Two samples of (Ag NPs-zeolite) nanocomposite thin films have been prepared by easy hydrothermal method for 4 hours and 8 hours inside the hydrothermal autoclave at temperatures of 100°C. The two samples were used in a photoelectrochemical cell as a photocatalyst inside a cell consisting of three electrodes: the working electrode photoanode (AgNPs-zeolite), platinum as a cathode electrode, and Ag/AgCl as a reference electrode, to study the performance of AgNPs-zeolite under dark current and 473 nm laser light for water splitting. The results show the high performance of an eight-hour sample with high crystallinity compared with a four-hour sample as a reliable photocatalyst to generate hydrogen for renewable energies.

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

ABSTRACT : Diabetes mellitus stands for a set of metabolic diseases that if they are not managed, they can initiate threatening life problems. This study hypothesizes that insulin-like growth factor-1 level can be used as a biomarker for early diagnosing renal problems in patients with type 2 diabetic disease. This study included 30 recently identified type 2 diabetic patients with acute renal malfunction who had an entrance in National Diabetic Center,AL-Mustansiriyah University.They have beenin the Center from October 2018 up to end of April 2019. Their age range has been (40-62) years. Comprehensive clinical investigationhas beencompleted for each patient to discount other diabetic complications like cardiac, neurologic and eye complicat

Background: Obesity is an evolving major health problem in both developed and developing countries. Traditional obesity indices as body mass index, waist circumference, waist-hip-ratio are well known measures to identify obese subjects, however, neck circumference as an index of upper-body obesity was found to be a simple and time-saving screening measure that can be used to identify obesity and the likelihood of developing metabolic syndrome in type 2 diabetic patients.
Aim: to investigate the relationship of neck circumference (NC) to obesity and metabolic syndrome in Iraqi subjects with type 2 diabetes.
Methods: The study group included 90 type 2 diabetic subjects (48 men and 42 women) aged 30-68 years. The subjects were those w