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High-performance and multifunctional organic photovoltaic devices

Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第10期25卷 841-853页

作者： Yiming WANG Lijian ZUO State Key Laboratory of Silicon Materials Department of Polymer Science and EngineeringZhejiang UniversityHangzhou 310027China Zhejiang University-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 310014China

Organic photovoltaic devices(OPVs)are emerging as a promising renewable energy source for the *** unique advantages,such as semitransparency,light weight,superior flexibility,and low cost,enable a wide range of ***,compared to silicon-based photovoltaics,OPVs still face challenges for further improving their ***,there is a need to explore their potential of multi-functionality for practical application in various *** review summarizes the recent achievements in optimizing device performance and enhancing power-conversion efficiency,particularly via tuning the intermolecular interaction to reduce the electron-vibration coupling and non-radiative charge recombination(denoted as the“dilution effect”).Moreover,the representative development of ultra-thin Ag transparent electrode-based OPVs with multi-functional capabilities(such as semitransparency,flexibility,stretchability,and better aesthetics)has also been ***,this review aims to provide a broad landscape on the recent development of OPV and to unlock the full potential of OPVs.

关键词： Organic photovoltaic Multi-component Semitransparent Flexibility

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Impact of atmospheric circulations on droughts and drought propagation over China

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Science China Earth Sciences 2024年第8期67卷 2633-2648页

作者： Ziye GU Lei GU Jiabo YIN Wei FANG Lihua XIONG Jun GUO Ziyue ZENG Jun XIA School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Water Resources Engineering and Management Wuhan 430072China Changjiang River Scientific Research Institute Wuhan 430010China

The GRACE satellite mission provides a new approach for monitoring,tracking,and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage *** studies of terrestrial water storage anomalies related droughts paid rare attention to the behind atmospheric physical mechanisms,nor quantified the risk propagation patterns between terrestrial water storage deficits and hydrological or agricultural *** this study,we first extract terrestrial water storage(TWS) droughts,hydrological droughts,and agricultural droughts by using multiple variables including TWS from the GRACE/GRACE-FO satellites,runoff and soil moisture from the ERA5-Land reanalysis *** then identify key atmospheric and oceanic oscillation indices affecting water deficits by employing machine learning *** characterize the joint distributions between drought duration and severity by using the Copula function and quantify the risk propagation of hydrological and agricultural droughts to TWS *** results show that:(1) From 2002 to 2021,there is a significant decrasing trend of TWS in China;the WPIO group atmospheric circulation indices(sea surface temperature index within the Western Pacific and Indian Ocean) contributes the most to ***,the sea surface temperature anomalies within the NINO 3.4 region as well as the Western Pacific Warm Pool area index show significantly positive correlation relationships with TWS in southern China;(2) The northwestern China,the Yangtze River basin,and the downstream of the Pearl River basin are the hotspots of TWS ***,the hotspots of hydrological droughts locate in northwestern China and the hotspots of agricultural droughts locate in South China and eastern Tibetan Plateau;(3) The elastic coefficients of hydrological droughts propagating to TWS droughts are higher than those of agricultural droughts,indicating that the TWS droughts

关键词： GRACE satellites Drought Drought propagation Atmospheric circulation Copula function

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On the complete weight distributions of quantum error-correcting codes

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Chinese Physics B 2023年第5期32卷 272-287页

作者：杜超马智熊茂胜 State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenghzhou 450001China Henan Key Laboratory of Network Cryptography Technology Zhenghzhou 450001China Department of Mathematics Hong Kong University of Science and TechnologyHong KongChina

In a recent paper, Hu et al. defined the complete weight distributions of quantum codes and proved the Mac Williams identities, and as applications they showed how such weight distributions may be used to obtain the singleton-type and hamming-type bounds for asymmetric quantum codes. In this paper we extend their study much further and obtain several new results concerning the complete weight distributions of quantum codes and applications. In particular, we provide a new proof of the Mac Williams identities of the complete weight distributions of quantum codes. We obtain new information about the weight distributions of quantum MDS codes and the double weight distribution of asymmetric quantum MDS codes. We get new identities involving the complete weight distributions of two different quantum codes. We estimate the complete weight distributions of quantum codes under special conditions and show that quantum BCH codes by the Hermitian construction from primitive, narrow-sense BCH codes satisfy these conditions and hence these estimate applies.

关键词： quantum codes complete weight distributions Mac Williams identities BCH codes

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A model LayerDFN for characterizing the inherent anisotropic rocks with large-scale and dense joints

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Journal of Rock Mechanics and Geotechnical engineering 2025年第3期17卷 1569-1584页

作者： Gang Han Shuling Huang Chuanqing Zhang Xiuli Ding Yuting Zhang Yang Gao Jun He Key Laboratory of Geotechnical Mechanics and Engineering of the Ministry of Water Resources Changjiang River Scientific Research InstituteWuhan430010China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China University of Chinese Academy of Sciences Beijing101408China

Large-scale and heavily jointed rocks have inherent planes of anisotropy and secondary structural planes,such as dominant joint sets and random fractures,which result in significant differences in their failure mechanism and deformation behavior compared to other rock *** address this issue,inherent anisotropic rocks with large-scale and dense joints are considered to be composed of the rock matrix,inherent planes of anisotropy,and secondary structural *** a new implicit continuum model called LayerDFN is developed based on the crack tensor and damage tensor theories to characterize the mechanical properties of inherent anisotropic ***,the LayerDFN model is implemented in the FLAC3D software,and a series of numerical results for typical example problems is compared with those obtained from the 3DEC,the analytical solutions,similar classical models,laboratory uniaxial compression tests,and field rigid bearing plate *** results demonstrate that the LayerDFN model can effectively capture the anisotropic mechanical properties of inherent anisotropic rocks,and can quantitatively characterize the damaging effect of the secondary structural ***,the numerical method based on the LayerDFN model provides a comprehensive and reliable approach for describing and analyzing the behavior of inherent anisotropic rocks,which will provide valuable insights for engineering design and decision-making processes.

关键词： Inherent anisotropic rocks Secondary structural planes Constitutive model Crack tensor Damage tensor

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Cherenkov Radiation:A Stochastic Differential Model Driven by Brownian Motions

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Computer Modeling in engineering & Sciences 2023年第4期135卷 155-168页

作者： Qingqing Li Zhiwen Duan Dandan Yang School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan430074China

With the development of molecular imaging,Cherenkov optical imaging technology has been widely *** studies regard the partial boundary flux as a stochastic variable and reconstruct images based on the steadystate diffusion *** this paper,time-variable will be considered and the Cherenkov radiation emission process will be regarded as a stochastic *** on the original steady-state diffusion equation,we first propose a stochastic partial differential *** numerical solution to the stochastic partial differential model is carried out by using the finite element *** the time resolution is high enough,the numerical solution of the stochastic diffusion equation is better than the numerical solution of the steady-state diffusion equation,which may provide a new way to alleviate the problem of Cherenkov luminescent imaging *** addition,the process of generating Cerenkov and penetrating in vitro imaging of 18 F radionuclide inmuscle tissue are also first proposed by GEANT4Monte *** result of the GEANT4 simulation is compared with the numerical solution of the corresponding stochastic partial differential equations,which shows that the stochastic partial differential equation can simulate the corresponding process.

关键词： Cherenkov radiation stochastic partial differential equations numerical approximation and analysis GEANT4 Monte Carlo simulation

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TS-GGNN: Combining Graph and Sequence Features for Vulnerability Detection in Source Code 5

TS-GGNN: Combining Graph and Sequence Features for Vulnerabi...

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5th International Conference on Communications, Information System and Computer engineering, CISCE 2023

作者： Zhou, Xin Pang, Jianmin Zhang, Chunyan Yue, Feng Wang, Junchao Liu, Guangming State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798350326796

Software vulnerability detection is crucial for maintaining the security and stability of software systems. In this paper, we propose a novel neural network model called TS-GGNN to address the problem of vulnerability detection in source code slices. The TS-GGNN model effectively captures both local and global features of vulnerable code by fusing sequence features with graph features. To achieve this, we utilize graph structure and sequence structure learning approaches to comprehensively extract valuable information from the source code slices. Our experiments are conducted on the SARD dataset, which consists of 61,638 code samples annotated for the presence or absence of vulnerabilities. The results demonstrate that TS-GGNN has the best vulnerability detection performance, with an accuracy of 99.4%, a precision of 98.81%, and an F1 score as high as 99.4% thereby validating the effectiveness of the TS-GGNN model in capturing features relevant to software vulnerabilities. © 2023 IEEE.

关键词： Network coding

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Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the Department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： Communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

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ASYMPTOTICAL STABILITY OF NEUTRAL REACTION-DIFFUSION EQUATIONS WITH PCAS AND THEIR FINITE ELEMENT METHODS

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Acta Mathematica Scientia 2023年第4期43卷 1865-1880页

作者：韩豪张诚坚 School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China

This paper focuses on the analytical and numerical asymptotical stability of neutral reaction-diffusion equations with piecewise continuous ***,for the analytical solutions of the equations,we derive their expressions and asymptotical stability ***,for the semi-discrete and one-parameter fully-discrete finite element methods solving the above equations,we work out the sufficient conditions for assuring that the finite element solutions are asymptotically ***,with a typical example with numerical experiments,we illustrate the applicability of the obtained theoretical results.

关键词： neutral reaction-diffusion equations piecewise continuous arguments asymptotical stability finite element methods numerical experiment

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Research on Unpredetermined Behavior Recognition Techniques Based on Network Attacks 5

Research on Unpredetermined Behavior Recognition Techniques ...

引用

5th International Conference on Internet of Things, Automation and Artificial Intelligence, IoTAAI 2023

作者： Xiao, Yuxuan Fei, Jinlong Wang, Junyi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798400716485

With the increasing number of cyber-attack behaviors, it has caused great harm to the contemporary society. Currently, the cyber attack behavior recognition module is usually implemented by adopting a strategy based on rule-base matching, which often fails to identify the attack behaviors when faced with unpreset path attack behaviors of the actual attack process due to its reliance on predefined abnormal behavior patterns and attack labels. Therefore, this paper proposes an efficient and accurate unpreset behavior detection framework for cyber-attack behaviors, introduces machine learning techniques into the identification of unpreset attack behaviors, proposes an RF-Corr feature importance assessment method based on the Kendall correlation coefficient between features and the feature weight values, and designs an unpreset attack behavior identification method based on BiLSTM neural network, which improves the current effectiveness of identification and detection for unpresetted behavior of cyber attacks, and provides a solution for artificial intelligence detection of unpresetted behavior of cyber attacks. © 2023 ACM.

关键词： Crime

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Dynamic Resampling Based Boosting Random Forest for Network Anomaly Traffic Detection 36th

Dynamic Resampling Based Boosting Random Forest for Network...

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36th International Conference on Industrial, engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023

作者： Ren, Huajuan Wang, Ruimin Dong, Weiyu Li, Junhao Tang, Yonghe State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783031368219

Network anomaly traffic detection is an important technique for detecting intrusion activities and maintaining cyberspace security. Random forest is widely used in network anomalous traffic detection due to its good detection performance. However, Random Forest suffers from the insufficient ability to handle difficult samples and poor performance in dealing with imbalanced network traffic distribution. To address these two problems, a boosting random forest for network anomaly detection, called BRF, is proposed. The proposed method embeds the random forest model into Boosting training mechanism to enhance its classification ability for difficult samples. In the iterations, Random Forest is provided with relatively balanced and diverse training sets by dynamic resampling to alleviate the traffic imbalance problem. The effectiveness of BRF is demonstrated by multi-classification experiments on the NSL-KDD and UNSW-NB15 datasets. Compared with some shallow machine learning, deep learning, and ensemble learning methods, BRF has advantages in accuracy and time efficiency, which is a promising method for network anomaly detection. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anomaly detection

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