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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 *** 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 *** 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 *** correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically *** 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

DDI-Transform:A neural network for predicting drug-drug interaction events

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Quantitative Biology 2024年第2期12卷 155-163页

作者： Jiaming su Ying qian School of Computer Science and Technology Shanghai Frontiers Science Center of Molecule Intelligent SynthesesEast China Normal UniversityShanghaiChina

Drug-drug interaction(DDI)event prediction is a challenging problem,and accurate prediction of DDI events is critical to patient health and new drug ***,many machine learning-based techniques have been proposed for predicting DDI ***,most of the existing methods do not effectively integrate the multidimensional features of drugs and provide poor mitigation of noise to get effective feature *** address these limitations,we propose a DDI-Transform neural network framework for DDI event *** DDI-Transform,we design a drug structure information feature extraction module and a drug bind-protein feature extraction module to obtain multidimensional feature information.A stack of DDI-Transform layers in the DDI-Transform network module are then used for adaptive learning,thus adaptively selecting the effective feature information for *** results show that DDI-Transform can accurately predict DDI events and outperform the state-of-the-art *** on different scale datasets confirm the robustness of the method.

关键词： adaptive learning graph convolutional networks interaction prediction meta-path

On the Infinite-Dimensional Modular Lie superalgebras of O-Type

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Algebra Colloquium 2024年第2期31卷 347-360页

作者： Xiaoning Xu jing Zhao Yucai su School of Mathematics and Statistics Liaoning UniversityShenyang 110036China 不详

The natural filtrations of infinite-dimensional Lie superalgebras of O-type over a field of positive characteristic are proved to be invariant under automorphisms by studying ad-nilpotent *** observe that two Lie superalgebras of O-type are isomorphic if and only if the integers in the definition of these Lie superalgebras are ***,all the Lie superalgebras of O-type are classified in the sense of isomorphism.

关键词： filtration isomorphism classification

Tungsten oxide/nitrogen-doped carbon nanotubes composite catalysts for enhanced redox kinetics in lithium-sulfur batteries

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Chinese Journal of Chemical Engineering 2024年第3期67卷 58-67页

作者： Deqing He Zihao Xie qian Yang Wei Wang Chao su School of Energy and Power Jiangsu University of Science and TechnologyZhenjiang 212100China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China

The sluggish redox kinetics of polysulfides in lithium-sulfur(Li-S)batteries are a significant obstacle to their widespread adoption as energy storage ***,recent studies have shown that tungsten oxide(WO_(3))can facilitate the conversion kinetics of polysulfides in Li-S ***,we fabricated host materials for sulfur using nitrogen-doped carbon nanotubes(N-CNTs)and WO_(3).We used low-cost components and simple procedures to overcome the poor electrical conductivity that is a disadvantage of metal *** composites of WO_(3) and N-CNTs(WO_(3)/N-CNTs)create a stable framework structure,fast ion diffusion channels,and a 3D electron transport network during electrochemical reaction *** a result,the WO_(3)/N-CNT-Li2S6 cathode demonstrates high initial capacity(1162 mA·h·g^(-1) at 0.5℃),excellent rate performance(618 mA·h·g^(-1) at 5.5℃),and a low capacity decay rate(0.093%up to 600 cycles at 2℃).This work presents a novel approach for preparing tungsten oxide/carbon composite catalysts that facilitate the redox kinetics of polysulfide conversion.

关键词： Li-S batteries Composites Ion diffusion channels 3D electron transport network Redox kinetics

A versatile model with three-dimensional triangular lattice for unconventional transport and various topological effects

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National Science Review 2024年第1期11卷 204-214页

作者： jing-Yang You Gang su Yuan Ping Feng Department of Physics National University of Singapore Kavli Institute for Theoretical Sciences and CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Centre for Advanced 2D Materials National University of Singapore

The finite Berry curvature in topological materials can induce many subtle phenomena, such as the anomalous Hall effect(AHE), spin Hall effect(SHE), anomalous Nernst effect(ANE), non-linear Hall effect(NLHE) and bulk photovoltaic effects. To explore these novel physics as well as their connection and coupling, a precise and effective model should be developed. Here, we propose such a versatile model—a 3D triangular lattice with alternating hopping parameters, which can yield various topological phases,including kagome bands, triply degenerate fermions, double Weyl semimetals and so on. We reveal that this special lattice can present unconventional transport due to its unique topological surface states and the aforementioned topological phenomena, such as AHE, ANE, NLHE and the topological photocurrent effect. In addition, we also provide a number of material candidates that have been synthesized experimentally with this lattice, and discuss two materials, including a non-magnetic triangular system for SHE, NLHE and the shift current, and a ferromagnetic triangular lattice for AHE and ANE. Our work provides an excellent platform, including both the model and materials, for the study of Berry-curvature-related physics.

关键词： three-dimensional triangular lattice different topological phases various topological effects Berry curvature

Prediction of high-embankment settlement combining joint denoising technique and enhanced GWO-v-SVR method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 317-332页

作者： Qi Zhang qian su Zongyu Zhang Zhixing Deng De Chen School of Civil Engineering Southwest Jiaotong UniversityChengduChina MOE Key Laboratory of High Speed Railway Engineering Southwest Jiaotong UniversityChengduChina

Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure *** study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)***-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet ***,high-embankment settlements were predicted using the EGWO-n-SVR *** this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model *** proposed NHM was then tested in two case ***,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were *** results indicate that the NHM suppresses noise and restores details in high-embankment field ***,the NHM out-performs other alternative prediction methods in prediction accuracy and *** demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field ***,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.

关键词： High embankment Settlement prediction Joint denoising technique Enhanced gray wolf optimizer support vector regression

Free radicals trigger the closure of open pores in lignin-derived hard carbons toward improved sodium-storage capacity

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Journal of Energy Chemistry 2024年第7期94卷 551-559页

作者： Wen-Jun Ji Zong-Lin Yi Ming-Xin Song Xiao-qian Guo Yi-Lin Wang Yi-Xuan Mao Fang-Yuan su jing-Peng Chen Xian-Xian Wei Li-jing Xie Cheng-Meng Chen CAS Key Laboratory of Carbon Materials Institute of Coal ChemistryChinese Academy of SciencesTaiyuan 030001ShanxiChina University of Chinese Academy of Sciences Beijing 100049China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Environment and Safety Taiyuan University of Science and TechnologyTaiyuan 030001ShanxiChina

The chemical activation of various precursors is effective for creating additional closed pores in hard carbons for sodium ***,the formation mechanism of closed pores under the influence of pore-forming agents is not well ***,an effective chemical activation followed by a high-temperature self-healing strategy is employed to generate interconnected closed pores in lignin-derived hard carbon(HCs).By systematic experimental design combined with electron paramagnetic res-onance spectroscopy,it can be found that the content of free radicals in the carbon matrix influences the closure of open pores at high *** high activation temperature(>700 C)leads to a low free radical concentration,making it difficult to achieve self-healing of open pores at high *** activation at 700°C,a balance between pore making and self-healing is achieved in the final hard carbon.A large number of free radicals triggers rapid growth and aggregation of carbon microcrys-tals,blocking pre-formed open micropores and creating additional interconnected closed pores in as-obtained hard *** a result,the optimized carbon anode(LK-700-1300)delivers a high reversible capacity of 330.8 mA h g^(-1) at 0.03 A g^(-1),which is an increase of 86 mA h g^(-1) compared to the pristine lignin-derived carbon anode(L-700-1300),and exhibits a good rate performance(202.1 mA h g^(-1) at 1 A g^(-1)).This work provides a universal and effective guidance for tuning closed pores of hard carbons from otherprecursors.

关键词： Hard carbon Chemical activation Free radical Self-healing Closed pores Sodium ion batteries

The study of intelligent algorithm in particle identification of heavy-ion collisions at low and intermediate energies

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Nuclear Science and Techniques 2024年第2期35卷 170-182页

作者： Gao-Yi Cheng qian-Min su Xi-Guang Cao Guo-qiang Zhang School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghai 201620China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China

Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate *** urgently need solutions to the dilemma of traditional particle identification *** study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate *** intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 ***-based machine learning algorithms and deep learning algorithms *** show excellent performance and generalization *** additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is *** learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.

关键词： Heavy-ion collisions at low and intermediate energies Machine learning Ensemble learning algorithm Particle identification Data imbalance

The main strategies for soil pollution apportionment:A review of the numerical methods

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Journal of Environmental Sciences 2024年第2期136卷 95-109页

作者： Bin Shi jing Meng TieyuWang qianqian Li Qifan Zhang Guijin su Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention Shantou UniversityShantou 515063China

Nowadays,a large number of compounds with different physical and chemical properties have been determined in *** behaviors and source identification of pollutants in soil are the foundation of soil pollution *** and quantitative analysis of potential pollution sources are the prerequisites for its prevention and *** efforts have made to develop methods for identifying the sources of soil *** efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics *** have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our *** numerical methods,such as spatial geostatistics analysis,receptor models,and machine learning methods are addressed in *** most cases,however,the effectiveness of any single approach for source apportionment remains *** multiple methods to address soil quality problems can reduce uncertainty about the sources of soil *** review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source *** review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

关键词： Soil pollutants Source attribution Methodologies Chemical profiles Mathematical models