Search Results (2,810)

Sustainability education has become a global priority in educational systems, aiming to equip learners with the knowledge, values, and skills necessary to address complex environmental and social challenges. This study specifically aims to understand the role of science education in promoting students’ awareness of sustainability and their understanding of the interconnected relationship between humans and the environment, based on the perceptions and practices of primary science teachers in Al-Ahsa, Saudi Arabia. A qualitative approach was utilized, which included semi-structured interviews complemented by classroom observations as primary data collection instruments. The targeted participants comprised a purposive sample consisting of forty-nine primary-level science instructors from the Al-Ahsa district, located in eastern Saudi Arabia. Emergent concepts from open and axial coding processes by using grounded theory were developed with the gathered data. Based on the findings, teachers perceive science teaching not only as knowledge delivery but as an opportunity to cultivate critical thinking and nurture eco-friendly actions among pupils. Classroom practices that underscore environmental values and principles of sustainability foster a transformative view of the teacher’s role beyond traditional boundaries. The data also highlighted classroom practices that integrate environmental values and sustainability principles, reflecting a transformative perspective on the teacher’s educational role. Full article

Chromium–aluminum nitride (CrAlN) coatings were deposited on polished H13 tool steel substrates using direct current (DC) magnetron sputtering. The Cr/Al composition in the target was varied by inserting either four or eight chromium (Cr) plugs into cavities machined into an aluminum (Al) plate target. Nitrogen was introduced as a reactive gas to facilitate the formation of the nitride phase. Coatings were deposited at substrate bias voltages of −30 V, −50 V, and −60 V to study the combined effects of composition and ion energy on coating properties. Compositional analysis of coatings deposited at a −50 V bias revealed Cr/Al ratios of approximately 0.8 and 1.7 for the 4- and 8-plug configurations, respectively. This increase in the Cr/Al ratio led to a 2.6-fold improvement in coating hardness. Coatings produced using the eight-Cr-plug target exhibited a nearly linear increase in hardness with increasing substrate bias voltage. Cross-sectional scanning electron microscopy revealed a uniform bilayer structure consisting of an approximately 0.5 µm metal interlayer beneath a 2–3 µm CrAlN coating. Surface morphology analysis indicated the presence of coarse microdroplets in coatings with the lower Cr/Al ratio. These microdroplets were significantly suppressed in coatings with higher Cr/Al content, especially at increased bias voltages. This suppression is likely due to enhanced ion bombardment associated with the increased Cr content, attributed to Cr’s relatively higher atomic mass compared to Al. Coatings with lower hardness exhibited greater scratch resistance, likely due to the influence of residual compressive stresses. The findings highlight the critical role of both Cr/Al content and substrate bias in tailoring the tribo-mechanical performance of PVD CrAlN coatings for wear-resistant applications. Full article

Persistent reactive azo dyes released from textile finishing are a serious threat to water systems, but effective methods using sunlight to break them down are still limited. Everzol Yellow 3RS (EY-3RS) is particularly recalcitrant: past studies have relied almost exclusively on physical adsorption onto natural or modified clays and zeolites, and no photocatalytic pathway employing engineered nanomaterials has been documented to date. This study reports the synthesis, characterization, and performance of a visible-active ternary nanocomposite, Cu₄O₃/ZrO₂/TiO₂, prepared hydrothermally alongside its binary (Cu₄O₃/ZrO₂) and rutile TiO₂ counterparts. XRD, FT-IR, SEM-EDX, UV-Vis, and PL analyses confirm a heterostructured architecture with a narrowed optical bandgap of 2.91 eV, efficient charge separation, and a mesoporous nanosphere-in-matrix morphology. Photocatalytic tests conducted under midsummer sunlight reveal that the ternary catalyst removes 91.41% of 40 ppm EY-3RS within 100 min, markedly surpassing the binary catalyst (86.65%) and TiO₂ (81.48%). Activity trends persist across a wide range of operational variables, including dye concentrations (20–100 ppm), catalyst dosages (10–40 mg), pH levels (3–11), and irradiation times (up to 100 min). The material retains ≈ 93% of its initial efficiency after four consecutive cycles, evidencing good reusability. This work introduces the first nanophotocatalytic strategy for EY-3RS degradation and underscores the promise of multi-oxide heterojunctions for solar-driven remediation of colored effluents. Full article

Background: Artificial intelligence (AI) and robotics are increasingly pivotal for reducing carbon emissions in supply chain management (SCM); however, research exploring their combined potential from a sustainability perspective remains fragmented. This study aims to systematically map the research landscape and synthesize evidence on the applications, benefits, and challenges. Methods: A systematic scoping review was conducted on 23 peer-reviewed studies from the Scopus database, published between 2013 and 2024. Data were systematically extracted and analyzed for publication trends, application domains (e.g., transportation, warehousing), specific AI and robotic technologies, emissions reduction strategies, and implementation challenges. Results: The analysis reveals that AI-driven logistics optimization is the most frequently reported strategy for reducing transportation emissions. At the same time, robotic automation is commonly associated with improved energy efficiency in warehousing. Despite these benefits, the reviewed literature consistently identifies significant barriers, including the high energy demands of AI computation and complexities in data integration. Conclusions: This review confirms the transformative potential of AI and robotics for developing low-carbon supply chains. An evidence-based framework is proposed to guide practical implementation and identify critical gaps, such as the need for standardized validation benchmarks, to direct future research and accelerate the transition to sustainable SCM. Full article

This paper focuses on the numerical modeling of drug diffusion in biological tissues using fractional time-dependent parabolic equations with non-local boundary conditions. The model includes a Caputo fractional derivative to capture the non-local effects and memory inherent in biological processes, such as drug absorption and transport. The theoretical framework of the problem is based on the work of Alhazzani, et al.,which demonstrates the solution’s goodness, existence, and uniqueness. Building on this foundation, we present a robust numerical method designed to deal with the complexity of fractional derivatives and non-local interactions at the boundaries of biological tissues. Numerical simulations reveal how fractal order and non-local boundary conditions affect the drug concentration distribution over time, providing valuable insights into drug delivery dynamics in biological systems. The results underscore the potential of fractal models to accurately represent diffusion processes in heterogeneous and complex biological environments. Full article

Nanotechnology is revolutionizing medicine by enabling highly precise diagnostics, targeted therapies, and personalized healthcare solutions. This review explores the multifaceted applications of nanotechnology across medical fields such as oncology and infectious disease control. Engineered nanoparticles (NPs), such as liposomes, polymeric carriers, and carbon-based nanomaterials, enhance drug solubility, protect therapeutic agents from degradation, and enable site-specific delivery, thereby reducing toxicity to healthy tissues. In diagnostics, nanosensors and contrast agents provide ultra-sensitive detection of biomarkers, supporting early diagnosis and real-time monitoring. Nanotechnology also contributes to regenerative medicine, antimicrobial therapies, wearable devices, and theranostics, which integrate treatment and diagnosis into unified systems. Advanced innovations such as nanobots and smart nanosystems further extend these capabilities, enabling responsive drug delivery and minimally invasive interventions. Despite its immense potential, nanomedicine faces challenges, including biocompatibility, environmental safety, manufacturing scalability, and regulatory oversight. Addressing these issues is essential for clinical translation and public acceptance. In summary, nanotechnology offers transformative tools that are reshaping medical diagnostics, therapeutics, and disease prevention. Through continued research and interdisciplinary collaboration, it holds the potential to significantly enhance treatment outcomes, reduce healthcare costs, and usher in a new era of precise and personalized medicine. Full article

Background/Objectives: The aim of this study was to evaluate the level of awareness among dental students and practitioners regarding the utilization of endocrowns in clinical settings, along with any differences in knowledge based on gender, educational level, and workplace. Methods: A cross-sectional online survey-based study was conducted, including 1154 participants from various dental institutions across Saudi Arabia. The questionnaire included demographic data and closed-ended questions focused on knowledge and awareness of endocrowns. Data was analyzed using statistical tests, including chi-square, to see any significant differences. Results: Most participants (81%) had knowledge about endocrowns, mainly from their colleagues. Knowledge levels and preferences (like the use of lithium disilicate and adhesive resin cement) differed based on gender, educational level, and workplace. Male participants and undergraduates showed better awareness in some areas. Faculty members mostly depend on college training, while private practitioners obtain most of their information from workshops. Conclusions: Males showed significant superiority in knowledge about endocrown usage. Colleges were the most prevalent source of information regarding endocrown restorations. Significant molar tooth loss and restricted inter-arch space were the most common reasons for utilizing endocrowns. Moreover, endocrowns were considered a viable alternative to traditional post and core. Full article

Background: Stress hyperglycemia (SH), a transient elevation in blood glucose levels during acute stress such as stroke, has been increasingly recognized as a critical determinant of clinical outcomes. This review aims to evaluate the association between SH and clinical outcomes across different stroke subtypes and its role as a prognostic indicator. Methods: The current literature review was conducted through a comprehensive literature search of PubMed, Scopus, and Web of Science electronic databases. Initial title and abstract screening was conducted by two independent reviewers depending on the relevance to the topic of interest. Final study inclusion was based on the clinical relevance and agreement between reviewers. Results: Current evidence links SH with higher stroke severity (Higher national institutes of health stroke scale (NIHSS)), larger infarct volumes, increased risk of hemorrhagic transformation, and worse functional recovery (Lower modified rankin scale (mRS)), especially in ischemic stroke. In hemorrhagic stroke, SH is associated with hematoma expansion, perihematomal edema, and worsening neurological function. Although SH has been shown to be a reliable stroke outcome predictor, there is no scientific consensus regarding the most reliable measurement method. The use of absolute blood glucose values may not accurately reflect SH, particularly in diabetic patients, where chronic baseline hyperglycemia complicates interpretation. This underscores the necessity for individualized assessment rather than a uniform interpretation. Clinically, the early detection of SH may provide enhanced monitoring and supportive care; however, rigorous glucose management remains contentious due to the risk of hypoglycemia. Conclusions: This review synthesizes evidence from recent studies and supports SH as a prognostic marker of both short- and long-term adverse outcomes in stroke patients. Further research is warranted to evaluate the efficacy of targeted glycemic treatments on such outcomes. Full article

Objectives: Artificial intelligence (AI) symptom-checker apps are proliferating, yet their everyday usability and transparency remain under-examined. This study provides a triangulated evaluation of three widely used AI-powered mHealth apps: ADA, Mediktor, and WebMD. Methods: Five usability experts applied a 13-item AI-specific heuristic checklist. In parallel, thirty lay users (18–65 years) completed five health-scenario tasks on each app, while task success, errors, completion time, and System Usability Scale (SUS) ratings were recorded. A repeated-measures ANOVA followed by paired-sample t-tests was conducted to compare SUS scores across the three applications. Results: The analysis revealed statistically significant differences in usability across the apps. ADA achieved a significantly higher mean SUS score than both Mediktor (p = 0.0004) and WebMD (p < 0.001), while Mediktor also outperformed WebMD (p = 0.0009). Common issues across all apps included vague AI outputs, limited feedback for input errors, and inconsistent navigation. Each application also failed key explainability heuristics, offering no confidence scores or interpretable rationales for AI-generated recommendations. Conclusions: Even highly rated AI mHealth apps display critical gaps in explainability and error handling. Embedding explainable AI (XAI) cues such as confidence indicators, input validation, and transparent justifications can enhance user trust, safety, and overall adoption in real-world healthcare contexts. Full article

Neuroinflammation, driven by activated microglia, contributes to the progression of neurodegenerative diseases. Extracellular vesicles mediate intercellular communication and influence immune responses. Chrysin, a natural flavone found in fruits and propolis, has demonstrated anti-inflammatory effects. This study explored the immunomodulatory potential of chrysin-loaded EVs (EVs-Chry) derived from BV2 microglial cells. BV2 cells were treated with chrysin for 24 h to assess cytotoxicity and proliferation. EVs were isolated from treated and untreated cells, characterized by nanoparticle tracking analysis, and applied to naïve BV2 cells prior to LPS stimulation. Effects on cell morphology, migration, cytokine expression (IL-1β, IL-6), inflammasome activity (caspase-1), and apoptosis-related protein Bcl-xL were investigated. Our results show that EVs-Chry significantly reduced LPS-induced cell proliferation, restored resting microglial morphology, and reduced migratory capacity. Furthermore, co-treatment with EVs-Chry and LPS reduced pro-inflammatory cytokines such as IL-1β, IL-6, and caspase-1 expression while enhancing anti-apoptotic Bcl-xL levels, indicating a shift toward an anti-inflammatory, neuroprotective micro-glial phenotype. Together, our results demonstrated that EVs-Chry have neuroprotective effects on LPS-induced microglial activation and modulate microglial responses to inflammatory stimuli, attenuating pro-inflammatory signaling and promoting cellular homeostasis. These findings support the therapeutic potential of EVs-Chry in the context of neuroinflammatory and neurodegenerative disorders. Full article

This study investigates whether institutional quality amplifies the emissions-reducing effect of energy efficiency in hydrocarbon-dependent economies. Addressing a gap in the energy–environment literature, it tests how governance conditions shape the effectiveness of technical mitigation strategies. Using panel data from six Gulf Cooperation Council (GCC) countries between 2000 and 2023, we estimate a fixed-effects model with interaction terms between energy intensity (as a proxy for efficiency) and institutional quality (proxied by Control of Corruption). The results show that energy efficiency is associated with lower CO₂ emissions, and this relationship is significantly moderated by institutional quality. We also analyze the emissions impact of natural gas consumption and identify a structural shift following the 2014 energy reforms: while gas use was positively associated with emissions before 2014, the post-reform period shows a weaker or reversed effect. Robustness checks using alternative governance indicators—Regulatory Quality and Government Effectiveness—confirm the moderating role of institutions. The study offers new empirical evidence on the energy–institution–environment nexus and introduces a novel interaction-based methodology suited to resource-rich economies undergoing institutional transition. Full article

Healthcare abuse is a critical human rights and public health issue, particularly impacting medical interns and trainees who are vulnerable to mistreatment during their formative professional years. This cross-sectional study, conducted from February to June 2024, evaluated the prevalence and psychological impact of harassment and discrimination among 463 healthcare interns in Saudi Arabia from various specialties, including medicine, nursing, pharmacy, and dentistry. Using a self-administered online questionnaire, we found that mistreatment was widely reported, with female interns experiencing significantly higher rates of sexual harassment and gender-based discrimination. Common perpetrators included residents, lecturers, professors, nurses, and patients, with incidents most frequently occurring in surgical and internal medicine departments. Despite high prevalence, only 9% of interns reported the abuse due to mistrust in reporting systems or failure to recognize the behavior as abuse. These experiences were associated with significant psychological distress, including frustration, reduced motivation to learn, and higher DASS scores, particularly among female interns. The study underscores the need for institutional reforms, including policy development, cultural change, and effective reporting systems to ensure a safe and supportive learning environment for future healthcare professionals. Addressing abuse in medical training is essential for individual well-being and the sustainability and integrity of healthcare systems. Full article

Edible insects are emerging as a sustainable and eco-friendly alternative protein source, addressing global challenges in food security and environmental sustainability. This study investigates the willingness and acceptance of edible insects as sustainable alternative protein sources among Saudi participants, focusing on sociodemographic and attitudinal factors. A cross-sectional survey involving 2208 participants revealed that males and younger individuals (18–34 years) exhibited greater willingness to consume EIs, driven by environmental concerns, health benefits, and positive beliefs. Women and older participants showed higher levels of food neophobia, disgust, and uncertainty. Sociocultural barriers such as fear, a lack of familiarity, and perceptions of edible insects as unclean or forbidden were significant obstacles to acceptance and willingness. Interestingly, the education level did not significantly influence willingness, suggesting that cultural and religious norms may overshadow its impact. These findings underscore the need for targeted campaigns emphasizing the health, environmental, and sustainability benefits of edible insects, alongside culturally sensitive approaches to overcome psychological and social barriers. This research provides valuable insights to guide strategies for integrating EIs into Saudi diets as a step toward enhanced food security and environmental sustainability. Full article

In this paper, the authors introduce the transmuted geometric integer-valued autoregressive model with periodicity, designed specifically to analyze epidemiological and public health time series data. The model uses a transmuted geometric distribution as a marginal distribution of the process. It also captures varying tail behaviors seen in disease case counts and health data. Key statistical properties of the process, such as conditional mean, conditional variance, etc., are derived, along with estimation techniques like conditional least squares and conditional maximum likelihood. The ability to provide k-step-ahead forecasts makes this approach valuable for identifying disease trends and planning interventions. Monte Carlo simulation studies confirm the accuracy and reliability of the estimation methods. The effectiveness of the proposed model is analyzed using three real-world public health datasets: weekly reported cases of Legionnaires’ disease, syphilis, and dengue fever. Full article