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Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第9期16卷 3575-3594页

作者： shui-hua jiang Hong-Hu Jie Jiawei Xie Jinsong huang Chuang-Bing Zhou School of Infrastructure Engineering Nanchang UniversityXuefu Road 999Nanchang330031China Discipline of Civil Surveying and Environmental EngineeringFaculty of Engineering and Built EnvironmentThe University of NewcastleCallaghanNSW2308Australia

Probabilistic back-analysis is an important means to infer the statistics of uncertain soil parameters,making the slope reliability assessment closer to the engineering ***,multi-source information(including test data,monitored data,field observation and slope survival records)is rarely used in current probabilistic *** the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction under rainfalls by integrating multi-source information is a challenging task since thousands of random variables and high-dimensional likelihood function are usually *** this paper,a framework by integrating a modified Bayesian Updating with Subset simulation(mBUS)method with adaptive Conditional Sampling(aCS)algorithm is established for the probabilistic back-analysis of spatially varying soil parameters and slope reliability *** this framework,the high-dimensional probabilistic back-analysis problem can be easily tackled,and the multi-source information(*** pressure heads and slope survival records)can be fully used in the back-analysis.A real Taoyuan landslide case in Taiwan,China is investigated to illustrate the effectiveness and performance of the established *** findings show that the posterior knowledge of soil parameters obtained from the established framework is in good agreement with the field ***,the updated knowledge of soil parameters can be utilized to reliably predict the occurrence probability of a landslide caused by the heavy rainfall event on September 12,2004 or forecast the potential landslides under future rainfalls in the Fuhsing District of Taoyuan City,Taiwan,China.

关键词： Rainfall-induced landslide Spatial variability Probabilistic back-analysis Slope reliability analysis Bayesian updating

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 213-230页

作者： Faming huang Zuokui Teng Chi Yao shui-hua jiang Filippo Catani Wei Chen Jinsong huang School of Infrastructure Engineering Nanchang UniversityNanchang330031China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengdu610059China Department of Geosciences University of PadovaPadovaItaly College of Geology and Environment Xi’an University of Science and TechnologyXi’an710054China Discipline of Civil Surveying and Conditioning EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNewcastleNSWAustralia

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP *** study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning *** original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP ***,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter ***,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study *** typical machine learning models,*** perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP ***,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide *** conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random e

关键词： Landslide susceptibility prediction Conditioning factor errors Low-pass filter method Machine learning models Interpretability analysis

An updating of landslide susceptibility prediction from the perspective of space and time

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Geoscience Frontiers 2023年第5期14卷 295-307页

作者： Zhilu Chang Faming huang Jinsong huang shui-hua jiang Yuting Liu Sansar Raj Meena Filippo Catani School of Infrastructure Engineering Nanchang UniversityNanchang 330031China Department of Geosciences University of PaduaPaduaItaly Department of Civil Environmental and Architectural EngineeringUniversity of PaduaPadovaItaly Discipline of Civil Surveying and Environmental EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNSWAustralia

Due to the similarity of conditioning factors,the aggregation feature of landslides and the multi-temporal landslide inventory,the spatial and temporal effects of landslides need to be considered in landslide susceptibility prediction(LSP).The ignorance of this issue will result in some biases and time-invariance in landslide ***,a novel framework has been proposed to update landslide susceptibility by simultaneously considering the spatial and temporal effects of landslides at the regional *** this framework,the landslide inventory of Chongyi County has been divided into pre-and fresh-landslide *** to the LSP results predicted by the support vector machine(SVM)model using the slope unit-based conditioning factors and pre-landslide inventory,a normalized spatial distance index(NSDI)is calculated to quantitatively represent the spatial correlation between landslides and surrounding slope units to develop the SVM-NSDI ***,the SVM-Updating model,which incorporates the LSP results of the SVM-NSDI model and fresh-landslide inventory,could be developed to update the LSP ***,the confusion matrix,the area under the receiver operating characteristic curve(AUC)and frequency ratio(FR)accuracy are used to evaluate the prediction performance of the above LSP *** F1-score values of the SVM,SVM-NSDI and SVM-Updating models are 0.776,0.816 and 0.831,*** AUC values are 0.869,0.903 and 0.914 and the FR accuracies are 0.795,0.853 and *** can be concluded that landslide susceptibility is a time-variant variable,which can be updated by considering the spatial correlation between landslides and surrounding slope units as well as the temporal effects of multi-temporal landslide *** study provides a new framework to update landslide susceptibility over time and also provides more accurate LSP results for decisionmakers.

关键词： Landslide susceptibility updating Spatial effect Temporal effect Machine learning

Uncertainties in landslide susceptibility prediction modeling:A review on the incompleteness of landslide inventory and its influence rules

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Geoscience Frontiers 2024年第6期15卷 80-104页

作者： Faming huang Daxiong Mao shui-hua jiang Chuangbing Zhou Xuanmei Fan Ziqiang Zeng Filippo Catani Changshi Yu Zhilu Chang Jinsong huang Bingchen jiang Yijing Li School of Infrastructure Engineering Nanchang UniversityNanchang 330031China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengduSichuan 610059China Science and Technology Department of jiangxi Province Nanchang 330046China Department of Geosciences University of PadovaPadovaItaly Information Engineering School Nanchang UniversityNanchang 330031China Discipline of Civil Surveying and Conditioning EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNSWAustralia

Landslide inventory is an indispensable output variable of landslide susceptibility prediction(LSP)***,the influence of landslide inventory incompleteness on LSP and the transfer rules of LSP resulting error in the model have not been *** Xunwu County,China,as an example,the existing landslide inventory is first obtained and assumed to contain all landslide inventory samples under ideal conditions,after which different landslide inventory sample missing conditions are simulated by random *** includes the condition that the landslide inventory samples in the whole study area are missing randomly at the proportions of 10%,20%,30%,40%and 50%,as well as the condition that the landslide inventory samples in the south of Xunwu County are missing in ***,five machine learning models,namely,Random Forest(RF),and Support Vector Machine(SVM),are used to perform ***,the LSP results are evaluated to analyze the LSP uncertainties under various *** addition,this study introduces various interpretability methods of machine learning model to explore the changes in the decision basis of the RF model under various *** show that(1)randomly missing landslide inventory samples at certain proportions(10%–50%)may affect the LSP results for local areas.(2)Aggregation of missing landslide inventory samples may cause significant biases in LSP,particularly in areas where samples are missing.(3)When 50%of landslide samples are missing(either randomly or aggregated),the changes in the decision basis of the RF model are mainly manifested in two aspects:first,the importance ranking of environmental factors slightly differs;second,in regard to LSP modelling in the same test grid unit,the weights of individual model factors may drastically vary.

关键词： Landslide susceptibility prediction Landslide inventory Machine learning interpretability SHapley additive explanations Partial dependence plot

Clinicopathological differences between patients with schistosomal appendicitis and non schistosomal appendicitis:A retrospectively study of past ten years

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World Journal of Clinical Cases 2025年第2期13卷 24-32页

作者： Xiao-Yi Wang Yao Hao Zi-Jian Wang Xiu-Liang Xu jiang-hua Yang Department of Infectious Diseases The First Affiliated of Wannan Medical CollegeWuhu 241001Anhui ProvinceChina

BACKGROUND Chronic schistosomiasis causes multiple organ and multiple system diseases,especially the digestive *** eggs are mainly deposited in the stomach,liver and colorectal,but a few eggs are deposited in the appendix and cause *** present,there are few studies on schistosomal *** To explore the differences in epidemiological,clinical and pathological characteristics between schistosomal appendicitis and non-schistosomal appendicitis over the past decade in order to assess the impact of schistosomiasis on *** The differences of general data,clinical data and laboratory examination data of patients with appendicitis from October 2013 to October 2023 were retrospectively *** patients were divided into two groups for *** were 136 patients in schistosomal appendicitis group and 5418 patients in non-schistosomal appendicitis *** Schistosomal appendicitis accounted for 2.45%of all patients with appendicitis,and the annual proportion in the past decade was 2.2%,2.9%,1.8%,1.9%,3.4%,3.1%,1.9%,1.6%,3%,2.6%,*** prevalence of schistosomal appendicitis was middle-aged and elderly males,with an average age of 61.73±15.335 *** main population of non-schistosomal appendicitis was middle-aged men,with an average age of 35.8±24.013 years(P<0.001).The distribution of pathological types of appendicitis was different between the two groups(P<0.001).The incidence of acute suppurative appendicitis in non-schistosomal appendicitis was higher than that in schistosomal appendicitis[odds ratio(OR)=0.504;95%confidence interval(CI):0.349-0.728;P<0.001].The proportion of acute attack of chronic appendicitis in schistosomal appendicitis was higher than that in non-schistosomal appendicitis(OR=2.614;95%CI:1.815-3.763;P<0.001).The proportion of schistosomal appendicitis patients complicated with colorectal cancer was higher than that of nonschistosomal appendicitis patients(OR=5.087;95%CI:1.427-

关键词： Schistosomal appendicitis Schistosomiasis Appendix Colorectal cancer Clinicopathological characteristics

Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

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Nano-Micro Letters 2025年第1期17卷 98-134页

作者： Yang Shi Mingjun Wu Shengbo Ge Jianzhang Li Anoud Saud Alshammari Jing Luo Mohammed A.Amin hua Qiu Jinxuan jiang Yazeed M.Asiri Runzhou huang hua Hou Zeinhom M.El‑Bahy Zhanhu Guo Chong Jia Kaimeng Xu Xiangmeng Chen Co‑Innovation Center of Efficient Processing and Utilization of Forest Resources College of Materials Science and EngineeringNanjing Forestry UniversityNanjing 210037People’s Republic of China State Key Laboratory of Efficient Production of Forest Resourced Beijing Forestry UniversityQinghua East Road 35Haidian DistrictBeijing 100083People’s Republic of China Department of Physics Faculty of Sciences‑ArarNorthern Border UniversityArar 91431Saudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 1109921944 TaifSaudi Arabia Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’anShaanxi 710072People’s Republic of China Integrated Composites Lab Department of Mechanical and Construction EngineeringNorthumbria UniversityNewcastle Upon Tyne NE18STUK College of Materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024People’s Republic of China Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr CityCairo 11884Egypt Yunnan Provincial Key Laboratory of Wood Adhesives and Glued Products International Joint Research Center for Biomass MaterialsSouthwest Forestry UniversityKunming 650224People’s Republic of China School of Science Henan Agricultural UniversityZhengzhou 450002People’s Republic of China

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass *** materials offer numerous advantages such as being lightweight,porous,and *** to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding *** concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding *** particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be *** preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and *** composite methods and fillers of various biomass materials were *** paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

关键词： Biomass materials Electromagnetic interference shielding Micro-nano structure interface control Conductivity

Evolutionary p(x)-Laplacian Equation with a Convection Term

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Acta Mathematicae Applicatae Sinica 2019年第3期35卷 655-670页

作者： hua-shui ZHAN School of Applied Mathematics Xiamen University of Technology

The paper studies an evolutionary p(x)-Laplacian equation with a convection term ut=div(ρα|■u|p(x)-2■u)+∑N i=1■bi(u)/■xi,whereρ(x)=dist(x,■Ω),ess inf p(x)=p^->*** assure the well-posedness of the solutions,the paper shows only a part of the boundary,Σp■■Ω,on which we can impose the boundary value.Σp is determined by the convection term,in particular,when 1<α<(p^--2)/2,Σp={x∈■Ω:bi′(0)ni(x)<0}.So,there is an essential difference between the equation and the usual evolutionary p-Laplacian *** last,the existence and the stability of weak solutions are proved under the additional conditionsα<(p^--2)/2 andΣp=■Ω.

关键词： Evolutionary p(x)-Laplacian equation week solution Fichera-Oleinik theory boundary degeneracy

Analysis of the anti-T2DM components in dichloromethane fraction of Schisandra sphenanthera and its mechanism

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Traditional Medicine Research 2025年第1期10卷 27-43页

作者： Shi-Bo Feng Hai-Hui jiang Hui-Li Kang Yi jiang hua-Wei Zhang Xiao-Mei Song Yu-Ze Li Wen-Li huang Dong-Dong Zhang Chong Deng School of Pharmacy Shaanxi University of Chinese MedicineXianyang 712046China School of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine Shaanxi University of Chinese MedicineXianyang 712046China Key Laboratory for Research and Development of“Qin Medicine”of Shaanxi Administration of Traditional Chinese Medicine Xianyang 712046China Shaanxi Key Laboratory of Research and Application of“Taibai Qi Yao” Xianyang 712046China

Background:The type 2 diabetes mellitus(T2DM)pharmacodynamic study of various parts of Schisandra sphenanthera was conducted in the previous stage,and it was found that dichloromethane extracted part(SDP)had a significant hypoglycemic ***,the components of SDP were analyzed,and the specific mechanism of its anti-T2DM was ***:We used a high-fat,high-sugar diet in combination with streptozotocin to induce a T2DM rat model,and the model rats were divided into two groups according to body weight and blood ***,oral glucose tolerance test,fasting blood glucose,low density lipoprotein cholesterol,superoxide dismutase,insulin,glycated hemoglobin,total cholesterol,nonesterified free fatty acids,alanine aminotransferase,high-density lipoprotein cholesterol,aspartate aminotransferase,malondialdehyde,and glutathione peroxidase were measured,organ indices were calculated,and pathological sections of pancreas and liver were *** 16S rRNA V3–V4 region of intestinal flora was sequenced to explore the effect of SDP on biochemical indicators and intestinal *** on the above indicators,the anti-T2DM mechanism of SDP in Schisandra sphenanthera was ***:After six weeks of administration,the biochemical indices of diabetic rats were diminished compared to the control *** SDP could significantly increase the gut microbialα-diversity index,resulting in significant changes in the flora of T2DM rats,with increased richness and diversity,reduced harmful flora,and significantly back-regulated the levels of acetic acid,propionic acid,and butyric ***:SDP can improve the symptoms associated with elevated blood glucose,dyslipidemia,elevated fasting insulin levels,and damaged glucose tolerance in *** against T2DM may be through the control of intestinal flora to normalize and exert anti-diabetic effect;its main active components may be lignans and terpenoids.

关键词： Schisandra sphenanthera T2DM intestinal flora HPLC

High Strength and Stable Proton Exchange Membrane Based on Perfluorosulfonic Acid/Polybenzimidazole

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Chinese Journal of Polymer Science 2022年第7期40卷 764-771页

作者： Tang-Cheng Xu Chang-shui Wang Zhao-Yu Hu Jiao-Jiao Zheng Shao-hua jiang shui-Jian He Hao-Qing Hou College of Chemistry and Chemical Engineering Jiangxi Normal UniversityNanchang330022China Co-Innovation Center of Efficient Processing and Utilization of Forest Resources College of Materials Science and EngineeringNanjing Forestry UniversityNanjing210037China

In this work,a series of high strength,thermal stable and antioxidant proton exchange membranes were designed with solution processible polybenzimidazole(PBI)as the matrix and perfluorosulfonic acid(PFSA)as the fortifier for proton *** processible PBI was successfully synthesized by introducing 4,4’-dicarboxydiphenyl ether into the molecular chains of ***/PBI composite membranes were obtained by solution blending and film *** and PFSA/PBI composite membranes exhibited greatly enhanced tensile strength and Young’s modulus compared to ***/PBI composite membranes are stable below 300℃ which are suitable for practical application in proton exchange membrane fuel *** PFSA/PBI composite membranes show good dimensional stability with low water uptake and swelling *** PFSA/PBI composite membranes also exhibit excellent antioxidation stability with less than 5%initial mass loss over 120 h in Fenton *** proton conductivity of PBI is greatly enhanced by blending with PFSA and the proton conductivities of the composite membranes are increased with the raise of PFSA content and *** work offers valuable insights into the exploration of PBI based high-performance proton exchange membranes.

关键词： Solution processible polybenzimidazole Perfluorosulfonic acid Proton exchange membrane Film casting High strength