Most studies and research have tried to shed light on unemployment and employment in general, with less focus on the problems facing working women and the resulting social and economic consequences that threaten their human and professional lives. For women, working is one of the basic necessities for the sustainability of human life, and it constitutes an essential axis for both sexes and through it. It also gives a person the status and social status where the individual finds a ready opportunity to practice his intentions and desires, test his abilities and talents, and achieve his ambitions. The availability of full employment in general and the joining of women to the labor market is an important and fundamental factor in the sustai

Irisin is a myokine that controls energy metabolism by making adipose tissue brown. The present goal in doing this research was to determine how irisin concentration relates to other biochemical markers of disease. Hemodialysis (HD) for chronic kidney failure. The study included 30 individuals with end-stage renal disease on HD and 30 healthy subjects as the control group. The ages of all patients and the control group ranged from (25 to 60) years. The excluded criteria included patients with viral hepatitis and diabetes. Serum irisin concentration and the level of fasting serum glucose (FSG), urea, creatinine (Cr), total protein (TP), albumin (Alb), albumin to creatinine ratio (ACR), total cholesterol (TC), alanine aminotransferase (ALT),

Abstract

Objective(s): To assess the job satisfaction during of covid-19 among the nurses in respiratory isolation units of coronavirus disease.

Methodology: A descriptive cross-sectional design was carried out in four hospitals at isolation units of coronavirus disease from the period (21th December, 2021 to 27th January, 2022). A non-probability (convenience) sampling method consists of (300) nurse was selected convenience based on the study criteria. The tool used to measure the job satisfaction is Job satisfaction scale for clinical nursing (JSS-CN). This tool consists of two parts, the first part is for demographic information and consists of 8 items, and the second

Four species of insects, Carpophillus obsoletus Er., Carpophilus sp., Bitoma lycnformis Wall and Scatopse sp., were found in association with infected spathes of date palm with Mauginella scaettae Cav. The later fungus was the dominant species isolated in pure cultures both from diseased spathes and from contaminated insects. Bitoma lycriformis is the first record for Iraq.

Gastro oesophageal reflux disease is due to involuntary gastric contents reflux into the esophagus from stomach, causing heartburn and acid regurgitation symptoms. Genetic and environmental factors are important factors in the causation of disease. Human Leukocyte antigens considered as an excellent marker for population genetics analysis and disease association. This study aimed to investigate the association between HLA-DRB1-DQB1 haplotype that inherited in linkage and its association with gastro oesophageal reflux disease (GERD). Patients and healthy controls were prospectively recruited from gastrocolonoscope unit at Al-Kindy Teaching Hospital (Baghdad-Iraq) between January and July 2016. Forty Iraqi Arab Muslims patients with a history

To determine the relationship between chronic hepatitis B virus and autoimmune celiac disease, seventy five patients with chronic hepatitis B virus of ages (8-70) years have been investigated and compared with 50 healthy individuals. All the studied groups were carried out to measure antiGliadin antibodies IgA and IgG by ELISA test and anti-reticulin antibodies IgA and IgG by IFAT. There were significant elevation (P<0.05) in the concentration of AGA IgA and IgG antibodies compared to control group. The prevalence of AGA antibodies IgA and IgG was 8% and 9.33% respectively. There were a highly significant differences (P<0.01) between studies groups. The prevalence of antireticulin antibodies ARA IgA and IgG was 6.67% and 4.0% respectively i

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D