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Targets capture by distributed active swarms via bio-inspired reinforcement learning

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace control Technology institute Shanghai Key Laboratory of Aerospace Intelligent control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

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Neural Regeneration Research 2025年第9期20卷 2520-2537页

作者： Chonglin Su Taiqi Huang Meiyu Zhang Yanyu Zhang Yan Zeng Xingxing Chen Brain Science and Advanced Technology institute Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of MedicineWuhan University of Science and TechnologyWuhanHubei ProvinceChina

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental *** the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and *** glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic *** interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive *** appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive *** with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor *** review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive *** emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive *** provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.

关键词： brain-derived neurotrophic factor calcium signaling glucocorticoid receptor glucocorticoid glutamate transmission hypothalamic-pituitary-adrenal axis long-term potentiation neurocognitive disorders neuroplasticity stress

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Bandgap characteristics analysis and graded design of a novel metamaterial for flexural wave suppression

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 1-24页

作者： Fan YANG Zhaoyang MA Xingming GUO Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering ScienceShanghai University Shanghai institute of Aircraft Mechanics and control

A novel elastic metamaterial is proposed with the aim of achieving lowfrequency broad bandgaps and bandgap regulation. The band structure of the proposed metamaterial is calculated based on the Floquet-Bloch theorem, and the boundary modes of each bandgap are analyzed to understand the effects of each component of the unit cell on the bandgap formation. It is found that the metamaterials with a low elastic modulus of ligaments can generate flexural wave bandgaps below 300 Hz. Multi-frequency vibrations can be suppressed through the selective manipulation of bandgaps. The dual-graded design of metamaterials that can significantly improve the bandgap width is proposed based on parametric studies. A new way that can regulate the bandgap is revealed by studying the graded elastic modulus in the substrate. The results demonstrate that the nonlinear gradient of the elastic modulus in the substrate offers better bandgap performance. Based on these analyses, the proposed elastic metamaterials can pave the way for multi-frequency vibration control, low-frequency bandgap broadening, and bandgap tuning.

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A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 813-834页

作者： Chanhyeong Cho Byeori Kim Haehyun Cho Taek-Young Youn Department of Cyber security Dankook UniversityYongin16890Republic of Korea Department of Software Soongsil UniversitySeoul07027Republic of Korea

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly ***,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient *** paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative *** bundle includes updated information,allowing only the updated portions to be reencrypted when changes *** encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates *** proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext *** utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those *** approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data *** validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size *** show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size ***,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

关键词： Cloud collaboration mode of operation data update efficiency

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The Determination on Weight Hierarchies of q-Ary Linear Codes of Dimension 5 in Class IV

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Journal of systems Science & Complexity 2016年第1期29卷 243-258页

作者： WANG Lijun CHEN Wende School of Mathematics and Statistics South-Central University for Nationalities Laboratory of systems and control and Information security Center Institute of Systems ScienceChinese Academy of Science

The weight hierarchy of a linear[n;k;q]code C over GF(q) is the sequence(d_1,d_2,…,d_k)where d_r is the smallest support of any r-dimensional subcode of C. "Determining all possible weight hierarchies of general linear codes" is a basic theoretical issue and has important scientific significance in communication ***,it is impossible for g-ary linear codes of dimension k when q and k are slightly larger,then a reasonable formulation of the problem is modified as: "Determine almost all weight hierarchies of general g-ary linear codes of dimension k".In this paper,based on the finite projective geometry method,the authors study g-ary linear codes of dimension 5 in class IV,and find new necessary conditions of their weight hierarchies,and classify their weight hierarchies into6 *** authors also develop and improve the method of the subspace set,thus determine almost all weight hierarchies of 5-dimensional linear codes in class *** opens the way to determine the weight hierarchies of the rest two of 5-dimensional codes(classes III and VI),and break through the ***,the new necessary conditions show that original necessary conditions of the weight hierarchies of k-dimensional codes were not enough(not most tight nor best),so,it is important to excogitate further new necessary conditions for attacking and solving the fc-dimensional problem.

关键词： Difference sequence q-ary linear code of dimension 5 weight hierarchy

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Benefits of model predictive control for gasoline airpath control

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Science China(Information Sciences) 2018年第7期61卷 57-67页

作者： Thivaharan ALBIN institute for Dynamic systems and control

One effective possibility to reduce pollutant emissions and fuel consumption of an internal combustion engine is the use of improved process control. It is made viable by the implementation of additional actuators and sensors which allow to operate the process more flexible. For full exploitation of the setup an appropriate control algorithm is necessary. Classical engine control structures rely on the use of many calibration parameters which result in high demands on the calibration time. Model predictive control(MPC)is an advanced control algorithm which is able to overcome this drawback. It allows to use a mathematical plant model for control synthesis which reduces calibration time and makes reusability possible. The present paper introduces the MPC algorithm and discusses the benefits of MPC for engine control. A special emphasis is put on the application for gasoline airpath control. For clarification, the benefits are demonstrated by numerical simulation studies. For the example of gasoline two stage turbocharging, the advantage concerning control performance are shown as well as the possibility to easily adapt to changed specifications for the closed-loop control dynamics.

关键词： model predictive control engine control airpath control

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FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

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Computers, Materials & Continua 2024年第8期80卷 2351-2362页

作者： Yan Sun Caiyun Liu Jun Li Yitong Liu Data security institute China Industrial Control Systems Cyber Emergency Response TeamBeijing100040China

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage *** data of ICV(intelligent connected vehicles)is the key to organically maximizing their ***,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are *** study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on *** data holder publishes the shared data information and forms the corresponding label storage on the *** data demander browses the data directory information to select and purchase data assets and verify *** data demander selects and purchases data assets and verifies them by browsing the data directory ***,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal *** the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing *** this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

关键词： Blockchain connected vehicles data sharing smart contracts credible traceability

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Social Robot Detection Method with Improved Graph Neural Networks

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Computers, Materials & Continua 2024年第2期78卷 1773-1795页

作者： Zhenhua Yu Liangxue Bai Ou Ye Xuya Cong institute of systems security and control College of Computer Science and TechnologyXi’an University of Science and TechnologyXi’an710054China

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

关键词： Social robot detection social relationship subgraph graph attention network feature linear modulation behavioral gene sequences

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Hybrid event-and time-triggered control for double-integrator heterogeneous networks

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Science China(Information Sciences) 2019年第2期62卷 73-84页

作者： Gaopeng DUAN Feng XIAO Long WANG Center for systems and control College of Engineering Peking University Research institute of Intelligent control and systems Harbin Institute of Technology

This paper investigates the state consensus for double-integrator networks under heterogeneous interaction topologies. For double-integrator networks, the setting of heterogeneous topologies means that position and velocity information flows are modeled by two different graphs. The corresponding protocol proposed in this paper is based on edge-event-triggered control. The events based on position information are irrelevant to velocity information and independent of the events based on velocity information. And for different edges, the corresponding events are activated independently of each other. Once an event occurs,the agents connected by the associated edge will sample their corresponding relative state information and update their corresponding controllers. Furthermore, under the presented event-triggering rules, the state consensus of double-integrator networks can be achieved by designing appropriate parameters. In addition,the proposed protocol with the event-triggering rules can effectively improve the system performance and avoid the occurrence of Zeno behaviors. Finally, a simulation example is worked out to verify the theoretical analysis.

关键词： consensus sampled-data control multi-agent systems edge-event-triggered control heterogeneous networks

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Integral sliding mode control design for nonlinear stochastic systems under imperfect quantization

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Science China(Information Sciences) 2017年第12期60卷 71-81页

作者： Yabin GAO Wensheng LUO Jianxing LIU Ligang WU Research institute of Intelligent control and systems Harbin Institute of Technology

This paper presents a sliding mode control(SMC) scheme via output-feedback approach for It?o stochastic systems under a quantization mechanism. The quantization process is formulated with the imperfection that random packet loss occurs at the logarithmic quantizer. A Luenberger observer is designed, based on the packet loss rate and the imperfect quantized measurement. A novel SMC law is synthesized by utilization of an integral sliding surface. The stochastic stability of the resulting closed-loop system is analyzed in terms of Lyapunov stability, and a set of solvable matrix inequalities are established for practical application requirements. Finally, a simulation example is employed for the illustration of the effectiveness of the presented control scheme.

关键词： stochastic systems quantized control sliding mode control observer design packet loss

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