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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Yang, Shuqi Zhang, Lijuan Lan, Qing Ma, Qiujie Huang, Huan Miao, Jiaqing Mou, Shiyu Luo, Cheng Yao, Dezhong Tan, Ying Southwest Minzu University Key Laboratory for Computer Systems of State Ethnic Affairs Commission Chengdu China Moe Key Lab for Neuroinformation University of Electronic Science and Technology of China Clinical Hospital Chengdu Brain Science Institute Chengdu China University of Malaya Faculty of Engineering Department of Biomedical Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350386226

Autism spectrum disorder (ASD) is a mental disorder that severely affects social interaction and communication skills. A timely and accurate diagnosis is crucial for effective intervention. However, as an objective diagnostic tool, the existence of spurious connections and noise within the functional connectivity (FC) matrix in the brain contribute to the complexity of ASD diagnosis. In this study, we propose an unsupervised sparse graph structure learning framework, called NeuroSparse, for reasoning regarding the topological connectivity relationships between brain regions. First, the framework fuses spatiotemporal information from static and dynamic FC to provide a comprehensive representation of complex brain networks. Next, the context and neighborhood information of nodes are captured as their local and global embeddings, and the latent representations of node embeddings are learned, which are then decoded to infer the connectivity relationships among the regions of interest. Finally, we introduce three innovative loss functions to regularize and optimize the sparse representation generation process. The experimental results showed that, after learning using NeuroSparse, the FC matrix achieved state-of-the-art performance in ASD diagnosis using only a simple multilayer perceptron, indicating its wide-ranging application potential. The code is available at https://***/yangshuqigit/NeuroSparse. © 2024 IEEE.

关键词： Unsupervised learning

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel state Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Bioinspired Sensing of Undulatory Flow Fields Generated by Leg Kicks in Swimming

arXiv

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arXiv 2025年

作者： Wang, Jun Shen, Tongsheng Zhao, Dexin Zhang, Feitian Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China The National Innovation Institute of Defense Technology Beijing China National Innovation Institute of Defense Technology Beijing100071 China

The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming has not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer’s leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Adaptive Fuzzy Distributed Fault Detection for Large-scale systems with Overlapping Decompositions

Adaptive Fuzzy Distributed Fault Detection for Large-scale S...

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第33届中国控制与决策会议

作者： Dingguo Liang Ying Yang Rongchang Li State Key Lab for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of EngineeringPeking University

This paper focuses on the problem of distributed fault detection(FD) for large-scale dynamic systems which are modeled as the interconnection of several subsystems.A distributed estimator is constructed for each subsystem,in which an adaptive fuzzy approximator is embedded to learn the unknown nonlinear interconnection with the neighboring *** decompositions are considered in the FD scheme,thus allowing some state variables to be shared among different subsystems.A consensus filter is designed to help the shared state variable in each subsystem reach a common FD decision as well as improve the property of *** stability of the estimation error is analyzed and the sufficient conditions of the fault detectability are also *** results are provided to illustrate the effectiveness of the proposed method.

关键词： Distributed fault detection large-scale systems(LSSs) overlapping decompositions adaptive fuzzy approximator nonlinear systems

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Distributions of Tension and Torsion in a Threaded Connection

SSRN

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SSRN 2023年

作者： Shi, Tengfei Liu, Yang Liu, Zhao Liu, Caishan State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China Exeter Small-Scale Robotics Lab Engineering Department University of Exeter North Park Road ExeterEX4 4QF United Kingdom

Threaded connection is a common structure in engineering applications, and its load distribution plays a critical role on the static and dynamic performances of the system. Although Sopwith (1948) studied the tension distribution along a thread helix, a comprehensive model that includes the tension-torsion coupling in threaded connections is still missing. In this paper, we model the threaded connection by considering the bolt and nut as two linearly elastic bodies with a tension-torsion coupling deformation. Deflection of the thread is calculated by the modified theory of the trapezoidal cantilever beam model. Based on the compatibility condition of bolt-nut deformation, we establish a new equilibrium equations for the threaded connection with the tension-torsion coupling deformation. Our theoretical analysis shows that the proposed model agrees with the Sopwith’s theory when the lead angle of the threaded connections is sufficiently small. For large lead angles, the torque generated by the axial load is nonnegligible. In addition, we perform a three-dimensional finite element analysis to demonstrate the validity of the proposed model. Finally, influence of geometrical and material parameters on load distribution is investigated. The finding of this work may provide a new insight into the anti-loosening design for threaded connections. © 2023, The Authors. All rights reserved.

关键词： Finite element method

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Learning Pre-Grasp Manipulation of Flat Objects in Cluttered Environments using Sliding Primitives

Learning Pre-Grasp Manipulation of Flat Objects in Cluttered...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jiaxi Wu Haoran Wu Shanlin Zhong Quqin Sun Yinlin Li State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China Department of Automation University of Science and Technology of China Heifei China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing China Science and Technology on Thermal Energy and Power Laboratory Wuhan China

Flat objects with negligible thicknesses like books and disks are challenging to be grasped by the robot because of the width limit of the robot's gripper, especially when they are in cluttered environments. Pre-grasp manipulation is conducive to rearranging objects on the table and moving the flat objects to the table edge, making them graspable. In this paper, we formulate this task as Parameterized Action Markov Decision Process, and a novel method based on deep reinforcement learning is proposed to address this problem by introducing sliding primitives as actions. A weight-sharing policy network is utilized to predict the sliding primitive's parameters for each object, and a Q-network is adopted to select the acted object among all the candidates on the table. Meanwhile, via integrating a curriculum learning scheme, our method can be scaled to cluttered environments with more objects. In both simulation and real-world experiments, our method surpasses the existing methods and achieves pre-grasp manipulation with higher task success rates and fewer action steps. Without fine-tuning, it can be generalized to novel shapes and household objects with more than 85% success rates in the real world. Videos and supplementary materials are available at https://***/view/pre-grasp-sliding.

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Structural and temporal dynamics analysis on drug-eluting stents: History, research hotspots and emerging trends

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Bioactive Materials 2023年第5期23卷 170-186页

作者： Lili Tan Xiangxiu Wang Kungshan Yuan Tieying Yin Ruolin Du Li Shen Zhirong Zhu Suhua Yu Haijun Zhang Guixue Wang Key Laboratory of Biorheological and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular ImplantsModern Life Science Experiment Teaching Center at Bioengineering College of Chongqing UniversityChongqing400030China National United Engineering Laboratory for Biomedical Material Modification Shandong Rientech Medical Tech Co.LtdDezhouShandong251100China Department of Cardiology Zhongshan HospitalFudan UniversityShanghai Institute of Cardiovascular DiseasesShanghaiNational Clinical Research Center for Interventional MedicineShanghai200032China Shanghai Key Lab of Chemical Assessment and Sustainability School of Chemical Science and EngineeringTongji UniversityShanghai200092China Blue Sail Pioneer Lab JW Medical SystemsJiwei Shandong264200China JinFeng Laboratory Chongqing401329China

Purpose:This review aims to explore the history,research hotspots,and emerging trends of drug-eluting stents(DES)in the last two decades from the perspective of structural and temporal ***:Publications on DES were retrieved from *** bibliometric tools including CiteSpace and HistCite were used to identify the historical features,the evolution of active topics,and emerging trends on the DES ***:In the last 20 years,the field of DES is still in the hot phase and there is a wide range of extensive scientific *** addition,active topics emerge in different periods,as evidenced by a total of 41 disciplines,511 keywords,and 1377 papers with citation *** clustering anchored five emerging research subfields,namely#0 dual antiplatelet therapy,#3 drug-coated balloon,#4 bifurcation,5#rotational atherectomy,and 6#quantitative flow *** keyword alluvial map shows that the most persistent research concepts in this field are thrombosis,restenosis,etc.,and the emerging keywords are paclitaxel eluting balloon,coated balloon,drug-eluting balloon,*** are 7 recent research subfields anchored by reference clustering,namely#2 dual antiplatelet therapy,#4 drug-coated balloon,#5 peripheral artery disease,#8 fractional flow reserve,#10 bioresorbable vascular scaffold,#13 intravascular ultrasound,#14 biodegradable ***:The findings based on the bibliometric studies provide the current status and trends in DES research and may help researchers to identify hot topics and explore new research directions in this field.

关键词： Drug-eluting stents Dual antiplatelet therapy Drug-coated balloon Bioresorbable scaffold Bibliometric

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LARGE-EDDY SIMULATION OF SEPARATED FLOWS ON UNCONVENTIONALLY COARSE GRIDS

arXiv

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arXiv 2023年

作者： Bin, Yuanwei Park, George I. Lv, Yu Yang, Xiang I.A. Department of Mechanical Engineering The Pennsylvania State University University ParkPA16802 United States State Key Laboratory for Turbulence and Complex Systems Peking University Beijing100871 China Mechanical Engineering and Applied Mechanics The University of Pennsylvania PhiladelphiaPA19104 United States The State Key Lab of Nonlinear Mechanics Institute of Mechanics Chinese Academy of Sciences Beijing100190 China

We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at first glance. We distinguish this idea from very-large-eddy-simulation (VLES) and detached-eddy-simulation (DES), which require switching between RANS and LES formalism. LES on RANS grid is appealing because first, it requires minimal changes to a production code;second, it is more cost-effective than LES;third, it converges to LES;and most importantly, it accurately predicts flows with separation. This work quantifies the benefit of LES on RANS-like grids as compared to RANS on the same grids. Three canonical cases are considered: periodic hill, backward-facing step, and jet in cross flow. We conduct direct numerical simulation (DNS), proper LES on LES grids, LES on RANS-quality grids, and RANS. We show that while the LES solutions on the RANS-quality grids are not grid converged, they are twice as accurate as the RANS on the same grids. © 2023, CC BY.

关键词： Large eddy simulation

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An Accelerated Proximal Gradient-based Model Predictive Control Algorithm

arXiv

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arXiv 2021年

作者： Wang, Jia Yang, Ying The State Key Lab for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

In this letter, an accelerated quadratic programming (QP) algorithm is proposed based on the proximal gradient method. The algorithm can achieve convergence rate O(1/pα), where p is the iteration number and α is the given positive integer. The proposed algorithm improves the convergence rate of existing algorithms that achieve O(1/p2). The key idea is that iterative parameters are selected from a group of specific high order polynomial equations. The performance of the proposed algorithm is assessed on the randomly generated model predictive control (MPC) optimization problems. The experimental results show that our algorithm can outperform the state-of-the-art optimization software MOSEK and ECOS for the small size MPC problems. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control

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The enhanced photocatalytic sterilization of MOF-Based nanohybrid for rapid and portable therapy of bacteria-infected open wounds

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Bioactive Materials 2022年第7期7卷 200-211页

作者： Chaofeng Wang Yue Luo Xiangmei Liu Zhenduo Cui Yufeng Zheng Yanqin Liang Zhaoyang Li Shengli Zhu Jie Lei Xiaobo Feng Shuilin Wu Biomedical Materials Engineering Research Center Collaborative Innovation Center for Advanced Organic Chemical Materials Co-constructed by the Province and MinistryHubei Key Laboratory of Polymer MaterialsMinistry-of-Education Key Laboratory for the Green Preparation and Application of Functional MaterialsSchool of Materials Science&EngineeringHubei UniversityWuhan 430062China School of Life Science and Health Engineering Hebei University of TechnologyXiping Avenue 5340Beichen DistrictTianjin 300401China School of Materials Science&Engineering The Key Laboratory of Advanced Ceramics and Machining Technology by the Ministry of Education of ChinaTianjin UniversityTianjin 300072PR China School of Materials Science&Engineering State Key Laboratory for Turbulence and Complex SystemPeking UniversityBeijing 100871China Department of Orthopaedics Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022PR China

Open wounds are prone to infection and difficult to heal,which even threatens the life of patients because bacterial infections can induce other lethal complications without prompt *** commonly used antibiotics treatment for bacterial infections has been reported to cause globally bacterial resistance and even the occurrence of *** highly effective and antibiotic-independent therapeutic strategies are urgently needed for treating various kinds of bacteria-infected *** this work,we synthesized an eco-friendly nanohybrid material(ZnDMZ)consisting of a kind of biodegradable metal organic framework(MOF,ZIF-8)combined with Zn-doped MoS_(2)(Zn-MoS_(2))nanosheets,which exhibited great ability to kill bacteria and promote the healing of bacteria-infected wounds under 660 nm light *** underlying mechanism is that besides the local hyperthermia,the nanohybrid material exhibits enhanced photocatalytic performance than single component in it,i.e.,it can also be excited by 660 nm light to produce more oxygen radical species(ROS)due to the following *** one hand,the Zn doping can reduce the work function and the band gap of MoS_(2),which promotes the movement of photoexcited electrons to the surface of the *** the other hand,the combination between Zn-MoS_(2) and MOF induces the formation of a built-in electric field due to their work function difference,thus accelerating the separation of photoexcited electron-hole *** of the synergy of photocatalytic effect,photothermal effect and the released Zn ions,the synthesized ZnDMZ possessed a highly effective antibacterial efficacy of 99.9%against Staphylococcus aureus under 660 nm light irradiation for 20 min without *** vivo tests showed that this nanohybrid material promoted the wound healing due to the released Zn *** nanohybrid will be promising for rapid and portable treatment of bacteria-infected open wounds in pathogenic bacteria contaminated

关键词： Antibacterial Wound healing Bacterial infection MOF Photocatalytic

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