sina ghaffari

Healthcare workers are at the forefront of the fight against COVID-19 and are exposed to numerous risks and health consequences, including sleep disturbance. The present study aimed to investigate the prevalence of sleep disorders among HCWs during the COVID-19 pandemic using an umbrella review of meta-analyses.

Methods & Materials: 

Based on the guidance of PRISMA, literature was searched on the Web of Science, PubMed, Embase, Science Direct, Scopus, and Google Scholar (from the beginning of January 2020 to the end of March 2022). The random effects model was used for meta-analysis, and the I2 index was employed to ascertain heterogeneity among studies. Publication bias was investigated using the Begg test. Data were analyzed using STATA software version 14.

Initially, 561 studies were found after the primary literature search in the data resources, of which 27 eligible studies were selected for quality assessment and data extraction. The results showed that the prevalence of sleep disorders among HCWs during the COVID-19 pandemic was 38.27% (95% CI: 35.20- 41.01, I2= 74.2%, P= 0.008).

Based on the results of this review, the prevalence of sleep disorders among HCWs during the COVID-19 pandemic was relatively high. Therefore, these individuals should undergo routine screening for sleep quality and other mental health disorders.

As technological advances and environmental changes accelerate, technology-based corporations increasingly understand the need to forecast and comprehend future developments in the environment. Due to the technological conditions and desired criteria, it is not possible to use all methods of technology forecasting simultaneously. Therefore, it is necessary to select an effective and efficient method for forecasting specific technology. Considering the multiplicity of effective criteria on this choice and the difference in the importance between these criteria for choosing the appropriate technology forecasting method, the use of multi-criteria decision-making methods has been considered by the experts of this field. In this regard, this paper aims to provide a framework for selecting the appropriate technology forecasting method. For this purpose, firstly, by review the literature, the appropriate indicators for choosing the technology forecasting method were extracted. After the criteria were finalized with the help of the members of the relevant committee and using multi-criteria decision-making methods, the weight of each criterion was calculated and then the forecasting methods considered for aircraft engine were evaluated and prioritized. The results indicate that the Delphi forecasting method can be used as the best method for technology forecasting in this area.

Equal channel angular rolling (ECAR) is a severe plastic deformation method that covered plastic deformation of sheets. In this study, effects of ECAR route shave been investigated on the mechanical and microstructure properties of explosive-welded Al-Cu bimetal. At first, the explosive welding process has been performed to prepare the Al-Cu bimetals. Then, to relieve the stress and preparing of samples for ECAR process, the annealing process of the samples was done. Finally, the ECAR process was performed on the samples in two routes A and C. Results showed that yield and tensile strengths and micro hardness of ECARed samples significantly increased with increasing the number of passes, whereas their ductility decreased. The yield strength of bimetals has been increased from 80 MPa to 100 MPa and 130 MPa at the routes A and C, respectively. Also, with increasing the number of ECAR passes, the grain size of the ECARed bimetals decreased to about 2μm.