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Constructing 2D bismuth-based heterostructure for highly efficient photocatalytic CO2 reduction

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Tungsten 2025年第1期7卷 71-79页

作者： Ruo-Hang Xu Hao-Yu Jiang Dan-Dan Cui Kun-Rong Du Hong-Run Zhang Sheng-Jie Xu Ya-Qi Li Zhi-Zhen Ren Liang Wang Wei-Chang Hao Yi Du School of Physics and BUAA-UOW Joint Research Centre Beihang University Shenzhen institute of Beihang University Centre for Catalysis and Clean Energy School of Environment and Science Griffith University

Reforming carbon dioxide（CO2） into fuels and valuable chemicals using solar energy holds significant potential for emission reduction and addressing energy supply *** recombination of photocarriers remains a major obstacle,however,to enhancing solar energy conversion efficiency in the photocatalytic reaction *** two-dimensional materials,constructing heterogeneous structures has emerged as an effective strategy to enhance the separation of photoexcited carriers by leveraging the internal electric field at the heterogeneous ***,we present a facile strategy for preparing Bi4NbO8Br/Bi2WO6plate-on-plate Z-scheme junctions with a strong internal electric field by in situ *** unique heterostructure facilitates efficient separation and transport of photoexcited charges by harnessing the internal electric field induced by chemical bonding at the lateral ***,the Bi4NbO8Br/Bi2WO6heterostructure exhibits enhanced CO2photoreduction properties,along with a CO yield rate of approximately 35 μmol·g-1·h-1under full light *** work offers novel insights into the synthesis of unique hetero structures intended to enhance the efficiency of photocatalytic CO2reduction.

关键词： Bi4NbO8Br/Bi2WO6 CO2 reduction Heterostructures Photocatalysts

Subnetwork-based federated few-shot semantic segmentation of organ images

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Optoelectronics Letters 2025年

作者： Wu Junpeng Zhao Meng Zhang Huanping Key Laboratory of Computer Vision and system of Ministry of Education， School of Computer science and Engineering， Tianjin University of Technology

Federated learning(FL)， as a distributed learning paradigm， allows multiple medical institutions to collaborate on learning without the need to centralize all client data. However， existing methods pay little attention to more challenging medical image semantic segmentation tasks， especially in the scenario of the imbalanced dataset in federated few-shot learning. In this paper， we propose a subnetwork-based federated few-shot organ image segmentation method. Firstly， individual clients train using local training samples and then upload local model gradients to the server. The server utilizes their respective local model gradients to update the subnetwork maintained on the server and generate aggregation weights for forming personalized model parameters. Through this method， we can learn the similarities between different clients to address data heterogeneity issues. In addition， to enhance the communication efficiency between clients and the server， we have also designed a personalized layer aggregation strategy， which only transmits partial layer model parameters during the communication process to improve communication efficiency. Finally， we conducted experiments on ABD-MRI and ABD-CT datasets to demonstrate the effectiveness of our method.

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Multifunctional Nacre‑Like Nanocomposite Papers for Electromagnetic Interference Shielding via Heterocyclic Aramid/MXene Template‑Assisted In‑Situ Polypyrrole Assembly

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Nano-Micro Letters 2025年第3期17卷 37-54页

作者： Jinhua Xiong Xu Zhao Zonglin Liu He Chen Qian Yan Huanxin Lian Yunxiang Chen Qingyu Peng Xiaodong He National Key Laboratory of science and Technology On Advanced Composites in Special Environments Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbin 150080People’s Republic of China

Robust, ultra-flexible, and multifunctional MXene-basedelectromagnetic interference (EMI) shielding nanocomposite filmsexhibit enormous potential for applications in artificial intelligence,wireless telecommunication, and portable/wearable electronic *** this work, a nacre-inspired multifunctional heterocyclic aramid(HA)/MXene@polypyrrole (PPy) (HMP) nanocomposite paper withlarge-scale, high strength, super toughness, and excellent tolerance tocomplex conditions is fabricated through the strategy of HA/MXenehydrogel template-assisted in-situ assembly of PPy. Benefiting from the"brick-and-mortar" layered structure and the strong hydrogen-bondinginteractions among MXene, HA, and PPy, the paper exhibits remarkable mechanical performances, including high tensile strength (309.7 MPa),outstanding toughness (57.6 MJ m−3), exceptional foldability, and structural stability against ultrasonication. By using the template effect ofHA/MXene to guide the assembly of conductive polymers, the synthesized paper obtains excellent electronic conductivity. More importantly,the highly continuous conductive path enables the nanocomposite paper to achieve a splendid EMI shielding effectiveness (EMI SE) of 54.1 dBat an ultra-thin thickness (25.4 μm) and a high specific EMI SE of 17,204.7 dB cm2g−1. In addition, the papers also have excellent applicationsin electromagnetic protection, electro-/photothermal de-icing, thermal therapy, and fire safety. These findings broaden the ideas for developinghigh-performance and multifunctional MXene-based films with enormous application potential in EMI shielding and thermal management.

关键词： MXene Remarkable mechanical properties Heterocyclic aramid Electromagnetic interference shielding Polypyrrole Multifunctionality

Force and impulse multi-sensor based on flexible gate dielectric field effect transistor

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 214-220页

作者： Chao Tan Junling Lü Chunchi Zhang Dong Liang Lei Yang Zegao Wang College of Materials science and Engineering Sichuan UniversityChengdu 610065China The 54th Research institute of China Electronics Technology Group Corporation Shijiazhuang 050081China

Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other ***-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate ***,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of *** we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor *** systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 *** sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on ***,there was almost no performance loss for the device as left in the air for two months.

关键词： flexible gate dielectric transistor force sensor impulse sensor force sensor array

Domain generalization with semi-supervised learning for people-centric activity recognition

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science China(Information sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research institute on Networking systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Boosting Photocatalytic Performance of Cu-Mn Co-doped CeO_(2) Nanoparticles for Tetracycline Degradation

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Journal of Wuhan University of Technology(Materials science) 2025年第1期40卷 42-48页

作者： XU Rongqi MI Jianxin WANG Shulin XU Man ZHU Li BAI Lei TANG Dandan LEI Yu Engineering Research Center of Environmental Materials and Membrane Technology of Hubei Province School of Materials Science and EngineeringWuhan Institute of TechnologyWuhan 430205China Shaanxi Coal Chemical Industry Technology Research institute Co. Ltd.Xi’an 710100China

Cu-Mn co-doped CeO_(2) photocatalyst was successfully synthesized by the sol-gel method to assess its capability in degrading *** and TEM results showed that Cu and Mn were successfully co-doped into CeO_(2) without forming heterostructure,XPS and photoelectrochemical results revealed that Mn ions doping amplified the generation of photo-induced charge carriers,while Cu ions doping significantly facilitated the interfacial charge transfer ***,the optimized Cu3Mn2CeO_(2) nanoparticles exhibited the highest TC removal efficiency,achieved a rate of 78.18%and maintained a stable cycling performance.

关键词： photocatalyst co-doped charge separation water treatment

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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Wave effect of gravitational waves intersected with a microlens field Ⅱ:An adaptive hierarchical tree algorithm and population study

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science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 241-254页

作者： Xikai Shan Guoliang Li Xuechun Chen Wen Zhao Bin Hu Shude Mao Department of Astronomy Tsinghua University Purple Mountain Observatory Chinese Academy of Sciences institute for Frontier in Astronomy and Astrophysics Beijing Normal University School of Physics and Astronomy Beijing Normal University School of Astronomy and Space science University of Science and Technology of China CAS Key Laboratory for Researches in Galaxies and Cosmology Department of Astronomy University of Science and Technology of ChinaChinese Academy of Sciences

The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves （SLGWs）.This effect presents both challenges and opportunities for the detection and application of ***,investigating this wave effect requires computing a complete diffraction integral over each microlens in the *** is extremely time-consuming due to the large number of microlenses （10～3-10～6）.Therefore,simply adding all the microlenses is ***,the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical *** this paper,we propose a trapezoid approximation-based adaptive hierarchical tree algorithm to meet the challenges of calculation speed and *** find that this algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical tree algorithm proposed for electromagnetic *** importantly,our algorithm ensures controllable numerical errors,increasing confidence in the *** with our previous work （***.66,239511,2023）,this paper addresses all numerical issues,including integral convergence,precision,and computational time1).Finally,we conducted a population study on the microlensing wave effect of SLGWs using this algorithm and found that the microlensing wave effect cannot be ignored,especially for Type II SLGWs （from saddle position of the time delay surface） due to their intrinsic geometric structures and their typical intersection with a denser microlensing ***,more than 33%（11%） of SLGWs have a mismatch larger than 1%（3%） compared to the unlensed ***,we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10-3,and 61%（25%） of signal pairs have a mismatch larger than 1%（3%）.Therefo

关键词： gravitational lensing diffractional integral algorithm gravitational wave

Boundary Control for a Class of Reaction-diffusion systems

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International Journal of Automation and computing 2018年第1期15卷 94-102页

作者： Yuan-Chao Si Cheng-Kang Xie Na Zhao School of mathematics and system science Southwest University School of mathematics and system science Guizhou University

Boundary control for a class of partial integro-differential systems with space and time dependent coefficients is consid- ered. A control law is derived via the partial differential equation （PDE） backstepping. The existence of kernel equations is proved. Exponential stability of the closed-loop system is achieved. Simulation results are presented through figures.

关键词： Stability reaction-diffusion system boundary control backstepping partial differential equation.