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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Addendum: Solution epitaxy of polarization-gradient ferroelectric oxide films with colossal photovoltaic current

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Nature communications 2024年第1期15卷 3878-3878页

作者： Lin, Chen Zhang, Zijun Dai, Zhenbang Wu, Mengjiao Liu, Shi Chen, Jialu Hua, Chenqiang Lu, Yunhao Zhang, Fei Lou, Hongbo Dong, Hongliang Zeng, Qiaoshi Ma, Jing Pi, Xiaodong Zhou, Dikui Wu, Yongjun Tian, He Rappe, Andrew M. Ren, Zhaohui Han, Gaorong State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou 310027 China Center of Electron Microscope School of Materials Science and Engineering Zhejiang University Hangzhou 310027 China Department of Chemistry University of Pennsylvania Philadelphia PA United States Oden Institute for Computational Engineering and Sciences University of Texas at Austin Austin 78712 TX United States Key Laboratory for Quantum Materials of Zhejiang Province Department of Physics School of Science Westlake University Hangzhou 310024 China Zhejiang Province Key Laboratory of Quantum Technology and Device Department of physics Zhejiang University Hangzhou 310027 China Center for High Pressure Science and Technology Advanced Research 201203 Shanghai China State Key Lab of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University 100091 Beijing China Institute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 311215 China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou 311100 China State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou 310027 China

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An Image Denoising Method Based on Deep Residual GAN

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Journal of Physics: Conference Series 2020年第3期1550卷

作者： Ziyuan Wang Lidan Wang Shukai Duan Yunfei Li Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing 400715 China Schoolof Electronic and information engineering Southwest University Chongqing400715 China College of Artificiall Intelligence Southwest University Chongqing 400715 China Braininspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China

As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most of them is lack of capability when customers want more perceptual details of the image without information loss. In this paper, a deep residual network based on generative adversarial (GAN) network was proposed to complete the image denoising mission. Firstly, a generative-adversarial network structure based on residual blocks was designed. Secondly, a refined loss function was given to train the GAN network. The well designed loss function can help the generated image to be very close to the clear counterpart (ground truth) while enhancing more details in colours and brightness. Finally, extensive experiments show that our network is not only convincing for images denoising, but also effective for other image process tasks, such as image defogging, medical CT denoising etc., presenting impressive and competitive effects.

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A Brain-To-Brain Interface with a Flexible Neural Probe for Mouse Turning Control by Human Mind

A Brain-To-Brain Interface with a Flexible Neural Probe for ...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Yifei Ye Zhenyu Wang Ye Tian Han Wang Cunkai Zhou Honglin Hu Ting Zhou Zhitao Zhou Xiaoling Wei Jianlong Zhao Tiger H. Tao Liuyang Sun State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Intelligent Communication Lab Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China 2020 X-Lab Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Graduate Study University of Chinese Academy of Sciences Beijing China School of Microelectronics Shanghai University Shanghai China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China School of Physical Science and Technology ShanghaiTech University Shanghai China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Neuroxess Co. Ltd. (Jiangxi) Nanchang China Guangdong Institute of Intelligence Science and Technology Hengqin Zhuhai China Tianqiao and Chrissy Chen Institute for Translational Research Shanghai China

We proposed a brain-to-brain interface (B2BI) that enabled effective control of mouse turning behavior by human mind using an implantable, ultra-flexible neural probe. The neural probe was capable of writing in neural signals to the mouse brain, with effective electrical stimulation observed at a low current of 5 μA. Additionally, a wireless EEG device was developed for the remote transmission of human brain signals, which were decoded by the canonical correlation analysis (CCA) method with an accuracy rate of up to 98.6%. These results demonstrate the potential of B2BI technology to enable communication and control between humans and animals.

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New algorithm of target classification in polarimetric SAR

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Journal of Systems Engineering and Electronics 2008年第2期000卷

作者： Wang Yang Lu Jiaguo Wu Xianliang Wang Yang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Lu Jiaguo (The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Wu Xianliang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China)

The different approaches used for target decomposition (TD) theory in radar polarimetry are reviewed and three main types of theorems are introduced: those based on Mueller matrix, those using an eigenvector analysis of the coherency matrix, and those employing coherent decomposition of the scattering matrix. Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated success in many fields. A new algorithm of target classification, by combining target decomposition and the support vector machine, is *** conduct the experiment, the polarimetric synthetic aperture radar (SAR) data are used. Experimental results show that it is feasible and efficient to target classification by applying target decomposition to extract scattering mechanisms, and the effects of kernel function and its parameters on the classification efficiency are significant.

关键词： polarimetric synthetic aperture radar target decomposition support vector machine target classifi-cation kernel function.

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. Image R. 25(7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 27卷 57-57页

作者： Weizhi Xu Hui Yu Dianjie Lu Fenglong Song Da Wang Xiaochun Ye Songwei Pei Dongrui Fan Hongtao Xie Institute of Microelectronics Tsinghua University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Information Science and Engineering Shandong Normal University Jinan China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Institute of Information Engineering Chinese Academy of Sciences National Engineering Laboratory for Information Security Technologies Beijing China

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. 25 (7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 26卷 350-350页

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Social sensing enhanced time estimation for bus service

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Concurrency and Computation: Practice and Experience 2015年第15期27卷

作者： Jin Liu Juan Li Xiaohui Cui Xiaoguang Niu Xiaoping Sun Jing Zhou State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEA s and road condition attributions PRCA s. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEA s of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： social sensing in-time bus service bus route arrival time estimation

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Antitumor Effects of Cds-Ppix Adducts for Nuclear-Targeted Sonodynamic Therapy

SSRN

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SSRN 2023年

作者： Xue, Juanjuan Jia, Muyue Sang, Shengbo Li, Huaqian Wang, Xiaojuan Guo, Li Duan, Qianqian Xi, Yanfeng Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan030024 China Department of Pathology Shanxi Cancer Hospital Shanxi Hospital Affiliated to CancerHospital Chinese Academy of Medical Sciences Cancer Hospital Affiliated to Shanxi Medical University Shanxi Taiyuan030013 China Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair Department of Orthopaedics Second Hospital of Shanxi Medical University Taiyuan030001 China Department of Pathology Shanxi Tumor Hospital Taiyuan030013 China

To achieve high-efficiency treatment to diseases, accurate delivery of drugs with a carrier into the specific organelles is of great importance. The nucleus is the ultimate target for a large number of drugs and direct delivery of drugs into nucleus can greatly improve the therapeutic treatment. Whereas, in sonodynamic therapy (SDT), the fact that most drug delivery systems can only deliver drugs to the cytoplasm of the cells and cannot act directly on the nucleus. In this paper, nucleolus-targeted carbondots (CDs) are prepared. Also, the conjugate of CDs and PpIX is synthesized by amide cross-linking and then release singlet oxygen to kill cancer cells under ultrasound radiation. The resulting CDs-PpIX nanoparticles showed significant nuclear targeting properties, and greatly improved the efficiency of acoustic dynamics treatment, as the nucleus exhibited poor tolerance to reactive oxygen species (ROS) generated during acoustic dynamics treatment. In addition, ROS as an extracellular signal can activate the p38MAPK protein pathway, which is the main mechanism of ultrasound killing of cancer cells. Our results demonstrate the great potential of CDs-PpIX in targeting cell nuclei for acoustic dynamics treatment. © 2023, The Authors. All rights reserved.

关键词： Cancer cells

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The rise of intelligent fabric agent from mass-produced advanced fiber materials

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Science Bulletin 2024年第23期69卷 3644-3647页

作者： Pan Li Maiping Yang Yueheng Liu Jing Zhang Sisi He Cuiwei Yang Weizhong Yang Xinyuan Cai Liping Zhu Shenglin Ye Hongyu Sun Chong Hou Ning Zhou Meifang Zhu Guangming Tao Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Engineering and Electronic Information China University of Geosciences(Wuhan)Wuhan 430074China Shenzhen Key Laboratory of Flexible Printed Electronics Technology School of ScienceHarbin Institute of TechnologyShenzhen 518055China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200433China Shanghai Different Advanced Material Co. Ltd.Shanghai 201502China School of Architecture and Urban Planning Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China Meta Reality Lab Meta PlatformsInc.SunnyvaleCA 94089USA School of Nursing Peking UniversityBeijing 100191China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Department of Cardiology Beijing Anzhen HospitalCapital Medical UniversityNational Clinical Research Center for Cardiovascular DiseasesBeijing 100029China Key Laboratory of Vascular Aging Ministry of EducationTongji Hospital Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China School of Physical Education Huazhong University of Science and TechnologyWuhan 430074China

Artificial intelligence(AI)is crucial in driving scientific,technological,and industrial advancements,and it has given rise to an ambient intelligence that can potentially improve the physical execution of healthcare delivery[1,2].Among diverse advanced AI technologies,an intelligent agent with multi-parameter perception,decision-making,and execution capabilities demonstrates the potential for facilitating the development of next-generation optoelectronic *** intelligent agent is a physical or abstract entity that acts autonomously,perceives and interacts with its environment,and communicates with other agents[3].It could perceive dynamic environmental conditions,execute actions,and make appropriate *** emerges as an ideal carrier for human-centered intelligent agents,providing various properties such as perceptibility,adaptability,and *** fabric,known for its unique functionality,has attracted considerable attention from academia and *** 2014,Germany proposed a national strategy called FutureTEX to upgrade the entire textile industry by promoting integration between textiles and other *** years later,the United States announced the establishment of the Revolutionary Fibers and Textiles Manufacturing Innovation Institute,which intends to accelerate the revival of fabric *** with conventional fibers,revolutionary fibers focus on the design of multiple materials and structures,enabling the integration of various functionalities into a single *** in the United States,the advent of the digital revolution,advancements in Internet of Things technology,and mature fiber technology significantly boost the development of the intelligent fiber *** commercial applications of intelligent fibers are gradually *** Jacquard,a collaborative effort by Google and Levi’s,presents an intelligent jacket that combines the washability and texture of standard fabrics with the

关键词： agent execution fiber

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