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Journal of Energy Chemistry 2022年第10期31卷 549-555,I0014页

作者： yiming leng Bolong Yang Yun Zhao Zhonghua Xiang State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029China

The low activity and durability are still the critical barriers for non-precious metal electrocatalyst,mainly involving M-N/C(M=Fe,Co,Mn et al),applied in fuel cell.Constructing bimetallic sites has been explored as an effective method to boost the performance of the catalyst for the synergistic effect between metal atoms.However,this synergistic effect is always suppressed in acidic conditions and results in unstable catalytic performance.Here we create novel fluorinated iron(Fe)and cobalt(Co)bimetallic nanoparticles distributed on nitrogen-doped carbon nanofibers(CNFs)for oxygen reduction reaction(ORR).The fluorination strongly increased the charge density of the bimetallic catalyst and resulted in a remarkable catalytic performance with the half-wave potential of 804 m V in 0.1 M HCl O_(4)and 1.6 times power density improvement for the proton exchange membrane fuel cell device.Importantly,the chemical and mechanical robust CNFs support improved the electric conductivity and stability of bimetallic catalysts,which leads to an ultra-stable electrocatalyst.The fuel cell voltage can keep stable even after 110 h,instead of the continuingly decrease in the traditional M-N/C.

关键词： Bimetallic catalyst Fluorination Electrospinning ORR catalyst PEM fuel cell

Plastic deformation behavior of a Cu-10Ta alloy under strong impact loading

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Defence Technology（防务技术） 2024年第2期32卷 368-382页

作者： Ping Song Jianghai Liu Wenbin Li yiming Li Research Institute of Chemical Defense Academy of Military ScienceBeijing102205China Ministerial Key Laboratory of ZNDY Nanjing University of Science and TechnologyNanjing210094China

In this work,a Cu-10Ta alloy with a copper to tantalum mass ratio of 9:1 is prepared using powder metallurgy technology.Physical properties of the alloy,including density,microstructure,melting point,and constant-volume specific heat,are tested.Via the split Hopkinson pressure bar(SHPB)and flyerplate impact experiments,the relationship between equivalent stress and equivalent plastic strain of the material is studied at temperatures of 298-823 K and under strain rates of 1×10^(-3)-5.2×10^(3)s^(-1),and the Hugoniot relationship at impact pressures of 1.46-17.25 GPa and impact velocities of 108-942 m/s is obtained.Evolution of the Cu-10Ta microstructure that occurs during high-strain-rate impact is analyzed.Results indicate that the Cu-10Ta alloy possesses good thermal stability,and at ambient temperatures of up to 50%its melting point,stress softening of less than 15%of the initial strength is observed.A modified J-C constitutive model is employed to accurately predict the variation of yield strength with strain rate.Under strong impact,the copper phase is identified as the primary source of plastic deformation in the Cu-10Ta alloy,while significant deformation of the high-strength tantalum particles is less pronounced.Furthermore,the longitudinal wave speed D is found to correlate linearly with the particle velocity u upon strong impact.Analysis reveals that the sound speed and spallation strength of the alloy increase with increasing impact pressure.

关键词： Cu-10Ta SHPB Plastic deformation Flyer impact Hugoniot relationship

Fast spreading of surface ozone in both temporal and spatial scale in Pearl River Delta

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Journal of Environmental Sciences 2024年第3期137卷 540-552页

作者： Tianhui Cao Haichao Wang Lei Li Xiao Lu yiming Liu Shaojia Fan School of Atmospheric Sciences Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Key Laboratory of Tropical Atmosphere-Ocean SystemMinistry of EducationZhuhai 519082China

Surface ozone(O_(3))is a major air pollutant and draw increasing attention in the Pearl River Delta(PRD),China.Here,we characterize the spatial-temporal variability of ozone based on a dataset obtained from 57 national monitoring sites during 2013-2019.Our results show that:(1)the seasonal difference of ozone distribution in the inland and coastal areas was significant,which was largely affected by the wind pattern reversals related to the East Asian monsoon,and local ozone production and destruction;(2)the daily maximum 8hr average(MDA8 O_(3))showed an overall upward trend by 1.11 ppbv/year.While the trends in the nine cities varied differently by ranging from-0.12 to 2.51 ppbv/year.The hot spots of ozone were spreading to southwestern areas from the central areas since 2016.And ozone is becoming a year-round air pollution problem with the pollution season extending to winter and spring in PRD region.(3)at the central and southwestern PRD cities,the percentage of exceedance days from the continuous type(defined as≥3 days)was increasing.Furthermore,the ozone concentration of continuous type was much higher than that of scattered exceedance type(lenge in mitigation of O_(3)pollution in these cities.

关键词： Surface ozone pollution Ozone trend Spatial and temporal variability Pearl River Delta Pollution mitigation

Maximizing conditional independence for unsupervised domain adaptation

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Science China(Information Sciences) 2024年第5期67卷 136-149页

作者： yiming ZHAI Chuanxian REN Youwei LUO Daoqing DAI School of Mathematics Sun Yat-Sen University

Unsupervised domain adaptation(UDA) studies how to transfer a learner from a labeled source domain to an unlabeled target domain with different distributions. Existing methods mainly focus on matching marginal distributions of the source and target domains, which probably leads to a misalignment of samples from the same class but different domains. In this paper, we tackle this misalignment issue by achieving the class-conditioned transferring from a new perspective. Specifically, we propose a method named maximizing conditional independence(MCI) for UDA, which maximizes the conditional independence of feature and domain given class in the reproducing kernel Hilbert spaces. The optimization of conditional independence can be viewed as a surrogate for minimizing class-wise mutual information between feature and domain. An interpretable empirical estimation of the conditional dependence measure is deduced and connected with the unconditional case. Besides, we provide an upper bound on the target error by taking the class-conditional distribution into account, which provides a new theoretical insight for class-conditioned transferring. Extensive experiments on six benchmark datasets and various ablation studies validate the effectiveness of the proposed model in dealing with UDA.

关键词： conditional independence kernel method domain adaptation class-conditioned transferring

Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

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Computers, Materials & Continua 2024年第4期79卷 1063-1088页

作者： yiming Tang Jianwei Gao Yifan Huang School of Computer and Information Hefei University of TechnologyHefei230601China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R 2V4Canada

Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.

关键词： Fuzzy reasoning the CRI method the triple I method fuzzy implication interval robustness

Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

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Computers, Materials & Continua 2024年第5期79卷 2813-2831页

作者： Zheng Yang Ke Gu yiming Zuo School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

关键词： Federated learning Byzantine attacks backdoor triggers

Impact of carbon disclosure on debt financing costs

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Chinese Journal of Population,Resources and Environment 2024年第1期22卷 98-108页

作者： yiming Hu Yunfeng Liang School of Management and Economics Beijing Institute of TechnologyBeijing 100081China China Center for International Economic Exchanges Beijing 100050China

Creditors,such as banks,often use disclosed environmental information to assess a company’s environmental risk and ensure the safety of debt funds.Consequently,carbon disclosures have become an important consideration for creditors when making investments.This study explores the relationship between carbon disclosure and debt financing costs using data on listed companies from 2008 to 2019.The results show that carbon disclosure can reduce the debt financing costs of enterprises,and that this influence is more significant for private companies than for state-owned enterprises.Instrumental variables and Propensity Score Matching(PSM)were used to evaluate the robustness of negative relationships.Furthermore,carbon disclosure has a more significant impact on debt costs with less environmental supervision pressure,weak residents’environmental awareness,and weak product market competition.These findings provide guidance for companies’carbon information disclosure and support the establishment of official carbon disclosure standards.

关键词： Carbon disclosure Debt financing cost State-owned enterprise Private enterprise

A self-centering and stiffness-controlled MEMS accelerometer

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Microsystems & Nanoengineering 2024年第1期10卷 27-40页

作者： yiming Jin Zhipeng Ma Ziyi Ye Mingkang Li Xudong Zheng Zhonghe Jin School of Aeronautics and Astronautics Zhejiang UniversityHangzhou 310013China Key Laboratory of Micro/Nano-Satellite Research of Zhejiang Province Hangzhou 310007PR China

This paper presents a high-performance MEMS accelerometer with a DC/AC electrostatic stiffness tuning capability based on double-sided parallel plates(DSPPs).DC and AC electrostatic tuning enable the adjustment of the effective stiffness and the calibration of the geometric offset of the proof mass,respectively.A dynamical model of the proposed accelerometer was developed considering both DC/AC electrostatic tuning and the temperature effect.Based on the dynamical model,a self-centering closed loop is proposed for pulling the reference position of the forceto-rebalance(FTR)to the geometric center of DSPP.The self-centering accelerometer operates at the optimal reference position by eliminating the temperature drift of the readout circuit and nulling the net electrostatic tuning forces.The stiffness closed-loop is also incorporated to prevent the pull-in instability of the tuned low-stiffness accelerometer under a dramatic temperature variation.Real-time adjustments of the reference position and the DC tuning voltage are utilized to compensate for the residue temperature drift of the proposed accelerometer.As a result,a novel controlling approach composed of a self-centering closed loop,stiffness-closed loop,and temperature drift compensation is achieved for the accelerometer,realizing a temperature drift coefficient(TDC)of approximately 7μg/℃ and an Allan bias instability of less than 1μg.

关键词： stiffness electrostatic centering

SNR-adaptive deep joint source-channel coding scheme for image semantic transmission with convolutional block attention module

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 1-11页

作者： Yang Yujia Liu yiming Zhang Wenjia Zhang Zhi State Key Laboratory of Networking and Switch Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless environment.However,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and transmission.The uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)scenarios.To address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions respectively.The proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result.Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.

关键词： semantic communication joint source-channel coding image transmission

Review on the terahertz metasensor:from featureless refractive index sensing to molecular identification

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Photonics Research 2024年第2期12卷 194-217页

作者： JIAMING LYU LIHAO HUANG LIN CHEN yiming ZHU SONGLIN ZHUANG THz Technology Innovation Research Institute Shanghai Key Laboratory of Modern Optical SystemUniversity of Shanghai for Science and TechnologyShanghai 200093China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China

The terahertz(THz)wave is at the intersection between photonics and electronics in the electromagnetic spectrum.Since the vibration mode of many biomedical molecules and the weak interaction mode inside the molecules fall in the THz regime,utilizing THz radiation as a signal source to operate substance information sensing has its unique advantages.Recently,the metamaterial sensor(metasensor)has greatly enhanced the interaction between signal and substances and spectral selectivity on the subwavelength scale.However,most past review articles have demonstrated the THz metasensor in terms of their structures,applications,or materials.Until recently,with the rapid development of metasensing technologies,the molecular information has paid much more attention to the platform of THz metasensors.In this review,we comprehensively introduce the THz metasensor for detecting not only the featureless refractive index but also the vibrational/chiral molecular information of analytes.The objectives of this review are to improve metasensing specificity either by chemical material-assisted analyte capture or by physical molecular information.Later,to boost THz absorption features in a certain frequency,the resonant responses of metasensors can be tuned to the molecular vibrational modes of target molecules,while frequency multiplexing techniques are reviewed to enhance broadband THz spectroscopic fingerprints.The chiral metasensors are also summarized to specific identification chiral molecules.Finally,the potential prospects of next generation THz metasensors are discussed.Compared to featureless refractive index metasensing,the specific metasensor platforms accelerated by material modification and molecular information will lead to greater impact in the advancement of trace detection of conformational dynamics of biomolecules in practical applications.

关键词： refractive index sensor