt06NABs9lcmHC6ePGiPZqg0Jm8PLH0SQ8OHjyoj1AZ0y4L+rbG0RGcnMTjK1fggQfExmwnT958bLny3WyGf/8b1q+HBg0gIUEsmfvhB330KxDlyvcKpm8kync5Ub7LifJdTmT1XXkup77RseuJ1UvkSkLt2rXp0KEDly5dIj09nX/++YcTJ06gqdok5YYZM2YwY8YMrly5UsSrGlWrXqZ27c1cvNiRZcuWAdC+fXvy8vL4888/AQgJCWHjxo2cO3eOWrVq0aNHD6KiogBo3bo1jo6ObN++HYCBAweybds2zp49S/Xq1enXrx8L8quIp6WlceTIEbZs2QLA/fffz969e0lKSqJq1aoEBwczb948QOxy6O7uzqZNmwC47777OHjwIImJiTg5OTF06FDmzZtHXl4e3t7eeHh4sGHDBgACAwNJTEzkyJEjODg4MHz4cE6fPk14eDiNGjXC29u7sGBbQEAAycnJhYPH6NGjWbx4MRkZGXh6euLn58fq1asB6NKlCxaLhf351a2HDx/OypUruXjxIvXr16d9+/ZER0cD0KlTJ7KystiTP/vlypUrrFy5kvPnz+Pu7k6XLl1YunQpAO3atQNg586dAAwaNIi4uDhSUlKoWbMmgYGBLMovlNWqVSucnZ3ZunUrAEFBQezYsYMzZ85QrVo1+vfvT0REBAB+fn64uLgAsGDBAvr378/+/fs5efIkVapUISQkhPDwcAB8fHyoW7cuGzduBKB3794cPnyY48ePU7lyZYYNG0ZERAS5ubk0bdqUhg0bEhMTA4CXVy82bqyNxeJIy5aZrFjhwunTC8nOzqZhw4ZkZ2cX6nTr1o2UlBQOHDgAwMiRI1m2bBmXLl3Cw8ODli1bsmrVKgA6d+5Menp6YQ24sLAwVq9eTVpaGvXq1aNjx44sX74cgA4dOpCTk8Pu3bsBCA0NZcOGDSQlJbF69WoCAgJYvHgxAG3btsVsNrNjxw4AgoODiY+PJzk5GTc3N/r06cPCpCSc3n6bvj/9RLXNm4nftInDTk4MGDCAXbt2cerUKVxdXQkKCipcRuzr60utWrXYvHkzAH379iU1NZXw8HBcXFwIDQ1l7ty5aJrGPffcQ/369YmNjQWgV69eHDt2jKNHj+Lo6EhYWBgLFiwgJyeHJk2a0LhxY9avXw9A9+7dOXPmDIcOHcJkMjFq1CiioqLIzMzEy8sLX1/fwvcwMTGR9PR0EhISABgxYgTR0dGkp6fToEED2rRpw4oVKwDw9/cnIyODvflFzocOHcratWuxWCzUrVsXf39/q8aIpKQkwsPDrRojWrRogaura6nHiNOnTwNYNUZERkZy+fJlm4wRBbFbM0YMGTKEmJiYUo0ReXl5ABw5cqTQmzuNEW5ubsTFxQHQr1+/Uo8RSUlJbNmy5boxouDzcPjwYcxmMyNHjmThwqtjhI+PD2vWrCn1GJGXl8fy5cutGiNSU1OpXbu29WPEwoUAtGzZkipVqhAfH09SUhIXLlywaoxISEjgxIkTpRojvLy8ADHOm83mYo0Rv/32GwBdu3YlNTW11GNESkoKFy9etPt9RFFjxLlz5wgPD7f7fcStxojMzEy2b99u9/uIG8eIDh06FPpe8Nge9xG3GyMAm9xHlGSMKBhn7X0fcasxIj09vTD24o4RgNX3ETeOEZGRkYVee3p62u0+4nZjxNmzZwkPD7f7fURRY0RSUhJpaWl2v48oaozIysoq9Nze9xE3jhEWiwUQNZXXrl0L2Oc+AooeI1JSUggPD9flPqKoMSIrK4v4+Hi730cUNUYUjDV63EfA9WOE3pg0O2V5Dhw4UFiXacOGDZw4caLwtQJJNzc3unbtWjgoK8o+aWlpuLm5ARageuHzzz0Hn31mVKsU9iY7O5sPP/yQ1157DaeCKUd24OhRCAkRq8kqVxabsY0dazc5/cjLg6VLYfDgq+sBc3PBQZccf4nRy3dF2UL5LifKdzlRvsuJ8l1OlO9y8s8//1C3bl0sFgvVq1e/8wmlxCZL5DRNY+fOnXz++eeEhYVRr149/Pz8eOqpp/j5559JTExE0zQ8PT0ZOXIkX375JX/++SepqakquVROMZlEktDZWfz95ZewcqU+2gVZXSMwUrss6NubJk1g82ax3PLyZXj0UZg0SeRiyrXvZrPInBUkl1JTRaXzb74p1i5zFd3321GufS/n+kaifJcT5bucKN/lRFbfledy6hsdu56U6L/Pc3JyiI+PL5yhtHnz5sJaSgWzk0wmEy1atCAgIKDwp2HDhrZrucJQgoLyGDUKhg2D8ePh55/FjmC//w75M6ztRkZGhn0Fyqh2WdDXA1dXWLAA3nsP3n0Xpk2D8+ehX78K5PvMmaIu0/jxYpe5mTOhWjX99MsRqr/LifJdTpTvcqJ8lxNZfVeey6lvdOx6YnWCKTAwkPj4eLKzs4GrCSUnJyc6duxYmEzq1q0bNWrUsGljFWWH77/PpU4d8Xj2bDhzBtasgYEDIS6ueNvOlxRPT0/7XbwMa5cFfb0wm2HyZGjZEiZMgH/9CzIyKpDvr70GlSrBG2/Ar7/Ctm0QEQGtW+ujX45Q/V1OlO9yonyXE+W7nMjqu/JcTn2jY9cTqxNMBYULHRwc6NevH927dycgIIBOnTpRuXJlmzdQUfapXBkiI6FHD9i1C/r3h02bxDb09sDPz88+Fy7j2mVBX2/CwsTnydUVzp0TsZ89C/Xq6dsOm7/vZjO8+ioEBMCoUXDwIHTuDJ9/DuPGXV1KZy/9coTq73KifJcT5bucKN/lRFbfledy6hsdu56UqAaTyWTiypUrbN68mdjYWGJjY9m2bRuXL1+2dfsU5YTq1SE6Gho2FN+VBw0Ce80ELNghwQiM1C4L+kbg6ip+r169mq1boWlTmDq1WKWLbIbd3vdu3WDnTggKgqwsePJJkWTSS78coPq7nCjf5UT5LifKdzmR1XfluZz6RseuJ1YnmJ577jnat2+P2WzmwoULREdH88Ybb9C9e3fc3Nzo0aMHb7zxBitWrCAtLc0ebVaUURo0EIW+a9aEP/6ABx6AK1eMbpWiIhEVJRKXr7wCY8ZAZqbRLbIB7u5ih7mPPgJvbxGYQqFQKBQKhUKhUJQzrE4wTZs2ja1bt3LhwgVWrVrFm2++SY8ePXB2diY7O5uNGzfy4YcfEhwcTK1atWjbti0TJ05k3rx5nDp1yh4xKAzA4dFHYc4cMeviGpo3hyVLwMkJFi+GiRNtP9OkS5cutr1gOdEuC/pG0qVLF95/X+xYWKmSKCzfsyckJemjbVfMZnj5Zdi7F2rVEs9pmihspmnS+y6jdlnQNxLlu5wo3+VE+S4nsvquPJdT3+jY9aRES+QAqlatSt++fXnvvfdYv349Fy5cYNOmTXz44YcEBQXh5uZGXl4eu3fv5n//+x8PPPAAXl5eNG3alEceeYRvvvmGhIQEW8ai0BFzdLSYadGggZh9cQ0BAaJusckEX30FH3xgW22LxWLbC5YT7bKgbyQWiwWTCZ55BlavFnmYrVuhUyeIj7e/ti44O199PHs29O0Lo0dzUY8sWhlF9Xc5Ub7LifJdTpTvciKr78pzOfWNjl1PSpxguhFHR0e6dOnCK6+8wtKlSzl37hy7du3iyy+/ZMSIEdx1111omsaxY8f4+eefeeqpp2jRogV169a1VRMUOmIqmJZ04QKEhIhpS9cwdOjVUjJvvAE//WQ77f3799vuYuVIuyzoG8m1sffuLZJLLVrA6dOiwPzOnfpo60ZGBjg4wLx5NB42zL4BlmFUf5cT5bucKN/lRPkuJ7L6rjyXU9/o2PXEZgmmGzGZTLRq1Yqnn36a8PBwTp48yd9//82XX35JkyZN0DQNTdM4d+6cvZqg0IOCRNPYsTctl5s4UdTKAXj8cTHrRKGwFU2bQlwcDB4sdppr08boFtmYZ5+FDRvAy4tqZ89Cly5iSqCe1c0VCoVCoVAoFAqFopiYNM2+31YuXLjAxo0biY2NZcOGDezYsYPc3FwANE0r3JFOUT5IS0vDzc0NC1D9xhfnzIGHHrruqbw8sZLul1/EbmAbNkC7dqVrQ25uLg4ODqW7SDnUNlI/OzubDz/8kNdeew0nJyfd9eHWseflQXY2uLiIv7OyxN9ubvbX1oXUVPIeeQTzsmXi7xEj4JtvxNaNdqYs+17RtY3UV74r35Xv8ugr35Xvynd5tI32Xdb+ZrT2P//8Q926dbFYLFTX4fuDzWcwnTlzhvnz5zNx4kTatGmDu7s7ISEhfPzxx8THx5OTk1M4e8nFxYWePXvaugkKIzCbYdGiIp/+7juxpCk9XezGfuxY6aRWrlxZuguUU+2yoG8kt4rdbL6aXNI0GD8eOneGgwftr60LtWoRPX48fPKJWDIXESHVcjnV3+VE+S4nync5Ub7Liay+K8/l1Dc6dj0pdRrtyJEjbNiwoXCG0pEjR657/doJUtWrV6dr16706NGDHj160KlTJxwdHUvbBEVZIC8PUlOLfKlyZVi4UNTJ2b1bLGfatAlq1y6Z1MWLF0vR0NJhpHZZ0DeS4sR+9iysXw8nT4ok07x50K+fPtr25GJ6OkyaBF27iuJTEiXmVX+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1xOoE0969ewsTSrGxsZw+fbrwtRtX27m7uxMQEFCYUGrbti1ms93KPimMxGy+ur16Ebi5QXS0KCNz4ICom7NmzdWZJ9ZQv379UjS0dBipXRb0jaQ4sdevD9u2iSLzmzfDgAHw8cfw/PNiV0N7atuTQv177xU/BRw6BP/9L3z2mW3XBJYhVH+XE+W7nCjf5UT5Liey+q48l1Pf6Nj1xOoEU+vWrTHlf1O7MaHk6elJ9+7dCxNKzZs3t00rFWWfvDwYMuS2h3h4wMqV0K2b+PL/wAOwYAFUqmSdVPv27UvR0NJhpHZZ0DeS4sZerx6sWwdPPy2WZ06aJGbOzZwJJV1ubvT7XqS+pomaZ/HxEBsL8+dDBfx8qP4uJ8p3OVG+y4nyXU5k9V15Lqe+0bHrSYmmExXUUPL29ubRRx/l+++/5/DhwyQmJvLLL7/w5JNPquSSbNSoAWFhdzzMzw8WLxbL5qKi4LnnrN8UKzo6ukRNtAVGapcFfSOxJnYnJ/j2W/j8czG57ocfivXxtIm2PShS32SCL76ARo3g8GExPXDGjAq3y5zq73KifJcT5bucKN/lRFbfledy6hsdu55YPYNpwoQJ9OjRg549e0o11UtxB7y9RQHiYtCjB/z8M4wcKb4Pe3nBq6/auX0K6TCZ4NlnoXlzePBBMZOpwtG5syj4/eijInP7r39BTIzIrlXQJXMKhUKhUCgUCoWibGL1DKYZM2YwcuRImyWXZCp4VZHQCgraVKsmpiNt3w4TJhR79sTw4TBtmnj82mswZ07xtTt16mRla22HkdplQd9IShp7375w9Cj06nX1uTNn9NG2FbfVr1lT7OD42Wfg6CjWnbZvL4KuAKj+LifKdzlRvsuJ8l1OZPVdeS6nvtGx64lNKm5/8MEHJTrPYrHQt29fWzRBoTN5QUEiK5ScLLZNN5vFrIn33y/2NZ57Dl58UTx+7DFR9Ls4ZGVllaDFtsFI7bKgbySlib1q1auP//oLmjWD11+HK1fsr20L7qhvMokOtXEjNG4MdeqIomcVANXf5UT5LifKdzlRvsuJrL4rz+XUNzp2PbF6iVxRvPHGG9SuXZvx48cX+xyLxcJ9993Hjh07bNEEhZ2ZMWMGM2bM4Er+N/IFISG4VqrEUJOJtQ4O1Bk7lk7ffQdvv80fSUkc7dmT9u3bk5eXx59//glASEgIGzdu5Ny5c9SqVYsePXrQrl0UXbp0JS6uEaGhV3jjjdU0bnyBgQMHsm3bNs6ePUv16tXp168fCxYsACAtLY0qVaqwZcsWAO6//3727t1LUlISVatWJTg4mHnz5gHQrFkz3N3d2bRpEwD33XcfBw8eJDExEScnJ4YOHcq8efPIy8vD29sbDw8PNmzYAEBgYCCJiYkcOXIEBwcHhg8fzurVq9mzZw+NGjXC29ubdevWARAQEEBycjIHDx4EYPTo0SxevJiMjAw8PT3x8/Nj9erVAHTp0gWLxcL+/fsBGD58OCtXruTixYvUr1+f9u3bF67T7dSpE1lZWezZsweAK1eucPLkSc6fP4+7uztdunRh6dKlALRr1w6AnTt3AjBo0CDi4uJISUmhZs2aBAYGsmjRIgBatWqFs7MzW7duBSAoKIgdO3Zw5swZqlWrRv/+/YmIiADAz88Pl/zt/hYsWED//v3Zv38/J0+epEqVKoSEhBAeHg6Aj48PdevWZePGjQD07t2bw4cPc/z4cSpXrsywYcOIiIggNzeXpk2b0rBhQ2JiYgDo0aMHSUlJHD58GLPZzMiRI1m4cCHZ2dk0bNiQQ4cOFb4P3bp1IyUlhQMHDgAwcuRIli1bxqVLl/Dw8KBly5asWrUKgM6dO5Oens6+ffsASEoaQVpaJT78EGJiUoiIqExs7HIAOnToQE5ODrt37wYgNDSUDRs2sGfPHk6dOkVAQACLFy8GKNwVs2AMCw4OJj4+nuTkZNzc3OjTpw8LFy4EoGXLllSpUoX4+HgABgwYwK5duzh16hSurq4EBQUxf/58AHx9falVqxabN28GoG/fvvz+++/s2bMHFxcXQkNDmTt3Lpqmcc8991C/fn1iY2MB6NWrFye+/pqkQ4fIXbKEsLAwIufORbt0Cc8WLWjcuDHr168HoHv37pw5c4ZDhw5hMpkYNWoUUVFRZGZm4uXlha+vb+F7mJiYSHp6OgkJCQCMGDGC6Oho0tPTadCgAW3atGHFihUA+Pv7k5GRwd69ewEYOnQoa9euxWKxULduXfz9/Vm2bBlAscaIlStXsmfPHlq3bo2joyPbt28HuO0Y0aJFC1xdXUs9Rpw+fZqWLVtaNUZERkZy+fJlm4wRv/32G3v27LFqjBgyZAgxMTGlGiPy8vIAOHLkSKE3dxoj3NzciIuLA6Bfv36lHiOOHz/OpUuXrBojfHx8WJP/PxWlGSPy8vI4fvw4aWlp1KtXj44dO7J8+e3HiNTUVGrXrm2TMSIpKQlPT0+rxoiEhAROnDhRrDHi2LFjHD16FEdHR8LCwliwYAE5OTl4eXkBYpw3m83FGiN+++03ALp27Upqamqpx4iUlBQaNWpk1RgRFRUFUOoxIiYmhj179tj9PuJWY0RmZibZ2dl2v4+4cYzo0KFDoe8Fj+1xH3G7MSIjI6Owffa8jyhqjFi3bh179uyxaowICwtj9erVNhkj4uLiCmO3533EjWNEZGRkodeenp7FGiOaNGli9X3E7caINWvWsGfPHrvfRxQ1RiQlJdGwYUO730cUNUbs27ev0HN730fcOEZYLBZAfA9fu3YtYJ/7CCh6jFi/fj179uzR5T6iqDEiKyuLjIwMu99HFDVGFNzP6nEfAdePEbqj2QCTyaQ5ODho8+fPL9bx586d0zp06KCZTCatUqVKtmiCQicsFosGaMnJyTe/+Prrmgaa5uCgaStXFvuaWVma1quXOLV+fU07duz2x//6669Wttp2GKltpH5WVpY2efJkLSsryxB9TbNt7D//rGnOzuIz17y5ph06pJ92SSiV/iuvaFqTJpq2davVp1Y038uTtpH6ynflu1Eo3/VH+a58NwpZfTdS22jfZe1vRmsnJydrgGaxWHTRs8kSudDQUK5cucLDDz9cmDm9FefOnaNPnz7s2LEDs9nMV199ZYsmKMoCU6aIbdNzc8WWXcWcnebkBAsXQsuWojZO//6Qmnrr44cMGWKjBluPkdplQd9IbBn7gw/Chg3QoIFYMufvf/slmka/7yXWT08XNZmOHoWuXcWuc+VslznV3+VE+S4nync5Ub7Liay+K8/l1Dc6dj2xSYJp7ty59OrVi8uXLzNs2DD++OOPIo/7559/6N27N7t27cJsNvP1118zbtw4WzRBURYwmWD2bOjTR3yxHTgQjh0r1qk1asCKFeDpCQkJMHgwZGYWfWzBNEcjMFK7LOgbia1j79QJtm0TG7GdPy8Sm/mzhe2ubS0l1nd1FQX4hw6FnBxRp2nYMLhwwZbNsyuqv8uJ8l1OlO9yonyXE1l9V57LqW907HpikwRT5cqVWbJkCR07duTSpUsMHDiwcN1sAWfPnqV3797s2bOHSpUq8c033/D444/bQl5RlqhcGSIjoXVrMR1pwIDbT0e6Bk9PWLlS7K6+aZOYDFVUEebz58/buNHFx0jtsqBvJPaI/a67ICYGxowRE3y6d7/6WlaWqGM/bBhMmtSOYcPE30bU6CtV7DVqiFlMX3whdplbtAjatYP8NdplHdXf5UT5LifKdzlRvsuJrL4rz+XUNzp2PbFJggmgatWqrFy5El9fX86fP8/999/P0fxtss+cOUOvXr3Yt28flSpVYvbs2Tz66KO2klaUNdzcIDr66nSkkJBifytv0QIWLxZ5qoUL4YUXbl7R4+7ubodGFw8jtcuCvpHYK3ZnZ/jhBzGDrnJl8dyiRVC/vkg8RUXBX3/VIypK/N2gAeTXOtSNUsduMsHEibB5MzRpImYWDhgAFy/apH32RPV3OVG+y4nyXU6U73Iiq+/Kczn1jY5dT2yWYAKoVasWq1evxsvLi9OnT9O3b1+2bdtGYGAgCQkJVKpUie+//54xY8bYUlZRFvHwuDodaeNGMR0pf2eiO9GzJ/z0k3g8fTp8/PH1r3fp0sXGjS0+RmqXBX0jsWfsJhNUrSoeL1kiVpTlb7RR+LEt+H3hgsiZLllit+bchM1i79hR1EYbNkzMaKpWzTbXtSOqv8uJ8l1OlO9yonyXE1l9V57LqW907Hpi0wQTgKenJ7/99ht16tTh6NGjdO7cmYMHD1KpUiV++uknHnroIVtLKsoqLVqI6R8Fy+ZefLHYp44cCZ9+Kh6/8gr8+uvV15bqPX3kGozULgv6RqJH7FlZ8Mgjtz+mYEbd2LH6LZezaew1akBEhKh0XsCmTdcvmctfH+gwahRjvv8eh1GjDFsfqPq7nCjf5UT5LifKdzmR1XfluZz6RseuJzZPMAH4+PiwatUqqlWrhqZpODo68ssvvzB69Gh7yCnKMoGB8OOP4vFnn8G0acU+9YUXxA+IL/O3KsCsUNiKiIji1b/WNFEYfMECuzfJPphMVx8nJ8Pw4RAQIPrn4sViHeCYMZiXLKHJ8eOYlywxbn2gQqFQKBQKhUKhKBc4WHPwTwXrlopJWFgY3333HQMHDiQrK+uW56slcxWcUaPg5El4+WWYNEksnxsxolinfvwxJCXB/Pli2VJsLLRr187ODb41RmqXBX0j0SP2qCgwm4u3mtNsFrWa9JiUadfYnZygWzeRLZs0STyXn4Ay5b8RphvXB0ZFia0edUD1dzlRvsuJ8l1OlO9yIqvvynM59Y2OXU+sSjCNHTsW07X/810MTCYTixcvZvHixbd8XSWYJODFFyExURRVevhhUUG5R487nmY2iwlQZ8/C77+LusRz5jjg66tDmxXSce5csUuFkZdX7A0SyzZubiKD+/nnV6cM3lhZvwBNE8mnsWPh1ClRIV2hUCgUCoVCoVAoKMESOU3TbP6jkACTSSy/GToULl8WsyD27y/Wqc7OYsJEixbiO+2YMXUwaqfHnTt3GiNcRvSNRI/Ya9cWSc3iYDZDrVr2bU8Bdo/dZBLBFwed1wca+Zk3ur8ZrW8kync5Ub7LifJdTmT1XXkup77RseuJVTOYjh49aq92KGSgUiX4+We47z6xXfqAARAXJ+q63IEaNcQ28l26QFKSGyEhsHq1mkChsC2hobBwYfGOzcuDlBQxi0mvRJNdKavrAxUKhUKhUCgUCkW5wKoEU6NGjezVDoUsuLiI/d27doWDByEoCDZsgOrV73iql5dIMgUEaMTGmnj4YZg3r/gzTmzBoEGD9BMrg/pGokfsw4fDc8+JUkO3m1xZsFJ4wwZo3hy++EKUFbNyBXGx0cX3Mro+0MjPvNH9zWh9I1G+y4nyXU6U73Iiq+/Kczn1jY5dT6z+ar59+3Z7tEMhE7Vrw8qVULcu7NoFw4aJZXPFoFUrePPN7VSufLUmsZ6rLOPi4vQTK4P6RqJH7M7OVzc9vFWyqOD5Dz4QyaXkZFHHftAgUWbMHujiexldH2jkZ97o/ma0vpEo3+VE+S4nync5kdV35bmc+kbHridWJ5g6deqEp6cnTz75JMuWLSMrK8se7VJUdJo0gehoqFoV1qyBceOKnSny9DxUmAT4/HP49FM7tvMGUlJS9BMrg/pGolfsgwaJ1WI1aoi/C3IuBb9r1IDFi+HVV2HnTpg8GRwdYflyUSfsiy/gyhXbtkmX2ENDrZvBdN99dm1OAUZ+5o3ub0brG4nyXU6U73KifJcTWX1Xnsupb3TselKixUWnTp3i22+/JSQkhNq1azNo0CBmzZrFqVOnbN0+RUWmQweIiBC1mX76Cd5+u1in1axZk1GjYOpU8fdLL8HcuXZs5w3aRmK0vpHoGfvgwaKg/Jw5Iu/SqtU5QkPF36dOiSQUgJMTvPOOmIjXrRukp4sldn/8Ydv26BL78OFQs2bx1/m9+SbMnl38pFQJMfIzb3R/M1rfSJTvcqJ8lxPlu5zI6rvyXE59o2PXE6sTTCdPnmTmzJkEBQXh7OxMZmYmy5cvZ8KECXh5edGhQwcmT56sltIpiseAAfD11+Lx++9ffXwbAgMDAXjxRfFlHmDMGFi/3k5tLELbKIzWNxK9Y3d2FjWsIyMhPr4qkZHi76IKyzdvLuoxffUV/OtfItlUgC2WcOoSe3HXB5pM0LChqMH0xBMQEABJSXZrlpGfeaP7m9H6RqJ8lxPlu5wo3+VEVt+V53LqGx27nlidYGrQoAHjx49n6dKlpKSksHjxYsaNG8ddd92Fpmns3LmT//znP/j7++Ph4VF4bGZmpj3ar6gIPP64mAYC8PTTsGzZbQ9ftGgRIL7nfvophIVBTo6YabJnj32bWqBtFEbrG4mRsRdH22yGp56C6dOvPnfiBHTqBL//bn99m3DD+kAtf12gduP6wL//hk8+AVdXsZVe7dp2a1JZ970i6xuJ8l1OlO9yonyXE1l9V57LqW907HpSqv23XFxcGDRoEF9//TUnT55k69atvP3227Rr1w5N0zh9+jSzZ88mNDQUd3d3tZROcWveeQcee0wstxk5EuLji3Wa2SyWLXXvDmlpYkLUiRN2bqtCUUzefhu2b4fAQFFm7Px5o1tUDK5ZH5g3eDBHGzcmb/Dg69cHOjqKCvt//QXh4VendeXmwtKl+lbeVygUCoVCoVAoFGUCk6bZ55vAqVOnWLZsGUuXLmXdunWFM5hM+Usv2rZty6BBgxg0aBAdOnSwRxMUNmTGjBnMmDGDK1eucPDgQWbNmoWrqytDhw5l7dq1WCwW6tati7+/P8vyZyC1b9+evLw8/vzzTwBCQkLYuHEj586do1atWvTo0YOoqCgAWrdujSPg+uCDNNi1izx3d7ZMm8axSpWoXr06/fr1Y8GCBQC4ubnh6+vLli1bALj//vuJi0vgySdbkJTkRosWGs8/H0nVqjk0a9YMd3d3Nm3aBMB9993HwYMHSUxMxMnJiaFDhzJv3jzy8vLw9vbGw8ODDRs2AGIqY2JiIkeOHMHBwYHhw4fz3Xff4eLiQqNGjfD29mbdunUABAQEkJyczMGDBwEYPXo0ixcvJiMjA09PT/z8/Fi9ejUAXbp0wWKxsH//fgCGDx/OypUruXjxIvXr16d9+/ZER0cDoqh+VlYWe/KnZvn6+nL27FnOnz+Pu7s7Xbp0YenSpQC0a9cOgJ07dwJiO8y4uDhSUlKoWbMmgYGBhdnzVq1a4ezszNatWwEICgpix44dnDlzhmrVqtG/f38iIiIA8PPzw8XFhfDwcO6++2769+/P/v37OXnyJFWqVCEkJITw8HAAfHx8qFu3Lhs3bgSgd+/eHD58mOPHj1O5cmWGDRtGREQEubm5NG3alIYNGxITEwNAjx49SEpK4vDhw5jNZkaOHMnChQvJzs6mYcOGmEwmjh8/DkC3bt1ISUnhwIEDAIwcOZJly5Zx6dIlPDw8aNmyJatWrQKgc+fOpKens2/fPgDCwsJYvXo1aWlp1KtXj44dO7J8+XIAOnToQE5ODrt37wYgNDSUDRs2cPz4cRo3bkxAQACLFy8GxBhmNpvZsWMHAMHBwcTHx5OcnIybmxt9+vRhzpylzJ3bhrVr78n/7GbyyCPbmTy5Jbt37+LUqVO4uroSFBTE/PnzCz2uVasWmzdvBqBv3778/vvvXL58GRcXF0JDQ5k7dy6apnHPPfdQv359YmNjAejVqxfHjh3j6NGjODo6EhYWxoIFC8jJyaFJkyY0btyY9flrSbt3786ZM2c4dOgQJpOJUaNGERUVRWZmJl5eXvj6+rJq1Sr+/vtvHnjgAdLT00lISABgxIgRREdHk56eToMGDWjTpg0rVqyg2YoVtJ8zh4v33svvYWFcbNCg1GPEnDlzqFatmhgjHB0Ll18PHDiQbdu2cfbs2ZvGiBYtWuDq6nrdGLF3716SkpKoWrUqwcHBzJs3D+C2Y0RmZiaPPfaYVWNEZGQkly9ftskYsWXLFqpVq2bVGDFkyBBiYmJKNUbk5eXx999/M2LEiEJv7jRGuLm5Fe6Q0q9fv1KPEefPn6dNmzZWjRE+Pj6sWbOm1GNE8+bNSUpKsmqMSE1NpXbt2laPEQsXLgSgZcuWVKlShfj4eC5evMiIESPYtav4Y0RCQgInTpwo1Rjh5eXF2rVrufvuuzGbzcUaI3777TcAunbtSmpq6h3HCAB/f38yMjLYu3cvwHVjhMlkYuDAgSW/jyjFGLF27Vpyc3OtGiNKch9xqzGiQYMGuLq62v0+4sYxokOHDkyfPp2777678H7cHvcRtxsjvL29C9tnz/uIosaIbdu2Ua1aNbvfR9xqjDhx4gTnzp2zaowAGDBgQKnGiF9//ZVDhw5x//334+npabf7iNuNEb/88guOjo5WjRGl/q6RP0ZcvHiRUaNG2f0+oqgxIisri6T80gL2vo+4cYywWCz8/fffTJgwgbVr1xZrjLDld41Vq1Zx5coVXe4jihojPDw8cHZ2tvt9RFFjxNy5c6lWrZou9xE3jhEADzzwABaLherVq2N3NB3IzMzUli5dqo0fP17z8PDQTCaTZjKZNLPZrJnNZq1Bgwba+PHjtT///FOP5ihKgcVi0QAtOTnZPgIXL2pa+/aaBpp2992aVoTOoUOHijz1+HFNa9BAnNqzp6ZlZdm+ebfS1guj9LOysrTJkydrWfZ4U4uJke99abU3bNA0X1/x2QRNGzRI0xIT9dMvKVb7/sknmubsLIJ0dNS0N97QtEuXStWG8ux7edVX/V35bhTKd/1RvivfjUJW343UNtp3Wfub0drJyckaoFksFl30SrVErrg4OzsTHBx83VK6d955pzALevr0ab799tvCbJ1CYlxdxX7vjRuLOi+DBkFGxnWHFGTCb6RhQ4iOhmrVRM2bMWNsv8HVrbT1wmh9IzEy9tJqd+8Of/4plsw5OopVZDNn6qevG5Mmwb59EBQkCqNNmQItWtyxrtrtKM++l3d9I1G+y4nyXU6U73Iiq+/Kczn1jY5dT3RJMN1Ihw4deOedd9i2bRsnTpxg5syZDBw4kCpVqhjRHEVZo359WLECatWCLVtg9Gi4cqVYp7ZpA4sWiS/x8+fDyy/bua0KRTFxcoJ334WdO8VH+o03rr5WzI93+aBpU5FQWrQIvLzg2DGRKH77baNbplAoFAqFQqFQKOyIIQmmaynYlW7JkiW89NJLRjdHUVbw9YUlS8S38iVLYOLEwsLBQUFBtz21Tx/44Qfx+NNPYdo02zXrTtr2xmh9IzEydltqt2gBv/4KBfn0K1egVy+Rf8nOtr++LphMYlvHv/6CV18FFxcYPrxEl6oovpdHfSNRvsuJ8l1OlO9yIqvvynM59Y2OXU8MTzApFLekWzf45RfxZfWrr+D//g+gsNDZ7XjggcLDmTRJzGayBcXRtidG6xuJkbHbU3v5coiNhf/8R8zAy6+zqZu+XalaFT78EBIToVWrq89Pmwb5RSvvREX1vTzoG4nyXU6U73KifJcTWX1Xnsupb3TseqJLgunIkSO89tprBAcHExoayltvvcXRo0f1kFaUd4YNg88+E49ffx1+/pkzZ84U69SXX4Z//Us8fvhhUZeptBRX214YrW8kRsZuT+1Bg2DBArEy9MAB6NEDnnwSLlzQR18X3N2vPt69W3TOPn3gwQfh9OnbnlpRfS8P+kaifJcT5bucKN/lRFbfledy6hsdu56UKsG0bds23n77bd555x0uXbpU5DHLli2jZcuWTJ06lRUrVrB06VL++9//4ufnV7idpkJxW559Fl58UTx+7DEaHzlSrNNMJpGbGjoULl+GkBDI3/G0xFSrVq10FyglRusbiZGx21PbZBJ51P37Ydw48dysWeDnB/k7j1Ys3xs2hAkTwGwWawV9fWH6dMjNLfLwiup7edA3EuW7nCjf5UT5Liey+q48l1Pf6Nj1pFQJpq+++oopU6YQGxtL1apVb3r9zJkzPPTQQ2RlZaFpGt7e3vj6+mIymcjOzuaRRx4hISGhNE1QyMJHH8HIkZCTw70ffSRmQRSDSpXg55/FajuLBQYMgJMnS96M/v37l/xkG2C0vpEYGbse2jVrisRSTAz4+IiJPR98IGo0VSjfa9QQCaX4ePD3h7Q0kUT294c//rjp8Irue1nWNxLlu5wo3+VE+S4nsvquPJdT3+jY9aRUCaY1a9YA8MADDxT5+ueff05aWhqVKlUiMjKSgwcPsm/fPtauXUvVqlW5fPkyX3zxRWmaoJAFsxl+/BF69sSUlia2QT9xolinuriIOuG+viK5NGDA9cuPrCEiIqJkJ9oIo/WNxMjY9dTu2RN27RK7zH3zjUiSRkREcPky5OXp1gz706EDxMXBzJkiu7Zzp+icFy9ed5gsvpdFfSNRvsuJ8l1OlO9yIqvvynM59Y2OXU9KnGDKycnhRP4X/ICAgCKPmT9/PiaTiQcffJAhQ4YUPt+zZ09eeuklNE1jXTELvSoUODnBokVYPDwgKcmqTFGtWrByJdx1l1gmN2TIrXfsUiiMxtkZ3n8f2ra9+tzkyaI+0/79RrXKDpjNouDUgQPw6KPw3ntw7RTi/J0jFQqFQqFQKBQKRdmnxAmms2fPFj5u3LjxTa+fPn26sJD38CK2pw4LCwMoTFIpFMWiZk2Svv1WZIr27bMqU9SoEURHi++vMTEwdqz1M0L8/PysbrItMVrfSIyM3ej3vWHDlsycCZs2iaTT5MkVLEFapw589x1MnHj1uZUroVs32leqZFizjPbdaH0jkbm/G61vJMp3OVG+y4msvivP5dQ3OnY9sSrB1KRJE5o2bUrTpk3p0qVL4fN+fn6Fzxf8dOzYsfD1CRMm3PR6cHAwAFlZWTe9pheBgYGYTCarfmJiYm55vZUrVzJ06FA8PT1xcnLC09OToUOHsnLlymK3KSMjg6lTp+Lv70+tWrVwdXWlefPmvPTSSyQmJhb7Ovv27eOpp57i7rvvxsXFhTp16tCjRw++/vprcm9RTLe8UMXXF1asKFGmqG1biIwEBweYOxdefdU6bTc3N2uba1OM1jcSI2M3+n338KjGrl0QHAw5OfDuu9CunUg4VUg0TewaGReHz+jR8PzzolaTzhjtu9H6RiJzfzda30iU73KifJcTWX1Xnsupb3TsemJVgumRRx4p/ClY8mYymXj44Yeve+2RRx4pnNXUoEEDHn/88ZteHzt2bGHS5sbXyipms5l77rnnpuc1TePJJ59kwIABLFq0iKSkJC5fvkxSUhKLFi1iwIABPPnkk2h3WO5x+PBh2rdvzyuvvMLWrVs5f/48ly5dIiEhgU8++YTWrVsTHR19x3bOnj2bDh068PXXX3P48GGysrJISUkhNjaWp556iu7du3Pu3LkSvw9GExcXB23aiC22CjJFr71W7PP79hWTJQA+/hg+/9xKbQMxWt9IjIzd6Pc9Li4OLy9RS2zePKhbF/76CwICxIZsFouhzbM9JhMsXQrDh2PKyxOd1NdX9HUdl82VBd9lRfb+LivKdzlRvsuJrL4rz+XUNzp2PXGw5uDJkycXPj59+jRffvklmqYxYsQIWrRocd2xGzduxGQy0adPH955552brpWZmcm7775LtWrVinxdD77//nsuXbp022P279/PyJEjAejTpw8eHh43HfPmm28ya9YsANq1a8crr7yCt7c3hw8f5qOPPmLnzp3MmjWLOnXq8P777xepk56eTnBwMAcOHABg3LhxjBo1ChcXF9avX88HH3yAxWJh+PDhxMXF0bp16yKvs2rVKsaPH09eXh716tXjjTfeoHPnzqSmpvLNN9+wcOFC/vjjD4YOHcr69esxm0tV591Y7rtPZIrGjIGpU8HL6/olNrfh4YdFGafXX4cXXgAPD8hftalQlFlMJhgxQnz0X35ZfPznzBH51Qr3HyOenjB/Putff51eCxbA33/D6NHw7bcwYwY0a2Z0CxUKhUKhUCgUCsW1aKWgVq1amtls1p588snrnt+/f7/m4OCgmc1m7eeffy7y3J07d2omk0lr2bJlaZpgd1555RUN0ABtzpw5N71+6NAhzcHBQQO0jh07ahkZGde9funSJa1jx44aoDk4OGh///13kTrvvPNOoc5HH3100+ubN28u1OnVq1eR18jJydHuvvtuDdCqV69epNbTTz9dqPPjjz8W5y24DovFogFacnKy1efaipSUlOufmDJF00DTTCZNW7iw2NfJy9O0p58Wpzo5adqGDSXQ1hmj9LOysrTJkydrWVlZhuhrmrHvfVn1fd06Tfvpp+ufu3DBdrplxvfMTE177z3RUUHTFi3ST9tAVH+XT9tIfeW78t0olO/6o3yXU9to32Xtb0ZrJycna4BmsVh00SvV9JWhQ4eiaRrffPMN48aNY+nSpcyePZsBAwZw5coVatased3ucdeyfv16ANpeu01SGSMvL49ffvkFAFdXV4YOHXrTMdOmTSusaTR9+nRcXFyue71KlSpMnz4dgNzcXD777LObrpGTk8Pn+eu0mjdvzosvvnjTMV26dOHxxx8HxHu3ffv2m45ZtGgRf//9NwCvv/463t7eNx0zdepUatasWfi4PLL/xm20Xn9d7ESlafDAA7B5c7GuYzLBF19AaKgomDx48J136LpJW2eM1jcSI2M3+n2/lX6vXmI2XgHr1oli9l9/bX0B+7LK/v37xbZ6b70lCvu/9x6EhFw9ICnJvtoGYrS+kaj+LifKdzlRvsuJrL4rz+XUNzp2PSlVgum9997D3d0dTdP47rvvCA0NZfz48SQmJmIymZgyZQpVqlQp8twffvgBk8lE3759S9MEu7J27VqS8r+8hIWF3RSLpmksXrwYAF9fX+69994ir3PvvffSLH85R1RU1E21mGJiYrhw4QIg6lzdatna2LFjCx8vXLjwptejoqKKPPZaqlSpwogRIwDYu3cvhw4dKvK4sszJkyevf8Jkgi+/hEGDICtL/M5fangnKlWCX3+Frl3hwgXo3//231dv0tYZo/WNxMjYjX7fi6v/zTeiHtNTT0FgICQk2LddenBd7N7eItFkMom/U1KgdWuRcDp2zL7aBmC0vpGo/i4nync5Ub7Liay+K8/l1Dc6dj0pVYLprrvuYtOmTQQGBqJpWuFPjRo1+Pzzz3nyySeLPC8qKoo9e/bg4uJyyxlOZYGffvqp8PGYMWNuev3o0aOFCaiePXve9loFr588eZJjN3wRio2Nvem4oujYsSNVq1YFRI2rGym4TrNmzahfv/4d23Kr65R1ikxaOjhAeDj4+0NqqsgUnTlTrOu5uIjiyc2awYkTEBR066LJt0qY6oXR+kZiZOxGv+/F1f/5Z/jsM6haFWJjRS38//wHLl+2b/vsyW1j//13sbvckiXg5wcffGDTYMuL7xUR1d/lRPkuJ8p3OZHVd+W5nPpGx64npa7wfM8997Bu3TpOnz7N5s2b2blzJ8nJyfzrX/+65TnNmjVj/fr1xMbGUq1atdI2wS6kp6ezaNEiABo2bEhgYOBNx/z111+Fj319fW97vWtfv/Y8a67j4OBQuOztxmukp6cXZkZL05byQMi1y2OupWpVsfOUt7eYzRAcDOnpxbpm7dqwYgXUqwe7d8PQoUV/T72ltk4YrW8kRsZu9PteXP1KleC558RKsqAg8Rl++21o3x62bLFzI+3EbWMfNgx27YKePSEzE/79b5FVW7fO/to6YLS+kaj+LifKdzlRvsuJrL4rz+XUNzp2PbFqF7nbUa9ePerVq1esY5s3b07z5s1tJW0XIiMjC3eYe/jhhzEVLMm4hhMnThQ+9vT0vO31vLy8ijzv2r+rVq1KjRo17nid3bt3888//5CdnY2TkxMgZkYVLL0rTVtuJDs7m+zs7MK/09LSinxeTyIiIhg+fHjRL7q5wZIlVO7ZE9P27VwJCyM3MlLMcLoDDRpAVJSJvn0dWbfOxJgxV/j++1yuXbF4W20dMEq/wGujPAdj3/vy5nv9+hAZCRERZl56yYF9+0wcPJhD27bWFWYqF757e8PKlZjDw3F47TVMCQnQpw9XRo8md/ZsKMVOmeXNd1tRLnyvoNpG6ivfle9GoXxXvittfTDad1n7m9Haevtt0m4sCKQAoE+fPqzL/1/wAwcO4OPjc9MxU6dO5ZVXXgFgxYoV9O/f/5bXW7FiBUFBQQB8/PHH1xXybtGiBfv376devXqcucOyrpEjRzJ//nwAUlJSqF27NgBbt27F398fgFdffZUPP/zwltfIzMwsnKYXHBzM0qVLb3ns5MmTeffdd296/rXXXsPZ2fm2bTUSj5MneeSHH3DMzWVHu3YsHTz4at2WO/D330359dcHyMurRLdumwgMXM/+/S1ISGhGRoYLVapk4ut7AD+/fTg6XrFzJApF6cjIcGb37jZ07rylsAtcvFiVatUuGdswO+CUmUnvdevotHUr2zp2JDo42OgmKRQKhUKhUCgUhpGVlcWHH36IxWKhevXqdtez2QymisTJkyeJiYkBRIHuopJLIMwqoHLlyre9ZsFMIxAJnqKuc6dr3O46tmrLjbz++utMmjSp8O+0tDS8vLx45plnqFOnzh3baw927txJu3bt7nxg//5oI0bQfudOWgcHc+WNN4qt0bNnHuPGVWLTpm7s2NGVzEwTZrNGXp74/ddffqxfH8rs2bkMHKjfdl3Fjt3GZGdnM23aNF544YXrPj96YlTsRmvbTr8XAOfOQdu2lQkIyOPTT3O5665bn1EufX/3XXJ27KB1kya0zt8x0/T333DuHFrnzvbVtjGqv6v+rifKd+W78l0efeW7nNpG+y5rfzNa+59//rnt5BNboxJMRfDzzz+Tl7/H9yOPPHLL466dwXP5DoVlr52a5uLiUuR17nSN213HVm25EScnpyIHoFs9rwceHh7F0x42DGbMgAkTcPjPf3Bo0gQefbRYGk88IeoH//wzZGaKaR95edf/tlhMhIU5EhUFgweXKBSrKXbsdqJc+F7BtG2tHxcn6uAvWlSJdesqMXUqPP747VeSlTvfu3S5+ljT4PnnYc0aGDdOFALPn/lpF20bYrR+ufO9AmiXBX3luzEYra98Nwaj9ZXvcmkXYJTvRscuq+9665aqyPexY8f4/PPPefbZZ3n++eeZOXMmp0+fLva5vXv3pk+fPqVpgl2YM2cOIMwYOXLkLY+7tkB5+h2KSRfUcwJwdXUt8jp3usbtrmOrtpQHrNr57qmn4PXXxeNx42DVqmKdlpUFy5ff/piCxaVjx4rj9aA87vpnK4yM3ej33Zb6w4bBtm3QsaPYLXH8eOjVCw4cuHpMVhbMmQOjRjnw/fdjGDXKgTlz9PucX0upY8/OhoK6c998I7aL/O47yLvzzMOK5Ht5Q/V3OVG+y4nyXU5k9V15Lqe+0bHrSYkTTG+++SbNmjVj0qRJzJgxg+nTp/PMM8/QtGlTXn755TsWk7p06RIxMTGFS9HKCtu2bWP//v2AqE9UM3+JRVFcW0y7YAe3W3FtMe1ri2xfe51Lly5x4cKFYl2nTp0612UjbdWWCsmUKfDww3Dlivh2vWPHHU+JiIDz5+98aU0Txy1YYIN2KhQ60batmMn06adQpQps2CA2X5syBRYvFgXvx4yBJUvMHD/ehCVLzIwZI56/Tcm2somzs0goxcZCy5ZijeDjj0P37mIHOoVCoVAoFAqFQmETSpRgeu211/jggw/IyclB07TrfrKzs/n000/p2LEjB679L/Fywk8//VT4+HbL4wD8/PwKHyckJNz22Gtfv3EHveJeJzc3l8OHDxd5DVdX18JkUWnaUh7o3bu3dSeYTPDtt9CnD1y6JPZvP3bstqdERRV/8ymzGRYtsq5JJcXq2CsQRsZu9PtuD30HB3jhBdi3D/r3FxN9YmJgyBAoyHPfuCz0wgUICYElS2zenFtis9gDAkRy+ZNPwNUVNm+GDh3E0rlrKZi+NWwYQ6dPF0lpg6ZvGf25MxLV3+VE+S4nync5kdV35bmc+kbHridWJ5h2797N1KlTATGLZvr06ezdu5ft27fzySef0LBhQzRNY9++fXTr1o2tW7favNH2Iicnh7lz5wIitgEDBtz2+CZNmtCgQQMAfv/999seu2HDBkCsv2zcuPF1rwUEBBQ+vt11tm3bVri8rVu3bje9XnCdAwcO3HY3ums1irpOWacgyWYVlSuLfdtbt4azZ8U36tTUWx5+7lyxVtAA4rjbXMqmlCj2CoKRsRv9vttTv3FjiI6GH3+EguH6VnuLGrEs1KaxOzrCpEmQkAAjRoCPD/TocfX1JUuuTt+KisIpLk5kmw2avmX0585IVH+XE+W7nCjf5URW35XncuobHbueWJ1g+vrrr9E0jZo1axIXF8czzzyDn58f7dq144UXXuCvv/7imWeeASA1NZU+ffqwfv16mzfcHqxYsYJ//vkHgAceeAAHh9vXQDeZTISEhABiVtAff/xR5HF//PFH4ayhkJAQTAV7hecTGBiIm5sbAD/++CPaLb7d/fDDD4WPhwwZctProaGhRR57LRkZGcyfPx8QM6dutUNeWeb48eMlO9HNTXyT9vQUBWcGD77lt+Tata2bwVSrVsmaZC0ljr0CYGTsRr/v9tY3mcSPxXLr5FIBei8LtUvsHh4wb55YJ1iw6+bChWJ61tXpW9f/NmD6ltGfOyNR/V1OlO9yonyXE1l9V57LqW907HpidYLp999/x2Qy8cILL9C0adObXndxcWH69OnMmTMHJycn0tPTGThwIMuWLbNJg+3JtcvjxowZU6xznn/++cJE1MSJE8nMzLzu9czMTCZOnAiAg4MDzz///E3XqFy5Ms8++ywAf/31Fx9//PFNx8TFxTF79mwAevbsSadOnW46ZsiQIXh7ewPwwQcfFJkpffnllzmfX1zo5ZdfLlaMZY3KBV8IS4KHB6xcKZJNmzbBQw+J2kw3EBpq3QymIvJ9dqFUsZdzjIzd6PddD/2yuizUrrHnJ/bJyhJjAZSp6VtGf+6MRPV3OVG+y4nyXU5k9V15Lqe+0bHrimYl1atX18xms7Zp06Y7Hrt+/XqtevXqmslk0ipXrqzNnTu38LW9e/dqJpNJM5vN1jbBLqSmpmpOTk4aoLVs2dKqc1977TUN0ACtXbt22ty5c7WtW7dqc+fO1dq1a1f42uuvv37La6SlpWk+Pj6Fx44fP15bt26dFhcXp/33v//VXF1dNUBzcXHRdu7cecvrLF++XDObzRqg1atXT5s+fbq2ZcsWbeXKldqwYcMKrx8QEKDl5uZaFaemaZrFYtEALTk52epzyxTr12ta5cqaBpr27LOalpd33cuZmZpWs6ammUzikNv9mM2atmuXMWHoRVZWljZ58mQtKyvL6KYo7ETPnnf+rF/7ExhodIttyE8/WRf8nDlGt9iuqP4uJ8p3OVG+y4nyXU6U73KSnJysAZrFYtFFz+oZTFn5/3Pr4uJyx2MDAwNZu3YttWvXJicnh4ceeojvvvvOWkldmDdvXuHOd8WdvVTAlClTeOyxxwDYuXMno0aNolOnTowaNYqdO3cC8Pjjj/P+++/f8hrVqlVj+fLl3HPPPQDMmjWL3r1706VLF/7973+Tnp5O9erVmT9/Pm3btr3ldYKCgpg5cyaVK1fm7NmzTJw4kc6dO9O/f38iIyMB8Pf3Z9GiRVSqVMmqOMsKERERpb9IYKAoOgPwxRcwbdp1Lzs7X335hhWNhRQ8n5cnNqRavLj0zboTNom9nGJk7Ea/73roW7Ms1GTSb1moLu99GZ2+ZfTnzkhUf5cT5bucKN/lRFbfledy6hsdu55YnWCqXbs2AKdOnSrW8R07diQmJoa77rqLK1euMG7cOKZPn26trN2ZM2cOAJUqVeLBBx+06lyz2czs2bNZvnw5ISEhNGjQgMqVK9OgQQNCQkKIjo7m22+/xXyHLzB33303O3fu5P/+7//o2LEjNWrUoEqVKjRr1owXXniB3bt3ExwcfMf2jBs3ju3btzNu3DiaNm2Ks7MztWvXJiAggK+++opNmzbh7u5uVYxlidzcXNtcaNQoyC9Yz4svipos1zBokPjeWaOG+LvAvoLfNWqIJFT37pCWJpbVvfVWkSvubIbNYi+HGBm70e+7HvrWLAvVtKvLQm9YFWxzdHnvy2hVf6M/d0ai+rucKN/lRPkuJ7L6rjyXU9/o2PXk9lWsi8DPz4+zZ8+yadMmBg4cWKxzWrRowYYNG+jTpw+JiYk8//zzVidx7M2mTZtKfY2goCCCgoJKdY2qVavyyiuv8Morr5TqOi1btmTWrFmlukZZpajaXyXmxRchMRGmTxc7RdWvDz17Fr48eDCcOiUKGi9aBMeOWWjc2I0hQyAsTMx0Gj0aXnpJTIR6/33Yvh1++QVq1rRdMwuwaezlDCNjN/p910N/+HB47jlRy/p2hb5NJpFcDQuDnBxo0wa6dIF33gF7NFOX975g+lZxkkzFnelkA4z+3BmJ6u9yonyXE+W7nMjqu/JcTn2jY9cTq++Uu3XrhqZphcutiou3tzcbN27Ex8cHTdP45ZdfrJVWKABo2LCh7S5mMonlcUOHwuXLYhrHvn3XHeLsLOr/RkbCsmUZREaKv52dxeuOjvD55zBnDri4wIoV0LEj7N5tu2YWYNPYyxlGxm70+66HvjXLQn/8URy/di0cOgQ//QTNmsGTT8KJE7Ztly7vvbVV/WNiICgItm61Z6sM/9wZiervcqJ8lxPlu5zI6rvyXE59o2PXE6sTTP369QPg77//Zs2aNVad6+npSWxsLG3atEG7017YCsUtiImJse0FK1WCn3+Grl3F9I0BA8S0JSu1H3oINm+Gxo3hyBG4914ID7dtU20eeznCyNiNft/10r95Wah23e8aNUStsUGDxOv9+0N8vPidmwuzZsHdd8Ozz8Lp07Zpky6xDx8uphzeKrNWgMkETk5iFtOKFeDvL6Y55tfaszVGf+6MRPV3OVG+y4nyXU5k9V15Lqe+0bHrSYlmMHl5eWE2m5k8ebLVgnXq1CEmJoYuXbpYfa5CYTdcXGDJEvDxEVMwgoJEYSUradtWLJHr10/UpnngAZg0SSwlUijKAwXLQufMgcGD82jc+CiDB+cxZ454viC5VECnTiLXEhsrVpdevixWnHp7w7FjhoRgPdZM34qIgIMH4ZFHRKJp6VJo317MgrTHtEWFQqFQKBQKhaKcUKJiEsePHycnJ4eNGzeWSNTNzY3169dz9OhRjhw5UqJrKOSlR48e9rlw7dqwciXUqwe7dsGwYeLbspXatWpBdDT8+9/i72nToG9fOHu29E20W+zlACNjN/p911u/YFno3Lm5jB37E3Pn5l63LLQoAgJg/XpYs0bUZOrWTczmK6CktQ11i704Vf0Lpm95e8MPP8Bff8GDD4rk06JFYiakDTH6c2ckqr/LifJdTpTvciKr78pzOfWNjl1P9KtWegOVK1emUaNGNGrUyKgmKMopSUlJ9rt4kyawfDlUrSq+KT/xhJiKNGcODBtGtcGDReJpzhzIyrrlZSpVgilTYOFCqFYNfv8dOnQQy4lKg11jL+MYGbvR77vR+sXFZII+fWDTJlEYv4DkZNG1pkyBixetu6ausV87fSs0lLT27UV9pltN3/LxEUmlvXvh4Yfh5ZevvrZvHxw4UKrmlBff7YHq73KifJcT5bucyOq78lxOfaNj1xPDEkwKRUk5fPiwfQU6dBDLYCpVEl8sa9USO8xFRVF9xw4xy2HMGGjQQCyPuQ1DhoikUrNmkJQE3bvDt9+WvGl2j70MY2TsRr/vRutbi8kEbm5X/549G06ehDffFDvNffwxZGQU71q6x35NVf/lL73ETVX9i8LPT1Q6r1Pn6nMTJ4rnH3kEShhDefPdlqj+LifKdzlRvsuJrL4rz+XUNzp2PVEJJkW5w6zHNuEDBsCECeJxwUylgl2mCn5fuAAhIaJ2023w9RVJptBQseJu3DgYPx6ys61vli6xl1GMjN3o991o/dLyyivwyy+iAHhKipjo4+0tajXdqR+US98zMsTUxby8q1vsPfGE1UWpyrvvpaFc+l5B9I1E+S4nync5kdV35bmc+kbHricmzaDt3K5cuVI4VUymbfvKO2lpabi5uZGcnEyda/+3vqKRlSVmKJ0/f/vjTCZRm+XUqdvPcEB81/zwQzGLQ9PEBlSRkeDpabtm24vs7Gw+/PBDXnvtNZycnIxujkInbO17bq6YFPjuu3D8uHju7rvFarLKlUt9+bLH1q3wzjuiCjqAgwM8/ji88QZ4eRnbttug+rucKN/lRPkuJ8p3OVG+y8k///xD3bp1sVgsVK9e3e56DiU9MSMjg2nTprFgwQIOHz6M2WzG19eXkSNHMmHCBJzv8GU7ISGBVq1aYTabyS1p9VeFbsyYMYMZM2Zw5coVAKKionB1dWXo0KGsXbsWi8VC3bp18ff3Z9myZQC0b9+evLw8/vzzTwBCQkLYuHEj586do1atWvTo0YOoqCgAWrdujaOjI9u3bwdg4MCBbNu2jbNnz1K9enX69evHgvyiLhkZGfTq1YstW7YAcP/997N3716SkpKoWrUqwcHBzJs3D4BmzZrh7u7Opk2bALjvvvs4ePAgiYmJODk5MXToUObNm0deXh7e3t54eHiwYcMGGsfG0uVOySUQmaLz5zn39dccCwjg4MGDAIwePZrFixeTkZGBp6cnfn5+rF69miZN4Pvve/Hss+7ExzvQokUWixY5kJGxkosXL1K/fn3at29PdHQ0AJ06dSIrK4s9e/YA4ODgQLVq1Th//jzu7u506dKFpfnL9Nq1awfAzvwt0wcNGkRcXBwpKSnUrFmTwMBAFi1aBECrVq1wdnZm69atAAQFBbFjxw7OnDlDtWrV6N+/PxEREQD4+fnh4uICwIIFC+jfvz/79+/n5MmTVKlShZCQEMLDwwHw8fGhbt26hRsA9O7dm8OHD3P8+HEqV67MsGHDiIiIIDc3l6ZNm9KwYcPCbTt79OhBUlJS4XgycuRIFi5cSHZ2Ng0bNuT48eOY8nfy6tatGykpKRzIr3EzcuRIli1bxqVLl/Dw8KBly5asWrUKgM6dO5Oens6+ffsACAsLY/Xq1aSlpVGvXj06duzI8uXLAejQoQM5OTnszt8NLDQ0lA0bNrBv3z5atmxJQEAAixcvBqBt27aYzWZ27NgBQHBwMPHx8SQnJ+Pm5kafPn1YuHAhAC1btqRKlSrE5xfhGjBgALt27eLUqVO4uroSFBTE/PnzAfD19aVWrVps3rwZgL59+xIZGUn16tVxcXEhNDSUuXPnomka99xzD/Xr1yc2NhaAXr16cezYMY4ePYqjoyNhYWEsWLCAnJwcmjRpQuPGjVm/fj0A3bt358yZMxw6dAiTycSoUaOIiooiMzMTLy8vfH19C9/DxMRE0tPTSUhIAGDEiBFER0eTnp5OgwYNaNOmDSvykyj+/v5kZGSwd+9egJvGiLAwfxwcolm/vinLl7fF3/8ikZFCJyQkhNjYjaSmXh0jvvrqK+666y6rxogWLVrg6upa6jEiOTmZ5557rsgxAiAwMJDExESOHDmCg4MDw4cPJzIyksuXL9OoUSO8vb1Z9/DD1O7cmR5r1+IcGwtff80WTaPz118XOUYAdOnSBYvFwtq1a7nrrrsYPnw4K1cWb4wYMmQIMTExpRoj8vJnaR45cqRw/L7TGOHm5kZcXBwA/fr1K/UYceLECbp162bVGOHj48OaNWtKPUY4Ojri4uJi1RiRmppK7dq1bTJGnD59mscee8yqMSIhIYETJ06Uaozwyk96LliwALPZXKwx4rfffgOga9eupKamlnqMOH/+PA8//LDd7yOKGiPmz5+Pm5ubze4jij1GrFsHQG5uLn5+fne8j7h2jNi/fz9AqcaIDh06FPpe8Nge9xG3GyOuXLlCdv50VnveRxQ1RsTExHDXXXfZ/T7iVmPEli1bCr/o2/M+4sYxIjIystBrT09Pu91H3G6M+N///oe7u7vV9xG2+K5x+vRpnnjiCbvfRxQ1Rhw8eJBKlSoB1o0RAQEBJCcnl2qMsFgsAIX3GGCf+wgoeoz49ddfqVGjhi73EUWNEVeuXMHHx8fu9xFFjRHffvstd911ly73EXD9GKE7WglITEzUmjVrppnNZs1sNmsmk0kzmUyFfzdq1EiLiYm57TX27t1beI6i/GCxWDRAS05ONqwNv/76q/1Fhg7VNLNZ00QK6fY/ZrM43goOH9a0Nm3E6ZUqadq0aZqWl3fn83SJvQiysrK0yZMna1lZWYboa5pxsRutbaS+vX3PyNC08+ev/r19u6Y1b65p8+Zp2pUr4rkK5fvvv2vaQw9p2uXLV5/bvFnTTp/WR7+YqP6u+rtRKN/1R/mufDcKWX03Utto32Xtb0ZrJycna4BmsVh00bN6MeCVK1cYNmwYBw8eRNM0HB0d6dixI61ataJSpUpomkZiYiJ9+vRh6tSpts+IKaRHlyWV585drbV0J/LyIDXVqss3bQqbN4sdzq9cgRdeEHWE71T4WOblpEbGbvT7brS+vXBxEStMC5g6Ff76C0aOhHbtRHkzL68K5HuPHmKNoKOj+PvyZRg9WgwIL78M//xjX/1yhOrvcqJ8lxPlu5zI6rvyXE59o2PXE6sTTBEREWzbtg2TycSIESM4deoU8fHx7Nq1i6SkJF588UUcHBzIy8vjtdde45VXXrFHuxUS4+PjY3+R2rWhuMXYzGax05yVVKkivmt+/rnYsO7XX6FLFzhy5Nbn6BJ7GcXI2I1+343W14uvvxb1mapXh927RQ39Z5/1Z/VqMV1Qb+z+vp89C3fdBZmZYmu9Jk3g9ddFglsP/TKM6u9yonyXE+W7nMjqu/JcTn2jY9cTqxNMc+fOBcR6zfDwcGpd88W6Tp06TJ06ldjYWDw9PdE0jU8++YSnnnrKdi1WSE/B2li7Ehpq3QymIUNKJGMywbPPwrp1ULeu+FLdoQOsXFn08brEXkYxMnaj33ej9fWienV4+204elTkWapUgZ07Hbn/fhg1Sv/22P199/ISUxmjo6FjR7h0SewE0LgxvPUWv+fXjZAR1d/lRPkuJ8p3OZHVd+W5nPpGx64nVieYtm/fjslk4tlnny0suHsjnTt3ZuvWrbRv3x5N0/jmm2948MEHCwtEKxRlnuHDoWZNkQG6E2azWM9TCnr0gB07oHNnuHABgoJgypTi57gUiopErVrw3/+KRNOAAQk4OYk+UoAxe5/aCZMJBgyA+HhYvBjatIH0dHj/fdzyd1pVKBQKhUKhUCjKA1YnmFJSUgBo3rz5bY+rV68eMTExBAYGomkac+fOZdiwYeTk5JSspQpFPt26dbO/iLMz/PijeHyrJFPB83l5EBAA+TsJlBQPD/j9d3jySfEF+s03YehQSEu7eowusZdRjIzd6PfdaH2jqFsXZs6swuHD8MQTV5+fOxeCg0VS1p7o+r6bTDB4sAgqMhImTqTZY49dfX3tWrh4Ub/2GIzq73KifJcT5bucyOq78lxOfaNj1xOrE0wF2ypmZWXd8VhXV1dWrFhBcHAwmqaxdOlSgoODyczMtL6lCkU+BUlOuzNoEERFXa1CXFCTqeB3jRrw/fdw771Xpx19/HGpplc4OcHMmfDtt1C5spjQ4O8vCh+DjrGXQYyM3ej33Wh9I0lJScHDQ/QNEN3r/fdh+XKxnHTYMMjfydgu2rpjNovM8hdfXNU/c0aMR02bikroly7p3y6dUf1dTpTvcqJ8lxNZfVeey6lvdOx6YnWCydPTE4BDhw4V63gnJycWLVrEyJEj0TSNNWvWcP/995N27bQMhcIKDhw4oJ/Y4MFw6pSoxh0aytnmzUV9pjlzxPNjx0JMDDz2mJjJ9PLL8PDDomhvKXj8cdi4ETw94cABkWRauFDn2MsYRsZu9PtutL6R3Bi7yQSLFsEDD4jHCxdC69ZiR8aDB+2rrTeF+idOiMEgJQVeeUUkmqZNK/U4U5ZR/V1OlO9yonyXE1l9V57LqW907HpidYKpbdu2aJrGunXrin1OpUqV+PXXX3n88cfRNI1NmzYxcuRIa6UVCmNwdoaHHoLISNa99ZZYvvLQQ+J5EFMrvv0Wpk8X28H98gt07y6+FJaCTp1g+3YIDBQlWYYNg7lz26BKmSlkx8dHdLM9e0S/0DSxC6OfH/zf/xndOjvQqRPs3y9mTDZpAsnJMGkSeHvDl19CMWYUKxQKhUKhUCgUdkezkq+++kozmUxatWrVtPT0dGtP11544QXNZDJpZrO58Lei/GCxWDRAS05ONqwNV65cKbva69ZpWu3amgaaVreupsXGllozJ0fTJk0SlwRN69tX01JSSn1Zq8jKytImT56sZWVl6St8DWXa9wqqX158375d0wYOFP3jt9/01bYnRepfvqxp33yjaQ0bioCdnDTt5Emb6pYX3yuitpH6ynflu1Eo3/VH+S6nttG+y9rfjNZOTk7WAM1iseiiZ/UMpoEDB2Iymbh06RJfffWV1QmtTz/9lLfffhutQm0DpNCTZcuWlV3tXr1g2zaxZic5GXr3hlmzSqXp4ACffALh4eDklMtvv4kdzXfuLNVlyx1l2vcKrm8kxYm9fXtYtgx274Y+fa4+/8EHYqJPcrL9tO1JkfqOjqLi+aFD8NVX8PbbYoeAAlasgAqwmYbq73KifJcT5bucyOq78lxOfaNj1xOrE0xeXl68+eabPPbYY5w7d65EopMnT+bzzz+nZ8+e9Lh272mFohhcMrDAbbG0GzeGzZth+HDxRe/JJ2HCBLh8uVTao0bBu+/+hrc3HDsGXbuKUlCyUOZ9r8D6RmJN7K1aXd3c8cIFkWCaNk2sKvv3vyE11X7a9uC2+pUrw1NPicAKiI8Xmw00awY//AC5uXZvo71Q/V1OlO9yonyXE1l9V57LqW907HpidYIJ4N133+Wbb77hgw8+KLHwxIkTWb9+PevXry/xNRRy4nHt/9aXVe2qVWHePJgyRXzjnTkT7ruv5FMp8unSpSpbt4rvkFlZMGYMPPtshZiwcEfKhe8VVN9IShq7mxssWCDKF2VkiGRTkybw7rtgsdhX21ZYrX/qFNStC0ePwqOPiqJUv/xCeSzcpvq7nCjf5UT5Liey+q48l1Pf6Nj1pEQJJoXCSFq2bFk+tE0mMbtgyRKoVg1iY8Xath07SqVfsyYsXSpWxoCoLd67t9jJvCJTbnyvgPpGUtLYTSbo1w+2bBFdsE0bSEuDyZNFomn58qLPy8oSMwOHDYN//7sLw4aJv42oo2117KGhcOQIfPQR1K4tltE99BC0bCkS3nl5dmmnPVD9XU6U73KifJcTWX1Xnsupb3TseqISTIpyx6pVq8qXdnCwWLri4yN2luvWTRRUKoW+2SxmYixZAtWrw8aNog5NXFyJLlsuKHe+VyB9Iylt7CYTDBok8rrz54OvL1y8CM2b33zskiXQoIGYGRgVBZs2ORIVJf5u0EAkdvWkRLFXrQovvyxmMf33v1CzJiQkwIsvlnqZrp6o/i4nync5Ub7Liay+K8/l1Dc6dj1xsNWFjh8/zl9//cWJEydIT08nMzMTFxcXXF1d8fLyonnz5jRq1MhWcgpF+cLXV0yleOABUYT3gQfgzz/FF8BKlUp82UGDYOtWGDJE7GLesyd88YUo+1RQi0ahUIik7PDhMHSo6DNNm1597YUXxAylr7+++lzBZJ+C3xcuQEiISDwNHqxXq0tBtWrw+uvwzDPw+efQsCE4O4vXrlyBNWvEFK9rB4qsLIiIwGHhQsbs3InDn3+KN2z48KvnKhQKhUKhUCgUt6BUCaajR4/y2WefERUVxcmTJ+94vIeHB6GhoTz33HN4e3uXRlohMZ07dy6f2jVqiCkQb74JH34olrHs3g2//ipmGZRQ38cH/vgDHntM1JyZMEFMmPrf/yrWd8Jy63sF0DcSW8deqRLce+/Vv/fsgc8+u/N5miZyMWPHilJHevQtm8RevTq89db1z4WHw8MPiyW7770H/fuLsWnsWDh/HrPZTJO8PLQTJ0RG7bnn4McfRUZbJ1R/lxPlu5wo3+VEVt+V53LqGx27npR4idzbb7+Nr68vX375JSdOnEDTtDv+nDx5khkzZuDn58dbN97wKhTFJD09vfxqV6okqg2Hh4OLC6xcCZ07w19/lUq/WjWx/Oejj8RMje+/h+7dITGxdM0tS5Rr38u5vpHYO3YfH5FrKQ6aBufPi0SuHtgt9vPnxVK6bdvEjgG+vqJ+04ULAJjyp22Zbpy+tWSJfdpTBKq/y4nyXU6U73Iiq+/Kczn1jY5dT0qUYJowYQJTpkwhJycHTdNo1qwZ48eP59NPPyUiIoLo6GjWrl1LdHQ0ERERfPrpp4wfPx5fX180TSMnJ4f//ve/PPnkk7aORyEB+/btK//ao0bBpk1i2cqhQyLJVIwCL7fTN5lE6ZVVq0R9323boEMHWLfONk02mgrheznVNxJ7x+7kBJcuicRscTCbYdEiuzapELvFPnGiqNH08stiKtbBgyJ7pmlFH1/w/NixulU7V/1dTpTvcqJ8lxNZfVeey6lvdOx6YvUSuVWrVvH1119jMpno2LEj06dPt2rK1x9//MGzzz7Ltm3b+Pbbbxk2bBj9+vWzthkKRfmnXTtRDGb4cNiwQcwQeO89eOONUhVQuu8+kVwaNkwUNu7bF/7v/0SNX1WXSaG4mXPnir/BWl4epKbatz26UKeOmPLo5QXPPnvn46+dvvXQQ/Zvn0KhUCgUCoWi3GF1gmnWrFkAtGvXjt9//x0XFxerzr/33nvZsGED3bp1488//2TmzJkqwVQOmDFjBjNmzODKlSsAREVF4erqytChQ1m7di0Wi4W6devi7+/PsmXLAGjfvj15eXn8+eefAISEhLBx40bOnTtHrVq16NGjB1FRUQC0bt0aR0dHtm/fDsDAgQPZtm0bZ8+epXr16vTr148F+etSfH19OXLkCFu2bAHg/vvvZ+/evSQlJVG1alWCg4OZN28eAM2aNcPd3Z1NmzYBcN9993Hw4EESExNxcnJi6NChzJs3j7y8PLy9vfHw8GDDhg0ABAYGkpiYyJEjR3BwcGD48OE4ODgQHh5Oo0aN8Pb2Zl3+9KCAgACSk5M5ePAgAKNHj2bx4sVkZGTg6emJn58fq1evBqBLly5YLBb2798PwPCVKzkZFkbj6Gh46y1ytm4lKjSUXGdnOnXqRFZWFnv27AEgODiYlStXcv78edzd3enSpQtL82c+tWvXDoCdO3cCsHLlIB58MI3ffmvAyy/DH39cYeDAhTg759KqVSucnZ3ZunUrAEFBQezYsYMzZ85QrVo1+vfvT0REBAB+fn6F/XzBggX079+f/fv3c/LkSapUqUJISAjh+bvi+fj4ULduXTZu3AhA7969OXz4MMePH6dy5coMGzaMiIgIcnNzadq0KQ0bNiQmJgaAHj16kJSUxOHDhzGbzYwcOZKFCxeSnZ1Nw4YN6dmzZ6FOt27dSElJ4cCBAwCMHDmSZcuWcenSJTw8PGjZsmXhbg2dO3cmPT298H8OwsLCWL16NWlpadSrV4+OHTuyPH/P+g4dOpCTk8Pu3bsBCA0NZcOGDWiaxurVqwkICGDx4sUAtG3bFrPZzI4dOwq9iY+PJzk5GTc3N/r06cPChQsBsTVplSpViI+PB2DAgAHs2rWLU6dO4erqSlBQEPPnzy/8fNeqVYvNmzcD0LdvXzw8PAgPD8fFxYXQ0FDmzp2Lpmncc8891K9fn9jYWAB69erFsWPHOHr0KI6OjoSFhbFgwQJycnJo0qQJjRs3Zv369QB0796dM2fOcOjQIUwmE6NGjSIqKorMzEy8vLzw9fUtfA8TExNJT08nISEBgBEjRhAdHU16ejoNGjSgTZs2rFixAgB/f38yMjLYu3cvQKnHCE3TCA8Pt2qMaNGiBa6ursUeI1xcfDGZnNG04kxj0jh9+h9+/XUtvXrdPEZERkZy+fJlm4wRBbEPHz6clStXcvHiRerXr0/79u2Jjo4GuGmMGDJkCDExMcUaIwYNGsSl+fOpYzJhvtXspWsjN5k4+cUX7KpR46Yxws3Njbj8bSz79etX6jFC0zS2bNli1Rjh4+PDmjVrgNKNESEhISxfvtyqMSI1NZXatWvbZIzQNI0LFy5YNUYkJCRw4sSJUo0RXl5egBjnzWZzscaI3377DYCuXbuSmppa6jHC3d2dixcv2v0+oqgxon79+oSHh9v9PuJWY8S9997L9u3bS3YfUYoxokOHDoW+Fzy+doyIi4sjJSWFmjVrEhgYyKL8KZzW3kfcbowICwvT5T6iqDGiYJy1933ErcaINm3aFMZuz/uIG8eIyMjIQq89PT3tdh9xuzGiSpUqhIeH2/0+oqgxQtM00tLSbHYfYc0Y0bVr10LPrRkjSvVdI3+MsFgsAFgsFtauXQuU/j7CmjGibt26hIeHWz1G2Oq7RteuXYmPj7f7fURRY0TBWKPHfQRcP0bojmYlnp6emtls1ubNm2ftqdcxb948zWQyaZ6enqW6jkJfLBaLBmjJycmGtWHZsmUVU3vWLE1zdBQLVVq10rQjR0qtn5enaTNmaJqDg7hsy5aadvCg9U3LysrSJk+erGVlZVl/so2osL6XYX1ZfP/pp4L1YcX/8fPTtK++0rT0dPu1Sxffe/a0LvDAQPu3SVP93Qhk6e9lUdtIfeW78t0oZPXdSG2jfZe1vxmtnZycrAGaxWLRRc/qGkz//PMPQKl3gSs4PyUlpVTXUchHWlpaxdQeNw7Wr4d69cTWVh073lRAyVp9kwmefhpiYqB+fdi7Fzp1gvz/+ClXVFjfy4G+kegR+/DhYiPHOy0hNZlEzaYqVWD/frFjo4cHTJpkn4L6uvheu3bxC1ABHD4slvbaGdXf5UT5LifKdzmR1XfluZz6RseuJ1YnmOrUqQPA4cOHSyVccL67u3uprqOQj3r16lVc7W7dRAGljh1FoZd+/eCLLwqL7JZUv1s3UY+pa1ewWMRu4+++W/y6M2WBCu17Gdc3Ej1id3aGH38Uj2+VZCp4PiICTp2Czz6Du+8W/WnaNJF3sTW6+B4aat1AcOIE+PuLYm/FWFZXUlR/lxPlu5wo3+VEVt+V53LqGx27nlidYPL390fTNKZOnUp2dnaJRLOysvi///s/TCYTnTp1KtE1FPLSsWPHiq3t6SmKfj/8MFy5As89B489BllZpdK/6y4xQeqZZ8TfkyeLuuL5O5OXeSq872VY30j0in3QIIiKgho1xN8Fk3oKfteoAYsXi+Pc3ES3PHAAoqPFTKbAwKvX+vRT+PJLuHixdG3SJXZrpm9VqwajR4Ojo8iuXXvO+fM2bZbq73KifJcT5bucyOq78lxOfaNj1xOrE0zjxo0DYMeOHfTs2bOwcFdxiY+Pp2fPnoXFwcaPH29tExSSU1BIsUJru7iIKRWffiq+4f7wAwQGsu7nn0t12cqVxRffH34QszaWLROTEfLrKJZppPC9jOobiZ6xDx4sZifNmSMm9jRvfpbQUPH3qVMiuXQtZjMMGAD/+9/VXEt6utgMcuJEsXzu2Wchvx6n1egSuzXTt375BX79VawHfPvtq69v2SIy2I89BvmFVkuL6u9yonyXE+W7nMjqu/JcTn2jY9cTq3eR69+/P+PGjeObb75h69at3Hvvvfj6+tKzZ098fX3x9PTE1dWVypUrc/nyZdLT0zl58iQJCQn8/vvvhbsHADz22GP079/fpgEpFBUGkwleeAFatoSRI2HLFvodOADt28O995bq0o88Aq1awZAhcOiQuNx338GIETZqu0JRTnF2hoceEj/h4esYPXq0VedXqgRTpsD06WKG0/Tp4qd/f5F06t/fupJHulAwfWvsWDh/Hs1sxpSXV/ibGjVEEqogw1a//vXnL10K2dnw/ffip0cPkVkLCQEHq28zFAqFQqFQKBTllBLd+X399de4u7szdepUcnNzSUhIuC5xdDs0TcPBwYGXXnqJKVOmlEReITkF2+hKo923ryiqGxJClX37oGdPmDkTHn20VJdt3x62b4dRo2DtWpHD2roVPvigbH4nlM73MqRvJOXNdxcXsQx1wgRYs0Ykl5Yvh5Urxc9778Fbb9lPv8QUTN9asIC8yEgS//yThm3bUmnYMAgLE5m3W/Gf/8DAgfD557BggVjiu2EDNGwo3oxnn739+UVQ3nyvSPpGonyXE+W7nMjqu/JcTn2jY9eTEv8/6pQpU/jrr7+YMGECDRo0QNO0O/7cddddTJgwgX379vHf//4X051qPigURZCTkyOftrc3xMWR1rs3XL4slqI8+yyUsj3u7uJL76uvir8//hjuvx/yN4skK0ssDxo1yoHvvx/DqFEOzJkjntcbKX0vI/pGUl59N5tFjf6lS8UswUmToFYtePDBq8fs3y9+7KFfIvKnb+XOnctPY8eSO3eumMp1p+SQyQRdusDcuXDsGLzxhhhcEhNhxowSZazLq+8VQd9IlO9yonyXE1l9V57LqW907HpSqon63t7ezJgxgxMnTnD48GGWLVvGV199xUcffcR7773HRx99xFdffcXSpUs5fPgwJ0+eZMaMGdxzzz22ar9CQnbv3i2lNtWqsfyxx0R1bhBTI+6/H1JSSnVZBwf48EOxO1bVqrBundjE7pNPoEEDGDMGliwxc/x4E5YsMTNmjHh+6dLSh2QN0vpeBvSNpCL47u0t+tPp09C06dXn33gDWrQQkxSXLBE1/e2hryuenvD++yK59N13Yr1gQYIpJ0dMmVy69OZgb6Ai+F5e9Y1E+S4nync5kdV35bmc+kbHric2WwjTpEkTmjRpYqvLKRSKojCb4Z13oE0bscvc+vXQqZPY3qp161JdOiwMmje/WpfppZeuvpaXZ7ru94ULorxKVJRYWaNQKO5M5cpXH1+5Iuo1mc1iKd2aNdCkCTz9NDz+uNjYrVzj4nLzMt7ISJg3T/w0bSqKUj36qNiWT6FQKBQKhUJR7ilrpUYVijsSGhoqpfZ1+qGh8McfYmrEsWNieUpERKmv36IFxMaKXchvh6aJ32PH6rdcTvkuJxXV90qVRLmiw4fh5ZdFQunoUfHYw0NMAqpwvnftKgKsUQOOHBGbGHh6ikTTDVvtVVTfy4O+kSjf5UT5Liey+q48l1Pf6Nj1RCWYFOWODRs2SKl9k36LFhAfL9bXZGSILeDefBPy8kqlsXp18Uo7aRqcPy++JOuB8l1OKrrvjRvDRx/ByZPwzTdiImJmpsjBFOjn5EBurt2bYn8aNrwa7MyZ4OcH6enw5ZfQrBn8/XfhoRXd97KsbyTKdzlRvsuJrL4rz+XUNzp2PVEJJkW5IzU1VUrtIvVr1YLoaFFBGES9k5AQsFhKrBEVVfxt1M1mWLSoxFJWoXyXE1l8r1IFnngC/vwTfv8dHnnkqv5PP4nJiv/3f3DunG5Nsh9Vq8KTT8LevfDbbzBoEPToAXffXXiIY2wsXLxoSPOM7m9G6xuJLP29LOobifJdTmT1XXkup77RsetJqRJMmzZt4oUXXmDw4MGEhoby2muvsWPHjmKde+jQIZo2bYq3t3dpmqCQkNq1a0upfUt9BwdRQfinn8DJCZYtg3vvvWnJSXE5d674k6Dy8kCv8VL5Liey+W4yiVxLtWpX9X/9VdTMfu01saLs8cdFIqrcYzLBffeJCue//Xb1+ZQUek6dKoKdNEksp9MRo/ub0fpGIlt/L0v6RqJ8lxNZfVeey6lvdOx6UqIEU05ODg899BA9evTgiy++YPny5SxdupSpU6fSqVMnhg8fzj8F+5zfgsuXL3Ps2DGOHTtWkiYoJCYgIEBK7TvqP/ywKKDk4QEJCeDvDytWWK1Ru7Z1M5hq1bJaokQo3+VE+Q7Ll8P330O7dqLm2Xfficfdu+u3RNXuXFsB/dgxTA0bQloaTJsmZjaFhMDatVcLwNmRsuK7jKj+LifKdzmR1XfluZz6RseuJyVKMD3xxBP8+uuvaJpW5M/ChQtp3bo1GzdutHV7FQoWL14spXax9Dt1gm3bRDFdiwUGDhQ1T6z4UhYaat0Mprp1dfnOp3yXFOU7ODuLgvrbt8PGjTBypJi4uHEjfPutoU20Dx07Mm/yZLH89/77xQCzZImY7dSqlXgj7EhZ8V1GVH+XE+W7nMjqu/JcTn2jY9cTqxNMGzduZM6cOZhMJnx8fFi6dCkXL17k3LlzREZG4u/vj6ZpnD17ln79+rFkyRJ7tFuhUNyK+vVh3ToYN058MXv1VXjwQVEIvBgMHy52tDKZiic3c6ZY0rNrVynarFAo7ojJBN26wdy5YvPIt94Sm7IVkJQkElHbthnVQhtiNsOAAbByJfz1Fzz9tKjddOiQWDpXQIWofq5QKBQKhUJRMbA6wTR79mwAPDw82Lx5MwMHDqRq1arUrFmTIUOGEBcXx9SpU3FwcCArK4uwsDB++eUXmzdcIS9t27aVUtsqfScn+Ppr+N//xFSH8HAICBCFXO6AszP8+KN4fKskk8kkfh56CFxcxEyK9u3FbuPnzxevidaifJcT5XvReHjAe+9Bnz5Xn5s5U/TdTp3EJMbwcLh82f7ttAfXxe7rCzNmiN3noqKgXr2rrw0YAGFhYnmwjaZSlmXfKzqqv8uJ8l1OZPVdeS6nvtGx64nVCabNmzdjMpl48cUXqVVE8ZWC13777Tdq1qxJbm4ujzzyCDNnzrRJgxUKc3ELBFUwbav1TSaYMEHULXF3h507oWNHKMY2mYMGie9xNWoU6GrX/a5RAxYvhjlzRLmn4cPFcrkvvwQfH5g9u/jL7IqL8l1OlO/FJyRETFZ0dIS4OHjgAWjUCN59F86csVMj7USRsdeoIRJKBRw5AmvWQGSkmEbZoQP88IMoVGVrbR0xWt9IVH+XE+W7nMjqu/JcTn2jY9cTqyM9deoUAF26dLntcT179mTDhg00aNCAvLw8nnnmGT7++OOStVKhuIbi7lRY0bRLrN+jh1gz07Yt/POPmPLw1Vd3/N/+wYPh1CmRRBo8OI/GjY8yeHAec+aI5wcNEsc1bAjz54vvec2bQ0qK2G793nth61brm3srlO9yonwvPh07ws8/i4mKkyeL1bJnzojHfn53zrtkZYn+PmqUA99/P4ZRoxyYM6fU+ZoSUazYmzaFPXvEcmBnZ5FEf/RRMSi99ZYYqOylbUeM1jcS1d/lRPkuJ7L6rjyXU9/o2PXEwdoTcnJyAKhUqdIdj23RogWxsbHcd999HD16lFdffZWLFy/y7rvvWt9ShaHMmDGDGTNmcOXKFQCioqJwdXVl6NChrF27FovFQt26dfH392fZsmUAtG/fnry8PP7M3087JCSEjRs3cu7cOWrVqkWPHj2IiooCoHXr1jg6OrI9v3jrwIED2bZtG2fPnqV69er069ePBfnbJaWlpXHkyBG2bNkCwP3338/evXtJSkqiatWqBAcHM2/ePACaNWuGu7s7mzZtAuC+++7j4MGDJCYm4uTkxNChQ5k3bx55eXl4e3vj4eHBhvwZPoGBgSQmJnLkyBEcHBwYPnw4p0+fJjw8nEaNGuHt7c26desAsTNAcnIyBw8eBGD06NEsXryYjIwMPD098fPzY/Xq1YBIzlosFvbv3w/A8OHDWblyJRcvXqR+/fq0b9+e6OhoADp16kRWVhZ79uwB4MqVK6xcuZLz58/j7u5Oly5dWLp0KQDt2rUDYOfOnQAMGjSIuLg4UlJSqFmzJoFr13J24EAa/fEHPP00lt9/Z+XAgeQ5OBAUFMSOHTs4c+YM1apVo3///kRERADQqpUf/v4uhIeHc/fdd9O/f3+2bt3PyZMnqVKlCiEhIYSHhwPw/fc+LF/elI8/dmXrVkc6d9YIDk5m4MBNuLtrDBs2jIiICHJzc2natCkNGzYkJiYGgB49epCUlMThw4cxm82MHDmShQsXkp2dTcOGDcnOzi7U6datGykpKRw4cACAkSNHsmzZMi5duoSHhwctW7Zk1apVAHTu3Jn09HT27dsHQFhYGKtXryYtLY169erRsWNHli9fDkCHDh3Iyclh9+7dAISGhrJhwwaSkpJYvXo1AQEBhUX62rZti9lsLvwHIzg4mPj4eJKTk3Fzc6NPnz4sXLgQgJYtW1KlShXi4+MBGDBgALt27eLUqVO4uroSFBTE/PnzAfD19aVWrVps3rwZgL59+5Kamkp4eDguLi6EhoYyd+5cNE3jnnvuoX79+sTGxgLQq1cvjh07xtGjR3F0dCQsLIwFCxaQk5NDkyZNaNy4MevXrwege/funDlzhkOHDmEymRg1ahRRUVFkZmbi5eWFr69v4XuYmJhIeno6CQkJAIwYMYLo6GjS09Np0KABbdq0YUX+joX+/v5kZGSwd+9egFKPEUlJSYSHh1s1RrRo0QJXV9dSjxGnT58GsGqMiIyM5PLlyzYZIwpit2aMGDJkCH/+GYOPz3lmz67D2bMBfPDBRRo2vMCxY1cKx4jt2z14/fX27NgRl9+XfPj88/ZcuGDCZDKhaU04cUIjKgomTLjMt9/mUK9efJFjhJ+fH25ubsTFxQHQr18/9u8veozw8fGhbt26hZuA9O7dm8OHD3P8+HEqV65cOEYkJSWxZcuWO48RBw+S3asXTUNDaREXh+mrr6j6zz/w/vscc3Iiztvb6jEiLy+P5cuXWzVGpKamUrt2bZuMEUlJSVy4cMGqMSIhIYETJ06Uaozw8vICYMGCBZjN5mKNEb/99hsAXbt2JTU1tdRjREpKChcvXrT7fURRY8S5c+cIDw+3+33ErcaIzMxMtm/fbvf7iCFDhhATE1N4H9GhQ4dC3wse3/I+IjCQRYsWAdCqVSucnZ3Zmv8/Sbe7j7jTGAFYPUaU5D7Cx8eHNWvWAFfvIwrGWXvfR9xqjEhPTy+M3Z73ETeOEZGRkYVee3p62u0+4nZjxNmzZwkPD7f7fURRY0RSUhJpaWl2v48oaozIysoq9Nze9xE3jhEWiwUAi8XC2rVrgTuPEVZ917jDGJGSkkJ4eLgu9xFFjRFZWVnEx8dbNUbY6rtGwVijx30EXD9G6I5mJV5eXprZbNYWLlxY7HOSkpI0Pz8/zWQyaWazWZs0aZK2d+/ewr8V5QeLxaIBWnJysmFtSEtLk1LbJvp5eZr24YeaZjJpGmhat26adubMHU/LysrSJk+erGVlZRVL5tQpTXv4YSEBmlajhqZ9+aWm5eSUvOnKd/2x1nd7oHy3DdnZVx//8Yfol3Xratpbb2na99+LIaFgWLjxp+C1xYtt1pw7UuLYc3I0LSJC00JCNO3az+3cuZr288/XvxHXkpmpaT/9pGlDh2o5AQGaNnSo+Dszs2TtKAWqv8unbaS+8l35bhSy+m6kttG+y9rfjNZOTk7WAM1iseiiZ/USuZYtWwIUZrqLQ4MGDdiwYQPt2rVD0zQ+++wznn/+eWulFQqAwsysbNo20TeZxK5yy5aBmxts2iTW1dh426m77oKffhJ1d9u0gQsX4F//ElL5/+FgNcp3OVG+24bKla8+PntWFAlPTob//EesKitIJxVFwfNjx+q3XK7EsTs4iKLfUVFiswOAK1fg9dfFrgSNGonq6GfPXj1nyRJo0ADGjIGoKBw2bhTnjxkjns//n1u9MPpzZySqv8uJ8l1OZPVdeS6nvtGx64nVCabu3bujaRoRERFoVuzYUrt2bdavX0/Xrl3RNK1wup9CYS3JyclSattUPygI4uPF7kwnT0L37qJ4i40JCIDt28UGUDVrwq5dQurhhyF/9VGxUb7LifLd9gweDEePitppPj7FO0fTxA6R+asH7I5NY798GR57TGS+z5yBd94RdZoeeQSmTYPQUJEFh6u7ExT8vnBBVE9fssR27bkDRn/ujET1dzlRvsuJrL4rz+XUNzp2PbE6wdS/f39AFPsuWPNXXKpXr85vv/1G3759rUpOKRTX4ubmJqW2zfV9fOCPPyA4WExLePhheOklyM21nQZQqRI8/TQcPAjjx4tJVD//LOQ/+QTyy7rdEeW7nCjf7YOjo9j9sWVLKO7GJmYz5JdWsDs2jd3FBd58E44dg19/hc6dRdLpp59g0qQyN33L6M+dkaj+LifKdzmR1XfluZz6RseuJ1YnmNq1a0f37t1p2rQpP/74o9WCLi4uLFu2jCFDhlh9rkIB0KdPHym17aLv5gaLF8Mbb4i/P/lEzG5KTRV/528r5TBqFGO+/x6HUaMo6bZS7u7w9ddi4lTnzvw/e+cdFtXRNfDfLiCIKIiIvTfsXWONJfYCokRNjDHV9F7Ml+SNyZu8Mb2aYppKEiyoiF1jb7F3ROwFC6ICIoLg3u+Pw7KgVGH3gnd+z3Ofhd3Ze2b27Mzee+YUEhPFntWypVSgywuld2Oi9G5fLl2yOevkhcViWxrsjV3GXqoUjB4thvV//4U8quFm4GD3Lb2/d3qi5rsxUXo3JkbVu9K5MeXrPXZHUmADE8DatWs5fPgw4XfoMu7i4sKcOXOwWCwZVckUivxSUM+5u0W23eSbzfDhhxIv4+4OK1ZAhw7w/fcZeUnM4eHUOXkSc3h4ofOStGsHmzbBb79BxYpw8CD06SPeFKdO5fw+pXdjovRuXypUyL8HE8DevRLyGhtrvz6BA8besaOEzBVD9y29v3d6oua7MVF6NyZG1bvSuTHl6z12R3JHBiaFQnEXEhQklp9ateDoUXj++Yy8JKZ0FwdTEeUlMZslJcqhQyLGbBbnAD8/+OgjxyUSViiMTkBA/j2YQDyYnntObDO//263bjmG4uq+pVAoFAqFQlFCUQYmRYnDWsnQaLIdIr9lSynz5uws/9s5L0n58vDtt7BrF3TvDtevS6qUZs1g0aKsbZXejYnSu30JCpJ5aDLl3s5kkojaTz+Ftm0lVVu7drbX9+6F1asLZqzKDYd89gV13zp0yH59yYTe3zs9UfPdmCi9GxOj6l3p3Jjy9R67I1EGJkWJw93d3ZCyHSZ/9er8JfouwrwkLVrAmjWSf7dqVXGgGjwYhgyRv0Hp3agovdsXNzewplPMychkfT44GF5/HbZvl6T9LVrY2nz6KfTqJQ6QEybA/v2F65dDPvuCum+1bWv7Oy0NFi7Mf5WCAqD3905P1Hw3JkrvxsSoelc6N6Z8vcfuSJSBSVHi2Lp1qyFlO0x+WJgueUlMJsm/GxkJb7whTlQLF0KTJvDuu7B+/Y4ikXMnGELvxRQ13+3PkCEy7b285H+zWcvy6OUltQCGDLG9p0GDrOfw9ZV2Z87AJ59A8+bQqhV8/jmcPVvwPjlk7AV13/rhB9tzy5fLB1KtGrz8MuzZU2Td0vt7pydqvhsTpXdjYlS9K50bU77eY3ckysCkUCiyonNekrJl5QZ13z5J/n3jhuQgf/31QcyZk3PUnkKhuHOGDhVDUHAwDB1qoXbt4wwdaiE4WJ7PbFzKji+/hHPnYM4ccQxycRGby+uvQ9++DhlCwSmo+1aNGrbnL18Wq9rFi/D112JNa91a/o6JsWOnFQqFQqFQKIovysCkKHEMGDDAkLIdJr8geUnMZvD2tks3/Pxg2TKYOxdq1oTY2DKMGCE3qwcP2kVkjhhC78UUNd8dh5sbjBkDM2akMW7cdGbMSGPMGHk+v+8PDBSnxvPn4aefoEsXePBBW5ukJHj4YVi8OPfoMoeN/Xb3rayP2blvgXxQZ85INc0RI6BUKdi9W7yZqlWDY8fuuEt6f+/0RM13Y6L0bkyMqnelc2PK13vsjkQZmBQljj1FGIpQkmQ7TH5B8pJYLNC1q926YjLBsGFiUHr44RO4usI//0jul9dfh4QEu4nOgiH0XkxR871k4u0N48dLzYAJE2zPh4fD9OkwaJDYYV54AbZtu90z0aFjz+y+FRBAXKtWsg7m5b7l4iLJ4mbPFvetyZOhfXto3Bjq1LG1+/NP2LEj3+6XJVnvhUXNd2Oi9G5MjKp3pXNjytd77I5EGZgUJY6zd5LQ4y6Q7TD5+c1LYuX//g8mTZJYNjvh7g79+m0mIkLuBdPSJLeLnx/89Zf9w+YMofdiiprvJZ/MS0nLlmJUqlhRosu++w46dBCbzIcf2qLLHD52q/vWnDkseeMNifUriPuWtzc88wxs3SpWNeugExPhqaek5F7z5rJwnTuX66nuFr3fCWq+GxOld2NiVL0rnRtTvt5jdyTKwKQocXh4eBhStsPk5zcvickEzZpBcjK89Ra0aQPr19utWx4eHtStK9EqixZB/fpynzZmDHTvXqQ5drOVrSd6y9cTNd/vLho3hm++gehoCZMbPRpKl4ZDhySZ/9Wr0s7Dw0O3fGuF/tzLlbP9HR8vHlCurnDggLheVq8uLlyzZ8v6WdTySzBqvhsTpXdjYlS9K50bU77eY3ckysCkKHEMHDjQkLIdKv+WvCRaej4S7da8JHv3SrxLxYpy89S9Ozz2GMTGFnmXMo994EApg/6//4l304YNYt96/nm4cqXIRRtH78UQNd/vTlxcYMAA+PtvuHBBbNovvQT16snrAwcOZORICZGdOxdSUhzXtyL93KtVg5AQW1KqTp0ktHjxYrj/fsmObk/5JQw1342J0rsxMarelc6NKV/vsTsSZWBSlDhmzZplSNkOl58pL4ll6FCO166NZejQrHlJTCZ46CGIjIQnn5T3/f67xK798Uf+cznlg1vH7uoqjlORkXKfZrHA999Dw4bw229FKtpYei9mqPl+91O2LIwdC199ZXvujz/mERYmdu7hw6FyZVli1q8v2rmdHXb53L28JCnVpk2yaP3f/0n1gswZ0FesgEmTWPDTT0Uvv4Sg5rsxUXo3JkbVu9K5MeXrPXZHogxMCoUiZ9LzkqTNmMH0ceNImzEj+7wk3t7w889y89S8OVy6BI8+Cj16iGeTHalRA2bOhJUroUkTcZ56/HG45x5Jh6JQKEoeZcqksmMHvPmmRJTFxcEvv4iTZN268neJpVEj+OgjOHECatWyPf/NN/DWW/g//zz06yfuXUlJunVToVAoFAqFoqAoA5OixOHn52dI2cVBfp506iTVkj7/HMqUEXeDVq3E1aiQN0p5jb1XL6kS/uWX4hGxbRt07CjGposXCyVa989db/l6oua7MfHz86N5c6kfcPIkrFolNuty5eT/zKmLEhMlAq0oZTuEW3PcBQVBt26YNA2WLxfvpipV4IknYONGx/RJZ9R8NyZK78bEqHpXOjemfL3H7kiUgUlR4vD29jak7OIgP1+4uMCrr0JEhJT6TkuTu8SmTSU79x2Sn7G7uMDLL0NUlITcgITLNWwoFcTT0uwn257oLV9P1Hw3JpnHbjZDz54yl8+fh1mzYNQoW9sZMyTV0YABUlXy2rWik+1QHn4Y1q0jeu1a+M9/xLspIQF+/RVee02fPjkYNd+NidK7MTGq3pXOjSlf77E7Eme9O6AoGUyePJnJkydz8+ZNAMLCwvDw8CAwMJCVK1cSHx+Pr68vHTp0YOHChQC0adMGi8XC7t27AfD392fDhg1cunQJb29vunfvTlhYGAAtWrTAxcWFHTt2ADBo0CC2b9/OhQsXKFeuHH379iU0NBSAhIQE+vTpw5YtWwDo168f+/fvJzo6mjJlyjB48GBmzpwJQKNGjfDx8WFj+u7vfffdR1RUFKdOncLV1ZXAwEBmzpyJxWKhXr16VKtWjXXr1gHQo0cPTp06xbFjx3B2diYoKIg5c+ZQpUoVatWqRb169Vi1ahUAXbt2JSYmhqioKABGjx7N/PnzSUpKonr16jRp0oTly5cD0KlTJ+Lj44mIiAAgKCiIpUuXcvXqVSpXrkybNm1YvHgxAO3btyc5OZl9+/YBcPPmTQ4ePMiVK1fw8fGhU6dOLFiwAIDWrVsDsGvXLgCGDBnC5s2biY2NpXz58vTo0YN58+YB0Lx5c9zc3Ni2bRsgied27tzJ+fPnKVu2LP3792f27NkANGnShNKlSwMQGhpK//79iYiI4MyZM7i7u+Pv709ISAgADRs2xNfXlw0bNgDQ66efuHzPPdT8/HPKnDgBgwdzpkMHtj/0EFXat6dmzZqsWbMGgO7duxMdHc3Ro0cxm82MHDmSuXPnkpKSQs2aNTl8+DCurq4AdOnShdjYWA4dOgTAyJEjWbhwIdeuXaNatWo0a9aM/v2XUaeOD7NndyciwpXnnoPPPrvC1KlluXZtGQkJCVSqVIl27dqxKN3w1bZtW1JTU9m7dy8AAQEBrFu3jn379tGiRQu6du3K/PnzAWjVqhVms5mdO3cCMHjwYLZu3UpMTAyenp707t2buXPnAtCsWTPc3d3Zmh6zN2DAAPbs2cPZs2fx8PBg4MCBGbHZfn5+eHt7s2nTJgD69OnDwoUL8fb2pnTp0gQEBDBjxgw0TaNBgwZUrlyZ9enV+3r27MmJEyc4fvw4Li4ujBgxgtDQUFJTU6lTpw61a9dm9erVAHTr1o3z589z+PBhTCYTo0aNIiwsjOvXr1OjRg38/PxYtmwZAKdOnSIxMZHIyEgA7r//fhYvXkxiYiJVq1alZcuWLFmyBIAOHTqQlJTE/v37AQq9RsyePZtq1aoVaI1o2rQpHh4ehV4jzp07xyuvvFLgNeLGjRtFskasWLGCatWqFWiNGDZsGGvWrCnUGmFJT3J07NixDN3ktUZ4enqyefNmAPr27Zv/NaJXL44ePcrJkycpVaoUw4cPZ/bs2Zw8eZJu3bplu0akpR1l1SrbGjFrVjMsloYsXQpLl4KrayoDB96gd++zeHruwMlJy3aNsH6/O3bsSGJiIgfSw3ktFgv79+8v0Bpx+fJlKlSoUCRrRHR0NI+//DJ7evQgbdUqGm7aRLUxY5iZ/hk2rVKFBu+9x+6mTTndvj29hgwhMjKS06dPF2qNqFGjBiDrvNlsztcasWLFCgA6d+7M5cuXC71GxMbGMm7cOLtfR2S3RixYsIAKFSo45DoiuzXi+vXrtGzZ0u7XEbeuEW3bts3Qu/Vve1xH5LZGJCUlZfzm5XeNSEtLo27dugW6jmjYsCH//PMPYLuOWLVqFdWqVSvQGjFixAiWL19eJGvEhg0bMqpL2fM64tY1Ys6cORm6rl69ut2uI3JbI+bNm0elSpXsfh2R3RoRHR3Nk08+affriOzWiAMHDuCWnmrC3tcRt64R8fHxAMTHx7Ny5UrAPtcRkP0aER4ejo+Pj0OuI7JbI5KTk2natGmB1ojc7jUKskZYr2cdcR0BWdcIh6MpFAUgPj5eA7SYmBjd+vD3338bUrae8pOTk7WJEydqycnJd3aCxERNe+MNTXN21jTQNA8PTfvyS01LTc33Ke507GlpmvbDD5pWvryIBk0bM0bTzp7N/zmU3u9Q70WAmu+OpyTqPSpK0957T9Pq1bPNc9C0atU0LSkp7/dfv65p06drWmCgpjVufF4LDJT/r1+/s/4XhjzH/sMPtgF6eGjaI49o2tq1mnbzZqHklkS93y2y9ZSv9K70rhdG1buesvXWu1Hnm96yY2JiNECLj493iDwVIqcocfTp08eQsouD/DumTBn45BPYuRO6dJGkKa+8Au3aQfruUF7c6didnODppyVs7sknJe3Jn39K2NwXX0Bqqv1kFxV6y9cTNd+NSUHH3qABTJwIhw/D5s3wzDNQoYJE5qY7YAISQnfqVNb3hodD1aoSVhsWBgcPViIsTP6vWhXSN24dRp5jHzQIPvhAsp0nJkrFznvvhfr15UOIjXVIP+2Bmu/GROndmBhV70rnxpSv99gdiTIwKUocVvdao8kuDvILTfPmsG6d5BTx9oY9eyQx+NNPw5Urub61sGP38ZFCd1u3SvLvxERJa9KyJaR7w9pNdmHRW76eqPluTO507CaTVJCcPBnOnoXff7e9Fh0NDz0kqY169JBl6O+/JVVcXJy0SY8OzHiMiwN/fzFCOYo8x16zJrz7Lhw5IoUUHntMKhscPw4ffgjpoeyA+DnlRXIyBAfjPGoUY//4A+dRoyA4OGsmdQeh5rsxUXo3JkbVu9K5MeXrPXZHogxMihLH6dOnDSm7OMgvEsxmuSGKjIRx4+QG6KefwM9P3AtyuCEqqrG3awebNsmNZ8WKcPAg9OkDI0Zk9WxIv+di+HB48skGDB+u2z3X3aH3O0TNd2NSFGMvVUqSf1u5fFkcfQDWrpXibA8+aAuoyw7r8+PGOW7u53vsJhN07SqWsvPnxTXz7behUiVbm6FDxRVr1Sqb1Swzmdy3zOHh1Dl5EnN4uG7uW2q+GxOld2NiVL0rnRtTvt5jdyTKwKQocZTOHO9gINnFQX6RUrGihHasWQONG0NMDIwZA/fdB+kJ9TJTlGM3m+GRRyRs7oUX5P85c8TG9dFHEBpavEJm7iq9FxA1342JPcbevDmsXg0nT0phy8zGp9zQNHGwTM/9anfuaOzu7mIte/9923OnTsHChWIZ790b6tSxeT6BGJcyuW+Z0g1QJh3dt9R8NyZK78bEqHpXOjemfL3H7khMmpYf/2mFQkhISMDT05OYmBgqVqyod3cUDiIlJYVJkyYxYcKEjEpuRcqNG5IQ6YMPxE2gVCmYMAHeegvSK23Yk7174fnnJXrPismUvVeDySSPYWHiHHA3Y3e9K4olRtH78OEyj7Nz7LkVs1lsMemFl0oGmiY57qZOhRkzIL16ECChyfv2wbVruYfRmUzg5SXxhg5YixWOxyjzXZEVpXdjovRuTC5evIivry/x8fGUK1fO7vKUB5OixDFjxgxDyi4O8u1GqVJiTDpwAAYMEIPTBx+Iy0F6yVV7jr1FC3GkmjrVZkAqTiEzd63e84Ga78bEEWO/dCl/xiWQdgcP5pkqrkgosrFbE1L99JOE0M2YIeur2SyZ0BMT887R5GD3LTXfjYnSuzExqt6Vzo0pX++xOxJlYFKUOPR0utPb4U9v+Xanbl1YtMgWo3bkCPTrB6NH43r5sl1Fm0xy35Wfj9jRITN3vd5zQc13Y+KIsVeoIHM+vxw8CL6+4slkz+7ZZexubjByJCxeDKdPQ7Nm+R+82Qzz5hV9n7JBzXdjovRuTIyqd6VzY8rXe+yORBmYFCWOBg0aGFJ2cZDvEEwmiV2JjISXXpKbmxkzGPLGG1IaKnOFpCImLKxY3nMZQ+85oOa7MXHE2AMC8u/BBJKzKS0NXFxsno4A330n0WZFde1o97FXrSrWtYK4b9nZwG9FzXdjovRuTIyqd6VzY8rXe+yORBmYFCWOypUrG1J2cZDvUMqWha++gu3boX17nK9dg+eek5CPnTvtIrKgITMOuucylt5vQc13Y+KIsQcFQfnyWY1F2WEySbsjR+Dw4ax5tCMjpVBAixZQrx688orkcktLu/N+OUTvBXXfKl/efn3JhJrvxkTp3ZgYVe9K58aUr/fYHYkyMGUiNjaWTz/9lC5dulC5cmVcXV2pWrUqHTt25PXXX2fz5s15nmPp0qUEBgZSvXp1XF1dqV69OoGBgSxdujTf/UhKSuKzzz6jQ4cOeHt74+HhQePGjXnttdc4lbmOeh4cOHCAp556ivr161O6dGkqVqxI9+7d+fnnn0krzNWvzqxfv96QsouDfF1o3Ro2b2bbI4+Ap2eGwYkXX4SEhCIVVdB7rqgo2Lq1SLuQLYbUezpqvhsTR4zdzQ2mTZO/czIyWZ+fNk3a168PTZrYXr9xA4YMAVdXOH5cbOL33guVK0ulyjuxhTtE7wV13woMtP09cSKsWlU4K1oOqPluTJTejYlR9a50bkz5eo/dkSgDUzqzZ8/Gz8+PN998k02bNnHhwgVu3LjBuXPn2Lp1K59//jmffPJJju/XNI3x48czYMAA5s2bR3R0NDdu3CA6Opp58+YxYMAAxo8fn2f85dGjR2nTpg1vvPEG27Zt48qVK1y7do3IyEi++OILWrRoweLFi/Mcz2+//Ubbtm35+eefOXr0KMnJycTGxrJ+/XqeeuopunXrxqVLlwr8OSkUuuDkxJE+fcRd4IEH5Mbo22/Bzw9mzy6y2JSC3nOdPQsdO0LPnrBsmX3zsigUiqJnyBAJjfXykv+tBmbro5cXzJ8v7bKjRQsID4fYWKkw99BD4uxz6ZIUDTh71tY2JkbaFQsK4r7l6QkjRsj/ERHiwtW7N1SpAk88AUuXiqVNoVAoFAqF4VEGJmD69OmMGjWKS5cu4evry3vvvceKFSvYsWMHixYt4ttvv6VPnz64uLjkeI533nmHKVOmANC6dWtCQkLYunUrISEhtG7dGoApU6bw7rvv5niOxMREBg8ezKFDhwB44oknWLlyJZs2beKjjz7Cw8OD+Ph4goKC2Lt3b47nWbZsGU8++SQpKSlUqlSJb7/9li1btrBkyRIC03ch//33XwIDA7EU5G66mNCzZ09Dyi4O8vWkZ8+e4hbw11+wYgU0aADnzsH998PAgXD0aKFlFOSeq1w5GDMGnJ2lAl3//tCmjRRqKuqNfcPr3YCyi4N8PXHk2IcOFUNQcLAYmTt1SiEgQP4/ezZn41JmPDzEyWf6dLhwQRx8XnpJ7DBWvv4aKlWCHj3k7+PHsz+XQ8ZeEPet4GBpD5KA6vHHxd0zNhZ+/VUq01WqBA8/XOjwZTXfjYnSuzExqt6Vzo0pX++xOxTN4ERERGiurq4aoHXr1k2Li4vLsW1KSkq2zx8+fFhzdnbWAK1du3ZaUlJSltevXbumtWvXTgM0Z2dn7ciRI9me57333tMADdA+/fTT217ftGlThpyePXtme47U1FStfv36GqCVK1cuW1nPPPNMhpxp06blON7siI+P1wAtJiamQO8rSjZv3mxI2XrKT05O1iZOnKglJyfrIl/Tshn79euaNnGippUqpWmgaW5umvbhh5pWyD6Gh2uaySSH+CRlPayvhYdL+5MnNe2llzStTBlbmzp1NG3yZE27ZSm4Y5TejSdbT/lK7/aRHRR0+3rSooWm/ec/mrZzp6ZZLPaVny3z52ta+fKaBprFbM7yqJUvb1vobiU1VdNWrtS0p5/WtEqVbANasMDW5vJlTbt2rUDduRv1Xtzlq/mu9K4XRtW7nrL11rtR55vesmNiYjRAi4+Pd4g8w3swPf/886SkpODj48PcuXPx9PTMsW2pUqWyff6rr77KyGn03XffUbp06Syvu7u789133wGQlpbG119/fds5UlNT+eabbwBo3Lgxr7766m1tOnXqxGOPPQbA6tWr2bFjx21t5s2bx5EjRwB46623qFev3m1tPvvsM8qnJ+z87LPPsh1TceZ4Ttu+d7ns4iBfT24bu5sbvPeelG+67z5IToZ33oFWrcSl6A4paMhMzZqSd+XkSYkcqVBBPBOefRZq1YKPPoIrV+64O4DSuxFlFwf5enI36n3WLFkbvv5awmqdnGDvXvjgA+jb1xaee/z4cceF22Zy37IMHcrx2rWxDB2at/uWszP06gU//ADR0ZLZ/OWXoU8fW5vPPoOKFcU1dOZMuHo1z+7cjXovKfL1ROndmBhV70rnxpSv99gdiaENTJGRkaxcuRKA5557Dh8fnwKfQ9M05s+fD4Cfnx/33HNPtu3uueceGjVqBEBYWNhtuZjWrFlDXFwcAA8//DDmHDINjxs3LuPvuXPn3vZ6WFhYtm0z4+7uzv333w/A/v37OXz4cLbtiiu5hSrezbKLg3w9yXHsDRvC8uXw998SphEZKXdvDz8sSU/ugFtDZpo0ickzZKZCBfjPf8TQ9O23Yly6eFFsXjVrwmuvyX3YnaD0bjzZxUG+ntyteq9dW+oTrFoloXTTpklo3ahRYnACcHZ2oWVLGDtW8jolJtqtO4KbG4wZQ9qMGUwfN460GTMk/tcaFpcXTk7QrRt8+aVkO7eybRskJUFoqAywYkVZUP/8E+Ljsz3V3ar3kiBfT5TejYlR9a50bkz5eo/doTjET6qY8sEHH2SEih04cCDj+cuXL2tRUVFabGxsnuc4evRoxjnGjx+fa9snn3wyo+2xY8eyvPbuu+9mvJabC11qaqpWpkwZDdC6d+9+2+s1atTQAK1Ro0a59uXvv//OkPf777/n2jYzxSFETuF49HapzTdXrmjaM8/Y4tvKl9e0KVM07eZNh3flxg1NCw7WtGbNbNEjLi6a9uijmnbwoMO7c0eUGL0rihSld33Zti1rGJ2rq6YNGqRpv/yiaefP209ukevdYtG07ds1bcIETatfP+ugqlbVZV1W3I6a78ZE6d2YKL0bExUi50D+/fdfADw9PWncuDF//fUXLVu2xNvbm4YNG+Lj40PdunV5//33ScxhC/HgwYMZf/v5+eUqL/Prmd9XkPM4OztnhL3deo7ExETOnDlT6L4Ud0JDQw0puzjI15N8jd3LCyZPhn//lVC5K1fgySeha1eJRbGn7FtwcREngL17YdEi2eBPTYXff5cy54GBsGWL/eTfLaj5bkyMrPejR0NZvx5efRXq1YOUFFlDnnhCCrdlE2VfPDGZoG1b+PhjiIqCPXvg3XdlARw40BZ3bLFIddApU1jw22+6dVdvvestX0+MPN/1lq8nRtW70rkx5es9dkfirHcH9CQiIgKA2rVr8/zzzzN58uTb2hw/fpyJEycSGhrKsmXLqFq1apbXT58+nfF39erVc5VXo0aNbN+X+f8yZcrgZU3+kst59u7dy8WLF0lJScE13SX9zJkzGaF3helLZlJSUkhJScn4PyEhIdvnHUlycrIhZesp3yqzxIy9ZUvYsAGnn37CaeJETJs3o7Vpw80XXuDm229LySd7yc6G3r3l2LzZxBdfOLFwoRPz5sG8edC9u4XXXkujTx8tx2JOSu9qvjsSpXd99Z6amkz79im0bw8ffggRESYWLDCzYIGZHTvMNGlyg5QU+a3fssXEwoVmhg610LatRg7R9fnC7npv1AjefluO5GSxnAGmrVspFRICISEMMpmwTJ/OzcBAyQV1yzWXPdFb72q+G3O+K70bT+96ytZb70adb3rLdrRck6Y5LJVkscPT05OEhARcXV1JSUnBy8uLSZMmERgYSLly5di3bx//+c9/WLJkCQCdO3dm/fr1WfIjffbZZ7zxxhsALFmyhP79++cob8mSJQwcOBCAzz//PEsi76ZNmxIREUGlSpU4f/58rv0eOXIks2bNAiA2NpYKFSoAsG3bNjp06ADAm2++yaRJk3I8x/Xr13F3dwdg8ODBLFiwINt2EydO5P3337/t+QkTJuCW3/wMCoWOlE1IoN/SpTRNNyjHlyvHkoEDOZSHl589iYnxYdOmzuzd2wKLRRKvVKp0nq5dN9KkyQGcnAy7LCsUilyIjy+Hh8fVjDVi8eIBbN0qv/tlyybQqNEh/PwOUbv2cZydLfk6Z2qqExERTYmMbERSUmnc3a/j53eIJk0O4OJy025jseJx9Sot9+yhcUQE1c6ezXheA07XqMHqXr04UaeO3fuhUCgUCsXdSHJyMpMmTSI+Pp5y5crZXZ6hPZiuXbsGiFXPycmJJUuWZEnS3a5dOxYuXMjgwYNZsmQJmzZtYu7cuYwYMSKjTXJycsbfOVWZs+KaKfnl9evXs7xmPU9e58jtPEXVl8y89dZbvPLKKxn/JyQkUKNGDZ599lkqVqyYZ1/twYULF6hUqZLhZOspPyUlha+++oqXX345y3fHkRRq7P/7H6lLl+L84ot4njzJqBkzuDl4MGlffCHZuO0pOxdOn07ju+80fvvNiQsXKjNnznB27Ajk5ZfTGDvWgrUgpdK7mu+OROm95Oi9RQszf/99k6VLzVy9Wo7t29uzfXt7ypXT6NfPwg8/pFG2bM7vX7jQzOOPOxMXZ8Js1rBY5PHgwSasXh3Ab7+lMWhQ/gxVRUH09u1U2rABc1gY5n//pebp04weMwatWzdpcOKEhNTVrVvkskuS3osSNd+V3pXejSNbb70bdb7pLfvixYu5Op4UOQ7J9FRMsSbLBrRRo0bl2G7//v0Z7QIDA7O89umnn2a8tmTJklzlLV68OKPt559/nuW1Jk2aaIBWqVKlPPt9//33Z5wncyLyrVu3Zjz/5ptv5nqOpKSkjLaDBw/OU6aV4pDk+++//zakbD3lF4ekgEUy9mvXNO3//k+ybYOmubtr2qefSkZue8vOhUuXNO2DDzTNx8eWA7diRU378ENNu3xZ6d2IsvWUr/Re8vSenKxpixdr2vjxmla5sqwhtWpJnm0rK1dqWnS07f/586UegrUmwq2H9bX58ws/pvySZeynT2vaDz9oWlqa7blnn5XOtW6taR99pGmRkfaRrQNqvhtPtp7yld6NKVtvvRt1vuktWyX5diBlM23rDRgwIMd2TZs2pVq1aoCEoeV0jpwSgVuxekwBeNySA8Z6nrzOkdt5iqovCsVdi7s7fPQR7N4N3btLCe033oA2bWDjxqxtk5MhOBiGD6fXf/8Lw4fL/5k8BYsKb2/JfXvyJHz3nThVXbwI77wDNWvCn3+2Jj1/v0KhUNyGqysMGAA//QTR0bB5s6wl1rxuaWkwYgRUqwYdO8IHH8BDD8lrOSVKsD4/bpxdlr28qV4dnn4anJxsz8XFyf+7dkkuJz8/aN4c3n8fDhzIeTAKhUKhUCgcgqENTJkTXec3KXZMTEyW5zO/70wed4CZk2lnlp35PNeuXSMuLi5f56lYsWIW98ai6ktxp5vVVd5gsouDfD0p0rE3aQJr1sDUqeDjA/v3S6W5J56AS5cgPFySy44dC2FhVDp4EMLC5P+qVSGHnGWFxd0dnnsODh+GP/+U+6bERFi82I+6deHRRyEy0i6iiy1qvhsTpfc7x2yGe+6BIUNsz50/Lzm2AbZuhffeg4SEvO0xmibFOB1V/CbPsf/5pwzm11+hf39wdpb1e+JEqUxXUDJtJAz79lu7biTkhd7fOz1R892YGFXvSufGlK/32B2JoQ1MTZs2zfj75s3cE1laX3d2zpq2qkmTJhl/R+Zx55f59caNG9/RedLS0jh69Gi25/Dw8MgwFhWmL8WdvJKg362yi4N8PSnysZtM8PDDYrF5/HF57tdfoU4dCAiQnXKQfB+ZH+PiwN9fjFB2wsUFHnxQqnovWgStW18lNRX++ENsY8OGwb//2k18sULNd2Oi9F60VK8uXk1nz8LPP0NB0kCYzVLx0hHka+w+PvDYY7BkCcTEwLRpYk178EGby1ZqKnToIB6qW7dmb0m7ZSPB7d9/HbKRkBN6f+/0RM13Y2JUvSudG1O+3mN3JIY2MHXv3j3jb6vRJieOHTsGkBEqZ6VOnTpUTS+ju3bt2lzPsW7duoxz1K5dO8trXbt2zfg7t/Ns3749I7ytS5cut71uPc+hQ4dy/SJnlpHdeYozhw8fNqTs4iBfT+w29goV4JdfYMMGsd5cvWpLQ5IdDowbMZlkU/711xeyaZPYtTRN7oE6dYIePeQe626OClHz3ZgovduHKlXgySclsiy/WCwQG2u3LmWhwGMvX14MQuHh8L//2Z5fswa2bYPPPpOYwNq14eWXJRTaYpH2Om8k3Ire3zs9UfPdmBhV70rnxpSv99gdiaENTEOHDsXFxQWAuXPn5thu7dq1XLp0Cbjdvc1kMuHv7w+IV9C/ObgV/PvvvxleQ/7+/pisu2zp9OjRA09PTwCmTZuGlsMd49SpUzP+HjZs2G2vBwQEZNs2M0lJScyaNQsQz6mGDRtm2664cutnZxTZxUG+nth97F26wGuv5a+tg+NGTCYTnTqJYenAAbFtOTvD2rVigGrdGv7+W/Ks3G2o+W5MlN7tS4UK4pmUXzZulLXm66/ta2wqsrF37gyzZ8PIkVCmDJw6JZ3v2lUSUT3wgLQrBhsJVvT+3umJmu/GxKh6Vzo3pny9x+5QHJJKvBjz9NNPZ1RTCwkJue31hIQErVWrVhlttm7delubQ4cOac7OzhqgtWvXTktKSsryelJSktauXTsN0JydnbWoqKhs+/Luu+9myPn0009ve33Tpk0Zcu69995sz3Hjxg2tXr16GqCVK1dOO3LkyG1tnnnmmQw5f/zxR7bnyYniUEVO4Xj0rjrhMAIDNc1szr6k0q2H2SztdeLUKU17+WVNK1PG1qXatTXt+++lWF5RYBi9K7Kg9H73M316/pa57I7jx23nOXRI086f120Y+SMpSdPCwjRtzBhNK1eu4AMODtZ7BHZFzXdjovRuTJTejYmqIudg3n//fWrWrAnAQw89xPPPP8/q1avZsWMHU6dOpUOHDuzevRuAp59+mvbt2992joYNG/JauufD9u3b6dKlCzNnzmT79u3MnDmTLl26sH37dgBef/11GjRokG1fXn/99QxvojfeeIPx48ezevVq/v33Xz7++GP69u1LWloapUuX5uuvv872HC4uLnz77beYzWYSEhLo0qUL33//PVu3bmXZsmWMGDGCH374AZBwuoesZWRKEGFhYYaUXRzk64lDxn7pki1EIi8sFrh82b79SSe7sdeoAV9+KRvz//2vpCU5cUKShNeuDR9+KE5WJR01342J0rt9CQqS6LK8NlRNJmm3datEm40bJ+uLlVdfhcqVoVUreP11WL4crl+/837ZZeylS0u4W3Cw5Gzq2jX/7lsOTECl9/dOT9R8NyZG1bvSuTHl6z12R+Kcd5O7m4oVK7J06VKGDh3KkSNH+P777/n+++9va/foo4/yzTff5Hiejz76iJiYGH7//Xd27drFqFGjbmvz2GOP8eGHH+Z4jrJly7Jo0SIGDhzI4cOHmTJlClOmTMnSply5cvz111+0atUqx/MMHDiQn376ieeee44LFy7w/PPP39amQ4cOzJs3D6fM5X9LCNcLc/VagmUXB/l64pCxW+NG8mNkMpnAy8vuXYLcx+7tDe+8A6+8IknAP/9cDE3vvguTJsH48ZJ6JI9CmcUWNd+NidK7fXFzk9zY/v6ylGUXKWY1Pk2bBu3by5EZTZNKdCAFCfbskfXH1RW6dYPBg+HFFwvWL7uP3dUVnJwKtpGQniLB3uj9vdMTNd+NiVH1rnRuTPl6j92RGN6DCaSK2u7du/nss8/o2LEj3t7elCpViurVqzNy5EhWrVrFb7/9lpGvKTvMZjO//fYbixYtwt/fn6pVq1KqVCmqVq2Kv78/ixcv5tdff8Wcx65Z/fr12bVrF5988gnt2rXDy8sLd3d3GjVqxMsvv8zevXsZPHhwnmN64okn2LFjB0888QR169bFzc2NChUq0LVrV3788Uc2btyIj49PgT+r4oC1Up7RZBcH+XrikLEHBOT/xkPTJAnSt98Wbss+H+Rn7O7u8OyzcPgw/PUXNG8O166Jl1PduvDoo3DwoF27aRfUfDcmSu/2Z8gQyetmtZObzVqWRy8vmD9f2mWHySRL4IULkgNu3DhJb5SSAv/8I+fOzPz5UsUuNxwy9oImoKpQwfb36tV281zV+3unJ2q+GxOj6l3p3Jjy9R67IzG8B5OVMmXK8Nprr2WEut0pAwcOZODAgYXuyxtvvMEbb7xRqPM0a9bsNg+ouwG/gpS/uYtkFwf5euKQsQcFyZZ7XFzepdlMJolBe/FFqV70+uvw1FOSULaIKcjYnZ0lf+3o0bB0KXzyidwE/vGHHP7+MGEC3HNPkXfTLqj5bkyU3h3D0KFi9AkNhTlzLOzefYpWrWoyfLgTI0aIp1Ne+PrKejN6tCybkZESKpdeYBeAixdh2DB5vUkT6NsX+vSBe+/NumQ6ZOwBAZBLYZfbsBZUuXYNBgyA1FQp4zlwoBwtW+Yda5gP9P7e6Yma78bEqHpXOjemfL3H7kiUB5OixLFixQpDyi4O8vXEIWO3xo1AzjcMJpMcoaHw009Qq5Zs4b/2miQn+eQTuHq1SLt1J2M3meReaM0a2LxZ7qlAvAg6dZIbuyVLsrejJSdLupJRo5z544+xjBrlTHCww4opZUHNd2Oi9O443NxgzBiYMSONceOmM2NGGmPG5M+4dCsmEzRuLHb3oCDb8+fPQ7t28npEhBR0GzRI8jv17Anh4dLOIWMvaAKqESPk/9OnoUED8XLduBHefltKeFavDo8/Dhs2FKpben/v9ETNd2NiVL0rnRtTvt5jdyTKwKRQKBSZuT1uJOujNW4kMFASHB0+DL/9BvXqSf3uCRNsWbbj4x3f/2y45x7JUxsRAY88Ai4usG6dbL63aiXhLWlp0jY8XDwPxo6F8HAzJ0/WITzczNix8vyCBboORaFQlECaN5dE4RcvwqxZ8MQTYptPTRUjeOaos+PH4ddf4eRJO3UmvxsJIO2sljY/P9i3Tzr200/i/uXuLi5gv/0G27bZ3h8XJwtuXp6wCoVCoVDcZSgDk6LE0blzZ0PKLg7y9cShY7fGjQQHQ0AAyffcIy5AwcHyfOakJC4ukuAoMhKmT4dGjeRu6d135Q7qvfcKnbOjqMbeuDH8/jscOyZJwcuUgb174cEHZWN+/HgZZlyctLdYTFke4+IkxM7qbeAI1Hw3JkrvdycVKogD0ZQpYkiKioLJk6F/f3m9c+fOzJsnBqjatWU5fe45WXOsCcWLhPxuJGSXgKpmTVks58+XBODLl8NLL2VtO28eNG0KderAM8/AwoUSYpcLd7Pe80LNd2NiVL0rnRtTvt5jdyTKwKQocVx2UGn44ia7OMjXE4eP3Ro3MmcOB3/4AebMIde4EWdneOghOHAAQkIk0Uh8PHzwgdwp/d//iYfTHVDUY69eHb74Ak6dgv/+FypWlMpzU6bIhntOm+7W58eNc1y4nJrvxkTp/e7HZBLD9jPPQOXK8tzly5epXBk6d5Zib1YDlL+/GKe6dRPDVJFwy0bC1bZtc95IyAk3N0km9dVXUL++7fmzZ6Vi3cmT8OOPcq4KFcSS9u23Nit+Joyi9+xQ892YGFXvSufGlK/32B2JMjApShyRkZGGlF0c5OtJidG7kxOMGiWhFKGhkgD26lX4+GPxaHr9dcnZZC/5BcDbG955R4xLY8fm7z2aJrnNQ0Pt0qXbKDF6vwvl64nSuzGJjIzkgQckxdGlS+II9MwzYohKS5MoNKsxCsRp9Mcf4ejRO5OXjBvB2hiGM4eOSYsYzhyCtTEkcwcJqDLz9tviubpwoQygVi0pr7dsmXg7WWOSQYxQKSmG17sRZRcH+XpiVL0rnRtTvt5jdyTKwKRQKBT2wGyG4cNh1y4JpWjbFpKS4PPPxaPppZfyrtntINzdITEx/5W7zWa58VMoFAp74ekpDkWTJ4sn0/HjYtguXdrW5vPPxX5Tvz7UrSuFPOfMESN4XmTONxcWBgcPViIsjKLLN+fuLpnMJ0+WzkdESIeffRZ8fGztxo4Fb2+6ffEF/PyzuJYqFAqFQlFCMWmaykCoyD8JCQl4enoSExNDxYoVdenDzZs3cXJyMpxsPeWnpKQwadIkJkyYgKurq8Plw12gd02DpUvh/fdhyxZ5ztUVHnsM3nxT8nrYU34e9OgBa9cWrP3q1fbqjY0Sr/cSKF/Nd6X3kqB3TRPH0GXLYNOmrE5BZrNEwOVkCA8Pt1XWzO4q2JrjOyxMzmM3btwQ96xbjUrNmkkVhqFDoUsXO3ag5On9bpKtp3yld2PK1lvvRp1vesu+ePEivr6+xMfHU65cObvLUx5MihLH4sWLDSm7OMjXkxKvd5MJBgyAzZslKWzXrhIy8cMPsv3+5JM5JhdxxNgrVMi/BxPA7t2yMW/vkPISr/cSLF9PlN6NSUHGbjJJaru1a2UdWrAAXnhBihlYLJD5GtpikWIG330He/ZIHjkoBvnmSpWSGOXduzn40EPyu2A2w/798OmncmQmJsaOndEPNd+NiVH1rnRuTPl6j92ROOvdAUXJYPLkyUyePJmbN28CEBYWhoeHB4GBgaxcuZL4+Hh8fX3p0KEDCxcuBKBNmzZYLBZ2794NgL+/Pxs2bODSpUt4e3vTvXt3wsLCAGjRogUuLi7s2LEDgEGDBrF9+3YuXLhAuXLl6Nu3L6HpSV8SEhI4duwYW9K9QPr168f+/fuJjo6mTJkyDB48mJkzZwLQqFEjfHx82LhxIwD33XcfUVFRnDp1CldXVwIDA5k5cyYWi4V69epRrVo11q1bB0CPHj04deoUx44dw9nZmaCgIA4fPkxISAi1atWiXr16rFq1CoCuXbsSExNDVFQUAKNHj2b+/PkkJSVRvXp1mjRpwvLlywHo1KkT8fHxREREABAUFMTSpUu5evUqlStXpk2bNhmLUPv27UlOTmbfvn2AWL+XLl3KlStX8PHxoVOnTixI9+Nv3bo1ALt27QJgyJAhbN68mdjYWMqXL0+PHj2Yl76d27x5c9zc3NiWXlZ54MCB7Ny5k/Pnz1O2bFn69+/P7NmzAWjSpAml02MSQkND6d+/PxEREZw5cwZ3d3f8/f0JCQkBoGHDhvj6+rJhwwYAevXqxdGjRzl58iSlSpVi+PDhzJ49m7S0NOrWrUvNmjVZs2YNAN27dyc6OpqjR49iNpsZOXIkc+fOJSUlhZo1a3Lp0qUMOV26dCE2NpZDhw4BMHLkSBYuXMi1a9eoVq0azZo1Y9myZQB07NiRxMREDhw4AMCIESNYvnw5CQkJVKpUiXbt2rFo0SIA2rZtS2pqKnv37gUgICCAdevWcejQIVxdXenatSvz588HoFWrVpjNZnbu3AnA4MGD2bp1KzExMXh6etK7d2/mzp0LQLNmzXB3d2fr1q0ADBgwgD3//S9pK1fScv58fPbtg19+wfLbb1wZPJjkV15hXXr4XJ8+fTh16hQhISGULl2agIAAZsyYgaZpNGjQgMqVK7N+/XoAevbsyYkTJzh+/DguLi6MGDGC0NBQUlNTqVOnDrVr12Z1uttRt27dOH/+PIcPH8ZkMhEQMIr07uaLuDip7vTyyxYGD06jYcNNNG9+nnvuaU9SUhL79+8HKPQacejQIRITEwu0RjRt2hQPD49CrxHnzp0DKNAaMWfOHG7cuFEka4R17AVZI4YNG8aaNWsKtUZYLBYAjh07lqGbvNYIT09PNm/eDEDfvn0LvUacPHkSX1/fAq0RDRs25J9//gEKt0ZYLBYWLVpUoDXi8uXLVKhQoUjWiOjoaLp168aePXs4e/YsHh4eDBw4kFmzZgHg5+eHt7c3mzZtAmSNiIyM5PTp04VaI2rUqAHIOm82m29bI0aNGkVYWBjXr1+nRo0a+Pn5sWLFCkCq41y+fDkjx8T999/P4sWLSUxMpGrVqrRs2ZIlS5YA0KFDhxzXiNjYWK5evXrH1xHPPuvCPffs4NKl0nTt2ptVq7Zx4cIFLl6szt9/d+Pvv8k31nxzn39+grFjzUV2HZHTGnG9Rw+SXnyREzt3UnnfPrrEx7OjQgWiQkKoXr06zcqUoXzbtlyuXRvz4MFcbN+eHU5OaGZzodaItm3bZujd+rc9riNyWyOSkpIcch2R0xqRmJho9+uInNaI8+fPZ4y9wNcRhVgj5syZk6Hr6tWrF8l1REHXiKNHjxISElKgNaKo7jWio6O599577X4dkd0aERsbm6Fze19H3HqvER8fD0B8fDwrV64E7HMdAdmvESdOnCAkJMQh1xHZrRHJycls3brV7tcR2a0R1rXGEdcRkHWNcDiaQlEA4uPjNUCLiYnRrQ9r1qwxpGw95ScnJ2sTJ07UkpOTdZGvaXe53tev17S+fa0F3DTNbNa0MWM07eBBx8jXNO36dU0rX17TTCZbN7I7TCZN8/TUtM8+07QWLbK+Vq2apr31lqYdOlR0/bqr9V5M5av5rvSuF/Yae3S0pn3yiab17i3La25rXObDbNa0wEC7dOk28hz7jBm3L9De3po2erSmBQdr2qVLBRN4/bqmTZ+upQUEaMdq1dLSAgI0bfp0ed7BqPnueO7m+a5k54zeejfqfNNbdkxMjAZo8fHxDpGnQuQUJY6WLVsaUnZxkK8nd7Xeu3aVRCL//itJYS0W+PNPaNIERo2itYuLfeUj1banTZO/rflHbsX6fHAwvPaahMnt2CGeTN7eEB0tOVEaNZIh/fabFNArDHe13ou5fD1Rejcm9hp71arwxhvwzz8FS2lksUC6I6PdyXPsI0fC+fNSOm/UKPDyktjAkBB46CFI36EH4Pp16XxOZMpwbg4Pp87Jk5jDw4sww3nBUPPdmBhV70rnxpSv99gdiTIwKUocVhdao8kuDvL1xBB679hRylpv3y4ZaDUNZs6kXJcuUpEu3QXcXgwZIkltvbzkf7NZy/Lo5SUF8YYMkddNJmjTRvKanD0Ls2ZJmimzWcqMP/64lBR/+GG598ntficnDKH3YipfT5TejYkjxl6xYsHyzW3eLGnyHnkEfv89fxXq7oR8jd3XV4xJISFw8SJs2CCJqNq2hfvus7X75BMxFD3yCMyeLTHNVqwZztOfM6UvzNZH4uLA31/aOQg1342JUfWudG5M+XqP3ZEoA5NCoVAUN9q2lfJHe/ZAUBCayQRz50Lr1lJVKD2e3R4MHSrGouBgGDrUQu3axxk61EJwsDxvNS7diqsrBAXB4sVSEOnjj6FhQ0hKkg33nj3lJu2DD+DkSbt1X6FQKHIlIKBgxm6TCY4ehalTpejnpUu213bvhl27ID09pWNxdhZ3rI8+kk2JzFnN16yBCxek0/ffDz4+cO+98OGHYqCCYpDhXKFQKBR3I8rApChxdOjQwZCyi4N8PTGk3lu0gFmzOL14MTzwgGy7L1gAHTrYKtLZATc3GDMGZsxIY9y46cyYkcaYMfJ8fqhWDSZMgMhImydT2bJSJO+996BOHdls//tvieTIDUPqvZjI1xOld2PiiLEHBUH58jmHAlsxmaTduXOwZIk4Cvn7Q716tjb//a94cXp7w8CBYljfsEEKhBaUIh378uWwahW8+qqU1bt5E9atg3ffhYSEnI1LVqwZztMTHtsbNd+NiVH1rnRuTPl6j92RKAOTosSRlJRkSNnFQb6eGFnv8dWqwV9/wcGDEm/m5ARLl0LnzmKpSa9YVNwwmaSLv/wiN2lWTyZNg5UrpWx4lSrw1FOwZUv29zxG1rve8vVE6d2YOGLsBck3N20aVKoE/fuLo1BYWNb3uLuL8TwhwWaE6tYNPD1laS6Ip1SRjr1UKVlsP/8cIiLg2DGYPFlilvOL2SyetA5AzXdjYlS9K50bU77eY3ckysCkKHFYy5YaTXZxkK8nSu9IzNnUqRAVJW5Bzs5iqbn3XujRQ/7Oa2daJ8qUkciMVavkXue996BWLYiPh59/hnvugaZN4bPPJI+tFaV3Y6L0bkwcNfbb881lfbw131xOBAdLnu0dO+DrryVVnq+veDAlJWXN9TRmDLz0EsyZAzExt5/LrmOvUweeeUYqMOQXiwVOn7ZfnzKh5rsxMarelc6NKV/vsTsSZWBSKBSKkkbduuIWdOQIPP207FavXStb5l27indTMTU0gdzrTJwohqaVK+XGq3RpcdB64w2oXl1u7ObOhbQ09TOlUCiKnsz55gICoHHjCwQEkGe+uVtxdpYwuRdflIiy8+fh0CH45htbm4QEycv9zTcwYoR4RTVqJPsE06c7MC9dhQoFy3CeOaN5Soos0sX4t0WhUCgU+mPSNPVLocg/CQkJeHp6EhMTQ8WKFXXpQ0pKCq6uroaTraf8lJQUJk2axIQJEwz52Rd7vZ85I64/U6bYkrK2by/5NgYPzjvZSC5yHaX3+HipQvfHH1lTS/n4aDz4oIlHHgFHV3gt9nq3o1w135Xe9eBu1XtSkhRlW79ejv37s9ppRo+GP/4Q+RaLRLU1aVIwW1C+CA6GsWPz3/711+HTT+XvVaugd28Js+vVy3bUqVPobt2tei/O8tV8N65sPfVu1Pmmt+yLFy/i6+tLfHw85TIXhLATamtYUeJYuXKlIWUXB/l6ovSeC9Wry9b48eOS1NXdXSrNDR0qFenmzi1YMhAd8PSEJ56ATZtkk/zNN+U+JjbWxDffQKtW4iXw3XdZqzjZk2Kv97sYNd+Nyd2qd3d3GDVK0iDt3Str2IIF4rHZqZPYbazyDx6E5s2l8NuQIWLf2bwZbtwogo4UNMP5Bx/Ynjt+XBJYnT8vFRoef1y8aWvXhkcfFavYHXK36r0kyNcTo+pd6dyY8vUeuyNRBiZFiSM+Pt6QsouDfD1Res8HlStLUtfjx8VC4+EhNbSHDxf3n5kzdaqnXTD8/GDSJEn/8frraxk+HFxcZCgvvABVq8p90uLFkJZmv36UGL3fhaj5bkyMovfy5cW59JNPxKj+2GM2+UePikHqyhVYuFCW8s6dJS9Ur17wzz+FEJwpw3kybgQzhuGE0oNVDCeUYMaQTHq50GnTspYOfewxiIuDNWvgP/+RcGxnZ4nv++OPrBawzZth9my4eDFf3TKK3oujfD0xqt6Vzo0pX++xOxJlYFKUOHx9fQ0puzjI1xOl9wK9QSw0J07AO+9AuXISkzFqFDRrJhXp7GmZKSKcnaFfvzRCQyUnitWT6cYNyXUyaJAkCp8wQXKeFDUlTu93EWq+GxOld3E8jYuTypqffw7+/pI66fp1WL0aUlNt79m0SZxWw8IgNjafgoYMIfytzVQ1nWUswYQRwFp6EkYAYwmmquksC97+N/skVK6uUlTi/fcl1u/KFcn59/bb0KKFrd1PP8H998tvUcuW8PLL4rKVww2W0rsxMarelc6NKV/vsTsSZWBSlDg6dOhgSNnFQb6eKL3fARUqwH//KzvM778vW+CRkZJVu3FjqUiX+W7FSnIyBAfjPGoUY//4A+dRoyR3hzW/kwOxjt3HR7yXdu2yeTJVqCCGp08+Ea+nLl3g118loW5RytYLveXriZrvxkTpXXBxgQ4dbMajmBg4cEDsNl262N4THg5ffgnDhkHFilKJ86mnZA8hpwJw4eEQ8HFH4vACwIJTlsc4vPD/qAPh4fnotIcH9OsHH36YNWFUw4YS5wcSE/j112I58/aWkqEpKTmO3dEUJ70bDaPqXencmPL1HrsjUQYmRYlj4cKFhpRdHOTridJ7IfDykpCGkyfhf/8Ty8yRI/DII1LK6JdfbOEN4eESgzZ2LObwcOqcPIk5PFwSw1atKrvQDiS7sbdqJd5M0dE2TyazWXbzn3hCIgXHjpXd/sKknirxei/BqPluTJTes8dslqTf48eLQ6qVXr3gySdlvwAkDdLPP8seQs2aEBVla5uQIF5Q48bJ/5qWfR4m6/PjxhViT+Htt8WwdOGChGaPHw8NGsiCfP26eEJZefllTowbB+vW3WZ4cgTFWe93O0ad70rnxpSv99gdiTIwKRQKhVEoVw7eektC5z77TMIXjh+XO5T69WXrOyBA4jMAU7p1xvpIXJzEa+Rra9v+uLpKeqmFC6WQntWT6fp1cbjq1Qvq1RPnrRMn9O6tQqFQFC19+4pBKSJC0h3NmyfRaO3aQZUqYtOx8uSTsuRfuZK1gl12aJq0Cw0tZAd9fSVU7qefxNp16pS4mVq5fh1+/JHmc+dK6F358jKoSZNg69YSEcqtUCgUiqwoA5OixNGmTRtDyi4O8vVE6b0I8fCA114T49JXX8mdyOnTcqeiaTnffVifL9TWdsHI79irVJGKTBERkl/2ySfFnnbiBEycKJW0e/eGP/+UkuE5kR4dyPDh8PXX/gwfrlt0oO7fOz1R892YKL3fOT4+sj/w5ZdSRPTEiazF4rZvh8TE/J/PbBaDVZFSowa0b2/732KBb78lYeBAifG7fh1WrJCNkI4dJW9gZvKyjN0BJV3vJRmjznelc2PK13vsjkQZmBQlDouO5db1lF0c5OuJ0rsdcHeHl16CY8ckpiw/FNnWdv4o6NhNJknx8fPPcO6cGJR695bXVq2Chx4SY9STT4ohKvP9SqboQMLCYOtWd8LCdIsO1P17pydqvhsTpfeio1SprP9HREDr1gXpjxip7Bq1VqYMPPkk0Z9/LuF0+/bBt9+KpczLS8rnWTl9WjyigoLgxx+lssOdGpwy7SRUf+gh9NxJ0Pt7pydGne9K58aUr/fYHYkyMClKHLt37zak7OIgX0+U3u2Im5tsbZvz+ZNgl63t7CnM2N3d4cEHpaz3iRMSKlenjuQi+eUXuXdp0kRC66ZOzRIdmJG7Sc/oQL2/d3qi5rsxUXq3H6VKyfqX32UeYOdO8QTt2FEKK/z5pzi+FjW7d++W3YFmzeD55+X3JTYWnn7a1mj1ankuNBSeeSSv5t0AANbdSURBVEbioatXl12DP/6A8+fzJ+yWnYQy27ah506C3t87PTHqfFc6N6Z8vcfuSJSBSaFQKBRw6VL+M2JbLHD5sn37U8TUqiV5zo8ckfuUhx6C0qWlqN6ECZLvvJhFByoUCkWREhBQsMIHHh5S/2HrVvjuO1k333rL9rrFAosXi92nyHFykkXayqhRsGEDfPAB9OghFrOzZ8Xq9eijkiTcysWL2RucwsOL306CQqFQ3GUoA5OixOHv729I2cVBvp4ovduZChUKtrV99iwcPWq//qRT1GM3m+XeZPp0uf/45RfJb54fHBwdqPv3Tk/UfDcmSu/2JShI8mibsi8gl4HJJO1iYmSZ//tviabu1Am6d7e1O3xYqnhWrCgFFUaPhq+/lvDjghji8zX2UqWgSxd4913ZJYiLg5UrpWJdp06ysFv5+WeJhW7a1OYRdfZs5hJ62cvQYSdB7++dnhh1viudG1O+3mN3JM56d0BRMpg8eTKTJ0/m5s2bAISFheHh4UFgYCArV64kPj4eX19fOnTokFGGsU2bNlgslgyXQH9/fzZs2MClS5fw9vame/fuhIWFAdCiRQtcXFzYsWMHAIMGDWL79u1cuHCBcuXK0bdvX0LT7+osFgudOnViy5YtAPTr14/9+/cTHR1NmTJlGDx4MDNnzgSgUaNG+Pj4sHHjRgDuu+8+oqKiOHXqFK6urgQGBjJz5kwsFgv16tWjWrVqrEvfBevRowenTp3i2LFjODs7ExQUxO+//06FChWoVasW9erVY9WqVQB07dqVmJgYotJrAo8ePZr58+eTlJRE9erVadKkCcuXLwegU6dOxMfHExERAUBQUBBLly7l6tWrVK5cmTZt2rB48WIA2rdvT3JyMvv27QPA09MTs9nMlStX8PHxoVOnTixId+dunZ5cYdeuXQAMGTKEzZs3ExsbS/ny5enRowfz0sOamjdvjpubG9u2bQNg4MCB7Ny5k/Pnz1O2bFn69+/P7NmzAWjSpAml03cRQ0ND6d+/PxEREZw5cwZ3d3f8/f0JCQkBoGHDhvj6+rJhwwYAevXqxdGjRzl58iSlSpVi+PDhzJ49m7S0NOrWrUvNmjVZs2YNAN27dyc6OpqjR49iNpsZOXIkc+fOJSUlhZo1a3Lx4kWuX78OQJcuXYiNjeXQoUMAjBw5koULF3Lt2jWqVatGs2bNWLZsGQAdO3YkMTGRAwcOADBixAiWL19OQkIClSpVol27dixatAiAtm3bkpqayt69ewEICAhg3bp1HDp0CD8/P7p27cr8+fMBaNWqFWazmZ07dwIwePBgtm7dSkxMDJ6envTu3Zu5c+cC0KxZM9zd3dm6dSsAAwYMYM+ePZw9exYPDw8GDhzIrFmzAPDz88Pb25tNmzYB0KdPHxYsWICbmxulS5cmICCAGTNmoGkaDRo0oHLlyqxfvx6Anj17cuLECY4fP46LiwsjRowgNDSU1NRU6tSpQ+3atVm9ejUA3bp14/z58xw+fBiTycSogABI72++iIqC+vW53K4drs8/zwKTCc3ZmQ4dOpCUlMT+/fsBCr1G/Prrr1SsWLFAa0TTpk3x8PDI1xrRpk0j6tf34+jR0jmW7c6M2azx7bdncHLakO0aMWfOHG7cuFEka8TatWupWLFigdaIYcOGsWbNmkKtEdY8AceOHcvQTV5rhKenJ5s3bwagb9++hV4jzp07R8eOHQu0RjRs2JB//vkHKNwa4eXlhcViKdAacfnyZSpUqFAka8TFixcZO3ZsgdaIyMhITp8+Xag1okaNGoCs82az+fY1YtQowsLCuH79OjVq1MDPz48VK1YA0LlzZy5fvkxkZCQA999/P4sXLyYxMZGqVavSsmVLlixZApDrGnHt2rUMXYH9riOyWyPCwsIoXbq03a8jclojSpUqRe3ate1+HfHLL8MJCnJBuH3NM5nEyPLoo+u4ebMtR49uBmLp1688H38sa0RIiFxHHDjgRdWqZTl71pNjxySd34wZch5nZ40HH9xBv36HadKkCR4envz772bM5tvXiNKlS3Pp0iXgDq4jnn2WNU2bwsqVGWuE9+rV1DOZMEVESPKp779Hy3a02ZC+k5A4dSoLPD2BormOyGmN2LNnD1q6Ycue1xG3rhFz5swB5PegevXqRXMdUcA1Ytq0aXh5eRVojSiqe42LFy8ybty4IrmOKOgacebMGVLSk5vZ+zri1jUiPj4egPj4eFauXAnY5zoCsr/XCA0Nxd3d3SHXEdnda7i6ulK9enW7X0dkt0ZMnTqVihUrOuQ6ArKuEQ5HUygKQHx8vAZoMTExuvXh77//NqRsPeUnJydrEydO1JKTk3WRr2lK73bn+nVNK19e00wma6RY9ofJpGllymhanz5Z21aurGn/93+advx4kXbLEWO/997ch3zr0by5pjliKqj5bjzZespXejeO3ufPl+UeNM1stmR5LF9e08LDC3a+uDhNW7FC0z78UNOGDtW0SpXk3PPn29osWqRpnp6adt99mvb22/La+fPyml3GHhuraXPmaNqzz2pa48YFW+TNZk0LDCz6PmWDmu9KtiPRW+9GWmeLk+yYmBgN0OLj4x0iT3kwKUoc3t7ehpRdHOTridK7nXFzg2nTJP+EyZR9CIE1riIkBIYMkWyvv/4Kv/0m8Wb/+x98/DH06ydl2oYMAefC/cw4YuzW6MD85ibZt09CQgYOhGHD5LFs2aLvl97fOz1R892YKL07hqFDJWIsNBTmzLGwe/cpWrWqyfDhTowYIT8HBcHTE+67Tw6Qn49Tp8DHx9Zm2zaIj5eiC+kOAoDkx6tZsyfNm0uO7yKjQgUIDJQDpKpDundEnlgsEB0tA8krnrCQ6P290xOjznelc2PK13vsjkTlYFKUOLpnTgBgINnFQb6eKL07gCFDpJqOlxcAWnpOJusjXl4wf760AylJ9NFHUj46NBT69JEL8qVL5aK+Zk3Jl3Hy5B13yRFjL2jiW09PuHoVZs6UvLM+PpKH5NdfJWdJUaH3905P1Hw3JkrvjsPNDcaMgRkz0hg3bjozZqQxZkzBjUvZYTKJ4ahMGdtzb78Nu3bBTz9JTu6mTaXdyZOwfn3lLHacWbNg/Hj4/XfYvx/SszMUjipVCpZncMsW6NUr63N2KDOu9/dOT4w635XOjSlf77E7EmVgUpQ4rLHURpNdHOTridK7g7BubQcHYxk6lOO1a2MZOhSCg+V5q3EpMy4uMHw4LF8uZdrefBN8feHcOfjwQzFEDRoklXnS0grUHUeMvaCJb8+elY3wN9+Ehg2lytLixfDEE3IP0707fPVV4ct56/290xM1342J0vvdi7MztGolhqPffhPDUXw8rFoFo0fvxs/P1nbBApgyBR57DJo3l72Nnj2l4ufcuXeYfzvTTkIyrgQzhuGE0oNVDCeUYMaQjKutvZOTLPBWbtyQ37WePWXjZOlSGUAhudv1nhtGne9K58aUr/fYHYkyMCkUCoUiK+lb22kzZjB93DjSZswg31vb9erBpEni1TRzpuwAa5pYYPz9oXZtmDgRzpyx9yjyjTU6EHI2MlmfnzYN3N3hnntkmJGRcOCA2NHatpX7l/Xr4ZVXoG5duaF6/33YuzfnwkUKhUJhRMqWFXvNkCEHcXKyPf/ww/DGG3DvveIFlZgIa9bAJ5/IhkDmfYqVK+W1xMQ8hKXvJIQzlKqcZSzBhBHAWnoSRgBjCaYqZ1nAENlJuHhRFnYru3fDpUsi7MMPYcAAadeiBTzzDKxdW2Sfi0KhUJRklIFJUeJo0aKFIWUXB/l6ovRewihVCu6/X67+o6Lgtdckliw6WiwutWqJt9SiRbnGPzhq7LdEB2ZEUuQUHWjFZIImTST8Y/t2Cff45hupmG02w549Yk9r2RLq15ePYePG/IV8lEi9FxFqvhsTpXdjcuvY77tPjElr1oiT0N698Msv4iU6fDh4eNjavvOOGKk8PcXb6fHHpe2ePbc4zLq5Ef7MUgKYRxxeAFhwyvIYhxf+hBH+zFIxHlWsaHt/u3bidvXzzzB2rGymaJok5fvxx6z5nS5cgG+/hZ078/TaVXpXso2E3mNXencMKsm3osTh4uKSd6O7UHZxkK8nSu8lmAYN4LPPZNd37ly5QF+7VuIgFiyAGjXkruCxx6BatSxvdeTYMye+nTcPzpxJonp1d4YNI9+Jb2vWhBdekCM2FhYulHMtXy4lvL/4Qo5KlUTesGHi5OXqevu5SrzeC4Ga78ZE6d2Y5DZ2JycxHFmNR7dSv77sW5w+Lfaf/fslBA/kpye9ojvJyTD2+w5g0tC07F1VNcyYTBrjfujA2XduWfPNZkkc1bSpFLEAKW6xcaMc/frZ2q5eDS++KH97eEDHjtC1K3TpIu6vmapCKL0r2UZC77ErvTsG5cGkKHHs2LHDkLKLg3w9UXq/C3B1hdGjZVv64EGJI/P2ljuD994Tr6aAAFiyJMPFx9Fjtya+nTMHXnppPnPm5D868FZ8fGDcOPF8unhRDFcPPig77RcuyC77wIGS1mP0aElse/Wq7f13jd7vADXfjYnSuzEpzNiDg6Vi3dmz4oX61ltitC9bNmtVulmzxBsqJ+OSFU0zceWKrNd5UrmyuFR9+SW0bm17vnx5CaHz9JTYvZUrxXO3b19xh12yJKPpzq1bCzTeuwmjznc1140pX++xOxJlYFIoFAqF4/HzE1ee6Gj480/o1k2MSvPni9WlXj346CPcrlzRu6dFgoeH3If8+adUmlu2DJ56SpKCJyTAjBkwcqREZAweLDvwCQnZuDUpFAqF4jaqVJE0f//7n9hz4uJsnkwgKQHzi9ksnqd3TL9+knfw8mWJ7/vxR9mpqFNHEvU1b57RtPHCheL6Ono0fP+95HoqkrJ5CoVCoQ8qRE5R4hg0aJAhZRcH+Xqi9H6X4uYmbj0PPggREVI6aNo0SWb0zjsEODvL3cL48ZKYoyBlpguJvT73UqVkI7tvX5g8Waphh4XJDc3hw5KWatEiMJuH8fff4tQ1bJjkRzcKar4bE6V3Y2KPsZvN4khk5dq1/L/XYpHw5gEDxDHJetStW8CfILPZFt/31FPy3LlzYg1Lp0l8vHjxzpghB4j71T33SEjdK69kCam7mzDqfFdz3Zjy9R67I1EeTIoSx/bt2w0puzjI1xOldwPQpAl8/bXEOkybBp07Y0pLk7xN/fpJQo1JkyS+zAE44nM3m6FTJ0loe+iQ5A/573+hTRuwWEysWyf3F3XqyA3OBx9ITtm7vSKdmu/GROndmDhi7BUq5N84ZDLBjRuwdCl8/LHUq2jQQKLbuneXcLs7JpNxCWDTc8/BP//YQujKlpVY6RUr5Ichc3z2jBkiPDr6zuUnJ0NwMM6jRjH2jz9wHjVK4gyTk+/8nHeIUee7muvGlK/32B2J8mBSlDguOOjmsrjJLg7y9UTp3UCULi1VesaOZfGnnzLw9Gm5AD52TBJs/Oc/4tYzfryUD7KTV5OjP3eTyZZD9p134Ntv56Np/sybB+vXS+TE7t2SrqpePfFqGjZMNrod6NjlENR8NyZK78bEEWMPCJC9ivygabLOVqoEu3bJsW+f2H3Wr4cHHrC13bVLko+3bi0bA61bQ4sWUKZM/mSdTUiAQYOgd2954uZNEbZxo4TYZU4M/MEHkr8QxKW1Sxfb0bSpZETPjfBwSQx45Qpms5k6Fgva6dPiQvvii7Kxc2upVDti1Pmu5rox5es9dkeiDEyKEke5cuUMKbs4yNcTpXdjojVtCm+8ITu5M2dKBbotW2D2bDnq15eKPuPGZS0pXQTo/bnXq+fMoEFy3X/xohTcmzdPNraPHoXPP5ejcmXJPTJsmNjbSpXStdtFgprvxkTp3Zg4YuxBQbKWxsXl7gFqMomn0oQJWZ2HUlMhMlIMSt262Z7fvh127pTDmvPJZIJGjcTY9NJL0KFDzvJuG7uTE7RqJUdmLBYJE3dzgz174MQJOf76S15v21Y6Y+XGjaw/BuHhYmWzjtNiyfJIXJz8kISFSYlTB2DU+a7mujHl6z12R2LStLvd0V5RlCQkJODp6UlMTAwVi/hmLr+kpqbqVupRT9l6yk9JSWHSpElMmDAB1+zqqTsApXel9wz27JFcTcHBtrJrLi4QGCheTT16yBW+PWQ7kJzkJyZK6Ma8eZInJCHB9lq5crIZPmyY5A/x8Ci43GKrdwPI1lO+0rvS+92u9wULxIYC2RuZrD8b8+fn35HnwgXYsMHm6bRrl6RZsrJihdiFQNbrKVOy5nWqUiWVUqUKOParV2WjZcMG8XT691+xoP3+u7yeliYbLg0aiHdT+/bwzDPyY5Ef69rZs3dWOrWAGHW+6ylb7/lu1HVWb9kXL17E19eX+Ph4hxi67jKneoURCM1X7di7T3ZxkK8nSu/GJNuxt2wp2bHPnYNff5WL59RU8XDq1ctWoS42tuhlO5Cc5Ht4wIgRsnF98aIYm8aPF0+mhAQICZGcIT4+cpP0++/5+yjSU3MwapQzf/wxllGjnPVKzaHmu0FRejcmjhr7kCHioOPlJf9bQ4utj15eBTMugYTRDR8OH34oxRnOnoXz52HJEvjoI3EssrJ+vRi5PvjAVrihQgULvXvDa69Jru98UbasWK0mThQL1pUr8ptnZf9+8Ujatk3yGj74IMTH5528T9PkXA7Sh1Hnu5rrxpSv99gdiTIwKRQKhaJkUqYMPPYYbN0KO3aIlcXDA6Ki5Gq9WjW5sF637q7Nil2qlOQ//+knyfu6caMMvV49SEmRHfPHHpOboB494JtvpEDfrYSHQ9WqkvoqPNzMyZN1CA83M3asPL9ggcOHplAoFEXO0KFiBAoOloixxo0vEBAg/589WzQpiCpVgv794f/+L2sluwcflDV43DjZJ3F2hsREV1atEvvQzZu2ttOni9PRL79I5Fuuhn5n56yCWra0hc89/bS4tqaTjCvBjGE4ofRgFcMJJZgxJJPuzWI2i3usQqFQ3CEqB5OixNG0aVNDyi4O8vVE6d2Y5HvsbdqIleWzz8SF5+efJSnG33/L0bix5GoaOxa8vXM+T3Ky5HYKC2PIqVOykxsQIOEHDggZyExB9W42Q+fOcnz6KRw4IPcJ8+ZJ2MbatXK89JKEZliThB89Ko9WLBZTlkcdUnOo+W5QlN6NiaPH7uYGY8bIsXfvBVq0qOQQuS1ayGElJQXCwg6TmNiAAwegVi3ba/PnZ01K7uQkhVatoXVPPgnu7jkIMpnkZLVqSUbyiAhYu5ZwhjCOqVzBGzM3seCEmZvMZTgv8g3TeJghloWyKfO//0nyqA4dshioihKjznc1140pX++xOxLlwaQocXjcSVKRu0B2cZCvJ0rvxqTAYy9bVq68d+yQ8IDHHxdPp4MH4eWXbW46Gzfe7tWU2Y0nLAyP7dvFqqKTG09h9G4yQbNm8O67Ymc7fhy++kpKbJvNYnD6z3+geXNJXaVpOTt5WZ8fN85x4XJqvhsTpXdjYlS9u7pC+/ZOPPYYfPll1tSBjz4Kr78ukXAVKtiKy02fLgnIM6dymTw5a4jebWt5hQqEm/wJIIw4vACw4JTlMQ4v/JlPOEMkpvrtt6FPHzmpldOnJfdTEf0QGFXvaq4bU77eY3ckysCkKHFs2bLFkLKLg3w9UXo3JoUae7t2El9w9iz88IOEDaSkSCxE165iXfnuO8k5Ya2wExcn77VW1rm1wk54eCFGUzCKUu+1a4vn0tq1kh/k119h8GCJrLAOMTccnJpDzXeDovRuTJTeb2fQIPFEXbFCcu2dOiVeTRMnwnPPZTUwTZkimwmDB0tkeOXKEqL31lswZw4kDwxknCYJwLUcbv2sz49jKskjH4ZRo6BuXclxaCUkBO65Rzya2rWT8Ls//pCcT5nj+wo5dkdgVNl6o/fYld4dgwqRUygUCsXdTblyciH81FOSr+nnn2HGDIkhe+EFeOMNm5UlNzcek0nceBxUYcdeVKwoeZkee0xsZgsW5C9FlTU1x5gx9u+jQqFQKASTCWrUkCO7MGVrKsJduyAyEmJiYNkyORo1gqQ3grhCqTzlaJi5gjeh/aYw5pFs2t+8KT8gFy+Kl/COHRKaDuIpvG2bhKMDXL8uv5NFUNFVoVCULEyadpdmPlUUKZMnT2by5MncvHmTqKgopkyZgoeHB4GBgaxcuZL4+Hh8fX3p0KEDCxcuBKBNmzZYLBZ2794NgL+/Pxs2bODSpUt4e3vTvXt3wsLCAGjRogUuLi7s2LEDgEGDBrF9+3YuXLhAuXLl6Nu3b0b2/Vq1alG5cuUMS3C/fv3Yv38/0dHRlClThsGDBzNz5kwAGjVqhI+PDxs3bgTgvvvuIyoqilOnTuHq6kpgYCAzZ87EYrFQr149qlWrxrp16wDo0aMHp06d4tixYzg7OxMUFERISEhGH+rVq8eqVasA6Nq1KzExMURFRQEwevRo5s+fT1JSEtWrV6dJkyYsX74cgE6dOhEfH09ERAQAQUFBLF26lKtXr1K5cmXatGnD4sWLAWjfvj3Jycns27cvo0979uzhypUr+Pj40KlTJxakh+20bt0agF27dgEwZMgQNm/eTGxsLOXLl6dHjx7MS0/c2Lx5c9zc3Ni2bRsAAwcOZOfOnZw/f56yZcvSv39/Zs+eDUCTJk0oXbo0ISEh1K9fn/79+xMREcGZM2dwd3fH398/43Np2LAhvr6+bNiwAYBevXpx9OhRTp48SalSpRg+fDizZ88mLS2NunXrUrNmTdasWQNA9+7diY6O5ujRo5jNZkaOHMncuXNJSUmhZs2aVKpUKaO/Xbp0ITY2lkOHDgEwcuRIFi5cyLVr16hWrRrNmjVj2bJlAHTs2JHExEQOHDgAwIgRI1i+fDkJCQlUqlSJdu3asSjdBbxt27akpqayd+9eAAICAli3bh0XLlygcuXKdO3alfnz5wPQqlUrzGYzO3fuBGDw4MFs3bqVmJgYPD096d27N3PTEyg0a9YMd3d3tm7dCsCAAQPYs2cPZ8+excPDg4EDBzJr1iwA/Pz88Pb2ZtOmTQD06dOHXbt2ERsbS+nSpQkICGDGjBlomkaDBg2oXLky69evB6Bnz56cOHGC48eP4+LiwogRIwgNDSU1NZU6depQu3ZtVq9eDUC3bt04f/48hw8fxmQyMWrUKMLCwrh+/To1atTAz8+PZcuWceTIER544AESExOJjIwE4P7772fx4sUkJiZStWpVWrZsyZIlSwDo0KEDSUlJ7N+/H6DQa8Ts2bNxcXEp0BrRtGlTPDw8cl0j5v7+O7U3bKDphg2UPnqUgrD5mWc40bVrtmvEnDlzuHHjRpGsEXv27MHFxaVAa8SwYcNYs2ZNvteILl1usHdvLjmpbqFs2WQefjiKF19swrZttjXC09OTzZs3A9C3b99CrxHXr1+nUaNGBVojGjZsyD///AMUbo3o1asX27dvL9AacfnyZSpUqFAka0RqaipDhw4t0BoRGRnJ6dOnC7VG1KhRg5UrV1K/fn3MZnO+1ogVK1YA0LlzZy5fvlzoNaJs2bLce++9dr+OyG6N2LZtG5cvX7b7dUROa0SLFi1ITk62+3XErWtE27Zt+e6776hfvz5t00ue2eM6Irc1olu3bhnz0Z7XEdmtEfv378fFxcXu1xE5rRFJSUkZOi+K64iUFCfM5pacPu3DqlVX8PRM5saNBixZ7IJFyztwxWyy0P3eKzz55PLsryNq1WLr7Nl4Hz1Ky5QU2LYNtwMHMKel4XTtGmFLlnD9+nV6zJhBpU2bOFejBpfq1aPSoEFcqFmTAxcuALJGzJs3j9TUVLtfR2S3RqSmphIQEFCo64g7XSPKli2b0V97X0fcukbEx8dz5MgRnn76aVauXAkU/jqiIGvExo0bM9b6gqwRRXWv0apVK65evWr364js1oiwsDBcXFwcch0BWdcIgAceeID4+HjK2SmnWhY0haIAxMfHa4AWExOjWx/Wrl1rSNl6yk9OTtYmTpyoJScn6yJf05Te9cAQerdYNO3ee60piPI+zGZNCwy0b5/ScYTeAwNlSPkdfuajfn1Ne/ppTZszR9OuXCnafqn57ngMMd+LqWw95Su93/16L8hPHGhajx7y0/j885r29deatnKlpl24kIuAtDRNO3Ik63Pt2mV/8rp1NW3UKE1LTTWs3vWUrfd8N8J8K46yY2JiNECLj493iDwVIqcocURHRxtSdnGQrydK78bE7mMvqPu+xQKXL9unL7fgCL0HBGStVJQXw4ZJ+MW//8KRI3L8+KOEz7VvLzlh+/SRNB2l8o7IyBE1342J0rsxUXq3LxUqyBqdn3x7ZrMUWj1/XlIUZsbXV4pHNG8uOZ76909/wckJ6tXL2nj9eti9W8Lmtm6VIyoKjh2T152dbWN/6ikJv2vfXqrWNW2aNcmUHTDyd05P9B670rtjUAYmRYmjTJkyhpRdHOTridK7MXHI2Aty9Q2SbXXdOkkUbrZfrQxHjD0oCF58UXKY5xYwbzKBlxf8/bek1UhIgDVrJAHtihVw6JAUF9qyRaoZlSkD995rMzg1aVIwW56a78ZE6d2YKL3bl4JsJFgsspFgNkvi8H37JIf30aOyubBqlRxms83AdOUKPPywzfjUrBk0auRGqXvukd0GK3FxsH07XL0KpI/dYpHk4QkJUn0CoHRpaN1ajE333isDKAqSk2H2bAgLo09UlFStCAiQH0IH5lXU+zunJ3qP3chrjSNROZgUBSIhIQFPT09iYmKoWLGiLn2wWCyY7XhTV1xl6yk/JSWFSZMmMWHCBFxdXR0uH5Teld7tSHAwjB1b8PdVqSIXpiNHykV0EffTUXpfsECSfUP2RiarYWj+fBgyJPtznD4N//wjxqZ//pEcsJmpUkXKbffpI49VquTeJzXf1Xw3kmw95Su93/16T06GqlXzv5GQXR2La9fg4EGbwalvX+jXT15bvx66d8/a3tlZEow3aya1MTK8nTJhsVgwWyywcKHNy2n7doiPtzXq21eylVv59FNJJN6+vZTLyy/h4dKRK1dsG0rWx/LlYdq0nH/gihg9v3N6z3cjzLfiKPvixYv4+vo6LAeTfhpWKO4Qa1I9o8kuDvL1ROndmDhk7EFBcoGZl4uNyQQeHlJGzdMTzp2Db7+FLl2gVi145RVx4SmifRtH6X3IEAgLkxsLALNZy/Lo5ZW7cQmkutEjj4iH0/nzUs3os8/k3sDNTT4qqx2valXZ5X7lFVi8WG5cbkXNd2Oi9G5MlN7ti5ub2E8g55856/PTpmXvzFOmDLRrJ+v8F1/YjEsAdevC99/D+PHyc1iuHKSlSaHWmTNtUXEgUXMdOkjlu4cf3s0/a5w5f08A2kf/k92Jy5elFN706fD88zBihO3NMTHw5ptSSq9KFahZU17/9FNYvVq8oLIjPFw8leLi5H+rt7L1MS5OdlnCw3P+EIsQvb9zeqL32I281jgSFSKnUCgUCmNjvfr295er7NzceP7+WywtKSnirjNzplhfzpyBr76So1YtuP9+Odq2LRFlmocOlV3r0FCYM8fC7t2naNWqJsOHOzFiRMGiB8xmaNVKjtdek93zjRtt3k07d8oO+P798nG5uEDnzjbvpnbt7DVKhUKhMCbWjQSbE4+GxWLKePTyunMnnmrV4Nlnbf9rmvwkWr2deva0vWZNyySFxdrw55/yvI+PeDu9+66ZXr0aQaNGaGMeyvrzmZwsA9i2DSIixHX29GmYM0def/pp+OEH+TslRTrQsKG8B0jWSjGbIMII4BLeVOAyAYQRpM3GzXRD2mXnvqVQKAqEMjApShyNGjUypOziIF9PlN6NicPGfvvVd1YX+luvvl1dYfBgOZKTYelSmDVLdkBPnhT3nc8+k61dq7GpVasCGZscrXc3N3HOCgpKY9Kk6eku9E5Fct7eveUAiI2VHB7W/E0nT8LatXK884581G3a9Cc+XoxOt+aOtTd6zze95euJWueNidK7YyjKjYTcMJnEq7VGDRg4MOtr/frJT+X+/bB+fRxnznhx5Ij8LqxZA2+9ZWs7a5Y4LNlyO9Wk+ct/0KgRuN64Cjt2ZE0i3r697c27dkGnTpKA/OZNwhnCOKZyBW/M3MSCE2ZuMpfhvMg3TNMeZsiVhfLhjBlTNB9EDuj9ndMTvcdu5LXGkSgDk6LE4ePjY0jZxUG+nii9GxOHjj3z1fe8eSSfPYtb1aqS8TS3q283N3G/DwiApCRYskQ8mxYulNiASZPkaNBADE0jR8oVcx7GprtV7z4+NpubpknyWKuxadUqiVZYtao8q1ZJ+zp1bPmbevWSnOz27Z+a73qh1nljovTuOOy1kZBfrKkLg4Lg1KkEatb0IinJlt8pswfrvn2yAXHyJCxaZHve2RkaNizLtGk9aPd6DwCuXwfXUpot98v581IO7/JlwhlCAGEZ77fglOUxDi/8mU+YKZCh8+bZ3cCk93dOT/Qeu5HXGkeicjApShwbN240pOziIF9PlN6NicPHbr36njOHeS+8IK73Y8bkf2vX3R2GD5et14sXxdAUGCjvP3wYPvoIWrSQsmoTJ4qbfw4YQe8mE9SvL5ENc+fKLvbmzRAUtJfu3eVG4vhx+OUXMUhVrCib1G+9JcaolJSi75Pen7ve8vVErfPGROndmFjH7u4u0eTjxolNyMqrr4pn6+TJ8NRTUrjV01PyO0VEZG37xRdQtpyJDh3g0Ufhq+MBrAiJ5UTLoYxjKgBaDre91ufHab+TvGkn/PyzeERdv26PYSudG1S+3mN3JMqDSaFQKBQKe1CmjM1V5+pVKdc2a5Z4OEVGwvvvy9Gsma2dgVyos8PZWQryDRt2gNGjW5CYKDcY1vxNBw5IkaHt28UprHRpqV5kzd/UokWJSHmlUCgUijwoX17W98wV6jQNoqPFu6l2bdvzBw+KA7EtvxOACZifL1kaZq7gTej5Lox56il50skJ/Pzgzz8lxB1sofMKhSJHlIFJUeK47777DCm7OMjXE6V3Y3LX6L1sWXjgATni4yVX06xZUn7ZmvH6P/+Bli0zjE1K71K0b9AgOUAiGP/5x2ZwOn9ePkJrFWtfX1s43X33QfXq+ZOXnAyzZ0sarvPnhxMaKhGPQUGOz/eq9G482cVBvp4ovRuTOxm7ySTr+q1r+/Tp8hO6f78tufi+fRAVZS3akffOg4mb/F3xJR5sdRHT7l3ihXzggPywWHn/fRHWujW0aSOPrVtL7F8+dzeUzo0pX++xOxJlglWUOKKiogwpuzjI1xOld2NyV+rd0xMeekg8mi5cgD/+gP79xX1nzx54+21o0IDSXbtK+eXjx+3Tj2JMTp991aowdiwEB4uxad8++PJLGDBAwixiYqTQ3yOPSILZxo3hhRfko756NXtZ4eG284aFwaZNpQgLk/+rVpX3OhI1340nuzjI1xOld2NSlGN3chIH4OHDJfo8NBQOHYJuXSzkx7gEoOHEkottSQlfJr/NZ86waOI25m6uQkQE3LiBlEE9cQLmzYN335VCH9WqQeXK8jt+6VKecpTOjSlf77E7EmVgUpQ4Tp06ZUjZxUG+nii9G5O7Xu/ly0viiSVLxB3nl1/E/cbJCY+oKCmhU7cudOwoSSYM8l3Iz2dvMkl04csvw+LFcPkyrF4t9rkOHSSKITISvvtO8rd7e0sOj/ffh02bJI9HeLh4KsXFyTktlqyPcXHg7y/tHIWa78aTXRzk64nSuzFxxNgrVnLCbNLybgiAhoeHSbxWTSaoVo3/LW/H8BEmmjaVTYxGkWH4d45hQs8tTOv0E1qTpvJjExMDGzZIGVQrTz0F3brJLscff8Du3XDjhtK5QeXrPXZHokLkFCUOV1dXQ8ouDvL1ROndmBhK7xUqwOOPy3HxIrvefZfWUVGShMhahvm116T08v33S/xWtWqO7aODuJPP3tUVevSQ48MP4coVSQRuDac7ehQ2bpRj4kSJWkxOlpweOaFpcp8xbpx4TDkiXE7Nd+PJLg7y9UTp3Zg4YuwBATB3bn4T85mYPDnrM23bQmqqbFZcvQpRR5yIOlKRcCpSo0YHHj41XpI/7d/Pqx+WJ/kFJ/z8JHVT45WHqHZkA6YNG2wnLFWK/tWrw7p18MMPhksaqPf33chrjSMxaVpul1YKRVYSEhLw9PQkJiaGihUr6t0dhYNISUlh0qRJ6eVsjbNAGh2l92LC+fNSYm3mTFi/PqtFpGtXGDlS4gKqVCkScXer3o8fF2PTihWwcqUYoApCcLDdq1fryt2qd0XuKL0bE6PoPTlZQp3j4nLfTDCZxPkop40ETZPXIiPlOHhQcgROmmRrU6WK/FxnxsMtlUblztPVZQtfJz4uORgBS9PmmPfvtTUcOVI6Yc3p1Lq1lE0tKtITDd6cO5dTu3ZRs3VrnAID9Uk0qHA4Fy9exNfXl/j4eMqVK2d3eSpETlHimDlzpiFlFwf5eqL0bkyU3pHcDs88I55MZ87At99Cly7y2oYN8Pzz4snUowf8+KO46pdw7PHZ16kDTz4pybwvXoSePfO/eWw2i43PEej9vdMTNd+NidK7MXHE2N3cYNo0+Tun9d76/LRpOdta0iPm6N0bnn0Wvv8+q3FJ0+CTT+Ctt8Rrys9P0iomJruwI6YGexqMkF2NY8fY8MorNIjdhJ+ftJ3whoWpc8uxZeZx4if8D/r1k8Ti1avDkCHym18YwsNJrlKH4LHLuT/sIR45+Qf3hz1E8NjlJFep49BEg3p/34281jgSFSKnKHFYrMkxDCa7OMjXE6V3Y6L0fgtVq4pB6fnnxdg0e7ZUo/v3XzFArV0Lzz0n1pP774fAQPDxcXznC4m9P3snJ8mzlF8fbotF8jD16ydOY126SFqsMmWKvm96f+/0RM13Y6L0bkwcNfYhQ6SAw7hxYuMxm2VNtz56eYlxaciQO5dhMklhiMykpkpo9sGDULp0eqM6dTjc7B6OXfCAC5KIfD5m4Bdbf91XEp50H0RHQ3Q06+NbUCdQDFwmNLFKNWhg83Rq1Eh+1LIjPJxw/98YxwGu4I2Zm1hwwsxN5hLIi3GXmTZ0HEPma5Ks0M7o/X038lrjSJSBSVHiqFevniFlFwf5eqL0bkyU3nOhenXJcP3yy3DypBibZs6E7dslBmzlSvF86t1b3O8DAiTTdU6ku9A7z53L2F27cN69WwxUOrjQO+Kzr1DBdoORH27ehOXL5QC5nm/d2mZw6tKlaKIU9f7e6Yma78ZE6d2YOHLsQ4dKiFtoqBSAO3Eigdq1yzFsGIwYYZ+fOBcXMvIxZaZJk1qcOWMLtcv8ePYsVHqgN3wRD3v2kLx1L/e+/gxaDQnJ86t7A7+9I2jMQfyYQyvepW7p89CihfwgDRkCAweKoORkwh+YQQDzMmRbcMryGIcX/oQR9sAYhsb2tftvvd7fdyOvNY5EGZgUJY5qOia11VN2cZCvJ0rvxkTpPZ/UqiUJwF97DY4dE6+mWbNg1y6bVWT8eOjbVzyb/P2zVrsJD8/Y3jWbzdSxWNBOn5Zt3xdfLPz2bgFxxGcvyV/z3/6//5WPbONGiUw8c0Zsedu3w9dfS5u6dW0Gp65d5cbCXMBkBHp/7/REzXdjovRuTBw9djc3yaM3ZgxER1+lWjX756LJjurVq1Gtmi3kLjMJCXD9OlCuHHTrRkytbjT8BY4cgcRE2L7Xle08lNH+Yec/mXr9IdiyhdQtO3h35/34xUDjxlB7zQzGXfseAC2HrDgaZkxYGHfte87+PRe3Rx+w17AB/b/vRl5rHInKwaQocaxbt86QsouDfD1RejcmSu93QN26MGEC7NwJUVFSUq1FC0hLg8WLxZBUqZJs6f75J8yYIdaWuDgATOkuPdZH4uLEIBUeXtgh5RtHfPZBQVC+fN55mEwmaffaaxJ9GBICp0+L09hff4mTWIsW0u7YMZg+XWx5TZtKdOKQIZKrY8MGcRLLC72/d3qi5rsxUXo3JkbVe26yy5WTn2crNWuKZ1NSkng5zZ0L//sfPPQQtG8PrT99QBqEhHD0sY/5ZGtPHnkE7rkHKk8YxxW8czQuWdEwcwVvQn+8WFRDzBG9v+/FVe93G8qDSZEvJk+ezOTJk7l58yYAYWFheHh4EBgYyMqVK4mPj8fX15cOHTqwcOFCANq0aYPFYmH37t0A+Pv7s2HDBi5duoS3tzfdu3cnLCwMgBYtWuDi4sKOHTsAGDRoENu3b+fChQuUK1eOvn37EhoaCkglu2PHjrFlyxYA+vXrx/79+4mOjqZMmTIMHjw4I5Fao0aN8PHxYePGjQDcd999REVFcerUKVxdXQkMDGTmzJlYLBbq1atHtWrVMhaAHj16cOrUKY4dO4azszNBQUGcO3eOkJAQatWqRb169Vi1ahUAXbt2JSYmhqioKABGjx7N/PnzSUpKonr16jRp0oTl6XEVnTp1Ij4+noiICACCgoJYunQpV69epXLlyrRp04bFixcD0L59e5KTk9m3bx8AN2/eZOnSpVy5cgUfHx86derEgvTkfK1btwZg165dAAwZMoTNmzcTGxtL+fLl6dGjB/PmiZts8+bNcXNzY9u2bQAMHDiQnTt3cv78ecqWLUv//v2ZPXs2AE2aNKF06dIAhIaG0r9/fyIiIjhz5gzu7u74+/sTEhICQMOGDfH19WVDeknWXr16cfToUU6ePEmpUqUYPnw4s2fPJi0tjbp161KzZk3WrFkDQPfu3YmOjubo0aOYzWZGjhzJ3LlzSUlJoWbNmqSkpGTI6dKlC7GxsRw6dAiAkSNHsnDhQq5du0a1atVo1qwZy5YtA6Bjx44kJiZy4MABAEaMGMHy5ctJSEigUqVKtGvXjkWLFgHQtm1bUlNT2btXKnsEBASwbt06oqOjWb58OV27dmX+/PkAtGrVCrPZzM6dOwEYPHgwW7duJSYmBk9PT3r37s3cdPeIZs2a4e7uztatWwEYMGAAe/bs4ezZs3h4eDBw4EBmzZoFgJ+fH97e3mzatAmAPn36cPnyZUJCQihdujQBAQHMmDEDTdNo0KABlStXZv369QD07NmTEydOcPz4cVxcXBgxYgShoaGkpqZSp04dateuzerVqwHo1q0b58+f5/Dhw5hMJkaNGkVYWBjXr1+nRo0a+Pn5ZXyGp06dIjExkcjISADuv/9+Fi9eTGJiIlWrVqVly5YsWbIEgA4dOpCUlMT+/fsBCr1GREdHExISUqA1omnTpnh4eBR6jTh37hxAgdaIOXPmcOPGjSJZI6xjL8gaMWzYMNasWZN1jUg3OHX09KTskiWUmjcPz+hoSey5YAHWNEQ52lk0Dc1kIu3BB5n7/feUqVDhtjXC09OTzZs3A9C3b99CrxHR0dFs2bKlQGtEw4YN+eeff4D8rxGPPlqVL7/sjskEmnb7J2Ayyafz6KPrmDfv7G1rxLBhAVSosI6uXS/j5lYJk6kz06YdISqqIseOVeTKFTMLF0L6Vx4XFwu1a1+iRYsERo2qyaVL4ZQrdyPLGhEdHU1cXFyB1ojIyEhOnz5dqDWiRo0agKzzZrM5X2vEihUrAOjcuTOXL18u9BoRGxvL1atX7X4dkd0acenSJUJCQux+HZHTGnH9+nV27Nhh9+uIW9eItm3bZujd+rc9riNyWyMAh1xHZLdGWNdZe19HXL58mQoVKtx2HZGYmJgxdnteR9y6RsyZMydD19WrV7fbdURua8SFCxcICQmx+3VEdmtEdHQ0CQkJdr+OyG6NSE5OztB5Qa8jataMITk5itq1Yfr00cyfv4CQnbJGuD/djz6nojh7thyxsT5cuJD/23wTFn7a1Q7fwOe495H+bLqawHnAp2LFIr3XiI2NJSQkpMBrRFHdayQnJ7N169YivY6A/K0R1rWmoGtEUdxrOBqTpuU3xaVCIcYdT09PYmJiqFiU5TMLwLlz56hSROW4S5JsPeUXh3K2Su9K70aSbXf5Bw5ICN2UKbfXVc6N4GCJL7AzjvzsM0UH3pb8tXz5O48OTE2VCMWNG21hdRcu3N6uUaOsYXVlypyjalU1340kW0/5Su9K70rvd6fsbj4H2XCpcYHfV4ZEPuN1nq4wG5o1I75he/Z3e5qG/evi45P/6qvZYdT5prfsixcv4uvrS3x8POXK2T80VIXIKUocp06dMqTs4iBfT5TejYnSu51o2hTefx86d85/kiCzWbKjOgBHfvbW5K/BwRIp2KZNPAEB8v/Zs3eeesrFBTp0kBzsoaFw7pzk0Zg6FZ54QnJkgFQR+u03ePRRaNgQmjXzITAQvvgCtmyBGzeKaKAlADXfjYnSuzExqt4dJdu3jjtmbuaztYa7UzJmbnIND8qZEuHSJVi7ln9/2UvXsXXx9ZVNl/YNrvBA9bW8120Vfz67mVP/RMmOSj7Q+/tuBL0XB5SBSVHiOHbsmCFlFwf5eqL0bkyU3u3MpUv5L6NmscDmzTB/vmQbtSOO/uytyV/nzIHXXlvMnDnyf1EW1DGZoF49ePhhcRyLiIDYWPGgevNN8WAqVQquXHFh3jzJ+XTPPeDpCT16wNtvw5IlGamy7krUfDcmSu/GxKh6d5TsgKerZFSLyxsTP/9i5nqKE5GRMPDMFNixA6ZOJWnoaGpWv4nJBPHxsP1IeUKi7+WDDb146IdOrOnzoZS4a9mSbQP+w0PDrvLBB5KvcPt2eY8Vvb/vRtB7cUDlYFKUOJyd9fva6im7OMjXE6V3Y6L0bmcqVLDFg+WHc+fEzadUKejeXcohDxworjeF8Zu/BaPovUIF8ZCyekklJ8Nnn63C1bVXRmhd+iYya9dKG5NJHNAyh9XVqnXnH39yMsyeDXPnOrNr11h273YmMFCSoNu5YvVtGEXvxVG+nii9GxOj6t1RsoMeKMWLL9wg7ppzrom+TVjwKpPGiNGlKFVKwrahNFRtA23aMOxhGIb8Vhw9CodXnODwmmiiDlk4fLYMzdKOQ9IN2LuXbXu78CdlISyrDN/SCTSoksj9916H/legfHmuXZPXypSx0weQjvU3LiwMIiN7ExoqlzGO/o0z0lxXOZgUBaI45GBSOJ7iEKuvcDxK7wYgOBjGjs1/+z595Arz1p24unVtxqYePSC9MICicGiahNBt2GDL43TkyO3tqlbNanBq0QLycy2bNf+UhsViyngsTP4pRclBrfPGROndGCxYAP7+mhTryMbIZMICJhPz55vufK3XNCmrum8fe1bGsth3HIePmDh8GA5vu8KFlPIZTdfTla5shGrVmOL1BuMPvEDVqtCgATSor9GgoUn+Tj8K+9UMD4dxD2tciTNh5iYWnDIey3tpTJteiHGXIFQOJoUiD6yVL4wmuzjI1xOld2Oi9G5ngoIkqUJe7i8mk7QLDxcLx6FD8NVXYnAqVUoMTt9/LwYmb28YNAgmT77dEJVPlN4Fkwn8/ODxx+GPP+DwYcnJPmcOvPKK5HhydpZcUbNmwYsvQtu2oqo+fWDiRPjnH7h69XY54eGyi2sNubNYTFke4+LA31/aOQqld2Oi9G5MjKp3R8oeMgTCwkx4ecm6bs3JZH308iqkcQnkh6p2bRgyhJZfP8Jb/2fi999h/Xo4v/sC8VNmsv3h7whp9Qn1vNMrmkVHcyoyCZDfr7Vr4dffTLz5JgQGQvPm8O/nG+QawmJh40b48ksxmEVG5i83ofzGacTFiS+NNVzQ+hgXp+HvrznsN85Ic904vlqKu4YbOmY81VN2cZCvJ0rvxkTp3c64uYmbir+/XCRm59RsNT5Nm2bzJ2/YUI6XXpJ8TKtWweLFcpw+bfsbxEIyYIAYn7p1y9eWpNJ7zlSqJBfggYHyf1ISbNtm83LatElyXvzzjxwgUZCtWtk8nNq2Fc8lyF7l1udNJml39qxjQgmU3o2J0rsxMareHS176FA4e85EaKhsTuzefZxWrWoyfDiMGGGy79ru50c5Pz/aPgFtgZCQmoweOBD27+fDs2d5pbdsnBw+DIdf/YnDMeU4TAMO04AG79wP75yDMmVY4PUTn0TbKtiazRq1atm8nSZMgOrVbWKTk2HcAzdAyzk8UMOMSbMw7oFUzsaWsvtvnJHmujIwKUoctWrVMqTs4iBfT5TejYnSuwOQLc6MWCnNbMZksWQ84uWVe6yUh4dcwQ4dKlaJAwdsBqYNG2S7MTJSPJ7KlIH77hNj04ABUKNGtqdUes8/7u5w771ygKTTOnAga1jdyZOwc6cc332X/3NrmoTPhYZK0nN7o/RuTJTejYlR9a6HbGshi6CgNCZNmp4eGpnfBOBFR61ataRyRZcuAHgDHTvKQc8hsG8f7FuDtvc72FcJDl6Ca9do6bmb++8fQ1SUGKOuXTNx/DgcPw7Ll8ObdWbBvXWhSRPe/8ydH3+wcOVaqTz7o2HmyrVShIbcYMwjebcv9NgNgjIwKUoc9erVM6Ts4iBfT5TejYnSu4MYOlTcVEJDscyZw6ndu6nZqhVOssWZf/cVkwmaNZPjjTfElWbFCjE2LVki8V3z58sB4gdvzd3UqRO4uABK74XBbJaPtXlzePppee7MGTKShm/YALt2Fex88+Y5xsCk9G5MlN6NiVH1rnSeA9WqydG/PxlB+2lpcPgwo+PiGN1JntIsGufLNeTwtSocpgFHqE+1194GxO32QMVVXIjpke8+mbjJ1C8u4T+iCmXL3uHA8oGR9K5yMClKHKtWrTKk7OIgX0+U3o2J0rsDSd/iTJsxg+njxpE2Y4ZYFQrjN+7pKQaq33+H6Ggpe/zhh9C5s1gu9u2DTz4R95uKFeH++2HqVDbNnVt04yogd6Peq1eHkSPh22/Fi6lr1/y/12KR9yxeDBcuFHnXsqDmuzFRejcmRtW70nkBcHaGxo1lAyodk9lElQu76b7lcx77tTMfv3gBc6+ecg2haXzT8g9aljuebxEaTqw8UIVy5cDXF+65Bx54AN55R0LQiwoj6d3wHkymfNb1vffee1mzZk2ubZYuXcqUKVPYunUrFy9epGLFinTo0IEnn3yS/v3750tOUlISkydPZvbs2Rw5coQbN25Qo0YNBg0axAsvvEDNmjXzdZ4DBw7w3Xff8c8//xAdHY2HhweNGzfmwQcf5LHHHjNUqUSFQqFQFAPMZmgjZY95+224dEl82xcvhqVLITZWagnPns0wgF9/tXk3degATo53579b8fUVdVgs+Wt/4oTkbQeJamzXzna0bQsVKtitqwqFQqFQZKVMGbku6NAh6/MxMVRJTKRex1Pso2ZGQu/c0ShlSuOG5sLFi3DxImzZIratiRNtrR59VLyA69WTwrl169r+rlNHsgUoBGVlKAI0TeOpp55iypQpWZ6Pjo5m3rx5zJs3jyeffJKffvopV4PW0aNHGTRoEIcOHcryfGRkJJGRkfz666/8/fffDBw4MNf+/Pbbbzz77LOkpKRkPJecnMz69etZv349U6dOZeHChVQooVeEXQuy9XoXyS4O8vVE6d2YKL3fxVSoAKNHy3HzJmzfbsvdtH27LWnQhx9K2379xNjUrx/4+NitW3p/7o6QHxAABXES69IFLl+WVFqnT8sxb57t9Tp1bjc6eXoWvF9qvhsTpXdjYlS9K53bEV9f8PUloPZC5sbem883mfit7Q8MmT2W43V6coy6HDXVJ75sbZwDl4oHVZMmROy4n6io0kRF3X4GZ2e4fl0eQfIWJibajFBVquij9+Rk2bebOdOxJh8VIpfO008/zb59+3I8/vjjjxzf+84772QYl1q3bk1ISAhbt24lJCSE1q1bAzBlyhTefffdHM+RmJjI4MGDM4xLTzzxBCtXrmTTpk189NFHeHh4EB8fT1BQEHv37s3xPMuWLePJJ58kJSWFSpUq8e2337JlyxaWLFlCYHrJmX///ZfAwEAs+d26LGbExMQYUnZxkK8nSu/GROndIDg5SZbP99+HbdvYs2wZTJ0qIXOenuLt9PffErLn6yvu8v/9r4TcFfFvmd6fuyPkBwVB+fK2AoE5YTJJu3/+gYgISam1di188YXYBRs0kHbHj8tF7JtvQu/ekhe+USN48EHJ7b5+vVxs54Wa78ZE6d2YGFXvSuf2J+ipCpTnMiZyvz4wYaE8lxnxdEU8b16mVSd3Ar1W87r2GR9eeRYWLIBPP4Vx45jV8iNWroRffoG3Xr3ByIY7aVcrBu9yqdSsdpPMwUFffgmPPCLR/9WrSzGO7t19GDQIXn45a/XWtDT7fAbh4VC1KowdC4sXO9bkowxM6fj6+tKsWbMcjzp16mT7viNHjvDpp58C0K5dOzZu3MioUaNo3749o0aNYsOGDbRr1w6ATz75hKNHj2Z7ns8//5zIyEgAPv30U6ZMmUKvXr3o1KkT//d//8fy5ctxdnYmKSmJl156KdtzpKWl8dxzz2GxWChXrhwbN27k+eefp0OHDvTv3585c+bwzDPPALBu3Tr+/PPPwnxkuhGVnenYALKLg3w9UXo3JkrvxiTi0iV4+GGYOVNC59atkzrELVrIldm//8J//iPuMlWrypXc7NkQF1do2Xp/7o6Q7+YmhQEhZyOT9flp02xpuMqWhe7d4ZVXxN4XFSVV5lauhEmTJN1W7drSNipK2rzyirynXDlo2lTU+t13sHmz7PhmRs13Y6L0bkyMqnelc/vj9uBwppV5FiBHI5P1+WllnsXtgUBxNdq0Sdx1z52TH7bvv4dnn4Vevah5X0N69YLHH4f/jdzDjKi2bDtZiUsJpdh3sqzkgOreHcaP595aJ+jTR07p7AwpKXDiRGkWL5aivZl/d++9FypXFk/hhx6C996T390NG6T2yp0QHi6eytZLIk3LX0qgokKFyBWSr776irR00+N3331H6dKls7zu7u7Od999R6dOnUhLS+Prr7/mu1tqBKempvLNN98A0LhxY1599dXb5HTq1InHHnuMn3/+mdWrV7Njxw7atm2bpc28efM4cuQIAG+99Va22eo/++wzQkJCuHLlCp999hljx46988ErFAqFQmFvnJ2hWzc5Pv5YSqItXSqhdCtWSObpqVPlcHKSqzRr7qZmzfJ20wGbH3lYGL0OHhT/9oAAcfUpTJLzYsyQIXKhO26cGInMZg2LxZTx6OUlF7lDhuR+Hi8v6NVLDiuxseJctn277ThzRrygIiJg+nRp5+QkRqf27cVWeOmSNykp4OpqnzErFAqFwgC4uTEk5AHChg5jHH9wBW/M3MSCU8ajF3FMYxxDQp7I+jtvMonFp3LlrD9smfHygldfhYMHISIC9xMnIPa6uOuuX8/HX/qJqxKQtucAp8e+zUZLba437I9WuQocdpf4OScnjh2Ty5gLF8S+lZlatSQHopWvv5buWUPv6tSBW0wPJCfL7zpk9ZRyKJrBATRAe++99wr8XovFolWrVk0DND8/v1zbNmrUSAO06tWraxaLJctry5cvz+jHpEmTcjzH5s2bM9r93//9322vP/DAAxmvnzt3LsfzjB8/PqNdVFRUHqPMSnx8vAZoMTExBXqfomSTnJysTZw4UUtOTta7KwoHovRuTEqU3lNSNG3lSk179VVNa9xY0+R6ynZUr65pTzyhafPmaVpCQvbnmD9f08qXl/Zmc9bH8uU1LTzcoUNyNNeva1pwsKYFBKRptWsf0wIC0rTgYHm+KDl3TtMWLtS0iRM1bfBgTatU6XZ1gaa5uGha27aaNn68pv3yi6bt2qVpN24UbV8UNkrUfFcUGUrvxsRwep8/X7vuVVkL5kEtkDlaD1ZpgczRgnlQu+5Vueh+3xMTNW3HDk37809Ne/tt+dtKSEj2P3aurprWvLl2+c9F2vbtmjZrlqZ9/N9U7YlH07TevTWtdm1N69Mnq5iqVW8/TZUqmta1q1wGaZqmTZ+enTi5f4+Pjy+a8eaBCpErBMePHyc6OhqQKnO5YX39zJkznMhsigTWr19/W7vsaNeuHWXKlAFgw4YNt71uPU+jRo2oXLlynn3J6TzFnfnz5xtSdnGQrydK78ZE6d2Y5HvspUrJDuPnn4trzLFjMHmylDwrXVrcZn75BYYNk0Th990nyREiI+Wa61Y/cms+J+tjXBz4+0s7B+Fovbu5SWqrGTPSGDduOjNmpDFmTNE7blWuLGp57z1Ja3HunC1Z+NtvS+72smVTSE0V76eff4YnnoDWrSU075574LnnxFHtwAHJC19YkpMhOBiGD4fmzWMZPlz+T04u/LkLiprvxpNdHOTriVH1rnTuQIYOxe3cccYE92dO4F/MavYCcwL/Ykxwf9zOHc/bRTe/lCkjFXIffFAKk7RpY3utRw8IDeXgAw9I8sJWreQHNiUF9u2jfNk02rYVh+kJjeczZZor/5xqyPEW/ixr85a4/G7bhpZwlYcekt+r1q0l7Bzkt3TDBvEUBvFMNpv0cl0SVIhcOrNnzyYkJIRTp07h7OxM5cqV6dy5M+PGjaNnz57ZvufgwYMZf/v5+eV6/syvHzx4MEtOp/yex9nZmXr16rF3794s7wFJEn7mzJk76ktJIykpyZCyi4N8PVF6NyZK78bkjsdepw4884wc169LRurFi2HRIjE+rVwpx6uviu/5+fPyvpz8yDVN/NHHjZNkCA4IlzOK3k0mSX5avbrY+AD+/nsunTuPzhJat327JBffskUOK+7ucg2fuXpdgwZgzufWaXh45vBAsFh8iIiQ6novvpi/8MCixCh6zw61zhsTo+pd6dzBWHdRxozhn5AQRo8e7Vj5lSvD8OHsvnGDxlbZFgucPCkbY/fcY2t7+LDsnhw+DIcPY8q0uWUCJoWHwyT5YdJOnOTKgbMcc23MsctepPugcOniTSyak4MGlz3KwJRORERElv+PHDnCkSNHmD59OgEBAUydOhXPW2runj59OuPv6tWr53r+GjVqZPu+zP+XKVMGLy+vPM+zd+9eLl68SEpKCq7piQrOnDmDln6BXJi+lATyGt/dKrs4yNcTpXdjovRuTIpk7KVLQ//+cnzzjVywLV4MS5bAmjVycZcfNE2sEKGhcpFqZ4ys9xo1qlO7tiQKHzFCnrNY4OjRrAannTulKt2GDXJYKVsW2rbNanSqW/f2NFxWxzUrOTmuhYXB0KF2GeptGFnvap03JkbVu9K5MeVnkW02y4bYrUXE3nxTKmFERGTkd+LgQTkuXJDES+mYZs3E+8038Qba+fhAkyawoDEVTjyKmbZY0M/IZHgDk7u7O0OHDqV37974+fnh4eHBxYsXWbt2LT/99BOXLl0iLCwMf39/VqxYgYuLS8Z7r169mvG3h4dHrnKsoW0g3kaZsZ4nr3Nkdx6rgamo+nIrKSkppKSkZPyfkJCQ7fOOpH79+oaUrad8q0wjjl1v2XrKV3pXetcLu4y9Vi14+mk5EhNxGTQI05Yt5Ke2imY2Y5kzh7SgoKLtUzYovd8uv2ZNOQID5X/Z4DWxY4eJnTtN7NhhZs8eE1evmlizRuyHVsqX12jdWqNNGwvt2mk0bWrh4YdLATlX1hHHNY2HH4YTJ244JM+70rta5x2J0rsxZeutd6POtwLJ9vaGrl3lyMzly+DpKaF1gBPgVLMmplOnbNV2160jgGvMJbjoB1AADG9gio6OztZrqE+fPjz//PMMGDCAXbt2sXbtWn788UdeeOGFjDbJmYL0S5Uqlasc10wlUa7fUpfXep68zpHbeYqqL7fy8ccf8/7779/2/OTJk3G7SyvrKHLmq6++0rsLCh1Qejcmd7vex54/T528mwFgslhIWrGCVSNHcqJ2beLKl7dr3/SkpOm9YkVxUuvTx0RsbEXOnq1KdHRVzp6tyoULlbhyxZlVq0ysWlWwtKOaZiIuDh55ZBEtW+6zT+eLESVN74qiQendmCi93yU8+iguKSn4XLqEz8WLVIyNZeC2hZRPvkwcXmjok27b8Aam3ELSKlWqRGhoKI0bN+bGjRt89913WQxMmQ0sN27cyFVOZotl6VvqCVrPk9c5cjtPUfXlVt566y1eeeWVjP8TEhKoUaMGzz77LBUrVsyzv/Zg9uzZBDlgF7m4ydZTfkpKCl999RUvv/xyFgOlI1F6V3o3kmw95RtF7867d6OdPo3JGheVB2WvXcM/PUGpVrMmlu7dMw5q1y6yfim9F93Yb9y4yYEDlnRPJzM7d5rYs8eUo+fSrZjNGprmz4QJg4qsTzmh9K7WeUei9G5M2Xrr3ajzzZGynUeNYur8RwjQ5mHCoouRyfAGpryoW7cuffr0YdGiRRw5coSzZ89StWpVAMqWLZvRLq9Qs2vXrmX8fWsIm/U8eZ0jt/MUVV9uxdXVNdsFKKfnHUHXrl0NKbs4yFd61we95Su964Pe8u96vQcGSpKd/DJ0qLihb92K6dQpnP78E6c//5TXateWSjHWo1atO+6W0nvRyXZ1lfypmXOodu8OmYr35orFYmLFCicee8yJFi3IOKpUuT2vU2FRejee7OIgX+ndWLKt6KV3vcduCL0HBjI0bCxhBDCOqVzBGxM3cWRdOX38pkoYTZo0yfg7Ojo64+/MybqsFdxyInMy7cxJtjOf59q1a8RZSyXncZ6KFStm+ZIWVV9KAvHx8YaUXRzk64nSuzFRejcmDhl7UBCUL5+3pcBkknYzZ8LGjZIBetkyeOst6NQJnJ3hxAmYOlXKktWuLZmlH31UygufOlWgbim925eKFfNfaQ7g2jX46y/JvTpgAFSrJufo1Qtefhn++AN27JCihYVB6d14souDfD0xqt6Vzo0p32Gy069thpoWcpaqBDOGwSx0jOx0lIEpH2g5lC/ObHiKjIzM9RyZX2/cuPEdnSctLY2jR49mew4PD48MY1Fh+lISuLXin1FkFwf5eqL0bkyU3o2JQ8bu5ia16CFnI5P1+WnTyMj0XKYM9O0L//sfbNokFeaWLYMJE8RVxskJjh8Xy8PDD4s3U9268NhjEBwMeVRvVXq3LwEBtmpx+eGVV+Cjj2DkSGjcWIxTly7B6tXw9ddiR2zXDjw85PWRI6X9ggVSqDCHS8jbUHo3nuziIF9PjKp3pXNjyneY7EzXNm6mG4zhL/5krGNkp6NC5PJB5i+ENTwOoE6dOlStWpWzZ8+ydu3aXM+xbt06AKpVq0btW3I1dM2UJX7t2rXck9mXOxPbt2/PCG/r0qXLba937dqVkJAQDh06xPnz56lcuXK258nc1+zOo1AoFAqFIRgyRMLkxo0TQ5HZLNYH66OXl1yoDRmS8zk8PMTg1Lev/H/1qhieVq+Wcmbbt4vB6fhx+P13aVO3LvTsaQupM3DZakcTFAQvviiOaLkZf0wmUf9HH5Glitz161Ixeu9e2LPH9njpEkRGyjFrlq29pydZwutatIBmzeRro1AoFApFkXPLtY1mMuV/t6Mo0BS5cvToUc3FxUUDtLp16972+tNPP60BGqBt3rw523Ns3rw5o80zzzxz2+spKSmap6enBmiNGzfWLBZLtucZP358xnm2bt162+szZ87MeP3jjz/O9hzXrl3TypcvrwFakyZNcht6tsTHx2uAFhMTU+D3FhWpqamGlK2n/OTkZG3ixIlacnKyLvI1TeldD5Teld71wuFjv35d04KDNS0wULt5772aFhgo/1+/XvhzJyRo2pIlmvbGG5rWoYOmOTlpmlzq2Y569TTt8cc17c8/tdQTJwov8w4wkt7DwzXNZJLjVlWA7bXw8Pydz2LRtLNnNW3pUk379FNNGzNG01q00DQXl+zPb1X5sGGa9t57mjZ3rqZFRqZqN2/addjZYiS9FzfZespXejembL31btT5ppvs9Guby4MGaYAWHx/vELGGDpFbsGABaWlpOb5+4cIFRowYQWpqKgDPPvvsbW1eeuklnJ3FEez555/n/9u777AorvWB499FugiKiApiQ7HHrjEaa+wFG5bERG96b7+0e29uYrrpuUlMco2JSUyCXewltlhi7F2xYEFRBBRBurDz++O4K8jShN0B5/08zzwsu7Pzzuy7e5h9OedM+k2D8NPT03nmmWcAcHZ25vnnn8+3DVdXV+vV6Y4cOcInn3ySb52tW7fyww8/ANCjRw86duyYb50RI0YQHBwMwAcffGAdTpfbyy+/TGJiovV2RbRy5UpDxi4P8fUkeTcmybsxOfzY3d1hwgSYP5/lL70E8+er33N3XblVVarAgAHw4YewbRtcvgzLl8PLL0PHjqq3VFQUTJ8OEybgXL8+NG4Mjz4Kv/8O58+Xfh8qCEfl3fLPXcuFhC1zMll+Vq0KixYV3nEtN5NJTfzdv79K68yZqldTSor6OXOmur9/f7UeqJQvXAhvvaXmm2/a1BlvbzWt12OPwdSpajLyIqbmvGUZGWq/xo1zZsaMBxg3zpmZM9X9jibtvDEZNe+Sc2PG1yX29XOb7BkzHBrW0EPknnnmGa5du8aoUaPo0qUL9evXx8PDg4SEBDZs2MB3333HpUuXADX8zFaBKSQkhJdeeokpU6awc+dOunbtyquvvkpwcDBRUVF8+OGH7NmzB1AFncaNG9vcl5dffpnZs2dz7NgxXnnlFU6cOMG4cePw8PBg/fr1vP/++2RnZ+Ph4cEXX3xhcxsuLi58+eWXDB06lOTkZLp27crrr79Op06dSExM5Pvvv2f+/PnW47n//vvL4FV0vKtXrxoydnmIryfJuzFJ3o3pts67t7eaLXrgQPV7cjJs3mwdUmfetQunEyfgxAn4/nu1TuPGN4bU9egBuYbr304cmfdhw1Ttbt48Veg5cuQizZrVZMQIGD26bGqLrq43hsXlFh8PBw7cGGK3fz8cOJBDamol/v4b/v477/r16uUfZteokZpf/lYsXpx7VKgTZnMDzp7ViIhQwweLGhVa1m7rz3s5j68no+Zdcm7M+HofuyMZusAEcP78eb766iu++uqrAtcZNWoU06dPL/DSgu+99x5xcXH8+OOP7Nmzh3HjxuVb56GHHuLdd98tMEaVKlVYtmwZgwYN4vjx40ybNo1p06blWcfb25vffvuNNm3aFLidQYMG8d133/H0009z8eJFa++p3Dp16sTChQupVKlSgdspzwqaW+p2j10e4utJ8m5MkndjMlTevb1h0CC1AJuXLKG7k5Oav2n9etizB44fV4vlvCAkJG/BydItpoJz9Gtv6bg2YQKsX3+YXr1qOiSu5Sp0vXvfuG/Nmk0EBva0FpwsS3S0miz8zBk1cXjufW/R4kbBqXVraNUK/PwKj714sZro3MJsNuX5eeUKhIaqHl7DhpXJ4RbJUJ/3chZfT0bNu+TcmPH1PnZHMnSB6eeff+bPP/9k69atnDx5koSEBJKTk61XZLvrrruYOHEiXbp0KXQ7Tk5O/PDDD4waNYpp06axY8cOEhIS8PPzo2PHjjz22GMMtPynshCNGjViz549TJ06lblz53LixAmysrIICgpi0KBBPPfcc9SrV6/I7TzyyCN06dKFL7/8krVr13L+/HkqV65Ms2bNuO+++3j44Yetw/oqonbt2hkydnmIryfJuzFJ3o3JyHlv3b27mhl68GB1x5UrqodT7oLTsWNq+d//1DpNmqhiU69equBUkhPZjAyYOxfnBQt4YM8enPfuVWO2wsLKphtPCRg57x07tsXH58aV6CwSE1Vvp9xFpwMHIC0Ndu1SS24BAfl7OzVponpTZWSonktQ8HyvmqaG/E2apHp4OeItYOS86x1fT0bNu+TcmPH1PnaHcshMT+K2UR4m+f79998NGVvP+HpPCqhpknc9SN4l73qRvBciMVHNPv3ii5rWtq3tmaqbNtW0xx/XtNmzNS02tuBtLVqkadWqaRpoZienPD+1atWKP8t1GZG8F09OjqYdP65p8+dr2htvaNrw4ZrWsGHBE4q7uGha69aa1rVrwevYWmbOtN/x5iZ5dzxp540ZW++8G/XzpnfsuLg4h07yXXG7sQghhBBCGE3VqmqCHMskOYmJajZoSw+nffsgMlIt332n1mnWLG8PJ3//fGOlTGZznp+6jJUSxeLkpOZgatRIdTazuHoVDh4k3zC75GT1tihpjIUL1fBBIYQQorikwCQqHFtX0DNC7PIQX0+Sd2OSvBuT5L0EqlVTBSBLEejy5RsFpw0bVGXhyBG1fPutWqdpUzh1quBxUqDLWCnJe+lUqaKuQpd7ZgdNU/M37d+vJvA+fbp42zKbYetW+PJLVZ9s1gwCA9VboqxJ3o3JqHmXnBszvt7H7khSYBIVToYe19AtB7HLQ3w9Sd6NSfJuTJL3UvD1VT2PQkPV75cvw8aNeQtOkZHF25amqR5S8+Y5pCuL5L3smUxQv75afv5ZTRpu6aRWlAsXVFHKokqVG8Umy9K8OTRoAKW5bozk3ZiMmnfJuTHj633sjuSk9w4IUVIHDhwwZOzyEF9Pkndjkrwbk+S9DPn6qqFwX3wBe/dCQgLceWfxu6I4OakCkwNI3u1r+PDiF5dAjcIcPlxNEl6pkhqCt327KlS99pqqYTZuDJUrq8nEx46Ft96COXPUROSZmcWLI3k3JqPmXXJuzPh6H7sjSQ8mIYQQQgijqF4d3NwKHx6Xm9ms5mvq3FmNvbrzTvWzbl37jJcSdhMWpnokXblSePpNJjXV15w5N0ZGZmXB8eM3RlseOQKHD8PRo+rqdAcOqCU3JycIDs7b26lZMzVCs0oVex2lEEIIPZk0rbhnGEJAcnIyPj4+xMXFUaNGDV32ISMjA3cHXzq5PMTWM35mZiZTpkzhtddew83NzeHxQfIueTdWbD3jS94NkPdRo9Tk3SXpznKzWrVuFJzuvBM6dABPz1LtluTd/vGXLLkxetLWNwBLzXDRohvzyBcmJ0fN8WQpOOUuQCUlFfy8OnVuFJwaNbrGHXe40Lw5+PmV/JhKwyh5v5m088aMrXfejfp50zt2fHw8/v7+JCUl4e3tbfd4MkROVDgbNmwwZOzyEF9Pkndjkrwbk+Tdzko6Vuqzz+C33+CZZ1QhydkZYmPVZcZefVVdmc7bG9q3h6efhl9/haio4veSuk7ybn9Dh6raYtWq6ncnJy3Pz6pVi19cAjV0rmFDGDwYXn4ZfvxRTQ6emKjmhl+zBr76Cp58Ul3EsGZN9bxz52D1avjvf+GZZ1zo0QNq1FBL9+7w2GPqsdWr4ezZEr+VCpWRATNnqjprp06pjBqlftdjihS933d6MurnXXJuzPh6H7sjyRA5UeEkJiYaMnZ5iK8nybsxSd6NSfJuZyUdK/XEE2qs1L33qvvT02HXLvj7b1VN2LpVzQi9e7dapk5V69WocaOHU5cu0LEjeHkVGE7y7hjDhqniz7x5MH++mb17o2nTpi6jRlVi9OiyuWCgyQS1a6ulT5+8jyUm5h1mt3bteZKSAjh9Wk0RtmmTWnLz8ip4gnHnEnybWbxYXRgxMVEN4TObq3PoECxYoD4SP/9c/OJaWdD7facno37eJefGjK/3sTuSFJhEsUydOpWpU6eSk5MDQEREBF5eXowcOZK1a9eSlJSEv78/nTp1YunSpQC0a9cOs9nM3r17AQgNDWXz5s1cunQJX19funfvTkREBAB33HEHLi4u7Nq1C4DBgwezc+dOLl68iLe3N/369WPe9UlGNU3j5MmTbNu2DYD+/ftz8OBBYmJiqFy5MkOGDGH27NkANGnSBD8/P7Zs2QLAPffcw7Fjx4iOjsbNzY2RI0cye/ZszGYzwcHBBAYGsnHjRgB69uxJdHQ0J0+exNnZmbCwMC5fvkx4eDj16tUjODiYdevWAdCtWzfi4uI4duwYAOPHj2fRokWkpaVRp04dmjdvzurVqwHo0qULSUlJHD58GICwsDBWrlzJ1atXqVWrFu3atWP58uWAuqRlRkaGdWK4qlWrsnLlShITE/Hz86NLly4sWbIEgLZt2wKwZ88eAIYOHcrWrVtJSEigWrVq9OzZk4ULFwLQqlUr3N3d2bFjBwCDBg1i9+7dxMbGUqVKFQYMGMDcuXMBaN68OR4eHgDMmzePAQMGcPjwYc6dO4enpyehoaGEh4cDEBISgr+/P5s3bwagd+/eREVFcebMGVxdXRk1ahRz584lOzubhg0bUrduXWtFv3v37sTExBAVFYWTkxNjx45lwYIFZGZmUrduXTw9Pa1xunbtSkJCAkePHgVg7NixLF26lNTUVAIDA2nZsiWrVq0CoHPnzqSkpHDo0CEARo8ezerVq0lOTqZmzZp06NCBZcuWAdC+fXuuXbvG/v37ARg+fDgbN24kPj6e1atX061bNxYtWgRAmzZtcHJyYvfu3QAMGTKE7du3ExcXh4+PD3369GHBggUAtGzZEk9PT7Zv3w7AwIED2bdvH+fPn8fLy4tBgwYxZ84cAJo2bYqvry9//fUXAH379iUjI4Pw8HA8PDwYPnw4s2bNQtM0GjduTK1atdh0/Uy8V69enD59mlOnTuHi4sLo0aOZN28e165do0GDBtSvX5/169cDcPfddxMbG8vx48cxmUyMGzeOiIgI0tPTCQoKomnTptbXMDo6mpSUFCKvX3lqzJgxLF++nJSUFAICAmjdujUrVqwAoFOnTqSlpXHw4EGAUrcR8fHxhIeHl6iNaNGiBV5eXqVuIy5fvgxQojZi/vz5ZGVllUkbYTn2krQRI0aMYMOGDaVqI8zXe7acPHnSmpui2ggfHx+2bt0KQL9+/UrdRsTHx7Nt27YStREhISGsWbMGKF0bUa1aNZYtW1aiNuLy5ctUr169TNqI+Ph4rly5UqI2IjIykrNnz5aojaj76KN0/egjNMDWTEra9bFSGx98kAsRETbbiD/OnoXRo7nr00+5evgwV1atwu/4cZpcvox51y4qxcerMVnX34Nmk4lrTZuS0rIlx6tXJ6FRI/o+9RRr160jKSmJ1NRUrl69avfzCFttRHp6OuHh4XY/jyiojXB1dWXXrl12P4/I3UbUrOnHDz+056uvfqFRo0a0b9+e06ftcx5xcxuRk3MYT89zdO/uyYABniQk/ElGRiVcXVty6VJN1q+/QEyMD1eu1ObkSSdSUpzYsQOuh7NyddWoWTOJgIBk7rqrKtWrx+HsfJyAgBTuvz8sTxtx8mRLJk70vl5TNVk78Vl+XrmiERoK7713iMceCyjT84jC2ghL+2jP84ib24j58+cDKtd16tSx23nEH3/8AcBdd93F5cuX85xHJCUlER4ebvfzCFttRHx8PMnJyXY/j7DVRri5uVlzbu/ziJvbiKTr41aTkpJYu3YtYJ/zCLDdRqSlpREeHu6Q8whb3zXc3NzYvn273c8jbLURlnM6R5xHQN42wtFkDiZRIuVhDqaUlBS8CvkP6O0aW8/4eo/ZBsm75N1YsfWML3k3UN5zdefQnJwwmc3Wn1SrVrruHJmZsGeP6t1k6el09mz+9Xx9rROIp7dujUePHuDjU6rDuhWGynsuFeHzfu0anDiRf56nyEjVmc4WJyc1dM/S26lRI/i//4OUlOJ12jt/vmx6chVF8m68dl7P2Hrn3ajtrN6xZQ4mIYpgqaIbLXZ5iK8nybsxSd6NSfLuIJaxUjNnYh42jFP162MeNkxNSHP+fOnGCrm5qaFxL7wAs2dDdLSaeGfePHjpJejaVX2Dv3wZVqyAN97AIzRUFbZatoRHHoEfflAVhdJMRl5Mhsp7OVPUsbu4qCLRyJHw+utqOrDdu1Wx6ORJWLYMPvkEHnpIjcSsWlW9ZU6cUJ3nPvoIHn0Url4tei4nTVPD5653ZLE7ybvENhK9j13y7hgyRE4IIYQQwqjc3WHCBLLDwvjl+n+2K9nrP9uBgWpm5VGj1O9ZWbBvn7WHU8qaNXjFx8OhQ2qZPl2t5+OjejlZ5nLq3FkVooShOTmpOZgaNIBBg27cr2lw8WLeHk9z5kB8fPG3/fbbqndU48ZqCQi4cYU9IYQQBZMCk6hwLON/jRa7PMTXk+TdmCTvxiR5NwhXVzXxd8eO8MwznIuMpGnVqrBt242hdTt2qOvdr16tFoumTW8UnO68E1q0UJc0K4mMDJg7FyIiGHb2rOq2Mny4mgTdwZeTNlTeb1LWx24yQa1aaunVS9138CD8+Wfxt3H8uOr1ZOHpeaPYdPPi73/rxSfJu8Q2Er2PXfLuGFJgEkIIIYQQ5UOtWhAaqhaA7Gw4cCDvXE4nTqgJeCIj4aef1HpeXtCp042C0513gp9fwXFuupxYZbNZXRlPr8uJCbuqXt1y1bii1zWZ1PxNISGq0HTqFKSlqc52+/blX9/b23bhKSRETTEmhBBGInMwiQrHcuUCo8UuD/H1JHk3Jsm7MUnejcnmsTs7Q9u28OST8Msv6hu/5ep0//oX9O6tikspKbBuHbz3nioM1aihvuU/8AB8842acDw7W21z8WLVU+nKFfV7/suJqQLX4sV2PuIbJO/2NXx48afy0jSYPBmWL1dvt/R0OHoUli6Fzz9Xb8V77oF69VQxKjlZ1SZnzYJ33lFvuS5dVFGrenVV67z/fjXsbtYstW5ysooleZfYRqL3sUveHUN6MAkhhBBCiIrDzw+GDFELQE6OmrMpdy+no0dVT6cTJ9Sk5aDGObVvD9cv41zgjM+apioHkyY57nJiwq7CwlTHtCtXincVudGjb9zn4qJ6I4WE5F8/I0NNNH78uFqOHbtxOyZGzWG/bZtabubvD1Wr3sPq1Td6PDVurK54V7lyaY/YNsuo0AULnNmz5wH27nVm5EhdRoUKIW5TUmASFc5QHbus6xm7PMTXk+TdmCTvxiR5N6ZbPvZKleCOO9Ty2GPqPss3e0vBads21W1k06bibTP35cQmTLi1/SoBybt9uburUY+hoaqIZKvIZJlH6eefi19scXeH5s3VcrPUVIiKyl94On5cTUIeFwdxcTU4diz/cwMC8g61s9wODr71QlDeUaFOmM0NOHtWIyJCn1GhRm3n5bNuzPh6H7sjyRA5UeFs3brVkLHLQ3w9Sd6NSfJuTJJ3YyrTY/f1hYED4a231OTgiYlqpud27Yq/DZMJpk27MZTOjiTv9jd0KEREqB5KoOZkyv2zalVYtKjsiiyVK6ua56hR8M9/wo8/qvpmbKyat37XLvjnP/fz9ttqCN2dd6ohdaA6zv35p7qQ4iuvwIgR0LKl6oRXr54aovfkk2rI3tKlqsNeVlbB+5J/VKgpz08dRoUatp2Xz7ox4+t97I4kPZhEhZOQkGDI2OUhvp4k78YkeTcmybsx2fXYnZzUleaqVCn+czRNVQSqVVNdR9q1y7sUNol4CUneHWPYMFW8mTcPFi6EI0cu0qxZTUaMUMPiHDVMzNtbvYWOHj3E+PF35Hns8uW8vZ1yL0lJEB2tlrVr826zUiWoXz//ZON168LEiWqd8jQq1KjtvHzWjRlf72N3JCkwiQqnWrVqhoxdHuLrSfJuTJJ3Y5K8G5NDjr0klxMD1WUkLU2NdYqKUhPYWNStm7fg1L69ugreLZC8O467uxr1OGECrFy5hwEDBjg0fm62jt3XFzp3Vktumqbmty+o+GQZkhcVBStXlnxfHDwq1LDtvHzWjRlf72N3JCkwiQqnZ8+ehoxdHuLrSfJuTJJ3Y5K8G5NDjn34cFiwoPjr/+9/aqjdnj2we7ca17R7t5o83NKVJCLixvq1a+ctOLVrB3Xq3JjgpwCSd+PFLml8k0lNDO7vD1275n1M0+DChfxFp2PH4MiR4tdTAaZMURdvbNAAGjZUHfWKePveEqPmXe/3nJ70PnbJu2PIHEyiwlm4cKEhY5eH+HqSvBuT5N2YJO/G5JBjDwtTQ96K+sZsMqn1Ro9WvZ7uuUdNhjN7tvrmfuUKbNgAn30G990HzZqp51y4AMuWqevVDx+uejn5+0P//vCvf6nuISdP5hurJHk3XuyyjG8yqYnBe/SAhx+GDz9UddSDB+Huu0u2rUOHYPx4NSeUv78azte6tXo7v/gifP01LF+uClfp6be+z0bNu97vOT3pfeySd8eQHkxCCCGEEMIYyupyYj4+6tt8jx437ktJgf378/Z0OnQIEhLUROOrV99Yt2pVaNvW2supyvnzqpuJk/zvV5StkowKNZkgKEhNJH7qFMTE3Hhb799v+zkBAaqnk6XHk2Vp0EB16JO3tBDGIgUmUeG0atXKkLHLQ3w9Sd6NSfJuTJJ3Y3LYsVsuJ3bjmu03ijtmsyr+3Mo127284K671GKRkQEHDtwoOO3erX6/cgXWr1cLMARg8mRVdMo9r1PTpmq80m1MPu/2VZJRoZoG7713Yw6mjAw4c0Z1ujt1Sv3MvVy9qiYFP38eNm/Ovz03N1VoslV8atiwdZkdY3FkZKgp1CIiIDp6KPPmqdcmLMxxk7uD/u85Pel97EZuaxzp9v6LJW5L7o78K1COYpeH+HqSvBuT5N2YJO/G5NBjv+lyYmkxMXgGBlLmlxNzd4eOHdVikZUFhw/nKTqZ9+7FKSVFXbVu06Yb63p4qPFJued1at4cXF1Lt1/Xv207L1jAA3v24Lx3L4wc6fhv28jn3d7CwuC551RNs6CryIHqvVS1qnr7W7i7Q5MmarmZpqkr3tkqPp06pQpTmZkQGamW/Jrj51dw76egoLKrrS5efHM92Yvdu1Xh7bnnbq2efKv0fs/pSe9jN3Jb40hSYBIVzo4dO2jUqJHhYpeH+HqSvEvejRS7PMTXk+Rd8u4QuS4ntig8nPHjxzsmrqsrtGmjloceAmDOr78yrm3bvD2d9uxR45P+/lstuZ/fqlXeicRbtSp+YSjXt20nJycamM1oZ8+qrh2O/raNfN7tHb+sRoXaek716mrJXT+1yM6Gs2cLLkAlJNxYtm/P//xKldRQvYIKUL6+xZt8fPFi1VPJwjJU0PLzyhX12kREqLqzven9ntOT3sdu5LbGkaTAJIQQQgghhI60SpWgRQu1PPCAutNsVlery1102r1bfSPetUst33+v1rU8P3fRqXVrqFw5b6Cbvm2brn/LNun1bVs4RP5RoRpms8n681ZHhRbGciW6Bg1sP/7DD3Pp0CHMZgHq9GnV+8nyuy3e3jcPubtxu359NTwvI0MdMxTce0vTVKFq0iTVqdFAHU2EsAuTphXWWVKIvJKTk/Hx8SEuLo4aNWrosg9JSUn4+PgYLrae8TMzM5kyZQqvvfYabm5uDo8PknfJu7Fi6xlf8i55l7yX4/iapr6N5y447dqluoHczMlJjW2yFJxatICxYyEpqXhjpRz0bVvy7rj4GRlqVOj8+Tns3RtNmzZ1GTWqUpmOCi2uwo7dbFYXZCyo99P584Vv22SCwEBVXz16tPj7NHPmjfmn7EXP95ze7bzRPm/lJXZ8fDz+/v4kJSXh7e1t93gyr7+ocHbv3m3I2OUhvp4k78YkeTcmybsxSd6LwWRS3TRGj4b334eVKyEuDqKjVReVN96AIUPU5bvMZnUt+V9/VdeX79+/6Il4QD2emKgqEQ4geXccy6jQWbOymTTpF2bNymbCBH167RR27E5OqkB0992qQ9/kyfDLL2oi8ZgYSEtT05gtXQpffQUvvKA63rVqpYpKmgbnzpWsuGQyqQ6Bp0/DtWulPrwC6f2e05Pex27ktsaRZIicKJapU6cydepUcnJyAIiIiMDLy4uRI0eydu1akpKS8Pf3p1OnTixduhSAdu3aYTab2bt3LwChoaFs3ryZS5cu4evrS/fu3YmIiADgjjvuwMXFhV27dgEwePBgdu7cycWLF/H29qZfv37Mu36ik5ycTL169di2bRsA/fv35+DBg8TExFC5cmWGDBnC7NmzAWjSpAl+fn5s2bIFgHvuuYdjx44RHR2Nm5sbI0eOZPbs2ZjNZoKDgwkMDGTjxo0A9OzZk+joaE6ePImzszNhYWHs2bOH2NhY6tWrR3BwMOvWrQOgW7duxMXFcezYMQDGjx/PokWLSEtLo06dOjRv3pzV1y9P3KVLF5KSkjh8+DAAYWFhrFy5kqtXr1KrVi3atWvH8uXLAejYsSMZGRkcOHAAgJycHFauXEliYiJ+fn506dKFJUuWANC2bVsA9uzZA8DQoUPZunUrCQkJVKtWjZ49e7Jw4UJAXcnA3d2dHTt2ADBo0CB2795NbGwsVapUYcCAAcydOxeA5s2b4+HhAcC8efMYMGAAhw8f5ty5c3h6ehIaGkp4eDgAISEh+Pv7s/n6pUR69+5NVFQUZ86cwdXVlVGjRjF37lyys7Np2LAhdevWZcOGDQB0796dmJgYoqKicHJyYuzYsSxYsIDMzEzq1q3LmTNnrHG6du1KQkICR6+fOYwdO5alS5eSmppKYGAgLVu2ZNWqVQB07tyZlJQUDh06BMDo0aNZvXo1ycnJ1KxZkw4dOrBs2TIA2rdvz7Vr19h//Vq8w4cPZ+PGjRw4cIBr167RrVs3Fi1aBECbNm1wcnKy/sEYMmQI27dvJy4uDh8fH/r06cOC65dtadmyJZ6enmy/PsnAwIED2bdvH+fPn8fLy4tBgwYxZ84cAJo2bYqvry9//fUXAH379uXw4cPExsbi4eHB8OHDmTVrFpqm0bhxY2rVqsWm6xPC9urVi9OnT3Pq1ClcXFwYPXo08+bN49q1azRo0ID69euz/voVi+6++25iY2M5fvw4JpOJcePGERERQXp6OkFBQTRt2tT6GkZHR5OSkkLk9Vk6x4wZw/Lly0lJSSEgIIDWrVuzYsUKADp16kRaWhoHDx4EKHUbsWvXLmJjY0vURrRo0QIvL69StxEXLlygV69eJWoj5s+fT1ZWVpm0EZZjL0kbMWLECDZs2FCqNsJ8fajMyZMnrbkpqo3w8fFh69atAPTr16/UbcSZM2fw9PQsURsREhLCmjVrSt1GmM1mli1bVqI24vLly1SvXr1M2oiYmBjatm1bojYiMjKSs2fPlqqNCAoKAlQ77+TkVKw24o8//gDgrrvu4vLly6VuIxISEujQoYPdzyNstRGHDh0iNjbW7ucRBbUR6enpeHt73/p5xL59XE1Lo1bPnrR78UWWL1+Oe2IinV1dqbRvH1nbtlF73z6cs7IoDs1kImfWLNbXrFkm5xGFtRFpaWkOOY+w1UZY2ll7n0cU1EacOHGC2NhYwL7nETe3EfPnzwfU34M6derY7TyisDZi3759xMbGlvo8omFDM9Wr76VjR9VGbNq0mdOnU8jICODbbztx9Gjx+lNoGmzcqIbYOTlp+Pvn4O2diJ9fKp061cTJ6RzOzjEEBZmZOLEnS5feWhtx+vRp6/vd3ucRN3/XSEpKAlRvmrVr1wL2OY8A223EwYMHHXYeYauNyMjIYPv27XY/j7DVRljaGkecR0DeNsLhNCFKICkpSQO0uLg43fZhyZIlhoytZ/yMjAxt8uTJWkZGhi7xNU3yrgfJu+RdL5J3x5O8GyDvPXpomvoeXfylSRNNGz1a0956S9MWLNC0Eyc0LSenTHdL8u54Rvm8jxypaU5OxX+7V66saW5uxVu3enVNa9dO04YP17TnntO0zz7TtPnzNW3nTk2Lj9c0s1m/4y6I3nk36udN79hxcXEaoCUlJTkknszBJEqkPMzBlJ2djXNZXbe0AsXWM77eY7ZB8i55N1ZsPeNL3iXvkvfbNP6oUWoYnWVC71tVubKaz6lVq7zLLZ4XSt7l824vM2femDO/uOvfe68adXrmjFqio2/ctizXOwIVytMT6tZVV8LLvQQGZtOwoTMBAWoidEfIyIC5c2HBghz27Immbdu6jBxZibAwxw6PNOrnTe/YMgeTEEWwdKc0WuzyEF9Pkndjkrwbk+TdmCTvdjZ8eMmKS199peZ4+vhj9S29bVt1aa7UVHVd+R9+gOefhz59wN8fatWCvn3VfE8zZsDOnWqynCJI3o3JEcceFgbVqqn5lQpjMqn1Ro9W8z/VqgWdO8OYMfDSS+qjsHgx7NunpjG7cgX274clS+Drr+Hll9W6d96ppj8D9daPjIRVq2DaNPj3v9X8V716OVOvnirs1K8PPXqoj9frr6s5oFavVnNHpaeXzWuweDEEBKgYixc7ceZMAxYvduKBB9T910e/OYTe73cjtzWOJHMwCSGEEEIIcbsLC4Pnnit6om/LVeQeflh9C+7f/8Zj2dlw4gQcOJB3OXkSLl5Uy/U5TKzbatQof2+n4GCoVMleRyoEoN6+P/+sJgA3mWy/7S3Fp59/Ln5vHh+fG29lWzIz4exZ272gDh26SmJiFa5du3FfQfz9bfeCqldP3V9U8WzxYlVXtjCbTXl+XrmiXpuICBg2rHjHLkRRpMAkKpzmzZsbMnZ5iK8nybsxSd6NSfJuTJJ3OyuLb9vOztC0qVrCwm7cn5oKhw7lLzzFx8Px42q5PhktAB4e1mF23X191fC6Vq2gZs2yPeYiGCLv5ZSjjn3oUFVAmTRJXRzRyUl15LP8rFpVvd2HDi27mG5uqq7aqFH+x/btO0mrVq25cMH28DvLfVevqqF6cXGqM6AtXl75i06W2zVrwsSJar2C6smapj7ykybB+fP2Hy6n9/vdyH9jHEkKTKLC8fHxMWTs8hBfT5J3Y5K8G5Pk3Zgk7w5w07dtzckJk9ls/XnL37YrV4ZOndSS28WLqtC0f/+NotOhQ2r8z86dsHMngQCffqrWtxSaci8tWqjtlxXLhDQREYTExEBgoOrm4egJadD/facnRx77sGGqgDJvHixcCOfPpxMQ4MGIEWpYnCPT7uPjg5OTetsFBkKXLvnX0TTVu6iweaDi4iAlRX2crl+87JZomiq8zZunhvDZk97vdyP/jXEkKTCJCmfr1q3Ur1/fcLHLQ3w9Sd71i68nybt+8fUkedcvvp4k7w6Kn+vbtnn+fKL37qVumzZUGjWq7L9t16yplnvuuXFfTg5ERVkLTmeXLyfoyhU19C4+HtatU4uFyQQNG+YvPDVqVPJZkhcvztOVxcPSlWXBAjV8sKy7shRB7/ednhx97O7uqoAyYQKEh0cwfvx4h8XOrTjHbZkTqlo1aNPG9jrp6XmH4dkqRpXkUl7/93+wfj3UqQNBQeqn5ba3d9HzWBWH3u93I/+NcSQpMAkhhBBCCGEk179tZ4eF8cv1q4lVctTVxCpVgpAQtYwaxeYmTdSX/bQ0OHw4/zC7ixdVQSoqSvW+snBzg+bNbxSc7rhD/axVy/a34fwT0uT9KRPSiArEw+PGx8iWnj3hzz+Lv724OPjxR9uPeXnlLTjZul21atkUoUTFJwUmUeH069fPkLHLQ3w9Sd6NSfJuTJJ3Y5K8G5P12D09oUMHteQWH297mF1aGuzZo5bcqle33dtp0iT1eHmZkAbJu8S2n+rVb8wzVRSTCdq1gxEjVK+oc+fUcvYsXL6shuJFRqqlIJUr3yg2FVSI6tvX8a97rhGxxMaOZt48fUbEGumz7qT3DghRUocPHzZk7PIQX0+Sd2OSvBuT5N2YJO/GVOSx16gBvXvD88/DDz/A9u1qBmTLxOFvvaWG9jVpor5RX7oEGzaoa8s/+qia5KZGDTUsrqgxQ7knpHEAybvEtpfhw4tXXAL1tn/+efj3v+G772DpUti7V32UUlPh2DFYu1aNIH3vPXjiCRgyRA3f8/NT20hNhaNHb6z37rvw+ONqvdatVcGrTp2qhIRAnz5qAvJ//xu+/fZGvISEkg3rK8rixRAQAA88oApMf/3lQkSE+j0gAJYsKbtYRTHSZ116MIkK59y5c4aMXR7i60nybkySd2OSvBuT5N2YbunYnZxuXKZrxIgb96enw5Ej+YfZXbhQsm3PnWv/GY+RvEts+wkLU9OKXblSeNHGZFLD20aPtv24pyc0bqyWgqSnQ0zMjV5PuXtAWW7Hx0NmZiXrRSUL4u5uuxdU7t/9/IoejlfeRsQa6bMuBSZR4Xh6ehoydnmIryfJuzFJ3o1J8m5MkndjKtNj9/BQY33atct7f9eu8NdfxduG2ay+ndarB82aqaVp0xu3a9Qos92VvEtse3F3Vz2JQkNVMcZWkclSpPn559INF/PwuFHvLUhGBvz00x80a9a3wEJUXJxa78QJtRTEzS1v4enmYlSNGqqHFJSfEbFG+qybNK0sO6KJ211ycjI+Pj7ExcVRowz/wIryLTMzkynXJwF1c9QkoEJ3kndjkrwbk+TdmAyT91GjVFeF4o4ZKkz16nkLTpbb9eqp3k8VgGHyLm66cKKG2Wyy/qxWzeEXTixUZuaNnlAFFaEuXiz7uDNnOqTDom7i4+Px9/cnKSkJb29vu8erGK2gELmEh4cbMnZ5iK8nybsxSd6NSfJuTJJ3Y3LIsZdkQhqAb76BTZtg2jR48UUYOBDq11ddHi5dgi1bYPp0dW33wYOhYUM1y3GbNjB+PLz9thpmd+CA+tZcAMm7xLa3YcNUD52ZM2HYMDP1659i2DAzM2eq+x1ZXCrq2N3c1Eepe3e491549VU1ldrChbBzJ8TGqo/TqVOwcSP8/jt89BE884waKduxo7qIZEk99ZT6iD/0EPznP2oeqsWLVczz5yE7+xYPOBcjfdZliJwQQgghhBDi9lXSCWn+8Q81ZqZbt7yPp6WpGY+PHFFLZKT6eeyYGtuzb59acnNyUt+ac/d6svR8EsIB3N1VD52wsGymTPnles+1Snrv1i1xdVW13vr1C16nRw9VgCqu5GRYubLgx52coGZNNTG4ZQkMzPt7QMCNK/eVF5Yr6M2e7diSjxSYRIUTEhJiyNjlIb6eJO/GJHk3Jsm7MUnejckhx15WE9J4eqpeSm3a5L0/OxtOn75ReMpdfEpKujGpzNKleZ42unp1+P77/MWngICiZzG+Fde/cTovWMADe/bgvHcvjBzp+Gu2Y9zPu3zW7c/PTxV6itNp0clJXWjywQdVb6Wbl9hYyMlR1wm4cAF27Sp4Wy4uULu27SJUSkp7Dh9Wt3187PPxzi330EiTybFVLykwiQrH39/fkLHLQ3w9Sd6NSfJuTJJ3Y5K8G5PDjn3oUDUP040JadQ3UMvPqlVvfUIaZ+cbsxznfr6mqW+olmJT7sJTTAwuly7B+vVqya1KlRtFp9zFp+BgFetW5PrG6eTkRAOzGe3sWfWaPPecwyfjMernXT7r9jd8OCxYULx1zWZ4/PGC52DKyVGTj9sqPlmWmBh1lbxr1yA6Wi353SiueXgU3hPKslSuXNIjV26+gp6m2bmadZNy1IlLiOLZvHmzIWOXh/h6krwbk+TdmCTvxiR5NyaHHnvuCWmGD+dis2bqm5i9JqQxmVSXhl694Mkn1YQyf/yhZitOSmLV22+rws5rr6neVU2aQKVKcPUq7NgBv/wC//qXmmCmaVPVg6p5czVp+euvw6+/qi4VqamF74flG+eVK2q3rnftMN18zfbFi8v2+Ath1M+7fNbtLywMqlUrupeQyaTWGz264HUqVVIf4fbtVfPw2GPw1luq4+GyZbBnjypAZWbCmTOwdSvMn68+6v/8p7qaXd++UKfOFapWVdtMT4eoKDXN26xZ8Nln8NJLat6pnj0hJAS8vFRPp2bN4J574IEHVDPx5Zcwb566KObp0/mneMvIUHVkKHw0sD1JDyYhhBBCCCGEMVgmpJkwgXXh4YwfP16f/fD25nKjRmpS8NyystRwuty9nSy309Ju/H6zoKD8czw1a6Z6QxX1jdPR12wXwo7KakRsSbi6Qt26arElPHwF48ePJy1NDbUrqkdUaqqaGyo5WX30C+Pnd6PXU1qa6qCpJykwiQqnd+/ehoxdHuLrSfJuTJJ3Y5K8G5Pk3Zgk7zdxdVW9lJo3z3u/2ax6Pt1ceDpyRI3POXtWLatX531e5cpF93AC9S08MVF1j3DANduNmne933N6cuSx23NE7K2wHLunpxrpGhxc8LqapjoxFlaEsiyZmZCQoJb9+x1zLEWRApMolqlTpzJ16lRycnIAiIiIwMvLi5EjR7J27VqSkpLw9/enU6dOLL0+gWG7du0wm83s3bsXgNDQUDZv3sylS5fw9fWle/fuREREAHDHHXfg4uLCruszpw0ePJidO3dy8eJFvL296devH/PmzQPA1dWVtm3bsm3bNgD69+/PwYMHiYmJoXLlygwZMoTZs2cD0KRJE/z8/NiyZQsA99xzD8eOHSM6Oho3NzdGjhzJ7NmzMZvNBAcHExgYyMbrlx3o2bMn0dHRnDx5EmdnZ8LCwoiIiMDb25t69eoRHBzMunXrAOjWrRtxcXEcO3YMgPHjx7No0SLS0tKoU6cOzZs3Z/X1P/hdunQhKSmJw4cPAxAWFsbKlSu5evUqtWrVol27dixfvhyAjh07kpGRwYEDBwAICAhgz549JCYm4ufnR5cuXViyZAkAbdu2BWDPnj0ADB06lK1bt5KQkEC1atXo2bMnCxcuBKBVq1a4u7uzY8cOAAYNGsTu3buJjY2lSpUqDBgwgLlz5wLQvHlzPDw8AJg3bx4DBgzg8OHDnDt3Dk9PT0JDQ62X3gwJCcHf39/aBbZ3795ERUVx5swZXF1dGTVqFHPnziU7O5uGDRtSt25dNmzYAED37t2JiYkhKioKJycnxo4dy4IFC8jMzKRu3bqkpqZy6dIlALp27UpCQgJHjx4FYOzYsSxdupTU1FQCAwNp2bIlq1atAqBz586kpKRw6NAhAEaPHs3q1atJTk6mZs2adOjQgWXLlgHQvn17rl27xv7rLfTw4cPZuHEjJ06coHHjxnTr1o1FixYB0KZNG5ycnNi9ezcAQ4YMYfv27cTFxeHj40OfPn1YcH0AeMuWLfH09GT79u0ADBw4kH379nH+/Hm8vLwYNGgQc+bMAaBp06b4+vry119/AdC3b1/WrFmDk5MTHh4eDB8+nFmzZqFpGo0bN6ZWrVps2rQJgF69enH69GlOnTqFi4sLo0ePZt68eVy7do0GDRpQv3591l+f5+Huu+8mNjaW48ePYzKZGDduHBEREaSnpxMUFETTpk2tr2F0dDQpKSlEXv8XypgxY1i+fDkpKSkEBATQunVrVqxYAUCnTp1IS0vj4MGDAKVuI+bNm4evr2+J2ogWLVrg5eVV6jYiOTmZxx57rERtxPz588nKyiqTNmLz5s34+vqWqI0YMWIEGzZsKFUbYb4+ZOLkyZPW3BTVRvj4+LB161YA+vXrV+o2Ii4ujg4dOpSojQgJCWHNmjWlbiPq1KnDzp07S9RGXL58merVq5dJG3H58mXuu+++ErURkZGRnD17tlRtRFBQEKDaeScnp2K1EX/88QcAd911F5cvXy51G5GVlcXIkSPtfh5hq434448/qFSpkt3PIwpqI3x8fKhZs6bdzyNubiPat29vzbvltj3OIwprI2rUqGF9Hex5HmGrjdi6dSu+vr52P48oqI04duwYaWlpJWojAAZOnJi3jejcmXXffIP3+fPUz8igyrlzmA8epHJCAqbiFJeu00wmrnzzDStNJlzc3Ep9HlFYG7FkyRIqV65s9/MIW23E5cuXuf/+++1+HmGrjbh06RJXrg9VtPd5xM1tRFJSEgBJSUmsXbsWsM95BNhuI1avXo2zs7NDziMsbcSuXXX55JPT7NhRh4wMT6pXN9G8+VHuvPMcQ4eG2eU8wlYbYTmfLWkbERjoxMWLuwkKgieeyNtG9O7dh19+WUpiogc+Ps1ISqrMp596EB9fxfYH3FE0IUogKSlJA7S4uDjd9uH33383ZGw942dkZGiTJ0/WMjIydImvaZJ3PUjeJe96kbw7nuRd8q4XybsdpaVpWvv2mqY6RRR/8fDQtFatNG3kSE179VVNmz5d0/78U9POn9c0s7lMds2oedcztt6f99v+81YOYo8cqWlOTjd/pNX396SkJIfsg/RgEhWOq6urIWOXh/h6krwbk+TdmCTvxiR5NybJux15eEC9emom4uJcs90iPR0OHFDLzby81NXyGjdWS0jIjdt+fsW+/rpR8673e05Peh+7EfJekivo2YtJ0/SaX1xURMnJyfj4+BAXF0eNGjX03h3hIJmZmUyZMoXXXnsNNzc3vXdHOIjk3Zgk78YkeTcmybsBzJypLkFVXDNmQNeucPx4/uXMmcILVT4+N4pNNy++vqU/FlEq8nm//WVkqMm+r1zJPbl5MuBDUlIS3t7edt8HJ7tHEKKMWcbrGi12eYivJ8m7MUnejUnybkySd2OSvNtZSa/ZPm6cKggNGgTPPQdffw2rVsHJkzeuYrd4MXz6KTz+OPTpoy6dZTJBUhLs3Anh4fD223D//XDnnVC9ulruvFPd9/bb/P3cc2rd6/MC2V1Ghiq2jRpFXIsWMGqU+j0jwzHxr9P7PacnvY/dCG2N5Qp6UOzOhGVOhsiJCic7O9uQsctDfD1J3o1J8m5Mkndjkrwbk+Tdzsrymu1ubtC0qVpulp6uilC2ej7FxMDly7Btm1qAOwG+/FI9t0aNgns+eXmV6vABVRDLdTkxf7NZXYlvwQJVRHPg5cT0fs/pSe9jN0pbc/MV9EwmzebH3l6kwCQqnIYNGxoydnmIryfJuzFJ3o1J8m5Mkndjkrw7wE3fODUnJ0xms/VnmVyz3cMDWrRQy81SUyEqShWbjh2D48dJ3r0b79hYuHgR4uPVcv3qmHnUrm278BQcrK75XpTFi9XENBaWIX6Wn1euqOJbRAQMG1bCgy45vd9zetL72I3U1gwbBufPw7x5MGuWmesXunQIKTCJCqdu3bqGjF0e4utJ8m5Mkndjkrwbk+TdmCTvDpLrG6d5/nyi9+6lbps2VBo1CkaPLrznUmlVrgx33KGW61IvXMC7dm1IToYTJ2z3fEpIgAsX1LJxY/7t1qlTcPHJzU0Nf5s0Sa1bUBcOTVM9uCZNUq+PPV8H9H/P6UnvYzdaW+PuDhMmQP/+2fj7Oy6uzMEkKpwNGzYYMnZ5iK8nybsxSd6NSfJuTJJ3Y5K8O9D1b5zZs2bxy6RJZM+apb6B2rmoYov12L29oV07GDsWXn9d9aT66y/VoykxEbZvh99+g8mT4b77oFMnNVcUwLlzsH49TJsGL7+seiq1aKF6U9WvDx06qG0UNT5I09R68+bZ74Cv0/s9pye9j93IbY0jSQ8mIYQQQgghhBDlS9Wq0LGjWm526ZLtXk/HjsHVq+qKdyXh5ASzZ6sill6zIwtxG5ACk6hwunfvbsjY5SG+niTvxiR5NybJuzFJ3o1J8m5MpT723Femy03TIC5OFZsefhiOHi3e9sxmWLpU9Y5q2DDv0qCB+lmvHri6lmq3JefGjK/3sTuSDJETFU5MTIwhY5eH+HqSvBuT5N2YJO/GJHk3Jsm7Mdnt2E0mqFkTunVTw+WcSvh1NykJ9uyB+fPh44/hiSdgwAAICVFD7+rVg1694KGH4L33IDxcXRkvPr7ooXhIzo0aX+9jdyQpMIkKJyoqypCxy0N8PUnejUnybkySd2OSvBuT5N2YHHLsw4ffuFpccUyfDocOwZIl8N//wnPPqcnRW7ZUV6wzmyE6GjZsgB9/VHNG3Xuv6kXl7w9VqqiJzIcPhxdfhK+/huXLITJSTTiOTjnPyICZM3EeN44HZszAedw4mDnTuk+Oovf73chtjSPJEDlR4TiV9D8Rt0ns8hBfT5J3Y5K8G5Pk3Zgk78YkeTcmhxx7WJgqEl25UnjvIpNJzfd0331qwvPmzfOvYxl6d/Kk7SUmBlJT4cABtdgSGMg9Xl6wcmX+YXi1atln7qfFi9UV8hITcXJyooHZjHb2LEREqNfm559h6NCyj2uD3u93I7c1jmTStGL05RPiuuTkZHx8fIiLi6NGjRp6745wkMzMTKZMmcJrr72Gm5ub3rsjHETybkySd2OSvBuT5N2YDJX3JUsgNFTdtvW111LUWbSodIWWzEw1sXhBBairVwt/vofHjbmecs/7ZLlduXLJ92nxYtWbCgo/9ogI1VNL3Jbi4+Px9/cnKSkJb29vu8czTilN3DYWLFhgyNjlIb6eJO/GJHk3Jsm7MUnejUnybkwOO/ahQ1UBpWpV9bulJ4nlZ9WqpS8uAbi5qXmaBgyAJ5+ETz6BBQtg7141r1N8PGzfzrYXX4T331cTkPfuDfXrq31JT4fDh9VE419+CS+8oApjrVqBl5fq4XTXXTBhArzxBvz0E/z5J5w9a3sYYEaG6rkEBffestw/aZJDhsvp/X43clvjSDJETlQ4mZmZhoxdHuLrSfJuTJJ3Y5K8G5Pk3Zgk78bk0GMfNgzOn4d582DhQi4eOULNZs1gxAgYPVoNi7Mnkwn8/MDPj5MnTtB5/Pi8j1+7puZ2svR2OnUqb++nxES4eFEtW7fm376rqypU5R5yFx2tnlcUTVPrzZunild2pPf73chtjSNJgUlUOHXr1jVk7PIQX0+Sd2OSvBuT5N2YJO/GJHk3Jocfu7u7KqBMmMCJLVuo2bWrY+NfZ/O4XVwgOFgttiQm5i86WZYzZyArC44dU8utcHKChQvtXmDS+/1u5LbGkaTAJCqckJAQQ8YuD/H1JHk3Jsm7MUnejUnybkySd2Myat5vKXa1ampp1y7/Y9nZaoLxmwtPy5YVPe+ThdkMq1fDqFFQr55a6te/cbtq1TKZgFzv93uFy3sFJXMwiQpnzZo1hoxdHuLrSfJuTJJ3Y5K8G5Pk3Zgk78Zk1LyXeWxnZ1UE6tULHnoI3nsPwsOhb98b80wVR0qKmjPq88/h+efV5OBt24KvL/j4qLmghg6Fp5+Gjz+GOXNg2zY1bK+Y1wzT+/1+W+W9HJMeTEIIIYQQQgghxO1i+HBVMCquF15QV6s7c0Ytp0+rn/HxqifUwYNqscXdHerWtd37qV49CAyESpXK4KBuQUYGzJ0LERH0PnJEzTU1fDiEhdl/7i2DkgKTKJapU6cydepUcnJyAIiIiMDLy4uRI0eydu1akpKS8Pf3p1OnTixduhSAdu3aYTab2bt3LwChoaFs3ryZS5cu4evrS/fu3YmIiADgjjvuwMXFhV27dgEwePBgdu7cycWLF/H29qZfv37MmzcPgFq1anHy5Em2bdsGQP/+/Tl48CAxMTFUrlyZIUOGMHv2bACaNGmCn58fW7ZsAeCee+7h2LFjREdH4+bmxsiRI5k9ezZms5ng4GACAwPZuHEjAD179iQ6OpqTJ0/i7OxMWFgY2dnZhIeHU69ePYKDg1m3bh0A3bp1Iy4ujmPXxz6PHz+eRYsWkZaWRp06dWjevDmrV68GoEuXLiQlJXH48GEAwsLCWLlyJVevXqVWrVq0a9eO5cuXA9CxY0cyMjI4cOCA9feVK1eSmJiIn58fXbp0YcmSJQC0bdsWgD179gAwdOhQtm7dSkJCAtWqVaNnz54sXLgQgFatWuHu7s6OHTsAGDRoELt37yY2NpYqVaowYMAA5s6dC0Dz5s3x8PAAYN68eQwYMIDDhw9z7tw5PD09CQ0NJTw8HFDdP/39/dm8eTMAvXv3JioqijNnzuDq6sqoUaOYO3cu2dnZNGzYkLp167JhwwYAunfvTkxMDFFRUTg5OTF27FgWLFhAZmYmdevWpUWLFtY4Xbt2JSEhgaNHjwIwduxYli5dSmpqKoGBgbRs2ZJVq1YB0LlzZ1JSUjh06BAAo0ePZvXq1SQnJ1OzZk06dOjAsmXLAGjfvj3Xrl1j//79AAwfPpyNGzeSnp7O6tWr6datG4sWLQKgTZs2ODk5sXv3bgCGDBnC9u3biYuLw8fHhz59+livGNGyZUs8PT3Zvn07AAMHDmTfvn2cP38eLy8vBg0axJw5cwBo2rQpvr6+/PXXXwD07duXKlWqEB4ejoeHB8OHD2fWrFlomkbjxo2pVasWmzZtAqBXr16cPn2aU6dO4eLiwujRo5k3bx7Xrl2jQYMG1K9fn/Xr1wNw9913Exsby/HjxzGZTIwbN46IiAjS09MJCgqiadOm1tcwOjqalJQUIiMjARgzZgzLly8nJSWFgIAAWrduzYoVKwDo1KkTaWlpHLx+ElLaNiI9PZ3w8PAStREtWrTAy8ur1G1EdnY2QInaiPnz55OVlVUmbYTl2EvSRowYMYINGzaUqo0wX78azcmTJ625KaqN8PHxYev1iUf79etX6jYiPT2dbdu2laiNCAkJsf6HsDRtROfOnVm2bFmJ2ojLly9TvXr1Mmkj0tPTuXLlSonaiMjISM6ePVuqNiIoKAhQ7byTk1Ox2og//vgDgLvuuovLly+Xuo1wd3fn6tWrdj+PsNVGVK5cmfDwcLufRxTURjRq1Ihdu3bZ/Tzi5jaiffv21rxbbtvjPKKwNqJr164OOY+w1UZY2ll7n0cU1EYEBQVZj92e5xE3txHz58+35rpOnTp2O48orI0ACA8Pt/t5hK02Ij09neTkZLufR9hqI0JCQqw5t+d5RHKTJjStXBmX1FQKG9ymmUzkVKnC/NatMbu6MuKRR/KeR7RuzYZffqFyQgLNPDxwPn+elIMHqZyQQPXUVEznz2PKyCh0DiizkxPUqUPfKlU49e23XAsIILh3b/48c4ZUPz/qdeuGd40aZXoekZ2dTbtz52j83ns4JSVhNpmoqWloR49iWrCArCeewDU8nAXXrpX5eYStNsLS1jjiPALythEOpwlRAklJSRqgxcXF6bYPu3btMmRsPeNnZGRokydP1jIyMnSJr2mSdz1I3iXvepG8O57kXfKuF8m740neDRJ78WJNM5nUogay5V0sjy1efOsxMjM1LSpK09at07QZMzRt8mRN+8c/NK1XL01r2FDTXFxsx755P2rX1rQ779S0ceM07dVXNe2bbzRt2TJNO3hQ065eLfl+LVpUvGNftOjWj70E9HzPxcXFaYCWlJTkkHgyB5OocCyVZKPFLg/x9SR5NybJuzFJ3o1J8m5MkndjMmreHRp76FCIiFCTdAPa9TmZLD+pWhUWLVLr3SpXV2jYUM0BNWkSvPkm/PgjrFsHUVGQng7nzsGWLfz11FPw/vvw2GMwYAA0awaenqrkc+EC/P03zJoFH34ITz4JgwdDy5ZQpQr4+UH79jBypBrO98UX6tj27IHLl/POA5WRofYFCp4fynL/pElqfTsz0mddhsgJIYQQQgghhBC3m2HD4Px5mDcP8/z5RO/dS902bag0ahSMHm3/eYgqVVJzMAUGcubMGe4aPz7v45oGCQk35n66eQ6oM2fgyhW4dEkt14eL5ePldWP+p4wMSEwset80Ta03bx5MmFDKAxUWJk0r5rTvQgDJycn4+PgQFxdHjRo1dNkHs9mMU0muinCbxNYzfmZmJlOmTOG1117Dzc3N4fFB8i55N1ZsPeNL3iXvknfjxJe8S94l78aJrXfeb/nYk5NtF54sy8WLt75TJhP07q0mAq9aVf1uB3rmPT4+Hn9/f5KSkvD29rZ7PBkiJyocy8R+RotdHuLrSfJuTJJ3Y5K8G5Pk3Zgk78Zk1LxLzm+Btze0agVDhsDTT8PHH8OcObBtG8TGQloaREbCqlUwbZq6ol1xaRqsXQu+vmooXtOm0LcvPPigGu43fTqsXAmHDqlC1y0yUt5liJyocFJTUw0ZuzzE15Pk3Zgk78YkeTcmybsxSd6Nyah5l5zbgYcHNGmiFlAFoXPn4PpVcYvk6gpZWZCaCkePqqUg3t4QFAR16qifNy916kDlyvmepkveMzJg7lycr1/x0FGkwCQqnMDAQEPGLg/x9SR5NybJuzFJ3o1J8m5MkndjMmreJecOMHw4LFhQ/PV/+AFGjVJFqXPn4OzZ/Mu5c2q+puRk1Zvp0KGCt1etWr7CU9uUFKhV60YRyt5zXy1erCYwT0zEyU7D/goiBSZR4bRs2dKQsctDfD1J3o1J8m5Mkndjkrwbk+TdmIyad8m5A4SFwXPPqcnBC5tu2mRS8y5ZJjtv3FgtBUlJyV+Auvn3q1dVISoxEfbvtz61KcAHH9zYVo0ahfeCCgxUPatuxeLFqshmOUwHT7ktczCJCmfVqlWGjF0e4utJ8m5Mkndjkrwbk+TdmCTvxmTUvEvOHcDdHX7+Wd0uqPeO5f6ffy5+byIvr/xzNH3/fd45mq5cgQMHYMUKNR/Uf/4DkyYR26KFGsLn6am2FR8Pe/aoYtDUqfDaa3DffdC9OzRsqPapdm3o1En1rnruOfjkE5g9G/76SxWzsrPz72NGhuq5BIUX1+xIejAJIYQQQgghhBDi9jB0KEREWIeJ4eSk5mSy/KxaVRWXhg4t27g+Pmq5qbfW+vBwxo8fr4o+iYmF94I6dw4yM9UE5rGxsGOH7VhOTqoIlbv3U2ys2r6OpMBUiFdeeYWPP/7Y+vv69evp2bNnoc9ZuXIl06ZNY/v27cTHx1OjRg06derEo48+yoABA4oVNy0tjalTpzJ37lxOnDhBVlYWQUFBDB48mGeffZa6xZwZ/9ChQ3z11VesWbOGmJgYvLy8aNasGffddx8PPfQQzs4VM/2dO3c2ZOzyEF9Pkndjkrwbk+TdmCTvxiR5Nyaj5l1y7kDDhsH58zBvHixcSHpMDB6BgTBixI1hcQ5iPXaTSV2xztcXWre2vbKmqR5OtopPliUmRvVgiolRy99/O+xYilIxKwwOsG/fPj7//PNir69pGo8//jjTpk3Lc39MTAwLFy5k4cKFPProo3z33XeYCploKyoqisGDB3P0ptnrIyMjiYyMZPr06fz+++8MGjSo0P354YcfeOqpp8jMzLTel5GRwaZNm9i0aRM//fQTS5cupXr16sU+xvIiJSXFkLHLQ3w9Sd6NSfJuTJJ3Y5K8G5Pk3ZiMmnfJuYO5u8OECTBhAsf37+eOO+5w/D5QwmM3mcDfXy3t29tex2yGixfzF55mzlTFKR3JHEw2mM1mHnnkEbKzs/H39y/Wc15//XVrcalt27aEh4ezfft2wsPDadu2LQDTpk3jP//5T4HbSElJYciQIdbi0iOPPMLatWv566+/eO+99/Dy8iIpKYmwsDD255o07GarVq3i0UcfJTMzk5o1a/Lll1+ybds2VqxYwciRIwH4+++/GTlyJObiXr6xHDlU2Kz9t3Hs8hBfT5J3Y5K8G5Pk3Zgk78YkeTcmo+Zdcm7M+GUe2zI8zjJH0/PPw6efwt13q8d0JAUmG7788kt27NhB06ZNeeihh4pc/8SJE3z00UcAdOjQgS1btjBu3Dg6duzIuHHj2Lx5Mx06dADgww8/JCoqyuZ2PvnkEyIjIwH46KOPmDZtGr1796ZLly7861//YvXq1Tg7O5OWlsbzzz9vcxvZ2dk8/fTTmM1mvL292bJlC8888wydOnViwIABzJ8/nyeffBKAjRs38uuvv5b05RFCCCGEEEIIIUR5Mny46t2kJ03kER0drXl5eWmAtn79eu3NN9/UAOvvtjz55JPWdbZu3Wpzna1bt1rXefrpp/M9npWVpVWtWlUDtGbNmmk5OTk2t/PYY49Zt7Nz5858j8+ZM8f6+AcffGBzG6mpqVq1atU0QGvZsmUBr4RtSUlJGqDFxcWV6HllKSsry5Cx9YyfkZGhTZ48WcvIyNAlvqZJ3vUgeZe860Xy7niSd8m7XiTvjid5N2ZsvfNu1M+bQ2Onp2tatWqaZjJpmprNSUu6XhtISkpyyC5ID6abPPnkk6SkpDBx4sQiJ/QGNffSokWLAGjatCl33nmnzfXuvPNOmjRpAkBERATaTZcN3LBhA1euXAFg4sSJOBXQtW2S5bKDwIIFC/I9HhERYXPd3Dw9PRkzZgwABw8e5Pjx4zbXK69Wr15tyNjlIb6eJO/GJHk3Jsm7MUnejUnybkxGzbvk3JjxHRbb3V1dHQ/UXE46kAJTLnPmzGHp0qX4+vrmuXpcYU6dOkVMTAwAPXr0KHRdy+Pnzp3j9OnTeR7btGlTvvVs6dChA5UrVwZg8+bN+R63bKdJkybUqlWryH0paDvlWXJysiFjl4f4epK8G5Pk3Zgk78YkeTcmybsxGTXvknNjxndo7KFDISICqlYFQHNwoUkKTNdduXKF5557DlDzJNWoUaNYzzty5Ij1dtOmTQtdN/fjuZ9Xku04OzsTHBxscxspKSmcO3eu1PtS3tWsWdOQsctDfD1J3o1J8m5Mkndjkrwbk+TdmIyad8m5MeM7PPawYXD+PMycibmIq8+XNSkwXffKK68QGxvLXXfdVayJvS3Onj1rvV2nTp1C1w0KCrL5vNy/V65cmarXq41FbSc+Pp7MzEzr/efOnbMOvSvNvpR3lgnTjRa7PMTXk+TdmCTvxiR5NybJuzFJ3o3JqHmXnBszvi6x3d1hwgSyZ8xwaFhnh0YrpzZv3sz06dNxdnbmu+++w1SCbmRXr1613vby8ip0XcvQNlC9jWxtp6ht2NqOm5tbme5LbpmZmXmKWJbufTff70iLFy8mLCzMcLH1jG/JtV45B8m75N1YsfWML3mXvOtF8i55N1JsPeNL3o0ZW++8G/XzpndsR+fbpN0827TBZGVl0aZNG44cOcLLL7/MRx99lOfxyZMn89ZbbwGwfv36fBN/v/POO7zxxhsArF27lt69excYa926dfTp08f6vNdff936WHBwMCdPniQoKIjo6OhC9/mBBx5g5syZgOp9ZOmttGnTJrp37w7Af/7zH95+++0Ct2E2m6lUqRIAffr0Yc2aNTbXy338ub322mu4u7sXup9CCCGEEEIIIYTQR0ZGBlOmTCEpKQlvb2+7xzN8D6b333+fI0eOULduXd58880SPz93kSUrK6vQdXNXDz08PGxup6htFLadstqX3P75z3/y4osvWn9PTk4mKCiIp556qtjzVJW1EydO0KhRI8PF1jN+ZmYmn3/+OS+88IK1x5yjSd4l70aKrWd8ybvkXfJunPiSd8m75N04sfXOu1E/b3rHjo+PZ8qUKQ6LZ+gCU2RkJB988AEAX331VZ5hY8VVpUoV6+3ChpoBpKamWm/fPITNsp2itlHYdspqX3Jzc3Oz2QAVdL+jGDW23vEl7/rR+9j1jm/E2HrHl7zrR+9j1zu+EWPrHV/yrh+9j13v+BJbn/h67UN5OHajxXZ0XENP8v3555+TlZVFw4YNSUtLY9asWfmWgwcPWtdft26d9X5LgSb3ZNqWK7gVJPdk2rkn2c69ndTUVK5cuVKs7dSoUSPPG6as9qW8279/vyFjl4f4epK8G5Pk3Zgk78YkeTcmybsxGTXvknNjxtf72B3J0D2YLMPETp48yfjx44tc/5133rHePnXqFJUrV6Z58+bW+yIjIwt9fu7HmzVrluex5s2bM3/+fOt6d955p81tZGdnExUVZXMbXl5eBAUFcfbs2VLtixBCCCGEEEIIIURJGLoHU1lo0KABAQEBAPz555+Frrtx40YAAgMDqV+/fp7HunXrZr1d2HZ27txp7T3VtWvXfI9btnP06FFiY2ML3E7uGLa2U54NHz7ckLHLQ3w9Sd6NSfJuTJJ3Y5K8G5Pk3ZiMmnfJuTHj633sjmToAtNPP/2EpmmFLrkn/l6/fr31fkuByGQyERoaCqheQX///bfNWH///be111BoaCgmkynP4z179sTHxweAn3/+mYIu7vfTTz9Zb48YMSLf47nfvLnXzS0tLY05c+YAqudUSEiIzfXKK0uhzmixy0N8PUnejUnybkySd2OSvBuT5N2YjJp3ybkx4+t97I5k6AJTWXn++edxdlajDZ955hnS09PzPJ6ens4zzzwDgLOzM88//3y+bbi6uvLss88CcOTIET755JN862zdupUffvgBgB49etCxY8d864wYMYLg4GAAPvjgA+twutxefvllEhMTrbcrmsuXLxsydnmIryfJuzFJ3o1J8m5Mkndjkrwbk1HzLjk3Zny9j92RpMBUBkJCQnjppZcANYSta9euzJ49m507dzJ79my6du3Kzp07AVXQady4sc3tvPzyy9beRK+88gqPPfYY69ev5++//+aDDz6gX79+ZGdn4+HhwRdffGFzGy4uLnz55Zc4OTmRnJxM165d+frrr9m+fTurVq1i9OjRfPPNN4AaTnf//feX8athf9WrVzdk7PIQX0+Sd2OSvBuT5N2YJO/GJHk3JqPmXXJuzPh6H7sjGXqS77L03nvvERcXx48//siePXsYN25cvnUeeugh3n333QK3UaVKFZYtW8agQYM4fvw406ZNY9q0aXnW8fb25rfffqNNmzYFbmfQoEF89913PP3001y8eNHaeyq3Tp06sXDhQipVqlT8gywncs9XZaTY5SG+niTvxiR5NybJuzFJ3o1J8m5MRs275NyY8fU+dkeSHkxlxMnJiR9++IFly5YRGhpKQEAArq6uBAQEEBoayvLly5k+fTpOToW/5I0aNWLPnj18+OGHdOjQgapVq+Lp6UmTJk144YUX2L9/P0OGDClyfx555BF27drFI488QsOGDXF3d6d69ep069aNb7/9li1btuDn51dWh+9QixYtMmTs8hBfT5J3Y5K8G5Pk3Zgk78YkeTcmo+Zdcm7M+HofuyNJD6YiTJ48mcmTJxd7/UGDBjFo0KBSxaxcuTKvvPIKr7zySqm207Jly3w9oIQQQgghhBBCCCHKmvRgEhVOYcMDb+fY5SG+niTvxiR5NybJuzFJ3o1J8m5MRs275NyY8fU+dkeSApOocIoaZni7xi4P8fUkeTcmybsxSd6NSfJuTJJ3YzJq3iXnxoyv97E7knGOVNw2du/ebcjY5SG+niTvxiR5NybJuzFJ3o1J8m5MRs275NyY8fU+dkeSApMQQgghhBBCCCGEKBUpMIkKpzhX0bsdY5eH+HqSvBuT5N2YJO/GJHk3Jsm7MRk175JzY8bX+9gdSQpMosLZvn27IWOXh/h6krwbk+TdmCTvxiR5NybJuzEZNe+Sc2PG1/vYHUkKTKLCiYuLM2Ts8hBfT5J3Y5K8G5Pk3Zgk78YkeTcmo+Zdcm7M+HofuyNJgUlUOD4+PoaMXR7i60nybkySd2OSvBuT5N2YJO/GZNS8S86NGV/vY3ckKTCJCqdPnz6GjF0e4utJ8m5Mkndjkrwbk+TdmCTvxmTUvEvOjRlf72N3JGe9d0BUDFOnTmXq1Knk5OQAEBERgZeXFyNHjmTt2rUkJSXh7+9Pp06dWLp0KQDt2rXDbDazd+9eAEJDQ9m8eTOXLl3C19eX7t27ExERAcAdd9yBi4sLu3btAmDw4MHs3LmTixcv4u3tTb9+/Zg3bx4AycnJ9O3bl23btgHQv39/Dh48SExMDJUrV2bIkCHMnj0bgCZNmuDn58eWLVsAuOeeezh27BjR0dG4ubkxcuRIZs+ejdlsJjg4mMDAQDZu3AhAz549iY6O5uTJkzg7OxMWFsbUqVOpXbs29erVIzg4mHXr1gHQrVs34uLiOHbsGADjx49n0aJFpKWlUadOHZo3b87q1asB6NKlC0lJSRw+fBiAsLAwVq5cydWrV6lVqxbt2rVj+fLlAHTs2JGMjAwOHDgAQE5ODn5+fiQmJuLn50eXLl1YsmQJAG3btgVgz549AAwdOpStW7eSkJBAtWrV6NmzJwsXLgSgVatWuLu7s2PHDgAGDRrE7t27iY2NpUqVKgwYMIC5c+cC0Lx5czw8PACYN28eAwYM4PDhw5w7dw5PT09CQ0MJDw8HICQkBH9/fzZv3gxA7969iYqK4syZM7i6ujJq1Cjmzp1LdnY2DRs2pG7dumzYsAGA7t27ExMTQ1RUFE5OTowdO5YFCxaQmZlJ3bp1OX78OG5ubgB07dqVhIQEjh49CsDYsWNZunQpqampBAYG0rJlS1atWgVA586dSUlJ4dChQwCMHj2a1atXk5ycTM2aNenQoQPLli0DoH379ly7do39+/cDMHz4cDZu3MiBAwe444476NatG4sWLQKgTZs2ODk5WS87OmTIELZv305cXBw+Pj706dOHBQsWANCyZUs8PT2t468HDhzIvn37OH/+PF5eXgwaNIg5c+YA0LRpU3x9ffnrr78A6Nu3L7Nnz8bX1xcPDw+GDx/OrFmz0DSNxo0bU6tWLTZt2gRAr169OH36NKdOncLFxYXRo0czb948rl27RoMGDahfvz7r168H4O677yY2Npbjx49jMpkYN24cERERpKenExQURNOmTa2vYXR0NCkpKURGRgIwZswYli9fTkpKCgEBAbRu3ZoVK1YA0KlTJ9LS0jh48CBAqduIqVOnEhgYWKI2okWLFnh5eZW6jbhw4QIvvvhiidqI+fPnk5WVVSZtxB9//EFgYGCJ2ogRI0awYcOGUrURZrMZgJMnT1pzU1Qb4ePjw9atWwHo169fqduIM2fOcPfdd5eojQgJCWHNmjWlbiPMZjNVq1YtURtx+fJlqlevXiZtRExMDA8//HCJ2ojIyEjOnj1bqjYiKCgIUO28k5NTsdqIP/74A4C77rqLy5cvl7qNSEhIYNKkSXY/j7DVRvz+++9Ur17d7ucRBbUR6enptG7d2u7nETe3Ee3bt7fm3XLbHucRhbURaWlpWNjzPMJWG7Fu3ToCAwPtfh5RUBuxefNmvLy8APueR9zcRsyfP9+a6zp16tjtPKKwNuLbb7+lZs2adj+PsNVGxMTE8Oijj9r9PMJWG3Ho0CHc3d0B+59H3NxGJCUlAZCUlMTatWsB+5xHgO024pdffsHPz88h5xG22oiMjAxatGhh9/MIW23EtGnTCAwMdMh5BORtIxzNpGma5vCoosJKSkqiatWqREVF4efnp8s+zJ07l7CwMMPF1jN+ZmYmn332GS+++KK1yONoknfJu5Fi6xlf8i55l7wbJ77kXfIueTdObL3zbtTPm96xExISCA4O5sqVKw4ZqicFJlEiJ0+eJDg4WO/dEEIIIYQQQgghRDFERUXRsGFDu8eRIXKiRHx9fQE1ZEavyco6duxo7W5ppNh6xk9OTiYoKIizZ8/i7e3t8PggeZe8Gyu2nvEl75J3ybtx4kveJe+Sd+PE1jvvRv286R07KSmJunXrWr/H25sUmESJODmpeeF9fHx0+4NUqVIlQ8YuD/G9vb0N+drr/brrHV/yrg+940ve9aF3fMm7PvSOL3nXh97xJe/Gim2hV971Pnaj593yPd7ucRwSRYgy9NRTTxkydnmIryfJuzFJ3o1J8m5Mkndjkrwbk1HzLjk3Zny9j92RZA4mUSLJycn4+PiQlJSkexVWOI7k3Zgk78YkeTcmybsxSd6NSfJuTJJ3Y3J03qUHkygRNzc33nzzTd2uOCH0IXk3Jsm7MUnejUnybkySd2OSvBuT5N2YHJ136cEkhBBCCCGEEEIIIUpFejAJIYQQQgghhBBCiFKRApMQQgghhBBCCCGEKBUpMAkhhBBCCCGEEEKIUpECkxBCCCGEEEIIIYQoFSkwiVvyyiuvYDKZrMuGDRv03iVhJwkJCXz00Ud07dqVWrVq4ebmRkBAAJ07d+bll19m69ateu+iKENZWVn88MMPDBgwgNq1a+Pm5oaXlxdNmjThwQcf5O+//9Z7F0UJxMXFsXTpUt544w0GDhyIn5+ftd2eNGlSibe3cuVKRo4cSZ06dXBzc6NOnTqMHDmSlStXlv3Oi1tWFnnPyMhg0aJFPPPMM3Tu3BlfX19cXFzw9fWlS5cuTJ48mQsXLtj3QESxlfVnPbe0tDQaNmxo3V79+vXLZJ9F6dkj79u3b+fJJ5+kWbNmeHt74+XlRXBwMIMHD+azzz4jPj6+bA9ClFhZ5v3MmTO89tprtG/fnqpVq1rb+bvuuot33nlH8l2O7N69m/fff5+BAwcSFBRkPUcPCQlh0qRJbNq0qUTbs9s5nSZECe3du1dzdnbWAOuyfv16vXdL2MGcOXO06tWr58n1zUtoaKjeuynKSHR0tNaqVatC8w1oL7zwgmY2m/XeXVEMheVx4sSJxd6O2WzWHn300UK39+ijj8r7opwobd737dunValSpci2oEqVKtrs2bPtf0CiSGX1Wbfl//7v//Jsr169emWyz6L0yjLvGRkZ2sMPP6yZTKZCt7tw4UK7HIsovrLK+2+//aZ5enoWur3q1atra9eutd/BiGLp3r17kX+TAe3+++/XMjMzC92Wvc/pnAutPglxE7PZzCOPPEJ2djb+/v7ExcXpvUvCTn755Rf+8Y9/YDab8ff354knnqBbt274+voSGxtLVFQUS5YswcXFRe9dFWUgOzubwYMHc+DAAQDuuOMOXnzxRZo0acLVq1fZvHkzn376KampqXz++efUrl2bl19+Wee9FiURFBREs2bNWL16dYmf+/rrrzNt2jQA2rZtyyuvvEJwcDBRUVF89NFH7Nmzh2nTplGjRg3efffdst51UQq3kvfk5GSuXr0KQNeuXRkyZAgdOnSgevXqxMfHs2DBAqZPn87Vq1e59957qVKlCgMHDrTXIYgSKs1n/WZ79uzhiy++wN3dHRcXF+v7QpQ/pcl7VlYWI0aMYMWKFQDcfffdPPDAAzRr1gxnZ2fOnDnDvn37mDt3blnvtiilW8371q1beeCBB8jJycHJyYmJEycSGhpKQEAA0dHR/PzzzyxZsoRLly4xbNgwDh48KL0XdRQTEwNAQEAAYWFh3H333dStW5ecnBy2bt3Kp59+SkxMDDNnziQ7O5vff/+9wG3Z/ZzulspSwrA+//xzDdCaNm2q/fOf/5QeTLepw4cPa25ubhqg3X333dqVK1cKXLeoKrmoGObNm2f9PHfp0kXLzs7Ot87OnTs1FxcXDdCqVaumXbt2TYc9FSXxxhtvaEuWLNFiY2M1TdO0U6dOlfi/nMePH7f2Wu3QoYOWlpaW5/HU1FStQ4cOGqA5OztrJ06cKOvDECVU2rxv2bJFGzNmjHbo0KEC14mIiLD2dAgODpbeazori8/6zbKzs7X27dtrgPb2229r9erVkx5M5UxZ5f0///mP9XmffPJJoetmZWWVZpdFGSiLvA8ZMsT6nKlTp9pc58UXX7Su88wzz5TV7otbMHjwYG327Nk2z881TdPi4+O1kJAQa742btxocz1HnNNJgUkUW3R0tObl5WUtKL355ptSYLpN9enTRwM0Pz8/LT4+Xu/dEQ7wwgsvWD/PixcvLnC9ESNGWNc7cOCAA/dQlIVbOQl98sknrc/ZunWrzXW2bt1qXefpp58uwz0WZaEsig22jBo1yrrd3bt3l9l2RemVRc4//fRTDdCaNGmiZWZmSoGpAriVvEdFRVn/eTRp0iT77qCwi1vJe7Vq1axD4Apy5coV63bbt29fRnsr7GXJkiXWfD377LM213HEOZ1M8i2K7cknnyQlJYWJEyfSs2dPvXdH2ElkZCRr164F4Omnn8bPz0/nPRKOkJWVZb3dsGHDAtcLDg623s7MzLTrPgn9aZrGokWLAGjatCl33nmnzfXuvPNOmjRpAkBERASapjlsH4V+evXqZb0dFRWl456IsnbmzBneeOMNAL799ltcXV113iNhL9OmTePatWuYTCZrzsXtz3Le16BBgwLX8fHxsX4PkHO+8i/393Nbf5MddU4nBSZRLHPmzGHp0qX4+vry8ccf6707wo5yj68PCwuz3k5MTOT48eNcunRJj90SdhYSEmK9ffLkyQLXs/zBMplMNG7c2O77JfR16tQp67j/Hj16FLqu5fFz585x+vRpe++aKAdyf+FwcpJTytvJk08+SWpqKvfff3+eQqK4/VjO+zp06GAtNpjNZs6dO8epU6dIT0/Xc/eEnVjO+06dOlXgOsnJySQkJORZX5Rfuf9ZbOtvsqPO6eRsQBTpypUrPPfccwB8+OGH1KhRQ+c9EvZkuQy9j48PzZo147fffqN169b4+voSEhKCn58fDRs25K233iIlJUXnvRVlZfz48Xh7ewPqc56Tk5NvnT179rBs2TIAxo0bZ11f3L6OHDlivd20adNC1839eO7nidvXn3/+ab1d1PtDVByzZs1i+fLlVKtWjU8++UTv3RF2FB8fb/2nUpcuXUhOTub555/Hz8+PoKAgGjZsiLe3Nz169LD+/Re3h8ceewyAS5cu8d1339lc55133sm3vii/ivqb7KhzOrmKnCjSK6+8QmxsLHfddRcPPfSQ3rsj7Ozw4cMA1K9fn2eeeYapU6fmW+fUqVNMnjyZefPmsWrVKgICAhy9m6KM1ahRg59++on77ruPLVu20LFjR55//nlCQkJISUlhy5YtfPrpp2RlZdGmTRs+++wzvXdZOMDZs2ett+vUqVPoukFBQTafJ25P+/bts37hbNGiBc2bN9d5j0RZSExM5PnnnwdgypQp+Pv767tDwq4s53wAHh4etGvXLt/QmuzsbDZu3MjGjRt54YUX5O//beLhhx9m06ZN/Pbbbzz11FPs2rWLYcOGUbt2baKjo/n1119ZuHAhAK+++ir9+vXTeY9FYcxmM1OmTLH+PmbMmHzrOOqcTnowiUJt3ryZ6dOn4+zszHfffYfJZNJ7l4SdXb58GVBzMU2dOpWqVavy3XffERcXR0ZGBjt27LBejvrgwYOEhYVhNpv13GVRRkaMGMHOnTt56KGH2Lt3LxMnTqRLly707duXyZMn4+npyWeffcbmzZupVauW3rsrHCD3Jcm9vLwKXbdy5crW29K78faWmZnJww8/bO3p+P777+u8R6KsvPzyy1y8eJEuXbrwyCOP6L07ws4s53wAX3zxBVFRUdx11138+eefpKWlcfnyZX777Tdq164NwOeff15gbxdRsVSqVIlff/2V2bNn07p1a6ZPn86wYcPo2LEjo0aNYuHChfTq1YtVq1blKVyI8unzzz9n+/btgDqf79ChQ751HHVOJwUmUaCsrCweffRRNE3jhRdeoFWrVnrvknCA1NRUQH2BqFSpEitWrOCxxx6jRo0auLm50aFDB5YuXWotMv31118sWLBAz10WZeTatWv8/vvvLFmyxOaEfhcvXiQ8PJwNGzY4fueELjIyMqy3i5rk183NzXpb5uy4vT399NPs3LkTgIkTJzJs2DCd90iUhY0bN/Ljjz/KPxUNxHLOB+q8r3379qxdu5bu3bvj4eFBtWrVuPfee/nzzz+tXzjfeOMNaeNvE5GRkfz+++8cOHDA5uNbt27ll19+4cKFCw7eM1ESf/75J6+99hoA/v7+fPvttzbXc9Q5nRSYRIHef/99jhw5Qt26dXnzzTf13h3hIO7u7tbbYWFhNq8w4OTklGey9/DwcIfsm7Cf1NRU7rnnHt577z0uXbrEK6+8wpEjR8jMzCQpKYnVq1fTrVs3duzYwdChQ/nvf/+r9y4LB8jdHuSePNKW3BM+e3h42G2fhL4++OADpk+fDkD79u1tDqMWFU9mZqb1n4rPPfccd9xxh967JBwgdxsP8N577+W7D6Bx48Y88cQTgJq3ac2aNQ7ZP2E/mzZtokuXLixatIjAwEBmzpxJbGwsWVlZnD17lqlTp+Lh4cFvv/1Gp06dZG7FcurQoUOMGDGC7Oxs3NzcmDNnDjVr1rS5rqPO6aTAJGyKjIzkgw8+AOCrr77K001O3N6qVKlivW3ppWRLixYtCAwMBGDHjh123y9hX2+++SYbN24E4IcffuDDDz+kadOmuLq64u3tTd++fVm/fj29evVC0zRefPFF9u/fr/NeC3vL3R4U1UU693/Ci+p6LSqm//3vf/zrX/8CoEmTJqxYsULOD24T7733HkePHiUoKIjJkyfrvTvCQXK38a6uroVeMbB///7W23LeV7FlZmYyfvx4rly5Qq1atfj777+ZMGECNWvWxMXFhTp16vDkk0+yadMm3N3dOXfuHA888IDeuy1ucurUKfr160diYiKVKlUiPDy80KvDOeqcTib5FjZ9/vnnZGVl0bBhQ9LS0pg1a1a+dQ4ePGi9vW7dOmJjYwEYOnSonHBWYEFBQdZcFmcCuJiYGOLi4hyxa8JONE1jxowZgLoM7cSJE22u5+zszDvvvEO3bt0wm83MmDGDzz//3JG7Khwsdxtw7ty5QtfNPQlk7skhxe0hPDycJ598EoB69eqxZs0auarsbeTDDz8E4J577mHp0qU217F84UhNTbWeF/r7+9O7d2/H7KQoc7nb6po1axY6bCb3unLeV7GtXLnSern6Z555psB5NVu0aMGECROYPn06O3fuZN++fbRu3dqRuyoKcP78ee655x7Onz+PyWTixx9/ZMSIEYU+x1HndFJgEjZZusWdPHmS8ePHF7l+7stYnjp1SgpMFViLFi2s/5mydan63CyPOztLU1KRXbx40TrRZ9u2bQtdt3379tbbkZGRdt0vob/cVwYrKt+5H2/WrJnd9kk43uLFi3nggQcwm83Url2btWvXFvkPCFGxWIZLzJgxw/oPh4IkJCRYzw179OghBaYKrHHjxri4uHDt2rVin/OBnPdVdLmHu7Vr167Qddu3b28dFh0ZGSkFpnIgISGBvn37cvLkSUCNNipODzNHndPJEDkhRB7du3e33r75UrU3szRslqFyomLKfaKYnZ1d6LrXrl2z+Txxe2rQoAEBAQGAmkSyMJYhloGBgdSvX9/euyYcZO3atYwZM4bs7GyqV6/OH3/8QXBwsN67JYQoAy4uLnTp0gVQ/2zKPSzmZrnPCeW8r2KT876KKykpif79+3P48GEApkyZwlNPPVWs5zrqnE4KTMKmn376CU3TCl1yT/y9fv166/3yxaJiGzZsGC4uLgCFXh3uzz//5NKlSwDcfffdDtk3YR++vr54e3sD6oohhZ1s5P6D1KBBA7vvm9CXyWQiNDQUUP/N+vvvv22u9/fff1v/2xUaGipXn7pN/PXXX4SGhpKZmYm3tzerVq2iRYsWeu+WsIOizvk0TaNevXqAGiJpuU+uKlrxjRo1ClA9lBYtWlTgernPCeW8r2LLff62adOmQteV877yIy0tjcGDB7N7924A/v3vf/Pqq68W+/mOOqeTApMQIo/q1avz8MMPA/DHH3/YnH/r6tWrPP/889bfH3vsMUftnrADJycnBg8eDKgx3e+9957N9RITE/P8IRsyZIhD9k/o6/nnn7f+1/KZZ57Jd7na9PR0nnnmGUD9dzN32yAqrr179zJ48GBSU1OpXLkyy5cvzzNEVghxe3jwwQfx9/cH4F//+hcXL17Mt86GDRuYOXMmAC1btqRr164O3UdRtvr06YOnpycA3377LQcOHLC53ooVK1i4cCGgerK0adPGUbsobpKVlcWIESPYsmULAM899xzvvvtuibfjiHM66ecmhMjnrbfeYtmyZURHR3P//fezZcsWRo4cibe3NwcOHODDDz+0VrafeOIJOnbsqPMei9J64403WLRoEWlpaUyePJldu3YxceJEGjZsSEZGBn///TdffPEF0dHRgDo56devn857LYqyefNmTpw4Yf09ISHBevvEiRP89NNPedafNGlSvm2EhITw0ksvMWXKFHbu3EnXrl159dVXCQ4OJioqig8//JA9e/YA8PLLL9O4cWO7HIsovtLmPSoqiv79+3PlyhUA3n33XXx8fPJc3ONm/v7+1i+pwvHK4rMuKp6yyLuXlxdffvkl48eP58yZM3Ts2JHXXnuNTp06kZGRwYoVK/j888/JycnB2dmZ7777Tnqp6qy0ea9atSqvvfYab7zxBlevXuWuu+7imWeeoW/fvlSrVo2LFy+yaNEivv/+e8xmM6CGYjk5Sd8UvYwfP57Vq1cD0Lt3bx566KFC/ya7uroSEhKS736HnNNpQtyiN998UwM0QFu/fr3euyPK2OHDh7VGjRpZc2xrefDBB7WsrCy9d1WUkT/++EPz8/MrNOeA1rt3b+3y5ct6764ohokTJxaZz9xLQXJycrQHH3yw0Oc+9NBDWk5OjgOPThSktHmfMWNGiZ4PaG+++abjD1RYldVnvTD16tXTAK1evXplu/PilpVl3r/++mvN1dW1wOd6eXlpERERDjoyUZiyyLvZbNaef/55zWQyFfpcFxcX7eOPP3bwEYqblfRvcmHttL3P6aQMKYSwqVmzZuzdu5ePP/6Yzp074+vri6urK3Xq1GHs2LGsW7eOH374wTpfk6j47rnnHiIjI/nwww/p2bMnNWrUwMXFBQ8PDxo0aMCYMWOIiIhgzZo1VKtWTe/dFQ7k5OTEDz/8wLJlywgNDSUgIABXV1cCAgIIDQ1l+fLlTJ8+Xf67KYQQFdRTTz3F7t27eeKJJ2jUqBEeHh54eXlxxx138Morr3Ds2DHr/C2i4jOZTHz++efs2LGDxx9/nJYtW1KlShUqVaqEj48P7du358UXX+TgwYO89NJLeu+uKEP2PqczXa+ICSGEEEIIIYQQQghxS+RfjUIIIYQQQgghhBCiVKTAJIQQQgghhBBCCCFKRQpMQgghhBBCCCGEEKJUpMAkhBBCCCGEEEIIIUpFCkxCCCGEEEIIIYQQolSkwCSEEEIIIYQQQgghSkUKTEIIIYQQQgghhBCiVKTAJIQQQgghhBBCCCFKRQpMQgghhBBCCCGEEKJUpMAkhBBCCCGEEEIIIUpFCkxCCCGEMLRJkyZhMpmoX7++3rtiaD179sRkMtGzZ0+9d6VQp0+fxmQyYTKZ+Omnn/TeHSGEEKLckAKTEEIIIewuKSmJqVOnMmjQIOrXr4+npyc+Pj6EhIRw3333MXv2bHJycvTezQrjp59+shY5bl6cnJzw9vamZcuWPP744+zevVvv3S13jh8/ziuvvEKnTp3w9fXFxcUFPz8/mjdvTr9+/Zg8eTIbNmwgIyND710VQgghKgxnvXdACCGEELe36dOn89prr3Hp0qU896enp5OcnMzx48f5/fffad68Of/73//o1q2bTnt6e9A0jatXr3Lo0CEOHTrE999/z7///W/efvttvXetXHjvvfeYPHky2dnZee6/dOkSly5d4siRI/zxxx+89dZbvPrqq0yZMkWnPRVCCCEqFikwCSGEEMJuXn75ZT755BMAnJ2dGTduHMOGDaNevXpkZWVx9OhRwsPDWbt2LYcPH+aee+7h119/ZfTo0TrvecXx7rvvEhoaav3dbDYTHx/Phg0b+OKLL0hJSeGdd96hQYMG/OMf/9BxT/X38ccf8/rrrwPg4+PDY489Ro8ePahduzZZWVmcO3eObdu2sWTJEiIjI21uo379+mia5sjdFkIIISoEKTAJIYQQwi6mTp1qLS4FBQWxZMkSWrdunWedbt268dBDDzF79mweeOABMjMzue+++2jUqBFt2rTRYa8rnsDAQFq2bJnv/j59+tCzZ0/69u2Lpml89NFHhi4wXbp0iTfffBOAOnXq8NdffxEUFJRnnc6dOzNq1Cg++ugjtm/fnq/XnRBCCCEKJnMwCSGEEKLMnTlzhpdeegkALy8v1q1bl6+4lNvYsWP5+eefAcjKyuL++++XXiJloE+fPrRv3x6AyMhIkpOTdd4j/axevZr09HQAXnvttXzFpZt16tSJgQMHOmLXhBBCiNuCFJiEEEIIUea++OIL6wTJb775Jo0aNSryOePGjWPw4MEAHDx4kKVLl+Zb5+YrjR0/fpynn36axo0b4+npiclk4vTp03mec/jwYSZOnEhQUBDu7u4EBQVx7733smPHjhIdU2JiIu+++y5dunTBz88PNzc3AgICCA0NZcGCBYU+1zIB9+TJkwFYt24dYWFhBAUF4eLiYtcr2OXedmGTVmdlZfHNN9/Qq1cvatSogaurK7Vq1WLQoEH8+uuvmM3mImOlpKQwZcoUunTpgq+vL25ubtSpU4fRo0fbzGdJ/f7777i4uGAymejSpQuJiYnFfu6ZM2est4vzfixIYVeRK2zydVuL5f1wM03TmDdvHqNGjbK+b6tVq0anTp145513uHLlyi3vvxBCCGEvMkROCCGEEGVK0zR++eUXADw8PHjkkUeK/dxnn32WZcuWATBjxgyGDh1a4LqLFi3ivvvuIzU1tcB1Zs2axcSJE8nKyrLed+7cOcLDw5k7dy7/+9//irVfy5cv57777sv3xf7ChQssXryYxYsXM3jwYGbNmoWXl1eh2/r3v//N+++/X6y4ZcFScHN3d6dGjRo21zlz5gwDBw7kyJEjee6/ePEiK1asYMWKFfzvf/9j0aJF+Pr62tzGnj17GDJkCOfPn89zf0xMDPPnz2f+/PmMHDmS3377DXd39xIfx9dff82zzz6Lpmn07duXhQsXUrly5WI/39XV1Xr7yJEj9O/fv8T74Ajx8fGMGDGCLVu25Lk/MzOTHTt2sGPHDqZOncqiRYvo3LmzTnsphBBC5CcFJiGEEEKUqUOHDnH58mUAunfvjo+PT7Gf26dPHzw9PUlLS2Pz5s0FrhcdHc2ECRPw9PTkP//5D3fffTeVKlVix44d1gLPtm3buP/++8nOzsbNzY0XXniBQYMG4ebmxrZt23j//fd5/PHHad68eaH79McffzBs2DBycnKoX78+TzzxBJ07d8bb25uYmBhmz57Nr7/+yrJly5g4cSLz588vcFsLFy5k//79tGrVihdeeIGWLVuSnp7O3r17i/0alcT69evZvXs3AEOHDsVkMuVbJyUlhd69e3Py5EkAhg8fzoMPPkhAQACnTp3i66+/5s8//2Tz5s0MGTKETZs2UalSpTzbiImJoU+fPiQmJmIymZg0aRLjxo2jevXqHD58mE8//ZR9+/axYMECJk6cyOzZs0t0HG+//bZ1/qRRo0bx+++/5ykYFUfbtm2tt9977z169epV6LDNWzF8+HA6dOhQ6Dovv/wyK1euBKBevXp5HktNTaVHjx4cOXIEV1dX/vGPfzBo0CCCgoJITU1l48aNfPbZZ1y8eJGBAweyZ8+efNsQQgghdKMJIYQQQpShX3/9VQM0QPvnP/9Z4ud36dLF+vyYmJg8j/Xo0cP6WEBAgHbmzJkCt9O+fXsN0FxcXLQ///wz3+Pnzp3T6tSpY91evXr18q2TkpKi1axZUwO0fv36aampqTZjTZs2zbqdNWvW5Hvc8hig9enTR8vIyCjiVSjcjBkzrNt79913tQMHDliXffv2aWvXrtXeeOMNzdvbWwO02rVra0ePHrW5rZdeesm6rddffz3f42azWbvvvvus63zzzTf51hk9erT18enTp+d7PCMjQ+vVq5d1neXLl+dbx5LbHj165In97LPPWp/38MMPazk5OSV4pW7IycnR7rjjDuu2TCaT1qNHD+2dd97RVq1apSUmJhZrO6dOnbJuY8aMGSXah6+//tr63Pvuuy/f408//bQGaD4+PtqOHTtsbuP06dNa7dq1NUCbMGFCieILIYQQ9iQFJiGEEEKUqS+++ML6Jfq///1viZ8/fPhw6/P379+f57HcBaZffvmlwG1s27bNut7TTz9d4HqzZ88utMD01VdfaYDm7u6uXbx4sdD97tSpU4GFA0sMJycn7dSpU4VupzhyF5gKW9zc3LRXXnlFO3v2rM3tZGRkaFWrVtUArXnz5lp2drbN9ZKSkrTq1atb18vt/PnzWqVKlTRA69+/f4H7fOrUKc3Z2VkDtEGDBuV7/OYC07Vr17T777/feiwvv/xyMV+dgh0/flxr1KiRzdfKZDJprVq10l555ZUCi3GW47iVAtOaNWusx9+pUyctPT09z+Px8fGau7t7sT4333zzjbV4WlDRUwghhHA0meRbCCGEEGXq6tWr1tslmSPH1nMKuuqZq6srYWFhBW5jzZo11tv/+Mc/ClxvxIgRVK1atcDHFy1aBECPHj3w9/cvcD1QwwEBtm7dWuA6Xbt2teuE3jfLzMxk5syZzJw50+ZV+Xbt2mWdV2rSpEn5hr5ZeHt7M2bMGEBNmn7hwgXrY+vXrycnJweAhx56qMB9qV+/Pn379gVgw4YN1ufYkpGRwciRI5k5cyYAH3zwAR999FEhR1o8jRo1Yu/evUyZMoXg4OA8j2maxoEDB/joo49o3rw5//d//0d2dnapY4KajD4sLIzs7GwCAwOJiIjINw/VqlWrrJOwW17rgljea9euXWPXrl1lso9CCCFEaUmBSQghhBBlqkqVKtbbKSkpJX5+7ud4e3vbXKdx48aFThR94MABQBWi7rjjjgLXc3FxyTM3z8127twJqC//RV0R7JNPPgEgNja2wO0Vti+3asaMGWiqV7p1uXr1Ktu3b+fhhx/mwoUL/Otf/2L8+PH5ikwHDx603i5qwujcj+d+3q1sIy0tzTrn082uXr1K//79WbJkCU5OTvzvf//jtddeK3S7JVG5cmVeffVVTpw4QWRkJD/++CPPPvssnTp1wslJnRrn5OTw2Wef8fDDD5c63pUrVxg6dCiJiYl4eHiwaNEiateunW89y3sNoHbt2oW+11q2bGldt7D3mxBCCOFIMsm3EEIIIcpU9erVrbdv5cvvxYsXbW4rt2rVqhW6Dcvl6319fXF2Lvx0p2bNmjbvv3bt2i1dDj4tLa3Ax4ra77Li5eVFx44d6dixI/7+/rz//vvMnj2bfv368eCDD1rXs0zGDgW/Dha1atWy+byy2EZulknJAR5//HEeffTRQrdZGk2aNKFJkybW32NiYpg8eTLTp08H4Oeff+bhhx+mW7dut7T9nJwcxo4dy9GjRwH46aefaN++vc114+LibilGYe83IYQQwpGkwCSEEEKIMpX7ylx79uwp0XNzcnLYv38/ADVq1CAgIMDmegUN5bKw9NSxddW0gta1tS8WY8aM4T//+U+R2ypKUfttD//3f//HlClTMJvN/PDDD3kKTLkV9VoV9DqVRHG20aJFC7Kzszl69Cj/+9//6N69O2PHji117OIIDAzk+++/JyUlhVmzZgEwd+7cWy4wvfDCC6xevRqAN954o9Chb5b3m6ura4mGvdWpU+eW9k0IIYQoa1JgEkIIIUSZatmyJb6+vly+fJmNGzeSlJSEj49PsZ67Zs0aa4+MW/1SD6rnEsClS5fIyckptLBTUM8Rd3d3PD09SUtL48qVK3mGJVUkvr6+1KhRg4sXL1qHDuZ+zCI2NpaQkJACt5O7Z1nu5+W+ffHiRerWrVvibeTm5+fH77//Ts+ePTl+/DgTJkygUqVKjB49usDtlrVHHnnEWmA6ceLELW1j2rRpfPXVVwCMGjWKyZMnF7q+pbdeVlYW1atXtzmMTgghhCjPZA4mIYQQQpQpk8nE/fffD0B6ejrff/99sZ9r+UIOatLpW9WqVStAfVnft29fgetlZ2ezd+/eAh+3zM+0ZcuWCj0UyTJZ9bVr1/Lcn7totm3btkK3sX37dpvPu5VteHp60qBBgwLXCwgIYP369TRq1Ijs7GzGjx9PREREodsuS7l7zlnmZSqJDRs28PTTTwPqPfTLL78U2UMs91xgll5PQgghREUiBSYhhBBClLnnnnsONzc3AN56661i9QKZNWsWy5YtA6B58+YMGTLkluPfc8891ts///xzgestXLjQOl+TLcOGDQMgNTWVqVOn3vL+6OnUqVNcunQJgKCgoDyPtW/f3noVvZ9//rnAK7tdvXqVOXPmACo3uXvX9OzZ09pD7IcffihwP6Kjo/njjz+szylqbqzAwEDWrVtHw4YNyc7OZsyYMSxevLjQ5xSmJEP8ck+4XVghzJaoqChGjx7NtWvXqFmzJosWLcLT07PI5w0cOBAXFxcAPv/88zK7gp0QQgjhKFJgEkIIIUSZa9CggfWy8ikpKfTp06fQnkRz5sxh4sSJgJqDZubMmbfUc8SiU6dOtGvXDoBvv/2WzZs351vnwoULvPTSS4Vu5/HHH8fPzw+A//znP6xYsaLQ9bds2cLGjRtvca/LntlsznMFtkGDBuV53M3NzXqltEOHDvHWW2/l24amaTz99NMkJCQAWHvmWAQEBDBixAhAXW3vxx9/zLeNrKwsHnzwQWsPqpu3UZCgoCDWr19P/fr1uXbtGmFhYdYiZEl9//33PProo0UWO8+cOcO///1v6++hoaHFjpGcnMzQoUO5dOkSbm5uRERE5CvqFSQwMJB//OMfAOzbt4/HHnus0CJTXFycdTJyIYQQojyQOZiEEEIIYRfPPvssJ0+e5L///S/R0dF06NCB8ePHM2zYMOrVq8e1a9eIjIzk999/Z+3atYAqLv3yyy/W4lBpfPPNN3Tr1o1r167Rt29fXnjhBQYNGoSbmxvbtm3j/fffJyEhgdatWxdY/PL29iY8PJyBAweSmZnJkCFDGDVqFKNGjSI4OBhQhapdu3axcOFC9u/fz1dffUX37t1Lvf/FFRMTw8GDB/Pcl5qayuHDh/n+++/ZunUroOb4yV1ssnjjjTdYsGABJ0+e5J133uHgwYM8+OCDBAQEcOrUKb7++ms2bNgAQJcuXWxe1e3zzz9n7dq1JCYm8vDDD7NlyxbGjRuHr68vkZGRfPLJJ9ahiGPGjGHgwIHFPr66deuyYcMGevTowZkzZxg1ahQREREMGDCg2NsAVeT6/vvv+f7777nrrrvo378/7du3p2bNmjg5ORETE8P69euZPn06V69eBVQPtj59+hQ7xtNPP82RI0cAeP755/Hy8sqXm9z8/f3x9/e3/v7pp5/y119/cfDgQX788Uf+/vtvHn30Udq3b4+XlxdXrlzh0KFDrFmzhuXLl9OqVStrgVAIIYTQnSaEEEIIYUfffvut5uvrqwGFLk2bNtU2bNhQ6LZ69OihAVqPHj2KFfv333/XXF1dbcZzdnbWvv/+e23ixIkaoNWrV6/A7axdu1arVatWkccAaD///HO+51see/PNN4u130WZMWNGsfbFsjRo0EDbtWtXgds7deqU1rRp00K30bVrV+3SpUsFbmP37t1aQEBAodsYOXKklp6ebvP5ReX25MmTWlBQkAZo7u7u2urVq0v0ms2ePbvA94Kt5d5779XS0tJsvlaWdWbMmGHzGIq72Ho/XLp0SRswYECxnt+rV68SvQZCCCGEPUkPJiGEEELY1eOPP864ceP49ddfWbZsGYcOHSI+Ph5nZ2dq1qxJx44dCQ0NZfTo0UXOy1NS48ePp3Xr1kyZMoW1a9eSkJBAjRo16Nq1Ky+++CKdO3e2OXzuZr179yYqKooZM2awdOlS9u3bx6VLl3BycqJGjRo0a9aMHj16MGrUKJo0aVKmx3Ar3N3d8fPzo3Xr1gwbNowJEyYUOg9Q/fr12bdvH99//z1z587l4MGDJCcn4+vrS9u2bbnvvvu49957Cx222LZtW44ePcrXX39NREQER48eJS0tDT8/P+68804mTZrE0KFDb/mYGjRowPr16+nZsyfnzp0jNDSUpUuX0rt372I9f8yYMfTv35/Vq1fz559/snv3bk6ePGmdg8vb25tGjRrRpUsX7rvvPtq3b3/L+1oavr6+rFixgnXr1vHrr7+yefNmLly4QEZGBt7e3gQHB9OpUycGDx5Mv379dNlHIYQQwhaTppVgxkMhhBBCCCGEEEIIIW4ik3wLIYQQQgghhBBCiFKRApMQQgghhBBCCCGEKBUpMAkhhBBCCCGEEEKIUpECkxBCCCGEEEIIIYQoFSkwCSGEEEIIIYQQQohSkQKTEEIIIYQQQgghhCgVKTAJIYQQQgghhBBCiFKRApMQQgghhBBCCCGEKBUpMAkhhBBCCCGEEEKIUpECkxBCCCGEEEIIIYQoFSkwCSGEEEIIIYQQQohSkQKTEEIIIYQQQgghhCgVKTAJIYQQQgghhBBCiFKRApMQQgghhBBCCCGEKBUpMAkhhBBCCCGEEEKIUvl/sS1ea9OnqwgAAAAASUVORK5CYII=",
-      "text/plain": [
-       "<Figure size 1300x900 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(13, 9))\n",
-    "plt.plot(orders_list, OCC_list_avg_HTGR, linestyle='-', marker='o', markersize=8, label= \"Reactor Concept A Average OCC\", color='red') \n",
-    "plt.plot(orders_list, TCI_list_avg_HTGR, linestyle='dashed', marker='o', markersize=8, label= \"Reactor Concept A Average NCI\", color='red')\n",
-    "\n",
-    "plt.plot(orders_list, OCC_list_avg_SFR, linestyle='-', marker='o', markersize=8, label='Reactor Concept B Average OCC', color='blue') \n",
-    "plt.plot(orders_list, TCI_list_avg_SFR, linestyle='dashed', marker='o', markersize=8, label='Reactor Concept B Average NCI', color= 'blue') \n",
-    "\n",
-    "#     # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "   \n",
-    "\n",
-    "\n",
-    "\n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "\n",
-    "plt.xlabel('Order Book Size', fontsize='20') # x-axis name\n",
-    "plt.ylabel('2022$/kWe', fontsize='20') # x-axis name\n",
-    "\n",
-    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
-    "plt.legend(loc='upper right', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(4, 20)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('orders.png')\n",
-    "plt.show() # Display the graph\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "8166d518",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[10129.426593668872,\n",
-       " 9054.364356093398,\n",
-       " 8293.675152027796,\n",
-       " 7719.580972658651,\n",
-       " 7267.1199076171115,\n",
-       " 6899.225446983411,\n",
-       " 6591.9060804843875,\n",
-       " 6331.086579065694,\n",
-       " 6105.572949904573,\n",
-       " 5908.11333540093,\n",
-       " 5733.391929705431,\n",
-       " 5577.767270570705,\n",
-       " 5437.851550664015,\n",
-       " 5311.1761056860005,\n",
-       " 5195.36334164328,\n",
-       " 5089.343188912801,\n",
-       " 4991.797561198853]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "TCI_list_avg_HTGR"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "f15a1174",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[9410.208845406803,\n",
-       " 8460.973294090489,\n",
-       " 7798.467989648133,\n",
-       " 7303.202162132135,\n",
-       " 6918.1355596638405,\n",
-       " 6607.075484293743,\n",
-       " 6349.302890667079,\n",
-       " 6131.373466375377,\n",
-       " 5943.1499192554,\n",
-       " 5779.3016910071765,\n",
-       " 5634.981155045442,\n",
-       " 5506.007888292734,\n",
-       " 5390.295118126247,\n",
-       " 5285.307360763239,\n",
-       " 5189.854956275479,\n",
-       " 5102.235827688789,\n",
-       " 5021.422116119418]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "TCI_list_avg_SFR"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b46eadd8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "startup_0 = 16\n",
-    "num_orders = 12\n",
-    "design_completion_0 = 0.8\n",
-    "Design_Maturity_0 = 1\n",
-    "proc_exp_0 = 0.5\n",
-    "ae_exp_0 = 0.5\n",
-    "ce_exp_0 = 1\n",
-    "\n",
-    "mod_0 = 'stick_built'\n",
-    "standardization_0 = 0.8\n",
-    "BOP_grade_0 = 'non_nuclear'\n",
-    "ITC_0 = 0\n",
-    "n_ITC = 0\n",
-    "RB_grade_0 = 'nuclear'\n",
-    "\n",
-    "for reactor_type in reactor_type_list:\n",
-    "    TCI_list_avg = []\n",
-    "    OCC_list_avg = []\n",
-    "    interest_list = []\n",
-    "    print(reactor_type)\n",
-    "    for interest_rate_0 in [x / 100.0 for x in range(3, 13)]:\n",
-    "        \n",
-    "        OCC_list = []\n",
-    "        TCI_list = []  \n",
-    "        for n_th in range(1, num_orders+1):\n",
-    "            results = calculate(num_orders ,n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type ) \n",
-    "            OCC_result = results[0]\n",
-    "            TCI_result = results[1]\n",
-    "            \n",
-    "            OCC_list.append(OCC_result)\n",
-    "            TCI_list.append( TCI_result )\n",
-    "            \n",
-    "        avg_TCI = np.mean(TCI_list)\n",
-    "        avg_OCC = np.mean(OCC_list)\n",
-    "        \n",
-    "        TCI_list_avg.append(avg_TCI)\n",
-    "        OCC_list_avg.append(avg_OCC)\n",
-    "        interest_list.append(interest_rate_0)\n",
-    "        \n",
-    "        \n",
-    "    if reactor_type == \"SFR\":\n",
-    "        OCC_list_avg_SFR = OCC_list_avg\n",
-    "        TCI_list_avg_SFR =  TCI_list_avg\n",
-    "    elif reactor_type == \"HTGR\":\n",
-    "        OCC_list_avg_HTGR = OCC_list_avg\n",
-    "        TCI_list_avg_HTGR =  TCI_list_avg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "49ac27d0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(13, 9))\n",
-    "plt.plot(interest_list, TCI_list_avg_HTGR, linestyle='dashed', marker='o', markersize=8, label= \"Reactor Concept A\", color='red')\n",
-    "\n",
-    "plt.plot(interest_list, TCI_list_avg_SFR, linestyle='dashed', marker='o', markersize=8, label='Reactor Concept B', color= 'blue') \n",
-    "\n",
-    "# #     # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "   \n",
-    "\n",
-    "\n",
-    "\n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "\n",
-    "plt.xlabel('Interest Rate (%)', fontsize='20') # x-axis name\n",
-    "plt.ylabel('Average NCI (2022$/kWe)', fontsize='20') # x-axis name\n",
-    "\n",
-    "plt.legend(loc='upper left', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(0.03, 0.12)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('orders.png')\n",
-    "plt.show() # Display the graph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "979af689",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "startup_0 = 16\n",
-    "num_orders = 12\n",
-    "design_completion_0 = 0.8\n",
-    "Design_Maturity_0 = 1\n",
-    "\n",
-    "interest_rate_0 = 0.06\n",
-    "\n",
-    "mod_0 = 'stick_built'\n",
-    "standardization_0 = 0.8\n",
-    "BOP_grade_0 = 'non_nuclear'\n",
-    "ITC_0 = 0\n",
-    "n_ITC = 0\n",
-    "RB_grade_0 = 'nuclear'\n",
-    "\n",
-    "\n",
-    "EPC_list = ['very low', 'low', 'medium', 'high', 'very high']\n",
-    "\n",
-    "for reactor_type in reactor_type_list:\n",
-    "    print('\\n' ,reactor_type)\n",
-    "    TCI_list_avg = []\n",
-    "    OCC_list_avg = []\n",
-    "    \n",
-    "    \n",
-    "    for epc_exp in EPC_list:\n",
-    "        print( epc_exp )\n",
-    "        OCC_list = []\n",
-    "        TCI_list = [] \n",
-    "        \n",
-    "        if epc_exp == \"very low\":\n",
-    "            proc_exp_0 = 0\n",
-    "            ae_exp_0 = 0\n",
-    "            ce_exp_0 = 0\n",
-    "\n",
-    "        elif epc_exp == \"low\":\n",
-    "            proc_exp_0 = 0\n",
-    "            ae_exp_0 = 0\n",
-    "            ce_exp_0 = 1 \n",
-    "\n",
-    "        elif epc_exp == \"medium\":\n",
-    "            proc_exp_0 = 1\n",
-    "            ae_exp_0 = 1\n",
-    "            ce_exp_0 = 1  \n",
-    "\n",
-    "        elif epc_exp == \"high\":\n",
-    "            proc_exp_0 = 1\n",
-    "            ae_exp_0 = 1\n",
-    "            ce_exp_0 = 2   \n",
-    "\n",
-    "        elif epc_exp == \"very high\":\n",
-    "            proc_exp_0 = 2\n",
-    "            ae_exp_0 = 2\n",
-    "            ce_exp_0 = 2            \n",
-    "             \n",
-    "        for n_th in range(1, num_orders+1):\n",
-    "            results = calculate(num_orders ,n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type ) \n",
-    "            OCC_result = results[0]\n",
-    "            TCI_result = results[1]\n",
-    "            \n",
-    "            OCC_list.append(OCC_result)\n",
-    "            TCI_list.append( TCI_result )\n",
-    "            \n",
-    "        avg_TCI = np.mean(TCI_list)\n",
-    "        avg_OCC = np.mean(OCC_list)\n",
-    "        \n",
-    "        TCI_list_avg.append(avg_TCI)\n",
-    "        OCC_list_avg.append(avg_OCC)\n",
-    "        \n",
-    "        \n",
-    "    if reactor_type == \"SFR\":\n",
-    "        OCC_list_avg_SFR = OCC_list_avg\n",
-    "        TCI_list_avg_SFR =  TCI_list_avg\n",
-    "    elif reactor_type == \"HTGR\":\n",
-    "        OCC_list_avg_HTGR = OCC_list_avg\n",
-    "        TCI_list_avg_HTGR =  TCI_list_avg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2dd233d5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "xx = np.arange(5) \n",
-    "plt.bar(xx + 0.3 , TCI_list_avg_HTGR,0.3, color = 'red')\n",
-    "plt.bar( xx , TCI_list_avg_SFR ,0.3, color = 'blue')\n",
-    "\n",
-    "plt.xlabel('\\n EPC Proficiency', fontsize='25') # x-axis name\n",
-    "plt.ylabel('Average NCI (2022$/kWe) \\n', fontsize='25') # x-axis name\n",
-    "\n",
-    "plt.xticks(xx, ['Very Low', 'Low', 'Medium', 'High', 'Very High'])\n",
-    "\n",
-    "plt.grid(which='major', linewidth=0.8, axis='y')\n",
-    "plt.grid(which='minor', linestyle='dashed',axis='y', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "plt.ylim(0, 8000)\n",
-    "plt.tick_params(labelsize=25)\n",
-    "plt.legend([\"Reactor Concept A\" , \"Reactor Concept B\"], loc='upper right', fontsize='25')\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "xx = np.arange(5) \n",
-    "plt.bar(xx + 0.3 , OCC_list_avg_HTGR,0.3, color = 'red')\n",
-    "plt.bar( xx , OCC_list_avg_SFR ,0.3, color = 'blue')\n",
-    "\n",
-    "plt.xlabel('\\n EPC Proficiency', fontsize='25') # x-axis name\n",
-    "plt.ylabel('Average OCC (2022$/kWe) \\n', fontsize='25') # x-axis name\n",
-    "\n",
-    "plt.xticks(xx, ['Very Low', 'Low', 'Medium', 'High', 'Very High'])\n",
-    "\n",
-    "plt.grid(which='major', linewidth=0.8, axis='y')\n",
-    "plt.grid(which='minor', linestyle='dashed',axis='y', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "plt.ylim(0, 6200)\n",
-    "plt.tick_params(labelsize=25)\n",
-    "plt.legend([\"Reactor Concept A\" , \"Reactor Concept B\"], loc='upper right', fontsize='25')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "21e5ad85",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "startup_0 = 16\n",
-    "ITC_0 = 0\n",
-    "n_ITC = 0\n",
-    "interest_rate_0 = 0.06\n",
-    "\n",
-    "for reactor_type in reactor_type_list:\n",
-    "    \n",
-    "    print( \"reactor type : \",reactor_type)\n",
-    "    \n",
-    "    avg_duration_list = []\n",
-    "    TCI_list_avg = []\n",
-    "    OCC_list_avg = []\n",
-    "    \n",
-    "    for num_orders in [5, 10]: \n",
-    "        print('number of orders = ',num_orders)\n",
-    "        for design_completion_0 in [0.5, 1]: \n",
-    "            for Design_Maturity_0  in [0, 2 ]: \n",
-    "                for proc_exp_0 in [0, 2 ]:\n",
-    "                    for ae_exp_0 in [0, 2 ]: \n",
-    "                        for ce_exp_0 in [0, 2]: \n",
-    "                            for  mod_0 in [\"stick_built\", \"modularized\"]:\n",
-    "                                for standardization_0 in [0.7, 0.95]: \n",
-    "                                    for BOP_grade_0 in [ \"nuclear\", 'non_nuclear' ]: \n",
-    "                                        for RB_grade_0 in [  \"nuc lear\" , 'non_nuclear']: # \n",
-    "                                            \n",
-    "                                            dur_list = []\n",
-    "                                            TCI_list = []\n",
-    "                                            OCC_list = []\n",
-    "                                            \n",
-    "                                            for n_th in range(1, num_orders+1):\n",
-    "                                                results = calculate(num_orders ,n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type )\n",
-    "                                                OCC_result = results[0]\n",
-    "                                                TCI_result = results[1]\n",
-    "                                                cons_dur  = results[2]\n",
-    "                                                \n",
-    "                                                OCC_list.append(OCC_result)\n",
-    "                                                TCI_list.append( TCI_result )\n",
-    "                                                dur_list.append(cons_dur )\n",
-    "                                                \n",
-    "                                            avg_duration = np.mean(dur_list)\n",
-    "                                            avg_TCI = np.mean(TCI_list)\n",
-    "                                            avg_OCC = np.mean(OCC_list)  \n",
-    "                                            \n",
-    "                                            avg_duration_list.append(avg_duration) \n",
-    "                                            TCI_list_avg.append(avg_TCI)\n",
-    "                                            OCC_list_avg.append(avg_OCC)\n",
-    "                                            \n",
-    "    if reactor_type == \"SFR\":\n",
-    "        avg_duration_list_SFR = avg_duration_list\n",
-    "        OCC_list_avg_SFR = OCC_list_avg\n",
-    "        TCI_list_avg_SFR =  TCI_list_avg\n",
-    "    \n",
-    "    elif reactor_type == \"HTGR\":\n",
-    "        avg_duration_list_HTGR = avg_duration_list   \n",
-    "        OCC_list_avg_HTGR      = OCC_list_avg\n",
-    "        TCI_list_avg_HTGR      =  TCI_list_avg                                   "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "54d00ef3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "plt.scatter(avg_duration_list_HTGR, OCC_list_avg_HTGR, label= \"Reactor Concept A\", color='red')\n",
-    "   \n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "plt.xlabel('Average Construction Duration (months)', fontsize='20') # x-axis name\n",
-    "plt.ylabel('Average OCC (2022$/kWe)', fontsize='20') # x-axis name\n",
-    "\n",
-    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
-    "plt.legend(loc='upper left', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(60, 110)\n",
-    "plt.ylim(3000, 12000)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('OCC_construction_HTGR.png')\n",
-    "plt.show() # Display the graph\n",
-    "\n",
-    "\n",
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "plt.scatter(avg_duration_list_HTGR, TCI_list_avg_HTGR, label= \"Reactor Concept A\", color='red')\n",
-    "   \n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "plt.xlabel('Average Construction Duration (months)', fontsize='20') # x-axis name\n",
-    "plt.ylabel('Average NCI (2022$/kWe)', fontsize='20') # x-axis name\n",
-    "\n",
-    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
-    "plt.legend(loc='upper left', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(60, 110)\n",
-    "plt.ylim(4000, 17000)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('TCI_construction_HTGR.png')\n",
-    "plt.show() # Display the graph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f8bbaa32",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "plt.scatter(avg_duration_list_SFR, OCC_list_avg_SFR, label= \"Reactor Concept B\", color='blue')\n",
-    "   \n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "plt.xlabel('Average Construction Duration (months)', fontsize='20') # x-axis name\n",
-    "plt.ylabel('Average OCC (2022$/kWe)', fontsize='20') # x-axis name\n",
-    "\n",
-    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
-    "plt.legend(loc='upper left', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(38, 75)\n",
-    "plt.ylim(4000, 11500)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('OCC_construction_SFR.png')\n",
-    "plt.show() # Display the graph\n",
-    "\n",
-    "\n",
-    "plt.figure(figsize=(13, 9))\n",
-    "\n",
-    "plt.scatter(avg_duration_list_SFR, TCI_list_avg_SFR, label= \"Reactor Concept B\", color='blue')\n",
-    "   \n",
-    "plt.legend()    # g.set_xticks(range(1,22,2))\n",
-    "\n",
-    "plt.xlabel('Average Construction Duration (months)', fontsize='20') # x-axis name\n",
-    "plt.ylabel('Average NCI (2022$/kWe)', fontsize='20') # x-axis name\n",
-    "\n",
-    "# # plt.ylabel('Order BookAveraged TCI (2022$/kWe)', fontsize='25') # x-axis name\n",
-    "plt.legend(loc='upper left', fontsize='20') # Add a legend\n",
-    "plt.tick_params(labelsize=20)\n",
-    "plt.xlim(38, 75)\n",
-    "plt.ylim(4500, 15000)\n",
-    "\n",
-    "plt.grid(which='major', color='grey', linewidth=0.8)\n",
-    "plt.grid(which='minor', color='grey', linestyle='dashed', linewidth=0.5)\n",
-    "plt.minorticks_on()\n",
-    "\n",
-    "plt.savefig('TCI_construction_HTGR.png')\n",
-    "plt.show() # Display the graph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "2edc4386",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "SFR\n",
-      "best\n",
-      "# Orders\n",
-      "Design Completion\n",
-      "A/E Proficiency\n",
-      "Construction Proficiency\n",
-      "Supply Chain Proficiency\n",
-      "Design Maturity\n",
-      "Standardization\n",
-      "Modularization\n",
-      "Commercial BOP\n",
-      "Safety-Related RB\n",
-      "ITC\n",
-      "Interest Rate\n",
-      "HTGR\n",
-      "best\n",
-      "# Orders\n",
-      "Design Completion\n",
-      "A/E Proficiency\n",
-      "Construction Proficiency\n",
-      "Supply Chain Proficiency\n",
-      "Design Maturity\n",
-      "Standardization\n",
-      "Modularization\n",
-      "Commercial BOP\n",
-      "Safety-Related RB\n",
-      "ITC\n",
-      "Interest Rate\n"
-     ]
-    }
-   ],
-   "source": [
-    "\n",
-    "scenarios_list = [\"best\", \"# Orders\",  \"Design Completion\", \"A/E Proficiency\", \"Construction Proficiency\",\\\n",
-    "        \"Supply Chain Proficiency\", \"Design Maturity\", \"Standardization\", \"Modularization\",\\\n",
-    "        \"Commercial BOP\", \"Safety-Related RB\", \"ITC\", \"Interest Rate\"]\n",
-    "\n",
-    "for reactor_type in reactor_type_list:\n",
-    "    print(reactor_type)\n",
-    "    \n",
-    "    TCI_list_avg = []\n",
-    "    \n",
-    "    for scenario in scenarios_list:\n",
-    "        print(scenario)\n",
-    "        \n",
-    "        if scenario == '# Orders':\n",
-    "            num_orders = 2\n",
-    "        else:   \n",
-    "            num_orders = 20 \n",
-    "        \n",
-    "        if scenario == \"Startup Duration\":\n",
-    "                startup_0 = 36 # start up duration (months)\n",
-    "        else:\n",
-    "                startup_0 = 12\n",
-    "        # land cost\n",
-    "            # From the SA report: the cost $22,000 per acre. The land area is 500 acres including recommended buffer\n",
-    "        if scenario == \"Land Cost\":\n",
-    "                land_cost_per_acre_0 =  100000 # d\n",
-    "        else:  \n",
-    "                land_cost_per_acre_0 =  1000 # dollars/acre   \n",
-    "  \n",
-    "\n",
-    "        # # interest rate :\n",
-    "        if scenario == \"Interest Rate\":\n",
-    "            interest_rate_0 = 0.12\n",
-    "        else:    \n",
-    "            interest_rate_0 = 0.04\n",
-    "\n",
-    "        if scenario == \"Design Completion\":\n",
-    "            design_completion_0 = 0.5 # 1 means 100%\n",
-    "        else: \n",
-    "            design_completion_0 = 1# 1 means 100%\n",
-    "        \n",
-    "        if scenario == \"Design Maturity\":\n",
-    "            Design_Maturity_0 = 0\n",
-    "        else:   \n",
-    "                Design_Maturity_0 = 2\n",
-    "                 \n",
-    "                 \n",
-    "                 \n",
-    "                 \n",
-    "                 # #procurement service experience (supply chain experience)\n",
-    "        \n",
-    "        \n",
-    "        if scenario == \"Supply Chain Proficiency\":\n",
-    "            proc_exp_0= 0 # 2 means procurement experts. This is ideal. \n",
-    "        else:\n",
-    "            proc_exp_0= 2\n",
-    "                \n",
-    "        # #  architecture and engineeringexperience\n",
-    "        if scenario == \"A/E Proficiency\":\n",
-    "            ae_exp_0 = 0\n",
-    "        else:    \n",
-    "            ae_exp_0 = 2\n",
-    "                \n",
-    "                \n",
-    "        if scenario == \"Construction Proficiency\":\n",
-    "        # #  Construction service experience\n",
-    "            ce_exp_0 = 0\n",
-    "        else:   \n",
-    "            ce_exp_0 = 2\n",
-    "\n",
-    "        if scenario == \"Modularization\":\n",
-    "        # modularity (applied on civil construction only) \"stick_built\"  or \"modularized\"\n",
-    "            mod_0 = \"stick_built\" \n",
-    "        else:  \n",
-    "            mod_0 = \"modularized\"\n",
-    "\n",
-    "        \n",
-    "        if scenario == \"Standardization\":\n",
-    "        # cross_site_standardization :\n",
-    "            standardization_0 = 0.7 # 0.7 corresponds to 70% standardization for PWRs\n",
-    "        else:\n",
-    "            standardization_0 = 0.95\n",
-    "        \n",
-    "            \n",
-    "        if scenario == \"Commercial BOP\":\n",
-    "        # # Determining if the BOP and reactor building (containtment) are non-nuclear or nuclear grade equipment (safety related)\n",
-    "            BOP_grade_0 = \"nuclear\"\n",
-    "        else:    \n",
-    "            BOP_grade_0 = \"non_nuclear\"\n",
-    "        \n",
-    "        \n",
-    "        if scenario == \"Safety-Related RB\":\n",
-    "            RB_grade_0 = \"nuclear\"\n",
-    "        else:    \n",
-    "                RB_grade_0 = \"non_nuclear\"\n",
-    "\n",
-    "\n",
-    "        if scenario == \"ITC\":\n",
-    "        # #investment tax credits subsidies\n",
-    "            ITC_0 =  0 #\n",
-    "            \n",
-    "            #number of reactors claiming ITC\n",
-    "            n_ITC = 3 \n",
-    "        else:  \n",
-    "            ITC_0 =  0.4 #\n",
-    "            n_ITC = 3\n",
-    "        \n",
-    "        TCI_list = [] \n",
-    "        for n_th in range(1, num_orders+1):\n",
-    "            results = calculate(num_orders ,n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type )\n",
-    "            \n",
-    "            TCI_result = results[1]\n",
-    "            TCI_list.append( TCI_result )\n",
-    "        avg_TCI = np.mean(TCI_list)\n",
-    "        \n",
-    "        TCI_list_avg.append(avg_TCI)\n",
-    "\n",
-    "    if reactor_type == \"SFR\":\n",
-    "        TCI_list_avg_SFR =  TCI_list_avg\n",
-    "    \n",
-    "    elif reactor_type == \"HTGR\":\n",
-    "        TCI_list_avg_HTGR      =  TCI_list_avg "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "id": "44f9773d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([['# Orders', 'Design Completion', 'A/E Proficiency',\n",
-       "        'Construction Proficiency', 'Supply Chain Proficiency',\n",
-       "        'Design Maturity', 'Standardization', 'Modularization',\n",
-       "        'Commercial BOP', 'Safety-Related RB', 'ITC', 'Interest Rate'],\n",
-       "       ['1348.7450431344796', '74.02039526858653', '130.9965193438593',\n",
-       "        '358.5831930659415', '13.531457947480703', '17.675555463713863',\n",
-       "        '638.6067166148432', '33.91727388325489', '150.33046271782314',\n",
-       "        '156.5078298991284', '258.9981143750297', '781.6795212483339'],\n",
-       "       ['903.0470363771133', '72.32958748945157', '120.40665744737998',\n",
-       "        '284.29905480954994', '12.963416976577719', '16.69519640982253',\n",
-       "        '433.8167368872532', '19.961834590577837', '159.03979159395112',\n",
-       "        '13.864902749768135', '269.07468026091146', '543.0183896110916']],\n",
-       "      dtype='<U32')"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#non-best scenarios\n",
-    "non_best_scenarios = scenarios_list[1:]\n",
-    "non_best_TCI_list_avg_HTGR = TCI_list_avg_HTGR[1:] - TCI_list_avg_HTGR[0]\n",
-    "non_best_TCI_list_avg_SFR = non_best_TCI_list_avg_SFR = TCI_list_avg_SFR [1:] - TCI_list_avg_SFR[0]\n",
-    "\n",
-    "sc_array = np.row_stack((non_best_scenarios, non_best_TCI_list_avg_HTGR, non_best_TCI_list_avg_SFR))\n",
-    "sc_array\n",
-    "# barWidth = 0.25\n",
-    "# fig = plt.subplots(figsize =(12, 8)) \n",
-    " \n",
-    "# # set height of bar \n",
-    "\n",
-    " \n",
-    "# # Set position of bar on X axis \n",
-    "# br1 = np.arange(len(TCI_list_avg_HTGR)) \n",
-    "# br2 = [x + barWidth for x in br1] \n",
-    " \n",
-    "# # Make the plot\n",
-    "# plt.bar(br1, TCI_list_avg_HTGR, color ='r', width = barWidth, \n",
-    "#         edgecolor ='grey', label ='Concept A') \n",
-    "# plt.bar(br2, TCI_list_avg_SFR, color ='g', width = barWidth, \n",
-    "#         edgecolor ='grey', label ='Concept B') \n",
-    "\n",
-    "# plt.xticks([r + barWidth for r in range(len(TCI_list_avg_HTGR))], \n",
-    "#         scenarios_list)\n",
-    "\n",
-    "# plt.legend()\n",
-    "# plt.show() \n",
-    "# # plt.bar(br3, CSE, color ='b', width = barWidth, \n",
-    "# #         edgecolor ='grey', label ='CSE')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "bc48b0a7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import csv\n",
-    "with open('var-impact.csv', 'a', newline='') as myfile:\n",
-    "     wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)\n",
-    "     wr.writerow(non_best_scenarios)\n",
-    "     wr.writerow(non_best_TCI_list_avg_HTGR)\n",
-    "\n",
-    "     wr.writerow(non_best_scenarios)\n",
-    "     wr.writerow(non_best_TCI_list_avg_SFR)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "5e8005ce",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results = calculate(num_orders , n_th, startup_0, interest_rate_0, design_completion_0, Design_Maturity_0, proc_exp_0 , ae_exp_0, ce_exp_0, mod_0 , standardization_0, BOP_grade_0, RB_grade_0, ITC_0, n_ITC, reactor_type )\n",
-    "res_list = []\n",
-    "for n in range(1, 20):\n",
-    "    results = calculate(20 ,n, 16, 0.04, 1, 2,2 , 2, 2,'modularized' , 0.95, 'non_nuclear', 'non_nuclear', 0, 0, 'SFR' )\n",
-    "    res_list.append(results[1])\n",
-    "    \n",
-    "# results = calculate(20 ,n, 16, 0.04, 1, 2,2 , 2, 2,'modularized' , 0.95, 'non_nuclear', 'non_nuclear', 0, 0, 'SFR' )\n",
-    "# results[1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "e56ce2a0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "4090.825562224371"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.mean(res_list)"
-   ]
-  }
- ],
- "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": "3.1.undefined"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/Cost_Reduction/src.py b/Cost_Reduction/src.py
index 36d3215..7e3b00f 100644
--- a/Cost_Reduction/src.py
+++ b/Cost_Reduction/src.py
@@ -1,7 +1,9 @@
 # Importing libararies
+import os
 import pandas as pd
 import numpy as np
-
+import scipy.stats as stats; 
+import threading
 
 import warnings
 warnings.simplefilter(action='ignore', category=FutureWarning)
@@ -156,4 +158,210 @@ def update_high_level_costs(db, reactor_power):
 def ITC_reduction_factor(itc_level):
     itc_values = [0, 0.06, 0.3, 0.4, 0.5]
     ITC_reduction_factor = [1, 0.95,	0.73,	0.63,	0.53 ]
-    return np.interp(itc_level, itc_values, ITC_reduction_factor)
\ No newline at end of file
+    return np.interp(itc_level, itc_values, ITC_reduction_factor)
+
+
+
+
+# A function to update the construction duration when the labor hours change
+def update_cons_duration(db0, db1, ref_duration):
+    # sum old hours
+    #sum of labor hours for Account 20 in the initial estimation (well exectued scenario)
+    sum_old_lab_hrs = (db0.loc[db0.Account == 21, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 22, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 23, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 24, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 26, 'Site Labor Hours']).values
+    
+    
+    sum_new_lab_hrs = (db1.loc[db1.Account == 21, 'Site Labor Hours']).values +\
+    (db1.loc[db1.Account == 22, 'Site Labor Hours']).values +\
+    (db1.loc[db1.Account == 23, 'Site Labor Hours']).values+\
+    (db1.loc[db1.Account == 24, 'Site Labor Hours']).values+\
+    (db1.loc[db1.Account == 26, 'Site Labor Hours']).values
+    
+    lab_hrs_delta = (sum_new_lab_hrs - sum_old_lab_hrs) / sum_old_lab_hrs
+    new_duration = 0.3 * lab_hrs_delta* ref_duration + ref_duration
+    return new_duration
+
+
+def sum_lab_hrs(db0):
+    # sum old hours
+    #sum of labor hours for Account 20 in the initial estimation (well exectued scenario)
+    sum_lab_hrs = (db0.loc[db0.Account == 21, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 22, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 23, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 24, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 26, 'Site Labor Hours']).values
+    
+    
+    return sum_lab_hrs
+
+def update_cons_duration_2(db0, db1, ref_duration, prev_cons_duration, baseline_lab_hours):
+    
+    # sum old hours
+    #sum of labor hours for Account 20 in the initial estimation (well exectued scenario)
+    sum_old_lab_hrs = (db0.loc[db0.Account == 21, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 22, 'Site Labor Hours']).values +\
+    (db0.loc[db0.Account == 23, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 24, 'Site Labor Hours']).values+\
+    (db0.loc[db0.Account == 26, 'Site Labor Hours']).values
+    
+    sum_new_lab_hrs = (db1.loc[db1.Account == 21, 'Site Labor Hours']).values +\
+    (db1.loc[db1.Account == 22, 'Site Labor Hours']).values +\
+    (db1.loc[db1.Account == 23, 'Site Labor Hours']).values+\
+    (db1.loc[db1.Account == 24, 'Site Labor Hours']).values+\
+    (db1.loc[db1.Account == 26, 'Site Labor Hours']).values
+    
+    lab_hrs_delta = (sum_new_lab_hrs -sum_old_lab_hrs ) / baseline_lab_hours
+    
+    return 0.3*lab_hrs_delta *ref_duration + prev_cons_duration
+    
+    
+    
+    
+
+# Arguments within the function
+
+# n_Samples_df, all_var_df ::  'n_Samples_df' contains number of scenarios to be sampled and simulated, 
+#                              'all_var_df' provided from the Excel sheet contains name, distribution types for  
+#                               multiple inputs to be sampled/varied
+
+def sampler(n_Samples, all_var_df): #  min_, max_, mean, stds
+  #  
+  # Reading number of samples requested
+  #    
+#   n_Samples     = n_Samples_df.iloc[0, 0]
+  #  
+  # Intitialize number of levers and sample-storing array
+  #
+  n_var          = all_var_df.shape[0]   # all_var_df.shape[0] provides of number of variables to be randomized
+  random_samples = np.empty((n_var, n_Samples))    # random sample-storing array
+  #  
+  # Extract information regarding distributions
+  #
+  dist_type = all_var_df['Distribution'];    min_ = all_var_df['Min'];     max_   = all_var_df['Max'];     med_ = all_var_df['Median']
+  low_ = all_var_df['Low'];                 high_ = all_var_df['High'];    Set_   = all_var_df['Set'];     Probabilities_ = all_var_df['Probabilities']
+  Type = all_var_df['Type'];
+  #  
+  # Intitialize random sample-storing array
+  #
+  for iter in range(n_var):
+    # print(iter)
+    #  
+    # Normal Distribution Sampler: Discrete and Continuous
+    #
+    if dist_type[iter] in ['normal', 'Normal', 'Gaussian', 'gaussian']:
+      random_samples[iter, :]  = trunc_normal(min_[iter], low_[iter], med_[iter], high_[iter], max_[iter], n_Samples)
+      if Type[iter] in ['discrete', 'Discrete', 'Integer', 'integer']:
+          random_samples[iter, :] = np.round(random_samples[iter, :])
+    #  
+    # Lognormal Distribution Sampler: Discrete and Continuous
+    #
+    elif dist_type[iter] in ['lognormal', 'LogNormal', 'Lognormal']:
+      random_samples[iter, :] = truncate_shift_lognormal(min_[iter], low_[iter], med_[iter],  high_[iter], max_[iter], n_Samples)
+      if Type[iter] in ['discrete', 'Discrete', 'Integer', 'integer']:
+          random_samples[iter, :] = np.round(random_samples[iter, :])
+    #  
+    # Triangular Distribution Sampler: Discrete and Continuous
+    #
+    elif dist_type[iter] in ['triangular', 'Triangular']:
+      random_samples[iter, :] = np.random.triangular(left=min_[iter], mode=med_[iter], right=max_[iter], size=n_Samples)
+      if Type[iter] in ['discrete', 'Discrete', 'Integer', 'integer']:
+          random_samples[iter, :] = np.round(random_samples[iter, :])
+    #  
+    # Uniform Distribution Sampler: Discrete and Continuous
+    #
+    elif dist_type[iter] in ['uniform', 'Uniform']:
+      random_samples[iter, :] = np.random.uniform(left=min_[iter], right=max_[iter], size=n_Samples)
+      if Type[iter] in ['discrete', 'Discrete', 'Integer', 'integer']:
+          random_samples[iter, :] = np.round(random_samples[iter, :])
+    #  
+    # Binary/Boolean/Discrete-Set Distribution Sampler
+    #
+    elif dist_type[iter] in ['binary', 'Binary', 'Boolean', 'boolean', 'set', 'Set']:
+      random_samples[iter, :] = np.random.choice(eval('['+Set_[iter]+']'), size = n_Samples, p = eval('['+Probabilities_[iter]+']'))
+    else:
+      raise ValueError("Enter valid distribution type. Invalid entry: {}".format(dist_type[i]))
+
+  return random_samples
+
+
+# Truncated Normal
+def trunc_normal(min_, low_, med_, high_, max_, n_Samples):
+    #
+    # 'low_' and 'high_' assumed to provide a spread of 4 standard deviations
+    #
+    std_dev = (high_ - low_)/4
+    #
+    # 'mean' same as 'median' provided in excel sheet due to distribution's symmetry 
+    #
+    mean_   = med_ 
+    #
+    # Scaling and shifting due to underlying script of scipy's truncated normal
+    #
+    a, b = (min_ - mean_)/std_dev, (max_ - mean_)/std_dev
+    #
+    # Generating 'n_Samples' samples from truncated normal
+    #
+    sample_ = stats.truncnorm.rvs(a=a, b=b, loc=mean_, scale=std_dev, size=n_Samples)
+    return sample_
+
+
+# Truncated and Shifted Lognormal via Normal Representation
+def truncate_shift_lognormal(min_, low_, med_, high_, max_, n_Samples):
+    # Calculate the shape and scale parameters
+    #
+    # X is lognormal, so the distribution logX is gaussian/normal in nature, 
+    # Thus, values of log(X_low) and log(X_high) assumed to span four standard deviations of the normal distribution of logX, 
+    # thereby providing shape factor for the lognormal distribution of X.
+    #
+    std_dev = (np.log(high_)-np.log(low_))/4   # standard deviation of normal distribution logX between high and low value
+    #
+    # 'median_' in the excel sheet provides the scale or the median for the distribution of logX
+    #
+    mean_ = np.log(med_)                             # mean of logX
+    #
+    # Scaling and shifting due to underlying script of scipy's truncated normal
+    #
+    a, b = (np.log(min_) - mean_)/std_dev, (np.log(max_) - mean_)/std_dev
+    #
+    # Generating ''n_Samples' samples from truncated normal
+    #
+    sample_normal = stats.truncnorm.rvs(a=a, b=b, loc=mean_, scale=std_dev, size=n_Samples)
+    sample_       = np.exp(sample_normal)
+    return sample_
+    
+    
+    
+def sheet_info(path_sheet, subsheet_names_dict):
+    #
+    # Reading Excel sheets as Dataframes
+    #
+    subsheet_keys   = subsheet_names_dict.keys()
+    subsheet_names  = subsheet_names_dict.values()
+    #
+    subsheets_df_dict = {};
+    #
+    for subsheet_keys, subsheet_names in subsheet_names_dict.items():
+        subsheets_df_dict[subsheet_keys] = pd.read_excel(path_sheet, sheet_name=subsheet_names_dict[subsheet_names])
+    return subsheets_df_dict    
+
+
+
+# def save_to_csv(batch_results, filename, mode='a'):
+#     """ Save batch results to CSV file. """
+#     df = pd.DataFrame(batch_results)
+    df.to_csv(filename, mode=mode, header=not os.path.isfile(filename), index=False)
+
+
+# Create a global lock
+csv_lock = threading.Lock()
+
+def save_to_csv(batch_results, filename, mode='a'):
+    """ Save batch results to CSV file in a thread-safe manner. """
+    df = pd.DataFrame(batch_results)
+    
+    # Acquire the lock before writing to the file
+    with csv_lock:
+        df.to_csv(filename, mode=mode, header=not os.path.isfile(filename), index=False)
\ No newline at end of file