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A survey on the network models applied in the industrial network optimization

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Science China(Information Sciences) 2024年第2期67卷 85-103页

作者： Chao DONG Xiaoxiong XIONG Qiulin XUE Zhengzhen ZHANG Kai NIU Ping ZHANG key laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and Telecommunications Smart City College Beijing Union University

Network architecture design is critical for optimizing industrial networks. Network architectures can be classified into small-scale networks and large-scale networks based on scale. Graph theory is an efficient mathematical tool for network topology modeling. For small-scale networks, their structure often has regular topology. For large-scale ones, the current body of work mainly focuses on random characteristics of network nodes and edges. Recently, widely used models include random networks, small-world networks,and scale-free networks. In this study, starting from the scale of the network, network modeling methods based on graph theory as well as their industrial applications, are summarized and analyzed. Moreover, a novel network performance metric, called system entropy, is proposed. From the perspective of mathematical properties, an analysis of its non-negativity and concavity is performed. The advantage of system entropy is that it can cover the existing regular networks, random networks, small-world networks, and scale-free networks, and has strong generality. The simulation results reveal that this proposed metric can achieve the comparison of various industrial networks under different models.

关键词： industrial network small-scale network large-scale network graph theory system entropy

UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 430-445页

作者： Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie IEEE School of Automation Guangdong University of TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing based on IoT Technology Guangzhou 510006China key laboratory of Intelligent Information Processing and system Integration of IoT Ministry of EducationGuangzhou 510006China School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Pillar of Information systems Technology and design Singapore University of Technology and DesignSingaporeSingapore College of Communication Engineering Army Engineering University of PLANanjing 210007China National Natural Science Foundation of China Beijing 100085China key laboratory of Intelligent Detection and IoT in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong key laboratory of IoT Information Technology Guangzhou 510006China

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach

关键词： Avatar blockchain metaverses multi-agent deep reinforcement learning transformer UAVs

Annealing-induced gradient nanostructured FeCrAlTiMo high-entropy alloy coatings with significantly enhanced wear resistance

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Tungsten 2024年第3期6卷 544-548页

作者： Jian Yang Ming-Yang Zhou Ji-Jun Yang key laboratory of Radiation Physics and Technology of ministry of education Institute of Nuclear Science and Technology Sichuan University Science and Technology on Reactor system design Technology laboratory Nuclear Power Institute of China

Recently, the amorphous high-entropy alloy(HEA) coatings exhibit an impressive resistance to the lead–bismuth eutectic(LBE) corrosion and ion irradiation, showing great application potential for lead-cooled fast reac...

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Simulation of random fiber Bragg grating array in polarization-maintaining fiber based on photonic localization effect

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Optoelectronics Letters 2024年第8期20卷 460-471页

作者： LI Zhihan HE Wei LI Shaode key laboratory of the ministry of education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing laboratory of Optical Fiber Sensing and system Beijing Information Science and Technology University

Mid-infrared wavelength switchable and dual-wavelength random laser output has many potential applications. A polarization-maintaining random fiber Bragg grating(PMRFBG) array based on the photonic localization effect of longitudinal invariant transverse disorder in fiber structure is proposed, which can be used as random feedback of dual-wavelength and wavelength switchable output of random fiber laser(RFL). The random fiber Bragg grating(RFBG) array was designed on the panda-type polarization-maintaining fiber(PMF), and the two center wavelengths were 2 151.60 nm and 2 152.22 nm, respectively. The RFBG array was designed on the bow tie-type PMF, and the two center wavelengths were obtained, which were 2 153.08 nm and 2 153.96 nm, respectively. The RFBG array with a center wavelength of 2 139.27 nm was designed on single-mode fiber(SMF). The length of individual fiber Bragg grating(FBG) and PMRFBG, the refractive index modulation depth, the number of cascaded gratings, and the distance between gratings have different effects on the full width at half maximum(FWHM) and reflectance of the RFBG and PMRFBG array, but not on the central wavelength, as obtained by simulation using the transmission matrix method. The designed PMRFBG array provides theoretical support for the design of the feedback mechanism of RFL.

关键词： A

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VSe_(2)/V_(2)C heterocatalyst with built-in electric field for efficient lithium-sulfur batteries:Remedies polysulfide shuttle and conversion kinetics

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Journal of Energy Chemistry 2024年第2期89卷 397-409,I0010页

作者： Yanwei Lv Lina Bai Qi Jin Siyu Deng Xinzhi Ma Fengfeng Han Juan Wang Lirong Zhang Lili Wu Xitian Zhang key laboratory for Photonic and Electronic Bandgap Materials Ministry of EducationSchool of Physics and Electronic EngineeringHarbin Normal UniversityHarbin 150025HeilongjiangChina

Lithium sulfur(Li-S)battery is a kind of burgeoning energy storage system with high energy ***,the electrolyte-soluble intermediate lithium polysulfides(Li PSs)undergo notorious shuttle effect,which seriously hinders the commercialization of Li-S ***,a unique VSe_(2)/V_(2)C heterostructure with local built-in electric field was rationally engineered from V_(2)C parent via a facile thermal selenization *** exquisitely synergizes the strong affinity of V_(2)C with the effective electrocatalytic activity of VSe_(2).More importantly,the local built-in electric field at the heterointerface can sufficiently promote the electron/ion transport ability and eventually boost the conversion kinetics of sulfur *** Li-S battery equipped with VSe_(2)/V_(2)C-CNTs-PP separator achieved an outstanding initial specific capacity of 1439.1 m A h g^(-1)with a high capacity retention of 73%after 100 cycles at0.1 *** impressively,a wonderful capacity of 571.6 mA h g^(-1)was effectively maintained after 600cycles at 2 C with a capacity decay rate of 0.07%.Even under a sulfur loading of 4.8 mg cm^(-2),areal capacity still can be up to 5.6 m A h cm^(-2).In-situ Raman tests explicitly illustrate the effectiveness of VSe_(2)/V_(2)C-CNTs modifier in restricting Li PSs *** with density functional theory calculations,the underlying mechanism of VSe_(2)/V_(2)C heterostructure for remedying Li PSs shuttling and conversion kinetics was *** strategy of constructing VSe_(2)/V_(2)C heterocatalyst in this work proposes a universal protocol to design metal selenide-based separator modifier for Li-S ***,it opens an efficient avenue for the separator engineering of Li-S batteries.

关键词： Li-S battery Shuttle effect Separator modifier VSe_(2)/V_(2)C heterostructure Built-in electric field

Control Policy Learning design for Vehicle Urban Positioning via BeiDou Navigation

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Journal of systems Science & Complexity 2024年第1期37卷 114-135页

作者： QIN Yahang ZHANG Chengye CHEN Ci XIE Shengli LEWIS Frank L School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong key laboratory of IoT Information Technology Guangzhou 510006China. Center for Intelligent Batch Manufacturing Based on IoT Technology key laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong-HongKong-Macao Joint laboratory for Smart Discrete Manufacturing Guangzhou 510006China key laboratory of Intelligent Information Processing and system Integration of IoT Ministry of EducationGuangzhou 510006China. UTA Research Institute The University of Texas at ArlingtonFort WorthTX 76019USA

This paper presents a learning-based control policy design for point-to-point vehicle positioning in the urban environment via BeiDou *** navigating in urban canyons,the multipath effect is a kind of interference that causes the navigation signal to drift and thus imposes severe impacts on vehicle localization due to the reflection and diffraction of the BeiDou ***,the authors formulated the navigation control system with unknown vehicle dynamics into an optimal control-seeking problem through a linear discrete-time system,and the point-to-point localization control is modeled and handled by leveraging off-policy reinforcement learning for feedback *** proposed learning-based design guarantees optimality with prescribed performance and also stabilizes the closed-loop navigation system,without the full knowledge of the vehicle *** is seen that the proposed method can withstand the impact of the multipath effect while satisfying the prescribed convergence rate.A case study demonstrates that the proposed algorithms effectively drive the vehicle to a desired setpoint under the multipath effect introduced by actual experiments of BeiDou navigation in the urban environment.

关键词： BeiDou navigation multipath effect prescribed convergence rate reinforcement learning urban localization.

Event-triggered sliding mode control of linear repetitive processes and its application in metal rolling process

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Science China(Information Sciences) 2024年第3期67卷 167-181页

作者： Xinyu LV Yugang NIU James LAM key laboratory of Smart Manufacturing in Energy Chemical Process (East China University of Science and Technology) Ministry of Education Department of Mechanical Engineering The University of Hong Kong

This paper investigates the design problem of a sliding mode controller for linear repetitive processes(LRPs) with a finite pass length on each pass. Under limited communication resources, an eventtriggered mechanism is implemented from the sensors to the controller, whose triggered sequence is consistent with the evolution direction of LRPs. To periodically orchestrate communication between the controller and actuator, a round-robin scheduling mechanism is established based on the pass length. A sliding function involving the state and pass profile is constructed, and the sliding mode controller is designed using triggered states and pass profile signals. Feasible controller gains are attained to ensure the stability of the resultant closed-loop system. Finally, the proposed strategy is implemented for a multi-roll metal rolling process.

关键词： event-triggered mechanism linear repetitive processes metal rolling process round-robin scheduling sliding mode control

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Applications of artificial intelligence to lipid nanoparticle delivery

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Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

Electrochemical reduction of carbon dioxide to produce formic acid coupled with oxidative conversion of biomass

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Journal of Energy Chemistry 2024年第5期92卷 705-729页

作者： Xi Liu Yifan Wang Zhiwei Dai Daihong Gao Xuebing Zhao key laboratory of Industrial Biocatalysis Ministry of EducationTsinghua UniversityBeijing 100084China Institute of Applied Chemistry Department of Chemical EngineeringTsinghua UniversityBeijing 100084China

Electrochemical reduction of CO_(2)(CO_(2)RR)has become a research hot spot in recent years in the context of carbon *** is one of the most promising products obtained by electrochemical reduction of CO_(2) due to its high energy value as estimated by market price per energy unit and wide application in chemical *** is the most abundant renewable resource in the natural *** biomass oxidative conversion with CO_(2)RR driven by renewable electricity would well achieve carbon *** this work,we comprehensively reviewed the current research progress on CO_(2)RR to produce HCOOH and coupled system for conversion of biomass and its derivatives to produce value-added ***-and Bi-based electrocatalysts are discussed for CO_(2)RR with regards to the structure of the catalyst and reaction ***-oxidation reactions of biomass derived sugars,alcohols,furan aldehydes and even polymeric components of lignocellulose were reviewed as alternatives to replace oxygen evolution reaction(OER)in the conventional electrolysis *** was recommended that to further improve the efficiency of the coupled system,future work should be focused on the development of more efficient and stable catalysts,careful design of the electrolytic cells for improving the mass transfer and development of environment-friendly processes for recovering the formed formate and biomass oxidation products.

关键词： Electrochemical reduction of CO_(2) Formic acid Oxidative conversion of biomass Lignocellulose Coupled system