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Polymer Science & Technology 2025年第1期1卷 25-45页

作者： Jinyang Yu Shuixing Li Minmin Shi Haiming Zhu Hongzheng Chen State Key Laboratory of Silicon and Advanced Semiconductor Materials Department of Polymer Science and Engineering Zhejiang University Hangzhou 310058 China Zhejiang University-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200 China Department of Chemistry Zhejiang University Hangzhou 310058 China State Key Laboratory of Silicon and Advanced Semiconductor Materials Department of Polymer Science and Engineering Zhejiang University Hangzhou 310058 China；Zhejiang University-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200 China

As an emerging photovoltaic technology, organic solar cells (OSCs) have attracted extensive attention in recent years due to the advantages of light weight, flexibility, semi-transparency, and potential for roll-to-roll device fabrication. Currently, state-of-the-art OSCs have achieved over 20% power conversion efficiency (PCE), indicating their bright application prospects. Thus, stability becomes a critical issue for the commercialization of OSCs. In practical environments, light and heat are the main factors affecting the stability of OSCs. In this review, we first summarize the key degradation routes induced by thermal and light stresses. Then, recent strategies to enhance thermo- and photostability of OSCs are reviewed, focusing on material design and morphology control. Finally, some suggestions are provided for the development of next-generation OSCs with high efficiency and excellent stability.

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Correction to: Optimal Error Estimates for Gegenbauer Approximations in Fractional Spaces

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Journal of scientific computing 2025年第2期103卷 1-2页

作者： Xie, Ruiyi Liu, Wenjie Wang, Haiyong Wu, Boying School of Mathematics Harbin Institute of Technology Harbin People’s Republic of China Key Laboratory of Computing and Stochastic Mathematics Ministry of Education (LCSM) Changsha People’s Republic of China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan People’s Republic of China China and Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan People’s Republic of China

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An investigation of scouring mechanism and equilibrium state by the submerged jet using synthesized oblique velocity

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Ocean engineering 2025年 316卷

作者： Hu, Xiguang Chen, Zhida Yang, Xing Li, Linglong Wu, Defa Ma, Yunxiang Liu, Yinshui State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China China Ship Scientific Research Center Wuxi214082 China

This paper uses a numerical simulation method based on synthesized oblique velocity to simulate the process of submerged oblique jet scouring of the sand bed. The concept of the initial scouring equilibrium state is introduced, and curves showing the variation of scour hole depth over time at varying angles are fitted based on experimental data. This enables predicting the scour hole depth at any point during the scouring process and the time required to reach the initial scouring equilibrium state. An ultrasonic displacement sensor was used to measure the depth and width of the scour holes accurately. The evolution of the scour holes formed by the submerged oblique jet on the sand bed was systematically studied within the range of oblique angles from θ = 30°–80°. The flow structure during the scouring process and its interaction with sediment movement were further revealed through numerical simulations. The synthesized oblique velocity method effectively addresses the complexity of simulating the oblique jet. This provides a new approach to investigating the submerged oblique jet scouring of the sand bed. The findings of this study offer valuable guidance for practical applications, such as underwater equipment cleaning and deep-sea dredging. © 2024 Elsevier Ltd

关键词： Scour

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Passive on-chip isolators based on the thin-film lithium niobate platform

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Chinese Physics B 2025年第3期34卷 408-413页

作者： Jiacheng Liu Gongyu Xia Qilin Hong Pingyu Zhu Kai-Kai Zhang keyu Xia Ping Xu Shiqiao Qin Zhihong Zhu College of Advanced Interdisciplinary Studies&Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Institute for Quantum Information and State Key Laboratory of High-Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Engineering and Applied Sciences National Laboratory of Solid State Microstructuresand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China

Optical isolators,the photonic analogs of electronic diodes,are essential for ensuring the unidirectional flow of light in optical systems,thereby mitigating the destabilizing effects of back ***-film lithium niobate(TFLN),hailed as“the silicon of photonics,”has emerged as a pivotal material in the realm of chip-scale nonlinear optics,propelling the demand for compact optical *** report a breakthrough in the development of a fully passive,integrated optical isolator on the TFLN platform,leveraging the Kerr effect to achieve an impressive 10.3 dB of isolation with a minimal insertion loss of 1.87 *** theoretical simulations have demonstrated that our design,when applied to a microring resonator with a Q factor of 5×10^(6),can achieve 20 dB of isolation with an input power of merely 8 *** advancement underscores the immense potential of lithium niobate-based Kerr-effect isolators in propelling the integration and application of high-performance on-chip lasers,heralding a new era in integrated photonics.

关键词： thin-film lithium niobate Kerr effect optical isolator

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Propagation of the effect of upstream bend circulations to downstream flow and sediment transport in consecutive river bends

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Journal of Hydrology 2025年 660卷

作者： He, Xin Yu, Minghui Wang, Kaixuan Liu, Yujiao State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan China Changjiang River Scientific Research Institute Wuhan China

Despite their critical role in shaping meandering rivers, the hydraulics, sediment transport, and the interplay of consecutive bends remain inadequately understood, hindering our full comprehension of fluvial processes and river evolution. A numerical approach, employing the RNG k-Ε model, is used to investigate the flow and sediment transport in a downstream bend (135°) affected by residual circulations (RC) from an upstream reverse bend (90°). Results reveal the mechanism of RC altering the flow and sediment transport in the downstream bend. Compared with a single bend, RC results in a shift of the high streamwise velocity zone to the inner bank in the downstream bend. The presence of a connected upstream bend substantially increases the maximum values of bed shear stress, sediment transport capacity, and the Darcy–Weisbach friction coefficient in the downstream bend. Besides, the rate of increase shows a positive relationship with the strength of RC, which decreases as the transition length increases. Moreover, the locations of the maximum bed shear stress and the maximum sediment transport capacity at the cross-section are closer to the inner bank (up to 0.25B). Further analysis of the influence of water depth reveals that the above effects of RC on bed shear stress are more pronounced at lower water depths. These effects of RC can promote the occurrence of shore cutting and the formation of outer bank benches in the downstream bend. The findings of this study will contribute to a better understanding of sediment transport and channel evolution in consecutive bends, and provide valuable insights for meandering river management. © 2025

关键词： Shear stress

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Towards Event Extraction with Massive Types: LLM-based Collaborative Annotation and Partitioning Extraction

arXiv

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arXiv 2025年

作者： Liu, Wenxuan Li, Zixuan Bai, Long Zuo, Yuxin Xu, Daozhu Jin, Xiaolong Guo, Jiafeng Cheng, Xueqi School of Computer Science and Technology University of Chinese Academy of Sciences China Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Geo-Information Engineering Shaanxi Xi’an China

Developing a general-purpose extraction system that can extract events with massive types is a long-standing target in Event Extraction (EE). In doing so, the challenge comes from two aspects: 1) The absence of an efficient and effective annotation method. 2) The absence of a powerful extraction method can handle massive types. For the first challenge, we propose a collaborative annotation method based on Large Language Models (LLMs). Through collaboration among multiple LLMs, it first refines annotations of trigger words from distant supervision and then carries out argument annotation. Next, a voting phase consolidates the annotation preferences across different LLMs. Finally, we create the EEMT dataset, the largest EE dataset to date, featuring over 200,000 samples, 3,465 event types, and 6,297 role types. For the second challenge, we propose an LLM-based Partitioning EE method called LLM-PEE. To overcome the limited context length of LLMs, LLM-PEE first recalls candidate event types and then splits them into multiple partitions for LLMs to extract events. The results in the supervised setting show that LLM-PEE outperforms the state-of-the-art methods by 5.4% in event detection and 6.1% in argument extraction. In the zero-shot setting, LLM-PEE achieves up to 12.9% improvement compared to mainstream LLMs, demonstrating its strong generalization capabilities. Copyright © 2025, The Authors. All rights reserved.

关键词： Large datasets

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Global method for monotone variational inequality problems on polyhedral sets

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OPTIMIZATION METHODS & SOFTWARE 1997年第2期7卷 111-122页

作者： Peng, JM [a] State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific Computing Beijing China

In this paper, we consider the optimization method for monotone variational inequality problems on polyhedral sets. First, we consider the mixed complementarity problem based on the original problem. Then, a merit function for the mixed complementarity problem is proposed and some desirable properties of the merit function are obtained. Under certain assumptions: we show that any stationary point of the merit function is a solution of the original problem. A descent method for the optimization problem is proposed and the global convergence of the method is shown.

关键词： variational inequality problem mixed complementarity problem optimization method

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Movable Antenna-Assisted Integrated Sensing and Communication Systems

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IEEE Transactions on Wireless Communications 2025年

作者： Jiang, Chengjun Zhang, Chensi Huang, Chongwen Ge, Jianhua Niyato, Dusit Yuen, Chau Xidian University State Key Lab. of Integrated Service Networks Xi’an China Zhejiang University College of Information Science and Electronic Engineering China Xidian University State Key Laboratory of Integrated Service Networks China Zhejiang Provincial Key Laboratory of Info. Proc China Nanyang Technological University College of Computing and Data Science Singapore Nanyang Technological University School of Electrical and Electronics Engineering Singapore

Movable antennas (MAs) enhance flexibility in beamforming gain and interference suppression by adjusting position within certain areas of the transceivers. In this paper, we propose an MA-assisted integrated sensing and communication framework, wherein MAs are deployed for reconfiguring the channel array responses at both the receiver and transmitter of a base station. Then, we develop an optimization framework aimed at maximizing the sensing signal-to-interference-plus-noise-ratio (SINR) by jointly optimizing the receive beamforming vector, the transmit beamforming matrix, and the positions of MAs while meeting the minimum SINR requirement for each user. To address this nonconvex problem involving complex coupled variables, we devise an alternating optimization-based algorithm that incorporates techniques including the Charnes-Cooper transform, second-order Taylor expansion, and successive convex approximation (SCA). Specifically, the closed form of the received vector and the optimal transmit matrix can be first obtained in each iteration. Subsequently, the solutions for the positions of the transmit and receive MAs are obtained using the SCA method based on the second-order Taylor expansion. The simulation results show that the proposed scheme has significant advantages over the other baseline schemes. In particular, the proposed scheme has the ability to match the performance of the fixed position antenna scheme while utilizing fewer resources. © 2002-2012 IEEE.

关键词： Signal to noise ratio

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Minimizing transformer inference overhead using controlling element on Shenwei AI accelerator

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Frontiers of Information Technology & Electronic engineering 2025年第4期26卷 605-622页

作者： Zhao, Yulong Wu, Chunzhi Wang, Yizhuo Zhang, Lufei Zhang, Yaguang Shen, Wenyuan Fan, Hao Fang, Hankang Qin, Yi Liu, Xin State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China School of Non-Commissioned Officer Space Engineering University Beijing China National Supercomputing Center in Wuxi Wuxi China Zhejiang Lab Hangzhou China National Research Centre of Parallel Computer Engineering and Technology Beijing China

Transformer models have become a cornerstone of various natural language processing (NLP) tasks. However, the substantial computational overhead during the inference remains a significant challenge, limiting their deployment in practical applications. In this study, we address this challenge by minimizing the inference overhead in transformer models using the controlling element on artificial intelligence (AI) accelerators. Our work is anchored by four key contributions. First, we conduct a comprehensive analysis of the overhead composition within the transformer inference process, identifying the primary bottlenecks. Second, we leverage the management processing element (MPE) of the Shenwei AI (SWAI) accelerator, implementing a three-tier scheduling framework that significantly reduces the number of host-device launches to approximately 1/10 000 of the original PyTorch-GPU setup. Third, we introduce a zero-copy memory management technique using segment-page fusion, which significantly reduces memory access latency and improves overall inference efficiency. Finally, we develop a fast model loading method that eliminates redundant computations during model verification and initialization, reducing the total loading time for large models from 22 128.31 ms to 1041.72 ms. Our contributions significantly enhance the optimization of transformer models, enabling more efficient and expedited inference processes on AI accelerators.

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GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

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Computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

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