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SEFormer:A Lightweight CNN-Transformer Based on Separable Multiscale Depthwise Convolution and Efficient Self-Attention for Rotating Machinery Fault Diagnosis

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Computers, Materials & Continua 2025年第1期82卷 1417-1437页

作者： Hongxing Wang Xilai Ju Hua zhu Huafeng Li State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing210016China School of Computer Science and Engineering Nanyang Technological UniversitySingapore639798Singapore

Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain ***,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis ***,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault ***,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative *** complexity results in high computational costs and limited industrial *** tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault ***,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration ***,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global ***,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and *** study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.

关键词： CNN-Transformer separable multiscale depthwise convolution efficient self-attention fault diagnosis

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Influence of rare earth doping on hydrogen absorption properties of Zr_(7)V_(5)Fe alloy

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Journal of Rare Earths 2025年第1期43卷 218-226,I0008页

作者： Shuang Yang Zifeng Luo Guo Yang Lijun Lv Linhua Xu Haiyan Leng Xingbo Han Jianhui zhu Wei Liu Pengfei zhu Jing Xu School of Mathematics Physics and StatisticsShanghai University of Engineering ScienceShanghai201620China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai201800China State Key Laboratory of Advanced Special Steels&Shanghai Key Laboratory of Advanced Ferrometallurgy&School of Materials Science and Engineering Shanghai UniversityShanghai200444China Instrumental Analysis and Research Center Shanghai UniversityShanghai200444China

As a representative of non-evaporative getter,Zr-V-Fe has gained widespread attention due to its advantages including low activation temperatures and rapid hydrogen absorption *** this study,we investigated the impact of La and Ce doping on the thermodynamic,kinetic,and activation properties of Zr_(7)V_(5)Fe alloy.X-ray diffraction analysis shows that rare earth doping causes a decrease in the cell volume of both the ZrV_(2) andα-Zr phases of Zr_(7)V_(5)Fe alloy,which results in an increase in the plateau pressure of the *** kinetic curves illustrate that rare earth doping leads to a coarseα-Zr phases and a larger particle size after activation,resulting in a decrease in the hydrogen absorption kinetic *** for the activation process,the rare earth doped alloys exhibit excellent activation with shorter incubation periods.X-ray photoelectron spectroscopy investigations reveal that Zr and V are initially in a highly oxidized *** the heating temperature increases,they undergo a transition from oxidation state to metal *** content of metal Zr in rare earth doped alloys is higher than that in undoped alloys at 250℃,primarily due to rare earth elements'affinity for oxygen.

关键词： Rare earths Hydrogen absorption thermodynamics X-rayphotoelectron spectroscopy Activation

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Mach reflection and pressure/heating loads on V-shaped blunt leading edges with variable cross-sections and crotches

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Chinese Journal of Aeronautics 2025年第1期38卷 271-285页

作者： Tao ZHANG Xuhui ZHANG Luoyu RAO Chongguang SHI Chengxiang zhu Yancheng YOU School of Aerospace Engineering Xiamen UniversityXiamen 361005China China Academy of Aerospace Science and Innovation Beijing 100176China

The primary Mach Reflection(MR)and pressure/heating loads on V-shaped Blunt Leading Edges(VBLEs)with variable elliptic cross-sections and conic crotches are theoretically investigated in this *** simplified continuity method is used to forecast the shock *** theoretical predictions and the numerical simulations for the Mach stem and the triple point as well as the curved shock accord *** on the theoretical model,an analysis of the impact of the axial ratio a/b of the cross-sectional shape and the eccentricity e of the crotch sweep path on shock structures is carried *** shock configurations obtained from the theoretical model enable the derivation of the transition boundaries between the primary MR and the same family Regular Reflection(sRR).It is found that the increase of a/b and e can both facilitate the primary MR to sRR *** resulting transition and the corresponding generation of the wall pressure and heat flux are then *** results indicate that higher values of the ratio a/b can significantly reduce the wall pressure and heating loads by inducing the primary MR to sRR ***,the increase in the eccentricity e results in increased loads,despite causing the same transition.

关键词： Aerodynamics Hypersonic flow Shock waves Heat flux V-shaped blunt leading edges

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Efficient activation of peroxymonosulfate for catalytic degradation of organic pollutants by simultaneously using low-level cobalt ions and calcium carbonate micro-particles

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Journal of Environmental Sciences 2025年第5期151卷 113-124页

作者： Yu Zhou Xiaobo Wang Nan Wang Shuangshuang Huang Lihua zhu College of Chemistry and Chemical Engineering Huazhong University of Science and TechnologyWuhan 430074China College of Chemistry and Chemical Engineering Hubei Polytechnic UniversityHuangshi 435003China College of Chemistry and Environmental Engineering Wuhan Polytechnic UniversityWuhan 430023China School of Physics and Technology Center for Electron MicroscopyWuhan UniversityWuhan 430072China

An efficient catalytic system was developed to remove various organic pollutants by simultaneously using low-level cobalt ions,calcium carbonate micro-particles and peroxymonosulfate(PMS).A simple base-induced precipitation was used to successfully loaded Co-centered reactive sites onto the surface of CaCO_(3)*** optimal conditions at 25°C,10 mg/L methylene blue(MB)could be completely degraded within 10 min with 480μg/L Co^(2+),0.4 g/L CaCO_(3)microparticles(or 0.4 g/L Co@CaCO_(3))and 0.1 g/L *** MB degradation followed the pseudo first order kinetics with a rate constant of 0.583 min^(−1),being 8.3,11.5 and 53.0 times that by using Co-OH(0.07 min^(−1)),Co^(2+)(0.044 min^(−1))and CaCO_(3)(0.011 min^(−1))as the catalyst,*** was confirmed that there was a synergistic effect in the catalytic activity between Co species and the CaCO_(3)particles but the major contributor was the highly dispersed Co *** Co^(2+)-containing simulated electroplating wastewater was used as the Co^(2+)source,not only the added MB was also completely degraded within 5 min in this catalytic system,but also the coexisting heavy metal ions were substantially *** presently developed method was applied to simultaneously treat organic wastewater and heavy metals *** present method was also successfully used to efficiently degrade other organic pollutants including bisphenol A,sulfamethoxazole,rhodamine B,tetrabromobisphenol A,ofloxacin and benzoic acid.A catalytic mechanism was proposed for the PMS activation by Co@CaCO_(3).The surface of CaCO_(3)particles favors the adsorption of Co^(2+).More importantly,the surface of CaCO_(3)particles provides plentiful surface-OH and-CO_(3)^(2+),and these surface groups complex with Co^(2+)to producemore catalytically active species such as surface[CoOH]^(−),resulting in rapid Co^(2+)/Co^(3+)cycling and electron *** interactions cause the observed synergistic effect between Co species and Ca

关键词： CaCO3 Low-level cobalt Peroxymonosulfate Oxidative degradation

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A Feature Transformation and Selection Method to Acquire an Interpretable Model Incorporating Nonlinear Effects

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Acta Mathematica Sinica,English Series 2025年第2期41卷 703-732页

作者： Yu Zheng Jin zhu Junxian zhu Xueqin Wang International Institute of Finance School of ManagementUniversity of Science and Technology of China Department of Statistical Science School of Mathematics Sun Yat-Sen University Saw Swee Hock School of Public Health National University of Singapore

Finding a highly interpretable nonlinear model has been an important yet challenging problem, and related research is relatively scarce in the current literature. To tackle this issue, we propose a new algorithm called Feat-ABESS based on a framework that utilizes feature transformation and selection for re-interpreting many machine learning algorithms. The core idea behind Feat-ABESS is to parameterize interpretable feature transformation within this framework and construct an objective function based on these parameters. This approach enables us to identify a proper interpretable feature transformation from the optimization perspective. By leveraging a recently advanced optimization technique, Feat-ABESS can obtain a concise and interpretable model. Moreover, Feat-ABESS can perform nonlinear variable selection. Our extensive experiments on 205 benchmark datasets and case studies on two datasets have demonstrated that Feat-ABESS can achieve powerful prediction accuracy while maintaining a high level of interpretability. The comparison with existing nonlinear variable selection methods exhibits Feat-ABESS has a higher true positive rate and a lower false discovery rate.

关键词： Interpretable machine learning Bayesian optimization Adaptive best subset selection Nonlinear variable selection Feature transformation

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Software-defined process-near-memory architecture using 3D hybrid bonding integration

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Science China(Information Sciences) 2025年第1期68卷 366-378页

作者： Anlin XU Chenchen DENG Jianfeng zhu Yao WANG Shaojun WEI Leibo LIU School of Integrated Circuits Tsinghua University Beijing Institution of Tracking and Communication Technology Beijing National Research Center for Information Science and Technology Tsinghua University

With the unprecedented explosive growing amount of global data, the development of computing chips, which encounter bottlenecks such as power wall and memory wall, cannot satisfy the demanding requirement. This work proposes a software-defined process-near-memory(SDPNM) computing architecture implemented using 3D hybrid bonding *** software-defined chip architecture, featuring spatial computations and dynamic reconfiguration, innovates in a top-down manner to achieve high energy efficiency while maintaining flexibility after fabrication. The process-near-memory integration further advances the SDNPM chip in a bottom-up way to reduce the energy consumption of data movement while improving the bandwidth. Utilizing a relatively mature fabrication and bonding process can result in feasible solutions for both data-intensive and compute-intensive applications including digital signal processing and artificial intelligence. The logic die is fabricated in the SMIC 40 nm process and the DRAM die is fabricated in the PSMC 25 nm process. The hybrid bonding is implemented by XMC. The experimental results show that the energy efficiency of the proposed SDPNM chip is 33.1× better than the state-of-the-art FPGA ranging from 8.2× to 104.1×.

关键词： software-defined chips process near memory energy efficiency dynamic reconfiguration domain specific

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Research progress of lignin-derived materials in lithium/sodium ion batteries

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Green Energy & Environment 2025年第2期10卷 322-344页

作者： Jingke Zhang Hengxue Xiang Zhiwei Cao Shichao Wang Meifang zhu Institute of Hybrid Materials National Center of International Research for Hybrid Materials TechnologyNational Base of International Science&Technology CooperationCollege of Materials Science and EngineeringQingdao UniversityQingdao266071China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai201620China

With the increase of energy consumption,the shortage of fossil resource,and the aggravation of environmental pollution,the development of cost-effective and environmental friendly bio-based energy storage devices has become an urgent *** the second most abundant natural polymer found in nature,lignin is mainly produced as the by-product of paper pulping and bio-refining *** possesses several inherent advantages,such as low-cost,high carbon content,abundant functional groups,and bio-renewable,making it an attractive candidate for the rechargeable battery ***,there has been a surge of research interest in utilizing lignin or lignin-based carbon materials as the components of lithium-ion(LIBs)or sodium-ion batteries(SIBs),including the electrode,binder,separator,and *** review provides a comprehensive overview on the research progress of lignin-derived materials used in LIBs/SIBs,especially the application of lignin-based carbons as the anodes of LIBs/*** preparation methods and properties of lignin-derived materials with different dimensions are systemically discussed,which emphasizes on the relationship between the chemical/physical structures of lignin-derived materials and the performances of LIBs/*** current challenges and future prospects of lignin-derived materials in energy storage devices are also proposed.

关键词： Lignin-based carbons Lithium battery Sodium battery Chemical structure evolution

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RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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Science China(Information Sciences) 2025年第2期68卷 103-119页

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao zhu Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

关键词： knowledge graph reasoning temporal knowledge graph Hawkes process semantic evidence

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Exploring the potential of extrachromosomal DNA as a novel oncogenic driver

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Science China(Life Sciences) 2025年第1期68卷 144-157页

作者： Huanbo zhu Longtao Huangfu Junbing Chen Jiafu Ji Xiaofang Xing Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Division of Gastrointestinal Cancer Translational Research LaboratoryPeking University Cancer Hospital&InstituteBeijing 100142China Department of Gastrointestinal Cancer Center Peking University Cancer Hospital&InstituteBeijing 100142China Department of Liver Surgery&Transplantation Liver Cancer InstituteZhongshan HospitalFudan UniversityKey Laboratory of Carcinogenesis and Cancer InvasionMinistry of EducationShanghai200032China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers Beijing Key Laboratory of Carcinogenesis and Translational ResearchDivision of Gastrointestinal Cancer Translational Research LaboratoryPeking University Cancer Hospital&InstituteBeijing 100142China

Extrachromosomal DNA(ecDNA)is a form of circular DNA mostly found in tumor *** the typical chromosomal DNA,ecDNA is circular,self-replicating,and carries complete or partial gene *** ecDNA occurrence remains a rare event in cancer,recent studies have shown that oncogene amplification on ecDNA is widespread throughout many types of cancer,implying that ecDNA plays a central role in accelerating tumor *** has also been associated with increased tumor mutation burden,chromosomal instability,and even tumor microenvironment *** may be crucial in influencing tumor heterogeneity,drug sensitivity,oncogenic senescence,and tumor immunogenicity,leading to a worsening prognosis for tumor *** this way,several clinical trials have been conducted to investigate the importance of ecDNA in clinical *** this review,we summarize the biogenesis,characteristics,and current research methods of ecDNA,discuss the vital role of ecDNA-caused tumor heterogeneity in cancers,and highlight the potential role of ecDNA in cancer therapy.

关键词： extrachromosomal DNA cancer therapy tumor heterogeneity drug resistance tumor evolution

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The controlled oxidation states of the H4PMo11VO40 catalyst induced by plasma for the selective oxidation of methacrolein

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Chinese Chemical Letters 2025年第02期36卷 189-194页

作者： Gang Hu Chun Wang Qinqin Wang Mingyuan zhu Lihua Kang School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering Shihezi University College of Chemistry&Chemical Engineering Yantai University

In this paper,low-temperature dielectric-blocked discharge plasma （DBD） was employed for the first time to treat silica-doped H4PMo11VO40（HPAV） catalysts (DBD（Ar/x）-MF-Catal) and apply them in the catalytic methacrolein （MAL） selective oxidation to produce methacrylic acid （MAA）.This work investigates in detail the controllable regulation of the concentration of oxidation states on silica-doped HPAV catalysts by adjusting the DBD discharge with controlled changes in voltage,current,treatment time,and treatment *** reports the intrinsic correlation between oxidation states and MAL oxidation *** research results indicated that the catalytic performance was related to the presence of oxygen vacancies and oxygen species (VO2+),and are the main reason for the selective oxidation of MAL to ***,the generation of oxygen vacancies and VO2+altered localized electrons,which resulted in the easier activation of *** calculations of DFT also proved the formation mechanism of oxygen vacancies and VO2+and electron properties on high-performance polymers,which elucidated the intrinsic influence of catalyst *** DBD（Ar/10）-MF-Catal catalysts with suitable VO2+and oxygen vacancy concentrations exhibited the highest catalytic performance with 90%MAL conversion and 70%MAA selectivity and showed good stability （500 h）.

关键词： Catalyst Dopant Methacrolein Methacrylic acid Oxygen vacancy Plasma

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