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High Voltage 2024年第1期9卷 56-65页

作者： Hao Hu Zhidong Jia Xilin Wang Ruiyang Guan Weinan Fan simin luo Tsinghua shenzhen International Graduate school Tsinghua UniversityShenzhenChina Guangzhou Power supply China Southern Power Grid Company Ltd.GuangzhouChina

silicone rubber(sR)is widely used for cable insulation and operates in multi-stress coupling *** dielectric properties and ageing performance are the essential factors affecting cable *** this study,the frequency domain spectroscopy of unaged sR and sR aged under various conditions is *** dielectric responses before and after ageing are analysed in depth by the conjoint analysis via multiple complex planes(permittivity,conductivity,and modulus).Typical conductivity and interfacial polarisation properties,as well as property changes resulting from thermal and tensile ageing,are *** results show that tensile ageing promotes conductance and interfacial polarisation,while thermal ageing shows the opposite *** on the multi-core model and charge carrier hopping transport model,thermal and tensile ageing mechanisms on the conductance and interfacial polarisation behaviours of sR are *** behaviours exhibit positively correlated changing characteristics,suggesting that the two behaviours may originate from a common *** carrier transport process,promoted by the tensile effect and slightly suppressed by the thermal effect,is the primary factor and considered an important indicator to evaluate the dielectric properties of sR insulation.

关键词： interfacial rubber insulation

Predicting microbial extracellular electron transfer activity in paddy soils with soil physicochemical properties using machine learning

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science China(Technological sciences) 2024年第1期67卷 259-270页

作者： OU JiaJun luo Xiaoshan LIU JunYang HUAnG LinYan ZHOU LiHua YUAn Yong school of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control Guangzhou Key Laboratory Environmental Catalysis and Pollution ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China school of Biomedical and Pharmaceutical sciences Guangdong University of TechnologyGuangzhou 510006China

soil extracellular electron transfer(EET)is a pivotal biological process within the realm of ***,EET suffers from a lack of predictive ***,an intricately crafted machine learning model has been developed for the purpose of predicting soil EET by using the physicochemical properties of soil as independent input variables and the EET capabilities in terms of current density(j_(max))and Coulombic charge(C_(out))as dependent output *** autoencoder ensemble stacking(AEs)model was developed to address the aforementioned issue by integrating support vector machine,multilayer perceptron,extreme gradient boosting,and light gradient boosting machine algorithms as the stacking *** 10-fold crossvalidation,the AEs model exhibited notable improvements in predicting j_(max)and C_(out),with average test R^(2)values of 0.83 and 0.84,respectively,surpassing those of single machine learning(ML)models and the basic ensemble *** utilizing partial correlation plots(PDPs),shapley Additive explanations(sHAP)values,and sHAP decision plots,we quantitatively explained the impact and contribution of the input molecules on the AEs model’s predictions of j_(max)and C_(out).In the context of the sHAP method for the AEs model,total carbon(TC)was identified as the most correlated descriptor for j_(max),while total organic carbon(TOC)stood out as the most relevant descriptor for C_(out).In the prediction tasks of j_(max)and C_(out)within the AEs model,employing a multitask ML approach allowed the model to benefit from the shared information of input variables,thereby enhancing its overall *** study provides a feasible tool for the prediction of soil EET from soil physiochemical properties and an advanced understanding of the relationship between soil physiochemical properties and EET capability.

关键词： extracellular electron transfer paddy soil machine learning prediction autoencoder ensemble stacking model

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Co-electrolysis of ethylene glycol and carbon dioxide for formate synthesis

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science China Chemistry 2024年第5期67卷 1539-1544页

作者： Dongfeng Du Fusong Kang shiru Yang Bin shao Jingshan luo Institute of Photoelectronic Thin Film Devices and Technology State Key Laboratory of Photovoltaic Materials and CellsKey Laboratory of Photoelectronic Thin Film Devices and Technology of TianjinMinistry of Education Engineering Research Center of Thin Film Photoelectronic TechnologyNankai UniversityTianjin 300350China Haihe Laboratory of sustainable Chemical Transformations Tianjin 300192China Frontiers science Center for new Organic Matter Nankai UniversityTianjin 300071China College of Electronic Information and Optical Engineering Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network TechnologyNankai UniversityTianjin 300350China

Co-electrolysis of waste plastics and carbon dioxide(CO_(2)) into value-added chemicals or fuels is a promising pathway for a sustainable society, but efficient and selective conversion remains a challenge. Herein, a gold-mediated nickel hydroxide(Au/ni(OH)_(2)) is developed to oxidize waste plastic-derived ethylene glycol(EG) into formate. In-situ electrochemical experiments and theoretical results reveal that the introduction of Au favors the redox properties and EG adsorption behavior of ni(OH)_(2). The Au/ni(OH)_(2) catalyst shows an excellent formate selectivity of >90% at high current densities of above 100 m A cm^(-2). When coupled with sputtered bismuth(Bi) cathode for CO_(2) reduction, a high formate Faradic efficiency(FE) of 188.2% at 200 m A cm^(-2)and a good formate productivity of 7.33 mmol m^(-2)s^(-1)at 10 A are obtained in a flow cell and a zero-gap membrane electrode assembly(MEA) cell, respectively. This work demonstrates a promising strategy to convert waste plastics and CO_(2) into valuable products.

关键词： waste plastic upcycling ethylene glycol oxidation carbon dioxide reduction electrocatalysis formate synthesis

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High Impedance Fault Detection Based on Attention Mechanism and Object Identification

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CsEE Journal of Power and Energy systems 2024年第1期10卷 197-207页

作者： Yongjie Zhang Xiaojun Wang Yiping luo Dahai Zhang sohrab Mirsaeidi Jinghan He school of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China

Detection of high impedance faults(HIFs)has been traditionally a main challenge in the protection of distribution systems,since they do not generate enough current to be reliably detected by conventional over-current ***-based methods are alternative HIF detection methods which avoid threshold settings by training a classification or regression ***,most of them lack interpretability and are not compatible with various distribution *** paper proposes an object detection-based HIF detection method,which has higher visualization and can be easily applied to different ***,based on the analysis of HIFs,a Butterworth band-pass filter is designed for HIF harmonic feature ***,based on the synchronized data provided by distribution-level phasor measurement units,global HIF feature gray-scale images are formed through combining the topology information of the distribution *** further enhance the feature information,a locally excitatory globally inhibitory oscillator region attention mechanism(LEGIO-RAM)is proposed to highlight the critical feature regions and inhibit useless and fake ***,an object detection network based You Only Look Once(YOLO)v2 is established to achieve fast HIF detection and section *** obtained results from the simulation of the proposed approach on three different distribution networks and one realistic distribution network verify that the proposed method is highly effective in terms of reliability and generalization.

关键词： Attention mechanism distribution-level phasor measurement units high impedance faults object detection

KsKV:Key-strategy for Key-Value Data Collection with Local Differential Privacy

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Computer Modeling in Engineering & sciences 2024年第6期139卷 3063-3083页

作者： Dan Zhao Yang You Chuanwen luo Ting Chen Yang Liu Artificial Intelligence Development Research Center Institute of Scientific and Technical Information of ChinaBeijing100038China Industry Development Department NSFOCUS Inc.BeijingChina school of Information science and Technology Beijing Forestry UniversityBeijing100083China school of Computer science and Engineering University of Electronic Science and Technology of ChinaChengdu610054China Institute of Computing Technology China Academy of Railway Sciences Corporation LimitedBeijing10081China

In recent years,the research field of data collection under local differential privacy(LDP)has expanded its focus fromelementary data types to includemore complex structural data,such as set-value and graph ***,our comprehensive review of existing literature reveals that there needs to be more studies that engage with key-value data *** studies would simultaneously collect the frequencies of keys and the mean of values associated with each ***,the allocation of the privacy budget between the frequencies of keys and the means of values for each key does not yield an optimal utility *** the importance of obtaining accurate key frequencies and mean estimations for key-value data collection,this paper presents a novel framework:the Key-strategy Framework forKey-ValueDataCollection under ***,theKey-strategyUnary Encoding(Ks-UE)strategy is proposed within non-interactive frameworks for the purpose of privacy budget allocation to achieve precise key frequencies;subsequently,the Key-strategy Generalized Randomized Response(Ks-GRR)strategy is introduced for interactive frameworks to enhance the efficiency of collecting frequent keys through group-anditeration *** strategies are adapted for scenarios in which users possess either a single or multiple key-value ***,we demonstrate that the variance of Ks-UE is lower than that of existing *** claims are substantiated through extensive experimental evaluation on real-world datasets,confirming the effectiveness and efficiency of the Ks-UE and Ks-GRR strategies.

关键词： Key-value local differential privacy frequency estimation mean estimation data perturbation

Temperature-dependent self-trapped exciton emission in Cu(I) doped zinc-based metal halides from well-resolved excited state structures

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nano Research 2024年第8期17卷 7768-7775页

作者： Yunlong Bai shuai Zhang nengneng luo Bingsuo Zou Ruosheng Zeng state Key Laboratory of Featured Metal Materials and Life-cycle safety for Composite structures School of Physical Science and TechnologyGuangxi UniversityNanning 530004China

Zero-dimensional metal halides are of unique structures and tunable photoluminescence properties,showing great potential applications such as light-emitting diodes(LEDs)and ***,we successfully synthesized Cu^(+)doped(MA)_(2)ZnCl_(4)metal halides by a slow evaporation solvent *** introduction of Cu^(+)results in sky-blue self-trapped exciton emission in(MA)_(2)ZnCl_(4) at 486 nm at room temperature,and a photoluminescence quantum yield is as high as 54.9%.Interestingly,at low temperatures,Cu^(+)-doped(MA)_(2)ZnCl_(4) exhibits two emission peaks located at 482 and 605 nm,*** temperaturedependent dual emission indicates two excited state structures that exist on the triplet excited-state potential energy *** addition,the temperature sensor we fitted has good performance(sr=1.65%·K^(−1)),which is the first attempt in Cu^(+) doped Znbased metal *** work enriches the family of sky-blue metal halides and provides a promising strategy for building skyblue LEDs.

关键词： sky-blue emission self-trapped exciton metal halides excited state structures temperature sensor

Revealing effect of Al content on oxidation of novel Co-Cr-nb-W carbide-strengthened superalloy

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Rare Metals 2024年第9期43卷 4521-4534页

作者： Chen Ling shang-Ping Li Jie Hou He-Li luo Central Iron & steel Research Institute Beijing GAOnA Materials&Technology Co. Ltd.

The high-temperature oxidation behavior of novel Co-Cr-nb-W carbide-strengthened wear-resistance alloys with different Al contents（1wt%, 2wt% and 3wt%）at 950, 1000 and 1050 °C was thoroughly investigated by scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and field emission electron probe analyzer. The porous property of nb C in-situ oxidation products（nb2O5, Co nb2O6and Co4nb2O9） induces a multi-layered oxide scale with micropores and ***-Cr-nb-W alloy with 1 wt% Al undergoes catastrophic oxidation and spalling above 1000 °C. The outward transportation of Cr and Co is effectively restrained by a continuous Al2O3scale formed around nb C in-situ oxidation region when Al content reaches 3 wt%. The β-Co Al in Co-Cr-nb-W alloy with 3 wt% Al has an oxidation priority over eutectic carbides and the alloy matrix which are both enriched with Cr, thereby preventing the formation of Cr-depletion area and improving the self-healing ability of the oxide film. A slight change in Al content has a remarkable influence on the cooperative effect of Al and Cr and multiplies the antioxidant capacity of Co-Cr-nb-W alloy above 1000 °C.

关键词： High-temperature oxidation behavior Microstructure Oxidation kinetics superalloy Wear-resistant alloy

Factors hindering the degradation of pharmaceuticals from human urine in an iron-activated persulfate system

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Journal of Environmental sciences 2024年第1期135卷 130-148页

作者： Yiruiwen Xie Dao Guan Yangfan Deng Yugo sato Yu luo Guanghao Chen Department of Civil and Environmental Engineering Water Technology LabHong Kong Branch of Chinese National Engineering Research Center for Control&Treatment of Heavy Metal PollutionThe Hong Kong University of Science&TechnologyHong Kong 999077China

This study investigated the degradation of clofibric acid(CFA),bezafibrate(BZF),and sulfamethoxazole(sMX)in synthetic human urine using a novel mesoporous iron powderactivated persulfate system(mFe-Ps system),and identified the factors limiting their degradation in synthetic human urine.A kinetic model was established to expose the radical production in various reaction conditions,and experiments were conducted to verify the modeling *** the phosphate-containing mFe-Ps system,the 120 min removal efficiency of CFA decreased from 95.1%to 76.6%as the phosphate concentration increased from 0.32 to 6.45 mmol/L,but recovered to 90.5%when phosphate concentration increased to 16.10 mmol/***,the increased concentration of phosphate from 0.32 to 16.10mmol/L reduced the BZF degradation efficacy from 91.5%to 79.0%,whereas sMX removal improved from 37.3%to 62.9%.The m Fe-Ps system containing(bi)carbonate,from 4.20 to166.70 mmol/L,reduced CFA and BZF removal efficiencies from 100%to 76.8%and 80.4%,respectively,and sMX from 83.5%to 56.7%within a 120-min reaction *** addition,alkaline conditions(pH≥8.0)inhibited CFA and BZF degradations,while nonacidic pH(pH≥7.0)remarkably inhibited sMX *** of the kinetic model indicated the formation of phosphate(H_(2)PO_(4)^(·)/HPO_(4)^(·-))and/or carbonate radicals(CO_(3)^(·-))could limit pharmaceutical *** transformation products(TPs)of the pharmaceuticals revealed more incompletely oxidized TPs occurred in the phosphate-and(bi)carbonate-containing m Fe-Ps systems,and indicated that H_(2)PO_(4)^(·)/HPO_(4)^(·-)mainly degraded pharmaceuticals via a benzene ring-opening reaction while CO_(3)^(·-)preferentially oxidized pharmaceuticals via a hydroxylation reaction.

关键词： Pharmaceutical degradation Human urine Iron-activated persulfate system Phosphate radicals Carbonate radicals Transformation products

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A Privacy Preservation Method for Attributed social network Based on negative Representation of Information

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Computer Modeling in Engineering & sciences 2024年第7期140卷 1045-1075页

作者： Hao Jiang Yuerong Liao Dongdong Zhao Wenjian luo Xingyi Zhang Key Laboratory of Intelligent Computing and signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230601China Chongqing Research Institute School of Computer Science and Artificial IntelligenceWuhan University of TechnologyWuhan430070China Guangdong Provincial Key Laboratory of novel security Intelligence Technologies School of Computer Science and TechnologyHarbin Institute of TechnologyShenzhen518055China

Due to the presence of a large amount of personal sensitive information in social networks,privacy preservation issues in social networks have attracted the attention of many *** by the self-nonself discrimination paradigmin the biological immune system,the negative representation of information indicates features such as simplicity and efficiency,which is very suitable for preserving social network ***,we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks,called ***,a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept ***,a negative database-based method is proposed to hide node attributes,so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes,which is crucial to the analysis of social *** evaluate the performance of the AttnetnRI,empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social *** experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding *** experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

关键词： Attributed social network topology privacy node attribute privacy negative representation of information negative survey negative database

Cross-Dimension Attentive Feature Fusion network for Unsupervised Time-series Anomaly Detection

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Computer Modeling in Engineering & sciences 2024年第6期139卷 3011-3027页

作者： Rui Wang Yao Zhou Guangchun luo Peng Chen Dezhong Peng school of Computer science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China school of Computer and software Engineering Xihua UniversityChengdu610039China school of Computer science Sichuan UniversityChengdu610065China national Innovation Center for UHD Video Technology Chengdu610095China

Time series anomaly detection is crucial in various industrial applications to identify unusual behaviors within the time series *** to the challenges associated with annotating anomaly events,time series reconstruction has become a prevalent approach for unsupervised anomaly ***,effectively learning representations and achieving accurate detection results remain challenging due to the intricate temporal patterns and dependencies in real-world time *** this paper,we propose a cross-dimension attentive feature fusion network for time series anomaly detection,referred to as ***,a series and feature mixing block is introduced to learn representations in 1D ***,a fast Fourier transform is employed to convert the time series into 2D space,providing the capability for 2D feature ***,a cross-dimension attentive feature fusion mechanism is designed that adaptively integrates features across different dimensions for anomaly *** results on real-world time series datasets demonstrate that CAFFn performs better than other competing methods in time series anomaly detection.

关键词： Time series anomaly detection unsupervised feature learning feature fusion