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Applications of artificial intelligence to lipid nanoparticle delivery

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

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1051-1053页

作者： Yichen Li Wenbin Yu Xinping Guan the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,This letter investigates the cooperative localization problem for multiple autonomous underwater vehicles(AUVs)in underwater anchor-free environments,where AUV localization errors grow without bound due to the accumulated errors in inertial measurements(termed accumulated errors hereafter)and the lack of anchors(with known positions).

关键词： AUVs underwater hereafter

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CenterRCNN: Two-Stage Anchor-Free Object Detection Using Center keypoint-Based Region Proposal Network

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Journal of Shanghai Jiaotong University (Science) 2023年 1-9页

作者： Liu, Chen Li, Wenfa Xu, Yunwen Li, Dewei Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

The classic two-stage object detection algorithms such as faster regions with convolutional neural network features (Faster RCNN) suffer from low speed and anchor hyper-parameter sensitive problems caused by dense anchor mechanism in region proposal network (RPN). Recently, the anchor-free method CenterNet shows the effectiveness of perceiving and classifing object by its center. However, the severe coincidence false positive problem between confusing categories caused by the multiple binary classifiers makes it still insufficient in accuracy. We introduce a two-stage network CenterRCNN to take advantage of both and overcome their shortcomings. CenterRPN is proposed as the first stage to give proposals that incorporate the center keypoint idea into RPN to perceive foreground objects, replacing dense anchor-based RPN. Then the proposals are classified by the multi-classifier of RCNN header that focuses more on the difference between confusing categories and only outputs the maximum probability one of them. To sum up, CenterRPN can eliminate the drawbacks of dense anchor based RPN in Faster RCNN, and multi-classifier’s classification ability is better than that of multiple binary classifiers in CenterNet. The experiment demonstrates that CenterRCNN outperforms both basic algorithms in the accuracy, and the speed is improved as compared with Faster RCNN. © 2023, Shanghai Jiao Tong University.

关键词： Object detection

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Indoor Vehicle Positioning Based on Multi-Sensor Data Fusion

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 77-85页

作者：王明阳时良仁李元龙 Department of Automation Shanghai Jiao Tong University、Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai 200240China

This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are *** fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit,we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter,*** then conducted simulations and experiments to examine the performances of the *** the experiment,the Kalman filtering hyperparameters are configured,and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via *** verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.

关键词： indoor vehicle positioning multi-sensor data fusion ultra-wideband linear Kalman filter extended Kalman filter

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Strong Structural controllability of Multi-Agent systems with Uncertain Connection Topologies

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Journal of systems Science & Complexity 2025年

作者： CHEN Qitian LI Shaoyuan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper investigates the strong structural controllability(SSC) of multi-agent systems(MASs) defined over Laplacian dynamics on directed graphs. The agents that are divided into leaders and followers are connected based on the consensus law and only leaders are manipulated by the external control input directly. In contrast to existing work, the topology of MAS contains uncertain interconnection edges between agents. The interconnection graph has a zero/nonzero/arbitrary structure, to handle the parameters uncertainty problem in MASs. Under this framework, the authors propose a color-changing rule based on the zero-forcing set(ZFS). A graph-theoretic sufficient condition of SSC is proved. Next, the authors investigate the leader selection problem to ensure the SSC of MASs. A greedy algorithm based on ZFS is introduced. In addition, the authors figure out that the redundant property of edges in MASs can help us decide the leader selection problem. A new heuristic algorithm of polynomial complexity is developed to select minimum leaders of the multi-agent ***, the authors support the proposed analysis with numerical results on various simulations.

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Current-Aided Multiple-AUV Cooperative Localization and Target Tracking in Anchor-Free Environments

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 792-806页

作者： Yichen Li Wenbin Yu Xinping Guan Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China IEEE

In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the accumulated errors in inertial *** paper aims to improve the localization and tracking accuracy by involving current information as extra *** first integrate current measurements and maps with belief propagation and design a distributed current-aided message-passing scheme that theoretically solves the localization and tracking *** on this scheme,we propose particle-based cooperative localization and target tracking algorithms,named CaCL and CaTT,*** AUV localization,CaCL uses the current measurements to correct the predicted and transmitted position information and alleviates the impact of the accumulated errors in inertial *** target tracking,the current maps are applied in CaTT to modify the position prediction of the target which is calculated through historical *** effectiveness and robustness of the proposed methods are validated through various simulations by comparisons with alternative methods under different trajectories and current conditions.

关键词： Anchor-free belief propagation cooperative localization current-aided target tracking

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C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5350-5367页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Layout Three-dimensional displays Image reconstruction Estimation Cameras Floors Cognition Transforms Training Semantics

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Connectivity-maintaining Consensus of Multi-agent systems With Communication Management Based on Predictive control Strategy

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 700-710页

作者： Jie Wang Shaoyuan Li Yuanyuan Zou Key Laboratory of System Control and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China IEEE

This paper studies the connectivity-maintaining consensus of multi-agent *** the impact of the sensing ranges of agents for connectivity and communication energy consumption,a novel communication management strategy is proposed for multi-agent systems so that the connectivity of the system can be maintained and the communication energy can be *** this paper,communication management means a strategy about how the sensing ranges of agents are adjusted in the process of reaching *** proposed communication management in this paper is not coupled with controller but only imposes a constraint for controller,so there is more freedom to develop an appropriate control strategy for achieving *** the multi-agent systems with this novel communication management,a predictive control based strategy is developed for achieving *** results indicate the effectiveness and advantages of our scheme.

关键词： Consensus energy-saving multi-agent system predictive control

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Non-uniform electron density estimation based on electromagnetic wave attenuation in plasma

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Chinese Physics B 2025年第1期34卷 381-386页

作者： Zhaoying Wang Lixin Guo Maixia Fu Shaoshuai Guo Yinsheng Li Key Laboratory of Grain Information Processing and Control(Henan University of Technology) Ministry of EducationZhengzhou 450001China College of Information Science and Engineering Henan University of TechnologyZhengzhou 450001China School of Physics Xidian UniversityXi’an 710071China

The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma *** to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the plasma sheath can be *** the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of *** this work,the relationship between electromagnetic wave attenuation and electron density is deduced *** attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron *** result is used to predict the electron density ***,the average electron density is obtained using a back-propagation neural network ***,the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation *** to traditional probe measurement methods,the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.

关键词： attenuation electromagnetic propagation plasma electron density

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