https://thaidj.org/index.php/jpphd/issue/feedJournal of Phrae Public Health for Development - วารสารสาธารณสุขแพร่เพื่อการพัฒนา2024-08-30T11:18:06+07:00นิพิฐพนธ์ แสงด้วงhrphrae.ejournal@gmail.comOpen Journal Systems<p><strong>วารสารสาธารณสุขแพร่เพื่อการพัฒนา</strong></p> <p>จัดทำขึ้นเพื่อเผยแพร่ผลงานวิจัยและผลงานวิชาการด้านการแพทย์ สาธารณสุข และการคุ้มครองผู้บริโภค รวมทั้งผลงานนวัตกรรมด้านการสาธารณสุขที่ก่อให้เกิดองค์ความรู้อันเป็นประโยชน์แก่บุคคลทางการแพทย์และสาธารณสุข </p> <p><strong>Language:</strong> Abstract in English. Text in Thai and/or English </p> <p><strong>Access:</strong> Free access online </p> <p><strong>กำหนดการตีพิมพ์เผยแพร่วารสารฯ</strong> วารสารมีกำหนดออก ปีละ 2 ฉบับ (ราย 6 เดือน) </p> <p>ฉบับที่ 1 เดือน มกราคม–มิถุนายน <br />ฉบับที่ 2 เดือน กรกฎาคม–ธันวาคม </p> <p>ISSN 2774-096X (Online) </p> <p> </p>https://thaidj.org/index.php/jpphd/article/view/15705Content2024-08-27T15:33:18+07:00Nithi Naewlekhrphrae.ejournal@gmail.com<p>Content</p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15689Factors Affected on Deciding to Write a Living Will among End-of-life Patients in the Palliative Clinic2024-08-27T13:39:47+07:00Warawut Somboon bboymd02@gmail.com<p>This research objectives were to study the relationships among various factors and to identify predictors influencing the intention to write a living will for accepting or refusing medical services among end-of-life patients in palliative care clinics. The study involved 128 patients, selected through simple random sampling. Data were collected using a Likert scale questionnaire with a reliability coefficient of 0.70 to 0.85. The data were analyzed by descriptive statistics, univariate analysis, and multiple logistic regression.</p> <p>The research findings indicated that: 1) factors significantly associated with the intention to a write Living Will at the 0.05 level include having a chronic illness, history of intubation, future time perspective, knowledge, attitude, and intention to a write Living Will (OR = 5.89, 3.54, 2.96, 6.53, 26.60, and 15.88, respectively).<br> 2) Factors predicting changes in the living will include having a chronic illness (DIS), attitude (ATT), and intention (INT), with logistic coefficients of -2.29, -0.60, and -0.60, respectively. These factors explain 63.20% of the variance the intention to write a living will. The predictive equation from row score were as follow:</p> <p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAvIAAACTCAYAAADsrP2aAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFxEAABcRAcom8z8AAKjkSURBVHhe7J0HQBdH2v+99733fe9STYymqrHHRE1TY4xGjb333iuKIiIWsKCioKKo2HtFkd4EsYAgRXrvvffe++c/+wMVLEnukvtfzO0nN6f+dnZ29plndr/P7OxsC5pRR31RPKmeFty7qMvhratRXTqb+TOmMHXKNKbMmMecJWtZufkAe87ewsInlegSqG3cW0bmt1ElUgTJXue4sHEpKyZPY/os4XMLFrJgwTzmz57OzBnzmbTuLNuMowlMl/LLyPyRyCEzwBwb7eVozpjGjJlzmT2/if/OWsqk9ZfZYxFLQk514z4yMjIyMjL/HM8IeQkh5iuKKM3LICs1kaS4GGKjo4iKklIM0bEJxCelk5pdSEF5rUJ6ycj8PtSLVE5lSSZZibHERUYLf4snLiGRhIR4EuKiiYmOJjIhk6ScCkqrpPwyMn8kqqkuzSUvOZakKOG/MU39V1xLY2KF/2aRkltBZY3svzIyMjIyv40XCHkZGRkZGRkZGRkZmT86spCXkZGRkZGRkZGReQWRhbyMjIyMjIyMjIzMK4gs5GVkZGRkZGRkZGReQWQhLyMjIyMjIyMjI/MKIgt5GRkZGRkZGRkZmVcQWcjLyMjIyMjIyMjIvILIQl5GRkZGRkZGRkbmFUQW8jIyMjIyMjIyMjKvILKQl5GRkZGRkZGRkXkFkYW8jIyMjIyMjIyMzCuILORlZGRkZGRkZGRkXkFkIS8jIyMjIyMjIyPzCiILeRkZGRkZGRkZGZlXEFnIy8jIyMjIyMjIyLyCyEJeRkZGRkZGRkZG5hVEFvIyMjIyMjIyMjIyryCykJeRkZGRkZGRkZF5BZGFvIyMjIyMjIyMjMwriCzkZWRkZGRkZGRkZF5BZCEvIyMjIyMjIyMj8woiC3kZGRkZGRkZGRmZVxBZyMvIyMjIyMjIyMi8gshCXkZGRkZGRkZGRuYVRBbyMjIyMjIyMjIyMq8gspCXkZGRkZGRkZGReQWRhbyMjIyMjIyMjIzMK4gs5GVkZGRkZGRkZGReQWQhLyMjIyMjIyMjI/MKIgt5GRkZGRkZGRkZmVcQWcjLyMjI/Bmpr6WuspjywlzycwvIL6qgvKaO2sbNIgPUVVBRnEteVhaZ2YXkl1ZTVde4uRn1orgqqkoLKMrJIjszm+z8YooqaqkSxTxHvSikppzqijLKKmuoqBGHelG+30Qt1ZUVlBaXUyGO8fS8HiMOWF9FdVkhRbmivlm55BaK+lTX8cJTlKirora8kOI8kT87j5yCckoqm9usvrKE8vwscjOzyMoVNqgU9Wjc+hSRT5RVVSKOLeyVmy3KE39mZWaQkS6SsF9WXhEFT+wt6lpdSqXUFqKuWVJ+Ud/8onJKq+uprasW9SqgODeTrKwcssV5FIt6VdXWiypXiG2inSsrKRNlPW+H34l6cRxRx5LyKkorxXFf0p71ot0rCnPIyxb1zCuluOJn7N2MGuGvRRTni/1yCsktrkaYVvF7fUUhJYo2ySevuJIKqWkV+/wCtWLfmmpq6upEKaJ5G35toL5atGUxpQXC3lK7iPbMzJKOIfw7K4PMDJFy88kpLqWwsJDC7ExyMjIV+RTt87g9M7LJzCmmuKz6qU1E36uvLKWqvFThb8Jc/0KE/1U87QcvtbXUH4V/5Ut1b/RbySa/SF258Ms84Ze5ZOULvxPGVxyjtkl5eS8rT9SnuoTSwjxyhW1zhG1zhd1ypLbMySZD8uUC4SPCQE/3Fb4u2qU4T2yTbJ2ZR4Gwf6nox4XCr17aVjk55BQVk1dSJdpC9Nlf53R/CmQhLyMjI/MnpL4ih8IAYx6c2oauxgF2n3biTkIh2Y3bIZfq1Pu4XNRi58pVLFM1QPdmAN4ZlVQ15niKEKV5YUQ7nOH6jtVsUlJhrc4Vjj9IxD+f54VKeTaVEbaEOJtj6R6Hc3w9xc8X+hsoE1WKJcDZBQvDh7j7pyCq8Yy4E3kKgwh3OMUFLTXWr97KliPWmPpnkiRUw/OiQ6jGvACSH5zAUHcd69dqsX6/DVdcM0gsf1yyCAa8b3JnnwpblymjrHWR486JBEnVaczRQA01xZGE2ZziqsYKtiqvQnm1EsuXLmbRgsUsXamOitZp9I19cE2uoaiqjLq42wRe38I+TWVWrFrNquU70L3sjF1CPsmZwcTYH+TSViXWqGxj42k7rvllE5RcTH64Fxku13Fxd8Umvoro8sYq/J7UFUOWE7G+Vtx0DMMuqAIR47yAfAqj7bl/XJNdKhtR1TbjgnMKSb/Y9qI1SkNJcDrFlf3bUN1+gd2m0QRniR1Lo8h1Ooah1hrU1umw44ob99NryGvc86UIEU9aFIURPkQkpRFWKmrXVNyVxlDmfwXro+tZs3QRi5asYMkK0aYrl6O8fBFLFi1iudZ+NC6bceTYCY6pKKGxcAmLRT4l5ZWiPVco2nPxovUs2XgFI/sISqUIQ6Iin4qgW4Q5mWDtn4Bzjjjcv0RYipOqjMHvgTPmhq54BKRSIH59tjuKDklFtAO+F4V/rVNFVfjtKecEQiue9dtnyaVc+OXDq9rs3rYHVf27GPmIQLeiCBJu43NeE521aqjuuspZt2QiRGFPg1qpFikUx9ngcGY3WstXsWbVCtZvXMOWvZtR36LKstXqKOsaceJBFmFSxRVhaBKZIcaY7hN5lqxh5ZI9HDl1FluHE5w9pYnyMtGHlig1aavFDW2lsZWNZ66hfdWDK9aJRCVVSgX+RyALeRkZGZk/IfVlaeQ46WG4cjCjug5h4GQ99LySiRLbpDHS6jxvkuy1OLzsBwZ260r7LsMYstyAffcTCCitp7KZ8KigIuMRvpc2oTv1G0Z+2Z3uw5YxatddznmXkttMyVdRl/aIFBNVLuqsQemYK/pu9WQIzfFipJt3BdVV5ZSW1VAhyqp/Xok0o7ookAz3M5zYocvq9Te4fDeKTPF70yrXVqZSHH6T24eXojyyN327fEnfkatYfOwBJjGVZFU3PUgt9TX5lISZ8/DoYjZP/pa+PfvR/YeVzN1zG4uoIorLy6nKeYjvBVW2jOzJ9+0/pev3sxm5zZoTj4pIKhVlNJYmyZmqfC8enV7FloEf8lXLd3nn7ff5oG0HOnTrzmc9v6VnnzEMm7uTzdf9cQhLJvXRBe5r/ciMr1ryfqtWtPpoJKM0r3HcNwQX1+vc3DiB5d9/Tp/vRzFUdT8bzfwwck0i/J4FkVfXc/Lgbtae8+B6kKirqMHLR+alWoo2qi2nvLyKsrI6ap6PahqR8lZSneVLvNU2LuzbyJqjjhx7WEZWSUOOJ9SUUpPzgGDj9WhN68t3Xb6i50AlFhxwwCy2lEyhq17crFVUFESS5HIGk10zWT51DN9O0mKevgfukbGUijZ00J7Gwt6d+arXYPotOcJWmwS8sqt+5hwFlYWUuVzD/7w2Zy0cOR9V1zzIyXhIrtka9i7oy2edO9Kx3Qe0/0C003sf8s6HHWjf4VM+HzWO3krqjJ88j5mfdWdop/Z0bP8hbd59j3dbfsBH7TrwaYd+dPp2DbuFyC0objRkWSalLgbcP6bKBr0raNkkEpArfKJh60sQZ1MvfKyq4lf2g3qqC/1Jcz3NUS1d1my4ydX70YpAvdludeXUFwcRZrYD/Zl9Gda9Kz1+XMjEPXZc8CslteJFVhRXCNEfiuIc8bq6mf1KIxkxZj79lQw5aC+OkepDko0WB2b0Zshnn9FjyDKm7rvLNRHRZjQ8RhFItYgiP/AYl9YOYdhHrXi31ft89PlX/DhjJEPHfUuv7h358Mvp9F9nxQmPEorqpNH+SJJd93B4Rh/Rx7rzaftpzF66hiOH5gvhPoRuXTuJtnqfdqKtWr73UUNbdexA96E/8c1CFX6ap80K5QtctA4nTATY5T/rJH8OZCEvIyMj82ekupiyBBfcz25j89CpLJwpRLtXLKFiU2VdMelO17i3ewW6mmtYs0kV1QVjWbpoCTMP3uWQZ+kzwrua6pIUUv3v4Wp8gOuHV7J6rRpjla6w+2oUCYVNlGBlGmWB1/A8NJ1ta5YwSdeZ3c71pL9UyBcK3RBJelokfoH5RMWJIOOlwlJCiOZ7Z7BaO5XV89exxMAV07BcaWyyiYCppyQ1lPj7l7C7dhiDg7vQVp7MqpkTGbX6OCo3YvFLbzpiV0R1eQyRD62wPXmIi4d2oq2+jMWjRwkRsYttVlG4BgSS9EAf4yMaKK3VYO3aRaxVmsfY6Tos13bBKaZAegbQSC21FUmk+J7HVHsq03p+z7fdxjF95Va0jhmgt28zmvNGMnPoYAbP28PyM97c8fImxHwHJ+b1ZOIPvflh3j42WTzkbugdTC8dZst8NTYra6F/6gQXTC9wzsaBszbhPHTxIPbuIS5sWMzcqWpsOuuIs1DyOY01eR7JuEmUFYcSFp5CQEgludLjjBci2SiYJI8THFo1n7kzNrHhgjcOidWUPKNKa/LiSb+ljYUQ46tU1jJ7mTLrl81m9faDqJnHYR9bR+1zwlQaEo4kxOEsp9YtR23JMtbuPs62qw+xehhEepgpARa72KSsyuw5S1m/fhlLVu9g4QYrrtyLJ+dnhG5dWRJJ1zdybdVIFmkcZ61dAT5NjFKf4EG29T6uHt2N6g7R3qoTUZvSm6+GzOSrGdtQ276NfYe2oLJzK0rK2mxZtRMDHXW0NkxndO8h9Ok5lXlrtqK5cy/b1x3g1rW7lJc2GkX0varEWzw6p47q1AXMUz7KWZ9UIqRNDTleQEM/SEuNxFf0g5j4nwuwJApIvHMSC5UprFqwnqXHPDAPz1P0g2aUhFAafJorehuYN3sly5cvQm2DCrOUjqJ+8BHucQWKVn6KZNQcChPuY2+wjZ2LFqCyToP1xywxsA7BO8iNLO/jXNPbxLw5q1ihtJh1G9aK8k6gYeCFV3JRk4All4r0BwQYrkJnzvf06j+RL2fsRuv0Za5c1+bE+lGM6f0tXb5fwSx9Z25nSEfOpzjOFs9Ta9Fdv5bF686z9+AF7C/t5sxZPdbt3IH22nGsFcF2r8Gz+WbmNtS1tqNjoMdaEdBsmDubLdMms3LnFXa6looAqrEqf2JkIS8jIyPzp6WO3HAP7DZv4bi6LtcCY4WYqKOkJgHvU4c4tngjx67cxTlZiF63PdzYs4Cxq86z4nQ8MZlNVUS94vbeoJuKoOw+j+wvoKVtgcHVCJIVQl4aDy+nNC2EpNvHeKA3h50aasw6/Ij90oj8U5X7DJL08CUl0Yc7ToX4hzT8+kKkKR7FbtzVX4/KjxNZqGzAMf98goUebE4dxUlRxLk7EhgaSVhGMunBF7h/fBmzF2gxRdOJOyEFiho3UEhVWSxhvoG4O0cSl5xGWoglrrpT2LVGiQVH3Tl0wRTXwys4K4T0lrvxPIjzJtjuIDunrWLhjENcck8gUZT01GrSUGAkKSFXOLhcE5W5p7jhlkS6+LWqJIpEu51clkYqf5jCdwsNOeyaR5ywQfjZFZzbqsJWixBscvLISLHgxu7tLJx0iAOXQkioFjKpLor0GC8cHyXgH5dLXpo3j44ps3vcEOaqH2abZwm+JT83lyOG2nI3PDzjcHSFfNGkL0J6SlGdcA6X0wuZMXUNI1eacNUrXcizx77wGCHs4zxw01rMoRVL0TB0xsjblRC7zRzdo8nk7Q84dqeA6mdHRyuTqIw4zfVNoxjZ7Ut69F7IAv37mMVUkFcQR/mjnVgeXMkMzZtomHnjH2yDlb42KpN2sO+kEwFV9U2CpybUV1BX4E2g4Vr2LRzO8KlazD0YJIKtyidtXpeeQFGwF5EJ6YTnZFMccJqAiyooaV9nhWEqAWk5lGX54vPQFptbPrgHZFNYEUpq2FUOqWijuvQyFo+SSC7KJifQl5KwMOqrHktYyTqZpLpf4uqSkaycPIclFz24klJD05i3OdIjDh+SE3xxcCoiMLzh1xci9YPCh9zWW8ca0Q8WqZzgZGARIiZ7jtoES5KNl7FjmxZT9zlj+MidIJcLHFyhwZoFxzDyiCdV5HviLfVV1Be5EGGmyoaR39Crw48MnKfHbocU/POqKU+xJsF4OVu27mb6AVeMvd0IdDrLviUiuF16ClPfZIQef1perQhQkq4SZLqZ5RpnWXgiAZ8UaYPoLT5HMFQdyuiBg+gtAlc18xQe5QsnqRMelnaXuEBnbIUSf+ibSmaALwnJmUTmZlDiewyf82tZpn0T5RuphGTkUlyUgb+bBz5nNmK3bTTzFmkweoc3NwNKFIFKc3/9cyELeRkZGZk/MQUxPtzdup3Tm/ZyIyiWKHFbK6z0w/6gPttmHODM9WBxIxdKrtwaF8OtzJ5vgLKWBzFJL1Pe4saceQd/JxPOmPhh7lFEgWJucCnVlelEBQbjY3wR/9NKXD6iybLTXuxzrSf9pUJelIcnCUII2t3JxTug4dcXUhJIbbAuJ3YoM3j6YdYc8yekoF4xleRZakqLKc4W4qu0Upq4I7SmK9HOeqiv2sPitdY4+GU2GR2toq6mmIK8InJyqxpe4M33o8RyNTcObmDhYWc27DiPxYZZnDtziiMxtSIgqqQgyAazZUvYMns9x5xC8Rb7PZ29IRUSS0bUTY6s3oX64stY+ecozlYh9/OcibHbisbEKYwcshXNm+E4xQbjd0GFazvXoW0XjV1xDblZd7HZvZ7lI9ejqf8AtwKptqLmVQXk5pdRUF5LdXU+BX4GuBycytzVOxilF4JZ0EsfgQhE7UuceegWhcODerJfMuG8Nj+R1OtrMBIBxzyNY6y2ScNb2Od5UZRHdqgdhsuU2TZzO8fuRxFRnkpxynku6e1g2qIbHL0aTXVN8z1rU1yJvzwbnQnv0bnNu/z3a1/y2citqJuGcz8kiHBDZa5rzUXp9EOOxZSTUZRA6Fld9KcsQkffCNuCOtIay2pGZQo16bfxczzEwT1bmDFlB0qqplj7pivepZBEZn2F9LJmMeWiKWqkcCDqnDjeOlbqmrDSOJ9wxZztMsoLssjOKaVIIZLjyIszwmCtLuuXXcfWL1vqOeJ4QoSXCS+saxo81VKZ9YhkMyUOb5zH4PWmrDPNEEFv0zxNkQ7oQXyMJ7fu5OEb3PDrCynxozpQB4NtUj8wQPWksFVxvSIUaI4IdLzO479/LFo7drHKNhvHolLyI+5iu3YVO+eqc+J+EF6iSk/8tiqfEs8jOGz+kim93uT/XmvLG+3HM0bDjDPeGQS4XuGR3kR27N6Pyu08XEtKyQu2w3KVEjuEeD79MAI/UcyT2Lpe1CrdiAjrbazafpmlZ9IIlObBSS0RborvFWU010+n/7hVjFY25qxrJjm1wpZ5rqSFuXIvohjPpDrKRb1rhMavlXp7+EmCrqixXNeC1aYFRDcGohVFhZQlOBPvuB+t2auZNuYgR61CiBfbXhDj/GmQhbyMjIzMn5YqskMeYrNRk6Mb9mEohHy0JOQr3LDarc26kbvQP+Mn5Il0m/PA2/YAS+fqs27DXWLjnxmmrRd5SmPIfHQB031KbFTfxprT3twIgSJJEVdlUZITS3BEBmGPPCm5twsPk91sNApF30vcl5/cScXduDqNokR3PO2NuXHxMBfPa6CzR4O16/TZsv0cZ85d46KVO3YB2SQXPB3GrUuyItdIiAiNFfTb5cPuBzVNRsB/DqmCvqSEXWGv1hk2bbnPw6CcJkL+BeRFguNOnAz3s/6yJ1t3HeeG8mgOH9jP3tAaJJ1VGe3Kw7VL0FuwikP3A3ESOvWpmJJKDyUh4BL7l29HZf4ZjN0TmwjPfGoybTBWXcSqgQtRO36PS16eOBxdxfktK9lqGohJVj05RVGEWBpwevVyNq9WR/OwIcetvHAOF+K56clX3ifHeztrVmym3+SbnLBKVoxWN0jnYuoLQon1uoWtoRDXF3dx3GADGzcJH1A/xUH9i1y8YcsN5xj8kisbV9KpoyLVj4dqs9g/ZigbLtzioohCpCcKz5NBbpgJR+ZrojblBDfdEoTAzRcBxm0M9fezeNIxzh/3Ev9uKuQryPMy5o7qUDaN78mwqWMZMGggPw0cw0j1y6w+bMm1jbMw1JzNLhs/jMTJZFeUkXJlH0YLJ6F76AwX02qIfD6qoDYvlrI4R2KSvXB45MbZ7Qc5vuEARs6hBFYJzf3sPlXZEGCA19lVLN5+iUUXU/BKfTaTZOxgkgIvsHfFdlbPP8dNlwSyGja+mPpUyD2D9Vk1Bo89wOzNHvinVTT6rDCy6AeF8W48smvsB+dEP9itgYroB1u1pH5gyEVrD+wDs0ktbNIPEkzJvj6BrZtX0k/bn70uNS8dcS5/cJoHG4exW/R37YAqETILH43xwkdzMceXL0bvthd2om829PY6aotEsH9OnTPTezBn0kD6jR/DwO/6MXTaOqbuv8M+nX2YrR3OkSP67A+rV4j2knBXPDfOx2DlCg6IfuAgXP9JcF0josT4y/gZbWTpplMsOBqJR7xohBLRE/xvEel+mSsWR1BZsYQ545VZc8QJi5BksqPvkeR/Bzv/LFyEGZ8GGhmiKx/E7ZQyC7SusfRKGn7NnLKaskxPzJSWsqn/VHacvoW98J2fm4b1qiMLeRkZGZk/LU2EvPperilG5OsoqvTFcY86GoPmo77TDPOERFIyLbh7dTuzFxxBWcuNmKRnRnTrJBVnScC52Swe1In2HYfx2dxL7HbIJq6wlNLkIGLdHfEIShBiPog8R22czmuy9qwHui51pD0pTlJSj0i6txPdhT8xoHsXundvT6dO7WnbtgufdviMz77oQ/fJO5h3IpAHMU/H0ir9LhOu/S1bVecy7mIsJ6IUYcGvoELs7EJSwGUMjluy93QEgbFlLxU/CjIiKBKBjZPxOQ7fj+Ci4TluaQ5j24b1LDaMwCoxh4RHVpgsXcb2OeocfRDKI7Hb0wcPTYX8NiHkTysErjSNoYEKagucubVFCPThs1hvYMdJFw9sD63kwpYVbDEJwFBkLqyuoCzbm0irvZxeO45Zw4cxcOJ6lurfwzKy6SpEERTEnWPHXBVGf6PNgUt+iqk+CvvUJ1MXewWb/XOZ9V0PenTvSLeu7WjfviNt23Wjc5fudB8wmwEbLDnqVNgQmIkzKY6/x5WZC1jbew67rz3AWfz6THgnkDJHkRhwHd15WqhMOY+5W5I4uwJqa+9yQwj5FWP1uXTETQj5hj0UIlaI/2j7C5yZMQuNpZvZZ2GDhd0hDPcuZKaSLoOn7mfPxBFc2zyH/XcDMBfqN7e6kvRrezFdMpY9h05wKrGGsOcGuIV/x4SQ8PA2wTHheEcH43xGm+tb1Tho7o6x0I/NZo1JVAo57t9UyCfjlfJswVLlg0hsJuTjFUL+5X4kPX+5h+OVncz4di0L5l7jblzDy8iK8krdib+9nT3zhzT0g89EP+jYpB/0+I7uU3ex8FQwrnGPp+2I6nqfI3Tn12xet5DxlxM4HdO44TlqSbc9wW2VoSJQ3oVeeJVCeJfG+hCwbQEnleahY/sISxF9NjwpqqBC+NrdnersHj+XLfvPcdbRHNvLKmhvVGbQ/OPMHb+Ki/MHc+LkEQziJIuI8iLc8dGYw1Hlxeg6+GMjVPcTP6l9gZCPE326MEHY3J7QIA+sA7wwO7eV48pTmKdyBNWTD3B1siQ68D63AnN4mNJEyFcK1e7TVMin4pfWvAWqc6Pw2TqLQ2N6s+bQNY4kQ9yzbf4nQhbyMjIyMn9amgp5XYWQl6beltWkEmu0k3OzBzN74jxmqm9jn95ytLavZPjqq6icjiNeWvqvKdIj8pwHRNlqobN6Ej/1GUffwZvYdPY+9+ND8Lp9mktr57F5jToqGuvZunwEiycM5PsJ6szY54RZeDEp4mZaJwmYimAyvM5yaccqlk0fz/RpQxg1cjA/DBjHkKFTmTJ9AdM3nmG7aTS+yU/UH0UPzvBwZVc0laazyDqZ6/miqMoiSkPs8Lyqzem92mjvPY321UfcCiqg8MkpiL9H2hFgd4lr1o8w9S0hreBl8ksScHmUxHvhc1OIX7P73I3JISTCkVDDJWgvEXWcqsJC7f1s193FstGrUZ6vz3WvBIQ0Uci9BqS/NRfyxs2EfDn1BU5Yb16G+pA5rD96m7Nuj7A7IoS85jK2GPtzWSjxBkEkhE/BI4LN92KgNhelebOYtVYH1dPumAXmk18h1TmLghRLjkxfwdwuSuiecsJfcRRBfSb1Kbd4eGUbWxbNYOb04Uyc8CODBo9gwI+TGTtuOtOXbWXZkQfcFLYpVYieLHKiTNk/bjlzPl/HgWueRArJWiUEeEaQHQ4n9DisrY3u/oOcdrjBeUtD1k3TQW3qBWw8kkWN84WQd+C6/j6Wjj/MBQOPJkJe+ksUvmZn2D12PdvVTbifVSR+DSHd77AI1HQZ+Y0Kuwf25armXPbfD8JcRCR5IqhJvbIX44UT0Dl0irPJtYQ/14z5JDnewHzzcnarqbNWQw3VaQOZO2o4Y3ZaoO1VTeITVdhIxYuE/LMhouRMzwv5Z1dLao50oEBcr+xndbc5LJ90AJOonManGsLI5UGkeUjLo65kqdQPpg5m5Mghin7w0zDRD2YsZPomEZyZxRCY+tSzCu8dw0WpM5tWiaDaNo2b0nSrigJKgm3xuKLNKakfHBRBtqEHl/buwWTlEPQP7OFgZHXDCLoQ8n5bFnJ8+QJ0b3k1Ed6ijDRHrq/fxuax2pw0F/4rSfxCc25f1mGq+G1ur4lcnPU9x88ewyC+QciXhLvhtWkuBquWsk8EXdII/5MR+ZcK+Vjws8M/IAT7xHxCw+3xvaKKxsIVzJyzlSMnjmHl5oJJQD6eotM8XtmTihcJ+eZtVZsjrl/6k7kwtxsL9p5jUyAEP9vmfyJkIS8jIyPzp6WWHMXLrts4sVGXG6FxilVrpIX7amIs8D+1ANWx39Hns54M6f8l4xavYLTuffY6lZP+/IRbQSV1FWnkJTzktsF+tKetQvfASW6EOGJsuI3tP3VhaIcOfNqxPR0/bsVHrVvydus+fD3vEDsfZOFXIdVI3JHrK6gpyyM/M1XxkmtinAmO94w5d9ETM6s4oqKTSUzPJbOwkvIm0zHy75/h/uIubF42jWV2KZiJm3N5cQa5Ntu5MK8To3t0olOP0XSad55tlqmkPb55V2aQKD0tsLLDNSiOyLJ6Xv4uqBBsVTFkRLnhYOeOvXMySfmVQoSmURZ5DbNt05jTrzt9f+xDz/Hz+GrETpS32OEclaeQbU9rK6nhCJJDrnJASQvVhecwFYrkyVSMuhgKQs9zfMl85v64ls0XH2EV4sPDU6u4uFWJbWbBGCYLvSMt9VJfQ21VOeVF+RSmeJDouJtTu9cwcfFJVA1CiciVnloUUZRqx6lpy1jcZRG7T93DS/za0IyiLtUi4MkXIjw5hqTE2wT7GXLD6A4XroXj4ZVIYkoGKTmlFJTXUadY9zCJjIjrQmivYHr3TRy85kuikKx1hBFmqYX2sK/p36kTn3/Vn9Ha+1A5Y4LKFG22zjyCibs0Up1BRf5NLh3cw+zZFzh5LqTJKiyS8IrBz/wse8YJIa9mxN3MYiHkMylIt+SY1imU+qtwdmxfru+YzzZrf66KoC27LIuoc3s5M2OuEPJXMMmuUwRPTxHl1oQQfHM7OqN68NOnHenQqQMd27Xhk87f0n76MVbfSG2c/96EylyhSI/hd2E1S3deZcmVNHzTXjQiH0pK6GX2r9yJysKLmLklKlYHetrmzyK1Sxgelw+g1m06ShN1uB6VKSwr7SP2qquguiyXvCf9wJj7d004e9ELC5s4ohX9IO+5fpDrcIx7izqzcfkslt9Ox0J64FSUQraVJufmdGKk1A/6zKTLwguoqm7BZN0wDA7rssO7FA9hosJIFxzVVrBv4RqO3A3ioShTqqkUBJVKQl4E9pvH7eKESRDxivP2wdP+Cuum70ez3wTMlv3AoVPH2OVfhY8wU0Hwfe6oLGXvUjWOOofhKqr65MlUrTC24mVXDZZrnmXR8Vi8EoUjlIiWC7xNgF8Ad7Kqia8tJDfUAtuti9k4ZhhKq1az4eItjrvl4S2ipScxueLpySE8z65h0S4jlhtmEJjRvK3qcuNIOTaJy4u6MUfnHKre4lA/98rIK44s5GVkZGT+xBTGBXJ/+24ubj+IZVyykJYNMkoaca1Oscfl8la2zxnHjB9/YtqSrWwwC8EuTcjC5oNcz1HiYY3FGnVO6h3FNMqP+55WWB7URE9tHeuU5qE6tS8Th3xLryErmKBly9WgQuKFJnheP0u3aH8yUv24+6CMoJ9ZraPI6QwuKzqjsVwakU/BqBAqpC+e+hrjdEwFXXUVVNR1UTnmhLFfScMoY00ltXlCjIeJACEig7yCAnHECkrF+T0RB80oFwI0npT4aEISCojNqqWiVJLoInd9Juk+ZtjqLEVj9o+MnTKHoSpX0DJLIjznRaUlkB1nytE1u9m45Co2wgYNAqeYyvAruBydy9yhkxgw8Tg6dzIJSw0j+rIK17XXoW0fi2WOCDjKEkmPjsYvuEyxFruCWhNczq1l3MgdzFzrjFeaJNeLKUwXwmeGEgu7LkfntKNi9PXpVJ+mCBFV64GnTxJO7mLP50YrJdGYSmbETfaOXcas7mqKEflo8Xs1KaR4G2O2exPbVVRYv2k7umb2XLR24MTSNegu2MDhu+F4ZUeS46fDad3NjFOxRd8iq9HvHpNLlM1pTkyewUZlfU6H5JJSk0JBsjEn9l1m9dQ9mKuMxWz/MpaddOGAXxapWV64HduNxth17D5ki2tpveIV0SdUCUGeegsvMz32aWxGZbkaauvWorZpMYuXLOCnCbtQ3u2CW8YzX+OtFfaLPEuE0XpW7TVD6WYBYc+t3ynZJIbsBBOOrN3LhmXXsfdLf365x2ZIDRaK+5UDrP1sNism7cdYCHnpqcxTWf4YKa8f6Sn+3HlQToj0wYeXUHD3GA+WCSGvNIvFtukYC0evKs+lyPsGjkdV0JH6geYR1p54wLUL+rjpT2KPjg6LjRK4k55CRpApF5VUUZ2xhwvO8YopWA2IAD/bE/sta9gxfgnbzwnBL5yjqtoNnzuXWbf8DLqzVuCoNZo9+gYsN03BKTNZ9IkbnF0i7DxvH1c84ogVJT21r3CuLGOi7Xaweqchy8+lE6JY1kao8xhnosNDcRFGFDGrcNZ40u7ocHXlYGYOHcbw5fpssUlGaPnGQEMgrYITfoJgQ3VW7LNG2bQIEUM3oy43nqQjk7k8/zPm7z3PBn95RF5GRkZG5lWjroa60nQSnI24sGQpmvPXs9feB8eiCoqEuK0qziQ33o9IDwtsLh9Hb8t+9A6ZYh+WTkp9HTV1ZRTm5JKekKn43H5JaQ45mSkkxsYSHx+Im5U5V7WPc/2aPZ45hWTWVAkxUUZ5aQmlKT6U2G/E8tBaFuvfZ/udChKK6p8Rco+RpJgfiQm+OD3MISBU3KtfMlpe4XOJYK0v2bJmDuMvxnIyumHcWxLr1eUllJWUUFJSRkl5FeVlxZTmRBLrdgsnkxtY2N7n1sMgHrn5ExYSSkxuNnH5+SQnZpGdWUCp9Ln+wmiS/O9x19QcYxN77rp54hocgYd/LHHRiZRmxZGZ4IfvnZuYH9rG0b370LPwxjy+nsxmOr6e+toiyvJc8LPdzaaJi5gxYiu6V+7xIDoSf29rbh8UQmnGD/w4ZhVjdzph5JtOkp85zrsmsH3JDGE3e076xRKV+hBvl3sYXvXC4V4UcVHuxPsYcF5vI9Nm6qOy25OgLEmlpFKYbIjuvLVM/Ho7By56Eyd+bSZYFUgSMpqyokd4+cTi4lFN1gvX2i4gL8aeC9Pno/z1PLSvPcBF/FosnZuwd2VZKaWSvUtLKausojAxgMCjazi3bi5qhy+hc+EcxgeWsENLetchgKs+0geoishNzSQtKZeCklLSH5ngsGkS21YsZ+UJc07bXOWWsS5bD9xkw15r3Az34HxxA8s3H0N533mMjfU4sE2LhfNPccQwgEThUApXqRdeUJlHUZAF3hc3c/TgYbbejMAyVPhiSQ6lRY74mGqxdsxsJo/TZI+ROw8zi8ipqhU+WUVNQQT5d7djsXMa41fsYcJ+b2xCSxVTsxpcUdisTgRheSI4stuN+pQVzBiry0ETf4ILKil/foH8RqQJJg9xurqHed+sZvGcSzjE5TUPPp4grafjS4Lok44PcwkKE4d8ST8o9zxD4LZebFKZz4TLCZwVyrlOqmPTfiCCz5LyaipT7pF5R4MDu7YyVf08+8+fxPjiblSX7UFZzZTbgQlkFuSSIfp5lrBJcV4UIec3c3bpWFZtOciWm7ewtjnEpXMGrNptx9ljFwg12cDR/drM2HSRQ5dOYHR+FyqL97BmgxX3wrObvPAtgujSOPK9DmJ7YCETF21nnJYj5t7JpER5kGR5Ggujm5x2S8E5R1pdqoy6YheCrq1Hc/Qgxo0XwcbNSBykKXRScfXl1OSFkmOvifH26YxV2sekg37Yh5dR9KSthBlyYwnaNYvjE79F+dBVDsSLmOH5jvCnQRbyMjIyMn9GKnIp87vK3R2jmNX9Y7p82I8v5p9A2ymaqFwhCJ0vYbRFmW2r16GuewG9qw+565tIeom0qkYR9ZX+3LtyHb2VxzG5eA1PrytcOryelZOnM3OWEgs3HEHr1F1sfJJJr3pWpKeBz05cL2xm5fkA9riDYvbHCxEitD6TwoIMklLKyMquo/bFip+6RAuyro5h+8alfLfLDx2X2heM8DeS4020xXaOrhjGhO/7MuCnEQwZN58xU3aw6fAN7KJcsL1nxYF1p7l0wha/2Ef4OhlwSnksM38YQL/+PzFi7FjGrdrBggN3uXzDEn/DrVzdp4LyBiHmdC9y0dYDt8R8koRIaH56NVQXBRNstoUD0z7nu1Yf0ebtrnze9yeGTprCuInjGD14GCPHLWG+riUnHgjx5GXJo0PTUPnhXbp9/CEf9ZrHNJ1LXPEVgYWfC0Znr3Bqkxrb5o1kzoQhDJ2+msmaVhy/l0GGYgKxF4Whe1FbvpkBoy9z3CxeISOfl5iSxfKoqkgjPUMEMmk1lL5w2L6asiQvHqhMR2f4MDZcsOOyKFAaTH0hVZmUBpzl/qFZKE0dynffDGTQ4BnM2X6NQ55ZhOfmkxnvhOHOE+xdZ4SdR7IQjiEkOWznvOpwxg8dzLff/8SoGULwHr7LRZ8U0uIDiL9/kENKk5nY52uGDPmJH+ftYtlhL2yD8xVTmRTUZkOiFR4G01k1qCu9+s2n/+4ArkvrDipwIt5wHgt6fsJ7b7SnS9+lLDnuiHVSEQX1KeQHnMZ84yAmfNaad9t+zvvDN7L0Uji3k6BUYUARFJcEifbU5OC07vR5ry1tWg+m17zTaNsmEF/wZM7QM2SKAq5hd3ETw0boMkf1AT7Cx1/07EbRD+oyKCjIbOgHOS/vB7VxxmRcGYXmxuX00w5gv+tLMirIoCbZGrujqqwa/SPDhR0HjZ3HSFVD9G6FEZkThK/NDQ4rn+DUcTfCcjIpCDfH7egc1s8YzHf9BvPDT5OYsu4ImmYRuEfEiADPknvHVFg1ciDD+37DoPHzGb3uOvssk4jOq2z0Oen/EymKvIb1rrHM6fkR733UjQ8HLWSm7lG0dDXYNHYQo74fycA54t+24Yr3d+qFbxYHmXNPazG71TTZbhWFtWjeCmm6V20Eed5Hubb2B8Z0a8M7bXvw4ShNlK5Gce/JC7H1VOUGYKciAuUB49h2ygoL4bdZz3eEPw2ykJeRkZH5M1KeRYnrUey3DGbu4F707DWOnlMN2GUdTHhmEOFWOhjMHM7MkfOYv8uMC55CQAhB2nC/y6e+3A3zQ8dYP1qLM3oGODrpc1BzBqN7fUOfPpOYoH6W/fcT8Ct4wahvqVBAAWfwsjjGPvNgLvoLXf1kYenfgLR+tv9ODLRWMnDWCdaeCiGy6EUfBaqmKuE+gReV2TP3O378sgc9ekjpB3r8oMaifUJIRt/DyvIym6bs5sCOa7iGOfLQRod9s35gwjcN+XuK1Gu8CuP23OX0FSPcjsxj39KRDJ+jweJjzlhElTdfAvIJ4vj5PnieU0d7dC9G9upFry970rOnVO5XfPXdCAZOVmOZjhU3AgpIKsyhPOASD3THsWi41Fbf0KvnFGZvOckZvwC8M+PxuWeMseZ8Vg7qSb+vBvPjYj222UTzSIiUaiooiTmP/3khVpW1GLrNh5veT9YN+aepyYsj+bIShqsGsWDrSVQdsvHNf9lSh8ILqsNIuL8fg8U/MfKrQXw/cTfrr4TiIw2Xkk16pBUGK3agOvU4N+7GCC+rpLbQBZ8Lq4Wo60ufHkP4YeZ+dlhEECzsKsnTirjbeOnPR33ol/TvP5Wxm29wyreQ2KZquCYdoq9w/8BUZg/pS8/+yxim5cj1IFFCvfCOfAciDFeiNqUfvURb9OwhglEtS67F5JNbF0e25yHOrxvP8J6inXr1pM8EJeafCcA4BooVJ1tNXZEPXuc2sHtUz4b27D2GnrOPscEwksjcFw331lNT6E/u/fWc0lrEIOXrKF9KJiHvZaL/H6DYiyo/LfS3rhL94BRqZ8KIKX3ZNCpBtQiK7h/muvIQpvbpw3fjN6N0wY+HRaUiUAnG9epxNo/bgbaWPf750mShdLJ9TmG4fiwTv/lWBEaLmL7DGpPIYsVzg/raVDIc9nN1xY9M6v0d/SZpsuaqP44ibil54hzSX6LJl74qu3kak4RtvxS27Td+MpO0drB041rmDhrIDz0G8cPIHWy56Yev2EUREBckUOp+HU97E0x90xVTa6okIV8TQJbrPgxEsD2ksa36TlrNovMhWIigTbEOVUk4mT5n2Dt3FXOH7+CwqZ8iQHgS9P0JkYW8jIyMzJ+RmjKq04JI8rTC0c4cU/M7mDgE4xuXS35ZDnlx3gTYW2JvdY97volEF0iTDB4jVLcQR7H+QTy0fkSIEJPJKf74udtjfd2ImzftsPOIJCirkhcu/lJdAnnR5CRFEpqUT2xePRU/N2j4a6kTUUOhM/YHVFH6cRLz1pzgRGAhIc8NcdZSW5RMTpizEMBmWBjfxMjoBkbXTblu5so9vxghnoWoigvHzc4bP88I0vKkEWBf/O6YY2dipMh/4/p1bti6YOubQmhkNOkBd/C9Z4XlHU8cw3NIkgZRG4/YnDpqK7PICHXH55Ypty3MsbA0xeSmKNNQ1MPEBou7PriFZSleyJVmnpMXTqqfnWgrC9FWlpib3Ob+oxDCcvLJqSojPzOOeK+7PDC/gbGRDVYuoQRmliuWDawri8Tv/DqOTh/EHFU91t7Lx136QuZvpL4qj6qYkzw4Ppvpk9cwarU5130ykaYkv6jZJblUkRNOpIsN9ibWmN8JwSu+tHGqRTll+XEEOnriYhdEVFJho78VUBjnid9tM8yNxD73QghIKXk697w8k6LwB8KOJlhY3OO28NVYUWCzuLBO5C6IIDnAgTs2lhhbumDnnUJMrmidemHbimQKYtzwchJ2tzAT7SDyecYRWVhJRX2hOEQAoW53sDG1wMLMBGuHBziGZRMtjNtQxzphiywyQz3wsTUR7Sl8yvo2JveCcYt8vGrQsxSS7X8TG9XRqM2YwewTLpyIqiRP8bWx30idkNP5jtjuVWH5wMnMX3ua06ElhL30qVcNNdnhpDyy4Z65OWa3ffCIl1b6l9oxj/SIINxsPPF6lEh2leQ3wn+L40jyvs1dExNumrlw1y+VlLKGLzwr+ldGCElu1twxs8DcwRfPxCLFWu3Nz66AytxQIjxEu5mYY2luiu0de257eXLf7SEOllZY3BT9SRzbMzpbMWqu8No6YfWiFIqyk0nOLSdTNLbCwnXZlKf5EfDQAWvRVpZSW91xEX0xl1gRt9bUFlHhexr3I9OZN0eNEWpOXH1UoPClF/fTPweykJeRkZGReYUoIMHuGMYrxrF8viqLT3lhJhSXNOL2O0ikV4+iWPJ9znFJbT6Lxy1j3dFb2ORIM+Z/DyRl6E+862F0Fs9mxuRNaFzxxSm9htIXDULLNCAC2Zq0B/hd0URz6gwWLNXhsGsCfsJBf48HUw3kEWdzBKPlY1k2X42lZ32xiPkP7gfiulCb60nABVUOLhrPrPUnULPL51Gzj0X9OZGFvIyMjIzMK0VVjg9J945wSHMnSupGXLoXo1jW8c886vZSYu6RcEONw1qbWHbQgfOeOYqR0d9HZ0uSsIyKDA/CjDZxfOd6Vhs4csKtlOynbzTKPEtxOqUuR7l3aCVrtx9nw40wHmVUKkaGfz+RXU9lticJdw6hr7ELpY3GXHGKVXwg7D+yH9RHUhFniNHB7axedgjtiz545NU3ftzsz40s5GVkZGReBSozKYhwwcfuGjfPH+eEwREMjp3j1FVrzJzD8Ump4HeYTfGKIFRkeSReDne5cf4ezl6JSAuv/CeORNYleJJ29zS3bttxLaSU4N8+Nf55agog3Z5wD2Mu2Qdh4VtO/ksnZMtQmk25twkBtue59jAc2xQo/B2mxj9PMfVl4XjelvqBIy4+ST8z7elPTm08lal3uGNzm1PXwnALKf6PCWhkIS8jIyPzh0bclmsyyA225cGpTexZOorJP35N7y+68tlnvfi8z2iGLtZhw2UvbkeXIi2g8Z9xI6+mvLiY/OxCiksqG5ah/E+ksoSqwiwKiorIq3p29ZzfC+FRdcVUl+eTU1hGXom0PGnjJpnnqa2mriSXsoIccsuqFN9k+Nf1yYZ+kCf1g9L/4H5QX0FdVQEFBUVkiY5Q9q/pCH9IZCEvIyMj8wemLjecDNdTmOmpoq60ksXLVrF6tRKrls9izuh+DPq8A107fk2P0aosPuqIZUwZKdX/KWJeRkZG5j8bWcjLyMjI/CGpE//LJ/vRZW5tnYbK7DlM17iCjlUYASk55ObFk+B2AWutsSzo1ZJP3vmUD4ZuZNG1SO6mS5/Sl5GRkZH5syMLeRkZGZk/JHnif864n9vMxrHTmbV4H3sfpOPf7JFxFoTqc0OpO9+9/b+0aDmEbivMOemWQ7Ws5GVkZGT+9MhCXkZGRuaPSFUMtcH6XNswmcE9JzNszj70b3vg5B9IQGAggYrkRMD9PZxa/TXft2xBixbt+N+vtrHjchCV/7GTZWVkZGT+c5CFvIyMjMwfkYJACm6twWB2V7pIn4T/9Fv6DhvB8NHDGTFsKEOHDmPYiJ8YNbQXfTq/wVstJCH/Ji3eW8gW/QdUVsuz5GVkZGT+7MhCXkZGRuYPSH3qIxLPz0J79Pu0a/MB77T7nM+//obe33zDN0/St3zTuy99vuvP9z8MYOCP0xg96wCG5v7U1MhCXkZGRubPjizkZWRkZP6A1CY4EX5kHOsHf0q7zyfSf6k++sbW3LKzw+7WLW4pkh237O/gcO8BTi6uuLn74OUbQ2p6IfWyjpeRkZH50yMLeRkZGZk/ILUJ9wk9NIY1/TvTrucKxut54fFrXmAtzYWyAmQlLyMjI/PnRxbyMjIyMn9A6lNdiTszHY0Bn9DukxH0WWPMpRTFWjYvpTwpltQHjuSGhFBX+x/zmVcZGRmZ/1hkIS8jIyPzR6QggHwbZfQnfkyHt9rTso8K8y4G4pBZ/4KvNwrRXhdD8H0rbhy6jqu9L9XVspCXkZGR+bMjC3kZGRmZPyJVidQFH8FMvTcDPniDv772DR0m7WeTUSDeGeUUVVRRWVVFVVU55QWh5IYYYnzpNFoHHbC4n0iVvGqNjIyMzJ8eWcjLyMjI/BGpL4ECDwKvLGdDv7dp2+IvtHj7a7oNV2Hp7gucuGGLjcNt7jkYc/PULg5uVEJVU59tJuHcjyulRv4glIyMjMyfHlnIy8jIyPxhKSTP/wa3t4xgyVdv89Eb/8Pf/uc93mz3LT1+nMzEOfNZtHgmU8dNYPjwZSzdeYPrYYXEyyJeRkZG5j8CWcjLyMjI/IGpLUoix+cqdnvnovxTe3q+1YK/KD7+9Df+7522fPTZ93wzeiUzNa9zxjGG6NI6yhv3lZGRkZH5cyML+d+FKuqKksmICSYoIIKAqGzSC+v4181QrRP/K6U0O5GUiBBCQ2KISMonu7RGeuXtX0JdRT6lGdEkhocQEhZPTHoh+dUveulO5nlqqS3NojA5gpjQUEIikknIKaVYakbFduEpdVVUlxdSmJ1KelwYcVERRCXnkFJUR1lTI9fVUFdZRFlBOpnJ8cSGRhEVlUxKfhml0mbxX1V+KlkRAYQHBBMal0VqidxOrzz1uRRE3ObhOQ32Lh/HtJ++4/tvv+XbfiMZNFmVVQcsueabTWyFwptkZGRkZP5DkIX8b0ZI59JwkpxPcmPvOtao6KKq74xtcNG/cFSsCirCibylz9m1C1m2eBsqR12xDS9UiLnfn3qqkl2JuKmJ/uoFLFyuy7ZrXrjm1lHYmEPmZ6gvoyzcikenVdi2dAkL155A3z6SICG6GnykGsrSyI525ZHFSS5sX8q2dWtYf9SOsz7VxBYrMjVQmUdxkhdhTpe4eUgLzUVqrF9/irPO0YRLm8V/hf6WPNBTZfeatWzQM+W8WyoxssB79akuoCQ1nNgA4ScP7nDX3g67247ccfHHNzqLNOFMwpNkZGRkZP6DeHWEfGU21cmehLhYYHrTCCNTC8ysb2FzS9zMbK2xtTTB3Pg6Rtevc/262G5sLrbfwd7ZB/fgBGKzyij+XZVMndDTKWRH3MHFcD9HNRajsnwJ01fuY/0RR+y8/EmKfMDDW6bcMDLB2NwaSxu7hq8y2tlga2WOuYmop5E51228uR+USUbJrx03FXfsEmdcD05iecfXePeN72g/+xp6zlnkN+b4famnPPgaLprfMOmTv/FaqxF8p2bGteRaMhpzyPwM9QUUOO/FZHF7vmv5Nq91nM+kI27cKQGFRq8tpSrNjyiHo1zVmMDcr96ie8fOdJ13HJVblQQoFg6XnLeC6qJYEj1uYK23kLVDe/D5653p0ksJJUMfHoocpZKQD7TGRV8VnaXTWbJiHcu3nuTQTQ8cY/JIF3GnLOhlZGRkZGT+HLw6Qj7fn5L7Ozizdij9v/qCL3r0pEfPXvTq9SVf9hJ/9uxBzx5f0OOLHvTo8RVffduP7waOYvg0JeZvPMp+I3ecYgvJ/r3mnlSnUB5yGeu9C1gyegwjJquw6og1591iCI1LIivOikDD1ahN+p6eok5SfXuKuvb6UqpvT0V9e4j6fvHlIL4Yv5tlx33wTP21Y/iSkHfl0dHZqPRsQ7sPf+KLxTc54ppNQWOO3xch5ENv4rZzILM/a02bTyfyk6YVN1NqyWrMIfMz1BdS6KqPxaovGPLJx7TpuYLZJx/hWCqaUdpeWURhlBuhJtu5sPJbhrdtwest2/L+tGOo2FURpGhUaRJOPqV54YTcv8K1jWNY+NmbtGnRilbdVrDomi/OIkepyFdTlEFunC+R909jemAFqyeOYszYVSzVv41RdBUZ8vLiMjIyMjIyfwpeHSFfFE7ZoxOY7F3C7NH96NepJR8qXvhqTG935+OvRzJ41EQmT57AxNGDGf5dd775rBOdPu/PV+PXsniXMZdd44kpqqGysdh/HGk8M4P8ECNu757BimHf02/YciZrmXPZv5AkRZ4aKHYj9tYe9q+dzpjvu/Nlm7/wZtP6/uV9WnXpS9/R8xmz5jQ7boQSnFmh2PuXqRbiL44E50uY6mqitfUoOoZ+PIgr+RdN56mnOt2POPvDXNqtgabWWY7aBONXUNcwoizz89SXUx7nSKCxDgbbtqGpa8SlhwlEVUlTYQRVZZSkRpLifJR7uwYzvftfhZDvxAfTTrDeoYpQxfwlScgXUV6SSmKwM3f3z2VTnzf59L/eo1WP1Sy+HtA4It+E6liyvc5hvHUii4f2p/9oFeYdcMI8qojsxiwyMjIyMjIyry6vjpCvraCuNIv8jHiiHplhtXMyq3q24CNJFP+9M2+P1mHZGV/u+kYRGxtMiJsZt0+sZdesLxnw6Zu89saHtGw/jmFrL3LKM5OYWsXs9n+c+nzq0yx5aLCAJf360Lv/YuYeccIwoohMocqelFlXQmVhOhnJQvBa6nFx2ZeM+6QF/6UQ8h15/dtVzNMxw8wriqCkbNLyhNirbnj18ZcRwUR9FVWl+RRmZ5KVmUt2QTmlVdKrjv8a6mvKqSrOJV8cLzMrj9ziCsrFyf6rjvfnol40VykVhdnkZgr7ZReSX1pFpdSMis111FZXimDpLilGC1Af1JI2rTrx0ZRjQshXEvzkRYRa6uqqqSrJIMlqC+emfMS3r79Pm56rWXTN/3khLwLK+opUCsMuc+fADOb370ffH1ez/JwXdtn1IiyQkZGRkZGReZV5RV92zaH07k6uzXqf71oKYfz+97RTsmafl7Tq8mOKqEp0xddQnR1j2vHFXyUB3ZI3vlzMGH13TGLKKf6Hl/Kop7rAn1hjZfZO7EWPbuPps9iQ0/6lpDbmeCG5bqSen8nWgX+j1d/+lxbvjqbbUhOOu/2rXk6VeSUp96H49hp2jmpD29ad+WTK0WeE/GOE7zrvw3RhRwa88yHvCyG/8JrfC4T8Y5Io9Dbg0vzejO72Nd/MOoyaVSJh/3gHkJGRkZGRkfkD8WoK+bpC6j0Pc1ulK0M/EgK9TT/aLTdHx7WOzGbLNtRQnuKCh95U1n3RgrbSaPg7/Wg14yJbbDJIK2vM9quoF8fNJtf/HIZLejO+W3e6TdBj2Y1Egn/pDdMCP8qsV3FgfEs+eOsNWnSYR99tHhiHyEJKpgklj8i/tRqtkb8g5GuLyb+vw80FHfnhnY9+hZCvpz7Xl7jLC9kzpivdv5jG98qmXA8toEDxSEBGRkZGRkbmVeTVFPLVQtn4HsNx4xeMaCcJ+e9ot8yUPS7ViiXYmlGZTK6lOmfGv8lXb4q8f+lCi+/2sPRsBFFF/8DkmvpKyHchwnA5Kr3b0qX9YAZuv83J2Dryf0kMFQZSfXstBlNa8VHLt2jRbSkDdQKwjJRVlEwTij3IvaXM9hG/IORrCsm7twej+R3p/6uEvEAEobXhR7De9D0D2n/Opz9sRNUiFq8ieclCGRkZGRmZV5VXU8hX5YOPAffUP1es8NGiTV/aPhbyz46yV6ZTcnsLhrPfoU8rkbdFZ1p8u4NFJ4MJL/wHRsRr8qgONMBhcz9+at+Jj3qvZsXNUNykJd0bs7yUfH8q7VU4MkkI+beFkO+6mAG7fTEP/2dm6ddSV11ORVEehVnJZKTEE5uQSlxaEfll0ox1UWZtHsUZMcQEB+LvH0hgcAghoSKJfwf6BRMUmkhiXpniRVXFHPeqQiqzokmOasgfEOBPYFAIQXGZxGeXU1JSQlVJDgXZqSTHJRAfm0JqdhFSHKSwYF0NtRXFlBVkkpuRTGJ8EnEJWWQVVVApclSX55KfHEVcqDh+QBCBoTFEpeSSWVqrmCf+ckS5JVli30hiQ/wJ8PHC28sbL28/fP1FOeK8QkODCQkS2/y88fEJICg2nSRRsdKXTt6vo06UWZgcSkyoP36Bwh4hoYSGBBEs6hYWkyJsU0F+Ub7IE0Z8qO+TY4WENBwrMCAEn/A04rIrqaiVDlRCdUEiydGhBEr2DhR5gsMJiMkkMauEshJh3+JscjJE2TEJJMSnk1FQRok492Ye8K8U8oiOUfaAgCsLWf7VJ3TqPJpBOx9wJrxG0Y6/SH2tOMdUcmJ8CffzxNPzt6QAvAMTiMssbvJRLBkZGRkZGZl/lFdXyHsbcHf9C4T8syPyZYlkmqhycsz/0Usakf+fz2nx4wFWXo4mTlIRv5L6sgTSLdZwfOIndP+gNx3GGbDPNU0xN/4XSxFCvsJuDYefCPlFDND2wSzsH51aI5RffQnl2aLuXrdwuraXU7qbWLP5MBtPPuJeuCTjSsQ5uxBkvoOdCyczYdRYxoyfyMRJIk0Yx9iR85mtdIyjzrGEiNwiDoEsHzJtt3Nm4xQmjhb5R49izNRFzNhtwcHbCQoBm+Zjyj1DffaqabBp7UEOm3riXlzfsNxlZS4lCb6E3r+K5Znd7Niwk/Ual7l4P5SI4hSSI2y5e3Q92kunMH2cqMcsZVboGnHSJZUQ0ZQv1vJCcBdGkeh8EQs9FTQWTWbaqJ8Y8dNPDBk6kuGjxblMmMikSROYNH40Y0YOZfioOSzUMeZ0QDlRL4uu6quoCLPB59RydiwZxagxExg3cRKTJoxnwpjpLN52kcMuybj7ueJ9bjUHlUYwetS4BhtObDjW2IlLGKF6jQP26aSVShYMp8DzKOe2LmK6sPfYMSLPTGUmaplz1CaE6EB3kjyuY3FKlx3KGmhsPs1ZpwgCxK7NhPe/VMhLXppIkuMu9IZ/ytcf9OLTGRdQv5VNavmveDJUW0qe5zXuaE9EbcpgBg/+LWkOoxcYsN9SBEZV9b9hBSkZGRkZGZn/bP5EQt4cXXfIbcyioDKT3EBTbDWHMb9jC96T5si3Hkz7Fabsdc4lu+JXCBgFtVTneeNzcDKqvVrxYdtxfL3ShhshBb88Gi/xewn5+lrFORUlOONlroPBygFM/KYDLTuOp9v8m5xwyRNyrVgIeScCjFRQH9GZLm+1aFwpR0pv8NqHP9J3ziF0HaMJEkUqhHymFxkWGzg6rwvfvP9XXnvtTf673RB6rr7CLuswPN0d8b22Gf3FAxjw/qd0+Ggs47ebcyOnlkxp/9J4sgMssDu6Eo3J3/D1Jz34pOtcpm4+JcS8ORYm+zm4ejzzf+wqgqC3aPl6a979YhpD1ptxyi2LtOr6hpH9x1QVi9P0JMx6P6dUJ7NgeD9+7N+PPv2+47tvuvNlp3f56LXH5yTSf7XmrU8+p+f3E5mldZ1jvuVEvGwdTknIh5jzSG8ca/q/SZv/elzOf9Pi7a/5askpdt5P5KGPM4+Oz2X3uPfp2rIFf318rP9+j9c7jaX7gvPo2KSRUiJZMJR8Vx3OLP+Gvm3+j//56+u0+HgYnZacQ9vEC5/7JrifUUZzwtd8+XYnuny+kEVnXbEXztNs3f9/qZCXKCPX/xKmi3sy6uN2vPetJjMNgggsrPnlYLS2hFz3i9htG4HyqD706fNb0mQGTT/AbpNAAmUhLyMjIyMj80/zSgv5e+pfMFyaI9/qGz6ce5ltd0pIeKxkypPI8b+B/cG5rBr4Ie3+VxK0rWjdbyWzzwdgm16NYibKr6KYsjQrbNf/yJQPW/N216UM3OnF3fhfue777yXk66pFVVIpTrqP960d7J3fk37vvUGL1wfxyUxDjrpkCWEuyqzJJD/uNm6X16E5qSu9/tYoQv/na3ot0EPLIRKPzGKFiFSYoCKXiiQPgs+vQG96dwYMHEWvhcfRMPXHOzGJuDB3XE6tY/eY9vT8y//yxpvDGKRpgWFWDVnSeHppDJmhVlgeWMyafh/S8X/e4f/eHczXY1eitmcXuscOs+/QAfT3bWDj/IGM6Pw2rf63Le/1WMncwy7cy61pstqQ0IyZ/sSbbcRg7rcM7vENPYYsYa72BQzMb2Nlegbj/fNQHd6arv8nnZc4/zYT+GHZEY6aOyq+4huVV/sz00XqqC1IJsvrCrd2jmNJr//mfYVA/5i/D9Rk/plQHJPKyM7LIifSAf9LK9k9pW3D+xUt/i4E+gR6L7+Ink0EYanllNVIFiykKs2NWEMl9s/6ih5fCRE/UYd1Vx/yMCaWsEe3cNg3F9W+79K2xZu88+lcZpxyxU64TzON/i8X8vWURdniptmPBSIYat12LsM07uKQVfnL3x+or6EqJ570YGd8ne9y9+5vSa44ukcQmlxAgTDfr+6GMjIyMjIyMs14pYX8/Y29GNHhv2jx93a88d1SxqufYN/Rs1w8bcAx3Q1sWzqUKX0/pEOrt/lbm8/p+N1CZu82xyg0n0ShP3+9gEijMOo0Fxd+xYCWH/PWt5sYfyIaj7RfM7lY8LsJeXG80jwq8wNJDD7NebUBDG/9Fn99fTAd59/ghGtmE0Em/lbgS5jhGrSHfkiX1/6Lv384lqH7HTEpekZAKqim4MFZHLfOQmObPhr2KXhkS6WViEMmEGSiw5kZHRnw2v/wVqsxDN5mg1FWLdmSkK/MpFCIb/drmmgP+4Sv//4ar7cZzJcT1rPx6HnO2zph5xNGUFQA/rZ6nF/SiyEt/5fXX+vH1ysucjyqQtEektCUalYQdBmbNX2Y8NGbvPnRKL5eeZ3zgUVkSFmkud4Z9/E6uwC1AW34+K8f8rcOK5h6wBOPXxlXKajJoyT4Cnd2DGJKJ1Hfd77iw1lX0bhTRrriMYWEqE+uB9HGK9k6tA3t3/qY//1yA1OOhOArXLAZ1YXUPzyAs+5slqkfZNnlUJxTRYAk7JedHIzX6TXoDHmX7v/9Fu92XcysM4+4UyktktqEf7mQF7smuRB+aDhqX73FR62G0Xf5da6K6DencbuMjIyMjIzMq8OrLeQ3fcWoTn+lxX+/zX9//DXd+g7hh+/78sPX3enRpQMd231M2/Zd+LTXUAbM3Y7aaSeshIhPr6hrPpXjF4kiz3cvh6d1pVfL9rw7WJu5hun4/drPY/5uU2uk6KOGeiFCqwoduHdgMgs6tqJly0F0mn+dYw+bCnmJSqpDDXHXHsysz/7GO2360H3VNfQC60lotlRJLfXViQQaneSCykYOn7XGJrOWdIW4rqO+too8LyF613/N5A9fo1WbMQzStOJ6Vh1ZUpb6amqri0h5eJJr87sy7N2/884nExi03pDLoalE5xdTWF5FZU0VVfF3iTg2CdVv3uD9t7rTYcZhdniWEqKIiaTQKobEBzs4MKId3f/3I/4uhPOMY/4ENhOzReT4X+Cm0jeMfOvvtHxjGP1VTbmeWc2z+vrliJOrCiXZcTv7xnWixzsdefcHLeadiyIor2mIV0hJ5DVM1nzHmA+FrdvNZNBmB2wSy5q9qFpTlETcNW1MNJXYdf4WZ6OqSFSM1tdTU5VH+m0dDGe3p/+b7/Je1yXMPO3xbxHypHuSdH4q2394h7bv9OWLOSc5ElJIQuPmV4F60Q9qa2vlJCc5yUlOcvq3pbq6P8bz5Fd7as3GXozs8N+0+PvHvP7VNIbMV0d5tTIqKxazbMkylqxQZfUmHbQOXeWSvR/uSeXkKsTpP0hdINkPNdkzvj1dhOBrPVqP5RZ5BOY1bv8lfreXXR8jVHitJ96n5rHmiza832oQnYWQP/qckBeUBJF3X519Ez6h6zttafndJmafjcbl6bCzKC6ZmhRLzI7rs0H1AmeswkgUPzedu1wdaYHXzh+Y1+Ft2nwgCXlLhZBXzJFvpCjgGrbKPRj3wVu07jSPcXtduCcq1CxmKAyk2GIF+0e2ocN7Xfhk4l42PijGT1EdqXHCiHbYwLbv2vBxi/b8/TtdlK4nkPZMu9VkPMRr91CWffQX3vvvb+gx/wzHYgtJbtz+6yilMsmGexqDmdleCOy24/hezYKbUaXNAoKa/Ac82D2Oxe3+xvv/9zndJh9gt3M6kaLODdXKpSzNBSvdnego7+bMrUD8xbanCyhVUepxFBulbgx9rzVtuv0bhXy2L5nX56Mz9D0+fecLOk05gLZXPuG/1C/qKiiOdMLfaDfn9mxm8+bfkvTQ0rfGzCNBBDv1//Dyl0lJSRgaGnLw4EE5yUlOcpKTnP4t6c6dO4pV/f7dvOIvuzbOkX/vGz6eJ33kKZ2QpGyyszLJysoiKzuXnLxCCorLKKusofqfEfGSVKv2IfP+erRGf0z7dzvTZvwhVtkUEtzsTcWf4XcX8kIBVnngebJRyL/3M0KeHKpTTbHdMpQp7d7lrXeH0mvJDU56Zj4Vq5muQuzv4qS+HisPeXLDs+i5FxArw8x4tHOAEPIthZAf+0Ihn+97GeuVXzD2o3eFWF3KJL2HPBDKsllZBQGU2KzmwLiP6di6Cx9P0GWDUxF+T6bFJJHirsfxKd3o/cZHvP35aqYccMc9p6ZRNDdQEWuP85YfmCvE9XvvjqCfignXk0r5tQ9JHlNfIIKWG8vZO6yNCHS60G7kTjY6pOD7eLi9Po+KFFscjixmRe9P+PxvLfn0m7lMPuaDSWqjWK/zJTvgDPpaB1izUQREbinNBbpolWJ3A6yVPhNCvs2/V8jn+JNjsqQhkHq3K+0m6KDpmkvgLw0s1BaT7XwCS9U+zPuuE506/ZY0hJ7Dd7L5qg++lfW/7oXxJjx48ICBAwfy2muvyUlOcpKTnOT0b0mrVq0iLS2t8c707+MVF/LdGf6JEPIf9Ke9sh0H/X6FkPmHEfKxyouMO2vZOvJDPnm3C+9PMmD1rWJCnhVYL+N3F/JC+lS68+jEXFb/opAXx6iKIva6CvuGtKbz397n3b6qLLkajHdVwxr45QHm+OsrcXDvQbY7pOOY+XzEUxFqiseOAcx9qZCvI8/nElZCyI/5+D3afLaMyXouPCipbS7UhC1KbNdwcPwnQsh35ZPxOmxwLMTvScWLKY6zxW3/ZJR6t6X9JwPpNesIuo5pRD2JCNLJdNrPmRkd+L5NG1p9rcrUw7645Va/4Px/gepsKkMOY73+S4Z82JK3usxg6EFvbgiRXi1Ffjk+5HqexPS6DqqrZjGx6wd81f5beiy6yvaHZaRVCPtmmBNjJgK93SdQPh3N/ehnPmZQX0aR2xGsVnzGT/9uIZ8bQJ7FMg6MaUOnVp34ZJw2m5xz8ReBy/Ot3oQ/0Ii8tbU17733XsML3HKSk5zkJCc5/RvS6NGjSUyU5i/8e3nFhfzj5SelL7uaofOwloxnh5J/M0LeVHuTeVeVbaM+pO27nXl/4hGUbYWQ//81Ii/Nja8so6a8lPKaGirFf3WVHnj+KiEvqCulwv8s9zV6M77d//HmRz/x9TpLTkeVkVmZSaLDBS6vXc9+vauYxpcS27hbU/4xId+qYUR+vzNOxbXN65TnT7G1NCLfKOQn6LLRsaCJkBeUJ1HkdxrTjcOZ/HknPvtyAiM3X2S/rS8u3g8JfHCWazuns/D7bvT6ciwDVI056JxH+j+s4iWE6C5xIujKfJR7v8cH737Lp7OusPNBCWnFBZT6iyDn2l4Mb1thYHqRgwv7M61TW9r2UWH6yUBckjNIf3iOe3uWscfgGvs9Kwh81i/+UELen1zzpeiNaS2EfGfajd+NxsNcAn5JyAvq62qpq6mmprqKqqrfkqqpqq6lpq7+F4/5Itzc3JgwYQKffvqpnP5/pQ6d6Ni5K10/60737p/xWddOdOn4KR2ebO+o2N7ls8/p/vnnfN69G5916UTnpnmaJpG/Q6cudOkmypPyfy6V2VmU2YGOzfJ2aDi2yNu1q0iizI4iT7OyfnMSx+zchc5dRf27dKZzh0+fqUNDng6dxLaun9GtuzhHYYPu3UR9Ool9Rf7meRvzd2yS/3Nxnor8wk5P8gsbdBTHFTb4rNEG3bsJG4gym9tMnK8oq1PX7oqyPlfkbZpE2Z91o5vC3mJfhW3FuTyxrUiP20M6vrBlZ1HWZ1JZ0u/SMTuL3zt2aqizsEVXqX3Fby9su98hdRDH6tSlq6iH8AFRp07CJs8fSzpvqa7CNx7XVeF3z9rn2SS11eP9JH8VfiudX4fHbdLk3EV5Cpu9sJymSdiig2iDTiK/wlZNt0n+KJ2PaANFWzfavFnqrjheN9FOXbp9TtcXtmND6v6ZqK/wAckmDeWLdpH6ivBNyf87/e7+/zg16QedX9YPRFJcC7qJa0GDX3/+WRe6CZs8re+LkuSXTa4hUn8XfvfYX58tr6G9ni9D0Q+6NPSpBntJZTW05+PrSPdm15EGH5L6jqLNFeV3EzYWx5ds3Wjz5qmhrT4TqUs34aOdhc1f6J+fKgamMjIaluH4d/InEfJ9abvUhN3OVaQ+Mxj62xFSo86f7Acb2Tn2Ezq804nWYw6y3CKfoP9fc+TLyqiKCCQ9yI/Q7HxSqaWiyhOfk3NR6fErhLxEkRsJlsvZPOg9Pn69My0H7mHVlYf4h9vgYmrAprUn2HvGg1Dpq6iNuzTl/6uQl14jrYomznYvx2b0ZeJXXfhq0E/0GT2BUaOGM3bEAAYPGkL/4QuZsekSBo4JBOfUUf1PvXci7ZRJhps+Z2Z25TshjFv1UmX+KReckgJxvWXI1b0nMX0QgmesFz6n57P1+w9p//FA+qw+jv7DhxidP8mRFRs4esEee+ETmU3fgpX4Iwl5aY680UJ0h79Hh3c/o+Pkfex4lEfIP6Oo/01kZmbi4ODAjRs35PT/KxmZcNPMGitbe+zsbLllaYqF8Q2Mnmw3xtjcGstbYvvt29y2s8FW5DFrmqdpEvlvmlpiYX2LW1J+e/GntfTNCSOMm+U1EnlNMTG1wMpKJFGmyU3xW7M8vzXdFOdmgZmVNRbmZpjfvPFMHRrzmJiLPLewsbuNvaivnY2oj9lNjI2ezduQ38hY5Le0FfnFdeG2nchvKfIbY/IkvzFGJhaYW9s12OC2KFNhA3GsZmWJ8xXHNlUc20Hh+w3pNg4K29lhf8sGG0tRd2lfybYmwrY24piNeaX2uGVpgplJg93NrMQx7e3FvuJ3azMszEwwNhZtfFPU2VyytfSbyPvCc/vtychYtKOlFeaWop6izqbiOM/7ibChsI9kc1tFXYXfSfUSPvJCn3qSpLaS7Gor9hM2uGXVaHfxu9Qmj8uTbGJlKmz2S+VJSbTVTTPMzITfizY3EX79dJvkj6aYWlhjbS9840n7NEmi/W/bW2NjayPaxR7rW6JNbr8gn4PoP7aivqbiGE9sL9pFnI+lpbnwfxNMjX9v/3+chC836Qdmoh8098PGJK4FxuJaYCldCyTfs7XE2lzYV+R/Lu+TJGx8U7S5uEZY3RJ9XbSlrfB1c2PJX5+WZ/+4PMnGz5Unzlu0n4llQx9U+L+DyC/2sRX/thO2l64jUh+yfHIduSn2sRB9R/J3kV/kdRB95dYtcXzRdx73j2ZJ0Vbi+nVL2MHGStHmpi+xhfSl8vLyf2oE8Xfl1RTy1ULZ+B7DccMXjJDmyEsj8svN2POw5p8clf05JIUTRq7XLvQmd6L725/Scsge5l7PwP/XTsguDKTq9loMprTiY0nId1vMwD1+mIc/q/heRD11+cnECed8cMMSx+g0xYuo5XW++J+ah2rP9/mg9WC6LDTiuFvWc3Pbn5JGcdRlbq75jhEftOaNDyfw3YzNHD6kyuETe1mm78LJ+1kUVr1Y0Ulz5D13DWRex5a8/+F4Bm+xwiinvmHVmkbyfa9go9yDsZ9IU2uWK6bWOD83tSaAUts16I9vS6c23Wg7cS+bHxTh3zRTdRm1hWFEO13hyo71bF8xlzVK05k6eQTDBw1m0NBJjF+sheqRO5j65ZL2z85QakJZ/G28dUexokdrPmgzgO/mrWfnzVPsOmXIdj0n7vjnUlqRRJmfDleXfknf99vS8fsxTNq5gznqh1FSusg121DFy7bPTxWpoMTdAJuV3Rna+n3e/2wZs88+4p7IWNyYQ0HJI/Lt16A18n3atelM22nH2XC3mpDmE+4V89ULHHUwXtiJH975mPd7qbD4uj9uYtMvxbH1GV4kXZiO1g8tadfyKz6bacCBwAJiGrfLyLyYMuoL4kkMDyAgOJqozAoKnr1UFKeQE+ZFgLsnnkGJxBbUNe/7zRDOX5pKRpQf/o88cfeOIiy5mMIXBuMib1UBWVkFZOQqvpTx+1NVQk1GEvl5BeSL83rhlbk6j9KkEKJ8PfH2Cyc4pYjsn72EF1GSGkGUnxfe3qEEx+eT89zFoYDCpGBCPR/h7hVJcHIpRS+6BFdmU5YcQFSQF4+8fPB65M4jVxdcXd1x9QzANyyZhPzHgyaiUhWppEcG4e8h6urpgbdos6C0CvIl49XlU5YaQrj3Izy8IgiME+chrtMNbzPlU1BYQFJmLcW/+9PtZ8hLpzQjjdyKup+5bhVSmRWmsKGXfwyhmc2/OfJyiqlIiyTGx58A/wTihW0alncopjIjVLShF54BcYRnifNU/P5rqKKqRtT1hXYppyInlngfd7wfuol28RDt5ImXZGN3V1zd/HD1jScmMpa8GB/iAx7i7uaKm/B9Dy9vPD3c8XB9KPbzxicilaTShtZoQLRqZS7pWaWk/9rBw3+WyuKGfpBfqHiH7sVjY8JXKlPIihIaxMsfn6gckkQD/qpxtNI0siICCfYMJSRG9IfH/UcqL9JHlCd8OTqPlJfpuOpc0a7BRAd7C7v54eURgL+nD6G+bvh5PcLTP4qIjPLmA2RVGZQk+RPs54GbdxBuwXEEB4UR6emOf7O28sBDtImrm49oqxhCgpLIiMugXJo++wfn1RTyNaIr+xhw7/Ec+dZ9+WSJCdrOVaT9S4KjBArCDDg9twd93vqEN3prMOF0HI/Sf+UQcGEAldKI/OR3G0fkFzNACHmLXyXkMyhIcMH8xCVOHbblQXgW0jvStfjgc3IeKj2EMHzvsZDP/hkhX01dgT+hZxawbUBrOrzTnjff78uPg4exYOs+1G3jsReK+GUvBFeFCyGveNn1bSHkxzUKeZoI+XrFy66KEfmPhJDvtozJB4SQL33mZl4QQJlCyH8ihHxXxao1m5yFkG9S8fqcMLIfHOTmYU1Udl5hz0VnXMWNy/3hfe7fucude664+ESJm14Jec+r5n+KusJQCu3Wc3RGF7q/+wFtPvmCIXMXMmWXIZuM03ik+GaAuDwUW+JyZBqzurxHu7fe5dM+P9Btpg4zdTyxCSx5yXzvRiHf+LLr+58tVawjLwn5Zu+7S0LebrUQ8q1pK4T8J1OPoX7nxUI+/74Q8gs68kPLDxUj8osM/XEVm35JyNckPSTi8CjWf/mm8MWBfL3kImdji0WYJyPzc0QL9zzORc2FrFDejubNKO4LUfH0CphHvvs5zDdMZ/mYiUxedYSddomNq1G9CHGDDL+J9YFVrJoyjUkzNFA/5cK99PoX+HAM2RF3MLx2n2s2caT94mOnf5yqYGfCrp7G4Z4HrqL8JwsBPKGO+iRH/M6oo7NoMrMXbkDpmCM3I+vEmb8IceL57vgabmf3klnMnq6C8n4bjMPKm1wzxZlmO+B8cg1qUycyZspmVh9z5W5q3fOBRPJdIq8oo7NyHGPGjWfsmNGMGTmCkWMmMGbqMhaoG7DfKhL3HOkCnklN7HUsdiuxZPRYxo0dzYTVeqgaxeGWVEBF4i18z69h05zpTJi3mzUGHth4p1FcEkt1iRCYro6cMQzHMeDlYdhvpiSZdKvLPDS6yZ3YIiIbf26O8K68+4TcWM+ORdOZsmg3atcicPzFmQxiv1QnfM5roT1P+JfyWU67Z5EsDcqVOBN0ZS1aC2YwZck+NhrF8PBXDcjliltoCKHhcTwUN6vs59R/ODG39TkydwKzR4xkxEjRPuOE7ceNYfSokYwcu5xRC46wf6sud3Vmc0x5BBNGi9/HjG1oz9GjGC2154hZLNx+jTNBVcQ1liz5f1niXcxMXLlslU7Cr4tk/ikqA50IuXIGB0cvXIV7vvhQSVQGnOLm9jksmSHuZVvNOPaonNSXaIenJJHtdp4bGmtQmaGJxpGHOOZJX3XPpCTgJMZbZrFoxgrm7LDmjG91k6f9Tch6QIKJGntXT2D02GmiHwjfn7GYzcsmsGLWWKbM3YjaOXdui+ZquI6Im2y6NcEXlFBfOI6RM1cxSl2fNWu3sn3yeFaIthr5XFstZNS8fWxacxRL/Uv4+UYqBk9/8fT+jbyaQp4Cah7uxXxpOwa2FkL+7S95d+oFNtuXkPIrtfU/Rr6I6IwwVf6e0UKIvdlNicE6/jgm/Mohi0Jvcm8sZPfQ12n9+mu06LCA77S8sYhu3P4yKlLJi7yB03Vt1mueYuPRYDwTH0tFV7yOTWdJ51a8/WY/Os64zGH3vJ8XclW5FHsdxEqtJ8M++T9atGjFX9sMY8TGy5wNLyJOeOrLnLU2yoSHm/sw/cO/06r1T/TbZMllcUF9+iGhagr9z2C0sBtDWr7Ju5/OZdx+cWMW94Jm4rY0mBJp+cnhQgS/25b3RokbyZ1SAp7c8Kspi7DAVWsIq4b3pufU3cw55Mp9vyiiYuOJi08kMTGJpETpzwQSEpJJTM0lu1QEIY0l/FPUiKt5oiEOOiMZ2/41XmvxN1p3G8+InVYcD6kjUXFPk44QRaz9DnSHfkLPFi3429878PGMg6y+lYW3uHi8mCpK3fQxmd+BgW++Rasuc5l43As7EXQ2u1UWCyFvvgjNwW/R+t1PeXf0QZStywl7rlGLybu3iytTP6Lvay1p9fkSZlwIwFHc/X/JBuUx9jza1p9Fnd7mvfcn86OaNVbp5f/AqJTMfx7Cq4r8Sbu9g6Ozv2DUwCEM2XabvQFCL0n9tjyVqjhT7A1Ws2bMDwzp9Tm9B01jkPJldlmmEJ5f9YwwFf8qjyLT+yJG2ktZOux7houAeMxybTbZxuMoaabGnIoniQnXsT2jwfw5e1Dacgf3mJ9/OamyrIzczCzycvOorHlOEjenPJ2aeAscDqqjuXAdmsfssBRBe1LT+0hNKfWFQUTfO82FzfNQGv0tPw38ka/HbWbBPmdsI4oUI4BPdqmvoyIvhBSXk9zQWcLycT/y01ff8uM4JeYcduZatKhfRRWVmW7EGG/i4MphjPy+N72++IHBMzaiYujLrbQaCh9fE+srqA63xPvITFR+aMWn77xG6/bdaN97CH1/HCrq0o9BPw5n8OydrDxyH4cgb6K9j3Ft/WCGd2zDW6070WbYZmYf98TitiNe59U4vXook8aOZeD0TczdfB39M3fweHSXmBhjLC5qo754C+r7bDGNqXz56GgjdbWirnl55GRkUVLa/Psaz1Errni53sTc0uPISiXWqR3huFsSvuLnZtdC8a/y7ADCDbdxYtEApvzYl179p/PTQn10TAMJLKptPuraSF1hKoWBZjif10BbeRHThi9hoZIBx51C8EoLwPvmDo7P7y/K60fP/rMYscQAPSsh0EvrfuYaKFq2yIlMj/0c2HeMVbsficCnsMl5itCsxIZ7p9exasAAhvX9ir7fdqJd6w9p9VYHuvToTZ8fp9BngBKrR0/jxJzeaM74joH9+/Dlp9LqYW/yYafP6dT7O/r07seYJVqoW6ZyV9yS6qWj1AaQ7nWKo+vVWLniMPttovAS0WP5L2idirLSxn6QT2XtL/SDslSqY82w11NDY+F6tpy8jXVGHcnNBIEoo76AbN+b3N05E7Ux3/DD90P5apgKi3ZaYBaUjdil8clHE+oqqEz2Ifb2Ea7uWYXStPlMGaPO5kO3sI2PJTjQHDtR3vrRX/P998P5eqQay3VtsQrLJVOU9+RaIMoh1o6g0/NZP7g1nVq/S+sOw/h2+FxWzBvNwiEd6NO5E58NV2XumVDs0ytEkCCuFTFGuOrNZOHAL/i63yC+XKDEyGninvntAKZKbfVNR9q2Em31tmirnr3pPXASfX9YwqoR0zi5eAa62sfZY52Ie1pzD/0j8QoK+VqqsvwIFRGWzk+v8/nfhJD/66f8pc9m5hj44JJc9oti5h+nhkoRCT7cNYZlXd6jdbup9F57B9Owol/xmLdYXFhu8mD7EBZ/1oLX//u/afHeWLouNeG4c6biE/XNqae+upiqghgSH13HSnsaG2aJSH3VSdaaFhCgeJabQV3KZcw0BzHivdf4rxZdeH/QTjYYhxAifO25jvSEStEP7xB8ZTbKfd7hzRYf8dfuq5l+6BFuWeLG0pjrOeqzSXU8zOW5nRkk7P3aGz3osvA4uzwKCVFc5CUrRBNls429Iz7hi7/8hb+/M5T+629wLqa0ydru9VTFiuMfnsi6r/+L1n9/k//ps5pJpyKwTZC2SpSQGyDObcXXTGr7Gq0++ZYOgxcye9UG1DW3oblVC60du9i1aze7dfaio3ecQ2ctMHGJICi76lc+dn0RwmuqAwm5qYLm961p/5f3eefLtcw76YmruGNUPrmgVVDgfwWb1V8ztvXfePu9IfRRNeJMTAWpL7lW1pdGE3lzA/t/eoceLYRtPhpKP00LToRXkfTEgSqpjTQl4OBwlvT6C//3tzb81zfrmHQ4mDuxYltjLummUlsUQtDFlez8/nW6SOW1G82AHbc4F1VNys86fyX5QYZYrfiScR+LC9fnKkza+4hHedVNypeReRZxkaopoiLhIVHnlnBGYx7LDJzQ9RexrzQ6nuRAls1mjh/UYdWBaxw5r8dpXRXmT9ZggYoFNiHZ0u20CaIz1RRTWZhCWqzwZftz3DuwgH3amqwxDONyhNAViutiBbWlAUR7GXBityrTJmuzZus9PGN/vpfnZaTi7+pBoF8QeRW/MNgSa0/i5Xlor5gprrEX2WYRT3RZPeVNBUxpGrXxTgQ63+K6uR3m5mcwPrae1ZMXM22GHofswwkV2Z7c5qUP6EV6EXbbEAd7K8ysrmGqv5wdK2cxatUZ1E1jCc9II+XBdaw1V3NwrxCI1y5wft9S9qyZyaQt11G3yiEq5/HNoY66kkyy/W9xa/MkNoztx3Q1XdRuemJ+3wk3Ex3Oa0xm6qCR9B+uwbrzrrhE+xLnqM05jZkMnbmFKXtdsPSJJ9T6Ilbr57Fv+1b2WDlx08ufB/ecsbpmz717j4hMDiTUfi9XV49k/rItzL0Uh+UvDDjVVJUSFRCIl4sHCakZP3P/ERQnUX5fC6tt45i+YAuz9rtzK6pEMaXq6TVIuigmkBJgwlmVdWyaux6dY2fQP7Ab7cWL2LFXBFQRxQQ/d60rJ9/XFOeds9GcM4kpKgdZe+IBt3wiScwNJ8zbiJNr1Ni8YAN7T57l4L6daC9axK4DF7kcU8bLX1kTB0o0J/TyclbNXMLgeRc57JDw9MlKfboQ+g/wcbLh8lkrLK0uYWG4BZWpC5j40wa0jhphescB81Pnsdilg+2xw9xxuIW1jTHn1GayccJgFmw5yJabtzA1O61418HwYTbu4sapWHS5vogy4afue2eyfd5kJmy3YLtjJfG/MPqSm56K30N3Av2Dya/82VYRt28b4i/OYccKEdysucIOqwRiRSdoLl0LqS/3xvmiHrumr2TLpr0cPH+afWrK7FBSZb+lJ/b5oHgo1ISagkhirmtxccVoFixUZpaWMYfN/QgRIj4tx43bZ/ezY8Yqtm3Zj/65U+xduxItZXUO3PLDQXT1J0/HRIBMWRb5wXbc15rI1mk/MmPjcTZZB+Lk602A0RZOLP6G4X1+pM8MA3EOUcRIH9AsSyfT6w63D+/nosEuzt6+yDHRj0+fsea2zQXMr2qwaqJoq2Gb2HnCGGOH+1icvoTP8fU8Oj4f9aUqjFp4DQOb2D/sF9BfHSFflkxlhC2uJofQ3biQxYM78vXrLfjL46WA/tqdj76fy0yVHegZ3sMiuJS433Gd/tqiCBIuLWbvIBFBt+5P56nnMPDMlB64NQrQJtQL9y8MJs3rJqand6KxeBRTerxO28d1bdGaFh3GMGi2Ght3aaOt3TQJkaqlwfZNK1g1YwBD279Bp4+/ove6m+h6lxCX5Ev0fT3Oa45g3Jdv8vbjMt/4hi/GbkT11B1uRUqPEZuOaj1GujGkkOl+iNMzevBTN7HPgnNsuJ1D4nPhvXRWeRQkueN+XYf9M39g5McthPiXjvcXWnw6iD7Lddhidguje7e5eW4bOyd/Sf+Wj9vkLV7/YjTD1A+w57Y71l5BOFlex2TzdFR/aMPn/9NY7791o/XgtUzeY89V9yzi8ivEtd4BL/0prOn9Jh//z3+JfK/zxjutef/D92nTujWtW4s/23zIh5+0p22nnnzWewRDZ2ux5rgL1iE5T+fd/cMUkuNqgPmSLxnfexA9Flxju31Gk0fhDdQk3yP27FTURn1H1x80mHvYC+/iZ+cDS3eFNNJD73D36Ho0x/Sg75st+G+Fbd7mb70m8NOmy+y9G8vDABEEOV3i3u7xrP7hbTr8tdE2f/2MNt+vYbqGGWYPI8jJT6QoxpEHx9eyaVgXvpaCWEV57/DaV5MZon6enVZhPEyopuS5xpfaN5NUVz2OjutA7zZd+WDkYZSupxBb+mzby8i8gPJMcNVVjOhuu+LGgSAht4SYqPa+SOjBuegZnGGXbxEBJcnCz85xbNYyVk7bxZmHMQht/vIBFumDdK7HeGB0gmP3E7BNaRhtrM1NoTD6Fv4eRzh8bBfzFxxCY4cjvnE/L+TL83Pwue9CgHdg8xftmyFdJPJIu3sCk4U/oTxHmaVXgjGPqn2+nuXZ1KYFkxAbj39qOdnluRRF2GCyZjnrJoiA+qYrd8VOTwRHXTVFiTEkBQUQm1lAdkUOFUlXuHN6HTPm7hPBzj0eRXvjYSTE5MIdnLjkhn9pFiWJF3E6rcS0pYeZrxNEUHzz2tcVZxF7fjNG6+ew64YzhnmKyX4igggny+0YRxcOY5K4Fk7cZMZZ/3Ry40zwN9vJSm0LNCzzScrNp8TuoDjfUWzcepgD4bWN78aIOoZFEBUm7g1FxZTG2xJuuBS1eSsYsuAm+qJBpOlDP3dZjfUPwOOuC6nZz09Keko5panueGrPY8/EUczdboiOWzFxzw6t15eJ+/0DQu7osWa+FovX2WIfkkFS4E08dk1m97atqN3J4FazKTEioiz1I/j6OjQGtOWLdz+g3cCVTD7mhVVCPqXF7kTc3o/agp0s3+TA3Yh0knyu4ioE4S6tXajfz+HOC5+o1ok7YTEFYbdwOqTK+tHjmDZ1IzvNfHgkLvgKiVEvwtTyBNIzc0R7S3PxkyhNN+esxn42LL2OjW+2aKc64UNRZPv4EB+eRIG4PdRU5hJzWQsj9UXsN3PDTJiusDaTanGdj0spI0moxic2L46nyGU3N7VmM3ryHmbv8uJhUqnCv5/TH42U5WXjLYK0AJ+gn5lyK92n8ki2O4Lx/CGsnKfC8uvhWMbUKrY0oyae2tRrXNq3nZnTDNC9FkZkqhDpN9W5sX4q607ZsD+0jvgnN0JRs7oMSiIMMVYdwoRP3uaj9t/x1fKzbL+XRmxhMhXJ17m2ZzuzZx7ngLEQ3qmhRF9dyxW1GaievYN+RD3Jz8Qg9SUZpBtuxGr7fHYYuXFZOKdioCDLg+Azy9Aa9xVjh0xh6nZTTodVNgxuFReR/9CZaPdbRBWEE1xcQqyIOGpFwFiUbMrJDfvZuNwIu0DRt6VjpMeLi5sDRYFnOae6kLk/LWL9EXscRBv9/Hsx/x5eHSGf70vxHRFxrRrAN13a0vaDVrR++3Xeev11Xn/9TV576z3ebfMJn7TvzncL96JmnYPbr30Z9ddQmUW5izamy0T573cTQcNmVK2j8BObntdMwhVSrQm6vILVY76ic9sP+ei9t3n3zddEXUV933iHt1p9yAeffEqH5z6WI5K0dFKHdrT7uA3vt/yI9l/OY9YpT26lZJMfcQ0nvQlM7dOej1q3pOUbr/Paa2/y5tvv895H/ekzWQftu1H4iD704ptYLSUxTrjrLkVv9XLWX3bjSlwdec85p/RDAinepzmz5CfRCd+n/btv0vJ1cQ5vvMWbrT6g7dc/MFxjK8v37WHFxOGM/rg1n7Z8k7dek/K05O3WH9Lu60GM3HmajZcs0V+/GLU+H9P7w3d4763XeEPY4rW33+OdT3ry8dgdzD8TiZu4ideVhVPstINzq/vzU49uoq0/pXP7dnRsJ+zYphWt3hHn/fbbvP22OEbLd2j57nu0at2XjoO3sva8Jx6FdT9zA/856qmOsCPyzHL0d25j1aVQboTVPn8RLBQCwUOXSwe2MW+LDfo2aWQ/N+Ah7RVMqO0edMd+zeAPW/PB22802OZNyTYf8emghYw98JBjpo7c11/Agckf81XblrQStnn99TcUPv3O+9/wcb+NrDvmQGyyF+kP9Dk69RuGCP9vI/z/zSflfcyH301n0FZ7jntIYqOhFk8R9an1JNR4Jaq9PxLB4UC+XCsuvJ5V5P7CYI3M70U99bXV4gZeSVVlw4tzNaKfvuxG/IejWAhux108PLUWTSE+9UMgUQj5csfTuG+Zgt6hYxyOrSVcyioC2NvKS9mzQBUDpxDcxEm+cNpfXR55IU54XjqGyRUTLMKyCRP+WFVdSUlkKEle1oRHX+fmnQusXXeOnULIB8Y3FfLCpnU11FSUUlZUQFFBPhGBftjeMMHe5jYRySnkFhRRWFxOeVVtEzEqrtH1Xjhd0GXNwGWsUTqDRXQB6S+MNkRUUVNBdVU1FaIAqb0qM8Nx09Xk+IpV6Fu6YC/629PROiEQqqqorqhUrKRVL4nMeid87xxHbdUxdhwwxyvCAdsrp9GccZDjZ/zElVZ6tCGCD7u9LF90kFXqjoRGNn+OUZ2XRNgpda6snYXW1XtcShOiQrFFSK6SKALPKHN4Vj9mqhxB3TQMf/creN7YipKWEWpGWURnFlH96DxOWyazad1GVl/1xiQ8n5zSUkpKKiirFGJTOrnqdEqSrLiwVpUl/dew66gDnuIQT61eJ2KVCipLiiguKCAjLQFnO3ssDE145BtIWkEhBYWizHLh40+WmJUGC+JJDb7BgbmrWDxEA/2bPgQJuzUfAJEQbZNhiJ+ZBvNUTzD7YAyPEqqpS7Mmy3Aee3W2MedKPFeFoz3pO9VJ1Eeewmb/JEZ8/TnvvfEu7dr14otpe1lx4h7uLmd4aLaFhZvOs9AgAf/kSuqSTUi9IoIiHW3mXkvGKKqxrGaUiz6bSmykP7cuX+Oq6lJOqC1nz/V7XEmAJIW/SE4h+rUwXoP4jRFB1HUM1mmzdt55jF2SGnyjvoZ60fdrGpdXqytKIfTkRi6pzGbXtTtcE3Fyw7xw4c/S9zVEYU/Or75SxDcB+FscZtPQJayYeQBDv2ThN4/FvtQPqoXPPe0H4QG+2Fw3xt7WgciUVNEPikU/qHimH4hWrfPk7qndrB6wjLXK57GOLyLjRf2gwp/aQF2O7t/OqHX27L8tjlWYQu0jLe7pz2GpvrkIsCoJexLLiaMUPCD1thpb5/1AJ3GPatOyDZ37TudHdVNOWYqAUQQnBof2MHbjPQzulVNdKIIFVw3s9Oaz6JAtG+9XE/1M3F6bl0DCpXXc1JjNlkuOnE2WviwjXCAjmkDT41hum8i+VcOZtExoipOB2MXVUpSTRZrTXQIe3CekUFr577HdIsmKuob+ml2oLryIuUeqImgVjS4ylFJfFEfs2dVcWfwDSton0fCuxefZwPMPwKsj5EvjKA8y4s55LTTU16O2aQsa27XZoRjF3om2liZbN69HfZ06W09YccWnmMjf0+B14jaUYYHPsQnM7voRn3w6gZEHXDHMENfQJ72tkXpxdcrzIcn5DBf2arBu/UbUNbezdWfjqPuubezYupFN6qqoqqig8mwSF9C1qmqsU9/Exi267Dlug0VQNinl4kKc/pBQ60Po79jCBlHmdsWI/k52ivPX3LiHXfoWmAelK+a7v0yf1RRlket9hxCXO3jEZRMpqvt8xC5dbLLJi73H/VO6HFbfzJatO9muqP8Odm7dxPadOzlgdJMzVhac1TuA/gZNdmzf2dAmu7ajpbmRLaKN9EzvYejsza0rJ7m6Q51d0hSZHdrs0t4l2m0L2zS3skHfhOP3M4kSwqC2MIIcOz2MddawYbsO6/Yc5IDePvT27maPOPaO7VvZtkWc7+YNbFZXZs3S6UzpN5D+30xhzvbrXI6rJOG54YRfSUEiZeF3CQ7wxCmujKgX+VCNuCzn+hAR7IPdo1T8Eyqpbbg2N0G6EiaR7GeOpd529m4U9d2+q8E2OyXbbGDb3pPo24bj4BlK8K2T2B7bhNY24SfCNtKTGe0dmmzT2In6rutccQgkMzeG/LBb3D6yAz3h/5pajf4vlachbLHrMHuM/XGIqqLo2cavE6Ig+QKO2kMY2a49H/dcxKwLQdgJJfB02pDMv44yqvKiifO4xX1DcXM3voVtYAZhwt9fGfuLm2zFHS0cj6uw+WKDkE8S9a9yPIzzhsHierwbjUcV+Iq+UBHphLPKEvbOV+aQUxAPxDlKUrUp9SVp5LgexXTTRBYNG82kVUfY65JMkBCW5YVp4gYbT1RkBAVVjwiKtGLPjhvs2+NGdGrTkqqpKgwnzEZcW7YosVlJiflzZjNh9FgmTpjE/CVC9CjtYP0ec256JIoeqZC9oj+Iv+Ve4urBTfz4416UtrgQrVi55ddRIa4THsf0ubJpG1fvefJI9LeX326EkYRID310VVynjTl83omQ6DvYn9RFfdgGduk541MlhBpeBN89gNJCPVaqOhAiRHZTKrNiCDq2jvOrZ7D1kj3nhIp7+k5YFcX3dbi9aSALVPaw4Lg7jrdO4XZVg+Vbr7LmoggCMoQoTfMnyUGPK7tXsEppFfNW7GDrMVtMg/JIbHoNq0nETVuVvT/8yIZdp7kgFKbQQ43kkBlky53Dm9m3WokVSxczbeJExo0ay8zZQtAprUdp3UkO3vDCK7u88YV+YfUKRyKddrNwqgZDx1/H2Dm1Ufg+i7ghJZ3C33ANM7deYcaFAnxTxM959lTeXsHefVqMPxrGaW9ptLyB+lw/CuzWcGHrZIbNW8/oJSqoLZ/KtHFKjJ+4mVP7V3DhihrjdS1YeLWEcOmF2RwrSmyXsXPfbiYcj+Ki33MXcWFWca0vjiAqKYOHPknE2J0m+PpmDlyyRud+EaHPPf6VyggnLfwyB9dooTz7FIb3ohVC89luXp0di7+BGmdXzWD7RVsuinNsPif9WarJ8LTEcOIINk6Yh7ZDKI5P7t1CxOeHEmp1nMuaTfrBqDGKfrBgyVLRD8S9RNcSU69kxRN7Rc3rEsVt/iLn925k4MB9rNZyJb7iJZWo8Qb3TRzZv42h2l7oKdY7FmcWrov7uaXM1TFmqXERgU8eYYtANuw8gaemsFppEf3nbmLJyvmsnjOLYcLv1yipYXJxOZuOH2To/mBOeohdSkXNQnYJzbGMWaKuK81EWz2NkBVUZ0cTc06FaxtmsumsAydjhLsIIxQmxON3yxJf6/3cM1RFfclCpizQY49NJM5RGQTfFkL+vhOB+WU0vC8tnWcwycEX2bdyO6vnnsHIOa75S7ZSAPVQCx+d/szesIeRl7KwTfj114n/X7w6Ql5ESPU1FVSVl1BSLFJpGaVl5ZSXV1BRXi6SiA5LpW3FlJRVUl4touOf7RT/KKLx6iNJFRHkocnd6N/+S7rPPct6+wJinxtqEgcW0XFtlaifqFNxSUN9y0RdpTVHK8rLKC8robSkmGJR35emklKxnyijQnRSxciGVG4VNZWiLGkURVGmtF2kslJRnkji3CtrGlY9+NnTr60RJq1BFKu49LyYOupqq6gSZZcpyi5/cg7S8aQ6lFWIf1cKe0t1EXnKpDaR6iPOUWoPqU5lFVVUVFVTKX6rkH6T2u5xOY35SsoqFGVVlyeR5GGGqQhOjuw9h6FPMgGl1ZSJG11VZQWVIo/U3uWivUuLCygpTCU91o27hzTQnTGN9VonORZaStALR9Z+BdLHt+qEXeoaRqdebBvJssI2Io/0Lp1kwxdTS221aA9hp4a2kWwjnbdof8kOZeLcK2uorK5RtGml8G3JNk/9pMHGJaWSjaU6SR9kEuUpbC/Z8Gl5CltLv1WI8kTFpdNoRlE4ORarOTqlK190GMQXs06g/yhDEfC9vP1lfhtCaNQKv60ooDDVn9C7p7m0aRYrBn/HhOlrUb4egpW4oxS/1H9ehmjfWtGfxHWlTFwLy6saXvT+h4v5R3lGyB8MEjdQodLqA84RoDeSdSuXM2nvbU4+9OOhzUWOz1nOxrnbOO0WSYDY/dnBgjoR2CQbr+X41LYM6PIRnwxTZaKBB2YefiR4muDiYMdVu4e4+plgZ74f1WXaKKsaY+udRl5Z4+ixKLU8y42HR5TQ+LEzP3TuxKftRaD64Ud8/PEnfNqxI506j+Db8fvYZR6MiD0UtqIqWAgQLU7oruTzqRdZeCiW1EJpCLSU6qJ0slLiiImJFSmF5MwiCqsbrqkK6gopSvXlzvkrXNS/zj1/sa/4+aWXnLocajJt8Xe8wmFht+vOyaRmBBJwcQf7Rk1kpfIB9BxccfM9h8X5jcxYZsCynV6ExDafG9pMyF+0e0bIV1L2YD/3tw9l0Tod5h19yH2bE0+EvPKZWMIyJdksjFYSSqzdPk6vGcfUHwczYJwaiw/c4WZgAWmVjaO1VXnEHlvJlSmfsUprP1uEuXyeDJ2nEHf/KGfm92dq94aP77T9+GM+EjZvJ2zfsfO3dP56JbO1bLARkV5DOCJ2zr5CsLkS4xbu5BslV0w9pdBHWK0yj6KsRBLjJHsnEh8dSq7XPlyurmb6TkNmXi7CRzKwJOTtldAVQn7skVBOeT1pEWrjnIk/OYtTmotZesaZEwFxhPhaYKS+DtXvR6CzZihbTqvy414bltwoI1xSa0LIF9suZ6fubsYdjeSC39PynlAQSUWwGa6Od7hq68EDawPsz6xltcYpVhwNxzX22ecJUhlhzwl5aVWwZ6+zlc8KeaFhk3/hYlzka4uLUh92zh3Jipu+XJTes1X0A3FfzHDGWX8ZGwd2pv9z/aCT6Aej6DPxADo2YaKGjQFtVSCEbuOw9iq6T7vEUgMhZKWAtrEfZCr6gZRSSQu1JttBFb2DWgzd64uem8hWIgn5vULIL2PO7pssuVlA4GMlLMoovruXB7vGoK59iHW34nCK9sH75mF2j56N+siB6B2YxmyDwww6GMYZL7FPiSTktYWQX85MEXwrmRYR/szMipcJ+fzoCCHkbxEc6Eh4pA2W+1exZeZslu82YpdxELZGdvg7PyCooKRxlTaprZ4X8pLIf3ItlaZ5RR8h5OJkJqzcydfbQjDye/4Z0r+bV/Bl138nQoim3sXv0ATW/dCJDr0WM1jTEeuk6ubLCMr8c9RnURNyiVuH1rJw/g6U9VzwaP50+SWUknL7MjfXKnNQ/yKGCWVEvuCa/J9LIZUxJtxWG8CszzvRechmpp0MxiVTBFiNOWT+BdSVUivEb0q4K86mRzm1YTLzv25Dl7//nU++nc2kU/4YS0K+Mfuvp4by3EQiHO7iankP7/h0xQjbv3yGVDMh74qev7iBSoPjua5k3d7AvsXDGDRgFMMWLWH6ajXGDl3H/2vvPuCqOPP9j2df/7337t67d5Nsdvdukt1sTNkYTdRIYno0sUdjb6iIYkGxgmBHUFGxAnZURLGhIiAKKKIoCCpSpUjvRXrv5fN/ztEYG8maaFY2v/cr5/Uix3PmzDwzz8z3eWbmmamTd+EWka3t5bq/SjZXFVAS6cFlR2Ps5g9i2OR59J7tjLW1HWfWDMVici8+6t6P3v2+pFfX92j3Zgf+8clkRqy5wLGIKiq0C6waMRWppAQcx2u7NVutrVk8fx6Gah40Pc6Lly1ntfUu7Bz9OBuVqz1Ia+ejIhguT8du2TheG3+EsQ4l5JeqNFAVTI7PSuxUg2vgwGHqZYbxOi8808tuX8aiFESRF6p5CM5pDnglEJXd0rCzt9RXpJN5yQX/484cC0jian69aqwXUxywjZPGPdDr/iWf9xnBxEn9mGY8ga+MDzLDMYu4+65v+P4e+WqKvZep6X2G/uxVGOy8ygVve22Qn7R4H9O2xxOT++0aUA3BfM0oPHtx2b6UpXNMmKhnzqK17nglFd4qo7pyCh0n4zr+VQyWrGBKQDP+d045lFKUeIkrh7fgtM6alSssmT11GpP0DTAxm88Ktf6sbY5z8IwKjCWqoaX5SrM6QqbaEb5vJD1Vg+ydBTG4hGsaTiqhxx/AZ4shk0dpynsaehOX47h9Jo775zBglTO6e4oJ1QT5/JNUnpjA6tVLGbwtjp139aDXxZ4l2noQ2xZNYb53Kh5q0jXVuSRuW8bugR+y3uQjpmw2ofMyDybuL+fGTRXVbh6nxFWfZauWM2R7Evsi7sS372RcIMNpEusMe/Jlz/706dWFHp92oE3HSXxudJIjkcX3XTKmiccPD/L3b/8PDfI/cNyqiTxJ5PyOWBl0ZcSeq2xIUQFW+50GGsqTSb54DM9t1mxR9WDRfLPb9cCIxctXqHqwm017L3Au5qa2PmpLr+IKBE5j7dLxtJlwjPF7SykuV0eFyitknV6BjammHoxWr8WYmy/G/aAhC7eu4ksV5DdqeuTL1ZJFLidguz56q45ieLyS699WlKYyClws8Z7XmyV2e1ibhHZIzapwb84YDsd2+DtYrhtMr7V2fLI6ip1qVjQ3QxNmztktExhj7c4M92pu/DM98mqWi+OiCDnlRVi0Kn+1T8i+ug03Vb/Hj1vIoEk7WbvGibMBlwgrr7zdI68puIcH+e+2LLWDy9lNzFF9vh5vzttTL7H/Usvn3v5VJMg/qposaq9txn1+L77p8BGdesxl1v5QfPNqHzh1LB5RURQ3nSeydnh73nh/NO9PPcL+KxnkltZQVa89H3GXRprrK6kszCYv7RoXDjuxZ+U2Drhe5FpZ3VN7d/nPr4zqXG8uO0xl5pfvofPeUL628GJHZD2593eRiserqZzGohukhJ3B03ENtlO6MuzN/+SPv/ovnntPn8E7I3FXB71H32/UUpISjI/VaraZWrM/MEp7r84T3/9UZNHkt4LAXSaYH7rGxgjI0rYESyHvPBdVwJ/3dSd6fP4u7XuPpMPAtcxeF0RwevkPnPVJpznVkSMOGxk7dQ9LjFdzYsVQzMfq8N677Wjf/jXeaPMSf3rhRf747jC+WOjFzqAKNLn7YXJSk/A74YX/+QByKiof/tvlV7UBxs5Sj9cmqCDvqIK62s9Q4Ue6ywwW636gfreTeo1i6FxnDiWX3w7y6uCfFUZWiA9BkXFcyW7gZsVDzoDdUU9tYSoJ/oFc8wvmRk4RhWqOtM/rKL5Glo8FtlP70KdDB77o0I7eupMYvPE8tlfryLqvd6ihJJO4HWbsn6OL5YHzOOVpblPUqKKxIIRLGwxYMfBTRhrvYKl3IjdCDxDsbI6hhTNzHNNIKlAtn7oKKotLKK/6dqSqbNLP7sB2yHCMRpqywT/p1tmT+grKnCbjPrENExZbMfliExdb6FSprS4l7KI/Pm5exCSmPvz+JM19Yym2hO0droL8Mt5ZFItLhFozTao1EmmHi3kfen6gKe++fNrTmHXb57PTxZwhC3ejty6Oq2l11Ke5krZjOCstFzHhSCbOmuukbmtOPEeS7VC2LDDA6HC09kbgitoKcg7a4G7Yi13rBjB7pzmfzHZisl2S9uFY9UmHSdw6FMtllhgczeG45oLze9RTE+dJ4Dpd5vVvR5d33+Gdd9S23bYDb77al6/0bLANzLprvHcNzdaWSEGKM3bGVszWc8DFP/Whg2I0lGYTvW0e+2aNZsUhHw6oDexWwGxZzXUPri/sxMqJ3RjucJX1KsQWabvWH5Sdksh5d0/8/S6RW1n18HpQdhkuGbLWXJ/XDFzQ31dBSblag+W+pB6ZxoKRmnrwkXqNx2DGfJxc56sgb02vuV7YeFdQUZJO7bmFeK4YzpSNriwMVEt/p0ehgvJTK/Bd3Aez1VtZfK1ZxWa1CcapfcLiieyf3ZX1eyYz0MqGbsa+2J+voqYkmZozc3FbPopJdqcwD2wi6b6ejqaSDDL2mnBs0RiW7PNjV6YqN1W4VakJRPv4cj0qkRLN+b/GcFLPbWDtlAkM/FSPseNXsN7lIv5FVXflgzhuJh5iw8wVzNF3xO1yxnc3rWupverNPcQcm6CC/BLaGQaoIH/fRftPAQnyj0zVmspEMn3WsmvCp/R//2PeH75ShflIQtQW8P0HLPF9mvLDSN45nKWf/YY/P/83ftNhHIMW7mKrayDnwhKJz8glKy+f/PxcbmYmkBIVQICrAwdtrVi9aitr9wdyOrqAwkZ1oLw9zV82VQr5gYQ4TmPpIB26fDCYzw33Y3MhF82AGD/Q+SN+quY6mmuKKctPJzXyAhEOhlj3+wtt//d3/K7jOAbuiOCEOng/+tm8Gori/TlhOp81BgvZfj4UdTh+8mcFVZBvVkE+aPfcW0E+TGXaO6mtivLUIEIOrmSH8XCmTTJkjJUbGy+UkFL+Q1uaCtC1Knh77MZkiRsbNp0jOugMwb5HOXZ4D4cOWrLaQh3w++gzYPRGNrrHEpVbT10Lk60szFPfvaB9SmSLjZtqNfNhpmxaYcAbuk7obc0it1TVl/osyhMvEHTamQMHDqmXN54Bat9T3qR+TzVIytPJTYol9kYyqfn5FNdWUVhSQ4nKqQ/OTgN1BZnkJ8ZwIzaDxDS1LZQUUl1dQrH6qVpVZs3lUaQE7GH/8lnMHqrL5GlWWJ+KJkBlhfsv2W8oySLe3lQF+ZEsdfJl383bQb7kCqmey1kxrDu9PxjGiGXeHInPoSztMFedlzDJ/AhzD2SSlF9BdXoU133PEXI9/c4ZhuqwIxzSHYjJkEmsOBurfUJ0ZV0lRarxf2zsm0wxX82cq80EtViYzSSEhBF45gIZuS08TKNZpbFse8IPj6P3BEs6zA7GJVjTl60KriCCxMvuuDlryvsEx9z9CI1xw++sLTMnLmfKbBdOhSUTe2kf3qYDWbbQnCUBhZzXNiJvyw2k2Hm8CvJqG1HLv+pyHhl5yUTs3ozDFBUanRZi42aLrsEaZpqd4Ox1Nb0LuzhpMoCl5lYsDSzh4j2BUdWm2hvEX3bDyXYLm9du4cDBQxw6fJR9W9axRm8oxhOmsfBoKB73NMY1cV0F+VRNkF+pDfLHVZC/1eC6V0NpDjGqweL0CEG+Mvwk14x1sBrfg3EHgtmqQmxxC6GjoiCXq2f9CAuOuO+swV2qrkGICestJ6l6cIDx27MpLFcbZ10GZQl+BHpr6sFR9TrL2Ytn1Xa/l+02VowZYcPavaFEJocTunMOu6YOxXSnJ1tV4+rWZSsaNTRdteXq+kFMMVmJrmMSZ7MLuBnmi8dcU3YtmsK+M2uYu2Y9I0ZtZdOhCKKTrhGydTrbp43CzFGF+zQ1vfsaKk2lmWTsM8FFE+SdLrA769ZNwtVpicT4nCUy8sbt4W4rqctS29I2Qxb068YX3YwYbeXFyYzKu4bDVUE+6bsg766C/D3tVc2ZpIztxBwawzeT1XZrco2DV554l8kjkyD/IzUXRpDmbsFWo28Y2HskX+svx2KXJ66BMUSklZJf3SSh/hE1laaQddqa/dM/ZvB7f+Xvr7Slzft9+HzoZPRnzMfMfAWWq9ZgvV4dzG1ssN24DmtLc7Vjt2DljuMcCC0g5uk76/Uza6SxKo+S1DCiAo7isWMR5mP7Mqz3EAbM3IWVZzZR93Y5iJ9Dkyr00I14zX6XL15+gWdVI3Xg9nBtj/yPCvIJKsibLWDtxEXseOJBXu3JGvOpTDhF8IZhWIz5gl4qEE1wSMA3o4riMnXwj7tI+AU3XJ2d2Gu7nj07HXG6FI+/ynUlKpDWZsSSHehJeEQEoTfLybyZQk6EN5e8juF8ZB/Hj2xhx76DqjEejldI+X29uqEqKDqyaNY2FizwJeIHhp8szssh6moIMddjKa6ueaAnVKshCTI3sdt6Nu/32MDEZcGkVLS0x9bcyZpI5uXDeNqrRoXVGpas3clW+50qdJ7EIzidS2FpJAb4cCNENZyzCkjIzSQ95AS+9lbYLF2Klc0ONu5ywWHPSbwvhhGen0tSZgzRfifxd9vL4X17sFm3l137fLmcnKcNfnfmprmBxsIEMvwccDLsiv5n7empNxu9jSosOjpx2M6EVdP6802PEXTX3chKl6uEJp7n+vE5rDLoiU7PSXxlchT78/EEBl7G12k3pw/twtv7GCfcndiyYglzh47HZM46doVkaa+frmsqIn7DLLb3ep85lnbaSzhiWugdqVehPzk6hvArIWTk5LVwiZdK3eUnifaaz/DhC/lkxHGOBtx8+LrRyiE/yp2DprNYMGIC88yXYqzC3wxdQyzsjuAcl0dk3GWSA7wIjk0mJi+J4vCteGyYyqgxcxhptJyV66xZPHctixbsxj3wNAHh7uxeOJdFowxYaGGBsbGJmt5Ulto6czyzFrWIimaOKqjIvUi061JWGU9n+Hh7Vh6+dR+EVp4fAQv7MuejdnQdZcKobYEcDC/UPlOhri6f0qSj+O6YyIQv+vFZZ0OmWHvhfqOIgjtDPKt9dKHani7sYe/kL9X67MjXBpbMPhaD381K7ehALW2JRdc8ODWmK+bDh2B2MgJXdbx7YLCN24pu5nBdUw+iVD2o0dxM/RANCZBuyzYrVQ+62zBlpVqH9zxE4W5qHdZFcvXABtbqjsds6mzmLbdk5nhDTIwssDsTwfm0VBKDvbl+5RLXsovIyjhDkscCls2ayte6CzG2WMXqlSq8G6nj986jXEr0w+PIJlaPNWCBkTHzl1swY9wU7fQ2nY0iSO0I7hzSVT2gJJncS3s5Oqsrk7t3pqfKXUZ7zuMZ6MvpgxtZY2aGhbUq1+Bc4ovUctTdpDFyJyeW6zO8lxEjTY7hllKqnWZjfR4FNw5xerMBep9+zec605i6/gyn4lVD+84Nv7UQsZrrm3syfM4KPrdJw/VGCxXhX0iC/I/VXKM9bZ7mv4djKw2ZNaQv/fqOZcisrVi73yA4t+7JX7P6b6a5oZqaghhSVJket56iDi6f0+OD9rR/U3NqvQ1t2rzOa/94h3bvfcZHPYYzYPwC5qzeyw73IC7G55KhDsSVLe2DfjFqqckKItrFCtvpg9Ht+w19hs3BaJ2rClaZJBQ3aXZN4ufWrA7PkXb4zH2Pbn/7kwryej8xyAfcCvKTVJD3C0NzeemTC/LqwFUTQva5pazXbUfH/3uOP7zUlQ+nHcQmJJeYpPOEO0xipUFf+oyey7gVzuzzTyS6qObOg34Kz+zmgml/1m/YwKrLqfhedsN/4xCMB3TmXZ2efDzImOk2HhwKyVOB+tavfieCpPD9WMzdiflSP66nfn9rvb6ulvLSMu2gCPWN341sco9mFZVrfTixxZJRH83GaJYz/nnfjrByv3waE47gs34sk774B++8/iavqv3Q2+106DbMlNnOkTi5+3Bm0Wj2WJli5RfO4aBz+NqOZ0m/tnR8tQ2vt23PW+90p323eUzf4s2Z1HCu+Gxm+4RvmNhvJGPMdrDqWBiBySpE1NbfG+SaqqmNPEzg6n5M/vB5Xnz2v3n+L3/jL/94l7fefZ/OnT/kk+7DGDB7J8tdIghLCyP1sgrlhh/x6UvP87vnX+KPXxjyzfqLbDubQIDnMYIdTNg5qzsjP+9A24590BmyAtPdwVzKrVVl0EBDVQReC02Y/+Ewlqw5zCkVUjWXlT+M5ib8qooKykrKqKmtayGEqhDWGEXq1R3MHzqLod2t2XkqRtt7+/DPa8JuNGkuS7Afr0OfTm15peNgPpuyCxv/XGKz0knZPx/X2QOxdHDBPruatLIE0rxWYTfuC3q/2YZ273bj/THrMHWO40pBMWVF18lwW8TmsZ3o2eltXuk0jK6Gu7E5k6wdqeVWB79mbtLJvGLH7vEf8uVf3+CvbxoxeuM1NPdiajTkuHDC6DMG/v43/PlPf+XPPU0Yuv06ntnNlJZcJ+GIKSt7voTOs6rB/lwnXu5jzVTHaKLzv+1arlXr05kg66+Z3OU5tT5/zwsvfcUnBruwC83Wju1/Xye0oin8fJLO7ce293DmDJrL1sBEwlXlailn1Ndq6kHprXrQ1FI9UC3tmtMc37iUkR8aM0MF3aAizTbQkkrKI4/iv3oYs756k3fbfcjrX5owwS4Q7zTVQA/14JrFEDYtNmZ5gKrnVYUUJp3kwvrxTP3kLXTatOXtbgZ8Y34Sh9B8cqpKKYw9wsWVgzHq+gbt23/Mmz3mMcnmAqcTyyhTM33nxJSqB9w4TqjdEKZ9+gdefv4Fnn+xK598M5FFFvrMntiFzu3b8lqXyfS2usTx65ojnfp2dSIJvgfYPm8t69a5cS6rRBvkayvCCHOciUW3l+ioWVfP6/Byv3XMOhBH3LfjcTeVUXnCDN95H2FgvgF9r2r88lqoCP9CEuR/qoYsysKP4mVnymKjmUw03c7qI5FcTq+SwPRjNRRQcsOP4GObcFg5lwXT9DAYPYzhQ4YwZNgoRoydwsTZlixcfxBHnxhCbjY8wRDT2qgwkhpA+EErNplMZMYMC+ZvPYNrTAV37nUTP786ldhDbfA2eY+ujynIe8xbyLrJi7F/5CCvYkJFIjkRZ/BzccRpmx2b7TZju9WR3Ud8ORmUyo38u5/0rD5fG0XeNXscl09j3LCRjBhqhMl6D5xjC0hMDyL26Hw2m45n/FwbFjtHcDHn3ssNSgJUeLQ2xMFhDzvCswgMP8s1xxmsmjqI/oMNGTF7B7YnoogoargvmGjmIonMRH+OHzqHy/FoUm5WPjyUPBJNr1omsa42bBnQl6ljFrDYM5mLKow9ECwb8qhN9iRgrzkWk0agO2gggwYOYMCAEYydY8c63yROBwQRZGuCyzZrtl2J5VT4ZYL2L2Grsebzg7SfHzhAn28mbmLlsWCu5cYRG7CXg6YTmWswF7NN3rhEldw79N23mmqoiztF+J5ZrJ49kmEjdRkxbAjDBvZnwKDhDB4zC0PzXWw5nUhIoSZIp1Fy3YkjVjOZOnQEo0YMZbTxKkwOhONyvZSUxChyL9jjZW2Aqa5ajrHzmWJ3HufIulsPuykIoyBwFSsmTqN/n/Ws2h+h7a3+acczzRoroSTZB485eszrNRyjdSfYE1tD7r2nX77TqBq/Gae4tm8OSyboMmzSKkwPRuOnsmd1WR4l7uvwsZrG5mOncVbvaRsF6aqh52DK6nGDGDlqJlNsvTmc2Hjrcg/Ng5sy3AjcNYMF+mp6U9Yw/3AMfpnfjv+uoZnPHHJV0HZZOpXZg0ejp79OrbNIrtVo7iuooiL3PBd2LGXZKF1VFwYzYuZqzFRj4YIKeOXl8aR6bcbBaCgzR45g5NipDJ3rxMrjCSTeuZi9Tq1PTyJUiLTWrs8xqj4ZM9vyCEdi8tTa09a4e9UV0pB8mLPb5jCmtyljjY7jGV9475mbH0VT29KJPrKOTf37Yqi3GPMz6fjn3H9P2l0qYym6vAmnJWOZMMqQMRbH2H6tijRVpepjz3HDbgZONqvYEpJDoJpIbW02ZZfscVUN3WmDh6vy2sgKryQuqx2Wdjmrr1N0aSMOC0ajrzsNveXu7LxSeuup0XdT9YDkM8QcMsPaWJehI/RVPZiJ8ZxFbN0yD2srffTGjWGQwRqMtodwNu67a68q89KJO+dPqH8YiWWV2kuN6tRyxB7fiL3hUKZr15URQ80OsuaEatiVapY+n/qb/py1nMCi/l8zw/qQ9gbz5Kcw2EmQ/8lUNaotoTxPVeDYEIKCIgkMyyAtv0qu0/4pGlRDqCyfotwMMlOTSE6MJyE+jvj4BOITk0lKzSQjp5CC8lrtUyDFt+rUTiuF9JBAIi5fJiwuncT8CkrV/rrFHbN48r4N8saPI8g3UJYShOeCxWwwNGe3vwoZ6t3vDlvfp4nm0niyghxxWzcVk5Ff0fuDd+j4dlveevs9OnYdTf8ZO1jjFsU1FeZvZSy15TSp/VnFTfKyUklKSCIxQW1jOcUUVtdTU1uuHUUnJzWRxLRcMopqHry+u6yQiqwk8vLyyK2so7yyhIq8ZDKTb2ivN49LVe+X1FDzQF3WvKEZeraCkuJyStRn6m4/UOena9D2dEes7svcsbr0nHeSNWcLyVM77nt+obleZQjNvQ4ZZCSp/VBcHHFxN7hxQ/2dmkN2aQ0lmuGCc1IpzM0it6Ka4kr1/+rzuWkJdz4fdyORG0m5ZBZWUllfrQ2j+WrflpqYRtrNUoprNU+afBi1zqqLVb1OJSstiYSkZFX+mvmI1c7DjYQ0UrIKya9Qy6P9vArzVfkUZmqGckwkKTGBpPQs0goq1fpqoq6uhoZyFYSzEkmNV8uRmEFKXqX6ffVLTWVUBG7lwsp+TNCfSS+LIHZfqdYey376/qOJxqJY8g9Px3Fad/obWDPOPp6AzLoWllv9YmMZ1UXpZCap/X5yNunFdWivgNIM71yUTUlmMjmFJRSoRKhtADZUqsybTk5SHAkJqarRV0aRmvlbwVh9saGEyoI0tR7V9DSjPWmm92Bqpl7Tk5yRospHlV+yWsdFKsBrh4BWy1BfptZtNllJ6rik1kNiiqZsqylTv9PYWENtcS55KQmkJWm+m0pCegFZhWrbvjMetpqOZn3mp5Kdlnh7faptILNAW5806/Desm6kITeY1ANT2DTjG3oa7mSKYzbXVavr8dSEBmpCnQhb2Yc5Y8fQc6E3684VaZ+Q/vB1XqvmP09tX2r51H4gMatE+wBCbd6pLqU6J5n87ExVD1Q9V29pt2q1PZaqz6fGxROfmku2KqzvcnoNzVU3Kci4Nb2kbM2lyWquHvhxtbQ1JVSr9ZedrupBovpttY7TU9PJzU0jS23PiarM45KySc5Vx7y7g0FjA/WqjtZohuttvDXEanOTqoOFOdxM/m5dxat1la32X7UNDTSVBpB+bgVL9cfTt88yLB2DiVULWffwQvmXkiD/mDXXq4NYSSXVqkI+nkomxKNQB+rqaipLKqjV7lnFU+GxBnmlMIqLlivYPnMlh8LVAej229+rqRQKrnLd047NC4yYaWDA1GlGGBkZMmXsN4zs8Q5d2rbh1bZfoqNrzdxD6jfSamnp+TD/FkqiqQ5ez75FBuiNWozJtoucUwHp5i9y512kyuMil/fMx1IFuvFm9qz0LyFUbaOPTZ3aBlNcCHWcpRpPU9Gbs5ddV3OJVyn8KezofAqogqlPID90D/vnjcNo7Gym77ysfQpt0eMssOJIKq+sZc8CA8bqLsXU/hJ+hU3k/WJDTBGZgbvxsBjDtAnzMVh9CdfwgluNxaeQBPknQTMWWcvjkQnxRMnm9xR6hCCvedhTfUURZfmZ5GZlkpl5/yuJKH9XHKfNYMnoWVgfPY2Hej/+gc9lkZmVz82iCirqGqgruU7BeSt2mukyZJgxekucORiUQlxBKfnp10jyscZ+Whd6vvYcz/7pY14ftp3FbmkkVT3kcpN/F5ob6GpSSHDdjsuieWx2cONoRgNJD+8i/jeXRnP2MU452mJqdgCbg9HEld8eKvOxURNrKqM46gx+axZjv2I9OwNTCKjSjHskHlStts9A0i/bs375FsyW+XAqrEB7A/njXS2qHlQnEe+ylaOL5rPZ0YNjmY13Pc33l0SzjWYRdcIBJ1MzbG0P45pQSerjrQiPlQR5IYR40h4hyDeWpJN52hYXy1HM1h/FqFH3v4YzpF93vni7HZ1eb88HX/Wmp3p/2AOf02fUmOXMs/XidFIysbGunLUazjz1byOWerAhqPy+5y2kkOU5j1U9/swbz/wP//VXXXpZnMEju/ahw+f9O6nLuEHupTNEhF8nQqWk/F9iT2RzIc2l4USHh+Lll0Fkcgsj/jwGzVVFlIZeJD7wIiHphSTVafuexQPq1X/JFGcEc8E/Bt8rReS3OLrST1eXHktOwBnCI6JVPWii4BfZI68J8iVkR4UR4uVHxPUU7bCgT/MJbgnyQgjxpD1CkG8oiCPxwBy2jHmLnp3e4q237n/9gzfavMLLf3iBPz33An/526v8Xb3/5gOf68Rb7fX4Zo4DB8L8OHdmDdaDuzDki4EMtzrO+rNhXAmPICLi25c/Z50WYNHzRd595hmeeeYNXhtpy/JrpcT+Inrm1AG8+dZNfk9v39uTdGvJtWf0br3xM/i5f6810hTQz1lOt3/v1l+/WM23y7w1kCAvhBBP2iME+aaqIoqjfQnxsOfwHnvs7e9/bWHjCjOm9+7LsM+/ZuzcJSxQ72964HMO2O86yTHfy0SneHB+/1Sm6LzMP154mb937sb7PfvSu3dPenbvTvceveih/v7y43a888Kv+G9tkP8tz/dYyGTPAgJ/1IX8QgghnjQJ8kII8aQ9QpD/Z1SlB3N6kTm2Uy3YExijfaz+A4Nv3FECec742w5h6Fsv8qffv8yLbTvS7n0dOnfufNdLB50PPqTLx5/wyedf8Fm3QYxctIeNgaVE3T8UnBBCiKeCBHkhhHjSHnOQb8gNw9fcks3Tl+MUnED07fcfrggyHPCx7EPv19rSppMuQ1Y4YePhiYfnKU6d+vbliZe3Dz7nL+J3KZCAoGBCbqSTVFhPWcutBCGEEP9CEuSFEOJJe6xB/hEfCNWcA8k78VrSnZ5t3ubNbouYcbqMsNv/3LIqqK+gsLyR0upf9vWyQgjxtJIgL4QQT5omyIfZcPruJ7vu+JmCvGZsmuyDnFvdm4FvvMRf2+vR3y4GN5XvW9SUC1kXiI8K4VxcFbFqEk2S5IUQ4qkjQV4IIZ60+kIIt8PHVIdur/yZ5zrqM9j+Oh7q7Ue//FwT5P05YbaAtRMXseP8DwV59S8V57i6ewwT2/+Bv/zPO7w+2A5T10xibj269QH1qYHEH7bF9ZALh6LKiCjRDmQhhBDiKSNBXgghnrSmYu2lNV5zOvDFy3/g9x3G0n9bJO4Fmlj+qG4HedP5rJm4UAX5UC6rd1sO8g3q9+NJ8lnG2r5t6Pjr/+J/X+pBl+kObLyYRnRxNdW1ddTVqVdNGdXlcUScOsT+pWu1o96cza4k8xf5YBghhHj6SZAXQognrpjmS6s4OuFVPvrjb/nNW8PouiaEw9nw6Bn5rh75SYvY4Rf2A0Feo5yyBFcuWPZA7/Vf8btn/of/16YrXcaaY7LpAHvdT+N57iynXfZwZPNCLEzmM3WeE5tO3CC+ql6euimEEE8pCfJCCPFE1NNUV0zpzTSSg9zwWT0S4w//g7/96hmeee49Xhlpi7FTFOejcskuqqKq6dZDWH5YHWWZEQRs3c5Ba3vcw+K1o9b8YNguj6Powkr2zvyQr157lmd/+2v+87cv8ue3PuGDr0cyZLwBesMHMrJXdwaMNWPK7hBc4hupkN54IYR4akmQF0KIJ+Imtdme+NrPZ97Xn9D9rRd45T80D1rSvH7NMy+05xWdcfQcv40NbteJqm78Jx9Trz5XUUhOdDQJYTGkFJRoBpj8nnHkb2tSUb84khRfGxzm9mWEzh94+de35+c/nuW3//cmf+/Qg88GGzPd5iSHo0pIVl+RS+OFEOLpJUFeCCGeiCxq0o/gvlqf8V060aXje3R6T4fOOjro6HSmc6eOdOrQh/f7WbFwXzAhlY3U3v7mE1WRTN5VJ05tnI7Z6N58/en7dNH5EJ3P+tPHYDlzdwVyKraCQhk7XgghnnoS5IUQ4omopLEiidSw8/i5ueLufpITXmfwPuODz2kvvE+6ccLVEzfvUK7G55Pf0Pwjrpf/MZqgOpfi1Ehigi8ScNab017eeJ7249zVWCIyKij4WVoUQgghfioJ8kIIIYQQQrRCEuSFEEIIIYRohSTICyGEEEII0QpJkBdCCCGEEKIVkiAvhBBCCCFEKyRBXgghhBBCiFZIgrwQQgghhBCtkAR5IYQQQgghWiEJ8kIIIYQQQrRCEuSFEEIIIYRohSTICyGEEEII0QpJkBdCCCGEEKIVkiAvhBBCCCFEKyRBXgghhBBCiFZIgrwQQgghhBCtkAR5IYQQQgghWiEJ8kIIIYQQQrRCEuSFEEIIIYRohSTICyGEEEII0QpJkBdCCCGEEKIVkiAvhBBCCCFEKyRBXgghhBBCiFZIgrwQQgghhBCtkAR5IYQQQgghWiEJ8kIIIYQQQrRCEuSFEEIIIYRohSTICyGEEEII0QpJkBdCCCGEEKIVkiAvhBBCCCFEKyRBXgghhBBCiFZIgrwQQgghhBCtDvx/tgJTN8VOjn4AAAAASUVORK5CYII=" alt="" width="323" height="63"></p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15691The development of a care referral model and telemedicine system for post-COVID-19 patient care in the Denchai community is underway at Denchai Crown Prince Hospital (DCPH) in Phrae province.2024-08-27T14:14:52+07:00Kamontip KadsomboonKamontip.612@gmail.comWanwipa Nopparat้hrphrae.ejournal@gmail.comNithit Tikaeohrphrae.ejournal@gmail.comPrakaiwan Chaichob hrphrae.ejournal@gmail.com<p>This study aims to: 1) evaluate the effectiveness of the DCPH Rapid Smart Refer model and telemedicine system; 2) examine the occurrence of complications and comorbidities in Long Covid-19 patients managed via telemedicine; 3) assess patient and family satisfaction, including comparisons of travel time to the hospital and waiting time to see a doctor; and 4) evaluate the satisfaction of medical personnel providing telemedicine services. The sample comprises 46 patients, aged 60 and above, diagnosed with Long Covid-19 and comorbidities. The research instruments include: 1) the DCPH Rapid Smart Refer Covid-19 model; 2) a patient monitoring record form for telemedicine follow-up; 3) a patient and family satisfaction survey; and 4) a medical personnel satisfaction survey regarding telemedicine services.</p> <p>The study results indicated that 100 per cent of patients were successfully followed up via telemedicine. Doctors and nurses can assess complications of Long Covid-19 and symptoms of comorbidities, providing holistic patient care and delivering appropriate treatments for both Long Covid-19 and comorbidities. In cases of severe complications detected during follow-up, patients were promptly referred back to the hospital. Both patients and caregivers were satisfied with the telemedicine monitoring system, citing reduced travel time to the hospital and shorter waiting times to see a doctor. Medical personnel were satisfied with the telemedicine system, noting its effectiveness in monitoring complications post-COVID-19 infection and managing comorbidities as effectively as in-hospital care, ensuring patients received timely, efficient, and safe services.</p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15693The effectiveness of pulmonary rehabilitation in COPD patients to re-admission rate from exacerbations within 1 year2024-08-27T14:36:30+07:00Jirawan Khamkruangptmuangpan64@gmail.comPawinee Tepsingptmuangpan64@gmail.comNatthathida Thongbaiptmuangpan64@gmail.com<p>This quasi-experimental research aimed to study the effectiveness of physiotherapists' pulmonary rehabilitation in patients with chronic obstructive pulmonary disease (COPD) in the rate of hospital readmissions due to exacerbations within one year. The sample consisted of 40 conveniently selected COPD patients. The research tools included a pulmonary rehabilitation program. Data collection instruments were the Pulmonary Rehabilitation Checklist, the 6-Minute Walk Test for assessing daily activity capability form, and the quality-of-life form. The content validity of the Pulmonary Rehabilitation Checklist was 0.93, and the intra-examiner reliability of the three assessment tools was good (ICC = 0.80). Data were analyzed using descriptive statistics, paired sample t-tests, and Pearson correlation coefficient.</p> <p>The study found that all 40 COPD patients who participated in the program had an average age of 70.63 years and an average body mass index (BMI) of 19.19. Of these, 87.50% correctly followed the pulmonary rehabilitation program. Statistical analysis showed significant differences in daily activity capability, quality of life, and the rate of hospital readmissions due to exacerbations within one year before and after participating in the pulmonary rehabilitation program (<em>p</em> < 0.001). After completing the program, patients showed improved daily activity capability, better quality of life, and a tendency for reduced hospital readmissions due to exacerbations compared to before participating in the rehabilitation activities.</p> <p> </p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15695Factor Related to Depression in Type 2 Diabetic Patients in Nong Muang Khai District, Phrae Province.2024-08-27T14:54:12+07:00Thanapong Lokkhamluetuesst@hotmail.comKanika Chainan hrphrae.ejournal@gmail.comNiphitphon Saengduang hrphrae.ejournal@gmail.com<p>This research aimed to investigate 1) the prevalence of depression among Type 2 Diabetes, and 2) identify factors associated with depression in this population. The study focused on a sample of 285 Type 2 diabetic patients undergoing outpatient treatment at Nong Muang Khai Hospital in Phrae Province. The research instruments were the general information questionnaire, the Perception of Health status questionnaire, and the 9-question depression assessment. The content validity index was 0.67-1.00, and Cronbach's alpha reliability test yielded a score of 0.74-0.82. Data were analyzed using descriptive statistics, chi-square test and logistic regression analysis.</p> <p>The findings revealed a 21.40 percent prevalence of depression among Type 2 diabetes patients at Nong Muang Khai Hospital in Phrae province. Factors that were significantly related to depression in patients with type 2 diabetes at the 0.05 level are gender, having other comorbidities, and duration of diabetes. Factors that have a negative relationship with depression with a statistical significance at the 0.05 level was the adequacy of income. Consequently, the proposed guidelines for preventing depression in Type 2 diabetes patients recommend regular assessment and monitoring, particularly among female patients, those with insufficient income, individuals with other co-morbidities, and those who have been diabetic for a decade or more.</p> <p> </p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15697Image rejection analysis of digital radiographic imaging system in Phrae Hospital2024-08-27T15:05:32+07:00Varavut Kumthipvaravut15@hotmail.com<p>This quasi-experimental research aimed to 1) analyze the reasons for the rejection rate of digital X-ray images due to can not be used for diagnosis and 2) compare the number of digital X-ray images rejected due to can not be used for diagnosis for diagnosis in both before and after the implementation of the radiology quality improvement guidelines. The sample group was digital radiographic images from ACROMA digital X-ray machine of X-ray room no. 1, Radiology Department, Phrae Hospital, of 72,837 images. Data were collected from ACROMA X-ray machine (X-ray room number 1) processing and using a digital X-ray image recorded form that categorized according to the cause of the organ found. Data were analyzed using descriptive statistics and a paired sample t-test.</p> <p>The results of the research found that 1) the digital radiological images that were discarded because they could not be used for diagnosis before implementing the radiology quality development guidelines were 9.66 percent, the causes were positioning, QA/QC, and poor inspiration of 6.05%, 1.25% and 0.99%, respectively. The analysis results by location or area of the X-ray images found that the majority were located in the Abdomen/KUB, Pelvis/hip, and Chest of 13.25%, 9.16%, and 11.89%, respectively. 2) The results of the comparison of the difference in the average value of the excluded X-ray images before and after implementing the radiology quality development guidelines found that after implementing the radiology quality development guidelines, the number of excluded X-ray images decreased less than before implementing the radiology quality development guidelines, with statistical significance level of 0.05 (t = 3.24, p-value = 0.04).</p> <p> </p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15701The Relationship Between Human Resource Management, Competency and Performance of The Staff at Yasothon Hospital2024-08-27T15:15:05+07:00Sittichai Thongborsittichaith@hotmail.comPrasert Prasomrukhrphrae.ejournal@gmail.comKornkawat Darunikornhrphrae.ejournal@gmail.com<p>The aim of this cross-sectional survey research was to study the human resource management, competency, and performance of staff and the relationship of those factors among the 148 staff at Yasothon Hospital, including academic and support staff. The sample size was calculated by the correlation formula using the multistage sampling technique. The data were collected using a questionnaire created by the researcher with a reliability of 0.75. The descriptive and inferential statistics were used to calculated by the Pearson correlation coefficient.</p> <p>The results found that the majority of the population was female (75.0%), aged between 41 and 50 years old (30.4%), graduated with a bachelor's degree (56.8%), and had a job experience of less than 5 years (18.2%). The overall human resource management factor was moderated with a mean of 3.42 (S.D.=0.67), and the competency and performance of the staff were high with a mean of 4.07 (S.D.=0.54) and 3.99 (S.D.=0.57), respectively. Human resource management had a moderate level, while staff competency had a high level correlated with staff performance and was statistically significant in all aspects (p<0.001). Therefore, the human resource management system should be improved to be more efficient.</p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)https://thaidj.org/index.php/jpphd/article/view/15721Editorial2024-08-30T11:18:06+07:00Nithi Naewlek้hrphrae.ejournal@gmail.com<p>Editorial</p>2024-06-28T00:00:00+07:00Copyright (c) 2024 Journal of Phrae Public Health for Development (JPPHD)