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Spatio-temporal analysis of forest fire events in the Margalla Hills,Islamabad,Pakistan using socio-economic and environmental variable data with machine learning methods

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Journal of Forestry Research 2022年第1期33卷 183-194页

作者： Aqil Tariq Hong Shu saima siddiqui Iqra Munir Alireza Sharifi Qingting Li Linlin Lu State Key Laboratory of Information Engineering in SurveyingMapping and Remote SensingWuhan UniversityWuhan 430079HubeiPeople’s Republic of China Department of Geography University of the PunjabLahorePunjabPakistan Department of Surveying Engineering Faculty of Civil EngineeringShahid Rajaee Teacher Training UniversityTehranIran Airborne Remote Sensing Center Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094People’s Republic of China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094People’s Republic of China

Most forest fires in the Margalla Hills are related to human activities and socioeconomic factors are essential to assess their likelihood of *** study considers both environmental(altitude,precipitation,forest type,terrain and humidity index)and socioeconomic(population density,distance from roads and urban areas)factors to analyze how human behavior affects the risk of forest *** entropy(Maxent)modelling and random forest(RF)machine learning methods were used to predict the probability and spatial diffusion patterns of forest fires in the Margalla *** receiver operating characteristic(ROC)curve and the area under the ROC curve(AUC)were used to compare the *** studied the fire history from 1990 to 2019 to establish the relationship between the probability of forest fire and environmental and socioeconomic *** Maxent,the AUC fire probability values for the 1999 s,2009 s,and 2019 s were 0.532,0.569,and 0.518,respectively;using RF,they were 0.782,0.825,and 0.789,*** were mainly distributed in urban areas and their probability of occurrence was related to accessibility and human behaviour/*** principles for validation were greater in the random forest models than in the Maxent *** results can be used to establish preventive measures to reduce risks of forest fires by considering socio-economic and environmental conditions.

关键词： Forest fires Maxent GIS Disaster risk reduction Random forest machine learning Multi-temporal analysis

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GC/GCMS analysis of the petroleum ether and dichloromethane extracts of Moringa oleifera roots

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Asian Pacific Journal of Tropical Biomedicine 2014年第8期4卷 650-654页

作者： Shaheen Faizi saima sumbul Muhammed Ali Versiani Rubeena Saleem Aisha Sana Hira siddiqui HEJ Research Institute of Chemistry International Center for Chemical and Biological SciencesUniversity of KarachiKarachi-75270Pakistan Department of Chemistry Federal Urdu University of ArtsSciences and TechnologyGulshan-e-IqbalScience CampusKarachi-75300Pakistan Pharmaceutical Chemistry Faculty of PharmacyHamdard UniversityKarachi-74600Pakistan Dr HMI Institute of Pharmacology and Herbal SciencesHamdard UniversityKarachi-74600Pakistan

Objective:To explore the phytochemical constituents from petroleum ether and diehloromethane extracts of Moringa oleifera(***)roots using GC/GC—***:A total of 5.11 kg fresh and undried crashed root of *** were cut into small pieces and extracted with petroleum ether and diehloromethane(20 ***) at room temperature for 2 *** concentrated extracts were subjected to their GC—MS ***:The GC-MS analysis of the petroleum ether and diehloromethane extracts of *** roots,which showed promising biological activities,has resulted in the identification 102 *** constituents belong to 15 classes of compounds including hydrocarbons,fatty acids,esters,alcohols,***,pyrazine,***,steroids,*** and N-hydroxyimine derivatives,unsaturated *** and ***/GC-MS studies on petroleum ether extraet of the roots revealed that it contained 39 compounds,belonging to nine *** S8 has been isolated as a pure compound from the *** major compounds identified from petroleum ether extract were trans-13-clocosene(37.9%).nonacosane(32.6%).cycloartenol(28.6%) nonadecanoic acid(13.9%) and cyclooctasulfur S8(13.9%).Dichloromethane extract of the roots was composed of 63 compounds of which nasimizinol(58.8%) along with oleic acid(46.5%),N—benzyl-N-(7—cyanato heptanamide(38.3%),N—benzyl-N—(1—chlorononyl) amide(30.3%),bis[3—benzyl prop-2-ene]-1-one(19.5%) and N.N-dibeuzyl—2-ene pent 1.5—diamide(11.6%) were the main ***:This study helps to predict the formula and structure of active molecules which can be used as *** result also enhances the traditional usage of *** which possesses a number of bioactive compounds.

关键词： Moringa oleifera Moringaceae Roots Petroleum ether and dichloromethane extracts Cyclooctasulfur S8 GC/GCMS

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