In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

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 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

To assess the impact of COVID‐19 on oral hygiene (OH) awareness, attitude towards dental treatment, fear of infection and economic impact in the Middle East.

The majority of used clothes represented a passion for brilliant
appearance and could be a reason for hiding body defects , as to avoid
criticism .
This may lead to purchase and wear un healthy or uncomfortable clothes
such as tide .As to appreciate the differences between wearing healthy clothes or
otherwise .
The study was carried out to assess healthy cloth awareness for university
girls as related to possibility of being subjected to harm caused by wearing tide
clothes .
The measurement items was determined and numbered ( 23 ). The answer
for these scale criteria was ( Always , Sometime ,Never ) for the weights (3,2,1)
. The scale was applied to a randomly selected sample of research community
that

          The research aims to identify the relationship between spatial ability  and the physical structure of concepts to the students of the Faculty of Education for Pure Sciences / Ibn al-Haitham، research involved students from the third class / morning study for the year 2011/2012  totaling (98) male and female students ،distributed into three groups which were selected randomly . The number of students (26 males and females)  represented research sample after excluding repeaters and absentees، the research included two tests ; one test of spatial ability، which included (20) items and other test the physical structure of concepts، which included (12) items distributed into four domains ، the first (linking b

In this work we define and study new concept of fibrewise topological spaces, namely fibrewise soft topological spaces, Also, we introduce the concepts of fibrewise closed soft topological spaces, fibrewise open soft topological spaces, fibrewise soft near compact spaces and fibrewise locally soft near compact spaces.