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The Anxiety Status of Chinese Medical Workers During the Epidemic of COVID-19: A Meta-Analysis
Pan Rong,Zhang Liqing,Pan Jiyang 대한신경정신의학회 2020 PSYCHIATRY INVESTIGATION Vol.17 No.5
Objective To analysis the anxiety status of Chinese medical workers during the epidemic of COVID-19 by meta-analysis method. Methods CNKI, VIP, WanFang Data, SinoMed, PubMed, Cochrane, EMBASE, MEDLINE, Scopus, Google Scholar and other databases were searched to collect literature on the anxiety status of Chinese medical workers during the epidemic of COVID-19. The retrieval time is from the database construction to 11/03/2020. Meta-analysis was performed on the included articles by using Stata 16.0 software. Results A total of 7 articles were included, with a total sample size of 7,741 people. Meta-analysis using the random effects model showed that the anxiety score of Chinese medical during the epidemic of COVID-19 was significantly higher than that of the national norm in each study, the difference was statistically significant [SMD (95% CI)=1.145 (0.705–1.584), p<0.001]. Conclusion The anxiety level of Chinese medical workers has increased significantly during the epidemic of COVID-19.
Liqing Zhang,Rong Pan,Yixian Cai,Jiyang Pan 대한신경정신의학회 2021 PSYCHIATRY INVESTIGATION Vol.18 No.5
Objective To investigate the prevalence of post-traumatic stress disorder (PTSD) in the general population during the COVID-19 pandemic by a systematic review and single-arm meta-analysis.Methods CNKI, PubMed, EMBASE, and MEDLINE were searched to collect literature on the prevalence of PTSD in the general population during the epidemic. The retrieval time is from the database construction to 31/08/2020. Meta-analysis was performed on the included articles by using Review Manger 5.3 and Stata 16.0 software.Results The prevalence of PTSD in the general population during the COVID-19 pandemic was 15% (95% CI: 11–21%, p<0.001).Conclusion The COVID-19 pandemic brought certain mental pain to general population, leading to a rise in the incidence of PTSD in a short time.
Optimization of long span portal frames using spatially distributed surrogates
Zhifang Zhang,Jingwen Pan,Jiyang Fu,Hemant Kumar Singh,Yong-Lin Pi,Jiurong Wu,Rui Rao 국제구조공학회 2017 Steel and Composite Structures, An International J Vol.24 No.2
This paper presents optimization of a long-span portal steel frame under dynamic wind loads using a surrogate-assisted evolutionary algorithm. Long-span portal steel frames are often used in low-rise industrial and commercial buildings. The structure needs be able to resist the wind loads, and at the same time it should be as light as possible in order to be cost-effective. In this work, numerical model of a portal steel frame is constructed using structural analysis program (SAP2000), with the web-heights at five locations of I-sections of the columns and rafters as the decision variables. In order to evaluate the performance of a given design under dynamic wind loading, the equivalent static wind load (ESWL) is obtained from a database of wind pressures measured in wind tunnel tests. A modified formulation of the problem compared to the one available in the literature is also presented, considering additional design constraints for practicality. Evolutionary algorithms (EA) are often used to solve such non-linear, black-box problems, but when each design evaluation is computationally expensive (e.g., in this case a SAP2000 simulation), the time taken for optimization using EAs becomes untenable. To overcome this challenge, we employ a surrogate-assisted evolutionary algorithm (SAEA) to expedite the convergence towards the optimum design. The presented SAEA uses multiple spatially distributed surrogate models to approximate the simulations more accurately in lieu of commonly used single global surrogate models. Through rigorous numerical experiments, improvements in results and time savings obtained using SAEA over EA are demonstrated.