diff --git a/dataMC_visualization.ipynb b/dataMC_visualization.ipynb
index 39e213f..3422b7d 100644
--- a/dataMC_visualization.ipynb
+++ b/dataMC_visualization.ipynb
@@ -30,9 +30,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "l_flv = ['e','mu']\n",
-    "data_type = ['MC','small_data']\n",
-    "tree_name = 'Ds_OfflineTree/DecayTree'"
+    "l_index = 1\n",
+    "data_index = None \n",
+    "mother_index = None"
    ]
   },
   {
@@ -41,18 +41,49 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "l_index = 1\n",
-    "data_index = None "
+    "mother_ID=['Ds','Dplus']\n",
+    "l_flv = ['e','mu']\n",
+    "data_type = ['MC','data']\n",
+    "\n",
+    "def find_file_path(l_index=l_index, mother_index=mother_index, data_index=data_index): \n",
+    "    return \"/disk/lhcb_data/davide/Rphipi/\"+data_type[data_index]+\"/\"+mother_ID[mother_index]+\"_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/\"+mother_ID[mother_index]+\"_phipi_\"+l_flv[l_index]+l_flv[l_index]+\".root\"\n",
+    "\n",
+    "mother_index=0\n",
+    "\n",
+    "data = r.TFile(find_file_path(l_index=l_index, mother_index=mother_index, data_index=1))\n",
+    "MC_Ds = r.TFile(find_file_path(l_index=l_index, mother_index=mother_index, data_index=0))\n",
+    "\n",
+    "tree_name_Ds = mother_ID[mother_index]+'_OfflineTree/DecayTree'\n",
+    "t_data = data.Get(tree_name_Ds)\n",
+    "t_MC_Ds = MC_Ds.Get(tree_name_Ds)\n",
+    "\n",
+    "\n",
+    "mother_index=1\n",
+    "\n",
+    "MC_Dplus = r.TFile(find_file_path(l_index=l_index, mother_index=mother_index, data_index=0))\n",
+    "\n",
+    "tree_name_Dplus = mother_ID[mother_index]+'_OfflineTree/DecayTree'\n",
+    "t_MC_Dplus = MC_Dplus.Get(tree_name_Dplus)\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<ROOT.TTree object (\"DecayTree\") at 0x55d10035d3a0>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "def find_file_path(l_index=l_index, data_index=data_index): \n",
-    "    return \"/disk/lhcb_data/davide/Rphipi/\"+data_type[data_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\".root\""
+    "t_MC_Dplus"
    ]
   },
   {
@@ -61,163 +92,174 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = r.TFile(find_file_path(l_index=l_index, data_index=1))\n",
-    "MC = r.TFile(find_file_path(l_index=l_index, data_index=0))"
+    "def return_branches(mother_index=None):\n",
+    "\n",
+    "    branches_needed = [\n",
+    "                    #________________________________________\n",
+    "                    #D\n",
+    "                    #________________________________________\n",
+    "                    #D Geometric variables, pT and FD\n",
+    "        \n",
+    "                    mother_ID[mother_index]+\"_ENDVERTEX_CHI2\",\n",
+    "                    mother_ID[mother_index]+\"_ENDVERTEX_NDOF\",\n",
+    "                    mother_ID[mother_index]+\"_IPCHI2_OWNPV\",\n",
+    "\n",
+    "                    mother_ID[mother_index]+\"_OWNPV_CHI2\",\n",
+    "                    mother_ID[mother_index]+\"_OWNPV_NDOF\",\n",
+    "                    mother_ID[mother_index]+\"_IP_OWNPV\",\n",
+    "                    mother_ID[mother_index]+\"_DIRA_OWNPV\",\n",
+    "        \n",
+    "                    mother_ID[mother_index]+\"_PT\",\n",
+    "                    mother_ID[mother_index]+\"_FD_OWNPV\",\n",
+    "                    \n",
+    "                    #D Reconstructed mass\n",
+    "                    mother_ID[mother_index]+\"_ConsD_M\",\n",
+    "        \n",
+    "                    #D Trigger variables\n",
+    "                    mother_ID[mother_index]+\"_Hlt1TrackMVADecision_TOS\",\n",
+    "                    mother_ID[mother_index]+\"_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",\n",
+    "                    mother_ID[mother_index]+\"_Hlt2Phys_TOS\",\n",
+    "                    \n",
+    "                    #________________________________________\n",
+    "                    #PHI\n",
+    "                    #________________________________________\n",
+    "                    #phi geometric variables, pT and FD\n",
+    "        \n",
+    "                    \"phi_ENDVERTEX_CHI2\",\n",
+    "                    \"phi_ENDVERTEX_NDOF\",\n",
+    "                    \"phi_IPCHI2_OWNPV\",\n",
+    "        \n",
+    "                    #\"phi_OWNPV_CHI2\",\n",
+    "                    #\"phi_OWNPV_NDOF\",\n",
+    "                    #\"phi_IP_OWNPV\",\n",
+    "                    #\"phi_DIRA_OWNPV\",\n",
+    "                    \n",
+    "                    \"phi_PT\",\n",
+    "        \n",
+    "                    #phi Reconstructed mass\n",
+    "        \n",
+    "                    \"phi_M\",\n",
+    "        \n",
+    "                    #________________________________________\n",
+    "                    #PION\n",
+    "                    #________________________________________\n",
+    "                    #pi Geometric variables and pT\n",
+    "                    #\"pi_OWNPV_CHI2\",\n",
+    "                    #\"pi_OWNPV_NDOF\",\n",
+    "                    #'pi_IP_OWNPV',\n",
+    "        \n",
+    "                    'pi_PT',\n",
+    "        \n",
+    "                    #pi PID variables\n",
+    "        \n",
+    "                    \"pi_MC15TuneV1_ProbNNpi\",\n",
+    "        \n",
+    "                    #________________________________________\n",
+    "                    #LEPTONS\n",
+    "                    #________________________________________\n",
+    "                    #leptons Geometric variables and pT\n",
+    "                    \n",
+    "                    #l_flv[l_index]+\"_plus_OWNPV_CHI2\",\n",
+    "                    #l_flv[l_index]+\"_plus_OWNPV_NDOF\",\n",
+    "                    #l_flv[l_index]+\"_minus_OWNPV_CHI2\",\n",
+    "                    #l_flv[l_index]+\"_minus_OWNPV_NDOF\",\n",
+    "                    #\n",
+    "                    #l_flv[l_index]+\"_plus_IP_OWNPV\",\n",
+    "                    #l_flv[l_index]+\"_minus_IP_OWNPV\",\n",
+    "        \n",
+    "                    l_flv[l_index]+\"_plus_PT\",\n",
+    "                    l_flv[l_index]+\"_minus_PT\",\n",
+    "        \n",
+    "                    #leptons PID variables\n",
+    "        \n",
+    "                    l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n",
+    "                    l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n",
+    "                    \n",
+    "                    \n",
+    "                  ] \n",
+    "    return branches_needed"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<ROOT.TTree object (\"DecayTree\") at 0x55f041fbe410>"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "t_data = data.Get(\"Ds_OfflineTree/DecayTree\")\n",
-    "t_data"
+    "#Switch on only the branches that you need\n",
+    "t_data.SetBranchStatus(\"*\",0)\n",
+    "t_MC_Dplus.SetBranchStatus(\"*\",0)\n",
+    "t_MC_Ds.SetBranchStatus(\"*\",0)\n",
+    "\n",
+    "\n",
+    "for branch in return_branches(mother_index=0):\n",
+    "    t_data.SetBranchStatus(branch, 1)\n",
+    "    t_MC_Ds.SetBranchStatus(branch, 1)\n",
+    "    \n",
+    "for branch in return_branches(mother_index=1):\n",
+    "    t_data.SetBranchStatus(branch, 1)\n",
+    "    t_MC_Ds.SetBranchStatus(branch, 1)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<ROOT.TTree object (\"DecayTree\") at 0x55f041a503a0>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "t_MC = MC.Get(\"Ds_OfflineTree/DecayTree\")\n",
-    "t_MC"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Switch on only the branches that you need\n",
-    "t_data.SetBranchStatus(\"*\",0)\n",
-    "t_MC.SetBranchStatus(\"*\",0)\n",
-    "\n",
-    "branches_needed = [\n",
-    "                    \"Ds_ENDVERTEX_CHI2\",\n",
-    "                    \"Ds_ENDVERTEX_NDOF\",\n",
-    "                    \"Ds_OWNPV_CHI2\",\n",
-    "                    \"Ds_OWNPV_NDOF\",\n",
-    "                    \"Ds_IPCHI2_OWNPV\",\n",
-    "                    \"Ds_IP_OWNPV\",\n",
-    "                    \"Ds_DIRA_OWNPV\",\n",
-    "                    \"Ds_ConsD_M\",\n",
-    "                    l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n",
-    "                    l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n",
-    "                    \"Ds_Hlt1TrackMVADecision_TOS\",\n",
-    "                    \"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",\n",
-    "                    \"Ds_Hlt2Phys_TOS\",\n",
-    "    \n",
-    "                    \"phi_ENDVERTEX_CHI2\",\n",
-    "                    \"phi_ENDVERTEX_NDOF\",\n",
-    "                    \"phi_OWNPV_CHI2\",\n",
-    "                    \"phi_OWNPV_NDOF\",\n",
-    "                    \"phi_IP_OWNPV\",\n",
-    "                    \"phi_IPCHI2_OWNPV\",\n",
-    "                    \"phi_DIRA_OWNPV\",\n",
-    "                    \"phi_M\",\n",
-    "                  ] \n",
-    "\n",
-    "for branch in branches_needed:\n",
-    "    t_data.SetBranchStatus(branch, 1)\n",
-    "    t_MC.SetBranchStatus(branch, 1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "MC event count 49002, data event count 233629\n"
-     ]
-    }
-   ],
-   "source": [
-    "#Count the events in the tuple\n",
-    "\n",
-    "MC_count=0\n",
-    "for event in enumerate(t_MC):\n",
-    "    MC_count+=1\n",
-    "    \n",
-    "data_count=0\n",
-    "for event in enumerate(t_data):\n",
-    "    data_count+=1\n",
-    "print(\"MC event count {0}, data event count {1}\".format(MC_count,data_count))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
    "outputs": [],
    "source": [
     "#Create a dictionary\n",
     "\n",
     "#dict ={'branch_name'=[branch_value[event]]}\n",
     "\n",
-    "MC_tuple_dict = {}\n",
-    "\n",
+    "MC_Ds_tuple_dict = {}\n",
+    "branches_needed=return_branches(mother_index=0)\n",
     "for branch in branches_needed:\n",
     "    \n",
-    "    MC_tuple_dict[branch] = rn.root2array(\n",
+    "    MC_Ds_tuple_dict[branch] = rn.root2array(\n",
     "        \n",
-    "        filenames=find_file_path(l_index, 0),\n",
-    "        treename = tree_name,\n",
+    "        filenames=find_file_path(l_index, mother_index=0, data_index=0),\n",
+    "        treename = tree_name_Ds,\n",
     "        branches = branch,\n",
     "        start=0,\n",
-    "        stop=MC_count,\n",
+    "        stop=t_MC_Ds.GetEntries(),\n",
+    "    )\n",
+    "    \n",
+    "MC_Dplus_tuple_dict = {}\n",
+    "branches_needed=return_branches(mother_index=1)\n",
+    "for branch in branches_needed:\n",
+    "    \n",
+    "    MC_Dplus_tuple_dict[branch] = rn.root2array(\n",
+    "        \n",
+    "        filenames=find_file_path(l_index, mother_index=1, data_index=0),\n",
+    "        treename = tree_name_Dplus,\n",
+    "        branches = branch,\n",
+    "        start=0,\n",
+    "        stop=t_MC_Dplus.GetEntries(),\n",
     "    )\n",
     "    \n",
     "data_tuple_dict = {}\n",
     "\n",
+    "branches_needed=return_branches(mother_index=0)\n",
     "for branch in branches_needed:\n",
     "    \n",
     "    data_tuple_dict[branch] = rn.root2array(\n",
     "        \n",
-    "        filenames=find_file_path(l_index, 1),\n",
-    "        treename = tree_name,\n",
+    "        filenames=find_file_path(l_index,mother_index=0, data_index=1),\n",
+    "        treename = tree_name_Ds,\n",
     "        branches = branch,\n",
     "        start=0,\n",
-    "        stop=data_count,\n",
+    "        stop=t_data.GetEntries(),\n",
     "    )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x432 with 2 Axes>"
       ]
@@ -230,80 +272,29 @@
    ],
    "source": [
     "#Check the Ds mass plot\n",
-    "\n",
-    "Ds_constrained_mass_MC = np.array([MC_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"]))])\n",
+    "Dplus_constrained_mass_MC = np.array([MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"][i][0] for i in range(len(MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"]))])\n",
+    "Ds_constrained_mass_MC = np.array([MC_Ds_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(MC_Ds_tuple_dict[\"Ds_ConsD_M\"]))])\n",
     "Ds_constrained_mass_data = np.array([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))])\n",
+    "\n",
     "plt.subplot(1,2,1)\n",
-    "plt.hist(Ds_constrained_mass_MC,bins=70, range=(0,3000));\n",
+    "plt.hist(Ds_constrained_mass_MC,bins=70, range=(1750,2100), density=True);\n",
+    "plt.hist(Dplus_constrained_mass_MC,bins=70, range=(1750,2100), density=True);\n",
     "plt.subplot(1,2,2)\n",
-    "plt.hist(Ds_constrained_mass_data,bins=70, range=(0,3000));\n",
+    "plt.hist(Ds_constrained_mass_data,bins=70, range=(1100,2750), density=True);\n",
     "fig = plt.gcf()\n",
     "fig.set_size_inches(16,6)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#HLT1 PRESELECTION\n",
-    "data_tuple_dict_presel_1={}\n",
-    "MC_tuple_dict_presel_1={}\n",
-    "\n",
-    "for label in branches_needed:  \n",
-    "\n",
-    "    data_tuple_dict_presel_1[label] = data_tuple_dict[label][data_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]]\n",
-    "    MC_tuple_dict_presel_1[label] = MC_tuple_dict[label][MC_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]]\n",
-    "\n",
-    "#RareCharm D2pi l l HLT2 PRESELECTION\n",
-    "\n",
-    "data_tuple_dict_presel_2={}\n",
-    "MC_tuple_dict_presel_2={}\n",
-    "\n",
-    "for label in branches_needed:  \n",
-    "\n",
-    "    data_tuple_dict_presel_2[label] = data_tuple_dict_presel_1[label][data_tuple_dict_presel_1[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]]\n",
-    "    MC_tuple_dict_presel_2[label] = MC_tuple_dict_presel_1[label][MC_tuple_dict_presel_1[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]]\n",
-    "\n",
-    "#PID preselection\n",
-    "\n",
-    "#MC_PID_indices=np.where(MC_tuple_dict_presel_2[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
-    "\n",
-    "data_PID_indices_plus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
-    "data_PID_indices_minus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
-    "\n",
-    "data_PID_indices = np.intersect1d(data_PID_indices_plus,data_PID_indices_minus)\n",
-    "\n",
-    "data_tuple_dict_presel_3={}\n",
-    "MC_tuple_dict_presel_3={}\n",
-    "\n",
-    "for label in branches_needed:  \n",
-    "\n",
-    "    data_tuple_dict_presel_3[label] = data_tuple_dict_presel_2[label][data_PID_indices]\n",
-    "    MC_tuple_dict_presel_3[label] = MC_tuple_dict_presel_2[label]#[MC_PID_indices]\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#np.float(MC_tuple_dict_presel_1[\"Ds_ConsD_M\"].shape[0])/np.float(MC_tuple_dict[\"Ds_ConsD_M\"].shape[0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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AANAt96kF4Ehx31kAOFzM1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6JZQCwAAQLeEWgAAALol1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6JZQCwAAQLeEWgAAALol1AIAANAtoRYAAIBuLcy6AADg4tbWN0f1X1lenFIlADBfzNQCAADQLaEWAACAbgm1AAAAdEuoBQAAoFtCLQAAAN0SagEAAOiWUAsAAEC3hFoAAAC6JdQCAADQLaEWAACAbgm1AAAAdEuoBQAAoFsLsy4AANh/a+ubo/qvLC9OqRIAmC4ztQAAAHTLTC1MwdgZEgAAYHfM1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6JZQCwAAQLeEWgAAALol1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6NbCrAsAAGZvbX1zx31XlhenWAkAjGOmFgAAgG4JtQAAAHRLqAUAAKBbQi0AAADdslEUHHLHnj47qv8Lx2+aUiUAALD/zNQCAADQLaEWAACAbgm1AAAAdEuoBQAAoFtCLQAAAN0SagEAAOiWUAsAAEC33KcWOjP2vrMAAHCYmakFAACgW0ItAAAA3bL8GAAYZW19c1T/leXFKVUCAEItcI4x1+y+cPymKVYCAAAXZ/kxAAAA3RJqAQAA6JZQCwAAQLf2HGqr6tKq+kRV/bfh9RVVdbaq1qrqoap67UTfO6vqqap6oqreNNF+cniPT1bV3VVVe60LAACAw28/Zmp/LMlTE6/fk+RMa20lyZnhdarqZJK3Jrkuyc1J3l9Vlw/HfDDJO1trb0hyPMlb9qEuAAAADrk9hdqqWk5yS5JfnGi+Jcl9w/P7h9evtJ9urb3UWltP8mSSG6vq9Ukuba09ep5jAAAAYFt7nal9b5J/nuTlibal1tpGkgyPVw3ty0menei3PrRt1/5lquqOqlqtqtWNjY09lg4AAEDvdh1qq+p7kjw/McM6da21e1prp1prp5aWlg7qjwUAAGBOLezh2G9L8neq6s1JviLJX6iq+5NsVNVSa22jqpaSPD/0X09y9cTxy0Pbdu0AAABwQbueqW2t3dlaW26tnUjyD5I83Fq7PcmDSW4fut2erc2iMrTfVlWXDdfiXpvkkdbaM0lerqobhn5vmzgGAAAAtrWXmdrtvDvJ6ap6R5LnktyaJK211ar6aJLHs3UN7rtaay8Ox7w9yb1V9ZokDyd5YAp1AQAAcMjsS6htrX0syceG53+c5I3b9LsryV3naV9Ncv1+1AIAAMDRsR/3qQUAAICZEGoBAADollALAABAt6axURRwRBx7+uyo/i8cv2lKlQAAcFSZqQUAAKBbQi0AAADdEmoBAADollALAABAt4RaAAAAuiXUAgAA0C239AEApmptfXPHfVeWF6dYCQCHkZlaAAAAuiXUAgAA0C2hFgAAgG4JtQAAAHRLqAUAAKBbQi0AAADdEmoBAADollALAABAt4RaAAAAuiXUAgAA0K2FWRcAJMeePjvrEgAAoEtmagEAAOiWmVoAYG6srW+O6r+yvDilSgDohZlaAAAAuiXUAgAA0C2hFgAAgG4JtQAAAHRLqAUAAKBbQi0AAADdEmoBAADolvvUAsA+Ofb02VH9Xzh+05QqAYCjQ6gFDsyYf/D7xz4AADth+TEAAADdEmoBAADollALAABAt4RaAAAAuiXUAgAA0C2hFgAAgG4JtQAAAHRLqAUAAKBbQi0AAADdWph1AQDnc+zps6P6v3D8pilVAgDAPDNTCwAAQLeEWgAAALol1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6NbCrAuAXqytb866BAAA4BxCLQDdO/b02R33feH4TVOsBAA4aJYfAwAA0C0ztQBAt8ZeGrKyvDilSgCYFTO1AAAAdMtMLXAojLmmMnFdJQDAYWGmFgAAgG4JtQAAAHRLqAUAAKBbQi0AAADdslEUAMzImA3ObG4GAOdnphYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3RJqAQAA6JZQCwAAQLeEWgAAALol1AIAANCthVkXADALx54+u+O+Lxy/aYqVAACwF2ZqAQAA6JaZWpiCMbOAAByctfXNHfddWV6cYiUA7BcztQAAAHTLTC3ARYydeXcNLgDAwTFTCwAAQLeEWgAAALol1AIAANAtoRYAAIBuCbUAAAB0S6gFAACgW0ItAAAA3XKfWoB9Nua+tu5pCwCwN2ZqAQAA6JZQCwAAQLcsPwaYoTFLlRPLlQEAzmWmFgAAgG7tOtRW1dVV9fGqeqKq/qCqfnJov6KqzlbVWlU9VFWvnTjmzqp6ajjmTRPtJ6vqE1X1yaq6u6pqbz8WAAAAR8FeZmpfSvKjrbVrk5xM8s6quj7Je5Kcaa2tJDkzvE5VnUzy1iTXJbk5yfur6vLhvT6Y5J2ttTckOZ7kLXuoCwAAgCNi16G2tfb51trjw/MXkjye5OuS3JLkvqHb/cPrDI+nW2svtdbWkzyZ5Maqen2SS1trj57nGAAAANjWvlxTW1Unknxzkt9KstRa20iS4fGqodtykmcnDlsf2rZrP9+fc0dVrVbV6sbGxn6UDgAAQMf2HGqr6muSfCTJj7fWNvde0vZaa/e01k611k4tLS1N848CAACgA3sKtVV1WZIHkny4tfYrQ/NGVS0N319K8vzQvp7k6onDl4e27doBAADggnZ9n9phh+IPJHmqtfazE996MMntSf798Hhmov19VfXeJH8pybVJHmmtvVhVL1fVDa21303ytmxdVwvAOdzXFgDg1XYdapN8W5J/mGStqh4b2v5FkncnOV1V70jyXJJbk6S1tlpVH83WhlIvJ3lXa+3F4bi3J7m3ql6T5OFszf4CAMzM2vq4q6pWlhenVAkAF7LrUNta+60k291P9o3bHHNXkrvO076a5Prd1gJs79c3H714pwk3L56cUiUAALD/9mX3YwAAAJgFoRYAAIBuCbUAAAB0ay8bRQEw58bslmyn5PMbu+M0AHCwzNQCAADQLTO1AMwds6MAwE4JtQAkGR8kxyxXFlIBgGkRaqEzY+87O833d0/bo01QBQDmgVAL7NrYgC0EAwCw34RaAOjANJeHA0DPhFoAjhTLpgHgcHFLHwAAALol1AIAANAtoRYAAIBuuaYWAA4hG0sBcFSYqQUAAKBbZmoBYJ+4d/PRtra+ueO+K8uLU6wE4GgRagGAUcuVLVUGYJ5YfgwAAEC3hFoAAAC6JdQCAADQLdfUwg6NvT0GAAAwfUItzIGxO6aOcc1/emxU/0/fev2UKgEAgP0n1HJkjbn1QpIcm1IdAL0Zu3LFbskATJNQCxyYMTPS7t8JAMBO2CgKAACAbpmphc6MvUYWAAAOM6EWgO5Z2g4AR5dQC7zKmJngae6UPHZHaEEF6MnYzQpXlhenVAlA/4RaYNfcLgj2xgwzAOydUAsATNWYWwC5/Q8AY9n9GAAAgG4JtQAAAHRLqAUAAKBbrqkFAObGmOtvE9fgAiDUAsC+sSM4ABw8oRY4FNzXFgDgaHJNLQAAAN0yUwtzYOySRQAAYItQC3ARljYDAMwvoRY4ksYGVQAA5pNQC1MwNjBdM6U6AADgsBNqAejeqOvSf9jycPqztr45qv/K8uKUKgGYP0ItcGDGBA/37wQAYCeEWoB9Nmb5uU2lAAD2xn1qAQAA6JaZWmAujb13b6/Lld0uCPbm2NNnR/V/4fhNU6oEgFkRagFgRmxwBQB7Z/kxAAAA3RJqAQAA6JblxwAdGXsN7hiu1z2/Mf/Nr5liHQDA+Qm1AEydDbEAgGkRaoFD4ajslnxUjA3BZkjZqTG7JdspGaAPQi1MwdiABT2a5lJoAICdEmoBSHJ0QmqvP+e067bk+3BZW9/ccd+V5cUpVgIwfUItcCSNmU23VBkAYH4JtQAX4XpdAID5JdRyZI3ZLATgsBuzvNlSZQDmySWzLgAAAAB2y0wtADCK+w4DME+EWoB9ZhMqOBzGXqbivrYAsyHUwg6NmZm4Zop1AAAAf06oBZghOysDAOyNUAsAzA3X6x68tfXNUf1XlhenVAnA7gi1AB0ZO7M7hllgpmVsUAWAMYRaAKbOMmsAYFqEWg6Nscunjk2pDujVNGeBx1ILPRqzW7KdkgH2zyWzLgAAAAB2y0wtAEeKmVcAOFyEWgDogOuSmRdjLvexUzJwEIRa2CGzO0BPhGAAjgqhFgDggI3ZVCqxsRTAhQi1AMAoZoEBmCdCLQDQ7SUWv7756NTe++bFk1N7bwD2j1ALADDnel2uPPYe8jaWAnZDqAUApmqas8CWNgMg1HJkjV2yds2U6gAAAHZPqAUAOI+xv/x0De7eWa4M7MYlsy4AAAAAdstMLQDAPhgzszvtWd0xG0vNy6ZSALsl1HJojN0ZstfbVwDw52xCdbSNWa5sqTIcXkItAMABc70uwP4RagEAzmPsLHCvM7u93gN3LJtQweEl1DLXxpyAjk2xDgCYpXma2XW9LjBvhFoAgH3g+t4v1/MssOt1oR9CLQDAITNPOzGP0WsItrQZZmtuQm1V3ZzkZ5JcmuSXW2v/esYl0ZmxS7OumVIdALDfpnl97zwtbR6r16XQQjDsr7kItVV1eZL3JfmOJJ9P8ttV9VBr7XdnWxmzNuZk5RY9ALBlzDlx7NLmsSF4jHkKzPPEUmi4sLkItUn+RpInW2vPJklVnU5ySxKhtgNjf9s4hs2fAGC65ula4M/8wgem9/6Pz8+M9DRnjaf577KxBGwOyryE2uUkz068Xk/ynbMpZf/M018q0zT2+pcxxp7cAID5Me1VVNN8/89kmmF/5CVTU5x5H/PeX//DPzTqvT/79Kjuo4z9xcA0A/Y0/83vFwM7My+hdkeq6o4kdwwv/6Sqfn+W9ezAlUm+MOsieBVjMp+My/wxJvPHmMwn4zJ/5n9MfvnXj+J7z/+4HD09jMnxnXSal1C7nuTqidfLQ9urtNbuSXLPQRW1V1W12lo7Nes6+HPGZD4Zl/ljTOaPMZlPxmX+GJP5ZFzmz2Eak0tmXcDgkSTXVtVyVV2W5LYkZ2ZcEwAAAHNuLmZqW2v/r6r+cZLfyFbQvr+1tjrjsgAAAJhzcxFqk6S19mCSB2ddxz7rZqn0EWJM5pNxmT/GZP4Yk/lkXOaPMZlPxmX+HJoxqdbarGsAAACAXZmXa2oBAABgNKF2hKq6t6qer6onJtquqKqzVbVWVQ9V1WsnvndnVT1VVU9U1Zsm2k9W1Seq6pNVdXdV1UH/LIfFNmPy74b/7k9V1a9V1ZVD+4mq+r9V9djw9b6JY4zJPtpmXH66qv5o4r//mye+57MyZduMyemJ8fhsVT02tPusHICqurqqPj78f/8HVfWTQ7vzygxdYFycW2bkAmPivDJDFxgX55YZqaqvqKrV4b/vp6vqvbXl8J9XWmu+dviV5G8muSHJExNt/yHJPxme/0SSu4fnJ5OsJrksW7co+mySy4fvPZ7k5PD8V5N836x/tl6/thmT70qyMDz/N0neOzw/MdnvnPcxJtMfl59O8s/O09dnZUZjcs73fzbJvxqe+6wczJh8bZLrhufHknw6yfXOK3M7Ls4t8zcmzitzOC7n9HFuOdgxqSRfPTy/LMnvDH93HfrzipnaEVprH0/yxXOab0ly3/D8/uH1K+2nW2svtdbWkzyZ5Maqen2SS1trj57nGEY635i01h5urX1pePlbSb7uQu9hTPbfNp+V7fisHIALjcnw29dbk3z4Qu9hTPZXa+3zrbXHh+cvZOsfEF8X55WZ2m5cnFtm5wKfle34rByAi42Lc8vBa1v+z/DysiSXJnk+R+C8ItTu3VJrbSNJhserhvblJM9O9Fsf2rZrZzruSPJfJ16fqKrfq6rfrqrvHtqMycH5kar6VFV9qKpeN7T5rMzedyR5rrX26Yk2n5UDVFUnknxztsKS88qcOGdcJjm3zMh5xsR5ZQ5s81lxbpmBqrp0WPL9fJKPtdaeyBE4rwi1HFpV9VNJvpSt3y4lyeeSLLfW/lqSH0ly3+Q1BUzdzyf5hiRvSPKZJHfPthzDd1LYAAACSElEQVQmfH9e/Zt0n5UDVFVfk+QjSX68tbY563rYst24OLfMznnGxHllDlzg7zDnlhlorf1Za+36bIXQ76iqvzXrmg7C3NyntmMbVbXUWtuoqqVs/VYk2fqNxtUT/ZaHtu3a2UdV9Y+SfG+S72rDxQCttReTvDg8/93a2jDnr8aYHIhXfkOYJMPmEB8bXvqszFBVLST5vmxdV5PEZ+UgVdVlSR5I8uHW2q8Mzc4rM7bNuDi3zND5xsR5ZfYu8Flxbpmx1tr/qqpfS/ItOQLnFTO1e/dgktuH57cnOTPRfltVXVZVy0muTfJIa+2ZJC9X1Q1Dv7dNHMM+qKqbk/xkku9trf3pRPvrquqS4fmJbI3JHxqTg1FVV028fGuSTw7PfVZm641JPjVcS5PEZ+WgDNebfSDJU621n534lvPKDG03Ls4ts3OBMXFemaEL/B2WOLfMRFVdWVXHhudfmeSmJE/kKJxXDmpHqsPwla0lFJ9L8lK2flvxQ0lel+Q3k6wNj1dM9P+pJE9l66Lrvz3RfirJY9n6y/fnktSsf7Zev7YZkz/M1nUAjw1f7xv6/r1hLNay9QH/+8bkQMfl/mxtIvGpJA8luXqiv8/KDMZkaP+lJO86p6/PysGMybcnacPn4pW/r97svDK34+LcMn9j4rwyh+MyfM+5ZTZjct3w3/H3kvx+kp8e2g/9eaWGogEAAKA7lh8DAADQLaEWAACAbgm1AAAAdEuoBQAAoFtCLQAAAN0SagEAAOiWUAsAAEC3hFoAAAC69f8BzuhUjPi8UdEAAAAASUVORK5CYII=\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1152x720 with 1 Axes>"
+       "<Figure size 1152x576 with 1 Axes>"
       ]
      },
      "metadata": {
@@ -313,12 +304,257 @@
     }
    ],
    "source": [
-    "plt.hist([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))],alpha=0.2,bins=70,range=(1000,3000));\n",
-    "plt.hist([data_tuple_dict_presel_1[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_1[\"Ds_ConsD_M\"]))],alpha=0.3,bins=70,range=(1000,3000));\n",
-    "plt.hist([data_tuple_dict_presel_2[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_2[\"Ds_ConsD_M\"]))],alpha=0.4,bins=70,range=(1000,3000));\n",
-    "plt.hist([data_tuple_dict_presel_3[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_3[\"Ds_ConsD_M\"]))],alpha=0.6,bins=70,range=(1000,3000));\n",
+    "#Check the phi mass plot\n",
+    "if l_flv[l_index]=='e':\n",
+    "    lower=700\n",
+    "    upper=1375\n",
+    "if l_flv[l_index]=='mu':\n",
+    "    lower=925\n",
+    "    upper=1100\n",
+    "\n",
+    "phi_mass_MC_Ds = np.array([MC_Ds_tuple_dict[\"phi_M\"][i] for i in range(len(MC_Ds_tuple_dict[\"phi_M\"]))])\n",
+    "#phi_ConsD_mass_MC_Ds = np.array([MC_Ds_tuple_dict[\"Ds_ConsD_phi_1020_M\"][i][0] for i in range(len(MC_Ds_tuple_dict[\"phi_M\"]))])\n",
+    "\n",
+    "phi_mass_MC_Dplus = np.array([MC_Dplus_tuple_dict[\"phi_M\"][i] for i in range(len(MC_Dplus_tuple_dict[\"phi_M\"]))])\n",
+    "#phi_ConsD_mass_MC_Dplus = np.array([MC_Ds_tuple_dict[\"Ds_ConsD_phi_1020_M\"][i][0] for i in range(len(MC_Ds_tuple_dict[\"phi_M\"]))])\n",
+    "\n",
+    "\n",
+    "\n",
+    "plt.hist(phi_mass_MC_Ds,bins=70, alpha=0.5, range=(lower,upper), density=True);\n",
+    "plt.hist(phi_mass_MC_Dplus,bins=70, alpha=0.7, range=(lower,upper), density=True);\n",
+    "fig = plt.gcf()\n",
+    "fig.set_size_inches(16,8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#HLT1 PRESELECTION\n",
+    "data_tuple_dict_presel_1={}\n",
+    "MC_Ds_tuple_dict_presel_1={}\n",
+    "MC_Dplus_tuple_dict_presel_1={}\n",
+    "\n",
+    "for label in return_branches(mother_index=0):  \n",
+    "\n",
+    "    data_tuple_dict_presel_1[label] = data_tuple_dict[label][data_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]]\n",
+    "    MC_Ds_tuple_dict_presel_1[label] = MC_Ds_tuple_dict[label][MC_Ds_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]]\n",
+    "\n",
+    "for label in return_branches(mother_index=1): \n",
+    "    MC_Dplus_tuple_dict_presel_1[label] = MC_Dplus_tuple_dict[label][MC_Dplus_tuple_dict[\"Dplus_Hlt1TrackMVADecision_TOS\"]]\n",
+    "\n",
+    "#RareCharm D2pi l l HLT2 PRESELECTION\n",
+    "\n",
+    "data_tuple_dict_presel_2={}\n",
+    "MC_Ds_tuple_dict_presel_2={}\n",
+    "MC_Dplus_tuple_dict_presel_2={}\n",
+    "\n",
+    "for label in return_branches(mother_index=0):\n",
+    "\n",
+    "    data_tuple_dict_presel_2[label] = data_tuple_dict_presel_1[label][data_tuple_dict_presel_1[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]]\n",
+    "    MC_Ds_tuple_dict_presel_2[label] = MC_Ds_tuple_dict_presel_1[label][MC_Ds_tuple_dict_presel_1[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]]\n",
+    "\n",
+    "for label in return_branches(mother_index=1):    \n",
+    "    \n",
+    "    MC_Dplus_tuple_dict_presel_2[label] = MC_Dplus_tuple_dict_presel_1[label][MC_Dplus_tuple_dict_presel_1[\"Dplus_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]]\n",
+    "\n",
+    "#PID preselection\n",
+    "\n",
+    "#MC_PID_indices=np.where(MC_tuple_dict_presel_2[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
+    "\n",
+    "data_PID_indices_plus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
+    "data_PID_indices_minus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n",
+    "data_PID_indices_pi=np.where(data_tuple_dict_presel_2[\"pi_MC15TuneV1_ProbNNpi\"]>0.4)\n",
+    "\n",
+    "data_PID_indices = np.intersect1d(data_PID_indices_plus,data_PID_indices_minus)\n",
+    "data_PID_indices = np.intersect1d(data_PID_indices,data_PID_indices_pi)\n",
+    "data_tuple_dict_presel_3={}\n",
+    "MC_Ds_tuple_dict_presel_3={}\n",
+    "MC_Dplus_tuple_dict_presel_3={}\n",
+    "\n",
+    "for label in return_branches(mother_index=0):\n",
+    "\n",
+    "    data_tuple_dict_presel_3[label] = data_tuple_dict_presel_2[label][data_PID_indices]\n",
+    "    MC_Ds_tuple_dict_presel_3[label] = MC_Ds_tuple_dict_presel_2[label]#[MC_PID_indices]\n",
+    "    \n",
+    "for label in return_branches(mother_index=1):\n",
+    "    MC_Dplus_tuple_dict_presel_3[label] = MC_Dplus_tuple_dict_presel_2[label]#[MC_PID_indices]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if l_flv[l_index]=='mu':\n",
+    "    lower_phi_mass = 980\n",
+    "    upper_phi_mass = 1060\n",
+    "    \n",
+    "if l_flv[l_index]=='e':\n",
+    "    lower_phi_mass = 850\n",
+    "    upper_phi_mass = 1100\n",
+    "    \n",
+    "#Retrieve mc signal and data bkg events\n",
+    "\n",
+    "MC_Dplus_indices=[]\n",
+    "MC_Ds_indices=[]\n",
+    "data_indices=[]\n",
+    "        \n",
+    "for i in range(len(MC_Ds_tuple_dict_presel_3[\"Ds_ConsD_M\"])):\n",
+    "\n",
+    "    phi_m = MC_Ds_tuple_dict_presel_3[\"phi_M\"][i]\n",
+    "    #fixing a window on the phi mass\n",
+    "    if lower_phi_mass<phi_m<upper_phi_mass:\n",
+    "        MC_Ds_indices.append(i)\n",
+    "        \n",
+    "for i in range(len(MC_Dplus_tuple_dict_presel_3[\"Dplus_ConsD_M\"])):\n",
+    "\n",
+    "    phi_m = MC_Dplus_tuple_dict_presel_3[\"phi_M\"][i]\n",
+    "    #fixing a window on the phi mass\n",
+    "    if lower_phi_mass<phi_m<upper_phi_mass:\n",
+    "        MC_Dplus_indices.append(i)\n",
+    "        \n",
+    "for i in range(len(data_tuple_dict_presel_3[\"Ds_ConsD_M\"])):\n",
+    "\n",
+    "    phi_m = data_tuple_dict_presel_3[\"phi_M\"][i]\n",
+    "    #fixing a window on the phi mass\n",
+    "    if lower_phi_mass<phi_m<upper_phi_mass:\n",
+    "        data_indices.append(i)\n",
+    "\n",
+    "MC_Ds_tuple_dict_presel_4 ={}\n",
+    "MC_Dplus_tuple_dict_presel_4 ={}\n",
+    "data_tuple_dict_presel_4={}\n",
+    "\n",
+    "\n",
+    "for label in return_branches(mother_index=0):  \n",
+    "    \n",
+    "    data_tuple_dict_presel_4[label] = data_tuple_dict_presel_3[label][data_indices]\n",
+    "    MC_Ds_tuple_dict_presel_4[label] = MC_Ds_tuple_dict_presel_3[label][MC_Ds_indices]\n",
+    "\n",
+    "for label in return_branches(mother_index=1):  \n",
+    "    MC_Dplus_tuple_dict_presel_4[label] = MC_Dplus_tuple_dict_presel_3[label][MC_Dplus_indices]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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VZt6XX36ZXbt2ceHCBRwcHHjvvfcYOnRouY7zP//zP2RmZuLj44O1tTW2trasWLECR0dHLl++TEREBCdPntT3RUdHl1qPq6sr/v7+nD59mnfffRd7e3uOHj1aJI+npycTJkygY8eO1KhRAysrKxYtWoS1tbU+YlYpxezZswFYvXo1I0eOZNKkSeTk5DBgwABcXV3LdV5VRRXM7XmUeXp6ag/SfCshRPVw9OhRnJ2dq7oZD4S6dety9erVqm6GqKDS/qaVUgc1TfOsoiY9UqQ/IoQoTvoaojxKe3VtdVXRvohMURFCCCGEEEIIIUS1J1NUhBBCVJiM3hBCCCGEqBrvvfdeVTfhgSEBDvHQ+SX5fKnpLY2N7nNLhBBCCPGwWLH/RKnpg7xa3OeWCCGEKItMURFCCCGEEEIIIUS1JwEOIYQQQgghhBBCVHsS4BBCCCGEEEIIIUS1JwEOIYSoxpRShISE6NvZ2dnY2dkRGBiop23cuJH27dtjMplwcXFh9OjRd3SM/v374+rqyrx584iOjiYjI6NCbY6Oji7RBj8/Pwpej+no6Mj58/9dS+eTTz7BbDZjNpupVasWBoMBs9nMlClTOHz4MB06dKB27dpF3lVfmKenJ2azmRYtWmBnZ6fXdfLkSS5evEhISAiurq64uLgwdOhQMjMzAcjKyuLVV1+lTZs2GI1GPDw8+PXXXyt07pXBwcGBS5cuVXUzhBBCPCKsra0xm820a9cOd3d35s6dS25u7i3LpKens2LFikprQ2xsLK1bt8bf35+kpCQ2bNhQ4Trr1q1bZLtw/2T69OlERUXp+86dO6f3H5o2bYq9vb2+/euvv/Lss8/i5uZGmzZtipQrEBkZqecvuJ5ms5l//etfACxYsACDwYDJZKJDhw7s2bOnyLm7urpiNBpxcXHh448/rvC5V9TUqVPL7HdVNVlkVAghKkvCksqtz3PYbbPUqVOH1NRULBYLtra2bN26FXt7e33/vn37CA8PZ/PmzTg6OpKTk8PixYvL3YQzZ86QmJjI8ePHgbxAhJubG82bNy93HTk5OVhbW5c7f3EjRoxgxIgRQN6X+/j4eJ544gkAzp49yz//+U/WrFlTZvmCwMknn3xCampqkRtyly5d6NmzJ8uXLwdg1qxZDB48mHXr1vHZZ59x5coVfvzxR6ysrMjIyOCxxx67q3Oo6DUQQgghAPj2r5Vbn//bt81ia2tLUlISgP5gIDMzkxkzZpRZpiDAMWjQoEpp5pIlS1iyZAm+vr5ER0eTkJBAr169yl2+ovfhxo0b69dg6tSpNGrUiPDwcAAyMjJYsGABbm5uZGZmYjab6dGjB25ubnr5iIgIIiIiyM7OplGjRnpdAMuXL+fzzz9n165d1K9fn5SUFAICAoiPj6dhw4aMGzeOxMREmjdvTlZWFidOlL7g8b2+BtWFjOAQQohqrlevXnzzzTcAxMTEMHDgQH3fvHnziIiIwNHREch7ChMWFlaijgMHDuDt7Y3RaMTd3Z3Dhw8D0K1bN06fPo3ZbGbmzJkkJCQwePBgzGYzFouFvXv34u3tjcFgwM/Pj1OnTgF5gZDw8HC8vb356KOP7tm5N2nSBE9PT2rUuPN4fXJyMqdPn2bChAl62jvvvENqaippaWmcO3eOZs2aYWWVd6ts3ry5HlgpzMHBgUmTJuHu7o7JZOKnn34CICQkhLCwMHx8fHjnnXe4cuUKAwYMwGg04urqqgdlDh06xDPPPIPZbMZgMPDzzz8DsHDhQv1pTWhoKNnZ2Xd8jkIIIURlatCgAYsXL2b+/PlomkZ6ejq+vr6YzWZcXV2Ji4sDYPLkycTHx2M2m5k3b16Z+Yrr3bs3Hh4etG7dWu8/REZGsmvXLkJDQ3njjTeIiIggNjYWs9lMbGwsV69eZeDAgfo9c9WqVUDeiIygoCC6detGly5d7tk1ad68uR7MePzxxzEYDJw+fbrc5T/88EOioqKoX78+AAaDgWHDhrF48WIyMzNRStGwYUMAatWqRatWrUrUMXXqVF555RU6duxIy5YtWbhwIQDbtm3Dz8+PF154AaPRCJTev7h58yaDBg3CYDBgMBj0h0FHjx7lueeew2g04uXlxZEjR+7+Qt0nMoJDCCGqueDgYCIjIwkMDCQ5OZnhw4cTHx8P5H2Jv9UTlgLOzs7s2bMHKysrtm3bxqRJk1i/fj1r164lMDBQf9Kwfft2oqKi8PT0JCsri9GjR7Np0ybs7OyIjY1l0qRJfP7550Dek4J9+/aVerzY2Fh27dqlbxeMELmfUlJS8PDwKJKmlMLd3Z2UlBSCg4N59tln2blzJ506dWLw4MF4enqWWpednR2JiYksXbqU8PBwfejs2bNn2b17N0opxo4dS58+fYiNjeXixYt4eHjQo0cPFixYwOTJk+nbty83b94kJyeHgwcPsmHDBhITE6lRowYjR45k2bJlDBt2+1E9QgghxL1kb29PzZo1OXfuHE2aNGHHjh3UqlWLtLQ0XnrpJVJSUpgzZw5RUVGsX78eAIvFUmq+4pYvX079+vWxWCy4u7sTHBxMREQEO3bs0PsfJpOJhIQE5s+fD8D48eMJCAggJiaGS5cu6fdXgMTERA4fPqwHDwqzWCyYzWZ9+/fffycoKKhC1+bnn38mKSkJHx+fcpdJTU0t0R/x9PTk448/pnnz5vj5+eHo6Ii/vz89e/Zk4MCBpT7YSUlJYf/+/WRmZuLm5kbv3r2BvJGsx44dw97evsz+Rdu2bbly5Yr+mVy5cgWA4cOHs3z5cp5++ml2795NWFgY33333d1envtCAhxCCFHNGY1G0tPTiYmJuaPhmoWdP3+e4OBg0tPTsbKywmKx3LZMcnIyaWlpdO3aFcgLaDRu3Fjf369fvzLLDhgwQO+YQN6IjweJpmk89dRTHD9+nO3btxMXF0eXLl1Ys2ZNqU+B+vfvD+QFm8aNG6en9+3bF6UUAFu2bOHbb79lzpw5QN56KadOneLZZ59lxowZHD9+nBdffJG2bduydetWDh48qAdULBZLkalHQgghRFXSNA2Aa9eu8dprr5GSkkKtWrU4duxYqfnLk0/TNObMmcO6deuwtrYmIyODtLQ0mjRpcsu2bNmyhS1btuhrX9y8eVOfxtG1a9dSgxtQdOoNoE99uVtXrlyhX79+/POf/6RevXp3XU+BgmscExNDYmIicXFxREVFsW3bNpYuXVoi/4svvkjNmjVp2LAh/v7+7N+/n8cff5wOHTrofYiy+hdBQUEcPXqUsWPH0rNnT7p3786ZM2dISkqib9+++jGysrIqfF73mgQ4hBDiIRAUFMTEiROJi4vjwoULerrBYCAxMREnJ6dblp8yZQo9e/Zk9OjRpKenlyvgoGkaJpNJHy1SXJ06de7oHO43g8HAe++9VyRN0zQOHTqkByFsbW0JDAwkMDCQRo0a8dVXX5Ua4CgIYhRX+Bpomsb69ev585//XCSPk5MTHTp0YMOGDQQEBPDpp5+iaRojR45k2rRpFT1NIYQQolJlZGToDzWmTJlCixYtWLlyJTk5OdjY2JRaZu7cubfNt3XrVuLj40lISMDGxgY/P79yTc/UNI21a9fy9NNPF0lPSEi4b32RrKws+vTpwyuvvHLHo0Dc3NxITEzEy8tLTzt48KA+pQTA3d0dd3d3Bg0aRKtWrUoNcBTvixRsF++LlNW/SEpKYtOmTSxcuJAvvviCyMhImjZtWiQIVB3IGhxCCPEQGD58ONOmTcNgMBRJDw8PJzIyUn/7R25urj4vszCLxUKzZs0AWLZsWZnHsbW15dq1a0DeyJETJ06QmJgI5I1I+PHHHyvlfO4Ho9FIs2bNiiw6+v777+Ps7Ezr1q05dOgQv/32G5B33VJSUnBwcCi1roL1NFatWlXmsNTu3buzYMECfTs1NRWAX3/9lVatWjF27FgCAwNJTEyka9euxMbG6m9LuXz5sr6+iRBCCFFVLl26xKhRo3j99ddRSmGxWGjatClKKWJiYsjJyQGK9heAMvMVZrFYaNCgATY2NqSlpZU5zbV43WXdX+8XTdMYOnQoZrO5yCjO8goPD+fNN9/U3+J2+PBhPv30U1599VUyMzOLXIekpKQy+yJff/01N2/e5OLFi8TFxdG+ffsSecrqX5w/fx6lFP369WPGjBl8//33NGvWjHr16rFx40b9PAvWaHuQyQgOIYR4CDg4ODB27NgS6T4+PkRFRdGvXz+ysrLIycmhc+fOJfJNnDiRkJAQ/vrXv+rzVkszZMgQhg0bRr169di7dy+rV69m1KhR3Lhxg+zsbMaMGXPb0SLlYTQa9cU9+/fvz4cfflhqvlOnTuHt7U1mZiZWVlZERUXx008/lfttJ2vWrGH06NG4urqiaRqenp76a+1Onz7NsGHDyMnJ4caNG3h5eTFmzJhS6zl79iweHh5kZ2ezevXqUvPMnj2bUaNG4eLigpWVFY6Ojqxfv56lS5eyatUqatSoQbNmzfTV2SdMmEDHjh2pUaMGVlZWLFq0qMxOjRBCCHGvFKxVoZRCKcWgQYMYP348AGFhYQQFBfH555/TtWtXfbSA2WwmKysLNzc3QkNDy8xXWI8ePZg/fz5OTk44Ozvj7e1danv8/f2ZPXs2RqORKVOmMHPmTMLCwnB2dqZGjRo4ODjoX8or4r333ivyEKSsBw3fffcdMTExGI1GfU2P999/n+7du5frOP/zP/9DZmYmPj4+WFtbY2try4oVK3B0dOTy5ctERERw8uRJfV90dHSp9bi6uuLv78/p06d59913sbe35+jRo0XyeHp6ltq/sLa2JjQ0FMgb+TF79mwAVq9ezciRI5k0aRI5OTkMGDAAV1fXcp1XVVEFc3seZZ6enlpF5luJB8svyedLTW9pbHSfWyIedkePHsXZ2bmqmyGqmIODA6mpqaW+YaW6Ke1vWil1UNO00ldXFZVK+iMPthX7S3814yCvFve5JeJRIn0NUR7FX11bnVW0LyJTVIQQQgghhBBCCFHtyRQVIYQQogJkbQwhhBBCVKXii6Y/ymQEhxBCCCGEEEIIIao9CXAIIYQQQgghhBCi2pMAhxBCCCGEEEIIIao9CXAIIYQQQgghhBCi2pMAhxBCVGNKKUJCQvTt7Oxs7OzsCAwM1NM2btxI+/btMZlMuLi4MHr06Ds6Rv/+/XF1dWXevHlER0eTkZFRoTZHR0eXaIOfnx8Fr8d0dHTk/Pn/vu75k08+wWw2YzabqVWrFgaDAbPZzJQpU4iOjsbNzQ03Nzc8PT1JTEwscTxPT0/MZjMtWrTAzs5Or+vkyZNcvHiRkJAQXF1dcXFxYejQoWRmZgKQlZXFq6++Sps2bTAajXh4ePDrr79W6Nwrg4ODA5cuXarqZgghhHhEWFtbYzabadeuHe7u7sydO5fc3NxblklPT2fFihWV1obY2Fhat26Nv78/SUlJbNiwoUL1ubu7c/PmzUpqXUnz58/n6aefxs3Njfnz55eaZ/ny5cyZM6dc9fXq1avUe7+joyMGgwEXFxeee+45Tp8+racX9KXu5vO7H+Li4or0VyuLvEVFCCEqyf8m/W+l1vea+bXb5qlTpw6pqalYLBZsbW3ZunUr9vb2+v59+/YRHh7O5s2bcXR0JCcnh8WLF5e7DWfOnCExMZHjx48DeYEINzc3mjdvXu46cnJysLa2Lnf+4kaMGMGIESOAvC/38fHxPPHEE0De+e3Zs4fHH3+cdevWMXLkSD1QUqBg+5NPPiE1NZW///3v+r4uXbrQs2dPli9fDsCsWbMYPHgw69at47PPPuPKlSv8+OOPWFlZkZGRwWOPPXZX51DRayCEuH9W7D9R1U0Qokyjt9/ZQ4rbmd+59C/fhdna2pKUlASgPxjIzMxkxowZZZYpCHAMGjSoUtq5ZMkSlixZgq+vL9HR0SQkJNCrV69yly9+H/bx8WH37t34+flVSvsKu379OtOnT+fnn3/m8ccf5+TJk6Xm6969OwMGDGDy5Mm3rfNWAZ1vv/2WRo0a8c477xAZGcmiRYuK7L+bz+9WHvQ+jYzgEEKIaq5Xr1588803AMTExDBw4EB937x584iIiMDR0RHIi+KHhYWVqOPAgQN4e3tjNBpxd3fn8OHDAHQEJKEUAAAgAElEQVTr1o3Tp09jNpuZOXMmCQkJDB48GLPZjMViYe/evXh7e2MwGPDz89Nfmern50d4eDje3t589NFH9+zcvb29efzxxwHw9fXVn1yUR3JyMqdPn2bChAl62jvvvENqaippaWmcO3eOZs2aYWWVd6ts3ry5HlgpzMHBgUmTJuHu7o7JZOKnn34CICQkhLCwMHx8fHjnnXe4cuUKAwYMwGg04urqypo1awA4dOgQzzzzDGazGYPBwM8//wzAwoULMRqNuLi4EBoaSnZ29t1dJCGEEKKSNGjQgMWLFzN//nw0TSM9PR1fX1/MZjOurq7ExcUBMHnyZOLj4zGbzcybN6/MfMX17t0bDw8PWrdurfcfIiMj2bVrF6GhobzxxhtEREQQGxuL2WwmNjaWq1evMnDgQP2euWrVKiBvxGhQUBDdunWjS5cuRY7Ts2dPNm3apG/7+fnxxhtv4OXlhZOTEwcOHKBv37489dRTvPXWW0Be0MbNzU0vExUVxfTp00ucg5WVFZqmceHCBQCefPLJUs/Vzs6O69evc+XKFSBvREOnTp3o3bs3bdq0YejQofpIi+KjW0vTqVMnvQ9RluKfX2G3On7dunWZMGECHh4e7Nu3r8z+37x583BxccFkMtG/f3+AMj+fe0VGcAghRDUXHBxMZGQkgYGBJCcnM3z4cOLj44G8L/HlidA7OzuzZ88erKys2LZtG5MmTWL9+vWsXbuWwMBAPfK/fft2oqKi8PT0JCsri9GjR7Np0ybs7OyIjY1l0qRJfP7550BehH/fvn2lHi82NpZdu3bp2wUjRCpi0aJFBAUFlTt/SkoKHh4eRdKUUri7u5OSkkJwcDDPPvssO3fupFOnTgwePBhPT89S67KzsyMxMZGlS5cSHh6uP2k5e/Ysu3fvRinF2LFj6dOnD7GxsVy8eBEPDw969OjBggULmDx5Mn379uXmzZvk5ORw8OBBNmzYQGJiIjVq1GDkyJEsW7aMYcOG3f0FEkIIISqBvb09NWvW5Ny5czRp0oQdO3ZQq1Yt0tLSeOmll0hJSWHOnDlERUWxfv16ACwWS6n5ilu+fDn169fHYrHg7u5OcHAwERER7NixQ+9/mEwmEhIS9Kkf48ePJyAggJiYGC5duqTfXwESExM5fPgw9evXL3Icf39/IiMji6TZ2Niwf/9+PvroI1544QV++OEH6tevT8uWLYs8DLmd3NxcWrZsSWBgIPHx8fzpT38qM2/nzp3Ztm0bffr0AfIeOB07downn3ySnj17snLlynKPglm/fj0uLi63zVf88yusrOP/8ccf+Pj4MHfuXLKysujQoUOp/b8PPviAX375hdq1a+uBm4iIiDI/n3tBAhxCCFHNGY1G0tPTiYmJuaPhmoWdP3+e4OBg0tPTsbKywmKx3LZMcnIyaWlpdO3aFcgLaDRu3Fjf369fvzLLDhgwoMic1IoOEd2+fTvLli0rEjSpCE3TeOqppzh+/Djbt28nLi6OLl26sGbNmhJPgQD9KUVwcDDjxo3T0/v27YtSCoAtW7bw7bff6vNts7OzOXXqFM8++ywzZszg+PHjvPjii7Rt25atW7dy8OBBPaBisViKTD0SQgghqlLB0/9r167x2muvkZKSQq1atTh27Fip+cuTT9M05syZw7p167C2tiYjI4O0tLQSX8KL27JlC1u2bCEqKgqAmzdvcuJE3lSzrl27lghuADz22GM88cQTZGRk6NNuC9aDMBgMuLm56X2aVq1acfr06VsGKgp7++23eeGFF/j9998JDAxk27ZtbN26le3bt/OPf/yjSN6ePXuydOlSPcDRvn17/vznPwN5faVdu3bdNsDh7+9Pbm4ubm5uLFiwoFxtLD56o0BZx7e2tubFF18Ebt3/MxqNDBkyhMDAQP2cbvX53AsS4BBCiIdAUFAQEydOJC4uTh8SCXk36cTERJycnG5ZfsqUKfTs2ZPRo0eTnp5eroCDpmmYTCZ9tEhxderUuaNzuFtJSUmMHDmSzZs306BBg3KXMxgMvPfee0XSNE3j0KFDehDC1taWwMBAAgMDadSoEV999VWpAY6CIEZxha+BpmmsX79e7zgUcHJyokOHDmzYsIGAgAA+/fRTNE1j5MiRTJs2rdznI4QQQtwPGRkZ+pfaKVOm0KJFC1auXElOTg42Njallpk7d+5t823dupX4+HgSEhKwsbHBz8+vXNMzNU1j7dq1PP3000XSExISbtkX6d69O5s2bWL48OEA1K5dG8ibYlLwe8F2bm6u/m+B69evl1rvxo0b2bZtGw4ODkyYMIGXX36Z+vXrl7rIu5eXF6+99t8114r3J8rqXxRWsAZHeRX+/Ior6/g2Njb6uhu36v9988037Ny5k/Xr1zN79mxSU1PL/HzKmqZUUfd1DQ6l1KdKqXNKqdRCabFKqaT8n3SlVFJ+uqNSylJo38JCZTyUUoeUUkeUUv9Q+VdeKVU7v75UpdQepZTj/Tw/IYSoKsOHD2fatGkYDIYi6eHh4URGRupv/8jNzWXhwoUlylssFpo1awbAsmXLyjyOra0t165dA/Ki9CdOnNDfXJKdnc2PP/5YKedTXunp6fTr148VK1bQqlWrOyprNBpp1qxZkUVH33//fZydnWndujWHDh3it99+A/KuW0pKCg4ODqXWVbCexqpVq/Dx8Sk1T/fu3Ys8WUlNzbsV/vrrr7Rq1YqxY8cSGBhIYmIiXbt2JTY2Vl8x/fLly/r8ViHEg2XF/hOl/gjxMLp06RKjRo3i9ddfRymFxWKhadOmKKWIiYkhJycHKNpfAMrMV5jFYqFBgwbY2NiQlpZW5jTX4nWXdX+9neLrcNxO48aNOXPmDBcuXODmzZv6+mfFubq6EhsbC8AHH3xAZmYmiYmJeHt7l8hrbW1N27ZtOXLkCJA3ReTEiRNomsbq1avp2LFjudtXHsU/v+LKc/yy+n+5ublkZGTg7+/PnDlzyMzM5NKlS3f9+dyt+73IaDRQZMKNpmkDNE0za5pmBv4NfFFo9/8V7NM0bVSh9CXACE3TXIA/A33y00cDZzVNcwM+AIqOARJCiIeUg4MDY8eOLZHu4+NDVFQU/fr1w2QyYTQaOXr0aIl8EydOZOLEiXh6enLjxo0yjzNkyBCGDRuG2WwmNzeX1atXM2rUKEwmEyaTqdKi8UajEQcHBxwcHBg/fnyZ+aZPn87vv//OX/7yF8xmM15eXnd0nDVr1nDgwAH9NbFHjhzRX2t3+vRpunbtisFgwMnJCSsrK8aMGVNqPWfPnsXDw4OoqKgiAZPCZs+ezalTp3BxccHNzU1fNX3p0qW4ublhNps5duwYISEheHp6MmHCBDp27IjJZMLPz6/Cr+cVQggh7obFYtFfM/r888/TqVMnfYRhWFgYH3/8Me7u7qSmpuojJsxmM1lZWbi5uTFv3rwy8xXWo0cPrl+/jpOTE2+99VapAQHIm5Jx8OBBjEYjsbGxzJw5k3PnzuHs7IzBYODNN98s13k5Ozvz008/lRpsKY2NjQ2TJ0+mXbt2dOvWjbZt25aa71//+hc7duygTZs2uLu789xzz+Ht7c0bb7xRav4ePXqwceNGAJ555hlGjx5N27ZtadKkCcHBweVq263c6vMrrjzHr127dqn9v5ycHAYMGIDJZKJdu3a89tprNGrU6K4/n7ulypp/c88OmDeqYn1+EKJwugJOAM9rmpZ2i3wtgI2aprnmb78M9NA0LVQptQOYpGna90opK+Ac0ETTtFv+1Xp6emrFXysoqq9fkktfYbilsfxDt4Qoj6NHj+Ls7FzVzRBVzMHBgdTU1FLfsFLdlPY3rZQ6qGla6aurikol/ZEHQ2WNvhjk1aJS6hGPNulr3FujRo1iyJAhlT5S4k785z//4ZVXXuGdd94psjDr/RYXF1elxy9Q0b7Ig/Sa2GfJG32RVijNUSn1g1Jqr1Kqc36aA1D4ZcKn8tOK7NM0LRe4AJScXAQopUYqpRKUUgkFQ5CFEEIIIYQQQjwaFi5cWKXBDYBmzZqxZcuWKm3Dw+RBWmR0IBBTaPs/gIOmaZeUUu7AeqWUa2UdTNO0xcBiyHtiUln1CiGEeLTI2hhCCCGEqCg/P78Kv1WuOh+/sjwQAQ6lVA3gJcCjIE3TtBvAjfzfE/MXJnUmb8TGk4WKO+SnUWjfmfwpKg0BGZ4hhBBCCCGEEEI85B6UKSpdgB81TdMfgymlGuYHKQrW7XADjmuadgLIzR/VATAY2Jj/+wYgJP/3F4B9mqbd/t1CQgghhBBCCCGEqNbu92tiY4C9QFul1CmlVGj+rmCKTk8B8AdSlFIpwHpgnKZp5/L3DQM+VUodIW/Uxr/z0+cDzfNHe0wCSr5SQAghhBBCCCGEEA+d+zpFRdO0gWWkDy0lbQ2wpoz8CYC5lPTrwMsVa6UQQgghhBBCCCGqmwdliooQQoi7oJQiJCRE387OzsbOzo7AwEA9bePGjbRv3x6TyYSLiwujR4++o2P0798fV1dX5s2bR3R0NBkZGZXW/vL46quvOHLkiL5dvA0jRowosv9BEx0dXeY179WrF5cuXbrPLXp0KKU+VUqdyx/ZWZD2oVLqaP7PN0qpRoX2vZ2fnqqU6l4o3UMpdUgpdUQp9Y/8V9ujlKqtlIrNz78nf0ptQZlX8vMfUUq9cn/OWAghKp+1tTVms5l27drh7u7O3Llzyc3NvWWZ9PR0VqxYUWltiI2NpXXr1vj7+5OUlMSGDRsqre7yKH4+xduwdu1a5syZc1/bdKfq1q1bavrChQv57LPP7nNr7p0HYpFRIYR4GJwcFVap9T25cMFt89SpU4fU1FQsFgu2trZs3boVe3t7ff++ffsIDw9n8+bNODo6kpOTw+LFi8vdhjNnzpCYmMjx48eBvBW23dzcaN68ebnryMnJwdrautz5i/vqq68IDAzExcUFyAsYFG7DJ598ctd1V7X73UF7BEWTN321cM9tPfCWpmnZSqn3galAuFLKA+gLGIEmwC6lVNv8Rc+XAMM0TTuolPoa6AN8AYwm7xX3A5RSfYB/AEFKqWZABNAO0IAkpdRmTdPO3IdzFkI8xKqir2Fra0tSUhIAFy9eJCQkhMzMTGbMmFFmmYKAwKBBgyqlnUuWLGHJkiX4+voSHR1NQkICvXr1Knf5ivZFip9PUlJSkTYEBQURFBR01/VXpVGjRlV1EyqVjOAQQohqrlevXnzzzTcAxMTEMHDgf2cDzps3j4iICBwdHYG8pzBhYSU7RwcOHMDb2xuj0Yi7uzuHDx8GoFu3bpw+fRqz2czMmTNJSEhg8ODBmM1mLBYLe/fuxdvbG4PBgJ+fn/7KVD8/P8LDw/H29uajjz4qcqwrV64QHByMi4sLRqOR1atXA0WfLKxZs4ahQ4eyZ88e1q5dy5tvvonZbOb9998v0QY/Pz8SEhL0OqZMmYLZbMZsNusjPX788UfMZjPu7u5MnTq1zKcYs2bNwsnJCScnJ/1JTHp6Os7OzvzlL3/B1dWV5557jqtXr5YoO3ToUEaNGoWXlxdPPfUUX3zxhb4vIyODgIAAWrZsybhx4/R0R0dHzp8/X6KuunXr8tZbb2EwGOjSpQv79u3j+eef58knn+Tf//633i5fX1/MZjOurq7ExcUBea+t7dSpE2azGTc3N3bu3El2djZDhgzBzc0Ng8FAVFRUqef/sNE0bSfwe7G0HYUWIN8FFEQEA4BYTdNu5i96fhhor5RqAVhrmnYwP9/y/LwFZZbl//414KOUsga6Aps0TcvUNO0KsCk/TQghqrUGDRqwePFi5s+fj6ZpZd6LJk+eTHx8PGazmXnz5pWZr7jevXvj4eFB69at9f5DZGQku3btIjQ0lDfeeIOIiAhiY2Mxm83ExsZy9epVBg4ciNFoxMXFhVWrVgF5D0SCgoLo1q0bXbp0KXGsRYsW4ezsjNlsZvDgwUDevXzNmv+uklDQXyh8Pu+//36JNhQerTl06FDGjh3Ls88+y5NPPsnnn38O5AVZhg8fTps2bejRowe9evUqcqwCBw4coF27dri5udGjRw8uXLgA5PWtJk2aRIcOHXB0dGT79u0lysbFxdGpUyd69+5NmzZtGDp0aJHRNqX1kaZPn15qv2Do0KGEhYXRsWNHnnrqKb799luGDRtG27Zti/Q1//KXv+Dp6Unr1q2ZNGmSnv7mm2/i4uKCyWTijTfeAPL6qW5ubpjNZnx9fUscszLICA4hhKjmgoODiYyMJDAwkOTkZIYPH058fDwAycnJt3zCUsDZ2Zk9e/ZgZWXFtm3bmDRpEuvXr2ft2rUEBgbqT262b99OVFQUnp6eZGVlMXr0aDZt2oSdnR2xsbFMmjSpyI183759JY41depU7O3tWblyJQCXL18us10+Pj4EBQURGBhIv379gLwpNwVtKO6PP/6gY8eOzJo1i7feeotFixYxY8YMxowZwzvvvEP//v35+OOPSz3Wnj17WLlyJUlJSWiahqenJ35+fjRt2pS0tDRiY2NZtGgR/fv3Z/Xq1QwbNqxEHSdOnGDfvn2kp6fj5eVFjx49gLwnPcnJydSoUYM2bdowbtw4nnrqqTLP+48//qBz58787W9/o0+fPkRERLB161ZSU1MZNGgQffv2pUmTJuzYsYNatWqRlpbGSy+9REpKCitWrCAgIIBJkyahaRp//PEHiYmJnD9/ntTUvJkaV65cKfPYj5iRwKr83x2AHYX2ncpPywFOlpJeUOYkgKZpuUqpC0DjwumllBFCiGrN3t6emjVrcu7cuTLvRXPmzCEqKor169cDYLFYSs1X3PLly6lfvz4WiwV3d3eCg4OJiIhgx44d+r3fZDKRkJDA/PnzARg/fjwBAQHExMRw6dIlPDw89PtvYmIihw8fpn79+kWOk5iYSFRUFN9//z1PPPHEbaeLFj+fJk2aFGlDdHR0kfxnz55l586dHD16lJ49ezJ48GBWrlzJuXPnOHbsGOfPn6dNmzYMHz68xLGGDBnC//t//w9fX19mzJjBlClTWLhwIQCaprF37142bNhAZGQknTt3LlH+wIEDHDt2jCeffJKePXuycuVKBg0aVGYf6VYuX77M7t27+frrrwkKCmL//v04OTnxzDPP8P333/PMM8/wt7/9jfr165OTk0Pnzp1JSEigRYsWbNiwgcOHD6OU0vsdM2fO5Ntvv6VJkyb3rC8iAQ4hhKjmjEYj6enpxMTE3NFwzcLOnz9PcHAw6enpWFlZYbFYblsmOTmZtLQ0unbNezCdk5ND48aN9f0FAYnitm3bxldffaVvF+90VEStWrXo2bMnAB4eHmzevBmAvXv3snFj3hvFBwwYoD9JKGzXrl306dMHGxsbAF566SXi4+N5+eWXadmyJUajUa/35MmTJcpD3jkrpWjZsiVOTk56QKFz5876UyBXV1dOnTp1ywBHrVq16NatGwAGg4HatWtjbW2NwWDQj33t2jVee+01UlJSqFWrFseOHQPA29ub0NBQLBZLkSdhx48fZ8yYMfTo0UO/Ro8ypdQUIJu8ERlV2Y6R5AVaaNGiRVU2RQghyk3TNKDse1Fx5cmnaRpz5sxh3bp1WFtbk5GRQVpaGk2aNLllW7Zs2cKWLVv0UQg3b97kxIkTAHTt2rXUfsb27dvp378/TzzxBID+b2UJCgpCKYWLi4s+UnP37t307dsXpRR2dnb4+/uXKHfu3DksFos+uiEkJKTI1JcXXngBuHVfpH379vz5z38G8vo8u3btYtCgQWX2kW4lICBvwKLBYKBp06b6dGFXV1dOnjzJM888w6effsqSJUtQSpGRkaGPmq1ZsyahoaH06tWL3r17A9CpUyeGDBlC3759eemll6hXr97tL+YdkikqQgjxEAgKCmLixIlFhgxC3g0pMTHxtuWnTJlCz549OXz4MOvWrSM7O/u2ZTRNw2QykZSURFJSEikpKUWGS9apU+eOzqGgswRw/fr1OypboGbNmuSv/4i1tfVtF0Err9q1a+u/36regmMX3y5v+QKFz8PKykovb2VlpZedO3cuLVq04PDhwyQkJOjpnTp14rvvvsPBwYERI0awdOlSGjRowKFDh/Dz8+OTTz4hNDS09AM/IvIX/ewNDNb++4d3CniyUDaH/LSy0ouUUUpZAQ2B325TpghN0xZrmuapaZqnnZ1dRU5LCCHui4yMDP2hRln3ouLKk2/r1q3Ex8eTkJDADz/8QLt27crdH/n666/1/siJEydwc3MD7rwvUvg+m5ubS1ZW1h2VL1D4vl+8b1ARBfXeTV/kbvpIhfsfhc+p4DodO3aM+fPnEx8fzw8//EBAQADZ2dnUqFGD/fv3069fPzZu3KiPqFm4cCEzZ87kP//5Dx4eHvr0m8okAQ4hhHgIDB8+nGnTpmEwGIqkh4eHExkZya+//grk3awLhjkWZrFYaNasGQDLli0rsb+Ara0t165dA/JGjpw4cUIPoGRnZ/Pjjz/etq1du3Zl0aJF+nbBFJWGDRty9OhRNE0rMsKj8DFL2y4Pb29vvc6CNT+K8/X15auvvuLGjRtcv36dL7/8kk6dOt3Rcf7973/rc5KPHTumd7DuBYvFQtOmTVFKERMTQ05ODgAnT56kadOmjBgxgtDQUL7//nu9A9G3b19mzpzJ999/f8/a9aBTSvUAJgG9NU0r/Ie0ARiglKqplHIA3IADmqadAHKVUu75+QYDGwuVKXiN0QvAvvz1PbYBPZRSjyul6gE989OEEKJau3TpEqNGjeL1119HKVXmvaj4vbqsfIVZLBYaNGiAjY0NaWlppU5zLa3u7t27s2DBfxdLLRg9eSudO3dm1apV+tSUgn8dHBw4eDBvyaVvvvmGmzdvlnrMu+mL+Pj48OWXX6JpGufPny91HZLGjRtja2vLnj17AFixYsUd90UOHDjAiRMn0DSN1atX07FjxzsqfyeuX79O3bp1qVevHufPn9dHy169epWrV6/Sq1cvPvzwQ72vWDCFd/r06TRp0oRffvml0tskAQ4hhHgIODg4MHbs2BLpPj4+REVF0a9fP0wmE0ajkaNHj5bIN3HiRCZOnIinpyc3btwo8zhDhgxh2LBhmM1mcnNzWb16NaNGjcJkMmEymcpcNKywmTNncuLECZydnTGZTGzblve9769//Svdu3fH19eXpk2b6vkHDBhAZGQkZrOZ//u//yvShvJMpQH4xz/+wcyZM/Hw8ODYsWPY2tqWyOPj48OAAQMwmUyYzWZCQkLw8vIqV/0FHBwc6NChA88//zz/+7//W+pxKktYWBgff/wx7u7upKam6k+ptm/fjtFopF27dsTGxjJu3DhOnjypL+4WEhLCX//613vWrgeJUioG2Au0VUqdUkqFkvdWlXrAVqVUklJqIYCmaQnAl0AysBkYlf8GFYBhwKdKqSPkjcT4d376fKB5/mtoJwFj8+vKAGYB+4EDwExN0/5zz09YCCHuAYvFor8m9vnnn6dTp05MmzYNKPteZDabycrKws3NjXnz5pWZr7AePXpw/fp1nJyceOutt/D29i61Pf7+/hw8eBCj0UhsbCwzZ87k3LlzODs7YzAYePPNN297Tu7u7kyYMAFvb2/MZjNjxowB8t4osnnzZsxmM7t37y7zfIq3oTwGDhzIn/70J9q2bUtISAju7u6l9hOWLVvG66+/jsFgYNeuXbz33nvlqr/AM888w+jRo2nbti1NmjQhODj4jsrfCZPJhMFgoHXr1gwaNEgPpmRmZtK9e3d9MdEPP/wQyHvwZjQacXNzw8vLCw8Pj0pvkyo8JPhR5enpqRWswC+qv1+SS76RAKClsdF9bol42B09ehRnZ+eqboYoh4LX6AKsXLmS6OhoNm3aVKnHGDp0aJHFUKuj0v6mlVIHNU0ruaKrqHTSH3kwrNh/olLqGeQla6qIipO+xsPl2rVrPPbYY1y4cAF3d3f27NmDvb397QuWU1xcXJHFUKujivZFZJFRIYQQD73vv/+eMWPGkJWVRb169fjss8+quklCCCGEeMT06NGDy5cvc/XqVd5+++1KDW6IPBLgEEII8dDr1KkTP/zwwz09RvFXxAkhhBBCFLZz5857Wr+fnx9+fn739BgPOlmDQwghhBBCCCGEENWeBDiEEEIIIYQQ4gElayaKR0Vl/K1LgEMIIYQQQgghHkA2NjZcuHBBghzioadpGhcuXMDGxqZC9cgaHEIIIYQQQgjxAHJwcODUqVP89ttvVd0UIe45GxsbHBwcKlSHBDiEEKIaU0oxePBgli9fDkB2djbNmjXDy8tLf0XYxo0bmTZtGjdu3ODmzZs8//zzzJ8/vyqbXWF169bl6tWrVd0MIYQQ4p6qWbMmLVu2rOpmCFFtSIBDCCEqyS/J5yu1vpbGRrfNU6dOHVJTU7FYLNja2rJ169Yirxzbt28f4eHhbN68GUdHR3Jycli8eHGltrO8cnJysLa2rpJjCyGEEEKIh5+swSGEENVcr169+OabbwCIiYlh4MCB+r558+YRERGBo6MjANbW1oSFhZWoY/r06QwfPpzOnTvTokULPvjgA33frFmzcHJywsnJiTlz5pTahrp16zJ+/HhMJhM+Pj6cPXsWyHtdWXh4ON7e3nz00UecOXOGgIAAjEYjJpOJuLg4ALZv347ZbNZ/MjMzAYiMjMRgMODk5MTkyZMrfK2EEEIIIcTDSwIcQghRzQUHB7Ny5UquX79OcnIyXl5e+r7k5GQ8PDzKVc+xY8fYvHkziYmJzJ49m+vXr7Nnzx5WrlxJUlIShw4dYtmyZezbt69E2T/++IP27dvzww8/EBAQwLvvvqvvy8nJYd++fYwfP57XXnuNt99+m+TkZNatW0doaCiapjH3/7N372Fel2Xix983oyCRbW2OiU6IlsVpDsEkiOayiSdgbU0SBNz1QAYtKinriZTUZcu0NNdNMVcpDEQxyQOkqPFTU1QYZocBNFiYnwMAACAASURBVMiQg4lAecoBg3l+f8yX2QFm5AvMgS/zfl3XXPP93J/neT73Z+S6GG6fw49+xKRJkygvL+eFF17gYx/7GA8//DCrV6+moqKCJUuWUFlZyZw5c/b8ByZJkqR9kktUJCnHFRUVsWLFCqZNm8aAAQN2e5wBAwaw3377cdBBB3HIIYfw1ltv8dxzz3H66afX7mj99a9/nWeffZY+ffps07dNmzYMHjwYgLPOOotBgwbV3tsaB3jyySd57bXXaq83btzIu+++y/HHH8/FF1/MWWedxemnn06nTp144okneOKJJ/jSl74EwPvvv88f//jH3X4/SZIk7dsscEjSPuC0005j3LhxzJ07lw0bNtTGCwsLKSsro0uXLjsdo127drWf8/LyqK6u3u18IqL2c4cOHba599JLL9G2bdttYldccQUDBw5k9uzZHHfccTzxxBOklLj66qs5//zzdzsPSZIktR4uUZGkfcB5553HhAkTKCws3CY+duxYrrvuOl5//XUAqqurueOOO7Ie97jjjmPmzJls2rSJjRs38tBDD3H88cfv0K66upqHHnoIgOnTp3PsscfWO17//v2ZNGlS7XVlZSUAK1asoLCwkMsuu4yjjz6ayspKTj75ZO655x6qqqoAWLt2rcfkSZIkqUHO4JCkfUBBQQEXXXTRDvG+ffty0003MXjwYD788EO2bNnCCSeckPW4ffv2ZciQIRQXFwNwzjnnbLPHx1YdOnTghRdeYOLEibRv37622LG9O+64g5EjRzJp0iRSShxzzDHcdddd3HjjjTzzzDNEBF27dmXgwIG0b9+eJUuW0LNnT9q2bUu7du2YNm0a+fn5WecvSZKk1iNSSi2dQ4srLS1N8+fPb+k01EgaOqozmyM3pV2xdOlSunbt2tJp7BU+/vGP8/7777d0GtpD9f2ZjogFKaXSFkqpVfH3kb3D1BdXNso4w3p3apRxJKm125XfRVyiIkmSJEmScp4FDknSHnP2hiRJklqaBQ5JkiRJkpTzLHBIkiRJkqScZ4FDkiRJkiTlPAsckiRJkiQp51ngkKQcFhGMGDGi9nrz5s3k5+czaNCg2tjs2bM5+uijKS4uplu3bowZM2aXnnHmmWfSvXt3br75ZiZPnswbb7yxRzlPnjx5hxz69evH1uMxO3fuzPr1/3fc81133UVJSQklJSW0bduWwsJCSkpKGD9+PIsXL+aYY46hXbt23HLLLfU+r7S0lJKSEjp16kR+fn7tWKtWreIvf/kLI0aMoHv37nTr1o1zzjmHd999F4APP/yQb37zm3zhC1+gqKiIXr168frrr+/RuzeGgoIC3n777ZZOQ5Ikaa+zX0snIEn7ioonf9Oo4xX1P2WnbTp06EBlZSVVVVW0b9+eOXPmcNhhh9XenzdvHmPHjuXxxx+nc+fObNmyhTvvvDPrHN58803KyspYvnw5UFOI6NGjB4ceemjWY2zZsoW8vLys229v5MiRjBw5Eqj5x/2zzz7LJz/5SQDWrl3Lf/3XfzFjxowG+28tnNx1111UVlZuUwjp378/p556Kvfeey8AEydOZPjw4TzyyCP84he/4L333uOVV16hTZs2vPHGG3zsYx/brXfY05+BpNwz9cWVO8SG9e7UAplIUuvhDA5JynEDBgzgscceA2DatGmcddZZtfduvvlmrrnmGjp37gxAXl4eo0eP3mGMl156iT59+lBUVETPnj1ZvHgxACeddBJr1qyhpKSE66+/nvnz5zN8+HBKSkqoqqrihRdeoE+fPhQWFtKvXz9Wr14N1BRCxo4dS58+ffjJT37SZO/+mc98htLSUvbbb9fr9RUVFaxZs4ZLL720NnbVVVdRWVnJsmXLeOutt+jYsSNt2tT8VXnooYfWFlbqKigo4PLLL6dnz54UFxfz+9//HoARI0YwevRo+vbty1VXXcV7773HkCFDKCoqonv37rVFmYULF/LlL3+ZkpISCgsLee211wC44447KCoqolu3bpx//vls3rx5l99RkiSpNbHAIUk5bujQodx3331s3LiRiooKevfuXXuvoqKCXr167XSMrl278vzzz1NRUcEPf/hDLr/8cgAefvhhPve5z1FeXs7VV19NaWkpv/zlLykvLycvL48xY8bwyCOPsGjRIkaPHl3bD2pmLcybN49LLrlkh+dNnz69dqlISUlJ7SyL5rRo0aIdfjYRQc+ePVm0aBFDhw7l/vvvp1evXnznO9/5yBzz8/MpKyvjkksuYezYsbXxtWvX8rvf/Y4bbriB8ePHc/rpp1NRUcFzzz3HZZddxvvvv8/tt9/OFVdcQXl5OWVlZRx66KEsWLCAWbNmUVZWxpIlS8jLy2PKlClN9rOQJEnaF7hERZJyXFFREStWrGDatGkMGDBgt8ZYv349Q4cOZcWKFbRp04aqqqqd9qmoqGDZsmWceOKJQE1B4+CDD669P3jw4Ab7DhkyhNtuu632ul+/fruVd1NJKXHkkUeyfPlynnrqKebOnUv//v2ZMWMG/fv336H9mWeeCdQUmy6++OLa+BlnnEFEAPDEE0/w29/+lh/84AdAzX4pq1ev5itf+QrXXnsty5cv55//+Z/54he/yJw5c1iwYAGlpaUAVFVVbbP0SJIkSTuywCFJ+4DTTjuNcePGMXfuXDZs2FAbLywspKysjC5dunxk//Hjx3PqqacyZswYVqxYkVXBIaVEcXExzz77bL33O3TosEvv0NwKCwv5j//4j21iKSUWLlxYW4Ro3749gwYNYtCgQRx00EHMnDmz3gLH1iLG9ur+DFJKPProoxx++OHbtOnSpQvHHHMMs2bNYuDAgdx9992klLjggguYMGHCnr6mJElSq+ESFUnaB5x33nlMmDCBwsLCbeJjx47luuuuqz39o7q6mjvuuGOH/lVVVXTs2BHgI5dCtG/fng8++AComTmycuVKysrKgJoZCa+88kqjvE9zKCoqomPHjttsOnrDDTfQtWtXjjrqKBYuXMi6deuAmp/bokWLKCgoqHesrftp3H///fTt27feNieffDK333577XVlZSUAr7/+Op///Oe56KKLGDRoEGVlZZx44olMnz699rSUd955p3Z/E0mSJNXPGRyStA8oKCjgoosu2iHet29fbrrpJgYPHsyHH37Ili1bOOGEE3ZoN27cOEaMGMH3v/99Tjml4dNbzj77bM4991wOPPBAXnjhBR544AFGjRrFpk2b2Lx5MxdeeOFOZ4tko6ioqHZzzzPPPJMf//jH9bZbvXo1ffr04d1336VNmzbcdNNN/P73v8/6tJMZM2YwZswYunfvTkqJ0tJSpk6dCsCaNWs499xz2bJlC5s2baJ3795ceOGF9Y6zdu1aevXqxebNm3nggQfqbfOf//mfjBo1im7dutGmTRs6d+7Mo48+ys9//nPuv/9+9ttvPzp27Mh3v/tdDjroIC699FKOPfZY9ttvP9q0acOkSZMaLLBIkiQJIqXU0jm0uNLS0tQSG9ypafyxYn298SOKDmrmTLSvW7p0KV27dm3pNNTCCgoKqKysrPeElVxT35/piFiQUiptoZRaFX8f2TvUd7xrY/GYWEnadbvyu4hLVCRJkiRJUs5ziYokSXvAvTEkSZL2DhY4lLMaWooiSZIkSWp9XKIiSZIkSZJyngUOSZIkSZKU8yxwSJIkSZKknGeBQ5JyWEQwYsSI2uvNmzeTn5/PoEGDamOzZ8/m6KOPpri4mG7dujFmzJhdesaZZ55J9+7dufnmm5k8eTJvvPHGHuU8efLkHXLo168fW4/H7Ny5M+vX/98eO3fddRclJSWUlJTQtm1bCgsLKSkpYfz48UyePJkePXrQo0cPSktLKSsr2+F5paWllJSU0KlTJ/Lz82vHWrVqFX/5y18YMWIE3bt3p1u3bpxzzjm8++67AHz44Yd885vf5Atf+AJFRUX06tWL119/fY/evTEUFBTw9ttvt3QakiRJe51m3WQ0Iu4GBgFvpZR6ZGLfA74JrMs0uyqlNCtz70rgX4AtwKUppccz8V7AXUA74Eng4pRSioh2wC+A7sC7wLCU0ormeTtJrd07cxr3H79/d+LhO23ToUMHKisrqaqqon379syZM4fDDjus9v68efMYO3Ysjz/+OJ07d2bLli3ceeedWefw5ptvUlZWxvLly4GaQkSPHj049NBDsx5jy5Yt5OXlZd1+eyNHjmTkyJFAzT/un332WT75yU8CNe/3/PPP84lPfIJHHnmECy64oLZQstXW67vuuovKykpuueWW2nv9+/fn1FNP5d577wVg4sSJDB8+nEceeYRf/OIXvPfee7zyyiu0adOGN954g4997GO79Q57+jOQJEnSzjX3DI7JwCn1xG9OKZVkvrYWN3oBZwBFmT6TMgUMgHuAkSmlbsDhwOmZ+BhgbaZ4ciNwa5O9iSTtJQYMGMBjjz0GwLRp0zjrrLNq7918881cc801dO7cGYC8vDxGjx69wxgvvfQSffr0oaioiJ49e7J48WIATjrpJNasWUNJSQnXX3898+fPZ/jw4ZSUlFBVVcULL7xAnz59KCwspF+/frVHpvbr14+xY8fSp08ffvKTnzTZu/fp04dPfOITABx33HGsWbMm674VFRWsWbOGSy+9tDZ21VVXUVlZybJly3jrrbfo2LEjbdrU/FV56KGH1hZW6iooKODyyy+nZ8+eFBcX8/vf/x6AESNGMHr0aPr27ctVV13Fe++9x5AhQygqKqJ79+7MmDEDgIULF/LlL3+ZkpISCgsLee211wC44447KCoqolu3bpx//vls3rx5935IkiRJrUSzFjhSSs8Af86y+UBgekrpbyml1cBi4OiI6ATkpZQWZNrdm2m7tc+UzOdfA30jwv9lJmmfNnToUO677z42btxIRUUFvXv3rr1XUVFBr169djpG165def7556moqOCHP/whl19+OQAPP/wwn/vc5ygvL+fqq6+mtLSUX/7yl5SXl5OXl8eYMWN45JFHWLRoEaNHj67tBzWzFubNm8cll1yyw/OmT59eu1SkpKRkh1kXu2PSpEmcdtppWbdftGjRDj+biKBnz54sWrSIoUOHcv/999OrVy++853vfGSO+fn5lJWVcckllzB27Nja+Nq1a/nd737HDTfcwPjx4zn99NOpqKjgueee47LLLuP999/n9ttv54orrqC8vJyysjIOPfRQFixYwKxZsygrK2PJkiXk5eUxZcqUBp8vSZKkZl6i8hH+LSJGAguAi1JKG4AC4Ok6bVZnYluAVfXEyXxfBZBSqo6IDcDBwJ+aNn1JajlFRUWsWLGCadOmMWDAgN0aY/369QwdOpQVK1bQpk0bqqqqdtqnoqKCZcuWceKJJwI1BY2DDz649v7gwYMb7DtkyBBuu+222ut+/frtVt5bPfXUU0yZMoXnnntuj8bZKqXEkUceyfLly3nqqaeYO3cu/fv3Z8aMGfTv33+H9meeeSZQU2y6+OKLa+NnnHEGEQHAE088wW9/+1t+8IMfADX7paxevZqvfOUrXHvttSxfvpx//ud/5otf/CJz5sxhwYIFlJaWAlBVVbXN0iNJkiTtaG8ocPw3cD2QgO9Rs6xkeFM/NCIuAC4A6NSpU1M/TpKa1Gmnnca4ceOYO3cuGzZsqI0XFhZSVlZGly5dPrL/+PHjOfXUUxkzZgwrVqzIquCQUqK4uJhnn3223vsdOnTYpXfYXeXl5VxwwQU8/vjjfOpTn8q6X2FhIf/xH/+xTSylxMKFC2uLEO3bt2fQoEEMGjSIgw46iJkzZ9Zb4NhaxNhe3Z9BSolHH32Uww/fdm+VLl26cMwxxzBr1iwGDhzI3XffTUqJCy64gAkTJmT9PpIkSa1di5+iklJal1LaklKqBu4Avpy5tRr4bJ2mBZlYQ/Ft+kREG+DT/N/mpds/986UUmlKqTQ/P7+xXkeSWsR5553HhAkTKCws3CY+duxYrrvuutrTP6qrq7njjjt26F9VVUXHjh0BPnIpRPv27fnggw+AmpkjK1eurD25ZPPmzbzyyiuN8j7ZWrFiBYMHD2bq1Kl8/vOf36W+RUVFdOzYcZtNR2+44Qa6du3KUUcdxcKFC1m3ruavkOrqahYtWkRBQUG9Y23dT+P++++nb9++9bY5+eSTuf3222uvKysrAXj99df5/Oc/z0UXXcSgQYMoKyvjxBNPZPr06bWnpbzzzju1+5tIkiSpfi1e4IiIg+tcngEsyXyeBQyJiP0jogDoAbyUUloJVEdEz0y74cDsOn22npf4NWBeSsld2STt8woKCrjooot2iPft25ebbrqJwYMHU1xcTFFREUuXLt2h3bhx4xg3bhylpaVs2rSpweecffbZnHvuuZSUlFBdXc0DDzzAqFGjKC4upri4mLlz5zbK+xQVFVFQUEBBQUG9e3hs9b3vfY8///nPfOtb36KkpGSb/UeyMWPGDF566aXaY2KXLFnC1KlTAVizZg0nnngihYWFdOnShTZt2nDhhRfWO87atWvp1asXN9100zYFk7r+8z//k9WrV9OtWzd69OjBFVdcAcDPf/5zevToQUlJCa+++iojRoygtLSUSy+9lGOPPZbi4mL69eu3x8fzSpIk7esipdR8D4uYBvQDDgLWAhOAf6TmpJS2wErg/JTSqkz78dQULKqBcSml2Zl4KTXHxLalZp+OCzPHxB5AzSajXYH3qTkm9rWd5VVaWpoaY4M7Na8/VqzfpfZHFB3URJmotVq6dCldu3Zt6TTUwgoKCqisrKz3hJVcU9+f6YhYkFIqbaGUWhV/H9k7TH1xZZONPay3y6IlaVftyu8izboHR0rprHrC//MR7ScCE+uJzwdK6olvBL6xJzlKkiRJkqTcszdsMipJUs5ybwxJkqS9Q4vvwSFJkiRJkrSnnMEhSZKkVqcp99qQJLUMZ3BIkiRJkqScZ4FDkiRJkiTlPAsckpTDIoIRI0bUXm/evJn8/HwGDRpUG5s9ezZHH300xcXFdOvWjTFjxuzSM84880y6d+/OzTffzOTJk3njjTcaLf9szJw5kyVLltReb5/DyJEjt7m/t5k8eXKDP/MBAwbw9ttvN3NGkiRJ+yb34JCkRjJ16tRGHW/YsGE7bdOhQwcqKyupqqqiffv2zJkzh8MOO6z2/rx58xg7diyPP/44nTt3ZsuWLdx5551Z5/Dmm29SVlbG8uXLAejXrx89evTg0EMPzXqMLVu2kJeXl3X77c2cOZNBgwbRrVs3oKZgUDeHu+66a7fHbmmzZs1q6RQkSZL2Gc7gkKQcN2DAAB577DEApk2bxllnnVV77+abb+aaa66hc+fOAOTl5TF69OgdxnjppZfo06cPRUVF9OzZk8WLFwNw0kknsWbNGkpKSrj++uuZP38+w4cPp6SkhKqqKl544QX69OlDYWEh/fr1qz0ytV+/fowdO5Y+ffrwk5/8ZJtnvffeewwdOpRu3bpRVFTEAw88AMDHP/7x2jYzZszgnHPO4fnnn+fhhx/m3//93ykpKeGGG27YIYd+/foxf/782jHGjx9PSUkJJSUltTM9XnnlFUpKSujZsyff/e53t3lWXRMnTqRLly506dKFH/zgBwCsWLGCrl278q1vfYvu3bvzD//wD7z//vs79D3nnHMYNWoUvXv35sgjj+RXv/pV7b033niDgQMHcsQRR3DxxRfXxjt37sz69et3GOvjH/84l112GYWFhfTv35958+bx1a9+lc9+9rM8+OCDtXkdd9xxlJSU0L17d+bOnQvUHFt7/PHHU1JSQo8ePXjmmWfYvHkzZ599Nj169KCwsJCbbrqp3veXJEnKZRY4JCnHDR06lPvuu4+NGzdSUVFB7969a+9VVFTQq1evnY7RtWtXnn/+eSoqKvjhD3/I5ZdfDsDDDz/M5z73OcrLy7n66qspLS3ll7/8JeXl5eTl5TFmzBgeeeQRFi1axOjRo2v7Qc3MjXnz5nHJJZds86zvfve7HHbYYSxZsoSKigpOOumkBvPq27cvp512GjfeeCPl5eVcfvnl2+TQvn37bdr/9a9/5dhjj6W8vJyTTjqJSZMmAXDhhRdy1VVXUVZWxuGHH17vs55//nnuu+8+ysvLWbhwIVOmTGHevHkALFu2jH/7t39j8eLFfOYzn6ktymxv5cqVzJs3j6eeeopRo0bxwQcfAFBeXs706dNZunQpDz30EK+99tpH/efgr3/9KyeccAKLFi3iwAMP5JprrmHOnDk8+uijXHPNNQB85jOf4emnn6a8vJyZM2dy4YUXAjUziQYOHEh5eTmLFi2iZ8+elJWVsX79eiorK1m0aBHf+ta3PvL5+4qIuDsi3oqIyjqxv4+IORGxKCKeiIhP1bl3ZUQsjYjKiDi5TrxXRCyMiCURcWtERCbeLiKmZ9o/HxGd6/T510z7JRHxr83zxpIktW4uUZGkHFdUVMSKFSuYNm0aAwYM2K0x1q9fz9ChQ1mxYgVt2rShqqpqp30qKipYtmwZJ554IlBT0Dj44INr7w8ePLjefk8++SQzZ86svf67v/u73cq5Pm3btuXUU08FoFevXjz++OMAvPDCC8yePRuAIUOG8J3vfGeHvs899xynn346BxxwAABf//rXefbZZ/nGN77BEUccQVFRUe24q1atqvf5gwcPJiI44ogj6NKlC5WVNf+uPuGEE2pnjXTv3p3Vq1dz5JFHfuR7bC38FBYW0q5dO/Ly8igsLKx99gcffMC3v/1tFi1aRNu2bXn11VcB6NOnD+effz5VVVX80z/9E7169eKoo45i+fLlXHjhhZxyyim1P6NWYDJwG/CLOrFrgdkppR9HxHcy1xdFRC/gDKAI+AzwXER8MaW0CbgHODeltCAifg2cDvwKGAOsTSkNiYjTgVuB0yKiI3AN8CUgAeUR8XhK6c1meGdJklotZ3BI0j7gtNNOY9y4cdssT4GafxyXlZXttP/48eM59dRTWbx4MY888gibN2/eaZ+UEsXFxZSXl9fOFnjqqadq73fo0GGX3iGlVPt548aNu9R3q/3335/M/1wnLy+P6urq3Rpne+3atav9/FHjbn329tfZ9t+q7nu0adOmtn+bNm1q+/7oRz+iU6dOLF68mPnz59fGjz/+eP7f//t/FBQUMHLkSH7+85/zqU99ioULF9KvXz/uuusuzj///F15/ZyVUnoG+PN24YHAlMznezPXW+PTU0p/SymtBhYDR0dEJyAvpbSggT5bx/o10Dci8oATgd+klN5NKb0H/CYTkyRJTcgChyTtA8477zwmTJhAYWHhNvGxY8dy3XXX8frrrwNQXV3NHXfcsUP/qqoqOnbsCMCUKVN2uL9V+/bta5ddFBUVsXLlytoCyubNm3nllVd2muuJJ55Yu3QE4J133gHg05/+NEuXLiWltM0Mj7rPrO86G3369Kkds6HlJccddxwzZ85k06ZNbNy4kYceeojjjz9+l57z4IMPklJixYoVvPrqq/To0WOX+u+KqqoqDjnkECKCadOmsWXLFgBWrVrFIYccwsiRIzn//PN5+eWX2bBhAwBnnHEG119/PS+//HKT5ZUD8lNK6wAy37dOOyoA6k7NWZ2JNRTfpk9KqRrYkBnvo/pIkqQmYoFDkvYBBQUFXHTRRTvE+/bty0033cTgwYMpLi6mqKiIpUuX7tBu3LhxjBs3jtLSUjZt2tTgc84++2zOPfdcSkpKqK6u5oEHHmDUqFEUFxdTXFxcu9HlR7n++utZuXIlXbt2pbi4mCeffBKA73//+5x88skcd9xxHHLIIbXthwwZwnXXXUdJSQl/+MMftskhm6U0ALfeeivXX389vXr14tVXX91h7w6o+VkNGTKE4uJiSkpKGDFixDb7mWSjoKCAY445hq9+9av89Kc/rfc5jWX06NH87Gc/o2fPnlRWVtbOmHnqqacoKiriS1/6EtOnT+fiiy9m1apVtRuSjhgxgu9///tNlpd2TURcEBHzI2L+unXrWjodSZJyWtSdEtxalZaWpq078Ct3/LFix5MHPsoRRQc1USZqrZYuXUrXrl1bOg1lYesxugD33XcfkydP5je/+U2jPuOcc85h0KBBDe49kgvq+zMdEQtSSqUtlNIey2z8+WhKqUfm+jWgd0ppXUTkA/NSSp+LiGuAqpTSjZl2jwE/AF6nZs+O7pn4N4BTUkrnR8TTwOUppZcjog3wFnAIMCzzjH/L9PnvzHManh6Fv480t6kvrmz2Zw7r3anZnylJuW5XfhdxBockaZ/38ssvU1xcTNeuXfnxj3/MLbfc0tIpqeXMAkZkPo8AZteJD4mI/SOiAOgBvJRSWglUR0TPTLvh2/XZOtbXqClibAaeBE6JiE9ExIHAqZmYJElqQp6iIkna5x1//PH87//+b5M+Y/LkyU06vnZdREwD+gEHRcRqYELma3pEnAesBc4ESCnNj4iHgAqgGhiVOUEF4Fzg7ohoCzwNPJiJ3wZMyRxD+z41MzdIKb0REROBFzPtrk8p/alJX1aSJFngkCRJ+6aU0lkN3OrfQPuJwMR64vOBknriG4FvNDDW3cDdWScrSZL2mAUOSdoDKaUdjgaVcpF7cklNr6F9P9ybQ5Iah3twSNJuOuCAA9iwYYP/MFTOSymxYcMGDjjggJZORZIkabc5g0OSdlNBQQGrV6/Gox21LzjggAMoKCho6TQkqUk4e0ZqHSxwSNJu2n///TniiCNaOg1JkiRJuERFkiRJkiTtAyxwSJIkSZKknGeBQ5IkSZIk5TwLHJIkSZIkKedZ4JAkSZIkSTnPAockSZIkScp5FjgkSZIkSVLOs8AhSZIkSZJy3n4tnYDUXP5Ysb7e+BFFBzVzJpIkSZKkxuYMDkmSJEmSlPMscEiSJEmSpJxngUOSJEmSJOU8CxySJEmSJCnnWeCQJEmSJEk5zwKHJEmSJEnKeRY4JEmSJElSzrPAIUmSJEmSRHJwEgAAIABJREFUcp4FDkmSJEmSlPMscEiSJEmSpJxngUOSJEmSJOU8CxySJEmSJCnnWeCQJEmSJEk5zwKHJEmSJEnKeRY4JEmSJElSzrPAIUmSJEmScl6zFjgi4u6IeCsiKuvEfhwRSzNfj0XEQZl454ioiojyzNcddfr0ioiFEbEkIm6NiMjE20XE9IiojIjnI6Jzc76fJEmSJElqGc09g2MycMp2sUeBwpRSV6AS+G6de39IKZVkvkbVid8DjEwpdQMOB07PxMcAa1NKPYAbgVub4B0kSZIkSdJeplkLHCmlZ4A/bxd7OqW0OXP5HHDYR40REZ2AvJTSgkzoXmBg5vNAYErm86+BvhGR1xi5S5IkSZKkvdfetgfHBcDDda47R8T/RsQLEXFCJlYArKrTZnUmts29lFI1sAE4uGlTliRJkiRJLW2/lk5gq4gYD2ymZkYGwJ+AgpTS2xHRE3g0Iro34vMuoKagQqdOnRprWEmSJGmXTH1xZb3xYb39HVWSdsVeMYMjIv4V+CdgeEopAaSUNqWU3s58LqNmf46u1MzY+Gyd7gWZGHXvRUQb4NPAuvqemVK6M6VUmlIqzc/Pb/yXkiRJkiRJzabFCxwRcQpwOfBPKaUP6sQ/nSlSkDkNpQewPKW0EqjOzOoAGA7MznyeBYzIfP4aMK/O/h6SJEmSJGkf1axLVCJiGtAPOCgiVgMTgCuBdsCczGmv8zInpvwjcG1EVAMBXJxSeisz1LnA3RHRFngaeDATvw2YkjmG9n1gWLO8mCRJkiRJalHNWuBIKZ1VT/h/Gmg7A5jRwL35QEk98Y3AN/YkR0mSJEmSlHtafImKJEmSJEnSnrLAIUmSJEmScp4FDkmSJEmSlPMscEiSJEmSpJxngUOSJEmSJOU8CxySJEmSJCnnWeCQJEmSJEk5b7+WTkCSJEmSGjL1xZU7xIb17tQCmUja2zmDQ5IkSZIk5TwLHJIkSZIkKedZ4JAkSZIkSTnPAockSZIkScp5FjgkSZIkSVLOs8AhSZIkSZJyngUOSZIkSZKU8yxwSJIkSZKknGeBQ5IktToRcW1ELIuIVyPiwYjoEBF/HxFzImJRRDwREZ+q0/7KiFgaEZURcXKdeK+IWBgRSyLi1oiITLxdREzPtH8+Ijo3/1tKktS6WOCQJEmtSkR8HvgXoCil9EVgC3AWcC0wO6VUCMzOXBMRvYAzgCLgFGBSRLTLDHcPMDKl1A04HDg9Ex8DrE0p9QBuBG5tjneTJKk126+lE5AkSWpmfwb+BrSPiL8BHwNWAlcBvTNt7gXmARcBA4HpKaW/AasjYjFwdES8DuSllBbU6TMQ+FXm++WZ+K+Bn0VEXkppS5O/nfYZU19cWW98WO9OzZyJJOUGZ3BIkqRWJaX0Z+AmaooafwLeSSk9AeSnlNZl2qwDDs50KQBW1RlidSbWUHybPimlamBDnfFqRcQFETE/IuavW7eucV5QkqRWygKHJElqVSLic8B3gCOAQ4EOETGiJXJJKd2ZUipNKZXm5+e3RAqSJO0zdrvAERH5EdE7Ijo0ZkKSJElN7Gjg+ZTSusyyk18BxwHrIiIfan7PAd7KtF8NfLZO/4JMrKH4Nn0iog3wacApGpIkNaGsChwRMTEirqtzfQrwOvA8sCIiipsoP0mSpMb2B6BPRHwsc+rJCZnYLGDrTI4R1Gw0SiY+JCL2j4gCoAfwUkppJVAdET0z7YZv12frWF8D5qWUNjflS0mS1NplO4NjGPD7Otc3Ar8FjgHKgR82cl6SJElNIqX0EjADqABeBdoD/w1MAAZGxCJqNgm9JtN+PvBQpv3jwKiU0qbMcOcCd0fEEmpmbTyYid8GHBoRldRsNnpRM7yaJEmtWranqBwGvAYQEZ2A7sA5KaUFEXELMLWJ8pMkSWp0KaUJ1BQ06voA6N9A+4nAxHri84GSeuIbgW/seaaSJClb2c7g+AD4u8znfwDernMk2rtAu3p7SZIkSZIkNYNsZ3A8A1xRs0yVccBjde51oWY/DkmSJEmSpBaR7QyOC4G2wK+BjcCVde4NA55r5LwkSZIkSZKyltUMjpTS69RsKFqfrwFVjZaRJDWhJ5esrTfev9tnmjkTSZLU0qa+uLLe+LDenZo5E0mNIdtjYp+OiC4N3D6Emh3FJUmSJEmSWkS2S1T6AZ9o4N6B1Gw8KkmSJEmS1CKyLXAApO0DEZEHHA/8udEykiRJkiRJ2kUN7sEREROAazKXCZiXOUWlPv/VyHlJkiRJkiRl7aM2GZ0FrAcCuBX4EbBiuzYfAq+klJ5tkuwkSZIkSZKy0GCBI6X0MvAyQES8BzyWUlrfXIlJkiRJkiRlK9tjYn/e1IlIkiRJkiTtrqwKHBHRFrgC+BrQsb5+KaWDGzc1SZIkSZKk7GRV4AAmASOAh4DHgC1NlpEkSZKkBk19cWW98WG9OzVzJpK0d8m2wHEGMDal9N9NmYwkSZIkSdLuaJNlu43AoqZMRJIkSZIkaXdlW+D4GXBWUyYiSZIkSZK0u7JdorIWGB4RvwGeBD7Y7n5KKd3eqJlJkiRJkiRlKdsCxy2Z752Ak+q5nwALHJIkSZIkqUVkVeBIKWW7lEWSJEnaazR04ogkad9j4UKSJEmSJOW8rAscEdE5Im6JiBcjYnlEdM/EL4yIY5suRUmSJEmSpI+WVYEjIo4GKoCTgTLgCKBd5vbBwOVZjnN3RLwVEZV1Yn8fEXMiYlFEPBERn6pz78qIWBoRlRFxcp14r4hYGBFLIuLWiIhMvF1ETM+0fz4iOmeTlyRJkiRJym3ZzuC4GZgNdAMuBKLOvReA3lmOMxk4ZbvYtcDslFJh5hnXQk0RAzgDKMr0mRQRW4sq9wAjU0rdgMOB0zPxMcDalFIP4Ebg1izzkiRJkiRJOSzbAkdP4PaUUqLmxJS63gY+mc0gKaVngD9vFx4ITMl8vjdzvTU+PaX0t5TSamAxcHREdALyUkoLGuizdaxfA30jIi+b3CRJkiRJUu7KtsDxDnBQA/eOAN7cgxzyU0rrADLfD87EC4BVddqtzsQaim/TJ6VUDWyoM54kSZIkSdpHZVvgeBi4LiIK6sRSRBwIjAN+1eiZNbGIuCAi5kfE/HXr1rV0OpIkSZIkaQ9kW+C4HNgILAOezMR+ArwGbAGu2YMc1kVEPkDm+1uZ+Grgs3XaFWRiDcW36RMRbYBPA/VWL1JKd6aUSlNKpfn5+XuQviRJkiRJamlZFThSSn8B+lCzieefqClyvAFcBRybUnpvD3KYBYzIfB5BzUajW+NDImL/zMyRHsBLKaWVQHVE9My0G75dn61jfQ2Yl1LavAe5SZIkSZKkHLBftg1TSh8C/5P52i0RMQ3oBxwUEauBCZmv6RFxHrAWODPzvPkR8RA1x9NWA6NSSpsyQ50L3B0RbYGngQcz8duAKZljaN8Hhu1urpIkSVIumfriynrjw3p3auZMJKllZFXgiIhngGnAjK0bgu6OlNJZDdzq30D7icDEeuLzgZJ64huBb+xufpIkSZIkKTdluwfHWuAmYE1EzImI8yLiU02YlyRJkiRJUtay3YPjG9Qct/qv1Cz9+G/gTxHxaEScnTlNRZIkSZIkqUVkO4ODlNJfU0rTUkqnU1PsuCBz62fAm02RnCRJkiRJUjayLnDUlTk15Q/AH4F3gfaNmZQkSZIkSdKu2KUCR0QcHRE/ioiVwDPAPwA/AY5qiuQkSZIkSZKyke0pKjdQczrJ4cAy4B5gekppSRPmJkmSJEmSlJWsChzUFDfuB+5LKZU3YT6SJEmSJEm7LKsCR0rpyKZORJIkSZIkaXdlvQdHRHwiIsZGxPSIeDIijsrEz4yIbk2XoiRJkiRJ0kfLdg+OLwBPU3NaykvAPwIHZm73Br4ODG2KBCVJkiRJknYm2xkctwKvUrPJ6D8BUefeM8BxjZyXJEmSJElS1rLdZPQrwNdSSu9HRN5299YBBzduWpIkSZIkSdnLdgbHRuCABu51BDY0TjqSJEmSJEm7LtsZHHOAqyLit9QUOwBSZjbHGGBWUyQnSZIkac9MfXFlvfFhvTs1cyaS1LSyLXD8O/A74A/Ab4AEXAH0ADoAZzVJdpIkSZIkSVnIaolKSmkVUAz8DPgCNYWOw4GZQK+U0ptNlqEkSZIkSdJOZDuDg5TSX4CrM1+SJEmSJEl7jWw3GZUkSZIkSdprWeCQJEmSJEk5L+slKpKUS55csralU5AkSZLUjJzBIUmSJEmScp4FDkmSJEmSlPOyLnBExL9ExCebMhlJkiRJkqTdsSszOO4BOgFEjWsi4pCmSUuSJEmSJCl7DW4yGhGzgXLgfzNfAaTM7TbABOBR4M0mzlGSJKlRZWal/gz4ItAWOA94BZgOHAL8CRiSUvpLpv2VwL8AW4BLU0qPZ+K9gLuAdsCTwMUppRQR7YBfAN2Bd4FhKaUVzfaCUhamvriy3viw3p2aORNJahwfNYPjN0BH4EpqChwJuC0ivgecwrYFD0mSpFzyM2BmSqkI6AEsBq4FZqeUCoHZmeutRYwzgCJqfgealClgQM0M15EppW7A4cDpmfgYYG1KqQdwI3Brs7yVJEmtWIMFjpTST1JK56SUioEDqSlolFHzfzpupaa4MSUiboqIU5olW0mSpD0UEZ8GvpRS+iVASmlzSukdYCAwJdPs3sw1me/TU0p/SymtpqYYcnREdALyUkoLGuizdaxfA30jIq8p30uSpNauwQJHRFwUEV+JiANTSpsy4XtSSmdRU+QIYBrwceC2pk9VkiSpURwFrIuIByJicURMiYgDgfyU0jqAzPeDM+0LgFV1+q/OxBqKb9MnpVQNbKgzXq2IuCAi5kfE/HXr1jXaC0qS1Bp91BKVQcAM4O2IeI2aGRtDI6I3NWtVoWYa56iU0uebOE9JkqTG0gb4MnBTSqk78Gfg6pZIJKV0Z0qpNKVUmp+f3xIpSJK0z2hwk9GU0kkAmZNSSoBZQH9gNNCemoLH6Ii4D3iuziwPSco5Ty5ZW2+8f7fPNHMmkprBKmBNSunFzPUMagoc6yIiP6W0LiLygbcy91cDn63TvyATayhet8+bEdEG+DTgFA1JkprQTo+JTSm9mVL6TeZyZErpU0ApNUtUPgtMBv7SZBlKkiQ1opTSKmB9RHwxEzqBmhNUZgEjMrER1Gw0SiY+JCL2j4gCajYlfSmltBKojoiemXbDt+uzdayvAfNSSpub6p0kSdJHzODYiaWZ71ellMoiomtjJSRJktQMzgd+GREfA1ZSU5wAmB4R5wFrgTMBUkrzI+IhoAKoBkbVmbl6LnB3RLQFngYezMRvo2Yz9krgfWBYM7yTJEmtWtYFjpRS3dkeCXgd2JS5t7TeTpIkSXuhlFI5NTNSt9e/gfYTgYn1xOdTs5R3+/hG4Bt7mKYkSdoFuzWDI7Mb+BGNnIskSZIkSdJu2ekeHJIkSZIkSXu73d2DQ5IkSdI+aOqLK+uND+vdqZkzkaRd4wwOSZIkSZKU8yxwSJIkSZKknGeBQ5IkSZIk5TwLHJIkSZIkKedZ4JAkSZIkSTnPU1QkSZKknShc9tN644uO+nYzZyJJaogzOCRJkiRJUs5zBof2en+sWN/SKUiSJEmS9nIWOCRJkiTt1NQXV9YbH9a7UzNnIkn1c4mKJEmSJEnKeRY4JEmSJElSztsrChwR8cWIKK/z9W5EjI2I70XEmjrxAXX6XBkRSyOiMiJOrhPvFRELI2JJRNwaEdEybyVJkiRJkprLXlHgSCm9mlIqSSmVAL2AD4CHMrdv3novpTQLaooYwBlAEXAKMCki2mXa3wOMTCl1Aw4HTm/Od5EkSZIkSc1vb9xk9ATgDyml1z9i8sVAYHpK6W/A6ohYDBwdEa8DeSmlBZl292ba/qqpk5YkSVLuK1z205ZOQXugoY1QJbUOe2OBYygwrc71v0XESGABcFFKaQNQADxdp83qTGwLsKqe+A4i4gLgAoBOndz5WZIkSbuuoYLIoqO+3cyZ5D6LE5L21F5V4IiItsBpwJWZ0H8D1wMJ+B5wKzC8MZ6VUroTuBOgtLQ0NcaYkiRJUmvj8bGS9hZ7VYEDOBUoSymtBUgprdt6IyLuAOZmLlcDn63TryATayguSZIkqRk1ZeHD2R6S6rNXbDJax1nUWZ4SEQfXuXcGsCTzeRYwJCL2j4gCoAfwUkppJVAdET0z7YYDs5s+bUmSJEmS1JL2mhkcEdEBOBH4Vp3wjyOiCGgLrATOB0gpzY+Ih4AKoBoYlVLalOlzLnB3ZrnL08CDzfQKkiRJknYiF2ZfuOxGyk17TYEjpfRX4NPbxUZ8RPuJwMR64vOBkkZPUJIkSZIk7bX2tiUqkiRJkiRJu8wChyRJkiRJynkWOCRJkiRJUs6zwCFJkiRJknKeBQ5JkiRJkpTzLHBIkiRJkqScZ4FDkiRJkiTlvP1aOgFJkiRJygVTX1xZb3xY707NnImk+jiDQ5IkSZIk5TxncEiSJEmNrHDZT3eILTrq2y2QiSS1Hs7gkCRJkiRJOc8ChyRJkiRJynkuUZEkSZK0T6tvyRC4bEja1ziDQ5IkSZIk5TwLHJIkSZIkKedZ4JAkSZIkSTnPAockSZIkScp5FjgkSZIkSVLO8xQV7XP+WDa33vgRPfs1ax6SJEmSpOZjgUOt3h8r1u8QO6LooBbIRJIkSblo6osr640P692pmTORWjeXqEiSJEmSpJxngUOSJEmSJOU8CxySJEmSJCnnuQeHJEmSWp3CZT9t6RQkSY3MGRySJEmSJCnnOYNDkiRJOa+hUywkSa2HBQ5JkiSpGTS0LGbRUd9u5kwkad/kEhVJkiRJkpTzLHBIkiRJkqScZ4FDkiRJkiTlPPfgkCRJrU5E5AHzgTUppUER8ffAdOAQ4E/AkJTSXzJtrwT+BdgCXJpSejwT7wXcBbQDngQuTimliGgH/ALoDrwLDEsprWjO95O0d2ho89thvTs1cyZS6+AMDkmS1BpdDCytc30tMDulVAjMzlxvLWKcARQBpwCTMgUMgHuAkSmlbsDhwOmZ+BhgbUqpB3AjcGsTv4skScIChyRJamUiogAYSM3si60GAlMyn+/NXG+NT08p/S2ltBpYDBwdEZ2AvJTSggb6bB3r10DfzIwRSZLUhCxwSJKk1uYW4DKguk4sP6W0DiDz/eBMvABYVafd6kysofg2fVJK1cCGOuNJkqQm4h4ckiSp1YiIQcBbKaUFEdFvL8jnAuACgE6dXJMv1adw2U93iC066tstkImkvZ0zOCRJUmtyLHBaRKwA7gO+GhH3AusiIh8g8/2tTPvVwGfr9C/IxBqKb9MnItoAnwbW1ZdMSunOlFJpSqk0Pz9/z99OkqRWzAKHJElqNVJKV6aUClJKnYGhwNMppRHALGBEptkIajYaJRMfEhH7Z/bu6AG8lFJaCVRHRM9Mu+Hb9dk61teAeSmlzU35XpIkySUqkiRJABOA6RFxHrAWOBMgpTQ/Ih4CKqjZs2NUSmlTps+5wN0R0RZ4GngwE78NmBIRlcD7wLDmew1JklovCxySJKlVSinNBeZmPm8A+jfQbiIwsZ74fKCknvhG4BuNmKokScqCBQ5JkiRpJ27c8nK98X/P+3IzZyJJaogFDuWsP5bNbekUJEmS9lh9p4SAJ4VI0q5yk1FJkiRJkpTznMEhSZIkSc1o6osr640P692pmTOR9i3O4JAkSZIkSTnPGRySJElSRkObiUqS9n4WOCRJkiS1Sm7wKu1b9poCR0SsAN4DtgCbU0qlEfH3wHTgEOBPwJCU0l8y7a8E/iXT/tKU0uOZeC/gLqAd8CRwcUopNfPrSJIkqRXw+FhJ2nvsbXtw/GNKqSSlVJq5vhaYnVIqBGZnrrcWMc4AioBTgEkR0S7T5x5gZEqpG3A48P/bu/NwScr60OPfHzMDhMWFAcbIzAASiUEkhEWCKygqCTHGiAKD+IREid5oNE80LvEak8hNvGBM0JsQjJpEZRFEcGGRRYJERAbUAQZEySAMMgvIvs7yu39UHaanT9WZ7jl9uru6v5/n6ed0v1Xd9dZbVV3v+fW7vL6fOyBJkiRJkvpv2AIc7Y4AvlA+/2L5eiL9rMxck5nLgZuAF0bEQmBWZl5X8R5JkiRJkjSihqaLCpDAJRExGzgtMz8F7JSZqwEyc3VE7FyuOx+4vOW9y8u0dcCdFemTRMQJwAkACxc6HZMkSZKGi+NDSFJ3hinAcXBmriiDGBdFxC0zubHMPA04DeCAAw5wjA5JkiRJkhpsaLqoZOaK8u8q4BzgQGB1ROwEUP5dVa6+HFjQ8vb5ZVpduiRJkiRJGmFDEeCIiG0jYpuJ5xQDhy4FLgDeXK72ZoqBRinTj4qIORExH9gb+H5m3gGsj4j9yvWObXmPJEmSJEkaUcPSRWUecF5EJLANxdSw5wPfAc6KiD8EVgJvAsjMxRHxVWAJsB54e2Y+UX7W8cDnImJLinE6vtLXPZEkSZIkSX03FAGOzPwfiilf290LHFbznhOBEyvSFwP79jSDkiRJkiRpqA1FgEOSJEmSZspJ666tTH/frAP7nBNJM8kAhyRJkiQNgdOvuaMyfdFBC/ucE6mZDHBobCy7/orK9N33O6Sv+VBvXbp05aCzIElSX73gJ/9cmX7Dc/9Xn3MiScPFAIckSZLUY1VdIuwOIUkzayimiZUkSZIkSZoOAxySJEmSJKnxDHBIkiRJkqTGM8AhSZIkSZIaz0FGJUmSNLLqZhwZRc6uImnc2YJDkiRJkiQ1ngEOSZIkSZLUeHZRkaQpXLp0ZWX6YXvN63NOJEmSJE3FAIckSZLGzknrrh10FiRJPWYXFUmSJEmS1Hi24JAkSZJGmLOrSBoXBjgkSZIkaYidfs0dlemLDlrY55xIw80AhyRJkqShVTVeyuEDyIek4WeAQ5IkSeqDuoFN3zfrwD7nRJJGk4OMSpIkSZKkxjPAIUmSJEmSGs8uKpIkSdIYcnYVSaPGAIeksbLLbWdWpt+1x9F9zokkSZKkXrKLiiRJkiRJajwDHJIkSZIkqfHsoiJJkiTpKY7NIampbMEhSZIkSZIazxYckiRJ0gCdtO7ayvT3zTqwzzmRpGazBYckSZIkSWo8W3BIkiRJ2iTH5pA07AxwaGgsW3LPoLMgSZKkBqsLwlzU53xIGgwDHJIkSZI2W69adsxkcOLIs++tXnB0Dz58gE6/5o7K9EUHLexzTqThYIBDkiRJUs/NZJeWus/uVu0Ar3bHkRrJAIckSZKkvulVcEKS2jmLiiRJkiRJajwDHJIkSZIkqfHsoiJJkiQNodrxIWYd2OecSFIzGOCQNJJ2ue3MQWdBkiRJUh8Z4JAkSZKkDszkzDCSps8xOCRJ0liJiAURcWVE3BgRt0bE+8v0HSLikoi4ISK+FRHPbHnPByPi5vI9r2lJ3z8ifhARSyPilIiIMn2riDirXP+7EbFbv/dTkqRxY4BDkiSNmzXAOzNzb2B/4K0RsS/w18CFmfkC4MLyNRGxP/AGYB/gcOBfI2Kr8rM+D7w1M/cCdgVeX6a/E1hZbuMk4JS+7JkkSWPMLiqSJGmsZOYKYEX5/KGIWALsAhwBHFSu9kXge8CflulnZeYaYHlE3AS8MCJ+BszKzOta3nMEcG759/1l+vnAZyJiVmaum/Ed1EbqBupsMgcflaRqtuCQJEljq+w6ciBwFbBTZq4GKP/uXK42H7iz5W3Ly7S69I3ek5nrgXtbPk+SJM0AW3BIkqSxFBHbAecA78nMB8rhM/qdhxOAEwAWLlzY9+030enX3DHoLEiTOPioNBwMcGjoLbv+ikFnQWOgblrZu/Y4us85kdQPETEH+ApwRmaeWyavjoidMnN1ROwErCrTlwMLWt4+v0yrS299z4qI2AKYC6xuz0dmngacBnDAAQdkL/ZNkqRxZYBDkiSNlXKmk88CN2fmJ1oWXQC8Gfhk+ffClvRTI+IfgXnA3sD3M/OJiFgfEftl5vXAsRTjcLR+1rXA64DvZebaGd41SQLqWzotOsiWYhptBjgkSdK4eTFwHHBDRPywTPsQ8FfAWRHxh8BK4E0Ambk4Ir4KLAHWA2/PzCfK9x0PfC4itgQup2gVAvBp4AsRcSPwMLBo5ndLkqTxNhQBjohYAHwJ2AHYEvhsZn48Ij4KvI0NTTo/lJkXlO/5IPAWYB3w55l5cZm+P/BvwFbApcC7M9Mmn5IkCYDMvAqoG3DjsJr3nAicWJG+GNi3Iv1x4I3TyKbUNWdXkTTuhiLAwYb56JdExPbA9RFxcbnsk5l5cuvKbfPRzwOuiohfLX9N+TxwfGZeFxHnU8xHfy6SJEkaWXWDPF7U53yo9448+97JiQ0ZIsvBR6X+GoppYjNzRWYuKZ8/RNEEdJcp3vLUfPSZuRyYmI9+IdXz0UuSJEmSpBE2FAGOVm3z0QP8SUTcEhFfioi5ZdrmzEffvp0TImJxRCxevXrSoOaSJEmSJKlBhqWLClA5H/3/A/4WSOCjwCkUI5RPm9OyaSrLltxTmb77Pjv2OSeSJEnT49gcksbF0AQ4quajz8zVLctPBa4oX27OfPQaE7feWX3I91xQ2ZhHkiRJkjQChqKLSt189BGxc8tqbwCWls8vAI6KiDkRMZ8N89HfAayPiP3K9Y5lwxz2kiRJkiRpRA1LC466+egXRcQ+FFPH3gH8EWz2fPSSJEmSNHDOriLNjKEIcEwxH/0FU7ynq/noJUmSJG3g2BySRs1QBDikQVp2/RWT0nbf75C+50NTu3TpykFnQZIkSdIQM8AhSZIkSWPg9GvumJS26KCFA8iJNDMMcEiSJEl6il1XJDWVAQ5JkiRJGgIOPipNz1BMEytJkiRJkjQdtuBQY9165/JBZ0GSJGls2HVF0rAzwCFJkiRpszU58HHk2fdWLzi6v/mQ1BsGOCRJkiT1XLeBj7r1j+xZjiSNOgMckiRJkvqmLpBS/VZ/AAAZzUlEQVQhSdNlgEOSNsOlS1dWph+217w+50SSJEkSGOCQJEmS1DDdtgJpejcXp4+VOmOAQ2Nj7uptK9Pv3emRPudEkiRJktRrBjg0Nq5+/MeV6Xsyv885US/tctuZg86CJGkIOK6DtHlOv+aOyvRFBy3sc06k6dti0BmQJEmSJEmaLltwqO+WLbln0FmQJEmSanU7xa2k4WALDkmSJEmS1HgGOCRJkiRJUuPZRUWSplA3iOldexzd55xIkqRBG7auK04fK23MAIeksfLzz5xRmf7stx3T55xIkiRJ6iW7qEiSJEmSpMazBYckSZIkTcOwdV2RxpUBDg2NZddfMegsSJIkSQJOv+aOyvRFBy3sc06kztlFRZIkSZIkNZ4tOCSNpLrBRCVJzVY3a8RFfc6H1IlBdV1xdhWNKwMcUheWLbmnMn33fXbsc04kSZIkSa0McEiSJElSHzkoqTQzHINDkiRJkiQ1ni04JA2VS5euHMh268bsePbbjulzTiRJkoaXs6tomBng0NC79c7lg86CJEnqs7p/ol7Q53xI/TTTXVeqBh914FGNEgMcmjF1A3JKkiRJktRrBjikCsuuv6Iyfff9DulrPiRJkiRJnTHAobFX1QVmzwXzB5ATjYK6MUQO22ten3MiSZJGhbOuSJ0xwCGpEXa57cxBZ0GSJEnSEDPAIUmSpMao+yVb0uapGngUuh981NlVNAwMcEiSJElSA9l1RdqYAQ5Nm7Ol1JfB7vvs2OecNEfdWBXd+vlnzujJ50iSJElqNgMc6ru6GUqkJqkbE+SuPY7uc04kSZJ6z64raiIDHJI0hboWIs9+2zF9zokkSaPtyLPvHXQWRoZdVzSuthh0BiRJkiRJkqbLFhwaGrfeuXzQWZAkSZI0BbuuaJgZ4FDHHEy0fvyQ3fc7pHp9Bx/t2WCiTVdXDoftNa/POZEkabB60RXF7iybp6rrit1WNEoMcEgaKnWDd0qSxkvdr8QX9Tkf2nwGIST1mwEOTWJLjfruMnsumN/nnDSLrTUkSZKapVcDktp1RcPAAMcYm+lAhtPB1rPrSve+/Oh1lekv6XM+NqXb6WPtuiJJ0vCpa31yzhvn9jknmmDgQ50wwKFp6zaQ4WCi9ZoS+BhES42XfOnWvm9zKk4fK0m9UfdPy0U1vypLgzROgY9ha9khdcIAxxiwy8nM63bw0aaYyUCGY21MrarsbdUhSRpGjrUxXoYt8GHLDrUayQBHRBwOnAzMAv4jM/9+wFnquUEELexy0v3YHL0KfMx0yw4DGTOv264rVezOIjXLONRHJGmCgQ8Ng5ELcETEVsCpwEuBFcDVEfGtzLx+sDnbPDMZyJjpgIVdUWbeed/4aVfrb/ec7WcoJ4VeBDPqun40xSC6rhj4kIbPqNVHJE1tnLqudKsu8FGnLiBSF/ioUxcQqQt81DEg0iwjF+AADgJuysw7ASLiLOAIoK8VilEcwHPu6m0r069+/Md9zsngrF23vjJ96e3dfVEu/8UFvcgOT9vzRV2t//D/PFSZPnfFlZXpO86rXr8bTQ9Y9ErdIKlvum36n93tAKa9YgBFmtJQ1EeawOlgJbXqNiBS530GRMbSKAY45gN3trxeDhzS70xccM5nK9O3f8YvV6Y/dP/dlem5xZzK9Fi/ZvMy1oE1ua4yfU7M6upzZjrv+eST1Z+/5ZZdrd/NZ0TN+nVlNntNdfqDjz9Smb52TnUZ779yq8r0H62qDh48Mru69cy2a6u70sz9xTaV6dfe14MbzFa7VSY/ja0r0x/k8a7Wb4pfP6c6/cf8oAefXv0ZNx/y7B58Nrxkq1+pTP/Od7v7nHuf9bLK9LoAW6/Wr1P3Od18dl2rqD3Wdvd9OWwDCasnhqI+0m3FfCbVBTJ69c+MZp5jbXTPlh2D0/V3yy3H92S7F93Sk4+p1G13n271auDXQQZ5RjHA0ZGIOAE4oXz5cET0uhnCjoCje27MMpnMMpnMMqnWfbnUBFVGiOfKZDNRJrv2+PPUwvpI10Zpfxq3L1+YenHj9mcTZnZ/vjljn1zH4zPcOtqfL3D5DGfj4z35lGN7f3w6rouMYoBjObCg5fX8Mm0jmXkacNpMZSIiFmfmATP1+U1kmUxmmUxmmVSzXCazTCazTIaK9ZEZMEr7M0r7Au7PsHN/hpv70ztbDGKjM+z7wN4RMT8i5gBHARcOOE+SJGm8WB+RJKnPRq4FR2Y+HhHvAC6mCOB8MTMXDzhbkiRpjFgfkSSp/0YuwAGQmRcAvZmmYvPNWHPTBrNMJrNMJrNMqlkuk1kmk1kmQ8T6yIwYpf0ZpX0B92fYuT/Dzf3pkcjMQW1bkiRJkiSpJ0ZxDA5JkiRJkjRmDHB0KSI+FxGrIuLGmuXPiojLImJpRNwaEW9vWXZ4RNwYETdHxAf6l+uZNc0yuT0iboiIH0bEyPRN7qBM5kbEhWWZfD8i9m5ZNq7nyVRlMqrnyYKIuLI83rdGxPsr1omIOKUslx9ExH4ty0buXOlBmYzcudJhmTwvIq6OiCci4r1ty0buPFFH36mN+e7oYF+OK6/rGyPiuog4oGXZ0F3zHezPIRHxQJnnH0bER1qWDdWxgY72530t+3JjRKyLiB3KZcN4fEbq3tvh/jTmGupwfxpxDXW4L425fiJi64hYXObnJxHxjxERbesM/trJTB9dPICXAfsBN9Ys/xjw8fL5TsD9wC8BWwG3U0wZNwdYDOw36P0ZZJmUr28Hdhz0PgygTD4F/FX5/HnA1eXzcT5PKstkxM+TZwH7lM+3B34C7Nu2zhuA84Eoy+9Ho3yuTKdMRvVc6bBMdgYOBE4E3tuSPpLniY+OvlMb893Rwb4cBDy9fP5bwA9blg3dNd/B/hwCfKMifeiOTSf707bua4HLh/z4jNS9t8P9acw11OH+NOIa6mRf2tYf6uunvB62LZ/PAa4BXtG2zsCvHVtwdCkzrwR+McUqy4Hty2jWdsA9wBMUXyw3ZeadmbkGOAs4Yqbz2w/TKJOR1UGZPA+4vFz3FmDniNiF8T5P6spkZGXmisxcUj5/CFgCtO/zERSzL2RmXg/MjogFjOi5Ms0yGUmdlElmrsrMa4E1bW8fyfNEHX2nNua7Y1P7kpnXZOYD5curmPydMFQ6ODZ1hu7YQNf7cwxwxgxmZ9pG7d7b4T2iMddQh8enzlAdn83Yl6G+fsrr4ZHy5RxgFrCqbbWBXzsGOHrvM8BewM+BG4B3Z+Z6YD5wZ8t6y8u0cVBXJgAJXFI2v3rXoDI4ADcAvw8QES8EdgUWMt7nSV2ZwBicJxGxG8Uv8Fe1Lao7J0b+XNmMMoERP1emKJM6I3+eqNaofnf8MfC1ltdNveYPLptqXx4R+5ZpjT42EbENcDjwlZbkoT4+o3bv7fAe0ZhraBP706hraFPHpinXT0TMiogfUgQ2rsjM9q5rA792RnKa2AH7IEV07lBgD4qT8juDzdLAVZZJZj4IHJyZKyJiZ+CiiLglMy8ZZGb75K+Bf4mIpcDNFM20xn1Ko6nKZKTPk4jYDjgHeE/LLyxjbRplMrLniueJxl1EHAL8EfCSluQmXvPXAQsy89GIeA1wXkQ8Z9CZ6oHXAv+dma2tPYb2+Izad2on+9Oka2gT+9Ooa6jDc60R109mrgP2jYhnABdHxKGZ+e1B5qmdLTh676XA2WWznJ8CyyhaLyyn6HM0YX6ZNg7qyoTMXFH+XUVx4R84sFz2UWY+kJmLMnOvzHwDRf/5Wxnj82SKMhnp8yQi5lBE68/IzHMrVqk7J0b2XJlGmYzsudJBmdQZ2fNEmzRS3x0RsQ/wWeB1mXnvRHoTr/nMfCgzHy2fXww8SdFXv5HHpsXRtDWvH9bjM2r33k7uEU26hja1P026hrq4fzfm+gHIzPuBbwK/2bZo4NeOAY7euw14JUBEzKP4R/524PvA3hExvzzRjwIuHFQm+6yyTCJi27I5FhGxLUWzrKUDy2UfRcTTI2J2+fzNwA/KiO3Ynid1ZTLK50k5Ls1ngZsz8xM1q10AHFuuvx+wPjPvZETPlemUyaieKx2WSZ2RPE/UkZH57oiIhcC5wHGZeWtLeiOv+YjYqeX5/hTjk62igcdmQkQ8HXg5xeCCE2lDeXxG7d7byf406RrqcH8acQ11ev9uyvUTETtGxPbl818CXgW0d1EZ+LVjF5UuRcQZFCP37hgRy4G/ohhkhcw8Ffgb4IsRcTPFwCv/eyL6FhHvAC6mCCx9MTMHPt1PL2xumZRNyc6LiAS2oRhs5vyKTTROB2XyfODfI+Jx4KcUzQXJzMfH+DypLBNgHiN6ngAvBo4DboiiPyPAhyjHHinL5SvAoVF03XkSOL5cNqrnymaXCaN7rmyyTCLiWRTdup4GrI+I9wB7ZeaDI3qejL0OvlMb893Rwb58BJgL/HPx/wJrM/MAhvSa72B/jomIE8rVnwQWZeZaYO2wHRvoaH8AXg98q2UAQhjS48Po3Xs72Z8mXUOd7E9TrqFO9gWac/08G/jPMnCzNUWrlK9HxNtheK6dyBz3bv+SJEmSJKnp7KIiSZIkSZIazwCHJEmSJElqPAMckiRJkiSp8QxwSJIkSZKkxjPAIUmSJEmSGs8Ah0ZGRHw0IrLl8UBEXBQRvz7ovE1HRGxZ7tu+fd7uzuV2d+vhZ54cEbdvYp3W47g+Iu6LiGsj4sRyKswZFRG3l9v+cMWyl7TkbbeZzksnIuKDEXFxRfrLI+L8iFgVEWvKv9+MiKMjouPv/oj4ekTcMMXyT0fE/RGxVUS8NiJui4gtN3d/JKnprI/0fLvWRyYvsz4yebn1EQEGODR6HgAOLh/HAwuAyyLimQPN1fRsSTHnfF8rFMDO5XZ36/N2YcNxfBFwNHAuG+YR378P23+43G67Y8plQyEingG8HzixLf09wLeBdcC7gFcC7wQeBL4EHNrFZs4A9o6IvSq2Pws4Ejg3M5/IzK8DjwJv7X5vJGmkWB/pHesjk1kf2Xg71kf0FAMcGjVrM/N75eNc4M3AXOB3B5yvvoiIXxp0Hnqk9ThenJl/B+wD3A2cWd7IZtI3gL0iYu+JhJab59dmeNvdeCtwd2ZeOZEQEfsBJwN/k5m/n5lnZeaVmfnlzDwGeAlwTxfbOJ+iknBMxbJDgXkUlY4JnwH+LCKiy32RpFFifWQ0WB/pjPURDQ0DHBp1E03ZdmlNjIgdIuK0iFgZEY9HxHcj4qC2dWaVze1ujYgnyyZ1X2pb550R8ZOIeCIifhoRf9a2/KMRcU9E/EZEfK/c1i0R8eq29d4UEUvK7TwSEddHxERU+6Hy7+dbmyOWj4yIYyPiPyPifuDr5edlRLyzKi9tabtGxBllHp+MiKURcVzZ3HGi7L49sd0uy+8ZEXF6RDwcEXdHxF9OPjydy8z7gb8AfgV4VSfviYh9I+LbZZk+WR7Ld3fw1ruAq9j4V5NXANtRUaGIiA9ExA8i4rFyfy+JiH3a1nlFRFxTltdjEXFjRBzVsnyqc6DOccB5bWnvAlYBH6t6Q2ZenZk/asvbWyPipvI8/llE/EXL+o9QnFdHtX8WRfmsAi5vSTuf4hj95ibyLknjxPpIW17a0qyPVLM+smF96yPqiAEOjboF5d/VEwkRsRVwKfAy4E+B3waWA5dGxHNa3vuvwEeA/wAOA/4YaL2pvgc4BTgLeHW53skR8YG2PGwD/Fu57hFlXs6OiKeXn/NrFBHnb1LcKH8XOBN4Wvn+V5R/P8aG5q53t3z+SRRf6r9LzU2kSkTsDFwNvICiueArgU9TNAW9Gzi2XPVPWrbbTfmdWX7mO4C3lOtXNbPsxhXAWjq4WUXxC8c3KJqX/n6Zl5OAOR1u6ww2zu8xFDfWRyrW3QH4JMV58EaKZqOXthzjHSgqIjdQnAO/RXF+bVsu39Q5ULV/8yh+Rfpe26KXAZdn5tpOdjIi3gf8c7m9VwH/APxNa6WizNtzo6U5bkTMoSjXL2fmuon0zPwZsAJ4TSfbl6QxYX2khvWRTbI+soH1EW1aZvrwMRIP4KMUTd1ml48FFDeUR4B5Lev9EfAEsGtL2izgFuCU8vXzKCoPb6vZ1qxyW6e2pX+S4ga2dUueEnhxyzrPL9NeV74+Flg9xX5tV67/B23pu5XpZ1a8J4F3VpVPy+u/A+4HdqrZ7t7l5xzSlt5J+f1G+d7fa1lnG2AlcHsnx3GK5XcD/9LB+bBLmYfnd3ke3U7RpHInYA1wIEW/4/uA3wN+p/zc3aY4N7Yu139Lmfbi8j3b1rxnynOg5j2HlZ/53Lb0x4C/a0uLlutiNrBFmf40isrPB9vW/zBwLzC7fD2x/ye1rDNRDi+qyNslwFe72R8fPnz4GJUH1kdal1kfsT7SmmZ9xMeMP2zBoVEzl+ImsAa4A3g5cERmrmxZ5zCKKPNdETE7ImZTfOFeQfmrAEVfvnUUAyBVeV65rXPa0r9M8SX9gpa0RzPzv1te31L+/eXy74+AuRHx+Yh4VURs18mOtvhml+tPeAVwQWau3uSaG+uk/F5E8cvGBRNvysxHgW9tZl5bddqXciVl5SMi3lj+wtCxslwup/jV5PByuxdWZijikIi4MiIepdjvx4BnAHuWq/y4TDs9ipG92weZ25xzYGJ/flGV/bbXb2DDdbEG+L9l+sEUv9qcPXEsy+N5OcWvQL8KkJlPUgys9qaIp/qyHgX8jOJXt3b3tuRPksaR9ZHOWR+ZgvUR6yPqjgEOjZoHKCLcv0nRhHMdRXPEVjtSNJtb0/b4Y4pKAuXfh8qbYJWJG0L7zXji9Q4taY+1rpAbms/NLl/fSNG07nkUN6xfRMTZXdwA7+twvXZzKW663eqk/J4JPFzeiFp1M5jUJBGxNR3mO4smka+hKJ9/B1ZE0e/4hV1s8kzgTcAi4LzMfKIiT3sAF1H0TT6G4tw7sMzj1mVe7inzsh1FJfSeiPhWRDy3XD6dc6C9gvVzYH5b2mVlng5k4+bEO5Z/f8LGx3KiAjy3Zd0zgIXAweVxeB3Fr3XtlZeqPEnSuLE+0jnrI5tmfWQD6yOa0uxBZ0DqsbWZubh8fk1EPAx8KSJOz8xLy/RfUHxhvqfi/RM3jHuB7SNim5pKxcRNfKe29InXVVHsWpl5HnBeRDyNoj/kp4BTgdd38zkt1lE0TWy1bdvrzY1qd1J+9wPbRcSWbZWKHSve041DKb63qqL0k2TmDcDryv6ZLwY+DnwjInbJzDUdfMRXKY7DGyn6qlZ5LcUN9MjMfAye6m+7UX/VzPwO8MooRpY/FPgnil/YfqNc3u05sKL8O5eNK2pXAq+OiFkTldfMvA9YXOat9XhMnKevprpi+uOW59+mqCQdTfFr3/ZsPFp5qx1a8idJ48j6SMH6CNZHrI+on2zBoVF3BnATxfzpEy4Dfg34SWYubntMjNR9OcUNuWoqKiiadd5DEeVudSTF3N43THpHBzLzwcw8C/gKMDHP98QNoNPBqKCIik80R6RsxvfKtnUuA34rIuZSrW67nZTfdylu/L/dkodtKG5cmyWKOdY/DvyUYlCxjmXmmsy8gmLAqp3osGKTxUjpH6c4HnXb3JKiQrG+Je11QOUUeZn5WGZeQDHQ26S53GvOgSoTZf38tvRPUVQUPzTFeydcTfGL3rMqjuXizJwYMX/il74vU1SuFgE3Z9vo5y32BpZ0sH1JGhfWR7A+Yn2klvUR9YwtODTSMjMj4v9Q/Gry0jJq/Z/A24H/ioiTgWUU/RMPphhY6Z8y88cRcRrwqXJ076soosBvyMy3ZOa6iDgR+EQUU51dCrwUeDfw4cx8vNM8RsTbgP2BiykqKXtSVEy+Wu7DkxGxDDgyIm6iuNFv6sv6a8AfRMR15f69lck30U9SNJf9dkR8jKISshewXWZ+gqLP8GPAcRHxILCu/DWqk/K7PiIuAf617L+5EngvRXPDTsyOiImRybcvy+cdFAODHd7SrLZWFNOifYyiCeYyiorEX1D8CtBxND8zP7KJVS4D/p5i2rx/A/YAPkDxq9FEXo6guAl/jaLJ5gLgBOC/yuVTngM1+VoVET+k6F98bkv69RHxXuAfImJfilH1f07xi9mLgWdRDORFZt4fER8FTo1iKr7vUFSOfg14eWa2T8V2BsW0b69n40r6UyJi13IbvejfLEkjwfqI9RGsj1gfUX/kEIx06sNHLx7UjHZN8cvHrcCFLWlPp2iSdyfFTW41xQjnL21734eA/ynXWQl8oe2z30URwX+yXO/POszTU6OKU9wQLirzsJbiy/8UYJuW9Y+guBGuLd+7GxtGLf+dis9/OnA28CjFzfPDwF+35wXYleKGc1+5DzcBx7YsP55i4KZ1xddFV+X3TIo+o4+UZfcRitHAb+/gOGb5WE9xY14MnEgR2e/0fJhHcQP8WVlu91HcoJ+ziffdDpw8xfJJo5ZTVA7uAh6nGPDsoNbPoejLel55bNeW5fUflCPGd3IO1OTlz4FlNcsOoajArC6P0SqKQdaOBqJt3TcD11FUIB8ty/v9NZ+7rNz/X6lZ/qcU10RMlXcfPnz4GNUH1kdo2z/rI9ZHrI/46NsjyhNAktQwZTPZ2yl+ybtswNkBICKWAKdl5qcHnRdJkjTzrI9omDgGhyQ1VG7ok/uXg84LQES8lmJk9s8MOi+SJKk/rI9omNiCQ1IjRcQWTBGkzWJaNkmSpBljfUQaLrbgkNRUn2PjudI3epSDVEmSJM0k6yPSELEFh6RGKisMU02vtiQ3nvNekiSpp6yPSMPFAIckSZIkSWo8u6hIkiRJkqTGM8AhSZIkSZIazwCHJEmSJElqPAMckiRJkiSp8QxwSJIkSZKkxvv/6yXgCu0bzTkAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1296x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if l_flv[l_index]=='mu':\n",
+    "    lower_MC = 1.8\n",
+    "    upper_MC = 2.1\n",
+    "    lower_data = 1.0\n",
+    "    upper_data = 3.0\n",
+    "    \n",
+    "if l_flv[l_index]=='e':\n",
+    "    lower_MC = 1.75\n",
+    "    upper_MC = 2.15\n",
+    "    lower_data = 1.0\n",
+    "    upper_data = 3.5\n",
+    "\n",
+    "\n",
+    "#plt.suptitle('Reconstructed D_s mass', fontsize=15)\n",
+    "plt.subplot(1,2,1)\n",
+    "label=\"Ds_ConsD_M\"\n",
+    "#plt.title('MC', fontsize=12)\n",
+    "plt.hist([MC_Ds_tuple_dict[label][i][0]/1000 for i in range(len(MC_Ds_tuple_dict[\"Ds_ConsD_M\"]))],alpha=0.3,bins=70,range=(1.8,2.1), label='MC no presel');\n",
+    "plt.hist([MC_Ds_tuple_dict_presel_1[label][i][0]/1000 for i in range(len(MC_Ds_tuple_dict_presel_1[\"Ds_ConsD_M\"]))],alpha=0.4,bins=70,range=(lower_MC,upper_MC), label='MC after HLT1 TOS presel');\n",
+    "plt.hist([MC_Ds_tuple_dict_presel_2[label][i][0]/1000 for i in range(len(MC_Ds_tuple_dict_presel_2[\"Ds_ConsD_M\"]))],alpha=0.5,bins=70,range=(lower_MC,upper_MC), label='MC after HLT2 TOS presel');\n",
+    "plt.hist([MC_Ds_tuple_dict_presel_4[label][i][0]/1000 for i in range(len(MC_Ds_tuple_dict_presel_4[\"Ds_ConsD_M\"]))],alpha=0.7,bins=70,range=(lower_MC,upper_MC), label='MC after cutting on phi mass');\n",
+    "label=\"Dplus_ConsD_M\"\n",
+    "plt.hist([MC_Dplus_tuple_dict[label][i][0]/1000 for i in range(len(MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"]))],alpha=0.3,bins=70,range=(1.8,2.1), label='MC no presel');\n",
+    "plt.hist([MC_Dplus_tuple_dict_presel_1[label][i][0]/1000 for i in range(len(MC_Dplus_tuple_dict_presel_1[\"Dplus_ConsD_M\"]))],alpha=0.4,bins=70,range=(lower_MC,upper_MC), label='MC after HLT1 TOS presel');\n",
+    "plt.hist([MC_Dplus_tuple_dict_presel_2[label][i][0]/1000 for i in range(len(MC_Dplus_tuple_dict_presel_2[\"Dplus_ConsD_M\"]))],alpha=0.5,bins=70,range=(lower_MC,upper_MC), label='MC after HLT2 TOS presel');\n",
+    "plt.hist([MC_Dplus_tuple_dict_presel_4[label][i][0]/1000 for i in range(len(MC_Dplus_tuple_dict_presel_4[\"Dplus_ConsD_M\"]))],alpha=0.7,bins=70,range=(lower_MC,upper_MC), label='MC after cutting on phi mass');\n",
+    "\n",
+    "plt.legend(fontsize='10')\n",
+    "plt.ylabel('# events', fontsize=15)\n",
+    "plt.xlabel('Reconstructed D_s Mass (GeV)', fontsize=15)\n",
+    "\n",
+    "label=\"Ds_ConsD_M\"\n",
+    "plt.subplot(1,2,2)\n",
+    "plt.title('Data', fontsize=12)\n",
+    "#plt.hist([data_tuple_dict[\"Ds_ConsD_M\"][i][0]/1000 for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))],alpha=0.3,bins=70,range=(1.0,3.0), label='Data');\n",
+    "plt.hist([data_tuple_dict_presel_1[label][i][0]/1000 for i in range(len(data_tuple_dict_presel_1[\"Ds_ConsD_M\"]))],alpha=0.4,bins=70,range=(lower_data,upper_data),label='Data after HLT1 TOS presel');\n",
+    "plt.hist([data_tuple_dict_presel_2[label][i][0]/1000 for i in range(len(data_tuple_dict_presel_2[\"Ds_ConsD_M\"]))],alpha=0.5,bins=70,range=(lower_data,upper_data), label='Data after HLT2 TOS presel');\n",
+    "plt.hist([data_tuple_dict_presel_3[label][i][0]/1000 for i in range(len(data_tuple_dict_presel_3[\"Ds_ConsD_M\"]))],alpha=0.7,bins=70,range=(lower_data,upper_data), label='Data after \\mu & \\pi PID presel');\n",
+    "plt.hist([data_tuple_dict_presel_4[label][i][0]/1000 for i in range(len(data_tuple_dict_presel_4[\"Ds_ConsD_M\"]))],alpha=0.7,bins=70,range=(lower_data,upper_data), label='Data after cutting on phi mass');\n",
+    "plt.legend(fontsize='10')\n",
+    "plt.xlabel('Reconstructed D_s Mass (GeV)', fontsize=15)\n",
     "fig=plt.gcf()\n",
-    "fig.set_size_inches(16,10)"
+    "fig.set_size_inches(18,8)\n",
+    "plt.savefig('/home/hep/davide/D_s_reco.png', format='png', dpi=100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_tuple_dict=data_tuple_dict_presel_4\n",
+    "MC_Ds_tuple_dict=MC_Ds_tuple_dict_presel_4\n",
+    "MC_Dplus_tuple_dict=MC_Dplus_tuple_dict_presel_4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1296x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#plt.suptitle('Reconstructed D_s mass', fontsize=15)\n",
+    "plt.subplot(1,2,1)\n",
+    "label=\"Ds_ConsD_M\"\n",
+    "left_h_Ds=[MC_Ds_tuple_dict[label][i][0]/1000 for i in range(len(MC_Ds_tuple_dict[\"Ds_ConsD_M\"]))]\n",
+    "label=\"Dplus_ConsD_M\"\n",
+    "left_h_Dplus=[MC_Dplus_tuple_dict[label][i][0]/1000 for i in range(len(MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"]))]\n",
+    "plt.hist(left_h_Ds,alpha=0.7,bins=70,range=(1.75,2.10), label='MC after presel cuts',density=True);\n",
+    "plt.hist(left_h_Dplus,alpha=0.7,bins=70,range=(1.75,2.10), label='MC after presel cuts',density=True);\n",
+    "plt.legend(fontsize='10')\n",
+    "plt.ylabel('# events', fontsize=15)\n",
+    "plt.xlabel('Reconstructed D_s Mass (GeV)', fontsize=15)\n",
+    "\n",
+    "label=\"Ds_ConsD_M\"\n",
+    "plt.subplot(1,2,2)\n",
+    "plt.title('Data', fontsize=12)\n",
+    "right_h=[data_tuple_dict[label][i][0]/1000 for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))]\n",
+    "plt.hist(right_h,alpha=0.7,bins=70,range=(1.90,2.1), label='Data after presel cuts',density=True);\n",
+    "plt.legend(fontsize='10')\n",
+    "plt.xlabel('Reconstructed D_s Mass (GeV)', fontsize=15)\n",
+    "fig=plt.gcf()\n",
+    "fig.set_size_inches(18,8)\n",
+    "plt.savefig('/home/hep/davide/D_s_reco.png', format='png', dpi=100)"
    ]
   },
   {
@@ -327,8 +563,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data_tuple_dict=data_tuple_dict_presel_3\n",
-    "MC_tuple_dict=MC_tuple_dict_presel_3"
+    "#data_tuple_dict_presel={}\n",
+    "#\n",
+    "##data_tuple_for_NN=data_tuple_dict\n",
+    "#\n",
+    "#indices=[]\n",
+    "#for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"])):\n",
+    "#    Ds_m = data_tuple_dict[\"Ds_ConsD_M\"][i]\n",
+    "#    if 1890<Ds_m<2050:\n",
+    "#        indices.append(i)\n",
+    "#\n",
+    "#for label in branches_needed:  \n",
+    "#\n",
+    "#    data_tuple_dict_presel[label] = data_tuple_dict[label][indices]\n",
+    "#\n",
+    "#data_tuple_dict=data_tuple_dict_presel"
    ]
   },
   {
@@ -337,37 +586,73 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "lower_Ds_mass = 1850\n",
-    "upper_Ds_mass = 2050\n",
+    "if l_flv[l_index]=='mu':\n",
+    "    lower_Dplus_mass=1830\n",
+    "    upper_Dplus_mass=1910\n",
     "\n",
-    "lower_phi_mass = 900\n",
-    "upper_phi_mass = 1100\n",
+    "    lower_Ds_mass = 1930\n",
+    "    upper_Ds_mass = 2010\n",
+    "    \n",
+    "if l_flv[l_index]=='e':\n",
+    "    lower_Dplus_mass=1810\n",
+    "    upper_Dplus_mass=1900\n",
+    "\n",
+    "    lower_Ds_mass = 1930\n",
+    "    upper_Ds_mass = 2000\n",
     "\n",
     "#Retrieve mc signal and data bkg events\n",
     "\n",
     "data_bkg_indices=[]\n",
-    "MC_sig_indices=[]\n",
+    "MC_Ds_sig_indices=[]\n",
+    "MC_Dplus_sig_indices=[]\n",
     "\n",
     "\n",
     "for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"])):\n",
     "    #retrieving the Ds reconstructed mass\n",
     "    \n",
-    "    if 0<data_tuple_dict[\"phi_M\"][i]<lower_phi_mass or upper_phi_mass<data_tuple_dict[\"phi_M\"][i]:\n",
-    "        Ds_m = data_tuple_dict[\"Ds_ConsD_M\"][i]\n",
-    "    \n",
-    "    #selecting the out of signal regions\n",
-    "        if 0<Ds_m<lower_Ds_mass or upper_Ds_mass < Ds_m:\n",
-    "            data_bkg_indices.append(i)\n",
+    "    #if 0<data_tuple_dict[\"phi_M\"][i]<lower_phi_mass or upper_phi_mass<data_tuple_dict[\"phi_M\"][i]:\n",
+    "        m = data_tuple_dict[\"Ds_ConsD_M\"][i]\n",
     "        \n",
-    "for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"])):\n",
+    "    #selecting the out of signal regions\n",
+    "        if 0<m<lower_Dplus_mass or upper_Dplus_mass < m < lower_Ds_mass or upper_Ds_mass < m:\n",
+    "        #if 0<m<lower_Ds_mass or upper_Ds_mass < m:\n",
+    "            data_bkg_indices.append(i)\n",
+    "            \n",
+    "for i in range(len(MC_Ds_tuple_dict[\"Ds_ConsD_M\"])):\n",
     "    \n",
     "    #retrieving the Ds reconstructed mass\n",
-    "    if lower_phi_mass<MC_tuple_dict[\"phi_M\"][i]<lower_phi_mass:\n",
-    "        Ds_m = MC_tuple_dict[\"Ds_ConsD_M\"][i]\n",
+    "    #if lower_phi_mass<MC_tuple_dict[\"phi_M\"][i]<lower_phi_mass:\n",
+    "        m = MC_Ds_tuple_dict[\"Ds_ConsD_M\"][i]\n",
     "    \n",
     "    #selecting the signal regions\n",
-    "        if lower_Ds_mass<Ds_m<upper_Ds_mass:\n",
-    "            MC_sig_indices.append(i)"
+    "        #if lower_Dplus_mass< m <upper_Dplus_mass or lower_Ds_mass< m <upper_Ds_mass:\n",
+    "        if lower_Ds_mass< m <upper_Ds_mass:\n",
+    "            MC_Ds_sig_indices.append(i)  \n",
+    "            \n",
+    "for i in range(len(MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"])):\n",
+    "    \n",
+    "    #retrieving the Ds reconstructed mass\n",
+    "    #if lower_phi_mass<MC_tuple_dict[\"phi_M\"][i]<lower_phi_mass:\n",
+    "        m = MC_Dplus_tuple_dict[\"Dplus_ConsD_M\"][i]\n",
+    "    \n",
+    "    #selecting the signal regions\n",
+    "        #if lower_Dplus_mass< m <upper_Dplus_mass or lower_Ds_mass< m <upper_Ds_mass:\n",
+    "        if lower_Dplus_mass< m <upper_Dplus_mass:\n",
+    "            MC_Dplus_sig_indices.append(i)\n",
+    "            \n",
+    "#Create the dict tuples with all MC signal and data bkg events\n",
+    "\n",
+    "data_tuple_bkg={}\n",
+    "MC_Ds_tuple_sig ={}\n",
+    "MC_Dplus_tuple_sig ={}\n",
+    "\n",
+    "for label in return_branches(mother_index=0):    \n",
+    "\n",
+    "    data_tuple_bkg[label] = data_tuple_dict[label][data_bkg_indices]\n",
+    "    MC_Ds_tuple_sig[label] = MC_Ds_tuple_dict[label][MC_Ds_sig_indices]\n",
+    "    \n",
+    "for label in return_branches(mother_index=1):  \n",
+    "    MC_Dplus_tuple_sig[label] = MC_Dplus_tuple_dict[label][MC_Dplus_sig_indices]"
    ]
   },
   {
@@ -376,51 +661,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#Create the dict tuples with all MC signal and data bkg events\n",
-    "\n",
-    "data_tuple_bkg={}\n",
-    "MC_tuple_sig ={}\n",
-    "\n",
-    "for label in branches_needed:  \n",
-    "\n",
-    "    data_tuple_bkg[label] = data_tuple_dict[label][data_bkg_indices]\n",
-    "    MC_tuple_sig[label] = MC_tuple_dict[label][MC_sig_indices]\n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(6151,)"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "MC_tuple_sig[\"Ds_ConsD_M\"].shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [],
-   "source": [
     "def plot_sb_comparison(nbins=None, particle=None, variable=None, \n",
     "                       MC_sig=None, data_bkg=None, \n",
     "                       width_MC=None, width_data=None,):\n",
     "                       #min_plt_range=None, max_plt_range=None):\n",
     "    \n",
     "    #Determine maximum between MC and data\n",
-    "    if \"CHI2\" in variable:\n",
+    "    if \"IP own pv\" or \"FD own pv\" or \"PT\" or \"CHI2\" in variable:\n",
     "        if np.max(MC_sig)>np.max(data_bkg):\n",
     "            upper_limit=np.max(MC_sig)\n",
     "        else:\n",
@@ -438,6 +685,7 @@
     "    if \"Hlt\" in variable:\n",
     "        lower_limit=0.\n",
     "        upper_limit=2.\n",
+    "        \n",
     "    \n",
     "    #Create and fill MC Signal histogram\n",
     "\n",
@@ -474,14 +722,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -491,27 +739,114 @@
     }
    ],
    "source": [
-    "\n",
     "#Retrieve data from needed branch\n",
-    "MC_Ds_endvtx_chi2ratio=MC_tuple_dict[\"Ds_ENDVERTEX_CHI2\"]/MC_tuple_dict[\"Ds_ENDVERTEX_NDOF\"]\n",
+    "plt.subplot(1,2,1)\n",
+    "MC_Ds_endvtx_chi2ratio=MC_Ds_tuple_dict[\"Ds_ENDVERTEX_CHI2\"]/MC_Ds_tuple_dict[\"Ds_ENDVERTEX_NDOF\"]\n",
     "data_Ds_endvtx_chi2ratio=data_tuple_bkg[\"Ds_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"Ds_ENDVERTEX_NDOF\"]\n",
     "\n",
     "#Plot\n",
     "plot_sb_comparison(nbins=70,particle=\"Ds\", variable=\"END VTX CHI2\", \n",
     "                   MC_sig=MC_Ds_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n",
+    "                   width_MC=0.05, width_data=0.06)\n",
+    "plt.subplot(1,2,2)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Dplus_endvtx_chi2ratio=MC_Dplus_tuple_dict[\"Dplus_ENDVERTEX_CHI2\"]/MC_Dplus_tuple_dict[\"Dplus_ENDVERTEX_NDOF\"]\n",
+    "data_Dplus_endvtx_chi2ratio=data_tuple_bkg[\"Ds_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"Ds_ENDVERTEX_NDOF\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"Dplus\", variable=\"END VTX CHI2\", \n",
+    "                   MC_sig=MC_Ds_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n",
     "                   width_MC=0.05, width_data=0.06)"
    ]
   },
   {
    "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Retrieve data from needed branch\n",
+    "plt.subplot(1,2,1)\n",
+    "MC_Ds_IP_ownpv=MC_Ds_tuple_dict[\"Ds_IP_OWNPV\"]\n",
+    "data_Ds_IP_ownpv=data_tuple_bkg[\"Ds_IP_OWNPV\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"Ds\", variable=\"Ds IP own pv\", \n",
+    "                   MC_sig=MC_Ds_IP_ownpv, data_bkg=data_Ds_IP_ownpv, \n",
+    "                   width_MC=0.001, width_data=0.002)\n",
+    "plt.subplot(1,2,2)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Dplus_IP_ownpv=MC_Dplus_tuple_dict[\"Dplus_IP_OWNPV\"]\n",
+    "data_Ds_IP_ownpv=data_tuple_bkg[\"Ds_IP_OWNPV\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"Dplus\", variable=\"Ds IP own pv\", \n",
+    "                   MC_sig=MC_Dplus_IP_ownpv, data_bkg=data_Ds_IP_ownpv, \n",
+    "                   width_MC=0.001, width_data=0.002)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Retrieve data from needed branch\n",
+    "plt.subplot(1,2,1)\n",
+    "MC_Ds_FD_ownpv=MC_Ds_tuple_dict[\"Ds_FD_OWNPV\"]\n",
+    "data_Ds_FD_ownpv=data_tuple_bkg[\"Ds_FD_OWNPV\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"Ds\", variable=\"Ds FD own pv\", \n",
+    "                   MC_sig=MC_Ds_FD_ownpv, data_bkg=data_Ds_FD_ownpv, \n",
+    "                   width_MC=0.8, width_data=0.8)\n",
+    "plt.subplot(1,2,2)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Dplus_FD_ownpv=MC_Dplus_tuple_dict[\"Dplus_FD_OWNPV\"]\n",
+    "data_Ds_FD_ownpv=data_tuple_bkg[\"Ds_FD_OWNPV\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"Dplus\", variable=\"Dplus FD own pv\", \n",
+    "                   MC_sig=MC_Dplus_FD_ownpv, data_bkg=data_Ds_FD_ownpv, \n",
+    "                   width_MC=1, width_data=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
    "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -521,14 +856,24 @@
     }
    ],
    "source": [
-    "\n",
     "#Retrieve data from needed branch\n",
-    "MC_Ds_endvtx_chi2ratio=MC_tuple_dict[\"phi_ENDVERTEX_CHI2\"]/MC_tuple_dict[\"phi_ENDVERTEX_NDOF\"]\n",
+    "plt.subplot(2,1,1)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Ds_endvtx_chi2ratio=MC_Ds_tuple_dict[\"phi_ENDVERTEX_CHI2\"]/MC_Ds_tuple_dict[\"phi_ENDVERTEX_NDOF\"]\n",
     "data_Ds_endvtx_chi2ratio=data_tuple_bkg[\"phi_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"phi_ENDVERTEX_NDOF\"]\n",
     "\n",
     "#Plot\n",
     "plot_sb_comparison(nbins=70,particle=\"phi\", variable=\"END VTX CHI2\", \n",
     "                   MC_sig=MC_Ds_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n",
+    "                   width_MC=0.07, width_data=0.08)\n",
+    "plt.subplot(2,1,2)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Dplus_endvtx_chi2ratio=MC_Dplus_tuple_dict[\"phi_ENDVERTEX_CHI2\"]/MC_Dplus_tuple_dict[\"phi_ENDVERTEX_NDOF\"]\n",
+    "data_Ds_endvtx_chi2ratio=data_tuple_bkg[\"phi_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"phi_ENDVERTEX_NDOF\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70,particle=\"phi\", variable=\"END VTX CHI2\", \n",
+    "                   MC_sig=MC_Dplus_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n",
     "                   width_MC=0.07, width_data=0.08)"
    ]
   },
@@ -539,9 +884,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -552,12 +897,22 @@
    ],
    "source": [
     "#Retrieve data from needed branch\n",
-    "MC_Ds_ownpv_chi2ratio=MC_tuple_dict[\"Ds_OWNPV_CHI2\"]/MC_tuple_dict[\"Ds_OWNPV_NDOF\"]\n",
+    "plt.subplot(1,2,1)\n",
+    "MC_Ds_ownpv_chi2ratio=MC_Ds_tuple_dict[\"Ds_OWNPV_CHI2\"]/MC_Ds_tuple_dict[\"Ds_OWNPV_NDOF\"]\n",
     "data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg[\"Ds_OWNPV_NDOF\"]\n",
     "\n",
     "#Plot\n",
     "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"Own PV CHI2\", \n",
     "                   MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n",
+    "                   width_MC=0.005, width_data=0.005)\n",
+    "plt.subplot(1,2,2)\n",
+    "#Retrieve data from needed branch\n",
+    "MC_Ds_ownpv_chi2ratio=MC_Dplus_tuple_dict[\"Dplus_OWNPV_CHI2\"]/MC_Dplus_tuple_dict[\"Dplus_OWNPV_NDOF\"]\n",
+    "data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg[\"Ds_OWNPV_NDOF\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70, particle=\"Dplus\", variable=\"Own PV CHI2\", \n",
+    "                   MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n",
     "                   width_MC=0.01, width_data=0.01)"
    ]
   },
@@ -565,29 +920,26 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "#Retrieve data from needed branch\n",
-    "MC_Ds_ownpv_chi2ratio=MC_tuple_dict[\"phi_OWNPV_CHI2\"]/MC_tuple_dict[\"phi_OWNPV_NDOF\"]\n",
-    "data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"phi_OWNPV_CHI2\"]/data_tuple_bkg[\"phi_OWNPV_NDOF\"]\n",
-    "\n",
-    "#Plot\n",
-    "plot_sb_comparison(nbins=70, particle=\"phi\", variable=\"Own PV CHI2\", \n",
-    "                   MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n",
-    "                   width_MC=0.009, width_data=0.008)"
+    "##Retrieve data from needed branch\n",
+    "#plt.subplot(1,2,1)\n",
+    "#MC_Ds_ownpv_chi2ratio=MC_Ds_tuple_dict[\"phi_OWNPV_CHI2\"]/MC_Ds_tuple_dict[\"phi_OWNPV_NDOF\"]\n",
+    "#data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"phi_OWNPV_CHI2\"]/data_tuple_bkg[\"phi_OWNPV_NDOF\"]\n",
+    "#\n",
+    "##Plot\n",
+    "#plot_sb_comparison(nbins=70, particle=\"phi\", variable=\"Own PV CHI2\", \n",
+    "#                   MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n",
+    "#                   width_MC=0.009, width_data=0.008)\n",
+    "#\n",
+    "#plt.subplot(1,2,2)\n",
+    "#MC_Ds_ownpv_chi2ratio=MC_Dplus_tuple_dict[\"phi_OWNPV_CHI2\"]/MC_Dplus_tuple_dict[\"phi_OWNPV_NDOF\"]\n",
+    "#data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"phi_OWNPV_CHI2\"]/data_tuple_bkg[\"phi_OWNPV_NDOF\"]\n",
+    "#\n",
+    "##Plot\n",
+    "#plot_sb_comparison(nbins=70, particle=\"phi\", variable=\"Own PV CHI2\", \n",
+    "#                   MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n",
+    "#                   width_MC=0.009, width_data=0.008)"
    ]
   },
   {
@@ -597,9 +949,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -609,13 +961,25 @@
     }
    ],
    "source": [
-    "MC_Ds_DIRA_ownpv=MC_tuple_sig[\"Ds_DIRA_OWNPV\"]\n",
-    "data_Ds_DIRA_ownpv=data_tuple_bkg[\"Ds_DIRA_OWNPV\"]\n",
+    "#Retrieve data from needed branch\n",
+    "plt.subplot(1,2,1)\n",
+    "\n",
+    "MC_Ds_pT=MC_Ds_tuple_sig[\"Ds_PT\"]/1000\n",
+    "data_Ds_pT=data_tuple_bkg[\"Ds_PT\"]/1000\n",
     "\n",
     "#Plot\n",
-    "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"DIRA Own PV\", \n",
-    "                   MC_sig=MC_Ds_DIRA_ownpv, data_bkg=data_Ds_DIRA_ownpv,\n",
-    "                   width_MC=0.000001, width_data=0.000001)\n"
+    "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"PT\", \n",
+    "                   MC_sig=MC_Ds_pT, data_bkg=data_Ds_pT,\n",
+    "                   width_MC=.4, width_data=.4)\n",
+    "plt.subplot(1,2,2)\n",
+    "\n",
+    "MC_Dplus_pT=MC_Dplus_tuple_sig[\"Dplus_PT\"]/1000\n",
+    "data_Ds_pT=data_tuple_bkg[\"Ds_PT\"]/1000\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70, particle=\"Dplus\", variable=\"PT\", \n",
+    "                   MC_sig=MC_Dplus_pT, data_bkg=data_Ds_pT,\n",
+    "                   width_MC=.4, width_data=.4)"
    ]
   },
   {
@@ -625,9 +989,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -637,13 +1001,22 @@
     }
    ],
    "source": [
-    "MC_probNNmu=MC_tuple_sig[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
-    "data_probNNmu=data_tuple_bkg[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
+    "plt.subplot(1,2,1)\n",
+    "MC_Ds_DIRA_ownpv=MC_Ds_tuple_sig[\"Ds_DIRA_OWNPV\"]\n",
+    "data_Ds_DIRA_ownpv=data_tuple_bkg[\"Ds_DIRA_OWNPV\"]\n",
     "\n",
     "#Plot\n",
-    "plot_sb_comparison(nbins=70, particle=\"Ds\",variable=\"probNN mu\", \n",
-    "                   MC_sig=MC_probNNmu, data_bkg=data_probNNmu,\n",
-    "                   width_MC=0.01, width_data=0.01)"
+    "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"DIRA Own PV\", \n",
+    "                   MC_sig=MC_Ds_DIRA_ownpv, data_bkg=data_Ds_DIRA_ownpv,\n",
+    "                   width_MC=0.000001, width_data=0.000001)\n",
+    "plt.subplot(1,2,2)\n",
+    "MC_Ds_DIRA_ownpv=MC_Dplus_tuple_sig[\"Dplus_DIRA_OWNPV\"]\n",
+    "data_Ds_DIRA_ownpv=data_tuple_bkg[\"Ds_DIRA_OWNPV\"]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70, particle=\"Dplus\", variable=\"DIRA Own PV\", \n",
+    "                   MC_sig=MC_Ds_DIRA_ownpv, data_bkg=data_Ds_DIRA_ownpv,\n",
+    "                   width_MC=0.000001, width_data=0.000001)\n"
    ]
   },
   {
@@ -653,9 +1026,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
+       "<Figure size 1152x576 with 2 Axes>"
       ]
      },
      "metadata": {
@@ -665,74 +1038,58 @@
     }
    ],
    "source": [
-    "MC_Hlt1TrackMVA_TOS=MC_tuple_sig[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
-    "data_Hlt1TrackMVA_TOS=data_tuple_bkg[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
+    "plt.subplot(2,1,1)\n",
+    "MC_probNNmu=MC_Ds_tuple_sig[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
+    "data_probNNmu=data_tuple_bkg[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
     "\n",
     "#Plot\n",
-    "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt1 Track MVA TOS\", \n",
-    "                   MC_sig=MC_Hlt1TrackMVA_TOS, data_bkg=data_Hlt1TrackMVA_TOS,\n",
-    "                   width_MC=0.5, width_data=0.5)"
+    "plot_sb_comparison(nbins=70, particle=\"Ds\",variable=\"probNN mu\", \n",
+    "                   MC_sig=MC_probNNmu, data_bkg=data_probNNmu,\n",
+    "                   width_MC=0.01, width_data=0.01)\n",
+    "plt.subplot(2,1,2)\n",
+    "MC_probNNmu=MC_Dplus_tuple_sig[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
+    "data_probNNmu=data_tuple_bkg[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
+    "\n",
+    "#Plot\n",
+    "plot_sb_comparison(nbins=70, particle=\"Dplus\",variable=\"probNN mu\", \n",
+    "                   MC_sig=MC_probNNmu, data_bkg=data_probNNmu,\n",
+    "                   width_MC=0.01, width_data=0.01)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "MC_Hlt2RareCharm_TOS=MC_tuple_sig[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
-    "data_Hlt2RareCharm_TOS=data_tuple_bkg[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
+    "#MC_Hlt1TrackMVA_TOS=MC_tuple_sig[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
+    "#data_Hlt1TrackMVA_TOS=data_tuple_bkg[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
+    "#\n",
+    "##Plot\n",
+    "#plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt1 Track MVA TOS\", \n",
+    "#                   MC_sig=MC_Hlt1TrackMVA_TOS, data_bkg=data_Hlt1TrackMVA_TOS,\n",
+    "#                   width_MC=0.5, width_data=0.5)\n",
     "\n",
-    "#Plot\n",
-    "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 RareCharm D2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\" TOS\", \n",
-    "                   MC_sig=MC_Hlt2RareCharm_TOS, data_bkg=data_Hlt2RareCharm_TOS,\n",
-    "                   width_MC=0.5, width_data=0.5)"
+    "#MC_Hlt2RareCharm_TOS=MC_tuple_sig[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
+    "#data_Hlt2RareCharm_TOS=data_tuple_bkg[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
+    "#\n",
+    "##Plot\n",
+    "#plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 RareCharm D2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\" TOS\", \n",
+    "#                   MC_sig=MC_Hlt2RareCharm_TOS, data_bkg=data_Hlt2RareCharm_TOS,\n",
+    "#                   width_MC=0.5, width_data=0.5)\n",
+    "\n",
+    "#MC_Hlt2Phys_TOS=MC_tuple_sig[\"Ds_Hlt2Phys_TOS\"]\n",
+    "#data_Hlt2Phys_TOS=data_tuple_bkg[\"Ds_Hlt2Phys_TOS\"]\n",
+    "#\n",
+    "#plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 Phys TOS\", \n",
+    "#                   MC_sig=MC_Hlt2Phys_TOS, data_bkg=data_Hlt2Phys_TOS,\n",
+    "#                   width_MC=0.5, width_data=0.5)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1152x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "MC_Hlt2Phys_TOS=MC_tuple_sig[\"Ds_Hlt2Phys_TOS\"]\n",
-    "data_Hlt2Phys_TOS=data_tuple_bkg[\"Ds_Hlt2Phys_TOS\"]\n",
-    "\n",
-    "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 Phys TOS\", \n",
-    "                   MC_sig=MC_Hlt2Phys_TOS, data_bkg=data_Hlt2Phys_TOS,\n",
-    "                   width_MC=0.5, width_data=0.5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
    "outputs": [],
    "source": [
     "#h_data_under.SetLineColor(38)\n",
@@ -754,24 +1111,82 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
-    "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n",
-    "    pickle.dump(MC_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
+    "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_Ds_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n",
+    "    pickle.dump(MC_Ds_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
+    "    \n",
+    "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_Dplus_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n",
+    "    pickle.dump(MC_Dplus_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
+    "    \n",
     "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n",
     "    pickle.dump(data_tuple_bkg, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
+    "    \n",
     "with open('/disk/lhcb_data/davide/Rphipi/NN_for_selection/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n",
     "    pickle.dump(data_tuple_dict, handle, protocol=pickle.HIGHEST_PROTOCOL)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "13821"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_tuple_bkg[\"Ds_ConsD_M\"].shape[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9639"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "MC_Dplus_tuple_sig[\"Dplus_ConsD_M\"].shape[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5881"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "MC_Ds_tuple_sig[\"Ds_ConsD_M\"].shape[0]"
+   ]
   },
   {
    "cell_type": "code",