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Moderate red wine alleviates high-fat diet-induced atherosclerosis in ApoE^(-/-)mice via modulations of liver metabolism through gut microbiota remodeling

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Food Science and Human Wellness 2025年第4期14卷 1411-1423页

作者： Xuanxuan Chen Hong Yang Kaikai Li Jianhong Cao Xiaoyun Xu Siyi Pan Erhu Li College of Food Science and Technology Huazhong Agricultural UniversityWuhan 430070China Key Laboratory of Environment Correlative Dietology Ministry of EducationHuazhong Agricultural UniversityWuhan 430070China Hubei Key Laboratory of Fruit&Vegetable Processing&Quality Control Huazhong Agricultural UniversityWuhan 430070China Shangri-La Winery Co. Ltd.Diqing 674412China

Red wine has a good potential for alleviating atherosclerosis,but the mechanisms related to hepatointestinal circulation remain to be *** study showed that administration of a high-polyphenol red wine(16 mL/(kg·day))for 16 weeks significantly reduced the atherosclerotic lesion in high-fat diet-fed ApoE^(-/-)*** total cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels of plasma were lowered by 11.54%and 18.98%.The pro-inflammatory cytokines including interleukin-6(IL-6)and tumor necrosis factorα(TNF-α)levels were decreased by 27.59%and 31.92%.Red wine also reduced triglyceride(TG)level and lipid deposition in the liver,and increased the concentration of total bile acids(TBA).Untargeted metabolomics analysis indicated that red wine modulated the disorder of liver metabolism by regulating sphingolipid signaling pathway,sphingolipid metabolism,glycerophosphlipid metabolism,choline metabolism and bile secretion.16S rRNA sequencing revealed that red wine increased the abundance of Akkermansia and Bifidobacterium and reduced the abundance of Mucispirillum,Romboutsia,Lactobacillus,Bilophila and Blautia,along with the increased concentrations of short-chain fatty acids(SCFAs)in *** findings indicated that red wine could exert anti-atherosclerotic effect by regulating gut microbiota,restoring SCFAs,alleviating liver metabolic disorders.

关键词： Wine Atherosclerosis Gut microbiota Untargeted metabolomics Short chain fatty acids

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Bandwidth-Aware Transmission Scheduling and Event-Triggered Distributed MPC for Vehicle Platoons 41

Bandwidth-Aware Transmission Scheduling and Event-Triggered ...

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第41届中国控制会议

作者： Qiaoni Han Guowen Cheng Hongjiu Yang Zhiqiang Zuo School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper j ointly designs the communication and control schemes for vehicle platoons by taking into consideration of the limited communication and computing resources of *** at achieving the stable tracking of the member vehicles at a desired inter-vehicle distance and the same velocity,while improving the communication and computation efficiency,we propose a bandwidth-aware transmission scheduling(BATS) mechanism and an event-triggered distributed model predictive control(ET-DMPC) scheme for the longitudinal control of a vehicle ***,by introducing bandwidth-aware parameters,the triggering threshold for the event-triggered BATS mechanism is dynamically adjusted according to vehicle and bandwidth ***,an output-based ET-DMPC scheme is designed to ensure that the platoon tracks a reference velocity and maintains the desired inter-vehicle ***,extensive simulations are carried out and the results demonstrate the effectiveness of the proposed BATS mechanism and ET-DMPC scheme in terms of adaptive communication scheduling and low computational burden.

关键词： Vehicle Platoon Longitudinal control Communication Efficiency Computational Burden MPC

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Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling 17th

Learning from Noisy Labels with Coarse-to-Fine Sample Cred...

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17th European Conference on Computer Vision, ECCV 2022

作者： Zhang, Boshen Li, Yuxi Tu, Yuanpeng Peng, Jinlong Wang, Yabiao Wu, Cunlin Xiao, Yang Zhao, Cairong YouTu Lab Shenzhen China Tongji University Shanghai China Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783031250620

Training deep neural network (DNN) with noisy labels is practically challenging since inaccurate labels severely degrade the generalization ability of DNN. Previous efforts tend to handle part or full data in a unified denoising flow via identifying noisy data with a coarse small-loss criterion to mitigate the interference from noisy labels, ignoring the fact that the difficulties of noisy samples are different, thus a rigid and unified data selection pipeline cannot tackle this problem well. In this paper, we first propose a coarse-to-fine robust learning method called CREMA, to handle noisy data in a divide-and-conquer manner. In coarse-level, clean and noisy sets are firstly separated in terms of credibility in a statistical sense. Since it is practically impossible to categorize all noisy samples correctly, we further process them in a fine-grained manner via modeling the credibility of each sample. Specifically, for the clean set, we deliberately design a memory-based modulation scheme to dynamically adjust the contribution of each sample in terms of its historical credibility sequence during training, thus alleviating the effect from noisy samples incorrectly grouped into the clean set. Meanwhile, for samples categorized into the noisy set, a selective label update strategy is proposed to correct noisy labels while mitigating the problem of correction error. Extensive experiments are conducted on benchmarks of different modality, including image classification (CIFAR, Clothing1M etc.) and text recognition (IMDB), with either synthetic or natural semantic noises, demonstrating the superiority and generality of CREMA. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep neural networks

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control Parameter Adjustment and Transmission Power Optimization for Vehicle Platoons with Communication Outage 41

Control Parameter Adjustment and Transmission Power Optimiza...

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第41届中国控制会议

作者： Qiaoni Han Chang Liu Hongjiu Yang Zhiqiang Zuo School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The advantage of vehicle platoons is reflected in their tighter inter-vehicle ***,under the non-ideal communication environment,communication outage occurs which may cause the distance between adjacent vehicles too close to result in a collision *** the communication outage with predecessor following between vehicles in a platoon,and applying the constant time headway policy,firstly,this paper quantifies the relationship among headway time,control parameter and communication reliability probability while satisfying plant stability and string ***,given a communication reliability probability,the parameter space method is used to obtain the range of the control parameter,so as to ensure platoon ***,we optimize the transmission power of vehicles to minimize the worst outage probability by some transformation and the adoption of the Perron-Frobenius *** this way,an iterative update rule is presented to obtain the optimal transmission ***,the simulation results demonstrate the effectiveness of the proposed control parameter adjustment method and power optimization scheme.

关键词： Plant stability String stability Outage probability Parameter adjustment Power optimization

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Quasi Markov Simplex Optimization of Nonlinear Functional Parameters in Multivariable Collaborative Cascade control 41

Quasi Markov Simplex Optimization of Nonlinear Functional Pa...

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第41届中国控制会议

作者： Tangwen Yin Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Exposition to risk for the benefit of automatic control creates *** and robustness are two options to reduce the inherent fragility risk of safety-critical ***,time and resource parameters that characterize the agile responsiveness and robust adaptivity are difficult to be optimized due to multilevel coupling structures with different time *** propose the quasi Markov simplex optimization(QMSO) of nonlinear functional parameters in multivariable collaborative cascade control(MCCC) to improve agility and robustness for systems with hierarchical multivariable coordination and multiple *** verify if the singularly perturbed feedback and control with quasi Markovian jumps through optimal nonlinear functional parameters can achieve the multivariable collaborative cascade control equivalent to that of singular perturbation modeling and design without decomposing slow and fast *** in aviation show that the nonlinear functional parameters in MCCC can be estimated through QMSO to improve agility and robustness for the consistence of flight *** find that the simplex optimization equivalently establishes the nonlinear singularly perturbed feedback and control with quasi Markovian jumps,without having to realize singular perturbation modeling and design,and there is no need to decompose slow and fast *** conclusion,the quasi Markov simplex estimation of nonlinear functional parameters optimizes the hierarchical multivariable coordination under multiple timescales,so that the synthesized collaborative cascade control is capable to improve agility and robustness.

关键词： Agility Hierarchical Multivariable Coordination Multiple Timescales Nonlinear Aircraft control Robustness

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Distributed Secondary control of DC Microgrids with Operation Loss Reduction 43

Distributed Secondary Control of DC Microgrids with Operatio...

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43rd Chinese control Conference, CCC 2024

作者： Qiu, Maoxiang Zhang, Zhicheng Zuo, Zhiqiang Wang, Yijing Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

ISBN: (纸本)9789887581581

In DC microgrids, current sharing and voltage regulation are two main objectives for real-time control, while the operation loss reduction is typically achieved by steady-state optimization. However, the ratio of current sharing is generally determined by the result of the centralized optimization in the classical hierarchical control framework of DC microgrids. Such an issue brings insufficient capability in respond to the changes of photovoltaic power and stored energy in the solar-powered energy systems. To handle this, this work proposes a distributed control scheme for single-bus DC microgrids. Under the proposed controller, the objectives of current sharing, bus voltage regulation and the total operation loss (converter loss and line loss) reduction can be guaranteed simultaneously. Moreover, the constraints on line currents and bus voltage are tackled as well. Finally, simulations verify the performance of the proposed control scheme. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Microgrids

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Silicon Content control for Blast Furnace: Model-free DDQN-ICM Method

Silicon Content Control for Blast Furnace: Model-free DDQN-I...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Baocong Ding, Xuda Liu, Wei Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai200240 China

ISBN: (纸本)9798350303759

Silicon content control is critical to ensure the quality of molten iron and the stable operation of the blast furnace. The complex reactions and large uncertainty of the blast furnace make it hard to control. Several predictive control-based methods were already studied in Silicon content control. However, the requirements of prediction model design and short predictive horizon limit the generalization and long-term optimization of the methods. To tackle these issues, we propose a deep double Q-learning (DDQN) and intrinsic curiosity module (ICM) based Silicon content control method. First, the deep Q-learning framework employed in our approach eliminates the need for a prediction model and supports long-range simulations, thereby enhancing algorithm generalization and long-term optimization capabilities. Second, DDQN and ICM help to avoid the over-optimistic of action taking and improve exploration efficiency to tackle the large uncertainty of the blast furnace. Third, to ensure operational safety, we have designed a regulation strategy that incorporates ϵ-greedy exploration and ICM, mitigating the risks posed by exploration actions. Finally, we validate the effectiveness of our method using on-site data, demonstrating that DDQN-ICM achieves superior performance in terms of tracking accuracy and disturbance rejection. © 2023 IEEE.

关键词： Blast furnaces

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Reinforcement Learning with Hierarchical Graph Structure for Flexible Job Shop Scheduling

Reinforcement Learning with Hierarchical Graph Structure for...

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2023 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2023

作者： Zhang, Linli Li, Dewei Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Dept. of Automation Shanghai China

ISBN: (纸本)9798350309003

The flexible job shop scheduling problem (FJSP) is a NP-hard combinatorial optimization challenge, having extensive real-world industrial applications. For a given instance of FJSP, a scheduling solution need to be devised, which entails determining the appropriate machine for each operation and establishing the sequence in which operations are processed on a given machine, all while adhering to certain constraints. However, many of the methods are lacking in flexibility, unable to cope effectively with multi-relational operations and machine selection scenarios. This can make the representation of state and action challenging in practice, leading to a significant increase in decision complexity. This paper considers these issues by a hierarchical graph structure with a model that synergistically integrates two modules: the environment and the decision module. The environment module is characterized by a hierarchical graph neural network which defines the multi-relational FJSP instance where all machine and operation data are stored. The decision module incorporates the Actor-Critic networks, designed to train reasoning strategies and enhance decision performance, based on the states and rewards provided at each step by the environment module. The objective is to derive optimal scheduling strategies through interactions between the decision agent and the environment, targeting the minimum resources consumed or makespan. Numerical simulations validate the efficacy of the proposed approach, showing its potential to yield superior results and thereby enhance performance. © 2023 IEEE.

关键词： Reinforcement learning

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Extended State Observer-based Hybrid Dynamic Event-Triggered Consensus control with External Disturbances 24

Extended State Observer-based Hybrid Dynamic Event-Triggered...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Pei, Wenliang Hua, Changchun Cui, Hailong Zhao, Guanglei Ma, Zhuang The Institute of Electrical Engineering The Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Yanshan University Hebei China Tangshan University Hebei China

ISBN: (纸本)9798400710681

This paper solves the event-triggered robust consensus problem of disturbed multi-agent systems (MASs) in fully distributed fashion. First, a distributed extended state observer (DESO) is developed for appropriately estimating system states and external disturbances. Then, by utilising these estimates, a fully distributed event-triggering control protocol, that composes of an adaptive distributed controller to avoid using global information while maintaining desired consensus property, and a novel hybrid dynamic event-triggering mechanism (ETM) to save communication resources, is put forward for the MASs. It is notable that an auxiliary differential equation is incorporated in the triggering condition, with which, positive minimum interevent times (MIETs) are available to ease the hardware implementation, while being with adaptive coefficients, the proposed hybrid dynamic ETM can be independent of any global information. Finally, the obtained main results are testified via a numerical example. © 2024 Copyright held by the owner/author(s).

关键词： State estimation

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V2X Communication Assisted Hierarchical Path Planning for Connected and Automated Vehicles

V2X Communication Assisted Hierarchical Path Planning for Co...

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2023 China Automation Congress, CAC 2023

作者： Li, Jiahang Chen, Cailian Gao, Fengkun Yang, Bo Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai200240 China

ISBN: (纸本)9798350303759

Connected and Automated Vehicles (CAVs) have attracted increasing attention in intelligent transportation systems. An effective path planning enables the efficient operation of CAVs so that they can coordinate traffic flow and avoid accidents. This paper presents a framework of V2X communication assisted hierarchical path planning system for CAVs that aims to improve computational efficiency and safety performance. The proposed framework consists of two stages: pre-planning and online-planning. The pre-planning stage leverages the computing and storage capabilities of Roadside Units (RSUs) to generate and filter candidate trajectories for different driving scenarios. The online-planning stage adjusts the pre-planned trajectory based on the vehicle's driving risk index, which considers the distance and relative speed to the surrounding vehicles. The performance of effectiveness, safety, and timeliness of the proposed framework is evaluated and demonstrated by a simulation study in different scenarios. Compared with conventional methods, the proposed method improves the computational efficiency by 23% and reduces the collision rate by 13 %. © 2023 IEEE.

关键词： Vehicle to Everything

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