This paper examines how the GCC countries are dealing with COVID-19. This paper shows how this outbreak creates difficult conditions for the economy of the GCC countries. From February 2020, the number of confirmed cases continues to increase around the globe. This pandemic situation creates a very alarming situation for the economic cycle. GCC countries depend on hydrocarbon exports, and this outbreak not only reduces the epidemic but also reduces oil prices. In this situation, the GCC countries have a considerable challenge to maintain growth. As a matter of concern, this paper examines how the GDP of the GCC countries has decreased and how demands and supply shortages are occurring. The decrease in oil prices indicates that it takes time to cover these circumstances. Research also suggests that it seems difficult for oil prices to reach $45 per barrel. This pandemic is reducing travel, and this is the main cause of this shortfall. Thus, in this case, the GCC countries must manage the fiscal deficit with a fiscal stimulus. The government is already working on public financing and is providing a fiscal stimulus to the industry.

The purpose of this paper is to explore, visualize, and analyze the state-of-the-art research of sentiment analysis in the tourism industry during COVID-19 using bibliometrics. The information source is obtained from the Scopus database from January 1, 2020, to November 27, 2021. A sample of 1690 documents was obtained within this period. Topic areas with titles, keywords, and abstract criteria in sentiment analysis and travel and tourism were used as a reference for extracting results. There was a significant increase in papers published in 2020 and 2021 related to COVID-19 and sentiment analysis. The top five most active countries were the United States (310 documents and 1799 citations), followed by the United Kingdom (170 documents and 12674 citations), China (240 documents and 1297 citations), Australia (120 documents and 430 citations), and Germany (44 documents and 172 citations). The maximum number of occurrences was "social media (401)" followed by "sentiment analysis (149)", "tourism (116)", "Covid-19 (131)", and "Twitter (77)". This study provides an overview of sentiment analysis and shows the trends in the research and publication with the tourism industry.

Cognitive science borrows from fields such as Artificial Intelligence (AI) which helps in simulating and modeling the human brain. Recently, there has been an increase in the number of research and applications involving cognitive science and AI cooperation. Based on data extracted from the Scopus database. This paper uses the Visualization Of Similarities Method (VOS) between objects in VOSviewer 1.6.18 to look at, evaluate, and find relevant literature, trends, and the scope of research in the fields of cognitive science and AI. The results showed that the USA, the UK, China, Germany, and Canada are the top 5 most active countries in terms of publications. The University of Calgary came out on top of the active institution while the top funding source came from the National Science Foundation in the USA. The study's results will serve as a road map for future academics and researchers developing theory and practice in artificial intelligence and cognitive science.

Nowadays, harvesting water from the atmosphere is becoming a new alternative for generating fresh water. To the author’s best knowledge, no mathematical model has been established to describe the process of harvesting water from the atmosphere using porous materials. This research seeks to develop a new mathematical model for water moisture absorption in porous materials to simulate and assess harvesting atmospheric water. The mathematical model consists of a set of governing partial differential equations, including mass conservation equation, momentum equation, associated parameterizations, and initial/boundary conditions. Moreover, the model represents a two-phase fluid flow that contains phase-change gas–liquid physics. A dataset has been collected from the literature containing five porous materials that have been experimentally used in water generation from the air. The five porous materials include copper chloride, copper sulfate, magnesium sulfate, manganese oxides, and crystallites of lithium bromide. A group of empirical models to relate the relative humidity and water content have been suggested and combined with the governing to close the mathematical system. The mathematical model has been solved numerically for different times, thicknesses, and other critical parameters. A comparison with experimental findings was made to demonstrate the validity of the simulation model. The results show that the proposed mathematical model precisely predicts the water content during the absorption process. In addition, the simulation results show that; during the absorption process, when the depth is smaller, the water content reaches a higher saturation point quickly and at a lower time, i.e., quick process. Finally, the highest average error of the harvesting atmospheric water model is around 1.9% compared to experimental data observed in manganese oxides

Psychological and social implications due to COVID-19 pandemic are particularly relevant in Higher Education Institutions (HEI). The objective of this chapter is to examine and analyze the level of depression, anxiety, and stress between university students and employees at the HEI in Saudi Arabia due to COVID-19. The method used in this study is based on a narrative review of recent literature on related mental health symptoms and interventions due to the pandemic and a survey conducted on 51 students and 72 employees using the Patient Health Questionnaire for depression, Generalized Anxiety Disorder (GAD), and Perceived Stress Scale (PSS). Results show that psychological well-being is crucial to overcoming COVID-19 and avoiding mental illness and emotional coping. Higher levels of stress, anxiety, and depression were found to be higher in adults than adolescents. The study concluded that there is a need for mental health awareness regarding COVID-19, and it is suggested that there should be an online therapy session with people who have severe levels of stress, anxiety, and depression.

Childhood Obesity (CHO) is a global epidemic that has increased in recent years. According to the World Health Organization (WHO), 39 million children under five will be overweight or obese in 2020. In Saudi Arabia, the prevalence of obesity reached its peak at 35.5%. WHO also anticipated that by 2030, 30% of all deaths worldwide would be caused by lifestyle diseases. Extensive studies have been published on the fundamental causes of obesity, its treatment, and its prevention. As a result of the efforts and resources invested in childhood obesity research, control, and prevention, it is necessary to assess and analyze these studies and provide valuable insights to public health officials and healthcare institutions. Using the Scopus database, this paper uses bibliometric analysis to evaluate and identify trends and studies in childhood obesity in Saudi Arabia based on VOSviewer. Results revealed that the top 5 active affiliations in childhood obesity are King Saud University (165 documents), King Abdulaziz University (139), King Saud University for Health Sciences (47), Imam Abdulrahman Bin Faisal University(42), and Princess Nourah Bint Abdulrahman University (39). King Saud University sponsored the highest number of published documents. Out of 643 documents retrieved from the Scopus database, 42.5% were in Medicine and 11.8% in biochemistry. Understanding state-of-the-art childhood obesity is critical in planning future measures to control and prevent highrisk children early and future obesity complications. This study aims to provide insight for Saudi Arabian authorities to consider boosting health measures to reduce the incidence and prevalence of CHO.

. Wind Farm Layout Optimization (WFLO) is a complex multidisciplinary topic that requires a lot of expertise and is becoming an essential part of today's wind farm planning. Yet, selecting optimum wind farm locations is complex, time-consuming, and influenced by environmental factors and upstream turbines inflow wind. The present study attempts to develop an optimization approach based on the Genetic Approach (GA) to determine the most suitable wind turbine locations that maximize the net energy production while minimizing the Cost of Energy (COE) ($/kWh). The WFLO for the optimized objective function was performed for 500, 1000, and 1500 iterations. The best output was obtained for 1500 iterations with the lowest value for the objective function.

This paper introduces two more definitions of the conditional average entropy. Some properties of the three definitions are studied and some mistakes in the preceding literature are corrected.