Search

Your search keyword '"Zhang, Wenyu"' showing total 2,985 results
Start Over Author "Zhang, Wenyu"
2,985 results on '"Zhang, Wenyu"'

58. Effect of cardiac rehabilitation therapy on depressed patients with cardiac insufficiency after cardiac surgery

Author

Zhang Wenyu, Zhu Guangjian, Li Beibei, Chen Chen, and Zhu Yingzhi

Subjects
cardiac rehabilitation therapy, cardiac surgery, anxiety and depression, cardiac autonomic function, cardiac insufficiency, Medicine
Abstract

This study aims to analyze the effect of cardiac rehabilitation therapy on cardiac autonomic nervous function in patients with cardiac insufficiency complicated with anxiety depression after cardiac operation to provide a reference for clinical practice. A total of 109 patients subject to cardiac operation in our hospital from January 2020 to March 2023 were enrolled as study subjects, including 50 patients who received conventional rehabilitation therapy (control group) and 69 patients who received cardiac rehabilitation therapy (research group). Before and after treatment, the left ventricular ejection fraction (LVEF) and central venous pressure (CVP) were determined, and the level of N-terminal pro-B-type natriuretic peptide (NT-proBNP) was measured. Low frequency/high frequency (LF/HF), standard deviation of normal to normal (SDNN), and root mean of successive square differences (RMSSD) were measured by a multi-lead ECG system. Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), Pittsburgh Sleep Quality Index (PSQI), Activity of daily living (ADL), and Barthel Index (BI) were applied for corresponding investigations, as well as the 6-min walk test (6MWT). After treatment, the research group showed higher LVEF, CVP, LF/HF, SDNN, and RMSSD, and lower NT-proBNP, SAS, and SDS than the control group (P < 0.05). Significantly elevated ADL score, BI, and 6MWT and reduced PSQI were observed in both groups after treatment, with more remarkable changes in the research group (P < 0.05). In conclusion, cardiac rehabilitation therapy effectively improved the cardiac function of patients with cardiac insufficiency complicated with anxiety and depression after the cardiac operation and alleviated their negative emotions.

Published
2023
Full Text
View/download PDF

59. Study on signal transmission mechanism of arbuscular mycorrhizal hyphal network against root rot of Salvia miltiorrhiza

Author

Song Han, Li Na, Zhang Rongchao, Hu Xiuqin, Zhang Wenyu, Zhang Bo, Li Xinpeng, Wang Zhen, and Xin Jie

Subjects
Medicine, Science
Abstract

Abstract To explore the signal transmission mechanism of the arbuscular mycorrhizal network against root rot of Salvia miltiorrhiza. In this experiment, the arbuscular mycorrhizal hyphal network was established among Salvia miltiorrhiza plants, and a two plant three-compartment culture model was established. The root of the donor Salvia miltiorrhiza was inoculated with the pathogenic fungi Fusarium solani. The changes of hormone signals such as jasmonic acid and salicylic acid and the expression of related defense genes in the recipient Salvia miltiorrhiza plants in different periods were measured, to study the underground disease resistance signal transmission mechanism among medicinal plants. Salvia miltiorrhiza can transmit the signal of resistance to root rot through the jasmonic acid pathway; When plants suffer from disease stress, the content of JA increases significantly, and the increase of JA content will inhibit the content of SA in plants; The gene expression of PR-10 gene in the roots of Salvia miltiorrhiza with arbuscular mycorrhizal network infected by pathogenic fungi was 17.56 times higher than that inoculated only with pathogenic fungi; Changes in hormone content will also cause changes in the expression of related defense genes, such as SnRK2 is inhibited by ABA in the signal transduction pathway, while JA and ABA show antagonistic changes after inoculation of pathogenic fungi in Salvia miltiorrhiza, so JA may positively regulate the expression of SnRK2 gene. Plants can transmit signals through AM hyphal network after being stressed by the pathogen Fusarium solani. In the arbuscular mycorrhizal hyphal network, JA has important significance for the signal transmission of resistance to root rot and disease resistance of Salvia miltiorrhiza, which can make Salvia miltiorrhiza ready for stress resistance and improve the stress resistance of Salvia miltiorrhiza. This experiment is of great significance to further analyze the signal transmission mechanism of the arbuscular mycorrhizal hyphal network.

Published
2023
Full Text
View/download PDF

60. An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series

Author

Garg, Astha, Zhang, Wenyu, Samaran, Jules, Ramasamy, Savitha, and Foo, Chuan-Sheng

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Several techniques for multivariate time series anomaly detection have been proposed recently, but a systematic comparison on a common set of datasets and metrics is lacking. This paper presents a systematic and comprehensive evaluation of unsupervised and semi-supervised deep-learning based methods for anomaly detection and diagnosis on multivariate time series data from cyberphysical systems. Unlike previous works, we vary the model and post-processing of model errors, i.e. the scoring functions independently of each other, through a grid of 10 models and 4 scoring functions, comparing these variants to state of the art methods. In time-series anomaly detection, detecting anomalous events is more important than detecting individual anomalous time-points. Through experiments, we find that the existing evaluation metrics either do not take events into account, or cannot distinguish between a good detector and trivial detectors, such as a random or an all-positive detector. We propose a new metric to overcome these drawbacks, namely, the composite F-score ($Fc_1$), for evaluating time-series anomaly detection. Our study highlights that dynamic scoring functions work much better than static ones for multivariate time series anomaly detection, and the choice of scoring functions often matters more than the choice of the underlying model. We also find that a simple, channel-wise model - the Univariate Fully-Connected Auto-Encoder, with the dynamic Gaussian scoring function emerges as a winning candidate for both anomaly detection and diagnosis, beating state of the art algorithms., Comment: IEEE Transactions on Neural Networks and Learning Systems

Published
2021
Full Text
View/download PDF

77. Graph-Based Multiobject Tracking with Embedded Particle Flow

Author

Zhang, Wenyu and Meyer, Florian

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Multiagent Systems, Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract

Seamless situational awareness provided by modern radar systems relies on effective methods for multiobject tracking (MOT). This paper presents a graph-based Bayesian method for nonlinear and high-dimensional MOT problems that embeds particle flow. To perform operations on the graph effectively, particles are migrated towards regions of high likelihood based on the solution of a partial differential equation. This makes it possible to obtain good object detection and tracking performance with a relatively small number of particles even if object states are high dimensional and sensor measurements are very informative. Simulation results demonstrate reduced computational complexity and memory requirements as well as favorable detection and estimation accuracy in a challenging 3-D MOT scenario., Comment: 6 pages, 2 figures. To be published in Proc. IEEE RadarConf-21

Published
2021

78. Torque Ripple Reduction of Permanent Magnet Synchronous Motor Based on Least Mean Square Algorithm

Author

Shen, Mengyuan, Xie, Fang, Zhang, Wenyu, Zhang, Jinqiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hu, Cungang, editor, and Cao, Wenping, editor

Published
2023
Full Text
View/download PDF

79. Research on Multi-operating Control Strategy of Vehicle Motor Based on ALO

Author

Zhang, Wenyu, Xie, Fang, Shen, Mengyuan, Zhang, Jinqiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hu, Cungang, editor, and Cao, Wenping, editor

Published
2023
Full Text
View/download PDF

85. Research on Machine Learning-Based Multi-source Precipitation Data Fusion

Author

Guo, Hengliang, Fu, Yu, Yang, Yaohuan, Yue, Yuanyuan, Kou, Menggang, Zhang, Wenyu, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Fox, Bob, editor, Zhao, Chuan, editor, and Anthony, Marcus T., editor

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results