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Understanding the correlation between energy-state mismatching and open-circuit voltage loss in bulk heterojunction solar cells

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Carbon Energy 2024年第5期6卷 164-174页

作者： Hyun-Seock Yang Danbi Kim Chang-Mok Oh Vellaiappillai Tamilavan Pesi MHangoma Hojun Yi bo rlee Insoo Shin In-Wook Hwang Sung Heum Park Pukyong National University BusanRepublic of Korea Clarendon Laboratory University of OxfordOxfordUK Institute of Energy Transport and Fusion Research Pukyong National UniversityBusanRepublic of Korea Advanced Photonics Research Institute Gwangju Institute of Science and TechnologyGwangjuRepublic of Korea Department of Chemical and Biomolecular Engineering Tandon School of EngineeringNew York UniversityBrooklynNew YorkUSA

Photoinduced intermolecular charge transfer(PICT)determines the voltage loss in bulk heterojunction(BHJ)organic photovoltaics(OPVs),and this voltage loss can be minimized by inducing efficient PICT,which requires energy-state matching between the donor and acceptor at the BHJ ***,both geometrically and energetically accessible delocalized state matching at the hot energy level is crucial for achieving efficient *** this study,an effective method for quantifying the hot state matching of OPVs was *** degree of energy-state matching between the electron donor and acceptor at BHJ interfaces was quantified using a mismatching factor(MF)calculated from the modified optical density of the ***,the correlation between the open-circuit voltage(Voc)of the OPV device and energy-state matching at the BHJ interface was investigated using the calculated *** OPVs with small absolute MF values exhibited high Voc *** result clearly indicates that the energy-state matching between the donor and acceptor is crucial for achieving a high Voc in *** the MF indicates the degree of energy-state matching,which is a critical factor for suppressing energy loss,it can be used to estimate the Voc loss in OPVs.

关键词： bulk heterojunction open circuit voltage organic photovoltaics photoinduced charge transfer voltage loss

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Traffic safety helmet wear detection based on improved YOLOv5 network

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Optoelectronics Letters 2025年第1期21卷 35-42页

作者： GUI Dongdong SUN bo College of Software Southeast University Quanzhou Equipment Research Centre Haixi Institute Chinese Academy of Sciences

Aiming at the problem that the current traffic safety helmet detection model can't balance the accuracy of detection with the size of the model and the poor generalization of the model, a method based on improving you only look once version 5(YOLOv5) is proposed. By incorporating the lightweight Ghost Net module into the YOLOv5 backbone network, we effectively reduce the model size. The addition of the receptive fields block(RFB) module enhances feature extraction and improves the feature acquisition capability of the lightweight model. Subsequently, the high-performance lightweight convolution, GSConv, is integrated into the neck structure for further model size compression. Moreover, the baseline model's loss function is substituted with efficient insertion over union(EIoU), accelerating network convergence and enhancing detection precision. Experimental results corroborate the effectiveness of this improved algorithm in real-world traffic scenarios.

关键词： Traffic control

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Sky location of massive black hole binaries in the foreground of Galactic white dwarf binaries

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 97-108页

作者： Pan Guo Hong-bo Jin Cong-Feng Qiao Yue-Liang Wu The International Centre for Theoretical Physics Asia-Pacific University of Chinese Academy of Sciences The School of Physical Sciences University of Chinese Academy of Sciences Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University National Astronomical Observatories Chinese Academy of Sciences Institute of Theoretical Physics Chinese Academy of Sciences

For space-based gravitational wave （GW） detection,the main noise source for massive black hole binaries （MBHBs） is attributed to approximately 10～7double white dwarf binaries in the *** a GW source,the amplitude of the detector response,recorded by a space-based gravitational wave detector,exhibits a modulation effect with a year period when observing the source from various orbital *** the adverse conditions mentioned above,where there is a strong foreground noise and annual modulation in the signals,we employed the wavelet transform and the strong-amplitude relevant orbital position search methods,which allows the weak MBHB sources to achieve higher locating *** detail,for two MBHB sources of lower intensity,the precision of luminosity distance,represented by the ratio ?DL/DLat the 95%confidence level,is enhanced by factors of ～*** angular resolutions,denoted by??s,are enhanced by a factor of ～*** improvements increase the number of detectable GW sources,facilitate multi-messenger follow-up observations and provide constraints on the cosmological constant.

关键词： space-based gravitational wave detection gravitational waves massive black hole binaries

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FK506 contributes to peripheral nerve regeneration by inhibiting neuroinflammatory responses and promoting neuron survival

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Neural Regeneration Research 2025年第7期20卷 2108-2115页

作者： Yuhui Kou Zongxue Jin Yusong Yuan bo Ma Wenyong Xie Na Han Department of Trauma and Orthopedics Peking University People’s HospitalBeijingChina National Center for Trauma Medicine Peking University People’s HospitalBeijingChina Key Laboratory of Trauma and Neural Regeneration(Peking University) Ministry of EducationBeijingChina Trauma Medicine Center Peking University People’s HospitalBeijingChina Department of Orthopedics China-Japan Friendship HospitalBeijingChina

FK506(Tacrolimus)is a systemic immunosuppressant approved by the *** and Drug ***506 has been shown to promote peripheral nerve regeneration,however,its precise mechanism of action and its pathways remain *** this study,we established a rat model of sciatic nerve injury and found that FK506 improved the morphology of the injured sciatic nerve,increased the numbers of motor and sensory neurons,reduced inflammatory responses,markedly improved the conduction function of the injured nerve,and promoted motor function *** findings suggest that FK506 promotes peripheral nerve structure recovery and functional regeneration by reducing the intensity of inflammation after neuronal injury and increasing the number of surviving neurons.

关键词： FK506 inflammation motor neurons nerve regeneration neuron peripheral nerve injury sensory neurons

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Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(Dbo)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with Dbo show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original Dbo,the R and RPD of models with the improved Dbo increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

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Anomaly monitoring and early warning of electric moped charging device with infrared image

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Optoelectronics Letters 2025年第3期 136-141页

作者： LI Jiamin HAN bo JIANG Mingshun School of Control Science and Engineering Shandong University

Potential high-temperature risks exist in heat-prone components of electric moped charging devices, such as sockets,interfaces, and controllers. Traditional detection methods have limitations in terms of real-time performance and monitoring scope. To address this, a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image, then applying an image segmentation algorithm to divide the image.

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数字公共性:数字乡村治理共同体的建构逻辑与优化路径

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西北农林科技大学学报（社会科学版） 2025年第1期25卷 10-16页

作者：丁波安徽大学社会与政治学院合肥230039

数字乡村建设以数字技术嵌入乡村社会,改变乡村社会的结构特征与治理模式,重构乡村治理共同体,形成具有数字公共性特征的数字乡村治理共同体。数字乡村治理共同体以数字主体、数字空间和数字场景的建构逻辑,培育数字参与理念、构建数字... 详细信息

数字乡村建设以数字技术嵌入乡村社会,改变乡村社会的结构特征与治理模式,重构乡村治理共同体,形成具有数字公共性特征的数字乡村治理共同体。数字乡村治理共同体以数字主体、数字空间和数字场景的建构逻辑,培育数字参与理念、构建数字联结纽带、搭建数字交往平台,实现数字公共性生产。数字乡村治理共同体通过治理主体的行动共建、治理方式的技术共治、治理资源的利益共享,推动乡村治理的数字赋权、数字赋能、数字赋利,有助于构建人人有责、人人尽责、人人享有的数字乡村治理共同体。

关键词：数字乡村建设数字公共性乡村治理数字乡村治理共同体

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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ICA-Net: improving class activation for weakly supervised semantic segmentation via joint contrastive and simulation learning

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Optoelectronics Letters 2025年第3期 188-192页

作者： YE Zhuang LIU Ruyu SUN bo School of Information Engineering Chengdu Aviation Vocational and Technical College School of Computer Science and Engineering Hangzhou Normal University Quanzhou Institute of Equipment Manufacturing Haixi Institutes Chinese Academy of Sciences

In the field of optoelectronics, certain types of data may be difficult to accurately annotate, such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges. Weakly supervised learning can provide a more reliable approach in these situations. Current popular approaches mainly adopt the classification-based class activation maps (CAM) as initial pseudo labels to solve the task.

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