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        Double displacement coupled forced response for electromechanical integrated electrostatic harmonic drive

        Xu, Lizhong,Zhu, Cuirong,Qin, Lei Techno-Press 2008 Structural Engineering and Mechanics, An Int'l Jou Vol.29 No.5

        In this paper, the double displacement coupled statics and dynamics of the electromechanical integrated electrostatic harmonic drive are developed. The linearization of the nonlinear dynamic equations is completed. Based on natural frequency and mode function, the double displacement coupled forced response of the drive system to voltage excitation are obtained. Changes of the forced response along with the system parameters are investigated. The voltage excitation can cause the radial and tangent coupled forced responses of the flexible ring. The flexible ring radius, ring thickness and clearance between the ring and stator have obvious influences on the double displacement coupled forced responses.

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        Double displacement coupled forced response for electromechanical integrated electrostatic harmonic drive

        Lizhong Xu,Cuirong Zhu,Lei Qin 국제구조공학회 2008 Structural Engineering and Mechanics, An Int'l Jou Vol.29 No.5

        In this paper, the double displacement coupled statics and dynamics of the electromechanical integrated electrostatic harmonic drive are developed. The linearization of the nonlinear dynamic equations is completed. Based on natural frequency and mode function, the double displacement coupled forced response of the drive system to voltage excitation are obtained. Changes of the forced response along with the system parameters are investigated. The voltage excitation can cause the radial and tangent coupled forced responses of the flexible ring. The flexible ring radius, ring thickness and clearance between the ring and stator have obvious influences on the double displacement coupled forced responses.

      • Application of PSO Algorithm Based on Improved Accelerating Convergence in Task Scheduling of Cloud Computing Environment

        Zhulin Li,Cuirong Wang,Haiyan Lv,Tongyu Xu 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.9

        Hadoop uses a reliable, efficient and scalable way to process data. It provides a good solution for dealing with big data. The task scheduler is the core component of Hadoop, and it is responsible for the managing and allocating the cluster resources. Therefore, scheduling algorithm directly affects the overall performance of Hadoop platform and utilization of cluster resource. Based on this, the improved accelerate particle swarm algorithm (IAPSO) is introduced to the cloud environment, and to solve the cloud task scheduling problem in this article. When we use particle swarm algorithm for task scheduling, the tasks are considered as particles, the resource pool is seen as the search space, and the process of finding the optimal solution is considered as a process of task scheduling. If all the sub tasks find the appropriate resources, then stop the iteration and allocate sub asks to the resource nodes. Finally, we simulate the experiment by using CloudSim software. When a single type of task is committed, our algorithm and the other three algorithms can also be used to complete the task scheduling process, and our algorithm is more efficient. But in practice, the cloud computing environment is facing multiuser, and the types of tasks are also varied. With the increase in the number of tasks, the advantage of the other three algorithms decreases gradually, but algorithm in this paper has been exhibited higher efficiency. In addition, with the increase of the number of nodes, task completed time of the algorithm in this paper is significantly less than the other three algorithms, and it has a steady downward trend. Therefore, IAPSO algorithm which is proposed in this paper is applied to solve task scheduling problem in the cloud environment, and it can effectively improve the efficiency of task scheduling.

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        Association of Perceived Stress With Depression Among Vaccinated Healthcare Workers During the SARS-CoV-2 Variant Outbreak: The Mediating Role of Compassion Fatigue

        Cai Xue,Li Guohong,Feng Haixia,Wang Xiaoyan,He Lijun,Luo Dan,Xu Cuirong,Huang Yingzi,Qiu Shanhu 대한신경정신의학회 2023 PSYCHIATRY INVESTIGATION Vol.20 No.4

        Objective Depression was common during coronavirus disease-2019 (COVID-19) pandemic, while the association of perceived stress with depression among vaccinated healthcare workers has not been investigated. This study aimed to address this issue.Methods We included a total of 898 fully vaccinated healthcare workers during the outbreak of severe acute respiratory syndrome coronavirus 2 Delta variant in Nanjing, 2021. Depression was ascertained by Patient Health Questionnaire-9, with a cut-off score of ≥5 indicative of mild-to-severe depression. Perceived stress, resilience, and compassion fatigue were assessed by Perceived Stress Scale-10, Resilience Scale-25, and Professional Quality of Life Scale version-5, respectively. Logistic regression analyses were used to estimate the odds ratio (OR) and 95% confidence interval (CI), along with subgroup and mediation analyses.Results The prevalence of mild-to-severe depression was 41.1% in vaccinated healthcare workers. The odd of mild-to-severe depression was increased with higher perceived stress. Compared with vaccinated healthcare workers with the lowest tertile of perceived stress, those with the highest tertile had increased odds of mild-to-severe depression by 120% (OR 2.20, 95% CI 1.46 to 3.31) after multivariable-adjustment. However, perceived stress was not associated with mild-to-severe depression in vaccinated healthcare workers with strong resilience, but was in those with weak resilience (p<sub>interaction</sub>=0.004). Further analysis showed that compassion fatigue mediated the relationship between perceived stress and mild-to-severe depression, with a mediating effect of 49.7%.Conclusion Perceived stress was related to an increased odd of mild-to-severe depression in vaccinated healthcare workers during COVID-19 pandemic, and this relationship might be explained by compassion fatigue.

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