News headlines are key elements in spreading news. They are unique texts written in a special language which enables readers understand the overall nature and importance of the topic. However, this special language causes difficulty for readers in understanding the headline. To illuminate this difficulty, it is argued that a pragmatic analysis from a speech act theory perspective is a plausible tool for a headline analysis. The main objective of the study is to pragmatically analyze the most frequently employed types of speech acts in the news headlines covering COVID-19 in Aljazeera English website. To this end, Bach and Harnish's (1979) Taxonomy of Speech Acts has been adopted to analyze the data. Thirty headlines have been collected f

Abstract:

              The hotel sector is one of the most vital sectors exposed to risks, and the authorities concerned with control must take their active and influential role in putting the hotel sector on the right track and compatible with the internationally approved approaches, and the importance of auditing the performance of the hotel sector in light of the (Covid-19) pandemic is embodied in the fact that it gives a clear and realistic picture to the management and regulatory bodies about the performance and activities of this sector and the shortcomings and deviations that must be addressed, and also helps government decision makers to ob

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.

We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.

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

  The Covid-19 virus disease has been shown to affect numerous organs and systems including the liver. The study aimed to compare lipid profiles and liver enzyme levels in individuals who had recovered from Covid-19 infection. To achieve the study objectives, liver Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), Alkaline phosphatase (ALP),  Random Blood Sugar (RBS) and Lipid profile which include cholesterol, High-Density Lipoprotein (HDL), Triglycerides (T.G), Low-Density Lipoprotein (LDL), and Very low-density Lipoprotein (VLDL) were determined.

One hundred twenty serum samples were obtained, of which fifty samples were utilized as the control healthy persons (not affected by COVID) and seventy samples came f

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre