diff --git a/notebooks/bdt/hhh_qcd_bdt.ipynb b/notebooks/bdt/hhh_qcd_bdt.ipynb
index 278806d..64825d8 100644
--- a/notebooks/bdt/hhh_qcd_bdt.ipynb
+++ b/notebooks/bdt/hhh_qcd_bdt.ipynb
@@ -679,7 +679,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/benchmark/west/target_weight.ipynb b/notebooks/benchmark/west/target_weight.ipynb
new file mode 100644
index 0000000..ee40fb1
--- /dev/null
+++ b/notebooks/benchmark/west/target_weight.ipynb
@@ -0,0 +1,696 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "196b974a-5d35-4859-96b3-5fc9d09a6975",
+   "metadata": {},
+   "source": [
+    "# A Notebook for Calculating Weight by Target Weight Distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "424892ff-7157-40b2-9945-8bee958aa985",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import shutil\n",
+    "import h5py as h5\n",
+    "import numpy as np\n",
+    "import mplhep as hep\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "import awkward as ak\n",
+    "\n",
+    "import vector\n",
+    "vector.register_awkward()\n",
+    "vector.register_numba()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ad71eb3-d698-405d-8498-5c3c8f191af5",
+   "metadata": {},
+   "source": [
+    "## load dataset and get the target weight distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d94b9676",
+   "metadata": {},
+   "source": [
+    "### simple load dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8f45c2e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def awk2npy(arr):\n",
+    "    return np.array(arr)[..., np.newaxis]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "120e02eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result_path = \"/Users/billyli/UCSD/hhh_bdt/data/delphes/v2/merged_training_all_w_weights.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f41f38eb-dffe-4bd2-996f-247465e27f5a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f = h5.File(result_path, 'r')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a60aecaa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<KeysViewHDF5 ['b1', 'b2', 'mask', 'mh', 'pt']>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f['TARGETS']['h1'].keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "abe2c262",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh{i}_mass = awk2npy(f[\\'TARGETS\\'][\\'h{i}\\'][\\'mh\\'])\")\n",
+    "    exec(f\"bh{i}_mass = awk2npy(f[\\'TARGETS\\'][\\'bh{i}\\'][\\'mh\\'])\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "41e6e532",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh{i}_mask = awk2npy(f[\\'TARGETS\\'][\\'h{i}\\'][\\'mask\\'])\")\n",
+    "    exec(f\"bh{i}_mask = awk2npy(f[\\'TARGETS\\'][\\'bh{i}\\'][\\'mask\\'])\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "04dafd3b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rh_mass_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh_mass_list.append(rh{i}_mass)\")\n",
+    "rh_mass = np.concatenate(rh_mass_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "66df5b9c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rh_mask_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh_mask_list.append(rh{i}_mask)\")\n",
+    "rh_mask = np.concatenate(rh_mask_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c38bccee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bh_mass_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"bh_mass_list.append(bh{i}_mass)\")\n",
+    "bh_mass = np.concatenate(bh_mass_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "041a8fe2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bh_mask_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"bh_mask_list.append(bh{i}_mask)\")\n",
+    "bh_mask = np.concatenate(bh_mask_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d1359006",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "j_pt = np.array(f[\"INPUTS\"][\"Jets\"][\"pt\"])\n",
+    "j_eta = np.array(f[\"INPUTS\"][\"Jets\"][\"eta\"])\n",
+    "j_phi = np.array(f[\"INPUTS\"][\"Jets\"][\"phi\"])\n",
+    "j_mass = np.array(f[\"INPUTS\"][\"Jets\"][\"mass\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2fb58110",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "js = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": j_pt,\n",
+    "            \"eta\": j_eta,\n",
+    "            \"phi\": j_phi,\n",
+    "            \"mass\": j_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\",\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "421ec331",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh{i}_b1s = awk2npy(f[\\\"TARGETS\\\"][\\\"h{i}\\\"][\\\"b1\\\"])\")\n",
+    "    exec(f\"rh{i}_b2s = awk2npy(f[\\\"TARGETS\\\"][\\\"h{i}\\\"][\\\"b2\\\"])\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "dcce01f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rh_b1_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh_b1_list.append(rh{i}_b1s)\")\n",
+    "rh_b1 = np.concatenate(rh_b1_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "017c68c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rh_b2_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh_b2_list.append(rh{i}_b2s)\")\n",
+    "rh_b2 = np.concatenate(rh_b2_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "849f6bda",
+   "metadata": {},
+   "source": [
+    "### calculate resolved reco mass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "95c12362",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "b1s = js[np.arange(rh_b1.shape[0])[:, None], rh_b1]\n",
+    "b2s = js[np.arange(rh_b2.shape[0])[:, None], rh_b2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "9b6f1712",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rH_reco = (b1s+b2s)[rh_mask]\n",
+    "rH_reco_mass = rH_reco.M"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ec109a1",
+   "metadata": {},
+   "source": [
+    "### plot the resolved Higgs mass distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "27e096fd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(rH_reco_mass, bins=np.arange(30, 230, 5), density=True)\n",
+    "plt.title(\"Reconstructed Resolved Mass Distribution\")\n",
+    "plt.xlabel('Reco Resolved Higgs Mass (GeV)')\n",
+    "plt.style.use(hep.style.CMS)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3fde24ea",
+   "metadata": {},
+   "source": [
+    "### calculate boosted reco mass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "a266f174",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fj_pt = np.array(f[\"INPUTS\"][\"BoostedJets\"][\"fj_pt\"])\n",
+    "fj_eta = np.array(f[\"INPUTS\"][\"BoostedJets\"][\"fj_eta\"])\n",
+    "fj_phi = np.array(f[\"INPUTS\"][\"BoostedJets\"][\"fj_phi\"])\n",
+    "fj_mass = np.array(f[\"INPUTS\"][\"BoostedJets\"][\"fj_mass\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "706f5051",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fjs = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": fj_pt,\n",
+    "            \"eta\": fj_eta,\n",
+    "            \"phi\": fj_phi,\n",
+    "            \"mass\": fj_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\",\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "26c1db55",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range(1, 4):\n",
+    "    exec(f\"bh{i}_bbs = awk2npy(f[\\\"TARGETS\\\"][\\\"bh{i}\\\"][\\\"bb\\\"])\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "780bd32c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bh_bb_list = []\n",
+    "for i in range(1, 4):\n",
+    "    exec(f\"bh_bb_list.append(bh{i}_bbs)\")\n",
+    "bh_bb = np.concatenate(bh_bb_list, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "57fbf12f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bb = fjs[np.arange(len(fjs))[:, None], bh_bb]\n",
+    "bH_reco = bb[bh_mask]\n",
+    "bH_reco_mass = bH_reco.M"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4645f764",
+   "metadata": {},
+   "source": [
+    "### plot the boosted Higgs reco mass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "3d17a556",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(1, 0, 'Target Boosted Higgs Reco Mass (GeV)')"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(bH_reco_mass, bins=np.arange(30, 230, 5))\n",
+    "plt.title(\"Target Boosted Higgs Reco Mass Distribution\")\n",
+    "plt.xlabel('Target Boosted Higgs Reco Mass (GeV)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41a2d177-3d1a-49fa-999c-322b36edcef7",
+   "metadata": {},
+   "source": [
+    "## Get the weight of each target"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "973ba9f2",
+   "metadata": {},
+   "source": [
+    "### get the weights of the resolved targets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "2dfc4465-bcdc-4a43-aad1-1d8968a77fab",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "\"Unable to open object (object 'WEIGHT' doesn't exist)\"",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [39], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m4\u001b[39m):\n\u001b[0;32m----> 2\u001b[0m     \u001b[43mexec\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrh\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mi\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_mass = awk2npy(f[\u001b[39;49m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43mTARGETS\u001b[39;49m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43m][\u001b[39;49m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43mh\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mi\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43m][\u001b[39;49m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43mWEIGHT\u001b[39;49m\u001b[38;5;130;43;01m\\'\u001b[39;49;00m\u001b[38;5;124;43m])\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      3\u001b[0m     exec(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbh\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_mass = awk2npy(f[\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124mTARGETS\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m][\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124mbh\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m][\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124mWEIGHT\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m])\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "File \u001b[0;32m<string>:1\u001b[0m\n",
+      "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32m~/miniforge_x86_new/lib/python3.9/site-packages/h5py/_hl/group.py:357\u001b[0m, in \u001b[0;36mGroup.__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m    355\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid HDF5 object reference\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    356\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(name, (\u001b[38;5;28mbytes\u001b[39m, \u001b[38;5;28mstr\u001b[39m)):\n\u001b[0;32m--> 357\u001b[0m     oid \u001b[38;5;241m=\u001b[39m \u001b[43mh5o\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_e\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlapl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_lapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    358\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    359\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAccessing a group is done with bytes or str, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    360\u001b[0m                     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnot \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mtype\u001b[39m(name)))\n",
+      "File \u001b[0;32mh5py/_objects.pyx:54\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mh5py/_objects.pyx:55\u001b[0m, in \u001b[0;36mh5py._objects.with_phil.wrapper\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mh5py/h5o.pyx:189\u001b[0m, in \u001b[0;36mh5py.h5o.open\u001b[0;34m()\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: \"Unable to open object (object 'WEIGHT' doesn't exist)\""
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(1, 4):\n",
+    "    exec(f\"rh{i}_mass = awk2npy(f[\\'TARGETS\\'][\\'h{i}\\'][\\'WEIGHT\\'])\")\n",
+    "    exec(f\"bh{i}_mass = awk2npy(f[\\'TARGETS\\'][\\'bh{i}\\'][\\'WEIGHT\\'])\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "1e94bef9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<KeysViewHDF5 ['b1', 'b2', 'mask', 'mh', 'pt']>"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53196c44",
+   "metadata": {},
+   "source": [
+    "### find which bin a target is"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "de0029d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# caluclate target reco mass\n",
+    "resolved_target_mass = (b1s+b2s).M\n",
+    "boosted_target_mass = bb.M"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e975f6b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# find which mass bin the target is\n",
+    "resolved_mass_bin_idx = np.digitize(resolved_target_mass, bins)\n",
+    "boosted_mass_bin_idx = np.digitize(boosted_target_mass, bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "319e1220",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "resolved_target_weight = ak.ones_like(resolved_target_mass)\n",
+    "resolved_target_weight = np.array(resolved_target_weight)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "325e5f87",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boosted_target_weight = ak.ones_like(boosted_target_mass)\n",
+    "boosted_target_weight = np.array(boosted_target_weight)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "6b5340b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# first and last bin weight is one\n",
+    "for i in range(1, len(bins)):\n",
+    "    resolved_in_bin_i = resolved_mass_bin_idx == i\n",
+    "    boosted_in_bin_i = boosted_mass_bin_idx == i\n",
+    "    \n",
+    "    resolved_target_weight[resolved_in_bin_i] = rH_weight[i-1]\n",
+    "    boosted_target_weight[boosted_in_bin_i] = bH_weight[i-1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "87824ef5",
+   "metadata": {},
+   "source": [
+    "## Plot weights"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "1d2c649d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<BarContainer object of 20 artists>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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iiIi44YYb4rTTTouqqqpi+3nnnRdnnXVW3HjjjTF//vw488wz4/7774+IiCzL4oILLogsy6K6ujp+//vfxy677FIce/zxx8eYMWPiU5/6VKxYsSIuvPDCeOKJJ9aYHwAAYH10aCdoyZIl8dvf/jYiInbddde1AlBERN++feOHP/xh7LTTThER8cADD0RjY2NEREyfPj2eeuqpiIg48sgj1whALXbdddc48sgjIyLiqaeeihkzZnTsFQEAALSjQyHohRdeiOXLl0dExDHHHNPmDk3fvn3ji1/8YvHPzz33XERE3HPPPcXHjjjiiDafZ/W2qVOndqREAACAdnUoBBUKheLxiBEj2u07dOjQ4nHL6XOrfz5o7NixbY5dva2tiysAAAB0Roc+E7TTTjvF5MmTIyJi//33b7fv008/XTweNWpURES88847ERFRU1MTgwYNanPsoEGDYsCAAbFo0aK1LqwAAACwPjoUgrbbbrvYbrvt1tlv+vTp8R//8R8REVFXVxdjxoyJiIh33303IqLdANRi8ODBsWjRomJwAgAAKIcOXx1uXaZNmxbjxo2LFStWRETEBRdcEH379o2I/90JarkMdnsGDx4cb731VixatGidfbMsiwULFnS65n79+kW/fv06PR4AAFg/S5cujaVLl3Z6fJZlJfctWwhasGBBTJw4Ma655ppiAPrKV74Sp5566hp9IiI22WSTdc7XEkpaPk/Unjlz5sTmm2/embIjIuKSSy6JSy+9tNPjAQCA9TNx4sSYMGFClzzXeoeg5cuXxy233BKXXnppzJ07t/j4SSedFDfeeGP06vW/117YeuutY86cOTFv3rx1ztvSp5TANGzYsHj55Zc7XHsLu0AAAFBZF1xwQZx99tmdHj9mzJiYM2dOSX3XKwQ9//zzceKJJxYvgR0Rse2228ZNN90Uhx566Fr9hw4dGnPmzImmpqZ1zt3Sp6amZp19q6qqYuDAgR2oHAAA6E7W9yMqbd2+pzUdukR2i+bm5rj44otjjz32KAagQYMGxbXXXhszZ85sNQBFRHzkIx+JiFUBp71z9rIsiw8++CAiIrbZZpvOlAgAANCqDoegLMsil8vF5ZdfHitWrIiqqqo444wzYtasWXH22WdH//792xzbcu+gZcuWtXvp65kzZxZvylpfX9/REgEAANrU4RB0+eWXx6RJkyIiora2Nv70pz/FddddF1tsscU6x+6+++7F47vvvrvNfqu37bPPPh0tEQAAoE0dCkELFiyIf/u3f4uIiC233DIee+yxDoWUcePGFc/Vu+OOO1o9JS7LsrjzzjsjYtV5fYcffnhHSgQAAGhXh0LQlClTivftueKKK2L77bfv0JMNGzYsxo8fHxERTz75ZNx8881r9Zk0aVI88cQTERFx/PHHF0+hAwAAKIcOXR3u0UcfLR4PGDAg7r///pLG7bnnnjFo0KCIiPj+978fDzzwQDQ1NcWpp54ajz/+eBx66KGxcuXKmDp1akyZMiUiVt0s9fLLL+9IeQAAAOvUoRBUKBSKx1//+tdLHvfII4/EAQccEBERI0eOjN/97nfxpS99KebOnRs///nP4+c///ka/YcMGRJ33XVXjBgxoiPlAQAArFOHTodbPQStj/322y9efPHFuPDCC6O+vj4GDBgQNTU1seOOO8Z3v/vdeOmll2Lvvfcuy3MBAACsrkM7QTNmzCjbE9fW1sYVV1wRV1xxRdnmBAAAWJdO3SwVAABgYyUEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJJSXekCyqFQKER9fX2rbblcLnK5XBdXBAAAlFs+n498Pt9qW6FQKHmeHhGCamtro6GhodJlAAAAG1B7Gxx1dXXR2NhY0jxOhwMAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUqorXQAAAFTayPOntvr47CsP6+JK6Ap2ggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkpbrSBZRDoVCI+vr6VttyuVzkcrkurggAACi3fD4f+Xy+1bZCoVDyPD0iBNXW1kZDQ0OlywAAADag9jY46urqorGxsaR5nA4HAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSUl3pAsqhUChEfX19q225XC5yuVwXVwQAAJRbPp+PfD7faluhUCh5nh4Rgmpra6OhoaHSZQAAABtQexscdXV10djYWNI8TocDAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkVFe6gHIoFApRX1/falsul4tcLtfFFQEAAOWWz+cjn8+32lYoFEqep0eEoNra2mhoaKh0GQAAwAbU3gZHXV1dNDY2ljSP0+EAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUsoWgvL5fFRVVcWll17abr/m5ubo169fVFVVlfQ1e/bscpUIAABQvhB0++23l9TvrbfeimXLlpXraQEAADqkuhyTTJ48OZ544omS+r766qvF45tuuilGjBjRbv/a2tr1qg0AAGB1nQ5B8+fPj+nTp8fkyZNL3gWKWDMEffWrX40BAwZ0tgQAAIAO61QI2nPPPePpp5/u1BO2hKC6ujoBCAAA6HKd+kzQe++91+knbAlBo0aN6vQcAAAAndWpnaCZM2dGlmXFP7/55puxww47lDT270PQkiVL4o033oh33303ttpqq9hhhx2iT58+nSkLAABgnTq1E9SvX7/o379/8atfv34ljVu+fHm8/vrrxTlOOeWU2GyzzaK+vj4OOuig+OQnPxmDBw+Ob37zm/H22293pjQAAIB2leXqcKWaPXt2NDc3R0TEdddd12qfhQsXxq233hp33nln3HXXXfHpT396nfNmWRYLFizodF39+vUrOcgBALB+Rp4/tdXHZ195WBdXQneydOnSWLp0aafHr36m2rqU7T5BpVj9ynAREePHj4/nnnsuFi1aFLNnz4677rordtlll4iIaGpqiiOPPDL++te/rnPeOXPmxOabb97pr4kTJ26Q1wsAAJRm4sSJ6/Uz/Zw5c0p+ri7dCZo1a1b07t07IiK+973vxcUXXxxVVVURETFixIgYMWJEjB07No477ri44447oqmpKS677LKYNGlSu/MOGzYsXn755U7XZRcIAAAq64ILLoizzz670+PHjBlTchDq0hB0+umnx+mnn95unz59+sR1110X999/fyxatCh+/etfRz6fj+rqtkutqqqKgQMHlrtcAACgi6zvR1RaNldK0aWnw5Vq+PDhsffee0dExLx582LWrFkVrggAAOgpumUIiog1Lrn9/vvvV7ASAACgJ+m2IWjFihXF480337yClQAAAD1Jl4WgRYsWxc477xw77bRTnHfeeevs33Khgz59+sSIESM2dHkAAEAiuiwEDRgwIIYPHx4zZsyIG2+8MT744IM2+86YMSMee+yxiIjYf//9o6ampqvKBAAAerguPR3uq1/9akSs2hUaP358qzdDamxsjBNOOKF4Olwpu0YAAACl6tJLZB977LHx61//Ou666674/e9/H6NGjYqTTz45Ro0aFQsWLIiXXnopfvrTn8bChQsjIuK0006Lz372s11ZIgAA0MN1aQjq1atX/OIXv4gjjjgiHn744XjrrbfioosuWqtfVVVVnHPOOTFx4sSuLA8AAEhAl4agiIiampp48MEH46GHHop8Ph+vvvpqvPnmm5FlWWyzzTZx0EEHxWmnnRY77rhjV5cGAAAkoCwhaOTIkZFlWcn9q6qq4pBDDolDDjmkHE/frYw8f+paj82+8rAKVAIAALSm294nCAAAYEMQggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSUl3pAsqhUChEfX19q225XC5yuVwXVwQAAJRbPp+PfD7faluhUCh5nh4Rgmpra6OhoaHSZQAAABtQexscdXV10djYWNI8TocDAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkVFe6gHIoFApRX1/falsul4tcLtfFFQEAAOWWz+cjn8+32lYoFEqep0eEoNra2mhoaKh0GQAAwAbU3gZHXV1dNDY2ljSP0+EAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACAp1ZUuoBwKhULU19e32pbL5SKXy3VxRQAAQLnl8/nI5/OtthUKhZLn6REhqLa2NhoaGipdBgAAsAG1t8FRV1cXjY2NJc3jdDgAACApQhAAAJAUIQgAAEiKEAQAACSlR1wYAQCA1o08f2qrj8++8rAurgS6DztBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAklJd6QLKoVAoRH19fattuVwucrlcF1cEAACUWz6fj3w+32pboVAoeZ4eEYJqa2ujoaGh0mUAAAAbUHsbHHV1ddHY2FjSPE6HAwAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACSlutIFNDY2xptvvhkRESNGjIjhw4dXuCIAAKAnK9tOUD6fj6qqqrj00ktL6n/ffffFHnvsEXV1dbHvvvvGvvvuG3V1dbH77rvHvffeW66yAAAA1lC2naDbb7+95L7XXnttnHPOOa22TZs2LQ477LC4+uqr2+xD6UaeP7XVx2dfeVgXVwIAAN1DWXaCJk+eHE888URJfR9++OE499xzIyJiq622iilTpkRTU1M0NTXF7bffHoMHD46IiHPPPTceeuihcpQHAABQ1OmdoPnz58f06dNj8uTJJe8CZVkWF1xwQWRZFtXV1fH73/8+dtlll2L78ccfH2PGjIlPfepTsWLFirjwwgvjiSeeiKqqqs6WCQAAsIZO7QTtueeescUWW8RnPvOZmDx5cixfvrykcdOnT4+nnnoqIiKOPPLINQJQi1133TWOPPLIiIh46qmnYsaMGZ0pEQAAoFWdCkHvvfdep57snnvuKR4fccQRbfZbvW3q1NY/0wIAANAZnQpBM2fOjMWLFxe//vKXv5Q8rsXYsWPb7Ld627PPPtuZEgEAAFrVqc8E9evXr90/t+Wdd96JiIiampoYNGhQm/0GDRoUAwYMiEWLFq0RnAAAANZX2e4TVIp33303IqLdANSi5SpxLcEJAACgHMp2n6BStASaloDTnsGDB8dbb70VixYtWmffLMtiwYIFna6rX79+Je9mAQAA5bd06dJYunRpp8dnWVZy3y4NQS1BZZNNNlln35ZQsnjx4nX2nTNnTmy++eadruuSSy6JSy+9tNPjAQCA9TNx4sSYMGFClzxXl4agrbfeOubMmRPz5s1bZ9+WPqUEpmHDhsXLL7/c6brsAgEAQGVdcMEFcfbZZ3d6/JgxY2LOnDkl9e3SEDR06NCYM2dONDU1rbNvS5+ampp19q2qqoqBAweud30AAEBlrO9HVKqqqkru26UXRvjIRz4SEasCTnvn7GVZFh988EFERGyzzTZdUhsAAJCGLg1BQ4cOjYiIZcuWtXvp65kzZ8by5csjIqK+vr5LagMAANLQpSFo9913Lx7ffffdbfZbvW2fffbZoDUBAABp6dIQNG7cuOK5enfccUerp8RlWRZ33nlnRKw6r+/www/vyhIBAIAerktD0LBhw2L8+PEREfHkk0/GzTffvFafSZMmxRNPPBEREccff3zxFDoAAIBy6NKrw0VEfP/7348HHnggmpqa4tRTT43HH388Dj300Fi5cmVMnTo1pkyZEhGrbpZ6+eWXd3V5AABAD9flIWjkyJHxu9/9Lr70pS/F3Llz4+c//3n8/Oc/X6PPkCFD4q677ooRI0Z0dXkAAEAP16Wnw7XYb7/94sUXX4wLL7ww6uvrY8CAAVFTUxM77rhjfPe7342XXnop9t5770qUBgAA9HBl2QkaOXJku/f9aU1tbW1cccUVccUVV5SjBAAAgJJUZCcIAACgUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKqK11AORQKhaivr2+1LZfLRS6X6+KKAACAcsvn85HP51ttKxQKJc/TI0JQbW1tNDQ0VLoMAABgA2pvg6Ouri4aGxtLmsfpcAAAQFKEIAAAIClCEAAAkJQe8ZkgAIDuYOT5U1t9fPaVh3VxJUB77AQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkpbrSBZRDoVCI+vr6VttyuVzkcrkurggAACi3fD4f+Xy+1bZCoVDyPD0iBNXW1kZDQ0OlywAAADag9jY46urqorGxsaR5nA4HAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKRUV7oA0jPy/KmtPj77ysO6uBIAAFJkJwgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUqorXUA5FAqFqK+vb7Utl8tFLpfr4ooAAIByy+fzkc/nW20rFAolz9MjQlBtbW00NDRUugwAAGADam+Do66uLhobG0uax+lwAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEmprnQBAACdNfL8qa0+PvvKw7q4EmBjYicIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJJSXekCyqFQKER9fX2rbblcLnK5XBdXBAAAlFs+n498Pt9qW6FQKHmeHhGCamtro6GhodJlAAAAG1B7Gxx1dXXR2NhY0jxOhwMAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJKVH3CwV1tfI86e2+vjsKw/r4koAANjQ7AQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJJSsRD02c9+Nqqqqkr6+tnPflapMgEAgB6mYiHolVdeqdRTAwAACauuxJMuWbIk3n777YiIOO2002LcuHHt9v/EJz7RFWUBAAAJqEgImjVrVmRZFhERX/ziF+MLX/hCJcoAAAASVJHT4V599dXi8ahRoypRAgAAkKiKhqA+ffrEiBEjKlECAACQqIqcDtcSgrbffvuorq6O5ubmePvtt2P27Nmx2Wabxcc//vEYOHBgJUoDAAB6uIrsBLVcGW7o0KExceLEGDJkSHz0ox+NAw88MHbfffcYPHhwHHroofHEE09UojwAAKAHq+jpcI888khceOGF0dTUtEb7ihUr4v7774999903rr/++kqUCAAA9FBdfjrcokWLYs6cOcU/77LLLnHVVVfFHnvsEStWrIgXX3wxbrrppvjVr34VK1eujDPOOCO23377GDt2bJtzZlkWCxYs6HRN/fr1i379+nV6PAAAsH6WLl0aS5cu7fT4lqtPl6LLQ9CsWbOid+/eERExduzY+Pd///eoqakpth9wwAFxwAEHxKc+9ak4++yzIyLi29/+dnzhC1+IXr1a37iaM2dObL755p2u6ZJLLolLL7200+MBAID1M3HixJgwYUKXPFeXh6BPfvKTsWLFinX2O+OMM2LKlCkxbdq0+Mtf/hLPP/987Lrrrq32HTZsWLz88sudrskuEAAAVNYFF1xQ3ATpjDFjxqxxxll7KnJ1uFL07t07jjrqqJg2bVpERDz99NNthqCqqipXkwMAgI3Y+n5EpaqqquS+FbkwQql22GGH4vH7779fwUoAAICeoluHoNVPm1ufz/wAAAC06PIQdPzxx8dOO+0UBx98cKxcubLdvqt/zmfUqFEbujQAACABXR6Cdt5555gxY0Y8/PDD8eCDD7bZb/HixfGLX/wiIiJqampiv/3266oSAQCAHqzLQ9D48eOLl7o+8cQT4+23316rz+LFi+P000+P119/PSJWXSluk0026dI6AQCAnqnLrw63zTbbxLXXXhtnnXVWNDY2xpgxY+KUU06JnXfeOaqrq+Pll1+OX/7yl/Haa69FRMRuu+0WF110UVeXCQAA9FAVuUT2mWeeGY2NjfGDH/wgFi1aFD/4wQ9a7ff5z38+/v3f/90uEAAAUDYVuTpcVVVVXH311dHQ0BD/9E//FLvttltstdVW0bdv39h2221j/Pjxce+998Z9990XgwYNqkSJAABAD1XRm6WOHj06br311kqWAAAAJKaiIQgA2HiMPH9qq4/PvvKwLq4EYP1065ulAgAAlJsQBAAAJEUIAgAAkiIEAQAASRGCAACApLg6HHRTrsIEALBh2AkCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEmprnQB5VAoFKK+vr7VtlwuF7lcrosrAgAAyi2fz0c+n2+1rVAolDxPjwhBtbW10dDQUOkyAACADai9DY66urpobGwsaR6nwwEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUqorXQCwcRh5/tRWH5995WFdXAkAwPqxEwQAACRFCAIAAJIiBAEAAEkRggAAgKS4MAIAdEMuRgKw4dgJAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJqa50AeVQKBSivr6+1bZcLhe5XK6LKwIAAMotn89HPp9vta1QKJQ8T48IQbW1tdHQ0FDpMoAuNvL8qa0+PvvKw7q4EgCgK7S3wVFXVxeNjY0lzeN0OAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApPSI+wQBwPpwzymAtNgJAgAAkiIEAQAASXE6HEAZOa0KALo/O0EAAEBShCAAACApQhAAAJAUIQgAAEiKCyMA0OVau4CEi0cA0FWEIIAezhXrAGBNTocDAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEmprnQB5VAoFKK+vr7VtlwuF7lcrosrAgAAyi2fz0c+n2+1rVAolDxPjwhBtbW10dDQUOkyAACADai9DY66urpobGwsaR6nwwEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQFCEIAABIihAEAAAkRQgCAACSIgQBAABJEYIAAICkCEEAAEBShCAAACApQhAAAJAUIQgAAEiKEAQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKqK11AORQKhaivr2+1LZfLRS6X6+KKAACAcsvn85HP51ttKxQKJc/TI0JQbW1tNDQ0VLoMAABgA2pvg6Ouri4aGxtLmsfpcAAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUJQIrIVy2Pen6ZEtmJ5pUthI2ctUS7WEuVkPVEu1lIahKBEZM3LY/5jv4ys2T9o1o+1RLlYS5ST9US5WEtpEIIAAICkCEEAAEBShCAAACApQhAAAJCU6koXEBHxwQcfxOuvvx4LFy6MYcOGxcc+9rHo1Us+AwAAyq+iSeOVV16JcePGxdZbbx277757HHjggTF69OgYOXJkXHvttdHc3FzJ8gAAgB6oYiHof/7nf2KXXXaJe+65Z62w8/bbb8c555wTX/rSlwQhAACgrCoSgv7f//t/cdRRR8Xf/va36NWrV/zrv/5rvP322/Hhhx/Gww8/HLvssktERPzXf/1X/Ou//mtJc+bz+Q1ZcqcsfPaeSpfQ7XXH90hNG6fu+B6paePUHd8jNW2cuuN7pKaNU3d8j7pjTYsWLSq5b0VC0FVXXRXvv/9+RET8+Mc/josvvjjq6upiwIABceCBB8Yf//jHGDlyZEREXHvttTF37tx1ztk9Q9DUSpfQ7XXH90hNG6fu+B6paePUHd8jNW2cuuN7pKaNU3d8j7pjTR9++GHJfbs8BDU3N8dtt90WERFDhgyJU089da0+AwcOjHPOOSciViW6X/3qV11aIwAA0HN1eQh64oknirtA48aNi969e7fa7/DDDy8eT53a/ZImAACwceryEDRz5szi8dixY9vst80228QnP/nJiIh49tlnN3hdAABAGro8BL3zzjvF4xEjRrTbd5tttomIiPfeey/mzZu3IcsCAAAS0eUh6N133y0eDxo0qN2+gwcPLh6vHp4AAAA6qyrLsqwrn/CYY46JO+64IyIi5s+fHwMHDmyz79lnnx0//OEPIyLi6aefjt13332N9r59+8by5cujV69e0atXrxgyZEinaqqqqurUuNa8O39J8bj5b/Oi96ZbxEc271+2+TtfTxbNHzZF75pBEVHVTWr63/coItT0d7pbTdZSadRUmlU1WUvtUVNputv/Td37PVJTe6yldeuKmtYnmsyZMyciIvr06RPLli1rt2+Xh6DPfe5z8Yc//CEiIpYtWxZ9+vRps+8FF1wQV155ZUREPProo/HpT396jfbevXvHypUrN1yxAADARqVXr17R3Nzcbp/qLqqlaOutty4ez5s3b40//73VPwe0ySabrNXev3//WLJkSfTu3bvdedalnDtBAABA56zP/szcuXOjubk5+vdf985Ul4egoUOHFo+bmpraDS9NTU3F45qamrXaO3JXWAAAgIgKXBjhIx/5SPF49ZDTmg8++KB4PHz48A1WEwAAkI4uD0Gr7wS98MILbfZbuXJlvPjiixERse2228Zmm222wWsDAAB6vi4PQatf4e3uu+9us9+0adOKl9PeZ599NnhdAABAGro8BI0ePTpGjx4dEREPPfTQGqe8re7OO+8sHh911FFdUhsAANDzdXkIilh1/5+IiKVLl8bpp5++1mWun3vuufjRj34UEREf/ehH48gjj+ziCgEAgJ6qy+8TFBGxfPny2G+//eKpp56KiIjPfOYz8Y1vfCMGDhwYTz31VNx4443x4YcfRlVVVfzud7+LcePGdXWJG5UVK1bE66+/Hu+99158/OMfjyFDhnTost+NjY3x5ptvRkTEiBEjXISCVq3vOlm5cmXMmjUrGhsbo6amJrbffvvYcsstN0Sp9HDWEuVkPdFi2bJl8frrr8e7774b2267bYwcOTJ69Sp9v2D58uXx2muvxbvvvhtbbrllbL/99j7T3p1lFfLOO+9ku+yySxYRrX716dMn+8lPflKp8jYKL7zwQva5z30u69Onzxrv3ZZbbpl95zvfyebPn9/u+HvvvTfbfffd13rvd9ttt2zq1Kld9CroajfccEMWEdkll1xSUv/1XSfNzc3ZD37wg2zbbbddY3zv3r2zww47LPvLX/6ynq+ISunoWpo+fXp2+umnZwcddFC2zTbbZDU1Ndnuu++efeMb38gefPDBdY63lnq2jq6n1syePTvbYostsojIHnnkkXb7Wk89V0fX0rx587IzzzwzGzRo0BprYdNNN80uuOCC7MMPP2x3/JIlS7KLLroo23rrrdcY379//+y4447LGhsby/CqKLeKhaAsy7KlS5dm119/fbb33ntngwYNyvr27ZuNHDkyO+mkk7Lp06dXsrRu70c/+lHWq1evNkNkRGS1tbXZzJkzWx1/zTXXtDs2IrKrr766i18VXWGvvfYq+ZvD+q6TFStWZEceeWS74zfZZJPsv//7v8v4CukqHVlLV1xxRVZVVdXuWjj22GOzQqHQ6nhrqefryHpqzfLly7N99tmnuB7aC0HWU8/WkbX02muvZSNGjGh3LYwaNarNXyx/+OGH2ac+9al2xw8ePDh7+eWXy/wqWV8VDUF0zmOPPZb17t27uOtz/fXXZ6+//nq2cOHCbNq0adnXvva14j+8XXbZJVuyZMka4x966KHiDyNbbbVVNmXKlKypqSlramrKbr/99mzw4MHF8aX8dpaNx2233Vb8u13XN4dyrJNLLrmk2GfXXXfNHnnkkezDDz/M3n777WzChAnFID9o0KDsvffe2wCvmA2lI2vpZz/7WbFvdXV1duqpp2a33nprNmXKlOy8885b47evu+yyS/a3v/1trTmspZ6tI+upLRdddNEaP3i2F4Ksp56rI2tp4cKF2Q477JBFRFZVVZWde+652SuvvJJ9+OGH2dNPP52NHTt2jV/StObrX/96sc8hhxySPfXUU9nf/va37LXXXsu+9a1vFds+9rGPrfXzGJUlBG2EDj744OI/2EcffbTVPt/85jeL//B+8YtfFB9fuXJltueeexZ/GHn22WfXGjtt2rSsuro6i4hszz33zFauXLnBXgsb3rx587JHH300O+GEE9Y4dbK9bw7lWCeFQiEbMGBAFhHZRz/60WzBggVrzfHjH/+4WM9555233q+VDasza2np0qXZ8OHDi6eGPP3002v1mTt3brb33nsX55s4ceIa7dZSz9SZ9dSWhx9+eK2dxrZCkPXU83R2LV122WXFvpMmTVqrfcWKFdn+++9f7PPKK6+s0f7iiy8W191ee+2VLVu2bK05zj777OL4G2+8cb1eJ+UlBG1kmpubs4EDB2YRke2xxx5t9nvxxReL/+jOOOOM4uPPP/988fFjjjmmzfHHHHNMsd+LL75Y1tdA19ljjz3a3J5v75tDOdbJj370o2LbDTfc0Or45ubmbMiQIVlEZFtvvXXW3NzcqdfJhtfZtfTwww8X+5111llt9nvjjTeyfv36ZRGRffzjH1+jzVrqeTq7nlozd+7cbNiwYVlEZEOHDl1nCLKeepbOrqWlS5cWPz/2D//wD23+wvcPf/hDcb5rrrlmjbZ/+Zd/Kbbdc889rY7/4IMPir8w3G233Tr9Oim/ilwim8577733YsGCBRERsc0227TZb8SIEcXjV155pXh8zz33FI+POOKINsev3jZ16tRO1Urlvffee50aV451svochx9+eKvje/XqVbz649y5c+Ppp5/uVL1seJ1dSy1XAY2I+D//5/+02W/kyJGxyy67RETEq6++GgsXLiy2WUs9T2fX09/LsixOPPHEmDNnTuywww7x3e9+d51jrKeepbNr6ZFHHol58+ZFRMQ//uM/tnlV3QMOOCAef/zxePzxx9f6ftiylgYMGBAHH3xwq+O32GKL2H///SMiYtq0afHOO+90ql7KTwjayAwePDj69OkTEREvvvhiZG1c4Xz69OnF42HDhhWPZ86cWTweO3Zsm8+zetuzzz7b6XqprJkzZ8bixYuLX3/5y19KHteis+ukZY5PfOIT7Qb2ww47rM056D46u5YKhULxePVfzrRm6NChxeMlS5as8dwR1lJP0tn19PduuOGGuPvuu6Nv377xy1/+MgYMGFDSc0dYTz1FZ9fSH/7wh+Lxl7/85Tb7VVdXx1577RV77bVXfOxjHys+vnz58pg1a1ZERBx00EHRv3//NudYfS09//zzJdXHhicEbWT69OkTX/nKVyJi1W9Lr7vuurX6LF68OM4555zin48//vjicctvIGpqamLQoEFtPs+gQYOK30xW/4GYjUu/fv2if//+xa9+/fqVNG5910mWZfHuu+9GxLp/8F39hxBrrfvq7Fo65phjYvLkyTF58uSora1ts19zc3PxB80tttgittpqq4iwlnqqzq6n1T3//PPF73VXXXVV7LzzzuscYz31PJ1dSzNmzIiIiL59+0ZdXV1ErPp/aMaMGfHHP/4x3nzzzTZ/0Ryxageqpd1a2jhVV7oAOu66666L6dOnx3PPPRdnnXVWPPTQQ3HYYYfFVlttFa+++mpMmjSpeFPLCRMmxEEHHVQc2/Kff3s/2LYYPHhwLFq0yNZtgtZ3nTQ1NcXy5ctLmmPw4MHFY2ut59lnn31in332WWe/m2++ufj/1uc///niqSnWEq1ZtGhRjB8/PpYtWxZjx46NM844o6Rx1hMtWsLIkCFDYvny5XHVVVfF9ddfv8bpdZtttlkcccQRcc0116z1S5yW75MR1tLGSgjaCG2++ebxpz/9KU4++eSYMmVK3HPPPWuc4xyxasfoV7/6VRx11FFrPN7yj2/1f5BtGTx4cLz11luxaNGi8hXPRmF918nq/8mva47V26219GRZFrfffnucfvrpERFRVVUVF110UbHdWqI1Z5xxRsycOTNqa2tj8uTJbX6e4+9ZT7SYP39+RKzaef7iF7+4xulxLRYuXBi33357TJ06NW6//fY1TgG3ljZ+TofbCGVZFjfffHPcfffdbfZZvnx5TJw4MaZNm7bG4y0XVdhkk03W+TwtW8qLFy9ej2rZGK3vOmkZX8ocq5+6YK2l5fXXX4+jjz46vva1r0Vzc3NERPzkJz+JnXbaqdjHWuLv/epXv4rbbrstIiL+7//9vzFkyJCSx1pPtGi5+MpLL70Uf/jDH2LEiBFx++23x6xZs2L+/Pnx+OOPFz9+8MEHH8SXv/zleOONN4rjraWNnxC0kcmyLE477bQ466yzYsGCBbHzzjvHf/7nf8Ybb7wRCxcujBdeeCEuu+yy2GyzzeLpp5+Oz3zmM/HHP/6xOH7rrbeOiCheEaU9LX1K+UGYnmV910nL+FLmWL3dWktDU1NTfPvb344ddtghfvvb30ZERP/+/ePGG2+MU045ZY2+1hKre+ONN+Lkk0+OiIhzzjknPve5z3VovPVEi+rq/z0ZatSoUfHSSy/F8ccfH9ttt10MHDgw9tprr5gyZUp85zvfiYhVOzgTJ04sjrGWNn5C0Ebm3nvvjZtuuikiIg488MB45pln4uijj46RI0dGTU1NfPKTn4yLLroo/vznP8cmm2wSf/vb3+JrX/taLF26NCL+9+pLTU1N63yulj41NTUb6NXQXa3vOln9Kl/rmmP1dmut5/vP//zPGDNmTPzgBz8ofjZjv/32i+effz7++Z//ea3+1hItli9fHscdd1wsWLAgdtttt7jiiis6PIf1RIvVr5z74x//uM2/44svvjg233zziIi46667ihdDsJY2fj4TtJG55ZZbisc33nhj9O7du9V+O+20U3zrW9+Kq6++Ot5+++144IEH4vDDD4+PfOQjEbHqH2SWZW2eR51lWXzwwQcR0f79iOiZ1ned1NTUxIABA2LRokXr/ObQMv7v56Bnef/99+Pkk0+OO++8s/jYmDFjYuLEiXH44Ye3ucasJVrccccd8eSTT0ZExNe+9rV4+OGH1+rz4osvFo+feuqp4qXWd9hhh+IvC60nIlaFmFmzZkVVVVXsu+++bfYbMGBAfOITn4g//elPMXfu3Jg3b15sueWWxe+TEesOQdZS9yQEbWReffXViFh1xZJRo0a123fPPfcsHrfcMLXlNxfLli2LmTNnxg477NDq2JkzZxZ/S1tfX7/edbNxKcc6GTp0aLz22msxffr0WLlyZfTq1frG8+r3tLLWeqaFCxfGF77whXjmmWciImLgwIFx5ZVXxje/+c01Tklpi7VExJr3jjrzzDPX2b/lNKaIiB/+8IfxL//yLxFhPbFKy05Q//79Y9NNN2237+qfO1u2bFlE/O99G5cvXx4vvPBCu+Otpe7J6XAbmb59+0bEqm8GLT98tmX1D+21fChv9913Lz7W3oUVVm8r5fK29CzlWCctc7z77rtrXaCj1DnY+GVZFkcddVQxAO29994xY8aM+Od//ueSAlCEtUR5WU9ERHz84x+PiFUXKpg9e3a7fVtuwNqnT5/iPcyqqqpit912i4hVu46r3xj677Wspb59+xbHUHlC0Eam5WZwy5cvj0ceeaTdvvfff3/x+B/+4R8iImLcuHHF007uuOOOVm8ElmVZ8ZSVqqqqOPzww8tROhuRcqyTI444onh8xx13tPo88+bNK57SMmbMmBg9enRZ6qf7+OMf/xgPPfRQRKwKQA8++GDxxoSlspaIiPjGN74RWZa1+zV58uRi/0ceeaT4eMsuUIT1xCqrf8+69dZb2+z37LPPxssvvxwREfvvv/8aH0NoWUtZlhUv8vL3Zs6cGQ0NDRERcfDBB8fAgQPXu3bKQwjayJx44onF45NOOilef/31tfpkWRY33XRT/OY3v4mIVVc9aTnfddiwYTF+/PiIiHjyySfj5ptvXmv8pEmT4oknnoiIiOOPP36ND/+RhnKsk6OOOqp4F+3rrrsunn/++TXam5ubI5fLFU9x+fa3v13ul0E30HIhl4iIn/70p+s87aQ11hLlZD0REbHHHnsUPzZw9dVXt3rWw5w5c+KEE04o/iKw5X5mLU466aTihQ4uueSSeOutt9ZoX7x4cZx66qnFP1tL3YvPBG1kPv3pT8cpp5wSkyZNisbGxhgzZkyccMIJsdtuu8WWW24Zr7/+evzud7+LP//5zxGxauv1lltuWeM3F9///vfjgQceiKampjj11FPj8ccfj0MPPTRWrlwZU6dOjSlTpkTEqvNdL7/88oq8TipvfddJv3794rrrrosjjzwylixZEp/5zGfi9NNPj9122y2ampriZz/7WTz22GMREbHXXnvF17/+9S59fXSNRx99NCIiamtr480334w333yzpHFf+MIXisfWEuVkPRGx6gyGH//4x/GZz3wmli1bFocffngcc8wxceCBB8aWW24ZL7zwQtx8883FixqMHz8+xo0bt8YcW221VXz/+9+PM844I957773YY4894swzz4z6+vr461//GpMmTYqXXnopIiKOOeaYOPjgg7v8ddKOjI3OihUrsksvvTTbdNNNs4ho86u+vj57+OGHW53jf/7nf7Ktt966zbFDhgzJ/vznP3fxK2NDe+ONN4p/x5dccsk6+5djnVx//fVZdXV1m3PstttuWaFQKNMrpKuUspaam5uz3r17t/v/VFtfrbGWeq6O/t/UlsmTJxfneeSRR9rtaz31TB1dS3feeWdWU1PT7v9HJ5xwQrZ48eJWx69cuTI7//zz2x3/+c9/Plu0aFGZXynry+lwG6HevXvHJZdcEq+88kp8+9vfjkMOOSS23Xbb2GSTTWKnnXaKo48+Om6++eZ44YUX4sADD2x1jv322y9efPHFuPDCC6O+vj4GDBgQNTU1seOOO8Z3v/vdeOmll2Lvvffu4ldGd1OOdfKtb30rnnnmmTjxxBNjxIgR0bdv3xg0aFDss88+ccMNN8Tjjz/eoTu+s/F4//33o7m5uWzzWUuUk/VExKrTIxsaGuK8886LHXfcMQYOHBh9+/aNESNGxD/+4z/Gn/70p7jtttuif//+rY6vqqqKiRMnxn//93/HscceG3V1ddGnT5/Yeuut4+CDD47bb7897r333k6dCsyGVZVlrXziGQAAoIeyEwQAACRFCAIAAJIiBAEAAEkRggAAgKQIQQAAQFKEIAAAIClCEAAAkBQhCAAASIoQBAAAJEUIAgAAkiIEAQAASRGCAACApAhBAABAUoQgAAAgKUIQAACQlP8PpLlR9zTIb+EAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(x=np.arange(75, 175, 5), height=rH_weight)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b3653b1b",
+   "metadata": {},
+   "source": [
+    "## Validate weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "8a714f8c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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2PXr00Mcff6wxY8bo3LlzmjlzpmbOnFlhzjXXXKPly5crICCg3voAAAAAcPmp03Mmaxpz9stVrrrqKm3atEmzZs1Snz591KJFC3l5eSkiIkIPPvigkpOTNW7cuDrX9/Pz08qVK5WYmKiYmBgFBQXJ09NTYWFhGj16tDZs2KAXXnjBJSG7Jr/97W+1Y8cOPfLII+rQoYN8fHwUEBCgrl276uWXX9b27dt17bXX1msPAAAAAC4/hulggnNz+3+50zAMFRcXW9+7amVSktLS0lxSB/aEhYUpMzNTbdq0UUZGRkO3AwAAAKCBOJoNHL7MtaadWg8dOmSrOQAAAADAL5vDYXLAgAH12QcAAPiFiHhmWUO3UMGhV4Y2dAsAcFlyOEwCwOWosf2jGTVzVahoqn/uhK7aNdU/+6aKzzTQsBosTJ48eVJ+fn7y9vZuqBYAAE0MQaBmTfX301TfFwA0drZ3c3XEkSNHdOLEiUo/P3funOLi4tSqVSsFBwerWbNm6t27t5YsWVIfbQAAAAAA6onLwuTJkyf10EMPqVWrVgoPD9fXX39dYby4uFgDBw7U3//+d506dcp6FEhSUpJGjRqlF154wVWtAAAAAADqmUvC5NmzZ9W3b1998MEHOnXqVJVzZs2apeTk5CrHTNNUfHy8UlJSXNEOAAAAAKCeuSRMzpgxQ/v27avwMx8fnwrfz5o1yzp+/PHHlZ2drR9++EF9+vSxfv7aa6+5oh0AAAAAQD1zOkyeOXNGM2bMkGEYkqQ///nPys3N1e23327NSUlJUVpamgzD0K9+9Su9/vrrCgoKUteuXbVs2TL5+fnJNE0tWLCgynstAQAAAACNi9NhMjU1VefOnZMkdevWTTNmzFDz5s0rzFm6dKl1fPfdd1vBU5ICAwN15513SpJKSkoqrXACAAAAABofp8PkwYMHrePY2Ngq52zYsME6vuWWWyqNR0VFWceHDh1ytiUAAAAAQD1zOkxmZmZax6GhoZXGi4uLtXHjRkml91F279690pwWLVpYx+np6c62BAAAAACoZ06HyfIBsqr7HZOSkpSXlyfDMNS7d295enpWmnPmzBnrOCAgwNmWAAAAAAD1zOkwec0111jHmzdvrjRe/n7JoUOHVlnjxx9/tI7Dw8OdbQkAAAAAUM+cDpO/+tWv5OnpKdM0tWTJEv3www/W2LFjx/Tuu+9a348cObLS+ZmZmVqwYIH1fdu2bZ1tCQAAAABQz5wOk1deeaUefPBBSaW7scbExOjxxx/Xa6+9pn79+unMmTMyDENdu3bV1VdfbZ2Xk5Ojf/3rX+rbt6/y8vIkScHBwerUqZOzLQEAAAAA6pmHK4pMmTJFiYmJOn/+vPLy8vT2229XmvO3v/2twvc9e/bUwYMHZZpmhWdUuru7u6IlAAAAAEA9cnplUirdhGfJkiXWrqymaVpfhmHo2WefVb9+/ao93zRNxcbG6oknnnBFOwAAAACAeuaSlUlJiomJ0e7du/Xhhx9q48aNKiws1LXXXqtRo0ZVGSRN05Qkde3aVX/84x/1wAMPsCoJAAAAAL8QLguTktSyZUuHVxc3btwof39/eXt7u7IFAAAAAMAl4NIwaUdQUFBDvTQAAAAAwEkuuWcSAAAAAHB5qZeVyZMnT+rcuXN1OpfnTAIAAABA4+eyMJmbm6snnnhCK1euVGZmZp1qGIahCxcuuKolAAAAAEA9cUmY/PnnnzVw4EAdPnzY2qUVv0zZ2dmKioqqciwuLk5xcXGXuCMAAAAArpaQkKCEhIQqx7Kzsx2q4ZIw+Ze//EWHDh2SYRjWz3x8fBQcHFzhZ2j8QkJClJqa2tBtAAAAAKhHNS0UhYWFOXS1qdNh8vDhw/rkk0+s0HjjjTfq3XffVY8ePeTmxv4+AAAAANAUOR0mf/zxR0mSaZpq0aKFVq1apZYtWzrdGAAAAACg8XJ66XDv3r2SSjfPue+++wiSAAAAAHAZcDpMenl5Wce/+tWvnC0HAAAAAPgFcDpMRkREWMcZGRnOlgMAAAAA/AI4HSZjYmLUokULSdL333/vdEMAAAAAgMbP6TDp6+urZ555RqZpat26dVq4cKEr+gIAAAAANGIueXbHpEmTdP/998s0Td1///36/PPPXVEWAAAAANBIOf1okDJz5sxRdHS0nnzySd1xxx3q1q2b7rvvPnXs2FFXX321fH19HarTtm1bV7UEAAAAAKgnLgmToaGhFb43TVPJyclKTk62VccwDF24cMEVLQEAAAAA6pFLwuTRo0dlGIZM05RhGDIMQ1JpqAQAAAAAND0uCZNt27a1AiQAAAAAoOlzSZg8dOiQK8oAAAAAAH4hXLKbKwAAAADg8kKYBAAAAADYdsnCZGFh4aV6KQAAAABAPXN5mCwpKdG///1vjR8/Xp07d1arVq3k7e2t5s2bV5jz0ksv6eeff3b1ywMAAAAALgGXhsktW7aoZ8+euvvuu/Xee+8pNTVVp06dUlFRUYXHhJimqb/+9a9q3769fv3rX2vfvn2ubAMAAAAAUM9cFia/++479e/fX9u2bZNpmtZXbVavXq2uXbvqu+++c1UrAAAAAIB65pIwefjwYY0cOVKFhYUyTVPNmjXTX//6V3399dcKDw+v/KJubvrTn/4kLy8vGYahc+fO6fbbb1dubq4r2gEAAAAA1DOXhMk33nhDp06dkmEY6tChg5KTkzV9+nTdcsst8vLyqjTfMAy9++672rVrl9q3by9JOnnypF599VVXtAMAAAAAqGdOh8kzZ85o7ty51vdz5sxRZGSkQ+dGRERo1apV8vDwkGma+tvf/qZz58452xIAAAAAoJ45HSa3b9+u/Px8GYahW265RTfffLOt89u3b6877rhDUunjQ3bv3u1sSwAAAACAeuZ0mDxw4IB13KNHjzrV6Nq1q3VMmAQAAACAxs/pMHns2DHruG3btnWq4efnZx1nZGQ42xIAAAAAoJ45HSaDg4Ot4/3799epxq5du6zjK6+80tmWAAAAAAD1zOkw2alTJ+t448aNts83TbPCMyY7dOjgbEsAAAAAgHrmdJjs1auXgoODZZqmvv/+e3355Ze2zp85c6a2bdsmSWrevLntDXwAAAAAAJee02HSzc1NTz75pPX9Qw89pA0bNtR6XnFxsWbPnq3JkydLKn325Lhx4+Tp6elsSwAAAACAeubhiiKPPPKI5s+frx9++EHHjh1TTEyM7rnnHv3mN79RQUGBNS85OVn79u3Tvn379Mknn2jv3r3WWNu2bTVlyhRXtAMAAAAAqGcuCZOenp766quvdOutt2r79u0qLi7WvHnzNG/ePEmlq46S1LNnz0rnmqap0NBQrVy5UgEBAa5oBwAAAABQz5y+zLVMy5YttWnTJv3lL3+Rn5+fTNO0vsqU/5lpmjIMQ7///e+1c+dOXXvtta5qBQAAAABQz1yyMlnGy8tLL7zwgp5++mnNnz9fa9euVXJyso4fP64zZ86oWbNmatGihTp37qybbrpJ99xzj8LDw13ZAgAAAADgEnBpmCxzxRVX6MEHH9SDDz5YH+UBAAAAAA3MZZe5AgAAAAAuH4RJAAAAAIBtLrvM9ejRo9q2bZtOnDihnJwc5eXl6YorrlBgYKCCgoIUHR2tkJAQV70c6kl2draioqKqHIuLi1NcXNwl7ggAAACAqyUkJCghIaHKsezsbIdqOBUmv//+e/3f//2fVq1apSNHjtQ6PywsTLfeeqsefPBB9e7d25mXRj0JCQlRampqQ7cBAAAAoB7VtFAUFhamzMzMWmvU6TLXLVu2qFu3brr55puVmJiozMzMCo8BufixIGXH6enpmjt3rm666Sb16NFDycnJdXl5AAAAAEADsx0m4+Pj1adPH23fvr3ScyQlyc3NTYGBgWrTpo2uvPJKubu7VxgvOyc5OVm9evXSCy+84Nw7AAAAAABccrYuc3366af1xhtvyDRNGYYhSWrXrp3uvvtuDRgwQF26dFFoaGil844ePaodO3Zo3bp1+vTTT5WWlibDMFRSUqL4+HidP39eL774omveEQAAAACg3jm8MrlkyRK9/vrr1vetW7fWvHnzdPDgQb388su67bbbqgySknTVVVfp17/+tV588UUdOHBA8+bNU+vWrWUYhkzT1CuvvKIvv/zS+XcDAAAAALgkHAqTBQUFmjhxovV9VFSUtmzZonvuucdaobTjnnvu0ZYtW/SrX/3KCpQTJ05UYWGh7VoAAAAAgEvPoTC5YsUKpaenS5J8fHz05ZdfqnXr1k69cOvWrfXll1/Kx8dHkvTzzz9r+fLlTtUEAAAAAFwaDoXJzz77TJJkGIYee+wxRUREuOTF27dvr0cffbTS6wAAAAAAGjeHwuSOHTus49/97ncubWD06NHWcUpKiktrAwAAAADqh0Nh8siRI5IkDw8PdenSxaUNdO7cWZ6enjJNU1lZWS6tDQAAAACoHw6FyVOnTskwDIWEhNRLE8HBwZKk06dP10t9AAAAAIBrOfxoEEnWZjmuVl91AQAAAAD1w1aYBAAAAABAIkwCAAAAAOqAMAkAAAAAsI0wCQAAAACwjTAJAAAAALDNw87kAwcOyN3dvb56AQAAAAD8QtgKk5JkmqbLmzAMw+U1AQAAAAD1x+EwWR8h8lLUBgAAAAC4nkNhcu7cufXdBwAAAADgF8ShMDlmzJj67gMAAAAA8AvCbq4AAAAAANsIkwAAAAAA2wiTAAAAAADbCJMAAAAAANsIkwAAAAAA2wiTAAAAAADbCJMAAAAAANsIkwAAAAAA2wiTAAAAAADbCJMAAAAAANsIkwAAAAAA2wiTAAAAAADbXBImz54964oy2rt3r0vqAAAAAADql0vCZJcuXbRhw4Y6n2+apmbMmKEbb7zRFe0AAAAAAOqZhyuKHD58WIMGDdITTzyh559/Xl5eXg6fu2fPHv3hD3/Qpk2bXNEKnJSdna2oqKgqx+Li4hQXF3eJOwIAAADgagkJCUpISKhyLDs726EahmmaprONuLm5yTAMSdL111+vefPmqXPnzjWeU1JSojfffFNTp05VYWGhTNOUYRgqLi52th3UQVhYmDIzM9WmTRtlZGQ0dDtAoxHxzLKGbgEAUI1Drwxt6BaAJsnRbOCSy1xfffVVeXt7yzRN7dy5Uz169NDrr7+u6nLq7t27ddNNN+npp5+2gmRgYKA++OADV7QDAAAAAKhnLgmTTz75pLZt26Y+ffpIkv773//qmWee0cCBA3X48GFrXklJiV577TVFR0crKSlJpmnKNE3dfvvt2rVrl8aMGeOKdgAAAAAA9cxljwaJjIzUhg0b9Oabb8rX11emaeq7775Tly5d9OGHH2rXrl3q27evJk+ebK1GhoSE6LPPPtNnn32mkJAQV7UCAAAAAKhnLn3OpJubmx577DGlpKSof//+Mk1TZ8+e1QMPPKDOnTtry5Yt1qWvY8aMUWpqqm6//XZXtgAAAAAAuARcGibLdOjQQd9++62efvppSaWP/igpKZFpmrriiiu0YsUKzZ07V1deeWV9vDwAAAAAoJ7VS5iUpPfee0/vvPOODMOwdno1DEN5eXlKSEjQ0aNH6+ulAQAAAAD1zOVh8tChQxo8eLAmTJigvLw8maapjh076plnnpGnp6ck6csvv1SnTp304YcfuvrlAQAAAACXgEvD5OzZs9W5c2etXbvW2qn10Ucf1bZt2/TSSy8pKSlJ119/vUzT1JkzZ/TAAw/of/7nf5Senu7KNgAAAAAA9cwlYXL//v0aMGCAHn30UeXn58s0TbVr105r1qzR3/72N/n6+kqSunTpoi1btuipp56SYRgyTVNff/21rr/+er333nuuaAUAAAAAcAm4JEx26dJF3333nbUa+dBDD2nnzp0aOHBgpbleXl565ZVXtG7dOrVv397a8XX8+PG65ZZbXNEOAAAAAKCeuSRMFhQUyDRNtW7dWsuXL9c//vEP+fn51XhOv379lJKSogcffFBS6Y6v3377rSvaAQAAAADUM5fdM3nffffpxx9/1G233ebwOX5+fnrvvfe0dOlSBQcHu6oVAAAAAEA983BFkYULF2rUqFF1Pn/o0KH68ccfNX78eFe0AwAAAACoZy5ZmXQmSJZp1aqV/v3vf7ugGwAAAABAfXP5cyYBAAAAAE0fYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGCbhyuKTJ8+XZLUokULPfzww7bPf/fdd3X8+HG1bdtWY8eOdUVLAAAAAIB65JIwOW3aNBmGoWuuuaZOYfJf//qX/vOf/ygyMrJewmROTo4OHjyos2fPKjQ0VB06dJCbm+sWZfPy8rR//37l5OQoJCREHTt2lKenp60ax48fV1pamgoKChQeHq6IiAgZhmGrRm5urnbv3i1PT09FRkaqWbNmts4HAAAAAEe5LFGZplnncy9cuCDTNJWRkeGqdiRJe/fuVWxsrIKCgtS9e3cNGjRIkZGRioiI0IwZM1RcXOxU/aysLN13330KCgpSdHS0YmJidN111yk0NFRTpkxRQUFBrTWSkpI0aNAgBQcHq1evXhowYICuvvpqderUSYmJibX+XktKSjR37lxdc801CggIUK9evdS1a1f5+fnp+uuv1xdffOHUnw0AAAAAVMXWyuQ///nPascMw1Bubm6Ncy5WUlKiAwcOaPPmzaXNeLhkoVSStGHDBt12223Kz8+vNJaenq5JkyZp/fr1WrRokdzd3W3X37Nnj/r166cTJ05UGjtx4oReeuklrV69WmvWrFHz5s2rrDF//nzde++9VYbaPXv2aOzYsfrhhx80c+bMKlcpCwoKdMstt+g///lPpTHTNPXTTz9p1KhR+u1vf6sFCxa4dDUWAAAAwOXNMG0sW7m5uVUZaspK2L0s82J9+vTRd99951QNqTTM/epXv9LJkyfl5uamadOm6f7779eVV16ppKQkPfHEE9q2bZskaerUqXruueds1S8sLFSXLl20d+9eSdLEiRP16KOPKjQ0VDt37tRf/vIXffPNN5Kk//3f/1ViYmKlGrt27VJ0dLQKCwvl6+ur119/XXfeead8fX21bt06TZw4UYcOHZIkffDBB7r//vsr1ZgwYYLeffddSVLv3r31/PPPq2vXrioqKtKmTZs0efJk7dq1S5L02muv6cknn6z2PYWFhSkzM1Nt2rRx+Qox8EsW8cyyhm4BAFCNQ68MbegWgCbJ0WxgO0zWF8MwtGTJEg0d6vxfCk899ZRef/11SdLs2bMVFxdXYTw3N1c33HCDDh06pObNmystLU1BQUEO13/nnXesmpMmTbJeq0xRUZH69eunpKQkGYahnTt36rrrrqsw56677tK///1vSdLSpUs1bNiwCuPp6enq3Lmzzpw5o7CwMO3fv1/e3t7WeEZGhsLDwyVJ119/vbZs2SIfH58KNU6cOKHOnTvr6NGj8vHxUW5ubrX3chImgaoRJgGg8SJMAvXD0Wxg67rSMWPGVPnzxMREGYYhPz8/3X777fY6ldSyZUuNHDlS/fr1s33uxYqLi/XBBx9IkoKDgzVu3LhKc/z9/TVp0iQ9/PDDOnfunObPn29r46D3339fUulluVOmTKk07unpqalTp2rYsGEyTVNz587VG2+8YY2fPHlSCxculCR17969UpCUpPDwcD300EN64403lJGRoVWrVlWYl5SUZB2PHz++UpCUpFatWunee+/VjBkzVFBQoB9//FHR0dEOv08AAAAAqI6tMDl37twqf152GWdISEi1cy6VTZs26eTJk5Kk2NjYau+HHD58uBUgly1b5nCYzMzM1Pbt2yVJAwYMUGBgYJXzBg8erObNm+vcuXNatmxZhTC5YsUKlZSUSJJGjBhR7WuNGDHCOm/ZsmUVwmTZJbaSrBXKqrRr167COYRJAAAAAK7QKHZzdaU9e/ZYx0OGDKl2Xnh4uLp06SJJ2rp1q8vr+/j4aPDgwZKk3bt369y5c7Zr9OnTxwqrF/fYunVr63jHjh3V1ig/FhoaWu08AAAAALDDJWEyLS1NaWlp+vbbb11RzilZWVnWcflVuaqUregdO3ZMp0+frrf6krRv3z7bNdzd3dWmTRtJpQG0fGAfMWKE/P39JUkzZszQwYMHK52flJRkrRq3b99effr0qbFfAAAAAHCUS57FUVuoupSOHj1qHbdo0aLGuS1btrSOs7Kyqr1k1VX1b7zxxgo1DMOo9TXLapw5c0YFBQXy9fWVJAUGBuqzzz5TbGyscnJy1KVLF40fP17R0dG6cOGCNm7cqDlz5qioqEiBgYFatGiRQ49eMU1Tubm5tc6rjre3d4WNggAAAABcWoWFhSosLKzz+Y5edeq6Bzs2EuVX/cqHuaqUHy9/GWp91y+rERgYWOszLi+uURYmJenWW2/VDz/8oCFDhig9Pb3CfZlloqOj9cUXX6ht27Y1vk6ZI0eOKCAgwKG5VYmPj9e0adPqfD4AAAAA57z88su2H39YFy4Nkx9++KFWr16tlJQUh8NZeYZh6MCBA071UH5VrXzwqkr5FbTz589fsvplNWo7v7Yes7Ky9Pzzzys9Pb3a83fs2KHXXntNL7/8sq644opaXy80NNR6NmVdsCoJAAAANKzJkyfr8ccfr/P5nTp10pEjR2qd55IwefbsWY0ePVpfffVVnWuYpinDMJzupfzzIk+fPl3j8yPL3yfpSLCrqn5NqqsfFBSkffv2OXSfZnU1MjIyNHDgQB04cEBubm4aO3asHnroIUVGRqqoqEipqal6++239cUXXyghIUFbt27VihUrrPssq2MYRq1zAAAAADRezt565mguc8kGPC+99JKWL19uXVtrmqbtL1cpv8vpqVOnapxbftzPz++S1S+rkZ+fr4KCgjrV+POf/2yt4s6ZM0dz5sxR7969deWVVyo4OFgDBw7U559/rmeffVaStHHjRr300ku1vT0AAAAAcIjTK5PHjx/XW2+9ZaVXX19f/fWvf1X//v0VGhrqktVGO6666irruLawl5OTYx2X7ZpaX/XL7+xavkZOTk6FgFpdjVatWsnHx8d63c8++0yS1KtXL40dO7ba8+Pj4/X+++/r6NGjeu+99/Tyyy9f8j8TAAAAAE2P02EyJSXF2inI3d1d3333nbVraUMoH8xSUlKqfRxGSUmJdu7cKUlq27atQ/cTVlV/9OjR1c4te8aju7u7OnbsWG2N6sJkbm6uDh06JEmKioqyfl7+vtIePXrU2K+7u7u6deumZcuWKScnRydPnlSrVq1qPAcAAAAAauP0Za5lz080DEO/+93vGjRISlL37t2t46VLl1Y7Lzk52XpER9++fR2u37lzZ3l6etZaPzs7W0lJSZJKA5+Xl5ftHleuXKmioqJKPZav5chjPMrPYYMcAAAAAK7gdJgsv2trbatkl0JkZKQiIyMlSd98802FS03LW7RokXU8atQoh+v7+/srJiZGkpSamqrdu3dXOe+LL76w7gW9uP7AgQOtldAlS5ZYgdHRHjt27GhtxrNu3boad6I9fvy4kpOTJUnt27d3eAUWAAAAAGridJgsf4mmMw/GdKWybXALCws1ceJElZSUVBjftm2b3nrrLUmlAWvkyJF1qi9J48ePr7SJzuHDhzV16lRJpeHzgQceqDDu7e2thx9+WFLprqzx8fGVNiFavny5Pv30U0lSv379KgT1Zs2aWZfXHj58WBMmTKjyd5+bm6t7771X+fn5kqQ//OEPtt4nAAAAAFTHMJ3cSjUzM1Nt27aVJI0cOVILFy50SWPOKCoqUr9+/azLTPv376+xY8fK399fSUlJeuedd5SXlyfDMLR48WLFxsZWOH/s2LFKTEyUVLqBzbRp0yqMm6apO+64w1o5vOGGGzRu3DiFhIRo586dmj17to4fPy5Jmj17tuLi4ir1ePr0aXXr1k0HDx6UJI0YMUJ33HGHvLy8tG7dOr333nu6cOGCvL299d1331W4NFYqvYy2R48e1jMmr776ao0ZM0bXXnutCgsLtWvXLs2ZM0cnTpyQJEVHR+s///lPtY9ACQsLU2Zmptq0aaOMjAyHf9dAUxfxzLKGbgEAUI1Drwxt6BaAJsnRbOD0Bjxt2rTRb3/7W3322Wf6+uuvtWfPHusy04bi6empxYsXa8iQIdq2bZvWr1+v9evXV5ozc+bMSkHSEYZhKDExUbm5uVq9erVSUlI0fvz4SvOmTJmiCRMmVFkjMDBQX375pYYOHaq0tDQtXrxYixcvrjDHz89P8+bNqxQkJSkkJETr1q1TXFycvvrqKx08eFDx8fFVvtZ9992nN9980+FnaQIAAABAbVzynMm///3vioiI0Llz5zRq1ChlZ2e7oqxTrrrqKm3atEmzZs1Snz591KJFC3l5eSkiIkIPPvigkpOTNW7cuDrX9/Pz08qVK5WYmKiYmBgFBQXJ09NTYWFhGj16tDZs2KAXXnihxsdwdOrUSSkpKXrxxRcVHR2tgIAA+fr6qmPHjnrssce0c+dOjRgxotrz27dvr+XLl+vrr7/W73//e/Xs2VMBAQFq1aqVbrrpJj3wwAPasmWLPvroIwUFBdX5vQIAAADAxZy+zLXM0aNHNWLECG3ZskXNmjXTI488onvuuUfXXHMNK2K/AFzmClSNy1wBoPHiMlegfrj0Mterr77aoRct2wQmPz9fr776ql599VVJpZdk+vj41Hq+YRgVnqEIAAAAAGicHAqThw4dqvFyzfLKzytb9HTkslfTNB1+DQAAAABAw3J4Ax5nroZ10ZW0AAAAAIBGwqEwmZaWVt99AAAAAAB+QRwKk+3atavvPgAAAAAAvyAueTQIAAAAAODyQpgEAAAAANhGmAQAAAAA2Obwbq41adu2rVPne3l5qXnz5mrevLnatWunyMhI9ejRQ7feequ8vLxc0SIAAAAAwIVcEiYzMjJkGEaNjwBxZFySNm/ebP3Mz89Pf/rTnzR16lT5+fm5olUAAAAAgAu45DLXZs2aqVmzZvLx8ZFUGgzLwmGZi4Nk2RzDMNSsWTN5eHjINM0KX2fPntWMGTMUHR2trKwsV7QKAAAAAHABl6xM5uXl6eTJk/rd736nb7/9VqZpysPDQ6NGjdJ1112n8PBwtW7dWidPntTPP/+svXv36t///rfy8/NlGIbuvvtu/eMf/7DG9+/frwULFuiLL76QJB04cEAjRoxQUlKSK9oFAAAAADjJJWHy7Nmz6t+/v3bv3i1Jeuqpp/Too4+qdevW1Z4zY8YMzZ49Wy+88ILmzp2r8+fP6+OPP1ZwcLC6d++uu+++W99++61Gjhyps2fPKjk5WZ9//rlGjRrlipYBAAAAAE5wyWWuDz/8sHbt2iVJeu+99/TKK6/UGCQlqUWLFpo6dao++ugjmaapTz/9VLNmzaowZ9CgQfr73/9ufV+2UgkAAAAAaFhOh8msrCx98sknMgxDffv21QMPPGDr/N/97nfq1auXTNPUc889p4KCggrjd999twICAiRJmzZtcrZdAAAAAIALOB0m165dq+LiYklSbGxsnWr069dPkpSTk6OVK1dWGDMMQ9ddd51M09Tx48edaxYAAAAA4BJOh8n09HTruFWrVnWq0b59e+s4LS2t0nhERIQk6dy5c3WqDwAAAABwLafDpL+/v3X8888/16nG9u3baxzPycmRJIWGhtapPgAAAADAtZwOkx07drSOFyxYoJKSElvnl5SUaN26ddb35VcpJenChQvaunWrDMPQ1Vdf7VyzAAAAAACXcDpMDhgwQC1btpQk7dmzR88++6yt859//nnt27dPkuTr66tbb721wviHH36o7OxsSVKnTp2cbRcAAAAA4AJOh0kPDw9NnjxZpmlKkl555RXdfvvt+uGHH2o8b/v27brrrrs0ffp0SaUb7Tz66KNq1qyZJOnkyZN68803NWHCBGt84sSJzrYLAAAAAHABD1cUefTRR/X111/r66+/lmEYWrx4sRYvXqxu3bopKipK7dq1U0hIiI4fP66ff/5Zu3bt0ubNmyXJCqHdu3evsKrZp08fHThwQKZpyjAMjR49WpGRka5oFwAAAADgJJeESXd3dy1evFj333+/Pv30U+vnycnJSk5OrvKcshApSYMHD9Znn30mHx+fCuNlc7p27arZs2e7olUAAAAAgAs4fZlrGW9vb33yySdasmSJ+vbtK+n/BcKqviQpMjJS//d//6evv/5aAQEBFep5eHioX79+euONN/Sf//yn0jgAAAAAoOG4ZGWyvGHDhmnYsGHat2+fNmzYoOTkZB07dkynT59Ws2bN1KJFC3Xu3Fk333yzevToUW2drVu3ytfX19XtAQAAAABcwOVhskzHjh3VsWNH/eEPf6jT+QTJhpGdna2oqKgqx+Li4hQXF3eJOwIAAADgagkJCUpISKhyrOxpGrWptzCJX6aQkBClpqY2dBsAAAAA6lFNC0VhYWHKzMystYbDYfLnn3+u8H3btm0dPRUAAAAA0MQ4HCYjIiJkGIak0mc+XrhwwRqLiYlxSTOGYeibb75xSS0AAAAAQP2xfZlr+Ud6lFm7dq0VNOuq7HmSAAAAAIDGz2X3TFYVMgEAAAAATZPDYXLMmDHVjn377bcuaQYAAAAA8MvgcJicO3dutWMDBgxwSTMAAAAAgF8Gt4ZuAAAAAADwy0OYBAAAAADY5rINeMq7cOGCkpOT9d133ykrK0tnz57V2bNn9cknn0gq3awnMzNTYWFh9fHyAAAAAIB65tIwWVJSolmzZik+Pl5nz561fl722I+yMFlSUqJ27dopJiZG999/v+655x5XtgEAAAAAqGcuu8w1NzdXffr00eOPP67c3FyZpml9VcU0Ta1Zs0a///3vddtttykvL89VrQAAAAAA6plLwuSFCxd0xx13aMuWLVZ4bNeune655x4FBgZWmm8Yhlq0aGGFzVWrVmnUqFGuaAUAAAAAcAm4JEy+9957Wr16tQzDkIeHh55//nkdOHBA8+bNU8uWLSu/qJubfv75Z7300ktyc3OzVik///xzV7QDAAAAAKhnTodJ0zQ1c+ZM6/vnn39eU6ZMkZtbzaWbNWumZ555RnPmzLF+9swzz6ikpMTZlgAAAAAA9czpMLlt2zbt3btXhmGoQ4cOeuKJJ2ydP2bMGHXt2lWmaWr//v06ePCgsy0BAAAAAOqZ02HywIED1vHgwYPl4WF/g9hhw4ZZx7t373a2JQAAAABAPXM6TB46dMg67ty5c51qtGnTxjreu3evsy0BAAAAAOqZ02GyWbNm1nFOTk6damRmZlrH7u7uzrYEAAAAAKhnTofJsLAw6/jHH3+sU42UlBTrODQ01NmWAAAAAAD1zOkwOXDgQHl4eMg0TS1evFg///yzrfO3bt2qZcuWWd/379/f2ZYAAAAAAPXM6TAZEBCgUaNGSZIKCgo0fvx4FRQUOHTu0aNHdd999+nChQsyDEODBg1SSEiIsy0BAAAAAOqZ02FSkl577TX5+vpKklasWKFevXrp22+/VVFRUZXz09PT9eKLL+raa6/Vnj17JEmGYejVV191RTsAAAAAgHpm/zkeVWjXrp0WLlyoESNG6MKFC/rxxx91yy23yNfXVxcuXLDmXX/99Tp48KAKCwslSaZpWmOzZs1St27dXNEOAAAAAKCeuWRlUpJuu+02ffvtt2rfvr1M05RpmsrPz1dRUZEMw5Ak7dq1SwUFBda4JAUGBurTTz/V+PHjXdUKAAAAAKCeuSxMSlLfvn31448/as6cOerbt6+1MU/5rzKRkZF68cUXtW/fPt11112ubAMAAAAAUM9ccplreT4+Prr//vt1//336/z589qxY4eOHz+uM2fOqFmzZmrRooWuv/56tWzZ0tUvDQAAAAC4RFweJsvz9fVVr1696vMlAAAAAAANwKHLXN955x399NNP9d0LAAAAAOAXwqGVyYcffliGYahFixYaMGCA9dW5c2drcx0AAAAAwOXD1mWuJ0+e1Oeff67PP/9cUulOrP3797fC5Y033ki4BAAAAIDLgMNhsvxOrGXf5+TkaMmSJVqyZIkkyd/fXzfffLMVLrt27So3N5duGAsAAAAAaAQcCpOLFi3Sxo0btWnTJv3www86f/68NWaapgzDkGmaOnPmjJYtW6Zly5ZJkvz8/NSvXz8rXHbv3l3u7u71804AAAAAAJeMQ2Fy5MiRGjlypCTpwoUL2rFjhxUuN27cqIMHD1pzy4fLs2fPasWKFVqxYoUkqVmzZrrpppuscNmjRw95enq6/l0BAAAAAOqV7UeDeHh4qGvXruratavi4uIkScePH7eC5aZNm7RlyxadO3dOUsXLY8+dO6dVq1Zp1apVkkqfSdm3b18rXPbq1UteXl6ueF8AAAAAgHrkkudMBgUFKTY2VrGxsZKk4uJi/fjjj9q4caMVMPft2yepYrg8f/681qxZozVr1kgqDZdlIRQAAAAA0Hi5JExezN3dXTfccINuuOEGjRs3TlLpTrCbN2+2wmVSUpLy8vIqhMuCgoL6aAc2ZGdnKyoqqsqxuLg4azUaAAAAwC9XQkKCEhISqhzLzs52qEa9hMmqtGzZUoMGDZKbm5vy8vKUnp6uvXv3Wo8SuXi3WDSMkJAQpaamNnQbAAAAAOpRTQtFYWFhyszMrLVGvYfJ7du36+uvv9bXX3+t7777TkVFRdZY2UY9ZQICAuq7HQAAAACAC7g8TB49elSrVq3S119/rVWrVun48ePW2MWrj+7u7urVq5d+/etf69e//rV69Ojh6nYAAAAAAPXA6TBZUFCgDRs2WKuPP/74ozVW1aWrV199tRUeBw0axGokAAAAAPwC1SlM7ty50wqPGzZsUGFhoTV2cYD09/dXTEyMFSCvvvpq5zoGAAAAADQ4h8Jkdna2Vq9ebV26Wn53n4vDo5ubm3r27GmFx549e8rD45Lt8wMAAAAAuAQcSnmtW7eucdfVdu3a6Te/+Y1+/etfKyYmRoGBgS5tEgAAAADQuNhaMiwLkm5ubho6dKj+53/+R7fccos6dOhQL80BAAAAABonW2Gy/Orkd999Jy8vLxmGIcMwdM0119RLgwAAAACAxsfNkUndunWTVBoiy1YnT58+rUWLFmnChAm69tprFRERoYceekjz58+v8DgQAAAAAEDT49DK5JYtW5STk6Nvv/1Wq1ev1qpVq3TgwIEKc9LT0/XBBx/ogw8+kCR16dJFt9xyi2655RbdfPPNatasmeu7BwAAAAA0CMOsakcdBxw+fFirV6/W6tWr9c033+jEiRMVC///l8RKkqenp/r06WOFyx49esjNzaFFUVwiYWFhyszMVJs2bZSRkdHQ7QCNRsQzyxq6BQBANQ69MrShWwCaJEezQZ3DZHmmaSolJcUKl+vXr1dBQUHFFyoXLq+44goNGjTICpeRkZHOtgAnESaBqhEmAaDxIkwC9eOShsmLFRYW6vvvv7fC5Q8//FDpkSLlw2VoaKhuueUWDR48WPfdd5+r24EDCJNA1QiTANB4ESaB+tGgYfJi5e+3XL16tfbv3191M4ah4uLi+m4HVSBMAlUjTAJA40WYBOqHo9ngkty4eOWVV+r222/XO++8o927d2vJkiXq3r27JFmPFgEAAAAA/HLYes5kXZw9e1abN2/W999/r++//16bN29Wbm6uJBEiAQAAAOAXyuVh8sCBA/r++++1ceNGff/99/rxxx8r3C9Z3VW11113nQYOHOjqdgAAAAAA9cCpMFlYWKgffvjBWnX8/vvvKz0ipLbwOHDgQPXv319BQUHOtAIAAAAAuIRshckjR45UCI7btm3ThQsXrPGy4GgYRqUQSXgEAAAAgKbDoTA5evRobdy4Uenp6RV+Xl14NE2T8AgAAAAATZhDYXL+/PkVAiPhEQAAAAAub3W6Z5LwCAAAAACXN4fDZFRUFOERAAAAACDJwTCZnZ1NeAQAAAAAWNwcmUSQBAAAAACU51CYBAAAAACgPMIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANo+GbgCNS3Z2tqKioqoci4uLU1xc3CXuCAAAAICrJSQkKCEhocqx7Oxsh2oQJlFBSEiIUlNTG7oNAAAAAPWopoWisLAwZWZm1lqDy1wBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAtnk0dAOXQk5Ojg4ePKizZ88qNDRUHTp0kJub63J0Xl6e9u/fr5ycHIWEhKhjx47y9PS0VeP48eNKS0tTQUGBwsPDFRERIcMwbNXIz89XWlqaTpw4oauvvlphYWG2awAAAACAI5r0yuTevXsVGxuroKAgde/eXYMGDVJkZKQiIiI0Y8YMFRcXO1U/KytL9913n4KCghQdHa2YmBhdd911Cg0N1ZQpU1RQUFBrjaSkJA0aNEjBwcHq1auXBgwYoKuvvlqdOnVSYmKiTNOstcaRI0d0//33Kzg4WNdff70GDhyotm3bqmXLlpoxY4aKioqcep8AAAAAcDHDdCSt/AJt2LBBt912m/Lz86udM3z4cC1atEju7u626+/Zs0f9+vXTiRMnqp3Ts2dPrVmzRs2bN69yfP78+br33ntrDLUPP/ywZs6cWe0KY1JSkoYMGaKTJ09WW+Pmm2/WN998U+NqaVhYmDIzM9WmTRtlZGRUOw+43EQ8s6yhWwAAVOPQK0MbugWgSXI0GzTJlckTJ05o1KhRys/Pl5ubm6ZPn6709HTl5eVpzZo1io6OliQtWbJE06dPt12/sLBQw4cPt4LkxIkTtX//fuXn52vz5s0aPHiwpNKgN2HChCpr7Nq1S2PGjFFxcbF8fX01e/ZsZWdnKzc3V0uXLlVERIQkafbs2frwww+rrHHkyBENHz5cJ0+elJeXl15++WUdPnxYubm5WrdunXr37i2pNFg/++yztt8nAAAAAFSnSa5MPvXUU3r99dcllYaxuLi4CuO5ubm64YYbdOjQITVv3lxpaWkKCgpyuP4777xj1Zw0aZL1WmWKiorUr18/JSUlyTAM7dy5U9ddd12FOXfddZf+/e9/S5KWLl2qYcOGVRhPT09X586ddebMGYWFhWn//v3y9vauMOfBBx/UnDlzZBiGli9frttuu63CeF5enrp37649e/bIy8tLJ06c0BVXXFHle2JlEqgaK5MA0HixMgnUj8t2ZbK4uFgffPCBJCk4OFjjxo2rNMff31+TJk2SJJ07d07z58+39Rrvv/++JMnDw0NTpkypNO7p6ampU6dKkkzT1Ny5cyuMnzx5UgsXLpQkde/evVKQlKTw8HA99NBDkqSMjAytWrWqwnhWVpa1Yjl8+PBKQVKS/Pz8rPf53//+V19//bWdtwkAAAAA1WpyYXLTpk3W/YOxsbHV3g85fPhw63jZMsdXHjIzM7V9+3ZJ0oABAxQYGFjlvMGDB1v3Sl5cf8WKFSopKZEkjRgxotrXKj92cY0lS5ZY91r+/ve/r7bG6NGjtXHjRm3cuFE9e/asdh4AAAAA2NHkwuSePXus4yFDhlQ7Lzw8XF26dJEkbd261eX1fXx8rHsnd+/erXPnztmu0adPHyusXtxj2Upls2bNNHRo9Zd4NG/eXL1791bv3r0VHh5e7TwAAAAAsKPJhcmsrCzruF27djXOLQtXx44d0+nTp+utviTt27fPdg13d3e1adNGUmkALX97608//SSp9HpmHx8fSaUbA6WkpGjdunU6cuSIQ48VAQAAAIC68GjoBlzt6NGj1nGLFi1qnNuyZUvrOCsrq9pLVl1V/8Ybb6xQwzCMWl+zrMaZM2dUUFAgX19flZSUWOE0ODhYZ8+eVXx8vObMmaPc3NwK/d1777168cUXq91452KmaVaoYZe3t3eljYIAAAAAXDqFhYUqLCys8/mOLko1uTBZftWvfJirSvnx8peh1nf9shqBgYG1PuPy4hq+vr46d+6cdb+kt7e3br75ZqWkpFQ699SpU5o1a5Y+//xzLVq0SD169KjxtaTSx40EBATUOq868fHxmjZtWp3PBwAAAOCcl19+Wc8991y9v06TC5PlV9V8fX1rnFt+Be38+fOXrH5ZjdrOr67G2bNnrZ998803kqTOnTtr+vTp6tatm5o3b66dO3fqxRdf1KpVq5SRkaERI0Zo9+7d8vf3r/H1QkNDtWvXrlr7cqRfAAAAAJfe5MmT9fjjj9f5/E6dOunIkSO1zmtyYbL88yJPnz5d4/Mjy98n6Uiwq6p+TaqrHxQUpH379jl0n2ZVNTw8Kv6xDRgwQKtWrZKnp2eFn/Xv31+jR4/W/PnzlZWVpdmzZ+svf/lLja9nGEatgRMAAABA4+XsrWeGYTg0r8ltwNO6dWvr+NSpUzXOLT/u5+d3yeqX1cjPz1dBQYHtGq1ataoQKP/xj39UCJJlDMPQjBkzrO8///zzGl8LAAAAABzV5MLkVVddZR3XFvZycnKs47JdU+urfvmdXcvXKD+nphqtWrWydm11c3OzagQHBysyMrLa89u0aaOwsDBJ0t69e2t8LQAAAABwVJMLk+VXDqvalKZMSUmJdu7cKUlq27atw7udOlpfknbs2CGp9BEfHTt2tF0jNzdXhw4dkiRFRUVVGAsNDZVU+46yUmnglKT//ve/tc4FAAAAAEc0uTDZvXt363jp0qXVzktOTrYe0dG3b1+H63fu3Nm6pLSm+tnZ2UpKSpIk9ejRQ15eXrZ7XLlypYqKiqrssSyc7tu3r8Ztf0tKSrRnzx5Jjq++AgAAAEBtmlyYjIyMtC77/Oabb6q9jHTRokXW8ahRoxyu7+/vr5iYGElSamqqdu/eXeW8L774wno+y8X1Bw4caK2ELlmyxAqMdnocPny4JKm4uFiJiYnV9rt06VLrsSSDBg2qdh4AAAAA2NHkwqQkaxvcwsJCTZw4USUlJRXGt23bprfeekuS1L59e40cObJO9SVp/PjxlTbROXz4sKZOnSqpNHw+8MADFca9vb318MMPS5IyMjIUHx9f6cGgy5cv16effipJ6tevX6VnRMbGxlr3YT711FPatGlTpT737NmjuLg46/vyxwAAAADgDMO8OMU0AUVFRerXr591mWn//v01duxY+fv7KykpSe+8847y8vJkGIYWL16s2NjYCuePHTvWWu2Lj4/XtGnTKoybpqk77rjDWjm84YYbNG7cOIWEhGjnzp2aPXu2jh8/LkmaPXt2lSHu9OnT6tatmw4ePChJGjFihO644w55eXlp3bp1eu+993ThwgV5e3vru+++q3BpbJlFixbpt7/9raTSTXnGjBmjvn37ytvbW1u2bNH7779vBd1nnnlGL7/8crW/s7CwMGVmZqpNmzbKyMio9XcMXC4inlnW0C0AAKpx6JWhDd0C0CQ5mg2a3HMmJcnT01OLFy/WkCFDtG3bNq1fv17r16+vNGfmzJmVgqQjDMNQYmKicnNztXr1aqWkpGj8+PGV5k2ZMkUTJkyoskZgYKC+/PJLDR06VGlpaVq8eLEWL15cYY6fn5/mzZtXZZCUpNtvv10JCQl67LHHVFRUpLlz52ru3LmVep08ebKef/552+8TAAAAAKrTJC9zlUofv7Fp0ybNmjVLffr0UYsWLeTl5aWIiAg9+OCDSk5O1rhx4+pc38/PTytXrlRiYqJiYmIUFBQkT09PhYWFafTo0dqwYYNeeOGFGh/42alTJ6WkpOjFF19UdHS0AgIC5Ovrq44dO+qxxx7Tzp07NWLEiBr7mDBhglJSUhQXF6eOHTuqefPmVo0//elP2rFjh1588UW5uTXZP2oAAAAADaBJXuYK+7jMFagal7kCQOPFZa5A/XA0G7BcBQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsM2joRtA45Kdna2oqKgqx+Li4hQXF3eJOwIAAADgagkJCUpISKhyLDs726EahElUEBISotTU1IZuAwAAAEA9qmmhKCwsTJmZmbXW4DJXAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbYRJAAAAAIBthEkAAAAAgG2ESQAAAACAbR4N3QAal+zsbEVFRVU5FhcXp7i4uEvcEQAAAABXS0hIUEJCQpVj2dnZDtUgTKKCkJAQpaamNnQbAAAAAOpRTQtFYWFhyszMrLUGl7kCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbCNMAgAAAABsI0wCAAAAAGwjTAIAAAAAbPNo6AbQuGRnZysqKqrKsbi4OMXFxV3ijgAAAAC4WkJCghISEqocy87OdqgGYRIVhISEKDU1taHbAAAAAFCPalooCgsLU2ZmZq01uMwVAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGAbYRIAAAAAYBthEgAAAABgG2ESAAAAAGCbR0M3cCnk5OTo4MGDOnv2rEJDQ9WhQwe5ubkuR+fl5Wn//v3KyclRSEiIOnbsKE9PT1s1jh8/rrS0NBUUFCg8PFwREREyDMNlPQIAAACAKzXplcm9e/cqNjZWQUFB6t69uwYNGqTIyEhFRERoxowZKi4udqp+VlaW7rvvPgUFBSk6OloxMTG67rrrFBoaqilTpqigoKDWGklJSRo0aJCCg4PVq1cvDRgwQFdffbU6deqkxMREmaZZp95++OEHeXl5yTAMHTp0qE41AAAAAKA6TTZMbtiwQdHR0fryyy8rhcb09HRNmjRJt99+e50D5Z49e9SlSxd9/PHHlULjiRMn9NJLL2nAgAE6d+5ctTXmz5+vvn37au3atVXWHzt2rB555BHbgfLs2bO6++67VVRUZOs8AAAAAHBUkwyTJ06c0KhRo5Sfny83NzdNnz5d6enpysvL05o1axQdHS1JWrJkiaZPn267fmFhoYYPH64TJ05IkiZOnKj9+/crPz9fmzdv1uDBgyWVrjpOmDChyhq7du3SmDFjVFxcLF9fX82ePVvZ2dnKzc3V0qVLFRERIUmaPXu2PvzwQ1v9TZgwQQcOHLD9vgAAAADAUU0yTL722ms6efKkJGnmzJl69tlnFRYWpubNm2vQoEFau3atFdZmzJih48eP26o/Z84c7d27V5I0adIkzZw5U9dcc418fX3Vs2dPffXVV+rZs6ck6aOPPtJPP/1UqUZ8fLwKCwslSQsWLFBcXJyCg4N1xRVXaNiwYVq/fr0CAgIkSVOnTrXm1uaf//yn5s2bZ+v9AAAAAIBdTS5MFhcX64MPPpAkBQcHa9y4cZXm+Pv7a9KkSZKkc+fOaf78+bZe4/3335ckeXh4aMqUKZXGPT09NXXqVEmSaZqaO3duhfGTJ09q4cKFkqTu3btr2LBhlWqEh4froYcekiRlZGRo1apVtfa1b98+ayW0devWNt4RAAAAANjT5MLkpk2brFXJ2NhYubu7Vzlv+PDh1vGyZcscrp+Zmant27dLkgYMGKDAwMAq5w0ePFjNmzevsv6KFStUUlIiSRoxYkS1r1V+rLYeCwsLdffdd+vcuXMaOHCgHnjggdreCgAAAADUWZMLk3v27LGOhwwZUu288PBwdenSRZK0detWl9f38fGx7p3cvXt3hY14HK3Rp08fK6zW1uNf/vIXbd26VS1atNBHH31UbYgGAAAAAFdocmEyKyvLOm7Xrl2Nc8PDwyVJx44d0+nTp+utvlR6CardGu7u7mrTpo2k0gBa3a6uX331ld58801JpfdzhoWF1dgXAAAAADjLo6EbcLWjR49axy1atKhxbsuWLa3jrKysai9ZdVX9G2+8sUINwzBqfc2yGmfOnFFBQYF8fX0rjGdlZWnMmDGSpPHjx2vkyJG1voeamKap3NzcOp/v7e0tb29vp3oAAAAAUHeFhYUOb+BZFUcfTdjkwmT5Vb/yYa4q5cdreh6kq+uX1QgMDKz1ctSLa5QPkyUlJfrf//1fHT9+XNddd51mzJjh0HuoyZEjR6xdZOsiPj5e06ZNc7oPAAAAAHXz8ssv67nnnqv312lyYbL8qtrFq3gXK7+Cdv78+UtWv6xGbefX1uPrr7+u1atXy9vbW//6178cqleb0NBQ7dq1q87nsyoJAAAANKzJkyfr8ccfr/P5nTp10pEjR2qd1+TCZFBQkHV8+vTpCt9frPx9ko4GsYvr16S6+kFBQdq3b59D92lWV2Pz5s3661//Kqn0WZmdO3eutZYjDMOQv7+/S2oBAAAAuPScvfXMMAyH5jW5DXjKP1/x1KlTNc4tP+7n53fJ6pfVyM/PV0FBge0aZ86c0ejRo3XhwgXFxsZaz5YEAAAAgEulya1MXnXVVdZxbWEvJyfHOi7bNbW+6pff2bV8jZycnAoBtboarVq1ko+PjyTp3XffVVpamjw9PXXXXXdp5cqVlc7bv3+/dbxu3Trt3r1bkhQdHa2QkJAa+wYAAACA2jS5MFk+mKWkpKhPnz5VzispKdHOnTslSW3bttUVV1xRp/qjR4+udu6OHTsklT7io2PHjtXWqC5M5ubm6tChQ5KkqKgo6+dlq5lFRUX6/e9/X2vPY8eOtY4///xzp3d8BQAAAIAmd5lr9+7dreOlS5dWOy85Odl6REffvn0drt+5c2d5enrWWj87O1tJSUmSpB49esjLy8t2jytXrlRRUZHtHgEAAACgvjW5MBkZGanIyEhJ0jfffFPhUtPyFi1aZB2PGjXK4fr+/v6KiYmRJKWmplqXj17siy++sJ7PcnH9gQMHWiuhS5YssQKjoz1OmzZNpmnW+BUfH2/NT0tLs37OqiQAAAAAV2hyYVKStQ1uYWGhJk6cqJKSkgrj27Zt01tvvSVJat++ve2AVX6b3fHjx1faROfw4cOaOnWqpNLw+cADD1QY9/b21sMPPyxJysjIUHx8fKUHgy5fvlyffvqpJKlfv37q0aOHrR4BAAAAoD41yTB5//33q2fPnpKkjz/+WIMGDdLcuXO1cOFCPf300+rfv78KCgpkGIbefvvtCpegSqX3GBqGIcMwNG3atEr1b731Vt1+++2SpLVr16p37976+9//rs8//1zTp09Xjx49dOzYMUnSSy+9pJYtW1aq8dRTT+nqq6+WVPpQ0VGjRmnevHlasGCB4uLiNGLECEmlwfNvf/ubw9vzAgAAAMCl0OQ24JEkT09PLV68WEOGDNG2bdu0fv16rV+/vtKcmTNnKjY21nZ9wzCUmJio3NxcrV69WikpKRo/fnyleVOmTKn2sR2BgYH68ssvNXToUKWlpWnx4sVavHhxhTl+fn6aN29ehXssAQAAAKAxaJIrk1Lp4zc2bdqkWbNmqU+fPmrRooW8vLwUERGhBx98UMnJyRo3blyd6/v5+WnlypVKTExUTEyMgoKC5OnpqbCwMI0ePVobNmzQCy+8UOOKYqdOnZSSkqIXX3xR0dHRCggIkK+vrzp27KjHHntMO3futFYoAQAAAKAxMcyLb9bDZSksLEyZmZlq06aNMjIyGrodoNGIeGZZQ7cAAKjGoVeGNnQLQJPkaDZosiuTAAAAAID6Q5gEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADYRpgEAAAAANhGmAQAAAAA2EaYBAAAAADY5tHQDaBxyc7OVlRUVJVjcXFxiouLu8QdAQAAAHC1hIQEJSQkVDmWnZ3tUA3CJCoICQlRampqQ7cBAAAAoB7VtFAUFhamzMzMWmtwmSsAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANo+GbgCNS3Z2tqKioqoci4uLU1xc3CXuCAAAAICrJSQkKCEhocqx7Oxsh2oQJlFBSEiIUlNTG7oNAAAAAPWopoWisLAwZWZm1lqDy1wBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAtnk0dANoXLKzsxUVFVXlWFxcnOLi4i5xRwAAAABcLSEhQQkJCVWOZWdnO1SDMIkKQkJClJqa2tBtAAAAAKhHNS0UhYWFKTMzs9YaXOYKAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsM2joRu4FHJycnTw4EGdPXtWoaGh6tChg9zcXJej8/LytH//fuXk5CgkJEQdO3aUp6enrRrHjx9XWlqaCgoKFB4eroiICBmG4bIeAQAAAMCVmvTK5N69exUbG6ugoCB1795dgwYNUmRkpCIiIjRjxgwVFxc7VT8rK0v33XefgoKCFB0drZiYGF133XUKDQ3VlClTVFBQUGuNpKQkDRo0SMHBwerVq5cGDBigq6++Wp06dVJiYqJM06y1xn/+8x/98Y9/1IABA9S6dWsFBgbqpptu0h//+Edt3brVqfcIAAAAAFUxTEfSyi/Qhg0bdNtttyk/P7/aOcOHD9eiRYvk7u5uu/6ePXvUr18/nThxoto5PXv21Jo1a9S8efMqx+fPn6977723xlD78MMPa+bMmVWuUhYXF2vixIl69913qz3fMAyNHz9er776qvz8/KqdFxYWpszMTLVp00YZGRnVzgMuNxHPLGvoFgAA1Tj0ytCGbgFokhzNBk1yZfLEiRMaNWqU8vPz5ebmpunTpys9PV15eXlas2aNoqOjJUlLlizR9OnTbdcvLCzU8OHDrSA5ceJE7d+/X/n5+dq8ebMGDx4sqXTVccKECVXW2LVrl8aMGaPi4mL5+vpq9uzZys7OVm5urpYuXaqIiAhJ0uzZs/Xhhx9WWeOFF16wgmTz5s31xBNPKDExUR9++KEmTpwoX19fmaapd955R3fddZdDq5wAAAAA4IgmuTL51FNP6fXXX5dUGsbi4uIqjOfm5uqGG27QoUOH1Lx5c6WlpSkoKMjh+u+8845Vc9KkSdZrlSkqKlK/fv2UlJQkwzC0c+dOXXfddRXm3HXXXfr3v/8tSVq6dKmGDRtWYTw9PV2dO3fWmTNnFBYWpv3798vb29saP3HihNq2bavz58/rqquu0oYNG9ShQ4cKNQ4fPqxbbrlF+/fvlyT961//0t13313le2JlEqgaK5MA0HixMgnUj8t2ZbK4uFgffPCBJCk4OFjjxo2rNMff31+TJk2SJJ07d07z58+39Rrvv/++JMnDw0NTpkypNO7p6ampU6dKkkzT1Ny5cyuMnzx5UgsXLpQkde/evVKQlKTw8HA99NBDkqSMjAytWrWqwvjSpUt1/vx5SdLkyZMrBUlJateunT766CPr+7LfCwAAAAA4q8mFyU2bNunkyZOSpNjY2Grvhxw+fLh1vGyZ4ysPmZmZ2r59uyRpwIABCgwMrHLe4MGDrXslL66/YsUKlZSUSJJGjBhR7WuVH7u4RlJSknV85513VlujV69euuqqqySJzXgAAAAAuEyTC5N79uyxjocMGVLtvPDwcHXp0kWSvZDlaH0fHx/r3sndu3fr3Llztmv06dPHCqsX95idnS1J8vLyUkhISLU1DMNQ69atJclayQQAAAAAZzW5MJmVlWUdt2vXrsa54eHhkqRjx47p9OnT9VZfkvbt22e7hru7u9q0aSOpNICWv7113Lhxmjt3rv75z3/W+MzM3NxcK7xee+21NfYLAAAAAI7yaOgGXO3o0aPWcYsWLWqc27JlS+s4Kyur2ktWXVX/xhtvrFDDMIxaX7OsxpkzZ1RQUCBfX19J0q9//etae5WkF1980Xo8ym9+85ta55umqdzcXIdqV8Xb27vCRkEAAAAALq3CwkIVFhbW+XxH92htcmGy/Kpf+TBXlfLj5S9Dre/6ZTUCAwNrfcblxTXKwmRtSkpK9Prrr+u1116TVProkMcff7zW844cOaKAgACHXqMq8fHxmjZtWp3PBwAAAOCcl19+Wc8991y9v06TC5PlV9VqC17lV9AcvZ/QFfXLajgSDOvSY0pKih599FGtW7dOUunlsvPnz1dwcHCt54aGhmrXrl0OvU5VWJUEAAAAGtbkyZMdWkiqTqdOnXTkyJFa5zW5MFn+eZGnT5+u8fmR5e+TdHTF7+L6NamuflBQkPbt2+fQfZp2eszIyNCzzz6rxMREa2k6MDBQH3zwgYYOdew5TIZhyN/f36G5AAAAABofZ289MwzDoXlNbgOesp1LJenUqVM1zi0/7ufnd8nql9XIz89XQUGB0z2WlJTo3XffVadOnfThhx9aQXLEiBH66aefNGrUqBpfAwAAAADsanJhsuyZilLtYS8nJ8c6Lts1tb7ql9/ZtXyN8nNqqtGqVSv5+PhUGj906JAGDRqkCRMmKC8vT1LpsyXXrVunL774QqGhoTXWBwAAAIC6aHJhsvzKYUpKSrXzSkpKtHPnTklS27ZtdcUVV7i0viTt2LFDUuk9ix07drRdIzc3V4cOHZIkRUVFVRo/cuSIYmJitH79ekmlIXX+/PnauHGj+vfvX/ubAQAAAIA6anJhsnv37tbx0qVLq52XnJxsPaKjb9++Dtfv3LmzPD09a62fnZ2tpKQkSVKPHj3k5eVlu8eVK1eqqKioyh7z8/P1m9/8RmlpaZKk4cOHKzU1VXfddZfD1zgDAAAAQF01uTAZGRmpyMhISdI333xT7WWkixYtso7t3FPo7++vmJgYSVJqaqp2795d5bwvvvjCunfx4voDBw60VkKXLFliBUY7Pc6fP18//vijJOn222/XwoULdeWVVzr8PgAAAADAGU0uTEqytsEtLCzUxIkTVVJSUmF827ZteuuttyRJ7du318iRI+tUX5LGjx9faROdw4cPa+rUqZJKw+cDDzxQYdzb21sPP/ywpNIdWOPj4ys9GHT58uX69NNPJUn9+vVTjx49Koz//e9/l1S6w+s//vEPeXg0uY15AQAAADRihnlximkCioqK1K9fP+sy0/79+2vs2LHy9/dXUlKS3nnnHeXl5ckwDC1evFixsbEVzh87dqwSExMlSfHx8Zo2bVqFcdM0dccdd1grhzfccIPGjRunkJAQ7dy5U7Nnz9bx48clSbNnz1ZcXFylHk+fPq1u3brp4MGDkkp3Xr3jjjvk5eWldevW6b333tOFCxfk7e2t7777rsKlsQUFBdZjQrp06aJXX33Vod+Lr6+vBgwYUOVYWFiYMjMz1aZNG2VkZDhUD7gcRDyzrKFbAABU49Arjj36DIA9jmaDJrmc5enpqcWLF2vIkCHatm2b1q9fb21SU37OzJkzKwVJRxiGocTEROXm5mr16tVKSUnR+PHjK82bMmWKJkyYUGWNwMBAffnllxo6dKjS0tK0ePFiLV68uMIcPz8/zZs3r0KQlKRjx45Zxzt27ND//M//ONR3u3btrA19AAAAAMAZTfIyV6l0Z9NNmzZp1qxZ6tOnj1q0aCEvLy9FRETowQcfVHJyssaNG1fn+n5+flq5cqUSExMVExOjoKAgeXp6KiwsTKNHj9aGDRv0wgsv1LgZTqdOnZSSkqIXX3xR0dHRCggIkK+vrzp27KjHHntMO3fu1IgRIyqdl52dXee+AQAAAMAVmuRlrrCPy1yBqnGZKwA0XlzmCtQPR7NBk12ZBAAAAADUH8IkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDbCJAAAAADANsIkAAAAAMA2wiQAAAAAwDaPhm4AjUt2draioqKqHIuLi1NcXNwl7ggAAACAqyUkJCghIaHKsezsbIdqECZRQUhIiFJTUxu6DQAAAAD1qKaForCwMGVmZtZag8tcAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALYRJgEAAAAAthEmAQAAAAC2ESYBAAAAALZ5NHQDaFyys7MVFRVV5VhcXJzi4uIucUcAAAAAXC0hIUEJCQlVjmVnZztUgzCJCkJCQpSamtrQbQAAAACoRzUtFIWFhSkzM7PWGlzmCgAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsM2joRtA45Kdna2oqKgqx+Li4hQXF3eJOwIAAADgagkJCUpISKhyLDs726EahElUEBISotTU1IZuAwAAAEA9qmmhKCwsTJmZmbXWIEwCaJIinlnW0C0AAAA0adwzCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsI0wCQAAAACwjTAJAAAAALCNMAkAAAAAsM2joRsAAAAA6iLimWUuqXPolaEuqQNcbgiTABoNV/2jAAAAAPWPMAkAAIDLGiucQN1wzyQAAAAAwDbCJAAAAADANi5zBQAAAFyAy2VxuWFlEgAAAABgGyuTAAAAQCPCCid+KQiTwC9MYWGhXn75ZU2ePFne3t4N3Y4kHukB55gXinRm0wIF9L5LhodnQ7cDOI3PNJqSxvjvDjQehEngF6awsFDPPfecHn/8cf5SR5NgFhfpzH/+Jf8eo/iHN5oEPtNoLFzxH3tLCvOV/hb/7kDVCJMAAAAAanR9/Eq5eTdzqgaX3TY9hEkAAAAA9Y57QZsewiQAAACAXwxCaeNBmAQuY2ycAwAALleEUufxnEkAAAAAgG2XxcpkTk6ODh48qLNnzyo0NFQdOnSQm5vrcnReXp7279+vnJwchYSEqGPHjvL0tLd72/Hjx5WWlqaCggKFh4crIiJChmE4fL5pmjp8+LDS09Pl5eWl9u3bKzg42O5bwS+IK26EBwAAgHNceaXXL22Vs0mHyb179+qJJ57QV199peLiYuvn4eHhevTRR/XYY4/J3d29zvWzsrL05JNPauHChSooKLB+3qpVK/3xj3/Us88+Kx8fnxprJCUl6emnn9batWsr/DwyMlKTJ0/W//7v/9YYKk3T1Lx58/TSSy9p9+7dFcb69++v1157Tb169bL/5lBBY7octKQwv6FbAAAAAJpumNywYYNuu+025edX/od3enq6Jk2apPXr12vRokV1CpR79uxRv379dOLEiUpjJ06c0EsvvaTVq1drzZo1at68eZU15s+fr3vvvbdC0C1ff+zYsfrhhx80c+bMKgOlaZp69NFHNWvWrCrrr1+/XjfddJPmzZunu+++2+Y7bFgJCQmKi4tzuo6rQuDZrV/qiq7DXFKrKWqMv5/G1hP9/LI0tt8P/dSssfXTGDW23xH91Kyx9dPYNLbfT2PrR3Ldv6Vr0yTvmTxx4oRGjRql/Px8ubm5afr06UpPT1deXp7WrFmj6OhoSdKSJUs0ffp02/ULCws1fPhwK0hOnDhR+/fvV35+vjZv3qzBgwdLKl11nDBhQpU1du3apTFjxqi4uFi+vr6aPXu2srOzlZubq6VLlyoiIkKSNHv2bH344YdV1khMTLSCZPv27bV06VLl5uYqOztbs2bNkq+vr4qLizV27Fjt2rXL9vtsSH+Of1URzyxz+stVzm5tPCuTjVFj/P00tp7o55elsf1+6Kdmja2fxqix/Y7op2aNrZ/GprH9fhpbP1JpmLwUmmSYfO2113Ty5ElJ0syZM/Xss88qLCxMzZs316BBg7R27VorrM2YMUPHjx+3VX/OnDnau3evJGnSpEmaOXOmrrnmGvn6+qpnz5766quv1LNnT0nSRx99pJ9++qlSjfj4eBUWFkqSFixYoLi4OAUHB+uKK67QsGHDtH79egUEBEiSpk6das0tU1hYqGeffVaSFBAQoPXr12vYsGG64oorFBwcrIcffljz58+35k6bNs3WewQAAACAmjS5MFlcXKwPPvhAkhQcHKxx48ZVmuPv769JkyZJks6dO2eFLke9//77kiQPDw9NmTKl0rinp6emTp0qqfRS1Llz51YYP3nypBYuXChJ6t69u4YNq7wsHh4eroceekiSlJGRoVWrVlUYX7FihTIyMiRJDz30kMLCwirViI2NVffu3SVJCxcu1OnTp+28TQAAAACoVpMLk5s2bbJWJWNjY6u9H3L48OHW8bJlji9NZ2Zmavv27ZKkAQMGKDAwsMp5gwcPtu6VvLj+ihUrVFJSIkkaMWJEta9VfuziGl9++WWV86qrUVxcrJUrV1Y7DwAAAADsaHJhcs+ePdbxkCFDqp0XHh6uLl26SJK2bt3q8vo+Pj7WvZO7d+/WuXPnbNfo06ePFVYv7rGsRmBgoPr06VNtjaFD/9/2wnbeJwAAAADUpMmFyaysLOu4Xbt2Nc4NDw+XJB07dszhS0DrUl+S9u3bZ7uGu7u72rRpI6k0PJqmWalGWFhYjbvRlu+hfIgFAAAAAGc0uUeDHD161Dpu0aJFjXNbtmxpHWdlZVV7yaqr6t94440VahiGUetrltU4c+aMCgoK5OvrW6FGbT1ceeWVMgxDpmlWCLEXO3bsmNVnWYCti5qeiWlHUc5RZSSMcUktVyjOP92I+in9jwpH/m+cJNf8vp3VuH4/pRpbT/RTEz7TtaGfmjW2fvhM145+ata4+uHzXBtX9hM2r+Zn1DsqOzvbqX/Tl2WNsoxQnSYXJssHpvJhrirlx8tfhlrf9ctqBAYG1vqMy4tr+Pr6Ki8vT3l5eQ714O7ursDAQOXk5NT4HsuedVlSUqIjR47UWPNSKc472dAtVND4+jnV0C1U0Nh+P1Lj64l+asZnumb0U7PG1o/EZ7o29FOzxtcPn+eauKqfzDyXlJEkl/ybviwjVKfJhcnc3FzruGwVrzre3t7W8fnz5y9Z/bIatZ1fXQ07PZSvUdN79PHxUUFBgdzd3RUUFFRrzeq4amUSAAAAQN2Vv0XOruPHj6u4uFg+PjWvlDa5MFk+CJ0+fbrGYFT+PklHQllV9WtSXf2goCDt27fPofs0q6rRqlUrh3soP6em9+joyiwAAAAASE1wA57WrVtbx6dO1bwcX37cz8/vktUvq5Gfn6+CggLbNby8vKzLW2vr4fz589ZrOPoeAQAAAKA2TS5MXnXVVdZxbUErJyfHOnb0BtW61i+/q2r5GuXn1FSjVatWFZaZy2rUtQcAAAAAcEaTC5PlVw5TUlKqnVdSUqKdO3dKktq2basrrrjCpfUlaceOHZJKN8Hp2LGj7Rq5ubk6dOiQJCkqKqrKPtLS0ircQ1ldD1XVAAAAAIC6anJhsnv37tbx0qVLq52XnJxsbXnbt29fh+t37txZnp6etdbPzs5WUlKSJKlHjx7y8vKy3ePKlStVVFRUZY9lNYqKirRy5cpqa5Svb+d9AgAAAEBNmlyYjIyMVGRkpCTpm2++qfYy0kWLFlnHo0aNcri+v7+/YmJiJEmpqanavXt3lfO++OILaweli+sPHDjQWgldsmSJFRjt9DhixAjreOHChVWeX1RUZIXJgIAADRo0qNr3BQAAAAB2NLkwKUmPP/64JKmwsFATJ05USUlJhfFt27bprbfekiS1b99eI0eOrFN9SRo/fnylTXQOHz6sqVOnSioNnw888ECFcW9vbz388MOSpIyMDMXHx1faunf58uX69NNPJUn9+vVTjx49Koz36tVLffr0kSTNnz9fK1asqDBumqaeffZZpaenS5ImTpxYYXUUAAAAAJxhmM48gKSRKioqUr9+/azLTPv376+xY8fK399fSUlJeuedd5SXlyfDMLR48WLFxsZWOH/s2LFKTEyUJMXHx2vatGkVxk3T1B133GGtHN5www0aN26cQkJCtHPnTs2ePVvHjx+XJM2ePVtxcXGVejx9+rS6deumgwcPSipdabzjjjvk5eWldevW6b333tOFCxfk7e2t7777rsKlsWW2bNmim2++WYWFhfL09NT48eN18803Kz8/XwsWLNCyZcskSddcc42Sk5MVEBDgxG8VvwSZmZk6fPiwJKldu3YObywFNARnP68lJSU6cOCAMjMz5efnp2uuuUZXXnllfbQKXBJ8ptGY8Hc0HGI2UVlZWWZ0dLQpqcovT09P8913363y3DFjxljz4uPjq5xz9uxZ85Zbbqm2viRzypQpZklJSbU9pqammu3bt6/2fD8/P/OLL76o8X1+9tlnZvPmzautcc0115h79uxx+PeGS6+2z1H5r7lz51ZZY/ny5Wb37t0rze/WrZu5bNmyS/uGcNmZPXt2jX9fXszZz2txcbH55ptvmm3btq1wvru7uzl06FBz9+7dTr4jXO4c/UxfuHDB9PLycvjv8LS0tCrr8JmGKx09etScNm2aOWzYMPPaa681fX19zaioKPPOO+8033//ffPChQs1ns/f0bCjyYZJ0zTNwsJCc9asWWafPn3MFi1amF5eXmZERIT54IMPmjt27Kj2PEfCpGmW/o8lMTHRjImJMYOCgkxPT08zLCzMHD16tLlhwwaHeszNzTVffPFFMzo62gwICDB9fX3Njh07mo899li1/6dzsQMHDpiPPPKI2aFDB9PHx8cMCAgwu3btar788svm2bNnHaqBhnPxX7Z2w+Qbb7xR63mvv/76pX9juGz07t3b4TDp7Of1woUL5siRI2s839fX11y3bp0L3yEuN45+pg8ePOjw39/VhUk+03Cl5cuXmwEBATV+nrp27WomJydXeT5/R8OuJh0mgcbu/PnzpmEYpiRzwoQJ5ldffVXjV0ZGRoXzv/nmG+v8Vq1amR9//LF56tQp89SpU+a8efPMli1bWn95r169uoHeJZqyDz74wKH/+Gaarvm8xsfHV/gH0bfffmvm5eWZ6enp5nPPPWe6ubmZkswWLVqYx44dq4d3jKbOzmd65cqV1ty///3vtf4dnp+fX6kGn2m4yk8//WT6+vpan6fY2Fjz7bffNhcsWGA+//zzZlRUlDUWEBBQaYXw/2vvzqOiuLI/gH/Zd1FQVCCAgIKIDopbUOMyJEbjRoSIxkSzTDLR6GQSM5lkojiJjhl1XGJ0RuNE1Gj8QVziFmNUUNyNG4qILDIDKovKJnt3398fnH5TRe8NBJf7OafPqe56detV8Szr9nv9iq/RzBycTDLWiq5evSouuvv37zdpW5VKRf379ycAZG1tTRcuXNAoc/78ebK2tiYA1L9/f73DrhkzVmlpKR07doxee+01srGxMerGuznaa2FhoRjW36VLFyovL9eI8eWXX4r6/OlPf2rysbIngzltmuh/w2EB0IMHD0zeL7dp1pxeeukl0Va++uorjWtobW0tzZgxQ5QZOXKkWMfXaGYuTiYZa0U7d+4UF9WsrCyTtr106ZLYNjo6Wme56OhoUe7KlStNrTJ7wvXr10/n0CV9N97N0V5XrFghu1HSRqlUkoeHBwGgDh06kFKpNOs42ZPD3DZNRPSHP/yBAJC3t7dZ++Y2zZpLdXW1+CKkT58+Or88rq2tpdDQUNHu1COe+BrNzPVYPhqEsUdFZmYmAMDGxga+vr4mbbt3716xLH3uaGPSdeoZfhkzV1FRkVnbNUd7lcYYN26c1u0tLS3FDN3FxcU4d+6cWfVlTw5z2zTwv2t4t27dzNqe2zRrLpcvXxbPLY+OjoaFhYXWcra2thgzZox4f/HiRQB8jWbm42SSsVakvhEJCAiAtbU1lEolcnNzkZycjPPnz6O8vFznthkZGWJ59OjROstJ1124cKEZas2eZBkZGaiurhav69evG72dmrntVR2jZ8+eeOqpp3TGeOGFF3TGYKwxc9s0oJlM1tTUID09HUlJSbhy5Yq4ude3b4DbNGu6wsJCsWzoy+nOnTuL5erqagB8jWbms27tCjD2JLtx4waAhgv7okWLsHTpUty/f1+st7a2RmRkJOLi4jBw4EDZtnfu3AEAODs7w83NTec+3Nzc4OTkhMrKStl/FoyZw87OTu97XZraXokIBQUFAAzfKElvYrjNM0PMbdP19fXiWdF2dnZ4++238c0330ChUIgyLi4umDRpEubNm6dxc81tmjWn0NBQbNiwAQAwdOhQvWWlvYHqL0L4Gs3MxckkY61I/a12UlISkpKSNNYrFAocOHAABw8exIoVKzBr1iyxTn3R1nfRV3N3d0dlZaX4z4KxX1tT2+v9+/dFL4+hGO7u7mKZ2zxrKbm5uVAqlQCAlStXai1TUVGB9evXY8eOHdi1axeGDBki1nGbZs3J398f/v7+BsulpqZi27ZtAABvb290794dAF+jmfl4mCtjraSyshK3b98W73v37o2ff/4ZpaWluHv3LpKSkjBp0iQAgEqlwuzZs7F//35RXn0Bll6UdVGXqaysbM5DYMxoTW2v0hsOQzGk67nNs5ai/jJQLTY2FhcvXkRlZSVyc3Oxa9cu9O7dG0DDjfaECROQn58vynObZr+28+fP4/nnnxe95x9//DFsbW0B8DWamY+TScZaSXZ2NqysrGBlZYWxY8fi2LFjiIyMhKurK9zd3TFs2DBs27YNy5YtE9t88MEHUKlUACB+T+ng4GBwX+phW+rfRjD2a2tqe5X+fthQDOkwRW7zrKVIr+F//etfsXXrVoSFhcHR0RG+vr4YP348zpw5g4kTJwJoSCg///xzsT23afZrKS8vx8cff4yBAweKpG/KlCn4/e9/LysD8DWamY6TScZaSa9evaBQKKBQKLB79244OztrLTd79myEh4cDAK5fv45Lly4BADp06AAAKC0tNbgvdRlj/pNgrCU0tb2qtzcmhnQ9t3nWUmbNmiWu4fPmzdM6e6aNjQ1WrlwJJycnAEBCQoLoFeI2zVpafX091qxZg8DAQHzxxRei7b355puIj4+HpeX/0gC+RjNzcTLJ2EPOysoKUVFR4r36h/Pq2dikE/booi6jK2FlrKU1tb1KZx80FEO6nts8a21eXl54+umnATTcRGdnZwPgNs1a1qVLlzBgwADMnDkTxcXFAAAfHx/s378fX3/9NWxsbGTl+RrNzMXJJGOPgODgYLF87949AECnTp0ANFyUiUjntkSEkpISANA7VTdjLamp7dXZ2Vn07hi6UVFv3zgGY61F2zWc2zRrCUqlEnPnzkW/fv3EMyTd3Nzwj3/8AxkZGRg1apTW7fgazczFySRjjwDpVPOurq4A/vctYF1dnd6ptTMyMsQMayEhIS1YS8Z0a472qo6RmpoqfjusTWpqqljmNs8eBtqu4QC3ada8iAgzZ87EggULoFAoYGFhgdmzZyM7Oxvvv/8+7O3tdW7L12hmLk4mGWslL7/8MkJDQ/Hb3/5W70UXANLT08Wy+plQffv2FZ/t2bNH57bSdREREeZWl7EmaY72qo5RUFCA8+fPmxWDseZQWVmJsLAwhIaG4k9/+pPB8upruI2NjewZfNymWXNasGAB1q5dCwDo2LEjjh8/jpUrV6Jt27YGt+VrNDMXJ5OMtZKwsDCkpaXhyJEjOHTokM5y1dXV2Lx5M4CGYSSDBw8GAIwdO1ZM+LB9+3atw1KICDt27AAAWFhYYNy4cc19GIwZpTna6/jx48Xy9u3bte6ntLQUR44cAQB0794dQUFBzVJ/xqScnJzg5eWFtLQ0rFmzRjZsr7G0tDScOHECQMPD5KW/EeM2zZpLeXk5/v73vwMA2rVrhxMnTpiUqPE1mpmLk0nGWklsbKyYSe31119HXl6eRpnq6mrMmjULOTk5ABpmdlXPfObp6YnY2FgAwJkzZ7Bu3TqN7deuXYvTp08DaOgJlf5AnrFfU3O016ioKNGrs3LlSjGzsZpSqcTMmTNRU1MDoOFROoy1lKlTpwJo6KWMjY1FbW2tRplbt27htddeE8NcG/dicptmzWXLli3imY0LFy5EQECASdvzNZqZy4L0/cqWMdaiVqxYgT/+8Y8AGr7pfvvttxEWFgZra2ukp6fju+++Q1ZWFgAgPDwcKSkpsmm0c3NzER4eLn7sPm3aNIwaNQoqlQr79u3Dli1bADQ8IPj8+fOy4VWMNYfc3Fx06dIFABAXF4f58+frLdvU9vrDDz9gwoQJAAAXFxfMmjVLxIyPjxc9QAMHDkRKSgqsra2b8WjZk8DYNq1SqTBx4kTs2rULQMNMmW+99Ra6deuG8vJyXL16Ff/+979RUVEBAJgxYwZWr16tEYfbNGsOkydPxrZt2wAAGzduhIeHh1Hb9e/fH25ubgD4Gs3MRIyxVqNSqWjOnDlkaWlJAHS+Ro4cSffu3dMaIyUlhTp06KBzWw8PDzp58uSvfGTsSXHz5k3R1uLi4gyWb472umrVKrK2ttYZIzw8nAoLC5vpCNmTxpQ2XVFRQSNGjNB7/bawsKAPP/yQFAqFzjjcpllTDR8+XG871PVKSkqSxeFrNDMVD3NlrBVZWFhgyZIluHbtGt544w2Eh4ejffv2sLW1hY+PD2JjY7F//378+OOP4pvDxgYPHowrV67gk08+QUhICJycnODs7IwePXrgL3/5C65evSqeccZYa2uO9vruu+/il19+weuvvw5fX1/Y2trCzc0NERER+Oqrr3Dq1Cmjv5VnrCmcnZ1x6NAh/Pzzz5gwYQJ69OghHpEQHByMGTNm4MqVK1i8eDGsrKx0xuE2zZqqsLCwWeLwNZqZioe5MsYYY4wxxhgzGfdMMsYYY4wxxhgzGSeTjDHGGGOMMcZMxskkY4wxxhhjjDGTcTLJGGOMMcYYY8xknEwyxhhjjDHGGDMZJ5OMMcYYY4wxxkzGySRjjDHGGGOMMZNxMskYY4wxxhhjzGScTDLGGGOMMcYYMxknk4wxxhhjjDHGTMbJJGOMMcYYY4wxk3EyyRhjjLFWM336dFhYWBj9srS0RLt27RASEoJp06Zh3759UCqVrX0Y7DGQm5sr2pmfn19rV6dFzZ8/Xxzr/PnzzY6TnJws+/eZm5trcoz4+HhZjKZoHMvCwgKrV682O96aNWs04sXHxzepjo8bTiYZY4wx9sggIpSWliI9PR2bNm3CmDFj0L9/f1y/fr21q8YYewglJiaave3333/fjDV5PFm3dgUYY4wxxgDA3t4eXl5eOtcTEYqLi1FRUSH7/MKFCxg2bBjOnDkDX1/flq4mY+wRcuzYMRQUFKBTp04mbVdcXIyjR4+2UK0eH9wzyRhjjLGHwoABA5CVlaXzlZ2djbKyMty9exeJiYno2rWr2LawsBDvvfde61WeMfZQIiLs2LHD5O127doFlUrVAjV6vHAyyRhjjLFHhoWFBdzd3REdHY1Lly6hS5cuYt2uXbtw+/btVqwdY+xh4erqKpbNGeoqHeIqjcXkOJlkjDHG2CPJ0dERCxculH3Gw9IYYwDQo0cP+Pv7A2i4LhQUFBi97f3793HkyBEAgL+/P3r06NEidXwccDLJGGOMsUdW3759Ze+5Z5IxBjSMYoiOjgZg+lDX3bt3Q6FQAACio6ObPMvs44wn4GGMMcbYI6vxhD1EZNR2paWlSE5ORn5+PqqqquDn54eAgAD07t0blpamfddORLh27RrOnz+PO3fuwM3NDUFBQQgODoaHh4dJsbKysnD69GkUFBSAiODh4YHw8HD06NGjxW9oa2trsX//fty4cQOdO3fGq6++qrNsVVUVjh49itzcXJSVlcHHxwf+/v4IDw+HjY2NSfvNy8tDZmYmsrKyUFZWhi5duiAgIAAhISGws7MzKdatW7eQkpKCO3fuoLa2Fh07dkRoaCjCw8NN/rv+mpRKJc6cOYP09HQUFRXBw8MDAQEBCAsLQ9u2bU2KpW6P586dw507d+Dq6oqAgAAMHz4ctra2LXMAD6mYmBgsXrwYQMNQ1xkzZhi13fbt28VydHQ0Tpw4YdJ+7969i/T0dOTn5yMvL09MLubp6Yk+ffqY1K6VSiUyMzORnZ2NzMxMWFlZwd/fHwEBAQgKCjL6utBccTQQY4wxxlgrmTZtGgEgADR06FCTt8/IyBDbA6Bt27bpLX/z5k166aWXyNraWrad+tWtWzf66quvqK6uzqj97927l0JCQrTGAkCjR4+m69ev642hUqlo79691KtXL51xunTpQhs3biSlUmn0udElKSlJxI2LiyMiouPHj5OPj4/4/De/+Y3WbYuKiujtt98mBwcHrfX08vKiRYsWUXl5ucF6nDt3jkaPHq3zmH18fCg+Pp4UCoXBWCdOnKDBgwfrjNWxY0davnw51dbW6oxx8+ZNUd7X11d8Xl1dTW3atBHrVq9ebbA+RESffPKJ2CYwMJBUKpVGmdraWlq6dCl5eHhorbejoyPNnDmTbt68adQ+Dxw4QKGhoVpjubm50dKlS0mpVFJcXJxGGzCHtC0BMLqeUhs2bJDFaApprEGDBpFKpSI/Pz8CQJaWllRQUGAwRllZGdna2oo2qFKpaNCgQSLuhg0bdG577do1Gjt2LFlZWelsix4eHjR37ly6e/eu3noolUpKTEzUe32JiIigo0eP/ipxdOFkkjHGGGOtpqnJ5LZt28T2lpaWem9mf/zxR51JUONXZGQklZaW6oylUqno/fffNyqWo6MjJScna42jVCrpvffeMyoOAIqOjqaamhqTz5NU42TyyJEjZG9vL9uPtmTyl19+ofbt2xtVz7CwMMrPz9dZhy+++MLoY544caLeJHrZsmVGxxoyZAiVlJRojaMrmSQimj59ulg3fPhwg+dYpVKRv7+/2OZvf/ubRpni4mLq16+fUfV2c3OjY8eO6d3fZ599ZlSsmJgYmjt37hORTBIRffjhh+KzNWvWGIyxZcsWUf79998nIjIqmTx+/Dg5OTkZ3Ra7du1K9+7d0xqrtraWxo0bZ3SslStXtmgcfXiYK2OMMcYeSVVVVfjkk0/E+/Hjx8PPz09r2ZMnT2LcuHGor68H0PBMy/HjxyM0NBTt2rXDlStXcPjwYWRlZQEADh06hMjISJw6dQrW1pq3S59//jmWLVsm3vv4+CA2NhYBAQEoKirC6dOnsW/fPlHPqKgoZGRkoEOHDrI4CxcuxIoVK8R7FxcXxMTEoHfv3rC2tkZaWhoSEhJQVFQEoGGGSWdnZ2zYsMH0E6bFrVu3MGnSJNTU1MDd3R2DBw9GYGAg+vXrJyuXnZ2NESNGoLy8HABgaWmJsWPHolevXujcuTPS09Nx9OhRpKamAgAuXbqEiIgIpKamasyEmZycjD//+c/ivZOTEyZPnoyQkBA4ODggJycHW7ZsEb9/3b59O7Zs2YJXXnlFo/6bN2/G+++/L97b2dkhKioKAwcOhIODA7KyspCYmIjc3FwAQEpKCl588UUcOnTIpGGvU6ZMQXx8PICGyVzUQ1F1OXv2LHJycsS5ajxkuLa2Fs899xwuXrwoPouIiMDTTz+NwMBA/Pe//8W5c+dw6NAhAA0TwkRGRuLYsWMYMGCAxv7Wr1+PefPmifdWVlYYN24chgwZAkdHR6Snp+O7775DUVEREhMTTR5+/SiLiYnBkiVLAAAJCQl455139JaXzuKq/s2lIbW1tXjllVdQWVkpPhs6dCiGDx+Ozp07o6qqCjk5OUhISEBhYSEAIDMzE4sWLRJ1k1q0aBF2794t3nt7eyM2NhZdunRBfX090tLS8O2336K6uhoAMGfOHLzwwgsICAhokTh6mZx+MsYYY4w1E3N6JsvKymjHjh2yYVvdunWjoqIireWrqqooICBAlB05cqTWHpTa2lr629/+JhuitmzZMo1yly9flg2TnTZtGlVVVWmUO3ToENnZ2Ylyf/zjH2Xrr1y5IosTERFBt27d0ohTWlpKL774oqwH4aeffjLqXGnTuDcJAL399ttUUVGhtXzjYX59+/al1NRUjXJKpZLWrl0r652ZPXu2RrkXXnhBrO/evbvWv1t1dTUNHDhQlIuKitIoU1hYSK6urqJMUFAQZWRkaJSrqamhmTNnyo537dq1GuX09UzW19fLhqJq217qD3/4gyg7atQojfV/+ctfxHoPDw/atWuX1mGwycnJsrbbu3dvqq+vl5W5ffs2ubi4iDJeXl504cIFjVglJSWyc69+Pe49kyqVinx9fQkwPNS1oqJCjF7w8vISPeKGeib37t0r1ltYWFBCQoLW+LW1tbK/Qf/+/bWWadeunSgzefJkrcPuc3JyZOUa9yo2VxxDOJlkjDHGWKuRJpP29vYUEBCg8+Xv709t27bVuBkePXo05eXl6dzHN998I8qGhoZSZWWl3jp9/vnnoryLi4vG7+ymTp0qu7nX95u+FStWiLKdO3eWDdd88803xTp3d3e9w2rr6upkyfPIkSP1HoM+jROA559/Xmsio3bkyBHZMRj63dmmTZtEeUtLS43hrm5ubmL9zp07dcbZt2+fKBcQEKCxfsGCBWK9jY0N5eTk6IylUqnoueeekyWejY9ZXzJJRDRr1iyx/tlnn9W5L4VCQZ07dxZlExMTZevLysrI2dlZnJ+kpCSdsYiI0tPTydHRUcRr/Lvg+fPnyxKZixcv6oxVXV1NXbt2bbFksjleTaEtmSQimjNnjvhc31DXhIQErV+EGEom582bJ9ZHR0frreO1a9dEWVtbW431qampsr+nrqGwRPIhvG+88UaLxDGEk0nGGGOMtRppMmnOq3///lRWVqZ3HxEREaL8zz//bLBOCoVC9GQAoJMnT4p15eXlYnIOALR161a9sUpLS2U9nf/5z3+IqKGnS9qD9/nnnxus18aNG2XHXlhYaHAbbRonACkpKXrLT5kyRZT9+uuvjdqHdDKcxudIetynTp3SGaO0tJQ2b95Mmzdvpm+//VYj+QsKCjLpBvjo0aOy4z537pxsvaFk8uTJk2K9lZWVzglUpMm3u7u7xm9c161bJ9a//PLLButNRPTpp5+Kbd566y3ZusDAQLEuJibGYCzp/p+UZPL06dPic32/eZ00aZIoJ/2NqqFkMiEhgWbOnEkzZ86kw4cP662jSqXSe7znzp0T6xwdHfV+WZWRkSH+jTS+tjVXHEM4mWSMMcZYq2lqMgmAOnXqpDMpqaysFENJHRwcjJ68RppALV68WHz+888/i8/bt29v1KyvmzZtouXLl9Py5cvFMNYLFy7Ieg3u379vME5dXR25u7uL7fbs2WPUsTQmTQCsrKz03mSqVCry9PQU5fX1AEtJZzKdMWOGbF3v3r3FuqioKKNnzpW6e/eurA1cvnzZ4DYqlUo2Y+6qVatk6w0lk9KZQQHQv//9b637+d3vfifKaBvmK21bmzdvNup4Dx48KLYJCQkRnxcWFsrOw+nTpw3Gqq6ulg1rbM5k0sfHR+/oAm2vDh06tHgyqVKpxGzFuoa6VlVViS86OnXqJPt3YexsrsaQtjNtx1taWipbv3TpUr0jB3RprjiG8AQ8jDHGGHsoDB06FMnJyXrL1NTUIDMzEz/99BPi4uJQVVWFgoICTJw4EZcvX0b79u1l5VNTU8XDxxUKBXr06GFUXe7duyeW79y5I5Z/+eUXsRwUFGTUMxW1TRyjnqgGaHhWZrt27QzGsbGxQbdu3XDq1CkAwOXLlzFmzBiD2+nTqVMnWFlZ6VxfWFgoJsIBgGHDhhkVt6ysTCxLzx8ATJw4UUw8s3PnToSEhOCdd97B6NGjjX7e3dWrV8WyhYUFgoODDW5jYWGBHj16iHN/+fJlo45Fuv3kyZOxaNEiAA0Ttbz++uuyMnV1dbIJXF577TWNOOfPnxfLf/7znzF//nyD+66rqxPL0vOZlpYmK9erVy+Dsezt7RESEmLysxONcfToUZ2TYOkSHx+v9Tw1JwsLC0RHR2PZsmVQqVTYsWOHxkQ8Bw8eFBPovPjii3r/XZjj7t27OHnyJP7617/qLefq6orIyEgx+dKcOXOwd+9eTJ8+Hc8//zw6duxo1P6aK44hnEwyxhhj7JFhb2+Pnj17omfPnnjmmWfEzJa3b9/Gzp078bvf/U5Wvri4WCzX19cjOzvb5H1WVFRojffUU0+ZHEutpKRELJty8+3r6yuSyfv375u9f7XOnTvrXS89XgBNPn8A8NFHHyEpKQmHDx8GAGRlZeGDDz7ABx98gI4dO2LIkCEYOnQoxo8fr/McS8+fl5cXbG1tjaqLr6+vWDbn/EmTyUOHDqGkpET2RcDBgwdF3fr06YOwsDCNGNJzeuvWLZPrUFFRASKChYWF7Bg8PT3h4OBgVAw/P78WSSYfZjExMWIG5sTERI1k0pxZXLV58OABkpKSkJqaiszMTPFq/G9Jn2+++QYRERHIz88H0DADsvqLtqCgIAwZMgQjRozACy+8gDZt2rR4HH2MnxOZMcYYY+wh0r9/f0RFRYn36m/gpaQ9ZOZSPw6jcTxPT0+zYz548EAsm9JDIN1ncxybk5OT3vXNff4AwNraGgcPHsTXX3+tcQ4LCwvx/fffY9asWfDx8cGAAQPEI1akWuv89ezZE6GhoQAavpyQPnYBALZt2yaWdfW2NfWcKhQK1NTUAIB4pANg+IsBKS8vrybV4VHUv39/8eWE+vEuarW1tdizZw8AoEOHDhgyZIjJ8fPz8zFt2jS4u7tj3Lhx+PTTT7Fx40acPHkSxcXFsLS0REhICD766CODsZ566imkp6djzpw5Gv9GMzIysH79ekyZMgUdOnTA+PHjkZ6e3qJx9OFkkjHGGGOPrEGDBollbb08jo6OYrl79+6ghvkiTHr93//9n4gh7fkpLS01u97Ozs5iWf3cOWNIezcMJYLNQXr+HBwcoFKpTD5/Z86c0YhraWmJN998E3l5eTh16hQ++ugjhIWFaQxxPXv2LMaMGYPf//73ICLxeWuevylTpohlaW9WVVUVfvjhBwCAra2trJyU9JyeOXPGrDapbofS3qTGw4n1kSZSTwpLS0vR46ge6qp2+PBhkeRHRUVpfbasPlevXsVvfvMbbNq0CXV1dbC3t8fYsWMxf/587Ny5E2lpaaiqqkJaWhq++OILo2I6OztjyZIluHv3Lvbs2YM33nhDYxRDXV0ddu/ejbCwMGzcuLFF4+jCySRjjDHGHlnSYYuNe8AAwM3NTSzn5ORApVI1aX/SeP/5z3/MjiMdGmlKnJycHK11aSnSfVRXV5uUsBjD0tISAwcOxBdffIGLFy+ipKQE+/btw7vvviv7/evatWuRkJAg3kvP3+3bt2W/KdSnOc5fbGysWD548KBIQvbu3St6TKOionTGl36elZVlVh3U3N3dxfLt27dlPZX63Lx5s0n7fVTFxMSIZWl72r59u1g2dYirSqVCTEyMGHI8ffp05OfnY/fu3YiLi8OECRMQEhICOzs7s+psb2+PMWPGYP369bh58yby8vLw7bffIjY2Vvxmu66uDjNmzJC175aK0xgnk4wxxhh7ZLVt21YsN/5tHgAxJBFoGMqWl5dnVFylUgmFQgGFQiFLQKUT+Ny4cUPWW6bLt99+i/feew/vvfcejh8/DqBhuKTarVu3jBr6qFAocOPGDfFeemwt5amnnpL1fmVmZhq1na7zZ4irqytGjx6NVatWITs7WzbcUNpDLD12lUolOy/6SIfxmXv+unTpgqeffhpAw8333r17AQDfffedKKNvQhnp397Y86lSqcT5VCqVsljS3twrV64YjKVQKHD9+nWj9vu4GTBggBjiqx7qWl9fj127dgFoSPSNnWRK7ciRI+J8BgQEYP369bIkv7GmfoHg7e2Nl19+Gd999x3S0tLEly5VVVWiLf6acTiZZIwxxthjQf07Mqn27dsjKChIvN+0aZPBOJWVlejYsSNsbGxgY2MjJq8AgIiICLGcl5eHH3/8UW8sIsLcuXOxcuVKrFy5UswQ2bNnTzHMUqVSYfXq1QbrtW3bNtkwTXVC05KsrKxk+zHm/KlUKvTq1Uucv5MnT4p1e/bsQWBgIAIDAzFq1Ci9cdq0aYN3331XvM/IyBDL7u7usr/rl19+abBex48fx4ULF8R76d/SVJMnTxbL33//PUpLS7F//34ADTfpkZGROreVDs3eunUr6uvrDe5v5syZ4nyqJwACGs6RNClesmSJwViJiYkmDQ1+nGgb6nr06FHRqzhhwgSjZmiWunbtmlgOCQkxOAts49/ZNvbpp5+KfyOGZvrt2rWrrLdV+m+kueIYwskkY4wxxh5Z0hs3bckkALz66qti+e9//7vsURfarFq1SjwaZPjw4fDx8RHrvL29MXz4cPF+wYIFenveDh8+jNzcXAANv5Xr27cvgIbHfEyaNEmUW758udZhump1dXVYuHCheD9ixIgmTQBkCun527BhAy5duqS3fEJCgrjB7tKliyx5srOzQ3Z2NrKzs3HgwAGDs5lKE3np7yQB4OWXXxbL8fHxeocLE5HshjowMFDMBGyOl156CZaWDbfRBw4cwObNm8VQ2+nTp+tNKKZMmSK2vXHjBv75z3/q3Vdubi42bNgg3k+dOlW2Xvr++++/F49d0aa+vl6WjD6JpElTYmJik2dxVf8tgYaeYfWjiLQ5dOgQPvnkE9lnjb9MUKlU4t/I1q1bDY5+0PVvpLniGNTsT65kjDHGGDPStGnTxEO1hw4davL2Fy9elD2Yu7y8XKNMcXExtW3bVpQJDg6mX375RaOcSqWi+Ph4srS0FGU3bdqkUW7//v2yfb711ltUXV2tUe7GjRvUuXNnUS4mJka2/vLly2RlZSXWP/PMM1RYWKgRp7S0lCZMmCDb548//mjKaZKRPmjemHNeW1tL/v7+YhtPT086ePCg1rIHDhwgBwcHUfazzz6TrS8pKZGd32effZZqa2u1xkpNTaWOHTuKsnPmzJGtv3PnDrm4uIj1ISEhlJ2drRGnurqa3nnnHdn5+9e//qVRTvoweV9fX4Pn5dlnnxXlpfXIysoyuO0rr7wiytvZ2dHy5ctJqVRqlMvJyaGAgABRdsSIERplioqKZO3b09NTa/uuqKigSZMmyc4DAIqLizNYX12kbQkA3bx50+QYGzZskMVoCmmsQYMGaS2jVCrJ09OTAJClpSW5ubkRAHJ1ddXZFgcNGiTibtiwQbYuJSVFVv9JkybJ2mFNTQ2dO3eOpk2bRtbW1hrn/+uvv5b97Xfv3i1bP3/+fJ3Hu3XrVtk1ZO/evc0exxBOJhljjDHWapqaTObl5clumA4cOKC13LZt22TlrK2tafz48TRv3jxau3YtzZs3j/r06SMrExkZqfUGn4ho+vTpsrLe3t40depUWrFiBS1dupReffVV2Y2jk5MTZWZmasSJi4uTxWnTpg1NmDCBFi5cSEuWLKGYmBhq3769rMzrr79u8nmSMjWZJCI6ceKE7GYTAI0cOZI+/vhjWrduHX322Wc0bNgw2foePXpQVVWVRqzY2FiNczdnzhxatWoVrV+/nhYsWEBjxoyRJZ3Ozs6Um5urEatxImJvb0+jRo2iuLg4WrFiBU2dOpW8vb1lZX77299q/buamkw23rcp5/PevXsioVG/evfuTbNmzaI1a9bQ4sWLKTY2VtaGHB0dKT093ai6WFpa0oQJE2jZsmW0bt06+vDDD8nLy0usHzt27BObTBIRzZ49W+Nv9+qrr+osry+ZfPDggexLI/XL1dWVPD09ycLCQvb54MGDKTw8XPaZm5sb7d+/n4gakk8fHx/Z+vDwcJo/fz7961//on/+85/06aefUt++fWVl+vTpQ/X19aJezRXHEE4mGWOMMdZqmppMKpVKateunexGqKSkRGvZ1atXa9zY6XoNHz6cysrKdO63pqaGXnzxRaNiOTk50U8//aSz/rNmzTIqDtDQ61FTU2PyeZIyJ5kkItq5cyfZ2dkZVc9evXpRfn6+1ji3b9+W9XQaejk4OIgbbW0WL15sdKxhw4ZRaWmp1jimJpOlpaUa52Pjxo1GnUsiouvXr2vc7Ot6ubm5UXJyst54CxYsMCrWxIkT6dKlS090Mtm4NxEA7d69W2d5fckkEdHhw4eNuraMGDGCysrKaOfOnRrrdu7cKeIlJyeTvb290e3a399fa698c8XRh5NJxhhjjLWapiaTRETjx4+X3RDNnTtXZ9mzZ8/S8OHDdd5MBQYGUmJiIqlUKoP7VSgUtH79eo2eL+lr3LhxdP36db1xVCoV/fDDDxQaGqr3Jm/z5s06e0pNYW4ySdSQAEVFRWn0UqpfnTp1onXr1hns2SguLqY33nhD742ui4sLffjhh3Tr1i2D9Tp27BhFRETojNWpUydauXKlzmGMRKYnk0Qk+0LB2dmZHjx4YNR2avfv36cPPviAnJyctNbbzs6OPvroI51fkDR24MABne2oTZs2tGjRIlIqlXTlypUnOpmUDnVV/+20DVVXM5RMEjWci8Y9juqXt7c3ffXVV7J/v5s3b6auXbuSi4sLPf3003T27FlZvNTUVIqMjNSb/Pn5+dGqVauosrJSZ92bK44uFkRGzGnNGGOMMfYYuXPnDo4dO4bbt29DqVSiW7duCA4Ohr+/v8kPLFepVDh//jwuX76MoqIi2Nvbw9vbG8888ww6depkUqwbN27g9OnTKCoqglKphIeHB/r27YvQ0FDZIyBa2/3795GcnIz8/HxUV1cjMDAQwcHB6Nq1K2xtbY2OU1FRgfT0dOTl5eG///0viAi+vr7w8/NDUFCQaROBoGGG3ZSUFBQWFqKmpgYeHh4IDQ1Fv379ZBOlPGxqa2uRkpKCrKwslJSUwNvbG8HBwQgODoaLi4tJsYgI6enpOHv2LAoKCuDg4AA/Pz88++yzcHR0bKEjYEDDtSA1NRWZmZm4efMm2rRpg+7du2Pw4MEGZ3nVpaCgAJmZmcjLy0NeXh6cnZ3h5+cHX19fBAcHG329aq44jXEyyRhjjDHGGGPMZA/vVzSMMcYYY4wxxh5anEwyxhhjjDHGGDMZJ5OMMcYYY4wxxkzGySRjjDHGGGOMMZNxMskYY4wxxhhjzGScTDLGGGOMMcYYMxknk4wxxhhjjDHGTMbJJGOMMcYYY4wxk3EyyRhjjDHGGGPMZJxMMsYYY4wxxhgzGSeTjDHGGGOMMcZMxskkY4wxxhhjjDGTcTLJGGOMMcYYY8xknEwyxhhjjDHGGDMZJ5OMMcYYY4wxxkz2/xCS3URS+97YAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(resolved_target_mass[rh_mask], bins=np.arange(30, 230, 5), weights=resolved_target_weight[rh_mask], density=True)\n",
+    "plt.xlabel('Reco resolved H Mass')\n",
+    "plt.ylabel('Weight x Density')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "53bc1532",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0.01000079, 0.00999994, 0.01000135, 0.00999906, 0.01000158,\n",
+       "        0.00999568, 0.01001068, 0.00999018, 0.01001107, 0.01000281,\n",
+       "        0.00998306, 0.01002262, 0.01000155, 0.00999508, 0.00999969,\n",
+       "        0.00999342, 0.00999894, 0.00999683, 0.01000268, 0.009993  ]),\n",
+       " array([ 75.,  80.,  85.,  90.,  95., 100., 105., 110., 115., 120., 125.,\n",
+       "        130., 135., 140., 145., 150., 155., 160., 165., 170., 175.]),\n",
+       " <BarContainer object of 20 artists>)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(boosted_target_mass[bh_mask], bins=bins, weights=boosted_target_weight[bh_mask], density=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e16a7f98",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/benchmark/west/trained_on_hh_B+R.ipynb b/notebooks/benchmark/west/trained_on_hh_B+R.ipynb
new file mode 100644
index 0000000..07a7d89
--- /dev/null
+++ b/notebooks/benchmark/west/trained_on_hh_B+R.ipynb
@@ -0,0 +1,228 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "13f819cb",
+   "metadata": {},
+   "source": [
+    "Side note: we are evaluating particle level information\n",
+    "maybe we should also do the event level information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "076e12b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-12-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "date = datetime.today().strftime('%Y-%m-%d')\n",
+    "print(date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7125f82a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "dask-awkward 2024.7.0 requires awkward>=2.5.1, but you have awkward 1.10.5 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -e ../../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b0305cb2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.7.1 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "324af322",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/envs/spanet/lib/python3.11/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from src.analysis.plot import plot_pur_eff_w_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "3f269726",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_path = '/Users/billyli/UCSD/hhh/reports/bv2_2h/hh_testing.h5'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3da82138",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_dict = {}\n",
+    "plot_dict['SPA-Net'] = \"/Users/billyli/UCSD/hhh/reports/bv2_2h/improve_v61_v3_v1.h5\"\n",
+    "plot_dict['Baseline'] = \"//Users/billyli/UCSD/hhh/reports/bv2_2h/mix_baseline_bdt_loose_hh.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "56eec654",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing SPA-Net\n",
+      "Average purity:\n",
+      "merged 0.6514093820799742 boosted 0.8429050279329608 resolved 0.6469421293579058\n",
+      "Average efficiency:\n",
+      "merged 0.6739282021688427 boosted 0.8225032708242477 resolved 0.6776466248616747\n",
+      "Number of correct Higgs canddiate predictions\n",
+      "merged 56642.0 boosted 7544.0 resolved 55113.0\n",
+      "Number of reconstructed Higgs targets\n",
+      "merged 56056.0 boosted 7544.0 resolved 55113.0\n",
+      "Number of Boosted Prediction: 8950\n",
+      "Number of Resolved Prediction before OR: 85190\n",
+      "Number of Resolved Prediction after OR: 78003\n",
+      "Processing Baseline\n",
+      "Average purity:\n",
+      "merged 0.40178290073803796 boosted 0.9255400254129607 resolved 0.38959565339826735\n",
+      "Average efficiency:\n",
+      "merged 0.5467912188319026 boosted 0.39707806367204534 resolved 0.57837206442887\n",
+      "Number of correct Higgs canddiate predictions\n",
+      "merged 48451.0 boosted 3642.0 resolved 47039.0\n",
+      "Number of reconstructed Higgs targets\n",
+      "merged 45481.0 boosted 3642.0 resolved 47039.0\n",
+      "Number of Boosted Prediction: 3935\n",
+      "Number of Resolved Prediction before OR: 120738\n",
+      "Number of Resolved Prediction after OR: 116655\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pur_eff_w_dict(plot_dict, target_path, save_path=\"/Users/billyli/Documents/SPANet/SPANet_results/HH/B+R/\",\n",
+    "                    num_higgs=2,\n",
+    "                    proj_name=date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea758caf",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/benchmark/west/trained_on_hh_resolved.ipynb b/notebooks/benchmark/west/trained_on_hh_resolved.ipynb
new file mode 100644
index 0000000..9fa8ec1
--- /dev/null
+++ b/notebooks/benchmark/west/trained_on_hh_resolved.ipynb
@@ -0,0 +1,354 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "13f819cb",
+   "metadata": {},
+   "source": [
+    "Side note: we are evaluating particle level information\n",
+    "maybe we should also do the event level information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "076e12b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-12-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "date = datetime.today().strftime('%Y-%m-%d')\n",
+    "print(date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b690b241",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "dask-awkward 2024.7.0 requires awkward>=2.5.1, but you have awkward 1.10.5 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -e ../../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "da442184",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.7.1 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b89fc571",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py as h5\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import mplhep as hep\n",
+    "hep.style.use(\"CMS\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4f49aefe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/envs/spanet/lib/python3.11/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from src.analysis.resolved import parse_resolved_w_target\n",
+    "from src.analysis.utils import calc_eff, calc_pur "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7f410c9a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_path = '/Users/billyli/UCSD/hhh/reports/bv2_2h/hh_testing.h5'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "e42662c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "baseline_path = \"//Users/billyli/UCSD/hhh/reports/bv2_2h/mix_baseline_bdt_loose_hh.h5\"\n",
+    "r_path = \"/Users/billyli/UCSD/hhh/reports/benchmark/HH_resolved/1118.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "11586b69",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "baseline_h5 = h5.File(baseline_path, \"a\")\n",
+    "r_h5 = h5.File(r_path, \"a\")\n",
+    "target_h5 = h5.File(target_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f16cddfa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if \"TARGETS\" not in r_h5.keys():\n",
+    "    r_h5[\"INPUTS\"] = r_h5[\"SpecialKey.Inputs\"]\n",
+    "    r_h5[\"TARGETS\"] = r_h5[\"SpecialKey.Targets\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "fb2cbbfd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "LUT_resolved_pred_bl, LUT_resolved_target_bl, _ = parse_resolved_w_target(target_h5, baseline_h5, fjs_reco=None, num_higgs=2) \n",
+    "LUT_resolved_pred_r, LUT_resolved_target_r, _ = parse_resolved_w_target(target_h5, r_h5, fjs_reco=None, num_higgs=2) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "b009a7aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = np.arange(0, 1050, 50)\n",
+    "plot_bins = np.append(bins, 2 * bins[-1] - bins[-2]) \n",
+    "bin_centers = [(plot_bins[i] + plot_bins[i + 1]) / 2 for i in range(plot_bins.size - 1)] \n",
+    "xerr = (plot_bins[1] - plot_bins[0]) / 2 * np.ones(plot_bins.shape[0] - 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "89f9f310",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bl_eff, bl_eff_err, bl_avg_eff, bl_n_reco_target = calc_eff(None, LUT_resolved_target_bl, bins)\n",
+    "bl_pur, bl_pur_err, bl_avg_pur, bl_n_correct_pred = calc_pur(None, LUT_resolved_pred_bl, bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "9b2779ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_eff, r_eff_err, r_avg_eff, r_n_reco_target = calc_eff(None, LUT_resolved_target_r, bins)\n",
+    "r_pur, r_pur_err, r_avg_pur, r_n_correct_pred = calc_pur(None, LUT_resolved_pred_r, bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "11b8c574",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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3VxluvfVWI8l0797dY7qf//zn1rFER0eb4uLiCu/z5MmTZunSpdbrzJkzHtP76x4pLCw0TZo0sfJNnjzZa10vXbpkwsLCrDxvvvmmx/RFRUWmadOmRpJJSUlxmWbXrl2mSZMmJjIy0hw4cMB6/9133zUhISEmOTnZXL582WvdAAAAAFQd1T1mSk1NtdKvXbvWGGNMenq66dGjh8syO3fubFavXl3hY6wI2gP8i/YAzyqjPcAbOq8BAADg0vV2Xi9evNjKHxQUZDIzM92m/fOf/2zq1KnjtoPY8TVu3DiPHVrnz583ffv29ams2NhYc/z4cZfl5OXl+VyOJPPHP/6x3OfoelTVYDUjI8NERkZ6PV8xMTEer4kb6cSJEz4HbnFxcVbaadOm3aAa+vceMcaYiRMnWukjIyO9Bt3Lly93up9PnDjhtc5Dhw41kkxERIQpKioqs33Xrl1m+vTpZa6DxYsXm5dfftlcunTJ6z4AAAAAVC3VPWa6tvN67dq1Th137l4ff/zxDTtW2gP8h/aAwLQHeMNYBgAAAPC7/Px8zZgxw1ofNmyYYmJiXKZdunSpHn74YWu9UaNGSklJUZcuXRQaGqpdu3Zp3bp11pzZCxcu1A8//KDly5eXGRLJbrdrxIgR+uKLL6z3br/9dg0bNkwtWrRQZmamPvnkE/373/+WJB06dEijRo3Sxo0bncqy2+0aOXKkUzlRUVH6r//6L91yyy0qKCjQV199peXLl6uwsFCS9NRTT6lZs2YaP358Bc9a9Xf+/Hndf//9OnnypCTpxz/+sQYPHqxGjRrp0KFDWrJkiTIzMyVJWVlZGjRokHbt2qV69eoFstr6/PPPreWePXu6TXf69Gnt37/fWk9OTq7Maln8eY+UGjNmjObPny/p6tDdmzdvVr9+/dzWwXGIsH79+ikyMtJrvZOSkrRmzRpdvHhRO3fuVFJSktP2rl27qmvXrmXyjRo1ymvZAAAAAKqemhQzSdLRo0c1ffp0FRQUKCYmRnfddZe6d++unJwcrV27Vl9//bWV9uGHH9aAAQPUsGHDyjvQKoz2gMpRU9sDvCp3dzcAAABqhYr88vr8+fNm+fLlJj4+3sobFxdnTp065TL9yZMnTePGja20Y8eOdZn2woULZurUqU5Pky5fvrxMunnz5jmlmTt3bpkhk4qLi82sWbOc0q1cudIpzfz58522T5o0yRQUFJTZ3/79+02nTp2sdA0bNjQ5OTk+navr5Vi/qvKkdenrpptuMitWrCiTrrCw0EybNs0p7YwZMyq8X3959NFHrfrs37/fbbovv/zSqe779u2r9Lr5+x4pVVJSYtq0aeN0jbtTWFhoGjVqZKV9++23far7J598YuX5wx/+4FMeAAAAANVXTYiZHH95XRoH/exnPzP5+flO6UpKSsyzzz7rVN4///nPSjtOR7QH+A/tAVWzPYDOawAAALjk2HkdGhpqYmNj3b7at2/v9GW29HXPPfeY7Oxst/t47rnnrLR33XWX16GKHOcX6tSpk9O24uJiExUVZW2fMmWK23LsdrsZPny4lXbUqFHWtpKSEnPLLbdY2wYNGuRxzqDMzEwTHBxspZ81a5bHY/CXa8/19b78Gay+8847btPa7XYzcuRIp8aAaxsBbrTSz7tx48YeP+t//OMfTsfpbU4qf/DnPXKtp59+2krbokULt0N5rVu3zkpXp04dtw+jXOvs2bNWvsGDB/uUBwAAAED1VRNiJsfOa0lm6NChbuPE4uJip4f3X375Zb8ckze0B/gP7QFVsz0gSAAAAIAXly9f1qFDh9y+Dh8+rLy8PKc8SUlJWrRokdq0aeOyTGOMFixYYK2/9dZbqlOnjsd6zJ49WzfddJMkae/evdawSJK0fv16HT16VJJUp04d/frXv3Zbjs1m0y9+8QtrPT093Wn5wIED1vqzzz7rcRixmJgYjRs3zlpfuHChx2Oo6dq0aeNx6HSbzaa0tDRrPS8vT2vWrJEkpaWlyWazVehVUVeuXLE+7w4dOngs69y5c07rDRo08Fr+woULfT6GCRMmOOX19z1yrdGjR1vLp06d0saNG12mcxwibODAgWrevLnHOpRq0qSJmjZtKkn69ttvfcoDAAAAoPqqaTGTJL344otu48Q6deqod+/e1vqlS5c8llXT0R7grCpf21W9PYDOawAAAFSK9PR0dezYUV9++aXL7QcPHrS+SMfGxqpDhw5ey6xfv74SExOt9S1btljLjvNTp6SkKCoqymNZAwYM0Ouvv67XX39dU6dOlTFGkrRt2zYrTffu3dWnTx+v9Zo8ebK1/N133+n8+fNe8/hT8+bNFRsbW66Xt/NTUb/61a8UEhLiMc2tt96qu+++21p3POc32qlTp6zl0sDKndDQUKf1/Pz8SqlTKX/fI9e67bbb1LFjR2t9yZIlZdLY7XatWLHCWi/vfNSl5/TUqVPWPQYAAACgZqppMVO3bt3UrVs3j+X5Mv9vZaI9oOJoD6i67QF1y5UaAAAAtVK/fv30+eefe0xz+fJlHThwQOvWrVNqaqry8/N18uRJjRw5Urt27VKzZs2c0u/YscNaPn78uE9fxCXp5MmT1vKJEyes5e3bt1vLXbp08VpOWFiYpk6dWub93bt3l6scSercubO1bIxRRkaGkpOTfcrrDy+//HKZp3S9ycrKUrt27fxeF8dAyZPbbrtNn3zyiSRp165dkq4+ae34FHaptLQ0zZw5U9HR0crKyvJXVSVJOTk51nKTJk08pr32Gs7NzVXDhg095gkPD1dsbKzb7RcuXNDp06ddbvP3PXItm82msWPH6rnnnpMkLVu2TG+++aaCg4OtNNu2bbPOUd26dTV8+HCf6lCq9JxeuXJFeXl5aty4cbnyAwAAAKg+alrMdMstt3gt63p++esPtAdUHO0BVbc9gM5rAAAA+EVoaKgSEhKUkJCgvn37qmfPnpKufsn++OOPnYbpluT0Bb2goECHDh0q9z4vXrzosry2bduWu6xSubm51nJMTIxPeUJDQxUZGWkFCdcOJ1Wb+HrOHAPlM2fOVFJtvHMMVr09aX3t8Fj79+/3erzDhw/3GOC9++67euSRR1xu8/c94sro0aOtYPXs2bPasGGDfvKTn1jbHYcIGzRokNdzdC3H9Dk5OXReAwAAADVYTYuZ2rdvX+7yajPaA5xV5WtbqtrtAQwbDgAAAL9LSkrS/fffb61/9tlnZdL4Y2jtCxcuuCyvVatWFS7zhx9+sJZvvvlmn/M57vNGDxtelbRu3dqndI5zoQfyfDk+rBAREeExbVxcnMLDw611fwxvdvbsWbfb/H2PuNKhQwclJSVZ645DhRljnILV8g4RJsnpSfTa/FAHAAAAUBvUtJgpLCzsusuvTWgPKB/aA9yj8xoAAACVwnHY7GPHjpXZXq9ePWt5yJAhMsaU+/XSSy9ZZTgGlXl5eRWut2Mw4vgUrjeOT8XWr1+/wvuv7jwFX44c55ZyvBZuNMcnf709lVy3bl317t3bWl+9evV17//gwYNut/n7HnFn9OjR1vLy5ct15coVSVeHbysdli04OFjDhg0r9/E5Bsv86hoAAACo2WpqzATf0B5QPlXh2q6q7QF0XgMAAKBSREdHW8uunvZ0nE/I0xd2XzmWd+TIkQqX4/iF2tdyCgsL9f3337usS23j6xxUjkNeBfJ8Of663pdAe8iQIdby9u3bneZaLy9jjDXPlyv+vkfcGTVqlDVPW25urtavXy/JeYiwu+++W40aNSp32Y7ntDwjGQAAAAConmpizATf0B7gu6pybVfV9gA6rwEAAFApHL/YunqCNSEhwVrOzMxUcXGxT+UWFxdbL2OM9X6XLl2s5f379/tUVlpamqZOnaqpU6da81U71uu7777zqZz9+/e7rUtts3fvXp/S7d6921q+9dZbK6s6XjkGUL4MYzVhwgQ1aNDAWp8+fbrsdnuF9r1s2TJlZ2e73e7ve8Sdli1bauDAgdb63//+d0m67iHCpP8Eq8HBwfzyGgAAAKgFamLMBN/QHuC7qnJtV9X2ADqvAQAAUOkuX75c5r2uXbtaw2sXFxdr0aJFXsvJzs5WvXr1rC++BQUF1jbHYcqXLVvmNIy3K1lZWZo5c6Zmz56tBQsWqGnTppKkO++800qzY8cObd261Wu9Zs+ebS3HxcWpWbNmXvPUVHPnzvUaIO3Zs0erVq2y1h3P+Y3WokULa9mXJ60bNGigiRMnWuv/+te/nD5/X505c0ZPP/20xzT+vkc8GTNmjLW8YsUKZWRk6Ntvv5Uk3XTTTUpJSfGpnGuVNgDcfPPN1tPcAAAAAGqumhozwTvaA3xT1a7tqtgeQOc1AAAAKkWdOnWsZVed18HBwU5fkP/nf/5Hly5d8ljmiy++qKKiIknSgw8+6DQH0H333aeIiAhJUn5+vl577TWPZS1YsMBaTk5OVnBwsCQpKSlJsbGx1rbnn3/eY/B1+PBhvf/++9b6uHHjPO63pvvmm2+cAtFrGWP03HPPWec0PDy8QnMn+UtISIhuueUWSVeH4vLlyeTnnnvOyiNJv/71rzV37lyf93n69Gndd999XodU8/c94smIESMUEhIiSTp//rwef/xxa9s999zj9HS5r3Jzc3XmzBlJUnx8fLnzAwAAAKieamLMBO9oD/CuKl7bVbE9gM5rAAAAVArHIYHy8vJcDh0+bdo0q9P42LFjGjRokNPcR6VKSkr0+9//XvPnz7fee+ihh5zSREREaNKkSdb6yy+/rAULFrgMPv73f/9Xs2bNstYdg6WgoCA9+eST1vq6des0depUFRYWliln//79GjJkiDV8U4MGDfToo4+WSSdJMTExstlsstlsiomJcZmmppgwYYK2bNlS5v0rV67oqaee0kcffWS99+ijj1YoEPKnAQMGSLoaXPkyl1R4eLgWLVqksLAw671f/epXuu+++zwOk1ZSUqLFixcrMTFR27ZtkyR169bN4778eY940qhRI91zzz3W+qZNm6zlig4R9vXXX1vLpecYAAAAQM1XE2Om60F7AO0BVfnarortAXUrtFcAAADAi2uHzt66dasGDx7s9F7nzp31wgsvaPr06ZKkbdu2qVu3bho6dKi6du2qZs2a6ciRI/roo4904MABK9/DDz+sPn36lNlnWlqaVq1apT179shut+sXv/iF5syZo969eyshIUFnzpzRpk2b9Omnn1p5EhIS9MgjjziVM3HiRC1dulQbNmyQJP3pT3/SihUr1K9fPyUmJurcuXNKT0/Xhg0bnDq133zzTac5k2qjBg0aKDc3V3369FG/fv3Uq1cvxcTE6PDhw1qyZIkyMzOttO3bt9fMmTMDWNurBgwYoHfeeUeS9NVXXzk9Re1OYmKiPv30U9177706f/68JGnVqlVatWqVunfvroEDB6p169Zq2LChzp07p++++06ffvqpjh07ZpWRmpqqn/3sZ06/9L+Wv+8RT8aMGaMVK1Y4vRcWFqahQ4eWq5xS6enp1jKd1wAAAEDtUhNjJnhGe0D1vbarXHuAAQAAAFwYP368kWQkmX79+pU7f0lJiWncuLFVRo8ePUxubm6ZdHa73TzzzDNWOm+v0aNHm8LCQrf7zc7ONh07dvSprNjYWHPkyBGX5eTm5prk5GSf6/XGG294PB/R0dFW2ujo6PKcSpcc9/2Xv/yl3PkzMzOdytiwYYNf6rJ582ZTv359r+crKirKHDx40KfyU1NT/XbeXDlx4oRVr8mTJ5crb0ZGhrnzzjt9vk4kmcjISPPhhx8aY65e/61atTKSzPjx413uw9/3iDv5+fkmPDzcqawHH3yw3OWUSklJMZJMRESEKSoqqnA5AAAAAKqv6hYzlcafkkxqaqrX4/MlPe0BtAdUhWvbk6rWHsCw4QAAAKgUQUFB6tu3r7W+c+dOl/NQ22w2zZo1S+vWrVNiYqLb8nr06KH169frww8/tObicaVNmzZKT0/XM888o/DwcJdpwsLCNHnyZO3YsUNRUVEu0zRq1Ejr16/Xq6++qhYtWrjdX58+fbRlyxZNmTLFbZraJDk5WTt37tTAgQNdbg8JCdHEiRO1c+dOj08Y30iRkZFKSEiQJG3evLlcebt06aLNmzfrww8/1IABAxQU5D7Eio2N1e9+9zvt27dPo0ePlnT1+ne8T1zx9z3iTlhYmEaMGOH0XkWHCCspKbGGQuvfv7/q1mXQLwAAAKA2qkkxEzyjPaD6XttVrT3AZowPM5ADAAAAN0hmZqa2bNminJwcBQUFqVOnTurUqZOio6M9BgKuFBYWauPGjTp06JDOnTuniIgIxcXFKTk5WRERET6XU1JSovT0dH377bc6ffq0QkNDFRkZqb59+6p169blPcQax2azWcuO4cXBgwe1adMm5eTkKDQ0VDExMRo4cGC557RKS0vTzJkzFR0draysLH9V28kbb7yhadOmSZIOHDigDh06VKicM2fO6KuvvtKJEyd06tQpRUREKDIyUvHx8YqPj3c6VxXlz3uksnz22WcaNGiQJGnFihVO88oDAAAAqL2ImWoW2gP+g2v7Kn+0B9B5DQAAAOC6uAtW/eVGBKt5eXlq1aqVCgoKlJaWptTU1ErZT23x0EMP6b333lNUVJQOHz6sOnXqBLpKAAAAAAA/oz0A1/JHe0DV6IYHAAAAgABq1KiRxo4dK0n64IMPKiXori0KCgq0bNkySdJjjz1GxzUAAAAAoMqiPcB//NUeQOc1AAAAAEh6/PHHJV0dJmz79u0Brk31tXr1al28eFEhISH6+c9/HujqAAAAAADgEe0B/uGv9gA6rwEAAABAUvfu3TV8+HBJ0h//+MfAVqaaMsbo1VdflSRNnjxZLVq0CHCNAAAAAADwjPaA6+fP9gDmvAYAAABwXSp7jqsb6ejRo+rcubPy8/O1a9cude3aNdBVqlZWr16tlJQUtW7dWnv27FFERESgqwQAAAAAqCS0B6CUP9sD+OU1AAAAAPx/UVFRSktLkySlpqYGtjLVjN1u17PPPitJmj17Nh3XAAAAAIBqg/aAivN3ewC/vAYAAABwXWrSk9aSVFRUpB49eigjI0Pbt29XYmJioKtULSxbtkwPPPCA7r77bv3jH/9wui4AAAAAADUP7QGQ/N8eQOc1AAAAAAAAAAAAACDgGDYcAAAAAAAAAAAAABBwdF4DAAAAAAAAAAAAAAKOzmsAAAAAAAAAAAAAQMDReQ0AAAAAAAAAAAAACDg6rwEAAAAAAAAAAAAAAUfnNQAAAAAAAAAAAAAg4Oi8BgAAAAAAAAAAAAAEHJ3XAAAAAAAAAAAAAICAo/MaAAAAAAAAAAAAABBwdF4DAAAAAAAAAAAAAALu/wFeyoCl3gB58gAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig_r, ax_r = plt.subplots(1, 2, figsize=(24, 10))\n",
+    "ax_r[0].set(\n",
+    "          xlabel=r\"Reco. H $p_\\mathrm{T}$ (GeV)”\",\n",
+    "          ylabel=r\"Reconstruction Purity\",\n",
+    "#           title=f\"Reconstruction Purity vs. Reco Resolved H pT\",\n",
+    ")   \n",
+    "ax_r[1].set(\n",
+    "          xlabel=r\"Gen. H $p_\\mathrm{T}$ (GeV)\",\n",
+    "          ylabel=r\"Reconstruction Efficiency\",\n",
+    "#           title=f\"Reconstruction Efficiency vs. Gen Resolved H pT\",\n",
+    ")   \n",
+    "\n",
+    "ax_r[0].errorbar(\n",
+    "           x=bin_centers, y=r_pur, xerr=xerr, yerr=r_pur_err, fmt=\"o\", capsize=5, label='SPA-Net'\n",
+    ")\n",
+    "ax_r[1].errorbar(\n",
+    "            x=bin_centers, y=r_eff, xerr=xerr, yerr=r_eff_err, fmt=\"o\", capsize=5, label='SPA-Net'\n",
+    ")\n",
+    "\n",
+    "ax_r[0].errorbar(\n",
+    "           x=bin_centers, y=bl_pur, xerr=xerr, yerr=bl_pur_err, fmt=\"o\", capsize=5, label='Baseline'\n",
+    ")\n",
+    "ax_r[1].errorbar(\n",
+    "            x=bin_centers, y=bl_eff, xerr=xerr, yerr=bl_eff_err, fmt=\"o\", capsize=5, label='Baseline'\n",
+    ")\n",
+    "\n",
+    "\n",
+    "\n",
+    "ax_r[0].legend(title='HH Resolved')\n",
+    "ax_r[1].legend(title='HH Resolved')\n",
+    "ax_r[0].set(ylim=[-0.1, 1.1])\n",
+    "ax_r[1].set(ylim=[-0.1, 1.1])\n",
+    "fig_r.savefig(f\"/Users/billyli/Documents/SPANet/SPANet_results/HH/R/{date}_west.pdf\", format='pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "23b7d389",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Average purity: 0.7021785245294454\n",
+      "Baseline Average purity: 0.38959565339826735\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Average purity:\", r_avg_pur)\n",
+    "print(\"Baseline Average purity:\", bl_avg_pur)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "293aaa47",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Average efficiency: 0.7692364441165621\n",
+      "Baseline Average efficiency: 0.57837206442887\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Average efficiency:\", r_avg_eff)\n",
+    "print(\"Baseline Average efficiency:\", bl_avg_eff)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "1fd2be74",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Number of correct Higgs candidate predictions: 62562.0\n",
+      "Baseline Number of correct Higgs candidate predictions: 47039.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Number of correct Higgs candidate predictions:\", r_n_correct_pred)\n",
+    "print(\"Baseline Number of correct Higgs candidate predictions:\", bl_n_correct_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "89ef438a-2cc2-4d55-963a-b303beb84f88",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Number of reconstructed Higgs targets: 62562.0\n",
+      "Baseline Number of reconstructed Higgs targets: 47039.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Number of reconstructed Higgs targets:\", r_n_reco_target)\n",
+    "print(\"Baseline Number of reconstructed Higgs targets:\", bl_n_reco_target)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/benchmark/west/trained_on_hhh_B+R.ipynb b/notebooks/benchmark/west/trained_on_hhh_B+R.ipynb
new file mode 100644
index 0000000..5797522
--- /dev/null
+++ b/notebooks/benchmark/west/trained_on_hhh_B+R.ipynb
@@ -0,0 +1,219 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0511a90a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-12-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "date = datetime.today().strftime('%Y-%m-%d')\n",
+    "print(date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8cab1016",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "dask-awkward 2024.7.0 requires awkward>=2.5.1, but you have awkward 1.10.5 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -e ../../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "55c3de67",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.7.1 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2a4ffe9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/envs/spanet/lib/python3.11/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from src.analysis.plot import plot_pur_eff_w_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "3d305b85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_path = '/Users/billyli/UCSD/hhh/reports/bv2/data/hhh_test.h5'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0e916bd5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_dict = {}\n",
+    "plot_dict['SPA-Net'] = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/072324/072324_v10.h5\"\n",
+    "plot_dict['Baseline'] = \"/Users/billyli/UCSD/hhh/reports/bv2/pred_baseline_bdt_loose_west.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "4be0a2b4",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing SPA-Net\n",
+      "Average purity:\n",
+      "merged 0.4079620482222331 boosted 0.5942420868458724 resolved 0.40202564893394754\n",
+      "Average efficiency:\n",
+      "merged 0.5062963581292185 boosted 0.8696461824953445 resolved 0.4939249480503606\n",
+      "Number of correct Higgs canddiate predictions\n",
+      "merged 41708.0 boosted 7472.0 resolved 40408.0\n",
+      "Number of reconstructed Higgs targets\n",
+      "merged 42457.0 boosted 7472.0 resolved 40408.0\n",
+      "Number of Boosted Prediction: 12574\n",
+      "Number of Resolved Prediction before OR: 100511\n",
+      "Number of Resolved Prediction after OR: 89661\n",
+      "Processing Baseline\n",
+      "Average purity:\n",
+      "merged 0.2603789454010233 boosted 0.8507501974203738 resolved 0.2507880174648019\n",
+      "Average efficiency:\n",
+      "merged 0.3671325335686518 boosted 0.3761638733705773 resolved 0.3938760542720939\n",
+      "Number of correct Higgs canddiate predictions\n",
+      "merged 33435.0 boosted 3232.0 resolved 32223.0\n",
+      "Number of reconstructed Higgs targets\n",
+      "merged 30787.0 boosted 3232.0 resolved 32223.0\n",
+      "Number of Boosted Prediction: 3799\n",
+      "Number of Resolved Prediction before OR: 128487\n",
+      "Number of Resolved Prediction after OR: 124610\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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DDzygc889V9u2bZPk6/d36dJFw4YN04QJE/yJa8uylJycrDfeeKPWmtLRQr8eAAAAAJyp0TOv77jjDi1atEiSrwxYVeL6+AR21b7XXntNHTt21Jw5c2wMNzYYY/T888/rwIEDWr58ub744gt/ibSa7rrrLt18881RiBAAAAAAgOCdfPLJ+uKLLzRp0iQtWLDA3+evSgRLde8DSNK5556r5557Tr17945ovKGiXw8AAAAAsalRM6//+9//6i9/+Yu/s2qM0aRJk7Rq1SoVFRWpqKhIq1at0m9/+1v/fsuy9PTTTys/P7+pf4aoSE5O1rJly/T888/rwgsvVOfOndWiRQv16NFD1113nd5//3098MAD/s49AAAAAABO0LFjR7300kvauHGj7rzzTp1zzjlq2bJlrQpsxhgNGDBAv/rVr/Thhx/q3XffdUziugr9egAAAACIPcYKNGT6OFOnTtX//d//SZJatmzpL6kVyEcffaTzzz/fXzJ84sSJevrpp20MuXnp0aOHCgoKlJaWpu3bt0c7nCZnVZTp6Av9JUktf/mNTIs2UY4IAAAgtvB5Cagr3vpNserQoUPav3+/2rRpo/bt28vlavRKZM0er1EAAAAAqF8wfaZG9TTfffddSb6R1X/4wx/qTVxL0tlnn60//OEP/tHYK1eubGzcAAAAAAAgRiUnJystLU0dO3YkcQ0AAAAAaBKN6m1u2bLFv33DDTc0ePyNN94oybcO1o4dO0IMDQAAAAAAAAAAAAAQL9yNOaikpESS1KZNG/Xq1avB43v27Kk2bdqorKxM5eXl4UUIAAAAAABs8d5779X6/rzzzotSJAAAAAAA1NWo5HVlZaWMMUpNTW1Uo1XHfvfdd2EFBwAAAAAA7HP++efLGCPJ13f3eDz+fZmZmbZcwxijzZs329IWAAAAACC+NCp5XaWqg2v3sQAAAAAAIHIsy6rz2NatW8Puy1uWxf0AAAAAAEDIgkpeAwAAAIhvVlmRrLKioM8zbbrItOnSBBEBCFagxHVj9gEAAAAA0NRIXgMAAABotMr181W59vGgz0s4c7LcZ/3O/oAABGX69On17tuyZUsEIwEAAAAAoC6S1wAAAAAaLeH0sXKlj6j1mOU5Is+SXEmSe9RCGXerOucx6xqIDSdKXvfq1SuCkQAAAAAAUBfJawAAAACNFqj8t1VR5t92pfSTadEm0mEBAAAAAACgGSB5DQAAAAAA6jh48KC++OILdenSRaeeemqd/W+88YZKS0uVk5Oj1NTUKEQIAAAAAGhugkpeb926VZmZmY06dvv27f7txp5jjNHmzZuDCQkAAAAAANho/fr1uvvuu7VkyRIdPXpUs2bNCpi8XrFihZ544glJUlZWlmbNmqXs7OxIhwsAAAAAaEaCSl5XVlZq69atjTrWGCNjjCQ1eI4xRpZl+Y8HAAAAAACR98orr2jChAmqqKhoVD+96pg1a9bovPPO03PPPadx48ZFKFoAAAAAQHPjauyBlmXJsqxGN1x1fGPOCaZdAAAAAABgv/z8fP3iF7/Q0aNH/Y917txZJ598csDjL774Yp1//vlyuVwyxsjj8ejGG2/UJ598EqmQAQAAAADNTKNmXk+fPr2p4wAAAAAAAFF0++23q7KyUsYYpaSk6JlnntHll19e7+zrn/70p/rpT3+qdevW6dprr9XXX3+tiooKTZ06VStWrIhw9AAAAACA5oDkNQAAAAAAca6goEAffPCBjDFyuVxavny5zjjjjEad27dvXy1btkynnnqqSktLtWrVKn3//fdKT09v4qgBAAAAAM1NUGteAwCA5sMqK5JVVhT0eaZNF5k2XZogIgAAEC0bNmzwb+fm5jY6cV2lW7duGjdunP76179Kkj788EOS1wAAAACAoJG8BgAgTlWun6/KtY8HfV7CmZPlPut39gcEAACipmby+qyzzgqpjb59+/q3d+zYEXZMAAAAAID4Q/IaAIA4lXD6WLnSR9R6zPIckWdJriTJPWqhjLtVnfOYdQ0AQPNTWlrq327fvn1IbVRUVPi3Kysrw44JAAAAABB/SF4DABCnApX/tirK/NuulH4yLdpEOiwAABAF3bp1829/8803IbXx8ccf+7dTU1PDjgkAAAAAEH9IXseIwsJC9evXL+C+W265RbfcckuEIwIAAACAyJk9e7Zmz54dcF9hYWGEo4k/w4YN82+/8soruvfee4OagX3gwAG98847/u9//OMf2xqfU9C3BwAAABCv7OrXk7yOEV27dtW3334b7TAAAAAAICpOlNjr0aOHCgoKIhxRfMnIyNDQoUOVn5+v4uJijR07Vq+99ppat27d4LkVFRX6xS9+od27d8sYo9NPP73W+tfxhL49AAAAgHhlV7/eZWdQAAAAAADAmWbOnCnLsiRJS5cu1SmnnKJHHnlE+/btC3j80aNHNWfOHJ122ml64403/I8/+OCDkQgXAAAAANAMMfMaAAAAiBKrrEhWWVHtxzxH/NvePd/KuFvVOS/QmvUAEK6zzz5bM2fO1JQpU2SM0Y4dO/THP/5Rd911l7p166aePXuqe/fu2rdvn7Zt26bvv/9eFRUVsixLxhhJ0qRJkzR69Ogo/yQAAACNs7fU0r7S4M/rkCR1TDL2BwQAIHkNAAAAREvl+vmqXPt4vfs9S3IDPp5w5mS5z/pdE0UFIJ797ne/U6dOnTR58mTt379flmWpsrJS27dvr1PirWbS2uVy6Z577tE999wTjbABAABCsvwrS4vWWEGfN2aoUW42yWsAaAokrwEAAIAoSTh9rFzpI4I+j1nXAJrSL3/5S1188cWaPXu25s6dqx07dkiSv6R4Ta1atdLPf/5z3XbbbRowYECkQwUAAAjLiIFGQzJrJ6HLPZbyFvo+9+TlGiW66yapOyRFJDwAiEskrwEAcCCrrEiV6+cr4fSxjkpihRt3oBLLjUGJZcQqXpsAYlVqaqruv/9+3X///dq8ebM++eQTFRcXa//+/WrdurU6deqk/v37a/DgwWrRokW0wwUAAAhJxySjjscloo9USJIveZ3R2ahVC2ZYA0AkkbwGAMCBrLIiVa59XK70EY5KfIUbd0MllutDiWUAAELXu3dv9e7dO9phAAAAAADiAMlrAADgZ3kr/dveXflypZ0r40qIYkS1BSqxbHmO+NcFdo9aKONuVec8JyX4AdiPqg0AAAAAAADOQPIaAABIkiq3LpXnozz/9563b5CSUuXOnq6EjJHRC6yGQIkkq6LMv+1K6SfTok2kwwIQ46jaAFR77733an1/3nnnRSkSAAAAAADqsjV5/cEHH+jtt9/W2rVrVVpaGvT5xhitWLHCzpAAAEAjVG5dKs+Km1W1ppNfaaHv8eFPxkwCGwCCRdUGoNr5558vY3zrNhpj5PF4/PsyMzNtuYYxRps3b7alLQAAAABAfLElee3xeDR16lQ99thjIbdhWZa/Aw0AABrH8hypNfM4pDa8lcdmXFuB9koy8nx0r0y3YWGXELc8R8I6HwBCQdUGoC7Lqvu+v3Xr1rD75fTtAcB+e0stLf/K0oiBRh2TYu9vbKzHBwAAnMWW5PXs2bM1a9YsSb4R1oE6wQAAwH5VswabliWV7VLFS2dE4FoAAKCpnajPTn8eAGLPvlJp0RpLQzKNOiY1/ry9pZb2BV8cUx2SFFQSOtT4AAAAAgk7eX3w4EHdf//9tcqO3XTTTcrJyVFqaiojrgEAAIAYYpUVqXL9fCWcPtYxZbGdGDMQq6ZPn17vvi1btkQwEgBAU1v+laVFa4IflDRmqFFuNvd0AQBAdISdvP78889VUlIiyZe4fvPNN3XxxReHHRgAAGiYe9RCuVL6hdWGd1e+PG/f0PC1Lp4rV2pWeNfa822EZosDqI9VVqTKtY/LlT7CMYlgJ8YMxKoTJa979eoVwUgAAE1txECjIZnVSeivf7D0r08tHThcfUz71tJlPzIa0LP6uA7MnoYDOaF8vRNiBIBYEHbyeuPGjZJ8iesrrriCxDUAABFk3K3CXqfVlXaulJQqlRYq8LrXRkpKlSvt3LDXvDbuVmGdDyA2Wd5K/7Z3V74tfy8AAAAQno5J1WW88zdZevmDuv29/Yellz+wNGWUUVYfkmlwLieUr3dCjAAQC8JOXlfNupak7OzscJsDAAARZlwJcmdPl2fFzZKMaiewfTcv3NnTSEQBCKhy61J5Psrzf+95+wYpKVXu7OlKyBgZvcAA1HHnnXdq165d6tKlix5++OE6+ydOnChJ9e4HAERXucfSkYrgz/N6Lc1ddeLy4fPe9WpATyOXK/gEdrkn+NLkQCzzeqtf0+sKLA1KV0i/GwCA0ISdvO7Zs6d/u0WLFuE2BwAAoiAhY6Q0/ElfAqqssHpHUqrc2dNIQAEIqHLr0mMDX467YVla6Ht8+JP8/QBiyFNPPaUDBw6oR48eAZPT8+bNkzFGvXv3JnkNADEob6GlwNWywldySJo4p+naB5wif1PtwR4zFlvqlGxpQo6L6gQAECFhJ6+zs7NljO+P9po1a8IOCAAAREdCxkiZbsNU8dIZko6tcU3pX6DZsjxHZFWUhX6+t/LYjOtANzgtSUaej+6V6TYs7L8jludIWOcD8ElISJBlWSooKND333+v9PT0aIcEAAAQM/I3WZq5xFvn8ZJD0swlXk0ZRQIbACIh7OR1RkaGfvazn2nx4sV6++23tX37dvXo0cOO2AAAQITVTDC5UrNIXAPNmGdJbhNfwZLKdvkHxACIvv79++uDDz6QZVkaNmyYrrnmGrVv377OcSUlJbrvvvvCuta0adPCOh8AUFderlFG5+ATZ+sKLM1Y3PCM6qmjjfqmBd/+1mLr2KxwIPpitbx+VWwAgIaFnbyWpKefflpffvmltmzZoquvvlorV65U69at7WgaAAAEYNp0UcKZk2XadIl2KMExLpnUoZJxRTuSRrPKilS5fr4STh/rvOcbAIAaJk+erPfff1/GGO3YsUOPPfZYnWMsy9LevXt17733hnUtktcAYL9Et1GrFsEnzQalS52SLZUcqv+YlGRpUHpoSblEt0S5ccQKyusDgPPZkrw+6aSTtGLFCl133XVas2aNMjMzdc8992jcuHFq166dHZcAAAA1mDZd5D7rd9EOI3iWV9auNZJVtwxXrLLKilS59nG50keQvEaz4h61UK6UfiGf792VL8/bNzR8nYvnypWaFfJ1JMm759sIzBQHmr+rrrpK999/vx544AGVl5fXe5xlhXdDtmppMQBAbHC5jCbkuAKWQ64yPscV8mxSAAAAO9mSvL7zzjslScOGDdOGDRtUWFioSZMmadKkSTrppJOUmZnZqJnYxhitWLHCjpAAAECcsLyV/m3vrnzW6QYaybhbybRoE/L5rrRzpaRUqbRQgWceGCkp1ZbfSeNuFdb5e0st7Ss9rk2PpW7HtrcVW7LcdX+GDklSxyRu4qJ5ueuuuzR+/HitXr1a//3vf3X06FH/vnvvvVfGGHXs2FGTJk2KYpQAALtl9TGaMsqluau82lvjc1FKsi9xzTq+aC5itby+RIl9AGgsW5LXDz/8cK2R1VXblmWpuLhYu3fvbrANy7IYnQ0AAIJSuXWpPB/l+b/3vH2DlJQqd/Z0JWSMjF5gQBwwrgS5s6fLs+JmSUa1E9i+z/Xu7GkxMZhk+VeWFq2pfZOopbx6Otm3PW2hV0dVdybSmKFGudn0UdD89OjRQ1dffXWdx6tKhXfq1EnTp0+PdFgAAJsdP4Cvcztp0k+l+17zfT8+Rzo11cjlkrYUVX9WiuQAvkCDDBuDQYaoT6yW1/fFJlFyHAAaZkvyWjpxWbFwS44BAAAcr3Lr0mNJs+M+Z5QW+h4f/iQJbKCJJWSMlIY/6RtEUlZYvSMpVe7saTHzOzhioNGQzNo3mI4eMdK/fdt3XWnUspWrznkdkiIRHRBb6L8DQPMRaABfTc+/K/n6U7WPCXYA34HDVo2vwSX1GoqxPsHGuLfU0vKvLI0YaEh6IyDK6wNA7LAleb1y5Uo7mgEAAHHC8hyRVVEW+vneymMzrgPd5PDdMPF8dK9Mt2Fhz/q0PEfCOh9o7hIyRsp0G6aKl86QdGyN6xgr398xyajjcYnoI2XVN516nWTUqg03oQCvt/6btQAQKickDbcWe/X8u5bG5xhldK47oC3ajLHUN833NZjkcKABfI0RyQF8gWIs91SXVs7LNUp01/0Zgo1xX6m0aI2lIZl1PxcCVSivDwCxwZbkdU5Ojh3NAAAgSbLKimSVFQV9nmnTRaZNlyaICHbzLMlt4itYUtkufzINQNOqmah2pWbFVOIaQLU777xTu3btUpcuXfTwww/X2T9x4kRJUteuXfXQQw9FOjwAzZQTkobb90jrCnxfMzo3/rxIlby2LKN1BZYsK7jEWaABfE2hXWvfEjK+r8EJFGNZefUg5cNHpVNTxWxXRExWH6MBPY0mzvG9DqeONmGVCgcABM+2suEAANilcv18Va59POjzEs6cLPdZv7M/ICAMDMZArDFtuijhzMmOen05MWYgFj311FM6cOCAevToETB5PW/ePBlj1Lt3b5LXAKIuUGLY67W0tVg6cFhq19qXaD4+oRTJtZAjVfI6nuRvsjR3VfVzOmOxpU7JliYw6xUR5Pu74nsd9k0jcQ0AkUbyGgAQcxJOHytX+ohaj1meI/7Zuu5RC2XcreqcR1LDOdyjFsqV0i/k87278uV5+4aGr3PxXLlSs0K+jiR593wb1kxxBmPgRCI1W6cm06aL415bTowZiEUJCQmyLEsFBQX6/vvvlZ6eHu2QAKBejU8Mh7decziOL3n99Q+W/vWppQOHq49p31q67Ee+mZxVIlmW20nyN1kB1xsuOSTNXOLVlFEksFG/Dkm+3/9Y/v1yQowAEAuaLHm9e/du5efn64svvlBJSYn279+vpKQkderUSQMGDNDZZ5+t1NTUpro8AMDBAs04rbk+siuln0yLNpEOCzYy7lZh/R+60s6VklKl0kIFXvfaSEmptqy7G2igRDAYjIETYbYOgEjq37+/PvjgA1mWpWHDhumaa65R+/bt6xxXUlKi++67L6xrTZs2LazzAaBmYvjrHyy9/EH9n5mu/0l1cjiSSaGaJa/zNwWOcf9h6eUPLE0ZZZp94rXcY+lIRWjner21Z1wHMu9drwb0DG0WbLkn+M/ccJaOSbHfR3JCjAAQC2xPXi9fvlwzZ87UsmXLGjx2+PDhuuOOO3TRRRfZHQYAAGjGjCtB7uzp8qy4WVJ1Oa9jeyVJ7uxpMbHuLoMxcCLHz9aRfDfW8hb6XtN5uUaJ7ro3NxipDyAUkydP1vvvvy9jjHbs2KHHHnuszjGWZWnv3r269957w7oWyWsAxws2sdm6pe+f12vpkX+eOPH41ueWhg+oLiF+pCK4ROXRSsv/NdhzJRKvVXyfYZsu1pJDOrYOsTOeDwAAEBrbktcVFRX69a9/rXnz5knydXgbsmLFCq1YsUI33nijZs+erRYtWtgVDgAAaOYSMkZKw5+U56M8qaywekdSqtzZ03z7gRhXc7ZOFd9NXd9n6YzORq1aMDIfgD2uuuoq3X///XrggQdUXl5e73GN6c+fiDH83QJQV1MmNu1Kav5tufS35XXLVtuBxCsAAEDj2JK8tixL119/vRYtWlSrk5uSkqJTTz1VvXr1Uvfu3VVcXKzvvvtOGzduVHFxsf/cZ599VqWlpXr55ZftCMeRCgsL1a9f4LU/b7nlFt1yyy0RjggAEAyrrEhWWVHQ5wWalRspgWK2PEf8294939ZbzjpWSlonZIyU6TZMFS+dIenYGtc2lAoHAETe7NmzNXv27ID7CgsLAz6O4N11110aP368Vq9erf/+9786evSof9+9994rY4w6duyoSZMmRTFK56JvDyCe5eUaZXQObQDTugJLMxY3nNifOtqob1rw19haXF3dCAAANA27+vW2JK9feuklvfbaa/7R1f369dPUqVN13XXXye2ue4nKykotWLBADz74oNavXy/LsvTKK6/osssu03XXXWdHSI7TtWtXffvtt9EOAwDCZpUVqXL9fCWcPjZmEpwNsSPmyvXzVbn28aDPSzhzstxn/S6ka4aroZir1mQ+XjRjDqRmotqVmkXiGgAc6kSJvR49eqigoCDCETVfPXr00NVXX13n8apS4Z06ddL06dMjHVazQN8eqF+oic2mTmpK0n82evW35dJNI6RzTnUFfT6JV59Ed+hVgwalS52SLZUcqv+YlGRpUHpopdcT3RKz3gEAaFp29ettSV7n5eX5t8eMGaMFCxYETFpXSUhI0Lhx43Tttdfqmmuu0eLFi2VZlqZNmxa3yWsAaC6ssiJVrn1crvQRzkpehxlzwulj5UofUbtdzxF/Atg9amG9s5ijJVDMjRFOzKZNFyWcOdkxrw3JmTEDABCqcEuGA0B9Qk1sNnVSU5JaJhhJllomxGaM8ZB4dbmMJuS4NHNJ/WXbx+e4Qv4/BgAAzhF28vqbb77Rli1bZIxRly5d9Nxzz50wcV1TixYt9Pzzz6tPnz7avXu3vvvuO33zzTfq379/uGEBAJoZy1vp3/buyo+50tCBSmlbFWX+bVdKP5kWbSId1glFo/y3adMlpmZtN4YTYwbQPDhxSQo4m9fbNOu8AkA4nJDUdEKMTpDVx2jKKJfmrvJqb2n14ynJvucvqw/PHwAA8SDs5PWnn37q377mmmvUtm3boM5v166dLrjgAi1cuFCS9Mknn5C8BgDUUrl1qTwf5fm/97x9g5SUKnf2dCVkjIxeYAAANCEnLkkBAIBd9pZa2ncsgdm5nXT9T4z+9amlA4erj2nfRrrsLKPO7aQtRb6ZyR2SpI5JkUlyOiFGp8nqYzSgp9HEOb7naupoE9as+nDV/D8OBv/HAACELuzkdVFR9UyAUJPOWVlZ/uR1zfYAAKjculSeFTerTom00kLf48OfJIENAGiWnLgkBeLb66+/roMHD0qSfvnLX0Y5GgBOt/wrS4vWnLhU9v4y6eUPLNXsL44ZapSbHZmkoRNidCJfotr3fPVNi17iWmrc/3Eg/B8DABC6sJPXxlS/CXs8npDaOHr0qH87ISF2SsACAEJneY7UKpsdUhveymMzrgN1FC1JRp6P7pXpNiysEuKW50jI5wIA0FScuCQFYtuFF14oSerRo4deeOGFBo//8ssvJUktW7bU6aef3uDx//u//6vvvvtOEslrAOEbMdBoSGbwyb8OSU0QTD2cEGMkdEjyJWtD+bkCzWwu91TfA9habB1b87vuNYOZ2RxqjIH+j8s9lvIW+mLMyzVKdNeNo7n9HwMnQoUCAHYLO3mdmprq3167dm1IbXz88cf+7S5dmCUAAM1B1aywpmVJZbtU8dIZEbgWEF9YaxcAmp9Vq1bJGKPevXs36vjBgwfLGKM+ffpow4YNjTrHsqxag9wBINSkYccko44RSgD2SJH6pvm+BiNSMYaTHI6EjkmhzzJuaGazL0lcd3+wM5tDjTHQ//GRCvljyuhs1KoF73uIb1QoAGC3sJPX2dnZknwd1IULF+qBBx5Q165dG31+cXGx3nnnnTrtAQAAIHpYaxcAIPn6+pYV/M1IAKgSTmIzUjI6uzT96mhHUT8nPIehitTs9b2llpZ/ZWnEQBOTMz1jPT7gRKhQAMBuYSeve/furYEDB+rrr7/WwYMHlZubqyVLlqht27YNnnvo0CHl5ubqwIEDMsZowIAB6tOnT7ghAQBigHvUQrlS+oXVhndXvjxv39DwtS6eK1dqVujX2fNthGaKA87BWrsAAEnMogYANKlIzV7fVyotWmNpSGbkZvQHI9bjA06ECgUA7BZ28lqSHnzwQV1++eUyxujDDz9U7969ddttt+nmm29W+/bt6xx/8OBBzZ49W7NmzdLu3bv9j//pT3+yIxwAQAww7lZhr8PpSjtXSkqVSgsVeN1rIyWlypV2blhrXgdKwAHxjrV2AQAAAKAur7f6/sS6AkuD0iWXi8QcAAB2sSV5PWrUKE2ePFmPP/64jDHavXu37r77bt1zzz1KS0tTRkaGunbtqsLCQm3btk0FBQXyer211sKaNGmSLrvsMjvCAQA0E8aVIHf2dHlW3CzJqHYC2/f+4c6eFlbiGgAAAAAAoDHyN1mau6r63sSMxZY6JVuakONSVh8S2E60t9TSvtLaj5V7qv+PtxZbSgyQRemQJEq8A0ATsSV5LUkzZ85Up06ddP/998vj8UiSvF6vfvjhB23fvt1/XNVaWVVJa5fLpbvvvlvTpk2zKxQAQDOSkDFSGv6kPB/lSWWF1TuSUuXOnubbHybrSEmtr05glRWpcv18JZw+ljLNAAAAAAA0sfxNlmYu8dZ5vOSQNHOJV1NGkcB2ouVfWVq0JlC1Px/fus11948Z2nzXogeAaLMteW2M0T333KOrrrpKjz32mF555RWVlvqGLFUlrGtq06aNrr32Wk2ePFkDBw60KwwAQDOUkDFSptswVbx0hqRja1yHWSq8lqqktdOS12sflyt9BMlrAAAAAAAaodxjHVuLNzheb+0Z14HMe9erAT1NSCXEa870RWSNGGg0JDP4/7MOrE0OAE3GtuR1lf79++vpp5/WnDlz9NVXX+nLL7/U3r17dejQISUnJ6tjx44aOHCgBg4cKLfb9ssDQJOxyopklRUFfV6gdWMjxYkx16dmotqVmuWIUuGWt9K/7d2Vb2/CHQAAAAAABKW+WbR2KDkkTZzTdO2jaXRMMupIIhoAYkqTZY8TEhI0ePBgDR48uKkuAQARVbl+virXPh70eQlnTpb7rN/ZH1AjRCNm06aLEs6cHHPJ7xNq1an2VxtUbl3qK3V+jOftG46VOp9uS6lzRI4TS7Q7MWYAAAAAAAAAYOozADRSwulj5UofUesxy3NEniW5kiT3qIUy7lZ1zotm4igaMZs2XaKWrA+VOZa0NjYlryu3LpVnxc2qM9q6tND3+PAnSWA7iBNLtDsxZgAAAABoanm5Rhmdgy8Rva7A0ozFDc+onjraqG9a8O1vLbaOzQoHAACNTl5///33tb5PT0+3PRgAaErhzkQMVErbqijzb7tS+sm0aBN2nLXad2DMTmZ5jtR6fkJqw1t5bMZ1oE6nJcnI89G9Mt2GhVVC3PIcCflcRB8l5YHgOLGagBNjBgAAaO4S3UatWgSfXB6ULnVKtlRyqP5jUpKlQemhrXmd6JYoNw4AgE+jk9cZGRkyxvfGa4yRx+Px77vwwgttCcYYoxUrVtjSFgAcz4kzEZ0Ys5NVzUhvWpZUtksVL50RgWshFlFSHgieE98PnRgzAAAAAnO5jCbkuDRzibfeY8bnuEJKXAMAgNqCLhtuWXVHgK1atcqf2A6VZVlhtwEAkcbsSQDBoKQ8EENqvIerMF9Wr/N4DwcAAEC9svoYTRnl0txVXu0trX48JdmXuM7qw71tAADsYNua14GS2gDQnEVi9qR1pKTWVydwcplU96iFcqX0C6sN765832uhoWtdPFeu1KzQr7Pn2wjNFI8tVlmRrLKi2o/VKKHu3fNtveu4h/t6DLesfKRKykuUlQcaUrl1qfSfPP/35p2JOkoFBAAAADQgq4/RgJ5GE+f4+nVTR5uQS4XbZW+ppX2lDR93vA5JUsckEu4AgNjT6OT1+PHj6923cuVKW4IBAKeI2OzJqqS105LXYZZJjVaC0rhbhb0GuCvtXCkpVSotVOAkpZGSUsOepR/o548Hlevnq3Lt4/Xury+hn3DmZLnP+l1Y1276wQKUlHeavaWWln9lacRA46ibPk6N2y5UQACkrVu3KjMz0/bjt2/fHk5YAAA4gi9R7fss2TctuolrSVr+laVFa4KfWDZmqFFudvz1BwAAsa/Ryeu5c+fWuy8nJ8eWYAAgEhw1e7LyaFjnB2zTAaXOo5mgDJdxJcidPf1YYqS6Q3tsryTJnT0t5p5zp0g4faxc6SOCPs9pVQDgDPtKpUVrLA3JNOqYFO1oGs+pcUv2vofXvU1HBQTEj8rKSm3durXB46qW9gr2eAAAYk2HJF+ytkOMfv4NJ74RA42GZNZ+Dy73WMpb6LsfkZdrlOiu+x4dq88FAAC2lQ0HAKeI59mTkSh1bgenJygTMkZKw5/0PddlhdU7klLlzp4WU8+109hR/jtU4ZaVj1RJeSl+y8o3F15v9aCXdQWWBqUr6rM5YoUT38NZ+gOxJpglv4JdHozlxAAAsapjUmzPMg4nvo5JdQelHqmQqgbTZ3Q2atUidn92AACOZ0vy+oUXXpAktW3bVldeeWXQ5y9evFj79+9X165ddckll9gREgDgOE4qkxrNBKVdEjJGynQb5k+AuC+eG5Oz3NF44ZaVj1RJeSl+y8o3B/mbLM1dVf36mLHYUqdkSxNyXMrqww0nR3Ja8jrMpT8Q26ZPnx7tEAAAAAAAOCFbktcTJkyQMUa9e/cOKXn9yCOPaPXq1erfvz/JayBOBFrTuDHsSGo6afZk5XdvqPKDqbIqjzqn1DllUv1qPpeu1CwS13GOkvJoSP4mSzOXeOs8XnJImrnEqymjSGA78T3cbk5Y/gOxi+Q1AADB2VtqaV9p7cfKPdV9ua3FlhID3GHvkOSbEQ0AAIJnW9nwcMqDud1uWZal7du32xUOgBjX0JrG9bFjTWNHzZ5MaClJqvxgapPcAK8Wu6XOI8G06aKEMyc7apaZE2MGJeWbq3KPdawsX+i83tozrgOZ965XA3qasEuI17zZ5jROfA+3k1OW/wAAAGguln9ladGa+j8/+9aVrrt/zNDYLlMOAEAsCyp5/d5779W7zxijw4cPn/CY43m9Xm3evFmrV6+WJHk8nmDCARAldqyHGGhNY8tzxL+WpXvUwoBlb8NJ1FWtORnu2pPMnmx+TJsuYQ+KiDQnxgwfSso3P/XdsLJbySFp4pzIXKu5qvkebsnIOOg93EnLfwAAADQXIwYaDckMPgndIanhYwAAQGBBJa/PP/98GRP4zdqyLO3YsUMXXHBBSIEYY3TKKaeEdC6AyLJjPcRA5b9rlsV2pfQLa2ZVQFVJaxvWnoz07MmEn8xQQuZlIZ8fyTKp3j3f+gchAAiMkvJA9FS9h1f8J0863PTv4eEu/SFFbvkPlv4AAACorWOSUccIJKL3llpa/pWlEQNNzJYbd0KMAIDmIeiy4ScqDx5O6XBJuvXWW8M6H4CzOW0Nx0jOnjQJLZ1TJjXAjHnAyZxYot2JMTtZXq5RRufwbt6sK7A0Y3HDn6WnjjbqmxbetbYWW8dmi8evhIyRqjjpHOnVQZIk68LnlNjrvCZ5D2/6pT+keF/+AwAAwOn2lUqL1lgakhmZZHkonBAjAKB5CCp5fd555wWcef3uu+/KGKNWrVopKyv4GXspKSkaM2aMrrvuuqDPBdA8OHUNR6fMnqTUORA6J5Zod2LMTpboNmrVIryE8qB0qVOypZJD9R+TkiwNSg9/zetEt0TpcUk13/O6xu57OAAAABAsr7f68/66AkuD0hV2PwIAgEgJKnm9atWqgI+7XC5JUlpamlauXBl2UADiS8TWcGzVqfZXJ7Ax5kiXOgcANJ7LZTQhx6WZS7z1HjM+xxUTN5z2llraV1r7MeOx1O3Y9rZiS5a7bnK8Q5JCLi/oyGoCx967E4b/TQlpw8JqKlLLf7D0BwAAgPPlb7I0d1X15/EZiy11SrY0IcelrD7R708AANCQoMuG1yfckuEAnMfyHHHMGo6SJLev7LZxUPK6Kla7Yo5kqXMAQHCy+hhNGeXS3FVe7a2RHE5J9iWuY+VG0/KvLC1aU/t9u6W8ejrZtz1toVdHVTcJP2aoUW52aD/DPquzlh+9VSMso44htRB5B62Oai3pUEKqOoSx9IcUueU/WPoDAADA2fI3WQEHxJYckmYu8WrKqNjpVyD2OGFdcyfECCB8tiSvq2Zbt27d2o7m4lJhYaH69esXcN8tt9yiW265JcIRAQ2LzMyc2FnD0SorklVWVPsxzxH/tnfPtwFv+po2XWJqpphTSp0DQDzK6mM0oKfRxDm+BOXU0caWUuF2GjHQaEhm7XiOHjHSv33bd11p1LKVq855HcJYF8+J6+sdOixf8vqw1CHMtuJl+Y/Zs2dr9uzZAfcVFhYGfByINfTtAQDhKPdYOlIR2rleb+0Z14HMe9erAT1D61+Ue5i81tw5od/lhBiBeGZXv96W5HVOTk6dx7Zv3y63263U1NQ6+/7zn/8oISFBQ4YMUUKCs2+w2KVr16769ttvox0GgBOoXD9flWsfr3d/fcn8hDMnh7z2rBPLpDoxZqApRaPEMpzNdyPJ95romxZbiWvJ97o8/ibBkbLqGHudZNSqTWzFHIjXK230DNU+q7Pa73BpUKYVc891TfGw/MeJEns9evRQQUFBhCMCgkffHgAQjryFlgJX2rFHySEdGyhLIhpNi3XXgxPo3lFjcO8Iscaufr1tZcMlac+ePXrooYf0yiuvaOfOnZo1a5ZuvfXWOsctXLhQTzzxhNq0aaPLLrtMf/rTn5SZmWlnKAAiwD1qoVwpgWcVNFak1nCUwl/HMeH0sXKljwj6vHCSuKZNl5AT39HixJiBphSNEsuIjA5Jvv+ncGYUR4NT47aTbx3ARO098rLvgSVSp2RvzK8DyPIfAAAAAGId664HL9C9o8bg3hGaK9uS1++//76uvPJK7d27V5ZlyZgT/8JYlqWysjL9/e9/15IlS/T6669r+PDhdoUDIAKMu5WMQ9ZwlMJfxzHWyn8DcIZolFi2yopUuX6+Ek4f65i/W06MuWOSMzuJTo3bLk5fB5DlPwAAAJqvvFyjjM6hfRZdV2BpxuKGk19TRxv1TQv+GluLrWMzwxFpTpqV6/T+VrQEundU7qn+ncvLNUp0133e4nlQOpo3W5LXGzdu1E9/+lOVlZX5k9Yul0spKSkBjx8yZIgyMjK0detWGWN06NAhXXnllfr00091yimn2BESAIeIlzUcAcSvaJRYtsqKVLn2cbnSRzgmEezEmBF54awBKB2/DmDg37tw1gGs6bC7s14/Oklnt3LO65mlPwAAAKIr0W3UqkVon0MHpUudki2VHKr/mJRkaVB6aJ91E90S5cajI9KzckPtdzX1uutVsTVHAe8dVUhVv3MZnUP/2wA4kS3J6ylTpvgT1y1bttSMGTM0YcIEtWvXLuDx119/va6//notX75c48eP165du1RaWqqpU6fqH//4hx0hAXCQeFjDEc2fVVYkq6yo9mOeI/5t755vA87+Z0Y/nMTyVvq3vbvyKVeMiGvqNQAlO9cB7CxpsoYGqKwQq1j6AwAAwLlcLqMJOa6As16rjM9xse6wA0V6Vm5T9rtYdx1AY4SdvC4uLtabb77pn3H95ptv6oILLmjUuSNGjNCqVavUv39/eTweLV68WEVFRerShZv4QLxhDcemQUI1cirXz1fl2sfr3V/feusJZ04mUQBHqNy61DfI6BjP2zccG2Q0nUFGAAAAABADsvoYTRnl0txVXu2tUWY6JdmXuKZcszMxKxdAvAk7eb1+/Xr/9qhRoxqduK5yyimnaOzYsXrhhRckSe+9956uvvrqcMMC4ECs4Wg/EqqRk3D6WLnSRwR9HoME4ASVW5ceW97huJHRpYW+x4c/SQIbERHOGoBS068DWBNrAsLJPvjgA7399ttau3atSkuDX2DRGKMVK1Y0QWQAAKAhWX2MBvQ0x2a3+j7bhloqHPEp1H5XJPpb9LOA+BB28nrDhg3+7ezs7JDaOOOMM/zb27dvDzckIO4Eml3bGKHOrnXqeohOjTscJFQjh9nqiEWW54isirLw2vBWHptxHahzaEky8nx0r0y3YWENOqpZFSLkNiL8fojIC2cNQKnp1wGsiTUB4UQej0dTp07VY489FnIblmX5K7MBAIDo8H2W9X0W7ZtG4hrBCbXfFYn+Fv0sID6EnbwuKSnxb4da7tvtrg7jyJHwb1wC8aah2bX1CXV2rR3rIUajnHU8ruNIQgaIb/VVV7CXJZXt8i/7EE2Rfj+E89ReB9A3+OJ4rAOIeDZ79mzNmjVLkm/2tGVxYxAAgEjokCSNGWpCXqM4EpwQI6KLddcB2CXs5HW3bt3825s3bw6pjU8++cS/zXrXiDdWWZEq189XwuljQ04yBppda3mO+JMW7lEL600Eh8KOmClnDQCwW6TfD+FM1esAVrIOIFDDwYMHdf/99/tnTRtjdNNNNyknJ0epqanMpgYAoAl1TDLKzY7t91onxIjoi9V11/eWWtoX/Go46pDke+0DiKywk9c/+tGP/NuvvPKK8vLylJiY2Ojzy8vLtWrVKv/3gwYNCjckwFGssiJVrn1crvQRYc0oPv7cmmViXSn9ZFq0CSvOWm3bEDPlrAGg6blHLZQrpV9YbXh35cvz9g0NX+viuXKlZoV+nT3fhj1TPNLvh3CurD5GA1LLtfHlG7XP6qz2Ix7RoMxWzABAXPv888/9ldWMMXrzzTd18cUXRzkqAAAAOE0srru+/CtLi9YEX1VozFAGbQDREHbyul+/furXr5/WrVun77//XjfffLOeeeaZRo/Knjx5srZv3y5jjHr06FErGQ4gdJa30r/t3ZUvV9q5Ya1FajfKWQNA0zPuVmEna11p50pJqVJpoQKvK2WkpNSw32cCzYgGmpLLJfV1r5EkWd0fJnGNuLdx40ZJvsT1FVdcQeIaAAAAIYu1dddHDDQaklk7hnKPpbyFvhjzco0S3XVjpEw+EB0uOxqZMWOGfy2sefPm6cc//rH+/ve/q7Kyst5zli5dqp/85Cd6+umn/Y/l5eXZEQ4Q9yq3LlXFPy7yf+95+wYd/ftPVLl1aRSjAgA4kXElyJ09veq74/dKktzZ02JqgBSaHyeur+fEmBHfqmZdS1J2dnYUIwEAAEA0OKEPE2qMHZOMTu5S+19G5+p7HBmd6+4/uYuhZDgQJWHPvJakUaNG6bbbbtOsWbNkjNHatWt13XXX6aSTTtJpp52mnj17qnv37tq3b5+2bdumjRs36ocffqjVxlVXXaUJEybYEQ4Q1yq3LpVnxc2qMzuutND3+PAnlZAxMiqxAQCcKSFjpDT8SXk+ypPKCqt3JKXKnT2N9xU0OSeur+fEmBHfevbs6d9u0aJFFCMBAABANDihD+OEGAGEz5bktSQ9+uijat++vR544AF5PB4ZY1RcXKzdu3fXe07VbO0JEyZozpw5jS41DjRHludIrXU5Q2rDW+lLLAQs62pJMvJ8dK9Mt2FhzZCzPEdCPhcA4EwJGSNlug1TxUtnSDq2xnWMLUmByLDKimSVFdV+8Mjh6u2Sb+Uta13nPJYMAWJbdna2v0++Zs2aKEcDAAAAAIhXtiWvJWnatGm68sor9cgjj2jhwoU6evSoP0EdyAUXXKA77rhDI0cyWwfwLMmNwFUsqWyXP/EAAEAwaiaqXalZJK7jVOX6+apc+3itx2oOQTXLrlFFgPMSzpws91m/a8rQmp29pZb2ldZ+zHgsdTu2va3YkuWu29/qkCTK2yFoGRkZ+tnPfqbFixfr7bff1vbt29WjR49ohwUAAAAAiDO2Jq8laeDAgXrxxRf11FNPac2aNfrkk09UXFys/fv3q3Xr1urUqZP69++vc845R2lpaXZfHgAAIO6ZNl2UcOZkR81ydWLM8Srh9LFypY+o9dhRj6XpC72SpHtzXWrprps45f82eMu/srRoTe3kdEt59XSyb3vaQq+OylvnvDFDKaWH0Dz99NP68ssvtWXLFl199dVauXKlWreuW0kBAADEjkADHss91Z8htxZbSgyQBYjUgMdA8TUGAzIBIH7ZnryukpycrOHDh2v48OFNdQmgWXGPWihXSr+w2vDuypfn7RsavtbFc+VKzQr9Onu+jdBMcQBAKEybLo6b4erEmONVwPLfFZa2eY8lUVNccrXgJpMdRgw0GpJZ+7k8esRI//Zt33WlUctWrjrndUiKRHRojk466SStWLFC1113ndasWaPMzEzdc889GjdunNq1axft8AAAQACBBjzWlLfQUqAlBiM14LGh+OrDgEwAiF9NlrwGEBzjbiXTok1YbbjSzpWSUqXSQgVe99pISalhr1Fq3K1CPhcAnGZvqaXlX1kaMdA4ZtS3E2MGUFfHJKOOxyWij5RV/073OsmoVRt+x2GfO++8U5I0bNgwbdiwQYWFhZo0aZImTZqkk046SZmZmY2aiW2M0YoVK5o6XAAAoMADHhsjUgMeA8VX7rGOJdWlvFyjxACVmxiQCcQWqiggkkheA82IcSXInT1dnhU3y7f6ZM0Etu8Nwp09jTVKASAI+0qlRWssDcmsm0SKVU6MGQAQfQ8//LCMqb6xVLVtWZaKi4u1e/fuBtuwLKtWGwAAoGkFGvAYSwIOyKyQqu5bZnQ2akXlJiDmUUUBkWRL8nrixIl2NCNjjJ599llb2gJCZZUVySorCvq8gCU0oyAhY6Q0/El5PsqTygqrdySlyp09zbcfABAxgd5XvIcPa6NnqPZZndV+w/camFYp13GVf2PlfQUAEF8sq/4bUifaBwAAAKD5oooCIsmW5PW8efNsG1ndFMnrvXv36rvvvtPBgwfVvXt39enTR67j7xCHwev1atu2bfrhhx+UmZmptLQ0Rpo7WOX6+apc+3jQ5yWcOTlm1upMyBgp022YKl46Q9KxNa7DLBUOAAjN8e8rn3gu1kvl92iv9bLvgfekjmanxiXeryHut/3HxdL7CgAgPqxcuTLaIdSLfj0AAAAQPVRRQCTZVjY82BHYNcuPHf+YXTZu3Kjf//73euutt1RZWel/vGfPnpo8ebJ+97vfKSEh9GTeli1bNHXqVL3xxhs6fPiw//Hk5GRdd911euCBB9SlCzOmnCbh9LFypY+o9ZjlOSLPklxJknvUwoBrPsfa7LiaiWpXahaJawCIkprvK/nft9Vf3k+rc8xeK1V/OTJbvzu3QFnpByXF3vsKAKD5y8nJiXYIddCvB5oOa1cCAAAgFtmSvJ47d26jjisvL9eWLVu0efNmvfPOOyopKZExRlOmTNHUqVNtTV6///77GjlypMrKyurs++GHH3T77bfrvffe0z/+8Y+QOrqvvfaaxo0bp/Ly8jr7Dh06pKefflqvvvqq3njjDZ177rkh/QyIjkBlWq2K6teRK6WfTIs2tl4v4czJjkpSODFmAAhXucc6NqI0SC06S+07y+u19Pxn9Q32830GemFtD53R38jlOvaZqCK08qzlHsq6AgCcj3490LRYuxIAAACxyJbk9fjx44M+5+DBg5o1a5YeeughzZw5UwcOHNBf//pXO8LR7t27deWVV6qsrEwul0t5eXm64YYb1LFjR+Xn5+v3v/+91q5dq3/+85+67777dO+99wbV/qZNmzRx4kSVl5erdevW+uMf/6hrr71WaWlp2rp1q5599lk98cQTOnDggMaOHavPP/9cKSkptvxsaH5Mmy6OKwvrxJgBIFy+NXyaNilcckiaOKfprwMAQKyjXw803t5SS8u/sjRioAlqRnSk1q4MNT4AAADEJ9vKhgerbdu2mjZtmtLT0zVx4kQ988wzOuuss/SrX/0q7LYfeeQR7dmzR5L0xBNP6JZbbvHvu+CCC7Rq1SoNGjRIW7du1aOPPqrf/va36ty5c6Pbf/jhh3XwoK+k5zPPPKOxY8f69/Xv318zZ87USSedpLvuukvbt2/XU089pbvvvjvsnwuoj1VWJKusqPZjniP+be+eb+stdc7saQAAAAD12b17t/Lz8/XFF1+opKRE+/fvV1JSkjp16qQBAwbo7LPPVmpqqu3XpV8PNN6+UmnRGktDMuuuRXkikVq7MtT4AKC5ifXBPLEeH4D4EbXkdZUJEyZo8eLFWrx4saZPn64bb7xRbnfoYVVWVuq5556TJHXp0kW//vWv6xzTrl073X777frtb3+r0tJSvfrqq/rtb3/b6Gvk5+dLkjp37qzrrrsu4DG//e1vddddd0mSPv7442B/DCAolevnq3Lt4/Xur1qv+3gJZ05mBjUANFJerlFG59A7b+sKLM1Y3PCM6qmjjfqmhddJ3FpcPWMGAIBQLF++XDNnztSyZcsaPHb48OG64447dNFFF9lybfr1QPR4vdWfIdcVWBqUruolbQAAYYn1wTyxHh+A+BH15LUkXXjhhVq8eLGKi4u1cuXKsDq8q1ev9o/Ovvzyy+td9+pnP/uZv2O7ZMmSoDq5GzdulCT17Nmz3nW627Vrp06dOqmkpMR/PNBUEk4fK1f6iKDPY9Y1ADReoju8mSeD0qVOyZZKDtV/TEqyNCjdhH2DMNEtUXocABCKiooK/frXv9a8efMkSZbV8PvJihUrtGLFCt14442aPXu2WrRoEVYM9OuB6MjfZGnuqurf+RmLLXVKtjQhx6WsPiSwASCWMNgIQHMWE8nrfv36+bc3b94cVvJ6w4YN/u1LL7203uN69uypM844Q19++aU+++yzoK7RrVs3bd26VevXr1d5ebkSExPrHFNQUKCSkhJJUvfu3YNqHwgW5b8BIPa5XEYTclyaucRb7zHjc1x0NgEAUWNZlq6//notWrSoVtI6JSVFp556qnr16qXu3buruLhY3333nTZu3Kji4mL/uc8++6xKS0v18ssvhxUH/Xog8vI3WQE/p5YckmYu8WrKKBLYABArGGwEoLlzRTsASfrhhx/82wcOHAirrZ07d/q3e/XqdcJje/bsKUkqKirSvn37Gn2N8ePHS5LKysr0hz/8oc5IdI/Ho8mTJ/u/HzduXKPbBgAAzVdWH6Mpo1x1ym+lJIsbggDqsMqK5N39da1/Kvm2+oCSb+vs9+7+WlZZUfSChqO99NJLeu211/zf9+vXT88//7x27typDz/8UPPnz9ef//xnPf/883r//fe1Y8cOvfDCCzrttNMk+RLYr7zyihYsWBBWHPTrgdCUeywdqQj+X1m5V3NX1T/AUpLmvetVWbk3pPbLPVQEApqDvaWWFq72am9pbP5Ox3p8dqkabLS3tPbjVYON8jc1758fQHyIiZnXr776qn/75JNPDqutXbt2+bc7dep0wmNTUlL82zt37lSHDh0adY0777xTa9as0dKlS/XYY4/pk08+0TXXXKO0tDRt2bJF8+bN09dffy1Jmjhxor9TfCKWZYWVuE9MTAw4UhwAAMSWrD5GA3oaTZzj61BOHW1sKRUOoPmpXD9flWsfr/VYzb8UZtk1qghwXsKZk+U+63dNGVrQysvLVV5eHvL5jSldjfDl5eX5t8eMGaMFCxbI7a7/tkFCQoLGjRuna6+9Vtdcc40WL14sy7I0bdq0eteRbgyn9usl+vaIrryFlppq6ZiSQzr2+ZW/x0C8ivX1kGM9vpp8g42CP8/rrT3jOpB573o1oGdo9xgYbATgRCLZr49q8rqyslL333+/li1b5n+sasR2qGqO0K7ZiQ2k5v7S0tITHFlby5Yt9a9//Ut33nmn/u///k8ffPCBPvjggzrH/eUvf9Ett9xS7/pZNe3YsUPt27dvdAzHmz59eq0bDfHKKitS5fr5Sjh9rGPKaDsxZgBAeHydSN8Htr5pJK4BBJZw+li50kfUeuyox9L0hb7ZcffmutTSXffvRyx+pnzooYd07733RjsMnMA333yjLVu2yBijLl266Lnnnjth4rqmFi1a6Pnnn1efPn20e/dufffdd/rmm2/Uv3//kGJxar9eom8PAEBjxPt6zQw2AuBEkezX25K8njhxYtDn7NmzR5999pl27NghSTLGaOjQoTrjjDPCiqXmCOfWrVuf8Niao5kPHz4c1HVeffVVvfjiiyc85i9/+YtOP/10jRgx4oTHSb71s9atWxdUDDUxMtvHKitS5drH5UofEZM37QJxYswAEE86JEljhhp1iPGR2zU5MWYAdZk2Xep+PqywtM17rLRrikuuFs64yffHP/5RU6ZMCfn8vn37+vuOaBqffvqpf/uaa65R27Ztgzq/Xbt2uuCCC7Rw4UJJ0ieffBJy8tqp/XqJvj2iKy/XKKNz8O8L6woszVjccJJj6mijvmnBt7+12DqWqAEA1msGAKeKZL/eluT1vHnzGj0KuSbLsvznud1uzZw5M+xYOnfu7N/et29fre+PV3M9rIY6xDXNmDFDf/jDHyRJmZmZmjZtmoYNG6bu3btr27ZtWr58uR544AFt3LhRI0eO1EsvvaSf//znJ2zTGKN27do1OgZEluWt9G97d+XLlXaujCshihEBACKlY5JRbrazOtBOjDle7S21tO+4iYI1S7VtLbaUGOATe4ck3/8z4BThlkIOpb+J4BQVVa+VHmrSOSsry5+8rtlesJzar5fo2yO6Et1GrUIY1DQoXeqUbKnkUP3HpCQr5KVufJ9lSF4DqF6v+XhV6zVPGRUfCWwGGwFwokj2620rGx7qGmSWZSkzM1MLFizQj3/847Dj6Natm3+7pKTkhJ3ckpIS/3ZycnKj2v/qq6/0xz/+UZLUr18/5efnKympelpT37591bdvX1199dUaPHiwioqK9D//8z8aPnz4CWNB7KrculSej/L833vevkFKSpU7e7oSMkZGLzAAAOB4y7+ytGhN/Z+j6ysnN2YoAxQA2KvmjQSPxxNSG0ePHvVvJySEPtiXfj0QWS6X0YQcV8CEUpXxOa64KukLoH6s1xw+BhsBwInZkryeO3duSOclJSVp8ODB6t27t20j6VNTU/3bNTuxgezdu9e/nZaW1qj2n332WX+i/tFHH63Vwa2pW7dumj59um655RaVlpZqwYIFuvXWWxt1DcSOyq1L5Vlxs+q8aZcW+h4f/iQJbAAAELIRA42GZAb/OZiS8ADsVrMvvXbt2pDa+Pjjj/3bXbqEviQS/Xog8rL6GE0Z5dLcVV7trVEVJiXZl7iOh5mQABqH9Zqjh8FGAOKFLcnr8ePH29GMLWqO0P7iiy909tlnBzzO6/Xqq6++kiSlp6c3ej2v//73v/7thmaKZ2Vl+bc3btzYqPZhD8tzRFZFWXhteCuPzbgO9GHJkmTk+ehemW7DwiohbnmOhHwuAABwto5JRh1JRAOIAdnZ2ZJ81dEWLlyoBx54QF27dm30+cXFxXrnnXfqtBcK+vVAdGT1MRrQ0xxLHPnKzoY6ew8A0DQYbAQgHthWNjxWDBkyxL/9r3/9S7/+9a8DHvfpp59q165dkqRzzjmn0e23bNnSv33gwAGlpKTUe+yBAwf82+HUgUfwPEtyI3AVSyrbpYqXzojAtQAAAOAke0stLf/K0oiBxjHrkzsxZtind+/eGjhwoL7++msdPHhQubm5WrJkSaMSwocOHVJubq4OHDggY4wGDBigPn36hBwL/XogenyJal/yum8aiWsAdbFec/Qx2AhAc+cKt4EXX3xRZ511ls466ywtXLjQjpjCctppp+m0006TJK1YsaJWCbGa/vGPf/i3r7zyyka3P3jwYP/2smXLTnjs0qVL/duDBg1q9DUAAACAprK31NLC1V7tLXXOjR0nxryvVFq0xtK+0oaPjRVOjBn2evDBB/3ltD/88EP17t1bDz30kPbv3x/w+IMHD+rhhx9W79699f777/sf/9Of/hRWHPTrgeB0SJLGDDVBLyuyt9TSlqLa/7YWV7/Xbi2uu39LkRX0+3Go8QGITVXrNQf7b1C6UafkE7ddtV5zKO0nuuMrcVszUc1gIwDNTdgzr3fu3KnPP/9cxhh9/PHHys2NxIzXE5syZYp+9atfqby8XJMmTdILL7wgl6s6T7927Vo99thjkqSTTz5ZV1xxRaPbHjdunP70pz+poqJCd9xxh4YMGVJrVHiVN954Q48++qgkqVOnTho9enRYPxOC4x61UK6UfmG14d2VL8/bNzR8rYvnypWa1eBx9V5nz7cRmikOAABQnaAckumckuVOjLmpeL3VCYN1BZYGpYsbVbDNqFGjNHnyZD3++OMyxmj37t26++67dc899ygtLU0ZGRnq2rWrCgsLtW3bNhUUFMjr9cqyLBnjex1OmjRJl112Wdix0K8HGq9jklFudvDvBcu/srRoTf2J6PrWtR0zNLjrhRofgOaF9ZpjfzBPrMcHIH6Enbw+9dRT/dubNm0Ktzlb3HDDDXr22WeVn5+vl19+WT/88IMmTJigdu3aKT8/X08++aSOHDkiY4wef/zxWiXDJGnChAl6/vnnJUnTp09XXl6ef1/v3r1133336Y9//KMOHTqkrKwsjR07Vuecc45SU1O1detWLV++XG+99Zb/nNmzZ6t9+/YR+dnhY9ytZFq0CasNV9q5UlKqVFqowOteGykpVa60c8Na89q4W4V8LgAAQCwgoRoZ+ZsszV1V/VzPWGypU7KlCaxtBxvNnDlTnTp10v333y+PxyPJt7b0Dz/8oO3bt/uPq5qhXZW0drlcuvvuuzVt2jRb4qBfj4bsLQ2tUkSHJLE0wjEjBhoNyQz+uSCpASBU8b5ec6wP5on1+ADEj7CT15deeql69uyp7du364MPPlBZWZnatAkvaRiuFi1aaPHixbr00ku1du1avffee3rvvffqHPPEE0/o8ssvD7r9qVOnql27drrnnntUUlKil19+WS+//HKd43r27KmZM2fq6quvDvlnQfQYV4Lc2dPlWXGzpOo1n47tlSS5s6eFlbgGAASHm5RA7CGhGhn5m6yAs1RKDkkzl3g1ZRTPN+xhjNE999yjq666So899pheeeUVlZb63nyrEtY1tWnTRtdee60mT56sgQMH2hYH/Xo0pKFZw/UJdtZwc9YxiYomACKP9ZoBAA0JO3ndsmVLzZ8/XxdddJH27NmjO+64Q7Nnz7YjtrCkpqZq9erV+tvf/qb58+drw4YNOnTokLp3764RI0bo1ltvDbljbYzRzTffrOuuu06PPfaYPv74Y23YsEE7duxQr169dNppp+m8887TzTffrNatW9v8kyGSEjJGSsOflOejPKmssHpHUqrc2dN8+wEAEcNNSiC2kFBtWLnH0pGK8NrwemsPEAhk3rteDegZ3k2/co9z1hRH0+vfv7+efvppzZkzR1999ZW+/PJL7d27V4cOHVJycrI6duyogQMHauDAgXK7w761EBD9epxIoFnD5R7rWKlrKS838PqnzBoGgOjzfWb1/b1mvWYAwPFs6WEOGzZMb775pq699lrNmTNH27Zt01133aXs7Gx/CbFoaNmypX7729/qt7/9bVDnzZs3T/PmzWvwuI4dO+ree+8NMTo4RULGSJluw1Tx0hmSjq1xHWapcABAaLhJiRMJNDPfeCx1O7a9rdiS5a6bnIvXmfnhJlUjlVCVnJ1UrW+9ULuVHNKx2SvOfa4QmxISEjR48GANHjw4KtenX4/6BJo17Htf8/0dzOhs1KpF/L2/A0BTifX1kGM9PgBA49mSvL7vvvskSaNHj9Yzzzyjt956S2+99ZYSEhKUmpqqbt26KSmp4XcNY4xWrFhhR0iArWomql2pWSSuASBKuEmJEwk0M7+lvHo62bc9baFXR1V3lnC8zsyPRFKVhCoAAADQPMT6esixHh8AoPFsSV7n5eX5Z1hXfbUsSx6PRwUFBSooKGiwDcuyojpLG82DadNFCWdOlmnTJdqhNJoTYwYAwG5WWZEq189XwuljQ35PDDQz/+gRI/3bt33XlUYtW7nqnBfqyHw7Ykbzl5drlNE5vH7OugJLMxY3PABg6mijvmmhX2trcXUlCzRf33//fa3v09PToxQJAAAAAAB12bYwlWUFvslR3+NAUzBtush91u+iHUZQnBgzAAB2s8qKVLn2cbnSR4ScCA44M7+sOpHX6ySjVm3sGyxpR8zRFG5SNVIJVcnZSdVEd/gVIQalS52SLZUcqv+YlGRpUHp4JdoT3RKz5Ju/jIyMWoPPPR6Pf9+FF15oyzWoqgYAABA/Ai3hVXPpp63F1rG+Rm3xuoQXgIbZkrxeuXKlHc0AAAAA9vJWVm8X5svqdR7LfxwTblI1UglViaSqy2U0IcelmUvqlr2vMj7HFfbzjPgSaKD5qlWrwq6IRlU1AACA+BJoCa+a6luyKl6X8ALQMFuS1zk5OXY0AwAAANimcutS6T95/u/NOxN1NClV7uzpSsgYGb3AmgkSqpGV1cdoyiiX5q7yam+NWQ0pyb7nOasPzzPsQfU0AAAABCPQEl6NEeoSXgCaP9vKhgMAAACxonLrUnlW3Kw6o7tLC32PD3+SBLYNSKhGVlYfowE9jSbO8b2up442tsxsR3wZP358vfuoqgYAAIBgBVrCCwDCYUvy+oUXXpAktW3bVldeeWXQ5y9evFj79+9X165ddckll9gREgAAQExg7afgWJ4jsirKwmvDWynPR3mSLNV9Bi1JRp6P7pXpNiysEuKW50jI5zYnJFQjy/e8+p7rvmk8zwje3Llz691HVTUAAAAAQLTZkryeMGGCjDHq3bt3SMnrRx55RKtXr1b//v1JXgMAgGaFtZ+C41mSG4GrWFLZLlW8dEYErhUfSKjW1SHJ93vspFJ4TowZAAAAQPzYW2pp+VeWRgw0MTngP9bjA5zCtrLh4ayL5Xa7ZVmWtm/fblc4AAAAMYG1nxBrnJigdGLMHZOcNwDFiTHDXlRVAwAAQCzbVyotWmNpSGZsliqP9fgApwgqef3ee+/Vu88Yo8OHD5/wmON5vV5t3rxZq1evliR5PJ5gwgEAAIh5rP0UHPeohXKl9AurDe+ufHnevqHha108V67UrNCvs+fbCM0Ut5cTE5ROjBlwIqqqAQAAIF54vdUTMtcVWBqULqqIATEiqOT1+eefL2MC//JalqUdO3boggsuCCkQY4xOOeWUkM4FAACAvayyIlllRbUfq7HGs3fPtzLuVnXOM226yLTpEvJ1jbuVTIs2IZ8vSa60c6WkVKm0UIFKsktGSkqVK+3csNa8DvTzA4DTUVUNAAAAzV3+JktzV1V/7p2x2FKnZEsTclzK6kMCG4i2oMuGn6gjG04nV5JuvfXWsM4HAACAPSrXz1fl2sfr3V/fjOOEMyfLfdbvmiiqxjGuBLmzp8uz4mZZMjK1Eti+Tqg7e1pYiWsAcDKqqgEAACBe5W+yNHOJt87jJYekmUu8mjKKBDYQbUElr88777yAM6/fffddGWPUqlUrZWUFX3oxJSVFY8aM0XXXXRf0uYDdojXTDACAWJJw+li50kcEfV6svBcmZIyUhj+piv/kSYcLq3ckpcqdPc23HwDiFFXVAABApOwttbSvtPZj5Z7qAcZbiy0lBshSdEjyLR8EBFLusXSkIvjzvN7aM64DmfeuVwN6mpBKiNd8bQMIXVDJ61WrVgV83OVySZLS0tK0cuXKsIMCosnJM80AINbtLbW0/CtLIwYax3RCnRizHZrDoKyEjJGqOOkc6dVBkiTrwueU2Os8ZlwDgKiqBgAAImP5V5YWran/s0XeQkuBlnsaM9QoNzt++uAITn2vGzuUHJImzmm69gE0LOiy4fUJt3MLxAqnzzQDgFi2r1RatMbSkEyjjknRjqZxnBgzaqiZqO6aReIaAERVNQAAEDkjBhoNyQw+Cd2B/jcAxC1bktdVs61bt25tR3NAVDWHmWYAEE+83uoBdOsKLA1KV0ilnRBdpk0XJZw52VHvwU6MGQAkqqoBAIDI6ZjEQHDYLy/XKKNz8Pd+1hVYmrG44YmYU0cb9U0Lvv2txdaxWeGItEBLFDQGSxTEJluS1zk5OXY0AwAAEJT8TbXXKpqx2FKnZEsTclzK6sMHTycxbbo4bvkNJ8YMAA2hqhoAAABiXaLbqFWL4O/7DEqXOiVbKjlU/zEpydKg9NDWvPat387n6WhoaImC+rBEQWyyrWx4Y61evVqvvfaaNmzYoOTkZJ133nkaN26c2rZtG+lQAACAg+VvsjRzibfO4yWHpJlLvJoyigQ2AADBoKoaAAAAmjOXy2hCjivg/aQq43NcVPRzoEBLFJR7qmfC5+UaJbrr/r+yREFssjV5/eGHH+r111/Xl19+qUmTJunyyy+vtf+hhx7SPffcU2sk99///nfNmDFDr7/+us4880w7wwEAADGq3GPpSEXo53u9tWdcBzLvXa8G9AxtpGxN5Z74HDFLuSUAiD+Bqqpt375dbrdbqampdfb95z//UUJCgoYMGaKEhIRIhAgAAACEJauP0ZRRLs1d5dXeGvc9UpJ9iWsmQgRmlRXJKiuq/aDHUi/XsYEAe1zyBkgOR2qZ1kBLFPjuPfru62V0Dm22PqLDtuT17bffrlmzZvm/nzBhQq39a9as0d133x2wBNn333+vn/70p9qwYYPat29vV0iOUlhYqH79+gXcd8stt+iWW26JcEQAADQd36jHpk0KlxySJs5p+us0V5RbQnMSsJN95HD1dsm38pbVnWkaqU42fGbPnq3Zs2cH3FdYWBjhaOLbnj179NBDD+mVV17Rzp07NWvWLN166611jlu4cKGeeOIJtWnTRpdddpn+9Kc/KTMzMwoRxw769gAAALEvq4/RgJ7m2H0j3xrXoZYKjxeV6+ercu3jtR4zku5rc+ybJVKgeSoJZ05mybU4Yle/3pbk9b/+9S/NnDnT/70xdX/B77rrLlmWJWOMTjnlFN14443avn27nnvuOZWWlqq4uFhPPfWU/vCHP9gRkuN07dpV3377bbTDAAAAkES5JTQv9XWy/dvLrqGTHQNOlNjr0aOHCgoKIhxRfHr//fd15ZVXau/evf4+/IlYlqWysjL9/e9/15IlS/T6669r+PDhEYo29tC3BwAAcAZfotp3j6Nvmj2J6wOHrRpfYzMRvrfU0vKvLI0YaIKqnJdw+li50kfUeuzokcMyy66RJFmX/F0tWwUeFI74YVe/Puzktdfr1Z133inJl7Q++eST9fvf/17nn3++/5jdu3dr1apVMsYoOTlZ77//vjp37ixJuuKKK/wd28cff1xTpkxRy5Ytww0LAADEsLxco4zOoX+IX1dgacbihmcFTx1t1DctvM7C1uLqhG08odwSmpOAnWyPpekLfeXN7s11qWU95c2AeLJx40b99Kc/VVlZmT9p7XK5lJKSEvD4IUOGKCMjQ1u3bpUxRocOHdKVV16pTz/9VKecckokQwcAAGi2Ai3rVXOJs63FlhIDZHqa47JeHZJ8Fd8YOB+6faXSojWWhmTWve9zIgErk5XVeGF26idXG/5jYI+wk9fffvutvvnmGxlj1LFjR33yySfq0KFDrWP++c9/yuv1yhija665xp+4lqQLLrhA559/vlatWqWioiKtX79eZ5xxRrhhAQCAGJboDi/xOShd6pRsqeRQ/cekJMuWkk++DmD8Ja+B5iRgJ7vC0jbvsbW5UlxyMRgD0JQpU/yJ65YtW2rGjBmaMGGC2rVrF/D466+/Xtdff72WL1+u8ePHa9euXSotLdXUqVP1j3/8I8LRAwAANE8NLetV39JszXFZr45Jsf0ztWvtm83t+xoer7f6/3RdgaVB6aKsOeJG2Mnr7777zr/9i1/8ok7iWpJWrVrl3x41alSd/RdccIH/mG3btpG8BgAAJ+RyGU3IcWnmEm+9x4zPcfGhHgCARiouLtabb77pn3H95ptv6oILLmjUuSNGjNCqVavUv39/eTweLV68WEVFRerSheoFAAAA4Qq0rFdjMDvZufI3WZq7qjp5PWOxpU7JlibkuJTVh3tdaP7CTl5v3rzZv11fWbD333/fv33uuefW2d+tWzf/9tatW8MNCQAANEKgslONEStlp7L6GE0Z5dLcVV7trfFzpCT7Etd8mAcAoPHWr1/v3x41alSjE9dVTjnlFI0dO1YvvPCCJOm9997T1VdfbWuMAAAA8SjQsl5ovvI3WQEna5QckmYu8WrKKO55ofkLO3mdmJjo37asuqUpvv/+e23btk3GGJ1++ukB18qqqKgIuA0AAJpOQ2Wn6hNLZaey+hgN6Gk0cY7v55g62thSKhwAgHizYcMG/3Z2dnZIbdSsorZ9+/awYwIAAACcqNxj6UgIqS6vt/aM60DmvevVgJ6h3/uquV46EKvCTl736dPHv/3f//63zv633nrLv33RRRcFbGPHjh3+7Z49e4YbEgAAaIRAZafKPdaxtZKkvFyjRHfdD8KxVnbK92HdF3PfNBLXAACEoqSkxL8darlvt7v6FsORI0fCjgkAAABwovrWIbdDySEdm8RBEhrNl63J6/nz5+uhhx5S69atJflmYv/tb3/z77/iiisCtrFw4UL/dnp6erghAQCARghUdso3KtT34Tejs1GrFvYmgjsk+WZux1oC/EScGDMAAMGquZxXzeXBgvHJJ5/4t1nvGgAAAAAQirCT15mZmcrOztbq1au1Z88eXXbZZXrsscfUtWtXPfTQQ1q7dq0kqVOnTnXWu66oqNBvfvMbbdy40ReM263TTjst3JAAAA7n9LWYUb+OSbFTcryxnBgzAADB+tGPfuTffuWVV5SXl1drmbCGlJeXa9WqVf7vBw0aZGd4AAAAgGPk5RpldA7+XtK6AkszFjc8o3rqaKO+aaHdq9paXF11EYhVYSevJen+++/3lwRftWqVBg8eXGu/MUZ33HGHEhIS/I/ddNNNevXVV3Xo0CH/MaNHj1aHDh3sCAkA4GDNYS1mAAAAJ+nXr5/69eundevW6fvvv9fNN9+sZ555RsY07rPV5MmTtX37dhlj1KNHj1rJcAAAACCeJLpDq2Y4KF3qlGyp5FD9x6QkS4PSQ182L9EtUXIcsc6W5PXw4cP161//WnPmzJExRpble+FXdXIHDhyoKVOm1Dpn5cqVOnjwoP+YTp066dFHH7UjHACAwzWXtZgBALEhUEWPck91Z31rsXWsA18bFT0Qb2bMmKHLL79cxhjNmzdPX3zxhf73f/9XY8aMqTUYvaalS5fqgQce0EcffeR/LC8vL0IRAwAAAM2Hy2U0IcelmUu89R4zPscVcuIacApbkteS9OSTT2ro0KH685//rG+++UaS1KFDB40ZM0aPPvqo3O7Al7IsS9nZ2Xr22WfVs2dPu8IBADhYNNZiBgA0Xw1V9PANjqq7n4oeiDejRo3SbbfdplmzZskYo7Vr1+q6667TSSedpNNOO009e/ZU9+7dtW/fPm3btk0bN27UDz/8UKuNq666ShMmTIjODwAAAAA4XFYfoymjXJq7yqu9NQZhpyT7EtdZfeijovmzLXktSePHj9f48eN16NAhlZeXKyUlpd5jb7/9drlcLp199tkaMGCAnWEAAADAYfaWWlr+laURA41jZro6MeZ4FaiiR2NEu6IHM8YRDY8++qjat2+vBx54QB6PR8YYFRcXa/fu3fWeU1V9bcKECf6KbAAAAABCk9XHaEBPo4lzfJ+zp442YZUKB5zG1uR1leTkZCUnJ5/wmF/96ldNcWkAAAA40L5SadEaS0My61ZeiFVOjDleBaro4QTMGEe0TJs2TVdeeaUeeeQRLVy4UEePHvUnqAO54IILdMcdd2jkyJERjBIAAABovnyJat9n8L5pJK4RX5okeQ0AiF9OnInoxJgBNI7XK230DNU+q7Pa73BpUKZFhw+O4dQZ42geBg4cqBdffFFPPfWU1qxZo08++UTFxcXav3+/WrdurU6dOql///4655xzlJaWFu1wAQAAgKjrkOQbTBzLfTInxAiQvAYA2MqJMxGdGDOAhuVvsjR3VaL2HnnZ98ASqVOyVxNYIwoO4dQZ42hekpOTNXz4cA0fPjzaoaCZivWBpLEeHwAAiB0dk2K/CpYTYgRsTV5/8MEHevvtt7V27VqVlpY2fMJxjDFasWKFnSEBAJoJr7e6VOW6AkuD0hXXsyedehPNqXHDefI3WZq5xFvn8ZJD0swlXk0ZRQIbAIBYEOsDSWM9PgAAADjD3lJL+4JPnapDkuLuPqotyWuPx6OpU6fqscceC7kNy7JkTHw9+QCAxvHNnqxOXs9YbKlTshXXsyedehPNqXEjcso9lo5UhNeG11vzb0bgvxHz3vVqQM/w1owq99S//isAAIg8BrwCAAAgVi3/ytKiNcHfSxozNP5my9uSvJ49e7ZmzZolyTd72rK4kQcAsAezJyOLG36ItryFlqSm/yxZckiaOCcy1wIAp5g4caIt7Rhj9Oyzz9rSFtBYDHgFAABALBsx0GhIZu3PpeUe69i9MCkv1yjRXfdzazyuTx528vrgwYO6//77/bOmjTG66aablJOTo9TUVGZTA0Ccsn/2ZGDMnrQPN/wAAIhv8+bNs60PT/IakcSAVwAAAMS6jkl1K1H67p/77sdmdDZq1YLPrJINyevPP/9cJSUlknyJ6zfffFMXX3xx2IEBAJyN2ZPOwg0/xIq8XKOMzuG91tYVWJqxuOG/CVNHG/VNC/1aW4urR8cCQHMRbCW1qmR3zfMYxI5QhDr4takHvDLQFQAAAIissJPXGzdulOTrnF5xxRUkrgEAiCAnzXCXuPmHhiW6wx9lOihd6pRsqeRQ/cekJEuD0sN7TSe6JQbOAGhO5s6d26jjysvLtWXLFm3evFnvvPOOSkpKZIzRlClTNHXqVJLXCElTDn5lwCsAAADgHGEnr6tmXUtSdnZ2uM0BAGy0t9TSvtLgz+uQ5CtjEg5mT0ZGvM1wD/SarpkQ31psHUso1mbHaxrO4XIZTchxHasmYEmq+38/PsfFeu4AcJzx48cHfc7Bgwc1a9YsPfTQQ5o5c6YOHDigv/71r00QHQAAAAAgHoSdvO7Zs6d/u0WLFuE2BwCw0fKvLC1aE3yyccxQo9zs8JI6zJ5EU2joNV1fMt+O1zScJauP0ZRRLs1dVam9NQY8pCT7EteUwQcAe7Rt21bTpk1Tenq6Jk6cqGeeeUZnnXWWfvWrX0U7NDhMqINfm3rAq5MHugIAAABOFHbyOjs7218SbM2aNWEHBACxKpqzmEM1YqDRkMza1y73VN98ycs1SnTXja1DUkTCa1Dt2ZOBxfvsSSfNcJfCv/kX6DXdGLHymkZkZfUxGpBaro0v36h9Vme1H/GIBmW2iuu/GQDQVCZMmKDFixdr8eLFmj59um688Ua53WHfckAcCXXwa1MPeGWgKwAAABBZYfckMzIy9LOf/UyLFy/W22+/re3bt6tHjx52xAYAMSUas5j3llpa/pWlEQNNSAnwjklGHY9L2vnWR/b9HBmdw58dfbwDh60aX8Nvu3r2pJfZkwE4aYa7FP7Nv0CvadQV7t+OaLD7b0cVl0vq6/YNsLS6P0ziGgCa0IUXXqjFixeruLhYK1eu1EUXXRTtkBAHGPAKAAAANC+2DIN++umn9eWXX2rLli26+uqrtXLlSrVu3dqOpgHANuEmc6Ixi/n73b6E+andnLNe78HDtb/aIauP0YCe5tiay74ZwHYkUuHDDb/mZ1+ptGiNpSGZJPubUock3wAlZvYDgE+/fv3825s3byZ5jYhhwCsAAADQfLjsaOSkk07SihUrNHToUOXn5yszM1NPPvmkDhw4YEfzAGCLqmROKKW/JV/y+OQutf/VLNec0bnu/pO7hDfrsSkSwV5v9azXdQVWre9jWc3Ead80Etd2q7rhd3yiMyVZmjKKG37wacq/H+1am1pfnaBjklFutssxg4sAoKn98MMP/m3uByDSsvoYPfqL6vfkqaON/nIDn2MBAAAAp7Fl5vWdd94pSRo2bJg2bNigwsJCTZo0SZMmTdJJJ52kzMzMRs3ENsZoxYoVdoQEABFxfCJnULpiOqmav8nS3FXVMc9YbKlTsqUJNs5GaNu69lcnYPakDzPccSKR+PsBAHC2V1991b998sknRzESxCvf51bf5xUGvAIAAADOZEvy+uGHH5Yx1R2Cqm3LslRcXKzdu3c32IZlWbXaAIBY57RETv4mK2BZ6JJD0swlXttm1/pmTVoOnD3pnHibEjf8EEik/n4AAJypsrJS999/v5YtW+Z/7LTTTotiRHCSWB9IGuvxAQAAAM2NLclryZd8DmUfADhRpBM5RystHakI/W+p11s70R7IvHe9GtAz/GRluYe/+ZHg1JtoTo3bqco9lo5UhNdGpP5+8LcDAKJv4sSJQZ+zZ88effbZZ9qxY4ck32D2oUOH6owzzrA7PDRTsT6QNNbjAwAAAJobW5LXK1eutKOZuFZYWKh+/foF3HfLLbfolltuiXBEQPMVbjInkongo5W+6/xtufS35XWT5XYqOaRj5aJJIIVib2lo66l3SFJI6+U69SaaU+N2qryFkfmd5u8HADvMnj1bs2fPDrivsLAwwtHEp3nz5oVUEa1mJTW3262ZM2faHZpj0LcHAAAAEK/s6tfbkrzOycmxo5m41rVrV3377bfRDgOIC5FI5pDICU+gRHDNWZlbiy0lBngHCzURbIflX1latCb4/+8xQ0nmAgAgnTix16NHDxUUFEQ4ovgUauU0y7KUmZmpBQsW6Mc//rHNUTkHfXsAAAAA8cqufr1tZcMBAE3nphHSOae6Qj5/XYGlGYsbvhE5dbRR37TwEqlbi61jAwRC11AiuL4BCNFMBI8YaDQks/a1yz3Vz0VerlGiu25slM9GU8rLNcroHN7vRKT+ftjxtwMAEJ65c+eGdF5SUpIGDx6s3r17hzRzG2iOIl2ZCQAAAGguSF4DiDvhJnMimQj+z0av/rZcaplg1KpF6G0NSpc6JVsqOVT/MSnJ0qD08Eud+2ZEh5eACpQIboxoJoI7Jhl1PO76vvL0vucio3N4/4dAKBLd4b/uIvX3w46/HQCA8IwfPz7aIQDNBpWZAAAAgNA0WfJ69+7dys/P1xdffKGSkhLt379fSUlJ6tSpkwYMGKCzzz5bqampTXV5AKhXuMmcSCaCWyYY2ZHMcbmMJuS4NHNJ/etmj89xhR2vXQIlggFEh9P+fgAAAMQCKjMBAAAAobE9eb18+XLNnDlTy5Yta/DY4cOH64477tBFF11kdxgA0GScmsjJ6mM0ZZRLc1d5tbdG+bqUZF+8WX1iK14AsYO/HwDQ/L344ouaNWuWJOmPf/yjcnNzoxwR4GxUZgIAAABCE/oCqsepqKjQjTfeqEsuuUTLli2TZVkN/luxYoVGjhypm266SRUVFXaFAgBNriqRc/zNiJRkacqo2E3kZPUxevQX1bFNHW30lxtiN14AsYO/HwDQvO3cuVOff/65vvjiC3388cfRDgcAAAAAEKdsmXltWZauv/56LVq0SJZVXd42JSVFp556qnr16qXu3buruLhY3333nTZu3Kji4mL/uc8++6xKS0v18ssv2xEOAEREVh+jAT2NJs7x/d2bOtrYUiq8qfni88XcNy324wUQO/j7AUnaW2ppX2ntx8o91X2ArcXWsTXMa+uQ5JuFBiA2nXrqqf7tTZs2RTESAAAAAEA8syV5/dJLL+m1116TMb6bUf369dPUqVN13XXXye2ue4nKykotWLBADz74oNavXy/LsvTKK6/osssu03XXXWdHSABiXKAb340Raze+mzqR07Z17a9O0CFJGjPUsFYbEEVO/D20I2arrEhWWVHtB48crt4u+Vbesrp/UE2bLjJtuoR+4Tiz/CtLi9ZY9e73reVZd/+YoUa52bHzHg6gtksvvVQ9e/bU9u3b9cEHH6isrExt2rSJdlgAAAAAgDhjS/I6Ly/Pvz1mzBgtWLAgYNK6SkJCgsaNG6drr71W11xzjRYvXizLsjRt2jSS14AD7C21tPwrSyMGmpATyQ3d+K5PODe+jbHUN833VQq+jWjMNEs/yWjMUN9Xp+iYRHICiDYn/h7aEXPl+vmqXPt4rcdqtmiWXaNAC9UknDlZ7rN+F9a148mIgUZDMoP/v3LSYAogHrVs2VLz58/XRRddpD179uiOO+7Q7Nmzox0WAAAAACDOhJ28/uabb7RlyxYZY9SlSxc999xzJ0xc19SiRQs9//zz6tOnj3bv3q3vvvtO33zzjfr37x9uWACa0L5SadEaS0MyTZ01nxsr0I3vco91bLaWlJdrlOiue2M8rBl5ltG6AkuW1TQJ96aYaebEBJQT2TEgI9LsiJnSv2huEk4fK1f6iFqPHfVYmr7QK0m6N9ellgHeW5h1HZyOSaG//wOIbcOGDdObb76pa6+9VnPmzNG2bdt01113KTs7219pDQAAAACAphR28vrTTz/1b19zzTVq27ZtUOe3a9dOF1xwgRYuXChJ+uSTT0heA3Eg0I3vsvLqpNnho9KpqYqp9VSdONOM5GTj2DEgI9LsiJnSv2huApb/rrC0zetLXivFJVcLXrsAUJ/77rtPkjR69Gg988wzeuutt/TWW28pISFBqamp6tatm5KSGv7gYYzRihUrmjpcAAAAAEAzFHbyuqioel3BUJPOWVlZ/uR1zfYAxI/8TZbmrqpOks1YbKlTsqUJOS5l9YmNRIMTZ5qRnIwur7f6uV1XYGlQOgMyAABA7MrLy/PPsK76almWPB6PCgoKVFBQ0GAblmUxSxsAAAAAELKwk9c1O6UejyekNo4ePerfTkhICDckAA6Tv8nSzCXeOo+XHJJmLvFqyqjYSWA7DcnJ6GFABgAAcCLLCjzwsb7HgebOCUsMOSFGAAAAoLHCTl6npqb6t9euXRtSGx9//LF/u0sX1hwEnKLcY+lIRXhteL21E3yBzHvXqwE9TdgzVmuWy44XJCejgwEZAADAiVauXBntEICY44QlhpwQIwAAiA2xPugt1uNDZISdvM7OzpbkG4W9cOFCPfDAA+ratWujzy8uLtY777xTpz0Asa++ktN2KzkkTZwTmWshvjlpQEY8DsYAAABNKycnJ9ohAM1arC8rBAAAmr9YH/QW6/EhMsJOXvfu3VsDBw7U119/rYMHDyo3N1dLlixR27ZtGzz30KFDys3N1YEDB2SM0YABA9SnT59wQwIAICQMyAAAAADQFJywrBAAAEAwvF5po2eo9lmd1X6HS4MyLQbmwRZhJ68l6cEHH9Tll18uY4w+/PBD9e7dW7fddptuvvlmtW/fvs7xBw8e1OzZszVr1izt3r3b//if/vQnO8IBECF5uUYZncN7M1pXYGnG4oYTeFNHG/VNC+9aW4utY8lJAAAAAMd74YUXJElt27bVlVdeGfT5ixcv1v79+9W1a1ddcskldocHOBbLCgEAgObGNzAvUXuPvOx7YInUKdnLwDzYwpbk9ahRozR58mQ9/vjjMsZo9+7duvvuu3XPPfcoLS1NGRkZ6tq1qwoLC7Vt2zYVFBTI6/XKsiwZ43sRT5o0SZdddpkd4QCIkES3UasW4b0RDUqXOiVbKjlU/zEpydKg9PDXvE50S8x0xYk4aUAGgzEAAIDdJkyYIGOMevfuHVLy+pFHHtHq1avVv39/ktdodkJdYigSywqxpBAAAIgkBuahqdmSvJakmTNnqlOnTrr//vvl8XgkSV6v9/9n787jo6ru/4+/78ywJREISwiEJSgIsimWAoqACFoUURFpFbVAt68VWyyiaFUIblS/dUG/oD+tghsqiEotliIoopVFISoSlgKNQCAJS9gyJmRm7u+PwCVDJstMZp/X8/HIw3PvPefcTzCEOfdzzznavXu39uzZY9UzzfIP1KeS1jabTQ888ICmTZsWrFAAxBCbzdD4wTaf/9idMm6wjeVGEBax9EIGL2MAAIBQODVmD4TD4ZBpml7PAIB4EcoththWCAAAhFtwXszz/WyzLi/m8VIepCAmrw3D0IMPPqjrr79ezzzzjN5++20VFxdL8j34TUpK0i9+8QtNmjRJPXv2DFYYAGJQ306GJo+wae5Kj4qKT59vnlKeuOYtLcQSXsgAAADRbtWqVVVeMwxDP/74Y7V1zuTxeLRjxw6tWbNGkqwX2gEAAABEJ17MQzQLWvL6lO7du+ull17SCy+8oI0bN+q7775TUVGRjh8/rpSUFKWmpqpnz57q2bOnHI6g3x5AjOrbyVCPdsbJf9TKl1QOxlLhQCTwQgYAAIhml156qbUa2plM09TevXs1ZMiQgPo2DEOdO3euS3hAVAp0i6FwbCvElkIAAFSvqNjU4WLvcxVn+ObuN0+ucuitabKUmsxzPCDcQpY9ttvtuuCCC3TBBReE6hYAYpjvDwyny43qSz8ckM58O4sPDIgVvJABAACiWXXLg9dl6XBJ+uMf/1in9kA0CnSLoXBsK8SWQgAAVG/5RlOL1lb9b2VVs5BH9zM0pn98PsuL1hfzeCkPUgiT13v27JHD4VB6enqla19++aXsdrv69Okju90eqhAAhEjT5PJ/uJsmB95HJD4wBCNuwB/lD5/Kf47PyyBxDQAAosOgQYN8zrz+7LPPZBiGGjZsqL59+/rdb/PmzTV69GjddNNNwQgTiAtsKwQAQOQN62moz9n+/1sbz8+Ro/XFPF7KgxTk5PXBgwc1c+ZMvf3229q3b5+efvppn29cL1y4UM8++6ySkpJ09dVX69FHH9XZZ58dzFAAhFBqct3fOIvEB4ZgxI34FIsvNsRizAAAIDqsXLnS53mbzSZJysjI0KeffhrGiID4xrZCAABEVmqyoVSeoQWF94t5pqTKn2N4MQ91FbTk9eeff65Ro0apqKhIpmlWuX/WKaZpyul0asGCBVqyZInef/99DR06NFjhAIhyfGBANInFFxtiMWYAABD96rpkOADf2FYIAADEi9Mv5rl5MQ8hEZTk9bZt23TllVfK6XRaSWubzabmzZv7rN+nTx9lZmYqNzdXhmHo+PHjGjVqlNavX6/OnTsHIyQAAAAAAOCHU7OtGzVqFOFIgPjEtkIAACBe9O1kqEd6qba9+WsdNluqybAndP7ZDfl8g6CwBaOTyZMnW4nr+vXr65lnntHBgwd18803+6x/8803a+fOnVq2bJnS09NlGIaKi4s1derUYIQDAAAAAAD8NHjwYA0ePDig/a6BeBUL2/XEQowAACD+2GzSeY61uqjeP3ReGw+JawRNnWde79+/Xx999JE14/qjjz7SkCFDatV22LBhWrlypbp37y6Xy6XFixersLBQaWlpdQ0LAAAAAACEyJo1a/Tuu+9q69atSklJ0aBBg3TLLbforLPOinRoQFDFwnY9sRAjAACIDtH+0lu0x4fwqPPM6y1btljlESNG1DpxfUrnzp01duxY63jVqlV1DQkAAAAAAATo3//+t6ZMmaIrrrhCH374YaXrM2fO1CWXXKKnn35aH330kRYsWKA77rhDPXv2VHZ2dgQiBgAAAFAb5S+92ZSaHJ0vvkV7fAiPOs+83rp1q1Xu379/QH306tXLKu/Zs6euIQEAACABFRWbOlzsfa7UZVrl3P2mGvj49Ns0WQyKAOCkKVOm6Omnn7aOx48f73V97dq1euCBB2Saps60a9cuXXnlldq6dauaNGkS6lABAAAAAHGozsnrQ4cOWeVAl/t2OE6HUVJSUteQAAAAkICWbzS1aG3lZMopWQtNSZWvj+7HUpsAIEkffvihnnrqKev41PZgFd1///0yTVOGYahz58769a9/rT179uiVV15RcXGx9u/fr+eff1733ntvOEMHAAAAAMSJOievW7dubZV37NgRUB9ff/21VU7U/a4LCgrUrVs3n9cmTpyoiRMnhjkiAACA2DKsp6E+Z/ufhGYfJSA6zJ49W7Nnz/Z5raCgIMzRJB6Px6M///nPksqT1h07dtRdd92lSy+91Kpz4MABrVy5UoZhKCUlRZ9//rlatmwpSbruuus0dOhQSdKsWbM0efJk1a9fP+zfR6QxtgcAAACQqII1rq9z8vonP/mJVX777beVlZWlBg0a1Lp9aWmpVq5caR2ff/75dQ0pJrVq1Uo5OTmRDgMAECCWKwYiLzXZUCqJaCBmVZfYa9u2rfLy8sIcUWLJycnRpk2bZBiGUlNT9fXXX6tp06Zedf7+97/L4/HIMAz9/Oc/txLXkjRkyBBdeumlWrlypQoLC7VlyxavLcISBWN7AAAAAIkqWOP6Oievu3Xrpm7dumnz5s3atWuXbr/9dv3tb3/zubyYL5MmTdKePXtkGIbatm3rlQwHACBWsFwxAACIZTt37rTKt956a6XEtSSvF89HjBhR6fqQIUOsOj/88ENCJq8BAAAAAHVT5+S1JD3++OMaOXKkDMPQvHnz9O233+qee+7R6NGjZbfbfbZZunSpHnnkEa1evdo6l5WVFYxwAAAIO5YrBgAAsaziNmCdO3f2Wefzzz+3ygMHDqx0veK2Yrm5ucELDgAAAACQMIKSvB4xYoT+9Kc/6emnn5ZhGMrOztZNN92kFi1aqEuXLmrXrp3atGmjw4cP64cfftC2bdu0e/durz6uv/56jR8/PhjhAAAQdixXDAAAYlnF7b9Ms/JqMbt27dIPP/wgwzDUtWtXNW/evFKdsrIyn2UgEbGtEAAAABCYoCSvJenJJ59UkyZN9Mgjj8jlcskwDO3fv18HDhyoss2pAfH48eP1wgsv1HqpcQAAAIQWD1wBILF06tTJKv/nP/+pdP2f//ynVb788st99rF3716r3K5duyBGB8QethUCAAAAAhO05LUkTZs2TaNGjdITTzyhhQsX6sSJEz7f2D5lyJAhuvvuuzV8+PBghgEAAIA64oErACSWisnr+fPna+bMmWrUqJGk8hfPX3zxRev6dddd57OPhQsXWuX27duHJlAgRrCtEAAAABCYoCavJalnz556/fXX9fzzz2vt2rX6+uuvtX//fh05ckSNGjVSs2bN1L17d1188cXKyMgI9u0BAAAQBDxwBYDEcvbZZ6t///5as2aNDh48qKuvvlrPPPOMWrVqpZkzZyo7O1uS1KxZs0r7XZeVlen3v/+9tm3bJklyOBzq0qVL2L8HIJqwrRAAAAAQmKAnr09JSUnR0KFDNXTo0FDdAgAAACHCA1cASDwPP/ywtST4ypUrdcEFF3hdNwxDd999t+x2u3Xud7/7nd555x0dP37cqnPttdeqadOm4QobCYotTgAAAID4FLLkNQAAAAAAiB1Dhw7VbbfdphdeeEGGYVjbgBlGeaKvZ8+emjx5slebTz/9VMeOHbPqNGvWTE8++WR4A0dCYosTAAAAID6FJHntcrm0fv16ffHFF9q3b5+OHTumY8eOaf78+ZLK98vKy8tT27ZtQ3F7AAAAAAAQgDlz5qhfv37661//qk2bNkmSmjZtqtGjR+vJJ5+Uw+H7MYJpmurfv79efvlltWvXLpwhI0GxxQkAAAAQn4KavPZ4PHruuec0ffp0HTt2zDpvmqYMw7CS1x6PRx06dNBll12mCRMmaOzYscEMA4gpRcWmlm80NaynEfDSZb6WS6uNQJdLC0bMAAAAAKLTuHHjNG7cOB0/flylpaVq3rx5lXWnTJkim82miy66SD169AhjlEh0bHECAAAAxKegJa+PHj2qyy+/XF9//bW1tFh1TNPUJ598ok8++USvvfaa3n33XaWkpAQrHCBmHC6WFq011efswAfeNS2XVpVAl0sLRswAAAAAoltKSkqN4/T/+Z//CVM0AAAAABBZsTCxLxZirElQktcul0s33HCDvvrqK+tchw4dNGDAAH300Uc6fPiwV33DMNSsWTMdOnRIkvTxxx9r1KhR+vjjj4MRDpBwfC2X9mOZRw+9W14eN1g6N92QzeZdh+XSAAAAAAAAAAAAahYLE/tiIcaa2ILRyYsvvqjly5fLMAw5HA49/PDD2rFjh9544w2fy4vZbDbt2rVLjz32mGw2mzUL+/333w9GOEDCSU021DHt9Nf+o9Jz/zx9/dXPpCeXmNp/VF71YvWtGwAAAAAAAAAAgFjm8ZxeUXdznul1nMjqPPPaNE09++yz1vHDDz+sqVOn1tguKSlJ9957r1q3bq0JEyZIku69915de+21stmCklMHEtK67aaeWuKpdP7QcempJR5NHmFT304krQEAAAD49sUXX2jZsmXKzs5WcXGx3+0Nw9CKFStCEBkAAAAAxId1203NXXk6Wf34YlPNUkyNH0wOp87J6+zsbG3btk2GYahTp0666667/Go/btw4Pffcc9qwYYO2b9+unTt3qlOnTnUNC4g5pS5TJWV168Pj8f5l58u8zzzq0a7yEuL+KHXx9g8AAAAQb1wul6ZOnapnnnkm4D5M05RhJPaDFgAAAACoDpMQq1fn5PWOHTus8tChQ+Vw+N/l1VdfrQ0bNkiStmzZQvIaCSlroSkp9EnhQ8elX70QnnsBAAAAiB2zZ8/W008/Lal89rRpMmYAAAAAgDPVZTJiqCchxsPkwzonr3Nzc61yz549A+ojIyPDKm/btq2uIQEAAAAAAD8cO3ZMDz/8sDVr2jAM/e53v9PgwYOVnp7ObGoAAAAAOCnUkxETfRJinZPXSUlJVrmoqCigPvLy8qyy3W6va0hATMoaYyizZd0eCG3OM/X44pp/mU291tB5GYHfK3e/efKXMwAAAIB48M033+jQoUOSyhPXH330ka644ooIRwUAAAAASDR1Tl63bdvWKn///fcB9fHtt99a5TZt2tQ1JCAmNXAYalivbsnr89tLzVJMHTpedZ3mKdL57eu253UDh5Sob/wAAAAA8ejUKmiGYei6664jcQ0AAAAAVajLZMRQT0KMh8mHdU5eX3rppXI4HHK5XFq8eLF27dql9u3b17r9hg0btGTJEut40KBBdQ0JSFg2m6Hxg216aomnyjrjBtvqlLgGAAAAEH9OzbqWpP79+0cwEgAAAACIbnWZjBjqSYjxMPnQVtcOmjRpolGjRkmSSkpK9Pvf/14lJSW1apufn69bbrlFLpdLhmFoyJAhatWqVV1DqqSoqEjr16/XypUrtW3bNnk8VSf2ArVnzx59+eWXWr9+vZxOZ9D7B2qrbydDk0fYlJrsfb55ijR5hE19O5G4BgAAAOCtXbt2VrlevXoRjMQ3xvUAAAAA4sGpSYjVSfRJiHVOXkvSE088oUaNGkmSli5dqn79+unTTz9VWVmZz/q7d+/Wo48+qnPPPVdbt26VVL402eOPPx6McCzbtm3TyJEj1bJlS/Xp00dDhgxRly5dlJmZqSeffFJut7tO/ZumqTfeeEO9e/dWu3btNGDAAPXp00cpKSkaOnRowMuoA/4qKjb138LTXy0bS3+48vT1cYOlySMMtWwsr3pFxbH99g0AAACA4Ojfv78Mo/zhyNq1ayMczWmM6wEAAADEGyYhVq/Oy4ZLUocOHbRo0SJde+21crlc+v777zVs2DA1atRILpfLqtejRw/t3LlTpaWlksoHiac899xz+slPfhKMcCRJn3/+uYYPH+7zbendu3drypQpWrVqld577z3Z7Xa/+/d4PJowYYJee+21StdM09Qnn3yiCy64QIsXL9aIESMC+h6A2lq+0dSitVUnol/9TCpfJsK7zuh+hsb0T+xfggAAAACkzMxMXXPNNVq8eLGWLVumPXv2qG3bthGNiXE9AAAAgHjVt5OhHu0M/eqF8rzN1GuNgJcKjzdBmXktScOHD9enn36qjh07yjRNmaYpp9OpsrIy6+3tzZs3q6SkxLouSU2bNtXbb7+t3//+98EKRQcOHNCoUaPkdDpls9n00EMPaffu3Tp+/Lg++eQT9e7dW5L097//XQ899FBA98jKyrIGuAMGDNCnn36qY8eOKTc3V4899pgaNGggt9utX/7yl9qzZ0/QvjfEn6bJ5Unkpsk1163KsJ6GZt5k8/trWM/AfgkGI2YAAAAA0eWll15Sx44dVVRUpBtuuEE//vhjxGJhXA8AAAAg3lVMVJ+XQeL6lKAlryXp4osv1vfff6+XX35ZF198sRwOh5WorpiwlqQuXbro0Ucf1X/+8x/9/Oc/D2YYeuKJJ3Tw4EFJ0rPPPqsHH3xQbdu2VXJysoYMGaKVK1cqMzNTkvTkk09q//79fvW/c+dOzZw5U5I0aNAgffLJJ7r00kuVkpKiDh066L777tPs2bMlSYcOHdLzzz8fvG8OcSc12dCY/jalJgf+Syk12VDHNP+/Ar1nMGIGAAAAEF1atGihFStWqF+/flq3bp3OPvtszZkzR0ePHg17LIzrAQAAAESbWJjYFwsx1sQwK2aUg+zHH3/Ud999p/379+vIkSNKSkpSs2bN1KNHDzVv3jwk93S73WrVqpUOHjyotLQ07d271+fyYbNnz9Ydd9whqXzJ8lPl2pg4caLmzJkjScrOztYFF1xQqY7H41GHDh20Z88e9ejRQxs3bvTZV9u2bZWXl6eMjIyEeJPbLHPqxGvdJUn1f7lJRr2kCEcEAAAAINol2rgpUv785z9Lkk6cOKFXXnlFhw8ftlZSa9Gihc4++2w1atSoxn4Mw9CKFSsCjiPWxvUSP6MAAAAIrpIyU+PneCRJ8263qWG96JtIVuIslvFWD0mSedP3apgUXdnSmPgzjIEYg8WfMVNQ9ryuSqNGjdSvX79Q3qKSNWvWWG9njxw5ssp9r6655hprYLtkyZJaD3I9Ho/ef/99SVL37t11/vnn+6xns9m0fPlyFRUVSSrfL+vUoB8AAAAAgGjzl7/8xWvceqpsmqb279+vAwcO1NhHMMa+jOsBAAAAIHGFNHkdCVu3brXKV111VZX12rVrp169eum7777Thg0bat1/Tk6O9u3bJ0n6xS9+Ue3AtUuXLrXuFwAAAACASKtucbYQLtzmhXE9AAAAACSuqEleHz16VE899ZSysrLq1M+pAagkdejQodq67dq103fffafCwkIdPnxYTZs2rbH/TZs2WeVOnTpZ5by8POXm5iopKUnnnXeeGjZs6H/wAAAAAABEyKeffhrpECQxrgcAAACARBZQ8jo/P1+fffaZ9u7dK9M01a5dO/Xr10/t27f3u6/i4mJ9+eWXuu+++5SdnV3n5HV+fr5VbtasWbV1K+67vW/fvloNciu+AZ6WlqZPP/1U99xzj77++mvrvN1u1/nnn6///d//1WWXXVaruE3T1NGjR2tV15cGDRqoQYMGAbcHAAAAgFApLS1VaWlpwO3DNeM30Q0ePDjSIUiK3XG9xNgeAAAAQHwK57jer+T17t27deedd+qDDz6odM1ms+m6667TCy+84DV4PHTokN5//30tX75ceXl5Onr0qI4dO6aSkhKVlJTo8OHDVtDB2Duq4hvaFePwpeL14uLiWvV/5MgRq/zRRx/pqaeeqlTH7XZrw4YNGjp0qG677TbNnj1bNput2n737t2rJk2a1CoGX6ZPn17nxD8AAAAAhMLMmTM1Y8aMSIeBGBGr43qJsT0AAAD8V1Rs6vAZH2VLXacTfbn7TTXwkc1rmiylJtc9rwbURjjH9bVOXm/dulVDhgxRQUGBlR2vmGx2u9167733tGnTJi1fvlxt2rTR2rVrdcMNN2jv3r2V+quYYQ9G0vqUim84N2rUqNq6Fd9m/vHHH2vV/7Fjx6zyU089JYfDocmTJ+sXv/iFzj33XOXl5elf//qXHnjgAR07dkwvvPCCzjnnHE2ZMqXaftu0aaPNmzfXKgZfeDMbAAAAQLS67777NHny5IDbn3feeT7HlYhPsTqulxjbAwAAwH/LN5patLbqWalZC01Jla+P7mdoTH+S1wiPcI7ra5W89ng8uvnmm5Wfny/DMGQYhkzTrDTF2zRNbd26Vbfddpvmz5+vUaNGWW2qmw5umqZSU1M1aNCgWgVdnZYtW1rlw4cPex2f6dSsb6nmAfEpDof3H9mSJUt0xRVXWMddunRRly5dNGTIEPXu3Vtut1uPPPKIfv/73ys5ObnKfg3DUOPGjWsVAwAAAADEkrouhRzMF57hnwMHDmjdunX69ttvdejQIR05ckTJyclq1qyZevTooYsuukjp6elBvWesjuslxvYAAADw37Cehvqc7f+Yp2n1H02BoArnuL5WyeulS5dqw4YNVhK6Y8eOevTRR9WnTx9lZGRoz5492rBhg+6//37t3LlTS5Ys0eWXX+6VuB41apQGDBigDh06WHtQ2e12paamqkWLFmrTpk1QHki0bt3aKh86dKjaQe6hQ4esckpKSq36b9OmjVW+8cYbvQa4FfXs2VO/+tWv9NJLL+nIkSNauXKlRowYUat7AAAAAAAQScuXL9dTTz2lf/3rXzXWHTp0qO6++25dfvnlQbk343oAAAAkktRkQ6kkogFLrZLXCxYssMrnnnuusrOzvd5o7ty5szp37qyRI0eqb9++ysnJ0bp16yRJSUlJ+uSTT/TTn/40yKH7VvGN74qDWF+KioqsckZGRq36rziIrmmmeL9+/fTSSy9JkrZt28YgFwAAAAAQ1crKynTbbbdp3rx5klTtKmqnrFixQitWrNCvf/1rzZ49W/Xq1atTDIzrAQAAgNAwnYVyb5kve9exMpLSIh1OJdEeH8LDVptKX331lVV+7LHHqlyKKykpSQ8//LCk8gGuYRiaMWNG2BLXkvcg9Ntvv62ynsfj0caNGyVJ7du311lnnVWr/iu+od2sWbNq66alnf6LdeLEiVr1DwAAAABAJJimqZtvvlnz5s3z2iqsefPmuuiii3TjjTdq8uTJuvXWWzVgwACvGdGmaerll1/W+PHj6xwH43oAAAAgNExnodzZs2Q6CyMdik/RHh/Co1bJ63379lnlIUOGVFt32LBhXsc/+9nPAggrcH369LHKH374YZX11q9fr/z8fEnSxRdfXOv+O3fubJU3bdpUbd0tW7ZY5dq+AQ4AAAAAQCS88cYbevfdd63jbt266dVXX9W+ffv073//W/Pnz9df//pXvfrqq/r888+1d+9evfbaa+rSpYuk8gT222+/rbfeeqtOcTCuBwAAAGKAx326XLBOZsVjoA5qlbw+cuSIJOmss85SampqtXXPOussa09ryXtQGA5dunSxBs4rVqzwWkKsovfee88qjxo1qtb9d+rUSeedd54k6c0335TT6fRZz+1265133rGOL7300lrfAwAAAACAcMvKyrLKo0eP1jfffKNbb71VDofvHcfsdrtuueUWffvtt7r22msllSewp02bVqc4GNcDAAAA0c2du1T6+xXWsfHJr3RiwSXl54E6qlXy+tQS4BWXBKtOxWW36tevH1hkdTB58mRJUmlpqf7whz/I4/F4Xc/OztYzzzwjSerYsaOuu+46v/q/4447JEk7d+7U7bffrpKSEq/rbrdbDzzwgNavXy+pfBDdtm3bAL4TAAAAAABCb9OmTfrvf/8rwzCUlpamV155pcqk9Znq1aunV199VS1atJBUPlauaUZzTRjXAwAAANHJnbtUrhW3Sz8WeF8oLpBrxe0ksFFntUpen2IYRlDrhcqECRPUt29fSeVvUQ8ZMkRz587VokWLNHXqVA0aNEglJSUyDEOzZs2qlGAfP368DMOQYRheb56f8tvf/lY/+clPJEmvvvqqLrzwQj3yyCN699139de//lUDBgzQX/7yF0nl+2M9/fTTof2GAQAAAACog1NJWkn6+c9/Xuv9o09p3Lix1zZjX3/9dZ3iYVwPAAAAhI7pKpFZ5vT7y1N6TK7VWZJMVc4EmpIk1+oZ8pQeC6h/01VSqVckntq9Rh1j6tWrp8WLF+uqq65Sdna2Vq1apVWrVlWq8+yzz2rkyJEB9b9kyRJdddVV2rBhgzZv3qwHH3ywUr3OnTvr/fffV4cOHQL+XgAAAAAACLXCwkKr3L1794D66Nu3rxYuXFipv0AwrgcAAABCx7VkTIh6NiVnvsre6BWi/pEI/Jp5HUvS09O1Zs0aPffcc7rooovUrFkz1a9fX5mZmfrNb36j9evX67bbbgu4/1atWmnt2rV68cUXddlllyktLU0Oh0MtWrTQZZddpueff14bN24MeNAPAAAAAEC4VFxBzeVyBdTHiRMnrLLdbq9zTIzrAQAAACDxxOXM61Pq16+vO+64w9rLqrbmzZunefPm1VjP4XDot7/9rX77298GGCEAAAAAAJGXnp5ulbOzswPq46uvvrLKaWlpdY5JYlwPAAAAhIJjxELZmnfzu50nf51cyybU3P8Vc2VL7+t//wdzQjgrHLEibmdeAwAAAACA2unfv78kyTRNLVy4UAUFBX61379/vz755JNK/QEAAACIPoajoYx6SX5/2TIGSsnpko8dr0/2LCW3li1jYED9G46G4fxjQJQieQ0AAAAAQII755xz1LNnTxmGoWPHjmnMmDE6duxYrdoeP35cY8aM0dGjR2UYhnr06KFOnTqFOGIAAAAA4WbY7HL0ny5JMislsMuPHf2nybDVfRshJC6S1wAAAAAAQI899phM05Qk/fvf/9Y555yjmTNn6siRIz7rHzt2TH/5y190zjnn6PPPP7fOP/roo2GJFwAAAED42TOHyzF0jtTojK2CktPlGDpH9szhkQkMccOvPa/z8vJ02WWX1areKbWpf4phGFqxYoU/IQEAAAAAgCAYMWKEJk2apFmzZskwDB04cEAPPPCAHnzwQWVkZCgzM1OtWrVSQUGBfvjhB+Xl5cnj8cg0TRlG+SyLP/zhD7r66qsj/J0AAAAACCV75nCVtbhYeud8SZJ52Stq0GEQM64RFH4lr0tKSvTZZ5/Vqu6pgWtt61cc7AIAAAAAgPB76qmn1KxZMz388MNyuVySJI/Ho927d2vPnj1WvVMztE+N4202mx544AFNmzYt/EEDAAAACL+KiepWfUlcI2hqvWy4aZoh/QIAAAAAAJFlGIYefPBBZWdn69e//rWSkpKsa77G8ElJSfrVr36lDRs2aPr06byUDgAAAEQxIylN9t6TZCSl1Vw5AqI9PoRHrWZejxs3LtRxAAAAAACAKNG9e3e99NJLeuGFF7Rx40Z99913Kioq0vHjx5WSkqLU1FT17NlTPXv2lMPh16JuAAAAACLESEqT48I7Ix1GlaI9PoRHrUaYc+fODXUcAAAAAAAgytjtdl1wwQW64IILIh0KAAAAACAB1HrZcAAAAAAAkFj27Nmj/Px8n9e+/PJLrV27Vm63O8xRAQAAAIhHRcWmFq7xqKg4Orcbjvb44gXJawAAAAAAYDl48KCmTJmitm3bqkOHDlqwYIHPegsXLtTFF1+spk2b6qabbtLOnTvDHCkAAACAeHK4WFq01tTh4khH4lu0xxcvSF4DAAAAAABJ0ueff64uXbro6aef1t69e2usb5qmnE6nFixYoAsuuEArVqwIQ5QAAAAAUD2P5/Ts6M15ptcxohvJawAAAAAAoG3btunKK6/UoUOHrHM2m03Nmzf3Wb9Pnz7KzMyUaZY/BDp+/LhGjRql//znP2GJFwAAAAB8Wbfd1F2vn05WP77Y1B1zPVq3nQR2LCB5DQAAAAAANHnyZDmdThmGofr16+uZZ57RwYMHdfPNN/usf/PNN2vnzp1atmyZ0tPTZRiGiouLNXXq1DBHDgAAAADl1m039dQSj4rOWNr70HHpqSUksGOBI9IBAAAAAACAyNq/f78++ugjGYYhSfroo480ZMiQWrUdNmyYVq5cqe7du8vlcmnx4sUqLCxUWlpaKEMGAAAAEKdKXaZKyvxv5/GYmruy+uT0vM886tHOkM1mBBQXQo/kNQAAAAAACW7Lli1WecSIEbVOXJ/SuXNnjR07Vq+99pokadWqVbrhhhuCGiMAAACAxJC10JQUmkTxoePSr14IXf+oO5YNBwAAAAAgwW3dutUq9+/fP6A+evXqZZX37NlT55gAAAAAAImHmdcAAAAAACS4Q4cOWeVAl/t2OE4/YigpKalzTAAAAAASU9YYQ5kt/V/We3OeqccX1zyjeuq1hs7L8L//3P3myVnhCCWS1wAAAAAAJLjWrVtb5R07dgTUx9dff22V2e8aAAAAQKAaOAw1rOd/cvn89lKzFFOHjlddp3mKdH77wPa8buCQWG489Fg2HAAAAACABPeTn/zEKr/99tsqLS31q31paalWrlxpHZ9//vnBCg0AAAAAasVmMzR+cPWpz3GDbQElrhE+zLyOEgUFBerWrZvPaxMnTtTEiRPDHBEAAAAAhM/s2bM1e/Zsn9cKCgrCHE3i6datm7p166bNmzdr165duv322/W3v/1NhlG7hzqTJk3Snj17ZBiG2rZt65UMTySM7QEAAIDI6tvJ0OQRNs1d6VFR8enzzVPKE9d9O5G4DpVgjetJXkeJVq1aKScnJ9JhAAAAAEB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",
+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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q2LChevTooX/9618aPXq0+vXrpzZt2sjLy0utWrXS/Pnz4yzpnJxJkybZ/P3ImzevKlSooF69emnx4sV6+PBhGr57uKKiRYuqdevWMk1T9+7dU8eOHVN83+qbN2+qc+fOunfvngzDUP369VWmTJm0DRgJov2RNrHGoP3hWLQ/0h/tDwAAkBGkeOZ1TINSiu5gREREWPtatGjhkGAMw9CWLVscUldGc/XqVVWtWjXBfUOHDtXQoUPTOSIAAIDHS2hoqEJDQxUYGKh169ZpwoQJ+uSTTzRw4EBnh4ZM5Pbt2xo7dqy++uorRUVFJVk2IiJCW7Zs0ZYtWzR79mx99tlneuqpp9Ikrrt37+ru3bs6ffq0Fi9eLB8fHy1YsEANGzZMk/MlZM6cOZozZ06C+1KaRIV9ZsyYodq1aysiIkK///67ypUrp379+unVV19VlSpV5OHx9xCCaZo6f/68vvzyS33xxRcKDg629k2fPt0Z4bsE+vZ4FO0PuALaHwAAID04ql9v87LhpmnGey3mF4T2ME3T7joysiJFiujYsWPODgMAACBDKlWqlLJkyZLo/tDQUF2+fDnOa8HBwRo0aJDCw8P1yiuvpHWIgAICAvTMM8/Ea/fXqlVLLVu2VMmSJZU9e3YFBgbq0KFD2rBhgzUD6cCBA/L19dX333+vXr16pfic7u7uSc6ANU1Tt2/f1u3bt+O87u/vr1atWmn79u168sknU/4m7ZBUYq9EiRIKDAxMlzgys6pVq+rHH39Uz549JUn379/XV199pa+++kqGYahIkSIqXry47ty5o4sXLyo8PFxS3HGCDz74QE8//bRT4ncF9O0zF9ofyAhofwAAgPTiqH69Q+55LSWc1AYAAADSw/bt25NdovbBgwc6ceKE3n//fS1dutR6/Y033lCHDh1UvHjxNI4SmdmlS5fUuHHjOLdgatGihT755BNVr149wWOCgoL00Ucf6YMPPlB4eLgiIiLUu3dvhYWFpXj53BIlSuj06dPJlgsKCtKePXs0ZswY7d+/X5IUEhKif/zjH/r999/l5pbiO04hg+vatat++eUXvfzyyzp37pzV1zdNU5cvX9aVK1es57Hlzp1bn376qV566aV0jxlwFtofcHW0PwAAQEaU4uR1v379Et23bds2hwQDAAAApJXs2bOrVq1aWrJkid5++21NmzZNUvTMwu+++05vv/22kyPE4yoqKkovvfRSnIHjd999V2PGjEly9am8efNqypQp6tSpk9q0aaObN29KkoYMGaKGDRuqcuXKDosxb968atOmjVq1aqWnn35av/32m6ToGVd79uxRo0aNHHYuuL4WLVrozz//1MKFCzV37lzt27fPunXYo0nr8uXL68UXX9TgwYNVpEgRZ4QLuDTaH3AW2h8AACCjSnHyet68eYnu8/X1dUgwAAAAQHoYN26cvvzyS925c0dS9G1wGDxGWvnss8+0ZcsW6/mECRM0duzYFB9fp04dbd26VY0aNVJoaKju37+vvn37au/evQ6fkeTm5qaPPvoozr0t/fz8GDzOhHLkyKFBgwZp0KBBun//vg4fPqzr168rKChIOXLkUIECBVS1alV5eXk5O1Qgw6D9gfRE+wMAAGRUrL0CAACATMfT01NVq1a1nl+6dMmJ0eBxFhYWZs2yk6R69epp/PjxNtdTs2ZNvffee9bz/fv3a+PGjQ6J8VG1a9eOMyOL7wdy5MihBg0aqH379urTp486d+6sZs2akbgGbET7A+mF9gcAAMjI7L7n9Q8//KCZM2dKkt5++21169bN7qAAAACAtObt7W1tP7oMbmIiIyO1Z88eHT9+XNeuXZOXl5d8fHxUq1Yt5cuXz6bz37p1SydOnJC/v78uXbokb29vlStXTlWrVrW5rrt372r79u26cOGCgoKCVLBgQZUrV05PP/20smfPblNd6e3EiRPat2+fLl++LE9PT5UrV07Vq1dXyZIlba7r8uXL2r59uwICAuTu7q6SJUuqZcuWyp8/fxpEnjKLFi3S5cuXreeffPKJPDxS1w0bNmyY5syZY91DcsaMGWrbtq1D4owte/bsKlSokK5fvy4p5d8PAEDyaH+4BtofKUf7AwAApDe7k9eXL1/WwYMHZRiG9u3bR/IaAAAAGUJAQIC1ndxA5cOHD/Xpp59q+vTpunbtWrz9OXPm1IABAzRy5EiVKVMmyboCAwP1/vvv6+uvv1Z4eHi8/Z6ennrzzTf15ptvKk+ePEnWdeHCBY0ZM0ZLlixJsK4cOXJo4MCBmjhxogoXLpxkXQl59tlnrdk13bp105IlS5I9ZtOmTWrTpo0kyTAMnTt3TqVKlYpTxjRN/fzzzxozZoz+/PPPeHUYhqHnn39eb731lho3bpzsOU+ePKkRI0Zo/fr18QY6s2bNqpdeekkff/xxsvWkhcWLF1vbderUUcOGDVNdl7u7u1599VW9+eabkqTNmzdbSQxHun//vm7cuGE9T81APgAgYbQ/kkf7w360PwAAQEZm97LhFStWtLZjfoEHAAAAuLL79+/r+PHj1vPY99d71I0bN9SkSRONHDkywYFjSQoNDdWcOXP05JNP6tdff020rq1bt6pixYr6/PPPExzslaSQkBC98847qlu3rjXzJCHbt29XjRo19OOPPyZa1/379zVnzhw98cQTOnLkSKJ1JaZXr17W9tq1axUaGprsMYsWLbK2W7duHW/gODIyUoMHD1bHjh0THDiWogeXV61apaZNm+rTTz9N8nwbN25UrVq1tG7dugRn6Dx8+FDffPON6tWrp5s3byYbf2L69+8vwzCSTQ7EFh4erp07d1rPe/bsGWc5zNTo2bNnnOex63eUw4cPx7mWSX0/8PiJiIjQe++9p6ZNmyp37txyd3e3+ZHa2X3A4472R8rQ/vgb7Q8AAJAZ2d2jbNeunUqWLKmAgADt3LlToaGhypkzpyNiAwAAANLEO++8ozt37kiKXqJw8ODBCZYLCwtTmzZtdODAAeu1p556So0aNVL58uV14cIF7du3T5s3b5YUvRRnq1attGPHDjVo0CBOXTdu3FD37t2tAdiY2T0NGjRQoUKFdOnSJf3888/av3+/JOmvv/7S6NGj9e2338aL6+TJk2rbtq3u379vvda8eXM988wzVl1r1qzR3r17JUWvltSyZUsdPXrUplkynTp10iuvvKKwsDCFhoZqw4YN6ty5c6Llw8LCtGLFCuv5wIED45UZPny4vvnmG+u5j4+PWrdurapVq+revXs6ePCg1qxZo/v37ysqKkqvv/66oqKiNHz48Hh1HTlyRM8//7wePnxovdawYUO1b99eRYoU0cWLF7Vs2TIdO3ZMp06d0pAhQ1L83h3hjz/+UEhIiPU8JbO4klO8eHGVLl1a58+flyT9+uuvSf6b2CoqKkojRoywntepU0dNmjRxWP1wbTdv3tRzzz2nffv2SWLJVsDRaH+kDO0P+9D+AAAAGZ7pADt37jRz5Mhhurm5mUOGDHFElZmGt7e3Kcn09vZ2digAAMCBJFmPefPm2Xz82bNn49Sxbdu2BMuVLl3aKjNx4sQ0i9XX19cq069fv1SdxxGxxti2bVucuM+ePZvsMQ8fPjSPHDli9unTxzQMw5Rkurm5mcuXL0/0mLFjx1rn8PLyMv/73/+aUVFR8cr5+fmZPj4+VtnatWub4eHhccp8+OGH1n5PT09z9+7d8eqJiooy33jjDatc/vz5450vKirKbNSoUZy61q5dm2Bd8+fPN93d3a2yvXr1SvB9xv63efRadunSJdnjY6xcudIqmy9fPvP+/ftx9v/yyy/Wfjc3N3P69OlmWFhYvHrOnDljtmrVKs57vHDhQrz3V69ePatMlixZzAULFsS7XhEREeaECRPifF4kmb6+vkm+l0f169fPlGSWLl06xccsWbIkzjlDQkJsOmdiOnXqZNX5/PPPx9s/ceJEa39K4w0ODjY3b94c57NVuHBh89SpUw6J2V70m9LHsGHDTMMwTMMwTDc3N2vb1oebm5uz30q6c5XPKO2PtIk1Bu0P2h+0PzJX+wMAADiOLX0mhySvTTO6Ae/l5WW6ubmZzz33nPnbb78l2LBGXK7SwQUAAI716ECVvY+UDB474pGSwWNHPBw9eFyqVCnTx8cn0Ufx4sWtAeOYh7e3t7l69epEzxEUFGTmypXLGuhM7N8gxvHjx82cOXNa9S9evDjO/s6dO1v7hg8fnmg99+7dixPrxYsX4+zfuXNnnPexYMGCJON677334gzYPlqfaSY9eLx8+XJrX65cueINCMfWo0cPq+zQoUPj7W/atKm1f8qUKUnGHRoaalarVs0q/89//jPOfj8/vzjX4ZNPPkmyvhdffDHdB48///xz63w5c+a06XxJGTx4sFVv48aN4+2PPXjs7u6e5HfDx8fHLFSoULzvaMOGDc0///zTYTHbi35T2rt8+bKZJUsW083NzXRzczNLlChhLl682Lx8+bKzQ8sQXOUzSvuD9gftD9oftD8AAIArsqXP5JAbUb3zzjuSpI4dO+qbb77R+vXrtX79erm7u6to0aIqVqyYPD09k63HMAxt2bLFESEBAAAgE7lw4YJN5bNmzaqFCxeqadOmiZb56aefFBwcLCn63ovNmjVLss7KlStrxIgRevfddyVF31+yR48e1v6wsDBru2jRoonWkytXLi1ZskQPHjywYo3thx9+sLYrVKgQ7x6Ejxo6dKg++OAD3b17V1FRUVq8eLFGjhyZ5DGxtWvXTnny5NHdu3cVHBysX375Rc8//3y8csHBwVq9erX1/NElO0+dOqUdO3ZIkkqWLKkxY8Yked4cOXLok08+UatWrSRFX8/YFixYYG17e3vrlVdeSbK+sWPHasGCBem6DPKtW7es7Xz58jms3vz581vbN27cSLJsZGSk/P39baq/bNmyWr58uYoXL56q+JAxHT58WBEREZKiv3+7du2Kd89YAHHR/kgc7Y9otD9SjvYHAACI4ZDk9aRJk2QYhiRZ/zVNUxEREQoMDFRgYGCydZimaR0LAADwOClcuLDy5Mlj0zHh4eE2D4jmz59fBQoUsOkYSTYPLOXKlUtFihSx+Tznzp1TZGSkzcelhYcPH6p58+YaN26cJk+enGAZPz8/a/vZZ59NUb2xB6N37twZZ1/FihW1du1aSdI333yjAQMGJHodu3btmug5/ve//1nbr732mtzd3ZOMKW/evOrfv79mz54tSdq9e3fSb+IR2bNnV+fOnTV//nxJ0rJlyxIcPF69erV1D8yaNWuqdu3acfZv377d2m7Tpo3c3NySPXejRo3k4eGhiIgInTp1SteuXbPumblr1y6r3LBhw5QtW7Yk66pUqZLatm2rdevWJXteR8mZM6e1Hfv+oPaKfY9NDw+HdOniOHv2rKpUqaIffvghwX9rPJ5OnjwpKbpP/+KLL5K4fgzQ/ohG+4P2RwzaH/ah/QEAANKLw1oaif2CMD1/WQgAAOCKpk+frv79+9t0zLlz51S2bFmbjnn99dc1adIkm46RZPMPCLt06WINJNqiTJkyOn/+vM3HpcTZs2dVpkyZRPdHRUUpICBAhw4d0tixY3XkyBFFRUXpnXfeUeXKldWrV694x+zfv9/aHj16dIqubexBvcuXL8fZ16lTJ82aNUumacrf31+VKlXSq6++qg4dOqh+/fopGgSMiorS0aNHrefVqlVL9phHyx06dChFx8TWq1cv69989erVCgsLizdYu2jRImt74MCB8T5Xsa/nypUr4wzOJyUqKsravnLliry8vBQZGakTJ05Yr9eqVStFddWuXTtdB48LFSpkbd+5c0eRkZHJDvanxM2bN63twoULJ1m2dOnSOnfuXJJlwsPD5e/vr19//VVvv/22bt68qbt376pPnz7av3+/KlasaHfMcH2xv2s1atRwYiRwFNof0Wh/0P6IQfvDPrQ/AABAenFI8nrbtm2OqAYAAABIE25ubipVqpRKlSqlZ555Rg0aNNDBgwclSZ999lmCg8fXr1+3tlOyktCj7t27F2d1oaefflrjx4+3brkTFBSkadOmadq0acqVK5caNWqkp59+Wh06dNATTzyR4KB+zNKbMZIaMI+tdOnS1nbspSRTqkWLFvLy8tK1a9cUFBSkzZs367nnnotT58aNGyVJWbJkUZ8+feLVEft63rp1K1Vx3Lt3T1L0QGzsH8mWK1cuRccnd71mz55tzRB71NWrVyVJAQEBKl++fIJlOnfurOnTp1vPY2ZpSdE/6j179myix9rizJkzCZ4jtbJkyaLKlSurcuXKeuaZZ1SpUiU9ePBAwcHB+u677/Tee+/ZfQ64Pnv/TgCIj/YH7Q+J9kdiaH8AAIDEOCR57evr64hqAAAAgDSXNWtWTZ48WR07dpQk7dmzR/fu3VPu3LnjlAsKCrLrPBEREXrw4IFy5MhhvTZ58mS1bNlSb7zxhv744w/r9eDgYG3atEmbNm3ShAkTVLZsWQ0bNkzDhg2LMyMq5h6YMVK6fGrsewem5n15eHioe/fu+uyzzyRFL90Ze/B4xYoVCg8PlyQ9//zzcWb82HPeR929e1dS/CUwixUrlqLjvb29k9x/69atZJexTeoejteuXYvzvG7dunGe79q1y+7B47CwMO3bt896Xr9+fbvqe1SpUqX06quvaubMmZKkzZs3M3icSTRv3lyenp4KDQ21eXlfAMmj/UH7IzG0P2h/AACAuJK/0QsAAADwmGncuLG1HRkZac1qiS32/QL37Nkj0zRtfsQeOI7RtGlT7d+/X3/99Zc+/PBDNWvWTNmzZ49T5uzZsxoxYoQaNmxozfaRou/3GVtCcSck9qwjT0/PFB3zqN69e1vbq1atsgaLpfhLdiYk9vX84IMPUnU927ZtK0nx7uH66BKpiXl0cDetFSxYUE888YT1POaeo/bYunWrwsLCrOctWrSwu85Hxf5+pGbWHzKmvHnzasiQITJNU5s2bdKOHTucHRLw2KH9YTvaH7aj/QEAADI6ktcAAADIdAoUKBBnIDZmRs2jZWKcPn3a4TGUL19eI0eO1LZt23Tnzh3t3LlTkyZNUuXKla0y+/fv17///W/reZ48eeTm9ncTPqX38Iy9zGPs92WLhg0bWste3r59W1u3bpUUPXAbc//I4sWLq02bNgke78jrmStXLmXJksV6Hvv9JeXs2bNJ7p80aVKiA9f9+vWTFL0EamJlEroXa/v27a3tFStW2D0Y+8knn1jbJUqUUM2aNe2qLyGxl3lN6LuBx9f777+vZ555RhEREerevXucGZoA7Ef7w3a0P2h/AACAzIfkNQAAADIdwzCUN29e63ns2UUxatSoYW3/9ddfKao3KipKERERioiIUGRkZIrjyZYtmxo3bqyJEyfq6NGjGjFihLXvp59+su6v6ObmpmrVqln7jh07lqL6jx8/bm1Xr149xXHFZhhGnHtzLlu2TJK0ZMkS6z6YL730UpxlRmNLzfU0TdO6nhEREdbrbm5ucWYUHTp0KEX1/fnnnykq50hDhw5V1qxZJUXPshs7dmyq69q6dat1b09JGjlypNzd3e2O8VH58uWztoODg+Pc3xOPN3d3d61atUojRozQtWvXVK9ePXXv3l2rV6/W8ePH48y6A2A72h+2o/2ROrQ/AABARuaQ5PXAgQMd8hg0aJAjwgEAAABs8uDBg3ivxV66cOHChXGWqUzM0KFDlSVLFmXJkkVTp061Xr927ZrKly9vPW7evJloHe7u7ho1apT1/Pbt27px44b1/KmnnrK2P/vss2QHqe/evau5c+cmeLytYg8er1y5UhEREXGW7BwwYECix8a+nrt27UrR7KclS5ZY1/PZZ5+Ns69Ro0bW9uzZs5NNqp0/f17//e9/kz2noxUrVizOUqbfffedlixZYnM9169ft2ZfSZKXl5defvllh8SYFNM09fDhwzQ/D1zDU089pWbNmum3335Tnjx5ZJqmli9frk6dOql69erKmTOn3N3dk30klkQCEBftj5Sh/WE72h8AACAjc0jyev78+fruu+/sfiS0zA0AAACQFmLPGElo8Lh3797WEpmnTp3SF198kWR9586d07x586znffv2tbbz5MmjM2fOyN/fX/7+/tqwYUOSdQUEBMR5HnuJ0T59+ljbJ0+e1NKlS5Os65NPPtGdO3ckRc8Yij0AbKsaNWpYM6du3ryp+fPna8+ePZKkJk2aqGLFiokeW79+fWt/eHh4nOVIExIWFqb333/fev7SSy/F2R/7+gYGBurLL79Msr5p06bFmT2VnqZNm6Zy5cpZz/v06aOffvopxcdfvHhRTZs2jfO5+O6771J9/9DkPDqbKqHvBx5Pu3fv1p49e7Rnzx7du3dPhmFY+2y9RyyAhNH+sB3tj9Sh/QEAADIqhy0bntqO7OPQuQ0ODtbBgwe1bds2HTt2LEW/igUAAIBz5c+f39q+ePFivP2lSpWKM1D773//W7NmzbKWqIzt7NmzatWqlTX7pkWLFtb9GSUpe/bsql27tvV89OjR8QaIY9y5c0fDhg2zntetW1c5cuSwnjdp0kT169e3nv/jH//Qpk2b4tVjmqbmzZunSZMmWa917949TlypEXvwOfbyoknNepKiB65jz+hauXKlBg0alOCSqcHBwerevbsOHz4sKXrwvVOnTnHK1KtXT02aNLGejxw5Uj/88EO8fkVUVJQ+/vjjZAeX01LevHm1ZMkS5cyZU5IUERGhnj17qm/fvrpw4UKixz148ECzZ89WzZo1deLECev1cePGxZsJ5kixvxtSwt8PPL4yazKafj3SC+2P1KH9YTvaHwAAIKNyyFpesX/hmZSwsDCdPXtW/v7+2rp1q27duiXDMDRixAiNGjUqzq+608KcOXP02muvaeLEiXEa0al1+fJlvfXWW1q+fHmcXwMWKlRIgwcP1vjx45U9e3a7zwMAAADHK1SokLW9a9cuvfbaa/HKzJo1S1u2bNGlS5cUFhamN954Q99//72aNGmiKlWqKDg4WH/88YeWLVtmzarJmTOn5syZE6+uwYMH65///Kek6JlNVapUUffu3VW9enXlzZtXt27d0rFjx7R06VIFBwdbx40ZMyZOPYZhaN68eXryySf14MEDBQcHq02bNnrqqafUoEEDlS9fXn/++ad27txpDb5K0cs8zp49276LJqlnz57WfRNjBn49PT3VrVu3ZI8dMGCAli1bpvXr10uS5s6dq19++UWtW7dWzZo15ebmplOnTmnhwoW6ffu2ddxnn32m3Llzx7sO//nPf1SnTh09ePBAEREReumllzRnzhx16NBBRYsW1eXLl7VixQodOHBAUvTA+5EjRxQUFGT3dbDVk08+qW3btql9+/a6fv26JOnHH3/UwoUL1ahRIzVt2lTFixdX9uzZdeXKFR05ckTr16+P81mQpKlTp8YZhE8LefPmlYeHh/WZ3rVrV6rvVYqMJaHkmKuhX4+MjvZH6tD+SB3aHwAAIEMyneTu3bvm5MmTzezZs5tubm7m4MGD0/ycDRs2NCWZEydOtLuuEydOmIUKFTIlJfqoX7++GRwcnGQ93t7epiTT29vb7pgAAIDriN0mmDdvns3Hnz17Nk4d27ZtS7Bc6dKlrTKpbeOkJFZfX1+rTL9+/VJ1HkfEGmPbtm1x4j579qzNdQwfPtw63t3d3dy6dWuC5U6cOGGWKlUqyXZfzKNAgQKmn59fgvWEh4ebHTp0SFE9MY9JkyYlGv/WrVvNXLlypaieEiVKmEePHk20rtj/Nim5ljHt6pjHgAEDkj0mxt27d81WrVqlKG4PDw9zxowZSdb3yy+/mNmzZ0+2rooVK5pXr141CxYsaEoyfX19UxyzaZpmv379TElm6dKlbTruUWfOnDHbt29v0+dAkunj42OuWrUqReeYOHGidVxq433iiSesOkqVKmVeuHAhVfU4Cv0mxHDFfr1pus5nlPZH2sQag/YH7Y8YtD/iexzbHwAAwHFs6TM5bNlwW+XOnVsTJkzQF198IdM09c033+irr75Ks/PNmzdPu3fvdkhdYWFhev7553Xjxg1J0rBhw3T69GmFhoZqz549atmypSRp7969GjJkiEPOCQAAAMdq1qyZtR0ZGal+/folWK5SpUo6ePCg3nzzzUTv8ZctWzaNGjVK/v7+8vX1TbCMh4eHli9frqlTp8rLyyvRuNzc3NSjRw/98ccfmjhxYqLlmjdvrsOHD6tnz57y8Eh4QaUcOXJo2LBhOnDggKpVq5ZoXbbq3bt3nOfJLdkZW+7cubV+/Xp9/vnn8vb2TrRc165ddezYMb3xxhtJ1te6dWsdOnRI7dq1S3AlJ3d3d7300kvat29fktc9OfPnz5dpmjp37lyq65CksmXL6ueff5afn5+6du0ab0ZXbIZhqHHjxvrss8907NgxPf/883ad2xaxvx8XLlywZrsBzkS/Ho8D2h+pR/sj9Wh/AEDGcjvE1NLdUbodYjo7lFTJ6PHD+QzTdP7Nqzp16qRVq1bJy8tLAQEBiTZ+bRUUFKTDhw9r3rx5WrBggXXPKnuXF/v88881dOhQSdH3tvnwww/j7A8PD1eTJk20d+9eGYahI0eOJNpYL1GihAIDA+Xt7Z3ofYcAAADgGsLCwvTrr7/q9OnTun37tkqUKKHKlSurcuXKSQ4CPio8PFzHjx/XhQsXdPHiRQUFBalkyZIqU6aMKlSoYPMgZ1BQkPz8/Ky6ChQooHLlyqlp06Zx7lfpaqKiovTHH3/o8OHDunbtmvLnz29dzyJFithc35UrV+Tn56fAwEBFRUXJ29tbLVq0UNGiRdMgesd4+PCh9uzZo4sXL+rq1asKCwtTkSJFVKxYMT355JMqXLiws0N0CfSbMq+M0K+X+IwibdH+cCzaH7Q/AMDVnb1m6u1FUZray01lvdL2drtpIaPHj7RhS5/JJZLXn376qYYPHy7DMLRhwwa1bt3a7jrr16+vffv2JbjP3k5u7dq1dfDgQXl4eOj69evKly9fvDJr165V+/btJUlvvvmmPvroowTrooMLAAAAAEmj3+Qc+/bt09atW7Vz505dvnxZ9+7d071793Tp0iVJ0QmgxYsXq1OnTmmSqMoo/XqJzygAAAAcJy2Tv1FRpo5fku6EmMrnaahKccnNzbHnIHmNhNjSZ3LMFGc7Va1a1dr29/d3SPL62rVrdteRkMDAQB08eFCS5Ovrm2AHV5JatmwpT09PhYSEaO3atUl2cgEAAAAAcBUXLlzQ8OHDtXr16jivm6YZZ3lc0zTVt29f5cqVSz179tTUqVNVsGBBh8VBvx4AAABwnL2nTc3fHqVbwTGvmCqQS+rv66b65Ukyw3U47Z7XsV28eNHavnv3rkPqPHnypO7fv289Tpw44bB6Y7Rr1y7RctmzZ7fukXXixAmFhIQ45PwAAAAAAKSV48ePq1atWlq9erVM04zzSExISIi+/fZb1axZ02F9b4l+PQAAAOAoe0+bmrE2duI62q1gacbaKO097fRFmgGLSySvf/rpJ2u7bNmyDqkzW7Zsyp49u/XIli2bQ+q9fPmytV26dOkky5YsWdLa/uuvvxxyfgAAAAAA0sKNGzfUrl073blzx5pl3bdvX/3nP/9RsWLF4pV3c3PTM888YyW2L1++rHbt2iksLMwh8dCvBwAAQGYWFmHqQbj9j9CwKM3zi0ryXPO3Ryk0LMoh5wuLIBEO+zh12fDIyEhNmTJFGzdutF6rVKmSEyNK3pUrV6ztAgUKJFk29nJply9fVq1atRIta5qmXbPOs2XL5rCOPAAAAAA4UlhYmF0JzaRm/cJxZs6cqfPnz8swDBUuXFg//fSTfH19JUkffPBBvPKGYWj9+vXavXu3nn/+ed28eVPnz5/Xp59+qpEjR6Z3+CmWVv16ib49AAAAHGfSUlNS+vSFbgVLA79Mv/Mh40nPfr1DktcDBw60+ZibN2/qjz/+0KVLlyRFd3obNGigmjVrOiKkNBP7F9rJ3csr9v7klhe7dOmS8ubNm+q4Jk6cqEmTJqX6eAAAAABIK1OnTtXkyZOdHQaScP/+fX311VfW8y+//NJKXCenYcOG2rBhg+rWrStJev/99zVs2DCXTcKmVb9eom8PAAAA4PGUnv16hySv58+fL8Ow/WbuMcuQSZKHh4dmzJjhiHDSVOxfUOfIkSPJsrE76vfv30+ybPHixXX8+PFUx+WqgwIAAAAA8Pbbb2vEiBGpPr5KlSrWD5+RNv744w/dunVLhmGoUaNGeuGFF2w6vk6dOurQoYN+/vlnBQUF6eTJky774/S06tdL9O0BAADgOJO6GSpT2PbcW4w7IabuhEpnr5n6bnvy5fv5SmW9DOXLKeXzTP15z103/3/WOB4n6dmvd9iy4aldxs00TZUrV06LFi1SvXr1HBVOmilcuLC1fefOnSTLxt6fXIfYMAzlyZPHntAAAAAAwCXZuxRyan4sDducOXPG2n7qqadSVUejRo30888/S5JOnDjhssnrtOrXS/TtAQAA4DjZPAxlz5L6vlDRfIaK5pMqFjX18/4o3QpOvGzBXNIzNd3k5mZ/3yubh8Ty44+f9OzXOyR5PW/evFQd5+npqVq1asnHxyfDDEYUK1bM2r5161aSZWPvz5UrV5rFBAAAAACAPQIDA63t8uXLp6qO2Etsnz171u6Y0gr9egAAAGQmbm6G+vu6acbaqETL9PN1TOIacASHJK/79evniGoyhKJFi1rbyXVyb9++bW2XLFkyzWICAAAAAMAesRPP58+fT1Udp06dsrZdefYx/XoAAABkNvXLGxrxnJvm+UXpdsjfrxfMFZ24rl+exDVch5uzA8hoYv9C+9ChQ0mWPXz4sCTJ3d1dFSpUSNO4AAAAAABIrdizrffv35+qOvbs2WNtlylTxt6Q0gz9egAAAGRG9csb+vjFv5PUozoa+nQAiWu4HpLXNqpRo4ayZMkiSda9vBJy9epV7d27V5JUr149Zc2aNV3iAwAAAADAVk2aNFHevHllmqY2bdqk3377zabjFy9erJ07d0qSsmbNKl9f37QI0yHo1wMAACCzir00eBVvg6XC4ZJSnbw+efKkFixYoJkzZ2r69OmaP3++/vzzT0fG5pLy5MmjFi1aSJKOHTumEydOJFjuv//9r0wz+ob0nTp1Srf4AAAAAACwVZYsWfTPf/7Tej5gwIA4y4AnZc2aNXr11VclSYZhqE+fPsqZM2eaxOkI9OsBAADgyvJ5Sl0aGMrn6exIUiejxw/ns/me1/PmzdPUqVPl7++f4P5y5cpp/Pjxeumll+wOzlWNGDFCGzdulCS9+uqrWr9+vbJnz27tP3/+vCZMmCApulM8aNAgp8QJAAAAAEBKjR07VkuXLtXZs2d1+vRp1a1bV2+88YaeeeYZRUZGWuVu3rypv/76S3/99Ze+//57bd261dqXP39+TZkyxRnh24R+PQAAAFxVfk9D3Rpm3BnRGT1+OF+KZ16Hh4erW7duevnll3X69GmZpmn9AjmGaZry9/fXgAED1KNHD0VERDg84PTQv39/GYYhwzA0adKkePtbt26tzp07S5L8/PzUsGFDffnll1q5cqXeeecd1atXT9euXZMkvf/++ypYsGB6hg8AAAAAgM1y5cqlTZs2ydvbW6ZpKiQkRO+++66efvppnT9/XlJ0v9/Ly0uNGzdW//79rcS1aZrKlSuX1qxZE+ee0s5Cvx4AAAAAMqYUz7x+6623tHz5cknRy4DFJK4fTWDH7Fu2bJny58+vL7/80oHhugbDMPTdd9/p7t272rx5sw4dOmQtkRbb2LFjNWTIECdECAAAAACA7cqWLatDhw5p2LBhWrRokdXnj0kES/HHASTp6aef1ty5c+Xj45Ou8aYW/XoAAAAAcE0pmnn9119/6dNPP7U6q4ZhaNiwYfLz89O1a9d07do1+fn56bXXXrP2m6apr7/+Wnv37k3r9+AUuXLl0saNG/Xdd9+pRYsWKly4sLJkyaISJUqoV69e+vXXX/Xuu+9anXsAAAAAADKC/Pnza8GCBTp16pTGjBmjp556SlmzZo2zApthGKpevbpeeeUV7dq1S9u3b88wiesY9OsBAAAAwPUYZkI/mX7EqFGj9OGHH0qSsmbNai2plZD//e9/atasmbVk+MCBA/X11187MOTHS4kSJRQYGChvb28FBAQ4OxwAAACnuR1i6k6I7cfl84y+nxKAxxf9JtcQHBysoKAg5cyZU3nz5pWbW4rvRPbY4zOacdH+AAAAmcmDcFP9P4+SJM0f4qbsWWjPIH3Y0mdK0bLh27dvlxT9y+rRo0cnmriWpEaNGmn06NGaMmWKDMPQtm3bbAgdAAAAmdXmI6aW70n2d5XxdGlgqFtDOlsAkNZy5cqlXLlyOTsMwKFofwAAAACuJUXJ67Nnz1rbAwYMSLb8oEGDNGXKFJmmqUuXLqU+OgAAAGQarWoYqlsu7iBwWISpSUujB5QndTOUzSP+IHE+z3QJDwAAPIZofwAAAACuJUXJ61u3bkmScubMqdKlSydbvmTJksqZM6dCQ0MVFhZmX4QAAADIFPJ7Gsr/yEDwg3BJih48LlPYYDkrALDTjh074jxv2rSpkyIBXAPtDwAAAMC1pCh5HRkZKcMwVLRo0RRVGlP2zJkzdgUHAAAAPK7Cw8N18OBBHTx4UDdv3lSuXLlUrlw5+fj4qGzZssqaNauzQwTwGGrWrJkMIzoRZxiGIiIirH3lypVzyDkMw5C/v79D6gLgWLQ/AAAA4OpSlLyOEdPBdXRZAAAAILN48OCBpk+frs8++0zXr19PsEy+fPk0YMAATZgwQfny5Yu3/9y5cypbtmyy5ypSpIgqVaqkKlWqaMCAAWrQoIFNsbZp00abNm2ynu/YsUNPP/20TXUkZdKkSZo8ebIkqWbNmvr999+VJUuWFB3r4eGhyMhI9evXT/Pnz3dYTEBmYZrx7/F77tw5u/vypmkyHgC4INoff6P9AQAA4NrcnB0AAAAAkFlcv35dDRo00MSJE62B46xZs6pKlSoqW7as3N3dJUl37tzRzJkzVb16dZ08eTLV57t69ap27Nihr776Sg0bNtTw4cMVFRWVomOvXLmiLVu2xHlt0aJFqY4lOYcPH9ZHH32UZvUD+FtCievY++x5AHA9tD8SR/sDAADA9dg08xoAAABA6kRFRemFF17Q4cOHJUlNmjTRu+++qyZNmliDxhEREfrtt980efJkbd26VYGBgWrbtq2OHj2qnDlzJlhvq1at9Oabb8Z7PSwsTH/99Zc2bNhgDQLPnj1bXl5eGjt2bLLxLl68ON5A85IlS/TJJ5+keHaSrSZPnqwuXbqoYsWKaVK/LcqUKaPz588zswqPnYkTJya67+zZs+kYCYD0QPsjebQ/AAAAXAvJawAAACAdrFixQr/99pskqXXr1lq3bp08POI2xz08PNS0aVNt3rxZvXv31uLFi3X27Fl98cUXCQ4QS5K3t7eeffbZRM/75ptv6quvvtKrr74qSZo6dapeffVVFShQIMl4f/zxRyum9u3b67///a9u3rypzZs3q23btil+37YICwvT4MGDtW3bNpYdBtJIUsnr0qVLp2MkANID7Y/k0f4AAABwLSwbDgAAgDR3O8TU0t1Ruh2SvkvKOuu8CVm6dKm1/dlnn8UbOI7NMAz95z//UY4cOSRFDzynlmEYeuWVV6wB35CQEO3ZsyfJY06dOqXff/9dktS2bVsNGTLE2rdw4cJUx5KU+vXrS5K2b9+ub7/9Nk3OAQDIPJzZBqD9QfsDAAAAqUfyGgAAAGnuToi0fI+pOyGZ47wJOXHihCQpX758qlChQrLlc+fOrZo1a8Y5NrUMw9Bzzz1nPT9+/HiS5WNmPUlS37591bx5cxUqVEiS9N///lehoaF2xZOQWbNmKW/evJKkkSNH6vLlyw4/BwDb3Lt3Tzt37tSpU6cS3L9mzRr99NNPunLlSjpHBiTPmW0A2h/RaH8AAAAgNWxKXp87d07lypVL0eP8+fPWcSk9xsfHx+FvEAAAABlXVNTfM5aOB5pxnmc0kZGRkqS7d++mePD1888/188//6zvv//e7vOXKVPG2vb390+0nGma1uBxnjx51KFDB3l4eKhLly6SpODgYK1Zs8bueB5VrFgxffjhh5KkoKAgDRs2zO46g4OD9dFHH6lJkyYqXLiwsmfPrgoVKqhjx45avXq19W8Sm2EYMgzD6s9899131mt+fn52xwRkBCdOnFDXrl3l5eUlX19fbdiwIcFyW7ZsUe/eveXt7a1GjRpp9+7d6RwpkDZof9D+sAftDwAAAPvYlLyOjIzUuXPnUvSIjIy07hOTXNnz589b2wAAAIAk7T1t6s0f/h4s/mCVqdfmRWnv6Yw5gFy+fHlJUlRUlN544w1FREQke0ydOnXUvn37OLOWUit2W7tEiRKJltu7d681uNy1a1dr6dDu3btbZdJq6c5BgwbJ19dXkrR8+XKtWrUq1XXt3r1bFSpU0FtvvaVdu3bpxo0bCgsL0+nTp7V69Wp17NhRTz/9NDNGgUcsXrxYtWrV0sqVKxUWFpZsedOM/pu8Z88eNW3aVAsWLEjrEIE0RfuD9gftDwAAAOdKcfLaNE2rU2pL+ZQcY0u9AAAAePztPW1qxtoo3X5kuc1bwdKMtRlzALlHjx7W9tdff60nn3xSX331la5du5bm5zZNU+vWrbOe16hRI9GysZfsfPHFF63tpk2bysvLS5K0bt063b592+Fxurm56T//+Y+yZcsmSRoyZIiCgoJsrufo0aNq2bKlrly5Ig8PD/Xv31+ff/65lixZonfeeUdVq1aVJP3vf/9TkyZNFBLy9wdt/fr1Wr9+vfVeW7VqZb0Ws4wq8Ljau3evXnzxRT18+NB6rXDhwipbtmyC5du0aaNmzZrJzc1NhmEoIiJCgwYNsu5ZC2Q0tD8ci/YH7Q8AAIDU8EhJoYkTJ6Z1HAAAAMgEwiJMPQhPukxUlKl5fkkPDs/fHqXqJQ25uRnJns9V9OjRQz/88IPWr18vSTp8+LD++c9/6tVXX1Xt2rXVqlUrtWrVSo0bN1bOnDkddl7TNPX1119bg8eFChVSkyZNEiwbERGhn376SZJUsmRJNW3a1NoXs3TnF198ofDwcK1YsUKDBg1yWJwxKlasqPHjx2vcuHG6dOmSRo8erS+++CLFx5umqf79+ys0NFRFixbVtm3bVLly5ThlRo8erXHjxmn69Ony9/fXhAkT9PHHH0uSnn32WUmyZnx5e3tbrwGPu5EjR1qrqBUsWFDffPONOnToYK2q9qi2bduqbdu2On78uHr06KGjR48qPDxco0aN0pYtW9I5eiBhKWl7SLQ/aH/Q/gAAAHAVJK8BAACQbiYtNSXZP6B7K1ga+KVj6kovbm5uWr16tSZMmKA5c+bo7t27kqIHO//44w/98ccfmj59urJmzarGjRura9euevHFF5U7d+4k6w0MDEzwfrQPHz7U6dOntWHDBm3atMl6febMmcqXL1+CdW3ZssWaidWnTx+5ucVdqKl79+7WQO7ChQvTZPBYkt566y399NNPOnLkiL788kv16dMn0QHvR/n5+Wn//v2SpB9++CHewLEkZcmSRVOnTtWePXu0fft2zZ8/Xx9++GG89wtkJoGBgdq5c6cMw5Cbm5s2b96c4tl+VapU0caNG1WxYkWFhITIz89PFy5cUKlSpdI4aiB5jmp7SLQ/YqP9ERftDwAAAMehdQQAAACkEw8PD73//vu6fPmyFi5cqH79+sW7/+PDhw+1bds2DR06VMWLF9eXX36ZZJ2bN2+2Zj/GfnTs2FFvvvmmNXDs7u6uiRMnqk+fPonWFXvJzr59+8bb//TTT6tIkSKSpG3btunSpUspfu+2yJo1q77++mtrtuc//vGPFN17V5LWrFkjSSpSpIhatGiRaDk3Nzd16tRJknTr1i0dPXrUzqiBjO3kyZPWdrdu3WxeprZYsWJx/m7s2rXLYbEBsA/tj5Sh/QEAAOAaUjTzGgAAAHCESd0MlSmc9FKbxwNNfbAq+RlNozoaquKddF3nrpv/P+PKteTMmVO9evVSr169ZJqmTp06pc2bN2vz5s3atGmTdQ/E4OBgvfrqq7p69WqqVkPKkiWLqlatqlq1amnYsGF68sknEy0bGhqqlStXSpJq166tatWqxSvj7u6url27as6cOTJNU0uWLNG//vWvOGUCAwN15MiRBM9RoEAB1a9fP0WxN2jQQMOGDdPs2bN14sQJvffee3rnnXeSPW7fvn2SpKtXr8rd3T1F55KkK1eucE9JZGqxk9d16tRJVR1VqlSxttMquQTYKiVtD4n2B+2PaLQ/AAAAnI/kNQAAANJNNg9D2bMkPeD7RCmpQC5Tt4ITL1Mwl/REqeTvOZnNQ3L1pT0Nw1ClSpVUqVIlDR06VCEhIVq9erXGjx8vf39/SdK7776rnj17qlKlSvGO79evn+bPn293HKtXr1ZwcPRFP3DgQKL3uI1t4cKF8QaPN23apAEDBiRY3tfXV35+fimO6d1339XKlSt18eJFTZs2Td27d1f16tWTPObGjRsprj+2oKCgVB0HPC5iklaSlDdv3lTVER7+942FIyMj7Y4JcISUtD0k2h+0P/5G+wMAAMC5SF4DAADApbi5Gerv66YZa6MSLdPP1y3ZgWNX8vDhQz18+FBS9KynpO5t6OnpqV69eumFF17Qs88+qx07digiIkI//PCD3n333TSLMfaSnSm1b98+nT59WuXLl0+DiKTcuXPryy+/1HPPPafw8HD94x//0M6dO5Oc0RQRESFJ8vHx0WeffZbic9WoUcPueIGMrFixYtb2n3/+mao6YmYeSlLRokXtjglIT7Q/aH/EoP0BAADgXCSvXcTVq1dVtWrVBPcNHTpUQ4cOTeeIAAAAnKd+eUMjnnPTPL8o3f57MqAK5ooeOK5fPuMMHEvS7Nmz9dZbb0mSfvvtNzVq1CjZY3LkyKFZs2ZZy/ceO3YszeK7ceOGNmzYIEkqXbq0Zs2alWT5n376SYsXL5YkLVq0SOPHj7f29e/fX/3793dYbO3atVPPnj21ePFi7d69W59//rmGDRuWaPkCBQpIkm7fvq1nn33WYXEg7c2ZM0dz5sxJcN/Vq1fTOZrMp3Hjxtb24sWLNXnyZJtmYN+9e1dbt261nterV8+h8WUU9O0zNtoftD9i0P4AAACwnaP69SSvXUSRIkXStEMAAACQ0dQvb6h6SUMDv4xednNURyNFS3W6otgzEA8fPpyiwWNJKleunLUdFZX4TDB7LV261Jox1Lt3b73wwgtJli9evLg1eLxw4UKNGzcuRct8ptasWbO0ceNG3b59W2PGjFHHjh0TLVujRg3t2bNHt27d0tWrV1WkSJFEyx4/flznz5+XYRhq06ZNmr4HJC+pxF6JEiUUGBiYzhFlLmXKlFGDBg20d+9eXb9+Xb1799ayZcuUI0eOZI8NDw/Xiy++qBs3bsgwDFWuXDnO/a8zE/r2GR/tD9ofMWh/AAAA2MZR/frE1wsCAAAAnCz2QHEV74w5cCxJTZs2tbbnz59vDdQm5/Dhw9Z2xYoVHR5XjNhLdvbq1SvZ8vXq1VPp0qUlSSdOnNChQ4fSLDYpOhk0Y8YMSVJwcLBeffVVmWbC9xJt3bq1tT19+vRE64yIiFD79u3Vtm1bvf/++wwcA5JmzJhhfbc2bNigChUqaPr06bpz506C5R8+fKgvv/xSlSpV0po1a6zX33///fQIF0gztD9of0i0PwAAAJyF5DUAAADSXD5PqUsDQ/k8M8d5H1WqVCk1b95ckrR7925NmjQp0cHPGGFhYRo3bpz1vHv37mkS27lz57Rr1y5JUrVq1VJ070XDMOLEs3DhwjSJLbZ+/fqpZcuWkqR169YlOhPshRdeUMmSJSVJn376qVatWhWvjGmaeuutt3TmzBlJSnKZ0ZCQkET3AY+bRo0axUlgX7p0SW+//bYKFy6sUqVKqXHjxurWrZtat26tihUrKk+ePBo6dKjOnTtn1TFs2LAkZycC6cWZbQDaH8mj/UH7AwCA5NwOMXX2mu2P2yFJt3fg+lg2HAAAAGkuv6ehbg3Tf2aJs86bkJkzZ6pRo0a6f/++3nvvPW3dulXvvfeeGjRooJw5c1rlwsPDtWbNGn344Yf63//+Jyl64LRu3bppElfsgd+UzHqK0b17d3344YeSou87OW3aNLm5pd1vYw3D0JdffqkaNWrowYMHiZbLmjWr5s6dqzZt2ig8PFwvvPCCOnfuLF9fX5UsWVIBAQFasGCB9u7dK0lq3769XnzxxXj1eHhEd5W2b9+utWvXysvLSz4+PtY9LYHH1b/+9S8VKFBAw4cPV1BQkEzTVGRkpAICAuIt8WaapjVr0M3NTePHj49zD1rAmZzZBqD9kTzaH7Q/AABIzuYjppbvsT0R3aWB67TFkDokrwEAAIB08MQTT2jVqlXq1q2bgoKC9L///U8tWrSQJBUrVkxeXl66du2arl69GmdWT+fOnfXVV1+lSUymacZZsrNnz54pPvbJJ59U2bJldfbsWQUEBGjXrl16+umn0yJMS/ny5TV58mSNGjUqyXKtWrXSsmXL9NJLLykkJEQrVqzQihUr4pVr166dFi1aZA0Ux1a/fn35+/vr+vXrat++vSRp27ZtatasmUPeC+DKXnrpJbVp00Zz5szRvHnzdOnSJUlKcMZm9uzZ1bNnT73xxhuqXr16eocKIBm0P+xH+wMAAOdoVcNQ3XJxk9BhEaYmLY3ul0zqZiibR/wktbNXv4H9WDYcAAAASCetW7fWsWPH9Morryh37tzW65cvX9ahQ4d0+fJla+C4QYMG+umnn7Rs2TJly5YtTeI5fPiwjh07Jil6sNTHxyfFxzpj6U5JeuONN1SrVq1ky3Xu3Fn+/v4aO3as6tSpo7x58ypHjhyqXr26unXrpm3btmnt2rXKlStXgsd/8skn6tmzpwoVKqRs2bKpdOnSiZYFHkdFixbVlClTFBAQoL/++kuLFi3S7NmzNWXKFH300UeaO3eu9uzZozt37ujbb78lcQ24MNof9qP9AQBA+svvaaisV9xHmcJ/J6vLFI6/v6yXofyezLrO6AwzuZvdIE2VKFFCgYGB8vb2VkBAgLPDAQAAcCkPwk31/zx6MHX+EDdlz/L4dEDCwsJ09uxZ63H79m3lyZNHpUqVUr169VS8eHFnhwi4DPpNcHV8Rh8vtD8AAMDjKqO3czJ6/JmZLX0mlg0HAAAAnCBbtmyqXLmyKleu7OxQAABAJkH7AwAAAK6O5DUAAAAAAJnEjh074jxv2rSpkyIBAAAAACA+hyavd+7cqV9++UUHDhxQSEiIzccbhqEtW7Y4MiQAAABkELdDTN15pAkZFvH3HW7OXTeVLYHWaz5PcT8jAEihZs2ayTCi/2YahqGIiAhrX7ly5RxyDsMw5O/v75C6gLRG+wMAAABwLQ5JXkdERGjUqFGaNWtWquswTdPqQAMAACDz2XzE1PI9ZqL7Jy01JcXf36WBoW4NaUcCgC1MM/7f03PnztndL6dvj4yG9gcAAADgWhySvJ4zZ45mzpwpKfoX1gl1ggEAAICktKphqG452weB83mmQTAA8BhLqs9Ofx6ZDe0PAAAAwLXYnby+d++epkyZEmfZscGDB8vX11dFixblF9cAAABIkfyehvIzEAwAaWrixImJ7jt79mw6RgK4BtofAAAAgGuxO3l98OBB3bp1S1J04nrdunVq06aN3YEBAAAAAADHSip5Xbp06XSMBAAAAACA+NzsreDUqVOSohPXL7zwAolrAAAAAAAAAAAAAIDN7J55HTPrWpIaNmxob3UAAAAAACANjBkzRleuXJGXl5emTZsWb//AgQMlKdH9AAAAAACkNbuT1yVLlrS2s2TJYm91AAAAAAAgDXzxxRe6e/euSpQokWByev78+TIMQz4+PiSvAQAAAABOYfey4Q0bNpRhGJKkPXv22B0QAAAAAABwPHd3d5mmqcDAQF24cMHZ4QAAAAAAEI/dM6/LlCmj559/XqtWrdIvv/yigIAAlShRwhGxAQAAAAAAB6lWrZp27twp0zTVuHFjde/eXXnz5o1X7tatW3rnnXfsOteECRPsOh4AAAAAkDnZnbyWpK+//lqHDx/W2bNn1bVrV23btk05cuRwRNUAAAAAAMABhg8frl9//VWGYejSpUuaNWtWvDKmaer27duaPHmyXecieQ0AAAAgM7t946pCbl2z+TjPAl7KX6hIGkSUcTgkeV2oUCFt2bJFvXr10p49e1SuXDmNHz9effv2VZ48eRxxCgAAAAAAYIfOnTtrypQpevfddxUWFpZoOdM07TpPzK3FAAAAACCzuvjbQlW6Ptvm404Wfl35n38jDSLKOBySvB4zZowkqXHjxjp58qSuXr2qYcOGadiwYSpUqJDKlSuXopnYhmFoy5YtjggJAAAAAAA8YuzYserXr592796tv/76Sw8fPrT2TZ48WYZhKH/+/Bo2bJgTowQAAACAjK3kU711/VarOK+FP7yv4nt6SJIuNfhJWbLGz52WLOCVLvG5Mockr6dNmxbnl9Ux26Zp6vr167px40aydZimya+zAQAAMjEz9JrMUNuXUzJyesnIScMeAFKqRIkS6tq1a7zXY5YKL1CggCZOnJjeYQFOQfsDAAAAaSF/oSLxlv9+EBoi7YneLlaumrLn9HRCZK7PIclrKellxexdcgwAAACPv8gTCxV54BObj3OvPVwedf7l+IAAIBOi/47MhvYHAAAA4Fockrzetm2bI6oBAABAJuZeubfcSsVdTsmMeKCItd0kSR7PLZXhkT3eccx6AgDHiIqKcnYIQLqj/QEAAAC4Fockr319fR1RDQAAADKxhJbfNMNDrW23glVlZMmZ3mEBwGNjzJgxunLliry8vDRt2rR4+wcOHChJKlKkiKZOnZre4QFOQfsDAAAAcC0OWzYcAAAAAAC4ri+++EJ3795ViRIlEkxez58/X4ZhyMfHh+Q1AAAAAMAp3JwdAAAAAJAZ9O/fX4ZhJPnw9PRUnTp11Lt3b61bt87ZIaeZmASZYRg6d+6cs8MBMg13d3eZpqnAwEBduHDB2eEASAe0P/5G+wMAACBjSLOZ1zdu3NDevXt16NAh3bp1S0FBQfL09FSBAgVUvXp1NWrUSEWLFk2r0wMAAAAZTmhoqA4cOKADBw5o0aJFateunb7//nsVLFjQ2aGlG8MwrO2zZ8+qTJkyzgsGeMxUq1ZNO3fulGmaaty4sbp37668efPGK3fr1i298847dp1rwoQJdh0PIP3Q/qD9AQAA4EocnrzevHmzZsyYoY0bNyZbtmXLlnrrrbfUunVrR4cBAAAAuKz58+erSJEicV6LjIxUYGCgjh8/rm+//Vb37t3TunXrNHjwYC1btizOoCoApMbw4cP166+/yjAMXbp0SbNmzYpXxjRN3b59W5MnT7brXCSvAddD+wMAAAAZgcOS1+Hh4frnP/+p+fPnS4ru8CZny5Yt2rJliwYNGqQ5c+YoS5YsjgoHAAAAcFm+vr5JzugZN26cnnrqKZ06dUorVqzQ+vXr1a5du/QLEMBjqXPnzpoyZYreffddhYWFJVouJf35pJDsAlwT7Q8AAABkBA5JXpumqT59+mj58uVxOrkFCxZUxYoVVbp0aRUvXlzXr1/XmTNndOrUKV2/ft069ttvv1VISIh+/PFHR4STIV29elVVq1ZNcN/QoUM1dOjQdI4IAADAcczQa4o8sVDulXvLyOn12J/XXgULFtSMGTPUvn17SdLOnTszzeCxvUkzZFxz5szRnDlzEtx39erVdI7m8TV27Fj169dPu3fv1l9//aWHDx9a+yZPnizDMJQ/f34NGzbMiVFmXPTtXYcz2wC0PzIe2h8AAAD2c1S/3iHJ6wULFsRZSqhq1aoaNWqUevXqJQ+P+KeIjIzUokWL9P777+vEiRMyTVOLFy9W+/bt1atXL0eElOEUKVJEx44dc3YYAAAAacIMvabIA5/IrVSr9E9eO+G8jlCvXj1r+8iRI06MBEgfSSX2SpQoocDAwHSO6PFVokQJde3aNd7rMUuFFyhQQBMnTkzvsB4L9O1dhzPbALQ/AAAAkBk5ql/v5ohgJk2aZG136dJFBw8e1Isvvphg4lqS3N3d1bdvXx06dEgdO3aUFP0LR+6JBQAAgNjMqEhrO+rK3jjPH3exl93NnTt3gmWOHj2qf/zjH3ryySdVpEgRZcuWTWXKlFHjxo31wQcf6MaNG0me4/r16xo7dqyefvppeXt7K0eOHKpcubLat2+vNWvWJDsLKTg4WB999JGaNGmiwoULK3v27KpQoYI6duyo1atXKzLS9n+vZs2ayTAMNWvWLN4+wzBkGIaWLVsmSTpw4ID69OmjUqVKWefu0qWL9u/fn+x5zp8/r7feeks1a9ZU3rx5lTt3btWoUUMvv/yyfv/9d5vjBh4XzD4EaH/EoP0RjfYHAABA+rJ75vWff/6ps2fPyjAMeXl5ae7cuYkmrR+VJUsWfffddypfvrxu3LihM2fO6M8//1S1atXsDQsAAAAZXOS5DYr43yTrecQvAyTPovJoOFHuZZ51XmDpJPYAZuxZUFJ0culf//qXZs+eHe+48+fP6/z58/rtt9/03nvv6ddff9UTTzwRr9zKlSvVt29fhYaGxnn95MmTOnnypNauXasOHTrov//9r9zc4v/mdffu3erUqZOuXLkS5/XTp0/r9OnTWr16tRo1aqQVK1aoaNGiNr33lFi4cKEGDBgQZ8njmHOvWLFCX331lQYPHpzgsV999ZWGDx8e756/R48e1dGjR/Xtt9/qlVde0ezZs5U1a1aHxw64qqioKGeHADgd7Q/aH0mh/QEAAJD27E5ex/5VYffu3RP9VWZi8uTJo+bNm2vp0qWSohvJJK8BAAAyt8hzGxSxZYikR2behFyNfr3l54/1APKtW7c0YsQISVL+/PnVr1+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+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pur_eff_w_dict(plot_dict, target_path, save_path=\"/Users/billyli/Documents/SPANet/SPANet_results/HHH/B+R/\", proj_name=date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef735eb3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/benchmark/west/trained_on_hhh_B+R_infer_on_QCD.ipynb b/notebooks/benchmark/west/trained_on_hhh_B+R_infer_on_QCD.ipynb
new file mode 100644
index 0000000..c4588d7
--- /dev/null
+++ b/notebooks/benchmark/west/trained_on_hhh_B+R_infer_on_QCD.ipynb
@@ -0,0 +1,533 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "50cb9178",
+   "metadata": {},
+   "source": [
+    "Side note: we are evaluating particle level information\n",
+    "maybe we should also do the event level information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "59c80b94",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-12-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "date = datetime.today().strftime('%Y-%m-%d')\n",
+    "print(date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "959f4f4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "dask-awkward 2024.7.0 requires awkward>=2.5.1, but you have awkward 1.10.5 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -e ../../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "ebf6c5df",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.7.1 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "26570c5c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/envs/spanet/lib/python3.11/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import logging\n",
+    "from pathlib import Path\n",
+    "import numba as nb\n",
+    "\n",
+    "import awkward as ak\n",
+    "import click\n",
+    "import h5py as h5\n",
+    "import numpy as np\n",
+    "import vector\n",
+    "\n",
+    "from coffea.hist.plot import clopper_pearson_interval\n",
+    "import matplotlib.pyplot as plt\n",
+    "import mplhep as hep\n",
+    "hep.style.use(\"CMS\")\n",
+    "\n",
+    "# from src.data.cms.convert_to_h5 import MIN_JETS, N_JETS, N_FJETS\n",
+    "\n",
+    "vector.register_awkward()\n",
+    "\n",
+    "logging.basicConfig(level=logging.INFO)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "885cebd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# read spanet prediction\n",
+    "# spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/qcd/qcd_finetune_i0_llow_pt.h5\"\n",
+    "# s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "# spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/qcd/qcd_finetune_i0_llow_pt.h5\"\n",
+    "# s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/072324/072324_v10_qcd.h5\"\n",
+    "s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "# read baseline prediction\n",
+    "# baseline_file = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/060524/060524_v4_qcd.h5\"\n",
+    "# b_h5 = h5.File(baseline_file)\n",
+    "baseline_file = \"//Users/billyli/UCSD/hhh/reports/bv2/pred_baseline_on_qcd_new.h5\"\n",
+    "b_h5 = h5.File(baseline_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53e6d6f2",
+   "metadata": {},
+   "source": [
+    "### Reco Boosted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "561105c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from src.analysis.utils import calc_eff, calc_pur, reset_collision_dp, dp_to_HiggsNumProb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "39e446bc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from src.analysis.boosted import sel_pred_bH_by_dp_ap, sel_target_bH_by_mask, gen_pred_bH_LUT, gen_target_bH_LUT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "df848618",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generate pred/target LUT\n",
+    "# each entry corresponds to [recoH correct or not, reco H pt]\n",
+    "# or \n",
+    "# [targetH retrieved or not, target H pt]\n",
+    "def get_reco_boosted_h_mass(predfile):\n",
+    "    # Collect H pt, mask, target and predicted jet and fjets for 3 Hs in each event\n",
+    "    if 'TARGETS' not in predfile.keys():\n",
+    "        predfile[\"INPUTS\"] = predfile[\"SpecialKey.Inputs\"]\n",
+    "        predfile[\"TARGETS\"] = predfile[\"SpecialKey.Targets\"]\n",
+    "\n",
+    "    try:\n",
+    "        # pred assignment\n",
+    "        bb_bh1_p = np.array(predfile[\"TARGETS\"][\"bh1\"]['bb'])\n",
+    "        bb_bh2_p = np.array(predfile[\"TARGETS\"][\"bh2\"]['bb'])\n",
+    "        bb_bh3_p = np.array(predfile[\"TARGETS\"][\"bh3\"]['bb'])\n",
+    "    \n",
+    "        # boosted Higgs detection probability\n",
+    "        dp_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['detection_probability'])\n",
+    "        dp_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['detection_probability'])\n",
+    "        dp_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['detection_probability'])\n",
+    "\n",
+    "        # fatjet assignment probability\n",
+    "        ap_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['assignment_probability'])\n",
+    "        ap_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['assignment_probability'])\n",
+    "        ap_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['assignment_probability'])\n",
+    "    except:\n",
+    "        # pred assignment\n",
+    "        bb_bh1_p = np.array(predfile[\"TARGETS\"][\"bh1\"]['bb'])+10\n",
+    "        bb_bh2_p = np.array(predfile[\"TARGETS\"][\"bh2\"]['bb'])+10\n",
+    "        bb_bh3_p = np.array(predfile[\"TARGETS\"][\"bh3\"]['bb'])+10\n",
+    "    \n",
+    "         # boosted Higgs detection probability\n",
+    "        dp_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['mask']).astype('float')\n",
+    "        dp_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['mask']).astype('float')\n",
+    "        dp_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['mask']).astype('float')\n",
+    "\n",
+    "        # fatjet assignment probability\n",
+    "        ap_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['mask']).astype('float')\n",
+    "        ap_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['mask']).astype('float')\n",
+    "        ap_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['mask']).astype('float')\n",
+    "    \n",
+    "    # collect fatjet pt\n",
+    "    fj_pt = np.array(predfile['INPUTS']['BoostedJets']['fj_pt'])\n",
+    "    \n",
+    "    dps = np.concatenate((dp_bh1.reshape(-1, 1), dp_bh2.reshape(-1, 1), dp_bh3.reshape(-1, 1)), axis=1)\n",
+    "    aps = np.concatenate((ap_bh1.reshape(-1, 1), ap_bh2.reshape(-1, 1), ap_bh3.reshape(-1, 1)), axis=1)\n",
+    "\n",
+    "    # convert some arrays to ak array\n",
+    "    bb_ps = np.concatenate((bb_bh1_p.reshape(-1, 1), bb_bh2_p.reshape(-1, 1), bb_bh3_p.reshape(-1, 1)), axis=1)\n",
+    "    bb_ps = ak.Array(bb_ps)\n",
+    "    fj_pt = ak.Array(fj_pt)\n",
+    "    \n",
+    "    # select predictions and targets\n",
+    "    bb_ps_selected = sel_pred_bH_by_dp_ap(dps, aps, bb_ps)\n",
+    "    \n",
+    "    # reconstruct bH to remove overlapped ak4 jets\n",
+    "    fj_eta = np.array(predfile['INPUTS']['BoostedJets']['fj_eta'])\n",
+    "    fj_phi = np.array(predfile['INPUTS']['BoostedJets']['fj_phi'])\n",
+    "    fj_mass = ak.Array(predfile['INPUTS']['BoostedJets']['fj_mass'])\n",
+    "    \n",
+    "    fjs = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": fj_pt,\n",
+    "            \"eta\": fj_eta,\n",
+    "            \"phi\": fj_phi,\n",
+    "            \"mass\": fj_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\"\n",
+    "    )\n",
+    "    fj_reco = fjs[bb_ps_selected-10]\n",
+    "    \n",
+    "    return fj_mass[bb_ps_selected-10], fj_reco"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "27c759a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_bh_mass_s, fjs_reco_s = get_reco_boosted_h_mass(s_h5)\n",
+    "reco_bh_mass_b, fjs_reco_b = get_reco_boosted_h_mass(b_h5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c6b1ee99",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(ak.ravel(reco_bh_mass_s), bins=np.arange(105, 150, 2.5), histtype='step', label='SPANet', density=True)\n",
+    "plt.hist(ak.ravel(reco_bh_mass_b), bins=np.arange(105, 150, 2.5), histtype='step', label='Baseline', density=True)\n",
+    "plt.xlabel('Mass (GeV)')\n",
+    "plt.legend(title='Boosted')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "0ed4bf55",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from src.analysis.resolved import (\n",
+    "    get_unoverlapped_jet_index,\n",
+    "    sel_pred_h_by_dp_ap,\n",
+    "    sel_target_h_by_mask,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "a6788f6f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A pred look up table is in shape\n",
+    "# [event,\n",
+    "#    pred_H, \n",
+    "#       [correct_or_not, pt, overlap_w_H_reco, has_boost_H_target, which_H_target]]\n",
+    "@nb.njit\n",
+    "def calc_reco_h_mass(b1_ps_passed, b2_ps_passed, js, goodJetIdx, builder):\n",
+    "    # for each event\n",
+    "    for b1_ps_e, b2_ps_e, jets_e, goodJetIdx_e in zip(b1_ps_passed, b2_ps_passed, js, goodJetIdx):\n",
+    "        # for each predicted bb assignment, check if any target H have a same bb assignment\n",
+    "        builder.begin_list()\n",
+    "        for b1_p, b2_p in zip(b1_ps_e, b2_ps_e):\n",
+    "            if (b1_p in goodJetIdx_e) and (b2_p in goodJetIdx_e):\n",
+    "                overlap = 0\n",
+    "            else:\n",
+    "                overlap = 1\n",
+    "                continue\n",
+    "                \n",
+    "            predH_mass = (jets_e[b1_p]+jets_e[b2_p]).mass\n",
+    "                    \n",
+    "            builder.append(predH_mass)\n",
+    "        \n",
+    "        builder.end_list()\n",
+    "    return builder"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "44e959b5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_reco_resolved_h_mass(predfile, fjs_reco=None):\n",
+    "    if 'TARGETS' not in predfile.keys():\n",
+    "        predfile[\"INPUTS\"] = predfile[\"SpecialKey.Inputs\"]\n",
+    "        predfile[\"TARGETS\"] = predfile[\"SpecialKey.Targets\"]\n",
+    "    \n",
+    "    # predict assignments\n",
+    "    b1_h1_p = np.array(predfile[\"TARGETS\"][\"h1\"]['b1']).astype('int')\n",
+    "    b1_h2_p = np.array(predfile[\"TARGETS\"][\"h2\"]['b1']).astype('int')\n",
+    "    b1_h3_p = np.array(predfile[\"TARGETS\"][\"h3\"]['b1']).astype('int')\n",
+    "\n",
+    "    b2_h1_p = np.array(predfile[\"TARGETS\"][\"h1\"]['b2']).astype('int')\n",
+    "    b2_h2_p = np.array(predfile[\"TARGETS\"][\"h2\"]['b2']).astype('int')\n",
+    "    b2_h3_p = np.array(predfile[\"TARGETS\"][\"h3\"]['b2']).astype('int')\n",
+    "    \n",
+    "    # resolved Higgs detection probability\n",
+    "    dp_h1 = np.array(predfile[\"TARGETS\"][\"h1\"]['detection_probability'])\n",
+    "    dp_h2 = np.array(predfile[\"TARGETS\"][\"h2\"]['detection_probability'])\n",
+    "    dp_h3 = np.array(predfile[\"TARGETS\"][\"h3\"]['detection_probability'])\n",
+    "    \n",
+    "    # ak4 jets assignment probability\n",
+    "    ap_h1 = np.array(predfile[\"TARGETS\"][\"h1\"]['assignment_probability'])\n",
+    "    ap_h2 = np.array(predfile[\"TARGETS\"][\"h2\"]['assignment_probability'])\n",
+    "    ap_h3 = np.array(predfile[\"TARGETS\"][\"h3\"]['assignment_probability'])\n",
+    "    \n",
+    "    # reconstruct jet 4-momentum objects\n",
+    "    j_pt = np.array(predfile['INPUTS']['Jets']['pt'])\n",
+    "    j_eta = np.array(predfile['INPUTS']['Jets']['eta'])\n",
+    "    j_phi = np.array(predfile['INPUTS']['Jets']['phi'])\n",
+    "    j_mass = np.array(predfile['INPUTS']['Jets']['mass'])\n",
+    "    js = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": j_pt,\n",
+    "            \"eta\": j_eta,\n",
+    "            \"phi\": j_phi,\n",
+    "            \"mass\": j_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\"\n",
+    "    )\n",
+    "    \n",
+    "    # convert some numpy arrays to ak arrays\n",
+    "    dps = np.concatenate((dp_h1.reshape(-1, 1), dp_h2.reshape(-1, 1), dp_h3.reshape(-1, 1)), axis=1)\n",
+    "    # dps = ak.Array(dps)\n",
+    "    aps = np.concatenate((ap_h1.reshape(-1, 1), ap_h2.reshape(-1, 1), ap_h3.reshape(-1, 1)), axis=1)\n",
+    "    # aps = ak.Array(aps)\n",
+    "    \n",
+    "    dps = reset_collision_dp(dps, aps)\n",
+    "    \n",
+    "    b1_ps = np.concatenate((b1_h1_p.reshape(-1, 1), b1_h2_p.reshape(-1, 1), b1_h3_p.reshape(-1, 1)), axis=1)\n",
+    "    b1_ps = ak.Array(b1_ps)\n",
+    "    b2_ps = np.concatenate((b2_h1_p.reshape(-1, 1), b2_h2_p.reshape(-1, 1), b2_h3_p.reshape(-1, 1)), axis=1)\n",
+    "    b2_ps = ak.Array(b2_ps)\n",
+    "\n",
+    "    \n",
+    "    # select predictions and targets\n",
+    "    b1_ps_selected, b2_ps_selected = sel_pred_h_by_dp_ap(dps, aps, b1_ps, b2_ps)\n",
+    "\n",
+    "    # find jets that are overlapped with reco boosted Higgs\n",
+    "    if fjs_reco is None:\n",
+    "        goodJetIdx =  ak.local_index(js)\n",
+    "    else:\n",
+    "        goodJetIdx = get_unoverlapped_jet_index(fjs_reco, js, dR_min=0.4)\n",
+    "    \n",
+    "    # get reco H mass\n",
+    "    h_mass = calc_reco_h_mass(b1_ps_selected, b2_ps_selected, js, goodJetIdx, ak.ArrayBuilder()).snapshot()\n",
+    "    \n",
+    "    return h_mass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "3eb50b68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_rh_mass_s = get_reco_resolved_h_mass(s_h5, fjs_reco=None)\n",
+    "reco_rh_mass_b = get_reco_resolved_h_mass(b_h5, fjs_reco=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "352cf694",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(1, 0, 'Mass (GeV)')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(ak.ravel(reco_rh_mass_s), bins=np.arange(30, 230, 5), histtype='step', label='SPANet', density=True)\n",
+    "plt.hist(ak.ravel(reco_rh_mass_b), bins=np.arange(30, 230, 5), histtype='step', label='Baseline', density=True)\n",
+    "plt.legend(title='Resolved')\n",
+    "plt.xlabel('Mass (GeV)')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "37c76ea3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_rh_wOR_mass_s = get_reco_resolved_h_mass(s_h5, fjs_reco=fjs_reco_s)\n",
+    "reco_rh_wOR_mass_b = get_reco_resolved_h_mass(b_h5, fjs_reco=fjs_reco_b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "610e5557",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_merged_h_mass_s = ak.ravel(reco_bh_mass_s).tolist() + ak.ravel(reco_rh_wOR_mass_s).tolist()\n",
+    "reco_merged_h_mass_b = ak.ravel(reco_bh_mass_b).tolist() + ak.ravel(reco_rh_wOR_mass_b).tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "ad6d6b54",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(reco_merged_h_mass_s, bins=np.arange(30, 230, 5), histtype='step', label='SPA-Net', density=True)\n",
+    "plt.hist(reco_merged_h_mass_b, bins=np.arange(30, 230, 5), histtype='step', label='Baseline', density=True)\n",
+    "plt.legend(title='Boosted+Resolved')\n",
+    "plt.xlabel('Mass (GeV)')\n",
+    "plt.savefig(f\"/Users/billyli/Documents/SPANet/SPANet_results/HHH/B+R/{date}_mass_sculpting.pdf\", format='pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "224211c2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5b5b9548",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/benchmark/west/trained_on_hhh_resolved.ipynb b/notebooks/benchmark/west/trained_on_hhh_resolved.ipynb
new file mode 100644
index 0000000..c06750e
--- /dev/null
+++ b/notebooks/benchmark/west/trained_on_hhh_resolved.ipynb
@@ -0,0 +1,364 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8e9bdd45",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-12-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "date = datetime.today().strftime('%Y-%m-%d')\n",
+    "print(date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8cab1016",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "dask-awkward 2024.7.0 requires awkward>=2.5.1, but you have awkward 1.10.5 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -e ../../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "55c3de67",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.7.1 which is incompatible.\u001b[0m\u001b[31m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d9834679",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py as h5\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import mplhep as hep\n",
+    "hep.style.use(\"CMS\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2a4ffe9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/envs/spanet/lib/python3.11/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from src.analysis.resolved import parse_resolved_w_target\n",
+    "from src.analysis.utils import calc_eff, calc_pur "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3d305b85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_path = '/Users/billyli/UCSD/hhh/reports/bv2/data/hhh_test.h5'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0e916bd5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "baseline_path = \"/Users/billyli/UCSD/hhh/reports/bv2/pred_baseline_bdt_loose_west.h5\"\n",
+    "r_path = \"/Users/billyli/UCSD/hhh/reports/benchmark/HHH_resolved/1118.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "69ffab6c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "baseline_h5 = h5.File(baseline_path, \"a\")\n",
+    "r_h5 = h5.File(r_path, \"a\")\n",
+    "target_h5 = h5.File(target_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "b04c4c08",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if \"TARGETS\" not in r_h5.keys():\n",
+    "    r_h5[\"INPUTS\"] = r_h5[\"SpecialKey.Inputs\"]\n",
+    "    r_h5[\"TARGETS\"] = r_h5[\"SpecialKey.Targets\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0a50300b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "LUT_resolved_pred_bl, LUT_resolved_target_bl, _ = parse_resolved_w_target(target_h5, baseline_h5, fjs_reco=None) \n",
+    "LUT_resolved_pred_r, LUT_resolved_target_r, _ = parse_resolved_w_target(target_h5, r_h5, fjs_reco=None) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "c56eac5c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bins = np.arange(0, 1050, 50)\n",
+    "plot_bins = np.append(bins, 2 * bins[-1] - bins[-2]) \n",
+    "bin_centers = [(plot_bins[i] + plot_bins[i + 1]) / 2 for i in range(plot_bins.size - 1)] \n",
+    "xerr = (plot_bins[1] - plot_bins[0]) / 2 * np.ones(plot_bins.shape[0] - 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "003cea2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bl_eff, bl_eff_err, bl_avg_eff, bl_n_reco_target = calc_eff(None, LUT_resolved_target_bl, bins)\n",
+    "bl_pur, bl_pur_err, bl_avg_pur, bl_n_correct_pred = calc_pur(None, LUT_resolved_pred_bl, bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "f0a447ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_eff, r_eff_err, r_avg_eff, r_n_reco_target = calc_eff(None, LUT_resolved_target_r, bins)\n",
+    "r_pur, r_pur_err, r_avg_pur, r_n_correct_pred = calc_pur(None, LUT_resolved_pred_r, bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f69ff1c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(-0.1, 1.1)]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig_r, ax_r = plt.subplots(1, 2, figsize=(24, 10))\n",
+    "ax_r[0].set(\n",
+    "          xlabel=r\"Reco. H $p_\\mathrm{T}$ (GeV)”\",\n",
+    "          ylabel=r\"Reconstruction Purity\",\n",
+    "#           title=f\"Reconstruction Purity vs. Reco Resolved H pT\",\n",
+    ")   \n",
+    "ax_r[1].set(\n",
+    "          xlabel=r\"Gen. H $p_\\mathrm{T}$ (GeV)\",\n",
+    "          ylabel=r\"Reconstruction Efficiency\",\n",
+    "#           title=f\"Reconstruction Efficiency vs. Gen Resolved H pT\",\n",
+    ")   \n",
+    "\n",
+    "ax_r[0].errorbar(\n",
+    "           x=bin_centers, y=r_pur, xerr=xerr, yerr=r_pur_err, fmt=\"o\", capsize=5, label='SPA-Net'\n",
+    ")\n",
+    "ax_r[1].errorbar(\n",
+    "            x=bin_centers, y=r_eff, xerr=xerr, yerr=r_eff_err, fmt=\"o\", capsize=5, label='SPA-Net'\n",
+    ")\n",
+    "\n",
+    "ax_r[0].errorbar(\n",
+    "           x=bin_centers, y=bl_pur, xerr=xerr, yerr=bl_pur_err, fmt=\"o\", capsize=5, label='Baseline'\n",
+    ")\n",
+    "ax_r[1].errorbar(\n",
+    "            x=bin_centers, y=bl_eff, xerr=xerr, yerr=bl_eff_err, fmt=\"o\", capsize=5, label='Baseline'\n",
+    ")\n",
+    "\n",
+    "\n",
+    "\n",
+    "ax_r[0].legend(title='HHH Resolved')\n",
+    "ax_r[1].legend(title='HHH Resolved')\n",
+    "ax_r[0].set(ylim=[-0.1, 1.1])\n",
+    "ax_r[1].set(ylim=[-0.1, 1.1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4be0a2b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig_r.savefig(f\"/Users/billyli/Documents/SPANet/SPANet_results/HHH/R/{date}_west.pdf\", format='pdf')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "ef735eb3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "HHH Resolved SPANet Average purity: 0.4300759648237076\n",
+      "HHH Resolved Baseline Average purity: 0.2507880174648019\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"HHH Resolved SPANet Average purity:\", r_avg_pur)\n",
+    "print(\"HHH Resolved Baseline Average purity:\", bl_avg_pur)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "736c876e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "HHH Resolved SPANet Average efficiency: 0.44774477447744776\n",
+      "HHH Resolved Baseline Average efficiency: 0.3938760542720939\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"HHH Resolved SPANet Average efficiency:\", r_avg_eff)\n",
+    "print(\"HHH Resolved Baseline Average efficiency:\", bl_avg_eff)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "2056dfef",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Number of correct Higgs candidate predictions: 36630.0\n",
+      "Baseline Number of correct Higgs candidate predictions: 32223.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Number of correct Higgs candidate predictions:\", r_n_correct_pred)\n",
+    "print(\"Baseline Number of correct Higgs candidate predictions:\", bl_n_correct_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "b3189a5d-a2de-4a0f-8373-3fac2607dbe6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SPANet Number of reconstructed Higgs targets: 36630.0\n",
+      "Baseline Number of reconstructed Higgs targets: 32223.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"SPANet Number of reconstructed Higgs targets:\", r_n_reco_target)\n",
+    "print(\"Baseline Number of reconstructed Higgs targets:\", bl_n_reco_target)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/dev/mix_basline_bdt.ipynb b/notebooks/dev/mix_basline_bdt.ipynb
index 6fdce27..9b88a65 100644
--- a/notebooks/dev/mix_basline_bdt.ipynb
+++ b/notebooks/dev/mix_basline_bdt.ipynb
@@ -660,7 +660,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/dev/mix_basline_sota.ipynb b/notebooks/dev/mix_basline_sota.ipynb
index 7aeb0dd..d64e327 100644
--- a/notebooks/dev/mix_basline_sota.ipynb
+++ b/notebooks/dev/mix_basline_sota.ipynb
@@ -502,7 +502,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/example_plot_higgs_metrics.ipynb b/notebooks/example_plot_higgs_metrics.ipynb
new file mode 100644
index 0000000..33b04a8
--- /dev/null
+++ b/notebooks/example_plot_higgs_metrics.ipynb
@@ -0,0 +1,179 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8cab1016",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install -e ../../. --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "55c3de67",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\r\n",
+      "coffea 0.7.20 requires awkward<2,>=1.5.1, but you have awkward 2.6.6 which is incompatible.\u001b[0m\u001b[31m\r\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --upgrade awkward --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2a4ffe9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/lib/python3.9/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from src.analysis.plot import plot_pur_eff_w_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3d305b85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_path = '/Users/billyli/UCSD/hhh/reports/bv2/data/hhh_test.h5'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "0e916bd5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_dict = {}\n",
+    "plot_dict['0723_v10'] = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/072324/072324_v10.h5\"\n",
+    "plot_dict['bdt_loose'] = \"/Users/billyli/UCSD/hhh/reports/bv2/pred_baseline_bdt_loose.h5\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4be0a2b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing 0723_v10\n",
+      "Average purity:\n",
+      "merged 0.4079620482222331 boosted 0.5942420868458724 resolved 0.40202564893394754\n",
+      "Average efficiency:\n",
+      "merged 0.5062963581292185 boosted 0.8696461824953445 resolved 0.4939249480503606\n",
+      "Number of Boosted Prediction: 12574\n",
+      "Number of Resolved Prediction before OR: 100511\n",
+      "Number of Resolved Prediction after OR: 89661\n",
+      "Processing bdt_loose\n",
+      "Average purity:\n",
+      "merged 0.2603789454010233 boosted 0.8507501974203738 resolved 0.2507880174648019\n",
+      "Average efficiency:\n",
+      "merged 0.3671325335686518 boosted 0.3761638733705773 resolved 0.3938760542720939\n",
+      "Number of Boosted Prediction: 3799\n",
+      "Number of Resolved Prediction before OR: 128487\n",
+      "Number of Resolved Prediction after OR: 124610\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pur_eff_w_dict(plot_dict, target_path, save_path=\"/Users/billyli/UCSD/hhh/reports/bv2/merge_all/figures\", proj_name=\"072324_v10_vs_loose\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef735eb3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/example_plot_mass_sculpting.ipynb b/notebooks/example_plot_mass_sculpting.ipynb
new file mode 100644
index 0000000..77083dd
--- /dev/null
+++ b/notebooks/example_plot_mass_sculpting.ipynb
@@ -0,0 +1,656 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Side note: we are evaluating particle level information\n",
+    "maybe we should also do the event level information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/billyli/miniforge_x86_new/lib/python3.9/site-packages/coffea/util.py:154: FutureWarning: In coffea version v0.8.0 (target date: 31 Dec 2022), this will be an error.\n",
+      "(Set coffea.deprecations_as_errors = True to get a stack trace now.)\n",
+      "ImportError: coffea.hist is deprecated\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import itertools\n",
+    "import logging\n",
+    "from pathlib import Path\n",
+    "import numba as nb\n",
+    "\n",
+    "import awkward as ak\n",
+    "import click\n",
+    "import h5py as h5\n",
+    "import numpy as np\n",
+    "import vector\n",
+    "\n",
+    "from coffea.hist.plot import clopper_pearson_interval\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# from src.data.cms.convert_to_h5 import MIN_JETS, N_JETS, N_FJETS\n",
+    "\n",
+    "vector.register_awkward()\n",
+    "\n",
+    "logging.basicConfig(level=logging.INFO)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# read spanet prediction\n",
+    "# spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/qcd/qcd_finetune_i0_llow_pt.h5\"\n",
+    "# s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "# spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/qcd/qcd_finetune_i0_llow_pt.h5\"\n",
+    "# s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "spanet_file = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/082024/082024_wide_v14_qcd.h5\"\n",
+    "s_h5 = h5.File(spanet_file, 'a')\n",
+    "\n",
+    "# read baseline prediction\n",
+    "# baseline_file = \"/Users/billyli/UCSD/hhh/reports/bv2/best_per_week/060524/060524_v4_qcd.h5\"\n",
+    "# b_h5 = h5.File(baseline_file)\n",
+    "baseline_file = \"/Users/billyli/UCSD/hhh/reports/bv2/pred_baseline_on_qcd_test.h5\"\n",
+    "b_h5 = h5.File(baseline_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Reco Boosted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def reset_collision_dp(dps, aps):\n",
+    "    ap_filter = aps < 1/(13*13)\n",
+    "    dps_reset = dps\n",
+    "    dps_reset[ap_filter] = 0\n",
+    "    return dps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dp_to_HiggsNumProb(dps):\n",
+    "    # get maximum number of targets\n",
+    "    Nmax = dps.shape[-1]\n",
+    "    \n",
+    "    # prepare a list for constructing [P_0H, P_1H, P_2H, ...]\n",
+    "    probs = []\n",
+    "    \n",
+    "    # loop through all possible number of existing targets\n",
+    "    for N in range(Nmax+1):\n",
+    "        # get all combinations of targets\n",
+    "        combs = list(itertools.combinations(range(Nmax),N))\n",
+    "    \n",
+    "        # calculate the probability of N particles existing for each combination\n",
+    "        P_exist_per_comb = [np.prod(dps[:,list(comb)], axis=-1) for comb in combs]\n",
+    "        \n",
+    "        # calculate the probability fo Nmax-N particles not existing for each  combination\n",
+    "        P_noexist_per_comb = [np.prod(1- dps[:, list(set(range(Nmax))-set(comb))], axis=-1) for comb in combs]\n",
+    "        \n",
+    "        # concatenate each combination to array for further calculation   \n",
+    "        P_exist_per_comb = [np.reshape(P_comb_e, newshape=(-1,1)) for P_comb_e in P_exist_per_comb]\n",
+    "        P_exist_per_comb = np.concatenate(P_exist_per_comb, axis=1)\n",
+    "        P_noexist_per_comb = [np.reshape(P_comb_e, newshape=(-1,1)) for P_comb_e in P_noexist_per_comb]\n",
+    "        P_noexist_per_comb = np.concatenate(P_noexist_per_comb, axis=1)\n",
+    "        \n",
+    "        # for each combination, calculate the joint probability \n",
+    "        # of N particles existing and Nmax-N not existing\n",
+    "        P_per_comb = P_exist_per_comb * P_noexist_per_comb\n",
+    "        \n",
+    "        # sum over all possible configurations of N existing and Nmax-N not existing\n",
+    "        P = np.sum(P_per_comb, axis=-1)\n",
+    "        \n",
+    "        # reshape and add to the prob list\n",
+    "        probs.append(np.reshape(P, newshape=(-1,1)))\n",
+    "\n",
+    "    # convert the probs list to arr\n",
+    "    probs_arr = np.concatenate(probs, axis=1)\n",
+    "    \n",
+    "    return probs_arr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sel_pred_bH_by_dp_ap(dps, aps, bb_ps):\n",
+    "    # get most possible number of H_reco by dps\n",
+    "    HiggsNumProb = dp_to_HiggsNumProb(dps)\n",
+    "    HiggsNum = np.argmax(HiggsNumProb, axis=-1)\n",
+    "    \n",
+    "    # get the top N (dp x ap) jet assignment indices\n",
+    "    ps = dps*aps\n",
+    "    idx_descend = np.flip(np.argsort(ps, axis=-1), axis=-1)\n",
+    "    idx_sel = [idx_e[:N_e] for idx_e, N_e in zip(idx_descend, HiggsNum)]\n",
+    "    \n",
+    "    # select the predicted bb assignment via the indices\n",
+    "    bb_ps_sel = bb_ps[idx_sel]\n",
+    "    \n",
+    "    # require bb assignment is a fatjet\n",
+    "    ak8Filter = bb_ps_sel>9\n",
+    "    bb_ps_passed = bb_ps_sel.mask[ak8Filter]\n",
+    "    bb_ps_passed = ak.drop_none(bb_ps_passed)\n",
+    "    \n",
+    "    return bb_ps_passed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sel_target_bH_by_mask(bb_ts, bh_pts, bh_masks):\n",
+    "    bb_ts_selected = bb_ts.mask[bh_masks]\n",
+    "    bb_ts_selected = ak.drop_none(bb_ts_selected)\n",
+    "    \n",
+    "    bh_selected_pts = bh_pts.mask[bh_masks]\n",
+    "    bh_selected_pts = ak.drop_none(bh_selected_pts)\n",
+    "    \n",
+    "    return bb_ts_selected, bh_selected_pts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A pred look up table is in shape\n",
+    "# [event,\n",
+    "#    pred_H, \n",
+    "#       [correct, pred_H_pt]]\n",
+    "def gen_pred_bH_LUT(bb_ps_passed, bb_ts_selected, fj_pts):\n",
+    "    LUT = []\n",
+    "    # for each event\n",
+    "    for bb_t_event, bb_p_event, fj_pt_event in zip(bb_ts_selected, bb_ps_passed, fj_pts):\n",
+    "        # for each predicted bb assignment, check if any target H have a same bb assignment\n",
+    "        LUT_event = []\n",
+    "        for i, bb_p in enumerate(bb_p_event):\n",
+    "            correct = 0\n",
+    "            predH_pt = fj_pt_event[bb_p-10]\n",
+    "            for bb_t in bb_t_event:\n",
+    "                if bb_p == bb_t+10:\n",
+    "                    correct = 1\n",
+    "            LUT_event.append([correct, predH_pt])\n",
+    "        LUT.append(LUT_event)\n",
+    "    return LUT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A target look up table is in shape\n",
+    "# [event,\n",
+    "#    target_H, \n",
+    "#        target_bb_assign,\n",
+    "#           [retrieved, targetH_pt]]\n",
+    "def gen_target_bH_LUT(bb_ps_passed, bb_ts_selected, targetH_pts):\n",
+    "    LUT = []\n",
+    "    # for each event\n",
+    "    for bb_t_event, bb_p_event, targetH_pts_event in zip(bb_ts_selected, bb_ps_passed, targetH_pts):\n",
+    "        # for each target fatjet, check if the predictions have a p fatject same with the t fatjet\n",
+    "        LUT_event = []\n",
+    "        for i, bb_t in enumerate(bb_t_event):\n",
+    "            retrieved = 0\n",
+    "            targetH_pt = targetH_pts_event[i]\n",
+    "            for bb_p in bb_p_event:\n",
+    "                if bb_p == bb_t+10:\n",
+    "                    retrieved = 1\n",
+    "            LUT_event.append([retrieved, targetH_pt])\n",
+    "        LUT.append(LUT_event)\n",
+    "    return LUT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generate pred/target LUT\n",
+    "# each entry corresponds to [recoH correct or not, reco H pt]\n",
+    "# or \n",
+    "# [targetH retrieved or not, target H pt]\n",
+    "def get_reco_boosted_h_mass(predfile):\n",
+    "    # Collect H pt, mask, target and predicted jet and fjets for 3 Hs in each event\n",
+    "    if 'TARGETS' not in predfile.keys():\n",
+    "        predfile[\"INPUTS\"] = predfile[\"SpecialKey.Inputs\"]\n",
+    "        predfile[\"TARGETS\"] = predfile[\"SpecialKey.Targets\"]\n",
+    "\n",
+    "    try:\n",
+    "        # pred assignment\n",
+    "        bb_bh1_p = np.array(predfile[\"TARGETS\"][\"bh1\"]['bb'])\n",
+    "        bb_bh2_p = np.array(predfile[\"TARGETS\"][\"bh2\"]['bb'])\n",
+    "        bb_bh3_p = np.array(predfile[\"TARGETS\"][\"bh3\"]['bb'])\n",
+    "    \n",
+    "        # boosted Higgs detection probability\n",
+    "        dp_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['detection_probability'])\n",
+    "        dp_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['detection_probability'])\n",
+    "        dp_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['detection_probability'])\n",
+    "\n",
+    "        # fatjet assignment probability\n",
+    "        ap_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['assignment_probability'])\n",
+    "        ap_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['assignment_probability'])\n",
+    "        ap_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['assignment_probability'])\n",
+    "    except:\n",
+    "        # pred assignment\n",
+    "        bb_bh1_p = np.array(predfile[\"TARGETS\"][\"bh1\"]['bb'])+10\n",
+    "        bb_bh2_p = np.array(predfile[\"TARGETS\"][\"bh2\"]['bb'])+10\n",
+    "        bb_bh3_p = np.array(predfile[\"TARGETS\"][\"bh3\"]['bb'])+10\n",
+    "    \n",
+    "         # boosted Higgs detection probability\n",
+    "        dp_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['mask']).astype('float')\n",
+    "        dp_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['mask']).astype('float')\n",
+    "        dp_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['mask']).astype('float')\n",
+    "\n",
+    "        # fatjet assignment probability\n",
+    "        ap_bh1 = np.array(predfile[\"TARGETS\"][\"bh1\"]['mask']).astype('float')\n",
+    "        ap_bh2 = np.array(predfile[\"TARGETS\"][\"bh2\"]['mask']).astype('float')\n",
+    "        ap_bh3 = np.array(predfile[\"TARGETS\"][\"bh3\"]['mask']).astype('float')\n",
+    "    \n",
+    "    # collect fatjet pt\n",
+    "    fj_pt = np.array(predfile['INPUTS']['BoostedJets']['fj_pt'])\n",
+    "    \n",
+    "    dps = np.concatenate((dp_bh1.reshape(-1, 1), dp_bh2.reshape(-1, 1), dp_bh3.reshape(-1, 1)), axis=1)\n",
+    "    aps = np.concatenate((ap_bh1.reshape(-1, 1), ap_bh2.reshape(-1, 1), ap_bh3.reshape(-1, 1)), axis=1)\n",
+    "\n",
+    "    # convert some arrays to ak array\n",
+    "    bb_ps = np.concatenate((bb_bh1_p.reshape(-1, 1), bb_bh2_p.reshape(-1, 1), bb_bh3_p.reshape(-1, 1)), axis=1)\n",
+    "    bb_ps = ak.Array(bb_ps)\n",
+    "    fj_pt = ak.Array(fj_pt)\n",
+    "    \n",
+    "    # select predictions and targets\n",
+    "    bb_ps_selected = sel_pred_bH_by_dp_ap(dps, aps, bb_ps)\n",
+    "    \n",
+    "    # reconstruct bH to remove overlapped ak4 jets\n",
+    "    fj_eta = np.array(predfile['INPUTS']['BoostedJets']['fj_eta'])\n",
+    "    fj_phi = np.array(predfile['INPUTS']['BoostedJets']['fj_phi'])\n",
+    "    fj_mass = ak.Array(predfile['INPUTS']['BoostedJets']['fj_mass'])\n",
+    "    \n",
+    "    fjs = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": fj_pt,\n",
+    "            \"eta\": fj_eta,\n",
+    "            \"phi\": fj_phi,\n",
+    "            \"mass\": fj_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\"\n",
+    "    )\n",
+    "    fj_reco = fjs[bb_ps_selected-10]\n",
+    "    \n",
+    "    return fj_mass[bb_ps_selected-10], fj_reco"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_bh_mass_s, fjs_reco_s = get_reco_boosted_h_mass(s_h5)\n",
+    "reco_bh_mass_b, fjs_reco_b = get_reco_boosted_h_mass(b_h5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(ak.ravel(reco_bh_mass_s), bins=np.arange(105, 150, 2.5), histtype='step', label='reweighted spanet', density=True)\n",
+    "plt.hist(ak.ravel(reco_bh_mass_b), bins=np.arange(105, 150, 2.5), histtype='step', label='baseline', density=True)\n",
+    "plt.xlabel('Boosted Mass Sculpting (GeV)')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_unoverlapped_jet_index(fjs, js, dR_min=0.8):\n",
+    "    overlapped = ak.sum(js[:, np.newaxis].deltaR(fjs)<dR_min, axis=-2)>0\n",
+    "    jet_index_passed = ak.local_index(js).mask[~overlapped]\n",
+    "    jet_index_passed = ak.drop_none(jet_index_passed)\n",
+    "    return jet_index_passed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sel_pred_h_by_dp_ap(dps, aps, b1_ps, b2_ps):\n",
+    "    # get most possible number of H_reco by dps\n",
+    "    HiggsNumProb = dp_to_HiggsNumProb(dps)\n",
+    "    HiggsNum = np.argmax(HiggsNumProb, axis=-1)\n",
+    "    \n",
+    "    # get the top N (dp x ap) jet assignment indices\n",
+    "    ps = dps*aps\n",
+    "    idx_descend = np.flip(np.argsort(ps, axis=-1), axis=-1)\n",
+    "#     print('ap', aps[0])\n",
+    "#     print('dp', dps[0])\n",
+    "#     print('HiggsNumProb', HiggsNumProb[0])\n",
+    "#     print('HiggsNum', HiggsNum[0])\n",
+    "#     print('b1', b1_ps[0])\n",
+    "#     print('b2', b2_ps[0])\n",
+    "    \n",
+    "    idx_sel = [idx_e[:N_e] for idx_e, N_e in zip(idx_descend, HiggsNum)]\n",
+    "    \n",
+    "    # select the predicted b assignment via the indices\n",
+    "    b1_ps_sel = b1_ps[idx_sel]\n",
+    "    b2_ps_sel = b2_ps[idx_sel]\n",
+    "\n",
+    "    # require b1 b2 assignment are AK4 jet\n",
+    "    b1_ak4_filter = b1_ps_sel<10\n",
+    "    b2_ak4_filter = b2_ps_sel<10\n",
+    "    filter = b1_ak4_filter & b2_ak4_filter\n",
+    "    \n",
+    "    b1_ps_passed = b1_ps_sel.mask[filter]\n",
+    "    b1_ps_passed = ak.drop_none(b1_ps_passed)\n",
+    "    \n",
+    "    b2_ps_passed = b2_ps_sel.mask[filter]\n",
+    "    b2_ps_passed = ak.drop_none(b2_ps_passed)\n",
+    "    \n",
+    "    return b1_ps_passed, b2_ps_passed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sel_target_h_by_mask(b1_ts, b2_ts, h_pts, bi_cat_H, h_masks):\n",
+    "    b1_ts_selected = b1_ts.mask[h_masks]\n",
+    "    b1_ts_selected = ak.drop_none(b1_ts_selected)\n",
+    "    \n",
+    "    b2_ts_selected = b2_ts.mask[h_masks]\n",
+    "    b2_ts_selected = ak.drop_none(b2_ts_selected)\n",
+    "    \n",
+    "    h_selected_pts = h_pts.mask[h_masks]\n",
+    "    h_selected_pts = ak.drop_none(h_selected_pts)\n",
+    "    \n",
+    "    bi_cat_H_passed = bi_cat_H.mask[h_masks]\n",
+    "    bi_cat_H_passed = ak.drop_none(bi_cat_H_passed)\n",
+    "    \n",
+    "    return b1_ts_selected, b2_ts_selected, h_selected_pts, bi_cat_H_passed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A pred look up table is in shape\n",
+    "# [event,\n",
+    "#    pred_H, \n",
+    "#       [correct_or_not, pt, overlap_w_H_reco, has_boost_H_target, which_H_target]]\n",
+    "@nb.njit\n",
+    "def calc_reco_h_mass(b1_ps_passed, b2_ps_passed, js, goodJetIdx, builder):\n",
+    "    # for each event\n",
+    "    for b1_ps_e, b2_ps_e, jets_e, goodJetIdx_e in zip(b1_ps_passed, b2_ps_passed, js, goodJetIdx):\n",
+    "        # for each predicted bb assignment, check if any target H have a same bb assignment\n",
+    "        builder.begin_list()\n",
+    "        for b1_p, b2_p in zip(b1_ps_e, b2_ps_e):\n",
+    "            if (b1_p in goodJetIdx_e) and (b2_p in goodJetIdx_e):\n",
+    "                overlap = 0\n",
+    "            else:\n",
+    "                overlap = 1\n",
+    "                continue\n",
+    "                \n",
+    "            predH_mass = (jets_e[b1_p]+jets_e[b2_p]).mass\n",
+    "                    \n",
+    "            builder.append(predH_mass)\n",
+    "        \n",
+    "        builder.end_list()\n",
+    "    return builder"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_reco_resolved_h_mass(predfile, fjs_reco=None):\n",
+    "    if 'TARGETS' not in predfile.keys():\n",
+    "        predfile[\"INPUTS\"] = predfile[\"SpecialKey.Inputs\"]\n",
+    "        predfile[\"TARGETS\"] = predfile[\"SpecialKey.Targets\"]\n",
+    "    \n",
+    "    # predict assignments\n",
+    "    b1_h1_p = np.array(predfile[\"TARGETS\"][\"h1\"]['b1']).astype('int')\n",
+    "    b1_h2_p = np.array(predfile[\"TARGETS\"][\"h2\"]['b1']).astype('int')\n",
+    "    b1_h3_p = np.array(predfile[\"TARGETS\"][\"h3\"]['b1']).astype('int')\n",
+    "\n",
+    "    b2_h1_p = np.array(predfile[\"TARGETS\"][\"h1\"]['b2']).astype('int')\n",
+    "    b2_h2_p = np.array(predfile[\"TARGETS\"][\"h2\"]['b2']).astype('int')\n",
+    "    b2_h3_p = np.array(predfile[\"TARGETS\"][\"h3\"]['b2']).astype('int')\n",
+    "    \n",
+    "    # resolved Higgs detection probability\n",
+    "    dp_h1 = np.array(predfile[\"TARGETS\"][\"h1\"]['detection_probability'])\n",
+    "    dp_h2 = np.array(predfile[\"TARGETS\"][\"h2\"]['detection_probability'])\n",
+    "    dp_h3 = np.array(predfile[\"TARGETS\"][\"h3\"]['detection_probability'])\n",
+    "    \n",
+    "    # ak4 jets assignment probability\n",
+    "    ap_h1 = np.array(predfile[\"TARGETS\"][\"h1\"]['assignment_probability'])\n",
+    "    ap_h2 = np.array(predfile[\"TARGETS\"][\"h2\"]['assignment_probability'])\n",
+    "    ap_h3 = np.array(predfile[\"TARGETS\"][\"h3\"]['assignment_probability'])\n",
+    "    \n",
+    "    # reconstruct jet 4-momentum objects\n",
+    "    j_pt = np.array(predfile['INPUTS']['Jets']['pt'])\n",
+    "    j_eta = np.array(predfile['INPUTS']['Jets']['eta'])\n",
+    "    j_phi = np.array(predfile['INPUTS']['Jets']['phi'])\n",
+    "    j_mass = np.array(predfile['INPUTS']['Jets']['mass'])\n",
+    "    js = ak.zip(\n",
+    "        {\n",
+    "            \"pt\": j_pt,\n",
+    "            \"eta\": j_eta,\n",
+    "            \"phi\": j_phi,\n",
+    "            \"mass\": j_mass,\n",
+    "        },\n",
+    "        with_name=\"Momentum4D\"\n",
+    "    )\n",
+    "    \n",
+    "    # convert some numpy arrays to ak arrays\n",
+    "    dps = np.concatenate((dp_h1.reshape(-1, 1), dp_h2.reshape(-1, 1), dp_h3.reshape(-1, 1)), axis=1)\n",
+    "    # dps = ak.Array(dps)\n",
+    "    aps = np.concatenate((ap_h1.reshape(-1, 1), ap_h2.reshape(-1, 1), ap_h3.reshape(-1, 1)), axis=1)\n",
+    "    # aps = ak.Array(aps)\n",
+    "    \n",
+    "    dps = reset_collision_dp(dps, aps)\n",
+    "    \n",
+    "    b1_ps = np.concatenate((b1_h1_p.reshape(-1, 1), b1_h2_p.reshape(-1, 1), b1_h3_p.reshape(-1, 1)), axis=1)\n",
+    "    b1_ps = ak.Array(b1_ps)\n",
+    "    b2_ps = np.concatenate((b2_h1_p.reshape(-1, 1), b2_h2_p.reshape(-1, 1), b2_h3_p.reshape(-1, 1)), axis=1)\n",
+    "    b2_ps = ak.Array(b2_ps)\n",
+    "\n",
+    "    \n",
+    "    # select predictions and targets\n",
+    "    b1_ps_selected, b2_ps_selected = sel_pred_h_by_dp_ap(dps, aps, b1_ps, b2_ps)\n",
+    "\n",
+    "    # find jets that are overlapped with reco boosted Higgs\n",
+    "    if fjs_reco is None:\n",
+    "        goodJetIdx =  ak.local_index(js)\n",
+    "    else:\n",
+    "        goodJetIdx = get_unoverlapped_jet_index(fjs_reco, js, dR_min=0.4)\n",
+    "    \n",
+    "    # get reco H mass\n",
+    "    h_mass = calc_reco_h_mass(b1_ps_selected, b2_ps_selected, js, goodJetIdx, ak.ArrayBuilder()).snapshot()\n",
+    "    \n",
+    "    return h_mass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_rh_mass_s = get_reco_resolved_h_mass(s_h5, fjs_reco=None)\n",
+    "reco_rh_mass_b = get_reco_resolved_h_mass(b_h5, fjs_reco=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Resolved Mass Sculpting (GeV)')"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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ERUUhJiYGgYGBWLduHUJCQpCcnAw3N7cq5U+ePIlx48YhOjoaw4YNw44dOxAaGoqzZ8+iW7duAID8/HwMGDAAo0ePRkRERJVzAMCrr76K/fv3Y/fu3XB0dERkZCRGjhyJn376SddLICJdcEaS8dG2dlBT0vF74vHHH0dAQADWrVvXdHWqwcSJE5GdnY3Y2FiDqA81Hp1DzTvvvIOIiAhMmjQJABATE4P9+/djy5YteP3116uUX79+PYYMGYLXXnsNgGo55Yq9N2JiYgAAzz//PADg6tWrWp8zJycHH3/8MXbs2IFBgwYBALZu3YouXbrg559/xqOPPqrrZRBRbTgjyThVt3ZQUzLy74k9e/ZU2YmajJNOoaakpARnzpzBvHnzpGNyuRzBwcFISEjQ+piEhARERUWpHQsJCZEScl2cOXMGpaWlCA4Olo517twZ3t7eSEhI0BpqiouLUVxcLH2dm5tb5+cjInBGkrHStnZQUzKB74mKHa3J+Ok0piYrKwtlZWXStuwV2rRpg/T0dK2PSU9P16l8deewsrJS23m0tvNER0fD0dFRunl5GecPG5FeOXmp1p+puFVeYO9GUtWuqaZQl+eqKHMjSdVSQQ/WDmrqWz2D0/379xEZGQlHR0e4urpi4cKF0mJxn332Gfr06YOWLVtCqVTif/7nf5CZmSk99u7duxg/fjxat24NhUIBPz8/bN26Vbr/2rVrGD16NJycnNCqVSuMGDGi2p4AQNX9NHPmTOlrHx8fvPXWW5g8eTJatmwJb29vbNq0Se0xuj4HNQ+Tnf00b9485OTkSLdr1/iLjqjBKndJbRqo+tfSVnVcH8+lWWbTQFXXC4ONwfvkk0/QokULnDp1CuvXr8c777yDjz76CABQWlqK5cuX4/z584iNjcXVq1cxceJE6bELFy7EpUuXcPDgQfz+++/44IMP4OrqKj02JCQELVu2xIkTJ/DTTz/B3t4eQ4YMQUlJ3Tf5XLNmDfr06YNz587hlVdewcsvv4zk5ORGfQ5qfDp1P7m6usLCwqLKrKOMjAwolUqtj1EqlTqVr+4cJSUlyM7OVmutqek81tbWsLa2rvNzEFEdaOuSqm6QaEXLSn1bc+ryXJplTKArxFx4eXlh7dq1kMlk6NSpE3777TesXbsWERERmDx5slSuXbt22LBhAx555BHk5eXB3t4eaWlp6NmzJ/r06QNA1bJSYdeuXSgvL8dHH30EmUwGQDUG08nJCceOHcNTTz1Vp/r985//xCuvvAIAmDt3LtauXYujR4+iU6dOjfYc1Ph0aqmxsrJC7969ER8fLx0rLy9HfHw8goKCtD4mKChIrTwAHDp0qNry2vTu3RuWlpZq50lOTkZaWppO5yGiRqDZJaUZHhqzNae259Is0xxjSKhRPProo1IgAFSfFZcvX0ZZWRnOnDmD4cOHw9vbGy1btsTAgQMBAGlpaQCAl19+GTt37kRAQADmzJmDkydPSuc5f/48UlJS0LJlS9jb28Pe3h6tWrVCUVERrly5Uuf69ejRQ/q/TCaDUqmUusAa6zmo8ek8+ykqKgphYWHo06cP+vbti3Xr1iE/P1+aDTVhwgR4enoiOjoaADBjxgwMHDgQa9aswdChQ7Fz506cPn1arX/yzp07SEtLw40bNwBAauJTKpVQKpVwdHREeHg4oqKi0KpVKzg4OGDatGkICgrizCciQ6NLaw6RhqKiIoSEhCAkJATbt29H69atkZaWhpCQEKlr5+mnn8bff/+NAwcO4NChQxg8eDCmTp2K1atXIy8vD71798b27durnLt169Z1rofmbCiZTIby8nIAaLTnoManc6gZM2YMbt26hUWLFiE9PR0BAQGIi4uTBgOnpaVBLn/QANSvXz/s2LEDCxYswPz58+Hn54fY2FhpjRoA+Pbbb6VQBABjx44FACxevBhLliwBAKxduxZyuRzPPvssiouLERISgvfff79eF01ETczQtjzQtm4Lg5ZeJSYmqn39888/w8/PD3/88Qdu376Nt99+W5rgcfr06SqPb926NcLCwhAWFobHHnsMr732GlavXo1evXph165dcHNzg4ODQ5PUvTmeg+qnXns/RUZGIjIyUut9x44dq3Js1KhRGDVqVLXnmzhxotogMG1sbGywceNGbNy4UZeqEpG5q27dFiNfW8XYpaWlISoqCi+++CLOnj2Ld999F2vWrIG3tzesrKzw7rvv4qWXXsKFCxewfPlytccuWrQIvXv3xsMPP4zi4mLs27cPXbp0AQCMHz8eq1atwogRI7Bs2TI89NBD+Pvvv7Fnzx7MmTMHDz30UIPr3hzPQfXDDS2JyLRpW7fFHAYUN8d0+wY8z4QJE1BYWIi+ffvCwsICM2bMwJQpUyCTybBt2zbMnz8fGzZsQK9evbB69Wr861//kh5rZWWFefPm4erVq1AoFHjsscewc+dOAICtrS1++OEHzJ07FyNHjsS9e/fg6emJwYMHN1qrSnM8B9WPTFQsDGDicnNz4ejoiJycHH7TEQHqXTIVH/JTjqsG3BqrG0mqwcmVr6Oux4xMUVERUlNT4evrCxsbmwd3cEVhMkLVfj9Dt89vttQQmSNtH3xNtd4MNS9tA7WbGscnkYFgqCEyR9q6ZEzpg6lyl0hzdcMYEkMbqE3UTBhqiMxZxVL6pqKmTTjZCkVk8hhqiMh0VNf1YkqtUERULYYaIjItunS9VO6aMtLgYyZzPcjENdb3MUMNEZkfbd1URjaDp2LF24KCAigUCj3XhqhhCgpUkxY0V3LWFUMNEZmf6jbCTEswmu0dLCws4OTkJO1HZGtrq7aXEpExEEKgoKAAmZmZcHJygoWFRYPOx1BDROapcjdVTQOMDbj1RqlUAoAUbIiMlZOTk/T93BAMNURE2gYYG8GqwzKZDO7u7nBzc0Npaam+q0NUL5aWlg1uoanAUENEBBj12i4WFhaN9qFAZMwYaojMgeYu1ea4IB0RmTyGGiJTV9Mu1VyQjohMCEMNkanTtiUCYNAze4iI6oOhhshcmNqWCEREGuT6rgARERFRY2CoISIiIpPAUENEREQmgaGGiIiITAJDDREREZkEzn4iMkWVF9vjQntEZCYYaohMjbbF9rjQHhGZAYYaIlOjbbE9LrRHRGaAoYbIVHGxPSIyMww1REQ1qTwmiS1eRAaNoYaISBtbF9VYpD0RD45Z2gJTTzHYEBkohhoiY1d5phPA2U6NxclLFWAqzyLbE6H6mqGGyCAx1BAZM20znQDOdmosTl4MMERGhKGGyJhpm+kEcOxHU9JsCeNrTWQwGGqITAFnOjU9bWNsAI6zITIgDDVERHWhOcYG4DgbIgPDUENUg+vZhbibX6J2zNnOCp5OCj3ViPSKY2yIDBpDDVE1rmcXInjNcRSWlqkdV1ha4PCsgQw2REQGhqGGqBp380tQWFqGdWMC0MHNHgCQkpmHmbuScDe/hKGGiMjAMNQQ1aKDmz26eTrquxpERFQLub4rQERERNQYGGqIiIjIJDDUEBERkUlgqCEiIiKTwFBDREREJoGzn4iMTeVdubkjNxGRhKGGyJho25WbO3ITEQFgqCEyLtp25eYu0UREABhqiIwTd+UmIqqCA4WJiIjIJLClhsiQVR4UDHBgMBFRDRhqiAyVtkHBAAcGExFVg6GGSE+uZxfibn6J2jFnO6sHu39rGxQMcGAwEVE1GGqI9OB6diGC1xxHYWmZ2nGFpQUOzxr4INgAHBRMRFRHDDVEenA3vwSFpWVYNyYAHdzsAQApmXmYuSsJd/NL1EMNERHVCUMNkR51cLNHN09HfVeDiMgkMNQQETVU5VlpHPNEpDcMNURE9WXropqNtifiwTFLW2DqKQYbIj1gqCEiqi8nL1WAqbzB6J4I1dcMNUTNjqGGiKghnLwYYIgMRL22Sdi4cSN8fHxgY2ODwMBAnDp1qsbyu3fvRufOnWFjY4Pu3bvjwIEDavcLIbBo0SK4u7tDoVAgODgYly9fVivz559/YsSIEXB1dYWDgwMGDBiAo0eP1qf6REREZIJ0DjW7du1CVFQUFi9ejLNnz8Lf3x8hISHIzMzUWv7kyZMYN24cwsPDce7cOYSGhiI0NBQXLlyQyqxcuRIbNmxATEwMEhMTYWdnh5CQEBQVFUllhg0bhvv37+PIkSM4c+YM/P39MWzYMKSnp9fjsomIiMjU6Bxq3nnnHURERGDSpEno2rUrYmJiYGtriy1btmgtv379egwZMgSvvfYaunTpguXLl6NXr1547733AKhaadatW4cFCxZgxIgR6NGjBz799FPcuHEDsbGxAICsrCxcvnwZr7/+Onr06AE/Pz+8/fbbKCgoUAtHlRUXFyM3N1ftRtRYUjLzcOF6Di5cz8H17EJ9V4cMTdafwI2kB7fsa3quEJF50GlMTUlJCc6cOYN58+ZJx+RyOYKDg5GQkKD1MQkJCYiKilI7FhISIgWW1NRUpKenIzg4WLrf0dERgYGBSEhIwNixY+Hi4oJOnTrh008/Ra9evWBtbY0PP/wQbm5u6N27t9bnjY6OxtKlS3W5PKJaOdtZQWFpgZm7kqRjWlcBJvOkbTYUwBlRRM1Ep1CTlZWFsrIytGnTRu14mzZt8Mcff2h9THp6utbyFd1GFf/WVEYmk+Hw4cMIDQ1Fy5YtIZfL4ebmhri4ODg7O2t93nnz5qmFqdzcXHh58RcKNYynkwKHZw2U9mziKsCkRnM2FMAZUUTNyChmPwkhMHXqVLi5ueHEiRNQKBT46KOPMHz4cPzyyy9wd3ev8hhra2tYW1vrobZk6jydFAwwVD3OhiLSG53G1Li6usLCwgIZGRlqxzMyMqBUKrU+RqlU1li+4t+ayhw5cgT79u3Dzp070b9/f/Tq1Qvvv/8+FAoFPvnkE10ugYiIiEyUTqHGysoKvXv3Rnx8vHSsvLwc8fHxCAoK0vqYoKAgtfIAcOjQIam8r68vlEqlWpnc3FwkJiZKZQoKClSVlatXVy6Xo7y8XJdLIJJczy6UBvty0C8RkfHTufspKioKYWFh6NOnD/r27Yt169YhPz8fkyZNAgBMmDABnp6eiI6OBgDMmDEDAwcOxJo1azB06FDs3LkTp0+fxqZNmwCoxsvMnDkTK1asgJ+fH3x9fbFw4UJ4eHggNDQUgCoYOTs7IywsDIsWLYJCocDmzZuRmpqKoUOHNtJLQebkenYhgtccR2FpmdpxDvolIjJeOoeaMWPG4NatW1i0aBHS09MREBCAuLg4aaBvWlqaWotKv379sGPHDixYsADz58+Hn58fYmNj0a1bN6nMnDlzkJ+fjylTpiA7OxsDBgxAXFwcbGxsAKi6veLi4vDGG29g0KBBKC0txcMPP4xvvvkG/v7+DX0NyAzdzS9BYWkZ1o0JQAc3ewAc9EvNKPua+mBigBthEjWCeg0UjoyMRGRkpNb7jh07VuXYqFGjMGrUqGrPJ5PJsGzZMixbtqzaMn369MF3332nc12JatLBzR7dPB2b/HmuZxdKM6YAVYAiM5V9DdjYFygtUD/Oad9EDWYUs5+IjFlNXV3OdlZ6qhXpTcFtVaAZuRlw7ag6xmnfRI2CoYaoiWnr6gJUC/mxm8uMuXYEPAL0XQsik8JQQ6ShomuosbuImquriwxU1p/q/xJRo2OoIfqv6rZAqEsXkWYAas5WGM3xOs39/FQLbVsnWNqqjhNRo2KoIZNUnw96zS0Q6vIYbUEIqP/UcA9kwSbrN0BmX6e/6Dk13Qho2zqBM52ImgRDDZmchnzQ67oFgrYgVN+p4ZZ513HY+jXY7i2udLDmv+g5Nd1IcOsEombBUEMmp7k/6KsLQrWOzdFYq8Q2PQm2smJce2I9vPwC/nuwbn/Rc7wOERFDDZkwfX3Qa+uSamd5F275fwA3/rvJakEWsOt5tbVKvAAUCGsUKPsCHl2rPX/lrjWud0NE9ABDDVEj0+ySssy7Dr/d4ZDv0NhXytIWeO5rwNYVAJByKw8TvriCTfae1Z5bW9dafde70Rx3xMHFRGTsGGqImoBal9SNVOB+ofpia0CVrqUikYMbyKnxvNq61uoTRqoLRxxcTETGjKGGqLk04mJrDe1a0wxHHFxMRKaAoYbMSlMtrGesOMCYiEwJQw2ZhYYsrEdERMaBoYbMQn0W1iMiIuPCUENGp76zdnRdWE9fKneNMXgREdUdQw0ZFVOetVNdF5kpXBsRUXNgqCGjUt2snV9S7+BupdWDjZFmFxlnJBER6YahhoxSxaydmjaUNMZBwMbSRUZEZIgYasioaRsADJjWWJTKLU/G2gpFRNQcGGrI6Jlq64aptUIRETU1hhoiA2UOrVBERI2JoYYMmub0bXPrfmnuVijN15cBioiMCUMNGSxt07cBdr80hZq6ujSnlHN37yaU9af61xqbniL7GlBwu+YyRGaMoYYMlrYdqQF+iDYFbV1d2qaUm/I6QXpl6wJY2gJ7ItSPW9oCU0+pQkv2NWBjX6C0oPoyRGaOoYYMHjddbB516eri7t5NxMlLFUwqt8Jk/akKOQW3VfcX3FYFmpGbVTu+aytDZOYYaojMQGOPTWLQbAJOXnULJq4dAY+AJq8OkTFiqCFqCpXHPmiOk2hmhjo2iWNziKixMdQQNTZtYx8sbVXjJvTAEMcmcWwOETUFhhrSG82/1AEj/Wtdc0ZK1p9Vxz4YwAwVQ+oy4tgcImoKDDWkFzV1icQ83xsudlbGsSZNTTNSvIP0HmQMnSEFLSIyfgw1pBfaukRu55fgpc/OIGzLKamcvsd91ErbjBTAIFpmiIjMDUMN6ZXmX+qaa6UYTXcUZ6RQM0m5lYcikQMAsMnKQwc914fIkDDUkEEx1c0piertv7Pn7qRdQCsAM3Ym4eJ/Q83DslTstwYy84rhpsMpTWY8G5EGhhoiMnlG+SGuscpwKwAFwhrThwXC00fV1XnrTyvgOJBbWFrnUFPTeDbOPiNjx1BDzabyB4tRDAImk2C0H+Iaqwyn3MrDhC+uYJNPR6nLNiVL97prG8/G2WdkKhhqqFlUty6JQQ8CNnIVwdHcA2Rzf4g3aqtQpVWGi0QObiCnMaoIgDPPyDQx1FCz0PbBYvDN/0ZK247bDJDN8yFutK1CRCaCoYaaFf86bHradtxmgGwe7Noh0i+GGiITxFlkzUfbWLHmDu/X7hSi6Lqqa4oBlswZQw0RUT3pe6yYg8ISABB76AhSvk8GABS2cMLi50PgUqkODDpkLhhqiMhoGNrUbH2PFXNz80B5CwXW433pWIGwRvCWVbgBV+kYx/SQuWCoISKjYMiDcJuqu6nWZRCcvCCP/OXBhqpZf8J2TwQ+HdceRa7dpcfVZ0yPoQVIorpgqCEio2Bug3Dr3LVVadp3hQ6t7QGP+ocsQw6QRDVhqCEio2IuM+j02bVlbgGSTAdDDRGRAdNniDOXAEmmg6GGiJqc5vgMc1/lWBu+RkQNx1BDRI2u8gf07fwSvPTZGa3jM8x9leMKNY1hMfTXSDOMcTAx6RNDDRHVqHKLQV1aD6ob4PrJ5L5cO6Ua2sawAI37GjXFXmDVvdccTEz6wlBDRFpp20MKqL31QN9rt+ii8ge8IdSxKcawNPZeYJoht/J7zcHEpG8MNUS6yr6mti6IqdK2hxSg/cNfW2tOcw4y1TWcVPdBb4otDI21F1hNIfcR31Ym97qRcWKoIdJF9jVgY1+gtODBMUtbwNZFf3VqQrXtIVXf1pzqaHaN1PbhW99wovlBb+otDI2xF5guIZdIXxhqiHRRcFsVaEZuBlw7qo7ZulRZ/MxcNNYHXU3hqKaA0pBwYtKbfmq2IDbS96hJv2ZkEhhqiOrDtSPgEaDvWhiEpmoFqGtAacwP2tpaigx+2rWti6rlcE+E+nFLW2DqKbMN32Q+GGqIyCDosxWgLi1FjTntusnCkZOXKrxUjPkCVK02eyJUxxhqyMQx1BCR2atLS1FjTbtu8jVptOwFRWQu5PV50MaNG+Hj4wMbGxsEBgbi1KlTNZbfvXs3OnfuDBsbG3Tv3h0HDhxQu18IgUWLFsHd3R0KhQLBwcG4fPlylfPs378fgYGBUCgUcHZ2RmhoaH2qT0RGJCUzDxeu5zR5V4+nkwLdPB2lW+XgUlnFrK6Km66tS5XD0b5pA6SbIcy8aq7Xmqip6NxSs2vXLkRFRSEmJgaBgYFYt24dQkJCkJycDDc3tyrlT548iXHjxiE6OhrDhg3Djh07EBoairNnz6Jbt24AgJUrV2LDhg345JNP4Ovri4ULFyIkJASXLl2CjY0NAODrr79GREQE3nrrLQwaNAj379/HhQsXGnj5RGSoGnt9FUNjSPsqmfprTeZD51DzzjvvICIiApMmTQIAxMTEYP/+/diyZQtef/31KuXXr1+PIUOG4LXXXgMALF++HIcOHcJ7772HmJgYCCGwbt06LFiwACNGjAAAfPrpp2jTpg1iY2MxduxY3L9/HzNmzMCqVasQHh4unbtr1671umgiMnyNtb4K1Y6vNZkKnbqfSkpKcObMGQQHBz84gVyO4OBgJCQkaH1MQkKCWnkACAkJkcqnpqYiPT1drYyjoyMCAwOlMmfPnsX169chl8vRs2dPuLu74+mnn66xpaa4uBi5ublqNyIyLppdQvyQbTp8rckU6BRqsrKyUFZWhjZt2qgdb9OmDdLT07U+Jj09vcbyFf/WVOavv/4CACxZsgQLFizAvn374OzsjMcffxx37tzR+rzR0dFwdHSUbl5eHDhHRPrD8SpETc8oZj+Vl5cDAN544w08++yzAICtW7fioYcewu7du/Hiiy9Wecy8efMQFRUlfZ2bm8tgQ0TNzmDGq1RekM+MF4wk06ZTqHF1dYWFhQUyMjLUjmdkZECpVGp9jFKprLF8xb8ZGRlwd3dXKxMQEAAA0vHKY2isra3Rrl07pKWlaX1ea2trWFtb63B1RFpU3ucJMOm9nqhp6H28irYF+bgYH5konUKNlZUVevfujfj4eGk6dXl5OeLj4xEZGan1MUFBQYiPj8fMmTOlY4cOHUJQUBAAwNfXF0qlEvHx8VKIyc3NRWJiIl5++WUAQO/evWFtbY3k5GQMGDAAAFBaWoqrV6+ibdu2ulwCUd1p2+cJMOm9nqiqiu6ihnQb6XV7Ac0F+bgYH5kwnbufoqKiEBYWhj59+qBv375Yt24d8vPzpdlQEyZMgKenJ6KjowEAM2bMwMCBA7FmzRoMHToUO3fuxOnTp7Fp0yYAgEwmw8yZM7FixQr4+flJU7o9PDyk4OTg4ICXXnoJixcvhpeXF9q2bYtVq1YBAEaNGtUYrwM1MoNfTr4utO3zBLDp3kwYTLdRY+CCfGQmdA41Y8aMwa1bt7Bo0SKkp6cjICAAcXFx0kDftLQ0yOUPxh/369cPO3bswIIFCzB//nz4+fkhNjZWWqMGAObMmYP8/HxMmTIF2dnZGDBgAOLi4qQ1agBg1apVaNGiBZ5//nkUFhYiMDAQR44cgbOzc0Oun5pAk6+Y2ty4z5PRqRyi6xuo9d5tREQ6kwkhhL4r0Rxyc3Ph6OiInJwcODg46Ls6Ju3C9RwMe/fHBi8nr3c3koBNA4EpxxlqjERNgdoQVuw1CE34fV3xs79v2gCDWViQjJ8un99GMfuJjJMhrZhK5kFb6wpghIHaxGh2R2vD94gaA0MNEZkUvQ7KpSqqaz3TxNY0agwMNURE1GSq2928Ms0d0Ynqi6GGiMgcaa651MSz+urSHV15UDe7o6g+GGqIiMyJtsX4AL0uyFfd9Hl2R5GuGGqIiMyJ5mJ8gN4X5NMc4M3uKKovhhoiInNjgIvxcYA3NQaGGiIiMgqaU8M57oY0MdQQEZHB0zY1nONuSBNDDZkvzR24Ae7rRGSgNKeGc9wNacNQQ+apph24x3wG2LpWnfJKRHrHlcqpJgw1ZJ607cBdkAXseh74/NkH5SxtVa03RFRnjbGhKFF9MNSQedPcgVtzqiu7o4jqTNt6M4Bq7IuznZV+KkVmhaGGqDIDnOpKZCy4oSjpG0MNERE1muZeb0aze4sByrwx1BARkdGpqauL07zNF0MNEREZHW1dXZzmTQw1RERkkGqbRcWtFUgTQw0RERkUzqKi+mKooUZReU8WrktBRA3BWVRUXww11GDV7cnCv6iIjJietxFh1xLVB0MNNZjmniwA/6IiMmo1bSMy9RTXciKDxVBDjYZ7shCZCG3biGT9CeyJUN3HUEMGiqGGiIi009xGhMjAyfVdASIiIqLGwFBDREREJoHdT0REpJL1p/q/REaGoYaIyNzZuqhmNu2JeHDM0lZ1nMiIMNQQEZk7Jy/VVO3K69I045o0RI2FoYaIiFQBpi4hRrNriuGHDAhDDRER1U5bFxXABfnIoDDUEBFR7bR1UXFBPjIwDDVERFQ3de2iItIThhoiIjIpKZl5al9zLzrzwVBDREQmwdnOCgpLC8zclaR2XGFpgcOzBjLYmAGGGjIf2dcejAfg4mJEJsfTSYHDswbibn6JdCwlMw8zdyXhbn4JQ40ZYKgh85B9DdjYV7XzcAUuLkbUOCr/kaDnKd6eTgqGFzPGUEPmoeC2KtCM3KzaeRjQ+y9fIqNX3UrEnOJNesJQQ+bFtSPgEaDvWhCZBs1p3pziTXrGUEM6u55dWKXPmojMlJFM8678e4qzoUwXQw3p5Hp2IYLXHEdhaZnacYWlBZztrPRUKyIi7bTNiNI2G0rzjzUGH+PEUEM6uZtfgsLSMqwbE4AObvbScf4CICJDpDkjSttsKG1/rHEauHFiqKF66eBmj26ejvquhkrlqdoVOAiYiP6rthlRmn+scRq48WKoIeOmbao2wBkYRKQzg/pjjeqFoYaMm7ap2pyBQUS1qDxwmJMdTAdDDZkGTtUmojqoaSsFTnYwfgw1RERkNrRtpQBon+zAjTGND0MNERE1Ls291Qxs4H5tA4e5MabxYqghIqLGoW3bBMDoBu5zY0zjxVBDRESNQ3PbBMBoB+5zY0zjxFBDRESNx0i2TSDTxFBDNTLqfZ4q9+tr9vETEZHJYaihahntPk819evbuuinTkRE1OQYaqhaRrvPk7Z+fcDgZmAQEVHjYqihWhnl0uHs1ycyLJW7gPkHBjURhhoiImo62rqDjWyKNxkPeX0etHHjRvj4+MDGxgaBgYE4depUjeV3796Nzp07w8bGBt27d8eBAwfU7hdCYNGiRXB3d4dCoUBwcDAuX76s9VzFxcUICAiATCZDUlJSfapPxi77GnAjSXXjAGAiw1bRHTzluOo2crNqvzbN7mGiRqBzqNm1axeioqKwePFinD17Fv7+/ggJCUFmZqbW8idPnsS4ceMQHh6Oc+fOITQ0FKGhobhw4YJUZuXKldiwYQNiYmKQmJgIOzs7hISEoKioqMr55syZAw8PD12rTaaiYlfuTQNVtz0RHABMZOicvFR7s3kEPNh4lqgJ6Bxq3nnnHURERGDSpEno2rUrYmJiYGtriy1btmgtv379egwZMgSvvfYaunTpguXLl6NXr1547733AKhaadatW4cFCxZgxIgR6NGjBz799FPcuHEDsbGxauc6ePAgvv/+e6xevVr3KyXTUHlX7oq//NiMTURE0DHUlJSU4MyZMwgODn5wArkcwcHBSEhI0PqYhIQEtfIAEBISIpVPTU1Fenq6WhlHR0cEBgaqnTMjIwMRERH47LPPYGtrW2tdi4uLkZubq3YjE1KxK7dHAAMNEREB0DHUZGVloaysDG3atFE73qZNG6Snp2t9THp6eo3lK/6tqYwQAhMnTsRLL72EPn361Kmu0dHRcHR0lG5eXvzgIyIiMmX1Gijc3N59913cu3cP8+bNq/Nj5s2bh5ycHOl27dq1JqwhERER6ZtOocbV1RUWFhbIyMhQO56RkQGlUqn1MUqlssbyFf/WVObIkSNISEiAtbU1WrRogQ4dOgAA+vTpg7CwMK3Pa21tDQcHB7UbERERmS6dQo2VlRV69+6N+Ph46Vh5eTni4+MRFBSk9TFBQUFq5QHg0KFDUnlfX18olUq1Mrm5uUhMTJTKbNiwAefPn0dSUhKSkpKkKeG7du3Cm2++qcslkLGpPH2bU7iJTJfmz3o2W9dJdzovvhcVFYWwsDD06dMHffv2xbp165Cfn49JkyYBACZMmABPT09ER0cDAGbMmIGBAwdizZo1GDp0KHbu3InTp09j06ZNAACZTIaZM2dixYoV8PPzg6+vLxYuXAgPDw+EhoYCALy9vdXqYG+vWrK/ffv2eOihh+p98WTgKqZvlxaoH+cUbiLTou1nnQv0UT3oHGrGjBmDW7duYdGiRUhPT0dAQADi4uKkgb5paWmQyx80APXr1w87duzAggULMH/+fPj5+SE2NhbdunWTysyZMwf5+fmYMmUKsrOzMWDAAMTFxcHGxqYRLpGMVuXp25XXtuAS60TGr3Kra9af6j/rWX+q1qAquM2fddJJvbZJiIyMRGRkpNb7jh07VuXYqFGjMGrUqGrPJ5PJsGzZMixbtqxOz+/j4wMhRJ3KkgmomL5NRMZP27YJgOqYdxBDDDUI934iNdezC3E3vwQAkJKZp+faEJHJqdg2QXObBLbAUiNgqCHJ9exCBK85jsLSMumYwtICznZWeqwVEZkcJy8GGGoSDDUkuZtfgsLSMqwbE4AObqrB2M52VvB0Uui5ZkRERLVjqKEqOrjZo5uno76rQUREpBOjWFGYiIiIqDYMNURERGQSGGqIiIjIJDDUEBERkUlgqCEiIiKTwFBDREREJoFTuomIyDBV3h8K4KrDVCuGGiIiMiw17Q/FnbupBgw1RERkWLTtD1Wxc3dawoPjbLkhDQw1RERkeDT3h9LWesOWG9LAUENERIZPs/VGW8sNwNYbM8dQQ4Yl+5r6Ly0iogqVW2847oa0YKghw5F9DdjYFygteHDM0lb1y4uIqLKaxt0U3GaoMVMMNWQ4Cm6rAs3IzYBrR9UxNiUTUXU0x92Q2WOoIf2p3NUEPOhucu0IeATopUpERGS8GGpIP7R1NQHsbiIig5aSmSf939nOCp5OCj3WhjQx1JB+aOtqAtjdREQGydnOCgpLC8zclSQdU1ha4PCsgQw2BoShhvSLXU1E1NQ0u7rr8ceTp5MCh2cNxN38EgCqFpuZu5JwN7+EocaAMNQQEZHpqm5WZT2mfXs6KWoNMNezC6XgA7CLqrkx1BARkenS7Opu5GnflcfY3M4vwUufnUFhaZl0jF1UzYuhhoiITF8jd3VrG2MDqELMJ5P7wsXOil1UesBQQ0REpCPNMTYV2N2kXww1RERE9VCXMTbUvOT6rgARERFRY2CoISIiIpPAUENEREQmgWNqzJjmegqVpyYSERmtin3kNP9fXRmAq5mbCIYaM3U9uxDBa46rracAqKYjOttZNc2TVl7Vs7pfNERE9WXrolpYb0+E+vHKe8rVVKYeC/KRYWGoMVN380tQWFqGdWMC0MHNXjreZNMRq1vVk5tXElFjcfJSBZPKWyIA6q0w2so08oJ8pD8MNWaug5s9unk6Nv6JNfdayfqz6gaWbO4losbm5FX775XqylRuQebvJ6PEUEONT1urDKBqmfEO4i8KIjIs2rqk2B1llBhqqPFp7rVSgX/5EJEh0uySYneU0WKooabTyHutEBE1mbp0W5HB4zo1REREZBLYUmNGKq9LwzVpiIjI1DDUmAlt69I06Zo0REREzYyhxkxoW5emydakISIi0gOGGjPTZOvSEBER6RlDDRERURPSHMPIVvKmw1BDRESkTQM3vXS2s4LC0gIzdyWpHVdYWuDwrIEMNk2AoYaIiKiyRtr00tNJgcOzBkqzTgFVq83MXUm4m1/CUNMEGGqIiIgqa8RNLz2dFAwvzYihhoiISBM3vTRKDDVERES14aaXRoGhhoiIqDbVbXqZlqDeTaXZepN9Te1+m6w8eCCrmSptfhhqqHFU/sHVnDFARGQKKndJ1WUwcfY1YGNfoLRAursDgMPW1riW9wgArhnW2BhqqOG0/ODC0lb1Q09EZIpqGkxc0XqT9afq9+LIzYBrRwDAtctJ8Do6AxZFd/RUcdPGUGOiKm9eCTTxBpYFt6v84HIAHRGZPM3BxNWNu/EOksoV3+Jmwk2JocYEadu8EmiGDSxdOwIeAU13fiIiQ6at9YZ/4DUrhhoTpG3zSoBLcxMRNbnqpoJTs2CoMWHcvJKIiMwJQw0REVEzu3anEEXXc6Sv2ZLeOOT1edDGjRvh4+MDGxsbBAYG4tSpUzWW3717Nzp37gwbGxt0794dBw4cULtfCIFFixbB3d0dCoUCwcHBuHz5snT/1atXER4eDl9fXygUCrRv3x6LFy9GSUmJ5lMREREZLAeFJQAg9tARzH3vM+n2/JqvcT27UM+1M346h5pdu3YhKioKixcvxtmzZ+Hv74+QkBBkZmZqLX/y5EmMGzcO4eHhOHfuHEJDQxEaGooLFy5IZVauXIkNGzYgJiYGiYmJsLOzQ0hICIqKigAAf/zxB8rLy/Hhhx/i4sWLWLt2LWJiYjB//vx6XjYREVHzc3PzQHkLBdZbvY/91m9It33yKORlpOq7ekZPJoQQujwgMDAQjzzyCN577z0AQHl5Oby8vDBt2jS8/vrrVcqPGTMG+fn52Ldvn3Ts0UcfRUBAAGJiYiCEgIeHB2bNmoXZs2cDAHJyctCmTRts27YNY8eO1VqPVatW4YMPPsBff/2l9f7i4mIUFxdLX+fm5sLLyws5OTlwcHDQ5ZKNzoXrORj27o/YN21A04yp0VghU1qbYcpxzn4iIqqNxu/QirVrrj2xHl5+AaqDnDUlyc3NhaOjY50+v3UaU1NSUoIzZ85g3rx50jG5XI7g4GAkJCRofUxCQgKioqLUjoWEhCA2NhYAkJqaivT0dAQHB0v3Ozo6IjAwEAkJCdWGmpycHLRq1araukZHR2Pp0qV1vTSqK20L7QFcbI+IqK40ZkgV3LNCgbCG19EZwNH/HuS+UvWiU6jJyspCWVkZ2rRpo3a8TZs2+OOPP7Q+Jj09XWv59PR06f6KY9WV0ZSSkoJ3330Xq1evrrau8+bNUwtTFS011EDaFtoD+FcFEVE9ldp7Irh4FT4d1x4dWtvXfV8pqsLoZj9dv34dQ4YMwahRoxAREVFtOWtra1hbWzdjzUyUtq4mgAvtERE1ohtwRZFrd8DDsW77SpFWOoUaV1dXWFhYICMjQ+14RkYGlEql1scolcoay1f8m5GRAXd3d7UyAQEBao+7ceMGnnjiCfTr1w+bNm3SpepUH+xqIiJqfjXtK1Vwm6GmBjrNfrKyskLv3r0RHx8vHSsvL0d8fDyCgoK0PiYoKEitPAAcOnRIKu/r6wulUqlWJjc3F4mJiWrnvH79Oh5//HH07t0bW7duhVxer9nopIvKXU1Tjj+48S8FIqKm5eSlag2vuFXu7qdq6dz9FBUVhbCwMPTp0wd9+/bFunXrkJ+fj0mTJgEAJkyYAE9PT0RHRwMAZsyYgYEDB2LNmjUYOnQodu7cidOnT0stLTKZDDNnzsSKFSvg5+cHX19fLFy4EB4eHggNDQXwINC0bdsWq1evxq1bt6T6VNdCRI2IXU1ERGQEdA41Y8aMwa1bt7Bo0SKkp6cjICAAcXFx0kDftLQ0tVaUfv36YceOHViwYAHmz58PPz8/xMbGolu3blKZOXPmID8/H1OmTEF2djYGDBiAuLg42NjYAFC17KSkpCAlJQUPPfSQWn10nJFORERkvCrGNQLaBw5rjoM0s8HFOq9TY6x0medu7BptnZobScCmgVx/hoioCdXpd7a2MY6WtsCYzwBbV9XXBVnAruerljHyIQNNtk4NmYHKKb/yXwRERKQ/moOHKwLM58+ql7O0BZ77WhV0zHBwMUMNPVDdXwKc6UREpH8ai/ZVmSEFmF13kyaGGhNxPbsQd/NVG3ymZObV7yTaFtYz8x8QIiKDpRlyiKHGFFzPLkTwmuMoLC2TjiksLeBsZ1XzA7mwHhERmRCGGhNwN78EhaVlWDcmAB3c7AEAznZW8HRSVP8gLqxHRGQeahsfaUIt8gw1JqSDm33Ns500BwFzDyciIoNReehArX+Y1kV12y1oMoEZUhUYasxFdYOAvYNM4huZiMhYOdtZQWFpgZm7kqRjCksLHJ41sGHBRtt2C5pMbIYUQ4254CBgIiKD5OmkwOFZA9Ume8zclYRfUu/g7n+HFAD1bL0xs8HEDDXmhoOAiYgMjqeTQgos2lpugEZqvTFxDDVEREQGRLPlBnjQenM3v8RwQo3mDFpA7z0ADDVEREQGpnLLjUGqaQatHgcdM9QQERGRbrSN0zSAQccMNURERKSurl1LBjZOk6HGCFXeEgFowLYIREREmgy0a6kuGGqMjLYtEYA6botARESkTeVVh7UtzmoAXUt1wVBjZLRtiQA00uqTRERkXqpbddhIF2dlqDFStW6JQEREVJvqVh020sVZGWqIiIjMmQmtOizXdwWIiIiIGgNbakyV5nS82raeJyIiMnIMNaaopul4ti76qRMRETVY5SU8OEGkKoYaU6RtpUfAaAd+ERGZO22bXHKDy6oYakyZga30SERE9aO5yaXeNrisGMpgoEMaGGqIiIiMgF43udS2no0BDmlgqCEiIqKaaVvPxgCHNDDUmIrKs50MtFmQiIiMmBGsZ8NQo0eaG1MCdRvN7oEs2GT9Bsj+u01CQRaw63n12U4G2CxIRETUlBhq9KSmjSk1R7NXDj/Xr/6Jw9avwXZvsfoJLW2B574GbF1VXxtgsyAREVFTYqjRE20bU2obza4Zfh6WpSLEuhh3hmxEK+9uD07IEENEZHYqr1sDcO0ahho909yY0gNZuPXnKaRkqb4pr90pRLv7KZgd0glerRSwzrYHjkIVaDhdm4jILGlbtwbg2jUMNQbEtSxT1bV0/EHXUgcAT1gDOF6pIMfLEBGZNc11awA9rl1jQBhqmlHlsTGaTYYAoGyRD8iKce2J9Sh26iAdd1BYws3e+kFBdjUREZk9va5bY6AYapqJtoHBCksLONtZVSnr5RfAriUiIiIdMdQ0E20Dg819QBcRETWt+i4dYqwYapqZ5sBgIiKixlQxvOF2fgle+uxMnZYOMRUMNURERCagup28P5ncFy7/Hepg6oOJGWqIiIhMgLYZUabc1aQNQ40+Vd6vCeCeTURE1CB1nRFVeQauKQUfhhp9yb4GbOyrvl8TwDVoiIioyVTXRWUqY2wYapqR2kaUWX+qAs3IzYBrxweFuAYNERE1Ec0uKlMbY8NQ00ws865X3YjS0hbwDmKIISKiZmPKi/Yx1DQTi6I7sP3vasFefgGqg2yVISIiA2AqG2My1DSR9LTLyLubIX2d/fcFAFBtf8DVgomIyACY2saYDDWNpPKqjXmZV9Ej9kkoZcVqZQqENeyd2+ijekRERFWY2saYDDWNQHNfp4dlqdhvXYzfg9bAUtlZKmfv3AZKbz99VZOIiKiK6sbYGGOXFENNI9Dc18kmyxHYC3Tp3oddTUREZFSMuUuKoaaReCAL3eSp6CCzB2Q39F0dIiKiejHmLimGmkZQ7XRtLqJHRERGqC7TvjV3ALfJykOHpq5YLRhqGgGnaxMRkTnRHEsKVIwnBTLziuGmp3ox1DQiTtcmIiJzoDmWFABu/WkFHAdyC0sZaoiIiMi4dHCzRzdPRwBASpb+x9rI9V0BIiIiosbAlhoiIiKqk4q1azTXsDEUDDVERERUI21r1ygsLeBsZ6W/SmnBUENEREQ10rZ2jSGuMFyvMTUbN26Ej48PbGxsEBgYiFOnTtVYfvfu3ejcuTNsbGzQvXt3HDhwQO1+IQQWLVoEd3d3KBQKBAcH4/Lly2pl7ty5g/Hjx8PBwQFOTk4IDw9HXp5hNn8RERGZGk8nBbp5Oko3Qws0QD1Cza5duxAVFYXFixfj7Nmz8Pf3R0hICDIzM7WWP3nyJMaNG4fw8HCcO3cOoaGhCA0NxYULF6QyK1euxIYNGxATE4PExETY2dkhJCQERUVFUpnx48fj4sWLOHToEPbt24cffvgBU6ZMqcclExERkUkSOurbt6+YOnWq9HVZWZnw8PAQ0dHRWsuPHj1aDB06VO1YYGCgePHFF4UQQpSXlwulUilWrVol3Z+dnS2sra3FF198IYQQ4tKlSwKA+OWXX6QyBw8eFDKZTFy/fr1O9c7JyREARE5OTt0uVAeXk04IsdhB9S8REZEZaqrPQl0+v3UaU1NSUoIzZ85g3rx50jG5XI7g4GAkJCRofUxCQgKioqLUjoWEhCA2NhYAkJqaivT0dAQHB0v3Ozo6IjAwEAkJCRg7diwSEhLg5OSEPn36SGWCg4Mhl8uRmJiIZ555psrzFhcXo7j4wbYFOTk5AIDc3FxdLrlO7uXlI7dYqP5tgvMTEREZuqb6LKw4lxCi1rI6hZqsrCyUlZWhTZs2asfbtGmDP/74Q+tj0tPTtZZPT0+X7q84VlMZNzf19QlbtGiBVq1aSWU0RUdHY+nSpVWOe3k14dYFbw9punMTEREZgyb6LLx37x4cHR1rLGOys5/mzZun1kJUXl6OO3fuwMXFBTKZrMbH5ubmwsvLC9euXYODg0NTV1UveI2mgddoGniNpoHX2DSEELh37x48PDxqLatTqHF1dYWFhQUyMjLUjmdkZECpVGp9jFKprLF8xb8ZGRlwd3dXKxMQECCV0RyIfP/+fdy5c6fa57W2toa1tbXaMScnp5ovUIODg4PJfmNW4DWaBl6jaeA1mgZeY+OrrYWmgk6zn6ysrNC7d2/Ex8dLx8rLyxEfH4+goCCtjwkKClIrDwCHDh2Syvv6+kKpVKqVyc3NRWJiolQmKCgI2dnZOHPmjFTmyJEjKC8vR2BgoC6XQERERCZK5+6nqKgohIWFoU+fPujbty/WrVuH/Px8TJo0CQAwYcIEeHp6Ijo6GgAwY8YMDBw4EGvWrMHQoUOxc+dOnD59Gps2bQIAyGQyzJw5EytWrICfnx98fX2xcOFCeHh4IDQ0FADQpUsXDBkyBBEREYiJiUFpaSkiIyMxduzYOjVHERERkenTOdSMGTMGt27dwqJFi5Ceno6AgADExcVJA33T0tIglz9oAOrXrx927NiBBQsWYP78+fDz80NsbCy6desmlZkzZw7y8/MxZcoUZGdnY8CAAYiLi4ONjY1UZvv27YiMjMTgwYMhl8vx7LPPYsOGDQ259mpZW1tj8eLFVbqvTAmv0TTwGk0Dr9E08Br1TybqMkeKiIiIyMDVa5sEIiIiIkPDUENEREQmgaGGiIiITAJDDREREZkEsw410dHReOSRR9CyZUu4ubkhNDQUycnJamUef/xxyGQytdtLL72kpxrrbsmSJVXq37lzZ+n+oqIiTJ06FS4uLrC3t8ezzz5bZbFEQ+fj41PlGmUyGaZOnQrAON/DH374AcOHD4eHhwdkMpm0V1oFIQQWLVoEd3d3KBQKBAcH4/Lly2pl7ty5g/Hjx8PBwQFOTk4IDw9HXl5eM15F9Wq6vtLSUsydOxfdu3eHnZ0dPDw8MGHCBNy4cUPtHNre97fffruZr6R6tb2HEydOrFL/IUPUl5c35PcQqP0atf1cymQyrFq1Sipj6O9jXT4n6vJ7NC0tDUOHDoWtrS3c3Nzw2muv4f79+815KdWq7Rrv3LmDadOmoVOnTlAoFPD29sb06dOlPRUraHuvd+7c2azXYtah5vjx45g6dSp+/vlnHDp0CKWlpXjqqaeQn5+vVi4iIgI3b96UbitXrtRTjevn4YcfVqv/jz/+KN336quv4v/+7/+we/duHD9+HDdu3MDIkSP1WFvd/fLLL2rXd+jQIQDAqFGjpDLG9h7m5+fD398fGzdu1Hr/ypUrsWHDBsTExCAxMRF2dnYICQlBUVGRVGb8+PG4ePEiDh06hH379uGHH37AlClTmusSalTT9RUUFODs2bNYuHAhzp49iz179iA5ORn/+te/qpRdtmyZ2vs6bdq05qh+ndT2HgLAkCFD1Or/xRdfqN1vyO8hUPs1Vr62mzdvYsuWLZDJZHj22WfVyhny+1iXz4nafo+WlZVh6NChKCkpwcmTJ/HJJ59g27ZtWLRokT4uqYrarvHGjRu4ceMGVq9ejQsXLmDbtm2Ii4tDeHh4lXNt3bpV7b2sWG+u2TTq/uBGLjMzUwAQx48fl44NHDhQzJgxQ3+VaqDFixcLf39/rfdlZ2cLS0tLsXv3bunY77//LgCIhISEZqph45sxY4Zo3769KC8vF0IY/3sIQOzdu1f6ury8XCiVSrFq1SrpWHZ2trC2thZffPGFEEKIS5cuCQDil19+kcocPHhQyGQycf369Ware11oXp82p06dEgDE33//LR1r27atWLt2bdNWrpFou8awsDAxYsSIah9jTO+hEHV7H0eMGCEGDRqkdsyY3kchqn5O1OX36IEDB4RcLhfp6elSmQ8++EA4ODiI4uLi5r2AOtD2Wajpyy+/FFZWVqK0tFQ6VpfvgaZm1i01miqa0lq1aqV2fPv27XB1dUW3bt0wb948FBQU6KN69Xb58mV4eHigXbt2GD9+PNLS0gAAZ86cQWlpKYKDg6WynTt3hre3NxISEvRV3QYpKSnB559/jsmTJ6ttXGrs72FlqampSE9PV3vfHB0dERgYKL1vCQkJcHJyQp8+faQywcHBkMvlSExMbPY6N1ROTg5kMlmV/dvefvttuLi4oGfPnli1apXBNOfX1bFjx+Dm5oZOnTrh5Zdfxu3bt6X7TO09zMjIwP79+7X+dW9M76Pm50Rdfo8mJCSge/fu0iK1ABASEoLc3FxcvHixGWtfN9V9FmqWcXBwQIsW6mv4Tp06Fa6urujbty+2bNkC0cxL4ZnsLt26Ki8vx8yZM9G/f3+11Y7/53/+B23btoWHhwd+/fVXzJ07F8nJydizZ48ea1t3gYGB2LZtGzp16oSbN29i6dKleOyxx3DhwgWkp6fDysqqygdFmzZtkJ6erp8KN1BsbCyys7MxceJE6Zixv4eaKt6byr8gK76uuC89PR1ubm5q97do0QKtWrUyuve2qKgIc+fOxbhx49Q20Js+fTp69eqFVq1a4eTJk5g3bx5u3ryJd955R4+1rbshQ4Zg5MiR8PX1xZUrVzB//nw8/fTTSEhIgIWFhUm9hwDwySefoGXLllW6t43pfdT2OVGX36Pp6elaf14r7jMk1X0WVpaVlYXly5dX6QpdtmwZBg0aBFtbW3z//fd45ZVXkJeXh+nTpzdH1QEw1EimTp2KCxcuqI03AaD2pnXv3h3u7u4YPHgwrly5gvbt2zd3NXX29NNPS//v0aMHAgMD0bZtW3z55ZdQKBR6rFnT+Pjjj/H000+r7Qlm7O+hOSstLcXo0aMhhMAHH3ygdl9UVJT0/x49esDKygovvvgioqOjDXYJ98rGjh0r/b979+7o0aMH2rdvj2PHjmHw4MF6rFnT2LJlC8aPH6+2/Q1gXO9jdZ8TpqS2a8zNzcXQoUPRtWtXLFmyRO2+hQsXSv/v2bMn8vPzsWrVqmYNNex+AhAZGYl9+/bh6NGjeOihh2osW7EreEpKSnNUrdE5OTmhY8eOSElJgVKpRElJCbKzs9XKZGRkQKlU6qeCDfD333/j8OHDeOGFF2osZ+zvYcV7ozm7ovL7plQqkZmZqXb//fv3cefOHaN5bysCzd9//41Dhw6ptdJoExgYiPv37+Pq1avNU8FG1q5dO7i6ukrfl6bwHlY4ceIEkpOTa/3ZBAz3fazuc6Iuv0eVSqXWn9eK+wxFbZ+F9+7dw5AhQ9CyZUvs3bsXlpaWNZ4vMDAQ//nPf1BcXNxUVa7CrEONEAKRkZHYu3cvjhw5Al9f31ofk5SUBABwd3dv4to1jby8PFy5cgXu7u7o3bs3LC0tER8fL92fnJyMtLQ0BAUF6bGW9bN161a4ublh6NChNZYz9vfQ19cXSqVS7X3Lzc1FYmKi9L4FBQUhOzsbZ86ckcocOXIE5eXlUqgzZBWB5vLlyzh8+DBcXFxqfUxSUhLkcnmVLhtj8Z///Ae3b9+Wvi+N/T2s7OOPP0bv3r3h7+9fa1lDex9r+5yoy+/RoKAg/Pbbb2ohtSKod+3atXkupAZ1+SzMzc3FU089BSsrK3z77bdVWty0SUpKgrOzc/O2uOl1mLKevfzyy8LR0VEcO3ZM3Lx5U7oVFBQIIYRISUkRy5YtE6dPnxapqanim2++Ee3atRP/+Mc/9Fzzups1a5Y4duyYSE1NFT/99JMIDg4Wrq6uIjMzUwghxEsvvSS8vb3FkSNHxOnTp0VQUJAICgrSc611V1ZWJry9vcXcuXPVjhvre3jv3j1x7tw5ce7cOQFAvPPOO+LcuXPS7J+3335bODk5iW+++Ub8+uuvYsSIEcLX11cUFhZK5xgyZIjo2bOnSExMFD/++KPw8/MT48aN09clqanp+kpKSsS//vUv8dBDD4mkpCS1n82KmSInT54Ua9euFUlJSeLKlSvi888/F61btxYTJkzQ85U9UNM13rt3T8yePVskJCSI1NRUcfjwYdGrVy/h5+cnioqKpHMY8nsoRO3fp0IIkZOTI2xtbcUHH3xQ5fHG8D7W9jkhRO2/R+/fvy+6desmnnrqKZGUlCTi4uJE69atxbx58/RxSVXUdo05OTkiMDBQdO/eXaSkpKiVuX//vhBCiG+//VZs3rxZ/Pbbb+Ly5cvi/fffF7a2tmLRokXNei1mHWoAaL1t3bpVCCFEWlqa+Mc//iFatWolrK2tRYcOHcRrr70mcnJy9FtxHYwZM0a4u7sLKysr4enpKcaMGSNSUlKk+wsLC8Urr7winJ2dha2trXjmmWfEzZs39Vjj+vnuu+8EAJGcnKx23Fjfw6NHj2r93gwLCxNCqKZ1L1y4ULRp00ZYW1uLwYMHV7n227dvi3Hjxgl7e3vh4OAgJk2aJO7du6eHq6mqputLTU2t9mfz6NGjQgghzpw5IwIDA4Wjo6OwsbERXbp0EW+99ZZaINC3mq6xoKBAPPXUU6J169bC0tJStG3bVkRERKhN+RXCsN9DIWr/PhVCiA8//FAoFAqRnZ1d5fHG8D7W9jkhRN1+j169elU8/fTTQqFQCFdXVzFr1iy16dD6VNs1Vvc+AxCpqalCCNVyAwEBAcLe3l7Y2dkJf39/ERMTI8rKypr1WmT/vSAiIiIio2bWY2qIiIjIdDDUEBERkUlgqCEiIiKTwFBDREREJoGhhoiIiEwCQw0RERGZBIYaIiIiMgkMNURERGQSGGqIjMDEiRMRGhra5M8jk8kQGxvb5M9jrLZt2wYnJ6cGn+fq1auQyWTSPmRNbeHChWq71Te3kpIS+Pj44PTp03qrA5kHhhqiWkycOBEymQwymQyWlpbw9fXFnDlzUFRUpO+qNbuK1+Kll16qct/UqVMhk8kwceLE5q8YgLKyMrz99tvo3LkzFAoFWrVqhcDAQHz00Ud6qU8FbYHUy8sLN2/eRLdu3Zr8+dPT07F+/Xq88cYbVY7PmDEDHTp0gI2NDdq0aYP+/fvjgw8+QEFBQZ3OvWbNGjg7O2v9WSgoKICDgwM2bNgAKysrzJ49G3Pnzm2UayKqDkMNUR0MGTIEN2/exF9//YW1a9fiww8/xOLFi/VdLb3w8vLCzp07UVhYKB0rKirCjh074O3trbd6LV26FGvXrsXy5ctx6dIlHD16FFOmTEF2drbe6lQdCwsLKJVKtGjRosmf66OPPkK/fv3Qtm1b6dhff/2Fnj174vvvv8dbb72Fc+fOISEhAXPmzMG+fftw+PDhOp37+eefR35+Pvbs2VPlvq+++golJSV47rnnAADjx4/Hjz/+iIsXLzbOhRFpwVBDVAfW1tZQKpXw8vJCaGgogoODcejQIen+8vJyREdHw9fXFwqFAv7+/vjqq6+k++/evYvx48ejdevWUCgU8PPzw9atW6X7f/vtNwwaNAgKhQIuLi6YMmUK8vLytNZl06ZN8PDwQHl5udrxESNGYPLkydLX33zzDXr16gUbGxu0a9cOS5cuxf3796X7L1++jH/84x+wsbFB165d1a6nJr169YKXl5faB9mePXvg7e2Nnj17qpWNi4vDgAED4OTkBBcXFwwbNgxXrlyR7i8pKUFkZCTc3d1hY2ODtm3bIjo6GgAghMCSJUvg7e0Na2treHh4YPr06dXW69tvv8Urr7yCUaNGwdfXF/7+/ggPD8fs2bOlMuXl5Vi5ciU6dOgAa2treHt748033wQAHDt2DDKZTC0EJSUlQSaT4erVq1qfc8mSJQgICMCHH34ILy8v2NraYvTo0cjJyZHu/+STT/DNN99IrX3Hjh2r0v1U8dzx8fHo06cPbG1t0a9fPyQnJ6s934oVK+Dm5oaWLVvihRdewOuvv46AgIBqXxMA2LlzJ4YPH6527JVXXkGLFi1w+vRpjB49Gl26dEG7du0wYsQI7N+/X618dnY2XnjhBbRu3RoODg4YNGgQzp8/DwBwc3PD8OHDsWXLlirPu2XLFoSGhqJVq1YAAGdnZ/Tv3x87d+6ssb5EDcFQQ6SjCxcu4OTJk7CyspKORUdH49NPP0VMTAwuXryIV199Fc899xyOHz8OQDWm4dKlSzh48CB+//13fPDBB3B1dQUA5OfnIyQkBM7Ozvjll1+we/duHD58GJGRkVqff9SoUbh9+zaOHj0qHbtz5w7i4uIwfvx4AMCJEycwYcIEzJgxA5cuXcKHH36Ibdu2SR/g5eXlGDlyJKysrJCYmIiYmBidugYmT56sFsq2bNmCSZMmVSmXn5+PqKgonD59GvHx8ZDL5XjmmWekQLZhwwZ8++23+PLLL5GcnIzt27fDx8cHAPD1119LrWKXL19GbGwsunfvXm2dlEoljhw5glu3blVbZt68eXj77bel92PHjh1o06ZNna9bm5SUFHz55Zf4v//7P8TFxeHcuXN45ZVXAACzZ8/G6NGjpZa+mzdvol+/ftWe64033sCaNWtw+vRptGjRQi2kbt++HW+++Sb+93//F2fOnIG3tzc++OCDGut2584dXLp0CX369JGO3b59G99//z2mTp0KOzs7rY+TyWTS/0eNGoXMzEwcPHgQZ86cQa9evTB48GDcuXMHABAeHo4jR47g77//lh7z119/4YcffkB4eLjaefv27YsTJ07UWGeiBmnWPcGJjFBYWJiwsLAQdnZ2wtraWgAQcrlcfPXVV0IIIYqKioStra04efKk2uPCw8PFuHHjhBBCDB8+XEyaNEnr+Tdt2iScnZ1FXl6edGz//v1CLpeL9PR0qQ4jRoyQ7h8xYoSYPHmy9PWHH34oPDw8RFlZmRBCiMGDB4u33npL7Xk+++wz4e7uLoQQ4rvvvhMtWrQQ169fl+4/ePCgACD27t1b42sxYsQIkZmZKaytrcXVq1fF1atXhY2Njbh165YYMWKECAsLq/bxt27dEgDEb7/9JoQQYtq0aWLQoEGivLy8Stk1a9aIjh07ipKSkmrPV9nFixdFly5dhFwuF927dxcvvviiOHDggHR/bm6usLa2Fps3b9b6+KNHjwoA4u7du9Kxc+fOCQAiNTVVCCHE1q1bhaOjo3T/4sWLhYWFhfjPf/4jHTt48KCQy+Xi5s2bQoiq750QQqSmpgoA4ty5c2rPffjwYanM/v37BQBRWFgohBAiMDBQTJ06Ve08/fv3F/7+/tW+JhX1T0tLk479/PPPAoDYs2ePWlkXFxdhZ2cn7OzsxJw5c4QQQpw4cUI4ODiIoqIitbLt27cXH374oRBCiPv37wtPT0+xePFi6f6FCxcKb29v6fuxwvr164WPj0+19SVqKLbUENXBE088gaSkJCQmJiIsLAyTJk3Cs88+C0D1l3pBQQGefPJJ2NvbS7dPP/1U6mp5+eWXsXPnTgQEBGDOnDk4efKkdO7ff/8d/v7+an819+/fH+Xl5VW6HyqMHz8eX3/9NYqLiwGo/oofO3Ys5HLVj/T58+exbNkytfpERETg5s2bKCgowO+//w4vLy94eHhI5wwKCqrz69G6dWsMHToU27Ztw9atWzF06FCp5amyy5cvY9y4cWjXrh0cHBykVpi0tDQAqkG0SUlJ6NSpE6ZPn47vv/9eeuyoUaNQWFiIdu3aISIiAnv37lXrPtPUtWtXXLhwAT///DMmT56MzMxMDB8+HC+88AIA1etcXFyMwYMH1/k668Lb2xuenp7S10FBQTW+dzXp0aOH9H93d3cAQGZmJgAgOTkZffv2VSuv+bWminFPNjY2tT73qVOnkJSUhIcfflj6vjp//jzy8vLg4uKi9r2UmpoqfW9bWFggLCwM27ZtgxAC5eXl+OSTTzBp0iTp+7GCQqGo8yBkovpo+lFqRCbAzs4OHTp0AKDqavH398fHH3+M8PBwaezL/v371T7cANVYHAB4+umn8ffff+PAgQM4dOgQBg8ejKlTp2L16tX1qs/w4cMhhMD+/fvxyCOP4MSJE1i7dq10f15eHpYuXYqRI0dWeWxdPuDqYvLkyVIX2caNG6utZ9u2bbF582ZpHFC3bt1QUlICQDU+JzU1FQcPHsThw4cxevRoBAcH46uvvoKXlxeSk5Nx+PBhHDp0CK+88gpWrVqF48ePw9LSUuvzyeVyPPLII3jkkUcwc+ZMfP7553j++efxxhtvQKFQ1Hg9FR/AQgjpWGlpqc6vS0NUvq6KLiDNsVO6qAiad+/eRevWrQEAHTp0gEwmqxK62rVrBwBqr1NeXh7c3d1x7NixKueuPLV98uTJiI6OxpEjR1BeXo5r165p7Y68c+eOVA+ipsCWGiIdyeVyzJ8/HwsWLEBhYSG6du0Ka2trpKWloUOHDmo3Ly8v6XGtW7dGWFgYPv/8c6xbtw6bNm0CAHTp0gXnz59Hfn6+VPann36CXC5Hp06dtNbBxsYGI0eOxPbt2/HFF1+gU6dO6NWrl3R/r169kJycXKU+HTp0gFwuR5cuXXDt2jXcvHlTeszPP/+s0+swZMgQlJSUoLS0FCEhIVXuv337NpKTk7FgwQIMHjwYXbp0wd27d6uUc3BwwJgxY7B582bs2rULX3/9tTReQ6FQYPjw4diwYQOOHTuGhIQE/Pbbb3WuY9euXQGoxvb4+flBoVAgPj5ea9mKD9vKr0ld1pFJS0vDjRs3pK9//vlntffOysoKZWVlda5zdTp16oRffvlF7Zjm15rat28PBwcHXLp0STrm4uKCJ598Eu+9957a95w2vXr1Qnp6Olq0aFHl+6hyy1z79u0xcOBAbNmyBVu3bkVwcLDabKsKFy5cqDKYnKgxsaWGqB5GjRqF1157DRs3bsTs2bMxe/ZsvPrqqygvL8eAAQOQk5ODn376CQ4ODggLC8OiRYvQu3dvqWl/37596NKlCwBVV9LixYsRFhaGJUuW4NatW5g2bRqef/75Ggexjh8/HsOGDcPFixelabMVFi1ahGHDhsHb2xv//ve/IZfLcf78eVy4cAErVqxAcHAwOnbsiLCwMKxatQq5ublV1jGpjYWFBX7//Xfp/5qcnZ3h4uKCTZs2wd3dHWlpaXj99dfVyrzzzjtwd3dHz549IZfLsXv3biiVSjg5OWHbtm0oKytDYGAgbG1t8fnnn0OhUGj9sASAf//73+jfvz/69esHpVKJ1NRUzJs3Dx07dkTnzp3RokULzJ07F3PmzIGVlRX69++PW7du4eLFiwgPD5dC6JIlS/Dmm2/izz//xJo1a2p9HWxsbBAWFobVq1cjNzcX06dPx+jRo6FUKgEAPj4++O6775CcnAwXFxc4Ojrq9DpXmDZtGiIiItCnTx/069cPu3btwq+//iq1sGgjl8sRHByMH3/8UW2tnPfffx/9+/dHnz59sGTJEvTo0QNyuRy//PIL/vjjD/Tu3RsAEBwcjKCgIISGhmLlypXo2LEjbty4gf379+OZZ55RG4AcHh6OiIgIAKpFCrU5ceIEli9fXq/rJ6oTPY/pITJ42gZ6CiFEdHS0aN26tcjLyxPl5eVi3bp1olOnTsLS0lK0bt1ahISEiOPHjwshhFi+fLno0qWLUCgUolWrVmLEiBHir7/+ks7166+/iieeeELY2NiIVq1aiYiICHHv3r0a61BWVibc3d0FAHHlypUq9YuLixP9+vUTCoVCODg4iL59+4pNmzZJ9ycnJ4sBAwYIKysr0bFjRxEXF1fngcLV0RwofOjQIdGlSxdhbW0tevToIY4dO6b2HJs2bRIBAQHCzs5OODg4iMGDB4uzZ88KIYTYu3evCAwMFA4ODsLOzk48+uijagNpNW3atEk88cQTonXr1sLKykp4e3uLiRMniqtXr6q9ZitWrBBt27YVlpaWwtvbW21A9Y8//ii6d+8ubGxsxGOPPSZ2795d60Bhf39/8f777wsPDw9hY2Mj/v3vf4s7d+5IZTIzM8WTTz4p7O3tBQBx9OjRagcK1zRIWQghli1bJlxdXYW9vb2YPHmymD59unj00UerfU2EEOLAgQPC09OzyqDdGzduiMjISOHr6yssLS2Fvb296Nu3r1i1apXIz8+XyuXm5opp06YJDw8PYWlpKby8vMT48ePVBh8LIURBQYFwdHQUrVq1qjKwWAghTp48KZycnERBQUGN9SVqCJkQlTqQiYiozpYsWYLY2Nhm2+5A05NPPgmlUonPPvus2jJCCAQGBuLVV1/FuHHjmrF26saMGQN/f3/Mnz9fb3Ug08fuJyIiI1BQUICYmBiEhITAwsICX3zxhTSIuiYymQybNm3SaSxSYyspKUH37t3x6quv6q0OZB4YaoiIjIBMJsOBAwfw5ptvoqioCJ06dcLXX3+N4ODgWh8bEBBQ68rDTcnKygoLFizQ2/OT+WD3ExEREZkETukmIiIik8BQQ0RERCaBoYaIiIhMAkMNERERmQSGGiIiIjIJDDVERERkEhhqiIiIyCQw1BAREZFJ+H8KQCxO/XtExAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(ak.ravel(reco_rh_mass_s), bins=np.arange(30, 230, 2), histtype='step', label='reweighted spanet', density=True)\n",
+    "plt.hist(ak.ravel(reco_rh_mass_b), bins=np.arange(30, 230, 2), histtype='step', label='baseline', density=True)\n",
+    "plt.legend()\n",
+    "plt.xlabel('Resolved Mass Sculpting (GeV)')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_rh_wOR_mass_s = get_reco_resolved_h_mass(s_h5, fjs_reco=fjs_reco_s)\n",
+    "reco_rh_wOR_mass_b = get_reco_resolved_h_mass(b_h5, fjs_reco=fjs_reco_b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "reco_merged_h_mass_s = ak.ravel(reco_bh_mass_s).tolist() + ak.ravel(reco_rh_wOR_mass_s).tolist()\n",
+    "reco_merged_h_mass_b = ak.ravel(reco_bh_mass_b).tolist() + ak.ravel(reco_rh_wOR_mass_b).tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Resolved+Boosted Mass Sculpting (GeV)')"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(reco_merged_h_mass_s, bins=np.arange(30, 230, 10), histtype='step', label='reweighted spanet', density=True)\n",
+    "plt.hist(reco_merged_h_mass_b, bins=np.arange(30, 230, 5), histtype='step', label='baseline', density=True)\n",
+    "plt.legend()\n",
+    "plt.xlabel('Resolved+Boosted Mass Sculpting (GeV)')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/analysis/boosted.py b/src/analysis/boosted.py
index 56c3b09..d899806 100644
--- a/src/analysis/boosted.py
+++ b/src/analysis/boosted.py
@@ -88,83 +88,66 @@ def gen_target_bH_LUT(bb_ps_passed, bb_ts_selected, targetH_pts):
 # each entry corresponds to [recoH correct or not, reco H pt]
 # or
 # [targetH retrieved or not, target H pt]
-def parse_boosted_w_target(testfile, predfile):
-    # Collect H pt, mask, target and predicted jet and fjets for 3 Hs in each event
-    # h pt
-    bh1_pt = np.array(testfile["TARGETS"]["bh1"]["pt"])
-    bh2_pt = np.array(testfile["TARGETS"]["bh2"]["pt"])
-    bh3_pt = np.array(testfile["TARGETS"]["bh3"]["pt"])
-
-    # mask
-    bh1_mask = np.array(testfile["TARGETS"]["bh1"]["mask"])
-    bh2_mask = np.array(testfile["TARGETS"]["bh2"]["mask"])
-    bh3_mask = np.array(testfile["TARGETS"]["bh3"]["mask"])
-
-    # target assignment
-    bb_bh1_t = np.array(testfile["TARGETS"]["bh1"]["bb"])
-    bb_bh2_t = np.array(testfile["TARGETS"]["bh2"]["bb"])
-    bb_bh3_t = np.array(testfile["TARGETS"]["bh3"]["bb"])
-
-    try:
-        # pred assignment
-        bb_bh1_p = np.array(predfile["TARGETS"]["bh1"]["bb"])
-        bb_bh2_p = np.array(predfile["TARGETS"]["bh2"]["bb"])
-        bb_bh3_p = np.array(predfile["TARGETS"]["bh3"]["bb"])
-
-        # boosted Higgs detection probability
-        dp_bh1 = np.array(predfile["TARGETS"]["bh1"]["detection_probability"])
-        dp_bh2 = np.array(predfile["TARGETS"]["bh2"]["detection_probability"])
-        dp_bh3 = np.array(predfile["TARGETS"]["bh3"]["detection_probability"])
-
-        # fatjet assignment probability
-        ap_bh1 = np.array(predfile["TARGETS"]["bh1"]["assignment_probability"])
-        ap_bh2 = np.array(predfile["TARGETS"]["bh2"]["assignment_probability"])
-        ap_bh3 = np.array(predfile["TARGETS"]["bh3"]["assignment_probability"])
-    except:
-        # pred assignment
-        bb_bh1_p = np.array(predfile["TARGETS"]["bh1"]["bb"]) + 10
-        bb_bh2_p = np.array(predfile["TARGETS"]["bh2"]["bb"]) + 10
-        bb_bh3_p = np.array(predfile["TARGETS"]["bh3"]["bb"]) + 10
-
-        # boosted Higgs detection probability
-        dp_bh1 = np.array(predfile["TARGETS"]["bh1"]["mask"]).astype("float")
-        dp_bh2 = np.array(predfile["TARGETS"]["bh2"]["mask"]).astype("float")
-        dp_bh3 = np.array(predfile["TARGETS"]["bh3"]["mask"]).astype("float")
-
-        # fatjet assignment probability
-        ap_bh1 = np.array(predfile["TARGETS"]["bh1"]["mask"]).astype("float")
-        ap_bh2 = np.array(predfile["TARGETS"]["bh2"]["mask"]).astype("float")
-        ap_bh3 = np.array(predfile["TARGETS"]["bh3"]["mask"]).astype("float")
-
-    # collect fatjet pt
-    fj_pt = np.array(testfile["INPUTS"]["BoostedJets"]["fj_pt"])
-
-    dps = np.concatenate((dp_bh1.reshape(-1, 1), dp_bh2.reshape(-1, 1), dp_bh3.reshape(-1, 1)), axis=1)
-    aps = np.concatenate((ap_bh1.reshape(-1, 1), ap_bh2.reshape(-1, 1), ap_bh3.reshape(-1, 1)), axis=1)
-
-    # convert some arrays to ak array
-    bb_ps = np.concatenate((bb_bh1_p.reshape(-1, 1), bb_bh2_p.reshape(-1, 1), bb_bh3_p.reshape(-1, 1)), axis=1)
+def parse_boosted_w_target(testfile, predfile, num_higgs=3):
+    # Initialize lists to store variables dynamically
+    dp_bh = []
+    ap_bh = []
+    bb_bh_p = []
+    bb_bh_t = []
+    bh_masks_list = []
+    bh_pts_list = []
+
+    for i in range(1, num_higgs + 1):
+        # Collect target pt, mask, and assignment for each Higgs
+        bh_pt = np.array(testfile['TARGETS'][f'bh{i}']['pt'])
+        bh_mask = np.array(testfile['TARGETS'][f'bh{i}']['mask'])
+        bb_bh_t.append(np.array(testfile['TARGETS'][f'bh{i}']['bb']))
+        bh_masks_list.append(bh_mask.reshape(-1, 1))
+        bh_pts_list.append(bh_pt.reshape(-1, 1))
+
+        try:
+            # Collect predicted assignment, detection probability, and fatjet assignment probability
+            bb_bh_p.append(np.array(predfile['TARGETS'][f'bh{i}']['bb']))
+            dp_bh.append(np.array(predfile['TARGETS'][f'bh{i}']['detection_probability']))
+            ap_bh.append(np.array(predfile['TARGETS'][f'bh{i}']['assignment_probability']))
+        except:
+            # In case of missing prediction, apply fallback logic
+            bb_bh_p.append(np.array(predfile['TARGETS'][f'bh{i}']['bb']) + 10)
+            dp_bh.append(np.array(predfile['TARGETS'][f'bh{i}']['mask']).astype('float'))
+            ap_bh.append(np.array(predfile['TARGETS'][f'bh{i}']['mask']).astype('float'))
+
+    # Collect fatjet pt
+    fj_pt = np.array(testfile['INPUTS']['BoostedJets']['fj_pt'])
+
+    # Concatenate detection and assignment probabilities into arrays
+    dps = np.concatenate([dp.reshape(-1, 1) for dp in dp_bh], axis=1)
+    aps = np.concatenate([ap.reshape(-1, 1) for ap in ap_bh], axis=1)
+
+    # Convert bb predictions and targets to awkward arrays
+    bb_ps = np.concatenate([bb.reshape(-1, 1) for bb in bb_bh_p], axis=1)
     bb_ps = ak.Array(bb_ps)
-    bb_ts = np.concatenate((bb_bh1_t.reshape(-1, 1), bb_bh2_t.reshape(-1, 1), bb_bh3_t.reshape(-1, 1)), axis=1)
+    bb_ts = np.concatenate([bb.reshape(-1, 1) for bb in bb_bh_t], axis=1)
     bb_ts = ak.Array(bb_ts)
     fj_pt = ak.Array(fj_pt)
-    bh_masks = np.concatenate((bh1_mask.reshape(-1, 1), bh2_mask.reshape(-1, 1), bh3_mask.reshape(-1, 1)), axis=1)
+
+    # Combine masks and pt values dynamically for all Higgs
+    bh_masks = np.concatenate(bh_masks_list, axis=1)
     bh_masks = ak.Array(bh_masks)
-    bh_pts = np.concatenate((bh1_pt.reshape(-1, 1), bh2_pt.reshape(-1, 1), bh3_pt.reshape(-1, 1)), axis=1)
+    bh_pts = np.concatenate(bh_pts_list, axis=1)
     bh_pts = ak.Array(bh_pts)
 
-    # select predictions and targets
+    # Select predictions and targets
     bb_ps_selected = sel_pred_bH_by_dp_ap(dps, aps, bb_ps)
     bb_ts_selected, targetH_selected_pts = sel_target_bH_by_mask(bb_ts, bh_pts, bh_masks)
 
-    # generate correct/retrieved LUT for pred/target respectively
+    # Generate correct/retrieved LUT for pred/target respectively
     LUT_pred = gen_pred_bH_LUT(bb_ps_selected, bb_ts_selected, fj_pt)
     LUT_target = gen_target_bH_LUT(bb_ps_selected, bb_ts_selected, targetH_selected_pts)
 
-    # reconstruct bH to remove overlapped ak4 jets
-    fj_eta = np.array(testfile["INPUTS"]["BoostedJets"]["fj_eta"])
-    fj_phi = np.array(testfile["INPUTS"]["BoostedJets"]["fj_phi"])
-    fj_mass = np.array(testfile["INPUTS"]["BoostedJets"]["fj_mass"])
+    # Reconstruct bH to remove overlapped ak4 jets
+    fj_eta = np.array(testfile['INPUTS']['BoostedJets']['fj_eta'])
+    fj_phi = np.array(testfile['INPUTS']['BoostedJets']['fj_phi'])
+    fj_mass = np.array(testfile['INPUTS']['BoostedJets']['fj_mass'])
 
     fjs = ak.zip(
         {
@@ -173,8 +156,10 @@ def parse_boosted_w_target(testfile, predfile):
             "phi": fj_phi,
             "mass": fj_mass,
         },
-        with_name="Momentum4D",
+        with_name="Momentum4D"
     )
     fj_reco = fjs[bb_ps_selected - 10]
 
+    # Return the predicted and target LUTs and the reconstructed jets
     return LUT_pred, LUT_target, fj_reco
+
diff --git a/src/analysis/plot.py b/src/analysis/plot.py
index d63b11a..435fe5f 100644
--- a/src/analysis/plot.py
+++ b/src/analysis/plot.py
@@ -1,13 +1,16 @@
 import h5py as h5
 import matplotlib.pyplot as plt
+import mplhep as hep
 import numpy as np
 
 from src.analysis.boosted import parse_boosted_w_target
 from src.analysis.resolved import parse_resolved_w_target
 from src.analysis.utils import calc_eff, calc_pur
 
+hep.style.use("CMS")
 
-def calc_pur_eff(target_path, pred_path, bins):
+
+def calc_pur_eff(target_path, pred_path, bins, num_higgs=3):
     # open files
     pred_h5 = h5.File(pred_path, "a")
     target_h5 = h5.File(target_path)
@@ -18,9 +21,9 @@ def calc_pur_eff(target_path, pred_path, bins):
         pred_h5["TARGETS"] = pred_h5["SpecialKey.Targets"]
 
     # generate look up tables
-    LUT_boosted_pred, LUT_boosted_target, fjs_reco = parse_boosted_w_target(target_h5, pred_h5)
-    LUT_resolved_pred, LUT_resolved_target, _ = parse_resolved_w_target(target_h5, pred_h5, fjs_reco=None)
-    LUT_resolved_wOR_pred, LUT_resolved_wOR_target, _ = parse_resolved_w_target(target_h5, pred_h5, fjs_reco=fjs_reco)
+    LUT_boosted_pred, LUT_boosted_target, fjs_reco = parse_boosted_w_target(target_h5, pred_h5, num_higgs)
+    LUT_resolved_pred, LUT_resolved_target, _ = parse_resolved_w_target(target_h5, pred_h5,  fjs_reco=None,  num_higgs=num_higgs)
+    LUT_resolved_wOR_pred, LUT_resolved_wOR_target, _ = parse_resolved_w_target(target_h5, pred_h5, fjs_reco=fjs_reco, num_higgs=num_higgs)
 
     LUT_resolved_pred_no_OR = []
     for event in LUT_resolved_wOR_pred:
@@ -40,18 +43,26 @@ def calc_pur_eff(target_path, pred_path, bins):
 
     # calculate efficiencies and purities for b+r, b, and r
     results = {}
-    results["pur_m"], results["purerr_m"] = calc_eff(LUT_boosted_pred, LUT_resolved_wOR_pred, bins)
-    results["eff_m"], results["efferr_m"] = calc_pur(LUT_boosted_target, LUT_resolved_wOR_target, bins)
-
-    results["pur_b"], results["purerr_b"] = calc_eff(LUT_boosted_pred, None, bins)
-    results["eff_b"], results["efferr_b"] = calc_pur(LUT_boosted_target, None, bins)
-
-    results["pur_r"], results["purerr_r"] = calc_eff(None, LUT_resolved_pred, bins)
-    results["eff_r"], results["efferr_r"] = calc_pur(None, LUT_resolved_target, bins)
-
-    results["pur_r_or"], results["purerr_r_or"] = calc_eff(None, LUT_resolved_pred_no_OR, bins)
-    results["eff_r_or"], results["efferr_r_or"] = calc_pur(None, LUT_resolved_target_no_OR, bins)
-
+    results["pur_m"], results["purerr_m"], avg_pur_m, n_correct_pred_m = calc_pur(LUT_boosted_pred, LUT_resolved_wOR_pred, bins)
+    results["eff_m"], results["efferr_m"], avg_eff_m, n_reco_target_m = calc_eff(LUT_boosted_target, LUT_resolved_wOR_target, bins)
+
+    results["pur_b"], results["purerr_b"], avg_pur_b, n_correct_pred_b = calc_pur(LUT_boosted_pred, None, bins)
+    results["eff_b"], results["efferr_b"], avg_eff_b, n_reco_target_b = calc_eff(LUT_boosted_target, None, bins)
+
+    results["pur_r"], results["purerr_r"], avg_pur_r, n_correct_pred_r = calc_pur(None, LUT_resolved_pred, bins)
+    results["eff_r"], results["efferr_r"], avg_eff_r, n_reco_target_r = calc_eff(None, LUT_resolved_target, bins)
+
+    results["pur_r_or"], results["purerr_r_or"], _, _ = calc_pur(None, LUT_resolved_pred_no_OR, bins)
+    results["eff_r_or"], results["efferr_r_or"], _, _ = calc_eff(None, LUT_resolved_target_no_OR, bins)
+
+    print("Average purity:")
+    print("merged", avg_pur_m, "boosted", avg_pur_b, "resolved", avg_pur_r)
+    print("Average efficiency:")
+    print("merged", avg_eff_m, "boosted", avg_eff_b, "resolved", avg_eff_r)
+    print("Number of correct Higgs canddiate predictions")
+    print("merged", n_correct_pred_m, "boosted", n_correct_pred_b, "resolved", n_correct_pred_r)
+    print("Number of reconstructed Higgs targets")
+    print("merged", n_reco_target_m, "boosted", n_reco_target_b, "resolved", n_reco_target_r)
     print("Number of Boosted Prediction:", np.array([pred for event in LUT_boosted_pred for pred in event]).shape[0])
     print(
         "Number of Resolved Prediction before OR:",
@@ -67,7 +78,7 @@ def calc_pur_eff(target_path, pred_path, bins):
 
 # I started to use "efficiency" for describing how many gen Higgs were reconstructed
 # and "purity" for desrcribing how many reco Higgs are actually gen Higgs
-def plot_pur_eff_w_dict(plot_dict, target_path, save_path=None, proj_name=None, bins=None):
+def plot_pur_eff_w_dict(plot_dict, target_path, save_path=None, proj_name=None, bins=None, num_higgs=3):
     if bins == None:
         bins = np.arange(0, 1050, 50)
 
@@ -78,57 +89,59 @@ def plot_pur_eff_w_dict(plot_dict, target_path, save_path=None, proj_name=None,
     # m: merged (b+r w OR)
     # b: boosted
     # r: resolved
-    fig_m, ax_m = plt.subplots(1, 2, figsize=(12, 5))
-    fig_b, ax_b = plt.subplots(1, 2, figsize=(12, 5))
-    fig_r, ax_r = plt.subplots(1, 2, figsize=(12, 5))
-    fig_r_or, ax_r_or = plt.subplots(1, 2, figsize=(12, 5))
+    fig_m, ax_m = plt.subplots(1, 2, figsize=(24, 10))
+    fig_b, ax_b = plt.subplots(1, 2, figsize=(24, 10))
+    fig_r, ax_r = plt.subplots(1, 2, figsize=(24, 10))
+    fig_r_or, ax_r_or = plt.subplots(1, 2, figsize=(24, 10))
 
     # preset figure labels, titles, limits, etc.
     ax_m[0].set(
-        xlabel=r"Merged Reco H pT (GeV)",
+        xlabel=r"Reco. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Purity",
-        title=f"Reconstruction Purity vs. Merged Reco H pT",
+        # title=f"Reconstruction Purity vs. Merged Reco H pT",
     )
     ax_m[1].set(
-        xlabel=r"Merged Gen H pT (GeV)",
+        xlabel=r"Gen. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Efficiency",
-        title=f"Reconstruction Efficiency vs. Merged Gen H pT",
+        # title=f"Reconstruction Efficiency vs. Merged Gen H pT",
     )
     ax_b[0].set(
-        xlabel=r"Reco Boosted H pT (GeV)",
+        xlabel=r"Reco. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Purity",
-        title=f"Reconstruction Purity vs. Reco Boosted H pT",
+        # title=f"Reconstruction Purity vs. Reco Boosted H pT",
     )
     ax_b[1].set(
-        xlabel=r"Gen Boosted H pT (GeV)",
+        xlabel=r"Gen. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Efficiency",
-        title=f"Reconstruction Efficiency vs. Gen Boosted H pT",
+        # title=f"Reconstruction Efficiency vs. Gen Boosted H pT",
     )
     ax_r[0].set(
-        xlabel=r"Reco Resolved H pT (GeV)",
+        xlabel=r"Reco. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Purity",
-        title=f"Reconstruction Purity vs. Reco Resolved H pT",
+        # title=f"Reconstruction Purity vs. Reco Resolved H pT",
     )
     ax_r[1].set(
-        xlabel=r"Gen Resolved H pT (GeV)",
+        xlabel=r"Gen. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Efficiency",
-        title=f"Reconstruction Efficiency vs. Gen Resolved H pT",
+        # title=f"Reconstruction Efficiency vs. Gen Resolved H pT",
     )
     ax_r_or[0].set(
-        xlabel=r"Reco Resolved H pT (GeV)",
+        xlabel=r"Reco. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Purity",
-        title=f"Resolved Purity After OR  vs. Reco Resolved H pT",
+        # title=f"Resolved Purity After OR  vs. Reco Resolved H pT",
     )
     ax_r_or[1].set(
-        xlabel=r"Gen Resolved H pT (GeV)",
+        xlabel=r"Gen. H $p_\mathrm{T}$ GeV",
         ylabel=r"Reconstruction Efficiency",
-        title=f"Resolved Efficiency After OR vs. Gen Resolved H pT",
+        # title=f"Resolved Efficiency After OR vs. Gen Resolved H pT",
     )
 
     # plot purities and efficiencies
     for tag, pred_path in plot_dict.items():
         print("Processing", tag)
-        results = calc_pur_eff(target_path, pred_path, bins)
+        
+        results = calc_pur_eff(target_path, pred_path, bins, num_higgs)
+
         ax_m[0].errorbar(
             x=bin_centers, y=results["pur_m"], xerr=xerr, yerr=results["purerr_m"], fmt="o", capsize=5, label=tag
         )
@@ -155,29 +168,30 @@ def plot_pur_eff_w_dict(plot_dict, target_path, save_path=None, proj_name=None,
         )
 
     # adjust limits and legends
-    ax_m[0].legend()
-    ax_m[1].legend()
+    event_type = "H" * num_higgs
+    ax_m[0].legend(title=f'{event_type} Boosted+Resolved')
+    ax_m[1].legend(title=f'{event_type} Boosted+Resolved')
     ax_m[0].set_ylim([-0.1, 1.1])
     ax_m[1].set_ylim([-0.1, 1.1])
-    ax_b[0].legend()
-    ax_b[1].legend()
+    ax_b[0].legend(title=f'{event_type} Boosted')
+    ax_b[1].legend(title=f'{event_type} Boosted')
     ax_b[0].set_ylim([-0.1, 1.1])
     ax_b[1].set_ylim([-0.1, 1.1])
-    ax_r[0].legend()
-    ax_r[1].legend()
+    ax_r[0].legend(title=f'{event_type} Resolved')
+    ax_r[1].legend(title=f'{event_type} Resolved')
     ax_r[0].set_ylim([-0.1, 1.1])
     ax_r[1].set_ylim([-0.1, 1.1])
-    ax_r_or[0].legend()
-    ax_r_or[1].legend()
+    ax_r_or[0].legend(title=f'{event_type} Resolved+OR')
+    ax_r_or[1].legend(title=f'{event_type} Resolved+OR')
     ax_r_or[0].set_ylim([-0.1, 1.1])
     ax_r_or[1].set_ylim([-0.1, 1.1])
 
     plt.show()
 
     if save_path is not None:
-        fig_m.savefig(f"{save_path}/{proj_name}_merged.png")
-        fig_b.savefig(f"{save_path}/{proj_name}_boosted.png")
-        fig_r.savefig(f"{save_path}/{proj_name}_resolved.png")
-        fig_r.savefig(f"{save_path}/{proj_name}_resolved_wOR.png")
+        fig_m.savefig(f"{save_path}/{proj_name}_merged.pdf", format='pdf')
+        fig_b.savefig(f"{save_path}/{proj_name}_boosted.pdf", format='pdf')
+        fig_r.savefig(f"{save_path}/{proj_name}_resolved.pdf", format='pdf')
+        fig_r_or.savefig(f"{save_path}/{proj_name}_resolved_wOR.pdf", format='pdf')
 
     return
diff --git a/src/analysis/resolved.py b/src/analysis/resolved.py
index e754240..c844acc 100644
--- a/src/analysis/resolved.py
+++ b/src/analysis/resolved.py
@@ -133,69 +133,62 @@ def gen_target_h_LUT(b1_ps_passed, b2_ps_passed, b1_ts_selected, b2_ts_selected,
         builder.end_list()
     return builder
 
-
-def parse_resolved_w_target(testfile, predfile, fjs_reco=None):
-    # h pt
-    h1_pt = np.array(testfile["TARGETS"]["h1"]["pt"])
-    h2_pt = np.array(testfile["TARGETS"]["h2"]["pt"])
-    h3_pt = np.array(testfile["TARGETS"]["h3"]["pt"])
-
-    # resolved mask
-    h1_mask = np.array(testfile["TARGETS"]["h1"]["mask"])
-    h2_mask = np.array(testfile["TARGETS"]["h2"]["mask"])
-    h3_mask = np.array(testfile["TARGETS"]["h3"]["mask"])
-
-    h_masks = np.concatenate((h1_mask.reshape(-1, 1), h2_mask.reshape(-1, 1), h3_mask.reshape(-1, 1)), axis=1)
-    # h_masks = h_masks.astype(float)
-    # h_masks = ak.Array(h_masks)
-
-    # boosted mask
-    bh1_mask = np.array(testfile["TARGETS"]["bh1"]["mask"])
-    bh2_mask = np.array(testfile["TARGETS"]["bh2"]["mask"])
-    bh3_mask = np.array(testfile["TARGETS"]["bh3"]["mask"])
-
-    bh_masks = np.concatenate((bh1_mask.reshape(-1, 1), bh2_mask.reshape(-1, 1), bh3_mask.reshape(-1, 1)), axis=1)
-    # bh_masks = bh_masks.astype(float)
-    # bh_masks = ak.Array(bh_masks)
-
-    # findout which resolved higgs also have boosted reco
+def parse_resolved_w_target(testfile, predfile, num_higgs=3, fjs_reco=None):
+    # Lists to store h_pt, h_masks, and bh_masks for each Higgs
+    h_pts_list = []
+    h_masks_list = []
+    bh_masks_list = []
+    
+    for i in range(1, num_higgs + 1):
+        # Collect pt and mask for resolved Higgs
+        h_pt = np.array(testfile['TARGETS'][f'h{i}']['pt'])
+        h_mask = np.array(testfile['TARGETS'][f'h{i}']['mask'])
+        h_pts_list.append(h_pt.reshape(-1, 1))
+        h_masks_list.append(h_mask.reshape(-1, 1))
+        
+        # Collect boosted mask for each Higgs
+        bh_mask = np.array(testfile['TARGETS'][f'bh{i}']['mask'])
+        bh_masks_list.append(bh_mask.reshape(-1, 1))
+
+    # Combine masks and pt arrays for resolved and boosted Higgs
+    h_masks = np.concatenate(h_masks_list, axis=1)
+    bh_masks = np.concatenate(bh_masks_list, axis=1)
+
+    # Find out which resolved Higgs also have boosted reco
     bi_cat_H = h_masks & bh_masks
     bi_cat_H = bi_cat_H.astype(float)
     bi_cat_H = ak.Array(bi_cat_H)
 
-    # target assignments
-    b1_h1_t = np.array(testfile["TARGETS"]["h1"]["b1"]).astype("int")
-    b1_h2_t = np.array(testfile["TARGETS"]["h2"]["b1"]).astype("int")
-    b1_h3_t = np.array(testfile["TARGETS"]["h3"]["b1"]).astype("int")
-
-    b2_h1_t = np.array(testfile["TARGETS"]["h1"]["b2"]).astype("int")
-    b2_h2_t = np.array(testfile["TARGETS"]["h2"]["b2"]).astype("int")
-    b2_h3_t = np.array(testfile["TARGETS"]["h3"]["b2"]).astype("int")
-
-    # predict assignments
-    b1_h1_p = np.array(predfile["TARGETS"]["h1"]["b1"]).astype("int")
-    b1_h2_p = np.array(predfile["TARGETS"]["h2"]["b1"]).astype("int")
-    b1_h3_p = np.array(predfile["TARGETS"]["h3"]["b1"]).astype("int")
-
-    b2_h1_p = np.array(predfile["TARGETS"]["h1"]["b2"]).astype("int")
-    b2_h2_p = np.array(predfile["TARGETS"]["h2"]["b2"]).astype("int")
-    b2_h3_p = np.array(predfile["TARGETS"]["h3"]["b2"]).astype("int")
-
-    # resolved Higgs detection probability
-    dp_h1 = np.array(predfile["TARGETS"]["h1"]["detection_probability"])
-    dp_h2 = np.array(predfile["TARGETS"]["h2"]["detection_probability"])
-    dp_h3 = np.array(predfile["TARGETS"]["h3"]["detection_probability"])
-
-    # ak4 jets assignment probability
-    ap_h1 = np.array(predfile["TARGETS"]["h1"]["assignment_probability"])
-    ap_h2 = np.array(predfile["TARGETS"]["h2"]["assignment_probability"])
-    ap_h3 = np.array(predfile["TARGETS"]["h3"]["assignment_probability"])
-
-    # reconstruct jet 4-momentum objects
-    j_pt = np.array(testfile["INPUTS"]["Jets"]["pt"])
-    j_eta = np.array(testfile["INPUTS"]["Jets"]["eta"])
-    j_phi = np.array(testfile["INPUTS"]["Jets"]["phi"])
-    j_mass = np.array(testfile["INPUTS"]["Jets"]["mass"])
+    # Lists for target and predicted assignments for b1 and b2
+    b1_ts_list, b1_ps_list = [], []
+    b2_ts_list, b2_ps_list = [], []
+
+    for i in range(1, num_higgs + 1):
+        # Collect target assignments for b1 and b2
+        b1_h_t = np.array(testfile['TARGETS'][f'h{i}']['b1']).astype('int')
+        b2_h_t = np.array(testfile['TARGETS'][f'h{i}']['b2']).astype('int')
+        b1_ts_list.append(b1_h_t.reshape(-1, 1))
+        b2_ts_list.append(b2_h_t.reshape(-1, 1))
+
+        # Collect predicted assignments for b1 and b2
+        b1_h_p = np.array(predfile['TARGETS'][f'h{i}']['b1']).astype('int')
+        b2_h_p = np.array(predfile['TARGETS'][f'h{i}']['b2']).astype('int')
+        b1_ps_list.append(b1_h_p.reshape(-1, 1))
+        b2_ps_list.append(b2_h_p.reshape(-1, 1))
+
+    # Lists for detection and assignment probabilities
+    dp_list, ap_list = [], []
+    for i in range(1, num_higgs + 1):
+        dp_h = np.array(predfile['TARGETS'][f'h{i}']['detection_probability'])
+        ap_h = np.array(predfile['TARGETS'][f'h{i}']['assignment_probability'])
+        dp_list.append(dp_h.reshape(-1, 1))
+        ap_list.append(ap_h.reshape(-1, 1))
+
+    # Reconstruct jet 4-momentum objects
+    j_pt = np.array(testfile['INPUTS']['Jets']['pt'])
+    j_eta = np.array(testfile['INPUTS']['Jets']['eta'])
+    j_phi = np.array(testfile['INPUTS']['Jets']['phi'])
+    j_mass = np.array(testfile['INPUTS']['Jets']['mass'])
     js = ak.zip(
         {
             "pt": j_pt,
@@ -203,53 +196,48 @@ def parse_resolved_w_target(testfile, predfile, fjs_reco=None):
             "phi": j_phi,
             "mass": j_mass,
         },
-        with_name="Momentum4D",
+        with_name="Momentum4D"
     )
+    if np.max(js.layout.minmax_depth) == 1:
+        js = [js] 
 
-    # convert some numpy arrays to ak arrays
-    dps = np.concatenate((dp_h1.reshape(-1, 1), dp_h2.reshape(-1, 1), dp_h3.reshape(-1, 1)), axis=1)
-    # dps = ak.Array(dps)
-    aps = np.concatenate((ap_h1.reshape(-1, 1), ap_h2.reshape(-1, 1), ap_h3.reshape(-1, 1)), axis=1)
-    # aps = ak.Array(aps)
+    # Concatenate detection and assignment probabilities
+    dps = np.concatenate(dp_list, axis=1)
+    aps = np.concatenate(ap_list, axis=1)
 
+    # Reset collision dp
     dps = reset_collision_dp(dps, aps)
 
-    b1_ps = np.concatenate((b1_h1_p.reshape(-1, 1), b1_h2_p.reshape(-1, 1), b1_h3_p.reshape(-1, 1)), axis=1)
-    b1_ps = ak.Array(b1_ps)
-    b1_ts = np.concatenate((b1_h1_t.reshape(-1, 1), b1_h2_t.reshape(-1, 1), b1_h3_t.reshape(-1, 1)), axis=1)
-    b1_ts = ak.Array(b1_ts)
-    b2_ps = np.concatenate((b2_h1_p.reshape(-1, 1), b2_h2_p.reshape(-1, 1), b2_h3_p.reshape(-1, 1)), axis=1)
-    b2_ps = ak.Array(b2_ps)
-    b2_ts = np.concatenate((b2_h1_t.reshape(-1, 1), b2_h2_t.reshape(-1, 1), b2_h3_t.reshape(-1, 1)), axis=1)
-    b2_ts = ak.Array(b2_ts)
+    # Convert numpy arrays to awkward arrays
+    b1_ps = ak.Array(np.concatenate(b1_ps_list, axis=1))
+    b1_ts = ak.Array(np.concatenate(b1_ts_list, axis=1))
+    b2_ps = ak.Array(np.concatenate(b2_ps_list, axis=1))
+    b2_ts = ak.Array(np.concatenate(b2_ts_list, axis=1))
 
-    h_pts = np.concatenate((h1_pt.reshape(-1, 1), h2_pt.reshape(-1, 1), h3_pt.reshape(-1, 1)), axis=1)
-    h_pts = ak.Array(h_pts)
+    h_pts = ak.Array(np.concatenate(h_pts_list, axis=1))
 
-    # select predictions and targets
+    # Select predictions and targets
     b1_ts_selected, b2_ts_selected, targetH_selected_pts, bi_cat_H_selected = sel_target_h_by_mask(
         b1_ts, b2_ts, h_pts, bi_cat_H, h_masks
     )
     b1_ps_selected, b2_ps_selected = sel_pred_h_by_dp_ap(dps, aps, b1_ps, b2_ps)
 
-    # find jets that are overlapped with reco boosted Higgs
+    # Find jets that are overlapped with reco boosted Higgs
     if fjs_reco is None:
         goodJetIdx = ak.local_index(js)
+        if np.max(goodJetIdx.layout.minmax_depth) == 1:
+            goodJetIdx = ak.Array([goodJetIdx])
     else:
         goodJetIdx = get_unoverlapped_jet_index(fjs_reco, js, dR_min=0.4)
 
-    # generate look up tables
+    # Generate look-up tables
     LUT_pred = gen_pred_h_LUT(
         b1_ps_selected, b2_ps_selected, b1_ts_selected, b2_ts_selected, js, goodJetIdx, bi_cat_H_selected, ak.ArrayBuilder()
     ).snapshot()
+    
     LUT_target = gen_target_h_LUT(
-        b1_ps_selected,
-        b2_ps_selected,
-        b1_ts_selected,
-        b2_ts_selected,
-        targetH_selected_pts,
-        bi_cat_H_selected,
-        ak.ArrayBuilder(),
+        b1_ps_selected, b2_ps_selected, b1_ts_selected, b2_ts_selected, targetH_selected_pts, bi_cat_H_selected, ak.ArrayBuilder()
     ).snapshot()
 
     return LUT_pred, LUT_target, goodJetIdx
+
diff --git a/src/analysis/utils.py b/src/analysis/utils.py
index f9276bb..c6cdd4b 100644
--- a/src/analysis/utils.py
+++ b/src/analysis/utils.py
@@ -52,9 +52,8 @@ def dp_to_HiggsNumProb(dps):
     return probs_arr
 
 
-# calculate efficiency
-# if bins=None, put all data in a single bin
-def calc_eff(LUT_boosted_pred, LUT_resolved_pred, bins):
+# calculate higgs purrity
+def calc_pur(LUT_boosted_pred, LUT_resolved_pred, bins):
 
     predHs = []
 
@@ -84,18 +83,22 @@ def calc_eff(LUT_boosted_pred, LUT_resolved_pred, bins):
         correctTruth_per_bin.append(predHs[:, 0][predHs_inds == bin_i])
     correctTruth_per_bin = ak.Array(correctTruth_per_bin)
 
-    means = ak.mean(correctTruth_per_bin, axis=-1)
+    mean_per_bin = ak.mean(correctTruth_per_bin, axis=-1)
 
-    errs = np.abs(
+    err_per_bin = np.abs(
         clopper_pearson_interval(num=ak.sum(correctTruth_per_bin, axis=-1), denom=ak.num(correctTruth_per_bin, axis=-1))
-        - means
+        - mean_per_bin
     )
 
-    return means, errs
+    num_correct_pred = np.sum(predHs[:,0])
+    
+    mean_pur = num_correct_pred/predHs.shape[0]
 
+    return mean_per_bin, err_per_bin, mean_pur, num_correct_pred
 
-# calculate purity
-def calc_pur(LUT_boosted_target, LUT_resolved_target, bins):
+
+# calculate higgs efficiency
+def calc_eff(LUT_boosted_target, LUT_resolved_target, bins):
 
     targetHs = []
 
@@ -124,11 +127,124 @@ def calc_pur(LUT_boosted_target, LUT_resolved_target, bins):
         correctTruth_per_bin.append(targetHs[:, 0][targetHs_inds == bin_i])
     correctTruth_per_bin = ak.Array(correctTruth_per_bin)
 
-    means = ak.mean(correctTruth_per_bin, axis=-1)
+    mean_per_bin = ak.mean(correctTruth_per_bin, axis=-1)
 
-    errs = np.abs(
+    err_per_bin = np.abs(
         clopper_pearson_interval(num=ak.sum(correctTruth_per_bin, axis=-1), denom=ak.num(correctTruth_per_bin, axis=-1))
-        - means
+        - mean_per_bin
     )
 
-    return means, errs
+    num_reco_target = np.sum(targetHs[:,0])
+    
+    mean_eff = num_reco_target/targetHs.shape[0]
+    
+    return mean_per_bin, err_per_bin, mean_eff, num_reco_target
+
+# calculate event purity
+def calc_event_purity(LUT_boosted_pred, LUT_resolved_pred, bins):
+    N_OR = 0
+
+    if LUT_boosted_pred is not None:
+        if LUT_resolved_pred is not None:
+            # merged case
+            # calculate merged efficiency
+            # Remove overlapped resolved H_reco
+            pred_events = []
+            for event_boost, event_resolved in zip(LUT_boosted_pred, LUT_resolved_pred):
+                pred_event = []
+                for pred_bH in event_boost:
+                    pred_event.append(pred_bH[0])
+                for pred_rH in event_resolved:
+                    # not overlapped
+                    if pred_rH[2] == 0:
+                        pred_event.append(pred_rH[0])
+                    else:
+                        N_OR += 1
+                pred_events.append(pred_event)
+        # boosted case
+        else:
+            # boosted H don't need post processing
+            pred_events = [[predH[0] for predH in event] for event in LUT_boosted_pred]
+    # resolved case
+    elif LUT_resolved_pred is not None:
+        pred_events = [[predH[0] for predH in event] for event in LUT_resolved_pred]
+
+    pred_events = ak.Array(pred_events)
+
+    # calculate average purity
+    N_event = ak.num(pred_events, axis=0)
+
+    correct_event = ak.all(pred_events, axis=1)
+    N_correct_event = ak.sum(correct_event)
+
+    metrics = {}
+    metrics['avg_event_purity'] = N_correct_event / N_event
+
+    # for each number of predicted candidates
+    # calculate purity
+    N_pred = ak.num(pred_events, axis=1)
+    N_max_pred = ak.max(N_pred)
+    for i in range(0, N_max_pred+1):
+        event_sel = N_pred == i
+        N_sel_event = ak.sum(event_sel)
+        N_correct_sel_event = ak.sum(correct_event[event_sel])
+
+        metrics[f'{i}_candidate_event_purity'] = N_correct_sel_event / N_sel_event
+        metrics[f'{i}_candidate_event_ratio'] = N_sel_event / N_event
+
+    return metrics
+
+# calculate event efficiency
+# calculate purity
+def calc_event_efficiency(LUT_boosted_target, LUT_resolved_target, bins):
+
+    if LUT_boosted_target is not None:
+        if LUT_resolved_target is not None:
+            # merged case
+            # calculate merged efficiency
+            # Remove overlapped resolved H_reco
+            target_events = []
+            for event_boost, event_resolved in zip(LUT_boosted_target, LUT_resolved_target):
+                target_event = []
+                for target_bH in event_boost:
+                    target_event.append(target_bH[0])
+                for target_rH in event_resolved:
+                    # only consider resolved target H that doesn't have a corresponding boosted H target
+                    if target_rH[2] == 0:
+                        target_event.append(target_rH[0])
+                    else:
+                        pass
+                target_events.append(target_event)
+        else:
+            # boosted case
+            target_events = [[targetH[0] for targetH in event] for event in LUT_boosted_target]
+
+    elif LUT_resolved_target is not None:
+        # resolved case
+        target_events = [[targetH[0] for targetH in event] for event in LUT_resolved_target]
+
+
+    target_events = ak.Array(target_events)
+
+    # calculate average purity
+    N_event = ak.num(target_events, axis=0)
+
+    retrieved_event = ak.all(target_events, axis=1)
+    N_retrieved_event = ak.sum(retrieved_event)
+
+    metrics = {}
+    metrics['avg_event_efficiency'] = N_retrieved_event / N_event
+
+    # for each number of targets
+    # calculate purity
+    N_target = ak.num(target_events, axis=1)
+    N_max_target = ak.max(N_target)
+    for i in range(0, N_max_target+1):
+        event_sel = N_target == i
+        N_sel_event = ak.sum(event_sel)
+        N_retrieved_sel_event = ak.sum(retrieved_event[event_sel])
+
+        metrics[f'{i}_target_event_purity'] = N_retrieved_sel_event / N_sel_event
+        metrics[f'{i}_target_event_ratio'] = N_sel_event / N_event
+
+    return metrics
diff --git a/src/models/test_baseline.py b/src/models/test_baseline.py
index 4dd7599..1cca5e8 100644
--- a/src/models/test_baseline.py
+++ b/src/models/test_baseline.py
@@ -53,6 +53,7 @@ def main(test_file, event_file, n_higgs, method):
     pt = ak.Array(in_file["INPUTS"]["Jets"]["pt"])
     eta = ak.Array(in_file["INPUTS"]["Jets"]["eta"])
     phi = ak.Array(in_file["INPUTS"]["Jets"]["phi"])
+    mass = ak.Array(in_file["INPUTS"]["Jets"]["mass"])
     btag = ak.Array(in_file["INPUTS"]["Jets"]["btag"])
     mask = ak.Array(in_file["INPUTS"]["Jets"]["MASK"])
 
@@ -60,6 +61,7 @@ def main(test_file, event_file, n_higgs, method):
     pt = pt[mask]
     eta = eta[mask]
     phi = phi[mask]
+    mass = mass[mask]
     btag = btag[mask]
 
     jets = ak.zip(
@@ -67,7 +69,8 @@ def main(test_file, event_file, n_higgs, method):
             "pt": pt,
             "eta": eta,
             "phi": phi,
-            "mass": ak.zeros_like(pt),
+            # "mass": ak.zeros_like(pt),
+            'mass': mass,
             "btag": btag,
         },
         with_name="Momentum4D",
@@ -168,6 +171,7 @@ def main(test_file, event_file, n_higgs, method):
 
     num_vectors = np.sum(mask, axis=-1).to_numpy()
     lines = 2
+    print('hello', masks.shape)
     results, jet_limits, clusters = evaluate_predictions(predictions, num_vectors, targets, masks, event_file, lines)
     display_table(results, jet_limits, clusters)