Search Results (65,108)

Background/Objectives: In the age of digitalization, nomophobia has emerged as a relevant issue, especially among university students who utilize smartphones heavily for academic and social purposes. The Stressor–Strain–Outcome (SSO) framework explains the relationship between stressors, strain, and outcomes. Stressors such as nomophobia induce psychological strain. This strain subsequently influences outcomes like mindfulness. Nomophobia has been linked to higher distress, including depression, anxiety, and stress, that can negatively impact students’ focus. However, the mechanisms by which nomophobia impacts mindfulness remain less explored. Hence, this study aims to analyze the mediating effect of distress on the relation between student’s nomophobia and mindfulness. Methods: In this quantitative study, the researcher employed a structured close-ended survey to collect data from 723 students at the University of Ha’il in Saudi Arabia. Nomophobia was measured using the Nomophobia Questionnaire (NMP-Q). The level of distress was measured using the Depression, Anxiety, and Stress scale (DASS-21) Furthermore, the assessment of mindfulness was conducted using the Mindful Attention Awareness Scale (MAAS). Structural equation modeling was utilized to test the hypotheses of this study. Results: The results from PLS-SEM indicate that nomophobia did not directly reduce mindfulness, as its effect was statistically non-significant (β_1 = −0.052, p-value = 0.168). This suggests that nomophobia alone may not weaken focus. However, it significantly increased distress, particularly depression (β_2a = 0.327, p-value < 0.001), anxiety (β_2b = 0.294, p-value < 0.001) and stress (β_2c = 0.259, p-value < 0.001). In plain terms, students with higher nomophobia reported more depression and stress, which in turn reduced mindfulness. Anxiety, however, did not significantly affect mindfulness (β_3b = 0.006, p-value < 0.933), indicating its influence may be negligible or context-specific. Mediation analysis confirmed indirect effects of nomophobia on mindfulness through depression (β_4a = −0.096, p-value < 0.001) and stress (β_4c = −0.045, p-value < 0.020). Together, these mediators explained a substantial portion of the variance in mindfulness. Conclusions: The findings align with the SSO model, indicating that nomophobia acts as a stressor, exacerbating distress, which in turn reduces mindfulness. From a practical perspective, the results highlight the need for comprehensive student support. Universities should integrate digital wellness programs, stress-management resources, and mindfulness training into their services. Limitations and Future Research: The cross-sectional design and convenience sampling restrict causal inference and generalizability. Future studies should employ longitudinal research designs. They should also examine diverse cultural contexts. In addition, researchers should investigate potential mediators such as social support and sleep quality. Full article

The integration of emerging technologies is reshaping the teaching skills required in the 21st century, yet little evidence exists on how contextualized training supports rural teachers in adopting active methodologies and critically incorporating AI into entrepreneurship education. This study evaluated the impact of a 40-h professional development program implemented in Educational District 15D01 in the Ecuadorian Amazon. Thirty-nine secondary school teachers participated (mean age = 43.1 years); 36% lacked prior entrepreneurship training, and 44% had not recently mentored student projects. A sequential explanatory mixed-methods design was employed. The quantitative phase employed a 22-item questionnaire that addressed four dimensions: entrepreneurial knowledge, competencies, methodological strategies, and AI integration. Significant pre–post improvements were found (p < 0.001), with large effects for knowledge (d = 1.43), methodologies (d = 1.39), and AI integration (d = 1.30), and a moderate effect for competences (d = 0.66). The qualitative phase analyzed 312 open-ended responses, highlighting greater openness to innovation, enhanced teacher agency, and favorable perceptions of AI as a resource for ideation, prototyping, and evaluation. Overall, the findings suggest that situated, contextually aligned training can strengthen digital equity policies, foster pedagogical innovation, and empower educators in underserved rural communities, contributing to sustainable pathways for teacher professional development. Full article

The aim of the study was to explore the impact of an intervention based on the manipulation of the margin of error and the provision of ball speed feedback on the ability to spike in introductory volleyball. To this end, an exploratory study without a control group was conducted. The sample consisted of two U-14 volleyball teams, one male team with 14 players (13.2 ± 0.75 years), and one female team with 12 players (14 ± 0 years). The intervention involved reducing the height of the net, providing immediate feedback on the speed of the ball after the spike, and challenging the target zone of the spike. It was applied across 12 sessions, with eight spikes per player per session. The study variables recorded in each spiking were ball speed (which was measured using the Pocket Radar Ball Coach instrument), jump height (which was measured using the VERT Wearable Jump Monitor), and target area for sending the ball (which was filmed using a high-speed video camera). The players’ perception of the intervention was also assessed. The most significant results indicated that the achievement of the impact in the more restricted target area of the spiking, compared to the larger target area, led to a significant increase in jumping, both in men and women. As maintaining spike ball speed was necessary to validate the challenge, speed values did not decrease when hitting toward the restricted zone. In fact, for male players, there was an unexpected significant increase in spike ball speed. The initial speed was the variable that best predicted the maximum speed acquired throughout the treatment. Reducing the net height while restricting the spiking area can have a positive impact on spike kinematics, provided that spike velocity is maintained. Full article

Arc fault detection in photovoltaic systems is crucial, since it may cause incidents like fires and explosions. So far, most existing methods rely on an arc’s local features and do not characterize arc faults globally, which may lead to detection failure in noisy environments. In this paper, a fundamentally different method is proposed that relies on an arc’s global features instead of local ones. The core idea of the method is that the physical mechanisms of the arc fault signals and the normal signals are so different that they are thought to be generated by two independent sources. Based on this insight, independent component analysis (ICA) is introduced to decompose the photovoltaic system’s DC currents. By using ICA, the DC current signals with an arc fault can be decomposed into two independent signals, while the normal signals without an arc fault cannot be decomposed into two such independent signals. This indicates that arc faults can be detected by using the concept of “independence”. Then, the dynamic time warping algorithm was used to determine the independence level of the ICA outputs so as to realize end-to-end arc fault detection. Experimental results showed that our method has better performance than traditional methods in terms of detection accuracy and robustness against environmental disturbances. Full article

Background/Objectives: Cardiometabolic risk remains a major challenge in patients with type 2 diabetes mellitus (DMT2). This study aimed to evaluate cardiovascular (CV) risk stratification using advanced glycation end-products (AGEs) measured via skin autofluorescence (SAF) and to assess the achievement of evidence-based ABC targets (HbA1c, blood pressure, low-density lipoprotein (LDL) cholesterol) in adults with DMT2 in Dalmatia. Methods: In this single-center cross-sectional study, 251 adults with DMT2 were stratified by CV risk based on SAF measured AGE levels. Clinical, biochemical, and anthropometric data were collected, including ABC goal attainment and medication use. Statistical analyses compared groups and explored predictors of ABC target achievement using regression models adjusted for clinical factors. Results: Only 17.5% of participants achieved all three ABC goals, indicating suboptimal cardiometabolic control. Those with elevated CV risk had higher hip circumference and lower diastolic blood pressure. Use of sodium-glucose cotransporter 2 (SGLT2) inhibitors was positively associated with ABC goal achievement in patients with prior CV or cerebrovascular events, while higher body mass index was negatively associated. SAF measured AGE levels correlated with cardiometabolic risk but showed no significant differences across LDL cholesterol or other traditional markers. Conclusions: SAF AGE measurement shows potential for CV risk stratification in DMT2 beyond traditional factors. The low rate of ABC goal attainment highlights the need for intensified individualized management incorporating novel biomarkers and therapeutics like SGLT2 inhibitors. Further prospective studies are needed to validate these findings and improve prevention of cardiovascular complications in DMT2. Full article

The presence of solid particles (or droplets) in a flow leads to a significant increase in heat fluxes, the occurrence of chemical reactions, and erosive surface wear of various aircraft moving in the dusty (or rainy) atmosphere of Earth or Mars. A review of computational, theoretical, and experimental work devoted to the study of the characteristics of the boundary layers (BL) of gas with solid particles was performed. The features of particle motion in laminar and turbulent boundary layers, as well as their inverse effect on gas flow, are considered. Available studies on the stability of the laminar boundary layer and the effect of particles on the laminar–turbulent transition are analyzed. At the end of the review, conclusions are drawn, and priorities for future research are discussed. Full article

Finding the causative mutations for musculoskeletal system development and health status is of a higher priority for all sport horse breeders’ associations. Of the regulating proteins involved in animal ossification, 15 gene polymorphisms were chosen to be identified as connected with the nine fetlock and 14 hock bone structures measurements of 198 horses. All measurements were taken using X-rays of the limbs, which were available at the beginning and end of the horse training. The analysis of variance (GLM, SAS program) was performed taking into account identified training and horse-connected characteristics, and gene polymorphism. The larger size of the bone structure was achieved in the fetlock for the heterozygotes of COL9A2, AOAH1, BMPER, HYAL3, and ELMO1. The heterozygotes were superior to homozygotes in the hock for the following genes: COL9A2, HYAL3, ANLN, and HYAL1. The lower homozygote values were obtained for GG in CPVL in fetlock measurements, TT for HYAL3 in fetlock, TT for ANLN in fetlock, CC for FRZB in the hock, TT for MATN in the hock, and TT for COL5A2 in the hock than their opposite homozygote and heterozygote variants. COL9A2 and HYAL3 are expressed in the same way for most of the bone structures in both joints. Full article

Early and accurate detection of lemon disease is necessary for effective citrus crop management. Traditional approaches often lack refined diagnosis, necessitating more powerful solutions. The article introduces adaptive PSO-LemonNetX, a novel framework integrating a novel deep learning model, adaptive Particle Swarm Optimization (PSO)-based feature selection, and explainable AI (XAI) using LIME. The approach improves the accuracy of classification while also enhancing the explainability of the model. Our end-to-end model obtained 97.01% testing and 98.55% validation accuracy. Performance was enhanced further with adaptive PSO and conventional classifiers—100% validation accuracy using Naive Bayes and 98.8% testing accuracy using Naive Bayes and an SVM. The suggested PSO-based feature selection performed better than ReliefF, Kruskal–Wallis, and Chi-squared approaches. Due to its lightweight design and good performance, this approach can be adapted for edge devices in IoT-enabled smart farms, contributing to sustainable and automated disease detection systems. These results show the potential of integrating deep learning, PSO, grid search, and XAI into smart agriculture workflows for enhancing agricultural disease detection and decision-making. Full article

Although liquefied natural gas (LNG) is already widely used as a marine fuel, its use on large cruise ships is a relatively new development. By the end of 2024, twenty-four LNG-fuelled cruise ships were in operation, each carrying several thousand passengers and making frequent port calls. These operational characteristics increase the potential risks compared to conventional cargo ships and require a rigorous safety assessment. In this study, the safety of LNG-fuelled cruise ships is assessed using the Formal Safety Assessment (FSA) framework prescribed by the International Maritime Organization (IMO). The assessment includes a hazard identification (HAZID), a risk analysis, an evaluation of risk control options, a cost–benefit analysis and recommendations for decision-making. Given the limited operational data on LNG-fuelled cruise ships, event trees are developed on the basis of LNG tanker incidents, adjusted to reflect passenger-related risks and cruise-specific operating conditions. A statistical overview of marine casualties involving cruise ships and LNG carriers of more than 20,000 GT over the last 35 years provides a further basis for the analysis. To ensure compliance, the study also analyses class requirements and regulatory frameworks, including risk assessments for ship design, bunker operations and emergency preparedness. These assessments, which are carried out at component, ship and process level, remain essential for safety validation and regulatory approval. The results provide a comprehensive framework for assessing LNG safety in the cruise sector by combining existing safety data, regulatory standards and probabilistic risk modelling. Recent work also confirms that event tree modelling identifies critical accident escalation pathways, particularly in scenarios involving passenger evacuation and port operations, which are under-researched in current practice. The results contribute to the wider debate on alternative fuels and support evidence-based decision-making by ship operators, regulators and industry stakeholders. Full article

Shaft deflection degrades roller alignment and intensifies stress concentration/edge effects at roller-ends and raceway edges, ultimately compromising service performance of tapered roller bearings (TRBs). Therefore, a dynamic model was developed for a TRB subjected to a deflected shaft in which Johnson’s load–deformation relationship was applied to reflect non-uniform cross-sectional structures of the tapered rollers and raceways, viscous damping was integrated into the roller/cage interaction, and friction actions at the raceways and flange areas were treated separately. Then, moment load and angular misalignment of the tapered roller were analyzed under various shaft deflection and operating conditions. Results indicate that tilt angle remains orders of magnitude smaller than skew angle. Shaft deflection amplifies both skew and tilt, and the influence level is proportional to the bearing size. Centrifugal effect primarily affects skew motion, whereas gyroscopic effect mainly influences tilt motion. Axial forces exert greater influence on roller skew than tilt. The flange typically constrains roller skew, whereas both raceways may induce bidirectional tilt/skew motion. Full article

To address the uncertainty in selecting the optimal spherical base curvature radius (SR) for tapered roller bearings, this study develops dynamic and friction torque models under combined loading conditions to evaluate three SR configurations—0.85ρ_p, 0.90ρ_p, and 0.95ρ_p, where ρ_p represents the curvature radius of the inner rib—in terms of load capacity, friction losses, and operational precision. The results indicate that (1) the 0.85ρ_p configuration minimizes friction by optimizing the contact zone’s f_V parameter under combined loads, making it ideal for low-friction applications; (2) the 0.95ρ_p design achieves superior operational accuracy; (3) the intermediate value of 0.90ρ_p offers an optimal compromise, balancing friction torque reduction with operational precision. These findings establish quantitative guidelines for SR selection based on specific bearing performance requirements. Full article

The methylation of CpG sites with 5mC mark is a dynamic epigenetic modification. However, the relationship between the methylation and the surrounding genomic sequence context remains poorly explored. Investigation of the allele methylation provides an opportunity to decipher the interplay between differences in the primary DNA sequence and epigenetic variation. Here, we performed high-coverage long-read whole-genome direct DNA sequencing of one individual using Oxford Nanopore technology. We also used Illumina whole-genome sequencing of the parental genomes in order to identify allele-specific methylation sites with a trio-binning approach. We have compared the results of the haplotype-specific methylation detection and revealed that trio binning outperformed other approaches that do not take into account parental information. Also, we analysed the cis-regulatory effects of the genomic variations for influence on CpG methylation. To this end, we have used available Deep Learning models trained on the primary DNA sequence to score the cis-regulatory potential of the genomic loci. We evaluated the functional role of the allele-specific epigenetic changes with respect to gene expression using long-read Nanopore RNA sequencing. Our analysis revealed that the frequency of SNVs near allele-specific methylation positions is approximately four times higher compared to the biallelic methylation positions. In addition, we identified that allele-specific methylation sites are more conserved and enriched at the chromatin states corresponding to bivalent promoters and enhancers. Together, these findings suggest that significant impact on methylation can be encoded in the DNA sequence context. In order to elucidate the effect of the SNVs around sites of allele-specific methylation, we applied the Deep Learning model for detection of the cis-regulatory modules and estimated the impact that a genomic variant brings with respect to changes to the regulatory activity of a DNA loci. We revealed higher cis-regulatory impact variants near differentially methylated sites that we further coupled with transcriptomic long-read sequencing results. Our investigation also highlights technical aspects of allele methylation analysis and the impact of sequencing coverage on the accuracy of genomic phasing. In particular, increasing coverage above 30X does not lead to a significant improvement in allele-specific methylation discovery, and only the addition of trio binning information significantly improves phasing. We investigated genomic variation in a single human individual and coupled computational discovery of cis-regulatory modules with allele-specific methylation (ASM) profiling. In this proof-of-concept analysis, we observed that SNPs located near methylated CpG sites on the same haplotype were enriched for sequence features suggestive of high-impact regulatory potential. This finding—derived from one deeply sequenced genome—illustrates how phased genetic and epigenetic data analyses can jointly put forward a hypotheses about the involvement of regulatory protein machinery in shaping allele-specific epigenetic states. Our investigation provides a methodological framework and candidate loci for future studies of genomic imprinting and cis-mediated epigenetic regulation in humans. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies, marked by late diagnosis, limited responsiveness to conventional therapies, and an immunosuppressive tumor microenvironment. While immunotherapy has transformed treatment paradigms in several cancers, its efficacy in PDAC has been minimal. Oncolytic viruses and therapeutic cancer vaccines have emerged as promising immunotherapeutic strategies designed to stimulate robust, tumor-specific immune responses and reshape the immune landscape. However, despite encouraging preclinical data, clinical translation in PDAC has been largely disappointing. This review critically evaluates the design, delivery, and efficacy of oncolytic virotherapy and cancer vaccines in PDAC, examining barriers such as stromal desmoplasia, immune exclusion, and tumor heterogeneity. We also explore combination strategies integrating checkpoint inhibitors, chemotherapy, radiotherapy, and stromal modulation to overcome resistance. Ultimately, the viability of these approaches hinges on a clearer understanding of their mechanistic limitations and the refinement of delivery platforms. These factors will determine whether oncolytic viruses and cancer vaccines can be successfully repositioned within the therapeutic arsenal or warrant reevaluation in the evolving landscape of PDAC treatment. Full article

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k–ω–SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k–ω–SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

I offer a close reading of Hölderlin’s “Mnemosyne“ (“Reif sind, in Feuer getaucht…”) that situates it in terms of its links to Greek tragedy and Homer. The essay explores Hölderlin’s focus on Achilles and the death of the Greek heroes Patroklos and Ajax against the notion of “poetic transport.” I also look at Hölderlin’s 2nd Böhlendorff Letter that traffics in the relation between antiquity and modernity. The essay also offers a reading of the second stanza of “Mnemosyne” in terms of Rousseau’s essay on “The Reveries of the Solitary Walker” and its appeal to the poet. As Hölderlin pursues the tense relation between memory and death, he poses questions about ethical responsibility that challenge the human being to find a path between wallowing in too excessive grief that ends in unbounded subjectivity and affirming the sense of the other that extends beyond our own self-preoccupation. Full article