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Absorptive Nonlinearity in Er-Doped Optical Fiber

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Wuhan University Journal of Natural Sciences 1999年第2期4卷 56-59页

作者： Song, Qian li, ji-xing Zhang, Yuan-cheng Wuhan Univ Wuhan China

Optical absorptive nonlinearity in Er doped optical fiber has been discussed and measured at the window wavelength 1.55 μm for optical communications firstly. It is proposed that the mechanism of this absorptive nonlinearity is the induced absorption. The first order nonlinear absorptive coefficient and the imaginary part and the complex value of the third order susceptibility at that wavelength are obtained from the measured absorptive nonlinearity.

关键词： optical nonlinearity Er doped fiber optical absorption

Robust Delay-dependent H∞ Consensus Control for Multi-agent Systems with Input Delays

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自动化学报 2014年第11期40卷 2556-2562页

作者： li Zhen-xing ji Hai-Bo Department of Automation University of Science and Technology of China Hefei 230027 China

This paper investigates the consensus control for multi-agent systems subject to external disturbances, input delays and model uncertainties of networks. By defining an appropriate controlled output, we transform this question into a robust H_∞ control problem. Then, we give two criteria to judge the consensusability of closed-loop multi-agent systems and present a cone-complementary linearization algorithm to get the state feedback controller's parameters. Finally, numerical examples are given to show the effectiveness of the proposed consensus protocols.

关键词：多代理系统控制输出时滞相关延迟输入状态反馈控制器线性化算法不确定性

Distributed optimal consensus control for multiagent systems based on event-triggered and prioritized experience replay strategies

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Science China(Information Sciences) 2025年第1期68卷 306-321页

作者： Cuijuan ZHANG lianghao ji Shasha YANG xing GUO Huaqing li Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University College of Electronic and Information Engineering Southwest University

This study uses event-triggered(ET) and reinforcement learning methods to investigate the optimal consensus control problem for cooperative-competitive multiagent systems. It proposes a novel distributed ET control strategy, which relies on a prioritized experience replay(PER) policy. This strategy not only conserves communication resources but also ensures acceptable system performance. To implement the proposed method, actor-critic(AC) dual-structured neural networks(NNs) are used to approximate the value function and control policy. In the AC NNs, the weight estimates for the NNs are updated at the moment of event triggering, resulting in a nonperiodic weight adjustment pattern. This approach decreases the computational cost in comparison with the traditional ET mechanism. The PER-based ET mechanism makes full use of valid historical data and effectively establishes a balance between system performance and communication resource ***, it does not require the following two conditions in most existing studies:(1) requirement of the system dynamics model to be known, and(2) persistent excitation. In addition, Zeno behavior is excluded from this study. Finally, a simulation is conducted to confirm the validity of the suggested approach.

关键词： multiagent systems event-triggered mechanism prioritized experience replay dual-structured neural networks optimal consensus control

Rapid Modeling and Finite Element Analysis of Missile Stiffener

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Computer Aided Drafting,Design and Manufacturing 2015年第3期25卷 31-38页

作者： WANG Tian XI Ping li ji-xing School of Mechanical Engineering and Automation Beihang University

Stiffener is the important missile structure to ensure the structural strength of the missile. In order to improve the design efficiency and the quality of the missile stiffener, the methods of missile stiffener rapid modeling and analysis are proposed. First, the problems of traditional manual modeling of the stiffener are analyzed. According to the problems and actual requirement of modeling, volume decomposition method is used to divide the stiffener into the upper section, the lower section and the web in order for feature analysis and parameter extraction. Then based on the parameters the basic unit decomposed above is created for Boolean operation to establish the stiffener. Finally, a rapid stiffener modeling and analysis program were developed based on UG Open API, the modeling and analysis result validates the feasibility of the method.

关键词： rapid modeling stiffener finite element analysis UG open API

Exploring the potential of extrachromosomal DNA as a novel oncogenic driver

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Science China life Sciences 2025年第1期68卷 144-157页

作者： Huanbo Zhu Longtao Huangfu Junbing Chen jiafu ji Xiaofang xing Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing) Division of Gastrointestinal Cancer Translational Research LaboratoryPeking University Cancer Hospital & Institute Department of Gastrointestinal Cancer Center Peking University Cancer Hospital & Institute Department of liver Surgery & Transplantation Liver Cancer InstituteZhongshan HospitalFudan University Key Laboratory of Carcinogenesis and Cancer Invasion Ministry of Education State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers Beijing Key Laboratory of Carcinogenesis and Translational ResearchDivision of Gastrointestinal Cancer Translational Research LaboratoryPeking University Cancer Hospital & Institute

Extrachromosomal DNA(ecDNA) is a form of circular DNA mostly found in tumor cells. Unlike the typical chromosomal DNA, ecDNA is circular, self-replicating, and carries complete or partial gene fragments. Although ecDNA occurrence remains a rare event in cancer, recent studies have shown that oncogene amplification on ecDNA is widespread throughout many types of cancer, implying that ecDNA plays a central role in accelerating tumor evolution. ecDNA has also been associated with increased tumor mutation burden, chromosomal instability, and even tumor microenvironment remodeling. ecDNA may be crucial in influencing tumor heterogeneity, drug sensitivity,oncogenic senescence, and tumor immunogenicity, leading to a worsening prognosis for tumor patients. In this way, several clinical trials have been conducted to investigate the importance of ecDNA in clinical treatment. In this review, we summarize the biogenesis, characteristics, and current research methods of ecDNA, discuss the vital role of ecDNA-caused tumor heterogeneity in cancers, and highlight the potential role of ecDNA in cancer therapy.

关键词： extrachromosomal DNA cancer therapy tumor heterogeneity drug resistance tumor evolution

Manufacture the conducting polymer with light

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Science China Chemistry 2025年第1期68卷 8-9页

作者： Yang li Tianyu li Yan ji Baoguang liu College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology) Nanjing University of Posts & Telecommunications

Poly(3,4-ethylenedioxythiophene) (PEDOT), heralded as the “king” of conducting polymers, is esteemed in bioelectronics for its mixed electronic and ionic conductivity, mechanical properties compatible with biological tissues, tunable healing ability and stability in diverse environments [1]. Based on additive manufacturing of three-dimensional structures,PEDOT realizes the implementation in the efficient production of flexible bioelectronics, the construction of intricate electrode-neural implantations, and the development of smart brain-computer-interfaces [2].

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A Turbine Blade Parametric Modeling Method Considering 1-D Heat Transfer Analysis

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Computer Aided Drafting,Design and Manufacturing 2015年第3期25卷 1-9页

作者： li ji-xing XI Ping GUO Yan-fei ZHANG jian-qi School of Mechanical Engineering and Automation Beihang University School of Software Engineering Beihang University School of Mechanical Engineering Northwestern Polytechnical University

Traditional feature-based turbine blade models can match the needs of geometric modeling but could hardly meet the requirement of data extraction in 1-D heat transfer analysis. In this paper, the requirements of data extraction in 1-D heat transfer analysis are taken into consideration as well as geometric representation in parametric design process. An improved turbine blade parametric modeling method is proposed. Based on the modeling method proposed, a system structure of blade modeling process considering 1-D heat transfer analysis is devised. Eventually, a turbine blade parametric modeling system is constructed to test and verify the feasibility of the proposed modeling method and system structure. Experiments show that the blade parametric modeling method proposed can make geometric models better adapt to the specific requirements of 1-D heat transfer analysis and has certain reference value to the creation of high quality digital models.

关键词： turbine blade parametric modeling 1-D heat transfer analysis data extraction

Insight Into the Separation-of-Variable Methods for the Closed-Form Solutions of Free Vibration of Rectangular Thin Plates

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 329-355页

作者： Yufeng xing Ye Yuan Gen li Institute of Solid Mechanics Beihang University(BUAA)Beijing100191China

The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical *** taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue ***,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are *** is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.

关键词： Separation-of-variable method Rayleigh quotient nodal line eigenvalue equation bisection method

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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