The post-Corona Covid-19 world is not the world before it, the problem of perception of personality traits with two axes: the characteristics of psychological and social compatibility, and the second aspect the mental disorder during the pandemic, and the accompanying precautions and prohibitions during the academic year 2020 AD. The aim of the research is to reveal the perception of the personal characteristics of Bisha University employees (students and faculty) during the Corona Covid-19 pandemic, and to reveal statistically significant differences in the perception of the personality traits of Bisha’s members during the Covid 19 according to the scientific qualification variables (female students -faculty members),  marital st

Prostate cancer is an important and potentially fatal disease in humans. Both genetic and environmental risk factors are associated with increased risk of prostate cancer among Asian pop

Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

Persuasion is an indispensable skill in everyday life; that is why, it has aroused researchers’ interest. This study aims to investigate the most frequently used persuasive strategies in texting WHO COVID-19 Virtual Press Conferences and explore how these strategies are employed to achieve persuasive messages.To this end, a text of WHO COVID-19 Virtual Press Conferences has been chosen randomly to be analyzed based on Dillard and Shen’s (2013) “Persuasive strategies in Health Campaigns”. A qualitative method has been adopted in analyzing the selected data to investigate the credibility and validity of the persuasive strategies used in such a domain. Findings have shown that most of the persuasive appeals based on the adopted mode

In the present study, an attempt has been made to study the change in water quality of the river in terms of turbidity during lockdown associated with COVID-19. Iraq announced the longest-ever lockdown on 25 March 2020 due to COVID-19 pandemic. 

In the absence of ground observations, remote sensing data was adopted, especially during this period. The change in the visible region's spectral reflectance of water in part of the river has been analyzed using the Landsat 8 OLI multispectral remote sensing data at Tigris River, Salah al-Din province (Bayji / near the refinery), Iraq. It was found that the green and red bands are most sensitive and can be used to estimate turbidity. Furthermore, the temporal variation in turbidity was a

<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

Abstract Depending on their protective properties against different cases of Colorectal Cancer (CRC), vitamins C, D, and E are the main focus of this research. CRC is one of the global public health concerns. 30 healthy individuals provided serum samples, whereas the group of CRC patients was divided into three, totaling 90 individuals. Group I consisted of 30 newly diagnosed cases of CRC. Group II 30 consisted of consisted of 30 CRC patients who were administered three cycles of chemotherapy. Group III consisted of 30 diagnosed CRC patients who also have non-alcoholic fatty liver disease (NAFLD). The concentrations and groups of vitamins C, D, and E were evaluated using ELISA. The levels of Vitamin C were significantly lower (p &l

       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

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