Search Results (257)

Social network platforms have a big impact on the development of companies by influencing clients’ behaviors and sentiments, which directly affect corporate reputations. Analyzing this feedback has become an essential component of business intelligence, supporting the improvement of long-term marketing strategies on a larger scale. The implementation of powerful sentiment analysis models requires a comprehensive and in-depth examination of each stage of the process. In this study, we present a new comparative approach for several feature extraction techniques, including TF-IDF, Word2Vec, FastText, and BERT embeddings. These methods are applied to three multilingual datasets collected from hotel review platforms in the tourism sector in English, French, and Arabic languages. Those datasets were preprocessed through cleaning, normalization, labeling, and balancing before being trained on various machine learning and deep learning algorithms. The effectiveness of each feature extraction method was evaluated using metrics such as accuracy, F1-score, precision, recall, ROC AUC curve, and a new metric that measures the execution time for generating word representations. Our extensive experiments demonstrate significant and excellent results, achieving accuracy rates of approximately 99% for the English dataset, 94% for the Arabic dataset, and 89% for the French dataset. These findings confirm the important impact of vectorization techniques on the performance of sentiment analysis models. They also highlight the important relationship between balanced datasets, effective feature extraction methods, and the choice of classification algorithms. So, this study aims to simplify the selection of feature extraction methods and appropriate classifiers for each language, thereby contributing to advancements in sentiment analysis. Full article

This study examines the role of AI tools in improving public communication via social media analysis. It reviews five of the top platforms—Google Cloud Natural Language, IBM Watson NLU, Hootsuite Insights, Talkwalker Analytics, and Sprout Social—to determine their accuracy in detecting sentiment, predicting trends, optimally timing content, and enhancing messaging engagement. Adopting a structured model approach and Partial Least Squares Structural Equation Modeling (PLS-SEM) via SMART PLS, this research uses 500 influencer posts from five Arab countries. The results demonstrate the impactful relationships between AI tool functions and communication outcomes: the utilization of text analysis tools significantly improved public engagement (β = 0.62, p = 0.001), trend forecasting tools improved strategic planning decisions (β = 0.74, p < 0.001), and timing optimization tools enhanced message efficacy (β = 0.59, p = 0.004). Beyond the technical dimensions, the study addresses urgent ethical considerations by outlining a five-principle ethical governance model that encourages transparency, fairness, privacy, human oversee of technologies, and institutional accountability considering data bias, algorithmic opacity, and over-reliance on automated solutions. The research adds a multidimensional framework for propelling AI into digital public communication in culturally sensitive and linguistically diverse environments and provides a blueprint for improving AI integration. Full article

This article analyzes the United Arab Emirates’ (UAE) efforts to achieve sustainable digital records management through government strategies, policies, and initiatives. Document analysis and literature review were employed to examine the UAE’s initiatives alongside global research on sustainable digital records management. The analysis benchmarks the UAE’s strategies against international practices, identifying gaps in research and policy that may affect progress toward environmentally sustainable records management. Key findings reveal that while UAE has made significant advancements in promoting overall sustainability, its policies and initiatives lack specific focus on digital records management. The study underscores the potential for achieving sustainability in digital records management, through the involvement of information management professionals in policy development and implementation. The research highlights both the strengths of the UAE’s current efforts and opportunities for improvement, offering a comprehensive understanding of the country’s commitment to achieving sustainability in the management of digital records. Full article

Introduction: Falls pose a significant health risk to older adults, with a reported prevalence of 31.6% among Saudi older adults. Medication-related falls are a preventable cause of morbidity and mortality. This study aimed to assess fall risk, evaluate knowledge of fall-risk-increasing drugs, and examine the impact of pharmacist counseling on community-dwelling older adults in Jazan, Saudi Arabia. Methods: A cross-sectional survey was conducted from December 2023 to March 2024 among 391 community-dwelling individuals aged ≥60 years in Jazan, Saudi Arabia. Fall risk was assessed using the Arabic Stay Independent screening tool, which remains unvalidated in Arabic-speaking populations. Participants answered demographic questions and reported any pharmacist counseling on medication in the past six months. Knowledge of prescription and over-the-counter fall-risk-increasing drugs was evaluated. Multivariable logistic regression and ordered probit models were used to analyze factors associated with fall risk and drug knowledge. Results: Approximately 57% of the participants were at risk of falling. Only 11.5% demonstrated good knowledge of prescription fall-risk-increasing drugs, whereas 24.6% showed good knowledge of over-the-counter fall-risk-increasing drugs. Age (OR, 1.07; 95% CI, 1.00–1.14; p = 0.05), arthritis (OR, 5.73; 95% CI, 2.51–13.06; p < 0.001), obesity (OR, 6.00; 95% CI, 2.33–15.46; p < 0.001) and diabetes (OR, 2.79; 95% CI, 1.38–5.64; p = 0.004) were associated with increased fall risk. Those who received pharmacist counseling had a greater likelihood (95% CI, 0.020–0.167; p = 0.01) of being in the very likely category of willingness to discuss medication changes. Conclusions: The findings highlight the role of pharmacist counseling and recommend improving fall prevention through medication reviews for arthritis and diabetes patients, standardized counseling protocols, and implementation of the Stay Independent screening tool for risk assessment in older adults. Full article

Background/Objectives: In recent years, increasing attention has been paid to the stabilization of natural biologically active compounds in order to expand their application in the food, pharmaceutical, and cosmetic industries. Such compounds, such as polyphenols, essential fatty acids, or vitamins, are extremely sensitive to environmental factors. This study aims to review the spray-drying-based microencapsulation technology and its application for stabilizing sensitive biologically active substances. Methods: This article systematically analyzes the main steps of the spray-drying microencapsulation process and discusses traditional and innovative wall materials, including natural polymers (polysaccharides and proteins), as well as new raw material sources (e.g., yeast cells, canola and pea protein isolates, and hemicelluloses). It also examines the potential of these systems for the stimulated release of active ingredients. Results: This review provides a comprehensive overview of the main stages of the spray-drying process and critically examines both conventional (e.g., maltodextrin and gum Arabic) and innovative wall materials (e.g., plant-based proteins and food industry by-products). Studies show that using different wall materials can achieve high encapsulation efficiency, improve the stability of biologically active substances, and control their release. Various compounds have been successfully microencapsulated—polyphenols, essential oils, carotenoids, fatty acids, and vitamins—protecting them from oxidation, light, and temperature. The review identifies key factors that can enhance product quality, increase encapsulation yield, and reduce processing costs and energy input—offering meaningful insights for optimizing the microencapsulation process. Conclusions: Spray-drying-based microencapsulation is an advanced technology that effectively protects sensitive active ingredients and allows for wider industrial food, pharmaceutical, and cosmetic applications. In the future, more attention is expected to be paid to personalized formulations, stimulated release systems, and sustainable wall materials from by-products. Full article

Background: Patient-reported outcome measures (PROMs) are essential for capturing the lived experiences of individuals managing chronic diseases. However, few PROMs have been culturally adapted and validated for Arabic-speaking populations. Aim: This study aimed to translate, culturally adapt, and validate the Long-Term Conditions Questionnaire (LTCQ) for use among Arabic-speaking adults living with chronic diseases in Jordan. Methods: Following forward–backward translation and an expert review, a cross-sectional survey of 1057 adults with chronic illnesses was conducted. The psychometric evaluation involved exploratory and confirmatory factor analyses (EFA and CFA) and Rasch modelling. While the original LTCQ assumed a unidimensional structure, EFA and CFA supported a two-factor solution: Empowerment and Functional Wellbeing, and Health-Related Psychosocial Distress. Results: The Rasch analysis confirmed that the item response thresholds were ordered, with good item targeting, and no differential item functioning (DIF) by gender. The removal of one poorly performing item resulted in a refined 19-item scale with strong reliability and validity. Conclusions: The Arabic LTCQ demonstrated robust psychometric properties and cultural relevance, supporting its use in clinical care, research, and policy initiatives. Future work should examine longitudinal responsiveness and further validate the tool across diverse Arabic-speaking populations. Full article

Background: Prediabetes, a precursor state to type 2 diabetes mellitus (T2DM), is characterized by elevated glucose levels that are not yet in the diabetic range. It is often associated with comorbidities such as obesity, hypertension, and dyslipidemia, driven by unhealthy lifestyle factors. This study aims to assess the relationship between adherence to the Mediterranean diet and anthropometric measures, such as body mass index and waist circumference, in Arab adults with prediabetes, considering other lifestyle patterns, including smoking, socioeconomic status, and physical activity. Methods: We performed baseline data analysis among a sample of prediabetic participants of a clinical trial aimed at improving physical activity and healthy lifestyle behaviors. Patients were recruited from the Sheikh Jarrah Clalit Health Services clinic in East Jerusalem. Eligible participants were identified via medical record review and invited by their primary physician. After providing informed consent, participants completed interviewer-administered questionnaires covering sociodemographic data, physical activity, and dietary habits. Physical measurements, including height, weight, and waist circumference, were taken using standardized protocols. Adherence to the Mediterranean diet was assessed using the locally adapted Israeli Mediterranean Diet Adherence Screener (I-MEDAS). Results: A total of 172 prediabetic adults aged 40–69.9 years were recruited. The majority of participants exhibited high adherence to the Mediterranean diet, with 80.2% achieving a high adherence score. However, no significant associations were found between Mediterranean diet adherence and BMI or waist circumference. Active smokers were 70.6% less likely to adhere to the Mediterranean diet compared to nonsmokers, and participants with equal-to-average income had lower odds of adhering to the diet compared to those with below-average income. Conclusions: These findings underscore the need for tailored public health strategies that address local cultural, economic, and environmental factors influencing dietary habits. Improving adherence to the Mediterranean diet in this population will require a multifaceted approach, with further research needed to understand the complex relationship between diet, lifestyle, and chronic disease prevention. Full article

Sentiment analysis, in the context of digital banking reviews, aims to assess customer satisfaction and support service enhancement. Despite increasing attention to sentiment analysis across domains, Arabic banking reviews remain underexplored. To bridge this gap, we introduce a dataset of 4922 Arabic reviews from three major Saudi digital banks with three sentiment categories positive, negative, or conflict—providing actionable insights for banks. We evaluate the dataset using several machine learning models and four large language models (LLMs)—GPT 3.5, GPT 4, Llama-3-8B-Instruct, and SILMA—using zero-shot (no labeled examples) and few-shot (a few labeled examples) learning strategies. Our results show that GPT 4 performs best among LLMs in few-shot settings, while traditional models still outperform LLMs, with a Voting Classifier achieving 90.24% accuracy. This study contributes a domain-specific dataset and comparative analysis to support research and practical improvements in Arabic digital banking services. Full article

This review maps the complex relationship between embodied carbon emissions and energy within the construction sector, aiming to generate insights that facilitate more informed and sustainable decision-making for new construction projects. It addresses the challenges associated with the variability in standards, methodologies, and emission factors used in embodied carbon assessments, which contribute to discrepancies and impede the development of cohesive carbon reduction strategies. The paper identifies key drivers of embodied emissions, with a particular emphasis on energy consumption, and represents the findings in the form of a detailed graph, elucidating the interplay between energy use and embodied emissions and providing actionable insights to enhance sustainability selections. Additionally, a case study of four residential low-rise projects in Abu Dhabi is conducted to analyze the energy-based carbon emissions of construction projects, examine their patterns over the entire construction period, and determine the energy-based carbon emission intensity of projects typically powered by diesel generators. This work expands the existing knowledge base by offering actionable insights into how energy-related decisions can significantly influence embodied carbon outcomes and aims to guide stakeholders in optimizing selections to advance sustainability practices within the construction industry. Full article

This review examines the meaning and scope of tarbiyah and its relationship to other key Islamic educational concepts, such as taʿlīm, tadrīs, and taʾdīb, in the English- and Arabic-language literature. The central question guiding this review is as follows: what does tarbiyah signify in primary and secondary sources, and how is it conceptually linked to taʿlīm, tadrīs, and taʾdīb? Employing a narrative review, this study critically examines relevant texts to clarify the distinctions and connections among these foundational concepts, offering insight into their roles within Islamic educational discourse. The English-language literature on the subject reveals divergent views on the meaning and the interplay between these concepts, their relationships, and their hierarchical order. This is less prominent in the Arabic-language literature. A deeper understanding of tarbiyah can help shape the vision and mission of Islamic schools and teacher education programmes, while also guiding the development of educational policies and praxes that are both academically rigorous and grounded in Islamic educational principles. Such an approach supports the holistic intellectual, moral, and spiritual development of learners. Full article

Mental health disorders represent a substantial global health concern, impacting millions and placing a significant burden on public health systems. Natural Language Processing (NLP) has emerged as a promising tool for analyzing large textual datasets to identify and predict mental health challenges. The aim of this scoping review is to identify the Arabic NLP techniques employed in mental health research, the specific mental health conditions addressed, and the effectiveness of these techniques in detecting and predicting such conditions. This scoping review was conducted according to the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) framework. Studies were included if they focused on the application of NLP techniques, addressed mental health issues (e.g., depression, anxiety, suicidal ideation) within Arabic text data, were published in peer-reviewed journals or conference proceedings, and were written in English or Arabic. The relevant literature was identified through a systematic search of four databases: PubMed, ScienceDirect, IEEE Xplore, and Google Scholar. The results of the included studies revealed a variety of NLP techniques used to address specific mental health issues among Arabic-speaking populations. Commonly utilized techniques included Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Recurrent Neural Network (RNN), and advanced transformer-based models such as AraBERT and MARBERT. The studies predominantly focused on detecting and predicting symptoms of depression and suicidality from Arabic social media data. The effectiveness of these techniques varied, with trans-former-based models like AraBERT and MARBERT demonstrating superior performance, achieving accuracy rates of up to 99.3% and 98.3%, respectively. Traditional machine learning models and RNNs also showed promise but generally lagged in accuracy and depth of insight compared to transformer models. This scoping review highlights the significant potential of NLP techniques, particularly advanced transformer-based models, in addressing mental health issues among Arabic-speaking populations. Ongoing research is essential to keep pace with the rapidly evolving field and to validate current findings. Full article

This systematic review critically examines the inclusive education practices for Students of Determination (SoDs) in Higher Education Institutions (HEIs), focusing on the specific case of the United Arab Emirates (UAE). The research will demonstrate best practices, key challenges, and most researched and less researched areas. In line with the PRISMA framework and using thematic analysis, this review synthesizes the findings of 41 peer-reviewed articles that focus on instructional practices, technological solutions, staff training, and institutional support. The results suggest that, globally, higher education institutions (HEIs) are increasingly adopting inclusive education policies, and that they are finding it challenging to implement these practices effectively, especially in the UAE. Important obstacles include restricted instructor education, variable institutional processes, and accessibility limitations. In addition, the use of assistive technologies has been shown to have positive outcomes, yet it remains underused because of the infrastructure and the training of faculty and students. This paper gives evidence-based suggestions to educational institutions like colleges or universities to make them more inclusive through better-trained faculty, better institutional policies, and the incorporation of assistive technologies. Also, the findings provide UAE-specific policy implications that underscore the importance of a well-defined national framework to support SoDs. Future studies must be longitudinal in nature, involving evaluations of the extent to which the strategies exert effects on SoDs’ academic performance and social inclusion. Full article

Background and Aim: This systematic scoping review examines rabies-related incidents, interventions, and post-exposure immunoprophylaxis in the Arabian Gulf region and Saudi Arabian Peninsula. Methods: A comprehensive literature search was conducted in databases including PubMed, Scopus, WoS, MedLine, and Cochrane Library up to July 2024. Studies were included discussing the reported cases of rabies that received the PEP in all countries of the Arabian Gulf, their epidemiological data, the received schedules of vaccination, and their safety. The search was done by using the following terminologies: rabies vaccine, rabies human diploid cell vaccine, vaccine, Saudi Arabia, Bahrain, Iraq, Kuwait, Oman, Qatar, United Arab Emirates, Southwest Asia, Iran, West Asia, Western Asia, Persian Gulf, Arabian Gulf, Gulf of Ajam, Saudi Arabian Peninsula, and The Kingdom of Saudi Arabia. Results: The systematic scoping review included 36 studies, synthesizing findings from diverse research designs, including large-scale cross-sectional studies and case reports, spanning nearly three decades. Findings indicated that young males in urban areas are most at risk for animal bites, predominantly from domestic dogs and cats. While post-exposure prophylaxis (PEP) was generally administered within recommended timeframes, vaccination completion rates varied. Conclusions: The review highlighted gaps in public awareness about rabies risks and prevention. Vaccine safety profiles were generally favorable, with mostly mild-to-moderate side effects reported. The study underscores the need for enhanced public health education, standardized PEP protocols, and a One Health approach to rabies prevention. Full article

The integration of sustainability in education has gained global attention as a critical component of achieving the United Nations Sustainable Development Goals (SDGs). Within the United Arab Emirates (UAE), significant efforts have been made to incorporate sustainability into national policies, reflecting the country’s vision for sustainable economic, social and environmental development. Within the context of Education for Sustainable Development (ESD), this research aims to investigate the alignment between national sustainability policies and their practical implementation in secondary schools, with a focus on identifying barriers and proposing actionable recommendations to enhance the integration of sustainability into education. This study employs a qualitative case study design with content analysis of data gathered from interviews and focus groups collected from a total of 21 teachers, school leaders, heads of departments and government officials, alongside the review of 14 relevant key policy documents. Key findings include a gap between policy and implementation, lack of a unified framework, resource disparities, and several barriers and strengths. This research concludes with recommendations to address these challenges, so that the UAE can strengthen its position as a leader in sustainability education, further aligning its national vision with global SDGs. Full article

Background/Objectives: Breast cancer is the most common malignancy in women and the second leading cause of cancer-related deaths globally. It is also the second most frequent source of brain metastases (BMs), contributing to 5–20% of cases. Despite this, routine brain imaging for screening is not recommended and is only conducted when clinical symptoms or physical findings suggest metastasis. This study aims to identify clinical predictors associated with overall survival (OS) and the timing of BM development in breast cancer patients. Methods: We performed a retrospective review of medical records for 113 patients diagnosed with BMs secondary to breast cancer at our institution between 2000 and 2020. Baseline demographic data and clinical characteristics related to BMs were collected. To identify factors associated with OS and time to BM development after breast cancer diagnosis, we conducted univariate analysis using Kaplan–Meier curves, bivariate analysis with the log-rank test, and multivariate analysis via the Cox Proportional Hazard model. Results: An early diagnosis of BMs was identified as a significant predictor of prolonged OS (aHR = 0.22; 95% CI: 0.049–0.98, p = 0.05). Post-menopausal status at breast cancer diagnosis (aHR = 1.69; 95% CI: 1.13–2.53, p = 0.01), Asian ethnicity (aHR = 2.30; 95% CI: 1.03–5.16, p = 0.04), and the ER+/HER2+ subtype (aHR = 2.06; 95% CI: 1.14–3.71, p = 0.02) were significantly associated with a shorter time to BM diagnosis. A subgroup analysis of patients with ER+ breast tumors revealed that Hispanic or Arabic ethnicity (aHR = 3.63; 95% CI: 1.34–9.81, p = 0.01) and stage IV diagnosis (aHR = 2.09; 95% CI: 1.16–3.76, p = 0.01) were significantly associated with shorter intervals to BM diagnosis. Conclusions: Breast cancer remains a significant global health burden for women, yet clear guidelines for routine BMs screening are still lacking. Early detection of BMs has been shown to notably improve long-term survival outcomes. Additionally, post-menopausal status, Hispanic or Arabic ethnicity, and the HER2+ tumor subtype are associated with shorter time to BM development, highlighting these factors as potential indicators for central nervous system screening. Full article