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Qingda Granule Attenuates Hypertension-Induced Cardiac Damage via Regulating Renin-Angiotensin System Pathway

Chinese Journal of Integrative Medicine 2025年第5期31卷 402-411页

作者： LONG Lin-zi TAN Ling XU Feng-qin YANG Wen-wen LI Hong-zheng LIU Jian-gang WANG Ke ZHAO Zhi-ru WANG Yue-qi WANG Chao-ju WEN Yi-chao HUANGMing-yan QU Hua FU Chang-geng CHEN Ke-ji Department of Geriatrics Xiyuan Hospital of China Academy of Chinese Medical SciencesBeijing100091China Department of Traditional Chinese Medicine the Eighth Affiliated Hospital of Sun Yat-Sen UniversityShenzhenGuangdong Province518033China Xiyuan Hospital National Cardiovascular Clinical Medical Research Center of Traditional MedicineBeijing100091China Graduate School of Beijing University of Chinese Medicine Beijing100091China Cardiovascular Department the Second Affiliated HospitalShanxi University of Chinese MedicineTaiyuan030002China Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijing100090China Cadre 2 Ward Xinjiang Uygur Autonomous Region Institute of Traditional Chinese MedicineUrumqi830000China Academy of Integrative Medicine Fujian Univrsity of Traditional Chinese MedicineFuzhou350122China

Objective:To assess the efficacy of Qingda Granule(QDG)in ameliorating hypertensioninduced cardiac damage and investigate the underlying mechanisms ***:Twenty spontaneously hypertensive rats(SHRs)were used to develope a hypertension-induced cardiac damage *** 10Wistar Kyoto(WKY)rats were used as normotension *** were administrated intragastrically QDG[0.9 g/(kg·d)]or an equivalent volume of pure water for 8 *** pressure,histopathological changes,cardiac function,levels of oxidative stress and inflammatory response markers were ***,to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertensioninduced cardiac injury,a network pharmacology study was *** results were validated by Western blot,radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction,***:The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs(P<0.01).Histological examinations,including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac ***,echocardiography demonstrated that QDG improved hypertension-associated cardiac ***-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum(P<0.01).Conclusion:Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertensioninduced cardiac damage by regulating the angiotensin converting enzyme(ACE)/angiotensinⅡ(AngⅡ)/AngⅡreceptor type 1 axis and ACE/AngⅡ/AngⅡreceptor type 2 axis.

关键词： blood pressure cardiac damage hypertension Qingda Granule renin-angiotensin system

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control Strategy of Electrolytic Capacitor-Less Multi-port Converter for Suppressing the Influences of Low-Frequency DC-Link Current Ripple

Control Strategy of Electrolytic Capacitor-Less Multi-port C...

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Smart Power & Internet Energy systems (SPIES), International Conference on

作者： Zihong Zhang Zhijian Fang Yuangeng Xia Hanlin Dong Haojiang Yue School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Multi-port Converter (MPC) gets growing applications due to its advantages of flexible control mode, high power density, bidirectional power delivery capability, etc. However, the inherent instantaneous power difference between each port will generate significant low frequency dc-link current ripple, which degrades the operational stability of the system. To suppress the influence, the mechanism of dc-link current ripple is analyzed. And then, a compound control strategy based on the repetitive controller (RC) plus a PR controller is adopted according to the ripple characteristics for the electrolytic Capacitor-Less Multi-port Converter. The developed current control strategy in this paper can achieve a minimum steady-state error while maintaining a relatively fast transient response. Finally, to validate the proposed strategy, a simulation is also built and tested. The simulation results validate the theoretical analysis.

关键词： Transient response Power system measurements Simulation Power system dynamics Power system stability Frequency conversion Stability analysis

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Trajectory Tracking for Directional Drilling in Underground Coal Mine Using Robust Model Predictive control 26

Trajectory Tracking for Directional Drilling in Underground ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Wu, Jiajun Lu, Chengda Li, Hao Wei, Hongchao Wu, Min School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi'an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi'an710077 China China Coal Research Institute Beijing100013 China

ISBN: (纸本)9798331521950

This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension model is obtained by the linearization of a drilling tool kinematic model through the Taylor series expansion in the borehole depth domain. Then, in view of the influence of the uncertainty of the drilling tool slope and external interference, a robust model predictive control method is introduced in the form of an optimal control problem. A sufficient condition is obtained to calculate the corresponding controller gain matrix on the premise of satisfying the stability of the closedloop control system and the H∞ performance index. At last, the effectiveness of our method is illustrated through simulation analysis. Compared with model predictive control, robust model predictive control directly incorporates the uncertainty of the drilling tool slope and external interference into the control design, enabling it to better adapt to the complex and variable underground coal mine environment. © 2025 IEEE.

关键词： Predictive control systems

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Broad-Deep Network-Based Fuzzy Emotional Inference Model with Personal Information for Intention Understanding

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IFAC-PapersOnLine 2023年第2期56卷 7071-7076页

作者： Min Li Luefeng Chen Min Wu Min Ding Kaoru Hirota Witold Pedrycz School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Tokyo Institute of Technology Yokohama 226-8502 Japan Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6R 2G7 Canada

A broad-deep fusion network-based fuzzy emotional inference model with personal information (BDFEI) is proposed for emotional intention understanding in human-robot interaction. It aims to understand students’ intentions in the university teaching scene. Specifically, feature extraction is carried out by convolution and maximum pooling, and then the ridge regression algorithm is used for emotional behavior recognition, which reduce the influence of the complex structure and slow network updates in deep learning. Multivariate analysis of variance is used to select the key personal information affecting the intention and obtain the coefficient of influence degree. Finally, fuzzy inference is used to understand the intention. According to the recognition results, the accuracy on FABO database of our proposal is 1.89%, 12.21% and 0.78% higher than those of the Residual Network combined with geodesic flow kernel (ResNet-101+GFK), a fuzzy deep neural network with sparse autoencoder (FDNNSA), and an affect recognition on a video-skeleton of bimodal information with a hierarchical classification fusion strategy (HCFS), respectively, indicating that our proposal can effectively capture the emotional intention of students in the teaching scene.

关键词： Convolution Neural Networks Broad Learning Emotional Intention Human-Robot Interaction

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Stability Analysis of Discrete Networked systems with Network Induced Delay and Malicious Packet Dropout Based on a Matrix Transformation Method

Stability Analysis of Discrete Networked Systems with Networ...

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Chinese control Conference (CCC)

作者： Meng-Ying Zhou Wen-Hu Chen Chuan-Ke Zhang Ya-Xin Hou Ke-You Xie School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

This paper is concerned with the stability of discrete-time networked control systems with network induced delay and malicious packet dropout. Firstly, network induced delay and malicious packet dropout are analyzed, and the data packet dropout is converted into the change rate of time delay. Secondly, the functional of time delay and change rate of time delay is constructed, and some summation terms are generated when calculating the functional forward difference. Moreover, the auxiliary-function-based summation inequality and reciprocally convex matrix inequality are used to estimate the resulting summation terms. Then, a less conservative stability criterion for discrete networked systems with network delay and data packet loss is established. Finally, the validity of the proposed stability criterion is illustrated by a numerical example.

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Group Consensus of Multi-agent systems with Additive Noises and Multiplicative Noises

Group Consensus of Multi-agent Systems with Additive Noises ...

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Chinese automation Congress (CAC)

作者： Haoxiang Qin Chuanjian Li Xiaofeng Zong School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

In this paper, we study the group consensus problem of multi-agent systems with additive noises and multiplicative noises. The multi-agent systems are composed of two sub networks affected by additive noises and multiplicative noises, respectively. A consensus protocol is designed to guarantee the group consensus. Based on this protocol, the mean square weak consensus condition and mean square strong consensus condition are obtained by algebraic graph theory and stochastic stability theory. Finally, the numerical simulations show the effectiveness of the group consensus protocol in this paper.

关键词： Additive noise Differential equations Numerical simulation Stability analysis Consensus protocol Thermal stability Numerical stability

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Exponential Stability Analysis for Delayed Neural Networks via A Cubic Function Negative-Determination Lemma

Exponential Stability Analysis for Delayed Neural Networks v...

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Chinese control Conference (CCC)

作者： Wen-Xuan Zhao Yun-Fan Liu Yu-Long Fan Chuan-Ke Zhang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan P. R. China

This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional (LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double integral state is established, which introduces more delayed states and has less conservatism. In the LKF's derivative, the function has high order of delay due to the existence of exponent. Thus, in order to obtain tractable linear matrix inequalities, three state vectors are used to reduce the order of the function to cubic. Secondly, to achieve the negative-definiteness requirement, a negative-determination lemma for cubic functions with less conservatism is employed. Then, a less conservative delay-dependent stability criterion for neural networks with time-varying delays is established. Finally, the validity of the proposed delay-dependent stability criterion is illustrated by two numerical examples.

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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Emotion Recognition via Environmental Context and Human Body

Emotion Recognition via Environmental Context and Human Body

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Industrial Cyber-Physical systems (ICPS)

作者： Cheng-Shan Jiang Zhen-Tao Liu School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

To promote the humanized interactive experience of the intelligent device and system, emotional intelligence has become a popular research field in the human-machine interaction. The previous research on emotion recognition based on computer vision has mostly been carried out by analysing facial expression or body posture, and psychological studies show that scene context also contributes some important information on emotion recognition. In addition, most context-aware emotion recognition studies focus on exploring the relevance analysis of environmental semantics, but the influence of feature encoder on semantic information embedding has not been fully discussed. In this paper, we proposed a Global Semantic Feature Enhancement-Dual Stream Densely Connected Network (GSFE-DSDCN) to enhance global semantic information learning from the perspectives of dimension and spatial. Densely connected pattern is introduced to concatenate the shallow and deep layers output, which fuses the semantic information of low-dimensional geometric features and high-dimensional abstract context features together. The Global Multi-Scale Feature Recalibration (GMSFR) module expands the receptive field in spatial, which effectively improves the global semantic features extraction capability of feature encoder. We evaluate the proposed method on the EMOTIC data set, and experimental results are shown to be competitive with the state-of-the-art algorithms.

关键词： Human computer interaction Emotion recognition Computer vision Fuses Biological system modeling Semantics Psychology

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Event-Triggered control of Networked System Considering Denial of Service Attack

Event-Triggered Control of Networked System Considering Deni...

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Chinese control Conference (CCC)

作者： Ting-Wei Zhang Yu-Long Fan Chuan-Ke Zhang School of Automation Chinese University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Ministry of Education Engineering Research Center of Intelligent Technology of Geo-Exploration Wuhan P. R. China

This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service (DoS) attack. Firstly, the DoS attack interval is divided into attack interval and no attack interval, therefore, a switching-like event-triggered control can be established to reduce the waste of network resources and improve network efficiency. Then, the studied system is transformed into a time-delay system, and an improved stability criterion and controller design method are established by using Lyapunov-Krasovskii functional (LKF). Finally, the effectiveness of the proposed method is verified by a simulation example.

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