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The article primarily focuses on the ineffectiveness of recent reforms to women's rights in Saudi Arabia, particularly in relation to the abolition of the male guardianship system. It argues that despite positive attention and perceptions of progress under Crown Prince Mohammed bin Salman al Saud, the reforms have not led to significant improvements in the lived experiences of Saudi women.

One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers' abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations. [ABSTRACT FROM AUTHOR]

Desert cities are special type of places that need extra environmental care and additional health planning during the process of growth and development. Special considerations and regards ought to be paid to health-related projects like building hospitals, primary health care (PHC) centers, emergency services, sanitation facilities, etc. In a country like Saudi Arabia, where deserts form a large part of the available biome, selecting which cities and places to focus on during health-related project development can be a difficult process, lacking proper ways of classifying and comparing the general health status of the population. While there are established indices to calculate other health-related qualities, like the Air Quality Health Index, there is no general health quality index. The article presented herein advocates an appropriate formula for a health quality index, HQI, as a tool for quantifying health quality for any given desert community. HQI is intended to offer a unique number, which expresses overall health quality at a certain desert locality, at a specified period of time, which is based on several quality parameters and health indicators. The objective of HQI is to turn complex health quality data into flat, simple information that is understandable and usable by health authorities, the public and desert community members. HQI depicts the composite influence of different public health quality parameters and communicates health quality information to the general public and legislative decision makers. It is intended to represent a reliable picture of the overall health quality within a particular community. [ABSTRACT FROM AUTHOR]

Background: Health policy and systems research (HPSR) can strengthen health systems and improve population health outcomes. In the Eastern Mediterranean Region (EMR), there is limited recognition of the importance of HPSR and funding remains the main challenge. This study seeks to: (1) assess the reporting of funding in HPSR papers published between 2010 and 2022 in the EMR, (2) examine the source of funding in the published HPSR papers in the EMR and (3) explore variables influencing funding sources, including any difference in funding sources for coronavirus disease 2019 (COVID-19)-related articles. Methods: We conducted a rapid scoping review of HPSR papers published between 2010 and 2022 (inclusively) in the EMR, addressing the following areas: reporting of funding in HPSR papers, source of funding in the published HPSR papers, authors' affiliations and country of focus. We followed the Joanna Briggs Institute (JBI) guidelines for conducting scoping reviews. We also conducted univariate and bivariate analyses for all variables at 0.05 significance level. Results: Of 10,797 articles screened, 3408 were included (of which 9.3% were COVID-19-related). More than half of the included articles originated from three EMR countries: Iran (n = 1018, 29.9%), the Kingdom of Saudi Arabia (n = 595, 17.5%) and Pakistan (n = 360, 10.6%). Approximately 30% of the included articles did not report any details on study funding. Among articles that reported funding (n = 1346, 39.5%), analysis of funding sources across all country income groups revealed that the most prominent source was national (55.4%), followed by international (41.7%) and lastly regional sources (3%). Among the national funding sources, universities accounted for 76.8%, while governments accounted for 14.9%. Further analysis of funding sources by country income group showed that, in low-income and lower-middle-income countries, all or the majority of funding came from international sources, while in high-income and upper-middle-income countries, national funding sources, mainly universities, were the primary sources of funding. The majority of funded articles' first authors were affiliated with academia/university, while a minority were affiliated with government, healthcare organizations or intergovernmental organizations. We identified the following characteristics to be significantly associated with the funding source: country income level, the focus of HPSR articles (within the EMR only, or extending beyond the EMR as part of international research consortia), and the first author's affiliation. Similar funding patterns were observed for COVID-19-related HPSR articles, with national funding sources (78.95%), mainly universities, comprising the main source of funding. In contrast, international funding sources decreased to 15.8%. Conclusion: This is the first study to address the reporting of funding and funding sources in published HPSR articles in the EMR. Approximately 30% of HPSR articles did not report on the funding source. Study findings revealed heavy reliance on universities and international funding sources with minimal role of national governments and regional entities in funding HPSR articles in the EMR. We provide implications for policy and practice to enhance the profile of HPSR in the region. [ABSTRACT FROM AUTHOR]

Patient‐reported outcomes (PROs) are closely related to the delivery of high‐quality care and services. Patient‐reported outcome measures (PROMs) are the tools used to measure the PROs. Despite the challenges and barriers associated with using PROs and PROMs, measuring PROs is valuable for a patient's health status and advancing evidence‐based medicine. Real‐world implementation of PROMs may especially open possibilities for healthcare systems under reform, such as Saudi Arabia. This paper highlights the concepts of PROs and PROMs. Moreover, it distinguishes between PROs and other concepts such as patient experience, quality of life, and patient satisfaction. It also explores the available literature in Saudi Arabia and the world regarding PROs and their role in improving healthcare systems. Last, this paper advocates for utilizing the national and comprehensive tools of PROMS in different levels and disciplines. Key points: Patient‐reported outcomes provide an opportunity to engage patients in their care, enhance shared decision making, and improve care effectively and safely.Integrating patient‐reported outcome measures (PROMs) in patient care has been associated with improving patient safety and patient experience and helping achieve more patient‐centered care.Related literature demonstrated some limitations that might hinder the effective implementation of PROMs, related to the integrity of data and lack of methodological standardization of PROMs data.Patient‐reported outcomes are poorly addressed within the Saudi literature, and the utilization of PROs is also underdeveloped and needs further consideration.There is an excellent opportunity for researching and implementing PROMs in the healthcare setting in Saudi Arabia, which is currently undergoing a major transformation. [ABSTRACT FROM AUTHOR]

Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is also exploring wind energy, leveraging its vast desert landscapes. These efforts are part of Saudi Arabia's broader strategy to become a global leader in renewable energy. This paper provides a detailed exploration of Saudi Arabia's ambitious journey from a fossil-fuel-dominated energy sector to a more sustainable, renewable-energy-driven future. Anchored in the broader context of global energy trends, the study emphasizes the critical shift toward renewable resources, with a particular focus on Saudi Arabia's unique position in this global movement. Key to this transition is Saudi Arabia's Vision 2030, a strategic framework that guides the country's renewable energy policies and initiatives. A comprehensive review of these policies, including other governmental and international collaborations that support renewable energy development, is offered. The current state of renewable energy in Saudi Arabia is assessed, including an overview of existing projects and production statistics. The paper also explores emerging technologies such as energy storage systems and smart grid solutions, emphasizing their role in Saudi Arabia's energy transition. An impact assessment is conducted to understand the environmental, economic, and social effects of this energy shift. The paper also includes a comparative analysis of other countries' renewable energy transitions, extracting lessons and best practices applicable to the Saudi context. Strategic recommendations and reflections on Saudi Arabia's future role in the global energy landscape are provided for stakeholders in energy policy, environmental planning, and sustainable development. [ABSTRACT FROM AUTHOR]

Sign language is an essential means of communication for individuals with hearing disabilities. However, there is a significant shortage of sign language interpreters in some languages, especially in Saudi Arabia. This shortage results in a large proportion of the hearing-impaired population being deprived of services, especially in public places. This paper aims to address this gap in accessibility by leveraging technology to develop systems capable of recognizing Arabic Sign Language (ArSL) using deep learning techniques. In this paper, we propose a hybrid model to capture the spatio-temporal aspects of sign language (i.e., letters and words). The hybrid model consists of a Convolutional Neural Network (CNN) classifier to extract spatial features from sign language data and a Long Short-Term Memory (LSTM) classifier to extract spatial and temporal characteristics to handle sequential data (i.e., hand movements). To demonstrate the feasibility of our proposed hybrid model, we created a dataset of 20 different words, resulting in 4000 images for ArSL: 10 static gesture words and 500 videos for 10 dynamic gesture words. Our proposed hybrid model demonstrates promising performance, with the CNN and LSTM classifiers achieving accuracy rates of 94.40% and 82.70%, respectively. These results indicate that our approach can significantly enhance communication accessibility for the hearing-impaired community in Saudi Arabia. Thus, this paper represents a major step toward promoting inclusivity and improving the quality of life for the hearing impaired. [ABSTRACT FROM AUTHOR]

Objectives: To map the current evidence about the health concerns and the potential solutions related to the Islamic pilgrimage to Mecca. Design: A scoping review was applied. Papers published in English between 2012 and 2023 were included but non‐human research and sources without any related data were excluded. Data charting and extraction were used to map the current evidence. Results: The total of 36 papers were included with the total number of pilgrims of 17,075,887. The majority of studies were published in the Asia Pacific region (36.11%) as original articles (88.89%). The health concerns were grouped into five main aspects. There were 7603 deaths recorded or about 44 incidences of deaths per 100,000 pilgrims during the pilgrimage. There were recorded 11,018; 6178; 3393; and 17,810 cases for communicable diseases; non‐communicable diseases; injuries and trauma; and health services (i.e., cardiac catheterization) and vaccination, respectively. Conclusion: Relating to the five health concerns, this study identified the top seven issues in each category (i.e., hypertension, influenza vaccination), except for the death record. Moreover, there were three solutions (for general health, non‐ and communicable‐diseases) presented. Stakeholders could use this evidence to improve healthcare quality particularly related to the annual Islamic pilgrimage to Mecca. [ABSTRACT FROM AUTHOR]

Scientometric studies play a crucial role in quantitatively assessing the impact and quantity of scholarly articles, providing a basis for policy-making and informed decision-making processes. Given the ongoing transformation within the Saudi scientific community across various domains, it is essential to establish a baseline for high-quality endodontic research. A comprehensive search in the PubMed database, using the keywords ["Saudi" OR "Saudi Arabia"] within the time frame of 2014 to 2021. The screening process involved evaluating the title and abstract of each article, with only those classified as endodontic articles included for analysis in this study. The analysis included factors such as the type of paper, the authors, the citations, and the year of publication. Featuring one or more authors affiliated with a Saudi dental institution, 70 papers were specifically categorized as endodontic papers. The most prevalent type of paper was case reports, accounting for 27 articles (28%), followed by literature reviews with 13 articles (18%). The number of authors ranged from one to ten, with a general trend of increasing publication rates over the years. In terms of citations, only four papers received more than 20 citations, while the majority of papers garnered between one and ten citations. Most articles in the field of endodontics exhibited low-level evidence. Therefore, it is recommended that the quality of research output and evidence be enhanced. [ABSTRACT FROM AUTHOR]

In the Kingdom of Saudi Arabia (KSA), qualitative research methods are infrequently employed, as researchers in the region are more accustomed to quantitative approaches, with a certain hesitancy to embrace qualitative methodology. This research endeavor focuses on exploring the impediments faced by individuals engaged in qualitative research within the Saudi context. To do so, I conducted semi-structured interviews with eight doctoral students and employed a qualitative case study design for this paper. Utilizing the MAXQDA software, I also applied thematic analysis to the data gathered from the interviews. The primary findings highlight three significant themes: (a) challenges related to organizational aspects, (b) difficulties stemming from social and cultural factors, and (c) obstacles specific to qualitative research practices. This paper, unique in its contribution to the region, addresses a wide range of issues faced by qualitative researchers to support and enhance their research endeavors. While this study holds relevance for researchers, its significance extends notably to policymakers, academics, and higher education institutions in the KSA. [ABSTRACT FROM AUTHOR]

The paper examines the global scientific literature on Molecular Docking (MD). MDis a keyapproachusedinbioinformatics to identify and developnovel compounds towards drug discovery. This study uses the bibliometric method to analyze scientific data covered in the Scopus database from 2013 to 2022 using MS Excel, R Studio, andVOS Viewer software. A total of 12173 documents on Molecular Docking were retrieved and considered for the study. The paper provides an in-depth evaluation of the research output of MD. The research found that MuthuS.was a most prolific author in MD scientific research, with 98 publications that received 1481 global citations. The most productivecountries in this field areIndia (4020 publications), followedbyChina (2675 publications), Saudi Arabia (1362 publications) and Egypt (1071 publications). The hot keywords in MD research are molecular modelling, molecular docking simulation, unclassified drug and controlled study, but Molecular Docking is the burning author keyword. The finding also shows that the publications are increasing consistently from 2013 onwards. Most articles have been published in the 'Journal of Molecular Structure'. As it is an emerging and a trending topic, it has scope for further studies. This study will benefit future researchers and practitioners worldwide in understanding the research pattern on MD and identifying the other key areas related to the topic. [ABSTRACT FROM AUTHOR]

The aim of this research paper is to engage with the ongoing scientific discourse surrounding the impact of electronic human resources management (EHRM) technology on organizational sustainability, performance, and innovation within the context of the dynamic Saudi Arabian hospitality industry. Drawing upon a quantitative research methodology, this study seeks to unveil the intricate relationship between the latent variable (e-HRM) and the dependent variables, namely, organizational innovation, organizational performance, and organizational sustainability. The systematic organization of literary sources and research approaches underpins the comprehensive nature of this study, which holds particular relevance against the backdrop of Saudi Arabia's ambitious Vision 2030 development plan. The plan envisions diversifying the economy, reducing dependence on oil, and fostering sustainable growth -- objectives that resonate strongly with the challenges and opportunities within the hospitality sector. The paper progresses logically, employing robust statistical software such as SPSS version 25 and SmartPLS 3.3.5 to rigorously evaluate and test the measuring and structural models. This meticulous approach includes hypothesis testing to assess indicators' reliability, convergent validity, and discriminant validity. The study meticulously examines a sample of 438 employees within the Saudi hospitality industry. Methodological tools, including detection analyses and correlation analysis, are deployed to ensure the integrity and accuracy of the data. The Saudi hospitality industry is strategically selected for its pivotal role in job creation, economic prosperity, and overall image projection. Empirical analysis forms the crux of this paper, revealing compelling results that underscore the positive and significant influence of e-HRM technologies on organizational innovation, organizational performance, and organizational sustainability. The model's robust fit, as evidenced by the SRMR value of 0.074 and the NFI score of 0.911, accentuates the reliability and validity of the research. Furthermore, the paper employs the blindfolding technique to assess the model's predictive validity, revealing effect sizes of 0.223, 0.109, and 0.439 for organizational innovation, organizational performance, and organizational sustainability, respectively. This research not only empirically confirms but also theoretically substantiates the pivotal role of e-HRM technologies in shaping organizational outcomes. By delving into the mediating relationship between organizational performance and organizational innovation, this study contributes significantly to understanding how e-HRM technologies can be a catalyst for organizational sustainability in the unique context of the Saudi hospitality industry. Beyond the academic realm, the findings provide actionable insights for policymakers, industry professionals, and stakeholders, aligning with the overarching goals of Saudi Vision 2030 to foster sustainable growth and development. [ABSTRACT FROM AUTHOR]

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of electronic advertising in Saudi Arabia. The main purpose of this research is to explore the impact of internet advertising on companies' visits to stores through an exploratory study. The systematization of literary sources and approaches for solving electronic advertising problems indicates that new mediating and moderating variables could have an impact on the relation between Internet advertising and visits to stores. In this research, the disposition to visit the point of sale is assimilated as a mediating construct rather than an implication with the product as a moderating variable. The relevance of this scientific problem decision is that this investigation of the consequences of electronic advertising for offline customer comportment in Saudi Arabia is unprecedented research that seeks to address this interesting question. The investigation of the role of online advertising and the impact of mediating and moderating variables on the visit to the store in the paper was carried out in the following logical sequence: the data were collected via an electronic survey. Of the 500 randomly selected Internet users in Saudi Arabia, only 350 responses were valid. This research used a structural equation model and multigroup analysis to examine the direct and indirect influences of variables. This paper presents the results of an empirical analysis that revealed a positive relation between internet advertising and visits to points of sale. The disposition to visit the point of sale mediates the relationship between Internet advertising and concrete visits to the store. The effect of the product moderates the effect of internet advertising on the disposition to visit the point of sale in Saudi Arabia. The research empirically confirms and theoretically proves that Saudi shoppers fine online advertising to be attractive when this advertising must have some actions and concepts flash. Therefore, Saudi directors should follow this form and use an effective mixture of content and animation. The e-shoppers who are involved are persons who have little engagement; for this reason, they are simply concerned about the tools of the publicity communication. [ABSTRACT FROM AUTHOR]

This paper questions the apparent hostility between Iran and Saudi Arabia and highlights its discursive construction. It explores the centrality of 'Muslimness' in both countries' discourses and how it both shapes and is shaped by their opposition. At the same time, it seeks to uncover how these discourses construct a specific regional and 'Muslim' dynamic. To do so, the paper draws on theories from both security and nationalism studies. The application of the theoretical framework was carried out over the 2010-2020 period through a discourse analysis of both primary and secondary sources. It is highlighted that Saudi Arabia resorts to a sectarian perspective, merging the 'Muslim' category with a 'Sunni' one, while Iran eludes the sectarian dimension and centers on the struggle against oppression and 'arrogant powers.' The paper concludes that, in the struggle over the definition of 'Muslimness,' both parties invest this label with different, but not opposing, attributes. While Saudi speeches express a closed and exclusive 'identity' defined by their understanding of religion and in direct opposition to Shias, Iranian speeches express an inclusive 'identity' based on 'Muslimness,' which is largely defined by the struggle against oppression. [ABSTRACT FROM AUTHOR]

Hybrid renewable energy systems (HRES) are gaining high interest in supplying electric energy for remote communities. Energy storage systems (ESS) are utilized by green autonomous HRESs to accommodate the variability of renewable resources such as wind and solar energy systems. The lack of any traditional energy source is adding a great reliability challenge which should be compensated using expensive ESS. This challenge can be avoided by using a pumped hydro energy storage system (PHES) in harmony with batteries. The PHES is an excellent option to be used in NEOM city due to the perfect topographical characteristic of this site. The minimum cost of energy and the highest reliability is used as an objective for sizing the proposed entire green HRES. Using smart grid principles (SGP) and demand‐side management (DSM) in the design and operation stages will minimize system size and cost, which can result in a significant reduction in consumer bills. As a result, this paper introduces an innovative DSM based on a dynamic tariff. The suggested DSM technique was developed utilizing a unique fuzzy logic that takes into account the present and day‐ahead ESS situations to intelligently determine the ideal tariff for the lowest cost and maximum reliability of the HRES. This paper introduces a modified grey wolf optimization (MGWO) technique to shorten convergence time while preserving the best accuracy. The suggested MGWO is assessed against 10 swarm optimization techniques. The payback period of the project is 7 years. The findings acquired from this unique program demonstrated its superiority, with conversion times reduced by 22% to 80% when compared to previous optimization procedures. Furthermore, as compared to the flat rate pricing tariff, the usage of the dynamic tariff lowered the LCOE by 53%. [ABSTRACT FROM AUTHOR]

Diabetes Mellitus (DM) causes global exhaustion, consumes economic resources, and has several risk factors. The bibliometric studies re-evaluate the research efforts on this illness using mathematical and statistical tools to indicate current research and future trends. This study examines KSA's DM research during 2010-2021. Data were acquired from Scopus and analyzed using VOSviewer and MS Excel. Several characteristics were examined to measure the quantity and quality of KSA-related DM articles. In total, 1,919 journal and conference papers were published. DM research included researchers from multidisciplinary sectors. Thirty-seven percent of them have ten or more scientific publications. Al-Daghri, N.M. (King Saud University) leads the pack. In total, 757 (39.44%) research projects got funding from 159 sources within and outside KSA. Memish, Z.A. is the most cited author. The Saudi Medical Journal has the most citations (1214). Al-Daghri, N.M. (KSU) collaborates the most. One hundred forty-one nations aided KSA's diabetes research. Egypt's High Institute of Public Health has the most scientific collaboration with KSA. Authors' and all Keywords analyses indicated a rich knowledge structure. Diabetes Care Journal has the most cocitations with 2,220 and a total link strength of 19,283, followed by The New England Journal of Medicine. The study results will be helpful to stakeholders to understand better the trends and performance of diabetes-related regional research, which will be beneficial. [ABSTRACT FROM AUTHOR]

Background: With the rise in medical errors, establishing a strong safety culture and an effective incident reporting system is crucial. As part of the Saudi National Health Transformation Vision of 2030, multiple projects have been initiated to periodically assess healthcare quality measures and ensure a commitment to continuous improvement. Among these is the Hospital Survey on Patient Safety Culture National Project (HSPSC), conducted regularly by the Saudi Patient Safety Center (SPSC). However, comprehensive tools for assessing reporting culture are lacking. Addressing this gap can enhance reporting, efficiency, and health safety. Objective: This paper aims to investigate the reporting practices among healthcare professionals (HCPs) in Saudi Arabian hospitals and examine the relationship between reporting culture domains and other variables such as hospital bed capabilities and HCPs' work positions. Methods: The study focuses on measuring the reporting culture-related items measures and employs secondary data analysis using information from the Hospital Survey on Patient Safety Culture conducted by the Saudi Center for Patient Safety in 2022, encompassing hospitals throughout Saudi Arabia. Data incorporated seven items in total: four items related to the Response to Error Domain, two related to the Reporting Patient Safety Events Domain, and one associated with the number of events reported in the past 12 months. Results: The sample for the analyzed data included 145,657 HCPs from 392 hospitals. The results showed that the average positive response rates for reporting culture-related items were between 50% and 70%. In addition, the research indicated that favorable response rates were relatively higher among managerial and quality/patient safety/risk management staff. In contrast, almost half had not reported any events in the preceding year, and a quarter reported only 1 or 2 events. Pearson correlation analysis demonstrates a strong negative correlation between bed capacity and reporting safety events, response to error, and number of events reported (r = -0.935, -0.920, and − 0.911, respectively; p < 0.05), while a strong positive correlation is observed between reporting safety events and response to error (r = 0.980; p < 0.01). Conclusions: Almost 75% of the HCPs reported fewer safety events over the last 12 months, indicating an unexpectedly minimal recorded occurrence variance ranging from 0 to 2 incidents. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic analyses, including the payback period and levelized cost of energy (LCOE), alongside an investigation of net metering and net billing scenarios, we delineated a pathway toward achieving net zero billing for the mosque's energy requirements. This study examined two scenarios: Scenario I involved net metering, while Scenario II explored net billing. Our theoretical and simulation results, derived from detailed analyses conducted using PVsyst software, unequivocally demonstrated the superiority of net metering for this specific application. With net metering, the mosque's energy needs can be efficiently met using minimal infrastructure—comprising only 34 photovoltaic modules and a single inverter. In contrast, net billing requires significantly higher resource demands, underscoring the economic and spatial advantages of net metering. Additionally, the payback period for Scenario I is 7.9 years, while for Scenario II, it extends to 87 years. Through rigorous simulations, this study reaffirmed the practicality and feasibility of the net metering approach within the context of Saudi Arabia. Furthermore, our research provides actionable insights for implementing sustainable solutions at specific sites, such as the Al-Abrar Mosque, and contributes to advancing renewable energy knowledge in the region. [ABSTRACT FROM AUTHOR]

Deaf and hard-of-hearing people mainly communicate using sign language, which is a set of signs made using hand gestures combined with facial expressions to make meaningful and complete sentences. The problem that faces deaf and hard-of-hearing people is the lack of automatic tools that translate sign languages into written or spoken text, which has led to a communication gap between them and their communities. Most state-of-the-art vision-based sign language recognition approaches focus on translating non-Arabic sign languages, with few targeting the Arabic Sign Language (ArSL) and even fewer targeting the Saudi Sign Language (SSL). This paper proposes a mobile application that helps deaf and hard-of-hearing people in Saudi Arabia to communicate efficiently with their communities. The prototype is an Android-based mobile application that applies deep learning techniques to translate isolated SSL to text and audio and includes unique features that are not available in other related applications targeting ArSL. The proposed approach, when evaluated on a comprehensive dataset, has demonstrated its effectiveness by outperforming several state-of-the-art approaches and producing results that are comparable to these approaches. Moreover, testing the prototype on several deaf and hard-of-hearing users, in addition to hearing users, proved its usefulness. In the future, we aim to improve the accuracy of the model and enrich the application with more features. [ABSTRACT FROM AUTHOR]

The objective of this study was to characterize the properties of pulp and paper manufactured from two agricultural residues namely, wheat straw ( Triticum aestivum L. em Thell.) and date palm midribs ( Phoenix dactylifera L.) widely available in Saudi Arabia by employing soda-anthraquinone (AQ) pulping process. Specimens from cedar wood ( Juniperus procera Hochst. ex Endl.) wood was also used as control samples. Chemical and the morphological characteristics of all three types of raw materials in addition to basic properties of hand sheets made from such resources were evaluated. The results indicated that wheat straw had the highest hemicellulose and ash values of 35% and 7% and the lowest lignin content value of 18%, respectively. The fibre length of the both palm fronds and wheat straw was lower than that of 2.2 mm which was found for J . procera . Overall strength properties of the handsheet made from two agricultural raw materials were significantly lower than those made from J . procera pulp. Wheat straw handsheets also had higher strength properties than those made from date palm midribs with an exception of their tear index. Based on the results of this study it appears that both types of raw materials, date palm midribs and wheat straw could have a potential to manufacture pulp and paper with accepted properties so that such underutilized species can be converted into value-added products. [ABSTRACT FROM AUTHOR]

Several research papers have attempted to describe the dynamics of COVID-19 based on systems of differential equations. These systems have taken into account quarantined or isolated cases, vaccinations, control measures, and demographic parameters, presenting propositions regarding theoretical results that often investigate the asymptotic behavior of the system. In this paper, we discuss issues that concern the theoretical results proposed in the paper "An Extended SEIR Model with Vaccination for Forecasting the COVID-19 Pandemic in Saudi Arabia Using an Ensemble Kalman Filter". We propose detailed explanations regarding the resolution of these issues. Additionally, this paper focuses on extending the local stability analysis of the disease-free equilibrium, as presented in the aforementioned paper, while emphasizing the derivation of theorems that validate the global stability of both epidemic equilibria. Emphasis is placed on the basic reproduction number R 0 , which determines the asymptotic behavior of the system. This index represents the expected number of secondary infections that are generated from an already infected case in a population where almost all individuals are susceptible. The derived propositions can inform health authorities about the long-term behavior of the phenomenon, potentially leading to more precise and efficient public measures. Finally, it is worth noting that the examined paper still presents an interesting epidemiological scheme, and the utilization of the Kalman filtering approach remains one of the state-of-the-art methods for modeling epidemic phenomena. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess, monitor, and analyzed water quality parameters recorded from reservoirs in of Saudi Arabia for Electrical Conductivity (EC) forecasting. Water quality parameters play a key role in the lives of humans, plants, and animals depending on those reservoirs for survival. In this paper, we evaluate the performance of a novel autoencoder stacked LSTM transfer learning (TL + aeSLSTM) model for EC forecasting. Although various factors such as pH, EC, CaCO3, Turbidity, Salinity, Sodium (Na+), Potassium (K+), Magnesium (Mg), Calcium (Ca2+), Fluoride (F−), Chloride (Cl−), Bromide (Br−), Nitrate (NO3−), and Sulfate ( SO 4 2 - ) affects EC forecasting, in this paper we utilized Total Dissolved Solids (TDS) and Na as our source dataset for EC forecasting. In order to select the most appropriate or suitable transfer learning model network for EC forecasting, a trail-by-error approach was employed where parameters e.g., hidden layers, number of neurons, batch-size, epochs, optimizers, and activation functions were varied and applied to each model. To assess the performance of the proposed model to the baseline model, we employed the most common evaluation metrics ie. MSE, MAE, and MAPE. Superior performance by the novel TL + aeSLSTM over the state-of-the-art models illustrates the capability of the model to utilize both the advantage of the autoencoder, stacked LSTM, and transfer learning capability for EC forecasting. The results show that the least value of train MAE, train MSE, train RMSE, test MAE, test MSE, test RMSE when Na is used as the source dataset for EC forecasting by the TL + aeSLSTM are 248.044, 519.292, 22.788, 206.114, 212.004, and 14.560, respectively. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

Introduction: D-dimer is a marker of coagulation and fibrinolysis widely used in clinical practice for assessing thrombotic activity. While it is commonly ordered in the Emergency Department (ED) for suspected venous thromboembolism (VTE), elevated D-dimer levels can occur due to various other disorders. The aim of this study was to find out the causes of elevated D-dimer in patients presenting to a large ED in Saudi Arabia and evaluate the accuracy of D-dimer in diagnosing these conditions. Methods: Data was collected from an electronic hospital information system of patients who visited the ED from January 2016 to December 2022. Demographic information, comorbidities, D-dimer levels, and diagnoses were analyzed. Statistical analysis was performed using the SPSS software. The different diagnoses associated with D-dimer levels were analyzed by plotting the median D-dimer levels for each diagnosis category and their interquartile ranges (IQR). The receiver operating characteristic (ROC) curves were calculated and their area under the curve (AUC) values were demonstrated. The optimal cut-off points for specific diseases were determined based on the ROC analysis, along with their corresponding sensitivities and specificities. Results: A total of 19,258 patients with D-dimer results were included in the study. The mean age of the participants was 50 years with a standard deviation of ± 18. Of the patients, 66% were female and 21.2% were aged 65 or above. Additionally, 21% had diabetes mellitus, 20.4% were hypertensive, and 15.1% had been diagnosed with dyslipidemia. The median D-dimer levels varied across different diagnoses, with the highest level observed in aortic aneurysm 5.46 g/L. Pulmonary embolism (PE) and deep vein thrombosis (DVT) were found in 729 patients (3.8%) of our study population and their median D-dimer levels 3.07 g/L (IQR: 1.35–7.05 g/L) and 3.36 g/L (IQR: 1.06–8.38 g/L) respectively. On the other hand, 1767 patients (9.2%) were diagnosed with respiratory infections and 936 patients (4.9%) were diagnosed with shortness of breath (not specified) with median D-dimer levels of 0.76 g/L (IQR: 0.40–1.47 g/L) and 0.51 g/L (IQR: 0.29–1.06 g/L), respectively. D-dimer levels showed superior or excellent discrimination for PE (AUC = 0.844), leukemia (AUC = 0.848), and aortic aneurysm (AUC = 0.963). DVT and aortic dissection demonstrated acceptable discrimination, with AUC values of 0.795 and 0.737, respectively. D-dimer levels in respiratory infections and shortness of breath (not specified) exhibited poor to discriminatory performance. Conclusion: This is the first paper to identify multiple causes of elevated D-dimer levels in Saudi Arabia population within the ED and it clearly highlights their accurate and diagnostic values. These findings draw attention to the importance of considering the specific clinical context and utilizing additional diagnostic tools when evaluating patients with elevated D-dimer levels. [ABSTRACT FROM AUTHOR]

One of the predominant health issues affecting Saudi Arabia and leading to many complications is Type 2 diabetes (T2D). Early detection and significant preventative measures lead to curbing and controlling the health issue. There are fewer datasets in the literature for the detection of T2D in the Saudi population. Past studies using Saudi data have favoured machine learning algorithms to classify T2D. Although the application of this data in machine learning is evident, no studies exist in the literature that compare this data, especially those related to deep learning algorithms. This study's objective is to use specific Saudi data to develop multiple deep learning models that could be used to detect T2D. The research uses a Deep Neural Network (DNN), an Autoencoder (AE), and a Convolutional Neural Network (CNN) to create predictive models and compare their performance with a traditional machine learning classifier used on the same dataset that outperformed other machine learning algorithms such as a Decision Forest (DF). Various metrics were used to evaluate the effectiveness of the models, such as accuracy, precision, recall, F1 score and area under the ROC curve (AUC) where the ROC acts as a receiver operating characteristic curve. There are two cases in this paper: (i) uses all features of the dataset and (ii) uses six of the ten features, such as DF. In case (i), the results were shown that AE outperformed other models with the highest accuracy for imbalanced and balanced data 81.12% and 79.16%, respectively. The results for case (ii) showed that AE scored the highest 81.01% accuracy with imbalanced data compared to DF and DF achieved the highest accuracy of 82.1% with balanced data. As a result, both cases explored in this study revealed that AE has a constant superior performance if imbalanced data is used. In contrast, DF demonstrated the highest accuracy when a balanced dataset was used with a feature set reduction. They help to identify the undiagnosed T2D, and they are essential for professionals in Saudi Arabia in the health sector to promote health connections, identify risks and contain or improve their diabetes management. [ABSTRACT FROM AUTHOR]

Businesses use data to enhance operational performance, creating demand for professionally trained data/business analytics graduates. Universities offer a variety of academic programs in response to the increasing labor market demands. Yet, research on how well educational offerings adapt to market demand is scant. This paper aims to evaluate how well university curricula match Saudi Arabia's marketplace needs. A content analysis was conducted to compare universities' analytics programs with a sample of internet job postings over a 12-month period. The results were evaluated quantitatively to assess the alignment between academia and industry. This information is of value to industry, universities, and learners. [ABSTRACT FROM AUTHOR]

Since the discovery and the development of many technological instruments such as modern communication and communication technologies, digital media has served widely from the technology, and thus intersected quasi all life's domains, by providing news, information, and also discussions of quasi all subjects. In social sciences, for example, a major part of digital media sites discusses the well-being of both individuals, and societies, especially with the presence of many challenging phenomena like pandemics, wars, and financial crises. A major concern for QoL index for example resides in whether it is a uniform stable index or on the contrary a non-uniform index depending strongly and point-wisely on the time scale. This motivates the consideration of a non-uniform QoL index based on non-uniform wavelets to take into account the influence of many factors issued from political, social, environmental, economic effects according to the time scale. The model developed is tested on Saudi Arabia QoL index case. Recall that the Kingdom of Saudi Arabia has fixed many aims in its 2030-vision plan including the quality of life as a major goal. For example, the KSA worldwide NEOM project necessitates surely a supportive environment to be realized. The second purpose of our paper is also to study the impact of digital media such as social one on the QoL. Therefore, the data collected is basically issued from a set of conversations on social media platforms. To obtain a suitable time series, we developed a backward-forward non-uniform wavelet forecasting model to extend the data sample suitably. The whole time series is by the next applied for the QoL index dynamics and interpretations. The findings showed that effectively, the QoL index is never a stable single index on the whole year, but on the contrary, the dependence on the time scale is non-uniform. Moreover, to interpret suitably and for a correct policy, the non-uniform behavior should be considered adequately. [ABSTRACT FROM AUTHOR]

Flight delays are a major concern for both travelers and airlines, with significant financial and reputational consequences. Accurately predicting flight delays is crucial for enhancing customer satisfaction and airline revenues. In this paper, we leverage the power of artificial intelligence and machine learning techniques to build a framework for accurately predicting flight delays. To achieve this, we collected flight information from September 2017 to April 2023, along with weather data, and performed extensive feature engineering to extract informative features to train our model. We conduct a comparative analysis of various popular machine learning architectures with distinctive characteristics, aiming to determine their efficacy in achieving optimal accuracy on our newly proposed dataset. Based on our evaluation of various architectures, our findings demonstrate that CatBoost outperformed the others by achieving the highest test accuracy and the lowest error rate in the challenging use case of Saudi Arabia. Moreover, to simulate real-world scenarios, our framework evaluates the best-performing model that has been selected for deployment in a web application, which provides users with the ability to accurately forecast flight delays and offers a user-friendly dashboard with valuable insights and analysis capabilities. [ABSTRACT FROM AUTHOR]

Background: Oral potentially malignant disorders (OPMDs) are a group of chronic oral mucosal diseases associated with an increased risk of malignant transformation. Multiple studies have investigated the prevalence of these conditions in multiple regions; however, there are limited data about the prevalence of OPMDs in the Kingdom of Saudi Arabia (KSA). This paper aims to review the prevalence of OPMDs in the KSA, to ensure better understanding of the population risk and propose a more standardised approach to the diagnosis and management of this group across the KSA. In addition, this review will discuss the prevalence of oral cancer in the KSA, considering independent risk factors for oral cancer development. Methods: Electronic databases including PubMed, Medline, Medscape, ScienceDirect, StatPearls, BMC Oral Health and the Cochrane Library were searched with the keywords "Oral Potentially Malignant Disorders"; "Saudi Arabia"; and "Oral Cancer". Identified articles were reviewed independently by 2 reviewers against defined inclusion and exclusion criteria. Results: 16 studies were included in this review. The prevalence of OPMDs in KSA varies significantly depending on age, gender, social habits, background disease and dental status. Conclusions: This review highlights the need for up-to-date data on the prevalence, distribution, and characteristics of OPMDs in KSA. The diverse prevalence rates and distinct characteristics of various OPMDs emphasise the necessity for targeted preventive measures. As the data on OPMDs in KSA remains limited, future research efforts should prioritise the establishment of comprehensive epidemiological studies to inform effective public health interventions in this region. [ABSTRACT FROM AUTHOR]

Technical debt (TD) poses a significant risk in the software industry, representing the compromises made during software development that result in long-term consequences. To facilitate the management of TD, it is important to explore the causes of TD and the effects of the presence of TD on software projects. While the concept of TD has been investigated in several countries, no study has explored TD in the context of Saudi Arabia. In this paper, we aim to investigate the familiarity of the TD concept within the Saudi software practitioners and identifying the common causes and effects of TD in the Saudi software industry. We replicated a global survey called InsighTD, using the same survey instrument and the analysis procedure but collecting the data from software practitioners in Saudi Arabia. A total of 48 Saudi software practitioners completed the survey. The study findings indicate that the TD concept is not well recognized among the Saudi software practitioners (50% of the survey respondents have never heard of it before). Additionally, we identify the common causes and effects of TD from the perspective of Saudi software practitioners. The top causes of TD were tight-release deadlines, work pressure, lack of experience, and inappropriate project planning. On the other hand, the top effects of TD were increased maintenance effort/cost, low software quality, and delayed delivery of new versions. In conclusion, our findings support previous research regarding the most common TD causes and effects. In addition, they highlight some important factors in the Saudi software industry. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) has gained a great deal of interest in recent years due to the need for information that can help many stakeholders (e.g., governments, investors, professional organizations, researchers, etc.) understand companies' contributions to the environment and society. CSR disclosure (CSRD) is now the key source of such information when analyzing, for example, an institution's future performance. In the current body of CSRD literature, the majority of quantitative CSRD studies have relied on traditional statistical approaches for the correlation analysis of CSRD influencing factors. In this paper, we intend to quantitatively analyze firms' characteristics related to CSRD in Saudi Arabia, understand CSRD and its influencing factors, and predict CSRD patterns. This study lays the groundwork to help companies make informed decisions. It also helps many other stakeholders better understand CSRD's impacts. To achieve this, we propose a deep learning framework based on long short-term memory (LSTM) for identifying and predicting CSRD patterns. Moreover, a correlation-based technique is also used to visualize the relationships between variables and identify the significant features. The dataset used in this study was collected from annual reports, CSR reports, and firms' websites between 2015 and 2018. It contains a variety of variables to explain the CSR behaviour of 117 companies. The proposed framework is evaluated with several approaches, including logistic regression (LR), K-nearest neighbours (KNN), support vector machines (SVM), random forests (RF), and decision trees (DT). Compared to other machine learning models, experiment results show that LSTM achieved acceptable results with the highest accuracy of 88 % . [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease-19 (COVID-19). This virus has caused a global pandemic, marked by several mutations leading to multiple waves of infection. This paper proposes a comprehensive and integrative mathematical approach to the third wave of COVID-19 (Omicron) in the Kingdom of Saudi Arabia (KSA) for the period between 16 December 2022 and 8 February 2023. It may help to implement a better response in the next waves. For this purpose, in this article, we generate a new mathematical transmission model for coronavirus, particularly during the third wave in the KSA caused by the Omicron variant, factoring in the impact of vaccination. We developed this model using a fractal-fractional derivative approach. It categorizes the total population into six segments: susceptible, vaccinated, exposed, asymptomatic infected, symptomatic infected, and recovered individuals. The conventional least-squares method is used for estimating the model parameters. The Perov fixed point theorem is utilized to demonstrate the solution's uniqueness and existence. Moreover, we investigate the Ulam–Hyers stability of this fractal–fractional model. Our numerical approach involves a two-step Newton polynomial approximation. We present simulation results that vary according to the fractional orders (γ) and fractal dimensions (θ), providing detailed analysis and discussion. Our graphical analysis shows that the fractal-fractional derivative model offers more biologically realistic results than traditional integer-order and other fractional models. [ABSTRACT FROM AUTHOR]

Background: Chiari malformation type III (CM III), a rare hindbrain anomaly, often presents with various concurrent anomalies. This paper reports a unique case of CM III associated with Klippel-Feil syndrome (KFS), a condition previously unreported in Saudi Arabia and documented in only one other case globally in Turkey. This study aims to share insights into the unusual association between CM III and KFS, considering their close embryological development and involvement in the craniocervical junction. Methodology: The study presents a case of a 2.5-year-old female diagnosed with CM III and KFS. Diagnostic tools such as ultrasound, CT scans, MRI, and physical examinations were used to confirm the patient's condition. Surgical interventions, including decompression and encephalocele repair, were performed. Results: Successful surgical interventions, including encephalocele repair and duraplasty, were carried out. Follow-up visits indicated a stable condition, marked improvement in lower limb strength, and the patient's ability to walk with assistance. CT follow-up affirmed a satisfactory surgical outcome. Conclusion: This case study illustrates the potential for an optimistic prognosis in CM III, even when accompanied by complex conditions such as KFS, through early diagnosis and intervention. It underscores the significance of antenatal screening for effective care planning and calls for further research and publications due to the rarity of this association. These findings contribute to our understanding of CM III and its related conditions, emphasizing the need for open-minded consideration of potential embryological associations. [ABSTRACT FROM AUTHOR]

Background: Five-fifths of all incidents of blindness in Saudi Arabia may be attributed to cataracts. Cataracts are the second major cause of blindness, responsible for 35.5% of cases. Therefore, the purpose of the research was to measure the visual acuity improvement after cataract surgery in children. Materials and Methods: This systematic review followed PRISMA guidelines for reporting systematic reviews. All procedures followed the recommendations of the Cochrane handbook. Studies of varying study designs, both published and unpublished, are included. Retrospective studies with outcomes of pediatric cataract surgery were identified from various databases. Result: After an initial screening, 108 out of 167 items were deemed unsuitable for publication. There were 59 full-text papers assessed for inclusion, and only seven matched the criteria. All the articles included were of a very high standard. Both the duration of therapy and the target population varied widely between the studies. Conclusion: The results indicated that the majority of childhood cataracts are hereditary. Primary posterior capsulectomy and anterior vitrectomy combined with cataract extraction and intra-ocular lens implantation is the treatment of choice for pediatric cataracts. It is recommended that surgery be performed in a properly equipped facility staffed by trained, cooperative personnel and that different procedures be used to enhance post-operative follow-up. [ABSTRACT FROM AUTHOR]

The Iran-Saudi Arabia conflict is an ongoing struggle for influence in the region that has created uncertainty, affected oil prices and regional economics. This paper uses wavelet analysis to examine the frequency and time-varying co-movement and casual nexus between petroleum prices (OP) and financial liquidness (MS) with and without geopolitical risk (GPR). The aim is to test the validity of the monetary equilibrium model from 1988 to 2019. The model is supported by the findings, as both short and medium-term association is found between OP and MS at high frequencies in the presence of GPR. We find a medium-term association between OP and MS in the absence of GPR. The paper's overall conclusion suggests that GPR affects OP and OP, in turn, impact MS. Diversifying economic activities to minimize oil dependency, which is sensitive to external shocks, is suggested as a mitigation solution. [ABSTRACT FROM AUTHOR]

The article discusses a study which examined the development of the paper-based Hajji Health Record (PHHR) instrument. Topics covered include the conduct of a survey among physicians in Alnoor Specialist Hospital in Saudi Arabia, the supportive effects of electronic health record system on health care and the need for standard-based health information technology to get quality of care.

Paper recycling industry is considered one of the important investment industries, included in the industrial zone south of Jeddah. This industry generates wastewater that causes a lot of damage when disposed in a non-secure method. The current study aims to study the characteristics of wastewater resulting from the different stages of production and the management methods used at one of the paperrecycling industries in the Industrial Zone City, south of Jeddah, KSA. The results of the field survey showed that the sources of water include the treated effluent from Al-Khumra wastewater treatment plant and the treated effluent emerging from the industrial wastewater treatment plant. Results of analysis showed that most of the locations discharged wastewater with low pH, high concentrations of suspended solids, dissolved solids, chemical oxygen demand, and presence of a significant difference between concentrations of chemical and biochemical oxygen demands. The results also showed that most of the measured parameters for most of the sites wastewater exceeded PME (Presidency of Meteorology and Environment) standards for direct discharge, for central treatment facilities, or both. The plant follows the various wastewater management options, where it used the treatment strategy with the wastewater of the 1st site before disposal, pollution minimization with the 2nd to 6th sites by recycling, recycling and treatment strategies with the wastewater of the 7th site (wastewater of floating solids removal basin), and disposal strategy with the wastewater of 8th site (wastewater of the aeration basin) by transferring it to be treated by Al-Khumra plant. Some recommendations were suggested. Of these, following pollution prevention with some units that leak pulp, using one of the various ways of waste minimization before wastewater discharge from aeration basin to the central treatment plant, studying the feasibility of discharging the wastewater into the industrial wastewater treatment plant located in south Jeddah, and taking the advantage of using the wastewater emerging from aeration basin rather than its disposal. [ABSTRACT FROM AUTHOR]

This paper examines how the pre-1980 works of Saudi female novelists were received by male critics in Saudi Arabia in their critical studies. It seeks to explain why many Saudi and Arab male literary critics either ignored or decried these pioneering novels, by highlighting the essential criteria they adopted in their evaluation and criticism of such texts. The paper determines that these novels were poorly received—and unjustly so—in comparison with those written by men in the same period, male critics having subconsciously dismissed or disregarded them on the grounds that they were of limited literary quality, did not belong to what was accepted as the Saudi social and cultural environment, or did not represent the reality of Saudi women's lives. Had these core evaluative criteria been adopted in criticism of the early novels of Saudi men, many of these would also have been excluded as having no artistic value or as failing to represent Saudi social reality. [ABSTRACT FROM AUTHOR]

This paper introduces an informed decision support framework (IDSF) from a strategic perspective in the health sector, focusing on Saudi Arabia. The study addresses the existing challenges and gaps in decision-making processes within Saudi organizations, highlighting the need for proper systems and identifying the loopholes that hinder informed decision making. The research aims to answer two key research questions: (1) how do decision makers ensure the accuracy of their decisions? and (2) what is the proper process to govern and control decision outcomes? To achieve these objectives, the research adopts a qualitative research approach, including an intensive literature review and interviews with decision makers in the Saudi health sector. The proposed IDSF fills the gap in the existing literature by providing a comprehensive and adaptable framework for decision making in Saudi organizations. The framework encompasses structured, semi-structured, and unstructured decisions, ensuring a thorough approach to informed decision making. It emphasizes the importance of integrating non-digital sources of information into the decision-making process, as well as considering factors that impact decision quality and accuracy. The study's methodology involves data collection through interviews with decision makers, as well as the use of visualization tools to present and evaluate the results. The analysis of the collected data highlights the deficiencies in current decision-making practices and supports the development of the IDSF. The research findings demonstrate that the proposed framework outperforms existing approaches, offering improved accuracy and efficiency in decision making. Overall, this research paper contributes to the state of the art by introducing a novel IDSF specifically designed for the Saudi health sector. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of using augmented reality (AR) with the ARCS (Attention, Relevance, Confidence, and Satisfaction) framework to improve student performance and motivation in primary schools in Saudi Arabia. A sample of 100 randomly selected primary school pupils from grades 4 to 6 were used in the study, and two motivational and learning use scales were used to collect data. The results of the study indicated that AR implementation using the ARCS framework significantly improved knowledge and motivation among the primary school students. The paper recommends that AR should be adopted in primary schools in Saudi Arabia, specifically for grades 4 to 6, as an effective method of enhancing student learning and motivation. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of involving electric vehicles (EVs) in the load profile on the generation system. The impact was studied from a reliability perspective on Saudi Arabia's total generation system capacity as one source supplying the expected load for the year 2030. The EV load profile was then added. The outcomes were examined considering the gradual penetration percentage to the total load. The reliability indices measured are the loss of load probability (LOLP) and the expected energy not supplied (EENS). The results show that the estimated generation system of Saudi Vision 2030 will not withstand the estimated number of EVs without negatively impacting reliability. Similarly, the reliability assessment was conducted for the central region considering EVs in Riyadh City to verify Saudi Vision 2030. The results show that EV integration will greatly affect the electrical network's reliability. Furthermore, a sensitivity analysis was conducted for Saudi Arabia and the central region to assess the generation system better. The study shows that investing in the generation infrastructure is essential to handle EV growth for the upcoming years. The work introduced in this paper will also help decision-makers make appropriate planning decisions in the future. [ABSTRACT FROM AUTHOR]

This paper analyses how Maldives' close ties with Saudi Arabia have affected its relations with other countries from Middle East Asia. Following the footsteps of Saudi Arabia, Maldives severed its diplomatic relations with Iran in 2016 and with Qatar in 2017. The paper discusses the economic investments Riyadh has made to develop civic infrastructure in the island nation. However, more than diplomatic ties and economic investments, close relations between Malé and Riyadh have affected the Island state's society. There is a spread of religious obstructionism in Maldivian society, for which several outside scholars and Maldivians blame Saudi Arabia. Finally, the paper briefly discusses Maldives' ties with Middle East countries other than Saudi Arabia. [ABSTRACT FROM AUTHOR]

This paper explores the potential of rooftop solar PV to meet the electricity demand in the urban areas of Abha city, Saudi Arabia (KSA), minimising imports from the grid. A localised energy system for Abha is proposed that considers two types of loads: (i) residential loads with a monthly aggregated energy consumption of 172,440 MWh and an electric demand of 239.5 MW, and (ii) commercial loads with a monthly aggregated energy consumption of 179,280 MWh and an electric demand of 249 MW. The grid currently supplies this load. This paper proposes a PV development planning tool for residential and commercial areas to calculate the total PV production for each type of load to achieve a balanced energy area, considering (i) the number of buildings, (ii) the type of load, (iii) the peak load, and (iv) the total PV array area in m2 per building. The results of the modelling study using real data demonstrate that the anticipated total PV production in residential and commercial areas is sufficient to meet local peak demand, and there is an excess of power that can either be stored locally or exported to the grid. [ABSTRACT FROM AUTHOR]

The integration of the Internet and communication technologies has improved our lives in numerous ways. To date, the Internet of Things has evolved the healthcare industry from healthcare 1.0 to 4.0 which is known as the MIoT. In Healthcare 4.0, data is shared among multiple stakeholders through the use of cloud computing, fog computing, and telehealth. MIoT devices and technology's interconnected, heterogeneous nature raises new concerns about access to confidential patient data, which is often done without patients' or medical staff's knowledge. This is because security and privacy concerns for MIoT devices and technology are frequently ignored or undermined by relevant stakeholders. Medical IoT security and privacy are becoming increasingly important as a result of the increasing number of security breaches targeting the MIoT in healthcare. To impartially reveal the research scenario of Security of MIoT biblioshiny and VOS viewer software are used to conduct a quantitative assessment of research papers belonging to this field for the period 2012-2021 in the Web of Science (WoS) and Scopus databases. From the results, it is seen that for the past 10 years, the sum of articles on Security of MIoT has increased. This research domain covers 35 territories. MIoT, Security, Privacy, authentication, access control are the most often used keywords in this field of research in recent years. The research flashpoints in the field primarily emphasize research directions such as the, the security and privacy concerns related to MIoT sensor data and how to get rid of them. The top five nations considering research volume are the China, India, Saudi Arabia, USA, and Korea, but a lack of collaborative work amongst these countries is seen. Finally, the paper provides future research directions on security of MIoT, such as Privacy of patient information, Lightweight Protocols for MIoT Devices, Trust management, patient data sharing and insecure networks. [ABSTRACT FROM AUTHOR]

Background: The implementation of the Electronic Medical Record (EMR) system initiated a significant transition in the healthcare system from traditional paper-based medical records to a digital version. Though EMR offers several benefits compared to Paper Medical Records (PMR), patient satisfaction with the EMR has been an area of concern. The objective of this study is to explore patient satisfaction with the EMR compared to the PMR of patients attending five Primary Healthcare Centers in the Western Region of Saudi Arabia. Methods: A cross-sectional survey was conducted with patients who attended five Primary Health Care centers (PHCs) in the Western Region during 2018. A sample of 377 participants was invited to complete a self-developed structured questionnaire with multiple choice and Likert Scale questions. The questionnaire was distributed to participants in the PHC waiting areas. Results: The sample size realized as (n = 377) participants, the majority (65.0%) were female. The overall patient satisfaction was 3.708. Patient satisfaction with the EMR was statistically significant compared to the PMR (3.7241 vs. 3.6919, p < 0.001). Several factors provided evidence of the overall satisfaction with the implementation of the EMR, including an increase in physician attention during the clinical consultation (82.3%), increased explanation of tests and medication (85.8%), increased time spent with the patient during the consultation (80.4%) and increased active listening by the physician (77.3%). Besides, the patients felt confident to ask the physician question related to health during clinical consultation (84.0%). Conclusion: Patient satisfaction during the clinical consultation and overall satisfaction with various PHC services improved with the implementation of EMR. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources (RES), such as photovoltaic (PV) systems, into power system networks increases uncertainty, leading to practical challenges. Therefore, an accurate photovoltaic (PV) power prediction model is required to provide essential data that supports smooth power system operation. Hence, the work presented in this paper compares and discusses the results of different machine learning (ML) techniques in predicting the power produced by the 300 MW Sakaka PV Power Plant in the north of Saudi Arabia. The validation of the presented work is performed using real-world operational data obtained from the specified solar farm. Several performance measures, including accuracy, precision, recall, F1 Score, and mean square error (MSE), are used in this work to evaluate the performance of the different ML approaches and determine the most precise prediction model. The obtained results show that the Support Vector Machine (SVM) with a Radial basis function (RBF) is the most effective approach for optimizing solar power prediction in large-scale solar farms. [ABSTRACT FROM AUTHOR]

Newcastle disease (ND) is a tremendously contagious avian infection with extensive monetary ramifications for the chicken zone. To reduce the effect of ND on the Saudi rooster enterprise, our analysis emphasizes the necessity of genotype-particular vaccinations, elevated surveillance, public recognition campaigns, and stepped-forward biosecurity. Data show that one-of-a-kind bird species, outdoor flocks, and nearby differences in susceptibility are all vulnerable. The pathogenesis consists of tropism in the respiratory and gastrointestinal structures and some genotypes boom virulence. Laboratory diagnostics use reverse transcription-polymerase chain reaction, sequencing, and serotyping among different strategies. Vital records are supplied through immune responses and serological trying out. Vaccination campaigns, biosecurity protocols, and emergency preparedness are all covered in prevention and manipulation techniques. Notably, co-circulating genotypes and disparities in immunization regulations worry Saudi Arabia. The effect of ND in Saudi Arabia is tested in this paper, with precise attention paid to immunological reaction, pathogenesis, susceptibility elements, laboratory analysis, and preventative and manipulation measures. Saudi Arabia can shield its bird region and beef up its defences against Newcastle’s ailment, enforcing those hints into its policies. [ABSTRACT FROM AUTHOR]

This paper is devoted to the analysis of air temperature and humidity changes during the two solar eclipses of 26 December 2019 and 21 June 2020 in Saudi Arabia based on data we collected from two different sites. We highlight the complexity of humidity's response to a solar eclipse, which is quite different from temperature's response. During the December event, the Sun rose already partially eclipsed, while for the June eclipse, it was only partial at Riyadh. This difference apparently affected the observed response on the recorded variables: temperature, relative humidity (RH), and vapor pressure (VP) in the two events. Changes in these variables went unnoticed for the first eclipse since they were within the natural variability of the day; yet for the other, they showed evident alterations in the slopes of the major parameters, which we analyze and discuss. A decrease in temperature of 3.2 °C was detected in Riyadh. However, RH and VP showed an oscillation that we explain taking into account a similar effect reported in other eclipses. We measured a time lag of about 15 min from the eclipse central phase in the city. Related fluctuations and dynamics from the computed rates of the temporal variation of temperature and RH are scrutinized. Furthermore, an overdue significant review of terrestrial atmospheric parameters is also offered in the context of the eclipse meteorology, particularly related to desert atmospheres. We also try to identify the influence of solar eclipses in similar environments doing a broad inter-comparison with other observations of these variables in the Near East, northern Africa, and in the United States. These inter-comparisons reveal how complex and dissimilar the response of the lower atmosphere to a solar eclipse can be within a desert environment and other similar environments. [ABSTRACT FROM AUTHOR]