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Existence of a Heterogeneous Pathway in Palladium-Catalyzed Carbon–Carbon Coupling Reaction:Evidence from Ag@Pd_(3)Cu Intermetallic Nanoplates

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CCS Chemistry 2022年第2期4卷 671-682页

作者： Rui Liu Cuihong Xu Yanan Chen Huachao Zhao Jiefang Sun Zuoliang He Wanyu Shan Gang Li Qiantao Shi Liping Fang Jingfu Liu Guibin Jiang State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085 School of Environment Hangzhou Institute of Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024 Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management Institute of Eco-Environmental and Soil SciencesGuangdong Academy of SciencesGuangzhou 510650 College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Center for Disease Prevention and Control Beijing 100013 Center for Environmental Systems Stevens Institute of TechnologyHobokenNJ 07030

Palladium(Pd)-catalyzed cross-coupling reaction is a widely studied process with significant economic interest and represents one of the most successful nanocatalytic *** to the observed leaching of Pd ions from both monometallic and short-range-ordered Pd bimetallic nanocatalysts,there is ambiguity regarding whether the coupling reaction has a heterogeneous ***,facilitated by theoretical calculations,we discovered that the Pd ion leaching-free Pd_(3)Cu intermetallic compound was able to catalyze the cross-coupling reaction heterogeneously with activity comparable with that of Pd ions leached from monometallic *** observation that Pd_(3)Cu acted as a heterogeneous catalyst was further confirmed by the reaction-promoting effect of hot electrons generated by the Ag core in Ag@Pd_(3)Cu nanoplates upon photon adsorption and could only participate in the reaction on the surface of the ***,it demonstrated experimentally the effectiveness of the heterogeneous route in the coupling *** study shows that the combination of plasmonic catalysis and intermetallic compounds is a promising strategy for designing robust nanocatalysts to synthesize value-added chemicals.

关键词： plasmonic catalysis intermetallics carbon-carbon coupling reaction mechanism heterogeneous pathway

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Learned Intelligent Recognizer with Adaptively Customized RIS Phases in Communication systems

Learned Intelligent Recognizer with Adaptively Customized RI...

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Future Communications and Networks (FCN), International Conference on

作者： Yixuan Huang Jie Yang Chao-Kai Wen Shuqiang Xia Xiao Li Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan ZTE Corporation Shenzhen China State Key Laboratory of Mobile Network and Mobile Multimedia Shenzhen China

ISBN: (数字)9798331512880

ISBN: (纸本)9798331512897

This study presents an advanced wireless system that embeds target recognition within reconfigurable intelligent surface (RIS)-aided communication systems, powered by cuttingedge deep learning innovations. Such a system faces the challenge of fine-tuning both the RIS phase shifts and neural network (NN) parameters, since they intricately interdepend on each other to accomplish the recognition task. To address these challenges, we propose an intelligent recognizer that strategically harnesses every piece of prior action responses, thereby ingeniously multiplexing downlink signals to facilitate environment sensing. Specifically, we design a novel NN based on the long short-term memory (LSTM) architecture and the physical channel model. The NN iteratively captures and fuses information from previous measurements and adaptively customizes RIS configurations to acquire the most relevant information for the recognition task in subsequent moments. Tailored dynamically, these configurations adapt to the scene, task, and target specifics. Simulation results reveal that our proposed method significantly outperforms the state-of-the-art method, while resulting in minimal impacts on communication performance, even as sensing is performed simultaneously.

关键词： Wireless communication Multiplexing Technological innovation Phase measurement Target recognition Simulation Memory architecture Reconfigurable intelligent surfaces Sensors Long short term memory

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Design and Visual Servoing control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

arXiv

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arXiv 2024年

作者： Chen, Jian Chen, Mingcong Zhao, Qingxiang Wang, Shuai Wang, Yihe Xiao, Ying Hu, Jian Chan, Danny Tat Ming Yeung, Kam Tong Leo Chan, David Yuen Chung Liu, Hongbin The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Beijing100190 China Hong Kong Department of Biomedical Engineering City University of Hong Kong Hong Kong CAIR-HKISI-CAS HKSAR China The State Key Laboratory of Multimodal Artificial Intelligence Systems CASIA Beijing100190 China Department of Surgery The Chinese University of Hong Kong Hong Kong The State Key Laboratory of Management and Control for Complex Systems CASIA Beijing100190 China The School of Biomedical Engineering and Imaging Sciences King's College London LondonSE1 7EU United Kingdom

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot's ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery. Copyright © 2024, The Authors. All rights reserved.

关键词： Visual servoing

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An adaptive federated control strategy for participant selection in multi-client collaboration 1

An adaptive federated control strategy for participant selec...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Chen, Yizhu Du, Xiaoming Wang, Xiao Zhang, Jun Jason Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (纸本)9781665433372

The federated ecology provides a new paradigm for breaking the isolated data island problem and fully activating the potential of big data and artificial intelligence, especially in multi-client collaboration tasks. Participant selection strategy in multi-client collaboration is the main limitation for increasing the convergence speed and lowing the communication costs. However, in the face of the unbalanced and non-IID data distributions, the performance of federated optimization algorithms will also decrease. To solve the above problems, we propose an adaptive federated control strategy for participant selection in multi-client collaboration based on the Mann-Kendall test, named FedMK. By adaptively selecting weak participants for training rather than random selection, FedMK can speed up model convergence and reduce communication costs. Experiment results show that our method outperforms the baseline method in non-IID scenarios, and the number of communication rounds on CIFAR-10 and synthetic datasets reduced by more than 15% and 10 %, 9 respectively. © 2021 IEEE.

关键词： Stream flow

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Optimization of Robot End-Effector Load Gravity Compensation for Unmanned Live Work in Electric Power Distribution Networks Based on Improved PSO Algorithm

Optimization of Robot End-Effector Load Gravity Compensation...

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2023 China Automation Congress, CAC 2023

作者： Chen, Jinge Chen, Xin Hu, Chenyu Huang, Guangxian Sun, Shu Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering-Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Distribution Department Xianning437000 China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Equipment Technology Center Wuhan430077 China

ISBN: (纸本)9798350303759

In the field of electric power distribution network operation, most tasks involve contact operations. A key technology to enable the flexible operation of robots in live distribution network tasks is the installation of six-dimensional force sensors on the robot's end flange. These sensors allow the robot to perceive external environmental contact forces. However, the presence of the end load interferes with the accurate perception of external forces. Aiming at the gravity compensation of robot end load, an optimization algorithm of gravity compensation based on particle swarm optimization is proposed. In this method, the optimal solution model is established with the objective of minimum sum of squared errors, and the particle swarm optimization algorithm is used to estimate the mounting declination angle of the force sensor and improve the precision of gravity compensation. The experiments show that the proposed method can effectively reduce the maximum gravity compensation error and the average gravity compensation error in each direction after optimization, in which the maximum gravity compensation error of the resultant force is reduced by 9.11% and the average gravity compensation error of the resultant force is reduced by 12.34%. © 2023 IEEE.

关键词： Error compensation

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Development and path planning of a novel unmanned surface vehicle system and its application to exploitation of Qarhan Salt Lake

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Science China(Information Sciences) 2019年第8期62卷 195-197页

作者： Zhibin XUE Jincun LIU Zhengxing WU Sheng DU Shihan KONG Junzhi YU College of Chemical Engineering Qinghai University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences

Qarhan Salt Lake is rich in mineral resources, such as sodium chloride, potassium, and magnesium [1].At present, liquid mine exploiting is the main exploitation form for the Qarhan Salt Lake. Salt mining ships with mining equipments are widely used to exploit carnallite which is located at the bottom of pools. Conventionally, workmen utilize rude ferric sampler to collect carnallite samples

关键词： USV simulation Development and path planning of a novel unmanned surface vehicle system and its application to exploitation of Qarhan Salt Lake

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SARS-CoV-2 Inhibits Exo-Endocytosis and Enhances Short-Term Depression at a Central Synapse

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Neuroscience Bulletin 2025年第1期41卷 165-171页

作者： Jiawei Hu Yuhan Zhang Qingzhuo Liu Jiaqi Hu Yichen Ru Lu Zhang Lixin Xie Lei Xue State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan UniversityShanghai200438China Department of Physiology and Neurobiology School of Life SciencesFudan UniversityShanghai200438China Department of Pulmonary and Critical Care Medicine Ruijin HospitalShanghai Jiao Tong University School of MedicineShanghai200025China Center for Rehabilitation Medicine Department of Pain ManagementZhejiang Provincial People’s HospitalAffiliated People’s HospitalHangzhou Medical CollegeHangzhou310014China Department of Microbiology and Immunology School of Life SciencesFudan UniversityShanghai200438China College of Pulmonary and Critical Care Medicine 8th Medical Center of Chinese PLA General HospitalBeijing100091China Research Institute of Intelligent Complex Systems Fudan UniversityShanghai200433China

Dear Editor,SARS-CoV-2 is the virus that caused the COVID-19 pandemic,leading to more than 774 million cases and 7,037,007 deaths by March 2024(World Health Organization,http://***/).Despite effective treatments,15%-20%of patients experience long-term symptoms,such as breathlessness,fatigue,depression,and cognitive impairment,which are often linked to an excessive immune response[1].All variants of the virus(α,,,Omicron,and BA.1),which can potentially access the brain via the olfactory mucosa,have been found in the brains of Syrian hamsters,triggering inflammation and demonstrating axonal travel[2].

关键词： travel spite fatigue

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A Reinforcement Learning Benchmark for Autonomous Driving in Intersection Scenarios

A Reinforcement Learning Benchmark for Autonomous Driving in...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yuqi Liu Qichao Zhang Dongbin Zhao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728190495

In recent years, control under urban intersection scenarios has become an emerging research topic. In such scenarios, the autonomous vehicle confronts complicated situations since it must deal with the interaction with social vehicles timely while obeying the traffic rules. Generally, the autonomous vehicle is supposed to avoid collisions while pursuing better efficiency. The existing work fails to provide a framework that emphasizes the integrity of the scenarios while deploying and testing reinforcement learning(RL) methods. Specifically, we propose a benchmark for training and testing RL-based autonomous driving agents in complex intersection scenarios, which is called RL-CIS. Then, a set of baselines consisting various algorithms are deployed. The test benchmark and baselines provide a fair and comprehensive training and testing platform for the study of RL for autonomous driving in the intersection scenario, advancing RL-based methods for autonomous driving control. The code of our proposed framework can be found at https://***/liuyufi123/complexUrbanScenarios.

关键词： Training Codes Stochastic processes Reinforcement learning Benchmark testing Sampling methods Concrete

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A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition

A Prototype-Based Generalized Zero-Shot Learning Framework f...

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International Conference on Pattern Recognition

作者： Jinting Wu Yujia Zhang Xiaoguang Zhao School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

Hand gesture recognition plays a significant role in human-computer interaction for understanding various human gestures and their intent. However, most prior works can only recognize gestures of limited labeled classes and fail to adapt to new categories. The task of Generalized Zero-Shot Learning (GZSL) for hand gesture recognition aims to address the above issue by leveraging semantic representations and detecting both seen and unseen class samples. In this paper, we propose an end-to-end prototype-based GZSL framework for hand gesture recognition which consists of two branches. The first branch is a prototype-based detector that learns gesture representations and determines whether an input sample belongs to a seen or unseen category. The second branch is a zero-shot label predictor which takes the features of unseen classes as input and outputs predictions through a learned mapping mechanism between the feature and the semantic space. We further establish a hand gesture dataset that specifically targets this GZSL task, and comprehensive experiments on this dataset demonstrate the effectiveness of our proposed approach on recognizing both seen and unseen gestures.

关键词： Human computer interaction Target recognition Semantics Prototypes Human-robot interaction Gesture recognition Detectors

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A reinforcement learning benchmark for autonomous driving in intersection scenarios

arXiv

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arXiv 2021年

作者： Liu, Yuqi Zhang, Qichao Zhao, Dongbin The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

In recent years, control under urban intersection scenarios becomes an emerging research topic. In such scenarios, the autonomous vehicle confronts complicated situations since it must deal with the interaction with social vehicles timely while obeying the traffic rules. Generally, the autonomous vehicle is supposed to avoid collisions while pursuing better efficiency. The existing work fails to provide a framework that emphasizes the integrity of the scenarios while being able to deploy and test reinforcement learning(RL) methods. Specifically, we propose a benchmark for training and testing RL-based autonomous driving agents in complex intersection scenarios, which is called RL-CIS. Then, a set of baselines are deployed consists of various algorithms. The test benchmark and baselines are to provide a fair and comprehensive training and testing platform for the study of RL for autonomous driving in the intersection scenario, advancing the progress of RL-based methods for intersection autonomous driving control. The code of our proposed framework can be found at https://***/liuyuqi123/complexUrbanScenarios. Copyright © 2021, The Authors. All rights reserved.

关键词： Decision making

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