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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

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

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

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

A Two-layer Framework for Mitigating the Con-gestion of Urban Power Grids Based on Flexible Topology with Dynamic Thermal Rating

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Protection and Control of Modern Power Systems 2024年第4期9卷 83-95页

作者： Yi su Jiashen Teh qian Luo Kangmiao Tan Jiaying Yong the School of Automation and Electronic In-formation Xiangtan Universityxiangtan 411100China IEEE the School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Penang 11800Malaysia the School of Computer Sciences Universiti Sains Malaysia(USM)Penang 11800Malaysia the Institute of Power Engineering College of EngineeringUniversiti Tenaga Nasional(UNITEN)Kajang 43000Malaysia

The urban power grid(UPG)combines transmission and distribution *** studies on UPG congestion mitigation have primarily focused on relieving local congestion while ignoring large-scale energy transfer with safety margins and load *** situation is expected to worsen with the proliferation of renewable energy and electric *** this paper,a two-layer congestion mitigation framework is proposed,one which considers the congestion of the UPG with flexible *** the upper-layer,the particle swarm optimization algorithm is employed to optimize the power supply distribution(PSD)of substation *** is known as the upper-layer *** lower-layer model recalculates the new PSD,known as the lower-layer PSD,based on the topology candidates.A candidate topology is at an optimum when the Euclidean distance mismatch between the upper-and lower-layer PSDs is the *** optimum topology is tested by standard power flow to ascertain its *** optimum transitioning sequence between the initial and optimum topologies is also determined by the two-layer framework to minimize voltage deviation and line overloading of the UPG considering dynamic thermal *** proposed framework is tested on a 56-node test *** show that the proposed framework can significantly reduce congestion,maintain safety margins,and determine the optimum transitioning sequence.

关键词： Congestion mitigation urban power grid two-layer framework transitioning sequence dynamic thermal rating

PN-ImTLSM facilitates high-throughput low background single-molecule localization microscopy deep in the cell

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Biophysics Reports 2021年第4期7卷 313-325页

作者： Boxin Xue Caiwei Zhou Yizhi Qin Yongzheng Li Yuao sun Lei Chang Shipeng Shao Yongliang Li Mengling Zhang Chaoying sun Renxi He qian peter su Yujie sun State Key Laboratory of Membrane Biology Biomedical Pioneer Innovation Center (BIOPIC)School of Life SciencesPeking University College of Chemistry and Molecular Engineering Peking University Academy for Advanced Interdisciplinary Studies Peking University Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) Beijing Institute of Heart Lung and Blood Vessel Disease Beijing Anzhen HospitalCapital Medical University Department of Geriatric Dentistry Peking University School and Hospital of Stomatology School of Biomedical Engineering Faculty of Engineering and Information TechnologyUniversity of Technology Sydney School of Future Technology Peking University

When imaging the nucleus structure of a cell, the out-of-focus fluorescence acts as background and hinders the detection of weak signals. Light-sheet fluorescence microscopy(LSFM) is a wide-field imaging approach which has the best of both background removal and imaging speed. However, the commonly adopted orthogonal excitation/detection scheme is hard to be applied to single-cell imaging due to steric hindrance. For LSFMs capable of high spatiotemporal single-cell imaging, the complex instrument design and operation largely limit their throughput of data collection. Here, we propose an approach for high-throughput background-free fluorescence imaging of single cells facilitated by the Immersion Tilted Light Sheet Microscopy(ImTLSM). ImTLSM is based on a light-sheet projected off the optical axis of a water immersion objective. With the illumination objective and the detection objective placed opposingly, ImTLSM can rapidly patrol and optically section multiple individual cells while maintaining single-molecule detection sensitivity and resolution. Further, the simplicity and robustness of ImTLSM in operation and maintenance enables high-throughput image collection to establish background removal datasets for deep learning. Using a deep learning model to train the mapping from epi-illumination images to ImTLSM illumination images, namely PN-ImTLSM, we demonstrated crossmodality fluorescence imaging, transforming the epi-illumination image to approach the background removal performance obtained with ImTLSM. We demonstrated that PN-ImTLSM can be generalized to large-field homogeneous illumination imaging, thereby further improving the imaging throughput. In addition, compared to commonly used background removal methods, PN-ImTLSM showed much better performance for areas where the background intensity changes sharply in space, facilitating high-density single-molecule localization microscopy. In summary, PN-ImTLSM paves the way for background-free fluorescence imaging

关键词： Light-sheet fluorescence microscopy Background-free fluorescence imaging Deep learning Single cell imaging Homogeneous illumination Single-molecule localization microscopy

Boring holes in Au nanoplates by active surface etching

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Nano Research 2024年第9期17卷 8610-8617页

作者： Haiyang Hu Yuntao Wang qian Wang Xudong Peng An su Hong Wang Hongyu Chen Institute of Advanced Synthesis(IAS)and School of Chemistry and Molecular Engineering Jiangsu National Synergetic Innovation Centre for Advanced MaterialsNanjing Tech UniversityNanjing 211816China Department of Environmental Science and Engineering University of Science and Technology of ChinaHefei 230026China Department of Chemistry School of Science and Key Laboratory for Quantum Materials of Zhejiang ProvinceResearch Center for Industries of the FutureWestlake UniversityHangzhou 310030China Institute of Natural Sciences Westlake Institute for Advanced StudyHangzhou 310024China

In contrast to the conventional etching that makes nanoparticles rounder and our previous sharpening etching mode that causes serrated edges,here,we developed a new boring etching mode that targets the faces of Au nanoplates to make *** critical factors are the pre-incubation step with the ligand 2-mercapto-5-benzimidazolecarboxylic acid(MBIA)and the subsequent removal of excess ligands in the ***,etching is focused onto the few sites with initial loss of ligands,which cannot be quickly *** choice of ligand MBIA is also of importance,as it carries negative charge and repels each *** inability of forming a dense layer probably plays a critical role in the site-selectivity for faces,because ligands at the higher curvature edges and corners are expected to have less *** etching results from the comproportionation reaction between Au3+and Au0 in the nanoplates,where Br-coordination to Au and the extra stabilization from cetyltrimethylammonium bromide(CTAB)are *** believe that the ability of boring holes is an important tool for future synthetic designs.

关键词： Au nanoplates active surface etching boring etching mode cetyltrimethylammonium bromide(CTAB)passivation holes

Stability analysis of loose accumulation slopes under rainfall:case study of a high‑speed railway in Southwest China

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Railway Engineering Science 2024年第1期32卷 95-106页

作者： Xin Wang qian su Zongyu Zhang Feihu Huang Chenfang He School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China Key Laboratory of High‑Speed Railway Engineering Ministry of Education School of Civil EngineeringSouthwest Jiaotong UniversityChengdu 610031China CCCC Second Highway Consultants Co. Ltd.Wuhan 430056China

The high and steep slopes along a high-speed railway in the mountainous area of Southwest China are mostly composed of loose accumulations of debris with large internal pores and poor stability,which can easily induce adverse geological disasters under rainfall *** ensure the smooth construction of the high-speed railway and the subsequent safe operation,it is necessary to master the stability evolution process of the loose accumulation slope under *** article simulates rainfall using the finite element analysis software’s hydromechanical coupling *** slope stability under various rainfall situations is calculated and analysed based on the strength reduction *** validate the simulation results,a field monitoring system is established to study the deformation characteristics of the slope under *** results show that rainfall duration is the key factor affecting slope *** a constant amount of rainfall,the stability of the slope decreases with increasing duration of ***,when the amount and duration of rainfall are constant,continuous rainfall has a greater impact on slope stability than intermittent *** setting of the field retaining structures has a significant role in improving slope *** field monitoring data show that the slope is in the initial deformation stage and has good stability,which verifies the rationality of the numerical simulation *** research results can provide some references for understanding the influence of rainfall on the stability of loose accumulation slopes along high-speed railways and establishing a monitoring system.

关键词： High-speed railway Loose accumulation slope Slope stability analysis Rainfall effect Strength reduction

Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

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Railway Engineering Science 2024年第2期32卷 194-210页

作者： Taifeng Li Kang Xie Xiaobin Chen Zhixing Deng qian su Railway Engineering Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China Department of Civil Engineering Central South UniversityChangsha 410075China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China

The compaction quality of subgrade filler strongly affects subgrade *** main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse ***,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade *** indexes of 2D subgrade filler are then computed and statistically ***,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine ***,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle *** dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine *** the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the *** study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

关键词： subgrade filler particles Deep learning particle Shape analysis Particle library Compaction characteristics Discrete element method(DEM)