Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the...Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.展开更多
Emerging and re-emerging viruses continue to surface all over the world.Some of these viruses have the potential for rapid and global spread with high morbidity and mortality,such as the SARS coronavirus outbreak.It i...Emerging and re-emerging viruses continue to surface all over the world.Some of these viruses have the potential for rapid and global spread with high morbidity and mortality,such as the SARS coronavirus outbreak.It is extremely urgent and important to identify a novel virus near-instantaneously to develop an active preventive and/or control strategy.As a cultureindependent approach,viral metagenomics has been widely used to investigate highly divergent and completely new viruses in humans,animals,and even environmental samples in the past decade.A new model of Koch's postulates,named the metagenomic Koch's postulates,has provided guidance for the study of the pathogenicity of novel viruses.This review explains the viral metagenomics strategy for virus discovery and describes viruses discovered in human feces in the past 10 years using this approach.This review also addresses issues related to the metagenomic Koch's postulates and the challenges for virus discovery in the future.展开更多
基金Science and Research Branch, Islamic Azad University
文摘Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.
文摘Emerging and re-emerging viruses continue to surface all over the world.Some of these viruses have the potential for rapid and global spread with high morbidity and mortality,such as the SARS coronavirus outbreak.It is extremely urgent and important to identify a novel virus near-instantaneously to develop an active preventive and/or control strategy.As a cultureindependent approach,viral metagenomics has been widely used to investigate highly divergent and completely new viruses in humans,animals,and even environmental samples in the past decade.A new model of Koch's postulates,named the metagenomic Koch's postulates,has provided guidance for the study of the pathogenicity of novel viruses.This review explains the viral metagenomics strategy for virus discovery and describes viruses discovered in human feces in the past 10 years using this approach.This review also addresses issues related to the metagenomic Koch's postulates and the challenges for virus discovery in the future.
