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NASTCNN: a spatio-temporal convolutional neural network with non-local attention mechanism for image-induced brain activity pattern recognition

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Optoelectronics Letters 2025年

作者： TAN Xiangxin SHAO Mingxiong ZENG Ke GU Yue School of Computer Science and engineering， Tianjin University of Technology engineering research center of Learning-Based intelligent system (Ministry of Education)， Tianjin University of Technology Krembil research Institute， University Health Network

Deciphering the brain’s visual processing mechanisms has always been a hot topic. Using neural signal patterns to predict the corresponding external visual stimuli is crucial in understanding the interaction of real visual scenes. There are some challenges in the study of image-induced brain activity pattern recognition based on electroencephalogram (EEG)， e.g. how to fully utilize the effective features of EEG signals to improve the classification， and how the frequency and the length of EEG effect the model performance. We design an experimental paradigm that minimizes the interaction between visual stimuli， and propose a spatio-temporal convolutional neural network with non-local attention mechanism (NASTCNN) for image-induced brain activity pattern recognition. The framework utilizes non-local feature extraction operations to realize global information interaction between EEG signals over long distances and enhance the feature expression of some important information. Our model achieves the best performance on both MNIST-EEG and ImageNet-EEG datasets. The classification results are 24.00% and 50.10% respectively， higher than the random probability. We also analyze the effects of different EEG frequency bands and time subsequences of different lengths on the classification performance and which brain regions are activated over time. The results show that when full frequency band and entire length sequence are selected， the classification result is optimal. The occipital region is essential for processing visual tasks， and the temporal region and some frontal regions also play important role in the later stage of visual decoding. This research can help us better understand the visual processing mechanism of the brain.

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Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao Ren Cheng Xu Chengkuo Lee Department of Electrical and Computer engineering National University of SingaporeSingapore 117583Singapore center for intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

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Learning to see speckle in the weak laser field through multimode fiber

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Optoelectronics Letters 2025年

作者： JI Yunqi SONG Binbin LI Xueqing LI Yonghui The engineering research center of Learning-Based intelligent system (Ministry of Education)， the Key Laboratory of Computer Vision and systems (Ministry of Education)， and the School of Computer Science and engineering， Tianjin University of Technology

Multimode fibers (MMFs) have great potential for endoscopic imaging due to the high number of modes and a small core diameter. Deep learning based on neural networks has received increasing attention in the field of scattering image reconstruction. However， most studies focus on designing complex network architectures to improve reconstruction， but these network models struggle to reconstruct images in a weak laser field. In the paper， a lightweight generative adversarial network model combined with a histogram specification algorithm is designed to reconstruct speckles in the weak laser field through MMF. Experimental results show that the reconstruction results of our algorithm have better metrics. Moreover， the model demonstrates excellent cross-domain generalization ability with regards to the Fashion-MNIST dataset. It is worth mentioning that we found that the speckles after inactivation still retain the ability to be reconstructed， which enhances the robustness of the model

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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

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 Lab Cluster and Grid Computing Lab School 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.

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Co-production of hydrogen, oxygen, and electricity via an integrated solar-driven system with decoupled water electrolyzer and Na-Zn ion battery

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Journal of Energy Chemistry 2025年第1期100卷 621-627页

作者： Fei Lv Longjie Liu Jiazhe Wu Pengfei Wang Lixia Pan Dengwei Jing Yubin Chen International research center for Renewable Energy State Key Laboratory of Multiphase Flow in Power Engineering Xi'an Jiaotong University

Combining water electrolysis and rechargeable battery technologies into a single system holds great promise for the co-production of hydrogen （H2） and ***,the design and development of such systems is still in its ***,an integrated hydrogen-oxygen （O2）-electricity co-production system featuring a bipolar membrane-assisted decoupled electrolyzer and a Na-Zn ion battery was established with sodium nickelhexacyanoferrate （NaNiHCF） and Zn2+/Zn as dual redox *** decoupled electrolyzer enables to produce H2and O2in different time and space with almost 100%Faradaic efficiency at 100 mA ***,the charged NaNiHCF and Zn electrodes after the electrolysis processes formed a Na-Zn ion battery,which can generate electricity with an average cell voltage of 1.75 V at 10 m A *** connecting Si photovoltaics with the modular electrochemical device,a well-matched solar driven system was built to convert the intermittent solar energy into hydrogen and electric energy with a solar to hydrogen-electricity efficiency of 16.7%,demonstrating the flexible storage and conversion of renewables.

关键词： Hydrogen Electricity Decoupled water electrolyzer Na-Zn ion battery Solar energy

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Broadband low-frequency sound absorption of multifunctional composite metastructure

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Science China Technological Sciences 2025年

作者： Yilong YANG Shanshan LIU Yan LI Tong GAO Yongdong PAN Yong LI Yabin JIN School of Aerospace engineering and Applied Mechanics Tongji University Institute of Acoustics School of Physics Science and Engineering Tongji University Shanghai Institute of Aircraft Mechanics and Control State International Joint research center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical University Shanghai Key Laboratory of intelligent sensing and Detection Technology School of Mechanical and Power Engineering East China University of Science and Technology

In this study, we fabricated multifunctional metastructures from carbon fiber-reinforced plastic composites using additive manufacturing technology. These metastructures are characterized by their lightweight, load-bearing capacity, and broadband low-frequency sound absorption properties. The metastructure consists of 36 unit cells, and non-local coupling mechanism was considered for designing the sound absorption performance. We developed an acoustic impedance theory tailored for the metastructure, facilitating an analysis of thermal and viscous dissipation mechanisms. It is proven theoretically and experimentally that the proposed composite metastructure can achieve a noise reduction with an average sound absorption coefficient greater than 0.9 across frequencies in the rage of 330–1500 Hz. We also studied the metastructure’s quasi-static and cyclic compression performance, confirming its efficient absorption capabilities after cyclic compression. The proposed design and additive manufacturing method for composite metastructures provides a novel pathway for creating lightweight, multifunctional structures with diverse applications, such as aerospace engineering.

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Self-assembled carbon monoxide nanoprodrug for chemiexcitationtriggered synergistic chemotherapy against breast cancer

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Science China Chemistry 2025年

作者： Shunfei Cui Yiyao Pan Chenzhe Ma Bin Qi Qingqiang Min Ming Li Huabing Chen Hengte Ke Xingyue Ji Jiangsu Province engineering research center of Precision Diagnostics and Therapeutics Development College of Pharmaceutical ScienceSoochow University

Carbon monoxide（CO） has recently been well-established as a promising therapeutic modality against cancer. The development of transition-metal-free and tumor-targeted delivery platforms for CO is highly demanded but remains very sporadic. Herein, we developed a polyprodrug system for the co-delivery of CO and a chemotherapeutic agent combretastin A-4（CA-4） to the tumor site based on a chemiexcitation mechanism. Such a poly-prodrug successfully achieved the co-activation of CO and CA-4 in response to H2O2at the tumor site both in vitro and in vivo. Importantly, a synergist effect between CO and CA-4 was observed in suppressing tumor growth in a mouse tumor model. It is anticipated that such a poly-prodrug system could be potentially adapted for the co-delivery of CO and another drug payload for combinational therapy for other indications.

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Enhanced solid-electrolyte interface efficiency for practically viable hydrogen-air fuel cell systems

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Journal of Energy Chemistry 2025年第1期100卷 356-368页

作者： Venkitesan Sakthivel Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering (BK21 FOUR) Hydrogen and Fuel Cell Research Center Jeonbuk National University Jeonju Department of Life Science Jeonbuk National University

Proton exchange membrane fuel cells （PEMFCs） provide an appealing sustainable energy system,with the solid-electrolyte membrane playing a crucial role in its overall ***,sulfonated poly（1,4-phenylene ether-ether sulfone）(SPEES),an aromatic hydrocarbon polymer,has garnered considerable attention as an alternative to Nafion ***,the long-term durability and stability of SPEES present a significant *** this context,we introduce a potential solution in the form of an additive,specifically a core–shell-based amine-functionalized iron titanate （A–Fe2TiO5）,which holds promise for improving the lifetime,proton conductivity,and power density of SPEES in *** modified SPEES/A–Fe2TiO5composite membranes exhibited notable characteristics,including high water uptake,enhanced thermomechanical stability,and oxidative ***,the SPEES membrane loaded with 1.2 wt%of A–Fe2TiO5demonstrates a maximum proton conductivity of 155 mS cm-1,a twofold increase compared to the SPEES membrane,at 80°C under 100%relative humidity （RH）.Furthermore,the 1.2 wt%of A–Fe2TiO5/SPEES composite membranes exhibited a maximum power density of 397.37 mW cm-2and a current density of 1148 mA cm-2at 60°C under 100%RH,with an opencircuit voltage decay of 0.05 m V/h during 103 h of continuous *** study offers significant insights into the development and understanding of innovative SPEES nanocomposite membranes for PEMFC applications.

关键词： Composite membranes

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Efficient photocatalytic reduction of CO2 to formate by a molecular noble metal-free system

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Science China Chemistry 2025年第1期 152-156页

作者： Lihua Zhang Lingjing Chen Huatian Shi Yue Wei Gui Chen Tai-Chu Lau School of Environment and Civil engineering Research Center for Eco-environmental Engineering Dongguan University of Technology Department of Chemistry and Institute of Molecular Functional Materials City University of Hong Kong

Reducing CO2to carbon-neutral solar fuels can not only alleviate the energy demand but also mitigate the greenhouse *** present,developing an efficient non-noble metal photo/electrocatalytic system for converting CO2to a specific product beyond CO is still a big ***,we report a new cobalt complex bearing 2,2′-bi-1,10-phenanthroline ligand that can photocatalytically reduce CO2to formate （HCOO-）.Turnover number （TON） for HCOO-up to 677 with 99%selectivity can be achieved using organic dyes purpurin as photosensitizer and 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzo[d]imidazole （BIH） as sacrificial reductant in a CO2-saturated NMP/TEA （v/v,3:1） solution under visible light *** potential electrolysis at-1.41 V （***/Ag Cl） in the presence of 12 m M Et3NHBF4also produced HCOO-with Faradaic efficiency of 39%.Spectroscopic and electrochemical studies suggest that a[CoI-H]species is the key intermediate for CO2reduction.

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Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

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Nano-Micro Letters 2025年第2期17卷 432-446页

作者： Hao Yin Yanting Li Zhiying Tian Qichao Li Chenhui Jiang Enfu Liang Yiping Guo State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Beijing Vacuum Electronics research Institute Beijing 100015People’s Republic of China Fundamental Science On Vibration Shock and Noise LaboratoryState Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing ***,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also ***,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic *** as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse *** ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate ***,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%*** structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

关键词： Flexible piezoelectric filaments Anisotropic Ultra-high sensitivity Structural health detection Texture recognition

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