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Synergistically enhanced ORR and HER performance on Co-N-C coupled in-situ generated PtCo intermetallic

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Journal of Energy Chemistry 2025年第1期100卷 721-729页

作者： Guanyu Luo Min Song Lulu An Xiao Huang Qian Zhang Chenhao Zhang Tao Shen Shuang Wang Deli Wang Key Laboratory of Material Chemistry for Energy Conversion and Storage (huazhong university of Science and Technology) Ministry of Education School of Chemistry and Chemical Engineering Huazhong University of Science and Technology

Integrating multi-scale sites in a composite catalyst is vital to realize efficient ***,a synergistic composite catalyst consisting of Co atomic sites and in-situ generated PtCo intermetallic compounds （IMCs）(o-PtCo@CoNC) is proposed through Co pre-anchoring and subsequent impregnation-reduction *** loading of Co atoms provides a chance for in-situ generating PtCo ordered intermetallic *** remaining Co single atoms and PtCo IMCs construct synergistic electrocatalytic *** from the ordered structure,synergistic effect of Pt Co IMCs and Co single atoms,o-PtCo@CoNC exhibits excellent electrocatalytic performance for oxygen reduction reaction （ORR） and hydrogen evolution reaction （HER） with mass activity of 1.21 A mgPt-1（at 0.9 V） and5.70 A mgPt-1（at an overpotential of 100 mV）,***,o-PtCo@CoNC delivers negligible loss of half-wave potential and overpotential during long-term stability test in acid solutions,with 13 mV decay after 50,000 potential cycles for ORR and a 2.7 mV decay after 20,000 potential cycles for *** integration strategy of single-atomic sites coupled IMCs paves the way for enhancing the activity and durability of Pt-based electrocatalysts.

关键词： Synergistic effect Intermetallics Single atomic sites Oxygen reduction reaction Hydrogen evolution reaction

A quantum-search-based multi-classifier for image recognition

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 21-31页

作者： Lu Liu Xingyu Wu Lufan Zhang Chuan Wang School of Artificial Intelligence Beijing Normal University Applied Optics Beijing Area Major Laboratory Beijing Normal University

The multi-class classification of images is a pivotal challenge within the realm of image processing. As the volume of visual data continues to expand, there is a burgeoning interest in harnessing the unique capabilities of quantum computation to augment the efficiency of classification tasks. However, many existing methods for training quantum image multi-classifiers parallel classical machine learning techniques, where the requisite circuit measurements increase linearly with the volume of training data. This work introduces a novel approach for training a quantum image multi-classifier based on the quantum search algorithm. We have meticulously conducted rigorous experiments on a handwritten digit dataset, a classic benchmark in the field. The results have been meticulously compared with previous works, and the comparative analysis not only validates the efficiency of our proposed approach, requiring only O(N/b) measurements during training, but also highlights a significant quadratic speedup of the algorithm.

关键词： quantum computation image recognition quantum search algorithm

Synergistic effect of bonding heterogeneity and phonon localization in introducing excellent thermoelectric properties in layered heteroanionic NdZnSbO material

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Journal of Energy Chemistry 2025年第1期100卷 259-272页

作者： Da Wan Shuwei Tang Shulin Bai Xiaodong Li Peng Ai Wanrong Guo Tuo Zheng College of Materials Science and Engineering Liaoning Technical University Faculty of Chemistry Northeast Normal University

Layered rare-earth metal oxides, harnessing the dual properties of oxides and two-dimensional layered materials, exhibit remarkable thermal stability and quantum confinement effects. Therefore, this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound. The coexistence of weak interlayer van der Waals interactions, robust intralayer ionic bonding, and partial covalent bonding leads to remarkable bonding heterogeneity, which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction. The weakened chemical bonds induced by the antibonding states, together with the rattling-like behavior of the Zn atom, culminate in the profound anharmonicity in the layered NdZnSbO compound. The weakening bond and heavy element contribute to the softness of phonon modes, which significantly diminishes the phonon group velocity. The redistribution-dominated four-phonon scattering process spans a large optical gap, which effectively reduces the lattice thermal conductivity. The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06) functional in combination with spin–orbit coupling(SOC) effect. The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy, thus amplifying the power factor. Consequently, an optimal figure-of-merit(ZT) of 3.40 at 900 K is achieved for the n-type NdZnSbO compound. The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.

关键词： Bond strength (chemical)

Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model

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Computers, Materials & Continua 2025年第1期82卷 843-862页

作者： Feifei Yu Yongxian Huang Guoyan Chen Xiaoqing Yang Canyi Du Yongkang Gong School of Mechatronic Engineering Guangdong Polytechnic Normal UniversityGuangzhou510665China School of Automotive and Transportation Engineering Guangdong Polytechnic Normal UniversityGuangzhou510665China

To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire *** the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different *** collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,*** collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two *** results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,*** underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other ***,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline *** analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire *** delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)*** findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant ***,in the SENET model,data points of various types were more widely and evenly dispersed,demonstra

关键词： Channel attention SENET model engine misfire fault fault detection

Observation of topological charge transformations in acoustic vortex using passive periodic systems

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 140-147页

作者： Di-Chao Chen Xie Liu Changqing Xu Da-Jian Wu Ying Cheng Xiao-Jun Liu School of Physics and Technology Nanjing Normal University Key Laboratory of Modern Acoustics School of Physics Nanjing University

Vortex transmutation utilizes a periodic system, which not only enables the alteration of the topological charge(TC) of unstable input vortices but also facilitates their transformation into stable structures. This approach is crucial for investigating the characteristics of vortices in various wave systems. Here, we achieve acoustic vortex TC transmutation by employing a welldesigned dual-structured plate external system(DPES). The interactions between the acoustic vortex and the finite-order discrete rotational symmetry lead to the transformation of its topological charge when complete rotational symmetry is broken to Nthorder discrete symmetry. Our results experimentally demonstrate the acoustic vortex TC transmutation based on passive artificial structures, enabling numerous applications in particle manipulation and information multiplexing as well as advancing our understanding and control over free-space acoustic vortices.

关键词： acoustic vortex topological charge transformation artificial structure

MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

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Computers, Materials & Continua 2025年第1期82卷 485-498页

作者： Jun Wang Mingjie Wang Zijie Li Ken Chen Jiatian Mei Shu Zhang Key Laboratory of Education Informatization for Nationalities Ministry of EducationYunnan Normal UniversityKunming650000China Yunnan Key Laboratory of Smart Education Yunnan Normal UniversityKunming650000China

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant *** tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional *** knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential ***,these models may neglect crucial short-term dynamics and other relevant *** paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)*** proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature *** architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key *** evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge *** results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

关键词： Knowledge tracing multilayer perceptron channel mixer sequence mixer

Attention Eraser and Quantitative Measures for Automated Bone Age Assessment

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Computers, Materials & Continua 2025年第1期82卷 627-644页

作者： Liuqiang Shu Lei Yu College of Computer and Information Science Chongqing Normal UniversityChongqing401331China

Bone age assessment(BAA)aims to determine whether a child’s growth and development are normal concerning their chronological *** predict bone age more accurately based on radiographs,and for the left-hand X-ray images of different races model can have better adaptability,we propose a neural network in parallel with the quantitative features from the left-hand bone measurements for *** this study,a lightweight feature extractor(LFE)is designed to obtain the featuremaps fromradiographs,and amodule called attention erasermodule(AEM)is proposed to capture the fine-grained ***,the dimensional information of the metacarpal parts in the radiographs is measured to enhance the model’s generalization capability across images fromdifferent *** is trained and validated on the RSNA,RHPE,and digital hand atlas datasets,which include images from various racial *** model achieves a mean absolute error(MAE)of 4.42 months on the RSNA dataset and 15.98 months on the RHPE *** to ResNet50,InceptionV3,and several state-of-the-art methods,our proposed method shows statistically significant improvements(p<0.05),with a reduction in MAE by 0.2±0.02 years across different racial ***,t-tests on the features also confirm the statistical significance of our approach(p<0.05).

关键词： Bone age assessment attention eraser quantitative feature metacarpal bones

Cell polarization in ischemic stroke: molecular mechanisms and advances

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Neural Regeneration Research 2025年第3期20卷 632-645页

作者： Yuanwei Li Xiaoxiao Xu Xuan Wu Jiarui Li Shiling Chen Danyang Chen Gaigai Li Zhouping Tang Department of Neurology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

Ischemic stroke is a cerebrovascular disease associated with high mortality and disability rates. Since the inflammation and immune response play a central role in driving ischemic damage, it becomes essential to modulate excessive inflammatory reactions to promote cell survival and facilitate tissue repair around the injury site. Various cell types are involved in the inflammatory response, including microglia, astrocytes, and neutrophils, each exhibiting distinct phenotypic profiles upon stimulation. They display either proinflammatory or anti-inflammatory states, a phenomenon known as ‘cell polarization.’ There are two cell polarization therapy strategies. The first involves inducing cells into a neuroprotective phenotype in vitro, then reintroducing them autologously. The second approach utilizes small molecular substances to directly affect cells in vivo. In this review, we elucidate the polarization dynamics of the three reactive cell populations(microglia, astrocytes, and neutrophils) in the context of ischemic stroke, and provide a comprehensive summary of the molecular mechanisms involved in their phenotypic switching. By unraveling the complexity of cell polarization, we hope to offer insights for future research on neuroinflammation and novel therapeutic strategies for ischemic stroke.

关键词： astrocyte polarization immune regulation inflammation ischemic injury microglia polarization neutrophil polarization signaling pathways stroke

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Local magnetic moment oscillation around an Anderson impurity on graphene

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 192-201页

作者： Shuai Li Zhen Ma Jin-Hua Gao School of Science Hebei University of Science and Technology School of Electronics and Information Zhengzhou University of Light Industry School of Physics and Wuhan National High Magnetic Field Center Huazhong University of Science and Technology

We theoretically investigate the spin resolved Friedel oscillation （FO） and quasiparticle interference （QPI） in graphene induced by an Anderson *** the impurity becomes magnetic,the resulted FO becomes spin dependent,which gives rise to a local magnetic moment oscillation with an envelop decaying as r-2in real space in the doping ***,at half filling,the electron density and local magnetic moment will not oscillate but decay as *** spin resolved FO has both sublattice and spin ***,the local magnetic moment decay at half filling only occurs at one sublattice of graphene,which is quite like the phenomenon observed in the STM experiment (***ález-Herrero et al.,Science 352,437 （2016）).We further give an analytic formula about such spin dependent FO based on the stationary phase ***,we study the interference of quasiparticles around the magnetic impurity by calculating the spin dependent Fourier-transformed local density of states （FT-LDOS）.Our work gives a comprehensive understanding about the local magnetic moment oscillation around an Anderson impurity on graphene.

关键词： Friedel oscillation local magnetic moment graphene Anderson impurity