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Using Support Vector Machine to Predict Eco-environment Burden:A Case Study of Wuhan,Hubei Province,China

Biomedical and Environmental Sciences 2008年第1期21卷 45-52页

作者： XIANG-MEI LI jing-xuan zhou SONG-HU YUAN XIN-PING zhou QIANG FU School of Environmental Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China China Environmental Monitoring Center Beijing 100029 China

Objective The human socio-economic development depends on the planet＇s natural capital. Humans have had a considerable impact on the earth, such as resources depression and environment deterioration. The objective of this study was to assess the impact of socio-economic development on the ecological environment of Wuhan, Hubei Province, China, during the general planning period 2006-2020. Methods Support vector machine （SVM） model was constructed to simulate the process of eco-economic system of Wuhan. Socio-economic factors of urban total ecological footprint （TEF） were selected by partial least squares （PLS） and leave-one-out cross validation （LOOCV）. Historical data of socio-economic factors as inputs, and corresponding historical data of TEF as target outputs, were presented to identify and validate the SVM model. When predicted input data after 2005 were presented to trained model as generalization sets, TEFs of 2005, 2006,…, till 2020 were simulated as output in succession. Results Up to 2020, the district would have suffered an accumulative TEF of 28.374 million gha, which was over 1.5 times that of 2004 and nearly 3 times that of 1988. The per capita EF would be up to 3.019 gha in 2020. Contusions The simulation indicated that although the increase rate of GDP would be restricted in a lower level during the general planning period, urban ecological environment burden could not respond to the socio-economic circumstances promptly. SVM provides tools for dynamic assessment of regional eco-environment. However, there still exist limitations and disadvantages in the model. We believe that the next logical step in deriving better dynamic models of ecosystem is to integrate SVM and other algorithms or technologies.

关键词： Urban eco-environment Total ecological footprint Support vector machine Partial least square

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Forecasting Loss of Ecosystem Service Value Using a BP Network: A Case Study of the Impact of the South-to-north Water Transfer Project on the Ecological Environmental in Xiangfan, Hubei Province, China

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Biomedical and Environmental Sciences 2003年第4期16卷 379-391页

作者： YUN-FENG CHEN, jing-xuan zhou, JIE XIAO, AND YAN-PING LIEnvironmental Science and Engineering College, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China Environmental Science and Engineering College Huazhong University of Science and Technology 湖北 Wuhan 430074

Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific countermeasures. Methods A three-layer BP network was built to simulate topology and process of the eco-economy system of Xiangfan. Historical data of ecological environmental factors and socio-economic factors as inputs, and corresponding historical data of ecosystem service value (ESV) and GDP as target outputs, were presented to train and test the network. When predicted input data after 2001 were presented to trained network as generalization sets, ESVs and GDPs of 2002, 2003, 2004... till 2050 were simulated as output in succession. Results Up to 2050, the area would have suffered an accumulative total ESV loss of RMB 104.9 billion, which accounted for 37.36% of the present ESV. The coinstantaneous GDP would change asynchronously with ESV, it would go through an up-to-down process and finally lose RMB89.3 billion, which accounted for 18.71% of 2001. Conclusions The simulation indicates that ESV loss means damage to the capability of socio-economic sustainable development, and suggests that artificial neural networks (ANNs) provide a feasible and effective method and have an important potential in ESV modeling.

关键词： Artificial neural network BP Ecosystem service value South-to-north Water Transfer Project

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Revealing the role of calcium ion intercalation of hydrated vanadium oxides for aqueous zinc-ion batteries

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Journal of Energy Chemistry 2024年第8期95卷 9-19,I0001页

作者： Tao zhou xuan Du Guo Gao Key Laboratory for Thin Film and Micro Fabrication of the Ministry of Education School of Sensing Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Exploring suitable high-capacity V_(2)O_(5)-based cathode materials is essential for the rapid advancement of aqueous zinc ion batteries(ZIBs).However,the typical problem of slow Zn^(2+)diffusion kinetics has severely limited the feasibility of such *** this work,unique hydrated vanadates(CaVO,BaVO)were obtained by intercalation of Ca^(2+)or Ba^(2+)into hydrated vanadium *** the CaVO//Zn and BaVO//Zn batteries systems,the former delivered up to a 489.8 mAh g^(-1)discharge specific capacity at 0.1 A g^(-1).Moreover,the remarkable energy density of 370.07 Wh kg^(-1)and favorable cycling stability yard outperform BaVO,pure V_(2)O_(5),and many reported cathodes of similar ionic intercalation *** addition,pseudocapacitance analysis,galvanostatic intermittent titration(GITT)tests,and Trasatti analysis revealed the high capacitance contribution and Zn^(2+)diffusion coefficient of CaVO,while an in-depth investigation based on EIS elucidated the reasons for the better electrochemical performance of ***,ex-situ XRD,XPS,and TEM tests further demonstrated the Zn^(2+)insertion/extraction and Zn-storage mechanism that occurred during the cycle in the CaVO//Zn battery *** work provides new insights into the intercalation of similar divalent cations in vanadium oxides and offers new solutions for designing cathodes for high-capacity aqueous ZIBs.

关键词： Aqueous zinc ion batteries Cathode materials Ion pre-intercalation Vanadium oxides Energy storage mechanism

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A benchmark-based method for evaluating hyperparameter optimization techniques of neural networks for surface water quality prediction

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 13-27页

作者： xuan Wang Yan Dong jing Yang Zhipeng Liu Jinsuo Lu School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an710055China Shaanxi Key Laboratory of Environmental Engineering Xi’an University of Architecture and TechnologyXi’an710055China State Key Laboratory of Green Building in West China Xi’an University of Architecture and TechnologyXi’an710055China

Neural networks(NNs)have been used extensively in surface water prediction tasks due to computing algorithm improvements and data *** essential step in developing an NN is the hyperparameter *** practice,it is common to manually determine hyperparameters in the studies of NNs in water resources *** may result in considerable randomness and require significant computation time;therefore,hyperparameter optimization(HPO)is *** study adopted five representatives of the HPO techniques in the surface water quality prediction tasks,including the grid sampling(GS),random search(RS),genetic algorithm(GA),Bayesian optimization(BO)based on the Gaussian process(GP),and the tree Parzen estimator(TPE).For the evaluation of these techniques,this study proposed a method:first,the optimal hyperparameter value sets achieved by GS were regarded as the benchmark;then,the other HPO techniques were evaluated and compared with the benchmark in convergence,optimization orientation,and consistency of the optimized *** results indicated that the TPE-based BO algorithm was recommended because it yielded stable convergence,reasonable optimization orientation,and the highest consistency rates with the benchmark *** optimization consistency rates via TPE for the hyperparameters hidden layers,hidden dimension,learning rate,and batch size were 86.7%,73.3%,73.3%,and 80.0%,*** the evaluation of HPO techniques directly based on the prediction performance of the optimized NN in a single HPO test,the proposed benchmark-based HPO evaluation approach is feasible and robust.

关键词： Neural networks Hyperparameter optimization Surface water quality prediction Bayes optimization Genetic algorithm

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Accurate atomic scanning transmission electron microscopy analysis enabled by deep learning

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Nano Research 2024年第4期17卷 2971-2980页

作者： Tianshu Chu Lei zhou Bowei Zhang Fu-Zhen xuan Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and TechnologyShanghai 200237China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Pressure Systems and Safety of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Currently,the machine learning(ML)-based scanning transmission electron microscopy(STEM)analysis is limited in the simulative stage,its application in experimental STEM is needed but ***,we built up a universal model to analyze the vacancy defects and single atoms accurately and rapidly in experimental STEM images using a full convolution *** our model,the unavoidable interference factors of noise,aberration,and carbon contamination were fully considered during the training,which were difficult to be considered in the *** toward the simultaneous identification of various vacancy types and low-contrast single atoms in the low-quality STEM images,our model showed rapid process speed(45 images per second)and high accuracy(>95%).This work represents an improvement in experimental STEM image analysis by ML.

关键词： deep learning low-dimensional materials atomic defects single atoms

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Data-driven rational design of single-atom materials for hydrogen evolution and sensing

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Nano Research 2024年第4期17卷 3352-3358页

作者： Lei zhou Pengfei Tian Bowei Zhang Fu-Zhen xuan Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and TechnologyShanghai 200237China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Pressure Systems and Safety of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Herein we proposed a data-driven high-throughput principle to screen high-performance single-atom materials for hydrogen evolution reaction(HER)and hydrogen sensing by combing the theoretical computations and a topology-based multi-scale convolution kernel machine learning *** the rational training by 25 groups of data and prediction of all 168 groups of single-atom materials for HER and sensing,respectively,a high prediction accuracy(>0.931 R^(2) score)was achieved by our *** show that the promising HER catalysts include Pt atoms in C_(4) and Sc atoms in C_(1)N_(3) coordination ***,Y atoms in C_(4) coordination environment and Cd atoms in C_(2)N_(2)-ortho coordination environment were predicted with great potential as hydrogen sensing *** method provides a way to accelerate the discovery of innovative materials by avoiding the time-consuming empirical principles in experiments.

关键词： machine learning single-atom materials sensing hydrogen evolution

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Perturbation of autophagy pathways in murine alveolar macrophage by 2D TMDCs is chalcogen-dependent

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Journal of Environmental Sciences 2024年第1期135卷 97-107页

作者： Xiaofei zhou Weitao Jin Rui Zhang xuan Mao Jianbo Jia Hongyu zhou College of Science&Technology Hebei Agricultural UniversityHuanghua 061100China Institute of Environmental Research at Greater Bay Area Key Laboratory for Water Quality and Conservation of the Pearl River DeltaMinistry of EducationGuangzhou UniversityGuangzhou 510006China

Increasing risks of incidental and occupational exposures to two-dimensional transition metal dichalcogenides(2D TMDCs)due to their broad application in various areas raised their public health *** the composition-dependent cytotoxicity of 2D TMDCs has been well-recognized,how the outer chalcogenide atoms and inner transition metal atoms differentially contribute to their perturbation on cell homeostasis at non-lethal doses remains to be *** the present work,we compared the autophagy induction and related mechanisms in response to WS_(2),NbS_(2),WSe_(2)and Nb Se_(2)nanosheets exposures in MH-S murine alveolar *** these 2D TMDCs had comparable physicochemical properties,overall cytotoxicity and capability in triggering autophagy in MH-S cells,but showed outer chalcogen-dependent subcellular localization and activation of autophagy ***,WS_(2)and NbS_(2)nanosheets adhered on the cell surface and internalized in the lysosomes,and triggered m TOR-dependent activation of ***,WSe_(2)and Nb Se_(2)nanosheets had extensive distribution in cytoplasm of MH-S cells and induced autophagy in an m TOR-independent ***,the 2D TMDCs-induced perturbation on autophagy aggravated the cytotoxicity of respirable benzo[a]*** findings provide a deeper insight into the potential health risk of environmental 2D TMDCs from the perspective of homeostasis perturbation.

关键词： Chalcogen group Autophagy pathway Cell function Endosomal escape Inhalation toxicity

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The Strategic Analysis of Demand Forecast-Sharing in a Hybrid-Format Online Platform Supply Chain

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 281-310页

作者： jing Zhao Zijun Yin Guobiao zhou School of Mathematical Sciences Tiangong UniversityTianjin300387China

This paper examines the optimal forecast-sharing strategy in a hybrid-format online platform supply chain where a supplier sells a product through agency format and reselling format provided by a platform retailer who possesses demand forecasts from two *** asymmetry and co-opetitive relationship arise between the platform retailer and the supplier,which affect their operational decisions and the supply chain’s *** improve supply chain efficiency,we compare different forecast-sharing strategies(i.e.,no forecast sharing,sharing a single forecast,and sharing two forecasts),and analyze the effects of co-opetitive parameters on the optimal forecast-sharing *** analysis shows that forecast sharing is always beneficial to the supplier,and sharing two forecasts is more beneficial than sharing a single *** for the platform retailer and the whole supply chain,forecast sharing is beneficial only under certain conditions,depending on the co-opetitive *** optimal forecast-sharing strategy is the result of a combination of the negative effect of double marginalization in reselling channel and the positive effect of responding pricing to demand uncertainty in agency *** illustrate the parameter regions of the platform retailer’s voluntary sharing,contract sharing,and no sharing,and also find that higher channel competition intensity,higher market share of agency channel,and higher commission rate can promote the platform retailer’s voluntary *** study extends the research scope of demand forecast-sharing and sheds light on the decision-making processes for managing a hybrid-format online platform supply chain.

关键词： Supply chain management hybrid-format online platform demand forecast-sharing co-opetitive relationship channel competition intensity

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Cybersecurity Landscape on Remote State Estimation:A Comprehensive Review

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 851-865页

作者： jing zhou Jun Shang Tongwen Chen the Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 1H9Canada the Department of Control Science and Engineering and Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China

Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)is an indispensable functional module of ***,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance *** paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against ***,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of ***,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from ***,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'***,several challenges and open problems are presented to inspire further exploration and future research in this field.

关键词： Cyber-attacks Kalman filtering remote state estimation unreliable transmission channels

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Synergistically constructed lamination-like network of redox-active polyimide and MXene via π-π interactions for aqueous NH_(4)^(+) storage

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Chinese Journal of Chemical Engineering 2024年第7期71卷 217-224页

作者： jing He Hongye xuan jing Jin Ke Yu Changyao Liyang Lintong Hu Minjie Shi Chao Yan School of Materials Science and Engineering Jiangsu University of Science and TechnologyZhenjiang 212003China Jiangsu New Yangzi Shipbuilding Co. LtdJingjiang 214532China

As a nonmetallic charge carrier,ammonium ion(NH_(4)^(+))has garnered significant attention in the construction of aqueous batteries due to its advantages of low molar mass,small hydration size and rapid diffusion in aqueous *** are a kind of potential electro-active materials for aqueous NH_(4)^(+)***,traditional polymer electrodes are typically created by covering the bulky collectors with excessive additives,which could lead to low volume capacity and unsatisfactory ***,a nanoparticle-like polyimide(PI)was synthesized and then combined with MXene nanosheets to synergistically construct an additive-free and self-standing PI@MXene composite ***,the redox-active PI nanoparticles are enclosed between conductive MXene flakes to create a 3D lamination-like network that promotes electron transmission,while theπ-πinteractions existing between PI and MXene contribute to the enhanced structural integrity and stability within the composite *** such,it delivers superior aqueous NH_(4)^(+)storage behaviors in terms of a notable specific capacity of 110.7 mA·h·cm^(–3) and a long lifespan with only 0.0064%drop each ***,in-situ Raman and UV–Vis examinations provide evidence of reversible and stable redox mechanism of the PI@MXene composite electrode during NH_(4)^(+)uptake/removal,highlighting its significance in the area of electrochemical energy storage.

关键词： Synergetic coupling Composite materials Polyimide Energy storage Aqueous ammonium ion batteries

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