Worldwide, there is an increased reliance on COVID-19-related health messages to curb the COVID-19 outbreak. Therefore, it is vital to provide a well-prepared and authentic translation of English-language messages to reach culturally and linguistically diverse audiences. However, few studies, if any, focus on how non-English-speaking readers receive and linguistically accept the lexical choices in the messages translated into their language. The present study tested a sample of translated Arabic COVID-19-related texts that were obtained from the World Health Organization and Australian New South Wales Health websites. This study investigated to that extent Arabic readers would receive translated COVID-19 health messages and whether the t

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

The current research aims to analyze the role of participatory budgeting in improving performance, especially during crises such as the Covid-19 crisis. The research used the descriptive analytical method to reach the results by distributing 100 questionnaires to a number of employees in Iraqi joint stock companies and at multiple administrative levels. The research came to several important conclusions, the most important of which is that the bottom-up approach to budgeting produces more achievable budgets than the top-down approach, which is imposed on the company by senior management with much less employee participation. Additionally, there is a better information flow from the lower levels of the organization to the upper management

This study was set out to investigate factors affecting labor productivity on construction in the north of Iraq (Kurdistan) and to rank all the factors based on engineers, contractors, and designer’s opinions. 76 factors were analyzed based on previous literature and a pilot study. Next, by using online Google Form, a questionnaire form was created and sent to people who have experience in the construction industry. Afterward, the questionnaire form was sent to targeted people by email and social media apps. Factors were divided into nine groups “Management, Technical and Technology, Human and Workforce, Leadership, Motivation, Safety, Time, Material and Equipment, and External”. However, 202 respondents participated in this study,

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t