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208 results on '"Zhang, Peiyun"'

12. School Bullying, Bystander Behavior, and Mental Health among Adolescents: The Mediating Roles of Self-Efficacy and Coping Styles.

Author

Wang, Xu, Shi, Leiyu, Ding, Yunzhi, Liu, Bowen, Chen, Hongbao, Zhou, Wei, Yu, Renjie, Zhang, Peiyun, Huang, Xin, Yang, Yong, and Wu, Zhijun

Subjects
SUICIDE risk factors, MENTAL depression risk factors, HIGH schools, VICTIMS, MENTAL health, SELF-efficacy, ADOLESCENT health, DATA analysis, RESEARCH funding, QUESTIONNAIRES, PSYCHOLOGICAL adaptation, ANXIETY, DESCRIPTIVE statistics, TEENAGERS' conduct of life, SURVEYS, BULLYING, CLUSTER sampling, STATISTICS, FACTOR analysis, SLEEP quality, DATA analysis software, COGNITION, SLEEP disorders, DISEASE risk factors, ADOLESCENCE
Abstract

While numerous studies have revealed the impact of different bullying behaviors, such as victimization and perpetration, on the psychological development of adolescents, the exploration of the correlates of positive/negative bystander behaviors and their potential underlying mechanisms remains scarce in China. The present study aims to compare the relationships between mental health and positive versus negative bystander behavior and to clarify whether self-efficacy and coping styles mediate the relationships between mental health and bullying dynamics. The current study was conducted on 11,734 students from 18 secondary schools in Suzhou, China (Meanage = 15.00, SDage = 1.47; 53.8% boys). The information on bullying victimization, perpetration, positive/negative bystander behaviors, as well as self-efficacy, coping styles and mental health variables (including depression, anxiety, sleep disturbance, suicide risk), were collected. Negative bystander behavior was positively associated with mental health problems, while positive bystander behavior was negatively associated with these factors. Also, further analysis showed that coping styles and self-efficacy mediated the relationship between different bullying behaviors and mental health outcomes. The results highlighted the comparison of the correlates of positive and negative bystander behaviors, which were comparably crucial to those of victims and perpetrators for prevention and intervention efforts. Promoting adaptive coping styles and self-efficacy to buffer the deleterious psychological consequences of bullying behavior in adolescents was also important. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Real-Time Automatic Configuration Tuning for Smart Manufacturing with Federated Deep Learning

Author

Zhang, Yilei, Li, Xinyuan, Zhang, Peiyun, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kafeza, Eleanna, editor, Benatallah, Boualem, editor, Martinelli, Fabio, editor, Hacid, Hakim, editor, Bouguettaya, Athman, editor, and Motahari, Hamid, editor

Published
2020
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27. Highly Efficient Oxygen Reduction N-Doped Carbon Nanosheets Were Prepared by Hydrothermal Carbonization.

Author

Liu, Yuchen, Zheng, Yajie, Zhang, Peiyun, and Hou, Junhua

Subjects
OXYGEN reduction, DOPING agents (Chemistry), CARBON-based materials, CATALYTIC activity, NANOSTRUCTURED materials, CHARGE exchange, HYDROGEN evolution reactions, NITROGEN
Abstract

A metal-free carbon catalyst is a kind of oxygen reduction catalyst with great prospects. It is an important material with potential to replace the traditional Pt catalyst. In this paper, a kind of irregular and ultra-thin carbon nanosheet (K180M-300-900) with high catalytic activity was synthesized by hydrothermal calcination using okra as a biomass and NH4Cl as an N source. The prepared nitrogen-doped metal-free catalyst with high pyridine-N and graphitic-N provides an extremely large number of active sites and has certain lattice defects. Ultra-thin carbon nanosheets promote sufficient contact between the catalyst and electrolyte, promote the diffusion of oxygen, and result in a faster transfer rate of electrons. The initial potential and half-slope potential of K180M-300-900 are 0.99 V and 0.82 V, respectively, which are comparable to those of 20% Pt/C. In addition, the stability and methanol tolerance of this catalyst (K180M-300-900) are better than 20% Pt/C, so it has great development potential and application value. This result provides a new method to prepare metal-free carbon materials that will take the place of traditional Pt catalysts. [ABSTRACT FROM AUTHOR]

Published
2024
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30. A Novel Deep-Learning-Based QoS Prediction Model for Service Recommendation Utilizing Multi-Stage Multi-Scale Feature Fusion With Individual Evaluations

Author

Zhang, Peiyun, Huang, Wenjun, Chen, Yutong, Zhou, MengChu, and Al-Turki, Yusuf

Abstract

With the rapid development of service computing, the demand for service recommendation is increasing. Quality of Service (QoS) prediction has been one of the key challenges for service recommendation. Existing deep learning-based methods have been proposed for QoS prediction, but further improvement of their neural network structures is still needed to improve the prediction accuracy. This work introduces multi-stage multi-scale feature fusion with individual evaluations to a deep learning model for accurate QoS prediction. In our model, non-negative matrix factorization is used to extract three-scale (i.e., global, local, and individual) features; distance similarity is exploited to find similar users and services; a multi-stage deep neural network is designed to fuse multi-scale features, where individual evaluations are input to each stage to correct QoS features. Finally, our model is compared with often-cited prediction methods, and the experimental results show that it can more accurately predict QoS than its peers. Note to Practitioners—Accurate QoS prediction is very helpful to recommend the most suitable services to users among many similar services. Affected by the sparsity of historical data, the accuracy of existing QoS prediction methods is often limited. The multi-scale features of users and services can be used to improve prediction accuracy. This work proposes a new QoS prediction method to do so. Specifically, it first extracts global and individual features through non-negative matrix factorization and uses distance similarity to obtain local features. Then, it proposes a new deep neural network that fuses the extracted multi-scale features in each learning stage, thereby improving QoS prediction for services recommendation.

Published
2024
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44. High-frequency repetitive transcranial magnetic stimulation alleviates the cognitive side effects of electroconvulsive therapy in major depression

Author

Chen, Xing, primary, Zhang, Tongtong, additional, Shan, Xiaoyan, additional, Yang, Qun, additional, Zhang, Peiyun, additional, Zhu, Haijiao, additional, Jiang, Fei, additional, Liu, Chao, additional, Li, Yanzhong, additional, Li, Weijun, additional, Xu, Jian, additional, and Shen, Hongmei, additional

Published
2022
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