Since its discovery in December 2019, corona virus was outbreak worldwide with very rapid rate, so it described by WHO as pandemic. It associated with severe acute respiratory distress syndrome, and can enter to cells through Angiotensin Converting Enzyme 2 (ACE 2) receptor which play an important role as regulator for blood pressure. Hypertension is a potential risk factor for sever acute respiratory syndrome COVID-19, and associated with high mortality rate as shown in many epidemiological studies. Moreover, specific antihypertensive medications that infected patients were receiving are not known; only data about renin-angiotensin-aldosterone system (RAAS) are available.  

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

Economics / University of Mosul

Abstract

The spread of the phenomenon of excessive buying in our society, especially for cosmetics, and at the same time increase the marketing deception by the organizations to take quick profit 'and accordingly was identified the problem of research in several questions, including:

Is there a significant effect of consumption culture on marketing deception?                                                &n

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

BACKGROUND: The number of coronavirus disease-19 (COVID-19) positive patients and fatalities keeps rising. It is important to recognize risk factors for severe outcomes. Evidence linking vitamin D deficiency and the severity of COVID-19 is tangential but substantial – relating to race, obesity, and institutionalization. OBJECTIVE: This study aims to examine the function of vitamin D and nutritional defense against infections such as COVID-19, which is the goal of this research. METHODS: This study includes observational cohort, cross-sectional, and case-control studies that estimated variances in serum levels of vitamin D among patients with mild or severe forms of COVID-19, and in patients who died or were discharged from hospit

On of the psychological disorders that the human encounters is guilty conscience, this feeling is negative and affects on the individual and on those around him and harms the psychological health of the individual.

      since the university students slice is one of the important slices in the community which the country dependes on their abilities , their energies and their faculties in the construction and development, the university professors and specialists in the field of education and psychology who are around them should help them in achieving psychological balance and adjustment with themselves and with others, the following research objectives have been set : 

Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.