This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a

This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a

Objective: The study aimed to assess Leucine-rich alpha-2-glycoprotein-1 biomarker serum level in hospitalized COVID-19 patients. Methods: The case control study from multi-centers in Baghdad included 45 adult patients (19 females and 26 males) with COVID-19, diagnosed with a positive real-time reverse transcription polymerase chain reaction and excluded negative RT-PCR for COVID-19 and comorbidity conditions. Second group, was 43 control (20 females and 23 males). Results: This study found a decrease Leucine-rich alpha-2-glycoprotein-1 biomarker serum level in these patients and a significant difference in D. dimer, neutrophil count, lymphocyte count, and the neutrophil-lymphocyte ratio between the patients and controls at a P valu

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

A case-control study was performed to examine age, gender, and ABO blood groups in 1014 Iraqi hospitalized cases with Coronavirus disease 2019 (COVID-19) and 901 blood donors (control group). The infection was molecularly diagnosed by detecting coronavirus RNA in nasal swabs of patients.

The current research aimed to identify the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis. It also aims to identify the recovery and resuming plan to the business environment. The research followed the descriptive survey to find out the views of 34 internal auditors at various functional levels in the Kingdom of Saudi Arabia. Spreadsheets (Excel) were used to analyze the data collected by a questionnaire which composed of 43 statements, covering the tasks that the internal auditors can perform to face the COVID-19 crisis. Results revealed that the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis is to en