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Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25% tested negative in both sample types at the time of this study and 53% of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients.

BMW and Daimler are both German international companies that deal with vehicles and motorcycles. In this article, we will analyze the two companies' financial performance and find out their positions. We will look at their financial data from 2016 to 2019 to determine their financial state, and include figures and tables for easier analysis, thus giving suggestions for potential improvement areas.

The Financial analysis of Hilton Worldwide Holdings Inc. has been conducted. The data was taken for the five years including 2021, 2020, 2019, 2018, and 2017. The data were gathered from the financial statements of the company. After gathering the data, methodology was set for the financial analysis of Hilton. The financial analysis was done due to ratios including Liquidity ratios, Leverage Ratios for Hilton, Asset Management (AM) Ratios, Profitability Ratios, and Market Value Measures. The status was then analyzed after the result of each ratio for the five years. It showed the performance of the company and its financial status in comparison with the other hotels in the market. There were loopholes found which need to be overcome soon by Hilton to stabilize the revenue. The impacts of COVID-19 on the Hilton and other hotel industries were discussed and suggestions were given for the stability of the economy through different surveys conducted in the world. Hilton shows a loss in recent years, but this loss was due to some circumstances, which compelled the company to incur a loss. The status of the company is improving, and it will grow again because the reasons due to which the company incurred a loss are solving. The company has good prospects therefore the investor's recommendations mentioned that the investor should invest in the industry because it will again increase the share price in near future.

This study is based on examining sustainable taxation policies internationally. For the purpose of this study 20 sources have been examined and research has been transformed into a meaningful study. This study also determines the importance of sustainability tax in the world and how it motivates the companies to decrease the activities related to carbon dioxide emissions.

This paper presents a graph-based grading system for Java introductory programming courses, eGrader. The assessment process undergoes two stages in succession. Namely, dynamically and statically. This analysis leads to producing detailed feedback reports to both students and instructors. The student report provides a detailed feedback on the submitted code with a total mark break down. In addition to showing the model solution, specific comments on syntax and semantic errors (if any) are provided. On the other hand, the automated class report is a comprehensive document that provides detailed analysis on all students' submissions. The success of eGrader is measured by four performance measures which are sensitivity (97.37%), specificity (98.1%), precision (98.04%) and accuracy (97.07%).

Learning how to program is a universal problem that is facing many students in introductory programming courses. This multinational problem created the need for an effective and easy to use learning system. The system introduced in this paper, Java Learning System using Dependence Graphs (JLearn-DG), teaches students the basic concepts of programming by creating the System Dependence Graph (SDG) for students program. The system defines four types of dependencies: control, method call, method library and data. It identifies the dependencies and relationships among all statements. When JLean-DG is compared to existing systems, it has two advantages: the ability to create the SDG in the presence of semantic-errors and the ability to create the dependencies among all statements in the program regardless of the execution. Based on our experimental evaluation, this tool has been an affective one and has good potential to teach programming.