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Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 213-224页

作者： Xinwu Sun Jiaxiang hu Zhenyuan Zhang Di Cao qi huang Zhe Chen Weihao hu the School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengduChina Southwest University of Science and TechnologyChengduChina

With the development of advanced metering infrastructure(AMI),large amounts of electricity consumption data can be collected for electricity theft ***,the imbalance of electricity consumption data is violent,which makes the training of detection model *** this case,this paper proposes an electricity theft detection method based on ensemble learning and prototype learning,which has great performance on imbalanced dataset and abnormal data with different abnormal *** this paper,convolutional neural network(CNN)and long short-term memory(LSTM)are employed to obtain abstract feature from electricity consumption *** calculating the means of the abstract feature,the prototype per class is obtained,which is used to predict the labels of unknown *** the meanwhile,through training the network by different balanced subsets of training set,the prototype is *** with some mainstream methods including CNN,random forest(RF)and so on,the proposed method has been proved to effectively deal with the electricity theft detection when abnormal data only account for 2.5%and 1.25%of normal *** results show that the proposed method outperforms other state-of-the-art methods.

关键词： Electricity theft detection ensemble learning prototype learning imbalanced dataset deep learning abnormal level

Theoretical study of the nonlinear force-loading control in single-molecule stretching experiments

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Communications in Theoretical Physics 2024年第4期76卷 167-175页

作者： Xingyu qi Zilong Guo Shimin Le hu Chen Research Institute for Biomimetics and Soft Matter Fujian Provincial Key Lab for Soft Functional Materials ResearchDepartment of PhysicsXiamen UniversityXiamen 361005China Center of Biomedical Physics Wenzhou InstituteUniversity of Chinese Academy of SciencesWenzhou 325000China

Force spectrum measurements with constant loading rates are widely used in single-molecule manipulation experiments to study the mechanical stability and force response of ***-dependent transition rates can be obtained from the transition force distribution,but it is limited to the force range with non-zero force *** constant loading rate control can be realized with magnetic tweezers,the loading rate range is limited due to the slow movement of permanent ***-linear exponential and exponential squared force loading functions are more feasible in magnetic tweezers,while there is no theoretical result available for these two kinds of non-linear force loading *** this study,we solved the unfolding process of a protein following Bell's model under nonlinear exponential and exponential squared force loading functions,which offer a broader range of unfolding force distribution compared to the traditional constant loading rate ***,we derived two force loading functions,which can produce uniform unfolding force *** research contributes fundamental equations for the analysis of experimental data obtained through single-molecule manipulation under nonlinear force loading controls,paving the way for the use of nonlinear force control in magnetic tweezer experiments.

关键词： single-molecule manipulation magnetic tweezers force loading transition rates force distribution

Non-Targeted Metabolomics Reveals the Metabolic Alterations in Response to Artificial Selective Breeding in the Fast-Growing Strains of Pacific Oyster

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Journal of Ocean University of China 2024年第2期23卷 518-528页

作者： hu Boyang TIAN Yuan LIU Shikai LI qi Key Laboratory of Mariculture Ministry of EducationOcean University of ChinaQingdao 266003China Laboratory for Marine Fisheries Science and Food Production Processes Laoshan LaboratoryQingdao 266237China

Pacific oyster(Crassostrea gigas)is one of the most important mollusks cultured all around the *** breeding programs of Pacific oysters in China is initiated since 2006 and developed the genetically improved strain with fast-growing ***,little is known about the metabolic signatures of the fast-growing *** the present study,the non-targeted metabolomics was performed to analyze the metabolic signatures of adductor muscle tissue in one-year old Pacific oysters from fast-growing strain and the wild population.A total of 7767 and 10174 valid peaks were extracted and quantified in ESI^(+)and ESI^(−)modes,resulting in 399 and 381 annotated metabolites,*** and OPLS-DA revealed that considerable separation among samples from fastgrowing strain and wild population,suggesting the differences in metabolic ***,81 significantly different metabolites(SDMs)were identified in the comparisons between fast-growing strain and wild population,based on the strict *** was found that there were highly correlation and conserved coordination among these *** enrichment analysis indicated that the SDMs were tightly related to pantothenate and CoA biosynthesis,steroid hormone biosynthesis,riboflavin metabolism,and arginine and proline *** them,the CoA biosynthesis and metabolism,affected by pantetheine and pantothenic acid,might be important for the growth of Pacific oysters under artificial selective *** study provides the comprehensive views of metabolic signatures in response to artificially selective breeding,and is helpful to better understand the molecular mechanism of fastgrowing traits in Pacific oysters.

关键词： metabolic signature Pacific oyster artificial selection fast-growing trait

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu qi Zhang Yufan hu hui Zeng Bin Fan the School of Intelligence Science and Technology and the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

Recyclable Polypropylene-based Insulation Materials for HVDC Cables:Progress and Perspective

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 2208-2220页

作者： Yao Zhou Shixun hu Chao Yuan Jun hu qi Li Jinliang He State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Beijing Key Lab of High Voltage&EMC and State Key Lab of Alternate Electrical Power System with Renewable Energy SourcesNorth China Electric Power UniversityBeijing 102206China.

Polypropylene(PP)-based recyclable materials have attracted tremendous interest for HVDC cable insulation applications due to their superior electrical properties,e.g.,high thermal stability and superior *** with crosslinked polyethylene(XLPE),PP-based materials exhibit the advantages of not only higher working temperatures but also facile and efficient cable manufacturing with reduced costs,which are highly desirable in HVDC cable *** their promising advantages,PP-based materials have received significant attention from both academia and industry in the field of HVDC cable *** order to adopt PP as a cable insulation material,the mechanical flexibility of PP should be ***,regulations of the mechanical properties inevitably influences the electrical properties of *** extensive research has been conducted on the regulation of the mechanical and electrical properties of *** review summarizes the research progress on recyclable PP-based materials for HVDC cable insulation *** attention is placed on the electrical property regulations and material structure-property *** challenges that remain to be addressed and the opportunities for future studies on PP-based recyclable HVDC cable insulation materials are also presented.

关键词： polypropylene HVDC cable dielectric materials recyclable insulation materials

Chemico-biological conversion of carbon dioxide

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Journal of Energy Chemistry 2024年第2期89卷 371-387,I0009页

作者： Liangwei hu Junzhu Yang qi Xia Jin Zhang Hongxin Zhao Yuan Lu Zhejiang Province Key Laboratory of Plant Secondary Metabolism and Regulation College of Life Sciences and MedicineZhejiang Sci-Tech UniversityHangzhou 310018ZhejiangChina Key Laboratory of Industrial Biocatalysis Ministry of EducationTsinghua UniversityBeijing 100084China Department of Chemical Engineering Tsinghua UniversityBeijing 100084China College of Biological and Chemical Engineering Jiaxing UniversityJiaxing 314000ZhejiangChina

The unabated carbon dioxide(CO_(2))emission into the atmosphere has exacerbated global climate change,resulting in extreme weather events,biodiversity loss,and an intensified greenhouse *** address these challenges and work toward carbon(C)neutrality and reduced CO_(2)emissions,the capture and utilization of CO_(2)have become imperative in both scientific research and *** cutting-edge approach to achieving efficient catalytic performance involves integrating green bioconversion and chemical *** innovative strategy offers several advantages,including environmental friendliness,high efficiency,and *** study provides a comprehensive review of existing technical routes for carbon sequestration(CS)and introduces two novel CS pathways:the electrochemicalbiological hybrid and artificial photosynthesis *** also thoroughly examines the synthesis of valuable Cnproducts from the two CS systems employing different catalysts and *** both systems heavily rely on electron transfer,direct and mediated electron transfer has been discussed and summarized in ***,this study explores the conditions suitable for different catalysts and assesses the strengths and weaknesses of *** also explored the biocompatibility of the electrode materials and developed novel *** materials were specifically engineered to combine with enzymes or microbial cells to solve the biocompatibility problem,while improving the electron transfer efficiency of ***,this review summarizes the relevant systems developed in recent years for manufacturing different products,along with their respective production efficiencies,providing a solid database for development in this *** novel chemical-biological combination proposed herein holds great promise for the future conversion of CO_(2)into advanced organic ***,it offers exciting prospects for utilizing CO_(2)in synthesizing

关键词： Carbon dioxide Bioelectric synthesis Artificial photosynthesis Synthetic product

Mechanical behaviors of warm and ice-rich frozen soil stabilized with sulphoaluminate cement

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Journal of Mountain Science 2024年第1期21卷 335-345页

作者： WANG Honglei ZHANG hu ZHANG Jianming ZHANG qi YIN Zhenhua State Key Laboratory of Frozen Soil Engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China School of Civil Engineering and Transportation Northeast Forestry UniversityHarbin 150040China National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment CCCC First Highway Consultants Co.LtdXi'an 710065China Railway Engineering Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China

The warm and ice-rich frozen soil is characterized by high unfrozen water content, low shear strength and large compressibility, which is unreliable to meet the stability requirements of engineering infrastructures and foundations in permafrost regions. In this study, a novel approach for stabilizing the warm and ice-rich frozen soil with sulphoaluminate cement was proposed based on chemical stabilization. The mechanical behaviors of the stabilized soil, such as strength and stress-strain relationship, were investigated through a series of triaxial compression tests conducted at -1.0℃, and the mechanism of strength variations of the stabilized soil was also explained based on scanning electron microscope test. The investigations indicated that the strength of stabilized soil to resist failure has been improved, and the linear Mohr-Coulomb criteria can accurately reflect the shear strength of stabilized soil under various applied confining pressure. The increase in both curing age and cement mixing ratio were favorable to the growth of cohesion and internal friction angle. More importantly, the strength improvement mechanism of the stabilized soil is attributed to the formation of structural skeleton and the generation of cementitious hydration products within itself. Therefore, the investigations conducted in this study provide valuable references for chemical stabilization of warm and ice-rich frozen ground, thereby providing a basis for in-situ ground improvement for reinforcing warm and ice-rich permafrost foundations by soil-cement column installation.

关键词： Permafrost regions Frozen soil Mechanical behavior Chemical stabilization Ground improvement Ground modification

Pathophysiological changes of muscle after ischemic stroke:a secondary consequence of stroke injury

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Neural Regeneration Research 2024年第4期19卷 737-746页

作者： hu qi Dan Tian Fei Luan Ruocong Yang Nan Zeng State Key Laboratory of Southwestern Chinese Medicine Resources Chengdu University of Traditional Chinese Medicine School of Pharmacy Chengdu University of Traditional Chinese Medicine Acupuncture and Tuina School Chengdu University of Traditional Chinese Medicine

Sufficient clinical evidence suggests that the damage caused by ischemic stroke to the body occurs not only in the acute phase but also during the recovery period,and that the latter has a greater impact on the long-term prognosis of the ***,current stroke studies have typically focused only on lesions in the central nervous system,ignoring secondary damage caused by this *** a phenomenon arises from the slow progress of pathophysiological studies examining the central nervous ***,the appropriate therapeutic time window and benefits of thrombolytic therapy are still controversial,leading scholars to explore more pragmatic intervention *** treatment measures targeting limb symptoms can greatly improve a patient’s quality of life,they have become a critical intervention *** the most vital component of the limbs,skeletal muscles have become potential points of *** this,to the best of our knowledge,there are no comprehensive reviews of pathophysiological changes and potential treatments for post-stroke skeletal *** current review seeks to fill a gap in the current understanding of the pathological processes and mechanisms of muscle wasting atrophy,inflammation,neuroregeneration,mitochondrial changes,and nutritional dysregulation in stroke *** addition,the challenges,as well as the optional solutions for individualized rehabilitation programs for stroke patients based on motor function are discussed.

关键词： inflammation ischemic stroke mitochondria muscle atrophy muscle fiber muscle nutrition quality of life rehabilitation ubiquitin

Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data

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Journal of Energy Chemistry 2024年第5期92卷 605-618页

作者： qingguang qi Wenxue Liu Zhongwei Deng Jinwen Li Ziyou Song Xiaosong hu College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina Department of Mechanical Engineering National University of SingaporeSingapore 117575Singapore

Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion *** numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery *** challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity *** fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field *** proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction ***,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation ***,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV ***,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 *** results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing *** work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.

关键词： Electricvehicle Lithium-ion battery pack Capacity estimation Machine learning Field data