diff --git a/.gitignore b/.gitignore
index e1c878ef..3037e45f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,7 @@
 *.[oa]
 *~
 *.nc
+!notebooks/data/*.nc
 *.pyc
 *.gcno
 *.gcda
@@ -29,3 +30,6 @@ include/cmor_locale.h
 recipes/cmor/meta.yaml
 CMOR.egg-info
 cmor.log*
+venv/
+notebooks/output/
+.ipynb_checkpoints/
diff --git a/notebooks/01_basic_ocean_surface_temperature.ipynb b/notebooks/01_basic_ocean_surface_temperature.ipynb
new file mode 100644
index 00000000..a1966b48
--- /dev/null
+++ b/notebooks/01_basic_ocean_surface_temperature.ipynb
@@ -0,0 +1,1894 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Basic Ocean Surface Temperature\n",
+    "\n",
+    "Create a CMIP7 monthly sea surface temperature file (`tos_tavg-u-hxy-sea`) on a global 10 degree latitude-longitude grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"tos_Omon_CanCM4_decadal1982_r5i1p1_198301-198310.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
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+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
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+       "  display: inline-block;\n",
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+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
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+       "  font-size: 11px;\n",
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+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
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+       "  grid-column: 1 / -1;\n",
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+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
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+       "  height: 1em;\n",
+       "  width: 26px;\n",
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+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
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+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2MB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 192, lon: 256)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 4.856e+04 4.859e+04 ... 4.88e+04 4.883e+04\n",
+       "  * lat        (lat) float64 2kB -89.43 -88.29 -87.15 ... 87.15 88.29 89.43\n",
+       "  * lon        (lon) float64 2kB 0.7031 2.109 3.516 4.922 ... 356.5 357.9 359.3\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 4.854e+04 4.858e+04 ... 4.885e+04\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -88.86 -88.86 ... 88.86 88.86 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 4kB 0.0 1.406 1.406 ... 358.6 358.6 360.0\n",
+       "    tos        (time, lat, lon) float32 2MB nan nan nan ... 271.2 271.2 271.2\n",
+       "Attributes:\n",
+       "    institution:            CCCma (Canadian Centre for Climate Modelling and ...\n",
+       "    institute_id:           CCCma\n",
+       "    experiment_id:          decadal1982\n",
+       "    source:                 CanCM4 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ...\n",
+       "    model_id:               CanCM4\n",
+       "    forcing:                GHG,Oz,SA,BC,OC,LU,Sl,Vl (GHG includes CO2,CH4,N2...\n",
+       "    parent_experiment_id:   N/A\n",
+       "    parent_experiment_rip:  N/A\n",
+       "    branch_time:            0.0\n",
+       "    contact:                cccma_info@ec.gc.ca\n",
+       "    references:             http://www.cccma.ec.gc.ca/models\n",
+       "    initialization_method:  1\n",
+       "    physics_version:        1\n",
+       "    tracking_id:            5152f593-3451-453f-9c5f-b45e46a2efc0\n",
+       "    branch_time_YMDH:       1983:01:01:00\n",
+       "    CCCma_runid:            DHFP1B_E005_I1983_M01\n",
+       "    CCCma_parent_runid:     DHFP1_E005\n",
+       "    CCCma_data_licence:     1) GRANT OF LICENCE - The Government of Canada (E...\n",
+       "    product:                output\n",
+       "    experiment:             10- or 30-year run initialized in year 1982\n",
+       "    frequency:              mon\n",
+       "    creation_date:          2011-07-13T02:25:29Z\n",
+       "    history:                2011-07-13T02:25:29Z CMOR rewrote data to comply ...\n",
+       "    Conventions:            CF-1.4\n",
+       "    project_id:             CMIP5\n",
+       "    table_id:               Table Omon (28 March 2011) d71862c6fdafa47720d8a4...\n",
+       "    title:                  CanCM4 model output prepared for CMIP5 10- or 30-...\n",
+       "    parent_experiment:      N/A\n",
+       "    modeling_realm:         ocean\n",
+       "    realization:            5\n",
+       "    cmor_version:           2.5.4</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0587f2ce-2d2f-42e0-8fee-ed314f1c8f24' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-0587f2ce-2d2f-42e0-8fee-ed314f1c8f24' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div></li><li class='xr-section-item'><input id='section-d258ee55-9281-405f-ba88-406edd19fff2' class='xr-section-summary-in' type='checkbox' checked /><label for='section-d258ee55-9281-405f-ba88-406edd19fff2' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.856e+04 4.859e+04 ... 4.883e+04</div><input id='attrs-085b8ebd-05b0-4521-9c11-a73788a19db7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-085b8ebd-05b0-4521-9c11-a73788a19db7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fab7ca16-d987-4f8c-adc8-b728bffee4c8' class='xr-var-data-in' type='checkbox'><label for='data-fab7ca16-d987-4f8c-adc8-b728bffee4c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-1-1</dd><dt><span>calendar :</span></dt><dd>365_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([48560.5, 48590. , 48619.5, 48650. , 48680.5, 48711. , 48741.5, 48772.5,\n",
+       "       48803. , 48833.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.43 -88.29 ... 88.29 89.43</div><input id='attrs-63b60ce7-1fe9-478c-bc68-8eb06f985a9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63b60ce7-1fe9-478c-bc68-8eb06f985a9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60a516da-68f7-485a-9121-ef13eb5e1d9b' class='xr-var-data-in' type='checkbox'><label for='data-60a516da-68f7-485a-9121-ef13eb5e1d9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.429619, -88.288872, -87.148125, -86.107635, -85.167389, -84.22715 ,\n",
+       "       -83.290031, -82.356026, -81.42202 , -80.488907, -79.556686, -78.624458,\n",
+       "       -77.692612, -76.761139, -75.829674, -74.898399, -73.967316, -73.03624 ,\n",
+       "       -72.10527 , -71.174423, -70.243568, -69.31279 , -68.382088, -67.451378,\n",
+       "       -66.520721, -65.590111, -64.6595  , -63.728931, -62.798389, -61.867851,\n",
+       "       -60.937336, -60.006847, -59.076359, -58.145885, -57.215435, -56.284985,\n",
+       "       -55.354546, -54.424126, -53.493702, -52.563293, -51.632893, -50.702496,\n",
+       "       -49.772106, -48.841724, -47.911343, -46.980972, -46.050606, -45.120239,\n",
+       "       -44.18988 , -43.259525, -42.329174, -41.398827, -40.468483, -39.538139,\n",
+       "       -38.6078  , -37.677464, -36.747131, -35.816799, -34.886471, -33.956142,\n",
+       "       -33.025818, -32.095497, -31.165176, -30.234856, -29.304539, -28.374222,\n",
+       "       -27.443909, -26.513596, -25.583282, -24.652971, -23.722664, -22.792355,\n",
+       "       -21.862047, -20.931742, -20.001434, -19.071131, -18.140827, -17.210524,\n",
+       "       -16.28022 , -15.34992 , -14.419619, -13.489318, -12.559018, -11.628718,\n",
+       "       -10.698419,  -9.768121,  -8.837822,  -7.907524,  -6.977227,  -6.046929,\n",
+       "        -5.116632,  -4.186335,  -3.256038,  -2.325742,  -1.395445,  -0.465148,\n",
+       "         0.465148,   1.395445,   2.325742,   3.256038,   4.186335,   5.116632,\n",
+       "         6.046929,   6.977227,   7.907525,   8.837822,   9.768121,  10.69842 ,\n",
+       "        11.628718,  12.559018,  13.489318,  14.419619,  15.34992 ,  16.28022 ,\n",
+       "        17.210524,  18.140827,  19.071131,  20.001434,  20.931742,  21.862047,\n",
+       "        22.792355,  23.722664,  24.652973,  25.583282,  26.513596,  27.443909,\n",
+       "        28.374224,  29.304539,  30.234856,  31.165176,  32.095497,  33.025818,\n",
+       "        33.956142,  34.886471,  35.816799,  36.747131,  37.677464,  38.6078  ,\n",
+       "        39.538139,  40.468483,  41.398827,  42.329174,  43.259525,  44.18988 ,\n",
+       "        45.120239,  46.050606,  46.980972,  47.911343,  48.841724,  49.772106,\n",
+       "        50.702496,  51.632893,  52.563293,  53.493702,  54.424126,  55.354546,\n",
+       "        56.284985,  57.215435,  58.145885,  59.076359,  60.006847,  60.937336,\n",
+       "        61.867851,  62.798389,  63.728931,  64.6595  ,  65.590111,  66.520721,\n",
+       "        67.451378,  68.382088,  69.31279 ,  70.243568,  71.174423,  72.10527 ,\n",
+       "        73.03624 ,  73.967316,  74.898399,  75.829674,  76.761139,  77.692612,\n",
+       "        78.624458,  79.556686,  80.488907,  81.42202 ,  82.356026,  83.290031,\n",
+       "        84.22715 ,  85.167389,  86.107635,  87.148125,  88.288872,  89.429619])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7031 2.109 3.516 ... 357.9 359.3</div><input id='attrs-044362ed-31d7-44ea-9013-f3b40222cba5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-044362ed-31d7-44ea-9013-f3b40222cba5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90abdead-3282-4d0b-9a28-4ae36cb8f32f' class='xr-var-data-in' type='checkbox'><label for='data-90abdead-3282-4d0b-9a28-4ae36cb8f32f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.703125,   2.109375,   3.515625, ..., 356.484375, 357.890625,\n",
+       "       359.296875], shape=(256,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-57189da1-154b-49b8-abc7-29e5aa46bd07' class='xr-section-summary-in' type='checkbox' checked /><label for='section-57189da1-154b-49b8-abc7-29e5aa46bd07' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.854e+04 4.858e+04 ... 4.885e+04</div><input id='attrs-619e3d8a-28d6-47c9-bbbf-918d875ffb2f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-619e3d8a-28d6-47c9-bbbf-918d875ffb2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba326166-f99e-4844-8cac-61d254b44f84' class='xr-var-data-in' type='checkbox'><label for='data-ba326166-f99e-4844-8cac-61d254b44f84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[48545., 48576.],\n",
+       "       [48576., 48604.],\n",
+       "       [48604., 48635.],\n",
+       "       [48635., 48665.],\n",
+       "       [48665., 48696.],\n",
+       "       [48696., 48726.],\n",
+       "       [48726., 48757.],\n",
+       "       [48757., 48788.],\n",
+       "       [48788., 48818.],\n",
+       "       [48818., 48849.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.86 -88.86 ... 88.86 90.0</div><input id='attrs-8631ce5b-05f3-4971-810a-a454ada41ac7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8631ce5b-05f3-4971-810a-a454ada41ac7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e002592-18bd-45c1-ba76-35c1d0ebf37b' class='xr-var-data-in' type='checkbox'><label for='data-0e002592-18bd-45c1-ba76-35c1d0ebf37b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-9.00000000e+01, -8.88592453e+01],\n",
+       "       [-8.88592453e+01, -8.77184982e+01],\n",
+       "       [-8.77184982e+01, -8.65777512e+01],\n",
+       "       [-8.65777512e+01, -8.56375122e+01],\n",
+       "       [-8.56375122e+01, -8.46972733e+01],\n",
+       "       [-8.46972733e+01, -8.37570343e+01],\n",
+       "       [-8.37570343e+01, -8.28230286e+01],\n",
+       "       [-8.28230286e+01, -8.18890228e+01],\n",
+       "       [-8.18890228e+01, -8.09550171e+01],\n",
+       "       [-8.09550171e+01, -8.00227966e+01],\n",
+       "       [-8.00227966e+01, -7.90905685e+01],\n",
+       "       [-7.90905685e+01, -7.81583481e+01],\n",
+       "       [-7.81583481e+01, -7.72268753e+01],\n",
+       "       [-7.72268753e+01, -7.62954102e+01],\n",
+       "       [-7.62954102e+01, -7.53639374e+01],\n",
+       "       [-7.53639374e+01, -7.44328613e+01],\n",
+       "       [-7.44328613e+01, -7.35017776e+01],\n",
+       "       [-7.35017776e+01, -7.25707016e+01],\n",
+       "       [-7.25707016e+01, -7.16398468e+01],\n",
+       "       [-7.16398468e+01, -7.07089920e+01],\n",
+       "...\n",
+       "       [ 7.07089920e+01,  7.16398468e+01],\n",
+       "       [ 7.16398468e+01,  7.25707016e+01],\n",
+       "       [ 7.25707016e+01,  7.35017776e+01],\n",
+       "       [ 7.35017776e+01,  7.44328613e+01],\n",
+       "       [ 7.44328613e+01,  7.53639374e+01],\n",
+       "       [ 7.53639374e+01,  7.62954102e+01],\n",
+       "       [ 7.62954102e+01,  7.72268753e+01],\n",
+       "       [ 7.72268753e+01,  7.81583481e+01],\n",
+       "       [ 7.81583481e+01,  7.90905685e+01],\n",
+       "       [ 7.90905685e+01,  8.00227966e+01],\n",
+       "       [ 8.00227966e+01,  8.09550171e+01],\n",
+       "       [ 8.09550171e+01,  8.18890228e+01],\n",
+       "       [ 8.18890228e+01,  8.28230286e+01],\n",
+       "       [ 8.28230286e+01,  8.37570343e+01],\n",
+       "       [ 8.37570343e+01,  8.46972733e+01],\n",
+       "       [ 8.46972733e+01,  8.56375122e+01],\n",
+       "       [ 8.56375122e+01,  8.65777512e+01],\n",
+       "       [ 8.65777512e+01,  8.77184982e+01],\n",
+       "       [ 8.77184982e+01,  8.88592453e+01],\n",
+       "       [ 8.88592453e+01,  9.00000000e+01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.406 1.406 ... 358.6 360.0</div><input id='attrs-ac4f21c7-9e2b-4a4b-b894-8b6ede19accc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ac4f21c7-9e2b-4a4b-b894-8b6ede19accc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b322e9-493a-4208-86b6-c8f346057724' class='xr-var-data-in' type='checkbox'><label for='data-54b322e9-493a-4208-86b6-c8f346057724' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.     ,   1.40625],\n",
+       "       [  1.40625,   2.8125 ],\n",
+       "       [  2.8125 ,   4.21875],\n",
+       "       [  4.21875,   5.625  ],\n",
+       "       [  5.625  ,   7.03125],\n",
+       "       [  7.03125,   8.4375 ],\n",
+       "       [  8.4375 ,   9.84375],\n",
+       "       [  9.84375,  11.25   ],\n",
+       "       [ 11.25   ,  12.65625],\n",
+       "       [ 12.65625,  14.0625 ],\n",
+       "       [ 14.0625 ,  15.46875],\n",
+       "       [ 15.46875,  16.875  ],\n",
+       "       [ 16.875  ,  18.28125],\n",
+       "       [ 18.28125,  19.6875 ],\n",
+       "       [ 19.6875 ,  21.09375],\n",
+       "       [ 21.09375,  22.5    ],\n",
+       "       [ 22.5    ,  23.90625],\n",
+       "       [ 23.90625,  25.3125 ],\n",
+       "       [ 25.3125 ,  26.71875],\n",
+       "       [ 26.71875,  28.125  ],\n",
+       "...\n",
+       "       [331.875  , 333.28125],\n",
+       "       [333.28125, 334.6875 ],\n",
+       "       [334.6875 , 336.09375],\n",
+       "       [336.09375, 337.5    ],\n",
+       "       [337.5    , 338.90625],\n",
+       "       [338.90625, 340.3125 ],\n",
+       "       [340.3125 , 341.71875],\n",
+       "       [341.71875, 343.125  ],\n",
+       "       [343.125  , 344.53125],\n",
+       "       [344.53125, 345.9375 ],\n",
+       "       [345.9375 , 347.34375],\n",
+       "       [347.34375, 348.75   ],\n",
+       "       [348.75   , 350.15625],\n",
+       "       [350.15625, 351.5625 ],\n",
+       "       [351.5625 , 352.96875],\n",
+       "       [352.96875, 354.375  ],\n",
+       "       [354.375  , 355.78125],\n",
+       "       [355.78125, 357.1875 ],\n",
+       "       [357.1875 , 358.59375],\n",
+       "       [358.59375, 360.     ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tos</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... 271.2 271.2 271.2</div><input id='attrs-b477af85-2ecc-430e-9156-9b1688df1f5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b477af85-2ecc-430e-9156-9b1688df1f5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd2d3df2-5048-4f4e-9db6-856997c7222a' class='xr-var-data-in' type='checkbox'><label for='data-dd2d3df2-5048-4f4e-9db6-856997c7222a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>Sea Surface Temperature</dd><dt><span>comment :</span></dt><dd>&quot;this may differ from &quot;&quot;surface temperature&quot;&quot; in regions of sea ice.&quot;</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>original_name :</span></dt><dd>SST</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 20 minutes)</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>history :</span></dt><dd>2011-07-13T02:25:29Z altered by CMOR: replaced missing value flag (1e+38) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_ocean_fx_CanCM4_decadal1982_r0i0p0.nc areacello: areacello_fx_CanCM4_decadal1982_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>array([[[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        ...,\n",
+       "        [271.21222, 271.21143, 271.2109 , ..., 271.21558, 271.21442,\n",
+       "         271.21326],\n",
+       "        [271.2112 , 271.21014, 271.20923, ..., 271.21497, 271.21368,\n",
+       "         271.2124 ],\n",
+       "        [271.20383, 271.20383, 271.20383, ..., 271.20383, 271.20383,\n",
+       "         271.20383]],\n",
+       "\n",
+       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "...\n",
+       "        [271.20197, 271.20206, 271.20227, ..., 271.20255, 271.2022 ,\n",
+       "         271.202  ],\n",
+       "        [271.2042 , 271.2042 , 271.20416, ..., 271.20383, 271.204  ,\n",
+       "         271.20413],\n",
+       "        [271.1999 , 271.1999 , 271.1999 , ..., 271.1999 , 271.1999 ,\n",
+       "         271.1999 ]],\n",
+       "\n",
+       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        ...,\n",
+       "        [271.20337, 271.20377, 271.20435, ..., 271.20395, 271.2034 ,\n",
+       "         271.20322],\n",
+       "        [271.20563, 271.20618, 271.2068 , ..., 271.2043 , 271.20468,\n",
+       "         271.2051 ],\n",
+       "        [271.1999 , 271.1999 , 271.1999 , ..., 271.1999 , 271.1999 ,\n",
+       "         271.1999 ]]], shape=(10, 192, 256), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-00909bbd-d530-43ba-b66f-345d46e6cb42' class='xr-section-summary-in' type='checkbox' checked /><label for='section-00909bbd-d530-43ba-b66f-345d46e6cb42' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(31)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>CCCma (Canadian Centre for Climate Modelling and Analysis, Victoria, BC, Canada)</dd><dt><span>institute_id :</span></dt><dd>CCCma</dd><dt><span>experiment_id :</span></dt><dd>decadal1982</dd><dt><span>source :</span></dt><dd>CanCM4 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ocean: CanOM4 (OGCM4.0, 256x192L40) sea ice: CanSIM1 (Cavitating Fluid, T63 Gaussian Grid) land: CLASS2.7</dd><dt><span>model_id :</span></dt><dd>CanCM4</dd><dt><span>forcing :</span></dt><dd>GHG,Oz,SA,BC,OC,LU,Sl,Vl (GHG includes CO2,CH4,N2O,CFC11,effective CFC12)</dd><dt><span>parent_experiment_id :</span></dt><dd>N/A</dd><dt><span>parent_experiment_rip :</span></dt><dd>N/A</dd><dt><span>branch_time :</span></dt><dd>0.0</dd><dt><span>contact :</span></dt><dd>cccma_info@ec.gc.ca</dd><dt><span>references :</span></dt><dd>http://www.cccma.ec.gc.ca/models</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5152f593-3451-453f-9c5f-b45e46a2efc0</dd><dt><span>branch_time_YMDH :</span></dt><dd>1983:01:01:00</dd><dt><span>CCCma_runid :</span></dt><dd>DHFP1B_E005_I1983_M01</dd><dt><span>CCCma_parent_runid :</span></dt><dd>DHFP1_E005</dd><dt><span>CCCma_data_licence :</span></dt><dd>1) GRANT OF LICENCE - The Government of Canada (Environment Canada) is the \n",
+       "owner of all intellectual property rights (including copyright) that may exist in this Data \n",
+       "product. You (as &quot;The Licensee&quot;) are hereby granted a non-exclusive, non-assignable, \n",
+       "non-transferable unrestricted licence to use this data product for any purpose including \n",
+       "the right to share these data with others and to make value-added and derivative \n",
+       "products from it. This licence is not a sale of any or all of the owner&#x27;s rights.\n",
+       "2) NO WARRANTY - This Data product is provided &quot;as-is&quot;; it has not been designed or \n",
+       "prepared to meet the Licensee&#x27;s particular requirements. Environment Canada makes no \n",
+       "warranty, either express or implied, including but not limited to, warranties of \n",
+       "merchantability and fitness for a particular purpose. In no event will Environment Canada \n",
+       "be liable for any indirect, special, consequential or other damages attributed to the \n",
+       "Licensee&#x27;s use of the Data product.</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>10- or 30-year run initialized in year 1982</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-07-13T02:25:29Z</dd><dt><span>history :</span></dt><dd>2011-07-13T02:25:29Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Omon (28 March 2011) d71862c6fdafa47720d8a402f39c8864</dd><dt><span>title :</span></dt><dd>CanCM4 model output prepared for CMIP5 10- or 30-year run initialized in year 1982</dd><dt><span>parent_experiment :</span></dt><dd>N/A</dd><dt><span>modeling_realm :</span></dt><dd>ocean</dd><dt><span>realization :</span></dt><dd>5</dd><dt><span>cmor_version :</span></dt><dd>2.5.4</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2MB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 192, lon: 256)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 4.856e+04 4.859e+04 ... 4.88e+04 4.883e+04\n",
+       "  * lat        (lat) float64 2kB -89.43 -88.29 -87.15 ... 87.15 88.29 89.43\n",
+       "  * lon        (lon) float64 2kB 0.7031 2.109 3.516 4.922 ... 356.5 357.9 359.3\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 4.854e+04 4.858e+04 ... 4.885e+04\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -88.86 -88.86 ... 88.86 88.86 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 4kB 0.0 1.406 1.406 ... 358.6 358.6 360.0\n",
+       "    tos        (time, lat, lon) float32 2MB nan nan nan ... 271.2 271.2 271.2\n",
+       "Attributes:\n",
+       "    institution:            CCCma (Canadian Centre for Climate Modelling and ...\n",
+       "    institute_id:           CCCma\n",
+       "    experiment_id:          decadal1982\n",
+       "    source:                 CanCM4 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ...\n",
+       "    model_id:               CanCM4\n",
+       "    forcing:                GHG,Oz,SA,BC,OC,LU,Sl,Vl (GHG includes CO2,CH4,N2...\n",
+       "    parent_experiment_id:   N/A\n",
+       "    parent_experiment_rip:  N/A\n",
+       "    branch_time:            0.0\n",
+       "    contact:                cccma_info@ec.gc.ca\n",
+       "    references:             http://www.cccma.ec.gc.ca/models\n",
+       "    initialization_method:  1\n",
+       "    physics_version:        1\n",
+       "    tracking_id:            5152f593-3451-453f-9c5f-b45e46a2efc0\n",
+       "    branch_time_YMDH:       1983:01:01:00\n",
+       "    CCCma_runid:            DHFP1B_E005_I1983_M01\n",
+       "    CCCma_parent_runid:     DHFP1_E005\n",
+       "    CCCma_data_licence:     1) GRANT OF LICENCE - The Government of Canada (E...\n",
+       "    product:                output\n",
+       "    experiment:             10- or 30-year run initialized in year 1982\n",
+       "    frequency:              mon\n",
+       "    creation_date:          2011-07-13T02:25:29Z\n",
+       "    history:                2011-07-13T02:25:29Z CMOR rewrote data to comply ...\n",
+       "    Conventions:            CF-1.4\n",
+       "    project_id:             CMIP5\n",
+       "    table_id:               Table Omon (28 March 2011) d71862c6fdafa47720d8a4...\n",
+       "    title:                  CanCM4 model output prepared for CMIP5 10- or 30-...\n",
+       "    parent_experiment:      N/A\n",
+       "    modeling_realm:         ocean\n",
+       "    realization:            5\n",
+       "    cmor_version:           2.5.4"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(10, 192, 256)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"01_basic_ocean_surface_temperature\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "lon = source[\"lon\"].values.astype(\"f8\")\n",
+    "lon_bnds = source[\"lon_bnds\"].values.astype(\"f8\")\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_bnds = source[\"time_bnds\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "tos_kelvin = source[\"tos\"].values.astype(\"f4\")\n",
+    "tos = np.where(np.isfinite(tos_kelvin), tos_kelvin - np.float32(273.15), missing_value).astype(\"f4\")\n",
+    "\n",
+    "print(tos.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/01_basic_ocean_surface_temperature/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/tos/tavg-u-hxy-sea/g999/v20260605/tos_tavg-u-hxy-sea_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_198301-198310.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "cmor.load_table(\"CMIP7_ocean.json\")\n",
+    "\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "lon_id = cmor.axis(\"longitude\", coord_vals=lon, cell_bounds=lon_bnds, units=\"degrees_east\")\n",
+    "time_id = cmor.axis(\"time\", coord_vals=time, cell_bounds=time_bnds, units=time_units)\n",
+    "\n",
+    "variable_name = \"tos_tavg-u-hxy-sea\"\n",
+    "tos_id = cmor.variable(variable_name, \"degC\", [time_id, lat_id, lon_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"ocean\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(tos_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(tos_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(tos_id, tos)\n",
+    "netcdf_path = Path(cmor.close(tos_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2MB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 192, lon: 256)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 4.856e+04 4.859e+04 ... 4.88e+04 4.883e+04\n",
+       "  * lat        (lat) float64 2kB -89.43 -88.29 -87.15 ... 87.15 88.29 89.43\n",
+       "  * lon        (lon) float64 2kB 0.7031 2.109 3.516 4.922 ... 356.5 357.9 359.3\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 4.854e+04 4.858e+04 ... 4.885e+04\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -88.86 -88.86 ... 88.86 88.86 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 4kB 0.0 1.406 1.406 ... 358.6 358.6 360.0\n",
+       "    tos        (time, lat, lon) float32 2MB nan nan nan ... -1.95 -1.95 -1.95\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            sea\n",
+       "    branded_variable:      tos_tavg-u-hxy-sea\n",
+       "    branding_suffix:       tavg-u-hxy-sea\n",
+       "    creation_date:         2026-06-05T21:59:20Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacello\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:20Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 ocean\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_ocean.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/f81ce082-86e4-413b-8b72-598c9e3ba40d\n",
+       "    variable_id:           tos\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-81b01ec2-a46b-40c0-b8a7-01663cb839ca' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-81b01ec2-a46b-40c0-b8a7-01663cb839ca' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div></li><li class='xr-section-item'><input id='section-7cb8fae3-142b-47b4-965c-2a03e2e2530b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7cb8fae3-142b-47b4-965c-2a03e2e2530b' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.856e+04 4.859e+04 ... 4.883e+04</div><input id='attrs-b5615228-8538-4ebb-8919-29d907806b52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5615228-8538-4ebb-8919-29d907806b52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b196424-1473-4cd7-bcd5-baf82bc1728f' class='xr-var-data-in' type='checkbox'><label for='data-0b196424-1473-4cd7-bcd5-baf82bc1728f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-1-1</dd><dt><span>calendar :</span></dt><dd>365_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([48560.5, 48590. , 48619.5, 48650. , 48680.5, 48711. , 48741.5, 48772.5,\n",
+       "       48803. , 48833.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.43 -88.29 ... 88.29 89.43</div><input id='attrs-ab814073-67ca-464b-9d81-c6aa8d242091' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab814073-67ca-464b-9d81-c6aa8d242091' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feef79a7-32db-46a4-a629-cc0a159ac567' class='xr-var-data-in' type='checkbox'><label for='data-feef79a7-32db-46a4-a629-cc0a159ac567' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.429619, -88.288872, -87.148125, -86.107635, -85.167389, -84.22715 ,\n",
+       "       -83.290031, -82.356026, -81.42202 , -80.488907, -79.556686, -78.624458,\n",
+       "       -77.692612, -76.761139, -75.829674, -74.898399, -73.967316, -73.03624 ,\n",
+       "       -72.10527 , -71.174423, -70.243568, -69.31279 , -68.382088, -67.451378,\n",
+       "       -66.520721, -65.590111, -64.6595  , -63.728931, -62.798389, -61.867851,\n",
+       "       -60.937336, -60.006847, -59.076359, -58.145885, -57.215435, -56.284985,\n",
+       "       -55.354546, -54.424126, -53.493702, -52.563293, -51.632893, -50.702496,\n",
+       "       -49.772106, -48.841724, -47.911343, -46.980972, -46.050606, -45.120239,\n",
+       "       -44.18988 , -43.259525, -42.329174, -41.398827, -40.468483, -39.538139,\n",
+       "       -38.6078  , -37.677464, -36.747131, -35.816799, -34.886471, -33.956142,\n",
+       "       -33.025818, -32.095497, -31.165176, -30.234856, -29.304539, -28.374222,\n",
+       "       -27.443909, -26.513596, -25.583282, -24.652971, -23.722664, -22.792355,\n",
+       "       -21.862047, -20.931742, -20.001434, -19.071131, -18.140827, -17.210524,\n",
+       "       -16.28022 , -15.34992 , -14.419619, -13.489318, -12.559018, -11.628718,\n",
+       "       -10.698419,  -9.768121,  -8.837822,  -7.907524,  -6.977227,  -6.046929,\n",
+       "        -5.116632,  -4.186335,  -3.256038,  -2.325742,  -1.395445,  -0.465148,\n",
+       "         0.465148,   1.395445,   2.325742,   3.256038,   4.186335,   5.116632,\n",
+       "         6.046929,   6.977227,   7.907525,   8.837822,   9.768121,  10.69842 ,\n",
+       "        11.628718,  12.559018,  13.489318,  14.419619,  15.34992 ,  16.28022 ,\n",
+       "        17.210524,  18.140827,  19.071131,  20.001434,  20.931742,  21.862047,\n",
+       "        22.792355,  23.722664,  24.652973,  25.583282,  26.513596,  27.443909,\n",
+       "        28.374224,  29.304539,  30.234856,  31.165176,  32.095497,  33.025818,\n",
+       "        33.956142,  34.886471,  35.816799,  36.747131,  37.677464,  38.6078  ,\n",
+       "        39.538139,  40.468483,  41.398827,  42.329174,  43.259525,  44.18988 ,\n",
+       "        45.120239,  46.050606,  46.980972,  47.911343,  48.841724,  49.772106,\n",
+       "        50.702496,  51.632893,  52.563293,  53.493702,  54.424126,  55.354546,\n",
+       "        56.284985,  57.215435,  58.145885,  59.076359,  60.006847,  60.937336,\n",
+       "        61.867851,  62.798389,  63.728931,  64.6595  ,  65.590111,  66.520721,\n",
+       "        67.451378,  68.382088,  69.31279 ,  70.243568,  71.174423,  72.10527 ,\n",
+       "        73.03624 ,  73.967316,  74.898399,  75.829674,  76.761139,  77.692612,\n",
+       "        78.624458,  79.556686,  80.488907,  81.42202 ,  82.356026,  83.290031,\n",
+       "        84.22715 ,  85.167389,  86.107635,  87.148125,  88.288872,  89.429619])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7031 2.109 3.516 ... 357.9 359.3</div><input id='attrs-e21ea6b6-51e9-4ee5-999f-96d1dc81d0ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e21ea6b6-51e9-4ee5-999f-96d1dc81d0ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa1f5b41-d002-4973-b713-59021f6ae19c' class='xr-var-data-in' type='checkbox'><label for='data-aa1f5b41-d002-4973-b713-59021f6ae19c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.703125,   2.109375,   3.515625, ..., 356.484375, 357.890625,\n",
+       "       359.296875], shape=(256,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6914907a-c637-4570-a9f8-7c5227adc623' class='xr-section-summary-in' type='checkbox' checked /><label for='section-6914907a-c637-4570-a9f8-7c5227adc623' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.854e+04 4.858e+04 ... 4.885e+04</div><input id='attrs-90c3686e-1ad0-4826-aa87-2d6a5ab25886' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-90c3686e-1ad0-4826-aa87-2d6a5ab25886' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-820a03ac-501c-4a83-8666-7a1755b3d7ef' class='xr-var-data-in' type='checkbox'><label for='data-820a03ac-501c-4a83-8666-7a1755b3d7ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[48545., 48576.],\n",
+       "       [48576., 48604.],\n",
+       "       [48604., 48635.],\n",
+       "       [48635., 48665.],\n",
+       "       [48665., 48696.],\n",
+       "       [48696., 48726.],\n",
+       "       [48726., 48757.],\n",
+       "       [48757., 48788.],\n",
+       "       [48788., 48818.],\n",
+       "       [48818., 48849.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.86 -88.86 ... 88.86 90.0</div><input id='attrs-1d8bfcdb-e05e-499c-9de0-a1a5f72face3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d8bfcdb-e05e-499c-9de0-a1a5f72face3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b70697f-8372-4e96-b842-19fa20a69ec0' class='xr-var-data-in' type='checkbox'><label for='data-9b70697f-8372-4e96-b842-19fa20a69ec0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-9.00000000e+01, -8.88592453e+01],\n",
+       "       [-8.88592453e+01, -8.77184982e+01],\n",
+       "       [-8.77184982e+01, -8.65777512e+01],\n",
+       "       [-8.65777512e+01, -8.56375122e+01],\n",
+       "       [-8.56375122e+01, -8.46972733e+01],\n",
+       "       [-8.46972733e+01, -8.37570343e+01],\n",
+       "       [-8.37570343e+01, -8.28230286e+01],\n",
+       "       [-8.28230286e+01, -8.18890228e+01],\n",
+       "       [-8.18890228e+01, -8.09550171e+01],\n",
+       "       [-8.09550171e+01, -8.00227966e+01],\n",
+       "       [-8.00227966e+01, -7.90905685e+01],\n",
+       "       [-7.90905685e+01, -7.81583481e+01],\n",
+       "       [-7.81583481e+01, -7.72268753e+01],\n",
+       "       [-7.72268753e+01, -7.62954102e+01],\n",
+       "       [-7.62954102e+01, -7.53639374e+01],\n",
+       "       [-7.53639374e+01, -7.44328613e+01],\n",
+       "       [-7.44328613e+01, -7.35017776e+01],\n",
+       "       [-7.35017776e+01, -7.25707016e+01],\n",
+       "       [-7.25707016e+01, -7.16398468e+01],\n",
+       "       [-7.16398468e+01, -7.07089920e+01],\n",
+       "...\n",
+       "       [ 7.07089920e+01,  7.16398468e+01],\n",
+       "       [ 7.16398468e+01,  7.25707016e+01],\n",
+       "       [ 7.25707016e+01,  7.35017776e+01],\n",
+       "       [ 7.35017776e+01,  7.44328613e+01],\n",
+       "       [ 7.44328613e+01,  7.53639374e+01],\n",
+       "       [ 7.53639374e+01,  7.62954102e+01],\n",
+       "       [ 7.62954102e+01,  7.72268753e+01],\n",
+       "       [ 7.72268753e+01,  7.81583481e+01],\n",
+       "       [ 7.81583481e+01,  7.90905685e+01],\n",
+       "       [ 7.90905685e+01,  8.00227966e+01],\n",
+       "       [ 8.00227966e+01,  8.09550171e+01],\n",
+       "       [ 8.09550171e+01,  8.18890228e+01],\n",
+       "       [ 8.18890228e+01,  8.28230286e+01],\n",
+       "       [ 8.28230286e+01,  8.37570343e+01],\n",
+       "       [ 8.37570343e+01,  8.46972733e+01],\n",
+       "       [ 8.46972733e+01,  8.56375122e+01],\n",
+       "       [ 8.56375122e+01,  8.65777512e+01],\n",
+       "       [ 8.65777512e+01,  8.77184982e+01],\n",
+       "       [ 8.77184982e+01,  8.88592453e+01],\n",
+       "       [ 8.88592453e+01,  9.00000000e+01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.406 1.406 ... 358.6 360.0</div><input id='attrs-f8c239e8-8f89-468d-9e12-c91f8b79aa3c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8c239e8-8f89-468d-9e12-c91f8b79aa3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de85888-c48f-4b97-abf4-a1fe3daa5f6e' class='xr-var-data-in' type='checkbox'><label for='data-6de85888-c48f-4b97-abf4-a1fe3daa5f6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.     ,   1.40625],\n",
+       "       [  1.40625,   2.8125 ],\n",
+       "       [  2.8125 ,   4.21875],\n",
+       "       [  4.21875,   5.625  ],\n",
+       "       [  5.625  ,   7.03125],\n",
+       "       [  7.03125,   8.4375 ],\n",
+       "       [  8.4375 ,   9.84375],\n",
+       "       [  9.84375,  11.25   ],\n",
+       "       [ 11.25   ,  12.65625],\n",
+       "       [ 12.65625,  14.0625 ],\n",
+       "       [ 14.0625 ,  15.46875],\n",
+       "       [ 15.46875,  16.875  ],\n",
+       "       [ 16.875  ,  18.28125],\n",
+       "       [ 18.28125,  19.6875 ],\n",
+       "       [ 19.6875 ,  21.09375],\n",
+       "       [ 21.09375,  22.5    ],\n",
+       "       [ 22.5    ,  23.90625],\n",
+       "       [ 23.90625,  25.3125 ],\n",
+       "       [ 25.3125 ,  26.71875],\n",
+       "       [ 26.71875,  28.125  ],\n",
+       "...\n",
+       "       [331.875  , 333.28125],\n",
+       "       [333.28125, 334.6875 ],\n",
+       "       [334.6875 , 336.09375],\n",
+       "       [336.09375, 337.5    ],\n",
+       "       [337.5    , 338.90625],\n",
+       "       [338.90625, 340.3125 ],\n",
+       "       [340.3125 , 341.71875],\n",
+       "       [341.71875, 343.125  ],\n",
+       "       [343.125  , 344.53125],\n",
+       "       [344.53125, 345.9375 ],\n",
+       "       [345.9375 , 347.34375],\n",
+       "       [347.34375, 348.75   ],\n",
+       "       [348.75   , 350.15625],\n",
+       "       [350.15625, 351.5625 ],\n",
+       "       [351.5625 , 352.96875],\n",
+       "       [352.96875, 354.375  ],\n",
+       "       [354.375  , 355.78125],\n",
+       "       [355.78125, 357.1875 ],\n",
+       "       [357.1875 , 358.59375],\n",
+       "       [358.59375, 360.     ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tos</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... -1.95 -1.95 -1.95</div><input id='attrs-cf680b4b-e645-4f0e-bbfd-bcf27c50e652' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf680b4b-e645-4f0e-bbfd-bcf27c50e652' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6b513cb-188d-4820-805c-d02ab0d6b8c6' class='xr-var-data-in' type='checkbox'><label for='data-d6b513cb-188d-4820-805c-d02ab0d6b8c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd></dl></div><div class='xr-var-data'><pre>array([[[       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        ...,\n",
+       "        [-1.9377747, -1.9385681, -1.9390869, ..., -1.9344177,\n",
+       "         -1.9355774, -1.9367371],\n",
+       "        [-1.9387817, -1.9398499, -1.9407654, ..., -1.9350281,\n",
+       "         -1.9363098, -1.9375916],\n",
+       "        [-1.946167 , -1.946167 , -1.946167 , ..., -1.946167 ,\n",
+       "         -1.946167 , -1.946167 ]],\n",
+       "\n",
+       "       [[       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "...\n",
+       "        [-1.9480286, -1.947937 , -1.9477234, ..., -1.9474487,\n",
+       "         -1.9477844, -1.947998 ],\n",
+       "        [-1.9458008, -1.9458008, -1.9458313, ..., -1.946167 ,\n",
+       "         -1.9459839, -1.9458618],\n",
+       "        [-1.9501038, -1.9501038, -1.9501038, ..., -1.9501038,\n",
+       "         -1.9501038, -1.9501038]],\n",
+       "\n",
+       "       [[       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        [       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan],\n",
+       "        ...,\n",
+       "        [-1.9466248, -1.946228 , -1.9456482, ..., -1.9460449,\n",
+       "         -1.9465942, -1.9467773],\n",
+       "        [-1.9443665, -1.9438171, -1.9432068, ..., -1.9456787,\n",
+       "         -1.9453125, -1.9448853],\n",
+       "        [-1.9501038, -1.9501038, -1.9501038, ..., -1.9501038,\n",
+       "         -1.9501038, -1.9501038]]], shape=(10, 192, 256), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-68d435e6-7b76-47e2-86e6-a0d13f0d7bcf' class='xr-section-summary-in' type='checkbox' checked /><label for='section-68d435e6-7b76-47e2-86e6-a0d13f0d7bcf' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>sea</dd><dt><span>branded_variable :</span></dt><dd>tos_tavg-u-hxy-sea</dd><dt><span>branding_suffix :</span></dt><dd>tavg-u-hxy-sea</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:20Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacello</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:20Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_ocean.json; Creation Date:(2026-04-21 15:01:29) MD5:a66e0fc7ab41aafa94f1ba3223e0c9fe</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/f81ce082-86e4-413b-8b72-598c9e3ba40d</dd><dt><span>variable_id :</span></dt><dd>tos</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>u</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2MB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 192, lon: 256)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 4.856e+04 4.859e+04 ... 4.88e+04 4.883e+04\n",
+       "  * lat        (lat) float64 2kB -89.43 -88.29 -87.15 ... 87.15 88.29 89.43\n",
+       "  * lon        (lon) float64 2kB 0.7031 2.109 3.516 4.922 ... 356.5 357.9 359.3\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 4.854e+04 4.858e+04 ... 4.885e+04\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -88.86 -88.86 ... 88.86 88.86 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 4kB 0.0 1.406 1.406 ... 358.6 358.6 360.0\n",
+       "    tos        (time, lat, lon) float32 2MB nan nan nan ... -1.95 -1.95 -1.95\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            sea\n",
+       "    branded_variable:      tos_tavg-u-hxy-sea\n",
+       "    branding_suffix:       tavg-u-hxy-sea\n",
+       "    creation_date:         2026-06-05T21:59:20Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacello\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:20Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 ocean\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_ocean.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/f81ce082-86e4-413b-8b72-598c9e3ba40d\n",
+       "    variable_id:           tos\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x540 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(11, 5.4))\n",
+    "map_plot = Basemap(\n",
+    "    projection=\"cyl\",\n",
+    "    llcrnrlon=-180,\n",
+    "    urcrnrlon=180,\n",
+    "    llcrnrlat=-90,\n",
+    "    urcrnrlat=90,\n",
+    "    resolution=\"c\",\n",
+    "    ax=ax,\n",
+    ")\n",
+    "map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "lon_wrapped = ((ds[\"lon\"].values + 180.0) % 360.0) - 180.0\n",
+    "lon_order = np.argsort(lon_wrapped)\n",
+    "lon_grid, lat_grid = np.meshgrid(lon_wrapped[lon_order], ds[\"lat\"].values)\n",
+    "x, y = map_plot(lon_grid, lat_grid)\n",
+    "field = ds[\"tos\"].isel(time=0).values[:, lon_order]\n",
+    "mesh = map_plot.pcolormesh(x, y, field, shading=\"auto\", cmap=\"coolwarm\")\n",
+    "map_plot.drawcoastlines(linewidth=0.7, color=\"0.15\")\n",
+    "map_plot.drawparallels(np.arange(-90, 91, 30), labels=[1, 0, 0, 0], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "map_plot.drawmeridians(np.arange(-180, 181, 60), labels=[0, 0, 0, 1], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "colorbar = map_plot.colorbar(mesh, location=\"right\", pad=\"5%\")\n",
+    "colorbar.set_label(\"degC\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "ax.set_title(f\"CMIP7 tos, {time_label}\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/02_atmos_surface_air_temperature.ipynb b/notebooks/02_atmos_surface_air_temperature.ipynb
new file mode 100644
index 00000000..c637b348
--- /dev/null
+++ b/notebooks/02_atmos_surface_air_temperature.ipynb
@@ -0,0 +1,1860 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Atmospheric Surface Air Temperature\n",
+    "\n",
+    "Create a CMIP7 monthly near-surface air temperature file (`tas_tavg-h2m-hxy-u`). This adds the CMIP7 fixed-height coordinate used for 2 m variables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"tas_Amon_GISS-E2-H_historical_r1i1p2_195101-195110.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
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+       "    var(--pst-color-on-background, white)\n",
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+       "  --xr-background-color-row-even: var(\n",
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+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
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+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
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+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
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+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
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+       "}\n",
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+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
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+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 524kB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 90, lon: 144)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 15.5 45.0 74.5 105.0 ... 227.5 258.0 288.5\n",
+       "  * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "  * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "    height     float64 8B 2.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 0.0 31.0 31.0 ... 273.0 273.0 304.0\n",
+       "    lat_bnds   (lat, bnds) float64 1kB -90.0 -88.0 -88.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 2kB 0.0 2.5 2.5 5.0 ... 357.5 357.5 360.0\n",
+       "    tas        (time, lat, lon) float32 518kB 246.9 246.9 246.9 ... 259.4 259.4\n",
+       "Attributes:\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh137Tcadf9a Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes or...\n",
+       "    parent_experiment_id:   piControl\n",
+       "    parent_experiment_rip:  r1i1p2\n",
+       "    branch_time:            2490.0\n",
+       "    contact:                Kenneth Lo (cdkkl@giss.nasa.gov)\n",
+       "    references:             http://data.giss.nasa.gov/modelE/ar5\n",
+       "    initialization_method:  1\n",
+       "    physics_version:        2\n",
+       "    tracking_id:            d43050cd-5c43-4dc5-914a-f724463bc109\n",
+       "    product:                output\n",
+       "    experiment:             historical\n",
+       "    frequency:              mon\n",
+       "    creation_date:          2011-10-18T13:06:09Z\n",
+       "    history:                2011-10-18T13:06:09Z CMOR rewrote data to comply ...\n",
+       "    Conventions:            CF-1.4\n",
+       "    project_id:             CMIP5\n",
+       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.5.7</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cc35d9f3-9b6a-422c-a935-682c50eda2f1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-cc35d9f3-9b6a-422c-a935-682c50eda2f1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div></li><li class='xr-section-item'><input id='section-91494840-a1d7-4f9d-b187-61969a2b654f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-91494840-a1d7-4f9d-b187-61969a2b654f' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.5 45.0 74.5 ... 258.0 288.5</div><input id='attrs-7b49c425-7133-42d2-8f83-20d789a77d91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b49c425-7133-42d2-8f83-20d789a77d91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b0dc9d4-f611-4432-a45c-231a0d3dae24' class='xr-var-data-in' type='checkbox'><label for='data-5b0dc9d4-f611-4432-a45c-231a0d3dae24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1951-1-1</dd><dt><span>calendar :</span></dt><dd>365_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([ 15.5,  45. ,  74.5, 105. , 135.5, 166. , 196.5, 227.5, 258. , 288.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-d2caa4a8-79b9-4934-873a-9d2eedea0126' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2caa4a8-79b9-4934-873a-9d2eedea0126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5365339-1e78-45bb-b8cf-e994ad6eef9d' class='xr-var-data-in' type='checkbox'><label for='data-d5365339-1e78-45bb-b8cf-e994ad6eef9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-d544ed7e-24c7-4610-b231-27625a448b0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d544ed7e-24c7-4610-b231-27625a448b0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d460f23-7a8c-471b-9bcf-23f503b2f7c3' class='xr-var-data-in' type='checkbox'><label for='data-7d460f23-7a8c-471b-9bcf-23f503b2f7c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-7b770fd2-26e8-401a-bf30-df5c43dc2f8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b770fd2-26e8-401a-bf30-df5c43dc2f8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23b855a7-af36-463b-8c89-461f193cfdd1' class='xr-var-data-in' type='checkbox'><label for='data-23b855a7-af36-463b-8c89-461f193cfdd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-10bda6a7-355f-4931-8e78-b2973c30bd68' class='xr-section-summary-in' type='checkbox' checked /><label for='section-10bda6a7-355f-4931-8e78-b2973c30bd68' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 31.0 31.0 ... 273.0 273.0 304.0</div><input id='attrs-f8736c5d-d600-4c7b-b54b-e1ce1d1462ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8736c5d-d600-4c7b-b54b-e1ce1d1462ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3cb79fa-0330-4e01-a81e-5718452a35d9' class='xr-var-data-in' type='checkbox'><label for='data-c3cb79fa-0330-4e01-a81e-5718452a35d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,  31.],\n",
+       "       [ 31.,  59.],\n",
+       "       [ 59.,  90.],\n",
+       "       [ 90., 120.],\n",
+       "       [120., 151.],\n",
+       "       [151., 181.],\n",
+       "       [181., 212.],\n",
+       "       [212., 243.],\n",
+       "       [243., 273.],\n",
+       "       [273., 304.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.0 -88.0 ... 88.0 90.0</div><input id='attrs-62fc83d6-469e-483b-b142-223a00f8ac4e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-62fc83d6-469e-483b-b142-223a00f8ac4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b78d8973-ba74-4871-95dc-ef3ef50c26a4' class='xr-var-data-in' type='checkbox'><label for='data-b78d8973-ba74-4871-95dc-ef3ef50c26a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -88.],\n",
+       "       [-88., -86.],\n",
+       "       [-86., -84.],\n",
+       "       [-84., -82.],\n",
+       "       [-82., -80.],\n",
+       "       [-80., -78.],\n",
+       "       [-78., -76.],\n",
+       "       [-76., -74.],\n",
+       "       [-74., -72.],\n",
+       "       [-72., -70.],\n",
+       "       [-70., -68.],\n",
+       "       [-68., -66.],\n",
+       "       [-66., -64.],\n",
+       "       [-64., -62.],\n",
+       "       [-62., -60.],\n",
+       "       [-60., -58.],\n",
+       "       [-58., -56.],\n",
+       "       [-56., -54.],\n",
+       "       [-54., -52.],\n",
+       "       [-52., -50.],\n",
+       "...\n",
+       "       [ 50.,  52.],\n",
+       "       [ 52.,  54.],\n",
+       "       [ 54.,  56.],\n",
+       "       [ 56.,  58.],\n",
+       "       [ 58.,  60.],\n",
+       "       [ 60.,  62.],\n",
+       "       [ 62.,  64.],\n",
+       "       [ 64.,  66.],\n",
+       "       [ 66.,  68.],\n",
+       "       [ 68.,  70.],\n",
+       "       [ 70.,  72.],\n",
+       "       [ 72.,  74.],\n",
+       "       [ 74.,  76.],\n",
+       "       [ 76.,  78.],\n",
+       "       [ 78.,  80.],\n",
+       "       [ 80.,  82.],\n",
+       "       [ 82.,  84.],\n",
+       "       [ 84.,  86.],\n",
+       "       [ 86.,  88.],\n",
+       "       [ 88.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 2.5 ... 357.5 357.5 360.0</div><input id='attrs-cad9b7d8-b236-4c37-90e9-a39349539d8d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cad9b7d8-b236-4c37-90e9-a39349539d8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e77b3572-d1bb-4da8-9dcf-8cfd8b85c32d' class='xr-var-data-in' type='checkbox'><label for='data-e77b3572-d1bb-4da8-9dcf-8cfd8b85c32d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0. ,   2.5],\n",
+       "       [  2.5,   5. ],\n",
+       "       [  5. ,   7.5],\n",
+       "       [  7.5,  10. ],\n",
+       "       [ 10. ,  12.5],\n",
+       "       [ 12.5,  15. ],\n",
+       "       [ 15. ,  17.5],\n",
+       "       [ 17.5,  20. ],\n",
+       "       [ 20. ,  22.5],\n",
+       "       [ 22.5,  25. ],\n",
+       "       [ 25. ,  27.5],\n",
+       "       [ 27.5,  30. ],\n",
+       "       [ 30. ,  32.5],\n",
+       "       [ 32.5,  35. ],\n",
+       "       [ 35. ,  37.5],\n",
+       "       [ 37.5,  40. ],\n",
+       "       [ 40. ,  42.5],\n",
+       "       [ 42.5,  45. ],\n",
+       "       [ 45. ,  47.5],\n",
+       "       [ 47.5,  50. ],\n",
+       "...\n",
+       "       [310. , 312.5],\n",
+       "       [312.5, 315. ],\n",
+       "       [315. , 317.5],\n",
+       "       [317.5, 320. ],\n",
+       "       [320. , 322.5],\n",
+       "       [322.5, 325. ],\n",
+       "       [325. , 327.5],\n",
+       "       [327.5, 330. ],\n",
+       "       [330. , 332.5],\n",
+       "       [332.5, 335. ],\n",
+       "       [335. , 337.5],\n",
+       "       [337.5, 340. ],\n",
+       "       [340. , 342.5],\n",
+       "       [342.5, 345. ],\n",
+       "       [345. , 347.5],\n",
+       "       [347.5, 350. ],\n",
+       "       [350. , 352.5],\n",
+       "       [352.5, 355. ],\n",
+       "       [355. , 357.5],\n",
+       "       [357.5, 360. ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>246.9 246.9 246.9 ... 259.4 259.4</div><input id='attrs-45665e1a-4ba5-42e4-9c9e-b5ddb7149383' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45665e1a-4ba5-42e4-9c9e-b5ddb7149383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e38e93a-cc37-4926-bc23-0b06771442e6' class='xr-var-data-in' type='checkbox'><label for='data-5e38e93a-cc37-4926-bc23-0b06771442e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>original_name :</span></dt><dd>dummy</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-10-18T13:06:08Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2011-10-18T13:06:08Z altered by CMOR: replaced missing value flag (-1e+30) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_GISS-E2-H_historical_r0i0p0.nc areacella: areacella_fx_GISS-E2-H_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>array([[[246.86728, 246.86728, 246.86728, ..., 246.86728, 246.86728,\n",
+       "         246.86728],\n",
+       "        [248.9035 , 248.54457, 248.41835, ..., 249.81686, 249.28986,\n",
+       "         249.04837],\n",
+       "        [249.00377, 247.89893, 247.59648, ..., 250.52367, 250.40804,\n",
+       "         249.95767],\n",
+       "        ...,\n",
+       "        [244.49625, 244.8527 , 244.9202 , ..., 244.34276, 244.54477,\n",
+       "         244.54547],\n",
+       "        [243.83018, 243.76509, 243.94258, ..., 243.30023, 243.545  ,\n",
+       "         243.58965],\n",
+       "        [240.78905, 240.78905, 240.78905, ..., 240.78905, 240.78905,\n",
+       "         240.78905]],\n",
+       "\n",
+       "       [[237.30267, 237.30267, 237.30267, ..., 237.30267, 237.30267,\n",
+       "         237.30267],\n",
+       "        [242.50592, 242.29816, 242.0082 , ..., 243.48294, 243.1406 ,\n",
+       "         242.75697],\n",
+       "        [244.73744, 244.23917, 243.90952, ..., 245.81609, 245.63405,\n",
+       "         245.1311 ],\n",
+       "...\n",
+       "        [265.2184 , 265.34525, 265.6025 , ..., 264.83234, 265.33496,\n",
+       "         265.30453],\n",
+       "        [265.6052 , 265.6468 , 265.736  , ..., 265.61053, 265.53055,\n",
+       "         265.7236 ],\n",
+       "        [265.90643, 265.90643, 265.90643, ..., 265.90643, 265.90643,\n",
+       "         265.90643]],\n",
+       "\n",
+       "       [[212.96765, 212.96765, 212.96765, ..., 212.96765, 212.96765,\n",
+       "         212.96765],\n",
+       "        [227.39067, 227.45868, 225.59088, ..., 228.0285 , 227.92722,\n",
+       "         227.8851 ],\n",
+       "        [228.12408, 227.8222 , 227.45256, ..., 229.52286, 229.08876,\n",
+       "         228.57202],\n",
+       "        ...,\n",
+       "        [263.1174 , 262.69617, 263.16614, ..., 262.4634 , 262.9137 ,\n",
+       "         262.76703],\n",
+       "        [260.8171 , 261.04578, 261.01935, ..., 261.011  , 260.5789 ,\n",
+       "         260.7901 ],\n",
+       "        [259.38904, 259.38904, 259.38904, ..., 259.38904, 259.38904,\n",
+       "         259.38904]]], shape=(10, 90, 144), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd2615b3-9e4c-46fa-9348-87ebad06c6c8' class='xr-section-summary-in' type='checkbox' checked /><label for='section-dd2615b3-9e4c-46fa-9348-87ebad06c6c8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>NASA/GISS (Goddard Institute for Space Studies) New York, NY</dd><dt><span>institute_id :</span></dt><dd>NASA-GISS</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>GISS-E2-H-Eh137Tcadf9a Atmosphere: GISS-E2; Ocean: H</dd><dt><span>model_id :</span></dt><dd>GISS-E2-H</dd><dt><span>forcing :</span></dt><dd>GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes orbital change - BC on snow - Nitrate aerosols)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p2</dd><dt><span>branch_time :</span></dt><dd>2490.0</dd><dt><span>contact :</span></dt><dd>Kenneth Lo (cdkkl@giss.nasa.gov)</dd><dt><span>references :</span></dt><dd>http://data.giss.nasa.gov/modelE/ar5</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>2</dd><dt><span>tracking_id :</span></dt><dd>d43050cd-5c43-4dc5-914a-f724463bc109</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-10-18T13:06:09Z</dd><dt><span>history :</span></dt><dd>2011-10-18T13:06:09Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>GISS-E2-H model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.7</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 524kB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 90, lon: 144)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 15.5 45.0 74.5 105.0 ... 227.5 258.0 288.5\n",
+       "  * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "  * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "    height     float64 8B 2.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 0.0 31.0 31.0 ... 273.0 273.0 304.0\n",
+       "    lat_bnds   (lat, bnds) float64 1kB -90.0 -88.0 -88.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 2kB 0.0 2.5 2.5 5.0 ... 357.5 357.5 360.0\n",
+       "    tas        (time, lat, lon) float32 518kB 246.9 246.9 246.9 ... 259.4 259.4\n",
+       "Attributes:\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh137Tcadf9a Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes or...\n",
+       "    parent_experiment_id:   piControl\n",
+       "    parent_experiment_rip:  r1i1p2\n",
+       "    branch_time:            2490.0\n",
+       "    contact:                Kenneth Lo (cdkkl@giss.nasa.gov)\n",
+       "    references:             http://data.giss.nasa.gov/modelE/ar5\n",
+       "    initialization_method:  1\n",
+       "    physics_version:        2\n",
+       "    tracking_id:            d43050cd-5c43-4dc5-914a-f724463bc109\n",
+       "    product:                output\n",
+       "    experiment:             historical\n",
+       "    frequency:              mon\n",
+       "    creation_date:          2011-10-18T13:06:09Z\n",
+       "    history:                2011-10-18T13:06:09Z CMOR rewrote data to comply ...\n",
+       "    Conventions:            CF-1.4\n",
+       "    project_id:             CMIP5\n",
+       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.5.7"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(10, 1, 90, 144)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"02_atmos_surface_air_temperature\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "lon = source[\"lon\"].values.astype(\"f8\")\n",
+    "lon_bnds = source[\"lon_bnds\"].values.astype(\"f8\")\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_bnds = source[\"time_bnds\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "height = np.array([float(source[\"height\"].values)], dtype=\"f8\")\n",
+    "height_units = source[\"height\"].attrs.get(\"units\", \"m\")\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "tas_source = source[\"tas\"].values.astype(\"f4\")\n",
+    "tas = np.where(np.isfinite(tas_source), tas_source, missing_value).astype(\"f4\")[:, None, :, :]\n",
+    "\n",
+    "print(tas.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/02_atmos_surface_air_temperature/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/tas/tavg-h2m-hxy-u/g999/v20260605/tas_tavg-h2m-hxy-u_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_195101-195110.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "cmor.load_table(\"CMIP7_atmos.json\")\n",
+    "\n",
+    "time_id = cmor.axis(\"time\", coord_vals=time, cell_bounds=time_bnds, units=time_units)\n",
+    "height_id = cmor.axis(\"height2m\", coord_vals=height, units=height_units)\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "lon_id = cmor.axis(\"longitude\", coord_vals=lon, cell_bounds=lon_bnds, units=\"degrees_east\")\n",
+    "\n",
+    "variable_name = \"tas_tavg-h2m-hxy-u\"\n",
+    "tas_id = cmor.variable(variable_name, \"K\", [time_id, height_id, lat_id, lon_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"atmos\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(tas_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(tas_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(tas_id, tas)\n",
+    "netcdf_path = Path(cmor.close(tas_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 524kB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 90, lon: 144)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 15.5 45.0 74.5 105.0 ... 227.5 258.0 288.5\n",
+       "  * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "  * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "    height     float64 8B 2.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 0.0 31.0 31.0 ... 273.0 273.0 304.0\n",
+       "    lat_bnds   (lat, bnds) float64 1kB -90.0 -88.0 -88.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 2kB 0.0 2.5 2.5 5.0 ... 357.5 357.5 360.0\n",
+       "    tas        (time, lat, lon) float32 518kB 246.9 246.9 246.9 ... 259.4 259.4\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      tas_tavg-h2m-hxy-u\n",
+       "    branding_suffix:       tavg-h2m-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:23Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:23Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/690c47b6-9792-4b4a-8b94-8ed784e21eae\n",
+       "    variable_id:           tas\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        h2m\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-05c1c6ec-4937-488a-bb22-aa811ce542a7' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-05c1c6ec-4937-488a-bb22-aa811ce542a7' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div></li><li class='xr-section-item'><input id='section-ec32c7df-ed1c-434d-95d4-5b4e39bc9993' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ec32c7df-ed1c-434d-95d4-5b4e39bc9993' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.5 45.0 74.5 ... 258.0 288.5</div><input id='attrs-90778208-c94d-4339-8468-7e867a6f764f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90778208-c94d-4339-8468-7e867a6f764f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e28a9d8d-364d-4fd6-9836-e7ede67beffc' class='xr-var-data-in' type='checkbox'><label for='data-e28a9d8d-364d-4fd6-9836-e7ede67beffc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1951-1-1</dd><dt><span>calendar :</span></dt><dd>365_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([ 15.5,  45. ,  74.5, 105. , 135.5, 166. , 196.5, 227.5, 258. , 288.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-319948dd-63ac-4ee0-bc28-2b1399b09320' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-319948dd-63ac-4ee0-bc28-2b1399b09320' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5915c25-bd41-4234-838d-338fc9836848' class='xr-var-data-in' type='checkbox'><label for='data-d5915c25-bd41-4234-838d-338fc9836848' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-e33e0ce8-0589-40d5-aa55-61caed59fbae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e33e0ce8-0589-40d5-aa55-61caed59fbae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66a7b047-7b11-48ca-9171-0a63faaf4789' class='xr-var-data-in' type='checkbox'><label for='data-66a7b047-7b11-48ca-9171-0a63faaf4789' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-61376632-10d3-4c68-90e3-fe2ee95319b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61376632-10d3-4c68-90e3-fe2ee95319b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb18077e-e33d-42e1-b1fb-eecea1cde4f8' class='xr-var-data-in' type='checkbox'><label for='data-eb18077e-e33d-42e1-b1fb-eecea1cde4f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4a9c0f4-58b5-467d-b871-fe7cc3d16e35' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f4a9c0f4-58b5-467d-b871-fe7cc3d16e35' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 31.0 31.0 ... 273.0 273.0 304.0</div><input id='attrs-679ee2ef-fed9-48ef-93fc-24a1520eeda8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-679ee2ef-fed9-48ef-93fc-24a1520eeda8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-107a1b27-1e2c-47b1-b706-7734bab562d2' class='xr-var-data-in' type='checkbox'><label for='data-107a1b27-1e2c-47b1-b706-7734bab562d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,  31.],\n",
+       "       [ 31.,  59.],\n",
+       "       [ 59.,  90.],\n",
+       "       [ 90., 120.],\n",
+       "       [120., 151.],\n",
+       "       [151., 181.],\n",
+       "       [181., 212.],\n",
+       "       [212., 243.],\n",
+       "       [243., 273.],\n",
+       "       [273., 304.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.0 -88.0 ... 88.0 90.0</div><input id='attrs-6aeb5d4f-57e0-42c3-8291-81458be1f0ea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6aeb5d4f-57e0-42c3-8291-81458be1f0ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3e135cd-6175-452e-a2fa-7f3d19fc16aa' class='xr-var-data-in' type='checkbox'><label for='data-e3e135cd-6175-452e-a2fa-7f3d19fc16aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -88.],\n",
+       "       [-88., -86.],\n",
+       "       [-86., -84.],\n",
+       "       [-84., -82.],\n",
+       "       [-82., -80.],\n",
+       "       [-80., -78.],\n",
+       "       [-78., -76.],\n",
+       "       [-76., -74.],\n",
+       "       [-74., -72.],\n",
+       "       [-72., -70.],\n",
+       "       [-70., -68.],\n",
+       "       [-68., -66.],\n",
+       "       [-66., -64.],\n",
+       "       [-64., -62.],\n",
+       "       [-62., -60.],\n",
+       "       [-60., -58.],\n",
+       "       [-58., -56.],\n",
+       "       [-56., -54.],\n",
+       "       [-54., -52.],\n",
+       "       [-52., -50.],\n",
+       "...\n",
+       "       [ 50.,  52.],\n",
+       "       [ 52.,  54.],\n",
+       "       [ 54.,  56.],\n",
+       "       [ 56.,  58.],\n",
+       "       [ 58.,  60.],\n",
+       "       [ 60.,  62.],\n",
+       "       [ 62.,  64.],\n",
+       "       [ 64.,  66.],\n",
+       "       [ 66.,  68.],\n",
+       "       [ 68.,  70.],\n",
+       "       [ 70.,  72.],\n",
+       "       [ 72.,  74.],\n",
+       "       [ 74.,  76.],\n",
+       "       [ 76.,  78.],\n",
+       "       [ 78.,  80.],\n",
+       "       [ 80.,  82.],\n",
+       "       [ 82.,  84.],\n",
+       "       [ 84.,  86.],\n",
+       "       [ 86.,  88.],\n",
+       "       [ 88.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 2.5 ... 357.5 357.5 360.0</div><input id='attrs-d3447a4f-4bc2-4688-a51d-316f19096875' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3447a4f-4bc2-4688-a51d-316f19096875' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e647470b-ad3a-4266-85c2-5bed61fd982a' class='xr-var-data-in' type='checkbox'><label for='data-e647470b-ad3a-4266-85c2-5bed61fd982a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0. ,   2.5],\n",
+       "       [  2.5,   5. ],\n",
+       "       [  5. ,   7.5],\n",
+       "       [  7.5,  10. ],\n",
+       "       [ 10. ,  12.5],\n",
+       "       [ 12.5,  15. ],\n",
+       "       [ 15. ,  17.5],\n",
+       "       [ 17.5,  20. ],\n",
+       "       [ 20. ,  22.5],\n",
+       "       [ 22.5,  25. ],\n",
+       "       [ 25. ,  27.5],\n",
+       "       [ 27.5,  30. ],\n",
+       "       [ 30. ,  32.5],\n",
+       "       [ 32.5,  35. ],\n",
+       "       [ 35. ,  37.5],\n",
+       "       [ 37.5,  40. ],\n",
+       "       [ 40. ,  42.5],\n",
+       "       [ 42.5,  45. ],\n",
+       "       [ 45. ,  47.5],\n",
+       "       [ 47.5,  50. ],\n",
+       "...\n",
+       "       [310. , 312.5],\n",
+       "       [312.5, 315. ],\n",
+       "       [315. , 317.5],\n",
+       "       [317.5, 320. ],\n",
+       "       [320. , 322.5],\n",
+       "       [322.5, 325. ],\n",
+       "       [325. , 327.5],\n",
+       "       [327.5, 330. ],\n",
+       "       [330. , 332.5],\n",
+       "       [332.5, 335. ],\n",
+       "       [335. , 337.5],\n",
+       "       [337.5, 340. ],\n",
+       "       [340. , 342.5],\n",
+       "       [342.5, 345. ],\n",
+       "       [345. , 347.5],\n",
+       "       [347.5, 350. ],\n",
+       "       [350. , 352.5],\n",
+       "       [352.5, 355. ],\n",
+       "       [355. , 357.5],\n",
+       "       [357.5, 360. ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>246.9 246.9 246.9 ... 259.4 259.4</div><input id='attrs-6e775ae5-f522-48d8-9cc7-b0aace2346dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e775ae5-f522-48d8-9cc7-b0aace2346dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31fb2ab6-9de9-446f-bfa5-665a4fcf4df7' class='xr-var-data-in' type='checkbox'><label for='data-31fb2ab6-9de9-446f-bfa5-665a4fcf4df7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:23Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;.</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[246.86728, 246.86728, 246.86728, ..., 246.86728, 246.86728,\n",
+       "         246.86728],\n",
+       "        [248.9035 , 248.54457, 248.41835, ..., 249.81686, 249.28986,\n",
+       "         249.04837],\n",
+       "        [249.00377, 247.89893, 247.59648, ..., 250.52367, 250.40804,\n",
+       "         249.95767],\n",
+       "        ...,\n",
+       "        [244.49625, 244.8527 , 244.9202 , ..., 244.34276, 244.54477,\n",
+       "         244.54547],\n",
+       "        [243.83018, 243.76509, 243.94258, ..., 243.30023, 243.545  ,\n",
+       "         243.58965],\n",
+       "        [240.78905, 240.78905, 240.78905, ..., 240.78905, 240.78905,\n",
+       "         240.78905]],\n",
+       "\n",
+       "       [[237.30267, 237.30267, 237.30267, ..., 237.30267, 237.30267,\n",
+       "         237.30267],\n",
+       "        [242.50592, 242.29816, 242.0082 , ..., 243.48294, 243.1406 ,\n",
+       "         242.75697],\n",
+       "        [244.73744, 244.23917, 243.90952, ..., 245.81609, 245.63405,\n",
+       "         245.1311 ],\n",
+       "...\n",
+       "        [265.2184 , 265.34525, 265.6025 , ..., 264.83234, 265.33496,\n",
+       "         265.30453],\n",
+       "        [265.6052 , 265.6468 , 265.736  , ..., 265.61053, 265.53055,\n",
+       "         265.7236 ],\n",
+       "        [265.90643, 265.90643, 265.90643, ..., 265.90643, 265.90643,\n",
+       "         265.90643]],\n",
+       "\n",
+       "       [[212.96765, 212.96765, 212.96765, ..., 212.96765, 212.96765,\n",
+       "         212.96765],\n",
+       "        [227.39067, 227.45868, 225.59088, ..., 228.0285 , 227.92722,\n",
+       "         227.8851 ],\n",
+       "        [228.12408, 227.8222 , 227.45256, ..., 229.52286, 229.08876,\n",
+       "         228.57202],\n",
+       "        ...,\n",
+       "        [263.1174 , 262.69617, 263.16614, ..., 262.4634 , 262.9137 ,\n",
+       "         262.76703],\n",
+       "        [260.8171 , 261.04578, 261.01935, ..., 261.011  , 260.5789 ,\n",
+       "         260.7901 ],\n",
+       "        [259.38904, 259.38904, 259.38904, ..., 259.38904, 259.38904,\n",
+       "         259.38904]]], shape=(10, 90, 144), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9aa9351a-0d22-42ac-9fef-3f07b9cc05c1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-9aa9351a-0d22-42ac-9fef-3f07b9cc05c1' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>u</dd><dt><span>branded_variable :</span></dt><dd>tas_tavg-h2m-hxy-u</dd><dt><span>branding_suffix :</span></dt><dd>tavg-h2m-hxy-u</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:23Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:23Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_atmos.json; Creation Date:(2026-04-21 15:01:29) MD5:6c425d5354e32ec5498084c927c982a9</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/690c47b6-9792-4b4a-8b94-8ed784e21eae</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>h2m</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 524kB\n",
+       "Dimensions:    (time: 10, bnds: 2, lat: 90, lon: 144)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 15.5 45.0 74.5 105.0 ... 227.5 258.0 288.5\n",
+       "  * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "  * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "    height     float64 8B 2.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 160B 0.0 31.0 31.0 ... 273.0 273.0 304.0\n",
+       "    lat_bnds   (lat, bnds) float64 1kB -90.0 -88.0 -88.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 2kB 0.0 2.5 2.5 5.0 ... 357.5 357.5 360.0\n",
+       "    tas        (time, lat, lon) float32 518kB 246.9 246.9 246.9 ... 259.4 259.4\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      tas_tavg-h2m-hxy-u\n",
+       "    branding_suffix:       tavg-h2m-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:23Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:23Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/690c47b6-9792-4b4a-8b94-8ed784e21eae\n",
+       "    variable_id:           tas\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        h2m\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x540 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(11, 5.4))\n",
+    "map_plot = Basemap(\n",
+    "    projection=\"cyl\",\n",
+    "    llcrnrlon=-180,\n",
+    "    urcrnrlon=180,\n",
+    "    llcrnrlat=-90,\n",
+    "    urcrnrlat=90,\n",
+    "    resolution=\"c\",\n",
+    "    ax=ax,\n",
+    ")\n",
+    "map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "lon_wrapped = ((ds[\"lon\"].values + 180.0) % 360.0) - 180.0\n",
+    "lon_order = np.argsort(lon_wrapped)\n",
+    "lon_grid, lat_grid = np.meshgrid(lon_wrapped[lon_order], ds[\"lat\"].values)\n",
+    "x, y = map_plot(lon_grid, lat_grid)\n",
+    "field = ds[\"tas\"].isel(time=0).values[:, lon_order]\n",
+    "mesh = map_plot.pcolormesh(x, y, field, shading=\"auto\", cmap=\"RdYlBu_r\")\n",
+    "map_plot.drawcoastlines(linewidth=0.7, color=\"0.15\")\n",
+    "map_plot.drawparallels(np.arange(-90, 91, 30), labels=[1, 0, 0, 0], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "map_plot.drawmeridians(np.arange(-180, 181, 60), labels=[0, 0, 0, 1], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "colorbar = map_plot.colorbar(mesh, location=\"right\", pad=\"5%\")\n",
+    "colorbar.set_label(\"K\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "ax.set_title(f\"CMIP7 tas at 2 m, {time_label}\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/03_pressure_level_air_temperature.ipynb b/notebooks/03_pressure_level_air_temperature.ipynb
new file mode 100644
index 00000000..3dd89ecb
--- /dev/null
+++ b/notebooks/03_pressure_level_air_temperature.ipynb
@@ -0,0 +1,1895 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Atmospheric Temperature On Pressure Levels\n",
+    "\n",
+    "Create a CMIP7 monthly air temperature file (`ta_tavg-p19-hxy-air`) on the requested 19 pressure levels."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"ta_Amon_E3SM-3-0_historical_r1i1p1f1_gr_187001-187002.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
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+       "  );\n",
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+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
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+       "  margin-bottom: 0;\n",
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+       "\n",
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+       "}\n",
+       "\n",
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+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
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+       "  padding-left: 0 !important;\n",
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+       "\n",
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+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
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+       "\n",
+       ".xr-section-summary > em {\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
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+       "}\n",
+       "\n",
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+       "  display: none;\n",
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+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
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+       "\n",
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+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
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+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
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+       "  font-weight: 900;\n",
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+       "\n",
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+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
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+       "  display: none;\n",
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+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
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+       "\n",
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+       "\n",
+       ".xr-dim-list li {\n",
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+       "\n",
+       ".xr-dim-list:after {\n",
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+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
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+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
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+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:    (time: 2, bnds: 2, lat: 180, lon: 360, plev: 19)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 16B 7.316e+03 7.345e+03\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 3kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "  * plev       (plev) float64 152B 1e+05 9.25e+04 8.5e+04 ... 1e+03 500.0 100.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 32B 7.3e+03 7.331e+03 7.331e+03 7.359e+03\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 6kB 0.0 1.0 1.0 2.0 ... 359.0 359.0 360.0\n",
+       "    ta         (time, plev, lat, lon) float32 10MB nan nan nan ... 269.4 269.4\n",
+       "Attributes:\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    branch_time_in_parent:  18250.0\n",
+       "    creation_date:          2025-08-10T17:00:06Z\n",
+       "    data contact:           E3SM-DATA-SUPPORT@LLNL.GOV\n",
+       "    data_specs_version:     01.00.33\n",
+       "    experiment:             all-forcing simulation of the recent past\n",
+       "    experiment_id:          historical\n",
+       "    external_variables:     areacella\n",
+       "    forcing_index:          1\n",
+       "    frequency:              mon\n",
+       "    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.E3SM-Project...\n",
+       "    grid:                   data regridded to a CMIP6 standard 1x1 degree lon...\n",
+       "    grid_label:             gr\n",
+       "    history:                2025-08-10T17:00:06Z ;rewrote data to be consiste...\n",
+       "    initialization_index:   1\n",
+       "    institution:            LLNL (Lawrence Livermore National Laboratory, Liv...\n",
+       "    institution_id:         E3SM-Project\n",
+       "    label:                  E3SM 3.0\n",
+       "    label_extended:         E3SM 3.0 (Energy Exascale Earth System Model)\n",
+       "    mip_era:                CMIP6\n",
+       "    nominal_resolution:     100 km\n",
+       "    parent_activity_id:     CMIP\n",
+       "    parent_experiment_id:   piControl\n",
+       "    parent_mip_era:         CMIP6\n",
+       "    parent_source_id:       E3SM-3-0\n",
+       "    parent_time_units:      days since 0001-01-01\n",
+       "    parent_variant_label:   r1i1p1f1\n",
+       "    physics_index:          1\n",
+       "    product:                model-output\n",
+       "    project PI:             Dr. Peter Caldwell (caldwell19@llnl.gov), Dr. Dav...\n",
+       "    realization_index:      1\n",
+       "    realm:                  atmos\n",
+       "    references:             Xie, S., and co-authors, 2025: The Energy Exascal...\n",
+       "    release_year:           2024\n",
+       "    source:                 E3SM 3.0 (2025): \\naerosol: MAM5 w/ prognostic st...\n",
+       "    source_id:              E3SM-3-0\n",
+       "    source_type:            AOGCM AER\n",
+       "    sub_experiment:         none\n",
+       "    sub_experiment_id:      none\n",
+       "    table_id:               Amon\n",
+       "    table_info:             Creation Date:(18 November 2020) MD5:4945869d85ef...\n",
+       "    title:                  E3SM-3-0 output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/e908eefe-4329-4f97-9de6-8b2dd3a78be0\n",
+       "    variable_id:            ta\n",
+       "    variant_label:          r1i1p1f1\n",
+       "    version:                v20250810\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.11.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-58d3fae0-480a-4fc3-8f59-5e9897b910f4' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-58d3fae0-480a-4fc3-8f59-5e9897b910f4' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>plev</span>: 19</li></ul></div></li><li class='xr-section-item'><input id='section-520849fc-9ea0-4f0f-bde3-24fc7da769fb' class='xr-section-summary-in' type='checkbox' checked /><label for='section-520849fc-9ea0-4f0f-bde3-24fc7da769fb' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.316e+03 7.345e+03</div><input id='attrs-cc877288-726c-4863-8bde-018751f33289' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc877288-726c-4863-8bde-018751f33289' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-141209ce-5f7d-4b55-8607-7eb2b8c5b925' class='xr-var-data-in' type='checkbox'><label for='data-141209ce-5f7d-4b55-8607-7eb2b8c5b925' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-01-01 00:00:00</dd><dt><span>calendar :</span></dt><dd>noleap</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([7315.5, 7345. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-991ad64e-2ccb-4a85-8516-9f9a32c82b05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-991ad64e-2ccb-4a85-8516-9f9a32c82b05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0468c66-304f-4c19-90b0-58978ad74c59' class='xr-var-data-in' type='checkbox'><label for='data-f0468c66-304f-4c19-90b0-58978ad74c59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-e9ec1ce3-4aea-4896-9066-c2e51e4243ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9ec1ce3-4aea-4896-9066-c2e51e4243ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7974fe58-369d-4293-a4af-785fb2b6121c' class='xr-var-data-in' type='checkbox'><label for='data-7974fe58-369d-4293-a4af-785fb2b6121c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], shape=(360,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05 9.25e+04 ... 500.0 100.0</div><input id='attrs-ea90f264-d338-4bd3-ad2d-2a94f412f50c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea90f264-d338-4bd3-ad2d-2a94f412f50c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-154327ac-88fa-4abf-b0d3-d78f43ad920e' class='xr-var-data-in' type='checkbox'><label for='data-154327ac-88fa-4abf-b0d3-d78f43ad920e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([100000.,  92500.,  85000.,  70000.,  60000.,  50000.,  40000.,  30000.,\n",
+       "        25000.,  20000.,  15000.,  10000.,   7000.,   5000.,   3000.,   2000.,\n",
+       "         1000.,    500.,    100.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-91b5f893-4f1c-48b0-99cb-bed34bdf9af1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-91b5f893-4f1c-48b0-99cb-bed34bdf9af1' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.3e+03 7.331e+03 ... 7.359e+03</div><input id='attrs-a91d4e8e-e648-4fb0-a98e-900bcac48801' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a91d4e8e-e648-4fb0-a98e-900bcac48801' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd889e5-5459-44ee-8a52-2919cd59ba7c' class='xr-var-data-in' type='checkbox'><label for='data-6dd889e5-5459-44ee-8a52-2919cd59ba7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7300., 7331.],\n",
+       "       [7331., 7359.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -89.0 ... 89.0 90.0</div><input id='attrs-47649cc1-7e25-4eaf-9301-6f75011a7a06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-47649cc1-7e25-4eaf-9301-6f75011a7a06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8de7487c-c86d-4b88-adb8-b694b6b1db91' class='xr-var-data-in' type='checkbox'><label for='data-8de7487c-c86d-4b88-adb8-b694b6b1db91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
+       "       [-89., -88.],\n",
+       "       [-88., -87.],\n",
+       "       [-87., -86.],\n",
+       "       [-86., -85.],\n",
+       "       [-85., -84.],\n",
+       "       [-84., -83.],\n",
+       "       [-83., -82.],\n",
+       "       [-82., -81.],\n",
+       "       [-81., -80.],\n",
+       "       [-80., -79.],\n",
+       "       [-79., -78.],\n",
+       "       [-78., -77.],\n",
+       "       [-77., -76.],\n",
+       "       [-76., -75.],\n",
+       "       [-75., -74.],\n",
+       "       [-74., -73.],\n",
+       "       [-73., -72.],\n",
+       "       [-72., -71.],\n",
+       "       [-71., -70.],\n",
+       "...\n",
+       "       [ 70.,  71.],\n",
+       "       [ 71.,  72.],\n",
+       "       [ 72.,  73.],\n",
+       "       [ 73.,  74.],\n",
+       "       [ 74.,  75.],\n",
+       "       [ 75.,  76.],\n",
+       "       [ 76.,  77.],\n",
+       "       [ 77.,  78.],\n",
+       "       [ 78.,  79.],\n",
+       "       [ 79.,  80.],\n",
+       "       [ 80.,  81.],\n",
+       "       [ 81.,  82.],\n",
+       "       [ 82.,  83.],\n",
+       "       [ 83.,  84.],\n",
+       "       [ 84.,  85.],\n",
+       "       [ 85.,  86.],\n",
+       "       [ 86.,  87.],\n",
+       "       [ 87.,  88.],\n",
+       "       [ 88.,  89.],\n",
+       "       [ 89.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 1.0 ... 359.0 359.0 360.0</div><input id='attrs-1fae377c-24a2-4f91-abb0-7d199b9aa7c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1fae377c-24a2-4f91-abb0-7d199b9aa7c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69273610-87c0-41da-aa72-96904398d23e' class='xr-var-data-in' type='checkbox'><label for='data-69273610-87c0-41da-aa72-96904398d23e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,   1.],\n",
+       "       [  1.,   2.],\n",
+       "       [  2.,   3.],\n",
+       "       [  3.,   4.],\n",
+       "       [  4.,   5.],\n",
+       "       [  5.,   6.],\n",
+       "       [  6.,   7.],\n",
+       "       [  7.,   8.],\n",
+       "       [  8.,   9.],\n",
+       "       [  9.,  10.],\n",
+       "       [ 10.,  11.],\n",
+       "       [ 11.,  12.],\n",
+       "       [ 12.,  13.],\n",
+       "       [ 13.,  14.],\n",
+       "       [ 14.,  15.],\n",
+       "       [ 15.,  16.],\n",
+       "       [ 16.,  17.],\n",
+       "       [ 17.,  18.],\n",
+       "       [ 18.,  19.],\n",
+       "       [ 19.,  20.],\n",
+       "...\n",
+       "       [340., 341.],\n",
+       "       [341., 342.],\n",
+       "       [342., 343.],\n",
+       "       [343., 344.],\n",
+       "       [344., 345.],\n",
+       "       [345., 346.],\n",
+       "       [346., 347.],\n",
+       "       [347., 348.],\n",
+       "       [348., 349.],\n",
+       "       [349., 350.],\n",
+       "       [350., 351.],\n",
+       "       [351., 352.],\n",
+       "       [352., 353.],\n",
+       "       [353., 354.],\n",
+       "       [354., 355.],\n",
+       "       [355., 356.],\n",
+       "       [356., 357.],\n",
+       "       [357., 358.],\n",
+       "       [358., 359.],\n",
+       "       [359., 360.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ta</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... 269.4 269.4 269.4</div><input id='attrs-74cadced-bb45-4c02-a379-7d105b4b4d29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74cadced-bb45-4c02-a379-7d105b4b4d29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6a69731-bf55-4536-bff0-fbc51813cf7c' class='xr-var-data-in' type='checkbox'><label for='data-b6a69731-bf55-4536-bff0-fbc51813cf7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Air Temperature</dd><dt><span>comment :</span></dt><dd>Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         ...,\n",
+       "         [248.62799, 248.62799, 248.62799, ..., 247.47401, 247.47401,\n",
+       "          247.47401],\n",
+       "         [248.55006, 248.54996, 248.54979, ..., 247.536  , 247.53587,\n",
+       "          247.53581],\n",
+       "         [248.4412 , 248.4412 , 248.4412 , ..., 247.61282, 247.61282,\n",
+       "          247.61282]],\n",
+       "\n",
+       "        [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "...\n",
+       "         [230.53004, 230.53004, 230.53004, ..., 230.00777, 230.00777,\n",
+       "          230.00777],\n",
+       "         [230.58401, 230.58408, 230.58418, ..., 230.0691 , 230.06897,\n",
+       "          230.06891],\n",
+       "         [230.65952, 230.65952, 230.65952, ..., 230.15445, 230.15445,\n",
+       "          230.15445]],\n",
+       "\n",
+       "        [[269.41315, 269.41315, 269.41315, ..., 269.38086, 269.38086,\n",
+       "          269.38086],\n",
+       "         [269.2813 , 269.2814 , 269.28162, ..., 269.21027, 269.21   ,\n",
+       "          269.20984],\n",
+       "         [269.18707, 269.18707, 269.18707, ..., 269.08765, 269.08765,\n",
+       "          269.08765],\n",
+       "         ...,\n",
+       "         [271.54065, 271.54065, 271.54065, ..., 270.91687, 270.91687,\n",
+       "          270.91687],\n",
+       "         [270.9006 , 270.89993, 270.89853, ..., 270.28284, 270.2842 ,\n",
+       "          270.2849 ],\n",
+       "         [270.00507, 270.00507, 270.00507, ..., 269.40063, 269.40063,\n",
+       "          269.40063]]]], shape=(2, 19, 180, 360), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e8b0e85a-eacc-4069-b4e1-70b66e85a5ec' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e8b0e85a-eacc-4069-b4e1-70b66e85a5ec' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(51)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>18250.0</dd><dt><span>creation_date :</span></dt><dd>2025-08-10T17:00:06Z</dd><dt><span>data contact :</span></dt><dd>E3SM-DATA-SUPPORT@LLNL.GOV</dd><dt><span>data_specs_version :</span></dt><dd>01.00.33</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.E3SM-Project.E3SM-3-0.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>data regridded to a CMIP6 standard 1x1 degree lonxlat grid from the native grid using an area-average preserving method.</dd><dt><span>grid_label :</span></dt><dd>gr</dd><dt><span>history :</span></dt><dd>2025-08-10T17:00:06Z ;rewrote data to be consistent with CMIP for variable ta found in table Amon.;\n",
+       "v3.LR.historical_0051</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>LLNL (Lawrence Livermore National Laboratory, Livermore, CA 94550, USA); ANL (Argonne National Laboratory, Argonne, IL 60439, USA); BNL (Brookhaven National Laboratory, Upton, NY 11973, USA); LANL (Los Alamos National Laboratory, Los Alamos, NM 87545, USA); LBNL (Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA); ORNL (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA); PNNL (Pacific Northwest National Laboratory, Richland, WA 99352, USA); SNL (Sandia National Laboratories, Albuquerque, NM 87185, USA). Mailing address: LLNL Climate Program, c/o David C. Bader, Principal Investigator, L-103, 7000 East Avenue, Livermore, CA 94550, USA</dd><dt><span>institution_id :</span></dt><dd>E3SM-Project</dd><dt><span>label :</span></dt><dd>E3SM 3.0</dd><dt><span>label_extended :</span></dt><dd>E3SM 3.0 (Energy Exascale Earth System Model)</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>E3SM-3-0</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project PI :</span></dt><dd>Dr. Peter Caldwell (caldwell19@llnl.gov), Dr. Dave Bader (PI until Feb 2025)</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>references :</span></dt><dd>Xie, S., and co-authors, 2025: The Energy Exascale Earth System Model Version 3. Part I: Overview of the Atmospheric Component. ESS Open Archive. April 13, 2025. in review with JAMES; Golaz, J.-C. and co-authors, 2025: The Energy Exascale Earth System Model version 3. Part II: Overview of the coupled system. JAMES, in review concurrent to data publication</dd><dt><span>release_year :</span></dt><dd>2024</dd><dt><span>source :</span></dt><dd>E3SM 3.0 (2025): \n",
+       "aerosol: MAM5 w/ prognostic stratospheric aerosols (atmos physics grid)\n",
+       "atmos: EAM (E3SMv3.0, cubed sphere spectral-element; 5400 els., 30x30 per cube face. Dynamics: degree 3 (p=3) polynomials within each spectral els., 112 km ave. resolution. Physics: 2x2 finite volume cells within each spectral els., 1.5 degree (168 km) average grid spacing; 80 vertical layers w/ top at 60 km)\n",
+       "atmosChem: Troposphere UC Irvine interactive chemistry module. Stratosphere linearized interactive ozone (LINOZ v3) (atmos physics grid)\n",
+       "land: ELM (E3SMv3.0, 0.5 deg lat/lon grid, dynamic vegetation growth model), MOSART (E3SMv3.0, 0.5 deg lat/lon grid)\n",
+       "landIce: none\n",
+       "ocean: MPAS-Ocean (E3SMv3.0, new IcoswISC30E3r5 mesh, nearly uniform 30 km mesh w/ Ice-Shelf Cavities (wISC) around Antarctica and has 64 vertical layers.)\n",
+       "ocnBgchem: none\n",
+       "seaIce: MPAS-Seaice (E3SMv3.0, MPAS-Ocean grid; the CICE Consortium&#x27;s Icepack as the default sea ice column physics)</dd><dt><span>source_id :</span></dt><dd>E3SM-3-0</dd><dt><span>source_type :</span></dt><dd>AOGCM AER</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(18 November 2020) MD5:4945869d85ef80414f20dc7dc0e4c705</dd><dt><span>title :</span></dt><dd>E3SM-3-0 output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/e908eefe-4329-4f97-9de6-8b2dd3a78be0</dd><dt><span>variable_id :</span></dt><dd>ta</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>version :</span></dt><dd>v20250810</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by E3SM-Project is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https://pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.11.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:    (time: 2, bnds: 2, lat: 180, lon: 360, plev: 19)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 16B 7.316e+03 7.345e+03\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 3kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "  * plev       (plev) float64 152B 1e+05 9.25e+04 8.5e+04 ... 1e+03 500.0 100.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 32B 7.3e+03 7.331e+03 7.331e+03 7.359e+03\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 6kB 0.0 1.0 1.0 2.0 ... 359.0 359.0 360.0\n",
+       "    ta         (time, plev, lat, lon) float32 10MB nan nan nan ... 269.4 269.4\n",
+       "Attributes:\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    branch_time_in_parent:  18250.0\n",
+       "    creation_date:          2025-08-10T17:00:06Z\n",
+       "    data contact:           E3SM-DATA-SUPPORT@LLNL.GOV\n",
+       "    data_specs_version:     01.00.33\n",
+       "    experiment:             all-forcing simulation of the recent past\n",
+       "    experiment_id:          historical\n",
+       "    external_variables:     areacella\n",
+       "    forcing_index:          1\n",
+       "    frequency:              mon\n",
+       "    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.E3SM-Project...\n",
+       "    grid:                   data regridded to a CMIP6 standard 1x1 degree lon...\n",
+       "    grid_label:             gr\n",
+       "    history:                2025-08-10T17:00:06Z ;rewrote data to be consiste...\n",
+       "    initialization_index:   1\n",
+       "    institution:            LLNL (Lawrence Livermore National Laboratory, Liv...\n",
+       "    institution_id:         E3SM-Project\n",
+       "    label:                  E3SM 3.0\n",
+       "    label_extended:         E3SM 3.0 (Energy Exascale Earth System Model)\n",
+       "    mip_era:                CMIP6\n",
+       "    nominal_resolution:     100 km\n",
+       "    parent_activity_id:     CMIP\n",
+       "    parent_experiment_id:   piControl\n",
+       "    parent_mip_era:         CMIP6\n",
+       "    parent_source_id:       E3SM-3-0\n",
+       "    parent_time_units:      days since 0001-01-01\n",
+       "    parent_variant_label:   r1i1p1f1\n",
+       "    physics_index:          1\n",
+       "    product:                model-output\n",
+       "    project PI:             Dr. Peter Caldwell (caldwell19@llnl.gov), Dr. Dav...\n",
+       "    realization_index:      1\n",
+       "    realm:                  atmos\n",
+       "    references:             Xie, S., and co-authors, 2025: The Energy Exascal...\n",
+       "    release_year:           2024\n",
+       "    source:                 E3SM 3.0 (2025): \\naerosol: MAM5 w/ prognostic st...\n",
+       "    source_id:              E3SM-3-0\n",
+       "    source_type:            AOGCM AER\n",
+       "    sub_experiment:         none\n",
+       "    sub_experiment_id:      none\n",
+       "    table_id:               Amon\n",
+       "    table_info:             Creation Date:(18 November 2020) MD5:4945869d85ef...\n",
+       "    title:                  E3SM-3-0 output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/e908eefe-4329-4f97-9de6-8b2dd3a78be0\n",
+       "    variable_id:            ta\n",
+       "    variant_label:          r1i1p1f1\n",
+       "    version:                v20250810\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.11.0"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 19, 180, 360)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"03_pressure_level_air_temperature\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "lon = source[\"lon\"].values.astype(\"f8\")\n",
+    "lon_bnds = source[\"lon_bnds\"].values.astype(\"f8\")\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_bnds = source[\"time_bnds\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "plev = source[\"plev\"].values.astype(\"f8\")\n",
+    "plev_units = source[\"plev\"].attrs.get(\"units\", \"Pa\")\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "ta_source = source[\"ta\"].values.astype(\"f4\")\n",
+    "ta = np.where(np.isfinite(ta_source), ta_source, missing_value).astype(\"f4\")\n",
+    "\n",
+    "print(ta.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/03_pressure_level_air_temperature/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/ta/tavg-p19-hxy-air/g999/v20260605/ta_tavg-p19-hxy-air_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_187001-187002.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "cmor.load_table(\"CMIP7_atmos.json\")\n",
+    "\n",
+    "time_id = cmor.axis(\"time\", coord_vals=time, cell_bounds=time_bnds, units=time_units)\n",
+    "plev_id = cmor.axis(\"plev19\", coord_vals=plev, units=plev_units)\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "lon_id = cmor.axis(\"longitude\", coord_vals=lon, cell_bounds=lon_bnds, units=\"degrees_east\")\n",
+    "\n",
+    "variable_name = \"ta_tavg-p19-hxy-air\"\n",
+    "ta_id = cmor.variable(variable_name, \"K\", [time_id, plev_id, lat_id, lon_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"atmos\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(ta_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(ta_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(ta_id, ta)\n",
+    "netcdf_path = Path(cmor.close(ta_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:    (time: 2, bnds: 2, lat: 180, lon: 360, plev: 19)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 16B 7.316e+03 7.345e+03\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 3kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "  * plev       (plev) float64 152B 1e+05 9.25e+04 8.5e+04 ... 1e+03 500.0 100.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 32B 7.3e+03 7.331e+03 7.331e+03 7.359e+03\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 6kB 0.0 1.0 1.0 2.0 ... 359.0 359.0 360.0\n",
+       "    ta         (time, plev, lat, lon) float32 10MB nan nan nan ... 269.4 269.4\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            air\n",
+       "    branded_variable:      ta_tavg-p19-hxy-air\n",
+       "    branding_suffix:       tavg-p19-hxy-air\n",
+       "    creation_date:         2026-06-05T21:59:27Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:27Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/68194740-6201-4c23-8c14-40acf6955be7\n",
+       "    variable_id:           ta\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        p19\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0398d008-ff1e-48f4-9b23-43ed76e99cb4' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-0398d008-ff1e-48f4-9b23-43ed76e99cb4' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>plev</span>: 19</li></ul></div></li><li class='xr-section-item'><input id='section-f0a366ce-7633-4d3d-abc8-13a2c3e81018' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f0a366ce-7633-4d3d-abc8-13a2c3e81018' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.316e+03 7.345e+03</div><input id='attrs-601a919e-25b4-4747-91b2-df21e72fd7a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-601a919e-25b4-4747-91b2-df21e72fd7a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ef9e98e-8ce8-454b-ac0c-daf90054bbb8' class='xr-var-data-in' type='checkbox'><label for='data-9ef9e98e-8ce8-454b-ac0c-daf90054bbb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-01-01 00:00:00</dd><dt><span>calendar :</span></dt><dd>noleap</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([7315.5, 7345. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-29a131ad-19ae-4c04-a7f3-2e583a447179' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29a131ad-19ae-4c04-a7f3-2e583a447179' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f56cbfd4-0c58-4a27-8854-7838c4d13b9b' class='xr-var-data-in' type='checkbox'><label for='data-f56cbfd4-0c58-4a27-8854-7838c4d13b9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-c52e12cb-8f0d-433d-988c-054c7cd6b055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c52e12cb-8f0d-433d-988c-054c7cd6b055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3708618-e426-4d5b-b8e7-ac68a4f3461b' class='xr-var-data-in' type='checkbox'><label for='data-d3708618-e426-4d5b-b8e7-ac68a4f3461b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], shape=(360,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05 9.25e+04 ... 500.0 100.0</div><input id='attrs-7873d942-b54b-47fc-bcb3-ae3e4f6f0f6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7873d942-b54b-47fc-bcb3-ae3e4f6f0f6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fbf81ec-b5e0-4776-8f22-4c6290d7b033' class='xr-var-data-in' type='checkbox'><label for='data-5fbf81ec-b5e0-4776-8f22-4c6290d7b033' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>Pressure Levels (19)</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([100000.,  92500.,  85000.,  70000.,  60000.,  50000.,  40000.,  30000.,\n",
+       "        25000.,  20000.,  15000.,  10000.,   7000.,   5000.,   3000.,   2000.,\n",
+       "         1000.,    500.,    100.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7fa85a65-a439-41d5-983f-36d51dc485ea' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7fa85a65-a439-41d5-983f-36d51dc485ea' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.3e+03 7.331e+03 ... 7.359e+03</div><input id='attrs-d1c8b55c-23c5-4cfd-8ccb-db5a124e0890' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d1c8b55c-23c5-4cfd-8ccb-db5a124e0890' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f8d2519-4d0a-4d3c-afe0-e94fa7344bac' class='xr-var-data-in' type='checkbox'><label for='data-4f8d2519-4d0a-4d3c-afe0-e94fa7344bac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7300., 7331.],\n",
+       "       [7331., 7359.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -89.0 ... 89.0 90.0</div><input id='attrs-b47ffbf8-6d2a-4e7d-b697-b9ca68fa0357' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b47ffbf8-6d2a-4e7d-b697-b9ca68fa0357' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fcb5b85-306d-4bc1-94e7-e59e32d067f8' class='xr-var-data-in' type='checkbox'><label for='data-2fcb5b85-306d-4bc1-94e7-e59e32d067f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
+       "       [-89., -88.],\n",
+       "       [-88., -87.],\n",
+       "       [-87., -86.],\n",
+       "       [-86., -85.],\n",
+       "       [-85., -84.],\n",
+       "       [-84., -83.],\n",
+       "       [-83., -82.],\n",
+       "       [-82., -81.],\n",
+       "       [-81., -80.],\n",
+       "       [-80., -79.],\n",
+       "       [-79., -78.],\n",
+       "       [-78., -77.],\n",
+       "       [-77., -76.],\n",
+       "       [-76., -75.],\n",
+       "       [-75., -74.],\n",
+       "       [-74., -73.],\n",
+       "       [-73., -72.],\n",
+       "       [-72., -71.],\n",
+       "       [-71., -70.],\n",
+       "...\n",
+       "       [ 70.,  71.],\n",
+       "       [ 71.,  72.],\n",
+       "       [ 72.,  73.],\n",
+       "       [ 73.,  74.],\n",
+       "       [ 74.,  75.],\n",
+       "       [ 75.,  76.],\n",
+       "       [ 76.,  77.],\n",
+       "       [ 77.,  78.],\n",
+       "       [ 78.,  79.],\n",
+       "       [ 79.,  80.],\n",
+       "       [ 80.,  81.],\n",
+       "       [ 81.,  82.],\n",
+       "       [ 82.,  83.],\n",
+       "       [ 83.,  84.],\n",
+       "       [ 84.,  85.],\n",
+       "       [ 85.,  86.],\n",
+       "       [ 86.,  87.],\n",
+       "       [ 87.,  88.],\n",
+       "       [ 88.,  89.],\n",
+       "       [ 89.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 1.0 ... 359.0 359.0 360.0</div><input id='attrs-9857f326-6de7-46be-9595-76fa910c389f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9857f326-6de7-46be-9595-76fa910c389f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f72a47d0-1146-4b0e-a742-152208be86c6' class='xr-var-data-in' type='checkbox'><label for='data-f72a47d0-1146-4b0e-a742-152208be86c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,   1.],\n",
+       "       [  1.,   2.],\n",
+       "       [  2.,   3.],\n",
+       "       [  3.,   4.],\n",
+       "       [  4.,   5.],\n",
+       "       [  5.,   6.],\n",
+       "       [  6.,   7.],\n",
+       "       [  7.,   8.],\n",
+       "       [  8.,   9.],\n",
+       "       [  9.,  10.],\n",
+       "       [ 10.,  11.],\n",
+       "       [ 11.,  12.],\n",
+       "       [ 12.,  13.],\n",
+       "       [ 13.,  14.],\n",
+       "       [ 14.,  15.],\n",
+       "       [ 15.,  16.],\n",
+       "       [ 16.,  17.],\n",
+       "       [ 17.,  18.],\n",
+       "       [ 18.,  19.],\n",
+       "       [ 19.,  20.],\n",
+       "...\n",
+       "       [340., 341.],\n",
+       "       [341., 342.],\n",
+       "       [342., 343.],\n",
+       "       [343., 344.],\n",
+       "       [344., 345.],\n",
+       "       [345., 346.],\n",
+       "       [346., 347.],\n",
+       "       [347., 348.],\n",
+       "       [348., 349.],\n",
+       "       [349., 350.],\n",
+       "       [350., 351.],\n",
+       "       [351., 352.],\n",
+       "       [352., 353.],\n",
+       "       [353., 354.],\n",
+       "       [354., 355.],\n",
+       "       [355., 356.],\n",
+       "       [356., 357.],\n",
+       "       [357., 358.],\n",
+       "       [358., 359.],\n",
+       "       [359., 360.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ta</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... 269.4 269.4 269.4</div><input id='attrs-4dc209ee-c211-445c-8207-1f5661cd35ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dc209ee-c211-445c-8207-1f5661cd35ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95d4841e-e022-4695-b361-4897473407d5' class='xr-var-data-in' type='checkbox'><label for='data-95d4841e-e022-4695-b361-4897473407d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean where air</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         ...,\n",
+       "         [248.62799, 248.62799, 248.62799, ..., 247.47401, 247.47401,\n",
+       "          247.47401],\n",
+       "         [248.55006, 248.54996, 248.54979, ..., 247.536  , 247.53587,\n",
+       "          247.53581],\n",
+       "         [248.4412 , 248.4412 , 248.4412 , ..., 247.61282, 247.61282,\n",
+       "          247.61282]],\n",
+       "\n",
+       "        [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "         [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "                nan],\n",
+       "...\n",
+       "         [230.53004, 230.53004, 230.53004, ..., 230.00777, 230.00777,\n",
+       "          230.00777],\n",
+       "         [230.58401, 230.58408, 230.58418, ..., 230.0691 , 230.06897,\n",
+       "          230.06891],\n",
+       "         [230.65952, 230.65952, 230.65952, ..., 230.15445, 230.15445,\n",
+       "          230.15445]],\n",
+       "\n",
+       "        [[269.41315, 269.41315, 269.41315, ..., 269.38086, 269.38086,\n",
+       "          269.38086],\n",
+       "         [269.2813 , 269.2814 , 269.28162, ..., 269.21027, 269.21   ,\n",
+       "          269.20984],\n",
+       "         [269.18707, 269.18707, 269.18707, ..., 269.08765, 269.08765,\n",
+       "          269.08765],\n",
+       "         ...,\n",
+       "         [271.54065, 271.54065, 271.54065, ..., 270.91687, 270.91687,\n",
+       "          270.91687],\n",
+       "         [270.9006 , 270.89993, 270.89853, ..., 270.28284, 270.2842 ,\n",
+       "          270.2849 ],\n",
+       "         [270.00507, 270.00507, 270.00507, ..., 269.40063, 269.40063,\n",
+       "          269.40063]]]], shape=(2, 19, 180, 360), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4d22330-68c2-406c-8b9f-33bac52e9533' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a4d22330-68c2-406c-8b9f-33bac52e9533' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>air</dd><dt><span>branded_variable :</span></dt><dd>ta_tavg-p19-hxy-air</dd><dt><span>branding_suffix :</span></dt><dd>tavg-p19-hxy-air</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:27Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:27Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_atmos.json; Creation Date:(2026-04-21 15:01:29) MD5:6c425d5354e32ec5498084c927c982a9</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/68194740-6201-4c23-8c14-40acf6955be7</dd><dt><span>variable_id :</span></dt><dd>ta</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>p19</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:    (time: 2, bnds: 2, lat: 180, lon: 360, plev: 19)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 16B 7.316e+03 7.345e+03\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 3kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "  * plev       (plev) float64 152B 1e+05 9.25e+04 8.5e+04 ... 1e+03 500.0 100.0\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 32B 7.3e+03 7.331e+03 7.331e+03 7.359e+03\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 6kB 0.0 1.0 1.0 2.0 ... 359.0 359.0 360.0\n",
+       "    ta         (time, plev, lat, lon) float32 10MB nan nan nan ... 269.4 269.4\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            air\n",
+       "    branded_variable:      ta_tavg-p19-hxy-air\n",
+       "    branding_suffix:       tavg-p19-hxy-air\n",
+       "    creation_date:         2026-06-05T21:59:27Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:27Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/68194740-6201-4c23-8c14-40acf6955be7\n",
+       "    variable_id:           ta\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        p19\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1100x540 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(11, 5.4))\n",
+    "map_plot = Basemap(\n",
+    "    projection=\"cyl\",\n",
+    "    llcrnrlon=-180,\n",
+    "    urcrnrlon=180,\n",
+    "    llcrnrlat=-90,\n",
+    "    urcrnrlat=90,\n",
+    "    resolution=\"c\",\n",
+    "    ax=ax,\n",
+    ")\n",
+    "map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "lon_wrapped = ((ds[\"lon\"].values + 180.0) % 360.0) - 180.0\n",
+    "lon_order = np.argsort(lon_wrapped)\n",
+    "lon_grid, lat_grid = np.meshgrid(lon_wrapped[lon_order], ds[\"lat\"].values)\n",
+    "x, y = map_plot(lon_grid, lat_grid)\n",
+    "field = ds[\"ta\"].sel(plev=50000.0).isel(time=0).values[:, lon_order]\n",
+    "mesh = map_plot.pcolormesh(x, y, field, shading=\"auto\", cmap=\"RdYlBu_r\")\n",
+    "map_plot.drawcoastlines(linewidth=0.7, color=\"0.15\")\n",
+    "map_plot.drawparallels(np.arange(-90, 91, 30), labels=[1, 0, 0, 0], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "map_plot.drawmeridians(np.arange(-180, 181, 60), labels=[0, 0, 0, 1], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "colorbar = map_plot.colorbar(mesh, location=\"right\", pad=\"5%\")\n",
+    "colorbar.set_label(\"K\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "ax.set_title(f\"CMIP7 ta at 500 hPa, {time_label}\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/04_hybrid_sigma_humidity_tendency.ipynb b/notebooks/04_hybrid_sigma_humidity_tendency.ipynb
new file mode 100644
index 00000000..b66fc99f
--- /dev/null
+++ b/notebooks/04_hybrid_sigma_humidity_tendency.ipynb
@@ -0,0 +1,2285 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hybrid Sigma Humidity Tendency With Z-Factors\n",
+    "\n",
+    "Create a CMIP7 monthly humidity tendency file (`tnhusscpbl_tavg-al-hxy-u`) on a standard hybrid sigma pressure coordinate. This example reads source data with xarray, defines the vertical coordinate formula terms with CMOR zfactors, and stores surface pressure with the data variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"tnhusscpbl_CFmon_MIROC-ES2L_amip_r2i1p1f2_gn_197901-197905.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 7MB\n",
+       "Dimensions:     (time: 5, bnds: 2, lev: 40, lat: 64, lon: 128)\n",
+       "Coordinates:\n",
+       "  * time        (time) float64 40B 15.5 45.0 74.5 105.0 135.5\n",
+       "  * lev         (lev) float64 320B 0.9975 0.9915 0.983 ... 0.0106 0.002905\n",
+       "  * lat         (lat) float64 512B -87.86 -85.1 -82.31 ... 82.31 85.1 87.86\n",
+       "  * lon         (lon) float64 1kB 0.0 2.812 5.625 8.438 ... 351.6 354.4 357.2\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds   (time, bnds) float64 80B 0.0 31.0 31.0 ... 120.0 120.0 151.0\n",
+       "    lev_bnds    (lev, bnds) float64 640B 1.0 0.995 0.995 ... 0.007 0.007 0.0\n",
+       "    p0          float64 8B 1e+05\n",
+       "    a           (lev) float64 320B 0.001113 0.003782 ... 0.0106 0.002905\n",
+       "    b           (lev) float64 320B 0.9964 0.9877 0.9754 0.9595 ... 0.0 0.0 0.0\n",
+       "    ps          (time, lat, lon) float32 164kB 6.951e+04 6.928e+04 ... 1.029e+05\n",
+       "    a_bnds      (lev, bnds) float64 640B 0.0 0.002224 0.002224 ... 0.007 0.0\n",
+       "    b_bnds      (lev, bnds) float64 640B 1.0 0.9928 0.9928 ... 0.0 0.0 0.0\n",
+       "    lat_bnds    (lat, bnds) float64 1kB -90.0 -86.58 -86.58 ... 86.58 86.58 90.0\n",
+       "    lon_bnds    (lon, bnds) float64 2kB -1.406 1.406 1.406 ... 355.8 355.8 358.6\n",
+       "    tnhusscpbl  (time, lev, lat, lon) float32 7MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.7 CMIP-6.2\n",
+       "    activity_id:           CMIP\n",
+       "    branch_method:         no parent\n",
+       "    creation_date:         2020-08-15T22:41:28Z\n",
+       "    data_specs_version:    01.00.28\n",
+       "    experiment:            AMIP\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         2\n",
+       "    frequency:             mon\n",
+       "    further_info_url:      https://furtherinfo.es-doc.org/CMIP6.MIROC.MIROC-E...\n",
+       "    grid:                  native atmosphere T42 Gaussian grid\n",
+       "    grid_label:            gn\n",
+       "    history:               2020-08-15T22:41:28Z ; CMOR rewrote data to be con...\n",
+       "    initialization_index:  1\n",
+       "    institution:           JAMSTEC (Japan Agency for Marine-Earth Science and...\n",
+       "    institution_id:        MIROC\n",
+       "    mip_era:               CMIP6\n",
+       "    nominal_resolution:    500 km\n",
+       "    parent_activity_id:    no parent\n",
+       "    parent_experiment_id:  no parent\n",
+       "    physics_index:         1\n",
+       "    product:               model-output\n",
+       "    realization_index:     2\n",
+       "    realm:                 atmos\n",
+       "    source:                MIROC-ES2L (2018): \\naerosol: SPRINTARS6.0\\natmos:...\n",
+       "    source_id:             MIROC-ES2L\n",
+       "    source_type:           AGCM AER BGC\n",
+       "    sub_experiment:        none\n",
+       "    sub_experiment_id:     none\n",
+       "    table_id:              CFmon\n",
+       "    table_info:            Creation Date:(06 November 2018) MD5:af8da38b788c1...\n",
+       "    title:                 MIROC-ES2L output prepared for CMIP6\n",
+       "    variable_id:           tnhusscpbl\n",
+       "    variant_label:         r2i1p1f2\n",
+       "    license:               CMIP6 model data produced by MIROC is licensed und...\n",
+       "    cmor_version:          3.3.2\n",
+       "    tracking_id:           hdl:21.14100/f575a148-89c0-40d7-bdd5-b67e0f73cf4a</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-789c7649-9d5e-4305-9fe9-a4672289dbc6' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-789c7649-9d5e-4305-9fe9-a4672289dbc6' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lev</span>: 40</li><li><span class='xr-has-index'>lat</span>: 64</li><li><span class='xr-has-index'>lon</span>: 128</li></ul></div></li><li class='xr-section-item'><input id='section-79779d50-4ef3-49c5-8155-4ad6fc6ce985' class='xr-section-summary-in' type='checkbox' checked /><label for='section-79779d50-4ef3-49c5-8155-4ad6fc6ce985' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.5 45.0 74.5 105.0 135.5</div><input id='attrs-e8ae87a3-b133-4f31-a130-e2237d89768e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8ae87a3-b133-4f31-a130-e2237d89768e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21b65d94-9f1d-42a7-bb08-11f89b9c38f7' class='xr-var-data-in' type='checkbox'><label for='data-21b65d94-9f1d-42a7-bb08-11f89b9c38f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1979-1-1</dd><dt><span>calendar :</span></dt><dd>gregorian</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([ 15.5,  45. ,  74.5, 105. , 135.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9975 0.9915 ... 0.0106 0.002905</div><input id='attrs-1d789098-b82c-49bd-80f0-369a6c126bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d789098-b82c-49bd-80f0-369a6c126bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e071d1-58bf-45d4-8974-69587a8bcd85' class='xr-var-data-in' type='checkbox'><label for='data-f2e071d1-58bf-45d4-8974-69587a8bcd85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>hybrid sigma pressure coordinate</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a b: b ps: ps</dd></dl></div><div class='xr-var-data'><pre>array([0.997499, 0.991499, 0.982997, 0.971996, 0.958493, 0.94199 , 0.922486,\n",
+       "       0.900483, 0.875977, 0.848972, 0.819967, 0.786951, 0.746923, 0.698885,\n",
+       "       0.642833, 0.574472, 0.501478, 0.43645 , 0.379852, 0.330596, 0.287725,\n",
+       "       0.250411, 0.21794 , 0.189681, 0.16508 , 0.143673, 0.125043, 0.108828,\n",
+       "       0.094716, 0.082434, 0.071745, 0.062441, 0.054278, 0.046937, 0.040158,\n",
+       "       0.033613, 0.026593, 0.018613, 0.010603, 0.002905])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-87.86 -85.1 -82.31 ... 85.1 87.86</div><input id='attrs-68c4fce4-9ba7-45c0-9640-ffd52e3f89f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68c4fce4-9ba7-45c0-9640-ffd52e3f89f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70bbc519-cb8c-4032-beac-471659e99833' class='xr-var-data-in' type='checkbox'><label for='data-70bbc519-cb8c-4032-beac-471659e99833' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-87.863799, -85.096527, -82.312913, -79.525607, -76.7369  , -73.947515,\n",
+       "       -71.157752, -68.367756, -65.577607, -62.787352, -59.99702 , -57.206632,\n",
+       "       -54.4162  , -51.625734, -48.835241, -46.044727, -43.254195, -40.463648,\n",
+       "       -37.67309 , -34.882521, -32.091944, -29.30136 , -26.510769, -23.720174,\n",
+       "       -20.929574, -18.138971, -15.348365, -12.557756,  -9.767146,  -6.976534,\n",
+       "        -4.185921,  -1.395307,   1.395307,   4.185921,   6.976534,   9.767146,\n",
+       "        12.557756,  15.348365,  18.138971,  20.929574,  23.720174,  26.510769,\n",
+       "        29.30136 ,  32.091944,  34.882521,  37.67309 ,  40.463648,  43.254195,\n",
+       "        46.044727,  48.835241,  51.625734,  54.4162  ,  57.206632,  59.99702 ,\n",
+       "        62.787352,  65.577607,  68.367756,  71.157752,  73.947515,  76.7369  ,\n",
+       "        79.525607,  82.312913,  85.096527,  87.863799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.812 5.625 ... 354.4 357.2</div><input id='attrs-740bea04-cd66-4ebe-a0eb-e663988ad5e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-740bea04-cd66-4ebe-a0eb-e663988ad5e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a1e6af9-6b39-4423-bf4b-458906923bac' class='xr-var-data-in' type='checkbox'><label for='data-5a1e6af9-6b39-4423-bf4b-458906923bac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.    ,   2.8125,   5.625 ,   8.4375,  11.25  ,  14.0625,  16.875 ,\n",
+       "        19.6875,  22.5   ,  25.3125,  28.125 ,  30.9375,  33.75  ,  36.5625,\n",
+       "        39.375 ,  42.1875,  45.    ,  47.8125,  50.625 ,  53.4375,  56.25  ,\n",
+       "        59.0625,  61.875 ,  64.6875,  67.5   ,  70.3125,  73.125 ,  75.9375,\n",
+       "        78.75  ,  81.5625,  84.375 ,  87.1875,  90.    ,  92.8125,  95.625 ,\n",
+       "        98.4375, 101.25  , 104.0625, 106.875 , 109.6875, 112.5   , 115.3125,\n",
+       "       118.125 , 120.9375, 123.75  , 126.5625, 129.375 , 132.1875, 135.    ,\n",
+       "       137.8125, 140.625 , 143.4375, 146.25  , 149.0625, 151.875 , 154.6875,\n",
+       "       157.5   , 160.3125, 163.125 , 165.9375, 168.75  , 171.5625, 174.375 ,\n",
+       "       177.1875, 180.    , 182.8125, 185.625 , 188.4375, 191.25  , 194.0625,\n",
+       "       196.875 , 199.6875, 202.5   , 205.3125, 208.125 , 210.9375, 213.75  ,\n",
+       "       216.5625, 219.375 , 222.1875, 225.    , 227.8125, 230.625 , 233.4375,\n",
+       "       236.25  , 239.0625, 241.875 , 244.6875, 247.5   , 250.3125, 253.125 ,\n",
+       "       255.9375, 258.75  , 261.5625, 264.375 , 267.1875, 270.    , 272.8125,\n",
+       "       275.625 , 278.4375, 281.25  , 284.0625, 286.875 , 289.6875, 292.5   ,\n",
+       "       295.3125, 298.125 , 300.9375, 303.75  , 306.5625, 309.375 , 312.1875,\n",
+       "       315.    , 317.8125, 320.625 , 323.4375, 326.25  , 329.0625, 331.875 ,\n",
+       "       334.6875, 337.5   , 340.3125, 343.125 , 345.9375, 348.75  , 351.5625,\n",
+       "       354.375 , 357.1875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f3324b6-896e-46c4-9f41-60c92805517f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0f3324b6-896e-46c4-9f41-60c92805517f' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 31.0 31.0 ... 120.0 120.0 151.0</div><input id='attrs-2439fade-f9ce-4549-9268-f673b51e25ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2439fade-f9ce-4549-9268-f673b51e25ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9993a621-eb67-469f-a4b8-517605a3207e' class='xr-var-data-in' type='checkbox'><label for='data-9993a621-eb67-469f-a4b8-517605a3207e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,  31.],\n",
+       "       [ 31.,  59.],\n",
+       "       [ 59.,  90.],\n",
+       "       [ 90., 120.],\n",
+       "       [120., 151.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.995 0.995 ... 0.007 0.007 0.0</div><input id='attrs-78f66408-bc4a-409e-ac11-8b7f45ebe4a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78f66408-bc4a-409e-ac11-8b7f45ebe4a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7375566e-4c0b-4d54-b0fd-821e9073f8e9' class='xr-var-data-in' type='checkbox'><label for='data-7375566e-4c0b-4d54-b0fd-821e9073f8e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd></dl></div><div class='xr-var-data'><pre>array([[1.        , 0.995     ],\n",
+       "       [0.995     , 0.98799998],\n",
+       "       [0.98799998, 0.97799999],\n",
+       "       [0.97799999, 0.96600002],\n",
+       "       [0.96600002, 0.95099998],\n",
+       "       [0.95099998, 0.93300003],\n",
+       "       [0.93300003, 0.912     ],\n",
+       "       [0.912     , 0.889     ],\n",
+       "       [0.889     , 0.86299998],\n",
+       "       [0.86299998, 0.83499998],\n",
+       "       [0.83499998, 0.80500001],\n",
+       "       [0.80500001, 0.76899999],\n",
+       "       [0.76899999, 0.72500002],\n",
+       "       [0.72500002, 0.67299998],\n",
+       "       [0.67299998, 0.61299998],\n",
+       "       [0.61299998, 0.53654999],\n",
+       "       [0.53654999, 0.46698001],\n",
+       "       [0.46698001, 0.40641999],\n",
+       "       [0.40641999, 0.35372001],\n",
+       "       [0.35372001, 0.30785   ],\n",
+       "       [0.30785   , 0.26793   ],\n",
+       "       [0.26793   , 0.23318   ],\n",
+       "       [0.23318   , 0.20295   ],\n",
+       "       [0.20295   , 0.17663001],\n",
+       "       [0.17663001, 0.15372001],\n",
+       "       [0.15372001, 0.13379   ],\n",
+       "       [0.13379   , 0.11644   ],\n",
+       "       [0.11644   , 0.10134   ],\n",
+       "       [0.10134   , 0.0882    ],\n",
+       "       [0.0882    , 0.076763  ],\n",
+       "       [0.076763  , 0.066809  ],\n",
+       "       [0.066809  , 0.058145  ],\n",
+       "       [0.058145  , 0.050475  ],\n",
+       "       [0.050475  , 0.043462  ],\n",
+       "       [0.043462  , 0.036917  ],\n",
+       "       [0.036917  , 0.030384  ],\n",
+       "       [0.030384  , 0.022927  ],\n",
+       "       [0.022927  , 0.014526  ],\n",
+       "       [0.014526  , 0.007     ],\n",
+       "       [0.007     , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05</div><input id='attrs-604bda88-d784-4399-be58-e5e3ad07bf00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-604bda88-d784-4399-be58-e5e3ad07bf00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c20ffb77-8232-485b-a44f-ce408c137298' class='xr-var-data-in' type='checkbox'><label for='data-c20ffb77-8232-485b-a44f-ce408c137298' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array(100000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001113 0.003782 ... 0.002905</div><input id='attrs-b2e2bca8-27f3-410a-90bb-d64d6efb1723' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2e2bca8-27f3-410a-90bb-d64d6efb1723' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b66307bb-9a2b-48f0-be6f-29c468a9e6fa' class='xr-var-data-in' type='checkbox'><label for='data-b66307bb-9a2b-48f0-be6f-29c468a9e6fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><pre>array([0.00111275, 0.00378219, 0.0075645 , 0.01245857, 0.01846599,\n",
+       "       0.0258086 , 0.03448657, 0.04427587, 0.05518012, 0.06719563,\n",
+       "       0.08010215, 0.09480408, 0.11264021, 0.13405917, 0.15908005,\n",
+       "       0.18977115, 0.22239427, 0.2515278 , 0.27720865, 0.30309604,\n",
+       "       0.2877251 , 0.25041144, 0.21794017, 0.18968127, 0.16508035,\n",
+       "       0.1436727 , 0.12504333, 0.10882762, 0.09471573, 0.08243426,\n",
+       "       0.07174488, 0.06244121, 0.05427773, 0.04693731, 0.04015774,\n",
+       "       0.03361269, 0.02659318, 0.01861324, 0.01060254, 0.00290465])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9964 0.9877 0.9754 ... 0.0 0.0</div><input id='attrs-abf66c3d-ebf4-4db7-a3f6-b0df3a34b5c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abf66c3d-ebf4-4db7-a3f6-b0df3a34b5c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d30bf7f7-d4a2-46e3-9d3b-f86c6c7db5ee' class='xr-var-data-in' type='checkbox'><label for='data-d30bf7f7-d4a2-46e3-9d3b-f86c6c7db5ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><pre>array([0.99638653, 0.98771632, 0.97543246, 0.95953703, 0.940027  ,\n",
+       "       0.91618115, 0.88799924, 0.85620666, 0.82079691, 0.78177685,\n",
+       "       0.73986518, 0.6921469 , 0.63428265, 0.56482565, 0.48375323,\n",
+       "       0.38470095, 0.27908337, 0.18492202, 0.10264368, 0.02749949,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.951e+04 6.928e+04 ... 1.029e+05</div><input id='attrs-ae396875-2c56-43d5-9098-5c340ab8aaa8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae396875-2c56-43d5-9098-5c340ab8aaa8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c0f374a-8ad5-41d9-989b-b17738215992' class='xr-var-data-in' type='checkbox'><label for='data-8c0f374a-8ad5-41d9-989b-b17738215992' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Air Pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>original_units :</span></dt><dd>hPa</dd><dt><span>history :</span></dt><dd>2020-08-15T22:41:28Z altered by CMOR: Converted units from &#x27;hPa&#x27; to &#x27;Pa&#x27;.</dd></dl></div><div class='xr-var-data'><pre>array([[[ 69506.68 ,  69276.34 ,  69050.01 , ...,  70217.68 ,\n",
+       "          69978.55 ,  69741.01 ],\n",
+       "        [ 70131.305,  69566.664,  69032.41 , ...,  71992.38 ,\n",
+       "          71346.164,  70724.734],\n",
+       "        [ 69113.99 ,  68264.625,  67517.63 , ...,  72280.305,\n",
+       "          71123.83 ,  70067.32 ],\n",
+       "        ...,\n",
+       "        [102419.91 , 102623.85 , 102737.43 , ..., 101161.06 ,\n",
+       "         101695.31 , 102113.6  ],\n",
+       "        [102910.98 , 102975.76 , 103014.15 , ..., 102552.67 ,\n",
+       "         102699.84 , 102819.8  ],\n",
+       "        [103155.71 , 103150.11 , 103142.12 , ..., 103156.51 ,\n",
+       "         103158.11 , 103158.11 ]],\n",
+       "\n",
+       "       [[ 69910.48 ,  69675.164,  69443.82 , ...,  70634.72 ,\n",
+       "          70390.66 ,  70148.98 ],\n",
+       "        [ 70598.14 ,  70024.96 ,  69482.77 , ...,  72486.24 ,\n",
+       "          71830.375,  71200.74 ],\n",
+       "        [ 69574.2  ,  68708.46 ,  67946.86 , ...,  72802.64 ,\n",
+       "          71624.48 ,  70547.266],\n",
+       "...\n",
+       "        [103368.234, 103566.87 , 103678.21 , ..., 102154.016,\n",
+       "         102668.21 , 103071.89 ],\n",
+       "        [103760.7  , 103823.17 , 103862.43 , ..., 103417.9  ,\n",
+       "         103558.07 , 103672.59 ],\n",
+       "        [103979.36 , 103973.76 , 103965.75 , ..., 103981.766,\n",
+       "         103983.36 , 103982.555]],\n",
+       "\n",
+       "       [[ 68441.375,  68197.09 ,  67957.55 , ...,  69196.28 ,\n",
+       "          68941.76 ,  68690.39 ],\n",
+       "        [ 69065.47 ,  68471.32 ,  67908.69 , ...,  71029.17 ,\n",
+       "          70345.97 ,  69691.14 ],\n",
+       "        [ 67980.4  ,  67089.164,  66306.68 , ...,  71308.914,\n",
+       "          70093.02 ,  68981.945],\n",
+       "        ...,\n",
+       "        [102202.45 , 102432.55 , 102581.484, ..., 100930.625,\n",
+       "         101457.01 , 101879.375],\n",
+       "        [102613.   , 102698.89 , 102761.94 , ..., 102212.695,\n",
+       "         102369.51 , 102503.47 ],\n",
+       "        [102897.48 , 102901.41 , 102903.77 , ..., 102873.05 ,\n",
+       "         102883.29 , 102891.95 ]]], shape=(5, 64, 128), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.002224 0.002224 ... 0.007 0.0</div><input id='attrs-d1b9c5de-147d-492e-b667-9c4d2cca4529' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1b9c5de-147d-492e-b667-9c4d2cca4529' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c50f1ad-f748-4e17-9211-453f7c0a9c8f' class='xr-var-data-in' type='checkbox'><label for='data-4c50f1ad-f748-4e17-9211-453f7c0a9c8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><pre>array([[0.        , 0.00222387],\n",
+       "       [0.00222387, 0.00533729],\n",
+       "       [0.00533729, 0.00978502],\n",
+       "       [0.00978502, 0.01512229],\n",
+       "       [0.01512229, 0.02179391],\n",
+       "       [0.02179391, 0.02979981],\n",
+       "       [0.02979981, 0.03914007],\n",
+       "       [0.03914007, 0.04936986],\n",
+       "       [0.04936986, 0.06093399],\n",
+       "       [0.06093399, 0.07338764],\n",
+       "       [0.07338764, 0.08673083],\n",
+       "       [0.08673083, 0.10274269],\n",
+       "       [0.10274269, 0.12231271],\n",
+       "       [0.12231271, 0.14544096],\n",
+       "       [0.14544096, 0.17212737],\n",
+       "       [0.17212737, 0.20613031],\n",
+       "       [0.20613031, 0.23707318],\n",
+       "       [0.23707318, 0.26400867],\n",
+       "       [0.26400867, 0.28744824],\n",
+       "       [0.28744824, 0.30785001],\n",
+       "       [0.30785001, 0.26792999],\n",
+       "       [0.26792999, 0.23318001],\n",
+       "       [0.23318001, 0.20295   ],\n",
+       "       [0.20295   , 0.17663   ],\n",
+       "       [0.17663   , 0.15372   ],\n",
+       "       [0.15372   , 0.13379001],\n",
+       "       [0.13379001, 0.11643999],\n",
+       "       [0.11643999, 0.10134   ],\n",
+       "       [0.10134   , 0.0882    ],\n",
+       "       [0.0882    , 0.07676299],\n",
+       "       [0.07676299, 0.066809  ],\n",
+       "       [0.066809  , 0.058145  ],\n",
+       "       [0.058145  , 0.050475  ],\n",
+       "       [0.050475  , 0.043462  ],\n",
+       "       [0.043462  , 0.036917  ],\n",
+       "       [0.036917  , 0.030384  ],\n",
+       "       [0.030384  , 0.022927  ],\n",
+       "       [0.022927  , 0.014526  ],\n",
+       "       [0.014526  , 0.007     ],\n",
+       "       [0.007     , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.9928 0.9928 ... 0.0 0.0 0.0</div><input id='attrs-51abe110-b1aa-494d-a07e-09fb97efc1d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51abe110-b1aa-494d-a07e-09fb97efc1d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db4389d8-d6a5-42b0-9794-20ddadafbcb9' class='xr-var-data-in' type='checkbox'><label for='data-db4389d8-d6a5-42b0-9794-20ddadafbcb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><pre>array([[1.        , 0.99277616],\n",
+       "       [0.99277616, 0.98266268],\n",
+       "       [0.98266268, 0.96821499],\n",
+       "       [0.96821499, 0.95087773],\n",
+       "       [0.95087773, 0.92920607],\n",
+       "       [0.92920607, 0.90320021],\n",
+       "       [0.90320021, 0.87285995],\n",
+       "       [0.87285995, 0.83963013],\n",
+       "       [0.83963013, 0.80206597],\n",
+       "       [0.80206597, 0.76161236],\n",
+       "       [0.76161236, 0.71826917],\n",
+       "       [0.71826917, 0.66625732],\n",
+       "       [0.66625732, 0.6026873 ],\n",
+       "       [0.6026873 , 0.52755904],\n",
+       "       [0.52755904, 0.44087261],\n",
+       "       [0.44087261, 0.33041969],\n",
+       "       [0.33041969, 0.22990683],\n",
+       "       [0.22990683, 0.14241131],\n",
+       "       [0.14241131, 0.06627177],\n",
+       "       [0.06627177, 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -86.58 -86.58 ... 86.58 90.0</div><input id='attrs-8bc5ca47-bdc1-4f53-bd34-ed2fbfd88243' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8bc5ca47-bdc1-4f53-bd34-ed2fbfd88243' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7887e07a-f6e0-4372-9861-093127112d77' class='xr-var-data-in' type='checkbox'><label for='data-7887e07a-f6e0-4372-9861-093127112d77' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90.        , -86.57774751],\n",
+       "       [-86.57774751, -83.75702878],\n",
+       "       [-83.75702878, -80.95502019],\n",
+       "       [-80.95502019, -78.15834785],\n",
+       "       [-78.15834785, -75.36393858],\n",
+       "       [-75.36393858, -72.5707002 ],\n",
+       "       [-72.5707002 , -69.77814617],\n",
+       "       [-69.77814617, -66.98602671],\n",
+       "       [-66.98602671, -64.19420036],\n",
+       "       [-64.19420036, -61.40258094],\n",
+       "       [-61.40258094, -58.61111296],\n",
+       "       [-58.61111296, -55.81975904],\n",
+       "       [-55.81975904, -53.02849308],\n",
+       "       [-53.02849308, -50.23729628],\n",
+       "       [-50.23729628, -47.44615476],\n",
+       "       [-47.44615476, -44.65505801],\n",
+       "       [-44.65505801, -41.86399795],\n",
+       "       [-41.86399795, -39.07296823],\n",
+       "       [-39.07296823, -36.28196381],\n",
+       "       [-36.28196381, -33.49098058],\n",
+       "...\n",
+       "       [ 33.49098058,  36.28196381],\n",
+       "       [ 36.28196381,  39.07296823],\n",
+       "       [ 39.07296823,  41.86399795],\n",
+       "       [ 41.86399795,  44.65505801],\n",
+       "       [ 44.65505801,  47.44615476],\n",
+       "       [ 47.44615476,  50.23729628],\n",
+       "       [ 50.23729628,  53.02849308],\n",
+       "       [ 53.02849308,  55.81975904],\n",
+       "       [ 55.81975904,  58.61111296],\n",
+       "       [ 58.61111296,  61.40258094],\n",
+       "       [ 61.40258094,  64.19420036],\n",
+       "       [ 64.19420036,  66.98602671],\n",
+       "       [ 66.98602671,  69.77814617],\n",
+       "       [ 69.77814617,  72.5707002 ],\n",
+       "       [ 72.5707002 ,  75.36393858],\n",
+       "       [ 75.36393858,  78.15834785],\n",
+       "       [ 78.15834785,  80.95502019],\n",
+       "       [ 80.95502019,  83.75702878],\n",
+       "       [ 83.75702878,  86.57774751],\n",
+       "       [ 86.57774751,  90.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.406 1.406 1.406 ... 355.8 358.6</div><input id='attrs-5e550439-560c-439a-9f14-8c0c8fff4ea0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e550439-560c-439a-9f14-8c0c8fff4ea0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a3e3f3e-d93b-4cb9-936f-c9b7bae2ac04' class='xr-var-data-in' type='checkbox'><label for='data-7a3e3f3e-d93b-4cb9-936f-c9b7bae2ac04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -1.40625,   1.40625],\n",
+       "       [  1.40625,   4.21875],\n",
+       "       [  4.21875,   7.03125],\n",
+       "       [  7.03125,   9.84375],\n",
+       "       [  9.84375,  12.65625],\n",
+       "       [ 12.65625,  15.46875],\n",
+       "       [ 15.46875,  18.28125],\n",
+       "       [ 18.28125,  21.09375],\n",
+       "       [ 21.09375,  23.90625],\n",
+       "       [ 23.90625,  26.71875],\n",
+       "       [ 26.71875,  29.53125],\n",
+       "       [ 29.53125,  32.34375],\n",
+       "       [ 32.34375,  35.15625],\n",
+       "       [ 35.15625,  37.96875],\n",
+       "       [ 37.96875,  40.78125],\n",
+       "       [ 40.78125,  43.59375],\n",
+       "       [ 43.59375,  46.40625],\n",
+       "       [ 46.40625,  49.21875],\n",
+       "       [ 49.21875,  52.03125],\n",
+       "       [ 52.03125,  54.84375],\n",
+       "...\n",
+       "       [302.34375, 305.15625],\n",
+       "       [305.15625, 307.96875],\n",
+       "       [307.96875, 310.78125],\n",
+       "       [310.78125, 313.59375],\n",
+       "       [313.59375, 316.40625],\n",
+       "       [316.40625, 319.21875],\n",
+       "       [319.21875, 322.03125],\n",
+       "       [322.03125, 324.84375],\n",
+       "       [324.84375, 327.65625],\n",
+       "       [327.65625, 330.46875],\n",
+       "       [330.46875, 333.28125],\n",
+       "       [333.28125, 336.09375],\n",
+       "       [336.09375, 338.90625],\n",
+       "       [338.90625, 341.71875],\n",
+       "       [341.71875, 344.53125],\n",
+       "       [344.53125, 347.34375],\n",
+       "       [347.34375, 350.15625],\n",
+       "       [350.15625, 352.96875],\n",
+       "       [352.96875, 355.78125],\n",
+       "       [355.78125, 358.59375]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tnhusscpbl</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-62bbf23e-67bb-4abc-8d38-f5759a252b91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62bbf23e-67bb-4abc-8d38-f5759a252b91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5914e19a-e874-4b66-a368-0cf20b6cb4f6' class='xr-var-data-in' type='checkbox'><label for='data-5914e19a-e874-4b66-a368-0cf20b6cb4f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>tendency_of_specific_humidity_due_to_stratiform_cloud_and_precipitation_and_boundary_layer_mixing</dd><dt><span>long_name :</span></dt><dd>Tendency of Specific Humidity Due to Stratiform Cloud and Precipitation and Boundary Layer Mixing</dd><dt><span>comment :</span></dt><dd>Tendency of Specific Humidity Due to Stratiform Cloud and Precipitation and Boundary Layer Mixing  (to be specified only in  models which do not separate budget terms for stratiform cloud, precipitation and boundary layer schemes.  Includes all boundary layer terms including and diffusive terms.)</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>original_name :</span></dt><dd>DQLSC</dd><dt><span>original_units :</span></dt><dd>1/s</dd><dt><span>history :</span></dt><dd>2020-08-15T22:41:28Z altered by CMOR: Converted units from &#x27;1/s&#x27; to &#x27;s-1&#x27;. 2020-08-15T22:41:28Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2020-08-15T22:41:28Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  1.90706153e-12, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 9.53530766e-13,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         ...,\n",
+       "         [-6.67471547e-12, -1.40169029e-10, -4.30042363e-10, ...,\n",
+       "          -8.20036469e-11, -2.11683823e-10, -8.29571759e-11],\n",
+       "         [-7.05612790e-10, -8.90597762e-10, -8.22897028e-10, ...,\n",
+       "          -3.45178136e-10, -5.94049643e-10, -6.19794993e-10],\n",
+       "         [ 5.24441914e-11,  7.43754017e-11,  8.86783633e-11, ...,\n",
+       "          -2.86059241e-12, -5.72118481e-12,  2.66988619e-11]],\n",
+       "\n",
+       "        [[ 6.86761628e-13,  0.00000000e+00,  6.86761628e-13, ...,\n",
+       "           0.00000000e+00,  1.37352326e-12,  0.00000000e+00],\n",
+       "         [-2.74704651e-12, -9.61466323e-12, -5.49409303e-12, ...,\n",
+       "          -6.18085444e-12, -4.12056977e-12, -6.86761628e-13],\n",
+       "         [-1.44219940e-11, -1.85425633e-11, -2.40366563e-11, ...,\n",
+       "          -1.09881861e-11, -1.03014246e-11,  2.74704651e-12],\n",
+       "...\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "        [[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         ...,\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]]],\n",
+       "      shape=(5, 40, 64, 128), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fc583ce9-046d-420e-b3ae-d64d54e40faa' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fc583ce9-046d-420e-b3ae-d64d54e40faa' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>no parent</dd><dt><span>creation_date :</span></dt><dd>2020-08-15T22:41:28Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.28</dd><dt><span>experiment :</span></dt><dd>AMIP</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>2</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.MIROC.MIROC-ES2L.amip.none.r2i1p1f2</dd><dt><span>grid :</span></dt><dd>native atmosphere T42 Gaussian grid</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-08-15T22:41:28Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan)</dd><dt><span>institution_id :</span></dt><dd>MIROC</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>500 km</dd><dt><span>parent_activity_id :</span></dt><dd>no parent</dd><dt><span>parent_experiment_id :</span></dt><dd>no parent</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>2</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>MIROC-ES2L (2018): \n",
+       "aerosol: SPRINTARS6.0\n",
+       "atmos: CCSR AGCM (T42; 128 x 64 longitude/latitude; 40 levels; top level 3 hPa)\n",
+       "atmosChem: none\n",
+       "land: MATSIRO6.0+VISIT-e ver.1.0\n",
+       "landIce: none\n",
+       "ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m)\n",
+       "ocnBgchem: OECO ver.2.0; NPZD-type with C/N/P/Fe/O cycles\n",
+       "seaIce: COCO4.9</dd><dt><span>source_id :</span></dt><dd>MIROC-ES2L</dd><dt><span>source_type :</span></dt><dd>AGCM AER BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>CFmon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(06 November 2018) MD5:af8da38b788c186666f15688d08f0197</dd><dt><span>title :</span></dt><dd>MIROC-ES2L output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tnhusscpbl</dd><dt><span>variant_label :</span></dt><dd>r2i1p1f2</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by MIROC is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.3.2</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/f575a148-89c0-40d7-bdd5-b67e0f73cf4a</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 7MB\n",
+       "Dimensions:     (time: 5, bnds: 2, lev: 40, lat: 64, lon: 128)\n",
+       "Coordinates:\n",
+       "  * time        (time) float64 40B 15.5 45.0 74.5 105.0 135.5\n",
+       "  * lev         (lev) float64 320B 0.9975 0.9915 0.983 ... 0.0106 0.002905\n",
+       "  * lat         (lat) float64 512B -87.86 -85.1 -82.31 ... 82.31 85.1 87.86\n",
+       "  * lon         (lon) float64 1kB 0.0 2.812 5.625 8.438 ... 351.6 354.4 357.2\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds   (time, bnds) float64 80B 0.0 31.0 31.0 ... 120.0 120.0 151.0\n",
+       "    lev_bnds    (lev, bnds) float64 640B 1.0 0.995 0.995 ... 0.007 0.007 0.0\n",
+       "    p0          float64 8B 1e+05\n",
+       "    a           (lev) float64 320B 0.001113 0.003782 ... 0.0106 0.002905\n",
+       "    b           (lev) float64 320B 0.9964 0.9877 0.9754 0.9595 ... 0.0 0.0 0.0\n",
+       "    ps          (time, lat, lon) float32 164kB 6.951e+04 6.928e+04 ... 1.029e+05\n",
+       "    a_bnds      (lev, bnds) float64 640B 0.0 0.002224 0.002224 ... 0.007 0.0\n",
+       "    b_bnds      (lev, bnds) float64 640B 1.0 0.9928 0.9928 ... 0.0 0.0 0.0\n",
+       "    lat_bnds    (lat, bnds) float64 1kB -90.0 -86.58 -86.58 ... 86.58 86.58 90.0\n",
+       "    lon_bnds    (lon, bnds) float64 2kB -1.406 1.406 1.406 ... 355.8 355.8 358.6\n",
+       "    tnhusscpbl  (time, lev, lat, lon) float32 7MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.7 CMIP-6.2\n",
+       "    activity_id:           CMIP\n",
+       "    branch_method:         no parent\n",
+       "    creation_date:         2020-08-15T22:41:28Z\n",
+       "    data_specs_version:    01.00.28\n",
+       "    experiment:            AMIP\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         2\n",
+       "    frequency:             mon\n",
+       "    further_info_url:      https://furtherinfo.es-doc.org/CMIP6.MIROC.MIROC-E...\n",
+       "    grid:                  native atmosphere T42 Gaussian grid\n",
+       "    grid_label:            gn\n",
+       "    history:               2020-08-15T22:41:28Z ; CMOR rewrote data to be con...\n",
+       "    initialization_index:  1\n",
+       "    institution:           JAMSTEC (Japan Agency for Marine-Earth Science and...\n",
+       "    institution_id:        MIROC\n",
+       "    mip_era:               CMIP6\n",
+       "    nominal_resolution:    500 km\n",
+       "    parent_activity_id:    no parent\n",
+       "    parent_experiment_id:  no parent\n",
+       "    physics_index:         1\n",
+       "    product:               model-output\n",
+       "    realization_index:     2\n",
+       "    realm:                 atmos\n",
+       "    source:                MIROC-ES2L (2018): \\naerosol: SPRINTARS6.0\\natmos:...\n",
+       "    source_id:             MIROC-ES2L\n",
+       "    source_type:           AGCM AER BGC\n",
+       "    sub_experiment:        none\n",
+       "    sub_experiment_id:     none\n",
+       "    table_id:              CFmon\n",
+       "    table_info:            Creation Date:(06 November 2018) MD5:af8da38b788c1...\n",
+       "    title:                 MIROC-ES2L output prepared for CMIP6\n",
+       "    variable_id:           tnhusscpbl\n",
+       "    variant_label:         r2i1p1f2\n",
+       "    license:               CMIP6 model data produced by MIROC is licensed und...\n",
+       "    cmor_version:          3.3.2\n",
+       "    tracking_id:           hdl:21.14100/f575a148-89c0-40d7-bdd5-b67e0f73cf4a"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5, 40, 64, 128) (5, 64, 128)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"04_hybrid_sigma_humidity_tendency\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "lon = source[\"lon\"].values.astype(\"f8\")\n",
+    "lon_bnds = source[\"lon_bnds\"].values.astype(\"f8\")\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_bnds = source[\"time_bnds\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "\n",
+    "lev = source[\"lev\"].values.astype(\"f8\")\n",
+    "lev_bnds = source[\"lev_bnds\"].values.astype(\"f8\")\n",
+    "a = source[\"a\"].values.astype(\"f8\")\n",
+    "a_bnds = source[\"a_bnds\"].values.astype(\"f8\")\n",
+    "b = source[\"b\"].values.astype(\"f8\")\n",
+    "b_bnds = source[\"b_bnds\"].values.astype(\"f8\")\n",
+    "p0 = np.array([float(source[\"p0\"].values)], dtype=\"f8\")\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "tnhusscpbl_source = source[\"tnhusscpbl\"].values.astype(\"f4\")\n",
+    "tnhusscpbl = np.where(np.isfinite(tnhusscpbl_source), tnhusscpbl_source, missing_value).astype(\"f4\")\n",
+    "ps = source[\"ps\"].values.astype(\"f4\")\n",
+    "\n",
+    "print(tnhusscpbl.shape, ps.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/04_hybrid_sigma_humidity_tendency/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/tnhusscpbl/tavg-al-hxy-u/g999/v20260605/tnhusscpbl_tavg-al-hxy-u_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_197901-197905.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "cmor.load_table(\"CMIP7_atmos.json\")\n",
+    "\n",
+    "time_id = cmor.axis(\"time\", coord_vals=time, cell_bounds=time_bnds, units=time_units)\n",
+    "lev_id = cmor.axis(\"standard_hybrid_sigma\", coord_vals=lev, cell_bounds=lev_bnds, units=\"1\")\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "lon_id = cmor.axis(\"longitude\", coord_vals=lon, cell_bounds=lon_bnds, units=\"degrees_east\")\n",
+    "\n",
+    "cmor.zfactor(zaxis_id=lev_id, zfactor_name=\"a\", axis_ids=[lev_id], zfactor_values=a, zfactor_bounds=a_bnds)\n",
+    "cmor.zfactor(zaxis_id=lev_id, zfactor_name=\"b\", axis_ids=[lev_id], zfactor_values=b, zfactor_bounds=b_bnds)\n",
+    "cmor.zfactor(zaxis_id=lev_id, zfactor_name=\"p0\", units=\"Pa\", zfactor_values=p0)\n",
+    "ps_id = cmor.zfactor(zaxis_id=lev_id, zfactor_name=\"ps\", axis_ids=[time_id, lat_id, lon_id], units=\"Pa\")\n",
+    "\n",
+    "variable_name = \"tnhusscpbl_tavg-al-hxy-u\"\n",
+    "tnhusscpbl_id = cmor.variable(variable_name, \"s-1\", [time_id, lev_id, lat_id, lon_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"atmos\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(tnhusscpbl_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(tnhusscpbl_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(tnhusscpbl_id, tnhusscpbl)\n",
+    "cmor.write(ps_id, ps, store_with=tnhusscpbl_id)\n",
+    "netcdf_path = Path(cmor.close(tnhusscpbl_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 7MB\n",
+       "Dimensions:     (time: 5, bnds: 2, lev: 40, lat: 64, lon: 128)\n",
+       "Coordinates:\n",
+       "  * time        (time) float64 40B 15.5 45.0 74.5 105.0 135.5\n",
+       "  * lev         (lev) float64 320B 0.9975 0.9915 0.983 ... 0.0106 0.002905\n",
+       "  * lat         (lat) float64 512B -87.86 -85.1 -82.31 ... 82.31 85.1 87.86\n",
+       "  * lon         (lon) float64 1kB 0.0 2.812 5.625 8.438 ... 351.6 354.4 357.2\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds   (time, bnds) float64 80B 0.0 31.0 31.0 ... 120.0 120.0 151.0\n",
+       "    lev_bnds    (lev, bnds) float64 640B 1.0 0.995 0.995 ... 0.007 0.007 0.0\n",
+       "    p0          float64 8B 1e+05\n",
+       "    a           (lev) float64 320B 0.001113 0.003782 ... 0.0106 0.002905\n",
+       "    b           (lev) float64 320B 0.9964 0.9877 0.9754 0.9595 ... 0.0 0.0 0.0\n",
+       "    ps          (time, lat, lon) float32 164kB 6.951e+04 6.928e+04 ... 1.029e+05\n",
+       "    a_bnds      (lev, bnds) float64 640B 0.0 0.002224 0.002224 ... 0.007 0.0\n",
+       "    b_bnds      (lev, bnds) float64 640B 1.0 0.9928 0.9928 ... 0.0 0.0 0.0\n",
+       "    lat_bnds    (lat, bnds) float64 1kB -90.0 -86.58 -86.58 ... 86.58 86.58 90.0\n",
+       "    lon_bnds    (lon, bnds) float64 2kB -1.406 1.406 1.406 ... 355.8 355.8 358.6\n",
+       "    tnhusscpbl  (time, lev, lat, lon) float32 7MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      tnhusscpbl_tavg-al-hxy-u\n",
+       "    branding_suffix:       tavg-al-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:30Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:30Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    variable_id:           tnhusscpbl\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        al\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1\n",
+       "    tracking_id:           hdl:21.14107/0706140a-0c18-498b-a18a-b6dc2d5082cd</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a6c280da-0785-4ed1-863a-206f783ad09b' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-a6c280da-0785-4ed1-863a-206f783ad09b' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lev</span>: 40</li><li><span class='xr-has-index'>lat</span>: 64</li><li><span class='xr-has-index'>lon</span>: 128</li></ul></div></li><li class='xr-section-item'><input id='section-0e6e92f7-176d-4106-a9c2-e4092c543cbe' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0e6e92f7-176d-4106-a9c2-e4092c543cbe' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.5 45.0 74.5 105.0 135.5</div><input id='attrs-c8f17704-4797-4fd8-8a9d-7d31806016c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8f17704-4797-4fd8-8a9d-7d31806016c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ca96f63-a49d-47d9-a582-1871d4ba1157' class='xr-var-data-in' type='checkbox'><label for='data-7ca96f63-a49d-47d9-a582-1871d4ba1157' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1979-1-1</dd><dt><span>calendar :</span></dt><dd>gregorian</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([ 15.5,  45. ,  74.5, 105. , 135.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9975 0.9915 ... 0.0106 0.002905</div><input id='attrs-e615ab49-282f-4fb7-9117-e69842de8366' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e615ab49-282f-4fb7-9117-e69842de8366' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-207175a9-4675-4a10-a128-faeaa4f74d97' class='xr-var-data-in' type='checkbox'><label for='data-207175a9-4675-4a10-a128-faeaa4f74d97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>long_name :</span></dt><dd>hybrid sigma pressure coordinate</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a b: b ps: ps</dd></dl></div><div class='xr-var-data'><pre>array([0.997499, 0.991499, 0.982997, 0.971996, 0.958493, 0.94199 , 0.922486,\n",
+       "       0.900483, 0.875977, 0.848972, 0.819967, 0.786951, 0.746923, 0.698885,\n",
+       "       0.642833, 0.574472, 0.501478, 0.43645 , 0.379852, 0.330596, 0.287725,\n",
+       "       0.250411, 0.21794 , 0.189681, 0.16508 , 0.143673, 0.125043, 0.108828,\n",
+       "       0.094716, 0.082434, 0.071745, 0.062441, 0.054278, 0.046937, 0.040158,\n",
+       "       0.033613, 0.026593, 0.018613, 0.010603, 0.002905])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-87.86 -85.1 -82.31 ... 85.1 87.86</div><input id='attrs-c53eaf8c-3951-410f-8f58-e91d716a7e41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c53eaf8c-3951-410f-8f58-e91d716a7e41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14470fd7-43ca-4787-b984-5a78d6c1e31e' class='xr-var-data-in' type='checkbox'><label for='data-14470fd7-43ca-4787-b984-5a78d6c1e31e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-87.863799, -85.096527, -82.312913, -79.525607, -76.7369  , -73.947515,\n",
+       "       -71.157752, -68.367756, -65.577607, -62.787352, -59.99702 , -57.206632,\n",
+       "       -54.4162  , -51.625734, -48.835241, -46.044727, -43.254195, -40.463648,\n",
+       "       -37.67309 , -34.882521, -32.091944, -29.30136 , -26.510769, -23.720174,\n",
+       "       -20.929574, -18.138971, -15.348365, -12.557756,  -9.767146,  -6.976534,\n",
+       "        -4.185921,  -1.395307,   1.395307,   4.185921,   6.976534,   9.767146,\n",
+       "        12.557756,  15.348365,  18.138971,  20.929574,  23.720174,  26.510769,\n",
+       "        29.30136 ,  32.091944,  34.882521,  37.67309 ,  40.463648,  43.254195,\n",
+       "        46.044727,  48.835241,  51.625734,  54.4162  ,  57.206632,  59.99702 ,\n",
+       "        62.787352,  65.577607,  68.367756,  71.157752,  73.947515,  76.7369  ,\n",
+       "        79.525607,  82.312913,  85.096527,  87.863799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.812 5.625 ... 354.4 357.2</div><input id='attrs-70bd25be-56ee-45be-95e5-512c4bf6c9f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70bd25be-56ee-45be-95e5-512c4bf6c9f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b751eb06-114d-460b-bf97-6fe72e09e0bc' class='xr-var-data-in' type='checkbox'><label for='data-b751eb06-114d-460b-bf97-6fe72e09e0bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.    ,   2.8125,   5.625 ,   8.4375,  11.25  ,  14.0625,  16.875 ,\n",
+       "        19.6875,  22.5   ,  25.3125,  28.125 ,  30.9375,  33.75  ,  36.5625,\n",
+       "        39.375 ,  42.1875,  45.    ,  47.8125,  50.625 ,  53.4375,  56.25  ,\n",
+       "        59.0625,  61.875 ,  64.6875,  67.5   ,  70.3125,  73.125 ,  75.9375,\n",
+       "        78.75  ,  81.5625,  84.375 ,  87.1875,  90.    ,  92.8125,  95.625 ,\n",
+       "        98.4375, 101.25  , 104.0625, 106.875 , 109.6875, 112.5   , 115.3125,\n",
+       "       118.125 , 120.9375, 123.75  , 126.5625, 129.375 , 132.1875, 135.    ,\n",
+       "       137.8125, 140.625 , 143.4375, 146.25  , 149.0625, 151.875 , 154.6875,\n",
+       "       157.5   , 160.3125, 163.125 , 165.9375, 168.75  , 171.5625, 174.375 ,\n",
+       "       177.1875, 180.    , 182.8125, 185.625 , 188.4375, 191.25  , 194.0625,\n",
+       "       196.875 , 199.6875, 202.5   , 205.3125, 208.125 , 210.9375, 213.75  ,\n",
+       "       216.5625, 219.375 , 222.1875, 225.    , 227.8125, 230.625 , 233.4375,\n",
+       "       236.25  , 239.0625, 241.875 , 244.6875, 247.5   , 250.3125, 253.125 ,\n",
+       "       255.9375, 258.75  , 261.5625, 264.375 , 267.1875, 270.    , 272.8125,\n",
+       "       275.625 , 278.4375, 281.25  , 284.0625, 286.875 , 289.6875, 292.5   ,\n",
+       "       295.3125, 298.125 , 300.9375, 303.75  , 306.5625, 309.375 , 312.1875,\n",
+       "       315.    , 317.8125, 320.625 , 323.4375, 326.25  , 329.0625, 331.875 ,\n",
+       "       334.6875, 337.5   , 340.3125, 343.125 , 345.9375, 348.75  , 351.5625,\n",
+       "       354.375 , 357.1875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-70a4fcce-c543-4055-b384-956b2db248b6' class='xr-section-summary-in' type='checkbox' checked /><label for='section-70a4fcce-c543-4055-b384-956b2db248b6' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 31.0 31.0 ... 120.0 120.0 151.0</div><input id='attrs-f96b0e13-a3bd-4e1d-9c2a-df0103bde3ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f96b0e13-a3bd-4e1d-9c2a-df0103bde3ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67b27c3c-8585-43a1-8eb9-e6fd1026e0ee' class='xr-var-data-in' type='checkbox'><label for='data-67b27c3c-8585-43a1-8eb9-e6fd1026e0ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.,  31.],\n",
+       "       [ 31.,  59.],\n",
+       "       [ 59.,  90.],\n",
+       "       [ 90., 120.],\n",
+       "       [120., 151.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.995 0.995 ... 0.007 0.007 0.0</div><input id='attrs-aa11924b-f4c8-4619-8a21-c01338c2702a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa11924b-f4c8-4619-8a21-c01338c2702a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21b7c1df-a615-4cf2-b099-dc7b4704082f' class='xr-var-data-in' type='checkbox'><label for='data-21b7c1df-a615-4cf2-b099-dc7b4704082f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd></dl></div><div class='xr-var-data'><pre>array([[1.        , 0.995     ],\n",
+       "       [0.995     , 0.98799998],\n",
+       "       [0.98799998, 0.97799999],\n",
+       "       [0.97799999, 0.96600002],\n",
+       "       [0.96600002, 0.95099998],\n",
+       "       [0.95099998, 0.93300003],\n",
+       "       [0.93300003, 0.912     ],\n",
+       "       [0.912     , 0.889     ],\n",
+       "       [0.889     , 0.86299998],\n",
+       "       [0.86299998, 0.83499998],\n",
+       "       [0.83499998, 0.80500001],\n",
+       "       [0.80500001, 0.76899999],\n",
+       "       [0.76899999, 0.72500002],\n",
+       "       [0.72500002, 0.67299998],\n",
+       "       [0.67299998, 0.61299998],\n",
+       "       [0.61299998, 0.53654999],\n",
+       "       [0.53654999, 0.46698001],\n",
+       "       [0.46698001, 0.40641999],\n",
+       "       [0.40641999, 0.35372001],\n",
+       "       [0.35372001, 0.30785   ],\n",
+       "       [0.30785   , 0.26793   ],\n",
+       "       [0.26793   , 0.23318   ],\n",
+       "       [0.23318   , 0.20295   ],\n",
+       "       [0.20295   , 0.17663001],\n",
+       "       [0.17663001, 0.15372001],\n",
+       "       [0.15372001, 0.13379   ],\n",
+       "       [0.13379   , 0.11644   ],\n",
+       "       [0.11644   , 0.10134   ],\n",
+       "       [0.10134   , 0.0882    ],\n",
+       "       [0.0882    , 0.076763  ],\n",
+       "       [0.076763  , 0.066809  ],\n",
+       "       [0.066809  , 0.058145  ],\n",
+       "       [0.058145  , 0.050475  ],\n",
+       "       [0.050475  , 0.043462  ],\n",
+       "       [0.043462  , 0.036917  ],\n",
+       "       [0.036917  , 0.030384  ],\n",
+       "       [0.030384  , 0.022927  ],\n",
+       "       [0.022927  , 0.014526  ],\n",
+       "       [0.014526  , 0.007     ],\n",
+       "       [0.007     , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05</div><input id='attrs-1f8557af-b259-457c-ab2a-d2457bb77eb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f8557af-b259-457c-ab2a-d2457bb77eb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71f50c03-bc8e-407a-a82f-38ab335cf8f7' class='xr-var-data-in' type='checkbox'><label for='data-71f50c03-bc8e-407a-a82f-38ab335cf8f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>reference_air_pressure_for_atmosphere_vertical_coordinate</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array(100000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001113 0.003782 ... 0.002905</div><input id='attrs-e3bcbbf4-26e3-4a07-b327-025a2efb9c3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3bcbbf4-26e3-4a07-b327-025a2efb9c3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1bfb94f-a19e-401e-8df7-4690a2cc2e98' class='xr-var-data-in' type='checkbox'><label for='data-b1bfb94f-a19e-401e-8df7-4690a2cc2e98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a</dd></dl></div><div class='xr-var-data'><pre>array([0.00111275, 0.00378219, 0.0075645 , 0.01245857, 0.01846599,\n",
+       "       0.0258086 , 0.03448657, 0.04427587, 0.05518012, 0.06719563,\n",
+       "       0.08010215, 0.09480408, 0.11264021, 0.13405917, 0.15908005,\n",
+       "       0.18977115, 0.22239427, 0.2515278 , 0.27720865, 0.30309604,\n",
+       "       0.2877251 , 0.25041144, 0.21794017, 0.18968127, 0.16508035,\n",
+       "       0.1436727 , 0.12504333, 0.10882762, 0.09471573, 0.08243426,\n",
+       "       0.07174488, 0.06244121, 0.05427773, 0.04693731, 0.04015774,\n",
+       "       0.03361269, 0.02659318, 0.01861324, 0.01060254, 0.00290465])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9964 0.9877 0.9754 ... 0.0 0.0</div><input id='attrs-bbdba623-5ab1-46b5-8134-bda135e59751' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbdba623-5ab1-46b5-8134-bda135e59751' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a85aa80-4729-43e1-a3ab-a290b804aeee' class='xr-var-data-in' type='checkbox'><label for='data-5a85aa80-4729-43e1-a3ab-a290b804aeee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b</dd></dl></div><div class='xr-var-data'><pre>array([0.99638653, 0.98771632, 0.97543246, 0.95953703, 0.940027  ,\n",
+       "       0.91618115, 0.88799924, 0.85620666, 0.82079691, 0.78177685,\n",
+       "       0.73986518, 0.6921469 , 0.63428265, 0.56482565, 0.48375323,\n",
+       "       0.38470095, 0.27908337, 0.18492202, 0.10264368, 0.02749949,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ,\n",
+       "       0.        , 0.        , 0.        , 0.        , 0.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.951e+04 6.928e+04 ... 1.029e+05</div><input id='attrs-6b9f32a3-b7dd-4061-b111-29dbbbd8311b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b9f32a3-b7dd-4061-b111-29dbbbd8311b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dbf0bce-e485-4109-a23f-7cf422b0ea4a' class='xr-var-data-in' type='checkbox'><label for='data-7dbf0bce-e485-4109-a23f-7cf422b0ea4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_pressure</dd><dt><span>long_name :</span></dt><dd>Surface Air Pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array([[[ 69506.68 ,  69276.34 ,  69050.01 , ...,  70217.68 ,\n",
+       "          69978.55 ,  69741.01 ],\n",
+       "        [ 70131.305,  69566.664,  69032.41 , ...,  71992.38 ,\n",
+       "          71346.164,  70724.734],\n",
+       "        [ 69113.99 ,  68264.625,  67517.63 , ...,  72280.305,\n",
+       "          71123.83 ,  70067.32 ],\n",
+       "        ...,\n",
+       "        [102419.91 , 102623.85 , 102737.43 , ..., 101161.06 ,\n",
+       "         101695.31 , 102113.6  ],\n",
+       "        [102910.98 , 102975.76 , 103014.15 , ..., 102552.67 ,\n",
+       "         102699.84 , 102819.8  ],\n",
+       "        [103155.71 , 103150.11 , 103142.12 , ..., 103156.51 ,\n",
+       "         103158.11 , 103158.11 ]],\n",
+       "\n",
+       "       [[ 69910.48 ,  69675.164,  69443.82 , ...,  70634.72 ,\n",
+       "          70390.66 ,  70148.98 ],\n",
+       "        [ 70598.14 ,  70024.96 ,  69482.77 , ...,  72486.24 ,\n",
+       "          71830.375,  71200.74 ],\n",
+       "        [ 69574.2  ,  68708.46 ,  67946.86 , ...,  72802.64 ,\n",
+       "          71624.48 ,  70547.266],\n",
+       "...\n",
+       "        [103368.234, 103566.87 , 103678.21 , ..., 102154.016,\n",
+       "         102668.21 , 103071.89 ],\n",
+       "        [103760.7  , 103823.17 , 103862.43 , ..., 103417.9  ,\n",
+       "         103558.07 , 103672.59 ],\n",
+       "        [103979.36 , 103973.76 , 103965.75 , ..., 103981.766,\n",
+       "         103983.36 , 103982.555]],\n",
+       "\n",
+       "       [[ 68441.375,  68197.09 ,  67957.55 , ...,  69196.28 ,\n",
+       "          68941.76 ,  68690.39 ],\n",
+       "        [ 69065.47 ,  68471.32 ,  67908.69 , ...,  71029.17 ,\n",
+       "          70345.97 ,  69691.14 ],\n",
+       "        [ 67980.4  ,  67089.164,  66306.68 , ...,  71308.914,\n",
+       "          70093.02 ,  68981.945],\n",
+       "        ...,\n",
+       "        [102202.45 , 102432.55 , 102581.484, ..., 100930.625,\n",
+       "         101457.01 , 101879.375],\n",
+       "        [102613.   , 102698.89 , 102761.94 , ..., 102212.695,\n",
+       "         102369.51 , 102503.47 ],\n",
+       "        [102897.48 , 102901.41 , 102903.77 , ..., 102873.05 ,\n",
+       "         102883.29 , 102891.95 ]]], shape=(5, 64, 128), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.002224 0.002224 ... 0.007 0.0</div><input id='attrs-a75f5d06-377a-4fa8-a662-c5fbcfe542c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a75f5d06-377a-4fa8-a662-c5fbcfe542c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2066e1a-f543-4b59-aebb-1df6564aeb71' class='xr-var-data-in' type='checkbox'><label for='data-b2066e1a-f543-4b59-aebb-1df6564aeb71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><pre>array([[0.        , 0.00222387],\n",
+       "       [0.00222387, 0.00533729],\n",
+       "       [0.00533729, 0.00978502],\n",
+       "       [0.00978502, 0.01512229],\n",
+       "       [0.01512229, 0.02179391],\n",
+       "       [0.02179391, 0.02979981],\n",
+       "       [0.02979981, 0.03914007],\n",
+       "       [0.03914007, 0.04936986],\n",
+       "       [0.04936986, 0.06093399],\n",
+       "       [0.06093399, 0.07338764],\n",
+       "       [0.07338764, 0.08673083],\n",
+       "       [0.08673083, 0.10274269],\n",
+       "       [0.10274269, 0.12231271],\n",
+       "       [0.12231271, 0.14544096],\n",
+       "       [0.14544096, 0.17212737],\n",
+       "       [0.17212737, 0.20613031],\n",
+       "       [0.20613031, 0.23707318],\n",
+       "       [0.23707318, 0.26400867],\n",
+       "       [0.26400867, 0.28744824],\n",
+       "       [0.28744824, 0.30785001],\n",
+       "       [0.30785001, 0.26792999],\n",
+       "       [0.26792999, 0.23318001],\n",
+       "       [0.23318001, 0.20295   ],\n",
+       "       [0.20295   , 0.17663   ],\n",
+       "       [0.17663   , 0.15372   ],\n",
+       "       [0.15372   , 0.13379001],\n",
+       "       [0.13379001, 0.11643999],\n",
+       "       [0.11643999, 0.10134   ],\n",
+       "       [0.10134   , 0.0882    ],\n",
+       "       [0.0882    , 0.07676299],\n",
+       "       [0.07676299, 0.066809  ],\n",
+       "       [0.066809  , 0.058145  ],\n",
+       "       [0.058145  , 0.050475  ],\n",
+       "       [0.050475  , 0.043462  ],\n",
+       "       [0.043462  , 0.036917  ],\n",
+       "       [0.036917  , 0.030384  ],\n",
+       "       [0.030384  , 0.022927  ],\n",
+       "       [0.022927  , 0.014526  ],\n",
+       "       [0.014526  , 0.007     ],\n",
+       "       [0.007     , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.9928 0.9928 ... 0.0 0.0 0.0</div><input id='attrs-fb6955d8-df99-4d13-aeaf-c40c2a4a08c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb6955d8-df99-4d13-aeaf-c40c2a4a08c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92f79226-07ba-4f77-b5a6-438544727d9b' class='xr-var-data-in' type='checkbox'><label for='data-92f79226-07ba-4f77-b5a6-438544727d9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><pre>array([[1.        , 0.99277616],\n",
+       "       [0.99277616, 0.98266268],\n",
+       "       [0.98266268, 0.96821499],\n",
+       "       [0.96821499, 0.95087773],\n",
+       "       [0.95087773, 0.92920607],\n",
+       "       [0.92920607, 0.90320021],\n",
+       "       [0.90320021, 0.87285995],\n",
+       "       [0.87285995, 0.83963013],\n",
+       "       [0.83963013, 0.80206597],\n",
+       "       [0.80206597, 0.76161236],\n",
+       "       [0.76161236, 0.71826917],\n",
+       "       [0.71826917, 0.66625732],\n",
+       "       [0.66625732, 0.6026873 ],\n",
+       "       [0.6026873 , 0.52755904],\n",
+       "       [0.52755904, 0.44087261],\n",
+       "       [0.44087261, 0.33041969],\n",
+       "       [0.33041969, 0.22990683],\n",
+       "       [0.22990683, 0.14241131],\n",
+       "       [0.14241131, 0.06627177],\n",
+       "       [0.06627177, 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ],\n",
+       "       [0.        , 0.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -86.58 -86.58 ... 86.58 90.0</div><input id='attrs-c14cceb6-e0bc-4358-b409-bc1376d241b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c14cceb6-e0bc-4358-b409-bc1376d241b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d29f1d98-29b4-48b0-a27c-223ea6fbb031' class='xr-var-data-in' type='checkbox'><label for='data-d29f1d98-29b4-48b0-a27c-223ea6fbb031' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90.        , -86.57774751],\n",
+       "       [-86.57774751, -83.75702878],\n",
+       "       [-83.75702878, -80.95502019],\n",
+       "       [-80.95502019, -78.15834785],\n",
+       "       [-78.15834785, -75.36393858],\n",
+       "       [-75.36393858, -72.5707002 ],\n",
+       "       [-72.5707002 , -69.77814617],\n",
+       "       [-69.77814617, -66.98602671],\n",
+       "       [-66.98602671, -64.19420036],\n",
+       "       [-64.19420036, -61.40258094],\n",
+       "       [-61.40258094, -58.61111296],\n",
+       "       [-58.61111296, -55.81975904],\n",
+       "       [-55.81975904, -53.02849308],\n",
+       "       [-53.02849308, -50.23729628],\n",
+       "       [-50.23729628, -47.44615476],\n",
+       "       [-47.44615476, -44.65505801],\n",
+       "       [-44.65505801, -41.86399795],\n",
+       "       [-41.86399795, -39.07296823],\n",
+       "       [-39.07296823, -36.28196381],\n",
+       "       [-36.28196381, -33.49098058],\n",
+       "...\n",
+       "       [ 33.49098058,  36.28196381],\n",
+       "       [ 36.28196381,  39.07296823],\n",
+       "       [ 39.07296823,  41.86399795],\n",
+       "       [ 41.86399795,  44.65505801],\n",
+       "       [ 44.65505801,  47.44615476],\n",
+       "       [ 47.44615476,  50.23729628],\n",
+       "       [ 50.23729628,  53.02849308],\n",
+       "       [ 53.02849308,  55.81975904],\n",
+       "       [ 55.81975904,  58.61111296],\n",
+       "       [ 58.61111296,  61.40258094],\n",
+       "       [ 61.40258094,  64.19420036],\n",
+       "       [ 64.19420036,  66.98602671],\n",
+       "       [ 66.98602671,  69.77814617],\n",
+       "       [ 69.77814617,  72.5707002 ],\n",
+       "       [ 72.5707002 ,  75.36393858],\n",
+       "       [ 75.36393858,  78.15834785],\n",
+       "       [ 78.15834785,  80.95502019],\n",
+       "       [ 80.95502019,  83.75702878],\n",
+       "       [ 83.75702878,  86.57774751],\n",
+       "       [ 86.57774751,  90.        ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.406 1.406 1.406 ... 355.8 358.6</div><input id='attrs-fb168bda-c314-4831-a4bf-ffa6ad4f53de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb168bda-c314-4831-a4bf-ffa6ad4f53de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04c786e2-d183-4d56-95a2-ce66e4aa9ff7' class='xr-var-data-in' type='checkbox'><label for='data-04c786e2-d183-4d56-95a2-ce66e4aa9ff7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -1.40625,   1.40625],\n",
+       "       [  1.40625,   4.21875],\n",
+       "       [  4.21875,   7.03125],\n",
+       "       [  7.03125,   9.84375],\n",
+       "       [  9.84375,  12.65625],\n",
+       "       [ 12.65625,  15.46875],\n",
+       "       [ 15.46875,  18.28125],\n",
+       "       [ 18.28125,  21.09375],\n",
+       "       [ 21.09375,  23.90625],\n",
+       "       [ 23.90625,  26.71875],\n",
+       "       [ 26.71875,  29.53125],\n",
+       "       [ 29.53125,  32.34375],\n",
+       "       [ 32.34375,  35.15625],\n",
+       "       [ 35.15625,  37.96875],\n",
+       "       [ 37.96875,  40.78125],\n",
+       "       [ 40.78125,  43.59375],\n",
+       "       [ 43.59375,  46.40625],\n",
+       "       [ 46.40625,  49.21875],\n",
+       "       [ 49.21875,  52.03125],\n",
+       "       [ 52.03125,  54.84375],\n",
+       "...\n",
+       "       [302.34375, 305.15625],\n",
+       "       [305.15625, 307.96875],\n",
+       "       [307.96875, 310.78125],\n",
+       "       [310.78125, 313.59375],\n",
+       "       [313.59375, 316.40625],\n",
+       "       [316.40625, 319.21875],\n",
+       "       [319.21875, 322.03125],\n",
+       "       [322.03125, 324.84375],\n",
+       "       [324.84375, 327.65625],\n",
+       "       [327.65625, 330.46875],\n",
+       "       [330.46875, 333.28125],\n",
+       "       [333.28125, 336.09375],\n",
+       "       [336.09375, 338.90625],\n",
+       "       [338.90625, 341.71875],\n",
+       "       [341.71875, 344.53125],\n",
+       "       [344.53125, 347.34375],\n",
+       "       [347.34375, 350.15625],\n",
+       "       [350.15625, 352.96875],\n",
+       "       [352.96875, 355.78125],\n",
+       "       [355.78125, 358.59375]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tnhusscpbl</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-d5bffdf2-e4e3-4913-98a5-b5854ca843a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5bffdf2-e4e3-4913-98a5-b5854ca843a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd43ea62-7b36-4862-849a-dc495346cd9c' class='xr-var-data-in' type='checkbox'><label for='data-cd43ea62-7b36-4862-849a-dc495346cd9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>tendency_of_specific_humidity_due_to_stratiform_cloud_and_precipitation_and_boundary_layer_mixing</dd><dt><span>long_name :</span></dt><dd>Tendency of Specific Humidity Due to Stratiform Cloud and Precipitation and Boundary Layer Mixing</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  1.90706153e-12, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 9.53530766e-13,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         ...,\n",
+       "         [-6.67471547e-12, -1.40169029e-10, -4.30042363e-10, ...,\n",
+       "          -8.20036469e-11, -2.11683823e-10, -8.29571759e-11],\n",
+       "         [-7.05612790e-10, -8.90597762e-10, -8.22897028e-10, ...,\n",
+       "          -3.45178136e-10, -5.94049643e-10, -6.19794993e-10],\n",
+       "         [ 5.24441914e-11,  7.43754017e-11,  8.86783633e-11, ...,\n",
+       "          -2.86059241e-12, -5.72118481e-12,  2.66988619e-11]],\n",
+       "\n",
+       "        [[ 6.86761628e-13,  0.00000000e+00,  6.86761628e-13, ...,\n",
+       "           0.00000000e+00,  1.37352326e-12,  0.00000000e+00],\n",
+       "         [-2.74704651e-12, -9.61466323e-12, -5.49409303e-12, ...,\n",
+       "          -6.18085444e-12, -4.12056977e-12, -6.86761628e-13],\n",
+       "         [-1.44219940e-11, -1.85425633e-11, -2.40366563e-11, ...,\n",
+       "          -1.09881861e-11, -1.03014246e-11,  2.74704651e-12],\n",
+       "...\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "        [[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         ...,\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
+       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
+       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]]],\n",
+       "      shape=(5, 40, 64, 128), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a87a69fe-20e9-42ed-b613-b43203b8b8d1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a87a69fe-20e9-42ed-b613-b43203b8b8d1' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>u</dd><dt><span>branded_variable :</span></dt><dd>tnhusscpbl_tavg-al-hxy-u</dd><dt><span>branding_suffix :</span></dt><dd>tavg-al-hxy-u</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:30Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:30Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_atmos.json; Creation Date:(2026-04-21 15:01:29) MD5:6c425d5354e32ec5498084c927c982a9</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>variable_id :</span></dt><dd>tnhusscpbl</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>al</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/0706140a-0c18-498b-a18a-b6dc2d5082cd</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 7MB\n",
+       "Dimensions:     (time: 5, bnds: 2, lev: 40, lat: 64, lon: 128)\n",
+       "Coordinates:\n",
+       "  * time        (time) float64 40B 15.5 45.0 74.5 105.0 135.5\n",
+       "  * lev         (lev) float64 320B 0.9975 0.9915 0.983 ... 0.0106 0.002905\n",
+       "  * lat         (lat) float64 512B -87.86 -85.1 -82.31 ... 82.31 85.1 87.86\n",
+       "  * lon         (lon) float64 1kB 0.0 2.812 5.625 8.438 ... 351.6 354.4 357.2\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds   (time, bnds) float64 80B 0.0 31.0 31.0 ... 120.0 120.0 151.0\n",
+       "    lev_bnds    (lev, bnds) float64 640B 1.0 0.995 0.995 ... 0.007 0.007 0.0\n",
+       "    p0          float64 8B 1e+05\n",
+       "    a           (lev) float64 320B 0.001113 0.003782 ... 0.0106 0.002905\n",
+       "    b           (lev) float64 320B 0.9964 0.9877 0.9754 0.9595 ... 0.0 0.0 0.0\n",
+       "    ps          (time, lat, lon) float32 164kB 6.951e+04 6.928e+04 ... 1.029e+05\n",
+       "    a_bnds      (lev, bnds) float64 640B 0.0 0.002224 0.002224 ... 0.007 0.0\n",
+       "    b_bnds      (lev, bnds) float64 640B 1.0 0.9928 0.9928 ... 0.0 0.0 0.0\n",
+       "    lat_bnds    (lat, bnds) float64 1kB -90.0 -86.58 -86.58 ... 86.58 86.58 90.0\n",
+       "    lon_bnds    (lon, bnds) float64 2kB -1.406 1.406 1.406 ... 355.8 355.8 358.6\n",
+       "    tnhusscpbl  (time, lev, lat, lon) float32 7MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      tnhusscpbl_tavg-al-hxy-u\n",
+       "    branding_suffix:       tavg-al-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:30Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:30Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 atmos\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_atmos.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    variable_id:           tnhusscpbl\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        al\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1\n",
+       "    tracking_id:           hdl:21.14107/0706140a-0c18-498b-a18a-b6dc2d5082cd"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x540 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(11, 5.4))\n",
+    "map_plot = Basemap(\n",
+    "    projection=\"cyl\",\n",
+    "    llcrnrlon=-180,\n",
+    "    urcrnrlon=180,\n",
+    "    llcrnrlat=-90,\n",
+    "    urcrnrlat=90,\n",
+    "    resolution=\"c\",\n",
+    "    ax=ax,\n",
+    ")\n",
+    "map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "lon_wrapped = ((ds[\"lon\"].values + 180.0) % 360.0) - 180.0\n",
+    "lon_order = np.argsort(lon_wrapped)\n",
+    "lon_grid, lat_grid = np.meshgrid(lon_wrapped[lon_order], ds[\"lat\"].values)\n",
+    "x, y = map_plot(lon_grid, lat_grid)\n",
+    "field = ds[\"tnhusscpbl\"].isel(time=0, lev=10).values[:, lon_order]\n",
+    "mesh = map_plot.pcolormesh(x, y, field, shading=\"auto\", cmap=\"PuOr\")\n",
+    "map_plot.drawcoastlines(linewidth=0.7, color=\"0.15\")\n",
+    "map_plot.drawparallels(np.arange(-90, 91, 30), labels=[1, 0, 0, 0], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "map_plot.drawmeridians(np.arange(-180, 181, 60), labels=[0, 0, 0, 1], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "colorbar = map_plot.colorbar(mesh, location=\"right\", pad=\"5%\")\n",
+    "colorbar.set_label(\"s-1\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "ax.set_title(f\"CMIP7 tnhusscpbl on hybrid level 11, {time_label}\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/05_ocean_heat_transport_by_basin.ipynb b/notebooks/05_ocean_heat_transport_by_basin.ipynb
new file mode 100644
index 00000000..4fe055e3
--- /dev/null
+++ b/notebooks/05_ocean_heat_transport_by_basin.ipynb
@@ -0,0 +1,1824 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ocean Heat Transport By Basin\n",
+    "\n",
+    "Create a CMIP7 monthly northward ocean heat transport file (`htovgyre_tavg-u-hyb-sea`) using latitude and ocean basin coordinates read from a source dataset with xarray."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"htovgyre_Omon_UKESM1-0-LL_ssp370-lowNTCFCH4_r2i1p1f2_gnz_201501-204912.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
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+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
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+       "\n",
+       ".xr-obj-type,\n",
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+       "  margin-left: 2px;\n",
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+       "}\n",
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+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
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+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
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+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
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+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2MB\n",
+       "Dimensions:    (time: 420, bnds: 2, lat: 330, basin: 3)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 3kB 5.942e+04 5.944e+04 ... 7.196e+04 7.198e+04\n",
+       "  * lat        (lat) float64 3kB -85.35 -85.19 -85.04 ... 81.73 81.77 81.79\n",
+       "    sector     (basin) |S21 63B b&#x27;atlantic_arctic_ocean&#x27; ... b&#x27;indian_pacific...\n",
+       "Dimensions without coordinates: bnds, basin\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 7kB 5.94e+04 5.943e+04 ... 7.197e+04 7.2e+04\n",
+       "    lat_bnds   (lat, bnds) float64 5kB -85.42 -85.27 -85.27 ... 81.78 81.78 81.8\n",
+       "    htovgyre   (time, basin, lat) float32 2MB nan nan nan nan ... nan nan nan\n",
+       "Attributes:\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            AerChemMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   59400.0\n",
+       "    branch_time_in_parent:  59400.0\n",
+       "    creation_date:          2020-08-21T14:28:52Z\n",
+       "    cv_version:             6.2.53.5\n",
+       "    data_specs_version:     01.00.31\n",
+       "    experiment:             SSP3-7.0, with low NTCF emissions and methane con...\n",
+       "    experiment_id:          ssp370-lowNTCFCH4\n",
+       "    forcing_index:          2\n",
+       "    frequency:              mon\n",
+       "    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.MOHC.UKESM1-...\n",
+       "    grid:                   Native eORCA1 tripolar primarily 1 deg with merid...\n",
+       "    grid_label:             gnz\n",
+       "    history:                2020-08-21T14:24:56Z ; CMOR rewrote data to be co...\n",
+       "    initialization_index:   1\n",
+       "    institution:            Met Office Hadley Centre, Fitzroy Road, Exeter, D...\n",
+       "    institution_id:         MOHC\n",
+       "    mip_era:                CMIP6\n",
+       "    mo_runid:               u-bu258\n",
+       "    nominal_resolution:     100 km\n",
+       "    parent_activity_id:     CMIP\n",
+       "    parent_experiment_id:   historical\n",
+       "    parent_mip_era:         CMIP6\n",
+       "    parent_source_id:       UKESM1-0-LL\n",
+       "    parent_time_units:      days since 1850-01-01\n",
+       "    parent_variant_label:   r4i1p1f2\n",
+       "    physics_index:          1\n",
+       "    product:                model-output\n",
+       "    realization_index:      2\n",
+       "    realm:                  ocean\n",
+       "    source:                 UKESM1.0-LL (2018): \\naerosol: UKCA-GLOMAP-mode\\n...\n",
+       "    source_id:              UKESM1-0-LL\n",
+       "    source_type:            AOGCM AER BGC CHEM\n",
+       "    sub_experiment:         none\n",
+       "    sub_experiment_id:      none\n",
+       "    table_id:               Omon\n",
+       "    table_info:             Creation Date:(22 July 2019) MD5:4dd1814731b1436d...\n",
+       "    title:                  UKESM1-0-LL output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/a774509f-e0a8-463b-a6ea-d77330aa8c17\n",
+       "    variable_id:            htovgyre\n",
+       "    variable_name:          htovgyre\n",
+       "    variant_label:          r2i1p1f2\n",
+       "    license:                CMIP6 model data produced by the Met Office Hadle...\n",
+       "    cmor_version:           3.4.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-040300f5-67bc-4b47-a294-2c19c9f53e82' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-040300f5-67bc-4b47-a294-2c19c9f53e82' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 420</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 330</li><li><span>basin</span>: 3</li></ul></div></li><li class='xr-section-item'><input id='section-e9819c11-c530-4627-8f61-913a686fd258' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e9819c11-c530-4627-8f61-913a686fd258' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.942e+04 5.944e+04 ... 7.198e+04</div><input id='attrs-c52184dc-5f21-4f0c-86c7-02bae3433b80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c52184dc-5f21-4f0c-86c7-02bae3433b80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ccdc2c5-d711-4aa8-95ac-c5f4e0aea4d5' class='xr-var-data-in' type='checkbox'><label for='data-5ccdc2c5-d711-4aa8-95ac-c5f4e0aea4d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-01-01</dd><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([59415., 59445., 59475., ..., 71925., 71955., 71985.], shape=(420,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-85.35 -85.19 ... 81.77 81.79</div><input id='attrs-3056fad9-5739-41b9-9392-abeead811f15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3056fad9-5739-41b9-9392-abeead811f15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e3fac39-294e-42db-9945-cf0bc8a37d2e' class='xr-var-data-in' type='checkbox'><label for='data-2e3fac39-294e-42db-9945-cf0bc8a37d2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-85.345169, -85.193054, -85.039757, ...,  81.732368,  81.771011,\n",
+       "        81.789879], shape=(330,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sector</span></div><div class='xr-var-dims'>(basin)</div><div class='xr-var-dtype'>|S21</div><div class='xr-var-preview xr-preview'>b&#x27;atlantic_arctic_ocean&#x27; ... b&#x27;i...</div><input id='attrs-49afe743-9ee5-43f7-a2e8-2fa1a0d3b7d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49afe743-9ee5-43f7-a2e8-2fa1a0d3b7d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e15cc42-f1fb-4ddd-a1e9-807cae1ac0c3' class='xr-var-data-in' type='checkbox'><label for='data-7e15cc42-f1fb-4ddd-a1e9-807cae1ac0c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ocean basin</dd><dt><span>standard_name :</span></dt><dd>region</dd></dl></div><div class='xr-var-data'><pre>array([b&#x27;atlantic_arctic_ocean&#x27;, b&#x27;global_ocean&#x27;, b&#x27;indian_pacific_ocean&#x27;],\n",
+       "      dtype=&#x27;|S21&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e06e76ef-26c2-4221-83bb-cc835a569057' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e06e76ef-26c2-4221-83bb-cc835a569057' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.94e+04 5.943e+04 ... 7.2e+04</div><input id='attrs-222dd609-87c1-4a37-9f39-fb21a1d6a637' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-222dd609-87c1-4a37-9f39-fb21a1d6a637' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dcd494f-6b9e-46aa-a952-870be9f83bc3' class='xr-var-data-in' type='checkbox'><label for='data-7dcd494f-6b9e-46aa-a952-870be9f83bc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[59400., 59430.],\n",
+       "       [59430., 59460.],\n",
+       "       [59460., 59490.],\n",
+       "       [59490., 59520.],\n",
+       "       [59520., 59550.],\n",
+       "       [59550., 59580.],\n",
+       "       [59580., 59610.],\n",
+       "       [59610., 59640.],\n",
+       "       [59640., 59670.],\n",
+       "       [59670., 59700.],\n",
+       "       [59700., 59730.],\n",
+       "       [59730., 59760.],\n",
+       "       [59760., 59790.],\n",
+       "       [59790., 59820.],\n",
+       "       [59820., 59850.],\n",
+       "       [59850., 59880.],\n",
+       "       [59880., 59910.],\n",
+       "       [59910., 59940.],\n",
+       "       [59940., 59970.],\n",
+       "       [59970., 60000.],\n",
+       "...\n",
+       "       [71400., 71430.],\n",
+       "       [71430., 71460.],\n",
+       "       [71460., 71490.],\n",
+       "       [71490., 71520.],\n",
+       "       [71520., 71550.],\n",
+       "       [71550., 71580.],\n",
+       "       [71580., 71610.],\n",
+       "       [71610., 71640.],\n",
+       "       [71640., 71670.],\n",
+       "       [71670., 71700.],\n",
+       "       [71700., 71730.],\n",
+       "       [71730., 71760.],\n",
+       "       [71760., 71790.],\n",
+       "       [71790., 71820.],\n",
+       "       [71820., 71850.],\n",
+       "       [71850., 71880.],\n",
+       "       [71880., 71910.],\n",
+       "       [71910., 71940.],\n",
+       "       [71940., 71970.],\n",
+       "       [71970., 72000.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-85.42 -85.27 -85.27 ... 81.78 81.8</div><input id='attrs-a694d731-d6d6-478a-b53e-829a7e6bd528' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a694d731-d6d6-478a-b53e-829a7e6bd528' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b941746-e24d-4a62-9b84-0cebfabfb148' class='xr-var-data-in' type='checkbox'><label for='data-0b941746-e24d-4a62-9b84-0cebfabfb148' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-85.4212265 , -85.26911163],\n",
+       "       [-85.26911163, -85.1164093 ],\n",
+       "       [-85.1164093 , -84.96253967],\n",
+       "       [-84.96253967, -84.80754089],\n",
+       "       [-84.80754089, -84.65143585],\n",
+       "       [-84.65143585, -84.49424744],\n",
+       "       [-84.49424744, -84.33598328],\n",
+       "       [-84.33598328, -84.176651  ],\n",
+       "       [-84.176651  , -84.01625061],\n",
+       "       [-84.01625061, -83.85476685],\n",
+       "       [-83.85476685, -83.69219971],\n",
+       "       [-83.69219971, -83.52854156],\n",
+       "       [-83.52854156, -83.3637619 ],\n",
+       "       [-83.3637619 , -83.19784546],\n",
+       "       [-83.19784546, -83.03075409],\n",
+       "       [-83.03075409, -82.86247253],\n",
+       "       [-82.86247253, -82.69296265],\n",
+       "       [-82.69296265, -82.52220154],\n",
+       "       [-82.52220154, -82.35012817],\n",
+       "       [-82.35012817, -82.17671967],\n",
+       "...\n",
+       "       [ 77.7896347 ,  78.1543045 ],\n",
+       "       [ 78.1543045 ,  78.50632477],\n",
+       "       [ 78.50632477,  78.84484863],\n",
+       "       [ 78.84484863,  79.16899109],\n",
+       "       [ 79.16899109,  79.47784424],\n",
+       "       [ 79.47784424,  79.77050781],\n",
+       "       [ 79.77050781,  80.04605865],\n",
+       "       [ 80.04605865,  80.30360413],\n",
+       "       [ 80.30360413,  80.54229736],\n",
+       "       [ 80.54229736,  80.76134491],\n",
+       "       [ 80.76134491,  80.96003723],\n",
+       "       [ 80.96003723,  81.13778687],\n",
+       "       [ 81.13778687,  81.29414368],\n",
+       "       [ 81.29414368,  81.42881775],\n",
+       "       [ 81.42881775,  81.54171753],\n",
+       "       [ 81.54171753,  81.63292694],\n",
+       "       [ 81.63292694,  81.70275116],\n",
+       "       [ 81.70275116,  81.75169373],\n",
+       "       [ 81.75169373,  81.78044128],\n",
+       "       [ 81.78044128,  81.79931641]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>htovgyre</span></div><div class='xr-var-dims'>(time, basin, lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1e87a728-8c9d-4146-88e0-f9cf6b096d6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e87a728-8c9d-4146-88e0-f9cf6b096d6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99857f72-7786-43ea-84dc-da408250693d' class='xr-var-data-in' type='checkbox'><label for='data-99857f72-7786-43ea-84dc-da408250693d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>northward_ocean_heat_transport_due_to_gyre</dd><dt><span>long_name :</span></dt><dd>Northward Ocean Heat Transport Due to Gyre</dd><dt><span>comment :</span></dt><dd>mo: The latitude coordinate is for reference only and is the closest native grid line passing through 65.6 N, 168.7 W (Bering Strait). The atlantic_arctic_ocean basin includes the baltic_sea and hudson_bay basins and the right-hand half of the arctic_ocean basin (with respect to the native model grid). The indian_pacific_ocean basin includes the red_sea basin. This diagnostic has been calculated with respect to the native grid and NOT with respect to true north as requested., AerChemMIP_table_comment: From all advective mass transport processes, resolved and parameterized.</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>original_name :</span></dt><dd>mo: combine_cubes_to_basin_coord((variable_name: hfovgyre_global), (variable_name: hfovgyre_atlantic), (variable_name: hfovgyre_indopacific), mask_global=(variable_name: global_ocean_1D_V), mask_atl=(variable_name: atlantic_arctic_ocean_1D_V), mask_indpac=(variable_name: indian_pacific_ocean_1D_V))</dd><dt><span>original_units :</span></dt><dd>PW</dd><dt><span>history :</span></dt><dd>2020-08-21T14:28:52Z altered by CMOR: Converted units from &#x27;PW&#x27; to &#x27;W&#x27;. 2020-08-21T14:28:52Z altered by CMOR: Reordered dimensions, original order: basin time lat.</dd><dt><span>cell_methods :</span></dt><dd>longitude: sum (comment: basin sum [along zig-zag grid path]) depth: sum time: mean</dd></dl></div><div class='xr-var-data'><pre>array([[[           nan,            nan,            nan, ...,\n",
+       "          5.9394045e+12,  5.0293663e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          5.1184492e+12,  4.1131914e+12,  1.5370929e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          2.2064136e+12,  2.5288180e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          1.8157083e+12,  1.9613407e+12, -2.4430687e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          8.4291656e+11,  2.0961806e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "         -6.7581130e+11,  4.5333476e+11,  1.5658895e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "...\n",
+       "          7.0244291e+13,  6.4462036e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.3372432e+13,  1.3172417e+13, -2.8057783e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          6.2237117e+13,  5.6790734e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.1562422e+13,  1.1689368e+13,  5.6201621e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          6.0197809e+13,  5.5676689e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.2134275e+13,  1.4477528e+13, -9.6522277e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]]],\n",
+       "      shape=(420, 3, 330), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ede1fad-915f-49b9-ae15-3cdc9bc01413' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3ede1fad-915f-49b9-ae15-3cdc9bc01413' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>AerChemMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>59400.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>59400.0</dd><dt><span>creation_date :</span></dt><dd>2020-08-21T14:28:52Z</dd><dt><span>cv_version :</span></dt><dd>6.2.53.5</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>SSP3-7.0, with low NTCF emissions and methane concentrations</dd><dt><span>experiment_id :</span></dt><dd>ssp370-lowNTCFCH4</dd><dt><span>forcing_index :</span></dt><dd>2</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.MOHC.UKESM1-0-LL.ssp370-lowNTCFCH4.none.r2i1p1f2</dd><dt><span>grid :</span></dt><dd>Native eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; Quasi-zonal mean, 330 latitude</dd><dt><span>grid_label :</span></dt><dd>gnz</dd><dt><span>history :</span></dt><dd>2020-08-21T14:24:56Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.;\n",
+       "2020-08-21T14:23:56Z MIP Convert v1.5.0, Python v2.7.16, Iris v2.2.0, Numpy v1.15.4, cftime v1.0.0b1.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK</dd><dt><span>institution_id :</span></dt><dd>MOHC</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>mo_runid :</span></dt><dd>u-bu258</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>historical</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>UKESM1-0-LL</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r4i1p1f2</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>2</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>source :</span></dt><dd>UKESM1.0-LL (2018): \n",
+       "aerosol: UKCA-GLOMAP-mode\n",
+       "atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km)\n",
+       "atmosChem: UKCA-StratTrop\n",
+       "land: JULES-ES-1.0\n",
+       "landIce: none\n",
+       "ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m)\n",
+       "ocnBgchem: MEDUSA2\n",
+       "seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude)</dd><dt><span>source_id :</span></dt><dd>UKESM1-0-LL</dd><dt><span>source_type :</span></dt><dd>AOGCM AER BGC CHEM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Omon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(22 July 2019) MD5:4dd1814731b1436d797f42e4c6226acf</dd><dt><span>title :</span></dt><dd>UKESM1-0-LL output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/a774509f-e0a8-463b-a6ea-d77330aa8c17</dd><dt><span>variable_id :</span></dt><dd>htovgyre</dd><dt><span>variable_name :</span></dt><dd>htovgyre</dd><dt><span>variant_label :</span></dt><dd>r2i1p1f2</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by the Met Office Hadley Centre is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https://ukesm.ac.uk/cmip6. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2MB\n",
+       "Dimensions:    (time: 420, bnds: 2, lat: 330, basin: 3)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 3kB 5.942e+04 5.944e+04 ... 7.196e+04 7.198e+04\n",
+       "  * lat        (lat) float64 3kB -85.35 -85.19 -85.04 ... 81.73 81.77 81.79\n",
+       "    sector     (basin) |S21 63B b'atlantic_arctic_ocean' ... b'indian_pacific...\n",
+       "Dimensions without coordinates: bnds, basin\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 7kB 5.94e+04 5.943e+04 ... 7.197e+04 7.2e+04\n",
+       "    lat_bnds   (lat, bnds) float64 5kB -85.42 -85.27 -85.27 ... 81.78 81.78 81.8\n",
+       "    htovgyre   (time, basin, lat) float32 2MB nan nan nan nan ... nan nan nan\n",
+       "Attributes:\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            AerChemMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   59400.0\n",
+       "    branch_time_in_parent:  59400.0\n",
+       "    creation_date:          2020-08-21T14:28:52Z\n",
+       "    cv_version:             6.2.53.5\n",
+       "    data_specs_version:     01.00.31\n",
+       "    experiment:             SSP3-7.0, with low NTCF emissions and methane con...\n",
+       "    experiment_id:          ssp370-lowNTCFCH4\n",
+       "    forcing_index:          2\n",
+       "    frequency:              mon\n",
+       "    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.MOHC.UKESM1-...\n",
+       "    grid:                   Native eORCA1 tripolar primarily 1 deg with merid...\n",
+       "    grid_label:             gnz\n",
+       "    history:                2020-08-21T14:24:56Z ; CMOR rewrote data to be co...\n",
+       "    initialization_index:   1\n",
+       "    institution:            Met Office Hadley Centre, Fitzroy Road, Exeter, D...\n",
+       "    institution_id:         MOHC\n",
+       "    mip_era:                CMIP6\n",
+       "    mo_runid:               u-bu258\n",
+       "    nominal_resolution:     100 km\n",
+       "    parent_activity_id:     CMIP\n",
+       "    parent_experiment_id:   historical\n",
+       "    parent_mip_era:         CMIP6\n",
+       "    parent_source_id:       UKESM1-0-LL\n",
+       "    parent_time_units:      days since 1850-01-01\n",
+       "    parent_variant_label:   r4i1p1f2\n",
+       "    physics_index:          1\n",
+       "    product:                model-output\n",
+       "    realization_index:      2\n",
+       "    realm:                  ocean\n",
+       "    source:                 UKESM1.0-LL (2018): \\naerosol: UKCA-GLOMAP-mode\\n...\n",
+       "    source_id:              UKESM1-0-LL\n",
+       "    source_type:            AOGCM AER BGC CHEM\n",
+       "    sub_experiment:         none\n",
+       "    sub_experiment_id:      none\n",
+       "    table_id:               Omon\n",
+       "    table_info:             Creation Date:(22 July 2019) MD5:4dd1814731b1436d...\n",
+       "    title:                  UKESM1-0-LL output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/a774509f-e0a8-463b-a6ea-d77330aa8c17\n",
+       "    variable_id:            htovgyre\n",
+       "    variable_name:          htovgyre\n",
+       "    variant_label:          r2i1p1f2\n",
+       "    license:                CMIP6 model data produced by the Met Office Hadle...\n",
+       "    cmor_version:           3.4.0"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(420, 3, 330)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"05_ocean_heat_transport_by_basin\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_bnds = source[\"time_bnds\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "basin = [value.decode() if isinstance(value, bytes) else str(value) for value in source[\"sector\"].values]\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "htovgyre_source = source[\"htovgyre\"].values.astype(\"f4\")\n",
+    "htovgyre = np.where(np.isfinite(htovgyre_source), htovgyre_source, missing_value).astype(\"f4\")\n",
+    "\n",
+    "print(htovgyre.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/05_ocean_heat_transport_by_basin/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/htovgyre/tavg-u-hyb-sea/g999/v20260605/htovgyre_tavg-u-hyb-sea_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_201501-204912.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "\n",
+    "ocean_table = cmor.load_table(\"CMIP7_ocean.json\")\n",
+    "\n",
+    "cmor.set_table(ocean_table)\n",
+    "time_id = cmor.axis(\"time\", coord_vals=time, cell_bounds=time_bnds, units=time_units)\n",
+    "basin_id = cmor.axis(\"basin\", coord_vals=basin, units=\"1\")\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "\n",
+    "variable_name = \"htovgyre_tavg-u-hyb-sea\"\n",
+    "htovgyre_id = cmor.variable(variable_name, \"W\", [time_id, basin_id, lat_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"ocean\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(htovgyre_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(htovgyre_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(htovgyre_id, htovgyre)\n",
+    "netcdf_path = Path(cmor.close(htovgyre_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2MB\n",
+       "Dimensions:    (time: 420, bnds: 2, lat: 330, basin: 3)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 3kB 5.942e+04 5.944e+04 ... 7.196e+04 7.198e+04\n",
+       "  * lat        (lat) float64 3kB -85.35 -85.19 -85.04 ... 81.73 81.77 81.79\n",
+       "    sector     (basin) |S21 63B b&#x27;atlantic_arctic_ocean&#x27; ... b&#x27;indian_pacific...\n",
+       "Dimensions without coordinates: bnds, basin\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 7kB 5.94e+04 5.943e+04 ... 7.197e+04 7.2e+04\n",
+       "    lat_bnds   (lat, bnds) float64 5kB -85.42 -85.27 -85.27 ... 81.78 81.78 81.8\n",
+       "    htovgyre   (time, basin, lat) float32 2MB nan nan nan nan ... nan nan nan\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            sea\n",
+       "    branded_variable:      htovgyre_tavg-u-hyb-sea\n",
+       "    branding_suffix:       tavg-u-hyb-sea\n",
+       "    creation_date:         2026-06-05T21:59:34Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:34Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hyb\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 ocean\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_ocean.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/c17c567e-bdad-4306-b790-12e7c390d9ad\n",
+       "    variable_id:           htovgyre\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0da1e3c8-5443-4152-b175-5ae2e7845946' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-0da1e3c8-5443-4152-b175-5ae2e7845946' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 420</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 330</li><li><span>basin</span>: 3</li></ul></div></li><li class='xr-section-item'><input id='section-732d0ddc-ed80-48b2-b943-39b58f06bdaa' class='xr-section-summary-in' type='checkbox' checked /><label for='section-732d0ddc-ed80-48b2-b943-39b58f06bdaa' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.942e+04 5.944e+04 ... 7.198e+04</div><input id='attrs-260ff128-0bb1-4e5b-a63d-cc3f8e7b6616' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-260ff128-0bb1-4e5b-a63d-cc3f8e7b6616' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59302b6a-0425-4b14-820d-fe1312f1711c' class='xr-var-data-in' type='checkbox'><label for='data-59302b6a-0425-4b14-820d-fe1312f1711c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1850-01-01</dd><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([59415., 59445., 59475., ..., 71925., 71955., 71985.], shape=(420,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-85.35 -85.19 ... 81.77 81.79</div><input id='attrs-5dde66bd-296d-4d80-8f95-1989a0e1bb57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dde66bd-296d-4d80-8f95-1989a0e1bb57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4faf192-90f5-49dd-8bcc-ae8058fe8790' class='xr-var-data-in' type='checkbox'><label for='data-e4faf192-90f5-49dd-8bcc-ae8058fe8790' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-85.345169, -85.193054, -85.039757, ...,  81.732368,  81.771011,\n",
+       "        81.789879], shape=(330,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sector</span></div><div class='xr-var-dims'>(basin)</div><div class='xr-var-dtype'>|S21</div><div class='xr-var-preview xr-preview'>b&#x27;atlantic_arctic_ocean&#x27; ... b&#x27;i...</div><input id='attrs-214c2a6d-09b0-45dc-a8d3-ac43a3a61638' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-214c2a6d-09b0-45dc-a8d3-ac43a3a61638' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46513de3-cf07-4298-aee1-7168c6af07ac' class='xr-var-data-in' type='checkbox'><label for='data-46513de3-cf07-4298-aee1-7168c6af07ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Basin</dd><dt><span>standard_name :</span></dt><dd>region</dd></dl></div><div class='xr-var-data'><pre>array([b&#x27;atlantic_arctic_ocean&#x27;, b&#x27;global_ocean&#x27;, b&#x27;indian_pacific_ocean&#x27;],\n",
+       "      dtype=&#x27;|S21&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8bd0ec13-e520-4714-9908-4beb85ddd510' class='xr-section-summary-in' type='checkbox' checked /><label for='section-8bd0ec13-e520-4714-9908-4beb85ddd510' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.94e+04 5.943e+04 ... 7.2e+04</div><input id='attrs-16ca6073-15ee-4c58-a414-f1d007cac7d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16ca6073-15ee-4c58-a414-f1d007cac7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0098504c-2765-45b5-ac37-eeeb86ed9426' class='xr-var-data-in' type='checkbox'><label for='data-0098504c-2765-45b5-ac37-eeeb86ed9426' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[59400., 59430.],\n",
+       "       [59430., 59460.],\n",
+       "       [59460., 59490.],\n",
+       "       [59490., 59520.],\n",
+       "       [59520., 59550.],\n",
+       "       [59550., 59580.],\n",
+       "       [59580., 59610.],\n",
+       "       [59610., 59640.],\n",
+       "       [59640., 59670.],\n",
+       "       [59670., 59700.],\n",
+       "       [59700., 59730.],\n",
+       "       [59730., 59760.],\n",
+       "       [59760., 59790.],\n",
+       "       [59790., 59820.],\n",
+       "       [59820., 59850.],\n",
+       "       [59850., 59880.],\n",
+       "       [59880., 59910.],\n",
+       "       [59910., 59940.],\n",
+       "       [59940., 59970.],\n",
+       "       [59970., 60000.],\n",
+       "...\n",
+       "       [71400., 71430.],\n",
+       "       [71430., 71460.],\n",
+       "       [71460., 71490.],\n",
+       "       [71490., 71520.],\n",
+       "       [71520., 71550.],\n",
+       "       [71550., 71580.],\n",
+       "       [71580., 71610.],\n",
+       "       [71610., 71640.],\n",
+       "       [71640., 71670.],\n",
+       "       [71670., 71700.],\n",
+       "       [71700., 71730.],\n",
+       "       [71730., 71760.],\n",
+       "       [71760., 71790.],\n",
+       "       [71790., 71820.],\n",
+       "       [71820., 71850.],\n",
+       "       [71850., 71880.],\n",
+       "       [71880., 71910.],\n",
+       "       [71910., 71940.],\n",
+       "       [71940., 71970.],\n",
+       "       [71970., 72000.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-85.42 -85.27 -85.27 ... 81.78 81.8</div><input id='attrs-ece5776e-2423-43da-8656-fdf3fe9f6372' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ece5776e-2423-43da-8656-fdf3fe9f6372' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a9c0d18-7415-41b0-ad0f-b2df835dde33' class='xr-var-data-in' type='checkbox'><label for='data-2a9c0d18-7415-41b0-ad0f-b2df835dde33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-85.4212265 , -85.26911163],\n",
+       "       [-85.26911163, -85.1164093 ],\n",
+       "       [-85.1164093 , -84.96253967],\n",
+       "       [-84.96253967, -84.80754089],\n",
+       "       [-84.80754089, -84.65143585],\n",
+       "       [-84.65143585, -84.49424744],\n",
+       "       [-84.49424744, -84.33598328],\n",
+       "       [-84.33598328, -84.176651  ],\n",
+       "       [-84.176651  , -84.01625061],\n",
+       "       [-84.01625061, -83.85476685],\n",
+       "       [-83.85476685, -83.69219971],\n",
+       "       [-83.69219971, -83.52854156],\n",
+       "       [-83.52854156, -83.3637619 ],\n",
+       "       [-83.3637619 , -83.19784546],\n",
+       "       [-83.19784546, -83.03075409],\n",
+       "       [-83.03075409, -82.86247253],\n",
+       "       [-82.86247253, -82.69296265],\n",
+       "       [-82.69296265, -82.52220154],\n",
+       "       [-82.52220154, -82.35012817],\n",
+       "       [-82.35012817, -82.17671967],\n",
+       "...\n",
+       "       [ 77.7896347 ,  78.1543045 ],\n",
+       "       [ 78.1543045 ,  78.50632477],\n",
+       "       [ 78.50632477,  78.84484863],\n",
+       "       [ 78.84484863,  79.16899109],\n",
+       "       [ 79.16899109,  79.47784424],\n",
+       "       [ 79.47784424,  79.77050781],\n",
+       "       [ 79.77050781,  80.04605865],\n",
+       "       [ 80.04605865,  80.30360413],\n",
+       "       [ 80.30360413,  80.54229736],\n",
+       "       [ 80.54229736,  80.76134491],\n",
+       "       [ 80.76134491,  80.96003723],\n",
+       "       [ 80.96003723,  81.13778687],\n",
+       "       [ 81.13778687,  81.29414368],\n",
+       "       [ 81.29414368,  81.42881775],\n",
+       "       [ 81.42881775,  81.54171753],\n",
+       "       [ 81.54171753,  81.63292694],\n",
+       "       [ 81.63292694,  81.70275116],\n",
+       "       [ 81.70275116,  81.75169373],\n",
+       "       [ 81.75169373,  81.78044128],\n",
+       "       [ 81.78044128,  81.79931641]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>htovgyre</span></div><div class='xr-var-dims'>(time, basin, lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6a4a6f79-077a-4055-a240-fe5514fd9d30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a4a6f79-077a-4055-a240-fe5514fd9d30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59ca000e-8c11-4dd1-91c6-aa01780994b4' class='xr-var-data-in' type='checkbox'><label for='data-59ca000e-8c11-4dd1-91c6-aa01780994b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>northward_ocean_heat_transport_due_to_gyre</dd><dt><span>long_name :</span></dt><dd>Northward Ocean Heat Transport Due to Gyre</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>cell_methods :</span></dt><dd>depth: longitude: sum where sea (along a zig-zag grid path spanning a basin)  time: mean</dd></dl></div><div class='xr-var-data'><pre>array([[[           nan,            nan,            nan, ...,\n",
+       "          5.9394045e+12,  5.0293663e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          5.1184492e+12,  4.1131914e+12,  1.5370929e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          2.2064136e+12,  2.5288180e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          1.8157083e+12,  1.9613407e+12, -2.4430687e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          8.4291656e+11,  2.0961806e+12,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "         -6.7581130e+11,  4.5333476e+11,  1.5658895e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "...\n",
+       "          7.0244291e+13,  6.4462036e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.3372432e+13,  1.3172417e+13, -2.8057783e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          6.2237117e+13,  5.6790734e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.1562422e+13,  1.1689368e+13,  5.6201621e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[           nan,            nan,            nan, ...,\n",
+       "          6.0197809e+13,  5.5676689e+13,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "          2.2134275e+13,  1.4477528e+13, -9.6522277e-04],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]]],\n",
+       "      shape=(420, 3, 330), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fab9a14-76a2-446d-8d52-229ba04e00b4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-8fab9a14-76a2-446d-8d52-229ba04e00b4' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>sea</dd><dt><span>branded_variable :</span></dt><dd>htovgyre_tavg-u-hyb-sea</dd><dt><span>branding_suffix :</span></dt><dd>tavg-u-hyb-sea</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:34Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:34Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hyb</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_ocean.json; Creation Date:(2026-04-21 15:01:29) MD5:a66e0fc7ab41aafa94f1ba3223e0c9fe</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/c17c567e-bdad-4306-b790-12e7c390d9ad</dd><dt><span>variable_id :</span></dt><dd>htovgyre</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>u</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2MB\n",
+       "Dimensions:    (time: 420, bnds: 2, lat: 330, basin: 3)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 3kB 5.942e+04 5.944e+04 ... 7.196e+04 7.198e+04\n",
+       "  * lat        (lat) float64 3kB -85.35 -85.19 -85.04 ... 81.73 81.77 81.79\n",
+       "    sector     (basin) |S21 63B b'atlantic_arctic_ocean' ... b'indian_pacific...\n",
+       "Dimensions without coordinates: bnds, basin\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) float64 7kB 5.94e+04 5.943e+04 ... 7.197e+04 7.2e+04\n",
+       "    lat_bnds   (lat, bnds) float64 5kB -85.42 -85.27 -85.27 ... 81.78 81.78 81.8\n",
+       "    htovgyre   (time, basin, lat) float32 2MB nan nan nan nan ... nan nan nan\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            sea\n",
+       "    branded_variable:      htovgyre_tavg-u-hyb-sea\n",
+       "    branding_suffix:       tavg-u-hyb-sea\n",
+       "    creation_date:         2026-06-05T21:59:34Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:34Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hyb\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 ocean\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_ocean.json; Creation Date:(2026-04-21 ...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/c17c567e-bdad-4306-b790-12e7c390d9ad\n",
+       "    variable_id:           htovgyre\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1050x560 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(10.5, 5.6))\n",
+    "basin_values = [value.decode() if isinstance(value, bytes) else str(value) for value in ds[\"sector\"].values]\n",
+    "field = ds[\"htovgyre\"].isel(time=0)\n",
+    "for basin_index, basin_name in enumerate(basin_values):\n",
+    "    ax.plot(ds[\"lat\"].values, field.isel(basin=basin_index).values, label=basin_name.replace(\"_\", \" \"))\n",
+    "ax.axhline(0.0, color=\"0.2\", linewidth=0.8)\n",
+    "ax.set_xlabel(\"Latitude\")\n",
+    "ax.set_ylabel(\"W\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "ax.set_title(f\"CMIP7 htovgyre by basin, {time_label}\")\n",
+    "ax.grid(True, linewidth=0.4, color=\"0.75\")\n",
+    "ax.legend(loc=\"best\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/06_land_use_fraction.ipynb b/notebooks/06_land_use_fraction.ipynb
new file mode 100644
index 00000000..1af41051
--- /dev/null
+++ b/notebooks/06_land_use_fraction.ipynb
@@ -0,0 +1,1901 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0",
+   "metadata": {},
+   "source": [
+    "# Land-Use Fraction\n",
+    "\n",
+    "Create a CMIP7 monthly land-use fraction file (`fracLut_tpt-u-hxy-u`) using time-point, land-use, latitude, and longitude coordinates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATH = Path(\"data\") / \"fracLut_Emon_GFDL-ESM4_land-noLu_r1i1p1f1_gr1_200702-200711.nc\"\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "if not DATA_PATH.exists():\n",
+    "    raise FileNotFoundError(f\"Source data file not found: {DATA_PATH}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2",
+   "metadata": {},
+   "outputs": [
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+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8MB\n",
+       "Dimensions:    (time: 10, landuse: 4, lat: 180, lon: 288, bnds: 2)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 1.122e+05 1.122e+05 ... 1.124e+05 1.125e+05\n",
+       "  * landuse    (landuse) int32 16B 0 1 2 3\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4\n",
+       "  * bnds       (bnds) float64 16B 1.0 2.0\n",
+       "Data variables:\n",
+       "    fracLut    (time, landuse, lat, lon) float32 8MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 5kB 0.0 1.25 1.25 2.5 ... 358.8 358.8 360.0\n",
+       "    time_bnds  (time, bnds) float64 160B 1.122e+05 1.122e+05 ... 1.125e+05\n",
+       "Attributes:\n",
+       "    external_variables:    areacella\n",
+       "    history:               File was processed by fremetar (GFDL analog of CMO...\n",
+       "    table_id:              Emon\n",
+       "    activity_id:           LUMIP\n",
+       "    branch_method:         no parent\n",
+       "    branch_time_in_child:  0.0\n",
+       "    comment:               &lt;null ref&gt;\n",
+       "    contact:               gfdl.climate.model.info@noaa.gov\n",
+       "    Conventions:           CF-1.7 CMIP-6.0 UGRID-1.0\n",
+       "    creation_date:         2019-08-25T02:53:14Z\n",
+       "    data_specs_version:    01.00.27\n",
+       "    experiment:            historical land-only with no land-use change\n",
+       "    experiment_id:         land-noLu\n",
+       "    forcing_index:         1\n",
+       "    frequency:             mon\n",
+       "    further_info_url:      https://furtherinfo.es-doc.org/CMIP6.NOAA-GFDL.GFD...\n",
+       "    grid:                  land data regridded from Cubed-sphere (c96) to 180...\n",
+       "    grid_label:            gr1\n",
+       "    initialization_index:  1\n",
+       "    institution:           National Oceanic and Atmospheric Administration, G...\n",
+       "    institution_id:        NOAA-GFDL\n",
+       "    license:               CMIP6 model data produced by NOAA-GFDL is licensed...\n",
+       "    mip_era:               CMIP6\n",
+       "    nominal_resolution:    100 km\n",
+       "    parent_activity_id:    no parent\n",
+       "    parent_experiment_id:  no parent\n",
+       "    parent_mip_era:        no parent\n",
+       "    parent_source_id:      no parent\n",
+       "    parent_time_units:     no parent\n",
+       "    parent_variant_label:  no parent\n",
+       "    physics_index:         1\n",
+       "    product:               model-output\n",
+       "    realization_index:     1\n",
+       "    realm:                 land\n",
+       "    source:                GFDL-ESM4 (2018):\\natmos: GFDL-AM4.1 (Cubed-sphere...\n",
+       "    source_id:             GFDL-ESM4\n",
+       "    source_type:           LAND BGC\n",
+       "    sub_experiment:        none\n",
+       "    sub_experiment_id:     none\n",
+       "    title:                 NOAA GFDL GFDL-ESM4 model output prepared for CMIP...\n",
+       "    tracking_id:           hdl:21.14100/3325dad3-4bc4-454e-8ab0-53c12ba60e51\n",
+       "    variable_id:           fracLut\n",
+       "    variant_info:          N/A\n",
+       "    references:            see further_info_url attribute\n",
+       "    variant_label:         r1i1p1f1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2a0d8089-973d-41cf-92f6-c7d87f181bf1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-2a0d8089-973d-41cf-92f6-c7d87f181bf1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 10</li><li><span class='xr-has-index'>landuse</span>: 4</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>bnds</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-33327ec1-c254-4d78-9ee0-74c06bc039f9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-33327ec1-c254-4d78-9ee0-74c06bc039f9' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.122e+05 1.122e+05 ... 1.125e+05</div><input id='attrs-0ea964d5-fb1a-4347-ae6f-ffe6ed1834cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ea964d5-fb1a-4347-ae6f-ffe6ed1834cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d333248e-67a3-49c2-bb82-057e86c3ff59' class='xr-var-data-in' type='checkbox'><label for='data-d333248e-67a3-49c2-bb82-057e86c3ff59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>days since 1700-01-01 00:00:00</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>julian</dd><dt><span>calendar :</span></dt><dd>julian</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>description :</span></dt><dd>Temporal mean</dd></dl></div><div class='xr-var-data'><pre>array([112177. , 112206.5, 112237. , 112267.5, 112298. , 112328.5, 112359.5,\n",
+       "       112390. , 112420.5, 112451. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>landuse</span></div><div class='xr-var-dims'>(landuse)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-5ca580d7-cfba-4abf-83b0-c12384c9df92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ca580d7-cfba-4abf-83b0-c12384c9df92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0102b4af-d2bb-4bd4-8ff2-5c02063c4e5d' class='xr-var-data-in' type='checkbox'><label for='data-0102b4af-d2bb-4bd4-8ff2-5c02063c4e5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Land use type</dd><dt><span>standard_name :</span></dt><dd>area_type</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>flag_meanings :</span></dt><dd>psl pst crp urb</dd></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-72cc213b-1c5a-49c0-9e00-22f8c8eb6845' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72cc213b-1c5a-49c0-9e00-22f8c8eb6845' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c0d4c76-fbd8-46de-857e-695b8ffae4b0' class='xr-var-data-in' type='checkbox'><label for='data-9c0d4c76-fbd8-46de-857e-695b8ffae4b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.625 1.875 3.125 ... 358.1 359.4</div><input id='attrs-877951e1-a2f0-4f68-816e-24a1b6129eeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-877951e1-a2f0-4f68-816e-24a1b6129eeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0ba59a6-c2bb-4fcb-9790-a6d1ae924413' class='xr-var-data-in' type='checkbox'><label for='data-c0ba59a6-c2bb-4fcb-9790-a6d1ae924413' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>array([  0.625,   1.875,   3.125, ..., 356.875, 358.125, 359.375], shape=(288,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>bnds</span></div><div class='xr-var-dims'>(bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-54dcef01-5d52-4de1-ba80-43fca1f375be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54dcef01-5d52-4de1-ba80-43fca1f375be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83be2ea3-e248-4603-bf2b-bcb7a5f65530' class='xr-var-data-in' type='checkbox'><label for='data-83be2ea3-e248-4603-bf2b-bcb7a5f65530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertex number</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd7a19b0-d76a-42e1-9175-051f72e22225' class='xr-section-summary-in' type='checkbox' checked /><label for='section-dd7a19b0-d76a-42e1-9175-051f72e22225' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>fracLut</span></div><div class='xr-var-dims'>(time, landuse, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ffa94ba6-1721-45fa-8500-9535b6531b0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffa94ba6-1721-45fa-8500-9535b6531b0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24dfc339-9ece-4770-a1e8-34d9a45fbbc7' class='xr-var-data-in' type='checkbox'><label for='data-24dfc339-9ece-4770-a1e8-34d9a45fbbc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Percentage of grid cell for each land use tile</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area: mean where land over all_area_types time: mean</dd><dt><span>ocean_fillvalue :</span></dt><dd>0.0</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>standard_name :</span></dt><dd>area_fraction</dd><dt><span>interp_method :</span></dt><dd>conserve_order1</dd><dt><span>original_name :</span></dt><dd>fracLut</dd><dt><span>comment :</span></dt><dd>land_area = areacella * fracLut * 0.01</dd></dl></div><div class='xr-var-data'><pre>array([[[[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "...\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]]]],\n",
+       "      shape=(10, 4, 180, 288), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -89.0 ... 89.0 90.0</div><input id='attrs-559109bd-ac2f-4942-ad7f-3c79642fc635' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-559109bd-ac2f-4942-ad7f-3c79642fc635' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbc64d23-81d2-408e-b43d-701f7066a934' class='xr-var-data-in' type='checkbox'><label for='data-cbc64d23-81d2-408e-b43d-701f7066a934' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
+       "       [-89., -88.],\n",
+       "       [-88., -87.],\n",
+       "       [-87., -86.],\n",
+       "       [-86., -85.],\n",
+       "       [-85., -84.],\n",
+       "       [-84., -83.],\n",
+       "       [-83., -82.],\n",
+       "       [-82., -81.],\n",
+       "       [-81., -80.],\n",
+       "       [-80., -79.],\n",
+       "       [-79., -78.],\n",
+       "       [-78., -77.],\n",
+       "       [-77., -76.],\n",
+       "       [-76., -75.],\n",
+       "       [-75., -74.],\n",
+       "       [-74., -73.],\n",
+       "       [-73., -72.],\n",
+       "       [-72., -71.],\n",
+       "       [-71., -70.],\n",
+       "...\n",
+       "       [ 70.,  71.],\n",
+       "       [ 71.,  72.],\n",
+       "       [ 72.,  73.],\n",
+       "       [ 73.,  74.],\n",
+       "       [ 74.,  75.],\n",
+       "       [ 75.,  76.],\n",
+       "       [ 76.,  77.],\n",
+       "       [ 77.,  78.],\n",
+       "       [ 78.,  79.],\n",
+       "       [ 79.,  80.],\n",
+       "       [ 80.,  81.],\n",
+       "       [ 81.,  82.],\n",
+       "       [ 82.,  83.],\n",
+       "       [ 83.,  84.],\n",
+       "       [ 84.,  85.],\n",
+       "       [ 85.,  86.],\n",
+       "       [ 86.,  87.],\n",
+       "       [ 87.,  88.],\n",
+       "       [ 88.,  89.],\n",
+       "       [ 89.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 1.25 ... 358.8 358.8 360.0</div><input id='attrs-301695a8-6715-4c0d-afb1-1b4337559fb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-301695a8-6715-4c0d-afb1-1b4337559fb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb29a09a-675c-4f68-ae54-6d81e662934c' class='xr-var-data-in' type='checkbox'><label for='data-eb29a09a-675c-4f68-ae54-6d81e662934c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[  0.  ,   1.25],\n",
+       "       [  1.25,   2.5 ],\n",
+       "       [  2.5 ,   3.75],\n",
+       "       [  3.75,   5.  ],\n",
+       "       [  5.  ,   6.25],\n",
+       "       [  6.25,   7.5 ],\n",
+       "       [  7.5 ,   8.75],\n",
+       "       [  8.75,  10.  ],\n",
+       "       [ 10.  ,  11.25],\n",
+       "       [ 11.25,  12.5 ],\n",
+       "       [ 12.5 ,  13.75],\n",
+       "       [ 13.75,  15.  ],\n",
+       "       [ 15.  ,  16.25],\n",
+       "       [ 16.25,  17.5 ],\n",
+       "       [ 17.5 ,  18.75],\n",
+       "       [ 18.75,  20.  ],\n",
+       "       [ 20.  ,  21.25],\n",
+       "       [ 21.25,  22.5 ],\n",
+       "       [ 22.5 ,  23.75],\n",
+       "       [ 23.75,  25.  ],\n",
+       "...\n",
+       "       [335.  , 336.25],\n",
+       "       [336.25, 337.5 ],\n",
+       "       [337.5 , 338.75],\n",
+       "       [338.75, 340.  ],\n",
+       "       [340.  , 341.25],\n",
+       "       [341.25, 342.5 ],\n",
+       "       [342.5 , 343.75],\n",
+       "       [343.75, 345.  ],\n",
+       "       [345.  , 346.25],\n",
+       "       [346.25, 347.5 ],\n",
+       "       [347.5 , 348.75],\n",
+       "       [348.75, 350.  ],\n",
+       "       [350.  , 351.25],\n",
+       "       [351.25, 352.5 ],\n",
+       "       [352.5 , 353.75],\n",
+       "       [353.75, 355.  ],\n",
+       "       [355.  , 356.25],\n",
+       "       [356.25, 357.5 ],\n",
+       "       [357.5 , 358.75],\n",
+       "       [358.75, 360.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.122e+05 1.122e+05 ... 1.125e+05</div><input id='attrs-9a3c183e-fb0e-45f1-9e7d-d2cc8dfcc49b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a3c183e-fb0e-45f1-9e7d-d2cc8dfcc49b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cbd473e-9dcf-4c68-890a-9d8e9596c139' class='xr-var-data-in' type='checkbox'><label for='data-0cbd473e-9dcf-4c68-890a-9d8e9596c139' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><pre>array([[112163., 112191.],\n",
+       "       [112191., 112222.],\n",
+       "       [112222., 112252.],\n",
+       "       [112252., 112283.],\n",
+       "       [112283., 112313.],\n",
+       "       [112313., 112344.],\n",
+       "       [112344., 112375.],\n",
+       "       [112375., 112405.],\n",
+       "       [112405., 112436.],\n",
+       "       [112436., 112466.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02bb80d7-d7cf-41f1-b656-d6fda6632f22' class='xr-section-summary-in' type='checkbox' checked /><label for='section-02bb80d7-d7cf-41f1-b656-d6fda6632f22' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(45)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>history :</span></dt><dd>File was processed by fremetar (GFDL analog of CMOR). TripleID: [exper_id_c4DzO28Hvy,realiz_id_ae3CbHYiNT,run_id_iBo24qg7Yw]</dd><dt><span>table_id :</span></dt><dd>Emon</dd><dt><span>activity_id :</span></dt><dd>LUMIP</dd><dt><span>branch_method :</span></dt><dd>no parent</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>&lt;null ref&gt;</dd><dt><span>contact :</span></dt><dd>gfdl.climate.model.info@noaa.gov</dd><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.0 UGRID-1.0</dd><dt><span>creation_date :</span></dt><dd>2019-08-25T02:53:14Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.27</dd><dt><span>experiment :</span></dt><dd>historical land-only with no land-use change</dd><dt><span>experiment_id :</span></dt><dd>land-noLu</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NOAA-GFDL.GFDL-ESM4.land-noLu.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>land data regridded from Cubed-sphere (c96) to 180,288; interpolation method: conserve_order1</dd><dt><span>grid_label :</span></dt><dd>gr1</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA</dd><dt><span>institution_id :</span></dt><dd>NOAA-GFDL</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by NOAA-GFDL is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>no parent</dd><dt><span>parent_experiment_id :</span></dt><dd>no parent</dd><dt><span>parent_mip_era :</span></dt><dd>no parent</dd><dt><span>parent_source_id :</span></dt><dd>no parent</dd><dt><span>parent_time_units :</span></dt><dd>no parent</dd><dt><span>parent_variant_label :</span></dt><dd>no parent</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>land</dd><dt><span>source :</span></dt><dd>GFDL-ESM4 (2018):\n",
+       "atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa)\n",
+       "ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m)\n",
+       "seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories)\n",
+       "land: GFDL-LM4.1\n",
+       "aerosol: interactive\n",
+       "atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry)\n",
+       "ocnBgchem: GFDL-COBALTv2\n",
+       "landIce: GFDL-LM4.1\n",
+       "(GFDL ID: 2019_0385)</dd><dt><span>source_id :</span></dt><dd>GFDL-ESM4</dd><dt><span>source_type :</span></dt><dd>LAND BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>title :</span></dt><dd>NOAA GFDL GFDL-ESM4 model output prepared for CMIP6 historical land-only with no land-use change</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/3325dad3-4bc4-454e-8ab0-53c12ba60e51</dd><dt><span>variable_id :</span></dt><dd>fracLut</dd><dt><span>variant_info :</span></dt><dd>N/A</dd><dt><span>references :</span></dt><dd>see further_info_url attribute</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 8MB\n",
+       "Dimensions:    (time: 10, landuse: 4, lat: 180, lon: 288, bnds: 2)\n",
+       "Coordinates:\n",
+       "  * time       (time) float64 80B 1.122e+05 1.122e+05 ... 1.124e+05 1.125e+05\n",
+       "  * landuse    (landuse) int32 16B 0 1 2 3\n",
+       "  * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4\n",
+       "  * bnds       (bnds) float64 16B 1.0 2.0\n",
+       "Data variables:\n",
+       "    fracLut    (time, landuse, lat, lon) float32 8MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    lat_bnds   (lat, bnds) float64 3kB -90.0 -89.0 -89.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds   (lon, bnds) float64 5kB 0.0 1.25 1.25 2.5 ... 358.8 358.8 360.0\n",
+       "    time_bnds  (time, bnds) float64 160B 1.122e+05 1.122e+05 ... 1.125e+05\n",
+       "Attributes:\n",
+       "    external_variables:    areacella\n",
+       "    history:               File was processed by fremetar (GFDL analog of CMO...\n",
+       "    table_id:              Emon\n",
+       "    activity_id:           LUMIP\n",
+       "    branch_method:         no parent\n",
+       "    branch_time_in_child:  0.0\n",
+       "    comment:               <null ref>\n",
+       "    contact:               gfdl.climate.model.info@noaa.gov\n",
+       "    Conventions:           CF-1.7 CMIP-6.0 UGRID-1.0\n",
+       "    creation_date:         2019-08-25T02:53:14Z\n",
+       "    data_specs_version:    01.00.27\n",
+       "    experiment:            historical land-only with no land-use change\n",
+       "    experiment_id:         land-noLu\n",
+       "    forcing_index:         1\n",
+       "    frequency:             mon\n",
+       "    further_info_url:      https://furtherinfo.es-doc.org/CMIP6.NOAA-GFDL.GFD...\n",
+       "    grid:                  land data regridded from Cubed-sphere (c96) to 180...\n",
+       "    grid_label:            gr1\n",
+       "    initialization_index:  1\n",
+       "    institution:           National Oceanic and Atmospheric Administration, G...\n",
+       "    institution_id:        NOAA-GFDL\n",
+       "    license:               CMIP6 model data produced by NOAA-GFDL is licensed...\n",
+       "    mip_era:               CMIP6\n",
+       "    nominal_resolution:    100 km\n",
+       "    parent_activity_id:    no parent\n",
+       "    parent_experiment_id:  no parent\n",
+       "    parent_mip_era:        no parent\n",
+       "    parent_source_id:      no parent\n",
+       "    parent_time_units:     no parent\n",
+       "    parent_variant_label:  no parent\n",
+       "    physics_index:         1\n",
+       "    product:               model-output\n",
+       "    realization_index:     1\n",
+       "    realm:                 land\n",
+       "    source:                GFDL-ESM4 (2018):\\natmos: GFDL-AM4.1 (Cubed-sphere...\n",
+       "    source_id:             GFDL-ESM4\n",
+       "    source_type:           LAND BGC\n",
+       "    sub_experiment:        none\n",
+       "    sub_experiment_id:     none\n",
+       "    title:                 NOAA GFDL GFDL-ESM4 model output prepared for CMIP...\n",
+       "    tracking_id:           hdl:21.14100/3325dad3-4bc4-454e-8ab0-53c12ba60e51\n",
+       "    variable_id:           fracLut\n",
+       "    variant_info:          N/A\n",
+       "    references:            see further_info_url attribute\n",
+       "    variant_label:         r1i1p1f1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATH, decode_times=False) as opened:\n",
+    "    source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(source)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(10, 4, 180, 288)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"06_land_use_fraction\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": source[\"time\"].attrs.get(\"calendar\", \"standard\"),\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"100 km\",\n",
+    "    \"outpath\": str(output_dir),\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"region\": \"glb\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "input_json = run_dir / \"input.json\"\n",
+    "input_json.write_text(json.dumps(DATASET_INFO, indent=2, sort_keys=True))\n",
+    "\n",
+    "time = source[\"time\"].values.astype(\"f8\")\n",
+    "time_units = source[\"time\"].attrs[\"units\"]\n",
+    "lat = source[\"lat\"].values.astype(\"f8\")\n",
+    "lat_bnds = source[\"lat_bnds\"].values.astype(\"f8\")\n",
+    "lon = source[\"lon\"].values.astype(\"f8\")\n",
+    "lon_bnds = source[\"lon_bnds\"].values.astype(\"f8\")\n",
+    "landuse = [\n",
+    "    \"primary_and_secondary_land\",\n",
+    "    \"pastures\",\n",
+    "    \"crops\",\n",
+    "    \"urban\",\n",
+    "]\n",
+    "\n",
+    "missing_value = np.float32(1.0e20)\n",
+    "frac_lut_source = source[\"fracLut\"].values.astype(\"f4\")\n",
+    "frac_lut = np.where(np.isfinite(frac_lut_source), frac_lut_source, missing_value).astype(\"f4\")\n",
+    "\n",
+    "print(frac_lut.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "output/06_land_use_fraction/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/glb/mon/fracLut/tpt-u-hxy-u/g999/v20260605/fracLut_tpt-u-hxy-u_mon_glb_g999_DUMMY-MODEL_amip_r9i1p1f3_200702-200711.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "cmor.setup(\n",
+    "    inpath=TABLES_DIR,\n",
+    "    netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "    logfile=str(run_dir / \"cmor.log\"),\n",
+    ")\n",
+    "cmor.dataset_json(str(input_json))\n",
+    "cmor.load_table(\"CMIP7_land.json\")\n",
+    "\n",
+    "time_id = cmor.axis(\"time1\", coord_vals=time, units=time_units)\n",
+    "landuse_id = cmor.axis(\"landuse\", coord_vals=landuse, units=\"1\")\n",
+    "lat_id = cmor.axis(\"latitude\", coord_vals=lat, cell_bounds=lat_bnds, units=\"degrees_north\")\n",
+    "lon_id = cmor.axis(\"longitude\", coord_vals=lon, cell_bounds=lon_bnds, units=\"degrees_east\")\n",
+    "\n",
+    "variable_name = \"fracLut_tpt-u-hxy-u\"\n",
+    "frac_lut_id = cmor.variable(variable_name, \"%\", [time_id, landuse_id, lat_id, lon_id], missing_value=missing_value)\n",
+    "compound_name = \".\".join([\"land\"] + variable_name.split(\"_\") + [\"mon\", \"glb\"])\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_cell_measures.json\") as handle:\n",
+    "    cell_measure = json.load(handle)[\"cell_measures\"].get(compound_name)\n",
+    "if cell_measure:\n",
+    "    cmor.set_variable_attribute(frac_lut_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "with open(Path(TABLES_DIR) / \"CMIP7_long_name_overrides.json\") as handle:\n",
+    "    long_name = json.load(handle)[\"long_name_overrides\"].get(compound_name)\n",
+    "if long_name:\n",
+    "    cmor.set_variable_attribute(frac_lut_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "cmor.write(frac_lut_id, frac_lut)\n",
+    "netcdf_path = Path(cmor.close(frac_lut_id, file_name=True))\n",
+    "cmor.close()\n",
+    "\n",
+    "print(netcdf_path.resolve().relative_to(Path.cwd().resolve()))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8MB\n",
+       "Dimensions:   (lat: 180, bnds: 2, lon: 288, time: 10, landuse: 4)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon       (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4\n",
+       "  * time      (time) float64 80B 1.122e+05 1.122e+05 ... 1.124e+05 1.125e+05\n",
+       "    sector    (landuse) |S26 104B b&#x27;primary_and_secondary_land&#x27; ... b&#x27;urban&#x27;\n",
+       "Dimensions without coordinates: bnds, landuse\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 3kB -90.0 -89.0 -89.0 -88.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 5kB 0.0 1.25 1.25 2.5 ... 358.8 358.8 360.0\n",
+       "    fracLut   (time, landuse, lat, lon) float32 8MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      fracLut_tpt-u-hxy-u\n",
+       "    branding_suffix:       tpt-u-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:37Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:37Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 land\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_land.json; Creation Date:(2026-04-21 1...\n",
+       "    temporal_label:        tpt\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/a1f5a1e2-37d7-4c50-ba58-b130068b50bc\n",
+       "    variable_id:           fracLut\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8e50a1c3-1a84-464a-8dcc-71a83b7a1ece' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-8e50a1c3-1a84-464a-8dcc-71a83b7a1ece' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 180</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>time</span>: 10</li><li><span>landuse</span>: 4</li></ul></div></li><li class='xr-section-item'><input id='section-932617fc-49d7-4675-b25f-794ea2cb4bc8' class='xr-section-summary-in' type='checkbox' checked /><label for='section-932617fc-49d7-4675-b25f-794ea2cb4bc8' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-b4e5b0e0-e4e1-426a-b2d5-ee7e69642af2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4e5b0e0-e4e1-426a-b2d5-ee7e69642af2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa44324c-f75e-43de-a1fd-619172407e70' class='xr-var-data-in' type='checkbox'><label for='data-fa44324c-f75e-43de-a1fd-619172407e70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.625 1.875 3.125 ... 358.1 359.4</div><input id='attrs-5a1db95a-ac9c-48c7-92c1-6dcdab7a77d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a1db95a-ac9c-48c7-92c1-6dcdab7a77d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca3a3557-fcc5-42d0-8389-a036346b1852' class='xr-var-data-in' type='checkbox'><label for='data-ca3a3557-fcc5-42d0-8389-a036346b1852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.625,   1.875,   3.125, ..., 356.875, 358.125, 359.375], shape=(288,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.122e+05 1.122e+05 ... 1.125e+05</div><input id='attrs-e1db81c2-be72-4cef-9660-cf916cd4e394' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1db81c2-be72-4cef-9660-cf916cd4e394' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e673230a-6aba-49fc-95d3-e5e465ae70e3' class='xr-var-data-in' type='checkbox'><label for='data-e673230a-6aba-49fc-95d3-e5e465ae70e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>days since 1700-01-01 00:00:00</dd><dt><span>calendar :</span></dt><dd>julian</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Points</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([112177. , 112206.5, 112237. , 112267.5, 112298. , 112328.5, 112359.5,\n",
+       "       112390. , 112420.5, 112451. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sector</span></div><div class='xr-var-dims'>(landuse)</div><div class='xr-var-dtype'>|S26</div><div class='xr-var-preview xr-preview'>b&#x27;primary_and_secondary_land&#x27; .....</div><input id='attrs-3843b1c2-6ceb-4b5f-82af-b497ee12c003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3843b1c2-6ceb-4b5f-82af-b497ee12c003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03adcbbb-aba6-4138-9b69-0a43c2e85212' class='xr-var-data-in' type='checkbox'><label for='data-03adcbbb-aba6-4138-9b69-0a43c2e85212' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Land use type</dd><dt><span>standard_name :</span></dt><dd>area_type</dd></dl></div><div class='xr-var-data'><pre>array([b&#x27;primary_and_secondary_land&#x27;, b&#x27;pastures&#x27;, b&#x27;crops&#x27;, b&#x27;urban&#x27;],\n",
+       "      dtype=&#x27;|S26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fde3890c-fde5-407c-ac31-e9bc7da6cd02' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fde3890c-fde5-407c-ac31-e9bc7da6cd02' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -89.0 ... 89.0 90.0</div><input id='attrs-94d3d6a3-89ec-4315-a919-821fa0597b91' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94d3d6a3-89ec-4315-a919-821fa0597b91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57bad24b-4203-4155-a410-7bf171324c42' class='xr-var-data-in' type='checkbox'><label for='data-57bad24b-4203-4155-a410-7bf171324c42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
+       "       [-89., -88.],\n",
+       "       [-88., -87.],\n",
+       "       [-87., -86.],\n",
+       "       [-86., -85.],\n",
+       "       [-85., -84.],\n",
+       "       [-84., -83.],\n",
+       "       [-83., -82.],\n",
+       "       [-82., -81.],\n",
+       "       [-81., -80.],\n",
+       "       [-80., -79.],\n",
+       "       [-79., -78.],\n",
+       "       [-78., -77.],\n",
+       "       [-77., -76.],\n",
+       "       [-76., -75.],\n",
+       "       [-75., -74.],\n",
+       "       [-74., -73.],\n",
+       "       [-73., -72.],\n",
+       "       [-72., -71.],\n",
+       "       [-71., -70.],\n",
+       "...\n",
+       "       [ 70.,  71.],\n",
+       "       [ 71.,  72.],\n",
+       "       [ 72.,  73.],\n",
+       "       [ 73.,  74.],\n",
+       "       [ 74.,  75.],\n",
+       "       [ 75.,  76.],\n",
+       "       [ 76.,  77.],\n",
+       "       [ 77.,  78.],\n",
+       "       [ 78.,  79.],\n",
+       "       [ 79.,  80.],\n",
+       "       [ 80.,  81.],\n",
+       "       [ 81.,  82.],\n",
+       "       [ 82.,  83.],\n",
+       "       [ 83.,  84.],\n",
+       "       [ 84.,  85.],\n",
+       "       [ 85.,  86.],\n",
+       "       [ 86.,  87.],\n",
+       "       [ 87.,  88.],\n",
+       "       [ 88.,  89.],\n",
+       "       [ 89.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 1.25 ... 358.8 358.8 360.0</div><input id='attrs-9609ea40-8e52-4356-92ca-2f9d2281f780' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9609ea40-8e52-4356-92ca-2f9d2281f780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a1ad8b5-ecf8-41c1-86cc-ff445735ef1c' class='xr-var-data-in' type='checkbox'><label for='data-3a1ad8b5-ecf8-41c1-86cc-ff445735ef1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0.  ,   1.25],\n",
+       "       [  1.25,   2.5 ],\n",
+       "       [  2.5 ,   3.75],\n",
+       "       [  3.75,   5.  ],\n",
+       "       [  5.  ,   6.25],\n",
+       "       [  6.25,   7.5 ],\n",
+       "       [  7.5 ,   8.75],\n",
+       "       [  8.75,  10.  ],\n",
+       "       [ 10.  ,  11.25],\n",
+       "       [ 11.25,  12.5 ],\n",
+       "       [ 12.5 ,  13.75],\n",
+       "       [ 13.75,  15.  ],\n",
+       "       [ 15.  ,  16.25],\n",
+       "       [ 16.25,  17.5 ],\n",
+       "       [ 17.5 ,  18.75],\n",
+       "       [ 18.75,  20.  ],\n",
+       "       [ 20.  ,  21.25],\n",
+       "       [ 21.25,  22.5 ],\n",
+       "       [ 22.5 ,  23.75],\n",
+       "       [ 23.75,  25.  ],\n",
+       "...\n",
+       "       [335.  , 336.25],\n",
+       "       [336.25, 337.5 ],\n",
+       "       [337.5 , 338.75],\n",
+       "       [338.75, 340.  ],\n",
+       "       [340.  , 341.25],\n",
+       "       [341.25, 342.5 ],\n",
+       "       [342.5 , 343.75],\n",
+       "       [343.75, 345.  ],\n",
+       "       [345.  , 346.25],\n",
+       "       [346.25, 347.5 ],\n",
+       "       [347.5 , 348.75],\n",
+       "       [348.75, 350.  ],\n",
+       "       [350.  , 351.25],\n",
+       "       [351.25, 352.5 ],\n",
+       "       [352.5 , 353.75],\n",
+       "       [353.75, 355.  ],\n",
+       "       [355.  , 356.25],\n",
+       "       [356.25, 357.5 ],\n",
+       "       [357.5 , 358.75],\n",
+       "       [358.75, 360.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fracLut</span></div><div class='xr-var-dims'>(time, landuse, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-cea4b629-ed2d-478c-9ded-f88c2adc1f48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cea4b629-ed2d-478c-9ded-f88c2adc1f48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df9db738-f18f-4d60-a6f7-d100cbbae820' class='xr-var-data-in' type='checkbox'><label for='data-df9db738-f18f-4d60-a6f7-d100cbbae820' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>area_fraction</dd><dt><span>long_name :</span></dt><dd>Percentage of Grid Cell for Each Land-Use Tile</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "...\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
+       "\n",
+       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         ...,\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.],\n",
+       "         [0., 0., 0., ..., 0., 0., 0.]]]],\n",
+       "      shape=(10, 4, 180, 288), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-59cf2122-5f47-4fae-a3a5-34d0966dc2e1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-59cf2122-5f47-4fae-a3a5-34d0966dc2e1' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>u</dd><dt><span>branded_variable :</span></dt><dd>fracLut_tpt-u-hxy-u</dd><dt><span>branding_suffix :</span></dt><dd>tpt-u-hxy-u</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:37Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:37Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>land</dd><dt><span>region :</span></dt><dd>glb</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_land.json; Creation Date:(2026-04-21 15:01:29) MD5:bafb8e42cac0efce87531baf8e7d21b2</dd><dt><span>temporal_label :</span></dt><dd>tpt</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/a1f5a1e2-37d7-4c50-ba58-b130068b50bc</dd><dt><span>variable_id :</span></dt><dd>fracLut</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>u</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 8MB\n",
+       "Dimensions:   (lat: 180, bnds: 2, lon: 288, time: 10, landuse: 4)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon       (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4\n",
+       "  * time      (time) float64 80B 1.122e+05 1.122e+05 ... 1.124e+05 1.125e+05\n",
+       "    sector    (landuse) |S26 104B b'primary_and_secondary_land' ... b'urban'\n",
+       "Dimensions without coordinates: bnds, landuse\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 3kB -90.0 -89.0 -89.0 -88.0 ... 89.0 89.0 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 5kB 0.0 1.25 1.25 2.5 ... 358.8 358.8 360.0\n",
+       "    fracLut   (time, landuse, lat, lon) float32 8MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      fracLut_tpt-u-hxy-u\n",
+       "    branding_suffix:       tpt-u-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:37Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    external_variables:    areacella\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:37Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    100 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 land\n",
+       "    region:                glb\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_land.json; Creation Date:(2026-04-21 1...\n",
+       "    temporal_label:        tpt\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/a1f5a1e2-37d7-4c50-ba58-b130068b50bc\n",
+       "    variable_id:           fracLut\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_path, decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=80,\n",
+    "):\n",
+    "    display(ds)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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qnMPG9MB5A3OkGnDbpZq1IAiCIDQcIjwKgiAIwgHCB2sWX6GLkCHO9YUP6HQGssBJYBGHgwHFAIqdLJRysPjyyy+V04mCk2+oIwUsX7gdFGNYLOVA950OP4Zm+sJQ6EDhYX9CuLmNdIr6CkMbNmxQ777FJygOsnAOxTQKuyyQElgwpK5QuGPlbRb58IX76Ftso64YVYPpuvN1+tHdRtHb11nG8GBfWHXa10XJbTDCqX3dlIHwHOOL1bZ53rFNWGTo6quvVseeYepDhgypl5uyIULxjWJOFNjqI9ofKFwvHXV1XafhzPSF511dC57UdE0Yx8vX5cpzjX+z+I9vu7KAUn3o3r07+vTpo85/OjC3b99eLVR6b7BSOQtNUVyfOHFijfPwPsFQeKa58HWmGkWUjPsIt4UCMlMM+IZM855AF3ZtYdTcdgrjHDgRBEEQBOHAkRyPgiAIgnCA0L3EytAUU1h5OBA6hhgyWxv8Hh/w6QY72LCS69q1a/fLWVkf6JaigOHrhGNIMt1EvtBhRacWK0MHuvjq69SjqBOYI4+CcKAbz6jiXZMgszdYbdl32/g3XZwjR470m48uLQqpdI6xHeiC3B/43cA2YOh2TW6vukDnJV2Er7/+uhJfDFhVOrAtKIz5vgz3mCHY+bYzc4wyTNcXhncHbrshCBmhrxR+eGzo5gyE+QX3dXz29zgShtFStKKrtKYclKz6fjDgPnOAgoJ8INwP7rcvvF58jzcrTFNgO/nkk+u0Ph4vOkx9jzdTIKSnp/vNZ7gffY8Z18NtrS88/3/++WcluDNUua7byorYrGxOcZqVsWvj7LPPVucNr20DnlMc1KCD3KjOTpclz126OX1TYdDlSvG3pvBvHneK4azQXd/K4IIgCIIg1Iw4HgVBEAThAOHDPd1c5513nnItMtyQbhs+7M+bN0+JRQxj3JsTjS6fQ4ER1tpQYda1QdcfxYMxY8YokZO56+hmYvEb5rgz4N///e9/lfjEohtnnnmmckguXrxYhUIy1NNXFKAztKZ8c9wfCrgsnMLcggxnZd5MCjyB7kAKYBRannzySZVjkOujA7C2XIOE7k3mnLvsssuUuMGCMT/++KMKpw4MCea+U3Dhcafosrfl7stJS0GWRWMGDx6MlStXquMXmI+xrlAkZftde+21an95vtLpSMGmrsscNWqUyiV51VVXeYXVd955R7UB3W0GFCIZLksBh9cHhZ8333xTiX1jx4715oHktvAY04HGZXMb6fJj21Gsp8hUGyxCQyhWUUisj8jL7WAuQopkffv2Vd8z9oHHlS5MQ2imYM5zjMeeIu2BwDb77rvv1LHlPYH7QOGWx5auQ67L93zl9TF06FBVOIbimiHm1RaqHQivCS6X1yFFTw6CUIgzBGQDbg/djjxePH95XlCgZu5VinT1gdc7t4/FrbjdPKb7goIq75vcNwr5geH3PP+Nc5TXH0XDyZMnq/sK24jnG9su0B1Mpy2/y3PtmmuuwY4dO9QAD881tklN4ifF34N9fxQEQRCEo4qAKteCIAiCIOwnGzZs0CZMmKC1adNGs9vtWkREhDZkyBDt5Zdf1srLy73ztW7dWhs3btxelzVt2jRaj7TFixd7p02ZMkVNy87O9k677LLLtLCwsDptn9vt1lJSUrS+ffvWe99qWw+358Ybb6zxO2+//bbWoUMHLSgoSOvcubPaJ2MfAnnnnXe0Pn36qHljYmK04cOHa7/88ov3c/7N79X0GjlypHf/Jk6cqMXHx2uhoaHa6NGjtbS0NNXe3H5f3nzzTa1du3aaxWJRy/j999/3ue+bNm3SRo0apZadlJSk9oXrrIkbbrhBLffjjz/W6krgdvKcueOOO7RmzZppISEh6lyaP3++agu+DLjtXNf06dP9lrdlyxY1ne3uy6uvvqq1bdtWtXX//v21OXPmVFvm3vjnn3+0AQMGqHO8VatW2nPPPec9X7lOsnTpUu2CCy5Qn3M9iYmJ2vjx47UlS5ZUW97UqVO1fv36qX3kNdOjRw/t7rvv1nbt2rXX7XC5XNrNN9+sJSQkaCaTye+84v95fAwCt8+37XieREVFacHBwVpqaqp2+eWX+23nypUr1XcnTZq0z7apy7VdVFSkTZ48WWvfvr1qQ56vgwcP1p555hnN4XD4Hbunn35ae/bZZ7WWLVuqdhw2bJi2YsUKv+Xt6x7A7/O65/d5DnHfAo+3x+PRHnvsMbX9nI/X4g8//KCWzWkGvtu1N8aOHavmmzdvnlYXjONT2yvwHC4rK9PuvPNOLTk5WW3vMccco82cObPGZc+dO1e1L48vzxXerwoLC2ucd+DAgepc5bklCIIgCELDYOI/jS1+CoIgCIIgHEmwwAzdV6wOLSGbhzd0btLBR7dgUlJSY2/OYQGdk3RxpqWlNfamCIIgCILQyEiOR0EQBEEQhAakvLxchbMy5FtEx8MfFjJhOLeIjnWDxZwYrl5TRWpBEARBEI4+xPEoCIIgCILQADDfHAtTMKcei4IsXbr0kFQpF4SmAPNCsor7W2+9pXK00iGanJzc2JslCIIgCEIjI8VlBEEQBEEQGgBWsmZRChaTeemll0R0FI4q/vzzT1UIicWHWOxFREdBEARBEIg4HgVBEARBEARBEARBEARBaHAkx6MgCIIgCIIgCIIgCIIgCA2OCI+CIAiCIAiCIAiCIAiCIDQ4IjwKgiAIgiAIgiAIgiAIgtDgiPAoCIIgCIIgCIIgCIIgCEKDI8KjIAiCIAiCIAiCIAiCIAgNjgiPgiAIgiAIgiAIgiAIgiA0OCI8CoIgCIIgCIIgCIIgCILQ4IjwKAiCIAiCIAiCIAiCIAhCgyPCoyAIgiAIgiAIgiAIgiAIDY4Ij4IgCIIgCIIgCIIgCIIgNDgiPAqCIAiCIAiCIAiCIAiC0OCI8CgIgiAIgiAIgiAIgiAIQoMjwqMgCIIgCIIgCIIgCIIgCA2OCI+CIAiCIAiCIAiCIAiCIDQ4IjwKgiAIgiAIgiAIgiAIgtDgiPAoCIIgCIIgCIIgCIIgCEKDI8KjIAiCIAiCIAiCIAiCIAgNjgiPgiAIgiAIgiAIgiAIgiA0OCI8CoIgCIIgCIIgCIIgCILQ4IjwKAiCIAiCIAiCIAiCIAhCgyPCoyAIgiAIgiAIgiAIgiAIIjwKgiAIgiAIgiAIgiAIgtD0EcejIAiCIAiCIAiCIAiCIAgNjgiPgiAIgiAIgiAIgiAIgiA0OCI8CoIgCIIgCIIgCIIgCILQ4IjwKAiCIAiCIAiCIAiCIAhCgyPCoyAIgiAIgiAIgiAIgiAIDY4Ij4IgCIIgCIIgCIIgCIIgNDgiPAqCIAiCIAiCIAiCIAiC0OCI8CgIgiAIgiAIgiAIgiAIQoMjwqMgCIIgCIIgCIIgCIIgCA2OCI+CIAiCIAiCIAiCIAiCIDQ4IjwKwkHEZDLhgQcekDbeD9hubL+jmaZ2/vzxxx9qm/h+qNm6data97vvvnvI1y0IgiAIgiAIgiDsHyI8CoIgCIIgCIIgCF5KS0vV4GdjDDYKgiAIRxbWxt4AQTiSKSsrg9Uql5kgCIIgCIJweAmPDz74oPr/8ccf39ibIwiCIBzGiONREBoYj8eD8vJy9f/g4OAmIzy6XC44HI7G3gyhkSgpKZG2FwRBEAShUZH+qCAIwtGHCI+CsJf8guvWrcO5556LyMhIxMXF4dZbb/WKigac76abbsJHH32Ebt26ISgoCDNnzqwxR5+x3A0bNuDiiy9GVFQUEhIScN9990HTNKSnp+O0005T60tOTsazzz7rty4Kh/fffz/69eunvhsWFoZhw4bh999/rzEf3jPPPIMXXngBqamparsWLVqkvsP9CGTHjh2wWCx4/PHH93pOcJmDBw9W7RESEqK25Ysvvqg2n9Eu33zzDbp3767Wz/Yx2saXv/76C8ccc4wSarmtb7zxRp3Py40bN+Kss85S7cXvt2jRAueffz4KCgr85vvwww/VtnKbY2Nj1Txs70AWLlyIsWPHIiYmRrVVz5498eKLL/rN89tvv6l25+fR0dHqmK1du9ZvHuNYp6Wl4fLLL1fz8ZhdccUVykXgS0VFBf7zn/+ocyEiIgKnnnqqOh6BbNu2DTfccAM6deqk9oPH4JxzzlHH2xfmQeS6//zzTzV/YmKiaheeJ5z+9ddfV1v2xx9/rD6bP38+6sPcuXPVNrRq1Uod45YtW6p9odvXF7ZBeHg4du7cidNPP139n/t75513wu12+82bn5+v5md7sd0uu+wyNU0QBEEQjlbq2jedNm0aRowYoX77+bvctWtXvPbaa9WWt2TJEowePRrx8fGqT9G2bVtceeWV6jP2K/gbTeh65Hp9+7R0QNbkguRvd5s2bfbZH12zZo36nPty9tlnq34Z+3D9+/fHd99957dMp9OptqFDhw5qHu7z0KFD8csvvzRY2wqCIAgHl6ZhxRKEJgo7duxAUYxbsGABXnrpJeTl5eH999+vJkR9/vnnSmhjB86301UT5513Hrp06YInnngCP/74Ix555BHV6aLgxs7ik08+qYRMijIU5I477jj1vcLCQrz11lu44IILMGHCBBQVFeHtt99WHUeKir179/ZbDzuf7Ixec801qqNHceiMM87AZ599hueee04JjQaffPKJEj8vuuiivW47RTgKY5yPQuinn36qhKcffvgB48aNqyYofvXVV0r8oqDG9qNIuH37dtVxJCtXrsSoUaNUB5cdWo6ET5kyBUlJSfs8Plw/953C3c0336zERwpb3BYKVRSuyKOPPqrEXR7Pq6++GtnZ2Xj55ZdVuy5btkyJW4Sd2PHjx6NZs2aqI8/lUVDk8gyxdvbs2Tj55JPRrl07tb0U2LisIUOGYOnSpdWOPdfJzjzPIX7O48eHAR5jA24ThdELL7xQibo8nwLbkixevBjz5s1ToimFRHbo+TDBzj878aGhoX7zs93ZrhSr6XjkfBQGeW7xPPCF0/hAMGjQINSH6dOnKyH1+uuvV8eU5yHbg8IpP/OFAiOP14ABA9RDCNuS4jrXy+8TnoMUcnnuXHfddeo6oVBK8VEQBEEQjnb21Tdlv4ADveyrMerm+++/V/0BRuTceOONap6srCxv32vSpEmqH8Q+BftshNO5HP42s79w5plnqukcjN0fAvuj7POuXr1a9Z1SUlLUNnAwl31pDk5++eWX3n4K+1rcV/aVjj32WNUXpmjKPtVJJ53UQK0qCIIgHFQ0QRCqMWXKFI2Xx6mnnuo3/YYbblDTV6xY4Z3Gv81ms7Z69epqy+FnXFbgcq+55hrvNJfLpbVo0UIzmUzaE0884Z2el5enhYSEaJdddpnfvBUVFX7r4HxJSUnalVde6Z22ZcsWtZ7IyEgtKyvLb/5Zs2apz3766Se/6T179tSGDx++z7OhtLTU72+Hw6F1795dGzFiRLV9t9vtWlpamnca243TX375Ze+0008/XQsODta2bdvmnbZmzRrNYrGoeffGsmXL1DzTp0+vdZ6tW7eqZT366KN+01euXKlZrVbvdLZt27ZttdatW6s29cXj8Xj/37t3by0xMVHLycnx2y+eA5deemm1Y+17XMgZZ5yhxcXFef9evny5mo/nli8XXnhhtfMnsO3J/Pnz1Xzvv/++d9q0adPUtKFDh6r98mXy5MlaUFCQlp+f753Gc4Rt4buumvj999/Vcvm+t216/PHH1fnse0x5HvO7Dz30kN+8ffr00fr16+f9+5tvvlHzPfXUU95p3Idhw4ap6dw3QRAEQTjaqGvftKbf5dGjR2vt2rXz/v3111+r7yxevLjW9WVnZ1frhxiwv1hTn5G/9exH1aU/OnLkSK1Hjx5aeXm5X39r8ODBWocOHbzTevXqpY0bN67W7RQEQRCaPhJqLQh7wRgZNqCrjsyYMcNv+vDhw1UoS13hqK0BXYcMLaFWd9VVV3mnc/SZIbWbN2/2m9dut6v/c+Q6NzdXOQT5fY78BkJ3oREqY3DiiSeiefPmyuFmsGrVKvz7778q/HtfMBzHgCPsDGlm2HFN6+e66GYz4Eg5Q4OMfaIDbtasWWp0m25MA7rc6IzbF4ajkcsIDF824Og924oOgT179nhfdDMybMcIU6fzccuWLbjtttu8DkgDhgmR3bt3Y/ny5SqUiKP1vvvFUffA84LQtecL2yonJ0eN2BPjO7fccovffNyOvbU9Q4+4nPbt26vtran96Yr1dbWSSy+9VDlEfcPj6YDleVSX47+3baKrkm1L1ybPZ7ZpXdrD9xxne9ChYTggCffBuPYEQRAE4WhmX31T399l9tH4u8x+Kn9rjTQ0Rj+HER3sTxxsAvuj7L8yuoN9M0bvGH0z9mvY/2MaHUawGNtKdySnCYIgCIcnIjwKwl6gMOULRTSz2Vwtpx5DaeuDr8hmCGjMW8Mw7cDpFPd8ee+995TQZeS5YUeO4dqBOQ1r2y5uP8OkmXvREOsoQnJ5DJneF+ykDhw4UM1P8c0Ix6lp/YH7SZg70dgnhjwzVDmwnQlF133B/bv99ttV+DLbjp3VV155xW9b2FGlCMZ1cFt9XwyjZrgR2bRpk3pnPsraYI7F2raNYik7zYFFXALbgPtPjDbgMnlMfAXa2tbBtmLYNMOlGarEfeZ+MKy8rse/c+fOKnzfV3jm/3lMKWLWF4bNG0KskbeRDzgkcJt4zgQK4b7ng9EeDHXnsup7PgiCIAjC0d43/fvvv9XAr5GHmr+799xzj9/vMn+nKQYydyL7EkxxwnBoDkweDAL7I8x/zb4Z0+AE9s2YbocY/bOHHnpI9XM6duyIHj164K677lKD5YIgCMLhg+R4FIR6YDjfAvEdXa4LgS602qYRPWpZh3kAKfLQIciOF3MFGgVhDOGsLttF19vTTz+txEfmi2RhEeY2NByEeyskwpxBzI346quvKoHIZrOpziqXsT/7dKAwRyDb5Ntvv8XPP/+snING3iPmQaTbkcftp59+qnF7AgWuhqYh24CuBrY13ZDMxcjjxX1jzkfuZ32OP3NWMg8jHzLYVv/73//qvT10rNLpSefCxIkTlajJBx26FHhMAreptrYQBEEQBOHA+6bsC44cOVL9HjOXNwcqGSlDN+Tzzz/v/V3mdxj5wN9/5oBk5AgLy7BPxWn76hvx+zX1YwKLxdXWHzG2g7nMa4twMQZD2efkfhn9PA42c19ef/11vwgiQRAEoekiwqMg7AW65XxHaTlCy87SvorHHCzYSWRRE4YP+3Y0jdHhukJXX58+fZTTjeIcXWssCLIvmOybrjV2UOm4M6AYtj9wZJud0ZrCZ9avX1/n5XAEnK97771XFV9hsnJ2SFm0h04Ado55HDlaXhuG45Bh53QK1ETr1q1r3TZWZqRrgMJbfeAyeU6xU+3r6qtpHTz+LLLiW+2cydrrW/GZQiWdoiwoRBclxWMWPKovLAzECu104VLMNDiQSpNsj19//RXFxcV+Dz71OR8EQRAE4Wjsm1JE5IAiK0P7RlwYaWUCYbQDXyzCxwFkRsSwaCAFvdoG241oBd80KYGRIfuCfVnC/kdtfS5fGFVxxRVXqBf7BxQjWXRGhEdBEITDAwm1FoS9wLBdXwxxjlWNGwPDMeY7yrxw4ULMnz+/3su65JJL1MjxCy+8oEK267JPXD87or4j2gztoXNyf+DyONLN71P8NGAINMXNfcE8icxN6AsFSIYcGeFCrMTI9TCcKHB0nn8znxDp27ev6sizPQKFPON7dHiycjiFNt95KFayLceOHVvvNjDanVUpfeF2BML9CNwHnpO1OQxqgwIp10sHLcXnMWPGVAvz39/zkf9n5fP9hW3IY8rwfQPuX12EcUEQBEE4mvumNf0uM7w6cICYKU4C+xPs3xCj/xQaGqreaxrc5GAtB1yZMsdgxYoVKsy7LjBi5/jjj8cbb7yh8mcH4rtco59mwEFJuiEPVli4IAiC0PCI41EQ9gKLjTC0mMIMxT0KNRdeeCF69erVKO3GcGi6Hc844wyMGzdObR+dfSxswxHg+sD9uPvuu/H111+rQh4cdd4XXCdDd9ge/D7z77ADzA7g/ubboSA4c+ZMVWTkhhtuUKITO9HdunXb5zKZmPymm25SuSnpZuR3P/jgA9XxZu4io3NM5+PkyZOVSMow9YiICNV23PdrrrlGhfpQrKTYdcopp6jON0fVKTSyY82k5oYQyhB1du4Z6sxiQHQMcnsZ9szR9/rCdTHcnaHrfDhgYRY6/uhgqOn4c/+4Lh5znpOzZ89WwnF9oUPx7LPPVv9/+OGHsT8wlIvty/ZjeDULB9EVG5iXtD6w/elYnTRpkjpe3E+e8zXlsBQEQRCEo4299U0ZlcLQav6WXnvttapv+Oabbyqhz1fg4wAq+x3sT/J3nAVeOB9/x41BVEak8DeYBejYx6LrkBEzfDEsm/1BDh6zL8T+IPuj7LsZxfP2BfuPQ4cOVQPGLIZHF2RmZqbaJ6aCoZBJuA0UKfv166e2YcmSJSoChP0/QRAE4TChsctqC0JTZMqUKRwG1tasWaOdffbZWkREhBYTE6PddNNNWllZmd+8nO/GG2+scTn8jMsKXG52drbffJdddpkWFhZW7fvDhw/XunXr5v3b4/Fojz32mNa6dWstKChI69Onj/bDDz+o73OawZYtW9R6nn766b3u59ixY9V88+bN0+rK22+/rXXo0EGtv3Pnztq0adO8+1WXduF2cnt9+fPPP7V+/fppdrtda9eunfb666/XuMxANm/erF155ZVaamqqFhwcrMXGxmonnHCCNnv27Grzfvnll9rQoUNVO/PFbef2rV+/3m++v/76SzvppJPUMed8PXv21F5++WW/ebj8IUOGaCEhIVpkZKR2yimnqHPFl9qONduL03mMDHhO3XLLLVpcXJxaJ5eXnp5e7fzJy8vTrrjiCi0+Pl4LDw/XRo8era1bt65amxrrWLx4ca1tV1FRoc7pqKioaud0bfz+++9quXw34H6feOKJanu4XRMmTNBWrFih5uN27Oscr+k45+TkaJdccolqW24f/79s2bJqyxQEQRCEo4W69k2/++471Xdhv6hNmzbak08+qb3zzjt+fY+lS5dqF1xwgdaqVSvVn0tMTNTGjx+vLVmyxG+d7B8a/bPAPsmHH36o+mz8rHfv3tqsWbPq3R/dtGmTdumll2rJycmazWbTUlJS1HZ88cUX3nkeeeQR7dhjj9Wio6NVv4v9t0cffVRzOBwN2r6CIAjCwcPEfxpb/BSEpgada3TiMdRjf0JQDxc40s08fTW564QjG7pDmzdvrlwRb7/9dmNvjiAIgiAIe+Fo6ZsKgiAIRx6S41EQjlIYcvPjjz+qXI/C0QfzavLhxbcojCAIgiAIgiAIgiA0JJLjURCOwtxATP791ltvqbyOzAEkHD2wGBFzZzKvIyubDx8+vLE3SRAEQRAEQRAEQThCqbfjkcmHb7vtNrRu3VolHWYhhMWLF3s/Z+T2/fffr4oy8PMTTzwRGzdu9FsGkwazoEKbNm2qhfixYi4TI2/bts1vOgtCXH755fXfQ0EQ/Pjzzz+Vy5ECJJOLJycnSwsdRbCADosJMdH8+++/39ibIwhHNdKnEgRBEARBEI506p3j8bzzzsOqVavUwyvzg7GS2vPPP481a9YgJSUFTz75JB5//HElaLRt2xb33XefyiHHzykoGtXJ6LahOMkwv99//x0tW7b0Ex7PPfdctQxf4TE6OhrvvvtuQ7eBIAiCIAjCIUf6VIIgCIIgCMKRTr0cj2VlZfjyyy/x1FNP4bjjjkP79u1VomO+U4ikhvnCCy/g3nvvxWmnnYaePXsqR82uXbtUPjGDkpIS9O3bF7169UJMTIwa8fflpptuUoImBU5BEARBEIQjDelTCYIgCIIgCEcD5vpWQXW73V7nogFDqv/66y8VupmRkaHCqw2ioqIwYMAAFV5twFDsLl26qM8GDhyoHJC+DBkyBOPHj8ekSZP2f88EQRAEQRCaKNKnEgRBEARBEI4G6lVcJiIiAoMGDVJh0hQOk5KS8MknnyhRka5Hio6E033h38Zn5KqrrsL5558Ph8OhHI81wXBtOibnzp2LYcOG7XW7PB6PclVy+xiqLQiCIAiCsC8YqcGoC6aOMZvrnfb6gGiqfSoi/SpBEARBEA6XPpVwBFa1/uCDD3DllVeqfI4Wi0WFTF9wwQX4559/6rWcsLAw9aoNuiCZ/5GuR1bg3RsUHY0ckYIgCIIgCPUhPT0dLVq0OOSN1hT7VET6VYIgCIIgHE59qiOJOXPm4Omnn1b9wd27d+Prr79WNU98Rd4pU6bgzTffRH5+vooYZurDDh06eOfJzc3FzTffjO+//14JwWeddRZefPFFhIeHHx7CY2pqqqqKyzyNhYWFqkAMk6O3a9fOWx03MzNTTTfg36xiXV8efPBBdOzY0S8/ZG2uAZKevgSRkY3TkELTweVyY8eOTLRp07yxN0VoApSVVSA3twApKYmNvSlCE6CwsATl5RVITIxt7E0RmgDbtu1Ez54jvf2IQ01T7FMR6VcJvmzatAOpqfIQKRjnw06kpqZIcwhyfxD8KCwsRsuW/RutT3UkUVJSouqhcHD6zDPPrPY5a6689NJLfgWdR48e7VfQ+aKLLlKi5S+//AKn04krrrgC11xzDT7++OPDQ3gMHF3Py8vDrFmz1M5zp9lR/vXXX72dYnakFy5ciOuvv77e66CLkYVm7rnnHtU5rw0jvJqiY2SknOhHOxQeIyJK5FwQFDabHU6nW84HoRITbDabnA+CIiJCH6xs7DQtTalPRaRfJfgSEREm90xBzgehRuT+INTWh2hqlJeXq7Q0jYGmadXaJSgoSL1q4uSTT1av2pblW9CZsKAzU/FwcJnpd9auXYuZM2di8eLF6N+/v5rn5ZdfxtixY/HMM8+ocPgmLzyyQ8yd7dSpE9LS0nDXXXehc+fOSkFlY95222145JFHlM3TUF+5Y77W0PowefJkZSFl4Rq6AARBEARBEI4EpE8lCIIgCIJw8EXHkKhwwOFulKYODw9HcXGx3zSGSj/wwAP1Xta+CjpTeOR7dHS0V3QknJ8h1xzAPuOMM9DkhceCggIlBu7YsQOxsbEqVvzRRx9VDhJy9913K2sobZyMNx86dKhSWwMrYdcVrmPixIlqhF4QBEEQjtSRWOHoQ/pUwuGB3DMFQZD7g3D4opyOFB2HtQesh7jwjcuD4rlpKvdlZGSkd3Jtbsd9UZfig3xPTPRPM2a1WpW25lugsEkLj+eee6567e2B7qGHHlKv/YFuykAodPIlCIIgCIJwpCB9KkEQBEEQhEMERUerpVGaOzIy0k94PNqQOueCIAiCIAiCIAiCIAjCkW3gb4xXA+JbfNAX/m18xvesrCy/z10ul6p0bcxzqBHhURCqQdetBg0On5er8uX2exnzHt77WaFeHq1EvdxagXq5tGz1cnp2w+nZoV5urVC9PFp55as04FXi8yr2exltKQiCIAiCIAiCIAhC/fAtPmhgFB8cNGiQ+pvvTHv4zz//eOf57bff4PF4VC7Iw6qqtSAIgiAcjtSU0kMQBEGo9a4pTSMIgtwfhMMf5nk/1Lne92N9xcXFqpCzb0GZ5cuXqxyNrVq12mdB5y5dumDMmDGYMGECXn/9dTidTtx0002q8ExjVLQmIjwKRxT+jkRXDXOYqnWknZ5d6p0uPeJ2e5CfX4K83FLk5RahtNQJi9kOq80Cq8UOm9UCi9UEi9UCzVSoppdpDlitZpR5HJWfmxFst8NqtSAyLFQtN8isF2CyWfTLzma2wGLSP7OYYtS72RRVuZW1557QnZaAW8vV3z056r3IWaTecyuKkFlcjF3bcrF6VTrys4thjQpCVEIY3BE2hMeHQbOa0CI8DAu+WYkVP2+A2WKG3awboCvKXcjYlVfvtj/vymE4b8IwuCpFHadH306Xx6PeHZXvyaFh6r1j1AmSsF4QBEEQjvCBnpKSUuTk5CMnJw8FBUVqGpPc22wWWCwW9X/9ZfF5rz6d8wYH29X7oSYrKwcrV67DunWbEBkZjubNk9SrWbNEREVFqBz369alYdKkJ+FwOL3fY59y69b0eq8vOTkBX375OuLjYxt4TwRBEISmzpIlS3DCCXxW1rn99tvV+2WXXYZ33323TgWdP/roIyU2jhw5UlWzZlHol156CY2FCI/CEcPOknkocZWrTl5OSTm0ws0wm3QxzWIyozC/FNs3ZyMvpxitkhMRFh2EmLgIvP6/Gdi6KRP5eSXweDSYzCZERoUgKiYM0bFhCA0NQpDJDrfLDc0TApfTDbfbApfLDZfLAZfbDafTofImuF1OzJu30m+7EptHISImVAl6HrcHwaF2tGyfgFYdEpHavTmat4mDp1IEdbjdXnnU6XBDK3MhOMQOS4gVxazGxRGQCgdWz92McG5jYjhiE8JhD7YhtLKy/L+/peGtx37aZ3t16NACbdo2w6wf3kJQkB1paZk4ZfzV9W53i8Ws2vyzd+Zi9Yrt8FigxFib3aq/2yw4/oxeaJGaoObfXVKs3iNsC5AY0qlO62BAuNUUV+9tExoS/RzV4Kk2rQpPwHQLTPIzIwiCcMRRUeHAli3bsXXrToSEBCMhIVaJZIsXr8A33/ysRMby8go1b1hYCOLiYhAbG42oqEhl/mAfyq36Ty69/+Rmn8oFp+pj6f/na+HCFcqp4Uu/fj1QVlauqpSazRa0b98aXbp0QNeu7TFoUN8ahUmup6iI/Tx3NTFvyZKVyMvLrxQSkxATw23UB6qLi0vRr9+4fbZHx45tVV/oxRenoEOHtmpap05VD431JSMjG2eddZ3aN7vdDrvdpvpq/H+fPt1w1lkn7/eyBUEQhKbN8ccfv9cIrboUdKY78uOPP0ZTQYRH4YiBote/K7dgT2YR8rMr4IEDe7IKUVpSgS0bM6tdrMeN6IacPUVYtWKbd/pp5w3ADXfrHUyPposoVpMF8cG6EzHI0sLPoWjkLPRoZep9yZLliEsMUZ3PDr2bIzY+HO4gExwVLhQWlKIwtxTbN2VjxbxNmDdrDdp2TkZcciTmz1qjvh8ZG4qQ8CAlPNqCrAgLD0Z5qQMnnNUHa5dvR3h0KEJjg/HnZ8tQkF2CFh0ToHk0OCvcsAdbEZsYgbiECPQ4tg1WLtrqt88XTjgO5YVOrF21A5dfeSJOOH4wQkKCYDXb1eft2rXEjJ+mqQ53aGgINm/ejosvul05FfYG99Vg1T9VbWlwzYPjEJMQodrAZrd47eYUcBesWImFC1bCbDapdYaGBntfXbq2RYsWSXU8+oIgCIIgNBTZ2bn4/fd5yMzcg127slFWVoqiomJkZeWisLBICWO+jB8/AtnZediwYTPy8gq809et+80r4tWX3NwCfPbZ95g/fymGDTsGqamtlbuQFBYWIzc3Hzt27MZffy3GzJl/ICUlGWeeeTJefPEdNQ/7EklJCcrpwUHSiIhwtd233HIF1q7dqKbz8+XLV+Onn/5AUlI8WrZsrraf/ZLExHjlaDzzzDH46quZfts2cGAfdOvWEbt2ZSpR84UXpkDTPEoYNPjtt08QHBykhFmKoddcMwkLFiyr8/5zWwPb+fbbr0bv3t2U6Mpl+oqsW7ak4/ff56vtp9ir96v0F/elf/8e+3UcBEEQjhgOQrGXOq1TEOFRaNqUuVfCVO1qNaG4uAwLF2zA33PXILewCL36tcGrz/0ER7lTdXBjYmJU1aba6N63Fdp1SULFSifOu3wYrrzpRFSUuFRH01Zqw6IF6/HetDlYu2bzXjvOmqaPwru1PHzy0a947JEPqz78vvp6h5/cA45yB045bwC+/2Qhhh/fTa1TK3NjwZz1Spjka/ipPXHx7SfC6XZj5keLkLk1F+PH9kVRYRmKc8oxalRv5GeXoFeftrj88rPVsktLK5CRkYPdu/dg964c9O26E7f950I1Sg6TPsZgqqwnZUIIzKYqKzYxW4DUdm2q9s1jQrduHTBwYF/Ex8fAZrPBajXBZrPCbCnT360eXHv1097vjDvlGMQ1j0DuniLM/mkFxp3dHztWZuKndxcq9yNdnAZ0f3br3Qp9B6YCZg2lJXnYtGkPZn29FEHBNky4czQGh3fR59U0dI89CYePK9BZQw0vk98xMERrE4LqvXzf5dXtW3q7e7TCyvfyyun6OwsDGU5GM/SHJlPlOaNprlrXbTLZ/f72pjeo/I7+t/5QFGTpUDlnw4x31ZxKoYb5NL14krGdbq0Ubs0Bt8bj4H8sCiq2wcoLAYC9MiVCVXuEqHebOWk/jpsgCELThQ7DVavWY86cRVi9eiO6d++IzMxsfP75j+rzuLg45OToaV0M2Aeg4GbAvsLy5WtUn+allx5UghuFSoYdr169AR9//C2+/362V5CjSLg31q/fjFNPvcr798KF1QW7kSOHqDs4XY5xcbqbkoLbRRedrlyXHDilGOfbj+M2fvDBVxgzZrjah927s9G6dQpOP32Ucje+9NIDSsyjIzM7O0cJi3xFR0fhlFNGomtX/besLvjuI92fDNG+5JIzkJraRq2b4eN2RoeosHP2sSy4885HkZ+v/1b37NkZ/fv3QnR0BN5553P07dtdRebcf/+zKCio/D336L/NdIe2aNEMJ5wwCL16dUFpaZkSZt99d7pqg9NPH41+/brvtwgsCIIgCAeCSTsCsuyzik9UVBQKCtYhMlIfCRWODBZlVYUMm03AysVbsXntbnw+da53+pgHRiJr/R5krMlCcVYxYlpGo3xnBTJ3+peQPxBefOkejBo1GOVuXYjMKs+vzFtUrkbRH580HQv/2uD3nbCwYMTFR8Ll0pQrsWevTio0aM6f/+Caa89EWVkZ7p58fuXclaKPKQIlxWVwO4MQExsFU6XoUZOoZQhCJpMx2q2/H4rQVodnk3rfXLhVdc6dldvG/uzSv9PwzOSvEJ8UiT4DU9F7UDslOj5y66d7XWa71CRER4fjjLMGYczYY5RgWiU6mxBkqVtYdiBlZRUqt1Rd3ZOGCKVpjgCRzVpNcC5x6Ul/cyr0/Jp2sz7Ptg1Z2LE1B127tURq21Q17fuffsfwkd3x77Z05O0pRnBCCELDgxBksSAuRM/12SpcD0cPsXSsXGelMFbpvq0KZSaVIrJXVLb6CXL69hu3d/3dA92Z6/bkq/cKj57X1OVxq3QExHi3Vu5LvkPft21FupBf4nR6rf/cdhJfuf0xQeH6dyvPSQtdJpXLC7JEV7ZRlbh9YOz9p8sQUllR3TcEvLCwFOXlDiQmRnvzuq7O0x3HOWVlcFfuG8P79e/r7/0TW6r3uKDu6t1kqi487i03q9A02bp1B9q2HYCCggJERkY29uY0GaRfdXRAcXH27L/w0ENVOZ+ef/5+5aZbuHA5VqxYq0KoExIS8P33PzfYehl2PW/eV9WmUyyjC/GLL2bglVfeV8KZLy1aJCtRsLS0XImFXbq0VyLikCH91WeXXnoW2rf3/43h79XOnZnq88MB9qnYrzQEQubEPPfcG5QDdciQfjjuuAHKbXnGGdeo0PHaiImJUg7OYcOOxcUXn6FyRjYUaWnpaN9e/008FLDv/O23P6NTp1R07pyqHKTLlq1W+0exOT19F8LDw5CSkiTCaiNwqM8HoelCN3xUVOcm2acy+jU4sTMLLhzalTvdwOx1TbJdDiUSai0cVjzxn8/9/h46phviU+OQ0CEeXcZ1hsmtIWdzHvLW5MOyzozijCI4yl0Ye/UgzH5/EQpz9LDhxLaxKC0oR3FuVRgxw5ofeOwCtE3ph9jYKPXiiL2v0MSR+ysufhGJLfiZDTO/Xeq3PZdcfQK6dmuFNu0SccFpTythMjIqDFGR4Vi8aBW6dU/FmnVfqnk9yonln7dI344QWEyHj4DOEXqnq8r10LJdAp798Gq0aBWnOoAUcvJzS1QYeG6WLmL5ktq1GU4e3Q+XXzUStsoCPFUuwcaHx3zXrixkZeVj3rxl+OXnvzFy5AAMHtIbiS2c2LI5EzNmLcGoU/rgtsvfrHEZPAfi4sPxxkszEREXiui4MCxbsBllxboTb/rcSSonptA45GYXIXNnPrZsz0b27gLkZhQhJ7MQmel5KMwpQWrP5ogLC0Onri1w3VUt1b1BEAThcOfMM6/Fnj3+xeToimP4MR1yZMeODPz8818wmzWsXLke5eXlKtSX4iFFPxIdHYl27Vph6dJVfsu6445r1PKY25EvOv4CHXf/+997+O23eRg9+jg899xbfp8xooNCYo8endV8v/yiDzq3adMC27btUClhZs/+GC1bNqt1H7m+w0V0NPpUvrAf+sQTk1RYt4pgUS5HD6644ly89NK0at/v1KkdWrVKwRNPTFRiXFOE4fsUvVmoZ+bMP5WzlIJ3fn6RcmveeusDOP/8U1Voem3+GJ5vdNwy9J7HPz19t3Ltkk8//Z/Kgyk0DnQOb9++U6VB2LkzQ91D+E7nMJ3MHCigG5lCMlM0HHtsbzlUgnAUII5H4YAwQjahQjn9i0/U7v7RkO9YjztufAuZ+YVISY1HRFyYym/IIiyRcWEIiw1RuQ77JFaVe2fnY/3qncjclYfHJk+v/aQ2mdD57sEoj9FwQlxzbF26Ext+34Si3FIUZOmFTQzOuHIwVv21HRs37FB/f/LpU+jduwc+/2wGpkx5ea/7fvaEYfCYNBVWlHpsK0TGhaJoWyFcRU6Vv9Dj9MBR4UTWrgIsmZ+G888/HmeePQRRYe0rtzPYG3Z7uCZ/MNx1xU79YaPUVeF1uJm9Dxf6+6bM3fj6g/n48+dVKt/j6DP74uQz+yEqNgypUfpDQYil4fMPMbwpN7cQzZvvfbTfXRmGXOLSXa0Oty4Kf/bhXLz09Pfo2qMl1qysqkzZf2B75OQUqeJDxcXlqqp5SUkFysscqkq4r8ialByNvse0R1RUKHbuyMG2LVlo1ToBPXq2RseObTBmlJ5X1GQyhNe9hWnXP8R6X+cZj6MRhm04/QwHZXUHreYNOz4cHH5GGxh/FRXR8ViBhIQYONxpKm3DlZc/h7QNu5XThIMGw07ohpad4hEbH4EFizaiRfsEOFxu/PTBIoy7YiDa9WiOed+vwqq/NmP0+f2Rv7sQg0Z0Qevm8WotIVbdqRwTpA8gBFu6HbbX+JEOC2O0bXvsUT8KHYg4Hg8//vhjPm6//RGMG3eCyuenOxXj1P8TE2MRFxdbTdSiAPTvv2tVDsWPPvqm1mU//fS9OPXUkeoeuX79Jjz66P+UcEDhyJexY09QfbAff/xN/X3CCYPx+uuPYtOmbbjrrkdVGPfeirMwl2JJSZkSK/v374lt23YqcZGFbDgISOcbXz/88KsKQ7766guU8/Fo5ZtvZmH69BlYsWINTjppGK644hz07KmnqDmYbN68A+3a6TnP6wtFqFNOuQJhYWFKcPQVEtu2bakcnqwefvzxg7Bs2SpVoZUh+3S67tlTlUKJ51bz5onqfFi1aoOqdk5BXA+bH43wcD0SQ8AhPx+efPJ1fPnlDHUsKQwz/J/pEJg/lWH/dKwydyoHHOiQe+ihO9S9ZMKESXjqqclKnOzevZOkBjgMEcdjLYjjUSHCo1AvjFxpRoii06MXbSlyFqlwTeLyhoXqNAupng/HjULMnLEYd98x1TstuRXzCFpVARJ2XC1WCyY+eAaatfCvPsjwW+YQXLp1B569/jO/zzoe1xYxLaKxY14Gjr20O/5+/x84K1woyimByye/YCBxLaJx22vnqHW2CI/AtKdn4ffv/q1x3ideuwwJXeKwa2sOfl+4AZkb92DnxmwVTh3aMhLtWsap5XRJTFAhxm2SW2HkyL6w2/WRZyO3IsOqq4Qb0xEjRJe69BFnp6a3t9vjxpqV2/Hh+39g5/YcnHX+YIw8uReCg+zeUGpbZT69GHvfRhAea8rLWDXd4UnHgvlr8dRTn6BH39YYfEIX/DbjX2xJy8S6lbpgTXoOboexdw9H3u5CLPpuNVb/uQmOUieikyJw+SNjEeI0o7iwDF3bNkOLNvGIDNI7xdH2cAQZodWwHVHnQ1OEoWkMtabw6BuuzYdaPuCuXrsc69ZuRX5BNlwuj6pab7xD03DuVcPw9ks/wxRiwdol25DcOhYWmwWbV+1G/+M74PKJo9EpPlEtMymknXo3m8JgNunH+0i75g93RHisGREeDz9YRfq00yb4iTkdOrRBUFCQ6lvl5RXi1luvUOJgIHSObdy4BTffPEW5lAzoZDz//FOwbt0W9O7dBTk5ufj557mqqJwhAtGFx/tnIN9++yY6d9YHWhctWo5LLvlPjdsdERGGJUt+UNvP/IsUQhnizdyLFKI4OEfxiftgVHamkEFX5tEK2+qTT75TAu+IEYNVTktW5D5UHIjwSOh2fPbZN5UD7qabLse//65T1dDnzFnoN9+ff36uIgw+/PAbFX5PAZth6M8+ex/atm2hzmmeF3SDUswSGoeazgeaRVgYae3aNPXifYVOXQ5e6FXs9f+ffvpJ2LhxqypkxYr2TC3EXKXM6dq6dQs8/PCd6NFj/1ItCYeew0J4PKmRQq1/kVBrER6FRhMeydfz52DKlR9g4EldkNwyBvl7SpC9K1/lwKOwRx5+6SL0G6R3XokhVq3J0yv9LV+xDd8+9QcKs4uR1CFer/Kc64HT4kCXQW2w+PvVar7k9vGwh9lQkFGEsA6xsJV7sG2JLhyd98BoNGsWjaiEcKQmxKKspAIfPf0rCvNLsfyfLd51Hz+6B+566Az8s3orXrznG+RkFCKqWQRaDmuNhE4J8MQHoU98vHL0HRubjPIyJ7q17ozomHBvMYqjTXic8f1iPHSPnt8xNCwIcfERePrVK9A8Je6wER5JekE6Znz9D777bCHSt+6ptpRWnRJx3OX98dMr83DM6d0Q2zwKUckRaJ4YpVyxCZV5EFPCdRdcuE13DYrweOiFR+b9pAOopjyRLk0/tuWuXerdXXk/43tWZgFOO+lh9XdKu3iER+vObBZKolu7bcdkDB3XHR1idOejCI9NHxEea0aEx8MTPuyPGnWxyndOcY6uRIagGmGOLFrCHHnffusf0uwLHWT/+c9DqjoyhT8Kgzt2ZKmCfXSSURDYvTsLYWGhGDy4n1ouczOOHz8SL7/8rlrGQw/drsQgupoYYs3B5Lfe+lS5Mhcv9h/UZa5HznP11RPVsllkhUVcRo4cqnI40rnGbWJeR75TfGSo9dEK26B375O9f7ONJ0w4HxdddMZhIzwa0Kk5bdp0VVG8JmbMeA8PPfSCCrVnOC5DqpnH0bdyuND4bNq0A6mp+3c+dOqkD4TQqcr0DbwXsM/MY5ya2gqnnTZqn4WohKaDCI+1IMKjQoRHoVrYrMOth864tAo4PS7k5RZj+pd/4e/f1yKvoERV0KOwRjefxWrGKTcMRUq3JLSJ1POe2bxVYfXwztSIJNUZDrHpD+O+lLh08ZDrCYSjYWu37kBMXLiqcsy//128BUUOh1pvdkUZrEFWtOqQoDq1NrMZ5W43NOZ5zChHaJINu1Zm4MP79AI1QSE2WOOCUbKjKgQ2t30IHCFmJK+snqC776BU3PLf8Qi2ByHOGo+kZDqkdDHN6dFDzLPy8nHPf97HsiV6eG5NjD2lPx58/CKEWXX3U1X+xiNDbAyk2LlCvc/ZpRde2ZGWjfVL0/HDW/P85rtj0hk4/+Lj/KaFW3WB2WzSi5QcylDr2mDFZ6MCtFsrUOdyz65VlTbJqdcOQURsKH77dCkuuX8MenVIQYvwmMpgaf06cHh0YdNemccyKkh38trNbQ+LkOW6YRRkKfMWs9Eq289Iy5CXn6vCzTt0aaau2yCLfj3YzakHZVv8rzUtQHj0x+nJgLmyaIwJhntCP37r8v9S70szM7Bp6Q6s/CMNOzftQWhkMDJyCuHK1PeZHHNmD7Tpk4IRQzqpfewVl4JwW4y3orxvWL0ZhhM6pIndF+qWOkMPZQ8UcI3UAE3/vBbhsWZEeDx40OVDAY4OLrqA+DdDnikI0kU4atRxuOuua/dZhZqhp/WBv10UHlk4xnALrluXhszMHL/Kygx5ZS7GmoQFhkGfeOKF3qIvDIdes2ajEh4Jw31vv/1qnHXWtUooDGT69FeVM4/9OQqXgeGwdE6yiMi99z6z131Zv/53HK2wT8MK4c8996ZfVXGKwO+88/QhKa7SUMKjwSOPvOzNF0ratGmJBx64Dc88M1UVDDrttJMabF1HGryet2zZgcTEOFVQ6HATHvX7X7YSoOl4ZloFDnjMmvWnd55WrZpjypTb0Lt31yabt1Q4jITH0V0ax/E4a22TbJdDiVQzEHxyoOkPmDZziuqgfv3H53j95Z9RlF2CDqPaI+nktsj7eSMKt+QjZUALZK3MgDXUis9en4OongkYeWJ3RDePRJ9EPcwwt7gUv3z6D5b8vl452257/AzEJ+sXm8Ojr2tnsZ5zcVOB7oDcvjgdmauz4Cx3ITgmWImFWeuy0fHEDkjpmYTf3/wLGasyEdsiSoVOF2YVw2q3oMPQtkhbsA3OUicsrcIRaQlF3paAqtYhVnQdlqry722evw3Zm3IQm6Z3lgeP6IK+/VOxKz0XWzZlYMvGTGxel4GUmAS0iOvndSka2My6UNk8bjv69+uowm7z8/3Fy9atk5TAMfHOWxBmicWunXnYsGELcnMKEBMTrUb24uNjVCfceIDQK/DqoZlNS4SoO+G2Xup9YLILH77zO1554Uf1N9udzrD4lCiEhAWhML8cIZa4ym81XYHCCJEFQpUIyT79stUvISszHzNn/YMFf6/Hvz9vRGRUKL78+BXd3YEgr9CmVVaSrgq1rV4N+XBwOWuVDlYOUBQ49AruGwv0ayy7oFgJzAWFpWpgwgqzCqmxaCaUF1Uo9/Lu7bnKyWyzWJCxKw9f/XYPgkPsCLXoD05xwfu3XdUxclNWnVPGdZVbsRYlFQ64nBrsjlDYKit3L8naqh6EN+TmIT44WOW5DA6yqQe4x2bPhXN7MQo/3Qxzl0hYQ21wbSqC6YQErC10AmYXgu1OxIWa4Laa4DEDi79aqV7vh8xSmpyZL5suYIZGBCGkcwxOO6Uf4lvH4LgUvbPePqqtereZWx90J7TRHk6P7vjOdxR4c7Tm5RQjOjYMjsrBoKKicoSFByHMpp+3KaEd/RzCHpTDYtIfdiymmADR0sgx2nSvb0E4VBgP159//iNOPfVEXH75OZg//x98++0vOO64Y5UoSEGQD98TJz6OM888WRXIMAqKkLlzF+Hdd6erfGiTJ9+oXIZ7X+cevPjiO+r/rP5L9yLdjyEhQbjnnpuwYMEyFfJqfEYhlOLfqFHD1P1v1qw56runnDKqxqrWdDUyL+OMGb8poZHFX/jq2rUDTj75eCUiMISbOdu2b9+lqkvvLQch95XFUViBOSsrR/2O+IZ9M9ffY49NVH8XFhZjw4bNKmdcWFgIYmP1PlWzZknq7yMRCtNDhpyl/s+QY74iIsKVC9DpdCpR8nAMOb733puV2P7nnwuU05bXwH//+7Ryzg4degyONnjeM6ycbmL2Tfg3Bxv4fx7jrVvTkZa2TRVY4jTeO9h+Z51V5YRtbLi97A8ydJr1gficwxyzFBrpmL7kktsqUym0VaH2vOfcdNNl6jrnQIYxL8XUTz/9Dldddbdabr9+PdQAssfDsGx9PbxPjh49XFV9b2pu2OLiEjWoYxQr5eAN73NMESAIRxvieBR8hMdKYUFzoEvnU7wtE9MyChpt76E2tBvfEVGto7DgmXko2KqPeBNLqBUpHRJRnFOC7r1bofsxbRCdEolPn/8NLrcHfUZ0wOIZazHwxM7YuWUPtm7IQtuuyTjxxiHq+2n5BVj5xSqs/m6t3xHpPLYjUvqmYOkHy9Dvwl5o1j0ZRetzsfHvrbAGW5WosX7OZjTvloSwlAhs/DlNdZajo6ORl5cH+9BExkiqEEhLsA1R5SZVzTopNQ7Fu4pQUeKAaU8FiovKUVRQhuRmMWjbIREt2yRgwDGd0KZdEqJsXasJj0aoucOzXW85zakqWN9241Rs3LBbiVA7tushmxwV5o9j85Qk9QObmBCPvLwC5OTkIzs7V3X0WeGNnfRevVvDbDYf1sKjQW7FP3A4XLjkouewfX2VCBybHIm7pp6Pse17w+J1NurChMUU2eQcj74YQo3To1cBLXfr4pfZY1GhIRFB+gPVkSw8uj0O/Lv+b6z6dxvm/7Mem9dmwOXxoGWHRASF21VhpaI9JcjLKkJeVrFKW2APssIeZENYRDAiI0PQd0AqrrxBdzCEWvT2iAvuv1/bVV/hMS+3FHt2F6HcUa4KAG3elIG33qh6oG6eGo9dm/RrN6FFNHJdFTCH2+BM0wdHQs5sDXOEDRXBGtYsydC/VFQZpm82qTyQIWUa3FbAY9GFSI/NjIi2+rndv3cr7PlkIyrSdLHv3ufOQ7/B7RtVeNyauQs/fLUIv/3yr7r/VJQ70X9oe3VfXL1sO3ZUphYYe2Z/9O7SHantW6Bb91YIDw+pRXg8fJyP4nisGXE8NixPP/2GCjUmFOX4QM0H5gsuOBXnnDNOiYnPP/+233coKq5evUGFILKPcMwxvZSoR7fbddddpHItdu3aXg1kfvnlTyov2n333YwOHfR7yV9/LVZVj5kv0ZfXX38M8+bx99mpXGXMw8b1UySkC5HrYFGXqVMfxzXXTFbfiY2NVaHW3F5WmSZ8kKYzkpWsu3btqKpdUyyhYFhQUKhERgqaDJdk9Vo6KYcNO6ZejjxWsv700++VwMZ+E7fRcMRFRoahY8d2Srzg7zxFOToxmauXVZ3Zp2IBkiOtyMhXX83E5MlP+k375ps3VVj6oaKhHY+B0PzA85P5PI8GeO7yOmV+U4quGRl71HVDpx+vF15TvE53785U/6doxdytHCyg0MyiLQ8++B/Ex1eP5DjYUBRdvnwd7HaL2kYOsDz00Evez3leMscjad++tXrn4AAHUQjFZW7/wIF9VP+jJmja4P2FIiQdj3wZwh3vpTNn/oE77nhE/U0B8+WXH0JjwvP3p59+x/ff/6qKKTGnJe/VvE9On/6jcirz2Y/3KN6v+WzIfLhMJXC4I47HWhDHo0KEx6MaIyyywk8gYfAfb4o2mxm5FXoFwow9+YiOCUOwxYbXXvgJH03zz8fisZthCjEDZR6YHFUj1KHNw1G6S3/IpSuRhVgsGtCxVwvlZrzgthHqM4vJhMdv+AS5mUWISQjH1vV67siB47oiqU0sdqbtwY4N2bjl1XPgrhwBt1e6BCl0vHb714g5phk2FefD2iwEIUVWZP+2CeZgK8whVoSXmeB2uGGxWxASFYzwmBA0DwpThWs6dWiB8IhgJRQ+/+S3aplL/30FIfbWXlHMCIusPdxQ7wxzZM8QcF3uMuUAiIyICXDOVXW66aBjR3rGb1/j11krsG7tDhXiffzo7ujULQXNQnVHYLClGSzm2FqqDDdd6HI49VT/sGQK2Be+egZO69wBXWKOP+hCRUMKj0fjgIRR7Xpn7mr8944PsGVrJhLbxKJ15yQkdYhD8/YJSC4Iwtefz8fmtAxV5bt5SjxSUuJUHs8W/H+LeDRPSVQuG5u5pVqeCQf2QGGI/4HsLtVD/SvcThTkleKv2Wvw3a/LUJJbivziMtVZD4kJhTPEA3eoGeZIO9IW7YTTbkJZqEkfZKnwKEc1RUMYVWCDKjvE1sr3Av2a3yvGpR4fjJAE3YETbDUjaEc5Ipfp7Xrb2+cjJjkSZ6eeqC/edPDPU0MUz3fo1eg/+PlvTHvgJwy4oDeadUpEYVEZ/py9CprTg83mCgRnOxC1qSqU3BZpx3U3jsb4s4/B9qJ8FDscfvlLO0W39EvfYa4smmS3dGhyIqQIjzUjwmPDwodjDk4ZD9Z0wdD1QncOhbsLLrjZb34+VFPYY24z38rRzHVHcU/PqThCFWWgq3HMmONVcY5PP/2fN0z63Xe/UDkXmzVLUPOR0NAQ3H33daioqMDLL7+HDz98oUbB6rXXPlSVhc8//1T1HRZ3+eGHX/DLL3/hmGN6Ktfknj15ypVE4ZNOQ87HB2yGX/NvurBefHGacm19/vkr6NWr6wE/zLPduJ69hZlzPgodM2b8rgpWUPA8+eQTcPzxA9V3D3eMnHgGPAZPPXUPxo3T+9NHgvB4tPDKK++r1AKMgOrVq4tyAzOcmE7Bzz//Xrk/CSvTc2ChRYtkdU/Q/98MMTGRhyS03oBmCYqfvLdQZOQ1ztUnJSUhLi5KOZWTk+OVw48iIe9XzEHKAQFWuKbAyPO1IeH1np6+CyeddLH6+5JLzlQO2sYOfz/vvJvUsbrppkvV8fznn5VYuHA5zjlnrLoPXXzxbd75KbAPHtwfr732yCE9nket8DimkUKtZ0qotQiPR7Gg4PboLpZi104l3r374a8oyC1BRm6hcimlZxegGC6EtI2CuVUobEmhmNC+K3Zuzlad4vJSJwpyi1VV1y+e+wMZO3QXmEFcYoRyDqZ2TEab1CSEhwapm6+TeRhNGgYP76xcUKR5mBFyq99w8/OL8dOPS/BPxg5YrCYEhdrRZXAb2INtWJrlX9iDoZuOEgfWfbsWeZvz4Cp1qhtLUVmRygHJirNhsaHwuDwwezR43BqSgkLw7z9b0aJVvLrJN28ei23bsrBlky54/jrnUcTH6y4euh0tptiD6lpzevRCFhkFmzFv7jrcf9dH6u+PvrkDrdsmIsIWAas5/pAJE/uPBqdnp/pfuXuPGgk9Ych/UVLkn+tpxPl9cdF1x2NIs7Hq74MpRojwWD8MEb3crRcJ2lG8Bzu27VFpF9b/sx0Is+Ge58/Fj+8vQIjNhk3rdqNrp1Y4+7zBGHLsOHU91UVUdGv6/ULTnN77ktVcc+h9TecHHbXqs8pOmi76Aw8s0EMDizKKMO9+fYBkW1sbHEEmaOVuhFrtCLLYkOcopQKHg0KC7pBu1TGayXJhzXPCtasM1j0O2J0mWBKDceHYY9G1bysM7K4/9Je79XZweVyID9bvPeFW/cHOGHSgG13HcAW4fHIwGm1e+bfJXutARdVAicsrEG7duguvTH0bJSUVKHCUw2oxq7blMTaZTQgzhWPtmq14c+ozKqwPJn09u0oWwVM5iBVp0++P4bbWfs7lAxWZDyYiPNaMCI8Hzpw5i1TxDIYEM0SY7xzU7d69o3IvUmAw3Dx8gOfDJ0U6upgonL366gd+ywsNDUa7dq1VKDLzQeruJk31q/hbS9GitqIrdFdSNKRoQFGAwh1zAtY2P4XSr7+eiV9/nadCmRMTE5CdrVeZpoOnZ8/OKrTXqFDL6AYum9WWw8LC0K5dSyU20L1FnnxyMk4/fRQONRQlVq5cr/Ihzp+/FFdeeR4mTrwOhzN0xr7++od+0xieyiI99c37ub+I8Hjg/dIXXnhbOY95/b/++qOqCBSvF94nKN6cd94pqgK9EaLblETvW265AhdeeJo679hPOJTnA69pupo50MJCVcwxy/yWvKdy0IOvhhY391d8ZDX2JUv+VYPuJpOeGoGDT2wzvvMzhpczTPxICb0W4bEWRHhUiPAoYEn2T6rjetl1b8CzoQilA6PhCbYgq7ACFreGkHwXQgrdCCpxwxRmhSfcguBSTT2Mai1DYOocgXHD++CWrv2we1cedmXvQUrreJjDrermynxppMipP+xuKSiEw21UwNY/6xQTrd6DYMbqJdvw4uRv0GtwOyzdsYt2SBXCSLeiuVsUErsnI/vVVSqEWn3Hqt+sg9nhMplgMZsRMbItXB3s2L05C+71hUBmBbQip3I/moItCOodB7vNqhw9jsxSuAscCGseAXehAwkxEbCFWHFM6+aqcMSAY1ORFKGP2rQM1wvEGK6thsIoYOL0pGNHejbGjr4PIaF2nH3REFx+/UhYTGbEBeu5M23mFk0mZNetMVG9E/9u+BttUhNxXJ/JCAqzIyopHFmbc2v8zulnDsPFl45C505tYDUnHPR9EeGxbrg0vdBTWoFecTSztATzZq7Gu09Wz+tl8O57U1TYbVxcQoDQZKnxXPHNDZhXobt45mdsU+8lTicGN9Ovq+ahbf1d2UZYdWW4N7l21pcoWJ8Dj8MDj8OFguIyeBxubNqQCZOb4e+ArdAFW74T6YlmlAfrAqUSHs0UHmt2TB4QibqbJoyDHbsdCM1zwlrshtlVJXB6LEB5nA2mcg8yuoQp6ZD31gQW5dKAxFbRSE6IhiXYipD4UIQ2C0dimN6uiZW5u+akp8ORW47lH/8LZ6QV5Ql2HD+6m/ps4rF6Pqz+iUYb6tjMzb0DKNXRt8+t6ekzXJ5MrMzdoq9rpz6QsKdMHzwY11YPsxyUZLiVef/Vj0tViojDBxEea0aExwNn9uy/VEjshReejpEjB6tcfHzYZDglH5gpSvJvhi7Tycfw5sGD++LUU0ehR49OSkykm5HuQuYObt26xX49UNMxyVBvhkAyNJkPuCwiw3fmRjv11JNUSDOdV775JImRm+344wfh9tuvUg/9FEt++22eyjFntZpVBe3hwwcgOTlRDQAxf9vatZvUuihaUkg1XgyR5L4ZxW0OFUOHno3s7BzlEps9+6Mm7yqiGNWmTYoKH2VIPfNoMsS6JljQhxXMD2V+PxEe9w+K8YMG1V59/I03HlPXEQcWGgM9zDtbhTUzYov9Z7qr+c5q6nQtMp/rxRefiXvuufGQnQ+8P/L8p2OQYh3vXXRfGnTr1kE5LJla4aKLTlf3UjoMec3rodksZBWmcr8OHNi3xuvfEAoZhUZ3NI9BU79PNEUOC+Hx5K6N43j8aU2TbJdDyZEhrwsHTHmpA1qJC+bOkXAlBykBz+V0wWUCKiKsyK+8+SbGBsGc70RopgvutGKqB9DWFGDJaicy703FmpXb4bZ6EB4ZgvydZZj/6zoMHNkJ7To3w7THZmLXlhyUlDmQ0DYW7Qe2QptjWqqiIyR7Zz5mvb8IC2avU38v/2sTPMNiYSp0wfxvIbRYO9Cl8mL1AHHXdIWn2InOzRPVj0PE9nLM/2Yl+p3WDZuDPNj5zio4c8tgahYCa/sImEKsqPgunYkZ4VytP2CHDU0GwqywRNuR/8cOJTyGD20FZ4gNqzO3InNbLj5//jdcdt1InDS+9yE501q0TMDfK55Cfl4Jrr/8VQwb2Q0dOzVHU6V3z7P9/mbeTLpKA2nTNRn9R3bClBuuPIRbJ+wPbpcHa5Zsq1V07NSzBf77wnno12z/Q+c2bdyN9Wt2YktJnqpSz0GBTtZoxMbrIltxcRmCg221PmiX7ylF2qer0WxIS5jtHHQArBF2OCOs0CwmmGxmlLUKRonTg4pdVZXsDxYmjwZbqRttVleFJLvtJjhirPC4NAQVulAeYUVO3wjYit1wOzxosbwIHrMJ5eEWaC2sapBFc2kozy5F+o+6MNv6tA4oDA2Bo6gCJZ0SYQ2yIXvJNhSt3ANnohWWUg/i/inE1pVLYLKY8UjUBlisFpx7xhCcd4F/1fj6smPLHmRu3YPQmGC4bFAOckEQ9g0FOgp9FAvPO2+8KiJnwJyNp5yip1YwxIivv56l3I58uKbLUH/Qnor16zcpFyH7OHxwfv/9L1VoNHODff/9bHzyyXeq0AIfuk86aajKC2nkeaO7knkl6awy6N69kwo7/u9/n1LF74x8kxRAb7rpcvTt272yaAnztWXh8cdfVesbNWo43nnnc1UYp1OnthgwoA/OPXccnnrqDfz00x/qRVh9mEIql/vBB19iz558Ffp94olDVSGYXbuyMHnyWjXfLbdcWa169sHir7++UO8TJkxSAuu4cSObrMOITtNJk/xzOBpFfgIL+1BIff75+w6Z01HYf5ibcdiws9W15ls0iTAk97nn7vO6oPeHYhb0/GWOctaxSj3TytDRzHynPNfpeqaIyAGQ2pgy5TmVSoGh3XRacrCAbkLmkaTjmikXrr76fCQl6RFYB/seSuGQFe7//HOhdzoHS7hNzBHJfbvzzmvQtm0r5ObmqQGWDz74WuXG5L2MYd4lJaWq7Zl6gcu5+OIz0KFDG+WapEuc+8h76NSpHysRn+HiHIhJS9uqUmGw7Tggw/v2fffdckBVtVlYZtmyVer3gOH1vP+JuCkcTRxRjsecvDmIioo5bEK8GgsjzG5x1q/qfeaSdZj14lwkHN8KzQa2wBvT5+nzuTRER9lVOGK80wTT5hKYtujOPFeEBc5mQcjOL4fbArTc6UZ5tBVlUVaElngQluWf/8zZMQzmHAfK+0UjtHkI2oTHIOf3HQjvEovoAcmY0KsnPnvuN/z75yZ07dkSLVrFISw8GG+WbIQp3wVLRgXCXCa404ow8JmRWPfGMljDbNizaLdafrd+rdG1UwucP+E4hIYF4fz/vI28wnwUdtLPg9JyF2KWFCA40wFT5RlfFG/F7s6hTHSm/o4o9qDZVgdcIWaYHRrMhnhmggr1jmoeiYtuG4HEltHonKiP1rePau/n9GGRhf0554xCGe7Kog855Xoi5uN6T/LO88DTF2Lo8V3QLKJT5boim4TzkTmk+CPtiyvaimMu6Yuo1Bic2a2j+mGNrKw0NyDppEN6bTZdx6Nx6238EVW3VoASl+5w25ifgc+nzsE37+u5hTKOj0VQjgNxmS7Y+8bh10dvRUxYqt95v7dz0EjtsLtUTyS+KDMdeZlFmPrf79Hl+FQs3LRduZe1Mjfcq/PR7sY+uPGUwXh94rfI2JaLez++DLO3p6NwWwHWLNisHDi2lFBkO0phmZkJT+cIaM2Dsbtcd1KWrfFP+RBIQzkeKTRGlmiIz9dgqXyGKAgDgpzAjhSrKizjxemppXE0NchT4/I1Tbmyg8o9qlhNVG6V27PCDmQkW1FhN1WFi1e+h3eKQfNZejqKYycOwdMXjFf/Twrp43VWu7Qc9W4zJevrqiye5fBsRX5eMc4890Hs2VFVPMzdLAjmCo8KG+dAUCCnXT0YDLCPahmJVl2TcWGPs+rggGz8858h5tu27kLbtoOO+lHoQMTxuP/QMfPAA88rB80jj9xVY5XhrVt34Ndf/1ZCIoVHPkjTiTNixGAlPtx99+PKOcKwQbodn3lmqt/3+fDN+Rg2fccdE5RoSfGP4d3vv/+cmocP5jfccK8Kj2b+OEYnUFzk8ii+sbjBDz/8iilTblNupr//XuJ11Q0a1FeJDDfccIkKq/7nnzV44IFnlBhqCHY//zxH/fYzl7PBihUzvaGhDC/v3/8U5YgMCwvG7t26q57w4Z15IM8//xRVXOdAHubrwxdfzFDVksnTT9+jctCxfZoSDGUfOfKCatOfeGIi+vfvpfL8NbZYIY7H+kEX8PHHn6f+z/DpSZOuVzkATzttVLWBif2Bj/I33zxF5VfkwAMHEygy0i3Lgk68xumiPeWUK7Fw4bfeCvG83jmwwQInvXt3w/TpP6jCl2efPVZdG3V1WDfE+UBhdNmy1eqewrQIhGkleH9hjliKhPs67w1Bt6YiNWwjXlvr1qUp0fG5597yfkZHJAdCLrvsrGrbxAGcBx98QbUV77mfffZKvfftscdewXvvfaEETN6HR44cou77DKtnhXJWJveFYewUfynw9u/fQ+XGbOxr/ohyPI5tJMfjDHE8Ns3hvv1kdd5KJFdW10yNHKDejaIgDfdwoz8sOTx6eKBv6NqXm36Eo9ylnDZMIj6kWSs1vVmo/pBuYl4uk34zrHDrglmotbOfCGMk49enNdzhMZaraRXeNumfMEy9P//ZlzBXaHAt24NuXdpizn1XqBvc4t2ZiK4APnlyNlJaxiKdN+2QCtibhSF8ZAt4Sl0oW5CuCstsDqrgzqjlFbs8iIk0ozQIKGf/M8iK8IIKxOe5UPpvHnbuLoZlgAVaz1AU/7wNWTEu7GjXDkMmHIvbrz4TX3/5NxYtXIfhx/fAm6eNR/rWbLw45TvEdYpH7OhmSMvIRqnDAcf6HNhTI3HjfeMRnRCOKLsdu9wlqMjMR9huF4ZOGKyEALPVjLfemYNgzYMQH5k9M9gDpFeJD822uVEUakJBJNAio2rG/BgLonMdyNq4B8/f+LmaFnVaG3VKdW/VDEndknDrAP18SwjuCktlbrX6YAg3LLJDYoNaKTeC1WZR+TfJA3d9jLDIYJQUlqv8mV/OmKw+jw/uW7mMQ3k5V4bId6pKZt6yVSLSt2fBGWTCnmZ2LPlhFSxbSvEHZuHpl6/E0BG6Y9Tt0QUNq1kPHT8yYfuY/ETl9OLF6t1VGS4cF6T/IBc5S7G1UA8ZaR6uT0sJ1QUhu0UXtg92QQ6K2J7KHIlPTvoC65emo+dxqeqV0zoYO+enY8vcrUjpkYI31i3F3X1T/IQlYx8DBUiXJ8sbws1OH19XP/EZIlcUIqN1MBbs3IL4Zvp3krYBlt5xyNiVizsmTAOKXCo9wsQxr6E8woLgokoBM8WGkGVuBDsAc5kHloW60MhHx4ogE7Yn6gVi9sr+/BxoGhLzNEQX+Y/V8a8diWaUUlswOoYUAeuSP3IvHUnNZEKFy40KK1AYAWRGWFSO2phCDXEFGlpvd2FD64BcmJqG0uLKCtsMm8/eg9dXLlP/L8mYgxXvLlOVulse1waOMifmrt4ErcKNMqZmjLPDlueGZ085KipFx83dg+EqdAAmF/NgKOIsZsTl+XeSP1i6Cia3hoi3dGfpk6NnwtY1GnOuurZyN/X9tJkjvb9F+RW6+Blp1/NCGkXDbGb97yBLBzQ0gZXQ8ypWosBZc0oIoWlgPPg1pTxn+4IPqBTx6KShI5HimlHUhLkcP/roG1U0goJXXl6hesB85JE71T4yNJnf+d//HvIKlhQwGVZIFw8fWOnOYSgknUB8wKbjh44pOpEYBs38kHQpDht2LP7883MlMn777S/KHbdp01aEhXVRD9J0/oSEhOC44waoCqw//vibErUmT74BJ56o9w8NGF45duwI9dBMMYLXNF2NvqLjf/97k99xYuEM8vLLDyrXpSE8UnBkYRq6Op944jX1YnjkmDHDsWnTdpV7ku6ig0FuboH3/wyDp0BjMHPm+40uQt5zz1OqQjmhyGHkyLz//luUW/TEEy9Uf/fr1wMff1xVOVhounz33S/KSUgHHgcWeD+gK1FPs9D6gN2DPKenTftcFZq5995bvNMp4vE+dMYZo/HUU6+r9Aipqa0xYMBpKg0CHc0UvlgNm/cduq5ZuIqh1hToDb788nXllN4b+2th4j3nxRffUaHRvtxxxzXqnsDQ6PpQW1VswnsWq0YblaOvvfYiJVT+8stc3HLLA3jssf8pJ3psbJTfd7hM/gYRCra+poZnnnlDpZWYMOF8NcBChyYrlPNee+yxvZW4+O+/65ToSF54YYq6L/umtFi9egMuv/wOdSwMeK+PjY1RgyTMpUvWr/+9Xm0hCE2RI8rxOGfzK0iO9RcezaaQgyY8Oh0u/Ls8E2XMgVFShve++wa70vYop0hYdAjOuXAw+hybikhTkrqhDBrUC2HhoU1GeDQKFWwr1keW/lqxETM/XITsXQUwm0zIKypFUnIUug9ph1PPPgY5mYW4/Rz/UXe1L1FW7IgBtFC6fGgvrOzIGSM4wfp+WD3Mu6bBEWJB5wG6sKL9kQ2EWXDueYOR1C4OV/fUQwPZqf71l2X4/Js5KC2pQFh4EMKPS0HR7iIs+2g5Qo5NRMSwZihbvgfBa0sw4uL+GHh8R1jNFhTmleLtx37FzrRdcDlc6gfREO/MlWd7bpQJe6Jr+YGiaKFpMNPDowHuSMYYApG5biRvc8AZYYHdBYT2TUDJ3xnqK7HxEbjqhpMwuN9wdEjtut8hPIYb1eXJUT+Ib3z1GbJ2FmDV2p3o1CkZ30z92ztv524t8NbHNzea8Mgf3V69qucUqgg1w2MzwTIkHtYleTBnOXDuhUMx+b/nqs/t5qRDKjw2juOxduFx9+5czP5hOZolxCE+PhL2CAu+/3EJyssc6N61FXof2xaDuvVQHZ5DJTxyK/MdukD12e8LMP+n1Sp8OX19FiKPTUZspzhs/XcXMn/dhsTWsXhm8vXo1q2tTzEY7FN4/GXOUrz85PfYUFqAslYhyArXr7/4mCB1vSX8U6yazb2rFOgYDgyMhaPECdsPmTBV3lNKQ83Yk2RFeYiJipUSu4LKPAjPdSF2lwMuK7AjwQwHnYC14C0uU1E/x6PNqaHtLg+KQ4D8CDPK7VBux8JwE8qDDt1IdOtdbuWq3NTCDLevq1LT0HG7B3kpduxpF4K+EVEoXZyFzoPaIiQmBGm/bsI5tw5HwZ4SLJmzESGRwdjqKFYDZSUb86DlOdQgjbVdBJw7S1BcWIGdHYKBnEqxzlgVw+LdGsIK3ShmFfBQK2I6x8BU4Ubk33mwF7lhirWr5Z530rHo2auNCgPMyytGYb4LeXkFqngYfxAiIkMQHx2JyKhQ9OrTFh06Nj/kwmP69lz07nhFkxydPxodjxSy+PDG+zYfyBhiygc55hZjaC/dQjabHSUlJerhjg/STRU6ipgzjMIDHY3M1xgVFYFOnVIxceL1aiCGDiMKb4F8993biI6OQFxcbK2uIz4ML1myAoMG9fNOYyjhW299gssvP0eJU8aDMtfF3JIUFDZvTlcOyYceul2Jo7ff/jCaNUvCfffdrFJcPPbYy2qZN9xwqffB/8kn38D33/+i+mYU64xHB7o7jf+vXftrrQ/+FCzZL6LAwSrTFJTZLx448HTlwOR9gaHiDEWkWEImT75RCTN0OjVUSDYLUVDMo+OUwifbxKj4TRYs+EaFrTcGbEeKoRSAAqEgyoIedLEZjs3GFCKakuOR59Knn36nrgeG3lKYDw62K0du8+bJGDr0GOX4bazBC57nr776vrpW+OK5PmnSDUrge+edz1Se4WuvvVDlWq1PDle6lK+5ZrIKJWaOz2uuuVAVqDL4/PMf1CAH18/pH3zwAhISYvHIIy/jgw++UvNw0IPr5iCE0ZZ0A27fvku5pXm/oiP5rrv0QcTa2LRpB1JT638+nHjiRSq1A9fPAisMQ161aoNycR8qmDPyootuxaOP3qWcnr589NHXeOihl9S1xvkY4cVBJOZcfe21D1TKBp5fdK7z+k1IiENcXLS6vyxcuEz9bvG48rfg++9/xaxZ79ea33bWrD/RtWtHrzDKY8FUFu++O10tMyoqEl27tke/fj1VODjPIwqbFJ7z8wvUfTkqKlz9XvPFQSQOVB1qp6Q4HmtBHI9HnvD4a9pL6JGij1bGB/eq/NTUIGGdDs8WJQTd8do0pP+7GwU7C5CxKQfx3RKxIT9fOWxKoywoi7Kg5cYKlKUEwbWzTIXJaWYgOt8DRFhhbxepHsiiokJhsppRVFHBMsWIjNT/PrtrZ9hsFkSFhWDRnkyERAXhzGO7K2dbj9jBaltcmlHVWX8Yt5vbeYsC5FcWbChz6w9YeRV6aF2Iy4blSzYjuHkwVnuK8c4Fn2DIiC6488EzkByluza3rM1Gt+6tkbPHqSpwOe35iLLrnT27WXdt/vDn53h6ylfI3lMEzVVL+GAlaa0tKn+ZF+P/fKPYwEl0yeS6kMQCMdkOtGuTgNbdktH7pE6ITozA6W17er/+7LK/sHDaEqyfnYbIm7ui3KWPApVkFsM6I1MVa/j854mIjA7Fzo2FePm5r5GVX4hWnROxeNU2FcpZ2lPfnx0F5fCYgOS0cpTHWOEMMcNpMcFtM6H5TieCsh2o6B0JZ5sQZOwoQe8B+g/qCT06wlnqxNrcPcj7cSuKF2fVuO89hrbDbZPHIzo2HF1jBlXuft07zh5NF0Wc2m6sX5eOc854qMb5et10DG46W3cmDEke7heCfTDhQ+GoURerBylfjjulBzLzi5GfUYTMjVWftWgTh5kz/qdXPK4UvmsvdHH4CY9G6Gp22Qb1HhsUg82FO9T+XvTEh3BnlSGYFY55v/p+G4K6RqN0ji5aExZsMhdXiuMU8EtdCI8NxSvf3KCW0SFKF2sjbS0PimDLcGhD3HR69EERp2cPdu/KxYvPzkRFhRMerQKax4NSpwNJiVG4+4GzYDHp31mXr1eDD7Pqx7ZP/DDvgMeGAv0h8ouP5qn72OxYvcjMb+/rQqfhlB4yvhMKP9+MkH4J2DVzK4qT7Mjndnk0WCs0WFkdutwDp82kF4oxHIWVghspCoUaUOA8FMgUwSzaUjmvW0OoxY4gkxV5zlLAUTlI0tR+BQ1B0dguH/ck28HFZjdchJWCqEFepAnZ8Ra1/2y7KKcZtnIPyntHomhToX/ot3FP5vI1TS8Gxmn827h1+87ju03Gxx4N7dOr1p+ZYEZBuEkV9+E5HJzvUsvy2E2oKHGq/KEUTLn5FjfQvH0UUOFBxE43Wo1siw7H6781Dw+oqoBrNSd7U1n43h9dWtU1tC1/O7ZvzkZy8xglaHLwTP+Ofh4EW4MQYgnxG6TZWboLu9LzMazbDSI8NpLwSCHoq69+wvr1W1QOQDoCL7vsbNUHoYjAh9E5cxYoQY15DWfP/ludO8w1SOhQobjGB2u6SPR3O4KCbOpd/3/VZ3xopFh5oEIWHwpXrVqvhDI69BhaTafizz9/6HXrsUptWFioWi8fxviwGPgQSPHr+uv/qx62+VsVmPvNl9dee1Q5pvYGu/R//LFAPfQuWbJSuWUYls3cZUOG9K82/9Klq3DBBTer3GWG+EAB59lnp2LatOnKiUnhYdOmdMyc+Ts++eRb5dih2EGBggVNRo06ToVrMjSTDia6OfkAT6GRhTIWL16uHt6Z55HOPYZVG+3A7eU+U1xmMYsxYy6tdd+mT39NFaZpiAdpozpvICxS8eWXbzRKWOOjj/5PCRi+0PXFa4JtZOTR9G0PhsEfTcIjzxeK5lOnfqIKgFCQffLJ15CSkqRy+xl07NhWhRYb7jEKaeSHH95RYcWNBbf/2WffVM5C49xn94Tv9957c70ctxScbrrpvr06X+lUZiErtgEdjxQfuV6Knuy/64VkKqpVnL/00tvVPYTOQ4rdt9125UERHpsCvIdzHynKErbPMcecogRsA1+Rf9Gi5WoA59JLz9qrE5TL4f19bzk1a+PCC29RxXEIB9seeOA/6rdr7dqN6r7O+yUHbDhIwne6NM003hQWKbGT74sWrVDbQEHVcNzXF56n/C4HzuqaR/awEB7HNVKo9Y8San1ECY8rd76Dzs30jpUZwftdZVN/qNFPyPQS3aV08lNvwj0nG64wM9ztwrC9sBxWpwZXdqkKifN9gGaxEj9KXOqhzlrqgc3hUS4678uiP6AxPxbD5Ojg0aebYQ21wlLhgbXQBY1FXsIsqAgz47hTuiMsJQJ92+id23+zdfGrdHcxdizagZD20ciuKIGW60DemlwE7XHAludSz5GlISZvPjJuNg9+UPdovUL0snzkHxuFYKcGS55TPaxqdPvF2TH+5H6IaRWNXJcDxRnF+OuhP2CLsKN1t2bK3ZnhKsPaLZnwWE0IZaEHD1CYYlcPrUFBPhc3T7c9DoTHBgHhVsQm62KMdVGeqjBd/E+WClcfMLoLzr9jJMrcLmRuycHnz/wGT7MQRLWPxYaPVyG8exyKTU4g2IzsIgfiVxWrdus2pC3adGuGocN6IqZ5MKJzw7Bx40506thJFcu54ubH4CyogNvDh2z15Op3qMLbR6M4TRdxR47thV9nrNA/6B0FU89o3dHJ/Ew7dUt8hAeImZeHkJNT4Pgyvdq5NHPhA2gZpSeLtpoS6pVzj2wrXq7eV2Zl4MM/lqsqvsVbC+F2uJC/NgfNOydi+md3qnligjp5z/mD75DTc1SNHn2J9++LLxmPYcMGIDrWhEUL12Dau98jP6cYnXu0xBOvXIZOCUZH/9B26BtSeDScw0b7ZpXp94e7/9LzpSLfify0XKz5fJVy6VEgslZqWwUJVlgdGrJbBSnBPSbDicx2wbCUe+DSPLBXaGidVuXI4ndN4VZYCvR19nlwGEJiQxAfpt/TTmmnd56HJo+o8V5Hd5emVW6vybgnGe/69FW5esL6GVu34PgWeqexV5yeIqKgMgdiTJA++mo369Mdnk3YVap34tfmZsHj0TDxvk/h2lwMpw3wRFgRkhwKU5QdzmAgomWUeogbWhGDzUt3ILprAhI6xOO5L+fqm1KmN1Bqn3gE/Z6L8DPbIOuDDSjqHYGczVVhcZU74rODVdduUIWGhHwNwWV0KleR0dqOwuY++dU8GkJNNgSZLMhzl3EnK5ujclm+gym+AyV6g1Zbr3d7An9G6/KrGrhcX6HPWLfxWeAgT+U91Wo2o926chRHmLErzqRvjyEQGssL8fk9chg3/4B9NIRI3/BwQ/y0BTiYjH2u/Dy80I3m6U5s7GyvCnEvddXeDsbyou1+y4tPCkH4P4Vw2c0o6hqG9vYweDLLYbKbYQ+1KwduSIgd5iALXCYPyrYWIjI+HInD9fNy5bvL4MouU+v0lLvVgJ8pyKJ+V7h/XIvFZkFQSjhSe7RAXIc4XDikJ/bsLsIZ/e5skp3kxuRgC4+8L9M9wiqlN954qQrbpfuOD9N0atQFCjIUFOgmoaOObiKGJRvvVdP0d74omLFoAAsxsPACQ5JZvZTvDFf2dexx+QzD44Mp87BR8OD2Mpx58eIV6nM+0NPlUlBQqP5m2CSLq9BpMmXK8+qBvkuXDuqBkdWluY90tXB/KXIZhWAuueQ2rFy5HgMH9lHCJQVL/RWiKlBT2KPIymIJgXC7KCIwNNcQzCgAUtRlHkm6DH0fntkOkyY9oR5QmWNu2rTPlJuGwiEfvinaPPDAC+o3no6oceNOwJgxI9C7d2dVMIdtwMIIdC4+/PBL+OuvxZWDiiblwvKFRRwYJs62Of/8U9W8zC15ySVn4PTTR1d7cOdxY646uojozArk8ccnKrdRQ+XdYy65BQuWorCwBPPmLVFtM2fO54e86jah+HHllXepEFlCofjUU09UQhnb7OOPv8WCBctUPkAKwhS8Gyvv26ESHnk+UeCno/GHH35T0+jC47nLSup0eY0efZwSx88770Y8//wUJfbw2qboPmTIWeqYGlAQN8KImfeQ3zNSBzQlONDyyivvqQGTNm1aqnsCRUm9WExzNaDCa2XUqEtUHlbedzggEOg45mAI95+DH3TH8V5bF3jP5GAKBxF4zzJCoVk1mqkTAqO6Dmfh0RdKIn37jlWDIP/886PK/dgYcGDk66+nqt+JA9kXHv8vvvhRXRc8/nRV8hyhmKi/gr3/5+8IxfqJE69TYinvNUz9wHOO931eIzEx0eq64nXJASqug+cjB7f69OmuBoZcLpcIjzUhwuORJzx+9N19OH3U6epGfSDCo8NZiG+//R05e/KxO38TCvJK8dOclSp0tCRC/3Havr2ySqpPjsC9Co9qwZ6q8GPjR854CDMe2IwHzFAr7M30G56jwOENKQwq8aBH8ziU7CyGzaEhslkEXPF2FKzNQcn2QsSf1g4FizPg8nhgirIhJwRwxNkQtiBPFSIoDTOjPMysPyCGWZUA0t5sVw//RWYN1gIXTPFB8MRYEZYcCk+eA8hxoL09Crnp+Wq5kS0iVXhdwYZcmEpdKimuKdKOLK0CBZ3CEBmrt31ZqRMmh4ZgswnmYhesuypgzaqAJ8isnEuIsiGYbheXhop5Vc7Bm184C4nNoxEeHYJtW7PxwjWf4cxbh2NNSQH2LM1AwY4ChKRGoXC+7nYpTbChqFUwEt1mmJYXqPyaZ189An/M+AfDh/TCLbeejtgYvSr0ea8+g40frkTZiFhERoSh+P00/SHcraHd9b0R2TEWTx+nC2QaNGTsysND789C2nQ9z442OhFIDtaFR7MJYXRTqSqVMSh7Jw0oqcoXRLr1aoXPP3vmgIXH1TlZ+DpNd7PyobosqwTLn9SLf0z/cRKat4g9qMIjbxN765g5XLnYsmUXZv+8WFXVi4mNQJ/hrTBgeCc0i9cLPrUKH3JEC4/OIgfWvKg/gJXs1oXp9GYWlLEwh1uDxxCADHGnspq7uubLK8+bEieCHIDDBoSUa4jrGAX7mmJYsvWOc2izcCWssRJ8335t0bFXC1x80vlISIipVXhkmE14eETlaGXdhcec0kK8P/U3vDv1V7z+5p044bhxXuExLXsL/v1nC/5esgEDxnTFo3d8DlOYFUUdQ5TgGu42Qytwwp1bAVOuQ3e0xYWh79jOKHS6kP7PDmzOLUBGOyaC9XiFR9t3mQg/uy0Kpq2Hyf9SQm4k869WuhnVDgb8dAVbYXFpsDs9sDuAsBIPwgs92DAo8ogUHtW9e5NThZ/vSA0CjNyOh1h4DC12o8U2JzZ09Qljq4/wqAHRWU6EJIfAFWWBNb0codvLEdEnAcEdopWz3u42weNww+YywVPhhqPcieCW4ahYm4+yzBKEtY5EQUYRnDtKEHNhe9jbRKB4TzE0DvRxfTYzgkLsiAwNRgXnydWQuzEH2p5yxCdF46uPZ4nwWEu/avNm5iLU7wkHAsPUGOJKcYXiHwUfCmlXXHFuvcILGwoKFtu27VBiIHMi8p3iDt0jFCL5wPnGGx+rJP8UzTgvxSgWexkypB9++20+srL24JhjeqlpRp42w3H4zTezlKjHd+ZTYwViLpcumjVrNmD16o1KGKSgyAc7iksMLec2sH3CwsKQmtoKV111nlq+4bKkYMp7Oiu4/v33P/jtt79VH4yOKf7Wsao1Hyy/+262KlpAGILJMHUWKOD29es3XlWu5bLnzuVv9lzlAuUDpVE9lgUU6Ia69dYH1N9TptyOjz76Ei1bpuCqq85V+00o8pxzzg1K/GCl68mTn1DuTbbZ0KH98cYbT/gdX27/8uWrcfPN96uHe+aFpJDIIjmBobDvvvsFHn+8eiGHlSt/9suRdqBQwOEAWq9euqB5/fWX7NPhdbD7VIRCwZw5C5XTUc/vOARjxhyvhOHGFsoOhfBIYYO5EXkeGuH3FKzvvvt6dcwoluwtp5+va4uCSU4O+6npyuVLN69RvITXlcvlQceObdR5zdx8bOPals3topi3P6IU74PMJ3jssb1Uvj8DbgPvCfPn/6PEeIqtFJrpVjNyv3IggC8OttAdTm6++XI1OEHBaP36TXjiiclq2w2Y25GDB3Tp8Z7L+68BRcSzzz5ZOZFrg4Muu3ZlYM2aNHUPZN5W5p+lg7qpht4fCCNHXqjuwY0pOhrC47JlM/bbqcj7+M6dGejevaM6hhxIYtoKDoRRNNZ/h3WnJ+/DfKdrkvdV3nc5WMZUHwwPv+CCU3H33dep30zekyhiMyKBA2KE5yYHS/hi6grem7777qem7Xgc361xHI8/rG6S7XIoOaKEx06n9ENMsRnRzSJwwvCu6DMwFSN7jK1zmGuFe716v+3OV7F4yWZ0HN4OMzZuUdVJGUKtMRSX+cdISeVDnm/rGf0Ao0MQWOCgMpzNj9pan18N7FhUilyIqOxwmU3Klch8XyG7yhCT58GmFBNSd2rY0NGmf994ePR9kK3twdTYtkoHknoYNR5IK0VVU5hNCaB2CpSahjYd4lC2IEs90LYa0ArZ67MRFKJvn9OkwWK3QAuxwJlfgfJKl6Avtm7RLK0Ka5AVtlbhmDhyKDp0ba6cKeQ1dqwn/aI6hYZAaAqxIKhjFMpX6EUBMjqGoDBZd8TEFroRtbYESckJ0E5NQMpmt8pblnRSG5TllmHuk3NgaRYCS58YOIIBLbMc+EEXMKe9fxf69e8Am7mlV2AhU9/6CdM/+xvnXHccPv1ukXIcMsxbG5GAtG2VjqxK4ajNxgrlXPPlh58eQstWCYA7Rd3UDffZ3nMy6stwa3rhjALHFtx59zT8PVMfCTcYeElfvPPfKQc9xJo/ggz5Of74Qephhp1Aujo4Crp9+07VaeJDDV0eI0cO9UvO3Ng0lPDIXIXMWUj+3r1Rvd/wzKfAigJgV5XLY0OvUKDAJ5ecce0ZgkuAyxZxQVXzGKG/xZXCTYX+d1iZhpJQE5AYgqCYIJgosOU7EZzrQhivRZeG7se0QctezfD8hJvUDz/DUtOLF+Hi8c8ic3c+TEFmNOvdDOHNI3H3WSeiW8/W2F68B2UlFfjs75VYu2YHSncWIy89X+X4U9db5ba62oUCmRVqmtutwWwzwxlvgznKjuBlBSiOt8ERakZusKZXc/aKq/w/EFLiQYRmRmiuE45Ym6oaX6F5kN3SXjUwEx2EqDIN8WtLsLt9MOK3V6AkzAyn3YT4DCfy4q2qsvO2tjZ94MQQawMHfoxbXogV7RcXY8NxeiivQtMQarbpVa0pPBr3POPzIse+iy5rPvdjurt9j5uxTYH3eWUvDwhV9smZ6G0rQvd5oMhptGel05HCc/s15WowaVsr694rZ/tuvyF2G78lxnLL9iIUGttVmR7D287czsp9N5e4ldu92m9epbhoq9xu57Yi/ZzWNAQ7TapIDc/tQDZ05vdMVdtlLNd499kms5MDcm6ElHpUao/CBJu+LSyKo/YRVcfI2OZ4fXDMEmNHVLEJue8vOOo7g7X1q04/fawK4aKIREdNr171z2H8558L1MM23VsUp+ig5EPQgVZyPRgwhI0iJF8siPLww3dg0qQn8dRT9+C0005q8PVRMOTvKEVIinW8CGfM+EMJFBRBKG5SlCMcVA0NDVUPxHzo++MPffDRF+Z6Y0g3xT5d0Gyn3FKcRtjlZ07HGTN+V/0RiijMscaK2sa+s9jMm28+oeanMDphwkQVBXTvvTeq9d5779P45ps31efXXXePKoJDhyLdZNwfOs9YUIHiCkM7A2FlWYZU33vvTaqCLgvbUJBkXjeK0b7QsUPnlS9vv/2UEofIgQiQ6em7VI65QJYv/6nGSuQNCR2uDIWcOvUJ5RBiiDXzENK5SnGJjj6mEOBxYYqBpiA2HgqhiY5n5tVjZWOD+otAgb8p1duNYgn7hnQ6E/ZhKd5RoGNoMvN+UvjneUaxxreoyOzZf+HGG+/zXm/sC3NQgaIwrztjUINCoHEv4fXAa0+/xqHcqnRJl5c79EAFj6ZEUFaTf+ed6WrwYcyY41SqCUPk9yUrK0e5QOm+phBEtzL//+qrj3ivdWM/6W7mNtJ9zHmGDx+oBjkoIrHI0+23X622p67PAgwJv+SSM4844fHcc2/AihVrvVW/GxNeB/V9juKzGAecGEkQyJtvPonjjju2Tsvh+btx4xYlIrIg2PjxI9T5U/ft2IXWrY9pkn0qER4bnyNKeFTl0c0m2B0aEiNCYMusUPmvTB0j8NGzE9C+Mk9akEV/GDKb9B8ymznFLw/kxrTNmPnLV1i0YAM278xG294pWBxbrB52NqTpQhB2VgqQbD7jYaYh8XO9aP4Pi0bosiEQ8kHOeB6LtCN1eSkqQszIbWb35gtyM1Q7xKSHhRsPbcZyKsUNr2PGeJhuHoqgSrGkYp0efuzdpkrxk8Va2q/UR9CYd83NKOsQ3UlJUZQ5E5mTjP0AW1llHrYIM7KTrWpahENfHudngQhznB6erU5LDXBUuBGeXVWl1YAiR1aiFWWhZhWGrm+A/kAbWg607dsK2cFliLRZYPopEwUnxCnXZ2nrEDiTg5DLh9JKEfaS5NbYsngHnn/ucrRum4hIux76VOjQhc2c8iJsL9I7C3R8krdmLMTmz9agbGAUEGPHhi0FVcKF3YLQPBfGdG6DVV/rTkmDITcPwoUn90doeBCOSegDm1l3YtaGR9MFrS82foX7TtE7+oF8Nm+Seu8a08UvJLahQpGYd4gjxKxEyU4RR1+Z1J8/zAz9MMI+fPMFqndNP25mk+FiaJxOMzuXOTkFSEnZv9yIvvuzrXiR+v91v8xE/i/pyP9th/rbyaImLWyq86qEN1+XWaAgFChE8loyBKBCp7+QFXhvSQqpum4Nt55Nz+UXarIgIqMC4XSHDYzBe/+5EM3D9B/9yY9OR3C4HUG5Lvw5Q88b88jXV+OZl2eqfXCFW5AbbkJFsAkOjwetdrphM7S0IBMKI82qQrwS/Lhvxj2k3K1chtxv1Xuu6cHI111XeX3yvlEc6y9gmZweJO7mgAaQE21CSpYHO9rY4bKZEJHvRrPdughVGGNBRhu7qnrthyGIGUTZ0XFugS485lYKwRr0HI/BduS5SquOheHQ47YYrsCaxMPA42ccN+N41eW5p7afi0CHpU/beKkUzDr+U6LuexuPDQf2VO7bPnLu+i3X2JfAw+WbxzFQGPU9X33nLXJWtZnh9jfOf+M7VhPCsxxI3KSnKPGFbs3SSEv1febyueza9sF3P/a2Lwa+f/oIpBGwo2jW8ibZSW4qodZ0AzEMde7cRVi+fK1KcP/gg7fXOU8iHXp8WOdDL8OJ27VrqUSm+jzMNCbHHnuqEoJY7Zm/fXSP88VQaYYcNzRGfi8Ks/x9NZxdfLA08mxRhKRDivDzF198AAMH9lYVtdne7PvR4cR7M52a7FPx/3zncTDylzFMnMV8+HvO4iXMm8eQc18oUCxatBJjxuguJ7ogKTxQQJw7dyGefVYXYQy43kcffVm5WZkDsi5wm2+88V4ltBi5Jv23oQAff/wNvvnmZyUYGlD4ef75+1W71FeEpHjE8zKQ2bM/9hZ4aGh4DF5++T0V8sj+FcVa9qnotE1Ojldt37p1i0YXPvbFwQitDRSCZ8x4Vx1TDmrvHf3mrnlHmaqPGpq8SVjq1g/l9UPxkYPsDM2+6aZLcfLJJ3jFXwozLPwxYEBvJY7TJffRRy8q0YUFgghdwBQkWUzq99/n+RWR4mdcnq870cBIFVHX3ICsBL9gwT84/fQx1apA0y3LwjZPPjlZ5dLlvWDChAtUeor+/U/xzvfXX196cxzurS/cudOJmDDhPNxx5wS/yCrmgE1NbdyK8AfCG298hOeeewtz536h8hkeDvCeeOmltyEtTc8XasB78z333FgnN/DB4LDI8SiOx0bjUJbBPTSYTHAEmVDeIUy94iKCoP2wGxcOfRKp7ZMRHhGiKskmJ8dg3Pih6N6j+k2fI/GXtz4Rl199Ij5dswwLvvoX+GqnciF11CoddmiauG1m7G4XhGabK9Bss3+uHZIbb8GeZpVuyFqgiEHB1pbtQCiLOpS6YctyqwfdHckWlZPSzZucyaScJRt6h8BU4oLJbFafmaPt8JgBVxCTbJkQZDcjanMZojfpAqXLalJiAslLrAqtyWmlISVcf7D2sONgAnKLnMjqrt887Xt0oSV6t0NtS2lEgGunElXx1hBPuQ2JQYj4JRvOFiFwJtgRuqYY5jIXyqKtKI+0oqLEAbfLjYL8SjG5Dtgi7ShnPrG/XMAp1Tuo5eEWpB7fDl3GdUYzlxVr5m/B7PcW4++X56vXwBO74JWCHzHl/rtq7HgEsmdnQK477lpMMFqd0vCVXw0YfnbnnY9g4sQb8NJLDzTaj9iBojTsBhxfWbNiO7ZO9nGaDInDluzK1AuVQnpDEVPgUbkLme+RBTscFieckRocwWZvF5tQECyLsaEsxorw3S5YfshE4eWlXuHRw1A8t4Y1y7ajc68WaNsnBdOf/13lCk24oCNW5eWiYEelI7lEU6LjlrY25Tb0Uoujzk13GSs17QOmhlCDEBwcKterIvO7VuaxdWqIKPSgpPJ20Dzbgz3RVfeJoiiLEkUjSzRduKqL86NSXGLIdqAxven4RvYP3v/cdv3+erhAQdkZbEZJlEm9F0dZ4AgxH5yBu/psV6Ou/fCAzguG8PLFB3JW3WXyffaVgoKC1KAUBTgOTFE48q2sSihQMpyWL96LmR/xuuv+q3KH0elHF+S77z7TZH9jvvjiNVUA5vHHX632GXMufvnl63sVINlmDBelC4ruRr4oaqxcuQ7vvPO0yuHGdjFcXSwWQSci82gZL7riKMAYbUt31imn6OHADJMz3CzMo2hw3XUXKzGHIiPbVn+ZVLVouqKY25BCBKumsmABRbyaXKgUxXxFYkY/MA8jw8effHKSyifJ8Goe5yuuOEcJaoYrq66wCjFFUOaMZO7HQIdbeHiIEjEpSvLBNisrFxdddIvKQde798lKEOa2051z3nlVgsreqEl0HDNmOJo3b/gCboTH8Y47HlFO1K++euOguyoPJg3Zp6LQxjB3Y5l0Df7776w6F7OoD3TwDh6su/WYt5UhpW3apKhCVryWjXsQ3+lA5ItV1a+++m4ljhvXF69PnqNMH8HjymuNuU9ZSfuVVx5WIh7d4QYUHfv27a6u7X05V3mNB95Da4JpDjiQwx5OSEiIcs3yGs7IyFL3Gz11Q4YSGpmrj65Ghs0SippLlnyvnM/ffz/bLw/mvsjMrH5dH+4WJiPNA++PhwscxOCgE0Pl6WqnY5r/b6q/o02KxngQOHxOrYPKEeV4bDm4q6pMnNEtHMiuFN3KXHrVzc0uFKSGoKh1CFrGhChnUfvCYBTllOKOG07HqDF9VbVd5spZvnotfpu3EutWpGPpym0qR1T8iFZwZJUhd/Z273qL46zYFWeue2VUUx3C9wLnr+kzw4Fi5IusCcMVZfzAuT2ILPQgOdNdFQ4aUaU7h+S7kLKhTIVA+tKqZzNs/1evcks8sTaY8pzYMjRKPfhqRpVU368ZLhfDocnPNE2FSSZluJCdYEFejMV/HsNBFShu0PFitEOEkROsqkKtHywY49FUPrCksGhsdxcAcXrHLr4MiF1SUM3ME5kSiduvG4fxpx3rzUMUYulROZ/hqDLB4dadBXNWrcD7//sNG9btQn5WMSpCzdjWNxzYUZnr026BVQNStjNXHy2dVli4C2YTXCVOBPeIRfnGAm9I5ulnD8TkKecg2t63pqMIDXpnYGvRAozpX5UPRm1ViAX2Ecn46eEb1N/Nw47dZwg38/7pTejyhny7PNm49eYX8evsJZj5yyMYc9K9aNkyHsHBoXjmuTvRuaPeHnWl3L1WvX/07a94avKXOPn0fhgwtBMGDuqErZuzkNIhFnN+WY0dO3JgCbMpW//Pn/+DxBbRWLdkO3757Tm0TOnWINXoSVkZHY/5aNHiwML6thf/hTEPvAb397rbwn1SAjZnFqsUDF5nluEG4zVgONAqHV4sdMETT8tnyLKP85jCeeB5b5zaIRaEFXmQkq4v3906BFGx4XDmlMNMwS7EijzNoQq6MPzZvKUUcS2iYQu3IzjPidySMsR2ScDmf3egoks4dpU4EJ7jUgU76MxkflRuv5ZRVpU+wmJGx01ObOgWpG8nt03TEJ/tRmyeB5vb29XggXfbibGvgfc3fj/MqlzRdDn6woEDFttixWrOXh5thancjcJYK/INd6URlm5c8775Bo32C8QIJ46yoeNfVUNEaV2ClMhpCwlCkMmGXBbPCUyPodXgeAy8//p2TANddfub09F3ek0/ycY9v9JJGGQ1o/WyEmztEgKHVrm95QEOUIMD/YU3ttMYzAncZ96HKYKSQDe9sW9GyLThLPXFWK7xXaP9+fu274i5KgLb1XDAGpeW7zVmtHF8MCLdVhR+sqhJjs43hX7VJZecq4QqIyTRYMSI87FzZ6bKQ8X7K11zv/zyl3L2MHfYf/5zpdcJz/BRhg5TcGQeKIYbXn752Srv2sSJj/std92635pUSOm+nEZjx15WYygbxYhLL/2PCrEMhKGbdO4RPjDSUXjTTZerNqkPzAN31lnXVau62tBQvEhL245jjunhdVRRqOjZc7T6f1wc8+fpUTEUYMeNG6HySu7LQWWIss8//7bKM2kUwfntt0/8XJfsIzzxxKv44IOvlDjJojasuGu0Jd2oFCDrew6dcspV3lx5Bgynf+KJSQf88E4xliHtLMTBXJwMi6VQz5yhF11U3dG5L9gf5XU0/LgLEJ8Qg5tvugjHH98f2dl5aN0mBRs2bMWyZWsRHGRHWHgwpn/+MyIiQvHnn//gttsux/XX6+dpQ5GWlo727Q/c4cY8cyzmQSjyvf/+80rArkv70xXIc4MV7ClSVnc86ujOvKrzgaHsp512tYqGMQpLUSSnWMflsLgVxWG+z527ROWGpAuV4c8cMOjVqzOaNUtSAvhDD92h7mt0nVEEYpXxmipTM0SZ5xZTNhiweMdll92Ou+66Fldfff5+OfR8YZ5Wnvbp6bvV9clrkcYGDvBwHRRX9w+9PT1aGe6/7yVMnz5L/f3UU5NVMREOXuzevQft2zdctNWhhkJy9+4nYdSoYXj55Ycae3MOaw4Lx+MpjZTj8XvJ8XhECY+9Tuqninu0OK4VduUUqAf9ZRXF6gHWll4CU4gVLdaV+YV6tWwdj7MuGYwxp/fDW9N+w4/vzkdFhQv5MRbkNbcrl01wsQfhGRXKZaJai+mjwirdOCpvI+pfYCDwgTfwYc5XpKwL+xIyfT7vuNWtDEp5cRa1n24Wsin3ICndgbJwM7q1ScLuRXoFs8RO8bCHByG/oERVe2botMdmwhYWMwhcvhGyXRluZ4vXO6hOQ5hleDP3k/MZAue+Hlg5PXBfAoVH44HSrSEqw4HkXA0xMTHIzdVDpZ0dQmELtQHbSpXrxtouAqFhwXjo4vHoN6A9ooL1fCh2sz6i79F051e+Yx2WLtmEndm5WOjKU/kqczblYPm0pdiVYkNBkp1x2P774daQGhYCyxK9E37GS6fg61u+V/8PaROJmGOTsevzDervwUO74M2pusvDbNr7yDfzTfbocnW16Z0v6oF3J12u/h9t775Psa5KTHXj/fc/RVraDqzcvRlr5+id7059WqJTq5Y4/8IRaJ/aTY3o1id3pEvLQU5eGo4bpId/+2KOYk7AILhzymFpEQrX+kJYhyboxYWSrTBtKIF5TRGGXdYfN109UgnBXWL0KvUWU0yjCY/l7lXq/dinX0DFND3vZ1arIOQn26rOQW8BKXeV6MGceJqG09q1QcaiXfDkliOY11JJGaxhNhQxTDbYgrTV+nmqL8fpvzyjcnCQHcGFLiX+nXB+Xxx3Xh80DwtHSVE5ksrisG1bJlZs24gt6zOwYEmaSi+RVlYGrdSF0FINoSUe5MRZdHciMbbbV1zzEfg7rihV9z61CU7NW5mb9w0KiBu62PV7V2CexYDCIwx3js50InF7BTa2r8zNaFzbldcM79MUBO0wo9zjVvcYr5C7t3sg3cy+8wQWTvEJ8+24ssr9TYdWWbQdaWF6BWQ/9iYk1jYQ5PuZQV0EM60WAbWmPLyhASHMdgva/lOkXKRbTopV7e7cXuwv8tWFve1T4Dz7Cs8mYVX5h/3uzcZ7TeHggcKmMU9NTsjAdXM9gQJD4O+wIdryfAsoItTnlPawFmpYPPG7JtlJbgr9qttuu1aFO/LBm8VH6EajWMauI8Uiij733vuMCg2loMgHXbrjKN6wSuY110xS4Yd8uGchBLobNc2jEthzecwZyByGrN7JKrWHIxQVCB9ar7zyPFVdmu3DUF62C0UMQyRgFVHmQ+zcuT1eemmactrQ+fa//z2M/v3rN8jnK3IeLPccRdFBg85AXFwccnJ0pxOPIQudfPnlT8o5RecNi9VER0fh4otZ4LH2Pgiro86fv0y1CQvy8Jy5++7H1f/pFKvJ6cV5Bgw4Tf2f1ZwZjfHRR9+ov3/44R2MH39lvUJGDbiMhx560W8ajxdzvO0PFNW/++4XVRHYqJxsuCgZwj5kyDH1DuM0Ur3QYfrLz3/7fZaQEI2oqDB1y4uIDMXyZRsxYsQA9OrdHh07tYbFouGG65/CgAE98MijNyIpKQ7myv7cgRYgbAjh0eNx44ILblGuQZ5PkybdWKcQdwprdPBxsIOV3ylA8hqY8sCtKhdtIHqYtamamM7jT9cvv//jj3pePP4/PT1DuZN532IRJ4ra/fr1UI5tunw5mMACUryn8djW5x5BoZPXCwVMwvseXd9vvPGYyqEOb2nL2kRUq9rGHj1GY+rUx1W+xurt6lFtw+1nf4di6IFhhLIbqU/M+PDDb/DIw1WFn3h/+Pvv6YfNoFFNzJmzSOWzbQo5Hg9nDgvh8dTujSM8freqSbbLoeSICrVOGtka0SEhcBQ7YDUFw5VdjpbLirCnbQjK+MCtwrwsiNrjQnnHMEy5aAwGD++CoHD9YWnA6C5IahWDVyZ+g8hsD7Jb6+JaeYQFFR49J2FokRtB5ZpysxlhgPzVjyzWUBh+GNxwTSakt7QhLseFuD1u9UKlq25T12AlDBiiY0JqHLLW71H/Z9XQLnccixn/pum/QZlVldHqhfdB8eDo3QVRZhRFm9DcakKu1YzkIDtsGytDqE9Jhnlpofeh86Vnv0eLlnEYP24ohp/QG/aAAujp2/fg2ce+Qd/B7bBm1VZ4nG7kbs5FWGI4TJ6KWmMLPK1CoNlM6GiLVqLjCdcOhObRsHTRZmT+sBmdz+mG5gNS8PzYU+s1qn7T9Euw6pcN+GOqXnWSsLo1Oxn1Wc706TMw7Z0vEBsbjptvORe23cEYec1AdK/MgTgkWa+gaanMgVpfrDYrIiJDUFTof47Y2kQgbGxLOCqcqnNiP52V1XRBqKKgFFr/aFx9+xi8dfV0zP9oKT6bW128bAzogr7h2tdQMU8XHR0DY5CvGeLO3s9jsxtY+/6/6HheN5xyWh8lPH6ftgk7v9qI4l+zoY3zz6VVGyzewpyILSpc6HmCHl7/90+r8dXUuUiIjVbFRkZd0hezPl8C9IkG2obBvbxCiVrFESYUh9fPvVEYbUFwiUcvJmMBdiVZVA5XEuqq332OomNRjFUXHWuA050sQMUBi7x95CncHyo7wgVxFmQmWBHrtKFNpoYYpwf5EaZat6ups71nGFKXFKPtL7nIbxuCHItWJSwLftgrPIjNdMFdeazNLo86n53LcqHlBIjngh+XXXa2coVRIOMDM/PwMdyQhcRGjTpO5RQkFHuuu+4i5XakqEQoULJyK8OUKRYxrxhFTL4oQrKYCcOEZ86cg3Xr0jBkSH9v5AGFmzPOGH1Qwi0bmj///BxTp36shIyff57rnX7//beqsOQRIy5QfzPUkvmSOQ/zILJS6JVXnqtcW/Ut2OPLwQzZZZg13ZRr126Gx+PCr7/+jddf/1A5Du+88xoVWjpixBBVBIdhn3T6UYyh6zEwbJti7F13Pa7EG1bvpcuMziyeXyNGDEJeXoFfYQwDigAM6WY/5667HsPEiderfJsUvSnu9unTTeWw4/lWH3hseA4PHXqWn8jJ7YiJiaqXOHvuuTcqQeiBB/6jvstrYd+5CesO84kGCo+9+7bHnXedh+bNdbFOc+udWKtN/x31aBVYtuJ99Oh6EU4YPgHL//0MAYXDGw2G9jNUnlBspOhc11hEhj3zfvTKK4+oAjDsh3F5V155F77+5g2VQ3Zf0M04ceJ1yklLFy2h4/HCC29GfHysKjKii9wblVOV55xxnfF846s+MA/pM89MVQIp72nM8cicquwL07lc03lfG59+qpsZahIdCa8TuhD5OlgYAuO69bPhcnowfPgFOPPMa/HMM/dWHpPDDzrWeYw5yMGw5SlTblP3KqE6HFxhxXSKjExzwdQf/fv3hM1mUZEQgnBUOB5X7ZyGbs1HqWlOj1704ZeFf2L298sxf3EacrdXFkgB8PvSR5EcqlfFq4rF0h/Ol6X9jiee+BoFOcXILyxT0kLhTj1kz9o5Cq51BXDF2VA6Ih4ZizLRcZv+/Q1tAjrIh7JlAwvR1GXdlU4QOkBTdrtQHGZCTiwrtZphcQMxqZHQchxwRlrhrgyJLjFC5Qxnlq9jM0SfxxZs9fvIVelc8TDElNBxahSyCQw3rKyCarihImODUVy5Ts+Wyjx6BiYgJs8NzWZGSbgZzlALYttFwlLuQdvcIOSWF6J7uxbYsXgHrGOao2JDAbKLS+BIDUNZhRvNgmzAvwXoHp8At9ODsaP7YtiIrmibrHden3r+c8z6dilKzG5YKOxpGop3664izWqC1j0SaRWVTirD7UnHZqVzx1TuQmKGCxEmC8z5Ttz6zJkqnHhEu2GIjAxTTkIT6tYLZIh0iVMP2Rp07F1wlFYVXWjRJg4vfHItuscO36fj0XAvEOaW4oNeQ8LQcBbE2bUrG/c/8zz27C7AhmX6tVh4QizcMTZk5+jnwRmn9kJkUBBcZS6UpxehaEs+POsKEBMfjv89eydiYiJgNScecMh1fR2PRji621OgEqifdf0UONP1476xk91fqIq0+7u+DAdghA1jT+8JR3YZ8qatw9mPjEGrlBhsXJKOWR8uRmSzCCyyF8EdbkXh+vyq5QReXwHhoyxK1GqnC5akEISarCjLLIEjVz8HeT6q4jQ7ymCqvKVtSK10oNV2m/d1q9WW0sFbcKSGeU21pHYw5g23IT7Xjdgt5djQszLpuVFtOLCac2C1b9/lGxjOYlXIBv7OOOMaDHCgm8Js6LC6HFu6BMNZ7kKYNQjNiswwZ+j3k8x4MwqifO7dxv4a74FFX+oSXh04C/fRcGDWVn26Jue8ETZe6e6kwMzBr9AiD4LKPaiItCCkwI2g0qplZiRbURhlrlqP77Ey2qq257uaCrDU5uasyS1rHH/jOBnH1Ndp61s8pr7uy8B5fa9F4xw0vm/sv92M0GIPWlSmK/DlkutPQFx8FG645KmjfhR6b8VlWIXagGIPQ16Zz4xiE8MWyYcfvlBj9VV1KJwu/O9/76qCKcyTRgGzosKp8g/ywY4hthQg//nnB4SHh6mCZsxX9scfn6m8a4cbFBcoQj777JtYu/ZXNY1hnQyVJcyByIrPTTEXF4VRFj456aRhyilF9yIfE6ZO/QwVFWVqm3nsuf0nnTQUDz30kspbZ+z3e+99oYoefP31TFVAiI4u5sgjfDhlNWfmBDXgd/igyvBahoLyPNqbkMrlU8RmnlH2X1jFl+1aX9FxX5WzV6yY6c37VtcK1cxx+u67z+JgwGtm6tRPsHLVv/j7rxWqGvIVV52Mm26hw1S/91lNehtQyGbo7/LlqzDv7+XYvj0Dd9xxFY4bfkyDpK85EMcjj/fzL7yF9979Uv3t7/TbNxUVFap4C3MzMnch3Y+vvfYB1q/fjOuvvxgjRw6uwXVXu6DJwZCrrrpbDYbw/GPYNJ2ChMIgCzpRhDTSAHz77VvKtXhwoeNR7ycFPqKbTGYVnt6v7+mq+A7DqxuD7t1HoU+frt6q9T/++Aduv/1B7+cHM/VDQ8LfJlZvZsEtVjRPTIxX5w/zXhqceupJuP/+W+pc7OdooLi4FOPHX+HN52vA6uqnnnoiLrvslibZpxLHY+NzRAmP2Xk/IT5ad2vVFK5QXLYWmRn5SEqOVT8y7sqKwQbBlnbqnbnvNE1/iM0tX4XycicW5aZj/eLtWPz3JuTvKkTapkzsaGtHhzW6SLGhdXUrf70qmu7Pd3wf9gJdO0b+x/o8xCEg5E0lXzX5hU+HN9NdcMVGKKQhIvChuvIhOamFPurqrHzwyzWq7xqiCu3GRkXuAGI7Rav3hDhdpMjOKdMrUBMjn6QPrXe5ERTwPBnTPBJnnDEESSlhiLJHo0+f9hg9UnfP0dF69i3DsWjWWuxJL0BKm3j8NVMPpWWemNjYCMz+9UM1Ilni1HMVlrsdiLZXjeDxktmQvRLPP/wt5s5eraaldQ1WhXZCSjxoualSuGoWBFe3CES2i0bF1DSExoVi/PPjcN8xY/1Cu+uK0RH5d/OvOPfkp7zT/1nxmu4iMbfbZyfr6WdexVtvTlf/nzNnugpvOli4tUK8/953eOLxtxGXEIGk1rHIzSxEeItIJLePR0y5BRtX7UJWVgFGntgPPXulYtDAgWjePAEWU93dBgciPPK+YFQ7zCzTK1YvzkrHhmXpeGfqH3D6nHNpPUPgMQRzI+TVm8dUv9AS20Wp/1/UszuWzVyHovRCDL7yGLgrXJj/+XJVEGhlSIWqIl2Rp58nzdaXobBFMEribYiM0h8KyioFTKfhLDauAQo6oRYEl3qU+BRa6EZFpBXZ7YKBrKr7WWqaAxYPsKGjveYcjNUaYi8FWwLDfmvKcWgIZIbAZIhAIVaE73Gg+aYKbOgbqq+jcr+98xhhxL4/RUaoeWAFcF/Ry5gncLsCBK2ochOSdjmxoWuQEoYpPAaZrcitqMzLGrju2tphb6k0qj3nBEww+YQhewKE0sCwdx+S8jREFdQsVLLgkBEC77ICO1vaEJPjVrl8a8LNSGOrXqE8j8Kkn+jrqV7VujYBMjAEuqbmCgy59z1n6poTmd81xOnAddcUhl3b8fEVuCsF0RbdYmBdXYyeQTE458YTcMnQ/zbJTnJTFB59ocOroKBYuRTr4xDjQwtzBVJw+uijr5XLbObMP1WRlldeeQ8//PAbvvnmzWp5JYWDz/TpP6rQeV+YU7F79y4YMWKgirCgk2rmzD+UAE3oDKMgzdBruoYYgs9jy34JnTHvvfccBg7ss9f10vnIMGVj3azSTeck19ely0jvfI8/PlEVMLrqqrtUaDNFT4bBHqio17Xrid6/Weho0KB+dfrupk3bMHasnu6GQhhdoAeTPTl7MGTwOer/w4f3x46dmYiJjkC//l1gtYZg2dLVWL58HYYNO0a5tuiy7d27W4OHwNZXeGTahW+/+xkvPP+OdxqF6WuuoRt439tGcZnn1w8//Kryeo45eRjenPqZKqDCwi6+RTX++GM+vvpqFp5//r46O6YpoPz112L14gD9Y4/d7edYpSB/wQU3Y86czw+qk7D2UOuqv3Xh8Qw89PCtOPfc8XvN634wMK6XWbM+8LrbmQP2cMjxyFzDF110a42fcfCDA2MGTz99jxowuu++mgcTmCaEz1BsAzp26zpQcaRC4XbKlOfx+OOT0KfPiU1beDytkUKtv5VQ66NKeHS40yr/0n+c9iU8ctTwmuvvxpa0DJXAP6V9PNoc31Y937zw5Vy0X+eoEh35o74vgVDfkKYtPGoaWmRp2NHStk/h0VLhQczmUuQl2uAOtVQJjymhsKWXI3RhlcO0MNGGjLbBDS486isMQeLWckQVeWAq8yC1fyv8d/K5aNYqHCnh+gjwHyuXqLyOi1dsxh9fLMdxZ/TEsOFdVWcsqtyO7Vuz4SozY+DgroiO0K31FB5378qFNcSClvGdfJpIQ3rJevXd625+G1vnb1eOy/JQ/RUXHoTgVUXwRFigRdlgLfVAK3WjRY9kDL558AELjxml/2Dj+l2YcP7/1N8DBnbGW9Pu3KvwSKfB44+/okb1yMcfP41+/RrW7ViT8Eh2l65U71sLc1V15d+WpiEzbQ9O6tEJw47tqqpVWkwRfrkcG0N4/GPxl7j24qqcNWEjU+DeU47s3GIUtQhGcbkTMET0GoRHioCJFSaYi1xI7ZiM+EEpCEsOx7p3/0VIdDDCT0hBSLNwfDlDT4pvCI8x6RVI2O1Ul+qeE2LVtVzMRIrM2+crPGoabCYzEnI9yGxlh9vIcWgIdywQU4nZraH9Jl0kLQk1ISPerIfhNoLw2HGh7izc2CdUd4seYuEx1GNGi636cdvS0gJ7SDCCTFa9uIzv/jdB4THcYYLVBZRGW+AIYk5hVN9nLeCezzQG5R602aTvc26yDVYW8SnXq4fbfQZqeG7sbmaFx1h3ExQeLS4NNqemhPQyO1RRpAMRHrm8Zt1i1Dl1urk5yotceOvZz5tkJ7mpC4/7w48//qpccswHyErGV111ngrTZrjj229/pkK3fR9ojwTo4KRYUpewPeZ9ZA5IhnL6ikV0lt588/3qt5ywYMTPP3+oQqEPBnQVnn76BFUwg27U7757F506VbmrKM7QvcaHbeZopAOSoct0rLLa7ubN21UePRaf8BVw+GDPz+lk9d0/9qv499y5i3D11RNVpW+KlXRdRkVFqJBqwqrVa9akKbGbqVqY564hXF+BAiedqntzpFIovfvux5RgTni8Pvnk5YOe487I+ejRSrw3uczMLPyzZC00jx19+nZFi5QWAdvR8NtUF+GRYuPll9+hqrgTOgXHjTsBq1evx8gTB+OU8aMqt9NU68DGrf9n7yrgpKre6Jnu7WYbWLq7WwVEVErAAgVbEQMDCwsDRcECAwwU9W8ggkEIKEh3w8IW2zm70zPv/7s1xYKogIjz+cOZnXnz3n1133fPPd859zxFz0NhYTFGjBiCK64YgDfe+IhqM06ePB6XXdYbcnkggEBYkAMHjqPvX375UbRs2YSWgwbLGZBrjlyLjz/+Cq6/fgTVZj3d+bviipsos5K0h1x3vXr5zKTOJ/A4+LKbcexYPr799i00adrovAOP5Lg1bdqfvidMQGKWdLbMhs51kD7p88+/Q/fuHek9eybu4aLfWrDgC7zxxoe47rqr6IQKAcPJP9JXiiCmWDNmTKV9+IUaBEwlDF4CtpNJpb/7rCXrM5vrKJN9z55DmDbtOSxfvuKCzKlCwOM/HxcV8FhZtQ0R4fF/aKwhccDRJTFTBxnYgFApZ4LUbk8ViuqO4NlHP8eSvYdgzLdRnTO7SYkKLdOGijADMeVuHMpSeV1rT1mC18DgG5QL92PxcIvVBg7CRYklKUcVpyacz6IIttWpStT8o74B5B8FqQZ0SsgoYA+4Wr0MFVFy2LRy3+DN6HvAyV0SGu1g+omyCBXM8WrqKm3It58ELJY3N6A8VuXbD8F+5ANTVRI7RkmxDHAMj2QA5/HcKtQIoEKYJ4hI0NMBdXtDOKp+ZaURH3/6GFq0zERRgRwZGUknPZC9ZbRSLX4vWk/fN4pgs5dxWjZr7pSYi/fUqW9QQLLUZoHL6qSMxagG4Sg9Ug6jXInJ91+KYX3604fwL3s34ci+Qnz32x4c33OCmmNIZraPvSZ2hlwhw92XD0KjxklQyZP+FrgmzG/MjkPo3Po+dtySorBi1Xx2LqCFnOsziiT1u+++xwP3s1KiTdvegl5nhEouSpPOly6cFABIEkMdX9nPuWvD6YDHOtcuzHj6U3zz2e8nfXe4mYY5VgvQi9yjXtMTKQCATG0SAeWWKozv0wH9h7VB09QkWF0OlJfWYMKNbyHj3nb47lsGwApN97gEds1r69zQLg8sV7B1jYArTY9KDrpb65yIyLcjLts3WXI8RQmHWuaVOPCWefsBhUYrkHTCZzZCtBqp3mN9YKI3vz0FECbARX+J1uBlg5N2vRJaqwep2Ww/bDoZ8lNVDDwSEcX7N7UCBn4860qs9YNz/sYjpyob9u6bH2gpA1JyndBZJRS0MELjVjDgMXg/zlYElx6T4yv2U2xL9Gv19dWnAjKDy739S85FcDC8Qb4ThhoPsrM0TI+YHEtq1iVB55LBVOVGRIUb+elqWPR8JfbTmMCcTs4jeOJL/CnuHfE96feDZTX4OuVOULMct+TxGbfZ3cjMc3uZnQ4lcDxZEQgyB5+6gGtagkamgM7qgUGSIw5qqA1qaGRyOG1OyD1Au55ZmPvMJxdkknyxAY/Ll/+CDz74nJYuCiCClPQS1hMpVSUlj7fddh2mTPGZhVwMIYwliPHO2LHDqbPxqeLWWx/xOjSPHj0UDRumUwYhYer4x8iRQzB9+l1nXd+RAHAff/w1LTUkJhpPPXUvNdXIzS3+28ACOf8vvfQOUlOTqJ4eASmJfh4BEAmjjIA/EyaMogARGegT7TtSBkm0IwmzUJS7EnMb4gJM9MUuv9wHFp6NIE7URKeSxMqVn1ItwNO54JL49tv51Czon4tg7ZM/H05PHoqsufR9kp7lwqczFjwd0EQkFcaNY/qN/jFv3sw/ZSC1c+c+vPbaB7Q/ICWcDBSUMGnSQ7jllnHo2LF+aQcSY8bcQU1rRBBzn3feef4kwKRNm8u8f99xx/W0vPp0QUDNqVNneN3q61vv2Y3ABxwBJAlYeuMND1CQh8Qnn7zGjalk5/WaEexo4kROzGX+DcDj3wmiZ0tMnu67bzJn6gYCmmRSjZiIkev0wAHWh/yTQa5vAi6SCgMyASTi6adfp8xhUmlAYtOmJXRy50yCjHfJvpJ7c8cOwq7eTycIyO/JOEuhkNNJoW++WXZhA49XtvpnGI/f7L4gj8v5jIsKePy7CbJglLk85Rh6x6OQ3BJ+19VCXemEfo+ZljcSIpJ3uxEKyiQ6SbNL9OMJDPwxxvgSw7ojNQirdiPKBkgaOS57chDqTpihTTBQA5Iff2PgREmFDY0zGRDapDEDiKpsDHRY+c2eQKZQqc0HOgQPCus7vX9wxrUOUPZgeK2EaqMMxbEKHzCqlsNQ40a4UQ1XlArJJyR4nB4MHdkBX23cA/euKkguDy0xdmXo6UC3vJoNsImuIt18mf2kga0+zRjYfCGZt7/y5Aby49v+6iawrSiEa1clvlrzCJrGd6GJEmGqEle6jIzTa/4QLUL+LuBzl8SEce+YOx/7fzqMvE4a5J6og9IuQV1uh0Mnh8wlIT7HDlO4FuqscLwz41r6m7bRmVDJ02kbDh3dhh+WbUJYmB43TrwMchnbR4Us6qy4CtrdB6lOVqd2d3k/m7XkVlzSuDM8kgtFhRW0DIA8CF55+Rt88N4SuszBg+SB+N8xoagPeBQA9JHq9bi884yA5QvT1TDHEMZvENBCQBnB1uIMYOIALfQqs1/bhjfn3QxTuA6togah0MIGjyPvfhP6NBO21DBH0Koydt01bMSAZ6NCDSt3yxZls6Y2MXBk10DRMgKqtlHYf7gMMreElJ/ZOrTd41ByuBJFzQ1ABQewRNuEuzMBXvyAwchqiTLn7GQiIdh1mCwnPjuVBt8pGIWnBdzIZAuftCBMu/RDfNJHKUNZAxU85CuVAhKRUFXJYTSx415jcVJw0uF2s+367xMJcusQPUv/CGb+CckIUl4r+keFDAaFGhqFChVOi58u5F+YqPkzIfNnDorjXI8GY3BIpwD9AtbNvlPKZAxgq5O85dbFCUpUa4hJUNDKSX8uScg65MShZhrfcTid5qf/vpyiDafUEvUHgRP1dIKqb1gMzEcqobS46bNPrleh8lgltP0SoWkWgYoVuVCWOCE53LC7PSjqEQGrYL37g4tBx8aUFQFFnQvJVTK4jpnRp3NTtGidgi4dmqBV8860/FOswG53obCwHI0yB/znk8FzDTwS7bRHH32JauARJ9onnniFAkr5+Wyij547kwHLli38U86/JIVdu3YjZZ4R45PvvnuPXgqEiUeALfL8+6edVgkrhpjlkH+EBRasf1ZeXokPP/wK7du3oIxGMqAnJcvEqOfNN4l+3VEMGdKfatida81Lsv1hwybis8/mBhhonA1GU2lpBa655k6q60eczwm4SABFcg5JWT1hE61evR4JCXF4990XTjpvxBGbgFrLlhEA85FzZqozdOiNVCORhP9xIOXkpE2kJJO0pXfv0fTzHTuWn1ODn/MRZJJakpzeSeE/itNdD4Q5SgBsEQRMnjr1Zt73+sfp7ksJCxf+j5ZKX3st0yUXQcDoOXMWYv78maf8dbt2g73mhQLEJxMejRtn4J57JlA9RxLPPPM6Pvroa2rytGbNRspaPVMQhlyLBBy/4QafOdHZya39GY++z+pj3d5151PUjZkEKfNv0CAeSqWSHjcCALF/7G+qY5mWyPcvMPEQlT9/tf2s1DrlohpbEKY3uWaIERZh4pP+izDzf/hhIX22nGqSaezYK6jJ1PkOch0sXvwdZQeTcQ9hc5I+izARFy2ag2+++ZHq2RYUFNHJH3JfkufKmR6Lb775CZ99tgTR0ZGUHUwkHIicg78DOJmQqa2tRVRUiwsypwoBj/98XFSu1mczEjskYcvcjUiyumhJY52G6fjJIWODZdG3CubeH4VHgjHbiqQDHCTg8fuTa2Ap8jH5lASwa/LPCtgSRqdNq0AxyW/rGUfqa90wHmdtJv9Xx+iw/tvd8JRXQ9E6HJYGGgY4nG0WkX9IEuy/lUCqtOOLlQ/BYDz7Sd/69zaz8XLHODpwdmllcEXwW0YpIT9Liw4tEmH5qQCP3riALtswNQlvvjmTPuyzspLpv3MZRJfy2reuwuf3LUVSahRm3/cV3tf8gL17jtPvB13SAX37tfWCjlu3Mje8ULCob94lqsjJgMc/EQR8d1bakXOkGC3aB5Z9uWodUJAy21MoBUAtQ02iGmGFDgo6liWpoD5UjcgbsmDeWgLLJ9nQp2hgSdRAO7EhbO8fhW19CZT+hih/FDIZKiNkAAEd/6EggP2hNnoonR6kHbQhIYeXrdcT9RUPWvRyVMcoYY5QXFTJrUySEF8m0ecKKX22aJnTd8AyHglRVR5oHBI8MuLEDbq82inBEGgeT8NskqMiRgG7Tg5Y6u+H9eLz8+zqrTG7EH/ICvSOQca4FujRJJWa5pyoqsVXk76G5ecC2HeUAw31MLSLhyuvFpa95b6ybX7PEraiwgUoPRLVr3SoQRmtkZurIbe5oeiVSEHMx8aPoctHaIxQKwLv6zMtswrF3w/C3COssH79rvGWpBGmDnGQJWVaUVF/vgKAsI5Gjbot4LNRo273mriI2LDhGwpq/h3n6L8TZAKQsKnIv/qCDGiJU7QIMqg9cOAoHUgS/cKZMx+izr/nOgirkpSdEgbTn3XtPZMgoCIBmsnELAkC4PlvhwAnhMlIjF4uu+wGZGQkU/YnYQ8RwI9o65GB8pkOlv9qLF36AXViJ+ZHpJyalOkKmRpRvnv//c/S9wRk+LeDjmc7/EFHEh988AXVv4yO/nOyAIRV1bhxJmX4+QM9ZCI5MvLUgAYB5B599C460UGCaMeS8v1HH72TTnqQ8m1y3T300G2YPv1uCjy+//7nVKeWTAycKfBI7s0OHVrinwry/Jo3/znqKv3447Ooa/afCTLBM3LUEFx37ZWIivIZPl0M8fnnS+lEFDEu6tev20mu4bRS7ZffsWjRt1Tyg1wX5J/QmiWvwa7yhA07atTQU05kid+QZc5nkPvj+effpCxy0ocSoy0ikUGCSB1s2LCNTib17t0FDzwwmTIW58//FJ07t/UeCwIYkvu2rKwS5eUVFGgk35O/iQ7zTz+tw5Ah/agpKXlmnyrIM/ZMdVX/0SBDofM9HLrwvOT+kQgxHuuJn/O/xpbiUnozfvbBGthXFMJtUMCerIWl1omKRJWv5JKwg4JL+4Sjp8S131RKxBy3QVvrQXWsCiUZGrSKCYdjUxmMkhKN2jfA6Jt648W7F8MMF2RKOSSjElf2aQ2HzQmTLIxSpuMaG9GmcyaWvLcB42/oh8+qma7EK4vWwFNoCWScBIvw/5G5hH+IAR5hxQimkVgvL4UWbEuVUka1HqNitSjjpeAOroOnEk69PJyiDWS5oI5bxU01hCENpSSTOMH3y+/4qhuFQVPlRB9XOG5+eiiuaDgygEF4pozHU4VbqqavyzcswSfz1mClogKlAhwW+yDKTg1KCgo0ynNBVu1Ck96Z+OLtB+lXSjkr0XG6avH8swvx2ac/Y+36FxAVycBIpTz+b7MeSXgkdozyarfi2JFiNEtPwbBrX0T1ESYlIGL0+F544jHGjlTKzrU49j8bgr1MZBQY47E6iPHo8pYXtWoWWNbnNUHh9wEpkycl1xJh7gWz6vh10KJpDDx7qpHh1EJjUOOdFycjzMgezpNnvIEDa7KpKVX4wBQ4JDfc5TYozW64ahyIjTbhBKyQKp1AsY3qpWqTDfBUOtD/0pbY8csR1GRpoW4Xja0/HqX9i9IhQZaoY3p+vJy1rpQjUEL7sD4Wo3jwietX3G8218msteDkSuhZ0uXdpy+tFX0I2Y4oBfcvOyZfWVxouNOCw610DGizkjYgqP/yUKZkmAUIr3JTnT8Sh1vqIFn99tO/3acqvSWhUTDGo1KNCmfdqZni5yUkxFZKiKypf6O5SQpE1HgQVuv73kMIfkGkxOpwOQUa7XKJlbB7dTeDzr2/Zq9KRtmOdjWQk672sWVFUM3iUxwMKeh6oOXb8G2L/C7YoZwzLGOdCjSR6THw9u64c2Bv+lWUlukyuzxlOLD/OH5asw5KpRyffvorcmCHm8gJ2Dxw6OVQQYaobHady+I1UEfqYIzUw1pYS8FHso3Jdw1CRotEDEplZhZq+ekdSIl2XkZGlwtydv5i1Hgkjsfdul1J3xNTCDJoImVrf8awgTA2SEkb0QMkjI4VKxZBp9NgwoT76cDn6NFcrFnzOWXQEfYgcVYm4CbRBySDQ/JMsFqtFGggZcSrVq2ng0miUXghDJrIMSK3IGGSnE+2JmH6vf328/WCnGfDPIKwBL/99mdqPENKuE8Xs2e/T92KT+WQS0DZSZOmUWYRAf/OVZDSWsKaJUY2pAw7OP5IC/LiiGCZHAOOHik8JeNxwYIvqaa4CMIiJCY3Xn1Kj5MCGoLZLOSuyDuxDNnmunWbsWH9dqxfvw0vvfQolSoQAPmLL72NY9l5FNQnOrGEOUtYqgQsJvdwRkYKZQcT0JPcRwTEttrs6NunGzZu3E5/9+yzD8Jo1NOxXllZBe1DDEY+xmF7HLD/J094KurRYGTXQv26iyeXTfuHYB2yz4PXK+LUzESPW0Lz5oNoOTvRoKw/ZKisrMayZSvx5ZfLqV4qifnvEs1K4nr+V/o/yY8B+89OCm/Zshvjx7Myf3LfukWuDtC+Qi6X0ckV/yB9rD8JgUg5jBgxmF6zSUlxZ/xMuPfeGVi2bDX27VtxVp8jxMznVOsjoOKzz86hMhX1gaJEi/LVV9+lermvvfY+ZZMTrWEyAZSUFE/vk/ffJyZNh6nWI9HjJQxJctzIvUS0fMmkwbBhA8/YPIdIYISHN72wGY9X/0Ol1l+FSq1DwKNfiIeqy0P0AtnNW2WvwtuvLYdeo0HDRol4bN7XUDePwI5iVgIsN6ogET0/MvgSg7daNiCWSxIS851IbBiN+KGZKF10CFU5VchslYTs3Sdwycj2aNM4HVeP6o5wPTe2gYp2gGvWrUFVZRW0OjW0WiXUaiWWrd6IpYs3w05MLgD8tpM5G9+2chm+/GobIvMdsCVr4dIr4LRwYFSUYQow4kzKI0X4M2GEaYRYRuyrGHzS5yTvuHlZdgI3imnahiUnRcdL2WtJHaqEYYww6xCl3KLvFwCffxk7b4MmVgdDgQ139OiA4dd1Q9uYLgHGJH8XeBTx1Bcv4uf5v2N7ugRLXm3gMQnjiRIBZj0S4otcCK9wI6VdEpYtYg98lZwBXTe9/Dh+m78JtigV5A4Ppr80CimN49C/QQ8o5eeibIqVaZAB2e6jq5CQGImDOwvQrXtTRIedW0OZfybYRSNBlN4qApKn02k81jp34q7nP8T6T7bRv49maeAWs/UxWgrwNa1VQJNhQp7JjVp+X4lLXcWBtqysOEhODxL2OXD45yO4/5mrcPOoW/myTpo4vPbWm1i3ei+KiqvoPayQyxAVbYI2QguXTo6y7ApUKJyQmV2wEuZjpg76MgedrJCE9qvHL+/kkwDRXDtQtMnCwTQbmYzwTjgEsdsEGCUmFshkSXBuHXwvit+SZcXvgr8LNhMhL+LhLsxw1HIYy5xIOsAApMNN1Ax49Aczg0EvP5OZxgcddLXEyKk8SQWrRsYAN0dQn3GKsmTqaq1SMY1Hsa8CKCO/OZVMRRBwyo7jH0zoBOj7+44JKYlOKWS/zY+TM41FcYokIKXQDQ0/5aXRclSFy6GzSbCo6wEF/wgs9S9LDv5NsHmPv4amX39O9Hwz0sMhc3gQExkOt8VFdReVBhXyDhYjIjmMPgvjbSoUbiuEXeGBPFyNWrsDjmQdCuVu6CucSN5nxZWjuuK+R69CnC5QmP947ToUFVRiygMfwpBoxOriIvS/qhWK3tuL4dd0QXFuBdo3TofJpINWEYmrruoLucxE9WzJ/fX1N0vQp29HxESz+9ynH3v6CAGP5xd4JEE0C8ngn5TbEiBw48Yd1BWUDHZItQA5n+Q5Xh8j9Z13PqEafIR9Qp5xjzzyIh1gEvCHsDYIq6lHj44nGY6Q80x0BAk7Ta/XQqvV0oEVKaEjJZMkvv/+A9omMQglRhIE5Agu9bwYg5wHwh5dsuS9er8/G8AjKa2ePPkhejz/SJuRAMaElUOMSQiI7M9YImycdu2GoGPH1vT7m28egxtvZE7P5zKEvll1dQ0d4JNr7mJ0XhfgnyTZvYabwX3q6UqtCWtQMJvvuWcibr/9Ou+aCcC3Zu16fLpoKT7/gumOy2S+fE3cexLYhPqWzUdx/XUPUiOXd98lpdUyr1zOxo2b8c7bX+LosRzYrA447C5ExZgQEWlAfGIEjh0qRUZmEiorrJQN9vY7M/Drum3o268LGjXMPMW+OyBJrgBJHg8/DkLzUhwPVjRYf8ly/aXS4rNgwKM+YDMQ9BTHxQcs+S/L+r5WLQfTv6ZPvxPXXXd1Pclc8O/Yuf7ggy/xwsy36d8PPXwz+vbthLS05HrO+6mTDXE9iP32lW7Xv93Tr+/0Jfj1LUsAtlatLqHvhw8fhBdeeNh7rMixI5NQc+YsoH8TBuQTT0yh1wRhB55dgy4p4JqRydhYMRjQJc84MplBgL2q6ipUV5lRVV2JuNgoHDtWhMioCMTGRNOJNCK3QZ6FBBQkzy4iF0Am7chzj5j8EACRsHrr2w9yXMjviVv7s88+QMF78swkz0Gy76T/JKAicYx//PF7AuQQiKQBcVDv1q39nzoCIeDxFBECHmmEgMczDIeHiS4Pv+JBZB8uRlxyBE06knunYd+qwzAkh6F00wlUJqlRmsw66a7tUlDxzn5kDWiILhM7QrexGscPlmPc+EFo17Yn7Uj+3OySRKnQP634nrLnbHYLLh3cHjOf+ZJ+q9Yo4dEpkDa1PcpKqyA3qLDx6wP1M5Tqi9M9o4LL8YJZnuSFsxYRyYAQI2dF1gpn3voATg5UGPhvPHy91nJboKGOf7s8EtXJTKiTQZ6oQ79OWRg4riMuz+wOtTz1bwOPxC1w+/b9uOmOx9H7kT54d+UWWHPM9evcCeIbZGh4gLVZ2SICyjQDnHEqeNaXQzrEfnu0Rzga/sbYlMbRGVj12F0IUzO2z9lgPv53QjzYWWLqliqwd+8xbN2xk7rzmrQRGHH1SDqAlUHzB67WDnyzdTEeGvc+/VtzY0PITUpItS6kbrXR2VGDTgOny43qYfEoKGAlfCKhsVnsQJkd+l+qoDWpUV1ci+atUvHFFy9DDjZYd0sMcCcx8cbn0aRDAjr1bAwphtz/wIZD+XjrszVwE/MqB0t4TdwBuSYYoPfLZeXcmKpRKkuGSVtJ5BUykLyOaEkKVqAAlDxBEwnc4ENjUHmNXSqKLIHgJL9Hdfwedbg8cGfz+0HcysJ8SuSa/iCluN+FJq1chqw1VahIUqMsTQuIe91fmsF7f9XTz5D7p05CQqmbltuSIKXxxY208JD9qnYGTo74s9KJ+RUFHtUMeBTsdNF+ktwHS0QIdmgws5L8Rhwj0b/6OUsHHAfy4rdeQx0pmwYqIvyMfkTI/NoTfBzOhJEZ3M/6g8LiOgg2qxHLiGMWrUX7Pmk0Yb8lIgtfLPgNfXq2R3iEEZER0QgPN8LhrENebjE6dexOS0VLSyshk7lx44QRqLPlok+Pu2Gzses2PSOOgkrlZWa0at0Q734wDXKw63dt4Qa6nftf/BK2rWXI1bhhMcjR7tJMGH8oQ+dRbfDwmMsC2JH+DJm/GyHg8fwDj/6xYsWv1LGYDKrIdUAGOaT0jWhrEVZUsCbioEHjaUkcMXQglSAEyLr33ptp2SNxx/4rQRiSH3/8FX7/fTuGDu3vHaB2796BltgSDb+SknI6ULtYg4C4I0bcSrW/CPOFMGj83U7/LvBIDAiIvuOYMcPovzOJ7t2vpvqXpMyxS5f2VJvvhx9+wbRpM72mLtdeO4WyWYlrOClJ/6f1PP+tQQAoD6/2cXgKUFNjweJv18LtkRCu0qNbj6bIyujsBeBOBzz6O4QT5thzzz1IgRaiy0jKX8PCjSguKsW77z1DrzfwChQWSuqWfsP106DVabF5EzNVWrv2c8qK9mnxl8DhqcA3/9uAz5b8hn5j2kOZaIBKq0Q0VKgoNqNHg5Zo0iQFSplPN8oHGirqB+KozqUAHp1+DuLkMan3Mj4D1+Ef/q7jvjxVTkHLwAe4YEX6wCmVH/ArwF8xdvOcBtB049ZbnsXaNduwa8/nUKtOVTYtO+VY4/jxPDzxxKu0D6R7ppBj8RfPoVmzdMi5EaZM5k3wvOtj/5f7AY9icj6IzRngYO8OApy9iUjAvpK/xTHyZ8IGb1uwxJ98cjaef34aDAZ/1uo/S4SobwKUsHOJKQ8BDMlzLyLCRJ+xpjA9Nm/ehe7dOlB90tLScgpMEiMxsizRV5wx43W6jri4GCofQsBT8vs333yWmrX5x4EDR/Dooy9ToPWWW8ZTEPOttz5Gbm4BvSfPVV/5rwAeR/xDjMf/hRiPIY3HPxlDR3ZCVvMkyBK0sNXZ8fHH6xHRLAYKtQJOtQylmVrIrG7oa9yw7SyHIlaLzF7p9LfXTuyLKA1zNFbK/5q2FAE7BwzsSP8dyt6LLxf/RgEHAtgRVmRtlQ1HH98AmUaB8Dua4mKNmjA5khKMkIWpUHGiBjtWH6bA49kKojcV0yQGG17bAF2MB/XIqAWEWwnkZaqhitQgYWsVXHurgAgVZJlGSDLg+KBouJ0eFDfWIf6wFbWfH4PrITfOkJQTitNEdvYJvPLyYjRqGoeflm1Hi5YZGDXyzNkPMYnh6Du8Ddas3Av37kq4XB548iy44pFhaNU5A0aFChMvfx3Vjx+H8paTyzZlNS7YLQ70GNcOU8ddisjokzVaCRjusDtx+bDumDP3C3jcHnQbzRwZjTEGuGL4hXBq2cO/HpTFJ53MaP6HQlvNknoKOv7FIM7cR1J11HDHZPYg4bAVpjInaiOVKExSnqSReKFFnUGOOjaGuWDDY3ZSmZFtTZWY+c4NaJ3CQD+FjIFQHokB3Cp5sh8LhV3Aer0G6ze+garqckREGuHin6sVSij4IIbMxO/edQQb9+7HxhX74XJaEXZdI1i+P0y/t/1QgOTEWMQ3PHOjkVD8+4JoPb7wwkMYNKg3LXUkwAQpxyUMtvvuewbfffc+BSSJEQ1hSZLB1mWX9aUgI8mHfvyRleP+nWjYMJUyYAi7g+h7ZWVl4tChbK+uX9u2jEkUbLhyMQXRtXvxxYepNhpxQCXOp++9x6pqzkbI5QoMGNCTGoYcPnwMDz98xx+WI3700au0LPvNNz+k5YDLl69Gly5Ml2z16s/oYJy8duw4jBofXHJJbwwY0OOstfm/GjXVFnyx+Ff8tuEAlb3IOVyKjp0an/HvyX05Z86TeOaZuRSAmjVrPmUbt27dFF9/PQ+QubH4s6W49JKbMGfuYxg4MJD9TmL37kP0Xv/xp4XUWVypODlZNput6NajGeYv+BnfvrEOY2cxQFtv0kIfpkWTlHPnskxyOjK5faEEAR0/+5zpy/+VIJMMCxfOgtNTjl07D+OhB1/DyKsfot8tWz6flqpfyEHGbK+//iQu5CDXzHvvfUbLsUnZd/CzhICrAwf2OCU4PH78Vbj00j5U7/RUZc+kbyWTqcTRnZjiPP30/bS0WrhyE/By/vwXzsHehSIUZxYhxuNfZlsxKEqCDTN++wRHfjmGXWuPQNcuBrLN5WjQOhGVsXLoG0Wg2sko1x8NH450U/fT6H/82Zaw9Zrt+7Ho8A76/v2N2+A8WgPL/5gjX9aLvejr0rc3+Jgzp5IrOZ1rrXSKZf0dRUW5nixoPZxV5WUXefy+48yrhplsMKpSs+Ny4ABz7yVsMu96g51d+fp6DcxC2Tv7cMuMyxFdqaLl6S2yOiCrSbLXQfqvhN19GGWl1Rgx/hlsjLCz/RJlnP4lif5tMyihqXPDTTQBZYBbJQs8HsQkokZCTAEbiC9d8zjCwvWI17Fy8VD8cYiZTydnId8zdTZO5FdAF6fH9pWHkN6IlD3L0DgrGW/Mffm0jEexRhIVVYX47ddt0JusiI4Ow6ZNB7D2l73YtfM43lhwK26+Zg7qLo2FJ1yFQq6n2LZ1Ah0UaxcXYNr74zAwjYH9emWqd6Zz3BOP4ujaY1DK5Rg4sTO2bc+BJlyL/AbcJEMug7WWsf6O51bR1xrBEhZMOr8yZTFLp+faiWrOjhOXYmyEBrJDtVBsrKTXn8IpoSxdiwoC9JkdXrkCEg3iGPqlVClgtbIZ2iLOQDRxhqJgIdt4KbOtwhaoI0kigiVBWs561vJ70+70IJp/Jhal5eoesk15wPqdbsnrfO8RDE9RYu46DfOPt1MDOdJ2M5bB0Z6kHNjpcyMXrs1uznhU8lJr0beIvsm/5NzreC0uk6BOkDiaCxan0NgV/YII0S+Qz8UJCo76WOV/huH4RxFQYn0K/U5xHAjrVZLQtkEUYg46MPGugRgz+Pozdjo9k3B4jtN75qoJT0KhlGNrWSkcUSqUl9QF7HtGYhhU6yvorPz+Az+xZp+DudIQ4/GfZTzWF+T6IC7YDz/8IqZPvwsLFnxBWY5Eu4wwIoUj7bncPmFtCWDMX5dyz56f/zGTmvMZhElKWIRqtZqa9WRlNUSnTq3OyuD77rufwOTJ46gz6pnqLJISw8LCErRs2eSk73/8cQ3uvpuBDosXv3HG6w0FAnSvra799P37S1fhvWeWo/ngJtj6xW5Ex5ug0argsUtYuOh+pCV1OyOXc8JyJBp0FquZui0fzzmGNau3Yu3abbj7nrF4bfanuOWWMZgwcbTfw5A9d2fOnI/WrZtgyJDeAexCwnDbv/8I1dsk6+/dpwOuHjEQTz/1NhZ+woCyakcRfQ1ThflNjgl2YfC9K5iFTj+mmihvZnmOB3Uwmy3o3vlO+jdhmEXHRGDp0je96/XAHKARD/5bH5tRBw+X85Jx5qSYxPMxKH2MP8GYJBU99BPJEfAcFmXwtN5KpqITeUoV36ZYD2cUilyUTPoJVqXvONRfEi1JVtRZajBm9DQcPZKPJ56ajLHXkPJt//AxFoWrtcTb6WU+Cjarl+Wo8WMrKuo9J/56iz6WZXCIfbtwwN/ACBxoE/bhY4/NQteu7XHnnTecE2M70g++/fYn6NmzEwWShw0bQPtvEfv2HaaTAKTs+qefPj5nDP5/BeNxZOt/hvH45a4L8ricz7j4s6ezHGTQRKLKXoqjhwtxz6uLadmhyqCGsRbor0vC3V/ch8hIk5/BBbvxVfIGZ7WTJGWkJIzqLAxIYZqTaWEmePp7cO+St+iA85e5v6OWuN8KLUYyCA8eQIuyPq9rqNhZdz26b0FAmxiwkxCgnCg3FNs0qgLKR80E/OCDS7maLWPm7uBqXupHGJt0c+RVmFOIMkBbYLngxmUHkV5pxwuPfg2bSQG1G0hVLEOJxoLbbx+I5CZxGNN4CN/FUzu3Oam2p4+1o1akIikB0ERq0SBFA8mkxInsmkBAJNicwuZmTrJ0Y0EPTH7MKsLdiClgH7363nL0HtMOoxuymS+57J91NP83hLiHSOJ16GA+Vi3fRctCJtx5Nbpe1x6mGglrFu3A8Ks70aTHm/icZo0koiKSMOzyJGwsWYZn71+M8MZRMLWMQmxZJUoUVrz32d24a8p7aDGxHbZFsGulYVo8qneVIqtNQwzOaAWtQgx4ZDhmXosDe/JxYtsJjJ11BWUR/DpvI5wqGRJ6p+JoLgNOXU43iku4Szy/DwiAHXBPimtfrUAUN21S8O8EICgWralzQhajgrJbBPRWCdKeGmj0CkSEq+Emv5UkKJ0SJI2clqaTMEUaoDex9Wj4vafWqLztI1FYysA1G7nnhQA7l0LQR7I2NebsNBkX23fYHIhJYvdcGndNrLQyYDMjgunRlFrYevMrKlFVypN3N9umpY7di9UcMK3hx8cfN3NXsgRcGa9HQYoODZaVId0qQz4HV+01TkAcV9I3ETCB/FMqfaXoCX6lOV79yiCwU2CKvM8zxelgLgmSkQjW0Aww3RHl7qfQrwyesPH/fTBQWN/k0KmiPq3L4M94Gf1Nwztj30c70UOXjOmLH6Sus2eqlXgmQQZTG4p2YdXXO7CvuBTWjhEoKbABhbzcnoSWXfv2FC0GjmyLiBjDOQEcQ3Fhlvt+882PVHeRAI1kAEp0/h588NbzCiYRsNufjUfYNPfdN4kO2ojG5Lhxw/30tE7nZnU24lQzxec21qzZSPW/CIOQmPC89toH9Nlw5ZWXYuDAnn/ZyZkwsggzce3ajWd8ToXZTXR0/fkbYQHdd99kzJo1D9dffy927frxL7Xtvxykj/VIHnrPzZn2Df0sKjMK17x1JVKUWuxadxSyMjfi4o1nkFOxIPcQAUEcnmP4bskGLF+2Htdd3x+rf9mElDQjVq1eiClTnoPd7sStt43nv5LTfmDd2s24+aZrTnr+WO3leOSRF/DUC6MQmWLEZ++vxZMzZuO6m/pRsIxEuJoZOypk4h71PX8FMCbKfIUWnwAFGWAWrDvlgdGowbsL7kN5WQ2efGwhUlIiUWcth1bL8qSqylqYwgyQcfc3cYwEeAlY4fDwcQ5fJlgH0dc2NdwSy4VqHAJ4ZL9RKdg+Ot1sXW7JDY1CRZtcwXMrUUKr4KCdSs72VauooMXW7DNtQPm4KAkX+6yQx0KnU2DJdy9j2OVT8dQT8zBmDBtHiWPpKw33QIIVHsnsBVHFeErkGgJAlFNhKvE8DwR46+/jgjUthXmP4gLvX4X2pAPvvLMIq1dvwFNPTaVs8nMRxHCNSIR8+OFs+ryqL4jJ2tSpN6OuzlKvgVgoQnE+IpTN/8k4dCgfhw/lo7C0CK+9uAQRfZOhj9FDrlJg9is3Iy0jDkbV+WUHBIdcIYd1RCI1qYheUYqkXCcvPwRqL8LSXodegUNdTYyFpZFTVZCY5Ag4S9xY/9UuWopdfZUVVwzvgwaJpwYe64vaWgs16pHZ5ZDO4mmtjpAjvMqDlR9uRmqLBEiZUkib6C9EalocJk8bjHkvLMfiR5fDXMZZU0Rg+wkmbv5Xory4BgMf6I0dPxxASUEVDm7PQ4+RfeHkABhJzqW1ZTi2phKOChve/3J6vevZvvEosnplUGaXPlKHS6b1xfFqDl6fwyCgojNRSxlsHhVg2lwN0z7fsfEPV48oIL7+ROXfFqT0moTUzAgIl+8LIORuCZJHumBLwJV2D6JOOLDjzc3IGtkcD08ciTDNuZsE+W3ZHthan37GV3W4DscshaguqwVOb4Abin9xEFfrlSvXU5D7zjsfo6BUmzbNsX37HjzwwC247LI+F8SzkTD0iCnKe+8tRrduV2H06KHURZS0218L8WKJYCfpfv16wuNx4euvf6RGDcTY5aqrLqXOr3/2/BDdTsKKOZsxaFBPCjwSkxxiXtS9e8d/WOvt3xnkXN7/+mi8fPfn+GnmL2g1rBk+/Y4xIZ98ZtxfXm/O8SIMu6ILoqKN0GrU+HzxGvToNhCJibE0zyZBSlA//fQ71JrrMGHCqHo1Wwn7mEw0ZzVtgAqbGeMn9YXxdt15OS6du7CKlthYEybe8Ao6trux3mW792iOOW9NvqBKsf9OuF1uLPjwEVxIQSaniTt3TMxfr2o7l0EYqF99tRwfffQVBg/uR2U6/I1bznZ8//1qWop9KtBRmKW9+up7OHDgKDVU69SJyT2FIhTnM0LA4x8EmakjUVxbgJvGzEFOdkngATxsxovPTUfXrm1Poo+fryAzVo3D+9L3DQx76Gvvbs3pQHfr9ytRkaJBfLEDcoeEw801kARLj7MNvWV2glX1R2wZf3MK8Vsy4PcyJwNNKQQTUvxJGD46bmQhDDHqOPOoVszq8XU55Mw5nISnnLfPGlQCKQ43WQfFGmSocNWg0G7Bt3oH5OEScn5ZilkLP0dacjRS2zVAUqQJ6ZGRUKkVaJHeBG3aNoRazrQ4nZ4C6hA3a+lcrPp4MypTFMgvrAEK/VicosRS7LNgScn93otnjGCFcqYaYV8VN1bBXOlEmlqLD6Z9hyWvrEGXvk0w84mJ/NQIl/OLECn+m1FnqcC6dVvx0Udf4pLLOlLQkUTrrhkYNKYDaovr4Kl04t575+HzxU3oZUL0pdgFc+oBkpjxbWyKp6W4uzcdx8FNOXjj89sQFWuCC25079kEzvVl6O7RIapZM9x59whadhcfm3GSk53Oo8bCt1ZRjaR7Jg2Cgg/OxOxzD0KnJWVNu3bTUmf6XTEbjNl4ma9DXG88CGuYuGHTZfm1p9NIAWxJNwffdFoFZOT+bBEOffckuHNqoYrRQh6hgcVspf2D6ZgTVSvyEJUSD2Mn5rDu5IxlO59RFwYhURyc3Lwlz2d4HM1mzTNSGbMgMz0hYB+Jv7pGwe6VKK0u4LXcyoDBajubpY8OMyI+IhCMkvNjZnextlTzGf2qMjMk7j5urWPHXKNl94rsjijKBY/kx7CI3I+cmSmLJ9tW0fITHWTe0u4A8y1haFWfmzdZB3cRd5D+0isfIQUyHcXfCjlll2YeccIco0RhUz1wwhLYdwT/xt9Z2xv1GNAEf6U4BXOyPnYkX4SU/0dWuBFe5YCnhQlr336GDuo0CqIJdPbBHpdUipX7suFQAMUHKut32A5jHae+SsITD09Au/ZZ55j19c+DWv/V+OSTbzBjxmsBnxFtKgLwEWdW/zKxCyH0eh3VfiRsxxMnSjBq1O0YM+ZyzJhx3znc6oVxfZJcrVGjDEybditlf/7222Y6qH7yyVcxaFAvxMVF0/JBcs7Ia+/enU86f8eO5VENSSJv8NprT5zV9mVkpODXX/+HxYu/w513Pk4/I6Do3LkzTsmUDIUvvv1lIVb9zNzdndwYRK1Xoe3AJkholUAn4D/9dA3CknS4tHsCWFHD6XMqtoSbVvIU5FeiR59GuOfOeZj50mR06tyUlif36dsar81ejOKSEuzdcwTvzHuOPgJTUhLob70VLqT82OPBiy+8hd27D+On3IM4Ws3ypVone2a35Od5WDqrINLwqiOaR3OGo2AViiTGx0wUZoVOuHhZsFouypK5nh7/vEOnRti5700cyc5DWWkN2rbPhFaloxPS23cewoRxr6FD6ynYvOdVyiIVR8rFGY8uD1uPUs5yFx1nVwv5LEkyw+lmE8WFFia/I/JHkRO5eP5DwqBi7TMotQHL1LpsAX9XO+rg4HmdmCzQErYkzdlYnubm7TWpnFDIWa629Adm5kQYjd7jyZmZtC1SCSRUw+VReKvKlDJW/eJGlZ+5Dhki+bQJfUY5wYYx/mXxgUY27PhIuOeep+gEw86dy716h0KGyTcGP5O+sz5X1TP9bf2AI2HtL1z4Jfr27YaPPpp9ll2z64916zZh5sxpf8iKJHqps2c/EZqUkf0Dj9YL41H+j0cIeAwI1vE4PDmQJNZh17lY53/jyNnIzylH/wFtMfm2ocjMaEpvXNG5/vMhHiJMAPrp7j3pq3pbP9TV2nBF72fo3zq3HBZloEYi1fXyBxP99dtOVdEnwDUx2CUDdzGQDgYlOfBYRbTheFiDQc4g3TqhL1cepqZuuzKHB2Y+4Ad/9YKTosSbbosnQgr+z+Ghj7ZcjwNooESepxq6XyohV8sRG6ahg/6k8lV468vbkW6yobbWitsefAsFh0uR7bCgJlYFaxkpzwzSrxQhBvVGfgwJSCr03qQgV2C+T1Z+7CwaGQ5bLUjQyYDiGixbvJn+I/HJV/cjo2E8orTtLnAdk/MXHslG3Ss7dxrpNVQis+epabEoKqrEb0v30H8kPv11GgrLq/DY469g8p2DYVRkUVDwdDp1ouTEURON7CNFMP1kRNvUDKTqM6C0kxJnGe6/ewIOHcxFaloiGjVOgUteguKiKjw2fw6O7TqB2pJaDBrZHoe2F+Dnr7bR9TUcnIVPDh5Ew3CWeDWJZInZ3nIGvBDXSAGexcYxlpkhjLXFyV2u66rZNVVcakGEiSWK4dGMgmsIY8lhuIn9ptrMlrVbHV7tSCK2jpZar4aqADrTW8QAl5NjI6GggiWIxASHBNFKJSHjgJBIVEmpd+lxloCGZbJ90hrYPVlSdTKLpbKEaR5VVTGgsZZPMghwVc37iRYtE5Ecx2avwzSagOQ6XMPOW7sEVh6y31SGwiq23vQ0pt1ZWMran3+c6cPa+X0WE6lBGb8niVu5JJMhPMoAudwDBZdMqOXl2gH9GJGloDseuD8Sn/iwqyVf/ycmIsSkCO8DO1zSEJYvjkPZzIBSaxDgKEBl0X+Jsu/6+txgcK4+3UZeWu4N4RYuvvdfL3kvSUjJc8JDmpNlgCxNh18K91ITrAa6o0iLjqXnPFzdGHW1VlRVVyCpQSx1NGWHpX5x89MFmdzZd6IUNjI5FcPbm1MbMDEzalg7VB8oh3t9CaIiU6HXEh2iUMZ2sQVxTxWg4xtvPE3LwIhZyIUec+bMoK/EoZkEcSE9t1Ffh/D374eamloKpP4VVhb5TZ8+Xek/UhZLygirqmpQU1NHSwsJIEDAPmGeQAbhX365nDLY+vfvTl3IzwX7h6yf6KdVVVXjo4++poYmxBmbxF133Ui/C0VgbCldjidv+wSHdxf4KknaJiGpWRxO7C/B0mdWoLK0Fje/MAzRN0Xg6Sf/h9hXwhBtaEVlif7oOUByV6KJv379LuzZewgOpwsqgxv7Dx9EVmYG2ndIwtjruiIjMwH3JY9HfGwkdfRd++sKbN60H9u3HkLXbi3Qqk0qbp00m66zQXI0usalIEbHnvX5tSzv6BjH8gMln/gU4YEFkoc9D10ceFRy0EwhZ2M4iQNcBEDzeFheYOHAnUrO/pbzcmEFBzHT0+ORkhbLt+Kmw4M2bTKxbe9rPp1CP41CYZDj4uCeAPmIhiRrE8t/bO58VDnYczFMzXIfUSJNy6pp+sD1tBVGb3mz0JMUepVyWSHPndl2yOQ5Mf7xDzsHQ21u9huTikvUeJzQifJoDrwKoNADVrUjNPQVIDktIeVIcEssr1XKYgNevdJj/LizD8XYTbiIC5BW5EJyyGTBoKQaixcvoezr5s0bQa0hephWul4fMKr6E9JVAoCuh3jj3fKZQyWzZ7+HxYuXYvDgvnRChshUEHam1WalJAXR70keGbKzc9CwYdppdCzPPCwWK5UnqS8IC3zLll2UURwbGw2j8QJ3NgzFRR0h4PEM4/2v7qGvCTquHcJngv4NYTBqkXxpJvJ/zIa+2gWt04OK6H8HkCV3eqDLsyJihxnODibYIpR/uyyb/JOZVIhNYwwu+So+8CUPca0ahnAtkhrFYIOjlH3Iy2vPRbhUMuSnqpCa44TW5htgfP3FBlxxdWd0bs2Ax/96EEH6Fi2YsyiJt965D117ZOKrL3/D0SOFeHbm9WjbKQPbthzFtCkLsHH1AVwxvgtWfbYTIwY/jyeeuAsjR11yRrOVxNk0MjIMO3ccQZMmqZh4w3MoKChDRmY8YqKjqB5RekYSkpPjsPyHdYiMNCI8Kxxt+zdGRlI0flq8FeuWMQD0+nkjYL6wSDuhOF8hSbCvL6HgpLvChrqkC+xxK5MhL0EOnU1CQr4V8r1mvJv9PY7sKkBKWgx1oL532nD06NQYDz7wClav3oy9Bz7/25vVxulhL7MAUcpAABVAXL4DR97dibBm0Zj66DA0bcqY36G4+KJr13YnlfP+m4KwRvr0GY3s7FzK/CM6g4T1928IYkJAHIeJSQZxDT+TOFXxC3HDJiY0waXU/kHMgMizddas6XQgfq5j+vS7cdll/TB+/N3ez4j+GXHEbtOm2QXHpP2n4uabp1GmlFwhg7ZlJExXZcBdYUftkgKkt2+A+54YDp1BjXvHzMc3c9Zh+MtD0PWGDrhp/By0b9caCxY+94fbIABcUVEF7rt/DB59eD6GjeiMN1/9Hht+O4C4uAiaP8UlhqOsZB2uHnEpli1dT3Owtu0y0alzM4we3Q/Llm3wgo6vvTEJffq1omXWobhw4lT9w9mOPXsO4t13F6Nt2ybo2bMDLrSYMuUmtGyZRSfWxoy5g37WuHE6ncQlfeD4a4dj7NgrsHXLXtxww1R8//37lEn+d6Nz5zbUkI2Anf5BjGSeemo2NWUjchQ9e57sIP+fDDJLcL4lXC4AyZgLIS6wkdA/E05PHn21utnsGaHDR6ib0feRnGkTxQ0XLvQQM175dWxG6kQdA9XmPDUW3zbZiAWvr6B/h5k9ON6Kzzhz8wivAYNg4JCbxGuyFsSaEX+LEkWybLBrKy8n8K7Pfx3B5X+cBWThrJdOQ5iWinV5Hhw5VTA0jobzWA2qe0WiooKxk3hBpG9dGiWxtmUzY2RWiTC2xIRaDQcPidEEaUK1A4fM7H2EU46vjx7FA+1bQ6kGhk7ujjm3fwl9YyUklRzWE37aeNyh11uGKQwoRBDGk9cFFwEl7Vbv8fU57KrcQMYR1jaHEshrqIHO4sGXn/6Gz3/ahOtGbMO4SX3QKKwf/us6YCSaNUvDzJmPoAkFJNzYsfV/mPn8Q2jVugm2bPsFR/YzKYRjOaVo5EhDXEs2EPzhhxW4ZGgyjNosOuPrFdT2eFBSWoy5cz+Cpc6C779fg1g+405mJz9fvAqbts3DsexCNM6Kh0zhoIn0O1/9jPU/b0fUbS2gUCvgVipxBG4UOiphvCoT0yZ3xq7SMpSSq5RfqDtLGZC9cNvOgGcQYTWS8lbaHn4P2SzsmrBb7QHMR61GAb2R90lxjHkWrWf7Eq1jr1VqNjtdaqmDMYJ9puKlPLVma8D6S3j/EK7VwuVk2xDrjzMZA8qcKz2MsVde7YA6hi2TlMxKSJycJZnL2YYW3i+QUmaPjV/3Yodlgfetg9/727YV4LCeDVhJebr4PQk1ZxC278yAqIaRUXDy/kWUcifGsraQEnK6bycqfS7dgoVN+gHiV6VVwq0gJWD8+hLMRfJbUX4tQvRrguVdZfe5WgsTIMFijGR/N84IA34th7uwhg7k5APj4SiqBqpOPavulb4gbRUNE32nf58slhHb1QQyKGX8O6lGHtgP+Ttu8/W7jAqYyWmucCFGAaw7nIfqRAXKmwPJNcCk6+Yio/3XqC5m18nq3HUYmHY5/k7c1Lol3muVh+N1RXBEqGAzqqByeNC0aRychUX48t37kdQgChpF0xDTOxQXbCQkxOJ//3sbDz74PJ55Zg79d3Ydr083kv/rZYGEBXjffc+gf/8eFIDMzS04Jy7h/rqP/fp1w969h7By5W8YOVIYVJybIM/n1q0vpYN8EvPmzaSD7latLsHcuQspM/OLL94MgY9knJDPGHG6ISmojpDQJi4aVeVlaNmrOe64fyicFg++/WIDvbrK8quQbjIitZMey+0rcejQcdRaD0OtSKfXvH81CTn2iz79DJs27cFvv+2AzepAfGIEIuNN+O5/m/D4B9eh7/XtkZYSAwOpxiAVC7kV+OmTLbj1rgHo1KWxl6VHqjHGTeiGq69nIBP5vMpeS+1MMsJY9UiPhCYBJdGC8eYzIlESx0r6Xhl0rwj3aFHlVuu0eI1chDmLyDV86ii+Z6lgIArNJzln6LlFKbe3pJv857tGA0xgYApoi83l8JY+x6oZq1AcX8EwFWM9to9B5cK83SYVY5B7wPbNJEl+rEj2WYmN5WyidXbOfPS4HV4DG72SvarkmiAmITsuchgok9TpsXvXo5Dz77yu3r7j5K3gkgnN9OD+SzAgJe93xBX8k0++xQfvf4mCgmKoVAo8P/N+PwYlOSeB7EhSJcXWI8gjohRbdxKL02c+xPcfFu85EQxMlSyJH3teDVQPhEIYjUOG9EdmZhrVUiQapldffRm69UrAb7/uxjNPfYxXZs2nYCSJLVt3nRXgkUzkrV27yQs8kn6OTAARMHLEiMG49dZr//Y2QhGKsxEXHfAoOgih1yYo6G6pCgoZm2kNdtRSypm2mYF/Tzr4f6u2nujQeyYMoK8HqtbT14ZhaZh6axrGj+mDdpNmImZfHVL2W1CcqIJDuDAHA4ekBFKUY4tBdzCIKH5DBrtiystvfMt+G7QseSYEmyx4AUz2gCg4WkRfY5uGw7K+EDe9OQKzp/2PAqbM4w2QBEAgxvJklbRsk5dZkweywItFqbQAQ60eInhC35rdCny+YC1GN86iiUD/5MY40L8NirJ3AykGHCZlpWL/RTuDgdNgYEC0h27AGfi3AAA8EtxyoCBZiTqtcMP1oFYDHO4VgcbrqvDJvDVoP7IlGp3eh+GiDyLgT8q2tm/fi8cfn43PP3+TJjB6vQEWq5OWWl87dibUaiWeeGMcTMlh1GQoqmEkbn/5SnzyzCqMGfMiEmOj8cbbd8OgYYnqs8/OoZpQxjAdXn5tIrr1SUX3rm2g02ug1rJzXW4vQmSGDAqlE4er2XWpaBqJ7k27o6COJYqtolly2Jg7NZPSnxi9LqBEpoxrGgqAT5RBkySUlI3T9/w7HQf/qsp5WRDPeCMjdcjIZOVEJPH2X79IYhOMLClsFBWFShvbZo2dgWXlHIAM46XcaeHCWbrO62KdGMYutmYxMfRV3KoFZgY+5cQVITKabaNBIlsmJ6coQKvVyQF5mmB7+4N6Sn5pw9kHTpsLFfw+IgwMtk9skTr+m60bs+lrdF89ah08mVQH3pKGcLZvifyYlVSc8E2qkP5BJiEnz4xKjxUKMaEk+iZSxl4rgNKgviOcJ90cbPQQQFNUWsey89Ug3gBk10G2KJ/+7UjQwNUlAjlOGxmhsIXFq7e/DCyfliXoIIkJDdFu3ld5+xlRBk7+5jpU4vfhBva3piW7JosL+MQJKScX6xPb5mX75ngdCH9EHI+wI1ZU7WSl6znZpQgblobMfSbsOlqIfqmMafJXZUZ6JfZEST87fliwAHUmBdoPykTtGwfQMyscxgHxiIlsBrVcHwIdQ3HBR8uWTSj4WFZWiYEDx+GqqyZhwICeuPfem87aNnwDY9dpnF3PvByblLQTDWviKH3FFQOpUcwLLzyMsxnp6Sl4993P8Mwz9yOC6/aSAfErr8w/58AjeQ6+9NKj6NOnS4Dz9v79K3HVVZMpGFBVZf7XsFPPfvDnracQt9w2DA89+CbqvstFwrQ26J6UhIIaJZzFVYjUmNCuPWOM9pzSHWFJYYjXs/HUT1tn4M6x72PsmOdht3ow+/V70aIZY1KRks5Jkx6ipZ8PTL8aaX1jIVfJkdwkDhFaLRRKBbRKpVdKpdbpQKxOj8zMOEx/djQMKh0F9gTo5eBlz6I8WYCBJIwq7WkBR195LvlcyCUJrUeWEwn3aIuT63OTEWJQObIACkWbmIATa4sPRBT6jcJtWgBZ4qhLXldrAarqlazdbu6oXedi8jEVdjPC1CyPEUBhcEm76Be48uNpz7gP6PO9l3HJlDgutVViLT6pTN0LvHJtS6ebjauNSiG3wpMvmQNqeTS0ini/9rLv3BLLG33jb7kXEHRLZfyV7bdKLpyWfW0gyxfkF2PYsDtgtdqpRuGdd12LESO7AvIquD1CD1LjB+0Kl2xxDeXyoyRKsEn7WX7ka68q4PqQ8X2WpArUudg1Yncz8kC0NiGgjNwHxEpw8X1qmKXGJ5897C3hPlaWjVsnverdr/SMZFx3/Qjk5PgkDv5OdOjQGrNmzff+TWRMqqtrkJychF69QizHUFw4cdEBj6H447JriTNidBaJlvpeyKHJDEPvGzpi0YNLIXN5oNxeDbTQnVXKctj4hrCsOIEn712EqU9eCZlGhvy8Mp/W5TkMj0JGB99eQIEHcSAPhS/IIIaAjiR69+6CN9/8CJs27UBhYQlGjhqMt978BDGxYXj4yZGIbxGFFT/uRsd+xJQCaNAoFs/Ovx5HDuThx0+3eRPFX37ZgI8//gY333MJBSxbtk5Dqzbp0CrZ7LMQ9w5FKE4bkgRtkR0KmwfYWANZuQOqZuHQ9U1EUSV3MC/i+o7/klC0jIBnZxVk4Sp4ap3w1DkRmxqJ0hxuCPM3o0vXltC94kRVuhbOXRVQxGkx9cnh9LuQ/lAo/k1BwC1RPnz48HFMmDAaF3IQIwZSXj1lylMwmQzUGfbo0Vw0bJh61rYxadI1+O67FbTU+fHHp6BTp9bYtWs/iovZoPxcB3FCDw5S6UAmLwnwePx43n8YeGRBQBwCOpLQtYuBfXcFlv26BiXHKjB+VG/8/ON2GKP0aNErE0ltE1GyrxTlRTWITmCg04yXxkNvlOOBOz6kjEYSRN9z/Ph7MHHiaNQ5C9G9TzMcdJV72X8EdAxFKM4k9u3Lxv792diz6wgWL/6BfvbhRy+hY8cWdHLBLQkKyr8jhJEqifTMOBw/VoCbJqZjxc+/npX1k7yJaPaWllagrKwCBw8epXIgjRv/fTblRRsXNvxx0cZFCzySWRIW3MELqnpo0bKAmSSFcC67CEKUkjaPHBhANY+Uu/Dxyzfi3kvm0r/TjzowftYV0BrVeOGrXyhrpqbM5hssB5VFnjKIE65gBglTGdHRBjMp/RmPwaXbHIA7wh1PSQmqNTEM7iHxkH+eDVQ6oa9RwxKl8hpleP0W5DI4XB7KdKMMRdImajZTT2m4X0nlxg25gIFULNZhwh3zYTtRB8nsRPbASCDfzNiTyqD2ipJr4YArGkFYVgLMFdsSphHBx5CURvrhjTqrB42jw+lAH7ts3uIArTPUO3bv3sE7m1deXolWrZri2WcfoGYE5Npu2aoRfvxpNe67w6dXdengtih1WChG/eAN76Ompgbjrh2AfXvz8evaX/DO24vpclndUhGbFIFNJTn07yruspxqYgm23S1KelWI1TFQMiOcvf5WwJhtbWLY7GkBL10+XFXjZQg24CXLotxZzIDn5nK3P7nPXVkwG1XljKkoQnyekRCBtAg2yNUpVV62Ir0UHbwsm5ceE0agmHWvtrF9SjKydkfqAjVqi2rNXoOb/RVsnwrNbJb3xtYt6WuMlrELHD1aeVmVTfiAuyA5mb7OzFtJXy02P2dor1wDfw2+nP3c7sU9EkyaFlHJ9Va37DiMiBh2fjxRrC2lJ1giqtHzUnNeam0j5dXxrD80xWihgxJROg0MpOSe37f2CG5m4/KgXJhDCcMZbtrSvCkbqJaVs+9LCHvQ6YHCKSFmB9eJlQPyLlEoTdEApdUoKeXnkchDiD5E7JyQXBCmMLwt5JRpOQvByRnnbn/XbXFcxW+8/Sz7LJrvS0oWYw/U1DKWqLXE6jPDEexK3o81IG2QJFj3mBG9txZOwSuvdSF1WCOUbSzEvi7AzpVFePoGflz+arckuZDcIBoNdAa0rDUhPtyI8e+NQqapE29aSPg8FP+uIIM+4p5M3JQfeeRFNGmSSbUP4+Njz4KJimCPu/xcW5UB7BwfQ0jktPLTlmNnZWVg4cJX8N57n+GDD76gztQffeRj49QXf2aulwADV1wxCFlZmZg8+SF06NCKGhssWDAL5zMIqPrGGwuRn1+MoqISlJQw4PPIkRx07twW/+WQZCz/INHUFIFOjRtiUM8hVMZGobJj545DSG0Wj43f7qH/SAx+N5OyHol78rcrt+GN17+hnxtMSny39Bvcfx8ziwqPsmPYyN5s3bIYr0mcnTMGhTyKhudE4vs6lw0mFev/BXtNGLpo+LUuWHg2twNy/1JqP+dkXxmUj/ko894PorqK5Q0uDys1VnADGbKkcIEWEewEraJuy+wOs7rZ87COVDX45Y96FTcB5MxFwm4U691fydiF4VwWx6Jh67C4WH6zraQINp53js8yBlSGeO99SThh0xYHnltvkiEP6h+cPuMWYfbCvxPu1lbeBmJeIw5DuY0xEvXcNduoZOt3cJmyOlcZapxlKLPXwahk+YySl4oLxqpewbarkEd45c1ya1mumWpMDihzJm7WL73wATZuZC7rl1/eF/dNG4zoaCM8xCVbIudaF+hKDpeXtejyFAaxQsU1w/IxtcLp/b2vOlsZdO2Ic65ElYPl2HvKmZRT7yR23sLVTKLCd0zdcPPrqcrBjllZXg0mXvcaqqp8RIaICAO0Gg2qzeUUILTb7dBoSC72d8Z6EtWwfeaZ13H8eD5eeeXxEOgYigsyZJLXeuvfGwRQCA8PR3X1AYSFsYF1KE4dz8x/Fh+9zLQeg8N8RTx69WNOhJ9/9Luv7PBUGo/iVeYngCLKs4PBRTFY9n+oBzH9vCHAy1gtkpJ4ubzLg/D/FSG3kwn2MCViI3k5KgcjiDswebDTElu3HoUes9dQTirmAIC31NAPAeLtlCvl0Nd5QNJ7SS6DPdzPqVboqAn3Wim4RBy+dfH90yXpIXN6kMlniPVGndcBmCyRd7QYeiMb+F8dlYkNP+3DTfcOQt7RUny46Deo4/VoaYrC9JdG/+c1Hk8XLrcFc+d8jE2bt6JBcgyWfLMejRonUp0e0r0RpoNeG4ZmzdOwcsVG9OrVAY2aRKNx42Q0a9YItWqWTKwvZCUP1byEN1ortHS4m6Bc7gUPU4xhAUnmkWqWxBfWMVBqQ0EBGkYw/aFKDvqVc1djIrROL32ufVhVWefdBgHO6TXC9f7EreLm4D0ByiKi2P2QkhIXUHKd7AVKRTmPBCcHo0TpUO8UluAZuQ7ZlmJWOvLlys3IFVqmIrnm92BsJDsOMbFGL2Bq5/dtuw4p9LWuht1fh4+wgZ1FsIX9Hy/BTxpeTizT+wGywf1BcB7G71WVWoFw4iBPJydkASXFicm8DDyVgcHZR0phc7D7tFFmFNRuBQxaHWwaF/o2bRygdXnCbMaRfSwpLuHAY2wQkFdZzM714aMVsArnaA4UNmnEStdLytjxqBRMR6ILKSZgRL+YyAYkWQ3ZbzQ6tj/Zx6u8+6Th56CKyzU4xfrEcYrT+dbHX5pmRgQAsPsOsHPsJJIRor/m7Y3IYM/LdI2eum/T09LYgJIMLe7v0A77N+Wi8+RO+OqRH1DRywT3dycwZ95NiE0IR7uYS/FngyToTg8D+Oe98w2iok0YPXIMvf6FW/b5juPHC5CR0RnV1dUI4zIDoQjlVX8mzOZadOw4rN7vCKD310AuoQ3HdaklH2jgK7EWZYaBAEMwEHG6TrVJk350Yu+DD14+bWuys/ORmZn85/ZAkrBp004K+LVokYW4uJi/zWgmRnMFBUzawz/YY8v3kCHl7088MRsTJoyiQDDRtbzkkl74/PPvsWzZAkRFsX4yFCcHKX3d+PtuPP7Ua+hzWUt8/NYviIg0IDY2nObhJLHWaQ1ISIxAubkMNpsTLdqnIrVhHDQJeiSkRcHCtaFJGbXQyhcToRU8JxLaiQ0M7DlEmJGk9JpEnI7lOREaQ4CLc63T6i0JFkCYWi5KXg2nvP59YFywzrIUIM9FZLmExqNwtRYhPnfxMlxSOn2wkj1ft3FQO9HA8vzBaaziJlIT72sBLzGucbBJXQFaxusiA0DFPRXHvcBlioHJ2agUbN9ECIkdds8LUJLrN57UTwiQ0meUKUA+X4h9Ym1Uyw3eZ3KZ/Rh9za5hoFrjcHa8hQ5lXm05jh2rQkyyHk4OmCp4Hmnm57NJBNuPSK0JldwYKKeW5VLNIxMCSs91Cl5yLZOj0HKIviVgNwmTiuW9Ci71IvOWzkve3CK39kRA2Xi0lu2Hi19vTo8L4Wp2PJW8vFsOtn6nVOidIGUbUCLXzHLCSp7vt4higKNe2SRIU7IWtU7WhuyiQlwz6CX6Pj4hAnPeuhXJKdEYO+IVfPLpc1j63W8guHNZaRVMxgjcOOGqvzXpSs7tnj2H8emipXjkkbv+0cqRmhozwsObXpA5lcCLMKatT1f9fAUZhyzecUEel/MZFy3jMRSnjm6XNPcCj06NDA6ljAJupOs0fleMcn0korswEd0LKuQy1PWIhN0n23PWy55rw04ue/6roTS7ELPdDFccnxHlZSY2Dl7Ja61w8c8K20Zg6isjkRBhwvLPt8LQMhoVP+RgA0pQXmpGisbBZ8RCERzvvfclPv54CaJjTNSE5YuvHkNcAwN2bMtGZqMEREQYUXZCg+XL1iImNgrPzbwHLqnEm2zU1rL3oQjFfzHUhXZYNrN7wDaOz+BXO1BVWofMViwpd9lddEJJ3j4SX8xfh9sf+3sGMyRumnzJSSYUoQjFvzFMJiMmTx6HefMW0b8HD+6L9eu3orrajOuuuxcDB/bEzJnT6HIXWnz22VykpZ19cxlxbxMWztkKYlpy112Pw+VyBZjD+Oa3fMCjUqnAiy8+TCcXV61aT8HVd95h52fNmt+pAUQop6o/cnMLcecdz0FvUuPXn/fhnmlXYMjwjijLM1NTj8aNs5CXU42DB7Mx+/VFuOOxy9GwOXtWFPJJvFCE4r8aZaU1XtBx/kd3oUXrVOiUGvp5QkI0oqLCYbXaEBkVicsv74VrRj+KESMvQTjXXv+r0bJlYzz73H31mt6EIhQXSoSuzv9g9EsdjP0HBmPCT68g97vDyNt+Am4joCx2UDZ/3mcHUJesYhqHgqUo2IycOeSlYvmbxAQzHL0DSv6B1zk2iAlFFwliVIrtFltxQpQ8iu+4o244cZWl7rWcqaUguh8SZTzK9YTSL0PX5g2oCc3vlbmgGsSiTf7OtYKJJNhAgm0pthelObnk3BW0T4L56PKg9cAMuA9Uw/VbKWK7JKFtUjx0Bg3atchAv0taocbBZlajNWGI1DTzzlaRpLp7/wmwlFlQmaZFBCFPSsD1Q0gJ1Ku45NJOmPnibTBomRtaSKCCxeTJ4+k/ccKsFicddMyY/gISEmKolpFGo8GIkQPx2eKnqZsfceFjp8/kFfGO5+7QdU42E5xkYIPEhuFsZtXissPiYt+ZeIlMkoGxJgx8drrGwWZaC/JKUVHJZnWFcUxpQUXAJaTVKr2vwtVaQQAeP4ajwaAOMEypqaiFuYpdP9l8Wx7OaizQsxn3pAasvZFaHVLIzB6ATM4EbxHNvpu3axd9XfUb080sriBGKYHMOSe/R7APdN0AAQAASURBVE4U1gW8+sf6tdkB976C3zteZ2WyO0GlwN7gzGivkQrpA4L7BSHy7jVi4SLvdjfKgt2n+frKuOu0KHkx6pVomMVmyTs3SgPsQLRSB4VJ7i2jz+SmQGFqDbJ6RgcwSaN5WbqFG/8cM7BzEZMYieI8tg01Zys2S2cD+H3ZjD1beYiXs5HzyY1cjA3YtZeZzlgOjTMDJ3mM4QbIgsy3Co8zVsUxUjZOjwdf1qSCnRtfOfl3RSXsPEVH+JivXmkHztgOI0xJUkZ/WRcsu/07+r7BM52x+seDbFmlHBa7E0qTGokGPWUvhFkVsFdLWLtpD264sT+kGMGqOPM0giyrlCUEOGSGkuRQXAxx332T6L8NG7ZSh+urrroUCxZ8STUVV6z4FcuXd8Ho0cGAPbk36wfeBUNL8jrokuU89RhLkGV4v8vLMSXKcApcr48FFuj8SnQP/0zU1lpoeWBiYhxlMJJn7bkOt9uNX3/djFdffQ9KpRIdOrSkwCMpZ7/mmitOy+5ZtOhbPPXUbDz55L2Ijo6kUi0PPfQC/de3b1fcdNOY/3zZdXCkp2Vg67avvX/bbG7qXL1g7stYt3YHlGo5FAo1MppH49m51yEuIdzLICOVRyQOVLJnY565BilGloccN1cGgJMq/nwvtrCcRq9Ueo1nRBm2VslyIA1nPIrSa8K2U8ujvHkcCSFF4GM31lfQF8yG5IZ2nG1GXgUbUKlm7TQ7WLutbsZ4K7awz4/XVGF1HnvWd0tiz7W+DVh+7i0ZF8xCGbWtoW/D1ezZz46KX/AcrGVUw3raLXbJ55Lt3372WZAuvUzkSPXIPYh8z5tzseOtVrC8Vw4NZNxJO1rDmM6yMPabWl5WXlDLyol/LypGRaENCpccWmFgyCUmRL67q4yXtMvkqORmh+GcTFHETRpF6Xl6GMtla51O7Cln79vEMJZlu5imvPnKAHMgwjQ8VsPyJPEbJc+jsiKiAo5Ztd2ORhEsz0vUM+aZRBJD+kYcQ04QgRZxOpYfqhXsvIuSeeFCLl4trjIsPbYP37/JdBvnLb0b3Rp25L8Jh8xTCrWaVLypUVdnRV2tDvPe+ZqyyZ966i28Mutx/NXwGSuFJnJDcREDjzNnzsTDDz+Me+65B7Nnz6af9e3bF2vWrAlY7pZbbsHbb7/t/XvJkiW4//776WzorFmzcPnlLBk7fvw4MjIyEBsbi6NHj8Jk8pVNt23bFldeeSWefPLJv9PkUHDXbhIfXDIVuAT4fdcPmDD6NSjUCrgdbkQ0jIRtwVHo2plgzebmCEKfjFPrT9IrJF8L2rIoSxbLCPBAaED6A4sCdBARDE74r0d8xUG+bKK/SH8jtgNExeggk2To2DAFRTtzUfrabiQ3isUAtRG2OjsqB8RCplNi96ZCH/gofi/arVIEgqxkOV6a6ANP+Xd63tnb3dDYPIis8sA27zBrpkaGPUeKsNteA7lTQqPlu1EdJ+G6Tl3ZT5W+hH/F8R/w7ORFFHS0dAhHabUFpQ1VVJlURTTkFCr89ONmqlEy/43XQ9dxwKWnoILKPXuO8A6E2rdvQYWWic7U6NFDUVpWREuTa5yH4HD5SkR0ikiEq1lCo5AxIK+MlwHZeMlyGE+ojSqdV8fH7mbJZDkvGSGAFYlUzmiJjA+HkX+m42XNh/az8rAaXu4fH8Xuw0bNElFexAAqGQceNdxdmJSVkajl+jB6oxYurg1o4a7YCj4poBeTAzw0SgUahrOkqhEHIA1cF7KEJ3qlHNR3EB1SkYiKazwYBDwpUfULYVzvrkeSwV+OwX893t/6rS/4u+DfBn9OgieXsdHseHpxNg5Etm2XCb0qkC2slsuhVMhRwvUxlXIGxGWEh0PPz5com1+fnxeQbDbgJe0pYeGkhoa+N3L2jYb3cTv2HQsop26cFoYGDVnJlcTbHs+fb+K3URzgJE7jwo38MC+Fp8CwX+jIZAhnFDlFX8qj6ggbDFQRoJEeCLY/UZlh6NS1IS1JyixVYtUr67BsCQMdCwbHoGDDMaZFSQYAqUZk/56Lmx++DM2jY6GRKyCtrcCt9wzEz57deGzqp1i9+ir8lRDlcKE4OUI51b8/unUjzLqZVFuQBJH6ICDd/Pmf0vJewn706pJJDm+poNch1hsCYGD3JJkwEx2hT9fMHAAqyiThzEqmX5UBA1LhxCsL1oOk2xfakKeuqnC7Pfj66x8oYEeiZ8+OVKbggQduqdfM5WwEYYx++um3FHAUMXEiAQrbUDByyZIVtA8k4GF9QY75yy/PQ6NGaRg79gr6jzxTv/pqOTIzU6kRyi+//I4NG76hLKRQBMbo0bdi187jyGgYD4NBC5NJh/AIHeZ8eAvys2uQ0SjKWy5sdbOJrwQO5Bw3V3uftULRS81LXyvtjoBnqpB+SdAbkGRgv9dxwFGAXGqes4lybVI2KxM6fScJSQeCR4HfBUfwbyUv4AbufC3SElGqe6KO3XeHqqq9EjoxWtaWSA3LARWyoHvpTFTNvMuQttQvlyBkFbzA42nW6520kPlKrM+0PaSP8XC37eD4vYhpM4qJWxJ1DgdIF5UcwwA9cc4PVlYF5JwNwsLQLYFNBAvToYJaPplezY7rtlKW99Q6XbDzkv1OPNcSDtX5dSyfPlxV4b2W8mtrAyaJhWwSWQ+JSA50mtRqRKiNAX2n6Gd9DunCMV0Jk4qVzRuUHGgEey23HaGvvxUeQ0VRDT58cQWK9rPqkfkf3IPOmU28pdwkFn/6M1q1bka3UVdnw/++XI1+/brg1Vcfw733Po0XZj5CAf6/FiHA8U8frvN9yEKn6O8Bj5s3b8Y777yD1q1bn/TdpEmTMGPGDO/fes4kIkFEVO+44w588MEHtGOaOHEiLrmEuMr6Ommz2YyXX34ZTz311F9tXij+RDTMSsSKTc/g0j5PIqZVHMr3lUJyS1BXqxBocfEvCLcEXbYFZXuOQt5Ui5F39EGv4a1hdTuxa91RLJr7C2QmJRQxspOUXv5WSBLSctjDzZapg6WZERWHqtHosAMoYQ9TXWY01Nr6heYLsstQlMMNHRSgIGaYWYLGBVRHKKDNYQ/mtSv2UMF04aIZChbEnZMEYUIQsLGuzoLbb78BKSkJ8Hg8UPBZ2FCE4r8YMcdtCN9Wi2PfMFF7ouYYlxWDpuNbISw5HO989ZtvYUlCxNYaXHLzACQ3jKXP6YKccnTt3xRtumTg2iGj6KA/FGc3QjnVxRPJyQl4/vlp9D7Jzs6D0+mkbspffPE9BR7/bbFhwzbMmfMhWrRohNtuuw433DCC5iAVFVUUvFuw4Atce+1VuPzyAWd1u3PnLsSHH/6PAocvvvgI1Yns02c03n+fGcORuPHGkfX+lvRbBHQkMWBAD2zatAM1NbXUzXvOnBlYuXK9d9lFi77BnXfecFbbfjEEAR1JTL7jMgqUNMtKQUpKDFxwnxemayhCcaHG5k0HMOOpBcg5VuoFWUmMf3gQWvXIpKCjf3z99U84dOgY3nyLYSOWOiv27j2CDz96AUZDFC69tE9onBKK/0T8JeCxtrYW48ePx/z58/HMM8+c9D0BGhMS2OxEcBDgkYAAhMFIG6BU0s/8gce77roLr7zyCgUo4+LYzEgozh3zMUabBTK5k9Y1FWGJJpTtZjM2DmJ+IZiOgj0j+ldiuEJC6CGGqXzGLYI5KEIwHfk6FGo53Lw80FuiLFhWgjElnKD9HbGDZgvcgrFImImShEizHDG/liBtQCZGDOmCw/uOI0yrhrLWhR6ZGegxOgNXXNIOX3zwK77OOYwDLk6tF+0WY2lxKYpyR7KP1Y4gxiNvl8UNld2DjGOMAZfTVAs7+X1eLT0OR5pqEK/XwLStBsOv6ITLmjSFQdnaO6PocOdiy+aDGNC6OY6M7YG6CMBSY8NxeQlKD5fDUm2h+pv+sWv3TmqQIueufKEg5coafPvtfGzcuAPr1v2O9eu344UXH4BK3QA2mwsymQoymRp6JStxUcoY+8wtlXld7YXj87gstkysjoG7uytYKQ2Z2S6xMih+wbad9LV/Y1YS0zSSlWIIQfURTZt6S00qbezaaXAFm8lfuX1fwCm7NKsxchPYzPLuPMa6tJjZdmyVzIlY6ODZrQ5vkqM3aIl1HiLdWthzzKjZfAASMTN6sCtMaeGIMxi9TIJwDdvHYs7wG9usGcoLquHu6YZMKcfBPbmQrG7IC+1wlTogaeSoljywxKh896rXYMp3T8o4M1OY4QgTF0m4vRMGHS8x9r6ebsadszZ1pK8gsgkOCR41kVBgXxP5BBLUBVwoI/DybifviyLD2A2c1TKVvg7OzPSeF7vbA4/CA4WbmJnIUcNLfoTLpnDuZp/x8nfO2E4lDEcARyvZBEGSyYRGkexaSTIw4FtsZ1TPDvTV3YM1kpQfidKx3JqaAKajYMkKpiVp4+Eqts1tVUyo3MLLqNXchTqOs2XJZSH22+bvdE2CG/zEWICoEz7Gg2pYEqQkHfWt/ngDc420CWZ7uBqxuXb06tkUU667ln60s2gHIqINyDlagmN5pWgXEw1eDReKsxShnOrijFGjhuLttz9By5ZZFHgkQB3lKknsfpRggyRxczvex3sNIvgy4vlElhXhYzzy9fC+VCbj/a6k8LEgvQwenxMv+9tnyuBz+hVbYN8dPZKL226bTuVCHn30HthsddQshjARw8KMlMG5ZMl7OHo0By+++PZZAx4JYHvFFTdR9+k77riegoKEOUrihx8+pK6tV145if7dvn3Lk35/+PAxWlb9yCN3wGazw2DQY+nSlbTdTqcLt976SMDyhw5xyZBQ8MuAPWc2bFqIFT//jn17D+Lgvnxs2nUE4+/qB41ViUq7FWorqbRg16tMxp4/R6v5BDoPUg0iTD52lrES2Jwac4C8jZ6DmEnGMOh4SbWQCDGo2LNOVJsIxqObMCLt2QHGM0K+Q4RCxk1bBIOR5glOVFWZERsbeZLZDLkXSksqceDgIRw8kIs33/wKdpsTfQe2wnOzroeC70exheVnPx85CqOOrXtDUTGtZijOraDmOp3iUum1lr23Ctu3HYZOp0FUjBGdOjVBbKyo5uNjI++973Wp9CuPFk72bN+UcmbS4vYwJqEbjFlaP6szSKpGJkN1VR30eg1U6vof4v6MaCffBnEQJ7GtlDEdN5xgbEMNTwSsLied4CfzkTp+LgXrUORYwrm81uHwOnYLpmNGODseJ2pZfnq0iu1TvrnGa7KzYB/LmxXyA/TV4c3puEGRyehlNuZVV3vbRSJeyCZxSZ1+ycnQKcO8hjAknB57gHGQXhnjZzrDpYTkfEyweycm3vCi95gNG9MZE+4eiHCdHrFaxvhUKzL5UVRiy5bd+OjDb6jRmFLBzmOdxYYmTdKxbNkajB51VQh0PN9B7rnzrS8e0jOn8ZeGDwQQHDp0KAYOHFgv8PjJJ5/g448/puDjsGHD8Nhjj3lZj8TJZ8KECUhMTKSDafJ7/5JqEmPHjsXPP/9MWZNz5879K00MxZ8I8XC+9voemDHhIxS1N1GjFavZ7tN2DMYIBCApjNHIIFd8dioGPy+jps8w8SAMBhxFiNJmAgoGu8GKcmwxlpbLoLJJiN3HHlq5a47jvaNmVMQ4oDzhwAcfrEFyagys1Ta4bC5UFbJBdpMuUUCkChV6Fzw6BZx8MzWirNHigdzNH+Vi30TEaKGyepC+1Ux1GGsjFDjR0sAAWQ4OoNwOjwIojlDAmaHFl6u3Y09DCU/14CVPbuDm+9/DsTXHsH7j23jy8Vuhkid7BxQnTpTg3ilPY9y1g7F3z158uHAFunRtht69eoUMGeqJpk0b0X8kdu/ZhkcfeRV33Hk9evfuzBMwhVfb0cO5vKS8osrOtGfcPDEq5OXTK/MZ6LM8myW3+cUVSI5nWjF1HBj8NZeVfeRxMCk9nCU2jSPCYFQFAo95NSwZGs7F9jfwEt7iujokGllilBOmp2zjuP0OFO4ohPUY0xbSjMuALEwFNzyI+LkSGr0KijoPUtJisW4102kM6xQPdYwOZhNQV1sLo4oArYFd/DHeTpI4L39xBSqOVWLOktsxc+FRGOVKtO/SEnGpEaipsuCjb36HMlaHXS4uFs9duGH3eO/bJp2jgXwr1NvNcFTY4HG4UT0yAcVCl5UAk0JOQUxWCIBM3Ne8JJr0NRFxXOPHpYZlOUty61NEs8WqUdqRJY7JCeycxjZg58bE3eOLC9mxm1e8CTXlbB/qrC5oJSUGdmoBjxPoxCfIBLBbZrVBp3R5y3FIjMhiZTZVPIEWpVVkYKTlgKUIAfQaVcZAtQmZT88qiruli79Ft5ZrZv3XjuJir9unRsfa0Lgx66MjYtk+R0Sy9TtcbrjdDBiv4gCs2RN4vKO21qEmTgV7cxMQTq5JN1DEjoet1BpwDnqmJKDOUon3n3kKKjnbpuTYiqryOvrv4Wvew/ADQ+jnChk73qH4+xHKqS7O6NixFdUmTM9ogJdnPYKhQ/tx/Tl/3UYEAI0Qpddcw8z3ufwMyiMFSEHWzwFLXi4qwEox4RxYYioFOd2y9g0fPskr9zF37gJ07tyKgpDTp7/EtZPVtAIjO5s9Bx96aCb69u2G9PQGSE1tQOVOgqOqiriKmurNYQhQ88gjL2LJkp/p32vXfo74eCaFItqo02mpYcz8+S/giSdeoSxGAoKKIHqad9zxGCZNGov775980jaIu3VMTCQGDepF2ZqktHHqVAZihkIEOzdR4akYPTLVCwaPHHUTtn9zHFeMbAebyoNwtQ57KxiLfkcpy6PK+ORsR37eyIRbLtd2TOTXQ4so9uxIMYUH6DZGqo1eYNFBHtB+5c3iVhEgIwEoBVBX6WDPM52CT9ApWO6l5Zp8CqixcsUWfL90DX74gbH7pz18IwZd0hWJiVF45+2v8OvaXSgvr0JcXBQ2b97D2hNlwLgbemPAJYEGSUIHnOhrx/KxbcNwE0pzKjHz7kUY/caV2LpoL9au3oMO7dugY8cWcDjcOHwgB599shYfLXqY7TfY8RAl4+Le3LfvCN5//yPs35+No0fy8Mmnj6NtWybNJJyxRf9A1iEmF8Q9Le55f1D1REEZRo14HNXVpzb/2b77HUoGYtux4vdilvtWczfnBkaWf1zbjGnTR/Pyco1ChY9/2wNNtBK/5AXmbdE6dnzUfOK12mbDFweZU3WsnuVukVp2TkWf4D2+kuQFLglgWV+ICZtSSx3svK8SkcGBxrZxwoVb7gUk8+vyA/J+kXOJNqQYWHs1dOKfj9m4lu4nH65BQmI0Hn1sDLp3bw6uCgCnxwkFd1gX/XZ+fjmeeGIW3n77ORiNPpmZXTsPoqSkHI9Nfx3NmzWnk1OhWtxQ/BfiTwOPn332GbZt20bLguqLcePGIS0tDUlJSdi1axemTZuGgwcP4quvvvIu88QTT2DKlCl0BjMYdBQ3PtE6IqDlvffei4YNTyO0G4qzFm7eaSutHphTtAABHv8l4dTKcfzSaDRrHAuZ3Q2PWQaP0gJ1Fx0khxvOdWbENY5GwW42U0dC2lsDpOphKLdBbnFDkslQ08ro7fvJs6bRXpZE5aWrKBhLQuGWkLyn2rvdnPZG73f1hgywRqhQvr0YGx9ahfmjLBTYyc0uxbFdLGGfdv+beGveAwE/S0qKw6LFz9H3g4c2w30PjmarC82a/GE0b9EQj06fhIemvcaBx78fZDbcVliH2gMVcId5oIg/eVB1NuL4oxvoa6dbO6PsYCnyN+XDtugYNT2SxWlQUmDFkAf74tHxQ2ibrrt2No7tKUTcVY0gV8q9ifsfRaN+maiNKsUrD/4PbYc0xT3jGVvF7GBJJgUek/TA4foTVZXNA8+KYuC4BQkTW+H4+7thviz2b8/q6Y5ZYNldAplRBcXgRCqNYM43Q17qgKrMASlMhfKUkMP7mcahviz5NpmUp33gh1e4ULOtBMk3tfSyi0g4nW5odSos/G4qrh/6Cr3mQn3Q2YtQTnXxhrhPCBN/+vQ78W+LPXt/oK8V5TUoLzcjKyvN+x0pYy4pKaOmeCK+/vpHxMfH4IcffkFubgEsFhuGDOmHu+660Xsshg69EWVllXj44dvRsWNr+jnpU+bMWUD1Fkm8++4L6NXr9M/tJk0ycOJEMTp1GkaZpQSQLCgowsqVv3n1He++ewLUvPJAxKxZ073vDxxYRbUrQ2XDfxykUm3um/fg7jvnoHmbBKhNf8+BVwRh4G3bkE2ZheOv6YtzEV9/tQqPPjIXer0Wiz59AePGTsOHC5fihecX4MGHrsfrsz+jy+3a/Q0Fon9Y8S3uvXM+br1nMIZe2QnyU+gtBofT7kJKhyT8vmAL0gxhWLxkGsLVouRWjq++/s4LdNUXhDX4wgvzsXDBV7hieF8kxEejX/+2aNOWTaj/1cjNLcbY0U+iuroOzzw3CZcN7oIThcXYtzcHmzcdRGlJFe57cGToPjjDeP6FWwNMZU4y9eFxLDsf99zzAmbMuA8pKYEmgqYwA1566UG88soHsHFd+VCcxwhpPP47gMe8vDxqJEPYiFq/kjT/mDzZN8PYqlUrymwcMGAANYvxBxDDudnBqeLSSy9Fz549KVty0aJFZ9S+igozXMFmJUHhr8XwV4PlT3+fonuhtaWu0I5h13TDu2XHoPcAklLnYyOJ564ou1QJtWW/GSa1nM1J81khnwEE/9vtdZfwrc9rWuMzpaCzmKJc22H3fSeoQR7BfOTrEKBfjRzHtpDSWRliJR3KnBbUxXsQsbcWyS1TYSLlgutPIK1JEswRMmiLHBh+Qy90aZ2BO0e/jdY3dcChb/YjJw5wRKpgc9pR3FGHpKN2ZBUHJQsJOrh6RqGo0gY61y7cZgmbie9nTIUbCqcEXaEbMrOLTNVTIsGSxVuATD3k5S7odDrccFt/jBl+OSorbVDKgsWcRdKc6L1e6lC/4PN/+do96TNYkZKSSgcdJeVHUVPlgFJtRo6ZGf/olGyG2KjSYntpHm3MKj5TG8NNPkT59CVxbLBVnqvB+p/3oUObZPyy7gAkVQ0OZ9VAUstRZGTyBLkprDzjeHQkOicyUemNvHw6L4cJZpfms/MXEc5mP3VOFZrxbaUZlHhNtx333Hs1hlzehZY8zXrpU/z4wyZ0GdEahREe5L63B6vnbKT/5Ao5GnVJwR3398eavDx6Txi4m6LD7EZ+MQMNZRZ2nMNc3HAg1409e6ox6fqhiIgyolFmE7is5Th2rBiPTv8YCpUMqmI3XLuqYRLzD06ByCvRemAjWH/Mx+jRnZHeJAENkiLwjdWIn9fshdTVAAsvnaF9ALmnyckOPk+eYPMoCVEqHRQxCugMbqj6xaOISDHYnLDJVJDiVEAcO2Zyqwt6zoqOC2PMvK4J7DyJAW5VDjvO+/aXAkUWbx8iKdXYLj+GOrkDx1LKAkrbOzXNQBJnn5ZUc/d5zlA0ciZA/xjGAHFJHkh21nYzF8sPDv8ZeDUv3RaEbYNKQfvLUoswM2LLhrs1XpaHzMD2LTqFtSmBt61ZNLvOqhx2RDcn16uEA/sZgzbfKtzCOSBg5zP4SQZExbPn7qGD7Ho1ETaCJKGZUQ+3w4L5sydBq1WB6LVLKKTLHNlegvDwMOTvrcT3P89AdaVIG/xLvP69/cvpGCDnOi70nIpERUWNt5z/7JxfUmr8N1fxr2mLB1lZmVi48AVUVlT6fepTz/aav3B3VjkCAR0PWD9EmJKiXNoTxGIUpSfEcIKxwMjkAO/zvMkWl47gEi0+N3n/dgvmo3gvDGqUsFgsKC9nZbTrN2zH+vXbcPnl/amhGCmJJrqPGzZspzn4Y49NwUsvvY3k5ETk5xdixozXKfhI1vTddwvwxRdLMXv2BycdrXnzZqJVq2be604cAXGO9u07hJdemo/ExFgK5pL8icTSpauoizgx3iCfNWmSiZkzH4LZbPmXXS8Xdlt06mQkxCfBYnXhaG0JCjzV3koAZy17ZnlsrK+oUrPPc6016BibQt83NDUIWF9dmQz33DAXl1/RG7+u3Y39W0swcGAndOveCjJ+bSs5w09crS5eEmvnLDQSbj4msMi4zjpPLsy0cqgcCxZ8S6+Ln1d8SK/lzz6biwkTHkBkZAQGDuiOOa99QZfv0nksfW2QEo0FX0xFQlwkaquIARS7dzx8Oylyloc0DYtDZRW7l49IVVjz5u+YOLEfwqIM6NSsLZxmNYpddXji8dkoKi5Bbg57pk66+Xp27L26Tqy9q39ZRUH+hQtfRcNGidi6dS/eeONDNGgQh/4DW/HzFTxs93iNZnyl2r77loRCoUGD5AT07tMAvfq0oWW+YeEGdO3enB5rsWxlhRNuiZVXF9aVYu0xVk3h5JPZkYSQIiO5cQb9W+1K9BpBtw8rQXyUARlKlvuFq9nz7LdClv+aLey8xSp0qOC5ZF0Vy5tWVjIChgiv6VCwQY+f27kIB8+ViAyPlZdfR3MWKsmtSZSWWQNyMFLNVqWxefM4cviEEU2UhsvYRLBlIzTkqLJl5bw94ni7PQx4rHZUe40obZxle+TgYcyc+S4effRuZGSk+vVnxDTShcoKM9as3Yq5b8yg5dcEv7hY+hez+Z/LqUJxkQGPW7duRUlJCdq3b+/9jNDv165dS0uihX6jf3Tp0oW+Hjly5E8zFwnrsVu3bnjggUAm2N+Js0MWk12Ubak4UYPU1BhIecypC2RmjusPeQHH4EZ7gUNA4qV+XkAwyG3VC2ISoEET5Bwd4KhL0UefI6so8RS9oBi5CyDT65bt4SCGDJKGTWdkxIfB9ksl4hPCkXewBJJaBkuXcJRYLLgkswEK8ytR1zyFugVvf3szdAl6RNllkKK1qNUroah2AZkK4HAdefrCo5KhvGsE2nRNZ83fzx6qVcQJ2yMh0S2HbH05NW4g2iMdezbC6l/2wtg5AZbiWrhyahGfFomGrZMxuFNXtGjeBhHUeVj9r7tezsJa/uTy7Px7IB5qniBwVpSuquH0lODgoRykN41FXm0OwkF0V2xIN7GZYxdPrvZXnkAcKfeQAQlcp08lk+HYxjxsrdyPyOYxaJPOkuX05FjUNW+KKXdeg1rzXMQlhmP5qj1QDUrAsRw2qDTXMkZtdXwdirjDXhVNKIBhHZgWVRY3BjJxp+VEowlKKGA2W3Hbgx/h8mE9MXzYaO8+T3vwXrRp+wW+W7IZGrjQonUa+vVvhc4deuC7Jauxev1GFG8tRK6tBDK5DDVVLElKbRyPCl4W3CmJzbY245qES77fjUEj2qNTJ9Y/y2V6zHzjPaz63w52ZK9MRE60i5UF8gGFV0IhSY9eWZlY8788qqUq3L11OjWVFnAQAE2UUcv8JgyCXbHFo8LLFpahvNpOP9c1N8Jea4NbbJSwYoLKtLt0ZRo6nZKEayBbj42DfU0z2OcNkqJQUc0SRGudDSqXArYaMpiQYefOEwF6UiSh1OoZ0Ei0Vkm0a8ru9WTOzt9ZQkrLJFpelBTGPkvhOo0CMDvCNYrieGlZmFoNK2/X15uZPmhYJPtthxQmryCYEKTfqHPaA5LqWK5RFMlLm2r49y6PhEiuMWUKZ8m2tL8qsJ/krtbhUUY4bQygsFayJLtdtxTY1pegozEGd715OeIMfs92D9uHd1f8DlWXWDw952voGoXj3QeuR3mZGR5bLLKy0oOccP/N/cv5j39LTuU7H2fjmJLStbMwuvoXtKW0tBIxMVH1AAPiV0pfeTSdm5H89BvdAeXPBHAg/bT/9iQpEFz0EGdWOq+r8bne8vX5NB39Sre9nwdeYzKZm2tPsj6EtIm0h7ySfnP2q+/TV2Iws2PHXowYORjX33A1Bg7qgddfW0CPaYcOrfHss3PQrl0LlJVVUG09lUqN6uoaqulO2I5btuyi6ydGPF24BEmgVo9ENRqHDJmA5s0bw253ICEhlmo1durUGs2bZ2Hhwi95m+WUJXnzzdcgNTWpHlb2hX+9/PNt8SmA1hfk+iJAcnRKN9iLZIgx6Kh+MYkSrnuYSfNZUp7L9fX0emgUahw+WICtm/PRqVNzZDWNp+cnzKSjxoA3XD8KSQmJsNtteP/dpUhNjUWDZPb8VnCQz8OvW6H+RK5yp4dd/+RZzFrNna95mbbd48Dtk9+C0ajDJ5/MhpyCdjKkpSVj6dL3cdNND2D2q4uRlpaE7j06YNDAntQAZPHiJVjx7WGMHjsAUVFh3vJml4eBR53i07zlw98ePUrfm/JtaNaiAa4YONKryZiTk0+lxUg8/cwd6NqtbQCAJY6z08PykI1bfkOvgc3QOCsZHskCg1FJ+4WISIOfm7WQU/A7R375CwuhIctetXoZnnn+RgZuEZTQb4JWHgQDrClgGor7K6vgFDkEj91Eo1MGHOeSPTHag/TVoNKwS0cCOsamBmhji6iLYTlLuEaL9ScK6eIFtSw3bhvLypMFcFjM89Zc7nLtr88oSvmrKeAtQccljcY2aYJS/rvtvOxfxXNPA9ez1HFpHCKRU8ZZhkJ70sAnliODJgBJ/6uUB0ryiIkfm8fq+5zI6ShiqSbk9m37MXfuIjw1YypSeX7nt0aqiduhY1PaF0+b9jweeugORESEYfOm3ejenemDXzz9SyhC8TeARzLLvns3E6MXQTrVpk2b0pLq+pxjd+xgA1kyS/9no3Pnzrj66qvx0EMPndHyUVEmhPGBYCjOPMRDdcO+o2g2sBFqrGyQDvIQ4Jpl3islOC8RmA/pu0XJjQAWnAJU9CIM/G/SSfP3ck8QSMkfVoIQQIBEtytwmWAAw8uklFMQUg4ZDHI3zHInIppG4URcAYYObYN39i6HY0g0nHonio5VY9U6puFXpHfCrnVDOyGD7l4LhRF5a3KQrlLj0NYT9DFPmpPwQFsczmFMoROEEkRm1hoxEGlyehYWPbQUdZVW3HHneLRp3RSduzbFrl2HcDz7BGL0RiR1TMPVM3ugScM+J5X/hOKPo87FBilz16/D7p8OwWlUIiI9AjE6LQXc9GpiICODWqlAk6gorPl1N9p2SEV8dBiUViUiIlVsYEY0gexuFJ2ohKvcBk+SGgqlApc1TcOWdYfx/cJN6NS5MdpnNMePX29GQQcbLru2M4rCzTj8+RE8+OjLePyRSUhJiYO77g3Ia2U43i0amigtlv3C+seDRWU4WsKSn+hIBmT9kMfYluXylACQavfeYkxs3QrH9p3AFVf0w1Mz7vYKiYsYO+YmtGvTF3qDBmmp7PckWrdqg0kl5bSsLHr9Xoy+oSd+yKqgxyO/vBJ1Nra/2XsZ27JlBgNRm1+SgZenfY6Yl40YPKQjtIo0jBzWBcd2FuBgkgPycDlqymrqnUDQG3QoRh2skh23T38fhlgDnCYFDn+4G57rUyjQaD7sx4YTxlRGfs0LIDK4L5HLqF4qfZtEEnMJTj4xIQxjrDa2QGW1AzqqVwhUyNg+GoRBGX9J0LMBkNFhR4WM9XHGKBOUDjYx4VHLYatm+9ijV2P6WnKiAptWs2QaZtaf7c5j93zz5szozGq2efUWcyysH3CoWXLZmDNXG+rZKwVhSXtdDpTaWae25QgXZlexc5KczJbV8/YX1prh8LA+r3EcYzbGcVDcza+ZSsIEp4CvFUdLWPv2HGdaW1aXLdD4i/ePG3bmQs4nfIyxSgretjjogTY5ES/OmEGf3wJEJNqnu8oZC6HkQCGUg5NQ2koB7d5CXD76WUjldnTs1RgPvTgKraIG4d8cNdzo4J+ICz2nIkEG3qG86q/Fvv0HqL5jVJQwsmDhkfxBBH+tRf8QOQJn4JCCT5kAYRRBEyauIJMZld+9LFiRwsCCPVsEiMkYl8KIRgCa7pPaVFmpRlSUnq574sSrYDbbaCo2esxlmDx5DF2me7fb6Otbby1EgwaJuPPO6zB0aH/Y7U7MmjUPFRXVWLduk3edzz3/AK6++lKvEY5/kF2ZPv1lfPnlMnTu3AY33zwWWVkZSEyMw6BB43HZZX3w7bc/YdGi1yi4GxfHTB1C8eeCgFNEW/P771dQB/YBA7tCrVJTuQ2Z3AW5XMbfy1BRdRwGowxOowSdQQljuBpx0eyazEyMpOXShYcrkNk4AU4Nv3bKJbz43HeoKK/GsCsG4qv/rUN+QT4+/OhJKFRWXHFlJ9x884O4486rccmgkWjbLh0znnwfTz43Gg2So2HQs+tfIRNjO649LDnh4sQIAcJ5ODNPIWcTdApZLKIi9Vi2/CMo5IE5d1RUOD755DXk5p5A27bNvfIi7du3wogRQ+i1NXXKK+jduyOGjWtKK0PEs1UMPXo3boSEWDYpaPAoMXHeL7j77iew4MPpUMljoVanYcw1Q1FcVIpLLx0INQHo6okqBwMvldFyvL/gJ6xYsQ0Dh7fBgzcvwMvvTETrTnGI0ftkDlgbbH6MaD5JESywz0FGetQiYiCB5BqKAPDT10+wdXRSs0nq3CN1qOaVHKIXKOJ5lIUvG8XPTYXHCvKoMquUSI1g6/s5l+VRaZyJ3yumKz834WiTup++313OqozC1ey4FFrYZH2WxM7xpuJiHKpgOdZxF8spNXwiNYaX+osKpS4Zmd68qQjb6auTg4rpESwXNHCQ8kRtLeT82onTsPUk6Nl5TDWxbRuUbN90yhQoZCxH8wXbTqTEtTm9+boSPyzfgHnzFuGtt56lfVV94+1Dhw6hQ8dGGH/dQKxauQ3TH52J8vJqFBSUYveepVCrfFqQ/8ZQ+mYHLtwgTTzfzfwXHJYLDngkeowtWwY6yBkMBkRHR9PPSekPKeEZMmQI/YxoPBKNxt69e6N1a+bk+2fj2WefRYsWLbyCt6E4d1FVUI2IBqcv1/q3hbvOCcnlQXxSBKPv88TarZGj0dQOcNbYsWP+VkQ2ioIzSgNXlR273tsOt8ONGrUCOqMGOpMG7rYRUEZoAIZVBgRJ9le8sx7dr2mH52+5BkZdlvcB07ZtU/Qa1AJ2uwt3T7qSAWN8djYUfz5efekbLFu9A60uyUJBYRXK9pciTyan54AAzsRVkJzhTQolTZTHju3JSwYCE7KF76zE7+sOokFqNPbsyUV0YhhcVhfikiLw6pybkdQgGkq5CeOvHYRhVz+MDv2zoI7WYsac8dj+ezbuvnM2Fn70KCbcNRAL5q7E3rlbYCuxQNkrCq74+pPL00V1aS1WfLAJzzwytd7vyXVDBPVFcugfZMD16KN3Ykt2Bj77YC0O/roP8QPSIKUyILa+aNwxFanN47Fn13EKPJLIapqE2+4ZjLseWkAZznK3dFrt0qY3t0W4pELexjxUF1iQMaIpjsp9pW0XbgTzji7+0Ne6EXfUjKp0LWxhSpiOWqEpdSBtYhtcNb5bvQDXuy//iJ++2gZZmgEynQKolcHWzAhjqQeu9aUUpC/Mq0Crf73HzD83qx/KqS7uOHo0Fw0bMgbQxRQrV23Ao4/chc2bd8Fo8JWGf/X1XKpldvVVt0OpVFEXVwLwTJ78CC2NJlqKhOFGTGmI8c6AAd1PuY0lS1agrs6C1as/Q1JSfMB3L7/8KL77biXee+8luv5Q/PVYt24LZj7/Dnr2bIeGjZLx4cIlIPgdAfE8bhcFt5ljsQdujxWjx/aivwsuwzx6oBCvPP4NWrdNx7EjzCAtLjECVUW1mDLlJvTu3QFyuQ6jRg3Ba6+9jY8+XI4bb+qLGydegsFDemLaA29Co45Cr95NcNPNV+CtOcuxeuUu9B/YGi/PnkiBrT8TpL0vvvAJOnRqEqBZ7B8EsCb/goPoPI4cOQSXD+uGb75eiSmT3kWPvs1wxbjOMIXXr+2t06vx8POj8NCtC72fETOR+++fhOFXTML773+OAf17onFjVqZcX/Qb3gZN2iTDXeHEFwt/w/BxXZCWIcyVLuz4r3HjamvrMPaaqWjfsRnGjxuGDRt24ttvViEtLQUffPASLeMPDsJ0HDLkRmRmpmD2nLvpZ/0HtIfHLcOKFZsp8PjM029ixoyzV+UZilBcaHFW0TxSPrFixQrMnj0bdXV1SElJwYgRIzB9uk/M+c9GVlYWJk6ciHnz5p3NpoainrBLbhwhLC0LBzdI6bR4XnurdqTAEmsxs0FYUQKkENNjfFbeqwfp71wt2DjiN0IXUiACYtHTiUwEgypusS0ZZGrOftQrITk9yC4tx/HsUshax1EwRqaU40BxMZSfsBk3W60drg+OwlzAGFDhGRHo/khvb4nlrlLGKrI3YZR7JSmtJgyyhHhUHCiDSm/HwzcPhU6b4GUUKGQaEIxxysQHQ9fbWYgKuxmGKC1OOC04VHYcDkKPiwVatGTMn6Etm9LXLYWFnNcIvJG9m8pfOWtccIZJXoZIyfc7MPvjSWiTcBkFJY8fz4fH40bDhmmwuZlLdJGFXRvTp43H+3OXY8LDg/AVKauJBcbc0A33P/ga5r5+P2ZMvw233JaDS3s+BuO6CqQ2jceJlhq4wtg1YuPlrZs2MtQ69whjpqm5NEGEyYDXHv0M46YOQM8ebFY4OGodO1FVWQenXQ+V0oDExBivG72IjplD0fHpocgrOIpnn5mHtumJMHSK9bpYk9jJ2XErc/IQcWk6dv6ajX1lOWgf3xRRmlYY2LMVZs9yY9lXW2Grq4K1fTiKDpTzOkC2HYvZicPFjK1XY9QDAxIQwxP7VK73dCSXs8hKbb4+Q8g1CMd6Xsaj1rO/05KM0OrZbHlCMmP61XLtxeRYtq9Hchlb0HGoDLe2aUPff3mYSUPE89ls4SwtXBQPVLhQml/hNdDSuJXIO2xGhdsCcFfnNW7mshgdrvH1aZyZac9hs/Dbid4kYT42ZcwatVaFzikpAY6Lb69Yz37Kj8fxPFb2HBWmRngkG6C3bc36kLj4yIDyaVJiLcLpYDPqJXW1Aa9iBl8Ayvt3HUd1LS+fLrcFyleQiRJJQtt8wF7lwpz3b8HK5TuQd6wMY6dchr5920GnZQzYwHJpYPO2VRR0JEHAZe2vNcjq3gCFv+Xhql7tcMkj7dGqUf+Qycw5jlBO9e8OcpvarP7GASe7WYtpEG+mI8zBvIv4QBOvmYHXfZo7YHslKVR+zKf6DQ98WjieM9BW9SVk7CuWX7Vo0Zg67+7bdxjde7Tlv3OjWbN0zHjqHeTlFVHX6Cn3zsCWzaxSgcT6DZ9R4NHHzCT75hXU4FuUU6Drtdfew2efvVEvk7FNm+b0Xyj+fsTHk+Mr4drr+yIpKREjRvaCG2avszEJOWffCkady+PAkaoypJki4eQVSQc3FOO2W4dj9AimX0jK4Y8cOU7ZhDI5uwfcHvYcnjTpGowaNRWNm0Wgc9csxCdo8NIrEzF54hykpT2DIUOGYsiQy3D7bU9i1YqNuOry53HV6K4Ycy0DPUkYlEZoFOz5JfF2ergWHyQ3hg6eDvJIXbFyvldmoD4tutpaCy3nJ4B5sMmQVhOJa64ZiSuvGoTPFy/H8w99ieffuh4r81kuR8gMDXg1ArmPG7SIR0ZmArKPHUGThow5qFKqqWbjypW/YtSo2ynLkjDhoqJ8wJReycBzY5gOWa2TkW6KQtM+TOIl21qD7JIaXJbKllHJuUkJrxqTSUQr2h3AvHNLbBxTaGFVN07OBCSlzMLZOUprDGD2iX4oUc/uN490GDW8skI4S7u5HnebeMbkywhj+0B+qXCFo2F8LFRydk4Gp7HtVNprA8q+yb1vVLIKk46xbNuHqvMCcqCNRSXeXG5qhw4B284IY7lhtYNNclfY2OuOshwU8DzJwku2w3kViSixjtWyHEyjUELNj0MYZ1uGq7nDtiYuoH/0sRnZXpD44otl1I36qRlToNfr8Nyz76FHj06YP//FeoFs9ks3xo67i75PSYnHfVPmYNjwXtBqNVi9chvuuut6zHzuiVA13PkKPyLSed1mKCCTzoaK+z8cNTU1VFi9uvpAqCToL4R4INw36yk6MH99915fqaHQZRQhgEJRLuldiQRjEuu4rXb28HCLgXDwzUaACMKg8QcwnUEGMt5lPeRpyd7768b5L+vVeKRPUcp8SwmLRKFkRkayCdLvFVCWO6FKNcLSgj14iKZjZK4bJ75loEXWpY1xfGs+NLE62LP0kKfosWsfA1eSYnXeTak4KHF573b0dULzFnh44gc4doiBSbv3L4RafvExHC6EqHIwIKRj9wdRPSgWKWkMuJnSj7EmYnnJxY/Hc6HnIFTr2Gi47B4Y7CqEx2uwPicfxzbk4tC3h/DOu3eieRZzcvYPp4clQVUOJgQeo22PH5avwVtvfYzklpEYPK4zFCYVfvhoEw7+fhzVlRZ89tljjCUpS8SRI7mYcNvDyGuthmTyze1YOHBltrDruVVLxuJIjI1CZokMW/63G3PnT0JktBHhanadvrt1C/avPoLfl+2BTKuACx7EqPSITo/EM4+OoLp+ycaMgASpwp6DHVuz8dycJRjx6ED6WTzXGownepbkGOWwMtqDX++HtcqKRXPuRISmvbekfdnSLZg+7SMoG+hRWW1FYZLSdx8n6tG1Gyv70XA9RFLm7g/2VZi56Ha5GTKe4BUXslKZ4AeOVs1+06JNOuJ5Ei/0McX6Srgwd2EuM4PJbNYAl2Qyjce9RHeIlvSwJPiE2RwwSMqpqsKqJfvYxoosMCg1NPGssNf5+jMBNpIJEaFVK/o+ft68JefRXAOozkWEOulbWRgfmBVxzZ8Efryj2LIdOzVCWkR4gOGMkh8XAYYfKmf7kXuwEHVc17ZBCrvGTZFskJDIdSZ3H2ADn72bCwEOPHoBXg7kXnVtR2TP3YER/brgvgdHQa9iTOwziX0HNuOq4WzC5J57h6NHrxb44rONdKA1Y8YjfKmLI4kikw4ZGV1QXV2NsDBWkhWKUF51NqK0tAK33PIQ/vfVm/RviZc+EvMzeHspoaEbDATKAswkyISmMJoRy1INXr9lBDDJZ2H5+8D1ikkGUbbtX2rtAyVPBiCPHClAo0bJdFu7dx/CfVOfo0zpr7+ZQxmMJAoKSjBwANO0Gz1mCHJzClBUVIbrrh+O4cMHwGgMC2qTAE4VAdt8882P8NprzHzmww9f9dN/DMXZDlKKT8xPBg/thPYdGahVx8taha6gWh7IUVHIVMg+WorMhlFQyOKwZfN+vDtvKVq1aoIpU26uZxsCdHJ4r73s7Fy8OvtdVFeZcftdg9G+QxY2b96J2bO+RUlxNSZMvALXXjcYCnkMBQYfefg5NGueiRtv6uddl7iGxatb4u2GAgcP5uK5pz/F9Tdchcsu7e9tCwG1167dhIUffomqyhpERoVTPcLKympMf+x2tG3Tup5nm0S1dwcOugZffPUYDtnZpHS51YIaPukoSn7rjpvx1nPf44MPHkZcXCTUcgYgkn1o0+YypKU1oIzKOXOeQjpnM7ok9uzfXLLLmxsIE5VcM8t9lPxcxHHjFKFNmGKMRIw2KuA4iNy12MKOx7GaKq9Ui8g7GhhYLhGnY6+bS/IDJqnJJGd+LetP4riOtAAtm3Ct8H4NunjBUJL3NmqU6if7ILQkVQGTJUTGRS4TYCfrN1weBjTKufGVW2Ka6S6p0jueEsuIa3MFly4qqGN9YqRG7T1m4lyk8P4mQc/aq1OwY2d2mr35oYIfVwM3xVErMuqZjBWSFg68+cYnWL9hB5599j6kpwWWv58+JPTuPRrFxWVITk7A51/MxZJvV2L58l+oqRbReLxYgsjXhIc3vSBzKoEX4br25GSf340TUsBH2y7I43I+I1S/HApvRDcIxwHOyrqook04TAYDlAk6WDjziURk+3ioo3WIsMnhcbqRcVsbqCO1OHKMPbRPGZUO7Jy3FXXFtdgjXw9LHXED74z0RifreYTi7IbN6oAUDE6fQZBkc/Hrq7F90zGkd0nB+wvvQUpq/SUsZaVVmDvnK2zeshcPPHY1BvZoj8sG90H/ge3w6sfz8Or9X6JJpzT0H90OE2/rjwWv/oxpD8zDHXddiR7dEmjypQ/TEjvGk9Ytc3qgL3FAbXbBYSmDnLij64yoLnRApVVh7KUv0eUaN0mkroPZBaVo0icThrGZkOuUqCypxuUDu+PI2mOYetN7VHeoRdNGSE2Ng1KhhscjYeuOXThy6ASajW/xh8el7aiW+P3dzXjr9WV4+AGfwUW/AUwaQ0sYkytyEV/sRnFC6HHxTwWZH7QfqEJ+URFiuwc6g54qnNUOKPRKPPgw01/7M5GRkYRGzRNxZF8hXnv1W4we2xtPPjXpL7Q8FKH47wYxXzGb6+jz51Tlnv/GaNmyMZ5+Zgratm0Gtd/gjbDn3v/gecp4LCosxdAhvdCpcyvIg4Cr4Kirs2Lu3AXYtWs/ysurUFVVg6uvvoyyHYmuYyjObVRUVCEq+s8PhFf8tANvv/ETGmelYuJNo9C1K5uQry8++OB/+H7pKnTu0hrTHrwTmZmpeP316di79zBee20+5r2zFLfdeRk+/HQqflu3D7Ne/A4utwfjx11DWWGdu7REba3PDd7/2bht+37s3ZON0rIiNGuehjZtsnDkcD4yMlNwz93PAHgGYWFGNG3akF5bLVtm4YEHJlH5GgGCHzxwFM8++zZlQDZsmI5GjdIom42sv7S0HKtWbcCVV/WAiWgLipKaeqJxiyRcf9cA3HX765j//gOI4cRGsg8kcnIK8MILD+H66+/D0u/fpO0KxT8Tx44WY92qvUhJi8XwoUSW6fRBroU1azbj7befoYD1n42rrroUb7/9CfLzi/DLLxsxYcIo+u9imcQNRSjOJEIjyVB4Z50PbclDVscUYDljQ9G+ULAMBUOR0919xi78ALo9qK3mbonuoNJKwUgUvyHMIWE8Y1IHfsfZkl6KIWEbiW2Kz4RZhWApiT6bsCdpEuzrxPOL2IydQy4Bx2qh1bLZt/S0eCSYwoCESOzIITN9hCnpoKCiYGilJbLZw7SsBERwxlhFqRnl3+/H7c+OQsNmiWiTwAAalTzYuSwUZzuUMgXMVVYoTSrExuhhq2PZ38Lde+hrHHf+JWzHQs6YI6UikkMCfixGVKQBv/68gOvZnayVKCIvvwSlpVV4fvYNeHjKQgz84Sr6uUYVhYcmTMPU8U4s/vJ9vP/g92jdOwNX3tQDGz7fi0kTZwGYhc+/fAF1pXWwNdJTBl18nAmSzQ39Z9nebYy+uy8iDTq88/xyHEMOjpHL2uCbYd0Wa4Pb5IIzXoNDdScQQYTRK4mwtgpfbt0JGADn0EiUWNzIrjsKz7b9MFezmV9DsgnyIRHYtHMv4grImgGdkc0wh0ezY9Q0joHkKWEmdJnYET89uQoL3u2H75a9jIyMeCh1Hsg0CrgP1kAepkZtmg7NW7MSHJvFgapSNguvM7H1uozcvZm/RpISbFLOYzJ4y4Mj49jAhuhwklDzkujKcsZQdLrd3ln8WovNCzSTiI1hSV7H9BRvydDqHDZJUlXFzvWyVYwtUF5oCSg5jko1Qc6ZiZ4yOes3DCpCtYQ6kbWzBTeOqSo1I7YBYw+4nGzGvrKEm+zwOLavwseOrGTXoFTCB0QZbNa8cyfWzsZcmyxcq4GVr8/Gy4ASjOxclNSxPkqUg5stTui4CQxdt8uDpDXVcLkkRMVFofrXMpTFcmYT2S/RL/L+Ni7dBM2ROtR8fBjX3NANavmfH7hv+H0rcpx1MIxMR3qJHLO+WIrnb378T68nFKH4L8eePQeoGzNLKcj96Qlg09DS0OCiI6/b9MnpuRysf/XIrAHLMNYieUbqAhhD7Dvudi/KMb1MR+5yTZyqOePRpyEcaPbn3xbBZOrcuXWQIY1ETQW6dWtN/0lE44SGy7uLPl9A/1Jr4L77nqEGMq+//hQtQT2VNnEozn6Q64AYW8RERUMCe9a5hUkLz6WpPjovg2fnTYV9e8rx6aJf8OGHr1OdTcG+rS/cnip8umgJ3v/oHkx/aCG2bduD9u1bUhZvyxYtMX/ea9i+fS9mz54PnU7CHXcPw9Mzx2L8qJfx0gsfYep943DiRAU6dmzhxwRW4847XsaObUdpDtChY3Ncd+0VWPz5D7hvCmMYGwy6ALD8hRcfgFoto2AfYQe7PeXe9TVqEocPPnwcpHI3+2g+jhzJgc1O2HlyNG2ehMm3PAs9yRuIAUssk3nxSLU4YWFMvONmds/lmKsR2SIaQ65shx5d7sAtt47FvfdOpPcQ0Y0kZjZffvUV7pk6BNmObZBXyGDipjORGpZPVTnsKLFYAioial18fMXTG3GL2N1lUHFgX6Ng/YK432J1LOeqsPN8yuXyGqwcqGRl2MuOH+e/Zf1BRrjJ25aRjZrR91EaJg8j531JjTM3oJ9RIoaWd7ukclhdrGJod0UBfU3Us/UVW1iep5IrEKMzBLANE/RZAexIpYyRAlRIht3NXLZ3lLP8+QR3wq7l+VQGN5QlJdMifxTl03E6hvoalMKIjfVvJrUSy7/fhPfmL8fYcf0x69mvMHTQFRwcDu4LCXHBgdWrN+Kdtz9Dw0apCA+POGX5/qmCTD4tWfIzPl38LDZu3IOffvwFI64e8qfWEYqzGEw15PxG6LFGIwQ8hsLbgfbp1gS7th5HBB+MVx0z+0A/EeJPr46jX0bJS0i9+o0iBMgoPibAowANg0FF8TQVnxPQUvTvQiuSA5mqcJa8O/22R2UbuB6Ii66DfVfNHWoJI4zum8WK0ir2ADt+pCRAQ0QM+tu0ZQP2/ilpMO8txS9fbMf4hwbgQ/0xjBlwU+jKOc9xwlKO71dsocxVlUYFvSlQ5DuSl1e0i4tFCS8X0SkV2Lv8MKIUBjz50A1QKViS4vQIjZ6wkxKI1NQEqi0YExdO9VZ8gyT6f6q7dt24WzB6xAS88e5sfPzCSuzecRxvvH8rpt72Pv73xVrceutQvPTJMkSNz0LJiXJIcgmpzeJRV2VFeWEN7hlzFyzqfRR4VEVr4ewVBZuHpO4SEKVGmL98AAGuYlgCSYDHmkoOppNyXDmQQzJlLaA2cm3RMBlQa0NSogkufu9VlTNwzs3/LuJAeoLRQG8YUsbz7LNTkJrcCEq5AZJMgmR3w7q/Eml3tYQyRgs5b5PH7UFdDTu+ZUWs7MXDy5BVGv5I4cmtKJX2BxzLC3nZj5+mIYmailqcULPfy3kJdNNGDNA38UQyp5r9dtfOYzi+mwOANTwhD+6reP9QUWhB4+YMTGx8SXPqam2ACi6D5F1vpY3tjyEj2etEXc2T9faN0gKcpbM78gFGSTlloJI4cIR91qUrKwvq0TgzIJknQGlMmD5gECfKl/aXMUmHGA549m3fFCMaEyYGEOPU4skHP0X/S7pTTcbLhzyI4ff2wfADFdi/Mw+tdCpUaRSI6paEPEUdpCIbknY6cMkVXXHXhHspY+OvZDsVFeVwHq6B4tIERDVLwu/LDwEnV9CFIhShOE0QI4lDh47BZrPwcmRRGs0lGiQZJC/I5tWQCSrvE/2krxxZ6EiLZ5cotRagIFtWON26g4BGHyDo+1700+I1mJ3pFd32aycv9z6J2C8+IKpxgev1V3bau+cw3pn3OcaOHQaHw4GOHVsjOjpQtzgU5z6KigtgNpthCLPD6ubPUh7iWUWMYujf/JxXlDqx+NOf8eabM/y0Cv2vvcCQybRokBwPya2D0WikpivB0a5dCyxcMBvrN/yK+6e8hYzMJNx73zg47Aq8MusjLFs2H3ff/TTSMyLRtFkaBQ779e2C3JwyCjxOnnQtevdphylTZtL1vfX2I4iNi6CO3Yy96BvueiSLr/ybt1smseexVidH81bJ9J9veQLIOuCWagMc4T1wQsvNIoWOoAAPc61yXHl1T4y4eqgXuHe5XNi0aQcGX90BbQak4yAH/wQAF8Y1CZMMYSiVsTzPzjU0Y3mJNZGJISE0CiM1Otg97J628fPn4H/ruX5jOndqLrfVYTvXq69zsmUyOdDYJZ5VUqSamHaqQhZ1Um5MgEUSRhWbqD1aw8qdd5TuRGmuBQaX2uuEHaFhfdSuUpbfkHJ2EjFaDXbynEfJx30GVX7A/qeb2DWVakzG+mLmjr29hP2mmpe2m1RsWRvP1xQyGaK4XnaURhew/xLX/iTAKQEA35j7A3bvOoaFC1/BjTdORZ9+rfHJJ9/jf1/8TPP8mJhwtG7TEPfeNwYupwoTbpiB1LQkvPjio8jIYJPKfzbMtbU4caIEbrcTN918Oa4e/jBl1xr5JH0oQvFfiYun9iMUfzu69W2KvdtzIbOdeubyvxYEUPll/u/46OkfkXegBK/e+CkGXN/pn27WfzKIScvbLy6HPOXkpPV0UXWiGklJ0WfMooiKMmHr1oO4eezr6D3g1OXKZCB53cR+qKyohcGoxcofd2LHzqV44sm7Mfqa3tA2iUDRjC2Q8ixUwzR3fzEFHQ8eXE0FqElzxk7oDTcBECNVQIyGgo7nO3J/z4PBpMXVIwZ5ha3Jsbpz5nD63rbHJ08QivMTX8//FU/d+CF10xw3sQ9unDAE77/3Pf1u1cLN6DGwOd7+6g7MWngTvX7cXAdXKrUjPjEc3fs146DjX4uYmDDIG7MBicNsh8KPgRmKUITizIIwrgYO7EGdcf/tcTZJiDt27MfIkXfj559+xcQJ0xAebqKGNaE4/zF50uPUVOXPSAEUFZZDqVT+KV064n4+qP8UlJVVIz391HIhXbq2xthxQ5B9tAAffbgMkyaNwb79PyKzYQpmv/YoRl49HXfcRqpLgN837KbL7dr1I/r27UY/mzP3MWreQfBxognZuk1WAPPxfASpjFr86Woqv0M0HUW88MLD9PWnb7d7SRAXTVzgbK7Nmw7i6qum4fIhU1FXa8W8eU/DYrHi4IF8fPv1ejqh/vmXs/Dd97Mw5PIe2LXrKP1dVaWZ6jJeemnPvww6ktDptGjYMJU6xxMw3OVyQ/4XZKNCcZbNZc73v1CEGI+h8EXDyAxMnTIKD89dhOhL0rA6vxaSXQo0WBCGC2Lm2v/ZKUqrhQmDV/vHczK7URg4BJdLi0lTMckvr8dMRvjRiO14J+AlmjwRcxn6sYzMsrH3Wj5wjo5niRIpnd64m83WuXhpeFkFmxWLj9V5WZHV3xyHdTsTfu7cvwlSo5PxxA2TQ5fNPxAyfk04vs5D2vPdvG7AIsp5acqGEye8n01p0x4rclfjuLwcSlmcd+ZZLW94yu2oFPFY/sO7SEwyUiBOLhOudhKOHj1MZy3LKgpRWWmmwvl7duYgLT0ON998GeSEyUKuOzTF4hkTMWnvHOT/WOw1HyHx7dIPceng9kgwZGLVst3w1Lmgs8qpkYsxgoGqDl5iLBh11WWsBIp8X1djCWAQpnO3Q8FuFI7rGp3GyyrU8Ws8ISkqwKXwUHkF8nbl49Zre9DSJXqc+TG6ZfgwXNamM26c9jpaJSZg81FWXmOttcLA2XupjVgpsZy7QYo2mesYg1CjVXvFzGX8XjRFsn1slcKE7C185r1jQgLyeYm8XbgSarUBt/66Lfvp6/Fd5T5jGK/UAu9LOLOhdW+WJDZtmIxeKYy9sPFEIV2XxeqE0+3Bsl920s8N3Gl7WO/23vakEgFqP0F1wdZpyx0dG0VFwdSandelDdisfNsGbJ+STayMutTLvPWxLUTp+aYi5tBtcbDtxXEWSJzegENHq9G2ZQYuH3IlBg7sSUuaMjPTMP2xmzF23GVQyFnb1q5bhbrsaoQ3CEdJtA2IV0CeGospdyzAym960pIywc44s2Ai+q+//R1U7aPgybWg8lAdnnvqz+tEhiIUoZBh4sQxuPY6oimcgIzMRCQkxBD9BG/JtSSJ2klhtBI4OPGyGinfLLDEOjiFJ8YN/q8k5MIkwTvoEcY0ol9z+TExfS7W7P8+9uLJpbTBjEzBxmR9IntuihyQsy8lJ/buOYKx10ylf48aPYQatxFAhkmghOJ8R0SkCRt/34X8EwWIjDPWm967uCuyUcXkVvbs2k3zoJoaG2JjjAEs3PpCITPh6acfxGOPW6lup5AaINdOZUU1Dh3eh8rKGlRUVKKqyo4VP69HTk4h3n33Kei0vonmxo2y8MSTt+GpJ99C7x73oYpXfzw1YxYef/x2aDVhcDmBvLxizH/nK/Tq3SLgymT/lwcYmQjGowh6T/LPfGZN4v5gOaeMP1Nr7Cdg5SXQsbx82KjSobKmBm3aNEFSIjGW8b+HHDhw8EcMvfJGVNTUIVqnD2DviSqLw9Xl3jxB3JOijFglY68ezpIsrDMjhq9HlE9X2Nj93z8lPeD8/ZSbgzKrLYCBeFkaq+xKNbXkJ53fz6TqhbNCSUk5iW2lm+irYE3+VsDKqbsnJUElU0AtV2BMY8aYtLhYGz49xHIjLc8RyfbFvoncqiFnXVbaWNtKLCyHz6utweGqqsAiOL7fUVwzs2U0c7lWK+SI5k7dYSp2PGQ8dydGRHm5J6BUKDH8yu6YdPONVBbCbndj0CU98cIL02Dgxot1lmo89cS79L3baUB8fBQ+WDgD0x+ZA8kjp/nYX0FZv/32B/To2R615jq8MPMr9Onb5W9NDociFP/WCJVah8IbKnkaLrs0Ddm5eXj95e+QGa/GUWEowfXSYPcEDvK9eaV0com1+E4SAAF/cvjP9LkFSHmK2VaCEgTX8ojfi+0JAMLioumtRNLyaDlUkhxNsphWSHQ8G6hrOABQZbWhgpdoOjioGsPdalMz2IOMzIDp+yZ4gcdNqw7ipbVPQiELlQP9E5EVn4YnZozH/F9+RXJYGBwWJ+QqOYy8ZFXEwbJS9ElLR02RGV+++StaNE3DPXfdCrlM502k/B3rnB5W5lHNnQDD1FFITgOsthMoPlGLuHhW9qFTNsPNN0+HyWRA/0HNKDNyzeodSGoQi/fenYXkFKEjw7aQbuyCGU+qMXHCIzBo1aitYQDTg/d9gCFDBlInwFdffQrjxt0Nba4dSZ1SceAg08exWlg7a7hjcbiRDeZyjpXDxIG1+BQ2CHDze8hqtgU4IGt1auzaykrK9VwX9ZJ2LCncyxPHWocD6qwIfPLpb+jQujESEiNh5Ho4MuigVhlgdzipDmH+cXYfnCixwsTbkxTHtRz5MbJZ7QEl3QSsE0wKBQdERfsEwHeksMRbll3AHRybxbD7toFBJJDsHu/TibW/UdNkWPnvjx9gSapIBRtkMmCweSLTJWoSFUlL7kkMbZgBR50bFWY71BEKL5goAM4wjdrrGqkJKncXbRCSDNmVlUjiLtNd01k5diJvr1ivi78S/Urxe6HpKACGCH79pkdEejWL2j86ACeyy/DcC7NhVhzBoo/XoTS/Cs1aJKPcXoDrrhqLiMgwGP/P3lXASVH/0bcd190Fd0d3d0p3gyIgSoqkKKGIYCCCqCCilEiDgqAgDYJ0N0fcwQHXHdu7/88vZu/26OYv8z6fvbmtmdnZ2ZnvvN/3vefEtpPypgGRN4xo/nETLN5xELIQGYZ9/Am6jmyEduHEvPzuEEiDs+eP4NLF6/CNlOObqX/gsiofXqUjkLH8Cga8MxTVK7J0dBEiRDx6wMwXn3+Arl2H0PvnL/wJGx9FIwQikaE6kIZ2aw/Bv7FQF7yQZs3JB0Jl3A1kvlY7CSm8Vhg0FgZsBf/GwoSf4/yKkqCOzxd9bVGZtqSQ9LuA3ClRssBzds3qTZg6dbS9017E88fPP3+J+vV6IDgwHAZDFvQGExS8xhBIHo2cnWcsJmesXvU3li/bhHnzPoePN6uVHwwJPDzcYbO5IeF2Mvz8vO1e24t/WYPly/9A23bV4R3oioQEPZKT0/DFFx+gXr36d8ypV8+ulHj08/ewE4+/rd2Kt9/uiWIRbqhWrSKqViuHo0fOwGZxot2c5DwnEOIFxLvVgZgvSN42FCLThSlXghQRCbopnWDlv6c8M6u/so35CIj0xKWL13DkyFFUr1qfnvuZvYJg56SEl9IJAZ6shtPIeC3HCb5kXZpdNu2iYORUko7VRlo5Wxe1jK23UiZHnoktu4SHlwOBeT4t2UHCXM3PD2dSGTl5LIkNfG6MZZ19gc7svpoPAJTz8rUPPMRkMNXL2XQ2vZye4VAL7bxxA245SpjM5B3ssWw+oJrDpdEZXElnsFjsxzgXLseO5TbalXzYfiYMVpN1zTEJ5Cd7TTgP4ynjyfY9X+4hqZERwpi9SCXj1wR8OeS7btO+OkqVDsf8nzZhzdrVSEhMxPZtxxEaEoCFC39Fo0aNaNe11VpwPGzfbijGfvgGGjVsgK+/Hou33pqIKlWj4eHOBtwflOy8du0mtGvfCD/NW4nTZ87jm29G4tixi9Qn/b2JoneNiFcTIvEo4g706F0fu7efwbF84qnxH5MDPCKk6oKfSKt2VWnBJOLFgYSNpBxLRMa5VEhVMtpFV2VETcg1CuTcyIIhSw9dVhbiU+Q4tfYMxgxphxo1S9p3YzK6Hht7E7GxCYiNjYebmyuiS7kjLjYBmzbvg6eXM4pHhODK5VuIi0ugBWNgkBfcPZwwY/rnmDnrfSz99S9s2XQclaoUp8bfW7f/ALn07mQ0MeD3jPCAi58LcpPzUKJWOBbM+ND+fJUq5TDzh/4YNWQBMvbfhrRDICS+auIkDmlcPmTucljcCy7KZFkmSPKtlOg3q3SQ+z75iKk2yh0RCldMHPMrJSs7dWyKipWikZqSgZiYeNiEwQERzw1E+h5VIRg1G5TAHysPoUGnisjL1mPbL4ex86/TKF+8Cho0qIpKlUrh9PkfcftWGlq8NgFXdjMDdksxLdIvZCM+JhlgTQ/3hE6nR5eOTAJWLNof741rg4ln9rMnJUBk5ANmIEKEiPuifPmS+OGHKRgy5CN60f0qK64IEVQYJHBDxIsDSRQ3GIxo1/pDyOUS6HUmjJvcFZWrFUdaag4uXrgJBZzpfvvXn0fh7e2B2bM/gZwTYOS9cXE3ce3aDVpT6fV6lCwZSYM6fv/9bypnLV48DAaDAceOnYFGo6FWM/v2HcbpM3+ib9/OsEkyaUJ28RL+OHPiJub+OAHly1W95zqPHv02duzaCR8fV2Rk5GLN2jmIiGCqBh8fTyxY8DkqlG+LcmU7oFOnppg8ZTCkEhmWL/sTnl5uaN68tt1HmvjsHT16DmFhPrgWexONGt07mfthIZNJMeXz/li+dDumfroCLZrXQ/MWDWE06pCYkIqszDyYBO97Ec/tuFOyVAh6930NUyevQI+eDTF9xkAsWrANs79fjbjYVHw9Yzz1XLx4aTvM1jS80etjDBk0HRcuNoCvnxf69uuIuT+sxPjxwx+4vH793sfZs5ewcuUG9OjZBqPf/4TuF+SaJSDQ+7nL/0UUgRgu88IgsRV2e/4/RXZ2Ntzc3JCVdRGuPOFKxOODjPalp2eiTfe3cUKlg0ErK+h4FIadhMpZSLsmJ3FBai3sUYKZs0BcWAolVwvdRLxzyj5YLnRUFpZVC8vmHVP2DkeSYl14eWS+UjImKUGdMuHIVBdIQv28WMfj9XhmUJyWnI1cHoaj5N2Wnh48kdeXvVafzzoG3I0K3JzNJJnEn0/EiwEZkSbeKPn6m9A6qZFhSMC2TSexfPkeuHk7Q6KzoXi0Pyyw0lHixk0roGrlOtDpjNi4eTOW/bINVjnpFPREujPg5OcEY64R6XEZULmpkButgVVnge5WNmReatzOyaHejM7rEtFubCN81f9De/dJTm4mNm3ajdKlSqJcuRL3lV5cuLwdP/6wGX9vOo5BQ9ti5HtMZiaMqhv0ZlSo0AKNm5fH6Wu3qGxWkmFAeGl/xJy5Ba2rGrf9JbCk6OAcb4R3oBviziXAvWUYPKsHIDGDDRenJRQkmRIkpeQjg9sHKLiUuHQJRpw7ubHfhZsLN0m32RDm5o68hFyYTqUi7XoG8tUSKN1ViDVkw+qnwk0SNkVA0ut5SrQgIfd0ZdtFy4l6wb6ALpv/TuVCOA0/5TjzcCBBDk5GgW8kMdnhmlHd7LJjgoVnz9GpO+9MdFEqEeLCnovPYV0PN7KZLD3cTTC7L4Ag8/FSq2DKtyI9Rw+5m8weJCNIfkjXpZwf24paMAkdkEJgzr+3btv/L+7ubh/Np9uBJ3Yn5LHPE5eZATduOi90I5TnyeKC7KhOAOs0zTMZcTWLbevSnh4w6Iz4ddo25Gbm48NRnaHVqlClQkPaMUISakmn1IULV9Gxw1C89XFLrMljkvgyKWrIFFIsHPvVHduDmOsTZBrP48/1R/DLzsNwDXfDvoxEenz18lBjUM3qWPvZNuzZtOY/LYMkF80RETWQlZUFV9eH9yz7r0Osq54uSKk9efJM6mf43gjWhczOJ45yZJp0fY+uQ6Ejyp5mzUNqhLRrITjGYsuyy0WlJHmsUIeXACHduiD1j72azb9ItzcUuHLlNiIjiV9dQReR42uLhuSQ/iNzkWWwz2o0ABUrMA/hS5d2vvwGcf9x5OQwn2ob8nH7dgoGD/wEteuUw759Z1CnTkXIZCqa7hwUFIhevdrRNPIDB49g+bI/cC32BiIighAREUBvao0cFy9cR2aWHh06NICPjy9NiCaekNWqVqLe2IMHTcbt20nYsGGBfR1I6MfhIwdw/XoaunUjgSz3PueQMKKNf27C+HHf3rMuHzJkIs6cuYhGjWrj4qUrqFSpNGIuxSI8IhjHjp7F62+0hV5vwPp12xEVFYYzZy/B19cTCxZ9TLseCWzc2kDopJNLWEehfZ1tucg3MyVIhpH9NjMN+Q6diRK9BLu2nsGRvVfh7OIEf39PBAS6o0u3+lDK2fxkElY/CMu1Ig9GC+tAzOTzFbpPiZSbQCn1sQenCOdzIVTmdh7ralTytGt/LbPYUUp9YbSyLsg9t2Po9HgyW/9UHfusidzuhqg5QrmiIy6btyRyCB2JgiVOttEAjxw14COxBxKRQD0CC69vpIUk48L7PXkgJKnLCIq5uTpY02QZDPbwGA/eHVnGi9VNHioX+37D3sP20cLHNntwED++CN8jub9s6S4s+OkvvDf8dZQqVQw+PkG0sUTY78wWI8qUbk7/P39xPfuO0/Px3rDPsHz5bNwLpK7PysqhSqbhw19HseI+CI8gtR37HP37fYXRo/ugQvkq+K+CdHu6uZV8KWsqoa5B3yqF7OCeEwiXsfjYS7ldnifEjkcRd4AceL08vfDT7EHo1PtrGBu640Yi9yHiIQZ3yJ2t0kKJ1zZHwrHoFTyRfQrEoqpIurVwXyA2CZlYtD2gKOEorBOZJyVYJDAaTNBbjchMZ+udwyUZ+bmsqM/KMyEnj52kXZxYgZCVxZ7LzWEnfyXxobTYkLuMSXEdT2TiT+d5g1ykKRXkFk3ve6k1aNbQG99M/wOpKTn4fOYbyM8zwJIlRbk6wUhNzkbr14cjJzkfSj8XOHUJRb7KilhCaLk402/SatXAECKhojTqkegshSVYTUsEU6aNXod5V/XHuVvJsNms9l3Rxdkd3bt1eKj1LhXVFN9+0xSWGTraQZluOOZQiLmrK9sLZ1JEbd++D5CY0LhxDUBixsGDp7Fu12YElPLAOx0GwKCIQd9us5AboUVqbh5MRrZPqrSsMNPnsf04Iz7H/tsx8UGB2OuMnCxRUungLxjg4sISo7XArUAT0d0g9gbx1jEhLzmP6IMJI1b4y6AQuiHT+HFAxqXXhX+ygtTaPlahYcsWOg5yuOXB9Vu59oTqnrPW0Gn1mqzb7o8uveh0320mCzqQkIQOEUx23XzJYvZ5k1lxfNydrUOtMiwZOtjFBTn8c5KLf4veSg9NEqvNXszrzBY7CajlRa9ARgqHJiFNMdfEByxkMntqdSQ32RcSLbPIlTUt+FlhnZqfZy+mTVZBKsXuNwtl5vOCT9Pp1CS4cOmhp1qN9SuP49z+WKz/cyJKRTUpunvBZrOgZMlwuj0zjEbq8Wmz2KDJsyAkquBCyWi9ik+WrcT5PdeQnJNHv7tcnQHmFD10DT2JaS70ZMOYbajlEog93x6ALc/ynyYdRYh4XiDH/okTh2PQoAlY9/sOdOzUmNcTjknCApF3p6eivIBwFEgZPohjBff9LeSlKBxwBTJSeI4kuzqmUpsLyEP7cbtofXNvYrCAgBTI0ELHi3u0NXz22Q/2/5OS0kQlyQuGC/ckBlwQEuSC0LBg/P7bHnzw4QBKysTHpyA6KhxBwb6YNWs+tm7dCw9PV/Tp1wDFq7Nz0jVSP1A7eDMiSwYhyp2QXflQqlJRoSY7P8oVOlisOnTv0QxLftlABx2F8wupE2rWqIOaNR68vkqlEp07dUCnjoQElVCivfA+SIinH36Yan/9hQtXcPHiFbzdvxftiExISKYyWE9PN0ybNh7R0RGYO3cJPL3cqf/qrXxWZwgyapWUnY/9tT4OfpaE6FLJeNI12DWGq5LVAPE5bJ3cVWrUaFUS3bvXs0uAldJQ/n7htyhx9JCE0l5bOCvYQKKSr4Mw+J1hYLY8JNHazFPHhT4iVyWbr4+a+VxLJUJDjhUqGVt2i1BWR3uqWfDVlutsOV/WbkmnJ9OuwlfD9ossIyMl99xkno6C/NnAaxq1QgGlQQK5SgYLXwdh/QUCUrDWKVxbCY8Jr03kA7WVfZmUOczFjUrJ6XaQs23jrvJy2A5WGx+okZCjWNHgSeFYyo+xfN3OnYvHl58twyefvItuXTsXeQ+fnVRPScktW3ZTQpjU5sQ71NGX0YZbtxLx089LqZrKZCahMSakpmSiffs6aNy0HD/OEjLSjOHvTsfNm8nIK1xLi3iBHY/PecBLHF+jENkTEfdEeDE/mCu6QXEiGwh4RXeVQqTpz5vee6GrIuJOLFq4AXV6VIJHgCsWzt4OX383KGwKfP/deqi1SlTqWQ5BJfyw79JNGF2sxDn6kTejWwkvJB8qCKx5XDxMqjYpvps1q28fwSZ+pbVqVYCkGCPVSFhIio6kpaqQQ8g+Ua3xn8a2307g4smbOHLym/v6oCUkpND9Kzk2DRmrTkPqpkCMtxs6DCRG6MD167fw2eff4bY+EzU6lsP+o9dgyjHCLDdD1cENKV+fhjVABWWYGt4Hs7BfkkpJg+mz+z3HTytCxH9f7jdr1kfo0PEdNG9RG1re0f2qgXg7EixZ8o1IOr5kuHjxKrKzcrF123x8+umP2P/vcQQG+mPWN4tgtVrQqXNzrPvjW8TGXUCx4l6Iz2Pe2I8C0mFILG9u3kx0SH1+FjUVQalSkfQmICDAF8OG9XV4DelEzuHqCRH/XSTcTsOgd2biz7/m0pTp+2H9+p3o2qMmypTqjsjIYCQmptM0bALSLTt//kps2fIPhg7tQQd8T526AJVKjtea1cSC+b+hbKnXsWTZR3irz+c0xZqgWfO6qFat/HP5rCJEvIx4RdkkEQ8DZ0VZ/D11CMYPWwKn+DQ4FXPDJWsuDL5K5N3Oc+x4LKzYF2SWXMpcEEQjKdKZWFgmXaQ7UngPuSskYAtdkkLCtjAV5iGXQKFgqdZZ2UakSvSQ8WU68YO+IAFVK2Vw4rJQwSBZgEajoJ9BlWCE6UQGylYLx5SPRyOqWKjY6fgSQCDlTsUexo6dByB5qzgk8mzEFCcjn3q4ejjBqWwo7WI8psrBiSu50Frk0Jst8OPSEUFyQboOg8goNxmZ5Z1sVzO4tEUqgTxeB312Kt74qDmVFz0JpDxEwE0ZWSQx8W6v1TqM1JbyYEEpZPQ03ZADhVqGnNvZkFk1SElgI+vx/DepESwOSJejCzcgzzNDZrZBGXT3z2CxWZHEpdpnD94qkFSzJ+98g2CrIPx23FgHgJ8fGyE3Gdi2JMWWUqVwSNuWK3lXghA6I2Wj6f4+GiTz372Zz/fQwTg6jT4znU6F64w+rWvhx7Osc7Rx2RL858+eVHBJdBj/rl8LLYZfLpyxdxlapFbqFa9UFoTLCF2OguyZrgN/juw37KMK99lnS8jNQdz1JAeJdUlPJmn65cBROm1RgXVl+jo540o6kz9V45LqdsWK0am70rmIpEqCcty0P6OMDMd2xGDiB7/j2+8m3vW7I3IvjdYKi9mKf1edhFIlx6SpPdDxtS70+c27lmPqR6ugi9Yi63gSLh6Lp4dSq7OcHiuhJR1PgDTBgC5loyBtEYYpH39Awy08PF5dOYgIEU8fEjg7O6Ntmybo3GksSpaIQPUa5dC+fWNonRzDWYoGx5Aux4IkXpNDAq09hZd3PpL/Crp/7D429vnYuyIpyDyUDp1cBYqOwucL8r4HEz0F4TgKe0COUKSdOHEBCxesRnR0MbzxRgfUqFHxgfMT8fxgtujx7bcLMHhoV7i5qzFtRm/6eIYhFb3frWQ/B17KOYprmRlIS05Hko7tc/m8fiK1BMGRJEZIOikUqOTN6hdnRQ4yMnIwYMA3+HLa6CciHRnY/ij8LgqHGD0qnJxViI27gWxTPDsvEoJSG+hQh5GAwsJYvmwL2neLdvjc+bwbUOgK9OFKBmdFGKQSZuN0bxm5kLwts3fy5fPQGh3//Ros7HebzbsQSYepUIYJigsPlbODhFsIsCLHBaHuFOZf0p3VI9tvsA7KJZcO0WmuyYQsAw/g5PVNGS/mZd6heBSdLjp/lk5dlQpkkIAbo8XexSikcN+xnRUKOPGwmzyuIhHqLvIc3e5OrvZ0arWMbXO51K/IcUuo4YV7RntAVwGEa8QCP01nFzWq1yyFEcO/xOzZnyIiIvSedRVJoJ4xbR2937VbM/To3o16l+oNOrRt9zbq1imPjIx0TJ/+M7Kz86h/aG5OPpo2q4yzZ1ntOnfOn2jZqgFaNG9E5f5eXqxGFPGCIXo8vjCIxKOIe4IUn9G+9bF2VX1k5cTixPHLmLP4Nyjy5VitNcJKJM85Qgs7vVJ3JBgFMlIgCAWJNCFGhMcEUtFuC2RznJLnhfkJU/vey09s+cL8ZZDLmMdjTr4ZGVYjpPyslM1b2wWyUaWUIiuXrTsx/CXwdmMnwxaR0Tgw9xA6NquGXuMaIDSwpkg4vgQw25g/58GEg9j1xymsWr4fnm0iEHv2hsPod0ZaLnR5rAAJKBsOovxykSph1trsJHO2gT2fmpEND3cuJ8lhBfSFGJbcF0Bkwwop0tJzsfHPE3izXFW4aaMcZB4CmXg3CBeDJisr6BRcXiPjxacwvR+E5XiqCozWx63cglsZmTCVd4cpz4B4IRKQ2yHoBHaO7Pue7H9nPeAdo0NssNZBji0Y/WcWMvyXeLKLTxtP4b6rXk6odIvU+VIumVFpuEyZfw90vpxoNOoKZM8EOfnsPvmthvqz9TPyAQ3/IFY4q7mMfP8+IpQHTiUlompAoINspyhu8/ToK1mp6Bld0n5xkJ9jwt7rN+n7kvJ1DsQjIRAFCTwpvAn2XmPLLBvICnQlX15yerZdup6cdIJO//XhvpPxjAyec3WvfX2EY88Vf+bdVDcw0JF45Pvk7bx8OPPCvHqNaFRfFo1xw9YgJiYWJaIZyeqwzSVauLtpcfTEfKjVSiikTF4Vl7IPyxbtwpJFO9lAzsk8yI02SDVyNGxTDkd3XIJapYDtn1wM+qQvunRtALVcDJIRIeJZY/jwt/Huu/1w6dI17Nz5L17v9QGmTh2GsuXY+YWgIFm34BH7b14gFSUC2ZPjIKO2SQyFJNCOJIc9vbeQ31lRSCRCkrbwnJkO+rDHCxK5HSG7gzwpHGA1ceJ0enE+YEBPVK1a/qG71UQ8H5w8dRqffTYHVaqURrXqJDhPhzwTO48ZLWw/yzOzc9Sp1GRk5OiRmlFwfnfmvsaBGjbgl8ntRtyVKgQ5MeLRZM2DVG4CKRO2bduN4OAABAX52QnvRwGpr+6wHriPL+T9QLzD5/+8Cj/M+xAmazYCtGH0cYWUBdYU/S2R3ybZp6d8Ohdlyk9E6TJhsNqY1NzMCUgNlwgL0mOzLR1KycMP5Fn5bzpdn+tAzgnekYK/NCEefbXO9mRn+hxfb8EDtrBXq5Svg0DgaeWM0KvgwyTMR5KS7ccFYd0FCvFiBtsf/LVsEPXNkmxg1WyzYHfeDbj6q3Akkb1fICDJAD77PLDLsusHsVrqZArzlzRwy55AJycHH0uN3AMyvr72VHJu5WCzOfpvkn2I7LPscxfxqJXwmtZmgouLE2Z+8x42/3kev6/7G6NHDbjr9if1+a7dv8AmyYFGGWLf5zZs2ILp03+iPo7//nsSKSmZ8Pf3QtmyUcjPN0Ct1mDEsO9Qpkw0lv46C558MFqECBEMIvEo4qFAErjq1iuP/LB87P7tJLw3xiE5WvAnefkgnIweCVYbJLf0OLDnEGoNroGRHdo+i1UT8QQ4eSIGUycvR3T5IAQOKcdSx0+ygu9ZwBKgRvGmpZC69yZ6dpmOCuVKw2A0IiqqGOrXq4qyZcvaO/fuBiIlWrR4ObKz8lCxYlW0atnwiQoRQtbd+OMywruWxMVMRsQ+DLJCVfCOyUfYjjQkVXSFLdAMidOrfPj//7jozczIQ26OjqZibt68567EowBCOhbGhbM3sGQBCW4AlG2DYdzEOlkVXmpotEoM/qwdIgK9kZ9rwGuVmSRbhAgRzwfE26506SiUKl0MzZrXw/D3PsHa32ZBo7n3YNaLxN0IygeBePglJaVixIjJaN/+NfTq1UEkHF8ypKdnYcaMnxAXdwOfTB6MkiUj7qvGeFJonVRYtWYqtvx9EO8Nm4qAAB+o1WoaDFq3bjXUrFn5vom/JEWbpGWTVOxSpaLQsGFNlOWqh8fFqlUbUa9BJQQEeCNN7xikci8Iv9MeXaZi/MReCC7jhrDizANSxMsLUkOfPn0FjRrXxE8/rcDIEW/fs4Yn9jYWmyOZ/f77X9LpzFmjsHjhBiiVcqSnZ+ON3hXg4uyKTp1b4Pixc6hR878bHiNCxJPgVb7yFPEQEEYUhZG/VuEd0HxEW+z+uzu6tKmBH5bvhcxkg8VZDiiKBM4IEk2F0LEozFRSEDxTtJYVRsEF3rDw+cAeWiN0RfLHVXzGShmVUksF6bbZAitfjpFLu01mPhqpksHA11MtSDSX34JMLcf67VPg6ekCtayMuI+8RNh4Zitmffg7shq4I8Vbh6xrvMtD6piaTDroXHlqM+lslJolsBit0MstOHeKyR8S01jHnzHfDC9vVkCm82ATXGcjzAkZ7P66lPN0WqG5D65p8yFTSmHMuoLNM/+BIkuK5Ss+h1YtSKELZBpjp07FmSNxUNb2gypKg7Tz/2Dh6lVo36Iq/ALc0b5VGygUcsglD1+s/rVlNZINOlw6exUW4XeQWmCuzRfOpmS0OpennLqpcLW2G0KPZCPgWDaMx7IRW8kJpeowqZNSoyyQQvPtaBJ+m0JXsvC7LrwMQefCf1e3bmbaf18EKvI707EOGaELNZ8ERpHn+HytfF5OGjn8Q9iouzeX+Obo2Wc7fyreYblE8iV0zMj5OghBMYIcTJBrkxF8YWQ9z2SCVWeDyWCBVCG1v0aQT9P58CI0nac8piWyz7SbS9EVXCoeez0TOXz7Zqew9UxI1TnaTCjZvBRqOUx8+73RknUJ/JuQ4CDTFmRGpHPkenY2bl5Iwq8f/kW9Sjt3r421K/6lHSKdOze3d8Kyr53tv3IJ66AUEFkuAJVrFMfxQ1eRrtOjdLAXPps8AGXLFINGzb73wvMRIULE8wfpooqOKo42bRpj1aqt6NuXpe0ajDlwcdEWConRFQpLMNxpcePQ+aUoVDwJHUHsuFWQNC1ADnBJtHA8KOjsKpxGTbQksofoKiso6ubOXYrvv1+MxYu/Rq1a4oX4y4ixH0zFa6/VwaRPewESIyy2dOgtrLMty8gISJVM4XCeJOcqo9xMJbZV/dh5x0/DZLgKKe94NLCBURelBkoZs5eR2xipZ5FmonXbqmjaMgqXLt6CSuaG1NQs7Nu7F9OmzcWUqaNQo3rlImtqw+HDpzBp0tdo2qwG3h5UB9euZmD06Elo1bo+/Py9UK9OfQQFkVrs4Uny3Nw8LFu2HstXTqX7t4fKF3IpS06+V9ewcP/c+b8wbdpP+Hzqcnq/UuUSmD6fydNzuYxYkByz90geKqSSLFewKfDXsu2axyXXglJEIZXZ05yFDsGC9SvqBy1YMrBn6V/7tZbFYT1NwrVZoVqI2L/QufDXHOZdkadSU+3Be8YsC6SqPHtQjKJIKJ1Ql3mqVfDj3rYtwpwdaqBIN1YLa2WsfpdLvAt1bQrryxUzvN6T2OSFbCaEkB3eLW4/rvG32myoUGYg/f+TT9+mydVkUOTLLz+AVqu9a5ekXOJb+FNgxMi+mPXNYqjVMmidnDDr2wkoVaoE9Q0V9ouaNasX2f4iXjrQDv7nu0jb/0e/wzOHSDyKeCSQE6VcJsfwQS1w+nAcVL4a+B7NhovVCkOgEpZIJ8Sl5BdExxcGJzYoEWl0JCzsJKJdai3IRWXkzOI4H5I+TN9bJAmbPJWup+WxjcgcSNqvcA7l5xQ3nmDt6qxAGvew83RVQnYlDxWqRWDSzJ4I8Kkm7hUvISZNXw9pGS0yiNwn0WAvnIRdRpDsBgS4wt2HEVfXLydAbpUiJVaHFEsecDv/jv0tLZ4RjXc0yWbyizsu0z9ltuIUmKefitgFuAKt/PzQdeREjOjXFMWi/BHhziTRZlsqNm0+CbcBJXHpfCKQzlKmNVYrYg/sh+yWHtPmb4LSU43KoQFoUL0UqtWKQph3Geh0Bixf/xv+2XoWVthQs2EJSNwVyMsxYN0vB5DoBJiv5xT4LLpz8kg4i5L0GQIvNTEaYv/rLLQkiy3NClRtngUWixWJiYy8zc7Mh7c/kzUH+rDXXBfmw4lD+2+18LYSCEhOJmZxIi4ty2D/vRV8T+y1mVyeJeXkpIcL+02SLjy1Eyv2inuwYttdzUi1q+e576Qgg87Ohy1QICEljgmUnDgVOnSIvF7KV5hIqi1yK2QWCeRyqV3iI5CMSXl5BVJrLhXz9GOS+HOnbjkU5rlk/+DLCi/O9jdnF7btcrLZ/FIyuE9ThtHue7n1BCOyq5WMYNuM+yhtO3eJTsuGBaKUpxclHT2D3NBsSG0sm7CZPjdh/ExUqumK4kEN7F/FvS5ewj0j0bpFPUo8uh/IwsAPuqN6lTtTsUWI1aCIF4/eb3ZC927voXv317Bly34q46zfoAratq+BevWJNNkKCRy7IQs8zQRiQUi+VRQkVdtRlEwsgPDae/kYU39JSnTc7bdyd3XJjRu3sHnzLvz++zwqOxTx8uH8+cswm3Xo2KUydOZkezqyzsL2K42c1Ra3ctngW7KOEZGlPb0htTkjPMILSml4EXKO7SO+GsG2o2CfkUk8HNOc5UD5suT8KgPpWaxbrwK6dU/HB2NnYfiIHihfIQqe7qF2meyhw8fQd0BDNG9dGXKJDOXKVEHF8mVw7vxVmjjcr98YVKlSFk5OTggLC6bdkCEhgbT2OH78LE2yvn07CSVKFEejRjWRl6fDtm170aNHW7i5MtJLIXWF2SqoSQSSj0mDTVZmkyKXstfKZCqMHz+M3pKSknAzPhEBWibLdVeyeuFKFqsZk3S3EaB1dbBKKPBAdQT5PcokTBnjzAckneSsprAKVgn8Z2e0mqCVe97DO9JOuTnMm0EYZGBTN5Wj3J14ZRNP7ML+lYLcWyARBbirVMiSG6CQy6DnJKJWsLDiNZwAQlon5LGau5qvkO7NXuusED6H2u5lK5CIRescwarIfjyzWWFGhsNrZYL1BN9ms2aup9Nv5wzFkkXbEHvtNr3VqVsB3bt1KrLl7vbdyNCtWxtKPA4ZNB316lVD48Z1RSsuESIeASLxKOKx0LBZOSxf/A9kARYYXWTwqBGChPhUKHanAoTceEn8e+RGK1Q6KywyKcyE8HSx3XXd5Ffz8N7CN2kwg4iXE9YcMxSl1ICJE2IvAUq3KYlre2Kxdul+XItJRERoGEaOehMmSwZsZjJqXWhfk0igc5HBUswJlnAt/AL9YTVaEOUfhHOnb+CXn3bC080DaWlZqFa/GN4Z2Rx6kwmj3pyPmq1Kw8Vdiwrdy+HI3yy45EmQ7/p4Xkginj4yrmcgPzUfNhXr4jRk6DF/KOugeOu7DpDKpPhu2zDs3XAa6+buo/LFh0XVqkyCpg13RfOWRTtIRIgQ8bLAxcUZrVo3xOrVW1C9ejnUrVsJb/RugxlfL4RKpUCNmk8mJ32aIAQOIRO1Wg18fDzotCh27jyANm2aiqTjS4zk5FRERTOi7GVBZGQIho94Hf/sOYrZ368GsZd8s09nNGxYFWdOx6BdiXIOrw8LD0BoOOtKa9emNdLSM5GfZ0JMzDVMnPg1MjOz6Xk1NDQI3bq1RlRUBPr1G439+4+hceNadP/s0aNdQRDJY8LPz5veLDbWLSrixSE/T4+//z6G15rUg7uHCyWe3+j5GU6fuoo5c4ejXsOyaNS4Iq5dTcDbfWdSAvph4eSkRe3a5bF//2mMnzDkmX4OEc8O5Jjw3H2GJUUj415NiCyLiMeCr1Mg3n67DW6tXg9lFQ+E5isx8MPO2Dz3X2Sm3oYhQIVsQQIqSEI51yFRSGETJJr5ReTTRaXWpGtSSLgWjhHCfTmgzrEgohYzR05PyEOKzoSg4zkItCngkiEkPJKkBTbiZVXlQVfdDbKYfGKdjFxvBQJJiEiEE64dzUHN12vfJ3FOxIuEjHT2ZZsBfo0jyOaF4KDcJFY8hIR54tJZNtqcdCwFSqkcbjI1SVS530DwvSFIjG/wzkjS4Mf338/mbqFTn3AXoLIM+V556DpsPNw1GtwuoUHssXgYrnDPIL6+8RlsBDxewkbVt7lehtJXAxQDPOVpsIVJcSr/KuavuUpPjE5SG1ZfuYY8HwVw2lQQzGT/XfHfg4btt1of1lUQWcwT1+LYCHDuRe6DKXRJ8qCnFuoAnN8WA5NKgkxNJqyV3eAX6uVgCn7tbJqjpQHd6EbHjkceRGMSXsN/o0RWLQTF2DsmeaeyVc6mzlo2ou/u7WqX9ggFgWBuXq0aC10wHoih0xMnbiE7nX0fvsFsfUv7seOAl0bjEBhDRuuFfYWmOZPtRu5abfYAmfOp7Ls4e+I6tGr2GUKiWZeDRqOyB1LRj5rJu0glErjzQKpGtRxtGW5k8YuPczfp5HquCVIntUOnYyU/drF06p8zOLDyONsG1f1x9PAZSPzUkHUIwoxNe2Aj3aRLmdQ8KMQLeQb9A6Va7CsIQInoAJy7uJbdl7DtJEKEiJcPpO7o82ZX9OgxBF06t0RMTDwqlC+P0WP6YsnijaheMxIS+++eHXe4sYw9VAG8s0cmcYatyLFB6HSS8iAPezI2fbzg2H7tWjw83D3h6elOZahKpRInjp/HyJGfIT09HcWLh+Hq1esO8x47dhAN6SPd+r17d4KzsxavvVYXo0dPxeDBbzyT7SXiyREQ4If4+Nuw2rKplFfobHOSs3OVi4KdU69lsxqggjeTVQdoqyE2PREqbsF0d9z7ol4Ik1FK2bmwADZYbfloUL8mqtX2JhUKUtOyMW/O35gzZzHe7NMcTRs0pqF4MqlXIfsAVhOFhMgQEsK66GrXroK+fbsiOzsXZrMFnp4FYX7VqlXA2bMxGDXqnUJLFpQSZGpxCG3KM7JOx5jMJAdJsIeqnP2zCKXkwf1XsHHjTqxftx29erVGgxbhKFchHHE5qbDZLtDXBDqVYu+xCR3LVocUaroWEheH9GkbT6y3d/NJ2XekkKrtnZN3XrvYHvidkO1IUNefDUyGOLOuzBs52TiTyr53oU5Scnm34KGfy5PMSVCfk0IOtVIOi4E9F+3OtnetAPZ96Hgw0fn0VGp5Q6C3cNWZSgjdEeo0oePRXCjFGg7PFcjJhW5vg13lQgJfJn+0jN66dG2ItWt208d37v4J/v5kvwJatxqK2GvM7sbP36PQtrrffiuDWqXBokWzHvhaESJE3B0i8SjisaCQBqFdm45Y9OsmVPIKwebtp1F13030fqMujn+wFMrqvjjDpczI5SdXbhpHSEepkp3ArAKJKHTxCIEXAkFCLrqLkEShkW6QH8mE/DIjkoJ0OVAoZXBJz0Oj2qG46SaBKdOKsGK++HvTMiopVXDJyC+r5mLb5hOo16sMZv68BRJXORLSdJB6yLB+4w406RSJICdWbIl4ebDnwm/QX8yAvLgWSdxPz5Csc5D5CpLg4/tuFMiDCclEyKunzSULhBv38ks5w5KwU+QZALGtkVmANDOQpnOUKBM484JJkEGnG2BMZ7+RRIGQF34HFhtCZIBnnA55Chuc/LXwOGjAzVLaAkl1EifYuY9peH12MeDs7oTiEWx+p3VsPW182xHikXQDH1x6HI36VEP76hXx6cpNkKXLkSAXvAxld/1NOvtqkJsoyLr5/ARyMdPoYH9gJASiQJRyQs/uGckly1on9ttMvpkGpZptG0HuHO3FiuLyvuw3Ka/D3nvs+BVcOMXIwgtnmc/QxSBG8kWWZIShMyf6XFUqhLm525MgbWYbJFZAaiEp51w2ncO2ZWaOEQkJ7HvR8f1KSNYuIC85KWqxIZNLyxNzOQnKUxmzOCmaw0lxWSHSNiWfHbcuprF9Zr9HDhTvFId0QwIyDyfCo2MEDmVlApfT4eOhovtv6LulYNNbcGt+DGYv2IL5XzbFgyBcoIiEowgR/x9wdXVG165tMGbMdDRtWhfvDv0U38yaiFu3fkFSYi4C/Jl0UCJhgysyu1xSGKjJuiPx1wZ+jOYEyb0GKy5dikPH9sPt90uUKEaDPNzdXdG2bcHxZunSWTQIhJA/BGlpGXjnnQ/RqlUjSj4OHDgO8+Z9QdOKSYAOIbaI3FXEywWDKQU/zF2A6nWjkG3Mh6tCC7UswME3WCph57NqPqzekUqcHzjg9WQg+zH3fFaUpFNnfyW+mFK3EFEuu4Nks/BEaYG4K/wc+U0VRe3aVbFx43bExycgOMQLo0Z+juGj2iMoyAdyqT+9vqHzs7Ha6lLmv3SaYWB1wuUs5nFY3isGSv5agYwbMvgTREQE4ccfP6fJx7O+WIVVq2cgyNmMfE6+CYnVwgBCrpkRmy5yNi+51O8Ooq1gC0kdjgF3WirQOThsq8IEWYFvpUC0ck9GTiIXc2E1V7hzLkp5XKX/n01PdPBizNCzzxGbnWN/nDxls0goCUngwSXWbkq2D/lq2GdSy5S4mceOUwqpcIwSSD+ZgxTfYisY7C+8Bdg2FBoJCieas+eKRUTizPlfsHr1Dkz5ZAl97Mz5ZVDIGOlIlrhi5Vc0kK9i+e4YNWI6WrdsiYeHSDiKEPG4EIlHEY8FcsIkdefKJd/hk0/mINDHDX9vPoWLN5NR2t8XDXxLYl4JdpK6cCzJMXBBLYdcww7cJt6lZePdRHaSRrhQtxX83/C1aGSsuQrZxjS4uGkx9LP+aN++MRRyV9oqr9bIMP/n5bhgvIbU1BycO3cJVnIi5KQjQZ/ug9GnOxsh1Uc5YeMXO3HzbDqy3WRIM0gxb+8hTG7BTNCFkUwRzx9mKyvsNsbtwpUTN/HztL9xq7gauoQs2BI54cZJnzvAOx/viyftdxfIsyIeh3bLrbsRjcL6CoT83SDMT/AvlUuQ4yFDgEWOit4e8DOqEJudhmoNwnHpIvtdZSew4ljKu+8Ef0s6O06slSvFRuj1YWzZLh5OsBktMGXexHlzNmY1qkSDSPr1mIVbpOZzkuPSFd4laRI+IyfpyO+YeFzShfICTDAkFz6jUBMSkk7YVpx4dCHek4VCZa7fZB2h+WkG+IawiwS1E1u2insMCdNwd9bN6VG7HHYrmFfilRvs/UkxrJhNimPFcEAE2w5BoZ5Iy8+3G57LjBKY9VYYNBaoFWy+V2PYttTdKuiKvc2J1lTu9Wk0FvmMkoKO7WNHrrH15J9Vz/1tiY8kgZebCtn8fSmZOQ6elwmJbP3bD66BfZ/sgizDBE/u20m3NVmM0QDbDbZu/Xo3vIt5vAgRIv4L6NevG7y8PPDzzytQtWpZvN1/LFq3qYOvp63FV9OHUMKvgHzg3Va8K0gghNhFOSMcpZygEHzOCjqE2PSfXZfw7tBpCA0LRNeurTFq1Nu029HIwzFOnDiP9eu3oEqVcti2bQ8lEitUYAFZBGRdiY+jADc3F0yaNANfzxiPtm2bUIJnyJA3n/l2E/HwIGTxyFEfo2y5CPTs1pAqDBTSEMgkBbVDYZDnngfYPiq9a/1dNAiNkOyCz9+jDq4RH0hCqI8cORlzf/wImzbtQb+xtWDKyYSvJgVaOauXTFY2CJuYn+sw6Ch0/p1JuwlnBasd0vWs7nxnSDMcO3wFDRqWp/cvX47F6lU70euNhrDwcB0pl+0IBK9WxrsbeVcj+7wCCcd9IXkHZKEtwLaZzQSJpGhInCOpWLh7Q/jdCyjq+VoQqqKBv5ZtXx8NW+80PatzLmWy+txFWVCHmG1WePpqkGFgx52ynixw0VnO/F2FdQzQquGpYp2Ucil7TPge7ccq7utIu7P5+ghEo9CFKnx+4b3kkxR8XjktPbt0q24nHm3IgcWmsneEu7l62OvjPn3bi2TiKwayfzx3RzjJk196/hcgEo8inggajRoTJw5C177voW73iti76iS6v10Pv/28D1YnPSTF7xxtfFxk/XUdulNp8PByxrxVQxHlxZLDSNFEpD1klH/AwG7UA+3WzRyEh5NR9nsfWWQKGT3wqPMtyHOTIbJuBK7siyPqDhEvGNnZeVi0cCO27D0AmUIKa1Mf6DKFzo1XC5meMgTpFNAfT0VsphESVwWs9yJdHwESpQy+PaKQ8hsb1SY+YgPfbYEx01fCXE2Q/DwbKDJN8N6bgbTKrtD5i8nKBK7Brnjtu1a4rcvBRS4pF2C7mQ/r1iTUrF8CQVwKL0KEiP8mWrRoiPT0NMTExKF1m3q4dSuZdlGNHPENXn+jBWrXqvFUlrP/33MYOuRr+v+cOZMRFVnc/hyRWBPUqFGR3q5evYnZsz954DxDQwPx5ZdzaR3WokUD9O49CoMH937+floi7gAhkLdt24crV65j5Oi2aNSkYiFC+tWBt7cnhg7tQ8n9unXesNusVKvDLF2eBL37NcLuHadx82YigoP9qdVAt25DUbK0P8qU87N3Cj9t6HR69OwxErm5+di+49dnsoz/R5w4+x0yechfYZBmlebN3oFKpcSAgV1eyLqJEPEqQiQeRTwRrLZcjB8/A9fPJSIoJQuB9cOwd+0ZfD9nID6fsRa2HBvyorm33WnuFVdIeioVOqb41MKnSt45ZLRYUSLSHbYb+cjbk4RNRyahmGu9u/qZkNF+4nVik1ggkeQ+0Kvj7dLVcdrzOM7fTCVmLbjgrkfmhhiYLEn2EWARzxcWGxthfnPCZ1C5qLBTlQML6YY9ZyzoKhS6Al8EZHyfIp6MBFwifV94c6nMo5CFwmfUsd9KYik13Hfno3WHKnALd8WpvVfh1DYUEqkEGcms00/LE5UFWMwWKFRsRFrJp2ouP5bzhHmVqxNkGjm++H4VJgwbjFbNg7H93EVcOngdtuR8ZFd0RYYgn3aRQ26wQpJjhimbf+4i6YZ3gMrc+TbjU59bBsiPZyHPW4EMdxmsgmReK4czl4s7uzKpjYE4yxdKXBRkPCTp8bWaZen/9auy/eLkNeaDmHiTSZiT+HeTkBhvlzoT30oNFFBChkybHh6uSocU7oCSHnYvx7gTTMJtFDpUtYJJLf885BjF1zeZy909PNn2DQpkXQq3E1ingEIhZbJp8pl0bH6pYF0U3p7se9t9hpGNN+MzkJ6ud9gPynr5QtdQiwVzp/ELePEiXoSI/yKIp9uOHXvxxRfz4OPrhj7vVseS/usxc8ZoKn8e98FcbNteBUrabSS5qzc26Wuy2bjCBI4KAEE+m51lwsC3v8YvS75CzRrVHrheD8sburu7IT9fRzu63dydEBzsh3PnYlC27MsTjvMq4vjxM1iz5i989PEQREWF2YlgiURIQn9x3uZCF57JehtyCfM+fhDM1kTIZAW+jY+Kzp1b4sSJcwgJCaBJxTO+mYPSUaE443wTajmTFgvdewI0XHkhdD7mmozIM7PzuYmrPi5mJqB+x/KYMPErfPFVHwT51cCUKSOxYsWfOP/RZXz88XuoWVMIerNRO4MzZ7NQuXLpIp2L/Pvh3YsFnYoShy5nKwzIzzGgWlVGnv29ZfFdOx0L5mG19wc6wrGWY68V7FqYRNlHzY4dXn6s69DKaxibzYrr1lxEBPjYOxKVUiGxWnOH97SQ2G0tcmwSOjWJXyNbe6X9fwsc5ek2G9vuFrAaix3v+Laxd3urQZpTfX38HdLEybEpIyMDGRnZOHVqk32QRcSrA/Ibft6DYTaJpEh/8asJkXgU8WQ7kNQHs76Zim9mfYe/fv8XWicVIisHY/SYhZgzczAmjPsF5Q0aVO5ZAVOub2NvStPDyOWnzlyyKcgu9dzcWgikIKSISqOE1dlMx2VdFNqnViARY+uPJozC3lbvoHJoCI7dSIVGYsPZmDMIL+YHT5VIPD4vCAbaW+N34tLxeJw7ch3Jtd1gIR55gvr1QSTXswYhmVwVjp6GwvR+SCwUcvSw4FJdgdhKS9HB6iGDW4AzJgzojqmJy3HsbApCmkTgrFG4wHSETC6DhZP8gqyXeHAVRnZuPrQdQrFj71VcH/gJpn/XDzNGDaDPrftrBxb8sA0+VSOhddcg7WQScrN1yMjT4VQpZ3olauIybzspzENrBFk2/c6E740/Jz+YRW0ObrlLmM8l/+27uqvsgS7FPVlhWsKLTaW8oBQCb6QWoJibmwNHW4WHtWRz4/JL3EMxMS+34PNLpFRqfTs2FfkKDXJz2H4X4seIzjydGQlnBIm51THERzjuCDJzhdQurTbwzy/j5GpONiuo07lMm9T0QhBNkJK9/1Ys86hM50E98lT2noxCo/Oly/jAPO8qUoMTsWjVCMilj3+hJUKEiJcf5GK5ZcvXqPfttC8XYEDP2ejUpQ7GjJmJr6dPwJt92uON1z/AZ5+PogQSgSCRtUjYIJTenG8/ZgpWvVK7PQM7rsllfDCKe7E9LZQsWZz6U77V7wMs+XUGmjWvR7vsROLxxSE5OQ2ffz4HU6eOQYkSrK4Vzol39wh8PiiQz2bZ5dVCUMqD8DQaAwYNegPDh39C91cXNyu++GgF3p/V3k44WovUnDo+EOpkY+dylUyGfLPJwacwx2RE6frFoFUp0afPN5jz7UeoWDkcVapMoF2Q77//Gf78cycqVSqDs2cv4cCB4zCbzZg5cyLKly+wMCiKotc9BWE4EsycuYj+f/HSlrv6ODoGSQnft0Bk3p2kdFwWnx8nRmUSZnkjQ4H6Qia5TUlFOQLusV8JRKrMLp+WCOQp99IUSMaCeRLiUZBdax3l2HZZNvfNRJ7dG9JOMBZ5r4Bx477C+nW78MPcSVAqRUstESKeJ17cGUfEfwYKhRwjR3fH9Pl98dZ7TXHucBwCwjxx8MBFzP3pXUo8nFnP/NgeF9IgLUqVCUZ21mOQOPdBULAfyg6ritRjCZRgkOgsPOFMxIvAP+tPYcfKY0ir6PICDDhebmT5KrB301kYjSaMfr8LEg/eRO4tnpj9BJDIpQjrUhI34lJw/Mg1LPh5EwwGExo2LYdv5r0NFx8n6LL0aNmrGq5fSoIuXQfn2wZI7ITcQ4IX8aYAFdQ8GOpFIP9qJswrr8Oa9PJL9218G/fq24AO6ogQIeLVQL16VbBi5XQsWTYG/+w5iw5damLWN7+gf//OeH/s2xg44KMnmj+xp/lwXB+cOXMJTxOki2TOnClIS8tEQkIybtxIQETE/dKPRTxL3LqViN69R6J//+6UFBZRACKFDg8Pxr59R1C1WmlUrVoKv//CgmSeFLUalUSlmsVw+nQMZn+/ApcuXaPLW7LkGzRtWgcpKWmoU6cqIiPDacjN3LnLkJ7OBz0fEgJ5PHhwTzoVfFmfN3Jy8vDG6yPRt8/7+H8AIR0JGjVidl0iRIh4fhA7HkU8IST2RLRqxfxRrRgwb/Y2FK8ZinXr/0XFJmFoVbkMNm04gkrR7lCWccehDZfsHV1y3vko5SEMQkdWDpc+SuVySKRSmC9k4cK5BKg0Ty9UQRgdW9CnB2al/IFlS3bDL8wTvm5sJFVvuUCnalmpp7ZMEXeH2XaLTn9bdQjWht7IOZ3n2En3MkBvLtQFJ3T0Pcz7HuMz2Iq812SlY86pfhps/vMaunZthfcmtsGyGTsg7xlCyUNTkc5Hq8VKpdh0dnx+wn37a3i7YFJeLuQBGowb/yv0GXrUblUMFUJawi8UmDOsOlKS09G17xj62jGfd8KmdceQHJuBXIMCzgHOyHSzQOarQZ7ERLsd9ak6SHItkOusUGTbYMu3wBKbB2vHAOikcigSDND6sE6bfC6J9vfWwl3DHqvEuxedefhLTAbriNCZeTq3zQZPDRvxduMymVwTe85VwY4RYbwjspSXF9RyGd0eGqUC301cBreqAfCuHojUZFbonzvPzNKNpINTCMHixyR70JUTl6RxKbZSLrV3bBMpNX2Ob16hi9EOCZDHv8vYK8kOqdkWvi/pDXadJPx5em3lmyocIdYDvVoiOzsfC9fMQacuteCuFaRaIkSI+C+CJAi7uZKbLzp1TEKu+QZS01KRlHoZ3t4+UCgUmPXNYvTp2wmevEOchjFwWPlJxGBhXUVaudahQyglzYQvv/gF3333YN/Gx8HYsQPR7LU+MJlM2L//92eyDBEPxs6d+9GjRxu0bNnIIbTlZRjXFWrwArl3IfuAh3zvk+Kdd3rg889/QL16MzD8vcHo3vNtFKscjGKlA6iE2DF12bHzUSYhfX2C3QEcaq1Mgx4hpfzww5wVSEnJhKeHD7VKII0aDRvWQv36NfD5599i27a9GDKkB8xmC4YO/Qjp6VkICPBBdHQxREWF0/cQWwXSLXnzZgK9EaLy9u0kZGRkYfyEAdRLleDYsTOoWbOCvau54EsWpndT6Aifrehr7wbhOVbvEB9Xklw/4J3x9P7sOR/f5z2Flsg7He/0F7U62EEQ3/6CblgeRCp0btu7UYWUcyUk4N3bEh7MU4TiIMs7fOgM/f/XpV/T7trf122mIV6hIaLC7VXCiwqXESESjyKeIoRExRB/D2jSrUhMzsLJuNt4560eaN28CUaP+QZvt6mJ4TWzEXOEJcGZ3VkRFOzLTjRObqyYiLvG/NXSSEKxzQbzkVSUqxQOhaAbeopwVVXA6BHROH7kBho2qk5JVILLGTvotJRH8TsS9UQ8XdzIvYG4K8kw6My4EZ9TIDV+mWBz9Cd1wP3tcp4aLqRm4ZclK9GgpT961m+Ei1tvgHBl3qV8cCjuBlt0IXmQ4KEq5d6INk40Cq+RcqLfaDDhkqcBrid0cPPU4t+sJBhUm+lzP+w5gjNzjyIuSAqFXIuLVxOwcM677P1WP8TF3salyxdwOeYWrsdmwtXFGSE1QujoflCQB/yDJPD2ccOHk3/CucPXcf1KOuCtgl5IieZyci9/dxgtXBrDK4IsAytQ3dX8gpo3KcZmZiIui5GGPlp27MjgqZImPg8z/4yBzi6Qn87Azh8PYubvg+hjvd+sC+8wF3y5Yx/7/KmFPBWFFG4um5b4cl9Mvq1MOnbRQXhCT+6VycMRC1TlfLtr+GcLDXTG7WTWrZ1F5OXkWKfhhbSNzVej4stzVuD9erWwbuZuHIm7gGXLP8XyC/ux6tOtSLuZhRSNDmO7lnc45ooQIeK/Cgm8vDyx+/ddqF47En9s3IWBbw3Gho1z8dNPazFt2nx8+eVo2mkoeKepZZm4mctqqGQdG8SLdGPHHU9VEJ0eOkiGNIAmTeo8k7Um5MrEie9i2rS5NPlaxPMH8Q/8888d+PzzD17SzS/Ib19cfV2yZCQl9o4fP4fKlctizJj+WPbbOtSuGonEfPbbMVkd61F9oQFQwSfORa6wS60JjFYrytYphlPbYpGZlYeoqAJiy2QyY8KEr+DkpMDfW3/ExPHfYfGvkyGXetB5JiWmIybmGmJiYvHrr+toJ2NISCCtqcjvKjg4AIGBvrh48SreffdjHDl8js63Vq0q9xAzWh9C6Ggr8tq7va7gOfIZypVtia+++pBK+cMjguHs7FxIYn0vlsVm93IHzA5E4x2vtBmgN+fYbXIIhEtAYQBFSOEmFhV2b0heUwmfyCax0TCZH39YjYULNqJ37w4oXyEcK1eux49z16JmrUqY9uW4e6yvCBEinibEqxYRTx0jP+6AudM34eaVFEztuwSG923o1r0Jxn/SFRPG/AoUe3RWRqKVY8qM1x/69Y9qB+jkpMHv675/5PUS8XTw64+7sHLBXiSVfTqj2P9VWOQS1KhTAg2qfohT5+ahbfuaeO/DnxDZKgogIe5PAKtWhqwWPvA5acTGL3diVUIuJSaJp2OZtyrh0rkYmJxl2L/hDFa5+KBGrWiUiAxCdIkwFI92BVoDCkmgQzcC8e4x2xLo/28Ma4zfF/+L66TjTy6BPN8CsxDY8owRVTcCh9ecxqhOP1Ij8afZOf20QewefhqxjpLEf2/9FsHBvpg27FcElfRFTmoeIsoxDyURIkS8GmjevD7SMi9j1sx11G7mxOFE/PDDJAwa1BNj3/8Sn302F+PGDQQfX3oo5OfrMfbDNx86ZfdxLJZ79GhHbyKePzIzs1GjRnt88MFgFC/Ogj5E3B1jxw5C27ZvYdu2pahYMRrTZqRi3leb0fytmlBrH58UJaTkt7OHYPa3f2DOnGX47LN5tEtQr9ejfftmGDqsM32Nf4AXPvl4Htq1a4mKFUshIMCX3ho0qHnf+ZcvXworVn6Lxo1epx3QGzfsRNt2jZ/L10w6N98fOwBjx36JsLBA+Pv54GXGd9+uxNIlf+HHeR+gYcPG2PPPv/j99x2oVbsyGjeu9aJXT8RzhhjR+OIgEo8injrKBNbC7G9q4ffX1uCHmZswd+5aVG8RhMqlWmHxwuro9fZQJMulyAlSwcC7ntx9mDm6tweb6nJZB1LarTzIeFeRWq6E4iGNpx8EMjJmsFyGXm/EjWtGXLkSD53eivLlo1GyRGlajEe5lbQHnxCTYxFPH+R7ICO8hHS0VHeHITMfIJLhF5wj88h4Vuur5heFQoIK6Wop7waNmwoKaSBq1QjE+jUeGDHkZ/i3DoQ20BmxKSw93mS0Io97ogq/L0GOTRKvCVRqtl9nZ+ch9Srzi0zxl0KTmwpzKQ09O5sSrDj193F7yEp8FQ8sOHUMs3/biWgXd0yb3RfhHvXvuvqEgFRKmK9UZZ9ghL1VCZlpedi+7gSCo7SwequhJxJkhRTBPh6oHsCISxcul87iyYV5vPMxl3sYkY7IzHzW4Xg7mY2e5/NAF40z61AMCWDG5/kmEzKsZrT6pjUCswG1Rg2tWkmN4YVEcORxeTXpdnTmxxgSbES+2kTeSSmkk5v5dyG1IZd3PwqSdQuXSwtp2T5eTA4eXNwftgUH7dvF6qmAc4Q7XOsGIJsbv5MLHP3hFOTvSELlKiUw96cxcHHyx4kTF3ErKQuIdkONmlGoGhgsdjqKEPEKgZATvXr0Rt06NTF61Le4eOEK/tm7H40aNME330zC11/Pw/D3PsP0r9+HRqOmQTLpBnbcSshjybOuPETBSxVBp2RgQwiYeZqwWi3UVzAmJo7KQosXD0OFCqXg4uL81Jcl4t5Ytmw9tFoN3nqrm7iZHoDo6AhK3KlUSjhpfLBm5TTM/eF37Fp1HF0H1EeantVRShmrxzxUrBZIys+DWnr3axInXsNoVX4YO3YAYi4lwcfbD97enrBarVSFIoQqfvb5YGzetB+//76RdkLOnPkxype7d9BMYQQFBtLO4qlTZ+Prr+ejZat6yM7Ohaene6HgGGFqu488p6ia527qHseRjbf790Snji2RnJzMVTQWe1r2vUNAJZBLWWe2xZpVZE0shRKqSZ2ngkbOg7N4AI0QSGS0mrH81z34Ztp6et/NzQmhYb4YPrIjKlWOpMQoWVZmZi7q1x4Jb293rF37HcqUjaLz/2raQsz98UMMfGcaJk8ecY91FSFCxNOGSDyKeOoQEha7tO6DrEQtMjOyEOHK5Dx+ft74Y+V8NOnZD8HFw/H7xav08bREJptUaVlxLOdko8ZLDScXDQxSKZyUajgpnk4C499btmHipB+Qm8GKc7rMOj6wLdVDmm2GR+NgLBzZk0pVi7sy/xQRTx9n0//BP3+fRZabFEmEOHqZPB1fJLjMF4InoyBLtljw5bZ/4WM1Y+aC79G8Y2WU82mG0SPVGD97JqoMqY7rMkbEGXVGyOSOEmuhu0WY5nOC/9SJBGJKZF88/VXE3N2oPO5COuKITNgJCAxVo++o+di1sJ5dcnQvEG8pby8/fPfFJ4jpG4cO7YfTx518NQgbUwV+GidIsgxw9XbCxQx2PHBVsuI9Q8fW82YOI0edFEoYdGz9lCr2Gk2AY/hKfAIjYEuFBcBgsdDC+JoWMKalQf5XOvbsOIWousGIal8S3x/Zyt6kkkLK06etnHi0+3rm8vucVESOETnCawRwH0dLSSYtjCwZbL8ISR9Sgn6vttNZ0J9MQ/6xFHpz8XainYxSFzVcXNSYOW8yGjWsZ99q7m4+cNLbYD6UjDfHDUOYS9R9t7MIESL+eyDHz7CQspg65UN8//1iRBZj3tOEwBg7djCWLPkNE8Z/g5nfjKOps0FObg6yUCGh12xLtttDCBYcTwMkGGPw4Ak4ebIgSHDU6L7Ytn03Pv98NurWq4LBg3vD3d31PqSEiKfzXWThr7924p9/Vosb9CExcGAvfPbZbEyZMgZubkEYMmggWrZ7He171bBfKTvJ2bnfzL1VSKI0qS0IjFyOLRD8Fb3YeVqwPyhVkk0JhN8dkQcTqJRe6NChLdq3b4GrV+MxcsQ0LF48g5KUD4PevTuja9c26N//fZQt04Y+dvjIOri6OiMpKRVOTk40TOr+o+X3k2fjrknYxAPT09MN7h5O2LJlHzp0GISqVcth3k+fwdnJ5Z7rW+Azyj6/1ZZdxPOTPw+5Pb3cZrlOpxnGNPu2b925Ktq0qYbkpEyMHr4AZ07H4u1+M+Hu7oLMTCbRLh4ZjG7dWmPKlNEOpKu7uxsWzN9EvTZVyqdzXSlChIgHQ0y1FvFM0b9/V4we8w41IC4say7RuxxiN8YUdHI9ADJPFc6fZR52jyo3yclhI/4CJk+ehRHvzYBBZ0K74fVRqnEkfdx6PQ9wksGlog8y997G6P4LcPpY3CMvU8TDQ5dvpCmCqT7iGMhDQypBam13XD53G4u/3U4fqlWrMrKfQsL1oyKkaQTSL6QgNVXw7Hk4eHq5Q+OsROUm0QgaUI4+lnwqET8NXIu4U7ef+npe23EVG95aR287J2zHri1naLGcejYZ+cnPLmHbkmdC5r+3oU9gy5AopFBGuUJZvKAo17io0OPzVli0bjiWbBiJBg0ckxZJx1Cj9hVw+ewtlC3LjlUiRIh4NUGSiUlqNPF8K4zevTvRsImTJ1ko3oMQGuqPs2evPPLyibdbYmKKg5fw+fOXUatWR0o6du/eGj/P/5w+vn7ddujyDWjfoQlu30pCp46DsGjR2heWvvuq4LvvFuLtt3uIXaaPgHff7YPGjevgjTeGIz9fRy1ZKtYohpizLPjweaF48RDUrl0Ff/6585Hep1arqJdqWFgQli//hpKORNbdoH5PtGnd/6mvZ0ZGNkqWbIISJRqjVMlm+HTybPp43bpVsHQp60J8FiBhfBvWHkbctWQk3EqHh6czgkK80albbftrIiODMXJUL+zYPQ+r1kzjpKMjvvpqDFat3IROnVo8s3UV8fKCENekWeK53sR0GQrxav8pQG85S6dKaTH+iONo1quKewUfkMffqFkeC7bE40peCvRecqRnso4mTRLrdMrNYp2I7i5KmE0WqKr74NtvNyCyUgCC76PYMVuTqWz611UbcebkFTraT8a4ZFYpPpveG5VKtUS9etVRrHgAGjUPgbu7E7TyErSIJnIBIg86df4I9iafww1XEz6dtQEL5+1A/Wpl0bRZZVQsJyQDij+dp4Fp63YjOSMXlkAx7svxR8K3h9ABWijUJvci+41kDC6H3aN3YcKITCqrUclliHR1xVH+Omd3JxoaQ0CkPYVH2oX7p04nshfHO5Lzd4XwFRF5Me8CTNkWh+J1w+Hj83Aj8wQyiQv8fFywYNl7+GjMUoSX94VfiA/+Pc7CDrKMJqh4l46FX9zmcsN2E0+Azrbq6XGBoGIY6yrM4685e+0mnfJASmSuugJlvhVVa0Xi5o00dH69LiKDiqNR44r4cf1anPznasEAiFIGNU+tzudhMlT6T8BDYRy6G7nUWnA898kD8j0VkKUYaHJ3+r/noc82IG/Xbeiy9XDzdoLFbEW1GsXQ6qsOaNW6OlRyJkW/nyn7uAEfYEy/0ZBLX+1ziggRIu4jx369Pdas3oLyFQbBW806Hu3ZrzycId/MOttr1S6F779fjksxV1Ai+v5d1Hq9AVu3/oOTp87getwterwngRI9e7ZD375d4ePjRbsZSbpuyZKsDr50aRdyc/Nx5UocYmKu0uRt8r7MjAx06jQQ1WtUoHLSDh2aiV/pU8aKFRswZsxAcbs+4u+H7IsbNmzDrFkLMX78UHi7u0Buktp/OySpmkDBawOSai3UKMJrKngxKwOV7GEGCW0O4ToSiZIGxhw6dBIrVzIi71Hw9dfjMWHC11i3bivKlC2BrVv30sc9uIXVw+HBydebNu3G7O9/RfXqFem8SWNJ5coV0KFDE5DN0LXLULzeq+MDie+CUBlLoVRzx7CZ02cu4JfFv2HYez1x7twVzJixgA5maLQK3LqZTl8TGOSJkBBfDB/RG507N4OfL6sJ74fgoHCcPbuNS7JFiBDxvCD+4p4ClNJIh3bxG6kX4OSshq+2Kr0vykruhMVgxsm9V2Gp5045FgMnMpKTWHu8il/IE3nQzdgU+n+pUHf8tGInJr8jbFdHaaUNZqy9tgOLJvyJW1oJEkKMULspaFhD+XMSFAtlBUHjxgUjY3ZIgAD/MHprUL8B+vbKRddeZJRQgbxoJyQhG++NmosBfW6iQcOKCAkWUmVFydCToFPxSHyadRROARrkeSoKJMX3So/+r0PF9ycvTjDxTjk7F1UoWVvLJcakA4Wgc/uaOPTdYYS0C4RcI0dceobdy1HwIMxMZceoa9e5t8713Ef3qNTI0bRLeaRtjIX0qgXLlk5/xA/JPkzlkq/h1yXVMGzYx7j5Zyw6tamMbW4a6DN1sJhY4enLpdaCfEkgHslxwahnROOF5GQH/0qTnm+P2pVgNVtxaOM/+HnxHGrzQJCTk0e9XTVKDwzt3BPdV05EGasaTp3CcXhvnP1YZJe5C9tG2CezjI5y+ELPuQY4weMwI4Y7v1ELH40dSgvbeQuX4bvpG9Ghaw2MHTaGFuqPkuRJBjqUYoEs4hWF0WigxzC1WiTe74fpX/2M+rxjWiZhxKOvmpX5OgvzSJNyggRSE0a/3x3TvvwRCxZ8fV+rjA0b/8bVq7EYOaoHoqNK0NcOHTIFkZHh9HlCKI4Y8dYd7yPyzooVS9Nbt27AZ599j23bDqB69XJo3LgGPvroW8TF3UC9ejVoovCD7DpEPBhCJ+qkSTMwbfp7dJuSJogXmRz9MniJm62MpFJI7x/OFhrmQzseCVo0rYsJH/yMPt5NULx0ANL1eod6ivhEe6q5j7Mzqy9Usmg+p4fZlyUO39uSJWvx88+r8NNPX1Cv1keFUqnCV1+Nx5w5v6Bpk95o2LAmZs78CGt/22RfnjDAabuDYLybzZHNYZ8Sfp+x126ic+cWePvtnvZXXrt20040EmlzmzZvYdGir1Gs2L2DjYTrJym35xJSrgu/gqR3k+5PciMD5xs2/ozIyDAkp15H/Tr9ERjojd//mAp3l8hHvh4TScdXF2RXfu6nG/H0RiFKrZ8BJn+4gnbyEJmviLvDaDA/MuHR/M3q2L36BPLyCnwZi8JkMCM/Sw+znxo2Fdu9Vcey0Kdfc2g0jkTl/UBkCp98/zriLicjbe9NJN/IoL6TU6cswaJFm7FkyTq88/Y4fPTR1/j224VYvvwP7NvHOrZEPDyq1I7EtPl94ZZUpJtMxEPBs4Kv3Uqg74AmaNS0HM5/dxQG3kH8rJBzOAlSpQwzZ46DkpODjwPSqbn41w/x+x9T8NY7ryE/QwfPUGKK/mQghXLqlTTsnfUvGr1Wzk46succC+lRo3vCdDkbeX9cf2jrh3vBGukEq7scTVpXQP/hzWhhGx+fhNMn4uDqrsXBvZeQlMQ8ikSIEPFw+Pvvf9CqVT8cP87UJSLuDm9vD3jRUImHQ5WqJeDiosWePQXBV3fDwYMn8VqzuoiKCqXHzIMHTtIAmbp1qz3SVzF+whCoNSqsXPkXtmzZi6jIMMybtwITJkzHiRPn0LfvaIwd+zm++upHLFq0Ghs3br/DKkfE/UG+n4sXd+L06Ys0NO5Z4XFSzv8fUKNGeXh5sd9QmTLhmPX9MMyf9jeO7Il5psu9fTsJ69dvxRdfvo/SpaOe6PsnsvG9e1dj6tQx1M+7RAlBjfdkSElJx+zZS7FnzyH06NHW4bnC1gs9e7andgwDBozDmTOXnmiZRD7+4bjBdHDj2LGNlHQ0my1Y+usmBAf7QqGUY/u2Y0+0DBEiRDw/iMTj09iIEjUbUeS3+Nup2LPjLDZu3AyrTSya7obqEeGYs3gQQi/oUMbLze6BkJSuZ7c0djMardAZLPS28OoF6Mu4YOacWYjPPQKzLYXerLZ8esszncOPy/ZAH6hEzu08ZFzLRvlK4VDn2+DqEgKF9N4jb3dD5aDG+OGHSfhmSh/07l4fkz7tjr37Z2HchO7Yf2QP9u49gviILBy0XsQv5zZjyAeTUKJEI2RlJ9uT14SkNnIT1lNEAcJdAnHrXAZ8qvqier1wwEPJbpK7jA6RDjRy89OwW4CW3UgSMbndB/83nRQkUdlZjgrVAukNzgp2Ix3A5Ea67PhQncFsgdxDjRvxl2GxZcBLXR5v9uiP4e81h+3Pm9CqlJDJZfRmtVjp7cKldHozXM6iN0q0kRvZrsI2v9eNyIvITSFFObU7Or9WESEhYY9tKUE6MMhNKQ2HShYBucQbJtiQaTQhwNmZ3gRoFQp6IxIncjNYzLhyLZ3e0hIy+S2D3pzdtMDOFOTuvoXhg5pj7Mj3iyy5oEBWSP1Rr05TzFw9EKaLWQiOId2WVnqDhd8YU+n4duEmDJuS70UmgYdEDVWAM2bP+BIRLjVhtmZgyKAvoC/rgne/7YScfD3y8rJh42ndIl4G/EevoP9DkMullOgihJSIe4OEOhw9dgbff7ectKZDItHSbiJy08rd6E0ldaI3m01Hb6PGvI6ZM+fDYLxzsIrULQmJiTh7JgZhYX40/IEcs69du00TgB8VpCPpo4nvYdGi6WjfrjmGvvsmNv+9CJs3L0Zubg4OHDiOEiXCUKVKSWid1Dh+4gyqVm2LNWv+FL/2R0BCYgIlzxROycg3X4PZmlropHXnd0xuJms8jNY4eiMdguR2PxQmml52kPTk8xln6M1iy6Y34XML20W4r/bORXx8PH0NCTaJKl4NS5aMwp+LD0GfpoOzUgmzzUpvBMVdQ+jNRVGW3sg+Tm5F53/3W8G2TEhIhp+fL+rVrfEUPjG5nuJy8EL++gV2Luz/wvfvhI2uF7mR+vmPP3ag/1vj4enhicWLZ8K5UH3GPoOj3ySxWoiPv40uXQY9xNoK60LWlWw7q70jkyx/zeq/sHXrUmi1WthsJsyevRh5eTmY9/MYNGteDTfjUx7wWUSIKLLPSV7MTYQotX6qIN5lBN/OHENHZCqWfxonkP8m/LXV4V+rOlb/6oFxo35BRLUA+FcJxJ6Ll+nzF68yWYQ+2wIXQrwAOH4oFpDbsGbrMazacAgdh9SHs4cW6WeScf7IdejVEiRfSYKpoQ8kt2yAXIKcHy/AnGFA7VpVH6kNn3x/q9csp5JOk9yIPl360hP4uXMx6NR+LHxD2En3+NErkJfzgKvECtdqfkjZHIdmr/XHnB9HoUx51mUlk7DXSoUpiqbLvbpQy0qiYrlc+B47hQoliuPwIRYgJHVn3alWweOQyFu5917DdqXp1EPDJC5/bD7DXnuFy4f/f+rhO5HFOj+9/JhMLrq6P53G3hQsCKQwcikw8XT0LOWFGbMWweqWjsaV2tPHX2/TGWf3JiL2Ui5ygtmZTki3lnKCVpAKUVKTgLxMkLkbLXez9QF8NZDrrSh30wbXMA/0btrlqX50IoGKKOkP6e186MMdJTeCp5IHlzU5K5TQcFl6dhYj8wPDvGmRWuGSBOqq0Zj58SfsM/OExLtfNLEP17RsLdStdwAHThQKZuD7G3T3qBbI8uUSeCSZIDNYkOorYzLxfBNM1gQmcZOq4OPrgRAnLY6uOYd6dUsjOoql0T4K1u/6BXu2noWPjyuiSwWhS8t+DusvQsR/GTVrVsWPP35O/ZlF3BuuLm6Y9+OXmDJlFj4Y8z2GDuuJkFBXbmwvJMnycwAfHA0MckbzFrXRulU/NGlaB/37d8PevUexe/dBZGdnIyM9C5M+GcL9geU4duwsPv30O0yaNOKRv4oDB47iytXrsFotaN68Hvz9AqhVSLduQyHh1hbfffcrDh9Zi9OnL8NqsdCu+IkTZyAhIQXvvdePWuo4eo+InttF4efrS1N95TY/2nVPiEeTmXXay/hAoUzKfJltNkYw/hm3HxkGNiDWI6oinWrlZf8T5xmZ1B2381gN5aRg3XHBTqy20lt0Dh6N15V5uHApBr+sWIK+PQfS346fVzl8MHYQ5s5ago++6WFPijdarbDwQUTh+sJi43UoJ84k0BSqQyR3rUUGD54Ig8GA11/v8NQ/e/nypWj38P08pBmE51n9JxCOBIcOncWSJX9gxYrv4exc4L/oiDsLbyIZJ12PSUkp8PPzeYi1ZdvsyJEz+O23LXh3aF8EBPjSQJmsrBxotWRbWuHr64Hc3HQcOxaDf3afxvKVXz7yPkqUc19+OQdubq5UEdOlS6vHkreLECHi0SAOETwDlCwZhrJln05r+38dQcFemDN/MPISc3Fk1gGY1tyANf4+XYFSCXwHlYHPW6Vw+Pcz2Lv8OJUw9p/QEiWaR8PQ0KuAMCDcgJMSUpkEbm4FKbIPi6mfrsDnU1Zi+qTf0aL5O3bPIlc3JyrB1miVMB5Jg251HHQ3cuh5r3HHimjStAoiox5sbiyCoVq1CkiLSf2/GkF/WeBRxgdDP2yNL8atpRdmAsZ+2BvXNl+GNe/pSNglNht84vQIupSPcj3K4avpIxEQ8DCF5KPBL8obSVdId8ajw5pjQu6qWNisNrTvX+eR3ksK7Lk/jYbCRQmJme+HRTsd7wKpxQaf2yZ4pllQ/JIR0lAnSNRSrF65y/6a90Z0wtndV1GhSgTeee/xghSO7r8MHz9XKFUK/L7ywGPNQ4SI/1d4erqhUaNaVDYo4v4gRNMnk4ejZq3y+OLz+Wjbagy+nbWKDqbeC4MHd8ffW+ZBoVBgyOCPaXfpgAE9MXnyu/jiy1GoVauC/bUGTk41aXIXr+wH4N9/j2LqlNn4/LO5aFC/F9LTMyGVSqgPXFxsPLRaNXx8PND7jffxxedzYTCYaOBHmzZNRNL5EUAGyatUKYdjRx8u4VxEAVQaBeYsGoSD/17Cr78WpDPXrVcFLm4a/LP13FPbXERaPXToR1CpFNQPsWnTuk/9q/D19UJaWuZ9f//3AknF/vHHlfhq2jx8993H9yEd744GDWrSwQKiDhMgeJLfD4sWrsX6ddvQtOnryM7OwUcfDaMWDGR9CEiIDZnPpUs3sGjxp49koyWAdGPeuHGb+s/+9NMKu6+nCBEini3EcJmnCslDmReLKBgd9FRVgacP8Md3bPRx5/ljmDNpA5y1CrhV8cPZlGTkkvRYkmyrY9MjB2PpNMeLFMA6bDp0GCA3MjpnstKm/QCpM5U+VqkQjn79WRL1o4Bc4Jw5+xcuXrgKJyclPDyIzEiDiPBobPpriX10LyvnOtav24PX32jDRwfldump1aZ36LgqGoYjgm0VqVSG7Dw9Vm09BH8fNjrcrnElOo3PZqPHmVl59o6IkdWq2rveCC7FsBTj80Iys8UGqdkG9ywrFCYbTE5WQM1l2kKnnzA4SmXMnKhO59KiF8l/8pCSnX/yCwYFW9GwEEac16pWApeu36b/W/hnmZdyCabK7ljz22oMGtIKalkp+Hj5YfjQlpizbg+Ce5VCvokRkGVKeNHpGWE75JoKPrsQnuLG91MieScj5sW9YT6VgXrBwWjZoxraVGxjDy542ihe0g/7Fh1BttHg0OGYa+Tp3JwI9NCoEVWSHTOIx4/hajZUGxLQ+e36GNn1dfo4kQU+LJTSEDoNDvLEdVkuzFoZXPWAy8FMxJTi26Oo/yORr8ukiCmngcQGRJ3V4cqemzA4S/HjL3/iunsWJrQehiqVQvD7AnKR/qCOg3tjT0wc/OsGI1afjbxrN6mEmxxvZBKPR56XCBEi/tuQShTo1rUTvZnM+fh21hL0eeMLdOveDE1eq0AHUAXdlw0mKislhyUSHgP0sKfLFqDg2EcGcQkR+HAdTI4YM2YQOnduDbPZTKXapJuRYNq0cQ6vW79+C2rUqES7ne5eOwrr/mAS49UEVzpInCCTuCJJfxkrYs7Tx4JdGHnkqWJ1KhEZE3x75Bh0eey8W9mXbfcKXiwohcjrrVYrduz8F1u3/ENDnrp1ayf4jfBlsvlYbCxcTbATkUt9X3jHJFn/JsFVHPaZpPxEOt0ez64nSnqyDtB8sxlyrQzDPmyD8UNWonfvtvaU5U8/6o++vadhZMVAuLhrkZCXi/MZrP4s6ylsc7dCn7sgsdpiIx2X7BpGr5Pi5MnzWLBgJaZPH3/fAJangajocFy5EosSJYvdp/NR4jAlHbPD3v0U5cuXpAnbSuXjhROFhQXh6tXr9H9CfpYt+xr+/fc3eHt73qXYZuv2w9ypdFq2THO0bv0W9h9Yg/37j2Pu3KXUv9JJq8WnkyfgSZCRkUnDsZo2rYM1a/5CSkoa9ZMU8WpAsHd7zguFCJF4FPGSQMWTwVuWjcRrq7pgz771+GvjYehPGaAs5Q7f6kGIyWfya1dPJlkmskbiN3fwIJPnIlXwKJIACgukeSYc3BeD8m1L3YNNuv9BQKnQonz5cvd4lr3XzSUcfd5kyY5FIZPc/0RtgxE2m/mRSZL/EohH57YdhyDNMUO7KsH+eMWm9eAT4gGdOZDed1bI7ScJOZfEEJ8/Ai9/bqbvmwpVrgUB5/OgNLDvO89FCq80G/SuEiQTIo2T2MIJwDvaHV4erAC/dIgVosjnFzPaIuMyhPh+lLRtex3H/1HLHNOSBRk5kewKyxSeS2P7sntJ9tnq1WDy3AAXFwSXYwmAB2JZMXftUiJgs2LDnwdQu1spVPdjr+3VqTN+WrgDZdXuSHXmBS8fbXa5wQhdPZdgmzRye3dfqzblYEzOh9fhbNyKTUNQrg3lKlTAsMFD4eLi9EwJ9IYR4fhNoUR8SgZkarn9u/bksvrUfNYNnabToVfl8rCYLJCeysL6f2Lx/bdTULp05GOtn8l6i3bcxp6+jQaf1ELShqvIOMg6L/1SLEgKVwG5RS5yya6g4QmRwlecZ4XeVY7r0XIs/mQTpHH5aNW1Kir4NnqsVFEi2zp54iLS4zKAWl4IdnfHNUhhsxV4OIkQIULEPQfC5U4YM2Ywrl69ho0bd+L1npNRIjocbdrVQe065SGXEy86dmwjp1STyWTvIJJIhHOgBRIJOX+ZsWrVRtSsyaS4j4OICDbIcz906ND8Ps8W1G2Se/ZOFPUJebVAasvfftuMtWuFNGPAp00E3OsFQc5tS3KNjBi0WFlNYzFb6CAewe1cNohbxiMdRqMJo0d8h127mEQ5JNSPdp7t2HEQ//w7rxBJzbZ5su4inWYYmJS/hHsVSLkNlZWSbwUQCL1HOzfypGXiA2hjXWrMS5H57TsO+gs+hBbIJWygMsvECNjdt+Lo9AYPL0rIY7VFNT9fOMnVcPJRo3hkEI4cPYYa1ZiCwtcrGt26tcGhvy+g7es16HsU1IIAiHBhy1TLrQ7rIJynU/IT8cvsAzhy+DysFgnKlo3GlCljULIku/Z5lihfrhQNGyLE451p1kUho2FSK5ZvoDLtDz4Y/ETLPnz4JEqVisKNG7fw2mtv0Md69BhGZdskMObulgnsfp06VbBnz2Hq0TlixFt4771JGDVqCj74YNBjDXwIyM7OxYYN2xEU5E/rPnLMI4+JECHi2UPseBTx0oF0G9atV4be1l08imV/HMG13y4gPz0P8uIuyDSmwHgrDzazFRKtHPJAGczqOy/CPdIsUHopcODPs7i0bgYd0UpOTqcnmZYtG9LkNQ+PZ9O5JeLhceTIeVgjtEBld0RWCsOtH05j1sDVGLOoF9Rej0bIuiUYkO+pQFwYJ58sNmTpgFLxZlx7dLX9/w8UUhQrFUCTF6t3a0Ufoh6DCilkChlge3iZjdVkRfr2eNRvVhF9JrRAzcAI+riL8tFkNo+L0hVCcComA67l719YJl5OwZnNlxDi6opxn3elpOOTIDdXB4vRgovj90HhrkKHcU0QWi4AM/ose6j3J4Up4XfdAJ2LDNZQBfKbeCPxZjoWf7cd30x99K5rAT///Dvk3mpIXRS4sfQ8gruU4H5rIkSIEPFwKFY8FMNH9MXQYV1w4sRFbNywA199+Qtq1ykLrZMKp05eQVpqLr0QH/vBADRseKef5pUr1/HHH9voRf/Uqd/Tmook3WZkZKFMmWi89Va3J0rkFfF0cO1aPIKD/fD9D0Pg7eOG2es2YOW0HTDnmuDf5tFsoG7fSqWk4+Gji+h+QkA89xo3GI4jh8+hevXHJ6FfdnTu3ARLf/0LlSvWoBYGBKRTV0GC/h4B5De1b9d5xN9IwoJFE+DhFvYA4vzpomrVcli4cDW68trwXiA+imvXbMIff2zH++8PfCrf7apVBcFQhMTs1as9Bg0aT1OvC4jHu+OLL0ejdq3u6PvmJCxd+j3mzv0M27btw9tvf/AAv8n7Y9++I7h48Qo6d26BZcvWIzg44D+9H4u4Ey8k7OXVHAe7AyLxKOKlhEpWkk57lCmBjqVq0v/PxF3Ekf2XERbqixKlgxDiGYJ/953FiIk/I6B1MexU3IYpiYyASmCTSZDur8BZZyPOxVyGTnIZFpUUJn/2y0+M2Y4NvTbjkyl9ULNqixf2OYnM6VXGot9X4tDRkzBWcQOUEiSmZELaJQTufyXh23fXoMuPHenrkvLyYOYj8wqe0ic0B0r5CH6ArxZygwSSSCf48G5Cg8kKhU2GLLUNAWlGJITxcBIequLjrbWn/rkXY52Eebwr0tWJHR6VhLgjXXZZBhh5JyKy+fcmdEDyoBO48pF7lRSRxRip7eTCzcV5d6GcF7BOruzxrLQc3LyRQf8PDWdSaKHzIJJLzUinowChUyE3k3UUKORsQyQUV2LvR38gSOuBps0qQq0IhsxkQ7SPBzLTWPde0ROtnye7kCgWHYDqZnfE/BuLvJ9j0KJOCXz45vu82H5+Z8sw50gMfqsr2vabhHRPG3yiWWFp4QmSmQa2/ZPz8iD/JQ7detdFt3Zv0IuBR+l0LCqxUEiD4OkG7D+4GNdiryAw0AtePuw7mC5fTnY6QFqkK5VIr4WuVakEWW4y+JHgrCs6XOd+Sr9GWeC+OxP9euxDhbKNH3l7WGypKFHSDzvzr0C37wbKhXijfYvKhTo5RIgQIeIhjnm83FfI3FG9ak1Uq1oZRqMR//xzEEaTCb16dURgQBiSk9Pw4QfTcGD/SYwe05dKLFk4jYSSl78unY5rV2+gfIUoShz4+njCzd0F+/89hq+mz0WpklG0I0m8ynoxSEpKxciRn2LylH7wo/WOER3aVUOeSoKNn25Hozer05rJl6sIBOgt5jvcRPLMCTh26hi2H5gKkyIFmUabPYhl1g8DMG7M99i0hcli88ysYyxNz6ZC6nOW8So0cnZuzjGyDkW9hdUwHip2HlPLWJ0jk3jau2xtvGPQbGNKJ6G7MTaHSZuzjAZYuErDxL3/Mnh94KNhA9YRrqyeupaVCgN/TbKOdTbKitQAxbgPvK9Wa1+/KjV88Xb/A+idPJwmxru4KKgXIPFalkokcFUq7PYvAjIN7PPfyruF+GspOLDjAk7su4LwUF98OGY0PN0injsDUbFiGTpAQCTPxYsz0vNOFZgVK1duQGJCGr7/fjLCwx/cmeyIu3+mY8f+QkJCEhXUREezQWzSaUiOPXe+13GdvDx90PvNdvh1yQbo9Lk0Lfu1ZnWQnJJKZdeEHH0clCoVSZtOiNR6zJjPsWnToseajwgRIh4dEtt/INGBJO+5ubkhK+siXF3/y21NIu6G20nHMWHcQtxS5uOit4ERUZlyJNpyYBCIImEvFyStShm+6dAYt+NS8dX4L8QN+4LQoHlnNOhSEb/nMrl8Whoj0zw8NHSUWK1l0hldrg45uaxQEY5YSp7QLJcxb0/JpVxIbuphauYDOSf5rBYb5DYpXM0qZK2JgfzNCEiUUruXkc5ggYGnOWdkGx1qIC83RiL6+7FjisZZXYgQ9HHwWRQIMQHEf7KiH6GhyKqx+afreHoi71YTClYidRKKYhUnQXU8NVF4zaXEZDpVa5TIz2XLSrjByERSALPVtgGpRihj9bAm67F0/jAsWbYL5aqF4yon3HO5d+LtHCZ5quzvj5TLqTi76BRq16yAFq1qoka12pSMfZGepHVf7wWf6oEwhrOLo+LuzHsnQ88/e24ONIuT8Ntv86BUFvUjuz+IpEavN8LX9/6j7UI6Zdm63eHSJwpHtl9z8N1EntmRhCTfu86GwDgjYqI5AS2VwD3DgvGvN8b7Ax19zB4GJHn2ypUbaNtmCGQaOaRuSrjUC8DMzm1RolQQPNTlRO/YJ0Rc3E1ERNRAVlYWXF3Z4IMIsa56lUH8/ObPX4mtW//BtGljEVEsEFev3kLx4sS/nNtLwOjgYU3O10SW27nTMPz51wK7j7eI54ufflqOQ4cP4Ls578KAHPvAXYaBdbPquEWN4JGtkQmyegnMVp5ozAvmA7su4utP12HpX6Og0apgsrL3EhI6LV6PXxduRWikDzq/URtyKsUHNHI2X7VMmJI6iM0v35xEpzdyUx2IQoE4vJCRYa9n3Ph5Xbify21iTqWwED2FVAZvTp4KNZZcOB9zqGVy+/PErofAhc+3RRjrzL2ew4hNX41AgirslwuEYE1NycaODVfx9+Z/0b1ba5QrH415Cxbho2k9cDAxHrdyGZHpoWaf10ejgT7PiN++2kW3U/u2TdC4cVV4uAc/lt3K08KePQexceN2TP/6wyLPFEiv58xeitDQELRr99ojz//KlXhERj4cWfnttwspAUq8Yh1xJx2Rk5uBqlU6Y/PfixERwUI7MzOzMXDABKxePeexSFzyO6hVqyPt1C5ePBR9+naEm6s7GjeuBaVS9OJ/UpBAIDe3ki9lTSXwRU5Da0Cier69dzaDGXlzDr2U2+V5Qux4FPF/j0C/ylgwvyIWLFyEFas2o2K1COgjnOBTxQu/7DwEGG24npDLSAITP8kaLNBADnftq+mt+LJg+o99MfbtRbBFKiDxU8PEOwhv3GIFs5szI8rc3NR2wlEg+4jcR5psgGxnGr1vU0lh6BzArOd5sapQSiG3SmG22GDqFoS8fAOQD6RnsYumkAAnlI5k3j8XT8fTqZ53sRl5urFSwwpVrYsaKqUCCXPO4GZgKir0rQR/77t3npFVFEhDYlZOkK5nxKMTL/iNvNgmhbVQXAsEZoZO8Cji87NwcjQ1G2lJ2fT/+CRW8Ab7suJbQ9YzUI4LyXlQ+Unx5oA5eP3t+ti97RxqDmKyuaoR4UhJyEJighwXTsfjyPnD0KhVWDR/FkJDg/Cy4MORrTHvy824btXQ7zKwHCN/hSYFlVyOsLBgXL9+E1FRbBT9yXCnJ5jgP6XIt0H/wyW4NPWgrHeF6ABIFFLsPRgHCGQ1P64Y5Gw+5NLcSjpR5VLonYF/jl7G4wzOk3WIjiqFNwc3xoE9F3H5/G2kr7mKvmtm0edX/j0WlSJaPuFnFyFChIhCxx2pFAMG9EL16hUwcuRnCAkJQIUKpaFW1UJgsCdNtjYa9dTz12YTbB/kNDyCDVqJVhAvCm+/3QMpqckY9/6vaNqmBOrULwWVTAk/DRu8yzaxusFoMTmQjAqJHAq5DFmZeZgw6lecPMZCV1Zv+gBqrYq+Ssr9Cq02K61vxn7SCW5yJzr4J5WwC+l8MyMVk3RMxRHspIKMd+hr5WzA1lWZ6zDAemj7Bcyfuhlvze2MWzJ2TrUWIaFIaCRdTykjOD3UagSRkCRaW7E6UckHbov203iqVfDVau7a6RjlxrottXKuTJE4Id3A/L51FiOcPNUYMrQr3urfDu8NnU79UK9fS4HCLIeHSo3Snt7Iy9Uj/kIKzp26gR1n05GUlIZBg3o/wKv0+aJ+/RqYPfsXOtAWHs4IPAbht2pFZFQYzp/jA6zPEFWrlsdbb72PZs3q0Y5qIvFOTU2nJGBRuDh72InTiIgudI91d3dBXl4+jCYjlIpHJwpJTUm6HGvV6kTTsT/+6Fv7c5999j66dCE1laiL/S9DDJd5cRCJRxH/mUK5X/92qNM+FKeOxGH9lrPYPX8fVCZG7niGqpAexrrnBBDipUGzsi9ojUUQuHs6IeFmBnATkFVwB4o9ZBFhtUHzWyIkJhusPkqYGnjBJqRT3wukM7KolugxoIl2x62dN3Hr8E1Ue70iyrVhYS4vEwxaGVw6BGPriqMwGc0ol6GD1WzFz/M3U+KySvXiqNOoND4Z15ImnD6rlOrHRXCENzx9XHDtVg4kwXcfHCCJqERW9nSIx3tjwPR2+GH475CYrHA/kY20/dlQl/KARCJcshXAzM+ohUtWg0aCVBIO8wTo9HothIR7w6Sy4YdJfyKXGJcCOHnkGio9248vQoSIVxQVK5bG+vU/4eKly9i6ZT/Gj/8Ghw+fsV+4nbuw1uH1Z8/GoGzZEi9obUUItTCxSNmy5V9623t8GnUKeRAIWbflrxOYOmEVvf/d/AGoWLWYnYC717IeVXFwN4SXZIO/Cwf/BtcwN9QcV6+AD3tJQGS+388Zh3eHfA4vb1fs2HYK6ignXN4Xh1UL9qJ6rWiUqRCCfr16IyDABzLpy6W+I7/XgQN7Yt68Ffjii/fv+hovL1ZTPWtUq1aByq43b95DPf1nzVpAu6X/+mvhPX0br1xmYYoCIiPDcOVKHEqXerzjDakf16yZg9S0DOr5uGzpH/TxZcvWceJRhAgRzwIi8SjiPwO5xAelfV5DdDMLapZKRMS3QcjT38LkST9jw879CO8YiOMneXJythGXz93Ge++3fcSlCIl6JlqoLVz2EzLT8zB4UEfEXktE6RIkwU/0X3tYeKoKijNlA3+YYtNoW5veyAhjFyv3WVQp4OXFque861lQbEpGbktf2FzkMJNuQDLCzTsVSWojIYkIZFIJFDYp8vOsSJcYkZ3LRvmdeWJ1aFQAQt0Y6eZVkxFc9k5FE3uth1rj8LhHi0hcPM26LJ2LeyDbyPaFwpIfg9lsH7EXuE5hfkLHpjA/ks6t5yP/zkqlQ6djnvAe3vFIisfrFxmJpfZh6+UfwnyMDDp+ccBl5ocvJeKDQbXx95e7cGT2YTi7aFCnVk28Nasj5FKhzb+AIjNbk+nnUFBpFJFnMQmSBFqHxMjngRAnLwwZ3BL9R/8Mt4p+SOQpm8J2qREQgANHDmHcuCGPNX/h+xLkggbLVTpVywpIZCFxPsEZCKgUiCyznnZL9OvTADs3nUaFTDPitBZkBhCy3ITIkzrc5sQ59Z4ib5cDCoMN6Tcy6TKLeks+LIp5hqFY2zBkGTPQeldl6NKAFq+Nw6wvNmDZ/N2Y8tUbqFWx/WPNW4QIESLuDgmkUhlKlyoJpUJLk2UNBgP1iuvYcSAux9xAZFQge6VEjZMnz6JSpTKPuTHZMfnchaNYsXwLhgzpC4vZCk9PHzg5OfoRirg/Yq8xH8Sff30XMpkESmnBpZ7UxM5B+WaTfUrOTV1rf4GO3Wph24EpcOGdhJJCkmM65d2GVLKtkMBN6QSZxMvh+0s35DjULvG5idByj0cllz7nm40O1jLRxfzRpmd1bFt/ApHVQxHs5gIzr5OE1xQFSZPWytn8rHy8WkiYFmTVgrokj3TG8XV3UjCi1MRl5UQOTddNyrwPrbZ85JtZB6WebyObjXWJqtWumP3DePTt8wGWLNgFHx9X+PkFYu2q7+HlyX4HRWG1sXlIJcQPklkJSbg9wfMKlxHQpEld/PDDMtyMT0JwiF8RqbUU27cfQIMGNR5z7g8/qE/I6uHD38KRI6foQEWrVo2wd+9h9Oz5HpVgf/zxcHh6umHgwPFo164pfw/x8ZbaU7l37TqI19/ogMeHBOXLl6br3bhRbXwwdggNmpk2bS7q1euKN97oiIEDe4mdj/9RiOEyLw4i8SjiPw0ndRC+mvYJIuZ/g717zsNUwQsSlQwXz6VArpfBy+XhfBasNkZ8ZJtioNcZsTP2En7//h9cOnqD+v5lO5uxatoOVH+7KuYNfwsymRRyaQAvOARCixVkmQZGcrgqgyCTMOLtVSUrPVQlsPiXqejbZyJ0312En7sc1nYBdq8eFU8PlEilcPXSwmoww7jpMlDaBVZnktZcUOwI/xK5tsDv6C02Gi5jy7Ei22oAUpmE2RLqDK+TOfBvXNBN58UNyYmEhyCb+yEKxCEhE2mPm0KOchNrUy9Rm1yB1Px86HiBqpGzojYpL9cu+yHvo1MurU4z5zusLyFHtbxAVvNCWij0BSmSQJRpSKokD7/x5B6UBiIfJ5+Jy9RJ+jFdb4sNB/48A12WHj/PnwxXVyfuu2WB3nKOvuZU2g1YrTaci72NTauPIfbgDXRp2wBjP3wdCmlhOc7zhbsqClXLRSHYby0qyb2xOZ6Ndrt5s9+LNS4HFSqUgkbzZGSo4LlUmHC0P8e/A38i0dKb4R2ogdGUgz7dm2LYO+2Qn6dH/c6foGS5IBy6kgipTYfgqwbk+ymBAHahrHVWQHtTj16Daj0S6UjkXPRz2vKRmZENL0+W2D3vx0+RdDsT5auG44+DE7F2/SGsnf0P5vy8GbXmiMSjCBEini1UKhVKl47GH3/Mw+hRn+OTTwegcmUWBnjyxEWMGdPokY9zRLatNybij3V78e2sNTAYTAgPC8f06Qvo80eP/WaXXIoSyAfj668noXLlVnin92x6/8yF+cg1ZbJtzX0ayYCnQBB+9R7rchz+YVvaxUg8PgnknKwTCEehLlHKVFBKFdS/USZl34vZmoS1a3YjV56JWo1K2sMASciM2cbD/ozC4KvVYfCVTHsMbojXhzTEbR0j53I5cZnJZdRuKqXD4C4hHV34QK2/E6uf5Zx4FJYtWNfkmEww2MMJ2WtM/PPrOMnoo2aPW5ANDfenJJJyNs2z76+nTl/C6VNx+GB8F/Tr8469hhAGMclrSb2WnRuPLX8fw9Jft8NksmDD+l+gVj9eCvPTAqlp3nmnJ376aQU+nTLS4Tmyznt2H8bIEe88l3Vh8uoMnD9/mXY/jhz5Nl2HRYvWYMGCVTQ4RqfTY9QoFl40cFA3WG0GGj5EgmmI1U71ao+XRE28HUm4DMHFi9fw2WffU1/L116ri+Yt6qJfv7H4+ecV6PdWl8eScosQIeLeeMma2UWIeDbo+WYDNGxcFoafGeknM9oglUnsnWQPg4sXYzFm2AK0bfopFkz8C2VrR6BqwxLQOquw7ZcjUKjkuLo7Fu1aTcKRw5foe4gXEvE9IiDTWzeTEX89BTEXbyEmhgWqvOqoXqMc2s5hnaeSTPN95dDp088AVTyAmsIo+2OCdFV6KQrzlo8EIUn7ZYdcq4BXBT9MmTyfSllu3UrG9u2HsG3LCfR5fSY+fGMhJvRZhLUzdsEz1B21+1ez768vA6p3KY+j687e8bghj4TDPOE+8AhQO6tgvpIDWbgzXF0ZQa11UkFbzQfpCy7CKcWIPE9GGqdWcoVvTD6kRgu0t/RwuaZDmcp3ehc9DP7++1/UrtXbfj83R48b11Iw4+P1uHTuJqo0ioZao8Ctq89eHiVChAgRAkqULIYff5yCN3pNsPvCpaZmPtIAC0kI/nTyd2jc+E30eWMqYmLi8fXModR37c8/dyEoyA9+ft544/X38dlnjESzWCzQczKKgKT1xsffxuXLsTh69DR9/lUH6RA9d247WrSoS++fOsnq3rvh0PaLuHk1FRv2f0RJxydBaKgv/IMEgvjRIJVK/i/qKkKONW9ZGb+v3U/T3cm+uH37Phw+fBrvj5mGNq2GoW2b4ejfdybiYhMx68cB9D0qTpy+aDRvXh+nT1+kv5uiID9dIil/HnBzc4HJZMKePYfQujULmSHHjp4922Hdui0YPXoKvvhiLH18+/YlOH/+Ctau3YJLl2IxePDHaNjw8TozCZlZs2YHnD3LrtEIyU7CaiZO/BqzZy9BQIAv2rZtgpycPFy7Jl6jiRDxtCF2PIp4JeAk90Hnjs0x48v1cIo1QpepQ3Dp4vjmxw2YMrLKA99/I+04Ro6aA9f2ESjZpAa2nrqEs9fOQ3YpAy639Uhr6wvINTiXaUTTsiEY8N4cODsvgEwhhUYiQ7POVfD35pNIOM/SiQmKlwnAujUf0/9VMtYx8KpBxg3JpzZqjtfXlsaA9+ainEcIdoMFvaTx8A6jKQteRjMUA4ojlyRSG3g6ORnB5tJiA5dnk4FtFfd71KhkNNVaYpXBKFEhM4WNgOvyzdB5K5BpMSJMrnUYhRe6DAUTc+FxZ60Wqfls5DuLpys7ubBi0pkn4flwA3ONXG6XGu05fZ5Oyag3QUhxP7t8nL1WAQ2XBgnQcjmQXOrYCXv7egrREdH/c3hCuyaLdVBKeJeoVc+3jQW4WcoGBKsRn5+NOo3fgdRZAedwN+QbjPBoFozzV/X2ZPAcbyMyF5+F+WYeJn386AnMTxOC5+SgZnVwZP4xuLo4QaqRw9tJC5vFioQjSZBqlLDa9M9QAs72oWBnJ1w5cJ2mSleaWBdyKfOjkkncsWxMb0xJXolDe2PgVtUPWelJCP2bkYCBZgWaNCiLfjOaoFRw/UdastEaRy9WRo34it632sy0KPf1cMMf5w7Rx75bvhtrvhmKNZs/QEpStr3j4kUmZ4oQIeLVAJGJhoSEoHr18pgw/gcsWvwFxk8YjA8/nIZly76l0sgHYdpXc+Dn54nZ895BmVLR9LHE2+ycNHBwJ7zWrCaTV9ps6N71Q7Rs+SakMhnMJgvq1quCkiUiMHEiC9oScODAeirTfNVBvPO++moilMqv8esvuzD1y25UnSMQw4L8umXLivSmVhEpMKt1LFx+LLE5dv+bebckeZ0NFlihgwzewhJRvUZ5XMw8S0W3et5RSCTNOUajvfuRQMVrK0HuLMBdRaTbTF2Uz1Osb+Sw+y4Gtj8J8uraEUFwkrNzfyxPptbxmkuQkQsWNgaL1Z6KbeLNBkTpQRDkzFUU0Nml16Sbk0CqkDookojMt1r1Mggr54qYC7cx9N2JgE2GmrXKIjMrE23a1sSULzvSbay3MHL88oVbuBGXQgd9g4NZ7fAiQcjlFi0aYveug+jWrY09XGjXzv20C/F5Ye3azdi1az/GjRvq4BNKVCyffjoKQ4d+hNu32fVS06ZvOvjOvv/+AFStWuGxlkuSvQmIlyWRefv4eCEmJhYlShTD+vVb8OWXH2DYu/3QtUtreHk9Hoku4uWH9AXEBz15wsB/AyLxKOKVgEIaAi93ICo6EJf/ikP1SE/s0KTBsvYs2jbaiFJlQpBj0iE1JRvTfvwLWg8N+netAzcPJxRzCcaGI6fgHuoKr5IslU9JEmvJfG8ZkO0lh+FcFnI95FQ/u/3ENaCcyu61JzOacHrtHlgUUuTWcAWUEoQezMbl2CQMf38u+o18DdVDouhrmRT21YNaVgaVypXBT3NteP+9hXBSm+DSOQKxWy/T57OdFMjOY8Uk8Swi0KpkDsSjkFRNLlLM1oLtaLNJoCaj6aTg5tJtTw+VvYg15RmhcFLak6WFYljHC1UhfdpbKsWNrCz6f242I/t8i0h8ziSzQinMzR1HLrJUyMunUtiK8GWTTjkCjTMrml0Dve1EYy4v0D3UcgfptR9fznVjArRe7P1uTuw5oUuAdAzQ+buyAt3TVUkvNAjOSnNga+4FiwzIgg3ZecD1KzehN3LZklqG4n7euKCJw4I1018aOZu32hcNG1TEkeQk+Ff3pd9J4r/x8MgF1v75NwJLKzGk19BnRLix7z02mxXjFp0ZF5KSYLGy71Mu80KUZ0Msmd8Q+abLmDXzNxywXUDMMUaa//n7xwjye/RReRsMOJp8EaM6z6P3N2z6BFIJ+x6HDxmK4wdv4ujRc6hZvwScFR7YvnsX9u+6gGLjy9OUWZlEJB5FiBDxfNCqVRN88sk3qF2rB1avmY0GDWriu+8WYcyYgex4ZrNh+Yp1yEjPRqNGtVCmTDSsNkbyHDp4Amv/GIdci87+2NIlW9GpcxNs3LAXzZqRjj0J7cRasXoSJXTIAAvhtDb9dRDXrl3Gr8vHU6+2MaO+w6GD5zFw4Af4+OORKFdODLkhsvjPPhuLWbN+RrWKo3Ds5FK4cs9qJznzinZRau2kop4nXRutgnUMkwbLJNzbkV86E7k2IR6ZVF4g91jtczs3B7pcA9zcuTc0JDDwcBrBw1qol4T5eRWSIFN/5EKoGcAGai+ks/WtGcDIu3Dn0vbBtmRdjoPEOpsPEOt57aaSSe0kZD6fXsvOZvNxdefvZeufa8q1r1dBTciWnWnkpKjZgOAoL3w+/02oVAooFDK4K1mNlm9mxLmAmJgEdO5em3bvvixo3Lg2vvnmZ0o8kt9Xenompk6dg7w8HcqUaYqz5/5+5v6ThBgn8Pdn11SF0bRpXVy6tAtnzlzCyJGfID6epYxPmPAu9V583M7crVv/wUcfzcCHHw6m24DAx8cTkyePwqRJM9G9ext6jCGqnwkTvsbIkf3FsCwRIp4yXv6+dhEiniJ+XTEWi34dhYDaIbCsuwlZXW/07j4TVcuOxOcTV6Nrsy9x9PczOLjiBD4auhQbVhzC2TNxWPf9P4iqHHLH/AjZqMmxwKwoQtQUkhtZlFKkhWuQGaSCWS2l9+UkjdldQcmif7edF+VBHOHF/DBr7gCYb+fDyonGZ4msM6n4Z9RW7Bj4J/ISWVH5X4VEfX9S25hlgCnHiFKlGAn+sqBR44pIOHybXsCmHL2NK8vPoUw5Jl3+8YtNiIu79cjzfCS/RZsN7oGukJdyQ97iK/bO1cIgnq42qw0yhQxObmrMXzyCJl8+Lr4etQaZqbnYu/9rhIcXXLCQgnvwkJ5smXIpLl64gZWL9mLX32ewbOmmx16eCBEiRNwfdz9mEmkk6XBc/8c8TBj/NYoXD8WJE+dQokQjjBs3DWXLNsOnk7+nMsaPPpqJ/v0/QHJSGsZ9OBNh4b72ATMBLVrVwbatBxAVFXrPYzYhLdq1r4PhI7ugYqUoevxt2KgysrNzMWxYb5qSS0gUESzIY8z7/dG8RU2sWc26vZ4lDDoTPuj4EwY1moUtK47+p78CMohMSMf7YfeOM2j8WoXHDpZ7FiCeijduJCAtLQOJiSno1XME0tIyERjoR0m3pUvXP8ZcH+3zhYQE0lCZL7/8Abt2Hbjra8ixQa1Ro3TpSPTq1R5vvtnpsUnHgwdPYNiwSZg4cRj69evm8H20adMYrq7OkMvl9FpsypTvcPz4WYwd+8VjLUvEyw/y/b+Imwix41HEKwYP5wqoXb0CfqvWAKWXtIdl/S0oi7lA5qnCEWUWlaK+1roC8rJ12Lf5HNZsOIKFs7ah1qT6yAxywpU0lmYsFMspEWqkhFM9LluASl5AOgqPkQ49G5NtuN4ywPci65aT3zZglccVOO89h83rj6HjoLoY0moYXmU4yb0RHeENa44JGd+eA6rwkfAcI/SF5NNCiExhyHkXqslUMGJOD/Z0xJrmkJMF0MeDg5kUSxPmgZozmuDyr2dx6JM9KDOuFkKLsRFYFe82FNKoD8fdwKVzt9kyLHxEnBdBhAQiSLnFJD/rThwBcrnkmSdsg6/3+UtsH/JwY52LqYlZCI1k5FKIp4ddqk3nz/cl0kVAcON2rr3j09mZvZ94ixLo89nof0QoG8HPy9Xj3B7WfQfe4anhgTTCNhSmvr7O8D+ch3Yj2kFRRPb9IiGTeKBSxSqIDtmI5F8vIPt6Bub9OQy6Ky6A23aYGnhjzJhPsWzlWKjldwbEPA3kpOYj83Y2DOV9INebcPj4eVSsUox/nbzzWRKM+nUbwN3dDb2+fw0erkw2+DhYuHAFzh+7gS27P4WvV1EbCAky0rPgF+KBVRM2YxU2w1rFHajkgs1/70Hvd6rDVSHKg0SIEPH8ULVqeTrt2LEFRoz4FDVrVkKtWhVRv35lpGdkIOF2Mnr37oSJE2egYaOaaNDgTQx7rwtG9GuCHLMOWiqZZcfS8hWKYdc/86DVkHO/FTab0aEDnXS2k65w4lmsULLBlwkfLsLlGJbknJySSsMnunQZRDuYXn+940t1TnsRkEpUqFa1KqZOnY3Xe/bgMnge4CcVAuzyoZByqbWNPWexOYbMgD9OQmaIBJ4odCw8eFFIs/b3cMWve8di07qj2L3uFC4cvY6BX7LgMxPvQNTzusZDxVQfgVoWxEi+1xQeLuOvZbWfj4Z1ErYKa8g+C5g0WiIhHt2su7CkOyOps02sizHEmdV3cTmsU/FaVhZ0fNlCx2OkO3uNv9bTYVuRbk4hhVsIv7mRm+yQyh3pWpNOzbZk6MxsGXre1Wng3aJmqwXHDl6BxKZEwzoN8DKB1MVjxw5E375jEB4ejDfe6ICePTvQbsf9B5Zj4IBJqFG9MqKjiz2zdVi4cBUGDXodXbq0wpYt/9Bu6KIgMuimTeqiWbN6NNDqcZGTk4s+fUbRjklyHCoK4ndJ0rRJqjW5lS9fEosWf4WBAyYgLu4m3UYiRIh4Oni1z8Yi/pMgNU3RUfS7eQuePrMeK1b8hYBwCb6a+htMaVlwdVJh9MDOUMhlaLFnAt6e1ArTh6/G4YSbQAIhc5hvi1wwweZkGHhBQgJrBO8YQjiFH82BUudIkOV6ypFSXA0TKWryzEgPkCHH14wrkzfA3+yMZi0rw1nxeP4l/+9QSllX6eKNI/DJyOVwLuMKmb8GR/Zfh4UTeBIuQ5Zzsk8r3OeEHNn8AilJCkdyc3dSwCZT2r+bgGBvu1SayJvD+pZF2ogknPviAFjeM6D21aLKpHqIT2OF5cnj8cjPFC6CGA4fYebTFi5ZhvB8rqkgtlrYFbkHJRIY8ZzBnzZbbTBeSKD/u1RlMigvDZsqeDI2KfEJ9AYLFNx3SK937AglpCRBdKSn/bWCvFtYtu4yk4rrnJi0u2Q1Rni+5h+BhEM30a19F7xMkEk8QTbBghkzsGnTHjpKXj6qJGb8sRBWvQXpUivkzlJsPHwYXWs/HPH4sCOPErCLj9F1G6Pat74Y/+UyeNcMws8b/0E1bRZGVChh934iPpP16tWht8eFIBvr0r0aevfueteL5e0HNmDMmHkoU6cYkuIzYGrsDQSqyU4ES7IV+Xo9XAvskkQ8FMRRaBEiHoQH1VQEb73VjXqlkWCGf/45iLFjp6Ny5TLo3r0dunZtg99++xtdu7SEp6cG1aqXg7uKHz+hhNnGaiuZzQS1WgorJ7SsYI8L0s81K/fg08ks7VqAi4sW388eg0aN6kEmk6FL5/bIzc3H998vwqhRn2LWrEn08VcZhFiKjb2Jb79dTD3yJOA+hhImiVbKjJQsI7CnUHPpteBzrZIp7P6QEkpYkkF1x/e4cjl1+87VEV08AJOHLsPIZiwYiOCHzcMg4T7VQU6sDpNKBKm1BuW9eM3DLUPI4CO7X1RBYINEwgdfpYx4dFWwekzKxXzRbmyfydTr7Z6RWdzORkjHlvN5EP9G4bMJHo9yKds2N3KZb7OLgtVlNjDCUwoNXJWMNHWyMdIzJvMUuy9VYv73WzH726mQSdlg8MuEhg1rISDADxcuXEabNk1h5d+9h4cH+vTtRP0Ox44d/FSPD4WxZs1cfPPNfERGhtNQKKIsKVqXkQDBESP640nh7OyEY8f+grMz+z4Lg4TLtGjxpj1Uh3RXrlnzA/J1+bTD8tSp8yLx+B8E2dWeewOiWGpSiFJrEa8syIX9m2+2R5UakVj2+xi4+7siuLQ/tFoVlUk27VcDm3/cj6yGjiOiD4uIw9mUdLxazRlXqrvgWiUnxNRwwe2yTjBpHItgs6scmZVcMe79JcjMZCO+rzJ8/d3Qe1Aj5P8ZD/2eREh4h+HTAvWBzDLQqR0SwK2sNxrObUVvhHR8FUC2weFfj2PcuH4vrRSArFfr1g3pSDRBv35dYdGy31C56hE48e+VZypVa/paJQS0KIa0wwm4vC8OO777F2fOxDz1ZV24cBU1qgzDwQMn7/r84X/ZMkvXCkeDbpUgjcuHJNkAxcrbtMP1bjJwESJEiHhex+m6dauhZcuGmDp1DCZMHEpJq1KlIunz078eh5kzF2DwkC6oUvXRO9T/3nSIko5TPxuCM+dXY+Nf3+L8xd9w8PAiNG5SzYFcJCQDCa7YunUv/v57D151EHn6kCG9cfLkOQwePBExl+Ke+jKyMvNgKDQgKvw/d+cIeluwexRUmldjZGzD2sOoXL04wsOD8LKCDBJ06NCc7hukC7ZOnaqIj09AnTpVsHv3wWe6bFLLzZgxET/9tJwGyrz55iisXLnBsSZ/CiDEYr16XTBnzi/0/6K4dYv5R37yyQjq/ZiRkU07pjt0GIjvvlsMJ6c7yUoRIkQ8PsSORxH/STzMuUsYZfVSVwLUwLpFrJVf6GKaNKgTRgz+CS76fFy7zjrFAn3YiGceTw724fedNeynRAJQcvPNlChTGGyILaGCJZ2N2FuJFJg0u/FOPRAyja9oTmw2tLmMNGjeZSo2/DIZfv6eMJuMMFuskNg08PQIewUCaBjxVdy1IYq3bYi2TWpi9cq9+GnFDlwvIYPVWY58PdtONhsfGeedjmredZpTyBvS28sJMqsUHipnSJNMiNTJkROfjVvbDsNktEBf3AuurUKhDXahcvjwcoF0dJzgxOmrdJqWwe7n55nZd8YWTieW+DxHObXDx5DcfacUXpvCPKjylVLk5LBReMthtszccqxYrRHKRvJLerPOAEOzkji4n71GyYNjVBqerK1l9zXObJ+UpOQVDC3pOCHFt5VfNJMZhRT3R+6JFFQpE4ZyZR+c7v6iUDQ4hqQNKs1AUJYE2/84ibcnt3qk+T1KcauSsZCCT99qiUXpW7A1LR4Z2jy8M3IyZnw6GrVrV7CncD8J9OYrmDx5BlWzvfPORPy4aigaVezi0A05/N1u6Ne7Nfz9IrDpr304f+4WXHM1IHtEZPFiCPKo9MTrIUKECBFF8ah8gEwmR4/u7elNQEhwEAYNegO/LtmCcePegUzCZLNmaw5NEybINyfRabaJKQOE5GInuRPeH/0jOnZsii5dmFwyOpKdF20S4Zwv1EbCyrJ5zp+/gnq3kTRfMiU34mVHSIVXSYbt7e1J/TiPHj2D98dOR7+3WqNV2zL2jlKFzHHgSghZ0SpYN5iUd0labCbYbAbcuBGPTRvP4Pz5WFyPu4lr1xiJM3Z8Z5StG4qrZ245yKY91ay21siETkWhi5GnaEMBlUyQ9z58nSvh3ZFyaSCdquWMVHVWsOXVCpDiXBpbt8NJTDZ9MT2TTv+UskG+JsFRdqm12cTqOqWUnXezDKyG9+brX/gaQqglEvPZoKDObEZ2Zj7+Wnscy1d9ZFdO/D+gRo2KmP7VAkikEnTq1PyR3vs4fKGnpzsmTRqBhQtX00ECEkp15cp1jB8/9LG9HIvi99//plLqQ4dOYvLkbzF58kiH54mKZseOFTRx3GQyY8GCVfjrr124zr3DSdCNCBEinh5enTOuCBH3gCDhIbLOwlDLnCGTyiHTyCDhcmmVmhVeQmeY4O2nVCnsz2vVRnoWjg1XMDm14EXI/XHsxJOtgAiC1IZ8jRQxZdRQ51vQpOs45gtJnpdKYLPYEBzoibIdS+Pb3m+yZUoj/vPfqZu2It55qyIqV6yFN9/7CM6vBeNkfoYD2RtdOpQWf04mKawWG1KhR0YyI4qbly2FG3tvwHggA2VD3dG1R1eUKh0JXx9fWmScv3gA3bp8bF+ed7Q3rugZIXg5jklntLw7VaaU2uXe4OQn1XUXhsA1Ejm0ID0p2q0pvIfPw5Kmh5IT2AJpmnSDSXtMQUEOKZClvX0Q48p9Gzlys9gFWokyrOgO9Wb7cXZaDnEHYODr4hLNJD8+3qyArujhi537zuLD1SP+73QAP84cTv296gytizJln04gjtEahxmLVyDxRjqKR/ghMMQTLWq0g1arRgWvCLRrUhO7FlyHrIwHzhnSMG7Kt6jRvQKm9x1dRDL2YJBUUAKLlXiSmdFrxEzYXIGYUipEn9NjUPc56Nz1FEaO6gAfT0YKu2hKwoXtKmjVsjVMRmDcuG9QtlxxzJnzGZV8ixAhQsTLClI7ubkRwomc0/gx0Gax++kJycF5Jkb25JrYwJ+rwoBf/xiFaiVaU3/B+w1MFRCPwMVL22jozMQJMynBQboiSYcXmWZmZtNwHJLuq1IVncd/FRLqybls6WyMHfs5zp65gbEf9KMErASMlJMgz24hk5qaDY2/C91mUomGdo0dPnAOq1fsQ2pqGrp2bYvWrVojLCyYSheJxL169Xb0/ZWrRMHFTQN3FTsveqsYqWixsfqMpWIzyTJdrkRxnzrEWuS7lRV6rZBCzZajkjH5s9582050hrgwkvM092kXpNYxGWxdqvvp7ijRzqczEvxqFnuNj4Z1v/lrBYLWgizjRfpfmp5tMw+1Bst/2Yn+/bvB3YU1C/y/oF2716gdEfE0JL6KTwvXrt3A0qW/IzQ0EGFhIShZsjgCAnzpc5Url8XEiV8jJCQA06Z9SINdJkyYjs8+e/+JycdNm3bixx+X4dChP7Bt2166nJiYa/jgg8GoWLG0/XWEdCQgv4H586dhzJjP6P39+39/ouWLeInxAqTWAgXwqkMkHkWIuA9SCIEVLAUeNSBRIoFJ+XhHGb1WittRrBPAhXexkTCTttUr4Nz68xj0z0x8O3sYlJyAeBVQqVIpePQpgcy1V+EBM7JD1bSLT3oxFze2HaeJwkpnJb2o0WXrYfNSADIpdq1LRGiNUIya0AFRJX3hp6lqnycpMkqXCUdUmxK4/Ocl1BlZB7nJuTC7mJGx+ToUGgtMTv/l7lLg0l+XEF4/HF5ej5/A/KJQp255epNJWBjQ00Jmah7SknLg7+2GXZvPYNXcQ/h5/mQQj/vSZUKBVHZBbFHL0H5iE6z96G8Ye5moJPtRQTpv9v17CkePnMeFXVcxaGlPbPhiHWT9I2DdnIAb15ORlZUPn7u4PZAL5w4dm6Bx03J0XyZyJREiRIh4mZGcnAZf38ezrwkK8XosOxCSWPv995P5vYL3E+Lxl1/WomPHAfjyyw9QvvyzCSh7GUG2yQ8/TMWcHxagf79JGPZeT5St4ImtW45h9apdSE/PhUathKeXC27dTEdoqA+iS4Tjnz2nULJkKNp3aIymr1WjfumF4ebmguPHN6Fy5VZ4/8Nu+OfQcaSn5uDn77egdfMmaNy4oAb7LyL2ShIuX7iNaZOb4v8NhAwcPPiNpz5fIuMm0u0BA3rh8OGT+Prrefjoo+E0hIqQi0TBQroSfXw88fHHwzFq1BTs3XsYDRqwEJ9HxdWr13Hw4HF8+ul3lMx0d3dF166tkZGRRTsg4+NvOxCPhVGyZCQ2blyI9PRMul4iRLwoWCwWfPLJJ1i6dCkSExMRGBiIvn37YuLEifbzIGm6mTRpEn7++WdkZmaiTp06mDt3LqKink4zxrOASDyKEHEvSCTIy9fD3cUTgpBHCPTwCWQnJKOOSTHSU9kofUqGAfpcxwASe50rdL4VrpuLWo7wLjjTLTZ6mq7iI35GK76P20f/bR3qgqoVB2LFqi9R4X/snQV4FEcbx//nuYu7QoIGD+7uXqxIoQZFSqFQChTqtEiFflWsFCoUKLRYKYUWdynubgFC3C/n+z0zs3vJHQEChOj8nmeyub293bndudnZd973/UdVtiffLsmQmewdw6bC/IIFH3y/AMe3XYLppgHNe9bFxBf7QqvVQKNgeaQyDXdx5Ph+ZKQb0K5VT1itNqQkGxGkvddApZKXwatj2+OHeAP2frmXrvMOcof+bjrKuSmBBt5IFZWwy/m64oyoSC0pVMMoXkBRKRGiFyYVHZJC6p1DUIjwDP1S4j70VpjSHYVikl2ZcSs6jc2061TMqOWh0aB+PfY9b8UxBe2De1hY0ZVbrA0mlmMeoTduZ8CvHHsoCA1locBqMSybeC+Yr6XDcikDsxYNhUpe/FT7yLXLb9TyCIQ0K4N9287h35hbyAh3Qb+aZfH8xLex7vu5CAsJh5tNiQ4NovDJvo344+J5ZHrLcer0UdSuU+kej0ej9RLbryL8Hq8ck/Uqvp+/AYs274Kupi+uRGow4ZM1UFgFyA4kQYgx4O25Y1E+4v7KkuR4Xh4l3/OZw+GUDMgDvSAQzzEBgsDumyq5EqmmTAdBEzcVm0jx0bBJWI1Cun8/3PAoCYUAlgeGuhKDxLhxQ6m4RteuL6Jv3y6YOXMySgcyyOUKjB0zHE0an8Sy5asxdco5tGlbD59/+j7CygTZz50g2HDtWjTOnL2AoS+/AD9ff1y9euseo6OEq6uWGnxeHz2PGpR+nrsNer0Rm/48iomT+6Pvs42hc3VBqpFFlfiI6tY2IQsykveIDr+l68baiE0UH5IGVJI4DtuW3VsFgbUdqV4ahcEeXeCpZuPyUDFnX5KC7S/NzD5zKoGFYpfz9EIFjwr0fz8XFiES7MreC3P1pcsEA0t3cyM9ya7U7eOiRUZaFuZM34R33x4KpcIxLLs0QzwKiRGRGBNJ7lci2tK160s4dGg9nTStUaMyjhw5hc6dW1GDSu/enbFjx/7HMjwSo+PYsR9QL+Y//piPmjVZqpwffviN5pAk6RZ69HiwUZjUgRsdSzZ5FZnM72M+Cp9++ik1Iv7888+oXr06Dh8+jJdffhmenp54/fXX6TafffYZvvnmG7pNuXLl8N5776FTp044e/YsXFyKpjNCoRse58yZg88//5xac6OiovDtt9+iYcOG9L0LFy5g6NChuHHjBkaNGkWtvBxOXsiP/sRi06Nh40pYte801PXYACQxmQ1WAsXQ1di7bOB090Y6+1CaOTt8WuZUGbvKsRReLSOSeux/T9EokWpyNFJKKslkW3HdhkvX4e+rwKr16+FfqQvKuD6+km5xQikPhFIDfDb2I2Ds/bdzdQlGy8YsBxTBYCDXTBq03ku3iH7o/GNvGE1ZVNlOALuWr03+CNv/PAHfkWwQGn0nza5Ibb+2OcPmCVJ4tbuaGospVnEpKaF7iNfaRZH9vlnK/ygqRIrh+cePswGuVYz98QnwQPVyLPy6bCAbBAf1Ym3zThwzOFotbB+hZisCy7IcWEqVwm5wJDSBD7btvYEflnyJQF+yTemKAXjQAGBcsxEYvvp5DHlzHFRyFf6Oi4b7uTQMGjEWzwxvig6da8HtVCq91maTmebBIg82UthYTrJzPyrsodVZlrN0OWrlKpxZcwwn/S0Qrsawa28GvDIAa0IaZv82HNWq1niMb+eY34xTuuBjKs7TIL+e0chD/6BBY/DysGdgFdj4RiHXwmJjYykvNTPY+GhYmKpCzu5h987gPRyLLREqMe/fg6hQoSyWLfsGb745PVd13ZIfeh1Fy323kMlRvnw4LXmFiJZ06tSKRgIoxLHPocO78fzgD1CpciiaNKsGLw0bwyjlAXYDJwu3pmZRtk7cn01ghmmZLOdjKxsnkXyTDtsI0j7YWEsuU8FdxcZ1zYLZd7CJe76TySZ3k8QUO8lGA367xCb5w8XwbCnVjULGJntvpLPPmK02+IgP9242F7w/+Ve8MuwFNKzXBqWNh/1kSC7Hv/7aihdeeBNLl/0PQ57vjb59R2Lc+JfRv38PvPPOZ+jUqQX97anoeFV4LA8xEk5NwrTr1GG5SwknT57H3LlLMGrUYLzyysDH+XocToGzb98+PPPMM+jWrRt9HRERgeXLl+PQoUP0NblXffXVV9Q2RrYj/PLLLwgMDMTatWsxcGDRbOuFqmq9YsUKTJgwgbqJHj16lBoeiaU2Lo7lGRkzZgyGDBmCdevW0UIuAodTEJA8NqdP3sDRw1eAGk8uHJGvyGRIDFDh5NH8VyUsrZCwVRKqmvOB46WJHVCmgj8E/b0GpeKM6XYmts3fjx5T2iAwUHqo4+REp9Oiw6tNEX8tEXKDFalNvNCoYxXMf2c96jStgC1rj0ElebsKrL/IK6v/2IeRw77DmR+OouqQWhAkY7VIppscYRG+cPMoRbkUOPkCH1NxijKxsQlUXfbDaaNR1KhXryZV+b161TGHMufxIWOqnErjdetGYsKbz+HixVsl6rQS9e63Xv8JPfs0Qteupc/omFe6d2+HgQO745uvf8aECcMwZ840LF26Fnv2HEJoaBBWrtxAtyPjKRKplFdOn75A85V27foyWrdu7GB0JFSoEE7zVlavXjnfRGs4nMclLS3NoRhF8SpnmjZtiq1bt+LiRSZcdeLECezZswddunShr69du0ad9tq3z/bgJd6QjRo1wv79+4vsBSrUX+D//vc/DB8+nLqOVqtWDfPnz4dOp8PixYvp+8nJyahXrx5q1apFY9tJ/DqHUxCQPCCvv/sj/PtWQEyGEXFJBlr0Bgst/x2+Rcvdmxm0UM9EUoinmtHKCvFQdBYWIRDvNakQQ5dM9HwkhYRa02JhRdoH8ayTPmO20UTs8Vl6fLJ2GwQYaeE8ucgQKURkiJRguSfUciVcg9zh6qmD2Zzj2krXSbo+xHgkl6HC6Sy4prHrp0s0we9aFsJP61H5UAZCz+kBFfFctbGSZWFFMmARxP1o1ApaiII3KSSEn5RjJ2Ko9yMpRouFFrlMRkugnxctly8n0OIb7E09HUmRK+RUqbBOggts629h8YI3MaFNFxqq+yiCKKUDYgiUYXjN7pjz6WT4nMlEmEyDb88dw61qKnz0+nKkZBgQmSxD3K7bSPGU4adf/8Yd/b0PU8STg5S9e7fjxNV/cTluF2Z+uxZXGqhx1M+KpX8fBeINrIhtyeCjgkqjwu/zdz1SrYnHJSlT3/4Ayenn7K85pQc+puIUVTIyMtGv3yjUrVcNXbpFwSakQi5TsgJXBGor0uLrUokWGuEgD4QMCrGw+3PeIN7lxAvdKe3NQ2jYsDb++GMDTCbH1Cec/LmnKuTeOHXyBho0iKQq5oJgoIV4JpJCxNGk6y195o/fN6FTx6GQy3SIvpmKxYs24JWhM1CtSi9Uq9IHt2/dyfF5Np4hodcs/Jrtg8QkSG3NXxtIS5C2HC21/SrTkmoy0WKwWGCxCbTcykinJdIrkBbptcVmo0WrUkKTLMM3E9ege7eOGNL/efsxObkzcGBPnD59EQsWLIOPrwfmzPkAmzbtoN6QGzdux+TJs1ChYln8998JmoP1QbliSeg2Yc6cX6j69IYNP2LkyMG5hv6TlApDh056rMuyceMOWjglB+nRu6ALoUyZMtRAKJVZs2YhN6ZMmUK9FqtUqQKVSoU6depg/PjxGDyYtXFidCQQD8eckNfSe0WRQgu1NplMOHLkCKZOnWpfR2YiiOVWstR+9NFH9HVWVha6d+9OvSE5nKfN2Tub8fW33+NqhAznL1ymM29Bvsz7KCaBhWPYrjjdEHPaF51DqqXXzpC3TaI63h29o5xebuMWaZ34mWsRMiR+sh3bw2qjeYuaND8dJ/+Y88dm+FXzxaajt9lllEKn6QvxOqkV2SrWxHPSZgYRNQ89yPIt0sulkSE5QAXvODMq70rF9RpamHSK7HyQxGAtze6K4dcuJEdkjhBpP39mHLwRnYrLd+Ic3rOJn028yyZmMkQPTdL8iMGR8Hr1KKz8egdMLnKsW/kp/Hwq86byEIjxuUqkD76dNxQLv/gH/8mSYSnvihvl1PC9ngWXIC2auQfAZLBg+6aT6NCzNsLbNWHnPset9ezZSxg2bAasLnJY3ZXIEmw4t+8akHqfyQKzgNgKKtw4eAFXb+5FaKgfUrJSsHnjMWi8VAivEIBa4VWod+4/m/dh0us/4sKF7VQp9MqVW1i9aje27DyKP377EmFhgffNw8UpWfAxFacoQ9Rq27RtgBde7AqrkEKNQVJYLRlAKeX5JxImhdg+au7i/v27UUGKsWPfx4IFuT8Mch6fzAwzzp69jFo1ptL7lwWx9wygpZQkUhj1L7+sxe3bsdTQKEFS4nTs2AxXrt5Ah/ZjMHxEP7wx4fnsHI9yln4GMjFcWzBQRW66yumxVy7mlIwQw6qzrBaUcWfh/mFubJ1O6ZgrTaNQ0jDHK1tuYt3vR/Hhh2NRr17JFs3JL4gH7KJFn+OXX1ZhzJhpWLz4U3z73XsYOeI9xMUnoWmzehj+ylRcuXIT/fuPxr///prrvW7MmHdx9uwVNGoURbf97rtpDt61OSFtKrJKBFXV3rhpO7p0Zl6pBw8eR0pKKipWLIfw8FCaiighIQnNmvXFTz/NRpMm9eh1Hj+eCVOR955/PjuNE4fzOERHR8PDI3tcrtHknod45cqVWLp0KZYtW0ZzPB4/fpwaHokj3osvvlhsT36hGR4TEhJoPobcLLXnz5+n/3ft2hXx8fHUFdXfP3+VSzkcZ+KyDmHT+iP46H9rYHNVIMGqBGIsNGfj1STRSCCF3UoGQud0asRjTTQIUe/HnDiFVFJjlZQj0Fl4Rto2N5ulKFqSlGKEl0lAhiwZtzJuoLwHNzzmJ5mpBlw7cRuCn+g1QQRg7JdQ/MdDdY8x0veOCfHBKiT7yJn1TzQixkdoEHTVgIjTWYit7op0D7beRgzJ4u4U3uwGlJzGjhngxxKhVwwPpm3OJ9ALmWnM+O3pw5LuX7t0hy4vXWN5hxSiEVStUWFq48a4djYGCydtwvDhfdDrmWdKWf6qJ4Fdz+qVy+KVVzvi0jer4FuzDLZeTEFGFRf43zLizK04yH01+Orb0ahRLSJXjxyimorOgbiSpIc2wwqLXPx9Szk/pX5CvG7wVqNHmXL47a+beH3MXHz25cvo3XUG/Cv6wifYA0m3UmFKM0LnpkHMjSQMGdKbfox4kPyxcgv9Py0hk/tclDL4mIpTFLl+/RZmzvwOV6/exM+/zKC5+1Ryadwv3YskD7f8Je8ektkpNoiIChGd4eQ/ySmx1IiYmpoGLy93qOQsX3VOUSCrjeVRlMmYse/iRZZSqEyZYPz+xxx4e3nZxWYE6HHwwCm8/NKHWLFiI/YfWJxrMJ9VSMvRFkRxGpkKaWmZUOnYhK2Hmo294lL1qOTFVNfLu7P6WcRcpGoxTLeMxgsfTl6GkMBwLF8+B25ubJzGyRuuri549dXBWL9+C8wmGxVy+WPVdzh06CQ+/ngOmjWtjxdf7IdKlXJ/pjl06AQqVgzHbyu+wo0bt3E3Jh5yxb2h2ZIRmxikXV3VuHnzDt4Y/zHKrS2LWbPm4MCBYxg0qCeWLFmN6OgYaDRquj9Cgwa16fLWrWzPsQd5YHKKF4UpLuPh4eFgeLwfkyZNsns9EmrWrEk1T4iHJDE8BgUF0fWxsbEIDg62f468rl2btd+iSKGLyzwMYgnOq9ExMTEVJsmD7B6LTbb0+JPC2o7sgcdxhNelIM8LVTFOSYera8ojXaNkQxYO7b0KVXU/WAI18LydQR/mieHR/gml2L7URFTC0fBIt8lpUJDbqC1KJljpezSXmwwQpM5OJc9WX1QI9+5H3L+zbVOmlENlEuB/w4r0il4wG4CrF+KhK5Nw3xm/0tx2jUYTUlMzqHreo9Rl34rTdOntp4WNCAbRz0uKiiIKUU2RNAm9Fa6uMug9FUCoCt6SYIwoICQoFTBU1kGoIoPSRQ4vsR0IKtJI2KYk1Ih8ylVg11GXqQCOpeDayiPU8OjWLhTqAA3krkqoslg701lYHbzEgbpcnOXXGBSIvpCIVd/swSfTJyAkNAAJCY+WrqIktpeMDD0MhoeH4LFBq4DkrCz4B/pCGWuFItYKLwXznDBFaKE6nQXcseD8uduIiqqEhITke+qi07lCF6eAl1ILeAEaK5OjIb9/OhCR21g/Q8LwKS74b9sVjPuoDzo0rY3pH/wGV1dXqGRqGJMtdH8+7u7ITDOgWYeaGDFiML2uNiENlSPL0XQlhF07j6Fjp6aQy2zF7hoVZF2Sk0VhsFLCo4ypCKRtGY3ZXtSPcz2dt8mHy8vrUsDnhYyp4uOTH/kanTlzES4uWixf/h2RekNiQhoZxDhtScJr5Xmui9lspv24UqmkXkrEYPCw3G0POy9knzNmfIfKlcujXbtmOH78HPz8vJ2UQXnblc4dGVNljyfydl727DlO72Wb/z2A1m0a5hCSEduDjKSRYf2xXMbu0dL9bPlv31LRPemYNmoMzKIGqG075uLOnQQkJqbTepDUMzmvNdunKEQDAX+s3I5du07i6pXbaNshCt161odLEBtHZaWbkWo10vaSaGRiNVai+kYmo1NMsFkFTP/uD9RrFIkBvQdR8UImYFi6+7qUFKk95LUuAmrVqoLfftuAzl2YQGa5cmXRp3cnfPfdr9Q7ceHCT3Ptc8j3uH4jBvHxKXBzc0XFSq5ISEh1UDp3NDxa8MPClXj55f549tmu1FPy5MkLCA4OxKVLN+g4LDQ0mF7HGjWqYOrU15CczIyMSqWKtlnCL7+sxsCBzzzSeclZm7ydFzwxhV2X9PTsiC/O46PX6++5r5FnfCmnPFGxJsZHkgdSMjQSR72DBw/i1VdfLbKnvtAMj35+fvQEEstsTshryYr7qJBByIOMC0/ngebx4XXJ3/NiFcjgwgpBZqOD0Ye1BcebkwzLt/yHXdtP4U4zLwipBtiyzOwqE48k55kRwUnNWHq2t+Sou1oO93Qb/BOs93ynO5VcYNDJADauyVZAlpAMiFIIrk2AzB7WC/jeNSNDCWgSjJg043dosqyoVXsLvAPc0bJxJFrVa0YH45JaYGluu6STflh7yFkXiy0Gly/fAhFGLP9cdVw6f4NtZCFWY3YseTAbDHu6sX0mp5vhdz2LenGnldHCbLXmMCSJ9RPzRtFHeAON15FqaN8k0JMNnOSi4bmm3BPWKA9M/rQzLl68g4/f/w0ujfyhbRiAlEzWeHQ+rC6uyeIgWfTGrR0YhL/nHcI7U4ajfLnIvJ/Q+5yXktJeWFvIS//A3g9VNaDLae8kYN63GxFaWUs9Xa9fSoHi+bKwbLkLuZcN1/W3UNWbzTpm580U0Lhxbaxa9TcsUTo2+aAXJy9s1hwGR8FuoC4T5AJFjA3PdmiDE0mXcfzIVQSHemPOD6Nw7vQt6DOMMFusqFw1BBVDiWGReQuZbKmIqh1A22CnbnXRrVuL1Ij/AAEAAElEQVQHyORymGyXcOzwFcxZ8g9S7qbDr4wX+ndshw4dG4i5tMi5dRXVXBUOoYqlob0wBc3iz9MYUzmPq/Ln+ubnwxWvS0GdF9K28jqmyt6LCVOnfoavvnobShXpX1weo39xrEtaWgZ69Bh6z1a9e3fC66+/fF8D5MPOy9ate+Hioqa55cg+iBDOtWs30atXRxra27lza7i7k34ST0xJaLuOY6oH14XkGiZGne3b96Jjp3po1iISCqXB7gEkHd0i3ITBxqKLPFXhuH0njt7PWras73As+lcgr5mXokqlRsUKnqJWtWBXxJb2rLCpYRPzoCcmZmHXrhOYNm0c9VTs2WM0Nm86ih//Gkffr+rnD5ONjNJkMMhYCiS5uL9gD3csX7QL4WHlMfjZIZDLcg+RzPnNS0t7eZRnLqkuY8a8SPsHQbCi5zNEIMOK3n06UG+w7dtZyrXc9lmzZhWcOX0Rh/87g2bN69n3KY1n7A4d9olMORITk/Hssz3g5+eLP/+cT9vVihVzaPg08XIkzwne3p5UgCYn5Pj+/t64ezcB//67hN4PCXFxCfjjj43Yu/cwnaCIiqqGAQO6U0Po41My2ot0jjhPRo8ePTBjxgyULVuWhlofO3aM5vEeOpTd/0j/SUKvp0+fjkqVKlFD5HvvvUdDsXv1yk5NUdQotNahVqupcAyx1EoniPzwyWuiZv04eHq6wsOD5ebglEZY6Cm5oegzYuHpmbe2YLKxUI7VP+yEZ/cySIthOfQgKU0RMREJMWzWbmCUQq6JR5wUBm3vrWXI8ABiSMgtuQmQ/QgCAuNt8D3NwmKvRmpgIYYHm9Vx/67i/iSDJzFMqmxQGG3wSLVBnmigQ/eUUDUS5EaUSbTh+M4LSPFWYMOGI9Dpl0KmluPbuSNQr2FFeKrLidVkISSlCTLgJV6wJLQnL1gEL6SmXYYhPQv+tfyRefYSe0OfBVkIM/I1axpClynxbHbeeCEZithMXInUIlNmBDJEoaGcIbSS4VhqTzbxNbnE4iZeCmac9PBkXnXpZ5PRuE8tBJbzwK69JxHUoxxMtdj3iPDxpsuzN2PoUnARZ8EqBECwCYj94zyef74fWrXgKos5IUbdrCxjntuDTWCztx3btUdwQAReefMTRE1qgjOX9+HIyTtwl5mw/Pe92Hz2Et57XQazyYImEa3Fz2aiRasIqlrndcGCW3XcgaSs3FMvaNXQpViAVdGo06cTfL0rYuu/62EwGHDtZix6jPkSar0AS4oRWqsckz7ti6qVb8BNFcWuP6rCzxv46Zcp+GHhX/D0Yg9Fe87cwNQpP8LawAcnw4zQZMTg7rzl8GqkRIfwtnSbG+mnkJ6WhV2nLqFMZCC6hNeCSl5WrObDwshIf1d8w/eTk0tGmNzTGFMRvLzc4OGRt98Kp+RCIory2mcyBCxa9CuaNo1Cg0aR0OmIuIfrY4VA54TU4cSJjQ7rduzYj5Ej38by5eswffpEPPtstzzvz2y2YP/+o3j//dn2dcTA8NNPf2DXrgNITk7FnTux+PzzBfS9sWNfwrBhA6hic2mGCHbkdYzNDI9q7NxxFBs2foXAIBYurZB5isPba3S5/fYNlPNg72mMyejb+01ERVXBN9++BzkVi8m5TxJRxMboTEiGebax15LhkY3FLTYDDFY25r5+9BJq1ymLKlWDkZSUikqRgfh+yVgci2dq5mkmoz3UWq1h+0kxMgPkuV13kXArHdPn3T+fYGnlUdpDzt/yggUz8eKLE9CoUW1EVilD19eoUQ7Hjp3EK69Mwuo182iIs4+3j0NorNlswoQJH+PQf2vpcz8xNmfnB5WQ0YmKfn3HQKvVUmVrUsfduw/Syc2vv16EEyfOokyZUNqHEENos2aSITObv/76EQMGjKbGVakPHDlyCgICfPHrr1/SZ4xvvvmRTlqQiQoJ8ix64sQ5GjLuLuYNLQ0UB+HwnGIvBXnMR+Hbb7+lhsTRo0cjLi6OGhRHjhyJ999/377N5MmTkZmZiREjRlAB5ubNm2PTpk1OnvpFi0JtHhMmTMDChQvx888/49y5c9Q1lJxAonLN4RQ0gtEKj7qBkOWmRJ1fyGSILavBpZpaanAsf8F43+O5J5hR+WA6wk9lwiXDigpHMlDhhB7+V4m7HHvU97xtQqVoG1xEEca4YCVuRagR/GpNKoYy5pX5uHFNNKRy8kybNvXgUd4L6dEPz+livZgG73OZiK/rjkzv/J3LObv7GrwC3XH4wGV8N3sDPCozY+ODMN/IQMr351G5aqjDIIjz5NSsWRFuZT0Rf5gZewnp/mpUe64mYg7dxgttZ2NY56+QmJgd0q5SK/HNipFQSKH3DyDwmgE9J7XGh9PG0tepd9PRsH8UNAPDIaSZkXUlFZqy7pi99BVUqhGaex1rVcDX3zLvDYJarcQzgxrDdDoZrkkWWo+k2HSkJGTaUxH8ufIghvb+GrtWncAXI5Zj9meraDhSfngecgoOPqbiFCVIuGLffh1gMj6auvSj0rp1EyqwNW3aG3j33dnYs+e/XLeLjY1HVFRnREa2wZ9/bsann85HjRodMHz4W1CrxbBfmQw1a3bEJ5/Mpa+feaYD5s2bgd27/6CGh2+//QmLFq14qt+nJEK8Rt/74BWsWrXtodtm6U1o3fJ1VKoURvP45Wcuth3bTiIg0IuGirdoNgxNmld96P5Jfaa/8RuWL92GT2eP5EbHfITkVX3rrVfxxRc/2NdFVimP6TPeoBNnzw0aj6ZN+mH58j8dPrd372p07NgCFy8yo/X9+OGHFahfvxZ+/30OgoL8kZVlQPnyZXH69GZUrBiBy5dv4PbtGCxd+jU1POYG8Xpcvfp7h9yv3bq1pZN9X3+9GLdv30VSUgquXBGjo4iR+txlNG3ah+b4HjRoLF5//QNs3rybCuNwOHnB3d0dX31F8pjeoCLLV65cod6NpN1JkL6LCDETFWvipLBlyxZUrly0xUML1R92wIABVDyGWG/JSSMx6sRS6yw4w+E8Ko8yTpG8AH0DPXH1g/0I81Ygvp4nDImGbM8ku9q0uGO1uJTWS1DnRjlc9DaUveaoWnu5ugvLFWi20nnYqzW1qHxUjwoXjLhcU0uPo4YMEceIQSD7sxqyr0skkTZwOUqHiif0MGhlcMkSEF1OifBrFlyPUFH1ZCpSYxGwc9sFKCqoUOGKGQOH/A8auQIBNQIxuHcj6vGlkikQ4u2LOvXKw0Ndk321op/ytUBQyvypVfetST3w0zdbUKdVIGQuCtyJTsbd28xYkxzHDJJqrQqmrbFIC1IjhRgdJbEgeY62Ia0TRYHsXq2Sxxt5KeYFVYrbWMxs5tY9whPfvLICFj2zLO87f421IeKAWY61z9OnmBGsUgUf2FJNUG68i+YNK2HKmxOe8pkqvjzKg4xcxmaq5WDLhdNexriR30MRroRVTJHw464TqHwnO1dg337j8MXPw1ArjHkat6nVAO7ev6JVlTCc1UfD5KtCeoIRNnK5xbzEOh81LJ5KVNZ50aT5mZlZ2LX6OPyej0TcnmSoZTa4ahTwbxSC5hVa0c/QXJHSdxLzG9kEMy5fuo0zl/5BcIgPIiuF4Y1x4TREe+3yA+LngA8G/4Tae8Pw5UfrsO3iFQiN3fFHbAxkXgIyky/i0KdfICU+A9261EX7LrVRqwJT7ZTUZ0kYpZS4X+pDiXooqwP7nTineuA8XfiYivO0eHTbjwwREaH45uulVCDk1JnfIX+CIQbxHqpWjYRjZjNnzsdo3765/fXAgT2pOMywYZPx11+LUalSOWq8qFq13T37mzRpJl3Onz8Tp06dx5w5v9DXr7wyEAsXLkfjxnXw88//s29PvJuIsaJKlbbU+EiMCMTrcdCgZ+Dj4wmbjYQm2lCvXs1S5d2UF6Sx5bP9nsGA/uOxr9l+1GtQEWlmZqjxc2GpIIJ0bsgwm7B5/TH6es2fn0KAUczbKHfYF/Nwk8KujbmEYRMkDzgrVGLjq1ApEPO+/QtffLaKvq4TVQWuSk/U9GVRLNfTE1HeQxRtyEqm7eeP7/fg2IGr2Ld/BbxE9WuO0zV+AtswMQyS39yhQ2fQsGGUXZ08NDQA27cfpP9Pm/YVAgN90K5dC/ra29sD9erVwP59h2Ew6OHv74MKFcpSw2LO31/VKuVw9sxluwfYF18spCHR8fGJNMy6WrVKiIwsj7p1azywjsSwePToaRpKXaFCOF54oS81NHbt+pLdKLpjxwHab5B8scQDctSowTSvJJnAPXnyHBXTIccnfUSPHu3RoEEtbsQuJGSFEKdTfOOC8pdCtzSQEKAnCQPicJ4UKd/Qm5/2xncT1+C4NY3dRCVPRGLokTx/xPBZpVyO8hfFnDF+CiT6s59SYIwF2gwb1GYByd4K+h4ZLpW/ZELFMwZcr6mDyUPN9qdWID3CBe7XDah8Qgy/JF5OoRokecqogcnvjgmeiVZcjFSzO7vRirhABdGjwM1gGbRZrD4mN4Wj4rZMDiuxQ8qADFgR5yVAd/kWTn0dywRsZDL4uqhhSzfj6xkvoHpUWYS6NrGfEQ7Qt/XL0GSUxTcLF+LVmT3x0c49UImGQZWGGXmsZivkldxh9ZLD3VUFpWhMTCKh+EQFO+fpdGOfUbiytiI1KRu5bqKRUm0SgEwrbouGZ9dAwBbmBp8LeqBrINQWGzJEI2T0tQS69BD3261+Tez7ah8+mDkWLVrWgVI0mHHyl8phbdCh3WXIb/6HnZpk+rs0mW240cYb4WFuwMrbKBceiprBNZFlZQqdnqoIjB3SAWdOR8PT5gkhVkBCrBkZyXr4NQuDX70gpKZn4frG4+jWgeRe1CA9LQ06nQYVdV5IvGiAOdWIa008YFp8EoYx0TQPmVZRE2YbUzW/lXmZLjvX/8Chvv4BHlj979tQiCJEumA36GMyYHZToGfPzwB3JS4HyoE0A2Cw0Ee3Y2dicIw87NkEXNl3EPNX7ECItwcimobjrec7wtvHDSG6OtmGehGSK5IghVRKxsnspO+8b3na8DEVp6jQt19XQKbA/HnLoFS42HOw3Q/iiShBPBgJW7bswaefzqOKtISdO1dSL6nZs7/Ha6+9h4kTR1BjIYE84L/00rM0TLp7d8c8kAcOrKV5G8PDQ1G7dhccObLBrkZMjAWrV2/C9u2/0dfECDJ9+qR76kfGTUQF9+DB4/jss7epl+TqNRthPGOk+XStFis++2wBBg9+Bv3793jknJglHY3aDXPnzsDIkZMx6a0XEFaLnZ8Y/S26tAo26JQqVK0WivoNKlHBNKvAQqQlJXRpIpAYeaUJLivYRLDUvqQQbiJaRNrEX+v3oXuPpnRNu3Z1UK1aOD7/bBXe+rAvKlUKQZopCe5qlt6momcAMi1sPJ5mMmDflrMQDFqcOrMKamXpS1VUULzxxiuYOvUTLFr0Kbx92Pjhf19OhkymxNixHyMhPgWenuS6Zqeyaty4Lr777mckJaVh3/6jcNVpafh8ragqaNOmMS1vvDHTwZOReCK2atUIH330FY4dO4tZs97C0qVraE7Jtm1ZG3Hmr7+24s03pzus27jxZ2rkJHTv3o5uQ4yR7703m3qk/fzzFwgM9Lf3GyQHJCkWixX79x/B6tUbqTG1devG1AhZtWrFAldZ5nAKA5lQAmKpiIoP6ZBSU8/zXEQcOjMeHR2LiAg2g/kwbIKBeheNemsqTAYz/nZJgaCSI+tSarZnmpSvTzQsKRRyBN4xQ6+TISDWMa+IwYXkdlQgyTc7h5/KaEP4NTM1GDqTGaaBvoIrDbnOtNioQcCWxG5o7kkWCHIggzy3SzclKUGC0UYNVRHRFlys4eJoeJQMZEYBZuKdKRq25BXYbK1CLkPNGoGwxhlQ8bQVTVtXxYRXJ4s7Llk3P5J/heSnIrOnj8Pnyz/HP8sOI6GVJ5IyWK4f3wB2Hm1ERIbMkt9kobV2w2Nc1mMZHiuf0jPDYzc2YFGJ3o2B/uwByWCw2A2PkhFU6sB7Va2CM6vOYPuq7+4xCHGySUvLpG0iIODxHyJIXrAuI4fh/M04pNRwg0mcpChfxh3CH7dxav8PdBCZYYmn6z1VlaG3XKH/bzh5Akd3XkJk+4qIPnsXWzefRvzBO9CEuCJ0YBWseH4wdMqK9IGp2+vjkX47DRmJeqjcVLghGOEeY8TmP99HSKhProbH9b8cglanho+PO6w2G96b8ivm/DgKLRs3RNc3ZiB6E6sHbTvNfIFKrrh0XlSOTBY9R8j3ERuWf21fuhzWsj6u7b+J9GPxqFU3Ah++PYU+WN8vB6TJZMbOXXupJ0LtqJpFtm+5fv02ypVriNTUVJrUnsPg4ypOTq5ciUaFCiwHW15ZvWYDFi/+A9Onj0WtWpVziG7l3g/MnDmHqtl+/PE3Dut1OhfUqlUVCxbMoiG7BOKJNmbM+1QUxhmyzTfffIgyZUKosZEYFqWHeqK4+skn8zBjxr2GxZwG0EOH/oSn5705LWNi4uh6YvwkOOeVy0jXY+7cX3H69EUaoi0ZN0saV67cQoUKYY/12Tt3L+DVUZ9g0IimaNi8MhRiUrj4rAxqeCRU8GD7lrwaczc8pj3U8Hjq1CUMeHYS9h+aD3d3HfXQJ6SaWO5mhehJ6apiHnFZFhOsArumt9KS8NbQH7FowQyEhPjn2C8nP/oHZzb9sx3z5i7FN9++Q/sBlrNTgdmzF6FunSjRuznb8MjaB7tWPyxcgfYdmlJRzZ07DuLDD7+hHpAjRw5Cz56d7L//bdv2UeMgEZEhv2Pyew4M9EPdujUxeHDughzHjp2hHs7E05F85sMPv0TZsqFYtuwb6vXYv/9ryMjIpMcg3pPLl39r7x8eBDFcbt++D+vXb6W5ZD///B2UKcMECu8H8Zy8fTuWhpkX1TyjaWnp8PSsUiTHVNK4JmBiM8g1BTsxZDNaEDd7b5E8LwUJNzxyShxkRik6+i7Klcs9B5ozJtsV7NpxEpPnLkXg4EhsWn6cvZEpGo6I8UfyfpTCZe0fFgedMqDyFQuyXGSIDlM6KV6L/7go4JVkRUCshYZZK7JsMLrJmUFREiCRjIfS8aR9EMOndGwnIyhCxcF8dEZ2aK80rneeQZNEcMhnxc/X71oR+j+j0atlTXTsXRc1wsrSXEYe6lriVyuaN7e8QoRESM69sLDHS+FAQn1IuMeU/30NU2dmvHT3Yg8Td28yr8OkFGawUYvX0WC0IiXN5Hj9jey66Xw1duM1XRKhY1FwpspZEwzR6bjUxoteH0EUMQoJYsdzc1UjNZ0dyySG+Qb4sQFO7fMKdB/cCEPaDX+s71laIMnGDQbTExkeCQbrJbQfPwNZN9NwMVwOQSlH2SA3WNfexoV9/+R5P3funsG+fafRpVttashTycOoxyPhx/0/YN3cPUiMScPwT3tg5ku/Qq5RoOuz9dFpcAN0COv9CDUWcDP6LDIys+AamIUvpq/B3kMXERQVjFueJshDdTi+Idsoae+DXBQO4khBlTygOZuBhq7+eO/zAagR3A6CwNq6ADM1mJpMyYiPT0HH9hPg6euKP7e+yz6rbYyixvXrt1CuXKNSPxh0hhseOTm5fDkaFSvm3bBADEMtWvTD+g3fwdODGWyyDY95+byAiROn46+/tjl4JzpDhCcaNXoGH3/8JjUwEmXaggx1JsIpjrBx1Zo1/2Llig2YOWsSgoL8aFh2cR9LPUl7cIaoDD//wmh8/t0wmNzZ+CfdbEJFTz/6v4eKXW+zaAR0UTCDpEqWPY4j3nAEo/U2XVrEbeXiNVArPHDu7A307zsN3859C23bNrAbK1NNbFLQYGXjfFdltkJ1mpl5PB7aehHHjlzFrI9mPPb3LC08aXuQIOHM7777OWZ9Mgm1alWiv6fXX/8YY8cMReXKLHVNXli79h80bFgbISH3jvv7DxiN6tUqoUnTuli29E86BvD19cYff8x7ZK9D4uhCPKBJ+DRRuH7rrVn0uB06NKe5Z3PmhbyXbL8vIkzz4Ydf4aOP3qT7ym0il3hYDxw4hhpC161biCpVKqIoUhwMj4GTmheK4TH28z1F8rwUJDwOgFPqkUGHuvVqAUk/ItjdnbiKORr2iCHP2eBoVybOvnFcDFc45oOUsLu2CUjxkiPFS00NlhbiiUgNSwIZ/bBtRGOSvQ7Sw39Or0tp91LuQCkXpWS8JJ+R6iAdW7qXCk77BXB4+zXATUDG7uNYvv4/aAU5XGv6Yd88lt+otHvOESNQ2zYtETrvB5yJSQfclEhPZiE+6aL3YZbYHszieVUrZXB1lcJLGTZXwcHgqJGuF1knXkttdW9qeHTLEmDyVMBI1LGJcYp4UNJQJaM9tFpSjiMDJcFgRVaSBb1bNXqap6LEkB+O/i6KStj+9XSsXbMLX/2wCjV6RuL02ZswBLkjzcwmL1yVkpr8/T0lQoKqo1+f6rm+V8HFGzqZCgaVGk2Dy2H0uC6oU788qldlitOPhgxly7DjJBmP4MOZg6G0eGH/vtPYsmU/Tqy7hmoqF7h0K4Ojf1/O7mekPklc3r2QSpwQ4GlKxdD/Lcdv72rg7eKOC2dv4cTl69iy9jjOnbqFiDps4qd9v7oIcKlN/zdYz9i9SVyVbGKDw+EUBx6tzyTKwrVqVcHdmFR4ekiTPI7eSg/+vAxffPEeLQ+CPNhLYdlF43yw9b16taJK3jNmfEMnPlUqFRYvms3zP4oQQ8/AQR2w898L6PMCUxL2t1mhkYuRIeIAx2q1ORgI5Yqkey6BZHC02JgRWCHLNvB6+zCv1UMHzqBd2yaQgxm/PVRsW3cVm8jNsoqTZ0J2WNLWv89h/BuDH7+JlCryJ3iS5Fok4fhEjKVnz3YoV74Mjh4581BPQGd69ep03/eMBnKtZYiLTcTIkc8hNjbxsYUYiddh06as/ZJQbeIpffbsJZoi4uWXJ1IPTCKeU6dObmO87H6wQYPamDr1NZrmgeSdJBMVJAfl8eNnoddn0Zy048YNpUZH4qFZVI2OHM7D4IZHDoc4N2ZmwZicBavRefa6lCCTwRDFZmAq1Y3A7a+PIzPTAFdXFn7CAVq0r4azX/wD4YXHMfrkDcEqQOGugirDApPnI3TPt7PQoNGDk2Nzng69erfElrtnseOrPfS10kuDN0YvRLkKgYisWAPtOzSCN81NlG3wzOusun+AJ8LK+iI0zBdqjRL9nmuWr3XXajVo264eWrWtSD3F69UaB8t5McXEQ9A1DEDmnrsYNWAuOnapQ7/bj99vgYeXDoLVhssHbqBm43Ko14p4LXA4nNJGlsGIixeuIzIy755KJYmOHZuhQ8eG1NPxm29+xebNe9CnT+fCrlaRoWPn+mjVbBzKVfVGnQbln8oxSFoUEt1w6dLNR/4c8eKrVPnpjfc4uRMREYZFiz5H8+Z97euIYFTFiuE03JnkdiQhzRIk7QLJeZ1XiFL9lSs36b6aNGFGw/yCjO1IGDcpxFD45ZeLMHbs+9izh4kZPYg6dWpg9+5D6NNnJM352KVLa0yb9jU1hhOHhQULlsLDww3vvfd6vta5NEKG4AWdUpOn8GRwwyOn1KOU+yAkyAv9Xm6OPd+dQEA5F1g9lEi8wPL2UYUWqYOSvA6dvRpz613EmVq756S0PudnJW8i5/BpyZtR2lTIESYtfV5aSuHZ9uPkmEhzPrbdAzJHjyt668VdYQaHnekX4a0RsP/AHrRsXQNKZen2eJQY0LMbvv96M9o3rYkDF6/RdZnRYm48kXTRM1HhoYJa9JLVatjsu6uWdbdEVZygN7Drlp5pgVFUsTaX0cCabobPHcCjmieuJ4jerGIot1Elh5s/C602i21G7aKCUNYNO3eeRvu+tdG4MvckKyhIWDRh7ujJMA83o0nTwchKMyG+hgtizUnYuedvfLLgF7zyYisY1QI2LfsPZr0ZVWuVwfAXn0W16tkP5Cr5vTP6VUPb47Ppjkqu+eFdsPM2ywf5TLnI7O+hAKZ8NQCfjF8BWS0tBLuno9WxL8li7fbAkZuAFrC4yvHLD9uwaNk4dOxcF+vXHkJEeABqRUWgVjUmFiGFjtsEG44nsAfARgFMOZQrX3M4JZPx44bhgw++RKY+AwMHds0hNpUd1lo8cO5vZRCQS8LuB9CyZX38umQjNzzmwN83ApUqhSPDmIU0kx7pJhNCXNm4SW1j4yWdkoVeS7kZpdB2i81qD8M2it6KKjH0WqNU29tZSHAIHXMd2H8Sx4+dR+06Vel7SnFbkuOdoDdfp0u5TEbzPJLcklWqlsWKlX9h8MBscRJOwUByQ589uwWLFv2GL774AX36dkBYWBCuXrmFyZNnUEGW0NAgGpr9zz+7aBh2586t0Y8IWj3Es3ro0AEFdhlfe+0FzJ//K3buPEhFbR6Eq6uWej22adMUb7/9GYKDA/DPP0uwdOla+p2IMZMogBMvSg6nuMINj5xSDxmckOjX98aOxqnWl/HShFkoN6Ya1t0Rcz1ajNn3Menh+34QY6Bk3JPCsyWDobNxkYRZO4dPy51CoXOGTItJsO8N5RaXzvty2MZpZU7jpHSsrOxwYb2HAidPXkOTllVKffuQCA4sj2ZdqyPougkqNes6reK5U0jXWDTSWA1y6PxYyJBJzNN4K44J0/h5sYcui7ieeIoJeva5O5mZUDb2guuBFISkKIGq3nT99ats0I00E1LSHcO73T0sgEaGMg1DsfSvA2g8oSe/ZgWMQuYBhRp4/4NBOLj/Ag79cwldXmiEnd5x0AlW/LLrCJJTMiCroIPN1w237sZg++jp8Hm+Mt5v14KKwTQObEj3JZOpoZCx6y7hrA79KA/wkvgMCfeWcqz1KNfWIVG/RGwqa2ehlw24VVXMqSa1bYUM7skWlHd3gzrIFYaqzABu2nAbY9/ohogK/gjQNULtKff36NEpa6JpUDWx7gqH5PAWW4yDMZfD4RRviIrrihVzMGTIWFSvXgk1arKJFrlo9CmuOQ8dBWXseWzEJRuHyaRwX0Euhp1Xx9mzjqI5pR25TINpH43D13Pmo2nTqkg2GiAXx7lmGzvHWiWLupGBTb6mGlmotVaphk7JonSsNjYBLHm9ycAMM3KZFmoVsOKP6WjfZizeGP8ZNm//nHqlKWRe4jbsnuim0trFZqSw7tHjOmLau8u54bGQIGHMrVo1gVKpwvSP5+Ltd15F3XrV4OvniV07/0NmZgaCQ3ywddsi3LwRg5kzF0LjIkeLFo3h6qqDSjRAFybxCSyX6IgRU3Du/L+QyxxTMN28eRs//7yKhlAvXfo1DbEmQjPE63PkyMHUGDlixKBCqn3JJYfMQcFR9LQVC4W8+yZzOKWAmjUrwr2qD+I330BpRmEW4O1TcAnaiwvtBtTDtpXHIDzI4/UJsYS5QOGmQtrx+HsNxg9g74rj0LoXN0+SkkWnLnUx5d1+6PR8Q1w6cQuxf1+DJc0E/ZVUCHFGCAlGGhYPFzlcmwQiZdVVvP/yzzh1kHnQElKS0/H77xvw/ffLqRAO4cD+41TJkEBChH788d6wHRIqnZQkemk/BiQv0Y8fbIRcIYfCAgTcMEImtnPPJAv87pgRHG1G1tlkpG67BdPKm7CcSIG8kS+2bDqOpT/ufOxjczickgnxzvl4+jh88P63MBpFwbVSSEaGPleV7NJO3brVYLHYcO509FM7hq+vJ154qStiY5Nw4Xzej7Nj2ylcv8buu5zCgYRUDx3aH0t+/QJJSan47tsl2L3rP5o3dfPmvYiPS8KmjXuQnJKGceNewNo1WzD05bfw9tTPHcLmSa7Ejz76GpcuXbMb/A4fPknDtMnYaebMOTCZHPsn4hRAjkmEXR4HIjzTo/twGh5NhAMnT/oUZ85cpO8RQZtx4z5Ehw5D8Ouva+j63r1HYMqUT9CwYRTKlyeK3FOp8jWHU5LgHo8cjvRjEEVUvn53ACa/uBg+VVwgqOVIzjBni8mIYbP217khiofYcbYdyXN4xzkbsKTXzjMjudmfcoZW088ih3ekFFrttK1G8prMMe3gFDGkU8vhGWtCw/pR0CodPa9KMzKZChEhvhAsNshMAuQ6hd3T0UMUkjEFiF5gJpaThaDPYDP1gthmElMdBzc24sHoyrpiZmeUwVJOC+upNKiNgMxTiYAQNitv9tciVVRbV4nHTklhA5PaTcMB0ZuS87Br+XSmHolHn04JTBpYDRhInJqZ2iaJY7558wb27T2HyzduI+5uKs7fiIXCIofZaMKVi7HQW2OQkZ6F9i3fg1UMvf9uzo/o8Vwj/LGY5Y+U6NS5ESy2lrhwPg7TP5mDmFvJiItJobP/G/9e5hCKk1sId26CUTExcWjUJBINGlWCq68GX2/eC//YLJxBFlRGAT5JVuK8g537Z9Hcr9diY/D5+2twMjUTnq9Uwy+zdiOqVnlERUXA272Kk4pt9vl29nKSXitkT6YyzuFwniaP32dGRlZG06b1sWHDDvTu0xqCwO6JMlnuStVF9bvn9HSUiQOo7HW2B9xr5Pjj939omCQnJ2zcU71aWURfSkCt8p40HQch08LGNWo589hXypUOQjJEQEYmft5N5WYfoxFUsiCH/StkanTo0AzLfv0HW7YcQKUqPrAJTCDQIIZpaxWiirbNCFfRy7JSpTB068EiETh5+408LWrWqEaLszF/956DuHrlJg4ePI3bd+IQH5dIDY3nz1+xPwBNmTILf/21jf5PwpZfGzMEP/+0BhkZrA1ITJkyiq773/8W4uDBY7h1K5YaJufOnY4WLR69HZCJY5KrkYjPaDQqVKoUgcmTZ2L+/JlUXXnTJjZZSzwdSd9A6r1q1d+YMuVTzJ8/A3Pm/IIffviNCuU8qrgOh1NU4YZHDseJuoFtMahfImL3r4eqng+SYzJzhDE7q0Q7fViWY5v7hWeLuf3o+w8zMEphjjmVqp3fcya3/XqwAZlaMowR41cSG/w7b9vA7AZ5U0/UrF4/9/2XYqJvJ0LjqkaazEpD06VQawl3YnUixsUcM6dWKVdeKjMY2sSlPQeoRYDWhxkMU9LZ5+J85VA08YAyNQtIN9BLr06zwE+nQqpoMDaJbTImgeWVrFnGE0cPXYW1X5o9/JdTOMhl7MFFLatgX1cxIgIVI1rds21KShoNEXNTyuHqJWDo0E6wWbWoVSsSJ8/9hwN7LqBxh6qo0TACZVzKon37hvDycsP3C9Zg5frNaNm4GlLiM/HGhJfw/PM9c8n/k7cHgnbtmtEi8eKzL+DL/y3B5i274BKsRqa7AR/MeA5BXnXp+7XCamDu103Rb+AIHNt/EUJjH0x+/xd4hHpgzqyX4evnDj8XJngkz5OBgbVnsz3kmg+0OZySADEQDRnSB2PHvoPevdvBhgx7Wgnp/eKLPaH2fbc4dfIS/v57J5Yt46HWjmeOnbMTR29iQP/OkGv0UMrFiSlxeCQZID3Vbg4CbYocKUmkpZR6RDJACgIbG9lgRM2a4di1ZwEMxkTIoaZtj3iy/fnHIfQf2JqMqOi25PieGjYJVq+eFnO/2WA3LhfX1AAlFTc3Hbp0Znmkc0IMeEQRWvptvvLKICog2qZNE7i4aPDPPztRoUIZ9Hu2M8wmgSppV61ageaLfO/92ahXrzp8fX1QsWIEJk4c9dhGP29vT2pUdKyzG4YPnwIfHy9aXnqpH+rVq0nfI16RAwf2xI0bt6koDclF+e67n+Pvv7fj3XfHolkz/kyWX5AJoaflgPCgY3K44ZHDyZW+/Tpj9qIlUNYpXV44ukwb0q+nosZYfoPLDb9gT7jo1LDGGaAIeLqK31aNHMocRmvXu0ZorqdC2dwTFpd7B8AelX1wadEJxMYmIjDQ96nWjZN/eHkxA7FN0NOBydhxvaCSh9J1qVk3sO3fkziz+SaCwrzxxlvt6PrrV29j/rxV8AnzgMloxtxFoxERnP+/2TcmPI+XXmMz/QrpgTAH7u6uGPfRM5g45mcoyrkjrFYQLm26hDFD5+ONKc+ga1uutM7hcICQkECEhPjjyJFzqFev9CjdE6+sd96ZjS+/fJcaPTj38uyANvh95XYMePXB4htPik7nAo1W8sIH4uJSMOPjJbBYLBj8fMt7tnd310HjosKunYfQshX3fCwuEAMeEWaRIF6HxMuQcO1aNDZs2IoTJ84jNTUdmzYtEQ1CAmbMmAMXjQbnzl3FW5NHoV79Gvk+KUKMjJs2/fLAbSZOHIERI6bis8/mUUGZrVv3YujQSXT9sGEDHknBm8MpahTnaUYO56lAZk29vTSoUS8C5XTBOOcdD5OkHC15rzmLwEgIuXg65gytlrbJuT07qPjaSVQmZzi1XeHaSbzGuQ6OX4YhKiqTEGAK8XiUjqFi++nWvw5uzDuJFT+NoyGb2WGSHIYC5Ty9MeSllvh4wQboepdDWmacw2k2GsRrbLQiQ888G2VKMUxL8pqVroF43qGUISuezcyrfERjprgfoyj4Q8hUy0DSoetijEgJ0divu8adze5fSkmAta4nnn12PH5cPQ6V/ZmACKd4IHkFahSV7B4WvXq2RrcuzbFxwyE0bVbdHiKtdknEq6OfRYMWIahfvdtD9szaSUZmIn3wYsd6eP5WyWPWXeWOHxf9S2fve/dtbk/cL9G1Xj/4/uyKa5djcfrqHXhZ5Ti56wqUMnkePR2l7+/q4AXF4XBKFkOe74OlS/5E3Xpl6WtBVBSW5aE/Kq58/NG3GDKkFypWZMI6nJywsVG3bm3Qt9ck9H6pnv0eJXk2quSiuIyMRevoVGLqGlju8XDMxuKwfxJWLRmQpPsMWZYJ9aDH+2fjUbzwQi9xv0a7gjbxtpz26SC8O/EHpGXeRo+u/fjlK+aUK1cG33//CQ4fPgGrzebghdalSytUqFgWLVs2gEL+8HEI8awk7VRNFIwekZMnz2HZsnWYNeutezzhiKjOd999hBMnziEmJpYqYy9cuByxsQncay6foPqqBeyAyP0dGdzwyOHch/fG9KaKdhWbeOGsZFASDUSwOeVQzC30WqtwNDCZpdDa3HMB5Rm7eGIOxev79W6S4TJTHIiJisjU+CWGavtW8aL78NycgElvdkf5MvfO/HJYmI2HSodG9SNhmb4KZpMFbqJB1yZeC6OUv9FkhV40GsrF8yyIYe72NmQU24FablcUt98IJSO11O481DC4yaHUqeCjF6ANdrVvG1EpkO3fJsBWXgn3S1aki2FDeSe3+PySi/RQU1SRQro08orQaIBn+ziqy5cNrYJXRz1Ycd4qMPXPqfuX0pyRf41YR18/8257DGpUB2Fl/eCjqcg2FkjomcxhsoE82BEWnt2Pn375Fy4uKtiqKzCoWgWnuqrRuPIzaFz5yb+1tD8Oh1PUePI+s0GDOvhi9mJcvBCDyMhwWAWmRiyTueTZs4j0S4LA7m8ymabQQmCF7KTaTu9k30fXrd0Mg8GE/v27F2jdihsqlQXhEQFIikuHryjAIxfDsNUKFkYtF42MWoXGfv7NNiYCKUUIkHbkiML+Wem97LYip+nYa0VF4sL5a7iVcAGeXq4wWk24nMKUiLVKFaADtFolKlRiKtic+1G0x1SOyFC/fu171pGQ7LwgiOPr4cOnYv9+YrTui/79u6FcubJQKhX2MeaDQmt/+209FbzZufMAWrducs/7RN26ceM69tevv/5yHr8bh1O04f66HM59KF8hCPUbVoTtGBscl1gEAS5X9AgI9kSztlULuzZFnovnbkPuW/AhU+osG32mseUSZi0h0ylhNDya0ZEoKPfoMSwfasgpiiScj8eBr/ahXY8o+vrgyuMYP/IHDOn9BTq0exXVqvRFp47DkZCQez8Xfy0JOi8tqjcth6NbmCIjh8PhPCrkQfz9D8bhvXcWPLZSbHGAGB1InrYffliBjz9+k3spPQSiKnztagxCyxRsihjisRYXm0j/17nef0wXHOqDxMT0PO83NjYekZFtkJ7OcplyShZJSSmYNPFTBAf701Q5S5euwYQJH6Nr1xcxatTb9NpXqdIWGzfuyPXzpO87d+4SJk0aQT0ZOZzSBPd45HDug04ZjjfGjcRfvUZRsWCzpwqZkpp1vMHRm1GCeL65Owq5BHizAc2tWNHT7U6mozdbzslC57Bp6XXOiTPnSTT7rFoO90vnbSRBG0uO/XmooDTa4Ls2Dt4R3pjx3nt0lq00eb49CsTT4vTVm/hk+irIG3jCqDfCVfR4tIjXKSV7YzthYju4eSXN0dMx52UjXo9kQHJDHKjaPR+zvSLlxHtVAFwDdPAJ87I/zFQKYuG3t9LSqNdjSkoWsvSicNBDMNou4/vvf4HRZsJff/+NLl2ac1GaEgIJQ7t27Tb2frob7qEe2Jp5BzfLq3FRlQ5leRdAZoQ2wQy/eBmSMtOw4PhqvNfhdfvnbWK42e9fbaPtMbGGGw7MPYpZY1Jp2+PiRRwO59H6JAVqVK+Cdu2bYs53a/H6hM50vdWWBIXc1+Hm6ewBKXlHmm13kWlmYyh3tR9dquQh+eQtfT/vReGRvLtatxpEPZ8++2wqPD25yNv9z7aVqgZPnfod2nepBZtCgMHKDNIKGRsTudsvhdzh1N/VJyPUNcLJ09HmENEgeaYp5N4QRLVsmUyMUiGq1jIrjEYTPDxcEWdMBYxAmtmE04nMGFne05MuXXUaXLkcgxaNH3jZxWNasGbtJvj7e+Ptd2bh668+EnPy8XF1SaFpkwF0OXv2O+jZsyPNw+jiokZSUiquXr1J09KsXr0JRmPu43BidDx79jLatmuMP/74GydOnEVUlKNiN+fpwsVlCg/u8cjh3AeFzAtajT9endwFXuf10KjkULiraIGfCysBYiGq0aQQ4xAJqTbbqMIxKVqtihZ/Hw0tIIYoUh7guXYPgmjUJIUYnEhRiIUYP0lRiuV+atcOv3wZ3INd4alTo3JkGfy5bDp0Wk97zhzOvZityXhnwjJEPR8FZYgOcqWcGhxJiU0y0GK/RqQdkJB6iw16g5UWqmJNinTdpHyglhzrSHg+KWqxeKtpkasVMARoYBVssN7MpDdNi9lKy92MDFp8tFpaSFvzdn94bj2r1YopXy5GmkGPjC7+mD9vGawCCzHiFB8stliYrXdxNX4n9h5fA6stgz5UXUjYj/emfYbMSq64Wl+LizdTYCAPX3orLHf1sMToEd4mBCqTgNGjOmN865b3PBTSB0OtHEKUJ05di4bBakFi8jXeTjgczmMzYsTz2LH9MOJj9ZDDhaaFsNjiaDHb7tBiERJpIcYjUohRkRSTzYgMSxYr5kRaSB9ICsnPR8rjYu/zhCxapP1JdXBM4n1/pWaioPvFF++hfn3mZc7JHZuQgfkLfobVBWg5KAqppixo5CpafDTutJDzSYogkBB7i70daJVkqaJFes9+DWRyWqTrR44jgFzPLGrkJoXcI+UKA+rVr4q7dxMRdzsFCrkcGrkC/jotLeR+R4vRBP9AZoR8GFu37sSpU+fw2tjesFgMOHP2gj1nM6d4QQzYJBcjMU7T17Biya+rUK5cGM6e+wvde7RB4yZR1HBN8jwGBfmhadN61IM3KMgfvXp1ynW/KSlp6NOnI/2/efP6NOSawyktcI9HDue+MANevdDycHVRIaxWKP47yHLKUCMjmWknSWLIluK0bJa7GojV0/8TxVx+SWniTcvZW5J4s91vQj0vSJ6O0j6kpWTUkv532Db7QDoXBVQyGTq0b4MAXz7b9jBOnDgJ+KiREqCEOY4NctMyzY45A3WsS1Xk8IRNSDY6ejpKBmepPbgqaQ5HSgrbVh3EvCSrVQlwyBOZftUA2c0s6BMyERIZxHanZMe8m8I81MqU88fdWymo/gBBdvKQdicmAX9/vx+2jgHITM1EOY0KiUnxCPZzzOHHKbpYhVT0W/Y1zn28n74W3JWoVHc9mg5viEv/XobZT43bGVbgaprdqzZnf1DW3Ru3y7qj76BmsIgeIc4I8UbI2wTg4pVkBMoFdBzxMbTVvfH3O6/S93009Qriq3I4nBKCSqmGRqOGxeQOpdwfJmumPSetTeyH5DJ2PxNkbBylkDHvRq3Cz65MLOWkVcoDnPL3OSffzhvZxivBKRew5C2Xc3/Ox2D9K/lIYKAf6tSp/kjHLo1YbZn4+6+deP3rZ6iBz12thovS0WvVKrAQZ6sgivWJ59tL7Qm56OlIDIrsPdYeiNGYLVkEiULmSY3ZhEupbGmxsWvavE05/LluJy4cvo3qFcvicspNKjpCCHZloke161XAuTPR6Nbh/t9FMi6+Nno6WreNQq/eLZGVZaJGpRo1njgBMqcAIV64b7wxDZs27aKvIyPLYe68aZDLFfh1yVqsXvsFILMwr9kcEC9tGVwQHX0bixd/ft/9Hz16Bs2a16X9TXhEML768mcanj9+/DCo1TzHdUEg+e8UJAV9vKIK93jkcPKQ61EZoEXm9jv3CrkUd8wC3N25enVe2LL5MPxqM2NfYSE094W8dUC2aFAuELGZS+fY4Pp+JCWloUO7MRAquwEhbPBeMyoCJ09eR2ngQUm/ixNZWUac/+Qg/d/c2hfmHoHITNDjlyErsP+XIzi35VLOuYZ7iN9yA74twx54DJmHEshgD+QpYRpoa/gg82Ac/tlwNH+/DIfDKcLkb585efKrNE9aSkrec+cVBwwGI1xceORIXrhw/gbKhgfCRVd4xpaWbWtgzqJXUa1mmftuU6lyMM6evvnA/RAjdfduLFf2J5+9QkPta9euiOPHzqF0UDLGVISZM+dQo2P37m2x/8BKTJ06Cu3avoD27Z7H9eu3sHPHkft+dvfu/2jexwoVwu+7TfnyZXHj+m36f1RUFfR7tgu0Ohe8/vq0p/J9OJyiBPd45HAegkZRBb/PfRWzP1wLy41ouLYOxtGrcfQ9g57NwrromAdkeIgr7ojebubrbEAtKMUbMgmDpiscdu6Yy08ybD7Ivmn3YoTjtjkn4KVtJAOVpIDtFIYtIyHh7mxWl/PgQeX2HUfgOjwSqUYDYuPYtSXh9wRfTxbaTJR/CWqNCmYxeX5KGvNijE0XRV9EL1m7urlaAa3YDrLEy1SrZjBdtq5WiS51KtZVrzt0EkatyqF5JKWzWdcIPx9Y9GYc2nUavQc7JiOyCcwL98CVf3FgxwUs+HwTfZ1YUQuBeGTe1GP5sZ1QesrRqS1vCUUdSXG6efPnIZhtuF1Bg8zkLCA5C+oz7FqTNhJdVgWBWB5Jv0KneB33k+hpQ8r6S/ij4UFUqBGC1iGRDp5EZOZfyLQyb8nYLBrEePBWHDSeNizfeACJlZQYU5N7PHI4nEeDKLYOHToQLzw/Ga+9NhBt2lejufDkooejTWCRIUYry7enUbB7pFIeZPdMzJ5AcuzYpNx+LOej7BH6VOtDfDRyG5g5riOCInwyN2/8888utOtQA8lGdq2reAfCJOZ4TDKyMZbezMZPRqvVoR14qLUI0rKwDgGSNySLFMm+jmxb4oV2Jima/r/nDpuUTRKPOaCSAiHVfeDr4m5vU74ubD8ZJtaO1vxyEN26N8z1OxiMKTh8+AzGjPmY5taev3g05Boz0tIyMW7s1xAE0v5yjybgFD1W/r4eS5ashpubDp/PnkTbkl7PPGfbt29C0yi0aUvaArmujh7R5FWVqmWRlpaOOXN+wqhXn4NCfq9R/caNWwgIJGrtNri6ajBgQBe6vmuX4TQXKUkTwOGUVEqU4dEiJORMRcwppZCxKBXiyK/9QYFK3m0x/6s22LbzD8yb8zd0rjpEPlMFS/Ycp9tkJIjh074uKF+GtcELieK6DFG9UXI98hRvRKmmbLEXKQxSCtGVPpNzTCt9JWcDprMXJnkpfX9n0RppvYIFrMhLgccjaw9PdiPPyMjEHaMewvUY+rp5U2agiUlgcjIuoiKih4YtLYIAo4U9HClusLyJsVdS2c7U4jUQjY0qDzXcxBDtLBJ2DeDMmbt0mSoqKTatx45XISIIx45dof/fuMgG0G6e7Po917Qxlv1vG0YMG4T64Y7Ww2VHV+KnaRsRnZwKeKlgCdIgq7E3ZDKBtgN/nQY2pGPgM455/koihZFUOr+wCmnUo+ar3xfh7MHryMo0IcNDjkxXud2Qfam2FvRZR3r2kkL8yW/f/pzO/rmakAlVkAIzP1pD1z03/DQq1A/D81Xb0TCi/fvOwqCTIyM1i+WuJaSaIRhsSJHrcSUl1Z5/rThhsjHP3lsZN3An0y4JxeFw7kN+jqkkunRpjZo1q2Du3F+wcOEqjH5tCFq3rkv7Z3I/IhgE5hmUaWQeZ74aBRRyxzwighhaC5lkeGL3VpanURIruV+OPimsWpwYZDty2EK6X2SHXufmNW8rVYbH/GgPF8/Ho0+f7kh3Z9d4S/RlhLmx8XOaiRkcU8T8ekrxeCpxLFfJywdBOim8XUx5AzbpZhVDrKWwbJLnMdKLTeZ6a1gb+ffmNbo8Hh9Lr2XzELa+uk8AMkVjp5/WHQd2n0fcXSN6PzPonvpPm/Yp9u0/iqi65eHt7YqFv45BxUohsEGAzWpFXFwyJk0aXiqCC59G/1CQ7Nt/CDt2HMLPP62irzdvWUQHUSSEvnWbBjhy9HfodJKIkdzJ4JjtBeLr54pFP07DV1/+imd6jkCv3h3Qt28neHv52ZXUidr17398kyM9A9sPyRNJxndardSPFVeKfmQguWIF3WKL9y8k/yhRhkcO52lCBifNWlRD0+ZVMXz+rzg87z94CgZkVHq4kEdRhXs85g2ViiQwL9ybqdVkxek3d0Lhr4a1E8tpRRAsNljOpGDW2uWo2aQc+va9NxHRwY1n0aBDFdw2sFn/LNELE2bROiWT4cWX2yEkVFIW5RRFiAfilLe+wr//7LOvS/dSioZE8QHa/gCQt/Zq1siR2swLilQzLh++iR1LDqP8+/5o0qwCVv62C4Zy9w6CzWoZzJlm3Dl0G2iBYgl5AOBwOIVLWFgQZs6cjGvXr2POd7/i+wXLMGbsEDRpWrFYXpr09MxSYXjMD1RqJWxEcK8Q+W7U70i8nYp1u96Fq5uYM1IQcObYTaxfchByhRwzp79zj6H5xo3bOH/hBn5bN5mJ/dkcvWUtVhvCwvwx7JX+Bfp9OI/OP//sxNtvf4aMDGa4bt+hKTw9syPByPXNNjo+HGJAnPzWy0gZ0Rdr1uzE80MmomXLxpg0aSS2bdtLvb1dXbV2g6NE794dMXHiDMyZM73YjqlUYnQWh3M/SlQLUciI6zKH8/RSMbooWMLwH0ePg22UDbOXLcE/v/6Ho0EymDxVyNCbEVyWGW8qVGcDkdtxbDbeEKd3FBdRaEi8h6NHosLJM1Fan3Od9OWkgZDzTCMJq5ZCqqVwXmfkMri5qkh+ZLi58UHywyA3U5vJiqqVWT68NmXLsksQzvK4GCzsWqeKoTlxmZm4lc6S4ytV7Hqr/ZkBx9ONhWPHix6xSoXMLkAkReRkpbDXl/TMOKJzY6JGDWa2xn9v74BLrBW1OkcidudNyHYmoXX7Ghg162V4eXtAISkdscZC/2799zS8XqgEUyrbn0oM/88ysPfdbpowdNYQaBSlow8tbCPy47Lsv1U4f+MKEspo4BdtxNUaLrAQr2kiVCRNwmdJxmTxtfRVSToHKe2DyrF/SRbTQqx0vQtFoA1vffQ9vAPdkZmUhTitnoZw2zERLwAgKVKFpG3nYBp/DRoF88gtDmI8JFRq2oy5OHzgMtasnQVBx1NNcDgP42l3meUiIjB79ru4dOkaPvlkHo4drYTXxjxn775uZSTTZabFgAAXL/q/Vhkhvit5JLJ7rlzGJoNlMuVD518cFYclcRo4ejQJjh5rzAiVe66bxMRkPqbKIyqVAkazEcfiY+nr/Xfuwiwa8NxUzIveW8sMPj4atgx21drFYYxWFoGSaWZjKS+NNN6VrpfKLjKjUbBxeZgb83xtEMjuaeaveuK7Z5fgmZbTsWLfFESfiMPShbvg6+uJKRNfR/UalewiNs5h4h27VEeqmY3rifY2wUPN2t6G9Qcx6LlOOQSPSjbFdEhFf/8//vg7Fv84Hf2fnYCZM8ejd5/2Tls5/9bl2f0LXW2xe9bm9Ib08nbF0KG98NJLPfHRtAUYNGgMEhKSMWfuR/cYHQkvvtQXK1dugNVqhUJMKVBc+PPPzZgx4zt88slbqFevJoo6hRH5VFwjrfKbEmV4LC0dPKfwUcmD6f3l7RcmYHCr2xjyypvoOaAF3lq9DRHl2U0osCxzrddo2WD4gjiza00Tw6iJcVDK8SiqI9vDInO7iUt5GqXOSwzLtYdASsZG8lrar94pZ2QOI+WIyChsPvQfqlThKsYPgwwC/LQ6XLsUA7lOCWMoM0AeuMNChLLEsOqOEeXospKXB34/z4w5cbHpDgZHs3S9xGuSdTvTroZNjDoO4fQ20UCYyQzU5xPjUXVobaTfTEXNS0CYiy/e++PLhz7oyN1VsErGzRyo1aydaGwy+PsFQc5zyxTZEGvC7xcuIjY5HUn+MqS4u8BGjI7OYxnpt26w3ps3VmxP9j5E6jMkr5MUI30M/y8IUKbFw+oiE9NB3Hucy4l6hMYasCfmHNqGVSwW92CSu/LMqYvYs+08FbW4E00mXgILu1ocDkekUqVymD9/JiZPnol5c//AiNEs/YdCzlKWxGdlItPM7mUVPNh9Uq1gom+CmBdSeviXy9wgl7H77v2Q+iwh13BY+X0nrqQuVJrEInnZsrIM+PrrHzFr1lv8euaBkOAQnDl1C/XbBdkNj81DQ+n/Hmp23bZFszHW+QSW67NXJTZeDdS5I83E8lur5Gz8JOX+lFTOJdVhGTQ5DMxsG6KgTWgUFIw6WyZgyguLcOFSDJZ+vQX/+2I6KlaMeHDdQwJw4fJNu8FREG+8LgpmGE1PN6NiRTJBzY0NRRmbzUrDxOVyFQ4cXAlPMXVRbnk5ZWIqB5m9X5DGU+K4RyCt4N5ICpLq6YMPX0NMTDw1KpYpE3yfYwgIDQ3E7dt3UbYs+x0UB0wmM77/fhmd1N2z53CxMDxyCo+Sn3iCw3nKhIeHos3z9XFmF8u9V1y4eOQmWj1bm4YFcB5Ox+fqw7SbiQoVJoENQuAd6YsdW05j9Jtd8+RdoQzRwUwMnLkgTzPDJ9D9ifNgcp4uKclpiP7pDIL7VaaGQ5uTUFR+QsK1SQi2TfKQzAWbSg65VcDRnZeKlQdp4yZ18O+WeThybDlq1Khc2NXhcDi5RBh8/vk72LBhW7E6NyT8lijWVq/O+5W88Mrw/vhx8WpkpksG48JBrVFi4lf98fNn/2L8xGceanQkREVVw8njLE9kbuzZfRSNGtXK55py8ptPP1mAGjUjUb16RXh6uj9VbzdirM42OuZOZJUKWLRoJc0VW1wgz5Dr1v2AXbtW4r33XkdxgGotFkLhlDCPRw6noJFEFWpWCsHVvTeoYnFKPPNO8gnychAecdeyn1uKJETDdsCQPBQlb7jcOii7gJpTOLb0WlqS8ElJJdv5OJKxIkALS4IJDSqwUGHOw5n04rNYueIAtHoZdt5kie51Kma01Ysh1lYxfCLU1Q0VfVgC/KPidYpPYV6LkoK1VhKUIZ6ImeIsqWTAEcOzpWtsEXMxquLMSNp+Fmq1Ej8umo0gL/+H1Jp9vmPrGri87wZOK032/EMEXx8tbFez0LV73WInEFJSYTPmovjLjcM4/N8FrNm9HzdOxeBOsAJXb9zOIT4lZPcD9+sPciKtM1gcPWulfkEaGZG2Kv2f7drjuK9kI26XVWPh8p3Yt/YUho7tgB4tn0dRRiYOeTzdc3oT8NEgh1PUUCoV9IHWYnKDRqOGh5qFu97VZyBd9HjUWwwOSscQQ6wlZS3iASmzr7sf7PcvlxGvuHujAth+HNVrc/fZUOD69bvw9+d5kvOKj7c/nn++L/5ZcgxvTe2P1mXikWYyO1xT6dzfSmSh9pf82fi6WbAAHw1Lk2GwsrFVlpVNrrrJzHYPd+l6CaL3o3TtNAo2dktIScAvn21G6p0MTJjYC21a9M5zbtK7MemQCTIoFHL72E8mU+Hatbtwc3eFnx+LeuIUHUgex4MHj+HUqfM4fvwsvL098cUX70AueS1KubLFPkRGl4oHRnRI60lfI/UhgiB52Dr3HfeHeOyOGfMcfv/9H/TvPxoDB/bEoEHPFAvnEBIV5uPDnnk5nAfBDY+cEklBzyxERZTBipQdgBdgEo2HFlG8QCXeNEzO+RZJLjZpnZT30faA3IzSdxINmHYkRWyJ7PtktrKt3YjAFk3CA2A9L0eres0f/cuWUtTyMhjzVhes+mYnbmttdAZzUMM69L0IDzYADhEVGTVyBar4sHyJfv7sPYVoGEpONzmm6PR1gU1SQJc55eATFy46ZhTUnDMgLKg8vvgfGSg9vPu2CSz/0PXoRKQZTfZE7lIbDQ/xRuLtGDzbrQtKE0Ux14rZFgO93oDP//wNB5PikLQjGvHXU5Dpo4TBZoNBJ4Mt2QYk6x2NilIe2Jz5YO+Hs6GR5IakB3eaAMmZN/Z+3oxmGywy4JLSghvKZPw3+Rfs73kez49ui6pe7ZCfREa2wZDn22PSlD702mkUVfJ1/xwO58EURpdJjHiJCRkIDQ2wpwEhf7OsUkitwtF4CGaclIlGBJtgsKta521iLXdhrmxV6+yxVnaItZgORW/E3DlL8N13Hz/29y2NDBjQHf0HrMfVy5loEByMzw8fputXpTBDY0JcCl2axcmyM/Es5D4uIp2qRxM8VI4CaGaB5YxUyYLuGwJrktpQloBjuy/j4MF18PLyyHO94+OTmI62wQAXrRpKsc3JocG/fx9Dt25tqRGytFAEh1T23+l/h4/B18cLG/7eho1/70KLFvVRq1Y19OnTCWXKhDqNB2UOk5R5MZNkGxtt9nyg0i5JHyT+l4fa2mj6o8GDu+KZZ1pj0Q+r8Oyzo7By5Tw6+ZKffP31YsyduwT/HV4Ld3e3Ip8mh1Ny4LF1HE4+oNWpkaXPfba8qCGzCkj9+yamffwKD699REIr+CO0oj8sp9lguKDxquZHZxYfxXB27eotXP33Cqo+y4SRcmK5mwWFlxoeHlxgqLAHx1s2/4dB/d/D6e2Xkbj5JryahCA6yhVJZV2gd5U/1dDqJ8XkpsDtGjoc2HEBRoNkxcw/Fv88Gb8u2YI3Xl8AfWbhhuVxOJyCQafTQq/PIWxVhPnf/xahX7+uNPUOJ++Q8cxbU1/EzBk/FkrKDh9/d4SG+z7SmIrk6Zs0aQYmTn6OGh2d2br1MDp04JP6hU109B2MHDkVixf9jg8+/Jp6N65a/S2mvj0S3bu3o3kUi+IkNMHNTYfxb7yERo2isG3bvnzf/6uvDqHLBvV74dy5yyhtyOSyQikc7vHI4eQLJKc19WiTyZAihkEGqdhMmVkMHTFKYdSSZxIZZEkeSM4K1bmFN8qdvCElryfJ41ESkyCbSfn6pM+IRgufCh5wuarHMz1qIaIsTwD8KJCZzGbB5VHjrSB06vYRjIFK7Lt9i77XPKSBeNmybyxW8dpJg2m1il0TX0+Ng9ehIssCvR+bJbUmiyrnogCRNpQZBDWix+MtuREud67h8Im/0SCqx0PrnGY+j3kLV0DRKgAnEmNhE9uMWWxDYTGAT4fq9mTsnIKDKCAajSbsPvQ3lv68A1f0qag0vBp+XLkfUAvAgcvZqRckz8TcwqcfhmSwJEJC9pBqOO5POo4kbkS2dXb+kbaV9pGzLqIKe2oZV4yetwr7pnVGftK4UWN8POM1vPfOHDRu8AaWrngbNWuVg0bORG04HE7Jw2w2QyHXUpVqyavtpi0FGoXSIVxWJqoXS56O2WGOVrvgSLb3mSwP6taOnZ+zd2P2/kk3aERKcjr27z+CqW9/ny/fu7TRsF5zBAftxoU9JjSpwLwUD5676rCNpHunFMe2MshgsrJxUorN5uAB66YSVaiVd+lCJQuAQsbCQE22G3SZIYbrqzRKdHm2PubOn4s3Jw2AWv7w/I4HDx2Cv78n6jYLQqqZhXC7Ktkxr1xKhL+/H7y9WMQLp+A5efI8Dh06jj///BeT3xqOpk1r3fPbF0QPxMfx9JO8ZwWBjdezvWmJD67kMamxp3Cg74jb5kzXkFt/4nAcQUCPnm0x57tl6NKlNfITtVqNzZuXoHPnF9G71ygMG9YfEycNz1MkFYfzJPAWxuHkA6u3/ofQagHA8dNID2AD5DPWGLrUx4oz9lkWx/sOuelIoY0acVSVKT7Me6gdP0MMA1I4tmRolAyYzvkcyXox3wxEg5aGGDhlQFvfUFw5cBHdWzXnrvWPgaeqCjz9gLq9ayL1VioOH2YzhWlRUeJlY9ctxWTATwePOihSS7NdKnFptyNb5TCb2TW1Dz9EI6WkhC0NUGw2G/q+1BQ/L9mWJ8NjsjEDJ45fg6GLF4xJGXaDo4koFQsCUs7G46M3+/D8joWAxZaIfzfvx6Q350PVIgBnMlOx56c9LA5B+m3bJyKe4EA5bZWyPG5LDJ3SpIgkMPMgj0vRMHo6KwMRv8Ug8rc26DC2Gb55bYpdXfZJIA+N/fv1Rdu2tfDeu99j8ICZOHR0DtSuVt6PcTglEIvFiqtXo1G+PMlDLYObik2O1fZTQqcIdsjh5xzSKsBgD3NUyNg92Sqw3ID2UEjRMJBtcCT3xtwndnLziiLGguTkNKSlZeLdd79BmzZNoJCXntDa/EWGiRNH4uWX38ScJUOpF+FCj2P0Hb0oPKNzZ+PqV2rVoEtXlQo20SBsEo3LNnFwbbQqHNSuVfTexbZJN7HxuBSu76FSo8MztfHGoIUY/UZHqNUPNzwePnwCTZvVhFmwQCFaRCWj58a/D6Fr17b5dmY4j95vPPvsq6hTpxpW/v4lzY8oGQal8GlBMNsnKR4P5/7gQWHUMod+Jzss23LfLDY5qVatAg4ePE7TzVSsGI4NG35CflG2bBhOn/4Xa9f+i6lTP6Pq3hMnjkKpQCYreG/XIupdW9BwwyOHkw+cPXwDNRuXo4bHIoMgwOeGAbpkM3SpVtgUwDltBlpNb4v6DSILu3bFmoiWEdj87magVd5zAuUXbh5au+diXggO80FsshEyP/agJaFKsaBsuWDoRPEjTsFz+tQVKBv6QVnLG9iaWuwvAQm5TiqjQWgqcP3o7Xzfv6eXG775bgL0WSlwceFiSBxOSeXkyXOoWTOyyKWDOXbsLGZ/vghGoxGnT19GWFggRr06AM/261XYVSvWBAT4olatqrh8MQY1osILXMhIo1Hl2RBRvnwozp27iqYIucdDbeu2/Vi27H9Pqaach3HhwhU0bBiFj6e/USxEWR4GaZNz532IFb9txMaNO/J9/6R/7dOnM3r17gCDQfLK5HCeHtzwyCmRFHSqmMvnYtBoYBTzVEpinbdeUq+WPBSdPRNzehFJY2vJy0jygLRKrxXZX0oKu5SQPCGtbF9KmQyhggKKBBPaRFVEn2HNUN0njA6sVEp3uLvr8hROwrkXEvJFCPVwg0ouR/TtDDqLte0WM7JE+TElazeVCqYscWZTNBI65/eQBrkWiwCDJC5jFNuIeK3vxrHZ+ZAyolBNgBfMZgsUUjt5CKGuZdG5fROc3b0F7tUDkJLEwoL0Bgt8b2ahz4ReCHOtX+oudWHkknImw3IXh4+eQVyYDMKdlOzftyB7POGY+yEZqUkYtSSOILWfB+WckVI6SDFueckxGZ+FBHdAqOCK9MPRWLL6F7TtHIUyrs0ev/6sEmK1A+nSw5WphfKE6BxOwVDQXebp0xdQu3Y1+2uV+NtXyYMgCJJAmzT5IM/10YZ4QkriMsTLiS6l0Eq7x5OkgJ39BZ0NUCaTDX+u24obN25h167/MHv2u1CpFFT8xmQy0dxxT+aWziGEhARCn6CAryYMrStVoOuOx7Jw6Yws0fNRyYxJcpnM7vHojOTp6KJgbUZGw13Z9fHSMNVxpSyRLqMz0uyh25L34sNo3rwJFn6/Fi+81tiuZu2iUOPc2WiULRMKD/fSF2ZdBIZU9Nd95MgptO/QjOZatfcTufQP2eIxj4593CGGUUtjNtLXZKdluN9nxT5LJtw3xNq+rbiTRo1qoXHj2oiLi8enn87H6NFDqCBM/iB5ZCqhcxYu5XCeAryVcTj5gNZNA6MkLiPlS7sf0g2a3KD0Uii1eGP0VDuFU7MbnMxLDSFG7+jVLxkUxHyA8FLDK86MKoIOr77cCWFl/NC6RQ9688qboiPnUdB5aaFITYNVLceui1fYOiXrUit4uuPWrRSHAZmXu+M1yBDD6JNj9dntwMkQ5CW2h4aVy9FlOaMKy+buRveeTfNUR2JgbtfGFZ//uBr+3SrhrpYN2iPLe8PyXzratG5uz0HDKVjiM1OQkpKBBB8boHcyMjrnVcwPiLFRal/S5MX9DJo5m6FzbkdnhBzbiIvEmAykBMrxxY//Ys7hw/h3GguT81LXfaKvkG1o5AqMHE5JxsPDDXfvMgVjgjSGkXKz5YZkTFDI3OnSJqhhE1IdQxylxx6xr8oZpp1tcMxWyz59+iLef+9LNGtWH9WqReKVV55zUj/mwmz5RXBwAO7ejYNc5oFWocybUG9m49uLScxQGO7OJnfJqDbNJI6JRdzEPKAe6kCHUHx2sdkFz7IwQ2OykU3qKszAusX7aF5GjRjC/zC8PP3g6emJmFtJ8AxixyC62Rv/PoKuXds84VngPC6kbyCe0oMGdaZGx+xw6uzfs+PrJ0PKHys9lLFw6vuZVZzHWqQOuRses+st5oukCwE//fwplv66AePHf4SFCz8pct7gxQn6XFzAoc9FVciooOGGRw4nH3Dz1iIjqfDUF9UmAe53TFBn2dD7607oX78FXc87uqeHu78rVHdTYS0Am67FYMH1DZdw9loaZn88ElG1mTdAXggM9KfL+B03IdgMQLwR1hgDZAEu0GrFJOycAoeEd3l6u0KlT4FZV/IMaValDF59KyDxh3O4djUW5cqzh0EOh8PJS+jtqVPnC+1EZWTosWfPEXz37c/48ssPUFmc/OM8PUJDA3Hm7NkCOcXEM+3E7ivY+MshtO5ZC/+bNvKRPk9Uq7+d/Rf6vNAUd28n49rpu9i39zzGjXnzqdWZ83CialfF3r3HUKdutrd0SUGlUuLll5/FrVsx+OGH3zBixHOFXSUO55HhhkcOJx8w6s3QuKiIy9u9Ho/O4Yx276AcM2DSZ6R1RFWWIKme2XL5fA517IA4K3QGAa2/7YI3GvSESu6Ye4aTv0R6e+FyGV8o4+6SaXaotcz6uPniJbpMLlsGiVKovSgUYxJDV1UK9jo5TfSQzSSS6JKKuXgAcZugAFcId7Jw9P2d6PZ8Y7z9vxFwUedtVj4na3+diJVL9+DQuasoW6c8nhlfF+UqEkMQn4ErLFRQ4OyJaIS5K5DQ2hfpanHiwpbjstgFpMSZ8SdxgCT7kGZcH+ZJKTygv3mQ4I3NcZvdq89Ao7XhzTcX47Wv+qBvpSfzeORwOKWD1LR0aDTqHOIvkneRLIcirbRGcZ/wQQ0EMC84m6B3CLlm4bc5PuEUZnvtWjTGj/sIv/8+lxsdC4jg4EDExBAvVwF6C7tOHcqWoUtPDbte3moWKi3ACJUo6CKFO3uoSMg7GU55OoTYkvYihdxnWgxITdFj7vg18Av0wPKfP0FAoA8UMuZJmVeGDOmNgCAt1v+2BRUqBqNTp46YPGkMXF1Ze+MUPOR6r12zmaZpGDGyP9Rqu5Kn08BGmeP3/vhjYClaSIAoAvlAT0qnVEvE/CJzTvPA6vugcG3SHxKl7iGD30SjRrURFVXyDKwFATm3XFumcOCGR06JpCA7FKPRhOtX43HYlsrCGaUwRrts8X0e8sn7zkZJMRxXLRmrpBDcZKPdGOVohSSQHtSKH34bi0pVQrjRsQBoFVIL6TX0WL7zJLJCZDh66Dpdb7Wya6PWqKAhRugcZEjq5uI29ucpWY7QerPYVjzZQMbL3wPGO2ZkpBnwytB2j2V0JIT7t8Ck8S3s4WalPVS1KHgC79p+hi5V6VYmFiTVSZ6jv5AUpW3yvKVxeBA02iwfckU6h1yTl879WI4QbqNGBqtVQEJ64XmEczicJ6Ogu8zt2/ejb9/OOdZk52TMTh2TbVhyROp/ZLAKSXaFa/oJOcuNJpOx+7NNMNqNBtI6cowL5y9j6ND+qFWrylP4dpz7hVpfu3obFrMCLYLL03UKMZzUKKpQG20sTzXBXRUkXjvWHmSicnA22Y3WKiTTZapJjxRDJi6cuY1ZM0ciOKjiY48hOnXogk4dpDZa+GOKwqQIDKmowY4YHQmHDp5E8xZ12Pp7QppNEKQwZlHd/vGQ9vG442npc9K4HE4GSHmO8ap0gm1Qq5U0pP/cucvc8MgpdvAEARzOE3LgwDF4VPR+YmOGyiQg+HQGgk9lwPd0BrwvZMIlTZrlfzB6nRxnT0U/0fE5j0anTvWhTTRDlfngBNFPisxNhWcGNHqqx+AUPE1bV4G3rxsSGjLvjJKMyWCBRlf8FSY5HM7Tx2q14sTxc6hbt8YT7cdiseKLz1fgtVFf4e23fsInM1Zi2dJNeRIXI2IOJ06ce6Ljcx4N4uHapUtL/PzTmqd66jy8dAgPD0SFijwyqCRBnsEmTHgFLVrUQ/MW9VCSuXMnjnoIczjFDW545JRIClJhbfv2fbih0GPb3jPM21HyZCRei6SQXxkpxBtSEngghfxPvIdIcVGg3E0L3OPNcEsww/22EZ7XDTRnI/U0Ih5xbipWvDWskHWkaBSQKWTQ6biAzP3bQ/42CBKW46IJQIVBVVElQY70K6lIv5pG2x0pVpsAY6aZlUQDLdTTUfJ2lLzZ7B5tAitkApQUg5WWkydu486Ru2jWsCYCtSxX45NAPANYUZRaRWB2jQpfgjHELRTfzhmLoLtW1KodKlUs942lvkPqU4pabEpu3tuS56NVQIbShsXbDz/1KnI4nKdDQfaZx4+fRc2akVCSPs8uDELunTYaKp0tDGB1KhaxsG3fGP8Rflq8CQf2n8WG9YewfOkO/PXnXioCQUKvWcmkxSqkUu9HUsh3NVssPGz2ge3h6Vz7ESMH488/tyEr0QfemmxvU+maaxRutGgVAZBBRUtuIbcszFpqO1bIoaOlokdlKBLcUL58OWiU4flQ45zeaKWXojCmItdh6NABiI9Pxs2b8Q+8NkQYhhYYaSkcWD/1aO+zB8qIiDCcPFkw+VBLIlJ/UtCFww2PnBJIQRoWTNZoHDh4GKnuCqZSnFMlVjImSWMfydAkGQ9y9EEqgb242MgNlxq742JDN1rSy+sgcxcNjjkNVQStkpaGnSogQKlGk3pR8NE8uXGqpPE02oNC5k3LL68OQqNyZeDrooFrhDuyEg20HD5wjYXYW3Jcf8lwIxXJ0ET+d1GyohELyQdpscHPTQ23JAvq1WsAhdwvX79D6aUoDJDJTzkAdWs3RnCYD8olqXO0ixwb2duOWKS+Q6NgpSCQ6iC112yB0BzbiO9JfZ4TyaFK3PzzMoomRaM9cDhFmYKzKwjYtm0fWrepT5Vpc64XB1IQBCst2YZCZkRwZvPmvfh4+igcO/Erzp5fTcuvv02CVYinIdikZBserA5GiG1b9yMqqmpBfelix9MaY+u0Orz55nDMmvUDvem5KoNoaRlSgRaSG4+pl7NcnyzMnrUNkseRFXItrbAKabQQw7JcpqVFIfPFls1nUK9eLbsKOufJKRJ2R1GAZeLEkfjs04VUsZ4WuyGakdMoTSYySCGpGKR0DAWH3Knc7/176dOnE/7+ewdN9cXhFCe4xyOH8wRcjrsAlQZIyzAjLdXk+GBOBGJIkYwFziWHx2PYZQOsxI5AwhG1Ssg91LS46VS0KIiRwe5Ox4p/WTf4B+vg/08y+j1THxXLNYFazvLicAqGYF1dfPj2ZFSMk+G9/m3s1z4zVs/y8T0oJ59kaPJQIaSMGy0qdxUtbiGu8PBxQb3zSrwxogvCgitDKWNJ1TklY3ZeIfOgZc5HLyJ5SzTgqWaF/L4lo7XUhsTffL45WUgeipLHtfN+c/NevN+xc87iOhslxT7LK5h4qJROD1sOp2RQMH0mMRhdvHgFVaqUhWAXlCE45jlz9ASSvCGJIYHV8+RJpojds3cUze9nERJpybKk0WKx6WmRkMs8IIeWlgXzV1Bl3CFD+nBvtgJHhjZtmsJmtWHXrv/s191dFUwLycnnnJcv2wDJio0aG9MQb7hBi1VIp5Eegk2J2Z//ghPHL2LgwB4F/9VKNIU/ppJo0aIhzGYLTpy4KIYQEQOzMjviR6ayr8u79+HDYQZvi1O/JRnFmTE8dx52bMU9Rkit1gUKKe8/55GRyWWFUjjc8MjhPBHuHlpkpBueeLpPZRQQXz7vangqgw3KeCO0ZzPQsE0kug5q+ETH5zw+AYG+qNK2Io6sOp1/p1EQ4H00DS8Ob4d+g5rxy1OC8Q/whEqlgCynYbGEYYvJgjzEOfE/h8Ph3EvlyuVw7tzVJzo1a1Zvpsu8hreRvJJrVm/BiRMXsHv3YXy/cCa8vDz45Skk3n57OL6Y/TMMhvzz6Fq2dAOSklIwf/4MuLszkSFOyaRZs3o4d+4KSipxcYnw8HCneVE5nOIE9zPncJ6AQwcuIjTCF1pdEvX8obqtkhGShMvmpgIrKhZTBWMSni1iy+EQZDOw9RYxn5tGJYfexP7XuivheTET7ieYSt/UkROgoN5EfDaloCG5oggTR3bC5GE/IqiMC2yeKsTdSL+/MVqa9aL5q9hliyeq5Tno6hoCY2NfPNPxhaf7BTiFDvHiiAgPQ4ghC1Y/Ne7e1ecUZXXsS6Q2kxckVXWT+FmSD1bvFI4o5YuUCY7He5ANNLcwa+fwamk/4ox8kEGNqB418153DodTKjGbTdix4wAGDe7g1NlIfV+2Z1B2qKyk/prdPyYksPGRTMYmdLNzAabTvyabmS4VctYnxsfH4e23v6b/r127ECrlk6jdcp6UsDJh6NqtNRb/8BdeG9s/11B6Z5y38dYw46JS7odr1+7i99//xYoVc6BQ8Effkk7ZsqHYvfsQC7OWsd8y84pl/8ll7IFLUrfOL+zpIWTZxxJXOLxyJPdxXc7+LLvfY+sOHz6F+vX5mOpxYQFnBfvMzFM8MrifLofzBNy9lYw6Dcpn9ygPDDsUS6aFFSIgolEg6BYbAGfq5ECmmZU0VrLu6mnRZ1khV8lpebFRLXhcoSZOLP5pGlRKV7sBjFM4RPpUxwfvDUfwNQuaN6n8YAORFDIv5nFEhhnmdFa6dKiGVuVDYDyVhqUz3ynIr8ApJJTyQDw/ZADCY+UY1Knhg/MpSm1GKmRSQwqbDtTSIqvoQUv1VmVQrWkoohqHoVZUMHwqegLhbqxIwlQS0msp9DpnsYtkicdxDrWW8jrmND7myGtLsyklGjCoWa0COZ8cDqf4YrGYodFoEBzs7xSGKHU81hxhiyz8kDygs4d0VoinE8nv+OG0UVDI3MXiSYubKoIWrUJHCzFemowChjz3Pj1avXo1UbVqxUI9BxwmhDds6EBs3XoE0TeT7snT9yCkcGyVPISWtBQbpk75AtOmTYBOl/fIIk7xpXnzBtQ4d/v2Xfu6bFFFWS6Ci6w8DIvFiuvXb2HnzgOIjSUCNtmw9smKlDtSSv8gCCQVhC2HAFa2CJYz2UIkOcOrpf9ZP/jvv7vQpEndJzpHHE5hwKd9OJwnQK1RIi0lO0/Qo+KabIFHkgXXauggOHtG5oYgYNuH2+i/n30+Ho0b8xmvokLdupFQuqqgv572eDsQBCRuj0b6qQSsXTSDh1CUIurVrwmVToWEM44D2bwitwrQpFmhNtigvmOGWm+F+UgGM4D7aWiuWa+raVBr5UgPUEFvEyAUUL4Z/1gLeo5tAjnPb8PhcB4CCR00mZ4svLZ3r9F47rke6D+gY562//yT5Yi5E09DvH/++X/8GhUR1Go1xowdhJ9+XIf33n/xsfZx8sRFvPfuArw2+gXUrVsj3+vIKZqo1SqMG/cyvvnmJ3z66ZRH/jwxMF68eBVXrtzA1as3ceXKTVy/Hk1TMoSFBaNMmRDMm/crjTbr3LkVOnVqhYAAHxQE+/YdQXp6Jho35oZHTvGDGx45nCc0PBpNZihzerhJD9g6MXZaSgBsFBMLSxNcxENI3NaslTuGVEohkJIxMsuC555rDH1MBs5sO4DFP7+Opo2e4deuiEBm1cmspodKjRDBheWCvh+SY5g9JF9ARAU3KPcloXV4KCasGwMfV+4d9jQp6BCLB8Fm4AGlnxZp6Xo2oe0caq0SG5TkVSj2C1ovF3Rw8UPc1STUrhyOkAhf1K1SHhHlA1C5bF3I5XJ7eJHVmoX1uzdj39az+HPDUWS08EFsTKZ9fx6JFmhTLYgNVjkKzDhPiEh9lFSXnB6Z9vqy/qtyDX/g7C0836MLPDx0+XfSOBxOAVMwfaZcrhAFYhxDC4mnI8EmZNhFGhRiCGVuvPRybzG8WgrDZn2oDKwfUsnL0iVRQd6x/SRGj34e48YNfWrfi/N47c1qkeHuXZLKSHxcdVA6d/6EeI1lRPlcwK+//IM/123Ht99MQ/ny4fwSPFWKzphKoly5MGRkZOZaN6kPyU7XwAYyJAfo779vwLp1m1GpUgQqVSpHS+fOrREREXaPQwDxqNy0aQdeeWUyevXuiJdf7sX2Jo6LatbojlOn/7L3X9kZmO6tk9RHZT9A5Mx9I/0eBMyd8ys6dmxZpMaxxY1sr9KCPSaHGx45nCciXTAjKUMPq1UcJMtyPKhLBkfpAd7Z4CQDMj1zbCMIqHxUj4sN3LLvN6IqsjZIh9kt2mLGe79jwEcT0LRRd37lihhmsxmp11PQ7t3OWHrpIowknJ7gxR6OpHQtAgmjB1C+ije95nV9Q5C5IRrDxw9E756PN6vPKb6QB+kzpy/j5qFoQONLvRPtkPBp0lbKutsnOuhniNHvQjoqpmowYdjLaN6iHhTyB4eQKZVAvzYvo18bwN9/Onb8cwq7y7rAppbDXSWH5/lEKLJsiA0R+yPJwGh16rfs/ZjT+hx9nbqsGzTJZpT5z4CRc4bAz6vaE58nDodTGnDOgsb6IRamKBkMbA/8jJubDufOXUeZMsHo1HEopr49Cm3aNBL3I9iNU4RdO04gIqIMNzoWUXbuPIy+fbtkh1lLBshcwq6JIjkhLi4Z06fPg4e7B5Yu/QZaLQ+vLm2kpqbj11/X0t+280xuzpD9nErTd+7E4pVhUzFgQA+sWPFdngSIQkODMGzYQDRoEIWpUz9FcJA/OndpRY2Iy5b+ST0n9XoLdFLO7QeiyLWeZPKY/J+WloFx46bRdBBDhvR+hLPB4RQduMcjh/MExMekwtXdBXjM6FqSE/JiA1f6r1y8/ynMAqxqp5kRQcD/Zq2Du7sLnn22G79mRTQsqELtUGxdchiKrOzBjNJgg1u8CZpMK6xqOSyCDTaFDPJ9SZDFG3GnogWLvh6OiHKBhVp/TuGxePEaININ8HGcTSdK1z43DJBfMtDXtpzhynoLJi17FS3LNXjk4w14uQW8fd1w6qdNSIvQwuNUKp0wMWrYBMgTey8IAnzPZuL9JS8gKNT7yfb12FUQ+Awzh1PMIKIw6idUav3v8Fr62ydiIzdvxuDkifN2w2NO9u07iq++WowffvjkiY7HeXr06NEW3y/4DVqtDU2b1abriNL17l3HsWf3cWh1Ghri6ufnhRvX47F712E6Fnvuue7o2bMzvzSllKNHT1NvxC++eOeeccE//+zEmjX/wGZznMC4cfM2pn34Bpo0qffIx6tVqyqWLPkKQ4aMQ9Nm9fDl/xbh4MHj9L34+ESEhz/5+H7RohU0d+WwYQNQGGRP2hR/zz3u8Vh4cMMjh/MYkFkyctPasOoIGr7ZFPoTzDDggKQm6zzTlTNc0ir+Tx74xb68wvFM+DcOgWekLw6dug6l3oaQaEBeVYF333+uRHT6JZV3Xnsef63fh8r7rsC1ki/0t9IQaNShTocohEcGID0lC4pMKzLSDGhYvzJq1YlAgFt1KGQehV11TqEhQ4uW9bDz22MIqeCOK74pULkqoI0zofpNOep1qYvx/fuI3QObEZfDDd4+nnBz9cpTQnRnynk0Rv9u1fDlx+vgHm3EhFl9MH/GBuiNRkSF++NEUiqQKoa0SZ6Pzt1OTg9Ip/equ7nDHG5Do0gpp1bB9lkkvKpeve7UK+Ddd8fyPpPDKSYQL6F+/UhuxtzzlchkKtgEJq6X7fnouK00RiLbNmpUG/PmLceRI2fRtl0TlC0bgtu3YxF98w4OHDiOH374FH5+vk/1O3Een8aN6mHf3mNY+us/+G35Fri4qHH27BU0b14fXbt2gMVsQXx8Eu7eSUS5iAi8+MIA+Ph48VNeyqlevTKio2Mwb95SPPdcLwQF+ePOnRh89NG38PBww6RJI6HVujgEbJC25ef3+HkaSbsjuSAbNuiFV14ZSA2YV69G4/33vsIvSz532poJZTHu75EpYTSasH79VmzY8CMKi549X6F5Lw8d+hOeniwKh8N5VLjhkcN5DJKNx7B7x1lkugO7L11hCtXO+dAkA6O0lN6SlsToaBU/Z7bRIXRSJz+4HU1DebihhkswWjUKRkioDypElEWjeh1pzjZO0aVmtea0jHt9NDZv3oo6dSNRNqxKYVeLc5+Z26KAXOaKPr17okGj8vh1ySYoUlJgumtFZJXymPrNZAQGSuqu+QdR/PT28sMnn43B6dNXsePfU9BnGKF1U6N8uhpC3WCc3HnT0fBoHxs7pY7ImQ/SS00Nkl6XTfCrQBRFw1DQCLDA1U2DynXK4Ndf19AybvkQjKzTBwpZ4XhfcjjFn6fdZwr04Xrjxt34Y9XXOXKvOcKUaWX3yYmWvZXED4tmYfHi3zFv7lK0b98ch/87g7CwQDRv3gijR78Ib2/Pp/aNOE8OEe8gRiLC3r2HqeJ53brV+Vi4yFF0xlSEgABfrFu3kBrrpk79BCkpaXBx0WD8+GFo1qz+Uzvun38uwrx5S6iQ0ejR79J1RKDm0qUbNGekY5i3Iw9SbT927Cz14CTfobCYOXM8+vV7HQ0b9sT0GePwbD+Wz5LDeRS44ZHDeUxW/Lob8lr5O7Nq0ypgKK+jD/cvD2sHpZb9RHVKDz7QKkaQmdTuPVoUdjU4xYigIF9MnDQYqaZWcFOx3EIuivw3Oub0CurRsyUtm67uwAtTOmLbmuNIik2HYcFJqMupYNI8+kSHRk8mUWyoPyAKhcnoWT0xpc9CGPQmXNx3HahTqNXhcDgPgRgJ2rVvDJ3OJd/OlUqlxIgRA/HrkrXU4FCxYgS/DsWUp2kw4pQ8SMg9yQ9KSkERGVkeX331AZ3cPnFiE86evYQtW/ZgzGsfoF27pnjrrVcfa78zZnyHLVuWFWr0RvUalTBx0jDM/nwRFsxfgT69e9CJgeIIybkv5d0vyGNycsvOy+FwHsrqfUeQbjHi7K0UnD4Ry8KqSbEIzCOIFOJVRYrewgrxfJS8HwnkPSIeQwpRvDZaka63INFdDr8QD/y2aje81XVp0cgrirP4PMy6OEC8NRQyH1o4nLygkgfT4ufSAC6KqrQ8bZQyf1q6lO+IjuEdMH3cS5g7cyz8Az2gUyiBIG12fyYhdUPEu5sUpRzQKGgJKOsOX08XtK5fBS9Vr029OUkp6N8eKR0j2mH+POZxsPHbPahWpc89OZ04HE7RwCZYsXTZWgwe3MMu/sIEYORisYpFYe9XyMM9816XOiXnMVJ2TrLZs9/Bu+/OLqRvx+FwShOkzyHeicTzcfLkUdTgSDyvHbaB3MkD0kZLzi2k/sxisVCxrMJELtNg6MsD6f/R0XdRq1YnbN22q1DrxCl+cMMjh/MIWIUkXLh0Av97dy0Sa7tmGw5NVlYkYyMt4rhXMjhKr3M+yKvkDsVsttFy7fJdlK3oR3NJ5lRd43A4nPxGIfOkhUxwkDJ2zGCEajSoVy8028Ao9VP+WlZEYyMpPhU94BfqhsaBwShn0yI0MACe6sINayZh1U0at0C5uqH2dZ//+jm23lqLJbt+wP9WfAGDKQ5W4XGVwTgcTn4xauQ7aNgwCsHBQczoCBUtOWY6xJLzf6tTEZxKNhcuXEXVqmQCl8PhcAoWokRNFLZjYxPuu022IZL1eUTF+uTJc1i7ZjO02sILsc5ZQ4VCiS1bFtFXRLH7o2nfwGwxIi09FevW/YvY2HgUB0i6DklgpsAKdxyi8FBrDucRITcAhYcamvIewKn8PX0Kow1+V7NQo0sNVK9dll8bDodT4PTp2xYf/7ECWWtuwl1vhV4nh1XFJkvcEs0IuZiFuyFKpHkpoEu3wW9dHH0vOUsLXag7ejzTuMhctb7vtMf8Eb8jvokb9v59GpuW/QeNiwopiZnoEtUWak1RGNBzOKWb9PRMDBvWP9/3azZb8PeG7VTFdvnyb/N9/xwOh/MwvLw88N57YzFs2GT07NkBLVs2pGHZxCBFjJGtWg5ElSoV8Pvvc5CcnIaWLVlf+MwzHajB8sMP3ygyJzk0LBDPPtsJLVvXwsGDZ9Cj+3DqS+Pv74vLl69j+PBBhV1FThGGGx45nEdAEMwIDvaCJcWI9MTMbOEF+y9Kni20YFeDlTn6FyvlcEu2QG0BLN5KqAw2hLhoYY3PQqhJg5bPNcDEocOgVJIk6sUzfwaHU5ThyvAPRqXww/HfFuH4sQtYsnEVzh+Oxt30DKh8XOCZCdyWZSHojoWVusF4683uaN22JpRylptSLS+HwsYqpNIwzN2bzsK3sh+O6tORWgaQBcnQt2lVJP5wFJUql8WNG7GFXVUOpxjwdNO81KtXA0ePnkanTs3oaynkUApFlMnYBAHLVmO9Z1x2+1Ysli77G5UrR8BksuLixWu0xMcl0Yf8BQtm0tzLHA7nacDTQD2M5s0b4PvvP8HOnQfx7bc/U9GZGjUiaR7IMmVCcP78FXTo8DwV2SKCSoMH9yqSfdbNm3dx+PAZTJoyBG3bNYLFpKQTR5MmfY5u3ZsVOaEhTtGCGx45nEeAhj2TSGkfNcxxemZozGlcJCGJRK2aQEKvnd8jeKjhd9cAT7UKz3VriuBgH9Sq1pImPXd11fHrweFwCh2l3Av16zVCvXosoX9KSjLOnbuMRg3r04Tid+5exsaNe/Hii11gg77IGBwlbEIaflu+Ff/9fBSN3mwK9dGzaNyoAu7MO4nMu3cwfeJIKOW+UMiyCruqHE6pp0bNSJw4fg6dOjFRtuxJV+khVmbPM+aMTcjCrVux+HHxKowf/yLUai3atG6KkSOGUHVbPtHE4XCKAiEhgRg0qCctxBubhFKXLRsKf38f+nr16o1o1qwBwsKCUBSffxMSktGj+6t44cWe0BHxU8GCxYvXYP2fO9GkST1UiaxGQ8SLOlL4c0Efk8MNj5wSCPltyyWvw6dAZmYWbElGyL3Vj70Po06OnlPa49Wu7elrd9XTF5Io3e2Bp7PlFN6AoyTg5eWOJk3q2A0CAYE+ePGlHnTgWRQh3o79B7TB+pjTOLbgMORRLsg4GgeXcA8sXTQrx5a8LXA4D+NpjqkIO3YcQIf2zNvxcUhLz8RLL/fBqFefgwyPPzbjFI32wCle8Pbw6KhUSpr7MefrAQOYuFZRHVP5+nrh9z++xKxZC7FyxRZ06NgIf/21C6vW/A86F7/CriKnGMCfxjmcR8BgjcOSpWsR563A8bNx2cIxUv5zgygyI3k7EnRKeBiBMoIKASHuCFGqoLMCvapXg5uqJi1csZrD4RRFiKGRFQ0tp679i4GDX8Hsb+dhz8ntuHrtBt7+bCE+/3F5IdeUCUqkGY5j9JjxqFntRVyKuYD+FashPMAH9eqVge5oGuZ/8BwVniGFw+EUPtHRMbh08TratG2Uy1go99dEVfWNNz7G5s17cOrUZezfdwJenl6iIA2Hw+EUH6ZO/RQfffQ19u49jKSkFKxd+w+mTfuKGvuKAhs2bEPVKh3w/YLfcCs6EXXqMIPp9wvW4KWXesNF41q8nmMlkdeCLpwnNzx+8skn1Htk/Pjx9nWtW7e+R81n1KhRDp/7888/UblyZURGRuKvv/5yeG/NmjVo3LgxPD094e7ujurVqzvsn8N5GE+rr86ymJCWrof/lSxU3JkCn5sGQG/JNkDmol6tC3eDm0KBgU2j0FkVgGFlq2PGlIGoVb6p/aGew+EUHEVlMFcckcvkiItNxSeb9mLIyAVoO/gdbL8djWXL9hVqvcy2GFo6vv01DmXEIilEjT7tZ+Gdt5bgwvnb8NmchAHPPoO64R1Q1OHjKk5R4+l2mQJOn76I5wZNQIvm/e15HR/EnTuxNK/YgQPHsOSX9QgLC0W/ft2Kz4Mvh1OC4EOqJ+PmzTsIDQ3Cxo07MHz4FFy7Fo1Tpy7g1q27KGxIHebNX4K5c9/HH39swGuvfYDvFyzDunX7cPrUDfTp3RNyGU8TximAHI///fcfFixYgFq1at3z3vDhw/HRRx/ZX+t02Y3SaDTitddew48//kgfAIcOHYqOHTtCrVZj69atGDBgAGbMmIGePXtSo+XZs2exefPmJ6kqh5NvtOlYCwvW7oY2wQyLMo+DXJkMaSmZEGwCRr3WBZ5erjzck8PhFDsCg7zg5+8B77NJuN7Ag+a5Da/ri4x/b9H7eWGGsd+9m4iM/2IRNLomjvyrh9lFjgZaL3QZ1RTlPD3Rq1E/FHX4uIpT2ggNDUSLFvWxe/fhPH+GiO8Rz6CyZUPQsWMLdOzY8qnWkcPhcJ4WY8e+hBdfnIAjR/6Cmxuzl8yfvxSbNu0oVJVoMqabPv0bTJ40As1bRCE8IgTjx32CadPGI8ugR+PGtaFUcOcZTgEYHjMyMjB48GAsXLgQ06dPv+d9YmgMCso9OSoxPJLk9LVr12aVUCrpOmJ4XL9+PZo1a4ZJkybZtyeekb169XrcqnI4+cbB2BuAJ1BxaE3c/uworBo5oJIDRkeVxZxTgPrYLChlNmxff5K+vnL1LmrVjoBC6cmvDIfDKVZ4qoMw+LkuODFxLmrVCMCN9dfhZ0mDtkZQoRod99w+hAXTNuC6nwxntl1AFbMSgtmCH5eOhVanhq8LE8kpyvBxFac0QnIwL/zhE1SJbE8Nig+GjauqVKmAM2cu0kKeJ7jhkcPhFFfq1q1Ol+fPX0VAgDc++2wBPD3dCz3n4z//7IJGo6ZGx9Onz2LKlG/w2WdTUb16JciKsT4xF5cphqHWxGOxW7duaN+eiWM4s3TpUvj5+aFGjRqYOnUq9Hqmeknw8PDAyy+/jODgYISEhODVV1+lIdUEYqw8c+YMTp8+/diqS6RIYVcCTLRwOE+C1K6i/IJp0cSYENCiDDKDNDSHowNSmguSfFsug9pXA1ezDA2aVMKv6yagRcNe8FQzozuHw+EUJ1TyMDzTox9en9oDtsXXUN6gQuvaVfDqSx0LvC4WIR7LLy3DrDVfYHj/uTgYHwM3yFDmkgG2/5Lw3jcDEeJdG96aaigOFNVxFYfzdJFRRVeiQH302HoIsOWyjZTDhrF79yFUrBiOL798H2+//Rq/QBwOp9hCHK/+/HMRRo2airFjP0RQkD969eoEDw+3QqlPfHwS3nnnc/z003K8+FJndOs2AmPHfIrJk4eiRvWqxdroyClcHqvl/Pbbbzh69CgNCcqN5557DuHh4XTwe/LkSbz11lu4cOECVq9ebd/mgw8+oHkbyUynNDgmjB07Frt370bNmjXpPkiuRxKGTbwrNRrNQ+sm5YZRyNg+ubpd6eRpOd78dukcXf638xLc4s1AJY3jwRQyQC3O2HsxZcW2dcrj7tXL+HHxTNEjiOcg4nAKE65q/URnj/597aUJGNzrFVy9dh1169ybbuVpYrbdQnq6Hj1HvI+YywmwuilgqOdB6+a5OcG+XYeA5sUm91BRHldxOE/TmZlM6l69chMpKWm4ePEaatSonMPI6Hxg9nrx4pX46af/wd/fh18cDqeQ4boZT05kZHkcOLAOR46cQu3a1ainYUGHVS9dtgo//bga7u4uePHl7nj/o74YMnAGrl65TbdJSTaiJCCTs1LQx+Q8huExOjoa48aNozkXXVxcct1mxIgR9v/JQJfMwLdr1w5XrlxBhQoV7O8R8RhnXF1dsWHDBrrt9u3bceDAAbz55pv4+uuvsX//fodckc7ExyfDYGDejTYhiy7lMkdvRxsR/3hCmGbIk4/CeF2eznmxWm1ISkqDVpt7+3y8urBQaksqW3poXeGuNcNProGNGBtz3iBI6DVBpoRGb0PWvkR4hfogPj6NrlY+Ztvh7eXxzovRaEJqagZ9GL8f/Dddes4LMViRNkH6icKuS1E6L49bl5DgQJpbsSDrEn3nKj6btRShtcJwJ9yFTje6K2TQXNFjyPjOaNA6ElW9o2C1AnFxSQ/cV3JyKgqbojyuio1Ngl5vyrfrSx5u8kOIgNelYM8LGVPpdOx3nt91IYbHlNR0+Pr64OLFGwgI8LOL7pF6sLqwCsXExFHRhaws0ocL9r4nv+rywHrytmsnOTnd3rfy88LbS872wH9HT9a/hIeXoefzcXmcvs5iseK7735GVpYeixZ/ApXKCAECTp64AVc3N+zY+Qtk0NJtH9bnpqdnPHbdOSWfRzY8HjlyBHFxcahbt659ndVqxa5du/Ddd9/Z8zfmpFGjRnR5+fJlhwHygyDbkfLKK6/gnXfeoXkeV6xYQUOJ7odWq4FOx34YEH8gT0fNlCh1P/leeF2eznkh7dHFhbQFl3yri9kWSzvmf/ecgkyjgOu1DBoMpJe8G61mtiQ5H8lhBaCRQQ2lVonBrRujZasa8HANype6PBmlr+0qlXKYTGa4uj6oPZS+81Ja60L6B4VC9pD2UPrOS3GoizShOPTFGSjfPAK7E+7Yt32mQ02cO3EUg7oOgY+PV57rUtBeBcVtXEXuo9m/lSe/vjmNSE8Gr0tBnhcXF/Vj9JkPr8uJE+egUALDX3mbvq5bNxI6nRoyqMS6yOx12bhxJ1auXI82bZpQcYNHqw9vL/l5Xkh7kMbY/DedO6XpvORsD4Vdl0eB14Xx88+rsH79Zuzeu5gaLS22NHqJjhy+gqZNa8HNNe+e5VarBUUdnuOxGBkeyQz7qVOnHNaRQWuVKlVo6I/z4Jhw/PhxuiQz9I9DREQEnZHPzMx84HZECUpSg+KUXsgDG/Fwy8+2cCszBtu3nkLMkrP2dW6jIqE/wtzPoRbFZYhniK8rXBPM8JABsxe8gPIe7AGxuIT8lTRUKiVMJgvc3V0LuyqcIgAxVBFBM94eih9WgXnead1VMMdloFGgFqFNykCfoIdh2Q10a1of4eGhj7TP7MnKwqMoj6vc3XX8t8KhRoX87jMzM7MwdOhE++uRowYhPJxN0Mpl7Hcp5Xsk47rZX8zH7yvnPfJvnJP/EEcP/rzF4e2hZJCWloayZYMx5a1v0L1HK4SF+WLlis04fy4a8+fPeKS+XxAeP5qIU/J5ZMMjyRtEEps7h/H4+vrS9SSUZ9myZejatStdR3IRvfHGG2jZsiVq1Xp4HqgPP/yQJkwnnye5iFJSUvDNN9/AbDajQ4cOj1pdDidfMBnNmD51Bf1foVZA3SEYcjc2I58bmb5KBLp44+sZ69GtnQVt2zaG+v6bczgcDiePvLNwMDUgr95xCpc3XoKLlwu+mjYKFSqGFctzyMdVnNJI3bpd7f/37NkOY8e+aE9r4wwxvs+aOQlvvjkd/ft3Q6tWjRAY6F+AteVwOJySyfjxQzFixCDExN7En2u3Y/2fd9Cnb1tM/3jqA9NUcTiPivJpKDNt2bIFX331FZ1JL1OmDPr27Yt33303T59v1aoV5syZgxdeeAGxsbHw9vZGnTp18O+//yIyMjK/q8spoeRL1GAOwr2jqAt6q3bDYTVYkXUhGYYgZfaBTOIMD8lNFsfCAb8PiIbbbTMOH72GveaT+Kj7GLpeBp7Mn8MpTPInrJhT0Chk3nTZo1pvtqzeGXiNDWMUMiIuUzLh4ypOYfM0uswTJzZh//6jGDXqbfz551ZMfXs0vL3v9zsW0LZdE/j6eeL3lf/g1q0YTJgwPP8rxeFwHhk+pCreaLVaWkie3RrVaqOkw0Oti7nhcceOHfb/iaFx586dj72vNm3a0MLhFBVsggE7brM2bTOIs/GXMxE1rD4uXmfCBEK6mONRLgO8mGFxyuA2OLvuHISr6XilSUNucORwOJx8QC6Tckk9eR7fogofV3FKOhoXJWTybIvmTz/9gTfeGHafrVkyt8SENBw/fgZTpowuoFpyOBwOh8Mpkh6PHE5JxmdkVSQtOIea7zeDUnf/2Gm13oqt07YivFkEvv1lDJSqe3N0cTgcDofD4ZRWSMg04dn+XTFu3Ev33c5ms2HCG9NhtdqwaNHnCAriYdYcDofDeXS4x2PhwQ2PHM5DkMlUOBafQP83JhnoMuSuDQ3qR2BZ1iG2kVWctXdVoiZcYLOaMWViTzRvXQ0B2ob8HHM4HA6Hw+FIYytkT8j+vvJvTP940j1qtzLI8c8/uxAbmwCZTI7vvpvGzx+Hw+FwOMUQbnjklEhkLConn7CgYVAg/W/Jrli63LbtDA77ZZHEYg5blon0gvH3GHj5uqJ7+0FUUTkvCLA4vJbxnyaH81RnOzkcDoeT1z4z/8+UACsOHGDq7IS0tHS4e+jY8ZAtaLBgwVKcOXMJv/8+N/8rweFwnhg+pOJwOHmBSxVxOI9AlYnMe9F8OQ3mO5mObwoCNNsS8ML4dpiz7rU8Gx05HA6Hw+FwShuNG2cLGXz77U/3vE/yPnp5eeDIkQ2oVatqAdeOw+FwOCUNmVxWKIXDDY+cEkr+KqwpUcHDl5Y1m08hPZSJx6T9dAmqRCOQYQY0CqjkcsgTzbh48A5q+laiYUQ5Q4nuqSMsuJS6nZYX//2MlpsZ+2kRYKSFkz9wFWNOdlvg7YHD4XCKyj102bLP6PKXX1bjvXe/oKMjATZaZs2ai717j0Ch4H4SRQmuYswpqP6Bw+GUHPidnFPiyG/DAjEeBuoiaflqZHd07xRlfy9AUCDAwwVVIrxR3qaGXKfEwQPnsPPIYRpGRMqD9lzGLYCWhe360BKg9aKFZUHgHpP5ATc0cZxaBD8hHN4eOJxHvI/mN9LkbFTt6vZ1q1f/g7/+2oJb0bfxxezvUbZsCJRKBb788gfedxchuKGJ49ge+PngFD9xmYIuHG7Z4HAemeDIbDVFl5sGuJ7LhM1NSQVmXKv5IlivRGqyUxg2h8MpMvCHJg6Hw3mkXvOpnS6FQgGdTgu9PguNGtfGxDc/pevVahXq1q2O+vVr0PyPHA6nqMItjxwO5+FwlyoOJw8oZMQLERhWtQlQFThoSIT+QjJil12g6wObhyFxz20k3kxBo8lt8MnMdVBkqdCiRXX4+dSk28igdtgnmel3UWTP9BcWklem2XabLhUyd3HpXaj14nA4HA6HU7IhY6P/Dv+BG9fvoGvX4XRd+/bNkJCYjBMnzuHjGa9h9mc/4bPP56Bf3x4oXz68sKvM4XA4HA7nEeGGRw4nD0i5GtWKCnT514AJdNkkbRLS/rqB2E3X6WtNBvDTnG2wuMqwaOdezPpuNUL9PFGvZSVMGTmKulorZb5F6pwLAssleVd/ky6DdMF0KZd50OWD8lRyOBwOh8PhPD4yKBU6VKhQEdt3LMPAAa9jy5a99nenf/wDvvhiItat24aZM+cgNjYRzZs3wEsv9UNgoB8/8RwOh8N5lFtOwSux80hrCjc8cjhPiCrcDeYbGfbXQbctsMmJIS8GliwLbD42pCVnwmaz0ZAiDofD4XA4HI4jVosVQUF+VEzmzp04um7njoMYMOBNCDYbTCYLtFoXpKdn0NBsDofD4XA4xQNueORwHgGZ+JNRyliex4Oz59LlgbjtdBmnz4RcnEYhKteENqHV6FKjCCiS51omYyrdYa51HEKvuacjh8PhcDicgqJMmTCsXDnvITnkuOsIh8PhcB6PwhB74eIyDG545HCeALlMR5dNA7sV28GxZGCUyVwLuyocToHABwAcDofzSL1mKT8+h8O5P/z3yeFwHg43PHI4HA6Hw+FwOBwOh8PhcEos3OOx8OCGRw4nX+GzfhwOh8PhcDgcDofD4XA4BJaEjsPhcDgcDofD4XA4HA6Hw+Fw8hHu8cjhcDicUoUg5MzFyuFwOJyH9Jr8BHE4HN4/cIo9MrmMloI+Jod7PHI4HA6Hw+FwOBwOh8PhcDicpwD3eORwOBwOh8PhcDgcDofD4ZRYuLhM4cFzPHI4HA6Hw+FwOBwOh8PhcDicfIcbHjkcDofD4XA4HA6Hw+FwOBxOvsNDrTkcDodTqiBhFhwOh8PJc6/JTxWHw+H9A6dE3M0K+jGA30EZ3PDI4RQBTCYzzp27hCNHTmPr1r1QKhVYsGAWXFw0hV01DofD4XA4nGKDIAiIjr6DY8fOYteuAzhx4jy++D97ZwInY/3H8e+u+xY5I2euSrnlJlEoSkJK7vtWQshVUsqVW0jORMiRsz9dJCJR5ChHjuS+j93/6/0dz5hdu2vP2dnd77vX08zOjJlnnnme3+/7+3yvD9+Sxx4rEtu7ZhiGYRgJEhMejXgHXgz/ONC2/sKFizJz5iL57rstaiAXLJhP76dLl0ZSpkwhp06dkRw5ssb2bsaT88GqShjO+eBnEY+G5whhR8Mw7kFcsKkQG1ev3ihLlqyRvXsPSooUyWTfvr8lICBA7r//Pvnjj/0mPCag88HwHnY+GHEJay4Te5jwaBheFhuTJEki8+Ytlblzv5KCBfPI+fMXJE2a1HL06HHp1audtGzZ0H4Tw4hFbt68JceOnZScObPZ72AYhuGjXL9+XW7dCpBff/1DRo6cKqlTp1I76+bNm5Iq1X1SvPgjMn36CEmaNEls76phJGhY42TKlNGuRcNIwJjwaMRLAgPF57h27bq8+GIHvZ8ly/3y77//yeXLV+TkyVP62Ny5Y9VINgwj5iNjQoPo45Yte0mGDOklWbKk0qbNy/LQQ3ncz//ww89y5MhxefLJ8loWYc2ab6VRo+ekcePnIrQPt27d0ttEiRJF4ZsYhmEkTJuKcXzcuJmycOFKKVLkIdm//2997MKFS/p85swZZd68j2N7Nw1DEvr40KFDPzlz5pycO3dBGjV6VmrUqOTORDp27ISsXv2tlCxZVO6/P4O+tmbNitKhQ1O1wyLCjRs3JUkSkzYMw1exq9MwYpjNm7fL1Knz1NtXuXIZ6d27vdZ0XLnyG1m06GspWrSQjB07yNKBjVjlypWr8tNP2+XgwSPy11+H5a+/jsiJE6c0JSFFiuQqlpctW0yeeqqiZMuW2ad/LVLrjhw5puUKcufOIffdly5c6dUsWnfs+F0dAO+911t27/5Tpk9foE4CR6ykJELBgnnl448/VZFywoR35NlnW+r9Rx4pIEWKFJAHH8we4vU8d+5SWbVqg5w8+Z+WAGCfMK6feaZKlNK/+exDh/5Rwx2x1OH33/fJV1+tVaeHsxEhdO3aDQkIuCVZs2aSHDmya2Sna8uupR4MwzB8FcSL4cMnyLZtv0mePDnls89G6e3WrTvliy9WyK+//i5jxgySvHkfjO1dNRI4ROLu2bNf/v77qNpU3BKNmzhxYk3/L1Qov9SoUVEee6ywz68BEA4PHDgkmTJlkAceyBpup+m//55WW+p//5svZ8+el1mzvpTevd9z21RkfHEMKDW1YcNmGTr0dVmwYLm8+eZ7UqVKWbWrsLtCqnlP+YTRo6fJP/+c0HUVwmPNmpWkXbsm+r6R5eLFy7J1669SuPBD6sBwIJoaOw4bjs9z2VPYVTf0FvsJO8qxqXLkyKa2szmYfQs/fz/dvP2ZhohfYFihH3GE8+fPS7p06eTcuT8kbVpbNCV0iCQ6fPiE5M6dPVaFDybY8eNnytdfb5S+fTuGKi707z9CnniiuNSqVS1W9jW+c/XqNTl9+rxkz54ptnfFJ8XG5cvXy8WLlzRdbdq0+dKpUzMV61jIYXBhDF+6dEW90t9++5PMmPGF9OnTUZ5+urL4Xnr0CalevYmkT59WihYtrIY9hv7p02f1MRaieNSPHz8lhw4d0WvUMfYxDBHjcuXKIe3bvyqPPlow3J994sS/snPnHvntt72ya9deFQE5dhjMfOaff/6li+RUqVLI8OF93MeVfzd69HR9jv0rUCCvFCiQR489Y4WnUUutsu+//1nSpEml32Hfvr/k8uWr+p6pUqWU3LkfkC1bfpVChfJpNOaWLTtkz54D0rz5S2oMI0iSbsgtm5+fvxw/flIOHz6mwiW3iLUcE4Rmx2h2jGgMepwniJsPPJBFpk37XJthzZz5kcRl/vrrqOTJU1rOnTsnadOmje3d8RnMrjI82b//iOTLlyNWD8rp0+dk27adMnbsDB2nR4x4K8S0TRxo06YtkIkT34mV/UwIHDhwRPLmjd3zwVdBQGPuzZXrAXnrrQ+kfv1n1JmJXcV8yvzLfHrq1GnZvn23fP75Mp3DP/54sPgSyANnzpyXrl0H6jX1+ONF1J75778zagtgM+XOnVNtj7NnL8nRo0fl2LF/9d86Sx2+a0BAoEY5khkSXsgGw5Ziw67ieNJ0E/vm4YcLyKVLl+Xnn3fKoUNHpV+/zlK69OPu4zp//lcyf/4y3Yd8+XJpxgp2FWUYsKdu3HCJhHyPH37YJkeO/KO/z8GDh9XZjqMam7hUqcdUMMVWq169gtpFiKYNG9bR93TZVHfsKm5xijj2lMum+keOH3cdk6xZM7sdvNyiV/CZ2bJlkrJli8vPP/8qPXsOlaVLp0qWLHF3vUL5sHTpCvmkTeXYNeU+aSCJU3q3/MbNyzfkh5YLfPK4eBMTHo14hy8IjwgdVas20glu0aLJOumF5s1s27aPigNEkxnRjwmPQYXGH3/cJpMnz1GPNX+TLgz16tVQI2vevHEqZoUGkX4U8MdllS/fg2qkOUaXywgLaogFvX/neTaErdSpU0bp92V/li1bp+k1mTPfr2Ia0S4YnMEXrQcPHlKj8L777pOiRQvqvjtgsBKJgHEZHQY7JRQwmPfvP6THCcPW8/NCGjNoiPDnnwc1MgKjOUkSl0jIscJQLV++pNvTnj9/LjXE8cw76Ug4PIiw4DflM5977qlIRVFg9JNOfkeQ/EcjNDCcN23aJj/9tEMNfxwqr732osRlTHgMGRMeDV8THtu3f0s2bNikUeLYTKHNU8wHzHPvvPOG1/cxoWDC4531Bo7G99+fqDZRrlzZ1TkLr776guzYsVuaN28QZmABWVGjRn2iNgoNJbHNPB2FYdlQno9zHxuDTIao8Msvu+Tttz9Sm4j34zuS6dKqVaMgr0O8w1ZBPCOLokSJR1REc6L7sEcc52hUMjoccICTxbFr1x5twFmixKNuJ21IsH+UX3DsKuxd57hxvNKmTa2CH45colLz58+tzmpsN2xJ530RDteu/U4zX5o1axCmHReWYxxHs+PoxcmLqJsnTw51jm/a9Isex4wZ75PvvvvC56Nf47rwWH7aS7EiPH7f4nOfPC7exIRHI97BJHnkyAk1AGITvG5EIOGVDw0imPCgka5pxAwJUXhE+MJYIg3Fte1TAwzxCE/tq68+rxFvpFTjjS5fvoQaXxEBo460Gzy8jhc5eNqJKxXF874r1Zf7/C4YYaTJhSV0Bv9eX3+9QT3DRBFiIBYr9rCm5oQ3lYX6X1evXpdMme6L0Pc17sBvTgo6Amf27Jm1XhNF4x2w1xFDiUwgcoDFCUJmyZKPRvg8i2lMeAwZEx4NXxOaaPjVrNnrWg87Q4aQF//MK/Xrt5Xp0z8MkiJpxL/zwdvg5EOgwqZybrEnKK3CHIhz0VWi5l/NuKDuaERAqDt69IRmboRlO4VkYznP79r1p9pDZCaEF4Q5Ml/Iovj77yOSLFkyGTmyvzz44APhfo+EeD5EN0uWrJElS1ZrSjtCL/aTI35yg42L2IooiXDJuYZQSbkuX8KEx5Ax4dGF1Xg0jCiwceNPsnPnHxqeX63aE1KlyhPu54i4ol5JWALphx9Olg8/7G+/gRFiXRy8u4iG3HKOlSnzuFSt+oQ88kjBuzyiGK0U2icajai4rFnv17QUNurkEAGHl9eTiKQTBwfveuHC+aP0y1Er54UX2kq6dKnVeCbisFKlMvLaa/XvSjVB7Jow4TMVsEjbadOmcRCvtOE9SN3u1q2FdO3aXFOgiAbYu/dAkNcQ6UkaFHWWSDEjCoPSEyzGqlUrp9GuRHZYTUnDMBwYM3BokLJJZFGLFi+569bitEiSBAdT6BWiZsxYIHXqVDfR0bgLIt6Yp7Cnfv99v94nYg6bqly5kiE6QLHhqTdItgSCHPWdqTdIBGP37q3uin7j/SILNp1TGzCy4Mxt1aqX7pcjVJLaS9QlqcOe9hLPEfzAOoTyMs8++6SWMLDmLLFD3bpP6Ubk65o1G7WRYfBMlAEDPpIUKZLJAw9k0xR3HKdnz56TF154WtPgsauowWk1JQ1fxYRHwwgn1D4jjROjA2FnzJjpapQ8/3xNLWb82WeLZObMRSoYYRjjjRw5ckCo74dxzXtFxVAxwgaxipQrxI+IRDySYkIaa0iiFikT1JlCdCZ6EC/36dNn5L//zmrxayLwiMwjtQPxzKnnFxoIhqRauIxh14bxSMoHwh5b69aN1bPJd6G2Hp52PjdJkiQyb95SWbJkqqaXkf46YkTfOCPI0Qm6Vq2qkiiRv6a/kKq0ePEqqVTpJenatYWkTJlchX3ELVKgK1cuK6NHv21GlY/AOeaI2+GhZ8/W8t13P2vRdprsICKfP39RhQVESM71sFIoDcOIPyB8EImPMMI1j+OMUg7MsaRT7969V156qYPOq7yWtE3EkdA63TJvuxp4feb175JQ4BhTd++PPw5EKMINRzvzO3ZVSGADffPNDzofUCLk6tWr2hwOsYXGK0TUIxRSfoR0ZM8maqGVLsGWonwMztu9e/8Sf38/FQ6ZZ6hR3bnza5o58b///aj2PHYTzt0PP5yidZJpUPLRR1O0LjOBBHFBkEO0/PLLyfo7OWnF1J9u3fpNXWu8/HJdLcfy22971F5k7p4yZbjPNwxMSBDN3bDhs+F+PdcO9hTRkthUZAIB5zNj6yuvPK/lvgwPWB55e43k+0syr2Cp1ka8IyZSremS2KBBB/dimxD4l16qramrZcoUU0MIsQnx5/XX39HubfeayBEoX3uth3z++fgo17lLKHCMMUxJ6+V3ZoGCcMet8zfd7TZv/kXT3PmtEAIRCQMDA/T3ypgxvWTPnkWyZ3f9ZqSXUKMHoQ/xg6LZpCljpGIoMzdxi6GL+IXAWKxYEalUqbRs27ZLIzQQBVkMkXbzyy+/6fvSrZDi4YjUCGucD66i0tklefKkKqZhGCOOUoSc1xcp4hIa2Y+wxEoWYXTwpJsf+8q+8R7jx78TqmEfV+CYNWzYSWuecp09+mghKVgwz13RmpHFUq19D9Ijue5oXkR0CUXoiW5iXKQgvOcttZ2i05tvqdYhY6nWRkymUrrmyDt17ypWLK3Xd506T+p8xt+uzz0kzzzzmjqpBg7sfs/37dRpgDbzIIrNCH8kIAJfcHvKtQVoJ18aiWFXMU4zL5848Z+cPPmvjsXYRTQcw65Knz6dpusi6GGLYMtwu2PHH5I0aWJ9Pwf+LYIztfuwv8jMwJm6bt13ki5dWrWpOBdowIKYQvM1zhv2Acc+/wZ7yukcjMMWkREhhog/x3HL5jQDCet8pMYeXdHnzftKhU7szE8+eT9eBAf07DlEzp69oKm6ZLqQNROZWoWhYanWvgXXLmsPxHoaGJJ6z+8e3J5Klcp1G1KTrnidaj2dGo/Rs6YILzcvX5fvm1uNRxMejXhHdAuPCEOIiRs33kmbxshZs2Z2iIYMRhtCU3gizj799AtNoe3Vq1207Gt8FCTwzGJ4siES0v0XEYpjjOGKUcut8zcGI15rJlrSOHmPgwePSKFCefU9nY581NLhN8ITiJeY9AbqpmDskrIQ3ChF7MNAJi04osIH3mfq9jiFpTH0iXbF2xxa9EZEz3mEyrgQ5RjbmPDo21Afa8WKb/R3oqYWNSK5vXTJdcsC+fr1mxq5Qso2i1XGhMhiwmPImPBoxJSwwHxKdOPs2Ys1Ms0BkadChVJ3vR4xjH8TnnmXub1du76yYMEEjZQ07j6W2EPbt+/SjWg4SJMm1W07ymVTYU84thXCIg5cOgfj4MTO2LVrvzYb4hgzLmPfcOzJDCJdl+Zn1I/mMewdah4GjxjELuI5PgeHUkTPIWw5x6Y6fvyU2nGIjNRcjI7mHNjycd2R6y1MePRdOI+XLVsr//xz8i57yrGxWN+wXsJhQ7QvEb6RXU/EBeGxwozYER6/a2bCo+/HjRsJdqCkgxjFxDFMMW5SpcI7k1I9qPdKxSNCLTojsLZt+01rk7FfeHMRs7ifLAS7NiKGSpMmz2sqEYIaHdWMO8yZs0Q+/XShFC/+sDz+eBHp3LmZGrORiXbCe+5MokRSsT32WJEgr6EGXWjdAPm3iMz3Su8JDQxuCnVHpFh3RLB6LhLhRYvhm1CegHTrey2e6Ri+fv0P0qLF6zovMEa3a/eKdOr0mgnwhhHCmIcTFZsKcR+IeuHawfmFMzUsonvI/N//NmnEGqVIyCLA3iP1MyQiIiJhH9auXU2mTp2nY4FxB6JHiQhFoENIrF37Sendu2OkSltQZ84RdomYIqKQLThh1fDFLkqSJHWkfiJsMseW47vEBCY6hh8zqXwXzuN69Wre83XMC99886MMHz5RHQnMDTS6mTdvXKjNvAwjopjwaPgEM2Z8ITt27FajGOOY6DUi1xCCSGNF6MMoJeLswIG/VcCpWbOypg2kT59GB0hHWKKgMnWD7rsvTaQaFxA99vnny9UDjBHLtmXLUhk16hNZvfpbFXkQrSZPni0dOzaNUgooE0Lfvh1lyJAxMmPGhwlmwYxwgKBMtGfQ7V9NqTl58rRkzpxBFi+erN52wzAMTyGCTo5sNLmhGyRNlUjVRrS00hVGQufnn3fKwoUrtBQHoh7RZ2nTptaSH46DzWVTXdZoMWysp56qIFWrllPbi9c6wouT3po0aSItKxMZO+XHH7dqdJpjU82ZM1rTd0eMmKxRzDh2v/tui+TOnVOjmaMCDWnq12+vjRpIxU0oEL2EHUUK9N221SmNRKKZYVSayhmGEX+dvpS5YaMUWLVqjXQ9vHPn71pfPT7h7+enm7c/0zDhMUGD+IMB6QtiF0Vx33ijrRqfiIVh7RNGMLXxvv76f7J06RqtP4PxjMeN5zCwixQpIJMmfab1AF318/Ld7kaXXzuBhRQhhmGMR5g07VmzFrlr3eBN5X3YJerYON5VOrkyUFOsOSqkTZtGDX8+L75HrtHplmLdCMNEOxBlkTlzJr3l96FuIvdZ+ERnzRHDMOInjPk09lq69JMoCxaGEVWYx6MjzTM66lLjkB027M1wdTklswObZuzYGRrlgs3DohNu3rwpefLklps3r6sASW04rjWXXZVPa++FFDWH6Lly5TeSLVsW6dFjsKRIkULT+rCjaPhGnT7KJFStWlY7BlOTbODAkTJnzpgo2qV+KpySWhjfhUec8dOnfy5ffbVWjyn2k+eGc8axscwhYxhGeGA8admykXTp0swn5jMj/mARjwkUvJ/UwaFLIEag05mUhht4x3kebzepOBhwRP9h1Dj3MWidwYiFH7XxiPwjOjEy6QmkxjRv/rrep5nEF19MCPW1GKQIlGzBYV8wko8e/Vdy586uhjONQ2jkQSfgr75ap4WniaJzDGciAKg1xHctWfJR2bx5m9a7cJg48V01jhEhicZz1Qc8rl77qNQWc4x9ij7Hp069HHMWHECxcX4vvGcsaOgw2KNHKylXrkRs76ZhGHEQhItRo6apOILDiZpiefNGPUrKMKIqOA4dOlZTiO80tsin6afUsUMEo1MvdhQ2FLZU6tSOTeV6zLMGHuc3TlWccJGJ+seJV7t2cxXlYf36uWqzhAYpq060S0jf7eDBf7SmH1BbD5tqz579Mm/eUtm796BmmlAbGSGSa5HGa0Qw1q//tNbHpqkI1y707NlGbT4n/Rv70am7fPbsOYkKvOegQaOkfPmSWus5PsB3YpwjS4RsH84T7FEiWilH88ILT6vjJbKlYAzDSNgwjlNH36n5SHfsRYsmmehoRDsmPMYTMAwx2hgwSJnBk3zt2jW9f/Wq6z6POc+tXr1RevfuIE88UVy7ABNBiDC3efN2rbmDd5TIQVJfqT+I9xsjmIL/ToQhzztCE+k3GEIYpBiYFIrmfYgOxJDFuA6L5s0baBORlSv/Jzt3/hHp44DI5Wqy4fobMY+OdGxPP13Z/Tq+D92+nO/cvXtLd82/Zs0ahPjeCKqubshZpFSpxySq8Dt07vy29OjRWgXQ+ECbNr1V6EXM5jxAgOTYU/y7TZuXZeDAbjaRGbGOL0R5G+GHeeuTT+ZrZDyOJeYUFttOd8bIlNQwjHtBwzEcsZ72lGNH3bGzXH/jVMPmWbdujtpJiHLYF8uWrVN7KGvWzHquYnuwqHPZUxfl/HmXTcWGDQXMnWnTptLai0QB8v7YH4iQNM5o3LjuPYV2akaPGvW2dOs2yC1khiU8hoWnTQU4mHEeejoQaRRCV2C6Cv/yyy7JkyeHOhkdMfXdd3uFOA7jvGWjy250MG3a5/qbtG//isQHFixYLhMmzNJzC0H7r7+O6Hlw7tx5Pf5Eh0bVAW4YUcVMqrgF6/Zdu/Zq41TGd9ZsXbu2cHe5xqaKz825YiPb09YdLkx4jKPGMKIZhi2eZjzPrvSVrDpY4PVkwGAjfSV58qTu+/ffn1Kf//DDfu5C0E7NnerVK0TaGxv8gsJrQnQg3v9GjTpp91GMpE2btsn332/Vmj548e+7z2V0pk+fTqMCHDCSMbJiCoRQuh6zxRYTJ87S3xIDkihMFhRxeWAiSpRIWCavZ56poo+xkEK4Rnw0b7xhGBGBur+fffal3jIf0BRh6tT34/Q4afgeCFWU/3BsKuwrSq5gn+CEvWNLuewpz/tEKpLKjHBWsWIpPTexL3BORtZBGZJNhbBHhgRO4qFDx+hc+/LL9eTQoaNa2xQbIkmSJFrzGpuK64VFpMOOHb9Hm7gXEgiMBQrk0e25556S2ABbg1IuNKIjeufhhx+KUg3u2IbzgHMJx/T48UPdjxMsQB10Sv0YhmGEF4KD5s5dqmXKmCco9dW/f+e7mm0aRkxhwmMsghebOoUIhxTdJt2ExzAoPLuE4elGtEmcOLEKVRjD1NQpWDCP1KtXQ+/HZsRHSItAVyTKg5p688or9WTx4tWyfPl6FR8p/o9RjNBI+ggiI7ek2FSqVEbFwKiKjnGhw1rr1o11YUJ0wLJl6/UcIGWQKFG6OJNyHhcaq9A9kt/2xo0bGmXBIsyBc9cXojmti7Fx51yw8yEugHPqpZc6uv8mkhoGDx4tb7/dLRb3zPBVGOe3bt0pmzb9ooIccyo2k2NTAeYKNguCFOIh0YmQL58rTRj7o0mT5zUCJLYE7pA+F2GPsjBsOHLp4v7FFyvkoYdyS69e7dTWwtGHI9NlT7k2bApSuWvWrBTv59B8+XLJF19MVJtqzpwlsnv3Xv3ujk31+OMP37N7ty+Ao+Wjj6ZqxghBARUqlAryPFk3sU0cOB0MLxIXxgeDjL6e6lwDnFWAnbVnzzcJ6vBYc5nYw4THWIDoxDlzlsqXX36tUYaIT/XrP6MGRkhCE55u0nyuX7+p3uy4VugVA/+ll+ro5gnflQ1DOiEKC6RfeaYrkS5PcxuMZoRa6kVx7B5/vLAUK/aIGs5OzcTYT+s/rpPXn38e1PR4xPNJk971yc5nceV8MLyFnQtxpRFVrVpVtTmGvz9pMf56G/3zn50PcR3Gd7IrpkyZq05LyqpQ4zBHjuzqqA0+Z5Jm5qRJMw/HxWj84sUf0S24OEmtRrboJi5MofzOrtqa+d1N/4jwwaYiAnLmzEXq6Kb2JiIkgiRis2dtzdiC/SJiE7tq2zaXeE7k6Acf9BVfxGwqI+j5YMcj7jjnlml0vFOaDLvKMLxF7M+28QCKY+N5xnilsx8pMHe2O3+Tijpr1pdaX5H6VAsWjNeaP/cCo8gXDCMjZmECIGKQrUGD2voYEQukSGE4U+sHDzjh8a5GP6m00Dj1zmLKi08xc+qA/PnnXyoyckt9T0RyUvULFMgt77zzhkYaxIXoTMMAWzT5PmQAOF11g6dL/vDDVrdo5MyxrvvcJo9zzjnjbkgFI1oxqE2VIsgtc8769T9oXT8i/wYP7qHz572g9jPnC5sRXuKmskA9Shz8Tikh7HBqb27fvkvrxnI/RYpkki6dy67CvkLwo9FgTEATnt2797ntKW5pPIRAzjnM+fvii7WkT5+Ouu+GETeIm+NDQoKgkXPnLqqTI2fO7EGeoz4vjg9nfnXsKce2Mg3CiC7ilZq1bt336unMk+dBr3iwWRRRJHzSpNkqIObKlV2791L8GXHm0qUrt29d93n9888/LV9+OTleF201og+M4MqVy+jmTBzUz3Sa/dCQp3XrNzUtm5RmVy2qpLogow4VBrVz66pJlfx2zc/koU4knKfU4Zw//yutJVSixKNatwkxFMMY49wwDCMmqVKlrNbde+GFttK06QtSp051zRagJEevXu/K009X0WwAUrKdeZb7lPBwGp+B4xC8I0zeEa+4f+OGS9w0Qmbr1t802j4may57OgRYFP300w5NlaWUDHPdsWMn3b9vcLuKqLUxYwZpgzvDuBdJkyaRokUL6da0aX19jPPKaZyIc3f69M+1ViRiJY6M4LaTU9/zzn2npnrSUDNSWBfMn79MvvnmB/1sSiTRebtZsxc16ye2M1kMw4jf4JAdMqSHdO06UIoWLSzt2r2iTl3m3KlT58qJE6e0NIdrjg1qVzmNzxim/P0T3Xb+hWxTxYUISku1jj3ilfBINz3SbQ4cOCyBgQGSI0c2NQYIKXZFDTq3znbncWrRef6dNGliranoPMZ9mqXw3qTD/v33Ee2uyWcUKpRfi1nzHoYR0xMHxcadLuEI7UTPfvfdFu1qjvGM+H316lXtZu66dbqbXwvyGBOJZ+QXhi/G9OXLV3UxRw3Kxx4rbAaxYRheB+dJp06vaQONKVPmyKuvdlPxi8igWrWqacfceznwGN+IcAruCHQELG4RtYzQWbFivTpXib4nsp7IMGwiBBzHNrrbnuL5oI972lPOLcefSAtsKjayR+jkzOLHiaQ3jJjGiX7l/CbikJqKOD1+/vlXtZU4L4PaUa7tyhU6m3N71Z26H3z84ToBFuaUG+ratbkFHhiGEStUqfKEVKxYWuvyI0AyD9PcFbuKsSk8TWZw+DLm3bGl7jgC2f799z+vfBcjbuIXGA9yzs6fPy/p0qWTc+f+0A5NwGKDaC0MAZpecKEgFHLr/M1rgj8W+v0bkilTRi3gjTGcK9cDcbIuUEIAQe3w4eOSJ88Dsb0rcQqiKbleEDfj07nN4uC//85KjhyxX5DdiH2IoOKcyJIlY2zviuEDEImUJ08ZOXfunKRNmza2d8dn7SpMRZyvXD+OPUXdaU8b6Y6dFfQxXhfS40TjIzJiV7F5I6rSiBz79h2S/PkftMMXAbhmONc5/2m4GJ/Yt++w5M+fM7Z3w/ARbHwwHM6fvyDp0hXySZvKsWuqz24iSVJ6d5174/J1Wdtktk8eF28SryIePcHLmDt3jtjeDcOIMyA4Wp1GwzAMIzhExGfJkkk3wzDujdM9PXiNWsMwDMNIiFgFdsMwDCNBYfW0DMMwIjRq2uEyDMPGB8PwEkePHpVXXnlFMmbMKClSpJBHH31Ufv755yBR9QMGDJBs2bLp89WrV5c///zTp38fEx4NwzAMwzAMwzAMwzCMeB18EBtbRDhz5oyUL19ea2KvXLlSdu/eLR9++KHcd9997te8//77MmbMGJk4caJs3rxZUqVKJTVr1tReDr5KvE21NgzDMAzDMAzDMAzDMIy4wPDhwyVnzpwyffp092N58uQJEu04atQo6devn9StW1cfmzlzpmTJkkUWL14sjRo1El/EIh4NwzAMwzAMwzAMwzCMeIu/+MXK5jS48dyuXbsmIbF06VIpWbKkNGjQQDJnzizFihWTKVOmuJ8/ePCgHD9+XNOrHWicU6ZMGfnxxx/FVzHh0TAMw0hQ4Ck0DMMwwj1q2qEyDMPGB8OIAjlz5lSB0NmGDRsW4usOHDggEyZMkIceekhWrVol7du3ly5dusinn36qzyM6AhGOnvC385wvYqnWhmEYhmEYhmEYhmEYRrzF38+1efsz4fDhw5I2bVpxSJYsmYREQECARjy+++67+jcRj7/99pvWc3zttdckrmIRj4ZhGIZhGIZhGIZhGIYRA6RNmzbIFprwSKfqIkWKBHmscOHCcujQIb2fNWtWvT1x4kSQ1/C385wvYsKjYRiGYRiGYRiGYRiGYcQi5cuXlz179gR5bO/evZIrVy53oxkExnXr1rmfp2Yk3a2feOIJ8VUs1dowDMMwDMMwDMMwDMOIt/j5+enm7c+MCN27d5dy5cppqvVLL70kP/30k0yePFk35/26desmQ4cO1TqQCJH9+/eX7NmzS7169SReRTxeuHBBvyyqa4oUKfTAbNmyJUjh/gEDBmiYKM/TcefPP/8M8h503Hn88ccld+7c8sknnwR5bsOGDVKtWjXJkCGDpEyZUg8o+ezXr1+P7Pc0DMMwDMXbBodh3AuzqwzfxsZMwzBsfDAMb1CqVCn58ssvZe7cufLII4/IkCFDZNSoUdKkSRP3a3r16iWdO3eWNm3a6OsvXrwoX3/9tSRPnjx+CY+tWrWSNWvWyGeffSY7d+6UGjVqqLh49OhRff7999+XMWPGaAFMQj5TpUolNWvWlKtXr7rfo2XLlqrMzpkzRzv6UGwTdu/eLU8//bQW1Ny4caO+/9ixYyVp0qRy69at6PrehmEYhmEYPoHZVYZhGIZhGDGLv59frGwRpU6dOqqDoZ/9/vvv0rp167uCKAYPHqxdrHnN2rVrpUCBAuLLRDjV+sqVK7Jw4UJZsmSJVKpUSR8bOHCgfPXVV9r221Fk+/XrJ3Xr1tXnZ86cqe29Fy9eLI0aNdLHLl26JMWLF5fMmTPLfffdp95+WL16teasI1465MuXT8VIwwgPXNv+3m5XZfj4+WDlbI3YS7EwfJnYPxfMrjJ8HbOpDDsfDBsfDMOIChFejd+8eVMjD4OHcZJS/d1338nBgwdVeSUC0iFdunRSpkwZTa92IBWb7jw8V7ZsWXfnHkTHY8eOabSjYRiGYRhGfMbsKsMwDMMwDCM+E+GIxzRp0mi3HCIbEQ6JZCT/HFExf/78KjoCj3vC385zTqo10Y/UbSTi0aFBgwayatUqqVy5soqQiJJPPvmkNG3aVNuOG0Z4CAy042QYRmjjgw0Qhu9gdpXh69iQaRiGjQ9GfCCyqc9R/Uwjkl2tqe3YokULeeCBByRRokSaMt24cWPZunVrhN6H2o9snvB+06dP1y4969ev1xqRdPQZPny4dvShYU1oi8h9+w5J6tRB3y+010YF17kT9RPI9iVmjsutWwHy77+no6UZkf1Gcf+4XLt2XS5cuCQXLlyM9X0JD7YvMXtcLl26oufEmTPnIv0e9hvFn+Pyzz8no+0zo4Kv2lV//vm3266Knt83MFpELNsX7x6Xo0dPys2bNyL0LvYbxd/j4jofbvrEvgTF9iU2jgvnw61bzvlwL+w3is/H5eLFS653MG+VEV3CIzUX6TxNncbz58+r0dqwYUPJmzevRinCiRMnghiz/E0X6/CC8f3qq6/qRnQlxTJpVjNo0KC7XuvUhyxRokZkvo5hGIZhGAkY7AhKv8QWvmpXlSxZM1q+n2EYhmEYCYPYtqnCwiIe45jwGNyzfubMGU2PpiFMnjx51Ehet26d2yDGiMbD3r59+0h9DqnYGNsY5CGRPXt27YpNupI1DTAMwzAMIzzglcdAxo7wBcyuMgzDMAwjLuJrNpURD4RHREZOrIIFC8q+ffvkjTfekEKFCknz5s1V+OvWrZum9Dz00EMqRPbv319PwHr16t3zvSdNmiTbt2+X559/XiMAaA9OV+xdu3bJ2LFjQ/w3dKzNkSNHZL6KYRiGYRgJGF/wyptdZRiGYRhGXMcXbCojHgmP586dkz59+siRI0ckQ4YMUr9+fXnnnXckSZIk+nyvXr00OrFNmzZy9uxZqVChgnz99dd3dcIOidKlS2t37Hbt2sk///wjqVOnlocfflgWL16sDWcMwzAMwzDiE2ZXGYZhGIZhxCx+t//zJt7+PF/FL9CqfxqGYRiGYRiGYRiGYRjxDEr/EY35/IIWkiRlUq9+9o3L1+XLBtPUyZw2bVpJqESpxqNhGIZhGIZhGIZhGIZh+DLWXCb28I/FzzYMwzAMwzAMwzAMwzAMI57ic8IjDWSyZMkiiRIl0kY11JL05Pjx41K0aFH388mSJZOXX345yGuoK/noo49q0xle88ADD8hvv/0W5DVvvfWWJE2aVLcBAwZ45bsZ4YNuWDQoypUrl6RIkULKlSsnW7ZscT9PdQB+Mzqd83z16tXlzz//DPIeP/74o3ZVz507t3zyySfux8uWLav1Qz2ZOHGiniczZswI8nizZs2kYsWK9rPFQcaNG6e/PXVly5QpIz/99JP7uT179kj58uW1IRVNsIy4S0yOFcC4ENI2b948r31H496Y3WDHxggbs6uMqGA2VcLAbCrDwewqI0EIj2fOnNFu2K+//nqIz1etWlV+//13+fDDD+Xbb7+VBg0ayNy5c1VIdEBU4DUffPCBfPbZZ5rTz4LUgb+HDx+uosPgwYPl3XfflYsXL3rl+xn3plWrVrJmzRr97Xbu3Ck1atRQweDo0aP6/Pvvvy9jxoxRwXDz5s2SKlUqqVmzpnZAd2jZsqV2U58zZ44MGzZMDh8+7D5//ve//wX5vG+++UZy5sx51+P8Xa1aNfvJ4hjz58+XHj16yNtvvy3btm2Txx57TM+PkydP6vOdOnWSV155RZYsWaLbDz/8ENu7bPjgWOEwffp0OXbsWJCtXr169pv5EGY32LExwsbsKiOymE2VcDCbykgIdpW/+LnTrb22WXMZF4E+DLvXu3fvII8lS5YssFq1akEeS5EiRWD58uX1/t9//63/rkePHu7nly9fro9NmTJF/z58+HBgokSJAv/44w/dEidOHHj06FGvfCcjbC5fvqy/zbJly4I8Xrx48cC33norMCAgIDBr1qyBH3zwgfu5s2fP6nkxd+5c92MPPvhg4IEDBwIvXrwYWLJkycBdu3bp46tWrdJz4dixY+7XZsmSJXDcuHGBuXLlcj/Gv+V133zzjf1kcYzSpUsHduzY0f33rVu3ArNnzx44bNgw/btEiRKBmzdvDrx+/Xrgc889p+ODEfeI6bECGAO+/PJLL30jIzowu8GOjREUs6uMqGA2VcLAbCojvttV586d089v8EWrwJdXdvDqxmeKiO5DQsbnIh7vRZ48eWTTpk3y888/S0BAgHz00Udy5coVadiwoT6/YMECve3SpYv739SqVUtTs5ctW6Z/k2JJCm2hQoV0e+qppyR79uyx9I0MT27evCm3bt3SFFlPSJP87rvv5ODBg5puT1STAx2qSKclZdKB9MrChQvrc6RXFylSxO19SZIkiUY5wu7du/X8Ierpv//+0/cHnmcfnnjiCfuB4hDXr1+XrVu3Bjk/KLnA3875gVeNv1OmTKnPEQFnxD1ieqww4g9mN9ixSciYXWVEFrOpEg5mUxkJxa6iZJK3Ix75TCMOdrUmXa5YsWJSqlQp92OtW7eWzp076/0DBw7oLTW/PGFxSoqcA8LSoUOHJHHixCY6+hBp0qRRsW/IkCEqBlDvk9BthIL8+fOrkAA87gl/O88BQmKjRo3UaLrvvvvcj5NqWbp0aU2jbty4sd5WqFBBa4US/s3fDKbcsh88bsQdTp06pWJUSOfHH3/84Z74/v33Xw3xz5QpUyztqeHrY4UD4wSGkic4LB588EH7EeMIZjfYsUnImF1lRBazqRIOZlMZEcHsKiMyxLmIRxrJUIOrX79+qqa/+OKLMmXKFK3lFVFYOFqko+9BHQgiu2kKhPBHjTYW/0SnRQRExpCEhCpVqrjrOXLL31C5cuUgj1O/woifcF6Z6Bj3iemxAkaOHCnbt28Pstm8Ebcwu8GOTULH7CojJjGbKn5gNpWREOwqgg9jYzPimPB4+vRpWb58ufTt21ejXDjJOdkLFCjgPtHz5s2rt3///XeQf0szATqbGr5Pvnz5ZMOGDVpglkGNjsQ3btzQ3zZr1qz6mhMnTgT5N/ztPHcvEBT37t2rDSgQGBEcPYXH/fv36+daY5m4x/3336/RaVE5P4y4Q0yPFcBriaD03IiUN+IGZjfYsTHMrjIih9lUCQuzqYzwYHaVkSCEx8uXL+tt8GgW/nbVPhXtqgQff/yx+/mVK1dq+mWdOnW8ur9G1CAKCbGYzlqrVq2SunXraho0QsC6devcryNllpDv8NZjJKU6adKkMn78eBWkS5QooY+Tvk8K7rRp09wp2Ubcgt+V39Pz/KD2CH9bvc74S0yNFUbcx+wGOzbGHcyuMiKC2VQJE7OpjLAwu8qILD4XtkHtLSJYHGjDPn/+fA3DZbFIAwDaradNm1aKFy8uM2fO1Npt1OgCXkdzANLjWIhmzpxZ2rdvL6lTp5ZWrVrF4jczwgvCAUJywYIFZd++ffLGG29o0dnmzZtrcdZu3brJ0KFD5aGHHlJxoX///hqiXa9evXC9P80naCIxduxYbTbj1G/DwPJ8nCY0RtyjR48e8tprr0nJkiVVPB41apRcunRJzx8jfhHTYwWcPXs2SE1IpxYShrnhG5jdYMfGCBuzq4zIYjZVwsFsKiMh2FVOwxdvf6ZBX28fY+TIkdpuPPiWL18+fX7Hjh2B+fPnD/T399fHkyZNGvjcc88F3rp1y/0eZ86cCXzkkUcC/fz89DXZsmXTf2fEDebPnx+YN29e/W2zZs0a2LFjx8CzZ8+6nw8ICAjs379/YJYsWQKTJUsW+OSTTwbu2bMnQp/x9ttv67nx3nvvBXl84MCB+viwYcOi7fsY3mfs2LGBDz74oJ5DpUuXDty0aZP9DPGQmB4rQpqLbHzwPcxusGNjhI3ZVUZUMJsqYWA2lRGf7apz587pfjT+sk3ga6s7eXXjM0VE9yEh48f/TIE1DMMwDMMwDMMwDMMw4hOUWyJSs8nitpI0VVKvfvb1S9dldr1Jcu7cOY0STajEqRqPhmEYhmEYhmEYhmEYhmHEDUx4NAzDMAzDMAzDMAzDMAwj/jeXMQzDMAzDMAzDMAzDMIzogjYvfvp/72GtZVxYxKNhGIZhGIZhGIZhGIZhGNGORTwahmEYhmEYhmEYhmEY8RZ/Pz/dvP2ZhkU8GoZhGIZhGIZhGIZhGIYRA1iqtWEYhmEYhmEYhmEYhmEY0Y6lWhuGYRiGYRiGYRiGYRjxFku1jj0s4tEwDMMwDMMwDMMwDMMwjGjHIh4NwzAMwzAMwzAMwzCMeItFPMYeFvFoGIZhGIZhGIZhGIZhGEa0YxGPhmEYhmEYhmEYhmEYRrzFz89PN29/pmERj4ZhGIZhGIZhGIZhGIZhxACWam0YhmEYhmEYhmEYhmEYRrRjqdaGYRiGYRiGYRiGYRhGvMXfz7V5+zMNi3g0DMMwDMMwDMMwDMMwDCMGsIhHwzAMwzAMwzAMwzAMI97iL366efszDYt4NAzDMAzDMAzDMAzDMAwjBrDmMoZhGIZhGIZhGIZhGIZhRDuWam0YhmEYhmEYhmEYhmHEW/z8/MTfz8/rn2lYxKNhGIZhGIZhGIZhGIZhGDGARTwahmEYhmEYhmEYhmEY8RaiD70dgWgRjy6sxqNhGIZhGIZhGIZhGIZhGNGOCY+GYRiGYRiGYRiGYRiGYUQ7lmptGIZhGIZhGIZhGIZhxFv8Y6G5jLc/z1exiEfDMAzDMAzDMAzDMAzDMKIdi3g0DMMwDMMwDMMwDMMw4i0W8Rh7WMSjYRiGYRiGYRiGYRiGYRjRjgmPhmEYhmEYhmEYhmEYhmFEO5ZqbRiGYRiGYRiGYRiGYcRb/Pz8dPP2Z8Z1Tp06JZs3b5Zbt25JqVKlJFu2bBF+DxMeDcMwDMMwDMMwDMMwDMNws3DhQmnZsqUUKFBAbty4IXv27JFx48ZJ8+bNJSKY8GgYhmEYhmEYhmEYhmHEW6y5zL25ePGipE6d2v33oEGD5KefflLhEZYvXy6tW7eOsPBoNR4NwzAMwzAMwzAMwzAMIwFTokQJWbJkifvvxIkTy8mTJ91/nzhxQpImTRrh97WIR8MwDMMwDMMwDMMwDCPe4h8LkXdxLdJv1apV0rFjR5kxY4amVI8ePVoaNmyo9R1v3rwp/v7++lxEMeHRMAzDMAzDMAzDMAzDMBIwuXPn1nTquXPnSuXKlaVLly6yb98+3RAfCxUqJMmTJ4/3AqxhGIZhGIZhGIZhGIZhGDFA48aNZcuWLbJjxw6pUqWKBAQEyOOPPx4p0REs4tEwDMMwDMMwDMMwDMOIt/j5+enm7c+Ma6xYsUJ+//13eeyxx2Tq1KmyYcMGadKkiTzzzDMyePBgSZEiRYTf0yIeDcMwDMMwDMMwDMMwDCMB07NnT+1YTbRj27ZtZciQIZpyvW3bNo12LFasmKxcuTLC7+sXGBgYGCN7bBiGYRiGYRiGYRiGYRixxPnz5yVdunTyxrrXJVmqZF797GuXrskHT46Qc+fOSdq0acXXyZgxo6xevVq7W58+fVrKli0re/fudT+/e/duFSS//fbbCL2vRTwahmEYhmEYhmEYhmEYRgImVapUcvDgQb1/+PDhu2o6FilSJMKiI5jwaBiGYRiGYRiGYRiGYRgJmGHDhknTpk0le/bsmmJNqnV0YM1lDMMwDMMwDMMwDMMwjHgLUXf+Xu71Etci/Zo0aSJPP/20HDhwQB566CFJnz59tLyvCY+GYRiGYRiGYRiGYRiGkcDJmDGjbtGJCY+GYRiGYRiGYRiGYRhGvMXv9n/e/kwj7kV+GoZhGIZhGIZhGIZhGIYRBzDh0TAMwzAMwzAMwzAMwzCMaMdSrQ3DMAzDMAzDMAzDMIx4i5+fn/j7eTnV2suf56tYxKNhGIZhGIZhGIZhGIZhGNGORTwahmEYhmEYhmEYhmEY8RZ/P9fm7c80LOLRMAzDMAzDMAzDMAzDMIwYwCIeDcMwDMMwDMMwDMMwjHiL3+3/vP2ZhkU8GoZhGIZhGIZhGIZhGIYRA1hzGcMwDMMwDMMwDMMwDMMwoh1LtTYMwzAMwzAMwzAMwzDiLf5+frp5+zMNi3g0DMMwDMMwDMMwDMMwDCMGsIhHwzAMwzAMwzAMwzAMI97i7+favP2ZhkU8GoZhGIZhGIZhGIZhGIYRA1hzGcMwDMMwDMMwDMMwDMMwoh1LtTYMwzAMwzAMwzAMwzDiLfR58fNysxfrLePCIh4NwzAMwzAMwzAMwzAMw4h2LOLRMAzDMAzDMAzDMAzDiLf4i59u3v5MwyIeDcMwDMMwDMMwDMMwDMOIASzV2jAMwzAMwzAMwzAMwzCMaMeER8MwDMMwDMMwDMPNX3/9pU0YRowYYUfFMIx4gb9f7GyGCY+GYRiGYRiGYRiGYRiGYcQA1lzGMAzDMAzDMAzDMAzDiLcQxc3m7c80LOLRMIx4wqVLl2J7FwzDMAzDMOI0AQEBcvXq1djeDcMwDCMeYTUeDcPwSY4ePSotW7aU7NmzS7JkySRPnjzSvn17uX79usyYMUO9Rxs2bJAOHTpI5syZJUeOHO5/O378eHn44Yf13/HvO3bsKGfPng3y/lWqVJFHHnlEtm7dKuXKlZMUKVLoZ0ycOPGufRk7dqy+X8qUKeW+++6TkiVLypw5c7xyHAzDMAzDMCJKs2bNJHfu3Hc9PnDgwCARONzv1KmTzJ492207ff3110H+zciRIyVXrlxqK1WuXFl+++23IM//+uuv+nl58+aV5MmTS9asWaVFixby33//hfjZ+/bt09enT59e0qVLJ82bN5fLly/bj2wYRoziL36xshmWam0Yhg/yzz//SOnSpVUsbNOmjRQqVEiFyC+++CKIYYromClTJhkwYIA74hGjdtCgQVK9enUVKvfs2SMTJkyQLVu2yPfffy9JkiRx//szZ85IrVq15KWXXpLGjRvL559/rv8madKkajDDlClTpEuXLvLiiy9K165dNQoAA3vz5s3y8ssvx8LRMQzDMAzDiD7Wr1+vNhAC5P333x9EsJw5c6ZcuHBBnbjYQKNHj5Zq1arJzp07JUuWLPqaNWvWyIEDB1RARHTctWuXTJ48WW83bdp0V6ohdhfO3mHDhsm2bdtk6tSp6kQePny4/ayGYRjxEKvxaBiGz9GnTx85fvy4intEFzoMHjxYAgMD3X9nyJBB1q1bJ4kSJdK///33XzVia9SoIStXrhR/f1dQN8IlxvSsWbPUKPYUOD/88EPp0aOH/t22bVspU6aMfv6rr76qIuXy5cs1AmDBggVePAKGYRiGYRjeASctQmKRIkWCdLUGohP//PNPeeCBB/Tvp59+Wm0lRMKPPvrI7Qju2bNnkPcsW7asOnW/++47qVixYpDnihUrJp988on7byIj+duER8MwjPiJpVobhuFztYUWL14szz77bBDR0cHTa966dWu36Ahr167VVOxu3bq5RUfndWnTplUR0ZPEiROr2OhApCN/nzx5UlOwgTSgI0eOaMSkYRiGYRhGfIP0aU/R0ZN69eq5RUcgIwXhccWKFe7HSMF2ICry1KlTKjwCEY3BadeuXZC/ESYRH8+fPx8t38cwDCMkWEb6e3mz3jIuTHg0DMOnIGoRw5P6i/eCNB1P/v77b70tWLBgkMcRFKk75DzvQP3HVKlSBXmsQIECQTz9b775pqROnVoN7YceekhTjUjZNgzDMAzDiA8Et6c8wfYJDraSYyfB6dOntRwNqdeIkJTBcd7z3Llzd/37Bx98MMjf1M92SuAYhmEY8Q8THg3DiLN4ethjisKFC2sK0rx586RChQqycOFCvX377bdj/LMNwzAMwzAiQ/C6ig63bt2KdnuKmo3UxCaScdGiRbJ69Wp3gxoyWYLjma3iiWc5HcMwjJgYF2NjM0x4NAzDx8BLTlp08I6J4YGOi4BQ6Anp1wcPHnQ/71nj0WlK47B371699SysTlRkw4YNZfr06XLo0CGpXbu2vPPOO5pOZBiGYRiG4WsQRUiTvuAEz/64F9R3DA62kmMnEaVIve3evXtrc7/nn39ennrqKc00MQzDMAywiEfDMHwKajNST+irr76Sn3/+OULecDpZk1Y9ZsyYIK+jYDmpPgiGnty8eVMmTZoURKDkb8TPEiVK6GPUHPKE96cOEu9/48aNKH1XwzAMwzCMmCBfvnxq+/z666/ux44dOyZffvllhN6HuttHjx51//3TTz9p879nnnkmSPRicPts1KhRUfwGhmEYRnzBulobhuFzvPvuu5qmQ7HzNm3aaLozxjKdpemOGBoIhnSkxuNO18XnnntOox/Hjx8vpUqVkldeeeWuGo90UKROEfWK5s+fL9u3b5fJkydrR2ugQ3bWrFmlfPnyWrvo999/l48//lhFzDRp0sT4sTAMwzAMw4gojRo10jrVRCB26dJFLl++LBMmTFB7J6SGL6GRP39+LTHTvn17uXbtmgqKGTNmlF69eunzZKlUqlRJ3n//fXXI0ogGG45ME8MwDF/C389PN29/pmHCo2EYPghGK970/v37y+zZs7XZDI/hXU+ZMmWY/3bgwIEqQCIOdu/eXTJkyKDiJWKmIyZ6piF9+umn0rlzZ61NhLDIv6MLtgNdrtmHjz76SC5evCg5cuRQA75fv34x9v0NwzAMwzCiAuIg0Y09evRQkZBmL8OGDdPU6YgIj02bNtVsFATHkydParM9bKVs2bK5XzNnzhy1pcaNG6eRjzhtV65cqQ5ewzAMw/ALtCq+hmEkQKpUqSKnTp2KVC1JwzAMwzAMwzAMw/chiCVdunTy0Y/9JUXq5F797CsXr0qPJ4Zo6QsixBMqVuPRMAzDMAzDMAzDMAzDMIxox4RHwzAMwzAMwzAMwzAMwzBiX3i8cOGCdOvWTXLlyiUpUqSQcuXKyZYtW9zPk7k9YMAArfvB83SZpZaIJz/++KM8/vjjkjt3bu0264mfn58kT55c/v777yCP0+W2WbNmEf+GhmEYhmEYPojZVIZhGIZhGN4BrSk2NiMSwmOrVq1kzZo18tlnn8nOnTu1eDDi4tGjR/V5OpqNGTNGJk6cqM0hUqVKJTVr1pSrV6+636Nly5baNIJCxBQ5Pnz4cJDP4MdBvDQMw4gp/ve//1l9R8MwYhWzqQzDMAzDMIz4ToSExytXrsjChQtVXKxUqZLkz59fO8hyO2HCBI12pOMZ3V7r1q0rRYsWlZkzZ8o///wjixcvdr/PpUuXpHjx4vLYY49pV1k8/p506tRJZs2aZaKAYRiGYRjxErOpDMMwDMMwvIe/n1+sbEYEhcebN2/KrVu3NBXaE1Kqv/vuOzl48KAcP35cIyAd6B5UpkwZTa92IJqxcOHC+lzZsmWlSJEiQd6vfPnyUqdOHendu7f9RoZhGIZhxDvMpjIMwzAMwzASAokj8uI0adLIE088IUOGDFHhMEuWLDJ37lwVFYl6RHQEHveEv53nnFTrRo0ayfXr1zXiMSRIwSZi8ttvv5WKFSuGuV8BAQEaVcn+WQ69YRiGYRjhgUwNsi6yZ88u/v7e7bfnqzYVmF1lGIZhGEZcsamMeCY8ArUdW7RoIQ888IAkSpRIU6YbN24sW7dujdD7UPuRLTSIgmzatKlGPX7//fdhvheiY86cOSP0+YZhGIZhGECt6Rw5cnj9YPiiTQVmVxmGYRiGEZdsqvDg7+favP2ZRiSEx3z58smGDRu0TuP58+e1e3XDhg0lb968kjVrVn3NiRMn9HEH/qaLdUQZNGiQFChQIEh9yNCiBuDw4Z8lbdrU9rsmcG7evCVHjpyQ3Lmzx/auGD7AlSvX5PTpc/LAA5lje1cMH+D8+Uty7dp1yZQp5MgwI2Hx999HpWjRJ912hLfxRZsKzK4yPNm//6jky/eAHRTDzgfjLmx8MBzOn78oOXOWjDWbyohnwmNw7/qZM2dk1apV2nAmT548aiivW7fObRRjSNPdun379hH+DKIYaTTTt29fNc5Dw0mvRnRMm9ZO9IQOwmOaNJfsXDCUJEmSyo0bt+x8MG7jp2K0zRUGpEnjclbGdpkWX7KpwOwqw5M0aVLamGl4nA+p7HwwbHww7mlD+CJ+t//z9mcaEWwuAxjEX3/9tTaSWbNmjVStWlUKFSokzZs315OsW7duMnToUFm6dKns3LlTU3vI869Xr16kjnefPn005Wft2rX2exmGYRiGEW8wm8owDMMwDMOI70RYeDx37px07NhRxUZExQoVKqjhnCRJEn2+V69e0rlzZ2nTpo2UKlVKLl68qEJl8E7Y4SVDhgzy5ptvytWrVyP17w3DMAzDMHwRs6kMwzAMwzC8W+PR25sh4hdI+6E4DqlH6dKlk3Pn/rDQf0NTrQ8fPi558lg9IsNV4/G//85KjhxBO8MaCbf+DOdEliwZY3tXDB/gr7+OSJ48ZVQATJs2bWzvjs9gdpXhyb59hyR//gftoBi3z4fDkj+/NfU0bHwwgtsOFyRdukI+aVM5ds34LQMlRerIBcRFlisXr0qHUgN98rh4E+tzbhiGYRiGYRiGYRiGYRhGtGPCo2EYhpGg8OWi14ZhGL6HjZmGYdj4YMR9/P38YmWLCu+99567l4oDZQgpf5gxY0ZJnTq11K9fX06cOCG+jAmPhpHAuXDholy6dEWuXbuuaerxoPqCYRiGYRiG17ly5apcvHhJb69fvyEBAQH2KxiGYRiRYsuWLTJp0iQpWrRokMe7d+8uX331lSxYsEA2bNigzZhfeOEF8WUSx/YOGEZ0g1PBPxJVXDEOz569IKdPn9GagP/9d0ZOnz4rly9fEX9/f0mcOLEkTpzo9pbY4zbo44kSJZIkSRKrgEc9ucqVy+pz/H3jxg19De8Xk5w8+Z98/vky2bfvL92HPHlyyoMPZpcHHsgq2bJllmzZskjatKll4MCRsmPH75I8eVK5deuWXL16Xfbv/ztSn1m0aCGZP39cjH+3yJ0PvrVPRuyBx9AiHg2PM8IOhmHcg8jYVNg8ODWD21TYWZAkSVCbCTuJ+zzG33fuux5nO3v2vDz8cAHJmjWTvgd2S0BAoL4+JsE+XLhwpfz66+9y6NA/kiXL/ZI374OSPXsW3bCrsmTJJBs2bJL33hsv992XTh25N2/elCNHjsulS5cj9blffz1T7bf4cD4Y8Rc7H4y4hN/t/7z9mZGBJs1NmjSRKVOmyNChQ92PUyvyk08+kTlz5ki1atX0senTp0vhwoVl06ZNUrZsWfFFTHg04j0Yv3iff/31DzUYT506LRkypJf7779PMmbMIAMGfCjHjp3QzuwFCuTR59gyZrxPbzNnzii3bgWogXvjxk2NDLx8+aoalPzN4677t/T+p59+EeTzU6ZMoUYpYBwj7mXKdJ8ULvyQlC1bTJ58srz7tbzfhQuXNArR2bJnzyq5ct1plIMxO3bsDLnvvrT6vjyfPXtm3VcElUWLvpY+fYYH2Yfvv//5ruOSO3cOqV27mixdOlX/3Z49B+S551qGehxTp04l6dKl1gZObNxPkya1Ps535vhWrPiiJE2aVJImTeJxm0TefLO9PP54kSj9joZhGIZhxC5OVsT27bvl6NHj2qAJOwebKlOmDLJu3Q+ycOEKFQQR5xDpEOKwqTJmdNleOARdwpzLfrp27VqQv+/c3tT3O3z4nyD7kC9fLr1NlMhf9wdRslChfGpXNWhQW1KlSuEWDHEe44Blw6aCUqUeC/J+y5evl7//PnpbSHQ5Z9lv7JeLFy9LiRK173lcHnoot35HHLDYY1CwYNVQX897p0uX1m1XpUuXRm2qNGlSyZ9/HpSfftohtWo102OaLJnLnnLdJpWKFUtLx45NI/zbGYZhGLHb4MaTZMmS6RYapFLXrl1bqlevHkR43Lp1qwYz8bhDoUKF5MEHH5Qff/zRhEfDiGkmT54r33zzg5w48Z8Kg2nTphQ/P3+tgXD8+L9BXovx1qJFQzl1aosaqLxe5KrkyJFN3nuvd5DXYtSGN0JqxowFUqzYwypWPvBANsmRI6u+55kzZ+XEiVO6H2y7du2Vw4ePye+//ymjR09T0c8B73bu3DklbdpUaoRu2rRNxcktW35Vgz1r1syyZs23cuzYSalQoaRkyHCfCqenT59TYz5z5vulRo2Ksnr1t0H2bdy4IZr6g3H9xBPFpUSJR4M8X7BgXtmz5xv33999t0Vatuzl/hvxlu3o0dDrR5w6dSbI3ylTJpdFiyarMb5z5x491o5hTfTDN9/8KJs2/aL7zcLFcytT5nEpWTJoWLlhRAdWTsAwDCNsEBbHjJmuNsuZMxfkypXLGmlI+jCCY3C6dWupEYH//HPytk0lsnv3n7Jo0aQgNlREbCoEOOwlnKwIewh6jz5aSG2ZEyewp07p7cGDh+V//9ukn7d37wGNTnRAnHziiRKa5YH9wfthA2F/YSNmy5ZJjh37V7799icVHhH1/vnnhL4vzuD06dNKrVpVZcWKO/YRtGv3ihQunF/Onj2nDuPWrRvftf+eNhUCaLFitdx/cxz//fc/3UID4RTbMbgth330xx/79ThiT7HxXbAX16//Qe1B7C02x6bCLm3Y8FmL+DeiHavQZBjhI2fOoBHsb7/9tgwcODDE186bN0+2bdumqdbBOX78uDqh0qd3ObkcsmTJos/5KhbxaMQ5MFp/+22vGolsGKCIaNu371JRjFQcLkQEttDA4Fu58n/y11+HNfJv69blkjp1SvWIb968XebNWxrEyPzllxVquIVFz55DZNmy9aE+j51do0Yl2bNnv7zwwjOaCo2hiqcDw3Lu3CXyyy+71IAuUCCvvP9+X/13K1asl+vXb8qrr9aXc+fOq+BIZCaLAaIJiFp0IOLy339Pq9Fcq1Y1eeqpipq+FBkw8gcM6CL58uXWSE3XlkTfz3XrSoGqVOklff0jjxSUp5+urCndiKQY/nXrPiUDBnyk+8134rfCQCd0PFWqVFKpUmlp1qyBXL9+XdPDEWDnzl2qkQssDAzDMAzDiFmYfzdu3CwbN/6kwh2OyFSpUsrWrTvl6tVrkiFDBp2/sU9C48cft8nmzb/o/SVLpuo8jnCHzbNhw2bN1OBvmDp1uAp8YcG/adPmjiP4p5+23/UanKzYfk8+WUH3F1sQUe7pp6vIqlUb5IsvVmjGCo7UP/5Yr6IbtuHKld9Iv35d1JY5fvyk2lX8OyIiu3ZtoRGU4JTMwabCvsHOoWRNZGCROGRIT03JRhB0UsqdW8fG6tFjiB537jdr9qLaedh2I0ZMVsc2tusHH0yWAgVyaxkZHMLYVRxbnLXYfQisZPfw3TgGpLe3bPmSiY6GYSR4tASXl6tFOL62w4cPS9q0ad2PhxbtyOu6du0qa9askeTJk0t8wS8wHoR+ELaaLl06OXfuD01XMOIvw4dPUK/2gQOH3I/9+ONi2bnzd9m0abts2bJDAgJuSeLESWXHjl3R9rkhGcmkXCMKkmrcqdOAIM/hfeZxDElqHOXMmV2KFSuiBvDMmQtlxIi31PuN9zm+gZH7zjtjpWzZ4lKpUhk9bkQttGvnElJDgwUE0Zv16z+j9SKjCxZNp0+fl+zZXTWhYpIzZ85phAILMCIvWCSwUCHNbOrUefLss9Xln3+Oq9D84IMPqBiL4G14DxZoV65ck8yZM9zztVyjLPhYxBnxk7/+Oip58pTWejmexmBCx+yqhAE20zvvfCy//77P/djMmSNVGMMJi5D499//qANy3bqgWRRRoVSpojJr1ui7HqcsDI5KMlg89wkQ/IheZE7HEcz8SkYJgiYZLEQu4tx16j/GF3Am16nTXL8rzlrsKoRhz+jJkMC+wEmNDUbEJqna0cWBA0ckb94cEtO4Gh9eU9uKkj5Eu2JT5c+fW8VjMnxSpEimGUTYUoUK5dcUeavj7F327z8i+fLd+3yghALXN1lQRvzk/PkLki5dIZ+0qRy7ZvLWwZIytXfFvMsXr0qbEgPCfVwWL14szz//vNsJBqxHGNtwOK1atUrTrM+cORMk6jFXrlza+ZrGM76ICY9GnCJ4vZyhQ1/Xej6enDlzXtav/1H27t2ndQcRGho1elbWrftefvhhq76mevUKKgKSmu2AUfbFFxO1nmLy5Hc8EAhJiIwYu3i+a9R4xW04E9nngLcdbzaFzzGAn376NU3VwWDH68y/rVatnEyY8I7EZzhOFJrGu+8ZYTps2DiZM2fJXa+n/mPRooWlZMlHY2x/oiI8EglC+hi/5cyZX2qULIZ85cou45+UJsTkl1+uKz173qm/ERyiJagVRUQoi6fFi1fruQk7d64KcrwM7wmPXN+k+xMFQ/rgkSPH9NaJIOFvSh9wThMd3bdvR3UkGPEDEx5DxoTHhMEzz7wWxJEL27evlBQpkgcRC775ZpMcPHhIhUjmc+oSUmdx0qQ5GhVIyjHz+Pz5XwV5r/79u8hzzz11OxXYFfLhNNqj3jXzc4cO/WTnzj+kfPmSd9WjxsZDZOL9J0+eI+PGzdQ5lJAJ6j7i1MNuo6xNfIXjxXxEqrgn2LcNGrS/6/VEbGKDctw9F63RSVSER84nolfJ2iGQgMhUmDTpXX2sTp3q8sILbaRRo+c0ypPFdkiUKVNMbSlSyBEgcfhyHsH06SOkXLkSUfiGRlSER5pUkpnm2FM0WKKkAL/Xn3/+pU4EAjMQIBs3fk6d8kb8IC4Ij1O3DYkV4bFV8f7hPi4XLlyQv/8O2uy1efPmWsfxzTff1JTtTJkyydy5c6V+/fr6/J49e/R5X67xaMKjEWtUr95EDUfEGxb0LOYzZcKAcG14LoNHgyHy/PffaWncuLNbtAkOxu3SpdM0DeWPP/ZpbcE1a77T+8Fr5VAzEVGR96KwNx54PMR9+74fpEZQSFBnB6MOQaJkycfk77+PqECFdxrDHMOaWx6n8Uy7dk00fTihemI5FhMmfCZLlqxWI5EUawTgyKaCe0t4XLJkjfTr94EuqugSTio/3qYmTerKzz/vVEGZ8whDivt0r3SMLIcHHsgi6dOn01pRCJhEZhOtUbz4I9p05/777x19Z0QPXOtOgycnooLu7tT7YgFOjVXOS8Yjzk3GHCJoMJinT18gvXt30DHi3XfHydKla6RLl+Z6jbNYKl36sQR7fcdVTHgMGRMe4x7Llq1T5xdjV86c2TRF17GnsK0Y24KnCWP/kEaMoPj22yNDfe+BA3tK48Z11Hn2ww8/y9q132lUPyJCcPgcUrJxxjZpUk969mytolCzZj3D3P9XX31eKlcuq2PyY48V1sd27PhdRQzKsVByBrvKaRbYsGEddTzfqwxOfAaH+vTpn+s4hoDD5jS2iUmiIjwiLr7ySje1zXAA/v77fnUAkibPuUOAAGniLVs20nJKRDAyP2NHe9pVRHRiUxERSRkAIiGxq9gQxbHTDO8Q/HwgOvXrrzdo+STsqKpVn1B7lwAP7GSaKlEDnuub8wAHBQJ0ly4D9T7lGQjiQDxPyNd3XMSEx+gRHkOiSpUq8vjjj8uoUaP07/bt28uKFStkxowZ+p6dO3fWx3/44U5Qla9hwqMRayAE9u493J1Og8Hh2bUPA2PgwO4hei3xABOxiFfUszELBi71c959d7y0aPGiikZMep6vCQnq6BB55xgqCxYsl6++WqcGefBuihRKxwNPAW+ERiZOxChqIj72WBEtgo4nj+/ALaLUQw/lkYQK3m0EmlmzvlSBmWONiOctoiPVmjSeDz6YpKIikYvUWAoemUFq/c8/f6XF3T//fLnWykKDKlgwn8yY8aEumDhPOB8sutF3hMfgi3DKAjAmYRy7Ota7uqtyn3GnePFHVYgm2oI0RZoRcJ3TgZSaZnQ09YyYNnwbEx5DxoTHuAfi3KBBo7XciQN2CTWksK1wvNarV0Pat39Vx6zgMMZNmDBLU5cdcLK0afOyvPvuBMmW7X4VMamDyBiJQAgIA5Sl8ATRAOcs9hDg1KFUDo1nqCHpCQLpypWfajMbIuEcsREHJQIk34EITMeuYitatGCCnkcRXqdNm6+2CYKtK5Xae8cjqqnWnKszZiyUJUtWabYIAjZOaacpkcPy5dM1qpVIVzITDh36Rx2577zzhtrbpO0SAMBrjNgjtPMBQZmIR8YLHPLYU4wzbGSUcIvgPHv2Yjl58pTa0QhXlBXAGUL901Gj3tZoaCNuYMKj94THq1evSs+ePTXqEQdMzZo1Zfz48ZI1q+9mAJjwaEQIJgoW7q6BJY2mfkQllYOJaMiQ0RphxHthGPMYYt/PP/+qi3+MV54PKxV29uwv1aBNnjypesW/++5nKV6cSLKMMmfOYn0d3tD06dPo64gw8yxU3qdPB+0WTXoKtwgN7du/pZMkBjBg9E6ZMlyjFvHmE/HEZIrXjtRbRAcERiZavK9sGOMPP1xQ8uV7UBIq/DaDB48J8ticOWPu6qodU0RnjUfOGQTUVas23vXcK688r/WHPvtskTblIT2Xa8SIO8LjvWB8qlSpgUYPURqAKFYEZcap++5LK0WKFJCKFUupGGmRj3EDEx5DxoRH74C9gJ1ADTuEI8aRqAhIOEf69/9QBT+ivogORJwi5RG7hY7OjF/fffdFmPtE8zuEQBb+iAN//fWP/PvvKXn++RoyZoxLmCRNkuiy06fPanMWbDjHyfvaay9KkSL5b9tVmTVqjchyREXP1G5qM/bq1VbvDxo0Sp05rnG2jIqXpFiT+YIg5bKrrmgkJZGRCRV+0xIl6gR57JlnqsjIkQO8Nu9EV41HMoRIz/cUuz356qtp8vrrQ/U8ofkPwndMpY8bsXM+cC5zTletWk4d82SXOBltOB3KlSsphQvnS9COhrhEXBAeP9k2VFKm8XKq9YWr0rJ4P588Lt7EhEfjnkYshiJdnrdt+0295ufOXdToRAxZIgKnTfsgzFoqTCjUVMuUKUOkPt8xpBCQ2A8ec7orE1n0zDNVNUrSASP5yJETOoERut+nz3C3Vx1D9quv1urfpUs/Lm3aNNYop44d+9/12UQ0UY+RIuthQdTlrl1/hvo8nZ2dDtUJDYRbUiZY8ASvf4gh+eab7WJ8H2KiuYxjKDnQwZMIR1LQxo4dZM1IQoG05QMH/taxg9TkmE6zj27h0QHx2SnFQPQuUZJ0IXXAgMZQJrKIMZMxiRRFPjtDhnSWOuRDmPAYMiY8xhyILUQl0pwOke/cuQs6Z1Bf+ptvfpQXX6ylEV2hwb9BTOT1kcHTriJlmvq2nt2V6YyMjRdcWMiVK5sKlzgSnVp61OGjq/Qff+xXR1u3bi2lbNli8tprPTWCKTgLFky4Z/O4FSu+ke7dB4f5mj17vpGEPI9ia1BbGvvcgQjR//1vnleEuehuLkOWUb9+I9x/EwX5wgvPSO/ew2TIkNc1Tde4G9Yv2NcESBBcEdkxIbbPB4I4iIgmDZ8oa5ovTpkyN8hrWrR4SUsJ8BxjGM6Iixcvir9/okitL42YwYTHkDHh0cXduRaGcVssZNCfOHG2Ru8MHNhNnniihKZ2uDzySdQLjYe7efPXtdEGxjKdjJ0C2EyIffuSSr1f/3733V5az46oSSIKPYuXO9D5d9q0z/Xflir1mH7Gtm07pWnT+vLqqy/I0aMnZO7cJTrxICgRwv/mm+9ptCGGL2BQZ86cWU6cOBHkvfGyP/poQd1PujUSveZEPdasWUk/jzQORAQ2avHhebsXnTs31wLZjvHt0KpVIzUGWrVqrPvJe+7de1BOnTqj4gPRAmykEsXXDm8zZizQFGVPiJAg5Tp37tgxkKKDrVuXqai6Zct22bhxi9YExTM7efKwBOeV5XomdY6FKMIai2LKILhub2kkD9cBUSwcM5wFGJc4DGJDeAwJ9pF9wphlY3wiRZ4xhjHhu++2yOjR0zTShvOX6J7PPx+naUHAv+U1jH1EP7711gfauIpyDcmSJdESDvxbXo+zhgjomjUrS5UqZd3v4QvwfX/5ZZc6aPgu/H5EPdG4gUWtRXEaRuRgXEHko4M048cbb7SVt9/upuIRIiJjBA4Z7BBESRwb/ft3lgoVSmszFefaw/n66acLVSR86qkK0rlzM32O9GfEy+AcOnRU6tdvp2MyEYhcx4xB2F/jx7ucgUTpMzbTAIZsE8Z0xiXSV51SM1myYFOdvOv9eZ6IJMZ7GvsRtQhEVVL6BluO+WHv3r/k6NFjGrV4LxCZmjdvoHMGIqSn8EBDv7ZtX1b7jOwYbCoavjG+ZsyYXjJkuE/y5Mmh43d8HK+ofVi+vKuRgAOOd+YTUt75HeNiRCC1Otmw07GnqQk6YMCHMmbM4ASXMcRYwTWKqMytY1MxH7syqq7pOc+1zX0CMUg579evc6wJj8FxssXYXza+E+MJAuHhw8d139u1cwVkkEbNONKvXxft2s51y79HgGScAxwRrA3ZiOQGxjDGLOwWjs1TT1XStZyvHAPge1MLl30l+AU4LjyeK1eOEEteGDEPK3tvV4C1irMuLOLRCLN7NCnOiG+//bZHU1uo9YNI9uijNYK8Hk8bRi1dzDCCKlQopZMGkwSLckTDxYtXqTGId47UIrzj8+Z9rP+eQbhBgw5uL7rD66+3kRdeeFreeONdqVGjonrXMdLXrfvOLVwSIeCkurZs2UsnLVrL02IeQ5VGHnjvSdGgOQjGLPeZ0P/776x65UnXZuKiKDviKB5/hKSQDPnQwFgnrZtJhnRuR9SkkzXGN+9HMWwMcoSO06fPyMmTp/V1TJ6kyjBxIkrGF4jyqlatkUZ0OGAcb9jw+V0dGuNSxGNCheuURTMG8Y4du/WW35Zrncg/1/Mn5Nixf/X6YqMuJotCCt5z7iNiEW1MrTFv7zsLYwz2o0dPqqecsQkjcM2ab92vo7uiExWNyMiYwD4zljG2rFgxQ6/XsMYGap9R9iGkBSD70aXL27J6tesziYYmKjo2YUweP/4zHX8Z/4jgpgnFpUuXtHi/s68IApSTYCyjvAQOhLiORTyGjEU8Ri/Dh09Uxy3jSYUKJTWlmDGxQ4emGiE4YsQkmTp1fpB/Q9QXC3TGqRIlikqpUkXVvpg7d6k6UKmDzfjL++D4DAgIlDFjBrkjChE1ETqDs2bNLPn++62ydu23Mn78O/oYdZipu5c6dWrZv/8vmTlzkUby16jxij6fIUMGOX36tNStW0OFIMZyPhdt75dfdkvWrPer4wnxlIg89o3IF8raMGbgZMmT58EId5+mljJOHK5TnLccC8RTV6OcLNqckPsIMDQexKZz1ZM7JtWqlVe7itfEJxGSOpyjRn0S5LFPPnlf7W5vEd0RjwkZ7GTmXqdm/P79h7TsE0EJrFWOHz+lthS2FxvXlqt+fAadn5mrEdvatGlyzwyt6Ia1HGuqnTv/lICAG3p9sjFGhWRTcS0yBuJM2bfvb9m4cbOWXqKmI+UYQoM1FJdwaI59moi++KIrgwq7ZNWqzyQ2QTgdP36mrF69UQVGHC7UeOf7U8+U34mapXxvxmvGSG69eQ0n5IjH6bGUat3cUq1NeDQiDrUN6VjmCWIjE0NwECTwSAMLVVeH55ta8wdBrnXrxu7F+Jgx09VrT00gJ0oO7xVCJ2Ijr8G4Cg6PU4+RCfrJJyvowvnQoWMyatQUNcQRD/j3iH2uSMMMmobNvvDepEXiKWc/HQ/ctm0rvDqBs/CnYQkCCPtINBiiL0ZFXOavv45IzZqvBnmMxcLXX3+mUbPewITH6DOOa9duppE5zz1XXYVGDGOu/cWLV2uUDqIyhhSLS24xiLmlK7S3oxuJ2sawo0Mmt47HnX3JmBEBNLPedzaMeEcoxGiMif1lH/DsE9HhCAI0JIqIgyMmQHzt0KGfigPUKSW6gi6iLCr4nWkE9tlnX+pr+Y0xkOlWW6NGJYnrmPAYMiY8eg/KNLz8cpcgj2Gb/Pffmbtey/XJ9cq1SZ1kxjkW/k6txVmzRrvnVsp/UG4GewsHLQ5k7j/5ZHm110jXnTz5PW2WFxwcxYiPOG8ff/xhuXbthqxdu1G+/HKVPPVURbXViDjETmLsZH+JbELwI/qOhTQ2V+PGnbUO7scfD9Z/5y3Yv3XrfpCVK79RsQZ7ChEyPjT6cwIDHIh4I9sirJJH0Y0Jj9EDneSJbsamwrGHTYVAj91Cdhf2AvXCsZtdtpXLrmLztsgIjCM4O3CisJZLkSKZNvS8//771abiPvaUU9fVabRHYAe2Y0w4ALjWGUNJ1aeMBU1JScmOTfi+PXoM0TEcJxG2JdHKW7f+po4njgW1eB0QJOkf0Lt3hzjvJIkLwuOnv7wTK8Lja8Xe8snj4k0s4tFQrl+/oU1e8BYziJMuyKSCAetEABYp8pB6sg4ePKQh40wsvJ5JkpRqJ/KQf4MhygRJCrTTdIUJCiEwMDBA/Pz8VZQMbYBl0CalhlsGbFKuSf9zXo+xzf4hDvA8Dy9dula9hq56i/6SL19OjbSiMxoRSk6KN4t/wCvPQO+kRxPZidGMET59+ohYS4HEW1+vXmu9T4dcjn9cPq8aNeqkdaE8qV27mnz00d11NWMCEx6jBgtUomGc+ktEK9JFc8SIyRrxwliB0YxxxXXvK5CKV6nSS3p/69blOoYAUTlEx2TOHPP7ykIcrz6NshAAiHLCKK9fv5ZGL9GV07M+bWzCuE8qKNHaGMX+/n63b133GbMRErp0aRYnU/lCw4THkDHhMerQoIVGd45N5XR+JmIY0RC7CpGfTAwimMgc4bWpUqXSTIj335/o/jcIeyzksZscu4rxFnPGSWXE4ROWE4PPQYTDbiKFkWZYjnhBtOPFi1fcNhX2EFHt3367Re2q8+cvS7p0qVT4XL/+e7WPEBRv3HB1qMUGI6qHaCbmXL6vqw7bFf2bSEwiO2MDhJJWrXppJ2jKAiG2xmUmT54jH3445a7Hd+9e67Wx2YTHyMN1QaBD3bqt9D7XUt++HWXNmu/k+PGTel1xnSGe4fjzJSGqTJm6Grk3fHifIFkr+/cfkXz5vBMBi4D388875dtvf9JgDdYZOBVoSIVd5St2KL8tNh+Ob8ZbxlTsKOwp5z7Rq9jOwWvqxmVMeAwZEx5dWHEBwy0W5sz5gNYko4tcliwZNaSdlEFSeFg4L1u2Tus9EtJPhBMpAYhizZq9qPUbESGIFGLQIbIopMmSgRjjlKiZkMBIxdgmTJ9aIBjbeHMxyrml+yHG+dNPN9U6jxi8fCa3bBjVTELjx78r5coV0w6LeAoZ+ElVwPvGZ7ds2cgdKcC+sqBGECDyEJFy5MhPbtc4SqvRh2GlAEQ37A/eTL4n3npfFx4xQvi9EJ+qVXNFsIYG58SYMQOlfPm4n06QEJg+/XN5770JQR5zaqMyDpCmly5d1DrbR+W8oyC900H+znbN3f2USAFSq3fv3quCqTdgjKPrOWmOeOEZWxmTHBhXaSrB86NGDdCURV7HeIqAgECK8IAAgBMEgzokfvxxq9bELVAgn0YqEi0RlXpBCBbPP/90pP+9YRhBwVk7atQ06dTpNV2kUx6Ga5yUYRyr1NFmQYqYiD3yySfzNcuBhSjXNMKDUyICuyS06xvnkCMYhiaAOtE1lHvhfRiXuKWEDvWoR4yYIt9/v0XHAceewrbCUYPDuUWLRvLGG621LA011kiBJu3bNXak0gwWFs+8FrsKewsHNemjvCe1GhEKeC2iK7UsvQVlfYjEevrpLPLHHwf0N8Ch4svMmbNEj/O4cTPVec55wZwXEv37d1FBNT45hOIrRORVqBC0RifXPnXCYd26ufpbO45Sb7NkyRqNssRZcLdddUXtPpwj1N73Zrkc1mYTJ86Sr7/eoPvGepMIbwdqUTOmVqxYSsdbalVjVzFesZbjeHLLWNmhg6vpX3AYtyhhgBOGcZEsPdZjkYX1Dnant2xPw4gLWMSjodDVsHv3QdKw4bO6hQai4sKFX6sgRhFojOaUKZNLtmxZpGnTF3SwT5YsmXr08eRT44LOrtQwa9iwoxqxDPgYfaT7NG/+ktvjTsOXjz6aohOIw7Jl01TkIC0Rg7lbtxY6ITz/fBvtHoygSOQl3iPSF+m8/dZbnSVJkqTyxhtDtRYRDW/YmDTZB4xph/fee1MFR/Z10KDRajSzr9QfxPOIkcok3LhxXenTx7sh8Ii+eET5ztS39NWmJcHTfqBr1xYqVrM4AURUGvuQmunNdCCwiMeIQ3oIEY2LFn1913P8js2aNdCo1ahcD//734+yefMOSZrU1U2VxSFCW8mSj+q5Tm2z9OnThVoLlOuyWbPXtUkD0dQs6pMnT67j0Z3bZLp5LjKjo6t1cFjIMv6wgKAeLWDkUjSdWk3c53Mx2hlfKQSPId+160AtEYFoSKokYyMp7bxP166D9H2fe+4pPc6IFVw7OGS2bdulTpoePVpp85sNGzZpGiWvh5s3A6RcueI6FkYlZZxoAhp60ayBpg1OUywnfSo+YBGPIWMRj1EDZwN2C7Wchw3rHaqQgMBHSvSiRSs1iodrGCcr9VVHjhygGRk0pEOEwp4ZPHi0Loixq3C8zJ69WMdIxhPGTqLRCxXKr++NUEUmy7Jl692fh8hIt+DXXuuu/6Zjx6ZSv/4zKk4yBjMWuxy+idWRixhKWYUyZYrLzJlfaKMYMkXY8ufPIx069NUajw5dujSXwoXza9TR1KlzNcoQqA3JvILdSAQlEV3vv99HM2O8Sc+eQ9Re5TghRsaViMann66sYgu/EzYs4hTiNHMmv6m3o+Is4jFi4EAgpZrGcyExZEhPtY+jUl6J9QuNorB3mPexibA5KJVA8ASiG3ZVWOUGWCPh7CRy2bGleJ87GzZV8rucIDFxPrAuJUqbMjAOjDsEnfB9EB6xh2rVqqp1X7H1P/xwstZQLFbsESlR4hFdH1JnHLsKYZIUceooclwQJhmrGFt5npq3nTo10zUh9inp7k7EOWDHjRjRT3LmzBalTJxZsxarHY1NRZkvxlscMr4U2RrfIx5nbn83VlKtmz7e1yePizcx4dGQDRs2y8CBI2X48N4hembwGFEgl2hIIocY8BHyEMOY0PAO0XGMlAAW0Hi1PQsLAwtmFttDhryuKdOkOY8f/6lkzpxJ2rRxRcmNHTtDjWgmAqL88JZTlJjJBUMVA5wooW+//UJrMSLMIW5Rr5GJMl++3PLSS7X1vUaOnC6ZMqWX11570b0PTF6EvZMCBIMGdddmNQ5404h0ZAKj4YwDoibpkJcvX5UBA7qqQEAkg7dFPb5L9+4tQ+wGHlvQrZs6T02bdg/yOBMoghALoYcfLhir3YtNeIz4gpnOpNRshJ9+WqoLXK6djh1fU4MpqgYSIhmp2wjULLz5TCJkiA6aO3esPPJIAXnhhbYaUfP77+vUkCZiZsmS1Vo+gbGmWLEiMmDAR5pagyHJ2BVaJLUn0SE8svAjEvzjjz/V7psOPXq01NTHdu1cDRmiCkYvhjcGcvDI08GDe4ToJOJ4FilSXe9PmTJcu0R67rcrxSf034/r+ckn70Qu81qi2hmHKa1B9+7guMRRxqt8OgfgaIgr3RpNeAwZEx4jDzYTDaS4FpgHg19vlH1hYbt27fdaggH7grqp1EYsU+ZxFeMYgxEKSMdGEOzYMWhpEhbLjJOIUdQF4z2p2Th69DRZuHCSfibjxhtvvKMLZqIMyVghihIbAictpWXGjftMxxKimGig5Th+aQiIgwG7g8X9t99ulY8/nqYNAZ3vg11IUyrKwwDz/M6dq92OHqfcBWMB47ZnxB4OF44T3/n552tqxJ43ohDJ3OnZ09XNu127Jhp56UsNHRjzSSV99dXuKiR5gsDI+cBv6a3mfKFhwmPEREeuxSZNuurf3bq1lBdeqCkNG3bSBprUPo1qyRXWYU2b9tBrCSGLuZ5gC7IiSEF+8832ul5iH2guhXiHY2Ho0LG6f4iR2FSMC2Rf1KnzpF4XCHfeOh+wARFOGYccnn32SRUFP/ywf7TUtMQ+wllLJky/fh/qteaArUQZhpDso5Yt39CyGax/N25c4H6cY0fgyr3WOGSDsV5yaNv2ZV0HY1etW/f9Xa9nnUwEOZ/HNc+6MyrRl97EhMeQMeHRRdxYGcQRGIDwtOCxwqiKK+DloQsYRY4R7ljMYnAS6cKiFw8S3mpHIKBRS+vWBWX9+h904c0A+dlno9zvh7HNhIXHjBQijgupIogEiJy8nsiZLl1aaP2/5s0bqGHauXMzadq0vhqGFDCnQzapI6RLIwryfnj5GajZD4xdBuP33usjuXM/4P58BE4idd58s602RWCwTpcurX6u5wCPwesJEzQpKxgBdeo0dwuUvXq1k2HDxut9og0AY5wFPAY90QfRIcaEZIA6aZp4w2jo49nUZ+vWZbFWh9LBM7WaKA1q0xAJR4dxvIUvvdTRfQxbtmwYa/vp1PU07k3z5q+ryM/vyPXFuYdR6qTgPPzwQ5FO6WJxi2PC1ZXzbV08O7BQ79mzlQqcb731vjoeGEsLF34ySLryF19MlF9/3a3NTng/bp3GJ45QykI99HMhcucDi2bGBVKlPClTppiMHz8kRq5FVyOXwroRHQ7UXeO6YjwNLjwiGjoiAwsdz+/J2Dt06BhN7SaVk6hKvgu3OJBIUWLcJMrA4Y8/1t81riGUUE+XepCAcfzaa/X196GRBJDqxFgdmw4HI35AlBwRf2RR+Hp6rANjGItkxjrKuOCIIMKGMQSbav78ZRIQcEuvReZMUhkRwBhfKdPAYviTTz5QOwm4jidNeldSpEih9hW2B8cE0YDrGuHRSZtmnCYThMggxoE1a2brXIwjiTEBGE9wFlJzkbGSz6asBvVoifbp2bO1On09r/2vvlqj8wGp04id2FU4GJwa2fDBB32D/EaLFq3SpgnTpn2gqcOkDQPvzTgC3LIxjtJMkIhI9h1ndXgcSRHFc3+J5pw4cXasdYYOiW7dBulv6oAgxfz30UcD5OrVq+4GiLBnzzextJeuedQIH/Pnf6UZVVyPOBY4/8nmYIxwZTKUjLTwyLqMiONPP12g5Q48bQKuK6Lq+Mw2bXqr0IXj4amngjpGZ88ercEWdLrHoUqUMmOIA42LGFtiwsYeMOBDHQ+Ds2LFjCD2YXSB7YrNwvb99+XcNWBLl35OI88Zoz0FPgJcWIsxRiI8MuY5zQdxrLz55nsqmDZoUFvHUpwpjN+Uy+KYcc1yPTui4/r1c/U5T1yR5fOC2LF9+3bSiNNXXumm45SvNCKMLzBLeduaiBvWS8xjEY+RxFVP8F/ZsOFHTVchlJvBBU/Txo0uo6FOnWoaGciCjPB26gr6iiAZUtdWhDa8TXQzZHCmNiJpHAyeGIF8ZwoLEzHkCYYaohLvR001vOMhiXBEnhE16BjTMGzYOBU48XYzsGOcO/8WYZEF7o0b19U7hweOqEgM2GHD3tT6IqTyvv/+JI14bNWqoaZonj17QQYPHiMbN/6ozWxIXcIjxdsSFcDfRA6GFpXEa5gkEGOZTJ39cRb8Vas+oZ5oBEo6cTsQqUkKKsb5gw9mjxYhEiOcjRQNUpOIZvAkNg1PjlFINR1ZPNB1s0+fjpp+yjmFCEHKeGzA9UmkVo4cWcQXYOGGgIzhCTQJoKM5HtjixR/VEgQYqLE1VnBuU0qBRR8LVhaiXJs8PmPGF3qdk05HektE4DtyvfD9GBuddEDgOnvnnbHyv/9tVi89neYpto6YTaQy9Qy5Lrmu8NzTodQB8fGDDyap8YpnmKhkFruhwThHxGNEm8s4RibjTvXqFTV1kjEf45imDt6C+lAIhrt2rXWP4Rw/HDUvvthO07tZ6FO64uOPZ6jThTGZcYTURurFIRpiXHOOEf3kFGon7ad27SfVkMZg7t69VajRFYgUjHmMc3w+6d7t2r2l90kBRMAkworodcQIBBicRmwY9yy00qZNozVCuWW/PX9Xb/HXX0ckT54yCT79xRciHrk2iahlEcy4TYYFjk4WcpzzzK2MOwgxx4/TybnIPRfE3iKkrq3YGjhoJ02ard/NKSfBmP/yy/VUQOR5z1RC4NogzZpb0oIZ90KLIOZa5TpzQDTo0+c9jUJmPMQp6pRpQXhAQDxw4LA2OGjbtomO66RXkspLN1iiLN99d5xe45RqcNIKP/lkgUyZMlvtWVeUz63b4lOgPsZ3YUwKze6hRhuRnIxZzmsY0x955Cm97onGatToWRVOWYgDNhj7VaXKE+rwio5yMxyD/fv/0vkIwZdzDUHBgYya2Jp7Oea9eg3TffOE851SQ9jJNCRDRArNMeQt9u07LPnz+0ZDDJxnlIbhfHIa3iHuYDenSpVcSwmUKFFUAyFiw3nBeot11bVr1/RaIXuMOoPsL4//9NMOzb7CYReRqD6+N5khnBOIjtjent+PqGrWRzTVZE338cdDtFwDayiOF+tWxC1qO2M3eZ6HlHN57bUe6hAgGpvIzJg4H0g9J2sNZyjjA+M8NrI3bQFsn1at3pQvv5wcJJuNeYfam9h5rLWwASdPnquOpaefrqJBMvQdwG5fuHCFjofYWnyfgwePqJCJsNypU1O1Ofl3/fp1CbIG9oQ1L4KoU8qGcZDO2EShMsa7BNFATSOnTMSZMy57ymVbndMxmUho5hnmbOxSHNbebmAYFyIeZ8VSqvUrlmptwmNEINx7woTPNLUOEQ1xhdo3RNJR94KJjbBoIueYAIg+oZsvg8iQIWM0eocoHhb0GBJsLm9mUrdXk/t3Hk+iQiZGaq5cOSIdPcJgxH4gIhByz8D2+OPP6H4sWTJFRT0MZNIY69Wrqf8mNGMGI3XkyKma9ujZMCEkNm9ecs96JUy8TDIYnSx+CYFH8CQVgcnO83UY3vPmLVUv//ffL3JHNWEoV6/eRA3Ir7+eqZGRGNazZi3SmpP58+fSRTcCBamd/DvqDxEZVLPmq/qbMKgT0s/v17nz2yqukl5IFCbfE2MmuGePFCNP4dETxAga7kRHYxjOs1q1moX4XFgCakzC+U86JlEXniBQMwkSxYEw4UCUxpw5Y2LFSI4t4REvKucsizjOP2qHcu5g9DFuELHmQNQsxg94FpFnIYcRHZqhEtPw2bNmfakLNMYIpys9BhCLVk/uVbAfARrj9+WX64b6Gko2EE1M9A1OG7zzznvzG2L4Oc2XPD+XqEjAKUB0Ldd0WN+Jc4IGWnERxnPPiFOM29at33T/zbjDQgtc0ebbVdTGIx8TzQc8U7Mfe6ywpkQhVvDZPEcEBecFvxvnMbeI7ixuzp2j2+8FvVZcjXLySM+ebSI112F4f/fdT3pusIBhAeCcj+wL8wRiS3DxwoTH2BMe+V1wcuA0QEhkIczcQcQddhOOSKLzSP/FNmAeIWuBaYRad8wxCFKI647dhLPCsZ9Csq9Y2DM/I+REpYEDi0Icn3wHrrc2bfroGE5kImIocx0LTUq38D08nZjBRQkcUTh1WOg6dVpD4p133tAF+r1A9Kc2NhGOlKnhe7OPZCJ4jiPAcX355S4qLDjjhmfpmRYtXlJnz759h2TfvoP6WIECuXWOwvmIkwh7FzsJkZSxm9IcjMVEB5EOThQn9YJxno4Y8Zb+tji0POH4EPEZPBrLExzORItFRxmH4sVr6/kGiKY4px127lwVKzW1yaih3JAnCO3YgKSqI0A4MLZ9/vl4FZYTivDIOcv8zZqhd+/hKqrkzZtTbXGytcjaCsmmwq6ncQgsXDhR7X3srNiKoEZcR/x2AiM497nF9vF0ItzLpuIabN/+LS1PExo4Nsg4Y+z89NOFaoc7OA02ierzXG8BtaqXLl2jayCOO2unsGB8yJ8/dLvLl3HGXOdYYysULepaCzvrmunTRwRZBxMUQ1o7dkZMl9miISf1P5k/WMcS4cpc4dhTrgj09DqOcX24bKqLOv8gPuPE8jyvwgvnJU5qxmtsKtbmnuMi63Lm6+CR6SY8howJjy4s4jGc4PH44IOJGsbOYINoxWKcCzK8YgoXMRMFog0DG4aa69bZnL/v3DK4kBqCt5iLGxGycOF8UrBgfilUKK87vY9QcKLLCK1nkMSwJu2bmj979x5UQ5TPx4PMwMEkQ6SLI8zxWd9886N06NBU6/78/vufcv78Je3qjAfI2fDWs0/UCeF7U8OPxxnU2BeMegwkDH0EwODwb9lPjE720xnoSR8hpRrvPTRsWEcGD+6p99kvRBq8N0RXkoadNm0qNeiJoET4pWAw4L0jOqtXrw6SPXsmnVDwPOHlQ0zkczgeyZMn1d/Bs9EMIIqQYoBQROOGjz6aqo8T3UitJhYQnvC7UZcOAyh4pzr44YdFKh5HB0w4eEaJaMCD97ZnGQABAABJREFUiZDDfn34YdBoCW+BsdKuXR8VHxFY+W3wvLKYI60LA5rjX6tWNV1IxlbapXeER5cYze+DF9RJHeEawQOJsMLiDXEcwQ5xlkUhCz0WPCykSNGoWPFOTVImeq4XzlNn0cnCzRUFk9nrXszQ4Dfu1MnVBAEHTNasmbUZCdHPXC/cZs+eWY3YBQtW6NhDRCce7eBjZ4MG7TXF8NVXu8no0QN1jGLcYuEQ1jjLApgOsUSKeNYRIzpx+PA+8Up49ARnTZMmXbTxFdHWsQF13nDWRDX6msUNEd2Mb4iPCFI4zJj32JhbnPuISFu3/qbnBVFajC2cg8ybPIaAwfUEnDecOlwvGMrM2aSWEz3HYozryyIevS88snijtjS/a7durXR+dwTiiNQxxvZhbgzJfgrJvsKBTLrznj379TGcFERfu2yr/GqbOFG8CByMKfwbbD/GGQQ9FnTsP2MJ0S2pU6dWG4Nzj8fIcEF8RFBkXmQsp14t/56xHoG9SJECbrsKZ+jrr7+jizzSn9kPbC2XTUU3Vs75pCqqBx/3+W4//viLzi1EBzqpeDNmLFAHMfXanFIVzjXKvNK2bV+1YYlA53siQGAfIkYQUUO0GPMU4zvHZOjQXlKihKsBFrYli10W3cOHT9TPYt7nmGEXeIIoiZ2FYEwpG5zH/Hu+50sv1dGSHsHBdmCuYz4IDtk1OJeiA8cpv2nTdj2HcIBTnmft2jnRZrdFFEQ0ouCwqfltGKs4XxC5qXGOzU7kI1kHnCOxhbeER85LykGRxeSAg4vzukWLhvobcpyo9Uwqf5s2L+v163Qtbt26tzsLDUqXfkztNOA4EtXPteU4xnwFxHtK0nC9Mz4QMOLYU1yn3KcRVKVKDVSMJ0qX6yl47U/OGRyOXNfcvvDC07puIuMjLHGd48q/xZZ3ahE6hJTyG5eFR0+cKOzYjihGeNy0aXGU6zoSKEXg05tvtlObiK7gCJSOLeVpWzE/sT6mZAbrd/SE4cMnaDQtmYk8z/Fxjgl2FxvRnMxjjk3FPJgx48M+HfE4e8ewWIl4bPJYH588Lt4kXgmPEycOlxo1KuugHJXBAsORbswIKnhEMb4YZGlGEhmvQXTBfmEsE47NIh+hjnQ4DGdqc7CvM2aM0DoRpMwRJemIkNRiZGAg9cbTQ8PPj0cMQxQhD4GT12H4Mtkx4SBC7tr1p6Y9YbAzWXGM8ZRjrGFoYkxjgCOCEc3ieF245TW8FsOTxwgRx4PLv8GoYjHg1PtxPJJ8PpMkkQ6kAb3xRhvJkSO7GonUSyEtD6PaKYLeunVjbVhByhJC5GOPPSIbNvygggfCgxMhxaBLTRFC6jkOTOw8htD4+efjVDjzBIP5yy+/1kYYQPonn81iIHjRZTz9wRtAEA0wceI70XYOsMjgt0dIZqECGMlR6bIW3uiO0IpMO6npnJeIEOwfRZpJRcBAjO26XN4QHv/99z+9dmgIQOQz5ygLl0WLJqoQFxFYSDtGgNNU5f33J+pzlBRwOhOy8ENkZ0P4DW2xjjiVPr3LcA1PxBtjAtctnkyieLjmaDxFtLRTsoBFNxHUiEQYu6NGfaKG6qeffqSL9L//PqJRdoj+LOac5gOk8yAw4PHnHJ4/f1wQQZrIZUQ0xisW6p4QwUAzAMawsOB8RHhioUZ0dHBBLL4Ijxyf559vo11pWYTGFkThUNsxssIj5znNHhiPXfWTbuo5S4Qwtd4wapnbuC6ceksIJkT6rFnznQr9jnGOmO9EnIUG8zllM1jAk06GUL1s2dcJ3hgMza5at26BimfOQj4yMKawkOZccf2Ol3UMef31thoZF1swVjD3Mz45thUldFg4IaRhs5BRQLmXkydP6xzI+MO2evUG/S4lSz52V/1Jomg5L4lS+frr/2npB4RGxj7GVRZ3XL+OXcV5TeTWhQuX5b//qLt6WcdTRHK6rNLIz7GnnA0hAMcyYzCRhjzPwpJ9Y2HJ+Ow4YYhadCKJ+S0KFaqmdgzp3seOndAofOYP7CTmcCdjhfqaXNs4zvr27SLTp8/TRSrOM1K5neu3ZcteaocRyb9ixXrZvHmHCowcl2XL7s4KYXxmrAcEXaLV2DfP8huA/UeNM46ZJzSwicr56AnHg7mb34BSFdEtboYGNjeCfkjfg33i2O/ff0hFM6KWsPOZ/ytXfiJammz4uvDI78G5hfBBcAQRwTByZH91ZkcEJ0iEW8Yd0l8//nimdmhH+EaUx4ZDkEM8QZzErmIcCAl+G65dxM7wOkkQ/ojGxhlBx3KcEUuXfqJjCDYVNgkODa5bnLNcy7Nnfyljxw7WNQ32EjYVzdC4ddLxiUhkLuRcwQFAdBuOXQfK0OA8YMzAlvTs0kyN2aZNXeunsNbMnI+kQDNWkn4d0m8QH4RHz8Z8TlPD2ALh8ddfV0UqwIDvgVDP74VNRaQiAT+cRzjjOQ85Dzw35hzWFHwe1xx2GPPBpk3btLQQYmRocP3gsMGe+uWX33TNsG7dBp+0qUx4jH3ilfA4fvxwXeQeP35SJw0WqtSniGg6DaHrGIZENmIUI8ghqvliq3sMZ4wmDGa8pEQJVq/+cow2HkFIJMUJYxBhsnfv93RCp0kMi31EOYRaJnoGQLzlpPshWganVq0qkiJFSo1AxGvJwIjg6RxrolEee+zpIP+G56j3+NVXa3WgHDKkp7seCKIXkS+FCxeQUaP6qcCBkUG0GceoT5/hamjgIWS/iF6geyAsWjRJPz84GOI7d+7RFCcEUs4xDCI6dOPd8QSBaPny9UG6Efbr11kHexYBIUWBhpcnn3xZo1E9oU7MvVIgomsSxOtOLRgWVRwHDDRnfzCiELj5HXxBbPSG8IgAOGTIaI3i82TPnvW370XfeMH5FlJBagxVtu3bf9dxDoGAyDfPhUnbtn3U6ADSEun+jqefawhcC+C9t50Z+9XhgrAJCI28b6lSj+sC1RX5FKjXHU4NyjQ0a9ZTBUGEzWeeqRqioYRRw3W0ePFqHTeoddSgQR13KrXnQpPmNgid1NJhMUv0JIY6KWdEF69e/Vm4Cmw7BcPjo/CIQfnMM6/Jq68+rzWD4hrMG8uWrZV33vk4xOcjavSzSCNqi/OeOT8i/5YFW/78T/ikkewLdlX37nSX36fCBzYVW0RrmrLgpXbd889TH7WCpjnjHI2NdNZ7gUlM9CDjIVF/CGMtWrwRow3SHAGUxnhY5ET+IqIjIOCgJVuDSCZsOvaPyHIazZBuHhyER2pC4mTCiYxdhTDvKXBRNww7xRN+V8Z9BA7qzeFod+Y5bKp//z0jY8e+rWMvYuRXX7nqTTdu3EmFfifrAZEDW4XsFTJI3n672137iIjx7rsfa+3ngwcPqZ2GmPPEEyWka9fmQWxthBhSkLFzHbA1SUvleAUXKyMCdv6zz95tP3kj0smJxOO8YpGPE5w5lQg/hACuD6LbcL5Q49IXxEZvCI/UCsap7jR3hG3bVkT798c+cBpEOnDccUgREYldhZhPcARNL7F/HVjP0JwJEEVz5nxAI6bbtGmsTmPOb9YJCJtOoADv7dQuhWrVntBO0K56ooEqBrGe4Pcm6pXPJiOG+QzbKjhcZ4wRZICxz841Tx1nz+/EuqNLl4HqfGY8YX9Y22L3EXlMEAjiY3jFXNYCvXu3dze7iy/Co2fJHs/62XFp/7HzmTucBlrMGc51RDp+8PVqWLCmR1ynvBGBJBFpasO4nD59YZ+0qRy7Zu6v78VKxGPjor198rh4k3glPDopQVwwW7b8qvU9SJvFGzR06Ou3U678wuWZYuLB4GHycUXy9b9nvUJfgGiOsmXr6X3ScEk95jsjFDRp8ny0N0FAUGABDHS/9RwEOV5M1hh3GJVEPQK/BeH+RLIg/HEKcswRJRjkSB9wask56elOLUHETMRIDOqPPx58lxgD//xzXC5cuCoFC+ZWo7lu3VYyZswg6dfvA424wgPkCSIaBZjfe+9NFazDAx77Dh36a2FhDPbgYDzyW/DZnmCYYzRHtHMikY6PPnqn5oi3GswQGUSaO15dJxKW3wAji98JwTE66i3FNeHx+vVr0rRpD621AjRLYYyIbriOwjtuIb4sX75OF8u9erVXY8GBWqT8bhiZXGeMB4sXT1bhh/pbLHhYVBcsmE8jzzzry1D2gLGEczak/QitdlloUPcPI9zTkHciQOjoSYdHujBSY4goZOqx0lymWbPX9XXsHw0A7vWZRCs//HD1u4zI+CA88vsg8FPjK65AFCvNwTypUKGkvP9+31hLawSr8Xhvu4pFBxkW2FTffrtFLl68KKNHD3LbE/e6Fl0prX/qdYxdhT1A8zGi7uICtWs3U2er0zgOWOTjDAltXIwK1KrDsepZYoJxlnHsoYfy6LyAs4ixDPuIfSDbBKctJQgQLXgNaXY062H+dtXoddXpdWq7edbCw8794IO3pHTpx+9adGN/bN++R0qXdkVSkTXCIhYx8Pr1m5rGF9w+QjxiHO/Ro3W4vjPjdf/+I9RxhVgZ/JgizhJJT/pn8C64NNPCaRxRG535IXi5nZjOIuHY07CCY4fjjnk6WbJkel4hGJGlE1NBA74uPCKGI4oDouD27V9HW2SrJ/eqnejAWoO14KhRU1Vcb9/+FbezhN+PMgPUMKV+Kc7hBQvGaxT+5Mlz9DVEBlIWi7Tot9/+SNOWASd9ly7NpHTpYqGmd0fErsKeIjiCCEzP78X3RMREKH377a4qSuGYQLRnbVSiRB13NDH18UMSOEOyPZy6r/FJeCRbicjv6Iymjmk862s7sB6bMuU9deLEFnGhxqMJj7FHvBQeg9OxY3+tncNgDxSYJ4qRyDcMx7BC5TGQWZjTYIFFO+AtIrUNQ80XPfYspN57b7zWRgwOHtT58z8O1UBDSMTrzXvgpeM+nngikWDLlq/UU8bkFZpHiFOKzXMCJP2me3eXQYHoSJHw0EK2mWz5jTw7RPJ+1JhggiVShtf17t0hxPfAkDx8+LjkyeOqx0jkFMZ3uXLF1Uv3+utDVfTEKGaiHj16ug7WLIRIIQ9vQXy+D6kK333nSgHxhEUBwiOp+YijTBC1arkEWiD0ne8zfvxQjUi4F/weNMIJTkx0i3YMHq4ZBCtSPYLXtoxuOO+iUujfm8LjmjXfagSIw9y5Y7SrXUxAww1SZQBxECcKJRT4PbgNHomNF5+0ZyJIli2bppEujG90j2f8Q2TneHCeEwlMhOJTT1XQdHBPARnjMjpTTTinqNtF1DPjBg6hJ5+soMIF0cFseO2JkCEdkzRCvOrBO19jXPMejCHhge/xxReuxYFznCLb1dqXwNnDuBybNYgiCimh/Lauc/cBdVr4goFvwmPE7SqntijZDU6TECKSiNYhkjks0YYFLw1P6KrKdY6dAatXz9LxKniNMl8Au4MastiBnpFYDjNnjlR7IiQQzIj+c9lUR27bV0d1DGTRj2hG1BORUiE5UkMTS0hFLV681j0dkNhD/FuEnOBdtxl3cUjRWJDoKaKnQ+vo7Ck0IUIjpOAUGjasl3z++XL9Pvx2pH4iDNLoiZrhpAeHB4Sb555rpcJcSLWxiSIja4XjROQ+0CQxOBFxAno62BywjWleGJ0RT84yC+cg65EmTepq9khMn7OIuDHRUCy6hcfgzTwQw6dOHS4xAWu6cuVe0PuMXURgO3MSNhXXoKctxLWzevW32im+b99OWj4BgZ/STqR/u1KmV6v4T2QyKds0eKPhldMA0znXwlr7RAai/Bcu/FrPVaIpuXYofcN9gjhw9mD3MR5jE7Zu3Ujq1q0RZBzhuqIcBFlg4RHu+R4Eb8yb93GQ4+RLXc4jA1H5NDdcteqzcK0DfQHmgDlzFus6EycG57AvzJ8mPIaMRTzGQ+GxevUq6imkfl9IdRuctA/+xluFlwpxhW6f1LjwTF8kTJ5oJiIGmUwQKfF+OZ4soJA3DRDiCggNdeq0CNFI5ThgEAUHDz9FnJ2uXwzIGKsbNnweYe8ywkKjRp004pFjHhNgvFKzMVWq1FKtWlm3Ee3Z+RVRE6+/E3HTuXPzcHefxtggZYzjwLmCoEHKtSfUuqDWJLWiiBLk3zgQVUlXSCfagKYrFMOOjJFMGgapqEQhRgV+WzyfGKqTJ78nbdr01scRZYkU9ezoHV5Y7EydOle/KwsIummyAEF44H3x/P72216ta0XEBGIeRhOC8v/+Nz/UepKxLTzS0X3ixNl6f8WKGW5nRsg4Q6urUcFvu/7QRV+yZIkka1ZqiLmuHz8Je2HAuUIBcWAcokYqEzsLWIxGhEWiJbhlQe+KiAnUNB8Wm9mzZ1VjG6OZZlCI4hxnhF6K04ckXHGu7d691r1oYR+otco5H9GUDT7r0UdrBHkMxw+RHizE+B6I8KQskdqNkE4x6+gQ1CpUeFEXAs61x+eQUsQ8EZeFR6dG2iefvB/h6GkjKCY8hm1XVa5cQes7Bc8GoGwJNhS2BOMbdhJReqT+ISBSa4wxhsURnc3JQvn55x3qkMNhy9xJbcJx4z4NEnUWl8R0vhuCBM5pBAVPhwjzabFiIXeg7tTpNY0ABuwoFvDUkvTsOh0eEG6fe66lZoRw3GIChFPm62vXbkjp0kU12wHhwlMs8kzpYxwnNfWFF54JVzYE9jiOPOYYzhvS3KkV7Gl38FlEwOM4Q3Qk+pTHoFmzFzXtfMKEzyJ8DpEdxPnowLxGhH+9eiFnl0QEUqdxAhJdht3D3EypHVLYIxvpi+DL7w3YftTZZC1TsGAedcohkLkaPaaUtWu/l4CAW5ppxDHCsR6dRJfQ5OlUx3ExY8aHEbL3se2cBizBO6WHBhG81K8mIpjzmXUOY5LLFjmudgjHEccogjziImvBvXtdjlNOLYQexEV+T0S+w4ePqSjuRK6GZFMh7tHV3bG7qQlPzUdKek2c+K5EhHbt3pJvvvkhyGPURea6wD7gd+e4cE2RsdKqVeNoSVdHbMWR7ayByZLBrsyQIUOcjnh0at8yfi1fHjQzw4h/wuO8WEq1bmSp1vFLeGze3FVXBhEJkRBvfPfuLdUry98UNHc8XQ4U/WZCZsKbOHGWCiVAXQ2i0ZjAEdoosEpqqWtLpN7tiNQ88CUcAYvox5YtX9LJEKMRz0nevLlk/frvVbxzDDEia5hMiVihWDjpP3Se9UXYb9I106dPL2fOuNKzne6LCGDUNHniiWJ6biBu4FkNy0ClID7iDikIRAZwLEhXwOijy3VI0FiE9GSgKxk19hBvOc6IhE6jkOALlXsRvDsfkO5A2kNEFxJc9qTZIkazQHKaf7Dw4TdGnIms54yU2fLl7+7wzTHHMEKIpekOxxGvNtcmaQFbt/6qizHqfyHIRkbwjEnhccevu+SlBp30fvjE0UAV3T74YIKsXLlRHsiRRR7MmV2uXbsq+w8clo8+6isPPZRL/P2S3bMeJOMa5xD1VEnvp2yC00EUIR2DmcXnJ5/M1zGKmj0cU4THAwcOy/ffb1FPt6cHPqKRIBjVNDkgVXvnzlXhjvYmbZBGA2EtBll8Ms4SQRwTUXCe34e0NsTZhQuDNoKKazjjQUzW800ImPAYtl01YEBPbRKVKdN9Op41blxXo6+BRTqNLzw7zrLQZX4kLZFjS7kR/h01zHBaELWN0IiziYg/xisEKpx5XJdxEc/xBZHn1Vfrq2gxbdrnOp4hBjjzvtMoAschogPzHccBJzb2qK/h1MrNmDGj/Pefy4kD1IvDqYPzjfkHWwrhh/MDWyk0sDVIqSU6Byfa2bPnNJoUIYYoqpDsajIiSpRwOasJHqBeHRknzjlF92vmQ+wpHNvhjfIjwKBJk67RUr6GEk8bNmzWhiCc706WEKJVo0bPSsWKpaJUj7Jy5ZeC1A4Hzi0cAqxJWOfgCCCrB+cuNjvljygjxHX41ludIuQw9IbwyHVRtmxdbeoyduwgjT4MT5YFgiEp2azPOA+xIanV26hRHbWNwgN2LzYVNif2B+eec65x/lLTGvEO4ZH61NSjrl37SXUUUN6ALCoyRRDdwgOiVkjLbWxdalhHZD3A55cpU1fWrZsbavksp0wVHxkT3bo9gzmA8WHjxvlxrjZiSMI+wUsEjRiRw4THkDHhMR4Kj9u3r1WPjivFwFXPDG86TUEQEhE+qE2DZxCvE8XSMX48F8OuQqouIYcO0UzmGEK8J4INtXDodIjHEq+102wFwzusrk++BGIFqTUYxXjGHDDgqLtG9BvRU0QLOmlQpJeT1hvTKbfRgZNqnSpVctm8+Rd39+fZs0ertw5DgXOBQrwYzBg7RGAG71iO4UhRc84fjhO/P50qWeQj7JDSEJKBjeGCQEmjHcfjjXGAuIsAQzMYDIzIpMBQc/Gll+54rtkXok8jkqaMMEo9E4SoN95op8Yr3tzoSqtlAUH9S09vLIIXjXBofHIvga1q1UbqqaWjmy8Ij/xupUo96/77k2nDpUL5u+t63k3g7aiX2jJlylApX6GEHuOLF8/LO0Mnyf79h2X+56PCJTwCxnGDBh1k0KAeungfN26mpsI7dOvWUn9bIksxkvHIRxYWMIyfiAL8FpzvjriFMYsoHd7zhUU519i4ca5SC7EB++CUJUCI5TjmypVdO0JHV3Slt2Gh66QaYiRTvxanW1z8LjENYzENQlgUsXBkjCaqCfOHBeucOQt80jvvC3bVwYObNbIOm4C5dfjw8RopXa1aeSlWrIjWOUMIqFq1rNStW1Mj0jzHBsZA5mDsJhbZROhiUzFnUTYB0YEmKSxWJk4c5o7K6dlziAwe/LrPNdUIbc6jFtz06Z+7G3kBpXyI/GzZ8g357rufNeLNsbmIsmI+JGooLoDQlD37/VpqhxIglPLB5p0yZZ7WqyNSkRRybGTqz3J94dD3BEGOztHYWwiaOHXJdMCuIkW7Zs1KoYrPpJUiNNar11odmNjmOISpaczj2OuRsalCisinPAdzbHjh+qhWrbEKPERrMsawBolOJxpCF93DPWENgn0ZlpPYs2lGdNavi4rwyLjLOUS5BSeT46OPwl8ju379durgGDNmoDpEeT/EwZ4935ElS6ZKvnzhj7yjFBPNMBibsNvJCsMRwnmBA4UsD35fMpNoyhdZO5mGH0SEMwfxHlWqlJXHHnNlWnEtIBKH970p+TBkyJgYre9+L2j0R5Sxsw/lyr2ojgns0FdeqRdnA3PatevrLlNGyjznZliOlIQKOgJOReYznIY4NwhMIMAHB8mkSZ/6pE3l2DXzdw6PlYjHho++6ZPHxZvEK+ExpFpEpPIxIbmaxfys6UAQVv0yFiWffDJP/y2vR1jEE0K6IoMqYpJTg8SJ7sKgXLvWlYIZ1+AUoOg/kYx0cPR8HGMSAy+m6sREFaIJXanwVd3eSOqaYAyTZoL4Q33F4cP7yKRJszW9k/QUvhseO5pxcAUgsuANfvbZJ93GwGefLVKDmLQL3otb0nIweFyC0sOavuqZcs778jqnTiL/nvOPRdc777yhYh+PR8Ur+PLLXdQL60CUxNKlrkjde4GhX6GCKxqRlJbgC4PoAg80+0h6vdNQgkmcSEdP7yvGHanpiLyIqnRPxWihTlh0GchRER4xQOhcTYouhN/QC5SAwGvy3bd05PxYZs3+QFKnTiFz5y6XRQvXSN16VeXlJrV1Ue0SHl0paX7ijEkhi0cs+oYOHavnH8YQvyedxRHPWLSx8KMGKmk/EdvfmIPaQr16vRtrKZROtMzGjZ/fTlO/KOvW/SDvvTdORVRSpeji6utg4NGYgw2hh8UKzhLOBb6HA2lbRAURPRqXow+iExqccR1jByCKcOwwlBmTOIblyj2b4I3B8NpViI+UZsGpxxiPbQREDDEnhsbSpWs05RR7ijmbMZnod2ryMb4yV2zdulwFyZo1m8pffx2WH39cHCPROt4AQXvgwJHy2Wcj3Y+5otQvaykMX6jFFVqtMzpOP/vsU1K3bnVNpSQi8513xmsWCXYzgjGOHMaXL75Yqc0MnDFq5sxF+hvi2G7QoJYULvyQZnswn3NM3nrrfXWiueyqAL2PXYUdxfEh8pOgAE/7HKcv0fscN+wE0paHDRuvC15sH/5dVMQBOimTeuvJjh1fh/s9nYhXGvN4/t7RDWVSSDOnCQ/RgghhZL1wvDzroWMTODbV5s075PHHC2u9zegsYRNZ4RHncv/+H6qQ6tR2jUhAA8Ehb7wxTMcNBGzeBycsddM7dHgtQqKjY4PSeHLHjj/0PZw0ZaCBJfME84aTbbRgwQQpWrSQxCZO+bCYtOHDc84Ttc0cClu27JQxY6Zpw1CuG64fXwenB413sKewq1gHIjpzPTnzGuDYYL2PY9dEyDvXDfPE3LlLNdKdFHWca0Qgd+z4qlSoUM8nbSoTHmOfeC88RrabWdDotb81eogoINKQeYzFCqkLeDkffbSQfPFF3E7bi6vg9WNB41nwnRTQYcN6a1drjFuMGicyiJRrUsBIF6WQNPVdnOYdRHbhbaeT7r2EVi4bjB1HVPvpp6Ua1cek++qr3fUxDGmEaqIeSFWiEQhFy6NK8A7Xwbv2hgXRhBh+EFIB95gSnYgaJcqUWl9OV3KnPg8Ly5o1K6vgy+8R3am24RceXUNhoNySBQtWyPhxs7ROp8OOX5drFIO+JtDVCdDPzxlLEgXxBJJK9sWC5ZIpc0bp0aOxbNy4TRZ8vkbqPFdJXnmlVpAI1SertZXq1ctJnz6txd8/ebC6jyELdZzvlH/A6OZY4jDwFPWeeqqJGs8ROTdiCtKIqI0bW8Ij1yjpVM7nx6Wu1s8+20JFs+DQ3IuSCCwuSV2kRALNtnByOF1BQwPDcM6cO6mxCTkK8sMPJ8uQIb3kkUcq+6SRHBfsqojaVIDgSJ1XFnoIVMwJLPA5L0l1Q0zfvHlJhOtIG1GHdGEWlPwenrRt+6o891w1tan4XUgdx7EKRN0RscpYRbQ9TlsW7szlRMpOmPCOjjv3gsV/8+aumtlDhvTUrBLPiD1o0aKh1K//tM4p2BfRJb4QYbtsmatOJvX2cOCEB5zK1PQG1gTUt4xJiL574onnNYsLQZHjzG9FFDJ2K38nTuzvtqlwtMTEdRRR4ZF5ilIwRP05jBr1driaD2FvIxCR0cGYgV2dIkUyGTv2U83MInPBM1KWEkmIm4wh4S0vg0MFQRubiiCT119vE6SECXMtda4jGg0bk92MI3KexoTwuXAhjfsKxqmu1thInTu/fdfjrBMpoXb8+CktTURt9E8//VAFNsp3EbEaFmSehbfGaHyFsYlgIJxSTz7ZwCdtKhMeY58EJzxGBDzz1H+5efOmejmqVHlCC09zxNKlSy2PP15Lw+UnTRom8QVnQglPpBRp2NT4ILoGT69TSBzvNbXoPFOOqHOzbt2dxjzRDYttxB4MXVIi6tR5yt3VGpwIRIwyUnNoNOR0LuM56uPh/eIxRxzBy44hTGQCdYycCAWEJSIAMOao50NXOdIeeQ2eUKLYhgxxpa0TRUkdISI6SFcnHTI6jU9g4scACAvqcLVte6cUQGwu6lhUEtlI+rk3Jup7C4+BuriZNn2efPD+VPejo0a/JcmTJ9Uoi6JFC8r999/vFgQRJ4MSIMuWfSOTJ83X8YL0ufovPqXnRaeOg6T2sxXllVefkjRpUoq/nyMuukTM77/fLq1augqOv9WvveTMmVXKli2pY45n45nTp8/J6tUbtGbirFmj7mr2ENJ17EBpiTp1nowV4c+JBvnqq2l6TXgbFiq1ajXT+++/31cN9bgiPDLGOmUvInqNkZLIv8eRwvlP9DpGtWcTBli/fm6Y3XRjGzoo79//l2YgkKYbVlTdvcBpSNQQ1zXfmZrAmzZtl3HjpvqkkRwf7SqcAAhTzJfU8aUEB1kVlPto3Lizilfbtq2IEynW4YUahD16tA6XQPbaaz30PK9fv5Y72hNRhPI4ffu+H+S10d2ILaR6Z7w/dtXHH78jBQrkusumwk5CwGc+8ixbgZ2Ec5EFPU5dBzIcTp48rREyvDev571Iz+Nv6k5TCoYxK2PG9PLoo4WlQIHcGlmJLUWUFemvNE/j/JkyZXi02REsmh27NaysqJCaB1Hzu1WrRhIbYL9Qv5xb5lhvZCiFR3j0FJIBJymZPzTE4frH0RwWnEP16rWS5MmT6zmAg5XzjHRYotBIzw+pLiqOjMcec9VLJBME24cAkeDXCucdUdhkEZFqjWgcVkQbZSWmTZuv94m27Nu3o6Z6e5tnn22p5z/9CV57rX6s2HVPPvmyRtaWLVtMa/6TbRMXhEeuW+wizpuIOMw4V5YuXauBFJTPYP2ETUVTrI8+urNugF692knLlg3FV2FcJluBIBTGUM7lyJ5DrDUYs8+cOa9rOo4TwTcbN37vkzaVY9cs0FRr7167ly9ckQaWam3CY2ggQlG8n0mLlA4HlHyMwnffHaspvXGpA2NEPGkOYXWgJvKucuWGKoJhBDz5ZDk1QvEAe8LANn36iHsaGZGB1FNETva7dOnHNOyfRRI1Hj2Fx8jQtGkPNZiJVCS1iPQwojQoqM5v7tR5ZPJi8CWNiDpE1BAlosPpZs3Cqnz5UpIzZzZNZ48uGOBJD3JSQMISi5lkMK4gvp2zURUe6ajoGd1RpWoZeSh/Luneo1kwwyRRmMJj/34jpewTxaRmzYqSOHFSjYrknGnUsKvMW/CepEzp+rfBhceDB/+RWs+0DvJu77/fW2rXqSqJE91ZsFEfFNHR4V7iI1AKgsUqUSzQv3+XCHdOjY6xlGsJwQdmzx4T7oLs0QnRFkTpEJ189er1OCE8Rha89LVrN9Oo15DECYQMorNZFEa0S3l0w5yB8U4xfwQFypY44iLjapUqjdTAhyefLK9N38ILNXwRLom0pjma46jBOcCi6d9/z2iafYsWXX3SSI5vwiMN/H77ba82lnHALiDyibplbEQatW59xwaJD3g2n7lXB1si+YgSB65LBJr163/QKCxPeI+o1JwLDUQbHLnYPJTyoGYhDtXoiGgiEo1MEWr+Uk+P651MCK5HIimLFMmvkduUswHGBaLQsKm4JSXSibBdtWqmOoyje+yi4c+777q69i5YMF6KFi0cZhfcmBaAfZWwhEeCADwj76nFSTPLfv06h9oMJSSIcqT+K//OOSfgzTeHaadmzqPwRLBCpUplZNIk13XnXDOendmBtQ5rnrDg/Js+fYG7WRT7RRNJbxK8Rmbbti9rFGh0jwX3gjGidu3mWj+fhp5xQXiMyjGfPXuxZtmFJiw6HdoJUtmy5SuJzX0lAAhhkTHWJeDXcJ+/fAfKSzglpNjX8Jb+ICDLVUZrt9pVOLNxCpA953we1/rHH/umM9eEx9jHIh7DmLRSpEih3eioC0ZNIy4yUnQBrxiRfhHpSgx4+og4IUUEQWvNmtkagUc0HIOWE7Yem7AoJdT888+Xa3e84A1BMIwxhIsVe0TD1vF4kUrLd8OozJYtk3Tp0lyjIGN6cO3adZCmRtDZ1RHTnOYyURUeiRIkDXv58hnuz8MQxtBAdB0xYoqKfjQaIpKRiE8MGcdjyv1t23Zq8XwWzDG1aH/kkafcf3/zzTw1gBn8N236RSPvSD0vWrSGGva+UvfPd4THQClY0LV4cCCqedDgbsgerlcEBrjTqv3ElQYeKDeCpmcH3pTn63WWOXNHaeSOnySlp7U+99FHEyVb9vvlhQbF9G9/P5eXLZGfy5A+9PcpebpmG/fnly5dVM+l3bv3a0Q1Xn2iszivW7XqpYsvonpZiJFmFl6IJCKChugiZ7/D09QmOhe0pLg4QjnRMRwrnBZOZ1vuc8vfFFsnTezxxx92R1NHB3Ep1ToikXzMT4zHX3yxwn2tz5w5UtOHQsKJCtm9e63Xa/giaAwbNk4dR/y2zLFELS1evEqdR5zv48fPVMMYZw91vVau/DRcCysMa84xGokhXNLdnSYoRE6F1ITLulp7R3h0ul+zsC9e/GH53/82q3OOjsaeC3+ieCIS7UhU+cyZC7VJBE4OIngZ61gIMb5wXvlC13cir4naI+IPR6wn2E7t27+lNcS4NhifGR9Jp8XZRDQgkU1EfHlGD8YEiD1Nm3Z318R1iA7hkd+qRo1XZeLEd7S7t7OQxY7BriKiCHH62rVrsnDhJH2Mf0PUt2ODEa1EAxuORXSXZXEg4nLOnCV6f+TI/lKrVjXdT2r94RghqpA08549XU6Q2BhDfVl49BTagWjD6dM/iHDDEdYaBC6wvgj62X9p/dRZs0aH+m8994Hrn67iRDdS+5gGj/zNmoH58q23PlBbmcZziJPBG02GFT3HWMN1G1s4+w84CJg7uS6C2lWujVJBiMCsWcKbgh5e4kqqdXjBduC3/fbbLbpGp+YwcJ7QCCm0653zrl27V6R795Ze399PP10oixatVPuP64a14J49+7X7OnYVvSvWrv1eyxQQqUtQTOXKZcP1/thJzLOsKzl/sKmwzZ2o9bjW1fqL32In4vHFR6y5jAmPoYBxQ0g1dT0gqvX5SJPs23e4u1uWA/XXEBQcEPq6dWulE0hMGVVRhUF45Miptw1kV21EJjsGILxA5cqViPGIOoS/119/Vw1T6up4HqvoEh6ZQPh9tm//OlThgwUxnk/Skkh1Ca1+GothhEjHgI5OMNqpc4m4xsRABIEzSToRFs55lxAN5LCER0TFQoXu1I+CF198Roa+05MzSf8OCLzkjnL0l6AL2AC5oreXLp2Rp6p1k06dG0mDl56S5MkQtVzXQKtWPeTFBtWkfMWHJEmSRBLgd00f9/fzkzNnLsrhA36yevX38tXS/0nxEg9Lo0a1ZeiQ8TJ+wtty4MAxGfnRNKn3fA1p1+5lOfXvWalQ4UX99w0aPCNDhvb0EBGdceTO74sgGrQWZXBcj/vdbm7jDThf8bhSrymiIOCTLh2RLu4hCY9EPGbOjAAb+2DQPfPMa/qduFaff/7pu1IyiRalzhARjIhvCDNc5wgSwSEin39PIytq2obG6NHTZPz4O10pvQHCAc0rcFB17dpcatSo5J4rPLt0I7hTo4zHSK9k/KTphJMmxDiKWEMUGFFPzAOcG8xNc+cuUVEDoaZQofz33CcTHr0jPDJnT5o0R1OtHZYvn6616SID5wSO4D59ht/ztUSHU6c7OjMOohMchWQvkD4JXOOkIiMckCZKaZiYsB2Cw/GcOfMLjUDleEVXF+Pg0Zz3akREXV4cymQMINiGlqVBJE9MpeSzwD5+/KRMnOhqGsl440BzScRPGDiwu9a1TGhERHgEggMi6gDo3NmV0koEtOf5SODGN9/8ICNG9HOXwnJw1Ys9LFu2/KqiHNlQdLpu376vRrczN2KzExAwbtxgFUNJmUdEpCwATUSCn/txAYJjOnYMf2dwBxqpUE+VutFRITrGh+iCNSBlExhDcN5Ur15ef3vPdSIRgQSWYDMA4ys2GOs0z54BwHmB4EjUbFjHySnrs2rVZ+5SXt4AGwbxGbsHwdNzrnj99Xe0riq/M2UqKNuDPbl69beydOlUPf8ZR3GscEzILsGm4nqgESsiP9G1PEcpAmy2e9WNN+ExZEx4dGHC4z2gK1zDhp3Uo0XkBQLU++/3Cbd4g7H92WfUAVypgxIX7htvtFFjhsglDE6iKlu0eMntDUcooaZVnjwP6iTK4ssVnVJEypcvoZMxEXYsUBMqTgrGhx+6inp7El3CIwMxaap41lnMh/W6kiVd3cBpJEP9D08Y1Nu27a2GUEyn5HC+EeH45ZdfS+/eQRdk8TGFLToiHqtXf1nPF4ff/1hze5HjEu327P1dMmZMJ/dlSB2q8BgQcEk2b9otmzf9KVt/3i0jR73tjhZZtnyJfD5/nfy0ebfUql1aUqRKLAcPnJAjh0/J/ZnSycOFC0uevNnl++9+0XqPoJ5jPz/Jl/dBjfrq0qWZVKpc2t31Wkvz+jmCY9wSHoN3m/7llxVh1knieqaEAWMoCwmIimHnK8Ij379Wrdc0itpV7y6djhEOzAlE3TD2O9Adlr/pjMuGw4eoe+aGiHTJ5fwhUhpRY/jwoN1coyoqI44++GD2u5w1GLLOmDRwYDf1yIfkyKFkxapVG7VuUI0aFfU9iYxDROU6RrgEomCI3sUpSOQkQgHR99TSC0twDY4Jj96t8ci5V7nySyoWYFeRqkUqZUTqv2I7IWAR4Yh9RPkG5j4iwhl3mZPpdoxozbnEOUT2AR2WiaZjTrhy5Yqeg/Xq1dTsjoCAWyq4xUbNNl/h6aebaqPEkASi6BAW+I34PRAE7jXuUMfPcZiG5BwhLR8HFuMknZ1jsmwFYxn2O47d+fOXBXn+XrUg4ythnQ9kRBHB67BixQyd4xy4ZhnfQ0tjd2AuYA1GpNbrr7d1N1Lh8alT52rDT8YRysfw+xw8eESFSJq/4NDgd8HB5sD6iXqRiMjY6kSmec5TTt3SuIqT/k/wR/Co6uDgwCNqFwcwNmanTq9pdk1cFx5xbDlNP2vXrqY1W7GVgOPi1B51IPKTx1mn8bpEifw1whnnJ46qiFzbMdVIkU7rCPAhRQyzDkZjGDCgS4illzgnKH/GXElWwFNPVZC8eXNpqjW2NYIk60Wc2KxzmYfJFnAce/7+fjJkyOsRqq0dF4THhbvel1Rejni8dOGK1H+4l08eF29iwmM4IP2LsHUmMmrU0CilTh1XeiYLH6IjCc3nAifc2fE2cCG/+mo3XSy2bNlIGjfupJFxDGYsNoncYfFbtmzxuwapw4eP6UDBpMr74anBWCN9zKmVtnPnavU8IF6y6OzXb4S8+uoLUfZcxQWYLJkoMDqDw29w5MgJyZUre5Q+A6GDjdSLsFJE+N1Xrvyfes9ID2XB4wnRPWPGTFfRj7SyPn063JW+HhMwcSBSEJF67txFPUdiu8NxbMAxOH36vGTPfncB+kC5KRMmzJTRo1wNNzZ+O0cyZ3a97vTp07J7158yeswnUrlKUWnV7kltLAXO5XojwCX2Hb30n5z+94K80+1z2b/vmEyZOkAqVawapB7kqlXr5bOZS+XQ4aM64WfJcp+mRLCwwRgmcqN8hcfl1s0ASZkqsdSuU1727/tXypYtKon8nQnyzjgREOgSPQMDr931rSCR/x1hJzAwaE1KPz/nPLhdszLwZgiGkutvJ73c+Zvv49n0JjJMmDBLRo1yXScR7bxN5B/XGzRr9qKWqQhPZJsDUTQIj5kyxWxH97BgXHEaRXz77RdBmscwnowePV1LchD5PmzYmzr3IKZENFUtuqAjKV3UGUfOnTsv585dUCGRSEPmH9LXEPtITSJigEhEjGVo27aJOtdIoxw+fII8/PBDsmiRqzZVSA6loUPHaHQCUUREkVP2ZNCgHloTjnkWYYjFYvCyJCxQCxbMF2ZzgJCgKH6ePKUTvDHoLeERqNm3a9ceyZ8/j4pRzI8slLGZcCiwAESYJ00aR4GnqE7tOJ6nzhZpZN27u2rJsUCkNAORtAUL5nc3ZnHAniKVkvRrbCo2zlGawznR1zRiQsSnVhXiGw4Poqs++OBOY7b4CvYU9uqiRZNCfP7AgSOSN2/UoniouUpUFmWK7mWn4kxgnERgDN6YjNrF5cvX14gc6oVynhC9g9M1psG+RLhOmjSx3kZ3ympcIazzAVGrWjWXk5tgC7KSPLtT4yRatWqDls+4lw07d+5SGTx4tK6jaJIX/HxCaMJhx3yUPn06SZs2lY4drJm4fe656nqtk6HFXPTbb3/ouecL5ReiE+bk0qVdkbesWWiGGl6og9ykiasGPLXyWZ+QghsRuyw6xoeowPheokSdULul//LLLmnUyHUe4vSoW/cpjXplfRQb6yLsOWqQ0iOB385lV11UTQBbB6cYdhW2Dmt/xjYa7NFjAIfd2LGD9ZynpiSsWTMrxEhdbDHKEqBh9OvXRaM627TprTVSSbtHhCeK8fvvf9Zj4rkO4PM4roiTEcGEx5Ax4dGFCY8R5OGHq6togPrPRY/HjnpSCJAIgp7eVyIpnn++tYZ6Uwic+lsMMlzkIUV7hBfel3SyjRt/Ug8e3g5gEUg4NB2OGWRC6vYWX3C6NPMdWagg4joLzugQHvG0Iwx8+eXkcHVMJFKnUiWXCPrQQ7nVc0SkJItmmhDx2Jw5Y6VUKVdkZLt2TaR791aR3j8jKHj0fvhxixqqnPtEdzJhI5CFJTwio505+5+ULeMSgtetnybZs2eWnTv3ylt9R0upUo9KsuR+8tPmXTLo3YaS6oHb51iAq4ZekkSJZeOa3+Sd3p+737F9hwbStWsbdxQh4qbeBl6Ttm0HSukyuaXe809IQApXnchE4i9+V7Oo8Jg4iRPR6KRjpwrSiIYYS9d2J9ryDs6/ve6uIXlHYAz2rW9HQt4KPH97H2+4a1Im9nOJYNSpdOEXNDrSz89jf5xoS+cv1755PhK8jiQlMwsXri5jxw7UsTAydSZZRHz00RSNeHBYsmRKuARIXxAe//hjv0Z9RKVDszdARGRhh+hIhCFzDCJU+vRpdB5k4Ud5CbrUIgZgszoLHoxbp6kR9X7pUItoiHhIdIUnzKX8njjm6HqKAY1zrmXLNzSdLiYakzmY8Oh94dEThAUWRjh0XbVsb+rnkXaMgBE84o1GVdS3RbRgLKIZCClkLI4iG2WC6Ea5EqJHiNal27mTYodjee3aOfqZREnFVzgGL7zQVv7557jW7urWrYVe29ElLHCNE1FJVFVoDQuDU7jwkzqnE4HzwANZZMyYQdrgwakLitOGRiNEMCEob9681GdLFMU1sGmnTp2vx5+N8d+pyxme88FJt+7Ro5UKfggYRLxziWbIcJ+K+h07NtX5Irjw4ymiud4rr5YwCkksJI2UjXWXZ1QlcxdOjdhy1nmbatUaaeRiZEunMJ8z/lHf1AHBmGjS8ET9xbbwyPhC+rDTRMWXYX05YsQkqVOnujYdxXmRLl3a201pdmhdaiLysXMRDhGBec5TIC5cOL9mz3FN8Fzz5i/d1biJeQynHmMuQizCP6VJWDMT7RtTmPAYMiY8ujDhMRILRgxTFlBMxggeeOTxmmBAU0uIbplE5FCI+urVq/LBB2/FSHotC1dC5fEIs18sYvHgU58BNmz4PFyiWVwFTzeRQuvX/6iRhq1aNXILj4cPn5DcuSMvPGL40EWYaAcMrpAiK0My3KF4cVIA71PjCsOKdMmZMz/S54iYJTIV1q2bG6EOf0bIIMATPffcc1Vl2rSF8txz1aRT52Y6yaZInvKewiOi25zZX8m8ecs0HfvK1Wty9uwF+XBEb8md5wHZt/936fXGWPnj979k5c8D7xIed/96SLo3nyqz5/eSx4uW0cWvv18at/AYEHhDI5ivX78s//xzUkaO/ETKlSssr3VyGeaJ/RJJ+mT5ggh30Sk8Mh6wTwg/viA87tj+h5av2LPH6TgZtZQUImOoY0OqVXjGPYRHIlViO9Xa16EQP4sQ0pVatGgY7VEBGNQsFBCXcN698MIz0rTpC+5FDtEJjO9EzMRkFL8Jj7ErPHIeEMHoRGtwHX/11TqtqUVZGWwqFmWk2G/e/Its3/679OrVNkYatjFn0LETcYvPYx5HwGDMgNC6mcYXuBZJYydymGufCFDnety//4jky5cjSscW5zt2MkyePOyeEYoIRzdu3NJ669Sww85DxGLOp8wO44NnqRtH5DKiBusIREfEHARDIp/GjRuiIp5TU/NeQhPC4tixn+rvg8OKKC6yfrCneT9qZOLcp3Yv17on2PBFilTXUiChlbbCRmesoIPu4MGjtB4/pYy8ATalE53tKyD0RlcpJ3oSTJ48W7t3A+Wj7uV0ier4kBAgMOjdd8epMEcWR3SvzxljERuJYiQDBCcMNWhx3ADz2qRJs+WNN9pqDe2YctLEBeFx0a4PYiXV+oWH3/DJ4+JNTHiMBphQuaCpQ4X4RxoBxcCJ8sBj7u2aIdROqVOnRYLpYIzwSyQhaRhEnSIKlylTXMqUubveRUQhDfbZZ1vKypUzwl3rA0MLQ4mFenDDGrGaCMgXX2wXYu0bIyK4RC8WSBQQz5wlnWz438+SJm1yuXjhquTJ+4DM/HTsPYTHoL8NqZ1p0ibWaCtEYiIdT506K0u+Gi6NGvaXoe82kwoV70SpBch1TZeu/dQQ+Xr1GElyeyJP5JfWLdy92XuIHDt2Si5euCQ1apaVg38dkuLFH5J6L7giw24EXJZbtztnJ0/kmggT+7uMRz9JHlRUlGsSEHg5xNqOTkr3rcALMnXSavl49J1aVL3ebC7Nmtd1p0jfCnQ5J67dcjWIYoxK5JckiPDofv/b9SHviI0Ios7921Gdga7oTUe8vNP1m+euBEnZ9rvd1dt5/zv1JRN51KIMDEX8DAnXay9cPCvVqjbV8WDRlx9L4cKu1Dw/v8RB0sVNeAwbFpujRk3TCC86EMfE+MS4SudcirUTDU7adPAFE+m4jJN0kV271tXgISYw4TF2hceQQOxwOhy76l+v0C7PRH5Qv80bKbWeUCOSmqjw229rQm02F5949dXuGlWDaETDgWLFHpU6dapGSz1DnK8IGU7NtfA4dZMnT6qpsyGlNmODk46LaDp8eG+t22lEHsT3Dh36SZcuzTViivpy/O5kW/3vf/O0jmp4I9woxYENRjM0IuqoLUegBA1NCBqgJEL//l3uEhffeedjLZ2A+BgchGeez5s3p84llFvBXvv0U5eDPybXGQ5hlQyJLyBkYQswDhNVTmfk0DDhMWwoLUAJHRwjpP/HhC7wySfz9dpFVMyTJ4d2kw+eOk1jWDKFvvlmXri7t0cUEx5DxoRHFwmvInI0gUcOjzhpP3jtEB0pfJ8rVw754ouJ8tJLddQbFhuFiqkHRj0UBhWMBtK7I09gsM33oOYFYBQh9mIUUUOuSZOuumDBWI0seIRI8yCqKrzgFUb8DGlxhPHGwsnBSUU0Ig7RdTt+3S1z5ixVQ7RTlwayet04eaJyAfHz95OerzdSMc4R5O4Fvw2/9X2Zz8kHIybI4+WyS9P2lSVLtnRy4uwhWbCon7w7dI58s3Grpk87KdTz53yrBZuTJc0gif3u1w2R7mbgaVmzbrWcPvOvjJ/aUkZNay7HTx+VzA+kkieezCuXb13QDdExeaKUuiXyy6AbEYmuqERXhCOCHpurwzaPuz7bEec8NyId27ZrIDt3fyrjJ3aSDBnSyDfrN8nlK2flxq3Tsn3HVpk7Z60cOnxCxcbE/kklIDBArt66otvNwP90Q5zULeC0bgGBF3VD6LwVeFE3Z18QRF2i6DndnH9zK+CUXLx5UrfDl/bc3nbodvDCNt1OXd2l242Av+VmwEndrt86pNuNgGO63Qo8rRuiK5tz/F0bxydAkqe8JN9vGq/HZM++LXIz8KRuAYFX3ccvcuNYaGOgb46HUYE6P0SjMncQaRZTThHq3iI6dujwqtYaCilKg3GS9LngtZqM+AuCxIABH8pLL3WUdeu+U+fdvn1/y7RpI7RpEKm/3hYdAaFx7NhBWiLn9deHajRXfIfox7Nnz0nWrPdL5cpltM4YDm0i9rG1ogKNGxCgwgtRdghTodVTJM2eRTa8+eZ7Udq3hA5i08svd5GzZ3E8pJHNm5do6RpqwxHt6zTNCy+M7dSSozwS6dsffzxYu7W7RK0BGlE8YMBHIUTebpWqVcvd9X7Y8++9N15mzBghEya8o2n7NJF6663OEpOQzkogx6+/fq2R0Kz3aAYKfC/qxP7003ZNWY4vsH6lSzJlMJzuz0bE4Nzo0mWgZicijAevoxidcyeZlkSn8hmUgQv+OUSId+jQVAoUyKvncEKGQxMbm+GEqxjhhlQRiiNjkFEYlgL4pKRhSLVp87JPFCxmsCH6j1TsqlUb6SKvfftX1QvRu3eHeFcDh8WxZ2QnojARj35+gdoY6KWXOmhtGryidD2NiMceA4iw9ehe7LCI6dz5bW22QFHhbt1axuluerEF4sSkyYOkbZu3pUrFNkGeo45fZDn93wUp9cRDMn3iWrl+7aacOX1RHi2UXy5cuCIP5s4sN67flNYtxsrZs0S3+su8eeNCfJ9ffvlDijycU3/bZMmSSPtuz4i/l35nPrN8xYdl+IetpHXzkVKyWMgdC2vULC5DP2gS1Yxnn+DK5WtStlxBeaZ2+CJpvAULI4y+kIp/+wIsmEiLY3HFwpBI/ZiCBSdlMkJrYuEwYsRkfV1Cbd6QUKCG4owZC7TpHqIWIhdOW7pPT5jwrs/UqqYeLSI5qWoNGnTQ7BZsCupSUtM5vrF+vauOokPOnDklS5YMagP37/+h1uLk++MYiEgdPewzShRF91hI3Vg6ygJCFnW0YyqiJz6D3bB163IpUaK29Ow5VOvRIZoAEceRhXIz/Hsi2YmiRbzGFqdMVfbsrpJDdN1dsGCZipHU+nXSuj2hfBXBBo6zijTt4KnaMUmyZMk0uKR798FSt27rUF8XkxFl3oaxbvr0D8SXIB3811936znli2snsqamTJkjmzfvkE6dmmoUYkxCijWlarieQoNoSAKlEMd3796nTWoMw9uY8BiBQaRSpaCdiOk4SloaXjeMT1+DAQiRkdosb7zxru4r3quICY++N6CHB+YhFs9du7bQwrrU2/zyy69l6NCxUrLko9rlznV8kmoqHx6i4IIjBhd1HunA6NlRMboWMRj2LKyHDRsvEyfO1t+FGi1ESzqd0Y27OXL0gCxevF7Gjpktzz5XVb5a6hKdu/doKNWql5Cjx/+W5EmTy8ABk2XW7ELhPpZOZGTAjXSSOHFSWbt+h5w4eVbmLX1TO1jelGtStdaj0qX9JA1EfLpOceneua0KKYn8UwWpcegn/rJ3zwH5ZMpiSZU6mTRpXUXOX3dF3jrCY9qkKfX2ZsAtuR7gSk1Ok+T2v7+d9uzUa3Qg4tHPL2mIEXfOv/ELdJraXNProEyZAvLTzo/k5o1b4nd7xE/s77qzZete6fDaBCleNo8883xJfezSjat6m+T2axK7hfqLt/c7tzt12UmxdupO3jmWrhqVNwJu0jpH72dI5hKQLt28GmRkocomXL11WS7dPO2ue6n7kOiC3iZP5Po8/9up5670adf9QHG93+WbZ4Rs8BETWsjFG1ckTRLXJyTyu+9O926tZXlTxC/gdndu/3uOc3fqVgYGqY/p2od7T6GUfyD6mgU63RZ9CYqVjx07XcecPn06SJEiD3lFaMqWLdM9u08fO3ZCjxfpnkb8jazCcesJ4zX1PitVKu1zC0r2h1INCG44dhG4SEGMj8JjcPgpiHp74YWndUNIWrJktTRu3Fny5s2ljhXH5uTapjO9p9OAdOkffvhZs1CIUEQYjE747B07vpZffvlNmjV73d2pnGaLCFvBu5wbdyBdmd9l6tR5Kgw7Yy7CBAEVBFiQKj169DRNGY2MiMK4j0DYtSsNgka7hUOuJZzwK1d+o9fX8uXTtUFgSNc+UZg0KOIaZPyIrfGBfZ8372M9VuCZJu40aapXr7X89JOrnmlcJ3g38ZDw5k9B6YsOHd7STtVc8/eyJbwJDWFwgFByrWXLl6R3745e6Zr9/fdbVHi8VxmwatXKy5tvukp9GUZsYMJjOOnRY4i7uDjdivHE+ZpRHBy8iRs3LtDUBERH+PXXP6R8eZfAEJfAS+qZohzR40CkIxvHYvfuvepRdbrejR49wy08UrCa2mMYEjRVIOKCrmMxAWI19WtoOEJnToy/cuVcEwcd/Dw7Shoix48flrPnLkjd5zpKmrQpdTIvVCSj/L47h5w8eUbGj/tSRn7kKi7+4y8jpFmb6tK56wBp0+kZeShnGZcQ51GnMDhO/cPzF87Kn3sPy2fjLki2B+6T5eu3SNLkSaRE0XxSrEw+KVQ0p7z4dA2NYLx46bL8sm2PbNq8SX7esk/+O3VeatcrJbOn/08uX3aJb6271FRhMdFtAe/aLZdw5QiRCHzJErnExPPXXULb1VsuwTFl4mRBREBqQKrA5tHgJuC2MHblpuvfJLst0iXxTySJbgt4CHH62psu8SyJv2sfChfNKd/88q4k9U8s/rfrKwb6uV5z7bYYGhgQGEQMDAi8IEn8XY2bbgWec70m8GoQ8dY5zn5yS5InTh1ENEyV+Lbjw6nneLu+5ZVbx+R6gGu/rt9OJU/j1JdM5Lq9dftzrt7+rq7Pvl0P8vZ4nCZJqiCNeQICz2vNzTv7F6hNdW4FUtfStW9hnxf+wepXXnOLwv5+LvH4jgAZGOQ4XL1yU9566wN57rmnfK6DNTVN+/cfoccNJw0iAeMjTjYM1Hz5HnRHMlFDjSYgpUpFvW4uwsT163dKBXjCeLx162+a8s1tx47eT6s1vAOZI4iORBHSQZl0zJCaSPgaFOaHtm37uKOZ4yJEnJE6TpRzZMAuIsqQcgmUosF2wobBrpo9+0ste+OMecOGjdM0wKefrqLdV8uUeTxG7GcECDrC9u3bUZs4QP36rkU25xnR3MYdGOepXVizZlO5ceOGOthxxJOGSX1FGrb07v2e/r6U3iAKkdqfCG758kUsEpm0ZAQ5GmpwzZBuTbkNbgkOqFr1CY2E5LwgbZTxgUj8PXsOqO3PfjkRrdQHZf6K7fEipM9nbbhq1cxY2Z+Ewscfu2rjc674kugIODyooViixCNaG/nUqdNq89CwifPbifRGoKapXo0aFaPlPEas5xoODvYx9hulMlat2hjuurrxHQIinKAIb36mYcJjuMFDF1fBSz1yZH/p3n2ILF68Wosyk+bmawN2aF5SikZPmTJXo1+iWu+LY4FB7MnHH98xEjDCX3nleU0t8Ub3yvvvz6ALGYRHTyjo3LBhHf2+sW1c+QKkBlSu3FRrbRUrkV/eHtRU8uS9XyZ8vEwy3p9Ohg3vIAUKFJDdu/ZL40Zvyuqvf5Fn6pSQq9euS8cWE6Rdu3PSqfPL9/wcojh++32fZMqUXk78c1YeKZZLls39SXZtOyQFCmeX/A9nl6uXr8uKOdskS7YM8vfBk1K8ZGEpXjKnNHm1ivgl9ZMlCzep6Pjs86XljX4vyA2/kEUWI37DArxfvw9VvMPhQ/S1L4FDhnmAzqBvvz1SqlVrLIUK5VOBkQiuHTt+l1atGmlECl3jMVqjo1kZ6WenT5/RhgPB5yCiYehcS20vPpumBkb8BEdgXG5+9/77faV06efURiGimU7bjz3m+6lrCDbjx38m48fP1MZoUf0NGEdoDuUJC2pPiGClDnOzZi96Jf30tddeVLtpyJAx7sfILpk5c6E880xVyZQpQ4zvQ1ygR4+h+luVLFlUbU1s399/3yfdug2Wtm1flpkzR+o5UqdOc41K3LRpsWZ41ajximTIkEF+/HHhPT8DZ9b27bu0FiPlM4iMJZAAm5duu6VLP6aiIoImgvQPP2zVeQg7nRJE+fPnkv/9b5NMmPCZvt+6dXMlRw7fyzAzvAO9FRYu/FrPC1+s/4wzBicHJSnat3dFijLecD4jPhYpUkAzD6ld3K3bIPn883HRMm8wn27atP2u7D0cPqyfseOGDHldGzIZRmxiEY8JhFq1qkmKFCmkXbu++jeRddu2LRdfhwGTosYtWjRUwyO6vEOhgQcNA2n+/GXqqUIYjEnwJD//vKs2YZ8+HTVUHm8wRhgi6ZYtv8qgQd0loUOXU7gvYypp2q6K3Jcjifx+5pDsPnhIOnerLQ8VSiezZy6T9et+0tftPXhESl7NJ9eyu6LV1qzdKCUrZJQi+Z5QYcOJVMPruGv3bhk1crpcvHRB9vxxSB4qlF2SpkgkhSvmkZ+37Jeqw2tI3uvFJGOalHLt1i0hYav0tcSy7Zu9Mmpoc1f63fVrclouycXr1+XxZwvImKc7S8H7MskVmprcjhj0u+3tctKGr91yOkEHyo0A12M0efFMx07k7zrXE9++JZIu4HaEn5OefeV2dOSZq66oxlRJkrgjH52oEhabkCSRa8hPdDuSMIkTUahdrV33L950vc+F21GSRENCyiQukchfUmrnbKARjGt/XcfTX27XuL3t2EuUOINHR+ngRdedz779/onzSPJETiOoW8E6YAcE+TxSuJ1j5eCOoLkd1ZnqdnqLv39Gjy7bfFYi7bQdEHin23Uid/p6SB5JvyBRkf6395f3CAy8FiTPyEk9P3jgmHTtNliuX7uhwgRpWb64WCKtFdGgX7/OMmvWIqlYsbQ89VQl+e+/0ypGUg/ok0/mSaLb5w0RTdFRI7h48Uc0JZLoJDzyLCxpgsaxmjSJKHNXRK1h+CpECG/Y8Ln06jVMNm/+RRvi7Ny52udraGNTjB07Q0XA1au/VacIZYNiEup04khF/EMUjEkYTwoVqqb3Gc9IE8WBUbBgVTl06B+pW7eV1t8LqxZaQuGvvw7rLVFQiI7AOFyxYilNp8c+JVDhn39OBIl0JRry8OET+jx2avB6nUTTMm9QyoNoK0BgRBRZsmSNivZEOVPiw4Fuv0TKkmVEtL0ndLRnMxIuOCopS8UYgnM0d+4HpGnT+uKLMN4xP5BpSIkCuljToOeDDyZpNCQlvJzybAj90SU8fvnlKrfwSKQwkcObNm2T6tUr+Oyxii1YL3g7a9XXs2S9hV+gk6cWhzl/nu5r6eTcuT80tNkIG2od9u493B3JibfTVyEap1atZvLjj1+qsfz44w/f5dEJDmkgR46ckFy5wrd4bdfuLcmePbNGHjr1ACdOnKXGKnWKYrpWyaVLl++K7EFoK1Gijt6Py1Eh0QXHqHjx2no/W/b7ZOHKviq8fTD4S3mh7jOSO3c2ebJKe8mVK5t8PLOV/HXjrA7y565dkxMHz8gPc3ZKslR+cuLgOZk9v4+kT/WwLlDat+8nGzduknTpUstH81rK+bOXZfeNC5I4aSI5dfVqECHv0Pnz8uj99+v9h9Kn11tnHvn7/Hm9PXJbIC2QPp08mCbob+rUSsyQPGWQ9Gk/j/RoOlx7pkZnSu76HM+GNP9dc4l+ziNOivX5665bR5C7cOO6ZEjmMuyT3RbrU90WD91C5u3hP0XipO66j6evur7LiSuu7+JUQUye2PV8ofQ53I/eCHAJb8kSufaTjtqufXMW34ndIqLTBTy4uOekKVO70kl3d3BSlh2Bz0l3vnzzb3c6+o2AW0G+d1L/O8KrfufED0hif6drcqDWh7p85aJGtTqCpv9tgZN6juGp+3hn3xwx9fbxuB4g778/UT777Ev9m8V9/fq1or1GbEwzbdrn2vjKWWi+915vmTHjC+natbk89FDUv8vy5etl794D0r17Kx0DK1SoL61bN1ZjnfHdm52L//rrqOTJU1rOnTsnadNahKWD2VXhBwdW8eK19D4CCVFhvoojzJHeiuBE9OPUqS57MCwOHDgiefMy9t8bMmtmzfpS3nvvTcmfP7c+duTIcende5jMmhXz2UOhOY0RH2HFik/vErcSInSQx8kONJRBRCTFmdqd777bK8jxevDB7Jpx4vDGG8MkMDBAxcf+/bvIE08Ud4/tb745TMf18eOHardxbDGLMo3fRGR8iCh0OKduK5AN0aBBLU3T9zwffR1EyGLFXHME8B1wjFADvEeP0JsUhRfK1NDsaMWKGXq90RgqZcrkUrBgPh3nqavrLWhkmy5dIZ+0qRy7ZunvH0qqNHc3r4pJLl24Is8V7umTx8WbxJ2r1og28Lw4+Frdsf+zdxXQbWNbcBxu0jZlZmZmZmZmZmZmZmbmbhl/mZmZmZmSNAz+Z64sJ06TNty01ex569SWbVmWpat5c2fgD/TxYDhO1aqtpC2Ds0X0XvyVWW9w6PR580ZLCw5N0mfOHCEza2y1psoyvMETZ0DthH/BfECYgkmiKipWy4Ohfdfgwf3XiJfAHvHjxUK/PrMQM2Z0DBnWBt+/u2HNrENo2FNRPcRObI+6bYri4uk7sPZWzO+pAOTs49GjZzBhUhfEjRsTtlG9YBvVBg9eq6o7DX8rwvL3xePF2DHzxRvxxImLct+IET0ldCKyq58CAn8bajsOj0+fP3+TWfm0aVPg4cOnYUI8sqWOx1y2o9OLjb7DbK3WoOFPhF8hQ3gr+kILXpSePr0Fbdr0l98gCSKmnf7KUzo4h8waNcrJMYTe6C1b1hVvx7lzV8LGJmJC8wIiHXnM79ChiUwqMxn5Xwf9HVXSkT6d06YtFs9VMzMdmjSpJRNN9I1r3ry2JM7TboPeipkzp5PntGnTEB8/fsTduw+N7fNUWfE7p00RPVtJeGhBif8GwvqShRZbhw+fxq1b9yWwhQQ2iWy26v+J4Gfwe1179eodtGxZH9u2HQiT1+dkLf1TX716K5MB9FRdtGhCpAy+1fBvQyMe/0H4LTAzZSqDwYO7oECBXKI2YYER2UCZOFUE3buPkMLm0KFTko4XVqBHUYsWdcXLhu/x9asD3r37KK0mEQmeaNet2yFEBhMzVdD8O6QG8H8LGjaqioULFWPxhHHjoVyZ/MiaqYih7V6H3r3ao0vXYWjbWgmBso1ug5o9vOHq7gl3Zy9M7b5dZrpKlc2OzZuP4PTJOTh2+KYsa58RsInpjjtflNCWDLGYggy8dVYUfyruf/6C6x8/yd9xDMrYdDGUC5xH35SQlTiGC6sY1jawNrSnungp7bdqAqJKeqkpz2zBVlt91ZZgeys7k2KOrcXEF3cnvHF2NHldeyvlPS0Nikqd2kZtUDXK9rC0MrlPbfu2MKyjnUUUmBtSsW3slNtolooy872rg8n7vXX5bEyitrNQ3tvKTFEkqonbOp3fC0zDVbne/2SB/7RoD0B9vkH5aFRAGl5PbXe2tUgFa/Nv8reDxzvD+pqqLtVbtQ3cL7iNlO2kMw2O4QY3sAg6/Kz9Wl03c3h7eeLSpVvSJkwriJo1K/yBbWF6Oc7QB5gm5CrYCsdAgWnTlmDAgI7YufOg2HaEBTHA41yTJt0lITUi/HQ1aAgv8HfCCcxOnYaiefNeQraxfZkXy5HRNoC/P/q7suZgMveIETOwa9fSMH2PbNkyYvHiiahWrTXWrt2BmzfvRbhXOjtm6PP44cNnsYlwcVEmFanqUwm0fxVRo9ohRYok0hbNOqpEiYKivKLqkXj79gMePXomSdccRJ06lcRvmxNG7JxavlwJ8+PE1Pbt+0U9q1ppsG7XoCGkYIv+0aNnxcuRIhAmq/9pJDbrSSq/x4yZbXJ/pkxpRS388uVrPH/+SoK5eP0dFu3WrOHYwbV69QwJD9MQMFjmR3Tns9ZprUBrtf4HsX79TowYMT3Ax/buXRmhkuzgKnEyZiyNQ4fW/rSYJ8FD/5kUKYJX8PN59ABi4AF9OcKC7KPHBmegfuX1cPLkBXz69FXaW3hxf/bsFVkPfk564WgIHN8cPmHw4OlwcPiGRIniYMf2E0iRKr4c5K0sLWBtY40E8eMhT940mDV3C4rWyg6POFaIkTQG3Gx0KJpYUQCntFdO0l4+vq3KRExr32LnmaNCwj11VNqdU9tHN0lq9jGQaCmixTASdbZqirMBqpeimkYd3dLOSORZGdqD1fQz9X41wZr/Vj0dv7m7mLRwq2nZFobXtzI3N76etaGNOoohJTuKuVLkqGnPZrqofshCderax5cQlDZw5TOb6ayNBKAP3Exaq39MefZ9PbYxK4+prczqoyoh62X8XfiSfip0PzxHTdL20n+WW0szdWbX9PX9r4vSau2GePEUgtkUvtP2P7Z9m3pKmn4Wnb9U76C1a/8apinZpp9Fud//egbv1ZXXXbFiIyaMXyR/L1o0FsWLFxJS4smTl+jfv4Mkw65ePR1t2w6QiSoWzqEFj3MJE8YLk6Ts0EBrtQ4YWqt18NRjefJUDfCxUaN6SbhKZG0LzJq1nIQ00HfvZ3j8+BVSp04SorZnDvoAUkEX2u3w7ZtjgEni/msq+sBR0TluXH+ZUG/WrCcaNKiKzZv3YMuWPyNc8XcSJrxOYIo0CR9OPFHVSOKHJCX9MWPEiIEsWdKKTyTvK126kLR1Jk+e5JcdSRr+PoT0+PC3gtYSpUs3lL85EUVSn5MfrKV27FgsPo/8PVHw8vr1O7H6Ci04+U2VKFXKvzOU9E9otd517/e0WlfNoLVaR85KSEO4gsXX+vU75KKSBVmVKqWwefNeKQ4rVmwuSr/x4/tHum+BykQSo+GlIOCBmu0hYQWSiUzxoxfJr5AuXSoMG1YVPj56HD9+HgkTxjW2wdDoO378uJEynCIyYNfOI/j08SvsY9jIPnL4+HhYRzPD5vWnkTZNYqROmwgvnjpj/br9SJI2HorXyYHbBnWju5shHESDhn8Uixatx7SpS1GqVAHMm68ohgkqIFUfNLYmskju1asNpk5djKVLJ4X6fatV+7lXrwYNfwqYXM8Qkz59xsqkZePG1XHz5gPxJqOikAEd+/evFqI9smHfvlXh6r9HdWVYhfSxG6V1637iS/6rcBjWc8uXT5XPRjUe234nTFB8a6mCpIpK83kMGEzfJUHL7UMvXgZ+URHJYA8q1ankdXJyxdGjp/DgwVPMmjXC6OWpQcO/jpcv36JMmUby9//+t9z42+CkSYIEcWTSg77APC6y46NWrfZo2rSWtEqHBsmTJ0arVvXC5DP87aC4QxV4ROR7atBarf9JcGZ4506lrYbtEmyjcHBwNLYM0UexbdsGSJUqOSIbgqrGVCe/9+49Bnd3d/G54HPpExm2UBVSvgeUO3ceYOnSDdi9+4i0XNKjhEnKnA3u3LlZoK/ENMGCBZVkwYkTB0o7C03aGzXqJvcxoGLLlgURGrzwJ6BJ01oy+B0wlOfpk5dIGcML2zadQ/REUeH8zRVe5pZIVjE5Xri7YdS+43D6+l2eGytBDGNrdcZYyjzMCxdHk6CX29+V9upoVlaIZaPMkHkY2qYffFUUkDFtlO8kWTRFSZjA1nc/U9uk1RZoNy+F7PQw3M+QHPW9VKjBKP5tc7z03sZ2aXsrZV3Uf6vLehnCVqistDFX1svK0FJtba60H1uaJfYXAhP4CVFtn6Yq0j+MKdY/hapiDHgG1jdcxjxAVWHAzzGHzqCutDC+rqlS0/ez+V8XHcx05j9RCgZsVqSqGH3XUfLIDX+rCkc1SCcg5WZgys/At726LNWgsqTO3OR+H72Dn7TtoHwX6joo63333m0hHXPmzIi584YYtwmVkLzA9EtIbNiwS46n585dxYEDJ1CuXLEgvJ8GDf8GqlYtI4Otq/S5U/1d6eHMC04SOfTS+51KlIAQVA8wtaYi0XTx4nXxCuegl2N4p3V++eKALVv2yEQuE2PZQs3ty23LgKrAfN/YJUOSke2OJM8I2tnwu+Dg+g8Z0hUlSxYM1/X/00B1KlvxCbZWP3r0VNpB6R135MgZxIsXB1+/Oopogctp6lENWhupAh7r27UbIH/fuLHfZIKE16Lq9RsDM5kW37XrMCH3mzfvjf37V2k7koa/HqY9acHEhAkTpODo0aOH8b4SJUoYY8rV0aFDB5Pn7dy5E+nSpUP69Omxe7ei6iKePXsmy8eLFw9OTkpbn4ocOXJgxIgRoVldDQGAfmTr189BvnzZJRGcyVsk6OrU6STtQ5Eben/DF48ePUeXLsPQo8dInDp1Sdr6SOA9ffryl68nbZx+RsBLesnw0bvK4HIHD51ApUrNUbNmeyEdmzSpgUaNqmPcuL5o2rQmNm7cLb4lAYHbXSUdV66cJubsJB/PnNmKEyc2onHjGlLw589fIxTb6+8EE49fv36JDOnLoGSpBmg+YDDylx2AFx+/4Lr3VzzNbYV3Ga1w8OUTxE0QQ0bCFHFlfHj9Fbc/fZbxzd1NRtwotjKszMxlePr4yPjm7o4PLs4y3ru4yvjgqoxzb97J+O7hIcPd21OSqTm+un+XEcXcWkZsm3gyolpEkfHa2QE+er0M9T8XL3cZXj5eMjz1ylCX42ASNYeZzkwGyUu/BCbJRhKYHJZmylBIOR8/vxmFiIscELdLA/mlrtfP1k8lEa1lKPNoHIr3YmjWI+ChPqrOlarv43d9TdfB9zjiYRwKOekdxDVR3kv9jCQcObz132T46N2hhzJ89G4yAjoequC6ODg6YODAiciQvjxqVu+FNGmSYN366dCJx6fyOd68/oA9e44gd+4s8jwGUDBsYNKkgejYsSlWrtwSiu2rITBoNdWfD/rmrVo1HTVrlhffLp7bOaFL4oyTun8qvn93waRJCyTob9SomTh9+hIGD56E5cs3havyjumsBQvWENKRyckM7xkxogf69Gkv25Yti4Fh8ODJQjqSEKZib/jwHrh374i0OnLynTY4HToMEj9DDT+CqdaZM5fB7NkrUbduR+zbd1wsiBYvniCt+S1a1NFIRw3/PDjBwWM7fy/581eX67zDh9ebkI5KoOUilC2reJ9S8aiGpbKTj5YFrLM0RAz881QRNTSEQvF48eJFLFy4ENmyZfvhsbZt22LUqFHGf9va2pow/p07d8by5cvFR6RVq1YoV66ciYqLpOOUKVMwcuRI7TuKALCQWLRoIkqWbCBkmWoQfe3aHRQtmi8Sfwc//ohpIs5WwA8fvqBFi1ro0qU5MmRILY8xsa9z56His8HCKfC2atVPLfBEWqPXmuFA8v27I7p0Hi7eNsNHdESdumXg5OiBQgUVjw/V+DdxkoCl9DTnJjiLz3CHt2/fY/Hi/2Rmn7PxNFkmWGhTxp80qW8y+b8Onc4aCRIo7feZMqZCpgIJcdXlKxLkToRT9x/D3FsHSxcddFY6fHdyleW+flCUivnzpIOrl3Kyv/dVSZ279kFROBZPorxmtZSZDO+kN6oWo5grasPLHx/L7evvykSJpUHNcu/rO7gbVJGq7+N7VyWsJmssRW2o4vbnz3huqaxPKoPPZNwoUU32cAtjUIwvsWhmmDcyN1OWItmpKijlcW8dolsqCkcLs7gmCjxvHyWYxdwsdoDegX8GTMk1/96RgT5LH9JUa90vfSADh99104XY25Eku1/fTZ3OwqiG1OucTLaDevzy0bugQf3euH79vsk79OvfAg0a1ICtrY1RNakSDF27jpCL9MSJE8q2ondQlSqlxfJB85wNH2g11d8DBnTUr19VJkA/fPgkNQeVYv/9twt161bGnwQq3jZs2ImtWw+iXr2KWLFiCvLlyyHKTaqiO3YcLORfgwbVwrzNb/DgKTh//qrY/9ADjWEJvLCnqkjFoUNK6Jx/8LilEr1Mal67dru0as+evULIy6tXbxmXXbx4PYYN6x6m6/63BFEy8ZxBPMWK5UPp0oWNbfNhnWKs4c9GyGqqPxe0b+jff4LJffx9DBrUJUBbLB534sSJiXr1qhiv5SiEYecICcr7949G2Lpr0PA7EaKrze/fv6Nx48ZYvHgxxowZ88PjJBoTJAi4fYPEIwsWKhhlBSwsTOTHRNeuXTFt2jQhKKl+1BD+IGFWvXpZfPyokC9EWPnyRARY2FOyfuzYOfTp0w6FCuXBrl2H5QKgbNmi4u+TM2dmrFkzAzNnLpd2wbDyc+T79O0zXv4+dmI5YsVSzHRjxoyOu/f+h6tXHqJRox4oWjTPD23SHh4e2LRpj1yMjB7dW9SmLI6pbmRrNYlHlXRU8fHjZ4149AceU06dWYC7d5/j/N0reH7kKcwszaHwKX/mLJO3lzdu3XmNOPGiI0kS07R5GlK/ffURjx68wc3rz3Hp/CM8fqiEGE1c2BxZcv3aJuHkiavInDmXtNPy4pITDfQlffHitVzg0f+1UaMaxpTLX/3+SJpTJU2/s7CA2tqVOHF8JEgQz9i6qBa5IZ88/LcK5HbthpuQjqdOr0Gs2Mp3amaSPq4EbPXtO1YCBUguEK6ubkiRIilu334g4+9Lg/39+4NWU/2dYApw796jUaZMUSEe2Sb8J4HtyFQNcvK2a9dWuH37HnbtOiRqHU6kMhl57tzRYiczceKCMCMeWeMUKVJH/l60aAKKF/f1yT5/foe8f65cleTfAU3CclunTp0cS5ZMlHMTfTfZzkgPaGLlys0my/MYp+FHULl7+/Z9CeC6efOuhB7OmDH8jyaaqKJ9//4z8uTJ+sNjDCS6f/+JJLDfuHEPhw6dkvuZrPy//6345WtzX9u375jRv5jvdeLEBVy5chNRokQRq6dy5YoG6RxK9Zu5uZmQ+2ERyqSq7q5evS0KbJJjfms1paYKea38h+4OIQI76PySjsuWTUbhwnkCXZ7HzOvX78qxTAVbrYsUySNCn549W4f7OmvQEFkQoiMZCcHKlSujTJkyARKPa9euxZo1a4R8rFq1KoYOHWpUPTLhqGXLlkiYMKEc5Pj8aAZfNBUNGzbEwYMHRTU5Z86ckH42DcFEvXqVUbZsE0yfPkxaWmLGVNRSfwLevfsgxAlJlBkzlqJKlbKoXbsCDhw4idWrt2DkyBlCcrMwYDFAXLhwDdmyZRBDXibxJU2aQIhBVRVGMobm8Ax38evrRnj7fMbOHScwcMA8+ffQYe3QsFElmOmiwNPntdxnoYsvtzlzZcb06UOwbt021KxdGNHtFZXUd0drdOk8Gpcu3ZSTljoTRpAs5ax+xoxpRHV6//5jMUavVKkkcuVS2h81wEQNFjd2esQtkh7FipRDwaJbMaTzGrgk1MEqR2y4O+rhYO6KdKkVtWHlzBnkNm2M6NJGTVgaLkoqplRIu1xxlYS+aJYJjeq2bx5Kq7zeXFGZpYimkPMJ7ZRjmKOHcgHz0skR71wUdWVMQ7tFquiK7+Odr8r+lzSq8u/U9vZ47uRoTKjmftet2SJ8/fwd798pysQR4xshTbqEiG5vi2plRiN58nhImTI50qVPjg1rTsoyI6coyyRKqqoYf0xiNvo1QodtW0+hQ/uJ2L13PDp3nIMc2TPJvlahQnEhv7ds2SsXnmynCgyctV29equkhzKVnWArW2gKWKUlZSGWLdsY6DL58+fEqlVTA3n01+8duoumkH021Vfxx8TuX0NpoabvqLI/0ObB97W8TdWQ0s7NB5X92cPdE1Om9kWp0nkRxUbZT33Tw61NtgnbGXk89KvK4kU+24AImqCH9vvV8CO0murvBInGhw+fIWbMGDh0aG24BeOFF7Zt248sWdILsUhvxEqVisukFLsyGJijevupFjKFCtUSexm1puIt2839gonUJDJJWvoHuzkYcOjp6YkSJQpg7twxASYk29lFEaVjmzb9ce/eI2TIkMZ4DGOnyNSpi1C+fDHMmuXbNUWilGBdS+URA/3oxUYSJiwSZf9GcNtnz55JRrVqZWR79+s3Dr17t8OfhlmzlosCVm2rpz9ljRrlpfYuWrSO1C+8HuD+zrqH1wpMe+/QoTHSpk0ZpPdg637fvuMkfIdEPEPZGC7ZvHldeb0nT55L2BS92n+GPXuOYsWKTUJWEZs3L0DWrOlD9fnZ8dWwYdefLnP79qFQJJL/O8wj9yEmVbdu3eCXwVwkepmjQBLf77aloIS1Lq3ASIJH7u7Cvw9mofUaDOF7aggB8fjff//hypUr0hYUEBo1aoTkyZMjUaJEuHHjBvr374/79+9j69atxmWGDx8uvpCcffRPOhK8qKHXEUnLnj17InVqpVVWQ/jCyUlpBY0a1QYxYoaNail8YBrSwAvvpMni4tx5eg0pxM3Ll++RMmUiFCiYQ0iU9u0GixH558/KhTtBY9/8+XPg4sUbojrkBUKXLs3EX5Hw9PSQQouo36A07OxsoNe54+WLjzh04Lrc37J1efToXRtWhrAOvd7TSDiyDZJg4Mnbdx9w8eJtFCrQAgUL5YCrixs+fvyG16/fGWX4U6cOMfmUXN/27RvL35kypRU/Tg1BQ8H0pbFmdTbUqNcDzXoWwNUn7+EVXY9WWTPL49aGsBWe+JNGU9qbE9oqROPZdzflduXdG3Ib0+aesj+4eSHWCz3OnrqHalXKokjRHMaWaA9vhTjUQWmZdrbxxDNHpfU1TXxlf4hjoxD5MayU53zzUDxU3by98N3g7ZIsahwUzNZHef9V46H3McfGTXswYuA6mf3OlkNJx+vVtyEyZEiJmDGj4fSZC7h98wXyF0kPKysLfHNXfsfefsi12DY2/gJILKRtloV2uzYzMHnSIEkKVe0KaL/AFiuGTAUGXkCOGDFdfjebNs1Hixa9sWfPcn9KRNVHMuiYO3eVkI70wqEKmBeKbm4e8luh4o6J73nyZvUT0hK5whoC968MDuGobjNDuAxMSUUvH2XfMtM5w8VL+b5tLZT2fzOdgVw0PHfFyol+Xkv1EDJVOvJ3wImNz5+/iHeXX3h4uMtE1MKF49Gzp6+FioawgVZT/f1gOvCfRjoSa9fONP796NELpEnjG+43fvxcaSVXaxhVMUYlFa0ZqPQiIUnFOhO/1W4P1jrsOMmRI5Occ1jvk6BZvXqbPM7kbxIzPwsC5PHq1as3MiFSvXpb6V5JlCi+WNQ8eaJMkuzff8KoxPcLqrlVMGlcQ9DA72n+/LFo27a/fOfRo4demECimMQMSRhFbd8+XCa16EnKVntOWG7fvhjz56+WCVN6sffo0do4aTpnzighoklKs7ahvYhKagcFjx49k326W7fhcm0xZEg34+Tdly9fceTIaem8CgwMlOzUabCQUVwvkvfZs2cMNenIDqomTRQrgY0b5wqRzO3NWo9dVVQY02sw5KTjvwX1uuxXOHPmshwnqQr3PwFDC61evdpg06b/ybFLg4Z/BcEiHl++fInu3buLGtHGcCHrH+3a+c6EZc2aVZSNpUuXxuPHj00IRHv7n5+0ypcvjyJFiohact26gD1c/OP16w9wdHQJUNGinsxYsCiP//h8/+e7wJfRiWfMz97H9HX+jHW5desRWrVqgOTJk+HFcxaTZpF6uwjxIMv4DWowg7ePNz68/yqtCWxXaNNmIKpWKYXYsWNhzpyVKFq0APLmy4oD+08K8d2oUU3Urt1B0g05w//t23eUKVNYXu3gwXXYuGkHNm3cb7IezdqUQ8XquRHdKiZevfwGCwPJKK5s3nohiUaOmIdXr97B28cH352cjfv8ndtPUbZsQbi4PJT7pk4djJQpk+HVq/dhsl3+xX3X//v44LuQVdy+7p+8YP5dJ/vK17eKcoyhMbKcXg9Lh++yPj5RlOLz2ydlGc8vyn7lam3wgDz1FK5PHFGgcAZMm7oBkyasxdDhTZEgYSx46RXy54ubQiZ+cXWF+xfleZ+gHJOs7NS0bOV1nTwURaSDszvcvivL/nf2rKzzrFmDkCgRbSYskShRQrmvY+eaSJcxNnp2WYJhg33bfqrWyIfxk1vjy0dlvZ29lFsvHz08rWhoCLgYVJcWBhXc8RMX8c3BGYOHdEFUO1tYWtrg8eNX0k7FEBG2Wbu6euDAgdOIGjVagNt/1qyV6N+/s1xQs2Dt1q2V/Nb69+8oAQt+v+fg7C958mRHkiSJULFiKTmec/C7trS0Rq5cSnsUJxaMz6d+Mxj7CydYWOBz/4jsvyNV2Ug1I0OHfPQK4ejlo+xT5mbmcPN2k2VtzJXPYyFBO4r3Kd9Hbwwc4pv4yHupyleStmzb53GR7Yhdu7bGq1emQQsnTpzD06dvsHLlVvm+X75899u3i+lrhG5d2Hb3uxDZayplHd8hWrTvhv2GBunB/z79wsdHb7Jc0L9P02X+hHXhxX3mzBnQunVD2Y6/c11Cu13ev/9iJPHWr9+F8+dviupn/fodiBHDCb16tZUOkbNnr6Nz56YYPnw64sWLi7Rp2aY9EoMGdRZLlLFj+wsh2afPWDx9qnSHEDFixMDKlVNFCclzj1oPcV24HSlUYFfLuHFz5EKdE8d8DvH1qxMKFMiNKFFs8eWLkxBGzZrVxrt3n/6o/eVPWBc7Ozt8/+4Kd3cf2NhYhWpd6Cfcv/9EadHfseMg6tbtLD55/P7CarvQruXKlTsoVCgfRo7sAQcHZ5QsWQTbtx+SRPeKFUvif/87JuRbtWrKsZbk+a5dKxAlirX8boOyLrSGWbBgvdQ/tFmKEsUGL168w5cv32SfjR07higY+Rto1qxOgNuFbdr8vQwc2FV+ay9evJFz85cvjhJWFdhn/tV2sbKyRrFiBUXMECNGTDx//tb4HSVLlkTG27efQ7W/fPz4VRTQkXnfjch1Iem4detejBnTD2ZmFibHf06I3Lr1ENOnL0fXri1gbW0jx7u/ZbtE/mBa33CZiH5PDcEkHi9fvowPHz4gV65cxvtYEJw4cUJaolX/Rr/In1/xZnn06FGwlYtUPRYsWBB9+/YN0vJx48aUZGYNIcP79x+QLl0KJEiotmpGztkv36Rp/0c+5X4qHumdGDduNDkZvnv7Xlprjh07i8pViqFVqzqIFy8WHB0c8PbdW5Qukwdp0yXHgAHjET9BbJSyzIHYcdmMaoU1a3bj/LkrxpT1WnUKoU//Orj2+Skc4YpY0RSVUZwoXvj00QEbNx/EisWHRYlGX7RWrWtj+bLN6NatKQ4dOo0LF26gfIWiKFQ4D9q0aSzkknYwCnv46KPg/PkbyJwlIcpmTo5Tb1/CTeeN9a8V9WL99IrHTta4CaTtmLC1VEieeB422Lb2LHzcfFCkVCY4xTKXi548uZLg/MtHqF+3HCz0MWU2eurklVi8ZBisoyjhLQn0Cnn5xc0BKZMoF0UxDQrH0++eye1lQ3jNRxeFrHzr5ITCSZLC5Zsrtk//H3r3bYBcuZS2MKJ7t5bInTsjJk1cLCf28uULo0pVpk1mwP/+dxSrV2+GpbktmjQrLfudt15RXb53/QpPH+UzmZsrRFWcKMpnPXvmEho0rIRMGX29hlgcb9z4P/l7zZppP/iR+gdDE/Lnz278zd24cQdZsqRDtmzppej2hf/f6c9PvgkSxJHwJ5KflvTpNHklNWzFPAivpw9wGRbH9E3iMSBywXd9VTUnFdQKlM/trbc2abl28HCCj+FwGM1ACthbqf7K6jYyhBzpXaCDqoq0MXqb9e8/HpkypUP79o0CPBY9ePAIgwe3FRL6wYMHMjnFViMSlkyK/dPh6qpMAPwORPaaiogfP7ZWV4UQtHWJHdtetuGfDmdnNzk2E/fuPYRO5wMvL0/Y2lpj1KgeKFmyELJkSYNx4+YhenQ7tGpVF+3bD8TTpy9ExciWRE5QkQiaP3+V+Jqqx+Pdu5dLjeYfnDh++PApGjXqJkQMCcf27RuImrF6dXah2GHhwrWIGzc20qdPiZo1y2HixH6/PHdpCBlIRJA0zps3q5BXQT2H8pjG9uHjx89LazPVXiTBCJ7jS5YsIPsWvQxnzlwmqsBcuQJXBgYHFSs2FbukUaOU7gkiYcI4OHx4DRo06IIePUYgXryYaN26rqzX06evsGDBakycOBedOjWVtumg4Nq123L9lDNnRuN9t28/ROPGiupx2rQhmDlT8ccMDG/evEWZMkWQLJli73Pjxl259ihXrkiojyETJvST7qt48Uz9wsMKTk4ukbCm+j1gqz59HWfPHvmD0lFtey9UKBfy5s2O/v3HinUBJ/ApfGHX3Z8OnhM0aAgT4pGz7DdvKm2IKujXmCFDBmmp9l8gE9euXZNbztIHF/ny5UOtWrUwYMCAIC3PwsR/W4WGoINtK6VLF4K1VcDKi8jTYh0Y0cDvXpkZt7TUwcrKDIkSxUbatMlQqXIxIR5bta6MRImi4uGD+1iyZKOkiSVLERMO377i+OnZiBYtClau2oEK5TvAW++Dj+8UEidGLDus3tsLMayjwgNuiGmnXMB/NrQ5Pr99A+0azZHiYOnSSUiVKqm0sl6/fkcK6717T6Bq1dJiLsziSiMbQ/Lte0vhe/HSRaxZtUtabjNlSQ0znQ5m5lS9ecvfVJt64RuOHLoBq5R2uPzlHSwszWFhBXjqFEInQ5w4uH7hKS5fd0bevGmQJGkceLnHxapVu/C/XSfRomUdxI0XFbt2HoObzgFdBlfBaS9PONm6okrt/hg/sgly5rbH6zflMGzoAtSqUwp58mSGnZ0SWGRnk9xIAHp4K2RksWSKT1DcaIZgD8N+nMo+NuwsbHDy2G3YNq6Cli2awExnehwrVbIo8uXNLSpe7rMq6terilo1K2Lbtn1o32aqqAWat6gqM+52Nl7w1ithUa5eyjqYmyuqy1bti6BJ/eHo3bsV2rarLyQ7Z17ZKkffo4D8t/x/F9Gi2aJRo85InCQ+kidPiv/978gv/P8CIyB/JNySpeQ2coEZlPXwfU3VJcU8gDTroM0msh2dF0KR71zhm2Stplarikcfg6IWBsWju5fyuLe5D+JGUS6molooQWzmBlWrmsDObcXfjZOTOeyjqxYaOmmHHDx4kvhYNW5c84e1cXH9Lq1YvKDq268pSpXJhe3bjmDuvOU4dPAc0qRNjmLFc8LG+s+e7AsL0/6QIrLXVIRWV4UcVCyxzTryHWuCDxJE6ufghBODKXiuZUtp+fLFjR6wBD212f48cmRPCdgh2UgChuqvd+8+Gl9zx47FgbayUhVED0ZaevDcRA9sklVcB1rjcNKEJNGlS7vCLHzjX8X795+k9ZikIokvbkt+tzyHUDXO4xDPwY6OTqIG5MQiPdP979dM6T1z5pJ8p9myZRSi+cSJ80Im5siRWRSyp09fQrNmPbFxIwnqqOjRoxVat+4rgSzt2tGqKxE6dBiEzp2by0RmsmSKjVFIQOKahM6CBeMCUAFaYseOJdIBoZKgRM6cmcRWhLX7rFkr5DNw/6P348/A8+i0aYuRPXsF3L17WO5jizR/A/zMFSqU+OX6MlySbeH29tHRoEFVCXZat26WeKKGFvy8fj9neB4f/hU4OjJM0c64b1HBu2zZBlG28jqQbft+wTqMXXD8jeTOnUVyCDJnTithV8+evRJCklkLAaVi/0n41/YDDcFDsM7UbEvNksU02IIzjrFjx5b72frDFp5KlSrJffR4pEdjsWLFkC2b4h8WXIwdOxaZM2eWk5yG8AWLhrBKeo4MjmrE16+OUjTREF1Jh1P2o9RpkuDq9Y24fPkOunYejxYtq8Le3g6nT93E+tXH4eLshkTJYiNmTDtEiWqNavXzBUqo+Hj7YNrY7ZizvD1KFagMczPfC3F6qQwb1l08XvwmM2oIGbp1HYnvzk7o2Kk+3r79iDevP8LHx9vQjuUpLZo8uXt4OSJ27GiImSfgE/isUTuV7ydDKowdvQHv3n6FDpaoXqMkNm+ZJ4U1yZ6iRXOhbqNueHD7Ncxjm6F824L48sYBo0f8hzkLOqBx46qy7KqVu9Cx/Ri0aVsTXbo2kNaW4ODW9eeYP3MPpk4ZGugygaVLc5/mRRm9STdv3oumTfqhbLnCaNuuFgKbQ8iYOSmq1yoAp+/Ovj6QsWNKsc90eBZA9Pyht2hgWLV6Kry9XfC//x3Ht2+uWLV6yh9DqP8p6xkW4MU+Jz5mzVwlAQFUcNBknypVengGpFrk76hb11E4efIi6jeoAJsoVrLNChTMhnPnFKLs0UN6Q31B0iR/NvH4O6HVVH836J/GdOW/A77HzAsXros1zfHj50zUsDdu7BeiplKlFtIKzYtvEo3Tpi2RiW12gcSJo6iiqC7jvwMDL8bpb8fEWL+Tbcpj08Qvb+hQKiE1dWNoE3pnzlwuISqlShWS0EXWUzwHKIMtlz6icOe/uVxA4MT+jBnLULVqGWzYsEtIM+4LadKkwPTpwyVoiKCakbUGW4jZfl+uXDEUL15AlPfr1++UcKLx4/vjyJGzRk/hs2e3SQ0fHFDd1737SCF3Ajvf89ogMDKOtTv3X3pdM3SNdV6fPu0C/T3zsy5ZMgnVq7c2uY/EO4P6aC3A7cvQo4AmlIgmTWqiVq0KMmGxd+8x8Ub9WQ0WufDv1FTsqCNJ367dQOl8om8sbSYYFMq6mV6oAZFvbL9u1aqvqMM5wa8GkCVJklACRNXfI5W2GsIXWqv170OYsnksAA4dOoQZM2bA2dkZSZMmRe3atTFkiGloRnCQLl06tGrVCosWLQrLVdUQAHgCJpnDGfo/A369HWFsTdTrveGN76I4ixHTAt4+XtJGTgPpGDGtJSHWR+cC5nm0aTVCnrd//1msWbMHTgaP0LqNiiBfc4Us/+TqBitLC1z9+A6xbQytigbvsJdOTnhw/jnixrVHiqTx/aiMfKGGdmgILfSoWbMsFi9Zi1y5k0IPReH12lnxiTr37pXcpraPCVvDRAUTqz3cvJExd2zESWiLWAZ1VvOFM7BmXT/EjJ4d6KgUEp6e3pKWqSrPpB1VB4wa2gED+89HtiaZULRQWsRJbYPk/SqgV68lGDcqJooXz4lqVSugU6chOH/uNg4e7IUePZqgXHmlXdrSTCEhY1srF1x54yr7kFoMv377GW2bzsboMR2QOVPmQMmjBw+ewMXVVQqaggVzwtzM8ofjL4v2WrXLYfLkRVi8ajlatCojj0UxV97T3BA8YmFuhaZNamL4sEVo3bYiYkRTimnOrG/ZoiRK01y9TZsGYsjuv11Er3eDtTXg5PkSFWqkgp1FIn/qxYCKUF0gVglqKjNvFcWjt4+i1DQzbDtFzcxlDGnOOotIawURknAs+bdR5egJH72rSZiM2nLtY/BrdPNW/h3Xxh5WZkqLorlOuTBT/Rv5et++OaFatY6IHy82DhxYLRdzDAPiZMjPCBESCyQdifPnbqJG9Z7iS3v40Dl07tIM48b1h5VlZFXG/z3Qaqo/GyRLSCL8bWBC9Pnz13Dv3mNUr66E8REkCKtWbSXqHRIm9ep1FvJVnSDbsGFukNQwJLiWLt3wQxKsinjxYqNBA9+QGA0hR8GCuSV1l4QgScJcuUzFJUEF24pJnJFoIzgBTN/DgIg9qrrY5kxymd8j95uxY/tJAApb8qmY7Ny5GZIlSyQJ5W3a9BM7kGHDgk40M2GdBOeSJWq4mik48Xbz5j2D57O7tL0GtK65c2fFihVTcfbsFUms3rp1YaDvyWsnrjvJ23z5chjrPIY0cTK3fftB0m3B7Zwx449KXxKSVBJnzpxOhobIBx6bSJovXLhOiGm273Mit1Spwhg+vOdPA3pIOhKPHz9D585DJdyRxD6PjcuWTQlXRaoGDZEFOr1/l9E/EI6OjmKs7uBwT/MiCgXYrsmCsWfPNoic8G1FVODzw+PeekcpKF68eIrkKWLB1dsZi+ftx44t59GkRQnUa1JUlvzi7ojNy89g+bxDiBLFCuUr58LlS49QvEwWVKudH/ETxkBMK8VT5Yv7J2m7lnc0/FweO34WpeP9Z+8xs80G4xrcvvsfLMy0hLLwAD3qeLiqUrk1tu4eDEcPhST+37MHcvvCYGhcOFECuHsr+8jtz1/g46GHpasO1rEtUMoqBbZvPYPDh25h2fIxSJH8x+JPbW/18CDJZyVtyLzAmjlrPj45fkHDdsXhHN8St44/xrUzj/Hqyhts3jwYqVInhJV5GklRb968JyZO6oJ06ZJJ0I3yugZCEwqZ5uihmOc/dfoI22+W6N19KaZOG4DUqZNCFXjfuXcDa1cdws2bz5ArV1rY2Jrh8ydHUWgOHNwS6dMng6W5ur+ZGcm5A/tPYcfOveg7Ubk4Uw/zHgZDwORRFdJ276772LnjBBYuHAMba9+i59ChU1IYVa9eVo4JixdP9Ec+Kq/n5aO0zfkYAnQsdMrrmukCVmcSavu3t8EP01yneA55+rzxJUbNFM9MXyjFXMBko/+Wbd0v22MYLBOefkTGFGojUWrjx2vRQCrq3U22gwqdLoqJLyPh6aMQjV6G45D6CaNZpvGzrU0/t4uLM2rW6Cjkcd26lQOcFAkMnM2vWLG5/N2hYyO0bl0P/9t9/IdU2L8B3L9TpswPBwcHRI+uFf4qtLoq9KDqqn79zuJh+KerrB89eok0aZIau2Pq1eskJMuKFVOMCq4XL16jbNkm8jeVWzxvkjxq3LiGEDtB2QY8f/bpM0aSfYmFC8f9FV6ykRlDhkyR8BKSbMHdH0gu7t59GBs37pbvvHlzJTglsNZntnDTDonn4RUrNmH//uNo2rQWatWqKCrZRYvWSdI12/fZhq3WL1Qd8nm9e7cN0vqxFZ+qSxJ8XCeSO9z/vn1zlCTh7dv3I2PGtBL6YmZmLupdnivZ8h0QecTJ3zp1Okh7NsnBwMDPwOTvqVOHmNgIcHI7a9by0nHAvwcO7CSk798Cv8eHv/23QvKRCeyqZ2hQUaVKS5n45aQv08W5n584cQF9+7b7q5TbtGSwt88QKWsqta459HAm7AwZDREFZydXlEnbPVJul4iE1r+swQimatJX529Ds9al0LhZCUSNFgVeahIDL6CbF0OJslnh8MEFHh5e6NS3kvi//ao4PnnkNpYtOAQvLx9EjWOLbCXToFiJjEia0j9ZoiGs4eLihih2wTcu9nLzwr5RR3EpagzUrF0IvXp1/qF9SwW97wYOmCzBAH37tkH16hVFCThrTk/sPn0Y6xcfh7O3F0o0zo2iXQri3v4H6Nl9IerVL4ZGDZNJMUJVh39ii2mbbOHf+78reHD/BWDuhSzZkgH2Zrh9QlGF1KzeQ25jxIgmQTHx4ttLaMyI0S2l6Pb0cRIfyxvXn2LKpPV49/Yz4saLh+TJEsHM3Bx6Hx9RHsSJGxMDBtVn+f3T7VK9RnF8/uyA/v2mYMKEQcZQGPVCj/5Ijo7OGDp0CmbNGhns7a4hbODu7ol1q47j6pUnaNW+LLJm/3X75v37T5A0aUJpww8umPaZJm0KPHr4DAvmr0OTJjX+OsJRg4bwBi2C2KJK4uRPJx79gpY8e/euNLZNq6Af34kTm/Dy5Vu8f/8RPXq0lpCwX+H163cYMWKGnHOp+qFSjW3UadOmFCWehvAFvZ25zYMLBvswRKNy5dLii5ggQeA1MGsIqmTpYzh37mjxd+zWrSWaNKmFJUvWo3bt9mjduj5Gj+6Nu3cfyf7AADsqH3k+YoCQ/7A52idxkLy8ffuBWH9QKUi1Lb2JSTKSsOQgSPiQ+GSb67p1s00mU9u1ayhelFR/sjbkerIDhr9dvi4D1RgC8jPSkWAAElvLe/YciVmzRhk7yFRiiSpLko4dOgyW30pA4SMaIgZHj56V/ZfHmY4dlQmTn4GWWfT+XL16RojUicWK5RfikSpwtt+TEC9aNF8I116Dhj8TGvGowQi2BzBxLvJC90NLot/7qRKiiogtm6qO18bcGja21vjm4QQXLzd891SImJufPih6SRsgV26lTfSj23fwJa3N1TZdhaR85PAJ3z2U90yot8XiGfuxfsNQxI4dHeY6pfA216lF2x8vII60YHstybvYsexhBhtEtVS2dZUUiun3Nw9FWfjBxRmxrJWZrKRRo8PZyR0LFx1As/rF0aROC8NrBX4R+NXhCeIniIqJs3uiRf0ZQjwSlmZJULNoMxmnz+/BvNk74WXjjepti+CSmwUmjt8oY/rMzkLmUTGphzXcvJ3w7ZszyhbxtZyYv3AQYsSwQ8P6g433RYvuO/u2dFUXpE6TEGZQilU3b0cR+Dp7uYn6NlH62Jgwr7EUxa7fPPHq5SdYmik+fB27FkXsONFFHejkqXxOM4PaLbplErn1hhJS4uXzAc1aFkCLxpeQI0dF7Ny5BOnTpzZaCTBRlOmStWtX9P9tyP8tzOIF2D6sqpJ99Mp34hcOHk/l1tVLUfzFsVFUgY4eTohu4IItoHhz6n56igpeWrbJMwMR+lPtqqoUja9q2FfU+wNTGJq+vpeJelavdzYGxKjHLS8fJXxI3RW5TxPKcmp6tyU+fXRA755LUbhwNuTNkwlb1p1HgVwF8fbtZ1jHdYOVlR9rAH5nj+5jwbxNePXqI/r1p99U8AmPgwdPIl7cmFi0aDjWrN6Nw4dOokGDWsF+HQ0a/mUwVIUeXpw0+vNhesz0TzqqINEYFLLRLwYNmiSqNwabaPhdxGPwPBTpsUnF1vbtS37aXqri8uVbovyl1yGtPAoWzCX3x4plj379OqBFi7pYtGit2LyQkBw8uIu0Y5OgKVIkL1KkSCItyv5bV+nBSJDAIaFHwnL27BVyn52db+cFvSl/1s3FCeMRI3oaCSaq/tmCzfM/SVK+d1AnD9KlI5HVFJUqNRcl6YQJA4wBNFREknxi+/XfRTr+Odc+VCwyOIgkIlWuvXqNluAjFxdXUcb6J5cZGrN27TZs335ArARC8r1R7Uv7CPqV8rywYMGan6qDNWj4W6ERjxqMoMkzTaEjb/GnnNh0OqXI8fL5pPzb4P/mtw1TPODodWY4F0YxtzZplY5uZQ0bQz9rNEuF8LG3UooUFwMhcumD4h146clbvD3wGKe238TK9T0RxcYaCeMq/n0/4u9RNUQ2kMTavn0v8uRPDU8fF2P7u4Xhou6ru5vc3v36FYntlDTkAglSYPGqA8iSKSMa12kIM52yH7AlnzAXPzzT7yxZ0uR4/eoz4GmGGDGj+Xtc+btw/soolK8SDh7ag+Uzd+PRwxfYe3AMZk07gOfPnDFqVG907DANixYPgX0sa8SLZY0cOdILIZ4wYQLky1MYVtYKuVSgUHqMm9VMlDEWMIe1jSU89V5w8CAB5Wzi6efp7QULM2U/t5DUSR2SJEggQyW03L094e7tAR/SnubKb8Pa3HBRoVP2eZ1eeQ0PQwvv06evsXv3MmNhr14o799/QpImFTXEr/0b1d+gun1Joqltx2rbsEp+2hu8vnQGwi1ulBTS1h7wewT03mH/W+P6q8cXI4mqV/YrL/07uTWH6qkYS/xi5Xn+UsjVdTPXRffj26hsE1evz3L7xkVpOU8WVVGJvHFRjjcvvjsgZ5ykYhnx8N5jjBr6H/r17Sg2Io0a9kL3nrXRsMEw2Fhb4ZvDN7h5uKN2k0Jo3bgGDh+8jMUL96Fr98YoUaxEiFVWUaPZ4MyZq0iQMBZq1CyLqVOWasSjBg3BBNsqSTKwrZTkhQYF9Ln777+dGD9+Hvr0aQ93dw9RimmIeFB9xYm4qFGVmikoYKv90aPnsGzZhCCRjgSTel+9egsnp+9ImFCdsDT17RwypJsQc0y1JrlDIpCqfRLTDFpp06a/kNoMaSGaN68t6sjEieOjf/8Oomi8d++RPEYvRirZSPjY2toE61xIpSMTqUMDprFT8duqVT3jfZzUZWgMk5B/lZKtIezB/Zwq2GHDpiJevDiivM2Zs5Jc89LTnPsSu5Xo+8laeM6cUUJG1q7dAXXqVMTmzQsMPvDBB49xBAltEulTpy4WW4ngtmtrCBto4TK/D3/DNKyGMDQMf/XqndEMXAPg9MUFZ5dcENKRaN5wOkaMaaRtmt8AtvzOm7sRyVPEC97zHFzw+fO3IC9vbx8VN248QrdOC9GwUbGfnrhKlc4rM6RUCM6fuxvTZwxChw4NULRoXnTv3hDFirTG7p3n8fmzE65du4+nz15j5swRklDNlp8BA9vi9q0X8re1taWQjhGN1cuPomq1ElKk+y3ON22aL7dsRdEQsRjSbzUa15qCeTP3YPyUZihRIj+WLtkkj127+ggTJ3XHytWjsXnbYNm/VQWnq5uHTK5wciQ0rZ1UfDRqXFn+vn/vCVKm+vu9mzRoCGvw3EC1+KpVW7SN64d03LfvOEaNmiVk4/jxcyXA7M9J7/27UKNGW6n7g3O+YHvzx4+f5LsMKuzto4tvMNuxSSYGBu4TVII9ePAUkyYtkHBGtiSToFm0aDw6dhyMYsXqyrJz564SYoiBeKxfCPpRsy2bZD9JJBJFEW1z8PjxC9y4cVcsSvxa+rCdN126VLh69Y5MLGqIONC3vHjxemjbdoAQf7RyePfuo/GxsmWLYvv2xVL31qhRDk+fvjDu6wRrrChRgm/zpIL7INv3GShD718SkcEh+zVo+FugKR41mBwYhw7tir59x6Jx45ooWbKgpDJGPgm/hanS0ZDiqoNOFEhKiAcLDZ1RteTpo7Q8fmE7NS/Qvb2QLU4i4/MIO0vls3oZEnXj2ETBztUnJDyEyJg1KcqXLom8OUuH+yfW8COsrZXvqXunRTh8ZcwPQRsxrRXlXIEECeHurXzfBx/fw8lTd1CtUhF46T/CXKfMLqq3AcHcLDbu3jsInc5/YajHgUN78fLlezEa//bVCW/ffsP5c7dQomRODBveBjpDcAxRokRR1KlbAYMHrDTe5+jwHTNnLUW3bs1hbmaL+fP+g5OjK04cu40CxdLjnbvSfhvNSnkde0ulMLGyVPZ1B70zbAwqRlW9+9n9i4lyV1UxmuvMYGlQ+qrrpdoUqEo9a/No+O7oiRw5lARGv2CBdPDgGowbN9fw6ZXnKltc/U2a+1M8KnNZZjq1oPI2JjFbmiUyeW+9QQFpYaYs63fb/T74XqCo6k2d4bNYILHcunjdV/5t9hZehuOKrYWiXvBVdyrqRp1OUfF4+bzHO1elkFWVuqqlw1d3pe39rbNyG93SGj6eSrtPyeKlkSNjRXj7uKJGzTLo3KUxMmVKY9xWO/93DA5fXXDp7CPUq/4ZlapkR7YsWdG9+2QsXpTKoCIK3kUXwwKWLtmIyVM7iipp2ZL/YfmKSSHamho0/Otg0i/TeqlyypYt4z/vWUgPYrY2qu3aJGfVEBENEQ+SfIsXrxcS5mcejX6xZcseJEuWJFDLkoAwadJAGf5JQBKMFy9eF/WXOk6duijnoSNH1sPGxrcuYOfF2rWz0LhxN6RPX9IktIMKR54zHz16ho8fP6Nfv/E4eVKZrItokJCloi4gP8hdu5ZKMJObm5tGPEUgmF9AdS7DripXLiX38dgzblw/CUVS90vud9OnLzUGz7HFf9u2hRg+fDrWr98h18bBBX8n/I1VrVoGT5++wujRM4Xc5Ptr+F3glX9EdyhqHZGEpnjUYILs2TOJvwpbG9q06Rcptw7JDQ6SGxz0gVOGDSx0sWEhvou8uPfGi+9vZVz/9FrGa2cnGbYWlohmaacMq9gyvnt8k/Ha+asMtps271XW+L53b75Ek6a1oTO062qIWNhYx8H48b3QpUcV+DgCL+98greDjxA5HF/cXGXYWVohVfR4+HbfEfumnEO5UvnQoF5DWJulDvB16UfIwVZgpR3YGzqdj4TMnD17VVq8leGKKVNXYPOW/XCL7oLkReKI6XjZcgUwfvwQRLU19R+i517dOlWRJEl8tGnr64+3du0OIzG+a9cyxIoVHQd2XZW26Dg2UWXEso4mw87SRgYDZTji2EQXv0YOR09XGUprte9gizbHe1cHP78N5TfDll+lJdvbMCxRslQeLF36H06ePAFPL4X49BuO4OnpKsnL3j7fZJA4ZAu1MhxlePm8keHu81iGQkzqoUMUaZ/m8NJ/lqEHJwfc4Oz1QYbiyfqr2X9le/1O8PvksLPMKINt1F56bxl60M/T1bgPqZ/Z0+edjM/ur/HBxUmGg7urDBdPDxnvXZxkvHH+LmPf8+co0TMXqgwsgo2btmLRipmoULU5xk+Zh4FDxmPAsBF4/uKpkJy5ciqpmPZRYqJWjbG49uIxkqTQoVefKhg6dDK8fX702AwI27btw5gxs3D4yEk0bNgFTZpWQfLkiXH65A1MmjQIyZJqikcNGkICKp5mzBiOOXNWimddcMiavxGc0FJBf77+/Tv9VcE7fxpY79OHlOorBpLRfy4wKG2q03Dy5CUMHNjxl0ErfsHvmEqv48fPy62Ko0fPYMaMpZL0XLp0YQm047ln5cppEirjH3nyZJUJtQ4dfMNAXrx4I+2xBMkdPsZgGqoefwfSpk0hgUnr1+8UIss/lLrK1EtaQ/iiUqWS2Lt3lUx2zJ27Gp06DUGbNgPEd7F37zHia00wYDFz5rSiwKYf6ebNe2BrGwXDh/eQ75PBWUHBixev0aJFb2n957U0w7ZI8tOmgKpXektq0PAvQqPbNfwAJtrWq1fZmML2JyKs6lhFPamA6cKaNP73gtds2zafxbnT9xA/YUzcvfMSQ6fWR9z40XHmwB18++yMqJZWsNBb4OCeKxg3oSOSJU8AVydlJpOFNU/86qCPEBVk/Pv06Usyu842IBay9ByiqrBTxxHIkCEV1q2fgjFzmuLQ7ms4tPUarGwsYOFjhZmz+sIsEAVl9uwZkSxZQhw+dF7+3bpNDfTt28X4OP2K5i0YhAb1BqBYjgHoN6I2ylfNibu3X+K/1SdQvHhWlK+omLATx4/ewqcvDnBz80TMJFGRLY/SXhQaZM+RBv36N8HO7ScxbtxilC5dVFQ5VA08efISXt6KQu9vwp9woWsb3Qa1GhTCp4+O6D6uBi4df4gze25j+4ZzqFOtjszcc9y6uw737j7DnlpncHDnNeTokgqFi2bCrh23cO7cDRQuVPin70OFyYABE+XvFy/fYNnyiYgXL5oQy65u7po3nQYNoQQJlAULxqFr1+GivPHbfvnnIOyOmUyEJYlFFCumpbr+TrCVlAQdSRJ6Jb5+/R6NGlUXFRjbhS9duilhHCTMDx8+LWEpffq0w4cPX6Vd+MEDpaaidx1vXV3dkDFjGtjY2GD37kNwd/dEokTxpLWUbdF8bMqUhaJ0vHfvCFq2rIckSRJKcMepU5eEqCFBRPIxMHTr1gIzZiyTv6kkPnx4vTHwg78tKmgZ3pE3b1UhkEhisrYbM2a2hOg0a1bb6K1HImnfvmOibOPffj0ZQ1NfsOV769Z9onZmi2358sXlt//u3QchJYPTpv5nIPLXVNw36tevinnzVgnxx/2RZOL//ndEru3Ybs32/K1bF8n3kydPFQwePFkCZWiP1KtXW3nu+PH9f/lerVv3k+uI7t1HSVCSepxTlK62f0ngmAYNwYdO/xdMvzo6OsLe3h4ODvfEgF9D6MEigYlxTPr6/WEzAe+iVKCZgoouVymGLj04j4TJosLZU2kPffVdKXLT2CtJjDGs7WBtbmUM7CAcPJUZ0y9uhhAMQ7vr0T03MG0EVWrA/ftHw+HzaQgO1JZfb5+vuHr1PgYPmgtrawvkyZsRGTIkkwAZKtPy5cuKxEkSSyG9fft+7NlzArlypUfKlImQPGU0JEseDw4Obrh75wnixrVHvqJp4eOjx8c3DkiYKBZsbKxkX8qbvSc2bB6JHFmLGfdFd++nuHnjCVIkyyqF7M/ahL9+/SbJjJMnL8KIEd3RsGENk8f5HsOGj0fJUnlx6OAJPH/+Hg4OrmjTrjKuX32G69cfolixbHj8+A2cnb8jTeYEOLzvBiq3KYAcRdMgeTSlgI4bRbEKUA/pthbWxvZmNbSF7ebKMh7GECblcW4zW7i4uOHQwcu4f+8p4iWIjvjxYyNDhuRInjwBzHRRTX5nhG+4ivL65oZl1HWgUtLF650J2WdtprSE+xi+RxtzpU3ZN1gmfMGLLDc3D8SLF1Aq689Oh4Z0a8N6M9zKGBjjrRwzbAyt7Q6GhPUv7t+Nz3Q3XGioLfJ3vijhWC4Gr6cLb5XtFMPGBmliKN/pexdXuH93x54+e5EpZzKMH9UJdnY2iGWfxvC6FqJ85D5eulRzdB9VHRUrKUT1iR334e3ljVYtOgT6iaj0Xb58M7y8nJE/fxZkzpJavidPn/d4/dIFfXrOwdaty/4IojakYDtVypT54eDggOjRlTAgDVpdFR5YsWITrl+/i6lTh/xxF56PHr1EmjRho3ymVUnBgkrL4p07h2BuHrSAEg3hDyb4sva3srKQiV62hHJf5TmAoTBMo+YyBw+exqpVm0ShmCZNciHXUqZMKoQjycNv3xxQsWIpxIgRTdq4+R2raeckc7y8vDBx4kCT9/7w4TPev//0y2AXEqFs2a9Tp4Oo00gU+cemTf+TyWaq1das2SYTyiQbaXfAhOJChfJIajWJ1Ro1yuPcuSviBzl79qgw3Z6sha5cuYUjR84IScp2dk5E0LvybzqvhuXxISLQr984+U6WLJmEDBmUusfvhBC/twwZSplc9zEYib8N1f88MFDd2KnTUOkWYZ3pVxlcv35nae9mENLfCkdHJ9jbZ4iUNZXKFx19PBtRo4UsKCik+O7kipKpu0bK7RKR0BSPGgIED8CzZ49E8+a9ET9+3FAnvJlC9WAM7rNUTz+lYFfTZ42EgN4L3non+MAHlubmsDSzQCJbxZ8tqqVCCNhZKD6A0SxtjT50OijtpdGhpFpHtfA9GLm4uBtJRw2RAypBRZVh3DhJ4OHuDXI6OXPkwXcnZ7x5/xm162THk6dP0aHjUMSMGQ2ZsqbA8nWdETOakkhsYZbA6OOXM0cm+dtLrwTQ2Kf2PSGYW1qiResyOHToDHJkLWrc16zNUyFPzlRBWt+YMWOgTZuGMky9Es2MbTfjxg6Rv8uWLi/hTiz0WcTXrgGZHb9y9TrKly+HDOkzAGafcOZIL9QunxdW1paIF0Up9sx0hv3WQGyZm8WAXu/pL2XZ4GOqV0gvLx/VZ1EhxGyiAJWrZZdhaZbY5Pfm+5vVw8fQGm2m05sog7313038G33gjqiWyU2+N5JdfreDuo78t5oOHZ5+jz9PswvKccnM6BP6zeOV/H3qzVO5fWFo91J9HN86K9uhWOKE4rlJWBsustVlDz9TnuvyXSFxi6RNBWdPZZsUiZ8AK1ceQKaMKTF9YlfEi63sq37B1u548W1hG9Ua0WLbigfo2zdfcfnSfVSp5qsmotqCF4o7dx6Gl5dhv9BByMlVa4dJyz9Je7asrVt/CDOmbUWCBLH/qoujgPG3fz4NkQVstRs5cgZmzlyOnj1b408CA9TCCp07DzX+/eWLA+LGDWgSSMPvAMk3ht2RBKxYsYR0Pr18+UYIOyoTu3QZJv9OmzY1pkwZgtSpk/3wGv7v859Y3qBBNQwfPlXUkWxtVcEuE45fgfURr0l+JgSoW1cJRyMqVCghdVS6dCnl2oaBTySd6GHPVHUmzru6uiJ58iQIa/D8mTt3Vhl/M8Ly+BDeYLI4W/4XLhyPHIb6P6DvjS37z5+/MpKOVPyyy8Qvzp+/hjlzVshkiirjonCHFgbq74C1F8n4unU7yf5Hi6a/mXjUoOFn0IhHDYGCJ+UxY3pLW8SiRRPCsD1IFwSl0Y/L+CdAfIkMtRXUA3q9K/R6HwnaiGHlmxhm6a1c7FsYVAZu3kx/VS70VahkgRpEEzdKfHgbAh+Imzf3B/NzaggPqMSVl/4D5i9YgW59KyNl6gT439arSJgwFuyiWaNfvxmIEycG5s7vJ4rEr1+cETt6TFFCmpB0MIeFQa1nASUt20fvGxDCWU9rKzs8eaIEDIUF1FAk3/3WFP4LEs6OJ0oc10iUevkACRLGgfc3c8RNHucHgtDHoEbkZ1PJeV8CUiXtDaSnTiHbzXQxjOtF5aP6XoF9AqPPqV5dRnlPb/0Xk9+mpS4BdIZtTnWeqWJQId489S+VV/B2QRRzVbGuBtIon81Xbfn7oX4ObtsYVko6ZzzbDyZkYsUUSgv84ZdKoMwbZxdkjKVcXN/5/Flu9z1UvLS+fVRUkzHiKoS3N9Ucn5RlHu68hw8fHLBz3WIxRg8IVK++ffsBLt/dsXX+KYzpvB7x4sVEnjzZUaZkLfm9nDx5EVOnLEbxErkwd35/HDx4Rlrl4sWzQ63aRZE/j6KKHDykM8aOmWv01lq6dHK4bEMNGv5F8GJ2yJBuEoZBYiRJkh897P52UK1GBRjBFlmNdIxcoPKP3wnbkxctWieEHffTlSs3S2tq69b1pQvqyZNXSJUqZEQd21idnd2k3d4v8RheiBXLXoYKXsuQVPULtna/ehU0/z4Nfy5oCdC//3jxV/9ZO7+qUC9fvpgEGbH+SpMmBaZPHyaPseaaOHG+EJJDh3YXT8fLl2/Jck2b1kKHDgNFVTloUGdjQCPRpUsLFCiQM9w/p4agRMtELFke8WE2kRMa8ajhp6AfCw/OtWq1Q6xYMSXpmgfVyJ7GFVoDgY/vHbByw3GcOnkLffq2RP16NcX7Q0PkwY3rj/Hg/kv0GVpFZsD7DVDMms11sdCqVSX5Ww8v8UMMKf5bd0hIx4mTA29XjWiQDGVLNFu0g4pjxy7g8eMXaNW6ariu25+CP8VhJFvxNHD46Iz69Xpg0+aZMA+kOzNmTIW0fP/uG1q2qoq69cogVcrMct+mjXukzb9a9VJYuGAz1qzeDTNzc1EzRo1qjbz5lbCHBAljw9HBCZMnD0CFCiW1450GDeEAXpi2bdsQvXuPluM4wzJat24Q6UnI0B4yGR6yY8dBaXulf2CLFnUj/Wf+10AbEqpxR4zoKcf/Ll2aGx9jO3JYgG2oDO1YtmyStG5HFrB9PDi+i6wh2BG2YsWUP842ITzwh5RUotpt374x2rUbICnrDFQNDHnzZpdjVpYs6cWnkepIftf8nVSq1EL8TqmevHKls6iE7exsZb/g/Wp9/unTV4wZ0we5cmXRVI4aNGjEo4ZfgW0Wo0b1lr8587lx4//ELHnatKEBJs6FHL5tnL+G2t5pWiQwrZe+cUqrdRRYmUcFDC2hcW2UWVU3b0WZ5ertjuiWiiLSx6B0VFVgV089wawZu9C2bWP06d1dFG8afj9UpdzHL3cxe+Z23L37DENH14W1pZWJKk6SznXRjapCCzN3mJtZwMKMijNzf2o+nZ8AIbUdWX09a+TIkQfr1x/BtMlb0aJFAyROHMdkXwmKLyHJT2VZC3+K3aD7Wvlddu/+A0icJDrSpEkfoBJYVSz6fW9Xt6+YMnkpWreuYSRn/SohldRrc3/+j6ZWBv7XSFnG0t9nMzduO3U5WiAYFpYbb71ibUBvQsLdR1Eee/l445On4kGpIraNsn7W5hl/2A6/HzpYGDw0c8dVPlNCW0WxGc/gt9k6k3JhZQYb43eRMrqy7U++em2ieIweRVHhxokSBbaWynaNFzcmavcsgZOzb+HatRvInSv/D2thpouGqHbRcPvuf/JvCzOlre3lq1fo2WMMbt68jxgxoopdgHpML1Y8H27dfABHB3d06zQXa9bMkCJbgwYN4Q+2enKQ7Dh9+iLatx+Arl1bokKF4n/l5ifZ1K3bCOTKlVW6Z1SvPw2RR4XKcJclS/4TX3d63oUXKGBIlSophg+fLgEfhQrl/u12HkzZXrt2OzZs8FWmBSWU5/z5q7hw4bqmYPuDQEK9c+dmIqohqfgz4nHJEiV0zy+oXqT6l36hbLMmOIFCL1EmldPDs2bNdujYsQm2bFkY6UU6/yrMdDoZEf2eGjTFo4ZggEQjfYmOHMmI8ePnYc6cUSH0bfzZssH5YfqYECW8VQgUhRAyo0+cITzDB0oLpI15FD8+b8qrqN5rn98Au3efwZnTd7Fq1QzEiR15ZmM1KGEeO7afxOLFW9GwWXH0HFhZZh+jmMcxeu75kmAKmajsDxyWBpJQ54+01puQkH5Bn8FsWbNix44F2Lf3BLp3Gy7ktruHF9KlTY4iRbOhZPHyiB075g/P5et7+3zDmdPXsWzZDjg5OiNbtkxo0rQ6UqVKEWISzcPTGYsXHMTseV1MyL3AoL5HuXIKYZUxQ1XUq19O/IaqVStpbMtWPBV1JoSg3uCz+KPHo991N50o8CViVRLTzdfTUq+2cFsbI2pkSZ1iZ+Cl98ZbF4XAe+mkkHHJDME52WIrvk8WZvEiFQGpbhsLM6XlOrGdtb/WcHX7+Bhb2a9+VNoMSydX/H+iWinb7JubQsDSKimZwYx847lbcH7piPy5EmDWmlVYnjPrD+Sy2vZubtwfYGwFIulIrNswHo3qD5a/aapfqmQR9O7VDjFi2MsFlJoIqkGDhogD002ZdpsvXw6Z0M2XL7tY3PwtYBvitWt3MGHCPAwa1AWFC+f53aukwR/oKT106FTxo1uzZqZJS3J4gEQMyefbtx9g6dINGDdujvhcMxi0aNG8kv6bIYMSnhYQXr16h+XLN+LMmctInz6V/H78t00HF0uWbJC0Y3o9BhVsEactTvPmveR3y4k7Kpfpkakh8oKKxMWL16N589qYOHGB2AeQNAwqSDoSI0f2xLZt+ySgiOFJU6YMln2Cx3L6owbFq1SDhn8RGhWvIdhgu/WyZRtw795jmRm9des+EiaMi9ixY/3RJ6NyZXogQ8bk2LhxrtZmGAnx+PFrrFt7AAtWdoa9PcOBIqa9hYVy1WqlULFKXnx2eAxra0s8ue+IU6duoFGj7rK/2Nv/mFDWq+dUmJuZoW+/5kiUKB5OHr+FDu2HImeuLEicKL4UqVGjBk9Nu2njXhQukhkJEwWvqCHRfvP2OkyetA6rVu7Gxg0HkDZtcqTLoBVHkRV3jj3GtZmnYG5rge8JXuPtk8+YGHeJWD+YBeHMnT17RnTu0hRz56yGq6s70qVLgZkzR/5AbISdd68GDRpCAqpnmjSpheXLN6F377Zy4fr581dj2uqfijlzVmLFis3Yt2+VhKVpiHx178CBE9GvXwdJWY5IZM6cTjqnSPyQePz06QtOnryAYcOmoUWLOqhUSUkU9ot9+45j/vzVYlXAdSZpyvVnuyuVZpUrl/ypgi0gMEX78OFT2LJlQbA/w549K3D27BW0aNFblI9cP96nIXKCisQsWcrK30+fvsSzZy/RqFE3LFgwTvafoIDLdu48RI7ZHz9+xbx5Y8WOzG8dpZGOGjQEDo141BBssBCmVH3evNWYNWsEZs1ajkePniFdulQyi1SwYO6ftk2z/TV4iqWA27B9Qzo8/LQ+xoNO7wMz3TdRHanLqAYk7j5KK+c39++IZqWohqJZJMb06evRoEFlDB/R1Y+STENkwqqVu9CuQwUkiZPGpL3X3ExVOqoenHo/CejczxQNbOCKvZ9f2KkKPUszaySIqRB1uXJ6IFfOgogTKxl69RqDKlVKif9LihRJjReKDx++xO7/zYG5oe27WrUkKFgwH96+fYdDh06jRo22iBMnJqJGjSrPLVWqEDJmTI3nz19j46YdOHb0AtzdPVGgYA6kS5saDg5O2Lv3CP7bMBtWZlED+F0E3hLNhGv6Aw4Y2ErG27dfxBdQb1AC++h1xvXUIYo/pePPt47fdVBb0I1qZHj+sF6qWs/H8By1/cDFyx0O7ora8pmTko596YOSvh3f0MKc0FZ5rrKuIb8gD9nF/I/HM2+9otb87PZIbp09FdWiraWyz8SwUtbbXMdgI4VkzhNPMeR/+f2r3CY2kM8ZYiqF7zsXJzz79BV7Zp5A7ppZkL1SBmwbf1geW7FiG5q1zofE8Qr4fpZAjqXWVjawM2yv2jX6YNGi8X+VmkqDhr8JtWtXkBa9Vq3qSQsnW/rYklylSmnxQwwsXCqiENxD5vXrd4SUOX16C+LE+XMnpf9mXLx4XRKnI5p09AtVbcb1oOqwRImCaNasF969+yR1EQlKldThdUb79o2MpGSmTGmxfv1sUUEy3KNHj1FSU/E1SQbxtQoWzAVvbx/s2XMEW7bshZOTs5BGpUsXlvThM2cuSXoxLUhCAr4+07XpYcq04n8Vf8L8SOPG3eT20qVdonIl7t59hAsXrqFaNYWQ/BUyZUoj+1PTpj1RtWoZSUrX8GfurxG9z/4Jv5GIgEY8aggRChTIhdmzV+LBg6dSGPCgnSoVSZjR2LZtoUjOFdKB+LFVM2yg+4H8UFpqSXqYQ683w/Xr17F58xHEiRNP1qlO3VLSSpLQ3MFIKJmbxca1q08wYcIAjXSMxPDy1CNO7Lgw18Xwl0ytIiBiMTD8jKz7GVR/RmXfadiwmuz3V6/exN69R/H27Ud07NhUlATeXnpj+7cKpkVysO2a6Xaurm5wdHSS2XLO5N+580jUw7XqFEbHzqNgbm6OvLlaok+flEibNgUqVx4D++j+yaNf+6Ia93WDf2XiRAYPTL2dBBxYWVkAhgtblcj39T61/mGb/Xr7ql6a/I7U9G7F41Bv8F3VG9LDXTyV2w8u3+FuMHf3MNyqITBHXz2T23LJlFNWbOuUQqYq7xHeir2A9xW203v6KKnVJ988lVtrc+VzJ42mbF8rgzQxqmU0eBkSvx9+UyY/3jgr5Oqt44/x4u47DOhfA1bWFnh9/QOGdVkJGxtLTB3WSEjSKCOscH7LDdzYew9eHrog7r861KxZEcuXb0abNvVRrNiP/pAaNGiIHCDx0ahRDUlSrV69HLJly4Dx4/tj5MgZOHToVKTxf/Tw8DT4NWaRMA62mObKlfmHgA1e0LMNViMdI7cCTLGKiTwg2b5w4TghrTds2IVr1+6idOlCki58/Pi5H0hSkowkfzg4eUt1v7OzCx48eIKjR89iypRFUkdUqlRSEolJcDZo0AUHDpxAo0bV0alTU7meCYvfr+p7z/ejb2Q0g2WKhoj3lB05ciZ69WojSdT00s2du7I8RkUqv5du3VogS5Z0GDRoEr5+VSx+goK4cWOja9cW2L37sATOaNCgIXjQiEcNIQIvhnnCnjt3paTdkXSpXLmUFAe7dx9B3bpKqnB4gSd1hl/Mnr0cnTrXRZQo1rhy9Z4Uw1Urd8O3by749u2brKffBNsVy7egbbs6OHfuCnLmzIA2bWuIEqxSpRL43/+OyMynhsgJe/uoePPmE3LlRKQBL7Y4412goBLM8eH9F0mFpDpl9erpvzS55qC/XtKkiSRsQK/3kX3W0+etYSkdokaNIi3ZofUxCghDh87C1i0HYWNjjSxZ0mL6jIGIGcvXP1BD+MPHR48Lu++g1u47xvvadS2PJq1LinbXydEVc5utk/sTJY6N9++/IrkimvwlOMly6tQmw7+06VYNGiIzWDfVqNEOzZvXkVZAnl+YLDx69OxwJx5ZJzGB9fLlm+JTRz9GtrKSmLpz5yH69p2AL1++yATYw4fPcPSoElZFMKWa60q/WLaKk9wpV644WrbsLXXin9wu/jeDtcebN+8R2ZAiRRIZnNglOUoCctasFejdu91Pg1y4D3Lf5WC7a5EieY31v999kCnFJDaDqnILDrZv3y9BNTdu3DN4t9YQAl5DxIGt+ySpDx8+bbyPwpOLF3cZw15KlWoo3owE97GgQj0m+0181/DnQWf4L6LfU4NGPGoIBViYbt26DwcPnoSbmwfGjp2Nli3roXv3EahTpyKg86/E8g1aCFwF6f85ftU9vhg0aDL27z8hf7NQdnB0QoL4cWBtsxtfvjjCzIxm1VFx/vwOk5l4esicOnURvXt1wZYtezBi2AqMHtNLSJ1WrfqjffvGWpEcCXH5ylWcO3sPXbu28qN0jDwHcVUBGD9+XIwb1y/kr2NoVVZVnSTXWSQzbZJFMs36ixati7t3D5u8e3DWVF3fJ09eYPOm/Zg9ZxgyZcyIY8dPYvasNRg+osNPn6vAv+JOF7D6UOe7rI/exfBMReGowsnL1dhOHd1KUVe6eyuF4EMHJWTm5mdFLajHQ7ktlNAFKaMpZK/awuz73j/bHnqTYdqSH3yo+2IsG+XWzUtZ75jWCnkbxeJH24bYhmXtDMnVlVpURf/mVTBu7Ebs2HAeY6c3RbUKZeQxF69PsIlphd0XhuHRvbfo0Wwxjhy9jHy5ywdjLSPP70SDBg0/V011794Sbdr0EzKvVas+mD9/rLHNlOqd8ALrqMaNu8vfdna2orynd7GDg6MQKCrmzRuDZMkSG/9NNdHo0TNl0pktiO3bDxQfNKq/EiaMJ17gTJDVELng6Phd2vlJDEdmkChq0qSmjJAgINKbykgShLQDoCdk/vzVsW7dbAnYCS36958gqszDh9fLb6dv33EoXDivBElpiBhwsuT27UMycVKpUgs5Dh07prRWqzh+fKPcpk9fEpMnL5SEdQ0aNIQ/NMWjhhCDJ/SpU4cIKULykeqtadMWi4n4woXr0L6D/wO5ITWXLZw6jwDJAr2/tky/abs+Pj7ImLG0/M0T+6FD65A0qZImq4IzXEWLvMOHD19x795DE7UjUbRoPhkEZfJ9+ozFvn3HULlyCSRIEAf37j1Cxoxptb0ikoDf+fr1O7Blyz7Mnj0a0aMFzQD6zydjzIy/j5o1K2DhwvUYM2a2JBVzmwSNNNP/9PNSUdCocVV8/vQVSZIkQKOGtdGwYVfcv/9GQg1gTP72Mvmt8n19U8F9icyAwPv1huercPZ8JbcWOtoh6BHPRiFZLc1i4qPbS/k7oZ1CTrrLZ/VtvX7mqLQnO7g/RUXDNXhSO+UYYGmmhBfodJb+PD8D877k/KOZybZim7leb/i8OptAPpthWb0bzKB4OOaIo0gQvQ1t5NEsbU19aPWuxpb16FYK8Whm8IO0MVfasYrUzibE44OHr+FTXiFcbcyVZZNGtcLDb2/k72bNKvwB+68GDRpCAqqjGHQwePBkFC2aH23a9BfvOyYP06c1rNs36dE9d+4q8cZjKyonYf2SNS9fvpG6qnXr+ti6dQ+8vNRjvwISKhMnDjT+29zcTBSaCxaMFQ+0nTsPacRjJAMVrCTI+J1SFfivgZO5MWJER79+4zFz5gh8++YonpBhgbVrZ2H69CVSU3HUq1cFixatRa9ebRERYH3o3/bgXwVTx9kFd+XKrQAfV2ppYPjwHhG8Zho0/LvQjk4aQgUWqEWL5sWbNx9Qo0Y58f+pU6eS0prTZwKuXLkdZlu4Y8fBMpPFYmnNmhk/kI4EDaMbN64h67BkyUTxyPvZujPI4+yZq/JvpUg+GGbrqyHkeP36HTp1GoKKFVvgwYNnWLNmuhBl/yJoYZAzZ2YxwKZil8bo9FYNLVictm/fEBs27BECkP8eMKAThg6ZhqNHz0nbXHhh1bIjyJWlOw4fvI7fAf8TEpEBseJFw5KjPVGvRZEfHtu98yJ6dluCeg2KI3bsHxPUNWjQ8PeAakG2lLLdmn5iVO6w7bR5895Yv35nmL0P6x22hdIfb//+1eKD518hRhsQhtuULFlI/NHoafwz8Plsw2b7IpVl/JtekBp+L3jOo99h1aqtMH78XEyZMlhq9n8R7IYaM6avkOjVq7eR+/77L2x+V3nyZIWNjZV4nBK8Hjl+/Ly0i9N7MLxw//4TUe9lyxacboiwQyQsqQQMH7p378gP91OpTSELj30VKoS9jZGGyA0zyg50ETw0wYBAIx41hBqbN+/Bx4+f4eLiKu2gEyfOx+DBnZEuXQqsWLEFPj4MmfEtPJXCVhmKekpVOSpJuooKiYQh1VLK89as2YZjx87hzJmt6NevQxi1Q+uQOXN6fPr8DR4e3ihZqoAQLlqR/PvBfYhJ0Xv3rsDIkT1ha0jnjSzgfumr+vv10kEJgPEL7t/qPs7bYcO6i2/N4MFdMXfuaAwYMBEe7t4/bRGmes9H7yzjx/VV1ilB/ATInTsrBg6cCGdnVyE4ach96uRFNGzQE/fvPTMI4y3g7eOFs2cv48yZy34Ug+ZBaFNWl7WQMbDfSsyZvhujxjRFhQr5YGUWT4aP3hWuXu4yHD08ZNiYm8tw9PCU8cXVVcYHVzfsevpExqr7F2Rc+HBMxmvnizLcvR/J8NY7wEf/3TBc4aN3M9w6w9PnnQwPn+cyvrjdxCe32zIUpaeXn7Zsb3/Dy/h3NMtEhmErg+nWknCtM5eh01lIAjaHpZm5jCgWVjKcvRxlpLaPgzQx4iJJVCVAicNCF1vG7VvP0XdALYwaORBW5qFvB9OgQUPkxcOHT7F69TaZgMuaNYO0hNLnlzYeDCH79Cn06bnv33+SNtCFC8dj165l8vphgVSpksst04Ppq8aQHIanafi9YEAR1asbN87D6tUzkD59qn/6KyGxX61aGREcsO2WJPzVq2EjlGjXrjEGDJggHVRsFZ8zZ7SoKtu0GYB163aYTHy+fPkWGzfuNqrvQgK+RrVqrcUS4cqVPWHyGf4mBHS9yBR0pqLv3LlUvLA1aNAQMdBarTWEGkOGdEOWLBmkvYYzfbVqlUf79oOwePFEfPz4Fa1aDsS48b2RKFE8Y8ummnjtv9Xxx6RqXtgDxUvkw+zZYa/06dmzNerV64TNm/ahUeNqSJYsIR4/fiGzYBoiHpyBXrt2m5BgFSv+qL74/TAYlQdrzib4n0FtayZBRlhYREGLFnXw7NkrNGtWS4IGaGswcGDnn76Gb7K82u78o7cqf7/r1m1D48bdsHnzfBQqlEcGZ+zZjkWFC5O4T526JCpjzqwfOLBa/Mh+xM/SlpX3Prz3Oho1L47adaqbPOrs6YAH3z7L308dneT24ddvJsv4GAp2eim+cFTsGjiTSFx5/0Fu7W2UFukUhpbExFHtTNbKw8Ubya3t4RwlitGDUU3wjmJujTg2mQzL+k/zVlO5fb1qffcDgx2E4TFzQ6uTuaEVGzqeapX7vPVKG3W8KEqLuYWZQqrbWSjEsJkuuvF1feCErBnbIF68WDh4eIGfddKgQcPfioIFc2Pv3pVCXtSp0wGVK5eWduhu3VrKJFTz5r0kaIOKwpAiVqwYQgq6uyvH0bACzxEdOjRG8+Y9hdCktQ0nqxjCpuH34Nq1O5g+fal0AZEM1qCgadPaaNq0u3RSjR8/AD16jBSFXGj9GPPnz4GJEwdIK/fQod0k+Z3+8U2a1BI/1F27DiFHjky4deu+KIMZ6kR/8OLF84fo/das2Sq3vwo0DG9QtPGzLrPIghIl6ott0aZN8yPhNYaGiIAqf4pIaHuaAk3xqCFMwJaNkyc3YcGC8di27QDKli2KAwdOiI8ii9sN//0vVK9PrxS22obFTL9f0Odl1qwRUggw4ezFi7fiUanh94Ap5TTRp9eUVhCYonr1Mjh69KwEzNBugHYGp09fCvU253Ym6U6z+b17j6Ffv3GSGs9AABZmfK+8ebNh0qSBojpmAjYTJklMBvWilUTy27dKm1G9xkWxbuVx/C4c33Id7erOxYM7imdiZIazs+IDOWVaL2MaowYNGv5+cMKH6rSjRzfg2bOXqFmzvKgdy5QpgunTh4vnb2jA40n16uVw584DhDV69mwjBMT589dw+/YDqQE1/B7QloX+oGytZtq4Bl9Q6aaQ/EclWIZ2BgzJDAtkyJAG+fPnlInabt1GSIo207YnTBiASZMGSacJJxF43UEl6rx5q+T38uWLQ5An6V+9eif2Vt27t5L7vn4N2nPDGhRrNGnSHY0adcOfAJKO9DHXjksaNEQ8tCsZDWEKnrxjx46BkqXyY/SoOUJoZMiYBnNmrxKlUJeujWFl5av+8VVkqWEa6i6p93PrhYkTF8usbVAl8cGZxEqfPjWqVSuHEsUbIlmyRNoF/m8EiS36d4a1gf6fN2elM0lNph2BpZUFateuKB5f7do1kgK2bdsB2LhxbiBtcmzXNgTCGAJToDNt5/Ftk9ahRIn8GDFiBjw8PDB8eE+5l4FRNGKn/2PfvmOFqJ8woT/OnLmCRYvWifcYf9ck69OlSyUXyyRGWRC/evVWBlvubG2jiL/Rnr2LkS9vOmxcexJePm/lPSx0ihL6q/t3OHgoROb1DwpJ6eKpHB8yxI4tt1ENSdA0aPhi8KBUk6RtDY85uiv3vzPMvL/87gxXT094OLojaiw7HN14BQ26l4Z1Ujt8cFXUhxliJDYG1OiM21xViSpKRLZo+4Ve7wkPH0VlaWZII7cwU/ZbSzNrP0pHRSFrBuU7ihclgeH1TdvvzXS+KguqIt3dPVGn1gijb9TrV++xbOky9OjZAjHsle2hQYOGvxs8BpcoUVBaMUnmkaSgIit+/Djig9ynT7tf+i4GBPpHjh49CytWTAnS8sEVBpFcqVmzrRAkXbo0D/b6aQgbHDlyGk2b1pS2Ug0/omXLuujadZi0XJN4PHHivIQp0S8+tGBnSocOg+Dq6o4iRfIYVb9UBTPMiYSktbU1OnduhuTJk+B//zssRDHbskkSp02bQuoqHgP81lQfPnyWECcfHz2aN68tATYEjw30AI8ofPz4RbphevUaJf/+7785iOxYtGi93A4d2l2OqVOnLhblOIlgDRo0hD804lFDmCNlymTYvu2QtBDcvHkflSuVRpnSRdGr12js2nUStWuX95NwrSbIqgSIuQkhojcsd/78DWmLNjMLexk/FV8Mo3n+/BWyZ1faLDVEPI4fPyfEVuQlHX8H1NRohdiqX78K6tbthDp1KksAQaFCuUX1yCTUgNqcjanxxt8XjInMcreB7OLrd+/eGlev3oGzswtsbW2k+GVb1s2b9zBixHTMnDUMp09fwZkzF9GxUxPD8yyEqHzy5CUePHgiRTON2zmTzKACKpXV73Plqo2oXq2jKB8rVsovHoaENxTy78V3B9haWJi0TyeOrtgrfHFzMyHrUttHR1ID2UrvRyKmdUCt38BbF1cc3nYNt9ZcR7IOSnF539YND+/cQafsOUzIT2Xbeflrn1bfW033NjQK6HTGFGszA8ForjMlBPUwkKPer2FlpiSyq0nYPnA2WdZH72J4WQvsPXgG/buvkH+fPrsC3xy+omvXcXB18UCFisVQIL9GPGrQ8K+A3R7Tpi2RCYh163aid++20hJKX7qxY+dgwYJxwZ4wvX79rrRbFygQPi3QtKtZsmSS+NeFlX+khuCBHULs5lm6dLK26QIB66jUqVNItwdrlk6dmgo5RTIqtF03JLOqVCmNffuOS8IyOz8ILy8vmTRgcGD58sXQunU/bN68ANWrl5XHOZn75s178XplTUVVY5IkCaVlO2nSBIgbN7ZMBj958kJeZ//+E/K8bNkyRtj3zOu7IkVqixLbwcFJJj8ic5fSly/f0LJlH9y79xhTpw6RY+nEiQtw6tQFODo6acTjPwY18CWi31ODRjxqCAeMGtULy5ZtENKxebPeaNKkphTKo0b3ROdOwyWEhjOwwQEVU+qsXngkrHFG8Wd+eRrCF61b9xUPwZMnN/8zKcYhAS/g6tatjIIFa+D+/aNCRNJHiO1sDIUJDezto0lrNdPjy5dvKu/FGWH+9hhAkChxXMSLFxttWg/Ahw9fUKhwLhQskEeIRbatcPwMzZrVgLe3DyZOWIi9e86jVesqyJgpBSICyYungONLB7xYcFMUBuZWFsGM+wm7/ZAFu6L6Dvjxq1ceCumYKUtSLFs2DlGiWKNd21Fo0LA8Vq3Ygzx5skT4emvQoOH3gRNMrFFog/H69XucOnURW7bMF5XW8+evRVU1c+bwYBF87u7u4jsXVLIgJOdQKrw0b8ffA4ZnlC3bREjpBAmUSa+wxF9SUgn69m2PokXrSOdGpkzppCW6WbNe0p5OZXFoMHx4D6RJkwJDhkyR35CdnS3c3NzQsWNTISUJ2ie0aNELlSqVQuHCeZA8eWIhRDmodg4MJPvWrZst9SAxadICCd+MCHCiY+XKaeI3y4kRKjN/Fzj5HbDnuAJOonftOlxIR3rnKttth4hNOEFSpUqZCF1fDRr+ZWiKRw1hv1NZWEiqW7Hi+dC1ywhs2Lgbnbs0QexYsbFixVT06TNaiud+/doZFYxsWxToAto1veHj7Q0zMz7Iakf3y4IoKEUyT/6cMXz48LnMLLq6usmMIYt8tg9oiBhwNvfKldvYsGGuEFthjaDuD5Ebvvt8mTKFRcVApE2bUsjCzp2HiD8QTc0DfrY/pbAuYIN5CwtzLF48QbyCAmrZiR7NHitWTsDFC7dw9txVzJ61CitXTg+SBQLVl00a10bKlAnQof1InL14Gc6en2FuoUOadInwyuk7zr97J8t+dFHUgF6GpMd4dsoFtaqIdPXyRqyoymdIElVRENpbK/929FBUhk8dFb8jpmJHt7FG4Tb5YFU2ESy8zKA308HbR48U0WIbA13UJHA1/MXccJ+ZYVupikS/thDW5opqU69X3lNVSzIxW/6lV8JxPrk5oFzu7ibbI4qtFXoOrY4qlfLBzdVDfgcLZ+/Dtk3n0KZtTfTo2RgW5vY4d/Yq4saNAUtLc5QrVwwW5lo4QNjiTz82aPgXkCdPNuzatVwsL65cuYVDh06LQqtr1xbYsmUvmjfvjXnzRktIRVDASSC2awYVQTmFcqKKtR3rKXo1s/WTSi+uOy07NEQcaMlCYrpkycCJq9Dgz6+pfMG6k2Qf637WQBMnDsT27Qcwe/YKjBnTJ9Sv37hxDVEzkhzjBIJ/0IqACkv6QLLtmyFSJCODAtZeDHGqWrUV9u07hlq1KuDz52+i4ONnCe9k8Lt3D4uS8/17JRgwIrF48XpMmbLI5L4BAzqiVq2KMmFL33IKXUjAU1l64sRG4/FxxYpNWLNmJlq27C0e5hr+LXDCLaIVupFZERyR0On/grOHo6Mj7O3t4eBwD9GjG1JENUQKsH2BARQ86ao/OiafDRw4HjlzZkKDhoqK0Uf/3Z+3ndICqtcz1doNjRsOwrz544QM+YFE8Qd6Cr18+Q4pUyq+bQFh9eqtP5izL148Btdv3MOB/adQsmQ+tGunqL60LKrwLx5YuPTooRhkhzXor8NCLEmSv8NYnYfsdu0Gik8QZ7cZ9sKgmQkT5mHVqml+lvzZSe5n6dNBx/79x+UChy11QS1y9fAWQ3V6qhLJMsZH1xm18e6bE/YcuoWYGWIjSdyY8th3g+djUkO7diKDosfJwxPpYhhatQM5hUU3zIA/cfgGLx89PN084WYOfHr8FYdnncPrl+9RolxWDJlQH0ns8iqv5fMN3vqvRr9HtfXZry2E2nJtprOW45NynzJxoqZOe+uVECwXr/fK5/B0hb2Vsu7nzz/AmZN3sWbFUZP1jRo1CrJmS41+/TohU0bflil6Y7Zs1Qdenl5YuHCCFn4VxmBSfMqU+eHg4IDohtZ+DVpdFZmDEf77bydat24gthYqjh8/jyVL1mPVqulBusBZu3a71GLNmtUO0vs+evQCadIE7iVJD7q6dTtKS6MKhsR9/fpN1o1EJ89X6dP/PmXUv6R2pMKLk5IBEV1hgUePXiJNmr8niHHz5j34779dQjrSq54keu3aHTBnzihRHkYUPn/+KirCGTOGi1IyOHVhmzb9pHOIuHJljyg3L1y4hhgx7EXZF9agnzc7Xqg4XLRoI2bPXirbir7jceJEnHiDikZ6jtMjnr7jfsHjTYMG1dCoUXWT++mv+fHjZ1GYah60YQu2rtvbZ4iUNZXKF114vhBRoyt+7hGF746uyJe8faTcLhEJLdVaQ7iiYsUSknjttxCmQfqAge2xatV2fP+uqoh+jowZU8psYHDAlsarV2/L8Ju+27hxdyEdSdxs2DgLU6cNlNmxsWPn4/KlW8idJzNOnLyMWrU6YO3aHfI6GsIHTPDbvn0/2rdvpG3iIIK/pYUL2T4VT1rvCBrHf/qkEGYRicKF88oFJ2eWgwOSpUmTx0HNugXRYaJSED48/wJ3F1+Fw8OwTa739vLBngWnMa7uCkyrtQIbhuyDw1dnFC6TCQ7fnHH/zmuEBzgBcuXSYwzsvRLHDt7E82dKEI3zdzdcuvBQ/ra1s0L7zhVw7Mx4nLu4EIuX9kPGjKYt65yh79evNezto2qkowYN/zgSJownqdF+SUeiePH8otw6cuRMkF6H5wyGhAUXVDGy1dsvwXju3FWULt1Q7hsypKtYptA/cubM5di6dT9ix44px/w2bfpj8ODJeP/+U7DfV0PQQRVY797two10/BtBn/ehQ7uKZyLrUnookpRie25Egr+VXLmyynVLcOvCVKmSi3Lz0KG1Qjqyi6Jp055o3Djs06Zp75MnT1WkT18SWbOWx7p12+X+jh2biJggvMDjT58+Y2XSWz3W0ZecxxSVdKRidO3aWbh16yB27lz6A+lIjB3bR3w0a9Rg5oCGfw263zQ0aK3WYQLf0AGtcz2oiBHDDqlSJ8Ht2/eRL19WUUGZtFwbOXEfeOu/o2Xb8ujUfiZKly4AG+ufh4+cP39FDNgfPXqKrNnSShrjieNXsGzZZGTOnA6TJw8Sc2fOzJEEzZE9K6pULiczhlQTPHz4BM7f3REjRjS8evUGlau0QJrUKVCvXuWf+q1oCD7OnbuCR4+ey0WJhqCDRXHbtg2QIUMpUQ+Kh5NODwfHT4ge3XemOXB1cNicAseOnY02beoHOW1eeWczxIwRAyvX9UTfHsvxbdMVpMyRGPeOKAV+kjgxpD2aMLdW9gsbNXTG8BoMklHvu2Boz45hWDZHXCUoxsJMWXr9kL3Ilikd8nROB53eFsWL54OllZVMZly8fAwL5+9G6bw1/LRaK5MUFkYVoyGZWmfYR/XqWljATE0NN2znZs16IGeudIgVMw4uXLglKkVzCyusWngUo578J8tkypwU1Wvkx/RpQ5EiRSKY6X4dplSieDEZGjRo0BAYaMVw7NjZICXy5syZWRSPJA3ZMvkzkFBcvnwzrl27gXjx4oinGydvy5YtKv7duXJlxvbti5E0aSJJ3CbOnt1mVEU9fPgMt27dlwt9toDS0zlWrJjS9UISVUPYgmEjgwd31TZrMMFwydixY2DEiGmYNWukhOtRFReRYFggVfjDh5taswQFgwZ1lrTsQYMmY8SInpKSTYR1ojnV0hQMdOjQBAkTxkWUKFHk91ykSG6ZcK1Vq510agTV9uFn4CRHhw6DsWTJBJw8eVFSx+nFydAqVd3Jf3PiZc2aGciaNUOQrieo1Dx+fGOo10+DBg3Bg8aUhQH8E44krpIlSywhBhoChoODCw4dPIsB/VsLuQi9j/HCn/AxdE/yYt9MFwWJEiZG+fKFsXLlFrRv1zzQzcoE2hkzlqJNu5ooVborzHVR8fjxCzx+9AYZMigtPokSxQ90xpCPcRQsmAe9eo0S37wxY3shio2tJPuyZYhJdPQs0hB68AKGoNEzfXA0BB3cX6l6UdNMO3dqjhbNB2PWrGFIkjShYSm9SSuwX3/C0ICBBt27jxDVZf36VYP5bIX0TBQnP5Yvy4UxY2bg6f/eomu7Rth7+hgSeFnCxlJRarx1URTRDgbFsrlBOR3Fwhx2FsoyGWIpbdlRzJXPZGu4/7WzE1y+u8PZ0Q3du3Yx+rZSncn2e3o35stTBnM99yND+vK4e2+3bB81oZresqbbzMyUgDSB8pyu3auiaSMlQXTMuI6oU6uOfE9r/1uJUcNXYtKMlqhWsbHh9cLXf0mDhr8F9JylV1dEtjz+iWDQWN26lYK8/IABnUQ1z9ZITsIGBnoKU0G1ZctCuajnJG3Dhl2lo4Wgd13GjGkCvcDPlSuLDL7H/PmrhQghSdKx4xCpz4oWzYvatSuFuyfdvwB+NySAe/cejRUrpmnbNJigx7vaIcVurc6dh4rlkhoEE17gJMDIkTMkAXvHjiU//T0GBtYaDIzi9z9o0ET5fVL5N2fOijBd16dPX6BatbJo2rSWiRUD35/1aJs2DVGsWD15b6ZHhwYFCuSCp6eneNjyGMOcAKpCmaSdL181IRwXLZoQBp9KgwYNEQGt1TocMGHCfNSr11mCSzQEDEtLG5lZfPWK7Ydm0OmiyDDXxZRBUoCDoQ30VuNo2aoaduw4jA8f3xkJSr/gfVR8eXp5Ik3qdBIOQa/Ifn2noVWrejA3EBNBAVtUOGNIkmLUyNmYN2+VEMmcSb5+/Q569hwqLQYNG3ZE164DMXLUDCxfsUF8YTQEHbwAYXFCgleD6d7869ALPYoUyWuckSchTpVDhw5DcP/eU2PQiQIWseZCdoUF4cULUapdJk8eGGLDZK6HtZUNRo8agAXzJ6J0qQJ48+QTsmRLhtfOzjJ4guJw8fKSQT9HDobMpIqeQEbSqNFlJLSLJiOWTXTY6m3w+uRHzOm1Hd27tA00LIoELFMnGbJQu3ZPODt7ykQHB8NwONQmCT18ZPh/BQ6SkhyZM+dE8hSJxOC8bu268MF3XLx8ARvWHxWV99Tx2yR4QQs00aAh6Dh+/ByqVGklKhsNgaNCheJyG9Q6hF52VD5u3brvp8tRFUlCRlUS0bubYXzBVVJxcpF+ziRXevQYZVR4nThxAUeOnJaaqlq11mjXboC0ZE+fvlSsPDQEHTwfHziwGh8/fpUARQ3BA8ktkoAEJzqY3MzwpmXLwlcd9/r1O7lmZMgi7RRCA4ZO8XVatKiLN2/eIUeOzGFCaF+6dEMmnN+9+4SGDX9sX1ZRpUoppE2bAv37jxcFdmjAyYi2bRuKUnrjxnlCOtKii8cH1nV37jzC/PlrQvUeGv49mOl0v2Vo0IjHcMGHD58l0e/evUfaPhYIOHu+afNcTJq0FNu3KQm9vwJ9GNu3r4Pp05bDxSXggmrlip0oViynsZGURe73786ws1Paf4IDmiMzBY2zj5xR27p1AU6d2oTWresje470iGJrgzlzB6Bz1/ooW7YwDh44hYwZS+Pp05fa9x4MXL58AwUL5tK2WQiQJEkCvHjxxvhvzi5PmTIYQ4ZMCTdvUnrs8PiWMmUSUbOEJaLHsMV3J9dQvYazsxs6tpyHly8+Ys68zqha7Uelgl+ylKmr+w+sxJ3bD1GzWt9Qvfeli3dQoEAWtGxZ11is9+k1GTNm9cS+Q+MQLbqtsRVRgwYNQQNbHql4ZKudhsAxdmw/uSWp5+bmHqRNxWCF5cs3iUdaQFmT9HIj+cdzjQrWOPHjxwnRV7F370rxgJw3bwxWr56Bixd3Ye7c0UiePAlixIiOzp2bYejQbqhdu6K8B70jqQT7C3IwIwy0X+HEvhKOqCE4SJIkodQ4Kuzto0n9z8Ro/hbCA7xGuXDhOqJGDXsfZ3qtOjg4hvp16NdKgq9RoxqYPXtkAEpaUx//3buX49Wrt2jfflCofrucRDl06JSEZqmepTNmLJEJEx5HKlcuqdVUGjT8QdAUj+GANWtmygGxUqVS4fHyfwWodkqcKBFWrZ6GPXtOYfzYpbh65QE83PXQwRI62Mgw09lJqiwHvTQrVSkEL2931KjRHsuWrcWuXXvQu/dIlC3XGNWqtsPt20/Rvn1DQJ5jifz5qwkx8ysPI/+gKXOPHiOkLWj5cnqz6cTH5Nz5K0ifvhRmzFgDVxc3TJ22GgkTxsHx4xeQMVMaMXevUKGZKPj0cDcMJnN7B1HF9u8hf/6cuHjx+u9ejUgK//uM6f5TtmwRsRY4fPik8b6MGdOiYMHcWLF8q3Hf81U6hs7imIU3E7UzZEiNokXzISxBpXPenGnw+ZEj7K2sZFiam8nw9PGRwZZrjpffneHu4ykjpnVUGVbmlvD20GNEv/Vo2LAk+vbpg+RJ8wWprTxpksTS+kelA5fnYHs6h6pm9A+qH728XdGkaXeUKtUIrm6usI8eE/fvvZDjB2Gms0SWrOlwYN8ldG6/UEzOEyVMGGzV6f/2HECjRl3QvftwrFih+RJp+LdQsmRBHDmyHlOnDvndqxKpQTJgyJBuMgHVokVvuWD/9OnnYV0k+zp0aCyhGm3bDsDZs5cxadICUR6WL98MvXqNwYwZw4znjYMHT2LWrOWoUEFpsw4OaKkyatRMaf0kucMJaB8fb5mwZes202mZNssJLQZFcJBgoJ/b8OHTQ7xd/jVQMUeyiRPvGoIHTqg6OHzH+PFzjS3XbB8eObKX7IP0MAxLKMnyvXD//hN06dIszL8ueh7evHk/VK/B39/Nm/ewcOF45M+fI8hdLnv2rJRbelYGB6tXb0X27BVECU1Qaf3gwRPj4zlzZpHwnYkT50v4T0DhMb8CjzUNGnRBhw6DMGzYNPm3hn8Haq9SxP6ngdCIx3AAZ8g4y6Th14gWNToWLBiP9OnTYtOmg6hevQvWrv2fof2aZIklzGAnQ/7WWWHchPbYun0CXr56ifsPHqBBo5LY/b8pWLFyJObMGQJLSxKXSvsji+NSpQqJYiI4YKHBWf7163dhyZJNqFKlpdyfKWN68X3JnSsbatWqgA/vnFC1ck8kTBAfhQvlRceOTTFwYGcp/NVWzbBqb/1bkS1bBjGe19rU/cJ/FppCQJq2+uqQLVsm8XGaM2e1oYVXAVUju3YdxbNnT6DXuwlpr4ZgBRUqaalYGHxBq1Z90bXrMIwb109MxcNa7Uhkz5YS926/QgK7KDI8vX1kRLW0kGGmI5kHfHN3x/2vb2Wop/QPD13Qu9UylChRFHXr1Avm706H5s3rIF68WPjw6SW89d/g7u4ktg4+encZfr8D5XvwhqurC8zNddImlSN7ZWTLlhmFCufGrFlLZbvR6mHggG7w8rRAv36d0LhR3RCRvzeu30P9BhVRvkIhnDmjGKpr0PCvgB6Cmr9j0NGsWW306dMely/fFI86koq0jQkM9GvbsmUBqlYtg507DwlZsXbtTOzatRQbNswRVbgKNTCCQTbB/x4tsXv3YWzYsBt163aS0BrWa4MHd0GmTGmkRbNBg2oSTkGCk7VbvXpV0LVrCwlT0xA0kBhiF8n581e1TRbsfdQKy5dPFtUeLZb8tmCTdFuxYlOYbVMS+FWrthZhBH8DWbKkD5frUXd3dyOJGhzwmNG79xghADn5EFwPVlo5DBzYSQJh/Kpxg+LpmyxZIrRt2x937z7ChAkDMHDgRCORTksJ7t9Uhy5dqnxXwQVrNgpF6HNLuwcGNmrQoCH8oYXLaPjt4MmsTt2KMlxdnTFixGw0atgb1aqVQvkKhREzZvQfnmNjY4XBQxQyUEWMmNFEqeR3RpIn3erVy4aocNu8eb60d1lYWEgxIu8RIzomThxoMltJdSP9j36Epm4MCqgO4wUJT/xqS0ZIfQMJEpj04mTRyIKESYWtW/+9Fy0snnhRtnnzHiG91RniQYM7Y8SIeVi2bLQku4cETCSlp+nWLftRuHAeLF06KVTfza+QNn0iPLz/GtmRPVjP27PjEnZtvohJU9ohfdqQt+1Hi2YnwTPOzpbY97+rGDViGe7c3RPoZ6ZiZ/nycdDrdciUsRLOn7+OTp0ao0WL/jh69DxKlSwmLYpsZwwNvnx1QIoUiZE6dVLMnrVG9nGtUNagQUNg4OSnGuywffsB1KvXSYg8koxUrAcE1kr+6yW1vVEFjz1cJiSWEXXqVJL3Z93Ec5R6XG3SpKYMFVQz0SNOaxUOOb58cZB2a/U7C+35gvYq7AA6ffqK2B4NHdoTadKEbVtwZAHrRp6za9fugK5dWxoJN95H//5y5YpKgGhIwOuT+/cfi18iCS+mwfv/jYU1MmRIIwRejhyZgkXM0WuVtXPNmuVDXPfxGuzt24/G1yxVqiH2719tDJYMCN26tZRRsWJzNGrUDdev70O9epUxcuR0jB/fX76f0IZRctKDkyhcD6qqaY2WL1+OUL2mBg0afg2N4tcQKaCqk2yjRMekiYMxZepgODq5oFXLwejcaRT27Ttp9Cxi6IyXpznu3n4HF2dzmJvFkGGmi27Slv3q9SucO3cFOXP6nmxJbHl4BHXmTwdbW1sj6RgQeAIMmHREAMom///Wh0iJ9ndBj507D+Lhw2diLJ8hQykZBw4eN2lPD2qr+p49RyTprkePkfj2zQmlSxcWQm7lys34E+GrOlRbps1ESaeEK/lujzJlikjiut99u0CBHPDy9MDrNy+h13vICOgdAmrnvnLlJqpXa4cWzfvh8KGzKFGioKhowpN0JGyt7eSCNqa3BZJGjQZ7aysZ3z29ZFiamcmIGyUK3jp/x9MPnzF9/HYsnX8AM6aPRoZ0hcSegeNnCMhziBdnZ85ch8t3HXp3XyGko62tDerW6SqWCUrKtTf0ek8ZhmfJ0OkUJSoJWgsLM0yZMhBLl2zG4MET4eD4zZ96NTjQi7fUlcu3EStWdDx69Aq2tgzi0po2NGjQEDSwS2PbtkUSBjNt2mJRFC5Z8p+J+ojHRLY/B94WqZdlOKFXsWLJHyYPg+rjRpKFHSg/O4aRCNBIx5CD38X//ndESDLWVWxlb9Omf4jahElg5s5dGZUrt8Tu3UdQoUIxUcAOGTIZfzN4ns2bN7uJWo/7bZMmNSRcKbjgb4RWBuyeWrRonXxH06YNDXfSUe0qunHjbpCX37Bhl1ge1KxZQTq7glZvBPz7ZzDPu3cfpD4l6chtWL580yCFRnGChNd9HPSWjBs3tuzTwfksAYHHvaVLNwgxz5qZnrXRo4d9B4+GSAwdBS4RO7ReawWa4lFDpESSxInQoX1TtG/XBLfv3MHOnUcwa+YaZMiYEu/efoaj03ekSZ1CThijx/RA9uwZjMSKXk9ywBtbNh8Q/6CBA8fj48dvxlYjb28fZM6cFi1b1kfWrGHf2qAh6PDRu+DKlWvo07c5WrWuJaTyrFmr0LXLCKxaPQn58qnenGxvVeDrt2daDJGYe/P2PYYM6YoaNcob7+dFUqNG3TFocAeYm1n+UCT9mFTs+07K/39fm7xer7SWeOu/yq2FWSJ4+yh/k2xXYA5LKzMUK5YXs+esQK+ebY2FooenO6LYeUrrMMHWX5PX/+GzAy+ev8WMGcswbFh35MmTDREJK7OkKFgwLz5e/Yj8tfLikYOD3M9Ea4IkJBEvShS433TC1rUnUbJYcezd0x9R7exD9d5qYFXdWiPkeHLi5AZJTaxapbXsl+qFtUL68g+/p089Nm6ainp1e6NipeIoVbIo1qyZgTVrt2DQwMmYM4eq05DN8+3YcRDlK+RH1Gg6dO40C1OnDdaIRw0aNAQLvOCvUqW0jM+fv2LPnqOSUEvlIUmWJ09eIkmS+EI0cRkGZPlXydFz8eLFG0IKcjKPr8N6ytzcTCZoOTnFRF1a1Wj4faCaLleuLFi/frZRrUjisHnzXtJCHxx4eXlJKvLixRNM9odCheoIKVesWH78rahbtzKGDZsqnz9WLKW+YGhfcElxhsesXbtdvDe5HSMabEseOXKm/D5/BpKB9F99/vw15swZFep0bYLHCw7aK2zaNA/ZsmWUtGsqDv0GVgWEyZMHy3GqaNE6EkLVt297PHjwVIQFbIdXbR+CiytXbkk9xwl71rq8pSpUgwYN4Q+tOtAQqUEChSQhR58+zXH79iMkTpwQceLElPAYFsv9+41H2XJF0Lp1TZPCqGu3JqhVqzRcXN0QL1582NtHVdSQej3Onb2OUaNmiCcj2480/B4sWrgRjo7OaNK0qvG+bt2aSSvWhPELsXXbgiC/1sePX0St0cZfWzW9wbp3b4Ehg6di/PgB+FtRu05FVKvaFlaWVuKTFSeuvaJwCIIS5c2b99i75xj27TshF6H0+sqdW2nTi2g0aVIFTZv3QYWqP2+ZXjL/AIaNbYACOSqGCRFHpeW9e4fx3fm7XDhbW1vL/UENZMyaNZ3cdus6Brdu7Zd1atKkGs6fuyYXgnnzhqyNJ3fuLHj/4RX27j0jx8E0aXz91jRo0KAhuIgdOyaaNq0lg+dMkkupUiWT+olecAyXoTqL3mqcfFGRJk0KnDy5SYgJ1mCxYsU0koxso1y2bCOOHTuL6dMZRqPhd4AttSNGTMesWSNNvrdDh9ahTJlGUhMEx6uPClkq8/yT0KtWTUOtWm1x9eqeEHns/QnIkiUd7tx5iNq128v25L/5WwkKse7q6oajR89i796jIpDgdQa9Sn8H+P3b2dlKHfKzyWR2B/E4QL/JsPLwvnfviCgWed3F2pKgylMN4PsZuJ8y+GrBgrVi+8N1SpcupbRhz527CqNG9Q5xTbVkyXp8/+4iyuDDh9eH6HU0/Ln4HXEvWryMAq3VWkOkhxrSYmUZHTlz5EK8uAlFgUQlWupUKbBu3Sx8/uSA1q0H493719DDzdCO6obESRIjbdrUiBEjmoGcYFukHoUK5UHbtg1l5ut3fjI1QfdfxZmzV5ElaypYWLBVyxV6vY+Mnj1bYuu2eX6W9C1s1XAPtU2d4/Lla5g0cQHso9sZVHx+W4j1KFg4A3bsPAQnp4/w0TsbA0OouFTe1xU+egfDcJSh3u/bDq+8Flsz1Lb/oMG3Xdy0Zdxvi7PpMr7t1Ao8fb7J8PJ5L+pHDh+9m2Hw8zgjbdpEOHN2vShYqGw4feoyChfJghPHb0EPV8MwXQdPD29pD+7QfihsbGwwf/5YrFo1XWb6f0c7r5kuKuLFTYrChTLj/OFHSBrVTkY0SysZKrhu1pZRkTNDBZjprOX4EBagKpGBVzbWtkb7BxbJDg5+00GVlmvDGhuCsCxlLF8xCZ6enn4CaIDixfPh2rU7IV0jVKlSBqtW7sGMaeslWGbokInYuGkXPn/5HOrPq0GDhn8b9DgjMaESS9bWVhg6tJskxfI8whZJv6DaK3PmdKI28kvAcIKPhAWJLw2/Dwzqs7ePjjhxfAljImnShLh//2iQSUd2CPXpMxYODk6BhDPqUKtWRSxdujHU60xSisRSZAPrjDt3DklAyowZSzFixAyxVjpy5OxPPwtVeUxMZhJ0u3aNsWvXMvTq1daExI9odOrUFPPmrf7pMiQGGYwalsGB3Ibcf1TSkUiaNJFJGOLP0L17K7n98OGL8b6iRfPhxo17IV4nHrtIltev31kmYajAJMFOZXBQLSM0aNAQMvy7jIeGvwZWVtYYNKiLzLR3aDce0aJHRe7cGVGmbB7EoLHxu09IkzolYsa0h06nFlB6Uchx1l7D7wPbTkqXaorLl++gVu1SqFihlMmhybfNWU12VlqqCU9Pd0yevASrVm6Xf1eoWAy9+7BI8YKPXlmGyegk8CzMo+DWrZ3w1n+Bt97dSFR5gySjQiqZG9qQSf8p72g4PBrqEDMoj5cs2V6Klg0bpyJBgiQm7d8q2aR4MaptzEqbMNv/lQcVJZ0veeULkq7K63iYLGNmIAE9fT7DXGcVwLbhc7wQI6atEOrVq5eTRMD6Dcth/96LqFa9hCzj5uaCM2eu4uqVu2Lg/+2bo4TvrFs3M1xSqkOK1m1qokO7yZhUspm08T03XJR4+Shfhqe3t/hMPXnyQi6CwxMfPnxG/nw1ce/+Pnz+/A3Xr91GosTxkCFDWuj1XibfQepUihrx7dv30qZEcjtj5uRYvHBLiN8/QYK4GDe+DxYt/E/USZs2HZQxdMg0HDq0GkmTBm7SrkGDBg0hAf2RqfAi2TJlykLkypUNJUvml3TfT5++Suhe+vSpTJ7j5OQsyioNvw+cNGQLfOnSDcWjb9CgzsGaRGSCMWsHFefP7wjUh3DEiB5hss7r1u3AqFEzsXz5lJ94pv8esNZjgnvZskUxcuQMWVduXyYv85pCJXsvXLguQgb6ldOygFY1v6trJDCfR04uMCyQNV9AYKBTRCShU3XZsGFXSbFnZwlJxG/fHKTl2T/UCZGtW/dKq7Ua6kdPbqpKAybFf42VK6ehcOFaeP/+I27ffiD3LVy4Dr17t0O7dg1D9fk0aNAQODTiUcNfgxIlCqB4iVx48eIt9u8/jsED5+DBgxfyWNOmVTFocDuT5alCCm0ymobQgb5QJIA5SpcJulfQq5dvUb58C/GXGjKkIxo1rhphCr2u3eph+LBFKFG8BVq1qot+/ZViKLIlXS9aNAFt2/WF83dXnDt7W7yJli7eJ60qBQrklja7kHrkhDfixYuJXLnS4dShOyhePkuAy1CZwwvdkCA4+8qOnYtRv15XISD79pkENzc3SZhu174BUqVKZFyOM+UxY8YwJjmqSJMmGa5cCZ0Zes2a5ZAje0bYRY2CYUNn4PjxC3L/fxt2o1PH5lKIa9CgQUNYgucHquCdnV2xd+9xIaXatx+EGDGiy6QVFXR+cf363WAl52oIH7CFlOdGKu54XgrK+Y4+hPQTJgFIRdn06UMjbDKyQoXi8r4tW/aRf9+9ezjUKdxhDW5Dkon0SiTpvmrVFgmfIVF36dJN8UVl6jXJu8jaeq6qHhcuHB/mNVVwkjN4jGBozbZt+4U4ZIv3q1dvRX2YNWsGoyrX775LktEvkiRJiHv3HksQVUhABebRoxvkOMZ08YkT54vNxNSpiyRBmzWcFuL390Jrtf59iFxHdg0aQn0osUbiRElRtkwZ7Nq1Ugrj/v07Yv/+M/j0yQF6Pb1G3Nlkijt3HiBTppAbCvMkNXbsbPTuPVoKvX37jmsy/WB/Y74FWqkShfDhA8NEAi7a1PbVXbsOoUyZZjh1+j/cvbcXjZtUkfZ5RVlItaM7fOAsw1vapp2MrcVmumgymFLM4eH9HS6e7jK+e36V8dH1vYwPrq9lOHl8kuHi/UZG+erpUahIJjRuWhKNm1QwtGkrrdt+9y/fFGQlDdQX6v1ehuEBH/13Gb4t0WzXVdKTOajU5aDa0dIsiQzflnPTtmz1s8aPH0fIR3cPL+zedQXnzz1F69YNMHx4T5QvXzxA0vHt2w/G5Ev/LeYRCXNdDLRt2wg71pxHDEs7JIsWVUZMaysZn7+7iGIzIsJvqIrmceLrVydEsbVBvXrVoNebYeiQmRg+fB70enP4+LgjY4YKWLp0rTyH7e7q/n3zxiPxhQpNC4+ZzhKpU6dCvLjx5KLh2rU9UrivWb0dRYrUxvHj58Ls82rQoEGDX3BigwEbJF5YU23dulDu93/cuXr1VqiJx4MHT4oaiiqoy5dv4v37T9qXEUzQs5lguzz9BX8F1q+5c1eRyTV+v0uWTIzQDggSTgwFJOFJ1WNkIx1VcL2GD++ORIniiV/ikSOnReHLdW7YsJqkMPsnHdmyrgZb/m4wcIjXLVRoBgT6HbI2jIjtSKEI9zcSgPnz50DhwnmEzGX7Mz1kCaZgT5igWC75365nzlwWojQ04ARK8uSJ5bu7fn0fNm9eIGKIYsXqYtCgSaF6bQ0aNAQMTfGo4a8DJ8jMzHxn31q1qoeUqRKjdauhmDN3qHjdkIRkYcWTTFBALz0FXnjw4Dm+fvmOKVOW4s2bD+Lb8t9/OzB58iI0bFhVCBP6HWkI0reFM2e2olChWihevLkQPFu3zRUvTkJvTJZmIarH/XuP0bfPREyZOhAxY0ZXltGrbc5efpZVDm1K0rkeOjPFP5HeoPItermiZPEO2LCzL6JFV9RiLl6Kb+M3dxe5jWplWNbQIm2mN6Obn+xbMxe0lfuimFuK36KZTkk51EFt+/BbOKufRTHTVlu71fu5rBnU9mv18xraynUKoWimN7Sv6XyMydSePu8MyyoFmZqarL6PDpZo22YgPn74jP79OhlTGVUwwIf+TWwZevnyDVav3ioXeWyfmzp16G/1HuX2TJI4JbJlTYuLx18hS2ElXfGRg+Lz8/jSS2nJCo5JvgrOYgdnJpv7E5W116/fx/Nnb0TZUKdOJSESmQp75fI95MyTWJadMWMVRo1pCb3OAd56PtcaDx4+RZu29UM0e852ogcPnhgTF8eOm4Nbtx4gW9Z0GDmqC2rWKoMWzftJG1Lx4gWC/foalG9YgwYNP4ffmor1zalTW9Cx42B8/eqIGjXKGbtIateuFOxN+enTFyHLtm7dJ8QjJ79u3LiL0aNnyeMkBNjiHZLj/b+IKVMGSztw377j5N/+lal+QSVZlSothYTp2bN1iPYHFePHzxUlGrspggs17Ciyg+Tc/v0nxPexRYu6Jo+xJnB2dpGairYsDJY5deqiWBMcP77ROCH5O8FAzfnz12Du3NE/rPuFC9cwcmSvEL1uQPvDz8Caip6K/O2zlV0N+Txw4ASWLv1PgmNISC5fvgmZMqVF377tTNS5KVMmlftDAvrQss4lAcrjTMeOQ1CmTGHUrVsFZ89uQ926HSVNmxMtIW3l1hDJofsNpZ9Wago04lHDPwHOrrm5uqNc2VaikmOiGtuHguMRcvToeUyYsBDubh7IXyAHhgzthJ07jmDdul3SgtS0aU0hFzp1GoJWrerLSZPFH5VnNPr+8sUBhw+fEl8YKsuiRbNDjRrl8a+Ds9137+0TxdidO49++p20bTsY8xeMQsmSBQP0SAwq6Bu4bPlQ2Nr93UbSPXu2wePHz9Gp02DMnj0K9+49EuKKpCOVoyTNuT9y/+zevTU+fPj0mwOXTNGmXVUM7L8Q4ws3Nrmf4sGILOIZJnT58i3UqFnWV82o04mfVpMmPdGufU00b1kFK5fvRo1aRVGtSi9Mn9kbO7efwskTlzFt+pAQvS9TYidPXmi8cLSxtoKLsytWrdqOXLkzo1y5IihWLL9RIaBBgwYNEQGeO5Yvn4w8eaoifvzYKFgwt5AX9LdNkiRoE6+0WOnVazQuX76BypVLI2vW9Fi2bAqqVWstXnrt2jXCly/fhIhwc/PAuHH98OXLV3mftGlTysQMCQIek1k3kMjo0KHJP08WkFChh92iReswdepiHDlyxkjs+MexY+eEdDx69L9Q7xP0l/7b21OzZcuI8eP7Y9myDRLKxKAUEowUMpA45+ePHTuGbNMCBXKid++2qFatTaQgHYl8+bJLUM6LF6+RLJkyYUpwvS0tLSOM3OfvlUpqTqzyd62iVKnCGDp0KnbvPoI9e1ZIOzZJyM2b9+LFizfInj0j5s1bhUaNQmaTRfVpjRptsXr1dOTLl0M8Jnm9sWHDbrx8+RbLlk1G+/aNMWTIFHk//z62GjRoCB004lHDXwn/XY1UhZUuXVT+btq0PxYsGI3atStg0qQFGD781wbZb97fwtQpCzF/RTtEjRYFcaMqgRZbtyqKtAULRxuKXR88f/4WfXqPx/bt+yUhjgl3+fJlw+nTl6XthUQbCcmyZYugWrUyhraSv7tY+xWYTHz58m4MGz4FK1duQ8uWNUWNynAYQg1qOXHyPz/bSr1VlY5WAagMlXZktlt765lSHMfwfnZIly6DhM14+HyV+6JZGlI9zRQjdbV+VvclBr9YmivFo4ePp4nKUm0P1/0Q/OK7mor60jeIxvfw6zv1xmRkE+iVZcx06q21MVxHfS/1daE3JG3rVL8/nVxscDCIpV69TkKGs92Gycvbty/+4QKtYsXmEtjSr18H/F4o2yNFsvTQ+5jB6YsrYseNBidPD7i7eODC/+4gS4qQefsQwW17ZlsPcfGSEmSkgu1B3FbLlm9A8uQJ5b5smZQUxtYtRqJd+4bYvGUOrCwVRWxwwJYoko7q+vLCIEnShMY2tCdPnsDMrBgWLBgrF+AaNGjQEF4I6JBJsqV69bJo0aIPNmyYi1GjesnE67p1sxE9+q9bdUeMmI4mTWpIa6/aNnnnzkO5pfqOgR4qevcegy5dhor1BVVlVEVSBUlFlF80blzznyce/RKBiRLFN6rGGFTmHxUrlpARFvCfpP03gq25HDz3s+OB52N2QbB7ZNq0ofKYX1BFyLr/1at3QSbkwxOsIypVKonDh0+jZct6xvuXL98o6sOgeoL6R3CdZDZs2CWesCQd/bbWk/hcs2YGWrXqh1at+sp9der41qM1a5bH4sUTA9yXgwK1dVtdX77O589fxBddrfOo4Pa9NtOgQUNYQvtVafhnwGQ+FrKXLt5A7VqdJLWRs35Hj54VBRhx7txVtGnTD8OHT5P0N56E6b336MkzpEmfEDFi2cHC0kxarzlOHL+MunUrYN/eo4aEWz2SJ0+ATZtnYtnycZgytR+2bpuH3LmzYPiIbrh5ay+OHF0rvjBUKTVu3APv3mkeRkTUqHYYMrgbzpy+ilo1uxo8O6W52cRj0Pc+c5NB0k4ZFtImzEGCka3JvkbCJGh8jP6FLi7ApXOPYa6zhKWZhQw7SxsZVmaWyjC3kCHvrFOGrYW9DPV91GH0bRRyUCEUTdfFTvwLlWEvQ2n/Vj8HP5fvZ2P7NAc/g9pirde7yVBfV4XqW0mCVAbcjftpyVL5Zb+bMGEA6tWrEujFGS8cTpwwvZD7neD3WbJUQdw8+xyxrKMja+y4uLPrPlIliI9Nm/Zg0qR5EbEWxr8+f6IHqS9YmLZuXR+nTm1CqZKFUaOGrz/S8RPr0KxpvRCRjvSEzJZNUUNfvvw/44VAwwY1jKmxuXMxMdMce/Yck+MIZ+s1aNCgISKhJtHSm+3mzfvS7UFCUa2pnJy+o0+fsejZc5SEl3BCRTnGeUs4ROnSRUy82nbsOCChf//9t9PkfaZOJaE5C7NmjcTSpZMl4ZZk2rlz20URXrt2RQmEaN68l7Rra1BIpsqVSwlZU7x4PVGPhjcYYsf2Yt7+zWAn03//zZF9kl6aHTs2+YF0JFjnc1+NDKSjipIlC4kKVgWvg2bMWCbkaYYMpYy/3fBO2Sb4nv7fj2rmkyc3iaI6efIkRgKQ25o1bEhJx+nTl2DLlr3yOpyEJ6hM7d+/k/hNstWfvxkem0qWbCC+/Rr+Tuh+038aNOJRwz+G2bNHCrHCWbYyZRqjU6dm6NBhEDJlKoNatdpL0Xry5EWR+fNEPGzYVOzedQwTRm9G9Vo/pi43b14TDx8+R7bsykk0IHAGr2Kl4ihQIAcsLS2kyOaM/bt3H8WIff36nZHGfPp3gwpRfkdUcF2/fi/c3+/qlXto13oWsmfqhHNnw//9IjPYks39ki10kQmlShXAju3npNVuy6oz2LTiNAoUVAIM9u07ISbv4QnuiylSJEW3bi3RsmVfuLioHp2meP36PR4/eY1cuTPg0KEVIZ4tZxGeOXNZ+fvmzQOIGtXg72nAiBE9ES2arVzAb9m8F1OmLJIWQyoINGjQoCEiQX+2kyc34/z5HaKse/bspXQLsKaiyp6t2LT12Lv3GHbvPow6dTqKCqxJk+6ivKLtiV80bFhdlEcVK5b86ftmyZIe1aqVFasQokiRPEJiMPxj6dINcj7ToJCPJB7bt2+EadOWhPsm4fmrdet+yJKlLLp1G24Mq/sXwdqBRBfVkZEJJEFZ65H4Z+3QqFF3ZM+eCblzZxVSb8KE+eG+DvR4bNOG5N4xOT4EVlNxG9LPccaM4bJ+IcWSJf9hwYK1YkHg/3Xo2U1/eW9vLyEgqbBkK7iqjtSgQUPYQVM8avjnijDOVKppuI0adRPPEKqWWrWuIyfkpUsnoW3bBlL88uTTt+9UTF3SGulzJTYq3tQE5RYtq2P9f5OROnVKUdoZ3sUwFPXak8cv8eDBMwmiadmiHzKkLyNLkWzMmze7GFE3aNAFGzfu1lKxoUOMGPZ4+vQVGtTvYWiHUJSKvmpCJfHZ9zu18LPtVSjbni3PMnRRRG3o23rtLKNgkZS4dXcVJk/thPat52LHtqu4ffMVzp15iNcvP8NMZwYrM6ofbRDNMiEszOLLMNfFlWEmikV7PwnQ6vhxZktdlx9djc2NSdc/QlVAKkpNJXZGTbxWlI9sF+f4ERa+KlCjSjRgUNk7btxcSYCPXO0l5kiXLjUqVSqA1s1m48jOGzh7cSocvphLwvSKlaNEnezt4zfVO2zx+vVbuZjOkCEFSpbMj4sXfyQ6+b1SRdqhfVOsWTMLSZMml2CZkIAXzcSVK/8Tlbb/izqa26dIkQTt2o3A3LmrMWx4J8yZO8ygYPi7PUs1aNAQ+cA2RSqHmjWrhYUL14nykb7a9GgsUiSv1FebNs3DiRPnxcexadOeqFq1jPjf+W/r5LFt375VQgYEBk7+HD9+Hh4eHpgzZyXSpy+Jnj2VsAxXV3dpwR48eLL4tH375oh/HdzG9CLctOl/Um+GJ+hlSAXqoUNrpb04c+Yy4i1NspmThMG1OfmTsXPnIaRNm0L2x8iGceP6o2/fsRg4cCIGD+6CxYsnSIr8gQNr8OTJ83Cf0KWHKwOlWHOeOnUpwGXSpUsllgv0YwyNHQBV17StYfo4fTf94+LF6+L7v27dThQtWkeuD7kd2BWkWj9o+LughkxG9NCgeTxq+EsRlN83iyOSi+nSpUT//uOl5ZoqosSJ40txTFPjXr3aIGGi6EidQPFvM9NF9/9O/v5lZfQj/PLZAYUK1f7hfceN6ysz9VQ/qj58Dg6OYqjMGXuSnv+65+PVq3vE34XfiWKKTjJMIZd89D7+fBTVQlbZZgoB6O3H91FvIC1J2Cnp5J4+n+XWydMF0SxtUaZCBqA3MGzwMuM6FC6SCfMWdRKikVCTqwOGqSH3z0g+/5DPobMO8PnqvuQ7R0TiW1HAkUJVHlFaps11MZUlDCRscNaBBvNs4VXbTyIL1FbyFs3bIF/e4ogXNy5iRY8FW9sXSJUqERIljoEMGVLi0qVryJ8vX9BfNxgFQOLECbF370pRb9SoURanTl1AseJ5TH08ATGa5wgteLHOERCOHT+LBQvWILtBYd2nXwsULZoTT568EpKSF+S2tqYKSQ0aNGgILYJyyGRdQyUiVUo8d/fvP0GIF55bsmbNIGQj1Ua8sGe3R3DB12XbNidf/KJevcoSpMaOCYLhcyS4Nm/eg/btB2LVqukm7dz/IhiExvpyzJhZmDRpEMzNwzdEhEQna93q1dvK8Fvb2dqqPtR/LxheyXAfkmaRERkypBb1H1WFvN5R2515XdKsWW3s3HnQKNAICoLLqZw9ux1TpiyUMENOVPC37X/Sm90etAoILehFG1iyOycvWrbsY7JdSMSyRZ7+tbdvPwhxerYGDRp+RGSStmjQEOEoVCi3+NrRM4gJsc2b10bixAnEK2jIkK6SuNihY80QvrZCOt65c0hOevfvH5FBLyKFdPQF348kJ9smHz9+gX8dLEwHDeoiyYEdOgwWtWhYgRckH95/w97dl35oA6pUJR9u3Jkvg6TjvwAWXmzB+v2BMj8Hiz+1DZwFIVt1iMyZ0+DSpfBL4mYxnCpVMowd1wcbN+2RdGt6xDJNNaxBFQ/VO6tXbw3w8SePX8ixYuiwzhg6rBPOnr6Go0cvoErljqLsCe+LSQ0aNGj4GXis5AQMg02mTRsiai8SksSwYd2xatUW8XDjcsHF4sXrhXRkMJpSUylj9Og+RtLR7+QSybZr1+5g5crN2pdmaGMnCVyjRjscOnQqTLfJ9+8u8pq0EFJB8obw+139C6QjsXDhGiHEGSYZWcHfDElHgrUD/VoZhpkxY1pcunQznN/bXoI96cdKxXTFii2EFKfyMKzrW9ZUJBcDssn59EkJl9y0ab6E1nAZFxc3NGzYFdOnLw3RcUpD5IfuNw0NmuJRgwYjevb0nZUlihbNJwEWjx9+ReasipLJW6+Yc+skEISKNOUk6RvywcAPc2nRVmf1fMmAnx92Pn/+htSpk6Jrt2Ho3auteK2QGONgd0q2bOkl6flfAc2n16yZKUblbdsMwOAh7VGwYHbj4wxPkVsJ9TGNoTYmP8MTPnpPOH3/hBUrj+LEsRt49+6rhHe8fvUZ8RPERINGRVGpal5ZPl3WBHD3Ub47W/NEhtdQ1Yh+08dNVZbBURcGBHX/UdfbV+moPu5LKOmN76mslxnU9FCLAJb18bd+putNrFq1FWXKFI5U5uf+4V9dyCAiJ0cXjBi+DJcv3cGatZMjZH+sWKE4kiVPiOLF86F797FwdHRCgwbVwuT1acbPiYdatSpgzJjZcsHC9iK/6kx6IjGJ0sLCAp8+OmHrlgO4cPG2PEbbBmvrkLV3a9CgQUNYo3jxAjJUMOm6a9cWoqZSCY/gYO7cVRg4sFOwWld5HGXb6PfvzqhQoYTUU1R3cSRNmhDx44csqOJPhJ1dFIwa1Vt87Njlw1ThHj1ahWjCihO4x4+fw/btB/DgwRNRlN6+rbSlcnKdZHN4k1eRFS9fvpFJRJJZfxLY8dK37zjpnujUqWm4vx/3mfHj+0u9s3v3Mixd+h86dRoiPu8BhR+GBEuWbBD7BqJ+/S5i+UA7ABVMfb99+5B48bMG44T2hAlzjUFMofGV1KBBw4/wb4ymQYMGP3B2dkbsOHGMrbt6vYHsMhA3avutDqZebDyxBa+lRCcnuP/tWS6+OPQt8vH2gbmFBSzMzeDp6S1BN0x7rFu30j9FQNIjiorUHj1H4e6d52jVup6QMXq9Mnvp6e2BD++/4PWrD0Io0rPT1k45tN1/8Azr1h7EnVsvUKFCQYwfN1wKDZXM+fz5KwoVqoWZ05QEzXTZEsNcZ2by3aoEp1/7PN92ZssASWWFQPTvZaSSieaBtIr73qcSkOpjvv+WNTN5HXpM+l2nn7Vs+ycgP378im3b9v1xBTKxdNkkPHv2Cr16tv9B7RJy6LFgwUpcvXpXEiqTJ0+EEiUKiwqa2y5Pnuw4dvw0atUqi0WLxqJb15EyQ8/WpNCAs+zVq7cRopHK5+fPX0kKLNVBU6YMMZLCTDi3sDAzthPGjh0Ddet2kpCGyZMHhckW0KBBg4bwAgnAOHFCpgJjgnVwFXNnzmwVsnHu3JVYtmyjEAwk2hhqQ+KNoRoMXuEx/l8BFWZUdzHlt127AZg8eYgo0PySil+/OuLNm3f4+PGL2BGp24ft2qwZ9uw5LhPlzZvXkW4E1Y+Yz82bt6oxVIWt9v8aJk5cgF692v7g0RzZUaNGeWmRJyEfFrYxKtiuzMCaZMkSSUo1a3TV1oeKQnY08XfZoUMTrF27TfZJeu2H9jpn5sxlYpm1f/9qmXygfVPVqq3EloE1kwq+N8FOtC1bFmD27BXy75s394fq/TVo0PAjNOJRg4afgEVXzFiAl8975Q4DueOtVwy6zXWxA/Z61OlC1FJC4ilpksSYOOFHEoGm4CtWbJJUSBaNDMn5V5AwYXysWjkdo0fPQvt2g9CkSXVEjWaLZUs34/Hjl0iUOB6SJE4oxMyUyf/ByspCij4LC0s0aFAV7du2QbJkCQJUQ0yfMQhTJi/FsOGtsG7hfrjXtELP7jOxfMUI5C+QFT56RQEJOMNcF8OfytIsEMIQfshq03Zune5HwtFXoelfefCjx6NKHvq+jin8qiV1gZCcqlKXFx4dOzb9I9ufUqZILiNsoZNWNAYlFCyUA0+fvELbdgMwf/4wJE+WGpkzp5MLWFnO1g7z549BjRrtRaVIFWZIfKA2btqJK1du4/37T1IQ87VZdLP1KH361D/9brJly4i7dw9HskAgDRo0aAgYVNuR+AoJQnqeIrHQvXurH+6n6nH//uPo2HGwnAfLlSv6z9hVcJv07dse+/YdR7NmPaQNu2DBXNix44Dcx8k8TtKSJGbdyVo4WbLEePHitRBUgwZ1RY4cP6pWWfsy4Zyp5nz9cePmiJd6u3YD0a5dQ3Tr1hJ/M86evQxPT08UL54ffxqoSOaEZlgjYcJ4ePv2Azp0aCy3s2Ytl6R1Bkhxf6GvPr0mOcHKkL7nz99g797jYqkTEjBo7+TJCxJgs379bFFWkgRv2rQWrl+/89PjT8yY9mIJQastra76e6Ez/BfR76lBIx41/KUIq+A8hs3cvv0Y2XL8/nYcnhBJTNAfqVixuli0aLxJG9PfDhYPY8b0wcVLl7Fj+yGZkW/ZshZy58nxA7n2+csHODm5IEXyFHBzc8eXL06Bvm6FCkVx/do9tG83Xv4dJYoVEiaMje7dJqNGzZLoN6Ah/kZs3LhHLgLDwrz7T8PPkjWr1yiNEycv4eiR8xgwsB1sba0xfPgcLF0yRS7Gvju7yL4XK2ZsmZHn7P39+09C1JIzceJ82NrZiOJm2tRhUoTTI4tBNrwobtSouokSJSBoxbEGDRr+lJrK2dlFSKyaIbPODlOQZKxUqRTy588pnQ+5cmURouJfQoUKxeUcRsJxxIgZqFSpBHbuXPpDGA+98p48eYE0aVIKaclAs59tVwb6dO48RAgltrCmSpUU8+evwY0b9zBx4oBI7X0YUtDTkm3Dc+eOwb+Gnx0fWDfRP3/q1MWYNGmg7HO5c1eR5Ht67DNoioQtPVmJkiULYP/+EyEiHpmezlAfWjrweolkKjF8+HQcO3ZWrHGCEpqj1VUaNIQPfrtMYu7cuUiRIgVsbGyQP39+XLhwwfjY/fv3UbgwvceSYMyYf+9AruH3gzPA58/fMFrDmsFOBj35ZOisZIQePGsHrbKvUqW0+KIcPnwG/yLy5smNMWP6Y+7csciTJ7cQjqZKQR1ix4qPFMlTBsnS10xng4EDuxrNz2fOGIdjxzahS5fGWLVyN/Q+ZgYPRnPj963TWcsI7PX1eg8htxSCi4dZM2mF9tsOTZWjMqg+9DHkVDN5m76UjjKU1/Ed6uf7mW2xuj2UbaI3GXp4yC0HLhwAAJvSSURBVNi18yh27jiCWbNGBCvh+V9A9GixsWjhRCRLngS9e01EhUr5kCZNYtSp0wZnzh1BgwaVsXLFVsN3x+9MH2yVDPeL/7d3FtBNtE0UnrY4heLu1uLu7u4uPxR3d3eX4u7u7q4f7locinuB4jT/uRM2TapJG+88nCVpZLPZ3ezO3nfmzsGDJ7lUvE/vdpQls5um4dTChWv4AmbnziXk6prGRN9SsFckphKsGQh9yDK0JiCCHT++nn3dlO6+4QlkpKHMdfnyKSzMBNYBHINsbm7pNGWpIYFS2sOH13JMtXbtTBYz9+xZxplo16/fIXvjxYvXLLSOHt1H4yko+IFsw+HDe1DnzkN58AHWMM2a9aD589dQnTqV2VZGafaIsDk0mccYSB85cgaNG9ePMxwV0fH8+atsD9CzZ2tq376JbBaBr3ssMQkWFh7XrVtHPXr0oKFDh9KlS5coe/bsVL58eXrzRt3BtlOnTtSkSRPatm0bT//9Fz6FFsH8wHNt46ZddOnSDWrRvCFFcIzPk0IEx4Q8qctpzR+oYsTwyhV1UwnB2KiFvKbN6lGmTOno48fv5OAQkZwcXNjTUT0p4h5ESaXpjAP5fP1Jf//4L4NWi4oBxeXAREu8z08w9KWf/yYfnoj+hLjcgaEIjhC89u8/SStXbqO5c0fbZIm1OUCA0KplQ4oYMRKdPXOHBgxoRxMmdaGJ41dSypSJ6MDBU/Tff+d5zTo5OgTaLTEoxoydSRUqNGVT/jFj+gQYWW/SpBZfCMMLTRAMQWIqwZpBNhK8qidOHEjWBprMoGnNnTsPLL0odgsEuT592vGAm74gZvny5StZMxC82rUbwCW6yN4TAgcNpSD+jR49k5sPbdw4l16+fM2DrUjymDRpHmfHIiYyJKY6dOgU1a7djitF0BTHv/CLTGbMHxVsgiCEY+FxypQp1Lp1a2revDllypSJ5s6dS9GiRaPFixfz8x8/fqTcuXNTtmzZKEmSJPTpk7rLlCCYmvXrd9HRo2doxsxhOh3QrAUIRhjN27BhF5+oBdMEk+geHC+e/o1LUD6yf/8J7mo+c8ZKKl2qGWV0q8yTm2sFNma3FGiCMmXyElqyeDPNmzeGYsRQumELQTFwYCea6rGcFi/aTEmSxKNpM3pSq5aD6cH9pzRjxgoaP34eVatehkvIgivfhtcQDNaRUXPxwnXavmMBzZw5ItBO4gia0X107tyVem0Y/59bokR99oMVwh8SUwnWChq59e07jjp2bKZpLGFtFCiQkxYsWMN+u4JpQMajIRZB6GReuHBtPs/Bu69+/Y7k6lpSM+ExS3L8+Dlyd+/Jgmq+fNa5X1sTZcoU4bi6V6/R9O7dRxo8uAvHRcuWbWILhv/9rxvFjx+HbtzwJC+vl0HOBwMEK1Zs5v1i9eqtNG5cX86sRYM+/yB7Eg0ABw2apNcy+vr66sRV2AdRvi0Igg0Lj/ALuXjxIpUpU8ZvYRwd+e/Tp0/z3yNGjOC/IUbiOWRDCoI+hCWj+e27tzRnzgpq26Y2JU8em3xVPvTj7zOeNPuqQ0ye1DapxujRFHJJsH+mTBlCY8fOpv37jxvh8wX/oBwsa7YMWqXSQZdWa7Nq1VbKmaMGzZq1imLGjEFt2jagFSsnk0usGJQ/X11at27nv1cqGZBOWpOSQfvvbzSmUf0lX9V3nv6qvmqyF/VBXQrsS/fvP6PGjXpRlChRaeXKaRQ7NsTU8Jv2r2/JAxo4rd8wix49ekkb1h+lpEmT0OatHtS0WVVydHDiRjSjR83mTJ4DBwMvHzx27Ax3V+zffzw1bNiZsufIGEK3SxWb8GPgAyVC4MvXzzRx4lxatmwD/Xf6PL19+55UKl+aNn0hubn5eXRevHidzdsLFKhB9+8/NnCtCLaMxFSCKQlrlVifPmPYw61YsXxkraDkM0GCeNxVVzA+EJggGKVOnVzv92zevIcz1XCeQxMg+EzWqFGOPDyGUKdOzfgxVBCYu0Qeg8sjRkyjxYvXcTO4IkXyUnjGkOPD5MmDuGqrR48RfG2P0uju3VvS3bsPqWbNCtSt23C6e/cR1a7dNtD3f/78lXr2HEnr1++kSpXc6f79JyF24c6WzY0SJYpPM2cu430FZd1I3MDfiPWxX+ExDBBnzFiaTp26wO/DY2iGA39KZGoK9oGDhSbBgs1l3r17xz/+hAlRruoH/r5zR+3/UalSJXr79i19/vyZ4se3fHMPwd5R0dy5q2jLln1Up04FypwlvfphByeK4qTunuvoEDWI7sPm5/nzV+yVgvIgwfi8ffOJ9u45QUMGd9fr9Urm6YUL12jDhtkc6Gh3mT57djPt2H6IevceRw4OKqpXryI/7kCRNK+BuMjvUf389161wPju7Wv6w8fL2OTgqD59OTooGYtKZ+2Ah3OUge/efZSz50aO7EnZs0sZkKE4O0ehxk2q0dw5q6hp01rk5paS+vVvTmtWH6B5c9ezMb+Hx2DuABoYO3YcojnzBlD27OnpwwdvihAhMg9mODnE0GwlbbAv3L79gDNusd2iRo3CZUSurqkoffqU7FV0//5Tzf6Gcm0F7UEIiN5C+EFiKsEauXXrHvXsOYoHcerVUzePsFZ+/PjBGXQQRQTj8+3bD87GR/arvs1l0JwGtGrVgLtk+weelEWK1OYu2vCT1BdktaEpnJtbWoO9116/fktt2w5gAVS6HxsO1jcyHyHooaQaFVzwGK1QoQQLyRAj58wZFWS8evnyTS6dHjSoC1fyYCA2pG0I8RqN+1B9UrZsUR4ExvUTGvidPXuZxUsI4yBZssTsEQnwHoXAKlQEQbAR4VFfIkeOrLfo+PTpS4oRQ13K6L/qTTkm+fqGvTWf2iSUgv0cbWRZzLte/v71pbdvP4b4Of6XBRlEV6/eoY4dm1K27G705MlrUvlCBvilEXccOesNUkFwGUt+YLQMwc2fP384yylSpAiUOnVKcnJyDNN6wajc0qUbqWXLhnT8+AW6evUupU6dlFxckIUZNOFx30Vg4u39NVh/l8CWZcOGPXx7+/ZDihYtShDLotK8//p1T4odOzZ3yIwRIwY9evT83yvUoiLIkjUjbd8xj0tNHj16oX4vRdS8RqX6wTqUAzecIXr+4hXNmrGJHj9+xX+XKp2dypQuSqnSJCFHB7XvkUrloCOGa68XjCAvX76Fxozpz+W7yjLpiz3uL+h2jn3i69dven0umv1EihiZnj9/T/v3n6X06ZPwNkJgumzpDrpw4SZt3nyA6tatxFvB/7IkSpSQ9u89R7FclO7Uf+jjx2/k5PCVL378C48/fn6nw4fP0OrVsyhOnJjUvv1g3q8yZ0H2rQO5ZUxHrq4YFFFRosQJKXfu7PTkiXpfwuN4Ldiz5xh3jVTANkCWhn9fT2vcRuZclhcv1J7S4QVDYirw+PELjS2D9sWdIdvT/2uCsyXQF1kW866XFy/eGizQ4PWXLt2kbNkysfeaj88P8vF5EeZlefbsFb17p7ZCwZQkSYIQB1pCWi8QxdCRuGjR/BQzpguf/+H7mDJlkmCXJbzuu69evdPEsfouC7L448SJQzt3HqFixfLrtSyxYqmtburVq8rHosCWZf/+VTwQh/NgSMuC51DRdOXKLY4B0qdPRWXKFKWiRfPqtV5+/PhJI0ZMpxYtGlC2bBnp6dNXVruNzLksyv5gyLLky5eTpk9fRvXqVfk3Xwe+pkF2IR738BhKnz8HjNMcHZ3o2rW7dP++l6bZkRID+f8cBdjhDBzYmYoVK0CHDp1k/+7y5fPRz59/KFmypFzNom5q48iZ2cq+hhgN+yyAN3qxYgV1PsPHB8JpFB2vbmvdRuZaFmv3ZAUO//6Z+zMFCwqP8eLFY9+F16/Vo1kK+DtRotCNKiRNGnLwYYTfdJhLThRkWUyzXiD2YRslSxZ4BlJQ7Nt/iI4ePU1Tp3fjA7ejQ7R/y+IYSIajfjsBsicHDw7oK9KiRT3q0aOVQYG8sl5wMujbdzR/vydPvMjFxZk2bjxGUaJE4t9U3rzZqVCh3OTqmjbAPMLjvotAET6dOD7ouyynT19iT9kTJzax+BPIp/77/68m27Bhw078no4dG1Oy5NqfFfwCYt/yy3j05n3C91/G465d/1HNWmWodq2qdOTIaerceRhlzpyWChfNRL6kDsgcHaLzrZODWnBS9lVcnKHEd9as4ZQ8edLgV5Ke68Ue9hdvbx/eJxIkUAeT+jJ+Qlfq1nU89e3fhPLlz8KP7d4zm5o160+xYztT3Lgx2RbEP/nyZaU2bfpTi5a1KXbsGDqDGBzcaZpTqb/g9+8+9O2bD2XP7kp/fX/Q48dPKEnShDRkSDfavGkfff36lQcyipfIT26uGXTWS6xYzjRgwDg2cW/SpLrm8TVrtnOJP4J0BNLFi+enrl1bWO02MueyYF3aA6aIqQDOM0pcZYvbNyRkWfRbL79+/aHkyRMZnEE4atR0rgAwNB4Lalm8vT9T69a9A7wGGXTbty8McvA1pP0FfnGJE8ejrVv3UrduLejWLU+aOXMJ5cmTjZ+vU6cS5ciRkQWLsGIP++7Pn791tmlIy4JmaStXbqQOHZpQw4bV9FqWM2cukbe3N3Xt2tyg/Se4ZXn27AW9efOWdu9ewufC7Nkr0N27D6hRo6rBLgvA63v0GEkVKxajypVLhHlZ7Gl/8b8/6LMsaDQzePBkWr16C/Xr14EfxzHm16+fdPDgSYKWlzRpwGMOXtO6dR86dOgEtWpVX4/PUtHPn9/JzS0NJU+ekPbtO8r71ciRPdhLEokcqMBEd/cqVfzs3xSyZ3fja8NDh1ZpbHKQaDBr1jKuTMFAdoYMqah373Y8CBIW7GF/+fzZcl729sTYsWNp8+bNXAUcNWpUKlSoEI0fP55cXV11zrE9e/aktWvX0s+fP9mScPbs2QGqia0JiwmPkSJF4sYxhw4doho1amgO6vgb3axDA4JuTIKA0Sd99wXlwh/NIpatGKkZQXN0iBhkCau+IAtKnQnlx969x6hr12G0aNE6WrNmBndc05dduw7T/Plr6M6d+3Tt2h363/9qUcmSBWjFCrUx89Ch3bhjYK1abTXNMWCqHJ5RHxccNdtVH5AVFitWTG4sE7g4rAiP6ue6dhnB5UN79iylNGlS/HuNg7/XqsVFdRfswOZG9JczvVTk9K+k/9bNR1SxYilyiuBI9+49ohEj21Pduuqg/a9KN+vW6V8nbcwfI/nduw+nYcO6UurUyvIIIEIER4P3B5AurRstWDCeWrbqTZs2zaCIkX9zZmqvXk1o7ZqDNGvWUmrQsAqv+yyZM2veV7RoPg58m/6vL+3es4A7pOtudWU/caS1a3bQsGHTqX//Drx8x49cppguzhQlciRq13YAJUwYly5fuU3O0aNS5SrFA3wHXHSfPLmRO2Yrxz8E1cggaNOmEbVr15hH6OvX70AdOjTVaZyFkkhMpUoVojhx9G+oZOsoWTu2jiliKoB9zNDfimB/ODk5GLwfLF68nuOPTJnSGy02h8B4585hncfQDKZ06YZUqFAtqlmzPHvG6cuTJ89o3rzVtGnTHnJ0dOBsa/U85nCZJQZwIUqggQjImTMzzZ49KlwdI8MaY4MYMaLzdsKguD770bVrt6lFiz7Utm0jat/+f2Qsbt26TzlyZKaIESNw8xI0hFm+fIpe750+fSnFjx+XmjSpabTlsRfw2zH0N479YMKEflxeDZ9s7BsApdDwLG7dui9t2jSXbt++z9ml2vFKnjxZacqUBVS7dgWKFy/oQWQMwOPYAA9ON7d0vIyYH7Z7p06DOR5KkSIJNwnC9VNg+ybKvtFgBudT5fkBA8ZT2rQpaf78sdwMB2XjKNnGAIUCbAUOHDhBWbK4siWWoRnjtorEC8bh2LFj1LFjR8qbNy8PkA8YMIDKlStHt27doujR1Qkn3bt3p127dtGGDRvIxcWFY71atWrRqVOnyFqxaMTdo0cPWrBgAS1btoxu375N7du3Jx8fH+5yLQhmR6WiFCkScUmR8Wap4hObdpkv/IPgRVO/flX2GYFfjDYQLpC1iUxJpXMfTI1xi9FWiI7KvFeu3EJVq7Zk0TFz5vRUv34VGjCgI50/v4Nfg/ehQQUCPmOk8IcXIAbnzZuN/vvvYoivnTRxAe3bd5x2716sJToah5MnL/D+s3nzPpo2bSkVLJQ9xPdAdEJ37UaNakiXRSODEfHy5YrQmjW7NI9lz5GB2rVvSMuXb6Xy5VpQ7VqdONhV4DL8G3v1mv/8Betow4aZ5O5el//2evqCWrSoS6vXTOFR/m3bDlHNmqVp3fppOiWA2iAIhx+WQvLkSWj06N4c2KNj67p1O9jPSPEuevfuAw0ZMpmDfDSmadmyD7Vu3Y+2bz/A+55gO0hMJVgTKH/FefTmzXtGnS9ECWTQKcA/8saNA7Rz52KuMlm6dIPO6yEYoPzvwoXrmpiqefNeVLp0IypX7n/8Hmfn6Cw64nidN281FiJB6dKFqX37JnT9+n72qIS/3PDhU+nTp8+cOS/oBwSfKVMG04IFIXcHxrmpbt0O5O5eh3r0aG3UVXzmzGXeHzCQW6ZMIx64Dwnsa9hnkB03YEDoB3GEwAVsdASfOnWR5hoFQh5iIIjDFSs2o//9rzstWaL7m16+3IP9PdGEJjg2bNjJgx8LF46nmDGdOd5Bc6NlyxDzNOKBWWQt7tq1hKpXLxvoPHBMQCMjZ2e/ihYkdcAfFMcCVJPs3XucB24BvseOHQe5yR+uvSBY16jRmsu9vbwCloQL5kdtxWP+yRD27t1L7u7ulDlzZsqePTstXbqUnj59yo2ZAbJ2Fy1aRFOmTKFSpUrxwPOSJUvov//+ozNnzpC1YlGPx/r163PzmCFDhtCrV68oR44cvKKtOUVUsD+UDLRcuTNT8aItqVChHLRo8cgwZTri4n7IEN1R1AMHVlKKFH4lryNG9OBuasWK1aMzZ7ZS7NgufLHfu/eYAPNbvnwTValSiiZNGsTd/RDMnz9/jfbvX8nB08mTm/hkrYAT7OnTW6hgwZpsgp0gQVzO4MNIojKqj6YV1auXY+8/ISDdu7eiLl2G0uzZI3m7IWPRr+Tez1dx4cJ13HQkTdoUQWQ1BmweoguCrX+l1vSDbx1JvU3gP9Sr5xj2r8V2ih8vMTmQetTXyUHZP/1KReFbNGXKQho7rg/VqqluXiMYF3gQ1a3bkWrXLkfRndVenMlTRmNv2bhxXej9e28eYT99eh3FjhOXn48UMRL//tav202fvL9Q9eql2bsINgkJEsTSBKvRo0WhN28+8N9oRLNu3S5atdqDNm3aS89foFt1DoobNx5Fiqge7QwMXGAfPnyaA9ykSROy+FypUknas+cIZz4qlC//Pz7udO8+krMyV6yYysJ5587u7EuLwBnNtjJmTMvlR8gYwIWAYL1ITCVYE7lzZ6GhQz1YSLp162CYsh7RyTZvXt1yWByrIAgopE+fmsaN60v9+o3nAReIhhAI8+f3s51ImTIpPXnyXDOoePz4Bjp06BQLCBBBxo7tQ337jmPRq3//jpr3ocRy5MhetH79Lq5ageCBY3a5ckU5+xExFQStkiULciaUEBDEn2jusXHjbp3MMP+gzBZor39jkSZNclq0aD3Nn68WQHPnzhrs65E00LnzUPaknDt3tFTVmQD8XtCVGr+rihX9StgRu2B/QQYdhEkMMNSqVYGfw281Q4bUtHPnIf4tQkxEQ0cM+mbJAgsaddwdO3Ys8vS8pPkbyRjw8b969TYtWrSW/RxfvnwdYrOj06cv0pUrtzlzF4Ij4iFcZ82YsZQbUoHHj70oc+YM9Pv3b86gRIVMsWL5NNmPuN7r3388J5ZUqVKav6u+TZYE++Hz588BfLcxhQSERqB4jkKAxL5WpoyfPYCbmxulSJGCTp8+TQUKhDyoYgksfhWBtNCwlAEJQthRn5CGDu1Bz7zeUqVKpcjhX6lrUDx65EUVKjTl+66uaWjOnNFsRF6oUE3y9lb7W8ycOYIDLYz6o+te2bJNaMiQLpyJhpMeTppI8UdgjJExhUmTBvJJCbRvP4iOHPlPp1vf/PnjWFxYuXIaj94CbdFRAcEwJmQ/NW9el54+fcFZT+xf6ej4b1S5PT9Xu3ZFHXNkAQFqCho1qjdvgxkzRlDqNEkDlE3jXo+eLSlfvmz/nlOX7avISSNS+r3233Oqf+Kkg7K+VZp98OJ5T7p//zk1aqQupx47ridf8OzefYjata/3zw/yj07na4d/AqSv7y8aP24uj+xi3xJMg7OzM5daDR7kQWMntOHtgwY0124tJfKNRiWLt6ZatSpSrNhxdMqp4ev64MFTev78Dbk3609x48Zin6BChXJS02Y1+PF7955ome6reF85d/4CrVu7S122c3AllSvblOrWqRLI71X9WXny6F6cA2TrFCyYm/bvP8EX5BAl8ZuvUqU5Zw20adNQ5/U4prm6tmEf2kuXrnNn7nHjZrPwWbVqacqZKzM5OerXYEswLxJTCdZCiRIFqUuXTyw06SM6IqtMYfv2RZQ8eWIug547dyU/hjJXWEmALVv2ssCIi34MmsD79sePXxQrlrqJV4cOgzTzSpUqGe3du5zvIz6DEIljouLXhkqR69fv0NixfflvCI9BWdQ0blyDS3THj+/HF4toVAFxCnEVSrLxXggfXbq0oDhxlIZiAsA6mjlzJJfWIi4OyusRjdtatgzZu08fIAZjm0ycOID/xrkZdiLYJ5s3r8cD/sGxfv1OLvPt3r2lbEQTgkEEVFsgdlWEe5Q+DxnSlcW6L1982LtaG8RKyFaEMDlo0CTOSERCBZroobIMA65jx86ikSPVNgmK/+DLl295AOHFi9fUsmUD3sbwcCxXrligy4ZGnpiPNkuWTOJYCuB6DQIoMnrHjJnJjy9cOEEnQxL7GWItTPjcnTsPc5VJnDixqWrVMjxIov16wbSoWxmZF+XzkidPrvP40KFDadiwYSEex7p160aFCxemLFnU9mxI2IPFjtKASwHJe3jOWnFQ2UH9JdRj1LZ7e98JsbmMYP9gNMnL6xV3edYXlCp36jyYChbISR07NeUTWcCGMn7gxHbx4nVKliwxZw5pg4t1jKIqpuRK9hJOSMgi8g+CXZy4YFAM8QAlPwoQJpBlhBG2wHj+/BVnSK5ePT3YxipBgeWaMGEOB4SjRvWyy9Hc799/0vv3n0Jtbo/ymr59x9IUj0HkmiFtAOFRF6VRSOiERzfX8nx7684m9WtIHYio6J/ISBHJwSFSoMLjsWPnaPu2wzRlypB/8w0ffjKhyZzBPgG/xNCC0+aiRSvo6LGz3IwqpouShepMVSp1od17limv5P/V2dMqzYUvMlOLFstDjx49owP7j5GHx1KqWq0UDRrUnmK5xNVsuxUr19DhQ+fo9ev3lC2bKzk5ReQusePH9+fRfX9LpWmMFCVKFA7AEaxgcGHVqumUI0cmmjlzGY/Q45iAY8P06cOofPniIX1b/v/nrx906tRF2rb1AH356kNTJg/hLM7gytNWrNhCSZIkDLKEyRqAJ27q1Pl5NDlmzKC/T3hD4ipBm/v3n1K6dIZZiSDDGse6CRP6s01FSGAgFVn+KK9UBnABMoMKFMjJ9jTa5WrLlm2kMWN0BQGAAV8IFhh4/fTJW8cDDiIhMo+qVQv6mFS5sjutXz8n0GoQvB8xWVADtTjmqsu9N3KGXGDNMewBdBROl073AlpfED937DiYhSNklpoSCEqo+vFfFaQPOEfCLx1e7C4ucm1p7OODf1D23KfPGBo2rDs3yVTAbxxiNJriBQUGIJAhifgaFRuNG3eldOlS8vUVhGPtz+jSZRgLnMiSPH78LGXPnokHgoMq68dAw9OnzznbET7aaNqIw9DkyYP58UqV3FlIB9jHTpzYqHdZLbI1d+48SAcPnuIqOO3rxsCAwInElxYt6ltttRrEXRcXN6uMqZS4xvPlcooR07xC75fP38g1cVPy8vLSWS/6ZDzCinDPnj108uRJSpYsGT+2evVqtiZEUxlt8uXLRyVLluRGNNaICI+C3REa4fHkyfO0fcd+Gj8e3RKVJh1OBgkR1aq1YlNyZDYFFwShw+yMGcMpQoSgg1dzghP1xInzeRQOI/8I0tGQxF4MgsMqPAL4amLUdfOWWTrioSImOjioTxoqlV/Zs66wyI8E87daPBw2bAqtXbObrl7bQZEj+3XPVKn8PEL9mpNE0FmGxo160MiR3Sht2nSh/p7hRXhEZoyhXa0DoqKdu/bRwgUbaNqMXpQ0WQLy+fqdmrsPo82bFuo9F3i6IgMRJc1q/ALWR09u06SJy+jRo+e0eOkQKlW8HSVLlohata7PTasMtYPAZymDG2hUtXDhWr6gKlu2CJUuXYQSJYof6PcESqd1sGvXUZo/bwMtWjSeEiSIF8B/DesYF+ilSjXk7IXdu5eStSLCY+CI8CiERWhCTITf/759KzSZhYYCD+s1a7Zx9mNQg6Lfvn2nRo260IQJA1i0BNbQxAHe2ijf7tatJVfDoMQbpZn2QliER4DzQ7NmPWjYsG7c9MNUoLKnePF6NHnyIE0lkb6sWrWVmwZ26SJ9B0y9P2gnU3TqNIQrtSpXLsWPtWs3kPr2bcdCob6g+SYqN7TjaAWIkiiJRqMoZDtCjCxaNC9bWRl67MBx7s2bd/wbh0A5cuQ03ucgqiOuyprVTa/rPLwXTUdbt26oU26uAP9tDN7UqdOes7ORwW3I+jAntiA83n21wiLCY4ZE/zN4vaCKZdu2bXT8+HFKndqvmu3w4cNUunRp+vjxo07WY8qUKTk7Eo1nrBGLl1oLgjWAUSZkJKpUMIBVymVJbwESJ6sdOxbpVXqEyZqAQNa7d1vavHkvHThwkk/8GEnzy5wTEBjDi8XzzgNydUuj8WT0EwH/eT5qfBf9fBz9kspVgQqSeF6JdZIkScyC75UrnpQ/fw6tbRRJq/xW7SuoHR+hdAQfkyatlFibDweqUrk8JUqYmNq3HUv58menu3cfUvz4sUmlCNJ6HDtQXoOOh4Hx9fMvev78Hf36+YccKRotWDiWLQASJwqdiK5dyoOgHhP8zuCp1b37CM4UOHJELUZqf0/g6BCFb/HdqlQpSxfO36Q1a7dxxopLTBfavfsIPXz4lC/WPnz4pPlOwXl5CYJgnyAmQuUHBAB0oA0NsLQIqYNwtGhRaetWP+9aawEZW8hMR4bSu3cfWdxAeSZ86gRk+USihg2rs42HKYVHxFfIUEU2raHC4969R2nMGHX5vWAekCG8dOlk9tXctm0/xzuwm5o2zbDrkYAVIX4gPkFTz1ev3nB2JSreQnuMwnEOoiOANQSssFDtcezYWc56RlJL377tQ4yD8F40Lpo8eb6m3BwNkJAJ+f37d7acQLwG0RGCo7WKjoJxj12dO3emLVu20NGjR3VER4BmMhEjRqRDhw5R7dpqaxBPT09uQFOwoHXpDNqI8CgI/05EEG9evHhDSZMGlvVj3+DkCc83TJAWatduz2XY4lHkR8VKJah69Q507fp2ihjRNNmgMKhHZgdGNw3h3NmrAfxvBPMNWowe04Ma1O/OjZtix45JVSq35MYuadOmYk8fZLsA+LkimAjJV0ohdZpkVLtWGfrrq+Iyn0KFcht9+bFs8NPChJIhXGyhpDEk2rZrSBs27KEmjbtzkFy8eAHOUMJywuvs9u37PE90ghUEIfyBi/ubNz1DfVFv6yCrChNYvHg9HThwIkQhNTxRpkwRLq1Fs0RTDcij9F0dU7026H2wPoIvepIkIVsECMYFA5/z5o2hHDkqsh9+9OjRqGJFdxbtUT6NWAP7jlLhhngZlSD6Ziv27Nmanj17yb7XiH+U+MxYoKJEGdjdtu0AN8bRZwAWdjhonoMkGFx/derUlI4dO8MVMfC3RTk5jidjxqAyT7B3OnbsyOXUyHaMESOGxrcRGZtRo0bl25YtW1KPHj244QyyKCFUQnS01sYyQEqtBbsjNKXW4OTJczRu3BwaOKg9N1HwA359Spaa5Ut4TA0ymqZMWURuruk0pQ7hvdQaoHy0atUWtHffEooSRT1m40D+yzj8yqfRcES7LFtF6nJpZV/yy5Z00rzv3dtPVKRIHYoWLQrt2r1Y44ulvAd+kSqVuvO1YgkAYLzdrGkfGjmyC2XN6ueNI5iy1DrgBU7GjOqMimXLx3OQjCyX2bPXULGiebisY9euYxQ1ShS+EEJDl9JlCmveb4i1Q9jxX+6v5tq121S3bgfatWsxd5kM7DVKNqeSeTtkyHTatfMIrV07iy/SkDWNLvDIeLRWDyJtpNQ6cKTUWghrKSWEx6FDp3ITvQEDjN+h2JaAl9uUKQto7twxZA8Yq7QWZbUQW9DwxRRgoK9Vqz508uQF8vAYzM0j9WX8+LkUKVIE6t69lUmWzZ4w1v7gnxEjpnEVBY4faMLy4METmj17BcdX8Ni/fPkm+fh847gOHpCo3rIGCysFDMJmylSGmjWro/cxEB606L5ds2YF6tatBR05cpr3YzStUrIrrRlbKLW+92qlRUqt0ydqovd6CUpIX7JkCbm7u/P9Hz9+UM+ePWnNmjXs9Vi+fHmaPXs2JUpkvd7C1vPrFAQLU6RIXh5lGz1qNp/EFPxEx/CCitzc0nCaf8DmKeEX+DPBV2/d2t3/RD+nYHqkObAoyZMDGsJE5FJVTCibVpdO+70H+ximePFj0Zq10+nbtx+0fPmWf+tfaT6DeTpxObd6Us8X92PGdOFOw7duY5sJIWGKnmoIdg8eXEW9erWhAf09aP/+/8jJKQKVKJ6PnCI4UIIEzjRzVk9as2EQTZraljw85tOhIzvpypWr9PfvNxb0FFHPUj39rl69xbcjRmg3q1L2QRV5eCwkN9cyVK1qG/rzB7YUEenXz998YYbyoBgxnPkiEhlOtiA6CoKgL4YfM3GRPGfOKHr82IuzdcIzyNTCIIdAAZoxomu5qfqc4uJ91qxRXMI7cOAkFoL0BZ7tJ06cM8ly2R+m2X7oJr5ihQeLjfPmraK3b99TyZIF2SM/QYK4bPWydu1M2rJlPg/Ao3keGn8iY9AauHnzHtsnoRFWYPs4KkMKFqxJrq4l2RtSsY/AwC8qRrD/QpRH12tbEB0F46FSqQKdFNERoJHkrFmz6MOHD+Tj40ObN2+2atERhDdFRRCCBcGJu3ttGj9ufrheU69fv9OrC2V4o2nT2rR+/S7udmgqcubMRClTJaU9u49yFp2+rF61g+LG8TMYFswPfHpatapPixaP43Lq27cfUOIkCejVq3e0aOF2mj9vKy2cv4MunL9D1WsWpnVrjtDIEXNoz54TOoFo584wV+/L95HBvWLFZjp+/Bw3btm+/QCbrWvz5ctXzqg5e/aKQRdW2uACa9SomRwkw6sRBuywoABDh3pQ2bJNaO7cVZpMpmpVW9OQIR7Ur197unXrHg0cODFM604QBPsDF84jR/aiSZPm6wzohjdwLI0XL7alF8PqgIcfMuTRXdhURIkSmerWrcyNiCBK6QvKXDEILFgODGaiW/X+/Sv59u7dxxwXI75asWILLV++mTw8FtHWrfu4QQxikSVLNtCAAX4dfT9+9Garg2LF6rIXNTpQnz59iRt94rk3b95TvnzVdOJ6xFoocT537gq9e/chVMuO+dWt257LYhFX1azZhg4dOsXPXb/uyWJjjRqtNXEWOr3Xq9eBUqVKTuXLF6MGDTrx8gnGx8FC/wTxeBQELdQHhVq1K9Cq1Tvo5Ut7F98C77aMi4PNm/fRnNmjw0VpuSE4OkEIVNGfPyibjkgqrYxFNQHXl1JCqwpivQeWUduieT0OppApkiZNcq1MuL8B3ofya1C7dnmKYUddM20TZAE6UOpUKXlS+F+TOuwZhVLmZ89e0Ivnb+jFC2/6+8eJ3rz5QK9eIbBV8Yg9AlEFGInXqFGWli7dpPMpQ4d249s9e47StGmL2cwcBumFi+SmnDnHBtkBNqQAv3//DpQ+fWr2E3r85Am17zCIhg3rSjFiRme/K2Q1btmygINoWAiMHDmdVq3eRmPH9qGGDbvQ8uWbqGLFkhQ/vnHL2AVBsF1QFonssY0bd1OLFvUoPIKMLcWXTtAFGV5fv34z6WqpUKE47dx5kJvMQMDShyxZXOnp0+cmXS5Bf99HZP1h0s6WxSApyq9fvHhNDx485WYb2GbaMVD//uO5XBmgiV6nTs1o1qzlnD02bJgHP46YBQI13jt48GQeLEb8jWPXzJkjKF48w2MaDBrDTxIe2GjslzRpYmrffiBna0LYjBMnFouOaOiXJInaCgpCZ7duwznLEzHjuHGzWTSHl7gg2APi8SjYHaH1eNRmw4Zd9NTLi3r0aGGnHo9K+a5yX/EPVFHPHqOpSNG8VLuWfXSjNZbHI3j1+iW1bzeENm2e8c9/I0IQ4mHA/cSv07GuYAhhMrASW3W3a7+Mx8OHTnMw1KhxjUDns2P7AXr0+Bl17SJ+RMEBYR37RMKEcckaUMpvFD+Xo0dP8yh3zpxZaOmy9bR/30nKkiU9tWvfkBwoIndrxEt79x5L7z+85w7XGOVHuTM8jvy6poedLVv20qFD/3HZNH5DI0f21BmMQeZAy5a9qcn/qrO5+9gxczlLYNGiCRxs28LxUjweA0c8HgVt7t9/SunSpQj1SkFjrSZNutK2bQtDNTBiyyDLafXqrbRgwXir8p+zFk+/5s17cedfN7e0ZGrUcZX6vASxc/jwqXxeg+gUWMZanTrtaOfOJSZfrvB+fDDldkbZ9bp1O6hAgZxcreHhsZj+/PnD+1ysWDHI1TUtC5vIhpwzZwV3pD9//iqVL1+cy52jRo1itOV68uQ5jR8/h4VMT88H1Lp1wwADEqtXb6OzZy/T2LF9aebMZbRmzTbq2rUFubvXJVvAFjwe779aZRGPx3SJGlvlejEn0tVaEAIBJsbIPOrQ4X8UJYqjjkhkHwSWmedImzbt4cC4Vk10txb8kyhhYkqdOgWdOXOdChbMpaf/Z1DeN4rg+0crK/KvTuacto/k7duPaMaMZZQvfzb2i/Kb6x/+P3+BzDRr1kru+Jc9e0Y72lftG/8G0trdPfE7fPniLR09eobc3NJRjx7qbMhbt+7SwYMnuXN26VJFacSIXhQxovFP5zA3xxQU+MypU4dSs2Y9KFGi+DydO3eVKlduQaNH96bateU4IggCUaxYMSlXriyceRSeMv8gdEyevICWLZtiN6KjKSxs4IEHocWc51tYlMC6BBZLaOLhH4iRaGCyaNE6at68rmw/G0J7O8eJ40Lt2zfh+xjULV26EC1duoHGjp1Fhw+v0bwWIt/v37+5Wc3CheNN4qmIDtqzZ48K9jUNG1YjT8+HHFeh7Bpj02PHzqY7dx7QmDF9ZD80AtjkejZBNxrm/jxrRYRHQQgEBBxlyxWmnTsOU5264ePiGWUKCP5Wr54eZDctgbhUbPr0xSw8mpNcuTPzdjl06DQLj/6JHz82zZw1kBo17ENHjq4h5+hSdh0UtrJ/I7sRDa9u3LhL6dMrXaaJy3ImTx7IInTMGC56zQtBK8r2I0Xy34k9ZAYMmMAlRxh19w/KhTZtnsO+sBBJM2RIw0IpytQEQbAXwn7MbNKkFo0aNSPcCI/w20VmOjKrxH4iaJCpP3XqIvbSC01Ja2jBQFncuLHp8OFTgQqPwMNjCHXoMIg9BdE4TQgK24ipsB379GnHYjd+n9qxIMqiEWfBc1Qf4A0Jv0nsR4aCgWN4Zq9ZMyPAoDGWadiwblyG/eLFG26mg87eOXJkEtFRsHlk+E0QgqBRo2q0bPlm+vr1SyAdXu0Bv+/y8+cv6tNnLI0a1Yu93oSgSZ48CX369EUn25HL1P9lxQZE6Uit7lyt06Fak+movF/3tX7vUVHGjGm5s/bZM1f9ddRWd9h2cIhCMWLEprRpU5Bz9OgGbcLQNiQRTI16f4CIFzmyXylYrFguVKZMUb1FR/y+q1dvRVmzlqcFC9bQsWNn+TEAr6GQzNNRdrRv33Hy9tY+FvoRKWJkSp4sKXtnoXRo1app5OqaxqBvKgiCfQOP2MiRI9HJk+cpPDB//hrKlCkdC2tC0CATNEGCeNz8xZxA4MmUKT13E37//mOgr0GZLcpyUX5rCBJTWTcQC5Hpqg38I/UVHcHIkdOoePF6XB2HMm3YSWC7KzFVcJ3aYb8Ar2z4jga1b0IUz5rVlSpVKskxVYMG1Qz4hkJwSHMZyyHCo2B3YADL0THso2+JEyWmhg2q0/jxCzUiXfACk22CxhToOFmuXFHKnj0T2ef+YKxDnYrOnr3Eo6LqfeE3T+qmL3/1EpH8/60WH/9oSqYDx5c9XyJFikjp0qXWiJbqKcK/yYkSJkhAHz9+Djbg8c+ECXMpU6YyFF5AQGcrGY/GYOrUxZQ9ewXNxS88GCdPnk9lyzbmrooQI8uV+x97HQbG3r3HyMUlJtWrV4VH3e2P8LMvCEJoMUZMBZDJgxLHoAYx7CWmunTpBmfSoQGGPWKs/UEpeUYjD5Q1mxMMvj165MXiIjLhggIN17B8+oLqAsRUKLMPLxhzf7B24KmdKVNpbuiHfRaetRAeq1RpTlWrtuSYqnBhtX1AYODYh4HcAQM60tKlGzlrUhDCC1JqLQjB0KhRdWrdui8dOXKGSpYsYHfrCt3gKlVqzqJEv34dLL04Vs/Vq7fZZ3HuvOA9WkwBAmM0RQkuwEMA8+7dR/Lx+U7OzvplPaIsFtsfmXDIVhPsh9u377NZ+v/+V5MaNqxBU6YM5v1CKTF6/vwVC5N37z5iD7bAgO8rygTRWbFWrbbslRSehFtBEIwHsoxatWpAI0ZMpcmTB9vlqs2duwofM5cv9wiVtUV4AlmO6PTbubO72ctIMZDr5ORIvr7Bfy4yHp89e6X3fI8fP8tWPF26DOPuxLIP2Bc1a7bh22HDulO8eLHZbgYxEeJvWM7cvHmXunYdxr7cgYG4Cz6S2bJlpIwZ09Hp05eocOE8Zv4WgmAZJONRsEsMSPgKFpxM4AeyaOH6f4+oM9vQEEQ94f5fmy3BRjCF8oKZM0eGu06ThoIOvn37jqPpM4ZSkiTx/u0Ljv8mdblzwKxGfVCayARc/0qGrUrlSzlzZqSoUSPTf/9dDPAqdTbub3Jw/MuBUJSoEfT6Ph07DuKykImT+tHmzXspvGBIRqgtgIwRBLs7dhzUlFCj7Kdv37E0ZEhXGjSoi7oE/58Yjd86LvIgAuzceYg6dWoapPAIcFGIztbweYSvkSAI4QtjHjJr1ChP9+49ppcv35A9kjhxAtq4cS6lSWM9XX6tlSlTFlDZskWpWrWyZv9sxPcQfFAWi2YeQYGMyAQJ4uo1z3nzVtHevUe5QiB16uR07dodCg/YWUjFMSJK8NENG0KhwqhR01lU9vQ8wl3Y4UmKWAr7EuIq+G8jpsqcOQN30Q6M+/cfs1c8yJ07Kw8QC+ZFSq0thwiPghACUaNG5Qyy3798yYEi8uQnMPmJPuqSW1s6+zrQ16/f2OMGI79C8KDUOU/erJQqVVIWAjEF9G8MDkWc9i9Sq0il+sNTQMHxN08ODo4UMWJEKl+hCGenvXr9Smvf8xO/kYiWwTU1X9SFxL17j+jgwVO0YOFY9o6MGzcWvX5tnxeC9sy1a7cpT56qnI24a9cRatWqL/+uUeZTuHBeaty4RpDvvXLlFhUtmo/Kly8e5GtevHjFDWMA9v327Qdw90d7E28FQTAPuEiHfcObN+/sbpXjuIhBmtA0nAhvIPP+5MkL1LBhdYstQ+XKpXibBRzQ9SNPnmx08eL1EOeFjLcpUxZSgQK52JcvZ87MdPnyTSMvsWBqvn//QaVLN2T/xiFDplCbNv14O6JC7PDh0zR//rhgB/QfPvSimTNHBPmaJ0+eszAJUqVKRqtXb+PP+PDB2yTfRxCsCREeBSEEkidPzEFE795j+KRiT3z+/JVixDCsEUl4Zd++Y1SunGW7cQ4c2J42bpoVrB9R4kTx6f79J8HO5+rVW1wu0qNnSw58ADrmXb58y+jLLJi2E33duh14lP348Q00d+5o+vnzJ+XOXZlmz15Ba9du12RABsbixeupatUyITZTevr0Od9v164JTZw4kP/GewVBEELDkCFdaODAiUF6y9oqGKTGYLUQMhDzsmVzs+jAN0TFQ4dWU8WKJYJ8TaJECVh0CkmsypixNN/v1UtdipsjR2Ye3BNshz9//lLlys3p+fPXNH58f7p16yDHPA0adKJKldw5+/Hw4f+CfD98XVEZgmZJQYFMaGV/wj4yceIAqlWrIrVt288k30kIBAe1/785J7ETVyPCoyDoQZs2jTgzsH79jpwlRipHnQYfCir6FUzZdVAZb5bjyxcf6WKt58j8+fPXeCSbMxwdIvAUPLrbOajGROps2V+B7juODpF5UjJtkfmYOXMaihjRQSvLFvNEduRfeub1gv47fYnKlAkokP769ZvOnLlMgwdPonr1OvJjSrnH+vW7acGCtXZb+mavVKrUjG+nTh3Cwa7iQwrgyTh//ljuIhsUXbs2p8WL19H69TsD7cKJfQaj80r2DgTOtGlTUtOmtdlAXxAEITSgYceYMX2pQ4dBnEGNhiz2AL6HDObqx/79x4PNtjcXCRPG53NbYCAbcurUheTuXjfQ5x4+fMrVBTlyVOTHDh5czaW36JJdrVpLjrkE22H69MUsLqKMukaNclw+/fGjOhNx1Khe3CyqfPliQb6/ePEC7O/ao8dIzfv8c/nyDU0VScSIEbjcukKF4jxoIZUkgr0jwqNgl5ii90Hbto1p6tShdODACapXrwMdO3ZWc5JQhCH87SciqVFKYRWhyFflwxM8Ii0tQn79KhmP+hqgu7jEoEgRI/0rqVaLfX6en4qoqL09dYe4/Jdja/YL1R9yIMw3UoD3+O076vkjQzVgV2a1z+Tbt940ePB06t2rHUWNEi1AZhxGa7dt288BVf/+Hej27YMUMQL2W0cuG0cWZc2a5Sk8YMvNUeBH5eGxiGrVUmdVwB9Luxs9vIcwIUjOmzd7iBf/q1ZN4y6NuEiaP381ffjwSfP8wYMn2QMrWrSoATyv3r59L0GyIIQTTHHIRLbb5s3zuDQZmdvz56/hc62t++3GiOFs6cWwCby8XlKGDKktugyIqYLqKowKp0WL1lHs2LHY108bxPotWvSmMWNm8d+wNLl6dS9XSIHIkSPz7ZQpgyg8YMMhFW/LlSu3UPPmvWjevNX82KZN8zTPIwZCTIXBXFwHBhc/RokSmcaM6UNFiuSl//2vG/XvP55u3PDUPI/j26lTFwNNDsAgMQRrwRw4WGgSpKu1IBhAihRJOf0eQs7MmUvZSLpHj5ZcrmGLSMajfqArIbK/LAlKefLlrc3373ju1WkQhOZHFy/eoBYta3OHav+sX7+D99NKlUr9e0RX7P7w/hM1bFgt2AYjguVBI6BOnYZofKMQECMQDgtoOIPujLgA27JlLzVr1pP3hUaNqtOaNdtp2LBuAd6D8vy4cWPTihWbOfvR1kB2J4zj0VxHEATLgQv15s3rUb16VWnlys1Uu3Y7ql+/KjVpUpMiRHCy0ZhK7Gv0ASXWlo6rIDZBGNq/fyWlTJmUH/vx4ydt2rSbvffggTx4cJcA70MzN4iLsDcJDHQ3RkktMuAE62bJkg20atVWevbsJf+NhnxhOfZAmKxduyIP5J84cZ5mzFjKj02bNowbzyDLF5mO/unYsSnHd2vXziRbBNciSZMGnjksCAqS8SgIoQAdYj08hvAJaty4ubR799F/Jbh+XjV+TT/8HlEX3H5XT6pvFh0FwSgfRpyRyScED4KQ379/a20vpQu10tVayXxUZ7sG1vFc0zBGUyL959+Ejngoo46olRWpZE6q56tkmd26vZ/vjxo1hz5+/Er9+k2irl1GUr58OWjr1gVUs0blQJf/1KkLVKJEQa1H1N9DWaZ9+05Q69YNZUTOykHpDgJYDH4AHIOyZnU1yrzRYKhZszq0YcNsOnToFFWs2IxFAZRW+wflRyjTt0X/qtev35K7e09uxgPxURAEy4OsRwyirFs3i549e0G9e4+2SU9txFQxY0pMpQ9omKeOqyzHpk1zqVCh3FSuXBP+G5lv8L9++/YjrVgxjfr16xBojHzy5HkqXbpQkPM9cuQ/cnevY9JlF4wDttWCBeqGMUuXTg62IZ8hoOQeiQDz5o3ljFl4R86YsYzq168S6OuRBenj883iYnxoriU9PBZy1Qx+P4IQHJLxKAhhAGWrixZN4I5kyBwqViyfVqGtousrwqL6bycHJassgkaY1PaJNBd79hzhEkp8ByF4ILQgSH70yItSp06utb1U/vIHFaEZpTtOOtvf7z264z2BV20oDzoFCGQ2bppND+4/oWlTl1JGt/Q0bmz/EEuH06RJyV59GTOm+7e8ynKi1FtF37//ZJFJsG5evnzLF+PwHqpevaxJSsaxH+CYxrYRwXSuTpUqOT1+7EW2xtu3Hzi7E1nMyGyR8hdBsB4wADJwYGf2fYQf8bhxttNwAceVuXNX8vFTCBlX1zR09OgZcnNTxyWWYvHiiTR27Gy6cOEaWylh8A3xfHCkS5eKq0yC4v37T5QiRRITLK1g7EoiiH0ot79z57DJbHgwqIsJn4M4PriqOi+vF4EO+ForiElxbYQM5r9/A7ctsDYCWlaZ5zMFyXgUhDCD0dAuXZrT8eNnbWptoglF7doV5GCoJ336tGU/H0ubP2fMmJbevf9I9+49pqZNa+m1/XLmzKQpz/XP1at3KFOmdMEGQ4LlQffXgQMn0OTJg8wSxGD+we0TyFCCGI8yIpii2wpZsrjStm0L6cSJDZqO7oIgWA849nTu7E7Xrt0hW+Lp0+fchDCoRiWCLhBidu06bPGmdtjf0NV66NAp1L9/xxBFR5AjRya6ciXwmAox4okTZzmTUrDuDtZoAlO3bhUWks0hDIUUZ+fJk5WvM+7ff0y2AgTH6dOH05kzWyXLVwgRudIU7BJza0OJEyegFy9e833/na4DTzSO8K+sNqTXhhb/HbT9dVhWqejWrfsSIBtAwYK5udz58OH/tB71bxyslGAH7Hge9HuCC3aUUmv19luzejvlyV2d3rz+wKP0jo767Ts5cmT+FyT7b2akot27jlLFSiUoPGFp8VgfMDJ+7NgZGj9+LpuUt28/kMaO7avxobIGli/3oOjRo1GdOu3YD9JUpZFBdYcUBME8WOKQiexrW2o2gyZd4nFm2Pbt2rUFjR8/hywFmnnkzFmJl2H69BF6VwDFixeHPn/+EmhZ7PXrnlwZo4+AaS/YQEjFoAs5muh17jyEqlRpTpkzZ2BPa2sBfretWtXnpjTI+IZXqCn4+tX2SrqNibSWsRwiPAqCEUAQErAbWVCikiL+GGt0LXBxMbjXortxokTxuautoD/9+rWnqVMX0c+ffl3LgeLN6MCCcgQDxeTgtpmuiPn69XvOEhgwoKNBpdGnT1+ihAnja/ZJZXnRZOPEiQtUvJi2/6NgSX+wpUs30ubNe9mDcO/eY5Q7dxaaNGkg7dmzjLJly2hVGwddGOH1uGbNDA7o+/VT+yQZmwIFalDVqi3DdaAsCOGNePFi20yX13fvPvCx2929rqUXxaYoXbowN+Q5c+ayRT4fZbaoWlq5chp7t+vLvXuP/g38qgK1MapYsaSRl1QIbUM+NAnat+8YdekyjAYMmECxY7tQp07utHPnEurUqZlVJjnA6xbe7Rh0hoWDsUEjr6xZy3GWtiCYExEeBcEIwCvx27cfNrEuMYI2f/4aGjiwk6UXxeZACRU6Qy9cuNYin48GMdeu3TYoY+/ChetsA4DSNf9cvHiTsmbNIP6OVhAcz569gjp0GEQ/fvygBw+e0Jw5oznDEYbjatHYekE3dIjhd+8+JG/vL0af/8GDq3neZco04s6JgiDYP7YSV+F8PGzYVOratTnFiRPL0otjU6C8FbEoMg4t0UwoSZJEFCOGMzcd0xd4A/fpM5bGjevLXsH+KxXgW1mihHSztjRoqlinTnuuRoOwjcxGDJLWrVuZ/UXD0rnaHCXZVauW4QmiqbFBIy/EbWXLNjHJ/AUhKER4FAQjgJKLqFEjW0nSeNCiFDoub9u2l2rVLs8nHcFwkOG1d+9Rev5cWwAxVndy3YxEv3Jt9eM5c2YmZ+do3FHRkJHN/v07sA+Lf/bsPkEVK8nIvKWASIcugAiOccGyceMcateuCfXu3ZbtG2ztArJChRK0ffsBo5dHJk+emLtNYtCkdOmGnFkkCIJ98+XLVwvGVfqD49KzZy+pfPnill4UmyRNmhTsh7hq1VazfzbEp86dm9G0aYsNErRQiYAyXf/ASxtN/CCaC5Zh27YDXH2BOGHmzBHUq1cbGjq0G3eWtrUGH2giuHXrfqMP6GI97N27nPLkycaZoGXLNuYB8PCCg4X+CSI8CnaKuc8tCESQHq+fqKQuxw2+TNqQ8unAPwcTuhdjevzkIb1+85xmz1pNe/eeoBLFZTQ2LOWlPXq0psmTF5CxUJEvTwEJKGi6u9dmcUdf7tx5QJkyKQGyen/CZ/3+85tOn75MhQvnofCGtQSfBw+epJEjp1P79v/jkh/sW7ZMtWpladSoGeyZha60xgQXDbduHaQhQ7rQ2LGzuBulIAjmwdyHTGSVvXz5lpInt87OwLBbuXnzLgtNLVr0pkaNqlt6kWwanAPXr99Jnz59Nvtnly1blC5duql3JQm2e9asgdueoMy6UjgczLWSkIp/l336jOHy5Pnzx3KXaFsGy49GM/nyVSNXV+PuVyg5X7VqGu3YsZiePn1BU6fqL74LQmhR1A9BEMIAMtDq1KlkVesQJ+D+A8bR9WuefFKBqJEsWSLavmMuRXCKYunFs2lQRjNhwlyLfHbEiBHI0Un/ZHWMyl+/fody5cqi8/jZs1coV67MgWZCCuYBXVvh31ihgn1kyiAzcdGiCexRaYpOpU5OTtS4cU2eBEGwXy5cuMYdXq1lkEg7m2ratEX048cv9p9EM5mRI3uFywE8Y4JKDmxveCfmzZvdrJ+NfSxy5Ih672vZs2fkcmpko2kDz+yTJy9Q797tTLSkQkigsU/lyqVo+PDuVnfsCC2ohEEM3737SJPMP0OG1OTpeYTCE9g3zL1/2Mv+GFZEeBTsEnN3WENjBX274ekS+IHIf/abIc1KTp+5SNu3HeCu1dWrl6PJkwaTSuXLniEhfa69YuwuxjiBoEQHnkQQAsM8v3+uF8hO1f7bL9tV2V4q+vnrl0GfWbJkQTpy5D8WGbU/b8/uY1S5cmkTdVW3XrArWEtXa3QaR1m1PQUkRYrk5Y6ebdv2Jw+PRdSlizsLhoIg2C7mPmbC59bVNTQxlfF5+/YDLVy4hp48ec6ZmFu3LmShTDemCl+YYndInDghvXhh/AErffZtX1/9v1D+/Dlp3Lg5/D7tc/f589dYlLT1yoXQYC0x1aVL17k6Ar6d9gKyvjEdPnya2rTpR4MHd+VBXkGwRcLvWVOwWywhLMSNG5s+fvQ24SeE/H0ggg0ZMoXmzllFtWpVpLlzx7AfIQIjdfc9bR/I8IOp9ocECeLRmzfvQv1+pQxeG8Xb0f92UtFP8lX9oD17D9PQIdOoZAn9u1AXLZqPTpw4rzO/X7/+cNOZAgVyUfjDOgJk/F7hhYgLWHsjadJEtHnzPC6bmzNnJVk31rE/CII1Y25dwfQxlX6g8UKzZj0oY8b01LNna1q4cALFjOkcrkVHYIqYCr7GL1++JnMCMblVqz6cbakvUaJEppQpk5Gn50Odx3fvDp9l1sBKdEfy9HzAnqH2CKpjmjSpRV27DuMBEEGwRSTjURCMQLx4cejNmw9h9hNB8xflnhr9MoUOHDhBa9Zsp0yZ0tOSJZPCfVBsDlBihXJSiCxhRUW/dba3/wxIL6+XNHLkbIrh7MxNNhIkiKv3vF1cYvDo6IABE3g0HiUbV67coipVSll1Vz97H51H1ioaPGFb5MiRiewNdPtEt9KmTbtz6Vz+/DksvUiCIIQa8x4z48ePyxlklgJdjmfMWEa3bt1jHzT4oQmmj6kuXbphltWMRhrz56+h/fuPU//+HTlLzhBQZo2Yqn79Ktxo8OLFGywGDRrUmcInlo+pQK5cWdkOIXdu/YVkW6JYsXzs+ThmzCwaMaKHpRfHZrFECk74SvkJmvA9ZCcIRgKBR/z4cSy2PuGpdu7cFerRo5WIjmZCXRZk+tH5HTsOU9kyzanp/6rTlCmDDRIdFaZNG0bFi+cnb+/PVKVKadqwYQ517uxukuUV9O/YCo/H+vU72u0qg3/opEmDaPjwqTJCLwiCzcRU7959pA0bdtGMGcNFdDRjTGUKb2D/4DOyZi3P5yT45xkqOoKKFUvQxIkDuQzfzS0dTZkyiDZtmiue2RZm/Pg5tG7dDqvIljYVzZvX5WqrY8fOWHpRBMFgJONREIwgIMBkPGXKpHqOBDoE+ZwDRfTn8ajfKKKPz3favHm+iI5mBIbM6EqMTr6GoQpYcq1SZzwqdkF+r/ClqFHVfkFFihYI9ZgZysLKl7ePBib2AkTH8AAaWiG70558LAVBMC2HD/9H7ds3sdhqRqZjmzaNjFLRIOhHwoTx6OnT5xxTm9KjD1UgoFatCpyZH1rSpk1BnTo1M+KSCWGtZEFTTfDgwVODyudtCcRSyOiE6C2Ech3++2dOzP151opkPApCGIF/HhoqBAVERP/NYpRntJ/bt+84ubqW4ilXzqpUqmQj2rx5v15iU6lSBen06Yth+h6CYZQqVYi8vF5wqWzYkvx9ycEBHRUhOqP02UnL69GJ/v5VUatWDcJdExh7B11QMc2aZZpOhdbE9+8/wqXhviAIhgPxAOWEsI4JC8h6KlmyAbm6lqQsWcpRkSK1qXPnIXpZbaAp2+nTl8L0+YJhYICqWbM6NG3aEpOuuogRI3IDNEyCfQlyHh6D+bdrr6KjdtYufOYFwdYQ4VEQwsiRI6epVKnCYV6PXboMY683mFOjA3GcOLEpVZBZlLpg5AvG3IJ5gxx0lxs1agb9+aPbJMaYXLp4w279asI7Q4d2o5kzl3GjGXsmTZqUdPnyTUsvhiAINsDZs1e4c3BYs6RbtuzNdiioSihcODclS5aYG0/oM1+UWidOHD9Mny8YDjwTr127zRmnpuLOnQeUMWM6ycK3QypWLEk+Pt94H7JnIKwePXra0oshCAYjpdaCEAYgOKFkcty4vkG+JrhMNeU5dBgG69bNMngZ3r37wCegpk1rG/xeIWy4uqbhAGDNmm30v//VMui9fg1kQODC5ZvXH+jYsXPUvn1T2VRGxFrKfmHPgKxH7D/2/PuFJ9HKlZspZ87Mll4UQRBChfmOmYcPn+IqjrBy8+Y9Wrx4Ih9jDcHX15c2btxFOXNmCfMyCIbh5OREgwZ1oZEjp3NTH2N3D8e2Xb9+Bzc8E4yJg9XEdmgWNGLENFq9errd2k+VK1ecm1/BZit69KiWXhybA5cA5r4OsJLLDotjn79IQTATP358p2jRInOwFBYaN+7CI7Ch6bzo7t6TevZsw/44gvnp1MmdO4ob7reilFz7iY5KiTXK72/fuUctWvTmzsDSUdN+gY/ZqlXbyJ5BaWPUqBIcC4IQMq9evaMkSRKG2SMSGCo6gn79xpGvr8rgwUTBOGTL5kYZMqShTZv2GL2Ev0OHwXwuqlevilHnLVgPsGhInjwJnTlzmewVJydHPkaJhY1ga4jwKAhhIFq0qPTp02ejlNq6u9fR+7UXL16n2bNX0Lhxc6hLl+bsNyhYBmfnaGwwjm56xuLbt+/Ut8947mJdrFg+o81XsD6cnaNT7Ngx+Thir1y4cM3uPZcEQTAO8N67fft+mOZhaBnir1+/qU+fMbR9+wH2pB0ypCt7DgqWoXv3lrR48XqjdieeNm0xZcmSgQYM6EgRIohntj2TI0dGevDgCdkr8JdPliyh7MdhbC5j7n+CCI+CECYOHjxFBQvm1uvgz92LdabfpKI/5Puvo3GsWDH/Fd6GbHy+e/cRDqJwW7ZsUdmKFqZixRL04cMn9qYyFHQyVyaFSRMXUp06lcjVNa3VlLAIpgO+Y1evGtqkyHbAQEnu3NksvRiCIFg5v3794lJrNIgIC3fvPjLo9Y8eedG2bQeod+8xXKopWBbEw61bN6QpUxYYbfALPsPt2lmuU7pgXl9pwxs/2g6w55KYSrBFJONREMKAt/cXSp8+lZ6vRgOJP6RS/fw34f4fKlhAnelYpGiuYDpg+3Hw4ElauXIL39+9e5nV+NWFZ7ANBg3qTOPGzQ5FoxDd7bdhwy6+CGrSpKZRl1HwQ5+upuakZcsG3Mnz71/jNSn6+hUG63do69Z9tHTpRt6nLMHTp885ayVZskQW+XxBEIyBeY6ZKB+EZ1mMGM6hnseOHQdZZFq5cqper8egYbVqLfk+uiqHtcxbMA41apSjhw+9wjwoh8y3oUOn0NixfSVDzGRYV0xVoEBObixlzCZFqGx7+PApX4MtWrSO/vvvokkbSwYXv27dul+qocLs8Wj+SZDmMoIQJuCvge6HoWXTpn1cYnnh4la9fCJxkuvYcTDf37ZtAaVNmyLUny0YP2stc+YMdO7clVD5SqG8esSI6VzmNXPmCLs1xRYCgt9x1qxuHNCWL1/c4CD05s27dPXqbQ6KMb18+YaiR4/G+yTmjfswW8dASfnyxahChRLc2CaweRl7IGPYsKnUt287GSARBEGvmApefGGhV6/RNH58P70biAwcOFEjOqIMV7AOEAPBSgge2tmzZwrVPFA6v2DBGho7th+lSpXM6MsoWCeIY+B9D0sqxNOhadp56tTFfzHVE3r8+DmpVL6ULFkSjqlSpEhCO3ceouHDp1H+/Dm46ilfvuwBruNMEVPhcxMkiEtZsrgadb6CYA7EwEQQwkCkyBHo588fXDoddAdr9UigSqV+DcqrlddCGADOzmi84Es+Pj+D7VCG0TuYbi9aNIFPPIL1gGw1jKz/+PHD4PfifSjxql27IjVqVENEmnAIfvcRIkQwaH9DZs/q1dsoTpzYVLBgTi5PbNWqATea8i9co1HC+/cfaf/+E9SkSTeaNWsEZcuWUfP8vHmr6MCBk7Rxo/G8SpF1dPbsZZo6dajR5ikIgv2Ci3RjJKSnT5+abzGQBzEzuIE8T88HtGKFB+XLlyPsHywYlXv3HtGPHz8Nfh/E69GjZ3BiwMqV08jFJYZsmXAGrqsM9fK8ccOTK0Tu3n3INlZubmmpcuVSlCpVUooUKZLOa+vXr8resKdPX2Rx+9ChU1z5pI2bWyny9DxCxuLz5680Z85KatOmkdHmKQjmRIRHQQgDUaJEpB8QHlXf+W8Hh4DlQX6l0+rA10Hzs1NRjhzp/50YVTwyljtXNbrjuU+rbMFvpAwB9KRJ86lbtxYiOlohKBFDyVaRInn1fg+EoL17j9LatTto9Og+3M1RCH8g0xGCIAJZfZk+fQk9f/6aJk8eTMmTJ9brPXHjxqaGDatRjBjRWeieP38cZz56eb2kefNWk4/Pt3/HnrCP0EMUXbJkPdtBxIwZ+rJJQRAEQ8A5GNndIEeOijRhwgCqXr1soK9dvnwT5ciRWURHKwUWIcgm0xcIQefPXyUPj0VUuXJJGj68hwzkhkOePXtFU6Ys5N+2IaJj//4TqF+/9lSoUG699ptIkSJS8eIFKEWKpDR0qAc3RGrRoh5bLkH4BrCaiR3bhcIKSsfbtRtAbds2DvJ4JuiHJZq9SHMZNSI8CkIYuHH9LiVPpt9Ff2DgxHb9xja+7+39lW/v3XtMGdKnDzB626nTYC6TLF26sGwzKwQdMIsXz089eoyk5s3rUZ482bg0Hhlfe/Yc5RHUePHisGiM0leYnfv6+lKxYvllRD6cs3//cQ52/Zc/o3PhmDGz6PHjZwGC4KRJE9GcOaND5VlVpUpp9lCbOHEeubvXYf8reDAiswQXbv5H9g0Fx6tZs5bThg2zw+TVFlowiIN1lzx5ErnoFAQbAsc6daO90IOKEG0uXLhK1aqVCXAsWLduBx05cpqPo4J1UqNGeerffxy9evWWq0EQZ6H8FTHViRPnuFIgfvy4PD1+7MXxM2IvdCWXgdzwy6NHTznObtu2UYDYBNmJKFf2nwX9+/dvmj17lCZb2hBSp05Oc+eOpjp12rMQOWrUdPrzR13d9vz5K6MIjxgcbteuMVWqVIosAcrPo0aNGmxVniCEhAiPghCG7ou7dh2h9Rs8gu3T5PDvOU0Oo4OT5uJYRT81ZdhOEdSl2FWrtKWsWV2pcOHchPOil9crun37AXc5bty4hmwvKwaC4+nTl2jGjKUc1GCEEkFwhQrFqXfvtpzh+PbtB/r8+Qv7SUm5vGWwtoZM1aqVZYHx4sUbPLiAjMS9e4/Rvn3HqE+fdgZl0epLjhyZqE2bfnTgwAm+UG/Zsg8/vnjJOmrXVrvzp+Hras+eI7zfW0J0BMjcLFu2CaVLl5K2bJkfZiFVEATzHDORgWjMxmqImVat2kq7dx/l8zAGd5ANhYEJDAzOmzeGokSJbLTPE4xLliwZqGXL+txkpm7d9uTo6EAuLjE5C3L69OEs7rx9+57evHnP2zdTpvRWd34PH1jXOocn6Pz5a6h9+4HUqFF1Spw4Ib18+ZqzIOFxvX37QqPHBdGiRWXbpEqVmtHgwV34WkDxkN22bWGY5u3j850HqDFfS9G8eW9OoNi7dzn7pdr27wzLbu7lt+X1ZTxEeBSEULJz52EqUTI3RYvuSA4OkfQ42PzzePynQDo4RCRSRfz3nCM5R49El69spfHjF5D3Jx/2cnR0dKJSpYpxKWVYswAE05M4cQKqVasC1axZnn2j0qZNxSP0CvAZUnw9BUEBwuLWrQt4FH7t2u0snGXMmJ42bJjD/mSmAPvigQMr6dKlGyxwKqXYp05epIoVSlLKlKEz4keJETySkKliKZydo7MH0vz5qylr1vJ07tx28fgSBCsH5dFnzlymAQM6GW2eyHxDs7chQyazVxsy5yBKIKZKlCi+NHGzciBu1KxZge/DiiRatCgUJ04snddIF3LBP7B3gW/rtWu3acuWfVzujAGGWbNGciWEqbhyZQ93nEYG5MiR0znTEc3+MMALz8jQcuDAcW5c4+RkuaaTCxaMo+LF61GFCk2pV6821Lp1Q4sti2C7OKiQdmXjfP78mVxcXMjb+w7FjCkGwuEdNF149uw1pUxpupMLfja1a7ejaTN6UJIk8cnRIaY//8aA+Kp8dP6G8KhSqVPxtTMmT564SNOmraA5c0ZRggTxTPQNwg8oH/3w4TNvJ0H48sWHfvz4RfHjx5aV4Y8jR/5jM/5BgybRsmVTqECBnAavoytXbtGiRWtpxgzDO0ka+xhdpEht/j4tWtSn7t1bsh+Tf9CtMnXqfOTt7U0xY8rgjoLEVYI2Dx8+ozRpTNsVeOHCtXyLBlnGPhaUKFGfRo3qRUWL5jPqvMMr5tgfBNtB9oeg1stTjolWrtzCtjjr188O1fqtVMmd1q2babEqEoXduw9T9+4j+f7Fizt5kNc/qOhycXGzyphKiWtef9hCMWNGN/Nn+1DCODWtcr2YE8tJ54Jgw5z67wylSJGIEieJh7Yw3KE68I7W2jj9m5QUbxVnSqqniDw5OkSmYsUKUbFi+bg0SBAEwVyULFmI6tatTPnz5+RSxNDw5s07Hu23hkyZtWtn8v3Fi9dR1qzl2N9JEATrA7/NLVv2Ur16VUxyLFiyZBJNnbrY6PMWBEEIClQ4oQoKHt6wWQoNbMulUllcdATa/pK5c1ehVau2kO3KX5aYBFkLgl1iyjxedD4bOmQatWtfhzMc1VmOIftFKOKig0MEntSv//tvQubjH1LRX/ry9QsdPHiKihY1vq+bIAjqQE4ImqZNa9Hu3Uc4Wzgwvn7Vzd5G+eKxY2dp2bKN3KE9YULryC5GSVXnzu46GVUQOPDd5sxZSV++qBt6CYIQPKY+ZNap044aN67JJZKmAI1kypULfamjIAhBIyFV8GTO7EpRo0ah27fvB/r89+8/2KZGAbEXurNv2rSHmwDCGsdagHWNwrRpS+j163ec2TllygK6ft3TossmWD/i8SgIofDxixcvNmXIkNag9ykZkX7xu0rj+4hnUSJ+5fJtmjptCTVpUoPSphUvQEEQzE+ZMkW4MRLEgBIlCrIHZa5cWbhUaPr0pTRnzgo2bO/btz1f0KMxDrpso0SydesGlDt3VqvZbPB6hMfTpk1zaebMpVStWkvKli0je1tWrlzS0osnCAIRdyU2RRk0/NXQXObOnQe0ePFEWdeCIJgddIKePn0Yde48lLutI6aC9yz8Sq9evUX16nXk1128uItu3bpL//tfd/67Z882lDNnZm5GaS1ABK1duyKVL1+cXr16Q126DGXRNFmyRNxpPmVK62+C6vDvn7k/UxDhURAMBg0Y0GEMI1Kh7Ya4YsUWunzpJqVKlYSev3hD9+49pl8/f3FDmW5dm1OePNllywiCYDGaNq1NVauWodOnL9L27Qdo+PCpbGyeJYsr1alTiVav3sZThw7/o//+28zHRWsDWQSzZi2n4sXzc3OuQYO6cGd5eC4hYE6RIil7PAqCYFkwsHHx4nVu+hIa0E127NjZlCFDavr16zfdvfuIM3Hg5VutWlnOfEZzBkEQBEuQLl0q2r59EV25cpNOnrxAy5dv4oQTBwdHateuMa1bt5Ny565M6dKlpPXrZ3ETLGusFjpx4jxdvHiDhg3rzr7ZaP6EgZ1hwzyoX78Oll5EwcqRjEdBCAUpUyalhw+fU+bMGQx+rwM50vJlm7mkqEyZouzpmD59anJ2jibbQhAEqwEdGeHpgwkBJxq1xI8fh58bOrQbB9D58uUgawVdwmHqPnXqEP7727fv1LhxV8qbNxtnEgiCYD0X5TieEJUL1fshMiLbpkGDqhQxYkTOvk6YMB77OwqCIFgDESNGoLx5s/OEhnefPn3mTu2RIkWi7t1bcalyihRJrKq0WhsM3PboMYIHcxTLotGjZ/LxF16W6DCP5jKCEBQiPAp2ieliTRW9efOenj59TukzJNIpnDYEN7e0fJJJmzal0ZdQEITgkYvR0K0zRXQEGOm2ZtHxwYOnnJmZNasrdeo0lDJlysDNK2rWLE9t2za29OIJgk1hav0Ov8127ZqE+v3wa8X7YRMhCIJ5EX0/dKASQxvEK9YKvLzRxfrw4bU0evQMHtTF8fb69du0ceNccnS0pbYhIfdlMM1nCiI8CoKBrFixmRo3qcR+Z/oye/YKunjxGlWsWJID5Fu37vMBXBAEwZZ48uQ5NWjQiT2KSpcuTI6ODrR37zEeROnYsamlF49tMOrVa0/37z+hpUsnsScllhGj89u2HaCNG+dYehEFQdDC0/MhZyPDy0xf7t17RD16jOSYCpmNBw6c5ExmQRAEW6NJk65cco2YKmPGdHT8+Fm6du02LV062SosItCMb+rURdSwYTXuzo2MTFTtTZ++mDp1crcx0VGwJGHeU8aNG8eZEN26ddM8VqJECX5Me2rXrp3O+7Zv304ZMmQgV1dX2rlzp85zW7ZsoQIFCpCLiwvFiBGDMmfOrDN/QbAkEAyHDplDmdxq0ehR88iBIoX4nufPX1GFCiU4HT1KlCg0bdowDpYFQRBsCVhCIOisUqUUXb16ky5cuEq1apVn8dEamDVrGWc6jhrViz3f0EQGYmnz5r2oU6dmFC1aVLJ2JK4SwhNo1nfu3FVydS3Jkz68f/+JPbFhB/Hu3Qdq2LAqNW5s/U0NBEEQ/IPrwho1ymmyvyE+IkPu8eNnFl9ZN2540tGjp2nPnmXcdPDgwZMc7yGhBqJoyZIFyTblL0tMQpgyHs+fP0/z5s2jbNkCjjK2bt2aRowYofk7WjQ//7qfP39Sx44dacmSJZyF0KJFCypXrhx7HBw6dIjq169Po0ePpmrVqrFoeevWLTpw4IBsLcEqqFatDIuPI0ZM4/I9fdKncbGO0SK8DyNY6IwtCIJga6CJDDxu27TpT56eR0hFf8n7kw/dvfuQz+eWLGNH5tTZs1do3bpZnOXo6fmAbS0GD+7Cz8eI4UzWjsRVQngDnV0HDuzEXmH6gsGP3buP8HGnfv2qVLx4AZMuoyAIgqno3bstVavWkhv1uburO1j37DmKRT5LWnKh+c3IkdNpyJCulCZNCu6u/fLlG5ozZzRFiBCBEiWKb7FlE8KZ8Pj161dq3LgxLViwgEaNGhXgeQiNiRLBAy8gEB6hkufIofaHws6LxyA87tixgwoXLky9e/fWvB6ZkTVqyEimYB1ANMyXTy22p02bQq/35MiRmZYu3cjNGby9P4vwKAiCzdKiRX06efI8+90uX76BTp++wt6JlhQdP3/+yl0Vhwzpwt23+/Ydy6VA48b1s5kyIImrhPAIjhtNm9Zm4bFECf0ERHSk9/X15e7V6F4vCIJgq0BcRNxy/vw1Sp48MfXoMYoSJIjHTbIsBQaSFyxYQ9myZeRGqocOneKKkoULJ9h+xR5iVXPHq2KEyoQ6GkfGYuXKlalMmTKBPr9q1SqKFy8eZcmShfr370/fvn3TPBczZkxq3rw5JU6cmJIkSULt27fnkmoAsfLmzZt048aN0C6aINC/ZlsmM6T19HzEF9rZs2cK8R2/f/9hX0hcrF+/vo/c3JBCLwiCpVC68QmhI3/+HLRw4XgqU6YRbd9+iNq3b8Llzebm16/f3Ohr9ept7DuJZYCno5tbKfZz7N27nc2IjkDiKsFaMfUhE3ESLrQnTRqo1+vXrdtBuXNnpf37V1Lr1g1Nu3CCIASLhFRhAz0Djh/fwMJeq1Z9qXHj6tShw/8s4u/4+vVbOnPmMjVu3JVtakqVKsgWGB06DKIOHZravugo2F7G49q1a+nSpUtcEhQYjRo1opQpU7KoeO3aNerbty95enrS5s2bNa8ZOnQo+zbiokARHUHnzp3pxIkTlDVrVp4HvB5Rho3sysiRI4dmcQXB6Ny8eY8uXLjOF77o7hocuDCGD1Hfvro+p4IgCLZKwYK56cqVPfThwyeKF8+v27W5wHG1W7fh/NnweluzZgY9euRFV6/e4ueLFMlDP378pMiRQ/bgtQYkrhLCMyiZfvv2Pd2584Dy5s0e4ut37jxIK1dOswnPVkEQhJBALLNjx2L2rIX9hLkHTXE9O2bMTLp+3ZNSp05OAwZ05EzHqlVb8PMotY4eXY63gpmFRy8vL+ratSt7LsIMNTDatGmjuQ8BEZmNpUuXpgcPHlDatGk1z6F5jH+iR49Ou3bt4tceOXKEzpw5Qz179qRp06bR6dOndbwi/fPo0fMQPZx8fcM+bKtumBPm2ciymGi9/P3ryyXNKMMx1bJ8//6L4sWLS56ejylq1MB/B1+++HDjBTQ3wEH84cOwmQTLvhu69YKT6efPPvTtW9DlWPKbDj/r5evX75p9wtLLYk3rJSzL8umTj1mX5eLF67R+/U5q1aoxi47g7dtPtGvXUerevQ3lz5+Tl+X9e2+eguPFizdkaaw5rnrwAHFVdKNtX2TGGCPjWJbFvOvlxYu3Bm83Q5bl4UMvSpEiGb1581EnVtJdFhVdunST7ty5TxEiRKIXL96ZZFmCQvZd3f1B1ovsLwovX77V+/clv6OQ14sSU4WG0BzrEA+PHz+b8uTJRhMmIOvcgZflyJFzlDJlCpo61a9nx/37XsHOC9e+1o7Dv3/m/kyByEFlYCSxdetWqlmzpk76L8xHsaNDnVf8G7Xx8fEhZ2dn2rt3L5UvX97g9f7o0SP2eZw/fz6XaPvn8+fPHGx/+nSbYsb0y54UwifYH728XlOqVEmM7iGGBjFJkyaiiRPn8WN37hwO9LVfv34jd/eeVKpUISpYMBdlyeJKESOGqZeTEEqQ9fThw2dKkkRMkAV1UPT9+09KkMD8WXqCcUApdZcuzbkUScHH5zs1aNCRVq+eblATGZQSpU6dn7y9vdkGxhJIXCVYOxAD06RJZvT5wkPs589fNHPmMv4b5YYJEsQN9LXTpy9hT0fY3KDMOlYsy/xeBdPtD4JtIvuDbTNjxlKaNWu5zjUt5CFc6yJxpm7dynrP6/PnLxQrVkaLxlRBoehFbz/uoZgxo5v5s30ofuyKVrlezInBSghG2K9fv67zGMRANzc3LqkOzI/gypUrfIsR+tCQKlUqHpGHgBmyyi+KcnhHLYIbf19A0AsvMYWLF3cF+RnXr9/h2zZtGongaGGU44IcGwRlf8AgmewPtkv69Klo585D3MG6evWy9Pz5K9qz5yg1aVIzFIOPlo8ZJK4SrB1TnENv3PCkyZMXaP4eO7ZvkP5hGFDetGkPLVgwnlxd1VnOguWQmEqQ/cG+fs/JkiXmztplyxblBjdr1+6gZMkSUceOTQ069ttGbI0ydnP7f9uO37hVCY/wY0TDGP9lPHHjxuXHUcqzevVqqlSpEj8Gj8fu3btTsWLFKFs2dSfg4Bg2bBg3osH74fH46dMnmj59Ov3+/ZvKli1r6OIKgtGy5lau3ML3o0WLQnPnjiVn56DL0woVys3lgMh6xP3mzeuKF5EgCIIR2LlzCd/C03H79gPclGLjxrk26z8kcZUQHqld28/32t29DmcyBgWSGubMGU1duw6jYsXy82szZpRGfYIgCGGlc2d3nr5+9eFBXFhfTJgwgFKmTCorV7Bu+TVSpEh08OBBbgiDLEj4CNWuXZt27Nih1/uLFy9ODx8+pKZNm/L7K1asSK9evaL9+/eTq6ursRdXsFOM3WEtSpTI5Ol5hO/DK7BduwE8Ah8cnTo1o+HDu9PBgyc5I0ewHNLFWPDbF2R/sBdQAtS1awtq2LCazYqO+iBxlWCP51DEVEoX66VLN9K9e4+DfT0aHcBKAQ2j9uxRx2OCZZAuxoLu/mDitveCWXB2js5l1T17thbRUTAJRjGdO3r0qOZ+8uTJ6dixY6GeV8mSJXkSBGsUFuArhEzGb9++0/fvP/ggHRQvX77hMiKkrMuokeUQoUnwt0fIChGsfn+QuEqwJkylK6RLl0pz/8yZS5QhQ+ogX4umYBs27KKjR8/Q+PH9TLNAgl6I0CTo7g+yPgRbAuXg5i4Jt4USdNMjBeeCYAADBnTk2ytX9gQrOl64cJ3atOlH9etXoenTh3PGiiAI1oFcNAmCIBh01DTJ6lLKpZG53LRp7WBFx0aNunBjsA0bZlOmTOlNsjyCIIQGUR4FQQgZabMrCAaALEelLKh9+yaBChp163YgFxdnGjasB+XJk1XWryAIgiAIQiAxE5g2bbFOl3pt0PH6/v3HXGrdrVsLWYeCIAhCGJDmMpZCMh4FwQCGDvXg22XLNgb6/Js377ijtYODI+XKlVnWrSAIgiAIQiCgM73CixevAzzv6+tLhw//xw0PWrasJ+tQEARBEGwUER4FwQC2b1/Etx8/etPOnYd0nkOzmQYNOtPs2aNo4cLx5OgoPy9BEARBEITAKFAgJzk4qL2vOnceGuB5D49F7JF969ZBSpFCOqwKgiAIgq0iyoggGECECE5Uu3ZFvt+z5yi6c+eBzmg9prFjZ4uHnCAIgiAIQghs2TKfb2/c8KRatdrqPDd//mravfsIffjgLetREARBCDMOFvoniPAoCKHqbK2wcuUWznycO3cltW07gOLGjU1fvnyl27fvy5oVBCtFybARBEEQ9Dpqmmw1ubqm0dx/8OAJZzmeOHGOmjXrTnHixOJpwYI1spkEwWqRmEoQhJCR5jKCYCC5cmXR3N+wYRdPadKkoG/fvlOlSiXoxYs3dPPmXem6KAiCIAiCEAywpcmePSNdvXqbXFxi8EAuiBIlMuXLl53y5MlGZ85cZjsbJycnWZeCIAhCGBGx3BJIqbUgGEjq1MnJ0/MIbdgwR/NYqVKFOCiG9+OECQM4E9LDYyFdvXqLzdEFQRAEQRCEgKxfP5uuXt1Lr1+/47/LlSvK1SW3bt2jmjUrUMaM6ahjxyG0f/9x8vH5LqtQEARBEGwMER4FIZRky+ZGLVqouywuXLiW3r79QDt3HqbVq7fSmDF9KEGCuDR9+lIqVqwuDR8+lf78+SvrWhAEQRAEwR/IcNy5czHf37//BJ06dYHevftIRYvWoVq1KlC1amXo9OlLVKpUA2rduh/dvftI1qEgCIIg2AhSai0IYaB06SKUNGkiunz5Jn3+/JX9idBw5uLF6+Tt/YW+fvWhMmWKUN682cjJSXR+QbAGVCqVpRdBEATBhjDPMTN+/LjUu3dbjp/glf3u3Qf2eJw2bTF9+vSZPnz4xOXXyIaMFy+2WZZJEISQkJhKsCVwPW7ua3LRAIAIj4IQBvLkycpTkyY1ZT0KgiAIgiCEklixYlKrVg1k/QmCIAiCnSHCoyAIgiAIgiAIgiAIgmDnjWXM3VxGmtkAyfsUBEEQBEEQBEEQBEEQBMHoSMajIAiCIAiCIAiCIAiCYLc4kCNP5v5MQTIeBUEQhHCGg4OUPAiCIBhw1JSVJQiCHB8EQQg1Ir8KgiAIgiAIgiAIgiAIgmB0pNRasDuQzOToKKPzgvb+IGMsgrI/OEjGo6B9xpC1IQghIDGVIPuDIMcHwT6Q5jKWQq7GBUEQBEEQBEEQBEEQBEEwOpLxKNglKpWll0AQBGtFJQcIQRAEA46ZsrIEQZDjg2AnpXDm9noXb3lGMh4FQRAEQRAEQRAEQRAEQTA6IjwKgiAIgiAIgiAIgiAIgmB0pNRaECyMr68vPXrkRZcv36QDB07Q0aNn+PHTp7dSnDgull48QRAEQRAEm+HDh08cU50/f5WWL99Ef//6kofHYKpUqZSlF00QBEGweN6duXPvJNcPiPAo2CW2YKXw4METmjlzGd26dY8+f/5KWbK40vHjZ6l27YoUIYITqVS+ll5EQbDbztaCIAiCvsdM619TPj7facmS9bR371H6+vUbxYgRnby8XlLWrG6UIUNqihHD2dKLKAh2iS0cHwRBsDwiPAqCGbl9+z5nOK5evY3OnLlM6dOnosePn1HSpAlZbJw2bRhVqFBctokgWJDXr9/yb7VQoTwUKVLEIF/38+cv/j1HjRrFrMsnCIIgEL19+4GP11ev3qKlSzdS6tTJ6eXLt/T1qw/lyVOGcuTIRCNG9JTBJkGwIIiVcM3j5paGEiaMH+xrP336TLFixTTbsgnhD4d//8z9mYIIj4Jgti66Dx8+pXbtBlDGjOkpbtxY9Pz5Kw6GITg+f/6aJk0aRLlyZZEtIlhVBomv719ydo4ebi7c7t17RO3aDaSCBXPRhAnzqF69Kpwto3Dq1AX+7ZYqVYjvnzt3lUqXLkyDBnXW+zN+/PhJL168JheXGBQ3bmwTfRNBEAT75eNHb5oyZQEPEhUsmJvev//EU/z4cVh4fPXqDa1cOc3SiykIGv78+UufP3/hc7+Tk1O4WTONGnWhzJnT0+TJ83kwoGzZoprvj1gINlO5c2ejBAni0Nixs8nNLS2NHNmTUqRIqtf8//79y4MQiFnTpk1h4m8jCEJokYxHQTAxO3YcpNmzV1Dy5ImpU6dmVLduZRYi69evSps376GrV2/TunUzKVKkSLItBIuBoG3btv2cgfv4sRe9e/eRokWLysI4ytYcHR0oV66sVLZsESpQIBdFjGidpw/8thDI3rnzgH2+UqZMSmnSpGCBT1s8xetw4YqReJTgRY8elb59+0GHDp2i/Plz0KhRvfj5DRt20eHDpzTvy5AhDZUrV5QOH/6Pfv36Tfv2raDy5f9HT58+p8yZM/AE24SECePpfB4uOMaPn0MnT56nyJEjUZIkCfk95coV42NCokTxQxR3f//+w7dY95ifj883iho1Mp08eYGePn1BJUoUoFSpkmm+3549R2jr1v3048cv+vXrF39X3KpU6ueRVYDjUvLkSfg2WTL1LS7cHR3Fj0YQBOvj1au31LXrMD4eFi6chxYvnkhx4sSiFi3q0fbtB/iYvXLlVMqbN7ulF1UI52zZspdjkSdPntOzZy/5sZgxY7D4CN9RnG8hwpUuXcSqPd2/fPlKnp4POYECsRRiKsQNiA/9D6oidnR2jsYD1k5OjnThwjV68+Y9bdo0lwXC/ftP0LFjai974OzsTF27tqArV27Rnj1HadmyybRlyz7q2HEI5c2bjTJlSk9ZsmSgtGlTBYg7jx07SxMmzOH7CRLE43WKmKhjx2YsXgZXsQIQByEuihIlMt9HtiVE4bt3H3GshngOxxHlez548JTmzl1Jb9++5/hPianwuXg/YrtkyRL/i6f8YitUtck1niAQOajwS7FxPn/GgcKFvL3v8AFdCN/gxPbs2WtKmTKJxZYBJyOcROfPX0W3bz+gOXNGUfbsmQJ97fjxcyl16mScWSUYHwRCHz58piRJgi/vCK9i48iR01h4Q7kwvLE8PIZwuZp/oQ5B1tmzl2nUqBlUu3YlcnevE2JQZy4gjL58+ZqePXvFWcUI8sqXL87fAeIegmUEwwgoUebz+vV7Pm/Eju3CQSo8Vr99+87fF9mLDRtWZyFQX1BuDeHv5s27dOPGXb59/fodB5wYfb9//zFnNSOLcsiQrpr1ioB11aqtHDzjYhoXz+nTp+b1j5dgnSsTPGHv3XvMgXyUKJFYTMT6x3Lj4huCIxpTQSwtXjw/Xbx4nYPeVq0a8PdG0IugGIE7REW18PqZL4aePXvBXmjq6QXvF/gciKOKIIllQKZnvnzZ+bHRo2dycH758m6yZR4/fk6pU+cjb29vihlTyrsUJK4StHn48BmlSaMe1LAU167dprNnr9CyZZuoSpVS1K9fh0BfhwzIMWNm0ooVU82+jOEFa9gfrBGcVz08FvK51NU1DS1evJ4TDooVy09JkybSEc7wWpzX589fzcLkvHljrabEGKI+YpgXL17R//7XnR+D/3zatCk5lnr06CnHDohlEGf8/PmHXrx4yQIe4i7EJRArf/36Q5kypaMGDarxgK4hfPjgTbduqeMpTFhX0aNHYyESmY14LF68ODR6dC9eBoXTpy/RmjXbuGknYh0sM6pWIIRqi4XIjr506Tr/jfng81xcnDn+gQ0W4ijEc5cu3aRcuTJzjIzruh49WnGchngKMRhiK0WYxPUG4iTEUdoxFR7DOo0XL7ZGkMRnPXzoxbFmkSJ5OX6bOnURHTu23qD409pQZ/S6WWVMpcQ1Hz6doZgxzev5i+uMOLEKWOV6MSciPAp2KTx6eb2mVKksJzzihFuu3P84S2z37mV84R+UYNGwYWf2IEKQIhgfER7VILhCGfF//11ksQsiF4KyGzc8OZhr164JB3mjR/fh7L/gRvARIEHMw/sx2OMXgEXU3FeLXH73/T+PYC1rVle9S2kCA4Hi8OEeHNghmINQhvk3blyTEiSIG+D13t5f6NGjZxzcp0oV+s/VB1xUYLnu33/CgW+KFElCzGh8//4ji3kImPFafBdlfUHsc3VNyyWEjo5OQW4jjNhDyIR4mS2bW6iXH0EyxFwlcEZZFNYvgnpke+IiYNy4vlSjRnmbLsMX4TFwRHgUtHnw4BmlTWtZoal///G0e/cRGj68Ox93gmLp0g08ANO9eyuzLl94QoRHdfwOQQkZjRCMkMaTOHECzpQDI0b0YKGqYsWSVKxYviDXJd6/evVWvv3yxYdjM+04KfAYSvd55fH48eNSgQI5wxQn7tp1mGbNWs4xBM75WJ6cOTNR8eIFArweAh5ihI8fv1Lu3JlMHgsgvkFDTgicqCwJafAb8T9ilbt3H3JFi/b6g/CXI0dmihgxIh8vIAoGtvyoLkHWJrIcsS39Z3kaEhMixlNiKsSjGDDG4DiqVhBX5c6dlTO48f1sFREeg1ovIjwCER4Fu8MahEeAi38EExjFDAqUQWLEDcKjYBrCm/CI4AYjtghiMXl63udMOQTFGMVF+UmtWhW4jBoBj6+vih8LTWkt1i2EMPUIsjozT7n/+7dS2uuXtaeMNCv3UQq8ePEkLktWlj24wBViGMpczp9H6c47FhBRptSyZX29lxmB/ffvP9lLSAgd2H7wZEKGLETSokXzc3m2AjZh7NixqGjRvJwVAbEXt4UK5aacOTNblVApwmPgiPAoWJvwiAHdBg066Zwz/AMBoXHjrrR+/Wwu9xRMQ3gTHpHBh4FbJa7ChH0NWYyIn0qWLMjnthcv3nCmYMaM6YIdwA3u+gWClDpm0o2h/O77xVH+nztx4hw1bFiNqlYtw/NTihqDO+ceOXKaNm7cTU+ePOM4EAOcAwd2Mij70hqOD7bOtWt3aOfOQ7wNsf+gzFvZbrjBtoG3OLY1LJEQeyG7tHLlUiymWgu2ITyes1DGYz6rXC/mxDpNugTBRli1agtduHCd/UsQeLi71+XRMAQPCJKDaxyBQGbBgtW0bNkUsy6zYP0goL1z5z6X6aNsDKO137//4AC3RImCXAKi7FsYdUdwAhGwb99x7MMTP35sfi0CSHf3eiw4BjaC6uaWLkzLiXmGZWQ2W7aM1LRpd035EYRFeDK2bNmAS3qVoAvf/ebNe/x7wfeaOLE/+/lYk4AVnkDWAIJdTChzP3XqPAdV2mD/Xbt2O29PZE4kS5aIFi1ax1kDyJxAhiou2pInT8RZGuIpKQgCyqnXrt3B1hOwwujTpy3bY0BAwfkBA2XI0A+KmTOXUfPmdUV0FHSAUIfqA2TLKbHVu3cfeB/D+ahkyQIcLykxBeIqnJNWrNhM69fv5Ix/lNci/ihTpgiXTwcW36s9kxOHeu3jc5BhGFoaNapObdv25wFaBXwP2MdgwFmJ1/D9IFwdOvQfe1gPH96DfRut1bs7PIAKFUy+vu3p8uWbXFXk/5qxT5+xvN8hUxITtmH16q2oaNF8vP0QZyGuwmRNYqQgKEjGo2B3mCLjUTvVHgIj/NqGDJnMB/0uXZpz1hUCFBgjI7MnXbqUFDduHBozpg+fCAID5QxnzlyikSN7GW05BT9wkYIyYpSGJk2amHLnzsLm3cj08492ph0CMpRm4G+8Fhc5uFUCspcv33BJBEYlEYiiEznKJ9DIBCf6/Plz8nuvX7/DWRnwckG5SmAlIfhc+BKqA+H7dOvWfR51xkgcREF442DkE5+DgBFBM0anYcyNABWfCW+g5cs9uHwaRtxNmtS0aUEO28vdvSdVqlSS1zt8fLCe4OuDC4QKFYqHaf6S8WhZUGZ0+fIN3u9RpobjJTJ0sctiP4d/UljK7w1FMh4DRzIeBVNnNOE8i+M7MntSpkxGPXuOpDt3HlKyZAlp1Kje/Bz88iAY4UIapZDI5qpZs0KQ5/wSJerR0aPrRUAxoX0IfDafPn1FzZqpYw0IZf5jDv+ZdsgCxIAqsgBxXseEmAbPQ1CBBQxiGwzYV6tWlgcbEVfByw9dkGFXcv781X+2I0nYugSefYGBjEFkJCKmun37Hg/G4rogXbpUlDFjesqYMS3HVfD1Q9IA4il8NuJ5xO5ofgKBsUOH/9HKlVtpwYJxNl36ivVYsmQDjm2bNavDmXX43hgQzJ4dg7+1Q5WdqY1kPFoO/Fbw+0FshXgKcRUaLCIzEr9N+LHjGtVc1wW2kfF43kIZj3mtcr2YExEeBbvDFM1lEADXqtVW8zeydcaP708RIzpRqlTJNR6OyutOnNgYqMecNgio6tVrT0uWTA7xtYIaBK7oKvf792/ezurJl28hDuMWJ1w0QYE4DA8YmEKvWrWdswBxQoTPS7RoUShJkkQcHEPoUzrSobQEQSsugrBtERBjO+EW88drcCKH+AyzcAgoEP4wAhk3biwWtSCcIcBD2Q0EFSUQwPuR2YWAGc1BEAzjeVxQIQhWJmSIQVQMCQSO69btYCEU88qXLwf17dvO5ncVnJynTVvM6wHrI1OmDGEOirXBNkJjFuwPgvWA3wcGYiZMmEs5c2bh0m2USkL4x4SLTKVTJn6nxjpmivAYOCI8CqYsrcW51M2tlOZvxFBosIcGFopIBNRCVCuqWrU09ejROsT5jhgxjUUjadanHyjPRUUFMte14yklpvL1RfWODzcru37dkz0M0eXX0/MRPX3qRVGjRuUBUDQjw0Arjs04pvr4fOP5YzA2QoQILATjveqY6hvf4jwM8F4M2KKMFK87ePAkubjE5JgK70dzD4jUefJkw57DAguaucHmBecDZBjis/E4xEPEC4gdMHiLW/inBzbg7B8INcrALmIzzH/27NFW3W1aX5YsWc8WM6h+yZrVjdeXMYWo8FZ6bwvgGIvroYkT5/FvGNdDSgylxFbaf+OaKLT+ldqI8BjUehHhEYjwKNgdxhYeEcyUKdNI5zEITQcOrAqzIIIMyUOHTtGkSQPDuJT2edJUd829wQbdEHUx6pwhQxoORiHO4SSJMhLc4m9MECQgwinNPALzeISYiG59eF4tMkbgz4PoiM51pihRgBiJYBb70/fv37msB+KKLWcn2iIiPFo3uPg7d+4KbydcoOLiDxfFyi0eUy4KIf6jCznKk/78+cMm8Yb+nkR4DBwRHgVTCQs418KHEWKWNrNmjeQy1rCAczga9q1aNY3LaAVdUF6M9Y6YCuWcEHYRiyD7RzuO0r6PmAhZhxCslMoN//uD0gX50ydvHjSMEcNZczxHRpapujVj+ZE9j9J8CJBIBDCGeCIYhgiP1g2qv5Ck4BdP+Y+tfDgWQiyFmApdtqNGjczWFoaW34vwGNR6EeERiJmDYHXgAIgD5MuXb+nVqzc8mholShQW+TBCkyZNch0vlsD4V+VhFBBowRsFB19klqFRB0QtYwQ3KBuFfwwutCGWCX7i8dixs7jECifAOnUq07Bh3UNd7qKU/ShgX0JZpzbYn0wVHAMIpBhlDsoUXzAP2BX87w+C9QDRH35F+gRxx4+fpeXLN7EFATJdypcvTlOmDJYLT0HQQhGFEE8hAwb3cb5TZxNH5YFUZJMFN+Bm7GNmnjxZKWtWV65gQFkslkcRq8ICMifRbAwl2tK0T3f7IaN8xIjpnFmI7rktWtTXaQpmCP53B8THsBXyby2EfcqUXnPYZ5RqEcFySExl3SDbEVNI110YjIDv56xZy/g6HAPAe/eqO5zbEw7kyJO5P1MQ4VGwElAeAw9FBMgIhhMnjk+JEiXg0gzc/vz5kw+AGNXcseMgl6+i3BXBE0oyEHy4uDhTzJgx+GCJjtLv3qUnN7c0QfrABAVGZydNms/vU4x627Vrwhe5KPXF87jo7d59BI0f3y9MwTKC7UGDulCvXqNo06a54aLBAsp30E0ZFz+Y0J1Yuf/69VvezlgPhQvnocWLJ4Z5nYjQJPjbI2SF2AHI0KlSpTRP27cfoN69x3C5EGwYDBsUkv1BsD/QdX7+/NV8PkUmMAa8lLgqUSJ19j+yh58//8wN8kaNmsFei4irUDWgjqlicEyFMd6zZ6/S06fPuGwVcZmhmcUYYMWgLeIpxFUVK5akT58+c4Zi0qQJ6dOnLywWdu7szuf+sFCzZnnu0ossn5Autu0FWK+oReW3WvGUevrw4SNnLsHTEDEVtl9YEaFJ0N0fZH3YOshuxgAUppYt61HZsk04AxLHaEEwFpLxGI6B4bBiDG1p0Iijf/8OlDdvDr0uGpEViQYfMNSFCOg3feEL0hw5stKmTbu5VBdCIbp/IWBWOv0iY1Fb0ELHO3RSRBcxZDVeunRDJ4hFgIygDn44KN9B4Obp+YCWL99MHTs2DdN3R8kvRovtveQWgSrKytF1Ehc+mNCtEhdEuOBRsgEh+Nr7uhAsi1w02ddABgSW06e3WMW5TAi/ID5AViE8oC09iIgBWDSO6NKlhV4m+rACgZfeyZPnuXkIYiklrkJ8lDdvTnr69CktW7aRq1HgkavEU5jgHYeSXG3QDGTLln3sbazdZRdiIGIweB9j/siIQyULMm5GjpxOe/YsC1MMALEVHoKW3gbmAIO4U6Ys5HJjbIMECdRxFDymlfgKXon6+EYLQugR5dGeWLZsE/Xr157q169K9gnOL+a+zpTrWiDCYzgFfnnIEEFAClENQSCCSHTfhX8WRkkRqMSIEZ1fAzEItxgFVx7DLf6GsIcuaShJxkg5gh08Z0jgiE5r7u5+3Z09PY8E+3osDzrfYQrsQtTL6xWlTp1U8zcaiKCc58aNu7Rp0x42plZ3Dk7LGQC7dx+m0qWLsLcFgmAEc3gfuucNHtxV4+UIwQLrCwEzJgTUYeH+/cc0btxsWrx4kl2IbbhAQQAMH0MEIjlyZOasCfgJTZo0j9f1zJkjg+z0LQiCEJQwgmPy27fvadCgSWzBgQx5PI4O6CI6CpYEcVCnToPp168/7KOH8x4EuQwZUnFTBwiBeI1uPKWOofxiK/VjiKVu3rxH3t6fWUhCXIWOzoaIR7AdKFasLq1YsYX/3rlzcQB7EW0g0qH8GVNg3L//lNKlS6GJgxAnYvAVcRXESMQy+C2mSZOCvzdK9hwdHahJk5psg4CBX8QGyEru1as1FSyYW2fdvXjxhmMqeASGJRbCMaFbt+HUqlUDypQpPdk6am/o9xxTvXv3kWNWeCii+mb27BXs19itWwv2u7WHGFIQBPMOluFabeLE+Zxwg2MxwHmoc2cP2RSC0ZHmMnYAAhN08EXgB6NlmDljQlMNTMp99ePqx/Da6dNHUNq0Kfj9CGru3LnPwTHENIiHKpUvj0Zj9BjzxX1kGqofUz+O+8jWw8g6RqtR7oEJj4MsWTJQy5YNOOjUPtChEQBGx7UDJXh1jR49Uy/hMTj8C49BgcAN2Y0QJUuVKhxqr5vQggvnZs16cHdsewiQQa1abbj0HRc46IZ4+fItNi9OkiQB9erVhjMbzQ0u+t6//0TJkiU0+2cL1geOTdgnEiaUTvK2AEQOlGgiY2rfvmPcXArlmEWK5KFIkcLuHfb48TNKnTo/eXt7U8yYpvN4tTXCe3MZlJeh2y/iGb8YCvGT333t2Apdd+vVq0yNG9fUxBcQ5e7de8QddVElgVvteEo3tsKt+m/ME551ENPVMdU7rlBBx2FkrzVqVJ2FRUWIxG8EZdOYv3aWHyo4KlZsxvc3b54XpvOvtvAY3MCj2rPxPqVIkZStcMwJ1sPQoVM4hsUxwh5YvHg9rV27nT3A0V351q37HK+jEzS8LGvUKGeRbMb7970oXTr78n0TyKTHB8F6wOAYLMkGDJjAiUclSxbiAQz/1+WhwRaay3z8dEmvSgDjfvZXih0rl1WuF3MiGY9WOLIJ4QxNNCJHxhRJp6MUsu0QDKOEGLcQztQeOYm4zAIXCOr3RuKSYOU+JmWeuEWZq/KjQ6CKEVRMxv4+J09eoFGjprNvY8GCuejMmcv08KEXRY8ehS/+Ab5frFguHHArIGg3dUdCzL9AgZw8WYJVq7byhceuXYe5jBtdA+HBY4tgn3306CkH/OhKWbduZZ2LkdB0mxUEIXwD70ZceON8AHNzZLiPGdNHjiWCQcE+YiTtOAgZhcr5COcntcXKI01s5eWlroiAyI1YSXkfMhXjxIlNUaLoxlN4Hq9HHKYdXyDmwWRMsGyLFq2jOXNWsQ3MkyfPuaQZywHBEuIbMg0RC2pfWEEENfXAHwYCLNnoA+IvSrvh+7phwy6OqdKmTWmzJdcQnWE9hESAUaP8KoIwyB+abrOCIIRvkHQ0Y8ZSOnHiPGdPK4Ij7oc/5JrUEkjGowVB2cmaNds40H358jUHEiipiRAhgiYzESPpEHUAAkqkPyMYRgYhbjNkSG1ygc4YIIX76tVbXF6DZdcWoRD4f/z4mUVVTGH9TvpmPFpLYHnlyk0uS8IE8TVTpgzsz4MJmYPG6J5tSpClCuP4/PlzULZsGbnsEeVW1oJkPAraSMajbQCxKF++agEeR7bX0KHdjPY5kvFoPxmPiJc2b95LZ89eZjsVpbQZZc9KJQgmxBxKMwRkjqVOnYLjDlx84dYaPBpDAqXOO3cepLRpU1G+fNlZeNQWpnCcU2IqlDcHV2ZtTxlN2OZoKqPEVBjoTp48MYuQuXJl4WYJhjYcNDfwLu/dezT/7ooWzcexFWyArAnJeBRs8fgQ3ilVqgFXSPonLFWGtpvxaN64BusltmQ8SsajpUYcYIaP22bN6lKDBlUpceKEVi8whQUEfJiCGiVXGouENyA0lytXjCeACyKU0ly+fIPmzFnJGRhqo/AslDNnJsqePRPFihXT4mX9KB9TT485uEemo7t7XSpUyM+3SRCsFcm+tX5wfqxduyJnOApCcMACZvXq7bRly14+l7Zr15iSJ0+q8Wa2R2AN07x5vUCfQ+ktBm+NOyhtG9khKBXMmzc7T8qAPURoxCn79h2niRPn8eNZs7pRrlyZ2Yca1T6WPCdAHMbxDkkIiKtu377PA+jFi+enfv06WGy5BMHejg/hHWTp3759yOoH1kwPvr+510F4X+dqJE/fCMAQG516UW6DkmL1FJVv4bmjPPb79y9auXIre/u1adOISpQoIBfAQgARFiPzmJo3VwfN8N1E0IzUeOxnPj7f1T/eCE4cMKMxT5482Yy+JvHZFy/eoOvXb/8LiB/zBR7KyZAVggyKQoXy0IgRPXg/FwRBMBY4T6KsFOdX7RJWsGrVFvLx+cGWHcr51e9cG1VzH7coqxVsC5x7pk5dTB8+fAywbbW3d7RoUejQof9o//7jVKtWBdqwYbbVZ7MJ5gWComIlBD9EAN9pxDXo4r1r1xE+xqhfS+xRXa1aGapZswLH9MYGn4WMRgiNiKkwkBsrVgxKly4Vx1RlyxalDh2acjMhGSATBMGYiSOw94IFWtGieXWOL7DrOH/+WqDahfoxv7gK2fVybBJCi10Jj/Pnr+EyXngdonTGFEGDduc8XBTBG2j16m0cLKC8FAbfyoRSMXj3qf/+zuUv7u5qkUh+tII+YD9Bp3FMlSuX0nkO2ZHofLlw4VqaNGk+d5JUvKeiRIny7772bWTNFDWqnz+VMuH3glEw+KnBJwlTunQpucynTp1KHBSb24xXEITwCbxiESh36DCIs5eqVi3NQTOOTzNmLKPOnZtxuSzsKnx8vDTnWUzfvn3XnIcVqxKlrNa/QOnoaL+VBsZg/fpd3DwOwogpbV0gNqJrL2IqXARBmEFGn3ZMhe364YO31mPfeZBuy5b5OqXGghAcKD2H7Y92Z22AGB0l7GvWbKcaNVqz3Q2OESHFTkqchWxLPKf9GgwQ4xh07NgZWrduB2c34tgG78+mTWtzbCfXA4IgmBpc3y1bNoWmT19MCxas5gQoXPcp13wxYjhT7txZWLtAwov2eVeJrfA3rOAQeym6JY5/2jGVPVdvCmHHrjwe16yZw0EDRhEfPfLizsm40EBjC5gwK7fwUNT+GxkR+KEE/rqIFCmS+j46C8IvBl2QsdqSJUvCXaFhpA1RSIIH68CWPB6NBbocvnr1hv0McVKAzxG8rHCr7sL5Q+MZqn7up9ZrFT9R9ckEJyKYs8O4Hl01bR3xeBS0gfcZfhMJEthmI6fweDzftm0/nT59SVM+ijLTGjXKG9xcAfP6/t0vgMbt48fPqXr1plbpR2QNcdXs2ePYjxpC4KdPX/7FVLpxEmIk7fgpsHhK9776Fhc0iNUgNuJ3ie2KQWPEVTgHxY0b29KrQQinnn7IivT0fBAgZkKsFHDSjrPUnc6V++pGML7sw1m/flWTN/gxF+FtfxCCR/YH2+Lmzbvc4BTnYnVcFZNKlixIKVIYdt0MLQTHR+0B39ev31GpUnWsMqZS4ppP3lct4vEYyyW7Va4Xc2JXwmNgJug46eNi4/fv35ylqJ5+69xCoPz1S/dxPOb/teg4jA55aD2PkljBOgmPwqMQNCI8CtpIcxlBG2kuY1hchZBRiZsCi6eCi7NwXzvWwiAXKkUwoQGMYL1I8whBd38Q4VGQ44Ngm81lRHi0HHZVah2UyTYmU5ZdC4IgCIIg2Duo7ECViHhnCoIgCIJgezhYoCGSNGAC0mJHEARBEARBEARBEARBEASjI8KjIAiCIAiCIAiCIAiCIAhGx+5LrQVBEARBEARBEARBEITwnndn7tw7yfWTtSAIgiCES586QRAEQe+jpqwqQRDk+CAIQqiRjEdBEARBEARBEARBEATBjpHmMpZC8j4FuwPJTI6OMjovaO8PcqgTlP3BQTIeBe0zhqwNQQgBiakE2R8EOT4IghAWJONREARBEARBEARBEARBsFscyJEnc3+mIBmPgp2iUll6CQRBsFZUcoAQBEEw4JgpK0sQBDk+CII5mTVrFqVKlYqiRIlC+fPnp3Pnztn0BhD5VRAEQRAEQRAEQRAEQRAszLp166hHjx40dOhQunTpEmXPnp3Kly9Pb968oXAlPH758oW6detGKVOmpKhRo1KhQoXo/PnzOtkkQ4YMocSJE/PzZcqUoXv37unM4/Tp05QjRw5WcRctWqTz3LFjx6hUqVIUJ04cihYtGqVPn56aNWtGv379Cu33FARBEARBsEokrhIEQRAEQTBXcxlzT4YxZcoUat26NTVv3pwyZcpEc+fOZV1s8eLFFK6Ex1atWtGBAwdoxYoVdP36dSpXrhyLi8+fP+fnJ0yYQNOnT+cVdPbsWYoePTortD9+/NDMo2XLljR48GBavXo1jR07lry8vPjxW7duUYUKFShPnjx0/Phxnv+MGTMoUqRI9PfvX2N9b0EQBEEQBKtA4ipBEARBEATT8vnzF4tM4PPnzzrTz58/KTCQbHfx4kXW1xTQKBV/I3kv3DSX+f79O23atIm2bdtGxYoV48eGDRtGO3bsoDlz5tDIkSNp6tSpNGjQIKpevTo/v3z5ckqYMCFt3bqVGjRowI/5+PhQrly5KEGCBBQ7dmwe7Qf79++nRIkSsXipkDZtWhYjBcGQTsaCIAiBHx/kACFYDxJXCdaOHDIFQZDjg2DLIIkNGlPy5Hkt8vnOzs6UPHlyncdQRg0dzT/v3r3jhDvoZ9rg7zt37lC4ER7//PnDKwIml9qgpPrkyZP06NEjevXqlY5C6+LiwoaYUGgV4RGl2BkzZuT5tW/fnlNIAXaIly9fcrajImwKgiAIgiDYIxJXCYIgCIIgmA5oV9CpLGXdp1KpAiQ+RI4cmcITBguPMWLEoIIFC3JmI4RDKK9r1qxhUTFdunQsOoLAFFrlOaXUGiIkNj4yHhXq1q1L+/bto+LFi7MIWaBAASpdujQ1bdqUYsaMGbZvKwiCIAiCYEVIXCUIgiAIgmB68dF/8pw1Ei9ePHJycqLXr1/rPI6/oY+FG+ERwNuxRYsWlDRpUl4pKJlu2LAh16IbArwfMWmD+S1ZsoRGjRpFhw8fZo/IMWPG0Pjx47mFOBrWBKYgg+vX75Kzs+78/OPrS2EGYrUxyk5kWUyzXnx9fen9e2/69Olz2GYk28gu1svv37/pyxcfev36vcWXRR9kWUy7Xnx8ftCvX7/JxSVGqOch28h+1surV+904ghLYa1x1dWrfnGVMbYvZmuMVS3LYt718vr1O/L2/mrQfGQb2e96efXqPX358tUqlkUbWRbLrBft/SEkZBvZ93r5+tXHKmIqeygLz507Nx06dIhq1Kih0Tfwd6dOnchmUYWBr1+/ql68eMH369Wrp6pUqZLqwYMH2NNUly9f1nltsWLFVF26dAnV53z48EEVL1481ZAhQwJ93svLiz9TJlkHsg/IPiD7gOwDsg/IPmDoPoA4whqQuEr2XTl+yT4g+4DsA7IPyD5gy/uAtcRUtszatWtVkSNHVi1dulR169YtVZs2bVSxYsVSvXr1SmWrhCrj0f/I+sePH7k8Gg1hUqdOzSmgUGRz5MjBr0PXHoyww8sxNKAUGyPyaEgTGEmSJOGu2ChXkqYBgiAIgiDoA0bl0dwOcYQ1IHGVIAiCIAi2iLXFVLZM/fr16e3bt9wXBXaF0NX27t0bwM7QlnCA+mjomyAy4m2urq50//596t27N9fLnzhxgiJGjMjlO+PGjaNly5axEDl48GC6du0a3bp1K8S6+nnz5tGVK1eoZs2a3M36x48f3BV70qRJXCIE70dBEARBEAR7QeIqQRAEQRAEwV4JVcajt7c39e/fn549e0Zx4sSh2rVr0+jRo1l0BH369OHsxDZt2tCnT5+oSJEirNDqY+aZL18+7o7drl07evHiBbcez5w5M23dulVER0EQBEEQ7A6JqwRBEARBEAR7JVQZj4IgCIIgCIIgCIIgCIIgCMHhKKtHEARBEARBEARBEARBEARjI8KjIAiCIAiCIAiCIAiCIAj2LzzOmDGDu/U4OTlxh2p4SWqDrj7ZsmXTPB85cmRq1KiRzmvgK5k1a1ZydHTk1yRNmpRu3Lih85qBAwdSpEiReEK3IMF6QDesbt26UcqUKSlq1KhUqFAhOn/+vOZ5uANgm6HTOZ4vU6YM3bt3T2cep0+f5u5PqVKlokWLFmkeL1CgAPuHajN37lzeT5YuXarzuLu7OxUtWtRk31MwHbNmzeJtD1/Z/Pnz07lz5zTPeXp6UuHChSlZsmQ0atQo2Qw2jCmPFQDHhcCmtWvXmu07CiEjcYOsGyF4JK4SwoLEVOEDiakEBYmrBJOgsjKGDx+uKly4sKpPnz7wnlT169dP53k3NzdVhAgRVB4eHqoTJ06oGjduzK8bMGCA5jWZMmVSOTk5qSZNmqRasWKFytnZWRUjRgzN897e3vz8+PHjVWPHjuX7X758Mev3FIKmXr16vA2PHTumunfvnmro0KGqmDFjqp49e8bPjxs3TuXi4qLaunWr6urVq6pq1aqpUqdOrfr+/btmHhkzZlRt3LhRderUKVXatGlVT58+5cexP7m6ugb4vOTJk6uaNWum83jKlClVQ4YMkU1lY6xdu1YVKVIk1eLFi1U3b95UtW7dWhUrVizV69ev+fkyZcqoZs+erbpw4YIqT548vI8ItokpjxUA55YlS5aoXr58qTNpv1+wPBI3yLoRgkfiKiG0SEwVfpCYSlCQuEowBVYnPGoTmPAYOXJkValSpXQeixo1KouV4MmTJ/y+Hj16aJ7ftWsXP7ZgwQL+28vLi8XGO3fu8AQh8/nz52b5TkLwfPv2jbfNzp07dR7PlSuXauDAgSpfX19VokSJVBMnTtQ89+nTJ94v1qxZo3ksRYoUqocPH6q+fv3K4hIEKLBv3z7eFyAeKCRMmFA1a9YsFhoV8F687siRI7LJbIx8+fKpOnbsqPn779+/qiRJkvAgA8idO7fq7Nmzql+/frEQheODYHuY+lgBcAzYsmWLmb6RYAwkbpB1I+gicZUQFiSmCh9ITCUEhcRVgrGwulLrkEidOjWdOXOGLly4QL6+vjRlyhT6/v071a9fn5/fsGED33bp0kXznkqVKnFp9s6dO/lvlFiihNbNzY2nsmXLUpIkSSz0jQRt/vz5Q3///uUSWW1QJnny5El69OgRl9ujZFLBxcWFy2lRMqmA8sqMGTPycyivzpQpEz+OEtuIESPSkSNH+O9bt27x/tOyZUt6//49zx/geSxDwYIFZQPZEL9+/aKLFy/q7B+wXMDfyv4xYsQI/jtatGj8XPny5S24xIK1HisE+0HiBlk34RmJq4TQIjFV+EFiKsEQJK4SQkMEsjHOnj1LOXPmpLx582oea926NXXu3JnvP3z4kG/h+aUNLk5fvnyp+RvC0tOnTylChAgiOloRMWLEYLFv5MiRLAbA73PNmjUsFKRLl46FBIDHtcHfynMAQmKDBg04aIodO7bm8ejRo1O+fPno6NGj1LBhQ74tUqQIe4XCHw5/42CKWywHHhdsh3fv3rEYFdj+cefOHc1AxNu3b+nz588UP358Cy2pYO3HCgUcJzBwpQ0GLFKkSCEb0UaQuEHWTXhG4iohtEhMFX6QmEowBImrhNBgcxmPaCTj5eVFgwYN4uzGOnXq0IIFC2jChAkGzwsXjpLpaH2sWLGCm0KgKRCEv+nTp/PFP7LTDAEiY2BCQokSJVhYBLjF36B48eI6j5csWdIo30ewPrBfieho+5j6WAE8PDzoypUrOpOcN2wLiRtk3YR3JK4STInEVPaBxFSCvkhcJdi98PjhwwfatWsXDRgwgLNcIDpCfMyQIYNGeEyTJg3fPnnyROe9P3784M6mgvWTNm1aOnbsGH39+pVFZnQk/v37N2/bRIkS8Wtev36t8x78rTwXEhAU7969S8+fP2eBEYKjtvD44MED/txSpUqZ4NsJpiRevHicnRaW/UOwHUx9rAB4LTIotSdkygu2gcQNsm4EiauE0CExVfhCYipBHySuEsKF8Pjt2ze+9Z/Ngr/V3qdEdevW5duZM2dqnt+zZw+XX1apUsWsyyuEDWQhQSz++PEj7du3j6pXr85l0BACDh06pHkdSmaR8q2vHyNKqiNFikSzZ89mQTp37tz8OMr3UYK7ePFiTUm2YFtgu2J7au8f8ILF3+LXab+Y6lgh2D4SN8i6EfyQuEowBImpwicSUwnBIXGVEFqsLm0D3lvIYFG4ffs2rVu3jsuicbGIBgBjxoyhmDFjUq5cuWj58uXs3QaPLoDXoTkAyuNwIZogQQJq3749OTs7U6tWrSz4zQR9gXAAIdnV1ZXu379PvXv35iZAzZs3JwcHB+rWrRuNGjWK0qdPz+LC4MGDufSxRo0aes0fzSfQRGLGjBncbEbxb0OApf04mtAItkePHj2oWbNmlCdPHhaPp06dSj4+Prz/CPaFqY8V4NOnTzqekIoXEgJzwTqQuEHWjRA8ElcJoUViqvCDxFSCgsRVgklQWRkeHh7ctt3/lDZtWn7+6tWrqnTp0qkcHR358UiRIqmqVaum+vv3r2YeHz9+VGXJkkXl4ODAr0mcODG/T7AN1q1bp0qTJg1v20SJEqk6duyo+vTpk+Z5X19f1eDBg1UJEyZURY4cWVW6dGmVp6enQZ8xdOhQ3jfGjRun8/iwYcP48bFjxxrt+wjmZ8aMGaoUKVLwPpQvXz7VmTNnZDPYIaY+VgR2LpLjg/UhcYOsGyF4JK4SwoLEVOEDiakEBYmrBFPggP9MI2kKgiAIgiAIgiAIgiAIghBesSmPR0EQBEEQBEEQBEEQBEEQbAMRHgVBEARBEARBEARBEARBMDoiPAqCIAiCIAiCIAiCIAiCYHREeBQEQRAEQRAEQRAEQRAEweiI8CgIgiAIgiAIgiAIgiAIgtER4VEQBEEQBEEQBEEQBEEQBKMjwqMgCIIgCIIgCIIgCIIgCEZHhEdBEARBEARBEARBEARBEIyOCI+CIAiCIAiCIAiCIAiCIBgdER4FQRAEQRAEQRAEQRAEQTA6IjwKgiAIgiAIgiAIgiAIgkDG5v/K6fR9BLmrtQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1300x760 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(2, 2, figsize=(13, 7.6), constrained_layout=True)\n",
+    "lon_wrapped = ((ds[\"lon\"].values + 180.0) % 360.0) - 180.0\n",
+    "lon_order = np.argsort(lon_wrapped)\n",
+    "lon_grid, lat_grid = np.meshgrid(lon_wrapped[lon_order], ds[\"lat\"].values)\n",
+    "\n",
+    "for axis, landuse_index, landuse_name in zip(axes.ravel(), range(len(landuse)), landuse):\n",
+    "    map_plot = Basemap(\n",
+    "        projection=\"cyl\",\n",
+    "        llcrnrlon=-180,\n",
+    "        urcrnrlon=180,\n",
+    "        llcrnrlat=-90,\n",
+    "        urcrnrlat=90,\n",
+    "        resolution=\"c\",\n",
+    "        ax=axis,\n",
+    "    )\n",
+    "    map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "    x, y = map_plot(lon_grid, lat_grid)\n",
+    "    field = ds[\"fracLut\"].isel(time=0, landuse=landuse_index).values[:, lon_order]\n",
+    "    mesh = map_plot.pcolormesh(x, y, field, shading=\"auto\", cmap=\"YlGn\", vmin=0, vmax=100)\n",
+    "    map_plot.drawcoastlines(linewidth=0.6, color=\"0.15\")\n",
+    "    map_plot.drawparallels(np.arange(-90, 91, 45), labels=[1, 0, 0, 0], linewidth=0.35, color=\"0.45\", dashes=[1, 1])\n",
+    "    map_plot.drawmeridians(np.arange(-180, 181, 90), labels=[0, 0, 0, 1], linewidth=0.35, color=\"0.45\", dashes=[1, 1])\n",
+    "    axis.set_title(landuse_name.replace(\"_\", \" \"))\n",
+    "\n",
+    "colorbar = fig.colorbar(mesh, ax=axes, location=\"right\", shrink=0.86, pad=0.02)\n",
+    "colorbar.set_label(\"%\")\n",
+    "time_label = month_year_label(ds[\"time\"])\n",
+    "fig.suptitle(f\"CMIP7 fracLut by land-use tile, {time_label}\")\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/07_non_lat_lon_sea_ice_concentration.ipynb b/notebooks/07_non_lat_lon_sea_ice_concentration.ipynb
new file mode 100644
index 00000000..61689acb
--- /dev/null
+++ b/notebooks/07_non_lat_lon_sea_ice_concentration.ipynb
@@ -0,0 +1,1874 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0",
+   "metadata": {},
+   "source": [
+    "# Sea Ice Concentration On Projected Grids\n",
+    "\n",
+    "Create CMIP7 monthly sea-ice area percentage files (`siconc_tavg-u-hxy-u`) using the Northern and Southern Hemisphere EASE2 Lambert azimuthal equal-area grids from the NetCDF files in `data/`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib is building the font cache; this may take a moment.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using CMIP7 tables from ../cmip7-cmor-tables/tables\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import calendar\n",
+    "import json\n",
+    "import os\n",
+    "import shutil\n",
+    "\n",
+    "os.environ.setdefault(\"MPLCONFIGDIR\", str((Path(\"output\") / \".matplotlib\").resolve()))\n",
+    "os.environ.setdefault(\"XDG_CACHE_HOME\", str((Path(\"output\") / \".cache\").resolve()))\n",
+    "Path(os.environ[\"MPLCONFIGDIR\"]).mkdir(parents=True, exist_ok=True)\n",
+    "Path(os.environ[\"XDG_CACHE_HOME\"]).mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "import cmor\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import numpy as np\n",
+    "import pyproj\n",
+    "import xarray as xr\n",
+    "\n",
+    "TABLES_DIR = \"../cmip7-cmor-tables/tables\"\n",
+    "CV_PATH = \"../cmip7-cmor-tables/tables-cvs/cmor-cvs.json\"\n",
+    "DATA_PATHS = {\n",
+    "    \"nh\": Path(\"data\") / \"ice_conc_nh_ease2-250_cdr-v3p1_202002.nc\",\n",
+    "    \"sh\": Path(\"data\") / \"ice_conc_sh_ease2-250_cdr-v3p1_202002.nc\",\n",
+    "}\n",
+    "if not Path(TABLES_DIR).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 tables directory not found: {TABLES_DIR}\")\n",
+    "if not Path(CV_PATH).exists():\n",
+    "    raise FileNotFoundError(f\"CMIP7 CV file not found: {CV_PATH}\")\n",
+    "for data_path in DATA_PATHS.values():\n",
+    "    if not data_path.exists():\n",
+    "        raise FileNotFoundError(f\"Source data file not found: {data_path}\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "def month_year_label(time_coord):\n",
+    "    decoded_time = xr.coding.times.decode_cf_datetime(\n",
+    "        time_coord.values[:1],\n",
+    "        time_coord.attrs[\"units\"],\n",
+    "        calendar=time_coord.attrs.get(\"calendar\", \"standard\"),\n",
+    "    )[0]\n",
+    "    if hasattr(decoded_time, \"strftime\"):\n",
+    "        return decoded_time.strftime(\"%B %Y\")\n",
+    "    date_text = np.datetime_as_string(decoded_time, unit=\"D\")\n",
+    "    year, month = date_text.split(\"-\")[:2]\n",
+    "    return f\"{calendar.month_name[int(month)]} {year}\"\n",
+    "\n",
+    "\n",
+    "print(f\"Using CMIP7 tables from {TABLES_DIR}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 5MB\n",
+       "Dimensions:                 (time: 1, yc: 432, xc: 432, nv: 2)\n",
+       "Coordinates:\n",
+       "  * time                    (time) float64 8B 1.329e+09\n",
+       "  * yc                      (yc) float64 3kB 5.388e+03 5.362e+03 ... -5.388e+03\n",
+       "  * xc                      (xc) float64 3kB -5.388e+03 -5.362e+03 ... 5.388e+03\n",
+       "    lat                     (yc, xc) float32 746kB 16.62 16.82 ... 16.82 16.62\n",
+       "    lon                     (yc, xc) float32 746kB -135.0 -135.1 ... 44.87 45.0\n",
+       "Dimensions without coordinates: nv\n",
+       "Data variables:\n",
+       "    Lambert_Azimuthal_Grid  int32 4B -2147483647\n",
+       "    ice_conc                (time, yc, xc) float64 1MB 0.0 0.0 0.0 ... nan nan\n",
+       "    raw_ice_conc_values     (time, yc, xc) float64 1MB nan nan nan ... nan nan\n",
+       "    status_flag             (time, yc, xc) float32 746kB 128.0 128.0 ... 1.0 1.0\n",
+       "    time_bnds               (time, nv) float64 16B 1.328e+09 1.331e+09\n",
+       "Attributes:\n",
+       "    title:                     Monthly Sea Ice Concentration Climate Data Rec...\n",
+       "    summary:                   This climate data record of sea ice concentrat...\n",
+       "    topiccategory:             Oceans ClimatologyMeteorologyAtmosphere\n",
+       "    geospatial_lat_min:        16.62393\n",
+       "    geospatial_lat_max:        90.0\n",
+       "    geospatial_lon_min:        -180.0\n",
+       "    geospatial_lon_max:        180.0\n",
+       "    geospatial_vertical_min:   0.0\n",
+       "    geospatial_vertical_max:   0.0\n",
+       "    sensor:                    SMMR,SSM/I,SSMIS\n",
+       "    platform:                  Nimbus-7,DMSP-F&lt;08,10,11,13,14,15&gt;,DMSP-F&lt;16,1...\n",
+       "    time_coverage_start:       2020-02-01T00:00:00Z\n",
+       "    time_coverage_end:         2020-03-01T00:00:00Z\n",
+       "    time_coverage_duration:    P1M\n",
+       "    time_coverage_resolution:  P1M\n",
+       "    project:                   OSI SAF - EUMETSAT\n",
+       "    institution:               OSISAF - EUMETSAT\n",
+       "    creator_name:              OSISAF - EUMETSAT\n",
+       "    creator_type:              institution\n",
+       "    creator_url:               https://osi-saf.eumetsat.int/\n",
+       "    creator_email:             osi-saf.helpdesk@meteo.fr\n",
+       "    date_created:              2023-03-20\n",
+       "    cdm_data_type:             Grid\n",
+       "    spatial_resolution:        25.0 km grid spacing\n",
+       "    geospatial_bounds_crs:     EPSG:6931\n",
+       "    tracking_id:               537df889-640b-44f8-bb9f-f49d9b281ca1\n",
+       "    naming_authority:          int.eumetsat\n",
+       "    standard_name_vocabulary:  CF Standard Name Table (Version 78, 21 Septemb...\n",
+       "    product_name:              osi_saf_sea_ice_conc_climate_data_record_smmrs...\n",
+       "    keywords:                  GCMDSK:Earth Science &gt; Cryosphere &gt; Sea Ice &gt; ...\n",
+       "    keywords_vocabulary:       GCMDSK:GCMD Science Keywords:https://gcmd.eart...\n",
+       "    Conventions:               CF-1.7,ACDD-1.3\n",
+       "    algorithm:                 SICCI3LF (19V, 37V, 37H)\n",
+       "    contributor_name:          Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,C...\n",
+       "    contributor_role:          PrincipalInvestigator,author,author,author,aut...\n",
+       "    source:                    FCDR of SMMR / SSMI / SSMIS Brightness Tempera...\n",
+       "    product_status:            released\n",
+       "    history:                   2023-03-20T13:57:20Z creation\\n2025-02-17T11:0...\n",
+       "    product_version:           3.1\n",
+       "    product_id:                osi-450-a1\n",
+       "    doi:                       10.15770/EUM_SAF_OSI_0023\n",
+       "    references:                Product User Manual (2025),Algorithm Theoretic...\n",
+       "    license:                   http://creativecommons.org/licenses/by/4.0/</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3c99287-dc38-4b11-bd98-7c265793620c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f3c99287-dc38-4b11-bd98-7c265793620c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>yc</span>: 432</li><li><span class='xr-has-index'>xc</span>: 432</li><li><span>nv</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-8219e897-9080-489c-b0cc-af5166eb50f6' class='xr-section-summary-in' type='checkbox' checked /><label for='section-8219e897-9080-489c-b0cc-af5166eb50f6' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.329e+09</div><input id='attrs-6b21b9b3-47b4-426c-a632-bd221aec6709' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b21b9b3-47b4-426c-a632-bd221aec6709' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e408676-8a30-4a16-88b9-d704fdad378c' class='xr-var-data-in' type='checkbox'><label for='data-5e408676-8a30-4a16-88b9-d704fdad378c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>reference time of product</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>seconds since 1978-01-01</dd><dt><span>calendar :</span></dt><dd>standard</dd></dl></div><div class='xr-var-data'><pre>array([1.329394e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yc</span></div><div class='xr-var-dims'>(yc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.388e+03 5.362e+03 ... -5.388e+03</div><input id='attrs-8d0d723c-170a-4afa-8b27-4ffdbf2b8f69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d0d723c-170a-4afa-8b27-4ffdbf2b8f69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-900499ac-04d2-45d7-ae06-a8ab3362918d' class='xr-var-data-in' type='checkbox'><label for='data-900499ac-04d2-45d7-ae06-a8ab3362918d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>km</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection (northings)</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([ 5387.5,  5362.5,  5337.5, ..., -5337.5, -5362.5, -5387.5], shape=(432,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xc</span></div><div class='xr-var-dims'>(xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+03 -5.362e+03 ... 5.388e+03</div><input id='attrs-db3382f6-fc7f-4b06-b82d-0d5305a7974e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db3382f6-fc7f-4b06-b82d-0d5305a7974e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f3d2597-cbe0-4ea0-ab21-6fd31e52882b' class='xr-var-data-in' type='checkbox'><label for='data-1f3d2597-cbe0-4ea0-ab21-6fd31e52882b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>km</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection (eastings)</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5387.5, -5362.5, -5337.5, ...,  5337.5,  5362.5,  5387.5], shape=(432,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.62 16.82 17.02 ... 16.82 16.62</div><input id='attrs-8f13d07b-5521-4eb0-a8a7-13d04e7ec222' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f13d07b-5521-4eb0-a8a7-13d04e7ec222' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e7afdd4-df10-47f3-ac37-54012706f249' class='xr-var-data-in' type='checkbox'><label for='data-2e7afdd4-df10-47f3-ac37-54012706f249' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[16.623926, 16.822655, 17.020658, ..., 17.020658, 16.822655,\n",
+       "        16.623926],\n",
+       "       [16.822655, 17.021584, 17.219795, ..., 17.219795, 17.021584,\n",
+       "        16.822655],\n",
+       "       [17.020658, 17.219795, 17.418213, ..., 17.418213, 17.219795,\n",
+       "        17.020658],\n",
+       "       ...,\n",
+       "       [17.020658, 17.219795, 17.418213, ..., 17.418213, 17.219795,\n",
+       "        17.020658],\n",
+       "       [16.822655, 17.021584, 17.219795, ..., 17.219795, 17.021584,\n",
+       "        16.822655],\n",
+       "       [16.623926, 16.822655, 17.020658, ..., 17.020658, 16.822655,\n",
+       "        16.623926]], shape=(432, 432), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-135.0 -135.1 -135.3 ... 44.87 45.0</div><input id='attrs-abf5d874-29f1-4d01-aa89-8d6bab206aeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abf5d874-29f1-4d01-aa89-8d6bab206aeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce8b1f0a-0fef-4dd8-8f60-658ed18a3f55' class='xr-var-data-in' type='checkbox'><label for='data-ce8b1f0a-0fef-4dd8-8f60-658ed18a3f55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[-135.      , -135.13324 , -135.2671  , ...,  135.2671  ,\n",
+       "         135.13324 ,  135.      ],\n",
+       "       [-134.86676 , -135.      , -135.13387 , ...,  135.13387 ,\n",
+       "         135.      ,  134.86676 ],\n",
+       "       [-134.7329  , -134.86613 , -135.      , ...,  135.      ,\n",
+       "         134.86613 ,  134.7329  ],\n",
+       "       ...,\n",
+       "       [ -45.267113,  -45.13387 ,  -45.      , ...,   45.      ,\n",
+       "          45.13387 ,   45.267113],\n",
+       "       [ -45.133247,  -45.      ,  -44.86613 , ...,   44.86613 ,\n",
+       "          45.      ,   45.133247],\n",
+       "       [ -45.      ,  -44.866753,  -44.732887, ...,   44.732887,\n",
+       "          44.866753,   45.      ]], shape=(432, 432), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98941566-5eef-4617-ab7c-cf789626830a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-98941566-5eef-4617-ab7c-cf789626830a' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Azimuthal_Grid</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-4404d34e-93c5-4f1b-b3d3-ea32fb4c91e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4404d34e-93c5-4f1b-b3d3-ea32fb4c91e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bacdf73-04d3-43dc-b491-ffe39224c875' class='xr-var-data-in' type='checkbox'><label for='data-4bacdf73-04d3-43dc-b491-ffe39224c875' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>90.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>proj4_string :</span></dt><dd>+proj=laea +lon_0=0 +datum=WGS84 +ellps=WGS84 +lat_0=90.0</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ice_conc</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-d1d278df-a9b1-418d-af20-92e3bec3e488' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1d278df-a9b1-418d-af20-92e3bec3e488' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cd172e2-6118-4b28-af10-9efdc0a798e1' class='xr-var-data-in' type='checkbox'><label for='data-2cd172e2-6118-4b28-af10-9efdc0a798e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>fully filtered concentration of sea ice using atmospheric correction of brightness temperatures and open water filters</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>ancillary_variables :</span></dt><dd>total_standard_uncertainty status_flag</dd><dt><span>comment :</span></dt><dd>this field is the primary sea ice concentration estimate for this climate data record</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        ...,\n",
+       "        [ 0.,  0.,  0., ..., nan, nan, nan],\n",
+       "        [ 0.,  0.,  0., ..., nan, nan, nan],\n",
+       "        [ 0.,  0.,  0., ..., nan, nan, nan]]], shape=(1, 432, 432))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ice_conc_values</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-377ffab0-4c8e-4775-b676-8331f749e4b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-377ffab0-4c8e-4775-b676-8331f749e4b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e736b92-0c2c-4498-ba28-24e196b25f43' class='xr-var-data-in' type='checkbox'><label for='data-8e736b92-0c2c-4498-ba28-24e196b25f43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sea ice concentration estimates as retrieved by the algorithm, and that were edited away by the various filters</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>comment :</span></dt><dd>this field can be used in combination with &#x27;ice_conc&#x27; to access un-bounded normal distribution of sea ice concentration estimates corresponding to the uncertainty estimate in &#x27;total_standard_uncertainty&#x27;. It does also feature some amount of un-physical data (below 0% and above 100%).</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
+       "        [nan, nan, nan, ..., nan, nan, nan],\n",
+       "        [nan, nan, nan, ..., nan, nan, nan],\n",
+       "        ...,\n",
+       "        [nan, nan, nan, ..., nan, nan, nan],\n",
+       "        [nan, nan, nan, ..., nan, nan, nan],\n",
+       "        [nan, nan, nan, ..., nan, nan, nan]]], shape=(1, 432, 432))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_flag</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>128.0 128.0 128.0 ... 1.0 1.0 1.0</div><input id='attrs-8629e256-1e56-4c82-92d5-9919bfaf2b63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8629e256-1e56-4c82-92d5-9919bfaf2b63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88fb5773-8f02-406b-a28f-83def353d668' class='xr-var-data-in' type='checkbox'><label for='data-88fb5773-8f02-406b-a28f-83def353d668' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>status flag bit array for sea ice concentration retrievals</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction status_flag</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>flag_masks :</span></dt><dd>[  1   2   4   8  16  32  64 128]</dd><dt><span>flag_meanings :</span></dt><dd>land lake open_water_filtered land_spill_over high_t2m spatial_interp temporal_interp max_ice_climo</dd><dt><span>flag_descriptions :</span></dt><dd>\n",
+       "all bits to 0 (flag 0): Nominal retrieval by the SIC algorithm\n",
+       "bit 1 (flag 1): Position is over land\n",
+       "bit 2 (flag 2): Position is lake\n",
+       "bit 3 (flag 4): SIC is set to zero by the open water filter\n",
+       "bit 4 (flag 8): SIC value is changed for correcting land spill-over effects\n",
+       "bit 5 (flag 16): Handle with caution, the 2m air temperature is high at this position, and this might be false ice\n",
+       "bit 6 (flag 32): Value is the result of spatial interpolation\n",
+       "bit 7 (flag 64): Value is the result of temporal interpolation\n",
+       "bit 8 (flag 128): SIC is set to zero since position is outside maximum sea ice climatology.</dd><dt><span>comment :</span></dt><dd>Flag values found in the map might be combinations of those listed above. For example flag value 80 (= 2^4 + 2^6 = 16 + 64) indicates high_t2m AND temporal_interp</dd></dl></div><div class='xr-var-data'><pre>array([[[128., 128., 128., ..., 128., 128., 128.],\n",
+       "        [128., 128., 128., ..., 128., 128., 128.],\n",
+       "        [128., 128., 128., ..., 128., 128., 128.],\n",
+       "        ...,\n",
+       "        [128., 128., 128., ...,   1.,   1.,   1.],\n",
+       "        [128., 128., 128., ...,   1.,   1.,   1.],\n",
+       "        [128., 128., 128., ...,   1.,   1.,   1.]]],\n",
+       "      shape=(1, 432, 432), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.328e+09 1.331e+09</div><input id='attrs-e876d86a-a3fd-4fa8-b124-34cb265ab9b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e876d86a-a3fd-4fa8-b124-34cb265ab9b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49fc9cd8-7697-41da-ade0-721816741919' class='xr-var-data-in' type='checkbox'><label for='data-49fc9cd8-7697-41da-ade0-721816741919' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.3280544e+09, 1.3305600e+09]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fc71617f-c813-4005-9d6e-e635d51e82ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fc71617f-c813-4005-9d6e-e635d51e82ac' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(43)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>Monthly Sea Ice Concentration Climate Data Record Version 3 (SMMR, SSM/I, and SSMIS) from the EUMETSAT OSI SAF</dd><dt><span>summary :</span></dt><dd>This climate data record of sea ice concentration is obtained from coarse resolution passive microwave satellite data (SMMR, SSM/I, and SSMIS) over the polar regions (Arctic and Antarctic). The processing chain features: 1) dynamic tuning of tie-points and algorithms,  2) correction of atmospheric noise using a Radiative Transfer Model,  3) computation of per-pixel uncertainties, and 4) an optimal hybrid sea ice concentration algorithm. This dataset was generated by the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF). The ESA CCI Programme contributed with Research and Development on the algorithms.</dd><dt><span>topiccategory :</span></dt><dd>Oceans ClimatologyMeteorologyAtmosphere</dd><dt><span>geospatial_lat_min :</span></dt><dd>16.62393</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>sensor :</span></dt><dd>SMMR,SSM/I,SSMIS</dd><dt><span>platform :</span></dt><dd>Nimbus-7,DMSP-F&lt;08,10,11,13,14,15&gt;,DMSP-F&lt;16,17,18&gt;</dd><dt><span>time_coverage_start :</span></dt><dd>2020-02-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2020-03-01T00:00:00Z</dd><dt><span>time_coverage_duration :</span></dt><dd>P1M</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1M</dd><dt><span>project :</span></dt><dd>OSI SAF - EUMETSAT</dd><dt><span>institution :</span></dt><dd>OSISAF - EUMETSAT</dd><dt><span>creator_name :</span></dt><dd>OSISAF - EUMETSAT</dd><dt><span>creator_type :</span></dt><dd>institution</dd><dt><span>creator_url :</span></dt><dd>https://osi-saf.eumetsat.int/</dd><dt><span>creator_email :</span></dt><dd>osi-saf.helpdesk@meteo.fr</dd><dt><span>date_created :</span></dt><dd>2023-03-20</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>spatial_resolution :</span></dt><dd>25.0 km grid spacing</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:6931</dd><dt><span>tracking_id :</span></dt><dd>537df889-640b-44f8-bb9f-f49d9b281ca1</dd><dt><span>naming_authority :</span></dt><dd>int.eumetsat</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (Version 78, 21 September 2021)</dd><dt><span>product_name :</span></dt><dd>osi_saf_sea_ice_conc_climate_data_record_smmrssmissmis</dd><dt><span>keywords :</span></dt><dd>GCMDSK:Earth Science &gt; Cryosphere &gt; Sea Ice &gt; Sea Ice Concentration, GCMDSK:Earth Science &gt; Oceans &gt; Sea Ice &gt; Sea Ice Concentration, GCMDSK:Earth Science &gt; Climate Indicators &gt; Cryospheric Indicators &gt; Sea Ice Concentration, GCMDLOC:Geographic Region &gt; Northern Hemisphere, GCMDLOC:Vertical Location &gt; Sea Surface, GCMDPROV: Government Agencies-non-US &gt; Norway &gt; NO/MET &gt; Norwegian Meteorological Institute</dd><dt><span>keywords_vocabulary :</span></dt><dd>GCMDSK:GCMD Science Keywords:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords, GCMDPROV:GCMD Providers:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/providers, GCMDLOC:GCMD Locations:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/locations</dd><dt><span>Conventions :</span></dt><dd>CF-1.7,ACDD-1.3</dd><dt><span>algorithm :</span></dt><dd>SICCI3LF (19V, 37V, 37H)</dd><dt><span>contributor_name :</span></dt><dd>Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,Courtenay Strong,Matilde Kreiner,Roberto Saldo,Anton Birkedal,Fabrizio Baordo,Trygve Aspenes,Steinar Eastwood</dd><dt><span>contributor_role :</span></dt><dd>PrincipalInvestigator,author,author,author,author,author,author,author,author,author</dd><dt><span>source :</span></dt><dd>FCDR of SMMR / SSMI / SSMIS Brightness Temperatures R4 from EUMETSAT Climate Monitoring SAF (doi:10.5676/EUM_SAF_CM/FCDR_MWI/V004), ERA5</dd><dt><span>product_status :</span></dt><dd>released</dd><dt><span>history :</span></dt><dd>2023-03-20T13:57:20Z creation\n",
+       "2025-02-17T11:05:00Z assign new DOI and version number 3.1</dd><dt><span>product_version :</span></dt><dd>3.1</dd><dt><span>product_id :</span></dt><dd>osi-450-a1</dd><dt><span>doi :</span></dt><dd>10.15770/EUM_SAF_OSI_0023</dd><dt><span>references :</span></dt><dd>Product User Manual (2025),Algorithm Theoretical Basis Document (2025),Validation Report (2025),https://osi-saf.eumetsat.int/products/osi-450-a1</dd><dt><span>license :</span></dt><dd>http://creativecommons.org/licenses/by/4.0/</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 5MB\n",
+       "Dimensions:                 (time: 1, yc: 432, xc: 432, nv: 2)\n",
+       "Coordinates:\n",
+       "  * time                    (time) float64 8B 1.329e+09\n",
+       "  * yc                      (yc) float64 3kB 5.388e+03 5.362e+03 ... -5.388e+03\n",
+       "  * xc                      (xc) float64 3kB -5.388e+03 -5.362e+03 ... 5.388e+03\n",
+       "    lat                     (yc, xc) float32 746kB 16.62 16.82 ... 16.82 16.62\n",
+       "    lon                     (yc, xc) float32 746kB -135.0 -135.1 ... 44.87 45.0\n",
+       "Dimensions without coordinates: nv\n",
+       "Data variables:\n",
+       "    Lambert_Azimuthal_Grid  int32 4B -2147483647\n",
+       "    ice_conc                (time, yc, xc) float64 1MB 0.0 0.0 0.0 ... nan nan\n",
+       "    raw_ice_conc_values     (time, yc, xc) float64 1MB nan nan nan ... nan nan\n",
+       "    status_flag             (time, yc, xc) float32 746kB 128.0 128.0 ... 1.0 1.0\n",
+       "    time_bnds               (time, nv) float64 16B 1.328e+09 1.331e+09\n",
+       "Attributes:\n",
+       "    title:                     Monthly Sea Ice Concentration Climate Data Rec...\n",
+       "    summary:                   This climate data record of sea ice concentrat...\n",
+       "    topiccategory:             Oceans ClimatologyMeteorologyAtmosphere\n",
+       "    geospatial_lat_min:        16.62393\n",
+       "    geospatial_lat_max:        90.0\n",
+       "    geospatial_lon_min:        -180.0\n",
+       "    geospatial_lon_max:        180.0\n",
+       "    geospatial_vertical_min:   0.0\n",
+       "    geospatial_vertical_max:   0.0\n",
+       "    sensor:                    SMMR,SSM/I,SSMIS\n",
+       "    platform:                  Nimbus-7,DMSP-F<08,10,11,13,14,15>,DMSP-F<16,1...\n",
+       "    time_coverage_start:       2020-02-01T00:00:00Z\n",
+       "    time_coverage_end:         2020-03-01T00:00:00Z\n",
+       "    time_coverage_duration:    P1M\n",
+       "    time_coverage_resolution:  P1M\n",
+       "    project:                   OSI SAF - EUMETSAT\n",
+       "    institution:               OSISAF - EUMETSAT\n",
+       "    creator_name:              OSISAF - EUMETSAT\n",
+       "    creator_type:              institution\n",
+       "    creator_url:               https://osi-saf.eumetsat.int/\n",
+       "    creator_email:             osi-saf.helpdesk@meteo.fr\n",
+       "    date_created:              2023-03-20\n",
+       "    cdm_data_type:             Grid\n",
+       "    spatial_resolution:        25.0 km grid spacing\n",
+       "    geospatial_bounds_crs:     EPSG:6931\n",
+       "    tracking_id:               537df889-640b-44f8-bb9f-f49d9b281ca1\n",
+       "    naming_authority:          int.eumetsat\n",
+       "    standard_name_vocabulary:  CF Standard Name Table (Version 78, 21 Septemb...\n",
+       "    product_name:              osi_saf_sea_ice_conc_climate_data_record_smmrs...\n",
+       "    keywords:                  GCMDSK:Earth Science > Cryosphere > Sea Ice > ...\n",
+       "    keywords_vocabulary:       GCMDSK:GCMD Science Keywords:https://gcmd.eart...\n",
+       "    Conventions:               CF-1.7,ACDD-1.3\n",
+       "    algorithm:                 SICCI3LF (19V, 37V, 37H)\n",
+       "    contributor_name:          Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,C...\n",
+       "    contributor_role:          PrincipalInvestigator,author,author,author,aut...\n",
+       "    source:                    FCDR of SMMR / SSMI / SSMIS Brightness Tempera...\n",
+       "    product_status:            released\n",
+       "    history:                   2023-03-20T13:57:20Z creation\\n2025-02-17T11:0...\n",
+       "    product_version:           3.1\n",
+       "    product_id:                osi-450-a1\n",
+       "    doi:                       10.15770/EUM_SAF_OSI_0023\n",
+       "    references:                Product User Manual (2025),Algorithm Theoretic...\n",
+       "    license:                   http://creativecommons.org/licenses/by/4.0/"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(DATA_PATHS[\"nh\"], decode_times=False) as opened:\n",
+    "    north_source = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=90,\n",
+    "):\n",
+    "    display(north_source)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "nh (1, 432, 432) (432, 432) (432, 432, 4)\n",
+      "sh (1, 432, 432) (432, 432) (432, 432, 4)\n"
+     ]
+    }
+   ],
+   "source": [
+    "run_dir = Path(\"output\") / \"07_non_lat_lon_sea_ice_concentration\"\n",
+    "if run_dir.exists():\n",
+    "    shutil.rmtree(run_dir)\n",
+    "output_dir = run_dir / \"cmor_output\"\n",
+    "output_dir.mkdir(parents=True)\n",
+    "\n",
+    "DATASET_INFO_BASE = {\n",
+    "    \"_AXIS_ENTRY_FILE\": \"CMIP7_coordinate.json\",\n",
+    "    \"_FORMULA_VAR_FILE\": \"CMIP7_formula_terms.json\",\n",
+    "    \"_cmip7_option\": 1,\n",
+    "    \"_controlled_vocabulary_file\": CV_PATH,\n",
+    "    \"activity_id\": \"CMIP\",\n",
+    "    \"calendar\": \"standard\",\n",
+    "    \"experiment_id\": \"amip\",\n",
+    "    \"forcing_index\": \"f3\",\n",
+    "    \"frequency\": \"mon\",\n",
+    "    \"grid_label\": \"g999\",\n",
+    "    \"host_collection\": \"CMIP7\",\n",
+    "    \"initialization_index\": \"i1\",\n",
+    "    \"institution_id\": \"CCCma\",\n",
+    "    \"license_id\": \"CC-BY-4.0\",\n",
+    "    \"nominal_resolution\": \"25 km\",\n",
+    "    \"physics_index\": \"p1\",\n",
+    "    \"realization_index\": \"r9\",\n",
+    "    \"source_id\": \"DUMMY-MODEL\",\n",
+    "}\n",
+    "\n",
+    "\n",
+    "def cell_edges(values):\n",
+    "    return np.concatenate(\n",
+    "        ([values[0] - 0.5 * (values[1] - values[0])], 0.5 * (values[:-1] + values[1:]), [values[-1] + 0.5 * (values[-1] - values[-2])])\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "def prepare_ease2_source(data_path):\n",
+    "    with xr.open_dataset(data_path, decode_times=False) as opened:\n",
+    "        source = opened.load()\n",
+    "\n",
+    "    x = (source[\"xc\"].values * 1000.0).astype(\"f8\")\n",
+    "    y = (source[\"yc\"].values[::-1] * 1000.0).astype(\"f8\")\n",
+    "    latitude = source[\"lat\"].values[::-1, :].T.astype(\"f8\")\n",
+    "    longitude = (source[\"lon\"].values[::-1, :].T % 360.0).astype(\"f8\")\n",
+    "\n",
+    "    missing_value = np.float32(1.0e20)\n",
+    "    ice_conc = source[\"ice_conc\"].isel(time=0).values[::-1, :].T.astype(\"f4\")\n",
+    "    siconc = np.where(np.isfinite(ice_conc), ice_conc, missing_value).astype(\"f4\")[None, :, :]\n",
+    "\n",
+    "    x_edges = cell_edges(x)\n",
+    "    y_edges = cell_edges(y)\n",
+    "    mapping_attrs = source[\"Lambert_Azimuthal_Grid\"].attrs\n",
+    "    source_crs = pyproj.CRS.from_proj4(mapping_attrs[\"proj4_string\"])\n",
+    "    transformer = pyproj.Transformer.from_crs(source_crs, source_crs.geodetic_crs, always_xy=True)\n",
+    "    latitude_vertices = np.empty((*latitude.shape, 4), dtype=\"f8\")\n",
+    "    longitude_vertices = np.empty((*longitude.shape, 4), dtype=\"f8\")\n",
+    "    for vertex, (x_vertex, y_vertex) in enumerate(\n",
+    "        [\n",
+    "            (x_edges[:-1][:, None], y_edges[:-1][None, :]),\n",
+    "            (x_edges[1:][:, None], y_edges[:-1][None, :]),\n",
+    "            (x_edges[1:][:, None], y_edges[1:][None, :]),\n",
+    "            (x_edges[:-1][:, None], y_edges[1:][None, :]),\n",
+    "        ]\n",
+    "    ):\n",
+    "        lon_vertex, lat_vertex = transformer.transform(x_vertex, y_vertex)\n",
+    "        latitude_vertices[:, :, vertex] = lat_vertex\n",
+    "        longitude_vertices[:, :, vertex] = lon_vertex % 360.0\n",
+    "\n",
+    "    crs_params = {\n",
+    "        \"latitude_of_projection_origin\": [float(mapping_attrs[\"latitude_of_projection_origin\"]), \"degrees_north\"],\n",
+    "        \"longitude_of_projection_origin\": [float(mapping_attrs[\"longitude_of_projection_origin\"]), \"degrees_east\"],\n",
+    "        \"false_easting\": [float(mapping_attrs[\"false_easting\"]), \"m\"],\n",
+    "        \"false_northing\": [float(mapping_attrs[\"false_northing\"]), \"m\"],\n",
+    "        \"semi_major_axis\": [float(mapping_attrs[\"semi_major_axis\"]), \"m\"],\n",
+    "        \"inverse_flattening\": [float(mapping_attrs[\"inverse_flattening\"]), \"\"],\n",
+    "    }\n",
+    "\n",
+    "    return {\n",
+    "        \"x\": x,\n",
+    "        \"y\": y,\n",
+    "        \"latitude\": latitude,\n",
+    "        \"longitude\": longitude,\n",
+    "        \"latitude_vertices\": latitude_vertices,\n",
+    "        \"longitude_vertices\": longitude_vertices,\n",
+    "        \"siconc\": siconc,\n",
+    "        \"missing_value\": missing_value,\n",
+    "        \"time\": source[\"time\"].values.astype(\"f8\"),\n",
+    "        \"time_bnds\": source[\"time_bnds\"].values.astype(\"f8\").reshape(2),\n",
+    "        \"time_units\": source[\"time\"].attrs[\"units\"],\n",
+    "        \"crs_params\": crs_params,\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "prepared_sources = {region: prepare_ease2_source(data_path) for region, data_path in DATA_PATHS.items()}\n",
+    "for region, prepared in prepared_sources.items():\n",
+    "    print(region, prepared[\"siconc\"].shape, prepared[\"latitude\"].shape, prepared[\"latitude_vertices\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "nh output/07_non_lat_lon_sea_ice_concentration/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/nh/mon/siconc/tavg-u-hxy-u/g999/v20260605/siconc_tavg-u-hxy-u_mon_nh_g999_DUMMY-MODEL_amip_r9i1p1f3_202002-202002.nc\n",
+      "sh output/07_non_lat_lon_sea_ice_concentration/cmor_output/MIP-DRS7/CMIP7/CMIP/CCCma/DUMMY-MODEL/amip/r9i1p1f3/sh/mon/siconc/tavg-u-hxy-u/g999/v20260605/siconc_tavg-u-hxy-u_mon_sh_g999_DUMMY-MODEL_amip_r9i1p1f3_202002-202002.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "def table_lookup(table_name, section_name, compound_name):\n",
+    "    with open(Path(TABLES_DIR) / table_name) as handle:\n",
+    "        return json.load(handle)[section_name].get(compound_name)\n",
+    "\n",
+    "\n",
+    "def write_cmor_siconc(region, prepared):\n",
+    "    dataset_info = dict(DATASET_INFO_BASE)\n",
+    "    dataset_info.update({\"outpath\": str(output_dir), \"region\": region})\n",
+    "    input_json = run_dir / f\"input_{region}.json\"\n",
+    "    input_json.write_text(json.dumps(dataset_info, indent=2, sort_keys=True))\n",
+    "\n",
+    "    cmor.setup(\n",
+    "        inpath=TABLES_DIR,\n",
+    "        netcdf_file_action=cmor.CMOR_REPLACE,\n",
+    "        logfile=str(run_dir / f\"cmor_{region}.log\"),\n",
+    "    )\n",
+    "    cmor.dataset_json(str(input_json))\n",
+    "\n",
+    "    grid_table = cmor.load_table(\"CMIP7_grids.json\")\n",
+    "    seaice_table = cmor.load_table(\"CMIP7_seaIce.json\")\n",
+    "\n",
+    "    cmor.set_table(grid_table)\n",
+    "    x_id = cmor.axis(\"x\", coord_vals=prepared[\"x\"], units=\"m\")\n",
+    "    y_id = cmor.axis(\"y\", coord_vals=prepared[\"y\"], units=\"m\")\n",
+    "    grid_id = cmor.grid(\n",
+    "        axis_ids=[x_id, y_id],\n",
+    "        latitude=prepared[\"latitude\"],\n",
+    "        longitude=prepared[\"longitude\"],\n",
+    "        latitude_vertices=prepared[\"latitude_vertices\"],\n",
+    "        longitude_vertices=prepared[\"longitude_vertices\"],\n",
+    "    )\n",
+    "    cmor.set_crs(grid_id, \"lambert_azimuthal_equal_area\", prepared[\"crs_params\"])\n",
+    "\n",
+    "    cmor.set_table(seaice_table)\n",
+    "    time_id = cmor.axis(\"time\", coord_vals=prepared[\"time\"], cell_bounds=prepared[\"time_bnds\"], units=prepared[\"time_units\"])\n",
+    "\n",
+    "    variable_name = \"siconc_tavg-u-hxy-u\"\n",
+    "    siconc_id = cmor.variable(variable_name, \"%\", [time_id, grid_id], missing_value=prepared[\"missing_value\"])\n",
+    "    compound_name = \".\".join([\"seaIce\"] + variable_name.split(\"_\") + [\"mon\", region])\n",
+    "\n",
+    "    cell_measure = table_lookup(\"CMIP7_cell_measures.json\", \"cell_measures\", compound_name)\n",
+    "    if cell_measure:\n",
+    "        cmor.set_variable_attribute(siconc_id, \"cell_measures\", \"c\", cell_measure)\n",
+    "\n",
+    "    long_name = table_lookup(\"CMIP7_long_name_overrides.json\", \"long_name_overrides\", compound_name)\n",
+    "    if long_name:\n",
+    "        cmor.set_variable_attribute(siconc_id, \"long_name\", \"c\", long_name)\n",
+    "\n",
+    "    cmor.write(siconc_id, prepared[\"siconc\"])\n",
+    "    netcdf_path = Path(cmor.close(siconc_id, file_name=True))\n",
+    "    cmor.close()\n",
+    "    return netcdf_path\n",
+    "\n",
+    "\n",
+    "netcdf_paths = {region: write_cmor_siconc(region, prepared) for region, prepared in prepared_sources.items()}\n",
+    "for region, netcdf_path in netcdf_paths.items():\n",
+    "    print(region, netcdf_path.resolve().relative_to(Path.cwd().resolve()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 16MB\n",
+       "Dimensions:             (time: 1, bnds: 2, x: 432, y: 432, vertices: 4)\n",
+       "Coordinates:\n",
+       "  * time                (time) float64 8B 1.539e+04\n",
+       "  * x                   (x) float64 3kB -5.388e+06 -5.362e+06 ... 5.388e+06\n",
+       "  * y                   (y) float64 3kB -5.388e+06 -5.362e+06 ... 5.388e+06\n",
+       "    latitude            (x, y) float64 1MB 16.62 16.82 17.02 ... 16.82 16.62\n",
+       "    longitude           (x, y) float64 1MB 315.0 314.9 314.7 ... 134.9 135.0\n",
+       "Dimensions without coordinates: bnds, vertices\n",
+       "Data variables:\n",
+       "    time_bnds           (time, bnds) float64 16B 1.537e+04 1.54e+04\n",
+       "    crs                 int32 4B -2147483647\n",
+       "    vertices_latitude   (x, y, vertices) float64 6MB 16.42 16.62 ... 16.42 16.62\n",
+       "    vertices_longitude  (x, y, vertices) float64 6MB 315.0 315.1 ... 135.0 135.1\n",
+       "    siconc              (time, x, y) float32 746kB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      siconc_tavg-u-hxy-u\n",
+       "    branding_suffix:       tavg-u-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:50Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:50Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    25 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 seaIce\n",
+       "    region:                nh\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_seaIce.json; Creation Date:(2026-04-21...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/3a7338c7-6944-4ee7-b038-2d3c2b2ecf56\n",
+       "    variable_id:           siconc\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1c98496a-6742-4d25-8ea4-ee3da75359df' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-1c98496a-6742-4d25-8ea4-ee3da75359df' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>x</span>: 432</li><li><span class='xr-has-index'>y</span>: 432</li><li><span>vertices</span>: 4</li></ul></div></li><li class='xr-section-item'><input id='section-41d0667b-14af-424f-ab5e-f4cbcd9cb379' class='xr-section-summary-in' type='checkbox' checked /><label for='section-41d0667b-14af-424f-ab5e-f4cbcd9cb379' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.539e+04</div><input id='attrs-c14ef592-aa3f-4d68-96ee-e42e031b9fe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c14ef592-aa3f-4d68-96ee-e42e031b9fe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb53f63c-593b-4893-b35f-08829cc38de8' class='xr-var-data-in' type='checkbox'><label for='data-eb53f63c-593b-4893-b35f-08829cc38de8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>units :</span></dt><dd>days since 1978-01-01</dd><dt><span>calendar :</span></dt><dd>standard</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time Intervals</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([15385.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+06 -5.362e+06 ... 5.388e+06</div><input id='attrs-236e4a3f-41bb-4f22-a33d-3955a5c39f8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-236e4a3f-41bb-4f22-a33d-3955a5c39f8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1921a902-30d8-4462-b063-514f4bb56538' class='xr-var-data-in' type='checkbox'><label for='data-1921a902-30d8-4462-b063-514f4bb56538' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5387500., -5362500., -5337500., ...,  5337500.,  5362500.,  5387500.],\n",
+       "      shape=(432,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+06 -5.362e+06 ... 5.388e+06</div><input id='attrs-81f698fa-4ad8-41ef-90fe-0d621dd44055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81f698fa-4ad8-41ef-90fe-0d621dd44055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a66493c-aedf-4a93-a9e4-9c424756aeab' class='xr-var-data-in' type='checkbox'><label for='data-9a66493c-aedf-4a93-a9e4-9c424756aeab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5387500., -5362500., -5337500., ...,  5337500.,  5362500.,  5387500.],\n",
+       "      shape=(432,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>16.62 16.82 17.02 ... 16.82 16.62</div><input id='attrs-17b5f918-5da6-4dbf-87f2-1b9da0f532a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17b5f918-5da6-4dbf-87f2-1b9da0f532a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0b63173-e8f0-4ca5-9b31-0104892fc54f' class='xr-var-data-in' type='checkbox'><label for='data-b0b63173-e8f0-4ca5-9b31-0104892fc54f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>bounds :</span></dt><dd>vertices_latitude</dd></dl></div><div class='xr-var-data'><pre>array([[16.62392616, 16.82265472, 17.02065849, ..., 17.02065849,\n",
+       "        16.82265472, 16.62392616],\n",
+       "       [16.82265472, 17.02158356, 17.21979523, ..., 17.21979523,\n",
+       "        17.02158356, 16.82265472],\n",
+       "       [17.02065849, 17.21979523, 17.41821289, ..., 17.41821289,\n",
+       "        17.21979523, 17.02065849],\n",
+       "       ...,\n",
+       "       [17.02065849, 17.21979523, 17.41821289, ..., 17.41821289,\n",
+       "        17.21979523, 17.02065849],\n",
+       "       [16.82265472, 17.02158356, 17.21979523, ..., 17.21979523,\n",
+       "        17.02158356, 16.82265472],\n",
+       "       [16.62392616, 16.82265472, 17.02065849, ..., 17.02065849,\n",
+       "        16.82265472, 16.62392616]], shape=(432, 432))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>315.0 314.9 314.7 ... 134.9 135.0</div><input id='attrs-a18c4549-6b1b-403b-8f3d-75bf7e1be339' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a18c4549-6b1b-403b-8f3d-75bf7e1be339' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84146312-ffea-403e-b2c3-28baa048f839' class='xr-var-data-in' type='checkbox'><label for='data-84146312-ffea-403e-b2c3-28baa048f839' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>bounds :</span></dt><dd>vertices_longitude</dd></dl></div><div class='xr-var-data'><pre>array([[315.        , 314.86676025, 314.73287964, ..., 225.2671051 ,\n",
+       "        225.13323975, 225.        ],\n",
+       "       [315.13323975, 315.        , 314.86611938, ..., 225.13386536,\n",
+       "        225.        , 224.86676025],\n",
+       "       [315.26712036, 315.13388062, 315.        , ..., 225.        ,\n",
+       "        224.86613464, 224.7328949 ],\n",
+       "       ...,\n",
+       "       [ 44.73288727,  44.86613083,  45.        , ..., 135.        ,\n",
+       "        135.13386536, 135.2671051 ],\n",
+       "       [ 44.86675262,  45.        ,  45.13386917, ..., 134.86613464,\n",
+       "        135.        , 135.13323975],\n",
+       "       [ 45.        ,  45.13324738,  45.26711273, ..., 134.7328949 ,\n",
+       "        134.86676025, 135.        ]], shape=(432, 432))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9310cbc-c54d-4e8b-8b1f-9450e99ee276' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e9310cbc-c54d-4e8b-8b1f-9450e99ee276' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.537e+04 1.54e+04</div><input id='attrs-d77f49cd-aa44-4b0b-90a6-7e7459a0f298' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d77f49cd-aa44-4b0b-90a6-7e7459a0f298' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32c040fe-c3e6-4b50-b8ad-b2c35d360ba9' class='xr-var-data-in' type='checkbox'><label for='data-32c040fe-c3e6-4b50-b8ad-b2c35d360ba9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[15371., 15400.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-7c53c746-4536-4d50-9081-a7558ae81fe3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c53c746-4536-4d50-9081-a7558ae81fe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c92fb68d-96c4-45dd-9736-e1f05d8a59ec' class='xr-var-data-in' type='checkbox'><label for='data-c92fb68d-96c4-45dd-9736-e1f05d8a59ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>90.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertices_latitude</span></div><div class='xr-var-dims'>(x, y, vertices)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>16.42 16.62 16.82 ... 16.42 16.62</div><input id='attrs-7b98c672-63ed-4ec0-8625-41c9405d1ffe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b98c672-63ed-4ec0-8625-41c9405d1ffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8462cdd2-0732-4546-a2fc-fe499ff4ac76' class='xr-var-data-in' type='checkbox'><label for='data-8462cdd2-0732-4546-a2fc-fe499ff4ac76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[[16.42470792, 16.62369573, 16.822885  , 16.62369573],\n",
+       "        [16.822885  , 17.02135298, 17.22002648, 17.02135298],\n",
+       "        [17.22002648, 17.41798082, 17.61614471, 17.41798082],\n",
+       "        ...,\n",
+       "        [17.61614471, 17.41798082, 17.22002648, 17.41798082],\n",
+       "        [17.22002648, 17.02135298, 16.822885  , 17.02135298],\n",
+       "        [16.822885  , 16.62369573, 16.42470792, 16.62369573]],\n",
+       "\n",
+       "       [[16.42470792, 16.62369573, 16.822885  , 16.62369573],\n",
+       "        [16.822885  , 17.02135298, 17.22002648, 17.02135298],\n",
+       "        [17.22002648, 17.41798082, 17.61614471, 17.41798082],\n",
+       "        ...,\n",
+       "        [17.61614471, 17.41798082, 17.22002648, 17.41798082],\n",
+       "        [17.22002648, 17.02135298, 16.822885  , 17.02135298],\n",
+       "        [16.822885  , 16.62369573, 16.42470792, 16.62369573]],\n",
+       "\n",
+       "       [[16.42470792, 16.62369573, 16.822885  , 16.62369573],\n",
+       "        [16.822885  , 17.02135298, 17.22002648, 17.02135298],\n",
+       "        [17.22002648, 17.41798082, 17.61614471, 17.41798082],\n",
+       "        ...,\n",
+       "...\n",
+       "        [17.61614471, 17.41798082, 17.22002648, 17.41798082],\n",
+       "        [17.22002648, 17.02135298, 16.822885  , 17.02135298],\n",
+       "        [16.822885  , 16.62369573, 16.42470792, 16.62369573]],\n",
+       "\n",
+       "       [[16.42470792, 16.62369573, 16.822885  , 16.62369573],\n",
+       "        [16.822885  , 17.02135298, 17.22002648, 17.02135298],\n",
+       "        [17.22002648, 17.41798082, 17.61614471, 17.41798082],\n",
+       "        ...,\n",
+       "        [17.61614471, 17.41798082, 17.22002648, 17.41798082],\n",
+       "        [17.22002648, 17.02135298, 16.822885  , 17.02135298],\n",
+       "        [16.822885  , 16.62369573, 16.42470792, 16.62369573]],\n",
+       "\n",
+       "       [[16.42470792, 16.62369573, 16.822885  , 16.62369573],\n",
+       "        [16.822885  , 17.02135298, 17.22002648, 17.02135298],\n",
+       "        [17.22002648, 17.41798082, 17.61614471, 17.41798082],\n",
+       "        ...,\n",
+       "        [17.61614471, 17.41798082, 17.22002648, 17.41798082],\n",
+       "        [17.22002648, 17.02135298, 16.822885  , 17.02135298],\n",
+       "        [16.822885  , 16.62369573, 16.42470792, 16.62369573]]],\n",
+       "      shape=(432, 432, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertices_longitude</span></div><div class='xr-var-dims'>(x, y, vertices)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>315.0 315.1 315.0 ... 135.0 135.1</div><input id='attrs-37d54cdb-6bf0-4ccb-860c-0cdcb9e39445' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37d54cdb-6bf0-4ccb-860c-0cdcb9e39445' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20441628-ade3-47dd-a19e-bc967e25240f' class='xr-var-data-in' type='checkbox'><label for='data-20441628-ade3-47dd-a19e-bc967e25240f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[[315.        , 315.1329366 , 315.        , 314.8670634 ],\n",
+       "        [315.        , 315.1329366 , 315.        , 314.8670634 ],\n",
+       "        [315.        , 315.1329366 , 315.        , 314.8670634 ],\n",
+       "        ...,\n",
+       "        [315.        , 315.1329366 , 315.        , 314.8670634 ],\n",
+       "        [315.        , 315.1329366 , 315.        , 314.8670634 ],\n",
+       "        [315.        , 315.1329366 , 315.        , 314.8670634 ]],\n",
+       "\n",
+       "       [[315.        , 315.13355635, 315.        , 314.86644365],\n",
+       "        [315.        , 315.13355635, 315.        , 314.86644365],\n",
+       "        [315.        , 315.13355635, 315.        , 314.86644365],\n",
+       "        ...,\n",
+       "        [315.        , 315.13355635, 315.        , 314.86644365],\n",
+       "        [315.        , 315.13355635, 315.        , 314.86644365],\n",
+       "        [315.        , 315.13355635, 315.        , 314.86644365]],\n",
+       "\n",
+       "       [[315.        , 315.13418191, 315.        , 314.86581809],\n",
+       "        [315.        , 315.13418191, 315.        , 314.86581809],\n",
+       "        [315.        , 315.13418191, 315.        , 314.86581809],\n",
+       "        ...,\n",
+       "...\n",
+       "        [135.        , 134.86581809, 135.        , 135.13418191],\n",
+       "        [135.        , 134.86581809, 135.        , 135.13418191],\n",
+       "        [135.        , 134.86581809, 135.        , 135.13418191]],\n",
+       "\n",
+       "       [[135.        , 134.86644365, 135.        , 135.13355635],\n",
+       "        [135.        , 134.86644365, 135.        , 135.13355635],\n",
+       "        [135.        , 134.86644365, 135.        , 135.13355635],\n",
+       "        ...,\n",
+       "        [135.        , 134.86644365, 135.        , 135.13355635],\n",
+       "        [135.        , 134.86644365, 135.        , 135.13355635],\n",
+       "        [135.        , 134.86644365, 135.        , 135.13355635]],\n",
+       "\n",
+       "       [[135.        , 134.8670634 , 135.        , 135.1329366 ],\n",
+       "        [135.        , 134.8670634 , 135.        , 135.1329366 ],\n",
+       "        [135.        , 134.8670634 , 135.        , 135.1329366 ],\n",
+       "        ...,\n",
+       "        [135.        , 134.8670634 , 135.        , 135.1329366 ],\n",
+       "        [135.        , 134.8670634 , 135.        , 135.1329366 ],\n",
+       "        [135.        , 134.8670634 , 135.        , 135.1329366 ]]],\n",
+       "      shape=(432, 432, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>siconc</span></div><div class='xr-var-dims'>(time, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-124ca56f-c253-4a38-accc-259872b181a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-124ca56f-c253-4a38-accc-259872b181a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c7f22e3-ce3b-4ccf-9b49-18b8c3a70f2d' class='xr-var-data-in' type='checkbox'><label for='data-4c7f22e3-ce3b-4ccf-9b49-18b8c3a70f2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>long_name :</span></dt><dd>Sea-Ice Area Percentage (Ocean Grid)</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "        ...,\n",
+       "        [nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "        [nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "        [nan, nan, nan, ...,  0.,  0.,  0.]]],\n",
+       "      shape=(1, 432, 432), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b34b443-88da-49bc-a774-e45058a826fc' class='xr-section-summary-in' type='checkbox' checked /><label for='section-2b34b443-88da-49bc-a774-e45058a826fc' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.12</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>area_label :</span></dt><dd>u</dd><dt><span>branded_variable :</span></dt><dd>siconc_tavg-u-hxy-u</dd><dt><span>branding_suffix :</span></dt><dd>tavg-u-hxy-u</dd><dt><span>creation_date :</span></dt><dd>2026-06-05T21:59:50Z</dd><dt><span>data_specs_version :</span></dt><dd>MIP-DS7.1.0.0</dd><dt><span>description :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>drs_specs :</span></dt><dd>MIP-DRS7</dd><dt><span>experiment :</span></dt><dd>Simulation of the climate of the recent past with prescribed sea surface temperatures and sea ice concentrations.</dd><dt><span>experiment_id :</span></dt><dd>amip</dd><dt><span>forcing_index :</span></dt><dd>f3</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid_label :</span></dt><dd>g999</dd><dt><span>history :</span></dt><dd>2026-06-05T21:59:50Z ; CMOR rewrote data to be consistent with CF-1.12 and CMIP7 data requirements.</dd><dt><span>horizontal_label :</span></dt><dd>hxy</dd><dt><span>host_collection :</span></dt><dd>CMIP7</dd><dt><span>initialization_index :</span></dt><dd>i1</dd><dt><span>institution :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institution_id :</span></dt><dd>CCCma</dd><dt><span>license_id :</span></dt><dd>CC-BY-4.0</dd><dt><span>mip_era :</span></dt><dd>CMIP7</dd><dt><span>nominal_resolution :</span></dt><dd>25 km</dd><dt><span>physics_index :</span></dt><dd>p1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>r9</dd><dt><span>realm :</span></dt><dd>seaIce</dd><dt><span>region :</span></dt><dd>nh</dd><dt><span>source :</span></dt><dd>DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: Dummy Atmosphere; atmospheric_chemistry: Dummy Atmospheric Chemistry; land_surface: Dummy Land Surface; ocean: Dummy Ocean; ocean_biogeochemistry: Dummy Ocean Biogeochemistry; sea_ice: Dummy Sea Ice</dd><dt><span>source_id :</span></dt><dd>DUMMY-MODEL</dd><dt><span>table_info :</span></dt><dd>Name: CMIP7_seaIce.json; Creation Date:(2026-04-21 15:01:29) MD5:ac55986d4e9ece44a638ff080fdd9ada</dd><dt><span>temporal_label :</span></dt><dd>tavg</dd><dt><span>title :</span></dt><dd>DUMMY-MODEL output prepared for CMIP7</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14107/3a7338c7-6944-4ee7-b038-2d3c2b2ecf56</dd><dt><span>variable_id :</span></dt><dd>siconc</dd><dt><span>variant_label :</span></dt><dd>r9i1p1f3</dd><dt><span>vertical_label :</span></dt><dd>u</dd><dt><span>license :</span></dt><dd>CC-BY-4.0; CMIP7 data produced by CCCma is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Consult https://wcrp-cmip.github.io/cmip7-guidance/docs/CMIP7/Guidance_for_users/#2-terms-of-use-and-citations-requirements for terms of use governing CMIP7 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.15.1</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 16MB\n",
+       "Dimensions:             (time: 1, bnds: 2, x: 432, y: 432, vertices: 4)\n",
+       "Coordinates:\n",
+       "  * time                (time) float64 8B 1.539e+04\n",
+       "  * x                   (x) float64 3kB -5.388e+06 -5.362e+06 ... 5.388e+06\n",
+       "  * y                   (y) float64 3kB -5.388e+06 -5.362e+06 ... 5.388e+06\n",
+       "    latitude            (x, y) float64 1MB 16.62 16.82 17.02 ... 16.82 16.62\n",
+       "    longitude           (x, y) float64 1MB 315.0 314.9 314.7 ... 134.9 135.0\n",
+       "Dimensions without coordinates: bnds, vertices\n",
+       "Data variables:\n",
+       "    time_bnds           (time, bnds) float64 16B 1.537e+04 1.54e+04\n",
+       "    crs                 int32 4B -2147483647\n",
+       "    vertices_latitude   (x, y, vertices) float64 6MB 16.42 16.62 ... 16.42 16.62\n",
+       "    vertices_longitude  (x, y, vertices) float64 6MB 315.0 315.1 ... 135.0 135.1\n",
+       "    siconc              (time, x, y) float32 746kB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "Attributes:\n",
+       "    Conventions:           CF-1.12\n",
+       "    activity_id:           CMIP\n",
+       "    area_label:            u\n",
+       "    branded_variable:      siconc_tavg-u-hxy-u\n",
+       "    branding_suffix:       tavg-u-hxy-u\n",
+       "    creation_date:         2026-06-05T21:59:50Z\n",
+       "    data_specs_version:    MIP-DS7.1.0.0\n",
+       "    description:           Simulation of the climate of the recent past with ...\n",
+       "    drs_specs:             MIP-DRS7\n",
+       "    experiment:            Simulation of the climate of the recent past with ...\n",
+       "    experiment_id:         amip\n",
+       "    forcing_index:         f3\n",
+       "    frequency:             mon\n",
+       "    grid_label:            g999\n",
+       "    history:               2026-06-05T21:59:50Z ; CMOR rewrote data to be con...\n",
+       "    horizontal_label:      hxy\n",
+       "    host_collection:       CMIP7\n",
+       "    initialization_index:  i1\n",
+       "    institution:           Environment and Climate Change Canada\n",
+       "    institution_id:        CCCma\n",
+       "    license_id:            CC-BY-4.0\n",
+       "    mip_era:               CMIP7\n",
+       "    nominal_resolution:    25 km\n",
+       "    physics_index:         p1\n",
+       "    product:               model-output\n",
+       "    realization_index:     r9\n",
+       "    realm:                 seaIce\n",
+       "    region:                nh\n",
+       "    source:                DUMMY-MODEL: aerosol: Dummy Aerosol; atmosphere: D...\n",
+       "    source_id:             DUMMY-MODEL\n",
+       "    table_info:            Name: CMIP7_seaIce.json; Creation Date:(2026-04-21...\n",
+       "    temporal_label:        tavg\n",
+       "    title:                 DUMMY-MODEL output prepared for CMIP7\n",
+       "    tracking_id:           hdl:21.14107/3a7338c7-6944-4ee7-b038-2d3c2b2ecf56\n",
+       "    variable_id:           siconc\n",
+       "    variant_label:         r9i1p1f3\n",
+       "    vertical_label:        u\n",
+       "    license:               CC-BY-4.0; CMIP7 data produced by CCCma is license...\n",
+       "    cmor_version:          3.15.1"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_paths[\"nh\"], decode_times=False) as opened:\n",
+    "    ds = opened.load()\n",
+    "\n",
+    "with xr.set_options(\n",
+    "    display_style=\"html\",\n",
+    "    display_expand_attrs=True,\n",
+    "    display_expand_coords=True,\n",
+    "    display_expand_data_vars=True,\n",
+    "    display_max_rows=90,\n",
+    "):\n",
+    "    display(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1300x650 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with xr.open_dataset(netcdf_paths[\"sh\"], decode_times=False) as opened:\n",
+    "    south_ds = opened.load()\n",
+    "\n",
+    "\n",
+    "def plot_polar_siconc(ax, dataset, hemisphere):\n",
+    "    is_north = hemisphere == \"nh\"\n",
+    "    map_plot = Basemap(\n",
+    "        projection=\"laea\",\n",
+    "        lat_0=90 if is_north else -90,\n",
+    "        lon_0=0,\n",
+    "        width=10_800_000,\n",
+    "        height=10_800_000,\n",
+    "        resolution=\"l\",\n",
+    "        ax=ax,\n",
+    "    )\n",
+    "    map_plot.drawmapboundary(fill_color=\"#f7fbff\", linewidth=0.8)\n",
+    "    map_plot.fillcontinents(color=\"0.82\", lake_color=\"#f7fbff\", zorder=0)\n",
+    "    longitude_plot = dataset[\"longitude\"].values.T\n",
+    "    latitude_plot = dataset[\"latitude\"].values.T\n",
+    "    field = dataset[\"siconc\"].isel(time=0).values.T\n",
+    "    x_plot, y_plot = map_plot(longitude_plot, latitude_plot)\n",
+    "    mesh = map_plot.pcolormesh(x_plot, y_plot, field, shading=\"auto\", cmap=\"Blues\", vmin=0, vmax=100)\n",
+    "    map_plot.drawcoastlines(linewidth=0.7, color=\"0.15\")\n",
+    "    parallels = np.arange(40, 91, 10) if is_north else np.arange(-80, -39, 10)\n",
+    "    map_plot.drawparallels(parallels, labels=[1, 0, 0, 0], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "    map_plot.drawmeridians(np.arange(-180, 181, 45), labels=[0, 0, 0, 1], linewidth=0.4, color=\"0.45\", dashes=[1, 1])\n",
+    "    time_label = month_year_label(dataset[\"time\"])\n",
+    "    ax.set_title(f\"CMIP7 siconc on the {hemisphere.upper()} EASE2 projected grid, {time_label}\")\n",
+    "    return mesh\n",
+    "\n",
+    "\n",
+    "fig, axes = plt.subplots(1, 2, figsize=(13, 6.5), constrained_layout=True)\n",
+    "mesh = plot_polar_siconc(axes[0], ds, \"nh\")\n",
+    "plot_polar_siconc(axes[1], south_ds, \"sh\")\n",
+    "colorbar = fig.colorbar(mesh, ax=axes, location=\"right\", shrink=0.82, pad=0.03)\n",
+    "colorbar.set_label(\"%\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/README.md b/notebooks/README.md
new file mode 100644
index 00000000..2ec68f2e
--- /dev/null
+++ b/notebooks/README.md
@@ -0,0 +1,43 @@
+# CMIP7 CMOR Example Notebooks
+
+These notebooks demonstrate how to use CMOR to create CMIP7 dataset files. They use the `cmip7-cmor-tables` checkout in this repository.
+
+## Setup
+
+Create the notebook environment from the repository root:
+
+```bash
+python -m venv venv
+source venv/bin/activate
+pip install cmor --extra-index-url https://pcmdi.github.io/cmor
+pip install jupyterlab xarray matplotlib netCDF4 basemap pyproj nbstripout
+```
+
+Start JupyterLab:
+
+```bash
+jupyter lab notebooks
+```
+
+The notebooks write generated NetCDF files under `notebooks/output/`.
+
+### Rebuilding notebook output
+To rebuild checked-in example notebook output from the repository root:
+
+```bash
+tools/rebuild_notebook_output.sh notebooks/01_basic_ocean_surface_temperature.ipynb
+```
+
+Use `tools/rebuild_notebook_output.sh --all` to rebuild every example notebook.
+The tool executes notebooks in place, keeps the regenerated outputs, and strips
+notebook metadata with `nbstripout`.
+
+## Notebooks
+
+1. [Basic Ocean Surface Temperature](01_basic_ocean_surface_temperature.ipynb): writes monthly sea surface temperature (`tos_tavg-u-hxy-sea`) on a latitude-longitude grid.
+2. [Atmospheric Surface Air Temperature](02_atmos_surface_air_temperature.ipynb): writes 2 m air temperature (`tas_tavg-h2m-hxy-u`) and demonstrates the fixed-height coordinate.
+3. [Atmospheric Temperature On Pressure Levels](03_pressure_level_air_temperature.ipynb): writes air temperature (`ta_tavg-p19-hxy-air`) on the CMIP7 19 pressure levels.
+4. [Hybrid Sigma Humidity Tendency With Z-Factors](04_hybrid_sigma_humidity_tendency.ipynb): writes humidity tendency (`tnhusscpbl_tavg-al-hxy-u`) on a hybrid sigma pressure coordinate with CMOR zfactors and surface pressure.
+5. [Ocean Heat Transport By Basin](05_ocean_heat_transport_by_basin.ipynb): writes northward ocean heat transport (`htovgyre_tavg-u-hyb-sea`) using latitude and ocean basin coordinates.
+6. [Land-Use Fraction](06_land_use_fraction.ipynb): writes land-use fraction (`fracLut_tpt-u-hxy-u`) using time-point, land-use, latitude, and longitude coordinates.
+7. [Sea Ice Concentration On Projected Grids](07_non_lat_lon_sea_ice_concentration.ipynb): writes sea-ice area percentage (`siconc_tavg-u-hxy-u`) on projected Northern and Southern Hemisphere grids.
diff --git a/notebooks/data/fracLut_Emon_GFDL-ESM4_land-noLu_r1i1p1f1_gr1_200702-200711.nc b/notebooks/data/fracLut_Emon_GFDL-ESM4_land-noLu_r1i1p1f1_gr1_200702-200711.nc
new file mode 100644
index 00000000..3a962ddf
Binary files /dev/null and b/notebooks/data/fracLut_Emon_GFDL-ESM4_land-noLu_r1i1p1f1_gr1_200702-200711.nc differ
diff --git a/notebooks/data/htovgyre_Omon_UKESM1-0-LL_ssp370-lowNTCFCH4_r2i1p1f2_gnz_201501-204912.nc b/notebooks/data/htovgyre_Omon_UKESM1-0-LL_ssp370-lowNTCFCH4_r2i1p1f2_gnz_201501-204912.nc
new file mode 100644
index 00000000..662452c6
Binary files /dev/null and b/notebooks/data/htovgyre_Omon_UKESM1-0-LL_ssp370-lowNTCFCH4_r2i1p1f2_gnz_201501-204912.nc differ
diff --git a/notebooks/data/ice_conc_nh_ease2-250_cdr-v3p1_202002.nc b/notebooks/data/ice_conc_nh_ease2-250_cdr-v3p1_202002.nc
new file mode 100644
index 00000000..322cb34e
Binary files /dev/null and b/notebooks/data/ice_conc_nh_ease2-250_cdr-v3p1_202002.nc differ
diff --git a/notebooks/data/ice_conc_sh_ease2-250_cdr-v3p1_202002.nc b/notebooks/data/ice_conc_sh_ease2-250_cdr-v3p1_202002.nc
new file mode 100644
index 00000000..5ec8b0f7
Binary files /dev/null and b/notebooks/data/ice_conc_sh_ease2-250_cdr-v3p1_202002.nc differ
diff --git a/notebooks/data/ta_Amon_E3SM-3-0_historical_r1i1p1f1_gr_187001-187002.nc b/notebooks/data/ta_Amon_E3SM-3-0_historical_r1i1p1f1_gr_187001-187002.nc
new file mode 100644
index 00000000..4a4ef8ca
Binary files /dev/null and b/notebooks/data/ta_Amon_E3SM-3-0_historical_r1i1p1f1_gr_187001-187002.nc differ
diff --git a/notebooks/data/tas_Amon_GISS-E2-H_historical_r1i1p2_195101-195110.nc b/notebooks/data/tas_Amon_GISS-E2-H_historical_r1i1p2_195101-195110.nc
new file mode 100644
index 00000000..5450fab7
Binary files /dev/null and b/notebooks/data/tas_Amon_GISS-E2-H_historical_r1i1p2_195101-195110.nc differ
diff --git a/notebooks/data/tnhusscpbl_CFmon_MIROC-ES2L_amip_r2i1p1f2_gn_197901-197905.nc b/notebooks/data/tnhusscpbl_CFmon_MIROC-ES2L_amip_r2i1p1f2_gn_197901-197905.nc
new file mode 100644
index 00000000..21a59493
Binary files /dev/null and b/notebooks/data/tnhusscpbl_CFmon_MIROC-ES2L_amip_r2i1p1f2_gn_197901-197905.nc differ
diff --git a/notebooks/data/tos_Omon_CanCM4_decadal1982_r5i1p1_198301-198310.nc b/notebooks/data/tos_Omon_CanCM4_decadal1982_r5i1p1_198301-198310.nc
new file mode 100644
index 00000000..2332be0f
Binary files /dev/null and b/notebooks/data/tos_Omon_CanCM4_decadal1982_r5i1p1_198301-198310.nc differ
diff --git a/tools/rebuild_notebook_output.sh b/tools/rebuild_notebook_output.sh
new file mode 100755
index 00000000..b75a544c
--- /dev/null
+++ b/tools/rebuild_notebook_output.sh
@@ -0,0 +1,115 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+usage() {
+  cat <<'EOF'
+Usage:
+  tools/rebuild_notebook_output.sh [options] NOTEBOOK.ipynb [...]
+  tools/rebuild_notebook_output.sh [options] --all
+
+Executes CMOR example notebooks in place, then strips notebook metadata while
+keeping the regenerated outputs.
+
+Options:
+  --all              Rebuild every notebook in ./notebooks
+  --kernel NAME      Kernel name to execute with (default: python3)
+  --timeout SECONDS  Cell execution timeout; -1 disables it (default: -1)
+  -h, --help         Show this help
+EOF
+}
+
+die() { echo "error: $*" >&2; exit 1; }
+
+script_dir="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+repo_root="$(cd -- "${script_dir}/.." && pwd)"
+notebooks_dir="${repo_root}/notebooks"
+
+kernel_name="python3"
+timeout="-1"
+all_notebooks="0"
+notebook_args=()
+
+while [[ $# -gt 0 ]]; do
+  case "$1" in
+    --all)
+      all_notebooks="1"
+      shift
+      ;;
+    --kernel)
+      [[ $# -ge 2 ]] || die "--kernel requires a value"
+      kernel_name="$2"
+      shift 2
+      ;;
+    --timeout)
+      [[ $# -ge 2 ]] || die "--timeout requires a value"
+      timeout="$2"
+      shift 2
+      ;;
+    -h|--help)
+      usage
+      exit 0
+      ;;
+    --)
+      shift
+      notebook_args+=("$@")
+      break
+      ;;
+    -*)
+      die "unknown argument: $1 (use --help)"
+      ;;
+    *)
+      notebook_args+=("$1")
+      shift
+      ;;
+  esac
+done
+
+command -v jupyter >/dev/null 2>&1 || die "jupyter not found in PATH"
+command -v nbstripout >/dev/null 2>&1 || die "nbstripout not found in PATH"
+[[ -d "${notebooks_dir}" ]] || die "missing notebooks directory: ${notebooks_dir}"
+[[ "${timeout}" =~ ^-?[0-9]+$ ]] || die "--timeout must be an integer"
+
+if [[ "${all_notebooks}" == "1" && ${#notebook_args[@]} -gt 0 ]]; then
+  die "use either --all or explicit notebook paths, not both"
+fi
+
+notebooks=()
+if [[ "${all_notebooks}" == "1" ]]; then
+  shopt -s nullglob
+  notebooks=("${notebooks_dir}"/*.ipynb)
+  shopt -u nullglob
+else
+  [[ ${#notebook_args[@]} -gt 0 ]] || die "missing NOTEBOOK.ipynb path (or use --all)"
+  for notebook_arg in "${notebook_args[@]}"; do
+    if [[ "${notebook_arg}" = /* ]]; then
+      notebook_path="${notebook_arg}"
+    else
+      notebook_path="${PWD}/${notebook_arg}"
+    fi
+
+    [[ -f "${notebook_path}" ]] || die "not a file: ${notebook_arg}"
+    [[ "${notebook_path}" == *.ipynb ]] || die "not a notebook: ${notebook_arg}"
+    notebooks+=("${notebook_path}")
+  done
+fi
+
+[[ ${#notebooks[@]} -gt 0 ]] || die "no notebooks found"
+
+for notebook in "${notebooks[@]}"; do
+  echo "Rebuilding ${notebook#${repo_root}/}"
+  jupyter nbconvert \
+    --to notebook \
+    --execute \
+    --inplace \
+    --ExecutePreprocessor.cwd="${notebooks_dir}" \
+    --ExecutePreprocessor.kernel_name="${kernel_name}" \
+    --ExecutePreprocessor.timeout="${timeout}" \
+    "${notebook}"
+
+  nbstripout \
+    --keep-output \
+    --extra-keys "metadata.kernelspec metadata.language_info metadata.widgets" \
+    "${notebook}"
+done
+
+echo "Rebuilt ${#notebooks[@]} notebook(s)."