Search Results (2,385)

This study examines the role of Paradoxical Leadership (PL) in enhancing sustainable service performance in Egypt’s hotel industry, with Organizational Citizenship Behavior (OCB) serving as a key mediating mechanism. Moving beyond conventional performance frameworks, the research examines how the dual nature of PL behaviors encourages discretionary employee actions that advance social sustainability, employee well-being, responsible service delivery, and long-term organizational resilience. Employing a survey-based quantitative design, data were collected from 397 hotel employees in Egypt using a structured questionnaire assessing overall PL, its five core dimensions, and OCB. A structured questionnaire was used to measure overall PL, its five core dimensions, OCB, and sustainable service performance. The data were analyzed using SPSS Version 24 and WarpPLS 8, confirmatory factor analysis, reliability analysis, and regression-based mediation analysis to examine the relationships among the study variables. The findings reveal that PL positively influences sustainable service performance, while OCB not only enhances service outcomes but also significantly mediates the relationship between PL and performance. In addition, each dimension of PL—balancing self- and other-centeredness (SO), maintaining distance while fostering closeness (CD), treating employees uniformly while recognizing individuality (UI), preserving decision control while encouraging autonomy (CA), and enforcing work requirements while allowing flexibility (RF)—significantly strengthens employees’ citizenship behaviors. Full article

The increasing global demand for sustainable water purification technologies has accelerated research on catalytic degradation and advanced oxidation processes for the removal of refractory pollutants. This study provides a comprehensive bibliometric analysis of global research trends in catalytic water and wastewater treatment from 2010 to 2025, combining quantitative mapping with a qualitative synthesis of emerging technological directions. Bibliographic data were retrieved from the Scopus database and screened using the PRISMA framework, followed by analysis using VOSviewer (v1.6.20) and OriginPro (version 2023, OriginLab Corporation, Northampton, MA, USA) to examine publication growth, citation patterns, international collaboration networks, and thematic evolution. A total of 1550 publications, including 1265 research articles and 285 review papers, were analyzed. The results show a significant increase in research output after 2015, reflecting growing global attention to water sustainability and environmental remediation. China, the United States, and India were identified as the leading contributors, with strong international collaboration networks. Keyword co-occurrence analysis revealed three dominant research themes: photocatalytic degradation and semiconductor engineering, Fenton and Fenton-like advanced oxidation processes, and emerging hybrid catalytic systems involving carbon-based materials and metal–organic frameworks. The analysis also indicates a recent shift toward multifunctional hybrid catalysts designed to improve efficiency, stability, and performance in complex wastewater systems. These findings highlight key scientific developments and suggest future research priorities, including green catalyst synthesis, reactor and process scale-up, AI-assisted catalyst design, and life-cycle sustainability assessment to support the transition from laboratory research to practical water treatment applications. Full article

The sustainable management of olive wastes represents an important environmental challenge. Biochars and hydrochars derived from biomass are promising adsorbents for removing emerging pollutants from water. In the present work, olive stone wastes were converted into biochar and hydrochar by using pyrolysis (500 °C for 30 min) and hydrothermal carbonization (HTC) processes (220 °C for 10 h). Then, the obtained materials were physically activated by using CO₂ gas (750 °C for 30, 60 and 180 min). Various analytical techniques were applied for the chemical, textural and structural characterization of these carbonaceous materials (i.e., ultimate and proximate analysis, scanning electron microscopy (SEM), BET surface area, Raman spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy). Afterwards, the selected activated biochar and hydrochar were applied for the removal of amoxicillin from aqueous solutions. The experimental results show that the generated hydrochar has many microspheres on its surface and inside, while the produced biochar exhibits a porous structure with irregular forms. CO₂ physical activation has induced an important improvement of the biochar and hydrochar’s structural, textural, and surface chemistry properties. For instance, the activated biochar samples show a highly porous structure, with large specific surface areas that increase with the burn-off, reaching 1349.3 m² g⁻¹ following 3 h of activation. Regarding the activated hydrochar samples, they exhibit a spherical morphological structure with an important specific surface area, which increased to 846.7 m² g⁻¹ after 3 h of activation. Moreover, both activated materials have an amorphous structure with low oxygen surface groups. The selected novel CO₂-activated biochar and hydrochar efficiently remove amoxicillin from aqueous solutions under wide experimental conditions, with adsorption capacities of 386.4 and 215.9 mg g⁻¹, respectively. These efficiencies are higher than those reported for various activated biochars derived from lignocellulosic biomass, from sewage sludge, and from animal manure. Future research works are required to assess these materials’ effectiveness in treating real pharmaceutical effluents, to optimize the regeneration of the amoxicillin-loaded materials, and to design full-scale devices for a real application. Full article

The reciprocal relationship between genes and nutrients, known as nutrigenetics and nutrigenomics, has been established in many studies. However, current investigations of maternal and neonatal nutrition using a precision nutrition approach focused on genomics are limited, especially in the Middle East and North Africa (MENA) region. This review aims to summarize the impacts of the dietary micronutrients, folic acid, thiamine, and cobalamin on optimal health outcomes during pregnancy, fetal development, lactation, and infant growth. In this review, the roles of folic acid, thiamine, and cobalamin are discussed in the context of various aspects of pregnancy, such as preconception, fetal development, and lactation, highlighting how genetic events occurring during developmental periods can have consequential impacts on health outcomes later in life. Deficiency rates and related health consequences as well as the prevalence of genetic mutations related to these nutrients of interest in the MENA region are also elaborated on. How to advance knowledge and applications of precision nutrition, how genes interact with the neurochemical changes during pregnancy, and how this interaction impacts maternal eating behaviors, and consequently fetal development and infant and child growth and health, should be further explored in future studies. This includes taking advantage of cutting-edge technologies and the role of artificial intelligence in this endeavor. Full article

Chronic exposure to even low levels of pesticides is a serious public health issue, mainly due to the role of oxidative stress in damaging the liver and promoting cancer. This has driven interest in finding natural, plant-based antioxidants that can counteract this kind of chemical injury. In this study, we tested whether a methanol extract from the leaves of Pteropyrum scoparium (PSE) could protect the liver against oxidative harm caused by four common pesticides: acetochlor, deltamethrin, thiamethoxam, and rotenone. Chemical analysis showed that the extract contains high levels of phenolics (345.1 ± 7.6 mg GAE/g) and flavonoids (17.3 ± 1.3 mg CAE/g). GC–MS profiling revealed a diverse set of compounds, including fat-soluble antioxidants like squalene, α-tocopherol, and γ-sitosterol, and water-soluble phenolics like pyrogallol and catechol, suggesting PSE is equipped with a multi-layered antioxidant defence. In the animal experiment, rats were given each pesticide for 30 days, with or without PSE. All four pesticides caused clear oxidative stress in the liver: glutathione (GSH), total antioxidant capacity (TAC), antioxidant enzymes activities dropped, while markers of lipid damage (MDA) and free radical activity (DPPH) rose. Co-administration of PSE significantly restored GSH, TAC and antioxidant enzymes levels and reduced MDA and residual DPPH values compared to pesticide-only groups; these parameters were statistically comparable to the controls (p > 0.05), indicating a substantial recovery of hepatic redox balance. Histopathological examination of liver tissues confirmed these findings, as pesticide treatment caused visible liver injury; deltamethrin and thiamethoxam led to congestion in central veins, while rotenone and acetochlor triggered clusters of inflammatory Kupffer cells. In animals that also received PSE, liver structure remained largely normal, with much less congestion and inflammation. These results show that the combination of antioxidant constituents in PSE might contribute to hepatoprotection through redox modulation and preservation of endogenous antioxidant balance, as suggested by the observed biochemical and histological improvements. Full article

Simple shear testing is a widely used method in geotechnical engineering for evaluating soil liquefaction susceptibility, deformation characteristics, and shear strength under controlled loading conditions. This study presents a bibliometric analysis of research trends in simple shear testing based on 367 publications indexed in the Scopus database between 2000 and 2024, analyzed using VOS-viewer. It appears that the current research output on this topic has greatly increased lately. The number of research articles reached a peak in 2024 with a total of 42 research articles. The most frequently cited journals on this topic are Soil Dynamics and Earthquake Engineering, with a total of 48 research articles (1173 citations); the Journal of Geotechnical and Geo-environmental Engineering, with a total of 34 research articles (772 citations); and the Canadian Geotechnical Journal, with a total of 10 research articles (250 citations). This indicates substantial research interest in earthquake engineering and soil mechanics. The output shows that there is a major emphasis on research done in the USA, with a total of 104 research articles (1215 citations). The highest average citations per document belong interestingly to the research done by Taiwanese, with a total of 36.73 citations. Similarly, it appears that there is a good impact on soil liquefaction studies. The research findings show that confining pressure, strain rates, and volume ratio affect the shear strength of the soil. Advances in boundary control and shear testing techniques have improved the reliability of experimental results. The study underscores the growing need for more sophisticated numerical modeling techniques and field verification to bridge the gap between laboratory findings and real geotechnical applications. These findings contribute to improving soil characterization methods, which enable safer and more efficient geotechnical designs for infrastructure development. Full article

Plastic waste gasification offers a dual-benefit pathway for hydrogen production and waste management in emerging economies. However, existing hydrogen infrastructure planning focuses predominantly on blue and green pathways, with limited integration of waste-derived hydrogen or spatially distributed waste availability constraints. This study determines optimal waste-to-hydrogen infrastructure deployment in Oman through 2040 using mixed-integer linear programming with verified techno-economic parameters. Results indicate that plastic waste can produce 21,997 tonnes H₂ annually at a levelised cost of $2.88/kg, competitive with blue hydrogen ($1.80–2.50/kg) and significantly cheaper than current green hydrogen ($4–6/kg). The optimal network comprises four facilities at Muscat (500 TPD), Sohar (128 TPD), Salalah (192 TPD), and Nizwa (67 TPD), processing 275,000 tonnes of plastic waste whilst avoiding 137,000 tonnes of CO₂-eq through landfill diversion. However, feedstock availability constrains production to 24% of base case demand (90,000 tonnes), positioning waste-to-H₂ as a complementary pathway requiring integration with steam methane reforming for industrial hubs and electrolysis for the transport sector. Sensitivity analysis reveals hydrogen yield (±29% cost impact) and CAPEX (±20%) as critical parameters, with cost reduction pathways targeting $2.00–2.30/kg by 2035 through technology learning and co-benefit monetisation. Policy recommendations include extended producer responsibility schemes, government fleet procurement mandates, and regional waste trade agreements across the GCC. Waste-to-hydrogen demonstrates techno-economic viability as a guaranteed baseload contributor within diversified hydrogen strategies for Gulf economies. Full article

Prediabetes is a critical precursor to type 2 diabetes (T2DM) and cardiometabolic diseases, yet its burden in Oman remains understudied. Leveraging data from Oman’s 2023 National Screening Program, this study quantifies the prevalence of prediabetes and its risk profiles among adults in Muscat Governorate—providing urgent evidence to guide diabetes prevention strategies in the Gulf region. Objectives: To estimate the prevalence of prediabetes and identify associated risk factors among Omani adults screened at primary health centers in Muscat Governorate (2023), given its critical role in preventing type 2 diabetes mellitus (T2DM) progression. Methods: This cross-sectional study analyzed data from Oman’s national screening program. Socio-demographics, clinical parameters (blood pressure, body mass index [BMI]), and laboratory results (fasting glucose, lipids, renal function) were extracted from the Al-Shifa electronic health system and National Screening Register. Multivariable logistic regression was performed using SPSS 30.0 (IBM Corp., Armonk, NY, USA). Results: Among 4862 participants (mean age 43.2 ± 6.3 years; 61.7% female), prevalences were: prediabetes 29.0%, T2DM 5.5%, obesity (BMI 30–40 kg/m²) 35.7%, hypertension 42.0%, hypercholesterolemia 48.8%, and renal involvement 51.8%. Males had significantly higher prediabetes prevalence than females (35.4% vs. 24.7%; adjusted odds ratio [aOR] = 1.43; 95% confidence interval [CI]: 1.21–1.70). Independent risk factors included each 1-year age increase (aOR = 1.05; 95% CI: 1.03–1.08), each 1-unit BMI increase (aOR = 1.03; 95% CI: 1.01–1.05), and family history of diabetes (aOR = 1.28; 95% CI: 1.09–1.50). Conclusions: The high burden of prediabetes and comorbid non-communicable diseases in Oman necessitates urgent public health strategies, including enhanced screening, lifestyle interventions, and gender-specific approaches to curb the T2DM epidemic. Full article

Pyridoxine-dependent epilepsy due to ALDH7A1 deficiency (PDE-ALDH7A1) is a rare but treatable epileptic encephalopathy caused by disruption of lysine catabolism and secondary depletion of pyridoxal-5′-phosphate (PLP). Although seizures are often controlled with pyridoxine supplementation, many patients continue to experience neurodevelopmental impairment, underscoring the importance of early diagnosis and improved therapeutic strategies. Central to both diagnosis and pathophysiology is the accumulation of lysine-derived metabolites, most notably α-aminoadipate semialdehyde (α-AASA), its cyclic Schiff base Δ¹-piperideine-6-carboxylate (P6C), and pipecolic acid. These metabolites have become the biochemical hallmarks of PDE-ALDH7A1, linking ALDH7A1 pathogenic variants to PLP inactivation and neuronal dysfunction. However, their chemical instability and analytical requirements pose challenges for universal diagnostics and newborn screening. This review summarizes current understanding of lysine catabolism in health and disease, critically evaluates the diagnostic utility and limitations of classical biomarkers, and discusses emerging insights into their pathophysiological roles. We further highlight recent discoveries of novel, chemically stable biomarkers, including 6-oxopiperidine-2-carboxylic acid (6-oxo-PIP), 2-oxopropylpiperidine-2-carboxylic acid (2-OPP), and 6-hydroxy-2-aminocaproic acid (HACA), identified through advanced metabolomics approaches. These metabolites show promise for newborn screening and provide new mechanistic links between metabolic stress, seizure susceptibility, and ongoing neurological morbidity despite pyridoxine treatment. Collectively, advances in biomarker discovery are reshaping diagnostic strategies for PDE-ALDH7A1 and offering new perspectives on disease mechanisms, paving the way for earlier detection and the development of more effective, mechanism-based therapies. Full article

There is diminished transparency, fragmented information exchange, and lack of trust among geographically dispersed stakeholders, which increasingly challenge global supply chains. The classic centralized systems of supply chain management are not always capable of being able to offer real-time traceability and data integrity which is dependable and effective in contract enforcement. The proposed study is a blockchain-based smart contract design that is focused on ensuring increased transparency, traceability and trust in global supply chain management. The suggested framework will combine automated smart contracts, cryptographic provenance tracking, permissioned blockchain consensus, and a decentralized trust score evaluation mechanism to overcome some of the major operation and governance challenges. A simulated assessment with a multi-tier global supply chain setting of 15 blockchain nodes and 12,000 transactions was performed through experimentation. The findings show that the proposed system attained an average transaction delay of 210 ms, which is very low compared to centralized systems (520 ms), with throughput being raised to 120 transactions per minute. End-to-end traceability performance also improved significantly, with a reduction in trace-back time to 8 s compared with 95s this represents a 100% tampering detection rate. The consensus mechanism ensured that the ledger integrity failed only at a rate of less than 1.1%, even when more than 30% of nodes were faulty. Risk-wise, the trust evaluation algorithm dynamically enhanced reliable supplier scores up to 12%, which facilitated the selection of reliable partners. On the whole, the results prove that smart contracts based on blockchains can drastically enhance the efficiency of operations, data integrity, and confidence in global supply chains, with the platform capable of providing a resilient and scalable backbone for the future supply chain management model. Full article

Resource allocation in sixth-generation (6G) networks must meet throughput, latency, and reliability targets while network conditions keep changing. At the same time, the telemetry needed to train good models is distributed across many devices and edge nodes, so sending it to a central server can violate privacy or data-sharing constraints. Federated learning (FL) helps, but two practical concerns usually determine whether it works in practice: how much communication is needed to achieve strong performance, and whether weaker (tail) clients benefit-not only the average client. In this study, we run large-scale FL on 6G telemetry with 200 clients and quantify the communication fairness trade-off. We evaluate FedAvg and FedProx under multiple settings and benchmark them against a strong centralized model and a local-only baseline. Results are reported as mean ± 95% confidence intervals over five random seeds. We measure the accuracy, macro-F1, AUC, and AP, and we also focus on tail behavior using the worst eligible client accuracy, p10 client accuracy, and fairness gap. By plotting the accuracy/macro-F1 against cumulative communication (bytes), we show that some configurations match the average performance while transmitting far fewer data. Finally, we find that the worst client performance improves early and then stabilizes, and a sensitivity study suggests that FedProx’s $\mu$ has a limited impact in this setup. These findings offer actionable guidance for 6G operators and system designers by quantifying how participation and dropout policies translate into concrete communication budgets and tail client behavior. Full article

Background: Colorectal cancer (CRC) is a major global health concern and a leading cause of cancer-related mortality. In Saudi Arabia, it is the most common cancer among men and the third most common among women. The disease affects predominantly older adults, with an increasing number of cases reported in younger populations. Emerging evidence suggests a potential association between Vitamin D deficiency and CRC risk and progression. Aim: This study aimed to investigate the relationship between serum Vitamin D levels and colorectal cancer, and to evaluate its association with clinicopathological characteristics. Methodology: A retrospective case–control study was conducted on newly diagnosed CRC patients between January 2021 and August 2024 at King Abdul-Aziz Specialist Hospital, Prince Muteb Hospital, and the Oncology Center in Al Jouf, Saudi Arabia. A total of 100 CRC cases and 50 healthy controls were included. Serum 25-hydroxyvitamin D levels were measured and categorized as deficient (<20 ng/mL), insufficient (21–29 ng/mL), and normal (≥30 ng/mL). Histopathological features and tumor characteristics were analyzed. Statistical analyses included independent t-test, one-way ANOVA, and chi-square tests. Results: During the four-year period, 5399 gastrointestinal specimens were analyzed, of which 2111 (39.1%) were colorectal specimens. CRC was diagnosed in 107 cases (5.1%), and 100 patients met the inclusion criteria. The mean age of patients was 53.07 ± 13.3 years, and 69% were older than 50 years. Males represented 58% of cases (male-to-female ratio 1.4:1). Invasive adenocarcinoma was the predominant histological subtype (81%), with the sigmoid colon being the most common tumor site (39%). Vitamin D deficiency was significantly more prevalent in CRC patients (59%) compared to controls (22%). The mean serum Vitamin D level was significantly lower in cases (18.7 ± 11.3 ng/mL) than in controls (34.9 ± 15.6 ng/mL) (p < 0.001). No significant difference in Vitamin D levels was observed between males and females. Lower Vitamin D levels were significantly associated with advanced tumor grade (p = 0.004), lymphovascular invasion (p < 0.001), lymph node involvement (p = 0.001), and distant metastasis (p < 0.001). Representative histopathological images confirmed invasive moderately differentiated adenocarcinoma with characteristic malignant glandular architecture. Conclusions: Vitamin D deficiency was highly prevalent among colorectal cancer patients and was significantly associated with advanced tumor characteristics, including higher grade and metastatic features. These findings suggest a strong inverse relationship between serum Vitamin D levels and CRC development and progression. Further large-scale prospective and interventional studies are warranted to clarify the causal role of Vitamin D and its potential therapeutic implications in colorectal cancer prevention and management. Full article

Seismic attributes are widely used to enhance the interpretation of structural, stratigraphic, and lithologic features in subsurface data. Their effectiveness, however, can be limited by noise, resolution constraints, and processing artifacts. This study suggests new seismic attributes computed using 2D-Variational Mode Decomposition (2D-VMD), which are specifically Mode-Weighted Spectral Discontinuity (MWSD) (in Module and Phase modes), VMD-Directionality Coherence (VDC), Instantaneous Frequency Concentration (IFC-VMD), and Instantaneous Bandwidth Dispersion (IBD-VMD). The proposed 2D-VMD-based attributes are compared with seven key conventional seismic attributes: dip, azimuth, chaos, coherence (semblance), curvature (mean curvature), instantaneous frequency, and instantaneous bandwidth (Hilbert transform). Through applications on simulated and real seismic data, each method is compared in terms of its ability to enhance attribute stability, resolution, and interpretability while mitigating limitations such as noise sensitivity and loss of detail. Results indicate that MWSD (Module) is optimal for amplitude stability, MWSD (Phase) for phase-sensitive applications, VDC for high-resolution structural delineation, IFC-VMD for complex geological settings, and IBD-VMD for abrupt feature changes. The findings demonstrate that these new 2D-VMD-based techniques provide significant advantages over traditional approaches and that combining complementary methods can further improve seismic interpretation outcomes. Full article

This study develops and validates a two-stage comparative framework for predicting Photovoltaic (PV) cleaning schedules by integrating high-resolution operational data with regression-based simulated datasets generated from statistical models trained on real measurements. The work directly addresses the growing need to assess whether model-based regression-based simulated data can reliably substitute real measurements in predictive PV maintenance. These models are employed to generate clean-condition power baselines and to estimate daily energy losses attributable to soiling under two distinct paradigms: (i) using real historical PV performance and environmental measurements, and (ii) using regression-derived, regression-based simulated data representing idealized clean operating conditions. Model performance is rigorously quantified using correlation coefficients (R), coefficients of determination (R²), mean absolute deviations, and binary classification metrics including accuracy, precision, recall, and F1-score. The comprehensive results demonstrate that regression-based simulated datasets exhibit high fidelity with real measurements across key electrical variables. This is evident for datasets generated using PLSR, Ridge Regression, and Robust Regression. Strong correlations are observed for DC power (R² = 0.9545) and DC current (R² = 0.9520), with mean deviations consistently below 2.2%. When a threshold-based binary decision rule (“clean” versus “do not clean”) is applied, cleaning decisions derived from simulated and real datasets show near-perfect concordance, achieving a mean F1-score of 0.9792. These results indicate that for a fixed performance-loss threshold, models using regression-based simulated data reproduce real-data-based cleaning triggers with an accuracy exceeding 97%. Furthermore, the findings confirm that regression-based simulation frameworks constitute a reliable and scalable foundation for data-driven PV maintenance optimization. By enabling efficient cleaning scheduling, these frameworks can significantly reduce operational expenditure and maximize energy yield, particularly in regions where continuous, high-quality PV monitoring data are limited or difficult to obtain. Full article

Underwater Acoustic Sensor Networks (UASNs) are pivotal for environmental monitoring, surveillance, and marine data collection. However, their open and largely unattended operational settings, constrained communication capabilities, limited energy resources, and susceptibility to insider attacks make it difficult to achieve safe, secure, and efficient collaborative learning. Federated learning (FL) offers a privacy-preserving method for decentralized model training but is inherently vulnerable to Byzantine threats and malicious participants. This paper proposes trust-aware FL for underwater sensor networks (TAFL-UWSN), a trust-aware FL framework designed to improve security, reliability, and energy efficiency in UASNs by incorporating trust evaluation directly into the FL process. The goal is to mitigate the impact of adversarial nodes while maintaining model performance in low-resource underwater environments. TAFL-UWSN integrates continuous trust scoring based on packet forwarding reliability, sensing consistency, and model deviation. Trust scores are used to weight or filter model updates both at the node level and the edge layer, where Autonomous Underwater Vehicles (AUVs) act as mobile aggregators. A trust-aware federated averaging algorithm is implemented, and extensive simulations are conducted in a custom Python-based environment, comparing TAFL-UWSN to standard FedAvg and Byzantine-resilient FL approaches under various attack conditions. TAFL-UWSN achieved a model accuracy exceeding 92% with up to 30% malicious nodes while maintaining a false positive rate below 5.5%. Communication overhead was reduced by 28%, and energy usage per node dropped by 33% compared to baseline methods. The TAFL-UWSN framework demonstrates that integrating trust into FL enables secure, efficient, and resilient underwater intelligence, validating its potential for broader application in distributed, resource-constrained environments. Full article