Search Results (22,013)

Generative pre-trained transformers (GPTs) have rapidly entered educational contexts, raising questions about their impact on pedagogy, workload, and professional practice. While their potential to automate resource creation, planning, and administrative tasks is widely discussed, little empirical evidence exists regarding their use in vocational education (VE). This study explores how VE educators in England are currently engaging with AI tools and the implications for workload and teaching practice. Data were collected through a survey of 60 vocational teachers from diverse subject areas, combining quantitative measures of frequency, perceived usefulness, and delegated tasks with open qualitative reflections. Descriptive statistics, cross-tabulations, and thematic analyses were used to interpret responses about the application and allocation of work given by teachers to GPTs. Findings indicate cautious but positive adoption, with most educators using AI tools infrequently (0–10 times per month), yet rating them highly useful (average 4/5) for supporting workload. Resource and assessment creation dominated reported uses, while administrative applications were less common. The choice architecture framing indicates that some GPTs guide teachers to certain resources over others and the potential implications of this are discussed. Qualitative insights highlighted concerns around quality, overreliance, and the risk of diminishing professional agency. The study concludes that GPTs offer meaningful workload support but require careful integration, critical evaluation, and professional development to ensure they enhance rather than constrain VE pedagogy. Full article

Background: The CAMS Regional System provides crucial, reliable pollen forecasts for allergenic pollen types. These robust predictions support the scientific and medical communities, aiding in the diagnosis, evaluation, and protection of allergic populations. So, the main goal of this study was to evaluate which model, or models best represent and simulate the olive and grass pollen data of the Évora region in the years 2021 to 2024. Results: The results showed that there are statistically significant differences between the data of the models and between the years for each of the pollen types considered. These differences were not just in pollen concentrations; they also appeared in characteristics of the pollen season, like its duration, maximum peak concentration, start date and exposure level. According to Taylor diagrams, applying moving average for normalized data, it was shown that MOCAGE best represents and simulates olive concentration data. For grass pollen SILAM, EURAD-IM and MOCAGE were the best performers. Conclusions: CAMS data can enhance the quality of life of the allergic population, as well as support the scientific and medical community to improve, assist and create mitigation measures that reduce exposure and consequently significantly reduce the occurrence of allergic disease. Full article

Given the endangered status and very limited distribution of Barbarea vulgaris R.Br. subsp. lepuznica (Nyár.) Soó in stressful, high-elevation habitats, where these plants must prioritise the resource acquisition and vegetative growth to sustain their survival and persistence, we aimed to reveal possible abiotic/biotic-driven constraints in biomass allocation for flower production. Three functional traits, i.e., the tallest shoot height, leaf mass area (LMA) and number of inflorescences (racemes), were measured in thirty plants in each of the three studied populations differing in altitude and sheep grazing intensity (P1—1700 m, grazed; P2—1900 m, ungrazed; P3—2100 m, ungrazed). The LMA and dominant shoot height were significantly higher and, respectively, lower in P3 compared with P1. Although the mean number of racemes in P1 was lower than in P2 and P3, the differences were not statistically significant. The tallest shoot height, followed by the LMA, displayed the highest contribution to differentiating the three populations. The raceme count decreased significantly with increasing height of the dominant shoot in P1 and P2, and also with increasing LMA in P3. The observed constraint in raceme production within all populations is very likely one facet of the trade-off between reproductive and vegetative allocation under harsh edapho-climatic conditions. The studied plants have adopted a conservative-tolerant strategy to cope with the abiotic stress at higher elevations, but an acquisitive-tolerant strategy in face of grazing. The subspecies lepuznica seems to be in a favourable conservation status, but a close monitoring in grazed areas is recommended. Full article

Identifying the activation status of advanced driver assistance systems (ADAS) in real-world driving environments is crucial for safety, responsibility attribution, and accident forensics. Unlike prior studies that primarily rely on simulation-based settings or unsynchronized data, we collected a multimodal dataset comprising synchronized controller area network (CAN)-bus and smartphone-based inertial measurement unit (IMU) signals from drivers on consistent highway sections under both ADAS-enabled and manual modes. Using these data, we developed lightweight classification pipelines based on statistical and deep learning approaches to explore the feasibility of distinguishing ADAS operation. Our analyses revealed systematic behavioral differences between modes, particularly in speed regulation and steering stability, highlighting how ADAS reduces steering variability and stabilizes speed control. Although classification accuracy was moderate, this study provides one of the first data-driven demonstrations of ADAS status detection under naturalistic conditions. Beyond classification, the released dataset enables systematic behavioral analysis and offers a valuable resource for advancing research on driver monitoring, adaptive ADAS algorithms, and accident forensics. Full article

This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. Full article

Background and Objectives: Severe complications associated with cervical hyperextension during general anesthesia have been reported. The question is whether some of the cerebral/spinal ischemic complications could be partially related to the position itself. Cerebral oximetric monitoring, combined with optic nerve sheath diameter and cognitive function in non-anesthetized healthy volunteers, should provide more extensive information about the effects of cervical hyperextension, independent of anesthesia. Materials and Methods: 51 healthy volunteers with no vertebrobasilar abnormalities completed the study and were included in statistical analysis. Primary outcomes were cervical blood flow and cerebral relative hemoglobin change. The secondary outcomes were optic nerve sheath diameter and cognitive function assessment. After baseline Doppler ultrasonography of the cervical vessels, Mini-Mental State Examination, Montreal Cognitive Assessment, and optic nerve sheath diameter measurements at T0, volunteers underwent cervical hyperextension > 30°, with assessments repeated at the first and 30th minutes (T1, T30). Relative total, oxi-, and deoxyhemoglobin changes were assessed every 5 min. Results: Peak systolic velocities in the jugular veins at T1 and T30 were significantly lower than those at baseline (p1 and p2 < 0.001). After hyperextension, deoxyhemoglobin changes significantly increased at T1 and T30 (p1 < 0.001). The optic nerve sheath diameter increased at T30 compared to the baseline (p < 0.001). Cognitive scores improved at T30 (p = 0.044 and p < 0.001, respectively). Conclusions: Cervical hyperextension causes a significant increase in relative total and deoxyhemoglobin changes, which are related to acute cerebral congestion by severely impairing cerebral venous flow. A significant change in optic nerve sheath diameter indirectly indicates increased intracranial pressure. Full article

Football-themed eSports, combining entertainment and learning elements, are booming, offering benefits in terms of cognitive and motor skill development. Despite this, with the increasing use of eSports and their impact on cognitive and motor skills, there is still a paucity of empirical studies that systematically explore how cognitive stimulation from eSports can translate into psychomotor performance on the field, particularly with regard to linear speed. The aim of this study was to investigate the effects of an ecological–dynamic training protocol, integrated with football eSports, on the development of linear sprint speed in young soccer players. Thirty-two male youth football players (age range: 12–16 years) participated in the study. Participants were divided into an experimental group, which followed a combined ecological–dynamic training protocol including football eSports, and a control group, which performed standard training sessions. Pre- and post-intervention assessments of 30 m sprint performance were conducted using electronic timing gates. Statistical analysis using repeated-measures ANOVA indicated a marked improvement in 30 m sprint performance within the experimental group, decreasing from 4.908 s to 4.651 s. A significant time × group interaction was observed (F = 74.076, p < 0.001). Moreover, a robust main effect of time emerged (F = 141.12, p < 0.001), confirming consistent gains in linear sprint speed. Post hoc comparisons revealed significant differences across all assessment points (p < 0.001). The findings suggest that embedding football eSports into an ecologically grounded training framework may enhance the development of linear speed in young soccer players. This integrated approach shows potential as an innovative tool for performance enhancement, although further investigations are needed to confirm long-term efficacy and generalizability to other sporting populations. Full article

Introduction: Dry Eye Syndrome (DES) is a multifactorial disorder of the ocular surface, characterized by complex interactions between environmental factors, immune dysregulation, and potential genetic predispositions. Vitamin D deficiency, known for its immunomodulatory properties, has increasingly been implicated in the pathogenesis of DES; however, the underlying mechanisms remain insufficiently elucidated. Of particular interest is the vitamin D receptor (VDR) gene, whose polymorphisms may influence the bioavailability and biological activity of vitamin D. Objective: The aim of this study was to investigate the association between serum 25-hydroxyvitamin D [25(OH)D₃] levels and selected polymorphisms in the VDR gene (Taq, Fok, Apa, and Bsm) in patients with DES and to analyze their potential clinical and genetic interactions. Methods: This prospective observational study included 60 patients with a confirmed diagnosis of DES. Serum 25(OH)D₃ levels were measured, and genotyping of four VDR single-nucleotide polymorphisms (SNPs) was performed using PCR followed by restriction fragment length polymorphism analysis. Genotype distributions were assessed in relation to vitamin D status using appropriate statistical tests and Hardy–Weinberg equilibrium analysis. Results: Over 85% of patients exhibited insufficient or deficient vitamin D levels. Among the analyzed SNPs, only the ApaI polymorphism (rs7975232) showed a statistically significant association with vitamin D status (p = 0.0384), with the homozygous AA genotype being more prevalent among patients with hypovitaminosis. The remaining polymorphisms (TaqI, FokI, BsmI) did not reach statistical significance; however, potential trends were observed that may warrant further investigation in larger cohorts. Conclusion: The findings suggest a potential role for VDR gene variability in the regulation of systemic vitamin D levels in patients with DES. Identification of specific genotypes may contribute to the development of personalized diagnostic and therapeutic strategies, particularly for patients with treatment-resistant forms of the disease. These results support the integration of genetic biomarkers and nutritional parameters into modern ophthalmologic practice. Full article

The conceptual design phase in architecture establishes the foundation for subsequent design decisions and influences up to 80% of a building’s lifecycle environmental impact. While Building Information Modeling (BIM) demonstrates transformative potential for sustainable design, its application during conceptual design remains constrained by perceived technical complexity and limited support for abstract thinking. This research examines how BIM tools can facilitate conceptual design through diagrammatic reasoning, thereby bridging technical capabilities with creative exploration. A mixed-methods approach was employed to develop and validate a Diagrammatic BIM (D-BIM) framework. It integrates diagrammatic reasoning, parametric modeling, and performance evaluation within BIM environments. The framework defines three core relationships—dissection, articulation, and actualization—which enable transitions from abstract concepts to detailed architectural forms in Revit’s modeling environments. Using Richard Meier’s architectural language as a structured test case, a 14-week quasi-experimental study with 19 third-year architecture students assessed the framework’s effectiveness through pre- and post-surveys, observations, and artifact analysis. Statistical analysis revealed significant improvements (p < 0.05) with moderate to large effect sizes across all measures, including systematic design thinking, diagram utilization, and academic self-efficacy. Students demonstrated enhanced design iteration, abstraction-to-realization transitions, and performance-informed decision-making through quantitative and qualitative assessments during early design stages. However, the study’s limitations include a small, single-institution sample, the absence of a control group, a focus on a single architectural language, and the exploratory integration of environmental analysis tools. Findings indicate that the framework repositions BIM as a cognitive design environment that supports creative ideation while integrating structured design logic and performance analysis. The study advances Education for Sustainable Development (ESD) by embedding critical, systems-based, and problem-solving competencies, demonstrating BIM’s role in sustainability-focused early design. This research provides preliminary evidence that conceptual design and BIM are compatible when supported with diagrammatic reasoning, offering a foundation for integrating competency-based digital pedagogy that bridges creative and technical dimensions of architectural design. Full article

Seawater intrusion into coastal river systems poses increasing challenges for freshwater availability and estuarine ecosystem integrity, especially under evolving climatic and anthropogenic pressures. This study presents a multidisciplinary investigation of marine intrusion dynamics within the Magra River estuary (Northwest Italy), integrating field monitoring, isotopic tracing (δ¹⁸O; δD), and multivariate statistical modeling. Over an 18-month period, 11 fixed stations were monitored across six seasonal campaigns, yielding a comprehensive dataset of water electrical conductivity (EC) and stable isotope measurements from fresh water to salty water. EC and oxygen isotopic ratios displayed strong spatial and temporal coherence (R² = 0.99), confirming their combined effectiveness in identifying intrusion patterns. The mass-balance model based on δ¹⁸O revealed that marine water fractions exceeded 50% in the lower estuary for up to eight months annually, reaching as far as 8.5 km inland during dry periods. Complementary δD measurements provided additional insight into water origin and fractionation processes, revealing a slight excess relative to the local meteoric water line (LMWL), indicative of evaporative enrichment during anomalously warm periods. Multivariate regression models (PLS, Ridge, LASSO, and Elastic Net) identified river discharge as the primary limiting factor of intrusion, while wind intensity emerged as a key promoting variable, particularly when aligned with the valley axis. Tidal effects were marginal under standard conditions, except during anomalous events such as tidal surges. The results demonstrate that marine intrusion is governed by complex and interacting environmental drivers. Combined isotopic and machine learning approaches can offer high-resolution insights for environmental monitoring, early-warning systems, and adaptive resource management under climate-change scenarios. Full article

Ultra-high-energy cosmic rays (UHECRs) are the most energetic particles known—and yet their origin is still an open question. However, with the precision and accumulated statistics of the Pierre Auger Observatory and the Telescope Array, in combination with advancements in theory and modeling—e.g., of the Galactic magnetic field—it is now possible to set solid constraints on the sources of UHECRs. The spectrum and composition measurements above the ankle can be well described by a population of extragalactic, homogeneously distributed sources emitting mostly intermediate-mass nuclei. Additionally, using the observed anisotropy in the arrival directions, namely the large-scale dipole >8 EeV, as well as smaller-scale warm spots at higher energies, even more powerful constraints on the density and distribution of sources can be placed. Yet, open questions remain—like the striking similarity of the sources that is necessary to describe the rather pure mass composition above the ankle, or the origin of the highest energy events whose tracked back directions point toward voids. The current findings and possible interpretation of UHECR data will be presented in this review. Full article

If intraday price data are unavailable, then using daily returns to construct realized measures of the variances of lower-frequency returns is a natural substitute for using high-frequency returns in this context. Notably, a suitable application of this approach yields realized measures that are unbiased estimators of the unconditional and conditional variances of holding period returns for any investment horizon. I use a long sample of daily S&P 500 index returns to investigate the merits of constructing realized measures in this fashion. First, I conduct a Monte Carlo study using a data generating process that reproduces the key dynamic properties of index returns. The results of the study suggest that using realized measures constructed from daily returns to estimate the conditional and unconditional variances of lower-frequency returns should lead to substantial increases in efficiency. Next, I fit a multiplicative error model to the realized measures for weekly and monthly index returns to obtain out-of-sample forecasts of their conditional variances. Using the forecasts produced by a generalized autoregressive conditional heteroskedasticity model as a benchmark, I find that the forecasts produced by the multiplicative error model always generate lower mean absolute errors. Furthermore, the improvements in forecasting performance are statistically significant in most cases. Full article

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

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

Posttraumatic Stress Disorder (PTSD) is characterized by disruptions in central nervous system functioning and existential crises, yet the mechanistic links between neurobiological processes and dimensions of life meaning and identity remain underexplored. The aim of this study was to examine the relationships between stress biomarkers (serotonin, cortisol, noradrenaline, and interleukin-12 [IL-12]) and existential attitudes (measured using the Life Attitude Profile (Revised) [LAP-R]) in mining rescuers, considering PTSD duration and participant age. This cross-sectional study included 92 men aged 18–50 years, divided into three groups: no PTSD (n = 28), PTSD ≤ 5 years (n = 33), and PTSD > 5 years (n = 31). Serum levels of four biomarkers and LAP-R scores across eight domains were evaluated. Statistical analyses employed nonparametric tests, including the Kruskal–Wallis test for overall group differences (with Wilcoxon r effect sizes for pairwise comparisons, Mann–Whitney U tests for post hoc pairwise comparisons, and Spearman’s rank correlations for biomarker–LAP-R associations. Age effects were assessed in two strata: 18–35 years and 36–50 years. Kruskal–Wallis tests revealed significant group differences (p < 0.001) for all biomarkers and most LAP-R domains, with very large effect sizes (r > 0.7) in pairwise comparisons for serotonin (control median: 225.2 ng/mL vs. PTSD ≤ 5y: 109.9 ng/mL, r = 0.86; vs. PTSD > 5y: 148.0 ng/mL, r = 0.86), IL-12 (control: ~8.0 pg/mL vs. PTSD ≤ 5y: 62.4 pg/mL, r = 0.86; vs. PTSD > 5y: ~21.0 pg/mL, r = 0.69), and LAP-R scales such as Life Purpose (control: 54.0 vs. PTSD ≤ 5y: 39.0, r = 0.78; vs. PTSD > 5y: 20.0, r = 0.86) and Coherence (control: 53.0 vs. PTSD ≤ 5y: 34.0, r = 0.85; vs. PTSD > 5y: 23.0, r = 0.86). The PTSD ≤ 5y group exhibited decreased serotonin, cortisol (median: 9.8 µg/dL), and noradrenaline (271.7 pg/mL) with elevated IL-12 (all p < 0.001 vs. control), alongside reduced LAP-R scores. The PTSD > 5y group showed elevated cortisol (median: ~50.0 µg/dL, p < 0.001 vs. control, r = 0.86) and normalized IL-12 but persistent LAP-R deficits. Older participants (36–50 years) in the PTSD ≤ 5y group displayed improved existential attitudes (e.g., Life Purpose: 47.0 vs. 27.5 in 18–35 years, p < 0.001), whereas in PTSD > 5y, age exacerbated biological stress (cortisol: 57.6 µg/dL vs. 36.1 µg/dL, p = 0.003). Spearman correlations revealed stage-specific patterns, such as negative associations between cortisol and Death Acceptance in PTSD > 5y (ρ = −0.49, p = 0.005). PTSD alters biomarker levels and their associations with existential dimensions, with duration and age modulating patient profiles. These findings underscore the necessity for integrated therapies addressing both biological and existential facets of PTSD. Full article