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| 1 | Up-regulated microRNA-146a negatively modulate Helicobacter pylori -induced inflammatory response in human gastric epithelial cells显示文摘 | Zhen Liu Bin Xiao Bin Tang Bosheng Li Na Li Endong Zhu Gang Guo Jiang Gu Yuan Zhuang Xiaofei Liu Honglei Ding Xiaoyan Zhao Hong Guo Xuhu Mao Quanming Zou | 2010 | Microbes and Infection2010，，11： | 1 |
| 2 | Flexible triboelectric nanogenerator toward ultrahigh-frequency vibration sensing显示文摘Flexible high-frequency vibration sensors are highly desirable in various real-world applications such as structural health monitoring,environmental monitoring,and the internet of things.However,developing a facile and effective method to fabricate vibration sensors simultaneously featuring high vibration frequency response-ability and flexibility remains a grand challenge.Herein,we report a flexible ultrahigh-frequency triboelectric vibration sensor(UTVS)prepared by a layer-particle-layer structure.Owing to the flexibility of the materials(i.e.,polyethylene terephthalate membrane)and the ultrahigh-frequency vibration response-ability of internal microparticles,the flexible UTVS exhibits an enhanced working frequency range of 3–170 kHz,which is much broader than previously reported triboelectric vibration sensors.Moreover,the UTVS can work not only in a flat state but also in a bent state due to its flexibility and the unique layer-particle-layer structural design.The UTVS shows nanometer-level vibration response-ability,omnidirectional response,stability in the temperature range of 10–70°C,good frequency resolution of 0.01 kHz,and excellent performance in burst vibration detection(e.g.,pencil lead break events and impact events from falling steel balls).With a collection of compelling features,the device is successfully demonstrated in vibration monitoring of curved structures(e.g.,real-time water pipeline leak monitoring).Such a flexible ultrahigh-frequency triboelectric vibration sensor holds great potential in a wide range of practical applications,such as communication,health care,and infrastructure monitoring. | Zhiwei Lin Chenchen Sun Gaoqiang Zhang Endong Fan Zhihao Zhou Ziying Shen Jun Yang Mingyang Liu Yushu Xia Shaobo Si Jin Yang | 2022 | Nano Research2022，15，8： | 0 |
| 3 | Adversarial attack and defense in reinforcement learning-from AI security view显示文摘Reinforcement learning is a core technology for modern artificial intelligence,and it has become a workhorse for AI applications ranging from Atrai Game to Connected and Automated Vehicle System(CAV).Therefore,a reliable RL system is the foundation for the security critical applications in AI,which has attracted a concern that is more critical than ever.However,recent studies discover that the interesting attack mode adversarial attack also be effective when targeting neural network policies in the context of reinforcement learning,which has inspired innovative researches in this direction.Hence,in this paper,we give the very first attempt to conduct a comprehensive survey on adversarial attacks in reinforcement learning under AI security.Moreover,we give briefly introduction on the most representative defense technologies against existing adversarial attacks. | Tong Chen Jiqiang Liu Yingxiao Xiang Wenjia Niu Endong Tong Zhen Han | 2019 | Cybersecurity2019，2，1： | 0 |
| 4 | Adversarial attack and defense in reinforcement learning-from AI security view显示文摘Reinforcement learning is a core technology for modern artificial intelligence,and it has become a workhorse for AI applications ranging from Atrai Game to Connected and Automated Vehicle System(CAV).Therefore,a reliable RL system is the foundation for the security critical applications in AI,which has attracted a concern that is more critical than ever.However,recent studies discover that the interesting attack mode adversarial attack also be effective when targeting neural network policies in the context of reinforcement learning,which has inspired innovative researches in this direction.Hence,in this paper,we give the very first attempt to conduct a comprehensive survey on adversarial attacks in reinforcement learning under AI security.Moreover,we give briefly introduction on the most representative defense technologies against existing adversarial attacks. | Tong Chen Jiqiang Liu Yingxiao Xiang Wenjia Niu Endong Tong Zhen Han | 2018 | Cybersecurity2018，1，1： | 0 |
| 5 | Design and performance analysis of tracking controller for uncertain nonlinear composite system using neural networks显示文摘Based on high order dyna mi c neural network,this paper presents the tracking problem for uncertain nonlinear composite system,which contain s external disturbance,whose nonlinear ities are assumed to be unknown.A smooth contr oller is designed to guarantee a uniform ultimate boundedness property for the tracking error and a ll other signals in the closed loop.Certain meas ures are utilized to test its performance.No a priori knowledge of an upper bound on the “ optimal' weight and modeling error is required;the weights of neural networks are updated on-line.N umerical simulations performed on a simple example i llustrate and clarify the approach. | Endong LIU Yuanwei JING Siying ZHANG | 2005 | 控制理论与应用(英文版)2005，3，2： | 0 |
| 6 | Catalyst Enhanced Chemical Vapor Deposition of Nano-Particle Nickel Films on Teflon Surface显示文摘Films formed with nanosized nickel particles on teflon surface were prepared by means of catalyst enhanced chemical vapor deposition (CECVD) with Ni(dmg)2, Ni(acac)2, Ni(hfac)2, Ni(TMHD)2, and Ni(cp)2 as precursors, and complexes Pd(hfac)2, PdCl2 and Pd(η3-2-methylallyl)acac as catalyst under carrier gas (H2). The film growth rate depends on the precursors and substrate temperature. The chemical value, purity and surface morphology of the Ni particle films were characterized by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The films obtained were shiny with silvery color, and consisted of grains with a particle size of 50-140 nm. The Ni was metallic of which the purity was about 90%-95% from XPS analysis. SEM micrograph showed that the film had good morphology. | LIU Endong FENG Wenfang ZHOU Jinlan YU Kaichao | 2009 | Wuhan University Journal of Natural Sciences2009，14，2： | 0 |
| 7 | Curricular Robust Reinforcement Learning via GAN-Based Perturbation Through Continuously Scheduled Task Sequence显示文摘Reinforcement learning(RL),one of three branches of machine learning,aims for autonomous learning and is now greatly driving the artificial intelligence development,especially in autonomous distributed systems,such as cooperative Boston Dynamics robots.However,robust RL has been a challenging problem of reliable aspects due to the gap between laboratory simulation and real world.Existing efforts have been made to approach this problem,such as performing random environmental perturbations in the learning process.However,one cannot guarantee to train with a positive perturbation as bad ones might bring failures to RL.In this work,we treat robust RL as a multi-task RL problem,and propose a curricular robust RL approach.We first present a generative adversarial network(GAN)based task generation model to iteratively output new tasks at the appropriate level of difficulty for the current policy.Furthermore,with these progressive tasks,we can realize curricular learning and finally obtain a robust policy.Extensive experiments in multiple environments demonstrate that our method improves the training stability and is robust to differences in training/test conditions. | Yike Li Yunzhe Tian Endong Tong Wenjia Niu Yingxiao Xiang Tong Chen Yalun Wu Jiqiang Liu | 2023 | Tsinghua Science and Technology2023，28，1： | 0 |
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