Feshbach-Villars oscillator (FVO) in Kaluza-Klein Theory (KKT)

This research investigates the relativistic quantum dynamics of spin-0 scalar massive charged particles via the relativistic Feshbach-Villars oscillator in the background of the Kaluza-Klein Theory. We solve the Feshbach-Villars equation in the abckground of a cosmic string spec-time in the context of the Kaluza-Klein and presented the eigenvalue solution. Afterward, we rewrite this system in the case of the Feshbach-Villars quantum oscillator and obtain the eigenvalue analytically. Finally, we study the interaction of the Feshbach-Villars equation and oscillator in a cosmic dislocation in the Som-Raychaudhuri in the context of the Kaluza-Klein Theory and solve the wave equation analytically. We analyze the influence of topological defect in the quantification of energy and wave function of the Feshbach-Villars oscillator and with the external fields in the last oneComment: arXiv admin note: text overlap with arXiv:2304.12496 (Accepted for publication In Nuclear Physics B

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization

The COVID-19 basic reproductive ratio using SEIR model for the Middle East countries and some other countries for two stages of the disease

Abstract Background The new coronavirus disease appeared at the end of 2019, and it is now a global problem over the world. There are multiple epidemiologic indicators used for discussing the spread of pandemics, one of these indicators is the basic reproductive ratio which indicates whether the pandemic is going to spread more or relax, and the aim of this work is estimating this ratio for the Middle East countries for two stages of the pandemic. Main body of the abstract We employ Runge–Kutta method on SEIR model to simulate the basic reproductive ratio values of SARS-CoV-2 disease by using the recorded data of the disease for two stages, up to date May 29, 2020, in the first stage and up to date September 7, 2020, in the second stage. We estimate the coefficient of exposing rate, the coefficient of infection rate, the coefficient of recovery rate and the coefficient of mortality rate of the new coronavirus disease in addition to the basic reproductive ratio values of the disease in the Middle East countries, namely Bahrain, Cyprus, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, the Syrian Arab Republic, the United Arab Emirates, Turkey and Yemen where we apply the SEIR epidemic model. Short conclusion We find that the values of the basic reproductive ratio of the new coronavirus disease based on the used model in the Middle East countries start from 1.5583 to 3.0395 in the first stage and from 1.0001 to 4.5757. Besides, we find that the problem of the new coronavirus disease in Lebanon and in the Syrian Arab Republic is not good at all in the recent stage based on the values of the basic reproductive ratio comparing with other Middle East countries. Also, we find that the value of the basic reproductive ratio for the second stage is near one; however, if we apply the method for the following stages, we find that the values return to be larger because lots of people in that stage and after did not follow the governmental procedures for stopping the spreading of the disease

Analysing of the sustainable development goals in Damascus University during Syrian crisis using the strategy in the university and the bibliometrics data from SciVal

Abstract Most countries strive to reach effective sustainable development policies, given the repercussions of this policy on many aspects, such as the economic growth of countries. The adoption of policies of sustainability by developing countries may lead to their development faster than expected. This research aims to study the strategies applied in one of the universities of developing countries and the sustainability policies adopted at that university which is Damascus University. The study focuses on the time during last four years of the Syrian crisis through several factors, with a focus on the analysis based on the SciVal and Scopus databases and the strategies applied by the university itself. In this research, we use the method of extracting and analysing the data of the sixteen sustainable development goals (SDGs) of Damascus University within Scopus and SciVal. We also analyse the strategies used in the university in order to reach some of the determinants of SDGs. By analysing Scopus and SciVal data, we find that the third goal of SDGs is the most widespread in terms of scientific research in Damascus University. We find that the application of such policies led to an important goal in the environment, which is the ratio of green space in Damascus University reaching to more than 63 percent of the total flat area of the university. In addition, we find that the application of sustainable development policies led to the generation of energy from renewable sources by 11% of the total electrical energy consumed at the university. The university has been able to reach lots of indicators of the sustainable development goals and it remains apply others

Scopus-Based Study of Sustainability in the Syrian Higher Education Focusing on the Largest University

Achieving an effective sustainable developmental policy is considered a primary goal in a large number of institutions around the world. The application of this policy in universities is reflected throughout the country, especially in developing and low-income countries. This research aims to analyse the sustainability policies adopted at Damascus University during the past 5 years of the Syrian crisis through several factors, with a focus on the analysis based on the SciVal and Scopus databases. We consider Damascus University as an example of an institution of a developing country. We use the method of extracting and analysing the data of the 16 sustainable development goals (SDGs) of Damascus University within Scopus. Based on Scopus and SciVal data, we find that Damascus University made a significant leap in the number of its research related to sustainable development in the year 2022, as these research studies constituted 46.0% of all published, abstracted, and indexed research studies in Scopus by Damascus University researchers. Also, by analysing the citation data which the SDG documents have received, we find that the citations resulted from these documents represent about 53% of the total citation of the university during the same time

Superconductors and the periodic penetration parameter: Defining and utilizing in diverse applications

There are various types of materials that have different levels of electrical conductivity, and one category is known as superconductors or superconducting materials. Superconducting materials are characterized by their complete lack of electrical resistivity. These materials are highly important due to their wide range of applications in electricity transmission, although they do have certain limitations. The Bardeen–Cooper–Schryver theory and the Ginzburg–Landau theory are two significant theories used to explain the nature of superconducting materials. Of particular interest in this study is the Ginzburg–Landau differential equation, which is considered a vital equation in this field. This equation belongs to a class of nonlinear differential equations. Our research focuses on simulating solutions to the Ginzburg–Landau equation under steady-state conditions. We conducted simulations for several superconducting materials, including aluminum, niobium, lead, tin, niobium germanide, niobium tin, vanadium silicate, lead hexa-molybdenum octa-sulfur, magnesium diboride, uranium triplatinum, potassium, barium copper oxide, yttrium, calcium copper oxide, and barium mercury. We define a new parameter of the superconductor conduction materials, which is the periodic parameter of the superconductor. By analyzing the periodic solutions obtained from the Ginzburg–Landau differential equation, we were able to determine the values of the periodic penetration parameters for each material. Notably, monatomic superconducting materials exhibited periodic penetration parameters in the range of tens of micrometers, while tetra- and penta-elements materials had values in the tens of nanometers. Superconducting materials of two or three different elements showed average values for these parameters. These findings provide valuable insights into the characteristics and behavior of various superconducting materials

Assessment and treatment of large tumor from the jaws in a 55-Syrian male patient: A case report

Large bone tumors can form in the upper and lower jaws of the mouth, leading to dental and jaw lesions. These tumors pose a significant challenge in performing dental prosthetics and restorative procedures in the affected jaws. This case report highlights a successful surgical intervention for a fifty-five-year-old Syrian man who presented with multiple bone tumors in the jaw bones. The surgery, performed at the dental clinic of the International University of Science and Technology, aimed to remove the tumors, allowing for future dental restorations. The surgical procedure was successful, and the tumorous lesions were examined and removed from both the upper and lower jaws. The jaws were then prepared for complete dental restorations. This case emphasizes the importance of timely intervention and surgical management for bone tumors in the jaws to restore oral function and improve quality of life