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A Privacy-preserving Energy Management System Based on Homomorphic Cryptosystem for IoT-enabled Active Distribution Network

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 167-178页

作者： Qian Hu Siqi bu Wencong Su Vladimir Terzija the Department of Physics Hong Kong Baptist UniversityHong KongChina the Department of Electrical and Electronic Engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHong KongChina the Department of Electrical and Computer Engineering University of Michigan-DearbornDearbornMI 48128USA the School of Engineering Newcastle UniversityNewcastleUK

Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity threats.In this paper,the eavesdropping attacks that lead to privacy breaches are addressed for the IoT-enabled ADN.A privacy-preserving energy management system(EMS)is proposed and empowered by secure data exchange protocols based on the homomorphic cryptosystem.During the information transmission among distributed generators and load customers in the EMS,private information including power usage and electricity bidding price can be effectively protected against eavesdropping attacks.The correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically guaranteed.The simulation results demonstrate the effectiveness and the computational efficiency of the proposed homomorphically encrypted EMS.

关键词： Eavesdropping attack energy management system homomorphic cryptosystem Internet of Things(IOTs) active distribution network(ADN) privacy-preserving

NCAD v1.0: a database for non-coding variant annotation and interpretation

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Journal of Genetics and Genomics 2024年第2期51卷 230-242页

作者： Xiaoshu Feng Sihan Liu Ke Li Fengxiao bu Huijun Yuan Institute of Rare Diseases West China HospitalSichuan UniversityChengduSichuan 610044China

The application of whole genome sequencing is expanding in clinical diagnostics across various genetic disorders, and the significance of non-coding variants in penetrant diseases is increasingly being demonstrated. Therefore, it is urgent to improve the diagnostic yield by exploring the pathogenic mechanisms of variants in non-coding regions. However, the interpretation of non-coding variants remains a significant challenge, due to the complex functional regulatory mechanisms of non-coding regions and the current limitations of available databases and tools. Hence, we develop the non-coding variant annotation database (NCAD, http://***/), encompassing comprehensive insights into 665,679,194 variants, regulatory elements, and element interaction details. Integrating data from 96 sources, spanning both GRCh37 and GRCh38 versions, NCAD v1.0 provides vital information to support the genetic diagnosis of non-coding variants, including allele frequencies of 12 diverse populations, with a particular focus on the population frequency information for 230,235,698 variants in 20,964 Chinese individuals. Moreover, it offers prediction scores for variant functionality, five categories of regulatory elements, and four types of non-coding RNAs. With its rich data and comprehensive coverage, NCAD serves as a valuable platform, empowering researchers and clinicians with profound insights into non-coding regulatory mechanisms while facilitating the interpretation of non-coding variants.

关键词： Non-coding variants Annotation Variant interpretation Database

Photocatalytic reduction of CO_(2) with H_(2)O into C_(2)H_(6) mediated by dual metalation strategy

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Science China Chemistry 2024年第5期67卷 1381-1383页

作者： Mei Wang Tong-bu Lu School of Materials Science and Engineering Institute for New Energy Materials&Low Carbon TechnologiesTianjin University of TechnologyTianjin 300384China

Artificial solar-energy-driven CO_(2) reduction into value-added fuels under mild conditions provides a promising strategy to mitigate energy crisis and alleviate environmental issues around the world. Among diverse products of CO_(2) reduction reaction, C_(2+) compounds are more desirable in terms of their high energy density and commercial value [1].Thus far, various photocatalysts have been constructed for CO_(2) reduction.

关键词： reduction desirable value

Detection of Nonlinear Behavior Induced by Hard Limiting in Voltage Source Converters in Wind Farms Based on Higher-order Spectral Analysis

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 630-645页

作者： Zetian Zheng Shaowei Huang Qiangsheng bu Chen Shen Jun Yan State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China State Grid Jiangsu Electric Power Co. Ltd.Research InstituteNanjingChina

In recent years, sub-synchronous oscillation accidents caused by wind power integration have received extensive attention. The recorded constant-amplitude waveforms can be induced by either linear or nonlinear oscillation mechanisms. Hence, the nonlinear behavior needs to be distinguished prior to choosing the analysis method. Since the 1960s, the higher-order statistics(HOS) theory has become a powerful tool for the detection of nonlinear behavior(DNB) in production quality control wherein it has mainly been applied to mechanical condition monitoring and fault diagnosis. This study focuses on the hard limiters of the voltage source converter(VSC) control systems in the wind farms and attempts to detect the nonlinear behavior caused by bi-or uni-lateral saturation hard limiting using the HOS analysis. First, the conventional describing function is extended to obtain the detailed frequency domain information on the bi-and uni-lateral saturation hard limiting. Furthermore, the bi-and tri-spectra are introduced as the HOS, which are extended into bi-and tri-coherence spectra to eliminate the effects of the linear parts on the harmonic characteristics of hard limiting in the VSC control system, respectively. The effectiveness of the HOS in the DNB and the classification of the hard-limiting types is proven, and its detailed derivation and estimation procedure is presented. Finally, the quadratic and cubic phase coupling in the signals is illustrated, and the performance of the proposed method is evaluated and discussed.

关键词： Bi-coherence spectrum detection of nonlinear behavior hard limiting higher-order statistics tri-coherence spectrum voltage source converter wind farms.

Effects of acid mine drainage on photochemical and biological degradation of dissolved organic matter in karst river water

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Journal of Environmental Sciences 2024年第1期135卷 26-38页

作者： Linwei Li Xingxing Cao Chujie bu Pan Wu Biao Tian Yongheng Dai Yeye Ren College of Resources and Environmental Engineering Guizhou UniversityGuiyang 550025China Key Laboratory of Karst Georesources and Environment Ministry of EducationGuizhou UniversityGuiyang 550025China Guizhou Karst Environmental Ecosystems Observation and Research Station Ministry of EducationGuizhou UniversityGuiyang 550025China

Dissolved organic matter(DOM)can be removed or transformed by photochemical and biological processes,producing the negative effect of transforming organic carbon into inorganic carbon,which plays a vital role in the karst carbon cycle.However,acid mine drainage(AMD)will affect this process,so the degradation of DOM in karst river water(KRW)needs to be studied in this context.In this study,to reveal the evolution processes of DOM under photochemical and biological conditions in AMD-impacted KRW,AMD and KRW were mixed in different ratios under conditions of visible light irradiation(VL),biodegradation(BD),ultraviolet irradiation(UV)and ultraviolet irradiation+biodegradation(UV+BD).The average DOC concentrations in samples after mixing AMD and KRW in different proportions decreased significantly(by 23%)in UV+BD,which was 1.2–1.4 times higher than under the other conditions and would lead to a significant release of inorganic carbon.Further analysis of the fluorescence parameters via parallel factor analysis(PARAFAC)revealed that the DOM fluorescence components in AMD comprised mainly protein-like substances derived from autochthonous components,while the DOM fluorescence components in KRW were mainly humic-like substances with both autochthonous and allochthonous sources.Therefore,AMD could promote both the photochemical and biological degradation of DOM in karst receiving streams,resulting in the conversion of DOC to inorganic carbon.The results showed that the synergistic effects of UV+BD and AMD accelerated the degradation of DOM and the release of inorganic carbon in KRW,thus affecting the stability of the karst carbon cycle.

关键词： Acid mine drainage Dissolved organic matter Karst river water Photochemical degradation Biological degradation

Efficient reduction and adsorption of Cr(Ⅵ)using FeCl_(3)-modified biochar:Synergistic roles of persistent free radicals and Fe(Ⅱ)

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Journal of Environmental Sciences 2024年第3期137卷 626-638页

作者： Shujie Hu Chengshuai Liu Hongling bu Manjia Chen Ying-heng Fei National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and ManagementInstitute of Eco-environmental and Soil SciencesGuangdong Academy of SciencesGuangzhou 510650China State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of ScienceGuiyang 550081China School of Environment Science and Engineering Guangzhou UniversityGuangzhou 510006China College of Resources and Environment Chongqing SchoolUniversity of Chinese Academy of SciencesChongqing 400714China School of Environmental Science and Engineering Guangdong University of TechnologyGuangzhou 510006China

Transition metal iron and persistent free radicals(PFRs)both affect the redox properties of biochar,but the electron transfer relationship between them and the coupling reduction mechanism of Cr(Ⅵ)requires further investigation.To untangle the interplay between iron and PFRs in biochar and the infuences on redox properties,FeCl_(3)-modified rice husk biochar(FBCs)was prepared and its reduction mechanism for Cr(Ⅵ)without light was evaluated.The FBCs had higher surface positive charges,oxygen-containing functional groups,and PFRs compared with pristine rice husk biochar(BC).Phenoxyl PFRs with high electrondonating capability formed in biochar.The pronounced electron paramagnetic resonance signals showed that the PFRs preferred to form at lower Fe(Ⅲ)concentrations.While a high concentration of Fe(Ⅲ)would be reduced to Fe(Ⅱ)and consumed the formed PFRs.Adsorption kinetics and X-ray photoelectron spectroscopy analysis indicated that the FBCs effectively enhanced the Cr(Ⅵ)removal efficiency by 1.54-8.20 fold and the Cr(Ⅵ)reduction efficiency by 1.88-9.29 fold compared to those of BC.PFRs quenching and competitive reductant addition experiments revealed that the higher Cr(Ⅵ)reduction performance of FBCs was mainly attributed to the formed PFRs,which could contribute to~74.0%of Cr(Ⅵ)reduction by direct or indirect electron transfer.The PFRs on FBCs surfaces could promote the Fe(Ⅲ)/Fe(Ⅱ)cycle through single electron transfer and synergistically accelerate~52.3%of Cr(Ⅵ)reduction.This study provides an improved understanding of the reduction mechanism of iron-modified biochar PFRs on Cr(Ⅵ)in environments.

关键词： Biochar Iron-modification Cr(Ⅵ) Electron transfer Reduction mechanism

An End-To-End Hyperbolic Deep Graph Convolutional Neural Network Framework

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 537-563页

作者： Yuchen Zhou Hongtao Huo Zhiwen Hou Lingbin bu Yifan Wang Jingyi Mao Xiaojun Lv Fanliang bu School of Information Network Security People’s Public Security University of ChinaBeijing100038China Institute of Computing Technology China Academy of Railway Sciences Corporation LimitedBeijing100081China

Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial distortions.Moreover,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical structures.To more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic space.In HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic space.Additionally,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing framework.In addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention coefficients.Through the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical graphs.Experimental results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding representations.Furthermore,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhancements.

关键词： Graph neural networks hyperbolic graph convolutional neural networks deep graph convolutional neural networks message passing framework

Epicatechin attenuates lead(Pb)-induced cognitive impairment in mice:regulation on Nrf2 signaling pathway,and interference on the interaction between Pb with albumin

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Food Science and Human Wellness 2024年第2期13卷 1065-1078页

作者： Dai Cheng Qianqian Yu Kexin Zhu Dingdong bu Zijian Wu State Key Laboratory of Food Nutrition and Safety Tianjin University of Science&TechnologyTianjin 300457China School of Biotechnology and Food Science Tianjin University of CommerceTianjin 300134China

Epicatechin(EC)was used in this study to antagonize the cognitive dysfunction caused by lead(Pb)exposure in mice.Eight-week-old male Kunming mice were treated with PbCl_(2)(20 mg/kg)and/or EC(50 mg/kg)by gavage administration for 4 weeks.Morris water maze test showed that EC could improve memory dysfunction induced by Pb.EC antagonized Ca^(2+)overload,activated Nrf2 signaling pathway and reduced the accumulation of Pb in the brain and serum,which suggested that EC might alter Pb distribution in mice.In vitro,spectroscopic analysis,potentiometric titration and docking studies were applied to inquiry into the interaction between bovine serum albumin(BSA)and Pb^(2+)in presence or absence of EC.EC was proved to chelate Pb^(2+)and reduced the interaction between BSA and Pb^(2+).In summary,EC might protect Pb-induced cognitive impairment by activating Nrf2 signaling pathway,and suppressing Pb accumulation via interference on the binding of Pb to albumin.

关键词： Lead Epicatechin Bovine serum albumin Interaction Oxidative stress

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 32-42页

作者： Xiao Liu Pingting Lin Fan bu Shaoling Zhuang Shoudao Huang CES&IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China CES

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

关键词： Generator optimization Gaussian Process Regression(GPR) Conditional Likelihood Lower Bound Search(CLLBS) Constraint improvement expectation(CEI) Finite element calculation