As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been ...As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.展开更多
The toxicity of the new hemostatic material S-100 absorbable stanching satin was studied by embedding it in the body of rats. The staching satin embedded in the abdominal cavity of rats could be absorbed rapidly witho...The toxicity of the new hemostatic material S-100 absorbable stanching satin was studied by embedding it in the body of rats. The staching satin embedded in the abdominal cavity of rats could be absorbed rapidly without any macroscopic residue or organic abnormality in one week. After being embedded outside the dura mater of rats for a week, some stanching satin was found to remain in the form of unadherent small soft balls which disappeared in one more week. In the pathological examination no residue in cells was found in the major organs, and no degeneration, necrosis, hemorrhage or thrombosis in these organs and the vessels was observed. All the biochemical parameters in blood and routine urine examination were in the normal ranges. The results of the three behavior function tests were negative. It showed S-100 stanching satin, embedded in the body of rats for 12 weeks, had neither general toxicity nor adverse effect on the higher nervous activity, general behavior and equilibrium function of rats.展开更多
The distribution of soil salinization was investigated based on GIS and field sampling in Tianjin Binhai New Area. The results showed that the average soil total salt content was 0.818%, with an average pH of 8.43, an...The distribution of soil salinization was investigated based on GIS and field sampling in Tianjin Binhai New Area. The results showed that the average soil total salt content was 0.818%, with an average pH of 8.43, and the average CI and Na＋ contents were 0.27% and 0.22%, respectively. Presenting zonal distribution feature, the soil total salt content increased gradually from west to east of Binhai New Area. Statistics on the distribution areas of different salinization degrees showed that the area of non-salinzed soils only accounted for 3.18% of the total area; with an area of 107.43 km2, mild saline soil accounted for 6.34% of the total area; the area of moderate saline soil was 173.51 km2, accounting for 10.24%; and the area of sal- inzed soils was 217.36 km2, accounting for 12.82% of the total soil area. The area of saline soils （total salt content 〉0.6%） was 1 142.8 km2, accounting 67.42% of the total land area in Binhai New Area. And the areas for the soils with total salt content of 0.6%-1.0%, 1.0%-1.5%, 〉1.5% were respectively 388.47, 411.82, 342.51 km2, accounting for 22.92%, 24.3%, 20.21% of the total area.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41807192,41790441)Innovation Capability Support Program of Shaanxi(Grant No.2020KJXX-005)Natural Science Basic Research Program of Shaanxi(Grant Nos.2019JLM-7,2019JQ-094)。
文摘As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.
文摘The toxicity of the new hemostatic material S-100 absorbable stanching satin was studied by embedding it in the body of rats. The staching satin embedded in the abdominal cavity of rats could be absorbed rapidly without any macroscopic residue or organic abnormality in one week. After being embedded outside the dura mater of rats for a week, some stanching satin was found to remain in the form of unadherent small soft balls which disappeared in one more week. In the pathological examination no residue in cells was found in the major organs, and no degeneration, necrosis, hemorrhage or thrombosis in these organs and the vessels was observed. All the biochemical parameters in blood and routine urine examination were in the normal ranges. The results of the three behavior function tests were negative. It showed S-100 stanching satin, embedded in the body of rats for 12 weeks, had neither general toxicity nor adverse effect on the higher nervous activity, general behavior and equilibrium function of rats.
基金Supported by the National Key Technology R&D Program during the 11th Five-Year Plan,China (2007BAD67B01)~~
文摘The distribution of soil salinization was investigated based on GIS and field sampling in Tianjin Binhai New Area. The results showed that the average soil total salt content was 0.818%, with an average pH of 8.43, and the average CI and Na＋ contents were 0.27% and 0.22%, respectively. Presenting zonal distribution feature, the soil total salt content increased gradually from west to east of Binhai New Area. Statistics on the distribution areas of different salinization degrees showed that the area of non-salinzed soils only accounted for 3.18% of the total area; with an area of 107.43 km2, mild saline soil accounted for 6.34% of the total area; the area of moderate saline soil was 173.51 km2, accounting for 10.24%; and the area of sal- inzed soils was 217.36 km2, accounting for 12.82% of the total soil area. The area of saline soils （total salt content 〉0.6%） was 1 142.8 km2, accounting 67.42% of the total land area in Binhai New Area. And the areas for the soils with total salt content of 0.6%-1.0%, 1.0%-1.5%, 〉1.5% were respectively 388.47, 411.82, 342.51 km2, accounting for 22.92%, 24.3%, 20.21% of the total area.
