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Permafrost change in Northeast China in the 1950s-2010s

Advances in Climate Change Research 2021年第1期12卷 18-28页

作者： ZHANG Zhong-Qiong WU Qing-Bai HOU Mei-Ting TAI Bo-Wen AN Yu-Ke State Key Laboratory of Frozen Soils engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of ScienceLanzhou730000China China Meteorological Administration Training Centre Beijing100081China Gansu Province Transportation Planning Survey&Design Institute Limited Liability CompanyLanzhou730000China

Permafrost in Northeast China is highly sensitive to climate *** degradation significantly affects forest and vegetation ecosystems,as well as the safety of engineering projects and other man-made ***,the permafrost change in the region is still *** study uses metrological data from 258 weather stations,alongside reanalysis data,and other environmental data to investigate permafrost degradation and its related environmental impacts in Northeast China from the 1950s to *** show that the total permafrost area decreased from 4.8×10^(5)to 3.1×10^(5)km^(2)from the 1950s to the *** southern limit of permafrost moved 0.1-1.1°northward,and its average elevation rose 160.5 *** the study period,the degradation of predominantly continuous permafrost,and discontinuous and island permafrost was more pronounced than that of sparsely island *** south boundary of those three permafrost zones northward by 0-3.4°,0-5.5°and 0.4-1.1°,the average altitude raised by 339.2 m,208.3 m,67.1 *** permafrost degradation shows the elevation and latitude *** degradation is mainly caused by the rising of surface temperatures and the impacts of other environmental *** snowfall warming the ground of 1.1-10.2℃in cold seasons and rainfall cooling on surface conditions in warm seasons,those may result in temporal and spatial differences in permafrost ***,there are lack of researches in the impact of environment factors on soil temperatures,moisture and permafrost degradation.

关键词： Northeast China Climate warming Permafrost degradation Impact of environmental factors

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Bibliometric Review of Biodiversity Offsetting During 1992-2019

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Chinese Geographical Science 2022年第2期32卷 189-203页

作者： YU Shuling CUI Baoshan XIE Chengjie man Ying FU Jing State Key Laboratory of Water environment Simulation School of EnvironmentBeijing Normal UniversityBeijing 100875China School of environmental Science and engineering Tiangong UniversityTianjin 300387China Yellow River Estuary Wetland Ecosystem Observation and Research Station Ministry of EducationDongying 257500China East China Sea Fisheries Research institute Chinese Academy of Fishery SciencesShanghai 200090China

Biodiversity offsetting plays a crucial role in managing the impacts of development on natural habitats. Developers, conservation groups, governments and financial institutions have used biodiversity offsetting to design measurable conservation actions to compensate for significant residual adverse biodiversity impacts arising from development. However, the concepts and methodologies of biodiversity offsetting have rarely been systematically reviewed, and best practices are still lacking. This hinders the development and applications of this field, and makes it difficult for new researchers to learn, develop, and apply biodiversity offsetting. This paper aims to review research progress on biodiversity offsetting during the period of 1992 to 2019. We mainly used bibliometric analysis and social network analysis methods to expose the topic diversity, development and promotion of this research field, and assess collaboration among biodiversity offsetting scholars. Our research identified 1190 records, and revealed that the total number of publications increased rapidly since 2002. The most productive journal, country, and author were Biological Conservation, USA, and Dr. Maron M of University of Queensland, respectively. Co-author analysis identified that the 23 authors most relevant to biodiversity offsetting were involved in a collaboration network. And they were mainly from 30 countries in a collaboration network, and the authors from USA, Australia and the United Kingdom have the most cooperation, which mainly driven by policy related to biodiversity offsetting. Our review shows that biodiversity offsetting research is at an early stage of rapid development with topically diverse and collaborative science domains. The majority of studies focus on terrestrial environments, which makes the implementation of aquatic ecosystem is more difficult. Theoretical problems and the implications of research evolution and social network in biodiversity offsetting are discussed,

关键词： academic influence biodiversity offsetting compensation bibliometric analysis social network analysis

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Hybrid assembly of conducting nanofiber network for ultra-stretchable and highly sensitive conductive hydrogels

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Journal of Materials Science & Technology 2024年第2期169卷 1-10页

作者： Yalei Wang Shulong Zeng Shaohong Shi Yuheng Jiang Zhiwei Du Bingzhen Wang Xiurong Li State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures School of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China State Key Laboratory of Polymer Materials engineering Polymer Research Institute of Sichuan UniversitySichuan UniversityChengdu 610065China

Conductive hydrogels have attracted extensive attention owing to their promising application prospects in flexible and wearable ***,achieving both high sensitivity and mechanical robustness remains ***,a novel and versatile conductive hydrogel based on the hybrid assem-bly of conductive cellulose nanofiber(CNF)networks has been designed and *** by the templating effect of CNFs and stabilizing effect of negatively charged poly(styrene sulfonate)(PSS),conducting polymer poly(3,4-ethylenedioxythiophene)(PEDOT)was self-organized into three-dimensional nanostructures which constructed a robust conductive network after in-situ oxidative *** unique structure derived from CNF bio-template endowed polyacrylamide(PAM)hydrogels with improved electrical conductivity and excellent mechanical *** a result,the as-fabricated CNF/PEDOT:PSS/PAM hydrogel exhibited an ultimate tensile strain of 1881%and toughness of 3.72 MJ/m^(3),which were 4.07 and 8.27 times higher than the CNF-free hydrogel,*** significantly,the resultant hydrogel sensor showed highly desirable sensing properties,including remarkable sensing range(1100%),high gauge factor(GF=5.16),fast response time(185 ms),and commendable durability,as well as good ***,the hydrogel sensor was able to distinguish subtle physiological activities including phonation and facial expression,and monitor large human body motions such as finger flexion and elbow ***,it was feasible to integrate the strain sensor on the joints of robots to recognize complicated machine motion signals,showing potential in advanced human-machine interactions.

关键词： Strain sensor Cellulose nanofibers PEDOT:PSS Conductive hydrogel Templating method

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Study of Wave and Tide Influence on Slope Stability of the Navigation Channel of Tianjin Port

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China Ocean engineering 2007年第4期21卷 689-700页

作者：李飒 Lars GRANDE 赵智邦刘国辉杨进良 Geotechnical institute Civil Engineering DepartmentTianjin University Civil and Transport engineering Department Norwegian University of Science and TechnologyTrondheim NO-7491Norway China Communication First Design institute of Navigation engineering

The Tianjin Port is the largest man-made port in China. Since the navigation channel of the Tianjin Port is constructed by dredging, a very important problem, as many people concerned, is the submarine slope stability. As the environment on land is different from that in submarine, it is necessary to evaluate the influence of the environmental loading, such as wave and tide, on the stability of navigation channel slope. In the present study, based on the observed results, the characteristics of the navigation channel slope are summarized, and the causes of creating the special slope shape are analyzed. The ioles of waves and tides are evaluated, and failure mechanics are discussed to helq us predict what will happen in the future.

关键词： submarine wave tide slope stability navigation channel

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Digital Twin for Human-Robot Interactive Welding and Welder Behavior Analysis

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 334-343页

作者： Qiyue Wang Wenhua Jiao Peng Wang YuMing Zhang institute for Sustainable manufacturing and the Department of Electrical and Computer engineering University of KentuckyLexingtonKY 40506 USA the institute for Sustainable manufacturing and the Department of Electrical and Computer engineering and also with the Department of Mechanical EngineeringUniversity of KentuckyLexingtonKY 40506 USA

This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior *** humanrobot interaction(HRI)working style helps to enhance human users'operational productivity and comfort;while data-driven welder behavior analysis benefits to further novice welder *** HRI system includes three modules:1)a human user who demonstrates the welding operations offsite with her/his operations recorded by the motion-tracked handles;2)a robot that executes the demonstrated welding operations to complete the physical welding tasks onsite;3)a DT system that is developed based on virtual reality(VR)as a digital replica of the physical human-robot interactive welding *** DT system bridges a human user and robot through a bi-directional information flow:a)transmitting demonstrated welding operations in VR to the robot in the physical environment;b)displaying the physical welding scenes to human users in *** to existing DT systems reported in the literatures,the developed one provides better capability in engaging human users in interacting with welding scenes,through an augmented *** verify the effectiveness,six welders,skilled with certain manual welding training and unskilled without any training,tested the system by completing the same welding job;three skilled welders produce satisfied welded workpieces,while the other three unskilled do not.A data-driven approach as a combination of fast Fourier transform(FFT),principal component analysis(PCA),and support vector machine(SVM)is developed to analyze their *** an operation sequence,i.e.,motion speed sequence of the welding torch,frequency features are firstly extracted by FFT and then reduced in dimension through PCA,which are finally routed into SVM for *** trained model demonstrates a 94.44%classification accuracy in the testing *** successful pattern recognition in skilled

关键词： Digital twin(DT) human-robot interaction(HRI) machine learning virtual reality(VR) welder behavior analysis

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Economic Risk Assessment of Future Debris Flows by machine Learning Method

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International Journal of Disaster Risk Science 2024年第1期15卷 149-164页

作者： Chenchen Qiu Lijun Su Alessandro Pasuto Giulia Bossi Xueyu Geng School of engineering University of WarwickCoventry CV47ALUK Key Laboratory of Mountain Hazards and Earth Surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Research institute for Geo-Hydrological Protection(IRPI-CNR) National Research Council of ItalyPadova 35127Italy

A reliable economic risk map is critical for effective debris-flow ***,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its *** estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability *** selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every *** debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual *** employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate ***,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical ***,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and *** economic loss of elements at risk was calculated based on physical vulnerabilities and their economic ***,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow *** this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on *** results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire *** findings can provide a scientific support for the effective mitigation of future debris flows.

关键词： Economic risk Future debris fows Gyirong Zangbo Basin machine learning model Physical vulnerability matrix Southwest Tibet,China

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Mapping landslide susceptibility at the Three Gorges Reservoir, China, using gradient boosting decision tree,random forest and information value models

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Journal of Mountain Science 2020年第3期17卷 670-685页

作者： CHEN Tao ZHU Li NIU Rui-qing TRINDER C John PENG Ling LEI Tao institute of Geophysics and Geomatics China University of GeosciencesWuhan 430074China Geomatics Technology and Application key Laboratory of Qinghai Province Xining 810001China School of Civil and environmental engineering The University of New South WalesSydneyNSW 2052Australia China institute of Geo-environment Monitoring Beijing 100081China School of Electronical and Information engineering Shaanxi University of Science and TechnologyXi’an 710021China

This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR.

关键词： Mapping landslide susceptibility Gradient boosting decision tree Random forest Information value model Three Gorges Reservoir

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Cardiovascular Disease Prediction Among the Malaysian Cohort Participants Using Electrocardiogram

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Computers, Materials & Continua 2022年第4期71卷 1111-1132页

作者： Mohd Zubir Suboh Nazrul Anuar Nayan Noraidatulakma Abdullah Nurul Ain Mhd Yusof Mariatul Akma Hamid Azwa Shawani Kamalul Arinfin Syakila Mohd Abd Daud Mohd Arman Kamaruddin Rosmina Jaafar Rahman Jamal Faculty of engineering and Built environment Universiti Kebangsaan MalaysiaBangi43600Malaysia Medical engineering Technology Section Universiti Kuala Lumpur British Malaysian InstituteGombak53100Malaysia Institut Islam Hadhari Universiti Kebangsaan MalaysiaBangi43600Malaysia UKM Medical Molecular Biology institute(UMBI) Kuala Lumpur56000Malaysia Faculty of Health Sciences Universiti Kebangsaan MalaysiaBangi43600Malaysia

A comprehensive study was conducted to differentiate cardiovascular disease (CVD) subjects from non-CVD subjects using short recording electrocardiogram (ECG) of 244 Malaysian adults in The MalaysianCohort project. An automated peak detection algorithm to detect nine fiducialpoints of electrocardiogram (ECG) was developed. Forty-eight features wereextracted in both time and frequency domains, including statistical featuresobtained from heart rate variability and Poincare plot analysis. These includefive new features derived from spectrum counts of five different frequencyranges. Feature selection was then made based on p-value and correlationmatrix. Selected features were used as input for five classifiers of artificialneural network (ANN), k-nearest neighbors (kNN), support vector machine(SVM), discriminant analysis (DA), and decision tree (DT). Results showedthat six features related to T wave were statistically significant in distinguishingCVD and non-CVD groups. ANN had performed the best with 94.44% specificity and 86.3% accuracy, followed by kNN with 80.56% specificity, 86.49%sensitivity and 83.56% accuracy. The novelties of this study were in providingalternative solutions to detect P-onset, P-offset, T-offset as well as QRS-onsetpoints using discrete wavelet transform method. Additionally, two out of thefive newly proposed spectral features were significant in differentiating bothgroups, at frequency ranges of 1–10 Hz and 5–10 Hz. The prediction outcomeswere also comparable to previous related studies and significantly importantin using ECG to predict cardiac-related events among CVD and non-CVDsubjects in the Malaysian population.

关键词： Cardiovascular disease ECG fiducial point detection electrocardiogram feature extraction machine learning

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Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

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Frontiers of environmental Science & engineering 2023年第11期17卷 223-238页

作者： Jin Xue Fangting Wang Kun Zhang Hehe Zhai Dan Jin Yusen Duan Elly Yaluk Yangjun Wang Ling Huang Yuewu Li Thomas Lei Qingyan Fu Joshua S.Fu Li Li School of environmental and Chemical engineering Shanghai UniversityShanghai 200444China Key Laboratory of Organic Compound Pollution Control engineering(MOE) Shanghai UniversityShanghai 200444China Shanghai environmental Monitoring Center Shanghai 200235China institute of Science and environment University of Saint JosephMacao 999078China Department of Civil and environmental engineering University of TennesseeKnoxvilleTN 37996USA

Surface ozone(O_(3))is influenced by regional background and local photochemical formation under favorable meteorological *** the contribution of these factors to changes in O_(3)is crucial to address the issue of O_(3)*** this study,we propose a novel integrated method that combines random forest,principal component analysis,and Shapley additive explanations to distinguish observed O_(3)into meteorologically affected ozone(O_(3_MET)),chemically formed from local emissions(O_(3_LC)),and regional background ozone(O_(3_RBG)).Applied to three typical stations in Shanghai during the warm season from 2013 to 2021,the results indicate that O_(3_RBG)in Shanghai was 48.8±0.3 ppb,accounting for 79.6%–89.4%at different sites,with an overall declining trend of 0.018 ppb/yr.O_(3_LC)at urban and regional sites ranged from 5.9–9.0 ppb and 8.9–14.6 ppb,respectively,which were significantly higher than the contributions of 2.5–7.4 ppb at an upwind background site.O_(3_MET)can be categorized into those affecting O_(3)photochemical generation and those changing O_(3)dispersion conditions,with absolute contributions to O_(3)ranging from 13.4–19.0 ppb and 13.1–13.7 ppb,*** found that the O_(3)rebound in 2017,compared to 2013,was primarily influenced by unfavorable O_(3)dispersion conditions and unbalanced emission reductions;while the O_(3)decline in 2021,compared to 2017,was primarily influenced by overall favorable meteorological conditions and further emissions *** findings highlight the challenge of understanding O_(3)change due to meteorology and regional background,emphasizing the need for systematic interpretation of the different components of O_(3).

关键词： Ozone Integrated method machine learning

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AI-based small arms firing skill evaluation system in the military domain

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Defence Technology（防务技术） 2023年第11期29卷 164-180页

作者： Rezoanul Hafiz Chandan Nusrat Sharmin Muhaimin Bin Munir Abdur Razzak Tanvir Ahamad Naim Tasneem Mubashshira Mokhlesur Rahman Department of Computer Science and engineering Military Institute of Science and TechnologyDhakaBangladesh

Evaluation system of small arms firing has an important effect in the context of military domain. A partially automated evaluation system has been conducted and performed at the ground level. Automation of such system with the inclusion of artificial intelligence is a much required process. This papers puts focus on designing and developing an AI-based small arms firing evaluation systems in the context of military environment. Initially image processing techniques are used to calculate the target firing score. Additionally, firing errors during the shooting have also been detected using a machine learning algorithm. However, consistency in firing requires an abundance of practice and updated analysis of the previous results. Accuracy and precision are the basic requirements of a good shooter. To test the shooting skill of combatants, firing practices are held by the military personnel at frequent intervals that include 'grouping' and 'shoot to hit' scores. Shortage of skilled personnel and lack of personal interest leads to an inefficient evaluation of the firing standard of a firer. This paper introduces a system that will automatically be able to fetch the target data and evaluate the standard based on the fuzzy *** it will be able to predict the shooter performance based on linear regression ***, it compares with recognized patterns to analyze the individual expertise and suggest improvements based on previous values. The paper is developed on a Small Arms Firing Skill Evaluation System, which makes the whole process of firing and target evaluation faster with better accuracy. The experiment has been conducted on real-time scenarios considering the military field and shows a promising result to evaluate the system automatically.

关键词： machine learning Processing Firing system Artificial intelligence

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